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fix: use cache file for model availability instead of SDK calls

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- Changed fetchAvailableModels to read from ~/.cache/opencode/models.json
- Prevents plugin startup hanging caused by SDK client.config.providers() call
- Updated doctor model-resolution check to show available models from cache
- Added cache info display: provider count, model count, refresh command
This commit is contained in:
justsisyphus
2026-01-23 14:09:37 +09:00
parent f4348885f2
commit ab3e622baa
5 changed files with 148 additions and 80 deletions
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src/shared/model-availability.test.ts
+51 -61
View File
@@ -1,26 +1,43 @@
import { describe, it, expect, beforeEach } from "bun:test"
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, __resetModelCache } from "./model-availability"
describe("fetchAvailableModels", () => {
let mockClient: any
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
})
it("#given API returns list of models #when fetchAvailableModels called #then returns Set of model IDs", async () => {
const mockModels = [
{ id: "openai/gpt-5.2", name: "GPT-5.2" },
{ id: "anthropic/claude-opus-4-5", name: "Claude Opus 4.5" },
{ id: "google/gemini-3-pro", name: "Gemini 3 Pro" },
]
mockClient = {
model: {
list: async () => mockModels,
},
afterEach(() => {
if (originalXdgCache !== undefined) {
process.env.XDG_CACHE_HOME = originalXdgCache
} else {
delete process.env.XDG_CACHE_HOME
}
rmSync(tempDir, { recursive: true, force: true })
})
const result = await fetchAvailableModels(mockClient)
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 #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()
expect(result).toBeInstanceOf(Set)
expect(result.size).toBe(3)
@@ -29,77 +46,50 @@ describe("fetchAvailableModels", () => {
expect(result.has("google/gemini-3-pro")).toBe(true)
})
it("#given API fails #when fetchAvailableModels called #then returns empty Set without throwing", async () => {
mockClient = {
model: {
list: async () => {
throw new Error("API connection failed")
},
},
}
const result = await fetchAvailableModels(mockClient)
it("#given cache file not found #when fetchAvailableModels called #then returns empty Set", async () => {
const result = await fetchAvailableModels()
expect(result).toBeInstanceOf(Set)
expect(result.size).toBe(0)
})
it("#given API called twice #when second call made #then uses cached result without re-fetching", async () => {
let callCount = 0
const mockModels = [
{ id: "openai/gpt-5.2", name: "GPT-5.2" },
{ id: "anthropic/claude-opus-4-5", name: "Claude Opus 4.5" },
]
mockClient = {
model: {
list: async () => {
callCount++
return mockModels
},
},
}
it("#given cache read twice #when second call made #then uses cached result", 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(mockClient)
const result2 = await fetchAvailableModels(mockClient)
const result1 = await fetchAvailableModels()
const result2 = await fetchAvailableModels()
expect(callCount).toBe(1)
expect(result1).toEqual(result2)
expect(result1.has("openai/gpt-5.2")).toBe(true)
})
it("#given empty model list from API #when fetchAvailableModels called #then returns empty Set", async () => {
mockClient = {
model: {
list: async () => [],
},
}
it("#given empty providers in cache #when fetchAvailableModels called #then returns empty Set", async () => {
writeModelsCache({})
const result = await fetchAvailableModels(mockClient)
const result = await fetchAvailableModels()
expect(result).toBeInstanceOf(Set)
expect(result.size).toBe(0)
})
it("#given API returns models with various formats #when fetchAvailableModels called #then extracts all IDs correctly", async () => {
const mockModels = [
{ id: "openai/gpt-5.2-codex", name: "GPT-5.2 Codex" },
{ id: "anthropic/claude-sonnet-4-5", name: "Claude Sonnet 4.5" },
{ id: "google/gemini-3-flash", name: "Gemini 3 Flash" },
{ id: "opencode/grok-code", name: "Grok Code" },
]
mockClient = {
model: {
list: async () => mockModels,
},
}
it("#given cache file with various providers #when fetchAvailableModels called #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: { "grok-code": { id: "grok-code" } } },
})
const result = await fetchAvailableModels(mockClient)
const result = await fetchAvailableModels()
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/grok-code")).toBe(true)
expect(result.has("opencode/grok-code")).toBe(true)
})
})