oh-my-opencode/src/shared/model-availability.test.ts

import { describe, it, expect, beforeEach, afterEach } from "bun:test"
import { mkdtempSync, writeFileSync, rmSync } from "fs"
import { tmpdir } from "os"
import { join } from "path"
import { fetchAvailableModels, fuzzyMatchModel, getConnectedProviders, __resetModelCache, isModelAvailable } from "./model-availability"

describe("fetchAvailableModels", () => {
  let tempDir: string
  let originalXdgCache: string | undefined

  beforeEach(() => {
    __resetModelCache()
    tempDir = mkdtempSync(join(tmpdir(), "opencode-test-"))
    originalXdgCache = process.env.XDG_CACHE_HOME
    process.env.XDG_CACHE_HOME = tempDir
  })

  afterEach(() => {
    if (originalXdgCache !== undefined) {
      process.env.XDG_CACHE_HOME = originalXdgCache
    } else {
      delete process.env.XDG_CACHE_HOME
    }
    rmSync(tempDir, { recursive: true, force: true })
  })

  function writeModelsCache(data: Record<string, any>) {
    const cacheDir = join(tempDir, "opencode")
    require("fs").mkdirSync(cacheDir, { recursive: true })
    writeFileSync(join(cacheDir, "models.json"), JSON.stringify(data))
  }

  it("#given cache file with models #when fetchAvailableModels called with connectedProviders #then returns Set of model IDs", async () => {
    writeModelsCache({
      openai: { id: "openai", models: { "gpt-5.2": { id: "gpt-5.2" } } },
      anthropic: { id: "anthropic", models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
      google: { id: "google", models: { "gemini-3-pro": { id: "gemini-3-pro" } } },
    })

    const result = await fetchAvailableModels(undefined, {
      connectedProviders: ["openai", "anthropic", "google"]
    })

    expect(result).toBeInstanceOf(Set)
    expect(result.size).toBe(3)
    expect(result.has("openai/gpt-5.2")).toBe(true)
    expect(result.has("anthropic/claude-opus-4-5")).toBe(true)
    expect(result.has("google/gemini-3-pro")).toBe(true)
  })

  it("#given connectedProviders unknown #when fetchAvailableModels called without options #then returns empty Set", async () => {
    writeModelsCache({
      openai: { id: "openai", models: { "gpt-5.2": { id: "gpt-5.2" } } },
    })

    const result = await fetchAvailableModels()

    expect(result).toBeInstanceOf(Set)
    expect(result.size).toBe(0)
  })

  it("#given connectedProviders unknown but client can list #when fetchAvailableModels called with client #then returns models from API filtered by connected providers", async () => {
    const client = {
      provider: {
        list: async () => ({ data: { connected: ["openai"] } }),
      },
      model: {
        list: async () => ({
          data: [
            { id: "gpt-5.2-codex", provider: "openai" },
            { id: "gemini-3-pro", provider: "google" },
          ],
        }),
      },
    }

    const result = await fetchAvailableModels(client)

    expect(result).toBeInstanceOf(Set)
    expect(result.has("openai/gpt-5.2-codex")).toBe(true)
    expect(result.has("google/gemini-3-pro")).toBe(false)
  })

  it("#given cache file not found #when fetchAvailableModels called with connectedProviders #then returns empty Set", async () => {
    const result = await fetchAvailableModels(undefined, { connectedProviders: ["openai"] })

    expect(result).toBeInstanceOf(Set)
    expect(result.size).toBe(0)
  })

  it("#given cache missing but client can list #when fetchAvailableModels called with connectedProviders #then returns models from API", async () => {
    const client = {
      provider: {
        list: async () => ({ data: { connected: ["openai", "google"] } }),
      },
      model: {
        list: async () => ({
          data: [
            { id: "gpt-5.2-codex", provider: "openai" },
            { id: "gemini-3-pro", provider: "google" },
          ],
        }),
      },
    }

    const result = await fetchAvailableModels(client, { connectedProviders: ["openai", "google"] })

    expect(result).toBeInstanceOf(Set)
    expect(result.has("openai/gpt-5.2-codex")).toBe(true)
    expect(result.has("google/gemini-3-pro")).toBe(true)
  })

  it("#given cache read twice #when second call made with same providers #then reads fresh each time", async () => {
    writeModelsCache({
      openai: { id: "openai", models: { "gpt-5.2": { id: "gpt-5.2" } } },
      anthropic: { id: "anthropic", models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
    })

