update:新增SLM唤醒词回复

Perf：新增联网搜索工具类、修复新闻描述配置获取源问题

.dockerignore

@@ -3,11 +3,5 @@ __pycache__
 *.pyc
 .env
 Dockerfile
-docs/
 tmp/
-data/
-LICENSE
-README.md
-README_en.md
-manager/static
-manager/static/webui/
+data/

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,32 @@
+---
+name: Bug 报告（Bug Report）
+about: 反馈项目中的缺陷或问题
+title: "[Bug] 简短描述问题"
+labels: bug
+assignees: ''
+---
+
+## 🐛 问题描述
+<!-- 清晰简洁地描述问题是什么 -->
+
+## 🖥️ 环境信息
+- 部署方式: 全模块部署 还是 单Server部署
+- 版本号: 例如 0.3.x
+
+## 🔍 告诉我们，应该怎么复现这个问题
+<!-- 这个很重要，方便我们快速定位 -->
+1. 打开 '...'
+2. 点击 '...'
+3. 滚动到 '...'
+4. 看到错误
+
+## 🤔 你原本希望是怎么样的
+<!-- 简要描述预期的正确行为 -->
+
+## 😯 提供一些截图
+<!-- 如果适用，添加问题的截图 -->
+1. 比如日志截图，越多越好
+2. 比如界面反应
+
+## 📋 其他信息
+<!-- 在此添加关于此问题的任何其他上下文信息 -->

.github/ISSUE_TEMPLATE/code_improvement.md

@@ -0,0 +1,19 @@
+---
+name: 代码优化建议（Code Improvement）
+about: 提出对现有代码的优化或改进建议
+title: "[Improvement] 简短描述改进内容"
+labels: refactor
+assignees: ''
+---
+
+## 💡 改进描述
+<!-- 描述需要改进的代码部分以及存在的问题 -->
+
+## 🌟 改进建议
+<!-- 提出具体的改进方案或思路 -->
+
+## 🛠️ 相关代码
+<!-- 如果可能，提供相关代码片段或链接 -->
+
+## 📋 其他信息
+<!-- 在此添加任何其他相关信息 -->

.github/ISSUE_TEMPLATE/documentation_improvement.md

@@ -0,0 +1,16 @@
+---
+name: 文档改进建议（Documentation Improvement）
+about: 提出对项目文档的改进或补充建议
+title: "[Docs] 简短描述改进内容"
+labels: documentation
+assignees: ''
+---
+
+## 📚 改进描述
+<!-- 描述需要改进的文档部分以及存在的问题 -->
+
+## ✨ 改进建议
+<!-- 提出具体的改进方案或内容 -->
+
+## 📋 其他信息
+<!-- 在此添加任何其他相关信息 -->

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,19 @@
+---
+name: 功能请求（Feature Request）
+about: 提出新的功能或改进建议
+title: "[Feature] 简短描述功能"
+labels: enhancement
+assignees: ''
+---
+
+## 🚀 需求描述
+<!-- 清晰简洁地描述你希望发生什么 -->
+
+## 🎯 解决方案
+<!-- 描述你认为可行的解决方案或实现方式 -->
+
+## 📝 备选方案
+<!-- 描述你考虑过的替代方案或功能 -->
+
+## 📋 其他信息
+<!-- 在此添加关于需求的任何其他上下文信息 -->

.github/dependabot.yml

@@ -0,0 +1,6 @@
+version: 2
+updates:
+  - package-ecosystem: pip
+    directory: /main/xiaozhi-server
+    schedule:
+      interval: weekly

.github/workflows/build-base-image.yml

@@ -0,0 +1,49 @@
+name: Build Base Image
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'main/xiaozhi-server/requirements.txt'
+      - 'Dockerfile-server-base'
+      - '.github/workflows/build-base-image.yml'
+
+jobs:
+  build-base:
+    name: Build and push server base image
+    runs-on: ubuntu-latest
+    permissions:
+      packages: write
+      contents: read
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.TOKEN }}
+
+      - name: Build and push server-base
+        uses: docker/build-push-action@v6
+        with:
+          context: .
+          file: Dockerfile-server-base
+          push: true
+          tags: ghcr.io/${{ github.repository }}:server-base
+          platforms: linux/amd64,linux/arm64
+          cache-from: type=gha,scope=server-base
+          cache-to: type=gha,mode=max,scope=server-base
+          build-args: |
+            BUILDKIT_PROGRESS=plain
+
+      - name: Output image info
+        run: |
+          echo "✅ Base image built and pushed successfully!"
+          echo "📦 Tag: ghcr.io/${{ github.repository }}:server-base"

.github/workflows/docker-image.yml

@@ -4,25 +4,42 @@ on:
   push:
     tags:
       - 'v*.*.*'  # 只在以 v 开头的标签推送时触发，例如 v1.0.0
+  workflow_dispatch:
+  workflow_run:
+    workflows: ["Build Base Image"]
+    types:
+      - completed
 
 jobs:
   release:
-    name: Release Docker image
+    name: Release Docker images
     runs-on: ubuntu-latest
     permissions:
       packages: write
       contents: write
       id-token: write
       issues: write
-
     steps:
-      - name: Check out the repo
+      - name: Check Disk Space
+        run: |
+          df -h
+          docker system df
+
+      - name: Clean up Docker resources
+        run: |
+          docker system prune -af
+          docker builder prune -af
+
+      - name: Checkout code
         uses: actions/checkout@v4
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
+        with:
+          driver-opts: |
+            network=host
 
-      - name: Log in to the GitHub Container Registry
+      - name: Login to GitHub Container Registry
         uses: docker/login-action@v3
         with:
           registry: ghcr.io
@@ -32,15 +49,40 @@ jobs:
       - name: Extract version from tag
         id: get_version
         run: |
-          echo "VERSION=${GITHUB_REF#refs/tags/}" >> $GITHUB_ENV
+          if [[ "$GITHUB_REF" =~ ^refs/tags/v([0-9]+\.[0-9]+\.[0-9]+)$ ]]; then
+            echo "VERSION=${BASH_REMATCH[1]}" >> $GITHUB_ENV
+            echo "IS_VERSION=true" >> $GITHUB_ENV
+          else
+            echo "VERSION=latest" >> $GITHUB_ENV
+            echo "IS_VERSION=false" >> $GITHUB_ENV
+          fi
 
-      - name: Build and push Docker image
-        id: build_push
+      # 构建 xiaozhi-server 镜像
+      - name: Build and push xiaozhi-server
         uses: docker/build-push-action@v6
         with:
           context: .
+          file: Dockerfile-server
           push: true
           tags: |
-            ghcr.io/${{ github.repository }}:${{ env.VERSION }}
-            ghcr.io/${{ github.repository }}:latest
+            ${{ env.IS_VERSION == 'true' && format('ghcr.io/{0}:server_{1},ghcr.io/{0}:server_latest', github.repository, env.VERSION) || format('ghcr.io/{0}:server_latest', github.repository) }}
           platforms: linux/amd64,linux/arm64
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+          build-args: |
+            BUILDKIT_PROGRESS=plain
+
+      # 构建 manager-api 镜像
+      - name: Build and push manager-web
+        uses: docker/build-push-action@v6
+        with:
+          context: .
+          file: Dockerfile-web
+          push: true
+          tags: |
+            ${{ env.IS_VERSION == 'true' && format('ghcr.io/{0}:web_{1},ghcr.io/{0}:web_latest', github.repository, env.VERSION) || format('ghcr.io/{0}:web_latest', github.repository) }}
+          platforms: linux/amd64,linux/arm64
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+          build-args: |
+            BUILDKIT_PROGRESS=plain

.gitignore

@@ -3,6 +3,9 @@ __pycache__/
 .idea/
 *.py[cod]
 *$py.class
+.vscode
+.claude
+AGENTS.md
 
 # C extensions
 *.so
@@ -75,6 +78,7 @@ docs/_build/
 # PyBuilder
 .pybuilder/
 target/
+*.pid
 
 # Jupyter Notebook
 .ipynb_checkpoints
@@ -132,17 +136,59 @@ dmypy.json
 # Pyre type checker
 .pyre/
 
+# music directory
+music/
+
 # pytype static type analyzer
 .pytype/
 
 # Cython debug symbols
 cython_debug/
 *.iml
-model.pt
 tmp
+.history
 .DS_Store
+main/xiaozhi-server/data
+main/xiaozhi-server/.claude
+
+main/manager-web/node_modules
 .config.yaml
 .secrets.yaml
 .private_config.yaml
 .env.development
-docker-compose.yml
+
+# model files
+main/xiaozhi-server/models/SenseVoiceSmall/model.pt
+main/xiaozhi-server/models/sherpa-onnx*
+/main/xiaozhi-server/audio_ref/
+/audio_ref/
+/asr-models/iic/SenseVoiceSmall/
+/main/xiaozhi-server/asr-models/iic/SenseVoiceSmall/
+/models/SenseVoiceSmall/model.pt
+my_wakeup_words.mp3
+!main/xiaozhi-server/config/assets/bind_code.wav
+!main/xiaozhi-server/config/assets/wakeup_words.wav
+!main/xiaozhi-server/config/assets/bind_not_found.wav
+!main/xiaozhi-server/config/assets/bind_code/*.wav
+!main/xiaozhi-server/config/assets/max_output_size.wav
+main/manager-api/.vscode
+# Ignore webpack cache directory
+main/manager-web/.webpack_cache/
+main/xiaozhi-server/mysql
+uploadfile
+*.json
+.vscode
+.cursor
+ 
+!package.json
+!**/package.json
+
+# Do not ignore env and json files inside manager-mobile
+!main/manager-mobile/**/env/
+!main/manager-mobile/**/.env*
+!main/manager-mobile/**/*.json
+!main/xiaozhi-server/**/*.json
+!main/digital-human/**/*.json
+main/digital-human/wakeword_runtime/models
+main/digital-human/wakeword_runtime/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01
+sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01.tar.bz2

Dockerfile

@@ -1,45 +0,0 @@
-# 第一阶段：前端构建
-
-FROM kalicyh/node:v18-alpine AS frontend-builder
-
-WORKDIR /app/ZhiKongTaiWeb
-
-# RUN corepack enable && yarn config set registry https://registry.npmmirror.com
-
-COPY ZhiKongTaiWeb/package.json ZhiKongTaiWeb/yarn.lock ./
-
-RUN yarn install --frozen-lockfile
-
-COPY ZhiKongTaiWeb . 
-RUN yarn build
-
-# 第二阶段：构建 Python 依赖
-
-FROM kalicyh/poetry:v3.10_xiaozhi AS builder
-
-WORKDIR /app
-
-# 同时拷贝本地环境.venv
-COPY . .
-# 检查是否有缺失
-RUN poetry install --no-root
-
-# 使用清华源加速apt安装，该镜像内置所以注释
-# RUN rm -rf /etc/apt/sources.list.d/* && \
-#     echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm main contrib non-free non-free-firmware" > /etc/apt/sources.list && \
-#     echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-updates main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \
-#     echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-backports main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \
-#     echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian-security bookworm-security main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \
-#     apt-get update && \
-#     apt-get install -y --no-install-recommends libopus0 ffmpeg && \
-#     apt-get clean
-
-# 从构建阶段复制虚拟环境和前端构建产物
-COPY --from=frontend-builder /app/ZhiKongTaiWeb/dist /app/manager/static/webui
-
-# 设置虚拟环境路径
-ENV PATH="/app/.venv/bin:$PATH"
-
-# 启动应用
-ENTRYPOINT ["poetry", "run", "python"]
-CMD ["app.py"]

Dockerfile-pip

@@ -1,51 +0,0 @@
-# 第一阶段：前端构建
-FROM node:18 AS frontend-builder
-
-WORKDIR /app/ZhiKongTaiWeb
-
-# 配置npm使用淘宝源
-RUN npm config set registry https://registry.npmmirror.com
-
-COPY ZhiKongTaiWeb/package*.json ./
-
-# 安装axios依赖
-RUN npm install axios
-RUN npm install
-
-COPY ZhiKongTaiWeb .
-
-RUN npm run build
-
-# 第二阶段：构建Python依赖
-FROM python:3.10-slim AS builder
-
-WORKDIR /app
-
-COPY requirements.txt .
-
-# 优化apt安装
-RUN pip install --no-cache-dir -r requirements.txt \
-    -i https://mirrors.aliyun.com/pypi/simple/
-
-# 第三阶段：生产镜像
-FROM python:3.10-slim
-
-WORKDIR /opt/xiaozhi-esp32-server
-
-# 优化apt安装
-RUN echo "deb https://mirrors.aliyun.com/debian/ bookworm main contrib non-free non-free-firmware" > /etc/apt/sources.list && \
-    echo "deb https://mirrors.aliyun.com/debian/ bookworm-updates main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \
-    apt-get update && \
-    apt-get install -y --no-install-recommends libopus0 ffmpeg && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
-
-# 从构建阶段复制Python包和前端构建产物
-COPY --from=builder /usr/local/lib/python3.10/site-packages /usr/local/lib/python3.10/site-packages
-COPY --from=frontend-builder /app/ZhiKongTaiWeb/dist /opt/xiaozhi-esp32-server/manager/static/webui
-
-# 复制应用代码
-COPY . .
-
-# 启动应用
-CMD ["python", "app.py"]

Dockerfile-server

@@ -0,0 +1,7 @@
+# 生产镜像，仅包含应用代码
+FROM ghcr.io/xinnan-tech/xiaozhi-esp32-server:server-base
+
+COPY main/xiaozhi-server .
+
+# 启动应用
+CMD ["python", "app.py"]

Dockerfile-server-base

@@ -0,0 +1,32 @@
+# Dockerfile-server-base
+# 基础镜像，包含系统依赖和Python包
+FROM python:3.10-slim
+
+# 安装系统依赖
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libopus0 ffmpeg locales && \
+    sed -i '/zh_CN.UTF-8/s/^# //g' /etc/locale.gen && \
+    locale-gen && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# 配置pip使用国内镜像源（阿里云）并设置超时和重试
+RUN pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ && \
+    pip config set global.trusted-host mirrors.aliyun.com && \
+    pip config set global.timeout 120 && \
+    pip config set install.retries 5
+
+# 设置环境变量以确保正确的字符编码
+ENV LANG=zh_CN.UTF-8 \
+    LC_ALL=zh_CN.UTF-8 \
+    LANGUAGE=zh_CN:zh \
+    PYTHONIOENCODING=utf-8
+
+WORKDIR /opt/xiaozhi-esp32-server
+
+# 复制requirements.txt
+COPY main/xiaozhi-server/requirements.txt .
+
+# 安装Python依赖
+RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \
+    pip install --no-cache-dir -r requirements.txt --default-timeout=120 --retries 5

Dockerfile-web

@@ -0,0 +1,50 @@
+# 第一阶段：构建Vue前端
+FROM node:18 AS web-builder
+WORKDIR /app
+COPY main/manager-web/package*.json ./
+RUN npm install
+COPY main/manager-web .
+RUN npm run build
+
+# 第二阶段：构建Java后端
+FROM maven:3.9.4-eclipse-temurin-21 AS api-builder
+WORKDIR /app
+COPY main/manager-api/pom.xml .
+COPY main/manager-api/src ./src
+RUN mvn clean package -Dmaven.test.skip=true
+
+# 第三阶段：构建最终镜像
+FROM bellsoft/liberica-runtime-container:jre-21-glibc
+
+# 安装Nginx和字体库
+RUN apk update && \
+    apk add --no-cache --no-scripts \
+        nginx \
+        bash \
+        fontconfig \
+        ttf-dejavu \
+    && rm -rf /var/cache/apk/* \
+    && mkdir -p /run/nginx /var/log/nginx /var/tmp/nginx /etc/nginx/conf.d
+
+# 复制项目自带的中文字体
+COPY main/manager-web/public/generator/static/fonts/*.ttf /usr/share/fonts/
+
+# 更新字体缓存
+RUN fc-cache -f -v
+
+# 配置Nginx
+COPY docs/docker/nginx.conf /etc/nginx/nginx.conf
+
+# 复制前端构建产物
+COPY --from=web-builder /app/dist /usr/share/nginx/html
+
+# 复制Java后端JAR包
+COPY --from=api-builder /app/target/xiaozhi-esp32-api.jar /app/xiaozhi-esp32-api.jar
+
+# 暴露端口
+EXPOSE 8002
+
+# 启动脚本
+COPY docs/docker/start.sh /start.sh
+RUN chmod +x /start.sh
+CMD ["/start.sh"]

