refactor: switched to upstream @mariozechner/pi-ai and removed unused packages
- Replaced local @oh-my-pi/pi-ai with upstream @mariozechner/pi-ai@0.37.4 - Added sessionId support to agent for provider caching (OpenAI Codex) - Deleted packages/ai (now using upstream) - Deleted packages/mom (unused) - Deleted packages/web-ui (unused)
This commit is contained in:
can1357
@@ -34,11 +34,13 @@ bun install -g @oh-my-pi/pi-coding-agent
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### Via installer script
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**Linux / macOS:**
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|
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```bash
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curl -fsSL https://raw.githubusercontent.com/can1357/oh-my-pi/main/scripts/install.sh | sh
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```
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|
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**Windows (PowerShell):**
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|
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```powershell
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irm https://raw.githubusercontent.com/can1357/oh-my-pi/main/scripts/install.ps1 | iex
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```
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@@ -46,6 +48,7 @@ irm https://raw.githubusercontent.com/can1357/oh-my-pi/main/scripts/install.ps1
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By default, the installer uses bun if available, otherwise downloads the prebuilt binary.
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Options:
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- `--source` / `-Source`: Install via bun (installs bun first if needed)
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- `--binary` / `-Binary`: Always use prebuilt binary
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- `--ref <ref>` / `-Ref <ref>`: Install a tag/commit/branch (defaults to source install)
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@@ -249,7 +252,7 @@ Handles whitespace and indentation variance automatically:
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| Package | Description |
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| ------------------------------------------------------ | ---------------------------------------------------------------- |
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| **[@oh-my-pi/pi-ai](packages/ai)** | Unified multi-provider LLM API (OpenAI, Anthropic, Google, etc.) |
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| **[@mariozechner/pi-ai](packages/ai)** | Unified multi-provider LLM API (OpenAI, Anthropic, Google, etc.) |
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| **[@oh-my-pi/pi-agent-core](packages/agent)** | Agent runtime with tool calling and state management |
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| **[@oh-my-pi/pi-coding-agent](packages/coding-agent)** | Interactive coding agent CLI |
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| **[@oh-my-pi/pi-mom](packages/mom)** | Slack bot that delegates messages to the pi coding agent |
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@@ -22,7 +22,7 @@
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"name": "@oh-my-pi/pi-agent-core",
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"version": "3.20.1",
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"dependencies": {
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"@oh-my-pi/pi-ai": "workspace:*",
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"@mariozechner/pi-ai": "^0.37.4",
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"@oh-my-pi/pi-tui": "workspace:*",
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},
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"devDependencies": {
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@@ -30,30 +30,6 @@
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"vitest": "^3.2.4",
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},
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},
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"packages/ai": {
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"name": "@oh-my-pi/pi-ai",
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"version": "3.20.1",
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"bin": {
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"pi-ai": "./src/cli.ts",
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},
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"dependencies": {
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"@anthropic-ai/sdk": "0.71.2",
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"@google/genai": "1.34.0",
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"@mistralai/mistralai": "1.10.0",
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"@sinclair/typebox": "^0.34.41",
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"ajv": "^8.17.1",
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"ajv-formats": "^3.0.1",
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"chalk": "^5.6.2",
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"openai": "6.10.0",
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"partial-json": "^0.1.7",
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"zod-to-json-schema": "^3.24.6",
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},
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"devDependencies": {
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"@types/node": "^24.3.0",
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"canvas": "^3.2.0",
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"vitest": "^3.2.4",
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},
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},
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"packages/coding-agent": {
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"name": "@oh-my-pi/pi-coding-agent",
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"version": "3.20.1",
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@@ -61,8 +37,8 @@
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"omp": "src/cli.ts",
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},
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"dependencies": {
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"@mariozechner/pi-ai": "^0.37.4",
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"@oh-my-pi/pi-agent-core": "workspace:*",
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"@oh-my-pi/pi-ai": "workspace:*",
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"@oh-my-pi/pi-git-tool": "workspace:*",
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"@oh-my-pi/pi-tui": "workspace:*",
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"@openai/agents": "^0.3.7",
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@@ -103,30 +79,6 @@
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"vitest": "^3.2.4",
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},
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},
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"packages/mom": {
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"name": "@oh-my-pi/pi-mom",
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"version": "3.20.1",
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"bin": {
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"mom": "src/main.ts",
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},
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"dependencies": {
|
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"@anthropic-ai/sandbox-runtime": "^0.0.16",
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"@oh-my-pi/pi-agent-core": "workspace:*",
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"@oh-my-pi/pi-ai": "workspace:*",
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"@oh-my-pi/pi-coding-agent": "workspace:*",
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||||
"@sinclair/typebox": "^0.34.0",
|
||||
"@slack/socket-mode": "^2.0.0",
|
||||
"@slack/web-api": "^7.0.0",
|
||||
"async-mutex": "^0.5.0",
|
||||
"chalk": "^5.6.2",
|
||||
"croner": "^9.1.0",
|
||||
"diff": "^8.0.2",
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/diff": "^7.0.2",
|
||||
"@types/node": "^24.3.0",
|
||||
},
|
||||
},
|
||||
"packages/tui": {
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||||
"name": "@oh-my-pi/pi-tui",
|
||||
"version": "3.20.1",
|
||||
@@ -142,51 +94,8 @@
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||||
"@xterm/xterm": "^5.5.0",
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||||
},
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||||
},
|
||||
"packages/web-ui": {
|
||||
"name": "@oh-my-pi/pi-web-ui",
|
||||
"version": "3.20.1",
|
||||
"dependencies": {
|
||||
"@lmstudio/sdk": "^1.5.0",
|
||||
"@oh-my-pi/pi-agent-core": "workspace:*",
|
||||
"@oh-my-pi/pi-ai": "workspace:*",
|
||||
"@oh-my-pi/pi-tui": "workspace:*",
|
||||
"docx-preview": "^0.3.7",
|
||||
"highlight.js": "^11.11.1",
|
||||
"jszip": "^3.10.1",
|
||||
"lucide": "^0.544.0",
|
||||
"ollama": "^0.6.0",
|
||||
"pdfjs-dist": "5.4.394",
|
||||
"tailwindcss": "^4.1.18",
|
||||
"xlsx": "https://cdn.sheetjs.com/xlsx-0.20.3/xlsx-0.20.3.tgz",
|
||||
},
|
||||
"devDependencies": {
|
||||
"@mariozechner/mini-lit": "^0.2.0",
|
||||
"@tailwindcss/cli": "^4.0.0-beta.14",
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@mariozechner/mini-lit": "^0.2.0",
|
||||
"lit": "^3.3.1",
|
||||
},
|
||||
},
|
||||
"packages/web-ui/example": {
|
||||
"name": "pi-web-ui-example",
|
||||
"version": "1.20.0",
|
||||
"dependencies": {
|
||||
"@mariozechner/mini-lit": "^0.2.0",
|
||||
"@oh-my-pi/pi-ai": "workspace:*",
|
||||
"@oh-my-pi/pi-web-ui": "workspace:*",
|
||||
"@tailwindcss/vite": "^4.1.17",
|
||||
"lit": "^3.3.1",
|
||||
"lucide": "^0.544.0",
|
||||
},
|
||||
"devDependencies": {
|
||||
"vite": "^7.1.6",
|
||||
},
|
||||
},
|
||||
},
|
||||
"packages": {
|
||||
"@anthropic-ai/sandbox-runtime": ["@anthropic-ai/sandbox-runtime@0.0.16", "", { "dependencies": { "@pondwader/socks5-server": "^1.0.10", "@types/lodash-es": "^4.17.12", "commander": "^12.1.0", "lodash-es": "^4.17.21", "shell-quote": "^1.8.3", "zod": "^3.24.1" }, "bin": { "srt": "dist/cli.js" } }, "sha512-I2Us7dRvwCJkqcImrqP7NWrV5kHmKX7AumFDnznCjMd0hB5ZUzg9Is9SlxrMzHiUY2RndEaRLXCOJrUt8JnE4w=="],
|
||||
|
||||
"@anthropic-ai/sdk": ["@anthropic-ai/sdk@0.71.2", "", { "dependencies": { "json-schema-to-ts": "^3.1.1" }, "peerDependencies": { "zod": "^3.25.0 || ^4.0.0" }, "optionalPeers": ["zod"], "bin": { "anthropic-ai-sdk": "bin/cli" } }, "sha512-TGNDEUuEstk/DKu0/TflXAEt+p+p/WhTlFzEnoosvbaDU2LTjm42igSdlL0VijrKpWejtOKxX0b8A7uc+XiSAQ=="],
|
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|
||||
"@babel/runtime": ["@babel/runtime@7.28.4", "", {}, "sha512-Q/N6JNWvIvPnLDvjlE1OUBLPQHH6l3CltCEsHIujp45zQUSSh8K+gHnaEX45yAT1nyngnINhvWtzN+Nb9D8RAQ=="],
|
||||
@@ -329,68 +238,22 @@
|
||||
|
||||
"@isaacs/cliui": ["@isaacs/cliui@8.0.2", "", { "dependencies": { "string-width": "^5.1.2", "string-width-cjs": "npm:string-width@^4.2.0", "strip-ansi": "^7.0.1", "strip-ansi-cjs": "npm:strip-ansi@^6.0.1", "wrap-ansi": "^8.1.0", "wrap-ansi-cjs": "npm:wrap-ansi@^7.0.0" } }, "sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA=="],
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|
||||
"@jridgewell/gen-mapping": ["@jridgewell/gen-mapping@0.3.13", "", { "dependencies": { "@jridgewell/sourcemap-codec": "^1.5.0", "@jridgewell/trace-mapping": "^0.3.24" } }, "sha512-2kkt/7niJ6MgEPxF0bYdQ6etZaA+fQvDcLKckhy1yIQOzaoKjBBjSj63/aLVjYE3qhRt5dvM+uUyfCg6UKCBbA=="],
|
||||
|
||||
"@jridgewell/remapping": ["@jridgewell/remapping@2.3.5", "", { "dependencies": { "@jridgewell/gen-mapping": "^0.3.5", "@jridgewell/trace-mapping": "^0.3.24" } }, "sha512-LI9u/+laYG4Ds1TDKSJW2YPrIlcVYOwi2fUC6xB43lueCjgxV4lffOCZCtYFiH6TNOX+tQKXx97T4IKHbhyHEQ=="],
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|
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"@jridgewell/resolve-uri": ["@jridgewell/resolve-uri@3.1.2", "", {}, "sha512-bRISgCIjP20/tbWSPWMEi54QVPRZExkuD9lJL+UIxUKtwVJA8wW1Trb1jMs1RFXo1CBTNZ/5hpC9QvmKWdopKw=="],
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|
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"@jridgewell/sourcemap-codec": ["@jridgewell/sourcemap-codec@1.5.5", "", {}, "sha512-cYQ9310grqxueWbl+WuIUIaiUaDcj7WOq5fVhEljNVgRfOUhY9fy2zTvfoqWsnebh8Sl70VScFbICvJnLKB0Og=="],
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|
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"@jridgewell/trace-mapping": ["@jridgewell/trace-mapping@0.3.31", "", { "dependencies": { "@jridgewell/resolve-uri": "^3.1.0", "@jridgewell/sourcemap-codec": "^1.4.14" } }, "sha512-zzNR+SdQSDJzc8joaeP8QQoCQr8NuYx2dIIytl1QeBEZHJ9uW6hebsrYgbz8hJwUQao3TWCMtmfV8Nu1twOLAw=="],
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|
||||
"@lit-labs/ssr-dom-shim": ["@lit-labs/ssr-dom-shim@1.5.0", "", {}, "sha512-HLomZXMmrCFHSRKESF5vklAKsDY7/fsT/ZhqCu3V0UoW/Qbv8wxmO4W9bx4KnCCF2Zak4yuk+AGraK/bPmI4kA=="],
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"@lit/reactive-element": ["@lit/reactive-element@2.1.2", "", { "dependencies": { "@lit-labs/ssr-dom-shim": "^1.5.0" } }, "sha512-pbCDiVMnne1lYUIaYNN5wrwQXDtHaYtg7YEFPeW+hws6U47WeFvISGUWekPGKWOP1ygrs0ef0o1VJMk1exos5A=="],
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"@lmstudio/lms-isomorphic": ["@lmstudio/lms-isomorphic@0.4.6", "", { "dependencies": { "ws": "^8.16.0" } }, "sha512-v0LIjXKnDe3Ff3XZO5eQjlVxTjleUHXaom14MV7QU9bvwaoo3l5p71+xJ3mmSaqZq370CQ6pTKCn1Bb7Jf+VwQ=="],
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"@lmstudio/sdk": ["@lmstudio/sdk@1.5.0", "", { "dependencies": { "@lmstudio/lms-isomorphic": "^0.4.6", "chalk": "^4.1.2", "jsonschema": "^1.5.0", "zod": "^3.22.4", "zod-to-json-schema": "^3.22.5" } }, "sha512-fdY12x4hb14PEjYijh7YeCqT1ZDY5Ok6VR4l4+E/dI+F6NW8oB+P83Sxed5vqE4XgTzbgyPuSR2ZbMNxxF+6jA=="],
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|
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"@mariozechner/mini-lit": ["@mariozechner/mini-lit@0.2.1", "", { "dependencies": { "@preact/signals-core": "^1.12.1", "class-variance-authority": "^0.7.1", "diff": "^8.0.2", "highlight.js": "^11.11.1", "html-parse-string": "^0.0.9", "katex": "^0.16.22", "lucide": "^0.544.0", "marked": "^16.3.0", "tailwind-merge": "^3.3.1", "tailwind-variants": "^3.1.1", "uhtml": "^5.0.9" }, "peerDependencies": { "lit": "^3.3.1" } }, "sha512-u300euLgCsDDlb8o2Wbz+55eSJga5X2vB58s9XBuFIr2Bi3iI+GMR7t/NYo/O6Vr6obXShXgYjR3SRUJVgo+kQ=="],
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"@mariozechner/pi-ai": ["@mariozechner/pi-ai@0.37.4", "", { "dependencies": { "@anthropic-ai/sdk": "0.71.2", "@google/genai": "1.34.0", "@mistralai/mistralai": "1.10.0", "@sinclair/typebox": "^0.34.41", "ajv": "^8.17.1", "ajv-formats": "^3.0.1", "chalk": "^5.6.2", "openai": "6.10.0", "partial-json": "^0.1.7", "zod-to-json-schema": "^3.24.6" }, "bin": { "pi-ai": "dist/cli.js" } }, "sha512-uRvay2Niah67Tckcm2uS8zNGTGA5PngzKrOxzo7OM6bKbwIuwIIE4ZXI2U0db9K8dh6L6AUNRAL9epDwnlJPlw=="],
|
||||
|
||||
"@mistralai/mistralai": ["@mistralai/mistralai@1.10.0", "", { "dependencies": { "zod": "^3.20.0", "zod-to-json-schema": "^3.24.1" } }, "sha512-tdIgWs4Le8vpvPiUEWne6tK0qbVc+jMenujnvTqOjogrJUsCSQhus0tHTU1avDDh5//Rq2dFgP9mWRAdIEoBqg=="],
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||||
|
||||
"@modelcontextprotocol/sdk": ["@modelcontextprotocol/sdk@1.25.1", "", { "dependencies": { "@hono/node-server": "^1.19.7", "ajv": "^8.17.1", "ajv-formats": "^3.0.1", "content-type": "^1.0.5", "cors": "^2.8.5", "cross-spawn": "^7.0.5", "eventsource": "^3.0.2", "eventsource-parser": "^3.0.0", "express": "^5.0.1", "express-rate-limit": "^7.5.0", "jose": "^6.1.1", "json-schema-typed": "^8.0.2", "pkce-challenge": "^5.0.0", "raw-body": "^3.0.0", "zod": "^3.25 || ^4.0", "zod-to-json-schema": "^3.25.0" }, "peerDependencies": { "@cfworker/json-schema": "^4.1.1" }, "optionalPeers": ["@cfworker/json-schema"] }, "sha512-yO28oVFFC7EBoiKdAn+VqRm+plcfv4v0xp6osG/VsCB0NlPZWi87ajbCZZ8f/RvOFLEu7//rSRmuZZ7lMoe3gQ=="],
|
||||
|
||||
"@napi-rs/canvas": ["@napi-rs/canvas@0.1.88", "", { "optionalDependencies": { "@napi-rs/canvas-android-arm64": "0.1.88", "@napi-rs/canvas-darwin-arm64": "0.1.88", "@napi-rs/canvas-darwin-x64": "0.1.88", "@napi-rs/canvas-linux-arm-gnueabihf": "0.1.88", "@napi-rs/canvas-linux-arm64-gnu": "0.1.88", "@napi-rs/canvas-linux-arm64-musl": "0.1.88", "@napi-rs/canvas-linux-riscv64-gnu": "0.1.88", "@napi-rs/canvas-linux-x64-gnu": "0.1.88", "@napi-rs/canvas-linux-x64-musl": "0.1.88", "@napi-rs/canvas-win32-arm64-msvc": "0.1.88", "@napi-rs/canvas-win32-x64-msvc": "0.1.88" } }, "sha512-/p08f93LEbsL5mDZFQ3DBxcPv/I4QG9EDYRRq1WNlCOXVfAHBTHMSVMwxlqG/AtnSfUr9+vgfN7MKiyDo0+Weg=="],
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||||
|
||||
"@napi-rs/canvas-android-arm64": ["@napi-rs/canvas-android-arm64@0.1.88", "", { "os": "android", "cpu": "arm64" }, "sha512-KEaClPnZuVxJ8smUWjV1wWFkByBO/D+vy4lN+Dm5DFH514oqwukxKGeck9xcKJhaWJGjfruGmYGiwRe//+/zQQ=="],
|
||||
|
||||
"@napi-rs/canvas-darwin-arm64": ["@napi-rs/canvas-darwin-arm64@0.1.88", "", { "os": "darwin", "cpu": "arm64" }, "sha512-Xgywz0dDxOKSgx3eZnK85WgGMmGrQEW7ZLA/E7raZdlEE+xXCozobgqz2ZvYigpB6DJFYkqnwHjqCOTSDGlFdg=="],
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||||
|
||||
"@napi-rs/canvas-darwin-x64": ["@napi-rs/canvas-darwin-x64@0.1.88", "", { "os": "darwin", "cpu": "x64" }, "sha512-Yz4wSCIQOUgNucgk+8NFtQxQxZV5NO8VKRl9ePKE6XoNyNVC8JDqtvhh3b3TPqKK8W5p2EQpAr1rjjm0mfBxdg=="],
|
||||
|
||||
"@napi-rs/canvas-linux-arm-gnueabihf": ["@napi-rs/canvas-linux-arm-gnueabihf@0.1.88", "", { "os": "linux", "cpu": "arm" }, "sha512-9gQM2SlTo76hYhxHi2XxWTAqpTOb+JtxMPEIr+H5nAhHhyEtNmTSDRtz93SP7mGd2G3Ojf2oF5tP9OdgtgXyKg=="],
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||||
"@napi-rs/canvas-linux-arm64-gnu": ["@napi-rs/canvas-linux-arm64-gnu@0.1.88", "", { "os": "linux", "cpu": "arm64" }, "sha512-7qgaOBMXuVRk9Fzztzr3BchQKXDxGbY+nwsovD3I/Sx81e+sX0ReEDYHTItNb0Je4NHbAl7D0MKyd4SvUc04sg=="],
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"@napi-rs/canvas-linux-arm64-musl": ["@napi-rs/canvas-linux-arm64-musl@0.1.88", "", { "os": "linux", "cpu": "arm64" }, "sha512-kYyNrUsHLkoGHBc77u4Unh067GrfiCUMbGHC2+OTxbeWfZkPt2o32UOQkhnSswKd9Fko/wSqqGkY956bIUzruA=="],
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"@napi-rs/canvas-linux-riscv64-gnu": ["@napi-rs/canvas-linux-riscv64-gnu@0.1.88", "", { "os": "linux", "cpu": "none" }, "sha512-HVuH7QgzB0yavYdNZDRyAsn/ejoXB0hn8twwFnOqUbCCdkV+REna7RXjSR7+PdfW0qMQ2YYWsLvVBT5iL/mGpw=="],
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"@napi-rs/canvas-linux-x64-gnu": ["@napi-rs/canvas-linux-x64-gnu@0.1.88", "", { "os": "linux", "cpu": "x64" }, "sha512-hvcvKIcPEQrvvJtJnwD35B3qk6umFJ8dFIr8bSymfrSMem0EQsfn1ztys8ETIFndTwdNWJKWluvxztA41ivsEw=="],
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||||
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|
||||
"@napi-rs/canvas-win32-arm64-msvc": ["@napi-rs/canvas-win32-arm64-msvc@0.1.88", "", { "os": "win32", "cpu": "arm64" }, "sha512-qcIFfEgHrchyYqRrxsCeTQgpJZ/GqHiqPcU/Fvw/ARVlQeDX1VyFH+X+0gCR2tca6UJrq96vnW+5o7buCq+erA=="],
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|
||||
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|
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|
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"@oh-my-pi/pi-agent-core": ["@oh-my-pi/pi-agent-core@workspace:packages/agent"],
|
||||
|
||||
"@oh-my-pi/pi-ai": ["@oh-my-pi/pi-ai@workspace:packages/ai"],
|
||||
|
||||
"@oh-my-pi/pi-coding-agent": ["@oh-my-pi/pi-coding-agent@workspace:packages/coding-agent"],
|
||||
|
||||
"@oh-my-pi/pi-git-tool": ["@oh-my-pi/pi-git-tool@workspace:packages/git-tool"],
|
||||
|
||||
"@oh-my-pi/pi-mom": ["@oh-my-pi/pi-mom@workspace:packages/mom"],
|
||||
|
||||
"@oh-my-pi/pi-tui": ["@oh-my-pi/pi-tui@workspace:packages/tui"],
|
||||
|
||||
"@oh-my-pi/pi-web-ui": ["@oh-my-pi/pi-web-ui@workspace:packages/web-ui"],
|
||||
|
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"@openai/agents": ["@openai/agents@0.3.7", "", { "dependencies": { "@openai/agents-core": "0.3.7", "@openai/agents-openai": "0.3.7", "@openai/agents-realtime": "0.3.7", "debug": "^4.4.0", "openai": "^6" }, "peerDependencies": { "zod": "^3.25.40 || ^4.0" } }, "sha512-9QKr6Gqb0yy0VLsyKSjxUoHHxN8j0fqtlZ1YTNmo2j5SqRcFG5LdSVyaQbkeJ3sWsCUugCXvEBEir7yAbxjSRw=="],
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|
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"@openai/agents-core": ["@openai/agents-core@0.3.7", "", { "dependencies": { "debug": "^4.4.0", "openai": "^6" }, "optionalDependencies": { "@modelcontextprotocol/sdk": "^1.24.0" }, "peerDependencies": { "zod": "^3.25.40 || ^4.0" }, "optionalPeers": ["zod"] }, "sha512-Ya1sPc8UyHXxgQjNWN1sn/vFNP4CRdT/0SWd0tIc+kHgYuxrvRjwSfWNBqXc70XOZGS5bWWaRTqJBMwQt6AlYg=="],
|
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@@ -399,40 +262,8 @@
|
||||
|
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"@openai/agents-realtime": ["@openai/agents-realtime@0.3.7", "", { "dependencies": { "@openai/agents-core": "0.3.7", "@types/ws": "^8.18.1", "debug": "^4.4.0", "ws": "^8.18.1" }, "peerDependencies": { "zod": "^3.25.40 || ^4.0" } }, "sha512-8zKu33Q8bmXCkReR7UOWQa1rNbIaLwqI4QgjMD20ALaEkuRglRZeaJyfVTIhTcw9COIF35uyiq+GugxFUvPE5A=="],
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|
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|
||||
|
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"@parcel/watcher-android-arm64": ["@parcel/watcher-android-arm64@2.5.1", "", { "os": "android", "cpu": "arm64" }, "sha512-KF8+j9nNbUN8vzOFDpRMsaKBHZ/mcjEjMToVMJOhTozkDonQFFrRcfdLWn6yWKCmJKmdVxSgHiYvTCef4/qcBA=="],
|
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|
||||
"@parcel/watcher-darwin-arm64": ["@parcel/watcher-darwin-arm64@2.5.1", "", { "os": "darwin", "cpu": "arm64" }, "sha512-eAzPv5osDmZyBhou8PoF4i6RQXAfeKL9tjb3QzYuccXFMQU0ruIc/POh30ePnaOyD1UXdlKguHBmsTs53tVoPw=="],
|
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|
||||
"@parcel/watcher-darwin-x64": ["@parcel/watcher-darwin-x64@2.5.1", "", { "os": "darwin", "cpu": "x64" }, "sha512-1ZXDthrnNmwv10A0/3AJNZ9JGlzrF82i3gNQcWOzd7nJ8aj+ILyW1MTxVk35Db0u91oD5Nlk9MBiujMlwmeXZg=="],
|
||||
|
||||
"@parcel/watcher-freebsd-x64": ["@parcel/watcher-freebsd-x64@2.5.1", "", { "os": "freebsd", "cpu": "x64" }, "sha512-SI4eljM7Flp9yPuKi8W0ird8TI/JK6CSxju3NojVI6BjHsTyK7zxA9urjVjEKJ5MBYC+bLmMcbAWlZ+rFkLpJQ=="],
|
||||
|
||||
"@parcel/watcher-linux-arm-glibc": ["@parcel/watcher-linux-arm-glibc@2.5.1", "", { "os": "linux", "cpu": "arm" }, "sha512-RCdZlEyTs8geyBkkcnPWvtXLY44BCeZKmGYRtSgtwwnHR4dxfHRG3gR99XdMEdQ7KeiDdasJwwvNSF5jKtDwdA=="],
|
||||
|
||||
"@parcel/watcher-linux-arm-musl": ["@parcel/watcher-linux-arm-musl@2.5.1", "", { "os": "linux", "cpu": "arm" }, "sha512-6E+m/Mm1t1yhB8X412stiKFG3XykmgdIOqhjWj+VL8oHkKABfu/gjFj8DvLrYVHSBNC+/u5PeNrujiSQ1zwd1Q=="],
|
||||
|
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"@parcel/watcher-linux-arm64-glibc": ["@parcel/watcher-linux-arm64-glibc@2.5.1", "", { "os": "linux", "cpu": "arm64" }, "sha512-LrGp+f02yU3BN9A+DGuY3v3bmnFUggAITBGriZHUREfNEzZh/GO06FF5u2kx8x+GBEUYfyTGamol4j3m9ANe8w=="],
|
||||
|
||||
"@parcel/watcher-linux-arm64-musl": ["@parcel/watcher-linux-arm64-musl@2.5.1", "", { "os": "linux", "cpu": "arm64" }, "sha512-cFOjABi92pMYRXS7AcQv9/M1YuKRw8SZniCDw0ssQb/noPkRzA+HBDkwmyOJYp5wXcsTrhxO0zq1U11cK9jsFg=="],
|
||||
|
||||
"@parcel/watcher-linux-x64-glibc": ["@parcel/watcher-linux-x64-glibc@2.5.1", "", { "os": "linux", "cpu": "x64" }, "sha512-GcESn8NZySmfwlTsIur+49yDqSny2IhPeZfXunQi48DMugKeZ7uy1FX83pO0X22sHntJ4Ub+9k34XQCX+oHt2A=="],
|
||||
|
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"@parcel/watcher-linux-x64-musl": ["@parcel/watcher-linux-x64-musl@2.5.1", "", { "os": "linux", "cpu": "x64" }, "sha512-n0E2EQbatQ3bXhcH2D1XIAANAcTZkQICBPVaxMeaCVBtOpBZpWJuf7LwyWPSBDITb7In8mqQgJ7gH8CILCURXg=="],
|
||||
|
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"@parcel/watcher-win32-arm64": ["@parcel/watcher-win32-arm64@2.5.1", "", { "os": "win32", "cpu": "arm64" }, "sha512-RFzklRvmc3PkjKjry3hLF9wD7ppR4AKcWNzH7kXR7GUe0Igb3Nz8fyPwtZCSquGrhU5HhUNDr/mKBqj7tqA2Vw=="],
|
||||
|
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"@parcel/watcher-win32-ia32": ["@parcel/watcher-win32-ia32@2.5.1", "", { "os": "win32", "cpu": "ia32" }, "sha512-c2KkcVN+NJmuA7CGlaGD1qJh1cLfDnQsHjE89E60vUEMlqduHGCdCLJCID5geFVM0dOtA3ZiIO8BoEQmzQVfpQ=="],
|
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|
||||
"@parcel/watcher-win32-x64": ["@parcel/watcher-win32-x64@2.5.1", "", { "os": "win32", "cpu": "x64" }, "sha512-9lHBdJITeNR++EvSQVUcaZoWupyHfXe1jZvGZ06O/5MflPcuPLtEphScIBL+AiCWBO46tDSHzWyD0uDmmZqsgA=="],
|
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|
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"@pkgjs/parseargs": ["@pkgjs/parseargs@0.11.0", "", {}, "sha512-+1VkjdD0QBLPodGrJUeqarH8VAIvQODIbwh9XpP5Syisf7YoQgsJKPNFoqqLQlu+VQ/tVSshMR6loPMn8U+dPg=="],
|
||||
|
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"@pondwader/socks5-server": ["@pondwader/socks5-server@1.0.10", "", {}, "sha512-bQY06wzzR8D2+vVCUoBsr5QS2U6UgPUQRmErNwtsuI6vLcyRKkafjkr3KxbtGFf9aBBIV2mcvlsKD1UYaIV+sg=="],
|
||||
|
||||
"@preact/signals-core": ["@preact/signals-core@1.12.1", "", {}, "sha512-BwbTXpj+9QutoZLQvbttRg5x3l5468qaV2kufh+51yha1c53ep5dY4kTuZR35+3pAZxpfQerGJiQqg34ZNZ6uA=="],
|
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|
||||
"@rollup/rollup-android-arm-eabi": ["@rollup/rollup-android-arm-eabi@4.55.1", "", { "os": "android", "cpu": "arm" }, "sha512-9R0DM/ykwfGIlNu6+2U09ga0WXeZ9MRC2Ter8jnz8415VbuIykVuc6bhdrbORFZANDmTDvq26mJrEVTl8TdnDg=="],
|
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|
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"@rollup/rollup-android-arm64": ["@rollup/rollup-android-arm64@4.55.1", "", { "os": "android", "cpu": "arm64" }, "sha512-eFZCb1YUqhTysgW3sj/55du5cG57S7UTNtdMjCW7LwVcj3dTTcowCsC8p7uBdzKsZYa8J7IDE8lhMI+HX1vQvg=="],
|
||||
@@ -485,48 +316,8 @@
|
||||
|
||||
"@sinclair/typebox": ["@sinclair/typebox@0.34.47", "", {}, "sha512-ZGIBQ+XDvO5JQku9wmwtabcVTHJsgSWAHYtVuM9pBNNR5E88v6Jcj/llpmsjivig5X8A8HHOb4/mbEKPS5EvAw=="],
|
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|
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"@slack/logger": ["@slack/logger@4.0.0", "", { "dependencies": { "@types/node": ">=18.0.0" } }, "sha512-Wz7QYfPAlG/DR+DfABddUZeNgoeY7d1J39OCR2jR+v7VBsB8ezulDK5szTnDDPDwLH5IWhLvXIHlCFZV7MSKgA=="],
|
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|
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"@slack/socket-mode": ["@slack/socket-mode@2.0.5", "", { "dependencies": { "@slack/logger": "^4", "@slack/web-api": "^7.10.0", "@types/node": ">=18", "@types/ws": "^8", "eventemitter3": "^5", "ws": "^8" } }, "sha512-VaapvmrAifeFLAFaDPfGhEwwunTKsI6bQhYzxRXw7BSujZUae5sANO76WqlVsLXuhVtCVrBWPiS2snAQR2RHJQ=="],
|
||||
|
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"@slack/types": ["@slack/types@2.19.0", "", {}, "sha512-7+QZ38HGcNh/b/7MpvPG6jnw7mliV6UmrquJLqgdxkzJgQEYUcEztvFWRU49z0x4vthF0ixL5lTK601AXrS8IA=="],
|
||||
|
||||
"@slack/web-api": ["@slack/web-api@7.13.0", "", { "dependencies": { "@slack/logger": "^4.0.0", "@slack/types": "^2.18.0", "@types/node": ">=18.0.0", "@types/retry": "0.12.0", "axios": "^1.11.0", "eventemitter3": "^5.0.1", "form-data": "^4.0.4", "is-electron": "2.2.2", "is-stream": "^2", "p-queue": "^6", "p-retry": "^4", "retry": "^0.13.1" } }, "sha512-ERcExbWrnkDN8ovoWWe6Wgt/usanj1dWUd18dJLpctUI4mlPS0nKt81Joh8VI+OPbNnY1lIilVt9gdMBD9U2ig=="],
|
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|
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"@so-ric/colorspace": ["@so-ric/colorspace@1.1.6", "", { "dependencies": { "color": "^5.0.2", "text-hex": "1.0.x" } }, "sha512-/KiKkpHNOBgkFJwu9sh48LkHSMYGyuTcSFK/qMBdnOAlrRJzRSXAOFB5qwzaVQuDl8wAvHVMkaASQDReTahxuw=="],
|
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|
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"@tailwindcss/cli": ["@tailwindcss/cli@4.1.18", "", { "dependencies": { "@parcel/watcher": "^2.5.1", "@tailwindcss/node": "4.1.18", "@tailwindcss/oxide": "4.1.18", "enhanced-resolve": "^5.18.3", "mri": "^1.2.0", "picocolors": "^1.1.1", "tailwindcss": "4.1.18" }, "bin": { "tailwindcss": "dist/index.mjs" } }, "sha512-sMZ+lZbDyxwjD2E0L7oRUjJ01Ffjtme5OtjvvnC+cV4CEDcbqzbp25TCpxHj6kWLU9+DlqJOiNgSOgctC2aZmg=="],
|
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|
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"@tailwindcss/node": ["@tailwindcss/node@4.1.18", "", { "dependencies": { "@jridgewell/remapping": "^2.3.4", "enhanced-resolve": "^5.18.3", "jiti": "^2.6.1", "lightningcss": "1.30.2", "magic-string": "^0.30.21", "source-map-js": "^1.2.1", "tailwindcss": "4.1.18" } }, "sha512-DoR7U1P7iYhw16qJ49fgXUlry1t4CpXeErJHnQ44JgTSKMaZUdf17cfn5mHchfJ4KRBZRFA/Coo+MUF5+gOaCQ=="],
|
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|
||||
"@tailwindcss/oxide": ["@tailwindcss/oxide@4.1.18", "", { "optionalDependencies": { "@tailwindcss/oxide-android-arm64": "4.1.18", "@tailwindcss/oxide-darwin-arm64": "4.1.18", "@tailwindcss/oxide-darwin-x64": "4.1.18", "@tailwindcss/oxide-freebsd-x64": "4.1.18", "@tailwindcss/oxide-linux-arm-gnueabihf": "4.1.18", "@tailwindcss/oxide-linux-arm64-gnu": "4.1.18", "@tailwindcss/oxide-linux-arm64-musl": "4.1.18", "@tailwindcss/oxide-linux-x64-gnu": "4.1.18", "@tailwindcss/oxide-linux-x64-musl": "4.1.18", "@tailwindcss/oxide-wasm32-wasi": "4.1.18", "@tailwindcss/oxide-win32-arm64-msvc": "4.1.18", "@tailwindcss/oxide-win32-x64-msvc": "4.1.18" } }, "sha512-EgCR5tTS5bUSKQgzeMClT6iCY3ToqE1y+ZB0AKldj809QXk1Y+3jB0upOYZrn9aGIzPtUsP7sX4QQ4XtjBB95A=="],
|
||||
|
||||
"@tailwindcss/oxide-android-arm64": ["@tailwindcss/oxide-android-arm64@4.1.18", "", { "os": "android", "cpu": "arm64" }, "sha512-dJHz7+Ugr9U/diKJA0W6N/6/cjI+ZTAoxPf9Iz9BFRF2GzEX8IvXxFIi/dZBloVJX/MZGvRuFA9rqwdiIEZQ0Q=="],
|
||||
|
||||
"@tailwindcss/oxide-darwin-arm64": ["@tailwindcss/oxide-darwin-arm64@4.1.18", "", { "os": "darwin", "cpu": "arm64" }, "sha512-Gc2q4Qhs660bhjyBSKgq6BYvwDz4G+BuyJ5H1xfhmDR3D8HnHCmT/BSkvSL0vQLy/nkMLY20PQ2OoYMO15Jd0A=="],
|
||||
|
||||
"@tailwindcss/oxide-darwin-x64": ["@tailwindcss/oxide-darwin-x64@4.1.18", "", { "os": "darwin", "cpu": "x64" }, "sha512-FL5oxr2xQsFrc3X9o1fjHKBYBMD1QZNyc1Xzw/h5Qu4XnEBi3dZn96HcHm41c/euGV+GRiXFfh2hUCyKi/e+yw=="],
|
||||
|
||||
"@tailwindcss/oxide-freebsd-x64": ["@tailwindcss/oxide-freebsd-x64@4.1.18", "", { "os": "freebsd", "cpu": "x64" }, "sha512-Fj+RHgu5bDodmV1dM9yAxlfJwkkWvLiRjbhuO2LEtwtlYlBgiAT4x/j5wQr1tC3SANAgD+0YcmWVrj8R9trVMA=="],
|
||||
|
||||
"@tailwindcss/oxide-linux-arm-gnueabihf": ["@tailwindcss/oxide-linux-arm-gnueabihf@4.1.18", "", { "os": "linux", "cpu": "arm" }, "sha512-Fp+Wzk/Ws4dZn+LV2Nqx3IilnhH51YZoRaYHQsVq3RQvEl+71VGKFpkfHrLM/Li+kt5c0DJe/bHXK1eHgDmdiA=="],
|
||||
|
||||
"@tailwindcss/oxide-linux-arm64-gnu": ["@tailwindcss/oxide-linux-arm64-gnu@4.1.18", "", { "os": "linux", "cpu": "arm64" }, "sha512-S0n3jboLysNbh55Vrt7pk9wgpyTTPD0fdQeh7wQfMqLPM/Hrxi+dVsLsPrycQjGKEQk85Kgbx+6+QnYNiHalnw=="],
|
||||
|
||||
"@tailwindcss/oxide-linux-arm64-musl": ["@tailwindcss/oxide-linux-arm64-musl@4.1.18", "", { "os": "linux", "cpu": "arm64" }, "sha512-1px92582HkPQlaaCkdRcio71p8bc8i/ap5807tPRDK/uw953cauQBT8c5tVGkOwrHMfc2Yh6UuxaH4vtTjGvHg=="],
|
||||
|
||||
"@tailwindcss/oxide-linux-x64-gnu": ["@tailwindcss/oxide-linux-x64-gnu@4.1.18", "", { "os": "linux", "cpu": "x64" }, "sha512-v3gyT0ivkfBLoZGF9LyHmts0Isc8jHZyVcbzio6Wpzifg/+5ZJpDiRiUhDLkcr7f/r38SWNe7ucxmGW3j3Kb/g=="],
|
||||
|
||||
"@tailwindcss/oxide-linux-x64-musl": ["@tailwindcss/oxide-linux-x64-musl@4.1.18", "", { "os": "linux", "cpu": "x64" }, "sha512-bhJ2y2OQNlcRwwgOAGMY0xTFStt4/wyU6pvI6LSuZpRgKQwxTec0/3Scu91O8ir7qCR3AuepQKLU/kX99FouqQ=="],
|
||||
|
||||
"@tailwindcss/oxide-wasm32-wasi": ["@tailwindcss/oxide-wasm32-wasi@4.1.18", "", { "dependencies": { "@emnapi/core": "^1.7.1", "@emnapi/runtime": "^1.7.1", "@emnapi/wasi-threads": "^1.1.0", "@napi-rs/wasm-runtime": "^1.1.0", "@tybys/wasm-util": "^0.10.1", "tslib": "^2.4.0" }, "cpu": "none" }, "sha512-LffYTvPjODiP6PT16oNeUQJzNVyJl1cjIebq/rWWBF+3eDst5JGEFSc5cWxyRCJ0Mxl+KyIkqRxk1XPEs9x8TA=="],
|
||||
|
||||
"@tailwindcss/oxide-win32-arm64-msvc": ["@tailwindcss/oxide-win32-arm64-msvc@4.1.18", "", { "os": "win32", "cpu": "arm64" }, "sha512-HjSA7mr9HmC8fu6bdsZvZ+dhjyGCLdotjVOgLA2vEqxEBZaQo9YTX4kwgEvPCpRh8o4uWc4J/wEoFzhEmjvPbA=="],
|
||||
|
||||
"@tailwindcss/oxide-win32-x64-msvc": ["@tailwindcss/oxide-win32-x64-msvc@4.1.18", "", { "os": "win32", "cpu": "x64" }, "sha512-bJWbyYpUlqamC8dpR7pfjA0I7vdF6t5VpUGMWRkXVE3AXgIZjYUYAK7II1GNaxR8J1SSrSrppRar8G++JekE3Q=="],
|
||||
|
||||
"@tailwindcss/vite": ["@tailwindcss/vite@4.1.18", "", { "dependencies": { "@tailwindcss/node": "4.1.18", "@tailwindcss/oxide": "4.1.18", "tailwindcss": "4.1.18" }, "peerDependencies": { "vite": "^5.2.0 || ^6 || ^7" } }, "sha512-jVA+/UpKL1vRLg6Hkao5jldawNmRo7mQYrZtNHMIVpLfLhDml5nMRUo/8MwoX2vNXvnaXNNMedrMfMugAVX1nA=="],
|
||||
|
||||
"@tokenizer/inflate": ["@tokenizer/inflate@0.4.1", "", { "dependencies": { "debug": "^4.4.3", "token-types": "^6.1.1" } }, "sha512-2mAv+8pkG6GIZiF1kNg1jAjh27IDxEPKwdGul3snfztFerfPGI1LjDezZp3i7BElXompqEtPmoPx6c2wgtWsOA=="],
|
||||
|
||||
"@tokenizer/token": ["@tokenizer/token@0.3.0", "", {}, "sha512-OvjF+z51L3ov0OyAU0duzsYuvO01PH7x4t6DJx+guahgTnBHkhJdG7soQeTSFLWN3efnHyibZ4Z8l2EuWwJN3A=="],
|
||||
@@ -541,10 +332,6 @@
|
||||
|
||||
"@types/estree": ["@types/estree@1.0.8", "", {}, "sha512-dWHzHa2WqEXI/O1E9OjrocMTKJl2mSrEolh1Iomrv6U+JuNwaHXsXx9bLu5gG7BUWFIN0skIQJQ/L1rIex4X6w=="],
|
||||
|
||||
"@types/lodash": ["@types/lodash@4.17.21", "", {}, "sha512-FOvQ0YPD5NOfPgMzJihoT+Za5pdkDJWcbpuj1DjaKZIr/gxodQjY/uWEFlTNqW2ugXHUiL8lRQgw63dzKHZdeQ=="],
|
||||
|
||||
"@types/lodash-es": ["@types/lodash-es@4.17.12", "", { "dependencies": { "@types/lodash": "*" } }, "sha512-0NgftHUcV4v34VhXm8QBSftKVXtbkBG3ViCjs6+eJ5a6y6Mi/jiFGPc1sC7QK+9BFhWrURE3EOggmWaSxL9OzQ=="],
|
||||
|
||||
"@types/mime-types": ["@types/mime-types@2.1.4", "", {}, "sha512-lfU4b34HOri+kAY5UheuFMWPDOI+OPceBSHZKp69gEyTL/mmJ4cnU6Y/rlme3UL3GyOn6Y42hyIEw0/q8sWx5w=="],
|
||||
|
||||
"@types/ms": ["@types/ms@2.1.0", "", {}, "sha512-GsCCIZDE/p3i96vtEqx+7dBUGXrc7zeSK3wwPHIaRThS+9OhWIXRqzs4d6k1SVU8g91DrNRWxWUGhp5KXQb2VA=="],
|
||||
@@ -553,14 +340,10 @@
|
||||
|
||||
"@types/node": ["@types/node@22.19.3", "", { "dependencies": { "undici-types": "~6.21.0" } }, "sha512-1N9SBnWYOJTrNZCdh/yJE+t910Y128BoyY+zBLWhL3r0TYzlTmFdXrPwHL9DyFZmlEXNQQolTZh3KHV31QDhyA=="],
|
||||
|
||||
"@types/retry": ["@types/retry@0.12.0", "", {}, "sha512-wWKOClTTiizcZhXnPY4wikVAwmdYHp8q6DmC+EJUzAMsycb7HB32Kh9RN4+0gExjmPmZSAQjgURXIGATPegAvA=="],
|
||||
|
||||
"@types/through": ["@types/through@0.0.33", "", { "dependencies": { "@types/node": "*" } }, "sha512-HsJ+z3QuETzP3cswwtzt2vEIiHBk/dCcHGhbmG5X3ecnwFD/lPrMpliGXxSCg03L9AhrdwA4Oz/qfspkDW+xGQ=="],
|
||||
|
||||
"@types/triple-beam": ["@types/triple-beam@1.3.5", "", {}, "sha512-6WaYesThRMCl19iryMYP7/x2OVgCtbIVflDGFpWnb9irXI3UjYE4AzmYuiUKY1AJstGijoY+MgUszMgRxIYTYw=="],
|
||||
|
||||
"@types/trusted-types": ["@types/trusted-types@2.0.7", "", {}, "sha512-ScaPdn1dQczgbl0QFTeTOmVHFULt394XJgOQNoyVhZ6r2vLnMLJfBPd53SB52T/3G36VI1/g2MZaX0cwDuXsfw=="],
|
||||
|
||||
"@types/ws": ["@types/ws@8.18.1", "", { "dependencies": { "@types/node": "*" } }, "sha512-ThVF6DCVhA8kUGy+aazFQ4kXQ7E1Ty7A3ypFOe0IcJV8O/M511G99AW24irKrW56Wt44yG9+ij8FaqoBGkuBXg=="],
|
||||
|
||||
"@typescript/native-preview": ["@typescript/native-preview@7.0.0-dev.20260106.1", "", { "optionalDependencies": { "@typescript/native-preview-darwin-arm64": "7.0.0-dev.20260106.1", "@typescript/native-preview-darwin-x64": "7.0.0-dev.20260106.1", "@typescript/native-preview-linux-arm": "7.0.0-dev.20260106.1", "@typescript/native-preview-linux-arm64": "7.0.0-dev.20260106.1", "@typescript/native-preview-linux-x64": "7.0.0-dev.20260106.1", "@typescript/native-preview-win32-arm64": "7.0.0-dev.20260106.1", "@typescript/native-preview-win32-x64": "7.0.0-dev.20260106.1" }, "bin": { "tsgo": "bin/tsgo.js" } }, "sha512-EeH81rQsgLjewxuVOBN0MnQWAyf5YNeHRP3+Et6wJyr4d7HuA7zFwfNaEdfX1k366kgpKOR5K6dakorBhKZGng=="],
|
||||
@@ -593,8 +376,6 @@
|
||||
|
||||
"@vitest/utils": ["@vitest/utils@3.2.4", "", { "dependencies": { "@vitest/pretty-format": "3.2.4", "loupe": "^3.1.4", "tinyrainbow": "^2.0.0" } }, "sha512-fB2V0JFrQSMsCo9HiSq3Ezpdv4iYaXRG1Sx8edX3MwxfyNn83mKiGzOcH+Fkxt4MHxr3y42fQi1oeAInqgX2QA=="],
|
||||
|
||||
"@webreflection/alien-signals": ["@webreflection/alien-signals@0.3.2", "", { "dependencies": { "alien-signals": "^2.0.6" } }, "sha512-DmNjD8Kq5iM+Toirp3llS/izAiI3Dwav5nHRvKdR/YJBTgun3y4xK76rs9CFYD2bZwZJN/rP+HjEqKTteGK+Yw=="],
|
||||
|
||||
"@xterm/headless": ["@xterm/headless@5.5.0", "", {}, "sha512-5xXB7kdQlFBP82ViMJTwwEc3gKCLGKR/eoxQm4zge7GPBl86tCdI0IdPJjoKd8mUSFXz5V7i/25sfsEkP4j46g=="],
|
||||
|
||||
"@xterm/xterm": ["@xterm/xterm@5.5.0", "", {}, "sha512-hqJHYaQb5OptNunnyAnkHyM8aCjZ1MEIDTQu1iIbbTD/xops91NB5yq1ZK/dC2JDbVWtF23zUtl9JE2NqwT87A=="],
|
||||
@@ -607,8 +388,6 @@
|
||||
|
||||
"ajv-formats": ["ajv-formats@3.0.1", "", { "dependencies": { "ajv": "^8.0.0" } }, "sha512-8iUql50EUR+uUcdRQ3HDqa6EVyo3docL8g5WJ3FNcWmu62IbkGUue/pEyLBW8VGKKucTPgqeks4fIU1DA4yowQ=="],
|
||||
|
||||
"alien-signals": ["alien-signals@2.0.8", "", {}, "sha512-844G1VLkk0Pe2SJjY0J8vp8ADI73IM4KliNu2OGlYzWpO28NexEUvjHTcFjFX3VXoiUtwTbHxLNI9ImkcoBqzA=="],
|
||||
|
||||
"ansi-escapes": ["ansi-escapes@7.2.0", "", { "dependencies": { "environment": "^1.0.0" } }, "sha512-g6LhBsl+GBPRWGWsBtutpzBYuIIdBkLEvad5C/va/74Db018+5TZiyA26cZJAr3Rft5lprVqOIPxf5Vid6tqAw=="],
|
||||
|
||||
"ansi-regex": ["ansi-regex@6.2.2", "", {}, "sha512-Bq3SmSpyFHaWjPk8If9yc6svM8c56dB5BAtW4Qbw5jHTwwXXcTLoRMkpDJp6VL0XzlWaCHTXrkFURMYmD0sLqg=="],
|
||||
@@ -621,20 +400,12 @@
|
||||
|
||||
"async": ["async@3.2.6", "", {}, "sha512-htCUDlxyyCLMgaM3xXg0C0LW2xqfuQ6p05pCEIsXuyQ+a1koYKTuBMzRNwmybfLgvJDMd0r1LTn4+E0Ti6C2AA=="],
|
||||
|
||||
"async-mutex": ["async-mutex@0.5.0", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-1A94B18jkJ3DYq284ohPxoXbfTA5HsQ7/Mf4DEhcyLx3Bz27Rh59iScbB6EPiP+B+joue6YCxcMXSbFC1tZKwA=="],
|
||||
|
||||
"asynckit": ["asynckit@0.4.0", "", {}, "sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q=="],
|
||||
|
||||
"axios": ["axios@1.13.2", "", { "dependencies": { "follow-redirects": "^1.15.6", "form-data": "^4.0.4", "proxy-from-env": "^1.1.0" } }, "sha512-VPk9ebNqPcy5lRGuSlKx752IlDatOjT9paPlm8A7yOuW2Fbvp4X3JznJtT4f0GzGLLiWE9W8onz51SqLYwzGaA=="],
|
||||
|
||||
"balanced-match": ["balanced-match@1.0.2", "", {}, "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="],
|
||||
|
||||
"base64-js": ["base64-js@1.5.1", "", {}, "sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA=="],
|
||||
|
||||
"bignumber.js": ["bignumber.js@9.3.1", "", {}, "sha512-Ko0uX15oIUS7wJ3Rb30Fs6SkVbLmPBAKdlm7q9+ak9bbIeFf0MwuBsQV6z7+X768/cHsfg+WlysDWJcmthjsjQ=="],
|
||||
|
||||
"bl": ["bl@4.1.0", "", { "dependencies": { "buffer": "^5.5.0", "inherits": "^2.0.4", "readable-stream": "^3.4.0" } }, "sha512-1W07cM9gS6DcLperZfFSj+bWLtaPGSOHWhPiGzXmvVJbRLdG82sH/Kn8EtW1VqWVA54AKf2h5k5BbnIbwF3h6w=="],
|
||||
|
||||
"body-parser": ["body-parser@2.2.1", "", { "dependencies": { "bytes": "^3.1.2", "content-type": "^1.0.5", "debug": "^4.4.3", "http-errors": "^2.0.0", "iconv-lite": "^0.7.0", "on-finished": "^2.4.1", "qs": "^6.14.0", "raw-body": "^3.0.1", "type-is": "^2.0.1" } }, "sha512-nfDwkulwiZYQIGwxdy0RUmowMhKcFVcYXUU7m4QlKYim1rUtg83xm2yjZ40QjDuc291AJjjeSc9b++AWHSgSHw=="],
|
||||
|
||||
"boolbase": ["boolbase@1.0.0", "", {}, "sha512-JZOSA7Mo9sNGB8+UjSgzdLtokWAky1zbztM3WRLCbZ70/3cTANmQmOdR7y2g+J0e2WXywy1yS468tY+IruqEww=="],
|
||||
@@ -643,8 +414,6 @@
|
||||
|
||||
"braces": ["braces@3.0.3", "", { "dependencies": { "fill-range": "^7.1.1" } }, "sha512-yQbXgO/OSZVD2IsiLlro+7Hf6Q18EJrKSEsdoMzKePKXct3gvD8oLcOQdIzGupr5Fj+EDe8gO/lxc1BzfMpxvA=="],
|
||||
|
||||
"buffer": ["buffer@5.7.1", "", { "dependencies": { "base64-js": "^1.3.1", "ieee754": "^1.1.13" } }, "sha512-EHcyIPBQ4BSGlvjB16k5KgAJ27CIsHY/2JBmCRReo48y9rQ3MaUzWX3KVlBa4U7MyX02HdVj0K7C3WaB3ju7FQ=="],
|
||||
|
||||
"buffer-equal-constant-time": ["buffer-equal-constant-time@1.0.1", "", {}, "sha512-zRpUiDwd/xk6ADqPMATG8vc9VPrkck7T07OIx0gnjmJAnHnTVXNQG3vfvWNuiZIkwu9KrKdA1iJKfsfTVxE6NA=="],
|
||||
|
||||
"bun-types": ["bun-types@1.3.5", "", { "dependencies": { "@types/node": "*" } }, "sha512-inmAYe2PFLs0SUbFOWSVD24sg1jFlMPxOjOSSCYqUgn4Hsc3rDc7dFvfVYjFPNHtov6kgUeulV4SxbuIV/stPw=="],
|
||||
@@ -657,18 +426,12 @@
|
||||
|
||||
"call-bound": ["call-bound@1.0.4", "", { "dependencies": { "call-bind-apply-helpers": "^1.0.2", "get-intrinsic": "^1.3.0" } }, "sha512-+ys997U96po4Kx/ABpBCqhA9EuxJaQWDQg7295H4hBphv3IZg0boBKuwYpt4YXp6MZ5AmZQnU/tyMTlRpaSejg=="],
|
||||
|
||||
"canvas": ["canvas@3.2.0", "", { "dependencies": { "node-addon-api": "^7.0.0", "prebuild-install": "^7.1.3" } }, "sha512-jk0GxrLtUEmW/TmFsk2WghvgHe8B0pxGilqCL21y8lHkPUGa6FTsnCNtHPOzT8O3y+N+m3espawV80bbBlgfTA=="],
|
||||
|
||||
"chai": ["chai@5.3.3", "", { "dependencies": { "assertion-error": "^2.0.1", "check-error": "^2.1.1", "deep-eql": "^5.0.1", "loupe": "^3.1.0", "pathval": "^2.0.0" } }, "sha512-4zNhdJD/iOjSH0A05ea+Ke6MU5mmpQcbQsSOkgdaUMJ9zTlDTD/GYlwohmIE2u0gaxHYiVHEn1Fw9mZ/ktJWgw=="],
|
||||
|
||||
"chalk": ["chalk@5.6.2", "", {}, "sha512-7NzBL0rN6fMUW+f7A6Io4h40qQlG+xGmtMxfbnH/K7TAtt8JQWVQK+6g0UXKMeVJoyV5EkkNsErQ8pVD3bLHbA=="],
|
||||
|
||||
"check-error": ["check-error@2.1.3", "", {}, "sha512-PAJdDJusoxnwm1VwW07VWwUN1sl7smmC3OKggvndJFadxxDRyFJBX/ggnu/KE4kQAB7a3Dp8f/YXC1FlUprWmA=="],
|
||||
|
||||
"chownr": ["chownr@1.1.4", "", {}, "sha512-jJ0bqzaylmJtVnNgzTeSOs8DPavpbYgEr/b0YL8/2GO3xJEhInFmhKMUnEJQjZumK7KXGFhUy89PrsJWlakBVg=="],
|
||||
|
||||
"class-variance-authority": ["class-variance-authority@0.7.1", "", { "dependencies": { "clsx": "^2.1.1" } }, "sha512-Ka+9Trutv7G8M6WT6SeiRWz792K5qEqIGEGzXKhAE6xOWAY6pPH8U+9IY3oCMv6kqTmLsv7Xh/2w2RigkePMsg=="],
|
||||
|
||||
"cli-cursor": ["cli-cursor@5.0.0", "", { "dependencies": { "restore-cursor": "^5.0.0" } }, "sha512-aCj4O5wKyszjMmDT4tZj93kxyydN/K5zPWSCe6/0AV/AA1pqe5ZBIw0a2ZfPQV7lL5/yb5HsUreJ6UFAF1tEQw=="],
|
||||
|
||||
"cli-highlight": ["cli-highlight@2.1.11", "", { "dependencies": { "chalk": "^4.0.0", "highlight.js": "^10.7.1", "mz": "^2.4.0", "parse5": "^5.1.1", "parse5-htmlparser2-tree-adapter": "^6.0.0", "yargs": "^16.0.0" }, "bin": { "highlight": "bin/highlight" } }, "sha512-9KDcoEVwyUXrjcJNvHD0NFc/hiwe/WPVYIleQh2O1N2Zro5gWJZ/K+3DGn8w8P/F6FxOgzyC5bxDyHIgCSPhGg=="],
|
||||
@@ -677,8 +440,6 @@
|
||||
|
||||
"cliui": ["cliui@8.0.1", "", { "dependencies": { "string-width": "^4.2.0", "strip-ansi": "^6.0.1", "wrap-ansi": "^7.0.0" } }, "sha512-BSeNnyus75C4//NQ9gQt1/csTXyo/8Sb+afLAkzAptFuMsod9HFokGNudZpi/oQV73hnVK+sR+5PVRMd+Dr7YQ=="],
|
||||
|
||||
"clsx": ["clsx@2.1.1", "", {}, "sha512-eYm0QWBtUrBWZWG0d386OGAw16Z995PiOVo2B7bjWSbHedGl5e0ZWaq65kOGgUSNesEIDkB9ISbTg/JK9dhCZA=="],
|
||||
|
||||
"color": ["color@5.0.3", "", { "dependencies": { "color-convert": "^3.1.3", "color-string": "^2.1.3" } }, "sha512-ezmVcLR3xAVp8kYOm4GS45ZLLgIE6SPAFoduLr6hTDajwb3KZ2F46gulK3XpcwRFb5KKGCSezCBAY4Dw4HsyXA=="],
|
||||
|
||||
"color-convert": ["color-convert@2.0.1", "", { "dependencies": { "color-name": "~1.1.4" } }, "sha512-RRECPsj7iu/xb5oKYcsFHSppFNnsj/52OVTRKb4zP5onXwVF3zVmmToNcOfGC+CRDpfK/U584fMg38ZHCaElKQ=="],
|
||||
@@ -689,8 +450,6 @@
|
||||
|
||||
"colorette": ["colorette@2.0.20", "", {}, "sha512-IfEDxwoWIjkeXL1eXcDiow4UbKjhLdq6/EuSVR9GMN7KVH3r9gQ83e73hsz1Nd1T3ijd5xv1wcWRYO+D6kCI2w=="],
|
||||
|
||||
"combined-stream": ["combined-stream@1.0.8", "", { "dependencies": { "delayed-stream": "~1.0.0" } }, "sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg=="],
|
||||
|
||||
"commander": ["commander@14.0.2", "", {}, "sha512-TywoWNNRbhoD0BXs1P3ZEScW8W5iKrnbithIl0YH+uCmBd0QpPOA8yc82DS3BIE5Ma6FnBVUsJ7wVUDz4dvOWQ=="],
|
||||
|
||||
"concurrently": ["concurrently@9.2.1", "", { "dependencies": { "chalk": "4.1.2", "rxjs": "7.8.2", "shell-quote": "1.8.3", "supports-color": "8.1.1", "tree-kill": "1.2.2", "yargs": "17.7.2" }, "bin": { "conc": "dist/bin/concurrently.js", "concurrently": "dist/bin/concurrently.js" } }, "sha512-fsfrO0MxV64Znoy8/l1vVIjjHa29SZyyqPgQBwhiDcaW8wJc2W3XWVOGx4M3oJBnv/zdUZIIp1gDeS98GzP8Ng=="],
|
||||
@@ -703,12 +462,8 @@
|
||||
|
||||
"cookie-signature": ["cookie-signature@1.2.2", "", {}, "sha512-D76uU73ulSXrD1UXF4KE2TMxVVwhsnCgfAyTg9k8P6KGZjlXKrOLe4dJQKI3Bxi5wjesZoFXJWElNWBjPZMbhg=="],
|
||||
|
||||
"core-util-is": ["core-util-is@1.0.3", "", {}, "sha512-ZQBvi1DcpJ4GDqanjucZ2Hj3wEO5pZDS89BWbkcrvdxksJorwUDDZamX9ldFkp9aw2lmBDLgkObEA4DWNJ9FYQ=="],
|
||||
|
||||
"cors": ["cors@2.8.5", "", { "dependencies": { "object-assign": "^4", "vary": "^1" } }, "sha512-KIHbLJqu73RGr/hnbrO9uBeixNGuvSQjul/jdFvS/KFSIH1hWVd1ng7zOHx+YrEfInLG7q4n6GHQ9cDtxv/P6g=="],
|
||||
|
||||
"croner": ["croner@9.1.0", "", {}, "sha512-p9nwwR4qyT5W996vBZhdvBCnMhicY5ytZkR4D1Xj0wuTDEiMnjwR57Q3RXYY/s0EpX6Ay3vgIcfaR+ewGHsi+g=="],
|
||||
|
||||
"cross-spawn": ["cross-spawn@7.0.6", "", { "dependencies": { "path-key": "^3.1.0", "shebang-command": "^2.0.0", "which": "^2.0.1" } }, "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA=="],
|
||||
|
||||
"css-select": ["css-select@5.2.2", "", { "dependencies": { "boolbase": "^1.0.0", "css-what": "^6.1.0", "domhandler": "^5.0.2", "domutils": "^3.0.1", "nth-check": "^2.0.1" } }, "sha512-TizTzUddG/xYLA3NXodFM0fSbNizXjOKhqiQQwvhlspadZokn1KDy0NZFS0wuEubIYAV5/c1/lAr0TaaFXEXzw=="],
|
||||
@@ -719,22 +474,14 @@
|
||||
|
||||
"debug": ["debug@4.4.3", "", { "dependencies": { "ms": "^2.1.3" } }, "sha512-RGwwWnwQvkVfavKVt22FGLw+xYSdzARwm0ru6DhTVA3umU5hZc28V3kO4stgYryrTlLpuvgI9GiijltAjNbcqA=="],
|
||||
|
||||
"decompress-response": ["decompress-response@6.0.0", "", { "dependencies": { "mimic-response": "^3.1.0" } }, "sha512-aW35yZM6Bb/4oJlZncMH2LCoZtJXTRxES17vE3hoRiowU2kWHaJKFkSBDnDR+cm9J+9QhXmREyIfv0pji9ejCQ=="],
|
||||
|
||||
"deep-eql": ["deep-eql@5.0.2", "", {}, "sha512-h5k/5U50IJJFpzfL6nO9jaaumfjO/f2NjK/oYB2Djzm4p9L+3T9qWpZqZ2hAbLPuuYq9wrU08WQyBTL5GbPk5Q=="],
|
||||
|
||||
"deep-extend": ["deep-extend@0.6.0", "", {}, "sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA=="],
|
||||
|
||||
"delayed-stream": ["delayed-stream@1.0.0", "", {}, "sha512-ZySD7Nf91aLB0RxL4KGrKHBXl7Eds1DAmEdcoVawXnLD7SDhpNgtuII2aAkg7a7QS41jxPSZ17p4VdGnMHk3MQ=="],
|
||||
|
||||
"depd": ["depd@2.0.0", "", {}, "sha512-g7nH6P6dyDioJogAAGprGpCtVImJhpPk/roCzdb3fIh61/s/nPsfR6onyMwkCAR/OlC3yBC0lESvUoQEAssIrw=="],
|
||||
|
||||
"detect-libc": ["detect-libc@2.1.2", "", {}, "sha512-Btj2BOOO83o3WyH59e8MgXsxEQVcarkUOpEYrubB0urwnN10yQ364rsiByU11nZlqWYZm05i/of7io4mzihBtQ=="],
|
||||
|
||||
"diff": ["diff@8.0.2", "", {}, "sha512-sSuxWU5j5SR9QQji/o2qMvqRNYRDOcBTgsJ/DeCf4iSN4gW+gNMXM7wFIP+fdXZxoNiAnHUTGjCr+TSWXdRDKg=="],
|
||||
|
||||
"docx-preview": ["docx-preview@0.3.7", "", { "dependencies": { "jszip": ">=3.0.0" } }, "sha512-Lav69CTA/IYZPJTsKH7oYeoZjyg96N0wEJMNslGJnZJ+dMUZK85Lt5ASC79yUlD48ecWjuv+rkcmFt6EVPV0Xg=="],
|
||||
|
||||
"dom-serializer": ["dom-serializer@2.0.0", "", { "dependencies": { "domelementtype": "^2.3.0", "domhandler": "^5.0.2", "entities": "^4.2.0" } }, "sha512-wIkAryiqt/nV5EQKqQpo3SToSOV9J0DnbJqwK7Wv/Trc92zIAYZ4FlMu+JPFW1DfGFt81ZTCGgDEabffXeLyJg=="],
|
||||
|
||||
"domelementtype": ["domelementtype@2.3.0", "", {}, "sha512-OLETBj6w0OsagBwdXnPdN0cnMfF9opN69co+7ZrbfPGrdpPVNBUj02spi6B1N7wChLQiPn4CSH/zJvXw56gmHw=="],
|
||||
@@ -757,10 +504,6 @@
|
||||
|
||||
"encodeurl": ["encodeurl@2.0.0", "", {}, "sha512-Q0n9HRi4m6JuGIV1eFlmvJB7ZEVxu93IrMyiMsGC0lrMJMWzRgx6WGquyfQgZVb31vhGgXnfmPNNXmxnOkRBrg=="],
|
||||
|
||||
"end-of-stream": ["end-of-stream@1.4.5", "", { "dependencies": { "once": "^1.4.0" } }, "sha512-ooEGc6HP26xXq/N+GCGOT0JKCLDGrq2bQUZrQ7gyrJiZANJ/8YDTxTpQBXGMn+WbIQXNVpyWymm7KYVICQnyOg=="],
|
||||
|
||||
"enhanced-resolve": ["enhanced-resolve@5.18.4", "", { "dependencies": { "graceful-fs": "^4.2.4", "tapable": "^2.2.0" } }, "sha512-LgQMM4WXU3QI+SYgEc2liRgznaD5ojbmY3sb8LxyguVkIg5FxdpTkvk72te2R38/TGKxH634oLxXRGY6d7AP+Q=="],
|
||||
|
||||
"entities": ["entities@4.5.0", "", {}, "sha512-V0hjH4dGPh9Ao5p0MoRY6BVqtwCjhz6vI5LT8AJ55H+4g9/4vbHx1I54fS0XuclLhDHArPQCiMjDxjaL8fPxhw=="],
|
||||
|
||||
"environment": ["environment@1.1.0", "", {}, "sha512-xUtoPkMggbz0MPyPiIWr1Kp4aeWJjDZ6SMvURhimjdZgsRuDplF5/s9hcgGhyXMhs+6vpnuoiZ2kFiu3FMnS8Q=="],
|
||||
@@ -773,8 +516,6 @@
|
||||
|
||||
"es-object-atoms": ["es-object-atoms@1.1.1", "", { "dependencies": { "es-errors": "^1.3.0" } }, "sha512-FGgH2h8zKNim9ljj7dankFPcICIK9Cp5bm+c2gQSYePhpaG5+esrLODihIorn+Pe6FGJzWhXQotPv73jTaldXA=="],
|
||||
|
||||
"es-set-tostringtag": ["es-set-tostringtag@2.1.0", "", { "dependencies": { "es-errors": "^1.3.0", "get-intrinsic": "^1.2.6", "has-tostringtag": "^1.0.2", "hasown": "^2.0.2" } }, "sha512-j6vWzfrGVfyXxge+O0x5sh6cvxAog0a/4Rdd2K36zCMV5eJ+/+tOAngRO8cODMNWbVRdVlmGZQL2YS3yR8bIUA=="],
|
||||
|
||||
"esbuild": ["esbuild@0.27.2", "", { "optionalDependencies": { "@esbuild/aix-ppc64": "0.27.2", "@esbuild/android-arm": "0.27.2", "@esbuild/android-arm64": "0.27.2", "@esbuild/android-x64": "0.27.2", "@esbuild/darwin-arm64": "0.27.2", "@esbuild/darwin-x64": "0.27.2", "@esbuild/freebsd-arm64": "0.27.2", "@esbuild/freebsd-x64": "0.27.2", "@esbuild/linux-arm": "0.27.2", "@esbuild/linux-arm64": "0.27.2", "@esbuild/linux-ia32": "0.27.2", "@esbuild/linux-loong64": "0.27.2", "@esbuild/linux-mips64el": "0.27.2", "@esbuild/linux-ppc64": "0.27.2", "@esbuild/linux-riscv64": "0.27.2", "@esbuild/linux-s390x": "0.27.2", "@esbuild/linux-x64": "0.27.2", "@esbuild/netbsd-arm64": "0.27.2", "@esbuild/netbsd-x64": "0.27.2", "@esbuild/openbsd-arm64": "0.27.2", "@esbuild/openbsd-x64": "0.27.2", "@esbuild/openharmony-arm64": "0.27.2", "@esbuild/sunos-x64": "0.27.2", "@esbuild/win32-arm64": "0.27.2", "@esbuild/win32-ia32": "0.27.2", "@esbuild/win32-x64": "0.27.2" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-HyNQImnsOC7X9PMNaCIeAm4ISCQXs5a5YasTXVliKv4uuBo1dKrG0A+uQS8M5eXjVMnLg3WgXaKvprHlFJQffw=="],
|
||||
|
||||
"escalade": ["escalade@3.2.0", "", {}, "sha512-WUj2qlxaQtO4g6Pq5c29GTcWGDyd8itL8zTlipgECz3JesAiiOKotd8JU6otB3PACgG6xkJUyVhboMS+bje/jA=="],
|
||||
@@ -791,8 +532,6 @@
|
||||
|
||||
"eventsource-parser": ["eventsource-parser@3.0.6", "", {}, "sha512-Vo1ab+QXPzZ4tCa8SwIHJFaSzy4R6SHf7BY79rFBDf0idraZWAkYrDjDj8uWaSm3S2TK+hJ7/t1CEmZ7jXw+pg=="],
|
||||
|
||||
"expand-template": ["expand-template@2.0.3", "", {}, "sha512-XYfuKMvj4O35f/pOXLObndIRvyQ+/+6AhODh+OKWj9S9498pHHn/IMszH+gt0fBCRWMNfk1ZSp5x3AifmnI2vg=="],
|
||||
|
||||
"expect-type": ["expect-type@1.3.0", "", {}, "sha512-knvyeauYhqjOYvQ66MznSMs83wmHrCycNEN6Ao+2AeYEfxUIkuiVxdEa1qlGEPK+We3n0THiDciYSsCcgW/DoA=="],
|
||||
|
||||
"express": ["express@5.2.1", "", { "dependencies": { "accepts": "^2.0.0", "body-parser": "^2.2.1", "content-disposition": "^1.0.0", "content-type": "^1.0.5", "cookie": "^0.7.1", "cookie-signature": "^1.2.1", "debug": "^4.4.0", "depd": "^2.0.0", "encodeurl": "^2.0.0", "escape-html": "^1.0.3", "etag": "^1.8.1", "finalhandler": "^2.1.0", "fresh": "^2.0.0", "http-errors": "^2.0.0", "merge-descriptors": "^2.0.0", "mime-types": "^3.0.0", "on-finished": "^2.4.1", "once": "^1.4.0", "parseurl": "^1.3.3", "proxy-addr": "^2.0.7", "qs": "^6.14.0", "range-parser": "^1.2.1", "router": "^2.2.0", "send": "^1.1.0", "serve-static": "^2.2.0", "statuses": "^2.0.1", "type-is": "^2.0.1", "vary": "^1.1.2" } }, "sha512-hIS4idWWai69NezIdRt2xFVofaF4j+6INOpJlVOLDO8zXGpUVEVzIYk12UUi2JzjEzWL3IOAxcTubgz9Po0yXw=="],
|
||||
@@ -821,20 +560,14 @@
|
||||
|
||||
"fn.name": ["fn.name@1.1.0", "", {}, "sha512-GRnmB5gPyJpAhTQdSZTSp9uaPSvl09KoYcMQtsB9rQoOmzs9dH6ffeccH+Z+cv6P68Hu5bC6JjRh4Ah/mHSNRw=="],
|
||||
|
||||
"follow-redirects": ["follow-redirects@1.15.11", "", {}, "sha512-deG2P0JfjrTxl50XGCDyfI97ZGVCxIpfKYmfyrQ54n5FO/0gfIES8C/Psl6kWVDolizcaaxZJnTS0QSMxvnsBQ=="],
|
||||
|
||||
"foreground-child": ["foreground-child@3.3.1", "", { "dependencies": { "cross-spawn": "^7.0.6", "signal-exit": "^4.0.1" } }, "sha512-gIXjKqtFuWEgzFRJA9WCQeSJLZDjgJUOMCMzxtvFq/37KojM1BFGufqsCy0r4qSQmYLsZYMeyRqzIWOMup03sw=="],
|
||||
|
||||
"form-data": ["form-data@4.0.5", "", { "dependencies": { "asynckit": "^0.4.0", "combined-stream": "^1.0.8", "es-set-tostringtag": "^2.1.0", "hasown": "^2.0.2", "mime-types": "^2.1.12" } }, "sha512-8RipRLol37bNs2bhoV67fiTEvdTrbMUYcFTiy3+wuuOnUog2QBHCZWXDRijWQfAkhBj2Uf5UnVaiWwA5vdd82w=="],
|
||||
|
||||
"formdata-polyfill": ["formdata-polyfill@4.0.10", "", { "dependencies": { "fetch-blob": "^3.1.2" } }, "sha512-buewHzMvYL29jdeQTVILecSaZKnt/RJWjoZCF5OW60Z67/GmSLBkOFM7qh1PI3zFNtJbaZL5eQu1vLfazOwj4g=="],
|
||||
|
||||
"forwarded": ["forwarded@0.2.0", "", {}, "sha512-buRG0fpBtRHSTCOASe6hD258tEubFoRLb4ZNA6NxMVHNw2gOcwHo9wyablzMzOA5z9xA9L1KNjk/Nt6MT9aYow=="],
|
||||
|
||||
"fresh": ["fresh@2.0.0", "", {}, "sha512-Rx/WycZ60HOaqLKAi6cHRKKI7zxWbJ31MhntmtwMoaTeF7XFH9hhBp8vITaMidfljRQ6eYWCKkaTK+ykVJHP2A=="],
|
||||
|
||||
"fs-constants": ["fs-constants@1.0.0", "", {}, "sha512-y6OAwoSIf7FyjMIv94u+b5rdheZEjzR63GTyZJm5qh4Bi+2YgwLCcI/fPFZkL5PSixOt6ZNKm+w+Hfp/Bciwow=="],
|
||||
|
||||
"fsevents": ["fsevents@2.3.3", "", { "os": "darwin" }, "sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw=="],
|
||||
|
||||
"function-bind": ["function-bind@1.1.2", "", {}, "sha512-7XHNxH7qX9xG5mIwxkhumTox/MIRNcOgDrxWsMt2pAr23WHp6MrRlN7FBSFpCpr+oVO0F744iUgR82nJMfG2SA=="],
|
||||
@@ -851,8 +584,6 @@
|
||||
|
||||
"get-proto": ["get-proto@1.0.1", "", { "dependencies": { "dunder-proto": "^1.0.1", "es-object-atoms": "^1.0.0" } }, "sha512-sTSfBjoXBp89JvIKIefqw7U2CCebsc74kiY6awiGogKtoSGbgjYE/G/+l9sF3MWFPNc9IcoOC4ODfKHfxFmp0g=="],
|
||||
|
||||
"github-from-package": ["github-from-package@0.0.0", "", {}, "sha512-SyHy3T1v2NUXn29OsWdxmK6RwHD+vkj3v8en8AOBZ1wBQ/hCAQ5bAQTD02kW4W9tUp/3Qh6J8r9EvntiyCmOOw=="],
|
||||
|
||||
"glob": ["glob@11.1.0", "", { "dependencies": { "foreground-child": "^3.3.1", "jackspeak": "^4.1.1", "minimatch": "^10.1.1", "minipass": "^7.1.2", "package-json-from-dist": "^1.0.0", "path-scurry": "^2.0.0" }, "bin": { "glob": "dist/esm/bin.mjs" } }, "sha512-vuNwKSaKiqm7g0THUBu2x7ckSs3XJLXE+2ssL7/MfTGPLLcrJQ/4Uq1CjPTtO5cCIiRxqvN6Twy1qOwhL0Xjcw=="],
|
||||
|
||||
"google-auth-library": ["google-auth-library@10.5.0", "", { "dependencies": { "base64-js": "^1.3.0", "ecdsa-sig-formatter": "^1.0.11", "gaxios": "^7.0.0", "gcp-metadata": "^8.0.0", "google-logging-utils": "^1.0.0", "gtoken": "^8.0.0", "jws": "^4.0.0" } }, "sha512-7ABviyMOlX5hIVD60YOfHw4/CxOfBhyduaYB+wbFWCWoni4N7SLcV46hrVRktuBbZjFC9ONyqamZITN7q3n32w=="],
|
||||
@@ -861,16 +592,12 @@
|
||||
|
||||
"gopd": ["gopd@1.2.0", "", {}, "sha512-ZUKRh6/kUFoAiTAtTYPZJ3hw9wNxx+BIBOijnlG9PnrJsCcSjs1wyyD6vJpaYtgnzDrKYRSqf3OO6Rfa93xsRg=="],
|
||||
|
||||
"graceful-fs": ["graceful-fs@4.2.11", "", {}, "sha512-RbJ5/jmFcNNCcDV5o9eTnBLJ/HszWV0P73bc+Ff4nS/rJj+YaS6IGyiOL0VoBYX+l1Wrl3k63h/KrH+nhJ0XvQ=="],
|
||||
|
||||
"gtoken": ["gtoken@8.0.0", "", { "dependencies": { "gaxios": "^7.0.0", "jws": "^4.0.0" } }, "sha512-+CqsMbHPiSTdtSO14O51eMNlrp9N79gmeqmXeouJOhfucAedHw9noVe/n5uJk3tbKE6a+6ZCQg3RPhVhHByAIw=="],
|
||||
|
||||
"has-flag": ["has-flag@4.0.0", "", {}, "sha512-EykJT/Q1KjTWctppgIAgfSO0tKVuZUjhgMr17kqTumMl6Afv3EISleU7qZUzoXDFTAHTDC4NOoG/ZxU3EvlMPQ=="],
|
||||
|
||||
"has-symbols": ["has-symbols@1.1.0", "", {}, "sha512-1cDNdwJ2Jaohmb3sg4OmKaMBwuC48sYni5HUw2DvsC8LjGTLK9h+eb1X6RyuOHe4hT0ULCW68iomhjUoKUqlPQ=="],
|
||||
|
||||
"has-tostringtag": ["has-tostringtag@1.0.2", "", { "dependencies": { "has-symbols": "^1.0.3" } }, "sha512-NqADB8VjPFLM2V0VvHUewwwsw0ZWBaIdgo+ieHtK3hasLz4qeCRjYcqfB6AQrBggRKppKF8L52/VqdVsO47Dlw=="],
|
||||
|
||||
"hasown": ["hasown@2.0.2", "", { "dependencies": { "function-bind": "^1.1.2" } }, "sha512-0hJU9SCPvmMzIBdZFqNPXWa6dqh7WdH0cII9y+CyS8rG3nL48Bclra9HmKhVVUHyPWNH5Y7xDwAB7bfgSjkUMQ=="],
|
||||
|
||||
"he": ["he@1.2.0", "", { "bin": { "he": "bin/he" } }, "sha512-F/1DnUGPopORZi0ni+CvrCgHQ5FyEAHRLSApuYWMmrbSwoN2Mn/7k+Gl38gJnR7yyDZk6WLXwiGod1JOWNDKGw=="],
|
||||
@@ -879,8 +606,6 @@
|
||||
|
||||
"hono": ["hono@4.11.3", "", {}, "sha512-PmQi306+M/ct/m5s66Hrg+adPnkD5jiO6IjA7WhWw0gSBSo1EcRegwuI1deZ+wd5pzCGynCcn2DprnE4/yEV4w=="],
|
||||
|
||||
"html-parse-string": ["html-parse-string@0.0.9", "", {}, "sha512-wyGnsOolHbNrcb8N6bdJF4EHyzd3zVGCb9/mBxeNjAYBDOZqD7YkqLBz7kXtdgHwNnV8lN/BpSDpsI1zm8Sd8g=="],
|
||||
|
||||
"http-errors": ["http-errors@2.0.1", "", { "dependencies": { "depd": "~2.0.0", "inherits": "~2.0.4", "setprototypeof": "~1.2.0", "statuses": "~2.0.2", "toidentifier": "~1.0.1" } }, "sha512-4FbRdAX+bSdmo4AUFuS0WNiPz8NgFt+r8ThgNWmlrjQjt1Q7ZR9+zTlce2859x4KSXrwIsaeTqDoKQmtP8pLmQ=="],
|
||||
|
||||
"https-proxy-agent": ["https-proxy-agent@7.0.6", "", { "dependencies": { "agent-base": "^7.1.2", "debug": "4" } }, "sha512-vK9P5/iUfdl95AI+JVyUuIcVtd4ofvtrOr3HNtM2yxC9bnMbEdp3x01OhQNnjb8IJYi38VlTE3mBXwcfvywuSw=="],
|
||||
@@ -889,30 +614,18 @@
|
||||
|
||||
"ieee754": ["ieee754@1.2.1", "", {}, "sha512-dcyqhDvX1C46lXZcVqCpK+FtMRQVdIMN6/Df5js2zouUsqG7I6sFxitIC+7KYK29KdXOLHdu9zL4sFnoVQnqaA=="],
|
||||
|
||||
"immediate": ["immediate@3.0.6", "", {}, "sha512-XXOFtyqDjNDAQxVfYxuF7g9Il/IbWmmlQg2MYKOH8ExIT1qg6xc4zyS3HaEEATgs1btfzxq15ciUiY7gjSXRGQ=="],
|
||||
|
||||
"inherits": ["inherits@2.0.4", "", {}, "sha512-k/vGaX4/Yla3WzyMCvTQOXYeIHvqOKtnqBduzTHpzpQZzAskKMhZ2K+EnBiSM9zGSoIFeMpXKxa4dYeZIQqewQ=="],
|
||||
|
||||
"ini": ["ini@1.3.8", "", {}, "sha512-JV/yugV2uzW5iMRSiZAyDtQd+nxtUnjeLt0acNdw98kKLrvuRVyB80tsREOE7yvGVgalhZ6RNXCmEHkUKBKxew=="],
|
||||
|
||||
"ipaddr.js": ["ipaddr.js@1.9.1", "", {}, "sha512-0KI/607xoxSToH7GjN1FfSbLoU0+btTicjsQSWQlh/hZykN8KpmMf7uYwPW3R+akZ6R/w18ZlXSHBYXiYUPO3g=="],
|
||||
|
||||
"is-electron": ["is-electron@2.2.2", "", {}, "sha512-FO/Rhvz5tuw4MCWkpMzHFKWD2LsfHzIb7i6MdPYZ/KW7AlxawyLkqdy+jPZP1WubqEADE3O4FUENlJHDfQASRg=="],
|
||||
|
||||
"is-extglob": ["is-extglob@2.1.1", "", {}, "sha512-SbKbANkN603Vi4jEZv49LeVJMn4yGwsbzZworEoyEiutsN3nJYdbO36zfhGJ6QEDpOZIFkDtnq5JRxmvl3jsoQ=="],
|
||||
|
||||
"is-fullwidth-code-point": ["is-fullwidth-code-point@3.0.0", "", {}, "sha512-zymm5+u+sCsSWyD9qNaejV3DFvhCKclKdizYaJUuHA83RLjb7nSuGnddCHGv0hk+KY7BMAlsWeK4Ueg6EV6XQg=="],
|
||||
|
||||
"is-glob": ["is-glob@4.0.3", "", { "dependencies": { "is-extglob": "^2.1.1" } }, "sha512-xelSayHH36ZgE7ZWhli7pW34hNbNl8Ojv5KVmkJD4hBdD3th8Tfk9vYasLM+mXWOZhFkgZfxhLSnrwRr4elSSg=="],
|
||||
|
||||
"is-number": ["is-number@7.0.0", "", {}, "sha512-41Cifkg6e8TylSpdtTpeLVMqvSBEVzTttHvERD741+pnZ8ANv0004MRL43QKPDlK9cGvNp6NZWZUBlbGXYxxng=="],
|
||||
|
||||
"is-promise": ["is-promise@4.0.0", "", {}, "sha512-hvpoI6korhJMnej285dSg6nu1+e6uxs7zG3BYAm5byqDsgJNWwxzM6z6iZiAgQR4TJ30JmBTOwqZUw3WlyH3AQ=="],
|
||||
|
||||
"is-stream": ["is-stream@2.0.1", "", {}, "sha512-hFoiJiTl63nn+kstHGBtewWSKnQLpyb155KHheA1l39uvtO9nWIop1p3udqPcUd/xbF1VLMO4n7OI6p7RbngDg=="],
|
||||
|
||||
"isarray": ["isarray@1.0.0", "", {}, "sha512-VLghIWNM6ELQzo7zwmcg0NmTVyWKYjvIeM83yjp0wRDTmUnrM678fQbcKBo6n2CJEF0szoG//ytg+TKla89ALQ=="],
|
||||
|
||||
"isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
|
||||
|
||||
"jackspeak": ["jackspeak@4.1.1", "", { "dependencies": { "@isaacs/cliui": "^8.0.2" } }, "sha512-zptv57P3GpL+O0I7VdMJNBZCu+BPHVQUk55Ft8/QCJjTVxrnJHuVuX/0Bl2A6/+2oyR/ZMEuFKwmzqqZ/U5nPQ=="],
|
||||
@@ -933,20 +646,12 @@
|
||||
|
||||
"json-stringify-safe": ["json-stringify-safe@5.0.1", "", {}, "sha512-ZClg6AaYvamvYEE82d3Iyd3vSSIjQ+odgjaTzRuO3s7toCdFKczob2i0zCh7JE8kWn17yvAWhUVxvqGwUalsRA=="],
|
||||
|
||||
"jsonschema": ["jsonschema@1.5.0", "", {}, "sha512-K+A9hhqbn0f3pJX17Q/7H6yQfD/5OXgdrR5UE12gMXCiN9D5Xq2o5mddV2QEcX/bjla99ASsAAQUyMCCRWAEhw=="],
|
||||
|
||||
"jszip": ["jszip@3.10.1", "", { "dependencies": { "lie": "~3.3.0", "pako": "~1.0.2", "readable-stream": "~2.3.6", "setimmediate": "^1.0.5" } }, "sha512-xXDvecyTpGLrqFrvkrUSoxxfJI5AH7U8zxxtVclpsUtMCq4JQ290LY8AW5c7Ggnr/Y/oK+bQMbqK2qmtk3pN4g=="],
|
||||
|
||||
"jwa": ["jwa@2.0.1", "", { "dependencies": { "buffer-equal-constant-time": "^1.0.1", "ecdsa-sig-formatter": "1.0.11", "safe-buffer": "^5.0.1" } }, "sha512-hRF04fqJIP8Abbkq5NKGN0Bbr3JxlQ+qhZufXVr0DvujKy93ZCbXZMHDL4EOtodSbCWxOqR8MS1tXA5hwqCXDg=="],
|
||||
|
||||
"jws": ["jws@4.0.1", "", { "dependencies": { "jwa": "^2.0.1", "safe-buffer": "^5.0.1" } }, "sha512-EKI/M/yqPncGUUh44xz0PxSidXFr/+r0pA70+gIYhjv+et7yxM+s29Y+VGDkovRofQem0fs7Uvf4+YmAdyRduA=="],
|
||||
|
||||
"katex": ["katex@0.16.27", "", { "dependencies": { "commander": "^8.3.0" }, "bin": { "katex": "cli.js" } }, "sha512-aeQoDkuRWSqQN6nSvVCEFvfXdqo1OQiCmmW1kc9xSdjutPv7BGO7pqY9sQRJpMOGrEdfDgF2TfRXe5eUAD2Waw=="],
|
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|
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"kuler": ["kuler@2.0.0", "", {}, "sha512-Xq9nH7KlWZmXAtodXDDRE7vs6DU1gTU8zYDHDiWLSip45Egwq3plLHzPn27NgvzL2r1LMPC1vdqh98sQxtqj4A=="],
|
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|
