743 lines
24 KiB
TypeScript
743 lines
24 KiB
TypeScript
import * as fs from "node:fs";
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import * as os from "node:os";
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import * as path from "node:path";
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import { $env, $pickenv } from "@oh-my-pi/pi-utils";
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import { getCustomApi } from "./api-registry";
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import type { Effort } from "./model-thinking";
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import {
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mapEffortToAnthropicAdaptiveEffort,
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mapEffortToGoogleThinkingLevel,
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requireSupportedEffort,
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} from "./model-thinking";
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import { type BedrockOptions, streamBedrock } from "./providers/amazon-bedrock";
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import { type AnthropicOptions, streamAnthropic } from "./providers/anthropic";
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import { streamAzureOpenAIResponses } from "./providers/azure-openai-responses";
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import { type CursorOptions, streamCursor } from "./providers/cursor";
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import { isGitLabDuoModel, streamGitLabDuo } from "./providers/gitlab-duo";
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import { type GoogleOptions, streamGoogle } from "./providers/google";
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import { type GoogleGeminiCliOptions, streamGoogleGeminiCli } from "./providers/google-gemini-cli";
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import { type GoogleVertexOptions, streamGoogleVertex } from "./providers/google-vertex";
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import { isKimiModel, streamKimi } from "./providers/kimi";
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import { type OllamaChatOptions, streamOllama } from "./providers/ollama";
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import { streamOpenAICodexResponses } from "./providers/openai-codex-responses";
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import { type OpenAICompletionsOptions, streamOpenAICompletions } from "./providers/openai-completions";
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import { streamOpenAIResponses } from "./providers/openai-responses";
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import { isSyntheticModel, streamSynthetic } from "./providers/synthetic";
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import type {
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Api,
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AssistantMessage,
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AssistantMessageEventStream,
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Context,
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Model,
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OptionsForApi,
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SimpleStreamOptions,
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StreamOptions,
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ThinkingBudgets,
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ToolChoice,
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} from "./types";
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import { isFoundryEnabled } from "./utils/foundry";
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let cachedVertexAdcCredentialsExists: boolean | null = null;
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function hasVertexAdcCredentials(): boolean {
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if (cachedVertexAdcCredentialsExists === null) {
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const gacPath = $env.GOOGLE_APPLICATION_CREDENTIALS;
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if (gacPath) {
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cachedVertexAdcCredentialsExists = fs.existsSync(gacPath);
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} else {
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cachedVertexAdcCredentialsExists = fs.existsSync(
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path.join(os.homedir(), ".config", "gcloud", "application_default_credentials.json"),
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);
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}
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}
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return cachedVertexAdcCredentialsExists;
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}
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type KeyResolver = string | (() => string | undefined);
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const serviceProviderMap: Record<string, KeyResolver> = {
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"alibaba-coding-plan": "ALIBABA_CODING_PLAN_API_KEY",
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openai: "OPENAI_API_KEY",
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google: "GEMINI_API_KEY",
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groq: "GROQ_API_KEY",
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cerebras: "CEREBRAS_API_KEY",
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xai: "XAI_API_KEY",
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fireworks: "FIREWORKS_API_KEY",
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openrouter: "OPENROUTER_API_KEY",
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kilo: "KILO_API_KEY",
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"vercel-ai-gateway": "AI_GATEWAY_API_KEY",
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zai: "ZAI_API_KEY",
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mistral: "MISTRAL_API_KEY",
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minimax: "MINIMAX_API_KEY",
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"minimax-code": "MINIMAX_CODE_API_KEY",
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"minimax-code-cn": "MINIMAX_CODE_CN_API_KEY",
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"opencode-go": "OPENCODE_API_KEY",
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"opencode-zen": "OPENCODE_API_KEY",
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cursor: "CURSOR_ACCESS_TOKEN",
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deepseek: "DEEPSEEK_API_KEY",
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"openai-codex": "OPENAI_CODEX_OAUTH_TOKEN",
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"azure-openai-responses": "AZURE_OPENAI_API_KEY",
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exa: "EXA_API_KEY",
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jina: "JINA_API_KEY",
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brave: "BRAVE_API_KEY",
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perplexity: "PERPLEXITY_API_KEY",
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tavily: "TAVILY_API_KEY",
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parallel: "PARALLEL_API_KEY",
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kagi: "KAGI_API_KEY",
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// GitHub Copilot uses GitHub personal access token
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"github-copilot": () => $pickenv("COPILOT_GITHUB_TOKEN", "GH_TOKEN", "GITHUB_TOKEN"),
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// Foundry mode optionally switches Anthropic auth to enterprise gateway credentials.
