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@@ -121,6 +121,33 @@
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---
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---
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@@ -143,8 +170,8 @@
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#### 🚀 部署方式选择
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#### 🚀 部署方式选择
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||||||
| 部署方式 | 特点 | 适用场景 | 部署文档 | 配置要求 | 视频教程 |
|
| 部署方式 | 特点 | 适用场景 | 部署文档 | 配置要求 | 视频教程 |
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|---------|------|---------|---------|---------|---------|
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|---------|------|---------|---------|---------|---------|
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| **最简化安装** | 智能对话、IOT功能,数据存储在配置文件 | 低配置环境,无需数据库 | [Docker版](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [源码部署](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E5%8F%AA%E8%BF%90%E8%A1%8Cserver)| 如果使用`FunASR`要2核4G,如果全API,要2核2G | - |
|
| **最简化安装** | 智能对话、IOT功能,数据存储在配置文件 | 低配置环境,无需数据库 | [①Docker版](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②源码部署](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E5%8F%AA%E8%BF%90%E8%A1%8Cserver)| 如果使用`FunASR`要2核4G,如果全API,要2核2G | - |
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| **全模块安装** | 智能对话、IOT、OTA、智控台,数据存储在数据库 | 完整功能体验 |[Docker版](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [源码部署](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) | 如果使用`FunASR`要4核8G,如果全API,要2核4G| [本地源码视频教程](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
|
| **全模块安装** | 智能对话、IOT、OTA、智控台,数据存储在数据库 | 完整功能体验 |[①Docker版](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [②源码部署](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [③源码部署自动更新教程](./docs/dev-ops-integration.md) | 如果使用`FunASR`要4核8G,如果全API,要2核4G| [本地源码启动视频教程](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
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> 💡 提示:以下是按最新代码部署后的测试平台,有需要可烧录测试,并发为6个,每天会清空数据
|
> 💡 提示:以下是按最新代码部署后的测试平台,有需要可烧录测试,并发为6个,每天会清空数据
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@@ -159,34 +186,47 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
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#### 🚩 配置说明和推荐
|
#### 🚩 配置说明和推荐
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> [!Note]
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> [!Note]
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||||||
> 本项目默认的配置是`入门全免费`设置,如果想效果更优,推荐使用`全流式配置`。
|
> 本项目默认的配置是`入门全免费`设置,如果想效果更优,推荐使用`流式配置`。
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>
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>
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||||||
> 本项目自`0.5.2`版本,已支持整个生命周期全流式,相比`0.5`版本以前,响应速度提升约`2.5秒`
|
> 本项目自`0.5.2`版本,已支持使用流式配置,相比`0.5`版本以前,响应速度提升约`2.5秒`
|
||||||
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| 模块名称 | 入门全免费设置 | 流式配置 |
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| 模块名称 | 入门全免费设置 | 全流式配置 |
|
|:---:|:---:|:---:|
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||||||
|---------|---------|------|
|
| ASR(语音识别) | FunASR(本地) | 👍DoubaoStreamASR(火山流式语音识别) |
|
||||||
| ASR(语音识别) | FunASR(本地) | ✅DoubaoASR(火山流式语音识别) |
|
| LLM(大模型) | ChatGLMLLM(智谱glm-4-flash) | 👍DoubaoLLM(火山doubao-1-5-pro-32k-250115) |
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||||||
| LLM(大模型) | ChatGLMLLM(智谱glm-4-flash) | ✅DoubaoLLM(火山doubao-1-5-pro-32k-250115) |
|
| VLLM(视觉大模型) | ChatGLMVLLM(智谱glm-4v-flash) | 👍QwenVLVLLM(千问qwen2.5-vl-3b-instructh) |
|
||||||
| TTS(语音合成) | EdgeTTS(微软语音) | ✅HuoshanDoubleStreamTTS(火山双流式语音合成) |
|
| TTS(语音合成) | EdgeTTS(微软语音) | 👍HuoshanDoubleStreamTTS(火山双流式语音合成) |
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||||||
| Intent(意图识别) | function_call(函数调用) | ✅function_call(函数调用) |
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| Intent(意图识别) | function_call(函数调用) | ✅function_call(函数调用) |
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||||||
| Memory(记忆功能) | mem_local_short(本地短期记忆) | ✅mem_local_short(本地短期记忆) |
|
| Memory(记忆功能) | mem_local_short(本地短期记忆) | ✅mem_local_short(本地短期记忆) |
|
||||||
|
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||||||
|
#### 🔧 测试工具
|
||||||
|
本项目提供以下测试工具,帮助您验证系统和选择合适的模型:
|
||||||
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||||||
|
| 工具名称 | 位置 | 使用方法 | 功能说明 |
|
||||||
|
|:---:|:---|:---:|:---:|
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||||||
|
| 音频交互测试工具 | 位于`main/xiaozhi-server/test/test_page.html` | 使用谷歌浏览器直接打开 | 测试音频播放和接收功能,验证Python端音频处理是否正常 |
|
||||||
|
| 模型响应测试工具1 | 位于`main/xiaozhi-server/performance_tester.py` | 执行 `python performance_tester.py` | 测试ASR(语音识别)、LLM(大模型)、TTS(语音合成)三个核心模块的响应速度 |
|
||||||
|
| 模型响应测试工具2 | 位于`main/xiaozhi-server/performance_tester_vllm.py` | 执行 `python performance_tester_vllm.py` | 测试VLLM(视觉模型)的响应速度 |
|
||||||
|
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||||||
|
> 💡 提示:测试模型速度时,只会测试配置了密钥的模型。
|
||||||
|
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||||||
---
|
---
|
||||||
## 功能清单 ✨
|
## 功能清单 ✨
|
||||||
### 已实现 ✅
|
### 已实现 ✅
|
||||||
|
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||||||
| 功能模块 | 描述 |
|
| 功能模块 | 描述 |
|
||||||
|---------|------|
|
|:---:|:---|
|
||||||
| 通信协议 | 基于 `xiaozhi-esp32` 协议,通过 WebSocket 实现数据交互 |
|
| 核心服务架构 | 基于WebSocket和HTTP服务器,提供完整的控制台管理和认证系统 |
|
||||||
| 对话交互 | 支持唤醒对话、手动对话及实时打断。长时间无对话时自动休眠 |
|
| 语音交互系统 | 支持流式ASR(语音识别)、流式TTS(语音合成)、VAD(语音活动检测),支持多语言识别和语音处理 |
|
||||||
| 意图识别 | 支持使用LLM意图识别、function call函数调用,减少硬编码意图判断 |
|
| 智能对话系统 | 支持多种LLM(大语言模型),实现智能对话 |
|
||||||
| 多语言识别 | 支持国语、粤语、英语、日语、韩语(默认使用 FunASR) |
|
| 视觉感知系统 | 支持多种VLLM(视觉大模型),实现多模态交互 |
|
||||||
| LLM 模块 | 支持灵活切换 LLM 模块,默认使用 ChatGLMLLM,也可选用阿里百炼、DeepSeek、Ollama 等接口 |
|
| 意图识别系统 | 支持LLM意图识别、Function Call函数调用,提供插件化意图处理机制 |
|
||||||
| TTS 模块 | 支持 EdgeTTS(默认)、火山引擎豆包 TTS 等多种 TTS 接口,满足语音合成需求 |
|
| 记忆系统 | 支持本地短期记忆、mem0ai接口记忆,具备记忆总结功能 |
|
||||||
| 记忆功能 | 支持超长记忆、本地总结记忆、无记忆三种模式,满足不同场景需求 |
|
| IOT/MCP控制协议 | 支持设备注册管理、智能控制接口,同时支持IOT、MCP控制协议 |
|
||||||
| IOT功能 | 支持管理注册设备IOT功能,支持基于对话上下文语境下的智能物联网控制 |
|
| 管理后台 | 提供Web管理界面,支持用户管理、系统配置和设备管理 |
|
||||||
| 智控台 | 提供Web管理界面,支持智能体管理、用户管理、系统配置等功能,方便管理员和用户进行管理 |
|
| 测试工具 | 提供性能测试工具、视觉模型测试工具和音频交互测试工具 |
|
||||||
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| 部署支持 | 支持Docker部署和本地部署,提供完整的配置文件管理 |
|
||||||
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| 插件系统 | 支持功能插件扩展、自定义插件开发和插件热加载 |
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### 正在开发 🚧
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### 正在开发 🚧
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@@ -223,6 +263,16 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
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---
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---
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||||||
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### VLLM 视觉模型
|
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| 使用方式 | 支持平台 | 免费平台 |
|
||||||
|
|:---:|:---:|:---:|
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||||||
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| openai 接口调用 | 阿里百炼、智谱ChatGLMVLLM | 智谱ChatGLMVLLM |
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实际上,任何支持 openai 接口调用的 VLLM 均可接入使用。
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---
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### TTS 语音合成
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### TTS 语音合成
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| 使用方式 | 支持平台 | 免费平台 |
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| 使用方式 | 支持平台 | 免费平台 |
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+92
-54
@@ -6,14 +6,14 @@
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This project provides backend services for the open-source smart hardware project
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This project provides backend services for the open-source smart hardware project
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||||||
<a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a><br/>
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<a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a><br/>
|
||||||
Implemented using Python, Java, and Vue according to the <a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">Xiaozhi Communication Protocol</a><br/>
|
Implemented using Python, Java, and Vue according to the <a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">Xiaozhi Communication Protocol</a><br/>
|
||||||
Helping you quickly set up your Xiaozhi server
|
Helps you quickly set up your Xiaozhi server
|
||||||
</p>
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</p>
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||||||
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<p align="center">
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<p align="center">
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||||||
<a href="./README.md">中文</a>
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<a href="./README.md">中文</a>
|
||||||
· <a href="./docs/FAQ.md">FAQ</a>
|
· <a href="./docs/FAQ.md">FAQ</a>
|
||||||
· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">Report Issues</a>
|
· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">Report Issues</a>
|
||||||
· <a href="./README_ed.md#deployment-documentation">Deployment Guide</a>
|
· <a href="./README_en.md#deployment-documentation">Deployment Guide</a>
|
||||||
· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">Release Notes</a>
|
· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">Release Notes</a>
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||||||
</p>
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</p>
|
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<p align="center">
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<p align="center">
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@@ -50,7 +50,7 @@ Want to see it in action? Check out these videos 🎥
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<a href="https://www.bilibili.com/video/BV1FMFyejExX" target="_blank">
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|
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<picture>
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<img alt="Xiaozhi esp32 connecting to custom backend model" src="docs/images/demo1.png" />
|
<img alt="Xiaozhi esp32 connecting to own backend model" src="docs/images/demo1.png" />
|
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</a>
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<a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
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|
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<picture>
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<picture>
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<img alt="Cantonese communication" src="docs/images/demo3.png" />
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<img alt="Using Cantonese" src="docs/images/demo3.png" />
|
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</a>
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<a href="https://www.bilibili.com/video/BV1pNXWYGEx1" target="_blank">
|
<a href="https://www.bilibili.com/video/BV1pNXWYGEx1" target="_blank">
|
||||||
<picture>
|
<picture>
|
||||||
<img alt="Home appliance control" src="docs/images/demo5.png" />
|
<img alt="Control home appliances" src="docs/images/demo5.png" />
|
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</picture>
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</a>
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@@ -94,7 +94,7 @@ Want to see it in action? Check out these videos 🎥
|
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<a href="https://www.bilibili.com/video/BV1VC96Y5EMH" target="_blank">
|
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|
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|
||||||
<img alt="Music playback" src="docs/images/demo7.png" />
|
<img alt="Play music" src="docs/images/demo7.png" />
|
||||||
</picture>
|
</picture>
|
||||||
</a>
|
</a>
|
||||||
</td>
|
</td>
|
||||||
@@ -108,7 +108,7 @@ Want to see it in action? Check out these videos 🎥
|
|||||||
<td>
|
<td>
|
||||||
<a href="https://www.bilibili.com/video/BV178XuYfEpi" target="_blank">
|
<a href="https://www.bilibili.com/video/BV178XuYfEpi" target="_blank">
|
||||||
<picture>
|
<picture>
|
||||||
<img alt="IOT device control" src="docs/images/demo9.png" />
|
<img alt="IOT command control" src="docs/images/demo9.png" />
|
||||||
</picture>
|
</picture>
|
||||||
</a>
|
</a>
|
||||||
</td>
|
</td>
|
||||||
@@ -120,6 +120,33 @@ Want to see it in action? Check out these videos 🎥
|
|||||||
</a>
|
</a>
|
||||||
</td>
|
</td>
|
||||||
</tr>
|
</tr>
|
||||||
|
<tr>
|
||||||
|
<td>
|
||||||
|
<a href="https://www.bilibili.com/video/BV12J7WzBEaH" target="_blank">
|
||||||
|
<picture>
|
||||||
|
<img alt="Real-time interruption" src="docs/images/demo10.png" />
|
||||||
|
</picture>
|
||||||
|
</a>
|
||||||
|
</td>
|
||||||
|
<td>
|
||||||
|
<a href="https://www.bilibili.com/video/BV1Co76z7EvK" target="_blank">
|
||||||
|
<picture>
|
||||||
|
<img alt="Photo recognition" src="docs/images/demo12.png" />
|
||||||
|
</picture>
|
||||||
|
</a>
|
||||||
|
</td>
|
||||||
|
<td>
|
||||||
|
<a href="https://www.bilibili.com/video/BV1TJ7WzzEo6" target="_blank">
|
||||||
|
<picture>
|
||||||
|
<img alt="Multi-command tasks" src="docs/images/demo11.png" />
|
||||||
|
</picture>
|
||||||
|
</a>
|
||||||
|
</td>
|
||||||
|
<td>
|
||||||
|
</td>
|
||||||
|
<td>
|
||||||
|
</td>
|
||||||
|
</tr>
|
||||||
</table>
|
</table>
|
||||||
|
|
||||||
---
|
---
|
||||||
@@ -137,91 +164,102 @@ It is recommended that users prioritize service providers with relevant business
|
|||||||
|
|
||||||

|

|
||||||
|
|
||||||
This project offers two deployment methods. Please choose based on your specific needs:
|
This project provides two deployment methods. Please choose according to your specific needs:
|
||||||
|
|
||||||
#### 🚀 Deployment Method Selection
|
#### 🚀 Deployment Method Selection
|
||||||
|
| Deployment Method | Features | Suitable Scenarios | Deployment Guide | Requirements | Video Tutorial |
|
||||||
|
|---------|------|---------|---------|---------|---------|
|
||||||
|
| **Simplified Installation** | Smart dialogue, IOT functionality, data stored in configuration files | Low-configuration environment, no database needed | [Docker Version](./docs/Deployment.md#method-1-docker-server-only) / [Source Code Deployment](./docs/Deployment.md#method-2-local-source-code-server-only) | 2 cores 4G if using `FunASR`, 2 cores 2G if using all APIs | - |
|
||||||
|
| **Full Module Installation** | Smart dialogue, IOT, OTA, Control Panel, data stored in database | Complete functionality experience | [Docker Version](./docs/Deployment_all.md#method-1-docker-full-modules) / [Source Code Deployment](./docs/Deployment_all.md#method-2-local-source-code-full-modules) | 4 cores 8G if using `FunASR`, 2 cores 4G if using all APIs | [Local Source Code Startup Video Tutorial](https://www.bilibili.com/video/BV1wBJhz4Ewe) / [Local Source Code Auto-Update Tutorial](./docs/dev-ops-integration.md) |
|
||||||
|
|
||||||
| Deployment Method | Features | Use Case | Docker Deployment Guide | Source Code Deployment Guide |
|
> 💡 Note: Below are the test platforms deployed with the latest code. You can flash and test if needed. Concurrent users: 6, data will be cleared daily
|
||||||
|---------|------|---------|---------|---------|
|
|
||||||
| **Simplified Installation** | Smart dialogue, IOT functionality, data stored in configuration files | Low-configuration environment, no database required | [Docker Server Only](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) | [Local Source Code Server Only](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E5%8F%AA%E8%BF%90%E8%A1%8Cserver)|
|
|
||||||
| **Full Module Installation** | Smart dialogue, IOT, OTA, Control Panel, data stored in database | Complete functionality experience |[Docker Full Module](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) | [Local Source Code Full Module](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) |
|
|
||||||
|
|
||||||
> 💡 Note: Below is the test platform deployed with the latest code. You can flash and test if needed. Concurrent users: 6, data cleared daily
|
|
||||||
|
|
||||||
```
|
```
|
||||||
Control Panel: https://2662r3426b.vicp.fun
|
Control Panel Address: https://2662r3426b.vicp.fun
|
||||||
|
|
||||||
Service Test Tool: https://2662r3426b.vicp.fun/test/
|
Service Test Tool: https://2662r3426b.vicp.fun/test/
|
||||||
OTA Interface: https://2662r3426b.vicp.fun/xiaozhi/ota/
|
OTA Interface Address: https://2662r3426b.vicp.fun/xiaozhi/ota/
|
||||||
Websocket Interface: wss://2662r3426b.vicp.fun/xiaozhi/v1/
|
Websocket Interface Address: wss://2662r3426b.vicp.fun/xiaozhi/v1/
|
||||||
```
|
```
|
||||||
|
|
||||||
|
#### 🚩 Configuration Description and Recommendations
|
||||||
|
> [!Note]
|
||||||
|
> The default configuration of this project is `Entry Level Free` settings. For better results, we recommend using `Full Streaming Configuration`.
|
||||||
|
>
|
||||||
|
> Since version `0.5.2`, this project supports full streaming throughout the entire lifecycle. Compared to versions before `0.5`, response speed has improved by approximately `2.5 seconds`
|
||||||
|
|
||||||
|
| Module Name | Entry Level Free Settings | Full Streaming Configuration |
|
||||||
|
|---------|---------|------|
|
||||||
|
| ASR(Speech Recognition) | FunASR(Local) | ✅DoubaoASR(Volcano Streaming Speech Recognition) |
|
||||||
|
| LLM(Large Language Model) | ChatGLMLLM(Zhipu glm-4-flash) | ✅DoubaoLLM(Volcano doubao-1-5-pro-32k-250115) |
|
||||||
|
| VLLM(Vision Large Model) | ChatGLMVLLM(Zhipu glm-4v-flash) | ✅ChatGLMVLLM(Zhipu glm-4v-flash) |
|
||||||
|
| TTS(Speech Synthesis) | EdgeTTS(Microsoft Speech) | ✅HuoshanDoubleStreamTTS(Volcano Double Streaming Speech Synthesis) |
|
||||||
|
| Intent(Intent Recognition) | function_call(Function Call) | ✅function_call(Function Call) |
|
||||||
|
| Memory(Memory Function) | mem_local_short(Local Short-term Memory) | ✅mem_local_short(Local Short-term Memory) |
|
||||||
|
|
||||||
---
|
---
|
||||||
## Feature List ✨
|
## Feature List ✨
|
||||||
|
|
||||||
### Implemented ✅
|
### Implemented ✅
|
||||||
|
|
||||||
| Feature Module | Description |
|
| Feature Module | Description |
|
||||||
|---------|------|
|
|---------|------|
|
||||||
| Communication Protocol | Based on `xiaozhi-esp32` protocol, implements data interaction through WebSocket |
|
| Communication Protocol | Based on `xiaozhi-esp32` protocol, implements data interaction through WebSocket |
|
||||||
| Dialogue Interaction | Supports wake-up dialogue, manual dialogue, and real-time interruption. Auto-sleep after long periods of inactivity |
|
| Dialogue Interaction | Supports wake-up dialogue, manual dialogue, and real-time interruption. Auto-sleep after long periods of no dialogue |
|
||||||
| Intent Recognition | Supports LLM intent recognition, function call, reducing hard-coded intent judgment |
|
| Intent Recognition | Supports LLM intent recognition, function call, reducing hard-coded intent judgment |
|
||||||
| Multi-language Recognition | Supports Mandarin, Cantonese, English, Japanese, Korean (default using FunASR) |
|
| Multi-language Recognition | Supports Mandarin, Cantonese, English, Japanese, Korean (default using FunASR) |
|
||||||
| LLM Module | Supports flexible LLM module switching, default using ChatGLMLLM, also supports Ali Bailing, DeepSeek, Ollama, etc. |
|
| LLM Module | Supports flexible LLM module switching, default using ChatGLMLLM, can also use Ali Bailian, DeepSeek, Ollama, etc. |
|
||||||
| TTS Module | Supports EdgeTTS (default), Volcano Engine Doubao TTS, and other TTS interfaces for speech synthesis |
|
| TTS Module | Supports EdgeTTS (default), Volcano Engine Doubao TTS, and other TTS interfaces |
|
||||||
| Memory Function | Supports ultra-long memory, local summary memory, and no memory modes for different scenarios |
|
| Memory Function | Supports ultra-long memory, local summary memory, and no memory modes |
|
||||||
| IOT Function | Supports managing registered device IOT functionality, intelligent IoT control based on dialogue context |
|
| IOT Function | Supports managing registered device IOT functionality, supports smart IoT control based on dialogue context |
|
||||||
| Control Panel | Provides web management interface, supports agent management, user management, system configuration, etc. |
|
| Control Panel | Provides Web management interface, supports agent management, user management, system configuration, etc. |
|
||||||
|
|
||||||
### In Development 🚧
|
### In Development 🚧
|
||||||
|
|
||||||
To learn about specific development progress, [click here](https://github.com/users/xinnan-tech/projects/3)
|
To learn about specific development progress, [click here](https://github.com/users/xinnan-tech/projects/3)
|
||||||
|
|
||||||
If you're a software developer, here's an [Open Letter to Developers](docs/contributor_open_letter.md). Welcome to join!
|
If you are a software developer, here is an [Open Letter to Developers](docs/contributor_open_letter.md). Welcome to join!
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
## Product Ecosystem 👬
|
## Product Ecosystem 👬
|
||||||
Xiaozhi is an ecosystem. When using this product, you might want to check out other excellent projects in this ecosystem:
|
Xiaozhi is an ecosystem. When using this product, you might also want to check out other excellent projects in this ecosystem
|
||||||
|
|
||||||
| Project Name | Project Link | Description |
|
| Project Name | Project Address | Project Description |
|
||||||
|:---------------------|:--------|:--------|
|
|:---------------------|:--------|:--------|
|
||||||
| Xiaozhi Android Client | [xiaozhi-android-client](https://github.com/TOM88812/xiaozhi-android-client) | A Flutter-based Android and iOS voice dialogue application supporting real-time voice interaction and text dialogue |
|
| Xiaozhi Android Client | [xiaozhi-android-client](https://github.com/TOM88812/xiaozhi-android-client) | A Flutter-based Android and iOS voice dialogue application supporting real-time voice interaction and text dialogue. |
|
||||||
| Xiaozhi PC Client | [py-xiaozhi](https://github.com/Huang-junsen/py-xiaozhi) | A Python-based AI client that allows you to experience Xiaozhi AI functionality through code without physical hardware |
|
| Xiaozhi PC Client | [py-xiaozhi](https://github.com/Huang-junsen/py-xiaozhi) | This project provides a Python-based Xiaozhi AI client, allowing you to experience Xiaozhi AI's functionality through code even without physical hardware. |
|
||||||
| Xiaozhi Java Server | [xiaozhi-esp32-server-java](https://github.com/joey-zhou/xiaozhi-esp32-server-java) | A Java-based open-source project providing complete backend service solutions |
|
| Xiaozhi Java Server | [xiaozhi-esp32-server-java](https://github.com/joey-zhou/xiaozhi-esp32-server-java) | The Java version of Xiaozhi open-source backend service is a Java-based open-source project.<br/>It includes both frontend and backend services, aiming to provide users with a complete backend service solution. |
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
## Supported Platforms/Components 📋
|
## Supported Platforms/Components List 📋
|
||||||
|
|
||||||
### LLM Language Models
|
### LLM Language Models
|
||||||
|
|
||||||
| Usage Method | Supported Platforms | Free Platforms |
|
| Usage Method | Supported Platforms | Free Platforms |
|
||||||
|:---:|:---:|:---:|
|
|:---:|:---:|:---:|
|
||||||
| openai API | Ali Bailing, Volcano Engine Doubao, DeepSeek, ChatGLM, Gemini | ChatGLM, Gemini |
|
| openai interface call | Ali Bailian, Volcano Engine Doubao, DeepSeek, Zhipu ChatGLM, Gemini | Zhipu ChatGLM, Gemini |
|
||||||
| ollama API | Ollama | - |
|
| ollama interface call | Ollama | - |
|
||||||
| dify API | Dify | - |
|
| dify interface call | Dify | - |
|
||||||
| fastgpt API | Fastgpt | - |
|
| fastgpt interface call | Fastgpt | - |
|
||||||
| coze API | Coze | - |
|
| coze interface call | Coze | - |
|
||||||
|
|
||||||
Actually, any LLM supporting openai API calls can be integrated.
|
In fact, any LLM that supports openai interface calls can be integrated and used.
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### TTS Speech Synthesis
|
### TTS Speech Synthesis
|
||||||
|
|
||||||
| Usage Method | Supported Platforms | Free Platforms |
|
| Usage Method | Supported Platforms | Free Platforms |
|
||||||
|:---:|:---:|:---:|
|
|:---:|:---:|:---:|
|
||||||
| API Calls | EdgeTTS, Volcano Engine Doubao TTS, Tencent Cloud, Aliyun TTS, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS | EdgeTTS, CosyVoiceSiliconflow(partial) |
|
| API Call | EdgeTTS, Volcano Engine Doubao TTS, Tencent Cloud, Alibaba Cloud TTS, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS | EdgeTTS, CosyVoiceSiliconflow(partial) |
|
||||||
| Local Service | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS |
|
| Local Service | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS |
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
### VAD Voice Activity Detection
|
### VAD Voice Activity Detection
|
||||||
|
|
||||||
| Type | Platform Name | Usage Method | Pricing | Notes |
|
| Type | Platform Name | Usage Method | Pricing Model | Notes |
|
||||||
|:---:|:---------:|:----:|:----:|:--:|
|
|:---:|:---------:|:----:|:----:|:--:|
|
||||||
| VAD | SileroVAD | Local Use | Free | |
|
| VAD | SileroVAD | Local Usage | Free | |
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
@@ -229,26 +267,26 @@ Actually, any LLM supporting openai API calls can be integrated.
|
|||||||
|
|
||||||
| Usage Method | Supported Platforms | Free Platforms |
|
| Usage Method | Supported Platforms | Free Platforms |
|
||||||
|:---:|:---:|:---:|
|
|:---:|:---:|:---:|
|
||||||
| Local Use | FunASR, SherpaASR | FunASR, SherpaASR |
|
| Local Usage | FunASR, SherpaASR | FunASR, SherpaASR |
|
||||||
| API Calls | DoubaoASR, FunASRServer, TencentASR, AliyunASR | FunASRServer |
|
| API Call | DoubaoASR, FunASRServer, TencentASR, AliyunASR | FunASRServer |
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
### Memory Storage
|
### Memory Storage
|
||||||
|
|
||||||
| Type | Platform Name | Usage Method | Pricing | Notes |
|
| Type | Platform Name | Usage Method | Pricing Model | Notes |
|
||||||
|:------:|:---------------:|:----:|:---------:|:--:|
|
|:------:|:---------------:|:----:|:---------:|:--:|
|
||||||
| Memory | mem0ai | API Calls | 1000 calls/month quota | |
|
| Memory | mem0ai | API Call | 1000 calls/month quota | |
|
||||||
| Memory | mem_local_short | Local Summary | Free | |
|
| Memory | mem_local_short | Local Summary | Free | |
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
### Intent Recognition
|
### Intent Recognition
|
||||||
|
|
||||||
| Type | Platform Name | Usage Method | Pricing | Notes |
|
| Type | Platform Name | Usage Method | Pricing Model | Notes |
|
||||||
|:------:|:-------------:|:----:|:-------:|:---------------------:|
|
|:------:|:-------------:|:----:|:-------:|:---------------------:|
|
||||||
| Intent | intent_llm | API Calls | Based on LLM pricing | Uses large model for intent recognition, highly versatile |
|
| Intent | intent_llm | API Call | Based on LLM pricing | Uses large model for intent recognition, highly versatile |
|
||||||
| Intent | function_call | API Calls | Based on LLM pricing | Uses large model function calls for intent, fast and effective |
|
| Intent | function_call | API Call | Based on LLM pricing | Uses large model function calls for intent, fast and effective |
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
@@ -257,10 +295,10 @@ Actually, any LLM supporting openai API calls can be integrated.
|
|||||||
| Logo | Project/Company | Description |
|
| Logo | Project/Company | Description |
|
||||||
|:---:|:---:|:---|
|
|:---:|:---:|:---|
|
||||||
| <img src="./docs/images/logo_bailing.png" width="160"> | [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) | This project was inspired by [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) and implemented based on it |
|
| <img src="./docs/images/logo_bailing.png" width="160"> | [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) | This project was inspired by [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) and implemented based on it |
|
||||||
| <img src="./docs/images/logo_tenclass.png" width="160"> | [Tenclass](https://www.tenclass.com/) | Thanks to [Tenclass](https://www.tenclass.com/) for developing standard communication protocols, multi-device compatibility solutions, and high-concurrency scenario practices for the Xiaozhi ecosystem; providing comprehensive technical documentation support for this project |
|
| <img src="./docs/images/logo_tenclass.png" width="160"> | [Tenclass](https://www.tenclass.com/) | Thanks to [Tenclass](https://www.tenclass.com/) for establishing standard communication protocols, multi-device compatibility solutions, and high-concurrency scenario practices for the Xiaozhi ecosystem; providing full-chain technical documentation support for this project |
|
||||||
| <img src="./docs/images/logo_xuanfeng.png" width="160"> | [Xuanfeng Technology](https://github.com/Eric0308) | Thanks to [Xuanfeng Technology](https://github.com/Eric0308) for contributing function call framework, MCP communication protocol, and plugin call mechanism implementation code, significantly improving front-end device (IoT) interaction efficiency and functional extensibility through standardized instruction scheduling system and dynamic expansion capabilities |
|
| <img src="./docs/images/logo_xuanfeng.png" width="160"> | [Xuanfeng Technology](https://github.com/Eric0308) | Thanks to [Xuanfeng Technology](https://github.com/Eric0308) for contributing the function call framework, MCP communication protocol, and plugin call mechanism implementation code, significantly improving front-end device (IoT) interaction efficiency and functional extensibility through standardized instruction scheduling system and dynamic expansion capabilities |
|
||||||
| <img src="./docs/images/logo_huiyuan.png" width="160"> | [Huiyuan Design](http://ui.kwd988.net/) | Thanks to [Huiyuan Design](http://ui.kwd988.net/) for providing professional visual solutions for this project, empowering product user experience with their design experience serving over a thousand enterprises |
|
| <img src="./docs/images/logo_huiyuan.png" width="160"> | [Huiyuan Design](http://ui.kwd988.net/) | Thanks to [Huiyuan Design](http://ui.kwd988.net/) for providing professional visual solutions for this project, empowering the product user experience with their design experience serving over a thousand enterprises |
|
||||||
| <img src="./docs/images/logo_qinren.png" width="160"> | [Xi'an Qinren Information Technology](https://www.029app.com/) | Thanks to [Xi'an Qinren Information Technology](https://www.029app.com/) for deepening this project's visual system, ensuring consistency and extensibility of overall design style in multi-scenario applications |
|
| <img src="./docs/images/logo_qinren.png" width="160"> | [Xi'an Qinren Information Technology](https://www.029app.com/) | Thanks to [Xi'an Qinren Information Technology](https://www.029app.com/) for deepening the visual system of this project, ensuring consistency and extensibility of the overall design style in multi-scenario applications |
|
||||||
|
|
||||||
|
|
||||||
<a href="https://star-history.com/#xinnan-tech/xiaozhi-esp32-server&Date">
|
<a href="https://star-history.com/#xinnan-tech/xiaozhi-esp32-server&Date">
|
||||||
@@ -270,4 +308,4 @@ Actually, any LLM supporting openai API calls can be integrated.