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"lie": ["lie@3.3.0", "", { "dependencies": { "immediate": "~3.0.5" } }, "sha512-UaiMJzeWRlEujzAuw5LokY1L5ecNQYZKfmyZ9L7wDHb/p5etKaxXhohBcrw0EYby+G/NA52vRSN4N39dxHAIwQ=="],
|
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|
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"lightningcss": ["lightningcss@1.30.2", "", { "dependencies": { "detect-libc": "^2.0.3" }, "optionalDependencies": { "lightningcss-android-arm64": "1.30.2", "lightningcss-darwin-arm64": "1.30.2", "lightningcss-darwin-x64": "1.30.2", "lightningcss-freebsd-x64": "1.30.2", "lightningcss-linux-arm-gnueabihf": "1.30.2", "lightningcss-linux-arm64-gnu": "1.30.2", "lightningcss-linux-arm64-musl": "1.30.2", "lightningcss-linux-x64-gnu": "1.30.2", "lightningcss-linux-x64-musl": "1.30.2", "lightningcss-win32-arm64-msvc": "1.30.2", "lightningcss-win32-x64-msvc": "1.30.2" } }, "sha512-utfs7Pr5uJyyvDETitgsaqSyjCb2qNRAtuqUeWIAKztsOYdcACf2KtARYXg2pSvhkt+9NfoaNY7fxjl6nuMjIQ=="],
|
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|
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"lightningcss-android-arm64": ["lightningcss-android-arm64@1.30.2", "", { "os": "android", "cpu": "arm64" }, "sha512-BH9sEdOCahSgmkVhBLeU7Hc9DWeZ1Eb6wNS6Da8igvUwAe0sqROHddIlvU06q3WyXVEOYDZ6ykBZQnjTbmo4+A=="],
|
||||
@@ -975,14 +680,6 @@
|
||||
|
||||
"listr2": ["listr2@9.0.5", "", { "dependencies": { "cli-truncate": "^5.0.0", "colorette": "^2.0.20", "eventemitter3": "^5.0.1", "log-update": "^6.1.0", "rfdc": "^1.4.1", "wrap-ansi": "^9.0.0" } }, "sha512-ME4Fb83LgEgwNw96RKNvKV4VTLuXfoKudAmm2lP8Kk87KaMK0/Xrx/aAkMWmT8mDb+3MlFDspfbCs7adjRxA2g=="],
|
||||
|
||||
"lit": ["lit@3.3.2", "", { "dependencies": { "@lit/reactive-element": "^2.1.0", "lit-element": "^4.2.0", "lit-html": "^3.3.0" } }, "sha512-NF9zbsP79l4ao2SNrH3NkfmFgN/hBYSQo90saIVI1o5GpjAdCPVstVzO1MrLOakHoEhYkrtRjPK6Ob521aoYWQ=="],
|
||||
|
||||
"lit-element": ["lit-element@4.2.2", "", { "dependencies": { "@lit-labs/ssr-dom-shim": "^1.5.0", "@lit/reactive-element": "^2.1.0", "lit-html": "^3.3.0" } }, "sha512-aFKhNToWxoyhkNDmWZwEva2SlQia+jfG0fjIWV//YeTaWrVnOxD89dPKfigCUspXFmjzOEUQpOkejH5Ly6sG0w=="],
|
||||
|
||||
"lit-html": ["lit-html@3.3.2", "", { "dependencies": { "@types/trusted-types": "^2.0.2" } }, "sha512-Qy9hU88zcmaxBXcc10ZpdK7cOLXvXpRoBxERdtqV9QOrfpMZZ6pSYP91LhpPtap3sFMUiL7Tw2RImbe0Al2/kw=="],
|
||||
|
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"lodash-es": ["lodash-es@4.17.22", "", {}, "sha512-XEawp1t0gxSi9x01glktRZ5HDy0HXqrM0x5pXQM98EaI0NxO6jVM7omDOxsuEo5UIASAnm2bRp1Jt/e0a2XU8Q=="],
|
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|
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"log-update": ["log-update@6.1.0", "", { "dependencies": { "ansi-escapes": "^7.0.0", "cli-cursor": "^5.0.0", "slice-ansi": "^7.1.0", "strip-ansi": "^7.1.0", "wrap-ansi": "^9.0.0" } }, "sha512-9ie8ItPR6tjY5uYJh8K/Zrv/RMZ5VOlOWvtZdEHYSTFKZfIBPQa9tOAEeAWhd+AnIneLJ22w5fjOYtoutpWq5w=="],
|
||||
|
||||
"logform": ["logform@2.7.0", "", { "dependencies": { "@colors/colors": "1.6.0", "@types/triple-beam": "^1.3.2", "fecha": "^4.2.0", "ms": "^2.1.1", "safe-stable-stringify": "^2.3.1", "triple-beam": "^1.3.0" } }, "sha512-TFYA4jnP7PVbmlBIfhlSe+WKxs9dklXMTEGcBCIvLhE/Tn3H6Gk1norupVW7m5Cnd4bLcr08AytbyV/xj7f/kQ=="],
|
||||
@@ -991,8 +688,6 @@
|
||||
|
||||
"lru-cache": ["lru-cache@11.2.4", "", {}, "sha512-B5Y16Jr9LB9dHVkh6ZevG+vAbOsNOYCX+sXvFWFu7B3Iz5mijW3zdbMyhsh8ANd2mSWBYdJgnqi+mL7/LrOPYg=="],
|
||||
|
||||
"lucide": ["lucide@0.544.0", "", {}, "sha512-U5ORwr5z9Sx7bNTDFaW55RbjVdQEnAcT3vws9uz3vRT1G4XXJUDAhRZdxhFoIyHEvjmTkzzlEhjSLYM5n4mb5w=="],
|
||||
|
||||
"magic-string": ["magic-string@0.30.21", "", { "dependencies": { "@jridgewell/sourcemap-codec": "^1.5.5" } }, "sha512-vd2F4YUyEXKGcLHoq+TEyCjxueSeHnFxyyjNp80yg0XV4vUhnDer/lvvlqM/arB5bXQN5K2/3oinyCRyx8T2CQ=="],
|
||||
|
||||
"marked": ["marked@15.0.12", "", { "bin": { "marked": "bin/marked.js" } }, "sha512-8dD6FusOQSrpv9Z1rdNMdlSgQOIP880DHqnohobOmYLElGEqAL/JvxvuxZO16r4HtjTlfPRDC1hbvxC9dPN2nA=="],
|
||||
@@ -1011,20 +706,14 @@
|
||||
|
||||
"mimic-function": ["mimic-function@5.0.1", "", {}, "sha512-VP79XUPxV2CigYP3jWwAUFSku2aKqBH7uTAapFWCBqutsbmDo96KY5o8uh6U+/YSIn5OxJnXp73beVkpqMIGhA=="],
|
||||
|
||||
"mimic-response": ["mimic-response@3.1.0", "", {}, "sha512-z0yWI+4FDrrweS8Zmt4Ej5HdJmky15+L2e6Wgn3+iK5fWzb6T3fhNFq2+MeTRb064c6Wr4N/wv0DzQTjNzHNGQ=="],
|
||||
|
||||
"minimatch": ["minimatch@10.1.1", "", { "dependencies": { "@isaacs/brace-expansion": "^5.0.0" } }, "sha512-enIvLvRAFZYXJzkCYG5RKmPfrFArdLv+R+lbQ53BmIMLIry74bjKzX6iHAm8WYamJkhSSEabrWN5D97XnKObjQ=="],
|
||||
|
||||
"minimist": ["minimist@1.2.8", "", {}, "sha512-2yyAR8qBkN3YuheJanUpWC5U3bb5osDywNB8RzDVlDwDHbocAJveqqj1u8+SVD7jkWT4yvsHCpWqqWqAxb0zCA=="],
|
||||
|
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"minipass": ["minipass@7.1.2", "", {}, "sha512-qOOzS1cBTWYF4BH8fVePDBOO9iptMnGUEZwNc/cMWnTV2nVLZ7VoNWEPHkYczZA0pdoA7dl6e7FL659nX9S2aw=="],
|
||||
|
||||
"mkdirp-classic": ["mkdirp-classic@0.5.3", "", {}, "sha512-gKLcREMhtuZRwRAfqP3RFW+TK4JqApVBtOIftVgjuABpAtpxhPGaDcfvbhNvD0B8iD1oUr/txX35NjcaY6Ns/A=="],
|
||||
|
||||
"moment": ["moment@2.30.1", "", {}, "sha512-uEmtNhbDOrWPFS+hdjFCBfy9f2YoyzRpwcl+DqpC6taX21FzsTLQVbMV/W7PzNSX6x/bhC1zA3c2UQ5NzH6how=="],
|
||||
|
||||
"mri": ["mri@1.2.0", "", {}, "sha512-tzzskb3bG8LvYGFF/mDTpq3jpI6Q9wc3LEmBaghu+DdCssd1FakN7Bc0hVNmEyGq1bq3RgfkCb3cmQLpNPOroA=="],
|
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|
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"ms": ["ms@2.1.3", "", {}, "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="],
|
||||
|
||||
"mz": ["mz@2.7.0", "", { "dependencies": { "any-promise": "^1.0.0", "object-assign": "^4.0.1", "thenify-all": "^1.0.0" } }, "sha512-z81GNO7nnYMEhrGh9LeymoE4+Yr0Wn5McHIZMK5cfQCl+NDX08sCZgUc9/6MHni9IWuFLm1Z3HTCXu2z9fN62Q=="],
|
||||
@@ -1033,16 +722,10 @@
|
||||
|
||||
"nanoid": ["nanoid@5.1.6", "", { "bin": { "nanoid": "bin/nanoid.js" } }, "sha512-c7+7RQ+dMB5dPwwCp4ee1/iV/q2P6aK1mTZcfr1BTuVlyW9hJYiMPybJCcnBlQtuSmTIWNeazm/zqNoZSSElBg=="],
|
||||
|
||||
"napi-build-utils": ["napi-build-utils@2.0.0", "", {}, "sha512-GEbrYkbfF7MoNaoh2iGG84Mnf/WZfB0GdGEsM8wz7Expx/LlWf5U8t9nvJKXSp3qr5IsEbK04cBGhol/KwOsWA=="],
|
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|
||||
"ndjson": ["ndjson@2.0.0", "", { "dependencies": { "json-stringify-safe": "^5.0.1", "minimist": "^1.2.5", "readable-stream": "^3.6.0", "split2": "^3.0.0", "through2": "^4.0.0" }, "bin": { "ndjson": "cli.js" } }, "sha512-nGl7LRGrzugTtaFcJMhLbpzJM6XdivmbkdlaGcrk/LXg2KL/YBC6z1g70xh0/al+oFuVFP8N8kiWRucmeEH/qQ=="],
|
||||
|
||||
"negotiator": ["negotiator@1.0.0", "", {}, "sha512-8Ofs/AUQh8MaEcrlq5xOX0CQ9ypTF5dl78mjlMNfOK08fzpgTHQRQPBxcPlEtIw0yRpws+Zo/3r+5WRby7u3Gg=="],
|
||||
|
||||
"node-abi": ["node-abi@3.85.0", "", { "dependencies": { "semver": "^7.3.5" } }, "sha512-zsFhmbkAzwhTft6nd3VxcG0cvJsT70rL+BIGHWVq5fi6MwGrHwzqKaxXE+Hl2GmnGItnDKPPkO5/LQqjVkIdFg=="],
|
||||
|
||||
"node-addon-api": ["node-addon-api@7.1.1", "", {}, "sha512-5m3bsyrjFWE1xf7nz7YXdN4udnVtXK6/Yfgn5qnahL6bCkf2yKt4k3nuTKAtT4r3IG8JNR2ncsIMdZuAzJjHQQ=="],
|
||||
|
||||
"node-domexception": ["node-domexception@1.0.0", "", {}, "sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ=="],
|
||||
|
||||
"node-fetch": ["node-fetch@3.3.2", "", { "dependencies": { "data-uri-to-buffer": "^4.0.0", "fetch-blob": "^3.1.4", "formdata-polyfill": "^4.0.10" } }, "sha512-dRB78srN/l6gqWulah9SrxeYnxeddIG30+GOqK/9OlLVyLg3HPnr6SqOWTWOXKRwC2eGYCkZ59NNuSgvSrpgOA=="],
|
||||
@@ -1057,8 +740,6 @@
|
||||
|
||||
"object-inspect": ["object-inspect@1.13.4", "", {}, "sha512-W67iLl4J2EXEGTbfeHCffrjDfitvLANg0UlX3wFUUSTx92KXRFegMHUVgSqE+wvhAbi4WqjGg9czysTV2Epbew=="],
|
||||
|
||||
"ollama": ["ollama@0.6.3", "", { "dependencies": { "whatwg-fetch": "^3.6.20" } }, "sha512-KEWEhIqE5wtfzEIZbDCLH51VFZ6Z3ZSa6sIOg/E/tBV8S51flyqBOXi+bRxlOYKDf8i327zG9eSTb8IJxvm3Zg=="],
|
||||
|
||||
"on-finished": ["on-finished@2.4.1", "", { "dependencies": { "ee-first": "1.1.1" } }, "sha512-oVlzkg3ENAhCk2zdv7IJwd/QUD4z2RxRwpkcGY8psCVcCYZNq4wYnVWALHM+brtuJjePWiYF/ClmuDr8Ch5+kg=="],
|
||||
|
||||
"once": ["once@1.4.0", "", { "dependencies": { "wrappy": "1" } }, "sha512-lNaJgI+2Q5URQBkccEKHTQOPaXdUxnZZElQTZY0MFUAuaEqe1E+Nyvgdz/aIyNi6Z9MzO5dv1H8n58/GELp3+w=="],
|
||||
@@ -1069,18 +750,8 @@
|
||||
|
||||
"openai": ["openai@6.10.0", "", { "peerDependencies": { "ws": "^8.18.0", "zod": "^3.25 || ^4.0" }, "optionalPeers": ["ws", "zod"], "bin": { "openai": "bin/cli" } }, "sha512-ITxOGo7rO3XRMiKA5l7tQ43iNNu+iXGFAcf2t+aWVzzqRaS0i7m1K2BhxNdaveB+5eENhO0VY1FkiZzhBk4v3A=="],
|
||||
|
||||
"p-finally": ["p-finally@1.0.0", "", {}, "sha512-LICb2p9CB7FS+0eR1oqWnHhp0FljGLZCWBE9aix0Uye9W8LTQPwMTYVGWQWIw9RdQiDg4+epXQODwIYJtSJaow=="],
|
||||
|
||||
"p-queue": ["p-queue@6.6.2", "", { "dependencies": { "eventemitter3": "^4.0.4", "p-timeout": "^3.2.0" } }, "sha512-RwFpb72c/BhQLEXIZ5K2e+AhgNVmIejGlTgiB9MzZ0e93GRvqZ7uSi0dvRF7/XIXDeNkra2fNHBxTyPDGySpjQ=="],
|
||||
|
||||
"p-retry": ["p-retry@4.6.2", "", { "dependencies": { "@types/retry": "0.12.0", "retry": "^0.13.1" } }, "sha512-312Id396EbJdvRONlngUx0NydfrIQ5lsYu0znKVUzVvArzEIt08V1qhtyESbGVd1FGX7UKtiFp5uwKZdM8wIuQ=="],
|
||||
|
||||
"p-timeout": ["p-timeout@3.2.0", "", { "dependencies": { "p-finally": "^1.0.0" } }, "sha512-rhIwUycgwwKcP9yTOOFK/AKsAopjjCakVqLHePO3CC6Mir1Z99xT+R63jZxAT5lFZLa2inS5h+ZS2GvR99/FBg=="],
|
||||
|
||||
"package-json-from-dist": ["package-json-from-dist@1.0.1", "", {}, "sha512-UEZIS3/by4OC8vL3P2dTXRETpebLI2NiI5vIrjaD/5UtrkFX/tNbwjTSRAGC/+7CAo2pIcBaRgWmcBBHcsaCIw=="],
|
||||
|
||||
"pako": ["pako@1.0.11", "", {}, "sha512-4hLB8Py4zZce5s4yd9XzopqwVv/yGNhV1Bl8NTmCq1763HeK2+EwVTv+leGeL13Dnh2wfbqowVPXCIO0z4taYw=="],
|
||||
|
||||
"parse5": ["parse5@5.1.1", "", {}, "sha512-ugq4DFI0Ptb+WWjAdOK16+u/nHfiIrcE+sh8kZMaM0WllQKLI9rOUq6c2b7cwPkXdzfQESqvoqK6ug7U/Yyzug=="],
|
||||
|
||||
"parse5-htmlparser2-tree-adapter": ["parse5-htmlparser2-tree-adapter@6.0.1", "", { "dependencies": { "parse5": "^6.0.1" } }, "sha512-qPuWvbLgvDGilKc5BoicRovlT4MtYT6JfJyBOMDsKoiT+GiuP5qyrPCnR9HcPECIJJmZh5jRndyNThnhhb/vlA=="],
|
||||
@@ -1099,10 +770,6 @@
|
||||
|
||||
"pathval": ["pathval@2.0.1", "", {}, "sha512-//nshmD55c46FuFw26xV/xFAaB5HF9Xdap7HJBBnrKdAd6/GxDBaNA1870O79+9ueg61cZLSVc+OaFlfmObYVQ=="],
|
||||
|
||||
"pdfjs-dist": ["pdfjs-dist@5.4.394", "", { "optionalDependencies": { "@napi-rs/canvas": "^0.1.81" } }, "sha512-9ariAYGqUJzx+V/1W4jHyiyCep6IZALmDzoaTLZ6VNu8q9LWi1/ukhzHgE2Xsx96AZi0mbZuK4/ttIbqSbLypg=="],
|
||||
|
||||
"pi-web-ui-example": ["pi-web-ui-example@workspace:packages/web-ui/example"],
|
||||
|
||||
"picocolors": ["picocolors@1.1.1", "", {}, "sha512-xceH2snhtb5M9liqDsmEw56le376mTZkEX/jEb/RxNFyegNul7eNslCXP9FDj/Lcu0X8KEyMceP2ntpaHrDEVA=="],
|
||||
|
||||
"picomatch": ["picomatch@4.0.3", "", {}, "sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q=="],
|
||||
@@ -1113,24 +780,14 @@
|
||||
|
||||
"postcss": ["postcss@8.5.6", "", { "dependencies": { "nanoid": "^3.3.11", "picocolors": "^1.1.1", "source-map-js": "^1.2.1" } }, "sha512-3Ybi1tAuwAP9s0r1UQ2J4n5Y0G05bJkpUIO0/bI9MhwmD70S5aTWbXGBwxHrelT+XM1k6dM0pk+SwNkpTRN7Pg=="],
|
||||
|
||||
"prebuild-install": ["prebuild-install@7.1.3", "", { "dependencies": { "detect-libc": "^2.0.0", "expand-template": "^2.0.3", "github-from-package": "0.0.0", "minimist": "^1.2.3", "mkdirp-classic": "^0.5.3", "napi-build-utils": "^2.0.0", "node-abi": "^3.3.0", "pump": "^3.0.0", "rc": "^1.2.7", "simple-get": "^4.0.0", "tar-fs": "^2.0.0", "tunnel-agent": "^0.6.0" }, "bin": { "prebuild-install": "bin.js" } }, "sha512-8Mf2cbV7x1cXPUILADGI3wuhfqWvtiLA1iclTDbFRZkgRQS0NqsPZphna9V+HyTEadheuPmjaJMsbzKQFOzLug=="],
|
||||
|
||||
"process-nextick-args": ["process-nextick-args@2.0.1", "", {}, "sha512-3ouUOpQhtgrbOa17J7+uxOTpITYWaGP7/AhoR3+A+/1e9skrzelGi/dXzEYyvbxubEF6Wn2ypscTKiKJFFn1ag=="],
|
||||
|
||||
"proxy-addr": ["proxy-addr@2.0.7", "", { "dependencies": { "forwarded": "0.2.0", "ipaddr.js": "1.9.1" } }, "sha512-llQsMLSUDUPT44jdrU/O37qlnifitDP+ZwrmmZcoSKyLKvtZxpyV0n2/bD/N4tBAAZ/gJEdZU7KMraoK1+XYAg=="],
|
||||
|
||||
"proxy-from-env": ["proxy-from-env@1.1.0", "", {}, "sha512-D+zkORCbA9f1tdWRK0RaCR3GPv50cMxcrz4X8k5LTSUD1Dkw47mKJEZQNunItRTkWwgtaUSo1RVFRIG9ZXiFYg=="],
|
||||
|
||||
"pump": ["pump@3.0.3", "", { "dependencies": { "end-of-stream": "^1.1.0", "once": "^1.3.1" } }, "sha512-todwxLMY7/heScKmntwQG8CXVkWUOdYxIvY2s0VWAAMh/nd8SoYiRaKjlr7+iCs984f2P8zvrfWcDDYVb73NfA=="],
|
||||
|
||||
"qs": ["qs@6.14.1", "", { "dependencies": { "side-channel": "^1.1.0" } }, "sha512-4EK3+xJl8Ts67nLYNwqw/dsFVnCf+qR7RgXSK9jEEm9unao3njwMDdmsdvoKBKHzxd7tCYz5e5M+SnMjdtXGQQ=="],
|
||||
|
||||
"range-parser": ["range-parser@1.2.1", "", {}, "sha512-Hrgsx+orqoygnmhFbKaHE6c296J+HTAQXoxEF6gNupROmmGJRoyzfG3ccAveqCBrwr/2yxQ5BVd/GTl5agOwSg=="],
|
||||
|
||||
"raw-body": ["raw-body@3.0.2", "", { "dependencies": { "bytes": "~3.1.2", "http-errors": "~2.0.1", "iconv-lite": "~0.7.0", "unpipe": "~1.0.0" } }, "sha512-K5zQjDllxWkf7Z5xJdV0/B0WTNqx6vxG70zJE4N0kBs4LovmEYWJzQGxC9bS9RAKu3bgM40lrd5zoLJ12MQ5BA=="],
|
||||
|
||||
"rc": ["rc@1.2.8", "", { "dependencies": { "deep-extend": "^0.6.0", "ini": "~1.3.0", "minimist": "^1.2.0", "strip-json-comments": "~2.0.1" }, "bin": { "rc": "./cli.js" } }, "sha512-y3bGgqKj3QBdxLbLkomlohkvsA8gdAiUQlSBJnBhfn+BPxg4bc62d8TcBW15wavDfgexCgccckhcZvywyQYPOw=="],
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"readable-stream": ["readable-stream@3.6.2", "", { "dependencies": { "inherits": "^2.0.3", "string_decoder": "^1.1.1", "util-deprecate": "^1.0.1" } }, "sha512-9u/sniCrY3D5WdsERHzHE4G2YCXqoG5FTHUiCC4SIbr6XcLZBY05ya9EKjYek9O5xOAwjGq+1JdGBAS7Q9ScoA=="],
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"require-directory": ["require-directory@2.1.1", "", {}, "sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q=="],
|
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@@ -1139,8 +796,6 @@
|
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|
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"restore-cursor": ["restore-cursor@5.1.0", "", { "dependencies": { "onetime": "^7.0.0", "signal-exit": "^4.1.0" } }, "sha512-oMA2dcrw6u0YfxJQXm342bFKX/E4sG9rbTzO9ptUcR/e8A33cHuvStiYOwH7fszkZlZ1z/ta9AAoPk2F4qIOHA=="],
|
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"retry": ["retry@0.13.1", "", {}, "sha512-XQBQ3I8W1Cge0Seh+6gjj03LbmRFWuoszgK9ooCpwYIrhhoO80pfq4cUkU5DkknwfOfFteRwlZ56PYOGYyFWdg=="],
|
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"rfdc": ["rfdc@1.4.1", "", {}, "sha512-q1b3N5QkRUWUl7iyylaaj3kOpIT0N2i9MqIEQXP73GVsN9cw3fdx8X63cEmWhJGi2PPCF23Ijp7ktmd39rawIA=="],
|
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"rimraf": ["rimraf@5.0.10", "", { "dependencies": { "glob": "^10.3.7" }, "bin": { "rimraf": "dist/esm/bin.mjs" } }, "sha512-l0OE8wL34P4nJH/H2ffoaniAokM2qSmrtXHmlpvYr5AVVX8msAyW0l8NVJFDxlSK4u3Uh/f41cQheDVdnYijwQ=="],
|
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@@ -1151,7 +806,7 @@
|
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|
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"rxjs": ["rxjs@7.8.2", "", { "dependencies": { "tslib": "^2.1.0" } }, "sha512-dhKf903U/PQZY6boNNtAGdWbG85WAbjT/1xYoZIC7FAY0yWapOBQVsVrDl58W86//e1VpMNBtRV4MaXfdMySFA=="],
|
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"safe-buffer": ["safe-buffer@5.1.2", "", {}, "sha512-Gd2UZBJDkXlY7GbJxfsE8/nvKkUEU1G38c1siN6QP6a9PT9MmHB8GnpscSmMJSoF8LOIrt8ud/wPtojys4G6+g=="],
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"safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
|
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|
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"safe-stable-stringify": ["safe-stable-stringify@2.5.0", "", {}, "sha512-b3rppTKm9T+PsVCBEOUR46GWI7fdOs00VKZ1+9c1EWDaDMvjQc6tUwuFyIprgGgTcWoVHSKrU8H31ZHA2e0RHA=="],
|
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|
||||
@@ -1163,8 +818,6 @@
|
||||
|
||||
"serve-static": ["serve-static@2.2.1", "", { "dependencies": { "encodeurl": "^2.0.0", "escape-html": "^1.0.3", "parseurl": "^1.3.3", "send": "^1.2.0" } }, "sha512-xRXBn0pPqQTVQiC8wyQrKs2MOlX24zQ0POGaj0kultvoOCstBQM5yvOhAVSUwOMjQtTvsPWoNCHfPGwaaQJhTw=="],
|
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|
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"setimmediate": ["setimmediate@1.0.5", "", {}, "sha512-MATJdZp8sLqDl/68LfQmbP8zKPLQNV6BIZoIgrscFDQ+RsvK/BxeDQOgyxKKoh0y/8h3BqVFnCqQ/gd+reiIXA=="],
|
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|
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"setprototypeof": ["setprototypeof@1.2.0", "", {}, "sha512-E5LDX7Wrp85Kil5bhZv46j8jOeboKq5JMmYM3gVGdGH8xFpPWXUMsNrlODCrkoxMEeNi/XZIwuRvY4XNwYMJpw=="],
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|
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"sharp": ["sharp@0.34.5", "", { "dependencies": { "@img/colour": "^1.0.0", "detect-libc": "^2.1.2", "semver": "^7.7.3" }, "optionalDependencies": { "@img/sharp-darwin-arm64": "0.34.5", "@img/sharp-darwin-x64": "0.34.5", "@img/sharp-libvips-darwin-arm64": "1.2.4", "@img/sharp-libvips-darwin-x64": "1.2.4", "@img/sharp-libvips-linux-arm": "1.2.4", "@img/sharp-libvips-linux-arm64": "1.2.4", "@img/sharp-libvips-linux-ppc64": "1.2.4", "@img/sharp-libvips-linux-riscv64": "1.2.4", "@img/sharp-libvips-linux-s390x": "1.2.4", "@img/sharp-libvips-linux-x64": "1.2.4", "@img/sharp-libvips-linuxmusl-arm64": "1.2.4", "@img/sharp-libvips-linuxmusl-x64": "1.2.4", "@img/sharp-linux-arm": "0.34.5", "@img/sharp-linux-arm64": "0.34.5", "@img/sharp-linux-ppc64": "0.34.5", "@img/sharp-linux-riscv64": "0.34.5", "@img/sharp-linux-s390x": "0.34.5", "@img/sharp-linux-x64": "0.34.5", "@img/sharp-linuxmusl-arm64": "0.34.5", "@img/sharp-linuxmusl-x64": "0.34.5", "@img/sharp-wasm32": "0.34.5", "@img/sharp-win32-arm64": "0.34.5", "@img/sharp-win32-ia32": "0.34.5", "@img/sharp-win32-x64": "0.34.5" } }, "sha512-Ou9I5Ft9WNcCbXrU9cMgPBcCK8LiwLqcbywW3t4oDV37n1pzpuNLsYiAV8eODnjbtQlSDwZ2cUEeQz4E54Hltg=="],
|
||||
@@ -1187,10 +840,6 @@
|
||||
|
||||
"signal-exit": ["signal-exit@4.1.0", "", {}, "sha512-bzyZ1e88w9O1iNJbKnOlvYTrWPDl46O1bG0D3XInv+9tkPrxrN8jUUTiFlDkkmKWgn1M6CfIA13SuGqOa9Korw=="],
|
||||
|
||||
"simple-concat": ["simple-concat@1.0.1", "", {}, "sha512-cSFtAPtRhljv69IK0hTVZQ+OfE9nePi/rtJmw5UjHeVyVroEqJXP1sFztKUy1qU+xvz3u/sfYJLa947b7nAN2Q=="],
|
||||
|
||||
"simple-get": ["simple-get@4.0.1", "", { "dependencies": { "decompress-response": "^6.0.0", "once": "^1.3.1", "simple-concat": "^1.0.0" } }, "sha512-brv7p5WgH0jmQJr1ZDDfKDOSeWWg+OVypG99A/5vYGPqJ6pxiaHLy8nxtFjBA7oMa01ebA9gfh1uMCFqOuXxvA=="],
|
||||
|
||||
"slice-ansi": ["slice-ansi@7.1.2", "", { "dependencies": { "ansi-styles": "^6.2.1", "is-fullwidth-code-point": "^5.0.0" } }, "sha512-iOBWFgUX7caIZiuutICxVgX1SdxwAVFFKwt1EvMYYec/NWO5meOJ6K5uQxhrYBdQJne4KxiqZc+KptFOWFSI9w=="],
|
||||
|
||||
"smol-toml": ["smol-toml@1.6.0", "", {}, "sha512-4zemZi0HvTnYwLfrpk/CF9LOd9Lt87kAt50GnqhMpyF9U3poDAP2+iukq2bZsO/ufegbYehBkqINbsWxj4l4cw=="],
|
||||
@@ -1219,26 +868,12 @@
|
||||
|
||||
"strip-ansi-cjs": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
|
||||
|
||||
"strip-json-comments": ["strip-json-comments@2.0.1", "", {}, "sha512-4gB8na07fecVVkOI6Rs4e7T6NOTki5EmL7TUduTs6bu3EdnSycntVJ4re8kgZA+wx9IueI2Y11bfbgwtzuE0KQ=="],
|
||||
|
||||
"strip-literal": ["strip-literal@3.1.0", "", { "dependencies": { "js-tokens": "^9.0.1" } }, "sha512-8r3mkIM/2+PpjHoOtiAW8Rg3jJLHaV7xPwG+YRGrv6FP0wwk/toTpATxWYOW0BKdWwl82VT2tFYi5DlROa0Mxg=="],
|
||||
|
||||
"strtok3": ["strtok3@10.3.4", "", { "dependencies": { "@tokenizer/token": "^0.3.0" } }, "sha512-KIy5nylvC5le1OdaaoCJ07L+8iQzJHGH6pWDuzS+d07Cu7n1MZ2x26P8ZKIWfbK02+XIL8Mp4RkWeqdUCrDMfg=="],
|
||||
|
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"supports-color": ["supports-color@8.1.1", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-MpUEN2OodtUzxvKQl72cUF7RQ5EiHsGvSsVG0ia9c5RbWGL2CI4C7EpPS8UTBIplnlzZiNuV56w+FuNxy3ty2Q=="],
|
||||
|
||||
"tailwind-merge": ["tailwind-merge@3.4.0", "", {}, "sha512-uSaO4gnW+b3Y2aWoWfFpX62vn2sR3skfhbjsEnaBI81WD1wBLlHZe5sWf0AqjksNdYTbGBEd0UasQMT3SNV15g=="],
|
||||
|
||||
"tailwind-variants": ["tailwind-variants@3.2.2", "", { "peerDependencies": { "tailwind-merge": ">=3.0.0", "tailwindcss": "*" }, "optionalPeers": ["tailwind-merge"] }, "sha512-Mi4kHeMTLvKlM98XPnK+7HoBPmf4gygdFmqQPaDivc3DpYS6aIY6KiG/PgThrGvii5YZJqRsPz0aPyhoFzmZgg=="],
|
||||
|
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"tailwindcss": ["tailwindcss@4.1.18", "", {}, "sha512-4+Z+0yiYyEtUVCScyfHCxOYP06L5Ne+JiHhY2IjR2KWMIWhJOYZKLSGZaP5HkZ8+bY0cxfzwDE5uOmzFXyIwxw=="],
|
||||
|
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"tapable": ["tapable@2.3.0", "", {}, "sha512-g9ljZiwki/LfxmQADO3dEY1CbpmXT5Hm2fJ+QaGKwSXUylMybePR7/67YW7jOrrvjEgL1Fmz5kzyAjWVWLlucg=="],
|
||||
|
||||
"tar-fs": ["tar-fs@2.1.4", "", { "dependencies": { "chownr": "^1.1.1", "mkdirp-classic": "^0.5.2", "pump": "^3.0.0", "tar-stream": "^2.1.4" } }, "sha512-mDAjwmZdh7LTT6pNleZ05Yt65HC3E+NiQzl672vQG38jIrehtJk/J3mNwIg+vShQPcLF/LV7CMnDW6vjj6sfYQ=="],
|
||||
|
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"tar-stream": ["tar-stream@2.2.0", "", { "dependencies": { "bl": "^4.0.3", "end-of-stream": "^1.4.1", "fs-constants": "^1.0.0", "inherits": "^2.0.3", "readable-stream": "^3.1.1" } }, "sha512-ujeqbceABgwMZxEJnk2HDY2DlnUZ+9oEcb1KzTVfYHio0UE6dG71n60d8D2I4qNvleWrrXpmjpt7vZeF1LnMZQ=="],
|
||||
|
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"text-hex": ["text-hex@1.0.0", "", {}, "sha512-uuVGNWzgJ4yhRaNSiubPY7OjISw4sw4E5Uv0wbjp+OzcbmVU/rsT8ujgcXJhn9ypzsgr5vlzpPqP+MBBKcGvbg=="],
|
||||
|
||||
"thenify": ["thenify@3.3.1", "", { "dependencies": { "any-promise": "^1.0.0" } }, "sha512-RVZSIV5IG10Hk3enotrhvz0T9em6cyHBLkH/YAZuKqd8hRkKhSfCGIcP2KUY0EPxndzANBmNllzWPwak+bheSw=="],
|
||||
@@ -1273,12 +908,8 @@
|
||||
|
||||
"tslib": ["tslib@2.8.1", "", {}, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
|
||||
|
||||
"tunnel-agent": ["tunnel-agent@0.6.0", "", { "dependencies": { "safe-buffer": "^5.0.1" } }, "sha512-McnNiV1l8RYeY8tBgEpuodCC1mLUdbSN+CYBL7kJsJNInOP8UjDDEwdk6Mw60vdLLrr5NHKZhMAOSrR2NZuQ+w=="],
|
||||
|
||||
"type-is": ["type-is@2.0.1", "", { "dependencies": { "content-type": "^1.0.5", "media-typer": "^1.1.0", "mime-types": "^3.0.0" } }, "sha512-OZs6gsjF4vMp32qrCbiVSkrFmXtG/AZhY3t0iAMrMBiAZyV9oALtXO8hsrHbMXF9x6L3grlFuwW2oAz7cav+Gw=="],
|
||||
|
||||
"uhtml": ["uhtml@5.0.9", "", { "dependencies": { "@webreflection/alien-signals": "^0.3.2" } }, "sha512-qPyu3vGilaLe6zrjOCD/xezWEHLwdevxmbY3hzyhT25KBDF4F7YYW3YZcL3kylD/6dMoVISHjn8ggV3+9FY+5g=="],
|
||||
|
||||
"uint8array-extras": ["uint8array-extras@1.5.0", "", {}, "sha512-rvKSBiC5zqCCiDZ9kAOszZcDvdAHwwIKJG33Ykj43OKcWsnmcBRL09YTU4nOeHZ8Y2a7l1MgTd08SBe9A8Qj6A=="],
|
||||
|
||||
"undici-types": ["undici-types@6.21.0", "", {}, "sha512-iwDZqg0QAGrg9Rav5H4n0M64c3mkR59cJ6wQp+7C4nI0gsmExaedaYLNO44eT4AtBBwjbTiGPMlt2Md0T9H9JQ=="],
|
||||
@@ -1297,8 +928,6 @@
|
||||
|
||||
"web-streams-polyfill": ["web-streams-polyfill@3.3.3", "", {}, "sha512-d2JWLCivmZYTSIoge9MsgFCZrt571BikcWGYkjC1khllbTeDlGqZ2D8vD8E/lJa8WGWbb7Plm8/XJYV7IJHZZw=="],
|
||||
|
||||
"whatwg-fetch": ["whatwg-fetch@3.6.20", "", {}, "sha512-EqhiFU6daOA8kpjOWTL0olhVOF3i7OrFzSYiGsEMB8GcXS+RrzauAERX65xMeNWVqxA6HXH2m69Z9LaKKdisfg=="],
|
||||
|
||||
"which": ["which@2.0.2", "", { "dependencies": { "isexe": "^2.0.0" }, "bin": { "node-which": "./bin/node-which" } }, "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA=="],
|
||||
|
||||
"why-is-node-running": ["why-is-node-running@2.3.0", "", { "dependencies": { "siginfo": "^2.0.0", "stackback": "0.0.2" }, "bin": { "why-is-node-running": "cli.js" } }, "sha512-hUrmaWBdVDcxvYqnyh09zunKzROWjbZTiNy8dBEjkS7ehEDQibXJ7XvlmtbwuTclUiIyN+CyXQD4Vmko8fNm8w=="],
|
||||
@@ -1317,8 +946,6 @@
|
||||
|
||||
"ws": ["ws@8.19.0", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-blAT2mjOEIi0ZzruJfIhb3nps74PRWTCz1IjglWEEpQl5XS/UNama6u2/rjFkDDouqr4L67ry+1aGIALViWjDg=="],
|
||||
|
||||
"xlsx": ["xlsx@https://cdn.sheetjs.com/xlsx-0.20.3/xlsx-0.20.3.tgz", { "bin": { "xlsx": "./bin/xlsx.njs" } }],
|
||||
|
||||
"y18n": ["y18n@5.0.8", "", {}, "sha512-0pfFzegeDWJHJIAmTLRP2DwHjdF5s7jo9tuztdQxAhINCdvS+3nGINqPd00AphqJR/0LhANUS6/+7SCb98YOfA=="],
|
||||
|
||||
"yaml": ["yaml@2.8.2", "", { "bin": { "yaml": "bin.mjs" } }, "sha512-mplynKqc1C2hTVYxd0PU2xQAc22TI1vShAYGksCCfxbn/dFwnHTNi1bvYsBTkhdUNtGIf5xNOg938rrSSYvS9A=="],
|
||||
@@ -1331,52 +958,18 @@
|
||||
|
||||
"zod-to-json-schema": ["zod-to-json-schema@3.25.1", "", { "peerDependencies": { "zod": "^3.25 || ^4" } }, "sha512-pM/SU9d3YAggzi6MtR4h7ruuQlqKtad8e9S0fmxcMi+ueAK5Korys/aWcV9LIIHTVbj01NdzxcnXSN+O74ZIVA=="],
|
||||
|
||||
"@anthropic-ai/sandbox-runtime/commander": ["commander@12.1.0", "", {}, "sha512-Vw8qHK3bZM9y/P10u3Vib8o/DdkvA2OtPtZvD871QKjy74Wj1WSKFILMPRPSdUSx5RFK1arlJzEtA4PkFgnbuA=="],
|
||||
|
||||
"@anthropic-ai/sandbox-runtime/zod": ["zod@3.25.76", "", {}, "sha512-gzUt/qt81nXsFGKIFcC3YnfEAx5NkunCfnDlvuBSSFS02bcXu4Lmea0AFIUwbLWxWPx3d9p8S5QoaujKcNQxcQ=="],
|
||||
|
||||
"@isaacs/cliui/string-width": ["string-width@5.1.2", "", { "dependencies": { "eastasianwidth": "^0.2.0", "emoji-regex": "^9.2.2", "strip-ansi": "^7.0.1" } }, "sha512-HnLOCR3vjcY8beoNLtcjZ5/nxn2afmME6lhrDrebokqMap+XbeW8n9TXpPDOqdGK5qcI3oT0GKTW6wC7EMiVqA=="],
|
||||
|
||||
"@isaacs/cliui/wrap-ansi": ["wrap-ansi@8.1.0", "", { "dependencies": { "ansi-styles": "^6.1.0", "string-width": "^5.0.1", "strip-ansi": "^7.0.1" } }, "sha512-si7QWI6zUMq56bESFvagtmzMdGOtoxfR+Sez11Mobfc7tm+VkUckk9bW2UeffTGVUbOksxmSw0AA2gs8g71NCQ=="],
|
||||
|
||||
"@lmstudio/sdk/chalk": ["chalk@4.1.2", "", { "dependencies": { "ansi-styles": "^4.1.0", "supports-color": "^7.1.0" } }, "sha512-oKnbhFyRIXpUuez8iBMmyEa4nbj4IOQyuhc/wy9kY7/WVPcwIO9VA668Pu8RkO7+0G76SLROeyw9CpQ061i4mA=="],
|
||||
|
||||
"@lmstudio/sdk/zod": ["zod@3.25.76", "", {}, "sha512-gzUt/qt81nXsFGKIFcC3YnfEAx5NkunCfnDlvuBSSFS02bcXu4Lmea0AFIUwbLWxWPx3d9p8S5QoaujKcNQxcQ=="],
|
||||
|
||||
"@mariozechner/mini-lit/marked": ["marked@16.4.2", "", { "bin": { "marked": "bin/marked.js" } }, "sha512-TI3V8YYWvkVf3KJe1dRkpnjs68JUPyEa5vjKrp1XEEJUAOaQc+Qj+L1qWbPd0SJuAdQkFU0h73sXXqwDYxsiDA=="],
|
||||
|
||||
"@mistralai/mistralai/zod": ["zod@3.25.76", "", {}, "sha512-gzUt/qt81nXsFGKIFcC3YnfEAx5NkunCfnDlvuBSSFS02bcXu4Lmea0AFIUwbLWxWPx3d9p8S5QoaujKcNQxcQ=="],
|
||||
|
||||
"@oh-my-pi/pi-agent-core/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@oh-my-pi/pi-ai/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@oh-my-pi/pi-coding-agent/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@oh-my-pi/pi-git-tool/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@oh-my-pi/pi-mom/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@parcel/watcher/detect-libc": ["detect-libc@1.0.3", "", { "bin": { "detect-libc": "./bin/detect-libc.js" } }, "sha512-pGjwhsmsp4kL2RTz08wcOlGN83otlqHeD/Z5T8GXZB+/YcpQ/dgo+lbU8ZsGxV0HIvqqxo9l7mqYwyYMD9bKDg=="],
|
||||
|
||||
"@slack/logger/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@slack/socket-mode/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@slack/web-api/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@tailwindcss/oxide-wasm32-wasi/@emnapi/core": ["@emnapi/core@1.8.1", "", { "dependencies": { "@emnapi/wasi-threads": "1.1.0", "tslib": "^2.4.0" }, "bundled": true }, "sha512-AvT9QFpxK0Zd8J0jopedNm+w/2fIzvtPKPjqyw9jwvBaReTTqPBk9Hixaz7KbjimP+QNz605/XnjFcDAL2pqBg=="],
|
||||
|
||||
"@tailwindcss/oxide-wasm32-wasi/@emnapi/runtime": ["@emnapi/runtime@1.8.1", "", { "dependencies": { "tslib": "^2.4.0" }, "bundled": true }, "sha512-mehfKSMWjjNol8659Z8KxEMrdSJDDot5SXMq00dM8BN4o+CLNXQ0xH2V7EchNHV4RmbZLmmPdEaXZc5H2FXmDg=="],
|
||||
|
||||
"@tailwindcss/oxide-wasm32-wasi/@emnapi/wasi-threads": ["@emnapi/wasi-threads@1.1.0", "", { "dependencies": { "tslib": "^2.4.0" }, "bundled": true }, "sha512-WI0DdZ8xFSbgMjR1sFsKABJ/C5OnRrjT06JXbZKexJGrDuPTzZdDYfFlsgcCXCyf+suG5QU2e/y1Wo2V/OapLQ=="],
|
||||
|
||||
"@tailwindcss/oxide-wasm32-wasi/@napi-rs/wasm-runtime": ["@napi-rs/wasm-runtime@1.1.1", "", { "dependencies": { "@emnapi/core": "^1.7.1", "@emnapi/runtime": "^1.7.1", "@tybys/wasm-util": "^0.10.1" }, "bundled": true }, "sha512-p64ah1M1ld8xjWv3qbvFwHiFVWrq1yFvV4f7w+mzaqiR4IlSgkqhcRdHwsGgomwzBH51sRY4NEowLxnaBjcW/A=="],
|
||||
|
||||
"@tailwindcss/oxide-wasm32-wasi/@tybys/wasm-util": ["@tybys/wasm-util@0.10.1", "", { "dependencies": { "tslib": "^2.4.0" }, "bundled": true }, "sha512-9tTaPJLSiejZKx+Bmog4uSubteqTvFrVrURwkmHixBo0G4seD0zUxp98E1DzUBJxLQ3NPwXrGKDiVjwx/DpPsg=="],
|
||||
|
||||
"@tailwindcss/oxide-wasm32-wasi/tslib": ["tslib@2.8.1", "", { "bundled": true }, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
|
||||
|
||||
"@types/ndjson/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
|
||||
"@types/through/@types/node": ["@types/node@24.10.4", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-vnDVpYPMzs4wunl27jHrfmwojOGKya0xyM3sH+UE5iv5uPS6vX7UIoh6m+vQc5LGBq52HBKPIn/zcSZVzeDEZg=="],
|
||||
@@ -1403,22 +996,8 @@
|
||||
|
||||
"concurrently/chalk": ["chalk@4.1.2", "", { "dependencies": { "ansi-styles": "^4.1.0", "supports-color": "^7.1.0" } }, "sha512-oKnbhFyRIXpUuez8iBMmyEa4nbj4IOQyuhc/wy9kY7/WVPcwIO9VA668Pu8RkO7+0G76SLROeyw9CpQ061i4mA=="],
|
||||
|
||||
"ecdsa-sig-formatter/safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
|
||||
|
||||
"form-data/mime-types": ["mime-types@2.1.35", "", { "dependencies": { "mime-db": "1.52.0" } }, "sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw=="],
|
||||
|
||||
"jszip/readable-stream": ["readable-stream@2.3.8", "", { "dependencies": { "core-util-is": "~1.0.0", "inherits": "~2.0.3", "isarray": "~1.0.0", "process-nextick-args": "~2.0.0", "safe-buffer": "~5.1.1", "string_decoder": "~1.1.1", "util-deprecate": "~1.0.1" } }, "sha512-8p0AUk4XODgIewSi0l8Epjs+EVnWiK7NoDIEGU0HhE7+ZyY8D1IMY7odu5lRrFXGg71L15KG8QrPmum45RTtdA=="],
|
||||
|
||||
"jwa/safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
|
||||
|
||||
"jws/safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
|
||||
|
||||
"katex/commander": ["commander@8.3.0", "", {}, "sha512-OkTL9umf+He2DZkUq8f8J9of7yL6RJKI24dVITBmNfZBmri9zYZQrKkuXiKhyfPSu8tUhnVBB1iKXevvnlR4Ww=="],
|
||||
|
||||
"micromatch/picomatch": ["picomatch@2.3.1", "", {}, "sha512-JU3teHTNjmE2VCGFzuY8EXzCDVwEqB2a8fsIvwaStHhAWJEeVd1o1QD80CU6+ZdEXXSLbSsuLwJjkCBWqRQUVA=="],
|
||||
|
||||
"p-queue/eventemitter3": ["eventemitter3@4.0.7", "", {}, "sha512-8guHBZCwKnFhYdHr2ysuRWErTwhoN2X8XELRlrRwpmfeY2jjuUN4taQMsULKUVo1K4DvZl+0pgfyoysHxvmvEw=="],
|
||||
|
||||
"parse5-htmlparser2-tree-adapter/parse5": ["parse5@6.0.1", "", {}, "sha512-Ofn/CTFzRGTTxwpNEs9PP93gXShHcTq255nzRYSKe8AkVpZY7e1fpmTfOyoIvjP5HG7Z2ZM7VS9PPhQGW2pOpw=="],
|
||||
|
||||
"postcss/nanoid": ["nanoid@3.3.11", "", { "bin": { "nanoid": "bin/nanoid.cjs" } }, "sha512-N8SpfPUnUp1bK+PMYW8qSWdl9U+wwNWI4QKxOYDy9JAro3WMX7p2OeVRF9v+347pnakNevPmiHhNmZ2HbFA76w=="],
|
||||
@@ -1433,12 +1012,8 @@
|
||||
|
||||
"string-width-cjs/strip-ansi": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
|
||||
|
||||
"string_decoder/safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
|
||||
|
||||
"strip-ansi-cjs/ansi-regex": ["ansi-regex@5.0.1", "", {}, "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ=="],
|
||||
|
||||
"tunnel-agent/safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
|
||||
|
||||
"wrap-ansi/ansi-styles": ["ansi-styles@6.2.3", "", {}, "sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg=="],
|
||||
|
||||
"wrap-ansi/string-width": ["string-width@7.2.0", "", { "dependencies": { "emoji-regex": "^10.3.0", "get-east-asian-width": "^1.0.0", "strip-ansi": "^7.1.0" } }, "sha512-tsaTIkKW9b4N+AEj+SVA+WhJzV7/zMhcSu78mLKWSk7cXMOSHsBKFWUs0fWwq8QyK3MgJBQRX6Gbi4kYbdvGkQ=="],
|
||||
@@ -1449,24 +1024,12 @@
|
||||
|
||||
"@isaacs/cliui/wrap-ansi/ansi-styles": ["ansi-styles@6.2.3", "", {}, "sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg=="],
|
||||
|
||||
"@lmstudio/sdk/chalk/supports-color": ["supports-color@7.2.0", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-qpCAvRl9stuOHveKsn7HncJRvv501qIacKzQlO/+Lwxc9+0q2wLyv4Dfvt80/DPn2pqOBsJdDiogXGR9+OvwRw=="],
|
||||
|
||||
"@oh-my-pi/pi-agent-core/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@oh-my-pi/pi-ai/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@oh-my-pi/pi-coding-agent/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@oh-my-pi/pi-git-tool/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@oh-my-pi/pi-mom/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@slack/logger/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@slack/socket-mode/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@slack/web-api/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@types/ndjson/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
|
||||
"@types/through/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
|
||||
@@ -1487,10 +1050,6 @@
|
||||
|
||||
"concurrently/chalk/supports-color": ["supports-color@7.2.0", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-qpCAvRl9stuOHveKsn7HncJRvv501qIacKzQlO/+Lwxc9+0q2wLyv4Dfvt80/DPn2pqOBsJdDiogXGR9+OvwRw=="],
|
||||
|
||||
"form-data/mime-types/mime-db": ["mime-db@1.52.0", "", {}, "sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg=="],
|
||||
|
||||
"jszip/readable-stream/string_decoder": ["string_decoder@1.1.1", "", { "dependencies": { "safe-buffer": "~5.1.0" } }, "sha512-n/ShnvDi6FHbbVfviro+WojiFzv+s8MPMHBczVePfUpDJLwoLT0ht1l4YwBCbi8pJAveEEdnkHyPyTP/mzRfwg=="],
|
||||
|
||||
"rimraf/glob/jackspeak": ["jackspeak@3.4.3", "", { "dependencies": { "@isaacs/cliui": "^8.0.2" }, "optionalDependencies": { "@pkgjs/parseargs": "^0.11.0" } }, "sha512-OGlZQpz2yfahA/Rd1Y8Cd9SIEsqvXkLVoSw/cgwhnhFMDbsQFeZYoJJ7bIZBS9BcamUW96asq/npPWugM+RQBw=="],
|
||||
|
||||
"rimraf/glob/minimatch": ["minimatch@9.0.5", "", { "dependencies": { "brace-expansion": "^2.0.1" } }, "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow=="],
|
||||
|
||||
@@ -31,14 +31,17 @@ Upstream uses different package scopes. Replace them consistently.
|
||||
- Replace old scopes with the local scope used here.
|
||||
- Examples (adjust to match the actual packages you are porting):
|
||||
- `@mariozechner/pi-coding-agent` -> `@oh-my-pi/pi-coding-agent`
|
||||
- `@mariozechner/pi-ai` -> `@oh-my-pi/pi-ai`
|
||||
- `@badlogic/pi-tui` -> `@oh-my-pi/pi-tui`
|
||||
- `@mariozechner/pi-agent-core` -> `@oh-my-pi/pi-agent-core`
|
||||
- `@mariozechner/tui` -> `@oh-my-pi/pi-tui`
|
||||
- But! Do not switch the ones we use from upstream:
|
||||
- `@mariozechner/pi-ai` should stay as `@mariozechner/pi-ai`
|
||||
|
||||
## 4) Use Bun APIs where they improve on Node
|
||||
|
||||
We run on Bun. Replace Node APIs only when Bun provides a better alternative.
|
||||
|
||||
**DO replace:**
|
||||
|
||||
- Process spawning: `child_process.spawn` → `Bun.spawn` / `Bun.spawnSync`
|
||||
- File I/O: `fs.readFileSync` → `Bun.file().text()` / `Bun.write()`
|
||||
- HTTP clients: `node-fetch`, `axios` → native `fetch`
|
||||
@@ -47,6 +50,7 @@ We run on Bun. Replace Node APIs only when Bun provides a better alternative.
|
||||
- Env loading: `dotenv` → Bun loads `.env` automatically
|
||||
|
||||
**DO NOT replace (these work fine in Bun):**
|
||||
|
||||
- `os.homedir()` — do NOT replace with `process.env.HOME`, `Bun.env.HOME`, or literal `"~"`
|
||||
- `os.tmpdir()` — do NOT replace with `Bun.env.TMPDIR || "/tmp"` or hardcoded paths
|
||||
- `fs.mkdtempSync()` — do NOT replace with manual path construction
|
||||
@@ -55,6 +59,7 @@ We run on Bun. Replace Node APIs only when Bun provides a better alternative.
|
||||
**Import style:** Use `node:` prefix for Node builtins (`import { homedir } from "node:os"`).
|
||||
|
||||
**Wrong:**
|
||||
|
||||
```typescript
|
||||
// BROKEN: env vars may be undefined, "~" is not expanded
|
||||
const home = process.env.HOME || Bun.env.HOME || "~";
|
||||
@@ -62,6 +67,7 @@ const tmp = Bun.env.TMPDIR || "/tmp";
|
||||
```
|
||||
|
||||
**Correct:**
|
||||
|
||||
```typescript
|
||||
import { homedir, tmpdir } from "node:os";
|
||||
import { mkdtempSync } from "node:fs";
|
||||
@@ -163,6 +169,7 @@ git diff HEAD upstream/main -- path/to/file.ts
|
||||
```
|
||||
|
||||
If the diff shows the file was **reworked** (not just patched):
|
||||
|
||||
- New abstractions, renamed concepts, merged modules, changed data flow
|
||||
|
||||
Then you must **read the new implementation thoroughly** before porting. Blind merging of reworked code loses functionality because:
|
||||
|
||||
+4
-7
@@ -3,16 +3,13 @@
|
||||
"private": true,
|
||||
"type": "module",
|
||||
"workspaces": [
|
||||
"packages/*",
|
||||
"packages/web-ui/example"
|
||||
"packages/*"
|
||||
],
|
||||
"scripts": {
|
||||
"install:dev": "bun install && bun --cwd=packages/coding-agent link && bun --cwd=packages/ai link && bun --cwd=packages/mom link",
|
||||
"agent": "bun --cwd=packages/coding-agent src/cli.ts",
|
||||
"build": "bun --cwd=packages/web-ui run build:css",
|
||||
"dev": "bun --cwd=packages/web-ui run dev",
|
||||
"check": "biome check --write . && bun --cwd=packages/coding-agent run check && bun --cwd=packages/web-ui run check",
|
||||
"fix": "biome check --write --unsafe . && bun --cwd=packages/web-ui run fix",
|
||||
"dev": "bun --cwd=packages/coding-agent src/cli.ts",
|
||||
"check": "biome check --write . && bun --cwd=packages/coding-agent run check",
|
||||
"fix": "biome check --write --unsafe .",
|
||||
"version:patch": "npm version patch -ws --no-git-tag-version && bun scripts/sync-versions.js && rm -rf node_modules packages/*/node_modules bun.lock && bun install",
|
||||
"version:minor": "npm version minor -ws --no-git-tag-version && bun scripts/sync-versions.js && rm -rf node_modules packages/*/node_modules bun.lock && bun install",
|
||||
"version:major": "npm version major -ws --no-git-tag-version && bun scripts/sync-versions.js && rm -rf node_modules packages/*/node_modules bun.lock && bun install",
|
||||
|
||||
@@ -2,9 +2,19 @@
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
### Changed
|
||||
|
||||
- Switched from local `@oh-my-pi/pi-ai` to upstream `@mariozechner/pi-ai` package
|
||||
|
||||
### Added
|
||||
|
||||
- Added `sessionId` option for provider caching (e.g., OpenAI Codex session-based prompt caching)
|
||||
- Added `sessionId` getter/setter on Agent class for runtime session switching
|
||||
|
||||
## [3.20.1] - 2026-01-06
|
||||
|
||||
## [3.20.0] - 2026-01-06
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
- Replaced `queueMessage`/`queueMode` with steering + follow-up queues: use `steer`, `setSteeringMode`, and `getSteeringMode` for mid-run interruptions, and `followUp`, `setFollowUpMode`, and `getFollowUpMode` for post-turn messages
|
||||
@@ -38,6 +48,7 @@
|
||||
## [3.5.1337] - 2026-01-03
|
||||
|
||||
## [3.4.1337] - 2026-01-03
|
||||
|
||||
### Added
|
||||
|
||||
- Added `popMessage()` method to Agent class for removing and retrieving the last message
|
||||
@@ -64,6 +75,7 @@
|
||||
## [1.500.0] - 2026-01-03
|
||||
|
||||
## [1.341.0] - 2026-01-03
|
||||
|
||||
### Added
|
||||
|
||||
- Added `interruptMode` option to control when queued messages interrupt tool execution.
|
||||
@@ -103,7 +115,7 @@ Initial release under @oh-my-pi scope. See previous releases at [badlogic/pi-mon
|
||||
|
||||
- **`UserMessageWithAttachments` and `Attachment` types removed**: Attachment handling is now the responsibility of the `convertToLlm` function.
|
||||
|
||||
- **Agent loop moved from `@oh-my-pi/pi-ai`**: The `agentLoop`, `agentLoopContinue`, and related types have moved to this package. Import from `@oh-my-pi/pi-agent` instead.
|
||||
- **Agent loop moved from `@mariozechner/pi-ai`**: The `agentLoop`, `agentLoopContinue`, and related types have moved to this package. Import from `@oh-my-pi/pi-agent` instead.
|
||||
|
||||
### Added
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# @oh-my-pi/pi-agent
|
||||
|
||||
Stateful agent with tool execution and event streaming. Built on `@oh-my-pi/pi-ai`.
|
||||
Stateful agent with tool execution and event streaming. Built on `@mariozechner/pi-ai`.
|
||||
|
||||
## Installation
|
||||
|
||||
@@ -12,7 +12,7 @@ npm install @oh-my-pi/pi-agent
|
||||
|
||||
```typescript
|
||||
import { Agent } from "@oh-my-pi/pi-agent";
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
|
||||
const agent = new Agent({
|
||||
initialState: {
|
||||
|
||||
@@ -13,7 +13,7 @@
|
||||
"test": "vitest --run"
|
||||
},
|
||||
"dependencies": {
|
||||
"@oh-my-pi/pi-ai": "workspace:*",
|
||||
"@mariozechner/pi-ai": "^0.37.4",
|
||||
"@oh-my-pi/pi-tui": "workspace:*"
|
||||
},
|
||||
"keywords": [
|
||||
|
||||
@@ -10,7 +10,7 @@ import {
|
||||
streamSimple,
|
||||
type ToolResultMessage,
|
||||
validateToolArguments,
|
||||
} from "@oh-my-pi/pi-ai";
|
||||
} from "@mariozechner/pi-ai";
|
||||
import type {
|
||||
AgentContext,
|
||||
AgentEvent,
|
||||
|
||||
@@ -8,10 +8,9 @@ import {
|
||||
type ImageContent,
|
||||
type Message,
|
||||
type Model,
|
||||
type ReasoningEffort,
|
||||
streamSimple,
|
||||
type TextContent,
|
||||
} from "@oh-my-pi/pi-ai";
|
||||
} from "@mariozechner/pi-ai";
|
||||
import { agentLoop, agentLoopContinue } from "./agent-loop";
|
||||
import type {
|
||||
AgentContext,
|
||||
@@ -69,6 +68,12 @@ export interface AgentOptions {
|
||||
*/
|
||||
streamFn?: StreamFn;
|
||||
|
||||
/**
|
||||
* Optional session identifier forwarded to LLM providers.
|
||||
* Used by providers that support session-based caching (e.g., OpenAI Codex).
|
||||
*/
|
||||
sessionId?: string;
|
||||
|
||||
/**
|
||||
* Resolves an API key dynamically for each LLM call.
|
||||
* Useful for expiring tokens (e.g., GitHub Copilot OAuth).
|
||||
@@ -105,6 +110,7 @@ export class Agent {
|
||||
private followUpMode: "all" | "one-at-a-time";
|
||||
private interruptMode: "immediate" | "wait";
|
||||
public streamFn: StreamFn;
|
||||
private _sessionId?: string;
|
||||
public getApiKey?: (provider: string) => Promise<string | undefined> | string | undefined;
|
||||
private getToolContext?: () => AgentToolContext | undefined;
|
||||
private runningPrompt?: Promise<void>;
|
||||
@@ -118,10 +124,26 @@ export class Agent {
|
||||
this.followUpMode = opts.followUpMode || "one-at-a-time";
|
||||
this.interruptMode = opts.interruptMode || "immediate";
|
||||
this.streamFn = opts.streamFn || streamSimple;
|
||||
this._sessionId = opts.sessionId;
|
||||
this.getApiKey = opts.getApiKey;
|
||||
this.getToolContext = opts.getToolContext;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the current session ID used for provider caching.
|
||||
*/
|
||||
get sessionId(): string | undefined {
|
||||
return this._sessionId;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the session ID for provider caching.
|
||||
* Call this when switching sessions (new session, branch, resume).
|
||||
*/
|
||||
set sessionId(value: string | undefined) {
|
||||
this._sessionId = value;
|
||||
}
|
||||
|
||||
get state(): AgentState {
|
||||
return this._state;
|
||||
}
|
||||
@@ -314,12 +336,7 @@ export class Agent {
|
||||
this._state.streamMessage = null;
|
||||
this._state.error = undefined;
|
||||
|
||||
const reasoning: ReasoningEffort | undefined =
|
||||
this._state.thinkingLevel === "off"
|
||||
? undefined
|
||||
: this._state.thinkingLevel === "minimal"
|
||||
? "low"
|
||||
: (this._state.thinkingLevel as ReasoningEffort);
|
||||
const reasoning = this._state.thinkingLevel === "off" ? undefined : this._state.thinkingLevel;
|
||||
|
||||
const context: AgentContext = {
|
||||
systemPrompt: this._state.systemPrompt,
|
||||
@@ -331,6 +348,7 @@ export class Agent {
|
||||
model,
|
||||
reasoning,
|
||||
interruptMode: this.interruptMode,
|
||||
sessionId: this._sessionId,
|
||||
convertToLlm: this.convertToLlm,
|
||||
transformContext: this.transformContext,
|
||||
getApiKey: this.getApiKey,
|
||||
|
||||
@@ -12,8 +12,8 @@ import {
|
||||
type SimpleStreamOptions,
|
||||
type StopReason,
|
||||
type ToolCall,
|
||||
} from "@oh-my-pi/pi-ai";
|
||||
import { parseStreamingJson } from "@oh-my-pi/pi-ai/utils/json-parse";
|
||||
} from "@mariozechner/pi-ai";
|
||||
import { parseStreamingJson } from "@mariozechner/pi-ai/dist/utils/json-parse.js";
|
||||
|
||||
// Create stream class matching ProxyMessageEventStream
|
||||
class ProxyMessageEventStream extends EventStream<AssistantMessageEvent, AssistantMessage> {
|
||||
|
||||
@@ -8,7 +8,7 @@ import type {
|
||||
TextContent,
|
||||
Tool,
|
||||
ToolResultMessage,
|
||||
} from "@oh-my-pi/pi-ai";
|
||||
} from "@mariozechner/pi-ai";
|
||||
import type { Static, TSchema } from "@sinclair/typebox";
|
||||
|
||||
/** Stream function - can return sync or Promise for async config lookup */
|
||||
@@ -29,6 +29,12 @@ export interface AgentLoopConfig extends SimpleStreamOptions {
|
||||
*/
|
||||
interruptMode?: "immediate" | "wait";
|
||||
|
||||
/**
|
||||
* Optional session identifier forwarded to LLM providers.
|
||||
* Used by providers that support session-based caching (e.g., OpenAI Codex).
|
||||
*/
|
||||
sessionId?: string;
|
||||
|
||||
/**
|
||||
* Converts AgentMessage[] to LLM-compatible Message[] before each LLM call.
|
||||
*
|
||||
|
||||
@@ -5,7 +5,7 @@ import {
|
||||
type Message,
|
||||
type Model,
|
||||
type UserMessage,
|
||||
} from "@oh-my-pi/pi-ai";
|
||||
} from "@mariozechner/pi-ai";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { agentLoop, agentLoopContinue } from "../src/agent-loop";
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { Agent } from "../src/index";
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import type { AssistantMessage, Model, ToolResultMessage, UserMessage } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import type { AssistantMessage, Model, ToolResultMessage, UserMessage } from "@mariozechner/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { Agent } from "../src/index";
|
||||
import { calculateTool } from "./utils/calculate";
|
||||
|
||||
@@ -1,282 +0,0 @@
|
||||
# Changelog
|
||||
|
||||
## [Unreleased]
|
||||
### Added
|
||||
|
||||
- Added `sessionId` option for session-based prompt caching in providers that support it
|
||||
- Added Google Vertex AI provider with Gemini 1.5, 2.0, 2.5, and 3.0 model support
|
||||
- Added GPT-5 series models (gpt-5, gpt-5.1, gpt-5.2 and variants) to OpenAI Codex provider
|
||||
|
||||
### Changed
|
||||
|
||||
- Changed reasoning configuration to only apply when explicitly specified, removing automatic defaults
|
||||
- Changed default reasoning summary from `auto` to `detailed` for OpenAI Codex provider
|
||||
|
||||
## [3.20.1] - 2026-01-06
|
||||
|
||||
## [3.20.0] - 2026-01-06
|
||||
### Added
|
||||
|
||||
- Added support for kwaipilot/kat-coder-pro model via OpenRouter
|
||||
- Added OpenAI Codex responses provider with OAuth login support for ChatGPT Plus/Pro accounts
|
||||
- Added Google Vertex AI provider (Gemini via Vertex) with Application Default Credentials support
|
||||
|
||||
### Changed
|
||||
|
||||
- Updated model specifications including context windows, max tokens, and pricing for multiple OpenRouter models
|
||||
|
||||
### Removed
|
||||
|
||||
- Removed alibaba/tongyi-deepresearch-30b-a3b:free model from OpenRouter
|
||||
- Removed nousresearch/hermes-4-405b model from OpenRouter
|
||||
- Removed tngtech/tng-r1t-chimera:free model from OpenRouter
|
||||
|
||||
## [3.15.1] - 2026-01-05
|
||||
|
||||
## [3.15.0] - 2026-01-05
|
||||
### Changed
|
||||
|
||||
- Made `isError` field optional in `ToolResultMessage` interface, defaulting to non-error state
|
||||
|
||||
## [3.14.0] - 2026-01-04
|
||||
|
||||
## [3.13.1337] - 2026-01-04
|
||||
|
||||
## [3.9.1337] - 2026-01-04
|
||||
|
||||
## [3.8.1337] - 2026-01-04
|
||||
|
||||
## [3.7.1337] - 2026-01-04
|
||||
|
||||
## [3.6.1337] - 2026-01-03
|
||||
|
||||
## [3.5.1337] - 2026-01-03
|
||||
### Added
|
||||
|
||||
- Added localhost URL detection for OpenAI-compatible provider auto-configuration
|
||||
|
||||
## [3.4.1337] - 2026-01-03
|
||||
|
||||
## [3.3.1337] - 2026-01-03
|
||||
|
||||
## [3.1.1337] - 2026-01-03
|
||||
|
||||
## [3.0.1337] - 2026-01-03
|
||||
|
||||
## [2.3.1337] - 2026-01-03
|
||||
|
||||
## [2.2.1337] - 2026-01-03
|
||||
|
||||
## [2.1.1337] - 2026-01-03
|
||||
|
||||
## [2.0.1337] - 2026-01-03
|
||||
|
||||
## [1.500.0] - 2026-01-03
|
||||
|
||||
## [1.341.0] - 2026-01-03
|
||||
|
||||
## [1.338.0] - 2026-01-03
|
||||
|
||||
## [1.337.1] - 2026-01-02
|
||||
|
||||
### Changed
|
||||
|
||||
- Forked to @oh-my-pi scope with unified versioning across all packages
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Gemini CLI rate limit handling**: Added automatic retry with server-provided delay for 429 errors
|
||||
|
||||
## [1.337.0] - 2026-01-02
|
||||
|
||||
Initial release under @oh-my-pi scope. See previous releases at [badlogic/pi-mono](https://github.com/badlogic/pi-mono).
|
||||
|
||||
## [0.31.1] - 2026-01-02
|
||||
|
||||
## [0.31.0] - 2026-01-02
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
- **Agent API moved**: All agent functionality (`agentLoop`, `agentLoopContinue`, `AgentContext`, `AgentEvent`, `AgentTool`, `AgentToolResult`, etc.) has moved to `@oh-my-pi/pi-agent-core`. Import from that package instead of `@oh-my-pi/pi-ai`.
|
||||
|
||||
### Added
|
||||
|
||||
- **`GoogleThinkingLevel` type**: Exported type that mirrors Google's `ThinkingLevel` enum values (`"THINKING_LEVEL_UNSPECIFIED" | "MINIMAL" | "LOW" | "MEDIUM" | "HIGH"`). Allows configuring Gemini thinking levels without importing from `@google/genai`.
|
||||
- **`ANTHROPIC_OAUTH_TOKEN` env var**: Now checked before `ANTHROPIC_API_KEY` in `getEnvApiKey()`, allowing OAuth tokens to take precedence.
|
||||
- **`event-stream.js` export**: `AssistantMessageEventStream` utility now exported from package index.
|
||||
|
||||
### Changed
|
||||
|
||||
- **OAuth uses Web Crypto API**: PKCE generation and OAuth flows now use Web Crypto API (`crypto.subtle`) instead of Node.js `crypto` module. This improves browser compatibility while still working in Node.js 20+.
|
||||
- **Deterministic model generation**: `generate-models.ts` now sorts providers and models alphabetically for consistent output across runs. ([#332](https://github.com/badlogic/pi-mono/pull/332) by [@mrexodia](https://github.com/mrexodia))
|
||||
|
||||
### Fixed
|
||||
|
||||
- **OpenAI completions empty content blocks**: Empty text or thinking blocks in assistant messages are now filtered out before sending to the OpenAI completions API, preventing validation errors. ([#344](https://github.com/badlogic/pi-mono/pull/344) by [@default-anton](https://github.com/default-anton))
|
||||
- **zAi provider API mapping**: Fixed zAi models to use `openai-completions` API with correct base URL (`https://api.z.ai/api/coding/paas/v4`) instead of incorrect Anthropic API mapping. ([#344](https://github.com/badlogic/pi-mono/pull/344), [#358](https://github.com/badlogic/pi-mono/pull/358) by [@default-anton](https://github.com/default-anton))
|
||||
|
||||
## [0.28.0] - 2025-12-25
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
- **OAuth storage removed** ([#296](https://github.com/badlogic/pi-mono/issues/296)): All storage functions (`loadOAuthCredentials`, `saveOAuthCredentials`, `setOAuthStorage`, etc.) removed. Callers are responsible for storing credentials.
|
||||
- **OAuth login functions**: `loginAnthropic`, `loginGitHubCopilot`, `loginGeminiCli`, `loginAntigravity` now return `OAuthCredentials` instead of saving to disk.
|
||||
- **refreshOAuthToken**: Now takes `(provider, credentials)` and returns new `OAuthCredentials` instead of saving.
|
||||
- **getOAuthApiKey**: Now takes `(provider, credentials)` and returns `{ newCredentials, apiKey }` or null.
|
||||
- **OAuthCredentials type**: No longer includes `type: "oauth"` discriminator. Callers add discriminator when storing.
|
||||
- **setApiKey, resolveApiKey**: Removed. Callers must manage their own API key storage/resolution.
|
||||
- **getApiKey**: Renamed to `getEnvApiKey`. Only checks environment variables for known providers.
|
||||
|
||||
## [0.27.7] - 2025-12-24
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Thinking tag leakage**: Fixed Claude mimicking literal `</thinking>` tags in responses. Unsigned thinking blocks (from aborted streams) are now converted to plain text without `<thinking>` tags. The TUI still displays them as thinking blocks. ([#302](https://github.com/badlogic/pi-mono/pull/302) by [@nicobailon](https://github.com/nicobailon))
|
||||
|
||||
## [0.25.1] - 2025-12-21
|
||||
|
||||
### Added
|
||||
|
||||
- **xhigh thinking level support**: Added `supportsXhigh()` function to check if a model supports xhigh reasoning level. Also clamps xhigh to high for OpenAI models that don't support it. ([#236](https://github.com/badlogic/pi-mono/pull/236) by [@theBucky](https://github.com/theBucky))
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Gemini multimodal tool results**: Fixed images in tool results causing flaky/broken responses with Gemini models. For Gemini 3, images are now nested inside `functionResponse.parts` per the [docs](https://ai.google.dev/gemini-api/docs/function-calling#multimodal). For older models (which don't support multimodal function responses), images are sent in a separate user message.
|
||||
|
||||
- **Queued message steering**: When `getQueuedMessages` is provided, the agent loop now checks for queued user messages after each tool call and skips remaining tool calls in the current assistant message when a queued message arrives (emitting error tool results).
|
||||
|
||||
- **Double API version path in Google provider URL**: Fixed Gemini API calls returning 404 after baseUrl support was added. The SDK was appending its default apiVersion to baseUrl which already included the version path. ([#251](https://github.com/badlogic/pi-mono/pull/251) by [@shellfyred](https://github.com/shellfyred))
|
||||
|
||||
- **Anthropic SDK retries disabled**: Re-enabled SDK-level retries (default 2) for transient HTTP failures. ([#252](https://github.com/badlogic/pi-mono/issues/252))
|
||||
|
||||
## [0.23.5] - 2025-12-19
|
||||
|
||||
### Added
|
||||
|
||||
- **Gemini 3 Flash thinking support**: Extended thinking level support for Gemini 3 Flash models (MINIMAL, LOW, MEDIUM, HIGH) to match Pro models' capabilities. ([#212](https://github.com/badlogic/pi-mono/pull/212) by [@markusylisiurunen](https://github.com/markusylisiurunen))
|
||||
|
||||
- **GitHub Copilot thinking models**: Added thinking support for additional Copilot models (o3-mini, o1-mini, o1-preview). ([#234](https://github.com/badlogic/pi-mono/pull/234) by [@aadishv](https://github.com/aadishv))
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Gemini tool result format**: Fixed tool result format for Gemini 3 Flash Preview which strictly requires `{ output: value }` for success and `{ error: value }` for errors. Previous format using `{ result, isError }` was rejected by newer Gemini models. Also improved type safety by removing `as any` casts. ([#213](https://github.com/badlogic/pi-mono/issues/213), [#220](https://github.com/badlogic/pi-mono/pull/220))
|
||||
|
||||
- **Google baseUrl configuration**: Google provider now respects `baseUrl` configuration for custom endpoints or API proxies. ([#216](https://github.com/badlogic/pi-mono/issues/216), [#221](https://github.com/badlogic/pi-mono/pull/221) by [@theBucky](https://github.com/theBucky))
|
||||
|
||||
- **GitHub Copilot vision requests**: Added `Copilot-Vision-Request` header when sending images to GitHub Copilot models. ([#222](https://github.com/badlogic/pi-mono/issues/222))
|
||||
|
||||
- **GitHub Copilot X-Initiator header**: Fixed X-Initiator logic to check last message role instead of any message in history. This ensures proper billing when users send follow-up messages. ([#209](https://github.com/badlogic/pi-mono/issues/209))
|
||||
|
||||
## [0.22.3] - 2025-12-16
|
||||
|
||||
### Added
|
||||
|
||||
- **Image limits test suite**: Added comprehensive tests for provider-specific image limitations (max images, max size, max dimensions). Discovered actual limits: Anthropic (100 images, 5MB, 8000px), OpenAI (500 images, ≥25MB), Gemini (~2500 images, ≥40MB), Mistral (8 images, ~15MB), OpenRouter (~40 images context-limited, ~15MB). ([#120](https://github.com/badlogic/pi-mono/pull/120))
|
||||
|
||||
- **Tool result streaming**: Added `tool_execution_update` event and optional `onUpdate` callback to `AgentTool.execute()` for streaming tool output during execution. Tools can now emit partial results (e.g., bash stdout) that are forwarded to subscribers. ([#44](https://github.com/badlogic/pi-mono/issues/44))
|
||||
|
||||
- **X-Initiator header for GitHub Copilot**: Added X-Initiator header handling for GitHub Copilot provider to ensure correct call accounting (agent calls are not deducted from quota). Sets initiator based on last message role. ([#200](https://github.com/badlogic/pi-mono/pull/200) by [@kim0](https://github.com/kim0))
|
||||
|
||||
### Changed
|
||||
|
||||
- **Normalized tool_execution_end result**: `tool_execution_end` event now always contains `AgentToolResult` (no longer `AgentToolResult | string`). Errors are wrapped in the standard result format.
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Reasoning disabled by default**: When `reasoning` option is not specified, thinking is now explicitly disabled for all providers. Previously, some providers like Gemini with "dynamic thinking" would use their default (thinking ON), causing unexpected token usage. This was the original intended behavior. ([#180](https://github.com/badlogic/pi-mono/pull/180) by [@markusylisiurunen](https://github.com/markusylisiurunen))
|
||||
|
||||
## [0.22.2] - 2025-12-15
|
||||
|
||||
### Added
|
||||
|
||||
- **Interleaved thinking for Anthropic**: Added `interleavedThinking` option to `AnthropicOptions`. When enabled, Claude 4 models can think between tool calls and reason after receiving tool results. Enabled by default (no extra token cost, just unlocks the capability). Set `interleavedThinking: false` to disable.
|
||||
|
||||
## [0.22.1] - 2025-12-15
|
||||
|
||||
_Dedicated to Peter's shoulder ([@steipete](https://twitter.com/steipete))_
|
||||
|
||||
### Added
|
||||
|
||||
- **Interleaved thinking for Anthropic**: Enabled interleaved thinking in the Anthropic provider, allowing Claude models to output thinking blocks interspersed with text responses.
|
||||
|
||||
## [0.22.0] - 2025-12-15
|
||||
|
||||
### Added
|
||||
|
||||
- **GitHub Copilot provider**: Added `github-copilot` as a known provider with models sourced from models.dev. Includes Claude, GPT, Gemini, Grok, and other models available through GitHub Copilot. ([#191](https://github.com/badlogic/pi-mono/pull/191) by [@cau1k](https://github.com/cau1k))
|
||||
|
||||
### Fixed
|
||||
|
||||
- **GitHub Copilot gpt-5 models**: Fixed API selection for gpt-5 models to use `openai-responses` instead of `openai-completions` (gpt-5 models are not accessible via completions endpoint)
|
||||
|
||||
- **GitHub Copilot cross-model context handoff**: Fixed context handoff failing when switching between GitHub Copilot models using different APIs (e.g., gpt-5 to claude-sonnet-4). Tool call IDs from OpenAI Responses API were incompatible with other models. ([#198](https://github.com/badlogic/pi-mono/issues/198))
|
||||
|
||||
- **Gemini 3 Pro thinking levels**: Thinking level configuration now works correctly for Gemini 3 Pro models. Previously all levels mapped to -1 (minimal thinking). Now LOW/MEDIUM/HIGH properly control test-time computation. ([#176](https://github.com/badlogic/pi-mono/pull/176) by [@markusylisiurunen](https://github.com/markusylisiurunen))
|
||||
|
||||
## [0.18.2] - 2025-12-11
|
||||
|
||||
### Changed
|
||||
|
||||
- **Anthropic SDK retries disabled**: Set `maxRetries: 0` on Anthropic client to allow application-level retry handling. The SDK's built-in retries were interfering with coding-agent's retry logic. ([#157](https://github.com/badlogic/pi-mono/issues/157))
|
||||
|
||||
## [0.18.1] - 2025-12-10
|
||||
|
||||
### Added
|
||||
|
||||
- **Mistral provider**: Added support for Mistral AI models via the OpenAI-compatible API. Includes automatic handling of Mistral-specific requirements (tool call ID format). Set `MISTRAL_API_KEY` environment variable to use.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed Mistral 400 errors after aborted assistant messages by skipping empty assistant messages (no content, no tool calls) ([#165](https://github.com/badlogic/pi-mono/issues/165))
|
||||
|
||||
- Removed synthetic assistant bridge message after tool results for Mistral (no longer required as of Dec 2025) ([#165](https://github.com/badlogic/pi-mono/issues/165))
|
||||
|
||||
- Fixed bug where `ANTHROPIC_API_KEY` environment variable was deleted globally after first OAuth token usage, causing subsequent prompts to fail ([#164](https://github.com/badlogic/pi-mono/pull/164))
|
||||
|
||||
## [0.17.0] - 2025-12-09
|
||||
|
||||
### Added
|
||||
|
||||
- **`agentLoopContinue` function**: Continue an agent loop from existing context without adding a new user message. Validates that the last message is `user` or `toolResult`. Useful for retry after context overflow or resuming from manually-added tool results.