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anthropic: () =>
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isFoundryEnabled()
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? $pickenv("ANTHROPIC_FOUNDRY_API_KEY", "ANTHROPIC_OAUTH_TOKEN", "ANTHROPIC_API_KEY")
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: $pickenv("ANTHROPIC_OAUTH_TOKEN", "ANTHROPIC_API_KEY"),
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"gitlab-duo": "GITLAB_TOKEN",
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// Vertex AI supports either GOOGLE_CLOUD_API_KEY or Application Default Credentials.
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"google-vertex": () => {
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if ($env.GOOGLE_CLOUD_API_KEY) {
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return $env.GOOGLE_CLOUD_API_KEY;
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}
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const hasCredentials = hasVertexAdcCredentials();
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const hasProject = !!($env.GOOGLE_CLOUD_PROJECT || $env.GCLOUD_PROJECT);
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const hasLocation = !!$env.GOOGLE_CLOUD_LOCATION;
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if (hasCredentials && hasProject && hasLocation) {
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return "<authenticated>";
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}
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},
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// Amazon Bedrock supports multiple credential sources:
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// 1. AWS_PROFILE - named profile from ~/.aws/credentials
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// 2. AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY - standard IAM keys
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// 3. AWS_BEARER_TOKEN_BEDROCK - Bedrock API keys (bearer token)
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// 4. AWS_CONTAINER_CREDENTIALS_* - ECS/Task IAM role credentials
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// 5. AWS_WEB_IDENTITY_TOKEN_FILE + AWS_ROLE_ARN - IRSA (EKS) web identity
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"amazon-bedrock": () => {
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const hasEcsCredentials =
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!!$env.AWS_CONTAINER_CREDENTIALS_RELATIVE_URI || !!$env.AWS_CONTAINER_CREDENTIALS_FULL_URI;
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const hasWebIdentity = !!$env.AWS_WEB_IDENTITY_TOKEN_FILE && !!$env.AWS_ROLE_ARN;
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if (
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$env.AWS_PROFILE ||
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($env.AWS_ACCESS_KEY_ID && $env.AWS_SECRET_ACCESS_KEY) ||
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$env.AWS_BEARER_TOKEN_BEDROCK ||
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hasEcsCredentials ||
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hasWebIdentity
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) {
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return "<authenticated>";
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}
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},
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synthetic: "SYNTHETIC_API_KEY",
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"cloudflare-ai-gateway": "CLOUDFLARE_AI_GATEWAY_API_KEY",
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huggingface: () => $pickenv("HUGGINGFACE_HUB_TOKEN", "HF_TOKEN"),
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litellm: "LITELLM_API_KEY",
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moonshot: "MOONSHOT_API_KEY",
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nvidia: "NVIDIA_API_KEY",
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nanogpt: "NANO_GPT_API_KEY",
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"lm-studio": "LM_STUDIO_API_KEY",
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ollama: "OLLAMA_API_KEY",
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"ollama-cloud": "OLLAMA_CLOUD_API_KEY",
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"llama.cpp": "LLAMA_CPP_API_KEY",
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qianfan: "QIANFAN_API_KEY",
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"qwen-portal": () => $pickenv("QWEN_OAUTH_TOKEN", "QWEN_PORTAL_API_KEY"),
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together: "TOGETHER_API_KEY",
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zenmux: "ZENMUX_API_KEY",
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venice: "VENICE_API_KEY",
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vllm: "VLLM_API_KEY",
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xiaomi: "XIAOMI_API_KEY",
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};
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/**
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* Get API key for provider from known environment variables, e.g. OPENAI_API_KEY.