|
|||||||
<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date" />
|
<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date" />
|
||||||
<img alt="Star History Chart" src="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date" />
|
<img alt="Star History Chart" src="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date" />
|
||||||
</picture>
|
</picture>
|
||||||
</a>
|
</a>
|
||||||
|
|||||||
+5
-1
@@ -108,7 +108,11 @@ VAD:
|
|||||||
|
|
||||||
参考教程[阿里云短信集成指南](./ali-sms-integration.md)
|
参考教程[阿里云短信集成指南](./ali-sms-integration.md)
|
||||||
|
|
||||||
### 9、更多问题,可联系我们反馈 💬
|
### 9、如何开启视觉模型实现拍照识物 📷
|
||||||
|
|
||||||
|
参考教程[视觉模型使用指南](./mcp-vision-integration.md)
|
||||||
|
|
||||||
|
### 10、更多问题,可联系我们反馈 💬
|
||||||
|
|
||||||
可以在[issues](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues)提交您的问题。
|
可以在[issues](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues)提交您的问题。
|
||||||
|
|
||||||
|
|||||||
@@ -0,0 +1,163 @@
|
|||||||
|
# 全模块源码部署自动升级方法
|
||||||
|
|
||||||
|
本教程是方便全模块源码部署的爱好者,如何通过自动命令,自动拉取源码,自动编译,自动启动端口运行。实现最高效率的升级系统。
|
||||||
|
|
||||||
|
本项目的测试平台`https://2662r3426b.vicp.fun`,从开放以来就使用了该方法,效果良好。
|
||||||
|
|
||||||
|
# 开始条件
|
||||||
|
- 你的电脑/服务器是linux操作系统
|
||||||
|
- 你已经跑通了整个流程
|
||||||
|
- 你喜欢跟进最新功能,但是觉得每次手动部署有点麻烦,期待有一个自动更新的方法
|
||||||
|
|
||||||
|
第二个条件必须满足,因为本教程所涉及的某些文件,JDK、Node.js环境、Conda环境等,是需要你跑通整个流程才有的,如果你没有跑通,当我讲到某个文件的时候,你可能就不知道什么意思。
|
||||||
|
|
||||||
|
# 教程效果
|
||||||
|
- 解决国内不能拉取最新项目源码问题
|
||||||
|
- 自动拉取代码编译前端文件
|
||||||
|
- 自动拉取代码编译java文件,自动杀掉8002端口,自动启动8002端口
|
||||||
|
- 自动拉取python代码,自动杀掉8000端口,自动启动8000端口
|
||||||
|
|
||||||
|
# 第一步 选好你的项目目录
|
||||||
|
|
||||||
|
例如,我规划了我的项目目录是,这是一个新建的空白的目录,如果你不想出错,可以和我一样
|
||||||
|
```
|
||||||
|
/home/system/xiaozhi
|
||||||
|
```
|
||||||
|
|
||||||
|
# 第二步 克隆本项目
|
||||||
|
此刻,先要执行第一句话,拉取源码,这句命令适用于国内网络的服务器和电脑,无需翻墙
|
||||||
|
|
||||||
|
```
|
||||||
|
cd /home/system/xiaozhi
|
||||||
|
git clone https://ghproxy.net/https://github.com/xinnan-tech/xiaozhi-esp32-server.git
|
||||||
|
```
|
||||||
|
|
||||||
|
执行完后,你的项目目录会多了一个文件夹`xiaozhi-esp32-server`,这个就是项目的源码
|
||||||
|
|
||||||
|
# 第三步 复制基础的文件
|
||||||
|
|
||||||
|
如果你之前已经跑通了整个流程,对funasr的模型文件`xiaozhi-server/models/SenseVoiceSmall/model.pt`和你的私有配置文件`xiaozhi-server/data/.config.yaml`这两个文件不会陌生。
|
||||||
|
|
||||||
|
此刻你需要把`model.pt`文件复制到新的目录去,你可以这样
|
||||||
|
```
|
||||||
|
cp 你原来的.config.yaml完整路径 /home/system/xiaozhi/xiaozhi-esp32-server/main/xiaozhi-server/data/.config.yaml
|
||||||
|
cp 你原来的model.pt完整路径 /home/system/xiaozhi/xiaozhi-esp32-server/main/xiaozhi-server/models/SenseVoiceSmall/model.pt
|
||||||
|
```
|
||||||
|
|
||||||
|
# 第四步 建立三个自动编译文件
|
||||||
|
|
||||||
|
## 4.1 自动编译mananger-web模块
|
||||||
|
在`/home/system/xiaozhi/`目录下,创建名字为`update_8001.sh`的文件,内容如下
|
||||||
|
|
||||||
|
```
|
||||||
|
cd /home/system/xiaozhi/xiaozhi-esp32-server
|
||||||
|
git fetch --all
|
||||||
|
git reset --hard
|
||||||
|
git pull origin main
|
||||||
|
|
||||||
|
|
||||||
|
cd /home/system/xiaozhi/xiaozhi-esp32-server/main/manager-web
|
||||||
|
npm install
|
||||||
|
npm run build
|
||||||
|
rm -rf /home/system/xiaozhi/manager-web
|
||||||
|
mv /home/system/xiaozhi/xiaozhi-esp32-server/main/manager-web/dist /home/system/xiaozhi/manager-web
|
||||||
|
```
|
||||||
|
|
||||||
|
保存好后执行赋权命令
|
||||||
|
```
|
||||||
|
chmod 777 update_8001.sh
|
||||||
|
```
|
||||||
|
执行完后,继续往下
|
||||||
|
|
||||||
|
## 4.2 自动编译运行manager-api模块
|
||||||
|
在`/home/system/xiaozhi/`目录下,创建名字为`update_8002.sh`的文件,内容如下
|
||||||
|
|
||||||
|
```
|
||||||
|
cd /home/system/xiaozhi/xiaozhi-esp32-server
|
||||||
|
git pull origin main
|
||||||
|
|
||||||
|
|
||||||
|
cd /home/system/xiaozhi/xiaozhi-esp32-server/main/manager-api
|
||||||
|
rm -rf target
|
||||||
|
mvn clean package -Dmaven.test.skip=true
|
||||||
|
cd /home/system/xiaozhi/
|
||||||
|
|
||||||
|
# 查找占用8002端口的进程号
|
||||||
|
PID=$(sudo netstat -tulnp | grep 8002 | awk '{print $7}' | cut -d'/' -f1)
|
||||||
|
|
||||||
|
rm -rf /home/system/xiaozhi/xiaozhi-esp32-api.jar
|
||||||
|
mv /home/system/xiaozhi/xiaozhi-esp32-server/main/manager-api/target/xiaozhi-esp32-api.jar /home/system/xiaozhi/xiaozhi-esp32-api.jar
|
||||||
|
|
||||||
|
# 检查是否找到进程号
|
||||||
|
if [ -z "$PID" ]; then
|
||||||
|
echo "没有找到占用8002端口的进程"
|
||||||
|
else
|
||||||
|
echo "找到占用8002端口的进程,进程号为: $PID"
|
||||||
|
# 杀掉进程
|
||||||
|
kill -9 $PID
|
||||||
|
kill -9 $PID
|
||||||
|
echo "已杀掉进程 $PID"
|
||||||
|
fi
|
||||||
|
|
||||||
|
nohup java -jar xiaozhi-esp32-api.jar --spring.profiles.active=dev &
|
||||||
|
```
|
||||||
|
|
||||||
|
保存好后执行赋权命令
|
||||||
|
```
|
||||||
|
chmod 777 update_8002.sh
|
||||||
|
```
|
||||||
|
执行完后,继续往下
|
||||||
|
|
||||||
|
## 4.3 自动编译运行Python项目
|
||||||
|
在`/home/system/xiaozhi/`目录下,创建名字为`update_8000.sh`的文件,内容如下
|
||||||
|
|
||||||
|
```
|
||||||
|
cd /home/system/xiaozhi/xiaozhi-esp32-server
|
||||||
|
git pull origin main
|
||||||
|
|
||||||
|
# 查找占用8000端口的进程号
|
||||||
|
PID=$(sudo netstat -tulnp | grep 8000 | awk '{print $7}' | cut -d'/' -f1)
|
||||||
|
|
||||||
|
# 检查是否找到进程号
|
||||||
|
if [ -z "$PID" ]; then
|
||||||
|
echo "没有找到占用8000端口的进程"
|
||||||
|
else
|
||||||
|
echo "找到占用8000端口的进程,进程号为: $PID"
|
||||||
|
# 杀掉进程
|
||||||
|
kill -9 $PID
|
||||||
|
kill -9 $PID
|
||||||
|
echo "已杀掉进程 $PID"
|
||||||
|
fi
|
||||||
|
cd main/xiaozhi-server
|
||||||
|
pip install -r requirements.txt
|
||||||
|
nohup python app.py >/dev/null &
|
||||||
|
```
|
||||||
|
|
||||||
|
保存好后执行赋权命令
|
||||||
|
```
|
||||||
|
chmod 777 update_8000.sh
|
||||||
|
```
|
||||||
|
执行完后,继续往下
|
||||||
|
|
||||||
|
# 日常更新
|
||||||
|
|
||||||
|
以上的脚本都建立好后,日常更新,我们只要依次执行以下命令就可以做到自动更新和启动
|
||||||
|
|
||||||
|
```
|
||||||
|
# 进入pyhton环境
|
||||||
|
conda activate xiaozhi-esp32-server
|
||||||
|
cd /home/system/xiaozhi
|
||||||
|
# 更新并启动Java程序
|
||||||
|
./update_8001.sh
|
||||||
|
# 更新web程序
|
||||||
|
./update_8002.sh
|
||||||
|
# 更新并启动python程序
|
||||||
|
./update_8000.sh
|
||||||
|
# 查看Java日志
|
||||||
|
tail -f nohup.out
|
||||||
|
# 查看Python日志
|
||||||
|
tail -f /home/system/xiaozhi/xiaozhi-esp32-server/main/xiaozhi-server/tmp/server.log
|
||||||
|
```
|
||||||
|
|
||||||
|
# 注意事项
|
||||||
|
测试平台`https://2662r3426b.vicp.fun`,是使用nginx做了反向代理。nginx.conf详细配置可以[参考这里](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)
|
||||||
@@ -202,7 +202,15 @@ change_role;get_weather;get_news;play_music;hass_get_state;hass_set_state
|
|||||||
|
|
||||||
#### 2. 配置小智开源服务端MCP配置信息
|
#### 2. 配置小智开源服务端MCP配置信息
|
||||||
|
|
||||||
切换到小智开源服务端`xiaozhi-esp32-server`的`mcp_server_settings.json`文件内,在`"mcpServers"`的括号内添加以下内容:
|
|
||||||
|
进入`data`目录,找到`.mcp_server_settings.json`文件。
|
||||||
|
|
||||||
|
如果你的`data`目录下没有`.mcp_server_settings.json`文件,
|
||||||
|
- 请把在`xiaozhi-server`文件夹根目录的`mcp_server_settings.json`文件复制到`data`目录下,并重命名为`.mcp_server_settings.json`
|
||||||
|
- 或[下载这个文件](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/main/xiaozhi-server/mcp_server_settings.json),下载到`data`目录下,并重命名为`.mcp_server_settings.json`
|
||||||
|
|
||||||
|
|
||||||
|
修改`"mcpServers"`里的这部分的内容:
|
||||||
|
|
||||||
```json
|
```json
|
||||||
"Home Assistant": {
|
"Home Assistant": {
|
||||||
|
|||||||
Binary file not shown.
|
After Width: | Height: | Size: 386 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 518 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 361 KiB |
@@ -0,0 +1,171 @@
|
|||||||
|
# 视觉模型使用指南
|
||||||
|
本教程分为两部分:
|
||||||
|
- 第一部分:单模块运行xiaozhi-server开启视觉模型
|
||||||
|
- 第二部分:全模块运行时,如何开启视觉模型
|
||||||
|
|
||||||
|
开启视觉模型前,你需要准备三件事:
|
||||||
|
- 你需要准备一台带摄像头的设备,而且这台设备已经在虾哥仓库里,实现了调用摄像头功能。例如`立创·实战派ESP32-S3开发板`
|
||||||
|
- 你设备固件的版本升级到1.6.6及以上
|
||||||
|
- 你已经成功跑通基础对话模块
|
||||||
|
|
||||||
|
## 单模块运行xiaozhi-server开启视觉模型
|
||||||
|
|
||||||
|
### 第一步确认网络
|
||||||
|
由于视觉模型会默认启动8003端口。
|
||||||
|
|
||||||
|
如果你是docker运行,请确认一下你的`docker-compose.yml`是否放了`8003`端口,如果没有就更新最新的`docker-compose.yml`文件
|
||||||
|
|
||||||
|
如果你是源码运行,确认防火墙是否放行`8003`端口
|
||||||
|
|
||||||
|
### 第二步选择你的视觉模型
|
||||||
|
打开你的`data/.config.yaml`文件,设置你的`selected_module.VLLM`设置为某个视觉模型。目前我们已经支持`openai`类型接口的视觉模型。`ChatGLMVLLM`就是其中一款兼容`openai`的模型。
|
||||||
|
|
||||||
|
```
|
||||||
|
selected_module:
|
||||||
|
VAD: ..
|
||||||
|
ASR: ..
|
||||||
|
LLM: ..
|
||||||
|
VLLM: ChatGLMVLLM
|
||||||
|
TTS: ..
|
||||||
|
Memory: ..
|
||||||
|
Intent: ..
|
||||||
|
```
|
||||||
|
|
||||||
|
假设我们使用`ChatGLMVLLM`作为视觉模型,那我们需要先登录[智谱AI](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)网站,申请密钥。如果你之前已经申请过了密钥,可以复用这个密钥。
|
||||||
|
|
||||||
|
在你的配置文件中,增加这个配置,如果已经有了这个配置,就设置好你的api_key。
|
||||||
|
|
||||||
|
```
|
||||||
|
VLLM:
|
||||||
|
ChatGLMVLLM:
|
||||||
|
api_key: 你的api_key
|
||||||
|
```
|
||||||
|
|
||||||
|
### 第三步启动xiaozhi-server服务
|
||||||
|
如果你是源码,就输入命令启动
|
||||||
|
```
|
||||||
|
python app.py
|
||||||
|
```
|
||||||
|
如果你是docker运行,就重启容器
|
||||||
|
```
|
||||||
|
docker restart xiaozhi-esp32-server
|
||||||
|
```
|
||||||
|
|
||||||
|
启动后会输出以下内容的日志。
|
||||||
|
|
||||||
|
```
|
||||||
|
2025-06-01 **** - OTA接口是 http://192.168.4.7:8003/xiaozhi/ota/
|
||||||
|
2025-06-01 **** - 视觉分析接口是 http://192.168.4.7:8003/mcp/vision/explain
|
||||||
|
2025-06-01 **** - Websocket地址是 ws://192.168.4.7:8000/xiaozhi/v1/
|
||||||
|
2025-06-01 **** - =======上面的地址是websocket协议地址,请勿用浏览器访问=======
|
||||||
|
2025-06-01 **** - 如想测试websocket请用谷歌浏览器打开test目录下的test_page.html
|
||||||
|
2025-06-01 **** - =============================================================
|
||||||
|
```
|
||||||
|
|
||||||
|
启动后,使用使用浏览器打开日志里`视觉分析接口`连接。看看输出了什么?如果你是linux,没有浏览器,你可以执行这个命令:
|
||||||
|
```
|
||||||
|
curl -i 你的视觉分析接口
|
||||||
|
```
|
||||||
|
|
||||||
|
正常来说会这样显示
|
||||||
|
```
|
||||||
|
MCP Vision 接口运行正常,视觉解释接口地址是:http://xxxx:8003/mcp/vision/explain
|
||||||
|
```
|
||||||
|
|
||||||
|
请注意,如果你是公网部署,或者docker部署,一定要改一下你的`data/.config.yaml`里这个配置
|
||||||
|
```
|
||||||
|
server:
|
||||||
|
vision_explain: http://你的ip或者域名:端口号/mcp/vision/explain
|
||||||
|
```
|
||||||
|
|
||||||
|
为什么呢?因为视觉解释接口需要下发到设备,如果你的地址是局域网地址,或者是docker内部地址,设备是无法访问的。
|
||||||
|
|
||||||
|
假设你的公网地址是`111.111.111.111`,那么`vision_explain`应该这么配
|
||||||
|
|
||||||
|
```
|
||||||
|
server:
|
||||||
|
vision_explain: http://111.111.111.111:8003/mcp/vision/explain
|
||||||
|
```
|
||||||
|
|
||||||
|
如果你的MCP Vision 接口运行正常,且你也试着用浏览器访问正常打开下发的`视觉解释接口地址`,请继续下一步
|
||||||
|
|
||||||
|
### 第四步 设备唤醒开启
|
||||||
|
|
||||||
|
对设备说“请打开摄像头,说你你看到了什么”
|
||||||
|
|
||||||
|
留意xiaozhi-server的日志输出,看看有没有报错。
|
||||||
|
|
||||||
|
|
||||||
|
## 全模块运行时,如何开启视觉模型
|
||||||
|
|
||||||
|
### 第一步 确认网络
|
||||||
|
由于视觉模型会默认启动8003端口。
|
||||||
|
|
||||||
|
如果你是docker运行,请确认一下你的`docker-compose_all.yml`是否映射了`8003`端口,如果没有就更新最新的`docker-compose_all.yml`文件
|
||||||
|
|
||||||
|
如果你是源码运行,确认防火墙是否放行`8003`端口
|
||||||
|
|
||||||
|
### 第二步 确认你配置文件
|
||||||
|
|
||||||
|
打开你的`data/.config.yaml`文件,确认一下你的配置文件的结构,是否和`data/config_from_api.yaml`一样。如果不一样,或缺少某项,请补齐。
|
||||||
|
|
||||||
|
### 第三步 配置视觉模型密钥
|
||||||
|
|
||||||
|
那我们需要先登录[智谱AI](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)网站,申请密钥。如果你之前已经申请过了密钥,可以复用这个密钥。
|
||||||
|
|
||||||
|
登录`智控台`,顶部菜单点击`模型配置`,在左侧栏点击`视觉打语言模型`,找到`VLLM_ChatGLMVLLM`,点击修改按钮,在弹框中,在`API密钥`输入你密钥,点击保存。
|
||||||
|
|
||||||
|
保存成功后,去到你需要测试的智能体哪里,点击`配置角色`,在打开的内容里,查看`视觉大语言模型(VLLM)`是否选择了刚才的视觉模型。点击保存。
|
||||||
|
|
||||||
|
### 第三步 启动xiaozhi-server模块
|
||||||
|
如果你是源码,就输入命令启动
|
||||||
|
```
|
||||||
|
python app.py
|
||||||
|
```
|
||||||
|
如果你是docker运行,就重启容器
|
||||||
|
```
|
||||||
|
docker restart xiaozhi-esp32-server
|
||||||
|
```
|
||||||
|
|
||||||
|
启动后会输出以下内容的日志。
|
||||||
|
|
||||||
|
```
|
||||||
|
2025-06-01 **** - 视觉分析接口是 http://192.168.4.7:8003/mcp/vision/explain
|
||||||
|
2025-06-01 **** - Websocket地址是 ws://192.168.4.7:8000/xiaozhi/v1/
|
||||||
|
2025-06-01 **** - =======上面的地址是websocket协议地址,请勿用浏览器访问=======
|
||||||
|
2025-06-01 **** - 如想测试websocket请用谷歌浏览器打开test目录下的test_page.html
|
||||||
|
2025-06-01 **** - =============================================================
|
||||||
|
```
|
||||||
|
|
||||||
|
启动后,使用使用浏览器打开日志里`视觉分析接口`连接。看看输出了什么?如果你是linux,没有浏览器,你可以执行这个命令:
|
||||||
|
```
|
||||||
|
curl -i 你的视觉分析接口
|
||||||
|
```
|
||||||
|
|
||||||
|
正常来说会这样显示
|
||||||
|
```
|
||||||
|
MCP Vision 接口运行正常,视觉解释接口地址是:http://xxxx:8003/mcp/vision/explain
|
||||||
|
```
|
||||||
|
|
||||||
|
请注意,如果你是公网部署,或者docker部署,一定要改一下你的`data/.config.yaml`里这个配置
|
||||||
|
```
|
||||||
|
server:
|
||||||
|
vision_explain: http://你的ip或者域名:端口号/mcp/vision/explain
|
||||||
|
```
|
||||||
|
|
||||||
|
为什么呢?因为视觉解释接口需要下发到设备,如果你的地址是局域网地址,或者是docker内部地址,设备是无法访问的。
|
||||||
|
|
||||||
|
假设你的公网地址是`111.111.111.111`,那么`vision_explain`应该这么配
|
||||||
|
|
||||||
|
```
|
||||||
|
server:
|
||||||
|
vision_explain: http://111.111.111.111:8003/mcp/vision/explain
|
||||||
|
```
|
||||||
|
|
||||||
|
如果你的MCP Vision 接口运行正常,且你也试着用浏览器访问正常打开下发的`视觉解释接口地址`,请继续下一步
|
||||||
|
|
||||||
|
### 第四步 设备唤醒开启
|
||||||
|
|
||||||
|
对设备说“请打开摄像头,说你你看到了什么”
|
||||||
|
|
||||||
|
留意xiaozhi-server的日志输出,看看有没有报错。
|
||||||
@@ -227,7 +227,7 @@ public interface Constant {
|
|||||||
/**
|
/**
|
||||||
* 版本号
|
* 版本号
|
||||||
*/
|
*/
|
||||||
public static final String VERSION = "0.5.2";
|
public static final String VERSION = "0.5.4";
|
||||||
|
|
||||||
/**
|
/**
|
||||||
* 无效固件URL
|
* 无效固件URL
|
||||||
|
|||||||
@@ -171,6 +171,9 @@ public class AgentController {
|
|||||||
if (dto.getLlmModelId() != null) {
|
if (dto.getLlmModelId() != null) {
|
||||||
existingEntity.setLlmModelId(dto.getLlmModelId());
|
existingEntity.setLlmModelId(dto.getLlmModelId());
|
||||||
}
|
}
|
||||||
|
if (dto.getVllmModelId() != null) {
|
||||||
|
existingEntity.setVllmModelId(dto.getVllmModelId());
|
||||||
|
}
|
||||||
if (dto.getTtsModelId() != null) {
|
if (dto.getTtsModelId() != null) {
|
||||||
existingEntity.setTtsModelId(dto.getTtsModelId());
|
existingEntity.setTtsModelId(dto.getTtsModelId());
|
||||||
}
|
}
|
||||||
|
|||||||
@@ -27,6 +27,9 @@ public class AgentDTO {
|
|||||||
@Schema(description = "大语言模型名称", example = "llm_model_01")
|
@Schema(description = "大语言模型名称", example = "llm_model_01")
|
||||||
private String llmModelName;
|
private String llmModelName;
|
||||||
|
|
||||||
|
@Schema(description = "视觉模型名称", example = "vllm_model_01")
|
||||||
|
private String vllmModelName;
|
||||||
|
|
||||||
@Schema(description = "记忆模型ID", example = "mem_model_01")
|
@Schema(description = "记忆模型ID", example = "mem_model_01")
|
||||||
private String memModelId;
|
private String memModelId;
|
||||||
|
|
||||||
|
|||||||
@@ -30,6 +30,9 @@ public class AgentUpdateDTO implements Serializable {
|
|||||||
@Schema(description = "大语言模型标识", example = "llm_model_02", required = false)
|
@Schema(description = "大语言模型标识", example = "llm_model_02", required = false)
|
||||||
private String llmModelId;
|
private String llmModelId;
|
||||||
|
|
||||||
|
@Schema(description = "VLLM模型标识", example = "vllm_model_02", required = false)
|
||||||
|
private String vllmModelId;
|
||||||
|
|
||||||
@Schema(description = "语音合成模型标识", example = "tts_model_02", required = false)
|
@Schema(description = "语音合成模型标识", example = "tts_model_02", required = false)
|
||||||
private String ttsModelId;
|
private String ttsModelId;
|
||||||
|
|
||||||
|
|||||||
@@ -36,6 +36,9 @@ public class AgentEntity {
|
|||||||
@Schema(description = "大语言模型标识")
|
@Schema(description = "大语言模型标识")
|
||||||
private String llmModelId;
|
private String llmModelId;
|
||||||
|
|
||||||
|
@Schema(description = "VLLM模型标识")
|
||||||
|
private String vllmModelId;
|
||||||
|
|
||||||
@Schema(description = "语音合成模型标识")
|
@Schema(description = "语音合成模型标识")
|
||||||
private String ttsModelId;
|
private String ttsModelId;
|
||||||
|
|
||||||
|
|||||||
@@ -49,6 +49,11 @@ public class AgentTemplateEntity implements Serializable {
|
|||||||
*/
|
*/
|
||||||
private String llmModelId;
|
private String llmModelId;
|
||||||
|
|
||||||
|
/**
|
||||||
|
* VLLM模型标识
|
||||||
|
*/
|
||||||
|
private String vllmModelId;
|
||||||
|
|
||||||
/**
|
/**
|
||||||
* 语音合成模型标识
|
* 语音合成模型标识
|
||||||
*/
|
*/
|
||||||
|
|||||||
+3
@@ -102,6 +102,9 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
|
|||||||
// 获取 LLM 模型名称
|
// 获取 LLM 模型名称
|
||||||
dto.setLlmModelName(modelConfigService.getModelNameById(agent.getLlmModelId()));
|
dto.setLlmModelName(modelConfigService.getModelNameById(agent.getLlmModelId()));
|
||||||
|
|
||||||
|
// 获取 VLLM 模型名称
|
||||||
|
dto.setVllmModelName(modelConfigService.getModelNameById(agent.getVllmModelId()));
|
||||||
|
|
||||||
// 获取记忆模型名称
|
// 获取记忆模型名称
|
||||||
dto.setMemModelId(agent.getMemModelId());
|
dto.setMemModelId(agent.getMemModelId());
|
||||||
|
|
||||||
|
|||||||
+5
-2
@@ -72,6 +72,7 @@ public class ConfigServiceImpl implements ConfigService {
|
|||||||
null,
|
null,
|
||||||
null,
|
null,
|
||||||
null,
|
null,
|
||||||
|
null,
|
||||||
result,
|
result,
|
||||||
isCache);
|
isCache);
|
||||||
|
|
||||||
@@ -140,6 +141,7 @@ public class ConfigServiceImpl implements ConfigService {
|
|||||||
agent.getVadModelId(),
|
agent.getVadModelId(),
|
||||||
agent.getAsrModelId(),
|
agent.getAsrModelId(),
|
||||||
agent.getLlmModelId(),
|
agent.getLlmModelId(),
|
||||||
|
agent.getVllmModelId(),
|
||||||
agent.getTtsModelId(),
|
agent.getTtsModelId(),
|
||||||
agent.getMemModelId(),
|
agent.getMemModelId(),
|
||||||
agent.getIntentModelId(),
|
agent.getIntentModelId(),
|
||||||
@@ -241,6 +243,7 @@ public class ConfigServiceImpl implements ConfigService {
|
|||||||
String vadModelId,
|
String vadModelId,
|
||||||
String asrModelId,
|
String asrModelId,
|
||||||
String llmModelId,
|
String llmModelId,
|
||||||
|
String vllmModelId,
|
||||||
String ttsModelId,
|
String ttsModelId,
|
||||||
String memModelId,
|
String memModelId,
|
||||||
String intentModelId,
|
String intentModelId,
|
||||||
@@ -248,8 +251,8 @@ public class ConfigServiceImpl implements ConfigService {
|
|||||||
boolean isCache) {
|
boolean isCache) {
|
||||||
Map<String, String> selectedModule = new HashMap<>();
|
Map<String, String> selectedModule = new HashMap<>();
|
||||||
|
|
||||||
String[] modelTypes = { "VAD", "ASR", "TTS", "Memory", "Intent", "LLM" };
|
String[] modelTypes = { "VAD", "ASR", "TTS", "Memory", "Intent", "LLM", "VLLM" };
|
||||||
String[] modelIds = { vadModelId, asrModelId, ttsModelId, memModelId, intentModelId, llmModelId };
|
String[] modelIds = { vadModelId, asrModelId, ttsModelId, memModelId, intentModelId, llmModelId, vllmModelId };
|
||||||
String intentLLMModelId = null;
|
String intentLLMModelId = null;
|
||||||
String memLocalShortLLMModelId = null;
|
String memLocalShortLLMModelId = null;
|
||||||
|
|
||||||
|
|||||||
@@ -0,0 +1,29 @@
|
|||||||
|
-- VLLM模型供应器
|
||||||
|
delete from `ai_model_provider` where id = 'SYSTEM_VLLM_openai';
|
||||||
|
INSERT INTO `ai_model_provider` (`id`, `model_type`, `provider_code`, `name`, `fields`, `sort`, `creator`, `create_date`, `updater`, `update_date`) VALUES
|
||||||
|
('SYSTEM_VLLM_openai', 'VLLM', 'openai', 'OpenAI接口', '[{"key":"base_url","label":"基础URL","type":"string"},{"key":"model_name","label":"模型名称","type":"string"},{"key":"api_key","label":"API密钥","type":"string"}]', 9, 1, NOW(), 1, NOW());
|
||||||
|
|
||||||
|
-- VLLM模型配置
|
||||||
|
delete from `ai_model_config` where id = 'VLLM_ChatGLMVLLM';
|
||||||
|
INSERT INTO `ai_model_config` VALUES ('VLLM_ChatGLMVLLM', 'VLLM', 'ChatGLMVLLM', '智谱视觉AI', 1, 1, '{\"type\": \"openai\", \"model_name\": \"glm-4v-flash\", \"base_url\": \"https://open.bigmodel.cn/api/paas/v4/\", \"api_key\": \"你的api_key\"}', NULL, NULL, 1, NULL, NULL, NULL, NULL);
|
||||||
|
|
||||||
|
-- 更新文档
|
||||||
|
UPDATE `ai_model_config` SET
|
||||||
|
`doc_link` = 'https://bigmodel.cn/usercenter/proj-mgmt/apikeys',
|
||||||
|
`remark` = '智谱视觉AI配置说明:
|
||||||
|
1. 访问 https://bigmodel.cn/usercenter/proj-mgmt/apikeys
|
||||||
|
2. 注册并获取API密钥
|
||||||
|
3. 填入配置文件中' WHERE `id` = 'VLLM_ChatGLMVLLM';
|
||||||
|
|
||||||
|
|
||||||
|
-- 添加参数
|
||||||
|
INSERT INTO `sys_params` (id, param_code, param_value, value_type, param_type, remark) VALUES (113, 'server.http_port', '8003', 'number', 1, 'http服务的端口,用于启动视觉分析接口');
|
||||||
|
INSERT INTO `sys_params` (id, param_code, param_value, value_type, param_type, remark) VALUES (114, 'server.vision_explain', 'null', 'string', 1, '视觉分析接口地址,用于下发到设备,多个用;分隔');
|
||||||
|
|
||||||
|
-- 智能体表增加VLLM模型配置
|
||||||
|
ALTER TABLE `ai_agent`
|
||||||
|
ADD COLUMN `vllm_model_id` varchar(32) NULL DEFAULT 'VLLM_ChatGLMVLLM' COMMENT '视觉模型标识' AFTER `llm_model_id`;
|
||||||
|
|
||||||
|
-- 智能体模版表增加VLLM模型配置
|
||||||
|
ALTER TABLE `ai_agent_template`
|
||||||
|
ADD COLUMN `vllm_model_id` varchar(32) NULL DEFAULT 'VLLM_ChatGLMVLLM' COMMENT '视觉模型标识' AFTER `llm_model_id`;
|
||||||
@@ -0,0 +1,45 @@
|
|||||||
|
-- VLLM模型供应器
|
||||||
|
delete from `ai_model_provider` where id = 'SYSTEM_ASR_DoubaoStreamASR';
|
||||||
|
INSERT INTO `ai_model_provider` (`id`, `model_type`, `provider_code`, `name`, `fields`, `sort`, `creator`, `create_date`, `updater`, `update_date`) VALUES
|
||||||
|
('SYSTEM_ASR_DoubaoStreamASR', 'ASR', 'doubao_stream', '火山引擎语音识别(流式)', '[{"key":"appid","label":"应用ID","type":"string"},{"key":"access_token","label":"访问令牌","type":"string"},{"key":"cluster","label":"集群","type":"string"},{"key":"boosting_table_name","label":"热词文件名称","type":"string"},{"key":"correct_table_name","label":"替换词文件名称","type":"string"},{"key":"output_dir","label":"输出目录","type":"string"}]', 3, 1, NOW(), 1, NOW());
|
||||||
|
|
||||||
|
|
||||||
|
-- VLLM模型配置
|
||||||
|
delete from `ai_model_config` where id = 'ASR_DoubaoStreamASR';
|
||||||
|
INSERT INTO `ai_model_config` VALUES ('ASR_DoubaoStreamASR', 'ASR', 'DoubaoStreamASR', '豆包语音识别(流式)', 0, 1, '{\"type\": \"doubao_stream\", \"appid\": \"\", \"access_token\": \"\", \"cluster\": \"volcengine_input_common\", \"output_dir\": \"tmp/\"}', NULL, NULL, 3, NULL, NULL, NULL, NULL);
|
||||||
|
|
||||||
|
|
||||||
|
-- 更新豆包ASR配置说明
|
||||||
|
UPDATE `ai_model_config` SET
|
||||||
|
`doc_link` = 'https://console.volcengine.com/speech/app',
|
||||||
|
`remark` = '豆包ASR配置说明:
|
||||||
|
1. 豆包ASR和豆包(流式)ASR的区别是:豆包ASR是按次收费,豆包(流式)ASR是按时收费
|
||||||
|
2. 一般来说按次收费的更便宜,但是豆包(流式)ASR使用了大模型技术,效果更好
|
||||||
|
3. 需要在火山引擎控制台创建应用并获取appid和access_token
|
||||||
|
4. 支持中文语音识别
|
||||||
|
5. 需要网络连接
|
||||||
|
6. 输出文件保存在tmp/目录
|
||||||
|
申请步骤:
|
||||||
|
1. 访问 https://console.volcengine.com/speech/app
|
||||||
|
2. 创建新应用
|
||||||
|
3. 获取appid和access_token
|
||||||
|
4. 填入配置文件中
|
||||||
|
如需设置热词,请参考:https://www.volcengine.com/docs/6561/155738
|
||||||
|
' WHERE `id` = 'ASR_DoubaoASR';
|
||||||
|
|
||||||
|
UPDATE `ai_model_config` SET
|
||||||
|
`doc_link` = 'https://console.volcengine.com/speech/app',
|
||||||
|
`remark` = '豆包ASR配置说明:
|
||||||
|
1. 豆包ASR和豆包(流式)ASR的区别是:豆包ASR是按次收费,豆包(流式)ASR是按时收费
|
||||||
|
2. 一般来说按次收费的更便宜,但是豆包(流式)ASR使用了大模型技术,效果更好
|
||||||
|
3. 需要在火山引擎控制台创建应用并获取appid和access_token
|
||||||
|
4. 支持中文语音识别
|
||||||
|
5. 需要网络连接
|
||||||
|
6. 输出文件保存在tmp/目录
|
||||||
|
申请步骤:
|
||||||
|
1. 访问 https://console.volcengine.com/speech/app
|
||||||
|
2. 创建新应用
|
||||||
|
3. 获取appid和access_token
|
||||||
|
4. 填入配置文件中
|
||||||
|
如需设置热词,请参考:https://www.volcengine.com/docs/6561/155738
|
||||||
|
' WHERE `id` = 'ASR_DoubaoStreamASR';
|
||||||
@@ -0,0 +1,14 @@
|
|||||||
|
-- VLLM模型配置
|
||||||
|
delete from `ai_model_config` where id = 'VLLM_QwenVLVLLM';
|
||||||
|
INSERT INTO `ai_model_config` VALUES ('VLLM_QwenVLVLLM', 'VLLM', 'QwenVLVLLM', '千问视觉模型', 0, 1, '{\"type\": \"openai\", \"model_name\": \"qwen2.5-vl-3b-instruct\", \"base_url\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"api_key\": \"你的api_key\"}', NULL, NULL, 2, NULL, NULL, NULL, NULL);
|
||||||
|
|
||||||
|
-- 更新文档
|
||||||
|
UPDATE `ai_model_config` SET
|
||||||
|
`doc_link` = 'https://bailian.console.aliyun.com/?tab=api#/api/?type=model&url=https%3A%2F%2Fhelp.aliyun.com%2Fdocument_detail%2F2845564.html&renderType=iframe',
|
||||||
|
`remark` = '千问视觉模型配置说明:
|
||||||
|
1. 访问 https://bailian.console.aliyun.com/?tab=model#/api-key
|
||||||
|
2. 注册并获取API密钥
|
||||||
|
3. 填入配置文件中' WHERE `id` = 'VLLM_QwenVLVLLM';
|
||||||
|
|
||||||
