feat: v0.7.4 时序语义修正 · 防线实效补漏 · 全量测试翻倍 — 2406 用例 + jsdom 组件测试全量回归
P1 修复面收口: - 超时三态区分（aborted→USER_INTERRUPT / ETIMEDOUT→TIMEOUT / 其余→ERROR）， 根治"真实网络超时被误报为用户中断" - 流空闲超时统一（SSE/Ollama/Anthropic 读循环 60s 无数据抛 504 进重试通道） - 同会话并发 sendMessage 防重入（isRunning 守卫）+ 会话存在性预检 + 前置调用移入 try（ERROR+DONE 双事件保证，根治 isStreaming 假死） - 清空审计后 resetChainCache（根治 verifyChain 误报 TAMPERED） - DONE 不再提前清理 TRACE（TERMINATED 统一收尾，补全最终迭代录制） - IME 合成回车不发送（普通 Enter + Cmd/Ctrl+Enter 双分支）+ handleSend 闭包修复 P2 安全纵深: - preload 移除原始 electronAPI 暴露（渲染层零使用，关掉 XSS invoke 任意通道单点风险） - CORS 同源回显根治（仅当前浏览页面 Origin，did-navigate 同步） - MEMORY.md 命令保护正则扩展（括号/$/反引号/< 重定向边界 + 前导路径） - write_file append TOCTOU 统一（open 后 realpath 校验，新文件分支补漏） - 敏感键归一化（authKey 驼峰/连字符命中）+ MCP headers 鉴权值加密落库 - ReDoS 检测共享化（search_files/file_editor 统一拦截） - run_tests/lint_code 升风险 + 需确认 + npx --no-install（执行边界对齐 run_command） - MCP/SearXNG/llm.baseURL/updateFeedUrl 配置类 URL 高危目标校验（IPv6 去括号 + 十六进制映射解析 + 尾点剥离） P3 架构还债: - temperature/maxTokens 热生效（引擎/编排器/SubAgent 三处接线）+ setBatch 单事务落盘 - SessionRecorder flush 竞态根治（flushPromise 等待 + 超限内联落盘 + stopRecording async） - 内存收口（lastConsolidationBySession LRU / subTraces 清理 / 会话删除 disposeEngine） - i18n 全量收口（28 组件 + 353 key 双字典，状态标签改渲染时函数） - 死代码清理（updateTraceStep/HEADER_HEIGHT/void preA/失实注释） - 斜杠菜单 MUI 化 + 删除逻辑收敛 resetSessionState + Blob URL 统一释放 + 用户消息"仅保存"落库（saveMessage 透传前端 id 修复 id 错位） P4 能力演进: - 死循环检测拆分（驻留前置 + 乒乓后置带进度信号，合法交替不误报） - run-lock 30s 超时强制 abort（旧 run 卡死不无限排队） - RETRY 双通道 stream_reset（前端按 run 归属精确清空，根治重试文本重复） - FTS5 trigram 中文子串搜索（迁移 9 版本化 SCHEMA_VERSION=2，≤2 字符 LIKE 回退） - getContextWindow 兜底 1M→128K（未知模型防 413） 测试: - 855 → 2406 用例（+1551，2.8 倍）：服务层 +325（含 MemoryManager 51 新用例）、 工具实体 +483、IPC/适配器 +390（含 OpenAI/Anthropic/Ollama 独立套件）、 纯函数表格化 +330；引入 jsdom + @testing-library（14 组件测试文件 249 用例） - 修复 R1（saveMessage id 透传）/ R2（stream_reset 精确归属）两个回归缺陷 - 遗留低危项清零：git-tools 顺序耦合 / web-fetch 真实时间退避 / slo 内存断言 / mcp-security 多余 skipIf / deepseek-balance 命名误导 / 组件 mock 注入脆弱性 版本: 0.7.4; README 同步（工具风险表/版本徽章）; 依赖: 移除 @electron-toolkit/preload， 新增 jsdom/@testing-library（devDependencies 不打包） 回归: typecheck 双端 0 错误; ESLint 0/0; Electron ABI 全量 2406/2406 零跳过; 系统 Node 2110 通过 296 跳过（better-sqlite3 ABI）
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/**
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* OpenAIAdapter 独立测试（v0.6.4 P3-1 收敛后差异点）
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*
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* OpenAIAdapter 继承 OpenAICompatibleAdapter，本文件锁定 OpenAI 独有契约：
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* - 推理模型（o 系列 / gpt-5）字段路由：reasoning_effort / max_completion_tokens
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* - 推理模型拒图：ModelCapabilityError（status=400）
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* - 非推理模型 temperature / max_tokens 路由
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* - gpt-4.1 1M 上下文窗口（getContextWindow 回退链）
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* - listModels 动态 /models 合并与降级
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*/
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import { describe, it, expect, vi, beforeEach, afterEach } from 'vitest';
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vi.mock('electron-log', () => ({
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default: { info: vi.fn(), warn: vi.fn(), error: vi.fn(), debug: vi.fn() },
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}));
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import { OpenAIAdapter } from '../openai.adapter';
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import { ModelCapabilityError } from '../shared/openai-compatible-base';
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import type { MetonaRequest } from '../../types';
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const mockFetch = vi.fn();
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function makeAdapter(model: string, overrides: Record<string, unknown> = {}): OpenAIAdapter {
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return new OpenAIAdapter({
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provider: 'openai',
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baseURL: 'https://api.openai.com/v1',
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apiKey: 'sk-test',
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defaultModel: model,
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...overrides,
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});
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}
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function makeRequest(overrides?: Partial<MetonaRequest>): MetonaRequest {
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return {
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meta: {
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sessionId: 's1',
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iteration: 1,
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requestId: 'r1',
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timestamp: Date.now(),
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agentVersion: 'test',
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},
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systemPrompt: {
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roleDefinition: 'You are Metona.',
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outputConstraints: '',
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safetyGuidelines: '',
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},
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messages: [{ role: 'user', content: 'hi', timestamp: Date.now() }],
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params: { maxTokens: 4096, temperature: 0, stream: false },
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...overrides,