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*
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* Will not return API keys for providers that require OAuth tokens.
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* Checks Bun.env, then cwd/.env, then ~/.env.
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*/
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export function getEnvApiKey(provider: string): string | undefined {
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const resolver = serviceProviderMap[provider];
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if (typeof resolver === "string") {
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return $env[resolver];
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}
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return resolver?.();
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}
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export function stream<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: OptionsForApi<TApi>,
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): AssistantMessageEventStream {
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// Check custom API registry first (extension-provided APIs like "vertex-claude-api")
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const customApiProvider = getCustomApi(model.api);
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if (customApiProvider) {
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return customApiProvider.stream(model, context, options as StreamOptions);
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}
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if (isGitLabDuoModel(model)) {
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const apiKey = (options as StreamOptions | undefined)?.apiKey || getEnvApiKey(model.provider);
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if (!apiKey) {
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throw new Error(`No API key for provider: ${model.provider}`);
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}
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return streamGitLabDuo(model, context, {
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...(options as SimpleStreamOptions | undefined),
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apiKey,
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});
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}
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// Vertex AI uses Application Default Credentials, not API keys
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if (model.api === "google-vertex") {
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return streamGoogleVertex(model as Model<"google-vertex">, context, options as GoogleVertexOptions);
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} else if (model.api === "bedrock-converse-stream") {
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// Bedrock doesn't have any API keys instead it sources credentials from standard AWS env variables or from given AWS profile.
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return streamBedrock(model as Model<"bedrock-converse-stream">, context, (options || {}) as BedrockOptions);
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}
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const apiKey = options?.apiKey || getEnvApiKey(model.provider);
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if (!apiKey) {
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throw new Error(`No API key for provider: ${model.provider}`);
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}
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const providerOptions = { ...options, apiKey };
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const api: Api = model.api;
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switch (api) {
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case "anthropic-messages": {
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const anthropicOptions = providerOptions as AnthropicOptions;
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return streamAnthropic(model as Model<"anthropic-messages">, context, {
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...anthropicOptions,
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isOAuth: anthropicOptions.isOAuth ?? model.isOAuth,
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});
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}
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case "openai-completions":
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return streamOpenAICompletions(model as Model<"openai-completions">, context, providerOptions as any);
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case "openai-responses":
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return streamOpenAIResponses(model as Model<"openai-responses">, context, providerOptions as any);
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case "azure-openai-responses":
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return streamAzureOpenAIResponses(model as Model<"azure-openai-responses">, context, providerOptions as any);
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case "openai-codex-responses":
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return streamOpenAICodexResponses(model as Model<"openai-codex-responses">, context, providerOptions as any);
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case "google-generative-ai":
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return streamGoogle(model as Model<"google-generative-ai">, context, providerOptions);
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case "google-gemini-cli":
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return streamGoogleGeminiCli(
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model as Model<"google-gemini-cli">,
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context,
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providerOptions as GoogleGeminiCliOptions,
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);
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case "ollama-chat":
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return streamOllama(model as Model<"ollama-chat">, context, providerOptions as OllamaChatOptions);
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case "cursor-agent":
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return streamCursor(model as Model<"cursor-agent">, context, providerOptions as CursorOptions);
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default:
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throw new Error(`Unhandled API: ${api}`);
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}
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}
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export async function complete<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: OptionsForApi<TApi>,
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): Promise<AssistantMessage> {
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const s = stream(model, context, options);
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return s.result();
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}
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export function streamSimple<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: SimpleStreamOptions,
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): AssistantMessageEventStream {
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// Check custom API registry first (extension-provided APIs)
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const customApiProvider = getCustomApi(model.api);
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if (customApiProvider) {
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return customApiProvider.streamSimple(model, context, options);
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}
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// Vertex AI uses Application Default Credentials, not API keys
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if (model.api === "google-vertex") {
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const providerOptions = mapOptionsForApi(model, options, undefined);
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return stream(model, context, providerOptions);
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} else if (model.api === "bedrock-converse-stream") {
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// Bedrock doesn't have any API keys instead it sources credentials from standard AWS env variables or from given AWS profile.