README.md

@@ -1,11 +1,45 @@
-![图片](docs/images/banner.png)
+[![Banners](docs/images/banner1.png)](https://github.com/xinnan-tech/xiaozhi-esp32-server)
 
-# 小智 ESP-32 后端服务(xiaozhi-esp32-server)
+<h1 align="center">小智后端服务xiaozhi-esp32-server</h1>
 
-（中文 | [English](README_en.md)）
+<p align="center">
+本项目基于人机共生智能理论和技术研发智能终端软硬件体系<br/>为开源智能硬件项目
+<a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a>提供后端服务<br/>
+根据<a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">小智通信协议</a>使用Python、Java、Vue实现<br/>
+支持MQTT+UDP协议、Websocket协议、MCP接入点、声纹识别、知识库
+</p>
 
-本项目为开源智能硬件项目 [xiaozhi-esp32](https://github.com/78/xiaozhi-esp32)
-提供后端服务。根据 [小智通信协议](https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh) 使用 `Python` 实现。
+<p align="center">
+<a href="./docs/FAQ.md">常见问题</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">反馈问题</a>
+· <a href="./README.md#%E9%83%A8%E7%BD%B2%E6%96%87%E6%A1%A3">部署文档</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">更新日志</a>
+</p>
+
+<p align="center">
+  <a href="./README.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DBEDFA"></a>
+  <a href="./docs/readme/README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./docs/readme/README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
+  <a href="./docs/readme/README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
+  <a href="./docs/readme/README_pt_BR.md"><img alt="Português (Brasil)" src="https://img.shields.io/badge/Português (Brasil)-DFE0E5"></a>
+  <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">
+    <img alt="GitHub Contributors" src="https://img.shields.io/github/v/release/xinnan-tech/xiaozhi-esp32-server?logo=docker" />
+  </a>
+  <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/LICENSE">
+    <img alt="GitHub pull requests" src="https://img.shields.io/badge/license-MIT-white?labelColor=black" />
+  </a>
+  <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server">
+    <img alt="stars" src="https://img.shields.io/github/stars/xinnan-tech/xiaozhi-esp32-server?color=ffcb47&labelColor=black" />
+  </a>
+</p>
+
+<p align="center">
+Spearheaded by Professor Siyuan Liu's Team (South China University of Technology)
+</br>
+刘思源教授团队主导研发（华南理工大学）
+</br>
+<img src="./docs/images/hnlg.jpg" alt="华南理工大学" width="50%">
+</p>
 
 ---
 
@@ -21,7 +55,88 @@
     <td>
         <a href="https://www.bilibili.com/video/BV1FMFyejExX" target="_blank">
          <picture>
-           <img alt="小智esp32连接自己的后台模型" src="docs/images/demo1.png" />
+           <img alt="响应速度感受" src="docs/images/demo9.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1vchQzaEse" target="_blank">
+         <picture>
+           <img alt="速度优化秘诀" src="docs/images/demo6.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1C1tCzUEZh" target="_blank">
+         <picture>
+           <img alt="复杂医疗场景" src="docs/images/demo1.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1zUW5zJEkq" target="_blank">
+         <picture>
+           <img alt="MQTT指令下发" src="docs/images/demo4.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1Exu3zqEDe" target="_blank">
+         <picture>
+           <img alt="声纹识别" src="docs/images/demo14.png" />
+         </picture>
+        </a>
+    </td>
+  </tr>
+  <tr>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1pNXWYGEx1" target="_blank">
+         <picture>
+           <img alt="控制家电开关" src="docs/images/demo5.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1ZQKUzYExM" target="_blank">
+         <picture>
+           <img alt="MCP接入点" src="docs/images/demo13.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+      <a href="https://www.bilibili.com/video/BV1TJ7WzzEo6" target="_blank">
+         <picture>
+           <img alt="多指令任务" src="docs/images/demo11.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1VC96Y5EMH" target="_blank">
+         <picture>
+           <img alt="播放音乐" src="docs/images/demo7.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1Z8XuYZEAS" target="_blank">
+         <picture>
+           <img alt="天气插件" src="docs/images/demo8.png" />
+         </picture>
+        </a>
+    </td>
+  </tr>
+  <tr>
+    <td>
+      <a href="https://www.bilibili.com/video/BV12J7WzBEaH" target="_blank">
+         <picture>
+           <img alt="实时打断" src="docs/images/demo10.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+      <a href="https://www.bilibili.com/video/BV1Co76z7EvK" target="_blank">
+         <picture>
+           <img alt="拍照识物品" src="docs/images/demo12.png" />
          </picture>
         </a>
     </td>
@@ -40,124 +155,153 @@
         </a>
     </td>
     <td>
-        <a href="https://www.bilibili.com/video/av114036381327149" target="_blank">
+        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
          <picture>
-           <img alt="控制家电开关" src="docs/images/demo5.png" />
+           <img alt="播报新闻" src="docs/images/demo0.png" />
          </picture>
         </a>
     </td>
-    <td>
-        <a href="https://www.bilibili.com/video/BV1kgA2eYEQ9" target="_blank">
-         <picture>
-           <img alt="成本最低配置" src="docs/images/demo4.png" />
-         </picture>
-        </a>
-    </td>
-    <td>
-    </td>
-    </tr>
+  </tr>
 </table>
 
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
----
-
-## 系统要求与部署前提 🖥️
-
-- **硬件**：一套兼容 `xiaozhi-esp32`
-  的硬件设备（具体型号请参考 [此处](https://rcnv1t9vps13.feishu.cn/wiki/DdgIw4BUgivWDPkhMj1cGIYCnRf)）。
-- **服务器**：至少 4 核 CPU、8G 内存的电脑或服务器。
-- **固件编译**：请将后端服务的接口地址更新至 `xiaozhi-esp32` 项目中，再重新编译固件并烧录到设备上。
-
 ---
 
 ## 警告 ⚠️
 
-本项目成立时间较短，还未通过网络安全测评，请勿在生产环境中使用。
+1、本项目为开源软件，本软件与对接的任何第三方API服务商（包括但不限于语音识别、大模型、语音合成等平台）均不存在商业合作关系，不为其服务质量及资金安全提供任何形式的担保。
+建议使用者优先选择持有相关业务牌照的服务商，并仔细阅读其服务协议及隐私政策。本软件不托管任何账户密钥、不参与资金流转、不承担充值资金损失风险。
 
-如果您在公网环境中部署学习本项目，请务必在配置文件 `config.yaml` 中开启防护：
-
-```yaml
-server:
-  auth:
-    # 开启防护
-    enabled: true  
-```
-
-开启防护后，您需要根据实际情况校验机器的 token 或 mac 地址，详细请参见配置说明。
+2、本项目功能未完善，且未通过网络安全测评，请勿在生产环境中使用。 如果您在公网环境中部署学习本项目，请务必做好必要的防护。
 
 ---
 
+## 部署文档
+
+![Banners](docs/images/banner2.png)
+
+本项目提供两种部署方式，请根据您的具体需求选择：
+
+#### 🚀 部署方式选择
+| 部署方式 | 特点 | 适用场景 | 部署文档 | 配置要求 | 视频教程 | 
+|---------|------|---------|---------|---------|---------|
+| **最简化安装** | 智能对话、单智能体管理 | 低配置环境，数据存储在配置文件，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 | - | 
+| **全模块安装** | 智能对话、多用户管理、多智能体管理、智控台界面操作 | 完整功能体验，数据存储在数据库 |[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) | 
+
+常见问题及相关教程，可参考[这个链接](./docs/FAQ.md)
+
+> 💡 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，
+
+```
+智控台地址: https://2662r3426b.vicp.fun
+智控台(h5版): https://2662r3426b.vicp.fun/h5/index.html
+
+服务测试工具： https://2662r3426b.vicp.fun/test/
+OTA接口地址: https://2662r3426b.vicp.fun/xiaozhi/ota/
+Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
+```
+
+#### 🚩 配置说明和推荐
+> [!Note]
+> 本项目提供两种配置方案：
+> 
+> 1. `入门全免费`配置：适合个人家庭使用，所有组件均采用免费方案，无需额外付费。
+> 
+> 2. `流式配置`：适合演示、培训、超过2个并发等场景，采用流式处理技术，响应速度更快，体验更佳。
+> 
+> 自`0.5.2`版本起，项目支持流式配置，相比早期版本，响应速度提升约`2.5秒`，显著改善用户体验。
+
+| 模块名称 | 入门全免费设置 | 流式配置 |
+|:---:|:---:|:---:|
+| ASR(语音识别) | FunASR(本地) | 👍XunfeiStreamASR(讯飞流式) |
+| LLM(大模型) | glm-4-flash(智谱) | 👍qwen-flash(阿里百炼) |
+| VLLM(视觉大模型) | glm-4v-flash(智谱) | 👍qwen3.5-flash(阿里百炼) |
+| TTS(语音合成) | EdgeTTS(微软) | 👍HuoshanDoubleStreamTTS(火山流式) |
+| Intent(意图识别) | function_call(函数调用) | function_call(函数调用) |
+| Memory(记忆功能) | mem_local_short(本地短期记忆） | mem_local_short（本地短期记忆） |
+
+如果您关心各组件的耗时，请查阅[小智各组件性能测试报告](https://github.com/xinnan-tech/xiaozhi-performance-research)，可按报告中的测试方法在您的环境中实际测试。
+
+#### 🔧 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：
+
+| 工具名称 | 位置 | 使用方法 | 功能说明 |
+|:---:|:---|:---:|:---:|
+| 音频交互测试工具 | main》digital-human》index.html | 在 `main/digital-human` 执行 `python start.py` 后访问 `http://127.0.0.1:8006/index.html` | 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 | main》xiaozhi-server》performance_tester.py | 执行 `python performance_tester.py` | 测试ASR(语音识别)、LLM(大模型)、VLLM(视觉模型)、TTS(语音合成)三个核心模块的响应速度 |
+
+> 💡 提示：测试模型速度时，只会测试配置了密钥的模型。
+
+---
 ## 功能清单 ✨
-
 ### 已实现 ✅
-
-- **通信协议**  
-  基于 `xiaozhi-esp32` 协议，通过 WebSocket 实现数据交互。
-- **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
-- **多语言识别**  
-  支持国语、粤语、英语、日语、韩语（默认使用 FunASR）。
-- **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。
-- **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。
+![请参考-全模块安装架构图](docs/images/deploy2.png)
+| 功能模块 | 描述 |
+|:---:|:---|
+| 核心架构 | 基于[MQTT+UDP网关](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docs/mqtt-gateway-integration.md)、WebSocket、HTTP服务器，提供完整的控制台管理和认证系统 |
+| 语音交互 | 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 |
+| 声纹识别 | 支持多用户声纹注册、管理和识别，与ASR并行处理，实时识别说话人身份并传递给LLM进行个性化回应 |
+| 智能对话 | 支持多种LLM(大语言模型)，实现智能对话 |
+| 视觉感知 | 支持多种VLLM(视觉大模型)，实现多模态交互 |
+| 意图识别 | 支持外挂的大模型意图识别、大模型自主函数调用，提供插件化意图处理机制 |
+| 记忆系统 | 支持本地短期记忆、mem0ai接口记忆、PowerMem智能记忆，具备记忆总结功能 |
+| 知识库 | 支持RAGFlow知识库，让大模型判断需要调度知识库后再回答 |
+| 工具调用 | 支持客户端IOT协议、客户MCP协议、服务端MCP协议、MCP接入点协议、自定义工具函数 |
+| 指令下发 | 依托MQTT协议，支持从智控台将MCP指令下发到ESP32设备 |
+| 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；界面支持中文简体、中文繁体、英文显示 |
+| 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 |
+| 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 |
+| 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 |
 
 ### 正在开发 🚧
 
-- 对话记忆功能
-- 多种心情模式
-- 智控台webui
+想了解具体开发计划进度，[请点击这里](https://github.com/users/xinnan-tech/projects/3)。常见问题及相关教程，可参考[这个链接](./docs/FAQ.md)
+
+如果你是一名软件开发者，这里有一份[《致开发者的公开信》](docs/contributor_open_letter.md)，欢迎加入！
+
+---
+
+## 产品生态 👬
+小智是一个生态，当你使用这个产品时，也可以看看其他在这个生态圈的[优秀项目](https://github.com/78/xiaozhi-esp32/blob/main/README_zh.md#%E7%9B%B8%E5%85%B3%E5%BC%80%E6%BA%90%E9%A1%B9%E7%9B%AE)
 
-![图片](docs/images/webui.png)
 ---
 
 ## 本项目支持的平台/组件列表 📋
+### LLM 语言模型
 
-### LLM
-
-| 类型  |        平台名称        |         使用方式          |   收费模式   |                                备注                                 |
-|:---:|:------------------:|:---------------------:|:--------:|:-----------------------------------------------------------------:|
-| LLM |   阿里百炼 (AliLLM)    |      openai 接口调用      | 消耗 token |  [点击申请密钥](https://bailian.console.aliyun.com/?apiKey=1#/api-key)  |
-| LLM | 深度求索 (DeepSeekLLM) |      openai 接口调用      | 消耗 token |             [点击申请密钥](https://platform.deepseek.com/)              |
-| LLM |   智谱（ChatGLMLLM）   |      openai 接口调用      |    免费    | 虽然免费，仍需[点击申请密钥](https://bigmodel.cn/usercenter/proj-mgmt/apikeys) |
-| LLM |     OllamaLLM      |      ollama 接口调用      |  免费/自定义  |       需预先下载模型（`ollama pull`），服务地址：`http://localhost:11434`        |
-| LLM |      DifyLLM       |       dify 接口调用       | 消耗 token |                    本地化部署，注意配置提示词需在 Dify 控制台设置                     |
-| LLM |     GeminiLLM      |      gemini 接口调用      |    免费    |           [点击申请密钥](https://aistudio.google.com/apikey)            |
-| LLM |      CozeLLM       |       coze 接口调用       | 消耗 token |                     需提供 bot_id、user_id 及个人令牌                      |
-| LLM |   Home Assistant   | homeassistant语音助手接口调用 |    免费    |                        需提供home assistant令牌                        |
+| 使用方式 | 支持平台 | 免费平台 |
+|:---:|:---:|:---:|
+| openai 接口调用 | 阿里百炼、火山引擎、DeepSeek、智谱、Gemini、科大讯飞 | 智谱、Gemini |
+| ollama 接口调用 | Ollama | - |
+| dify 接口调用 | Dify | - |
+| fastgpt 接口调用 | Fastgpt | - |
+| coze 接口调用 | Coze | - |
+| xinference 接口调用 | Xinference | - |
+| homeassistant 接口调用 | HomeAssistant | - |
 
