can1357
212d56bc11
- Added `toolStrictMode` support with `all_strict`/`none`/`mixed` options to OpenAI compatibility. - Fixed OpenAI-completion strict-mode flows by capturing failed HTTP responses and retrying once as non-strict. - Fixed completion error reporting by surfacing captured status, headers, and JSON `type`/`param`/`code` details. - Improved strict-schema enforcement with WeakMap memoization and circular-schema detection in sanitization. - Fixed OpenRouter provider lookup by resolving fallback model IDs for suffix and date variants in registry resolution. - Refactored benchmark tooling and added async RPC error-window tracking for scheduled run execution.
880 lines
30 KiB
TypeScript
880 lines
30 KiB
TypeScript
import { describe, expect, test } from "bun:test";
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import { Effort, type Model } from "@oh-my-pi/pi-ai";
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import {
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expandRoleAlias,
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parseModelPattern,
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parseModelString,
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resolveAgentModelPatterns,
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resolveCliModel,
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resolveModelFromString,
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resolveModelOverride,
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resolveModelRoleValue,
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resolveModelScope,
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} from "@oh-my-pi/pi-coding-agent/config/model-resolver";
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import { Settings } from "@oh-my-pi/pi-coding-agent/config/settings";
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// Mock models for testing
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const mockModels: Model<"anthropic-messages">[] = [
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{
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id: "claude-sonnet-4-5",
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name: "Claude Sonnet 4.5",
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api: "anthropic-messages",
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provider: "anthropic",
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baseUrl: "https://api.anthropic.com",
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reasoning: true,
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thinking: {
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mode: "budget",
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minLevel: Effort.Minimal,
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maxLevel: Effort.High,
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},
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input: ["text", "image"],
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cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 },
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contextWindow: 200000,
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maxTokens: 8192,
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},
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{
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id: "gpt-4o",
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name: "GPT-4o",
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api: "anthropic-messages", // Using same type for simplicity
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provider: "openai",
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baseUrl: "https://api.openai.com",
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reasoning: false,
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input: ["text", "image"],
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cost: { input: 5, output: 15, cacheRead: 0.5, cacheWrite: 5 },
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contextWindow: 128000,
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maxTokens: 4096,
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},
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];
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// Mock OpenRouter models with colons in IDs
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const mockOpenRouterModels: Model<"anthropic-messages">[] = [
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{
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id: "qwen/qwen3-coder:exacto",
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name: "Qwen3 Coder Exacto",
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api: "anthropic-messages",
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provider: "openrouter",
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baseUrl: "https://openrouter.ai/api/v1",
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reasoning: true,
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thinking: {
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mode: "budget",
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minLevel: Effort.Minimal,
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maxLevel: Effort.High,
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},
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input: ["text"],
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cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
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contextWindow: 128000,
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maxTokens: 8192,
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},
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{
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id: "openai/gpt-4o:extended",
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name: "GPT-4o Extended",
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api: "anthropic-messages",
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provider: "openrouter",
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baseUrl: "https://openrouter.ai/api/v1",
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reasoning: false,
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input: ["text", "image"],
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cost: { input: 5, output: 15, cacheRead: 0.5, cacheWrite: 5 },
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contextWindow: 128000,
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maxTokens: 4096,
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},
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{
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id: "z-ai/glm-4.7",
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name: "GLM 4.7",
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api: "anthropic-messages",
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provider: "openrouter",
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baseUrl: "https://openrouter.ai/api/v1",
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reasoning: true,
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thinking: {
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mode: "budget",
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minLevel: Effort.Minimal,
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maxLevel: Effort.High,
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},
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input: ["text"],
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cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
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contextWindow: 128000,
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maxTokens: 8192,
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},
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];