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};
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}
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function okResponse(
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body: Record<string, unknown> = { choices: [{ message: { content: 'ok' } }] },
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): Response {
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return {
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ok: true,
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status: 200,
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json: async () => body,
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} as unknown as Response;
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}
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function lastBody(): Record<string, unknown> {
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const call = mockFetch.mock.calls[mockFetch.mock.calls.length - 1] as [string, RequestInit];
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return JSON.parse(String(call[1].body));
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}
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beforeEach(() => {
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mockFetch.mockReset();
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vi.stubGlobal('fetch', mockFetch);
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});
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afterEach(() => {
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vi.unstubAllGlobals();
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});
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// ===== reasoning_effort 映射 =====
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describe('OpenAIAdapter — 推理模型 reasoning_effort', () => {
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it.each([
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['low', 'low'],
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['medium', 'medium'],
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['high', 'high'],
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['max', 'high'], // max 归一 high
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] as const)('o3-mini effort=%s → reasoning_effort=%s', async (effort, expected) => {
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const adapter = makeAdapter('o3-mini');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({
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params: {
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maxTokens: 4096,
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temperature: 0,
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stream: false,
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thinkingEnabled: true,
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thinkingEffort: effort,
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},
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}),
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);
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expect(lastBody().reasoning_effort).toBe(expected);
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});
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it('o3-mini thinking 关闭 → 不传 reasoning_effort（可关闭服务端默认思考）', async () => {
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const adapter = makeAdapter('o3-mini');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({
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params: { maxTokens: 4096, temperature: 0, stream: false, thinkingEnabled: false },
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}),
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);
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expect(lastBody().reasoning_effort).toBeUndefined();
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});
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it('o3-mini thinking 未配置 → 不传 reasoning_effort', async () => {
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const adapter = makeAdapter('o3-mini');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(makeRequest({ params: { maxTokens: 4096, temperature: 0, stream: false } }));
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expect(lastBody().reasoning_effort).toBeUndefined();
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});
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it('o3-mini thinking 未配置 effort → 缺省 high', async () => {
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const adapter = makeAdapter('o3-mini');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({
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params: { maxTokens: 4096, temperature: 0, stream: false, thinkingEnabled: true },
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}),
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);
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expect(lastBody().reasoning_effort).toBe('high');
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});
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it('非推理模型 gpt-4o 即使 thinkingEnabled=true 也不传 reasoning_effort（忽略思考参数）', async () => {
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const adapter = makeAdapter('gpt-4o');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({
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params: { maxTokens: 4096, temperature: 0.3, stream: false, thinkingEnabled: true },
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}),
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);
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expect(lastBody().reasoning_effort).toBeUndefined();
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// 非推理模型仍传 temperature
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expect(lastBody().temperature).toBe(0.3);