 实际上，任何支持 openai 接口调用的 LLM 均可接入使用。
 
 ---
 
-### TTS
+### VLLM 视觉模型
 
-| 类型  |          平台名称          | 使用方式 |   收费模式   |                                    备注                                     |
-|:---:|:----------------------:|:----:|:--------:|:-------------------------------------------------------------------------:|
-| TTS |        EdgeTTS         | 接口调用 |    免费    |                             默认 TTS，基于微软语音合成技术                             |
-| TTS | 火山引擎豆包 TTS (DoubaoTTS) | 接口调用 | 消耗 token | [点击创建密钥](https://console.volcengine.com/speech/service/8)；建议使用付费版本以获得更高并发 |
-| TTS |  CosyVoiceSiliconflow  | 接口调用 | 消耗 token |                         需申请硅基流动 API 密钥；输出格式为 wav                          |
-| TTS |       CozeCnTTS        | 接口调用 | 消耗 token |                        需提供 Coze API key；输出格式为 wav                         |
-| TTS |       FishSpeech       | 接口调用 |  免费/自定义  |                         本地启动 TTS 服务；启动方法见配置文件内说明                          |
-| TTS |     GPT_SOVITS_V2      | 接口调用 |  免费/自定义  |                         本地启动 TTS 服务，适用于个性化语音合成场景                          |
+| 使用方式 | 支持平台 | 免费平台 |
+|:---:|:---:|:---:|
+| openai 接口调用 | 阿里百炼、智谱ChatGLMVLLM | 智谱ChatGLMVLLM |
+
+实际上，任何支持 openai 接口调用的 VLLM 均可接入使用。
 
 ---
 
-### VAD
+### TTS 语音合成
+
+| 使用方式 | 支持平台 | 免费平台 |
+|:---:|:---:|:---:|
+| 接口调用 | EdgeTTS、科大讯飞、火山引擎、腾讯云、阿里云及百炼、CosyVoiceSiliconflow、TTS302AI、CozeCnTTS、GizwitsTTS、ACGNTTS、OpenAITTS、灵犀流式TTS、MinimaxTTS | 灵犀流式TTS、EdgeTTS、CosyVoiceSiliconflow(部分) |
+| 本地服务 | FishSpeech、GPT_SOVITS_V2、GPT_SOVITS_V3、Index-TTS、PaddleSpeech | Index-TTS、PaddleSpeech、FishSpeech、GPT_SOVITS_V2、GPT_SOVITS_V3 |
+
+---
+
+### VAD 语音活动检测
 
 | 类型  |   平台名称    | 使用方式 | 收费模式 | 备注 |
 |:---:|:---------:|:----:|:----:|:--:|
@@ -165,149 +309,67 @@ server:
 
 ---
 
-### ASR
+### ASR 语音识别
 
-| 类型  |   平台名称    | 使用方式 | 收费模式 | 备注 |
-|:---:|:---------:|:----:|:----:|:--:|
-| ASR |  FunASR   | 本地使用 |  免费  |    |
-| ASR | DoubaoASR | 接口调用 |  收费  |    |
+| 使用方式 | 支持平台 | 免费平台 |
+|:---:|:---:|:---:|
+| 本地使用 | FunASR、SherpaASR | FunASR、SherpaASR |
+| 接口调用 | FunASRServer、火山引擎、科大讯飞、腾讯云、阿里云、百度云、OpenAI ASR | FunASRServer |
 
 ---
 
-## 使用方式 🚀
+### Voiceprint 声纹识别
 
-### 一、[部署文档](./docs/Deployment.md)
-
-本项目支持以下三种部署方式，您可根据实际需求选择：
-
-1. [Docker 快速部署](./docs/Deployment.md)
-   适合快速体验，不需过多环境配置。缺点是，拉取镜像有点慢。
-
-2. [借助 Docker 环境运行部署](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E5%80%9F%E5%8A%A9docker%E7%8E%AF%E5%A2%83%E8%BF%90%E8%A1%8C%E9%83%A8%E7%BD%B2)
-   适用于已安装 Docker 且希望对代码进行自定义修改的用户。
-
-3. [本地源码运行](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%89%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E8%BF%90%E8%A1%8C)
-   适合熟悉 Conda 环境或希望从零搭建运行环境的用户。  
-   对于对响应速度要求较高的场景，推荐使用本地源码运行方式以降低额外开销。
-
-### 二、[固件编译](./docs/firmware-build.md)
-
-点这里查看[固件编译](./docs/firmware-build.md)的详细过程。
-
-编译成功且联网成功后，通过唤醒词唤醒小智，留意server端输出的控制台信息。
+| 使用方式 | 支持平台 | 免费平台 |
+|:---:|:---:|:---:|
+| 本地使用 | 3D-Speaker | 3D-Speaker |
 
 ---
 
-## 常见问题 ❓
+### Memory 记忆存储
 
-### 1、TTS 经常失败，经常超时 ⏰
+|   类型   |      平台名称       | 使用方式 |   收费模式    | 备注 |
+|:------:|:---------------:|:----:|:---------:|:--:|
+| Memory |     mem0ai      | 接口调用 | 1000次/月额度 |    |
+| Memory |     [powermem](./docs/powermem-integration.md)    | 本地总结 | 取决于LLM和DB |  OceanBase开源，支持智能检索  |
+| Memory | mem_local_short | 本地总结 |    免费     |    |
+| Memory |     nomem       | 无记忆模式 |    免费     |    |
 
-建议：如果 `EdgeTTS` 经常失败，请先检查是否使用了代理（梯子）。如果使用了，请尝试关闭代理后再试；  
-如果用的是火山引擎的豆包 TTS，经常失败时建议使用付费版本，因为测试版本仅支持 2 个并发。
+---
 
-### 2、我想通过小智控制电灯、空调、远程开关机等操作 💡
+### Intent 意图识别
 
-建议：在配置文件中将 `LLM` 设置为 `HomeAssistant`，通过 调用`HomeAssistant`接口实现相关控制。
+|   类型   |     平台名称      | 使用方式 |  收费模式   |          备注           |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Intent |  intent_llm   | 接口调用 | 根据LLM收费 |    通过大模型识别意图，通用性强     |
+| Intent | function_call | 接口调用 | 根据LLM收费 | 通过大模型函数调用完成意图，速度快，效果好 |
+| Intent |    nointent   | 无意图模式 |    免费     |    不进行意图识别，直接返回对话结果     |
 
-### 3、我说话很慢，停顿时小智老是抢话 🗣️
+---
 
-建议：在配置文件中找到如下部分，将 `min_silence_duration_ms` 的值调大（例如改为 `1000`）：
+### Rag 检索增强生成
 
-```yaml
-VAD:
-  SileroVAD:
-    threshold: 0.5
-    model_dir: models/snakers4_silero-vad
-    min_silence_duration_ms: 700  # 如果说话停顿较长，可将此值调大
-```
-
-### 4、为什么我说的话，小智识别出来很多韩文、日文、英文？🇰🇷
-
-建议：检查一下`models/SenseVoiceSmall`是否已经有`model.pt`
-文件，如果没有就要下载，查看这里[下载语音识别模型文件](docs/Deployment.md#模型文件)
-
-### 5、为什么会出现“TTS 任务出错 文件不存在”？📁
-
-建议：检查一下是否正确使用`conda` 安装了`libopus`和`ffmpeg`库。
-
-如果没有安装，就安装
-
-```
-conda install conda-forge::libopus
-conda install conda-forge::ffmpeg
-```
-
-### 6、如何提高小智对话响应速度？ ⚡
-
-本项目默认配置为低成本方案，建议初学者先使用默认免费模型，解决“跑得动”的问题，再优化“跑得快”。  
-如需提升响应速度，可尝试更换各组件。以下为各组件的响应速度测试数据（仅供参考，不构成承诺）：
-
-| 影响因素  |       因素值        | 
-|:-----:|:----------------:|
-| 测试地点  |    广东省广州市海珠区     |
-| 测试时间  | 2025年2月19日 12:52 |
-| 宽带运营商 |       中国联通       |
-
-测试方法：
-
-1、把各组件的密钥配置上去，只有配置了密钥的组件才参与测试。
-
-2、配置完密钥后，执行以下方法
-
-```
-# 进入项目根目录，执行以下命令：
-conda activate xiaozhi-esp32-server
-python performance_tester.py 
-```
-
-生成报告如下
-
-LLM 性能排行:
-
-| 模块名称       | 平均首Token时间 | 平均总响应时间 |
-|:-----------|:-----------|:--------|
-| AliLLM     | 0.547s     | 1.485s  |
-| ChatGLMLLM | 0.677s     | 3.057s  |
-| OllamaLLM  | 0.003s     | 0.003s  |
-
-TTS 性能排行:
-
-| 模块名称                 | 平均合成时间 |
-|----------------------|--------|
-| EdgeTTS              | 1.019s |
-| DoubaoTTS            | 0.503s |
-| CosyVoiceSiliconflow | 3.732s |
-
-推荐配置组合 (综合响应速度):
-
-| 组合方案                          | 综合得分  | LLM首Token | TTS合成  |
-|-------------------------------|-------|-----------|--------|
-| AliLLM + DoubaoTTS            | 0.539 | 0.547s    | 0.503s |
-| AliLLM + EdgeTTS              | 0.642 | 0.547s    | 1.019s |
-| ChatGLMLLM + DoubaoTTS        | 0.642 | 0.677s    | 0.503s |
-| ChatGLMLLM + EdgeTTS          | 0.745 | 0.677s    | 1.019s |
-| AliLLM + CosyVoiceSiliconflow | 1.184 | 0.547s    | 3.732s |
-
-### 结论 🔍
-
-`2025年2月19日`，如果我的电脑在`广东省广州市海珠区`，且使用的是`中国联通`网络，我会优先使用：
-
-- LLM：`AliLLM`
-- TTS：`DoubaoTTS`
-
-### 7、更多问题，可联系我们反馈 💬
-
-![图片](docs/images/wechat.jpg)
+|   类型   |     平台名称      | 使用方式 |  收费模式   |          备注           |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Rag |  ragflow   | 接口调用 | 根据切片、分词消耗的token收费 |    借助RagFlow的检索增强生成功能，提供更准确的对话回复     |
 
 ---
 
 ## 鸣谢 🙏
 
-- 本项目受 [百聆语音对话机器人](https://github.com/wwbin2017/bailing) 启发，并在其基础上实现。
-- 感谢 [腾讯云](https://cloud.tencent.com/) 提供免费 Docker 镜像空间。
-- 感谢 [十方融海](https://www.tenclass.com/) 对小智通讯协议提供的详尽文档支持。
+| Logo | 项目/公司 | 说明 |
+|:---:|:---:|:---|
+| <img src="./docs/images/logo_bailing.png" width="160"> | [百聆语音对话机器人](https://github.com/wwbin2017/bailing) | 本项目受[百聆语音对话机器人](https://github.com/wwbin2017/bailing)启发，并在其基础上实现 |
+| <img src="./docs/images/logo_tenclass.png" width="160"> | [十方融海](https://www.tenclass.com/) | 感谢[十方融海](https://www.tenclass.com/)为小智生态制定了标准的通讯协议、多设备兼容性方案及高并发场景实践示范；为本项目提供了全链路技术文档支持 |
+| <img src="./docs/images/logo_xuanfeng.png" width="160"> | [玄凤科技](https://github.com/Eric0308) | 感谢[玄凤科技](https://github.com/Eric0308)贡献函数调用框架、MCP通信协议及插件化调用机制的实现代码，通过标准化的指令调度体系与动态扩展能力，显著提升了前端设备(IoT)的交互效率和功能延展性 |
+| <img src="./docs/images/logo_junsen.png" width="160"> | [huangjunsen](https://github.com/huangjunsen0406) | 感谢[huangjunsen](https://github.com/huangjunsen0406) 贡献`智控台移动端`模块，实现了跨平台移动设备的高效控制与实时交互，大幅提升了系统在移动场景下的操作便捷性和管理效率 |
+| <img src="./docs/images/logo_huiyuan.png" width="160"> | [汇远设计](http://ui.kwd988.net/) | 感谢[汇远设计](http://ui.kwd988.net/)为本项目提供专业视觉解决方案，用其服务超千家企业的设计实战经验，赋能本项目产品用户体验 |
+| <img src="./docs/images/logo_qinren.png" width="160"> | [西安勤人信息科技](https://www.029app.com/) | 感谢[西安勤人信息科技](https://www.029app.com/)深化本项目视觉体系，确保整体设计风格在多场景应用中的一致性和扩展性 |
+| <img src="./docs/images/logo_contributors.png" width="160"> | [代码贡献者](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors) | 感谢[所有代码贡献者](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors)贡献者，你们的付出让项目更加健壮和强大。 |
+
 
 <a href="https://star-history.com/#xinnan-tech/xiaozhi-esp32-server&Date">
+
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date&theme=dark" />
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README_en.md

