Files
metona-ai-desktop/e2e/mock-llm.ts
T
thzxx 9b45c445bf
CI / 类型检查 + Lint + 单元测试 (push) Failing after 9m8s
CI / 全量测试 (Electron ABI) (push) Failing after 6m0s
CI / 产物编译验证 (push) Successful in 10m58s
feat: v0.8.1 记忆深化 · 观测闭环 · 体验收口 — 窗口/输出上限全局单一配置 · 2478 用例全量回归 + E2E 冒烟
硬性契约:删除代码中一切写死的上下文窗口与最大输出上限(含六家模型元信息
钳制与全部兜底值)——唯一合法来源是设置面板「上下文长度」(llm.contextWindow)
与「最大输出上限」(llm.maxTokens),跨 Provider/模型原样透传。

P0 正确性收口:
- 迁移 11/12(SCHEMA_VERSION 5):记忆表 embedding 列 + 分 Provider 窗口键清理
- 记忆生命周期接线:会话终态清理 working memory / episodic 90 天 TTL / access_count 回写
- 回放缓冲模块化 + 会话终态清理(杜绝 4MB/会话内存滞留)
- i18n 收口:主进程 main-locale(zh/en,ui.locale 热切换)+ 渲染层 17 处出层

P1 能力演进:
- 本地向量混合检索:0.6×向量余弦 + 0.4×TF-IDF,Ollama embeddings 首次投产,
  存量记忆惰性回填,嵌入不可用自动回退 TF-IDF
- MEMORY.md 维护闭环:固化去重消除截断盲区;两阶段维护(AI 建议 → 用户确认 →
  原子改写 + 语义记忆双轨同步 + 审计);>50KB 告警
- 可观测闭环:cacheTokens 引擎→前端透传(Token 面板命中率/成本行)+ 输入框
  上下文占用指示条
- MCP Prompts/Resources 对话可用:/mcp:{server}:{prompt} 与 @mcp:{server}:{uri}

P2 体验补全:
- 工具自定义策略(正则白/黑名单 + 频率 + 强制确认,热生效)
- 连续 ≥3 同类工具确认聚合为单弹框
- 会话消息游标分页(首屏 200 条向上翻页)
- 开机自启;Playwright + Electron E2E 冒烟(本地 mock LLM 零外联)

Review 回归修复:MCP 大小写失配 / 分页状态复位 / 清空=未配置语义(Number(null)=0
隐患)/ MEMORY.md 告警位置 / working_memories FK(迁移 13)/ 全局配置层废键清理;
附带根治权限加固启动时序、代理回环放行、safeStorage 降级、悬空 symlink 逃逸。

验证:typecheck/lint 0 问题;test:electron 2478/2478(0 跳过);E2E 2/2;
docs/v0.8.1-迭代实施清单.md 全项留档。
2026-09-08 09:35:58 +08:00

102 lines
3.2 KiB
TypeScript
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/**
* Mock LLM Server — E2E 冒烟测试的本地 OpenAI 兼容 Providerv0.8.1 P2-5
*
* 实现 DeepSeek 适配器实际消费的最小协议面:
* - POST {baseURL}/chat/completionsstream=true):按 SSE 推送一段固定文本 +
* finish_reason=stop + usage + [DONE]
* - POST /chat/completionsstream=false):非流式 JSON(压缩摘要等内部调用兜底)。
*
* 端口随机分配(127.0.0.1),测试结束关闭 —— 不触外网、不落真实会话数据。
*/
import { createServer, type Server } from 'http';
import type { AddressInfo } from 'net';
/** 流式回复的固定文本(断言锚点) */
export const MOCK_REPLY = 'Hello from mock LLM. E2E smoke reply.';
export interface MockLLMHandle {
url: string;
close: () => Promise<void>;
/** 收到的 chat/completions 请求体列表(断言用) */
readonly requests: Array<Record<string, unknown>>;
}
export function startMockLLM(): Promise<MockLLMHandle> {
const requests: Array<Record<string, unknown>> = [];
const server: Server = createServer((req, res) => {
if (!req.url?.includes('/chat/completions')) {
res.writeHead(404).end();
return;
}
let body = '';
req.on('data', (chunk) => {
body += chunk;
});
req.on('end', () => {
let parsed: Record<string, unknown> = {};
try {
parsed = JSON.parse(body) as Record<string, unknown>;
} catch {
/* 忽略解析失败 */
}
requests.push(parsed);
const isStream = parsed.stream === true;
if (!isStream) {
res.writeHead(200, { 'Content-Type': 'application/json' });
res.end(
JSON.stringify({
id: 'mock-1',
model: parsed.model ?? 'mock',
choices: [
{
index: 0,
message: { role: 'assistant', content: MOCK_REPLY },
finish_reason: 'stop',
},
],
usage: { prompt_tokens: 10, completion_tokens: 8, total_tokens: 18 },
}),
);
return;
}
res.writeHead(200, {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
Connection: 'keep-alive',
});
const frame = (payload: Record<string, unknown>): void => {
res.write(`data: ${JSON.stringify(payload)}\n\n`);
};
// 首 chunk:正文增量
frame({
id: 'mock-1',
model: parsed.model ?? 'mock',
choices: [{ index: 0, delta: { role: 'assistant', content: MOCK_REPLY } }],
});
// 末帧:finish_reason + usage
frame({
id: 'mock-1',
model: parsed.model ?? 'mock',
choices: [{ index: 0, delta: {}, finish_reason: 'stop' }],
usage: { prompt_tokens: 10, completion_tokens: 8, total_tokens: 18 },
});
res.write('data: [DONE]\n\n');
res.end();
});
});
return new Promise((resolve) => {
server.listen(0, '127.0.0.1', () => {
const addr = server.address() as AddressInfo;
resolve({
url: `http://127.0.0.1:${addr.port}`,
close: () => new Promise<void>((r) => server.close(() => r())),
requests,
});
});
});
}