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const mockProviderOverlapModels: Model<"anthropic-messages">[] = [
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{
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id: "kimi-k2.5",
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name: "Kimi K2.5",
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api: "anthropic-messages",
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provider: "kimi-code",
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baseUrl: "https://api.kimi.ai",
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reasoning: false,
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input: ["text"],
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cost: { input: 2, output: 6, cacheRead: 0.2, cacheWrite: 2 },
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contextWindow: 128000,
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maxTokens: 8192,
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},
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{
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id: "moonshotai/kimi-k2.5",
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name: "Kimi K2.5 (OpenRouter)",
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api: "anthropic-messages",
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provider: "openrouter",
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baseUrl: "https://openrouter.ai/api/v1",
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reasoning: false,
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input: ["text"],
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cost: { input: 2.2, output: 6.2, cacheRead: 0.22, cacheWrite: 2.2 },
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contextWindow: 128000,
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maxTokens: 8192,
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},
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];
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const mockCodexOverlapModels: Model<"anthropic-messages">[] = [
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{
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id: "gpt-5.3-codex",
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name: "GPT-5.3 Codex",
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api: "anthropic-messages",
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provider: "openai-codex",
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baseUrl: "https://api.openai.com",
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reasoning: true,
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thinking: {
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mode: "effort",
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minLevel: Effort.Low,
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maxLevel: Effort.XHigh,
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},
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input: ["text"],
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cost: { input: 1.5, output: 6, cacheRead: 0.15, cacheWrite: 1.5 },
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contextWindow: 200000,
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maxTokens: 8192,
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},
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{
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id: "gpt-5.3-codex-spark",
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name: "GPT-5.3 Codex Spark",
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api: "anthropic-messages",
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provider: "openai-codex",
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baseUrl: "https://api.openai.com",
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reasoning: true,
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thinking: {
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mode: "effort",
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minLevel: Effort.Low,
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maxLevel: Effort.XHigh,
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},
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input: ["text"],
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cost: { input: 1, output: 4, cacheRead: 0.1, cacheWrite: 1 },
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contextWindow: 200000,
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maxTokens: 8192,
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},
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];
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const canonicalVariantModels: Model<"anthropic-messages">[] = [
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{
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id: "claude-sonnet-4-5",
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name: "Claude Sonnet 4.5",
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api: "anthropic-messages",
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provider: "anthropic",
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baseUrl: "https://api.anthropic.com",
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reasoning: true,
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thinking: {
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mode: "budget",
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minLevel: Effort.Minimal,
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maxLevel: Effort.High,
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},
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input: ["text", "image"],
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cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 },
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contextWindow: 200000,
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maxTokens: 8192,
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},
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{
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id: "anthropic/claude-sonnet-4.5",
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name: "Claude Sonnet 4.5 (Copilot)",
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api: "anthropic-messages",
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provider: "github-copilot",
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baseUrl: "https://api.githubcopilot.com",
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reasoning: true,
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thinking: {
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mode: "budget",
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minLevel: Effort.Minimal,
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maxLevel: Effort.High,
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},
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input: ["text", "image"],
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cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 },
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contextWindow: 200000,
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maxTokens: 8192,
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},
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];
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const canonicalRegistry = {
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resolveCanonicalModel: (canonicalId: string, options?: { candidates?: Model<"anthropic-messages">[] }) => {
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if (canonicalId !== "claude-sonnet-4-5") return undefined;
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const candidates = options?.candidates ?? canonicalVariantModels;
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return (
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candidates.find(model => model.provider === "github-copilot") ??