|
-- 删除参数,这两个参数已挪至python配置文件
|
||||||
|
delete from `sys_params` where id in (113,114);
|
||||||
@@ -169,4 +169,25 @@ databaseChangeLog:
|
|||||||
changes:
|
changes:
|
||||||
- sqlFile:
|
- sqlFile:
|
||||||
encoding: utf8
|
encoding: utf8
|
||||||
path: classpath:db/changelog/202505271414.sql
|
path: classpath:db/changelog/202505271414.sql
|
||||||
|
- changeSet:
|
||||||
|
id: 202506010920
|
||||||
|
author: hrz
|
||||||
|
changes:
|
||||||
|
- sqlFile:
|
||||||
|
encoding: utf8
|
||||||
|
path: classpath:db/changelog/202506010920.sql
|
||||||
|
- changeSet:
|
||||||
|
id: 202506031639
|
||||||
|
author: hrz
|
||||||
|
changes:
|
||||||
|
- sqlFile:
|
||||||
|
encoding: utf8
|
||||||
|
path: classpath:db/changelog/202506031639.sql
|
||||||
|
- changeSet:
|
||||||
|
id: 202506032232
|
||||||
|
author: hrz
|
||||||
|
changes:
|
||||||
|
- sqlFile:
|
||||||
|
encoding: utf8
|
||||||
|
path: classpath:db/changelog/202506032232.sql
|
||||||
@@ -14,10 +14,10 @@
|
|||||||
</div>
|
</div>
|
||||||
</div>
|
</div>
|
||||||
<div class="device-name">
|
<div class="device-name">
|
||||||
设备型号:{{ device.ttsModelName }}
|
语言模型:{{ device.llmModelName }}
|
||||||
</div>
|
</div>
|
||||||
<div class="device-name">
|
<div class="device-name">
|
||||||
音色模型:{{ device.ttsVoiceName }}
|
音色模型:{{ device.ttsModelName }} ({{ device.ttsVoiceName }})
|
||||||
</div>
|
</div>
|
||||||
<div style="display: flex;gap: 10px;align-items: center;">
|
<div style="display: flex;gap: 10px;align-items: center;">
|
||||||
<div class="settings-btn" @click="handleConfigure">
|
<div class="settings-btn" @click="handleConfigure">
|
||||||
|
|||||||
@@ -30,6 +30,9 @@
|
|||||||
<el-menu-item index="llm">
|
<el-menu-item index="llm">
|
||||||
<span class="menu-text">大语言模型</span>
|
<span class="menu-text">大语言模型</span>
|
||||||
</el-menu-item>
|
</el-menu-item>
|
||||||
|
<el-menu-item index="vllm">
|
||||||
|
<span class="menu-text">视觉大模型</span>
|
||||||
|
</el-menu-item>
|
||||||
<el-menu-item index="intent">
|
<el-menu-item index="intent">
|
||||||
<span class="menu-text">意图识别</span>
|
<span class="menu-text">意图识别</span>
|
||||||
</el-menu-item>
|
</el-menu-item>
|
||||||
@@ -173,6 +176,7 @@ export default {
|
|||||||
vad: '语言活动检测模型(VAD)',
|
vad: '语言活动检测模型(VAD)',
|
||||||
asr: '语音识别模型(ASR)',
|
asr: '语音识别模型(ASR)',
|
||||||
llm: '大语言模型(LLM)',
|
llm: '大语言模型(LLM)',
|
||||||
|
vllm: '视觉大模型(VLLM)',
|
||||||
intent: '意图识别模型(Intent)',
|
intent: '意图识别模型(Intent)',
|
||||||
tts: '语音合成模型(TTS)',
|
tts: '语音合成模型(TTS)',
|
||||||
memory: '记忆模型(Memory)'
|
memory: '记忆模型(Memory)'
|
||||||
|
|||||||
@@ -64,7 +64,27 @@
|
|||||||
</el-form-item>
|
</el-form-item>
|
||||||
</div>
|
</div>
|
||||||
<div class="form-column">
|
<div class="form-column">
|
||||||
<el-form-item v-for="(model, index) in models" :key="`model-${index}`" :label="model.label"
|
<div class="model-row">
|
||||||
|
<el-form-item label="语音活动检测(VAD)" class="model-item">
|
||||||
|
<div class="model-select-wrapper">
|
||||||
|
<el-select v-model="form.model.vadModelId" filterable placeholder="请选择" class="form-select"
|
||||||
|
@change="handleModelChange('VAD', $event)">
|
||||||
|
<el-option v-for="(item, optionIndex) in modelOptions['VAD']"
|
||||||
|
:key="`option-vad-${optionIndex}`" :label="item.label" :value="item.value" />
|
||||||
|
</el-select>
|
||||||
|
</div>
|
||||||
|
</el-form-item>
|
||||||
|
<el-form-item label="语音识别(ASR)" class="model-item">
|
||||||
|
<div class="model-select-wrapper">
|
||||||
|
<el-select v-model="form.model.asrModelId" filterable placeholder="请选择" class="form-select"
|
||||||
|
@change="handleModelChange('ASR', $event)">
|
||||||
|
<el-option v-for="(item, optionIndex) in modelOptions['ASR']"
|
||||||
|
:key="`option-asr-${optionIndex}`" :label="item.label" :value="item.value" />
|
||||||
|
</el-select>
|
||||||
|
</div>
|
||||||
|
</el-form-item>
|
||||||
|
</div>
|
||||||
|
<el-form-item v-for="(model, index) in models.slice(2)" :key="`model-${index}`" :label="model.label"
|
||||||
class="model-item">
|
class="model-item">
|
||||||
<div class="model-select-wrapper">
|
<div class="model-select-wrapper">
|
||||||
<el-select v-model="form.model[model.key]" filterable placeholder="请选择" class="form-select"
|
<el-select v-model="form.model[model.key]" filterable placeholder="请选择" class="form-select"
|
||||||
@@ -148,6 +168,7 @@ export default {
|
|||||||
vadModelId: "",
|
vadModelId: "",
|
||||||
asrModelId: "",
|
asrModelId: "",
|
||||||
llmModelId: "",
|
llmModelId: "",
|
||||||
|
vllmModelId: "",
|
||||||
memModelId: "",
|
memModelId: "",
|
||||||
intentModelId: "",
|
intentModelId: "",
|
||||||
}
|
}
|
||||||
@@ -156,6 +177,7 @@ export default {
|
|||||||
{ label: '语音活动检测(VAD)', key: 'vadModelId', type: 'VAD' },
|
{ label: '语音活动检测(VAD)', key: 'vadModelId', type: 'VAD' },
|
||||||
{ label: '语音识别(ASR)', key: 'asrModelId', type: 'ASR' },
|
{ label: '语音识别(ASR)', key: 'asrModelId', type: 'ASR' },
|
||||||
{ label: '大语言模型(LLM)', key: 'llmModelId', type: 'LLM' },
|
{ label: '大语言模型(LLM)', key: 'llmModelId', type: 'LLM' },
|
||||||
|
{ label: '视觉大模型(VLLM)', key: 'vllmModelId', type: 'VLLM' },
|
||||||
{ label: '意图识别(Intent)', key: 'intentModelId', type: 'Intent' },
|
{ label: '意图识别(Intent)', key: 'intentModelId', type: 'Intent' },
|
||||||
{ label: '记忆(Memory)', key: 'memModelId', type: 'Memory' },
|
{ label: '记忆(Memory)', key: 'memModelId', type: 'Memory' },
|
||||||
{ label: '语音合成(TTS)', key: 'ttsModelId', type: 'TTS' },
|
{ label: '语音合成(TTS)', key: 'ttsModelId', type: 'TTS' },
|
||||||
@@ -189,6 +211,7 @@ export default {
|
|||||||
asrModelId: this.form.model.asrModelId,
|
asrModelId: this.form.model.asrModelId,
|
||||||
vadModelId: this.form.model.vadModelId,
|
vadModelId: this.form.model.vadModelId,
|
||||||
llmModelId: this.form.model.llmModelId,
|
llmModelId: this.form.model.llmModelId,
|
||||||
|
vllmModelId: this.form.model.vllmModelId,
|
||||||
ttsModelId: this.form.model.ttsModelId,
|
ttsModelId: this.form.model.ttsModelId,
|
||||||
ttsVoiceId: this.form.ttsVoiceId,
|
ttsVoiceId: this.form.ttsVoiceId,
|
||||||
chatHistoryConf: this.form.chatHistoryConf,
|
chatHistoryConf: this.form.chatHistoryConf,
|
||||||
@@ -236,6 +259,7 @@ export default {
|
|||||||
vadModelId: "",
|
vadModelId: "",
|
||||||
asrModelId: "",
|
asrModelId: "",
|
||||||
llmModelId: "",
|
llmModelId: "",
|
||||||
|
vllmModelId: "",
|
||||||
memModelId: "",
|
memModelId: "",
|
||||||
intentModelId: "",
|
intentModelId: "",
|
||||||
}
|
}
|
||||||
@@ -289,6 +313,7 @@ export default {
|
|||||||
vadModelId: templateData.vadModelId || this.form.model.vadModelId,
|
vadModelId: templateData.vadModelId || this.form.model.vadModelId,
|
||||||
asrModelId: templateData.asrModelId || this.form.model.asrModelId,
|
asrModelId: templateData.asrModelId || this.form.model.asrModelId,
|
||||||
llmModelId: templateData.llmModelId || this.form.model.llmModelId,
|
llmModelId: templateData.llmModelId || this.form.model.llmModelId,
|
||||||
|
vllmModelId: templateData.vllmModelId || this.form.model.vllmModelId,
|
||||||
memModelId: templateData.memModelId || this.form.model.memModelId,
|
memModelId: templateData.memModelId || this.form.model.memModelId,
|
||||||
intentModelId: templateData.intentModelId || this.form.model.intentModelId
|
intentModelId: templateData.intentModelId || this.form.model.intentModelId
|
||||||
}
|
}
|
||||||
@@ -305,6 +330,7 @@ export default {
|
|||||||
vadModelId: data.data.vadModelId,
|
vadModelId: data.data.vadModelId,
|
||||||
asrModelId: data.data.asrModelId,
|
asrModelId: data.data.asrModelId,
|
||||||
llmModelId: data.data.llmModelId,
|
llmModelId: data.data.llmModelId,
|
||||||
|
vllmModelId: data.data.vllmModelId,
|
||||||
memModelId: data.data.memModelId,
|
memModelId: data.data.memModelId,
|
||||||
intentModelId: data.data.intentModelId
|
intentModelId: data.data.intentModelId
|
||||||
}
|
}
|
||||||
@@ -587,6 +613,25 @@ export default {
|
|||||||
width: 100%;
|
width: 100%;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
.model-row {
|
||||||
|
display: flex;
|
||||||
|
gap: 20px;
|
||||||
|
margin-bottom: 6px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.model-row .model-item {
|
||||||
|
flex: 1;
|
||||||
|
margin-bottom: 0;
|
||||||
|
}
|
||||||
|
|
||||||
|
.model-row .el-form-item__label {
|
||||||
|
font-size: 12px !important;
|
||||||
|
color: #3d4566 !important;
|
||||||
|
font-weight: 400;
|
||||||
|
line-height: 22px;
|
||||||
|
padding-bottom: 2px;
|
||||||
|
}
|
||||||
|
|
||||||
.function-icons {
|
.function-icons {
|
||||||
display: flex;
|
display: flex;
|
||||||
align-items: center;
|
align-items: center;
|
||||||
|
|||||||
@@ -1,11 +1,12 @@
|
|||||||
import sys
|
import sys
|
||||||
|
import uuid
|
||||||
import signal
|
import signal
|
||||||
import asyncio
|
import asyncio
|
||||||
from aioconsole import ainput
|
from aioconsole import ainput
|
||||||
from config.settings import load_config
|
from config.settings import load_config
|
||||||
from config.logger import setup_logging
|
from config.logger import setup_logging
|
||||||
from core.utils.util import get_local_ip
|
from core.utils.util import get_local_ip
|
||||||
from core.ota_server import SimpleOtaServer
|
from core.http_server import SimpleHttpServer
|
||||||
from core.websocket_server import WebSocketServer
|
from core.websocket_server import WebSocketServer
|
||||||
from core.utils.util import check_ffmpeg_installed
|
from core.utils.util import check_ffmpeg_installed
|
||||||
|
|
||||||
@@ -45,25 +46,37 @@ async def main():
|
|||||||
check_ffmpeg_installed()
|
check_ffmpeg_installed()
|
||||||
config = load_config()
|
config = load_config()
|
||||||
|
|
||||||
|
# 默认使用manager-api的secret作为auth_key
|
||||||
|
# 如果secret为空,则生成随机密钥
|
||||||
|
# auth_key用于jwt认证,比如视觉分析接口的jwt认证
|
||||||
|
auth_key = config.get("manager-api", {}).get("secret", "")
|
||||||
|
if not auth_key or len(auth_key) == 0 or "你" in auth_key:
|
||||||
|
auth_key = str(uuid.uuid4().hex)
|
||||||
|
config["server"]["auth_key"] = auth_key
|
||||||
|
|
||||||
# 添加 stdin 监控任务
|
# 添加 stdin 监控任务
|
||||||
stdin_task = asyncio.create_task(monitor_stdin())
|
stdin_task = asyncio.create_task(monitor_stdin())
|
||||||
|
|
||||||
# 启动 WebSocket 服务器
|
# 启动 WebSocket 服务器
|
||||||
ws_server = WebSocketServer(config)
|
ws_server = WebSocketServer(config)
|
||||||
ws_task = asyncio.create_task(ws_server.start())
|
ws_task = asyncio.create_task(ws_server.start())
|
||||||
ota_task = None
|
# 启动 Simple http 服务器
|
||||||
|
ota_server = SimpleHttpServer(config)
|
||||||
|
ota_task = asyncio.create_task(ota_server.start())
|
||||||
|
|
||||||
read_config_from_api = config.get("read_config_from_api", False)
|
read_config_from_api = config.get("read_config_from_api", False)
|
||||||
|
port = int(config["server"].get("http_port", 8003))
|
||||||
if not read_config_from_api:
|
if not read_config_from_api:
|
||||||
# 启动 Simple OTA 服务器
|
|
||||||
ota_server = SimpleOtaServer(config)
|
|
||||||
ota_task = asyncio.create_task(ota_server.start())
|
|
||||||
|
|
||||||
logger.bind(tag=TAG).info(
|
logger.bind(tag=TAG).info(
|
||||||
"OTA接口是\t\thttp://{}:{}/xiaozhi/ota/",
|
"OTA接口是\t\thttp://{}:{}/xiaozhi/ota/",
|
||||||
get_local_ip(),
|
get_local_ip(),
|
||||||
config["server"]["ota_port"],
|
port,
|
||||||
)
|
)
|
||||||
|
logger.bind(tag=TAG).info(
|
||||||
|
"视觉分析接口是\thttp://{}:{}/mcp/vision/explain",
|
||||||
|
get_local_ip(),
|
||||||
|
port,
|
||||||
|
)
|
||||||
|
|
||||||
# 获取WebSocket配置,使用安全的默认值
|
# 获取WebSocket配置,使用安全的默认值
|
||||||
websocket_port = 8000
|
websocket_port = 8000
|
||||||
|
|||||||
@@ -2,6 +2,7 @@
|
|||||||
# 然后你想修改覆盖修改什么配置,就修改【.config.yaml】文件,而不是修改【config.yaml】文件
|
# 然后你想修改覆盖修改什么配置,就修改【.config.yaml】文件,而不是修改【config.yaml】文件
|
||||||
# 系统会优先读取【data/.config.yaml】文件的配置,如果【.config.yaml】文件里的配置不存在,系统会自动去读取【config.yaml】文件的配置。
|
# 系统会优先读取【data/.config.yaml】文件的配置,如果【.config.yaml】文件里的配置不存在,系统会自动去读取【config.yaml】文件的配置。
|
||||||
# 这样做,可以最简化配置,保护您的密钥安全。
|
# 这样做,可以最简化配置,保护您的密钥安全。
|
||||||
|
# 如果你使用了智控台,那么以下所有配置,都不会生效,请在智控台中修改配置
|
||||||
|
|
||||||
# #####################################################################################
|
# #####################################################################################
|
||||||
# #############################以下是服务器基本运行配置####################################
|
# #############################以下是服务器基本运行配置####################################
|
||||||
@@ -9,13 +10,21 @@ server:
|
|||||||
# 服务器监听地址和端口(Server listening address and port)
|
# 服务器监听地址和端口(Server listening address and port)
|
||||||
ip: 0.0.0.0
|
ip: 0.0.0.0
|
||||||
port: 8000
|
port: 8000
|
||||||
# OTA接口的端口号
|
# http服务的端口,用于简单OTA接口(单服务部署),以及视觉分析接口
|
||||||
ota_port: 8002
|
http_port: 8003
|
||||||
# 这个websocket配置是指ota接口向设备发送的websocket地址
|
# 这个websocket配置是指ota接口向设备发送的websocket地址
|
||||||
# 如果按默认的写法,ota接口会自动生成websocket地址。这个地址你可以直接用浏览器访问ota接口确认一下
|
# 如果按默认的写法,ota接口会自动生成websocket地址,并输出在启动日志里,这个地址你可以直接用浏览器访问ota接口确认一下
|
||||||
# 当你使用docker部署或使用公网部署(使用ssl、域名)时,不一定准确
|
# 当你使用docker部署或使用公网部署(使用ssl、域名)时,不一定准确
|
||||||
# 所以如果你使用docker部署或使用公网部署时,请设置正确的websocket地址
|
# 所以如果你使用docker部署时,将websocket设置成局域网地址
|
||||||
|
# 如果你使用公网部署时,将vwebsocket设置成公网地址
|
||||||
websocket: ws://你的ip或者域名:端口号/xiaozhi/v1/
|
websocket: ws://你的ip或者域名:端口号/xiaozhi/v1/
|
||||||
|
# 视觉分析接口地址
|
||||||
|
# 向设备发送的视觉分析的接口地址
|
||||||
|
# 如果按下面默认的写法,系统会自动生成视觉识别地址,并输出在启动日志里,这个地址你可以直接用浏览器访问确认一下
|
||||||
|
# 当你使用docker部署或使用公网部署(使用ssl、域名)时,不一定准确
|
||||||
|
# 所以如果你使用docker部署时,将vision_explain设置成局域网地址
|
||||||
|
# 如果你使用公网部署时,将vision_explain设置成公网地址
|
||||||
|
vision_explain: http://你的ip或者域名:端口号/mcp/vision/explain
|
||||||
# OTA返回信息时区偏移量
|
# OTA返回信息时区偏移量
|
||||||
timezone_offset: +8
|
timezone_offset: +8
|
||||||
# 认证配置
|
# 认证配置
|
||||||
@@ -160,6 +169,8 @@ selected_module:
|
|||||||
ASR: FunASR
|
ASR: FunASR
|
||||||
# 将根据配置名称对应的type调用实际的LLM适配器
|
# 将根据配置名称对应的type调用实际的LLM适配器
|
||||||
LLM: ChatGLMLLM
|
LLM: ChatGLMLLM
|
||||||
|
# 视觉语言大模型
|
||||||
|
VLLM: ChatGLMVLLM
|
||||||
# TTS将根据配置名称对应的type调用实际的TTS适配器
|
# TTS将根据配置名称对应的type调用实际的TTS适配器
|
||||||
TTS: EdgeTTS
|
TTS: EdgeTTS
|
||||||
# 记忆模块,默认不开启记忆;如果想使用超长记忆,推荐使用mem0ai;如果注重隐私,请使用本地的mem_local_short
|
# 记忆模块,默认不开启记忆;如果想使用超长记忆,推荐使用mem0ai;如果注重隐私,请使用本地的mem_local_short
|
||||||
@@ -253,6 +264,8 @@ ASR:
|
|||||||
DoubaoASR:
|
DoubaoASR:
|
||||||
# 可以在这里申请相关Key等信息
|
# 可以在这里申请相关Key等信息
|
||||||
# https://console.volcengine.com/speech/app
|
# https://console.volcengine.com/speech/app
|
||||||
|
# DoubaoASR和DoubaoStreamASR的区别是:DoubaoASR是按次收费,DoubaoStreamASR是按时收费
|
||||||
|
# 一般来说按次收费的更便宜,但是DoubaoStreamASR使用了大模型技术,效果更好
|
||||||
type: doubao
|
type: doubao
|
||||||
appid: 你的火山引擎语音合成服务appid
|
appid: 你的火山引擎语音合成服务appid
|
||||||
access_token: 你的火山引擎语音合成服务access_token
|
access_token: 你的火山引擎语音合成服务access_token
|
||||||
@@ -261,6 +274,20 @@ ASR:
|
|||||||
boosting_table_name: (选填)你的热词文件名称
|
boosting_table_name: (选填)你的热词文件名称
|
||||||
correct_table_name: (选填)你的替换词文件名称
|
correct_table_name: (选填)你的替换词文件名称
|
||||||
output_dir: tmp/
|
output_dir: tmp/
|
||||||
|
DoubaoStreamASR:
|
||||||
|
# 可以在这里申请相关Key等信息
|
||||||
|
# https://console.volcengine.com/speech/app
|
||||||
|
# DoubaoASR和DoubaoStreamASR的区别是:DoubaoASR是按次收费,DoubaoStreamASR是按时收费
|
||||||
|
# 开通地址https://console.volcengine.com/speech/service/10011
|
||||||
|
# 一般来说按次收费的更便宜,但是DoubaoStreamASR使用了大模型技术,效果更好
|
||||||
|
type: doubao_stream
|
||||||
|
appid: 你的火山引擎语音合成服务appid
|
||||||
|
access_token: 你的火山引擎语音合成服务access_token
|
||||||
|
cluster: volcengine_input_common
|
||||||
|
# 热词、替换词使用流程:https://www.volcengine.com/docs/6561/155738
|
||||||
|
boosting_table_name: (选填)你的热词文件名称
|
||||||
|
correct_table_name: (选填)你的替换词文件名称
|
||||||
|
output_dir: tmp/
|
||||||
TencentASR:
|
TencentASR:
|
||||||
# token申请地址:https://console.cloud.tencent.com/cam/capi
|
# token申请地址:https://console.cloud.tencent.com/cam/capi
|
||||||
# 免费领取资源:https://console.cloud.tencent.com/asr/resourcebundle
|
# 免费领取资源:https://console.cloud.tencent.com/asr/resourcebundle
|
||||||
@@ -432,6 +459,21 @@ LLM:
|
|||||||
# Xinference服务地址和模型名称
|
# Xinference服务地址和模型名称
|
||||||
model_name: qwen2.5:3b-AWQ # 使用的小模型名称,用于意图识别
|
model_name: qwen2.5:3b-AWQ # 使用的小模型名称,用于意图识别
|
||||||
base_url: http://localhost:9997 # Xinference服务地址
|
base_url: http://localhost:9997 # Xinference服务地址
|
||||||
|
# VLLM配置(视觉语言大模型)
|
||||||
|
VLLM:
|
||||||
|
ChatGLMVLLM:
|
||||||
|
type: openai
|
||||||
|
# glm-4v-flash是智谱免费AI的视觉模型,需要先在智谱AI平台创建API密钥并获取api_key
|
||||||
|
# 可在这里找到你的api key https://bigmodel.cn/usercenter/proj-mgmt/apikeys
|
||||||
|
model_name: glm-4v-flash # 智谱AI的视觉模型
|
||||||
|
url: https://open.bigmodel.cn/api/paas/v4/
|
||||||
|
api_key: 你的api_key
|
||||||
|
QwenVLVLLM:
|
||||||
|
type: openai
|
||||||
|
model_name: qwen2.5-vl-3b-instruct
|
||||||
|
url: https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||||
|
# 可在这里找到你的api key https://bailian.console.aliyun.com/?apiKey=1#/api-key
|
||||||
|
api_key: 你的api_key
|
||||||
TTS:
|
TTS:
|
||||||
# 当前支持的type为edge、doubao,可自行适配
|
# 当前支持的type为edge、doubao,可自行适配
|
||||||
EdgeTTS:
|
EdgeTTS:
|
||||||
|
|||||||
@@ -59,10 +59,14 @@ def get_config_from_api(config):
|
|||||||
"url": config["manager-api"].get("url", ""),
|
"url": config["manager-api"].get("url", ""),
|
||||||
"secret": config["manager-api"].get("secret", ""),
|
"secret": config["manager-api"].get("secret", ""),
|
||||||
}
|
}
|
||||||
|
# server的配置以本地为准
|
||||||
if config.get("server"):
|
if config.get("server"):
|
||||||
config_data["server"] = {
|
config_data["server"] = {
|
||||||
"ip": config["server"].get("ip", ""),
|
"ip": config["server"].get("ip", ""),
|
||||||
"port": config["server"].get("port", ""),
|
"port": config["server"].get("port", ""),
|
||||||
|
"http_port": config["server"].get("http_port", ""),
|
||||||
|
"vision_explain": config["server"].get("vision_explain", ""),
|
||||||
|
"auth_key": config["server"].get("auth_key", ""),
|
||||||
}
|
}
|
||||||
return config_data
|
return config_data
|
||||||
|
|
||||||
|
|||||||
@@ -4,7 +4,7 @@ from loguru import logger
|
|||||||
from config.config_loader import load_config
|
from config.config_loader import load_config
|
||||||
from config.settings import check_config_file
|
from config.settings import check_config_file
|
||||||
|
|
||||||
SERVER_VERSION = "0.5.2"
|
SERVER_VERSION = "0.5.4"
|
||||||
_logger_initialized = False
|
_logger_initialized = False
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
@@ -8,6 +8,15 @@
|
|||||||
server:
|
server:
|
||||||
ip: 0.0.0.0
|
ip: 0.0.0.0
|
||||||
port: 8000
|
port: 8000
|
||||||
|
# http服务的端口,用于视觉分析接口
|
||||||
|
http_port: 8003
|
||||||
|
# 视觉分析接口地址
|
||||||
|
# 向设备发送的视觉分析的接口地址
|
||||||
|
# 如果按下面默认的写法,系统会自动生成视觉识别地址,并输出在启动日志里,这个地址你可以直接用浏览器访问确认一下
|
||||||
|
# 当你使用docker部署或使用公网部署(使用ssl、域名)时,不一定准确
|
||||||
|
# 所以如果你使用docker部署时,将vision_explain设置成局域网地址
|
||||||
|
# 如果你使用公网部署时,将vision_explain设置成公网地址
|
||||||
|
vision_explain: http://你的ip或者域名:端口号/mcp/vision/explain
|
||||||
manager-api:
|
manager-api:
|
||||||
# 你的manager-api的地址,最好使用局域网ip
|
# 你的manager-api的地址,最好使用局域网ip
|
||||||
url: http://127.0.0.1:8002/xiaozhi
|
url: http://127.0.0.1:8002/xiaozhi
|
||||||
|
|||||||
@@ -0,0 +1,16 @@
|
|||||||
|
from aiohttp import web
|
||||||
|
from config.logger import setup_logging
|
||||||
|
|
||||||
|
|
||||||
|
class BaseHandler:
|
||||||
|
def __init__(self, config: dict):
|
||||||
|
self.config = config
|
||||||
|
self.logger = setup_logging()
|
||||||
|
|
||||||
|
def _add_cors_headers(self, response):
|
||||||
|
"""添加CORS头信息"""
|
||||||
|
response.headers["Access-Control-Allow-Headers"] = (
|
||||||
|
"client-id, content-type, device-id"
|
||||||
|
)
|
||||||
|
response.headers["Access-Control-Allow-Credentials"] = "true"
|
||||||
|
response.headers["Access-Control-Allow-Origin"] = "*"
|
||||||
+11
-52
@@ -1,18 +1,15 @@
|
|||||||
import json
|
import json
|
||||||
import time
|
import time
|
||||||
import asyncio
|
|
||||||
from aiohttp import web
|
from aiohttp import web
|
||||||
from config.logger import setup_logging
|
|
||||||
from core.utils.util import get_local_ip
|
from core.utils.util import get_local_ip
|
||||||
from core.utils.modules_initialize import initialize_modules
|
from core.api.base_handler import BaseHandler
|
||||||
|
|
||||||
TAG = __name__
|
TAG = __name__
|
||||||
|
|
||||||
|
|
||||||
class SimpleOtaServer:
|
class OTAHandler(BaseHandler):
|
||||||
def __init__(self, config: dict):
|
def __init__(self, config: dict):
|
||||||
self.config = config
|
super().__init__(config)
|
||||||
self.logger = setup_logging()
|
|
||||||
|
|
||||||
def _get_websocket_url(self, local_ip: str, port: int) -> str:
|
def _get_websocket_url(self, local_ip: str, port: int) -> str:
|
||||||
"""获取websocket地址
|
"""获取websocket地址
|
||||||
@@ -25,41 +22,15 @@ class SimpleOtaServer:
|
|||||||
str: websocket地址
|
str: websocket地址
|
||||||
"""
|
"""
|
||||||
server_config = self.config["server"]
|
server_config = self.config["server"]
|
||||||
websocket_config = server_config.get("websocket")
|
websocket_config = server_config.get("websocket", "")
|
||||||
|
|
||||||
if websocket_config and "你" not in websocket_config:
|
if "你的" not in websocket_config:
|
||||||
return websocket_config
|
return websocket_config
|
||||||
else:
|
else:
|
||||||
return f"ws://{local_ip}:{port}/xiaozhi/v1/"
|
return f"ws://{local_ip}:{port}/xiaozhi/v1/"
|
||||||
|
|
||||||
async def start(self):
|
async def handle_post(self, request):
|
||||||
server_config = self.config["server"]
|
"""处理 OTA POST 请求"""
|
||||||
host = server_config.get("ip", "0.0.0.0")
|
|
||||||
port = int(server_config.get("ota_port"))
|
|
||||||
|
|
||||||
if port:
|
|
||||||
app = web.Application()
|
|
||||||
# 添加路由
|
|
||||||
app.add_routes(
|
|
||||||
[
|
|
||||||
web.get("/xiaozhi/ota/", self._handle_ota_get_request),
|
|
||||||
web.post("/xiaozhi/ota/", self._handle_ota_request),
|
|
||||||
web.options("/xiaozhi/ota/", self._handle_ota_request),
|
|
||||||
]
|
|
||||||
)
|
|
||||||
|
|
||||||
# 运行服务
|
|
||||||
runner = web.AppRunner(app)
|
|
||||||
await runner.setup()
|
|
||||||
site = web.TCPSite(runner, host, port)
|
|
||||||
await site.start()
|
|
||||||
|
|
||||||
# 保持服务运行
|
|
||||||
while True:
|
|
||||||
await asyncio.sleep(3600) # 每隔 1 小时检查一次
|
|
||||||
|
|
||||||
async def _handle_ota_request(self, request):
|
|
||||||
"""处理 /xiaozhi/ota/ 的 POST 请求"""
|
|
||||||
try:
|
try:
|
||||||
data = await request.text()
|
data = await request.text()
|
||||||
self.logger.bind(tag=TAG).debug(f"OTA请求方法: {request.method}")
|
self.logger.bind(tag=TAG).debug(f"OTA请求方法: {request.method}")
|
||||||
@@ -75,11 +46,9 @@ class SimpleOtaServer:
|
|||||||
data_json = json.loads(data)
|
data_json = json.loads(data)
|
||||||
|
|
||||||
server_config = self.config["server"]
|
server_config = self.config["server"]
|
||||||
host = server_config.get("ip", "0.0.0.0")
|
|
||||||
port = int(server_config.get("port", 8000))
|
port = int(server_config.get("port", 8000))
|
||||||
local_ip = get_local_ip()
|
local_ip = get_local_ip()
|
||||||
|
|
||||||
# OTA基础信息
|
|
||||||
return_json = {
|
return_json = {
|
||||||
"server_time": {
|
"server_time": {
|
||||||
"timestamp": int(round(time.time() * 1000)),
|
"timestamp": int(round(time.time() * 1000)),
|
||||||
@@ -104,16 +73,11 @@ class SimpleOtaServer:
|
|||||||
content_type="application/json",
|
content_type="application/json",
|
||||||
)
|
)
|
||||||
finally:
|
finally:
|
||||||
# 添加header,允许跨域访问
|
self._add_cors_headers(response)
|
||||||
response.headers["Access-Control-Allow-Headers"] = (
|
|
||||||
"client-id, content-type, device-id"
|
|
||||||
)
|
|
||||||
response.headers["Access-Control-Allow-Credentials"] = "true"
|
|
||||||
response.headers["Access-Control-Allow-Origin"] = "*"
|
|
||||||
return response
|
return response
|
||||||
|
|
||||||
async def _handle_ota_get_request(self, request):
|
async def handle_get(self, request):
|
||||||
"""处理 /xiaozhi/ota/ 的 GET 请求"""
|
"""处理 OTA GET 请求"""
|
||||||
try:
|
try:
|
||||||
server_config = self.config["server"]
|
server_config = self.config["server"]
|
||||||
local_ip = get_local_ip()
|
local_ip = get_local_ip()
|
||||||
@@ -125,10 +89,5 @@ class SimpleOtaServer:
|
|||||||
self.logger.bind(tag=TAG).error(f"OTA GET请求异常: {e}")
|
self.logger.bind(tag=TAG).error(f"OTA GET请求异常: {e}")
|
||||||
response = web.Response(text="OTA接口异常", content_type="text/plain")
|
response = web.Response(text="OTA接口异常", content_type="text/plain")
|
||||||
finally:
|
finally:
|
||||||
# 添加header,允许跨域访问
|
self._add_cors_headers(response)
|
||||||
response.headers["Access-Control-Allow-Headers"] = (
|
|
||||||
"client-id, content-type, device-id"
|
|
||||||
)
|
|
||||||
response.headers["Access-Control-Allow-Credentials"] = "true"
|
|
||||||
response.headers["Access-Control-Allow-Origin"] = "*"
|
|
||||||
return response
|
return response
|
||||||
@@ -0,0 +1,184 @@
|
|||||||
|
import json
|
||||||
|
import copy
|
||||||
|
from aiohttp import web
|
||||||
|
from config.logger import setup_logging
|
||||||
|
from core.utils.util import get_vision_url, is_valid_image_file
|
||||||
|
from core.utils.vllm import create_instance
|
||||||
|
from config.config_loader import get_private_config_from_api
|
||||||
|
from core.utils.auth import AuthToken
|
||||||
|
import base64
|
||||||
|
from typing import Tuple, Optional
|
||||||
|
|
||||||
|
TAG = __name__
|
||||||
|
|
||||||
|
# 设置最大文件大小为5MB
|
||||||
|
MAX_FILE_SIZE = 5 * 1024 * 1024
|
||||||
|
|
||||||
|
|
||||||
|
class VisionHandler:
|
||||||
|
def __init__(self, config: dict):
|
||||||
|
self.config = config
|
||||||
|
self.logger = setup_logging()
|
||||||
|
# 初始化认证工具
|
||||||
|
self.auth = AuthToken(config["server"]["auth_key"])
|
||||||
|
|
||||||
|
def _create_error_response(self, message: str) -> dict:
|
||||||
|
"""创建统一的错误响应格式"""
|
||||||
|
return {"success": False, "message": message}
|
||||||
|
|
||||||
|
def _verify_auth_token(self, request) -> Tuple[bool, Optional[str]]:
|
||||||
|
"""验证认证token"""
|
||||||
|
auth_header = request.headers.get("Authorization", "")
|
||||||
|
if not auth_header.startswith("Bearer "):
|
||||||
|
return False, None
|
||||||
|
|
||||||
|
token = auth_header[7:] # 移除"Bearer "前缀
|
||||||
|
return self.auth.verify_token(token)
|
||||||
|
|
||||||
|
async def handle_post(self, request):
|
||||||
|
"""处理 MCP Vision POST 请求"""
|
||||||
|
response = None # 初始化response变量
|
||||||
|
try:
|
||||||
|
# 验证token
|
||||||
|
is_valid, token_device_id = self._verify_auth_token(request)
|
||||||
|
if not is_valid:
|
||||||
|
response = web.Response(
|
||||||
|
text=json.dumps(
|
||||||
|
self._create_error_response("无效的认证token或token已过期")
|
||||||
|
),
|
||||||
|
content_type="application/json",
|
||||||
|
status=401,
|
||||||
|
)
|
||||||
|
return response
|
||||||
|
|
||||||
|
# 获取请求头信息
|
||||||
|
device_id = request.headers.get("Device-Id", "")
|
||||||
|
client_id = request.headers.get("Client-Id", "")
|
||||||
|
if device_id != token_device_id:
|
||||||
|
return web.Response(
|
||||||
|
text=json.dumps(self._create_error_response("设备ID与token不匹配")),
|
||||||
|
content_type="application/json",
|
||||||
|
status=401,
|
||||||
|
)
|
||||||
|
# 解析multipart/form-data请求
|
||||||
|
reader = await request.multipart()
|
||||||
|
|
||||||
|
# 读取question字段
|
||||||
|
question_field = await reader.next()
|
||||||
|
if question_field is None:
|
||||||
|
raise ValueError("缺少问题字段")
|
||||||
|
question = await question_field.text()
|
||||||
|
self.logger.bind(tag=TAG).debug(f"Question: {question}")
|
||||||
|
|
||||||
|
# 读取图片文件
|
||||||
|
image_field = await reader.next()
|
||||||
|
if image_field is None:
|
||||||
|
raise ValueError("缺少图片文件")
|
||||||
|
|
||||||
|
# 读取图片数据
|
||||||
|
image_data = await image_field.read()
|
||||||
|
if not image_data:
|
||||||
|
raise ValueError("图片数据为空")
|
||||||
|
|
||||||
|
# 检查文件大小
|
||||||
|
if len(image_data) > MAX_FILE_SIZE:
|
||||||
|
raise ValueError(
|
||||||
|
f"图片大小超过限制,最大允许{MAX_FILE_SIZE/1024/1024}MB"
|
||||||
|
)
|
||||||
|
|
||||||
|
# 检查文件格式
|
||||||
|
if not is_valid_image_file(image_data):
|
||||||
|
raise ValueError(
|
||||||
|
"不支持的文件格式,请上传有效的图片文件(支持JPEG、PNG、GIF、BMP、TIFF、WEBP格式)"
|
||||||
|
)
|
||||||
|
|
||||||
|
# 将图片转换为base64编码
|
||||||
|
image_base64 = base64.b64encode(image_data).decode("utf-8")
|
||||||
|
|
||||||
|
# 如果开启了智控台,则从智控台获取模型配置
|
||||||
|
current_config = copy.deepcopy(self.config)
|
||||||
|
read_config_from_api = current_config.get("read_config_from_api", False)
|
||||||
|
if read_config_from_api:
|
||||||
|
current_config = get_private_config_from_api(
|
||||||
|
current_config,
|
||||||
|
device_id,
|
||||||
|
client_id,
|
||||||
|
)
|
||||||
|
|
||||||
|
select_vllm_module = current_config["selected_module"].get("VLLM")
|
||||||
|
if not select_vllm_module:
|
||||||
|
raise ValueError("您还未设置默认的视觉分析模块")
|
||||||
|
|
||||||
|
vllm_type = (
|
||||||
|
select_vllm_module
|
||||||
|
if "type" not in current_config["VLLM"][select_vllm_module]
|
||||||
|
else current_config["VLLM"][select_vllm_module]["type"]
|
||||||
|
)
|
||||||
|
|
||||||
|
if not vllm_type:
|
||||||
|
raise ValueError(f"无法找到VLLM模块对应的供应器{vllm_type}")
|
||||||
|
|
||||||
|
vllm = create_instance(
|
||||||
|
vllm_type, current_config["VLLM"][select_vllm_module]
|
||||||
|
)
|
||||||
|
|
||||||
|
result = vllm.response(question, image_base64)
|
||||||
|
|
||||||
|
return_json = {
|
||||||
|
"success": True,
|
||||||
|
"result": result,
|
||||||
|
}
|
||||||
|
|
||||||
|
response = web.Response(
|
||||||
|
text=json.dumps(return_json, separators=(",", ":")),
|
||||||
|
content_type="application/json",
|
||||||
|
)
|
||||||
|
except ValueError as e:
|
||||||
|
self.logger.bind(tag=TAG).error(f"MCP Vision POST请求异常: {e}")
|
||||||
|
return_json = self._create_error_response(str(e))
|
||||||
|
response = web.Response(
|
||||||
|
text=json.dumps(return_json, separators=(",", ":")),
|
||||||
|
content_type="application/json",
|
||||||
|
)
|
||||||
|
except Exception as e:
|
||||||
|
self.logger.bind(tag=TAG).error(f"MCP Vision POST请求异常: {e}")
|
||||||
|
return_json = self._create_error_response("处理请求时发生错误")
|
||||||
|
response = web.Response(
|
||||||
|
text=json.dumps(return_json, separators=(",", ":")),
|
||||||
|
content_type="application/json",
|
||||||
|
)
|
||||||
|
finally:
|
||||||
|
if response:
|
||||||
|
self._add_cors_headers(response)
|
||||||
|
return response
|
||||||
|
|
||||||
|
async def handle_get(self, request):
|
||||||
|
"""处理 MCP Vision GET 请求"""
|
||||||
|
try:
|
||||||
|
vision_explain = get_vision_url(self.config)
|
||||||
|
if vision_explain and len(vision_explain) > 0 and "null" != vision_explain:
|
||||||
|
message = (
|
||||||
|
f"MCP Vision 接口运行正常,视觉解释接口地址是:{vision_explain}"
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
message = "MCP Vision 接口运行不正常,请打开data目录下的.config.yaml文件,找到【server.vision_explain】,设置好地址"
|
||||||
|
|
||||||
|
response = web.Response(text=message, content_type="text/plain")
|
||||||
|
except Exception as e:
|
||||||
|
self.logger.bind(tag=TAG).error(f"MCP Vision GET请求异常: {e}")
|
||||||
|
return_json = self._create_error_response("服务器内部错误")
|
||||||
|
response = web.Response(
|
||||||
|
text=json.dumps(return_json, separators=(",", ":")),
|
||||||
|
content_type="application/json",
|
||||||
|
)
|
||||||
|
finally:
|
||||||
|
self._add_cors_headers(response)
|
||||||
|
return response
|
||||||
|
|
||||||
|
def _add_cors_headers(self, response):
|
||||||
|
"""添加CORS头信息"""
|
||||||
|
response.headers["Access-Control-Allow-Headers"] = (
|
||||||
|
"client-id, content-type, device-id"
|
||||||
|
)
|
||||||
|
response.headers["Access-Control-Allow-Credentials"] = "true"
|
||||||
|
response.headers["Access-Control-Allow-Origin"] = "*"
|
||||||
@@ -35,7 +35,6 @@ from plugins_func.loadplugins import auto_import_modules
|
|||||||
from plugins_func.register import Action, ActionResponse
|
from plugins_func.register import Action, ActionResponse
|
||||||
from core.auth import AuthMiddleware, AuthenticationError
|
from core.auth import AuthMiddleware, AuthenticationError
|
||||||
from config.config_loader import get_private_config_from_api
|
from config.config_loader import get_private_config_from_api
|
||||||
from core.handle.receiveAudioHandle import handleAudioMessage
|
|
||||||
from core.providers.tts.dto.dto import ContentType, TTSMessageDTO, SentenceType
|
from core.providers.tts.dto.dto import ContentType, TTSMessageDTO, SentenceType
|
||||||
from config.logger import setup_logging, build_module_string, update_module_string
|
from config.logger import setup_logging, build_module_string, update_module_string
|
||||||
from config.manage_api_client import DeviceNotFoundException, DeviceBindException
|
from config.manage_api_client import DeviceNotFoundException, DeviceBindException
|
||||||
@@ -81,6 +80,7 @@ class ConnectionHandler:
|
|||||||
self.welcome_msg = None
|
self.welcome_msg = None
|
||||||
self.max_output_size = 0
|
self.max_output_size = 0
|
||||||
self.chat_history_conf = 0
|
self.chat_history_conf = 0
|
||||||
|
self.audio_format = "opus"
|
||||||
|
|
||||||
# 客户端状态相关
|
# 客户端状态相关
|
||||||
self.client_abort = False
|
self.client_abort = False
|
||||||
@@ -117,7 +117,10 @@ class ConnectionHandler:
|
|||||||
self.client_voice_stop = False
|
self.client_voice_stop = False
|
||||||
|
|
||||||
# asr相关变量
|
# asr相关变量
|
||||||
|
# 因为实际部署时可能会用到公共的本地ASR,不能把变量暴露给公共ASR
|
||||||
|
# 所以涉及到ASR的变量,需要在这里定义,属于connection的私有变量
|
||||||
self.asr_audio = []
|
self.asr_audio = []
|
||||||
|
self.asr_audio_queue = queue.Queue()
|
||||||
|
|
||||||
# llm相关变量
|
# llm相关变量
|
||||||
self.llm_finish_task = True
|
self.llm_finish_task = True
|
||||||
@@ -146,7 +149,6 @@ class ConnectionHandler:
|
|||||||
int(self.config.get("close_connection_no_voice_time", 120)) + 60
|
int(self.config.get("close_connection_no_voice_time", 120)) + 60
|
||||||
) # 在原来第一道关闭的基础上加60秒,进行二道关闭
|
) # 在原来第一道关闭的基础上加60秒,进行二道关闭
|
||||||
|
|
||||||
self.audio_format = "opus"
|
|
||||||
# {"mcp":true} 表示启用MCP功能
|
# {"mcp":true} 表示启用MCP功能
|
||||||
self.features = None
|
self.features = None
|
||||||
|
|
||||||
@@ -254,7 +256,11 @@ class ConnectionHandler:
|
|||||||
if isinstance(message, str):
|
if isinstance(message, str):
|
||||||
await handleTextMessage(self, message)
|
await handleTextMessage(self, message)
|
||||||
elif isinstance(message, bytes):
|
elif isinstance(message, bytes):
|
||||||
await handleAudioMessage(self, message)
|
if self.vad is None:
|
||||||
|
return
|
||||||
|
if self.asr is None:
|
||||||
|
return
|
||||||
|
self.asr_audio_queue.put(message)
|
||||||
|
|
||||||
async def handle_restart(self, message):
|
async def handle_restart(self, message):
|
||||||
"""处理服务器重启请求"""
|
"""处理服务器重启请求"""
|
||||||
@@ -478,6 +484,8 @@ class ConnectionHandler:
|
|||||||
self.memory = modules["memory"]
|
self.memory = modules["memory"]
|
||||||
|
|
||||||
def _initialize_memory(self):
|
def _initialize_memory(self):
|
||||||
|
if self.memory is None:
|
||||||
|
return
|
||||||
"""初始化记忆模块"""
|
"""初始化记忆模块"""
|
||||||
self.memory.init_memory(
|
self.memory.init_memory(
|
||||||
role_id=self.device_id,
|
role_id=self.device_id,
|
||||||
@@ -518,6 +526,8 @@ class ConnectionHandler:
|
|||||||
self.logger.bind(tag=TAG).info("使用主LLM作为意图识别模型")
|
self.logger.bind(tag=TAG).info("使用主LLM作为意图识别模型")
|
||||||
|
|
||||||
def _initialize_intent(self):
|
def _initialize_intent(self):
|
||||||
|
if self.intent is None:
|
||||||
|
return
|
||||||
self.intent_type = self.config["Intent"][
|
self.intent_type = self.config["Intent"][
|
||||||
self.config["selected_module"]["Intent"]
|
self.config["selected_module"]["Intent"]
|
||||||
]["type"]
|
]["type"]
|
||||||
@@ -708,15 +718,24 @@ class ConnectionHandler:
|
|||||||
# 处理Server端MCP工具调用
|
# 处理Server端MCP工具调用
|
||||||
if self.mcp_manager.is_mcp_tool(function_name):
|
if self.mcp_manager.is_mcp_tool(function_name):
|
||||||
result = self._handle_mcp_tool_call(function_call_data)
|
result = self._handle_mcp_tool_call(function_call_data)
|
||||||
elif hasattr(self, "mcp_client") and self.mcp_client.has_tool(function_name):
|
elif hasattr(self, "mcp_client") and self.mcp_client.has_tool(
|
||||||
# 如果是小智端MCP工具调用
|
function_name
|
||||||
|
):
|
||||||
|
# 如果是小智端MCP工具调用
|
||||||
self.logger.bind(tag=TAG).debug(
|
self.logger.bind(tag=TAG).debug(
|
||||||
f"调用小智端MCP工具: {function_name}, 参数: {function_arguments}"
|
f"调用小智端MCP工具: {function_name}, 参数: {function_arguments}"
|
||||||
)
|
)
|
||||||
try:
|
try:
|
||||||
result = asyncio.run_coroutine_threadsafe(call_mcp_tool(self, self.mcp_client, function_name, function_arguments), self.loop).result()
|
result = asyncio.run_coroutine_threadsafe(
|
||||||
|
call_mcp_tool(
|
||||||
|
self, self.mcp_client, function_name, function_arguments
|
||||||
|
),
|
||||||
|
self.loop,
|
||||||
|
).result()
|
||||||
self.logger.bind(tag=TAG).debug(f"MCP工具调用结果: {result}")
|
self.logger.bind(tag=TAG).debug(f"MCP工具调用结果: {result}")
|
||||||
result = ActionResponse(action=Action.REQLLM, result=result, response="")
|
result = ActionResponse(
|
||||||
|
action=Action.REQLLM, result=result, response=""
|
||||||
|
)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
self.logger.bind(tag=TAG).error(f"MCP工具调用失败: {e}")
|
self.logger.bind(tag=TAG).error(f"MCP工具调用失败: {e}")
|
||||||
result = ActionResponse(
|
result = ActionResponse(
|
||||||
|
|||||||
@@ -1,6 +1,4 @@
|
|||||||
import json
|
import json
|
||||||
import queue
|
|
||||||
from config.logger import setup_logging
|
|
||||||
|
|
||||||
TAG = __name__
|
TAG = __name__
|
||||||
|
|
||||||
|
|||||||
@@ -4,10 +4,14 @@ import json
|
|||||||
import random
|
import random
|
||||||
import shutil
|
import shutil
|
||||||
import asyncio
|
import asyncio
|
||||||
from core.handle.mcpHandle import MCPClient, send_mcp_initialize_message, send_mcp_tools_list_request
|
|
||||||
from core.handle.sendAudioHandle import send_stt_message
|
from core.handle.sendAudioHandle import send_stt_message
|
||||||
from core.utils.util import remove_punctuation_and_length
|
from core.utils.util import remove_punctuation_and_length
|
||||||
from core.providers.tts.dto.dto import ContentType, InterfaceType
|
from core.providers.tts.dto.dto import ContentType, InterfaceType
|
||||||
|
from core.handle.mcpHandle import (
|
||||||
|
MCPClient,
|
||||||
|
send_mcp_initialize_message,
|
||||||
|
send_mcp_tools_list_request,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
TAG = __name__
|
TAG = __name__
|
||||||
@@ -29,8 +33,6 @@ async def handleHelloMessage(conn, msg_json):
|
|||||||
format = audio_params.get("format")
|
format = audio_params.get("format")
|
||||||
conn.logger.bind(tag=TAG).info(f"客户端音频格式: {format}")
|
conn.logger.bind(tag=TAG).info(f"客户端音频格式: {format}")
|
||||||
conn.audio_format = format
|
conn.audio_format = format
|
||||||
if conn.asr is not None:
|
|
||||||
conn.asr.set_audio_format(format)
|
|
||||||
conn.welcome_msg["audio_params"] = audio_params
|
conn.welcome_msg["audio_params"] = audio_params
|
||||||
features = msg_json.get("features")
|
features = msg_json.get("features")
|
||||||
if features:
|
if features:
|
||||||
@@ -61,6 +63,8 @@ async def checkWakeupWords(conn, text):
|
|||||||
"""检查是否是唤醒词"""
|
"""检查是否是唤醒词"""
|
||||||
_, filtered_text = remove_punctuation_and_length(text)
|
_, filtered_text = remove_punctuation_and_length(text)
|
||||||
if filtered_text in conn.config.get("wakeup_words"):
|
if filtered_text in conn.config.get("wakeup_words"):
|
||||||
|
# 设置刚刚被唤醒的标志
|
||||||
|
conn.just_woken_up = True
|
||||||
await send_stt_message(conn, text)
|
await send_stt_message(conn, text)
|
||||||
|
|
||||||
file = getWakeupWordFile(WAKEUP_CONFIG["file_name"])
|
file = getWakeupWordFile(WAKEUP_CONFIG["file_name"])
|
||||||
@@ -70,6 +74,8 @@ async def checkWakeupWords(conn, text):
|
|||||||
text_hello = WAKEUP_CONFIG["text"]
|
text_hello = WAKEUP_CONFIG["text"]
|
||||||
if not text_hello:
|
if not text_hello:
|
||||||
text_hello = text
|
text_hello = text
|
||||||
|
if conn.tts is None:
|
||||||
|
return False
|
||||||
conn.tts.tts_one_sentence(
|
conn.tts.tts_one_sentence(
|
||||||
conn, ContentType.FILE, content_file=file, content_detail=text_hello
|
conn, ContentType.FILE, content_file=file, content_detail=text_hello
|
||||||
)
|
)
|
||||||
|
|||||||
@@ -96,6 +96,7 @@ async def process_intent_result(conn, intent_result, original_text):
|
|||||||
}
|
}
|
||||||
|
|
||||||
await send_stt_message(conn, original_text)
|
await send_stt_message(conn, original_text)
|
||||||
|
conn.client_abort = False
|
||||||
|
|
||||||
# 使用executor执行函数调用和结果处理
|
# 使用executor执行函数调用和结果处理
|
||||||
def process_function_call():
|
def process_function_call():
|
||||||
|
|||||||
@@ -1,6 +1,8 @@
|
|||||||
import json
|
import json
|
||||||
import asyncio
|
import asyncio
|
||||||
from concurrent.futures import Future
|
from concurrent.futures import Future
|
||||||
|
from core.utils.util import get_vision_url
|
||||||
|
from core.utils.auth import AuthToken
|
||||||
|
|
||||||
TAG = __name__
|
TAG = __name__
|
||||||
|
|
||||||
@@ -205,6 +207,20 @@ async def handle_mcp_message(conn, mcp_client: MCPClient, payload: dict):
|
|||||||
|
|
||||||
async def send_mcp_initialize_message(conn):
|
async def send_mcp_initialize_message(conn):
|
||||||
"""发送MCP初始化消息"""
|
"""发送MCP初始化消息"""
|
||||||
|
|
||||||
|
vision_url = get_vision_url(conn.config)
|
||||||
|
|
||||||
|
# 密钥生成token
|
||||||
|
auth = AuthToken(conn.config["server"]["auth_key"])
|
||||||
|
token = auth.generate_token(conn.headers.get("device-id"))
|
||||||
|
|
||||||
|
vision = {
|
||||||
|
"url": vision_url,
|
||||||
|
"token": token,
|
||||||
|
}
|
||||||
|
|
||||||
|
conn.logger.bind(tag=TAG).info(f"视觉服务信息: {vision}")
|
||||||
|
|
||||||
payload = {
|
payload = {
|
||||||
"jsonrpc": "2.0",
|
"jsonrpc": "2.0",
|
||||||
"id": 1, # mcpInitializeID
|
"id": 1, # mcpInitializeID
|
||||||
@@ -214,6 +230,7 @@ async def send_mcp_initialize_message(conn):
|
|||||||
"capabilities": {
|
"capabilities": {
|
||||||
"roots": {"listChanged": True},
|
"roots": {"listChanged": True},
|
||||||
"sampling": {},
|
"sampling": {},
|
||||||
|
"vision": vision,
|
||||||
},
|
},
|
||||||
"clientInfo": {
|
"clientInfo": {
|
||||||
"name": "XiaozhiClient",
|
"name": "XiaozhiClient",
|
||||||
|
|||||||
@@ -3,6 +3,7 @@ from core.handle.intentHandler import handle_user_intent
|
|||||||
from core.utils.output_counter import check_device_output_limit
|
from core.utils.output_counter import check_device_output_limit
|
||||||
from core.handle.abortHandle import handleAbortMessage
|
from core.handle.abortHandle import handleAbortMessage
|
||||||
import time
|
import time
|
||||||
|
import asyncio
|
||||||
from core.handle.sendAudioHandle import SentenceType
|
from core.handle.sendAudioHandle import SentenceType
|
||||||
from core.utils.util import audio_to_data
|
from core.utils.util import audio_to_data
|
||||||
|
|
||||||
@@ -10,21 +11,28 @@ TAG = __name__
|
|||||||
|
|
||||||
|
|
||||||
async def handleAudioMessage(conn, audio):
|
async def handleAudioMessage(conn, audio):
|
||||||
if conn.vad is None:
|
|
||||||
conn.logger.bind(tag=TAG).warning("VAD模块未初始化,继续等待")
|
|
||||||
return
|
|
||||||
if conn.asr is None or not hasattr(conn.asr, "conn") or conn.asr.conn is None:
|
|
||||||
conn.logger.bind(tag=TAG).warning("ASR模块未初始化或通道未就绪,继续等待")
|
|
||||||
return
|
|
||||||
# 当前片段是否有人说话
|
# 当前片段是否有人说话
|
||||||
have_voice = conn.vad.is_vad(conn, audio)
|
have_voice = conn.vad.is_vad(conn, audio)
|
||||||
|
|
||||||
|
# 如果设备刚刚被唤醒,短暂忽略VAD检测
|
||||||
|
if hasattr(conn, "just_woken_up") and conn.just_woken_up:
|
||||||
|
have_voice = False
|
||||||
|
# 设置一个短暂延迟后恢复VAD检测
|
||||||
|
asyncio.create_task(resume_vad_detection(conn))
|
||||||
|
|
||||||
if have_voice:
|
if have_voice:
|
||||||
if conn.client_is_speaking:
|
if conn.client_is_speaking:
|
||||||
await handleAbortMessage(conn)
|
await handleAbortMessage(conn)
|
||||||
# 设备长时间空闲检测,用于say goodbye
|
# 设备长时间空闲检测,用于say goodbye
|
||||||
await no_voice_close_connect(conn, have_voice)
|
await no_voice_close_connect(conn, have_voice)
|
||||||
# 接收音频
|
# 接收音频
|
||||||
await conn.asr.receive_audio(audio, have_voice)
|
await conn.asr.receive_audio(conn, audio, have_voice)
|
||||||
|
|
||||||
|
|
||||||
|
async def resume_vad_detection(conn):
|
||||||
|
# 等待2秒后恢复VAD检测
|
||||||
|
await asyncio.sleep(2)
|
||||||
|
conn.just_woken_up = False
|
||||||
|
|
||||||
|
|
||||||
async def startToChat(conn, text):
|
async def startToChat(conn, text):
|
||||||
|
|||||||
@@ -89,8 +89,7 @@ async def sendAudio(conn, audios, pre_buffer=True):
|
|||||||
# 播放剩余音频帧
|
# 播放剩余音频帧
|
||||||
for opus_packet in remaining_audios:
|
for opus_packet in remaining_audios:
|
||||||
if conn.client_abort:
|
if conn.client_abort:
|
||||||
conn.client_abort = False
|
break
|
||||||
return
|
|
||||||
|
|
||||||
# 每分钟重置一次计时器
|
# 每分钟重置一次计时器
|
||||||
if time.perf_counter() - last_reset_time > 60:
|
if time.perf_counter() - last_reset_time > 60:
|
||||||
|
|||||||
@@ -61,6 +61,7 @@ async def handleTextMessage(conn, message):
|
|||||||
await send_tts_message(conn, "stop", None)
|
await send_tts_message(conn, "stop", None)
|
||||||
conn.client_is_speaking = False
|
conn.client_is_speaking = False
|
||||||
elif is_wakeup_words:
|
elif is_wakeup_words:
|
||||||
|
conn.just_woken_up = True
|
||||||
# 上报纯文字数据(复用ASR上报功能,但不提供音频数据)
|
# 上报纯文字数据(复用ASR上报功能,但不提供音频数据)
|
||||||
enqueue_asr_report(conn, "嘿,你好呀", [])
|
enqueue_asr_report(conn, "嘿,你好呀", [])
|
||||||
await startToChat(conn, "嘿,你好呀")
|
await startToChat(conn, "嘿,你好呀")
|
||||||
@@ -78,7 +79,9 @@ async def handleTextMessage(conn, message):
|
|||||||
elif msg_json["type"] == "mcp":
|
elif msg_json["type"] == "mcp":
|
||||||
conn.logger.bind(tag=TAG).info(f"收到mcp消息:{message}")
|
conn.logger.bind(tag=TAG).info(f"收到mcp消息:{message}")
|
||||||
if "payload" in msg_json:
|
if "payload" in msg_json:
|
||||||
asyncio.create_task(handle_mcp_message(conn, conn.mcp_client, msg_json["payload"]))
|
asyncio.create_task(
|
||||||
|
handle_mcp_message(conn, conn.mcp_client, msg_json["payload"])
|
||||||
|
)
|
||||||
elif msg_json["type"] == "server":
|
elif msg_json["type"] == "server":
|
||||||
# 记录日志时过滤敏感信息
|
# 记录日志时过滤敏感信息
|
||||||
conn.logger.bind(tag=TAG).info(
|
conn.logger.bind(tag=TAG).info(
|
||||||
|
|||||||
@@ -0,0 +1,71 @@
|
|||||||
|
import asyncio
|
||||||
|
from aiohttp import web
|
||||||
|
from config.logger import setup_logging
|
||||||
|
from core.api.ota_handler import OTAHandler
|
||||||
|
from core.api.vision_handler import VisionHandler
|
||||||
|
|
||||||
|
TAG = __name__
|
||||||
|
|
||||||
|
|
||||||
|
class SimpleHttpServer:
|
||||||
|
def __init__(self, config: dict):
|
||||||
|
self.config = config
|
||||||
|
self.logger = setup_logging()
|
||||||
|
self.ota_handler = OTAHandler(config)
|
||||||
|
self.vision_handler = VisionHandler(config)
|
||||||
|
|
||||||
|
def _get_websocket_url(self, local_ip: str, port: int) -> str:
|
||||||
|
"""获取websocket地址
|
||||||
|
|
||||||
|
Args:
|
||||||
|
local_ip: 本地IP地址
|
||||||
|
port: 端口号
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: websocket地址
|
||||||
|
"""
|
||||||
|
server_config = self.config["server"]
|
||||||
|
websocket_config = server_config.get("websocket")
|
||||||
|
|
||||||
|
if websocket_config and "你" not in websocket_config:
|
||||||
|
return websocket_config
|
||||||
|
else:
|
||||||
|
return f"ws://{local_ip}:{port}/xiaozhi/v1/"
|
||||||
|
|
||||||
|
async def start(self):
|
||||||
|
server_config = self.config["server"]
|
||||||
|
host = server_config.get("ip", "0.0.0.0")
|
||||||
|
port = int(server_config.get("http_port", 8003))
|
||||||
|
|
||||||
|
if port:
|
||||||
|
app = web.Application()
|
||||||
|
|
||||||
|
read_config_from_api = server_config.get("read_config_from_api", False)
|
||||||
|
|
||||||
|
if not read_config_from_api:
|
||||||
|
# 如果没有开启智控台,只是单模块运行,就需要再添加简单OTA接口,用于下发websocket接口
|
||||||
|
app.add_routes(