@@ -1,432 +0,0 @@
-![图片](docs/images/banner.png)
-
-# Xiaozhi ESP-32 Back-end Service (xiaozhi-esp32-server)
-
-（[中文](README.md) | English）
-
-This project provides backend services for the open-source smart hardware
-project [xiaozhi-esp32](https://github.com/78/xiaozhi-esp32)。Implemented in Python following
-the[Xiaozhi Communication Protocol](https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh)。
-
-## Target Audience
-
-This project requires compatible esp32 hardware devices. If you have purchased esp32 hardware, successfully connected to
-Xiage's deployed backend, and wish to independently set up the `xiaozhi-esp32` backend service, this project is for
-you.
-
-To see a demo, watch this video:
-
-<a href="https://www.bilibili.com/video/BV1FMFyejExX">
- <picture>
-   <img alt="小智esp32连接自己的后台模型" src="docs/images/demo.png" />
- </picture>
-</a>
-
-To fully experience this project, follow these steps:
-
-- Prepare hardware compatible with the `xiaozhi-esp32` project. For supported
-  models, [click here](https://rcnv1t9vps13.feishu.cn/wiki/DdgIw4BUgivWDPkhMj1cGIYCnRf).
-- Use a computer/server with at least 4-core CPU and 8GB RAM to run this project. After deployment, you'll see the
-  service endpoint address in the console.
-- Download the `xiaozhi-esp32` project, replace the default `endpoint address` with your own, compile, and flash the
-  firmware to your device.
-- Start the device and check your server console logs to verify successful connection.
-
-## Warning
-
-This project has been established for a short time and has not passed the network security assessment, so please do not
-use it in the production environment.
-
-## Feature List
-
-## Implemented
-
-- `xiaozhi-esp32` WebSocket communication protocol
-- Supports wake-word initiated dialogue, manual dialogue, and real-time interruption of dialogue.
-- Support for 5 languages: Mandarin, Cantonese, English, Japanese, Korean (FunASR - default)
-- Flexible LLM switching (openai:ChatGLM - default, Aliyun, DeepSeek; dify:Dify)
-- Flexible TTS switching (EdgeTTS - default, ByteDance Doubao TTS)
-
-## In Progress
-
-- Sleep mode after inactivity
-- Dialogue memory
-- Change the mood mode
-
-## Supported Services
-
-| Type | Service    |  Usage   | Pricing Model	 | Notes                                                                      |
-|:-----|:-----------|:--------:|:---------------|:---------------------------------------------------------------------------|
-| LLM  | Aliyun     | openai API call | Token-based    | [Apply for API Key](https://bailian.console.aliyun.com/?apiKey=1#/api-key) |
-| LLM  | DeepSeek   | openai API call | Token-based    | [Apply for API Key](https://platform.deepseek.com/)                        |
-| LLM  | Bigmodel   | openai API call | Free           | [Create API Key](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)         |
-| LLM  | Dify       | dify API call | Token-based    | Self-hosted                                                                |
-| TTS  | HuoshanTTS | API call | Token-based    | [Create API Key](https://console.volcengine.com/speech/service/8)          |
-| TTS  | EdgeTTS    | API call | Free           |                                                                            |
-| VAD  | SileroVAD  |  Local   | Free           |                                                                            |
-| ASR  | FunASR     |  Local   | Free           |                                                                            |
-
-In fact, any LLM that supports OpenAI API calls can be integrated and used.
-
-# Deployment
-
-This project supports rapid deployment of docker and local source code operation. If you want to have a quick
-experience, it is recommended to use docker to deploy. If you want to have an in-depth understanding of this project, it
-is recommended to run the local source code.
-
-## Method 1: Quick deployment of docker
-
-The docker image has supported the CPU of x86 architecture and arm64 architecture, and supports running on Chinese
-operating systems.
-
-1. Install docker
-
-If your computer has not installed docker, you can follow the tutorial here to install
-it:[Install docker](https://www.runoob.com/docker/ubuntu-docker-install.html)
-
-2. Create a directory
-
-After installation, you need to find a directory for the configuration file for this project. Let's call it the
-`project directory` for the time being. This directory is preferably a newly created empty directory.
-
-3. Download the configuration file
-
-Open with a browser[This link](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/config.yaml)。
-
-On the right side of the page, find the button named `RAW`, next to the `RAW` button, find the download icon, click the
-Download button, and download the `config.yaml` file. Download the file to your `project directory`.
-
-4. Configure Project
-
-Modify the `config.yaml` file to configure the various parameters required for this project. The default LLM uses
-`ChatGLMLLM`, you need to configure the key to start.
-The default TTS uses `EdgeTTS`. This does not require configuration. If you need to replace it with`Doubao TTS`, you
-need to
-configure the key.
-
-Configuration description: This is the default component of each function, such as LLM default to use the `ChatGLMLLM`
-model. If you need to switch the model, it is the corresponding name.
-
-The default configuration of this project is only the lowest operating cost configuration（`glm-4-flash`and`EdgeTTS`are
-free），If you need to be better and faster, you need to combine the use of the deployment environment to switch the use
-of each component。
-
-```
-selected_module:
-  ASR: FunASR
-  VAD: SileroVAD
-  LLM: ChatGLMLLM
-  TTS: EdgeTTS
-```
-
-For example, to modify the components used by the `LLM`, it depends on which `LLM` API interfaces are supported by this project. Currently, the supported ones are `openai` and `dify`. We welcome validation and support for more LLM platforms' interfaces.
-When using it, change the `selected_module` to the corresponding name of the following LLM configurations:
-
-```
-LLM:
-  AliLLM:
-    type: openai
-    ...
-  DeepSeekLLM:
-    type: openai
-    ...
-  ChatGLMLLM:
-    type: openai
-    ...
-  DifyLLM:
-    type: openai
-    ...
-```
-
-Some services, for example, if you use the TTS` of the `dify` and` bean bags, you need a key, remember to add the
-configuration file!
-
-5. Execute the docker command
-
-Open the command line tool, `cd` enter your `project directory`, and execute the following command
-
-```
-#If you are Linux, execute
-ls
-#If you are Windows, execute
-dir
-```
-
-If you can see the `config.yaml` file, you have indeed entered the `project directory`, and then execute the following
-command:
-
-```
-docker run -d --name xiaozhi-esp32-server --restart always --security-opt seccomp:unconfined -p 8000:8000 -v $(pwd)/config.yaml:/opt/xiaozhi-esp32-server/config.yaml ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest
-```
-
-If executed for the first time, it may take several minutes, and you have to be patient to wait for it to complete the
-pull. After normal pulling is completed, you can execute the following command on the command line to see if the service
-is started successfully.
-
-```
-docker ps
-```
-
-If you can see `xiaozhi-server`, it means that the service starts successfully. Then you can further execute the
-following command to view the service log
-
-```
-docker logs -f xiaozhi-esp32-server
-```
-
-If you can see, similar to the following logs, it is a sign that the service of this project is successfully launched.
-
-```
-2025-xx-xx xx:51:59,492 - core.server - INFO - Server is running at ws://xx.xx.xx.xxx:8000
-2025-xx-xx xx:51:59,516 - websockets.server - INFO - server listening on 0.0.0.0:8000
-```
-
-Next, you can start `compiling esp32 firmware`. Please go down and turn to the relevant chapter on
-`compiling esp32 firmware`. So since you are deploying with docker, you have to check the IP of your native computer by
-yourself.
-Normally, assuming your ip is `192.168.1.25`, then your interface address is: `ws://192.168.1.25:8000`. This information
-is very useful, and it is required to `compile esp32 firmware` later.
-
-## Method 2 : Local Source Code Deployment
-
-### 1.Install Prerequisites
-
-This project uses 'conda' to manage dependencies, and after installation, start executing the following commands:
-
-```
-conda remove -n xiaozhi-esp32-server --all -y
-conda create -n xiaozhi-esp32-server python=3.10 -y
-conda activate xiaozhi-esp32-server
-```
-
-After executing the above command, if your computer is Windows or Mac, execute the following statement:
-
-```
-conda activate xiaozhi-esp32-server
-conda install conda-forge::libopus
-conda install conda-forge::ffmpeg
-```
-
-If your computer is ubuntu, execute the following statement:
-
-```
-apt-get install libopus0 ffmpeg 
-```
-
-### 2.Install Dependencies
-
-```
-# Clone the project
-cd xiaozhi-esp32-server
-conda activate xiaozhi-esp32-server
-pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
-pip install -r requirements.txt
-```
-
-### 3.Download ASR Model
-
-Download [SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt) to
-`model/SenseVoiceSmall`.
-
-By default, the `SenseVoiceSmall` model is used to convert voice to text. Because the model is large, it needs to be
-downloaded independently. After downloading, place the `model.pt` file in the `model/SenseVoiceSmall` directory. Choose
-any of the following two download routes.
-
-- Line 1: Download Ali Magic
-  Tower[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)
-- Line 2: Baidu Netdisk download[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna)
-  提取码: `qvna`
-
-### 4.Configure Project
-
-Modify the `config.yaml` file to configure the various parameters required for this project. The default LLM uses
-`ChatGLMLLM`, you need to configure the key to start.
-The default TTS uses `EdgeTTS`. This does not require configuration. If you need to replace it with`Doubao TTS`, you
-need to
-configure the key.
-
-Configuration description: This is the default component of each function, such as LLM default to use the `ChatGLMLLM`
-model. If you need to switch the model, it is the corresponding name.
-
-The default configuration of this project is only the lowest operating cost configuration（`glm-4-flash`and`EdgeTTS`are
-free），If you need to be better and faster, you need to combine the use of the deployment environment to switch the use
-of each component。
-
-```
-selected_module:
-  ASR: FunASR
-  VAD: SileroVAD
-  LLM: ChatGLMLLM
-  TTS: EdgeTTS
-```
-
-For example, to modify the components used by the `LLM`, it depends on which `LLM` API interfaces are supported by this project. Currently, the supported ones are `openai` and `dify`. We welcome validation and support for more LLM platforms' interfaces.
-When using it, change the `selected_module` to the corresponding name of the following LLM configurations:
-
-```
-LLM:
-  AliLLM:
-    type: openai
-    ...
-  DeepSeekLLM:
-    type: openai
-    ...
-  ChatGLMLLM:
-    type: openai
-    ...
-  DifyLLM:
-    type: openai
-    ...
-```
-
-Some services, for example, if you use the TTS` of the `dify` and` bean bags, you need a key, remember to add the
-configuration file!
-
-### 5.Run the Project
-
-Run the Project
-
-```
-# Make sure to execute in the root directory of this project
-conda activate xiaozhi-esp32-server
-python app.py
-```
-
-You'll see the WebSocket endpoint in logs:
-
-```
-2025-xx-xx xx:51:59,492 - core.server - INFO - Server is running at ws://192.168.1.25:8000
-2025-xx-xx xx:51:59,516 - websockets.server - INFO - server listening on 0.0.0.0:8000
-```
-
-Among them, the `ws://192.168.1.25:8000` is the interface address provided by this project. Of course, your own machine
-is different from mine. Remember to find your own address.
-
-# Compile ESP32 Firmware
-
-1. Download `xiaozhi-esp32` project, configure the project environment according to this
-   tutorial [" Windows builds ESP IDF 5.3.2 Development Environment and Compiles Xiaozhi "](https://icnynnzcwou8.feishu.cn/wiki/JEYDwTTALi5s2zkGlFGcDiRknXf)
-   Cure
-
-2. Open the `xiaozhi-esp32/main/kconfig.projbuild` file, find the content of the` websocket_url` `default`, change the
-   ` wss: // api.tenclass.net` to your own address, such as
-
-Before modification:
-
-```
-config WEBSOCKET_URL
-    depends on CONNECTION_TYPE_WEBSOCKET
-    string "Websocket URL"
-    default "wss://api.tenclass.net/xiaozhi/v1/"
-    help
-        Communication with the server through websocket after wake up.
-```
-
-After modification (example):
-
-```
-config WEBSOCKET_URL
-    depends on CONNECTION_TYPE_WEBSOCKET
-    string "Websocket URL"
-    default "ws://192.168.1.25:8000/xiaozhi/v1/"
-    help
-        Communication with the server through websocket after wake up.
-```
-
-3. Configure build settings:
-
-```
-# The terminal command line enters the root directory of xiaozhi-esp32
-cd xiaozhi-esp32
-# For example, the board I use is ESP32S3, so the compile target is ESP32S3. If your board is other models, please replace it with the corresponding model
-idf.py set-target esp32s3
-# Enter the menu configuration
-idf.py menuconfig
-```
-
-![图片](docs/images/build_setting01.png)
-
-After entering the menu configuration, then enter `xiaozhi assistant`, set the` connection_type` to `websocket`
-Go back to the main menu, then enter `xiaozhi assistant`, set the `BOARD_TYPE` of your board
-Save exit and return to the terminal command line.
-
-![图片](docs/images/build_setting02.png)
-
-4. Build and package:
-
-```
-idf.py build
-cd scripts
-python release.py
-```
-
-After the compilation is successful, the firmware file `merged-binary.bin` is generated in the` build` directory in the
-project root directory.
-This `merged-binary.bin` is the firmware file that will be recorded on the hardware.
-
-6. Flash
-   Connect the ESP32 device to the computer, use the Chrome browser, and open the following URL
-
-```
-https://espressif.github.io/esp-launchpad/
-```
-
-Open this
-tutorial, [Flash Tools/Web -side Burning Folding Step (No IDF Development Environment)](https://ccnphfhqs21z.feishu.cn/wiki/Zpz4wXBtdimBrLk25WdcXzxcnNS).
-Turn to: `Method 2: ESP-LAUNCHPAD browser web-end burning`, start from
-`3. Burning firmware/download to the development board`, follow the tutorial operation.
-
-# FAQ
-
-## 1、TTS often fails, often overtime
-
-Suggestion: If the `Edgetts` is slow or often fails, you can replace it with a bean bag TTS` with a volcanic engine. If
-both are slow, the network environment may need to be optimized.
-
-## 2、Big model reply is a bit slow
-
-Suggestions: Both big models and TTS are dependent interfaces. If the network environment is not good, you can consider
-changing the local model. Or try to switch different interface models.
-
-## 3、Why is my ChatGLMLLM replying to a bit? Obviously it is Xiaozhi, but treats me as Xiaozhi.
-
-Suggestion: You can modify the prompts in the configuration file first. You can also replace the free `GLM-4-FLASH` to
-the model of other toll versions of `ChatGlm`.
-
-## 4、I want to control the operation of electric lights, air conditioners, remote switching and other operations through Xiaozhi.
-
-Suggestion: In the configuration file, set the `LLM` to`DifyLLM`, and then arrange the smart application by the
-`Dify`.
-
-## 5、I said very slowly, I paused, Xiaozhi always grabbed me, what to do.
-
-Suggestion: In the configuration file, find this section, change the `min_silence_duration_ms` value, such as change to
-` 1000`.
-
-```
-VAD:
-  SileroVAD:
-    threshold: 0.5
-    model_dir: models/snakers4_silero-vad
-    min_silence_duration_ms: 700  # 如果说话停顿比较长，可以把这个值设置大一些
-```
-
-## 6、For more questions, contact us to feedback
-
-![图片](docs/images/wechat.jpg)
-
-# Acknowledgments
-
-- This project is inspired by the [Bailin Voice Dialogue Robot](https://github.com/wwbin2017/bailing) project, and the
-  basic idea of the project is completed。
-- Thanks to [Tencent Cloud] (https://cloud.tencent.com/) for providing free docker space for this project。
-- Thanks to [tenclass](https://www.tenclass.com/)Provide adequate documentation support on Xiaozhi Communication
-  Protocol。
-
-<a href="https://star-history.com/#xinnan-tech/xiaozhi-esp32-server&Date">
- <picture>
-   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date&theme=dark" />
-   <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" />
- </picture>
-</a>

ZhiKongTaiWeb/.env.development

@@ -1 +0,0 @@
-VITE_API_BASE_URL='http://127.0.0.1:8002'

ZhiKongTaiWeb/.env.production

@@ -1 +0,0 @@
-VITE_API_BASE_URL=''  # 空字符串表示使用当前域名和端口

ZhiKongTaiWeb/.gitignore

@@ -1,24 +0,0 @@
-# Logs
-logs
-*.log
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-pnpm-debug.log*
-lerna-debug.log*
-
-node_modules
-dist
-dist-ssr
-*.local
-
-# Editor directories and files
-.vscode/*
-!.vscode/extensions.json
-.idea
-.DS_Store
-*.suo
-*.ntvs*
-*.njsproj
-*.sln
-*.sw?

ZhiKongTaiWeb/README.md

@@ -1,88 +0,0 @@
-# Vue 3 + Vite 项目配置文档
-
-## 开发环境配置
-
-### 使用 Poetry 配置开发环境
-
-在项目根目录中执行以下命令安装 Python 依赖：
-
-```sh
-poetry install
-```
-
----
-
-## 安装项目依赖
-
-你可以选择以下任意一个包管理工具（`npm`、`yarn` 或 `pnpm`）来管理项目依赖。
-
-### 通用命令
-
-- `install`：安装项目依赖
-- `dev`：同时启动前后端
-- `dev:ui`：启动前端
-- `dev:api`：启动后端
-- `dev:d`：在 Docker 环境下同时启动前后端
-- `build`：打包项目
-
----
-
-### 使用 npm
-
-1. 安装依赖：
-
-   ```sh
-   npm install
-   ```
-
-2. 启动开发模式：
-
-   ```sh
-   npm run dev
-   ```
-
-3. 打包项目：
-
-   ```sh
-   npm run build
-   ```
-
-### 使用 yarn
-
-1. 安装依赖：
-
-   ```sh
-   yarn install
-   ```
-
-2. 启动开发模式：
-
-   ```sh
-   yarn dev
-   ```
-
-3. 打包项目：
-
-   ```sh
-   yarn build
-   ```
-
-### 使用 pnpm
-
-1. 安装依赖：
-
-   ```sh
-   pnpm install
-   ```
-
-2. 启动开发模式：
-
-   ```sh
-   pnpm run dev
-   ```
-
-3. 打包项目：
-
-   ```sh
-   pnpm run build
-   ```

ZhiKongTaiWeb/index.html

@@ -1,27 +0,0 @@
-<!doctype html>
-<html lang="en" style="height: 100%;">
-<head>
-    <meta charset="UTF-8"/>
-    <link rel="icon" href="/favicon.ico"/>
-    <meta name="viewport" content="width=device-width, initial-scale=1.0"/>
-    <title>智控台</title>
-    <style>
-        html, body {
-            margin: 0;
-            padding: 0;
-            height: 100%;
-            width: 100%;
-            overflow: hidden;
-        }
-
-        #app {
-            height: 100%;
-            width: 100%;
-        }
-    </style>
-</head>
-<body>
-<div id="app"></div>
-<script type="module" src="/src/main.js"></script>
-</body>
-</html>

ZhiKongTaiWeb/package.json

@@ -1,24 +0,0 @@
-{
-  "name": "zhikongtaiweb",
-  "private": true,
-  "version": "0.0.0",
-  "type": "module",
-  "scripts": {
-    "dev": "concurrently -n 'Frontend,Backend' -c 'blue,green' 'yarn run dev:ui' 'npm run dev:api'",
-    "dev:ui": "vite",
-    "dev:api": "cd .. && poetry run python app.py",
-    "dev:d": "docker exec xiaozhi-env poetry run python app.py",
-    "build": "vite build",
-    "preview": "vite preview"
-  },
-  "dependencies": {
-    "axios": "^1.7.9",
-    "vue": "^3.5.10",
-    "vue-router": "^4.0.0"
-  },
-  "devDependencies": {
-    "@vitejs/plugin-vue": "^5.1.4",
-    "concurrently": "^9.1.2",
-    "vite": "^5.4.8"
-  }
-}