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const providerOptions = mapOptionsForApi(model, options, undefined);
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return stream(model, context, providerOptions);
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}
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const apiKey = options?.apiKey || getEnvApiKey(model.provider);
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if (!apiKey) {
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throw new Error(`No API key for provider: ${model.provider}`);
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}
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// GitLab Duo - wraps Anthropic/OpenAI behind GitLab AI Gateway direct access tokens
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if (isGitLabDuoModel(model)) {
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return streamGitLabDuo(model, context, {
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...options,
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apiKey,
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});
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}
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// Kimi Code - route to dedicated handler that wraps OpenAI or Anthropic API
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if (isKimiModel(model)) {
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// Pass raw SimpleStreamOptions - streamKimi handles mapping internally
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return streamKimi(model as Model<"openai-completions">, context, {
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...options,
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apiKey,
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format: options?.kimiApiFormat ?? "anthropic",
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});
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}
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// Synthetic - route to dedicated handler that wraps OpenAI or Anthropic API
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if (isSyntheticModel(model)) {
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// Pass raw SimpleStreamOptions - streamSynthetic handles mapping internally
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return streamSynthetic(model as Model<"openai-completions">, context, {
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...options,
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apiKey,
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format: options?.syntheticApiFormat ?? "openai", // Default to OpenAI format
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});
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}
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const providerOptions = mapOptionsForApi(model, options, apiKey);
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return stream(model, context, providerOptions);
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}
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export async function completeSimple<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: SimpleStreamOptions,
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): Promise<AssistantMessage> {
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const s = streamSimple(model, context, options);
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return s.result();
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}
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const MIN_OUTPUT_TOKENS = 1024;
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export const OUTPUT_FALLBACK_BUFFER = 4000;
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const ANTHROPIC_USE_INTERLEAVED_THINKING = Bun.env.PI_NO_INTERLEAVED_THINKING !== "1";
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export const ANTHROPIC_THINKING: Record<Effort, number> = {
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minimal: 1024,
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low: 4096,
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medium: 8192,
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high: 16384,
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xhigh: 32768,
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};
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const GOOGLE_THINKING: Record<Effort, number> = {
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minimal: 1024,
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low: 4096,
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medium: 8192,
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high: 16384,
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xhigh: 24575,
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};
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const BEDROCK_CLAUDE_THINKING: Record<Effort, number> = {
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minimal: 1024,
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low: 2048,
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medium: 8192,
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high: 16384,
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xhigh: 16384,
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};
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function resolveBedrockThinkingBudget(
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model: Model<"bedrock-converse-stream">,
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options?: SimpleStreamOptions,
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): { budget: number; level: Effort } | null {
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if (!options?.reasoning || !model.reasoning) return null;
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const level = requireSupportedEffort(model, options.reasoning);
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const budget = options.thinkingBudgets?.[level] ?? BEDROCK_CLAUDE_THINKING[level];
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return { budget, level };
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}
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export function mapAnthropicToolChoice(choice?: ToolChoice): AnthropicOptions["toolChoice"] {
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if (!choice) return undefined;
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if (typeof choice === "string") {
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if (choice === "required") return "any";
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if (choice === "auto" || choice === "none" || choice === "any") return choice;
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return undefined;
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}
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if (choice.type === "tool") {
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return choice.name ? { type: "tool", name: choice.name } : undefined;
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}
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if (choice.type === "function") {
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const name = "function" in choice ? choice.function?.name : choice.name;
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return name ? { type: "tool", name } : undefined;
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}
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return undefined;
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}
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function mapGoogleToolChoice(
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choice?: ToolChoice,
