252 lines
7.7 KiB
TypeScript
252 lines
7.7 KiB
TypeScript
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import { describe, it, expect, beforeEach } from "bun:test"
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import { fetchAvailableModels, fuzzyMatchModel, __resetModelCache } from "./model-availability"
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describe("fetchAvailableModels", () => {
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let mockClient: any
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beforeEach(() => {
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__resetModelCache()
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})
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it("#given API returns list of models #when fetchAvailableModels called #then returns Set of model IDs", async () => {
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const mockModels = [
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{ id: "openai/gpt-5.2", name: "GPT-5.2" },
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{ id: "anthropic/claude-opus-4-5", name: "Claude Opus 4.5" },
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{ id: "google/gemini-3-pro", name: "Gemini 3 Pro" },
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]
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mockClient = {
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model: {
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list: async () => mockModels,
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},
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}
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const result = await fetchAvailableModels(mockClient)
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expect(result).toBeInstanceOf(Set)
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expect(result.size).toBe(3)
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expect(result.has("openai/gpt-5.2")).toBe(true)
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expect(result.has("anthropic/claude-opus-4-5")).toBe(true)
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expect(result.has("google/gemini-3-pro")).toBe(true)
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})
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it("#given API fails #when fetchAvailableModels called #then returns empty Set without throwing", async () => {
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mockClient = {
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model: {
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list: async () => {
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throw new Error("API connection failed")
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},
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},
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}
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const result = await fetchAvailableModels(mockClient)
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expect(result).toBeInstanceOf(Set)
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expect(result.size).toBe(0)
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})
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it("#given API called twice #when second call made #then uses cached result without re-fetching", async () => {
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let callCount = 0
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const mockModels = [
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{ id: "openai/gpt-5.2", name: "GPT-5.2" },
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{ id: "anthropic/claude-opus-4-5", name: "Claude Opus 4.5" },
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]
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mockClient = {
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model: {
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list: async () => {
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callCount++
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return mockModels
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},
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},
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}
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const result1 = await fetchAvailableModels(mockClient)
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const result2 = await fetchAvailableModels(mockClient)
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expect(callCount).toBe(1)
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expect(result1).toEqual(result2)
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expect(result1.has("openai/gpt-5.2")).toBe(true)
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})
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it("#given empty model list from API #when fetchAvailableModels called #then returns empty Set", async () => {
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mockClient = {
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model: {
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list: async () => [],
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},
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}
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const result = await fetchAvailableModels(mockClient)
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expect(result).toBeInstanceOf(Set)
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expect(result.size).toBe(0)
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})
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it("#given API returns models with various formats #when fetchAvailableModels called #then extracts all IDs correctly", async () => {
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const mockModels = [
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{ id: "openai/gpt-5.2-codex", name: "GPT-5.2 Codex" },
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{ id: "anthropic/claude-sonnet-4-5", name: "Claude Sonnet 4.5" },
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{ id: "google/gemini-3-flash", name: "Gemini 3 Flash" },
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{ id: "opencode/grok-code", name: "Grok Code" },
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]
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mockClient = {
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model: {
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list: async () => mockModels,
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},
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}
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const result = await fetchAvailableModels(mockClient)
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expect(result.size).toBe(4)
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expect(result.has("openai/gpt-5.2-codex")).toBe(true)
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expect(result.has("anthropic/claude-sonnet-4-5")).toBe(true)
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expect(result.has("google/gemini-3-flash")).toBe(true)
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expect(result.has("opencode/grok-code")).toBe(true)
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})
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})
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describe("fuzzyMatchModel", () => {
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// #given available models from multiple providers
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// #when searching for a substring match
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// #then return the matching model
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it("should match substring in model name", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"openai/gpt-5.2-codex",
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"anthropic/claude-opus-4-5",
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])
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const result = fuzzyMatchModel("gpt-5.2", available)
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expect(result).toBe("openai/gpt-5.2")
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})
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// #given available models with partial matches
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// #when searching for a substring
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// #then return exact match if it exists
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it("should prefer exact match over substring match", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"openai/gpt-5.2-codex",
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"openai/gpt-5.2-ultra",
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])
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const result = fuzzyMatchModel("gpt-5.2", available)
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expect(result).toBe("openai/gpt-5.2")
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})
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// #given available models with multiple substring matches
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// #when searching for a substring
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// #then return the shorter model name (more specific)
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it("should prefer shorter model name when multiple matches exist", () => {
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const available = new Set([
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"openai/gpt-5.2-ultra",
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"openai/gpt-5.2-ultra-mega",
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])
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const result = fuzzyMatchModel("gpt-5.2", available)
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expect(result).toBe("openai/gpt-5.2-ultra")
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})
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// #given available models with claude variants
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// #when searching for claude-opus
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// #then return matching claude-opus model
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it("should match claude-opus to claude-opus-4-5", () => {
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const available = new Set([
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"anthropic/claude-opus-4-5",
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"anthropic/claude-sonnet-4-5",
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])
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const result = fuzzyMatchModel("claude-opus", available)
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expect(result).toBe("anthropic/claude-opus-4-5")
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})
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// #given available models from multiple providers
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// #when providers filter is specified
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// #then only search models from specified providers
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it("should filter by provider when providers array is given", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"anthropic/claude-opus-4-5",
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"google/gemini-3",
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])
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const result = fuzzyMatchModel("gpt", available, ["openai"])
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expect(result).toBe("openai/gpt-5.2")
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})
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// #given available models from multiple providers
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// #when providers filter excludes matching models
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// #then return null
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it("should return null when provider filter excludes all matches", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"anthropic/claude-opus-4-5",
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])
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const result = fuzzyMatchModel("claude", available, ["openai"])
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expect(result).toBeNull()
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})
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// #given available models
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// #when no substring match exists
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// #then return null
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it("should return null when no match found", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"anthropic/claude-opus-4-5",
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])
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const result = fuzzyMatchModel("gemini", available)
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expect(result).toBeNull()
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})
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// #given available models with different cases
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// #when searching with different case
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// #then match case-insensitively
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it("should match case-insensitively", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"anthropic/claude-opus-4-5",
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])
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const result = fuzzyMatchModel("GPT-5.2", available)
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expect(result).toBe("openai/gpt-5.2")
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})
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// #given available models with exact match and longer variants
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// #when searching for exact match
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// #then return exact match first
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it("should prioritize exact match over longer variants", () => {
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const available = new Set([
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"anthropic/claude-opus-4-5",
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"anthropic/claude-opus-4-5-extended",
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])
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const result = fuzzyMatchModel("claude-opus-4-5", available)
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expect(result).toBe("anthropic/claude-opus-4-5")
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})
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// #given available models with multiple providers
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// #when multiple providers are specified
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// #then search all specified providers
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it("should search all specified providers", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"anthropic/claude-opus-4-5",
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"google/gemini-3",
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])
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const result = fuzzyMatchModel("gpt", available, ["openai", "google"])
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expect(result).toBe("openai/gpt-5.2")
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})
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// #given available models with provider prefix
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// #when searching with provider filter
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// #then only match models with correct provider prefix
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it("should only match models with correct provider prefix", () => {
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const available = new Set([
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"openai/gpt-5.2",
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"anthropic/gpt-something",
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])
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const result = fuzzyMatchModel("gpt", available, ["openai"])
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expect(result).toBe("openai/gpt-5.2")
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})
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// #given empty available set
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// #when searching
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// #then return null
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it("should return null for empty available set", () => {
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const available = new Set<string>()
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const result = fuzzyMatchModel("gpt", available)
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expect(result).toBeNull()
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})
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})
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