    const result1 = await fetchAvailableModels(undefined, { connectedProviders: ["openai"] })
    const result2 = await fetchAvailableModels(undefined, { connectedProviders: ["openai"] })

    expect(result1.size).toBe(result2.size)
    expect(result1.has("openai/gpt-5.2")).toBe(true)
  })

  it("#given empty providers in cache #when fetchAvailableModels called with connectedProviders #then returns empty Set", async () => {
    writeModelsCache({})

    const result = await fetchAvailableModels(undefined, { connectedProviders: ["openai"] })

    expect(result).toBeInstanceOf(Set)
    expect(result.size).toBe(0)
  })

  it("#given cache file with various providers #when fetchAvailableModels called with all providers #then extracts all IDs correctly", async () => {
    writeModelsCache({
      openai: { id: "openai", models: { "gpt-5.2-codex": { id: "gpt-5.2-codex" } } },
      anthropic: { id: "anthropic", models: { "claude-sonnet-4-5": { id: "claude-sonnet-4-5" } } },
      google: { id: "google", models: { "gemini-3-flash": { id: "gemini-3-flash" } } },
      opencode: { id: "opencode", models: { "gpt-5-nano": { id: "gpt-5-nano" } } },
    })

    const result = await fetchAvailableModels(undefined, {
      connectedProviders: ["openai", "anthropic", "google", "opencode"]
    })

    expect(result.size).toBe(4)
    expect(result.has("openai/gpt-5.2-codex")).toBe(true)
    expect(result.has("anthropic/claude-sonnet-4-5")).toBe(true)
    expect(result.has("google/gemini-3-flash")).toBe(true)
    expect(result.has("opencode/gpt-5-nano")).toBe(true)
  })
})

describe("fuzzyMatchModel", () => {
	// #given available models from multiple providers
	// #when searching for a substring match
	// #then return the matching model
	it("should match substring in model name", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"openai/gpt-5.2-codex",
			"anthropic/claude-opus-4-5",
		])
		const result = fuzzyMatchModel("gpt-5.2", available)
		expect(result).toBe("openai/gpt-5.2")
	})

	// #given available model with preview suffix
	// #when searching with provider-prefixed base model
	// #then return preview model
	it("should match preview suffix for gemini-3-flash", () => {
		const available = new Set(["google/gemini-3-flash-preview"])
		const result = fuzzyMatchModel(
			"google/gemini-3-flash",
			available,
			["google"],
		)
		expect(result).toBe("google/gemini-3-flash-preview")
	})

	// #given available models with partial matches
	// #when searching for a substring
	// #then return exact match if it exists
	it("should prefer exact match over substring match", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"openai/gpt-5.2-codex",
			"openai/gpt-5.2-ultra",
		])
		const result = fuzzyMatchModel("gpt-5.2", available)
		expect(result).toBe("openai/gpt-5.2")
	})

	// #given available models with multiple substring matches
	// #when searching for a substring
	// #then return the shorter model name (more specific)
	it("should prefer shorter model name when multiple matches exist", () => {
		const available = new Set([
			"openai/gpt-5.2-ultra",
			"openai/gpt-5.2-ultra-mega",
		])
		const result = fuzzyMatchModel("gpt-5.2", available)
		expect(result).toBe("openai/gpt-5.2-ultra")
	})

	// #given available models with claude variants
	// #when searching for claude-opus
	// #then return matching claude-opus model
	it("should match claude-opus to claude-opus-4-5", () => {
		const available = new Set([
			"anthropic/claude-opus-4-5",
			"anthropic/claude-sonnet-4-5",
		])
		const result = fuzzyMatchModel("claude-opus", available)
		expect(result).toBe("anthropic/claude-opus-4-5")
	})

	// #given available models from multiple providers
	// #when providers filter is specified
	// #then only search models from specified providers
	it("should filter by provider when providers array is given", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"anthropic/claude-opus-4-5",
			"google/gemini-3",
		])
		const result = fuzzyMatchModel("gpt", available, ["openai"])
		expect(result).toBe("openai/gpt-5.2")
	})

	// #given available models from multiple providers
	// #when providers filter excludes matching models
	// #then return null
	it("should return null when provider filter excludes all matches", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"anthropic/claude-opus-4-5",
		])
		const result = fuzzyMatchModel("claude", available, ["openai"])
		expect(result).toBeNull()
	})

	// #given available models
	// #when no substring match exists
	// #then return null
	it("should return null when no match found", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"anthropic/claude-opus-4-5",
		])
		const result = fuzzyMatchModel("gemini", available)
		expect(result).toBeNull()
	})