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});
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});
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// ===== 推理模型拒图 =====
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describe('OpenAIAdapter — 推理模型拒图（ModelCapabilityError）', () => {
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it.each(['o3-mini', 'o1', 'gpt-5.1'])(
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'%s 带图片 → 抛 ModelCapabilityError(status=400)',
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async (model) => {
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const adapter = makeAdapter(model);
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mockFetch.mockResolvedValue(okResponse());
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const request = makeRequest({
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messages: [
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{
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role: 'user',
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content: '看图',
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images: [{ url: 'data:image/png;base64,AAA' }],
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timestamp: Date.now(),
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},
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],
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});
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const err = await adapter.send(request).catch((e: unknown) => e);
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expect(err).toBeInstanceOf(ModelCapabilityError);
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expect((err as ModelCapabilityError).status).toBe(400);
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expect((err as Error).message).toContain('does not support');
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// 拒图不发出网络请求
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expect(mockFetch).not.toHaveBeenCalled();
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},
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);
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it('o3-mini 无图片 → 正常发送（不误拒）', async () => {
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const adapter = makeAdapter('o3-mini');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(makeRequest());
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expect(mockFetch).toHaveBeenCalledTimes(1);
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});
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it('非推理模型 gpt-4o 带图片 → 正常发送（多模态允许）', async () => {
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const adapter = makeAdapter('gpt-4o');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({
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messages: [
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{
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role: 'user',
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content: '看图',
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images: [{ url: 'data:image/png;base64,AAA' }],
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timestamp: Date.now(),
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},
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],
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}),
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);
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expect(mockFetch).toHaveBeenCalledTimes(1);
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const body = lastBody();
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// 图片转为 image_url parts
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const userMsg = (body.messages as Array<Record<string, unknown>>)[1];
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expect(userMsg.content).toEqual([
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{ type: 'text', text: '看图' },
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{ type: 'image_url', image_url: { url: 'data:image/png;base64,AAA' } },
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]);
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});
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});
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// ===== max_completion_tokens / max_tokens 路由 =====
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describe('OpenAIAdapter — token 参数路由', () => {
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it.each([
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['o3-mini', 63_488, 63_488, 'max_completion_tokens'],
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['o3-mini', 200_000, 100_000, 'max_completion_tokens'], // 上限 100000
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['gpt-4o', 63_488, 16_384, 'max_tokens'],
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['gpt-4.1', 63_488, 32_768, 'max_tokens'],
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] as const)('%s maxTokens=%d → %s=%d', async (model, requested, expected, field) => {
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const adapter = makeAdapter(model);
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({ params: { maxTokens: requested, temperature: 0, stream: false } }),
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);
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const body = lastBody();
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expect(body[field]).toBe(expected);
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// 另一个字段不出现
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const other = field === 'max_completion_tokens' ? 'max_tokens' : 'max_completion_tokens';
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expect(body[other]).toBeUndefined();