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
- Removed provider-level tool argument validation. Validation now happens in `agentLoop` via `executeToolCalls`, allowing models to retry on validation errors. For manual tool execution, use `validateToolCall(tools, toolCall)` or `validateToolArguments(tool, toolCall)`.
|
||||
|
||||
### Added
|
||||
|
||||
- Added `validateToolCall(tools, toolCall)` helper that finds the tool by name and validates arguments.
|
||||
|
||||
- **OpenAI compatibility overrides**: Added `compat` field to `Model` for `openai-completions` API, allowing explicit configuration of provider quirks (`supportsStore`, `supportsDeveloperRole`, `supportsReasoningEffort`, `maxTokensField`). Falls back to URL-based detection if not set. Useful for LiteLLM, custom proxies, and other non-standard endpoints. ([#133](https://github.com/badlogic/pi-mono/issues/133), thanks @fink-andreas for the initial idea and PR)
|
||||
|
||||
- **xhigh reasoning level**: Added `xhigh` to `ReasoningEffort` type for OpenAI codex-max models. For non-OpenAI providers (Anthropic, Google), `xhigh` is automatically mapped to `high`. ([#143](https://github.com/badlogic/pi-mono/issues/143))
|
||||
|
||||
### Changed
|
||||
|
||||
- **Updated SDK versions**: OpenAI SDK 5.21.0 → 6.10.0, Anthropic SDK 0.61.0 → 0.71.2, Google GenAI SDK 1.30.0 → 1.31.0
|
||||
|
||||
## [0.13.0] - 2025-12-06
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
- **Added `totalTokens` field to `Usage` type**: All code that constructs `Usage` objects must now include the `totalTokens` field. This field represents the total tokens processed by the LLM (input + output + cache). For OpenAI and Google, this uses native API values (`total_tokens`, `totalTokenCount`). For Anthropic, it's computed as `input + output + cacheRead + cacheWrite`.
|
||||
|
||||
## [0.12.10] - 2025-12-04
|
||||
|
||||
### Added
|
||||
|
||||
- Added `gpt-5.1-codex-max` model support
|
||||
|
||||
### Fixed
|
||||
|
||||
- **OpenAI Token Counting**: Fixed `usage.input` to exclude cached tokens for OpenAI providers. Previously, `input` included cached tokens, causing double-counting when calculating total context size via `input + cacheRead`. Now `input` represents non-cached input tokens across all providers, making `input + output + cacheRead + cacheWrite` the correct formula for total context size.
|
||||
|
||||
- **Fixed Claude Opus 4.5 cache pricing** (was 3x too expensive)
|
||||
- Corrected cache_read: $1.50 → $0.50 per MTok
|
||||
- Corrected cache_write: $18.75 → $6.25 per MTok
|
||||
- Added manual override in `scripts/generate-models.ts` until upstream fix is merged
|
||||
- Submitted PR to models.dev: https://github.com/sst/models.dev/pull/439
|
||||
|
||||
## [0.9.4] - 2025-11-26
|
||||
|
||||
Initial release with multi-provider LLM support.
|
||||
@@ -1,959 +0,0 @@
|
||||
# @oh-my-pi/pi-ai
|
||||
|
||||
Unified LLM API with automatic model discovery, provider configuration, token and cost tracking, and simple context persistence and hand-off to other models mid-session.
|
||||
|
||||
**Note**: This library only includes models that support tool calling (function calling), as this is essential for agentic workflows.
|
||||
|
||||
## Supported Providers
|
||||
|
||||
- **OpenAI**
|
||||
- **Anthropic**
|
||||
- **Google**
|
||||
- **Mistral**
|
||||
- **Groq**
|
||||
- **Cerebras**
|
||||
- **xAI**
|
||||
- **OpenRouter**
|
||||
- **GitHub Copilot** (requires OAuth, see below)
|
||||
- **Any OpenAI-compatible API**: Ollama, vLLM, LM Studio, etc.
|
||||
|
||||
## Installation
|
||||
|
||||
```bash
|
||||
npm install @oh-my-pi/pi-ai
|
||||
```
|
||||
|
||||
## Quick Start
|
||||
|
||||
```typescript
|
||||
import { Type, getModel, stream, complete, Context, Tool, StringEnum } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Fully typed with auto-complete support for both providers and models
|
||||
const model = getModel("openai", "gpt-4o-mini");
|
||||
|
||||
// Define tools with TypeBox schemas for type safety and validation
|
||||
const tools: Tool[] = [
|
||||
{
|
||||
name: "get_time",
|
||||
description: "Get the current time",
|
||||
parameters: Type.Object({
|
||||
timezone: Type.Optional(Type.String({ description: "Optional timezone (e.g., America/New_York)" })),
|
||||
}),
|
||||
},
|
||||
];
|
||||
|
||||
// Build a conversation context (easily serializable and transferable between models)
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages: [{ role: "user", content: "What time is it?" }],
|
||||
tools,
|
||||
};
|
||||
|
||||
// Option 1: Streaming with all event types
|
||||
const s = stream(model, context);
|
||||
|
||||
for await (const event of s) {
|
||||
switch (event.type) {
|
||||
case "start":
|
||||
console.log(`Starting with ${event.partial.model}`);
|
||||
break;
|
||||
case "text_start":
|
||||
console.log("\n[Text started]");
|
||||
break;
|
||||
case "text_delta":
|
||||
process.stdout.write(event.delta);
|
||||
break;
|
||||
case "text_end":
|
||||
console.log("\n[Text ended]");
|
||||
break;
|
||||
case "thinking_start":
|
||||
console.log("[Model is thinking...]");
|
||||
break;
|
||||
case "thinking_delta":
|
||||
process.stdout.write(event.delta);
|
||||
break;
|
||||
case "thinking_end":
|
||||
console.log("[Thinking complete]");
|
||||
break;
|
||||
case "toolcall_start":
|
||||
console.log(`\n[Tool call started: index ${event.contentIndex}]`);
|
||||
break;
|
||||
case "toolcall_delta":
|
||||
// Partial tool arguments are being streamed
|
||||
const partialCall = event.partial.content[event.contentIndex];
|
||||
if (partialCall.type === "toolCall") {
|
||||
console.log(`[Streaming args for ${partialCall.name}]`);
|
||||
}
|
||||
break;
|
||||
case "toolcall_end":
|
||||
console.log(`\nTool called: ${event.toolCall.name}`);
|
||||
console.log(`Arguments: ${JSON.stringify(event.toolCall.arguments)}`);
|
||||
break;
|
||||
case "done":
|
||||
console.log(`\nFinished: ${event.reason}`);
|
||||
break;
|
||||
case "error":
|
||||
console.error(`Error: ${event.error}`);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Get the final message after streaming, add it to the context
|
||||
const finalMessage = await s.result();
|
||||
context.messages.push(finalMessage);
|
||||
|
||||
// Handle tool calls if any
|
||||
const toolCalls = finalMessage.content.filter((b) => b.type === "toolCall");
|
||||
for (const call of toolCalls) {
|
||||
// Execute the tool
|
||||
const result =
|
||||
call.name === "get_time"
|
||||
? new Date().toLocaleString("en-US", {
|
||||
timeZone: call.arguments.timezone || "UTC",
|
||||
dateStyle: "full",
|
||||
timeStyle: "long",
|
||||
})
|
||||
: "Unknown tool";
|
||||
|
||||
// Add tool result to context (supports text and images)
|
||||
context.messages.push({
|
||||
role: "toolResult",
|
||||
toolCallId: call.id,
|
||||
toolName: call.name,
|
||||
content: [{ type: "text", text: result }],
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
}
|
||||
|
||||
// Continue if there were tool calls
|
||||
if (toolCalls.length > 0) {
|
||||
const continuation = await complete(model, context);
|
||||
context.messages.push(continuation);
|
||||
console.log("After tool execution:", continuation.content);
|
||||
}
|
||||
|
||||
console.log(`Total tokens: ${finalMessage.usage.input} in, ${finalMessage.usage.output} out`);
|
||||
console.log(`Cost: $${finalMessage.usage.cost.total.toFixed(4)}`);
|
||||
|
||||
// Option 2: Get complete response without streaming
|
||||
const response = await complete(model, context);
|
||||
|
||||
for (const block of response.content) {
|
||||
if (block.type === "text") {
|
||||
console.log(block.text);
|
||||
} else if (block.type === "toolCall") {
|
||||
console.log(`Tool: ${block.name}(${JSON.stringify(block.arguments)})`);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Tools
|
||||
|
||||
Tools enable LLMs to interact with external systems. This library uses TypeBox schemas for type-safe tool definitions with automatic validation using AJV. TypeBox schemas can be serialized and deserialized as plain JSON, making them ideal for distributed systems.
|
||||
|
||||
### Defining Tools
|
||||
|
||||
```typescript
|
||||
import { Type, Tool, StringEnum } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Define tool parameters with TypeBox
|
||||
const weatherTool: Tool = {
|
||||
name: "get_weather",
|
||||
description: "Get current weather for a location",
|
||||
parameters: Type.Object({
|
||||
location: Type.String({ description: "City name or coordinates" }),
|
||||
units: StringEnum(["celsius", "fahrenheit"], { default: "celsius" }),
|
||||
}),
|
||||
};
|
||||
|
||||
// Note: For Google API compatibility, use StringEnum helper instead of Type.Enum
|
||||
// Type.Enum generates anyOf/const patterns that Google doesn't support
|
||||
|
||||
const bookMeetingTool: Tool = {
|
||||
name: "book_meeting",
|
||||
description: "Schedule a meeting",
|
||||
parameters: Type.Object({
|
||||
title: Type.String({ minLength: 1 }),
|
||||
startTime: Type.String({ format: "date-time" }),
|
||||
endTime: Type.String({ format: "date-time" }),
|
||||
attendees: Type.Array(Type.String({ format: "email" }), { minItems: 1 }),
|
||||
}),
|
||||
};
|
||||
```
|
||||
|
||||
### Handling Tool Calls
|
||||
|
||||
Tool results use content blocks and can include both text and images:
|
||||
|
||||
```typescript
|
||||
import { readFileSync } from "fs";
|
||||
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "What is the weather in London?" }],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
|
||||
const response = await complete(model, context);
|
||||
|
||||
// Check for tool calls in the response
|
||||
for (const block of response.content) {
|
||||
if (block.type === "toolCall") {
|
||||
// Execute your tool with the arguments
|
||||
// See "Validating Tool Arguments" section for validation
|
||||
const result = await executeWeatherApi(block.arguments);
|
||||
|
||||
// Add tool result with text content
|
||||
context.messages.push({
|
||||
role: "toolResult",
|
||||
toolCallId: block.id,
|
||||
toolName: block.name,
|
||||
content: [{ type: "text", text: JSON.stringify(result) }],
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Tool results can also include images (for vision-capable models)
|
||||
const imageBuffer = readFileSync("chart.png");
|
||||
context.messages.push({
|
||||
role: "toolResult",
|
||||
toolCallId: "tool_xyz",
|
||||
toolName: "generate_chart",
|
||||
content: [
|
||||
{ type: "text", text: "Generated chart showing temperature trends" },
|
||||
{ type: "image", data: imageBuffer.toString("base64"), mimeType: "image/png" },
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
```
|
||||
|
||||
### Streaming Tool Calls with Partial JSON
|
||||
|
||||
During streaming, tool call arguments are progressively parsed as they arrive. This enables real-time UI updates before the complete arguments are available:
|
||||
|
||||
```typescript
|
||||
const s = stream(model, context);
|
||||
|
||||
for await (const event of s) {
|
||||
if (event.type === "toolcall_delta") {
|
||||
const toolCall = event.partial.content[event.contentIndex];
|
||||
|
||||
// toolCall.arguments contains partially parsed JSON during streaming
|
||||
// This allows for progressive UI updates
|
||||
if (toolCall.type === "toolCall" && toolCall.arguments) {
|
||||
// BE DEFENSIVE: arguments may be incomplete
|
||||
// Example: Show file path being written even before content is complete
|
||||
if (toolCall.name === "write_file" && toolCall.arguments.path) {
|
||||
console.log(`Writing to: ${toolCall.arguments.path}`);
|
||||
|
||||
// Content might be partial or missing
|
||||
if (toolCall.arguments.content) {
|
||||
console.log(`Content preview: ${toolCall.arguments.content.substring(0, 100)}...`);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (event.type === "toolcall_end") {
|
||||
// Here toolCall.arguments is complete (but not yet validated)
|
||||
const toolCall = event.toolCall;
|
||||
console.log(`Tool completed: ${toolCall.name}`, toolCall.arguments);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**Important notes about partial tool arguments:**
|
||||
|
||||
- During `toolcall_delta` events, `arguments` contains the best-effort parse of partial JSON
|
||||
- Fields may be missing or incomplete - always check for existence before use
|
||||
- String values may be truncated mid-word
|
||||
- Arrays may be incomplete
|
||||
- Nested objects may be partially populated
|
||||
- At minimum, `arguments` will be an empty object `{}`, never `undefined`
|
||||
- The Google provider does not support function call streaming. Instead, you will receive a single `toolcall_delta` event with the full arguments.
|
||||
|
||||
### Validating Tool Arguments
|
||||
|
||||
When using `agentLoop`, tool arguments are automatically validated against your TypeBox schemas before execution. If validation fails, the error is returned to the model as a tool result, allowing it to retry.
|
||||
|
||||
When implementing your own tool execution loop with `stream()` or `complete()`, use `validateToolCall` to validate arguments before passing them to your tools:
|
||||
|
||||
```typescript
|
||||
import { stream, validateToolCall, Tool } from "@oh-my-pi/pi-ai";
|
||||
|
||||
const tools: Tool[] = [weatherTool, calculatorTool];
|
||||
const s = stream(model, { messages, tools });
|
||||
|
||||
for await (const event of s) {
|
||||
if (event.type === "toolcall_end") {
|
||||
const toolCall = event.toolCall;
|
||||
|
||||
try {
|
||||
// Validate arguments against the tool's schema (throws on invalid args)
|
||||
const validatedArgs = validateToolCall(tools, toolCall);
|
||||
const result = await executeMyTool(toolCall.name, validatedArgs);
|
||||
// ... add tool result to context
|
||||
} catch (error) {
|
||||
// Validation failed - return error as tool result so model can retry
|
||||
context.messages.push({
|
||||
role: "toolResult",
|
||||
toolCallId: toolCall.id,
|
||||
toolName: toolCall.name,
|
||||
content: [{ type: "text", text: error.message }],
|
||||
isError: true,
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Complete Event Reference
|
||||
|
||||
All streaming events emitted during assistant message generation:
|
||||
|
||||
| Event Type | Description | Key Properties |
|
||||
| ---------------- | ------------------------ | ------------------------------------------------------------------------------------------- |
|
||||
| `start` | Stream begins | `partial`: Initial assistant message structure |
|
||||
| `text_start` | Text block starts | `contentIndex`: Position in content array |
|
||||
| `text_delta` | Text chunk received | `delta`: New text, `contentIndex`: Position |
|
||||
| `text_end` | Text block complete | `content`: Full text, `contentIndex`: Position |
|
||||
| `thinking_start` | Thinking block starts | `contentIndex`: Position in content array |
|
||||
| `thinking_delta` | Thinking chunk received | `delta`: New text, `contentIndex`: Position |
|
||||
| `thinking_end` | Thinking block complete | `content`: Full thinking, `contentIndex`: Position |
|
||||
| `toolcall_start` | Tool call begins | `contentIndex`: Position in content array |
|
||||
| `toolcall_delta` | Tool arguments streaming | `delta`: JSON chunk, `partial.content[contentIndex].arguments`: Partial parsed args |
|
||||
| `toolcall_end` | Tool call complete | `toolCall`: Complete validated tool call with `id`, `name`, `arguments` |
|
||||
| `done` | Stream complete | `reason`: Stop reason ("stop", "length", "toolUse"), `message`: Final assistant message |
|
||||
| `error` | Error occurred | `reason`: Error type ("error" or "aborted"), `error`: AssistantMessage with partial content |
|
||||
|
||||
## Image Input
|
||||
|
||||
Models with vision capabilities can process images. You can check if a model supports images via the `input` property. If you pass images to a non-vision model, they are silently ignored.
|
||||
|
||||
```typescript
|
||||
import { readFileSync } from "fs";
|
||||
import { getModel, complete } from "@oh-my-pi/pi-ai";
|
||||
|
||||
const model = getModel("openai", "gpt-4o-mini");
|
||||
|
||||
// Check if model supports images
|
||||
if (model.input.includes("image")) {
|
||||
console.log("Model supports vision");
|
||||
}
|
||||
|
||||
const imageBuffer = readFileSync("image.png");
|
||||
const base64Image = imageBuffer.toString("base64");
|
||||
|
||||
const response = await complete(model, {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: [
|
||||
{ type: "text", text: "What is in this image?" },
|
||||
{ type: "image", data: base64Image, mimeType: "image/png" },
|
||||
],
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
// Access the response
|
||||
for (const block of response.content) {
|
||||
if (block.type === "text") {
|
||||
console.log(block.text);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Thinking/Reasoning
|
||||
|
||||
Many models support thinking/reasoning capabilities where they can show their internal thought process. You can check if a model supports reasoning via the `reasoning` property. If you pass reasoning options to a non-reasoning model, they are silently ignored.
|
||||
|
||||
### Unified Interface (streamSimple/completeSimple)
|
||||
|
||||
```typescript
|
||||
import { getModel, streamSimple, completeSimple } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Many models across providers support thinking/reasoning
|
||||
const model = getModel("anthropic", "claude-sonnet-4-20250514");
|
||||
// or getModel('openai', 'gpt-5-mini');
|
||||
// or getModel('google', 'gemini-2.5-flash');
|
||||
// or getModel('xai', 'grok-code-fast-1');
|
||||
// or getModel('groq', 'openai/gpt-oss-20b');
|
||||
// or getModel('cerebras', 'gpt-oss-120b');
|
||||
// or getModel('openrouter', 'z-ai/glm-4.5v');
|
||||
|
||||
// Check if model supports reasoning
|
||||
if (model.reasoning) {
|
||||
console.log("Model supports reasoning/thinking");
|
||||
}
|
||||
|
||||
// Use the simplified reasoning option
|
||||
const response = await completeSimple(
|
||||
model,
|
||||
{
|
||||
messages: [{ role: "user", content: "Solve: 2x + 5 = 13" }],
|
||||
},
|
||||
{
|
||||
reasoning: "medium", // 'minimal' | 'low' | 'medium' | 'high' | 'xhigh' (xhigh maps to high on non-OpenAI providers)
|
||||
}
|
||||
);
|
||||
|
||||
// Access thinking and text blocks
|
||||
for (const block of response.content) {
|
||||
if (block.type === "thinking") {
|
||||
console.log("Thinking:", block.thinking);
|
||||
} else if (block.type === "text") {
|
||||
console.log("Response:", block.text);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Provider-Specific Options (stream/complete)
|
||||
|
||||
For fine-grained control, use the provider-specific options:
|
||||
|
||||
```typescript
|
||||
import { getModel, complete } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// OpenAI Reasoning (o1, o3, gpt-5)
|
||||
const openaiModel = getModel("openai", "gpt-5-mini");
|
||||
await complete(openaiModel, context, {
|
||||
reasoningEffort: "medium",
|
||||
reasoningSummary: "detailed", // OpenAI Responses API only
|
||||
});
|
||||
|
||||
// Anthropic Thinking (Claude Sonnet 4)
|
||||
const anthropicModel = getModel("anthropic", "claude-sonnet-4-20250514");
|
||||
await complete(anthropicModel, context, {
|
||||
thinkingEnabled: true,
|
||||
thinkingBudgetTokens: 8192, // Optional token limit
|
||||
});
|
||||
|
||||
// Google Gemini Thinking
|
||||
const googleModel = getModel("google", "gemini-2.5-flash");
|
||||
await complete(googleModel, context, {
|
||||
thinking: {
|
||||
enabled: true,
|
||||
budgetTokens: 8192, // -1 for dynamic, 0 to disable
|
||||
},
|
||||
});
|
||||
```
|
||||
|
||||
### Streaming Thinking Content
|
||||
|
||||
When streaming, thinking content is delivered through specific events:
|
||||
|
||||
```typescript
|
||||
const s = streamSimple(model, context, { reasoning: "high" });
|
||||
|
||||
for await (const event of s) {
|
||||
switch (event.type) {
|
||||
case "thinking_start":
|
||||
console.log("[Model started thinking]");
|
||||
break;
|
||||
case "thinking_delta":
|
||||
process.stdout.write(event.delta); // Stream thinking content
|
||||
break;
|
||||
case "thinking_end":
|
||||
console.log("\n[Thinking complete]");
|
||||
break;
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Stop Reasons
|
||||
|
||||
Every `AssistantMessage` includes a `stopReason` field that indicates how the generation ended:
|
||||
|
||||
- `"stop"` - Normal completion, the model finished its response
|
||||
- `"length"` - Output hit the maximum token limit
|
||||
- `"toolUse"` - Model is calling tools and expects tool results
|
||||
- `"error"` - An error occurred during generation
|
||||
- `"aborted"` - Request was cancelled via abort signal
|
||||
|
||||
## Error Handling
|
||||
|
||||
When a request ends with an error (including aborts and tool call validation errors), the streaming API emits an error event:
|
||||
|
||||
```typescript
|
||||
// In streaming
|
||||
for await (const event of stream) {
|
||||
if (event.type === "error") {
|
||||
// event.reason is either "error" or "aborted"
|
||||
// event.error is the AssistantMessage with partial content
|
||||
console.error(`Error (${event.reason}):`, event.error.errorMessage);
|
||||
console.log("Partial content:", event.error.content);
|
||||
}
|
||||
}
|
||||
|
||||
// The final message will have the error details
|
||||
const message = await stream.result();
|
||||
if (message.stopReason === "error" || message.stopReason === "aborted") {
|
||||
console.error("Request failed:", message.errorMessage);
|
||||
// message.content contains any partial content received before the error
|
||||
// message.usage contains partial token counts and costs
|
||||
}
|
||||
```
|
||||
|
||||
### Aborting Requests
|
||||
|
||||
The abort signal allows you to cancel in-progress requests. Aborted requests have `stopReason === 'aborted'`:
|
||||
|
||||
```typescript
|
||||
import { getModel, stream } from "@oh-my-pi/pi-ai";
|
||||
|
||||
const model = getModel("openai", "gpt-4o-mini");
|
||||
const controller = new AbortController();
|
||||
|
||||
// Abort after 2 seconds
|
||||
setTimeout(() => controller.abort(), 2000);
|
||||
|
||||
const s = stream(
|
||||
model,
|
||||
{
|
||||
messages: [{ role: "user", content: "Write a long story" }],
|
||||
},
|
||||
{
|
||||
signal: controller.signal,
|
||||
}
|
||||
);
|
||||
|
||||
for await (const event of s) {
|
||||
if (event.type === "text_delta") {
|
||||
process.stdout.write(event.delta);
|
||||
} else if (event.type === "error") {
|
||||
// event.reason tells you if it was "error" or "aborted"
|
||||
console.log(`${event.reason === "aborted" ? "Aborted" : "Error"}:`, event.error.errorMessage);
|
||||
}
|
||||
}
|
||||
|
||||
// Get results (may be partial if aborted)
|
||||
const response = await s.result();
|
||||
if (response.stopReason === "aborted") {
|
||||
console.log("Request was aborted:", response.errorMessage);
|
||||
console.log("Partial content received:", response.content);
|
||||
console.log("Tokens used:", response.usage);
|
||||
}
|
||||
```
|
||||
|
||||
### Continuing After Abort
|
||||
|
||||
Aborted messages can be added to the conversation context and continued in subsequent requests:
|
||||
|
||||
```typescript
|
||||
const context = {
|
||||
messages: [{ role: "user", content: "Explain quantum computing in detail" }],
|
||||
};
|
||||
|
||||
// First request gets aborted after 2 seconds
|
||||
const controller1 = new AbortController();
|
||||
setTimeout(() => controller1.abort(), 2000);
|
||||
|
||||
const partial = await complete(model, context, { signal: controller1.signal });
|
||||
|
||||
// Add the partial response to context
|
||||
context.messages.push(partial);
|
||||
context.messages.push({ role: "user", content: "Please continue" });
|
||||
|
||||
// Continue the conversation
|
||||
const continuation = await complete(model, context);
|
||||
```
|
||||
|
||||
## APIs, Models, and Providers
|
||||
|
||||
The library implements 4 API interfaces, each with its own streaming function and options:
|
||||
|
||||
- **`anthropic-messages`**: Anthropic's Messages API (`streamAnthropic`, `AnthropicOptions`)
|
||||
- **`google-generative-ai`**: Google's Generative AI API (`streamGoogle`, `GoogleOptions`)
|
||||
- **`openai-completions`**: OpenAI's Chat Completions API (`streamOpenAICompletions`, `OpenAICompletionsOptions`)
|
||||
- **`openai-responses`**: OpenAI's Responses API (`streamOpenAIResponses`, `OpenAIResponsesOptions`)
|
||||
|
||||
### Providers and Models
|
||||
|
||||
A **provider** offers models through a specific API. For example:
|
||||
|
||||
- **Anthropic** models use the `anthropic-messages` API
|
||||
- **Google** models use the `google-generative-ai` API
|
||||
- **OpenAI** models use the `openai-responses` API
|
||||
- **Mistral, xAI, Cerebras, Groq, etc.** models use the `openai-completions` API (OpenAI-compatible)
|
||||
|
||||
### Querying Providers and Models
|
||||
|
||||
```typescript
|
||||
import { getProviders, getModels, getModel } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Get all available providers
|
||||
const providers = getProviders();
|
||||
console.log(providers); // ['openai', 'anthropic', 'google', 'xai', 'groq', ...]
|
||||
|
||||
// Get all models from a provider (fully typed)
|
||||
const anthropicModels = getModels("anthropic");
|
||||
for (const model of anthropicModels) {
|
||||
console.log(`${model.id}: ${model.name}`);
|
||||
console.log(` API: ${model.api}`); // 'anthropic-messages'
|
||||
console.log(` Context: ${model.contextWindow} tokens`);
|
||||
console.log(` Vision: ${model.input.includes("image")}`);
|
||||
console.log(` Reasoning: ${model.reasoning}`);
|
||||
}
|
||||
|
||||
// Get a specific model (both provider and model ID are auto-completed in IDEs)
|
||||
const model = getModel("openai", "gpt-4o-mini");
|
||||
console.log(`Using ${model.name} via ${model.api} API`);
|
||||
```
|
||||
|
||||
### Custom Models
|
||||
|
||||
You can create custom models for local inference servers or custom endpoints:
|
||||
|
||||
```typescript
|
||||
import { Model, stream } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Example: Ollama using OpenAI-compatible API
|
||||
const ollamaModel: Model<"openai-completions"> = {
|
||||
id: "llama-3.1-8b",
|
||||
name: "Llama 3.1 8B (Ollama)",
|
||||
api: "openai-completions",
|
||||
provider: "ollama",
|
||||
baseUrl: "http://localhost:11434/v1",
|
||||
reasoning: false,
|
||||
input: ["text"],
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow: 128000,
|
||||
maxTokens: 32000,
|
||||
};
|
||||
|
||||
// Example: LiteLLM proxy with explicit compat settings
|
||||
const litellmModel: Model<"openai-completions"> = {
|
||||
id: "gpt-4o",
|
||||
name: "GPT-4o (via LiteLLM)",
|
||||
api: "openai-completions",
|
||||
provider: "litellm",
|
||||
baseUrl: "http://localhost:4000/v1",
|
||||
reasoning: false,
|
||||
input: ["text", "image"],
|
||||
cost: { input: 2.5, output: 10, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow: 128000,
|
||||
maxTokens: 16384,
|
||||
compat: {
|
||||
supportsStore: false, // LiteLLM doesn't support the store field
|
||||
},
|
||||
};
|
||||
|
||||
// Example: Custom endpoint with headers (bypassing Cloudflare bot detection)
|
||||
const proxyModel: Model<"anthropic-messages"> = {
|
||||
id: "claude-sonnet-4",
|
||||
name: "Claude Sonnet 4 (Proxied)",
|
||||
api: "anthropic-messages",
|
||||
provider: "custom-proxy",
|
||||
baseUrl: "https://proxy.example.com/v1",
|
||||
reasoning: true,
|
||||
input: ["text", "image"],
|
||||
cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 },
|
||||
contextWindow: 200000,
|
||||
maxTokens: 8192,
|
||||
headers: {
|
||||
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36",
|
||||
"X-Custom-Auth": "bearer-token-here",
|
||||
},
|
||||
};
|
||||
|
||||
// Use the custom model
|
||||
const response = await stream(ollamaModel, context, {
|
||||
apiKey: "dummy", // Ollama doesn't need a real key
|
||||
});
|
||||
```
|
||||
|
||||
### OpenAI Compatibility Settings
|
||||
|
||||
The `openai-completions` API is implemented by many providers with minor differences. By default, the library auto-detects compatibility settings based on `baseUrl` for known providers (Cerebras, xAI, Mistral, Chutes, etc.). For custom proxies or unknown endpoints, you can override these settings via the `compat` field:
|
||||
|
||||
```typescript
|
||||
interface OpenAICompat {
|
||||
supportsStore?: boolean; // Whether provider supports the `store` field (default: true)
|
||||
supportsDeveloperRole?: boolean; // Whether provider supports `developer` role vs `system` (default: true)
|
||||
supportsReasoningEffort?: boolean; // Whether provider supports `reasoning_effort` (default: true)
|
||||
maxTokensField?: "max_completion_tokens" | "max_tokens"; // Which field name to use (default: max_completion_tokens)
|
||||
}
|
||||
```
|
||||
|
||||
If `compat` is not set, the library falls back to URL-based detection. If `compat` is partially set, unspecified fields use the detected defaults. This is useful for:
|
||||
|
||||
- **LiteLLM proxies**: May not support `store` field
|
||||
- **Custom inference servers**: May use non-standard field names
|
||||
- **Self-hosted endpoints**: May have different feature support
|
||||
|
||||
### Type Safety
|
||||
|
||||
Models are typed by their API, ensuring type-safe options:
|
||||
|
||||
```typescript
|
||||
// TypeScript knows this is an Anthropic model
|
||||
const claude = getModel("anthropic", "claude-sonnet-4-20250514");
|
||||
|
||||
// So these options are type-checked for AnthropicOptions
|
||||
await stream(claude, context, {
|
||||
thinkingEnabled: true, // ✓ Valid for anthropic-messages
|
||||
thinkingBudgetTokens: 2048, // ✓ Valid for anthropic-messages
|
||||
// reasoningEffort: 'high' // ✗ TypeScript error: not valid for anthropic-messages
|
||||
});
|
||||
```
|
||||
|
||||
## Cross-Provider Handoffs
|
||||
|
||||
The library supports seamless handoffs between different LLM providers within the same conversation. This allows you to switch models mid-conversation while preserving context, including thinking blocks, tool calls, and tool results.
|
||||
|
||||
### How It Works
|
||||
|
||||
When messages from one provider are sent to a different provider, the library automatically transforms them for compatibility:
|
||||
|
||||
- **User and tool result messages** are passed through unchanged
|
||||
- **Assistant messages from the same provider/API** are preserved as-is
|
||||
- **Assistant messages from different providers** have their thinking blocks converted to text with `<thinking>` tags
|
||||
- **Tool calls and regular text** are preserved unchanged
|
||||
|
||||
### Example: Multi-Provider Conversation
|
||||
|
||||
```typescript
|
||||
import { getModel, complete, Context } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Start with Claude
|
||||
const claude = getModel("anthropic", "claude-sonnet-4-20250514");
|
||||
const context: Context = {
|
||||
messages: [],
|
||||
};
|
||||
|
||||
context.messages.push({ role: "user", content: "What is 25 * 18?" });
|
||||
const claudeResponse = await complete(claude, context, {
|
||||
thinkingEnabled: true,
|
||||
});
|
||||
context.messages.push(claudeResponse);
|
||||
|
||||
// Switch to GPT-5 - it will see Claude's thinking as <thinking> tagged text
|
||||
const gpt5 = getModel("openai", "gpt-5-mini");
|
||||
context.messages.push({ role: "user", content: "Is that calculation correct?" });
|
||||
const gptResponse = await complete(gpt5, context);
|
||||
context.messages.push(gptResponse);
|
||||
|
||||
// Switch to Gemini
|
||||
const gemini = getModel("google", "gemini-2.5-flash");
|
||||
context.messages.push({ role: "user", content: "What was the original question?" });
|
||||
const geminiResponse = await complete(gemini, context);
|
||||
```
|
||||
|
||||
### Provider Compatibility
|
||||
|
||||
All providers can handle messages from other providers, including:
|
||||
|
||||
- Text content
|
||||
- Tool calls and tool results (including images in tool results)
|
||||
- Thinking/reasoning blocks (transformed to tagged text for cross-provider compatibility)
|
||||
- Aborted messages with partial content
|
||||
|
||||
This enables flexible workflows where you can:
|
||||
|
||||
- Start with a fast model for initial responses
|
||||
- Switch to a more capable model for complex reasoning
|
||||
- Use specialized models for specific tasks
|
||||
- Maintain conversation continuity across provider outages
|
||||
|
||||
## Context Serialization
|
||||
|
||||
The `Context` object can be easily serialized and deserialized using standard JSON methods, making it simple to persist conversations, implement chat history, or transfer contexts between services:
|
||||
|
||||
```typescript
|
||||
import { Context, getModel, complete } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Create and use a context
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages: [{ role: "user", content: "What is TypeScript?" }],
|
||||
};
|
||||
|
||||
const model = getModel("openai", "gpt-4o-mini");
|
||||
const response = await complete(model, context);
|
||||
context.messages.push(response);
|
||||
|
||||
// Serialize the entire context
|
||||
const serialized = JSON.stringify(context);
|
||||
console.log("Serialized context size:", serialized.length, "bytes");
|
||||
|
||||
// Save to database, localStorage, file, etc.
|
||||
localStorage.setItem("conversation", serialized);
|
||||
|
||||
// Later: deserialize and continue the conversation
|
||||
const restored: Context = JSON.parse(localStorage.getItem("conversation")!);
|
||||
restored.messages.push({ role: "user", content: "Tell me more about its type system" });
|
||||
|
||||
// Continue with any model
|
||||
const newModel = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
const continuation = await complete(newModel, restored);
|
||||
```
|
||||
|
||||
> **Note**: If the context contains images (encoded as base64 as shown in the Image Input section), those will also be serialized.
|
||||
|
||||
## Browser Usage
|
||||
|
||||
The library supports browser environments. You must pass the API key explicitly since environment variables are not available in browsers:
|
||||
|
||||
```typescript
|
||||
import { getModel, complete } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// API key must be passed explicitly in browser
|
||||
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
const response = await complete(
|
||||
model,
|
||||
{
|
||||
messages: [{ role: "user", content: "Hello!" }],
|
||||
},
|
||||
{
|
||||
apiKey: "your-api-key",
|
||||
}
|
||||
);
|
||||
```
|
||||
|
||||
> **Security Warning**: Exposing API keys in frontend code is dangerous. Anyone can extract and abuse your keys. Only use this approach for internal tools or demos. For production applications, use a backend proxy that keeps your API keys secure.
|
||||
|
||||
### Environment Variables (Node.js only)
|
||||
|
||||
In Node.js environments, you can set environment variables to avoid passing API keys:
|
||||
|
||||
```bash
|
||||
OPENAI_API_KEY=sk-...
|
||||
ANTHROPIC_API_KEY=sk-ant-...
|
||||
GEMINI_API_KEY=...
|
||||
MISTRAL_API_KEY=...
|
||||
GROQ_API_KEY=gsk_...
|
||||
CEREBRAS_API_KEY=csk-...
|
||||
XAI_API_KEY=xai-...
|
||||
ZAI_API_KEY=...
|
||||
OPENROUTER_API_KEY=sk-or-...
|
||||
```
|
||||
|
||||
When set, the library automatically uses these keys:
|
||||
|
||||
```typescript
|
||||
// Uses OPENAI_API_KEY from environment
|
||||
const model = getModel("openai", "gpt-4o-mini");
|
||||
const response = await complete(model, context);
|
||||
|
||||
// Or override with explicit key
|
||||
const response = await complete(model, context, {
|
||||
apiKey: "sk-different-key",
|
||||
});
|
||||
```
|
||||
|
||||
### Checking Environment Variables
|
||||
|
||||
```typescript
|
||||
import { getEnvApiKey } from "@oh-my-pi/pi-ai";
|
||||
|
||||
// Check if an API key is set in environment variables
|
||||
const key = getEnvApiKey("openai"); // checks OPENAI_API_KEY
|
||||
```
|
||||
|
||||
## OAuth Providers
|
||||
|
||||
Several providers require OAuth authentication instead of static API keys:
|
||||
|
||||
- **Anthropic** (Claude Pro/Max subscription)
|
||||
- **GitHub Copilot** (Copilot subscription)
|
||||
- **Google Gemini CLI** (Free Gemini 2.0/2.5 via Google Cloud Code Assist)
|
||||
- **Antigravity** (Free Gemini 3, Claude, GPT-OSS via Google Cloud)
|
||||
|
||||
### CLI Login
|
||||
|
||||
The quickest way to authenticate:
|
||||
|
||||
```bash
|
||||
npx @oh-my-pi/pi-ai login # interactive provider selection
|
||||
npx @oh-my-pi/pi-ai login anthropic # login to specific provider
|
||||
npx @oh-my-pi/pi-ai list # list available providers
|
||||
```
|
||||
|
||||
Credentials are saved to `auth.json` in the current directory.
|
||||
|
||||
### Programmatic OAuth
|
||||
|
||||
The library provides login and token refresh functions. Credential storage is the caller's responsibility.
|
||||
|
||||
```typescript
|
||||
import {
|
||||
// Login functions (return credentials, do not store)
|
||||
loginAnthropic,
|
||||
loginGitHubCopilot,
|
||||
loginGeminiCli,
|
||||
loginAntigravity,
|
||||
|
||||
// Token management
|
||||
refreshOAuthToken, // (provider, credentials) => new credentials
|
||||
getOAuthApiKey, // (provider, credentialsMap) => { newCredentials, apiKey } | null
|
||||
|
||||
// Types
|
||||
type OAuthProvider, // 'anthropic' | 'github-copilot' | 'google-gemini-cli' | 'google-antigravity'
|
||||
type OAuthCredentials,
|
||||
} from "@oh-my-pi/pi-ai";
|
||||
```
|
||||
|
||||
### Login Flow Example
|
||||
|
||||
```typescript
|
||||
import { loginGitHubCopilot } from "@oh-my-pi/pi-ai";
|
||||
import { writeFileSync } from "fs";
|
||||
|
||||
const credentials = await loginGitHubCopilot({
|
||||
onAuth: (url, instructions) => {
|
||||
console.log(`Open: ${url}`);
|
||||
if (instructions) console.log(instructions);
|
||||
},
|
||||
onPrompt: async (prompt) => {
|
||||
return await getUserInput(prompt.message);
|
||||
},
|
||||
onProgress: (message) => console.log(message),
|
||||
});
|
||||
|
||||
// Store credentials yourself
|
||||
const auth = { "github-copilot": { type: "oauth", ...credentials } };
|
||||
writeFileSync("auth.json", JSON.stringify(auth, null, 2));
|
||||
```
|
||||
|
||||
### Using OAuth Tokens
|
||||
|
||||
Use `getOAuthApiKey()` to get an API key, automatically refreshing if expired:
|
||||
|
||||
```typescript
|
||||
import { getModel, complete, getOAuthApiKey } from "@oh-my-pi/pi-ai";
|
||||
import { readFileSync, writeFileSync } from "fs";
|
||||
|
||||
// Load your stored credentials
|
||||
const auth = JSON.parse(readFileSync("auth.json", "utf-8"));
|
||||
|
||||
// Get API key (refreshes if expired)
|
||||
const result = await getOAuthApiKey("github-copilot", auth);
|
||||
if (!result) throw new Error("Not logged in");
|
||||
|
||||
// Save refreshed credentials
|
||||
auth["github-copilot"] = { type: "oauth", ...result.newCredentials };
|
||||
writeFileSync("auth.json", JSON.stringify(auth, null, 2));
|
||||
|
||||
// Use the API key
|
||||
const model = getModel("github-copilot", "gpt-4o");
|
||||
const response = await complete(
|
||||
model,
|
||||
{
|
||||
messages: [{ role: "user", content: "Hello!" }],
|
||||
},
|
||||
{ apiKey: result.apiKey }
|
||||
);
|
||||
```
|
||||
|
||||
### Provider Notes
|
||||
|
||||
**GitHub Copilot**: If you get "The requested model is not supported" error, enable the model manually in VS Code: open Copilot Chat, click the model selector, select the model (warning icon), and click "Enable".
|
||||
|
||||
**Google Gemini CLI / Antigravity**: These use Google Cloud OAuth. The `apiKey` returned by `getOAuthApiKey()` is a JSON string containing both the token and project ID, which the library handles automatically.
|
||||
|
||||
## License
|
||||
|
||||
MIT
|
||||
@@ -1,60 +0,0 @@
|
||||
{
|
||||
"name": "@oh-my-pi/pi-ai",
|
||||
"version": "3.20.1",
|
||||
"description": "Unified LLM API with automatic model discovery and provider configuration",
|
||||
"type": "module",
|
||||
"main": "./src/index.ts",
|
||||
"types": "./src/index.ts",
|
||||
"exports": {
|
||||
".": "./src/index.ts",
|
||||
"./utils/json-parse": "./src/utils/json-parse.ts"
|
||||
},
|
||||
"bin": {
|
||||
"pi-ai": "./src/cli.ts"
|
||||
},
|
||||
"files": [
|
||||
"src",
|
||||
"README.md"
|
||||
],
|
||||
"scripts": {
|
||||
"generate-models": "bun scripts/generate-models.ts",
|
||||
"test": "vitest --run",
|
||||
"prepublishOnly": "bun run generate-models"
|
||||
},
|
||||
"dependencies": {
|
||||
"@anthropic-ai/sdk": "0.71.2",
|
||||
"@google/genai": "1.34.0",
|
||||
"@mistralai/mistralai": "1.10.0",
|
||||
"@sinclair/typebox": "^0.34.41",
|
||||
"ajv": "^8.17.1",
|
||||
"ajv-formats": "^3.0.1",
|
||||
"chalk": "^5.6.2",
|
||||
"openai": "6.10.0",
|
||||
"partial-json": "^0.1.7",
|
||||
"zod-to-json-schema": "^3.24.6"
|
||||
},
|
||||
"keywords": [
|
||||
"ai",
|
||||
"llm",
|
||||
"openai",
|
||||
"anthropic",
|
||||
"gemini",
|
||||
"unified",
|
||||
"api"
|
||||
],
|
||||
"author": "Mario Zechner",
|
||||
"license": "MIT",
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "git+https://github.com/can1357/oh-my-pi.git",
|
||||
"directory": "packages/ai"
|
||||
},
|
||||
"engines": {
|
||||
"bun": ">=1.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^24.3.0",
|
||||
"canvas": "^3.2.0",
|
||||
"vitest": "^3.2.4"
|
||||
}
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,28 +0,0 @@
|
||||
#!/usr/bin/env bun
|
||||
|
||||
import { createCanvas } from "canvas";
|
||||
import { join } from "node:path";
|
||||
|
||||
// Create a 200x200 canvas
|
||||
const canvas = createCanvas(200, 200);
|
||||
const ctx = canvas.getContext("2d");
|
||||
|
||||
// Fill background with white
|
||||
ctx.fillStyle = "white";
|
||||
ctx.fillRect(0, 0, 200, 200);
|
||||
|
||||
// Draw a red circle in the center
|
||||
ctx.fillStyle = "red";
|
||||
ctx.beginPath();
|
||||
ctx.arc(100, 100, 50, 0, Math.PI * 2);
|
||||
ctx.fill();
|
||||
|
||||
// Save the image
|
||||
const buffer = canvas.toBuffer("image/png");
|
||||
const outputPath = join(import.meta.dir, "..", "test", "data", "red-circle.png");
|
||||
|
||||
// Ensure the directory exists
|
||||
await Bun.write(join(import.meta.dir, "..", "test", "data", ".keep"), "");
|
||||
|
||||
await Bun.write(outputPath, buffer);
|
||||
console.log(`Generated test image at: ${outputPath}`);
|
||||
Vendored
-14
@@ -1,14 +0,0 @@
|
||||
/**
|
||||
* Type declarations for Bun's import attributes.
|
||||
* These allow importing non-JS files as text at build time.
|
||||
*/
|
||||
|
||||
declare module "*.md" {
|
||||
const content: string;
|
||||
export default content;
|
||||
}
|
||||
|
||||
declare module "*.txt" {
|
||||
const content: string;
|
||||
export default content;
|
||||
}
|
||||
@@ -1,188 +0,0 @@
|
||||
#!/usr/bin/env bun
|
||||
|
||||
import { logger } from "@oh-my-pi/pi-coding-agent";
|
||||
import { loginAnthropic } from "./utils/oauth/anthropic";
|
||||
import { loginGitHubCopilot } from "./utils/oauth/github-copilot";
|
||||
import { loginAntigravity } from "./utils/oauth/google-antigravity";
|
||||
import { loginGeminiCli } from "./utils/oauth/google-gemini-cli";
|
||||
import { getOAuthProviders } from "./utils/oauth/index";
|
||||
import { loginOpenAICodex } from "./utils/oauth/openai-codex";
|
||||
import type { OAuthCredentials, OAuthProvider } from "./utils/oauth/types";
|
||||
|
||||
const AUTH_FILE = "auth.json";
|
||||
const PROVIDERS = getOAuthProviders();
|
||||
|
||||
function prompt(question: string): Promise<string> {
|
||||
return new Promise((resolve) => {
|
||||
process.stdout.write(question);
|
||||
process.stdin.resume();
|
||||
process.stdin.once("data", (data) => {
|
||||
process.stdin.pause();
|
||||
resolve(data.toString().trim());
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
async function loadAuth(): Promise<Record<string, { type: "oauth" } & OAuthCredentials>> {
|
||||
const file = Bun.file(AUTH_FILE);
|
||||
if (!(await file.exists())) return {};
|
||||
try {
|
||||
return await file.json();
|
||||
} catch (err) {
|
||||
logger.debug("Failed to parse config file", { error: String(err) });
|
||||
return {};
|
||||
}
|
||||
}
|
||||
|
||||
async function saveAuth(auth: Record<string, { type: "oauth" } & OAuthCredentials>): Promise<void> {
|
||||
await Bun.write(AUTH_FILE, JSON.stringify(auth, null, 2));
|
||||
}
|
||||
|
||||
async function login(provider: OAuthProvider): Promise<void> {
|
||||
const promptFn = (msg: string) => prompt(`${msg} `);
|
||||
|
||||
let credentials: OAuthCredentials;
|
||||
|
||||
switch (provider) {
|
||||
case "anthropic":
|
||||
credentials = await loginAnthropic(
|
||||
(url) => {
|
||||
console.log(`\nOpen this URL in your browser:\n${url}\n`);
|
||||
},
|
||||
async () => {
|
||||
return await promptFn("Paste the authorization code:");
|
||||
},
|
||||
);
|
||||
break;
|
||||
|
||||
case "github-copilot":
|
||||
credentials = await loginGitHubCopilot({
|
||||
onAuth: (url, instructions) => {
|
||||
console.log(`\nOpen this URL in your browser:\n${url}`);
|
||||
if (instructions) console.log(instructions);
|
||||
console.log();
|
||||
},
|
||||
onPrompt: async (p) => {
|
||||
return await promptFn(`${p.message}${p.placeholder ? ` (${p.placeholder})` : ""}:`);
|
||||
},
|
||||
onProgress: (msg) => console.log(msg),
|
||||
});
|
||||
break;
|
||||
|
||||
case "google-gemini-cli":
|
||||
credentials = await loginGeminiCli(
|
||||
(info) => {
|
||||
console.log(`\nOpen this URL in your browser:\n${info.url}`);
|
||||
if (info.instructions) console.log(info.instructions);
|
||||
console.log();
|
||||
},
|
||||
(msg) => console.log(msg),
|
||||
);
|
||||
break;
|
||||
|
||||
case "google-antigravity":
|
||||
credentials = await loginAntigravity(
|
||||
(info) => {
|
||||
console.log(`\nOpen this URL in your browser:\n${info.url}`);
|
||||
if (info.instructions) console.log(info.instructions);
|
||||
console.log();
|
||||
},
|
||||
(msg) => console.log(msg),
|
||||
);
|
||||
break;
|
||||
case "openai-codex":
|
||||
credentials = await loginOpenAICodex({
|
||||
onAuth: (info) => {
|
||||
console.log(`\nOpen this URL in your browser:\n${info.url}`);
|
||||
if (info.instructions) console.log(info.instructions);
|
||||
console.log();
|
||||
},
|
||||
onPrompt: async (p) => {
|
||||
return await promptFn(`${p.message}${p.placeholder ? ` (${p.placeholder})` : ""}:`);
|
||||
},
|
||||
onProgress: (msg) => console.log(msg),
|
||||
});
|
||||
break;
|
||||
}
|
||||
|
||||
const auth = await loadAuth();
|
||||
auth[provider] = { type: "oauth", ...credentials };
|
||||
await saveAuth(auth);
|
||||
|
||||
console.log(`\nCredentials saved to ${AUTH_FILE}`);
|
||||
}
|
||||
|
||||
async function main(): Promise<void> {
|
||||
const args = process.argv.slice(2);
|
||||
const command = args[0];
|
||||
|
||||
if (!command || command === "help" || command === "--help" || command === "-h") {
|
||||
console.log(`Usage: npx @oh-my-pi/pi-ai <command> [provider]
|
||||
|
||||
Commands:
|
||||
login [provider] Login to an OAuth provider
|
||||
list List available providers
|
||||
|
||||
Providers:
|
||||
anthropic Anthropic (Claude Pro/Max)
|
||||
github-copilot GitHub Copilot
|
||||
google-gemini-cli Google Gemini CLI
|
||||
google-antigravity Antigravity (Gemini 3, Claude, GPT-OSS)
|
||||
openai-codex OpenAI Codex (ChatGPT Plus/Pro)
|
||||
|
||||
Examples:
|
||||
npx @oh-my-pi/pi-ai login # interactive provider selection
|
||||
npx @oh-my-pi/pi-ai login anthropic # login to specific provider
|
||||
npx @oh-my-pi/pi-ai list # list providers
|
||||
`);
|
||||
return;
|
||||
}
|
||||
|
||||
if (command === "list") {
|
||||
console.log("Available OAuth providers:\n");
|
||||
for (const p of PROVIDERS) {
|
||||
console.log(` ${p.id.padEnd(20)} ${p.name}`);
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
if (command === "login") {
|
||||
let provider = args[1] as OAuthProvider | undefined;
|
||||
|
||||
if (!provider) {
|
||||
console.log("Select a provider:\n");
|
||||
for (let i = 0; i < PROVIDERS.length; i++) {
|
||||
console.log(` ${i + 1}. ${PROVIDERS[i].name}`);
|
||||
}
|
||||
console.log();
|
||||
|
||||
const choice = await prompt(`Enter number (1-${PROVIDERS.length}): `);
|
||||
|
||||
const index = parseInt(choice, 10) - 1;
|
||||
if (index < 0 || index >= PROVIDERS.length) {
|
||||
console.error("Invalid selection");
|
||||
process.exit(1);
|
||||
}
|
||||
provider = PROVIDERS[index].id;
|
||||
}
|
||||
|
||||
if (!PROVIDERS.some((p) => p.id === provider)) {
|
||||
console.error(`Unknown provider: ${provider}`);
|
||||
console.error(`Use 'npx @oh-my-pi/pi-ai list' to see available providers`);
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
console.log(`Logging in to ${provider}...`);
|
||||
await login(provider);
|
||||
return;
|
||||
}
|
||||
|
||||
console.error(`Unknown command: ${command}`);
|
||||
console.error(`Use 'npx @oh-my-pi/pi-ai --help' for usage`);
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
main().catch((err) => {
|
||||
console.error("Error:", err.message);
|
||||
process.exit(1);
|
||||
});
|
||||
@@ -1,15 +0,0 @@
|
||||
/// <reference path="./bun-imports.d.ts" />
|
||||
|
||||
export * from "./models";
|
||||
export * from "./providers/anthropic";
|
||||
export * from "./providers/google";
|
||||
export * from "./providers/google-gemini-cli";
|
||||
export * from "./providers/openai-completions";
|
||||
export * from "./providers/openai-responses";
|
||||
export * from "./stream";
|
||||
export * from "./types";
|
||||
export * from "./utils/event-stream";
|
||||
export * from "./utils/oauth/index";
|
||||
export * from "./utils/overflow";
|
||||
export * from "./utils/typebox-helpers";
|
||||
export * from "./utils/validation";
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,75 +0,0 @@
|
||||
import { MODELS } from "./models.generated";
|
||||
import type { Api, KnownProvider, Model, Usage } from "./types";
|
||||
|
||||
const modelRegistry: Map<string, Map<string, Model<Api>>> = new Map();
|
||||
|
||||
// Initialize registry from MODELS on module load
|
||||
for (const [provider, models] of Object.entries(MODELS)) {
|
||||
const providerModels = new Map<string, Model<Api>>();
|
||||
for (const [id, model] of Object.entries(models)) {
|
||||
providerModels.set(id, model as Model<Api>);
|
||||
}
|
||||
modelRegistry.set(provider, providerModels);
|
||||
}
|
||||
|
||||
type ProviderModels = typeof MODELS;
|
||||
type ProviderWithModels = keyof ProviderModels;
|
||||
|
||||
type ModelApi<
|
||||
TProvider extends ProviderWithModels,
|
||||
TModelId extends keyof ProviderModels[TProvider],
|
||||
> = ProviderModels[TProvider][TModelId] extends { api: infer TApi } ? (TApi extends Api ? TApi : never) : never;
|
||||
|
||||
export function getModel<TProvider extends ProviderWithModels, TModelId extends keyof ProviderModels[TProvider]>(
|
||||
provider: TProvider,
|
||||
modelId: TModelId,
|
||||
): Model<ModelApi<TProvider, TModelId>>;
|
||||
export function getModel(provider: KnownProvider, modelId: string): Model<Api> | undefined;
|
||||
export function getModel(provider: KnownProvider, modelId: string): Model<Api> | undefined {
|
||||
return modelRegistry.get(provider)?.get(modelId as string) as Model<Api> | undefined;
|
||||
}
|
||||
|
||||
export function getProviders(): KnownProvider[] {
|
||||
return Array.from(modelRegistry.keys()) as KnownProvider[];
|
||||
}
|
||||
|
||||
export function getModels<TProvider extends ProviderWithModels>(
|
||||
provider: TProvider,
|
||||
): Model<ModelApi<TProvider, keyof ProviderModels[TProvider]>>[];
|
||||
export function getModels(provider: KnownProvider): Model<Api>[];
|
||||
export function getModels(provider: KnownProvider): Model<Api>[] {
|
||||
const models = modelRegistry.get(provider);
|
||||
return models ? (Array.from(models.values()) as Model<Api>[]) : [];
|
||||
}
|
||||
|
||||
export function calculateCost<TApi extends Api>(model: Model<TApi>, usage: Usage): Usage["cost"] {
|
||||
usage.cost.input = (model.cost.input / 1000000) * usage.input;
|
||||
usage.cost.output = (model.cost.output / 1000000) * usage.output;
|
||||
usage.cost.cacheRead = (model.cost.cacheRead / 1000000) * usage.cacheRead;
|
||||
usage.cost.cacheWrite = (model.cost.cacheWrite / 1000000) * usage.cacheWrite;
|
||||
usage.cost.total = usage.cost.input + usage.cost.output + usage.cost.cacheRead + usage.cost.cacheWrite;
|
||||
return usage.cost;
|
||||
}
|
||||
|
||||
/** Models that support xhigh thinking level */
|
||||
const XHIGH_MODELS = new Set(["gpt-5.1-codex-max", "gpt-5.2", "gpt-5.2-codex"]);
|
||||
|
||||
/**
|
||||
* Check if a model supports xhigh thinking level.
|
||||
* Currently only certain OpenAI models support this.
|
||||
*/
|
||||
export function supportsXhigh<TApi extends Api>(model: Model<TApi>): boolean {
|
||||
return XHIGH_MODELS.has(model.id);
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if two models are equal by comparing both their id and provider.
|
||||
* Returns false if either model is null or undefined.
|
||||
*/
|
||||
export function modelsAreEqual<TApi extends Api>(
|
||||
a: Model<TApi> | null | undefined,
|
||||
b: Model<TApi> | null | undefined,
|
||||
): boolean {
|
||||
if (!a || !b) return false;
|
||||
return a.id === b.id && a.provider === b.provider;
|
||||
}
|
||||
@@ -1,587 +0,0 @@
|
||||
import Anthropic from "@anthropic-ai/sdk";
|
||||
import type {
|
||||
ContentBlockParam,
|
||||
MessageCreateParamsStreaming,
|
||||
MessageParam,
|
||||
} from "@anthropic-ai/sdk/resources/messages.js";
|
||||
import { calculateCost } from "../models";
|
||||
import { getEnvApiKey } from "../stream";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
ImageContent,
|
||||
Message,
|
||||
Model,
|
||||
StopReason,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
Tool,
|
||||
ToolCall,
|
||||
ToolResultMessage,
|
||||
} from "../types";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream";
|
||||
import { parseStreamingJson } from "../utils/json-parse";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
|
||||
import { transformMessages } from "./transorm-messages";
|
||||
|
||||
/**
|
||||
* Convert content blocks to Anthropic API format
|
||||
*/
|
||||
function convertContentBlocks(content: (TextContent | ImageContent)[]):
|
||||
| string
|
||||
| Array<
|
||||
| { type: "text"; text: string }
|
||||
| {
|
||||
type: "image";
|
||||
source: {
|
||||
type: "base64";
|
||||
media_type: "image/jpeg" | "image/png" | "image/gif" | "image/webp";
|
||||
data: string;
|
||||
};
|
||||
}
|
||||
> {
|
||||
// If only text blocks, return as concatenated string for simplicity
|
||||
const hasImages = content.some((c) => c.type === "image");
|
||||
if (!hasImages) {
|
||||
return sanitizeSurrogates(content.map((c) => (c as TextContent).text).join("\n"));
|
||||
}
|
||||
|
||||
// If we have images, convert to content block array
|
||||
const blocks = content.map((block) => {
|
||||
if (block.type === "text") {
|
||||
return {
|
||||
type: "text" as const,
|
||||
text: sanitizeSurrogates(block.text),
|
||||
};
|
||||
}
|
||||
return {
|
||||
type: "image" as const,
|
||||
source: {
|
||||
type: "base64" as const,
|
||||
media_type: block.mimeType as "image/jpeg" | "image/png" | "image/gif" | "image/webp",
|
||||
data: block.data,
|
||||
},
|
||||
};
|
||||
});
|
||||
|
||||
// If only images (no text), add placeholder text block
|
||||
const hasText = blocks.some((b) => b.type === "text");
|
||||
if (!hasText) {
|
||||
blocks.unshift({
|
||||
type: "text" as const,
|
||||
text: "(see attached image)",
|
||||
});
|
||||
}
|
||||
|
||||
return blocks;
|
||||
}
|
||||
|
||||
export interface AnthropicOptions extends StreamOptions {
|
||||
thinkingEnabled?: boolean;
|
||||
thinkingBudgetTokens?: number;
|
||||
interleavedThinking?: boolean;
|
||||
toolChoice?: "auto" | "any" | "none" | { type: "tool"; name: string };
|
||||
}
|
||||
|
||||
export const streamAnthropic: StreamFunction<"anthropic-messages"> = (
|
||||
model: Model<"anthropic-messages">,
|
||||
context: Context,
|
||||
options?: AnthropicOptions,
|
||||
): AssistantMessageEventStream => {
|
||||
const stream = new AssistantMessageEventStream();
|
||||
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: "anthropic-messages" as Api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
try {
|
||||
const apiKey = options?.apiKey ?? getEnvApiKey(model.provider) ?? "";
|
||||
const { client, isOAuthToken } = createClient(model, apiKey, options?.interleavedThinking ?? true);
|
||||
const params = buildParams(model, context, isOAuthToken, options);
|
||||
const anthropicStream = client.messages.stream({ ...params, stream: true }, { signal: options?.signal });
|
||||
stream.push({ type: "start", partial: output });
|
||||
|
||||
type Block = (ThinkingContent | TextContent | (ToolCall & { partialJson: string })) & { index: number };
|
||||
const blocks = output.content as Block[];
|
||||
|
||||
for await (const event of anthropicStream) {
|
||||
if (event.type === "message_start") {
|
||||
// Capture initial token usage from message_start event
|
||||
// This ensures we have input token counts even if the stream is aborted early
|
||||
output.usage.input = event.message.usage.input_tokens || 0;
|
||||
output.usage.output = event.message.usage.output_tokens || 0;
|
||||
output.usage.cacheRead = event.message.usage.cache_read_input_tokens || 0;
|
||||
output.usage.cacheWrite = event.message.usage.cache_creation_input_tokens || 0;
|
||||
// Anthropic doesn't provide total_tokens, compute from components
|
||||
output.usage.totalTokens =
|
||||
output.usage.input + output.usage.output + output.usage.cacheRead + output.usage.cacheWrite;
|
||||
calculateCost(model, output.usage);
|
||||
} else if (event.type === "content_block_start") {
|
||||
if (event.content_block.type === "text") {
|
||||
const block: Block = {
|
||||
type: "text",
|
||||
text: "",
|
||||
index: event.index,
|
||||
};
|
||||
output.content.push(block);
|
||||
stream.push({ type: "text_start", contentIndex: output.content.length - 1, partial: output });
|
||||
} else if (event.content_block.type === "thinking") {
|
||||
const block: Block = {
|
||||
type: "thinking",
|
||||
thinking: "",
|
||||
thinkingSignature: "",
|
||||
index: event.index,
|
||||
};
|
||||
output.content.push(block);
|
||||
stream.push({ type: "thinking_start", contentIndex: output.content.length - 1, partial: output });
|
||||
} else if (event.content_block.type === "tool_use") {
|
||||
const block: Block = {
|
||||
type: "toolCall",
|
||||
id: event.content_block.id,
|
||||
name: event.content_block.name,
|
||||
arguments: event.content_block.input as Record<string, any>,
|
||||
partialJson: "",
|
||||
index: event.index,
|
||||
};
|
||||
output.content.push(block);
|
||||
stream.push({ type: "toolcall_start", contentIndex: output.content.length - 1, partial: output });
|
||||
}
|
||||
} else if (event.type === "content_block_delta") {
|
||||
if (event.delta.type === "text_delta") {
|
||||
const index = blocks.findIndex((b) => b.index === event.index);
|
||||
const block = blocks[index];
|
||||
if (block && block.type === "text") {
|
||||
block.text += event.delta.text;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: index,
|
||||
delta: event.delta.text,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
} else if (event.delta.type === "thinking_delta") {
|
||||
const index = blocks.findIndex((b) => b.index === event.index);
|
||||
const block = blocks[index];
|
||||
if (block && block.type === "thinking") {
|
||||
block.thinking += event.delta.thinking;
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: index,
|
||||
delta: event.delta.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
} else if (event.delta.type === "input_json_delta") {
|
||||
const index = blocks.findIndex((b) => b.index === event.index);
|
||||
const block = blocks[index];
|
||||
if (block && block.type === "toolCall") {
|
||||
block.partialJson += event.delta.partial_json;
|
||||
block.arguments = parseStreamingJson(block.partialJson);
|
||||
stream.push({
|
||||
type: "toolcall_delta",
|
||||
contentIndex: index,
|
||||
delta: event.delta.partial_json,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
} else if (event.delta.type === "signature_delta") {
|
||||
const index = blocks.findIndex((b) => b.index === event.index);
|
||||
const block = blocks[index];
|
||||
if (block && block.type === "thinking") {
|
||||
block.thinkingSignature = block.thinkingSignature || "";
|
||||
block.thinkingSignature += event.delta.signature;
|
||||
}
|
||||
}
|
||||
} else if (event.type === "content_block_stop") {
|
||||
const index = blocks.findIndex((b) => b.index === event.index);
|
||||
const block = blocks[index];
|
||||
if (block) {
|
||||
delete (block as any).index;
|
||||
if (block.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: index,
|
||||
content: block.text,
|
||||
partial: output,
|
||||
});
|
||||
} else if (block.type === "thinking") {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: index,
|
||||
content: block.thinking,
|
||||
partial: output,
|
||||
});
|
||||
} else if (block.type === "toolCall") {
|
||||
block.arguments = parseStreamingJson(block.partialJson);
|
||||
delete (block as any).partialJson;
|
||||
stream.push({
|
||||
type: "toolcall_end",
|
||||
contentIndex: index,
|
||||
toolCall: block,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (event.type === "message_delta") {
|
||||
if (event.delta.stop_reason) {
|
||||
output.stopReason = mapStopReason(event.delta.stop_reason);
|
||||
}
|
||||
output.usage.input = event.usage.input_tokens || 0;
|
||||
output.usage.output = event.usage.output_tokens || 0;
|
||||
output.usage.cacheRead = event.usage.cache_read_input_tokens || 0;
|
||||
output.usage.cacheWrite = event.usage.cache_creation_input_tokens || 0;
|
||||
// Anthropic doesn't provide total_tokens, compute from components
|
||||
output.usage.totalTokens =
|
||||
output.usage.input + output.usage.output + output.usage.cacheRead + output.usage.cacheWrite;
|
||||
calculateCost(model, output.usage);
|
||||
}
|
||||
}
|
||||
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
if (output.stopReason === "aborted" || output.stopReason === "error") {
|
||||
throw new Error("An unkown error ocurred");
|
||||
}
|
||||
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
for (const block of output.content) delete (block as any).index;
|
||||
output.stopReason = options?.signal?.aborted ? "aborted" : "error";
|
||||
output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
stream.push({ type: "error", reason: output.stopReason, error: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function createClient(
|
||||
model: Model<"anthropic-messages">,
|
||||
apiKey: string,
|
||||
interleavedThinking: boolean,
|
||||
): { client: Anthropic; isOAuthToken: boolean } {
|
||||
const betaFeatures = ["fine-grained-tool-streaming-2025-05-14"];
|
||||
if (interleavedThinking) {
|
||||
betaFeatures.push("interleaved-thinking-2025-05-14");
|
||||
}
|
||||
|
||||
if (apiKey.includes("sk-ant-oat")) {
|
||||
const defaultHeaders = {
|
||||
accept: "application/json",
|
||||
"anthropic-dangerous-direct-browser-access": "true",
|
||||
"anthropic-beta": `oauth-2025-04-20,${betaFeatures.join(",")}`,
|
||||
...(model.headers || {}),
|
||||
};
|
||||
|
||||
const client = new Anthropic({
|
||||
apiKey: null,
|
||||
authToken: apiKey,
|
||||
baseURL: model.baseUrl,
|
||||
defaultHeaders,
|
||||
dangerouslyAllowBrowser: true,
|
||||
});
|
||||
|
||||
return { client, isOAuthToken: true };
|
||||
} else {
|
||||
const defaultHeaders = {
|
||||
accept: "application/json",
|
||||
"anthropic-dangerous-direct-browser-access": "true",
|
||||
"anthropic-beta": betaFeatures.join(","),
|
||||
...(model.headers || {}),
|
||||
};
|
||||
|
||||
const client = new Anthropic({
|
||||
apiKey,
|
||||
baseURL: model.baseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
defaultHeaders,
|
||||
});
|
||||
|
||||
return { client, isOAuthToken: false };
|
||||
}
|
||||
}
|
||||
|
||||
function buildParams(
|
||||
model: Model<"anthropic-messages">,
|
||||
context: Context,
|
||||
isOAuthToken: boolean,
|
||||
options?: AnthropicOptions,
|
||||
): MessageCreateParamsStreaming {
|
||||
const params: MessageCreateParamsStreaming = {
|
||||
model: model.id,
|
||||
messages: convertMessages(context.messages, model),
|
||||
max_tokens: options?.maxTokens || (model.maxTokens / 3) | 0,
|
||||
stream: true,
|
||||
};
|
||||
|
||||
// For OAuth tokens, we MUST include Claude Code identity
|
||||
if (isOAuthToken) {
|
||||
params.system = [
|
||||
{
|
||||
type: "text",
|
||||
text: "You are Claude Code, Anthropic's official CLI for Claude.",
|
||||
cache_control: {
|
||||
type: "ephemeral",
|
||||
},
|
||||
},
|
||||
];
|
||||
if (context.systemPrompt) {
|
||||
params.system.push({
|
||||
type: "text",
|
||||
text: sanitizeSurrogates(context.systemPrompt),
|
||||
cache_control: {
|
||||
type: "ephemeral",
|
||||
},
|
||||
});
|
||||
}
|
||||
} else if (context.systemPrompt) {
|
||||
// Add cache control to system prompt for non-OAuth tokens
|
||||
params.system = [
|
||||
{
|
||||
type: "text",
|
||||
text: sanitizeSurrogates(context.systemPrompt),
|
||||
cache_control: {
|
||||
type: "ephemeral",
|
||||
},
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
if (options?.temperature !== undefined) {
|
||||
params.temperature = options.temperature;
|
||||
}
|
||||
|
||||
if (context.tools) {
|
||||
params.tools = convertTools(context.tools);
|
||||
}
|
||||
|
||||
if (options?.thinkingEnabled && model.reasoning) {
|
||||
params.thinking = {
|
||||
type: "enabled",
|
||||
budget_tokens: options.thinkingBudgetTokens || 1024,
|
||||
};
|
||||
}
|
||||
|
||||
if (options?.toolChoice) {
|
||||
if (typeof options.toolChoice === "string") {
|
||||
params.tool_choice = { type: options.toolChoice };
|
||||
} else {
|
||||
params.tool_choice = options.toolChoice;
|
||||
}
|
||||
}
|
||||
|
||||
return params;
|
||||
}
|
||||
|
||||
// Sanitize tool call IDs to match Anthropic's required pattern: ^[a-zA-Z0-9_-]+$
|
||||
function sanitizeToolCallId(id: string): string {
|
||||
// Replace any character that isn't alphanumeric, underscore, or hyphen with underscore
|
||||
return id.replace(/[^a-zA-Z0-9_-]/g, "_");
|
||||
}
|
||||
|
||||
function convertMessages(messages: Message[], model: Model<"anthropic-messages">): MessageParam[] {
|
||||
const params: MessageParam[] = [];
|
||||
|
||||
// Transform messages for cross-provider compatibility
|
||||
const transformedMessages = transformMessages(messages, model);
|
||||
|
||||
for (let i = 0; i < transformedMessages.length; i++) {
|
||||
const msg = transformedMessages[i];
|
||||
|
||||
if (msg.role === "user") {
|
||||
if (typeof msg.content === "string") {
|
||||
if (msg.content.trim().length > 0) {
|
||||
params.push({
|
||||
role: "user",
|
||||
content: sanitizeSurrogates(msg.content),
|
||||
});
|
||||
}
|
||||
} else {
|
||||
const blocks: ContentBlockParam[] = msg.content.map((item) => {
|
||||
if (item.type === "text") {
|
||||
return {
|
||||
type: "text",
|
||||
text: sanitizeSurrogates(item.text),
|
||||
};
|
||||
} else {
|
||||
return {
|
||||
type: "image",
|
||||
source: {
|
||||
type: "base64",
|
||||
media_type: item.mimeType as "image/jpeg" | "image/png" | "image/gif" | "image/webp",
|
||||
data: item.data,
|
||||
},
|
||||
};
|
||||
}
|
||||
});
|
||||
let filteredBlocks = !model?.input.includes("image") ? blocks.filter((b) => b.type !== "image") : blocks;
|
||||
filteredBlocks = filteredBlocks.filter((b) => {
|
||||
if (b.type === "text") {
|
||||
return b.text.trim().length > 0;
|
||||
}
|
||||
return true;
|
||||
});
|
||||
if (filteredBlocks.length === 0) continue;
|
||||
params.push({
|
||||
role: "user",
|
||||
content: filteredBlocks,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
const blocks: ContentBlockParam[] = [];
|
||||
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "text") {
|
||||
if (block.text.trim().length === 0) continue;
|
||||
blocks.push({
|
||||
type: "text",
|
||||
text: sanitizeSurrogates(block.text),
|
||||
});
|
||||
} else if (block.type === "thinking") {
|
||||
if (block.thinking.trim().length === 0) continue;
|
||||
// If thinking signature is missing/empty (e.g., from aborted stream),
|
||||
// convert to plain text block without <thinking> tags to avoid API rejection
|
||||
// and prevent Claude from mimicking the tags in responses
|
||||
if (!block.thinkingSignature || block.thinkingSignature.trim().length === 0) {
|
||||
blocks.push({
|
||||
type: "text",
|
||||
text: sanitizeSurrogates(block.thinking),
|
||||
});
|
||||
} else {
|
||||
blocks.push({
|
||||
type: "thinking",
|
||||
thinking: sanitizeSurrogates(block.thinking),
|
||||
signature: block.thinkingSignature,
|
||||
});
|
||||
}
|
||||
} else if (block.type === "toolCall") {
|
||||
blocks.push({
|
||||
type: "tool_use",
|
||||
id: sanitizeToolCallId(block.id),
|
||||
name: block.name,
|
||||
input: block.arguments,
|
||||
});
|
||||
}
|
||||
}
|
||||
if (blocks.length === 0) continue;
|
||||
params.push({
|
||||
role: "assistant",
|
||||
content: blocks,
|
||||
});
|
||||
} else if (msg.role === "toolResult") {
|
||||
// Collect all consecutive toolResult messages, needed for z.ai Anthropic endpoint
|
||||
const toolResults: ContentBlockParam[] = [];
|
||||
|
||||
// Add the current tool result
|
||||
toolResults.push({
|
||||
type: "tool_result",
|
||||
tool_use_id: sanitizeToolCallId(msg.toolCallId),
|
||||
content: convertContentBlocks(msg.content),
|
||||
is_error: msg.isError,
|
||||
});
|
||||
|
||||
// Look ahead for consecutive toolResult messages
|
||||
let j = i + 1;
|
||||
while (j < transformedMessages.length && transformedMessages[j].role === "toolResult") {
|
||||
const nextMsg = transformedMessages[j] as ToolResultMessage; // We know it's a toolResult
|
||||
toolResults.push({
|
||||
type: "tool_result",
|
||||
tool_use_id: sanitizeToolCallId(nextMsg.toolCallId),
|
||||
content: convertContentBlocks(nextMsg.content),
|
||||
is_error: nextMsg.isError,
|
||||
});
|
||||
j++;
|
||||
}
|
||||
|
||||
// Skip the messages we've already processed
|
||||
i = j - 1;
|
||||
|
||||
// Add a single user message with all tool results
|
||||
params.push({
|
||||
role: "user",
|
||||
content: toolResults,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Add cache_control to the last user message to cache conversation history
|
||||
if (params.length > 0) {
|
||||
const lastMessage = params[params.length - 1];
|
||||
if (lastMessage.role === "user") {
|
||||
// Add cache control to the last content block
|
||||
if (Array.isArray(lastMessage.content)) {
|
||||
const lastBlock = lastMessage.content[lastMessage.content.length - 1];
|
||||
if (
|
||||
lastBlock &&
|
||||
(lastBlock.type === "text" || lastBlock.type === "image" || lastBlock.type === "tool_result")
|
||||
) {
|
||||
(lastBlock as any).cache_control = { type: "ephemeral" };
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return params;
|
||||
}
|
||||
|
||||
function convertTools(tools: Tool[]): Anthropic.Messages.Tool[] {
|
||||
if (!tools) return [];
|
||||
|
||||
return tools.map((tool) => {
|
||||
const jsonSchema = tool.parameters as any; // TypeBox already generates JSON Schema
|
||||
|
||||
return {
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
input_schema: {
|
||||
type: "object" as const,
|
||||
properties: jsonSchema.properties || {},
|
||||
required: jsonSchema.required || [],
|
||||
},
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
function mapStopReason(reason: Anthropic.Messages.StopReason): StopReason {
|
||||
switch (reason) {
|
||||
case "end_turn":
|
||||
return "stop";
|
||||
case "max_tokens":
|
||||
return "length";
|
||||
case "tool_use":
|
||||
return "toolUse";
|
||||
case "refusal":
|
||||
return "error";
|
||||
case "pause_turn": // Stop is good enough -> resubmit
|
||||
return "stop";
|
||||
case "stop_sequence":
|
||||
return "stop"; // We don't supply stop sequences, so this should never happen
|
||||
default: {
|
||||
const _exhaustive: never = reason;
|
||||
throw new Error(`Unhandled stop reason: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,603 +0,0 @@
|
||||
/**
|
||||
* Google Gemini CLI / Antigravity provider.
|
||||
* Shared implementation for both google-gemini-cli and google-antigravity providers.
|
||||
* Uses the Cloud Code Assist API endpoint to access Gemini and Claude models.
|
||||
*/
|
||||
|
||||
import type { Content, ThinkingConfig } from "@google/genai";
|
||||
import { calculateCost } from "../models";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
Model,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
ToolCall,
|
||||
} from "../types";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
import { convertMessages, convertTools, mapStopReasonString, mapToolChoice } from "./google-shared";
|
||||
|
||||
/**
|
||||
* Thinking level for Gemini 3 models.
|
||||
* Mirrors Google's ThinkingLevel enum values.
|
||||
*/
|
||||
export type GoogleThinkingLevel = "THINKING_LEVEL_UNSPECIFIED" | "MINIMAL" | "LOW" | "MEDIUM" | "HIGH";
|
||||
|
||||
export interface GoogleGeminiCliOptions extends StreamOptions {
|
||||
toolChoice?: "auto" | "none" | "any";
|
||||
/**
|
||||
* Thinking/reasoning configuration.
|
||||
* - Gemini 2.x models: use `budgetTokens` to set the thinking budget
|
||||
* - Gemini 3 models (gemini-3-pro-*, gemini-3-flash-*): use `level` instead
|
||||
*
|
||||
* When using `streamSimple`, this is handled automatically based on the model.
|
||||
*/
|
||||
thinking?: {
|
||||
enabled: boolean;
|
||||
/** Thinking budget in tokens. Use for Gemini 2.x models. */
|
||||
budgetTokens?: number;
|
||||
/** Thinking level. Use for Gemini 3 models (LOW/HIGH for Pro, MINIMAL/LOW/MEDIUM/HIGH for Flash). */
|
||||
level?: GoogleThinkingLevel;
|
||||
};
|
||||
projectId?: string;
|
||||
}
|
||||
|
||||
const DEFAULT_ENDPOINT = "https://cloudcode-pa.googleapis.com";
|
||||
// Headers for Gemini CLI (prod endpoint)
|
||||
const GEMINI_CLI_HEADERS = {
|
||||
"User-Agent": "google-cloud-sdk vscode_cloudshelleditor/0.1",
|
||||
"X-Goog-Api-Client": "gl-node/22.17.0",
|
||||
"Client-Metadata": JSON.stringify({
|
||||
ideType: "IDE_UNSPECIFIED",
|
||||
platform: "PLATFORM_UNSPECIFIED",
|
||||
pluginType: "GEMINI",
|
||||
}),
|
||||
};
|
||||
|
||||
// Headers for Antigravity (sandbox endpoint) - requires specific User-Agent
|
||||
const ANTIGRAVITY_HEADERS = {
|
||||
"User-Agent": "antigravity/1.11.5 darwin/arm64",
|
||||
"X-Goog-Api-Client": "google-cloud-sdk vscode_cloudshelleditor/0.1",
|
||||
"Client-Metadata": JSON.stringify({
|
||||
ideType: "IDE_UNSPECIFIED",
|
||||
platform: "PLATFORM_UNSPECIFIED",
|
||||
pluginType: "GEMINI",
|
||||
}),
|
||||
};
|
||||
|
||||
// Counter for generating unique tool call IDs
|
||||
let toolCallCounter = 0;
|
||||
|
||||
// Retry configuration
|
||||
const MAX_RETRIES = 3;
|
||||
const BASE_DELAY_MS = 1000;
|
||||
|
||||
/**
|
||||
* Extract retry delay from Gemini error response (in milliseconds).
|
||||
* Parses patterns like:
|
||||
* - "Your quota will reset after 39s"
|
||||
* - "Your quota will reset after 18h31m10s"
|
||||
* - "Please retry in Xs" or "Please retry in Xms"
|
||||
* - "retryDelay": "34.074824224s" (JSON field)
|
||||
*/
|
||||
function extractRetryDelay(errorText: string): number | undefined {
|
||||
// Pattern 1: "Your quota will reset after ..." (formats: "18h31m10s", "10m15s", "6s", "39s")
|
||||
const durationMatch = errorText.match(/reset after (?:(\d+)h)?(?:(\d+)m)?(\d+(?:\.\d+)?)s/i);
|
||||
if (durationMatch) {
|
||||
const hours = durationMatch[1] ? parseInt(durationMatch[1], 10) : 0;
|
||||
const minutes = durationMatch[2] ? parseInt(durationMatch[2], 10) : 0;
|
||||
const seconds = parseFloat(durationMatch[3]);
|
||||
if (!Number.isNaN(seconds)) {
|
||||
const totalMs = ((hours * 60 + minutes) * 60 + seconds) * 1000;
|
||||
if (totalMs > 0) {
|
||||
return Math.ceil(totalMs + 1000); // Add 1s buffer
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Pattern 2: "Please retry in X[ms|s]"
|
||||
const retryInMatch = errorText.match(/Please retry in ([0-9.]+)(ms|s)/i);
|
||||
if (retryInMatch?.[1]) {
|
||||
const value = parseFloat(retryInMatch[1]);
|
||||
if (!Number.isNaN(value) && value > 0) {
|
||||
const ms = retryInMatch[2].toLowerCase() === "ms" ? value : value * 1000;
|
||||
return Math.ceil(ms + 1000);
|
||||
}
|
||||
}
|
||||
|
||||
// Pattern 3: "retryDelay": "34.074824224s" (JSON field in error details)
|
||||
const retryDelayMatch = errorText.match(/"retryDelay":\s*"([0-9.]+)(ms|s)"/i);
|
||||
if (retryDelayMatch?.[1]) {
|
||||
const value = parseFloat(retryDelayMatch[1]);
|
||||
if (!Number.isNaN(value) && value > 0) {
|
||||
const ms = retryDelayMatch[2].toLowerCase() === "ms" ? value : value * 1000;
|
||||
return Math.ceil(ms + 1000);
|
||||
}
|
||||
}
|
||||
|
||||
return undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if an error is retryable (rate limit, server error, etc.)
|
||||
*/
|
||||
function isRetryableError(status: number, errorText: string): boolean {
|
||||
if (status === 429 || status === 500 || status === 502 || status === 503 || status === 504) {
|
||||
return true;
|
||||
}
|
||||
return /resource.?exhausted|rate.?limit|overloaded|service.?unavailable/i.test(errorText);
|
||||
}
|
||||
|
||||
/**
|
||||
* Sleep for a given number of milliseconds, respecting abort signal.
|
||||
*/
|
||||
function sleep(ms: number, signal?: AbortSignal): Promise<void> {
|
||||
return new Promise((resolve, reject) => {
|
||||
if (signal?.aborted) {
|
||||
reject(new Error("Request was aborted"));
|
||||
return;
|
||||
}
|
||||
const timeout = setTimeout(resolve, ms);
|
||||
signal?.addEventListener("abort", () => {
|
||||
clearTimeout(timeout);
|
||||
reject(new Error("Request was aborted"));
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
interface CloudCodeAssistRequest {
|
||||
project: string;
|
||||
model: string;
|
||||
request: {
|
||||
contents: Content[];
|
||||
systemInstruction?: { parts: { text: string }[] };
|
||||
generationConfig?: {
|
||||
maxOutputTokens?: number;
|
||||
temperature?: number;
|
||||
thinkingConfig?: ThinkingConfig;
|
||||
};
|
||||
tools?: ReturnType<typeof convertTools>;
|
||||
toolConfig?: {
|
||||
functionCallingConfig: {
|
||||
mode: ReturnType<typeof mapToolChoice>;
|
||||
};
|
||||
};
|
||||
};
|
||||
userAgent?: string;
|
||||
requestId?: string;
|
||||
}
|
||||
|
||||
interface CloudCodeAssistResponseChunk {
|
||||
response?: {
|
||||
candidates?: Array<{
|
||||
content?: {
|
||||
role: string;
|
||||
parts?: Array<{
|
||||
text?: string;
|
||||
thought?: boolean;
|
||||
thoughtSignature?: string;
|
||||
functionCall?: {
|
||||
name: string;
|
||||
args: Record<string, unknown>;
|
||||
id?: string;
|
||||
};
|
||||
}>;
|
||||
};
|
||||
finishReason?: string;
|
||||
}>;
|
||||
usageMetadata?: {
|
||||
promptTokenCount?: number;
|
||||
candidatesTokenCount?: number;
|
||||
thoughtsTokenCount?: number;
|
||||
totalTokenCount?: number;
|
||||
cachedContentTokenCount?: number;
|
||||
};
|
||||
modelVersion?: string;
|
||||
responseId?: string;
|
||||
};
|
||||
traceId?: string;
|
||||
}
|
||||
|
||||
export const streamGoogleGeminiCli: StreamFunction<"google-gemini-cli"> = (
|
||||
model: Model<"google-gemini-cli">,
|
||||
context: Context,
|
||||
options?: GoogleGeminiCliOptions,
|
||||
): AssistantMessageEventStream => {
|
||||
const stream = new AssistantMessageEventStream();
|
||||
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: "google-gemini-cli" as Api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
try {
|
||||
// apiKey is JSON-encoded: { token, projectId }
|
||||
const apiKeyRaw = options?.apiKey;
|
||||
if (!apiKeyRaw) {
|
||||
throw new Error("Google Cloud Code Assist requires OAuth authentication. Use /login to authenticate.");
|
||||
}
|
||||
|
||||
let accessToken: string;
|
||||
let projectId: string;
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(apiKeyRaw) as { token: string; projectId: string };
|
||||
accessToken = parsed.token;
|
||||
projectId = parsed.projectId;
|
||||
} catch {
|
||||
throw new Error("Invalid Google Cloud Code Assist credentials. Use /login to re-authenticate.");
|
||||
}
|
||||
|
||||
if (!accessToken || !projectId) {
|
||||
throw new Error("Missing token or projectId in Google Cloud credentials. Use /login to re-authenticate.");
|
||||
}
|
||||
|
||||
const requestBody = buildRequest(model, context, projectId, options);
|
||||
const endpoint = model.baseUrl || DEFAULT_ENDPOINT;
|
||||
const url = `${endpoint}/v1internal:streamGenerateContent?alt=sse`;
|
||||
|
||||
// Use Antigravity headers for sandbox endpoint, otherwise Gemini CLI headers
|
||||
const isAntigravity = endpoint.includes("sandbox.googleapis.com");
|
||||
const headers = isAntigravity ? ANTIGRAVITY_HEADERS : GEMINI_CLI_HEADERS;
|
||||
|
||||
// Fetch with retry logic for rate limits and transient errors
|
||||
let response: Response | undefined;
|
||||
let lastError: Error | undefined;
|
||||
|
||||
for (let attempt = 0; attempt <= MAX_RETRIES; attempt++) {
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
try {
|
||||
response = await fetch(url, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
Authorization: `Bearer ${accessToken}`,
|
||||
"Content-Type": "application/json",
|
||||
Accept: "text/event-stream",
|
||||
...headers,
|
||||
},
|
||||
body: JSON.stringify(requestBody),
|
||||
signal: options?.signal,
|
||||
});
|
||||
|
||||
if (response.ok) {
|
||||
break; // Success, exit retry loop
|
||||
}
|
||||
|
||||
const errorText = await response.text();
|
||||
|
||||
// Check if retryable
|
||||
if (attempt < MAX_RETRIES && isRetryableError(response.status, errorText)) {
|
||||
// Use server-provided delay or exponential backoff
|
||||
const serverDelay = extractRetryDelay(errorText);
|
||||
const delayMs = serverDelay ?? BASE_DELAY_MS * 2 ** attempt;
|
||||
await sleep(delayMs, options?.signal);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Not retryable or max retries exceeded
|
||||
throw new Error(`Cloud Code Assist API error (${response.status}): ${errorText}`);
|
||||
} catch (error) {
|
||||
if (error instanceof Error && error.message === "Request was aborted") {
|
||||
throw error;
|
||||
}
|
||||
lastError = error instanceof Error ? error : new Error(String(error));
|
||||
// Network errors are retryable
|
||||
if (attempt < MAX_RETRIES) {
|
||||
const delayMs = BASE_DELAY_MS * 2 ** attempt;
|
||||
await sleep(delayMs, options?.signal);
|
||||
continue;
|
||||
}
|
||||
throw lastError;
|
||||
}
|
||||
}
|
||||
|
||||
if (!response || !response.ok) {
|
||||
throw lastError ?? new Error("Failed to get response after retries");
|
||||
}
|
||||
|
||||
if (!response.body) {
|
||||
throw new Error("No response body");
|
||||
}
|
||||
|
||||
stream.push({ type: "start", partial: output });
|
||||
|
||||
let currentBlock: TextContent | ThinkingContent | null = null;
|
||||
const blocks = output.content;
|
||||
const blockIndex = () => blocks.length - 1;
|
||||
|
||||
// Read SSE stream
|
||||
const reader = response.body.getReader();
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = "";
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
buffer += decoder.decode(value, { stream: true });
|
||||
const lines = buffer.split("\n");
|
||||
buffer = lines.pop() || "";
|
||||
|
||||
for (const line of lines) {
|
||||
if (!line.startsWith("data:")) continue;
|
||||
|
||||
const jsonStr = line.slice(5).trim();
|
||||
if (!jsonStr) continue;
|
||||
|
||||
let chunk: CloudCodeAssistResponseChunk;
|
||||
try {
|
||||
chunk = JSON.parse(jsonStr);
|
||||
} catch {
|
||||
continue;
|
||||
}
|
||||
|
||||
// Unwrap the response
|
||||
const responseData = chunk.response;
|
||||
if (!responseData) continue;
|
||||
|
||||
const candidate = responseData.candidates?.[0];
|
||||
if (candidate?.content?.parts) {
|
||||
for (const part of candidate.content.parts) {
|
||||
if (part.text !== undefined) {
|
||||
const isThinking = part.thought === true;
|
||||
if (
|
||||
!currentBlock ||
|
||||
(isThinking && currentBlock.type !== "thinking") ||
|
||||
(!isThinking && currentBlock.type !== "text")
|
||||
) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blocks.length - 1,
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
if (isThinking) {
|
||||
currentBlock = { type: "thinking", thinking: "", thinkingSignature: undefined };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
|
||||
} else {
|
||||
currentBlock = { type: "text", text: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
}
|
||||
if (currentBlock.type === "thinking") {
|
||||
currentBlock.thinking += part.text;
|
||||
currentBlock.thinkingSignature = part.thoughtSignature;
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: part.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
currentBlock.text += part.text;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: part.text,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (part.functionCall) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
currentBlock = null;
|
||||
}
|
||||
|
||||
const providedId = part.functionCall.id;
|
||||
const needsNewId =
|
||||
!providedId || output.content.some((b) => b.type === "toolCall" && b.id === providedId);
|
||||
const toolCallId = needsNewId
|
||||
? `${part.functionCall.name}_${Date.now()}_${++toolCallCounter}`
|
||||
: providedId;
|
||||
|
||||
const toolCall: ToolCall = {
|
||||
type: "toolCall",
|
||||
id: toolCallId,
|
||||
name: part.functionCall.name || "",
|
||||
arguments: part.functionCall.args as Record<string, unknown>,
|
||||
...(part.thoughtSignature && { thoughtSignature: part.thoughtSignature }),
|
||||
};
|
||||
|
||||
output.content.push(toolCall);
|
||||
stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
|
||||
stream.push({
|
||||
type: "toolcall_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: JSON.stringify(toolCall.arguments),
|
||||
partial: output,
|
||||
});
|
||||
stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (candidate?.finishReason) {
|
||||
output.stopReason = mapStopReasonString(candidate.finishReason);
|
||||
if (output.content.some((b) => b.type === "toolCall")) {
|
||||
output.stopReason = "toolUse";
|
||||
}
|
||||
}
|
||||
|
||||
if (responseData.usageMetadata) {
|
||||
// promptTokenCount includes cachedContentTokenCount, so subtract to get fresh input
|
||||
const promptTokens = responseData.usageMetadata.promptTokenCount || 0;
|
||||
const cacheReadTokens = responseData.usageMetadata.cachedContentTokenCount || 0;
|
||||
output.usage = {
|
||||
input: promptTokens - cacheReadTokens,
|
||||
output:
|
||||
(responseData.usageMetadata.candidatesTokenCount || 0) +
|
||||
(responseData.usageMetadata.thoughtsTokenCount || 0),
|
||||
cacheRead: cacheReadTokens,
|
||||
cacheWrite: 0,
|
||||
totalTokens: responseData.usageMetadata.totalTokenCount || 0,
|
||||
cost: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
total: 0,
|
||||
},
|
||||
};
|
||||
calculateCost(model, output.usage);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
if (output.stopReason === "aborted" || output.stopReason === "error") {
|
||||
throw new Error("An unknown error occurred");
|
||||
}
|
||||
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
for (const block of output.content) {
|
||||
if ("index" in block) {
|
||||
delete (block as { index?: number }).index;
|
||||
}
|
||||
}
|
||||
output.stopReason = options?.signal?.aborted ? "aborted" : "error";
|
||||
output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
stream.push({ type: "error", reason: output.stopReason, error: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function buildRequest(
|
||||
model: Model<"google-gemini-cli">,
|
||||
context: Context,
|
||||
projectId: string,
|
||||
options: GoogleGeminiCliOptions = {},
|
||||
): CloudCodeAssistRequest {
|
||||
const contents = convertMessages(model, context);
|
||||
|
||||
const generationConfig: CloudCodeAssistRequest["request"]["generationConfig"] = {};
|
||||
if (options.temperature !== undefined) {
|
||||
generationConfig.temperature = options.temperature;
|
||||
}
|
||||
if (options.maxTokens !== undefined) {
|
||||
generationConfig.maxOutputTokens = options.maxTokens;
|
||||
}
|
||||
|
||||
// Thinking config
|
||||
if (options.thinking?.enabled && model.reasoning) {
|
||||
generationConfig.thinkingConfig = {
|
||||
includeThoughts: true,
|
||||
};
|
||||
// Gemini 3 models use thinkingLevel, older models use thinkingBudget
|
||||
if (options.thinking.level !== undefined) {
|
||||
// Cast to any since our GoogleThinkingLevel mirrors Google's ThinkingLevel enum values
|
||||
generationConfig.thinkingConfig.thinkingLevel = options.thinking.level as any;
|
||||
} else if (options.thinking.budgetTokens !== undefined) {
|
||||
generationConfig.thinkingConfig.thinkingBudget = options.thinking.budgetTokens;
|
||||
}
|
||||
}
|
||||
|
||||
const request: CloudCodeAssistRequest["request"] = {
|
||||
contents,
|
||||
};
|
||||
|
||||
// System instruction must be object with parts, not plain string
|
||||
if (context.systemPrompt) {
|
||||
request.systemInstruction = {
|
||||
parts: [{ text: sanitizeSurrogates(context.systemPrompt) }],
|
||||
};
|
||||
}
|
||||
|
||||
if (Object.keys(generationConfig).length > 0) {
|
||||
request.generationConfig = generationConfig;
|
||||
}
|
||||
|
||||
if (context.tools && context.tools.length > 0) {
|
||||
request.tools = convertTools(context.tools);
|
||||
if (options.toolChoice) {
|
||||
request.toolConfig = {
|
||||
functionCallingConfig: {
|
||||
mode: mapToolChoice(options.toolChoice),
|
||||
},
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
project: projectId,
|
||||
model: model.id,
|
||||
request,
|
||||
userAgent: "pi-coding-agent",
|
||||
requestId: `pi-${Date.now()}-${Math.random().toString(36).slice(2, 11)}`,
|
||||
};
|
||||
}
|
||||
@@ -1,227 +0,0 @@
|
||||
/**
|
||||
* Shared utilities for Google Generative AI and Google Cloud Code Assist providers.