|
||||||
|
[
|
||||||
|
web.get("/xiaozhi/ota/", self.ota_handler.handle_get),
|
||||||
|
web.post("/xiaozhi/ota/", self.ota_handler.handle_post),
|
||||||
|
web.options("/xiaozhi/ota/", self.ota_handler.handle_post),
|
||||||
|
]
|
||||||
|
)
|
||||||
|
# 添加路由
|
||||||
|
app.add_routes(
|
||||||
|
[
|
||||||
|
web.get("/mcp/vision/explain", self.vision_handler.handle_get),
|
||||||
|
web.post("/mcp/vision/explain", self.vision_handler.handle_post),
|
||||||
|
web.options("/mcp/vision/explain", self.vision_handler.handle_post),
|
||||||
|
]
|
||||||
|
)
|
||||||
|
|
||||||
|
# 运行服务
|
||||||
|
runner = web.AppRunner(app)
|
||||||
|
await runner.setup()
|
||||||
|
site = web.TCPSite(runner, host, port)
|
||||||
|
await site.start()
|
||||||
|
|
||||||
|
# 保持服务运行
|
||||||
|
while True:
|
||||||
|
await asyncio.sleep(3600) # 每隔 1 小时检查一次
|
||||||
@@ -92,11 +92,21 @@ class MCPClient:
|
|||||||
args=self.config.get("args", []),
|
args=self.config.get("args", []),
|
||||||
env=env,
|
env=env,
|
||||||
)
|
)
|
||||||
stdio_r, stdio_w = await stack.enter_async_context(stdio_client(params))
|
stdio_r, stdio_w = await stack.enter_async_context(
|
||||||
|
stdio_client(params)
|
||||||
|
)
|
||||||
read_stream, write_stream = stdio_r, stdio_w
|
read_stream, write_stream = stdio_r, stdio_w
|
||||||
# 建立SSEClient
|
# 建立SSEClient
|
||||||
elif "url" in self.config:
|
elif "url" in self.config:
|
||||||
sse_r, sse_w = await stack.enter_async_context(sse_client(self.config["url"]))
|
if "API_ACCESS_TOKEN" in self.config:
|
||||||
|
headers = {
|
||||||
|
"Authorization": f"Bearer {self.config['API_ACCESS_TOKEN']}"
|
||||||
|
}
|
||||||
|
else:
|
||||||
|
headers = {}
|
||||||
|
sse_r, sse_w = await stack.enter_async_context(
|
||||||
|
sse_client(self.config["url"], headers=headers)
|
||||||
|
)
|
||||||
read_stream, write_stream = sse_r, sse_w
|
read_stream, write_stream = sse_r, sse_w
|
||||||
|
|
||||||
else:
|
else:
|
||||||
|
|||||||
@@ -213,7 +213,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
return None
|
return None
|
||||||
|
|
||||||
async def speech_to_text(
|
async def speech_to_text(
|
||||||
self, opus_data: List[bytes], session_id: str
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
) -> Tuple[Optional[str], Optional[str]]:
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
"""将语音数据转换为文本"""
|
"""将语音数据转换为文本"""
|
||||||
if self._is_token_expired():
|
if self._is_token_expired():
|
||||||
@@ -223,7 +223,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
file_path = None
|
file_path = None
|
||||||
try:
|
try:
|
||||||
# 解码Opus为PCM
|
# 解码Opus为PCM
|
||||||
if self.audio_format == "pcm":
|
if audio_format == "pcm":
|
||||||
pcm_data = opus_data
|
pcm_data = opus_data
|
||||||
else:
|
else:
|
||||||
pcm_data = self.decode_opus(opus_data)
|
pcm_data = self.decode_opus(opus_data)
|
||||||
|
|||||||
@@ -30,7 +30,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
os.makedirs(self.output_dir, exist_ok=True)
|
os.makedirs(self.output_dir, exist_ok=True)
|
||||||
|
|
||||||
async def speech_to_text(
|
async def speech_to_text(
|
||||||
self, opus_data: List[bytes], session_id: str
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
) -> Tuple[Optional[str], Optional[str]]:
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
"""将语音数据转换为文本"""
|
"""将语音数据转换为文本"""
|
||||||
if not opus_data:
|
if not opus_data:
|
||||||
@@ -45,7 +45,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
return None, file_path
|
return None, file_path
|
||||||
|
|
||||||
# 将Opus音频数据解码为PCM
|
# 将Opus音频数据解码为PCM
|
||||||
if self.audio_format == "pcm":
|
if audio_format == "pcm":
|
||||||
pcm_data = opus_data
|
pcm_data = opus_data
|
||||||
else:
|
else:
|
||||||
pcm_data = self.decode_opus(opus_data)
|
pcm_data = self.decode_opus(opus_data)
|
||||||
|
|||||||
@@ -1,15 +1,19 @@
|
|||||||
import os
|
import os
|
||||||
import time
|
import wave
|
||||||
import copy
|
import copy
|
||||||
import uuid
|
import uuid
|
||||||
import wave
|
import queue
|
||||||
|
import asyncio
|
||||||
|
import traceback
|
||||||
|
import threading
|
||||||
import opuslib_next
|
import opuslib_next
|
||||||
from abc import ABC, abstractmethod
|
from abc import ABC, abstractmethod
|
||||||
from config.logger import setup_logging
|
from config.logger import setup_logging
|
||||||
from typing import Optional, Tuple, List
|
from typing import Optional, Tuple, List
|
||||||
from core.utils.util import remove_punctuation_and_length
|
|
||||||
from core.handle.reportHandle import enqueue_asr_report
|
|
||||||
from core.handle.receiveAudioHandle import startToChat
|
from core.handle.receiveAudioHandle import startToChat
|
||||||
|
from core.handle.reportHandle import enqueue_asr_report
|
||||||
|
from core.utils.util import remove_punctuation_and_length
|
||||||
|
from core.handle.receiveAudioHandle import handleAudioMessage
|
||||||
|
|
||||||
TAG = __name__
|
TAG = __name__
|
||||||
logger = setup_logging()
|
logger = setup_logging()
|
||||||
@@ -17,53 +21,75 @@ logger = setup_logging()
|
|||||||
|
|
||||||
class ASRProviderBase(ABC):
|
class ASRProviderBase(ABC):
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
self.audio_format = "opus"
|
pass
|
||||||
self.conn = None
|
|
||||||
|
|
||||||
# 打开音频通道
|
# 打开音频通道
|
||||||
# 这里默认是非流式的处理方式
|
# 这里默认是非流式的处理方式
|
||||||
# 流式处理方式请在子类中重写
|
# 流式处理方式请在子类中重写
|
||||||
async def open_audio_channels(self, conn):
|
async def open_audio_channels(self, conn):
|
||||||
self.conn = conn
|
# tts 消化线程
|
||||||
|
conn.asr_priority_thread = threading.Thread(
|
||||||
|
target=self.asr_text_priority_thread, args=(conn,), daemon=True
|
||||||
|
)
|
||||||
|
conn.asr_priority_thread.start()
|
||||||
|
|
||||||
|
# 有序处理ASR音频
|
||||||
|
def asr_text_priority_thread(self, conn):
|
||||||
|
while not conn.stop_event.is_set():
|
||||||
|
try:
|
||||||
|
message = conn.asr_audio_queue.get(timeout=1)
|
||||||
|
future = asyncio.run_coroutine_threadsafe(
|
||||||
|
handleAudioMessage(conn, message),
|
||||||
|
conn.loop,
|
||||||
|
)
|
||||||
|
future.result()
|
||||||
|
except queue.Empty:
|
||||||
|
continue
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(
|
||||||
|
f"处理ASR文本失败: {str(e)}, 类型: {type(e).__name__}, 堆栈: {traceback.format_exc()}"
|
||||||
|
)
|
||||||
|
continue
|
||||||
|
|
||||||
# 接收音频
|
# 接收音频
|
||||||
# 这里默认是非流式的处理方式
|
# 这里默认是非流式的处理方式
|
||||||
# 流式处理方式请在子类中重写
|
# 流式处理方式请在子类中重写
|
||||||
async def receive_audio(self, audio, audio_have_voice):
|
async def receive_audio(self, conn, audio, audio_have_voice):
|
||||||
if (
|
if conn.client_listen_mode == "auto" or conn.client_listen_mode == "realtime":
|
||||||
self.conn.client_listen_mode == "auto"
|
|
||||||
or self.conn.client_listen_mode == "realtime"
|
|
||||||
):
|
|
||||||
have_voice = audio_have_voice
|
have_voice = audio_have_voice
|
||||||
else:
|
else:
|
||||||
have_voice = self.conn.client_have_voice
|
have_voice = conn.client_have_voice
|
||||||
# 如果本次没有声音,本段也没声音,就把声音丢弃了
|
# 如果本次没有声音,本段也没声音,就把声音丢弃了
|
||||||
self.conn.asr_audio.append(audio)
|
conn.asr_audio.append(audio)
|
||||||
if have_voice == False and self.conn.client_have_voice == False:
|
if have_voice == False and conn.client_have_voice == False:
|
||||||
self.conn.asr_audio = self.conn.asr_audio[-10:]
|
conn.asr_audio = conn.asr_audio[-10:]
|
||||||
return
|
return
|
||||||
|
|
||||||
# 如果本段有声音,且已经停止了
|
# 如果本段有声音,且已经停止了
|
||||||
if self.conn.client_voice_stop:
|
if conn.client_voice_stop:
|
||||||
asr_audio_task = copy.deepcopy(self.conn.asr_audio)
|
asr_audio_task = copy.deepcopy(conn.asr_audio)
|
||||||
self.conn.asr_audio.clear()
|
conn.asr_audio.clear()
|
||||||
|
|
||||||
# 音频太短了,无法识别
|
# 音频太短了,无法识别
|
||||||
self.conn.reset_vad_states()
|
conn.reset_vad_states()
|
||||||
if len(asr_audio_task) > 15:
|
if len(asr_audio_task) > 15:
|
||||||
await self.handle_voice_stop(asr_audio_task)
|
await self.handle_voice_stop(conn, asr_audio_task)
|
||||||
|
|
||||||
# 处理语音停止
|
# 处理语音停止
|
||||||
async def handle_voice_stop(self, asr_audio_task):
|
async def handle_voice_stop(self, conn, asr_audio_task):
|
||||||
raw_text, _ = await self.speech_to_text(
|
raw_text, _ = await self.speech_to_text(
|
||||||
asr_audio_task, self.conn.session_id
|
asr_audio_task, conn.session_id, conn.audio_format
|
||||||
) # 确保ASR模块返回原始文本
|
) # 确保ASR模块返回原始文本
|
||||||
self.conn.logger.bind(tag=TAG).info(f"识别文本: {raw_text}")
|
conn.logger.bind(tag=TAG).info(f"识别文本: {raw_text}")
|
||||||
text_len, _ = remove_punctuation_and_length(raw_text)
|
text_len, _ = remove_punctuation_and_length(raw_text)
|
||||||
|
self.stop_ws_connection()
|
||||||
if text_len > 0:
|
if text_len > 0:
|
||||||
# 使用自定义模块进行上报
|
# 使用自定义模块进行上报
|
||||||
await startToChat(self.conn, raw_text)
|
await startToChat(conn, raw_text)
|
||||||
enqueue_asr_report(self.conn, raw_text, asr_audio_task)
|
enqueue_asr_report(conn, raw_text, asr_audio_task)
|
||||||
|
|
||||||
|
def stop_ws_connection(self):
|
||||||
|
pass
|
||||||
|
|
||||||
def save_audio_to_file(self, pcm_data: List[bytes], session_id: str) -> str:
|
def save_audio_to_file(self, pcm_data: List[bytes], session_id: str) -> str:
|
||||||
"""PCM数据保存为WAV文件"""
|
"""PCM数据保存为WAV文件"""
|
||||||
@@ -81,15 +107,11 @@ class ASRProviderBase(ABC):
|
|||||||
|
|
||||||
@abstractmethod
|
@abstractmethod
|
||||||
async def speech_to_text(
|
async def speech_to_text(
|
||||||
self, opus_data: List[bytes], session_id: str
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
) -> Tuple[Optional[str], Optional[str]]:
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
"""将语音数据转换为文本"""
|
"""将语音数据转换为文本"""
|
||||||
pass
|
pass
|
||||||
|
|
||||||
def set_audio_format(self, format: str) -> None:
|
|
||||||
"""设置音频格式"""
|
|
||||||
self.audio_format = format
|
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def decode_opus(opus_data: List[bytes]) -> bytes:
|
def decode_opus(opus_data: List[bytes]) -> bytes:
|
||||||
"""将Opus音频数据解码为PCM数据"""
|
"""将Opus音频数据解码为PCM数据"""
|
||||||
|
|||||||
@@ -1,534 +1,267 @@
|
|||||||
|
import time
|
||||||
|
import os
|
||||||
|
import uuid
|
||||||
import json
|
import json
|
||||||
import gzip
|
import gzip
|
||||||
import uuid
|
|
||||||
import asyncio
|
|
||||||
import websockets
|
import websockets
|
||||||
import opuslib_next
|
|
||||||
from core.providers.asr.base import ASRProviderBase
|
|
||||||
from config.logger import setup_logging
|
from config.logger import setup_logging
|
||||||
|
from typing import Optional, Tuple, List
|
||||||
|
from core.providers.asr.base import ASRProviderBase
|
||||||
from core.providers.asr.dto.dto import InterfaceType
|
from core.providers.asr.dto.dto import InterfaceType
|
||||||
import threading
|
|
||||||
|
|
||||||
TAG = __name__
|
TAG = __name__
|
||||||
logger = setup_logging()
|
logger = setup_logging()
|
||||||
|
|
||||||
CLIENT_FULL_REQUEST = 0b0001
|
CLIENT_FULL_REQUEST = 0b0001
|
||||||
CLIENT_AUDIO_ONLY_REQUEST = 0b0010
|
CLIENT_AUDIO_ONLY_REQUEST = 0b0010
|
||||||
|
|
||||||
|
NO_SEQUENCE = 0b0000
|
||||||
|
NEG_SEQUENCE = 0b0010
|
||||||
|
|
||||||
SERVER_FULL_RESPONSE = 0b1001
|
SERVER_FULL_RESPONSE = 0b1001
|
||||||
SERVER_ACK = 0b1011
|
SERVER_ACK = 0b1011
|
||||||
SERVER_ERROR_RESPONSE = 0b1111
|
SERVER_ERROR_RESPONSE = 0b1111
|
||||||
NO_SEQUENCE = 0b0000
|
|
||||||
NEG_SEQUENCE = 0b0010
|
NO_SERIALIZATION = 0b0000
|
||||||
JSON_SERIALIZATION = 0b0001
|
JSON = 0b0001
|
||||||
GZIP_COMPRESSION = 0b0001
|
THRIFT = 0b0011
|
||||||
PROTOCOL_VERSION = 0b0001
|
CUSTOM_TYPE = 0b1111
|
||||||
|
NO_COMPRESSION = 0b0000
|
||||||
|
GZIP = 0b0001
|
||||||
|
CUSTOM_COMPRESSION = 0b1111
|
||||||
|
|
||||||
|
|
||||||
|
def parse_response(res):
|
||||||
|
"""
|
||||||
|
protocol_version(4 bits), header_size(4 bits),
|
||||||
|
message_type(4 bits), message_type_specific_flags(4 bits)
|
||||||
|
serialization_method(4 bits) message_compression(4 bits)
|
||||||
|
reserved (8bits) 保留字段
|
||||||
|
header_extensions 扩展头(大小等于 8 * 4 * (header_size - 1) )
|
||||||
|
payload 类似与http 请求体
|
||||||
|
"""
|
||||||
|
protocol_version = res[0] >> 4
|
||||||
|
header_size = res[0] & 0x0F
|
||||||
|
message_type = res[1] >> 4
|
||||||
|
message_type_specific_flags = res[1] & 0x0F
|
||||||
|
serialization_method = res[2] >> 4
|
||||||
|
message_compression = res[2] & 0x0F
|
||||||
|
reserved = res[3]
|
||||||
|
header_extensions = res[4 : header_size * 4]
|
||||||
|
payload = res[header_size * 4 :]
|
||||||
|
result = {}
|
||||||
|
payload_msg = None
|
||||||
|
payload_size = 0
|
||||||
|
if message_type == SERVER_FULL_RESPONSE:
|
||||||
|
payload_size = int.from_bytes(payload[:4], "big", signed=True)
|
||||||
|
payload_msg = payload[4:]
|
||||||
|
elif message_type == SERVER_ACK:
|
||||||
|
seq = int.from_bytes(payload[:4], "big", signed=True)
|
||||||
|
result["seq"] = seq
|
||||||
|
if len(payload) >= 8:
|
||||||
|
payload_size = int.from_bytes(payload[4:8], "big", signed=False)
|
||||||
|
payload_msg = payload[8:]
|
||||||
|
elif message_type == SERVER_ERROR_RESPONSE:
|
||||||
|
code = int.from_bytes(payload[:4], "big", signed=False)
|
||||||
|
result["code"] = code
|
||||||
|
payload_size = int.from_bytes(payload[4:8], "big", signed=False)
|
||||||
|
payload_msg = payload[8:]
|
||||||
|
if payload_msg is None:
|
||||||
|
return result
|
||||||
|
if message_compression == GZIP:
|
||||||
|
payload_msg = gzip.decompress(payload_msg)
|
||||||
|
if serialization_method == JSON:
|
||||||
|
payload_msg = json.loads(str(payload_msg, "utf-8"))
|
||||||
|
elif serialization_method != NO_SERIALIZATION:
|
||||||
|
payload_msg = str(payload_msg, "utf-8")
|
||||||
|
result["payload_msg"] = payload_msg
|
||||||
|
result["payload_size"] = payload_size
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
class ASRProvider(ASRProviderBase):
|
class ASRProvider(ASRProviderBase):
|
||||||
def __init__(self, config, delete_audio_file):
|
def __init__(self, config: dict, delete_audio_file: bool):
|
||||||
super().__init__()
|
super().__init__()
|
||||||
self.interface_type = InterfaceType.STREAM
|
self.interface_type = InterfaceType.NON_STREAM
|
||||||
self.config = config
|
self.appid = config.get("appid")
|
||||||
self.text = ""
|
|
||||||
self.max_retries = 3
|
|
||||||
self.retry_delay = 2 # 重试延迟秒数
|
|
||||||
self.recv_lock = asyncio.Lock() # 添加接收锁
|
|
||||||
self.reconnect_lock = asyncio.Lock() # 添加重连锁
|
|
||||||
self.last_reconnect_time = 0 # 上次重连时间
|
|
||||||
self.reconnect_cooldown = 1 # 增加重连冷却时间到10秒
|
|
||||||
self.reconnect_count = 0 # 当前重连次数
|
|
||||||
self.max_reconnect_count = 3 # 减少最大重连次数到3次
|
|
||||||
self.asr_thread = None # ASR监听线程
|
|
||||||
self.thread_lock = threading.Lock() # 线程管理锁
|
|
||||||
self.is_reconnecting = False # 添加重连状态标志
|
|
||||||
|
|
||||||
# 添加会话管理相关属性
|
|
||||||
self._session_lock = asyncio.Lock() # 会话操作的并发锁
|
|
||||||
self._current_session_id = None # 当前会话ID
|
|
||||||
self._session_started = False # 会话是否已开始
|
|
||||||
self._session_finished = False # 会话是否已结束
|
|
||||||
self._session_close_event = asyncio.Event() # 添加会话关闭事件
|
|
||||||
|
|
||||||
self.appid = str(config.get("appid"))
|
|
||||||
self.cluster = config.get("cluster")
|
self.cluster = config.get("cluster")
|
||||||
self.access_token = config.get("access_token")
|
self.access_token = config.get("access_token")
|
||||||
self.boosting_table_name = config.get("boosting_table_name", "")
|
self.boosting_table_name = config.get("boosting_table_name", "")
|
||||||
self.correct_table_name = config.get("correct_table_name", "")
|
self.correct_table_name = config.get("correct_table_name", "")
|
||||||
self.output_dir = config.get("output_dir", "temp/")
|
self.output_dir = config.get("output_dir")
|
||||||
self.delete_audio_file = delete_audio_file
|
self.delete_audio_file = delete_audio_file
|
||||||
|
|
||||||
self.ws_url = "wss://openspeech.bytedance.com/api/v2/asr"
|
self.host = "openspeech.bytedance.com"
|
||||||
self.uid = config.get("uid", "streaming_asr_service")
|
self.ws_url = f"wss://{self.host}/api/v2/asr"
|
||||||
self.workflow = config.get(
|
self.success_code = 1000
|
||||||
"workflow", "audio_in,resample,partition,vad,fe,decode,itn,nlu_punctuate"
|
self.seg_duration = 15000
|
||||||
)
|
|
||||||
self.result_type = config.get("result_type", "single")
|
|
||||||
self.format = config.get("format", "raw")
|
|
||||||
self.codec = config.get("codec", "pcm")
|
|
||||||
self.rate = config.get("sample_rate", 16000)
|
|
||||||
self.language = config.get("language", "zh-CN")
|
|
||||||
self.bits = config.get("bits", 16)
|
|
||||||
self.channel = config.get("channel", 1)
|
|
||||||
self.auth_method = config.get("auth_method", "token")
|
|
||||||
self.secret = config.get("secret", "access_secret")
|
|
||||||
self.decoder = opuslib_next.Decoder(16000, 1)
|
|
||||||
self.asr_ws = None
|
|
||||||
self.forward_task = None
|
|
||||||
self.conn = None
|
|
||||||
|
|
||||||
###################################################################################
|
# 确保输出目录存在
|
||||||
# 豆包流式ASR重写父类的方法--开始
|
os.makedirs(self.output_dir, exist_ok=True)
|
||||||
###################################################################################
|
|
||||||
async def open_audio_channels(self, conn):
|
|
||||||
await super().open_audio_channels(conn)
|
|
||||||
|
|
||||||
async with self._session_lock:
|
@staticmethod
|
||||||
# 如果正在重连,等待重连完成
|
def _generate_header(
|
||||||
if self.is_reconnecting:
|
message_type=CLIENT_FULL_REQUEST, message_type_specific_flags=NO_SEQUENCE
|
||||||
logger.bind(tag=TAG).info("等待当前重连完成...")
|
) -> bytearray:
|
||||||
await self._session_close_event.wait()
|
"""Generate protocol header."""
|
||||||
self._session_close_event.clear()
|
header = bytearray()
|
||||||
|
header_size = 1
|
||||||
|
header.append((0b0001 << 4) | header_size) # Protocol version
|
||||||
|
header.append((message_type << 4) | message_type_specific_flags)
|
||||||
|
header.append((0b0001 << 4) | 0b0001) # JSON serialization & GZIP compression
|
||||||
|
header.append(0x00) # reserved
|
||||||
|
return header
|
||||||
|
|
||||||
# 如果已有会话未结束,先关闭它
|
def _construct_request(self, reqid) -> dict:
|
||||||
if self._session_started and not self._session_finished:
|
"""Construct the request payload."""
|
||||||
logger.bind(tag=TAG).warning(
|
return {
|
||||||
f"发现未关闭的会话 {self._current_session_id},正在关闭..."
|
|
||||||
)
|
|
||||||
if self.asr_ws is not None:
|
|
||||||
try:
|
|
||||||
await self.asr_ws.close()
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).warning(f"关闭旧连接时发生错误: {e}")
|
|
||||||
finally:
|
|
||||||
self.asr_ws = None
|
|
||||||
self._session_finished = True
|
|
||||||
self._session_close_event.set()
|
|
||||||
|
|
||||||
# 重置会话状态
|
|
||||||
self._current_session_id = str(uuid.uuid4())
|
|
||||||
self._session_started = True
|
|
||||||
self._session_finished = False
|
|
||||||
self.is_reconnecting = True
|
|
||||||
|
|
||||||
try:
|
|
||||||
retry_count = 0
|
|
||||||
while retry_count < self.max_retries:
|
|
||||||
try:
|
|
||||||
headers = (
|
|
||||||
self.token_auth() if self.auth_method == "token" else None
|
|
||||||
)
|
|
||||||
self.asr_ws = await websockets.connect(
|
|
||||||
self.ws_url,
|
|
||||||
additional_headers=headers,
|
|
||||||
max_size=1000000000,
|
|
||||||
ping_interval=None,
|
|
||||||
ping_timeout=None,
|
|
||||||
close_timeout=10,
|
|
||||||
)
|
|
||||||
|
|
||||||
# 发送初始化请求
|
|
||||||
request_params = self.construct_request(
|
|
||||||
self._current_session_id
|
|
||||||
)
|
|
||||||
try:
|
|
||||||
payload_bytes = str.encode(json.dumps(request_params))
|
|
||||||
payload_bytes = gzip.compress(payload_bytes)
|
|
||||||
full_client_request = self.generate_header()
|
|
||||||
full_client_request.extend(
|
|
||||||
(len(payload_bytes)).to_bytes(4, "big")
|
|
||||||
)
|
|
||||||
full_client_request.extend(payload_bytes)
|
|
||||||
await self.asr_ws.send(full_client_request)
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"发送初始化请求失败: {e}")
|
|
||||||
raise e
|
|
||||||
|
|
||||||
# 等待初始化响应
|
|
||||||
try:
|
|
||||||
init_res = await self.asr_ws.recv()
|
|
||||||
self.parse_response(init_res)
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"ASR服务初始化失败: {e}")
|
|
||||||
raise e
|
|
||||||
|
|
||||||
# 启动接收ASR结果的异步任务
|
|
||||||
with self.thread_lock:
|
|
||||||
if (
|
|
||||||
self.asr_thread is None
|
|
||||||
or not self.asr_thread.is_alive()
|
|
||||||
):
|
|
||||||
logger.bind(tag=TAG).info("创建新的ASR监听线程...")
|
|
||||||
self.asr_thread = threading.Thread(
|
|
||||||
target=self._start_monitor_asr_response_thread,
|
|
||||||
daemon=True,
|
|
||||||
)
|
|
||||||
self.asr_thread.start()
|
|
||||||
# 等待一小段时间确保线程启动
|
|
||||||
await asyncio.sleep(0.1)
|
|
||||||
if not self.asr_thread.is_alive():
|
|
||||||
logger.bind(tag=TAG).error("ASR监听线程启动失败")
|
|
||||||
raise Exception("ASR监听线程启动失败")
|
|
||||||
logger.bind(tag=TAG).info("ASR监听线程已启动")
|
|
||||||
return
|
|
||||||
|
|
||||||
except websockets.exceptions.WebSocketException as e:
|
|
||||||
retry_count += 1
|
|
||||||
if retry_count < self.max_retries:
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
f"WebSocket连接失败,正在进行第{retry_count}次重试: {e}"
|
|
||||||
)
|
|
||||||
await asyncio.sleep(self.retry_delay)
|
|
||||||
else:
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
f"WebSocket连接失败,已达到最大重试次数: {e}"
|
|
||||||
)
|
|
||||||
raise
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"WebSocket连接发生未知错误: {e}")
|
|
||||||
raise
|
|
||||||
finally:
|
|
||||||
self.is_reconnecting = False
|
|
||||||
self._session_close_event.set()
|
|
||||||
|
|
||||||
async def receive_audio(self, audio, _):
|
|
||||||
if not isinstance(audio, bytes):
|
|
||||||
return
|
|
||||||
|
|
||||||
try:
|
|
||||||
# 解码opus得到PCM数据
|
|
||||||
pcm_frame = self.decoder.decode(audio, 960)
|
|
||||||
payload = gzip.compress(pcm_frame)
|
|
||||||
audio_request = bytearray(self.generate_audio_default_header())
|
|
||||||
audio_request.extend(len(payload).to_bytes(4, "big"))
|
|
||||||
audio_request.extend(payload)
|
|
||||||
if self.asr_ws:
|
|
||||||
await self.asr_ws.send(audio_request)
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).debug(f"发送音频数据时发生错误: {e}")
|
|
||||||
|
|
||||||
###################################################################################
|
|
||||||
# 豆包流式ASR重写父类的方法--结束
|
|
||||||
###################################################################################
|
|
||||||
|
|
||||||
def construct_request(self, reqid):
|
|
||||||
req = {
|
|
||||||
"app": {
|
"app": {
|
||||||
"appid": self.appid,
|
"appid": f"{self.appid}",
|
||||||
"cluster": self.cluster,
|
"cluster": self.cluster,
|
||||||
"token": self.access_token,
|
"token": self.access_token,
|
||||||
},
|
},
|
||||||
"user": {"uid": self.uid},
|
"user": {
|
||||||
|
"uid": str(uuid.uuid4()),
|
||||||
|
},
|
||||||
"request": {
|
"request": {
|
||||||
"reqid": reqid,
|
"reqid": reqid,
|
||||||
"workflow": self.workflow,
|
"show_utterances": False,
|
||||||
"show_utterances": True,
|
|
||||||
"result_type": self.result_type,
|
|
||||||
"sequence": 1,
|
"sequence": 1,
|
||||||
"boosting_table_name": self.boosting_table_name,
|
"boosting_table_name": self.boosting_table_name,
|
||||||
"correct_table_name": self.correct_table_name,
|
"correct_table_name": self.correct_table_name,
|
||||||
},
|
},
|
||||||
"audio": {
|
"audio": {
|
||||||
"format": self.format,
|
"format": "raw",
|
||||||
"codec": self.codec,
|
"rate": 16000,
|
||||||
"rate": self.rate,
|
"language": "zh-CN",
|
||||||
"language": self.language,
|
"bits": 16,
|
||||||
"bits": self.bits,
|
"channel": 1,
|
||||||
"channel": self.channel,
|
"codec": "raw",
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
return req
|
|
||||||
|
|
||||||
def token_auth(self):
|
async def _send_request(
|
||||||
return {"Authorization": f"Bearer; {self.access_token}"}
|
self, audio_data: List[bytes], segment_size: int
|
||||||
|
) -> Optional[str]:
|
||||||
def generate_header(
|
"""Send request to Volcano ASR service."""