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): GoogleOptions["toolChoice"] | GoogleGeminiCliOptions["toolChoice"] | GoogleVertexOptions["toolChoice"] {
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if (!choice) return undefined;
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if (typeof choice === "string") {
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if (choice === "required") return "any";
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if (choice === "auto" || choice === "none" || choice === "any") return choice;
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return undefined;
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}
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return "any";
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}
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function mapOpenAiToolChoice(choice?: ToolChoice): OpenAICompletionsOptions["toolChoice"] {
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|
if (!choice) return undefined;
|
|
if (typeof choice === "string") {
|
|
if (choice === "any") return "required";
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|
if (choice === "auto" || choice === "none" || choice === "required") return choice;
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return undefined;
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|
}
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|
if (choice.type === "tool") {
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|
return choice.name ? { type: "function", function: { name: choice.name } } : undefined;
|
|
}
|
|
if (choice.type === "function") {
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|
const name = "function" in choice ? choice.function?.name : choice.name;
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return name ? { type: "function", function: { name } } : undefined;
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|
}
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return undefined;
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|
}
|
|
|
|
function resolveOpenAiReasoningEffort<TApi extends Api>(
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model: Model<TApi>,
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|
options?: SimpleStreamOptions,
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|
): Effort | undefined {
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|
const reasoning = options?.reasoning;
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|
if (!reasoning || !model.reasoning) return undefined;
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|
return requireSupportedEffort(model, reasoning);
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}
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|
|
|
const castApi = <TApi extends Api>(api: OptionsForApi<TApi>): OptionsForApi<Api> => api as OptionsForApi<Api>;
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|
|
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function mapOptionsForApi<TApi extends Api>(
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model: Model<TApi>,
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options?: SimpleStreamOptions,
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apiKey?: string,
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|
): OptionsForApi<TApi> {
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|
const base = {
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|
temperature: options?.temperature,
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|
topP: options?.topP,
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|
topK: options?.topK,
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|
minP: options?.minP,
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|
presencePenalty: options?.presencePenalty,
|
|
repetitionPenalty: options?.repetitionPenalty,
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|
maxTokens: options?.maxTokens || Math.min(model.maxTokens, 32000),
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|
signal: options?.signal,
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|
apiKey: apiKey || options?.apiKey,
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|
cacheRetention: options?.cacheRetention,
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|
headers: options?.headers,
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|
initiatorOverride: options?.initiatorOverride,
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|
maxRetryDelayMs: options?.maxRetryDelayMs,
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|
metadata: options?.metadata,
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|
sessionId: options?.sessionId,
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|
providerSessionState: options?.providerSessionState,
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|
onPayload: options?.onPayload,
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|
onResponse: options?.onResponse,
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|
execHandlers: options?.execHandlers,
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|
};
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|
|
|
switch (model.api) {
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|
case "anthropic-messages": {
|
|
// Explicitly disable thinking when reasoning is not specified or model doesn't support it
|
|
const reasoning = options?.reasoning;
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|
if (!reasoning || !model.reasoning) {
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return castApi<"anthropic-messages">({
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...base,
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thinkingEnabled: false,
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toolChoice: mapAnthropicToolChoice(options?.toolChoice),
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});
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|
}
|
|
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let thinkingBudget = options.thinkingBudgets?.[reasoning] ?? ANTHROPIC_THINKING[reasoning];
|
|
if (thinkingBudget <= 0) {
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return castApi<"anthropic-messages">({
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...base,
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|
thinkingEnabled: false,
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toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
// For Opus 4.6+ and Sonnet 4.6+: use adaptive thinking with effort level
|
|
// For older models: use budget-based thinking
|
|
if (model.thinking?.mode === "anthropic-adaptive") {
|
|
const effort = mapEffortToAnthropicAdaptiveEffort(model, reasoning);
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
thinkingEnabled: true,
|
|
effort,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
if (ANTHROPIC_USE_INTERLEAVED_THINKING) {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: thinkingBudget,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
// 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 = maxTokens - MIN_OUTPUT_TOKENS;
|
|
}
|
|
|
|
// If thinking budget is too low, disable thinking
|
|
if (thinkingBudget <= 0) {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
thinkingEnabled: false,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
});
|
|
} else {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
maxTokens,
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: thinkingBudget,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
}
|
|
|
|
case "bedrock-converse-stream": {
|
|
const bedrockBase: BedrockOptions = {
|
|
...base,
|
|
reasoning: options?.reasoning,
|
|
thinkingBudgets: options?.thinkingBudgets,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
};
|
|
// Adaptive mode sends effort directly, no budget_tokens — skip budget inflation.