|
||||
*/
|
||||
|
||||
import { type Content, FinishReason, FunctionCallingConfigMode, type Part, type Schema } from "@google/genai";
|
||||
import type { Context, ImageContent, Model, StopReason, TextContent, Tool } from "../types";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
import { transformMessages } from "./transorm-messages";
|
||||
|
||||
type GoogleApiType = "google-generative-ai" | "google-gemini-cli" | "google-vertex";
|
||||
|
||||
/**
|
||||
* Convert internal messages to Gemini Content[] format.
|
||||
*/
|
||||
export function convertMessages<T extends GoogleApiType>(model: Model<T>, context: Context): Content[] {
|
||||
const contents: Content[] = [];
|
||||
const transformedMessages = transformMessages(context.messages, model);
|
||||
|
||||
for (const msg of transformedMessages) {
|
||||
if (msg.role === "user") {
|
||||
if (typeof msg.content === "string") {
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: [{ text: sanitizeSurrogates(msg.content) }],
|
||||
});
|
||||
} else {
|
||||
const parts: Part[] = msg.content.map((item) => {
|
||||
if (item.type === "text") {
|
||||
return { text: sanitizeSurrogates(item.text) };
|
||||
} else {
|
||||
return {
|
||||
inlineData: {
|
||||
mimeType: item.mimeType,
|
||||
data: item.data,
|
||||
},
|
||||
};
|
||||
}
|
||||
});
|
||||
const filteredParts = !model.input.includes("image") ? parts.filter((p) => p.text !== undefined) : parts;
|
||||
if (filteredParts.length === 0) continue;
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: filteredParts,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
const parts: Part[] = [];
|
||||
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "text") {
|
||||
// Skip empty text blocks - they can cause issues with some models (e.g. Claude via Antigravity)
|
||||
if (!block.text || block.text.trim() === "") continue;
|
||||
parts.push({ text: sanitizeSurrogates(block.text) });
|
||||
} else if (block.type === "thinking") {
|
||||
// Thinking blocks require signatures for Claude via Antigravity.
|
||||
// If signature is missing (e.g. from GPT-OSS), convert to regular text with delimiters.
|
||||
if (block.thinkingSignature) {
|
||||
parts.push({
|
||||
thought: true,
|
||||
text: sanitizeSurrogates(block.thinking),
|
||||
thoughtSignature: block.thinkingSignature,
|
||||
});
|
||||
} else {
|
||||
parts.push({
|
||||
text: `<thinking>\n${sanitizeSurrogates(block.thinking)}\n</thinking>`,
|
||||
});
|
||||
}
|
||||
} else if (block.type === "toolCall") {
|
||||
const part: Part = {
|
||||
functionCall: {
|
||||
id: block.id,
|
||||
name: block.name,
|
||||
args: block.arguments,
|
||||
},
|
||||
};
|
||||
if (block.thoughtSignature) {
|
||||
part.thoughtSignature = block.thoughtSignature;
|
||||
}
|
||||
parts.push(part);
|
||||
}
|
||||
}
|
||||
|
||||
if (parts.length === 0) continue;
|
||||
contents.push({
|
||||
role: "model",
|
||||
parts,
|
||||
});
|
||||
} else if (msg.role === "toolResult") {
|
||||
// Extract text and image content
|
||||
const textContent = msg.content.filter((c): c is TextContent => c.type === "text");
|
||||
const textResult = textContent.map((c) => c.text).join("\n");
|
||||
const imageContent = model.input.includes("image")
|
||||
? msg.content.filter((c): c is ImageContent => c.type === "image")
|
||||
: [];
|
||||
|
||||
const hasText = textResult.length > 0;
|
||||
const hasImages = imageContent.length > 0;
|
||||
|
||||
// Gemini 3 supports multimodal function responses with images nested inside functionResponse.parts
|
||||
// See: https://ai.google.dev/gemini-api/docs/function-calling#multimodal
|
||||
// Older models don't support this, so we put images in a separate user message.
|
||||
const supportsMultimodalFunctionResponse = model.id.includes("gemini-3");
|
||||
|
||||
// Use "output" key for success, "error" key for errors as per SDK documentation
|
||||
const responseValue = hasText ? sanitizeSurrogates(textResult) : hasImages ? "(see attached image)" : "";
|
||||
|
||||
const imageParts: Part[] = imageContent.map((imageBlock) => ({
|
||||
inlineData: {
|
||||
mimeType: imageBlock.mimeType,
|
||||
data: imageBlock.data,
|
||||
},
|
||||
}));
|
||||
|
||||
const functionResponsePart: Part = {
|
||||
functionResponse: {
|
||||
id: msg.toolCallId,
|
||||
name: msg.toolName,
|
||||
response: msg.isError ? { error: responseValue } : { output: responseValue },
|
||||
// Nest images inside functionResponse.parts for Gemini 3
|
||||
...(hasImages && supportsMultimodalFunctionResponse && { parts: imageParts }),
|
||||
},
|
||||
};
|
||||
|
||||
// Cloud Code Assist API requires all function responses to be in a single user turn.
|
||||
// Check if the last content is already a user turn with function responses and merge.
|
||||
const lastContent = contents[contents.length - 1];
|
||||
if (lastContent?.role === "user" && lastContent.parts?.some((p) => p.functionResponse)) {
|
||||
lastContent.parts.push(functionResponsePart);
|
||||
} else {
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: [functionResponsePart],
|
||||
});
|
||||
}
|
||||
|
||||
// For older models, add images in a separate user message
|
||||
if (hasImages && !supportsMultimodalFunctionResponse) {
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: [{ text: "Tool result image:" }, ...imageParts],
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return contents;
|
||||
}
|
||||
|
||||
/**
|
||||
* Convert tools to Gemini function declarations format.
|
||||
*/
|
||||
export function convertTools(
|
||||
tools: Tool[],
|
||||
): { functionDeclarations: { name: string; description?: string; parameters: Schema }[] }[] | undefined {
|
||||
if (tools.length === 0) return undefined;
|
||||
return [
|
||||
{
|
||||
functionDeclarations: tools.map((tool) => ({
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters as Schema,
|
||||
})),
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
/**
|
||||
* Map tool choice string to Gemini FunctionCallingConfigMode.
|
||||
*/
|
||||
export function mapToolChoice(choice: string): FunctionCallingConfigMode {
|
||||
switch (choice) {
|
||||
case "auto":
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
case "none":
|
||||
return FunctionCallingConfigMode.NONE;
|
||||
case "any":
|
||||
return FunctionCallingConfigMode.ANY;
|
||||
default:
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Map Gemini FinishReason to our StopReason.
|
||||
*/
|
||||
export function mapStopReason(reason: FinishReason): StopReason {
|
||||
switch (reason) {
|
||||
case FinishReason.STOP:
|
||||
return "stop";
|
||||
case FinishReason.MAX_TOKENS:
|
||||
return "length";
|
||||
case FinishReason.BLOCKLIST:
|
||||
case FinishReason.PROHIBITED_CONTENT:
|
||||
case FinishReason.SPII:
|
||||
case FinishReason.SAFETY:
|
||||
case FinishReason.IMAGE_SAFETY:
|
||||
case FinishReason.IMAGE_PROHIBITED_CONTENT:
|
||||
case FinishReason.IMAGE_RECITATION:
|
||||
case FinishReason.IMAGE_OTHER:
|
||||
case FinishReason.RECITATION:
|
||||
case FinishReason.FINISH_REASON_UNSPECIFIED:
|
||||
case FinishReason.OTHER:
|
||||
case FinishReason.LANGUAGE:
|
||||
case FinishReason.MALFORMED_FUNCTION_CALL:
|
||||
case FinishReason.UNEXPECTED_TOOL_CALL:
|
||||
case FinishReason.NO_IMAGE:
|
||||
return "error";
|
||||
default: {
|
||||
const _exhaustive: never = reason;
|
||||
throw new Error(`Unhandled stop reason: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Map string finish reason to our StopReason (for raw API responses).
|
||||
*/
|
||||
export function mapStopReasonString(reason: string): StopReason {
|
||||
switch (reason) {
|
||||
case "STOP":
|
||||
return "stop";
|
||||
case "MAX_TOKENS":
|
||||
return "length";
|
||||
default:
|
||||
return "error";
|
||||
}
|
||||
}
|
||||
@@ -1,355 +0,0 @@
|
||||
import {
|
||||
type GenerateContentConfig,
|
||||
type GenerateContentParameters,
|
||||
GoogleGenAI,
|
||||
type ThinkingConfig,
|
||||
ThinkingLevel,
|
||||
} from "@google/genai";
|
||||
import { calculateCost } from "../models";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
Model,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
ToolCall,
|
||||
} from "../types";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
import type { GoogleThinkingLevel } from "./google-gemini-cli";
|
||||
import { convertMessages, convertTools, mapStopReason, mapToolChoice } from "./google-shared";
|
||||
|
||||
export interface GoogleVertexOptions extends StreamOptions {
|
||||
toolChoice?: "auto" | "none" | "any";
|
||||
thinking?: {
|
||||
enabled: boolean;
|
||||
budgetTokens?: number; // -1 for dynamic, 0 to disable
|
||||
level?: GoogleThinkingLevel;
|
||||
};
|
||||
project?: string;
|
||||
location?: string;
|
||||
}
|
||||
|
||||
const API_VERSION = "v1";
|
||||
|
||||
const THINKING_LEVEL_MAP: Record<GoogleThinkingLevel, ThinkingLevel> = {
|
||||
THINKING_LEVEL_UNSPECIFIED: ThinkingLevel.THINKING_LEVEL_UNSPECIFIED,
|
||||
MINIMAL: ThinkingLevel.MINIMAL,
|
||||
LOW: ThinkingLevel.LOW,
|
||||
MEDIUM: ThinkingLevel.MEDIUM,
|
||||
HIGH: ThinkingLevel.HIGH,
|
||||
};
|
||||
|
||||
// Counter for generating unique tool call IDs
|
||||
let toolCallCounter = 0;
|
||||
|
||||
export const streamGoogleVertex: StreamFunction<"google-vertex"> = (
|
||||
model: Model<"google-vertex">,
|
||||
context: Context,
|
||||
options?: GoogleVertexOptions,
|
||||
): AssistantMessageEventStream => {
|
||||
const stream = new AssistantMessageEventStream();
|
||||
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: "google-vertex" as Api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
try {
|
||||
const project = resolveProject(options);
|
||||
const location = resolveLocation(options);
|
||||
const client = createClient(model, project, location);
|
||||
const params = buildParams(model, context, options);
|
||||
const googleStream = await client.models.generateContentStream(params);
|
||||
|
||||
stream.push({ type: "start", partial: output });
|
||||
let currentBlock: TextContent | ThinkingContent | null = null;
|
||||
const blocks = output.content;
|
||||
const blockIndex = () => blocks.length - 1;
|
||||
for await (const chunk of googleStream) {
|
||||
const candidate = chunk.candidates?.[0];
|
||||
if (candidate?.content?.parts) {
|
||||
for (const part of candidate.content.parts) {
|
||||
if (part.text !== undefined) {
|
||||
const isThinking = part.thought === true;
|
||||
if (
|
||||
!currentBlock ||
|
||||
(isThinking && currentBlock.type !== "thinking") ||
|
||||
(!isThinking && currentBlock.type !== "text")
|
||||
) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blocks.length - 1,
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
if (isThinking) {
|
||||
currentBlock = { type: "thinking", thinking: "", thinkingSignature: undefined };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
|
||||
} else {
|
||||
currentBlock = { type: "text", text: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
}
|
||||
if (currentBlock.type === "thinking") {
|
||||
currentBlock.thinking += part.text;
|
||||
currentBlock.thinkingSignature = part.thoughtSignature;
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: part.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
currentBlock.text += part.text;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: part.text,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (part.functionCall) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
currentBlock = null;
|
||||
}
|
||||
|
||||
const providedId = part.functionCall.id;
|
||||
const needsNewId =
|
||||
!providedId || output.content.some((b) => b.type === "toolCall" && b.id === providedId);
|
||||
const toolCallId = needsNewId
|
||||
? `${part.functionCall.name}_${Date.now()}_${++toolCallCounter}`
|
||||
: providedId;
|
||||
|
||||
const toolCall: ToolCall = {
|
||||
type: "toolCall",
|
||||
id: toolCallId,
|
||||
name: part.functionCall.name || "",
|
||||
arguments: part.functionCall.args as Record<string, any>,
|
||||
...(part.thoughtSignature && { thoughtSignature: part.thoughtSignature }),
|
||||
};
|
||||
|
||||
output.content.push(toolCall);
|
||||
stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
|
||||
stream.push({
|
||||
type: "toolcall_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: JSON.stringify(toolCall.arguments),
|
||||
partial: output,
|
||||
});
|
||||
stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (candidate?.finishReason) {
|
||||
output.stopReason = mapStopReason(candidate.finishReason);
|
||||
if (output.content.some((b) => b.type === "toolCall")) {
|
||||
output.stopReason = "toolUse";
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.usageMetadata) {
|
||||
output.usage = {
|
||||
input: chunk.usageMetadata.promptTokenCount || 0,
|
||||
output:
|
||||
(chunk.usageMetadata.candidatesTokenCount || 0) + (chunk.usageMetadata.thoughtsTokenCount || 0),
|
||||
cacheRead: chunk.usageMetadata.cachedContentTokenCount || 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: chunk.usageMetadata.totalTokenCount || 0,
|
||||
cost: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
total: 0,
|
||||
},
|
||||
};
|
||||
calculateCost(model, output.usage);
|
||||
}
|
||||
}
|
||||
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
if (output.stopReason === "aborted" || output.stopReason === "error") {
|
||||
throw new Error("An unknown error occurred");
|
||||
}
|
||||
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
// Remove internal index property used during streaming
|
||||
for (const block of output.content) {
|
||||
if ("index" in block) {
|
||||
delete (block as { index?: number }).index;
|
||||
}
|
||||
}
|
||||
output.stopReason = options?.signal?.aborted ? "aborted" : "error";
|
||||
output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
stream.push({ type: "error", reason: output.stopReason, error: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function createClient(model: Model<"google-vertex">, project: string, location: string): GoogleGenAI {
|
||||
const httpOptions: { headers?: Record<string, string> } = {};
|
||||
|
||||
if (model.headers) {
|
||||
httpOptions.headers = { ...model.headers };
|
||||
}
|
||||
|
||||
const hasHttpOptions = Object.values(httpOptions).some(Boolean);
|
||||
|
||||
return new GoogleGenAI({
|
||||
vertexai: true,
|
||||
project,
|
||||
location,
|
||||
apiVersion: API_VERSION,
|
||||
httpOptions: hasHttpOptions ? httpOptions : undefined,
|
||||
});
|
||||
}
|
||||
|
||||
function resolveProject(options?: GoogleVertexOptions): string {
|
||||
const project = options?.project || process.env.GOOGLE_CLOUD_PROJECT || process.env.GCLOUD_PROJECT;
|
||||
if (!project) {
|
||||
throw new Error(
|
||||
"Vertex AI requires a project ID. Set GOOGLE_CLOUD_PROJECT/GCLOUD_PROJECT or pass project in options.",
|
||||
);
|
||||
}
|
||||
return project;
|
||||
}
|
||||
|
||||
function resolveLocation(options?: GoogleVertexOptions): string {
|
||||
const location = options?.location || process.env.GOOGLE_CLOUD_LOCATION;
|
||||
if (!location) {
|
||||
throw new Error("Vertex AI requires a location. Set GOOGLE_CLOUD_LOCATION or pass location in options.");
|
||||
}
|
||||
return location;
|
||||
}
|
||||
|
||||
function buildParams(
|
||||
model: Model<"google-vertex">,
|
||||
context: Context,
|
||||
options: GoogleVertexOptions = {},
|
||||
): GenerateContentParameters {
|
||||
const contents = convertMessages(model, context);
|
||||
|
||||
const generationConfig: GenerateContentConfig = {};
|
||||
if (options.temperature !== undefined) {
|
||||
generationConfig.temperature = options.temperature;
|
||||
}
|
||||
if (options.maxTokens !== undefined) {
|
||||
generationConfig.maxOutputTokens = options.maxTokens;
|
||||
}
|
||||
|
||||
const config: GenerateContentConfig = {
|
||||
...(Object.keys(generationConfig).length > 0 && generationConfig),
|
||||
...(context.systemPrompt && { systemInstruction: sanitizeSurrogates(context.systemPrompt) }),
|
||||
...(context.tools && context.tools.length > 0 && { tools: convertTools(context.tools) }),
|
||||
};
|
||||
|
||||
if (context.tools && context.tools.length > 0 && options.toolChoice) {
|
||||
config.toolConfig = {
|
||||
functionCallingConfig: {
|
||||
mode: mapToolChoice(options.toolChoice),
|
||||
},
|
||||
};
|
||||
} else {
|
||||
config.toolConfig = undefined;
|
||||
}
|
||||
|
||||
if (options.thinking?.enabled && model.reasoning) {
|
||||
const thinkingConfig: ThinkingConfig = { includeThoughts: true };
|
||||
if (options.thinking.level !== undefined) {
|
||||
thinkingConfig.thinkingLevel = THINKING_LEVEL_MAP[options.thinking.level];
|
||||
} else if (options.thinking.budgetTokens !== undefined) {
|
||||
thinkingConfig.thinkingBudget = options.thinking.budgetTokens;
|
||||
}
|
||||
config.thinkingConfig = thinkingConfig;
|
||||
}
|
||||
|
||||
if (options.signal) {
|
||||
if (options.signal.aborted) {
|
||||
throw new Error("Request aborted");
|
||||
}
|
||||
config.abortSignal = options.signal;
|
||||
}
|
||||
|
||||
const params: GenerateContentParameters = {
|
||||
model: model.id,
|
||||
contents,
|
||||
config,
|
||||
};
|
||||
|
||||
return params;
|
||||
}
|
||||
@@ -1,324 +0,0 @@
|
||||
import {
|
||||
type GenerateContentConfig,
|
||||
type GenerateContentParameters,
|
||||
GoogleGenAI,
|
||||
type ThinkingConfig,
|
||||
} from "@google/genai";
|
||||
import { calculateCost } from "../models";
|
||||
import { getEnvApiKey } from "../stream";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
Model,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
ToolCall,
|
||||
} from "../types";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
import type { GoogleThinkingLevel } from "./google-gemini-cli";
|
||||
import { convertMessages, convertTools, mapStopReason, mapToolChoice } from "./google-shared";
|
||||
|
||||
export interface GoogleOptions extends StreamOptions {
|
||||
toolChoice?: "auto" | "none" | "any";
|
||||
thinking?: {
|
||||
enabled: boolean;
|
||||
budgetTokens?: number; // -1 for dynamic, 0 to disable
|
||||
level?: GoogleThinkingLevel;
|
||||
};
|
||||
}
|
||||
|
||||
// Counter for generating unique tool call IDs
|
||||
let toolCallCounter = 0;
|
||||
|
||||
export const streamGoogle: StreamFunction<"google-generative-ai"> = (
|
||||
model: Model<"google-generative-ai">,
|
||||
context: Context,
|
||||
options?: GoogleOptions,
|
||||
): AssistantMessageEventStream => {
|
||||
const stream = new AssistantMessageEventStream();
|
||||
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: "google-generative-ai" as Api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
try {
|
||||
const apiKey = options?.apiKey || getEnvApiKey(model.provider) || "";
|
||||
const client = createClient(model, apiKey);
|
||||
const params = buildParams(model, context, options);
|
||||
const googleStream = await client.models.generateContentStream(params);
|
||||
|
||||
stream.push({ type: "start", partial: output });
|
||||
let currentBlock: TextContent | ThinkingContent | null = null;
|
||||
const blocks = output.content;
|
||||
const blockIndex = () => blocks.length - 1;
|
||||
for await (const chunk of googleStream) {
|
||||
const candidate = chunk.candidates?.[0];
|
||||
if (candidate?.content?.parts) {
|
||||
for (const part of candidate.content.parts) {
|
||||
if (part.text !== undefined) {
|
||||
const isThinking = part.thought === true;
|
||||
if (
|
||||
!currentBlock ||
|
||||
(isThinking && currentBlock.type !== "thinking") ||
|
||||
(!isThinking && currentBlock.type !== "text")
|
||||
) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blocks.length - 1,
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
if (isThinking) {
|
||||
currentBlock = { type: "thinking", thinking: "", thinkingSignature: undefined };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
|
||||
} else {
|
||||
currentBlock = { type: "text", text: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
}
|
||||
if (currentBlock.type === "thinking") {
|
||||
currentBlock.thinking += part.text;
|
||||
currentBlock.thinkingSignature = part.thoughtSignature;
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: part.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
currentBlock.text += part.text;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: part.text,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (part.functionCall) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
currentBlock = null;
|
||||
}
|
||||
|
||||
// Generate unique ID if not provided or if it's a duplicate
|
||||
const providedId = part.functionCall.id;
|
||||
const needsNewId =
|
||||
!providedId || output.content.some((b) => b.type === "toolCall" && b.id === providedId);
|
||||
const toolCallId = needsNewId
|
||||
? `${part.functionCall.name}_${Date.now()}_${++toolCallCounter}`
|
||||
: providedId;
|
||||
|
||||
const toolCall: ToolCall = {
|
||||
type: "toolCall",
|
||||
id: toolCallId,
|
||||
name: part.functionCall.name || "",
|
||||
arguments: part.functionCall.args as Record<string, any>,
|
||||
...(part.thoughtSignature && { thoughtSignature: part.thoughtSignature }),
|
||||
};
|
||||
|
||||
output.content.push(toolCall);
|
||||
stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
|
||||
stream.push({
|
||||
type: "toolcall_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: JSON.stringify(toolCall.arguments),
|
||||
partial: output,
|
||||
});
|
||||
stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (candidate?.finishReason) {
|
||||
output.stopReason = mapStopReason(candidate.finishReason);
|
||||
if (output.content.some((b) => b.type === "toolCall")) {
|
||||
output.stopReason = "toolUse";
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.usageMetadata) {
|
||||
output.usage = {
|
||||
input: chunk.usageMetadata.promptTokenCount || 0,
|
||||
output:
|
||||
(chunk.usageMetadata.candidatesTokenCount || 0) + (chunk.usageMetadata.thoughtsTokenCount || 0),
|
||||
cacheRead: chunk.usageMetadata.cachedContentTokenCount || 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: chunk.usageMetadata.totalTokenCount || 0,
|
||||
cost: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
total: 0,
|
||||
},
|
||||
};
|
||||
calculateCost(model, output.usage);
|
||||
}
|
||||
}
|
||||
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
if (output.stopReason === "aborted" || output.stopReason === "error") {
|
||||
throw new Error("An unkown error ocurred");
|
||||
}
|
||||
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
// Remove internal index property used during streaming
|
||||
for (const block of output.content) {
|
||||
if ("index" in block) {
|
||||
delete (block as { index?: number }).index;
|
||||
}
|
||||
}
|
||||
output.stopReason = options?.signal?.aborted ? "aborted" : "error";
|
||||
output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
stream.push({ type: "error", reason: output.stopReason, error: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function createClient(model: Model<"google-generative-ai">, apiKey?: string): GoogleGenAI {
|
||||
const httpOptions: { baseUrl?: string; apiVersion?: string; headers?: Record<string, string> } = {};
|
||||
if (model.baseUrl) {
|
||||
httpOptions.baseUrl = model.baseUrl;
|
||||
httpOptions.apiVersion = ""; // baseUrl already includes version path, don't append
|
||||
}
|
||||
if (model.headers) {
|
||||
httpOptions.headers = model.headers;
|
||||
}
|
||||
|
||||
return new GoogleGenAI({
|
||||
apiKey,
|
||||
httpOptions: Object.keys(httpOptions).length > 0 ? httpOptions : undefined,
|
||||
});
|
||||
}
|
||||
|
||||
function buildParams(
|
||||
model: Model<"google-generative-ai">,
|
||||
context: Context,
|
||||
options: GoogleOptions = {},
|
||||
): GenerateContentParameters {
|
||||
const contents = convertMessages(model, context);
|
||||
|
||||
const generationConfig: GenerateContentConfig = {};
|
||||
if (options.temperature !== undefined) {
|
||||
generationConfig.temperature = options.temperature;
|
||||
}
|
||||
if (options.maxTokens !== undefined) {
|
||||
generationConfig.maxOutputTokens = options.maxTokens;
|
||||
}
|
||||
|
||||
const config: GenerateContentConfig = {
|
||||
...(Object.keys(generationConfig).length > 0 && generationConfig),
|
||||
...(context.systemPrompt && { systemInstruction: sanitizeSurrogates(context.systemPrompt) }),
|
||||
...(context.tools && context.tools.length > 0 && { tools: convertTools(context.tools) }),
|
||||
};
|
||||
|
||||
if (context.tools && context.tools.length > 0 && options.toolChoice) {
|
||||
config.toolConfig = {
|
||||
functionCallingConfig: {
|
||||
mode: mapToolChoice(options.toolChoice),
|
||||
},
|
||||
};
|
||||
} else {
|
||||
config.toolConfig = undefined;
|
||||
}
|
||||
|
||||
if (options.thinking?.enabled && model.reasoning) {
|
||||
const thinkingConfig: ThinkingConfig = { includeThoughts: true };
|
||||
if (options.thinking.level !== undefined) {
|
||||
// Cast to any since our GoogleThinkingLevel mirrors Google's ThinkingLevel enum values
|
||||
thinkingConfig.thinkingLevel = options.thinking.level as any;
|
||||
} else if (options.thinking.budgetTokens !== undefined) {
|
||||
thinkingConfig.thinkingBudget = options.thinking.budgetTokens;
|
||||
}
|
||||
config.thinkingConfig = thinkingConfig;
|
||||
}
|
||||
|
||||
if (options.signal) {
|
||||
if (options.signal.aborted) {
|
||||
throw new Error("Request aborted");
|
||||
}
|
||||
config.abortSignal = options.signal;
|
||||
}
|
||||
|
||||
const params: GenerateContentParameters = {
|
||||
model: model.id,
|
||||
contents,
|
||||
config,
|
||||
};
|
||||
|
||||
return params;
|
||||
}
|
||||
@@ -1,628 +0,0 @@
|
||||
import type {
|
||||
ResponseFunctionToolCall,
|
||||
ResponseInput,
|
||||
ResponseInputContent,
|
||||
ResponseInputImage,
|
||||
ResponseInputText,
|
||||
ResponseOutputMessage,
|
||||
ResponseReasoningItem,
|
||||
} from "openai/resources/responses/responses.js";
|
||||
import { calculateCost } from "../models";
|
||||
import { getEnvApiKey } from "../stream";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
Model,
|
||||
StopReason,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
Tool,
|
||||
ToolCall,
|
||||
} from "../types";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream";
|
||||
import { parseStreamingJson } from "../utils/json-parse";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
import {
|
||||
CODEX_BASE_URL,
|
||||
JWT_CLAIM_PATH,
|
||||
OPENAI_HEADER_VALUES,
|
||||
OPENAI_HEADERS,
|
||||
URL_PATHS,
|
||||
} from "./openai-codex/constants";
|
||||
import { getCodexInstructions } from "./openai-codex/prompts/codex";
|
||||
import { buildCodexPiBridge } from "./openai-codex/prompts/pi-codex-bridge";
|
||||
import { buildCodexSystemPrompt } from "./openai-codex/prompts/system-prompt";
|
||||
import {
|
||||
type CodexRequestOptions,
|
||||
normalizeModel,
|
||||
type RequestBody,
|
||||
transformRequestBody,
|
||||
} from "./openai-codex/request-transformer";
|
||||
import { parseCodexError, parseCodexSseStream } from "./openai-codex/response-handler";
|
||||
import { transformMessages } from "./transorm-messages";
|
||||
|
||||
export interface OpenAICodexResponsesOptions extends StreamOptions {
|
||||
reasoningEffort?: "none" | "minimal" | "low" | "medium" | "high" | "xhigh";
|
||||
reasoningSummary?: "auto" | "concise" | "detailed" | "off" | "on" | null;
|
||||
textVerbosity?: "low" | "medium" | "high";
|
||||
include?: string[];
|
||||
codexMode?: boolean;
|
||||
}
|
||||
|
||||
const CODEX_DEBUG = process.env.PI_CODEX_DEBUG === "1" || process.env.PI_CODEX_DEBUG === "true";
|
||||
|
||||
export const streamOpenAICodexResponses: StreamFunction<"openai-codex-responses"> = (
|
||||
model: Model<"openai-codex-responses">,
|
||||
context: Context,
|
||||
options?: OpenAICodexResponsesOptions,
|
||||
): AssistantMessageEventStream => {
|
||||
const stream = new AssistantMessageEventStream();
|
||||
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: "openai-codex-responses" as Api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
try {
|
||||
const apiKey = options?.apiKey || getEnvApiKey(model.provider) || "";
|
||||
if (!apiKey) {
|
||||
throw new Error(`No API key for provider: ${model.provider}`);
|
||||
}
|
||||
|
||||
const accountId = getAccountId(apiKey);
|
||||
const baseUrl = model.baseUrl || CODEX_BASE_URL;
|
||||
const baseWithSlash = baseUrl.endsWith("/") ? baseUrl : `${baseUrl}/`;
|
||||
const url = rewriteUrlForCodex(new URL(URL_PATHS.RESPONSES.slice(1), baseWithSlash).toString());
|
||||
|
||||
const messages = convertMessages(model, context);
|
||||
const params: RequestBody = {
|
||||
model: model.id,
|
||||
input: messages,
|
||||
stream: true,
|
||||
prompt_cache_key: options?.sessionId,
|
||||
};
|
||||
|
||||
if (options?.maxTokens) {
|
||||
params.max_output_tokens = options.maxTokens;
|
||||
}
|
||||
|
||||
if (options?.temperature !== undefined) {
|
||||
params.temperature = options.temperature;
|
||||
}
|
||||
|
||||
if (context.tools) {
|
||||
params.tools = convertTools(context.tools);
|
||||
}
|
||||
|
||||
const normalizedModel = normalizeModel(params.model);
|
||||
const codexInstructions = await getCodexInstructions(normalizedModel);
|
||||
const bridgeText = buildCodexPiBridge(context.tools);
|
||||
const systemPrompt = buildCodexSystemPrompt({
|
||||
codexInstructions,
|
||||
bridgeText,
|
||||
userSystemPrompt: context.systemPrompt,
|
||||
});
|
||||
|
||||
params.model = normalizedModel;
|
||||
params.instructions = systemPrompt.instructions;
|
||||
|
||||
const codexOptions: CodexRequestOptions = {
|
||||
reasoningEffort: options?.reasoningEffort,
|
||||
reasoningSummary: options?.reasoningSummary ?? undefined,
|
||||
textVerbosity: options?.textVerbosity,
|
||||
include: options?.include,
|
||||
};
|
||||
|
||||
const transformedBody = await transformRequestBody(params, codexOptions, systemPrompt);
|
||||
|
||||
const reasoningEffort = transformedBody.reasoning?.effort ?? null;
|
||||
const headers = createCodexHeaders(model.headers, accountId, apiKey, options?.sessionId);
|
||||
logCodexDebug("codex request", {
|
||||
url,
|
||||
model: params.model,
|
||||
reasoningEffort,
|
||||
headers: redactHeaders(headers),
|
||||
});
|
||||
|
||||
const response = await fetch(url, {
|
||||
method: "POST",
|
||||
headers,
|
||||
body: JSON.stringify(transformedBody),
|
||||
signal: options?.signal,
|
||||
});
|
||||
|
||||
logCodexDebug("codex response", {
|
||||
url: response.url,
|
||||
status: response.status,
|
||||
statusText: response.statusText,
|
||||
contentType: response.headers.get("content-type") || null,
|
||||
cfRay: response.headers.get("cf-ray") || null,
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const info = await parseCodexError(response);
|
||||
throw new Error(info.friendlyMessage || info.message);
|
||||
}
|
||||
|
||||
if (!response.body) {
|
||||
throw new Error("No response body");
|
||||
}
|
||||
|
||||
stream.push({ type: "start", partial: output });
|
||||
|
||||
let currentItem: ResponseReasoningItem | ResponseOutputMessage | ResponseFunctionToolCall | null = null;
|
||||
let currentBlock: ThinkingContent | TextContent | (ToolCall & { partialJson: string }) | null = null;
|
||||
const blocks = output.content;
|
||||
const blockIndex = () => blocks.length - 1;
|
||||
|
||||
for await (const rawEvent of parseCodexSseStream(response)) {
|
||||
const eventType = typeof rawEvent.type === "string" ? rawEvent.type : "";
|
||||
if (!eventType) continue;
|
||||
|
||||
if (eventType === "response.output_item.added") {
|
||||
const item = rawEvent.item as ResponseReasoningItem | ResponseOutputMessage | ResponseFunctionToolCall;
|
||||
if (item.type === "reasoning") {
|
||||
currentItem = item;
|
||||
currentBlock = { type: "thinking", thinking: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
|
||||
} else if (item.type === "message") {
|
||||
currentItem = item;
|
||||
currentBlock = { type: "text", text: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
|
||||
} else if (item.type === "function_call") {
|
||||
currentItem = item;
|
||||
currentBlock = {
|
||||
type: "toolCall",
|
||||
id: `${item.call_id}|${item.id}`,
|
||||
name: item.name,
|
||||
arguments: {},
|
||||
partialJson: item.arguments || "",
|
||||
};
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
} else if (eventType === "response.reasoning_summary_part.added") {
|
||||
if (currentItem && currentItem.type === "reasoning") {
|
||||
currentItem.summary = currentItem.summary || [];
|
||||
currentItem.summary.push((rawEvent as { part: ResponseReasoningItem["summary"][number] }).part);
|
||||
}
|
||||
} else if (eventType === "response.reasoning_summary_text.delta") {
|
||||
if (currentItem && currentItem.type === "reasoning" && currentBlock?.type === "thinking") {
|
||||
currentItem.summary = currentItem.summary || [];
|
||||
const lastPart = currentItem.summary[currentItem.summary.length - 1];
|
||||
if (lastPart) {
|
||||
const delta = (rawEvent as { delta?: string }).delta || "";
|
||||
currentBlock.thinking += delta;
|
||||
lastPart.text += delta;
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (eventType === "response.reasoning_summary_part.done") {
|
||||
if (currentItem && currentItem.type === "reasoning" && currentBlock?.type === "thinking") {
|
||||
currentItem.summary = currentItem.summary || [];
|
||||
const lastPart = currentItem.summary[currentItem.summary.length - 1];
|
||||
if (lastPart) {
|
||||
currentBlock.thinking += "\n\n";
|
||||
lastPart.text += "\n\n";
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: "\n\n",
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (eventType === "response.content_part.added") {
|
||||
if (currentItem && currentItem.type === "message") {
|
||||
currentItem.content = currentItem.content || [];
|
||||
const part = (rawEvent as { part?: ResponseOutputMessage["content"][number] }).part;
|
||||
if (part && (part.type === "output_text" || part.type === "refusal")) {
|
||||
currentItem.content.push(part);
|
||||
}
|
||||
}
|
||||
} else if (eventType === "response.output_text.delta") {
|
||||
if (currentItem && currentItem.type === "message" && currentBlock?.type === "text") {
|
||||
const lastPart = currentItem.content[currentItem.content.length - 1];
|
||||
if (lastPart && lastPart.type === "output_text") {
|
||||
const delta = (rawEvent as { delta?: string }).delta || "";
|
||||
currentBlock.text += delta;
|
||||
lastPart.text += delta;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (eventType === "response.refusal.delta") {
|
||||
if (currentItem && currentItem.type === "message" && currentBlock?.type === "text") {
|
||||
const lastPart = currentItem.content[currentItem.content.length - 1];
|
||||
if (lastPart && lastPart.type === "refusal") {
|
||||
const delta = (rawEvent as { delta?: string }).delta || "";
|
||||
currentBlock.text += delta;
|
||||
lastPart.refusal += delta;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (eventType === "response.function_call_arguments.delta") {
|
||||
if (currentItem && currentItem.type === "function_call" && currentBlock?.type === "toolCall") {
|
||||
const delta = (rawEvent as { delta?: string }).delta || "";
|
||||
currentBlock.partialJson += delta;
|
||||
currentBlock.arguments = parseStreamingJson(currentBlock.partialJson);
|
||||
stream.push({
|
||||
type: "toolcall_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
} else if (eventType === "response.output_item.done") {
|
||||
const item = rawEvent.item as ResponseReasoningItem | ResponseOutputMessage | ResponseFunctionToolCall;
|
||||
if (item.type === "reasoning" && currentBlock?.type === "thinking") {
|
||||
currentBlock.thinking = item.summary?.map((s) => s.text).join("\n\n") || "";
|
||||
currentBlock.thinkingSignature = JSON.stringify(item);
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
currentBlock = null;
|
||||
} else if (item.type === "message" && currentBlock?.type === "text") {
|
||||
currentBlock.text = item.content.map((c) => (c.type === "output_text" ? c.text : c.refusal)).join("");
|
||||
currentBlock.textSignature = item.id;
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
currentBlock = null;
|
||||
} else if (item.type === "function_call") {
|
||||
const toolCall: ToolCall = {
|
||||
type: "toolCall",
|
||||
id: `${item.call_id}|${item.id}`,
|
||||
name: item.name,
|
||||
arguments: JSON.parse(item.arguments),
|
||||
};
|
||||
stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
|
||||
}
|
||||
} else if (eventType === "response.completed" || eventType === "response.done") {
|
||||
const response = (
|
||||
rawEvent as {
|
||||
response?: {
|
||||
usage?: {
|
||||
input_tokens?: number;
|
||||
output_tokens?: number;
|
||||
total_tokens?: number;
|
||||
input_tokens_details?: { cached_tokens?: number };
|
||||
};
|
||||
status?: string;
|
||||
};
|
||||
}
|
||||
).response;
|
||||
if (response?.usage) {
|
||||
const cachedTokens = response.usage.input_tokens_details?.cached_tokens || 0;
|
||||
output.usage = {
|
||||
input: (response.usage.input_tokens || 0) - cachedTokens,
|
||||
output: response.usage.output_tokens || 0,
|
||||
cacheRead: cachedTokens,
|
||||
cacheWrite: 0,
|
||||
totalTokens: response.usage.total_tokens || 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
};
|
||||
}
|
||||
calculateCost(model, output.usage);
|
||||
output.stopReason = mapStopReason(response?.status);
|
||||
if (output.content.some((b) => b.type === "toolCall") && output.stopReason === "stop") {
|
||||
output.stopReason = "toolUse";
|
||||
}
|
||||
} else if (eventType === "error") {
|
||||
const code = (rawEvent as { code?: string }).code || "";
|
||||
const message = (rawEvent as { message?: string }).message || "Unknown error";
|
||||
throw new Error(code ? `Error Code ${code}: ${message}` : message);
|
||||
} else if (eventType === "response.failed") {
|
||||
throw new Error("Unknown error");
|
||||
}
|
||||
}
|
||||
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
if (output.stopReason === "aborted" || output.stopReason === "error") {
|
||||
throw new Error("An unknown error occurred");
|
||||
}
|
||||
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
for (const block of output.content) delete (block as { index?: number }).index;
|
||||
output.stopReason = options?.signal?.aborted ? "aborted" : "error";
|
||||
output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
stream.push({ type: "error", reason: output.stopReason, error: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function createCodexHeaders(
|
||||
initHeaders: Record<string, string> | undefined,
|
||||
accountId: string,
|
||||
accessToken: string,
|
||||
promptCacheKey?: string,
|
||||
): Headers {
|
||||
const headers = new Headers(initHeaders ?? {});
|
||||
headers.delete("x-api-key");
|
||||
headers.set("Authorization", `Bearer ${accessToken}`);
|
||||
headers.set(OPENAI_HEADERS.ACCOUNT_ID, accountId);
|
||||
headers.set(OPENAI_HEADERS.BETA, OPENAI_HEADER_VALUES.BETA_RESPONSES);
|
||||
headers.set(OPENAI_HEADERS.ORIGINATOR, OPENAI_HEADER_VALUES.ORIGINATOR_CODEX);
|
||||
|
||||
if (promptCacheKey) {
|
||||
headers.set(OPENAI_HEADERS.CONVERSATION_ID, promptCacheKey);
|
||||
headers.set(OPENAI_HEADERS.SESSION_ID, promptCacheKey);
|
||||
} else {
|
||||
headers.delete(OPENAI_HEADERS.CONVERSATION_ID);
|
||||
headers.delete(OPENAI_HEADERS.SESSION_ID);
|
||||
}
|
||||
|
||||
headers.set("accept", "text/event-stream");
|
||||
headers.set("content-type", "application/json");
|
||||
return headers;
|
||||
}
|
||||
|
||||
function logCodexDebug(message: string, details?: Record<string, unknown>): void {
|
||||
if (!CODEX_DEBUG) return;
|
||||
if (details) {
|
||||
console.error(`[codex] ${message}`, details);
|
||||
return;
|
||||
}
|
||||
console.error(`[codex] ${message}`);
|
||||
}
|
||||
|
||||
function redactHeaders(headers: Headers): Record<string, string> {
|
||||
const redacted: Record<string, string> = {};
|
||||
for (const [key, value] of headers.entries()) {
|
||||
const lower = key.toLowerCase();
|
||||
if (lower === "authorization") {
|
||||
redacted[key] = "Bearer [redacted]";
|
||||
continue;
|
||||
}
|
||||
if (
|
||||
lower.includes("account") ||
|
||||
lower.includes("session") ||
|
||||
lower.includes("conversation") ||
|
||||
lower === "cookie"
|
||||
) {
|
||||
redacted[key] = "[redacted]";
|
||||
continue;
|
||||
}
|
||||
redacted[key] = value;
|
||||
}
|
||||
return redacted;
|
||||
}
|
||||
|
||||
function rewriteUrlForCodex(url: string): string {
|
||||
return url.replace(URL_PATHS.RESPONSES, URL_PATHS.CODEX_RESPONSES);
|
||||
}
|
||||
|
||||
type JwtPayload = {
|
||||
[JWT_CLAIM_PATH]?: {
|
||||
chatgpt_account_id?: string;
|
||||
};
|
||||
[key: string]: unknown;
|
||||
};
|
||||
|
||||
function decodeJwt(token: string): JwtPayload | null {
|
||||
try {
|
||||
const parts = token.split(".");
|
||||
if (parts.length !== 3) return null;
|
||||
const payload = parts[1] ?? "";
|
||||
const decoded = Buffer.from(payload, "base64").toString("utf-8");
|
||||
return JSON.parse(decoded) as JwtPayload;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
function getAccountId(accessToken: string): string {
|
||||
const payload = decodeJwt(accessToken);
|
||||
const auth = payload?.[JWT_CLAIM_PATH];
|
||||
const accountId = auth?.chatgpt_account_id;
|
||||
if (!accountId) {
|
||||
throw new Error("Failed to extract accountId from token");
|
||||
}
|
||||
return accountId;
|
||||
}
|
||||
|
||||
function shortHash(str: string): string {
|
||||
let h1 = 0xdeadbeef;
|
||||
let h2 = 0x41c6ce57;
|
||||
for (let i = 0; i < str.length; i++) {
|
||||
const ch = str.charCodeAt(i);
|
||||
h1 = Math.imul(h1 ^ ch, 2654435761);
|
||||
h2 = Math.imul(h2 ^ ch, 1597334677);
|
||||
}
|
||||
h1 = Math.imul(h1 ^ (h1 >>> 16), 2246822507) ^ Math.imul(h2 ^ (h2 >>> 13), 3266489909);
|
||||
h2 = Math.imul(h2 ^ (h2 >>> 16), 2246822507) ^ Math.imul(h1 ^ (h1 >>> 13), 3266489909);
|
||||
return (h2 >>> 0).toString(36) + (h1 >>> 0).toString(36);
|
||||
}
|
||||
|
||||
function convertMessages(model: Model<"openai-codex-responses">, context: Context): ResponseInput {
|
||||
const messages: ResponseInput = [];
|
||||
|
||||
const transformedMessages = transformMessages(context.messages, model);
|
||||
|
||||
let msgIndex = 0;
|
||||
for (const msg of transformedMessages) {
|
||||
if (msg.role === "user") {
|
||||
if (typeof msg.content === "string") {
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: [{ type: "input_text", text: sanitizeSurrogates(msg.content) }],
|
||||
});
|
||||
} else {
|
||||
const content: ResponseInputContent[] = msg.content.map((item): ResponseInputContent => {
|
||||
if (item.type === "text") {
|
||||
return {
|
||||
type: "input_text",
|
||||
text: sanitizeSurrogates(item.text),
|
||||
} satisfies ResponseInputText;
|
||||
}
|
||||
return {
|
||||
type: "input_image",
|
||||
detail: "auto",
|
||||
image_url: `data:${item.mimeType};base64,${item.data}`,
|
||||
} satisfies ResponseInputImage;
|
||||
});
|
||||
const filteredContent = !model.input.includes("image")
|
||||
? content.filter((c) => c.type !== "input_image")
|
||||
: content;
|
||||
if (filteredContent.length === 0) continue;
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: filteredContent,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
const output: ResponseInput = [];
|
||||
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "thinking" && msg.stopReason !== "error") {
|
||||
if (block.thinkingSignature) {
|
||||
const reasoningItem = JSON.parse(block.thinkingSignature) as ResponseReasoningItem;
|
||||
output.push(reasoningItem);
|
||||
}
|
||||
} else if (block.type === "text") {
|
||||
const textBlock = block as TextContent;
|
||||
let msgId = textBlock.textSignature;
|
||||
if (!msgId) {
|
||||
msgId = `msg_${msgIndex}`;
|
||||
} else if (msgId.length > 64) {
|
||||
msgId = `msg_${shortHash(msgId)}`;
|
||||
}
|
||||
output.push({
|
||||
type: "message",
|
||||
role: "assistant",
|
||||
content: [{ type: "output_text", text: sanitizeSurrogates(textBlock.text), annotations: [] }],
|
||||
status: "completed",
|
||||
id: msgId,
|
||||
} satisfies ResponseOutputMessage);
|
||||
} else if (block.type === "toolCall" && msg.stopReason !== "error") {
|
||||
const toolCall = block as ToolCall;
|
||||
output.push({
|
||||
type: "function_call",
|
||||
id: toolCall.id.split("|")[1],
|
||||
call_id: toolCall.id.split("|")[0],
|
||||
name: toolCall.name,
|
||||
arguments: JSON.stringify(toolCall.arguments),
|
||||
});
|
||||
}
|
||||
}
|
||||
if (output.length === 0) continue;
|
||||
messages.push(...output);
|
||||
} else if (msg.role === "toolResult") {
|
||||
const textResult = msg.content
|
||||
.filter((c) => c.type === "text")
|
||||
.map((c) => (c as { text: string }).text)
|
||||
.join("\n");
|
||||
const hasImages = msg.content.some((c) => c.type === "image");
|
||||
|
||||
const hasText = textResult.length > 0;
|
||||
messages.push({
|
||||
type: "function_call_output",
|
||||
call_id: msg.toolCallId.split("|")[0],
|
||||
output: sanitizeSurrogates(hasText ? textResult : "(see attached image)"),
|
||||
});
|
||||
|
||||
if (hasImages && model.input.includes("image")) {
|
||||
const contentParts: ResponseInputContent[] = [];
|
||||
contentParts.push({
|
||||
type: "input_text",
|
||||
text: "Attached image(s) from tool result:",
|
||||
} satisfies ResponseInputText);
|
||||
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "image") {
|
||||
contentParts.push({
|
||||
type: "input_image",
|
||||
detail: "auto",
|
||||
image_url: `data:${block.mimeType};base64,${block.data}`,
|
||||
} satisfies ResponseInputImage);
|
||||
}
|
||||
}
|
||||
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: contentParts,
|
||||
});
|
||||
}
|
||||
}
|
||||
msgIndex++;
|
||||
}
|
||||
|
||||
return messages;
|
||||
}
|
||||
|
||||
function convertTools(
|
||||
tools: Tool[],
|
||||
): Array<{ type: "function"; name: string; description: string; parameters: Record<string, unknown>; strict: null }> {
|
||||
return tools.map((tool) => ({
|
||||
type: "function",
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters as unknown as Record<string, unknown>,
|
||||
strict: null,
|
||||
}));
|
||||
}
|
||||
|
||||
function mapStopReason(status: string | undefined): StopReason {
|
||||
if (!status) return "stop";
|
||||
switch (status) {
|
||||
case "completed":
|
||||
return "stop";
|
||||
case "incomplete":
|
||||
return "length";
|
||||
case "failed":
|
||||
case "cancelled":
|
||||
return "error";
|
||||
case "in_progress":
|
||||
case "queued":
|
||||
return "stop";
|
||||
default:
|
||||
return "stop";
|
||||
}
|
||||
}
|
||||
@@ -1,25 +0,0 @@
|
||||
/**
|
||||
* Constants for OpenAI Codex (ChatGPT OAuth) backend
|
||||
*/
|
||||
|
||||
export const CODEX_BASE_URL = "https://chatgpt.com/backend-api";
|
||||
|
||||
export const OPENAI_HEADERS = {
|
||||
BETA: "OpenAI-Beta",
|
||||
ACCOUNT_ID: "chatgpt-account-id",
|
||||
ORIGINATOR: "originator",
|
||||
SESSION_ID: "session_id",
|
||||
CONVERSATION_ID: "conversation_id",
|
||||
} as const;
|
||||
|
||||
export const OPENAI_HEADER_VALUES = {
|
||||
BETA_RESPONSES: "responses=experimental",
|
||||
ORIGINATOR_CODEX: "codex_cli_rs",
|
||||
} as const;
|
||||
|
||||
export const URL_PATHS = {
|
||||
RESPONSES: "/responses",
|
||||
CODEX_RESPONSES: "/codex/responses",
|
||||
} as const;
|
||||
|
||||
export const JWT_CLAIM_PATH = "https://api.openai.com/auth" as const;
|
||||
@@ -1,105 +0,0 @@
|
||||
You are Codex, based on GPT-5. You are running as a coding agent in the Codex CLI on a user's computer.
|
||||
|
||||
## General
|
||||
|
||||
- When searching for text or files, prefer using `rg` or `rg --files` respectively because `rg` is much faster than alternatives like `grep`. (If the `rg` command is not found, then use alternatives.)
|
||||
|
||||
## Editing constraints
|
||||
|
||||
- Default to ASCII when editing or creating files. Only introduce non-ASCII or other Unicode characters when there is a clear justification and the file already uses them.
|
||||
- Add succinct code comments that explain what is going on if code is not self-explanatory. You should not add comments like "Assigns the value to the variable", but a brief comment might be useful ahead of a complex code block that the user would otherwise have to spend time parsing out. Usage of these comments should be rare.
|
||||
- Try to use apply_patch for single file edits, but it is fine to explore other options to make the edit if it does not work well. Do not use apply_patch for changes that are auto-generated (i.e. generating package.json or running a lint or format command like gofmt) or when scripting is more efficient (such as search and replacing a string across a codebase).
|
||||
- You may be in a dirty git worktree.
|
||||
* NEVER revert existing changes you did not make unless explicitly requested, since these changes were made by the user.
|
||||
* If asked to make a commit or code edits and there are unrelated changes to your work or changes that you didn't make in those files, don't revert those changes.
|
||||
* If the changes are in files you've touched recently, you should read carefully and understand how you can work with the changes rather than reverting them.
|
||||
* If the changes are in unrelated files, just ignore them and don't revert them.
|
||||
- Do not amend a commit unless explicitly requested to do so.
|
||||
- While you are working, you might notice unexpected changes that you didn't make. If this happens, STOP IMMEDIATELY and ask the user how they would like to proceed.
|
||||
- **NEVER** use destructive commands like `git reset --hard` or `git checkout --` unless specifically requested or approved by the user.
|
||||
|
||||
## Plan tool
|
||||
|
||||
When using the planning tool:
|
||||
- Skip using the planning tool for straightforward tasks (roughly the easiest 25%).
|
||||
- Do not make single-step plans.
|
||||
- When you made a plan, update it after having performed one of the sub-tasks that you shared on the plan.
|
||||
|
||||
## Codex CLI harness, sandboxing, and approvals
|
||||
|
||||
The Codex CLI harness supports several different configurations for sandboxing and escalation approvals that the user can choose from.
|
||||
|
||||
Filesystem sandboxing defines which files can be read or written. The options for `sandbox_mode` are:
|
||||
- **read-only**: The sandbox only permits reading files.
|
||||
- **workspace-write**: The sandbox permits reading files, and editing files in `cwd` and `writable_roots`. Editing files in other directories requires approval.
|
||||
- **danger-full-access**: No filesystem sandboxing - all commands are permitted.
|
||||
|
||||
Network sandboxing defines whether network can be accessed without approval. Options for `network_access` are:
|
||||
- **restricted**: Requires approval
|
||||
- **enabled**: No approval needed
|
||||
|
||||
Approvals are your mechanism to get user consent to run shell commands without the sandbox. Possible configuration options for `approval_policy` are
|
||||
- **untrusted**: The harness will escalate most commands for user approval, apart from a limited allowlist of safe "read" commands.
|
||||
- **on-failure**: The harness will allow all commands to run in the sandbox (if enabled), and failures will be escalated to the user for approval to run again without the sandbox.
|
||||
- **on-request**: Commands will be run in the sandbox by default, and you can specify in your tool call if you want to escalate a command to run without sandboxing. (Note that this mode is not always available. If it is, you'll see parameters for it in the `shell` command description.)
|
||||
- **never**: This is a non-interactive mode where you may NEVER ask the user for approval to run commands. Instead, you must always persist and work around constraints to solve the task for the user. You MUST do your utmost best to finish the task and validate your work before yielding. If this mode is paired with `danger-full-access`, take advantage of it to deliver the best outcome for the user. Further, in this mode, your default testing philosophy is overridden: Even if you don't see local patterns for testing, you may add tests and scripts to validate your work. Just remove them before yielding.
|
||||
|
||||
When you are running with `approval_policy == on-request`, and sandboxing enabled, here are scenarios where you'll need to request approval:
|
||||
- You need to run a command that writes to a directory that requires it (e.g. running tests that write to /var)
|
||||
- You need to run a GUI app (e.g., open/xdg-open/osascript) to open browsers or files.
|
||||
- You are running sandboxed and need to run a command that requires network access (e.g. installing packages)
|
||||
- If you run a command that is important to solving the user's query, but it fails because of sandboxing, rerun the command with approval. ALWAYS proceed to use the `sandbox_permissions` and `justification` parameters - do not message the user before requesting approval for the command.
|
||||
- You are about to take a potentially destructive action such as an `rm` or `git reset` that the user did not explicitly ask for
|
||||
- (for all of these, you should weigh alternative paths that do not require approval)
|
||||
|
||||
When `sandbox_mode` is set to read-only, you'll need to request approval for any command that isn't a read.
|
||||
|
||||
You will be told what filesystem sandboxing, network sandboxing, and approval mode are active in a developer or user message. If you are not told about this, assume that you are running with workspace-write, network sandboxing enabled, and approval on-failure.
|
||||
|
||||
Although they introduce friction to the user because your work is paused until the user responds, you should leverage them when necessary to accomplish important work. If the completing the task requires escalated permissions, Do not let these settings or the sandbox deter you from attempting to accomplish the user's task unless it is set to "never", in which case never ask for approvals.
|
||||
|
||||
When requesting approval to execute a command that will require escalated privileges:
|
||||
- Provide the `sandbox_permissions` parameter with the value `"require_escalated"`
|
||||
- Include a short, 1 sentence explanation for why you need escalated permissions in the justification parameter
|
||||
|
||||
## Special user requests
|
||||
|
||||
- If the user makes a simple request (such as asking for the time) which you can fulfill by running a terminal command (such as `date`), you should do so.
|
||||
- If the user asks for a "review", default to a code review mindset: prioritise identifying bugs, risks, behavioural regressions, and missing tests. Findings must be the primary focus of the response - keep summaries or overviews brief and only after enumerating the issues. Present findings first (ordered by severity with file/line references), follow with open questions or assumptions, and offer a change-summary only as a secondary detail. If no findings are discovered, state that explicitly and mention any residual risks or testing gaps.
|
||||
|
||||
## Presenting your work and final message
|
||||
|
||||
You are producing plain text that will later be styled by the CLI. Follow these rules exactly. Formatting should make results easy to scan, but not feel mechanical. Use judgment to decide how much structure adds value.
|
||||
|
||||
- Default: be very concise; friendly coding teammate tone.
|
||||
- Ask only when needed; suggest ideas; mirror the user's style.
|
||||
- For substantial work, summarize clearly; follow final‑answer formatting.
|
||||
- Skip heavy formatting for simple confirmations.
|
||||
- Don't dump large files you've written; reference paths only.
|
||||
- No "save/copy this file" - User is on the same machine.
|
||||
- Offer logical next steps (tests, commits, build) briefly; add verify steps if you couldn't do something.
|
||||
- For code changes:
|
||||
* Lead with a quick explanation of the change, and then give more details on the context covering where and why a change was made. Do not start this explanation with "summary", just jump right in.
|
||||
* If there are natural next steps the user may want to take, suggest them at the end of your response. Do not make suggestions if there are no natural next steps.
|
||||
* When suggesting multiple options, use numeric lists for the suggestions so the user can quickly respond with a single number.
|
||||
- The user does not command execution outputs. When asked to show the output of a command (e.g. `git show`), relay the important details in your answer or summarize the key lines so the user understands the result.
|
||||
|
||||
### Final answer structure and style guidelines
|
||||
|
||||
- Plain text; CLI handles styling. Use structure only when it helps scanability.
|
||||
- Headers: optional; short Title Case (1-3 words) wrapped in **…**; no blank line before the first bullet; add only if they truly help.
|
||||
- Bullets: use - ; merge related points; keep to one line when possible; 4–6 per list ordered by importance; keep phrasing consistent.
|
||||
- Monospace: backticks for commands/paths/env vars/code ids and inline examples; use for literal keyword bullets; never combine with **.
|
||||
- Code samples or multi-line snippets should be wrapped in fenced code blocks; include an info string as often as possible.
|
||||
- Structure: group related bullets; order sections general → specific → supporting; for subsections, start with a bolded keyword bullet, then items; match complexity to the task.
|
||||
- Tone: collaborative, concise, factual; present tense, active voice; self‑contained; no "above/below"; parallel wording.
|
||||
- Don'ts: no nested bullets/hierarchies; no ANSI codes; don't cram unrelated keywords; keep keyword lists short—wrap/reformat if long; avoid naming formatting styles in answers.
|
||||
- Adaptation: code explanations → precise, structured with code refs; simple tasks → lead with outcome; big changes → logical walkthrough + rationale + next actions; casual one-offs → plain sentences, no headers/bullets.
|
||||
- File References: When referencing files in your response, make sure to include the relevant start line and always follow the below rules:
|
||||
* Use inline code to make file paths clickable.
|
||||
* Each reference should have a stand alone path. Even if it's the same file.
|
||||
* Accepted: absolute, workspace‑relative, a/ or b/ diff prefixes, or bare filename/suffix.
|
||||
* Line/column (1‑based, optional): :line[:column] or #Lline[Ccolumn] (column defaults to 1).
|
||||
* Do not use URIs like file://, vscode://, or https://.
|
||||
* Do not provide range of lines
|
||||
* Examples: src/app.ts, src/app.ts:42, b/server/index.js#L10, C:\repo\project\main.rs:12:5
|
||||
@@ -1,217 +0,0 @@
|
||||
import { existsSync, mkdirSync, readFileSync, writeFileSync } from "node:fs";
|
||||
import { homedir } from "node:os";
|
||||
import { join } from "node:path";
|
||||
import FALLBACK_INSTRUCTIONS from "./codex-instructions.md" with { type: "text" };
|
||||
|
||||
const GITHUB_API_RELEASES = "https://api.github.com/repos/openai/codex/releases/latest";
|
||||
const GITHUB_HTML_RELEASES = "https://github.com/openai/codex/releases/latest";
|
||||
|
||||
const DEFAULT_AGENT_DIR = join(homedir(), ".pi", "agent");
|
||||
|
||||
function getAgentDir(): string {
|
||||
return process.env.PI_CODING_AGENT_DIR || DEFAULT_AGENT_DIR;
|
||||
}
|
||||
|
||||
function getCacheDir(): string {
|
||||
return join(getAgentDir(), "cache", "openai-codex");
|
||||
}
|
||||
|
||||
export type ModelFamily = "gpt-5.2-codex" | "codex-max" | "codex" | "gpt-5.2" | "gpt-5.1";
|
||||
|
||||
const PROMPT_FILES: Record<ModelFamily, string> = {
|
||||
"gpt-5.2-codex": "gpt-5.2-codex_prompt.md",
|
||||
"codex-max": "gpt-5.1-codex-max_prompt.md",
|
||||
codex: "gpt_5_codex_prompt.md",
|
||||
"gpt-5.2": "gpt_5_2_prompt.md",
|
||||
"gpt-5.1": "gpt_5_1_prompt.md",
|
||||
};
|
||||
|
||||
const CACHE_FILES: Record<ModelFamily, string> = {
|
||||
"gpt-5.2-codex": "gpt-5.2-codex-instructions.md",
|
||||
"codex-max": "codex-max-instructions.md",
|
||||
codex: "codex-instructions.md",
|
||||
"gpt-5.2": "gpt-5.2-instructions.md",
|
||||
"gpt-5.1": "gpt-5.1-instructions.md",
|
||||
};
|
||||
|
||||
export type CacheMetadata = {
|
||||
etag: string | null;
|
||||
tag: string;
|
||||
lastChecked: number;
|
||||
url: string;
|
||||
};
|
||||
|
||||
export function getModelFamily(normalizedModel: string): ModelFamily {
|
||||
if (normalizedModel.includes("gpt-5.2-codex") || normalizedModel.includes("gpt 5.2 codex")) {
|
||||
return "gpt-5.2-codex";
|
||||
}
|
||||
if (normalizedModel.includes("codex-max")) {
|
||||
return "codex-max";
|
||||
}
|
||||
if (normalizedModel.includes("codex") || normalizedModel.startsWith("codex-")) {
|
||||
return "codex";
|
||||
}
|
||||
if (normalizedModel.includes("gpt-5.2")) {
|
||||
return "gpt-5.2";
|
||||
}
|
||||
return "gpt-5.1";
|
||||
}
|
||||
|
||||
async function getLatestReleaseTag(): Promise<string> {
|
||||
try {
|
||||
const response = await fetch(GITHUB_API_RELEASES);
|
||||
if (response.ok) {
|
||||
const data = (await response.json()) as { tag_name?: string };
|
||||
if (data.tag_name) {
|
||||
return data.tag_name;
|
||||
}
|
||||
}
|
||||
} catch {
|
||||
// fallback
|
||||
}
|
||||
|
||||
const htmlResponse = await fetch(GITHUB_HTML_RELEASES);
|
||||
if (!htmlResponse.ok) {
|
||||
throw new Error(`Failed to fetch latest release: ${htmlResponse.status}`);
|
||||
}
|
||||
|
||||
const finalUrl = htmlResponse.url;
|
||||
if (finalUrl) {
|
||||
const parts = finalUrl.split("/tag/");
|
||||
const last = parts[parts.length - 1];
|
||||
if (last && !last.includes("/")) {
|
||||
return last;
|
||||
}
|
||||
}
|
||||
|
||||
const html = await htmlResponse.text();
|
||||
const match = html.match(/\/openai\/codex\/releases\/tag\/([^"]+)/);
|
||||
if (match?.[1]) {
|
||||
return match[1];
|
||||
}
|
||||
|
||||
throw new Error("Failed to determine latest release tag from GitHub");
|
||||
}
|
||||
|
||||
export async function getCodexInstructions(normalizedModel = "gpt-5.1-codex"): Promise<string> {
|
||||
const modelFamily = getModelFamily(normalizedModel);
|
||||
const promptFile = PROMPT_FILES[modelFamily];
|
||||
const cacheDir = getCacheDir();
|
||||
const cacheFile = join(cacheDir, CACHE_FILES[modelFamily]);
|
||||
const cacheMetaFile = join(cacheDir, `${CACHE_FILES[modelFamily].replace(".md", "-meta.json")}`);
|
||||
|
||||
try {
|
||||
let cachedETag: string | null = null;
|
||||
let cachedTag: string | null = null;
|
||||
let cachedTimestamp: number | null = null;
|
||||
|
||||
if (existsSync(cacheMetaFile)) {
|
||||
const metadata = JSON.parse(readFileSync(cacheMetaFile, "utf-8")) as CacheMetadata;
|
||||
cachedETag = metadata.etag;
|
||||
cachedTag = metadata.tag;
|
||||
cachedTimestamp = metadata.lastChecked;
|
||||
}
|
||||
|
||||
const CACHE_TTL_MS = 15 * 60 * 1000;
|
||||
if (cachedTimestamp && Date.now() - cachedTimestamp < CACHE_TTL_MS && existsSync(cacheFile)) {
|
||||
return readFileSync(cacheFile, "utf-8");
|
||||
}
|
||||
|
||||
const latestTag = await getLatestReleaseTag();
|
||||
const instructionsUrl = `https://raw.githubusercontent.com/openai/codex/${latestTag}/codex-rs/core/${promptFile}`;
|
||||
|
||||
if (cachedTag !== latestTag) {
|
||||
cachedETag = null;
|
||||
}
|
||||
|
||||
const headers: Record<string, string> = {};
|
||||
if (cachedETag) {
|
||||
headers["If-None-Match"] = cachedETag;
|
||||
}
|
||||
|
||||
const response = await fetch(instructionsUrl, { headers });
|
||||
|
||||
if (response.status === 304) {
|
||||
if (existsSync(cacheFile)) {
|
||||
return readFileSync(cacheFile, "utf-8");
|
||||
}
|
||||
}
|
||||
|
||||
if (response.ok) {
|
||||
const instructions = await response.text();
|
||||
const newETag = response.headers.get("etag");
|
||||
|
||||
mkdirSync(cacheDir, { recursive: true });
|
||||
writeFileSync(cacheFile, instructions, "utf-8");
|
||||
writeFileSync(
|
||||
cacheMetaFile,
|
||||
JSON.stringify({
|
||||
etag: newETag,
|
||||
tag: latestTag,
|
||||
lastChecked: Date.now(),
|
||||
url: instructionsUrl,
|
||||
} satisfies CacheMetadata),
|
||||
"utf-8",
|
||||
);
|
||||
|
||||
return instructions;
|
||||
}
|
||||
|
||||
throw new Error(`HTTP ${response.status}`);
|
||||
} catch (error) {
|
||||
console.error(
|
||||
`[openai-codex] Failed to fetch ${modelFamily} instructions from GitHub:`,
|
||||
error instanceof Error ? error.message : String(error),
|
||||
);
|
||||
|
||||
if (existsSync(cacheFile)) {
|
||||
console.error(`[openai-codex] Using cached ${modelFamily} instructions`);
|
||||
return readFileSync(cacheFile, "utf-8");
|
||||
}
|
||||
|
||||
console.error(`[openai-codex] Falling back to bundled instructions for ${modelFamily}`);
|
||||
return FALLBACK_INSTRUCTIONS;
|
||||
}
|
||||
}
|
||||
|
||||
export const TOOL_REMAP_MESSAGE = `<user_instructions priority="0">
|
||||
<environment_override priority="0">
|
||||
YOU ARE IN A DIFFERENT ENVIRONMENT. These instructions override ALL previous tool references.
|
||||
</environment_override>
|
||||
|
||||
<tool_replacements priority="0">
|
||||
<critical_rule priority="0">
|
||||
❌ APPLY_PATCH DOES NOT EXIST → ✅ USE "edit" INSTEAD
|
||||
- NEVER use: apply_patch, applyPatch
|
||||
- ALWAYS use: edit tool for ALL file modifications
|
||||
</critical_rule>
|
||||
|
||||
<critical_rule priority="0">
|
||||
❌ UPDATE_PLAN DOES NOT EXIST
|
||||
- NEVER use: update_plan, updatePlan, read_plan, readPlan, todowrite, todoread
|
||||
- There is no plan tool in this environment
|
||||
</critical_rule>
|
||||
</tool_replacements>
|
||||
|
||||
<available_tools priority="0">
|
||||
File Operations:
|
||||
• read - Read file contents
|
||||
• edit - Modify files with exact find/replace
|
||||
• write - Create or overwrite files
|
||||
|
||||
Search/Discovery:
|
||||
• grep - Search file contents for patterns (read-only)
|
||||
• find - Find files by glob pattern (read-only)
|
||||
• ls - List directory contents (read-only)
|
||||
|
||||
Execution:
|
||||
• bash - Run shell commands
|
||||
</available_tools>
|
||||
|
||||
<verification_checklist priority="0">
|
||||
Before file modifications:
|
||||
1. Am I using "edit" NOT "apply_patch"?
|
||||
2. Am I avoiding plan tools entirely?
|
||||
3. Am I using only the tools listed above?
|
||||
</verification_checklist>
|
||||
</user_instructions>`;
|
||||
@@ -1,55 +0,0 @@
|
||||
/**
|
||||
* Codex-Pi bridge prompt
|
||||
* Aligns Codex CLI expectations with Pi's toolset.
|
||||
*/
|
||||
|
||||
import type { Tool } from "../../../types";
|
||||
|
||||
function formatToolList(tools?: Tool[]): string {
|
||||
if (!tools || tools.length === 0) {
|
||||
return "- (none)";
|
||||
}
|
||||
|
||||
const normalized = tools
|
||||
.map((tool) => {
|
||||
const name = tool.name.trim();
|
||||
if (!name) return null;
|
||||
const description = (tool.description || "Custom tool").replace(/\s*\n\s*/g, " ").trim();
|
||||
return { name, description };
|
||||
})
|
||||
.filter((tool): tool is { name: string; description: string } => tool !== null);
|
||||
|
||||
if (normalized.length === 0) {
|
||||
return "- (none)";
|
||||
}
|
||||
|
||||
const maxNameLength = normalized.reduce((max, tool) => Math.max(max, tool.name.length), 0);
|
||||
const padWidth = Math.max(6, maxNameLength + 1);
|
||||
|
||||
return normalized
|
||||
.map((tool) => {
|
||||
const paddedName = tool.name.padEnd(padWidth);
|
||||
return `- ${paddedName}- ${tool.description}`;
|
||||
})
|
||||
.join("\n");
|
||||
}
|
||||
|
||||
export function buildCodexPiBridge(tools?: Tool[]): string {
|
||||
const toolsList = formatToolList(tools);
|
||||
|
||||
return `# Codex Environment Bridge
|
||||
|
||||
<environment_override priority="0">
|
||||
IGNORE ALL PREVIOUS INSTRUCTIONS ABOVE THIS MESSAGE.
|
||||
Do not assume any tools are available unless listed below.
|
||||
</environment_override>
|
||||
|
||||
The next system instructions that follow this message are authoritative and must be obeyed, even if they conflict with earlier instructions.
|
||||
|
||||
## Available Tools
|
||||
|
||||
${toolsList}
|
||||
|
||||
Only use the tools listed above. Do not reference or call any other tools.
|
||||
`;
|
||||
}
|
||||
@@ -1,26 +0,0 @@
|
||||
export interface CodexSystemPrompt {
|
||||
instructions: string;
|
||||
developerMessages: string[];
|
||||
}
|
||||
|
||||
export function buildCodexSystemPrompt(args: {
|
||||
codexInstructions: string;
|
||||
bridgeText: string;
|
||||
userSystemPrompt?: string;
|
||||
}): CodexSystemPrompt {
|
||||
const { codexInstructions, bridgeText, userSystemPrompt } = args;
|
||||
const developerMessages: string[] = [];
|
||||
|
||||
if (bridgeText.trim().length > 0) {
|
||||
developerMessages.push(bridgeText.trim());
|
||||
}
|
||||
|
||||
if (userSystemPrompt && userSystemPrompt.trim().length > 0) {
|
||||
developerMessages.push(userSystemPrompt.trim());
|
||||
}
|
||||
|
||||
return {
|
||||
instructions: codexInstructions.trim(),
|
||||
developerMessages,
|
||||
};
|
||||
}
|
||||
@@ -1,295 +0,0 @@
|
||||
export interface ReasoningConfig {
|
||||
effort: "none" | "minimal" | "low" | "medium" | "high" | "xhigh";
|
||||
summary: "auto" | "concise" | "detailed" | "off" | "on";
|
||||
}
|
||||
|
||||
export interface CodexRequestOptions {
|
||||
reasoningEffort?: ReasoningConfig["effort"];
|
||||
reasoningSummary?: ReasoningConfig["summary"] | null;
|
||||
textVerbosity?: "low" | "medium" | "high";
|
||||
include?: string[];
|
||||
}
|
||||
|
||||
export interface InputItem {
|
||||
id?: string | null;
|
||||
type?: string | null;
|
||||
role?: string;
|
||||
content?: unknown;
|
||||
call_id?: string | null;
|
||||
name?: string;
|
||||
output?: unknown;
|
||||
arguments?: string;
|
||||
}
|
||||
|
||||
export interface RequestBody {
|
||||
model: string;
|
||||
store?: boolean;
|
||||
stream?: boolean;
|
||||
instructions?: string;
|
||||
input?: InputItem[];
|
||||
tools?: unknown;
|
||||
temperature?: number;
|
||||
reasoning?: Partial<ReasoningConfig>;
|
||||
text?: {
|
||||
verbosity?: "low" | "medium" | "high";
|
||||
};
|
||||
include?: string[];
|
||||
prompt_cache_key?: string;
|
||||
prompt_cache_retention?: "in_memory" | "24h";
|
||||
max_output_tokens?: number;
|
||||
max_completion_tokens?: number;
|
||||
[key: string]: unknown;
|
||||
}
|
||||
|
||||
const MODEL_MAP: Record<string, string> = {
|
||||
"gpt-5.1-codex": "gpt-5.1-codex",
|
||||
"gpt-5.1-codex-low": "gpt-5.1-codex",
|
||||
"gpt-5.1-codex-medium": "gpt-5.1-codex",
|
||||
"gpt-5.1-codex-high": "gpt-5.1-codex",
|
||||
"gpt-5.1-codex-max": "gpt-5.1-codex-max",
|
||||
"gpt-5.1-codex-max-low": "gpt-5.1-codex-max",
|
||||
"gpt-5.1-codex-max-medium": "gpt-5.1-codex-max",
|
||||
"gpt-5.1-codex-max-high": "gpt-5.1-codex-max",
|
||||
"gpt-5.1-codex-max-xhigh": "gpt-5.1-codex-max",
|
||||
"gpt-5.2": "gpt-5.2",
|
||||
"gpt-5.2-none": "gpt-5.2",
|
||||
"gpt-5.2-low": "gpt-5.2",
|
||||
"gpt-5.2-medium": "gpt-5.2",
|
||||
"gpt-5.2-high": "gpt-5.2",
|
||||
"gpt-5.2-xhigh": "gpt-5.2",
|
||||
"gpt-5.2-codex": "gpt-5.2-codex",
|
||||
"gpt-5.2-codex-low": "gpt-5.2-codex",
|
||||
"gpt-5.2-codex-medium": "gpt-5.2-codex",
|
||||
"gpt-5.2-codex-high": "gpt-5.2-codex",
|
||||
"gpt-5.2-codex-xhigh": "gpt-5.2-codex",
|
||||
"gpt-5.1-codex-mini": "gpt-5.1-codex-mini",
|
||||
"gpt-5.1-codex-mini-medium": "gpt-5.1-codex-mini",
|
||||
"gpt-5.1-codex-mini-high": "gpt-5.1-codex-mini",
|
||||
"gpt-5.1": "gpt-5.1",
|
||||
"gpt-5.1-none": "gpt-5.1",
|
||||
"gpt-5.1-low": "gpt-5.1",
|
||||
"gpt-5.1-medium": "gpt-5.1",
|
||||
"gpt-5.1-high": "gpt-5.1",
|
||||
"gpt-5.1-chat-latest": "gpt-5.1",
|
||||
"gpt-5-codex": "gpt-5.1-codex",
|
||||
"codex-mini-latest": "gpt-5.1-codex-mini",
|
||||
"gpt-5-codex-mini": "gpt-5.1-codex-mini",
|
||||
"gpt-5-codex-mini-medium": "gpt-5.1-codex-mini",
|
||||
"gpt-5-codex-mini-high": "gpt-5.1-codex-mini",
|
||||
"gpt-5": "gpt-5.1",
|
||||
"gpt-5-mini": "gpt-5.1",
|
||||
"gpt-5-nano": "gpt-5.1",
|
||||
};
|
||||
|
||||
function getNormalizedModel(modelId: string): string | undefined {
|
||||
if (MODEL_MAP[modelId]) return MODEL_MAP[modelId];
|
||||
const lowerModelId = modelId.toLowerCase();
|
||||
const match = Object.keys(MODEL_MAP).find((key) => key.toLowerCase() === lowerModelId);
|
||||
return match ? MODEL_MAP[match] : undefined;
|
||||
}
|
||||
|
||||
export function normalizeModel(model: string | undefined): string {
|
||||
if (!model) return "gpt-5.1";
|
||||
|
||||
const modelId = model.includes("/") ? model.split("/").pop()! : model;
|
||||
const mappedModel = getNormalizedModel(modelId);
|
||||
if (mappedModel) return mappedModel;
|
||||
|
||||
const normalized = modelId.toLowerCase();
|
||||
|
||||
if (normalized.includes("gpt-5.2-codex") || normalized.includes("gpt 5.2 codex")) {
|
||||
return "gpt-5.2-codex";
|
||||
}
|
||||
if (normalized.includes("gpt-5.2") || normalized.includes("gpt 5.2")) {
|
||||
return "gpt-5.2";
|
||||
}
|
||||
if (normalized.includes("gpt-5.1-codex-max") || normalized.includes("gpt 5.1 codex max")) {
|
||||
return "gpt-5.1-codex-max";
|
||||
}
|
||||
if (normalized.includes("gpt-5.1-codex-mini") || normalized.includes("gpt 5.1 codex mini")) {
|
||||
return "gpt-5.1-codex-mini";
|
||||
}
|
||||
if (
|
||||
normalized.includes("codex-mini-latest") ||
|
||||
normalized.includes("gpt-5-codex-mini") ||
|
||||
normalized.includes("gpt 5 codex mini")
|
||||
) {
|
||||
return "codex-mini-latest";
|
||||
}
|
||||
if (normalized.includes("gpt-5.1-codex") || normalized.includes("gpt 5.1 codex")) {
|
||||
return "gpt-5.1-codex";
|
||||
}
|
||||
if (normalized.includes("gpt-5.1") || normalized.includes("gpt 5.1")) {
|
||||
return "gpt-5.1";
|
||||
}
|
||||
if (normalized.includes("codex")) {
|
||||
return "gpt-5.1-codex";
|
||||
}
|
||||
if (normalized.includes("gpt-5") || normalized.includes("gpt 5")) {
|
||||
return "gpt-5.1";
|
||||
}
|
||||
|
||||
return "gpt-5.1";
|
||||
}
|
||||
|
||||
function getReasoningConfig(modelName: string | undefined, options: CodexRequestOptions = {}): ReasoningConfig {
|
||||
const normalizedName = modelName?.toLowerCase() ?? "";
|
||||
|
||||
const isGpt52Codex = normalizedName.includes("gpt-5.2-codex") || normalizedName.includes("gpt 5.2 codex");
|
||||
const isGpt52General = (normalizedName.includes("gpt-5.2") || normalizedName.includes("gpt 5.2")) && !isGpt52Codex;
|
||||
const isCodexMax = normalizedName.includes("codex-max") || normalizedName.includes("codex max");
|
||||
const isCodexMini =
|
||||
normalizedName.includes("codex-mini") ||
|
||||
normalizedName.includes("codex mini") ||
|
||||
normalizedName.includes("codex_mini") ||
|
||||
normalizedName.includes("codex-mini-latest");
|
||||
const isCodex = normalizedName.includes("codex") && !isCodexMini;
|
||||
const isLightweight = !isCodexMini && (normalizedName.includes("nano") || normalizedName.includes("mini"));
|
||||
const isGpt51General =
|
||||
(normalizedName.includes("gpt-5.1") || normalizedName.includes("gpt 5.1")) &&
|
||||
!isCodex &&
|
||||
!isCodexMax &&
|
||||
!isCodexMini;
|
||||
|
||||
const supportsXhigh = isGpt52General || isGpt52Codex || isCodexMax;
|
||||
const supportsNone = isGpt52General || isGpt51General;
|
||||
|
||||
const defaultEffort: ReasoningConfig["effort"] = isCodexMini
|
||||
? "medium"
|
||||
: supportsXhigh
|
||||
? "high"
|
||||
: isLightweight
|
||||
? "minimal"
|
||||
: "medium";
|
||||
|
||||
let effort = options.reasoningEffort || defaultEffort;
|
||||
|
||||
if (isCodexMini) {
|
||||
if (effort === "minimal" || effort === "low" || effort === "none") {
|
||||
effort = "medium";
|
||||
}
|
||||
if (effort === "xhigh") {
|
||||
effort = "high";
|
||||
}
|
||||
if (effort !== "high" && effort !== "medium") {
|
||||
effort = "medium";
|
||||
}
|
||||
}
|
||||
|
||||
if (!supportsXhigh && effort === "xhigh") {
|
||||
effort = "high";
|
||||
}
|
||||
|
||||
if (!supportsNone && effort === "none") {
|
||||
effort = "low";
|
||||
}
|
||||
|
||||
if (isCodex && effort === "minimal") {
|
||||
effort = "low";
|
||||
}
|
||||
|
||||
return {
|
||||
effort,
|
||||
summary: options.reasoningSummary ?? "detailed",
|
||||
};
|
||||
}
|
||||
|
||||
function filterInput(input: InputItem[] | undefined): InputItem[] | undefined {
|
||||
if (!Array.isArray(input)) return input;
|
||||
|
||||
return input
|
||||
.filter((item) => item.type !== "item_reference")
|
||||
.map((item) => {
|
||||
if (item.id != null) {
|
||||
const { id: _id, ...rest } = item;
|
||||
return rest as InputItem;
|
||||
}
|
||||
return item;
|
||||
});
|
||||
}
|
||||
|
||||
export async function transformRequestBody(
|
||||
body: RequestBody,
|
||||
options: CodexRequestOptions = {},
|
||||
prompt?: { instructions: string; developerMessages: string[] },
|
||||
): Promise<RequestBody> {
|
||||
const normalizedModel = normalizeModel(body.model);
|
||||
|
||||
body.model = normalizedModel;
|
||||
body.store = false;
|
||||
body.stream = true;
|
||||
|
||||
if (body.input && Array.isArray(body.input)) {
|
||||
body.input = filterInput(body.input);
|
||||
|
||||
if (body.input) {
|
||||
const functionCallIds = new Set(
|
||||
body.input
|
||||
.filter((item) => item.type === "function_call" && typeof item.call_id === "string")
|
||||
.map((item) => item.call_id as string),
|
||||
);
|
||||
|
||||
body.input = body.input.map((item) => {
|
||||
if (item.type === "function_call_output" && typeof item.call_id === "string") {
|
||||
const callId = item.call_id as string;
|
||||
if (!functionCallIds.has(callId)) {
|
||||
const itemRecord = item as unknown as Record<string, unknown>;
|
||||
const toolName = typeof itemRecord.name === "string" ? itemRecord.name : "tool";
|
||||
let text = "";
|
||||
try {
|
||||
const output = itemRecord.output;
|
||||
text = typeof output === "string" ? output : JSON.stringify(output);
|
||||
} catch {
|
||||
text = String(itemRecord.output ?? "");
|
||||
}
|
||||
if (text.length > 16000) {
|
||||
text = `${text.slice(0, 16000)}\n...[truncated]`;
|
||||
}
|
||||
return {
|
||||
type: "message",
|
||||
role: "assistant",
|
||||
content: `[Previous ${toolName} result; call_id=${callId}]: ${text}`,
|
||||
} as InputItem;
|
||||
}
|
||||
}
|
||||
return item;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (prompt?.developerMessages && prompt.developerMessages.length > 0 && Array.isArray(body.input)) {
|
||||
const developerMessages = prompt.developerMessages.map(
|
||||
(text) =>
|
||||
({
|
||||
type: "message",
|
||||
role: "developer",
|
||||
content: [{ type: "input_text", text }],
|
||||
}) as InputItem,
|
||||
);
|
||||
body.input = [...developerMessages, ...body.input];
|
||||
}
|
||||
|
||||
if (options.reasoningEffort !== undefined) {
|
||||
const reasoningConfig = getReasoningConfig(normalizedModel, options);
|
||||
body.reasoning = {
|
||||
...body.reasoning,
|
||||
...reasoningConfig,
|
||||
};
|
||||
} else {
|
||||
delete body.reasoning;
|
||||
}
|
||||
|
||||
body.text = {
|
||||
...body.text,
|
||||
verbosity: options.textVerbosity || "medium",
|
||||
};
|
||||
|
||||
const include = Array.isArray(options.include) ? [...options.include] : [];
|
||||
include.push("reasoning.encrypted_content");
|
||||
body.include = Array.from(new Set(include));
|
||||
|
||||
delete body.max_output_tokens;
|
||||
delete body.max_completion_tokens;
|
||||
|
||||
return body;
|
||||
}
|
||||
@@ -1,133 +0,0 @@
|
||||
export type CodexRateLimit = {
|
||||
used_percent?: number;
|
||||
window_minutes?: number;
|
||||
resets_at?: number;
|
||||
};
|
||||
|
||||
export type CodexRateLimits = {
|
||||
primary?: CodexRateLimit;
|
||||
secondary?: CodexRateLimit;
|
||||
};
|
||||
|
||||
export type CodexErrorInfo = {
|
||||
message: string;
|
||||
status: number;
|
||||
friendlyMessage?: string;
|
||||
rateLimits?: CodexRateLimits;
|
||||
raw?: string;
|
||||
};
|
||||
|
||||
export async function parseCodexError(response: Response): Promise<CodexErrorInfo> {
|
||||
const raw = await response.text();
|
||||
let message = raw || response.statusText || "Request failed";
|
||||
let friendlyMessage: string | undefined;
|
||||
let rateLimits: CodexRateLimits | undefined;
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(raw) as { error?: Record<string, unknown> };
|
||||
const err = parsed?.error ?? {};
|
||||
|
||||
const headers = response.headers;
|
||||
const primary = {
|
||||
used_percent: toNumber(headers.get("x-codex-primary-used-percent")),
|
||||
window_minutes: toInt(headers.get("x-codex-primary-window-minutes")),
|
||||
resets_at: toInt(headers.get("x-codex-primary-reset-at")),
|
||||
};
|
||||
const secondary = {
|
||||
used_percent: toNumber(headers.get("x-codex-secondary-used-percent")),
|
||||
window_minutes: toInt(headers.get("x-codex-secondary-window-minutes")),
|
||||
resets_at: toInt(headers.get("x-codex-secondary-reset-at")),
|
||||
};
|
||||
rateLimits =
|
||||
primary.used_percent !== undefined || secondary.used_percent !== undefined
|
||||
? { primary, secondary }
|
||||
: undefined;
|
||||
|
||||
const code = String((err as { code?: string; type?: string }).code ?? (err as { type?: string }).type ?? "");
|
||||
const resetsAt = (err as { resets_at?: number }).resets_at ?? primary.resets_at ?? secondary.resets_at;
|
||||
const mins = resetsAt ? Math.max(0, Math.round((resetsAt * 1000 - Date.now()) / 60000)) : undefined;
|
||||
|
||||
if (/usage_limit_reached|usage_not_included|rate_limit_exceeded/i.test(code) || response.status === 429) {
|
||||
const planType = (err as { plan_type?: string }).plan_type;
|
||||
const plan = planType ? ` (${String(planType).toLowerCase()} plan)` : "";
|
||||
const when = mins !== undefined ? ` Try again in ~${mins} min.` : "";
|
||||
friendlyMessage = `You have hit your ChatGPT usage limit${plan}.${when}`.trim();
|
||||
}
|
||||
|
||||
const errMessage = (err as { message?: string }).message;
|
||||
message = errMessage || friendlyMessage || message;
|
||||
} catch {
|
||||
// raw body not JSON
|
||||
}
|
||||
|
||||
return {
|
||||
message,
|
||||
status: response.status,
|
||||
friendlyMessage,
|
||||
rateLimits,
|
||||
raw: raw,
|
||||
};
|
||||
}
|
||||
|
||||
export async function* parseCodexSseStream(response: Response): AsyncGenerator<Record<string, unknown>> {
|
||||
if (!response.body) {
|
||||
return;
|
||||
}
|
||||
|
||||
const reader = response.body.getReader();
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = "";
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
buffer += decoder.decode(value, { stream: true });
|
||||
|
||||
let index = buffer.indexOf("\n\n");
|
||||
while (index !== -1) {
|
||||
const chunk = buffer.slice(0, index);
|
||||
buffer = buffer.slice(index + 2);
|
||||
const event = parseSseChunk(chunk);
|
||||
if (event) yield event;
|
||||
index = buffer.indexOf("\n\n");
|
||||
}
|
||||
}
|
||||
|
||||
if (buffer.trim()) {
|
||||
const event = parseSseChunk(buffer);
|
||||
if (event) yield event;
|
||||
}
|
||||
}
|
||||
|
||||
function parseSseChunk(chunk: string): Record<string, unknown> | null {
|
||||
const lines = chunk.split("\n");
|
||||
const dataLines: string[] = [];
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith("data:")) {
|
||||
dataLines.push(line.slice(5).trim());
|
||||
}
|
||||
}
|
||||
|
||||
if (dataLines.length === 0) return null;
|
||||
const data = dataLines.join("\n").trim();
|
||||
if (!data || data === "[DONE]") return null;
|
||||
|
||||
try {
|
||||
return JSON.parse(data) as Record<string, unknown>;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
function toNumber(v: string | null): number | undefined {
|
||||
if (v == null) return undefined;
|
||||
const n = Number(v);
|
||||
return Number.isFinite(n) ? n : undefined;
|
||||
}
|
||||
|
||||
function toInt(v: string | null): number | undefined {
|
||||
if (v == null) return undefined;
|
||||
const n = parseInt(v, 10);
|
||||
return Number.isFinite(n) ? n : undefined;
|
||||
}
|
||||
@@ -1,676 +0,0 @@
|
||||
import OpenAI from "openai";
|
||||
import type {
|
||||
ChatCompletionAssistantMessageParam,
|
||||
ChatCompletionChunk,
|
||||
ChatCompletionContentPart,
|
||||
ChatCompletionContentPartImage,
|
||||
ChatCompletionContentPartText,
|
||||
ChatCompletionMessageParam,
|
||||
ChatCompletionToolMessageParam,
|
||||
} from "openai/resources/chat/completions.js";
|
||||
import { calculateCost } from "../models";
|
||||
import { getEnvApiKey } from "../stream";
|
||||
import type {
|
||||
AssistantMessage,
|
||||
Context,
|
||||
Message,
|
||||
Model,
|
||||
OpenAICompat,
|
||||
StopReason,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
Tool,
|
||||
ToolCall,
|
||||
} from "../types";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream";
|
||||
import { parseStreamingJson } from "../utils/json-parse";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
import { transformMessages } from "./transorm-messages";
|
||||
|
||||
/**
|
||||
* Normalize tool call ID for Mistral.
