198 lines
4.7 KiB
Markdown
198 lines
4.7 KiB
Markdown
# SmartMeeting 智能会议
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这是一个基于 Docker Compose 的智能会议部署项目，包含 Speakr 前后端、Paraformer ASR、声纹向量提取服务，以及实时 WebSocket 转写桥接服务。
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## 目录结构
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```text
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/storage01/home/xll/202607/voice
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├── docker-compose.yml # 统一启动文件
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├── config.env # 运行环境变量，主要改这里
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├── asr/main.py # ASR 适配服务代码
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├── speakr/ # Speakr 前后端代码
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├── voice-dected/ # 声纹向量提取服务代码
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├── fastapi_wss/ # 实时 WebSocket 桥接服务代码
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└── deploy/data/ # 运行数据，已被 git 忽略
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```
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## 启动和停止
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启动全部服务：
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```bash
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cd /storage01/home/xll/202607/voice
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docker compose up -d
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```
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查看状态和日志：
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```bash
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docker compose ps
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docker compose logs -f
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```
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停止服务：
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```bash
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docker compose down
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```
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## 服务和端口
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| 服务 | 容器名 | 端口 | 作用 |
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| --- | --- | --- | --- |
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| Speakr | `voice-speakr` | `8899` | 页面和后端 |
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| ASR | `asr-test` | `59805` | Paraformer HTTP / WebSocket 识别 |
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| 声纹提取 | `voice-dected` | `18000` | `/extract_embedding` 声纹向量服务 |
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| 实时桥接 | `fastapi-wss` | `10095` | 页面实时 ASR WebSocket 桥接 |
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| Redis | `voice-redis` | `16380` | 实时桥接的缓存/会话存储 |
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页面访问地址：
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```text
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http://192.168.0.46:8899/tool/speakr/
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```
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浏览器麦克风录音需要安全上下文。局域网 IP 的 HTTP 页面可能无法调用麦克风。最快的本机访问方式是开 SSH 隧道：
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```bash
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ssh -L 8899:127.0.0.1:8899 xll@192.168.0.46
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```
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然后浏览器打开：
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```text
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http://localhost:8899/tool/speakr/
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```
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## 配置文件
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主要修改这个文件：
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```text
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/storage01/home/xll/202607/voice/config.env
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```
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改服务地址、模型地址、LLM 配置、声纹匹配阈值时，优先改 `config.env`。修改后执行：
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```bash
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cd /storage01/home/xll/202607/voice
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docker compose up -d
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```
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重要变量：
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```env
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ASR_BASE_URL=http://asr-test:59805
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TARGET_WS_URL=ws://asr-test:59805/ws/asr
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VOICE_DETECTED_URL=http://voice-dected:8000
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SPEAKER_DET_URL=http://voice-dected:8000/extract_embedding
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REDIS_URL=redis://redis:6379/0
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TEXT_MODEL_BASE_URL=http://192.168.0.46:59800/v1
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TEXT_MODEL_NAME=46-qwen3.5-35B
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TEXT_MODEL_API_KEY=none
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VOICEPRINT_STORE=/data/asr_voiceprints.json
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VOICEPRINT_MATCH_THRESHOLD=0.45
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```
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说明：
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- Compose 内部服务互相访问时，用 `asr-test`、`voice-dected`、`redis` 这种服务名。
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- 宿主机或外部机器访问时，用 `192.168.0.46:59805`、`192.168.0.46:18000`、`192.168.0.46:10095` 这种宿主机端口。
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- `VOICEPRINT_MATCH_THRESHOLD` 是声纹匹配阈值。值越低越容易匹配，值越高越不容易误匹配。
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## 运行数据
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运行数据放在：
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```text
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/storage01/home/xll/202607/voice/deploy/data/
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```
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常见子目录：
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```text
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deploy/data/speakr/uploads/ # 上传和录音文件
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deploy/data/speakr/instance/ # Speakr SQLite 数据库
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deploy/data/asr/ # ASR 声纹库
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deploy/data/redis/ # Redis 持久化数据
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```
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这些运行数据已被 `.gitignore` 忽略，不会提交到仓库。
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## 声纹流程
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Speakr 声纹管理页面会调用 ASR 适配层的兼容接口：
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```text
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POST /voice_insert
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GET /get_voice_name
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DELETE /delete_voice
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```
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ASR 适配层会把声纹向量保存到：
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```text
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deploy/data/asr/asr_voiceprints.json
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```
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转录时，`/asr` 会先把上传音频转成 `16k 单声道 wav`，再调用 `voice-dected` 提取声纹向量，并和已录入声纹做相似度匹配。如果分数超过 `VOICEPRINT_MATCH_THRESHOLD`，返回匹配到的说话人名称。
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目前这个逻辑是“整段音频匹配一个最像的人”。如果一段录音里多人轮流说话，还需要进一步接入分段说话人识别。
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## 常用检查命令
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检查 ASR：
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```bash
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curl http://127.0.0.1:59805/health
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```
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检查声纹列表：
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```bash
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curl http://127.0.0.1:59805/get_voice_name
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```
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检查 Speakr 配置：
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```bash
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curl http://127.0.0.1:8899/tool/speakr/api/config
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```
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检查实时 WebSocket 链路：
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```bash
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docker exec -it fastapi-wss python - <<'PY'
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import asyncio, json, websockets
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async def main():
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async with websockets.connect("ws://127.0.0.1:10095") as ws:
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await ws.send(json.dumps({"mode": "2pass", "is_speaking": True}))
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await ws.send(json.dumps({"type": "stop", "is_speaking": False}))
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print(await ws.recv())
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asyncio.run(main())
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PY
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```
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## Git 操作
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仓库地址：
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```text
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https://gitea.zkzdht.com/Ascend/SmartMeeting.git
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```
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常用命令：
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```bash
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cd /storage01/home/xll/202607/voice
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git status
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git add .
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git commit -m "更新说明"
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git push
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```
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