|
|
if (model.thinking?.mode === "anthropic-adaptive") {
|
|
return castApi<"bedrock-converse-stream">(bedrockBase);
|
|
}
|
|
const budgetInfo = resolveBedrockThinkingBudget(model as Model<"bedrock-converse-stream">, options);
|
|
if (!budgetInfo) return bedrockBase as OptionsForApi<TApi>;
|
|
let maxTokens = bedrockBase.maxTokens ?? model.maxTokens;
|
|
let thinkingBudgets = bedrockBase.thinkingBudgets;
|
|
if (maxTokens <= budgetInfo.budget) {
|
|
const desiredMaxTokens = Math.min(model.maxTokens, budgetInfo.budget + MIN_OUTPUT_TOKENS);
|
|
if (desiredMaxTokens > maxTokens) {
|
|
maxTokens = desiredMaxTokens;
|
|
}
|
|
}
|
|
if (maxTokens <= budgetInfo.budget) {
|
|
const adjustedBudget = Math.max(0, maxTokens - MIN_OUTPUT_TOKENS);
|
|
thinkingBudgets = { ...(thinkingBudgets ?? {}), [budgetInfo.level]: adjustedBudget };
|
|
}
|
|
return castApi<"bedrock-converse-stream">({ ...bedrockBase, maxTokens, thinkingBudgets });
|
|
}
|
|
|
|
case "openai-completions":
|
|
return castApi<"openai-completions">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
|
|
case "openai-responses":
|
|
return castApi<"openai-responses">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
|
|
case "azure-openai-responses":
|
|
return castApi<"azure-openai-responses">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
|
|
case "openai-codex-responses":
|
|
return castApi<"openai-codex-responses">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
preferWebsockets: options?.preferWebsockets,
|
|
});
|
|
|
|
case "google-generative-ai": {
|
|
// Explicitly disable thinking when reasoning is not specified or model doesn't support it
|
|
// This is needed because Gemini has "dynamic thinking" enabled by default
|
|
const reasoning = options?.reasoning;
|
|
if (!reasoning || !model.reasoning) {
|
|
return castApi<"google-generative-ai">({
|
|
...base,
|
|
thinking: { enabled: false },
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
const googleModel = model as Model<"google-generative-ai">;
|
|
const effort = requireSupportedEffort(googleModel, reasoning);
|
|
|
|
// Gemini 3+ models use thinkingLevel exclusively instead of thinkingBudget.