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});
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it('o3-mini 未配置 maxTokens → 默认 32768（thinking 场景安全值）', async () => {
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const adapter = makeAdapter('o3-mini');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(makeRequest({ params: { temperature: 0, stream: false } }));
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expect(lastBody().max_completion_tokens).toBe(32_768);
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});
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it('非推理模型未配置 maxTokens → 默认模型上限', async () => {
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const adapter = makeAdapter('gpt-4o');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(makeRequest({ params: { temperature: 0, stream: false } }));
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expect(lastBody().max_tokens).toBe(16_384);
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});
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});
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// ===== temperature 传递 =====
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describe('OpenAIAdapter — temperature 路由', () => {
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it('非推理模型 temperature 逐值透传', async () => {
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const adapter = makeAdapter('gpt-4o');
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mockFetch.mockResolvedValue(okResponse());
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for (const t of [0, 0.7, 1.0]) {
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await adapter.send(
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makeRequest({ params: { maxTokens: 4096, temperature: t, stream: false } }),
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);
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}
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expect(lastBody().temperature).toBe(1.0);
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const bodies = mockFetch.mock.calls.map((c) => JSON.parse(String((c[1] as RequestInit).body)));
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expect(bodies.map((b) => b.temperature)).toEqual([0, 0.7, 1.0]);
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});
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it('推理模型 o3-mini 不传 temperature（o 系列不支持）', async () => {
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const adapter = makeAdapter('o3-mini');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({ params: { maxTokens: 4096, temperature: 0.7, stream: false } }),
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);
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expect(lastBody().temperature).toBeUndefined();
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});
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it('gpt-5 系列同样不传 temperature（推理家族）', async () => {
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const adapter = makeAdapter('gpt-5');
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mockFetch.mockResolvedValue(okResponse());
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await adapter.send(
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makeRequest({ params: { maxTokens: 4096, temperature: 0.5, stream: false } }),
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);
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expect(lastBody().temperature).toBeUndefined();
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expect(lastBody().max_completion_tokens).toBe(4096);
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});
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});
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// ===== getContextWindow 回退链 =====
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describe('OpenAIAdapter — getContextWindow 回退链', () => {
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it('gpt-4.1 返回 1M 上下文', () => {
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expect(makeAdapter('gpt-4.1').getContextWindow()).toBe(1_000_000);
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});
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it('o3-mini 返回 200K', () => {
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expect(makeAdapter('o3-mini').getContextWindow()).toBe(200_000);
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});
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it('未知模型 → 兜底 128K（v0.7.4 P4-5 从 1M 降级）', () => {
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expect(makeAdapter('unknown-model-x').getContextWindow()).toBe(128_000);
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});
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it('config.contextWindow 显式配置优先', () => {
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const adapter = makeAdapter('gpt-4o', { contextWindow: 64_000 });
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expect(adapter.getContextWindow()).toBe(64_000);
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});
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});
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// ===== listModels =====
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describe('OpenAIAdapter — listModels 动态发现与降级', () => {
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it('API 成功 → 合并本地元信息（已知模型带 name，未知模型裸 id）', async () => {
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mockFetch.mockResolvedValue(okResponse({ data: [{ id: 'gpt-4o' }, { id: 'custom-model' }] }));
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const models = await makeAdapter('gpt-4o').listModels();
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expect(models).toHaveLength(2);