|
||||||
self,
|
|
||||||
version=PROTOCOL_VERSION,
|
|
||||||
message_type=CLIENT_FULL_REQUEST,
|
|
||||||
message_type_specific_flags=NO_SEQUENCE,
|
|
||||||
serial_method=JSON_SERIALIZATION,
|
|
||||||
compression_type=GZIP_COMPRESSION,
|
|
||||||
reserved_data=0x00,
|
|
||||||
extension_header: bytes = b"",
|
|
||||||
):
|
|
||||||
"""
|
|
||||||
生成协议头:
|
|
||||||
- 第1字节:高4位:协议版本,低4位:头部大小(单位 4 字节)
|
|
||||||
- 第2字节:高4位:消息类型,低4位:消息类型特定标志
|
|
||||||
- 第3字节:高4位:序列化方式,低4位:压缩方式
|
|
||||||
- 第4字节:保留字段
|
|
||||||
- 后续:扩展头(如果有)
|
|
||||||
"""
|
|
||||||
header = bytearray()
|
|
||||||
header_size = int(len(extension_header) / 4) + 1
|
|
||||||
header.append((version << 4) | header_size)
|
|
||||||
header.append((message_type << 4) | message_type_specific_flags)
|
|
||||||
header.append((serial_method << 4) | compression_type)
|
|
||||||
header.append(reserved_data)
|
|
||||||
header.extend(extension_header)
|
|
||||||
return header
|
|
||||||
|
|
||||||
def generate_full_default_header(self):
|
|
||||||
# full client request 默认头
|
|
||||||
return self.generate_header(
|
|
||||||
version=PROTOCOL_VERSION,
|
|
||||||
message_type=CLIENT_FULL_REQUEST,
|
|
||||||
message_type_specific_flags=NO_SEQUENCE,
|
|
||||||
serial_method=JSON_SERIALIZATION,
|
|
||||||
compression_type=GZIP_COMPRESSION,
|
|
||||||
)
|
|
||||||
|
|
||||||
def generate_audio_default_header(self):
|
|
||||||
# 普通音频片段请求
|
|
||||||
return self.generate_header(
|
|
||||||
version=PROTOCOL_VERSION,
|
|
||||||
message_type=CLIENT_AUDIO_ONLY_REQUEST,
|
|
||||||
message_type_specific_flags=NO_SEQUENCE,
|
|
||||||
serial_method=JSON_SERIALIZATION,
|
|
||||||
compression_type=GZIP_COMPRESSION,
|
|
||||||
)
|
|
||||||
|
|
||||||
def generate_last_audio_default_header(self):
|
|
||||||
# 最后一个音频片段标志
|
|
||||||
return self.generate_header(
|
|
||||||
version=PROTOCOL_VERSION,
|
|
||||||
message_type=CLIENT_AUDIO_ONLY_REQUEST,
|
|
||||||
message_type_specific_flags=NEG_SEQUENCE, # 用 NEG_SEQUENCE 表示结束
|
|
||||||
serial_method=JSON_SERIALIZATION,
|
|
||||||
compression_type=GZIP_COMPRESSION,
|
|
||||||
)
|
|
||||||
|
|
||||||
def _start_monitor_asr_response_thread(self):
|
|
||||||
# 初始化链接
|
|
||||||
try:
|
try:
|
||||||
with self.thread_lock:
|
auth_header = {"Authorization": "Bearer; {}".format(self.access_token)}
|
||||||
if self.conn is None or self.conn.loop is None:
|
async with websockets.connect(
|
||||||
logger.bind(tag=TAG).error(
|
self.ws_url, additional_headers=auth_header
|
||||||
"无法启动ASR监听线程:conn或loop未初始化"
|
) as websocket:
|
||||||
)
|
# Prepare request data
|
||||||
return
|
request_params = self._construct_request(str(uuid.uuid4()))
|
||||||
|
payload_bytes = str.encode(json.dumps(request_params))
|
||||||
|
payload_bytes = gzip.compress(payload_bytes)
|
||||||
|
full_client_request = self._generate_header()
|
||||||
|
full_client_request.extend(
|
||||||
|
(len(payload_bytes)).to_bytes(4, "big")
|
||||||
|
) # payload size(4 bytes)
|
||||||
|
full_client_request.extend(payload_bytes) # payload
|
||||||
|
|
||||||
try:
|
# Send header and metadata
|
||||||
logger.bind(tag=TAG).info("开始启动ASR监听...")
|
# full_client_request
|
||||||
asyncio.run_coroutine_threadsafe(
|
await websocket.send(full_client_request)
|
||||||
self._forward_asr_results(), loop=self.conn.loop
|
res = await websocket.recv()
|
||||||
)
|
result = parse_response(res)
|
||||||
logger.bind(tag=TAG).info("ASR监听已启动")
|
if (
|
||||||
except Exception as e:
|
"payload_msg" in result
|
||||||
logger.bind(tag=TAG).error(f"启动ASR监听线程失败: {e}")
|
and result["payload_msg"]["code"] != self.success_code
|
||||||
except Exception as e:
|
):
|
||||||
logger.bind(tag=TAG).error(f"ASR监听线程发生未预期的错误: {e}")
|
logger.bind(tag=TAG).error(f"ASR error: {result}")
|
||||||
|
return None
|
||||||
|
|
||||||
async def _forward_asr_results(self):
|
for seq, (chunk, last) in enumerate(
|
||||||
try:
|
self.slice_data(audio_data, segment_size), 1
|
||||||
while not self.conn.stop_event.is_set():
|
):
|
||||||
try:
|
if last:
|
||||||
if self.asr_ws is None:
|
audio_only_request = self._generate_header(
|
||||||
# 检查是否需要重连
|
message_type=CLIENT_AUDIO_ONLY_REQUEST,
|
||||||
async with self.reconnect_lock:
|
message_type_specific_flags=NEG_SEQUENCE,
|
||||||
current_time = asyncio.get_event_loop().time()
|
|
||||||
if (
|
|
||||||
current_time - self.last_reconnect_time
|
|
||||||
< self.reconnect_cooldown
|
|
||||||
):
|
|
||||||
await asyncio.sleep(1)
|
|
||||||
continue
|
|
||||||
|
|
||||||
if self.reconnect_count >= self.max_reconnect_count:
|
|
||||||
logger.bind(tag=TAG).error(
|
|
||||||
"达到最大重连次数限制,停止重连"
|
|
||||||
)
|
|
||||||
await asyncio.sleep(self.reconnect_cooldown)
|
|
||||||
self.reconnect_count = 0
|
|
||||||
continue
|
|
||||||
|
|
||||||
self.last_reconnect_time = current_time
|
|
||||||
self.reconnect_count += 1
|
|
||||||
logger.bind(tag=TAG).info(
|
|
||||||
f"尝试重新连接ASR服务... (第{self.reconnect_count}次)"
|
|
||||||
)
|
|
||||||
await self.open_audio_channels(self.conn)
|
|
||||||
continue
|
|
||||||
|
|
||||||
# 使用锁来确保同一时间只有一个协程在接收数据
|
|
||||||
async with self.recv_lock:
|
|
||||||
response = await self.asr_ws.recv()
|
|
||||||
result = self.parse_response(response)
|
|
||||||
|
|
||||||
# 检查是否需要重连
|
|
||||||
if result.get("need_reconnect", False):
|
|
||||||
logger.bind(tag=TAG).info(
|
|
||||||
"检测到需要重连的错误,准备重新连接..."
|
|
||||||
)
|
)
|
||||||
if self.asr_ws is not None:
|
else:
|
||||||
try:
|
audio_only_request = self._generate_header(
|
||||||
await self.asr_ws.close()
|
message_type=CLIENT_AUDIO_ONLY_REQUEST
|
||||||
except Exception as e:
|
)
|
||||||
logger.bind(tag=TAG).warning(
|
payload_bytes = gzip.compress(chunk)
|
||||||
f"关闭旧连接时发生错误: {e}"
|
audio_only_request.extend(
|
||||||
)
|
(len(payload_bytes)).to_bytes(4, "big")
|
||||||
finally:
|
) # payload size(4 bytes)
|
||||||
self.asr_ws = None
|
audio_only_request.extend(payload_bytes) # payload
|
||||||
continue
|
# Send audio data
|
||||||
|
await websocket.send(audio_only_request)
|
||||||
|
|
||||||
if "payload_msg" in result:
|
# Receive response
|
||||||
if "result" in result["payload_msg"]:
|
response = await websocket.recv()
|
||||||
# 检查是否有utterances并且definite为True
|
result = parse_response(response)
|
||||||
utterances = result["payload_msg"]["result"][0].get(
|
|
||||||
"utterances", []
|
|
||||||
)
|
|
||||||
for utterance in utterances:
|
|
||||||
if utterance.get("definite", False):
|
|
||||||
self.text = utterance["text"]
|
|
||||||
await self.handle_voice_stop(None)
|
|
||||||
break
|
|
||||||
|
|
||||||
except websockets.ConnectionClosed:
|
if (
|
||||||
logger.bind(tag=TAG).debug("ASR服务连接已关闭,准备重连...")
|
"payload_msg" in result
|
||||||
# 确保关闭旧连接
|
and result["payload_msg"]["code"] == self.success_code
|
||||||
if self.asr_ws is not None:
|
):
|
||||||
try:
|
if len(result["payload_msg"]["result"]) > 0:
|
||||||
await self.asr_ws.close()
|
return result["payload_msg"]["result"][0]["text"]
|
||||||
except Exception as e:
|
return None
|
||||||
logger.bind(tag=TAG).warning(f"关闭旧连接时发生错误: {e}")
|
else:
|
||||||
finally:
|
logger.bind(tag=TAG).error(f"ASR error: {result}")
|
||||||
self.asr_ws = None
|
return None
|
||||||
|
|
||||||
# 等待冷却时间
|
|
||||||
await asyncio.sleep(self.reconnect_cooldown)
|
|
||||||
continue
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
if not self.conn.stop_event.is_set():
|
|
||||||
logger.bind(tag=TAG).error(f"ASR监听发生错误: {e}")
|
|
||||||
await asyncio.sleep(self.retry_delay)
|
|
||||||
continue
|
|
||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.bind(tag=TAG).error(f"ASR监听线程发生错误: {e}")
|
logger.bind(tag=TAG).error(f"ASR request failed: {e}", exc_info=True)
|
||||||
# 确保在发生严重错误时也能继续尝试重连
|
return None
|
||||||
if not self.conn.stop_event.is_set():
|
|
||||||
await asyncio.sleep(self.retry_delay)
|
|
||||||
await self._forward_asr_results() # 递归重试
|
|
||||||
|
|
||||||
async def speech_to_text(self, opus_data, session_id):
|
@staticmethod
|
||||||
result = self.text
|
def slice_data(data: bytes, chunk_size: int) -> (list, bool):
|
||||||
self.text = "" # 清空text
|
|
||||||
return result, None
|
|
||||||
|
|
||||||
def parse_response(self, res: bytes) -> dict:
|
|
||||||
"""
|
"""
|
||||||
解析 ASR 服务返回的二进制响应。
|
slice data
|
||||||
根据协议格式解析头部和 payload,若采用 GZIP 压缩则先解压,再根据 JSON 反序列化。
|
:param data: wav data
|
||||||
|
:param chunk_size: the segment size in one request
|
||||||
|
:return: segment data, last flag
|
||||||
"""
|
"""
|
||||||
protocol_version = res[0] >> 4
|
data_len = len(data)
|
||||||
header_size = res[0] & 0x0F
|
offset = 0
|
||||||
message_type = res[1] >> 4
|
while offset + chunk_size < data_len:
|
||||||
serialization_method = res[2] >> 4
|
yield data[offset : offset + chunk_size], False
|
||||||
message_compression = res[2] & 0x0F
|
offset += chunk_size
|
||||||
payload = res[header_size * 4 :]
|
|
||||||
result = {}
|
|
||||||
payload_msg = None
|
|
||||||
payload_size = 0
|
|
||||||
|
|
||||||
if message_type == SERVER_FULL_RESPONSE:
|
|
||||||
payload_size = int.from_bytes(payload[:4], "big", signed=True)
|
|
||||||
payload_msg = payload[4:]
|
|
||||||
elif message_type == SERVER_ACK:
|
|
||||||
seq = int.from_bytes(payload[:4], "big", signed=True)
|
|
||||||
result["seq"] = seq
|
|
||||||
if len(payload) >= 8:
|
|
||||||
payload_size = int.from_bytes(payload[4:8], "big", signed=False)
|
|
||||||
payload_msg = payload[8:]
|
|
||||||
elif message_type == SERVER_ERROR_RESPONSE:
|
|
||||||
code = int.from_bytes(payload[:4], "big", signed=False)
|
|
||||||
result["code"] = code
|
|
||||||
payload_size = int.from_bytes(payload[4:8], "big", signed=False)
|
|
||||||
payload_msg = payload[8:]
|
|
||||||
|
|
||||||
if payload_msg is None:
|
|
||||||
return result
|
|
||||||
if message_compression == GZIP_COMPRESSION:
|
|
||||||
payload_msg = gzip.decompress(payload_msg)
|
|
||||||
if serialization_method == JSON_SERIALIZATION:
|
|
||||||
payload_msg = json.loads(payload_msg.decode("utf-8"))
|
|
||||||
else:
|
else:
|
||||||
payload_msg = payload_msg.decode("utf-8")
|
yield data[offset:data_len], True
|
||||||
result["payload_msg"] = payload_msg
|
|
||||||
result["payload_size"] = payload_size
|
|
||||||
|
|
||||||
# 错误码处理
|
async def speech_to_text(
|
||||||
if "code" in result:
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
error_code = result["code"]
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
error_message = ""
|
"""将语音数据转换为文本"""
|
||||||
|
|
||||||
if error_code == 1000:
|
file_path = None
|
||||||
error_message = "成功"
|
try:
|
||||||
elif error_code == 1001:
|
# 合并所有opus数据包
|
||||||
error_message = "请求参数无效:请求参数缺失必需字段/字段值无效/重复请求"
|
if audio_format == "pcm":
|
||||||
elif error_code == 1002:
|
pcm_data = opus_data
|
||||||
error_message = "无访问权限:token无效/过期/无权访问指定服务"
|
|
||||||
elif error_code == 1003:
|
|
||||||
error_message = "访问超频:当前appid访问QPS超出设定阈值"
|
|
||||||
elif error_code == 1004:
|
|
||||||
error_message = "访问超额:当前appid访问次数超出限制"
|
|
||||||
elif error_code == 1005:
|
|
||||||
error_message = "服务器繁忙:服务过载,无法处理当前请求"
|
|
||||||
elif error_code == 1010:
|
|
||||||
error_message = "音频过长:音频数据时长超出阈值"
|
|
||||||
elif error_code == 1011:
|
|
||||||
error_message = "音频过大:音频数据大小超出阈值"
|
|
||||||
elif error_code == 1012:
|
|
||||||
error_message = "音频格式无效:音频header有误/无法进行音频解码"
|
|
||||||
elif error_code == 1013:
|
|
||||||
error_message = "音频静音:音频未识别出任何文本结果"
|
|
||||||
elif error_code >= 1020 and error_code <= 1022:
|
|
||||||
error_message = "识别相关错误:需要重连"
|
|
||||||
if error_code == 1020:
|
|
||||||
error_message = "识别等待超时:等待下一包就绪超时"
|
|
||||||
elif error_code == 1021:
|
|
||||||
error_message = "识别处理超时:识别处理过程超时"
|
|
||||||
elif error_code == 1022:
|
|
||||||
error_message = "识别错误:识别过程中发生错误"
|
|
||||||
else:
|
else:
|
||||||
error_message = "未知错误:未归类错误"
|
pcm_data = self.decode_opus(opus_data)
|
||||||
|
combined_pcm_data = b"".join(pcm_data)
|
||||||
|
|
||||||
logger.bind(tag=TAG).debug(
|
# 判断是否保存为WAV文件
|
||||||
f"ASR错误: {error_message} (错误码: {error_code})"
|
if self.delete_audio_file:
|
||||||
)
|
pass
|
||||||
|
else:
|
||||||
|
file_path = self.save_audio_to_file(pcm_data, session_id)
|
||||||
|
|
||||||
# 如果是识别相关错误,标记需要重连
|
# 直接使用PCM数据
|
||||||
if error_code >= 1020 or error_code == 1001:
|
# 计算分段大小 (单声道, 16bit, 16kHz采样率)
|
||||||
result["need_reconnect"] = True
|
size_per_sec = 1 * 2 * 16000 # nchannels * sampwidth * framerate
|
||||||
|
segment_size = int(size_per_sec * self.seg_duration / 1000)
|
||||||
|
|
||||||
return result
|
# 语音识别
|
||||||
|
start_time = time.time()
|
||||||
async def close_session(self):
|
text = await self._send_request(combined_pcm_data, segment_size)
|
||||||
"""关闭当前会话"""
|
if text:
|
||||||
async with self._session_lock:
|
logger.bind(tag=TAG).debug(
|
||||||
if not self._session_started:
|
f"语音识别耗时: {time.time() - start_time:.3f}s | 结果: {text}"
|
||||||
logger.bind(tag=TAG).warning("尝试关闭未开始的会话")
|
|
||||||
return
|
|
||||||
|
|
||||||
if self._session_finished:
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
f"会话 {self._current_session_id} 已经关闭"
|
|
||||||
)
|
)
|
||||||
return
|
return text, file_path
|
||||||
|
return "", file_path
|
||||||
|
|
||||||
try:
|
except Exception as e:
|
||||||
if self.asr_ws is not None:
|
logger.bind(tag=TAG).error(f"语音识别失败: {e}", exc_info=True)
|
||||||
await self.asr_ws.close()
|
return "", file_path
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).warning(f"关闭WebSocket连接时发生错误: {e}")
|
|
||||||
finally:
|
|
||||||
self.asr_ws = None
|
|
||||||
self._session_finished = True
|
|
||||||
self._session_started = False
|
|
||||||
self._current_session_id = None
|
|
||||||
# 重置重连计数
|
|
||||||
self.reconnect_count = 0
|
|
||||||
|
|
||||||
async def close(self):
|
|
||||||
"""资源清理方法"""
|
|
||||||
await self.close_session()
|
|
||||||
|
|||||||
@@ -0,0 +1,344 @@
|
|||||||
|
import json
|
||||||
|
import gzip
|
||||||
|
import uuid
|
||||||
|
import asyncio
|
||||||
|
import websockets
|
||||||
|
import opuslib_next
|
||||||
|
from core.providers.asr.base import ASRProviderBase
|
||||||
|
from config.logger import setup_logging
|
||||||
|
from core.providers.asr.dto.dto import InterfaceType
|
||||||
|
|
||||||
|
TAG = __name__
|
||||||
|
logger = setup_logging()
|
||||||
|
|
||||||
|
|
||||||
|
class ASRProvider(ASRProviderBase):
|
||||||
|
def __init__(self, config, delete_audio_file):
|
||||||
|
super().__init__()
|
||||||
|
self.interface_type = InterfaceType.STREAM
|
||||||
|
self.config = config
|
||||||
|
self.text = ""
|
||||||
|
self.max_retries = 3
|
||||||
|
self.retry_delay = 2
|
||||||
|
self.decoder = opuslib_next.Decoder(16000, 1)
|
||||||
|
self.asr_ws = None
|
||||||
|
self.forward_task = None
|
||||||
|
self.is_processing = False # 添加处理状态标志
|
||||||
|
|
||||||
|
# 配置参数
|
||||||
|
self.appid = str(config.get("appid"))
|
||||||
|
self.cluster = config.get("cluster")
|
||||||
|
self.access_token = config.get("access_token")
|
||||||
|
self.boosting_table_name = config.get("boosting_table_name", "")
|
||||||
|
self.correct_table_name = config.get("correct_table_name", "")
|
||||||
|
self.output_dir = config.get("output_dir", "tmp/")
|
||||||
|
self.delete_audio_file = delete_audio_file
|
||||||
|
|
||||||
|
# 火山引擎ASR配置
|
||||||
|
self.ws_url = "wss://openspeech.bytedance.com/api/v3/sauc/bigmodel"
|
||||||
|
self.uid = config.get("uid", "streaming_asr_service")
|
||||||
|
self.workflow = config.get(
|
||||||
|
"workflow", "audio_in,resample,partition,vad,fe,decode,itn,nlu_punctuate"
|
||||||
|
)
|
||||||
|
self.result_type = config.get("result_type", "single")
|
||||||
|
self.format = config.get("format", "pcm")
|
||||||
|
self.codec = config.get("codec", "pcm")
|
||||||
|
self.rate = config.get("sample_rate", 16000)
|
||||||
|
self.language = config.get("language", "zh-CN")
|
||||||
|
self.bits = config.get("bits", 16)
|
||||||
|
self.channel = config.get("channel", 1)
|
||||||
|
self.auth_method = config.get("auth_method", "token")
|
||||||
|
self.secret = config.get("secret", "access_secret")
|
||||||
|
|
||||||
|
async def open_audio_channels(self, conn):
|
||||||
|
await super().open_audio_channels(conn)
|
||||||
|
|
||||||
|
async def receive_audio(self, conn, audio, audio_have_voice):
|
||||||
|
conn.asr_audio.append(audio)
|
||||||
|
conn.asr_audio = conn.asr_audio[-10:]
|
||||||
|
|
||||||
|
# 如果本次有声音,且之前没有建立连接
|
||||||
|
if audio_have_voice and self.asr_ws is None and not self.is_processing:
|
||||||
|
try:
|
||||||
|
self.is_processing = True
|
||||||
|
# 建立新的WebSocket连接
|
||||||
|
headers = self.token_auth() if self.auth_method == "token" else None
|
||||||
|
logger.bind(tag=TAG).info(f"正在连接ASR服务,headers: {headers}")
|
||||||
|
|
||||||
|
self.asr_ws = await websockets.connect(
|
||||||
|
self.ws_url,
|
||||||
|
additional_headers=headers,
|
||||||
|
max_size=1000000000,
|
||||||
|
ping_interval=None,
|
||||||
|
ping_timeout=None,
|
||||||
|
close_timeout=10,
|
||||||
|
)
|
||||||
|
|
||||||
|
# 发送初始化请求
|
||||||
|
request_params = self.construct_request(str(uuid.uuid4()))
|
||||||
|
try:
|
||||||
|
payload_bytes = str.encode(json.dumps(request_params))
|
||||||
|
payload_bytes = gzip.compress(payload_bytes)
|
||||||
|
full_client_request = self.generate_header()
|
||||||
|
full_client_request.extend((len(payload_bytes)).to_bytes(4, "big"))
|
||||||
|
full_client_request.extend(payload_bytes)
|
||||||
|
|
||||||
|
logger.bind(tag=TAG).info(f"发送初始化请求: {request_params}")
|
||||||
|
await self.asr_ws.send(full_client_request)
|
||||||
|
|
||||||
|
# 等待初始化响应
|
||||||
|
init_res = await self.asr_ws.recv()
|
||||||
|
result = self.parse_response(init_res)
|
||||||
|
logger.bind(tag=TAG).info(f"收到初始化响应: {result}")
|
||||||
|
|
||||||
|
# 检查初始化响应
|
||||||
|
if "code" in result and result["code"] != 1000:
|
||||||
|
error_msg = f"ASR服务初始化失败: {result.get('payload_msg', {}).get('message', '未知错误')}"
|
||||||
|
if "payload_msg" in result:
|
||||||
|
error_msg += f"\n详细错误信息: {json.dumps(result['payload_msg'], ensure_ascii=False)}"
|
||||||
|
logger.bind(tag=TAG).error(error_msg)
|
||||||
|
raise Exception(error_msg)
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"发送初始化请求失败: {str(e)}")
|
||||||
|
if hasattr(e, "__cause__") and e.__cause__:
|
||||||
|
logger.bind(tag=TAG).error(f"错误原因: {str(e.__cause__)}")
|
||||||
|
raise e
|
||||||
|
|
||||||
|
# 启动接收ASR结果的异步任务
|
||||||
|
self.forward_task = asyncio.create_task(self._forward_asr_results(conn))
|
||||||
|
|
||||||
|
# 发送缓存的音频数据
|
||||||
|
if conn.asr_audio and len(conn.asr_audio) > 0:
|
||||||
|
for cached_audio in conn.asr_audio[-10:]:
|
||||||
|
try:
|
||||||
|
pcm_frame = self.decoder.decode(cached_audio, 960)
|
||||||
|
payload = gzip.compress(pcm_frame)
|
||||||
|
audio_request = bytearray(
|
||||||
|
self.generate_audio_default_header()
|
||||||
|
)
|
||||||
|
audio_request.extend(len(payload).to_bytes(4, "big"))
|
||||||
|
audio_request.extend(payload)
|
||||||
|
await self.asr_ws.send(audio_request)
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).info(
|
||||||
|
f"发送缓存音频数据时发生错误: {e}"
|
||||||
|
)
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"建立ASR连接失败: {str(e)}")
|
||||||
|
if hasattr(e, "__cause__") and e.__cause__:
|
||||||
|
logger.bind(tag=TAG).error(f"错误原因: {str(e.__cause__)}")
|
||||||
|
if self.asr_ws:
|
||||||
|
await self.asr_ws.close()
|
||||||
|
self.asr_ws = None
|
||||||
|
self.is_processing = False
|
||||||
|
return
|
||||||
|
|
||||||
|
# 发送当前音频数据
|
||||||
|
if self.asr_ws and self.is_processing:
|
||||||
|
try:
|
||||||
|
pcm_frame = self.decoder.decode(audio, 960)
|
||||||
|
payload = gzip.compress(pcm_frame)
|
||||||
|
audio_request = bytearray(self.generate_audio_default_header())
|
||||||
|
audio_request.extend(len(payload).to_bytes(4, "big"))
|
||||||
|
audio_request.extend(payload)
|
||||||
|
await self.asr_ws.send(audio_request)
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).info(f"发送音频数据时发生错误: {e}")
|
||||||
|
|
||||||
|
async def _forward_asr_results(self, conn):
|
||||||
|
try:
|
||||||
|
while self.asr_ws and not conn.stop_event.is_set():
|
||||||
|
try:
|
||||||
|
response = await self.asr_ws.recv()
|
||||||
|
result = self.parse_response(response)
|
||||||
|
logger.bind(tag=TAG).debug(f"收到ASR结果: {result}")
|
||||||
|
|
||||||
|
if "payload_msg" in result:
|
||||||
|
payload = result["payload_msg"]
|
||||||
|
if "result" in payload:
|
||||||
|
utterances = payload["result"].get("utterances", [])
|
||||||
|
# 检查duration和空文本的情况
|
||||||
|
if (
|
||||||
|
payload.get("audio_info", {}).get("duration", 0) > 2000
|
||||||
|
and not utterances
|
||||||
|
and not payload["result"].get("text")
|
||||||
|
):
|
||||||
|
logger.bind(tag=TAG).error(f"识别文本:空")
|
||||||
|
self.text = ""
|
||||||
|
conn.reset_vad_states()
|
||||||
|
await self.handle_voice_stop(conn, None)
|
||||||
|
break
|
||||||
|
|
||||||
|
for utterance in utterances:
|
||||||
|
if utterance.get("definite", False):
|
||||||
|
self.text = utterance["text"]
|
||||||
|
logger.bind(tag=TAG).info(
|
||||||
|
f"识别到文本: {self.text}"
|
||||||
|
)
|
||||||
|
conn.reset_vad_states()
|
||||||
|
await self.handle_voice_stop(conn, None)
|
||||||
|
break
|
||||||
|
elif "error" in payload:
|
||||||
|
error_msg = payload.get("error", "未知错误")
|
||||||
|
logger.bind(tag=TAG).error(f"ASR服务返回错误: {error_msg}")
|
||||||
|
break
|
||||||
|
|
||||||
|
except websockets.ConnectionClosed:
|
||||||
|
logger.bind(tag=TAG).info("ASR服务连接已关闭")
|
||||||
|
self.is_processing = False
|
||||||
|
break
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"处理ASR结果时发生错误: {str(e)}")
|
||||||
|
if hasattr(e, "__cause__") and e.__cause__:
|
||||||
|
logger.bind(tag=TAG).error(f"错误原因: {str(e.__cause__)}")
|
||||||
|
self.is_processing = False
|
||||||
|
break
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"ASR结果转发任务发生错误: {str(e)}")
|
||||||
|
if hasattr(e, "__cause__") and e.__cause__:
|
||||||
|
logger.bind(tag=TAG).error(f"错误原因: {str(e.__cause__)}")
|
||||||
|
finally:
|
||||||
|
if self.asr_ws:
|
||||||
|
await self.asr_ws.close()
|
||||||
|
self.asr_ws = None
|
||||||
|
self.is_processing = False
|
||||||
|
|
||||||
|
def stop_ws_connection(self):
|
||||||
|
if self.asr_ws:
|
||||||
|
asyncio.create_task(self.asr_ws.close())
|
||||||
|
self.asr_ws = None
|
||||||
|
self.is_processing = False
|
||||||
|
|
||||||
|
def construct_request(self, reqid):
|
||||||
|
req = {
|
||||||
|
"app": {
|
||||||
|
"appid": self.appid,
|
||||||
|
"cluster": self.cluster,
|
||||||
|
"token": self.access_token,
|
||||||
|
},
|
||||||
|
"user": {"uid": self.uid},
|
||||||
|
"request": {
|
||||||
|
"reqid": reqid,
|
||||||
|
"workflow": self.workflow,
|
||||||
|
"show_utterances": True,
|
||||||
|
"result_type": self.result_type,
|
||||||
|
"sequence": 1,
|
||||||
|
"boosting_table_name": self.boosting_table_name,
|
||||||
|
"correct_table_name": self.correct_table_name,
|
||||||
|
"end_window_size": 200,
|
||||||
|
},
|
||||||
|
"audio": {
|
||||||
|
"format": self.format,
|
||||||
|
"codec": self.codec,
|
||||||
|
"rate": self.rate,
|
||||||
|
"language": self.language,
|
||||||
|
"bits": self.bits,
|
||||||
|
"channel": self.channel,
|
||||||
|
"sample_rate": self.rate,
|
||||||
|
},
|
||||||
|
}
|
||||||
|
logger.bind(tag=TAG).debug(
|
||||||
|
f"构造请求参数: {json.dumps(req, ensure_ascii=False)}"
|
||||||
|
)
|
||||||
|
return req
|
||||||
|
|
||||||
|
def token_auth(self):
|
||||||
|
return {
|
||||||
|
"X-Api-App-Key": self.appid,
|
||||||
|
"X-Api-Access-Key": self.access_token,
|
||||||
|
"X-Api-Resource-Id": "volc.bigasr.sauc.duration",
|
||||||
|
"X-Api-Connect-Id": str(uuid.uuid4()),
|
||||||
|
"Host": "openspeech.bytedance.com",
|
||||||
|
}
|
||||||
|
|
||||||
|
def generate_header(
|
||||||
|
self,
|
||||||
|
version=0x01,
|
||||||
|
message_type=0x01,
|
||||||
|
message_type_specific_flags=0x00,
|
||||||
|
serial_method=0x01,
|
||||||
|
compression_type=0x01,
|
||||||
|
reserved_data=0x00,
|
||||||
|
extension_header: bytes = b"",
|
||||||
|
):
|
||||||
|
header = bytearray()
|
||||||
|
header_size = int(len(extension_header) / 4) + 1
|
||||||
|
header.append((version << 4) | header_size)
|
||||||
|
header.append((message_type << 4) | message_type_specific_flags)
|
||||||
|
header.append((serial_method << 4) | compression_type)
|
||||||
|
header.append(reserved_data)
|
||||||
|
header.extend(extension_header)
|
||||||
|
return header
|
||||||
|
|
||||||
|
def generate_audio_default_header(self):
|
||||||
|
return self.generate_header(
|
||||||
|
version=0x01,
|
||||||
|
message_type=0x02,
|
||||||
|
message_type_specific_flags=0x00,
|
||||||
|
serial_method=0x01,
|
||||||
|
compression_type=0x01,
|
||||||
|
)
|
||||||
|
|
||||||
|
def generate_last_audio_default_header(self):
|
||||||
|
return self.generate_header(
|
||||||
|
version=0x01,
|
||||||
|
message_type=0x02,
|
||||||
|
message_type_specific_flags=0x02,
|
||||||
|
serial_method=0x01,
|
||||||
|
compression_type=0x01,
|
||||||
|
)
|
||||||
|
|
||||||
|
def parse_response(self, res: bytes) -> dict:
|
||||||
|
try:
|
||||||
|
# 检查响应长度
|
||||||
|
if len(res) < 4:
|
||||||
|
logger.bind(tag=TAG).error(f"响应数据长度不足: {len(res)}")
|
||||||
|
return {"error": "响应数据长度不足"}
|
||||||
|
|
||||||
|
# 获取消息头
|
||||||
|
header = res[:4]
|
||||||
|
message_type = header[1] >> 4
|
||||||
|
|
||||||
|
# 如果是错误响应
|
||||||
|
if message_type == 0x0F: # SERVER_ERROR_RESPONSE
|
||||||
|
code = int.from_bytes(header[4:8], "big", signed=False)
|
||||||
|
error_msg = res[8:].decode("utf-8")
|
||||||
|
return {"code": code, "error": error_msg}
|
||||||
|
|
||||||
|
# 获取JSON数据(跳过12字节头部)
|
||||||
|
try:
|
||||||
|
json_data = res[12:].decode("utf-8")
|
||||||
|
result = json.loads(json_data)
|
||||||
|
logger.bind(tag=TAG).debug(f"成功解析JSON响应: {result}")
|
||||||
|
return {"payload_msg": result}
|
||||||
|
except (UnicodeDecodeError, json.JSONDecodeError) as e:
|
||||||
|
logger.bind(tag=TAG).error(f"JSON解析失败: {str(e)}")
|
||||||
|
logger.bind(tag=TAG).error(f"原始数据: {res}")
|
||||||
|
raise
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"解析响应失败: {str(e)}")
|
||||||
|
logger.bind(tag=TAG).error(f"原始响应数据: {res.hex()}")
|
||||||
|
raise
|
||||||
|
|
||||||
|
async def speech_to_text(self, opus_data, session_id, audio_format):
|
||||||
|
result = self.text
|
||||||
|
self.text = "" # 清空text
|
||||||
|
return result, None
|
||||||
|
|
||||||
|
async def close(self):
|
||||||
|
"""资源清理方法"""
|
||||||
|
if self.asr_ws:
|
||||||
|
await self.asr_ws.close()
|
||||||
|
self.asr_ws = None
|
||||||
|
if self.forward_task:
|
||||||
|
self.forward_task.cancel()
|
||||||
|
try:
|
||||||
|
await self.forward_task
|
||||||
|
except asyncio.CancelledError:
|
||||||
|
pass
|
||||||
|
self.forward_task = None
|
||||||
|
self.is_processing = False
|
||||||
@@ -54,7 +54,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
)
|
)
|
||||||
|
|
||||||
async def speech_to_text(
|
async def speech_to_text(
|
||||||
self, opus_data: List[bytes], session_id: str
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
) -> Tuple[Optional[str], Optional[str]]:
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
"""语音转文本主处理逻辑"""
|
"""语音转文本主处理逻辑"""
|
||||||
file_path = None
|
file_path = None
|
||||||
@@ -63,7 +63,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
while retry_count < MAX_RETRIES:
|
while retry_count < MAX_RETRIES:
|
||||||
try:
|
try:
|
||||||
# 合并所有opus数据包
|
# 合并所有opus数据包
|
||||||
if self.audio_format == "pcm":
|
if audio_format == "pcm":
|
||||||
pcm_data = opus_data
|
pcm_data = opus_data
|
||||||
else:
|
else:
|
||||||
pcm_data = self.decode_opus(opus_data)
|
pcm_data = self.decode_opus(opus_data)
|
||||||
|
|||||||
@@ -100,7 +100,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
logger.bind(tag=TAG).debug(f"Sent end message: {end_message}")
|
logger.bind(tag=TAG).debug(f"Sent end message: {end_message}")
|
||||||
|
|
||||||
async def speech_to_text(
|
async def speech_to_text(
|
||||||
self, opus_data: List[bytes], session_id: str
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
) -> Tuple[Optional[str], Optional[str]]:
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
"""
|
"""
|
||||||
Convert speech data to text using FunASR.