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candidates.find(model => model.provider === "anthropic")
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);
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},
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getCanonicalVariants: (canonicalId: string, options?: { candidates?: Model<"anthropic-messages">[] }) => {
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if (canonicalId !== "claude-sonnet-4-5") return [];
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const candidates = options?.candidates ?? canonicalVariantModels;
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return candidates.map(model => ({
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canonicalId,
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selector: `${model.provider}/${model.id}`,
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model,
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source: model.id === canonicalId ? "bundled" : "heuristic",
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}));
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},
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getCanonicalId: () => "claude-sonnet-4-5",
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getAvailable: () => canonicalVariantModels,
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} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
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const allModels = [...mockModels, ...mockOpenRouterModels, ...mockProviderOverlapModels, ...mockCodexOverlapModels];
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describe("parseModelPattern", () => {
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describe("simple patterns without colons", () => {
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test("exact match returns model with undefined thinking level", () => {
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const result = parseModelPattern("claude-sonnet-4-5", allModels);
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expect(result.model?.id).toBe("claude-sonnet-4-5");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toBeUndefined();
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});
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test("partial match returns best model with undefined thinking level", () => {
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const result = parseModelPattern("sonnet", allModels);
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expect(result.model?.id).toBe("claude-sonnet-4-5");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toBeUndefined();
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});
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test("no match returns undefined model and thinking level", () => {
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const result = parseModelPattern("nonexistent", allModels);
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expect(result.model).toBeUndefined();
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toBeUndefined();
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});
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});
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describe("patterns with valid thinking levels", () => {
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test("sonnet:high returns sonnet with high thinking level", () => {
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const result = parseModelPattern("sonnet:high", allModels);
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expect(result.model?.id).toBe("claude-sonnet-4-5");
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expect(result.thinkingLevel).toBe(Effort.High);
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expect(result.warning).toBeUndefined();
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});
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test("gpt-4o:medium returns gpt-4o with medium thinking level", () => {
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const result = parseModelPattern("gpt-4o:medium", allModels);
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expect(result.model?.id).toBe("gpt-4o");
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expect(result.thinkingLevel).toBe(Effort.Medium);
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expect(result.warning).toBeUndefined();
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});
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test("all valid thinking levels work", () => {
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const levels = ["off", Effort.Minimal, Effort.Low, Effort.Medium, Effort.High, Effort.XHigh] as const;
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for (const level of levels) {
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const result = parseModelPattern(`sonnet:${level}`, allModels);
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expect(result.model?.id).toBe("claude-sonnet-4-5");
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expect(result.thinkingLevel).toBe(level);
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expect(result.warning).toBeUndefined();
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}
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});
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});