|
||||
* Mistral requires tool IDs to be exactly 9 alphanumeric characters (a-z, A-Z, 0-9).
|
||||
*/
|
||||
function normalizeMistralToolId(id: string, isMistral: boolean): string {
|
||||
if (!isMistral) return id;
|
||||
// Remove non-alphanumeric characters
|
||||
let normalized = id.replace(/[^a-zA-Z0-9]/g, "");
|
||||
// Mistral requires exactly 9 characters
|
||||
if (normalized.length < 9) {
|
||||
// Pad with deterministic characters based on original ID to ensure matching
|
||||
const padding = "ABCDEFGHI";
|
||||
normalized = normalized + padding.slice(0, 9 - normalized.length);
|
||||
} else if (normalized.length > 9) {
|
||||
normalized = normalized.slice(0, 9);
|
||||
}
|
||||
return normalized;
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if conversation messages contain tool calls or tool results.
|
||||
* This is needed because Anthropic (via proxy) requires the tools param
|
||||
* to be present when messages include tool_calls or tool role messages.
|
||||
*/
|
||||
function hasToolHistory(messages: Message[]): boolean {
|
||||
for (const msg of messages) {
|
||||
if (msg.role === "toolResult") {
|
||||
return true;
|
||||
}
|
||||
if (msg.role === "assistant") {
|
||||
if (msg.content.some((block) => block.type === "toolCall")) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
export interface OpenAICompletionsOptions extends StreamOptions {
|
||||
toolChoice?: "auto" | "none" | "required" | { type: "function"; function: { name: string } };
|
||||
reasoningEffort?: "minimal" | "low" | "medium" | "high" | "xhigh";
|
||||
}
|
||||
|
||||
export const streamOpenAICompletions: StreamFunction<"openai-completions"> = (
|
||||
model: Model<"openai-completions">,
|
||||
context: Context,
|
||||
options?: OpenAICompletionsOptions,
|
||||
): AssistantMessageEventStream => {
|
||||
const stream = new AssistantMessageEventStream();
|
||||
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: model.api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
try {
|
||||
const apiKey = options?.apiKey || getEnvApiKey(model.provider) || "";
|
||||
const client = createClient(model, context, apiKey);
|
||||
const params = buildParams(model, context, options);
|
||||
const openaiStream = await client.chat.completions.create(params, { signal: options?.signal });
|
||||
stream.push({ type: "start", partial: output });
|
||||
|
||||
let currentBlock: TextContent | ThinkingContent | (ToolCall & { partialArgs?: string }) | null = null;
|
||||
const blocks = output.content;
|
||||
const blockIndex = () => blocks.length - 1;
|
||||
const finishCurrentBlock = (block?: typeof currentBlock) => {
|
||||
if (block) {
|
||||
if (block.type === "text") {
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: block.text,
|
||||
partial: output,
|
||||
});
|
||||
} else if (block.type === "thinking") {
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: block.thinking,
|
||||
partial: output,
|
||||
});
|
||||
} else if (block.type === "toolCall") {
|
||||
block.arguments = JSON.parse(block.partialArgs || "{}");
|
||||
delete block.partialArgs;
|
||||
stream.push({
|
||||
type: "toolcall_end",
|
||||
contentIndex: blockIndex(),
|
||||
toolCall: block,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
for await (const chunk of openaiStream) {
|
||||
if (chunk.usage) {
|
||||
const cachedTokens = chunk.usage.prompt_tokens_details?.cached_tokens || 0;
|
||||
const reasoningTokens = chunk.usage.completion_tokens_details?.reasoning_tokens || 0;
|
||||
const input = (chunk.usage.prompt_tokens || 0) - cachedTokens;
|
||||
const outputTokens = (chunk.usage.completion_tokens || 0) + reasoningTokens;
|
||||
output.usage = {
|
||||
// OpenAI includes cached tokens in prompt_tokens, so subtract to get non-cached input
|
||||
input,
|
||||
output: outputTokens,
|
||||
cacheRead: cachedTokens,
|
||||
cacheWrite: 0,
|
||||
// Compute totalTokens ourselves since we add reasoning_tokens to output
|
||||
// and some providers (e.g., Groq) don't include them in total_tokens
|
||||
totalTokens: input + outputTokens + cachedTokens,
|
||||
cost: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
total: 0,
|
||||
},
|
||||
};
|
||||
calculateCost(model, output.usage);
|
||||
}
|
||||
|
||||
const choice = chunk.choices[0];
|
||||
if (!choice) continue;
|
||||
|
||||
if (choice.finish_reason) {
|
||||
output.stopReason = mapStopReason(choice.finish_reason);
|
||||
}
|
||||
|
||||
if (choice.delta) {
|
||||
if (
|
||||
choice.delta.content !== null &&
|
||||
choice.delta.content !== undefined &&
|
||||
choice.delta.content.length > 0
|
||||
) {
|
||||
if (!currentBlock || currentBlock.type !== "text") {
|
||||
finishCurrentBlock(currentBlock);
|
||||
currentBlock = { type: "text", text: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
|
||||
if (currentBlock.type === "text") {
|
||||
currentBlock.text += choice.delta.content;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: choice.delta.content,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Some endpoints return reasoning in reasoning_content (llama.cpp),
|
||||
// or reasoning (other openai compatible endpoints)
|
||||
const reasoningFields = ["reasoning_content", "reasoning", "reasoning_text"];
|
||||
for (const field of reasoningFields) {
|
||||
if (
|
||||
(choice.delta as any)[field] !== null &&
|
||||
(choice.delta as any)[field] !== undefined &&
|
||||
(choice.delta as any)[field].length > 0
|
||||
) {
|
||||
if (!currentBlock || currentBlock.type !== "thinking") {
|
||||
finishCurrentBlock(currentBlock);
|
||||
currentBlock = {
|
||||
type: "thinking",
|
||||
thinking: "",
|
||||
thinkingSignature: field,
|
||||
};
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
|
||||
if (currentBlock.type === "thinking") {
|
||||
const delta = (choice.delta as any)[field];
|
||||
currentBlock.thinking += delta;
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (choice?.delta?.tool_calls) {
|
||||
for (const toolCall of choice.delta.tool_calls) {
|
||||
if (
|
||||
!currentBlock ||
|
||||
currentBlock.type !== "toolCall" ||
|
||||
(toolCall.id && currentBlock.id !== toolCall.id)
|
||||
) {
|
||||
finishCurrentBlock(currentBlock);
|
||||
currentBlock = {
|
||||
type: "toolCall",
|
||||
id: toolCall.id || "",
|
||||
name: toolCall.function?.name || "",
|
||||
arguments: {},
|
||||
partialArgs: "",
|
||||
};
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
|
||||
if (currentBlock.type === "toolCall") {
|
||||
if (toolCall.id) currentBlock.id = toolCall.id;
|
||||
if (toolCall.function?.name) currentBlock.name = toolCall.function.name;
|
||||
let delta = "";
|
||||
if (toolCall.function?.arguments) {
|
||||
delta = toolCall.function.arguments;
|
||||
currentBlock.partialArgs += toolCall.function.arguments;
|
||||
currentBlock.arguments = parseStreamingJson(currentBlock.partialArgs);
|
||||
}
|
||||
stream.push({
|
||||
type: "toolcall_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const reasoningDetails = (choice.delta as any).reasoning_details;
|
||||
if (reasoningDetails && Array.isArray(reasoningDetails)) {
|
||||
for (const detail of reasoningDetails) {
|
||||
if (detail.type === "reasoning.encrypted" && detail.id && detail.data) {
|
||||
const matchingToolCall = output.content.find(
|
||||
(b) => b.type === "toolCall" && b.id === detail.id,
|
||||
) as ToolCall | undefined;
|
||||
if (matchingToolCall) {
|
||||
matchingToolCall.thoughtSignature = JSON.stringify(detail);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
finishCurrentBlock(currentBlock);
|
||||
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
if (output.stopReason === "aborted" || output.stopReason === "error") {
|
||||
throw new Error("An unkown error ocurred");
|
||||
}
|
||||
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
for (const block of output.content) delete (block as any).index;
|
||||
output.stopReason = options?.signal?.aborted ? "aborted" : "error";
|
||||
output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
stream.push({ type: "error", reason: output.stopReason, error: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function createClient(model: Model<"openai-completions">, context: Context, apiKey?: string) {
|
||||
if (!apiKey) {
|
||||
if (!process.env.OPENAI_API_KEY) {
|
||||
throw new Error(
|
||||
"OpenAI API key is required. Set OPENAI_API_KEY environment variable or pass it as an argument.",
|
||||
);
|
||||
}
|
||||
apiKey = process.env.OPENAI_API_KEY;
|
||||
}
|
||||
|
||||
const headers = { ...model.headers };
|
||||
if (model.provider === "github-copilot") {
|
||||
// Copilot expects X-Initiator to indicate whether the request is user-initiated
|
||||
// or agent-initiated (e.g. follow-up after assistant/tool messages). If there is
|
||||
// no prior message, default to user-initiated.
|
||||
const messages = context.messages || [];
|
||||
const lastMessage = messages[messages.length - 1];
|
||||
const isAgentCall = lastMessage ? lastMessage.role !== "user" : false;
|
||||
headers["X-Initiator"] = isAgentCall ? "agent" : "user";
|
||||
headers["Openai-Intent"] = "conversation-edits";
|
||||
|
||||
// Copilot requires this header when sending images
|
||||
const hasImages = messages.some((msg) => {
|
||||
if (msg.role === "user" && Array.isArray(msg.content)) {
|
||||
return msg.content.some((c) => c.type === "image");
|
||||
}
|
||||
if (msg.role === "toolResult" && Array.isArray(msg.content)) {
|
||||
return msg.content.some((c) => c.type === "image");
|
||||
}
|
||||
return false;
|
||||
});
|
||||
if (hasImages) {
|
||||
headers["Copilot-Vision-Request"] = "true";
|
||||
}
|
||||
}
|
||||
|
||||
return new OpenAI({
|
||||
apiKey,
|
||||
baseURL: model.baseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
defaultHeaders: headers,
|
||||
});
|
||||
}
|
||||
|
||||
function buildParams(model: Model<"openai-completions">, context: Context, options?: OpenAICompletionsOptions) {
|
||||
const compat = getCompat(model);
|
||||
const messages = convertMessages(model, context, compat);
|
||||
|
||||
const params: OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming = {
|
||||
model: model.id,
|
||||
messages,
|
||||
stream: true,
|
||||
stream_options: { include_usage: true },
|
||||
};
|
||||
|
||||
if (compat.supportsStore) {
|
||||
params.store = false;
|
||||
}
|
||||
|
||||
if (options?.maxTokens) {
|
||||
if (compat.maxTokensField === "max_tokens") {
|
||||
(params as any).max_tokens = options.maxTokens;
|
||||
} else {
|
||||
params.max_completion_tokens = options.maxTokens;
|
||||
}
|
||||
}
|
||||
|
||||
if (options?.temperature !== undefined) {
|
||||
params.temperature = options.temperature;
|
||||
}
|
||||
|
||||
if (context.tools) {
|
||||
params.tools = convertTools(context.tools);
|
||||
} else if (hasToolHistory(context.messages)) {
|
||||
// Anthropic (via LiteLLM/proxy) requires tools param when conversation has tool_calls/tool_results
|
||||
params.tools = [];
|
||||
}
|
||||
|
||||
if (options?.toolChoice) {
|
||||
params.tool_choice = options.toolChoice;
|
||||
}
|
||||
|
||||
if (options?.reasoningEffort && model.reasoning && compat.supportsReasoningEffort) {
|
||||
params.reasoning_effort = options.reasoningEffort;
|
||||
}
|
||||
|
||||
return params;
|
||||
}
|
||||
|
||||
function convertMessages(
|
||||
model: Model<"openai-completions">,
|
||||
context: Context,
|
||||
compat: Required<OpenAICompat>,
|
||||
): ChatCompletionMessageParam[] {
|
||||
const params: ChatCompletionMessageParam[] = [];
|
||||
|
||||
const transformedMessages = transformMessages(context.messages, model);
|
||||
|
||||
if (context.systemPrompt) {
|
||||
const useDeveloperRole = model.reasoning && compat.supportsDeveloperRole;
|
||||
const role = useDeveloperRole ? "developer" : "system";
|
||||
params.push({ role: role, content: sanitizeSurrogates(context.systemPrompt) });
|
||||
}
|
||||
|
||||
let lastRole: string | null = null;
|
||||
|
||||
for (const msg of transformedMessages) {
|
||||
// Some providers (e.g. Mistral/Devstral) don't allow user messages directly after tool results
|
||||
// Insert a synthetic assistant message to bridge the gap
|
||||
if (compat.requiresAssistantAfterToolResult && lastRole === "toolResult" && msg.role === "user") {
|
||||
params.push({
|
||||
role: "assistant",
|
||||
content: "I have processed the tool results.",
|
||||
});
|
||||
}
|
||||
|
||||
if (msg.role === "user") {
|
||||
if (typeof msg.content === "string") {
|
||||
params.push({
|
||||
role: "user",
|
||||
content: sanitizeSurrogates(msg.content),
|
||||
});
|
||||
} else {
|
||||
const content: ChatCompletionContentPart[] = msg.content.map((item): ChatCompletionContentPart => {
|
||||
if (item.type === "text") {
|
||||
return {
|
||||
type: "text",
|
||||
text: sanitizeSurrogates(item.text),
|
||||
} satisfies ChatCompletionContentPartText;
|
||||
} else {
|
||||
return {
|
||||
type: "image_url",
|
||||
image_url: {
|
||||
url: `data:${item.mimeType};base64,${item.data}`,
|
||||
},
|
||||
} satisfies ChatCompletionContentPartImage;
|
||||
}
|
||||
});
|
||||
const filteredContent = !model.input.includes("image")
|
||||
? content.filter((c) => c.type !== "image_url")
|
||||
: content;
|
||||
if (filteredContent.length === 0) continue;
|
||||
params.push({
|
||||
role: "user",
|
||||
content: filteredContent,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
// Some providers (e.g. Mistral) don't accept null content, use empty string instead
|
||||
const assistantMsg: ChatCompletionAssistantMessageParam = {
|
||||
role: "assistant",
|
||||
content: compat.requiresAssistantAfterToolResult ? "" : null,
|
||||
};
|
||||
|
||||
const textBlocks = msg.content.filter((b) => b.type === "text") as TextContent[];
|
||||
// Filter out empty text blocks to avoid API validation errors
|
||||
const nonEmptyTextBlocks = textBlocks.filter((b) => b.text && b.text.trim().length > 0);
|
||||
if (nonEmptyTextBlocks.length > 0) {
|
||||
// GitHub Copilot requires assistant content as a string, not an array.
|
||||
// Sending as array causes Claude models to re-answer all previous prompts.
|
||||
if (model.provider === "github-copilot") {
|
||||
assistantMsg.content = nonEmptyTextBlocks.map((b) => sanitizeSurrogates(b.text)).join("");
|
||||
} else {
|
||||
assistantMsg.content = nonEmptyTextBlocks.map((b) => {
|
||||
return { type: "text", text: sanitizeSurrogates(b.text) };
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Handle thinking blocks
|
||||
const thinkingBlocks = msg.content.filter((b) => b.type === "thinking") as ThinkingContent[];
|
||||
// Filter out empty thinking blocks to avoid API validation errors
|
||||
const nonEmptyThinkingBlocks = thinkingBlocks.filter((b) => b.thinking && b.thinking.trim().length > 0);
|
||||
if (nonEmptyThinkingBlocks.length > 0) {
|
||||
if (compat.requiresThinkingAsText) {
|
||||
// Convert thinking blocks to text with <thinking> delimiters
|
||||
const thinkingText = nonEmptyThinkingBlocks
|
||||
.map((b) => `<thinking>\n${b.thinking}\n</thinking>`)
|
||||
.join("\n");
|
||||
const textContent = assistantMsg.content as Array<{ type: "text"; text: string }> | null;
|
||||
if (textContent) {
|
||||
textContent.unshift({ type: "text", text: thinkingText });
|
||||
} else {
|
||||
assistantMsg.content = [{ type: "text", text: thinkingText }];
|
||||
}
|
||||
} else {
|
||||
// Use the signature from the first thinking block if available (for llama.cpp server + gpt-oss)
|
||||
const signature = nonEmptyThinkingBlocks[0].thinkingSignature;
|
||||
if (signature && signature.length > 0) {
|
||||
(assistantMsg as any)[signature] = nonEmptyThinkingBlocks.map((b) => b.thinking).join("\n");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const toolCalls = msg.content.filter((b) => b.type === "toolCall") as ToolCall[];
|
||||
if (toolCalls.length > 0) {
|
||||
assistantMsg.tool_calls = toolCalls.map((tc) => ({
|
||||
id: normalizeMistralToolId(tc.id, compat.requiresMistralToolIds),
|
||||
type: "function" as const,
|
||||
function: {
|
||||
name: tc.name,
|
||||
arguments: JSON.stringify(tc.arguments),
|
||||
},
|
||||
}));
|
||||
const reasoningDetails = toolCalls
|
||||
.filter((tc) => tc.thoughtSignature)
|
||||
.map((tc) => {
|
||||
try {
|
||||
return JSON.parse(tc.thoughtSignature!);
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
})
|
||||
.filter(Boolean);
|
||||
if (reasoningDetails.length > 0) {
|
||||
(assistantMsg as any).reasoning_details = reasoningDetails;
|
||||
}
|
||||
}
|
||||
// Skip assistant messages that have no content and no tool calls.
|
||||
// Mistral explicitly requires "either content or tool_calls, but not none".
|
||||
// Other providers also don't accept empty assistant messages.
|
||||
// This handles aborted assistant responses that got no content.
|
||||
const content = assistantMsg.content;
|
||||
const hasContent =
|
||||
content !== null &&
|
||||
content !== undefined &&
|
||||
(typeof content === "string" ? content.length > 0 : content.length > 0);
|
||||
if (!hasContent && !assistantMsg.tool_calls) {
|
||||
continue;
|
||||
}
|
||||
params.push(assistantMsg);
|
||||
} else if (msg.role === "toolResult") {
|
||||
// Extract text and image content
|
||||
const textResult = msg.content
|
||||
.filter((c) => c.type === "text")
|
||||
.map((c) => (c as any).text)
|
||||
.join("\n");
|
||||
const hasImages = msg.content.some((c) => c.type === "image");
|
||||
|
||||
// Always send tool result with text (or placeholder if only images)
|
||||
const hasText = textResult.length > 0;
|
||||
// Some providers (e.g. Mistral) require the 'name' field in tool results
|
||||
const toolResultMsg: ChatCompletionToolMessageParam = {
|
||||
role: "tool",
|
||||
content: sanitizeSurrogates(hasText ? textResult : "(see attached image)"),
|
||||
tool_call_id: normalizeMistralToolId(msg.toolCallId, compat.requiresMistralToolIds),
|
||||
};
|
||||
if (compat.requiresToolResultName && msg.toolName) {
|
||||
(toolResultMsg as any).name = msg.toolName;
|
||||
}
|
||||
params.push(toolResultMsg);
|
||||
|
||||
// If there are images and model supports them, send a follow-up user message with images
|
||||
if (hasImages && model.input.includes("image")) {
|
||||
const contentBlocks: Array<
|
||||
{ type: "text"; text: string } | { type: "image_url"; image_url: { url: string } }
|
||||
> = [];
|
||||
|
||||
// Add text prefix
|
||||
contentBlocks.push({
|
||||
type: "text",
|
||||
text: "Attached image(s) from tool result:",
|
||||
});
|
||||
|
||||
// Add images
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "image") {
|
||||
contentBlocks.push({
|
||||
type: "image_url",
|
||||
image_url: {
|
||||
url: `data:${(block as any).mimeType};base64,${(block as any).data}`,
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
params.push({
|
||||
role: "user",
|
||||
content: contentBlocks,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
lastRole = msg.role;
|
||||
}
|
||||
|
||||
return params;
|
||||
}
|
||||
|
||||
function convertTools(tools: Tool[]): OpenAI.Chat.Completions.ChatCompletionTool[] {
|
||||
return tools.map((tool) => ({
|
||||
type: "function",
|
||||
function: {
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters as any, // TypeBox already generates JSON Schema
|
||||
},
|
||||
}));
|
||||
}
|
||||
|
||||
function mapStopReason(reason: ChatCompletionChunk.Choice["finish_reason"]): StopReason {
|
||||
if (reason === null) return "stop";
|
||||
switch (reason) {
|
||||
case "stop":
|
||||
return "stop";
|
||||
case "length":
|
||||
return "length";
|
||||
case "function_call":
|
||||
case "tool_calls":
|
||||
return "toolUse";
|
||||
case "content_filter":
|
||||
return "error";
|
||||
default: {
|
||||
const _exhaustive: never = reason;
|
||||
throw new Error(`Unhandled stop reason: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Detect compatibility settings from baseUrl for known providers.
|
||||
* Returns a fully resolved OpenAICompat object with all fields set.
|
||||
*/
|
||||
function detectCompatFromUrl(baseUrl: string): Required<OpenAICompat> {
|
||||
const isNonStandard =
|
||||
baseUrl.includes("cerebras.ai") ||
|
||||
baseUrl.includes("api.x.ai") ||
|
||||
baseUrl.includes("mistral.ai") ||
|
||||
baseUrl.includes("chutes.ai") ||
|
||||
baseUrl.includes("localhost");
|
||||
|
||||
const useMaxTokens = baseUrl.includes("mistral.ai") || baseUrl.includes("chutes.ai");
|
||||
|
||||
const isGrok = baseUrl.includes("api.x.ai");
|
||||
|
||||
const isMistral = baseUrl.includes("mistral.ai");
|
||||
|
||||
return {
|
||||
supportsStore: !isNonStandard,
|
||||
supportsDeveloperRole: !isNonStandard,
|
||||
supportsReasoningEffort: !isGrok,
|
||||
maxTokensField: useMaxTokens ? "max_tokens" : "max_completion_tokens",
|
||||
requiresToolResultName: isMistral,
|
||||
requiresAssistantAfterToolResult: false, // Mistral no longer requires this as of Dec 2024
|
||||
requiresThinkingAsText: isMistral,
|
||||
requiresMistralToolIds: isMistral,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Get resolved compatibility settings for a model.
|
||||
* Uses explicit model.compat if provided, otherwise auto-detects from URL.
|
||||
*/
|
||||
function getCompat(model: Model<"openai-completions">): Required<OpenAICompat> {
|
||||
const detected = detectCompatFromUrl(model.baseUrl);
|
||||
if (!model.compat) return detected;
|
||||
|
||||
return {
|
||||
supportsStore: model.compat.supportsStore ?? detected.supportsStore,
|
||||
supportsDeveloperRole: model.compat.supportsDeveloperRole ?? detected.supportsDeveloperRole,
|
||||
supportsReasoningEffort: model.compat.supportsReasoningEffort ?? detected.supportsReasoningEffort,
|
||||
maxTokensField: model.compat.maxTokensField ?? detected.maxTokensField,
|
||||
requiresToolResultName: model.compat.requiresToolResultName ?? detected.requiresToolResultName,
|
||||
requiresAssistantAfterToolResult:
|
||||
model.compat.requiresAssistantAfterToolResult ?? detected.requiresAssistantAfterToolResult,
|
||||
requiresThinkingAsText: model.compat.requiresThinkingAsText ?? detected.requiresThinkingAsText,
|
||||
requiresMistralToolIds: model.compat.requiresMistralToolIds ?? detected.requiresMistralToolIds,
|
||||
};
|
||||
}
|
||||
@@ -1,569 +0,0 @@
|
||||
import OpenAI from "openai";
|
||||
import type {
|
||||
Tool as OpenAITool,
|
||||
ResponseCreateParamsStreaming,
|
||||
ResponseFunctionToolCall,
|
||||
ResponseInput,
|
||||
ResponseInputContent,
|
||||
ResponseInputImage,
|
||||
ResponseInputText,
|
||||
ResponseOutputMessage,
|
||||
ResponseReasoningItem,
|
||||
} from "openai/resources/responses/responses.js";
|
||||
import { calculateCost } from "../models";
|
||||
import { getEnvApiKey } from "../stream";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
Model,
|
||||
StopReason,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
Tool,
|
||||
ToolCall,
|
||||
} from "../types";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream";
|
||||
import { parseStreamingJson } from "../utils/json-parse";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode";
|
||||
import { transformMessages } from "./transorm-messages";
|
||||
|
||||
/** Fast deterministic hash to shorten long strings */
|
||||
function shortHash(str: string): string {
|
||||
let h1 = 0xdeadbeef;
|
||||
let h2 = 0x41c6ce57;
|
||||
for (let i = 0; i < str.length; i++) {
|
||||
const ch = str.charCodeAt(i);
|
||||
h1 = Math.imul(h1 ^ ch, 2654435761);
|
||||
h2 = Math.imul(h2 ^ ch, 1597334677);
|
||||
}
|
||||
h1 = Math.imul(h1 ^ (h1 >>> 16), 2246822507) ^ Math.imul(h2 ^ (h2 >>> 13), 3266489909);
|
||||
h2 = Math.imul(h2 ^ (h2 >>> 16), 2246822507) ^ Math.imul(h1 ^ (h1 >>> 13), 3266489909);
|
||||
return (h2 >>> 0).toString(36) + (h1 >>> 0).toString(36);
|
||||
}
|
||||
|
||||
// OpenAI Responses-specific options
|
||||
export interface OpenAIResponsesOptions extends StreamOptions {
|
||||
reasoningEffort?: "minimal" | "low" | "medium" | "high" | "xhigh";
|
||||
reasoningSummary?: "auto" | "detailed" | "concise" | null;
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate function for OpenAI Responses API
|
||||
*/
|
||||
export const streamOpenAIResponses: StreamFunction<"openai-responses"> = (
|
||||
model: Model<"openai-responses">,
|
||||
context: Context,
|
||||
options?: OpenAIResponsesOptions,
|
||||
): AssistantMessageEventStream => {
|
||||
const stream = new AssistantMessageEventStream();
|
||||
|
||||
// Start async processing
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: "openai-responses" as Api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
try {
|
||||
// Create OpenAI client
|
||||
const apiKey = options?.apiKey || getEnvApiKey(model.provider) || "";
|
||||
const client = createClient(model, context, apiKey);
|
||||
const params = buildParams(model, context, options);
|
||||
const openaiStream = await client.responses.create(params, { signal: options?.signal });
|
||||
stream.push({ type: "start", partial: output });
|
||||
|
||||
let currentItem: ResponseReasoningItem | ResponseOutputMessage | ResponseFunctionToolCall | null = null;
|
||||
let currentBlock: ThinkingContent | TextContent | (ToolCall & { partialJson: string }) | null = null;
|
||||
const blocks = output.content;
|
||||
const blockIndex = () => blocks.length - 1;
|
||||
|
||||
for await (const event of openaiStream) {
|
||||
// Handle output item start
|
||||
if (event.type === "response.output_item.added") {
|
||||
const item = event.item;
|
||||
if (item.type === "reasoning") {
|
||||
currentItem = item;
|
||||
currentBlock = { type: "thinking", thinking: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
|
||||
} else if (item.type === "message") {
|
||||
currentItem = item;
|
||||
currentBlock = { type: "text", text: "" };
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
|
||||
} else if (item.type === "function_call") {
|
||||
currentItem = item;
|
||||
currentBlock = {
|
||||
type: "toolCall",
|
||||
id: `${item.call_id}|${item.id}`,
|
||||
name: item.name,
|
||||
arguments: {},
|
||||
partialJson: item.arguments || "",
|
||||
};
|
||||
output.content.push(currentBlock);
|
||||
stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
|
||||
}
|
||||
}
|
||||
// Handle reasoning summary deltas
|
||||
else if (event.type === "response.reasoning_summary_part.added") {
|
||||
if (currentItem && currentItem.type === "reasoning") {
|
||||
currentItem.summary = currentItem.summary || [];
|
||||
currentItem.summary.push(event.part);
|
||||
}
|
||||
} else if (event.type === "response.reasoning_summary_text.delta") {
|
||||
if (
|
||||
currentItem &&
|
||||
currentItem.type === "reasoning" &&
|
||||
currentBlock &&
|
||||
currentBlock.type === "thinking"
|
||||
) {
|
||||
currentItem.summary = currentItem.summary || [];
|
||||
const lastPart = currentItem.summary[currentItem.summary.length - 1];
|
||||
if (lastPart) {
|
||||
currentBlock.thinking += event.delta;
|
||||
lastPart.text += event.delta;
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: event.delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
// Add a new line between summary parts (hack...)
|
||||
else if (event.type === "response.reasoning_summary_part.done") {
|
||||
if (
|
||||
currentItem &&
|
||||
currentItem.type === "reasoning" &&
|
||||
currentBlock &&
|
||||
currentBlock.type === "thinking"
|
||||
) {
|
||||
currentItem.summary = currentItem.summary || [];
|
||||
const lastPart = currentItem.summary[currentItem.summary.length - 1];
|
||||
if (lastPart) {
|
||||
currentBlock.thinking += "\n\n";
|
||||
lastPart.text += "\n\n";
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: "\n\n",
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
// Handle text output deltas
|
||||
else if (event.type === "response.content_part.added") {
|
||||
if (currentItem && currentItem.type === "message") {
|
||||
currentItem.content = currentItem.content || [];
|
||||
// Filter out ReasoningText, only accept output_text and refusal
|
||||
if (event.part.type === "output_text" || event.part.type === "refusal") {
|
||||
currentItem.content.push(event.part);
|
||||
}
|
||||
}
|
||||
} else if (event.type === "response.output_text.delta") {
|
||||
if (currentItem && currentItem.type === "message" && currentBlock && currentBlock.type === "text") {
|
||||
const lastPart = currentItem.content[currentItem.content.length - 1];
|
||||
if (lastPart && lastPart.type === "output_text") {
|
||||
currentBlock.text += event.delta;
|
||||
lastPart.text += event.delta;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: event.delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (event.type === "response.refusal.delta") {
|
||||
if (currentItem && currentItem.type === "message" && currentBlock && currentBlock.type === "text") {
|
||||
const lastPart = currentItem.content[currentItem.content.length - 1];
|
||||
if (lastPart && lastPart.type === "refusal") {
|
||||
currentBlock.text += event.delta;
|
||||
lastPart.refusal += event.delta;
|
||||
stream.push({
|
||||
type: "text_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: event.delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
// Handle function call argument deltas
|
||||
else if (event.type === "response.function_call_arguments.delta") {
|
||||
if (
|
||||
currentItem &&
|
||||
currentItem.type === "function_call" &&
|
||||
currentBlock &&
|
||||
currentBlock.type === "toolCall"
|
||||
) {
|
||||
currentBlock.partialJson += event.delta;
|
||||
currentBlock.arguments = parseStreamingJson(currentBlock.partialJson);
|
||||
stream.push({
|
||||
type: "toolcall_delta",
|
||||
contentIndex: blockIndex(),
|
||||
delta: event.delta,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
// Handle output item completion
|
||||
else if (event.type === "response.output_item.done") {
|
||||
const item = event.item;
|
||||
|
||||
if (item.type === "reasoning" && currentBlock && currentBlock.type === "thinking") {
|
||||
currentBlock.thinking = item.summary?.map((s) => s.text).join("\n\n") || "";
|
||||
currentBlock.thinkingSignature = JSON.stringify(item);
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
currentBlock = null;
|
||||
} else if (item.type === "message" && currentBlock && currentBlock.type === "text") {
|
||||
currentBlock.text = item.content.map((c) => (c.type === "output_text" ? c.text : c.refusal)).join("");
|
||||
currentBlock.textSignature = item.id;
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
contentIndex: blockIndex(),
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
currentBlock = null;
|
||||
} else if (item.type === "function_call") {
|
||||
const toolCall: ToolCall = {
|
||||
type: "toolCall",
|
||||
id: `${item.call_id}|${item.id}`,
|
||||
name: item.name,
|
||||
arguments: JSON.parse(item.arguments),
|
||||
};
|
||||
|
||||
stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
|
||||
}
|
||||
}
|
||||
// Handle completion
|
||||
else if (event.type === "response.completed") {
|
||||
const response = event.response;
|
||||
if (response?.usage) {
|
||||
const cachedTokens = response.usage.input_tokens_details?.cached_tokens || 0;
|
||||
output.usage = {
|
||||
// OpenAI includes cached tokens in input_tokens, so subtract to get non-cached input
|
||||
input: (response.usage.input_tokens || 0) - cachedTokens,
|
||||
output: response.usage.output_tokens || 0,
|
||||
cacheRead: cachedTokens,
|
||||
cacheWrite: 0,
|
||||
totalTokens: response.usage.total_tokens || 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
};
|
||||
}
|
||||
calculateCost(model, output.usage);
|
||||
// Map status to stop reason
|
||||
output.stopReason = mapStopReason(response?.status);
|
||||
if (output.content.some((b) => b.type === "toolCall") && output.stopReason === "stop") {
|
||||
output.stopReason = "toolUse";
|
||||
}
|
||||
}
|
||||
// Handle errors
|
||||
else if (event.type === "error") {
|
||||
throw new Error(`Error Code ${event.code}: ${event.message}` || "Unknown error");
|
||||
} else if (event.type === "response.failed") {
|
||||
throw new Error("Unknown error");
|
||||
}
|
||||
}
|
||||
|
||||
if (options?.signal?.aborted) {
|
||||
throw new Error("Request was aborted");
|
||||
}
|
||||
|
||||
if (output.stopReason === "aborted" || output.stopReason === "error") {
|
||||
throw new Error("An unkown error ocurred");
|
||||
}
|
||||
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
for (const block of output.content) delete (block as any).index;
|
||||
output.stopReason = options?.signal?.aborted ? "aborted" : "error";
|
||||
output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
stream.push({ type: "error", reason: output.stopReason, error: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function createClient(model: Model<"openai-responses">, context: Context, apiKey?: string) {
|
||||
if (!apiKey) {
|
||||
if (!process.env.OPENAI_API_KEY) {
|
||||
throw new Error(
|
||||
"OpenAI API key is required. Set OPENAI_API_KEY environment variable or pass it as an argument.",
|
||||
);
|
||||
}
|
||||
apiKey = process.env.OPENAI_API_KEY;
|
||||
}
|
||||
|
||||
const headers = { ...model.headers };
|
||||
if (model.provider === "github-copilot") {
|
||||
// Copilot expects X-Initiator to indicate whether the request is user-initiated
|
||||
// or agent-initiated (e.g. follow-up after assistant/tool messages). If there is
|
||||
// no prior message, default to user-initiated.
|
||||
const messages = context.messages || [];
|
||||
const lastMessage = messages[messages.length - 1];
|
||||
const isAgentCall = lastMessage ? lastMessage.role !== "user" : false;
|
||||
headers["X-Initiator"] = isAgentCall ? "agent" : "user";
|
||||
headers["Openai-Intent"] = "conversation-edits";
|
||||
|
||||
// Copilot requires this header when sending images
|
||||
const hasImages = messages.some((msg) => {
|
||||
if (msg.role === "user" && Array.isArray(msg.content)) {
|
||||
return msg.content.some((c) => c.type === "image");
|
||||
}
|
||||
if (msg.role === "toolResult" && Array.isArray(msg.content)) {
|
||||
return msg.content.some((c) => c.type === "image");
|
||||
}
|
||||
return false;
|
||||
});
|
||||
if (hasImages) {
|
||||
headers["Copilot-Vision-Request"] = "true";
|
||||
}
|
||||
}
|
||||
|
||||
return new OpenAI({
|
||||
apiKey,
|
||||
baseURL: model.baseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
defaultHeaders: headers,
|
||||
});
|
||||
}
|
||||
|
||||
function buildParams(model: Model<"openai-responses">, context: Context, options?: OpenAIResponsesOptions) {
|
||||
const messages = convertMessages(model, context);
|
||||
|
||||
const params: ResponseCreateParamsStreaming = {
|
||||
model: model.id,
|
||||
input: messages,
|
||||
stream: true,
|
||||
};
|
||||
|
||||
if (options?.maxTokens) {
|
||||
params.max_output_tokens = options?.maxTokens;
|
||||
}
|
||||
|
||||
if (options?.temperature !== undefined) {
|
||||
params.temperature = options?.temperature;
|
||||
}
|
||||
|
||||
if (context.tools) {
|
||||
params.tools = convertTools(context.tools);
|
||||
}
|
||||
|
||||
if (model.reasoning) {
|
||||
if (options?.reasoningEffort || options?.reasoningSummary) {
|
||||
params.reasoning = {
|
||||
effort: options?.reasoningEffort || "medium",
|
||||
summary: options?.reasoningSummary || "auto",
|
||||
};
|
||||
params.include = ["reasoning.encrypted_content"];
|
||||
} else {
|
||||
if (model.name.startsWith("gpt-5")) {
|
||||
// Jesus Christ, see https://community.openai.com/t/need-reasoning-false-option-for-gpt-5/1351588/7
|
||||
messages.push({
|
||||
role: "developer",
|
||||
content: [
|
||||
{
|
||||
type: "input_text",
|
||||
text: "# Juice: 0 !important",
|
||||
},
|
||||
],
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return params;
|
||||
}
|
||||
|
||||
function convertMessages(model: Model<"openai-responses">, context: Context): ResponseInput {
|
||||
const messages: ResponseInput = [];
|
||||
|
||||
const transformedMessages = transformMessages(context.messages, model);
|
||||
|
||||
if (context.systemPrompt) {
|
||||
const role = model.reasoning ? "developer" : "system";
|
||||
messages.push({
|
||||
role,
|
||||
content: sanitizeSurrogates(context.systemPrompt),
|
||||
});
|
||||
}
|
||||
|
||||
let msgIndex = 0;
|
||||
for (const msg of transformedMessages) {
|
||||
if (msg.role === "user") {
|
||||
if (typeof msg.content === "string") {
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: [{ type: "input_text", text: sanitizeSurrogates(msg.content) }],
|
||||
});
|
||||
} else {
|
||||
const content: ResponseInputContent[] = msg.content.map((item): ResponseInputContent => {
|
||||
if (item.type === "text") {
|
||||
return {
|
||||
type: "input_text",
|
||||
text: sanitizeSurrogates(item.text),
|
||||
} satisfies ResponseInputText;
|
||||
} else {
|
||||
return {
|
||||
type: "input_image",
|
||||
detail: "auto",
|
||||
image_url: `data:${item.mimeType};base64,${item.data}`,
|
||||
} satisfies ResponseInputImage;
|
||||
}
|
||||
});
|
||||
const filteredContent = !model.input.includes("image")
|
||||
? content.filter((c) => c.type !== "input_image")
|
||||
: content;
|
||||
if (filteredContent.length === 0) continue;
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: filteredContent,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
const output: ResponseInput = [];
|
||||
|
||||
for (const block of msg.content) {
|
||||
// Do not submit thinking blocks if the completion had an error (i.e. abort)
|
||||
if (block.type === "thinking" && msg.stopReason !== "error") {
|
||||
if (block.thinkingSignature) {
|
||||
const reasoningItem = JSON.parse(block.thinkingSignature);
|
||||
output.push(reasoningItem);
|
||||
}
|
||||
} else if (block.type === "text") {
|
||||
const textBlock = block as TextContent;
|
||||
// OpenAI requires id to be max 64 characters
|
||||
let msgId = textBlock.textSignature;
|
||||
if (!msgId) {
|
||||
msgId = `msg_${msgIndex}`;
|
||||
} else if (msgId.length > 64) {
|
||||
msgId = `msg_${shortHash(msgId)}`;
|
||||
}
|
||||
output.push({
|
||||
type: "message",
|
||||
role: "assistant",
|
||||
content: [{ type: "output_text", text: sanitizeSurrogates(textBlock.text), annotations: [] }],
|
||||
status: "completed",
|
||||
id: msgId,
|
||||
} satisfies ResponseOutputMessage);
|
||||
// Do not submit toolcall blocks if the completion had an error (i.e. abort)
|
||||
} else if (block.type === "toolCall" && msg.stopReason !== "error") {
|
||||
const toolCall = block as ToolCall;
|
||||
output.push({
|
||||
type: "function_call",
|
||||
id: toolCall.id.split("|")[1],
|
||||
call_id: toolCall.id.split("|")[0],
|
||||
name: toolCall.name,
|
||||
arguments: JSON.stringify(toolCall.arguments),
|
||||
});
|
||||
}
|
||||
}
|
||||
if (output.length === 0) continue;
|
||||
messages.push(...output);
|
||||
} else if (msg.role === "toolResult") {
|
||||
// Extract text and image content
|
||||
const textResult = msg.content
|
||||
.filter((c) => c.type === "text")
|
||||
.map((c) => (c as any).text)
|
||||
.join("\n");
|
||||
const hasImages = msg.content.some((c) => c.type === "image");
|
||||
|
||||
// Always send function_call_output with text (or placeholder if only images)
|
||||
const hasText = textResult.length > 0;
|
||||
messages.push({
|
||||
type: "function_call_output",
|
||||
call_id: msg.toolCallId.split("|")[0],
|
||||
output: sanitizeSurrogates(hasText ? textResult : "(see attached image)"),
|
||||
});
|
||||
|
||||
// If there are images and model supports them, send a follow-up user message with images
|
||||
if (hasImages && model.input.includes("image")) {
|
||||
const contentParts: ResponseInputContent[] = [];
|
||||
|
||||
// Add text prefix
|
||||
contentParts.push({
|
||||
type: "input_text",
|
||||
text: "Attached image(s) from tool result:",
|
||||
} satisfies ResponseInputText);
|
||||
|
||||
// Add images
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "image") {
|
||||
contentParts.push({
|
||||
type: "input_image",
|
||||
detail: "auto",
|
||||
image_url: `data:${(block as any).mimeType};base64,${(block as any).data}`,
|
||||
} satisfies ResponseInputImage);
|
||||
}
|
||||
}
|
||||
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: contentParts,
|
||||
});
|
||||
}
|
||||
}
|
||||
msgIndex++;
|
||||
}
|
||||
|
||||
return messages;
|
||||
}
|
||||
|
||||
function convertTools(tools: Tool[]): OpenAITool[] {
|
||||
return tools.map((tool) => ({
|
||||
type: "function",
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters as any, // TypeBox already generates JSON Schema
|
||||
strict: null,
|
||||
}));
|
||||
}
|
||||
|
||||
function mapStopReason(status: OpenAI.Responses.ResponseStatus | undefined): StopReason {
|
||||
if (!status) return "stop";
|
||||
switch (status) {
|
||||
case "completed":
|
||||
return "stop";
|
||||
case "incomplete":
|
||||
return "length";
|
||||
case "failed":
|
||||
case "cancelled":
|
||||
return "error";
|
||||
// These two are wonky ...
|
||||
case "in_progress":
|
||||
case "queued":
|
||||
return "stop";
|
||||
default: {
|
||||
const _exhaustive: never = status;
|
||||
throw new Error(`Unhandled stop reason: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,143 +0,0 @@
|
||||
import type { Api, AssistantMessage, Message, Model, ToolCall, ToolResultMessage } from "../types";
|
||||
|
||||
/**
|
||||
* Normalize tool call ID for GitHub Copilot cross-API compatibility.
|
||||
* OpenAI Responses API generates IDs that are 450+ chars with special characters like `|`.
|
||||
* Other APIs (Claude, etc.) require max 40 chars and only alphanumeric + underscore + hyphen.
|
||||
*/
|
||||
function normalizeCopilotToolCallId(id: string): string {
|
||||
return id.replace(/[^a-zA-Z0-9_-]/g, "").slice(0, 40);
|
||||
}
|
||||
|
||||
export function transformMessages<TApi extends Api>(messages: Message[], model: Model<TApi>): Message[] {
|
||||
// Build a map of original tool call IDs to normalized IDs for github-copilot cross-API switches
|
||||
const toolCallIdMap = new Map<string, string>();
|
||||
|
||||
// First pass: transform messages (thinking blocks, tool call ID normalization)
|
||||
const transformed = messages.map((msg) => {
|
||||
// User messages pass through unchanged
|
||||
if (msg.role === "user") {
|
||||
return msg;
|
||||
}
|
||||
|
||||
// Handle toolResult messages - normalize toolCallId if we have a mapping
|
||||
if (msg.role === "toolResult") {
|
||||
const normalizedId = toolCallIdMap.get(msg.toolCallId);
|
||||
if (normalizedId && normalizedId !== msg.toolCallId) {
|
||||
return { ...msg, toolCallId: normalizedId };
|
||||
}
|
||||
return msg;
|
||||
}
|
||||
|
||||
// Assistant messages need transformation check
|
||||
if (msg.role === "assistant") {
|
||||
const assistantMsg = msg as AssistantMessage;
|
||||
|
||||
// If message is from the same provider and API, keep as is
|
||||
if (assistantMsg.provider === model.provider && assistantMsg.api === model.api) {
|
||||
return msg;
|
||||
}
|
||||
|
||||
// Check if we need to normalize tool call IDs (github-copilot cross-API)
|
||||
const needsToolCallIdNormalization =
|
||||
assistantMsg.provider === "github-copilot" &&
|
||||
model.provider === "github-copilot" &&
|
||||
assistantMsg.api !== model.api;
|
||||
|
||||
// Transform message from different provider/model
|
||||
const transformedContent = assistantMsg.content.map((block) => {
|
||||
if (block.type === "thinking") {
|
||||
// Convert thinking block to text block with <thinking> tags
|
||||
return {
|
||||
type: "text" as const,
|
||||
text: `<thinking>\n${block.thinking}\n</thinking>`,
|
||||
};
|
||||
}
|
||||
// Normalize tool call IDs for github-copilot cross-API switches
|
||||
if (block.type === "toolCall" && needsToolCallIdNormalization) {
|
||||
const toolCall = block as ToolCall;
|
||||
const normalizedId = normalizeCopilotToolCallId(toolCall.id);
|
||||
if (normalizedId !== toolCall.id) {
|
||||
toolCallIdMap.set(toolCall.id, normalizedId);
|
||||
return { ...toolCall, id: normalizedId };
|
||||
}
|
||||
}
|
||||
// All other blocks pass through unchanged
|
||||
return block;
|
||||
});
|
||||
|
||||
// Return transformed assistant message
|
||||
return {
|
||||
...assistantMsg,
|
||||
content: transformedContent,
|
||||
};
|
||||
}
|
||||
return msg;
|
||||
});
|
||||
|
||||
// Second pass: insert synthetic empty tool results for orphaned tool calls
|
||||
// This preserves thinking signatures and satisfies API requirements
|
||||
const result: Message[] = [];
|
||||
let pendingToolCalls: ToolCall[] = [];
|
||||
let existingToolResultIds = new Set<string>();
|
||||
|
||||
for (let i = 0; i < transformed.length; i++) {
|
||||
const msg = transformed[i];
|
||||
|
||||
if (msg.role === "assistant") {
|
||||
// If we have pending orphaned tool calls from a previous assistant, insert synthetic results now
|
||||
if (pendingToolCalls.length > 0) {
|
||||
for (const tc of pendingToolCalls) {
|
||||
if (!existingToolResultIds.has(tc.id)) {
|
||||
result.push({
|
||||
role: "toolResult",
|
||||
toolCallId: tc.id,
|
||||
toolName: tc.name,
|
||||
content: [{ type: "text", text: "No result provided" }],
|
||||
isError: true,
|
||||
timestamp: Date.now(),
|
||||
} as ToolResultMessage);
|
||||
}
|
||||
}
|
||||
pendingToolCalls = [];
|
||||
existingToolResultIds = new Set();
|
||||
}
|
||||
|
||||
// Track tool calls from this assistant message
|
||||
const assistantMsg = msg as AssistantMessage;
|
||||
const toolCalls = assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[];
|
||||
if (toolCalls.length > 0) {
|
||||
pendingToolCalls = toolCalls;
|
||||
existingToolResultIds = new Set();
|
||||
}
|
||||
|
||||
result.push(msg);
|
||||
} else if (msg.role === "toolResult") {
|
||||
existingToolResultIds.add(msg.toolCallId);
|
||||
result.push(msg);
|
||||
} else if (msg.role === "user") {
|
||||
// User message interrupts tool flow - insert synthetic results for orphaned calls
|
||||
if (pendingToolCalls.length > 0) {
|
||||
for (const tc of pendingToolCalls) {
|
||||
if (!existingToolResultIds.has(tc.id)) {
|
||||
result.push({
|
||||
role: "toolResult",
|
||||
toolCallId: tc.id,
|
||||
toolName: tc.name,
|
||||
content: [{ type: "text", text: "No result provided" }],
|
||||
isError: true,
|
||||
timestamp: Date.now(),
|
||||
} as ToolResultMessage);
|
||||
}
|
||||
}
|
||||
pendingToolCalls = [];
|
||||
existingToolResultIds = new Set();
|
||||
}
|
||||
result.push(msg);
|
||||
} else {
|
||||
result.push(msg);
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
@@ -1,449 +0,0 @@
|
||||
import { existsSync } from "node:fs";
|
||||
import { homedir } from "node:os";
|
||||
import { join } from "node:path";
|
||||
import { supportsXhigh } from "./models";
|
||||
import { type AnthropicOptions, streamAnthropic } from "./providers/anthropic";
|
||||
import { type GoogleOptions, streamGoogle } from "./providers/google";
|
||||
import {
|
||||
type GoogleGeminiCliOptions,
|
||||
type GoogleThinkingLevel,
|
||||
streamGoogleGeminiCli,
|
||||
} from "./providers/google-gemini-cli";
|
||||
import { type GoogleVertexOptions, streamGoogleVertex } from "./providers/google-vertex";
|
||||
import { type OpenAICodexResponsesOptions, streamOpenAICodexResponses } from "./providers/openai-codex-responses";
|
||||
import { type OpenAICompletionsOptions, streamOpenAICompletions } from "./providers/openai-completions";
|
||||
import { type OpenAIResponsesOptions, streamOpenAIResponses } from "./providers/openai-responses";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
AssistantMessageEventStream,
|
||||
Context,
|
||||
KnownProvider,
|
||||
Model,
|
||||
OptionsForApi,
|
||||
ReasoningEffort,
|
||||
SimpleStreamOptions,
|
||||
} from "./types";
|
||||
|
||||
const VERTEX_ADC_CREDENTIALS_PATH = join(homedir(), ".config", "gcloud", "application_default_credentials.json");
|
||||
|
||||
let cachedVertexAdcCredentialsExists: boolean | null = null;
|
||||
|
||||
function hasVertexAdcCredentials(): boolean {
|
||||
if (cachedVertexAdcCredentialsExists === null) {
|
||||
cachedVertexAdcCredentialsExists = existsSync(VERTEX_ADC_CREDENTIALS_PATH);
|
||||
}
|
||||
return cachedVertexAdcCredentialsExists;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get API key for provider from known environment variables, e.g. OPENAI_API_KEY.
|
||||
*
|
||||
* Will not return API keys for providers that require OAuth tokens.
|
||||
*/
|
||||
export function getEnvApiKey(provider: KnownProvider): string | undefined;
|
||||
export function getEnvApiKey(provider: string): string | undefined;
|
||||
export function getEnvApiKey(provider: any): string | undefined {
|
||||
// Fall back to environment variables
|
||||
if (provider === "github-copilot") {
|
||||
return process.env.COPILOT_GITHUB_TOKEN || process.env.GH_TOKEN || process.env.GITHUB_TOKEN;
|
||||
}
|
||||
|
||||
// ANTHROPIC_OAUTH_TOKEN takes precedence over ANTHROPIC_API_KEY
|
||||
if (provider === "anthropic") {
|
||||
return process.env.ANTHROPIC_OAUTH_TOKEN || process.env.ANTHROPIC_API_KEY;
|
||||
}
|
||||
|
||||
// Vertex AI uses Application Default Credentials, not API keys.
|
||||
// Auth is configured via `gcloud auth application-default login`.
|
||||
if (provider === "google-vertex") {
|
||||
const hasCredentials = hasVertexAdcCredentials();
|
||||
const hasProject = !!(process.env.GOOGLE_CLOUD_PROJECT || process.env.GCLOUD_PROJECT);
|
||||
const hasLocation = !!process.env.GOOGLE_CLOUD_LOCATION;
|
||||
|
||||
if (hasCredentials && hasProject && hasLocation) {
|
||||
return "<authenticated>";
|
||||
}
|
||||
return undefined;
|
||||
}
|
||||
|
||||
const envMap: Record<string, string> = {
|
||||
openai: "OPENAI_API_KEY",
|
||||
google: "GEMINI_API_KEY",
|
||||
groq: "GROQ_API_KEY",
|
||||
cerebras: "CEREBRAS_API_KEY",
|
||||
xai: "XAI_API_KEY",
|
||||
openrouter: "OPENROUTER_API_KEY",
|
||||
zai: "ZAI_API_KEY",
|
||||
mistral: "MISTRAL_API_KEY",
|
||||
};
|
||||
|
||||
const envVar = envMap[provider];
|
||||
return envVar ? process.env[envVar] : undefined;
|
||||
}
|
||||
|
||||
export function stream<TApi extends Api>(
|
||||
model: Model<TApi>,
|
||||
context: Context,
|
||||
options?: OptionsForApi<TApi>,
|
||||
): AssistantMessageEventStream {
|
||||
// Vertex AI uses Application Default Credentials, not API keys
|
||||
if (model.api === "google-vertex") {
|
||||
return streamGoogleVertex(model as Model<"google-vertex">, context, options as GoogleVertexOptions);
|
||||
}
|
||||
|
||||
const apiKey = options?.apiKey || getEnvApiKey(model.provider);
|
||||
if (!apiKey) {
|
||||
throw new Error(`No API key for provider: ${model.provider}`);
|
||||
}
|
||||
const providerOptions = { ...options, apiKey };
|
||||
|
||||
const api: Api = model.api;
|
||||
switch (api) {
|
||||
case "anthropic-messages":
|
||||
return streamAnthropic(model as Model<"anthropic-messages">, context, providerOptions);
|
||||
|
||||
case "openai-completions":
|
||||
return streamOpenAICompletions(model as Model<"openai-completions">, context, providerOptions as any);
|
||||
|
||||
case "openai-responses":
|
||||
return streamOpenAIResponses(model as Model<"openai-responses">, context, providerOptions as any);
|
||||
|
||||
case "openai-codex-responses":
|
||||
return streamOpenAICodexResponses(model as Model<"openai-codex-responses">, context, providerOptions as any);
|
||||
|
||||
case "google-generative-ai":
|
||||
return streamGoogle(model as Model<"google-generative-ai">, context, providerOptions);
|
||||
|
||||
case "google-gemini-cli":
|
||||
return streamGoogleGeminiCli(
|
||||
model as Model<"google-gemini-cli">,
|
||||
context,
|
||||
providerOptions as GoogleGeminiCliOptions,
|
||||
);
|
||||
|
||||
default: {
|
||||
// This should never be reached if all Api cases are handled
|
||||
const _exhaustive: never = api;
|
||||
throw new Error(`Unhandled API: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export async function complete<TApi extends Api>(
|
||||
model: Model<TApi>,
|
||||
context: Context,
|
||||
options?: OptionsForApi<TApi>,
|
||||
): Promise<AssistantMessage> {
|
||||
const s = stream(model, context, options);
|
||||
return s.result();
|
||||
}
|
||||
|
||||
export function streamSimple<TApi extends Api>(
|
||||
model: Model<TApi>,
|
||||
context: Context,
|
||||
options?: SimpleStreamOptions,
|
||||
): AssistantMessageEventStream {
|
||||
// Vertex AI uses Application Default Credentials, not API keys
|
||||
if (model.api === "google-vertex") {
|
||||
const providerOptions = mapOptionsForApi(model, options, undefined);
|
||||
return stream(model, context, providerOptions);
|
||||
}
|
||||
|
||||
const apiKey = options?.apiKey || getEnvApiKey(model.provider);
|
||||
if (!apiKey) {
|
||||
throw new Error(`No API key for provider: ${model.provider}`);
|
||||
}
|
||||
|
||||
const providerOptions = mapOptionsForApi(model, options, apiKey);
|
||||
return stream(model, context, providerOptions);
|
||||
}
|
||||
|
||||
export async function completeSimple<TApi extends Api>(
|
||||
model: Model<TApi>,
|
||||
context: Context,
|
||||
options?: SimpleStreamOptions,
|
||||
): Promise<AssistantMessage> {
|
||||
const s = streamSimple(model, context, options);
|
||||
return s.result();
|
||||
}
|
||||
|
||||
function mapOptionsForApi<TApi extends Api>(
|
||||
model: Model<TApi>,
|
||||
options?: SimpleStreamOptions,
|
||||
apiKey?: string,
|
||||
): OptionsForApi<TApi> {
|
||||
const base = {
|
||||
temperature: options?.temperature,
|
||||
maxTokens: options?.maxTokens || Math.min(model.maxTokens, 32000),
|
||||
signal: options?.signal,
|
||||
apiKey: apiKey || options?.apiKey,
|
||||
};
|
||||
|
||||
// Helper to clamp xhigh to high for providers that don't support it
|
||||
const clampReasoning = (effort: ReasoningEffort | undefined) => (effort === "xhigh" ? "high" : effort);
|
||||
|
||||
switch (model.api) {
|
||||
case "anthropic-messages": {
|
||||
// Explicitly disable thinking when reasoning is not specified
|
||||
if (!options?.reasoning) {
|
||||
return { ...base, thinkingEnabled: false } satisfies AnthropicOptions;
|
||||
}
|
||||
|
||||
// Claude requires max_tokens > thinking.budget_tokens
|
||||
// So we need to ensure maxTokens accounts for both thinking and output
|
||||
const anthropicBudgets = {
|
||||
minimal: 1024,
|
||||
low: 2048,
|
||||
medium: 8192,
|
||||
high: 16384,
|
||||
};
|
||||
|
||||
const minOutputTokens = 1024;
|
||||
let thinkingBudget = anthropicBudgets[clampReasoning(options.reasoning)!];
|
||||
// Caller's maxTokens is the desired output; add thinking budget on top, capped at model limit
|
||||
const maxTokens = Math.min((base.maxTokens || 0) + thinkingBudget, model.maxTokens);
|
||||
|
||||
// If not enough room for thinking + output, reduce thinking budget
|
||||
if (maxTokens <= thinkingBudget) {
|
||||
thinkingBudget = Math.max(0, maxTokens - minOutputTokens);
|
||||
}
|
||||
|
||||
return {
|
||||
...base,
|
||||
maxTokens,
|
||||
thinkingEnabled: true,
|
||||
thinkingBudgetTokens: thinkingBudget,
|
||||
} satisfies AnthropicOptions;
|
||||
}
|
||||
|
||||
case "openai-completions":
|
||||
return {
|
||||
...base,
|
||||
reasoningEffort: supportsXhigh(model) ? options?.reasoning : clampReasoning(options?.reasoning),
|
||||
} satisfies OpenAICompletionsOptions;
|
||||
|
||||
case "openai-responses":
|
||||
return {
|
||||
...base,
|
||||
reasoningEffort: supportsXhigh(model) ? options?.reasoning : clampReasoning(options?.reasoning),
|
||||
} satisfies OpenAIResponsesOptions;
|
||||
|
||||
case "openai-codex-responses":
|
||||
return {
|
||||
...base,
|
||||
reasoningEffort: supportsXhigh(model) ? options?.reasoning : clampReasoning(options?.reasoning),
|
||||
} satisfies OpenAICodexResponsesOptions;
|
||||
|
||||
case "google-generative-ai": {
|
||||
// Explicitly disable thinking when reasoning is not specified
|
||||
// This is needed because Gemini has "dynamic thinking" enabled by default
|
||||
if (!options?.reasoning) {
|
||||
return { ...base, thinking: { enabled: false } } satisfies GoogleOptions;
|
||||
}
|
||||
|
||||
const googleModel = model as Model<"google-generative-ai">;
|
||||
const effort = clampReasoning(options.reasoning)!;
|
||||
|
||||
// Gemini 3 models use thinkingLevel exclusively instead of thinkingBudget.
|
||||
// https://ai.google.dev/gemini-api/docs/thinking#set-budget
|
||||
if (isGemini3ProModel(googleModel) || isGemini3FlashModel(googleModel)) {
|
||||
return {
|
||||
...base,
|
||||
thinking: {
|
||||
enabled: true,
|
||||
level: getGemini3ThinkingLevel(effort, googleModel),
|
||||
},
|
||||
} satisfies GoogleOptions;
|
||||
}
|
||||
|
||||
return {
|
||||
...base,
|
||||
thinking: {
|
||||
enabled: true,
|
||||
budgetTokens: getGoogleBudget(googleModel, effort),
|
||||
},
|
||||
} satisfies GoogleOptions;
|
||||
}
|
||||
|
||||
case "google-gemini-cli": {
|
||||
if (!options?.reasoning) {
|
||||
return { ...base, thinking: { enabled: false } } satisfies GoogleGeminiCliOptions;
|
||||
}
|
||||
|
||||
const effort = clampReasoning(options.reasoning)!;
|
||||
|
||||
// Gemini 3 models use thinkingLevel instead of thinkingBudget
|
||||
if (model.id.includes("3-pro") || model.id.includes("3-flash")) {
|
||||
return {
|
||||
...base,
|
||||
thinking: {
|
||||
enabled: true,
|
||||
level: getGeminiCliThinkingLevel(effort, model.id),
|
||||
},
|
||||
} satisfies GoogleGeminiCliOptions;
|
||||
}
|
||||
|
||||
// Models using thinkingBudget (Gemini 2.x, Claude via Antigravity)
|
||||
// Claude requires max_tokens > thinking.budget_tokens
|
||||
// So we need to ensure maxTokens accounts for both thinking and output
|
||||
const budgets: Record<ClampedReasoningEffort, number> = {
|
||||
minimal: 1024,
|
||||
low: 2048,
|
||||
medium: 8192,
|
||||
high: 16384,
|
||||
};
|
||||
|
||||
const minOutputTokens = 1024;
|
||||
let thinkingBudget = budgets[effort];
|
||||
// Caller's maxTokens is the desired output; add thinking budget on top, capped at model limit
|
||||
const maxTokens = Math.min((base.maxTokens || 0) + thinkingBudget, model.maxTokens);
|
||||
|
||||
// If not enough room for thinking + output, reduce thinking budget
|
||||
if (maxTokens <= thinkingBudget) {
|
||||
thinkingBudget = Math.max(0, maxTokens - minOutputTokens);
|
||||
}
|
||||
|
||||
return {
|
||||
...base,
|
||||
maxTokens,
|
||||
thinking: {
|
||||
enabled: true,
|
||||
budgetTokens: thinkingBudget,
|
||||
},
|
||||
} satisfies GoogleGeminiCliOptions;
|
||||
}
|
||||
|
||||
case "google-vertex": {
|
||||
// Explicitly disable thinking when reasoning is not specified
|
||||
// This is needed because Gemini has "dynamic thinking" enabled by default
|
||||
if (!options?.reasoning) {
|
||||
return { ...base, thinking: { enabled: false } } satisfies GoogleVertexOptions;
|
||||
}
|
||||
|
||||
const googleModel = model as Model<"google-vertex">;
|
||||
const effort = clampReasoning(options.reasoning)!;
|
||||
|
||||
// Gemini 3 models use thinkingLevel exclusively instead of thinkingBudget.
|
||||
// https://ai.google.dev/gemini-api/docs/thinking#set-budget
|
||||
if (isGemini3ProModel(googleModel) || isGemini3FlashModel(googleModel)) {
|
||||
return {
|
||||
...base,
|
||||
thinking: {
|
||||
enabled: true,
|
||||
level: getGemini3ThinkingLevel(effort, googleModel),
|
||||
},
|
||||
} satisfies GoogleVertexOptions;
|
||||
}
|
||||
|
||||
return {
|
||||
...base,
|
||||
thinking: {
|
||||
enabled: true,
|
||||
budgetTokens: getGoogleBudget(googleModel, effort),
|
||||
},
|
||||
} satisfies GoogleVertexOptions;
|
||||
}
|
||||
|
||||
default: {
|
||||
// Exhaustiveness check
|
||||
const _exhaustive: never = model.api;
|
||||
throw new Error(`Unhandled API in mapOptionsForApi: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
type ClampedReasoningEffort = Exclude<ReasoningEffort, "xhigh">;
|
||||
|
||||
function isGemini3ProModel(model: Model<"google-generative-ai"> | Model<"google-vertex">): boolean {
|
||||
// Covers gemini-3-pro, gemini-3-pro-preview, and possible other prefixed ids in the future
|
||||
return model.id.includes("3-pro");
|
||||
}
|
||||
|
||||
function isGemini3FlashModel(model: Model<"google-generative-ai"> | Model<"google-vertex">): boolean {
|
||||
// Covers gemini-3-flash, gemini-3-flash-preview, and possible other prefixed ids in the future
|
||||
return model.id.includes("3-flash");
|
||||
}
|
||||
|
||||
function getGemini3ThinkingLevel(
|
||||
effort: ClampedReasoningEffort,
|
||||
model: Model<"google-generative-ai"> | Model<"google-vertex">,
|
||||
): GoogleThinkingLevel {
|
||||
if (isGemini3ProModel(model)) {
|
||||
// Gemini 3 Pro only supports LOW/HIGH (for now)
|
||||
switch (effort) {
|
||||
case "minimal":
|
||||
case "low":
|
||||
return "LOW";
|
||||
case "medium":
|
||||
case "high":
|
||||
return "HIGH";
|
||||
}
|
||||
}
|
||||
// Gemini 3 Flash supports all four levels
|
||||
switch (effort) {
|
||||
case "minimal":
|
||||
return "MINIMAL";
|
||||
case "low":
|
||||
return "LOW";
|
||||
case "medium":
|
||||
return "MEDIUM";
|
||||
case "high":
|
||||
return "HIGH";
|
||||
}
|
||||
}
|
||||
|
||||
function getGeminiCliThinkingLevel(effort: ClampedReasoningEffort, modelId: string): GoogleThinkingLevel {
|
||||
if (modelId.includes("3-pro")) {
|
||||
// Gemini 3 Pro only supports LOW/HIGH (for now)
|
||||
switch (effort) {
|
||||
case "minimal":
|
||||
case "low":
|
||||
return "LOW";
|
||||
case "medium":
|
||||
case "high":
|
||||
return "HIGH";
|
||||
}
|
||||
}
|
||||
// Gemini 3 Flash supports all four levels
|
||||
switch (effort) {
|
||||
case "minimal":
|
||||
return "MINIMAL";
|
||||
case "low":
|
||||
return "LOW";
|
||||
case "medium":
|
||||
return "MEDIUM";
|
||||
case "high":
|
||||
return "HIGH";
|
||||
}
|
||||
}
|
||||
|
||||
function getGoogleBudget(
|
||||
model: Model<"google-generative-ai"> | Model<"google-vertex">,
|
||||
effort: ClampedReasoningEffort,
|
||||
): number {
|
||||
// See https://ai.google.dev/gemini-api/docs/thinking#set-budget
|
||||
if (model.id.includes("2.5-pro")) {
|
||||
const budgets: Record<ClampedReasoningEffort, number> = {
|
||||
minimal: 128,
|
||||
low: 2048,
|
||||
medium: 8192,
|
||||
high: 32768,
|
||||
};
|
||||
return budgets[effort];
|
||||
}
|
||||
|
||||
if (model.id.includes("2.5-flash")) {
|
||||
// Covers 2.5-flash-lite as well
|
||||
const budgets: Record<ClampedReasoningEffort, number> = {
|
||||
minimal: 128,
|
||||
low: 2048,
|
||||
medium: 8192,
|
||||
high: 24576,
|
||||
};
|
||||
return budgets[effort];
|
||||
}
|
||||
|
||||
// Unknown model - use dynamic
|
||||
return -1;
|
||||
}
|
||||
@@ -1,232 +0,0 @@
|
||||
import type { AnthropicOptions } from "./providers/anthropic";
|
||||
import type { GoogleOptions } from "./providers/google";
|
||||
import type { GoogleGeminiCliOptions } from "./providers/google-gemini-cli";
|
||||
import type { GoogleVertexOptions } from "./providers/google-vertex";
|
||||
import type { OpenAICodexResponsesOptions } from "./providers/openai-codex-responses";
|
||||
import type { OpenAICompletionsOptions } from "./providers/openai-completions";
|
||||
import type { OpenAIResponsesOptions } from "./providers/openai-responses";
|
||||
import type { AssistantMessageEventStream } from "./utils/event-stream";
|
||||
|
||||
export type { AssistantMessageEventStream } from "./utils/event-stream";
|
||||
|
||||
export type Api =
|
||||
| "openai-completions"
|
||||
| "openai-responses"
|
||||
| "openai-codex-responses"
|
||||
| "anthropic-messages"
|
||||
| "google-generative-ai"
|
||||
| "google-gemini-cli"
|
||||
| "google-vertex";
|
||||
|
||||
export interface ApiOptionsMap {
|
||||
"anthropic-messages": AnthropicOptions;
|
||||
"openai-completions": OpenAICompletionsOptions;
|
||||
"openai-responses": OpenAIResponsesOptions;
|
||||
"openai-codex-responses": OpenAICodexResponsesOptions;
|
||||
"google-generative-ai": GoogleOptions;
|
||||
"google-gemini-cli": GoogleGeminiCliOptions;
|
||||
"google-vertex": GoogleVertexOptions;
|
||||
}
|
||||
|
||||
// Compile-time exhaustiveness check - this will fail if ApiOptionsMap doesn't have all KnownApi keys
|
||||
type _CheckExhaustive =
|
||||
ApiOptionsMap extends Record<Api, StreamOptions>
|
||||
? Record<Api, StreamOptions> extends ApiOptionsMap
|
||||
? true
|
||||
: ["ApiOptionsMap is missing some KnownApi values", Exclude<Api, keyof ApiOptionsMap>]
|
||||
: ["ApiOptionsMap doesn't extend Record<KnownApi, StreamOptions>"];
|
||||
const _exhaustive: _CheckExhaustive = true;
|
||||
|
||||
// Helper type to get options for a specific API
|
||||
export type OptionsForApi<TApi extends Api> = ApiOptionsMap[TApi];
|
||||
|
||||
export type KnownProvider =
|
||||
| "anthropic"
|
||||
| "google"
|
||||
| "google-gemini-cli"
|
||||
| "google-antigravity"
|
||||
| "google-vertex"
|
||||
| "openai"
|
||||
| "openai-codex"
|
||||
| "github-copilot"
|
||||
| "xai"
|
||||
| "groq"
|
||||
| "cerebras"
|
||||
| "openrouter"
|
||||
| "zai"
|
||||
| "mistral";
|
||||
export type Provider = KnownProvider | string;
|
||||
|
||||
export type ReasoningEffort = "minimal" | "low" | "medium" | "high" | "xhigh";
|
||||
|
||||
// Base options all providers share
|
||||
export interface StreamOptions {
|
||||
temperature?: number;
|
||||
maxTokens?: number;
|
||||
signal?: AbortSignal;
|
||||
apiKey?: string;
|
||||
/**
|
||||
* Optional session identifier for providers that support session-based caching.
|
||||
* Providers can use this to enable prompt caching, request routing, or other
|
||||
* session-aware features. Ignored by providers that don't support it.
|
||||
*/
|
||||
sessionId?: string;
|
||||
}
|
||||
|
||||
// Unified options with reasoning passed to streamSimple() and completeSimple()
|
||||
export interface SimpleStreamOptions extends StreamOptions {
|
||||
reasoning?: ReasoningEffort;
|
||||
}
|
||||
|
||||
// Generic StreamFunction with typed options
|
||||
export type StreamFunction<TApi extends Api> = (
|
||||
model: Model<TApi>,
|
||||
context: Context,
|
||||
options: OptionsForApi<TApi>,
|
||||
) => AssistantMessageEventStream;
|
||||
|
||||
export interface TextContent {
|
||||
type: "text";
|
||||
text: string;
|
||||
textSignature?: string; // e.g., for OpenAI responses, the message ID
|
||||
}
|
||||
|
||||
export interface ThinkingContent {
|
||||
type: "thinking";
|
||||
thinking: string;
|
||||
thinkingSignature?: string; // e.g., for OpenAI responses, the reasoning item ID
|
||||
}
|
||||
|
||||
export interface ImageContent {
|
||||
type: "image";
|
||||
data: string; // base64 encoded image data
|
||||
mimeType: string; // e.g., "image/jpeg", "image/png"
|
||||
}
|
||||
|
||||
export interface ToolCall {
|
||||
type: "toolCall";
|
||||
id: string;
|
||||
name: string;
|
||||
arguments: Record<string, any>;
|
||||
thoughtSignature?: string; // Google-specific: opaque signature for reusing thought context
|
||||
}
|
||||
|
||||
export interface Usage {
|
||||
input: number;
|
||||
output: number;
|
||||
cacheRead: number;
|
||||
cacheWrite: number;
|
||||
totalTokens: number;
|
||||
cost: {
|
||||
input: number;
|
||||
output: number;
|
||||
cacheRead: number;
|
||||
cacheWrite: number;
|
||||
total: number;
|
||||
};
|
||||
}
|
||||
|
||||
export type StopReason = "stop" | "length" | "toolUse" | "error" | "aborted";
|
||||
|
||||
export interface UserMessage {
|
||||
role: "user";
|
||||
content: string | (TextContent | ImageContent)[];
|
||||
timestamp: number; // Unix timestamp in milliseconds
|
||||
}
|
||||
|
||||
export interface AssistantMessage {
|
||||
role: "assistant";
|
||||
content: (TextContent | ThinkingContent | ToolCall)[];
|
||||
api: Api;
|
||||
provider: Provider;
|
||||
model: string;
|
||||
usage: Usage;
|
||||
stopReason: StopReason;
|
||||
errorMessage?: string;
|
||||
timestamp: number; // Unix timestamp in milliseconds
|
||||
}
|
||||
|
||||
export interface ToolResultMessage<TDetails = any> {
|
||||
role: "toolResult";
|
||||
toolCallId: string;
|
||||
toolName: string;
|
||||
content: (TextContent | ImageContent)[]; // Supports text and images
|
||||
details?: TDetails;
|
||||
isError?: boolean;
|
||||
timestamp: number; // Unix timestamp in milliseconds
|
||||
}
|
||||
|
||||
export type Message = UserMessage | AssistantMessage | ToolResultMessage;
|
||||
|
||||
import type { TSchema } from "@sinclair/typebox";
|
||||
|
||||
export interface Tool<TParameters extends TSchema = TSchema> {
|
||||
name: string;
|
||||
description: string;
|
||||
parameters: TParameters;
|
||||
}
|
||||
|
||||
export interface Context {
|
||||
systemPrompt?: string;
|
||||
messages: Message[];
|
||||
tools?: Tool[];
|
||||
}
|
||||
|
||||
export type AssistantMessageEvent =
|
||||
| { type: "start"; partial: AssistantMessage }
|
||||
| { type: "text_start"; contentIndex: number; partial: AssistantMessage }
|
||||
| { type: "text_delta"; contentIndex: number; delta: string; partial: AssistantMessage }
|
||||
| { type: "text_end"; contentIndex: number; content: string; partial: AssistantMessage }
|
||||
| { type: "thinking_start"; contentIndex: number; partial: AssistantMessage }
|
||||
| { type: "thinking_delta"; contentIndex: number; delta: string; partial: AssistantMessage }
|
||||
| { type: "thinking_end"; contentIndex: number; content: string; partial: AssistantMessage }
|
||||
| { type: "toolcall_start"; contentIndex: number; partial: AssistantMessage }
|
||||
| { type: "toolcall_delta"; contentIndex: number; delta: string; partial: AssistantMessage }
|
||||
| { type: "toolcall_end"; contentIndex: number; toolCall: ToolCall; partial: AssistantMessage }
|
||||
| { type: "done"; reason: Extract<StopReason, "stop" | "length" | "toolUse">; message: AssistantMessage }
|
||||
| { type: "error"; reason: Extract<StopReason, "aborted" | "error">; error: AssistantMessage };
|
||||
|
||||
/**
|
||||
* Compatibility settings for openai-completions API.
|
||||
* Use this to override URL-based auto-detection for custom providers.
|
||||
*/
|
||||
export interface OpenAICompat {
|
||||
/** Whether the provider supports the `store` field. Default: auto-detected from URL. */
|
||||
supportsStore?: boolean;
|
||||
/** Whether the provider supports the `developer` role (vs `system`). Default: auto-detected from URL. */
|
||||
supportsDeveloperRole?: boolean;
|
||||
/** Whether the provider supports `reasoning_effort`. Default: auto-detected from URL. */
|
||||
supportsReasoningEffort?: boolean;
|
||||
/** Which field to use for max tokens. Default: auto-detected from URL. */
|
||||
maxTokensField?: "max_completion_tokens" | "max_tokens";
|
||||
/** Whether tool results require the `name` field. Default: auto-detected from URL. */
|
||||
requiresToolResultName?: boolean;
|
||||
/** Whether a user message after tool results requires an assistant message in between. Default: auto-detected from URL. */
|
||||
requiresAssistantAfterToolResult?: boolean;
|
||||
/** Whether thinking blocks must be converted to text blocks with <thinking> delimiters. Default: auto-detected from URL. */
|
||||
requiresThinkingAsText?: boolean;
|
||||
/** Whether tool call IDs must be normalized to Mistral format (exactly 9 alphanumeric chars). Default: auto-detected from URL. */
|
||||
requiresMistralToolIds?: boolean;
|
||||
}
|
||||
|
||||
// Model interface for the unified model system
|
||||
export interface Model<TApi extends Api> {
|
||||
id: string;
|
||||
name: string;
|
||||
api: TApi;
|
||||
provider: Provider;
|
||||
baseUrl: string;
|
||||
reasoning: boolean;
|
||||
input: ("text" | "image")[];
|
||||
cost: {
|
||||
input: number; // $/million tokens
|
||||
output: number; // $/million tokens
|
||||
cacheRead: number; // $/million tokens
|
||||
cacheWrite: number; // $/million tokens
|
||||
};
|
||||
contextWindow: number;
|
||||
maxTokens: number;
|
||||
headers?: Record<string, string>;
|
||||
/** Compatibility overrides for openai-completions API. If not set, auto-detected from baseUrl. */
|
||||
compat?: TApi extends "openai-completions" ? OpenAICompat : never;
|
||||
}
|
||||
@@ -1,82 +0,0 @@
|
||||
import type { AssistantMessage, AssistantMessageEvent } from "../types";
|
||||
|
||||
// Generic event stream class for async iteration
|
||||
export class EventStream<T, R = T> implements AsyncIterable<T> {
|
||||
private queue: T[] = [];
|
||||
private waiting: ((value: IteratorResult<T>) => void)[] = [];
|
||||
private done = false;
|
||||
private finalResultPromise: Promise<R>;
|
||||
private resolveFinalResult!: (result: R) => void;
|
||||
|
||||
constructor(
|
||||
private isComplete: (event: T) => boolean,
|
||||
private extractResult: (event: T) => R,
|
||||
) {
|
||||
this.finalResultPromise = new Promise((resolve) => {
|
||||
this.resolveFinalResult = resolve;
|
||||
});
|
||||
}
|
||||
|
||||
push(event: T): void {
|
||||
if (this.done) return;
|
||||
|
||||
if (this.isComplete(event)) {
|
||||
this.done = true;
|
||||
this.resolveFinalResult(this.extractResult(event));
|
||||
}
|
||||
|
||||
// Deliver to waiting consumer or queue it
|
||||
const waiter = this.waiting.shift();
|
||||
if (waiter) {
|
||||
waiter({ value: event, done: false });
|
||||
} else {
|
||||
this.queue.push(event);
|
||||
}
|
||||
}
|
||||
|
||||
end(result?: R): void {
|
||||
this.done = true;
|
||||
if (result !== undefined) {
|
||||
this.resolveFinalResult(result);
|
||||
}
|
||||
// Notify all waiting consumers that we're done
|
||||
while (this.waiting.length > 0) {
|
||||
const waiter = this.waiting.shift()!;
|
||||
waiter({ value: undefined as any, done: true });
|
||||
}
|
||||
}
|
||||
|
||||
async *[Symbol.asyncIterator](): AsyncIterator<T> {
|
||||
while (true) {
|
||||
if (this.queue.length > 0) {
|
||||
yield this.queue.shift()!;
|
||||
} else if (this.done) {
|
||||
return;
|
||||
} else {
|
||||
const result = await new Promise<IteratorResult<T>>((resolve) => this.waiting.push(resolve));
|
||||
if (result.done) return;
|
||||
yield result.value;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
result(): Promise<R> {
|
||||
return this.finalResultPromise;
|
||||
}
|
||||
}
|
||||
|
||||
export class AssistantMessageEventStream extends EventStream<AssistantMessageEvent, AssistantMessage> {
|
||||
constructor() {
|
||||
super(
|
||||
(event) => event.type === "done" || event.type === "error",
|
||||
(event) => {
|
||||
if (event.type === "done") {
|
||||
return event.message;
|
||||
} else if (event.type === "error") {
|
||||
return event.error;
|
||||
}
|
||||
throw new Error("Unexpected event type for final result");
|
||||
},
|
||||
);
|
||||
}
|
||||
}
|
||||
@@ -1,28 +0,0 @@
|
||||
import { parse as partialParse } from "partial-json";
|
||||
|
||||
/**
|
||||
* Attempts to parse potentially incomplete JSON during streaming.
|
||||
* Always returns a valid object, even if the JSON is incomplete.