	// #given available models with different cases
	// #when searching with different case
	// #then match case-insensitively
	it("should match case-insensitively", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"anthropic/claude-opus-4-5",
		])
		const result = fuzzyMatchModel("GPT-5.2", available)
		expect(result).toBe("openai/gpt-5.2")
	})

	// #given available models with exact match and longer variants
	// #when searching for exact match
	// #then return exact match first
	it("should prioritize exact match over longer variants", () => {
		const available = new Set([
			"anthropic/claude-opus-4-5",
			"anthropic/claude-opus-4-5-extended",
		])
		const result = fuzzyMatchModel("claude-opus-4-5", available)
		expect(result).toBe("anthropic/claude-opus-4-5")
	})

	// #given available models with multiple providers
	// #when multiple providers are specified
	// #then search all specified providers
	it("should search all specified providers", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"anthropic/claude-opus-4-5",
			"google/gemini-3",
		])
		const result = fuzzyMatchModel("gpt", available, ["openai", "google"])
		expect(result).toBe("openai/gpt-5.2")
	})

	// #given available models with provider prefix
	// #when searching with provider filter
	// #then only match models with correct provider prefix
	it("should only match models with correct provider prefix", () => {
		const available = new Set([
			"openai/gpt-5.2",
			"anthropic/gpt-something",
		])
		const result = fuzzyMatchModel("gpt", available, ["openai"])
		expect(result).toBe("openai/gpt-5.2")
	})

	// #given empty available set
	// #when searching
	// #then return null
	it("should return null for empty available set", () => {
		const available = new Set<string>()
		const result = fuzzyMatchModel("gpt", available)
		expect(result).toBeNull()
	})
})

describe("getConnectedProviders", () => {
	//#given SDK client with connected providers
	//#when provider.list returns data
	//#then returns connected array
	it("should return connected providers from SDK", async () => {
		const mockClient = {
			provider: {
				list: async () => ({
					data: { connected: ["anthropic", "opencode", "google"] }
				})
			}
		}

		const result = await getConnectedProviders(mockClient)

		expect(result).toEqual(["anthropic", "opencode", "google"])
	})

	//#given SDK client
	//#when provider.list throws error
	//#then returns empty array
	it("should return empty array on SDK error", async () => {
		const mockClient = {
			provider: {
				list: async () => { throw new Error("Network error") }
			}
		}

		const result = await getConnectedProviders(mockClient)

		expect(result).toEqual([])
	})

	//#given SDK client with empty connected array
	//#when provider.list returns empty
	//#then returns empty array
	it("should return empty array when no providers connected", async () => {
		const mockClient = {
			provider: {
				list: async () => ({ data: { connected: [] } })
			}
		}

		const result = await getConnectedProviders(mockClient)

		expect(result).toEqual([])
	})

	//#given SDK client without provider.list method
	//#when getConnectedProviders called
	//#then returns empty array
	it("should return empty array when client.provider.list not available", async () => {
		const mockClient = {}

		const result = await getConnectedProviders(mockClient)

		expect(result).toEqual([])
	})

	//#given null client
	//#when getConnectedProviders called
	//#then returns empty array
	it("should return empty array for null client", async () => {
		const result = await getConnectedProviders(null)

		expect(result).toEqual([])
	})

	//#given SDK client with missing data.connected
	//#when provider.list returns without connected field
	//#then returns empty array
	it("should return empty array when data.connected is undefined", async () => {
		const mockClient = {
			provider: {
				list: async () => ({ data: {} })
			}
		}

		const result = await getConnectedProviders(mockClient)

		expect(result).toEqual([])
	})
})

describe("fetchAvailableModels with connected providers filtering", () => {
	let tempDir: string
	let originalXdgCache: string | undefined

	beforeEach(() => {
		__resetModelCache()
		tempDir = mkdtempSync(join(tmpdir(), "opencode-test-"))
		originalXdgCache = process.env.XDG_CACHE_HOME
		process.env.XDG_CACHE_HOME = tempDir
	})

	afterEach(() => {
		if (originalXdgCache !== undefined) {
			process.env.XDG_CACHE_HOME = originalXdgCache
		} else {
			delete process.env.XDG_CACHE_HOME
		}
		rmSync(tempDir, { recursive: true, force: true })
	})

	function writeModelsCache(data: Record<string, any>) {
		const cacheDir = join(tempDir, "opencode")
		require("fs").mkdirSync(cacheDir, { recursive: true })
		writeFileSync(join(cacheDir, "models.json"), JSON.stringify(data))
	}