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describe("patterns with invalid thinking levels", () => {
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test("sonnet:random returns sonnet with undefined thinking level and warning", () => {
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const result = parseModelPattern("sonnet:random", allModels);
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expect(result.model?.id).toBe("claude-sonnet-4-5");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toContain("Invalid thinking level");
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expect(result.warning).toContain("random");
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});
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test("gpt-4o:invalid returns gpt-4o with undefined thinking level and warning", () => {
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const result = parseModelPattern("gpt-4o:invalid", allModels);
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expect(result.model?.id).toBe("gpt-4o");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toContain("Invalid thinking level");
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});
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});
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describe("OpenRouter models with colons in IDs", () => {
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test("qwen3-coder:exacto matches the model with undefined thinking level", () => {
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const result = parseModelPattern("qwen/qwen3-coder:exacto", allModels);
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expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toBeUndefined();
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});
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test("openrouter/qwen/qwen3-coder:exacto matches with provider prefix", () => {
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const result = parseModelPattern("openrouter/qwen/qwen3-coder:exacto", allModels);
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expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
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expect(result.model?.provider).toBe("openrouter");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toBeUndefined();
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});
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test("qwen3-coder:exacto:high matches model with high thinking level", () => {
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const result = parseModelPattern("qwen/qwen3-coder:exacto:high", allModels);
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expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
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expect(result.thinkingLevel).toBe(Effort.High);
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expect(result.explicitThinkingLevel).toBe(true);
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expect(result.warning).toBeUndefined();
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});
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test("openrouter/qwen/qwen3-coder:exacto:high matches with provider and thinking level", () => {
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const result = parseModelPattern("openrouter/qwen/qwen3-coder:exacto:high", allModels);
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expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
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expect(result.model?.provider).toBe("openrouter");
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expect(result.thinkingLevel).toBe(Effort.High);
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expect(result.explicitThinkingLevel).toBe(true);
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expect(result.warning).toBeUndefined();
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});
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test("gpt-4o:extended matches the extended model with undefined thinking level", () => {
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const result = parseModelPattern("openai/gpt-4o:extended", allModels);
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expect(result.model?.id).toBe("openai/gpt-4o:extended");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toBeUndefined();
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});
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test("supports OpenRouter route suffixes that are not present in the catalog", () => {
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const result = parseModelPattern("openrouter/z-ai/glm-4.7-20251222:nitro", allModels);
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expect(result.model?.provider).toBe("openrouter");
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expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toBeUndefined();
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});
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test("supports OpenRouter route suffixes with an appended thinking level", () => {
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const result = parseModelPattern("openrouter/z-ai/glm-4.7-20251222:nitro:high", allModels);
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expect(result.model?.provider).toBe("openrouter");