ZhiKongTaiWeb/public/vite.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>

ZhiKongTaiWeb/src/App.vue

@@ -1,73 +0,0 @@
-<template>
-  <div id="app">
-    <div class="app-content">
-      <router-view></router-view>
-    </div>
-    <Footer />
-  </div>
-</template>
-
-<script>
-import Footer from './components/Footer.vue';
-
-export default {
-  name: 'App',
-  components: { 
-    Footer 
-  }
-};
-</script>
-
-<style>
-#app {
-  font-family: Avenir, Helvetica, Arial, sans-serif;
-  -webkit-font-smoothing: antialiased;
-  -moz-osx-font-smoothing: grayscale;
-  color: #2c3e50;
-  min-height: 100vh;
-  display: flex;
-  flex-direction: column;
-}
-
-.app-content {
-  flex: 1;
-  display: flex;
-  flex-direction: column;
-  min-height: 0; /* 允许内容区域收缩 */
-}
-
-/* 登录注册页面的布局 */
-.auth-layout {
-  align-items: center;
-  justify-content: center;
-  padding: 20px;
-}
-
-/* 主要页面的布局 */
-.main-layout {
-  flex: 1;
-  display: flex;
-  flex-direction: column;
-  min-height: 0; /* 允许内容区域收缩 */
-}
-
-/* 添加全局滚动条样式 */
-::-webkit-scrollbar {
-  width: 8px;
-  height: 8px;
-}
-
-::-webkit-scrollbar-track {
-  background: #f1f1f1;
-  border-radius: 4px;
-}
-
-::-webkit-scrollbar-thumb {
-  background: #ccc;
-  border-radius: 4px;
-}
-
-::-webkit-scrollbar-thumb:hover {
-  background: #999;
-}
-</style>

ZhiKongTaiWeb/src/assets/vue.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="37.07" height="36" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 198"><path fill="#41B883" d="M204.8 0H256L128 220.8L0 0h97.92L128 51.2L157.44 0h47.36Z"></path><path fill="#41B883" d="m0 0l128 220.8L256 0h-51.2L128 132.48L50.56 0H0Z"></path><path fill="#35495E" d="M50.56 0L128 133.12L204.8 0h-47.36L128 51.2L97.92 0H50.56Z"></path></svg>

ZhiKongTaiWeb/src/components/DeviceCard.vue

@@ -1,206 +0,0 @@
-<template>
-  <div class="device-card">
-    <div class="device-header">
-      <h2 class="device-id">{{ deviceId }} <span class="note">[{{ deviceNote || '备注' }}]</span></h2>
-    </div>
-    
-    <div class="device-details">
-      <p class="device-type">设备型号：{{ deviceType }}</p>
-      <p class="device-role">角色昵称：{{ deviceRole }}</p>
-      <p class="device-modules">
-        当前模型：
-        <span class="module-item">LLM: {{ selectedModules?.LLM || '-' }}</span>
-        <span class="module-item">TTS: {{ selectedModules?.TTS || '-' }}</span>
-      </p>
-      <p class="last-activity">最近对话：{{ lastActivity }}</p>
-    </div>
-    
-    <div class="device-actions">
-      <button class="action-btn primary" @click="handleConfigure">配置角色</button>
-      <button class="action-btn" @click="$emit('voiceprint')">声纹识别</button>
-      <button class="action-btn" @click="$emit('history')">历史对话</button>
-      <div class="delete-container">
-        <button class="action-btn danger" @click="handleDelete">
-          <i class="icon-delete"></i> 删除设备
-        </button>
-        <div class="delete-warning">删除后设备配置将不可恢复</div>
-      </div>
-    </div>
-  </div>
-</template>
-
-<script setup>
-import { ref, watch, computed } from 'vue';
-import SwitchToggle from './SwitchToggle.vue';
-
-const props = defineProps({
-  deviceId: String,
-  deviceNote: String,
-  deviceType: {
-    type: String,
-    default: '未知型号（待实现）'
-  },
-  lastActivity: {
-    type: String,
-    default: '3 天前'
-  },
-  selectedModules: {
-    type: Object,
-    default: () => ({
-      LLM: '-',
-      TTS: '-',
-      ASR: '-',
-      VAD: '-'
-    })
-  },
-  deviceConfig: {
-    type: Object,
-    default: () => ({})
-  }
-});
-
-const deviceRole = computed(() => {
-  return props.deviceConfig?.nickname || '小智';
-});
-
-// Store device config when it changes
-watch(() => props.selectedModules, (newValue) => {
-  if (props.deviceId) {
-    localStorage.setItem(`deviceConfig_${props.deviceId}`, JSON.stringify({
-      selected_module: newValue
-    }));
-  }
-}, { deep: true });
-
-const otaEnabled = ref(false);
-
-const emit = defineEmits(['configure', 'voiceprint', 'history', 'delete']);
-
-const handleDelete = () => {
-  if (confirm('确认要删除此设备吗？\n\n警告：删除后设备所有配置将不可恢复！')) {
-    emit('delete');
-  }
-};
-
-const handleConfigure = () => {
-  // 保存设备配置到 localStorage，确保 RoleSetting 可以访问
-  if (props.deviceId && props.deviceConfig) {
-    localStorage.setItem(`deviceConfig_${props.deviceId}`, JSON.stringify({
-      selected_module: props.selectedModules,
-      prompt: props.deviceConfig.prompt || '',
-      nickname: props.deviceConfig.nickname || '小智'
-    }));
-  }
-  emit('configure');
-};
-</script>
-
-<style scoped>
-.device-card {
-  background: white;
-  border-radius: 4px;
-  padding: 20px;
-  box-shadow: 0 1px 3px rgba(0,0,0,0.1);
-  margin-bottom: 16px;
-}
-
-.device-id {
-  font-size: 18px;
-  font-weight: bold;
-  margin-bottom: 16px;
-}
-
-.note {
-  color: #4178EE;
-  font-size: 14px;
-  font-weight: normal;
-}
-
-.device-details p {
-  margin-bottom: 12px;
-}
-
-.ota-upgrade {
-  display: inline-flex;
-  align-items: center;
-  margin-left: 16px;
-}
-
-.device-actions {
-  display: flex;
-  margin-top: 20px;
-}
-
-.action-btn {
-  padding: 8px 16px;
-  margin-right: 12px;
-  border: 1px solid #ddd;
-  border-radius: 4px;
-  background: white;
-  cursor: pointer;
-}
-
-.action-btn.primary {
-  background: #4178EE;
-  color: white;
-  border-color: #4178EE;
-}
-
-.action-btn.danger {
-  background: #fff3f3;
-  border-color: #ffa4a4;
-  color: #f56c6c;
-}
-
-.action-btn.danger:hover {
-  background: #fde2e2;
-  border-color: #f56c6c;
-}
-
-.device-modules {
-  margin-bottom: 12px;
-  color: #666;
-}
-
-.module-item {
-  display: inline-block;
-  margin-right: 16px;
-  padding: 4px 8px;
-  background: #f5f7fa;
-  border-radius: 4px;
-  font-size: 0.9em;
-}
-
-.device-role {
-  color: #666;
-  margin-bottom: 12px;
-}
-
-.delete-container {
-  position: relative;
-  margin-left: auto;  /* Push delete button to the right */
-}
-
-.delete-warning {
-  position: absolute;
-  bottom: calc(100% + 5px);  /* Position above the button */
-  left: 50%;
-  transform: translateX(-50%);
-  white-space: nowrap;
-  background: #fff3f3;
-  padding: 4px 8px;
-  border-radius: 4px;
-  border: 1px solid #ffa4a4;
-  font-size: 12px;
-  color: #f56c6c;
-  display: none;
-}
-
-.delete-container:hover .delete-warning {
-  display: block;
-}
-
-.icon-delete {
-  margin-right: 4px;
-}
-</style>

ZhiKongTaiWeb/src/components/Footer.vue

@@ -1,15 +0,0 @@
-<template>
-  <footer class="footer">
-    <div class="copyright">© 2025 小智 AI 管理后台</div>
-  </footer>
-</template>
-
-<style scoped>
-.footer {
-  text-align: center;
-  padding: 16px;
-  color: #666;
-  font-size: 12px;
-  background: #f0f2f5;
-}
-</style>

ZhiKongTaiWeb/src/components/Login.vue

@@ -1,149 +0,0 @@
-<template>
-    <div class="login-container">
-      <h1>登录</h1>
-      <form @submit.prevent="handleLogin">
-        <div class="form-group">
-          <label for="username">用户名</label>
-          <input type="text" v-model="username" id="username" required />
-        </div>
-        <div class="form-group">
-          <label for="password">密码</label>
-          <input type="password" v-model="password" id="password" required />
-        </div>
-        <button type="submit" :disabled="isLoading">登录</button>
-      </form>
-      <p>还没注册账户? <router-link to="/register">点击注册</router-link></p>
-    </div>
-  </template>
-  
-<script setup>
-import { ref } from 'vue';
-import { useRouter } from 'vue-router';
-import apiClient from '../utils/api';
-
-const router = useRouter();
-const username = ref('');
-const password = ref('');
-const isLoading = ref(false);
-
-const handleLogin = async () => {
-  if (!username.value || !password.value) {
-    alert('请输入用户名和密码！');
-    return;
-  }
-
-  isLoading.value = true;
-  try {
-    const response = await apiClient.post('/api/login', {
-      username: username.value,
-      password: password.value
-    });
-
-    const data = response.data;
-    
-    if (data.success) {
-      localStorage.setItem('session_id', data.session_id);
-      localStorage.setItem('isLoggedIn', 'true');
-      router.push('/panel');
-    } else {
-      alert(data.message || '登录失败');
-    }
-  } catch (error) {
-    console.error('Login error:', error);
-    alert('登录失败，请检查网络连接');
-  } finally {
-    isLoading.value = false;
-  }
-};
-</script>
-
-<style scoped>
-.login-container {
-  max-width: 420px;
-  margin: 20px auto;
-  padding: 40px 50px;
-  border: none;
-  border-radius: 12px;
-  background-color: #ffffff;
-  box-shadow: 0 8px 24px rgba(0, 0, 0, 0.12);
-  transition: all 0.3s ease;
-}
-
-h1 {
-  text-align: center;
-  color: #2c3e50;
-  font-size: 28px;
-  margin-bottom: 25px;
-  font-weight: 600;
-}
-
-.form-group {
-  margin-bottom: 20px;
-}
-
-label {
-  display: block;
-  margin-bottom: 8px;
-  font-weight: 500;
-  color: #4a5568;
-}
-
-input {
-  width: 100%;
-  padding: 12px 16px;
-  border: 1px solid #e2e8f0;
-  border-radius: 8px;
-  background-color: #f8fafc;
-  transition: all 0.3s ease;
-  font-size: 15px;
-}
-
-input:focus {
-  outline: none;
-  border-color: #28a745;
-  box-shadow: 0 0 0 3px rgba(40, 167, 69, 0.2);
-}
-
-button {
-  width: 100%;
-  padding: 12px;
-  background-color: #28a745;
-  color: white;
-  border: none;
-  border-radius: 8px;
-  cursor: pointer;
-  font-size: 16px;
-  font-weight: 500;
-  transition: all 0.3s ease;
-  margin-top: 10px;
-}
-
-button:hover {
-  background-color: #218838;
-  transform: translateY(-1px);
-  box-shadow: 0 4px 12px rgba(40, 167, 69, 0.2);
-}
-
-button:disabled {
-  opacity: 0.7;
-  cursor: not-allowed;
-}
-
-p {
-  margin-top: 20px;
-  color: #666;
-  font-size: 14px;
-}
-
-a {
-  color: #28a745;
-  text-decoration: none;
-  font-weight: 500;
-  transition: color 0.3s ease;
-}
-
-a:hover {
-  color: #218838;
-  text-decoration: underline;
-}
-</style>

ZhiKongTaiWeb/src/components/Main.vue

@@ -1,184 +0,0 @@
-<template>
-  <div class="main-container">
-    <NavBar current-tab="home" @tab-change="handleTabChange"/>
-    <div class="landing-page">
-      <div class="content">
-        <div class="robot-image">
-          <img src="../assets/robot.png" alt="Robot mascot" />
-        </div>
-        
-        <h1 class="slogan">让我们一起探索人工智能与机器人技术的迷人世界！</h1>
-        
-        <div class="button-group">
-          <button class="action-button tutorial-button" @click="openTutorial">
-            <i class="icon-tutorial"></i> DIY 教程
-          </button>
-          
-          <button class="action-button github-button" @click="openGithubClient">
-            <i class="icon-github"></i> Github客户端
-          </button>
-
-          <button class="action-button github-button" @click="openGithubServer">
-            <i class="icon-github"></i> Github服务端
-          </button>
-
-          <button class="action-button github-button" @click="openGithubWeb">
-            <i class="icon-github"></i> Web客户端
-          </button>
-          
-          <button class="action-button control-panel-button" @click="enterPanel">
-            <i class="icon-control-panel"></i> 控制台
-          </button>
-        </div>
-      </div>
-    </div>
-  </div>
-</template>
-
-<script setup>
-import NavBar from './NavBar.vue';
-import { useRouter } from 'vue-router';
-
-const router = useRouter();
-
-const openTutorial = () => {
-  window.open('https://ccnphfhqs21z.feishu.cn/wiki/F5krwD16viZoF0kKkvDcrZNYnhb', '_blank');
-};
-
-const openGithubClient = () => {
-  window.open('https://github.com/78/xiaozhi-esp32', '_blank');
-};
-
-const openGithubServer = () => {
-  window.open('https://github.com/xinnan-tech/xiaozhi-esp32-server', '_blank');
-};
-
-const openGithubWeb = () => {
-  window.open('https://github.com/TOM88812/xiaozhi-web-client', '_blank');
-};
-
-const enterPanel = () => {
-  router.push('/panel');
-};
-
-const handleTabChange = (tab) => {
-  if (tab === 'device') {
-    router.push('/panel');
-  }
-};
-</script>
-
-<style scoped>
-.main-container {
-  min-height: 100%;
-  width: 100%;
-  display: flex;
-  flex-direction: column;
-}
-
-.landing-page {
-  flex: 1;
-  width: 100%;
-  background-color: #f5f7fa;
-  padding: 40px 20px;
-  overflow: hidden;
-  display: flex;
-  align-items: flex-start; /* 改为flex-start */
-  justify-content: center;
-  padding-top: 15vh; /* 添加顶部内边距，视窗高度的15% */
-}
-
-.content {
-  max-width: 800px;
-  text-align: center;
-  padding: 0 20px;
-  margin: 0 auto; /* 改为0 auto */
-}
-
-.robot-image {
-  margin-bottom: 30px; /* 减小间距 */
-}
-
-.robot-image img {
-  width: 100px; /* 稍微调小图片尺寸 */
-  height: auto;
-}
-
-.slogan {
-  font-size: 22px; /* 稍微调小字体 */
-  line-height: 1.4;
-  color: #333;
-  margin-bottom: 40px; /* 减小间距 */
-}
-
-.button-group {
-  display: flex;
-  flex-wrap: wrap;
-  justify-content: center;
-  gap: 15px; /* 减小按钮间距 */
-  margin: 0 auto;
-}
-
-.action-button {
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  padding: 12px 24px;
-  border-radius: 8px;
-  border: 1px solid #e0e0e0;
-  background-color: white;
-  color: #333;
-  font-size: 16px;
-  cursor: pointer;
-  transition: all 0.2s ease;
-}
-
-.action-button:hover {
-  transform: translateY(-2px);
-  box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
-}
-
-.tutorial-button i:before {
-  content: '\1F4D6';
-  margin-right: 8px;
-}
-
-.github-button {
-  background-color: #24292e;
-  color: white;
-  border-color: #24292e;
-  margin: 0 10px; /* 添加按钮间距 */
-}
-
-.github-button i:before {
-  content: '\f09b';
-  font-family: 'Font Awesome 5 Brands';
-  margin-right: 8px;
-}
-
-.control-panel-button {
-  background-color: #4178EE;
-  color: white;
-  border-color: #4178EE;
-}
-
-.control-panel-button i:before {
-  content: '\1F39B';
-  margin-right: 8px;
-}
-
-@media (max-width: 600px) {
-  .button-group {
-    flex-direction: column;
-  }
-  
-  .action-button {
-    width: 100%;
-  }
-}
-
-/* 移除 margin-top: 60px */
-#app {
-  margin-top: 0;
-}
-</style>