	//#given cache with multiple providers
	//#when connectedProviders specifies one provider
	//#then only returns models from that provider
	it("should filter models by connected providers", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
			anthropic: { models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
			google: { models: { "gemini-3-pro": { id: "gemini-3-pro" } } },
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: ["anthropic"]
		})

		expect(result.size).toBe(1)
		expect(result.has("anthropic/claude-opus-4-5")).toBe(true)
		expect(result.has("openai/gpt-5.2")).toBe(false)
		expect(result.has("google/gemini-3-pro")).toBe(false)
	})

	//#given cache with multiple providers
	//#when connectedProviders specifies multiple providers
	//#then returns models from all specified providers
	it("should filter models by multiple connected providers", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
			anthropic: { models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
			google: { models: { "gemini-3-pro": { id: "gemini-3-pro" } } },
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: ["anthropic", "google"]
		})

		expect(result.size).toBe(2)
		expect(result.has("anthropic/claude-opus-4-5")).toBe(true)
		expect(result.has("google/gemini-3-pro")).toBe(true)
		expect(result.has("openai/gpt-5.2")).toBe(false)
	})

	//#given cache with models
	//#when connectedProviders is empty array
	//#then returns empty set
	it("should return empty set when connectedProviders is empty", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
			anthropic: { models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: []
		})

		expect(result.size).toBe(0)
	})

	//#given cache with models
	//#when connectedProviders is undefined (no options)
	//#then returns empty set (triggers fallback in resolver)
	it("should return empty set when connectedProviders not specified", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
			anthropic: { models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
		})

		const result = await fetchAvailableModels()

		expect(result.size).toBe(0)
	})

	//#given cache with models
	//#when connectedProviders contains provider not in cache
	//#then returns empty set for that provider
	it("should handle provider not in cache gracefully", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: ["azure"]
		})

		expect(result.size).toBe(0)
	})

	//#given cache with models and mixed connected providers
	//#when some providers exist in cache and some don't
	//#then returns models only from matching providers
	it("should return models from providers that exist in both cache and connected list", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
			anthropic: { models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: ["anthropic", "azure", "unknown"]
		})

		expect(result.size).toBe(1)
		expect(result.has("anthropic/claude-opus-4-5")).toBe(true)
	})

	//#given filtered fetch
	//#when called twice with different filters
	//#then does NOT use cache (dynamic per-session)
	it("should not cache filtered results", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
			anthropic: { models: { "claude-opus-4-5": { id: "claude-opus-4-5" } } },
		})

		// First call with anthropic
		const result1 = await fetchAvailableModels(undefined, {
			connectedProviders: ["anthropic"]
		})
		expect(result1.size).toBe(1)

		// Second call with openai - should work, not cached
		const result2 = await fetchAvailableModels(undefined, {
			connectedProviders: ["openai"]
		})
		expect(result2.size).toBe(1)
		expect(result2.has("openai/gpt-5.2")).toBe(true)
	})

	//#given connectedProviders unknown
	//#when called twice without connectedProviders
	//#then always returns empty set (triggers fallback)
	it("should return empty set when connectedProviders unknown", async () => {
		writeModelsCache({
			openai: { models: { "gpt-5.2": { id: "gpt-5.2" } } },
		})

		const result1 = await fetchAvailableModels()
		const result2 = await fetchAvailableModels()

		expect(result1.size).toBe(0)
		expect(result2.size).toBe(0)
	})
})

describe("fetchAvailableModels with provider-models cache (whitelist-filtered)", () => {
	let tempDir: string
	let originalXdgCache: string | undefined

	beforeEach(() => {
		__resetModelCache()
		tempDir = mkdtempSync(join(tmpdir(), "opencode-test-"))
		originalXdgCache = process.env.XDG_CACHE_HOME
		process.env.XDG_CACHE_HOME = tempDir
	})

	afterEach(() => {
		if (originalXdgCache !== undefined) {
			process.env.XDG_CACHE_HOME = originalXdgCache
		} else {
			delete process.env.XDG_CACHE_HOME
		}
		rmSync(tempDir, { recursive: true, force: true })
	})

	function writeProviderModelsCache(data: { models: Record<string, string[]>; connected: string[] }) {
		const cacheDir = join(tempDir, "oh-my-opencode")
		require("fs").mkdirSync(cacheDir, { recursive: true })
		writeFileSync(join(cacheDir, "provider-models.json"), JSON.stringify({
			...data,
			updatedAt: new Date().toISOString()
		}))
	}

	function writeModelsCache(data: Record<string, any>) {
		const cacheDir = join(tempDir, "opencode")
		require("fs").mkdirSync(cacheDir, { recursive: true })
		writeFileSync(join(cacheDir, "models.json"), JSON.stringify(data))
	}