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expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
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expect(result.thinkingLevel).toBe(Effort.High);
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expect(result.explicitThinkingLevel).toBe(true);
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expect(result.warning).toBeUndefined();
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});
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});
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describe("invalid thinking levels with OpenRouter models", () => {
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test("qwen3-coder:exacto:random returns model with undefined thinking level and warning", () => {
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const result = parseModelPattern("qwen/qwen3-coder:exacto:random", allModels);
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expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toContain("Invalid thinking level");
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expect(result.warning).toContain("random");
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});
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test("qwen3-coder:exacto:high:random returns model with undefined thinking level and warning", () => {
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const result = parseModelPattern("qwen/qwen3-coder:exacto:high:random", allModels);
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expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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expect(result.warning).toContain("Invalid thinking level");
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expect(result.warning).toContain("random");
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});
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});
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describe("edge cases", () => {
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test("empty pattern matches via partial matching", () => {
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// Empty string is included in all model IDs, so partial matching finds a match
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const result = parseModelPattern("", allModels);
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expect(result.model).not.toBeNull();
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expect(result.thinkingLevel).toBeUndefined();
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expect(result.explicitThinkingLevel).toBe(false);
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});
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test("pattern ending with colon treats empty suffix as invalid", () => {
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const result = parseModelPattern("sonnet:", allModels);
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// Empty string after colon is not a valid thinking level
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// So it tries to match "sonnet:" which won't match, then tries "sonnet"
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expect(result.model?.id).toBe("claude-sonnet-4-5");
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expect(result.warning).toContain("Invalid thinking level");
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});
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});
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describe("preference logic", () => {
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test("prefers most recently used model when multiple providers match", () => {
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const result = parseModelPattern("k2.5", allModels, {
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usageOrder: ["kimi-code/kimi-k2.5"],
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});
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expect(result.model?.provider).toBe("kimi-code");
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});
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test("falls back to deprioritizing openrouter when no usage data", () => {
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const result = parseModelPattern("k2.5", allModels, { usageOrder: [] });
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expect(result.model?.provider).toBe("kimi-code");
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});
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test("respects most recently used provider even if openrouter", () => {
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const result = parseModelPattern("k2.5", allModels, {
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usageOrder: ["openrouter/moonshotai/kimi-k2.5"],
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});
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expect(result.model?.provider).toBe("openrouter");
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expect(result.model?.id).toBe("moonshotai/kimi-k2.5");
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});
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});
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describe("canonical ids", () => {