|
Convert speech data to text using FunASR.
|
||||||
@@ -109,7 +109,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
:return: Tuple containing recognized text and optional timestamp.
|
:return: Tuple containing recognized text and optional timestamp.
|
||||||
"""
|
"""
|
||||||
file_path = None
|
file_path = None
|
||||||
if self.audio_format == "pcm":
|
if audio_format == "pcm":
|
||||||
pcm_data = opus_data
|
pcm_data = opus_data
|
||||||
else:
|
else:
|
||||||
pcm_data = self.decode_opus(opus_data)
|
pcm_data = self.decode_opus(opus_data)
|
||||||
|
|||||||
@@ -109,14 +109,14 @@ class ASRProvider(ASRProviderBase):
|
|||||||
return samples_float32, f.getframerate()
|
return samples_float32, f.getframerate()
|
||||||
|
|
||||||
async def speech_to_text(
|
async def speech_to_text(
|
||||||
self, opus_data: List[bytes], session_id: str
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
) -> Tuple[Optional[str], Optional[str]]:
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
"""语音转文本主处理逻辑"""
|
"""语音转文本主处理逻辑"""
|
||||||
file_path = None
|
file_path = None
|
||||||
try:
|
try:
|
||||||
# 保存音频文件
|
# 保存音频文件
|
||||||
start_time = time.time()
|
start_time = time.time()
|
||||||
if self.audio_format == "pcm":
|
if audio_format == "pcm":
|
||||||
pcm_data = opus_data
|
pcm_data = opus_data
|
||||||
else:
|
else:
|
||||||
pcm_data = self.decode_opus(opus_data)
|
pcm_data = self.decode_opus(opus_data)
|
||||||
|
|||||||
@@ -32,7 +32,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
os.makedirs(self.output_dir, exist_ok=True)
|
os.makedirs(self.output_dir, exist_ok=True)
|
||||||
|
|
||||||
async def speech_to_text(
|
async def speech_to_text(
|
||||||
self, opus_data: List[bytes], session_id: str
|
self, opus_data: List[bytes], session_id: str, audio_format="opus"
|
||||||
) -> Tuple[Optional[str], Optional[str]]:
|
) -> Tuple[Optional[str], Optional[str]]:
|
||||||
"""将语音数据转换为文本"""
|
"""将语音数据转换为文本"""
|
||||||
if not opus_data:
|
if not opus_data:
|
||||||
@@ -47,7 +47,7 @@ class ASRProvider(ASRProviderBase):
|
|||||||
return None, file_path
|
return None, file_path
|
||||||
|
|
||||||
# 将Opus音频数据解码为PCM
|
# 将Opus音频数据解码为PCM
|
||||||
if self.audio_format == "pcm":
|
if audio_format == "pcm":
|
||||||
pcm_data = opus_data
|
pcm_data = opus_data
|
||||||
else:
|
else:
|
||||||
pcm_data = self.decode_opus(opus_data)
|
pcm_data = self.decode_opus(opus_data)
|
||||||
|
|||||||
@@ -122,6 +122,8 @@ class IntentProvider(IntentProviderBase):
|
|||||||
async def detect_intent(self, conn, dialogue_history: List[Dict], text: str) -> str:
|
async def detect_intent(self, conn, dialogue_history: List[Dict], text: str) -> str:
|
||||||
if not self.llm:
|
if not self.llm:
|
||||||
raise ValueError("LLM provider not set")
|
raise ValueError("LLM provider not set")
|
||||||
|
if conn.func_handler is None:
|
||||||
|
return '{"function_call": {"name": "continue_chat"}}'
|
||||||
|
|
||||||
# 记录整体开始时间
|
# 记录整体开始时间
|
||||||
total_start_time = time.time()
|
total_start_time = time.time()
|
||||||
@@ -148,9 +150,8 @@ class IntentProvider(IntentProviderBase):
|
|||||||
self.clean_cache()
|
self.clean_cache()
|
||||||
|
|
||||||
if self.promot == "":
|
if self.promot == "":
|
||||||
if hasattr(conn, "func_handler"):
|
functions = conn.func_handler.get_functions()
|
||||||
functions = conn.func_handler.get_functions()
|
self.promot = self.get_intent_system_prompt(functions)
|
||||||
self.promot = self.get_intent_system_prompt(functions)
|
|
||||||
|
|
||||||
music_config = initialize_music_handler(conn)
|
music_config = initialize_music_handler(conn)
|
||||||
music_file_names = music_config["music_file_names"]
|
music_file_names = music_config["music_file_names"]
|
||||||
|
|||||||
@@ -52,6 +52,7 @@ class TTSProviderBase(ABC):
|
|||||||
)
|
)
|
||||||
self.first_sentence_punctuations = (
|
self.first_sentence_punctuations = (
|
||||||
",",
|
",",
|
||||||
|
"~",
|
||||||
"~",
|
"~",
|
||||||
"、",
|
"、",
|
||||||
",",
|
",",
|
||||||
@@ -178,6 +179,9 @@ class TTSProviderBase(ABC):
|
|||||||
while not self.conn.stop_event.is_set():
|
while not self.conn.stop_event.is_set():
|
||||||
try:
|
try:
|
||||||
message = self.tts_text_queue.get(timeout=1)
|
message = self.tts_text_queue.get(timeout=1)
|
||||||
|
if self.conn.client_abort:
|
||||||
|
logger.bind(tag=TAG).info("收到打断信息,终止TTS文本处理线程")
|
||||||
|
continue
|
||||||
if message.sentence_type == SentenceType.FIRST:
|
if message.sentence_type == SentenceType.FIRST:
|
||||||
# 初始化参数
|
# 初始化参数
|
||||||
self.tts_stop_request = False
|
self.tts_stop_request = False
|
||||||
|
|||||||
@@ -3,14 +3,13 @@ import uuid
|
|||||||
import json
|
import json
|
||||||
import queue
|
import queue
|
||||||
import asyncio
|
import asyncio
|
||||||
import threading
|
|
||||||
import traceback
|
import traceback
|
||||||
import websockets
|
import websockets
|
||||||
import time
|
|
||||||
from config.logger import setup_logging
|
from config.logger import setup_logging
|
||||||
from core.utils import opus_encoder_utils
|
from core.utils import opus_encoder_utils
|
||||||
from core.utils.util import check_model_key
|
from core.utils.util import check_model_key
|
||||||
from core.providers.tts.base import TTSProviderBase
|
from core.providers.tts.base import TTSProviderBase
|
||||||
|
from core.handle.abortHandle import handleAbortMessage
|
||||||
from core.providers.tts.dto.dto import SentenceType, ContentType, InterfaceType
|
from core.providers.tts.dto.dto import SentenceType, ContentType, InterfaceType
|
||||||
|
|
||||||
TAG = __name__
|
TAG = __name__
|
||||||
@@ -139,7 +138,7 @@ class Response:
|
|||||||
class TTSProvider(TTSProviderBase):
|
class TTSProvider(TTSProviderBase):
|
||||||
def __init__(self, config, delete_audio_file):
|
def __init__(self, config, delete_audio_file):
|
||||||
super().__init__(config, delete_audio_file)
|
super().__init__(config, delete_audio_file)
|
||||||
self.ws = None # 初始化ws属性
|
self.ws = None
|
||||||
self.interface_type = InterfaceType.DUAL_STREAM
|
self.interface_type = InterfaceType.DUAL_STREAM
|
||||||
self.appId = config.get("appid")
|
self.appId = config.get("appid")
|
||||||
self.access_token = config.get("access_token")
|
self.access_token = config.get("access_token")
|
||||||
@@ -154,91 +153,55 @@ class TTSProvider(TTSProviderBase):
|
|||||||
self.authorization = config.get("authorization")
|
self.authorization = config.get("authorization")
|
||||||
self.header = {"Authorization": f"{self.authorization}{self.access_token}"}
|
self.header = {"Authorization": f"{self.authorization}{self.access_token}"}
|
||||||
self.enable_two_way = True
|
self.enable_two_way = True
|
||||||
self.start_connection_flag = False
|
|
||||||
self.tts_text = ""
|
self.tts_text = ""
|
||||||
# 合成文字语音后,播放的音频文件列表
|
|
||||||
self.before_stop_play_files = []
|
self.before_stop_play_files = []
|
||||||
self.opus_encoder = opus_encoder_utils.OpusEncoderUtils(
|
self.opus_encoder = opus_encoder_utils.OpusEncoderUtils(
|
||||||
sample_rate=16000, channels=1, frame_size_ms=60
|
sample_rate=16000, channels=1, frame_size_ms=60
|
||||||
)
|
)
|
||||||
check_model_key("TTS", self.access_token)
|
check_model_key("TTS", self.access_token)
|
||||||
|
|
||||||
# 添加会话状态控制
|
|
||||||
self._session_lock = asyncio.Lock() # 会话操作的并发锁
|
|
||||||
self._current_session_id = None # 当前会话ID
|
|
||||||
self._session_started = False # 会话是否已开始
|
|
||||||
self._session_finished = False # 会话是否已结束
|
|
||||||
self._connection_ready = False # 连接是否就绪
|
|
||||||
self._reconnect_attempts = 0 # 重连尝试次数
|
|
||||||
self._max_reconnect_attempts = 3 # 最大重连次数
|
|
||||||
|
|
||||||
###################################################################################
|
|
||||||
# 火山双流式TTS重写父类的方法--开始
|
|
||||||
###################################################################################
|
|
||||||
|
|
||||||
async def open_audio_channels(self, conn):
|
async def open_audio_channels(self, conn):
|
||||||
try:
|
try:
|
||||||
await super().open_audio_channels(conn)
|
await super().open_audio_channels(conn)
|
||||||
await self._ensure_connection()
|
|
||||||
tts_priority = threading.Thread(
|
|
||||||
target=self._start_monitor_tts_response_thread, daemon=True
|
|
||||||
)
|
|
||||||
tts_priority.start()
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.bind(tag=TAG).error(f"Failed to open audio channels: {str(e)}")
|
logger.bind(tag=TAG).error(f"Failed to open audio channels: {str(e)}")
|
||||||
self.ws = None
|
self.ws = None
|
||||||
raise
|
raise
|
||||||
|
|
||||||
async def _ensure_connection(self):
|
async def _ensure_connection(self):
|
||||||
"""确保WebSocket连接可用"""
|
"""建立新的WebSocket连接"""
|
||||||
try:
|
try:
|
||||||
if self.ws is None:
|
logger.bind(tag=TAG).info("开始建立新连接...")
|
||||||
logger.bind(tag=TAG).info("WebSocket连接不存在,开始建立新连接...")
|
ws_header = {
|
||||||
ws_header = {
|
"X-Api-App-Key": self.appId,
|
||||||
"X-Api-App-Key": self.appId,
|
"X-Api-Access-Key": self.access_token,
|
||||||
"X-Api-Access-Key": self.access_token,
|
"X-Api-Resource-Id": self.resource_id,
|
||||||
"X-Api-Resource-Id": self.resource_id,
|
"X-Api-Connect-Id": uuid.uuid4(),
|
||||||
"X-Api-Connect-Id": uuid.uuid4(),
|
}
|
||||||
}
|
self.ws = await websockets.connect(
|
||||||
self.ws = await websockets.connect(
|
self.ws_url, additional_headers=ws_header, max_size=1000000000
|
||||||
self.ws_url, additional_headers=ws_header, max_size=1000000000
|
)
|
||||||
)
|
logger.bind(tag=TAG).info("WebSocket连接建立成功")
|
||||||
self._connection_ready = True
|
return self.ws
|
||||||
self._reconnect_attempts = 0
|
|
||||||
logger.bind(tag=TAG).info("WebSocket连接建立成功")
|
|
||||||
else:
|
|
||||||
# 尝试发送ping来检查连接是否还活着
|
|
||||||
try:
|
|
||||||
logger.bind(tag=TAG).debug("检查WebSocket连接状态...")
|
|
||||||
pong_waiter = await self.ws.ping()
|
|
||||||
await asyncio.wait_for(pong_waiter, timeout=1.0)
|
|
||||||
logger.bind(tag=TAG).debug("WebSocket连接状态正常")
|
|
||||||
except (asyncio.TimeoutError, websockets.ConnectionClosed):
|
|
||||||
# 如果ping失败,重新建立连接
|
|
||||||
logger.bind(tag=TAG).warning("WebSocket连接已断开,准备重新连接...")
|
|
||||||
try:
|
|
||||||
await self.ws.close()
|
|
||||||
except:
|
|
||||||
pass
|
|
||||||
self.ws = None
|
|
||||||
self._connection_ready = False
|
|
||||||
# 重新建立连接
|
|
||||||
await self._ensure_connection()
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.bind(tag=TAG).error(f"确保连接失败: {str(e)}")
|
logger.bind(tag=TAG).error(f"建立连接失败: {str(e)}")
|
||||||
self._connection_ready = False
|
|
||||||
self.ws = None
|
self.ws = None
|
||||||
raise
|
raise
|
||||||
|
|
||||||
def tts_text_priority_thread(self):
|
def tts_text_priority_thread(self):
|
||||||
|
"""火山引擎双流式TTS的文本处理线程"""
|
||||||
logger.bind(tag=TAG).info("TTS文本处理线程启动")
|
logger.bind(tag=TAG).info("TTS文本处理线程启动")
|
||||||
while not self.conn.stop_event.is_set():
|
while not self.conn.stop_event.is_set():
|
||||||
try:
|
try:
|
||||||
logger.bind(tag=TAG).debug("等待TTS文本队列消息...")
|
logger.bind(tag=TAG).debug("等待TTS文本队列消息...")
|
||||||
message = self.tts_text_queue.get(timeout=1)
|
message = self.tts_text_queue.get(timeout=1)
|
||||||
logger.bind(tag=TAG).info(
|
logger.bind(tag=TAG).debug(
|
||||||
f"收到TTS任务|{message.sentence_type.name} | {message.content_type.name} | 会话ID: {self.conn.sentence_id}"
|
f"收到TTS任务|{message.sentence_type.name} | {message.content_type.name} | 会话ID: {self.conn.sentence_id}"
|
||||||
)
|
)
|
||||||
|
if self.conn.client_abort:
|
||||||
|
logger.bind(tag=TAG).info("收到打断信息,终止TTS文本处理线程")
|
||||||
|
continue
|
||||||
|
|
||||||
if message.sentence_type == SentenceType.FIRST:
|
if message.sentence_type == SentenceType.FIRST:
|
||||||
# 初始化参数
|
# 初始化参数
|
||||||
try:
|
try:
|
||||||
@@ -253,13 +216,12 @@ class TTSProvider(TTSProviderBase):
|
|||||||
logger.bind(tag=TAG).info("TTS会话启动成功")
|
logger.bind(tag=TAG).info("TTS会话启动成功")
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.bind(tag=TAG).error(f"启动TTS会话失败: {str(e)}")
|
logger.bind(tag=TAG).error(f"启动TTS会话失败: {str(e)}")
|
||||||
# 直接跳过当前消息,不重新入队
|
|
||||||
time.sleep(1)
|
|
||||||
continue
|
continue
|
||||||
|
|
||||||
elif ContentType.TEXT == message.content_type:
|
elif ContentType.TEXT == message.content_type:
|
||||||
if message.content_detail:
|
if message.content_detail:
|
||||||
try:
|
try:
|
||||||
logger.bind(tag=TAG).info(
|
logger.bind(tag=TAG).debug(
|
||||||
f"开始发送TTS文本: {message.content_detail}"
|
f"开始发送TTS文本: {message.content_detail}"
|
||||||
)
|
)
|
||||||
future = asyncio.run_coroutine_threadsafe(
|
future = asyncio.run_coroutine_threadsafe(
|
||||||
@@ -267,12 +229,11 @@ class TTSProvider(TTSProviderBase):
|
|||||||
loop=self.conn.loop,
|
loop=self.conn.loop,
|
||||||
)
|
)
|
||||||
future.result()
|
future.result()
|
||||||
logger.bind(tag=TAG).info("TTS文本发送成功")
|
logger.bind(tag=TAG).debug("TTS文本发送成功")
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.bind(tag=TAG).error(f"发送TTS文本失败: {str(e)}")
|
logger.bind(tag=TAG).error(f"发送TTS文本失败: {str(e)}")
|
||||||
# 直接跳过当前消息,不重新入队
|
|
||||||
time.sleep(1)
|
|
||||||
continue
|
continue
|
||||||
|
|
||||||
elif ContentType.FILE == message.content_type:
|
elif ContentType.FILE == message.content_type:
|
||||||
logger.bind(tag=TAG).info(
|
logger.bind(tag=TAG).info(
|
||||||
f"添加音频文件到待播放列表: {message.content_file}"
|
f"添加音频文件到待播放列表: {message.content_file}"
|
||||||
@@ -289,11 +250,8 @@ class TTSProvider(TTSProviderBase):
|
|||||||
loop=self.conn.loop,
|
loop=self.conn.loop,
|
||||||
)
|
)
|
||||||
future.result()
|
future.result()
|
||||||
logger.bind(tag=TAG).info("TTS会话结束成功")
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.bind(tag=TAG).error(f"结束TTS会话失败: {str(e)}")
|
logger.bind(tag=TAG).error(f"结束TTS会话失败: {str(e)}")
|
||||||
# 直接跳过当前消息,不重新入队
|
|
||||||
time.sleep(1)
|
|
||||||
continue
|
continue
|
||||||
|
|
||||||
except queue.Empty:
|
except queue.Empty:
|
||||||
@@ -302,103 +260,204 @@ class TTSProvider(TTSProviderBase):
|
|||||||
logger.bind(tag=TAG).error(
|
logger.bind(tag=TAG).error(
|
||||||
f"处理TTS文本失败: {str(e)}, 类型: {type(e).__name__}, 堆栈: {traceback.format_exc()}"
|
f"处理TTS文本失败: {str(e)}, 类型: {type(e).__name__}, 堆栈: {traceback.format_exc()}"
|
||||||
)
|
)
|
||||||
# 如果是WebSocket连接关闭错误,等待一段时间后继续
|
|
||||||
if "non-exist session" in str(e):
|
|
||||||
time.sleep(1)
|
|
||||||
continue
|
continue
|
||||||
|
|
||||||
async def text_to_speak(self, text, _):
|
async def text_to_speak(self, text, _):
|
||||||
"""发送文本到TTS服务"""
|
"""发送文本到TTS服务"""
|
||||||
try:
|
try:
|
||||||
# 确保WebSocket连接可用
|
# 建立新连接
|
||||||
if not self._connection_ready or self.ws is None:
|
if self.ws is None:
|
||||||
logger.bind(tag=TAG).warning("WebSocket连接不可用,尝试重新连接...")
|
await handleAbortMessage(self.conn)
|
||||||
await self._ensure_connection()
|
logger.bind(tag=TAG).error(f"WebSocket连接不存在,终止发送文本")
|
||||||
|
return
|
||||||
# 发送文本
|
# 发送文本
|
||||||
await self.send_text(self.speaker, text, self.conn.sentence_id)
|
await self.send_text(self.speaker, text, self.conn.sentence_id)
|
||||||
return
|
return
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.bind(tag=TAG).error(f"发送TTS文本失败: {str(e)}")
|
logger.bind(tag=TAG).error(f"发送TTS文本失败: {str(e)}")
|
||||||
# 如果是连接问题,尝试重新连接
|
if self.ws:
|
||||||
if isinstance(e, websockets.ConnectionClosed):
|
try:
|
||||||
self._connection_ready = False
|
await self.ws.close()
|
||||||
|
except:
|
||||||
|
pass
|
||||||
self.ws = None
|
self.ws = None
|
||||||
await self._handle_connection_error()
|
|
||||||
raise
|
raise
|
||||||
|
|
||||||
###################################################################################
|
async def start_session(self, session_id):
|
||||||
# 火山双流式TTS重写父类的方法--结束
|
logger.bind(tag=TAG).info(f"开始会话~~{session_id}")
|
||||||
###################################################################################
|
try:
|
||||||
def _start_monitor_tts_response_thread(self):
|
# 建立新连接
|
||||||
# 初始化链接
|
await self._ensure_connection()
|
||||||
asyncio.run_coroutine_threadsafe(
|
|
||||||
self._start_monitor_tts_response(), loop=self.conn.loop
|
# 启动监听任务
|
||||||
)
|
self._monitor_task = asyncio.create_task(self._start_monitor_tts_response())
|
||||||
|
|
||||||
|
header = Header(
|
||||||
|
message_type=FULL_CLIENT_REQUEST,
|
||||||
|
message_type_specific_flags=MsgTypeFlagWithEvent,
|
||||||
|
serial_method=JSON,
|
||||||
|
).as_bytes()
|
||||||
|
optional = Optional(
|
||||||
|
event=EVENT_StartSession, sessionId=session_id
|
||||||
|
).as_bytes()
|
||||||
|
payload = self.get_payload_bytes(
|
||||||
|
event=EVENT_StartSession, speaker=self.speaker
|
||||||
|
)
|
||||||
|
await self.send_event(header, optional, payload)
|
||||||
|
logger.bind(tag=TAG).info("会话启动请求已发送")
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"启动会话失败: {str(e)}")
|
||||||
|
# 确保清理资源
|
||||||
|
if hasattr(self, "_monitor_task"):
|
||||||
|
try:
|
||||||
|
self._monitor_task.cancel()
|
||||||
|
await self._monitor_task
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
self._monitor_task = None
|
||||||
|
if self.ws:
|
||||||
|
try:
|
||||||
|
await self.ws.close()
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
self.ws = None
|
||||||
|
raise
|
||||||
|
|
||||||
|
async def finish_session(self, session_id):
|
||||||
|
logger.bind(tag=TAG).info(f"关闭会话~~{session_id}")
|
||||||
|
try:
|
||||||
|
if self.ws:
|
||||||
|
header = Header(
|
||||||
|
message_type=FULL_CLIENT_REQUEST,
|
||||||
|
message_type_specific_flags=MsgTypeFlagWithEvent,
|
||||||
|
serial_method=JSON,
|
||||||
|
).as_bytes()
|
||||||
|
optional = Optional(
|
||||||
|
event=EVENT_FinishSession, sessionId=session_id
|
||||||
|
).as_bytes()
|
||||||
|
payload = str.encode("{}")
|
||||||
|
await self.send_event(header, optional, payload)
|
||||||
|
logger.bind(tag=TAG).info("会话结束请求已发送")
|
||||||
|
|
||||||
|
# 等待监听任务完成
|
||||||
|
if hasattr(self, "_monitor_task"):
|
||||||
|
try:
|
||||||
|
await self._monitor_task
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(
|
||||||
|
f"等待监听任务完成时发生错误: {str(e)}"
|
||||||
|
)
|
||||||
|
finally:
|
||||||
|
self._monitor_task = None
|
||||||
|
|
||||||
|
# 关闭连接
|
||||||
|
await self.close()
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"关闭会话失败: {str(e)}")
|
||||||
|
# 确保清理资源
|
||||||
|
if hasattr(self, "_monitor_task"):
|
||||||
|
try:
|
||||||
|
self._monitor_task.cancel()
|
||||||
|
await self._monitor_task
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
self._monitor_task = None
|
||||||
|
if self.ws:
|
||||||
|
try:
|
||||||
|
await self.ws.close()
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
self.ws = None
|
||||||
|
raise
|
||||||
|
|
||||||
|
async def close(self):
|
||||||
|
"""资源清理方法"""
|
||||||
|
if self.ws:
|
||||||
|
try:
|
||||||
|
await self.ws.close()
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
self.ws = None
|
||||||
|
|
||||||
async def _start_monitor_tts_response(self):
|
async def _start_monitor_tts_response(self):
|
||||||
|
"""监听TTS响应"""
|
||||||
opus_datas_cache = []
|
opus_datas_cache = []
|
||||||
# 添加标志来区分是否是第一句话
|
|
||||||
is_first_sentence = True
|
is_first_sentence = True
|
||||||
while not self.conn.stop_event.is_set():
|
try:
|
||||||
try:
|
while not self.conn.stop_event.is_set():
|
||||||
# 确保 `recv()` 运行在同一个 event loop
|
try:
|
||||||
msg = await self.ws.recv()
|
# 确保 `recv()` 运行在同一个 event loop
|
||||||
res = self.parser_response(msg)
|
msg = await self.ws.recv()
|
||||||
self.print_response(res, "send_text res:")
|
res = self.parser_response(msg)
|
||||||
|
self.print_response(res, "send_text res:")
|
||||||
|
|
||||||
if res.optional.event == EVENT_TTSSentenceStart:
|
# 检查客户端是否中止
|
||||||
json_data = json.loads(res.payload.decode("utf-8"))
|
if self.conn.client_abort:
|
||||||
self.tts_text = json_data.get("text", "")
|
logger.bind(tag=TAG).info("收到打断信息,终止监听TTS响应")
|
||||||
logger.bind(tag=TAG).debug(f"句子语音生成开始: {self.tts_text}")
|
break
|
||||||
self.tts_audio_queue.put((SentenceType.FIRST, [], self.tts_text))
|
|
||||||
opus_datas_cache = []
|
if res.optional.event == EVENT_TTSSentenceStart:
|
||||||
elif (
|
json_data = json.loads(res.payload.decode("utf-8"))
|
||||||
res.optional.event == EVENT_TTSResponse
|
self.tts_text = json_data.get("text", "")
|
||||||
and res.header.message_type == AUDIO_ONLY_RESPONSE
|
logger.bind(tag=TAG).debug(f"句子语音生成开始: {self.tts_text}")
|
||||||
):
|
|
||||||
logger.bind(tag=TAG).debug(f"推送数据到队列里面~~")
|
|
||||||
opus_datas = self.wav_to_opus_data_audio_raw(res.payload)
|
|
||||||
logger.bind(tag=TAG).debug(
|
|
||||||
f"推送数据到队列里面帧数~~{len(opus_datas)}"
|
|
||||||
)
|
|
||||||
if is_first_sentence:
|
|
||||||
# 第一句话直接发送
|
|
||||||
self.tts_audio_queue.put(
|
self.tts_audio_queue.put(
|
||||||
(SentenceType.MIDDLE, opus_datas, self.tts_text)
|
(SentenceType.FIRST, [], self.tts_text)
|
||||||
)
|
)
|
||||||
else:
|
opus_datas_cache = []
|
||||||
# 后续句子缓存
|
elif (
|
||||||
opus_datas_cache = opus_datas_cache + opus_datas
|
res.optional.event == EVENT_TTSResponse
|
||||||
elif res.optional.event == EVENT_TTSSentenceEnd:
|
and res.header.message_type == AUDIO_ONLY_RESPONSE
|
||||||
logger.bind(tag=TAG).info(f"句子语音生成成功:{self.tts_text}")
|
):
|
||||||
if not is_first_sentence:
|
logger.bind(tag=TAG).debug(f"推送数据到队列里面~~")
|
||||||
# 只有非第一句话才发送缓存的数据
|
opus_datas = self.wav_to_opus_data_audio_raw(res.payload)
|
||||||
self.tts_audio_queue.put(
|
logger.bind(tag=TAG).debug(
|
||||||
(SentenceType.MIDDLE, opus_datas_cache, self.tts_text)
|
f"推送数据到队列里面帧数~~{len(opus_datas)}"
|
||||||
)
|
)
|
||||||
# 第一句话结束后,将标志设置为False
|
if is_first_sentence:
|
||||||
is_first_sentence = False
|
# 第一句话直接发送
|
||||||
elif res.optional.event == EVENT_SessionFinished:
|
|
||||||
logger.bind(tag=TAG).debug(f"会话结束~~")
|
|
||||||
for tts_file, text in self.before_stop_play_files:
|
|
||||||
if tts_file and os.path.exists(tts_file):
|
|
||||||
audio_datas = self._process_audio_file(tts_file)
|
|
||||||
self.tts_audio_queue.put(
|
self.tts_audio_queue.put(
|
||||||
(SentenceType.MIDDLE, audio_datas, text)
|
(SentenceType.MIDDLE, opus_datas, self.tts_text)
|
||||||
)
|
)
|
||||||
self.before_stop_play_files.clear()
|
else:
|
||||||
self.tts_audio_queue.put((SentenceType.LAST, [], None))
|
# 后续句子缓存
|
||||||
|
opus_datas_cache = opus_datas_cache + opus_datas
|
||||||
opus_datas_cache = []
|
elif res.optional.event == EVENT_TTSSentenceEnd:
|
||||||
is_first_sentence = True
|
logger.bind(tag=TAG).info(f"句子语音生成成功:{self.tts_text}")
|
||||||
continue
|
if not is_first_sentence:
|
||||||
except websockets.ConnectionClosed:
|
# 只有非第一句话才发送缓存的数据
|
||||||
break # 连接关闭时退出监听
|
self.tts_audio_queue.put(
|
||||||
except Exception as e:
|
(SentenceType.MIDDLE, opus_datas_cache, self.tts_text)
|
||||||
logger.bind(tag=TAG).error(f"Error in _start_monitor_tts_response: {e}")
|
)
|
||||||
traceback.print_exc()
|
# 第一句话结束后,将标志设置为False
|
||||||
continue
|
is_first_sentence = False
|
||||||
|
elif res.optional.event == EVENT_SessionFinished:
|
||||||
|
logger.bind(tag=TAG).debug(f"会话结束~~")
|
||||||
|
for tts_file, text in self.before_stop_play_files:
|
||||||
|
if tts_file and os.path.exists(tts_file):
|
||||||
|
audio_datas = self._process_audio_file(tts_file)
|
||||||
|
self.tts_audio_queue.put(
|
||||||
|
(SentenceType.MIDDLE, audio_datas, text)
|
||||||
|
)
|
||||||
|
self.before_stop_play_files.clear()
|
||||||
|
self.tts_audio_queue.put((SentenceType.LAST, [], None))
|
||||||
|
break
|
||||||
|
except websockets.ConnectionClosed:
|
||||||
|
logger.bind(tag=TAG).warning("WebSocket连接已关闭")
|
||||||
|
break
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(
|
||||||
|
f"Error in _start_monitor_tts_response: {e}"
|
||||||
|
)
|
||||||
|
traceback.print_exc()
|
||||||
|
break
|
||||||
|
finally:
|
||||||
|
# 确保清理资源
|
||||||
|
if self.ws:
|
||||||
|
try:
|
||||||
|
await self.ws.close()
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
self.ws = None
|
||||||
|
|
||||||
async def send_event(
|
async def send_event(
|
||||||
self, header: bytes, optional: bytes | None = None, payload: bytes = None
|
self, header: bytes, optional: bytes | None = None, payload: bytes = None
|
||||||
@@ -413,11 +472,8 @@ class TTSProvider(TTSProviderBase):
|
|||||||
full_client_request.extend(payload)
|
full_client_request.extend(payload)
|
||||||
await self.ws.send(full_client_request)
|
await self.ws.send(full_client_request)
|
||||||
except websockets.ConnectionClosed:
|
except websockets.ConnectionClosed:
|
||||||
if await self._handle_connection_error():
|
logger.bind(tag=TAG).error(f"ConnectionClosed")
|
||||||
# 重连成功后重试发送
|
raise
|
||||||
await self.ws.send(full_client_request)
|
|
||||||
else:
|
|
||||||
raise
|
|
||||||
|
|
||||||
async def send_text(self, speaker: str, text: str, session_id):
|
async def send_text(self, speaker: str, text: str, session_id):
|
||||||
header = Header(
|
header = Header(
|
||||||
@@ -540,200 +596,6 @@ class TTSProvider(TTSProviderBase):
|
|||||||
)
|
)
|
||||||
)
|
)
|
||||||
|
|
||||||
async def finish_connection(self):
|
|
||||||
header = Header(
|
|
||||||
message_type=FULL_CLIENT_REQUEST,
|
|
||||||
message_type_specific_flags=MsgTypeFlagWithEvent,
|
|
||||||
serial_method=JSON,
|
|
||||||
).as_bytes()
|
|
||||||
optional = Optional(event=EVENT_FinishConnection).as_bytes()
|
|
||||||
payload = str.encode("{}")
|
|
||||||
await self.send_event(header, optional, payload)
|
|
||||||
return
|
|
||||||
|
|
||||||
async def start_session(self, session_id):
|
|
||||||
logger.bind(tag=TAG).info(f"开始会话~~{session_id}")
|
|
||||||
try:
|
|
||||||
async with self._session_lock:
|
|
||||||
try:
|
|
||||||
# 确保连接可用
|
|
||||||
logger.bind(tag=TAG).info("检查WebSocket连接状态...")
