feat: add git-consistent memory gateway architecture
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lingyuzeng
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TASK-RESULT.md
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TASK-RESULT.md
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# TASK RESULT
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## Research Notes
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1. **当前最适合 pin 的 QMD 版本**
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- 选择 `v1.0.7`（`@tobilu/qmd@1.0.7`），是截至 2026-03-07 的最新非预发布 stable release（发布时间 2026-02-18）。
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2. **是否已有官方 compose 参考**
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- 在 `tobi/qmd` 的 `v1.0.7` 源码树中未找到 `Dockerfile` / `docker-compose.yml` 参考，需要自行实现。
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3. **QMD HTTP MCP 启动与健康检查方式**
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- 启动：`qmd mcp --http`（默认端口 8181）
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- 端点：`POST /mcp`、`GET /health`
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4. **是否需要覆盖默认模型**
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- 第一版不覆盖，直接沿用源码默认模型（embeddinggemma / qwen3-reranker / qmd-query-expansion）。
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5. **Node 与 Bun 在容器中选型**
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- 选 Node（`node:22-bookworm-slim`）。理由：
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- 上游 package `engines.node >=22`
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- `npm install -g @tobilu/qmd@1.0.7` 路径直接、可复现
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- 官方生态和镜像稳定性更高，长期维护成本更低
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6. **缓存目录、索引目录、知识库目录挂载策略**
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- `XDG_CACHE_HOME=/var/lib/qmd/cache`（模型缓存 + 默认 sqlite 索引）
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- `XDG_CONFIG_HOME=/var/lib/qmd/config`（collection YAML 配置）
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- 业务知识库挂载到 `/data/knowledge`
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- 测试数据挂载到 `/data/testdata`
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7. **smoke test 最小闭环覆盖步骤**
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- compose 启动服务
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- `/health` 检查通过
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- 添加 collections（notes/docs/meetings）
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- `qmd update` + `qmd embed`
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- 至少一次 `qmd search`
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- 至少一次 `qmd query`（deep search 等价能力）
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## Implemented Files
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```text
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qmd-docker-http-mcp/
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├─ Dockerfile
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├─ docker-compose.yml
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├─ .dockerignore
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├─ README.md
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├─ TASK-RESULT.md
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├─ scripts/
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│ ├─ entrypoint.sh
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│ ├─ warmup.sh
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│ └─ smoke-test.sh
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├─ knowledge/
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└─ testdata/
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├─ notes/
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├─ docs/
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└─ meetings/
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```
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## Commands Executed (Real)
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```bash
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# Research
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curl -fsSL https://api.github.com/repos/tobi/qmd/releases?per_page=5 | jq ...
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curl -fsSL https://api.github.com/repos/tobi/qmd/git/trees/v1.0.7?recursive=1 | jq -r '.tree[].path' | rg 'docker|compose|Dockerfile|docker-compose' || true
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curl -fsSL https://raw.githubusercontent.com/tobi/qmd/v1.0.7/README.md
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curl -fsSL https://raw.githubusercontent.com/tobi/qmd/v1.0.7/src/llm.ts
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# Build / Run
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cd qmd-docker-http-mcp
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docker build -t hotwa/qmd:latest .
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docker compose up -d
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docker compose logs --no-color --tail=120 qmd
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curl -fsS http://127.0.0.1:8181/health
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# Warmup / Smoke
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./scripts/warmup.sh
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./scripts/smoke-test.sh
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# Extra MCP endpoint check
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curl -X POST http://127.0.0.1:8181/mcp -H 'content-type: application/json' -d '{}'
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```
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## Build Result
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- Image built successfully: `hotwa/qmd:latest`
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- Image inspect summary:
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- `hotwa/qmd:latest b5c811d89722 1.99GB`
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## Compose Startup Result
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- `docker compose up -d` 成功
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- `docker compose ps` 结果：
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- `qmd-http-mcp ... Up ... (healthy) ... 0.0.0.0:8181->8181/tcp`
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## Healthcheck Result
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- `GET /health` 返回成功：
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```json
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{"status":"ok","uptime":244}
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```
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- `POST /mcp` 路由可达（示例请求返回协议校验错误而非 404）：
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- HTTP `406`
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- `Not Acceptable: Client must accept both application/json and text/event-stream`
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## Warmup Result
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- 成功创建并索引 3 个 collection：`notes` / `docs` / `meetings`
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- 成功执行 `qmd update`
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- 成功执行 `qmd embed`
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- 首次运行完成 embedding 模型下载并生成向量
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## Smoke Test Result
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`scripts/smoke-test.sh` 真实执行通过，覆盖：
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- 服务启动与 `/health` 成功
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- collection 检查通过（3/3）
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- `qmd search "incident runbook" --json -n 5` 返回命中（含 `docs/incident-runbook.md`）
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- `qmd query "what is the RTO target for disaster recovery" --json -n 5` 返回命中（`docs/disaster-recovery.md` 得分最高）
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- 脚本最终输出：`[smoke] Smoke test passed`
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## Problems Found and Fixes
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1. **问题：容器外访问 8181 失败（连接被重置）**
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- 根因：QMD `v1.0.7` 的 HTTP MCP 在上游实现中绑定 `localhost`。
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- 修复：在 `entrypoint.sh` 引入 `socat` 转发，将容器 `0.0.0.0:8181` 转发到容器内 QMD 监听端口。
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2. **问题：初版转发到 `127.0.0.1:8182` 仍失败**
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- 根因：QMD 在容器内实际监听 `::1`（IPv6 localhost），`127.0.0.1` 不通。
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- 修复：改为 `socat ... TCP6:[::1]:8182`。
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3. **观察项：首次 query/embed 有 node-llama-cpp 的 CUDA 构建回退告警**
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- 现象：日志提示 `git/cmake not found`，随后回退并继续 CPU 路径，流程最终成功。
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- 结论：当前不阻塞功能闭环，但会增加首次请求噪声与时延。
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## Final Acceptance
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验收条件逐项结果：
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- [x] 成功构建 `hotwa/qmd:latest`
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- [x] `docker compose up -d` 后服务启动
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- [x] `/health` 返回成功
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- [x] 至少一组测试数据被索引
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- [x] 至少一次关键词搜索成功
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- [x] 至少一次深检索/混合检索成功
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- [x] README 可指导复现
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- [x] 本文件记录真实测试过程（无伪造）
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## Sources
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- QMD releases: https://api.github.com/repos/tobi/qmd/releases
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- QMD v1.0.7 README: https://raw.githubusercontent.com/tobi/qmd/v1.0.7/README.md
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- QMD v1.0.7 llm.ts: https://raw.githubusercontent.com/tobi/qmd/v1.0.7/src/llm.ts
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- QMD v1.0.7 mcp.ts: https://raw.githubusercontent.com/tobi/qmd/v1.0.7/src/mcp.ts
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- Codex MCP docs: https://developers.openai.com/codex/mcp/
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- Claude Code MCP docs: https://docs.anthropic.com/en/docs/claude-code/mcp
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