|
|
// https://ai.google.dev/gemini-api/docs/thinking#set-budget
|
|
if (googleModel.thinking?.mode === "google-level") {
|
|
return castApi<"google-generative-ai">({
|
|
...base,
|
|
thinking: {
|
|
enabled: true,
|
|
level: mapEffortToGoogleThinkingLevel(googleModel, effort),
|
|
},
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
return castApi<"google-gemini-cli">({
|
|
...base,
|
|
thinking: {
|
|
enabled: true,
|
|
budgetTokens: getGoogleBudget(googleModel, effort, options?.thinkingBudgets),
|
|
},
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
case "google-gemini-cli": {
|
|
const reasoning = options?.reasoning;
|
|
if (!reasoning || !model.reasoning) {
|
|
return castApi<"google-gemini-cli">({
|
|
...base,
|
|
thinking: { enabled: false },
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
const effort = requireSupportedEffort(model, reasoning);
|
|
|
|
// Gemini 3+ models use thinkingLevel instead of thinkingBudget
|
|
if (model.thinking?.mode === "google-level") {
|
|
return castApi<"google-gemini-cli">({
|
|
...base,
|
|
thinking: {
|
|
enabled: true,
|
|
level: mapEffortToGoogleThinkingLevel(model, effort),
|
|
},
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
let thinkingBudget = options.thinkingBudgets?.[effort] ?? GOOGLE_THINKING[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 - MIN_OUTPUT_TOKENS) ?? 0;
|
|
}
|
|
|
|
// If thinking budget is too low, disable thinking
|
|
if (thinkingBudget <= 0) {
|
|
return castApi<"google-gemini-cli">({
|
|
...base,
|
|
thinking: { enabled: false },
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
} else {
|
|
return castApi<"google-gemini-cli">({
|
|
...base,
|
|
maxTokens,
|
|
thinking: { enabled: true, budgetTokens: thinkingBudget },
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
}
|
|
|
|
case "google-vertex": {
|
|
// Explicitly disable thinking when reasoning is not specified or model doesn't support it
|
|
const reasoning = options?.reasoning;
|
|
if (!reasoning || !model.reasoning) {
|
|
return castApi<"google-vertex">({
|
|
...base,
|
|
thinking: { enabled: false },
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
const vertexModel = model as Model<"google-vertex">;
|
|
const effort = requireSupportedEffort(vertexModel, reasoning);
|
|
const geminiModel = vertexModel as unknown as Model<"google-generative-ai">;
|
|
|
|
if (geminiModel.thinking?.mode === "google-level") {
|
|
return castApi<"google-vertex">({
|
|
...base,
|
|
thinking: {
|
|
enabled: true,
|
|
level: mapEffortToGoogleThinkingLevel(geminiModel, effort),
|
|
},
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
return castApi<"google-vertex">({
|
|
...base,
|
|
thinking: {
|
|
enabled: true,
|
|
budgetTokens: getGoogleBudget(geminiModel, effort, options?.thinkingBudgets),
|
|
},
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
case "ollama-chat":
|
|
return castApi<"ollama-chat">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: options?.toolChoice,
|
|
});
|
|
|
|
case "cursor-agent": {
|
|
const execHandlers = options?.cursorExecHandlers ?? options?.execHandlers;
|
|
const onToolResult = options?.cursorOnToolResult ?? execHandlers?.onToolResult;
|
|
return castApi<"cursor-agent">({
|
|
...base,
|
|
execHandlers,
|
|
onToolResult,
|
|
});
|
|
}
|
|
|
|
default:
|
|
throw new Error(`Unhandled API in mapOptionsForApi: ${model.api}`);
|
|
}
|
|
}
|
|
|
|
function getGoogleBudget(
|
|
model: Model<"google-generative-ai">,
|
|
effort: Effort,
|
|
customBudgets?: ThinkingBudgets,
|
|
): number {
|
|
requireSupportedEffort(model, effort);
|
|
|
|
// Custom budgets take precedence if provided for this level
|
|
if (customBudgets?.[effort] !== undefined) {
|
|
return customBudgets[effort]!;
|
|
}
|
|
|
|
// See https://ai.google.dev/gemini-api/docs/thinking#set-budget
|
|
if (model.id.includes("2.5-")) {
|
|
switch (effort) {
|
|
case "minimal":
|
|
return 128;
|
|
case "low":
|
|
return 2048;
|
|
case "medium":
|
|
return 8192;
|
|
default:
|
|
return model.id.includes("2.5-flash") ? 24576 : 32768;
|
|
}
|
|
}
|
|
|
|
// Unknown model - use dynamic
|
|
return -1;
|
|
}
|