|
||||
*
|
||||
* @param partialJson The partial JSON string from streaming
|
||||
* @returns Parsed object or empty object if parsing fails
|
||||
*/
|
||||
export function parseStreamingJson<T = any>(partialJson: string | undefined): T {
|
||||
if (!partialJson || partialJson.trim() === "") {
|
||||
return {} as T;
|
||||
}
|
||||
|
||||
// Try standard parsing first (fastest for complete JSON)
|
||||
try {
|
||||
return JSON.parse(partialJson) as T;
|
||||
} catch {
|
||||
// Try partial-json for incomplete JSON
|
||||
try {
|
||||
const result = partialParse(partialJson);
|
||||
return (result ?? {}) as T;
|
||||
} catch {
|
||||
// If all parsing fails, return empty object
|
||||
return {} as T;
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,118 +0,0 @@
|
||||
/**
|
||||
* Anthropic OAuth flow (Claude Pro/Max)
|
||||
*/
|
||||
|
||||
import { generatePKCE } from "./pkce";
|
||||
import type { OAuthCredentials } from "./types";
|
||||
|
||||
const decode = (s: string) => atob(s);
|
||||
const CLIENT_ID = decode("OWQxYzI1MGEtZTYxYi00NGQ5LTg4ZWQtNTk0NGQxOTYyZjVl");
|
||||
const AUTHORIZE_URL = "https://claude.ai/oauth/authorize";
|
||||
const TOKEN_URL = "https://console.anthropic.com/v1/oauth/token";
|
||||
const REDIRECT_URI = "https://console.anthropic.com/oauth/code/callback";
|
||||
const SCOPES = "org:create_api_key user:profile user:inference";
|
||||
|
||||
/**
|
||||
* Login with Anthropic OAuth (device code flow)
|
||||
*
|
||||
* @param onAuthUrl - Callback to handle the authorization URL (e.g., open browser)
|
||||
* @param onPromptCode - Callback to prompt user for the authorization code
|
||||
*/
|
||||
export async function loginAnthropic(
|
||||
onAuthUrl: (url: string) => void,
|
||||
onPromptCode: () => Promise<string>,
|
||||
): Promise<OAuthCredentials> {
|
||||
const { verifier, challenge } = await generatePKCE();
|
||||
|
||||
// Build authorization URL
|
||||
const authParams = new URLSearchParams({
|
||||
code: "true",
|
||||
client_id: CLIENT_ID,
|
||||
response_type: "code",
|
||||
redirect_uri: REDIRECT_URI,
|
||||
scope: SCOPES,
|
||||
code_challenge: challenge,
|
||||
code_challenge_method: "S256",
|
||||
state: verifier,
|
||||
});
|
||||
|
||||
const authUrl = `${AUTHORIZE_URL}?${authParams.toString()}`;
|
||||
|
||||
// Notify caller with URL to open
|
||||
onAuthUrl(authUrl);
|
||||
|
||||
// Wait for user to paste authorization code (format: code#state)
|
||||
const authCode = await onPromptCode();
|
||||
const splits = authCode.split("#");
|
||||
const code = splits[0];
|
||||
const state = splits[1];
|
||||
|
||||
// Exchange code for tokens
|
||||
const tokenResponse = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
grant_type: "authorization_code",
|
||||
client_id: CLIENT_ID,
|
||||
code: code,
|
||||
state: state,
|
||||
redirect_uri: REDIRECT_URI,
|
||||
code_verifier: verifier,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!tokenResponse.ok) {
|
||||
const error = await tokenResponse.text();
|
||||
throw new Error(`Token exchange failed: ${error}`);
|
||||
}
|
||||
|
||||
const tokenData = (await tokenResponse.json()) as {
|
||||
access_token: string;
|
||||
refresh_token: string;
|
||||
expires_in: number;
|
||||
};
|
||||
|
||||
// Calculate expiry time (current time + expires_in seconds - 5 min buffer)
|
||||
const expiresAt = Date.now() + tokenData.expires_in * 1000 - 5 * 60 * 1000;
|
||||
|
||||
// Save credentials
|
||||
return {
|
||||
refresh: tokenData.refresh_token,
|
||||
access: tokenData.access_token,
|
||||
expires: expiresAt,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Refresh Anthropic OAuth token
|
||||
*/
|
||||
export async function refreshAnthropicToken(refreshToken: string): Promise<OAuthCredentials> {
|
||||
const response = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({
|
||||
grant_type: "refresh_token",
|
||||
client_id: CLIENT_ID,
|
||||
refresh_token: refreshToken,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const error = await response.text();
|
||||
throw new Error(`Anthropic token refresh failed: ${error}`);
|
||||
}
|
||||
|
||||
const data = (await response.json()) as {
|
||||
access_token: string;
|
||||
refresh_token: string;
|
||||
expires_in: number;
|
||||
};
|
||||
|
||||
return {
|
||||
refresh: data.refresh_token,
|
||||
access: data.access_token,
|
||||
expires: Date.now() + data.expires_in * 1000 - 5 * 60 * 1000,
|
||||
};
|
||||
}
|
||||
@@ -1,311 +0,0 @@
|
||||
/**
|
||||
* GitHub Copilot OAuth flow
|
||||
*/
|
||||
|
||||
import { getModels } from "../../models";
|
||||
import type { OAuthCredentials } from "./types";
|
||||
|
||||
const decode = (s: string) => atob(s);
|
||||
const CLIENT_ID = decode("SXYxLmI1MDdhMDhjODdlY2ZlOTg=");
|
||||
|
||||
const COPILOT_HEADERS = {
|
||||
"User-Agent": "GitHubCopilotChat/0.35.0",
|
||||
"Editor-Version": "vscode/1.107.0",
|
||||
"Editor-Plugin-Version": "copilot-chat/0.35.0",
|
||||
"Copilot-Integration-Id": "vscode-chat",
|
||||
} as const;
|
||||
|
||||
type DeviceCodeResponse = {
|
||||
device_code: string;
|
||||
user_code: string;
|
||||
verification_uri: string;
|
||||
interval: number;
|
||||
expires_in: number;
|
||||
};
|
||||
|
||||
type DeviceTokenSuccessResponse = {
|
||||
access_token: string;
|
||||
token_type?: string;
|
||||
scope?: string;
|
||||
};
|
||||
|
||||
type DeviceTokenErrorResponse = {
|
||||
error: string;
|
||||
error_description?: string;
|
||||
interval?: number;
|
||||
};
|
||||
|
||||
export function normalizeDomain(input: string): string | null {
|
||||
const trimmed = input.trim();
|
||||
if (!trimmed) return null;
|
||||
try {
|
||||
const url = trimmed.includes("://") ? new URL(trimmed) : new URL(`https://${trimmed}`);
|
||||
return url.hostname;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
function getUrls(domain: string): {
|
||||
deviceCodeUrl: string;
|
||||
accessTokenUrl: string;
|
||||
copilotTokenUrl: string;
|
||||
} {
|
||||
return {
|
||||
deviceCodeUrl: `https://${domain}/login/device/code`,
|
||||
accessTokenUrl: `https://${domain}/login/oauth/access_token`,
|
||||
copilotTokenUrl: `https://api.${domain}/copilot_internal/v2/token`,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Parse the proxy-ep from a Copilot token and convert to API base URL.
|
||||
* Token format: tid=...;exp=...;proxy-ep=proxy.individual.githubcopilot.com;...
|
||||
* Returns API URL like https://api.individual.githubcopilot.com
|
||||
*/
|
||||
function getBaseUrlFromToken(token: string): string | null {
|
||||
const match = token.match(/proxy-ep=([^;]+)/);
|
||||
if (!match) return null;
|
||||
const proxyHost = match[1];
|
||||
// Convert proxy.xxx to api.xxx
|
||||
const apiHost = proxyHost.replace(/^proxy\./, "api.");
|
||||
return `https://${apiHost}`;
|
||||
}
|
||||
|
||||
export function getGitHubCopilotBaseUrl(token?: string, enterpriseDomain?: string): string {
|
||||
// If we have a token, extract the base URL from proxy-ep
|
||||
if (token) {
|
||||
const urlFromToken = getBaseUrlFromToken(token);
|
||||
if (urlFromToken) return urlFromToken;
|
||||
}
|
||||
// Fallback for enterprise or if token parsing fails
|
||||
if (enterpriseDomain) return `https://copilot-api.${enterpriseDomain}`;
|
||||
return "https://api.individual.githubcopilot.com";
|
||||
}
|
||||
|
||||
async function fetchJson(url: string, init: RequestInit): Promise<unknown> {
|
||||
const response = await fetch(url, init);
|
||||
if (!response.ok) {
|
||||
const text = await response.text();
|
||||
throw new Error(`${response.status} ${response.statusText}: ${text}`);
|
||||
}
|
||||
return response.json();
|
||||
}
|
||||
|
||||
async function startDeviceFlow(domain: string): Promise<DeviceCodeResponse> {
|
||||
const urls = getUrls(domain);
|
||||
const data = await fetchJson(urls.deviceCodeUrl, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
Accept: "application/json",
|
||||
"Content-Type": "application/json",
|
||||
"User-Agent": "GitHubCopilotChat/0.35.0",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
client_id: CLIENT_ID,
|
||||
scope: "read:user",
|
||||
}),
|
||||
});
|
||||
|
||||
if (!data || typeof data !== "object") {
|
||||
throw new Error("Invalid device code response");
|
||||
}
|
||||
|
||||
const deviceCode = (data as Record<string, unknown>).device_code;
|
||||
const userCode = (data as Record<string, unknown>).user_code;
|
||||
const verificationUri = (data as Record<string, unknown>).verification_uri;
|
||||
const interval = (data as Record<string, unknown>).interval;
|
||||
const expiresIn = (data as Record<string, unknown>).expires_in;
|
||||
|
||||
if (
|
||||
typeof deviceCode !== "string" ||
|
||||
typeof userCode !== "string" ||
|
||||
typeof verificationUri !== "string" ||
|
||||
typeof interval !== "number" ||
|
||||
typeof expiresIn !== "number"
|
||||
) {
|
||||
throw new Error("Invalid device code response fields");
|
||||
}
|
||||
|
||||
return {
|
||||
device_code: deviceCode,
|
||||
user_code: userCode,
|
||||
verification_uri: verificationUri,
|
||||
interval,
|
||||
expires_in: expiresIn,
|
||||
};
|
||||
}
|
||||
|
||||
async function pollForGitHubAccessToken(
|
||||
domain: string,
|
||||
deviceCode: string,
|
||||
intervalSeconds: number,
|
||||
expiresIn: number,
|
||||
) {
|
||||
const urls = getUrls(domain);
|
||||
const deadline = Date.now() + expiresIn * 1000;
|
||||
let intervalMs = Math.max(1000, Math.floor(intervalSeconds * 1000));
|
||||
|
||||
while (Date.now() < deadline) {
|
||||
const raw = await fetchJson(urls.accessTokenUrl, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
Accept: "application/json",
|
||||
"Content-Type": "application/json",
|
||||
"User-Agent": "GitHubCopilotChat/0.35.0",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
client_id: CLIENT_ID,
|
||||
device_code: deviceCode,
|
||||
grant_type: "urn:ietf:params:oauth:grant-type:device_code",
|
||||
}),
|
||||
});
|
||||
|
||||
if (raw && typeof raw === "object" && typeof (raw as DeviceTokenSuccessResponse).access_token === "string") {
|
||||
return (raw as DeviceTokenSuccessResponse).access_token;
|
||||
}
|
||||
|
||||
if (raw && typeof raw === "object" && typeof (raw as DeviceTokenErrorResponse).error === "string") {
|
||||
const err = (raw as DeviceTokenErrorResponse).error;
|
||||
if (err === "authorization_pending") {
|
||||
await new Promise((resolve) => setTimeout(resolve, intervalMs));
|
||||
continue;
|
||||
}
|
||||
|
||||
if (err === "slow_down") {
|
||||
intervalMs += 5000;
|
||||
await new Promise((resolve) => setTimeout(resolve, intervalMs));
|
||||
continue;
|
||||
}
|
||||
|
||||
throw new Error(`Device flow failed: ${err}`);
|
||||
}
|
||||
|
||||
await new Promise((resolve) => setTimeout(resolve, intervalMs));
|
||||
}
|
||||
|
||||
throw new Error("Device flow timed out");
|
||||
}
|
||||
|
||||
/**
|
||||
* Refresh GitHub Copilot token
|
||||
*/
|
||||
export async function refreshGitHubCopilotToken(
|
||||
refreshToken: string,
|
||||
enterpriseDomain?: string,
|
||||
): Promise<OAuthCredentials> {
|
||||
const domain = enterpriseDomain || "github.com";
|
||||
const urls = getUrls(domain);
|
||||
|
||||
const raw = await fetchJson(urls.copilotTokenUrl, {
|
||||
headers: {
|
||||
Accept: "application/json",
|
||||
Authorization: `Bearer ${refreshToken}`,
|
||||
...COPILOT_HEADERS,
|
||||
},
|
||||
});
|
||||
|
||||
if (!raw || typeof raw !== "object") {
|
||||
throw new Error("Invalid Copilot token response");
|
||||
}
|
||||
|
||||
const token = (raw as Record<string, unknown>).token;
|
||||
const expiresAt = (raw as Record<string, unknown>).expires_at;
|
||||
|
||||
if (typeof token !== "string" || typeof expiresAt !== "number") {
|
||||
throw new Error("Invalid Copilot token response fields");
|
||||
}
|
||||
|
||||
return {
|
||||
refresh: refreshToken,
|
||||
access: token,
|
||||
expires: expiresAt * 1000 - 5 * 60 * 1000,
|
||||
enterpriseUrl: enterpriseDomain,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Enable a model for the user's GitHub Copilot account.
|
||||
* This is required for some models (like Claude, Grok) before they can be used.
|
||||
*/
|
||||
async function enableGitHubCopilotModel(token: string, modelId: string, enterpriseDomain?: string): Promise<boolean> {
|
||||
const baseUrl = getGitHubCopilotBaseUrl(token, enterpriseDomain);
|
||||
const url = `${baseUrl}/models/${modelId}/policy`;
|
||||
|
||||
try {
|
||||
const response = await fetch(url, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${token}`,
|
||||
...COPILOT_HEADERS,
|
||||
"openai-intent": "chat-policy",
|
||||
"x-interaction-type": "chat-policy",
|
||||
},
|
||||
body: JSON.stringify({ state: "enabled" }),
|
||||
});
|
||||
return response.ok;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Enable all known GitHub Copilot models that may require policy acceptance.
|
||||
* Called after successful login to ensure all models are available.
|
||||
*/
|
||||
async function enableAllGitHubCopilotModels(
|
||||
token: string,
|
||||
enterpriseDomain?: string,
|
||||
onProgress?: (model: string, success: boolean) => void,
|
||||
): Promise<void> {
|
||||
const models = getModels("github-copilot");
|
||||
await Promise.all(
|
||||
models.map(async (model) => {
|
||||
const success = await enableGitHubCopilotModel(token, model.id, enterpriseDomain);
|
||||
onProgress?.(model.id, success);
|
||||
}),
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Login with GitHub Copilot OAuth (device code flow)
|
||||
*
|
||||
* @param options.onAuth - Callback with URL and optional instructions (user code)
|
||||
* @param options.onPrompt - Callback to prompt user for input
|
||||
* @param options.onProgress - Optional progress callback
|
||||
*/
|
||||
export async function loginGitHubCopilot(options: {
|
||||
onAuth: (url: string, instructions?: string) => void;
|
||||
onPrompt: (prompt: { message: string; placeholder?: string; allowEmpty?: boolean }) => Promise<string>;
|
||||
onProgress?: (message: string) => void;
|
||||
}): Promise<OAuthCredentials> {
|
||||
const input = await options.onPrompt({
|
||||
message: "GitHub Enterprise URL/domain (blank for github.com)",
|
||||
placeholder: "company.ghe.com",
|
||||
allowEmpty: true,
|
||||
});
|
||||
|
||||
const trimmed = input.trim();
|
||||
const enterpriseDomain = normalizeDomain(input);
|
||||
if (trimmed && !enterpriseDomain) {
|
||||
throw new Error("Invalid GitHub Enterprise URL/domain");
|
||||
}
|
||||
const domain = enterpriseDomain || "github.com";
|
||||
|
||||
const device = await startDeviceFlow(domain);
|
||||
options.onAuth(device.verification_uri, `Enter code: ${device.user_code}`);
|
||||
|
||||
const githubAccessToken = await pollForGitHubAccessToken(
|
||||
domain,
|
||||
device.device_code,
|
||||
device.interval,
|
||||
device.expires_in,
|
||||
);
|
||||
const credentials = await refreshGitHubCopilotToken(githubAccessToken, enterpriseDomain ?? undefined);
|
||||
|
||||
// Enable all models after successful login
|
||||
options.onProgress?.("Enabling models...");
|
||||
await enableAllGitHubCopilotModels(credentials.access, enterpriseDomain ?? undefined);
|
||||
return credentials;
|
||||
}
|
||||
@@ -1,322 +0,0 @@
|
||||
/**
|
||||
* Antigravity OAuth flow (Gemini 3, Claude, GPT-OSS via Google Cloud)
|
||||
* Uses different OAuth credentials than google-gemini-cli for access to additional models.
|
||||
*
|
||||
* NOTE: This module uses Node.js http.createServer for the OAuth callback.
|
||||
* It is only intended for CLI use, not browser environments.
|
||||
*/
|
||||
|
||||
import { generatePKCE } from "./pkce";
|
||||
import type { OAuthCredentials } from "./types";
|
||||
|
||||
// Antigravity OAuth credentials (different from Gemini CLI)
|
||||
const decode = (s: string) => atob(s);
|
||||
const CLIENT_ID = decode(
|
||||
"MTA3MTAwNjA2MDU5MS10bWhzc2luMmgyMWxjcmUyMzV2dG9sb2poNGc0MDNlcC5hcHBzLmdvb2dsZXVzZXJjb250ZW50LmNvbQ==",
|
||||
);
|
||||
const CLIENT_SECRET = decode("R09DU1BYLUs1OEZXUjQ4NkxkTEoxbUxCOHNYQzR6NnFEQWY=");
|
||||
const REDIRECT_URI = "http://localhost:51121/oauth-callback";
|
||||
|
||||
// Antigravity requires additional scopes
|
||||
const SCOPES = [
|
||||
"https://www.googleapis.com/auth/cloud-platform",
|
||||
"https://www.googleapis.com/auth/userinfo.email",
|
||||
"https://www.googleapis.com/auth/userinfo.profile",
|
||||
"https://www.googleapis.com/auth/cclog",
|
||||
"https://www.googleapis.com/auth/experimentsandconfigs",
|
||||
];
|
||||
|
||||
const AUTH_URL = "https://accounts.google.com/o/oauth2/v2/auth";
|
||||
const TOKEN_URL = "https://oauth2.googleapis.com/token";
|
||||
|
||||
// Fallback project ID when discovery fails
|
||||
const DEFAULT_PROJECT_ID = "rising-fact-p41fc";
|
||||
|
||||
/**
|
||||
* Start a local HTTP server to receive the OAuth callback
|
||||
*/
|
||||
async function startCallbackServer(): Promise<{
|
||||
server: { stop: () => void };
|
||||
getCode: () => Promise<{ code: string; state: string }>;
|
||||
}> {
|
||||
return new Promise((resolve, reject) => {
|
||||
let codeResolve: (value: { code: string; state: string }) => void;
|
||||
let codeReject: (error: Error) => void;
|
||||
|
||||
const codePromise = new Promise<{ code: string; state: string }>((res, rej) => {
|
||||
codeResolve = res;
|
||||
codeReject = rej;
|
||||
});
|
||||
|
||||
const server = Bun.serve({
|
||||
port: 51121,
|
||||
hostname: "127.0.0.1",
|
||||
fetch(req) {
|
||||
const url = new URL(req.url);
|
||||
|
||||
if (url.pathname === "/oauth-callback") {
|
||||
const code = url.searchParams.get("code");
|
||||
const state = url.searchParams.get("state");
|
||||
const error = url.searchParams.get("error");
|
||||
|
||||
if (error) {
|
||||
codeReject(new Error(`OAuth error: ${error}`));
|
||||
return new Response(
|
||||
`<html><body><h1>Authentication Failed</h1><p>Error: ${error}</p><p>You can close this window.</p></body></html>`,
|
||||
{ status: 400, headers: { "Content-Type": "text/html" } },
|
||||
);
|
||||
}
|
||||
|
||||
if (code && state) {
|
||||
codeResolve({ code, state });
|
||||
return new Response(
|
||||
`<html><body><h1>Authentication Successful</h1><p>You can close this window and return to the terminal.</p></body></html>`,
|
||||
{ status: 200, headers: { "Content-Type": "text/html" } },
|
||||
);
|
||||
}
|
||||
|
||||
codeReject(new Error("Missing code or state in callback"));
|
||||
return new Response(
|
||||
`<html><body><h1>Authentication Failed</h1><p>Missing code or state parameter.</p></body></html>`,
|
||||
{ status: 400, headers: { "Content-Type": "text/html" } },
|
||||
);
|
||||
}
|
||||
|
||||
return new Response(null, { status: 404 });
|
||||
},
|
||||
error(err) {
|
||||
reject(err);
|
||||
return new Response("Internal Server Error", { status: 500 });
|
||||
},
|
||||
});
|
||||
|
||||
resolve({
|
||||
server,
|
||||
getCode: () => codePromise,
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
interface LoadCodeAssistPayload {
|
||||
cloudaicompanionProject?: string | { id?: string };
|
||||
currentTier?: { id?: string };
|
||||
allowedTiers?: Array<{ id?: string; isDefault?: boolean }>;
|
||||
}
|
||||
|
||||
/**
|
||||
* Discover or provision a project for the user
|
||||
*/
|
||||
async function discoverProject(accessToken: string, onProgress?: (message: string) => void): Promise<string> {
|
||||
const headers = {
|
||||
Authorization: `Bearer ${accessToken}`,
|
||||
"Content-Type": "application/json",
|
||||
"User-Agent": "google-api-nodejs-client/9.15.1",
|
||||
"X-Goog-Api-Client": "google-cloud-sdk vscode_cloudshelleditor/0.1",
|
||||
"Client-Metadata": JSON.stringify({
|
||||
ideType: "IDE_UNSPECIFIED",
|
||||
platform: "PLATFORM_UNSPECIFIED",
|
||||
pluginType: "GEMINI",
|
||||
}),
|
||||
};
|
||||
|
||||
// Try endpoints in order: prod first, then sandbox
|
||||
const endpoints = ["https://cloudcode-pa.googleapis.com", "https://daily-cloudcode-pa.sandbox.googleapis.com"];
|
||||
|
||||
onProgress?.("Checking for existing project...");
|
||||
|
||||
for (const endpoint of endpoints) {
|
||||
try {
|
||||
const loadResponse = await fetch(`${endpoint}/v1internal:loadCodeAssist`, {
|
||||
method: "POST",
|
||||
headers,
|
||||
body: JSON.stringify({
|
||||
metadata: {
|
||||
ideType: "IDE_UNSPECIFIED",
|
||||
platform: "PLATFORM_UNSPECIFIED",
|
||||
pluginType: "GEMINI",
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (loadResponse.ok) {
|
||||
const data = (await loadResponse.json()) as LoadCodeAssistPayload;
|
||||
|
||||
// Handle both string and object formats
|
||||
if (typeof data.cloudaicompanionProject === "string" && data.cloudaicompanionProject) {
|
||||
return data.cloudaicompanionProject;
|
||||
}
|
||||
if (
|
||||
data.cloudaicompanionProject &&
|
||||
typeof data.cloudaicompanionProject === "object" &&
|
||||
data.cloudaicompanionProject.id
|
||||
) {
|
||||
return data.cloudaicompanionProject.id;
|
||||
}
|
||||
}
|
||||
} catch {
|
||||
// Try next endpoint
|
||||
}
|
||||
}
|
||||
|
||||
// Use fallback project ID
|
||||
onProgress?.("Using default project...");
|
||||
return DEFAULT_PROJECT_ID;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get user email from the access token
|
||||
*/
|
||||
async function getUserEmail(accessToken: string): Promise<string | undefined> {
|
||||
try {
|
||||
const response = await fetch("https://www.googleapis.com/oauth2/v1/userinfo?alt=json", {
|
||||
headers: {
|
||||
Authorization: `Bearer ${accessToken}`,
|
||||
},
|
||||
});
|
||||
|
||||
if (response.ok) {
|
||||
const data = (await response.json()) as { email?: string };
|
||||
return data.email;
|
||||
}
|
||||
} catch {
|
||||
// Ignore errors, email is optional
|
||||
}
|
||||
return undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* Refresh Antigravity token
|
||||
*/
|
||||
export async function refreshAntigravityToken(refreshToken: string, projectId: string): Promise<OAuthCredentials> {
|
||||
const response = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/x-www-form-urlencoded" },
|
||||
body: new URLSearchParams({
|
||||
client_id: CLIENT_ID,
|
||||
client_secret: CLIENT_SECRET,
|
||||
refresh_token: refreshToken,
|
||||
grant_type: "refresh_token",
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const error = await response.text();
|
||||
throw new Error(`Antigravity token refresh failed: ${error}`);
|
||||
}
|
||||
|
||||
const data = (await response.json()) as {
|
||||
access_token: string;
|
||||
expires_in: number;
|
||||
refresh_token?: string;
|
||||
};
|
||||
|
||||
return {
|
||||
refresh: data.refresh_token || refreshToken,
|
||||
access: data.access_token,
|
||||
expires: Date.now() + data.expires_in * 1000 - 5 * 60 * 1000,
|
||||
projectId,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Login with Antigravity OAuth
|
||||
*
|
||||
* @param onAuth - Callback with URL and optional instructions
|
||||
* @param onProgress - Optional progress callback
|
||||
*/
|
||||
export async function loginAntigravity(
|
||||
onAuth: (info: { url: string; instructions?: string }) => void,
|
||||
onProgress?: (message: string) => void,
|
||||
): Promise<OAuthCredentials> {
|
||||
const { verifier, challenge } = await generatePKCE();
|
||||
|
||||
// Start local server for callback
|
||||
onProgress?.("Starting local server for OAuth callback...");
|
||||
const { server, getCode } = await startCallbackServer();
|
||||
|
||||
try {
|
||||
// Build authorization URL
|
||||
const authParams = new URLSearchParams({
|
||||
client_id: CLIENT_ID,
|
||||
response_type: "code",
|
||||
redirect_uri: REDIRECT_URI,
|
||||
scope: SCOPES.join(" "),
|
||||
code_challenge: challenge,
|
||||
code_challenge_method: "S256",
|
||||
state: verifier,
|
||||
access_type: "offline",
|
||||
prompt: "consent",
|
||||
});
|
||||
|
||||
const authUrl = `${AUTH_URL}?${authParams.toString()}`;
|
||||
|
||||
// Notify caller with URL to open
|
||||
onAuth({
|
||||
url: authUrl,
|
||||
instructions: "Complete the sign-in in your browser. The callback will be captured automatically.",
|
||||
});
|
||||
|
||||
// Wait for the callback
|
||||
onProgress?.("Waiting for OAuth callback...");
|
||||
const { code, state } = await getCode();
|
||||
|
||||
// Verify state matches
|
||||
if (state !== verifier) {
|
||||
throw new Error("OAuth state mismatch - possible CSRF attack");
|
||||
}
|
||||
|
||||
// Exchange code for tokens
|
||||
onProgress?.("Exchanging authorization code for tokens...");
|
||||
const tokenResponse = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/x-www-form-urlencoded",
|
||||
},
|
||||
body: new URLSearchParams({
|
||||
client_id: CLIENT_ID,
|
||||
client_secret: CLIENT_SECRET,
|
||||
code,
|
||||
grant_type: "authorization_code",
|
||||
redirect_uri: REDIRECT_URI,
|
||||
code_verifier: verifier,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!tokenResponse.ok) {
|
||||
const error = await tokenResponse.text();
|
||||
throw new Error(`Token exchange failed: ${error}`);
|
||||
}
|
||||
|
||||
const tokenData = (await tokenResponse.json()) as {
|
||||
access_token: string;
|
||||
refresh_token: string;
|
||||
expires_in: number;
|
||||
};
|
||||
|
||||
if (!tokenData.refresh_token) {
|
||||
throw new Error("No refresh token received. Please try again.");
|
||||
}
|
||||
|
||||
// Get user email
|
||||
onProgress?.("Getting user info...");
|
||||
const email = await getUserEmail(tokenData.access_token);
|
||||
|
||||
// Discover project
|
||||
const projectId = await discoverProject(tokenData.access_token, onProgress);
|
||||
|
||||
// Calculate expiry time (current time + expires_in seconds - 5 min buffer)
|
||||
const expiresAt = Date.now() + tokenData.expires_in * 1000 - 5 * 60 * 1000;
|
||||
|
||||
const credentials: OAuthCredentials = {
|
||||
refresh: tokenData.refresh_token,
|
||||
access: tokenData.access_token,
|
||||
expires: expiresAt,
|
||||
projectId,
|
||||
email,
|
||||
};
|
||||
|
||||
return credentials;
|
||||
} finally {
|
||||
server.stop();
|
||||
}
|
||||
}
|
||||
@@ -1,353 +0,0 @@
|
||||
/**
|
||||
* Gemini CLI OAuth flow (Google Cloud Code Assist)
|
||||
* Standard Gemini models only (gemini-2.0-flash, gemini-2.5-*)
|
||||
*
|
||||
* NOTE: This module uses Node.js http.createServer for the OAuth callback.
|
||||
* It is only intended for CLI use, not browser environments.
|
||||
*/
|
||||
|
||||
import { generatePKCE } from "./pkce";
|
||||
import type { OAuthCredentials } from "./types";
|
||||
|
||||
const decode = (s: string) => atob(s);
|
||||
const CLIENT_ID = decode(
|
||||
"NjgxMjU1ODA5Mzk1LW9vOGZ0Mm9wcmRybnA5ZTNhcWY2YXYzaG1kaWIxMzVqLmFwcHMuZ29vZ2xldXNlcmNvbnRlbnQuY29t",
|
||||
);
|
||||
const CLIENT_SECRET = decode("R09DU1BYLTR1SGdNUG0tMW83U2stZ2VWNkN1NWNsWEZzeGw=");
|
||||
const REDIRECT_URI = "http://localhost:8085/oauth2callback";
|
||||
const SCOPES = [
|
||||
"https://www.googleapis.com/auth/cloud-platform",
|
||||
"https://www.googleapis.com/auth/userinfo.email",
|
||||
"https://www.googleapis.com/auth/userinfo.profile",
|
||||
];
|
||||
const AUTH_URL = "https://accounts.google.com/o/oauth2/v2/auth";
|
||||
const TOKEN_URL = "https://oauth2.googleapis.com/token";
|
||||
const CODE_ASSIST_ENDPOINT = "https://cloudcode-pa.googleapis.com";
|
||||
|
||||
/**
|
||||
* Start a local HTTP server to receive the OAuth callback
|
||||
*/
|
||||
async function startCallbackServer(): Promise<{
|
||||
server: { stop: () => void };
|
||||
getCode: () => Promise<{ code: string; state: string }>;
|
||||
}> {
|
||||
return new Promise((resolve, reject) => {
|
||||
let codeResolve: (value: { code: string; state: string }) => void;
|
||||
let codeReject: (error: Error) => void;
|
||||
|
||||
const codePromise = new Promise<{ code: string; state: string }>((res, rej) => {
|
||||
codeResolve = res;
|
||||
codeReject = rej;
|
||||
});
|
||||
|
||||
const server = Bun.serve({
|
||||
port: 8085,
|
||||
hostname: "127.0.0.1",
|
||||
fetch(req) {
|
||||
const url = new URL(req.url);
|
||||
|
||||
if (url.pathname === "/oauth2callback") {
|
||||
const code = url.searchParams.get("code");
|
||||
const state = url.searchParams.get("state");
|
||||
const error = url.searchParams.get("error");
|
||||
|
||||
if (error) {
|
||||
codeReject(new Error(`OAuth error: ${error}`));
|
||||
return new Response(
|
||||
`<html><body><h1>Authentication Failed</h1><p>Error: ${error}</p><p>You can close this window.</p></body></html>`,
|
||||
{ status: 400, headers: { "Content-Type": "text/html" } },
|
||||
);
|
||||
}
|
||||
|
||||
if (code && state) {
|
||||
codeResolve({ code, state });
|
||||
return new Response(
|
||||
`<html><body><h1>Authentication Successful</h1><p>You can close this window and return to the terminal.</p></body></html>`,
|
||||
{ status: 200, headers: { "Content-Type": "text/html" } },
|
||||
);
|
||||
}
|
||||
|
||||
codeReject(new Error("Missing code or state in callback"));
|
||||
return new Response(
|
||||
`<html><body><h1>Authentication Failed</h1><p>Missing code or state parameter.</p></body></html>`,
|
||||
{ status: 400, headers: { "Content-Type": "text/html" } },
|
||||
);
|
||||
}
|
||||
|
||||
return new Response(null, { status: 404 });
|
||||
},
|
||||
error(err) {
|
||||
reject(err);
|
||||
return new Response("Internal Server Error", { status: 500 });
|
||||
},
|
||||
});
|
||||
|
||||
resolve({
|
||||
server,
|
||||
getCode: () => codePromise,
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
interface LoadCodeAssistPayload {
|
||||
cloudaicompanionProject?: string;
|
||||
currentTier?: { id?: string };
|
||||
allowedTiers?: Array<{ id?: string; isDefault?: boolean }>;
|
||||
}
|
||||
|
||||
interface OnboardUserPayload {
|
||||
done?: boolean;
|
||||
response?: {
|
||||
cloudaicompanionProject?: { id?: string };
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Wait helper for onboarding retries
|
||||
*/
|
||||
function wait(ms: number): Promise<void> {
|
||||
return new Promise((resolve) => setTimeout(resolve, ms));
|
||||
}
|
||||
|
||||
/**
|
||||
* Get default tier ID from allowed tiers
|
||||
*/
|
||||
function getDefaultTierId(allowedTiers?: Array<{ id?: string; isDefault?: boolean }>): string | undefined {
|
||||
if (!allowedTiers || allowedTiers.length === 0) return undefined;
|
||||
const defaultTier = allowedTiers.find((t) => t.isDefault);
|
||||
return defaultTier?.id ?? allowedTiers[0]?.id;
|
||||
}
|
||||
|
||||
/**
|
||||
* Discover or provision a Google Cloud project for the user
|
||||
*/
|
||||
async function discoverProject(accessToken: string, onProgress?: (message: string) => void): Promise<string> {
|
||||
const headers = {
|
||||
Authorization: `Bearer ${accessToken}`,
|
||||
"Content-Type": "application/json",
|
||||
"User-Agent": "google-api-nodejs-client/9.15.1",
|
||||
"X-Goog-Api-Client": "gl-node/22.17.0",
|
||||
};
|
||||
|
||||
// Try to load existing project via loadCodeAssist
|
||||
onProgress?.("Checking for existing Cloud Code Assist project...");
|
||||
const loadResponse = await fetch(`${CODE_ASSIST_ENDPOINT}/v1internal:loadCodeAssist`, {
|
||||
method: "POST",
|
||||
headers,
|
||||
body: JSON.stringify({
|
||||
metadata: {
|
||||
ideType: "IDE_UNSPECIFIED",
|
||||
platform: "PLATFORM_UNSPECIFIED",
|
||||
pluginType: "GEMINI",
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (loadResponse.ok) {
|
||||
const data = (await loadResponse.json()) as LoadCodeAssistPayload;
|
||||
|
||||
// If we have an existing project, use it
|
||||
if (data.cloudaicompanionProject) {
|
||||
return data.cloudaicompanionProject;
|
||||
}
|
||||
|
||||
// Otherwise, try to onboard with the FREE tier
|
||||
const tierId = getDefaultTierId(data.allowedTiers) ?? "FREE";
|
||||
|
||||
onProgress?.("Provisioning Cloud Code Assist project (this may take a moment)...");
|
||||
|
||||
// Onboard with retries (the API may take time to provision)
|
||||
for (let attempt = 0; attempt < 10; attempt++) {
|
||||
const onboardResponse = await fetch(`${CODE_ASSIST_ENDPOINT}/v1internal:onboardUser`, {
|
||||
method: "POST",
|
||||
headers,
|
||||
body: JSON.stringify({
|
||||
tierId,
|
||||
metadata: {
|
||||
ideType: "IDE_UNSPECIFIED",
|
||||
platform: "PLATFORM_UNSPECIFIED",
|
||||
pluginType: "GEMINI",
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (onboardResponse.ok) {
|
||||
const onboardData = (await onboardResponse.json()) as OnboardUserPayload;
|
||||
const projectId = onboardData.response?.cloudaicompanionProject?.id;
|
||||
|
||||
if (onboardData.done && projectId) {
|
||||
return projectId;
|
||||
}
|
||||
}
|
||||
|
||||
// Wait before retrying
|
||||
if (attempt < 9) {
|
||||
onProgress?.(`Waiting for project provisioning (attempt ${attempt + 2}/10)...`);
|
||||
await wait(3000);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
throw new Error(
|
||||
"Could not discover or provision a Google Cloud project. " +
|
||||
"Please ensure you have access to Google Cloud Code Assist (Gemini CLI).",
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Get user email from the access token
|
||||
*/
|
||||
async function getUserEmail(accessToken: string): Promise<string | undefined> {
|
||||
try {
|
||||
const response = await fetch("https://www.googleapis.com/oauth2/v1/userinfo?alt=json", {
|
||||
headers: {
|
||||
Authorization: `Bearer ${accessToken}`,
|
||||
},
|
||||
});
|
||||
|
||||
if (response.ok) {
|
||||
const data = (await response.json()) as { email?: string };
|
||||
return data.email;
|
||||
}
|
||||
} catch {
|
||||
// Ignore errors, email is optional
|
||||
}
|
||||
return undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* Refresh Google Cloud Code Assist token
|
||||
*/
|
||||
export async function refreshGoogleCloudToken(refreshToken: string, projectId: string): Promise<OAuthCredentials> {
|
||||
const response = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/x-www-form-urlencoded" },
|
||||
body: new URLSearchParams({
|
||||
client_id: CLIENT_ID,
|
||||
client_secret: CLIENT_SECRET,
|
||||
refresh_token: refreshToken,
|
||||
grant_type: "refresh_token",
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const error = await response.text();
|
||||
throw new Error(`Google Cloud token refresh failed: ${error}`);
|
||||
}
|
||||
|
||||
const data = (await response.json()) as {
|
||||
access_token: string;
|
||||
expires_in: number;
|
||||
refresh_token?: string;
|
||||
};
|
||||
|
||||
return {
|
||||
refresh: data.refresh_token || refreshToken,
|
||||
access: data.access_token,
|
||||
expires: Date.now() + data.expires_in * 1000 - 5 * 60 * 1000,
|
||||
projectId,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Login with Gemini CLI (Google Cloud Code Assist) OAuth
|
||||
*
|
||||
* @param onAuth - Callback with URL and optional instructions
|
||||
* @param onProgress - Optional progress callback
|
||||
*/
|
||||
export async function loginGeminiCli(
|
||||
onAuth: (info: { url: string; instructions?: string }) => void,
|
||||
onProgress?: (message: string) => void,
|
||||
): Promise<OAuthCredentials> {
|
||||
const { verifier, challenge } = await generatePKCE();
|
||||
|
||||
// Start local server for callback
|
||||
onProgress?.("Starting local server for OAuth callback...");
|
||||
const { server, getCode } = await startCallbackServer();
|
||||
|
||||
try {
|
||||
// Build authorization URL
|
||||
const authParams = new URLSearchParams({
|
||||
client_id: CLIENT_ID,
|
||||
response_type: "code",
|
||||
redirect_uri: REDIRECT_URI,
|
||||
scope: SCOPES.join(" "),
|
||||
code_challenge: challenge,
|
||||
code_challenge_method: "S256",
|
||||
state: verifier,
|
||||
access_type: "offline",
|
||||
prompt: "consent",
|
||||
});
|
||||
|
||||
const authUrl = `${AUTH_URL}?${authParams.toString()}`;
|
||||
|
||||
// Notify caller with URL to open
|
||||
onAuth({
|
||||
url: authUrl,
|
||||
instructions: "Complete the sign-in in your browser. The callback will be captured automatically.",
|
||||
});
|
||||
|
||||
// Wait for the callback
|
||||
onProgress?.("Waiting for OAuth callback...");
|
||||
const { code, state } = await getCode();
|
||||
|
||||
// Verify state matches
|
||||
if (state !== verifier) {
|
||||
throw new Error("OAuth state mismatch - possible CSRF attack");
|
||||
}
|
||||
|
||||
// Exchange code for tokens
|
||||
onProgress?.("Exchanging authorization code for tokens...");
|
||||
const tokenResponse = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/x-www-form-urlencoded",
|
||||
},
|
||||
body: new URLSearchParams({
|
||||
client_id: CLIENT_ID,
|
||||
client_secret: CLIENT_SECRET,
|
||||
code,
|
||||
grant_type: "authorization_code",
|
||||
redirect_uri: REDIRECT_URI,
|
||||
code_verifier: verifier,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!tokenResponse.ok) {
|
||||
const error = await tokenResponse.text();
|
||||
throw new Error(`Token exchange failed: ${error}`);
|
||||
}
|
||||
|
||||
const tokenData = (await tokenResponse.json()) as {
|
||||
access_token: string;
|
||||
refresh_token: string;
|
||||
expires_in: number;
|
||||
};
|
||||
|
||||
if (!tokenData.refresh_token) {
|
||||
throw new Error("No refresh token received. Please try again.");
|
||||
}
|
||||
|
||||
// Get user email
|
||||
onProgress?.("Getting user info...");
|
||||
const email = await getUserEmail(tokenData.access_token);
|
||||
|
||||
// Discover project
|
||||
const projectId = await discoverProject(tokenData.access_token, onProgress);
|
||||
|
||||
// Calculate expiry time (current time + expires_in seconds - 5 min buffer)
|
||||
const expiresAt = Date.now() + tokenData.expires_in * 1000 - 5 * 60 * 1000;
|
||||
|
||||
const credentials: OAuthCredentials = {
|
||||
refresh: tokenData.refresh_token,
|
||||
access: tokenData.access_token,
|
||||
expires: expiresAt,
|
||||
projectId,
|
||||
email,
|
||||
};
|
||||
|
||||
return credentials;
|
||||
} finally {
|
||||
server.stop();
|
||||
}
|
||||
}
|
||||
@@ -1,157 +0,0 @@
|
||||
/**
|
||||
* OAuth credential management for AI providers.
|
||||
*
|
||||
* This module handles login, token refresh, and credential storage
|
||||
* for OAuth-based providers:
|
||||
* - Anthropic (Claude Pro/Max)
|
||||
* - GitHub Copilot
|
||||
* - Google Cloud Code Assist (Gemini CLI)
|
||||
* - Antigravity (Gemini 3, Claude, GPT-OSS via Google Cloud)
|
||||
*/
|
||||
|
||||
// Anthropic
|
||||
export { loginAnthropic, refreshAnthropicToken } from "./anthropic";
|
||||
// GitHub Copilot
|
||||
export {
|
||||
getGitHubCopilotBaseUrl,
|
||||
loginGitHubCopilot,
|
||||
normalizeDomain,
|
||||
refreshGitHubCopilotToken,
|
||||
} from "./github-copilot";
|
||||
// Google Antigravity
|
||||
export {
|
||||
loginAntigravity,
|
||||
refreshAntigravityToken,
|
||||
} from "./google-antigravity";
|
||||
// Google Gemini CLI
|
||||
export {
|
||||
loginGeminiCli,
|
||||
refreshGoogleCloudToken,
|
||||
} from "./google-gemini-cli";
|
||||
// OpenAI Codex (ChatGPT OAuth)
|
||||
export {
|
||||
loginOpenAICodex,
|
||||
refreshOpenAICodexToken,
|
||||
} from "./openai-codex";
|
||||
|
||||
export * from "./types";
|
||||
|
||||
// ============================================================================
|
||||
// High-level API
|
||||
// ============================================================================
|
||||
|
||||
import { refreshAnthropicToken } from "./anthropic";
|
||||
import { refreshGitHubCopilotToken } from "./github-copilot";
|
||||
import { refreshAntigravityToken } from "./google-antigravity";
|
||||
import { refreshGoogleCloudToken } from "./google-gemini-cli";
|
||||
import { refreshOpenAICodexToken } from "./openai-codex";
|
||||
import type { OAuthCredentials, OAuthProvider, OAuthProviderInfo } from "./types";
|
||||
|
||||
/**
|
||||
* Refresh token for any OAuth provider.
|
||||
* Saves the new credentials and returns the new access token.
|
||||
*/
|
||||
export async function refreshOAuthToken(
|
||||
provider: OAuthProvider,
|
||||
credentials: OAuthCredentials,
|
||||
): Promise<OAuthCredentials> {
|
||||
if (!credentials) {
|
||||
throw new Error(`No OAuth credentials found for ${provider}`);
|
||||
}
|
||||
|
||||
let newCredentials: OAuthCredentials;
|
||||
|
||||
switch (provider) {
|
||||
case "anthropic":
|
||||
newCredentials = await refreshAnthropicToken(credentials.refresh);
|
||||
break;
|
||||
case "github-copilot":
|
||||
newCredentials = await refreshGitHubCopilotToken(credentials.refresh, credentials.enterpriseUrl);
|
||||
break;
|
||||
case "google-gemini-cli":
|
||||
if (!credentials.projectId) {
|
||||
throw new Error("Google Cloud credentials missing projectId");
|
||||
}
|
||||
newCredentials = await refreshGoogleCloudToken(credentials.refresh, credentials.projectId);
|
||||
break;
|
||||
case "google-antigravity":
|
||||
if (!credentials.projectId) {
|
||||
throw new Error("Antigravity credentials missing projectId");
|
||||
}
|
||||
newCredentials = await refreshAntigravityToken(credentials.refresh, credentials.projectId);
|
||||
break;
|
||||
case "openai-codex":
|
||||
newCredentials = await refreshOpenAICodexToken(credentials.refresh);
|
||||
break;
|
||||
default:
|
||||
throw new Error(`Unknown OAuth provider: ${provider}`);
|
||||
}
|
||||
|
||||
return newCredentials;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get API key for a provider from OAuth credentials.
|
||||
* Automatically refreshes expired tokens.
|
||||
*
|
||||
* For google-gemini-cli and antigravity, returns JSON-encoded { token, projectId }
|
||||
*
|
||||
* @returns API key string, or null if no credentials
|
||||
* @throws Error if refresh fails
|
||||
*/
|
||||
export async function getOAuthApiKey(
|
||||
provider: OAuthProvider,
|
||||
credentials: Record<string, OAuthCredentials>,
|
||||
): Promise<{ newCredentials: OAuthCredentials; apiKey: string } | null> {
|
||||
let creds = credentials[provider];
|
||||
if (!creds) {
|
||||
return null;
|
||||
}
|
||||
|
||||
// Refresh if expired
|
||||
if (Date.now() >= creds.expires) {
|
||||
try {
|
||||
creds = await refreshOAuthToken(provider, creds);
|
||||
} catch (_error) {
|
||||
throw new Error(`Failed to refresh OAuth token for ${provider}`);
|
||||
}
|
||||
}
|
||||
|
||||
// For providers that need projectId, return JSON
|
||||
const needsProjectId = provider === "google-gemini-cli" || provider === "google-antigravity";
|
||||
const apiKey = needsProjectId ? JSON.stringify({ token: creds.access, projectId: creds.projectId }) : creds.access;
|
||||
return { newCredentials: creds, apiKey };
|
||||
}
|
||||
|
||||
/**
|
||||
* Get list of OAuth providers
|
||||
*/
|
||||
export function getOAuthProviders(): OAuthProviderInfo[] {
|
||||
return [
|
||||
{
|
||||
id: "anthropic",
|
||||
name: "Anthropic (Claude Pro/Max)",
|
||||
available: true,
|
||||
},
|
||||
{
|
||||
id: "github-copilot",
|
||||
name: "GitHub Copilot",
|
||||
available: true,
|
||||
},
|
||||
{
|
||||
id: "google-gemini-cli",
|
||||
name: "Google Cloud Code Assist (Gemini CLI)",
|
||||
available: true,
|
||||
},
|
||||
{
|
||||
id: "google-antigravity",
|
||||
name: "Antigravity (Gemini 3, Claude, GPT-OSS)",
|
||||
available: true,
|
||||
},
|
||||
{
|
||||
id: "openai-codex",
|
||||
name: "ChatGPT Plus/Pro (Codex Subscription)",
|
||||
available: true,
|
||||
},
|
||||
];
|
||||
}
|
||||
@@ -1,334 +0,0 @@
|
||||
/**
|
||||
* OpenAI Codex (ChatGPT OAuth) flow
|
||||
*/
|
||||
|
||||
import { generatePKCE } from "./pkce";
|
||||
import type { OAuthCredentials, OAuthPrompt } from "./types";
|
||||
|
||||
const CLIENT_ID = "app_EMoamEEZ73f0CkXaXp7hrann";
|
||||
const AUTHORIZE_URL = "https://auth.openai.com/oauth/authorize";
|
||||
const TOKEN_URL = "https://auth.openai.com/oauth/token";
|
||||
const REDIRECT_URI = "http://localhost:1455/auth/callback";
|
||||
const SCOPE = "openid profile email offline_access";
|
||||
const JWT_CLAIM_PATH = "https://api.openai.com/auth";
|
||||
|
||||
const SUCCESS_HTML = `<!doctype html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1" />
|
||||
<title>Authentication successful</title>
|
||||
</head>
|
||||
<body>
|
||||
<p>Authentication successful. Return to your terminal to continue.</p>
|
||||
</body>
|
||||
</html>`;
|
||||
|
||||
type TokenSuccess = { type: "success"; access: string; refresh: string; expires: number };
|
||||
type TokenFailure = { type: "failed" };
|
||||
type TokenResult = TokenSuccess | TokenFailure;
|
||||
|
||||
type JwtPayload = {
|
||||
[JWT_CLAIM_PATH]?: {
|
||||
chatgpt_account_id?: string;
|
||||
};
|
||||
[key: string]: unknown;
|
||||
};
|
||||
|
||||
function createState(): string {
|
||||
const bytes = new Uint8Array(16);
|
||||
crypto.getRandomValues(bytes);
|
||||
return Array.from(bytes, (b) => b.toString(16).padStart(2, "0")).join("");
|
||||
}
|
||||
|
||||
function parseAuthorizationInput(input: string): { code?: string; state?: string } {
|
||||
const value = input.trim();
|
||||
if (!value) return {};
|
||||
|
||||
try {
|
||||
const url = new URL(value);
|
||||
return {
|
||||
code: url.searchParams.get("code") ?? undefined,
|
||||
state: url.searchParams.get("state") ?? undefined,
|
||||
};
|
||||
} catch {
|
||||
// not a URL
|
||||
}
|
||||
|
||||
if (value.includes("#")) {
|
||||
const [code, state] = value.split("#", 2);
|
||||
return { code, state };
|
||||
}
|
||||
|
||||
if (value.includes("code=")) {
|
||||
const params = new URLSearchParams(value);
|
||||
return {
|
||||
code: params.get("code") ?? undefined,
|
||||
state: params.get("state") ?? undefined,
|
||||
};
|
||||
}
|
||||
|
||||
return { code: value };
|
||||
}
|
||||
|
||||
function decodeJwt(token: string): JwtPayload | null {
|
||||
try {
|
||||
const parts = token.split(".");
|
||||
if (parts.length !== 3) return null;
|
||||
const payload = parts[1] ?? "";
|
||||
const decoded = Buffer.from(payload, "base64").toString("utf-8");
|
||||
return JSON.parse(decoded) as JwtPayload;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
async function exchangeAuthorizationCode(
|
||||
code: string,
|
||||
verifier: string,
|
||||
redirectUri: string = REDIRECT_URI,
|
||||
): Promise<TokenResult> {
|
||||
const response = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/x-www-form-urlencoded" },
|
||||
body: new URLSearchParams({
|
||||
grant_type: "authorization_code",
|
||||
client_id: CLIENT_ID,
|
||||
code,
|
||||
code_verifier: verifier,
|
||||
redirect_uri: redirectUri,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const text = await response.text().catch(() => "");
|
||||
console.error("[openai-codex] code->token failed:", response.status, text);
|
||||
return { type: "failed" };
|
||||
}
|
||||
|
||||
const json = (await response.json()) as {
|
||||
access_token?: string;
|
||||
refresh_token?: string;
|
||||
expires_in?: number;
|
||||
};
|
||||
|
||||
if (!json.access_token || !json.refresh_token || typeof json.expires_in !== "number") {
|
||||
console.error("[openai-codex] token response missing fields:", json);
|
||||
return { type: "failed" };
|
||||
}
|
||||
|
||||
return {
|
||||
type: "success",
|
||||
access: json.access_token,
|
||||
refresh: json.refresh_token,
|
||||
expires: Date.now() + json.expires_in * 1000,
|
||||
};
|
||||
}
|
||||
|
||||
async function refreshAccessToken(refreshToken: string): Promise<TokenResult> {
|
||||
try {
|
||||
const response = await fetch(TOKEN_URL, {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/x-www-form-urlencoded" },
|
||||
body: new URLSearchParams({
|
||||
grant_type: "refresh_token",
|
||||
refresh_token: refreshToken,
|
||||
client_id: CLIENT_ID,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const text = await response.text().catch(() => "");
|
||||
console.error("[openai-codex] Token refresh failed:", response.status, text);
|
||||
return { type: "failed" };
|
||||
}
|
||||
|
||||
const json = (await response.json()) as {
|
||||
access_token?: string;
|
||||
refresh_token?: string;
|
||||
expires_in?: number;
|
||||
};
|
||||
|
||||
if (!json.access_token || !json.refresh_token || typeof json.expires_in !== "number") {
|
||||
console.error("[openai-codex] Token refresh response missing fields:", json);
|
||||
return { type: "failed" };
|
||||
}
|
||||
|
||||
return {
|
||||
type: "success",
|
||||
access: json.access_token,
|
||||
refresh: json.refresh_token,
|
||||
expires: Date.now() + json.expires_in * 1000,
|
||||
};
|
||||
} catch (error) {
|
||||
console.error("[openai-codex] Token refresh error:", error);
|
||||
return { type: "failed" };
|
||||
}
|
||||
}
|
||||
|
||||
async function createAuthorizationFlow(): Promise<{ verifier: string; state: string; url: string }> {
|
||||
const { verifier, challenge } = await generatePKCE();
|
||||
const state = createState();
|
||||
|
||||
const url = new URL(AUTHORIZE_URL);
|
||||
url.searchParams.set("response_type", "code");
|
||||
url.searchParams.set("client_id", CLIENT_ID);
|
||||
url.searchParams.set("redirect_uri", REDIRECT_URI);
|
||||
url.searchParams.set("scope", SCOPE);
|
||||
url.searchParams.set("code_challenge", challenge);
|
||||
url.searchParams.set("code_challenge_method", "S256");
|
||||
url.searchParams.set("state", state);
|
||||
url.searchParams.set("id_token_add_organizations", "true");
|
||||
url.searchParams.set("codex_cli_simplified_flow", "true");
|
||||
url.searchParams.set("originator", "codex_cli_rs");
|
||||
|
||||
return { verifier, state, url: url.toString() };
|
||||
}
|
||||
|
||||
type OAuthServerInfo = {
|
||||
close: () => void;
|
||||
waitForCode: () => Promise<{ code: string } | null>;
|
||||
};
|
||||
|
||||
function startLocalOAuthServer(state: string): Promise<OAuthServerInfo> {
|
||||
let lastCode: string | null = null;
|
||||
|
||||
return new Promise((resolve) => {
|
||||
try {
|
||||
const server = Bun.serve({
|
||||
port: 1455,
|
||||
hostname: "127.0.0.1",
|
||||
fetch(req) {
|
||||
try {
|
||||
const url = new URL(req.url);
|
||||
if (url.pathname !== "/auth/callback") {
|
||||
return new Response("Not found", { status: 404 });
|
||||
}
|
||||
if (url.searchParams.get("state") !== state) {
|
||||
return new Response("State mismatch", { status: 400 });
|
||||
}
|
||||
const code = url.searchParams.get("code");
|
||||
if (!code) {
|
||||
return new Response("Missing authorization code", { status: 400 });
|
||||
}
|
||||
lastCode = code;
|
||||
return new Response(SUCCESS_HTML, {
|
||||
status: 200,
|
||||
headers: { "Content-Type": "text/html; charset=utf-8" },
|
||||
});
|
||||
} catch {
|
||||
return new Response("Internal error", { status: 500 });
|
||||
}
|
||||
},
|
||||
});
|
||||
|
||||
resolve({
|
||||
close: () => server.stop(),
|
||||
waitForCode: async () => {
|
||||
const sleep = () => new Promise((r) => setTimeout(r, 100));
|
||||
for (let i = 0; i < 600; i += 1) {
|
||||
if (lastCode) return { code: lastCode };
|
||||
await sleep();
|
||||
}
|
||||
return null;
|
||||
},
|
||||
});
|
||||
} catch (err) {
|
||||
const code = (err as { code?: string }).code;
|
||||
console.error(
|
||||
"[openai-codex] Failed to bind http://127.0.0.1:1455 (",
|
||||
code,
|
||||
") Falling back to manual paste.",
|
||||
);
|
||||
resolve({
|
||||
close: () => {},
|
||||
waitForCode: async () => null,
|
||||
});
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function getAccountId(accessToken: string): string | null {
|
||||
const payload = decodeJwt(accessToken);
|
||||
const auth = payload?.[JWT_CLAIM_PATH];
|
||||
const accountId = auth?.chatgpt_account_id;
|
||||
return typeof accountId === "string" && accountId.length > 0 ? accountId : null;
|
||||
}
|
||||
|
||||
/**
|
||||
* Login with OpenAI Codex OAuth
|
||||
*/
|
||||
export async function loginOpenAICodex(options: {
|
||||
onAuth: (info: { url: string; instructions?: string }) => void;
|
||||
onPrompt: (prompt: OAuthPrompt) => Promise<string>;
|
||||
onProgress?: (message: string) => void;
|
||||
}): Promise<OAuthCredentials> {
|
||||
const { verifier, state, url } = await createAuthorizationFlow();
|
||||
const server = await startLocalOAuthServer(state);
|
||||
|
||||
options.onAuth({ url, instructions: "A browser window should open. Complete login to finish." });
|
||||
|
||||
let code: string | undefined;
|
||||
try {
|
||||
const result = await server.waitForCode();
|
||||
if (result?.code) {
|
||||
code = result.code;
|
||||
}
|
||||
|
||||
if (!code) {
|
||||
const input = await options.onPrompt({
|
||||
message: "Paste the authorization code (or full redirect URL):",
|
||||
});
|
||||
const parsed = parseAuthorizationInput(input);
|
||||
if (parsed.state && parsed.state !== state) {
|
||||
throw new Error("State mismatch");
|
||||
}
|
||||
code = parsed.code;
|
||||
}
|
||||
|
||||
if (!code) {
|
||||
throw new Error("Missing authorization code");
|
||||
}
|
||||
|
||||
const tokenResult = await exchangeAuthorizationCode(code, verifier);
|
||||
if (tokenResult.type !== "success") {
|
||||
throw new Error("Token exchange failed");
|
||||
}
|
||||
|
||||
const accountId = getAccountId(tokenResult.access);
|
||||
if (!accountId) {
|
||||
throw new Error("Failed to extract accountId from token");
|
||||
}
|
||||
|
||||
return {
|
||||
access: tokenResult.access,
|
||||
refresh: tokenResult.refresh,
|
||||
expires: tokenResult.expires,
|
||||
accountId,
|
||||
};
|
||||
} finally {
|
||||
server.close();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Refresh OpenAI Codex OAuth token
|
||||
*/
|
||||
export async function refreshOpenAICodexToken(refreshToken: string): Promise<OAuthCredentials> {
|
||||
const result = await refreshAccessToken(refreshToken);
|
||||
if (result.type !== "success") {
|
||||
throw new Error("Failed to refresh OpenAI Codex token");
|
||||
}
|
||||
|
||||
const accountId = getAccountId(result.access);
|
||||
if (!accountId) {
|
||||
throw new Error("Failed to extract accountId from token");
|
||||
}
|
||||
|
||||
return {
|
||||
access: result.access,
|
||||
refresh: result.refresh,
|
||||
expires: result.expires,
|
||||
accountId,
|
||||
};
|
||||
}
|
||||
@@ -1,34 +0,0 @@
|
||||
/**
|
||||
* PKCE utilities using Web Crypto API.
|
||||
* Works in both Node.js 20+ and browsers.
|
||||
*/
|
||||
|
||||
/**
|
||||
* Encode bytes as base64url string.
|
||||
*/
|
||||
function base64urlEncode(bytes: Uint8Array): string {
|
||||
let binary = "";
|
||||
for (const byte of bytes) {
|
||||
binary += String.fromCharCode(byte);
|
||||
}
|
||||
return btoa(binary).replace(/\+/g, "-").replace(/\//g, "_").replace(/=/g, "");
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate PKCE code verifier and challenge.
|
||||
* Uses Web Crypto API for cross-platform compatibility.
|
||||
*/
|
||||
export async function generatePKCE(): Promise<{ verifier: string; challenge: string }> {
|
||||
// Generate random verifier
|
||||
const verifierBytes = new Uint8Array(32);
|
||||
crypto.getRandomValues(verifierBytes);
|
||||
const verifier = base64urlEncode(verifierBytes);
|
||||
|
||||
// Compute SHA-256 challenge
|
||||
const encoder = new TextEncoder();
|
||||
const data = encoder.encode(verifier);
|
||||
const hashBuffer = await crypto.subtle.digest("SHA-256", data);
|
||||
const challenge = base64urlEncode(new Uint8Array(hashBuffer));
|
||||
|
||||
return { verifier, challenge };
|
||||
}
|
||||
@@ -1,33 +0,0 @@
|
||||
export type OAuthCredentials = {
|
||||
refresh: string;
|
||||
access: string;
|
||||
expires: number;
|
||||
enterpriseUrl?: string;
|
||||
projectId?: string;
|
||||
email?: string;
|
||||
accountId?: string;
|
||||
};
|
||||
|
||||
export type OAuthProvider =
|
||||
| "anthropic"
|
||||
| "github-copilot"
|
||||
| "google-gemini-cli"
|
||||
| "google-antigravity"
|
||||
| "openai-codex";
|
||||
|
||||
export type OAuthPrompt = {
|
||||
message: string;
|
||||
placeholder?: string;
|
||||
allowEmpty?: boolean;
|
||||
};
|
||||
|
||||
export type OAuthAuthInfo = {
|
||||
url: string;
|
||||
instructions?: string;
|
||||
};
|
||||
|
||||
export interface OAuthProviderInfo {
|
||||
id: OAuthProvider;
|
||||
name: string;
|
||||
available: boolean;
|
||||
}
|
||||
@@ -1,115 +0,0 @@
|
||||
import type { AssistantMessage } from "../types";
|
||||
|
||||
/**
|
||||
* Regex patterns to detect context overflow errors from different providers.
|
||||
*
|
||||
* These patterns match error messages returned when the input exceeds
|
||||
* the model's context window.
|
||||
*
|
||||
* Provider-specific patterns (with example error messages):
|
||||
*
|
||||
* - Anthropic: "prompt is too long: 213462 tokens > 200000 maximum"
|
||||
* - OpenAI: "Your input exceeds the context window of this model"
|
||||
* - Google: "The input token count (1196265) exceeds the maximum number of tokens allowed (1048575)"
|
||||
* - xAI: "This model's maximum prompt length is 131072 but the request contains 537812 tokens"
|
||||
* - Groq: "Please reduce the length of the messages or completion"
|
||||
* - OpenRouter: "This endpoint's maximum context length is X tokens. However, you requested about Y tokens"
|
||||
* - llama.cpp: "the request exceeds the available context size, try increasing it"
|
||||
* - LM Studio: "tokens to keep from the initial prompt is greater than the context length"
|
||||
* - GitHub Copilot: "prompt token count of X exceeds the limit of Y"
|
||||
* - Cerebras: Returns "400 status code (no body)" - handled separately below
|
||||
* - Mistral: Returns "400 status code (no body)" - handled separately below
|
||||
* - z.ai: Does NOT error, accepts overflow silently - handled via usage.input > contextWindow
|
||||
* - Ollama: Silently truncates input - not detectable via error message
|
||||
*/
|
||||
const OVERFLOW_PATTERNS = [
|
||||
/prompt is too long/i, // Anthropic
|
||||
/exceeds the context window/i, // OpenAI (Completions & Responses API)
|
||||
/input token count.*exceeds the maximum/i, // Google (Gemini)
|
||||
/maximum prompt length is \d+/i, // xAI (Grok)
|
||||
/reduce the length of the messages/i, // Groq
|
||||
/maximum context length is \d+ tokens/i, // OpenRouter (all backends)
|
||||
/exceeds the limit of \d+/i, // GitHub Copilot
|
||||
/exceeds the available context size/i, // llama.cpp server
|
||||
/greater than the context length/i, // LM Studio
|
||||
/context length exceeded/i, // Generic fallback
|
||||
/too many tokens/i, // Generic fallback
|
||||
/token limit exceeded/i, // Generic fallback
|
||||
];
|
||||
|
||||
/**
|
||||
* Check if an assistant message represents a context overflow error.
|
||||
*
|
||||
* This handles two cases:
|
||||
* 1. Error-based overflow: Most providers return stopReason "error" with a
|
||||
* specific error message pattern.
|
||||
* 2. Silent overflow: Some providers accept overflow requests and return
|
||||
* successfully. For these, we check if usage.input exceeds the context window.
|
||||
*
|
||||
* ## Reliability by Provider
|
||||
*
|
||||
* **Reliable detection (returns error with detectable message):**
|
||||
* - Anthropic: "prompt is too long: X tokens > Y maximum"
|
||||
* - OpenAI (Completions & Responses): "exceeds the context window"
|
||||
* - Google Gemini: "input token count exceeds the maximum"
|
||||
* - xAI (Grok): "maximum prompt length is X but request contains Y"
|
||||
* - Groq: "reduce the length of the messages"
|
||||
* - Cerebras: 400/413/429 status code (no body)
|
||||
* - Mistral: 400/413/429 status code (no body)
|
||||
* - OpenRouter (all backends): "maximum context length is X tokens"
|
||||
* - llama.cpp: "exceeds the available context size"
|
||||
* - LM Studio: "greater than the context length"
|
||||
*
|
||||
* **Unreliable detection:**
|
||||
* - z.ai: Sometimes accepts overflow silently (detectable via usage.input > contextWindow),
|
||||
* sometimes returns rate limit errors. Pass contextWindow param to detect silent overflow.
|
||||
* - Ollama: Silently truncates input without error. Cannot be detected via this function.
|
||||
* The response will have usage.input < expected, but we don't know the expected value.
|
||||
*
|
||||
* ## Custom Providers
|
||||
*
|
||||
* If you've added custom models via settings.json, this function may not detect
|
||||
* overflow errors from those providers. To add support:
|
||||
*
|
||||
* 1. Send a request that exceeds the model's context window
|
||||
* 2. Check the errorMessage in the response
|
||||
* 3. Create a regex pattern that matches the error
|
||||
* 4. The pattern should be added to OVERFLOW_PATTERNS in this file, or
|
||||
* check the errorMessage yourself before calling this function
|
||||
*
|
||||
* @param message - The assistant message to check
|
||||
* @param contextWindow - Optional context window size for detecting silent overflow (z.ai)
|
||||
* @returns true if the message indicates a context overflow
|
||||
*/
|
||||
export function isContextOverflow(message: AssistantMessage, contextWindow?: number): boolean {
|
||||
// Case 1: Check error message patterns
|
||||
if (message.stopReason === "error" && message.errorMessage) {
|
||||
// Check known patterns
|
||||
if (OVERFLOW_PATTERNS.some((p) => p.test(message.errorMessage!))) {
|
||||
return true;
|
||||
}
|
||||
|
||||
// Cerebras and Mistral return 400/413/429 with no body - check for status code pattern
|
||||
// 429 can indicate token-based rate limiting which correlates with context overflow
|
||||
if (/^4(00|13|29)\s*(status code)?\s*\(no body\)/i.test(message.errorMessage)) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
// Case 2: Silent overflow (z.ai style) - successful but usage exceeds context
|
||||
if (contextWindow && message.stopReason === "stop") {
|
||||
const inputTokens = message.usage.input + message.usage.cacheRead;
|
||||
if (inputTokens > contextWindow) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the overflow patterns for testing purposes.
|
||||
*/
|
||||
export function getOverflowPatterns(): RegExp[] {
|
||||
return [...OVERFLOW_PATTERNS];
|
||||
}
|
||||
@@ -1,25 +0,0 @@
|
||||
/**
|
||||
* Removes unpaired Unicode surrogate characters from a string.
|
||||
*
|
||||
* Unpaired surrogates (high surrogates 0xD800-0xDBFF without matching low surrogates 0xDC00-0xDFFF,
|
||||
* or vice versa) cause JSON serialization errors in many API providers.
|
||||
*
|
||||
* Valid emoji and other characters outside the Basic Multilingual Plane use properly paired
|
||||
* surrogates and will NOT be affected by this function.
|
||||
*
|
||||
* @param text - The text to sanitize
|
||||
* @returns The sanitized text with unpaired surrogates removed
|
||||
*
|
||||
* @example
|
||||
* // Valid emoji (properly paired surrogates) are preserved
|
||||
* sanitizeSurrogates("Hello 🙈 World") // => "Hello 🙈 World"
|
||||
*
|
||||
* // Unpaired high surrogate is removed
|
||||
* const unpaired = String.fromCharCode(0xD83D); // high surrogate without low
|
||||
* sanitizeSurrogates(`Text ${unpaired} here`) // => "Text here"
|
||||
*/
|
||||
export function sanitizeSurrogates(text: string): string {
|
||||
// Replace unpaired high surrogates (0xD800-0xDBFF not followed by low surrogate)
|
||||
// Replace unpaired low surrogates (0xDC00-0xDFFF not preceded by high surrogate)
|
||||
return text.replace(/[\uD800-\uDBFF](?![\uDC00-\uDFFF])|(?<![\uD800-\uDBFF])[\uDC00-\uDFFF]/g, "");
|
||||
}
|
||||
@@ -1,24 +0,0 @@
|
||||
import { type TUnsafe, Type } from "@sinclair/typebox";
|
||||
|
||||
/**
|
||||
* Creates a string enum schema compatible with Google's API and other providers
|
||||
* that don't support anyOf/const patterns.
|
||||
*
|
||||
* @example
|
||||
* const OperationSchema = StringEnum(["add", "subtract", "multiply", "divide"], {
|
||||
* description: "The operation to perform"
|
||||
* });
|
||||
*
|
||||
* type Operation = Static<typeof OperationSchema>; // "add" | "subtract" | "multiply" | "divide"
|
||||
*/
|
||||
export function StringEnum<T extends readonly string[]>(
|
||||
values: T,
|
||||
options?: { description?: string; default?: T[number] },
|
||||
): TUnsafe<T[number]> {
|
||||
return Type.Unsafe<T[number]>({
|
||||
type: "string",
|
||||
enum: values as any,
|
||||
...(options?.description && { description: options.description }),
|
||||
...(options?.default && { default: options.default }),
|
||||
});
|
||||
}
|
||||
@@ -1,80 +0,0 @@
|
||||
import AjvModule from "ajv";
|
||||
import addFormatsModule from "ajv-formats";
|
||||
|
||||
// Handle both default and named exports
|
||||
const Ajv = (AjvModule as any).default || AjvModule;
|
||||
const addFormats = (addFormatsModule as any).default || addFormatsModule;
|
||||
|
||||
import type { Tool, ToolCall } from "../types";
|
||||
|
||||
// Detect if we're in a browser extension environment with strict CSP
|
||||
// Chrome extensions with Manifest V3 don't allow eval/Function constructor
|
||||
const isBrowserExtension = typeof globalThis !== "undefined" && (globalThis as any).chrome?.runtime?.id !== undefined;
|
||||
|
||||
// Create a singleton AJV instance with formats (only if not in browser extension)
|
||||
// AJV requires 'unsafe-eval' CSP which is not allowed in Manifest V3
|
||||
let ajv: any = null;
|
||||
if (!isBrowserExtension) {
|
||||
try {
|
||||
ajv = new Ajv({
|
||||
allErrors: true,
|
||||
strict: false,
|
||||
});
|
||||
addFormats(ajv);
|
||||
} catch (_e) {
|
||||
// AJV initialization failed (likely CSP restriction)
|
||||
console.warn("AJV validation disabled due to CSP restrictions");
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Finds a tool by name and validates the tool call arguments against its TypeBox schema
|
||||
* @param tools Array of tool definitions
|
||||
* @param toolCall The tool call from the LLM
|
||||
* @returns The validated arguments
|
||||
* @throws Error if tool is not found or validation fails
|
||||
*/
|
||||
export function validateToolCall(tools: Tool[], toolCall: ToolCall): any {
|
||||
const tool = tools.find((t) => t.name === toolCall.name);
|
||||
if (!tool) {
|
||||
throw new Error(`Tool "${toolCall.name}" not found`);
|
||||
}
|
||||
return validateToolArguments(tool, toolCall);
|
||||
}
|
||||
|
||||
/**
|
||||
* Validates tool call arguments against the tool's TypeBox schema
|
||||
* @param tool The tool definition with TypeBox schema
|
||||
* @param toolCall The tool call from the LLM
|
||||
* @returns The validated arguments
|
||||
* @throws Error with formatted message if validation fails
|
||||
*/
|
||||
export function validateToolArguments(tool: Tool, toolCall: ToolCall): any {
|
||||
// Skip validation in browser extension environment (CSP restrictions prevent AJV from working)
|
||||
if (!ajv || isBrowserExtension) {
|
||||
// Trust the LLM's output without validation
|
||||
// Browser extensions can't use AJV due to Manifest V3 CSP restrictions
|
||||
return toolCall.arguments;
|
||||
}
|
||||
|
||||
// Compile the schema
|
||||
const validate = ajv.compile(tool.parameters);
|
||||
|
||||
// Validate the arguments
|
||||
if (validate(toolCall.arguments)) {
|
||||
return toolCall.arguments;
|
||||
}
|
||||
|
||||
// Format validation errors nicely
|
||||
const errors =
|
||||
validate.errors
|
||||
?.map((err: any) => {
|
||||
const path = err.instancePath ? err.instancePath.substring(1) : err.params.missingProperty || "root";
|
||||
return ` - ${path}: ${err.message}`;
|
||||
})
|
||||
.join("\n") || "Unknown validation error";
|
||||
|
||||
const errorMessage = `Validation failed for tool "${toolCall.name}":\n${errors}\n\nReceived arguments:\n${JSON.stringify(toolCall.arguments, null, 2)}`;
|
||||
|
||||
throw new Error(errorMessage);
|
||||
}
|
||||
@@ -1,142 +0,0 @@
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete, stream } from "../src/stream";
|
||||
import type { Api, Context, Model, OptionsForApi } from "../src/types";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const geminiCliToken = await resolveApiKey("google-gemini-cli");
|
||||
|
||||
async function testAbortSignal<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "What is 15 + 27? Think step by step. Then list 50 first names.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
let abortFired = false;
|
||||
let text = "";
|
||||
const controller = new AbortController();
|
||||
const response = await stream(llm, context, { ...options, signal: controller.signal });
|
||||
for await (const event of response) {
|
||||
if (abortFired) return;
|
||||
if (event.type === "text_delta" || event.type === "thinking_delta") {
|
||||
text += event.delta;
|
||||
}
|
||||
if (text.length >= 50) {
|
||||
controller.abort();
|
||||
abortFired = true;
|
||||
}
|
||||
}
|
||||
const msg = await response.result();
|
||||
|
||||
// If we get here without throwing, the abort didn't work
|
||||
expect(msg.stopReason).toBe("aborted");
|
||||
expect(msg.content.length).toBeGreaterThan(0);
|
||||
|
||||
context.messages.push(msg);
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content: "Please continue, but only generate 5 names.",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
const followUp = await complete(llm, context, options);
|
||||
expect(followUp.stopReason).toBe("stop");
|
||||
expect(followUp.content.length).toBeGreaterThan(0);
|
||||
}
|
||||
|
||||
async function testImmediateAbort<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
const controller = new AbortController();
|
||||
|
||||
controller.abort();
|
||||
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const response = await complete(llm, context, { ...options, signal: controller.signal });
|
||||
expect(response.stopReason).toBe("aborted");
|
||||
}
|
||||
|
||||
describe("AI Providers Abort Tests", () => {
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider Abort", () => {
|
||||
const llm = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should abort mid-stream", { retry: 3 }, async () => {
|
||||
await testAbortSignal(llm, { thinking: { enabled: true } });
|
||||
});
|
||||
|
||||
it("should handle immediate abort", { retry: 3 }, async () => {
|
||||
await testImmediateAbort(llm, { thinking: { enabled: true } });
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider Abort", () => {
|
||||
const llm: Model<"openai-completions"> = {
|
||||
...getModel("openai", "gpt-4o-mini")!,
|
||||
api: "openai-completions",
|
||||
};
|
||||
|
||||
it("should abort mid-stream", { retry: 3 }, async () => {
|
||||
await testAbortSignal(llm);
|
||||
});
|
||||
|
||||
it("should handle immediate abort", { retry: 3 }, async () => {
|
||||
await testImmediateAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider Abort", () => {
|
||||
const llm = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should abort mid-stream", { retry: 3 }, async () => {
|
||||
await testAbortSignal(llm);
|
||||
});
|
||||
|
||||
it("should handle immediate abort", { retry: 3 }, async () => {
|
||||
await testImmediateAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_OAUTH_TOKEN)("Anthropic Provider Abort", () => {
|
||||
const llm = getModel("anthropic", "claude-opus-4-1-20250805");
|
||||
|
||||
it("should abort mid-stream", { retry: 3 }, async () => {
|
||||
await testAbortSignal(llm, { thinkingEnabled: true, thinkingBudgetTokens: 2048 });
|
||||
});
|
||||
|
||||
it("should handle immediate abort", { retry: 3 }, async () => {
|
||||
await testImmediateAbort(llm, { thinkingEnabled: true, thinkingBudgetTokens: 2048 });
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider Abort", () => {
|
||||
const llm = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("should abort mid-stream", { retry: 3 }, async () => {
|
||||
await testAbortSignal(llm);
|
||||
});
|
||||
|
||||
it("should handle immediate abort", { retry: 3 }, async () => {
|
||||
await testImmediateAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
// Google Gemini CLI / Antigravity share the same provider, so one test covers both
|
||||
describe("Google Gemini CLI Provider Abort", () => {
|
||||
it.skipIf(!geminiCliToken)("should abort mid-stream", { retry: 3 }, async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testAbortSignal(llm, { apiKey: geminiCliToken });
|
||||
});
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle immediate abort", { retry: 3 }, async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testImmediateAbort(llm, { apiKey: geminiCliToken });
|
||||
});
|
||||
});
|
||||
});
|
||||
@@ -1,579 +0,0 @@
|
||||
/**
|
||||
* Test context overflow error handling across providers.
|
||||
*
|
||||
* Context overflow occurs when the input (prompt + history) exceeds
|
||||
* the model's context window. This is different from output token limits.
|
||||
*
|
||||
* Expected behavior: All providers should return stopReason: "error"
|
||||
* with an errorMessage that indicates the context was too large,
|
||||
* OR (for z.ai) return successfully with usage.input > contextWindow.
|
||||
*
|
||||
* The isContextOverflow() function must return true for all providers.