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test("resolves an exact canonical id through the registry before bare-id matching", () => {
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const result = parseModelPattern("claude-sonnet-4-5", canonicalVariantModels, undefined, {
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modelRegistry: canonicalRegistry,
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});
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expect(result.model?.provider).toBe("github-copilot");
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expect(result.model?.id).toBe("anthropic/claude-sonnet-4.5");
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});
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});
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});
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describe("resolveModelRoleValue", () => {
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test("resolves pi/<role>:<thinking> by expanding role alias before parsing thinking", () => {
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const settings = {
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getModelRole: (role: string) => (role === "smol" ? "openrouter/qwen/qwen3-coder:exacto" : undefined),
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} as NonNullable<Parameters<typeof resolveModelRoleValue>[2]>["settings"];
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const result = resolveModelRoleValue("pi/smol:high", allModels, { settings });
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expect(result.model?.provider).toBe("openrouter");
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expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
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expect(result.thinkingLevel).toBe(Effort.High);
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expect(result.explicitThinkingLevel).toBe(true);
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});
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test("resolves pi/default through configured default role alias", () => {
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const settings = {
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getModelRole: (role: string) => (role === "default" ? "openrouter/qwen/qwen3-coder:exacto" : undefined),
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|
} as NonNullable<Parameters<typeof resolveModelRoleValue>[2]>["settings"];
|
|
|
|
const result = resolveModelRoleValue("pi/default", allModels, { settings });
|
|
|
|
expect(result.model?.provider).toBe("openrouter");
|
|
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
|
|
expect(result.thinkingLevel).toBeUndefined();
|
|
expect(result.explicitThinkingLevel).toBe(false);
|
|
expect(result.warning).toBeUndefined();
|
|
});
|
|
|
|
test("does not resolve exact codex role values to codex-spark via substring matching", () => {
|
|
const providerQualified = resolveModelRoleValue("openai-codex/gpt-5.3-codex:xhigh", allModels);
|
|
expect(providerQualified.model?.provider).toBe("openai-codex");
|
|
expect(providerQualified.model?.id).toBe("gpt-5.3-codex");
|
|
expect(providerQualified.thinkingLevel).toBe(Effort.XHigh);
|
|
expect(providerQualified.explicitThinkingLevel).toBe(true);
|
|
|
|
const idOnly = resolveModelRoleValue("gpt-5.3-codex:xhigh", allModels);
|
|
expect(idOnly.model?.provider).toBe("openai-codex");
|
|
expect(idOnly.model?.id).toBe("gpt-5.3-codex");
|
|
expect(idOnly.thinkingLevel).toBe(Effort.XHigh);
|
|
expect(idOnly.explicitThinkingLevel).toBe(true);
|
|
});
|
|
|
|
test("clamps explicit thinking selectors from model metadata", () => {
|
|
const result = resolveModelRoleValue("anthropic/claude-sonnet-4-5:xhigh", allModels);
|
|
|
|
expect(result.model?.provider).toBe("anthropic");
|
|
expect(result.model?.id).toBe("claude-sonnet-4-5");
|
|
expect(result.thinkingLevel).toBe(Effort.High);
|
|
expect(result.explicitThinkingLevel).toBe(true);
|
|
});
|
|
});
|
|
describe("resolveAgentModelPatterns", () => {
|
|
test("falls back to the active session model when pi/task is unset", () => {
|
|
const settings = Settings.isolated({
|
|
modelRoles: { default: "anthropic/claude-sonnet-4-5" },
|
|
});
|
|
|
|
const result = resolveAgentModelPatterns({
|
|
agentModel: "pi/task",
|
|
settings,
|
|
activeModelPattern: "openai/gpt-4o",
|
|
});
|
|
|
|
expect(result).toEqual(["openai/gpt-4o"]);
|
|
});
|
|
|
|
test("uses the configured task role before falling back to the session model", () => {
|
|
const settings = Settings.isolated({
|
|
modelRoles: {
|
|
default: "openai/gpt-4o",
|
|
task: "anthropic/claude-sonnet-4-5:high",
|
|
},
|
|
});
|
|
|
|
const result = resolveAgentModelPatterns({
|
|
agentModel: "pi/task",
|
|
settings,
|
|
activeModelPattern: "openai/gpt-4o",
|
|
});
|
|
|
|
expect(result).toEqual(["anthropic/claude-sonnet-4-5:high"]);
|
|
});
|
|
|
|
test("expands pi/designer to priority defaults", () => {
|
|
const settings = Settings.isolated({
|
|
modelRoles: {
|
|
default: "anthropic/claude-sonnet-4-5",
|
|
},
|
|
});
|
|
|
|
const result = resolveAgentModelPatterns({
|
|
agentModel: "pi/designer",
|
|
settings,
|
|
});
|
|
|
|
expect(result).toEqual([
|
|
"google-gemini-cli/gemini-3.1-pro",
|
|
"google-gemini-cli/gemini-3-pro",
|
|
"gemini-3.1-pro",
|
|
"gemini-3-1-pro",
|
|
"gemini-3-pro",
|
|
"gemini-3",
|
|
]);
|
|
});
|
|
|
|