	//#given provider-models cache exists (whitelist-filtered)
	//#when fetchAvailableModels called
	//#then uses provider-models cache instead of models.json
	it("should prefer provider-models cache over models.json", async () => {
		writeProviderModelsCache({
			models: {
				opencode: ["glm-4.7-free", "gpt-5-nano"],
				anthropic: ["claude-opus-4-5"]
			},
			connected: ["opencode", "anthropic"]
		})
		writeModelsCache({
			opencode: { models: { "glm-4.7-free": {}, "gpt-5-nano": {}, "gpt-5.2": {} } },
			anthropic: { models: { "claude-opus-4-5": {}, "claude-sonnet-4-5": {} } }
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: ["opencode", "anthropic"]
		})

		expect(result.size).toBe(3)
		expect(result.has("opencode/glm-4.7-free")).toBe(true)
		expect(result.has("opencode/gpt-5-nano")).toBe(true)
		expect(result.has("anthropic/claude-opus-4-5")).toBe(true)
		expect(result.has("opencode/gpt-5.2")).toBe(false)
		expect(result.has("anthropic/claude-sonnet-4-5")).toBe(false)
	})

	//#given provider-models cache exists but has no models (API failure)
	//#when fetchAvailableModels called
	//#then falls back to models.json so fuzzy matching can still work
	it("should fall back to models.json when provider-models cache is empty", async () => {
		writeProviderModelsCache({
			models: {
			},
			connected: ["google"],
		})
		writeModelsCache({
			google: { models: { "gemini-3-flash-preview": {} } },
		})

		const availableModels = await fetchAvailableModels(undefined, {
			connectedProviders: ["google"],
		})
		const match = fuzzyMatchModel("google/gemini-3-flash", availableModels, ["google"])

		expect(match).toBe("google/gemini-3-flash-preview")
	})

	//#given only models.json exists (no provider-models cache)
	//#when fetchAvailableModels called
	//#then falls back to models.json (no whitelist filtering)
	it("should fallback to models.json when provider-models cache not found", async () => {
		writeModelsCache({
			opencode: { models: { "glm-4.7-free": {}, "gpt-5-nano": {}, "gpt-5.2": {} } },
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: ["opencode"]
		})

		expect(result.size).toBe(3)
		expect(result.has("opencode/glm-4.7-free")).toBe(true)
		expect(result.has("opencode/gpt-5-nano")).toBe(true)
		expect(result.has("opencode/gpt-5.2")).toBe(true)
	})

	//#given provider-models cache with whitelist
	//#when connectedProviders filters to subset
	//#then only returns models from connected providers
	it("should filter by connectedProviders even with provider-models cache", async () => {
		writeProviderModelsCache({
			models: {
				opencode: ["glm-4.7-free"],
				anthropic: ["claude-opus-4-5"],
				google: ["gemini-3-pro"]
			},
			connected: ["opencode", "anthropic", "google"]
		})

		const result = await fetchAvailableModels(undefined, {
			connectedProviders: ["opencode"]
		})

		expect(result.size).toBe(1)
		expect(result.has("opencode/glm-4.7-free")).toBe(true)
		expect(result.has("anthropic/claude-opus-4-5")).toBe(false)
		expect(result.has("google/gemini-3-pro")).toBe(false)
	})
})

describe("isModelAvailable", () => {
	it("returns true when model exists via fuzzy match", () => {
		// #given
		const available = new Set(["openai/gpt-5.2-codex", "anthropic/claude-opus-4-5"])

		// #when
		const result = isModelAvailable("gpt-5.2-codex", available)

		// #then
		expect(result).toBe(true)
	})

	it("returns false when model not found", () => {
		// #given
		const available = new Set(["anthropic/claude-opus-4-5"])

		// #when
		const result = isModelAvailable("gpt-5.2-codex", available)

		// #then
		expect(result).toBe(false)
	})

	it("returns false for empty available set", () => {
		// #given
		const available = new Set<string>()

		// #when
		const result = isModelAvailable("gpt-5.2-codex", available)

		// #then
		expect(result).toBe(false)
	})
})