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expect(models[0]).toMatchObject({ id: 'gpt-4o', contextWindow: 128_000 });
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expect(models[1]).toEqual({ id: 'custom-model' });
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// /models 请求头携带 Bearer
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const [, init] = mockFetch.mock.calls[0] as [string, RequestInit];
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expect((init.headers as Record<string, string>).Authorization).toBe('Bearer sk-test');
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});
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it('API 失败 → 降级到 supportedModels（带元信息）', async () => {
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mockFetch.mockRejectedValue(new Error('network'));
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const models = await makeAdapter('gpt-4o').listModels();
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expect(models.map((m) => m.id)).toEqual(['gpt-4o', 'gpt-4o-mini', 'gpt-4.1', 'o3-mini']);
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});
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it('API 返回空 data → 降级到 supportedModels', async () => {
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mockFetch.mockResolvedValue(okResponse({ data: [] }));
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const models = await makeAdapter('gpt-4o').listModels();
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expect(models).toHaveLength(4);
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});
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it('healthCheck 基于 listModels 成功返回 true', async () => {
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mockFetch.mockResolvedValue(okResponse({ data: [{ id: 'gpt-4o' }] }));
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expect(await makeAdapter('gpt-4o').healthCheck()).toBe(true);
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});
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});
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// ===== 非流式响应组装 =====
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describe('OpenAIAdapter — 非流式响应组装', () => {
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it('send 返回 MetonaResponse（content/usage/finishReason 映射）', async () => {
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const adapter = makeAdapter('gpt-4o');
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mockFetch.mockResolvedValue(
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okResponse({
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id: 'cmpl-1',
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model: 'gpt-4o',
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choices: [{ message: { content: 'hello' }, finish_reason: 'stop' }],
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usage: { prompt_tokens: 10, completion_tokens: 5, total_tokens: 15 },
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||||
}),
|
||||
);
|
||||
const res = await adapter.send(makeRequest());
|
||||
expect(res.content).toBe('hello');
|
||||
expect(res.finishReason).toBe('stop');
|
||||
expect(res.usage.totalTokens).toBe(15);
|
||||
expect(res.meta.provider).toBe('openai');
|
||||
});
|
||||
|
||||
it('HTTP 非 2xx → 抛出带 status 的 Error', async () => {
|
||||
const adapter = makeAdapter('gpt-4o');
|
||||
mockFetch.mockResolvedValue({
|
||||
ok: false,
|
||||
status: 429,
|
||||
statusText: 'Too Many Requests',
|
||||
text: async () => '{"error":{"message":"rate limited"}}',
|
||||
} as unknown as Response);
|
||||
const err = await adapter.send(makeRequest()).catch((e: unknown) => e);
|
||||
expect((err as Error & { status?: number }).status).toBe(429);
|
||||
});
|
||||
|
||||
it('content_filter 错误体 → ContentFilterError 实例', async () => {
|
||||
const adapter = makeAdapter('gpt-4o');
|
||||
mockFetch.mockResolvedValue({
|
||||
ok: false,
|
||||
status: 400,
|
||||
statusText: 'Bad Request',
|
||||
text: async () => '{"error":{"code":"content_filter","message":"blocked"}}',
|
||||
} as unknown as Response);
|
||||
const err = await adapter.send(makeRequest()).catch((e: unknown) => e);
|
||||
expect((err as { name: string }).name).toBe('ContentFilterError');
|
||||
});
|
||||
|
||||
it('sendStream 走 SSE 解析（[DONE] 结束）', async () => {
|
||||
const adapter = makeAdapter('gpt-4o');
|
||||
const payload =
|
||||
'data: {"choices":[{"delta":{"content":"hi"}}]}\n\n' +
|
||||
'data: {"choices":[{"delta":{"content":""},"finish_reason":"stop"}]}\n\n' +
|
||||
'data: [DONE]\n\n';
|
||||
const body = new ReadableStream<Uint8Array>({
|
||||
start(controller) {
|
||||
controller.enqueue(new TextEncoder().encode(payload));
|
||||
controller.close();
|
||||
},
|
||||
});
|
||||
mockFetch.mockResolvedValue(new Response(body, { status: 200 }));
|
||||
const events: string[] = [];
|
||||
for await (const ev of adapter.sendStream(makeRequest({ params: { stream: true } }))) {
|
||||
events.push(ev.type);
|
||||
}
|
||||
expect(events[0]).toBe('text_delta');
|
||||
expect(events[events.length - 1]).toBe('done');
|
||||
});
|
||||
});
|
||||
|
||||
// ===== stop 序列 =====
|
||||
|
||||
describe('OpenAIAdapter — stop 序列透传', () => {
|
||||
it('stopSequences 透传为 stop 数组（o 系列已知边界透传）', async () => {
|
||||
const adapter = makeAdapter('gpt-4o');
|
||||
mockFetch.mockResolvedValue(okResponse());
|
||||
await adapter.send(
|
||||
makeRequest({
|
||||
params: { maxTokens: 4096, temperature: 0, stream: false, stopSequences: ['END'] },
|
||||
}),
|
||||
);
|
||||
expect(lastBody().stop).toEqual(['END']);
|
||||
});
|
||||
|
||||
it('未配置 stopSequences 不发送 stop', async () => {
|
||||
const adapter = makeAdapter('gpt-4o');
|
||||
mockFetch.mockResolvedValue(okResponse());
|
||||
await adapter.send(makeRequest());
|
||||
expect(lastBody().stop).toBeUndefined();
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user