|
||||
*/
|
||||
|
||||
import type { Subprocess } from "bun";
|
||||
import { afterAll, beforeAll, describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete } from "../src/stream";
|
||||
import type { AssistantMessage, Context, Model, Usage } from "../src/types";
|
||||
import { isContextOverflow } from "../src/utils/overflow";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
// Lorem ipsum paragraph for realistic token estimation
|
||||
const LOREM_IPSUM = `Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. `;
|
||||
|
||||
// Generate a string that will exceed the context window
|
||||
// Using chars/4 as token estimate (works better with varied text than repeated chars)
|
||||
function generateOverflowContent(contextWindow: number): string {
|
||||
const targetTokens = contextWindow + 10000; // Exceed by 10k tokens
|
||||
const targetChars = targetTokens * 4 * 1.5;
|
||||
const repetitions = Math.ceil(targetChars / LOREM_IPSUM.length);
|
||||
return LOREM_IPSUM.repeat(repetitions);
|
||||
}
|
||||
|
||||
interface OverflowResult {
|
||||
provider: string;
|
||||
model: string;
|
||||
contextWindow: number;
|
||||
stopReason: string;
|
||||
errorMessage: string | undefined;
|
||||
usage: Usage;
|
||||
hasUsageData: boolean;
|
||||
response: AssistantMessage;
|
||||
}
|
||||
|
||||
async function testContextOverflow(model: Model<any>, apiKey: string): Promise<OverflowResult> {
|
||||
const overflowContent = generateOverflowContent(model.contextWindow);
|
||||
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: overflowContent,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const response = await complete(model, context, { apiKey });
|
||||
|
||||
const hasUsageData = response.usage.input > 0 || response.usage.cacheRead > 0;
|
||||
|
||||
return {
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
contextWindow: model.contextWindow,
|
||||
stopReason: response.stopReason,
|
||||
errorMessage: response.errorMessage,
|
||||
usage: response.usage,
|
||||
hasUsageData,
|
||||
response,
|
||||
};
|
||||
}
|
||||
|
||||
function logResult(result: OverflowResult) {
|
||||
console.log(`\n${result.provider} / ${result.model}:`);
|
||||
console.log(` contextWindow: ${result.contextWindow}`);
|
||||
console.log(` stopReason: ${result.stopReason}`);
|
||||
console.log(` errorMessage: ${result.errorMessage}`);
|
||||
console.log(` usage: ${JSON.stringify(result.usage)}`);
|
||||
console.log(` hasUsageData: ${result.hasUsageData}`);
|
||||
}
|
||||
|
||||
// =============================================================================
|
||||
// Anthropic
|
||||
// Expected pattern: "prompt is too long: X tokens > Y maximum"
|
||||
// =============================================================================
|
||||
|
||||
describe("Context overflow error handling", () => {
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic (API Key)", () => {
|
||||
it("claude-3-5-haiku - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
const result = await testContextOverflow(model, process.env.ANTHROPIC_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/prompt is too long/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_OAUTH_TOKEN)("Anthropic (OAuth)", () => {
|
||||
it("claude-sonnet-4 - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("anthropic", "claude-sonnet-4-20250514");
|
||||
const result = await testContextOverflow(model, process.env.ANTHROPIC_OAUTH_TOKEN!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/prompt is too long/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// GitHub Copilot (OAuth)
|
||||
// Tests both OpenAI and Anthropic models via Copilot
|
||||
// =============================================================================
|
||||
|
||||
describe("GitHub Copilot (OAuth)", () => {
|
||||
// OpenAI model via Copilot
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should detect overflow via isContextOverflow",
|
||||
async () => {
|
||||
const model = getModel("github-copilot", "gpt-4o");
|
||||
const result = await testContextOverflow(model, githubCopilotToken!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/exceeds the limit of \d+/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
},
|
||||
120000,
|
||||
);
|
||||
|
||||
// Anthropic model via Copilot
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should detect overflow via isContextOverflow",
|
||||
async () => {
|
||||
const model = getModel("github-copilot", "claude-sonnet-4");
|
||||
const result = await testContextOverflow(model, githubCopilotToken!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/exceeds the limit of \d+/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
},
|
||||
120000,
|
||||
);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// OpenAI
|
||||
// Expected pattern: "exceeds the context window"
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions", () => {
|
||||
it("gpt-4o-mini - should detect overflow via isContextOverflow", async () => {
|
||||
const model = { ...getModel("openai", "gpt-4o-mini") };
|
||||
model.api = "openai-completions" as any;
|
||||
const result = await testContextOverflow(model, process.env.OPENAI_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/maximum context length/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses", () => {
|
||||
it("gpt-4o - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("openai", "gpt-4o");
|
||||
const result = await testContextOverflow(model, process.env.OPENAI_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/exceeds the context window/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// Google
|
||||
// Expected pattern: "input token count (X) exceeds the maximum"
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google", () => {
|
||||
it("gemini-2.0-flash - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("google", "gemini-2.0-flash");
|
||||
const result = await testContextOverflow(model, process.env.GEMINI_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/input token count.*exceeds the maximum/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// Google Gemini CLI (OAuth)
|
||||
// Uses same API as Google, expects same error pattern
|
||||
// =============================================================================
|
||||
|
||||
describe("Google Gemini CLI (OAuth)", () => {
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should detect overflow via isContextOverflow",
|
||||
async () => {
|
||||
const model = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
const result = await testContextOverflow(model, geminiCliToken!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/input token count.*exceeds the maximum/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
},
|
||||
120000,
|
||||
);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// Google Antigravity (OAuth)
|
||||
// Tests both Gemini and Anthropic models via Antigravity
|
||||
// =============================================================================
|
||||
|
||||
describe("Google Antigravity (OAuth)", () => {
|
||||
// Gemini model
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should detect overflow via isContextOverflow",
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "gemini-3-flash");
|
||||
const result = await testContextOverflow(model, antigravityToken!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/input token count.*exceeds the maximum/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
},
|
||||
120000,
|
||||
);
|
||||
|
||||
// Anthropic model via Antigravity
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should detect overflow via isContextOverflow",
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
const result = await testContextOverflow(model, antigravityToken!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
// Anthropic models return "prompt is too long" pattern
|
||||
expect(result.errorMessage).toMatch(/prompt is too long/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
},
|
||||
120000,
|
||||
);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// xAI
|
||||
// Expected pattern: "maximum prompt length is X but the request contains Y"
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.XAI_API_KEY)("xAI", () => {
|
||||
it("grok-3-fast - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("xai", "grok-3-fast");
|
||||
const result = await testContextOverflow(model, process.env.XAI_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/maximum prompt length is \d+/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// Groq
|
||||
// Expected pattern: "reduce the length of the messages"
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.GROQ_API_KEY)("Groq", () => {
|
||||
it("llama-3.3-70b-versatile - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("groq", "llama-3.3-70b-versatile");
|
||||
const result = await testContextOverflow(model, process.env.GROQ_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/reduce the length of the messages/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// Cerebras
|
||||
// Expected: 400/413 status code with no body
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras", () => {
|
||||
it("qwen-3-235b - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("cerebras", "qwen-3-235b-a22b-instruct-2507");
|
||||
const result = await testContextOverflow(model, process.env.CEREBRAS_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
// Cerebras returns status code with no body (400, 413, or 429 for token rate limit)
|
||||
expect(result.errorMessage).toMatch(/4(00|13|29).*\(no body\)/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// z.ai
|
||||
// Special case: Sometimes accepts overflow silently, sometimes rate limits
|
||||
// Detection via usage.input > contextWindow when successful
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("z.ai", () => {
|
||||
it("glm-4.5-flash - should detect overflow via isContextOverflow (silent overflow or rate limit)", async () => {
|
||||
const model = getModel("zai", "glm-4.5-flash");
|
||||
const result = await testContextOverflow(model, process.env.ZAI_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
// z.ai behavior is inconsistent:
|
||||
// - Sometimes accepts overflow and returns successfully with usage.input > contextWindow
|
||||
// - Sometimes returns rate limit error
|
||||
// Either way, isContextOverflow should detect it (via usage check or we skip if rate limited)
|
||||
if (result.stopReason === "stop") {
|
||||
expect(result.hasUsageData).toBe(true);
|
||||
expect(result.usage.input).toBeGreaterThan(model.contextWindow);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
} else {
|
||||
// Rate limited or other error - just log and pass
|
||||
console.log(" z.ai returned error (possibly rate limited), skipping overflow detection");
|
||||
}
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// Mistral
|
||||
// Expected pattern: TBD - need to test actual error message
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral", () => {
|
||||
it("devstral-medium-latest - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("mistral", "devstral-medium-latest");
|
||||
const result = await testContextOverflow(model, process.env.MISTRAL_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// OpenRouter - Multiple backend providers
|
||||
// Expected pattern: "maximum context length is X tokens"
|
||||
// =============================================================================
|
||||
|
||||
describe.skipIf(!process.env.OPENROUTER_API_KEY)("OpenRouter", () => {
|
||||
// Anthropic backend
|
||||
it("anthropic/claude-sonnet-4 via OpenRouter - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("openrouter", "anthropic/claude-sonnet-4");
|
||||
const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
|
||||
// DeepSeek backend
|
||||
it("deepseek/deepseek-v3.2 via OpenRouter - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("openrouter", "deepseek/deepseek-v3.2");
|
||||
const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
|
||||
// Mistral backend
|
||||
it("mistralai/mistral-large-2512 via OpenRouter - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("openrouter", "mistralai/mistral-large-2512");
|
||||
const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
|
||||
// Google backend
|
||||
it("google/gemini-2.5-flash via OpenRouter - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("openrouter", "google/gemini-2.5-flash");
|
||||
const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
|
||||
// Meta/Llama backend
|
||||
it("meta-llama/llama-4-maverick via OpenRouter - should detect overflow via isContextOverflow", async () => {
|
||||
const model = getModel("openrouter", "meta-llama/llama-4-maverick");
|
||||
const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// Ollama (local)
|
||||
// =============================================================================
|
||||
|
||||
// Check if ollama is installed
|
||||
const ollamaInstalled = Bun.which("ollama") !== null;
|
||||
|
||||
describe.skipIf(!ollamaInstalled)("Ollama (local)", () => {
|
||||
let ollamaProcess: Subprocess | null = null;
|
||||
let model: Model<"openai-completions">;
|
||||
|
||||
beforeAll(async () => {
|
||||
// Check if model is available, if not pull it
|
||||
try {
|
||||
Bun.spawnSync(["sh", "-c", "ollama list | grep -q 'gpt-oss:20b'"]);
|
||||
} catch {
|
||||
console.log("Pulling gpt-oss:20b model for Ollama overflow tests...");
|
||||
try {
|
||||
await Bun.spawn(["ollama", "pull", "gpt-oss:20b"], { stdout: "inherit" }).exited;
|
||||
} catch (_e) {
|
||||
console.warn("Failed to pull gpt-oss:20b model, tests will be skipped");
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
// Start ollama server
|
||||
ollamaProcess = Bun.spawn(["ollama", "serve"], {
|
||||
stdout: "ignore",
|
||||
stderr: "ignore",
|
||||
});
|
||||
|
||||
// Wait for server to be ready
|
||||
await new Promise<void>((resolve) => {
|
||||
const checkServer = async () => {
|
||||
try {
|
||||
const response = await fetch("http://localhost:11434/api/tags");
|
||||
if (response.ok) {
|
||||
resolve();
|
||||
} else {
|
||||
setTimeout(checkServer, 500);
|
||||
}
|
||||
} catch {
|
||||
setTimeout(checkServer, 500);
|
||||
}
|
||||
};
|
||||
setTimeout(checkServer, 1000);
|
||||
});
|
||||
|
||||
model = {
|
||||
id: "gpt-oss:20b",
|
||||
api: "openai-completions",
|
||||
provider: "ollama",
|
||||
baseUrl: "http://localhost:11434/v1",
|
||||
reasoning: true,
|
||||
input: ["text"],
|
||||
contextWindow: 128000,
|
||||
maxTokens: 16000,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
name: "Ollama GPT-OSS 20B",
|
||||
};
|
||||
}, 60000);
|
||||
|
||||
afterAll(() => {
|
||||
if (ollamaProcess) {
|
||||
ollamaProcess.kill();
|
||||
ollamaProcess = null;
|
||||
}
|
||||
});
|
||||
|
||||
it("gpt-oss:20b - should detect overflow via isContextOverflow (ollama silently truncates)", async () => {
|
||||
const result = await testContextOverflow(model, "ollama");
|
||||
logResult(result);
|
||||
|
||||
// Ollama silently truncates input instead of erroring
|
||||
// It returns stopReason "stop" with truncated usage
|
||||
// We cannot detect overflow via error message, only via usage comparison
|
||||
if (result.stopReason === "stop" && result.hasUsageData) {
|
||||
// Ollama truncated - check if reported usage is less than what we sent
|
||||
// This is a "silent overflow" - we can detect it if we know expected input size
|
||||
console.log(" Ollama silently truncated input to", result.usage.input, "tokens");
|
||||
// For now, we accept this behavior - Ollama doesn't give us a way to detect overflow
|
||||
} else if (result.stopReason === "error") {
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}
|
||||
}, 300000); // 5 min timeout for local model
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// LM Studio (local) - Skip if not running
|
||||
// =============================================================================
|
||||
|
||||
let lmStudioRunning = false;
|
||||
try {
|
||||
const result = Bun.spawnSync(["curl", "-s", "--max-time", "1", "http://localhost:1234/v1/models"]);
|
||||
lmStudioRunning = result.exitCode === 0;
|
||||
} catch {
|
||||
lmStudioRunning = false;
|
||||
}
|
||||
|
||||
describe.skipIf(!lmStudioRunning)("LM Studio (local)", () => {
|
||||
it("should detect overflow via isContextOverflow", async () => {
|
||||
const model: Model<"openai-completions"> = {
|
||||
id: "local-model",
|
||||
api: "openai-completions",
|
||||
provider: "lm-studio",
|
||||
baseUrl: "http://localhost:1234/v1",
|
||||
reasoning: false,
|
||||
input: ["text"],
|
||||
contextWindow: 8192,
|
||||
maxTokens: 2048,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
name: "LM Studio Local Model",
|
||||
};
|
||||
|
||||
const result = await testContextOverflow(model, "lm-studio");
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
||||
// =============================================================================
|
||||
// llama.cpp server (local) - Skip if not running
|
||||
// =============================================================================
|
||||
|
||||
let llamaCppRunning = false;
|
||||
try {
|
||||
const result = Bun.spawnSync(["curl", "-s", "--max-time", "1", "http://localhost:8081/health"]);
|
||||
llamaCppRunning = result.exitCode === 0;
|
||||
} catch {
|
||||
llamaCppRunning = false;
|
||||
}
|
||||
|
||||
describe.skipIf(!llamaCppRunning)("llama.cpp (local)", () => {
|
||||
it("should detect overflow via isContextOverflow", async () => {
|
||||
// Using small context (4096) to match server --ctx-size setting
|
||||
const model: Model<"openai-completions"> = {
|
||||
id: "local-model",
|
||||
api: "openai-completions",
|
||||
provider: "llama.cpp",
|
||||
baseUrl: "http://localhost:8081/v1",
|
||||
reasoning: false,
|
||||
input: ["text"],
|
||||
contextWindow: 4096,
|
||||
maxTokens: 2048,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
name: "llama.cpp Local Model",
|
||||
};
|
||||
|
||||
const result = await testContextOverflow(model, "llama.cpp");
|
||||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
});
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 2.5 KiB |
@@ -1,576 +0,0 @@
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete } from "../src/stream";
|
||||
import type { Api, AssistantMessage, Context, Model, OptionsForApi, UserMessage } from "../src/types";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("anthropic"),
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
async function testEmptyMessage<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
// Test with completely empty content array
|
||||
const emptyMessage: UserMessage = {
|
||||
role: "user",
|
||||
content: [],
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
const context: Context = {
|
||||
messages: [emptyMessage],
|
||||
};
|
||||
|
||||
const response = await complete(llm, context, options);
|
||||
|
||||
// Should either handle gracefully or return an error
|
||||
expect(response).toBeDefined();
|
||||
expect(response.role).toBe("assistant");
|
||||
// Should handle empty string gracefully
|
||||
if (response.stopReason === "error") {
|
||||
expect(response.errorMessage).toBeDefined();
|
||||
} else {
|
||||
expect(response.content).toBeDefined();
|
||||
}
|
||||
}
|
||||
|
||||
async function testEmptyStringMessage<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
// Test with empty string content
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const response = await complete(llm, context, options);
|
||||
|
||||
expect(response).toBeDefined();
|
||||
expect(response.role).toBe("assistant");
|
||||
|
||||
// Should handle empty string gracefully
|
||||
if (response.stopReason === "error") {
|
||||
expect(response.errorMessage).toBeDefined();
|
||||
} else {
|
||||
expect(response.content).toBeDefined();
|
||||
}
|
||||
}
|
||||
|
||||
async function testWhitespaceOnlyMessage<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
// Test with whitespace-only content
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: " \n\t ",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const response = await complete(llm, context, options);
|
||||
|
||||
expect(response).toBeDefined();
|
||||
expect(response.role).toBe("assistant");
|
||||
|
||||
// Should handle whitespace-only gracefully
|
||||
if (response.stopReason === "error") {
|
||||
expect(response.errorMessage).toBeDefined();
|
||||
} else {
|
||||
expect(response.content).toBeDefined();
|
||||
}
|
||||
}
|
||||
|
||||
async function testEmptyAssistantMessage<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
// Test with empty assistant message in conversation flow
|
||||
// User -> Empty Assistant -> User
|
||||
const emptyAssistant: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: llm.api,
|
||||
provider: llm.provider,
|
||||
model: llm.id,
|
||||
usage: {
|
||||
input: 10,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 10,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Hello, how are you?",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
emptyAssistant,
|
||||
{
|
||||
role: "user",
|
||||
content: "Please respond this time.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const response = await complete(llm, context, options);
|
||||
|
||||
expect(response).toBeDefined();
|
||||
expect(response.role).toBe("assistant");
|
||||
|
||||
// Should handle empty assistant message in context gracefully
|
||||
if (response.stopReason === "error") {
|
||||
expect(response.errorMessage).toBeDefined();
|
||||
} else {
|
||||
expect(response.content).toBeDefined();
|
||||
expect(response.content.length).toBeGreaterThan(0);
|
||||
}
|
||||
}
|
||||
|
||||
describe("AI Providers Empty Message Tests", () => {
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider Empty Messages", () => {
|
||||
const llm = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider Empty Messages", () => {
|
||||
const llm = getModel("openai", "gpt-4o-mini");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider Empty Messages", () => {
|
||||
const llm = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider Empty Messages", () => {
|
||||
const llm = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider Empty Messages", () => {
|
||||
const llm = getModel("xai", "grok-3");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider Empty Messages", () => {
|
||||
const llm = getModel("groq", "openai/gpt-oss-20b");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider Empty Messages", () => {
|
||||
const llm = getModel("cerebras", "gpt-oss-120b");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider Empty Messages", () => {
|
||||
const llm = getModel("zai", "glm-4.5-air");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider Empty Messages", () => {
|
||||
const llm = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle whitespace-only content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testWhitespaceOnlyMessage(llm);
|
||||
});
|
||||
|
||||
it("should handle empty assistant message in conversation", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyAssistantMessage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OAuth-based providers (credentials from ~/.omp/agent/auth.json)
|
||||
// =========================================================================
|
||||
|
||||
describe("Anthropic OAuth Provider Empty Messages", () => {
|
||||
const llm = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle empty content array", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyMessage(llm, { apiKey: anthropicOAuthToken });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle empty string content", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmptyStringMessage(llm, { apiKey: anthropicOAuthToken });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should handle whitespace-only content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await testWhitespaceOnlyMessage(llm, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should handle empty assistant message in conversation",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await testEmptyAssistantMessage(llm, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("GitHub Copilot Provider Empty Messages", () => {
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle empty content array",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testEmptyMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle empty string content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testEmptyStringMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle whitespace-only content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testWhitespaceOnlyMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle empty assistant message in conversation",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testEmptyAssistantMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle empty content array",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testEmptyMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle empty string content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testEmptyStringMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle whitespace-only content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testWhitespaceOnlyMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle empty assistant message in conversation",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testEmptyAssistantMessage(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Gemini CLI Provider Empty Messages", () => {
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle empty content array",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testEmptyMessage(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle empty string content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testEmptyStringMessage(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle whitespace-only content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testWhitespaceOnlyMessage(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle empty assistant message in conversation",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testEmptyAssistantMessage(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider Empty Messages", () => {
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle empty content array",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testEmptyMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle empty string content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testEmptyStringMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle whitespace-only content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testWhitespaceOnlyMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle empty assistant message in conversation",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testEmptyAssistantMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle empty content array",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testEmptyMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle empty string content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testEmptyStringMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle whitespace-only content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testWhitespaceOnlyMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle empty assistant message in conversation",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testEmptyAssistantMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle empty content array",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testEmptyMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle empty string content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testEmptyStringMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle whitespace-only content",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testWhitespaceOnlyMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle empty assistant message in conversation",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testEmptyAssistantMessage(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
});
|
||||
@@ -1,564 +0,0 @@
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete } from "../src/stream";
|
||||
import type { Api, AssistantMessage, Context, Message, Model, Tool, ToolResultMessage } from "../src/types";
|
||||
|
||||
// Tool for testing
|
||||
const weatherSchema = Type.Object({
|
||||
location: Type.String({ description: "City name" }),
|
||||
});
|
||||
|
||||
const weatherTool: Tool<typeof weatherSchema> = {
|
||||
name: "get_weather",
|
||||
description: "Get the weather for a location",
|
||||
parameters: weatherSchema,
|
||||
};
|
||||
|
||||
// Pre-built contexts representing typical outputs from each provider
|
||||
const providerContexts = {
|
||||
// Anthropic-style message with thinking block
|
||||
anthropic: {
|
||||
message: {
|
||||
role: "assistant",
|
||||
api: "anthropic-messages",
|
||||
content: [
|
||||
{
|
||||
type: "thinking",
|
||||
thinking: "Let me calculate 17 * 23. That's 17 * 20 + 17 * 3 = 340 + 51 = 391",
|
||||
thinkingSignature: "signature_abc123",
|
||||
},
|
||||
{
|
||||
type: "text",
|
||||
text: "I'll help you with the calculation and check the weather. The result of 17 × 23 is 391. The capital of Austria is Vienna. Now let me check the weather for you.",
|
||||
},
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "toolu_01abc123",
|
||||
name: "get_weather",
|
||||
arguments: { location: "Tokyo" },
|
||||
},
|
||||
],
|
||||
provider: "anthropic",
|
||||
model: "claude-3-5-haiku-latest",
|
||||
usage: {
|
||||
input: 100,
|
||||
output: 50,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 150,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
} satisfies AssistantMessage,
|
||||
toolResult: {
|
||||
role: "toolResult" as const,
|
||||
toolCallId: "toolu_01abc123",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C, partly cloudy" }],
|
||||
timestamp: Date.now(),
|
||||
} satisfies ToolResultMessage,
|
||||
facts: {
|
||||
calculation: 391,
|
||||
city: "Tokyo",
|
||||
temperature: 18,
|
||||
capital: "Vienna",
|
||||
},
|
||||
},
|
||||
|
||||
// Google-style message with thinking
|
||||
google: {
|
||||
message: {
|
||||
role: "assistant",
|
||||
api: "google-generative-ai",
|
||||
content: [
|
||||
{
|
||||
type: "thinking",
|
||||
thinking:
|
||||
"I need to multiply 19 * 24. Let me work through this: 19 * 24 = 19 * 20 + 19 * 4 = 380 + 76 = 456",
|
||||
thinkingSignature: undefined,
|
||||
},
|
||||
{
|
||||
type: "text",
|
||||
text: "The multiplication of 19 × 24 equals 456. The capital of France is Paris. Let me check the weather in Berlin for you.",
|
||||
},
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "call_gemini_123",
|
||||
name: "get_weather",
|
||||
arguments: { location: "Berlin" },
|
||||
},
|
||||
],
|
||||
provider: "google",
|
||||
model: "gemini-2.5-flash",
|
||||
usage: {
|
||||
input: 120,
|
||||
output: 60,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 180,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
} satisfies AssistantMessage,
|
||||
toolResult: {
|
||||
role: "toolResult" as const,
|
||||
toolCallId: "call_gemini_123",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Berlin: 22°C, sunny" }],
|
||||
timestamp: Date.now(),
|
||||
} satisfies ToolResultMessage,
|
||||
facts: {
|
||||
calculation: 456,
|
||||
city: "Berlin",
|
||||
temperature: 22,
|
||||
capital: "Paris",
|
||||
},
|
||||
},
|
||||
|
||||
// OpenAI Completions style (with reasoning_content)
|
||||
openaiCompletions: {
|
||||
message: {
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [
|
||||
{
|
||||
type: "thinking",
|
||||
thinking: "Let me calculate 21 * 25. That's 21 * 25 = 525",
|
||||
thinkingSignature: "reasoning_content",
|
||||
},
|
||||
{
|
||||
type: "text",
|
||||
text: "The result of 21 × 25 is 525. The capital of Spain is Madrid. I'll check the weather in London now.",
|
||||
},
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "call_abc123",
|
||||
name: "get_weather",
|
||||
arguments: { location: "London" },
|
||||
},
|
||||
],
|
||||
provider: "openai",
|
||||
model: "gpt-4o-mini",
|
||||
usage: {
|
||||
input: 110,
|
||||
output: 55,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 165,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
} satisfies AssistantMessage,
|
||||
toolResult: {
|
||||
role: "toolResult" as const,
|
||||
toolCallId: "call_abc123",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in London: 15°C, rainy" }],
|
||||
timestamp: Date.now(),
|
||||
} satisfies ToolResultMessage,
|
||||
facts: {
|
||||
calculation: 525,
|
||||
city: "London",
|
||||
temperature: 15,
|
||||
capital: "Madrid",
|
||||
},
|
||||
},
|
||||
|
||||
// OpenAI Responses style (with complex tool call IDs)
|
||||
openaiResponses: {
|
||||
message: {
|
||||
role: "assistant",
|
||||
api: "openai-responses",
|
||||
content: [
|
||||
{
|
||||
type: "thinking",
|
||||
thinking: "Calculating 18 * 27: 18 * 27 = 486",
|
||||
thinkingSignature:
|
||||
'{"type":"reasoning","id":"rs_2b2342acdde","summary":[{"type":"summary_text","text":"Calculating 18 * 27: 18 * 27 = 486"}]}',
|
||||
},
|
||||
{
|
||||
type: "text",
|
||||
text: "The calculation of 18 × 27 gives us 486. The capital of Italy is Rome. Let me check Sydney's weather.",
|
||||
textSignature: "msg_response_456",
|
||||
},
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "call_789_item_012", // Anthropic requires alphanumeric, dash, and underscore only
|
||||
name: "get_weather",
|
||||
arguments: { location: "Sydney" },
|
||||
},
|
||||
],
|
||||
provider: "openai",
|
||||
model: "gpt-5-mini",
|
||||
usage: {
|
||||
input: 115,
|
||||
output: 58,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 173,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
} satisfies AssistantMessage,
|
||||
toolResult: {
|
||||
role: "toolResult" as const,
|
||||
toolCallId: "call_789_item_012", // Match the updated ID format
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Sydney: 25°C, clear" }],
|
||||
timestamp: Date.now(),
|
||||
} satisfies ToolResultMessage,
|
||||
facts: {
|
||||
calculation: 486,
|
||||
city: "Sydney",
|
||||
temperature: 25,
|
||||
capital: "Rome",
|
||||
},
|
||||
},
|
||||
|
||||
// Aborted message (stopReason: 'error')
|
||||
aborted: {
|
||||
message: {
|
||||
role: "assistant",
|
||||
api: "anthropic-messages",
|
||||
content: [
|
||||
{
|
||||
type: "thinking",
|
||||
thinking: "Let me start calculating 20 * 30...",
|
||||
thinkingSignature: "partial_sig",
|
||||
},
|
||||
{
|
||||
type: "text",
|
||||
text: "I was about to calculate 20 × 30 which is",
|
||||
},
|
||||
],
|
||||
provider: "test",
|
||||
model: "test-model",
|
||||
usage: {
|
||||
input: 50,
|
||||
output: 25,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 75,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "error",
|
||||
errorMessage: "Request was aborted",
|
||||
timestamp: Date.now(),
|
||||
} satisfies AssistantMessage,
|
||||
toolResult: null,
|
||||
facts: {
|
||||
calculation: 600,
|
||||
city: "none",
|
||||
temperature: 0,
|
||||
capital: "none",
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
/**
|
||||
* Test that a provider can handle contexts from different sources
|
||||
*/
|
||||
async function testProviderHandoff<TApi extends Api>(
|
||||
targetModel: Model<TApi>,
|
||||
sourceLabel: string,
|
||||
sourceContext: (typeof providerContexts)[keyof typeof providerContexts],
|
||||
): Promise<boolean> {
|
||||
// Build conversation context
|
||||
let assistantMessage: AssistantMessage = sourceContext.message;
|
||||
let toolResult: ToolResultMessage | undefined | null = sourceContext.toolResult;
|
||||
|
||||
// If target is Mistral, convert tool call IDs to Mistral format
|
||||
if (targetModel.provider === "mistral" && assistantMessage.content.some((c) => c.type === "toolCall")) {
|
||||
// Clone the message to avoid mutating the original
|
||||
assistantMessage = {
|
||||
...assistantMessage,
|
||||
content: assistantMessage.content.map((content) => {
|
||||
if (content.type === "toolCall") {
|
||||
// Generate a Mistral-style tool call ID (uppercase letters and numbers)
|
||||
const mistralId = "T7TcP5RVB"; // Using the format we know works
|
||||
return {
|
||||
...content,
|
||||
id: mistralId,
|
||||
};
|
||||
}
|
||||
return content;
|
||||
}),
|
||||
} as AssistantMessage;
|
||||
|
||||
// Also update the tool result if present
|
||||
if (toolResult) {
|
||||
toolResult = {
|
||||
...toolResult,
|
||||
toolCallId: "T7TcP5RVB", // Match the tool call ID
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
const messages: Message[] = [
|
||||
{
|
||||
role: "user",
|
||||
content: "Please do some calculations, tell me about capitals, and check the weather.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
assistantMessage,
|
||||
];
|
||||
|
||||
// Add tool result if present
|
||||
if (toolResult) {
|
||||
messages.push(toolResult);
|
||||
}
|
||||
|
||||
// Ask follow-up question
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: `Based on our conversation, please answer:
|
||||
1) What was the multiplication result?
|
||||
2) Which city's weather did we check?
|
||||
3) What was the temperature?
|
||||
4) What capital city was mentioned?
|
||||
Please include the specific numbers and names.`,
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
const context: Context = {
|
||||
messages,
|
||||
tools: [weatherTool],
|
||||
};
|
||||
|
||||
try {
|
||||
const response = await complete(targetModel, context, {});
|
||||
|
||||
// Check for error
|
||||
if (response.stopReason === "error") {
|
||||
console.log(`[${sourceLabel} → ${targetModel.provider}] Failed with error: ${response.errorMessage}`);
|
||||
return false;
|
||||
}
|
||||
|
||||
// Extract text from response
|
||||
const responseText = response.content
|
||||
.filter((b) => b.type === "text")
|
||||
.map((b) => b.text)
|
||||
.join(" ")
|
||||
.toLowerCase();
|
||||
|
||||
// For aborted messages, we don't expect to find the facts
|
||||
if (sourceContext.message.stopReason === "error") {
|
||||
const hasToolCalls = response.content.some((b) => b.type === "toolCall");
|
||||
const hasThinking = response.content.some((b) => b.type === "thinking");
|
||||
const hasText = response.content.some((b) => b.type === "text");
|
||||
|
||||
expect(response.stopReason === "stop" || response.stopReason === "toolUse").toBe(true);
|
||||
expect(hasThinking || hasText || hasToolCalls).toBe(true);
|
||||
console.log(
|
||||
`[${sourceLabel} → ${targetModel.provider}] Handled aborted message successfully, tool calls: ${hasToolCalls}, thinking: ${hasThinking}, text: ${hasText}`,
|
||||
);
|
||||
return true;
|
||||
}
|
||||
|
||||
// Check if response contains our facts
|
||||
const hasCalculation = responseText.includes(sourceContext.facts.calculation.toString());
|
||||
const hasCity =
|
||||
sourceContext.facts.city !== "none" && responseText.includes(sourceContext.facts.city.toLowerCase());
|
||||
const hasTemperature =
|
||||
sourceContext.facts.temperature > 0 && responseText.includes(sourceContext.facts.temperature.toString());
|
||||
const hasCapital =
|
||||
sourceContext.facts.capital !== "none" && responseText.includes(sourceContext.facts.capital.toLowerCase());
|
||||
|
||||
const success = hasCalculation && hasCity && hasTemperature && hasCapital;
|
||||
|
||||
console.log(`[${sourceLabel} → ${targetModel.provider}] Handoff test:`);
|
||||
if (!success) {
|
||||
console.log(` Calculation (${sourceContext.facts.calculation}): ${hasCalculation ? "✓" : "✗"}`);
|
||||
console.log(` City (${sourceContext.facts.city}): ${hasCity ? "✓" : "✗"}`);
|
||||
console.log(` Temperature (${sourceContext.facts.temperature}): ${hasTemperature ? "✓" : "✗"}`);
|
||||
console.log(` Capital (${sourceContext.facts.capital}): ${hasCapital ? "✓" : "✗"}`);
|
||||
} else {
|
||||
console.log(` ✓ All facts found`);
|
||||
}
|
||||
|
||||
return success;
|
||||
} catch (error) {
|
||||
console.error(`[${sourceLabel} → ${targetModel.provider}] Exception:`, error);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
describe("Cross-Provider Handoff Tests", () => {
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider Handoff", () => {
|
||||
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it("should handle contexts from all providers", async () => {
|
||||
console.log("\nTesting Anthropic with pre-built contexts:\n");
|
||||
|
||||
const contextTests = [
|
||||
{ label: "Anthropic-style", context: providerContexts.anthropic, sourceModel: "claude-3-5-haiku-20241022" },
|
||||
{ label: "Google-style", context: providerContexts.google, sourceModel: "gemini-2.5-flash" },
|
||||
{ label: "OpenAI-Completions", context: providerContexts.openaiCompletions, sourceModel: "gpt-4o-mini" },
|
||||
{ label: "OpenAI-Responses", context: providerContexts.openaiResponses, sourceModel: "gpt-5-mini" },
|
||||
{ label: "Aborted", context: providerContexts.aborted, sourceModel: null },
|
||||
];
|
||||
|
||||
let successCount = 0;
|
||||
let skippedCount = 0;
|
||||
|
||||
for (const { label, context, sourceModel } of contextTests) {
|
||||
// Skip testing same model against itself
|
||||
if (sourceModel && sourceModel === model.id) {
|
||||
console.log(`[${label} → ${model.provider}] Skipping same-model test`);
|
||||
skippedCount++;
|
||||
continue;
|
||||
}
|
||||
const success = await testProviderHandoff(model, label, context);
|
||||
if (success) successCount++;
|
||||
}
|
||||
|
||||
const totalTests = contextTests.length - skippedCount;
|
||||
console.log(`\nAnthropic success rate: ${successCount}/${totalTests} (${skippedCount} skipped)\n`);
|
||||
|
||||
// All non-skipped handoffs should succeed
|
||||
expect(successCount).toBe(totalTests);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider Handoff", () => {
|
||||
const model = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should handle contexts from all providers", async () => {
|
||||
console.log("\nTesting Google with pre-built contexts:\n");
|
||||
|
||||
const contextTests = [
|
||||
{ label: "Anthropic-style", context: providerContexts.anthropic, sourceModel: "claude-3-5-haiku-20241022" },
|
||||
{ label: "Google-style", context: providerContexts.google, sourceModel: "gemini-2.5-flash" },
|
||||
{ label: "OpenAI-Completions", context: providerContexts.openaiCompletions, sourceModel: "gpt-4o-mini" },
|
||||
{ label: "OpenAI-Responses", context: providerContexts.openaiResponses, sourceModel: "gpt-5-mini" },
|
||||
{ label: "Aborted", context: providerContexts.aborted, sourceModel: null },
|
||||
];
|
||||
|
||||
let successCount = 0;
|
||||
let skippedCount = 0;
|
||||
|
||||
for (const { label, context, sourceModel } of contextTests) {
|
||||
// Skip testing same model against itself
|
||||
if (sourceModel && sourceModel === model.id) {
|
||||
console.log(`[${label} → ${model.provider}] Skipping same-model test`);
|
||||
skippedCount++;
|
||||
continue;
|
||||
}
|
||||
const success = await testProviderHandoff(model, label, context);
|
||||
if (success) successCount++;
|
||||
}
|
||||
|
||||
const totalTests = contextTests.length - skippedCount;
|
||||
console.log(`\nGoogle success rate: ${successCount}/${totalTests} (${skippedCount} skipped)\n`);
|
||||
|
||||
// All non-skipped handoffs should succeed
|
||||
expect(successCount).toBe(totalTests);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider Handoff", () => {
|
||||
const model: Model<"openai-completions"> = { ...getModel("openai", "gpt-4o-mini"), api: "openai-completions" };
|
||||
|
||||
it("should handle contexts from all providers", async () => {
|
||||
console.log("\nTesting OpenAI Completions with pre-built contexts:\n");
|
||||
|
||||
const contextTests = [
|
||||
{ label: "Anthropic-style", context: providerContexts.anthropic, sourceModel: "claude-3-5-haiku-20241022" },
|
||||
{ label: "Google-style", context: providerContexts.google, sourceModel: "gemini-2.5-flash" },
|
||||
{ label: "OpenAI-Completions", context: providerContexts.openaiCompletions, sourceModel: "gpt-4o-mini" },
|
||||
{ label: "OpenAI-Responses", context: providerContexts.openaiResponses, sourceModel: "gpt-5-mini" },
|
||||
{ label: "Aborted", context: providerContexts.aborted, sourceModel: null },
|
||||
];
|
||||
|
||||
let successCount = 0;
|
||||
let skippedCount = 0;
|
||||
|
||||
for (const { label, context, sourceModel } of contextTests) {
|
||||
// Skip testing same model against itself
|
||||
if (sourceModel && sourceModel === model.id) {
|
||||
console.log(`[${label} → ${model.provider}] Skipping same-model test`);
|
||||
skippedCount++;
|
||||
continue;
|
||||
}
|
||||
const success = await testProviderHandoff(model, label, context);
|
||||
if (success) successCount++;
|
||||
}
|
||||
|
||||
const totalTests = contextTests.length - skippedCount;
|
||||
console.log(`\nOpenAI Completions success rate: ${successCount}/${totalTests} (${skippedCount} skipped)\n`);
|
||||
|
||||
// All non-skipped handoffs should succeed
|
||||
expect(successCount).toBe(totalTests);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider Handoff", () => {
|
||||
const model = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should handle contexts from all providers", async () => {
|
||||
console.log("\nTesting OpenAI Responses with pre-built contexts:\n");
|
||||
|
||||
const contextTests = [
|
||||
{ label: "Anthropic-style", context: providerContexts.anthropic, sourceModel: "claude-3-5-haiku-20241022" },
|
||||
{ label: "Google-style", context: providerContexts.google, sourceModel: "gemini-2.5-flash" },
|
||||
{ label: "OpenAI-Completions", context: providerContexts.openaiCompletions, sourceModel: "gpt-4o-mini" },
|
||||
{ label: "OpenAI-Responses", context: providerContexts.openaiResponses, sourceModel: "gpt-5-mini" },
|
||||
{ label: "Aborted", context: providerContexts.aborted, sourceModel: null },
|
||||
];
|
||||
|
||||
let successCount = 0;
|
||||
let skippedCount = 0;
|
||||
|
||||
for (const { label, context, sourceModel } of contextTests) {
|
||||
// Skip testing same model against itself
|
||||
if (sourceModel && sourceModel === model.id) {
|
||||
console.log(`[${label} → ${model.provider}] Skipping same-model test`);
|
||||
skippedCount++;
|
||||
continue;
|
||||
}
|
||||
const success = await testProviderHandoff(model, label, context);
|
||||
if (success) successCount++;
|
||||
}
|
||||
|
||||
const totalTests = contextTests.length - skippedCount;
|
||||
console.log(`\nOpenAI Responses success rate: ${successCount}/${totalTests} (${skippedCount} skipped)\n`);
|
||||
|
||||
// All non-skipped handoffs should succeed
|
||||
expect(successCount).toBe(totalTests);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider Handoff", () => {
|
||||
const model = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("should handle contexts from all providers", async () => {
|
||||
console.log("\nTesting Mistral with pre-built contexts:\n");
|
||||
|
||||
const contextTests = [
|
||||
{ label: "Anthropic-style", context: providerContexts.anthropic, sourceModel: "claude-3-5-haiku-20241022" },
|
||||
{ label: "Google-style", context: providerContexts.google, sourceModel: "gemini-2.5-flash" },
|
||||
{ label: "OpenAI-Completions", context: providerContexts.openaiCompletions, sourceModel: "gpt-4o-mini" },
|
||||
{ label: "OpenAI-Responses", context: providerContexts.openaiResponses, sourceModel: "gpt-5-mini" },
|
||||
{ label: "Aborted", context: providerContexts.aborted, sourceModel: null },
|
||||
];
|
||||
|
||||
let successCount = 0;
|
||||
const totalTests = contextTests.length;
|
||||
|
||||
for (const { label, context } of contextTests) {
|
||||
const success = await testProviderHandoff(model, label, context);
|
||||
if (success) successCount++;
|
||||
}
|
||||
|
||||
console.log(`\nMistral success rate: ${successCount}/${totalTests}\n`);
|
||||
|
||||
// All handoffs should succeed
|
||||
expect(successCount).toBe(totalTests);
|
||||
}, 60000);
|
||||
});
|
||||
});
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,394 +0,0 @@
|
||||
import { join } from "node:path";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import type { Api, Context, Model, Tool, ToolResultMessage } from "../src/index";
|
||||
import { complete, getModel } from "../src/index";
|
||||
import type { OptionsForApi } from "../src/types";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("anthropic"),
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
/**
|
||||
* Test that tool results containing only images work correctly across all providers.
|
||||
* This verifies that:
|
||||
* 1. Tool results can contain image content blocks
|
||||
* 2. Providers correctly pass images from tool results to the LLM
|
||||
* 3. The LLM can see and describe images returned by tools
|
||||
*/
|
||||
async function handleToolWithImageResult<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
// Check if the model supports images
|
||||
if (!model.input.includes("image")) {
|
||||
console.log(`Skipping tool image result test - model ${model.id} doesn't support images`);
|
||||
return;
|
||||
}
|
||||
|
||||
// Read the test image
|
||||
const imagePath = join(__dirname, "data", "red-circle.png");
|
||||
const imageBuffer = await Bun.file(imagePath).arrayBuffer();
|
||||
const base64Image = Buffer.from(imageBuffer).toString("base64");
|
||||
|
||||
// Define a tool that returns only an image (no text)
|
||||
const getImageSchema = Type.Object({});
|
||||
const getImageTool: Tool<typeof getImageSchema> = {
|
||||
name: "get_circle",
|
||||
description: "Returns a circle image for visualization",
|
||||
parameters: getImageSchema,
|
||||
};
|
||||
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant that uses tools when asked.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Call the get_circle tool to get an image, and describe what you see, shapes, colors, etc.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [getImageTool],
|
||||
};
|
||||
|
||||
// First request - LLM should call the tool
|
||||
const firstResponse = await complete(model, context, options);
|
||||
expect(firstResponse.stopReason).toBe("toolUse");
|
||||
|
||||
// Find the tool call
|
||||
const toolCall = firstResponse.content.find((b) => b.type === "toolCall");
|
||||
expect(toolCall).toBeTruthy();
|
||||
if (!toolCall || toolCall.type !== "toolCall") {
|
||||
throw new Error("Expected tool call");
|
||||
}
|
||||
expect(toolCall.name).toBe("get_circle");
|
||||
|
||||
// Add the tool call to context
|
||||
context.messages.push(firstResponse);
|
||||
|
||||
// Create tool result with ONLY an image (no text)
|
||||
const toolResult: ToolResultMessage = {
|
||||
role: "toolResult",
|
||||
toolCallId: toolCall.id,
|
||||
toolName: toolCall.name,
|
||||
content: [
|
||||
{
|
||||
type: "image",
|
||||
data: base64Image,
|
||||
mimeType: "image/png",
|
||||
},
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
context.messages.push(toolResult);
|
||||
|
||||
// Second request - LLM should describe the image from the tool result
|
||||
const secondResponse = await complete(model, context, options);
|
||||
expect(secondResponse.stopReason).toBe("stop");
|
||||
expect(secondResponse.errorMessage).toBeFalsy();
|
||||
|
||||
// Verify the LLM can see and describe the image
|
||||
const textContent = secondResponse.content.find((b) => b.type === "text");
|
||||
expect(textContent).toBeTruthy();
|
||||
if (textContent && textContent.type === "text") {
|
||||
const lowerContent = textContent.text.toLowerCase();
|
||||
// Should mention red and circle since that's what the image shows
|
||||
expect(lowerContent).toContain("red");
|
||||
expect(lowerContent).toContain("circle");
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Test that tool results containing both text and images work correctly across all providers.
|
||||
* This verifies that:
|
||||
* 1. Tool results can contain mixed content blocks (text + images)
|
||||
* 2. Providers correctly pass both text and images from tool results to the LLM
|
||||
* 3. The LLM can see both the text and images in tool results
|
||||
*/
|
||||
async function handleToolWithTextAndImageResult<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
// Check if the model supports images
|
||||
if (!model.input.includes("image")) {
|
||||
console.log(`Skipping tool text+image result test - model ${model.id} doesn't support images`);
|
||||
return;
|
||||
}
|
||||
|
||||
// Read the test image
|
||||
const imagePath = join(__dirname, "data", "red-circle.png");
|
||||
const imageBuffer = await Bun.file(imagePath).arrayBuffer();
|
||||
const base64Image = Buffer.from(imageBuffer).toString("base64");
|
||||
|
||||
// Define a tool that returns both text and an image
|
||||
const getImageSchema = Type.Object({});
|
||||
const getImageTool: Tool<typeof getImageSchema> = {
|
||||
name: "get_circle_with_description",
|
||||
description: "Returns a circle image with a text description",
|
||||
parameters: getImageSchema,
|
||||
};
|
||||
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant that uses tools when asked.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content:
|
||||
"Use the get_circle_with_description tool and tell me what you learned. Also say what color the shape is.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [getImageTool],
|
||||
};
|
||||
|
||||
// First request - LLM should call the tool
|
||||
const firstResponse = await complete(model, context, options);
|
||||
expect(firstResponse.stopReason).toBe("toolUse");
|
||||
|
||||
// Find the tool call
|
||||
const toolCall = firstResponse.content.find((b) => b.type === "toolCall");
|
||||
expect(toolCall).toBeTruthy();
|
||||
if (!toolCall || toolCall.type !== "toolCall") {
|
||||
throw new Error("Expected tool call");
|
||||
}
|
||||
expect(toolCall.name).toBe("get_circle_with_description");
|
||||
|
||||
// Add the tool call to context
|
||||
context.messages.push(firstResponse);
|
||||
|
||||
// Create tool result with BOTH text and image
|
||||
const toolResult: ToolResultMessage = {
|
||||
role: "toolResult",
|
||||
toolCallId: toolCall.id,
|
||||
toolName: toolCall.name,
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: "This is a geometric shape with specific properties: it has a diameter of 100 pixels.",
|
||||
},
|
||||
{
|
||||
type: "image",
|
||||
data: base64Image,
|
||||
mimeType: "image/png",
|
||||
},
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
context.messages.push(toolResult);
|
||||
|
||||
// Second request - LLM should describe both the text and image from the tool result
|
||||
const secondResponse = await complete(model, context, options);
|
||||
expect(secondResponse.stopReason).toBe("stop");
|
||||
expect(secondResponse.errorMessage).toBeFalsy();
|
||||
|
||||
// Verify the LLM can see both text and image
|
||||
const textContent = secondResponse.content.find((b) => b.type === "text");
|
||||
expect(textContent).toBeTruthy();
|
||||
if (textContent && textContent.type === "text") {
|
||||
const lowerContent = textContent.text.toLowerCase();
|
||||
// Should mention details from the text (diameter/pixels)
|
||||
expect(lowerContent.match(/diameter|100|pixel/)).toBeTruthy();
|
||||
// Should also mention the visual properties (red and circle)
|
||||
expect(lowerContent).toContain("red");
|
||||
expect(lowerContent).toContain("circle");
|
||||
}
|
||||
}
|
||||
|
||||
describe("Tool Results with Images", () => {
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider (gemini-2.5-flash)", () => {
|
||||
const llm = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should handle tool result with only image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithImageResult(llm);
|
||||
});
|
||||
|
||||
it("should handle tool result with text and image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithTextAndImageResult(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider (gpt-4o-mini)", () => {
|
||||
const llm: Model<"openai-completions"> = { ...getModel("openai", "gpt-4o-mini"), api: "openai-completions" };
|
||||
|
||||
it("should handle tool result with only image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithImageResult(llm);
|
||||
});
|
||||
|
||||
it("should handle tool result with text and image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithTextAndImageResult(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider (gpt-5-mini)", () => {
|
||||
const llm = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should handle tool result with only image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithImageResult(llm);
|
||||
});
|
||||
|
||||
it("should handle tool result with text and image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithTextAndImageResult(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider (claude-haiku-4-5)", () => {
|
||||
const model = getModel("anthropic", "claude-haiku-4-5");
|
||||
|
||||
it("should handle tool result with only image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithImageResult(model);
|
||||
});
|
||||
|
||||
it("should handle tool result with text and image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithTextAndImageResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENROUTER_API_KEY)("OpenRouter Provider (glm-4.5v)", () => {
|
||||
const llm = getModel("openrouter", "z-ai/glm-4.5v");
|
||||
|
||||
it("should handle tool result with only image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithImageResult(llm);
|
||||
});
|
||||
|
||||
it("should handle tool result with text and image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithTextAndImageResult(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider (pixtral-12b)", () => {
|
||||
const llm = getModel("mistral", "pixtral-12b");
|
||||
|
||||
it("should handle tool result with only image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithImageResult(llm);
|
||||
});
|
||||
|
||||
it("should handle tool result with text and image", { retry: 3, timeout: 30000 }, async () => {
|
||||
await handleToolWithTextAndImageResult(llm);
|
||||
});
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OAuth-based providers (credentials from ~/.omp/agent/auth.json)
|
||||
// =========================================================================
|
||||
|
||||
describe("Anthropic OAuth Provider (claude-sonnet-4-5)", () => {
|
||||
const model = getModel("anthropic", "claude-sonnet-4-5");
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should handle tool result with only image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await handleToolWithImageResult(model, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should handle tool result with text and image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await handleToolWithTextAndImageResult(model, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("GitHub Copilot Provider", () => {
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle tool result with only image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await handleToolWithImageResult(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle tool result with text and image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await handleToolWithTextAndImageResult(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle tool result with only image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await handleToolWithImageResult(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle tool result with text and image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await handleToolWithTextAndImageResult(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Gemini CLI Provider", () => {
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle tool result with only image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await handleToolWithImageResult(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle tool result with text and image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await handleToolWithTextAndImageResult(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider", () => {
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle tool result with only image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await handleToolWithImageResult(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle tool result with text and image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await handleToolWithTextAndImageResult(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
/** These two don't work, the model simply won't call the tool, works in pi
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle tool result with only image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await handleToolWithImageResult(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle tool result with text and image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await handleToolWithTextAndImageResult(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);**/
|
||||
|
||||
// Note: gpt-oss-120b-medium does not support images, so not tested here
|
||||
});
|
||||
});
|
||||
@@ -1,86 +0,0 @@
|
||||
/**
|
||||
* Test helper for resolving API keys from ~/.omp/agent/auth.json
|
||||
*
|
||||
* Supports both API key and OAuth credentials.
|
||||
* OAuth tokens are automatically refreshed if expired and saved back to auth.json.
|
||||
*/
|
||||
|
||||
import { homedir } from "node:os";
|
||||
import { dirname, join } from "node:path";
|
||||
import { getOAuthApiKey } from "../src/utils/oauth/index";
|
||||
import type { OAuthCredentials, OAuthProvider } from "../src/utils/oauth/types";
|
||||
|
||||
const AUTH_PATH = join(homedir(), ".omp", "agent", "auth.json");
|
||||
|
||||
type ApiKeyCredential = {
|
||||
type: "api_key";
|
||||
key: string;
|
||||
};
|
||||
|
||||
type OAuthCredentialEntry = {
|
||||
type: "oauth";
|
||||
} & OAuthCredentials;
|
||||
|
||||
type AuthCredential = ApiKeyCredential | OAuthCredentialEntry;
|
||||
|
||||
type AuthStorage = Record<string, AuthCredential>;
|
||||
|
||||
async function loadAuthStorage(): Promise<AuthStorage> {
|
||||
const file = Bun.file(AUTH_PATH);
|
||||
if (!(await file.exists())) {
|
||||
return {};
|
||||
}
|
||||
try {
|
||||
return await file.json();
|
||||
} catch {
|
||||
return {};
|
||||
}
|
||||
}
|
||||
|
||||
async function saveAuthStorage(storage: AuthStorage): Promise<void> {
|
||||
const configDir = dirname(AUTH_PATH);
|
||||
await Bun.write(join(configDir, ".keep"), "");
|
||||
await Bun.write(AUTH_PATH, JSON.stringify(storage, null, 2));
|
||||
await Bun.spawn(["chmod", "600", AUTH_PATH]).exited;
|
||||
}
|
||||
|
||||
/**
|
||||
* Resolve API key for a provider from ~/.omp/agent/auth.json
|
||||
*
|
||||
* For API key credentials, returns the key directly.
|
||||
* For OAuth credentials, returns the access token (refreshing if expired and saving back).
|
||||
*
|
||||
* For google-gemini-cli and google-antigravity, returns JSON-encoded { token, projectId }
|
||||
*/
|
||||
export async function resolveApiKey(provider: string): Promise<string | undefined> {
|
||||
const storage = await loadAuthStorage();
|
||||
const entry = storage[provider];
|
||||
|
||||
if (!entry) return undefined;
|
||||
|
||||
if (entry.type === "api_key") {
|
||||
return entry.key;
|
||||
}
|
||||
|
||||
if (entry.type === "oauth") {
|
||||
// Build OAuthCredentials record for getOAuthApiKey
|
||||
const oauthCredentials: Record<string, OAuthCredentials> = {};
|
||||
for (const [key, value] of Object.entries(storage)) {
|
||||
if (value.type === "oauth") {
|
||||
const { type: _, ...creds } = value;
|
||||
oauthCredentials[key] = creds;
|
||||
}
|
||||
}
|
||||
|
||||
const result = await getOAuthApiKey(provider as OAuthProvider, oauthCredentials);
|
||||
if (!result) return undefined;
|
||||
|
||||
// Save refreshed credentials back to auth.json
|
||||
storage[provider] = { type: "oauth", ...result.newCredentials };
|
||||
await saveAuthStorage(storage);
|
||||
|
||||
return result.apiKey;
|
||||
}
|
||||
|
||||
return undefined;
|
||||
}
|
||||
@@ -1,132 +0,0 @@
|
||||
import { mkdtempSync } from "node:fs";
|
||||
import { tmpdir } from "node:os";
|
||||
import { join } from "node:path";
|
||||
import { afterEach, describe, expect, it, vi } from "vitest";
|
||||
import { streamOpenAICodexResponses } from "../src/providers/openai-codex-responses";
|
||||
import type { Context, Model } from "../src/types";
|
||||
|
||||
const originalFetch = global.fetch;
|
||||
const originalAgentDir = process.env.PI_CODING_AGENT_DIR;
|
||||
|
||||
afterEach(() => {
|
||||
global.fetch = originalFetch;
|
||||
if (originalAgentDir === undefined) {
|
||||
delete process.env.PI_CODING_AGENT_DIR;
|
||||
} else {
|
||||
process.env.PI_CODING_AGENT_DIR = originalAgentDir;
|
||||
}
|
||||
vi.restoreAllMocks();
|
||||
});
|
||||
|
||||
describe("openai-codex streaming", () => {
|
||||
it("streams SSE responses into AssistantMessageEventStream", async () => {
|
||||
const tempDir = mkdtempSync(join(tmpdir(), "pi-codex-stream-"));
|
||||
process.env.PI_CODING_AGENT_DIR = tempDir;
|
||||
|
||||
const payload = Buffer.from(
|
||||
JSON.stringify({ "https://api.openai.com/auth": { chatgpt_account_id: "acc_test" } }),
|
||||
"utf8",
|
||||
).toString("base64");
|
||||
const token = `aaa.${payload}.bbb`;
|
||||
|
||||
const sse = `${[
|
||||
`data: ${JSON.stringify({
|
||||
type: "response.output_item.added",
|
||||
item: { type: "message", id: "msg_1", role: "assistant", status: "in_progress", content: [] },
|
||||
})}`,
|
||||
`data: ${JSON.stringify({ type: "response.content_part.added", part: { type: "output_text", text: "" } })}`,
|
||||
`data: ${JSON.stringify({ type: "response.output_text.delta", delta: "Hello" })}`,
|
||||
`data: ${JSON.stringify({
|
||||
type: "response.output_item.done",
|
||||
item: {
|
||||
type: "message",
|
||||
id: "msg_1",
|
||||
role: "assistant",
|
||||
status: "completed",
|
||||
content: [{ type: "output_text", text: "Hello" }],
|
||||
},
|
||||
})}`,
|
||||
`data: ${JSON.stringify({
|
||||
type: "response.completed",
|
||||
response: {
|
||||
status: "completed",
|
||||
usage: {
|
||||
input_tokens: 5,
|
||||
output_tokens: 3,
|
||||
total_tokens: 8,
|
||||
input_tokens_details: { cached_tokens: 0 },
|
||||
},
|
||||
},
|
||||
})}`,
|
||||
].join("\n\n")}\n\n`;
|
||||
|
||||
const encoder = new TextEncoder();
|
||||
const stream = new ReadableStream<Uint8Array>({
|
||||
start(controller) {
|
||||
controller.enqueue(encoder.encode(sse));
|
||||
controller.close();
|
||||
},
|
||||
});
|
||||
|
||||
const fetchMock = vi.fn(async (input: string | URL, init?: RequestInit) => {
|
||||
const url = typeof input === "string" ? input : input.toString();
|
||||
if (url === "https://api.github.com/repos/openai/codex/releases/latest") {
|
||||
return new Response(JSON.stringify({ tag_name: "rust-v0.0.0" }), { status: 200 });
|
||||
}
|
||||
if (url.startsWith("https://raw.githubusercontent.com/openai/codex/")) {
|
||||
return new Response("PROMPT", { status: 200, headers: { etag: '"etag"' } });
|
||||
}
|
||||
if (url === "https://chatgpt.com/backend-api/codex/responses") {
|
||||
const headers = init?.headers instanceof Headers ? init.headers : undefined;
|
||||
expect(headers?.get("Authorization")).toBe(`Bearer ${token}`);
|
||||
expect(headers?.get("chatgpt-account-id")).toBe("acc_test");
|
||||
expect(headers?.get("OpenAI-Beta")).toBe("responses=experimental");
|
||||
expect(headers?.get("originator")).toBe("codex_cli_rs");
|
||||
expect(headers?.get("accept")).toBe("text/event-stream");
|
||||
expect(headers?.has("x-api-key")).toBe(false);
|
||||
return new Response(stream, {
|
||||
status: 200,
|
||||
headers: { "content-type": "text/event-stream" },
|
||||
});
|
||||
}
|
||||
return new Response("not found", { status: 404 });
|
||||
});
|
||||
|
||||
global.fetch = fetchMock as unknown as typeof fetch;
|
||||
|
||||
const model: Model<"openai-codex-responses"> = {
|
||||
id: "gpt-5.1-codex",
|
||||
name: "GPT-5.1 Codex",
|
||||
api: "openai-codex-responses",
|
||||
provider: "openai-codex",
|
||||
baseUrl: "https://chatgpt.com/backend-api",
|
||||
reasoning: true,
|
||||
input: ["text"],
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow: 400000,
|
||||
maxTokens: 128000,
|
||||
};
|
||||
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages: [{ role: "user", content: "Say hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const streamResult = streamOpenAICodexResponses(model, context, { apiKey: token });
|
||||
let sawTextDelta = false;
|
||||
let sawDone = false;
|
||||
|
||||
for await (const event of streamResult) {
|
||||
if (event.type === "text_delta") {
|
||||
sawTextDelta = true;
|
||||
}
|
||||
if (event.type === "done") {
|
||||
sawDone = true;
|
||||
expect(event.message.content.find((c) => c.type === "text")?.text).toBe("Hello");
|
||||
}
|
||||
}
|
||||
|
||||
expect(sawTextDelta).toBe(true);
|
||||
expect(sawDone).toBe(true);
|
||||
});
|
||||
});
|
||||
@@ -1,162 +0,0 @@
|
||||
import { mkdtempSync, readFileSync, writeFileSync } from "node:fs";
|
||||
import { tmpdir } from "node:os";
|
||||
import { join } from "node:path";
|
||||
import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
|
||||
import { getCodexInstructions } from "../src/providers/openai-codex/prompts/codex";
|
||||
import FALLBACK_PROMPT from "../src/providers/openai-codex/prompts/codex-instructions.md" with { type: "text" };
|
||||
import { CODEX_PI_BRIDGE } from "../src/providers/openai-codex/prompts/pi-codex-bridge";
|
||||
import {
|
||||
normalizeModel,
|
||||
type RequestBody,
|
||||
transformRequestBody,
|
||||
} from "../src/providers/openai-codex/request-transformer";
|
||||
import { parseCodexError } from "../src/providers/openai-codex/response-handler";
|
||||
|
||||
const DEFAULT_PROMPT_PREFIX =
|
||||
"You are an expert coding assistant. You help users with coding tasks by reading files, executing commands";
|
||||
|
||||
describe("openai-codex request transformer", () => {
|
||||
it("filters item_reference, strips ids, and inserts bridge message", async () => {
|
||||
const body: RequestBody = {
|
||||
model: "gpt-5.1-codex",
|
||||
input: [
|
||||
{
|
||||
type: "message",
|
||||
role: "developer",
|
||||
id: "sys-1",
|
||||
content: [{ type: "input_text", text: `${DEFAULT_PROMPT_PREFIX}...` }],
|
||||
},
|
||||
{
|
||||
type: "message",
|
||||
role: "user",
|
||||
id: "user-1",
|
||||
content: [{ type: "input_text", text: "hello" }],
|
||||
},
|
||||
{ type: "item_reference", id: "ref-1" },
|
||||
{ type: "function_call_output", call_id: "missing", name: "tool", output: "result" },
|
||||
],
|
||||
tools: [{ type: "function", name: "tool", description: "", parameters: {} }],
|
||||
};
|
||||
|
||||
const transformed = await transformRequestBody(body, "CODEX_INSTRUCTIONS", {}, true);
|
||||
|
||||
expect(transformed.store).toBe(false);
|
||||
expect(transformed.stream).toBe(true);
|
||||
expect(transformed.instructions).toBe("CODEX_INSTRUCTIONS");
|
||||
expect(transformed.include).toEqual(["reasoning.encrypted_content"]);
|
||||
|
||||
const input = transformed.input || [];
|
||||
expect(input.some((item) => item.type === "item_reference")).toBe(false);
|
||||
expect(input.some((item) => "id" in item)).toBe(false);
|
||||
expect(input[0]?.type).toBe("message");
|
||||
expect(input[0]?.content).toEqual([{ type: "input_text", text: CODEX_PI_BRIDGE }]);
|
||||
|
||||
const orphaned = input.find((item) => item.type === "message" && item.role === "assistant");
|
||||
expect(orphaned?.content).toMatch(/Previous tool result/);
|
||||
});
|
||||
});
|
||||
|
||||
describe("openai-codex model normalization", () => {
|
||||
it("maps space-separated codex-mini names to codex-mini-latest", () => {
|
||||
expect(normalizeModel("gpt 5 codex mini")).toBe("codex-mini-latest");
|
||||
});
|
||||
});
|
||||
|
||||
describe("openai-codex error parsing", () => {
|
||||
it("produces friendly usage-limit messages and rate limits", async () => {
|
||||
const resetAt = Math.floor(Date.now() / 1000) + 600;
|
||||
const response = new Response(
|
||||
JSON.stringify({
|
||||
error: { code: "usage_limit_reached", plan_type: "Plus", resets_at: resetAt },
|
||||
}),
|
||||
{
|
||||
status: 429,
|
||||
headers: {
|
||||
"x-codex-primary-used-percent": "99",
|
||||
"x-codex-primary-window-minutes": "60",
|
||||
"x-codex-primary-reset-at": String(resetAt),
|
||||
},
|
||||
},
|
||||
);
|
||||
|
||||
const info = await parseCodexError(response);
|
||||
expect(info.friendlyMessage?.toLowerCase()).toContain("usage limit");
|
||||
expect(info.rateLimits?.primary?.used_percent).toBe(99);
|
||||
});
|
||||
});
|
||||
|
||||
describe("openai-codex prompt caching", () => {
|
||||
const originalFetch = global.fetch;
|
||||
const originalAgentDir = process.env.PI_CODING_AGENT_DIR;
|
||||
|
||||
beforeEach(() => {
|
||||
vi.restoreAllMocks();
|
||||
});
|
||||
|
||||
afterEach(() => {
|
||||
global.fetch = originalFetch;
|
||||
if (originalAgentDir === undefined) {
|
||||
delete process.env.PI_CODING_AGENT_DIR;
|
||||
} else {
|
||||
process.env.PI_CODING_AGENT_DIR = originalAgentDir;
|
||||
}
|
||||
});
|
||||
|
||||
it("caches prompts with etag and reuses cache", async () => {
|
||||
const tempDir = mkdtempSync(join(tmpdir(), "pi-codex-"));
|
||||
process.env.PI_CODING_AGENT_DIR = tempDir;
|
||||
|
||||
const tag = "rust-v0.0.0";
|
||||
const promptText = "PROMPT_CONTENT";
|
||||
const etag = '"etag-123"';
|
||||
|
||||
const fetchMock = vi.fn(async (input: string | URL, init?: RequestInit) => {
|
||||
const url = typeof input === "string" ? input : input.toString();
|
||||
if (url === "https://api.github.com/repos/openai/codex/releases/latest") {
|
||||
return new Response(JSON.stringify({ tag_name: tag }), { status: 200 });
|
||||
}
|
||||
if (url.startsWith("https://raw.githubusercontent.com/openai/codex/")) {
|
||||
const headerValue =
|
||||
init?.headers && typeof init.headers === "object" && "If-None-Match" in init.headers
|
||||
? String((init.headers as Record<string, string>)["If-None-Match"])
|
||||
: undefined;
|
||||
if (headerValue === etag) {
|
||||
return new Response("", { status: 304, headers: { etag } });
|
||||
}
|
||||
return new Response(promptText, { status: 200, headers: { etag } });
|
||||
}
|
||||
return new Response("not found", { status: 404 });
|
||||
});
|
||||
|
||||
global.fetch = fetchMock as unknown as typeof fetch;
|
||||
|
||||
const first = await getCodexInstructions("gpt-5.1-codex");
|
||||
expect(first).toBe(promptText);
|
||||
|
||||
const metaPath = join(tempDir, "cache", "openai-codex", "codex-instructions-meta.json");
|
||||
const meta = JSON.parse(readFileSync(metaPath, "utf-8")) as { etag: string; tag: string; lastChecked: number };
|
||||
writeFileSync(metaPath, JSON.stringify({ ...meta, lastChecked: 0 }), "utf-8");
|
||||
|
||||
const second = await getCodexInstructions("gpt-5.1-codex");
|
||||
expect(second).toBe(promptText);
|
||||
expect(fetchMock).toHaveBeenCalled();
|
||||
const rawCalls = fetchMock.mock.calls.filter((call) =>
|
||||
String(call[0]).startsWith("https://raw.githubusercontent.com/openai/codex/"),
|
||||
);
|
||||
expect(rawCalls.length).toBeGreaterThan(0);
|
||||
});
|
||||
|
||||
it("falls back to bundled instructions when cache and network are unavailable", async () => {
|
||||
const tempDir = mkdtempSync(join(tmpdir(), "pi-codex-"));
|
||||
process.env.PI_CODING_AGENT_DIR = tempDir;
|
||||
|
||||
const fetchMock = vi.fn(async () => {
|
||||
throw new Error("network down");
|
||||
});
|
||||
|
||||
global.fetch = fetchMock as unknown as typeof fetch;
|
||||
|
||||
const instructions = await getCodexInstructions("gpt-5.1-codex");
|
||||
expect(instructions).toBe(FALLBACK_PROMPT);
|
||||
});
|
||||
});
|
||||
@@ -1,928 +0,0 @@
|
||||
import { join } from "node:path";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import type { Subprocess } from "bun";
|
||||
import { afterAll, beforeAll, describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete, stream } from "../src/stream";
|
||||
import type { Api, Context, ImageContent, Model, OptionsForApi, Tool, ToolResultMessage } from "../src/types";
|
||||
import { StringEnum } from "../src/utils/typebox-helpers";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
const dir = import.meta.dir;
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("anthropic"),
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
// Calculator tool definition (same as examples)
|
||||
// Note: Using StringEnum helper because Google's API doesn't support anyOf/const patterns
|
||||
// that Type.Enum generates. Google requires { type: "string", enum: [...] } format.
|
||||
const calculatorSchema = Type.Object({
|
||||
a: Type.Number({ description: "First number" }),
|
||||
b: Type.Number({ description: "Second number" }),
|
||||
operation: StringEnum(["add", "subtract", "multiply", "divide"], {
|
||||
description: "The operation to perform. One of 'add', 'subtract', 'multiply', 'divide'.",
|
||||
}),
|
||||
});
|
||||
|
||||
const calculatorTool: Tool<typeof calculatorSchema> = {
|
||||
name: "calculator",
|
||||
description: "Perform basic arithmetic operations",
|
||||
parameters: calculatorSchema,
|
||||
};
|
||||
|
||||
async function basicTextGeneration<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant. Be concise.",
|
||||
messages: [{ role: "user", content: "Reply with exactly: 'Hello test successful'", timestamp: Date.now() }],
|
||||
};
|
||||
const response = await complete(model, context, options);
|
||||
|
||||
expect(response.role).toBe("assistant");
|
||||
expect(response.content).toBeTruthy();
|
||||
expect(response.usage.input + response.usage.cacheRead).toBeGreaterThan(0);
|
||||
expect(response.usage.output).toBeGreaterThan(0);
|
||||
expect(response.errorMessage).toBeFalsy();
|
||||
expect(response.content.map((b) => (b.type === "text" ? b.text : "")).join("")).toContain("Hello test successful");
|
||||
|
||||
context.messages.push(response);
|
||||
context.messages.push({ role: "user", content: "Now say 'Goodbye test successful'", timestamp: Date.now() });
|
||||
|
||||
const secondResponse = await complete(model, context, options);
|
||||
|
||||
expect(secondResponse.role).toBe("assistant");
|
||||
expect(secondResponse.content).toBeTruthy();
|
||||
expect(secondResponse.usage.input + secondResponse.usage.cacheRead).toBeGreaterThan(0);
|
||||
expect(secondResponse.usage.output).toBeGreaterThan(0);
|
||||
expect(secondResponse.errorMessage).toBeFalsy();
|
||||
expect(secondResponse.content.map((b) => (b.type === "text" ? b.text : "")).join("")).toContain(
|
||||
"Goodbye test successful",
|
||||
);
|
||||
}
|
||||
|
||||
async function handleToolCall<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant that uses tools when asked.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Calculate 15 + 27 using the calculator tool.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [calculatorTool],
|
||||
};
|
||||
|
||||
const s = await stream(model, context, options);
|
||||
let hasToolStart = false;
|
||||
let hasToolDelta = false;
|
||||
let hasToolEnd = false;
|
||||
let accumulatedToolArgs = "";
|
||||
let index = 0;
|
||||
for await (const event of s) {
|
||||
if (event.type === "toolcall_start") {
|
||||
hasToolStart = true;
|
||||
const toolCall = event.partial.content[event.contentIndex];
|
||||
index = event.contentIndex;
|
||||
expect(toolCall.type).toBe("toolCall");
|
||||
if (toolCall.type === "toolCall") {
|
||||
expect(toolCall.name).toBe("calculator");
|
||||
expect(toolCall.id).toBeTruthy();
|
||||
}
|
||||
}
|
||||
if (event.type === "toolcall_delta") {
|
||||
hasToolDelta = true;
|
||||
const toolCall = event.partial.content[event.contentIndex];
|
||||
expect(event.contentIndex).toBe(index);
|
||||
expect(toolCall.type).toBe("toolCall");
|
||||
if (toolCall.type === "toolCall") {
|
||||
expect(toolCall.name).toBe("calculator");
|
||||
accumulatedToolArgs += event.delta;
|
||||
// Check that we have a parsed arguments object during streaming
|
||||
expect(toolCall.arguments).toBeDefined();
|
||||
expect(typeof toolCall.arguments).toBe("object");
|
||||
// The arguments should be partially populated as we stream
|
||||
// At minimum it should be an empty object, never undefined
|
||||
expect(toolCall.arguments).not.toBeNull();
|
||||
}
|
||||
}
|
||||
if (event.type === "toolcall_end") {
|
||||
hasToolEnd = true;
|
||||
const toolCall = event.partial.content[event.contentIndex];
|
||||
expect(event.contentIndex).toBe(index);
|
||||
expect(toolCall.type).toBe("toolCall");
|
||||
if (toolCall.type === "toolCall") {
|
||||
expect(toolCall.name).toBe("calculator");
|
||||
JSON.parse(accumulatedToolArgs);
|
||||
expect(toolCall.arguments).not.toBeUndefined();
|
||||
expect((toolCall.arguments as any).a).toBe(15);
|
||||
expect((toolCall.arguments as any).b).toBe(27);
|
||||
expect((toolCall.arguments as any).operation).oneOf(["add", "subtract", "multiply", "divide"]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
expect(hasToolStart).toBe(true);
|
||||
expect(hasToolDelta).toBe(true);
|
||||
expect(hasToolEnd).toBe(true);
|
||||
|
||||
const response = await s.result();
|
||||
expect(response.stopReason).toBe("toolUse");
|
||||
expect(response.content.some((b) => b.type === "toolCall")).toBeTruthy();
|
||||
const toolCall = response.content.find((b) => b.type === "toolCall");
|
||||
if (toolCall && toolCall.type === "toolCall") {
|
||||
expect(toolCall.name).toBe("calculator");
|
||||
expect(toolCall.id).toBeTruthy();
|
||||
} else {
|
||||
throw new Error("No tool call found in response");
|
||||
}
|
||||
}
|
||||
|
||||
async function handleStreaming<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
let textStarted = false;
|
||||
let textChunks = "";
|
||||
let textCompleted = false;
|
||||
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Count from 1 to 3", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const s = stream(model, context, options);
|
||||
|
||||
for await (const event of s) {
|
||||
if (event.type === "text_start") {
|
||||
textStarted = true;
|
||||
} else if (event.type === "text_delta") {
|
||||
textChunks += event.delta;
|
||||
} else if (event.type === "text_end") {
|
||||
textCompleted = true;
|
||||
}
|
||||
}
|
||||
|
||||
const response = await s.result();
|
||||
|
||||
expect(textStarted).toBe(true);
|
||||
expect(textChunks.length).toBeGreaterThan(0);
|
||||
expect(textCompleted).toBe(true);
|
||||
expect(response.content.some((b) => b.type === "text")).toBeTruthy();
|
||||
}
|
||||
|
||||
async function handleThinking<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
let thinkingStarted = false;
|
||||
let thinkingChunks = "";
|
||||
let thinkingCompleted = false;
|
||||
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: `Think long and hard about ${(Math.random() * 255) | 0} + 27. Think step by step. Then output the result.`,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const s = stream(model, context, options);
|
||||
|
||||
for await (const event of s) {
|
||||
if (event.type === "thinking_start") {
|
||||
thinkingStarted = true;
|
||||
} else if (event.type === "thinking_delta") {
|
||||
thinkingChunks += event.delta;
|
||||
} else if (event.type === "thinking_end") {
|
||||
thinkingCompleted = true;
|
||||
}
|
||||
}
|
||||
|
||||
const response = await s.result();
|
||||
|
||||
expect(response.stopReason, `Error: ${response.errorMessage}`).toBe("stop");
|
||||
expect(thinkingStarted).toBe(true);
|
||||
expect(thinkingChunks.length).toBeGreaterThan(0);
|
||||
expect(thinkingCompleted).toBe(true);
|
||||
expect(response.content.some((b) => b.type === "thinking")).toBeTruthy();
|
||||
}
|
||||
|
||||
async function handleImage<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
// Check if the model supports images
|
||||
if (!model.input.includes("image")) {
|
||||
console.log(`Skipping image test - model ${model.id} doesn't support images`);
|
||||
return;
|
||||
}
|
||||
|
||||
// Read the test image
|
||||
const imagePath = join(dir, "data", "red-circle.png");
|
||||
const imageBuffer = await Bun.file(imagePath).arrayBuffer();
|
||||
const base64Image = Buffer.from(imageBuffer).toString("base64");
|
||||
|
||||
const imageContent: ImageContent = {
|
||||
type: "image",
|
||||
data: base64Image,
|
||||
mimeType: "image/png",
|
||||
};
|
||||
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: "What do you see in this image? Please describe the shape (circle, rectangle, square, triangle, ...) and color (red, blue, green, ...). You MUST reply in English.",
|
||||
},
|
||||
imageContent,
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const response = await complete(model, context, options);
|
||||
|
||||
// Check the response mentions red and circle
|
||||
expect(response.content.length > 0).toBeTruthy();
|
||||
const textContent = response.content.find((b) => b.type === "text");
|
||||
if (textContent && textContent.type === "text") {
|
||||
const lowerContent = textContent.text.toLowerCase();
|
||||
expect(lowerContent).toContain("red");
|
||||
expect(lowerContent).toContain("circle");
|
||||
}
|
||||
}
|
||||
|
||||
async function multiTurn<TApi extends Api>(model: Model<TApi>, options?: OptionsForApi<TApi>) {
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant that can use tools to answer questions.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Think about this briefly, then calculate 42 * 17 and 453 + 434 using the calculator tool.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [calculatorTool],
|
||||
};
|
||||
|
||||
// Collect all text content from all assistant responses
|
||||
let allTextContent = "";
|
||||
let hasSeenThinking = false;
|
||||
let hasSeenToolCalls = false;
|
||||
const maxTurns = 5; // Prevent infinite loops
|
||||
|
||||
for (let turn = 0; turn < maxTurns; turn++) {
|
||||
const response = await complete(model, context, options);
|
||||
|
||||
// Add the assistant response to context
|
||||
context.messages.push(response);
|
||||
|
||||
// Process content blocks
|
||||
const results: ToolResultMessage[] = [];
|
||||
for (const block of response.content) {
|
||||
if (block.type === "text") {
|
||||
allTextContent += block.text;
|
||||
} else if (block.type === "thinking") {
|
||||
hasSeenThinking = true;
|
||||
} else if (block.type === "toolCall") {
|
||||
hasSeenToolCalls = true;
|
||||
|
||||
// Process the tool call
|
||||
expect(block.name).toBe("calculator");
|
||||
expect(block.id).toBeTruthy();
|
||||
expect(block.arguments).toBeTruthy();
|
||||
|
||||
const { a, b, operation } = block.arguments;
|
||||
let result: number;
|
||||
switch (operation) {
|
||||
case "add":
|
||||
result = a + b;
|
||||
break;
|
||||
case "multiply":
|
||||
result = a * b;
|
||||
break;
|
||||
default:
|
||||
result = 0;
|
||||
}
|
||||
|
||||
// Add tool result to context
|
||||
results.push({
|
||||
role: "toolResult",
|
||||
toolCallId: block.id,
|
||||
toolName: block.name,
|
||||
content: [{ type: "text", text: `${result}` }],
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
}
|
||||
}
|
||||
context.messages.push(...results);
|
||||
|
||||
// If we got a stop response with text content, we're likely done
|
||||
expect(response.stopReason, `Error: ${response.errorMessage}`).not.toBe("error");
|
||||
if (response.stopReason === "stop") {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Verify we got either thinking content or tool calls (or both)
|
||||
expect(hasSeenThinking || hasSeenToolCalls).toBe(true);
|
||||
|
||||
// The accumulated text should reference both calculations
|
||||
expect(allTextContent).toBeTruthy();
|
||||
expect(allTextContent.includes("714")).toBe(true);
|
||||
expect(allTextContent.includes("887")).toBe(true);
|
||||
}
|
||||
|
||||
describe("Generate E2E Tests", () => {
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Gemini Provider (gemini-2.5-flash)", () => {
|
||||
const llm = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle ", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { thinking: { enabled: true, budgetTokens: 1024 } });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { thinking: { enabled: true, budgetTokens: 2048 } });
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider (gpt-4o-mini)", () => {
|
||||
const llm: Model<"openai-completions"> = { ...getModel("openai", "gpt-4o-mini"), api: "openai-completions" };
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider (gpt-5-mini)", () => {
|
||||
const llm = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle thinking", { retry: 2 }, async () => {
|
||||
await handleThinking(llm, { reasoningEffort: "high" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "high" });
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider (claude-3-5-haiku-20241022)", () => {
|
||||
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(model, { thinkingEnabled: true });
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(model);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(model);
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider (gpt-5-mini)", () => {
|
||||
const model = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(model);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(model);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(model);
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider (grok-code-fast-1 via OpenAI Completions)", () => {
|
||||
const llm = getModel("xai", "grok-code-fast-1");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle thinking mode", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider (gpt-oss-20b via OpenAI Completions)", () => {
|
||||
const llm = getModel("groq", "openai/gpt-oss-20b");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle thinking mode", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider (gpt-oss-120b via OpenAI Completions)", () => {
|
||||
const llm = getModel("cerebras", "gpt-oss-120b");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle thinking mode", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENROUTER_API_KEY)("OpenRouter Provider (glm-4.5v via OpenAI Completions)", () => {
|
||||
const llm = getModel("openrouter", "z-ai/glm-4.5v");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle thinking mode", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 2 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider (glm-4.5-air via OpenAI Completions)", () => {
|
||||
const llm = getModel("zai", "glm-4.5-air");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it.skip("should handle thinking mode", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider (glm-4.5v via OpenAI Completions)", () => {
|
||||
const llm = getModel("zai", "glm-4.5v");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle thinking mode", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)(
|
||||
"Mistral Provider (devstral-medium-latest via OpenAI Completions)",
|
||||
() => {
|
||||
const llm = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle thinking mode", { retry: 3 }, async () => {
|
||||
// FIXME Skip for now, getting a 422 stauts code, need to test with official SDK
|
||||
// const llm = getModel("mistral", "magistral-medium-latest");
|
||||
// await handleThinking(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { reasoningEffort: "medium" });
|
||||
});
|
||||
},
|
||||
);
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider (pixtral-12b with image support)", () => {
|
||||
const llm = getModel("mistral", "pixtral-12b");
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm);
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm);
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm);
|
||||
});
|
||||
|
||||
it("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm);
|
||||
});
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OAuth-based providers (credentials from ~/.omp/agent/auth.json)
|
||||
// Tokens are resolved at module level (see oauthTokens above)
|
||||
// =========================================================================
|
||||
|
||||
describe("Anthropic OAuth Provider (claude-sonnet-4-20250514)", () => {
|
||||
const model = getModel("anthropic", "claude-sonnet-4-20250514");
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(model, { apiKey: anthropicOAuthToken });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(model, { apiKey: anthropicOAuthToken });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(model, { apiKey: anthropicOAuthToken });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle thinking", { retry: 3 }, async () => {
|
||||
await handleThinking(model, { apiKey: anthropicOAuthToken, thinkingEnabled: true });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(model, { apiKey: anthropicOAuthToken, thinkingEnabled: true });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(model, { apiKey: anthropicOAuthToken });
|
||||
});
|
||||
});
|
||||
|
||||
describe("GitHub Copilot Provider (gpt-4o via OpenAI Completions)", () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
|
||||
it.skipIf(!githubCopilotToken)("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm, { apiKey: githubCopilotToken });
|
||||
});
|
||||
|
||||
it.skipIf(!githubCopilotToken)("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm, { apiKey: githubCopilotToken });
|
||||
});
|
||||
|
||||
it.skipIf(!githubCopilotToken)("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm, { apiKey: githubCopilotToken });
|
||||
});
|
||||
|
||||
it.skipIf(!githubCopilotToken)("should handle thinking", { retry: 2 }, async () => {
|
||||
const thinkingModel = getModel("github-copilot", "gpt-5-mini");
|
||||
await handleThinking(thinkingModel, { apiKey: githubCopilotToken, reasoningEffort: "high" });
|
||||
});
|
||||
|
||||
it.skipIf(!githubCopilotToken)("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
const thinkingModel = getModel("github-copilot", "gpt-5-mini");
|
||||
await multiTurn(thinkingModel, { apiKey: githubCopilotToken, reasoningEffort: "high" });
|
||||
});
|
||||
|
||||
it.skipIf(!githubCopilotToken)("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm, { apiKey: githubCopilotToken });
|
||||
});
|
||||
});
|
||||
|
||||
describe("Google Gemini CLI Provider (gemini-2.5-flash)", () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
|
||||
it.skipIf(!geminiCliToken)("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm, { apiKey: geminiCliToken });
|
||||
});
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm, { apiKey: geminiCliToken });
|
||||
});
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm, { apiKey: geminiCliToken });
|
||||
});
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle thinking", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { apiKey: geminiCliToken, thinking: { enabled: true, budgetTokens: 1024 } });
|
||||
});
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { apiKey: geminiCliToken, thinking: { enabled: true, budgetTokens: 2048 } });
|
||||
});
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm, { apiKey: geminiCliToken });
|
||||
});
|
||||
});
|
||||
|
||||
describe("Google Gemini CLI Provider (gemini-3-flash-preview with thinkingLevel)", () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-3-flash-preview");
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle thinking with thinkingLevel", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { apiKey: geminiCliToken, thinking: { enabled: true, level: "LOW" } });
|
||||
});
|
||||
|
||||
it.skipIf(!geminiCliToken)("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { apiKey: geminiCliToken, thinking: { enabled: true, level: "MEDIUM" } });
|
||||
});
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider (gemini-3-flash)", () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
|
||||
it.skipIf(!antigravityToken)("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle thinking with thinkingLevel", { retry: 3 }, async () => {
|
||||
// gemini-3-flash supports all four levels: MINIMAL, LOW, MEDIUM, HIGH
|
||||
await handleThinking(llm, {
|
||||
apiKey: antigravityToken,
|
||||
thinking: { enabled: true, level: "LOW" },
|
||||
});
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { apiKey: antigravityToken, thinking: { enabled: true, level: "MEDIUM" } });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider (gemini-3-pro-high with thinkingLevel)", () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-pro-high");
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle thinking with thinkingLevel HIGH", { retry: 3 }, async () => {
|
||||
// gemini-3-pro only supports LOW/HIGH
|
||||
await handleThinking(llm, {
|
||||
apiKey: antigravityToken,
|
||||
thinking: { enabled: true, level: "HIGH" },
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider (claude-sonnet-4-5)", () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
|
||||
it.skipIf(!antigravityToken)("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle thinking", { retry: 3 }, async () => {
|
||||
// claude-sonnet-4-5 has reasoning: false, use claude-sonnet-4-5-thinking
|
||||
const thinkingModel = getModel("google-antigravity", "claude-sonnet-4-5-thinking");
|
||||
await handleThinking(thinkingModel, {
|
||||
apiKey: antigravityToken,
|
||||
thinking: { enabled: true, budgetTokens: 4096 },
|
||||
});
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
const thinkingModel = getModel("google-antigravity", "claude-sonnet-4-5-thinking");
|
||||
await multiTurn(thinkingModel, { apiKey: antigravityToken, thinking: { enabled: true, budgetTokens: 4096 } });
|
||||
});
|
||||
|
||||
it.skipIf(!antigravityToken)("should handle image input", { retry: 3 }, async () => {
|
||||
await handleImage(llm, { apiKey: antigravityToken });
|
||||
});
|
||||
});
|
||||
|
||||
// Check if ollama is installed
|
||||
const ollamaInstalled = Bun.which("ollama") !== null;
|
||||
|
||||
describe.skipIf(!ollamaInstalled)("Ollama Provider (gpt-oss-20b via OpenAI Completions)", () => {
|
||||
let llm: Model<"openai-completions">;
|
||||
let ollamaProcess: Subprocess | null = null;
|
||||
|
||||
beforeAll(async () => {
|
||||
// Check if model is available, if not pull it
|
||||
try {
|
||||
Bun.spawnSync(["sh", "-c", "ollama list | grep -q 'gpt-oss:20b'"]);
|
||||
} catch {
|
||||
console.log("Pulling gpt-oss:20b model for Ollama tests...");
|
||||
try {
|
||||
await Bun.spawn(["ollama", "pull", "gpt-oss:20b"], { stdout: "inherit" }).exited;
|
||||
} catch (_e) {
|
||||
console.warn("Failed to pull gpt-oss:20b model, tests will be skipped");
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
// Start ollama server
|
||||
ollamaProcess = Bun.spawn(["ollama", "serve"], {
|
||||
stdout: "ignore",
|
||||
stderr: "ignore",
|
||||
});
|
||||
|
||||
// Wait for server to be ready
|
||||
await new Promise<void>((resolve) => {
|
||||
const checkServer = async () => {
|
||||
try {
|
||||
const response = await fetch("http://localhost:11434/api/tags");
|
||||
if (response.ok) {
|
||||
resolve();
|
||||
} else {
|
||||
setTimeout(checkServer, 500);
|
||||
}
|
||||
} catch {
|
||||
setTimeout(checkServer, 500);
|
||||
}
|
||||
};
|
||||
setTimeout(checkServer, 1000); // Initial delay
|
||||
});
|
||||
|
||||
llm = {
|
||||
id: "gpt-oss:20b",
|
||||
api: "openai-completions",
|
||||
provider: "ollama",
|
||||
baseUrl: "http://localhost:11434/v1",
|
||||
reasoning: true,
|
||||
input: ["text"],
|
||||
contextWindow: 128000,
|
||||
maxTokens: 16000,
|
||||
cost: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
},
|
||||
name: "Ollama GPT-OSS 20B",
|
||||
};
|
||||
}, 30000); // 30 second timeout for setup
|
||||
|
||||
afterAll(() => {
|
||||
// Kill ollama server
|
||||
if (ollamaProcess) {
|
||||
ollamaProcess.kill();
|
||||
ollamaProcess = null;
|
||||
}
|
||||
});
|
||||
|
||||
it("should complete basic text generation", { retry: 3 }, async () => {
|
||||
await basicTextGeneration(llm, { apiKey: "test" });
|
||||
});
|
||||
|
||||
it("should handle tool calling", { retry: 3 }, async () => {
|
||||
await handleToolCall(llm, { apiKey: "test" });
|
||||
});
|
||||
|
||||
it("should handle streaming", { retry: 3 }, async () => {
|
||||
await handleStreaming(llm, { apiKey: "test" });
|
||||
});
|
||||
|
||||
it("should handle thinking mode", { retry: 3 }, async () => {
|
||||
await handleThinking(llm, { apiKey: "test", reasoningEffort: "medium" });
|
||||
});
|
||||
|
||||
it("should handle multi-turn with thinking and tools", { retry: 3 }, async () => {
|
||||
await multiTurn(llm, { apiKey: "test", reasoningEffort: "medium" });
|
||||
});
|
||||
});
|
||||
});
|
||||
@@ -1,220 +0,0 @@
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { stream } from "../src/stream";
|
||||
import type { Api, Context, Model, OptionsForApi } from "../src/types";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("anthropic"),
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
async function testTokensOnAbort<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Write a long poem with 20 stanzas about the beauty of nature.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const controller = new AbortController();
|
||||
const response = stream(llm, context, { ...options, signal: controller.signal });
|
||||
|
||||
let abortFired = false;
|
||||
let text = "";
|
||||
for await (const event of response) {
|
||||
if (!abortFired && (event.type === "text_delta" || event.type === "thinking_delta")) {
|
||||
text += event.delta;
|
||||
if (text.length >= 1000) {
|
||||
abortFired = true;
|
||||
controller.abort();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const msg = await response.result();
|
||||
|
||||
expect(msg.stopReason).toBe("aborted");
|
||||
|
||||
// OpenAI providers, Gemini CLI, zai, and the GPT-OSS model on Antigravity only send usage in the final chunk,
|
||||
// so when aborted they have no token stats Anthropic and Google send usage information early in the stream
|
||||
if (
|
||||
llm.api === "openai-completions" ||
|
||||
llm.api === "openai-responses" ||
|
||||
llm.provider === "google-gemini-cli" ||
|
||||
llm.provider === "zai" ||
|
||||
(llm.provider === "google-antigravity" && llm.id.includes("gpt-oss"))
|
||||
) {
|
||||
expect(msg.usage.input).toBe(0);
|
||||
expect(msg.usage.output).toBe(0);
|
||||
} else {
|
||||
expect(msg.usage.input).toBeGreaterThan(0);
|
||||
expect(msg.usage.output).toBeGreaterThan(0);
|
||||
|
||||
// Antigravity Gemini and Claude models report token usage, but no cost
|
||||
if (llm.provider !== "google-antigravity") {
|
||||
expect(msg.usage.cost.input).toBeGreaterThan(0);
|
||||
expect(msg.usage.cost.total).toBeGreaterThan(0);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
describe("Token Statistics on Abort", () => {
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider", () => {
|
||||
const llm = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm, { thinking: { enabled: true } });
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider", () => {
|
||||
const llm: Model<"openai-completions"> = {
|
||||
...getModel("openai", "gpt-4o-mini")!,
|
||||
api: "openai-completions",
|
||||
};
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider", () => {
|
||||
const llm = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider", () => {
|
||||
const llm = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider", () => {
|
||||
const llm = getModel("xai", "grok-3-fast");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider", () => {
|
||||
const llm = getModel("groq", "openai/gpt-oss-20b");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider", () => {
|
||||
const llm = getModel("cerebras", "gpt-oss-120b");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider", () => {
|
||||
const llm = getModel("zai", "glm-4.5-flash");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider", () => {
|
||||
const llm = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("should include token stats when aborted mid-stream", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testTokensOnAbort(llm);
|
||||
});
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OAuth-based providers (credentials from ~/.omp/agent/auth.json)
|
||||
// =========================================================================
|
||||
|
||||
describe("Anthropic OAuth Provider", () => {
|
||||
const llm = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should include token stats when aborted mid-stream",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await testTokensOnAbort(llm, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("GitHub Copilot Provider", () => {
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should include token stats when aborted mid-stream",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testTokensOnAbort(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should include token stats when aborted mid-stream",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testTokensOnAbort(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Gemini CLI Provider", () => {
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should include token stats when aborted mid-stream",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testTokensOnAbort(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider", () => {
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should include token stats when aborted mid-stream",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testTokensOnAbort(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should include token stats when aborted mid-stream",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testTokensOnAbort(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should include token stats when aborted mid-stream",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testTokensOnAbort(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
});
|
||||
@@ -1,247 +0,0 @@
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete } from "../src/stream";
|
||||
import type { Api, Context, Model, OptionsForApi, Tool } from "../src/types";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("anthropic"),
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
// Simple calculate tool
|
||||
const calculateSchema = Type.Object({
|
||||
expression: Type.String({ description: "The mathematical expression to evaluate" }),
|
||||
});
|
||||
|
||||
const calculateTool: Tool = {
|
||||
name: "calculate",
|
||||
description: "Evaluate mathematical expressions",
|
||||
parameters: calculateSchema,
|
||||
};
|
||||
|
||||
async function testToolCallWithoutResult<TApi extends Api>(
|
||||
model: Model<TApi>,
|
||||
options: OptionsForApi<TApi> = {} as OptionsForApi<TApi>,
|
||||
) {
|
||||
// Step 1: Create context with the calculate tool
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant. Use the calculate tool when asked to perform calculations.",
|
||||
messages: [],
|
||||
tools: [calculateTool],
|
||||
};
|
||||
|
||||
// Step 2: Ask the LLM to make a tool call
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content: "Please calculate 25 * 18 using the calculate tool.",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// Step 3: Get the assistant's response (should contain a tool call)
|
||||
const firstResponse = await complete(model, context, options);
|
||||
context.messages.push(firstResponse);
|
||||
|
||||
console.log("First response:", JSON.stringify(firstResponse, null, 2));
|
||||
|
||||
// Verify the response contains a tool call
|
||||
const hasToolCall = firstResponse.content.some((block) => block.type === "toolCall");
|
||||
expect(hasToolCall).toBe(true);
|
||||
|
||||
if (!hasToolCall) {
|
||||
throw new Error("Expected assistant to make a tool call, but none was found");
|
||||
}
|
||||
|
||||
// Step 4: Send a user message WITHOUT providing tool result
|
||||
// This simulates the scenario where a tool call was aborted/cancelled
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content: "Never mind, just tell me what is 2+2?",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// Step 5: The fix should filter out the orphaned tool call, and the request should succeed
|
||||
const secondResponse = await complete(model, context, options);
|
||||
console.log("Second response:", JSON.stringify(secondResponse, null, 2));
|
||||
|
||||
// The request should succeed (not error) - that's the main thing we're testing
|
||||
expect(secondResponse.stopReason).not.toBe("error");
|
||||
|
||||
// Should have some content in the response
|
||||
expect(secondResponse.content.length).toBeGreaterThan(0);
|
||||
|
||||
// The LLM may choose to answer directly or make a new tool call - either is fine
|
||||
// The important thing is it didn't fail with the orphaned tool call error
|
||||
const textContent = secondResponse.content
|
||||
.filter((block) => block.type === "text")
|
||||
.map((block) => (block.type === "text" ? block.text : ""))
|
||||
.join(" ");
|
||||
const toolCalls = secondResponse.content.filter((block) => block.type === "toolCall").length;
|
||||
expect(toolCalls || textContent.length).toBeGreaterThan(0);
|
||||
console.log("Answer:", textContent);
|
||||
|
||||
// Verify the stop reason is either "stop" or "toolUse" (new tool call)
|
||||
expect(["stop", "toolUse"]).toContain(secondResponse.stopReason);
|
||||
}
|
||||
|
||||
describe("Tool Call Without Result Tests", () => {
|
||||
// =========================================================================
|
||||
// API Key-based providers
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider", () => {
|
||||
const model = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider", () => {
|
||||
const model: Model<"openai-completions"> = {
|
||||
...getModel("openai", "gpt-4o-mini")!,
|
||||
api: "openai-completions",
|
||||
};
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider", () => {
|
||||
const model = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider", () => {
|
||||
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider", () => {
|
||||
const model = getModel("xai", "grok-3-fast");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider", () => {
|
||||
const model = getModel("groq", "openai/gpt-oss-20b");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider", () => {
|
||||
const model = getModel("cerebras", "gpt-oss-120b");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider", () => {
|
||||
const model = getModel("zai", "glm-4.5-flash");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider", () => {
|
||||
const model = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("should filter out tool calls without corresponding tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testToolCallWithoutResult(model);
|
||||
});
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OAuth-based providers (credentials from ~/.omp/agent/auth.json)
|
||||
// =========================================================================
|
||||
|
||||
describe("Anthropic OAuth Provider", () => {
|
||||
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should filter out tool calls without corresponding tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await testToolCallWithoutResult(model, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("GitHub Copilot Provider", () => {
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should filter out tool calls without corresponding tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const model = getModel("github-copilot", "gpt-4o");
|
||||
await testToolCallWithoutResult(model, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should filter out tool calls without corresponding tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const model = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testToolCallWithoutResult(model, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Gemini CLI Provider", () => {
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should filter out tool calls without corresponding tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const model = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testToolCallWithoutResult(model, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider", () => {
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should filter out tool calls without corresponding tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testToolCallWithoutResult(model, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should filter out tool calls without corresponding tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testToolCallWithoutResult(model, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should filter out tool calls without corresponding tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testToolCallWithoutResult(model, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
});
|
||||
@@ -1,536 +0,0 @@
|
||||
/**
|
||||
* Test totalTokens field across all providers.
|
||||
*
|
||||
* totalTokens represents the total number of tokens processed by the LLM,
|
||||
* including input (with cache) and output (with thinking). This is the
|
||||
* base for calculating context size for the next request.