|
|
||||||
await asyncio.wait_for(self._ensure_connection(), timeout=5)
|
|
||||||
|
|
||||||
# 如果已有会话未结束,先关闭它
|
|
||||||
if self._session_started and not self._session_finished:
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
f"发现未关闭的会话 {self._current_session_id},正在关闭..."
|
|
||||||
)
|
|
||||||
try:
|
|
||||||
await asyncio.wait_for(
|
|
||||||
self.finish_session(self._current_session_id), timeout=5
|
|
||||||
)
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"关闭旧会话失败: {str(e)}")
|
|
||||||
# 强制重置会话状态
|
|
||||||
self._session_started = False
|
|
||||||
self._session_finished = True
|
|
||||||
self._current_session_id = None
|
|
||||||
|
|
||||||
# 重置会话状态
|
|
||||||
self._current_session_id = session_id
|
|
||||||
self._session_started = True
|
|
||||||
self._session_finished = False
|
|
||||||
logger.bind(tag=TAG).info(
|
|
||||||
f"会话状态已更新 - 开始: {self._session_started}, 结束: {self._session_finished}"
|
|
||||||
)
|
|
||||||
|
|
||||||
header = Header(
|
|
||||||
message_type=FULL_CLIENT_REQUEST,
|
|
||||||
message_type_specific_flags=MsgTypeFlagWithEvent,
|
|
||||||
serial_method=JSON,
|
|
||||||
).as_bytes()
|
|
||||||
optional = Optional(
|
|
||||||
event=EVENT_StartSession, sessionId=session_id
|
|
||||||
).as_bytes()
|
|
||||||
payload = self.get_payload_bytes(
|
|
||||||
event=EVENT_StartSession, speaker=self.speaker
|
|
||||||
)
|
|
||||||
await asyncio.wait_for(
|
|
||||||
self.send_event(header, optional, payload), timeout=5
|
|
||||||
)
|
|
||||||
logger.bind(tag=TAG).info("会话启动请求已发送")
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"启动会话失败: {str(e)}")
|
|
||||||
self._session_started = False
|
|
||||||
self._session_finished = True
|
|
||||||
self._current_session_id = None
|
|
||||||
raise
|
|
||||||
except asyncio.TimeoutError:
|
|
||||||
logger.bind(tag=TAG).error(f"启动会话超时: {session_id}")
|
|
||||||
# 超时后强制重置会话状态
|
|
||||||
self._session_started = False
|
|
||||||
self._session_finished = True
|
|
||||||
self._current_session_id = None
|
|
||||||
# 尝试关闭WebSocket连接
|
|
||||||
if self.ws:
|
|
||||||
try:
|
|
||||||
await self.ws.close()
|
|
||||||
except:
|
|
||||||
pass
|
|
||||||
self.ws = None
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"启动会话时发生未知错误: {str(e)}")
|
|
||||||
# 发生未知错误时也重置会话状态
|
|
||||||
self._session_started = False
|
|
||||||
self._session_finished = True
|
|
||||||
self._current_session_id = None
|
|
||||||
|
|
||||||
async def finish_session(self, session_id):
|
|
||||||
logger.bind(tag=TAG).info(f"关闭会话~~{session_id}")
|
|
||||||
try:
|
|
||||||
async with self._session_lock:
|
|
||||||
try:
|
|
||||||
# 检查会话状态
|
|
||||||
if not self._session_started:
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
f"尝试关闭未开始的会话 {session_id}"
|
|
||||||
)
|
|
||||||
return
|
|
||||||
|
|
||||||
if self._session_finished:
|
|
||||||
logger.bind(tag=TAG).warning(f"会话 {session_id} 已经关闭")
|
|
||||||
return
|
|
||||||
|
|
||||||
if self._current_session_id != session_id:
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
f"尝试关闭错误的会话 {session_id},当前会话为 {self._current_session_id}"
|
|
||||||
)
|
|
||||||
# 即使会话ID不匹配,也尝试关闭当前会话
|
|
||||||
if self._current_session_id:
|
|
||||||
session_id = self._current_session_id
|
|
||||||
|
|
||||||
# 确保WebSocket连接可用
|
|
||||||
if self.ws is None:
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
"WebSocket连接不存在,尝试重新连接..."
|
|
||||||
)
|
|
||||||
await asyncio.wait_for(self._ensure_connection(), timeout=5)
|
|
||||||
|
|
||||||
header = Header(
|
|
||||||
message_type=FULL_CLIENT_REQUEST,
|
|
||||||
message_type_specific_flags=MsgTypeFlagWithEvent,
|
|
||||||
serial_method=JSON,
|
|
||||||
).as_bytes()
|
|
||||||
optional = Optional(
|
|
||||||
event=EVENT_FinishSession, sessionId=session_id
|
|
||||||
).as_bytes()
|
|
||||||
payload = str.encode("{}")
|
|
||||||
await asyncio.wait_for(
|
|
||||||
self.send_event(header, optional, payload), timeout=5
|
|
||||||
)
|
|
||||||
logger.bind(tag=TAG).info("会话结束请求已发送")
|
|
||||||
|
|
||||||
# 更新会话状态
|
|
||||||
self._session_finished = True
|
|
||||||
self._session_started = False
|
|
||||||
self._current_session_id = None
|
|
||||||
logger.bind(tag=TAG).info(
|
|
||||||
"会话状态已更新 - 开始: False, 结束: True"
|
|
||||||
)
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"关闭会话失败: {str(e)}")
|
|
||||||
# 即使发生错误,也要重置会话状态
|
|
||||||
self._session_finished = True
|
|
||||||
self._session_started = False
|
|
||||||
self._current_session_id = None
|
|
||||||
raise
|
|
||||||
except asyncio.TimeoutError:
|
|
||||||
logger.bind(tag=TAG).error(f"关闭会话超时: {session_id}")
|
|
||||||
# 超时后强制重置会话状态
|
|
||||||
self._session_finished = True
|
|
||||||
self._session_started = False
|
|
||||||
self._current_session_id = None
|
|
||||||
# 尝试关闭WebSocket连接
|
|
||||||
if self.ws:
|
|
||||||
try:
|
|
||||||
await self.ws.close()
|
|
||||||
except:
|
|
||||||
pass
|
|
||||||
self.ws = None
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"关闭会话时发生未知错误: {str(e)}")
|
|
||||||
# 发生未知错误时也重置会话状态
|
|
||||||
self._session_finished = True
|
|
||||||
self._session_started = False
|
|
||||||
self._current_session_id = None
|
|
||||||
|
|
||||||
async def reset(self):
|
|
||||||
# 关闭之前的对话
|
|
||||||
if self.start_connection_flag:
|
|
||||||
await self.finish_connection()
|
|
||||||
self.start_connection_flag = False
|
|
||||||
await self.start_connection()
|
|
||||||
self.start_connection_flag = True
|
|
||||||
|
|
||||||
async def close(self):
|
|
||||||
"""资源清理方法"""
|
|
||||||
await self.finish_connection()
|
|
||||||
await self.ws.close()
|
|
||||||
|
|
||||||
def wav_to_opus_data_audio_raw(self, raw_data_var, is_end=False):
|
def wav_to_opus_data_audio_raw(self, raw_data_var, is_end=False):
|
||||||
opus_datas = self.opus_encoder.encode_pcm_to_opus(raw_data_var, is_end)
|
opus_datas = self.opus_encoder.encode_pcm_to_opus(raw_data_var, is_end)
|
||||||
return opus_datas
|
return opus_datas
|
||||||
|
|
||||||
async def _handle_connection_error(self):
|
|
||||||
"""处理连接错误"""
|
|
||||||
if self._reconnect_attempts < self._max_reconnect_attempts:
|
|
||||||
self._reconnect_attempts += 1
|
|
||||||
logger.bind(tag=TAG).warning(
|
|
||||||
f"尝试重新连接 (第{self._reconnect_attempts}次)"
|
|
||||||
)
|
|
||||||
try:
|
|
||||||
await self._ensure_connection()
|
|
||||||
return True
|
|
||||||
except Exception as e:
|
|
||||||
logger.bind(tag=TAG).error(f"重新连接失败: {str(e)}")
|
|
||||||
return False
|
|
||||||
else:
|
|
||||||
logger.bind(tag=TAG).error("达到最大重连次数,放弃重连")
|
|
||||||
return False
|
|
||||||
|
|||||||
@@ -0,0 +1,12 @@
|
|||||||
|
from abc import ABC, abstractmethod
|
||||||
|
from config.logger import setup_logging
|
||||||
|
|
||||||
|
TAG = __name__
|
||||||
|
logger = setup_logging()
|
||||||
|
|
||||||
|
|
||||||
|
class VLLMProviderBase(ABC):
|
||||||
|
@abstractmethod
|
||||||
|
def response(self, question, base64_image):
|
||||||
|
"""VLLM response generator"""
|
||||||
|
pass
|
||||||
@@ -0,0 +1,65 @@
|
|||||||
|
import openai
|
||||||
|
import json
|
||||||
|
from config.logger import setup_logging
|
||||||
|
from core.utils.util import check_model_key
|
||||||
|
from core.providers.vllm.base import VLLMProviderBase
|
||||||
|
|
||||||
|
TAG = __name__
|
||||||
|
logger = setup_logging()
|
||||||
|
|
||||||
|
|
||||||
|
class VLLMProvider(VLLMProviderBase):
|
||||||
|
def __init__(self, config):
|
||||||
|
self.model_name = config.get("model_name")
|
||||||
|
self.api_key = config.get("api_key")
|
||||||
|
if "base_url" in config:
|
||||||
|
self.base_url = config.get("base_url")
|
||||||
|
else:
|
||||||
|
self.base_url = config.get("url")
|
||||||
|
|
||||||
|
param_defaults = {
|
||||||
|
"max_tokens": (500, int),
|
||||||
|
"temperature": (0.7, lambda x: round(float(x), 1)),
|
||||||
|
"top_p": (1.0, lambda x: round(float(x), 1)),
|
||||||
|
}
|
||||||
|
|
||||||
|
for param, (default, converter) in param_defaults.items():
|
||||||
|
value = config.get(param)
|
||||||
|
try:
|
||||||
|
setattr(
|
||||||
|
self,
|
||||||
|
param,
|
||||||
|
converter(value) if value not in (None, "") else default,
|
||||||
|
)
|
||||||
|
except (ValueError, TypeError):
|
||||||
|
setattr(self, param, default)
|
||||||
|
|
||||||
|
check_model_key("VLLM", self.api_key)
|
||||||
|
self.client = openai.OpenAI(api_key=self.api_key, base_url=self.base_url)
|
||||||
|
|
||||||
|
def response(self, question, base64_image):
|
||||||
|
try:
|
||||||
|
messages = [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": [
|
||||||
|
{"type": "text", "text": question},
|
||||||
|
{
|
||||||
|
"type": "image_url",
|
||||||
|
"image_url": {
|
||||||
|
"url": f"data:image/jpeg;base64,{base64_image}"
|
||||||
|
},
|
||||||
|
},
|
||||||
|
],
|
||||||
|
}
|
||||||
|
]
|
||||||
|
|
||||||
|
response = self.client.chat.completions.create(
|
||||||
|
model=self.model_name, messages=messages, stream=False
|
||||||
|
)
|
||||||
|
|
||||||
|
return response.choices[0].message.content
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.bind(tag=TAG).error(f"Error in response generation: {e}")
|
||||||
|
raise
|
||||||
@@ -0,0 +1,43 @@
|
|||||||
|
import jwt
|
||||||
|
import time
|
||||||
|
from datetime import datetime, timedelta, timezone
|
||||||
|
from typing import Optional, Tuple
|
||||||
|
|
||||||
|
|
||||||
|
class AuthToken:
|
||||||
|
def __init__(self, secret_key: str):
|
||||||
|
self.secret_key = secret_key
|
||||||
|
|
||||||
|
def generate_token(self, device_id: str) -> str:
|
||||||
|
"""
|
||||||
|
生成JWT token
|
||||||
|
:param device_id: 设备ID
|
||||||
|
:return: JWT token字符串
|
||||||
|
"""
|
||||||
|
# 设置过期时间为1小时后
|
||||||
|
expire_time = datetime.now(timezone.utc) + timedelta(hours=1)
|
||||||
|
|
||||||
|
# 创建payload
|
||||||
|
payload = {"device_id": device_id, "exp": expire_time.timestamp()}
|
||||||
|
|
||||||
|
# 使用JWT进行编码
|
||||||
|
token = jwt.encode(payload, self.secret_key, algorithm="HS256")
|
||||||
|
return token
|
||||||
|
|
||||||
|
def verify_token(self, token: str) -> Tuple[bool, Optional[str]]:
|
||||||
|
"""
|
||||||
|
验证token
|
||||||
|
:param token: JWT token字符串
|
||||||
|
:return: (是否有效, 设备ID)
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
# 解码token
|
||||||
|
payload = jwt.decode(token, self.secret_key, algorithms=["HS256"])
|
||||||
|
|
||||||
|
# 检查是否过期
|
||||||
|
if payload["exp"] < time.time():
|
||||||
|
return False, None
|
||||||
|
|
||||||
|
return True, payload["device_id"]
|
||||||
|
except jwt.InvalidTokenError:
|
||||||
|
return False, None
|
||||||
@@ -882,3 +882,51 @@ def filter_sensitive_info(config: dict) -> dict:
|
|||||||
return filtered
|
return filtered
|
||||||
|
|
||||||
return _filter_dict(copy.deepcopy(config))
|
return _filter_dict(copy.deepcopy(config))
|
||||||
|
|
||||||
|
|
||||||
|
def get_vision_url(config: dict) -> str:
|
||||||
|
"""获取 vision URL
|
||||||
|
|
||||||
|
Args:
|
||||||
|
config: 配置字典
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: vision URL
|
||||||
|
"""
|
||||||
|
server_config = config["server"]
|
||||||
|
vision_explain = server_config.get("vision_explain", "")
|
||||||
|
if "你的" in vision_explain:
|
||||||
|
local_ip = get_local_ip()
|
||||||
|
port = int(server_config.get("http_port", 8003))
|
||||||
|
vision_explain = f"http://{local_ip}:{port}/mcp/vision/explain"
|
||||||
|
return vision_explain
|
||||||
|
|
||||||
|
|
||||||
|
def is_valid_image_file(file_data: bytes) -> bool:
|
||||||
|
"""
|
||||||
|
检查文件数据是否为有效的图片格式
|
||||||
|
|
||||||
|
Args:
|
||||||
|
file_data: 文件的二进制数据
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
bool: 如果是有效的图片格式返回True,否则返回False
|
||||||
|
"""
|
||||||
|
# 常见图片格式的魔数(文件头)
|
||||||
|
image_signatures = {
|
||||||
|
b"\xff\xd8\xff": "JPEG",
|
||||||
|
b"\x89PNG\r\n\x1a\n": "PNG",
|
||||||
|
b"GIF87a": "GIF",
|
||||||
|
b"GIF89a": "GIF",
|
||||||
|
b"BM": "BMP",
|
||||||
|
b"II*\x00": "TIFF",
|
||||||
|
b"MM\x00*": "TIFF",
|
||||||
|
b"RIFF": "WEBP",
|
||||||
|
}
|
||||||
|
|
||||||
|
# 检查文件头是否匹配任何已知的图片格式
|
||||||
|
for signature in image_signatures:
|
||||||
|
if file_data.startswith(signature):
|
||||||
|
return True
|
||||||
|
|
||||||
|
return False
|
||||||
|
|||||||
@@ -0,0 +1,23 @@
|
|||||||
|
import os
|
||||||
|
import sys
|
||||||
|
|
||||||
|
# 添加项目根目录到Python路径
|
||||||
|
current_dir = os.path.dirname(os.path.abspath(__file__))
|
||||||
|
project_root = os.path.abspath(os.path.join(current_dir, "..", ".."))
|
||||||
|
sys.path.insert(0, project_root)
|
||||||
|
|
||||||
|
from config.logger import setup_logging
|
||||||
|
import importlib
|
||||||
|
|
||||||
|
logger = setup_logging()
|
||||||
|
|
||||||
|
|
||||||
|
def create_instance(class_name, *args, **kwargs):
|
||||||
|
# 创建LLM实例
|
||||||
|
if os.path.exists(os.path.join("core", "providers", "vllm", f"{class_name}.py")):
|
||||||
|
lib_name = f"core.providers.vllm.{class_name}"
|
||||||
|
if lib_name not in sys.modules:
|
||||||
|
sys.modules[lib_name] = importlib.import_module(f"{lib_name}")
|
||||||
|
return sys.modules[lib_name].VLLMProvider(*args, **kwargs)
|
||||||
|
|
||||||
|
raise ValueError(f"不支持的VLLM类型: {class_name},请检查该配置的type是否设置正确")
|
||||||
@@ -13,8 +13,8 @@ services:
|
|||||||
ports:
|
ports:
|
||||||
# ws服务端
|
# ws服务端
|
||||||
- "8000:8000"
|
- "8000:8000"
|
||||||
# ota服务端
|
# http服务的端口,用于简单OTA接口(单服务部署),以及视觉分析接口
|
||||||
- "8002:8002"
|
- "8003:8003"
|
||||||
volumes:
|
volumes:
|
||||||
# 配置文件目录
|
# 配置文件目录
|
||||||
- ./data:/opt/xiaozhi-esp32-server/data
|
- ./data:/opt/xiaozhi-esp32-server/data
|
||||||
|
|||||||
@@ -15,6 +15,8 @@ services:
|
|||||||
ports:
|
ports:
|
||||||
# ws服务端
|
# ws服务端
|
||||||
- "8000:8000"
|
- "8000:8000"
|
||||||
|
# http服务的端口,用于视觉分析接口
|
||||||
|
- "8003:8003"
|
||||||
security_opt:
|
security_opt:
|
||||||
- seccomp:unconfined
|
- seccomp:unconfined
|
||||||
environment:
|
environment:
|
||||||
|
|||||||
@@ -140,7 +140,9 @@ class AsyncPerformanceTester:
|
|||||||
|
|
||||||
print(f"🎵 测试 STT: {stt_name}")
|
print(f"🎵 测试 STT: {stt_name}")
|
||||||
|
|
||||||
text, _ = await stt.speech_to_text([self.test_wav_list[0]], "1")
|
text, _ = await stt.speech_to_text(
|
||||||
|
[self.test_wav_list[0]], "1", stt.audio_format
|
||||||
|
)
|
||||||
|
|
||||||
if text is None:
|
if text is None:
|
||||||
print(f"❌ {stt_name} 连接失败")
|
print(f"❌ {stt_name} 连接失败")
|
||||||
@@ -151,7 +153,7 @@ class AsyncPerformanceTester:
|
|||||||
|
|
||||||
for i, sentence in enumerate(self.test_wav_list, 1):
|
for i, sentence in enumerate(self.test_wav_list, 1):
|
||||||
start = time.time()
|
start = time.time()
|
||||||
text, _ = await stt.speech_to_text([sentence], "1")
|
text, _ = await stt.speech_to_text([sentence], "1", stt.audio_format)
|
||||||
duration = time.time() - start
|
duration = time.time() - start
|
||||||
total_time += duration
|
total_time += duration
|
||||||
|
|
||||||
|
|||||||
@@ -0,0 +1,189 @@
|
|||||||
|
import time
|
||||||
|
import asyncio
|
||||||
|
import logging
|
||||||
|
import statistics
|
||||||
|
import base64
|
||||||
|
from typing import Dict
|
||||||
|
from tabulate import tabulate
|
||||||
|
from config.settings import load_config
|
||||||
|
from core.utils.vllm import create_instance
|
||||||
|
|
||||||
|
# 设置全局日志级别为WARNING,抑制INFO级别日志
|
||||||
|
logging.basicConfig(level=logging.WARNING)
|
||||||
|
|
||||||
|
|
||||||
|
class AsyncVisionPerformanceTester:
|
||||||
|
def __init__(self):
|
||||||
|
self.config = load_config()
|
||||||
|
self.test_images = [
|
||||||
|
"../../docs/images/demo1.png",
|
||||||
|
"../../docs/images/demo2.png",
|
||||||
|
]
|
||||||
|
self.test_questions = [
|
||||||
|
"这张图片里有什么?",
|
||||||
|
"请详细描述这张图片的内容",
|
||||||
|
]
|
||||||
|
|
||||||
|
# 加载测试图片
|
||||||
|
self.results = {"vllm": {}}
|
||||||
|
|
||||||
|
async def _test_vllm(self, vllm_name: str, config: Dict) -> Dict:
|
||||||
|
"""异步测试单个视觉大模型性能"""
|
||||||
|
try:
|
||||||
|
# 检查API密钥配置
|
||||||
|
if "api_key" in config and any(
|
||||||
|
x in config["api_key"] for x in ["你的", "placeholder", "sk-xxx"]
|
||||||
|
):
|
||||||
|
print(f"⏭️ VLLM {vllm_name} 未配置api_key,已跳过")
|
||||||
|
return {"name": vllm_name, "type": "vllm", "errors": 1}
|
||||||
|
|
||||||
|
# 获取实际类型(兼容旧配置)
|
||||||
|
module_type = config.get("type", vllm_name)
|
||||||
|
vllm = create_instance(module_type, config)
|
||||||
|
|
||||||
|
print(f"🖼️ 测试 VLLM: {vllm_name}")
|
||||||
|
|
||||||
|
# 创建所有测试任务
|
||||||
|
test_tasks = []
|
||||||
|
for question in self.test_questions:
|
||||||
|
for image in self.test_images:
|
||||||
|
test_tasks.append(
|
||||||
|
self._test_single_vision(vllm_name, vllm, question, image)
|
||||||
|
)
|
||||||
|
|
||||||
|
# 并发执行所有测试
|
||||||
|
test_results = await asyncio.gather(*test_tasks)
|
||||||
|
|
||||||
|
# 处理结果
|
||||||
|
valid_results = [r for r in test_results if r is not None]
|
||||||
|
if not valid_results:
|
||||||
|
print(f"⚠️ {vllm_name} 无有效数据,可能配置错误")
|
||||||
|
return {"name": vllm_name, "type": "vllm", "errors": 1}
|
||||||
|
|
||||||
|
response_times = [r["response_time"] for r in valid_results]
|
||||||
|
|
||||||
|
# 过滤异常数据
|
||||||
|
mean = statistics.mean(response_times)
|
||||||
|
stdev = statistics.stdev(response_times) if len(response_times) > 1 else 0
|
||||||
|
filtered_times = [t for t in response_times if t <= mean + 3 * stdev]
|
||||||
|
|
||||||
|
if len(filtered_times) < len(test_tasks) * 0.5:
|
||||||
|
print(f"⚠️ {vllm_name} 有效数据不足,可能网络不稳定")
|
||||||
|
return {"name": vllm_name, "type": "vllm", "errors": 1}
|
||||||
|
|
||||||
|
return {
|
||||||
|
"name": vllm_name,
|
||||||
|
"type": "vllm",
|
||||||
|
"avg_response": sum(response_times) / len(response_times),
|
||||||
|
"std_response": (
|
||||||
|
statistics.stdev(response_times) if len(response_times) > 1 else 0
|
||||||
|
),
|
||||||
|
"errors": 0,
|
||||||
|
}
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
print(f"⚠️ VLLM {vllm_name} 测试失败: {str(e)}")
|
||||||
|
return {"name": vllm_name, "type": "vllm", "errors": 1}
|
||||||
|
|
||||||
|
async def _test_single_vision(
|
||||||
|
self, vllm_name: str, vllm, question: str, image: str
|
||||||
|
) -> Dict:
|
||||||
|
"""测试单个视觉问题的性能"""
|
||||||
|
try:
|
||||||
|
print(f"📝 {vllm_name} 开始测试: {question[:20]}...")
|
||||||
|
start_time = time.time()
|
||||||
|
|
||||||
|
# 读取图片并转换为base64
|
||||||
|
with open(image, "rb") as image_file:
|
||||||
|
image_data = image_file.read()
|
||||||
|
image_base64 = base64.b64encode(image_data).decode("utf-8")
|
||||||
|
|
||||||
|
# 直接获取响应
|
||||||
|
response = vllm.response(question, image_base64)
|
||||||
|
response_time = time.time() - start_time
|
||||||
|
print(f"✓ {vllm_name} 完成响应: {response_time:.3f}s")
|
||||||
|
|
||||||
|
return {
|
||||||
|
"name": vllm_name,
|
||||||
|
"type": "vllm",
|
||||||
|
"response_time": response_time,
|
||||||
|
}
|
||||||
|
except Exception as e:
|
||||||
|
print(f"⚠️ {vllm_name} 测试失败: {str(e)}")
|
||||||
|
return None
|
||||||
|
|
||||||
|
def _print_results(self):
|
||||||
|
"""打印测试结果"""
|
||||||
|
vllm_table = []
|
||||||
|
for name, data in self.results["vllm"].items():
|
||||||
|
if data["errors"] == 0:
|
||||||
|
stability = data["std_response"] / data["avg_response"]
|
||||||
|
vllm_table.append(
|
||||||
|
[
|
||||||
|
name,
|
||||||
|
f"{data['avg_response']:.3f}秒",
|
||||||
|
f"{stability:.3f}",
|
||||||
|
]
|
||||||
|
)
|
||||||
|
|
||||||
|
if vllm_table:
|
||||||
|
print("\n视觉大模型性能排行:\n")
|
||||||
|
print(
|
||||||
|
tabulate(
|
||||||
|
vllm_table,
|
||||||
|
headers=["模型名称", "响应耗时", "稳定性"],
|
||||||
|
tablefmt="github",
|
||||||
|
colalign=("left", "right", "right"),
|
||||||
|
disable_numparse=True,
|
||||||
|
)
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
print("\n⚠️ 没有可用的视觉大模型进行测试。")
|
||||||
|
|
||||||
|
async def run(self):
|
||||||
|
"""执行全量异步测试"""
|
||||||
|
print("🔍 开始筛选可用视觉大模型...")
|
||||||
|
|
||||||
|
if not self.test_images:
|
||||||
|
print(f"\n⚠️ {self.image_root} 路径下没有图片文件,无法进行测试")
|
||||||
|
return
|
||||||
|
|
||||||
|
# 创建所有测试任务
|
||||||
|
all_tasks = []
|
||||||
|
|
||||||
|
# VLLM测试任务
|
||||||
|
if self.config.get("VLLM") is not None:
|
||||||
|
for vllm_name, config in self.config.get("VLLM", {}).items():
|
||||||
|
if "api_key" in config and any(
|
||||||
|
x in config["api_key"] for x in ["你的", "placeholder", "sk-xxx"]
|
||||||
|
):
|
||||||
|
print(f"⏭️ VLLM {vllm_name} 未配置api_key,已跳过")
|
||||||
|
continue
|
||||||
|
print(f"🖼️ 添加VLLM测试任务: {vllm_name}")
|
||||||
|
all_tasks.append(self._test_vllm(vllm_name, config))
|
||||||
|
|
||||||
|
print(f"\n✅ 找到 {len(all_tasks)} 个可用视觉大模型")
|
||||||
|
print(f"✅ 使用 {len(self.test_images)} 张测试图片")
|
||||||
|
print(f"✅ 使用 {len(self.test_questions)} 个测试问题")
|
||||||
|
print("\n⏳ 开始并发测试所有模型...\n")
|
||||||
|
|
||||||
|
# 并发执行所有测试任务
|
||||||
|
all_results = await asyncio.gather(*all_tasks, return_exceptions=True)
|
||||||
|
|
||||||
|
# 处理结果
|
||||||
|
for result in all_results:
|
||||||
|
if isinstance(result, dict) and result["errors"] == 0:
|
||||||
|
self.results["vllm"][result["name"]] = result
|
||||||
|
|
||||||
|
# 打印结果
|
||||||
|
print("\n📊 生成测试报告...")
|
||||||
|
self._print_results()
|
||||||
|
|
||||||
|
|
||||||
|
async def main():
|
||||||
|
tester = AsyncVisionPerformanceTester()
|
||||||
|
await tester.run()
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
asyncio.run(main())
|
||||||
@@ -21,7 +21,7 @@ cozepy==0.12.0
|
|||||||
mem0ai==0.1.62
|
mem0ai==0.1.62
|
||||||
bs4==0.0.2
|
bs4==0.0.2
|
||||||
modelscope==1.23.2
|
modelscope==1.23.2
|
||||||
sherpa_onnx==1.11.0
|
sherpa_onnx==1.12.0
|
||||||
mcp==1.8.1
|
mcp==1.8.1
|
||||||
cnlunar==0.2.0
|
cnlunar==0.2.0
|
||||||
PySocks==1.7.1
|
PySocks==1.7.1
|
||||||
@@ -31,3 +31,4 @@ chardet==5.2.0
|
|||||||
aioconsole==0.8.1
|
aioconsole==0.8.1
|
||||||
markitdown==0.1.1
|
markitdown==0.1.1
|
||||||
mcp-proxy==0.6.0
|
mcp-proxy==0.6.0
|
||||||
|
PyJWT==2.8.0
|
||||||
Reference in New Issue
Block a user