test("prefers configured designer role override over priority defaults", () => {
|
|
const settings = Settings.isolated({
|
|
modelRoles: {
|
|
default: "anthropic/claude-sonnet-4-5",
|
|
designer: "openai/gpt-4o",
|
|
},
|
|
});
|
|
|
|
const result = resolveAgentModelPatterns({
|
|
agentModel: "pi/designer",
|
|
settings,
|
|
});
|
|
|
|
expect(result).toEqual(["openai/gpt-4o"]);
|
|
});
|
|
});
|
|
|
|
describe("resolveModelFromString", () => {
|
|
test("falls back to pattern parsing for provider/model:thinking when strict provider+id miss", () => {
|
|
const resolved = resolveModelFromString("openrouter/qwen/qwen3-coder:exacto:high", allModels);
|
|
expect(resolved?.provider).toBe("openrouter");
|
|
expect(resolved?.id).toBe("qwen/qwen3-coder:exacto");
|
|
});
|
|
|
|
test("treats colon-containing model IDs without thinking suffix as exact IDs", () => {
|
|
const resolved = resolveModelFromString("openrouter/qwen/qwen3-coder:exacto", allModels);
|
|
expect(resolved?.provider).toBe("openrouter");
|
|
expect(resolved?.id).toBe("qwen/qwen3-coder:exacto");
|
|
});
|
|
});
|
|
|
|
describe("resolveModelOverride", () => {
|
|
test("preserves explicit off and explicit-thinking metadata", () => {
|
|
const registry = {
|
|
getAvailable: () => allModels,
|
|
} as Parameters<typeof resolveModelOverride>[1];
|
|
|
|
const result = resolveModelOverride(["sonnet:off"], registry);
|
|
|
|
expect(result.model?.id).toBe("claude-sonnet-4-5");
|
|
expect(result.thinkingLevel).toBe("off");
|
|
expect(result.explicitThinkingLevel).toBe(true);
|
|
});
|
|
|
|
test("resolves colon-containing model IDs with appended thinking suffix", () => {
|
|
const registry = {
|
|
getAvailable: () => allModels,
|
|
} as Parameters<typeof resolveModelOverride>[1];
|
|
|
|
const result = resolveModelOverride(["openrouter/qwen/qwen3-coder:exacto:high"], registry);
|
|
|
|
expect(result.model?.provider).toBe("openrouter");
|
|
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
|
|
expect(result.thinkingLevel).toBe(Effort.High);
|
|
expect(result.explicitThinkingLevel).toBe(true);
|
|
});
|
|
});
|
|
describe("resolveCliModel", () => {
|
|
test("resolves exact canonical ids to the preferred concrete provider", () => {
|
|
const result = resolveCliModel({
|
|
cliModel: "claude-sonnet-4-5",
|
|
modelRegistry: {
|
|
...canonicalRegistry,
|
|
getAll: () => canonicalVariantModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"],
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.selector).toBe("claude-sonnet-4-5");
|
|
expect(result.model?.provider).toBe("github-copilot");
|
|
expect(result.model?.id).toBe("anthropic/claude-sonnet-4.5");
|
|
});
|
|
|
|
test("resolves --model provider/id without --provider", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliModel: "openai/gpt-4o",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.provider).toBe("openai");
|
|
expect(result.model?.id).toBe("gpt-4o");
|
|
});
|
|
|
|
test("resolves fuzzy patterns within an explicit provider", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliProvider: "openai",
|
|
cliModel: "4o",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.provider).toBe("openai");
|
|
expect(result.model?.id).toBe("gpt-4o");
|
|
});
|
|
|
|
test("supports --model <pattern>:<thinking> (without explicit --thinking)", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliModel: "sonnet:high",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.id).toBe("claude-sonnet-4-5");
|
|
expect(result.thinkingLevel).toBe(Effort.High);
|
|
});
|
|
|
|
test("prefers exact model id match over provider inference (OpenRouter-style ids)", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliModel: "openai/gpt-4o:extended",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.provider).toBe("openrouter");
|
|
expect(result.model?.id).toBe("openai/gpt-4o:extended");
|
|
});
|
|
|
|
test("does not strip invalid :suffix as thinking level in --model (fail fast)", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliProvider: "openai",
|
|
cliModel: "gpt-4o:extended",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.model).toBeUndefined();
|
|
expect(result.error).toContain("not found");
|
|
});
|
|
|
|
test("supports provider-prefixed OpenRouter route suffixes even when the base model is cataloged without them", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliModel: "openrouter/z-ai/glm-4.7-20251222:nitro",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.provider).toBe("openrouter");
|
|
expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
|
|
});
|
|
|
|
test("supports explicit OpenRouter provider with route suffixes that are not in the catalog", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliProvider: "openrouter",
|
|
cliModel: "z-ai/glm-4.7-20251222:nitro",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.provider).toBe("openrouter");
|
|
expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
|
|
});
|
|
|
|
test("returns a clear error when there are no models", () => {
|
|
const registry = {
|
|
getAll: () => [],
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliProvider: "openai",
|
|
cliModel: "gpt-4o",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.model).toBeUndefined();
|
|
expect(result.error).toContain("No models available");
|
|
});
|
|
|
|
test("resolves provider-prefixed fuzzy patterns (openrouter/qwen -> openrouter model)", () => {
|
|
const registry = {
|
|