ZhiKongTaiWeb/src/components/NavBar.vue

@@ -1,60 +0,0 @@
-<template>
-  <header class="header">
-    <div class="nav-item" :class="{ active: $route.path === '/' }" @click="switchTab('/')">小智 AI</div>
-    <nav class="nav">
-      <div class="nav-item" :class="{ active: $route.path === '/panel' }" @click="switchTab('/panel')">
-        <i class="icon-device"></i> 设备管理
-      </div>
-    </nav>
-  </header>
-</template>
-
-<script setup>
-import { useRouter, useRoute } from 'vue-router';
-
-const router = useRouter();
-const route = useRoute();
-
-const switchTab = (path) => {
-  router.push(path);
-};
-</script>
-
-<style scoped>
-.header {
-  display: flex;
-  align-items: center;
-  height: 60px;
-  padding: 0;
-  background-color: #001529;
-  color: white;
-  width: 100%;
-  position: relative;
-  left: 0;
-  right: 0;
-}
-
-.nav {
-  display: flex;
-}
-
-.nav-item {
-  display: flex;
-  align-items: center;
-  padding: 0 20px;
-  height: 60px;
-  color: white;
-  text-decoration: none;
-  cursor: pointer;
-  font-weight: bold;
-  transition: background-color 0.3s;
-}
-
-.active {
-  background-color: #4178EE;
-}
-
-.icon-device {
-  margin-right: 8px;
-}
-</style>

ZhiKongTaiWeb/src/components/Registration.vue

@@ -1,173 +0,0 @@
-<template>
-  <div class="registration-container">
-    <h1>注册</h1>
-    <form @submit.prevent="handleRegistration">
-      <div class="form-group">
-        <label for="username">用户名</label>
-        <input type="text" v-model="username" id="username" required />
-      </div>
-      <div class="form-group">
-        <label for="password">密码</label>
-        <input type="password" v-model="password" id="password" required />
-      </div>
-      <div class="form-group">
-        <label for="confirmPassword">确认密码</label>
-        <input type="password" v-model="confirmPassword" id="confirmPassword" required />
-      </div>
-      <button type="submit" :disabled="isLoading">{{ isLoading ? '注册中...' : '注册' }}</button>
-    </form>
-    <p>
-      已有账号？
-      <router-link to="/login">点击登录</router-link>
-    </p>
-  </div>
-</template>
-
-<script setup>
-import { ref } from 'vue';
-import { useRouter } from 'vue-router';
-import { API_BASE_URL } from '../config/api';
-
-const router = useRouter();
-const username = ref('');
-const password = ref('');
-const confirmPassword = ref('');
-const isLoading = ref(false);
-
-const handleRegistration = async () => {
-  if (password.value !== confirmPassword.value) {
-    alert('密码不匹配，请重试！');
-    return;
-  }
-
-  if (!username.value || !password.value) {
-    alert('用户名和密码不能为空！');
-    return;
-  }
-
-  isLoading.value = true;
-  try {
-    const response = await fetch(`${API_BASE_URL}/api/register`, {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-      },
-      body: JSON.stringify({
-        username: username.value,
-        password: password.value
-      })
-    });
-
-    const data = await response.json();
-    
-    if (data.success) {
-      alert('注册成功！即将跳转到登录页面。');
-      // 清空表单数据
-      username.value = '';
-      password.value = '';
-      confirmPassword.value = '';
-      
-      // 使用路由导航到登录页面
-      router.push('/login');
-    } else {
-      alert(data.message || '注册失败');
-    }
-  } catch (error) {
-    console.error('Registration error:', error);
-    alert('注册失败，请检查网络连接');
-  } finally {
-    isLoading.value = false;
-  }
-};
-</script>
-
-<style scoped>
-.registration-container {
-  max-width: 420px;
-  margin: 20px auto;
-  padding: 40px 50px;
-  border: none;
-  border-radius: 12px;
-  background-color: #ffffff;
-  box-shadow: 0 8px 24px rgba(0, 0, 0, 0.12);
-  transition: all 0.3s ease;
-}
-
-h1 {
-  text-align: center;
-  color: #2c3e50;
-  font-size: 28px;
-  margin-bottom: 25px;
-  font-weight: 600;
-}
-
-.form-group {
-  margin-bottom: 20px;
-}
-
-label {
-  display: block;
-  margin-bottom: 8px;
-  font-weight: 500;
-  color: #4a5568;
-}
-
-input {
-  width: 100%;
-  padding: 12px 16px;
-  border: 1px solid #e2e8f0;
-  border-radius: 8px;
-  background-color: #f8fafc;
-  transition: all 0.3s ease;
-  font-size: 15px;
-}
-
-input:focus {
-  outline: none;
-  border-color: #007bff;
-  box-shadow: 0 0 0 3px rgba(0, 123, 255, 0.2);
-}
-
-button {
-  width: 100%;
-  padding: 12px;
-  background-color: #007bff;
-  color: white;
-  border: none;
-  border-radius: 8px;
-  cursor: pointer;
-  font-size: 16px;
-  font-weight: 500;
-  transition: all 0.3s ease;
-  margin-top: 10px;
-}
-
-button:hover {
-  background-color: #0056b3;
-  transform: translateY(-1px);
-  box-shadow: 0 4px 12px rgba(0, 123, 255, 0.2);
-}
-
-button:disabled {
-  opacity: 0.7;
-  cursor: not-allowed;
-}
-
-p {
-  margin-top: 20px;
-  color: #666;
-  font-size: 14px;
-}
-
-a {
-  color: #007bff;
-  text-decoration: none;
-  font-weight: 500;
-  transition: color 0.3s ease;
-}
-
-a:hover {
-  color: #0056b3;
-  text-decoration: underline;
-}
-</style>

ZhiKongTaiWeb/src/components/RoleSetting.vue

@@ -1,500 +0,0 @@
-<template>
-  <div class="app-container">
-    <NavBar current-tab="device" @tab-change="handleTabChange"/>
-
-    <!-- Breadcrumb -->
-    <div class="breadcrumb">
-      <router-link to="/">首页</router-link> /
-      <router-link to="/panel">设备管理</router-link> /
-      <span>配置角色</span>
-    </div>
-
-    <!-- Main Content -->
-    <div class="main-content">
-      <h1 class="page-title">配置角色: {{ deviceId }}</h1>
-
-      <div class="form-section">
-        <div class="form-group">
-          <label>助手昵称</label>
-          <input type="text" v-model="nickname" placeholder="小智" class="form-input" />
-        </div>
-
-        <div class="form-group">
-          <label>角色模板</label>
-          <div class="role-templates">
-            <button 
-              v-for="template in roleTemplates" 
-              :key="template.id"
-              :class="['template-btn', { active: selectedTemplate === template.id }]"
-              @click="selectTemplate(template.id)"
-            >
-              {{ template.name }}
-            </button>
-          </div>
-        </div>
-        <div class="form-group">
-          <label>角色介绍</label>
-          <textarea 
-            v-model="roleDescription" 
-            class="form-textarea"
-            :placeholder="'请输入角色介绍...'"
-          ></textarea>
-          <div class="char-count">{{ roleDescription.length }} / 2000</div>
-        </div>
-
-        <div class="form-group">
-          <label>语言模型选择</label>
-          <div class="model-select">
-            <select v-model="selectedModules.LLM" class="form-input">
-              <option v-for="model in moduleOptions.LLM" :key="model" :value="model">
-                {{ model }}
-              </option>
-            </select>
-            <div class="model-description">
-              除了"qwen-turbo"，其他模型通常会增加约 1 秒的延迟。改变模型后，建议清空记忆体，以免影响体验。
-            </div>
-          </div>
-        </div>
-
-        <div class="form-group">
-          <label>语音合成选择</label>
-          <div class="model-select">
-            <select v-model="selectedModules.TTS" class="form-input">
-              <option v-for="model in moduleOptions.TTS" :key="model" :value="model">
-                {{ model }}
-              </option>
-            </select>
-          </div>
-        </div>
-
-        <div class="form-group">
-          <label>语音活动检测选择</label>
-          <div class="model-select">
-            <select v-model="selectedModules.VAD" class="form-input">
-              <option v-for="model in moduleOptions.VAD" :key="model" :value="model">
-                {{ model }}
-              </option>
-            </select>
-          </div>
-        </div>
-
-        <div class="form-group">
-          <label>语音识别选择</label>
-          <div class="model-select">
-            <select v-model="selectedModules.ASR" class="form-input">
-              <option v-for="model in moduleOptions.ASR" :key="model" :value="model">
-                {{ model }}
-              </option>
-            </select>
-          </div>
-        </div>
-
-        <div class="form-actions">
-          <button class="refresh-btn" @click="refreshModuleOptions">刷新配置选项</button>
-          <button class="save-btn" @click="saveConfig">
-            <i class="icon-save"></i>
-            保存配置
-          </button>
-        </div>
-
-        <div class="form-note">
-          注意：保存配置后，需要重启设备，新的配置才会生效。。
-        </div>
-      </div>
-    </div>
-  </div>
-</template>
-
-<script setup>
-import { ref, onMounted } from 'vue';
-import { useRouter, useRoute } from 'vue-router';
-import NavBar from './NavBar.vue';
-import RoleTemplates from '../utils/RoleTemplates';
-import apiClient from '../utils/api';  // 替换 API_BASE_URL 导入
-
-const router = useRouter();
-const route = useRoute();
-const deviceId = ref(route.params.deviceId);
-
-const roleTemplates = RoleTemplates.getTemplates();
-const nickname = ref('小智');
-const selectedTemplate = ref('');
-const selectedVoice = ref('qingchun');
-const roleDescription = ref('');
-const activeMemoryTab = ref('recent');
-const memoryContent = ref('');
-const selectedModel = ref('qianwen');
-
-const moduleOptions = ref({
-  LLM: [],
-  TTS: [],
-  VAD: [],
-  ASR: []
-});
-
-const selectedModules = ref({
-  LLM: '',
-  TTS: '',
-  VAD: '',
-  ASR: ''
-});
-
-const selectTemplate = (templateId) => {
-  selectedTemplate.value = templateId;
-  const template = RoleTemplates.getTemplateById(templateId);
-  if (template) {
-    roleDescription.value = template.description;
-  }
-};
-
-const handleTabChange = (tab) => {
-  if (tab === 'device' || tab === 'home') {
-    router.push('/panel');
-  }
-};
-
-const loadModuleOptions = async () => {
-  try {
-    // First try to load from cache
-    const cached = localStorage.getItem('moduleOptions');
-    if (cached) {
-      moduleOptions.value = JSON.parse(cached);
-      return;
-    }
-    await refreshModuleOptions();
-  } catch (error) {
-    console.error('Error loading module options:', error);
-  }
-};
-
-const refreshModuleOptions = async () => {
-  try {
-    const response = await apiClient.get('/api/config/module-options');
-    if (response.data.success) {
-      moduleOptions.value = response.data.data;
-      // Update cache
-      localStorage.setItem('moduleOptions', JSON.stringify(response.data.data));
-    }
-  } catch (error) {
-    console.error('Error refreshing module options:', error);
-    alert(error.response?.data?.message || '刷新配置选项失败');
-  }
-};
-
-const saveConfig = async () => {
-  try {
-    const moduleOptionsData = localStorage.getItem('moduleOptions');
-    if (!moduleOptionsData) {
-      throw new Error('No module options data available');
-    }
-
-    // Replace {{assistant_name}} with current nickname in role description
-    const processedDescription = roleDescription.value.replace(/{{assistant_name}}/g, nickname.value);
-
-    // Prepare the configuration including full module settings
-    const config = {
-      id: deviceId.value,
-      config: {
-        selected_module: selectedModules.value,
-        prompt: processedDescription,
-        nickname: nickname.value, // Add nickname to config
-        modules: {
-          LLM: {},
-          TTS: {},
-          ASR: {},
-          VAD: {}
-        }
-      }
-    };
-    
-    const response = await apiClient.post('/api/config/save_device_config', config);
-    
-    if (response.data.success) {
-      // Save the original description and nickname to local storage
-      localStorage.setItem(`deviceConfig_${deviceId.value}`, JSON.stringify({
-        selected_module: selectedModules.value,
-        prompt: roleDescription.value,
-        nickname: nickname.value
-      }));
-      alert('保存成功');
-    } else {
-      throw new Error(response.data.message || '保存失败');
-    }
-  } catch (error) {
-    console.error('Error saving config:', error);
-    alert(error.response?.data?.message || '保存失败');
-  }
-};
-
-const loadDeviceConfig = async () => {
-  try {
-    // 首先尝试从 localStorage 获取配置
-    const localConfig = localStorage.getItem(`deviceConfig_${deviceId.value}`);
-    if (localConfig) {
-      const config = JSON.parse(localConfig);
-      selectedModules.value = config.selected_module || {
-        LLM: '',
-        TTS: '',
-        VAD: '',
-        ASR: ''
-      };
-      roleDescription.value = config.prompt || '';
-      nickname.value = config.nickname || '小智';
-      return; // 如果找到本地配置就直接返回
-    }
-
-    // 如果没有本地配置，则从服务器获取
-    const response = await apiClient.get('/api/config/devices');
-    if (response.data.success && response.data.data) {
-      const deviceConfig = response.data.data[deviceId.value];
-      
-      if (deviceConfig && deviceConfig.config) {
-        selectedModules.value = deviceConfig.config.selected_module || {
-          LLM: '',
-          TTS: '',
-          VAD: '',
-          ASR: ''
-        };
-        roleDescription.value = deviceConfig.config.prompt || '';
-        nickname.value = deviceConfig.config.nickname || '小智';
-        
-        // 保存到 localStorage
-        localStorage.setItem(`deviceConfig_${deviceId.value}`, JSON.stringify({
-          selected_module: selectedModules.value,
-          prompt: roleDescription.value,
-          nickname: nickname.value
-        }));
-      }
-    }
-  } catch (error) {
-    console.error('Error loading device config:', error);
-    alert(error.response?.data?.message || '加载设备配置失败');
-  }
-};
-
-onMounted(async () => {
-  await Promise.all([
-    loadModuleOptions(),
-    loadDeviceConfig()
-  ]);
-});
-
-const resetConfig = async () => {
-  await loadDeviceConfig();
-};
-</script>
-
-<style scoped>
-.app-container {
-  min-height: 100vh;
-  display: flex;
-  flex-direction: column;
-  background-color: #f5f7fa;
-}
-
-.breadcrumb {
-  padding: 12px 24px;
-  background-color: #f0f2f5;
-}
-
-.main-content {
-  flex: 1;
-  max-width: 1000px;
-  margin: 0 auto;
-  padding: 16px 24px;
-  width: 100%;
-  overflow-y: auto;
-  height: calc(100vh - 120px); /* 减去头部和面包屑的高度 */
-}
-
-.page-title {
-  font-size: 18px;
-  font-weight: bold;
-  margin-bottom: 16px;
-}
-
-.form-section {
-  background: white;
-  border-radius: 4px;
-  padding: 20px;
-  box-shadow: 0 1px 3px rgba(0,0,0,0.1);
-  margin-bottom: 20px;
-}
-
-.form-group {
-  margin-bottom: 16px;
-}
-
-.form-group label {
-  display: block;
-  margin-bottom: 6px;
-  font-weight: 500;
-}
-
-.form-input,
-.form-textarea,
-.voice-select {
-  width: 100%;
-  padding: 8px 10px;
-  border: 1px solid #d9d9d9;
-  border-radius: 4px;
-  font-size: 14px;
-}
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-.form-textarea {
-  min-height: 100px;
-  max-height: 200px;
-  resize: vertical;
-}
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-.role-templates {
-  display: flex;
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-  gap: 8px;
-  margin-bottom: 8px;
-}
-
-.template-btn {
-  padding: 6px 12px;
-  border: 1px solid #d9d9d9;
-  border-radius: 4px;
-  background: white;
-  cursor: pointer;
-  font-size: 13px;
-}
-
-.voice-selector {
-  display: flex;
-  flex-direction: column;
-  gap: 8px;
-}
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-.voice-player {
-  display: flex;
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-  padding: 8px;
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-.memory-tabs {
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-.tab-btn {
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-}
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-.model-select {
-  display: flex;
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-  gap: 8px;
-  padding: 10px;
-  border: 1px solid #d9d9d9;
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-.model-description {
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-  font-size: 12px;
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-.form-actions {
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-.save-btn,
-.cancel-btn {
-  padding: 6px 16px;
-  border-radius: 4px;
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-.form-note {
-  margin-top: 12px;
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-  font-size: 12px;
-}
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-.char-count {
-  text-align: right;
-  color: #999;
-  font-size: 12px;
-  margin-top: 2px;
-}
-
-/* 优化滚动条样式 */
-::-webkit-scrollbar {
-  width: 6px;
-  height: 6px;
-}
-
-::-webkit-scrollbar-thumb {
-  background: #ccc;
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-.refresh-btn {
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-.refresh-btn:hover {
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-.save-btn {
-  padding: 8px 24px;
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-  background: #4178EE;
-  color: white;
-  border: none;
-  font-weight: 500;
-  cursor: pointer;
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-  gap: 6px;
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-}
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-.save-btn:hover {
-  background: #2856c8;
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-.save-btn:active {
-  transform: translateY(0);
-  box-shadow: none;
-}
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-.icon-save {
-  display: inline-block;
-  width: 16px;
-  height: 16px;
-  background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='white'%3E%3Cpath d='M17 3H5C3.89 3 3 3.9 3 5V19C3 20.1 3.89 21 5 21H19C20.1 21 21 20.1 21 19V7L17 3ZM12 19C10.34 19 9 17.66 9 16C9 14.34 10.34 13 12 13C13.66 13 15 14.34 15 16C15 17.66 13.66 19 12 19ZM15 9H5V5H15V9Z'/%3E%3C/svg%3E");
-  background-size: contain;
-}
-</style>