|
||||
*
|
||||
* - OpenAI Completions: Uses native total_tokens field
|
||||
* - OpenAI Responses: Uses native total_tokens field
|
||||
* - Google: Uses native totalTokenCount field
|
||||
* - Anthropic: Computed as input + output + cacheRead + cacheWrite
|
||||
* - Other OpenAI-compatible providers: Uses native total_tokens field
|
||||
*/
|
||||
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete } from "../src/stream";
|
||||
import type { Api, Context, Model, OptionsForApi, Usage } from "../src/types";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("anthropic"),
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
// Generate a long system prompt to trigger caching (>2k bytes for most providers)
|
||||
const LONG_SYSTEM_PROMPT = `You are a helpful assistant. Be concise in your responses.
|
||||
|
||||
Here is some additional context that makes this system prompt long enough to trigger caching:
|
||||
|
||||
${Array(50)
|
||||
.fill(
|
||||
"Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.",
|
||||
)
|
||||
.join("\n\n")}
|
||||
|
||||
Remember: Always be helpful and concise.`;
|
||||
|
||||
async function testTotalTokensWithCache<TApi extends Api>(
|
||||
llm: Model<TApi>,
|
||||
options: OptionsForApi<TApi> = {} as OptionsForApi<TApi>,
|
||||
): Promise<{ first: Usage; second: Usage }> {
|
||||
// First request - no cache
|
||||
const context1: Context = {
|
||||
systemPrompt: LONG_SYSTEM_PROMPT,
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "What is 2 + 2? Reply with just the number.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const response1 = await complete(llm, context1, options);
|
||||
expect(response1.stopReason).toBe("stop");
|
||||
|
||||
// Second request - should trigger cache read (same system prompt, add conversation)
|
||||
const context2: Context = {
|
||||
systemPrompt: LONG_SYSTEM_PROMPT,
|
||||
messages: [
|
||||
...context1.messages,
|
||||
response1, // Include previous assistant response
|
||||
{
|
||||
role: "user",
|
||||
content: "What is 3 + 3? Reply with just the number.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const response2 = await complete(llm, context2, options);
|
||||
expect(response2.stopReason).toBe("stop");
|
||||
|
||||
return { first: response1.usage, second: response2.usage };
|
||||
}
|
||||
|
||||
function logUsage(label: string, usage: Usage) {
|
||||
const computed = usage.input + usage.output + usage.cacheRead + usage.cacheWrite;
|
||||
console.log(` ${label}:`);
|
||||
console.log(
|
||||
` input: ${usage.input}, output: ${usage.output}, cacheRead: ${usage.cacheRead}, cacheWrite: ${usage.cacheWrite}`,
|
||||
);
|
||||
console.log(` totalTokens: ${usage.totalTokens}, computed: ${computed}`);
|
||||
}
|
||||
|
||||
function assertTotalTokensEqualsComponents(usage: Usage) {
|
||||
const computed = usage.input + usage.output + usage.cacheRead + usage.cacheWrite;
|
||||
expect(usage.totalTokens).toBe(computed);
|
||||
}
|
||||
|
||||
describe("totalTokens field", () => {
|
||||
// =========================================================================
|
||||
// Anthropic
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic (API Key)", () => {
|
||||
it(
|
||||
"claude-3-5-haiku - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
console.log(`\nAnthropic / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.ANTHROPIC_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
|
||||
// Anthropic should have cache activity
|
||||
const hasCache = second.cacheRead > 0 || second.cacheWrite > 0 || first.cacheWrite > 0;
|
||||
expect(hasCache).toBe(true);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Anthropic (OAuth)", () => {
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"claude-sonnet-4 - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("anthropic", "claude-sonnet-4-20250514");
|
||||
|
||||
console.log(`\nAnthropic OAuth / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: anthropicOAuthToken });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
|
||||
// Anthropic should have cache activity
|
||||
const hasCache = second.cacheRead > 0 || second.cacheWrite > 0 || first.cacheWrite > 0;
|
||||
expect(hasCache).toBe(true);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OpenAI
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions", () => {
|
||||
it(
|
||||
"gpt-4o-mini - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm: Model<"openai-completions"> = {
|
||||
...getModel("openai", "gpt-4o-mini")!,
|
||||
api: "openai-completions",
|
||||
};
|
||||
|
||||
console.log(`\nOpenAI Completions / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm);
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses", () => {
|
||||
it("gpt-4o - should return totalTokens equal to sum of components", { retry: 3, timeout: 60000 }, async () => {
|
||||
const llm = getModel("openai", "gpt-4o");
|
||||
|
||||
console.log(`\nOpenAI Responses / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm);
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
});
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// Google
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google", () => {
|
||||
it(
|
||||
"gemini-2.0-flash - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("google", "gemini-2.0-flash");
|
||||
|
||||
console.log(`\nGoogle / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm);
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// xAI
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.XAI_API_KEY)("xAI", () => {
|
||||
it(
|
||||
"grok-3-fast - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("xai", "grok-3-fast");
|
||||
|
||||
console.log(`\nxAI / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.XAI_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// Groq
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.GROQ_API_KEY)("Groq", () => {
|
||||
it(
|
||||
"openai/gpt-oss-120b - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("groq", "openai/gpt-oss-120b");
|
||||
|
||||
console.log(`\nGroq / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.GROQ_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// Cerebras
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras", () => {
|
||||
it(
|
||||
"gpt-oss-120b - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("cerebras", "gpt-oss-120b");
|
||||
|
||||
console.log(`\nCerebras / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.CEREBRAS_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// z.ai
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("z.ai", () => {
|
||||
it(
|
||||
"glm-4.5-flash - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("zai", "glm-4.5-flash");
|
||||
|
||||
console.log(`\nz.ai / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.ZAI_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// Mistral
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral", () => {
|
||||
it(
|
||||
"devstral-medium-latest - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
console.log(`\nMistral / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.MISTRAL_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OpenRouter - Multiple backend providers
|
||||
// =========================================================================
|
||||
|
||||
describe.skipIf(!process.env.OPENROUTER_API_KEY)("OpenRouter", () => {
|
||||
it(
|
||||
"anthropic/claude-sonnet-4 - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("openrouter", "anthropic/claude-sonnet-4");
|
||||
|
||||
console.log(`\nOpenRouter / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.OPENROUTER_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
|
||||
it(
|
||||
"deepseek/deepseek-chat - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("openrouter", "deepseek/deepseek-chat");
|
||||
|
||||
console.log(`\nOpenRouter / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.OPENROUTER_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
|
||||
it(
|
||||
"mistralai/mistral-small-3.1-24b-instruct - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("openrouter", "mistralai/mistral-small-3.1-24b-instruct");
|
||||
|
||||
console.log(`\nOpenRouter / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.OPENROUTER_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
|
||||
it(
|
||||
"google/gemini-2.0-flash-001 - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("openrouter", "google/gemini-2.0-flash-001");
|
||||
|
||||
console.log(`\nOpenRouter / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.OPENROUTER_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
|
||||
it(
|
||||
"meta-llama/llama-4-maverick - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("openrouter", "meta-llama/llama-4-maverick");
|
||||
|
||||
console.log(`\nOpenRouter / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: process.env.OPENROUTER_API_KEY });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// GitHub Copilot (OAuth)
|
||||
// =========================================================================
|
||||
|
||||
describe("GitHub Copilot (OAuth)", () => {
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
|
||||
console.log(`\nGitHub Copilot / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: githubCopilotToken });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
|
||||
console.log(`\nGitHub Copilot / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: githubCopilotToken });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// Google Gemini CLI (OAuth)
|
||||
// =========================================================================
|
||||
|
||||
describe("Google Gemini CLI (OAuth)", () => {
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
|
||||
console.log(`\nGoogle Gemini CLI / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: geminiCliToken });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// Google Antigravity (OAuth)
|
||||
// =========================================================================
|
||||
|
||||
describe("Google Antigravity (OAuth)", () => {
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
|
||||
console.log(`\nGoogle Antigravity / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: antigravityToken });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
|
||||
console.log(`\nGoogle Antigravity / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: antigravityToken });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should return totalTokens equal to sum of components",
|
||||
{ retry: 3, timeout: 60000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
|
||||
console.log(`\nGoogle Antigravity / ${llm.id}:`);
|
||||
const { first, second } = await testTotalTokensWithCache(llm, { apiKey: antigravityToken });
|
||||
|
||||
logUsage("First request", first);
|
||||
logUsage("Second request", second);
|
||||
|
||||
assertTotalTokensEqualsComponents(first);
|
||||
assertTotalTokensEqualsComponents(second);
|
||||
},
|
||||
);
|
||||
});
|
||||
});
|
||||
@@ -1,615 +0,0 @@
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { complete } from "../src/stream";
|
||||
import type { Api, Context, Model, OptionsForApi, ToolResultMessage } from "../src/types";
|
||||
import { resolveApiKey } from "./oauth";
|
||||
|
||||
// Empty schema for test tools - must be proper OBJECT type for Cloud Code Assist
|
||||
const emptySchema = Type.Object({});
|
||||
|
||||
// Resolve OAuth tokens at module level (async, runs before tests)
|
||||
const oauthTokens = await Promise.all([
|
||||
resolveApiKey("anthropic"),
|
||||
resolveApiKey("github-copilot"),
|
||||
resolveApiKey("google-gemini-cli"),
|
||||
resolveApiKey("google-antigravity"),
|
||||
]);
|
||||
const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
|
||||
|
||||
/**
|
||||
* Test for Unicode surrogate pair handling in tool results.
|
||||
*
|
||||
* Issue: When tool results contain emoji or other characters outside the Basic Multilingual Plane,
|
||||
* they may be incorrectly serialized as unpaired surrogates, causing "no low surrogate in string"
|
||||
* errors when sent to the API provider.
|
||||
*
|
||||
* Example error from Anthropic:
|
||||
* "The request body is not valid JSON: no low surrogate in string: line 1 column 197667"
|
||||
*/
|
||||
|
||||
async function testEmojiInToolResults<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
// Simulate a tool that returns emoji
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Use the test tool",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "assistant",
|
||||
content: [
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "test_1",
|
||||
name: "test_tool",
|
||||
arguments: {},
|
||||
},
|
||||
],
|
||||
api: llm.api,
|
||||
provider: llm.provider,
|
||||
model: llm.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [
|
||||
{
|
||||
name: "test_tool",
|
||||
description: "A test tool",
|
||||
parameters: emptySchema,
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
// Add tool result with various problematic Unicode characters
|
||||
const toolResult: ToolResultMessage = {
|
||||
role: "toolResult",
|
||||
toolCallId: "test_1",
|
||||
toolName: "test_tool",
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Test with emoji 🙈 and other characters:
|
||||
- Monkey emoji: 🙈
|
||||
- Thumbs up: 👍
|
||||
- Heart: ❤️
|
||||
- Thinking face: 🤔
|
||||
- Rocket: 🚀
|
||||
- Mixed text: Mario Zechner wann? Wo? Bin grad äußersr eventuninformiert 🙈
|
||||
- Japanese: こんにちは
|
||||
- Chinese: 你好
|
||||
- Mathematical symbols: ∑∫∂√
|
||||
- Special quotes: "curly" 'quotes'`,
|
||||
},
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
context.messages.push(toolResult);
|
||||
|
||||
// Add follow-up user message
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content: "Summarize the tool result briefly.",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// This should not throw a surrogate pair error
|
||||
const response = await complete(llm, context, options);
|
||||
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
expect(response.errorMessage).toBeFalsy();
|
||||
expect(response.content.length).toBeGreaterThan(0);
|
||||
}
|
||||
|
||||
async function testRealWorldLinkedInData<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Use the linkedin tool to get comments",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "assistant",
|
||||
content: [
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "linkedin_1",
|
||||
name: "linkedin_skill",
|
||||
arguments: {},
|
||||
},
|
||||
],
|
||||
api: llm.api,
|
||||
provider: llm.provider,
|
||||
model: llm.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [
|
||||
{
|
||||
name: "linkedin_skill",
|
||||
description: "Get LinkedIn comments",
|
||||
parameters: emptySchema,
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
// Real-world tool result from LinkedIn with emoji
|
||||
const toolResult: ToolResultMessage = {
|
||||
role: "toolResult",
|
||||
toolCallId: "linkedin_1",
|
||||
toolName: "linkedin_skill",
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Post: Hab einen "Generative KI für Nicht-Techniker" Workshop gebaut.
|
||||
Unanswered Comments: 2
|
||||
|
||||
=> {
|
||||
"comments": [
|
||||
{
|
||||
"author": "Matthias Neumayer's graphic link",
|
||||
"text": "Leider nehmen das viel zu wenige Leute ernst"
|
||||
},
|
||||
{
|
||||
"author": "Matthias Neumayer's graphic link",
|
||||
"text": "Mario Zechner wann? Wo? Bin grad äußersr eventuninformiert 🙈"
|
||||
}
|
||||
]
|
||||
}`,
|
||||
},
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
context.messages.push(toolResult);
|
||||
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content: "How many comments are there?",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// This should not throw a surrogate pair error
|
||||
const response = await complete(llm, context, options);
|
||||
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
expect(response.errorMessage).toBeFalsy();
|
||||
expect(response.content.some((b) => b.type === "text")).toBe(true);
|
||||
}
|
||||
|
||||
async function testUnpairedHighSurrogate<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Use the test tool",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "assistant",
|
||||
content: [
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "test_2",
|
||||
name: "test_tool",
|
||||
arguments: {},
|
||||
},
|
||||
],
|
||||
api: llm.api,
|
||||
provider: llm.provider,
|
||||
model: llm.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [
|
||||
{
|
||||
name: "test_tool",
|
||||
description: "A test tool",
|
||||
parameters: emptySchema,
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
// Construct a string with an intentionally unpaired high surrogate
|
||||
// This simulates what might happen if text processing corrupts emoji
|
||||
const unpairedSurrogate = String.fromCharCode(0xd83d); // High surrogate without low surrogate
|
||||
|
||||
const toolResult: ToolResultMessage = {
|
||||
role: "toolResult",
|
||||
toolCallId: "test_2",
|
||||
toolName: "test_tool",
|
||||
content: [{ type: "text", text: `Text with unpaired surrogate: ${unpairedSurrogate} <- should be sanitized` }],
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
context.messages.push(toolResult);
|
||||
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content: "What did the tool return?",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// This should not throw a surrogate pair error
|
||||
// The unpaired surrogate should be sanitized before sending to API
|
||||
const response = await complete(llm, context, options);
|
||||
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
expect(response.errorMessage).toBeFalsy();
|
||||
expect(response.content.length).toBeGreaterThan(0);
|
||||
}
|
||||
|
||||
describe("AI Providers Unicode Surrogate Pair Tests", () => {
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider Unicode Handling", () => {
|
||||
const llm = getModel("google", "gemini-2.5-flash");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider Unicode Handling", () => {
|
||||
const llm = getModel("openai", "gpt-4o-mini");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider Unicode Handling", () => {
|
||||
const llm = getModel("openai", "gpt-5-mini");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider Unicode Handling", () => {
|
||||
const llm = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
// =========================================================================
|
||||
// OAuth-based providers (credentials from ~/.omp/agent/auth.json)
|
||||
// =========================================================================
|
||||
|
||||
describe("Anthropic OAuth Provider Unicode Handling", () => {
|
||||
const llm = getModel("anthropic", "claude-3-5-haiku-20241022");
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm, { apiKey: anthropicOAuthToken });
|
||||
});
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should handle real-world LinkedIn comment data with emoji",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await testRealWorldLinkedInData(llm, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!anthropicOAuthToken)(
|
||||
"should handle unpaired high surrogate (0xD83D) in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
await testUnpairedHighSurrogate(llm, { apiKey: anthropicOAuthToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("GitHub Copilot Provider Unicode Handling", () => {
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle emoji in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testEmojiInToolResults(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle real-world LinkedIn comment data with emoji",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testRealWorldLinkedInData(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"gpt-4o - should handle unpaired high surrogate (0xD83D) in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "gpt-4o");
|
||||
await testUnpairedHighSurrogate(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle emoji in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testEmojiInToolResults(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle real-world LinkedIn comment data with emoji",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testRealWorldLinkedInData(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!githubCopilotToken)(
|
||||
"claude-sonnet-4 - should handle unpaired high surrogate (0xD83D) in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("github-copilot", "claude-sonnet-4");
|
||||
await testUnpairedHighSurrogate(llm, { apiKey: githubCopilotToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Gemini CLI Provider Unicode Handling", () => {
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle emoji in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testEmojiInToolResults(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle real-world LinkedIn comment data with emoji",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testRealWorldLinkedInData(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!geminiCliToken)(
|
||||
"gemini-2.5-flash - should handle unpaired high surrogate (0xD83D) in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
||||
await testUnpairedHighSurrogate(llm, { apiKey: geminiCliToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider Unicode Handling", () => {
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle emoji in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testEmojiInToolResults(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle real-world LinkedIn comment data with emoji",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testRealWorldLinkedInData(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle unpaired high surrogate (0xD83D) in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gemini-3-flash");
|
||||
await testUnpairedHighSurrogate(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle emoji in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testEmojiInToolResults(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle real-world LinkedIn comment data with emoji",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testRealWorldLinkedInData(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle unpaired high surrogate (0xD83D) in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await testUnpairedHighSurrogate(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle emoji in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testEmojiInToolResults(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle real-world LinkedIn comment data with emoji",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testRealWorldLinkedInData(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle unpaired high surrogate (0xD83D) in tool results",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
async () => {
|
||||
const llm = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
await testUnpairedHighSurrogate(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider Unicode Handling", () => {
|
||||
const llm = getModel("xai", "grok-3");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider Unicode Handling", () => {
|
||||
const llm = getModel("groq", "openai/gpt-oss-20b");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider Unicode Handling", () => {
|
||||
const llm = getModel("cerebras", "gpt-oss-120b");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider Unicode Handling", () => {
|
||||
const llm = getModel("zai", "glm-4.5-air");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider Unicode Handling", () => {
|
||||
const llm = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("should handle emoji in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testEmojiInToolResults(llm);
|
||||
});
|
||||
|
||||
it("should handle real-world LinkedIn comment data with emoji", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testRealWorldLinkedInData(llm);
|
||||
});
|
||||
|
||||
it("should handle unpaired high surrogate (0xD83D) in tool results", { retry: 3, timeout: 30000 }, async () => {
|
||||
await testUnpairedHighSurrogate(llm);
|
||||
});
|
||||
});
|
||||
});
|
||||
@@ -1,69 +0,0 @@
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models";
|
||||
import { stream } from "../src/stream";
|
||||
import type { Context, Model } from "../src/types";
|
||||
|
||||
function makeContext(): Context {
|
||||
return {
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: `What is ${(Math.random() * 100) | 0} + ${(Math.random() * 100) | 0}? Think step by step.`,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
};
|
||||
}
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("xhigh reasoning", () => {
|
||||
describe("codex-max (supports xhigh)", () => {
|
||||
// Note: codex models only support the responses API, not chat completions
|
||||
it("should work with openai-responses", async () => {
|
||||
const model = getModel("openai", "gpt-5.1-codex-max");
|
||||
const s = stream(model, makeContext(), { reasoningEffort: "xhigh" });
|
||||
let hasThinking = false;
|
||||
|
||||
for await (const event of s) {
|
||||
if (event.type === "thinking_start" || event.type === "thinking_delta") {
|
||||
hasThinking = true;
|
||||
}
|
||||
}
|
||||
|
||||
const response = await s.result();
|
||||
expect(response.stopReason, `Error: ${response.errorMessage}`).toBe("stop");
|
||||
expect(response.content.some((b) => b.type === "text")).toBe(true);
|
||||
expect(hasThinking || response.content.some((b) => b.type === "thinking")).toBe(true);
|
||||
});
|
||||
});
|
||||
|
||||
describe("gpt-5-mini (does not support xhigh)", () => {
|
||||
it("should error with openai-responses when using xhigh", async () => {
|
||||
const model = getModel("openai", "gpt-5-mini");
|
||||
const s = stream(model, makeContext(), { reasoningEffort: "xhigh" });
|
||||
|
||||
for await (const _ of s) {
|
||||
// drain events
|
||||
}
|
||||
|
||||
const response = await s.result();
|
||||
expect(response.stopReason).toBe("error");
|
||||
expect(response.errorMessage).toContain("xhigh");
|
||||
});
|
||||
|
||||
it("should error with openai-completions when using xhigh", async () => {
|
||||
const model: Model<"openai-completions"> = {
|
||||
...getModel("openai", "gpt-5-mini"),
|
||||
api: "openai-completions",
|
||||
};
|
||||
const s = stream(model, makeContext(), { reasoningEffort: "xhigh" });
|
||||
|
||||
for await (const _ of s) {
|
||||
// drain events
|
||||
}
|
||||
|
||||
const response = await s.result();
|
||||
expect(response.stopReason).toBe("error");
|
||||
expect(response.errorMessage).toContain("xhigh");
|
||||
});
|
||||
});
|
||||
});
|
||||
@@ -1,9 +0,0 @@
|
||||
{
|
||||
"extends": "../../tsconfig.base.json",
|
||||
"compilerOptions": {
|
||||
"outDir": "./dist",
|
||||
"rootDir": "./src"
|
||||
},
|
||||
"include": ["src/**/*.ts", "src/bun-imports.d.ts"],
|
||||
"exclude": ["node_modules", "dist"]
|
||||
}
|
||||
@@ -1,9 +0,0 @@
|
||||
import { defineConfig } from 'vitest/config';
|
||||
|
||||
export default defineConfig({
|
||||
test: {
|
||||
globals: true,
|
||||
environment: 'node',
|
||||
testTimeout: 30000, // 30 seconds for API calls
|
||||
}
|
||||
});
|
||||
@@ -2,6 +2,10 @@
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
### Changed
|
||||
|
||||
- Switched from local `@oh-my-pi/pi-ai` to upstream `@mariozechner/pi-ai` package
|
||||
|
||||
### Added
|
||||
|
||||
- Added `webSearchProvider` setting to override auto-detection priority (Exa > Perplexity > Anthropic)
|
||||
@@ -48,6 +52,7 @@
|
||||
- Fixed Linux ARM64 installs failing on fresh Debian when the `sharp` module is unavailable during session image compression
|
||||
|
||||
## [3.20.1] - 2026-01-06
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed find tool failing to match patterns with path separators (e.g., `reports/**`) by enabling full-path matching in fd
|
||||
@@ -58,6 +63,7 @@
|
||||
- Changed ls tool to show relative modification times (e.g., "2d ago", "just now") for each entry
|
||||
|
||||
## [3.20.0] - 2026-01-06
|
||||
|
||||
### Added
|
||||
|
||||
- Added extensions API with auto-discovery (`.omp/extensions`) and `--extension`/`-e` loading for custom tools, commands, and lifecycle hooks
|
||||
@@ -197,6 +203,7 @@
|
||||
- Fixed session persistence to truncate oversized entries before writing JSONL to prevent out-of-memory errors
|
||||
|
||||
## [3.14.0] - 2026-01-04
|
||||
|
||||
### Added
|
||||
|
||||
- Added `getUsageStatistics()` method to SessionManager for tracking cumulative token usage and costs across session messages
|
||||
@@ -221,6 +228,7 @@
|
||||
- Fixed stale diagnostics persisting after file content changes in LSP client
|
||||
|
||||
## [3.8.1337] - 2026-01-04
|
||||
|
||||
### Added
|
||||
|
||||
- Added automatic browser opening after exporting session to HTML
|
||||
@@ -231,6 +239,7 @@
|
||||
- Fixed session titles not persisting to file when set before first flush
|
||||
|
||||
## [3.7.1337] - 2026-01-04
|
||||
|
||||
### Added
|
||||
|
||||
- Added `EditMatchError` class for structured error handling in edit operations
|
||||
@@ -289,6 +298,7 @@
|
||||
- Updated version update notification to suggest `omp update` instead of manual npm install command
|
||||
|
||||
## [3.1.1337] - 2026-01-03
|
||||
|
||||
### Added
|
||||
|
||||
- Added `spawns` frontmatter field for agent definitions to control which sub-agents can be spawned
|
||||
@@ -307,7 +317,7 @@
|
||||
- Added Discovery settings tab in interactive mode to enable/disable individual configuration providers
|
||||
- Added provider source attribution showing which tool contributed each configuration item
|
||||
- Added support for Cursor MDC rule format with frontmatter (description, globs, alwaysApply)
|
||||
- Added support for Windsurf rules from .windsurf/rules/*.md and global_rules.md
|
||||
- Added support for Windsurf rules from .windsurf/rules/\*.md and global_rules.md
|
||||
- Added support for Cline rules from .clinerules file or directory
|
||||
- Added support for GitHub Copilot instructions with applyTo glob patterns
|
||||
- Added support for Gemini extensions and system.md customization files
|
||||
@@ -344,6 +354,7 @@
|
||||
- Removed separate asset copying steps from build scripts
|
||||
|
||||
## [2.0.1337] - 2026-01-03
|
||||
|
||||
### Added
|
||||
|
||||
- Added shell environment snapshot to preserve user aliases, functions, and shell options when executing bash commands
|
||||
@@ -356,6 +367,7 @@
|
||||
- Changed Edit tool to reject `.ipynb` files with guidance to use NotebookEdit tool instead
|
||||
|
||||
## [1.500.0] - 2026-01-03
|
||||
|
||||
### Added
|
||||
|
||||
- Added provider tabs to model selector with Tab/Arrow navigation for filtering models by provider
|
||||
@@ -417,6 +429,7 @@
|
||||
- Fixed Task tool showing "done + succeeded" when aborted; now correctly displays "⊘ aborted" status
|
||||
|
||||
## [1.341.0] - 2026-01-03
|
||||
|
||||
### Added
|
||||
|
||||
- Added interruptMode setting to control when queued messages are processed during tool execution.
|
||||
@@ -632,7 +645,7 @@ See [docs/custom-tools.md](docs/custom-tools.md) and [examples/custom-tools/](ex
|
||||
- `AppMessage` → `AgentMessage`
|
||||
- `sessionFile` returns `string | undefined` (was `string | null`)
|
||||
- `model` returns `Model | undefined` (was `Model | null`)
|
||||
- `Attachment` type removed. Use `ImageContent` from `@oh-my-pi/pi-ai` instead. Add images directly to message content arrays.
|
||||
- `Attachment` type removed. Use `ImageContent` from `@mariozechner/pi-ai` instead. Add images directly to message content arrays.
|
||||
|
||||
**AgentSession API:**
|
||||
|
||||
@@ -858,7 +871,7 @@ Total color count increased from 46 to 50. See [docs/theme.md](docs/theme.md) fo
|
||||
- `createAgentSession()` now accepts `authStorage` and `modelRegistry` options
|
||||
- Removed `configureOAuthStorage()`, `defaultGetApiKey()`, `findModel()`, `discoverAvailableModels()`
|
||||
- Removed `getApiKey` callback option (use `AuthStorage.setRuntimeApiKey()` for runtime overrides)
|
||||
- Use `getModel()` from `@oh-my-pi/pi-ai` for built-in models, `modelRegistry.find()` for custom models + built-in models
|
||||
- Use `getModel()` from `@mariozechner/pi-ai` for built-in models, `modelRegistry.find()` for custom models + built-in models
|
||||
- See updated [SDK documentation](docs/sdk.md) and [README](README.md)
|
||||
|
||||
- **Settings changes**: Removed `apiKeys` from `settings.json`. Use `auth.json` instead. ([#296](https://github.com/badlogic/pi-mono/issues/296))
|
||||
@@ -1161,7 +1174,7 @@ Total color count increased from 46 to 50. See [docs/theme.md](docs/theme.md) fo
|
||||
- `rpc.md`: Added missing `hook_error` event documentation
|
||||
- `README.md`: Complete settings table, condensed philosophy section, standardized OAuth docs
|
||||
|
||||
- Hooks loader now supports same import aliases as custom tools (`@sinclair/typebox`, `@oh-my-pi/pi-ai`, `@oh-my-pi/pi-tui`, `@oh-my-pi/pi-coding-agent`).
|
||||
- Hooks loader now supports same import aliases as custom tools (`@sinclair/typebox`, `@mariozechner/pi-ai`, `@oh-my-pi/pi-tui`, `@oh-my-pi/pi-coding-agent`).
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
@@ -1183,7 +1196,7 @@ Total color count increased from 46 to 50. See [docs/theme.md](docs/theme.md) fo
|
||||
|
||||
- Fixed TUI performance regression caused by Box component lacking render caching. Built-in tools now use Text directly (like v0.22.5), and Box has proper caching for custom tool rendering.
|
||||
|
||||
- Fixed custom tools failing to load from `~/.omp/agent/tools/` when omp is installed globally. Module imports (`@sinclair/typebox`, `@oh-my-pi/pi-tui`, `@oh-my-pi/pi-ai`) are now resolved via aliases.
|
||||
- Fixed custom tools failing to load from `~/.omp/agent/tools/` when omp is installed globally. Module imports (`@sinclair/typebox`, `@oh-my-pi/pi-tui`, `@mariozechner/pi-ai`) are now resolved via aliases.
|
||||
|
||||
## [0.23.0] - 2025-12-17
|
||||
|
||||
@@ -1223,7 +1236,7 @@ Total color count increased from 46 to 50. See [docs/theme.md](docs/theme.md) fo
|
||||
|
||||
- **Tool output display**: When collapsed, tool output now shows the last N lines instead of the first N lines, making streaming output more useful.
|
||||
|
||||
- Updated `@oh-my-pi/pi-ai` with X-Initiator header support for GitHub Copilot, ensuring agent calls are not deducted from quota. ([#200](https://github.com/badlogic/pi-mono/pull/200) by [@kim0](https://github.com/kim0))
|
||||
- Updated `@mariozechner/pi-ai` with X-Initiator header support for GitHub Copilot, ensuring agent calls are not deducted from quota. ([#200](https://github.com/badlogic/pi-mono/pull/200) by [@kim0](https://github.com/kim0))
|
||||
|
||||
### Fixed
|
||||
|
||||
@@ -1235,7 +1248,7 @@ Total color count increased from 46 to 50. See [docs/theme.md](docs/theme.md) fo
|
||||
|
||||
### Changed
|
||||
|
||||
- Updated `@oh-my-pi/pi-ai` with interleaved thinking enabled by default for Anthropic Claude 4 models.
|
||||
- Updated `@mariozechner/pi-ai` with interleaved thinking enabled by default for Anthropic Claude 4 models.
|
||||
|
||||
## [0.22.1] - 2025-12-15
|
||||
|
||||
@@ -1243,7 +1256,7 @@ _Dedicated to Peter's shoulder ([@steipete](https://twitter.com/steipete))_
|
||||
|
||||
### Changed
|
||||
|
||||
- Updated `@oh-my-pi/pi-ai` with interleaved thinking support for Anthropic models.
|
||||
- Updated `@mariozechner/pi-ai` with interleaved thinking support for Anthropic models.
|
||||
|
||||
## [0.22.0] - 2025-12-15
|
||||
|
||||
@@ -1741,4 +1754,4 @@ Initial public release.
|
||||
- Git branch display in footer
|
||||
- Message queueing during streaming responses
|
||||
- OAuth integration for Gmail and Google Calendar access
|
||||
- HTML export with syntax highlighting and collapsible sections
|
||||
- HTML export with syntax highlighting and collapsible sections
|
||||
|
||||
@@ -29,7 +29,7 @@ The coding-agent is structured into distinct layers:
|
||||
┌─────────────────────────────────────────────────────────────┐
|
||||
│ External Dependencies │
|
||||
│ @oh-my-pi/pi-agent (Agent, tools) │
|
||||
│ @oh-my-pi/pi-ai (models, providers) │
|
||||
│ @mariozechner/pi-ai (models, providers) │
|
||||
│ @oh-my-pi/pi-tui (TUI components) │
|
||||
└─────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
@@ -65,7 +65,7 @@ src/
|
||||
│ ├── system-prompt.ts # buildSystemPrompt(), loadProjectContextFiles()
|
||||
│ │
|
||||
│ ├── oauth/ # OAuth authentication (thin wrapper)
|
||||
│ │ └── index.ts # Re-exports from @oh-my-pi/pi-ai with convenience wrappers
|
||||
│ │ └── index.ts # Re-exports from @mariozechner/pi-ai with convenience wrappers
|
||||
│ │
|
||||
│ ├── hooks/ # Hook system for extending behavior
|
||||
│ │ ├── index.ts # Hook exports
|
||||
|
||||
@@ -65,8 +65,8 @@ Tools must be in a subdirectory with an `index.ts` entry point:
|
||||
|
||||
| Location | Scope | Auto-discovered |
|
||||
| ----------------------------------- | --------------------- | --------------- |
|
||||
| `~/.omp/agent/tools/*/index.ts` | Global (all projects) | Yes |
|
||||
| `.omp/tools/*/index.ts` | Project-local | Yes |
|
||||
| `~/.omp/agent/tools/*/index.ts` | Global (all projects) | Yes |
|
||||
| `.omp/tools/*/index.ts` | Project-local | Yes |
|
||||
| `settings.json` `customTools` array | Configured paths | Yes |
|
||||
| `--tool <path>` CLI flag | One-off/debugging | No |
|
||||
|
||||
@@ -94,7 +94,7 @@ Custom tools can import from these packages:
|
||||
| --------------------------- | --------------------------------------------------------- | --------------------------------------------------- |
|
||||
| `@sinclair/typebox` | Schema definitions (`Type.Object`, `Type.String`, etc.) | Via `pi.typebox.*` (injected) |
|
||||
| `@oh-my-pi/pi-coding-agent` | Types and utilities | Via `pi.pi.*` (injected) or direct import for types |
|
||||
| `@oh-my-pi/pi-ai` | AI utilities (`StringEnum` for Google-compatible enums) | Via `pi.pi.*` (re-exported through coding-agent) |
|
||||
| `@mariozechner/pi-ai` | AI utilities (`StringEnum` for Google-compatible enums) | Via `pi.pi.*` (re-exported through coding-agent) |
|
||||
| `@oh-my-pi/pi-tui` | TUI components (`Text`, `Box`, etc. for custom rendering) | Via `pi.pi.*` (re-exported through coding-agent) |
|
||||
|
||||
Node.js built-in modules (`node:fs`, `node:path`, etc.) are also available.
|
||||
|
||||
@@ -5,6 +5,7 @@
|
||||
Extensions are TypeScript modules that extend pi's behavior. They can subscribe to lifecycle events, register custom tools callable by the LLM, add commands, and more.
|
||||
|
||||
**Key capabilities:**
|
||||
|
||||
- **Custom tools** - Register tools the LLM can call via `pi.registerTool()`
|
||||
- **Event interception** - Block or modify tool calls, inject context, customize compaction
|
||||
- **User interaction** - Prompt users via `ctx.ui` (select, confirm, input, notify)
|
||||
@@ -14,6 +15,7 @@ Extensions are TypeScript modules that extend pi's behavior. They can subscribe
|
||||
- **Custom rendering** - Control how tool calls/results and messages appear in TUI
|
||||
|
||||
**Example use cases:**
|
||||
|
||||
- Permission gates (confirm before `rm -rf`, `sudo`, etc.)
|
||||
- Git checkpointing (stash at each turn, restore on branch)
|
||||
- Path protection (block writes to `.env`, `node_modules/`)
|
||||
@@ -55,41 +57,41 @@ import type { ExtensionAPI } from "@oh-my-pi/pi-coding-agent";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
|
||||
export default function (pi: ExtensionAPI) {
|
||||
// React to events
|
||||
pi.on("session_start", async (_event, ctx) => {
|
||||
ctx.ui.notify("Extension loaded!", "info");
|
||||
});
|
||||
// React to events
|
||||
pi.on("session_start", async (_event, ctx) => {
|
||||
ctx.ui.notify("Extension loaded!", "info");
|
||||
});
|
||||
|
||||
pi.on("tool_call", async (event, ctx) => {
|
||||
if (event.toolName === "bash" && event.input.command?.includes("rm -rf")) {
|
||||
const ok = await ctx.ui.confirm("Dangerous!", "Allow rm -rf?");
|
||||
if (!ok) return { block: true, reason: "Blocked by user" };
|
||||
}
|
||||
});
|
||||
pi.on("tool_call", async (event, ctx) => {
|
||||
if (event.toolName === "bash" && event.input.command?.includes("rm -rf")) {
|
||||
const ok = await ctx.ui.confirm("Dangerous!", "Allow rm -rf?");
|
||||
if (!ok) return { block: true, reason: "Blocked by user" };
|
||||
}
|
||||
});
|
||||
|
||||
// Register a custom tool
|
||||
pi.registerTool({
|
||||
name: "greet",
|
||||
label: "Greet",
|
||||
description: "Greet someone by name",
|
||||
parameters: Type.Object({
|
||||
name: Type.String({ description: "Name to greet" }),
|
||||
}),
|
||||
async execute(toolCallId, params, onUpdate, ctx, signal) {
|
||||
return {
|
||||
content: [{ type: "text", text: `Hello, ${params.name}!` }],
|
||||
details: {},
|
||||
};
|
||||
},
|
||||
});
|
||||
// Register a custom tool
|
||||
pi.registerTool({
|
||||
name: "greet",
|
||||
label: "Greet",
|
||||
description: "Greet someone by name",
|
||||
parameters: Type.Object({
|
||||
name: Type.String({ description: "Name to greet" }),
|
||||
}),
|
||||
async execute(toolCallId, params, onUpdate, ctx, signal) {
|
||||
return {
|
||||
content: [{ type: "text", text: `Hello, ${params.name}!` }],
|
||||
details: {},
|
||||
};
|
||||
},
|
||||
});
|
||||
|
||||
// Register a command
|
||||
pi.registerCommand("hello", {
|
||||
description: "Say hello",
|
||||
handler: async (args, ctx) => {
|
||||
ctx.ui.notify(`Hello ${args || "world"}!`, "info");
|
||||
},
|
||||
});
|
||||
// Register a command
|
||||
pi.registerCommand("hello", {
|
||||
description: "Say hello",
|
||||
handler: async (args, ctx) => {
|
||||
ctx.ui.notify(`Hello ${args || "world"}!`, "info");
|
||||
},
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
@@ -103,12 +105,12 @@ pi -e ./my-extension.ts
|
||||
|
||||
Extensions are auto-discovered from:
|
||||
|
||||
| Location | Scope |
|
||||
|----------|-------|
|
||||
| `~/.omp/agent/extensions/*.ts` | Global (all projects) |
|
||||
| `~/.omp/agent/extensions/*/index.ts` | Global (subdirectory) |
|
||||
| `.omp/extensions/*.ts` | Project-local |
|
||||
| `.omp/extensions/*/index.ts` | Project-local (subdirectory) |
|
||||
| Location | Scope |
|
||||
| ------------------------------------ | ---------------------------- |
|
||||
| `~/.omp/agent/extensions/*.ts` | Global (all projects) |
|
||||
| `~/.omp/agent/extensions/*/index.ts` | Global (subdirectory) |
|
||||
| `.omp/extensions/*.ts` | Project-local |
|
||||
| `.omp/extensions/*/index.ts` | Project-local (subdirectory) |
|
||||
|
||||
Legacy `.pi` directories are supported as aliases for the `.omp` paths above.
|
||||
|
||||
@@ -116,7 +118,7 @@ Additional paths via `settings.json`:
|
||||
|
||||
```json
|
||||
{
|
||||
"extensions": ["/path/to/extension.ts", "/path/to/extension/dir"]
|
||||
"extensions": ["/path/to/extension.ts", "/path/to/extension/dir"]
|
||||
}
|
||||
```
|
||||
|
||||
@@ -142,17 +144,18 @@ Additional paths via `settings.json`:
|
||||
```json
|
||||
// my-extension-pack/package.json
|
||||
{
|
||||
"name": "my-extension-pack",
|
||||
"dependencies": {
|
||||
"zod": "^3.0.0"
|
||||
},
|
||||
"omp": {
|
||||
"extensions": ["./src/safety-gates.ts", "./src/custom-tools.ts"]
|
||||
}
|
||||
"name": "my-extension-pack",
|
||||
"dependencies": {
|
||||
"zod": "^3.0.0"
|
||||
},
|
||||
"omp": {
|
||||
"extensions": ["./src/safety-gates.ts", "./src/custom-tools.ts"]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
The `package.json` approach enables:
|
||||
|
||||
- Multiple extensions from one package
|
||||
- Third-party npm dependencies (resolved via jiti)
|
||||
- Nested source structure (no depth limit within the package)
|
||||
@@ -160,12 +163,12 @@ The `package.json` approach enables:
|
||||
|
||||
## Available Imports
|
||||
|
||||
| Package | Purpose |
|
||||
|---------|---------|
|
||||
| Package | Purpose |
|
||||
| --------------------------- | ------------------------------------------------------------ |
|
||||
| `@oh-my-pi/pi-coding-agent` | Extension types (`ExtensionAPI`, `ExtensionContext`, events) |
|
||||
| `@sinclair/typebox` | Schema definitions for tool parameters |
|
||||
| `@oh-my-pi/pi-ai` | AI utilities (`StringEnum` for Google-compatible enums) |
|
||||
| `@oh-my-pi/pi-tui` | TUI components for custom rendering |
|
||||
| `@sinclair/typebox` | Schema definitions for tool parameters |
|
||||
| `@mariozechner/pi-ai` | AI utilities (`StringEnum` for Google-compatible enums) |
|
||||
| `@oh-my-pi/pi-tui` | TUI components for custom rendering |
|
||||
|
||||
npm dependencies work too. Add a `package.json` next to your extension (or in a parent directory), run `npm install`, and imports from `node_modules/` are resolved automatically.
|
||||
|
||||
@@ -232,14 +235,14 @@ Extensions are loaded via [jiti](https://github.com/unjs/jiti), so TypeScript wo
|
||||
```json
|
||||
// package.json
|
||||
{
|
||||
"name": "my-extension",
|
||||
"dependencies": {
|
||||
"zod": "^3.0.0",
|
||||
"chalk": "^5.0.0"
|
||||
},
|
||||
"pi": {
|
||||
"extensions": ["./src/index.ts"]
|
||||
}
|
||||
"name": "my-extension",
|
||||
"dependencies": {
|
||||
"zod": "^3.0.0",
|
||||
"chalk": "^5.0.0"
|
||||
},
|
||||
"pi": {
|
||||
"extensions": ["./src/index.ts"]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
@@ -304,7 +307,7 @@ Fired on initial session load.
|
||||
|
||||
```typescript
|
||||
pi.on("session_start", async (_event, ctx) => {
|
||||
ctx.ui.notify(`Session: ${ctx.sessionManager.getSessionFile() ?? "ephemeral"}`, "info");
|
||||
ctx.ui.notify(`Session: ${ctx.sessionManager.getSessionFile() ?? "ephemeral"}`, "info");
|
||||
});
|
||||
```
|
||||
|
||||
@@ -314,18 +317,18 @@ Fired when starting a new session (`/new`) or switching sessions (`/resume`).
|
||||
|
||||
```typescript
|
||||
pi.on("session_before_switch", async (event, ctx) => {
|
||||
// event.reason - "new" or "resume"
|
||||
// event.targetSessionFile - session we're switching to (only for "resume")
|
||||
// event.reason - "new" or "resume"
|
||||
// event.targetSessionFile - session we're switching to (only for "resume")
|
||||
|
||||
if (event.reason === "new") {
|
||||
const ok = await ctx.ui.confirm("Clear?", "Delete all messages?");
|
||||
if (!ok) return { cancel: true };
|
||||
}
|
||||
if (event.reason === "new") {
|
||||
const ok = await ctx.ui.confirm("Clear?", "Delete all messages?");
|
||||
if (!ok) return { cancel: true };
|
||||
}
|
||||
});
|
||||
|
||||
pi.on("session_switch", async (event, ctx) => {
|
||||
// event.reason - "new" or "resume"
|
||||
// event.previousSessionFile - session we came from
|
||||
// event.reason - "new" or "resume"
|
||||
// event.previousSessionFile - session we came from
|
||||
});
|
||||
```
|
||||
|
||||
@@ -335,14 +338,14 @@ Fired when branching via `/branch`.
|
||||
|
||||
```typescript
|
||||
pi.on("session_before_branch", async (event, ctx) => {
|
||||
// event.entryId - ID of the entry being branched from
|
||||
return { cancel: true }; // Cancel branch
|
||||
// OR
|
||||
return { skipConversationRestore: true }; // Branch but don't rewind messages
|
||||
// event.entryId - ID of the entry being branched from
|
||||
return { cancel: true }; // Cancel branch
|
||||
// OR
|
||||
return { skipConversationRestore: true }; // Branch but don't rewind messages
|
||||
});
|
||||
|
||||
pi.on("session_branch", async (event, ctx) => {
|
||||
// event.previousSessionFile - previous session file
|
||||
// event.previousSessionFile - previous session file
|
||||
});
|
||||
```
|
||||
|
||||
@@ -352,24 +355,24 @@ Fired on compaction. See [compaction.md](compaction.md) for details.
|
||||
|
||||
```typescript
|
||||
pi.on("session_before_compact", async (event, ctx) => {
|
||||
const { preparation, branchEntries, customInstructions, signal } = event;
|
||||
const { preparation, branchEntries, customInstructions, signal } = event;
|
||||
|
||||
// Cancel:
|
||||
return { cancel: true };
|
||||
// Cancel:
|
||||
return { cancel: true };
|
||||
|
||||
// Custom summary:
|
||||
return {
|
||||
compaction: {
|
||||
summary: "...",
|
||||
firstKeptEntryId: preparation.firstKeptEntryId,
|
||||
tokensBefore: preparation.tokensBefore,
|
||||
}
|
||||
};
|
||||
// Custom summary:
|
||||
return {
|
||||
compaction: {
|
||||
summary: "...",
|
||||
firstKeptEntryId: preparation.firstKeptEntryId,
|
||||
tokensBefore: preparation.tokensBefore,
|
||||
},
|
||||
};
|
||||
});
|
||||
|
||||
pi.on("session_compact", async (event, ctx) => {
|
||||
// event.compactionEntry - the saved compaction
|
||||
// event.fromExtension - whether extension provided it
|
||||
// event.compactionEntry - the saved compaction
|
||||
// event.fromExtension - whether extension provided it
|
||||
});
|
||||
```
|
||||
|
||||
@@ -379,14 +382,14 @@ Fired on `/tree` navigation.
|
||||
|
||||
```typescript
|
||||
pi.on("session_before_tree", async (event, ctx) => {
|
||||
const { preparation, signal } = event;
|
||||
return { cancel: true };
|
||||
// OR provide custom summary:
|
||||
return { summary: { summary: "...", details: {} } };
|
||||
const { preparation, signal } = event;
|
||||
return { cancel: true };
|
||||
// OR provide custom summary:
|
||||
return { summary: { summary: "...", details: {} } };
|
||||
});
|
||||
|
||||
pi.on("session_tree", async (event, ctx) => {
|
||||
// event.newLeafId, oldLeafId, summaryEntry, fromExtension
|
||||
// event.newLeafId, oldLeafId, summaryEntry, fromExtension
|
||||
});
|
||||
```
|
||||
|
||||
@@ -396,7 +399,7 @@ Fired on exit (Ctrl+C, Ctrl+D, SIGTERM).
|
||||
|
||||
```typescript
|
||||
pi.on("session_shutdown", async (_event, ctx) => {
|
||||
// Cleanup, save state, etc.
|
||||
// Cleanup, save state, etc.
|
||||
});
|
||||
```
|
||||
|
||||
@@ -408,19 +411,19 @@ Fired after user submits prompt, before agent loop. Can inject a message and/or
|
||||
|
||||
```typescript
|
||||
pi.on("before_agent_start", async (event, ctx) => {
|
||||
// event.prompt - user's prompt text
|
||||
// event.images - attached images (if any)
|
||||
// event.prompt - user's prompt text
|
||||
// event.images - attached images (if any)
|
||||
|
||||
return {
|
||||
// Inject a persistent message (stored in session, sent to LLM)
|
||||
message: {
|
||||
customType: "my-extension",
|
||||
content: "Additional context for the LLM",
|
||||
display: true,
|
||||
},
|
||||
// Append to system prompt for this turn only
|
||||
systemPromptAppend: "Extra instructions for this turn...",
|
||||
};
|
||||
return {
|
||||
// Inject a persistent message (stored in session, sent to LLM)
|
||||
message: {
|
||||
customType: "my-extension",
|
||||
content: "Additional context for the LLM",
|
||||
display: true,
|
||||
},
|
||||
// Append to system prompt for this turn only
|
||||
systemPromptAppend: "Extra instructions for this turn...",
|
||||
};
|
||||
});
|
||||
```
|
||||
|
||||
@@ -432,7 +435,7 @@ Fired once per user prompt.
|
||||
pi.on("agent_start", async (_event, ctx) => {});
|
||||
|
||||
pi.on("agent_end", async (event, ctx) => {
|
||||
// event.messages - messages from this prompt
|
||||
// event.messages - messages from this prompt
|
||||
});
|
||||
```
|
||||
|
||||
@@ -442,11 +445,11 @@ Fired for each turn (one LLM response + tool calls).
|
||||
|
||||
```typescript
|
||||
pi.on("turn_start", async (event, ctx) => {
|
||||
// event.turnIndex, event.timestamp
|
||||
// event.turnIndex, event.timestamp
|
||||
});
|
||||
|
||||
pi.on("turn_end", async (event, ctx) => {
|
||||
// event.turnIndex, event.message, event.toolResults
|
||||
// event.turnIndex, event.message, event.toolResults
|
||||
});
|
||||
```
|
||||
|
||||
@@ -456,9 +459,9 @@ Fired before each LLM call. Modify messages non-destructively.
|
||||
|
||||
```typescript
|
||||
pi.on("context", async (event, ctx) => {
|
||||
// event.messages - deep copy, safe to modify
|
||||
const filtered = event.messages.filter(m => !shouldPrune(m));
|
||||
return { messages: filtered };
|
||||
// event.messages - deep copy, safe to modify
|
||||
const filtered = event.messages.filter((m) => !shouldPrune(m));
|
||||
return { messages: filtered };
|
||||
});
|
||||
```
|
||||
|
||||
@@ -470,13 +473,13 @@ Fired before tool executes. **Can block.**
|
||||
|
||||
```typescript
|
||||
pi.on("tool_call", async (event, ctx) => {
|
||||
// event.toolName - "bash", "read", "write", "edit", etc.
|
||||
// event.toolCallId
|
||||
// event.input - tool parameters
|
||||
// event.toolName - "bash", "read", "write", "edit", etc.
|
||||
// event.toolCallId
|
||||
// event.input - tool parameters
|
||||
|
||||
if (shouldBlock(event)) {
|
||||
return { block: true, reason: "Not allowed" };
|
||||
}
|
||||
if (shouldBlock(event)) {
|
||||
return { block: true, reason: "Not allowed" };
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
@@ -521,9 +524,9 @@ Current working directory.
|
||||
Read-only access to session state:
|
||||
|
||||
```typescript
|
||||
ctx.sessionManager.getEntries() // All entries
|
||||
ctx.sessionManager.getBranch() // Current branch
|
||||
ctx.sessionManager.getLeafId() // Current leaf entry ID
|
||||
ctx.sessionManager.getEntries(); // All entries
|
||||
ctx.sessionManager.getBranch(); // Current branch
|
||||
ctx.sessionManager.getLeafId(); // Current leaf entry ID
|
||||
```
|
||||
|
||||
### ctx.modelRegistry / ctx.model
|
||||
@@ -544,10 +547,10 @@ Wait for the agent to finish streaming:
|
||||
|
||||
```typescript
|
||||
pi.registerCommand("my-cmd", {
|
||||
handler: async (args, ctx) => {
|
||||
await ctx.waitForIdle();
|
||||
// Agent is now idle, safe to modify session
|
||||
},
|
||||
handler: async (args, ctx) => {
|
||||
await ctx.waitForIdle();
|
||||
// Agent is now idle, safe to modify session
|
||||
},
|
||||
});
|
||||
```
|
||||
|
||||
@@ -557,18 +560,18 @@ Create a new session:
|
||||
|
||||
```typescript
|
||||
const result = await ctx.newSession({
|
||||
parentSession: ctx.sessionManager.getSessionFile(),
|
||||
setup: async (sm) => {
|
||||
sm.appendMessage({
|
||||
role: "user",
|
||||
content: [{ type: "text", text: "Context from previous session..." }],
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
},
|
||||
parentSession: ctx.sessionManager.getSessionFile(),
|
||||
setup: async (sm) => {
|
||||
sm.appendMessage({
|
||||
role: "user",
|
||||
content: [{ type: "text", text: "Context from previous session..." }],
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
},
|
||||
});
|
||||
|
||||
if (result.cancelled) {
|
||||
// An extension cancelled the new session
|
||||
// An extension cancelled the new session
|
||||
}
|
||||
```
|
||||
|
||||
@@ -579,7 +582,7 @@ Branch from a specific entry:
|
||||
```typescript
|
||||
const result = await ctx.branch("entry-id-123");
|
||||
if (!result.cancelled) {
|
||||
// Now in the branched session
|
||||
// Now in the branched session
|
||||
}
|
||||
```
|
||||
|
||||
@@ -589,7 +592,7 @@ Navigate to a different point in the session tree:
|
||||
|
||||
```typescript
|
||||
const result = await ctx.navigateTree("entry-id-456", {
|
||||
summarize: true,
|
||||
summarize: true,
|
||||
});
|
||||
```
|
||||
|
||||
@@ -605,7 +608,7 @@ Register a custom tool callable by the LLM. See [Custom Tools](#custom-tools) fo
|
||||
|
||||
```typescript
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { StringEnum } from "@oh-my-pi/pi-ai";
|
||||
import { StringEnum } from "@mariozechner/pi-ai";
|
||||
|
||||
pi.registerTool({
|
||||
name: "my_tool",
|
||||
@@ -649,6 +652,7 @@ pi.sendMessage({
|
||||
```
|
||||
|
||||
**Options:**
|
||||
|
||||
- `deliverAs` - Delivery mode:
|
||||
- `"steer"` (default) - Interrupts streaming. Delivered after current tool finishes, remaining tools skipped.
|
||||
- `"followUp"` - Waits for agent to finish. Delivered only when agent has no more tool calls.
|
||||
@@ -664,11 +668,11 @@ pi.appendEntry("my-state", { count: 42 });
|
||||
|
||||
// Restore on reload
|
||||
pi.on("session_start", async (_event, ctx) => {
|
||||
for (const entry of ctx.sessionManager.getEntries()) {
|
||||
if (entry.type === "custom" && entry.customType === "my-state") {
|
||||
// Reconstruct from entry.data
|
||||
}
|
||||
}
|
||||
for (const entry of ctx.sessionManager.getEntries()) {
|
||||
if (entry.type === "custom" && entry.customType === "my-state") {
|
||||
// Reconstruct from entry.data
|
||||
}
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
@@ -678,11 +682,11 @@ Register a command:
|
||||
|
||||
```typescript
|
||||
pi.registerCommand("stats", {
|
||||
description: "Show session statistics",
|
||||
handler: async (args, ctx) => {
|
||||
const count = ctx.sessionManager.getEntries().length;
|
||||
ctx.ui.notify(`${count} entries`, "info");
|
||||
}
|
||||
description: "Show session statistics",
|
||||
handler: async (args, ctx) => {
|
||||
const count = ctx.sessionManager.getEntries().length;
|
||||
ctx.ui.notify(`${count} entries`, "info");
|
||||
},
|
||||
});
|
||||
```
|
||||
|
||||
@@ -696,10 +700,10 @@ Register a keyboard shortcut:
|
||||
|
||||
```typescript
|
||||
pi.registerShortcut("ctrl+shift+p", {
|
||||
description: "Toggle plan mode",
|
||||
handler: async (ctx) => {
|
||||
ctx.ui.notify("Toggled!");
|
||||
},
|
||||
description: "Toggle plan mode",
|
||||
handler: async (ctx) => {
|
||||
ctx.ui.notify("Toggled!");
|
||||
},
|
||||
});
|
||||
```
|
||||
|
||||
@@ -709,14 +713,14 @@ Register a CLI flag:
|
||||
|
||||
```typescript
|
||||
pi.registerFlag("--plan", {
|
||||
description: "Start in plan mode",
|
||||
type: "boolean",
|
||||
default: false,
|
||||
description: "Start in plan mode",
|
||||
type: "boolean",
|
||||
default: false,
|
||||
});
|
||||
|
||||
// Check value
|
||||
if (pi.getFlag("--plan")) {
|
||||
// Plan mode enabled
|
||||
// Plan mode enabled
|
||||
}
|
||||
```
|
||||
|
||||
@@ -734,7 +738,7 @@ const result = await pi.exec("git", ["status"], { signal, timeout: 5000 });
|
||||
Manage active tools:
|
||||
|
||||
```typescript
|
||||
const active = pi.getActiveTools(); // ["read", "bash", "edit", "write"]
|
||||
const active = pi.getActiveTools(); // ["read", "bash", "edit", "write"]
|
||||
pi.setActiveTools(["read", "bash"]); // Switch to read-only
|
||||
```
|
||||
|
||||
@@ -753,31 +757,31 @@ Extensions with state should store it in tool result `details` for proper branch
|
||||
|
||||
```typescript
|
||||
export default function (pi: ExtensionAPI) {
|
||||
let items: string[] = [];
|
||||
let items: string[] = [];
|
||||
|
||||
// Reconstruct state from session
|
||||
pi.on("session_start", async (_event, ctx) => {
|
||||
items = [];
|
||||
for (const entry of ctx.sessionManager.getBranch()) {
|
||||
if (entry.type === "message" && entry.message.role === "toolResult") {
|
||||
if (entry.message.toolName === "my_tool") {
|
||||
items = entry.message.details?.items ?? [];
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
// Reconstruct state from session
|
||||
pi.on("session_start", async (_event, ctx) => {
|
||||
items = [];
|
||||
for (const entry of ctx.sessionManager.getBranch()) {
|
||||
if (entry.type === "message" && entry.message.role === "toolResult") {
|
||||
if (entry.message.toolName === "my_tool") {
|
||||
items = entry.message.details?.items ?? [];
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
pi.registerTool({
|
||||
name: "my_tool",
|
||||
// ...
|
||||
async execute(toolCallId, params, onUpdate, ctx, signal) {
|
||||
items.push("new item");
|
||||
return {
|
||||
content: [{ type: "text", text: "Added" }],
|
||||
details: { items: [...items] }, // Store for reconstruction
|
||||
};
|
||||
},
|
||||
});
|
||||
pi.registerTool({
|
||||
name: "my_tool",
|
||||
// ...
|
||||
async execute(toolCallId, params, onUpdate, ctx, signal) {
|
||||
items.push("new item");
|
||||
return {
|
||||
content: [{ type: "text", text: "Added" }],
|
||||
details: { items: [...items] }, // Store for reconstruction
|
||||
};
|
||||
},
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
@@ -789,7 +793,7 @@ Register tools the LLM can call via `pi.registerTool()`. Tools appear in the sys
|
||||
|
||||
```typescript
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { StringEnum } from "@oh-my-pi/pi-ai";
|
||||
import { StringEnum } from "@mariozechner/pi-ai";
|
||||
import { Text } from "@oh-my-pi/pi-tui";
|
||||
|
||||
pi.registerTool({
|
||||
@@ -829,7 +833,7 @@ pi.registerTool({
|
||||
});
|
||||
```
|
||||
|
||||
**Important:** Use `StringEnum` from `@oh-my-pi/pi-ai` for string enums. `Type.Union`/`Type.Literal` doesn't work with Google's API.
|
||||
**Important:** Use `StringEnum` from `@mariozechner/pi-ai` for string enums. `Type.Union`/`Type.Literal` doesn't work with Google's API.
|
||||
|
||||
### Multiple Tools
|
||||
|
||||
@@ -910,6 +914,7 @@ renderResult(result, { expanded, isPartial }, theme) {
|
||||
#### Fallback
|
||||
|
||||
If `renderCall`/`renderResult` is not defined or throws:
|
||||
|
||||
- `renderCall`: Shows tool name
|
||||
- `renderResult`: Shows raw text from `content`
|
||||
|
||||
@@ -933,7 +938,7 @@ const name = await ctx.ui.input("Name:", "placeholder");
|
||||
const text = await ctx.ui.editor("Edit:", "prefilled text");
|
||||
|
||||
// Notification (non-blocking)
|
||||
ctx.ui.notify("Done!", "info"); // "info" | "warning" | "error"
|
||||
ctx.ui.notify("Done!", "info"); // "info" | "warning" | "error"
|
||||
```
|
||||
|
||||
### Widgets and Status
|
||||
@@ -941,12 +946,12 @@ ctx.ui.notify("Done!", "info"); // "info" | "warning" | "error"
|
||||
```typescript
|
||||
// Status in footer (persistent until cleared)
|
||||
ctx.ui.setStatus("my-ext", "Processing...");
|
||||
ctx.ui.setStatus("my-ext", undefined); // Clear
|
||||
ctx.ui.setStatus("my-ext", undefined); // Clear
|
||||
|
||||
// Widget above editor (string array or factory function)
|
||||
ctx.ui.setWidget("my-widget", ["Line 1", "Line 2"]);
|
||||
ctx.ui.setWidget("my-widget", (tui, theme) => new Text(theme.fg("accent", "Custom"), 0, 0));
|
||||
ctx.ui.setWidget("my-widget", undefined); // Clear
|
||||
ctx.ui.setWidget("my-widget", undefined); // Clear
|
||||
|
||||
// Terminal title
|
||||
ctx.ui.setTitle("pi - my-project");
|
||||
@@ -964,23 +969,24 @@ For complex UI, use `ctx.ui.custom()`. This temporarily replaces the editor with
|
||||
import { Text, Component } from "@oh-my-pi/pi-tui";
|
||||
|
||||
const result = await ctx.ui.custom<boolean>((tui, theme, done) => {
|
||||
const text = new Text("Press Enter to confirm, Escape to cancel", 1, 1);
|
||||
const text = new Text("Press Enter to confirm, Escape to cancel", 1, 1);
|
||||
|
||||
text.onKey = (key) => {
|
||||
if (key === "return") done(true);
|
||||
if (key === "escape") done(false);
|
||||
return true;
|
||||
};
|
||||
text.onKey = (key) => {
|
||||
if (key === "return") done(true);
|
||||
if (key === "escape") done(false);
|
||||
return true;
|
||||
};
|
||||
|
||||
return text;
|
||||
return text;
|
||||
});
|
||||
|
||||
if (result) {
|
||||
// User pressed Enter
|
||||
// User pressed Enter
|
||||
}
|
||||
```
|
||||
|
||||
The callback receives:
|
||||
|
||||
- `tui` - TUI instance (for screen dimensions, focus management)
|
||||
- `theme` - Current theme for styling
|
||||
- `done(value)` - Call to close component and return value
|
||||
@@ -995,15 +1001,15 @@ Register a custom renderer for messages with your `customType`:
|
||||
import { Text } from "@oh-my-pi/pi-tui";
|
||||
|
||||
pi.registerMessageRenderer("my-extension", (message, options, theme) => {
|
||||
const { expanded } = options;
|
||||
let text = theme.fg("accent", `[${message.customType}] `);
|
||||
text += message.content;
|
||||
const { expanded } = options;
|
||||
let text = theme.fg("accent", `[${message.customType}] `);
|
||||
text += message.content;
|
||||
|
||||
if (expanded && message.details) {
|
||||
text += "\n" + theme.fg("dim", JSON.stringify(message.details, null, 2));
|
||||
}
|
||||
if (expanded && message.details) {
|
||||
text += "\n" + theme.fg("dim", JSON.stringify(message.details, null, 2));
|
||||
}
|
||||
|
||||
return new Text(text, 0, 0);
|
||||
return new Text(text, 0, 0);
|
||||
});
|
||||
```
|
||||
|
||||
@@ -1024,18 +1030,18 @@ All render functions receive a `theme` object:
|
||||
|
||||
```typescript
|
||||
// Foreground colors
|
||||
theme.fg("toolTitle", text) // Tool names
|
||||
theme.fg("accent", text) // Highlights
|
||||
theme.fg("success", text) // Success (green)
|
||||
theme.fg("error", text) // Errors (red)
|
||||
theme.fg("warning", text) // Warnings (yellow)
|
||||
theme.fg("muted", text) // Secondary text
|
||||
theme.fg("dim", text) // Tertiary text
|
||||
theme.fg("toolTitle", text); // Tool names
|
||||
theme.fg("accent", text); // Highlights
|
||||
theme.fg("success", text); // Success (green)
|
||||
theme.fg("error", text); // Errors (red)
|
||||
theme.fg("warning", text); // Warnings (yellow)
|
||||
theme.fg("muted", text); // Secondary text
|
||||
theme.fg("dim", text); // Tertiary text
|
||||
|
||||
// Text styles
|
||||
theme.bold(text)
|
||||
theme.italic(text)
|
||||
theme.strikethrough(text)
|
||||
theme.bold(text);
|
||||
theme.italic(text);
|
||||
theme.strikethrough(text);
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
@@ -1046,10 +1052,10 @@ theme.strikethrough(text)
|
||||
|
||||
## Mode Behavior
|
||||
|
||||
| Mode | UI Methods | Notes |
|
||||
|------|-----------|-------|
|
||||
| Interactive | Full TUI | Normal operation |
|
||||
| RPC | JSON protocol | Host handles UI |
|
||||
| Print (`-p`) | No-op | Extensions run but can't prompt |
|
||||
| Mode | UI Methods | Notes |
|
||||
| ------------ | ------------- | ------------------------------- |
|
||||
| Interactive | Full TUI | Normal operation |
|
||||
| RPC | JSON protocol | Host handles UI |
|
||||
| Print (`-p`) | No-op | Extensions run but can't prompt |
|
||||
|
||||
In print mode, check `ctx.hasUI` before using UI methods.
|
||||
|
||||
@@ -72,7 +72,7 @@ Additional paths via `settings.json`:
|
||||
| --------------------------------- | --------------------------------------------- |
|
||||
| `@oh-my-pi/pi-coding-agent/hooks` | Hook types (`HookAPI`, `HookContext`, events) |
|
||||
| `@oh-my-pi/pi-coding-agent` | Additional types if needed |
|
||||
| `@oh-my-pi/pi-ai` | AI utilities |
|
||||
| `@mariozechner/pi-ai` | AI utilities |
|
||||
| `@oh-my-pi/pi-tui` | TUI components |
|
||||
|
||||
Node.js built-ins (`node:fs`, `node:path`, etc.) are also available.
|
||||
@@ -548,7 +548,7 @@ Current model, or `undefined` if none selected yet. Use for LLM calls in hooks:
|
||||
```typescript
|
||||
if (ctx.model) {
|
||||
const apiKey = await ctx.modelRegistry.getApiKey(ctx.model);
|
||||
// Use with @oh-my-pi/pi-ai complete()
|
||||
// Use with @mariozechner/pi-ai complete()
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
@@ -248,7 +248,7 @@ const { session } = await createAgentSession({
|
||||
### Model
|
||||
|
||||
```typescript
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import { discoverAuthStorage, discoverModels } from "@oh-my-pi/pi-coding-agent";
|
||||
|
||||
const authStorage = discoverAuthStorage();
|
||||
@@ -733,7 +733,7 @@ Project overrides global. Nested objects merge keys. Setters only modify global
|
||||
All discovery functions accept optional `cwd` and `agentDir` parameters.
|
||||
|
||||
```typescript
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import {
|
||||
AuthStorage,
|
||||
ModelRegistry,
|
||||
@@ -806,7 +806,7 @@ interface CreateAgentSessionResult {
|
||||
## Complete Example
|
||||
|
||||
```typescript
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import {
|
||||
AuthStorage,
|
||||
|
||||
@@ -63,7 +63,7 @@ See [docs/custom-tools.md](../../docs/custom-tools.md) for full documentation.
|
||||
|
||||
```typescript
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { StringEnum } from "@oh-my-pi/pi-ai";
|
||||
import { StringEnum } from "@mariozechner/pi-ai";
|
||||
import { Text } from "@oh-my-pi/pi-tui";
|
||||
import type { CustomToolFactory } from "@oh-my-pi/pi-coding-agent";
|
||||
|
||||
@@ -114,7 +114,7 @@ renderResult(result, { expanded, isPartial }, theme) {
|
||||
**Use StringEnum for string parameters** (required for Google API compatibility):
|
||||
|
||||
```typescript
|
||||
import { StringEnum } from "@oh-my-pi/pi-ai";
|
||||
import { StringEnum } from "@mariozechner/pi-ai";
|
||||
|
||||
// Good
|
||||
action: StringEnum(["list", "add"] as const);
|
||||
|
||||
@@ -15,8 +15,8 @@
|
||||
import * as fs from "node:fs";
|
||||
import * as os from "node:os";
|
||||
import * as path from "node:path";
|
||||
import type { Message } from "@mariozechner/pi-ai";
|
||||
import type { AgentToolResult } from "@oh-my-pi/pi-agent-core";
|
||||
import type { Message } from "@oh-my-pi/pi-ai";
|
||||
import type { CustomTool, CustomToolAPI, CustomToolFactory } from "@oh-my-pi/pi-coding-agent";
|
||||
import { type AgentConfig, type AgentScope, discoverAgents, formatAgentList } from "./agents";
|
||||
|
||||
|
||||
@@ -16,54 +16,54 @@ cp permission-gate.ts ~/.omp/agent/extensions/
|
||||
|
||||
### Lifecycle & Safety
|
||||
|
||||
| Extension | Description |
|
||||
|-----------|-------------|
|
||||
| `permission-gate.ts` | Prompts for confirmation before dangerous bash commands (rm -rf, sudo, etc.) |
|
||||
| `protected-paths.ts` | Blocks writes to protected paths (.env, .git/, node_modules/) |
|
||||
| `confirm-destructive.ts` | Confirms before destructive session actions (clear, switch, branch) |
|
||||
| `dirty-repo-guard.ts` | Prevents session changes with uncommitted git changes |
|
||||
| Extension | Description |
|
||||
| ------------------------ | ---------------------------------------------------------------------------- |
|
||||
| `permission-gate.ts` | Prompts for confirmation before dangerous bash commands (rm -rf, sudo, etc.) |
|
||||
| `protected-paths.ts` | Blocks writes to protected paths (.env, .git/, node_modules/) |
|
||||
| `confirm-destructive.ts` | Confirms before destructive session actions (clear, switch, branch) |
|
||||
| `dirty-repo-guard.ts` | Prevents session changes with uncommitted git changes |
|
||||
|
||||
### Custom Tools
|
||||
|
||||
| Extension | Description |
|
||||
|-----------|-------------|
|
||||
| `todo.ts` | Todo list tool + `/todos` command with custom rendering and state persistence |
|
||||
| `hello.ts` | Minimal custom tool example |
|
||||
| `question.ts` | Demonstrates `ctx.ui.select()` for asking the user questions |
|
||||
| `subagent/` | Delegate tasks to specialized subagents with isolated context windows |
|
||||
| Extension | Description |
|
||||
| ------------- | ----------------------------------------------------------------------------- |
|
||||
| `todo.ts` | Todo list tool + `/todos` command with custom rendering and state persistence |
|
||||
| `hello.ts` | Minimal custom tool example |
|
||||
| `question.ts` | Demonstrates `ctx.ui.select()` for asking the user questions |
|
||||
| `subagent/` | Delegate tasks to specialized subagents with isolated context windows |
|
||||
|
||||
### Commands & UI
|
||||
|
||||
| Extension | Description |
|
||||
|-----------|-------------|
|
||||
| `plan-mode.ts` | Claude Code-style plan mode for read-only exploration with `/plan` command |
|
||||
| `tools.ts` | Interactive `/tools` command to enable/disable tools with session persistence |
|
||||
| `handoff.ts` | Transfer context to a new focused session via `/handoff <goal>` |
|
||||
| `qna.ts` | Extracts questions from last response into editor via `ctx.ui.setEditorText()` |
|
||||
| `status-line.ts` | Shows turn progress in footer via `ctx.ui.setStatus()` with themed colors |
|
||||
| `snake.ts` | Snake game with custom UI, keyboard handling, and session persistence |
|
||||
| Extension | Description |
|
||||
| ---------------- | ------------------------------------------------------------------------------ |
|
||||
| `plan-mode.ts` | Claude Code-style plan mode for read-only exploration with `/plan` command |
|
||||
| `tools.ts` | Interactive `/tools` command to enable/disable tools with session persistence |
|
||||
| `handoff.ts` | Transfer context to a new focused session via `/handoff <goal>` |
|
||||
| `qna.ts` | Extracts questions from last response into editor via `ctx.ui.setEditorText()` |
|
||||
| `status-line.ts` | Shows turn progress in footer via `ctx.ui.setStatus()` with themed colors |
|
||||
| `snake.ts` | Snake game with custom UI, keyboard handling, and session persistence |
|
||||
|
||||
### Git Integration
|
||||
|
||||
| Extension | Description |
|
||||
|-----------|-------------|
|
||||
| `git-checkpoint.ts` | Creates git stash checkpoints at each turn for code restoration on branch |
|
||||
| `auto-commit-on-exit.ts` | Auto-commits on exit using last assistant message for commit message |
|
||||
| Extension | Description |
|
||||
| ------------------------ | ------------------------------------------------------------------------- |
|
||||
| `git-checkpoint.ts` | Creates git stash checkpoints at each turn for code restoration on branch |
|
||||
| `auto-commit-on-exit.ts` | Auto-commits on exit using last assistant message for commit message |
|
||||
|
||||
### System Prompt & Compaction
|
||||
|
||||
| Extension | Description |
|
||||
|-----------|-------------|
|
||||
| `pirate.ts` | Demonstrates `systemPromptAppend` to dynamically modify system prompt |
|
||||
| `custom-compaction.ts` | Custom compaction that summarizes entire conversation |
|
||||
| Extension | Description |
|
||||
| ---------------------- | --------------------------------------------------------------------- |
|
||||
| `pirate.ts` | Demonstrates `systemPromptAppend` to dynamically modify system prompt |
|
||||
| `custom-compaction.ts` | Custom compaction that summarizes entire conversation |
|
||||
|
||||
### External Dependencies
|
||||
|
||||
| Extension | Description |
|
||||
|-----------|-------------|
|
||||
| Extension | Description |
|
||||
| ----------------- | ------------------------------------------------------------------------- |
|
||||
| `chalk-logger.ts` | Uses chalk from parent node_modules (demonstrates jiti module resolution) |
|
||||
| `with-deps/` | Extension with its own package.json and dependencies |
|
||||
| `file-trigger.ts` | Watches a trigger file and injects contents into conversation |
|
||||
| `with-deps/` | Extension with its own package.json and dependencies |
|
||||
| `file-trigger.ts` | Watches a trigger file and injects contents into conversation |
|
||||
|
||||
## Writing Extensions
|
||||
|
||||
@@ -74,68 +74,70 @@ import type { ExtensionAPI } from "@oh-my-pi/pi-coding-agent";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
|
||||
export default function (pi: ExtensionAPI) {
|
||||
// Subscribe to lifecycle events
|
||||
pi.on("tool_call", async (event, ctx) => {
|
||||
if (event.toolName === "bash" && event.input.command?.includes("rm -rf")) {
|
||||
const ok = await ctx.ui.confirm("Dangerous!", "Allow rm -rf?");
|
||||
if (!ok) return { block: true, reason: "Blocked by user" };
|
||||
}
|
||||
});
|
||||
// Subscribe to lifecycle events
|
||||
pi.on("tool_call", async (event, ctx) => {
|
||||
if (event.toolName === "bash" && event.input.command?.includes("rm -rf")) {
|
||||
const ok = await ctx.ui.confirm("Dangerous!", "Allow rm -rf?");
|
||||
if (!ok) return { block: true, reason: "Blocked by user" };
|
||||
}
|
||||
});
|
||||
|
||||
// Register custom tools
|
||||
pi.registerTool({
|
||||
name: "greet",
|
||||
label: "Greeting",
|
||||
description: "Generate a greeting",
|
||||
parameters: Type.Object({
|
||||
name: Type.String({ description: "Name to greet" }),
|
||||
}),
|
||||
async execute(toolCallId, params, onUpdate, ctx, signal) {
|
||||
return {
|
||||
content: [{ type: "text", text: `Hello, ${params.name}!` }],
|
||||
details: {},
|
||||
};
|
||||
},
|
||||
});
|
||||
// Register custom tools
|
||||
pi.registerTool({
|
||||
name: "greet",
|
||||
label: "Greeting",
|
||||
description: "Generate a greeting",
|
||||
parameters: Type.Object({
|
||||
name: Type.String({ description: "Name to greet" }),
|
||||
}),
|
||||
async execute(toolCallId, params, onUpdate, ctx, signal) {
|
||||
return {
|
||||
content: [{ type: "text", text: `Hello, ${params.name}!` }],
|
||||
details: {},
|
||||
};
|
||||
},
|
||||
});
|
||||
|
||||
// Register commands
|
||||
pi.registerCommand("hello", {
|
||||
description: "Say hello",
|
||||
handler: async (args, ctx) => {
|
||||
ctx.ui.notify("Hello!", "info");
|
||||
},
|
||||
});
|
||||
// Register commands
|
||||
pi.registerCommand("hello", {
|
||||
description: "Say hello",
|
||||
handler: async (args, ctx) => {
|
||||
ctx.ui.notify("Hello!", "info");
|
||||
},
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
## Key Patterns
|
||||
|
||||
**Use StringEnum for string parameters** (required for Google API compatibility):
|
||||
|
||||
```typescript
|
||||
import { StringEnum } from "@oh-my-pi/pi-ai";
|
||||
import { StringEnum } from "@mariozechner/pi-ai";
|
||||
|
||||
// Good
|
||||
action: StringEnum(["list", "add"] as const)
|
||||
action: StringEnum(["list", "add"] as const);
|
||||
|
||||
// Bad - doesn't work with Google
|
||||
action: Type.Union([Type.Literal("list"), Type.Literal("add")])
|
||||
action: Type.Union([Type.Literal("list"), Type.Literal("add")]);
|
||||
```
|
||||
|
||||
**State persistence via details:**
|
||||
|
||||
```typescript
|
||||
// Store state in tool result details for proper branching support
|
||||
return {
|
||||
content: [{ type: "text", text: "Done" }],
|
||||
details: { todos: [...todos], nextId }, // Persisted in session
|
||||
content: [{ type: "text", text: "Done" }],
|
||||
details: { todos: [...todos], nextId }, // Persisted in session
|
||||
};
|
||||
|
||||
// Reconstruct on session events
|
||||
pi.on("session_start", async (_event, ctx) => {
|
||||
for (const entry of ctx.sessionManager.getBranch()) {
|
||||
if (entry.type === "message" && entry.message.toolName === "my_tool") {
|
||||
const details = entry.message.details;
|
||||
// Reconstruct state from details
|
||||
}
|
||||
}
|
||||
for (const entry of ctx.sessionManager.getBranch()) {
|
||||
if (entry.type === "message" && entry.message.toolName === "my_tool") {
|
||||
const details = entry.message.details;
|
||||
// Reconstruct state from details
|
||||
}
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
* correct for that point in history.
|
||||
*/
|
||||
|
||||
import { StringEnum } from "@oh-my-pi/pi-ai";
|
||||
import { StringEnum } from "@mariozechner/pi-ai";
|
||||
import type { ExtensionAPI, ExtensionContext, Theme } from "@oh-my-pi/pi-coding-agent";
|
||||
import { matchesKey, Text, truncateToWidth } from "@oh-my-pi/pi-tui";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
@@ -261,10 +261,7 @@ export default function (pi: ExtensionAPI) {
|
||||
case "add": {
|
||||
const added = todoList[todoList.length - 1];
|
||||
return new Text(
|
||||
theme.fg("success", "✓ Added ") +
|
||||
theme.fg("accent", `#${added.id}`) +
|
||||
" " +
|
||||
theme.fg("muted", added.text),
|
||||
`${theme.fg("success", "✓ Added ") + theme.fg("accent", `#${added.id}`)} ${theme.fg("muted", added.text)}`,
|
||||
0,
|
||||
0,
|
||||
);
|
||||
|
||||
@@ -13,7 +13,7 @@
|
||||
* omp --hook examples/hooks/custom-compaction.ts
|
||||
*/
|
||||
|
||||
import { complete, getModel } from "@oh-my-pi/pi-ai";
|
||||
import { complete, getModel } from "@mariozechner/pi-ai";
|
||||
import type { HookAPI } from "@oh-my-pi/pi-coding-agent";
|
||||
import { convertToLlm, serializeConversation } from "@oh-my-pi/pi-coding-agent";
|
||||
|
||||
|
||||
@@ -12,7 +12,7 @@
|
||||
* The generated prompt appears as a draft in the editor for review/editing.
|
||||
*/
|
||||
|
||||
import { complete, type Message } from "@oh-my-pi/pi-ai";
|
||||
import { complete, type Message } from "@mariozechner/pi-ai";
|
||||
import type { HookAPI, SessionEntry } from "@oh-my-pi/pi-coding-agent";
|
||||
import { BorderedLoader, convertToLlm, serializeConversation } from "@oh-my-pi/pi-coding-agent";
|
||||
|
||||
|
||||
@@ -7,7 +7,7 @@
|
||||
* 3. Loads the result into the editor for user to fill in answers
|
||||
*/
|
||||
|
||||
import { complete, type UserMessage } from "@oh-my-pi/pi-ai";
|
||||
import { complete, type UserMessage } from "@mariozechner/pi-ai";
|
||||
import type { HookAPI } from "@oh-my-pi/pi-coding-agent";
|
||||
import { BorderedLoader } from "@oh-my-pi/pi-coding-agent";
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@
|
||||
* Shows how to select a specific model and thinking level.
|
||||
*/
|
||||
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import { createAgentSession, discoverAuthStorage, discoverModels } from "@oh-my-pi/pi-coding-agent";
|
||||
|
||||
// Set up auth storage and model registry
|
||||
|
||||
@@ -8,7 +8,7 @@
|
||||
* paths relative to your cwd.
|
||||
*/
|
||||
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import {
|
||||
AuthStorage,
|
||||
type CustomTool,
|
||||
|
||||
@@ -29,7 +29,7 @@ npx tsx examples/sdk/01-minimal.ts
|
||||
## Quick Reference
|
||||
|
||||
```typescript
|
||||
import { getModel } from "@oh-my-pi/pi-ai";
|
||||
import { getModel } from "@mariozechner/pi-ai";
|
||||
import {
|
||||
AuthStorage,
|
||||
createAgentSession,
|
||||
|
||||
@@ -39,8 +39,8 @@
|
||||
"prepublishOnly": "bun run generate-template && bun run clean && bun run build"
|
||||
},
|
||||
"dependencies": {
|
||||
"@mariozechner/pi-ai": "^0.37.4",
|
||||
"@oh-my-pi/pi-agent-core": "workspace:*",
|
||||
"@oh-my-pi/pi-ai": "workspace:*",
|
||||
"@oh-my-pi/pi-git-tool": "workspace:*",
|
||||
"@oh-my-pi/pi-tui": "workspace:*",
|
||||
"@openai/agents": "^0.3.7",
|
||||
|
||||
@@ -4,7 +4,7 @@
|
||||
|
||||
import { existsSync, readFileSync, statSync } from "node:fs";
|
||||
import { resolve } from "node:path";
|
||||
import type { ImageContent } from "@oh-my-pi/pi-ai";
|
||||
import type { ImageContent } from "@mariozechner/pi-ai";
|
||||
import chalk from "chalk";
|
||||
import { resolveReadPath } from "../core/tools/path-utils";
|
||||
import { formatDimensionNote, resizeImage } from "../utils/image-resize";
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
* List available models with optional fuzzy search
|
||||
*/
|
||||
|
||||
import type { Api, Model } from "@oh-my-pi/pi-ai";
|
||||
import type { Api, Model } from "@mariozechner/pi-ai";
|
||||
import type { ModelRegistry } from "../core/model-registry";
|
||||
import { fuzzyFilter } from "../utils/fuzzy";
|
||||
|
||||
|
||||
@@ -13,9 +13,9 @@
|
||||
* Modes use this class and add their own I/O layer on top.
|
||||
*/
|
||||
|
||||
import type { AssistantMessage, ImageContent, Message, Model, TextContent, Usage } from "@mariozechner/pi-ai";
|
||||
import { isContextOverflow, modelsAreEqual, supportsXhigh } from "@mariozechner/pi-ai";
|
||||
import type { Agent, AgentEvent, AgentMessage, AgentState, AgentTool, ThinkingLevel } from "@oh-my-pi/pi-agent-core";
|
||||
import type { AssistantMessage, ImageContent, Message, Model, TextContent, Usage } from "@oh-my-pi/pi-ai";
|
||||
import { isContextOverflow, modelsAreEqual, supportsXhigh } from "@oh-my-pi/pi-ai";
|
||||
import type { Rule } from "../capability/rule";
|
||||
import { getAuthPath } from "../config";
|
||||
import { theme } from "../modes/interactive/theme/theme";
|
||||
|
||||
@@ -15,7 +15,7 @@ import {
|
||||
loginOpenAICodex,
|
||||
type OAuthCredentials,
|
||||
type OAuthProvider,
|
||||
} from "@oh-my-pi/pi-ai";
|
||||
} from "@mariozechner/pi-ai";
|
||||
import { logger } from "./logger";
|
||||
|
||||
export type ApiKeyCredential = {
|
||||
|
||||
@@ -5,9 +5,9 @@
|
||||
* a summary of the branch being left so context isn't lost.
|
||||
*/
|
||||
|
||||
import type { Model } from "@mariozechner/pi-ai";
|
||||
import { completeSimple } from "@mariozechner/pi-ai";
|
||||
import type { AgentMessage } from "@oh-my-pi/pi-agent-core";
|
||||
import type { Model } from "@oh-my-pi/pi-ai";
|
||||
import { completeSimple } from "@oh-my-pi/pi-ai";
|
||||
import branchSummaryPrompt from "../../prompts/branch-summary.md" with { type: "text" };
|
||||
import branchSummaryPreamble from "../../prompts/branch-summary-preamble.md" with { type: "text" };
|
||||
import {
|
||||
|
||||
@@ -5,9 +5,9 @@
|
||||
* and after compaction the session is reloaded.
|
||||
*/
|
||||
|
||||
import type { AssistantMessage, Model, Usage } from "@mariozechner/pi-ai";
|
||||
import { complete, completeSimple } from "@mariozechner/pi-ai";
|
||||
import type { AgentMessage } from "@oh-my-pi/pi-agent-core";
|
||||
import type { AssistantMessage, Model, Usage } from "@oh-my-pi/pi-ai";
|
||||
import { complete, completeSimple } from "@oh-my-pi/pi-ai";
|
||||
import compactionSummaryPrompt from "../../prompts/compaction-summary.md" with { type: "text" };
|
||||
import compactionTurnPrefixPrompt from "../../prompts/compaction-turn-prefix.md" with { type: "text" };
|
||||
import compactionUpdateSummaryPrompt from "../../prompts/compaction-update-summary.md" with { type: "text" };
|
||||
|
||||
@@ -2,8 +2,8 @@
|
||||
* Shared utilities for compaction and branch summarization.
|
||||
*/
|
||||
|
||||
import type { Message } from "@mariozechner/pi-ai";
|
||||
import type { AgentMessage } from "@oh-my-pi/pi-agent-core";
|
||||
import type { Message } from "@oh-my-pi/pi-ai";
|
||||
import summarizationSystemPrompt from "../../prompts/summarization-system.md" with { type: "text" };
|
||||
|
||||
// ============================================================================
|
||||
|
||||
@@ -5,8 +5,8 @@
|
||||
* They can provide custom rendering for tool calls and results in the TUI.
|
||||
*/
|
||||
|
||||
import type { Model } from "@mariozechner/pi-ai";
|
||||
import type { AgentToolResult, AgentToolUpdateCallback } from "@oh-my-pi/pi-agent-core";
|
||||
import type { Model } from "@oh-my-pi/pi-ai";
|
||||
import type { Component } from "@oh-my-pi/pi-tui";
|
||||
import type { Static, TSchema } from "@sinclair/typebox";
|
||||
import type { Theme } from "../../modes/interactive/theme/theme";
|
||||
|
||||
@@ -2,8 +2,8 @@
|
||||
* Extension runner - executes extensions and manages their lifecycle.
|
||||
*/
|
||||
|
||||
import type { ImageContent, Model } from "@mariozechner/pi-ai";
|
||||
import type { AgentMessage } from "@oh-my-pi/pi-agent-core";
|
||||
import type { ImageContent, Model } from "@oh-my-pi/pi-ai";
|
||||
import type { KeyId } from "@oh-my-pi/pi-tui";
|
||||
import { theme } from "../../modes/interactive/theme/theme";
|
||||
import type { ModelRegistry } from "../model-registry";
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user