getAll: () => allModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliModel: "openrouter/qwen",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.provider).toBe("openrouter");
|
|
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
|
|
});
|
|
|
|
test("prefers decomposed provider+id over flat id match when ambiguous", () => {
|
|
// Simulates the zai/glm-5 bug: vercel-ai-gateway has id="zai/glm-5",
|
|
// zai has id="glm-5". Input "zai/glm-5" should resolve to provider=zai.
|
|
const ambiguousModels: Model<"anthropic-messages">[] = [
|
|
{
|
|
id: "zai/glm-5",
|
|
name: "GLM-5 (Vercel)",
|
|
api: "anthropic-messages",
|
|
provider: "vercel-ai-gateway",
|
|
baseUrl: "https://vercel.ai",
|
|
reasoning: false,
|
|
input: ["text"],
|
|
cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
|
|
contextWindow: 128000,
|
|
maxTokens: 4096,
|
|
},
|
|
{
|
|
id: "glm-5",
|
|
name: "GLM-5",
|
|
api: "anthropic-messages",
|
|
provider: "zai",
|
|
baseUrl: "https://api.z.ai",
|
|
reasoning: false,
|
|
input: ["text"],
|
|
cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
|
|
contextWindow: 128000,
|
|
maxTokens: 4096,
|
|
},
|
|
];
|
|
const registry = {
|
|
getAll: () => ambiguousModels,
|
|
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
|
|
|
|
const result = resolveCliModel({
|
|
cliModel: "zai/glm-5",
|
|
modelRegistry: registry,
|
|
});
|
|
|
|
expect(result.error).toBeUndefined();
|
|
expect(result.model?.provider).toBe("zai");
|
|
expect(result.model?.id).toBe("glm-5");
|
|
});
|
|
});
|
|
|
|
describe("resolveModelScope", () => {
|
|
test("expands exact canonical ids into all concrete variants", async () => {
|
|
const scoped = await resolveModelScope(["claude-sonnet-4-5"], {
|
|
getAvailable: () => canonicalVariantModels,
|
|
getCanonicalVariants: (canonicalId: string, options?: { candidates?: Model<"anthropic-messages">[] }) =>
|
|
canonicalRegistry.getCanonicalVariants!(canonicalId, options),
|
|
} as unknown as Parameters<typeof resolveModelScope>[1]);
|
|
|
|
expect(scoped).toHaveLength(2);
|
|
expect(scoped.map(entry => `${entry.model.provider}/${entry.model.id}`).sort()).toEqual([
|
|
"anthropic/claude-sonnet-4-5",
|
|
"github-copilot/anthropic/claude-sonnet-4.5",
|
|
]);
|
|
});
|
|
});
|
|
|
|
describe("parseModelString", () => {
|
|
test("parses standard provider/id format", () => {
|
|
const result = parseModelString("anthropic/claude-sonnet-4-5");
|
|
expect(result).toEqual({ provider: "anthropic", id: "claude-sonnet-4-5" });
|
|
});
|
|
|
|
test("returns undefined for strings without a slash", () => {
|
|
expect(parseModelString("claude-sonnet-4-5")).toBeUndefined();
|
|
expect(parseModelString("")).toBeUndefined();
|
|
expect(parseModelString("sonnet:high")).toBeUndefined();
|
|
});
|
|
|
|
test("returns undefined for strings starting with slash", () => {
|
|
expect(parseModelString("/claude-sonnet-4-5")).toBeUndefined();
|
|
});
|
|
|
|
describe("thinking level suffix extraction", () => {
|
|
test("extracts valid thinking level from provider/id:level", () => {
|
|
const result = parseModelString("anthropic/claude-sonnet-4-5:high");
|
|
expect(result).toEqual({ provider: "anthropic", id: "claude-sonnet-4-5", thinkingLevel: Effort.High });
|
|
});
|
|
|
|
test("extracts all valid thinking levels", () => {
|
|
const levels = ["off", Effort.Minimal, Effort.Low, Effort.Medium, Effort.High, Effort.XHigh] as const;
|
|
for (const level of levels) {
|
|
const result = parseModelString(`anthropic/claude-sonnet-4-5:${level}`);
|
|
expect(result?.id).toBe("claude-sonnet-4-5");
|
|
expect(result?.thinkingLevel).toBe(level);
|
|
}
|
|
});
|
|
|
|
test("does NOT strip invalid suffix — treats it as part of model ID", () => {
|
|
const result = parseModelString("openrouter/qwen/qwen3-coder:exacto");
|
|
expect(result).toEqual({ provider: "openrouter", id: "qwen/qwen3-coder:exacto" });
|
|
});
|
|
|
|
test("handles model ID with colon followed by valid thinking level", () => {
|
|
// e.g. "openrouter/qwen/qwen3-coder:exacto:high" — last colon is thinking level
|
|
const result = parseModelString("openrouter/qwen/qwen3-coder:exacto:high");
|
|
expect(result).toEqual({
|
|
provider: "openrouter",
|
|
id: "qwen/qwen3-coder:exacto",
|
|
thinkingLevel: Effort.High,
|
|
});
|
|
});
|
|
|
|
test("does not extract thinking level from model ID with invalid suffix", () => {
|
|
const result = parseModelString("openrouter/openai/gpt-4o:extended");
|
|
// :extended is not a valid thinking level, so it stays as part of the ID
|
|
expect(result).toEqual({ provider: "openrouter", id: "openai/gpt-4o:extended" });
|
|
});
|
|
|
|
test("handles empty suffix after colon", () => {
|
|
const result = parseModelString("anthropic/claude-sonnet-4-5:");
|
|
// Empty string is not a valid thinking level, so colon stays as part of ID
|
|
expect(result).toEqual({ provider: "anthropic", id: "claude-sonnet-4-5:" });
|
|
});
|
|
});
|
|
});
|
|
|
|
describe("expandRoleAlias", () => {
|
|
test("expands pi/vision to configured vision role", () => {
|
|
const settings = Settings.isolated();
|
|
settings.setModelRole("vision", "openai/gpt-4o");
|
|
|
|
expect(expandRoleAlias("pi/vision", settings)).toBe("openai/gpt-4o");
|
|
});
|
|
|
|
test("keeps pi/vision alias when vision role is unset", () => {
|
|
const settings = Settings.isolated();
|
|
settings.setModelRole("default", "anthropic/claude-sonnet-4-5");
|
|
|
|
expect(expandRoleAlias("pi/vision", settings)).toBe("pi/vision");
|
|
});
|
|
});
|