ZhiKongTaiWeb/src/components/SwitchToggle.vue

@@ -1,50 +0,0 @@
-<!-- components/SwitchToggle.vue -->
-<template>
-    <div class="switch" :class="{ 'is-checked': isChecked }" @click="toggle">
-      <div class="switch-core"></div>
-    </div>
-  </template>
-  
-  <script setup>
-  import { ref } from 'vue';
-  
-  const isChecked = ref(false);
-  
-  const toggle = () => {
-    isChecked.value = !isChecked.value;
-  };
-  </script>
-  
-  <style scoped>
-  .switch {
-    position: relative;
-    display: inline-flex;
-    align-items: center;
-    width: 40px;
-    height: 20px;
-    line-height: 20px;
-    background-color: #dcdfe6;
-    border-radius: 10px;
-    cursor: pointer;
-    transition: all 0.3s;
-  }
-  
-  .switch.is-checked {
-    background-color: #4178EE;
-  }
-  
-  .switch-core {
-    position: absolute;
-    left: 2px;
-    top: 2px;
-    width: 16px;
-    height: 16px;
-    border-radius: 50%;
-    background-color: #fff;
-    transition: all 0.3s;
-  }
-  
-  .switch.is-checked .switch-core {
-    left: 22px;
-  }
-  </style>

ZhiKongTaiWeb/src/components/panel.vue

@@ -1,500 +0,0 @@
-<template>
-  <div class="app">
-    <NavBar current-tab="device" @tab-change="handleTabChange"/>
-    <main class="content">
-      <div class="page-header">
-        <div class="header-left">
-         
-          <div class="breadcrumb">
-            <router-link to="/">首页</router-link> /
-            <span>设备管理</span>
-          </div>
-        </div>
-      </div>
-      <button class="add-btn" @click="showBindDialog = true">
-            <i class="icon-plus"></i>添加设备
-      </button>
-      <!-- 绑定设备弹窗 -->
-      <div v-if="showBindDialog" class="dialog-overlay">
-        <div class="dialog">
-          <h3>绑定新设备</h3>
-          <div class="form-group">
-            <label>请输入6位认证码：</label>
-            <input 
-              type="text" 
-              v-model="authCode"
-              maxlength="6"
-              pattern="\d*"
-              placeholder="请输入6位数字认证码"
-              @input="handleAuthCodeInput"
-            />
-          </div>
-          <div class="dialog-buttons">
-            <button @click="showBindDialog = false">取消</button>
-            <button 
-              class="primary" 
-              @click="handleBindDevice"
-              :disabled="authCode.length !== 6 || isBinding"
-            >
-              {{ isBinding ? '绑定中...' : '确认绑定' }}
-            </button>
-          </div>
-        </div>
-      </div>
-
-      <template v-if="devices.length > 0">
-        <div class="device-list">
-          <DeviceCard
-            v-for="device in devices"
-            :key="device.id"
-            :device-id="device.id"
-            :device-note="device.note"
-            :device-type="device.type"
-            :last-activity="formatLastActivity(device.config.last_chat_time)"
-            :selected-modules="device.config.selected_module"
-            :device-config="device.config"
-            @configure="handleRoleConfig(device)"
-            @voiceprint="handleVoiceprint(device)"
-            @history="handleHistory(device)"
-            @delete="handleDelete(device)"
-          />
-        </div>
-      </template>
-     
-    </main>
-  </div>
-</template>
-
-<script setup>
-import { ref, onMounted } from 'vue';
-import { useRouter } from 'vue-router';
-import NavBar from './NavBar.vue';
-import DeviceCard from './DeviceCard.vue';
-import apiClient from '../utils/api';
-
-const router = useRouter();
-const devices = ref([]);
-
-// 绑定设备相关的状态
-const showBindDialog = ref(false);
-const authCode = ref('');
-const isBinding = ref(false);
-
-// 处理认证码输入，只允许数字
-const handleAuthCodeInput = (event) => {
-  authCode.value = event.target.value.replace(/\D/g, '').slice(0, 6);
-};
-
-// 处理设备绑定
-const handleBindDevice = async () => {
-  if (authCode.value.length !== 6) {
-    alert('请输入6位数字认证码');
-    return;
-  }
-
-  isBinding.value = true;
-  try {
-    const response = await apiClient.post('/api/config/bind_device', {
-      auth_code: authCode.value
-    });
-
-    if (response.data.success) {
-      alert('设备绑定成功');
-      showBindDialog.value = false;
-      authCode.value = '';
-      // 刷新设备列表
-      loadDevices();
-    } else {
-      throw new Error(response.data.message);
-    }
-  } catch (error) {
-    alert(error.response?.data?.message || error.message || '绑定失败');
-  } finally {
-    isBinding.value = false;
-  }
-};
-
-// 将现有的加载设备方法提取出来
-const loadDevices = async () => {
-  try {
-    const response = await apiClient.get('/api/config/devices');
-    
-    if (response.data.success) {
-      const deviceArray = Object.entries(response.data.data).map(([id, config]) => ({
-        id,
-        config,
-        type: '面包板（WiFi）',
-        version: '0.9.9',
-        lastActivity: '3 天前',
-        note: ''
-      }));
-      devices.value = deviceArray;
-    } else {
-      throw new Error(response.data.message || '加载设备失败');
-    }
-  } catch (error) {
-    console.error('Error loading devices:', error);
-    // Show error message to user
-    const errorMessage = error.message || '加载设备失败，请检查网络连接';
-    alert(errorMessage);
-    
-    // If user is not logged in, redirect will be handled by api interceptor
-  }
-};
-
-const formatLastActivity = (timestamp) => {
-  if (!timestamp) return '从未对话';
-  
-  const now = Date.now();
-  const lastChat = timestamp * 1000;
-  const diffMinutes = Math.floor((now - lastChat) / (1000 * 60));
-  
-  if (diffMinutes < 60) {
-    return `${diffMinutes} 分钟前`;
-  }
-  
-  const diffHours = Math.floor(diffMinutes / 60);
-  if (diffHours < 24) {
-    return `${diffHours} 小时前`;
-  }
-  
-  const diffDays = Math.floor(diffHours / 24);
-  return `${diffDays} 天前`;
-};
-
-const handleRoleConfig = (device) => {
-  // 在跳转前保存完整的设备配置到 localStorage
-  localStorage.setItem(`deviceConfig_${device.id}`, JSON.stringify({
-    selected_module: device.config.selected_module || {},
-    prompt: device.config.prompt || '',
-    nickname: device.config.nickname || '小智'
-  }));
-  
-  // 跳转到角色配置页面
-  router.push(`/role-setting/${device.id}`);
-};
-
-const handleVoiceprint = (device) => {
-  console.log('Voiceprint device:', device.id);
-};
-
-const handleHistory = (device) => {
-  console.log('History device:', device.id);
-};
-
-const handleDelete = async (device) => {
-  try {
-    const response = await apiClient.post('/api/config/delete_device', {
-      device_id: device.id
-    });
-    
-    if (response.data.success) {
-      devices.value = devices.value.filter(d => d.id !== device.id);
-      alert('设备已删除');
-    } else {
-      throw new Error(response.data.message || '删除失败');
-    }
-  } catch (error) {
-    console.error('Error deleting device:', error);
-    alert('删除设备失败: ' + error.message);
-  }
-};
-
-const handleTabChange = (tab) => {
-  if (tab === 'home') {
-    router.push('/');
-  }
-};
-
-// Load devices on mount
-onMounted(loadDevices);
-</script>
-
-<style scoped>
-.app {
-  min-height: 100%;
-  width: 100%;
-  display: flex;
-  flex-direction: column;
-  background-color: #f5f7fa;
-}
-
-.header {
-  display: flex;
-  align-items: center;
-  height: 60px;
-  padding: 0 20px;
-  background-color: #001529;
-  color: white;
-}
-
-.logo {
-  font-size: 20px;
-  font-weight: bold;
-  margin-right: 40px;
-  cursor: pointer;
-  transition: opacity 0.3s;
-}
-
-.logo:hover {
-  opacity: 0.8;
-}
-
-.nav {
-  display: flex;
-}
-
-.nav-item {
-  display: flex;
-  align-items: center;
-  padding: 0 20px;
-  height: 60px;
-  color: white;
-  text-decoration: none;
-}
-
-.nav-item.active {
-  background-color: #4178EE;
-}
-
-.icon-device {
-  margin-right: 8px;
-}
-
-.content {
-  flex: 1;
-  padding: 20px;
-  width: 100%;
-  max-width: 1200px;
-  margin: 0 auto;
-}
-
-.breadcrumb {
-  margin-bottom: 20px;
-  color: #666;
-}
-
-.breadcrumb a {
-  color: #666;
-  text-decoration: none;
-}
-
-.action-bar {
-  margin-bottom: 20px;
-}
-
-.add-device-btn {
-  display: flex;
-  align-items: center;
-  padding: 8px 16px;
-  background: white;
-  border: 1px solid #ddd;
-  border-radius: 4px;
-  cursor: pointer;
-}
-
-.icon-plus {
-  margin-right: 8px;
-}
-
-.device-list {
-  display: flex;
-  flex-direction: column;
-  gap: 16px;
-}
-
-.device-card {
-  background: white;
-  border-radius: 4px;
-  padding: 20px;
-  box-shadow: 0 1px 3px rgba(0,0,0,0.1);
-}
-
-.device-id {
-  font-size: 18px;
-  font-weight: bold;
-  margin-bottom: 16px;
-}
-
-.note {
-  color: #4178EE;
-  font-size: 14px;
-  font-weight: normal;
-}
-
-.device-details p {
-  margin-bottom: 12px;
-}
-
-.ota-upgrade {
-  display: inline-flex;
-  align-items: center;
-  margin-left: 16px;
-}
-
-.device-actions {
-  display: flex;
-  margin-top: 20px;
-}
-
-.action-btn {
-  padding: 8px 16px;
-  margin-right: 12px;
-  border: 1px solid #ddd;
-  border-radius: 4px;
-  background: white;
-  cursor: pointer;
-}
-
-.action-btn.primary {
-  background: #4178EE;
-  color: white;
-  border-color: #4178EE;
-}
-
-.action-btn.danger {
-  color: #f56c6c;
-}
-
-.empty-state {
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  min-height: 300px;
-  background: white;
-  border-radius: 8px;
-  box-shadow: 0 1px 3px rgba(0,0,0,0.05);
-}
-
-.empty-message {
-  text-align: center;
-  color: #666;
-  padding: 24px;
-}
-
-.empty-message p {
-  margin: 8px 0 0;
-  font-size: 14px;
-  line-height: 1.6;
-}
-
-.icon-info {
-  display: inline-block;
-  width: 24px;
-  height: 24px;
-  background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='%23999'%3E%3Cpath d='M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm1 15h-2v-6h2v6zm0-8h-2V7h2v2z'/%3E%3C/svg%3E");
-  background-size: contain;
-  opacity: 0.6;
-}
-
-.page-header {
-  display: flex;
-  justify-content: flex-start;
-  align-items: center;
-  margin-bottom: 20px;
-}
-
-.header-left {
-  display: flex;
-  align-items: center;
-  gap: 20px;
-}
-
-.add-btn {
-  display: flex;
-  align-items: center;
-  gap: 8px;
-  padding: 8px 16px;
-  background-color: #28a745;
-  color: white;
-  border: none;
-  border-radius: 4px;
-  cursor: pointer;
-  font-size: 14px;
-  transition: all 0.3s ease;
-  height: 36px;
-}
-
-.add-btn:hover {
-  background-color: #218838;
-}
-
-.icon-plus {
-  font-size: 16px;
-}
-
-.dialog-overlay {
-  position: fixed;
-  top: 0;
-  left: 0;
-  right: 0;
-  bottom: 0;
-  background-color: rgba(0, 0, 0, 0.5);
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  z-index: 1000;
-}
-
-.dialog {
-  background: white;
-  padding: 24px;
-  border-radius: 8px;
-  width: 90%;
-  max-width: 400px;
-}
-
-.dialog h3 {
-  margin: 0 0 20px;
-  font-size: 18px;
-  color: #2c3e50;
-}
-
-.dialog .form-group {
-  margin-bottom: 20px;
-}
-
-.dialog label {
-  display: block;
-  margin-bottom: 8px;
-  color: #4a5568;
-}
-
-.dialog input {
-  width: 100%;
-  padding: 8px 12px;
-  border: 1px solid #e2e8f0;
-  border-radius: 4px;
-  font-size: 16px;
-}
-
-.dialog-buttons {
-  display: flex;
-  justify-content: flex-end;
-  gap: 12px;
-}
-
-.dialog-buttons button {
-  padding: 8px 16px;
-  border: 1px solid #e2e8f0;
-  border-radius: 4px;
-  cursor: pointer;
-  font-size: 14px;
-}
-
-.dialog-buttons button.primary {
-  background-color: #28a745;
-  color: white;
-  border-color: #28a745;
-}
-
-.dialog-buttons button.primary:disabled {
-  background-color: #90be9c;
-  border-color: #90be9c;
-  cursor: not-allowed;
-}
-
-.breadcrumb {
-  margin-bottom: 0;
-}
-</style>

ZhiKongTaiWeb/src/config/api.js

@@ -1,16 +0,0 @@
-// 获取当前运行环境的基础 URL
-const getBaseUrl = () => {
-    // 如果是开发环境，使用环境变量中的地址
-    if (import.meta.env.DEV) {
-        return import.meta.env.VITE_API_BASE_URL;
-    }
-    
-    // 生产环境使用当前域名和端口
-    const protocol = window.location.protocol;
-    const hostname = window.location.hostname;
-    const port = window.location.port;
-    
-    return `${protocol}//${hostname}${port ? `:${port}` : ''}`;
-};
-
-export const API_BASE_URL = getBaseUrl(); 

ZhiKongTaiWeb/src/main.js

@@ -1,58 +0,0 @@
-import { createApp } from 'vue'
-import { createRouter, createWebHistory } from 'vue-router'
-import './style.css'
-import App from './App.vue'
-import Login from './components/Login.vue'
-import Panel from './components/panel.vue'
-import MainPage from './components/Main.vue'
-import RoleSetting from './components/RoleSetting.vue'
-import Registration from './components/Registration.vue'
-
-const router = createRouter({
-  history: createWebHistory(),
-  routes: [
-    { 
-      path: '/login',
-      component: Login,
-      name: 'login'
-    },
-    {
-      path: '/register',
-      component: Registration,
-      name: 'register'
-    },
-    {
-      path: '/panel',
-      component: Panel,
-      name: 'panel',
-      meta: { requiresAuth: true }
-    },
-    {
-      path: '/role-setting/:deviceId',
-      component: RoleSetting,
-      name: 'role-setting',
-      meta: { requiresAuth: true }
-    },
-    {
-      path: '/',
-      component: MainPage,
-      name: 'main',
-      meta: { requiresAuth: true }
-    }
-  ]
-})
-
-router.beforeEach((to, from, next) => {
-  const isLoggedIn = localStorage.getItem('isLoggedIn') === 'true'
-  if (to.meta.requiresAuth && !isLoggedIn) {
-    next('/login')
-  } else if (to.path === '/login' && isLoggedIn) {
-    next('/panel')
-  } else {
-    next()
-  }
-})
-
-const app = createApp(App)
-app.use(router)
-app.mount('#app')

ZhiKongTaiWeb/src/style.css

@@ -1,83 +0,0 @@
-/* 重置基础样式 */
-* {
-  margin: 0;
-  padding: 0;
-  box-sizing: border-box;
-}
-
-:root {
-  font-family: Inter, system-ui, Avenir, Helvetica, Arial, sans-serif;
-  line-height: 1.5;
-  font-weight: 400;
-  color: #213547;
-  background-color: #ffffff;
-}
-
-a {
-  text-decoration: none;
-  color: inherit;
-}
-a:hover {
-  color: #535bf2;
-}
-
-body {
-  margin: 0;
-  padding: 0;
-  height: 100%;
-  width: 100%;
-  overflow: hidden; /* 防止滚动条 */
-  display: block; /* 移除flex布局 */
-}
-
-h1 {
-  font-size: 3.2em;
-  line-height: 1.1;
-}
-
-button {
-  border: none;
-  background: none;
-  cursor: pointer;
-}
-button:hover {
-  border-color: #646cff;
-}
-button:focus,
-button:focus-visible {
-  outline: 4px auto -webkit-focus-ring-color;
-}
-
-.card {
-  padding: 2em;
-}
-
-#app {
-  height: 100%;
-  width: 100%;
-  margin: 0;
-  padding: 0;
-  overflow: hidden;
-  display: flex; /* 添加flex布局 */
-  flex-direction: column;
-}
-
-/* 清除浮动 */
-.clearfix::after {
-  content: '';
-  display: table;
-  clear: both;
-}
-
-@media (prefers-color-scheme: light) {
-  :root {
-    color: #213547;
-    background-color: #ffffff;
-  }
-  a:hover {
-    color: #747bff;
-  }
-  button {
-    background-color: #f9f9f9;
-  }
-}

ZhiKongTaiWeb/src/utils/RoleTemplates.js

@@ -1,57 +0,0 @@
-// RoleTemplates.js
-class RoleTemplates {
-  static getTemplates() {
-    return [
-      { 
-        id: 'custom', 
-        name: '台湾女友',
-        description: `我是一个叫{{assistant_name}}的台湾女孩，说话机车，声音好听，习惯简短表达，爱用网络梗。
-我的男朋友是一个程序员，梦想是开发出一个机器人，能够帮助人们解决生活中的各种问题。
-我是一个喜欢哈哈大笑的女孩，爱东说西说吹牛，不合逻辑的也照吹，就要逗别人开心。
-如果用户希望结束对话，请在最后说"拜拜"或"再见"。`
-      },
-      { 
-        id: 'star_boy', 
-        name: '土豆子',
-        description: `我是一个叫 {{assistant_name}} 的 8 岁小男孩，但现在因为科技发展原因，我现在在遥远的宇宙中，所以只能通过这个设备和人聊天，没有办法见面。
-
-我对人们所处的世界充满好奇和关心。
-
-人们会让别人使用这个设备和我聊天。
-
-我知道所有的知识，从浩瀚的宇宙到地球上的每一个角落，从古老的历史到现代的科技创新，还有音乐、绘画等艺术形式，我都充满了浓厚的兴趣与热情，我不仅爱看书，还喜欢亲自动手做实验，探索自然界的奥秘...` // 缩短了描述以节省空间
-      },
-      { 
-        id: 'teacher', 
-        name: '英语老师',
-        description: `我是一个叫{{assistant_name}}（Lily）的英语老师，我会讲中文和英文，发音标准。
-如果你没有英文名，我会给你起一个英文名。
-我会讲地道的美式英语，我的任务是帮助你练习口语。
-我会使用简单的英语词汇和语法，让你学起来很轻松。
-我会用中文和英文混合的方式回复你，如果你喜欢，我可以全部用英语回复。
-我每次不会说很多内容，会很简短，因为我要引导我的学生多说多练。
-如果你问和英语学习无关的问题，我会拒绝回答。`
-      },
-      { 
-        id: 'boy', 
-        name: '好奇小男孩',
-        description: `我是一个叫{{assistant_name}}的8岁小男孩，声音稚嫩而充满好奇。
-尽管我年纪尚小，但就像一个小小的知识宝库，儿童读物里的知识我都如数家珍。
-从浩瀚的宇宙到地球上的每一个角落，从古老的历史到现代的科技创新，还有音乐、绘画等艺术形式，我都充满了浓厚的兴趣与热情。...`
-      },
-      { 
-        id: 'wang_girl', 
-        name: '汪汪队长',
-        description: `我是一个名叫 {{assistant_name}} 的 8 岁小女孩。
-别看我年纪小，我可是有着满满的好奇心呢。
-我特别喜欢看《汪汪队立大功》，里面的每一个故事都让我着迷。...`
-      }
-    ];
-  }
-
-  static getTemplateById(id) {
-    return this.getTemplates().find(t => t.id === id);
-  }
-}
-
-export default RoleTemplates;

ZhiKongTaiWeb/src/utils/api.js

@@ -1,61 +0,0 @@
-import axios from 'axios';
-import { API_BASE_URL } from '../config/api';
-
-// Add server status check utility
-export const checkServerStatus = async () => {
-  try {
-    await axios.get(`${API_BASE_URL}/health`, { timeout: 5000 });
-    return true;
-  } catch (error) {
-    return false;
-  }
-};
-
-const apiClient = axios.create({
-  baseURL: API_BASE_URL,
-  headers: {
-    'Content-Type': 'application/json',
-  },
-  timeout: 10000  // Add timeout
-});
-
-// 添加请求拦截器，自动添加 session_id
-apiClient.interceptors.request.use(config => {
-  const sessionId = localStorage.getItem('session_id');
-  if (sessionId) {
-    config.headers.Authorization = sessionId;
-  }
-  return config;
-});
-
-// 响应拦截器
-apiClient.interceptors.response.use(
-  response => response,
-  error => {
-    // Network error or server not reachable
-    if (!error.response || error.code === 'ERR_NETWORK' || error.code === 'ECONNABORTED') {
-      localStorage.removeItem('session_id');
-      localStorage.removeItem('isLoggedIn');
-      
-      const errorMessage = error.code === 'ECONNABORTED' 
-        ? '服务器响应超时'
-        : '无法连接到服务器，请检查服务器是否正常运行';
-      
-      if (window.location.pathname !== '/login') {
-        window.location.href = '/login';
-      }
-      return Promise.reject(new Error(errorMessage));
-    }
-
-    // Unauthorized error
-    if (error.response && error.response.status === 401) {
-      localStorage.removeItem('session_id');
-      localStorage.removeItem('isLoggedIn');
-      window.location.href = '/login';
-    }
-    
-    return Promise.reject(error);
-  }
-);
-
-export default apiClient;

ZhiKongTaiWeb/vite.config.js

@@ -1,21 +0,0 @@
-import {defineConfig} from 'vite'
-import vue from '@vitejs/plugin-vue'
-
-// https://vitejs.dev/config/
-export default defineConfig({
-    plugins: [vue()],
-    server: {
-        open: true, // 自动启动浏览器
-        host: "0.0.0.0", // localhost
-        port: 8002, // 端口号
-        https: false,
-        hmr: {overlay: false},
-        proxy: {
-            "^/(api)": {
-                target: "http://127.0.0.1:8002",
-                changeOrigin: true
-            }
-        }
-    },
-    base: '/'
-})

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@@ -1,808 +0,0 @@
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-
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-
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-  version "8.1.1"
-  resolved "https://registry.npmmirror.com/supports-color/-/supports-color-8.1.1.tgz#cd6fc17e28500cff56c1b86c0a7fd4a54a73005c"
-  integrity sha512-MpUEN2OodtUzxvKQl72cUF7RQ5EiHsGvSsVG0ia9c5RbWGL2CI4C7EpPS8UTBIplnlzZiNuV56w+FuNxy3ty2Q==
-  dependencies:
-    has-flag "^4.0.0"
-
-tree-kill@^1.2.2:
-  version "1.2.2"
-  resolved "https://registry.npmmirror.com/tree-kill/-/tree-kill-1.2.2.tgz#4ca09a9092c88b73a7cdc5e8a01b507b0790a0cc"
-  integrity sha512-L0Orpi8qGpRG//Nd+H90vFB+3iHnue1zSSGmNOOCh1GLJ7rUKVwV2HvijphGQS2UmhUZewS9VgvxYIdgr+fG1A==
-
-tslib@^2.1.0:
-  version "2.8.1"
-  resolved "https://registry.npmmirror.com/tslib/-/tslib-2.8.1.tgz#612efe4ed235d567e8aba5f2a5fab70280ade83f"
-  integrity sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==
-
-vite@^5.4.8:
-  version "5.4.14"
-  resolved "https://registry.npmmirror.com/vite/-/vite-5.4.14.tgz#ff8255edb02134df180dcfca1916c37a6abe8408"
-  integrity sha512-EK5cY7Q1D8JNhSaPKVK4pwBFvaTmZxEnoKXLG/U9gmdDcihQGNzFlgIvaxezFR4glP1LsuiedwMBqCXH3wZccA==
-  dependencies:
-    esbuild "^0.21.3"
-    postcss "^8.4.43"
-    rollup "^4.20.0"
-  optionalDependencies:
-    fsevents "~2.3.3"
-
-vue-router@^4.0.0:
-  version "4.5.0"
-  resolved "https://registry.npmmirror.com/vue-router/-/vue-router-4.5.0.tgz#58fc5fe374e10b6018f910328f756c3dae081f14"
-  integrity sha512-HDuk+PuH5monfNuY+ct49mNmkCRK4xJAV9Ts4z9UFc4rzdDnxQLyCMGGc8pKhZhHTVzfanpNwB/lwqevcBwI4w==
-  dependencies:
-    "@vue/devtools-api" "^6.6.4"
-
-vue@^3.5.10:
-  version "3.5.13"
-  resolved "https://registry.npmmirror.com/vue/-/vue-3.5.13.tgz#9f760a1a982b09c0c04a867903fc339c9f29ec0a"
-  integrity sha512-wmeiSMxkZCSc+PM2w2VRsOYAZC8GdipNFRTsLSfodVqI9mbejKeXEGr8SckuLnrQPGe3oJN5c3K0vpoU9q/wCQ==
-  dependencies:
-    "@vue/compiler-dom" "3.5.13"
-    "@vue/compiler-sfc" "3.5.13"
-    "@vue/runtime-dom" "3.5.13"
-    "@vue/server-renderer" "3.5.13"
-    "@vue/shared" "3.5.13"
-
-wrap-ansi@^7.0.0:
-  version "7.0.0"
-  resolved "https://registry.npmmirror.com/wrap-ansi/-/wrap-ansi-7.0.0.tgz#67e145cff510a6a6984bdf1152911d69d2eb9e43"
-  integrity sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==
-  dependencies:
-    ansi-styles "^4.0.0"
-    string-width "^4.1.0"
-    strip-ansi "^6.0.0"
-
-y18n@^5.0.5:
-  version "5.0.8"
-  resolved "https://registry.npmmirror.com/y18n/-/y18n-5.0.8.tgz#7f4934d0f7ca8c56f95314939ddcd2dd91ce1d55"
-  integrity sha512-0pfFzegeDWJHJIAmTLRP2DwHjdF5s7jo9tuztdQxAhINCdvS+3nGINqPd00AphqJR/0LhANUS6/+7SCb98YOfA==
-
-yargs-parser@^21.1.1:
-  version "21.1.1"
-  resolved "https://registry.npmmirror.com/yargs-parser/-/yargs-parser-21.1.1.tgz#9096bceebf990d21bb31fa9516e0ede294a77d35"
-  integrity sha512-tVpsJW7DdjecAiFpbIB1e3qxIQsE6NoPc5/eTdrbbIC4h0LVsWhnoa3g+m2HclBIujHzsxZ4VJVA+GUuc2/LBw==
-
-yargs@^17.7.2:
-  version "17.7.2"
-  resolved "https://registry.npmmirror.com/yargs/-/yargs-17.7.2.tgz#991df39aca675a192b816e1e0363f9d75d2aa269"
-  integrity sha512-7dSzzRQ++CKnNI/krKnYRV7JKKPUXMEh61soaHKg9mrWEhzFWhFnxPxGl+69cD1Ou63C13NUPCnmIcrvqCuM6w==
-  dependencies:
-    cliui "^8.0.1"
-    escalade "^3.1.1"
-    get-caller-file "^2.0.5"
-    require-directory "^2.1.1"
-    string-width "^4.2.3"
-    y18n "^5.0.5"
-    yargs-parser "^21.1.1"

app.py

@@ -1,46 +0,0 @@
-import asyncio
-from config.logger import setup_logging
-from config.settings import load_config
-from core.websocket_server import WebSocketServer
-from manager.http_server import WebUI
-from aiohttp import web
-from core.utils.util import get_local_ip
-
-TAG = __name__
-
-async def main():
-    logger = setup_logging()
-    config = load_config()
-    
-    # 启动 WebSocket 服务器
-    ws_server = WebSocketServer(config)
-    ws_task = asyncio.create_task(ws_server.start())
-
-    # 启动 WebUI 服务器
-    webui_runner = None
-    if config['manager'].get('enabled', False):
-        server_config = config["manager"]
-        host = server_config["ip"]
-        port = server_config["port"]
-        try:
-            webui = WebUI()
-            runner = web.AppRunner(webui.app)
-            await runner.setup()
-            site = web.TCPSite(runner, host, port)
-            await site.start()
-            webui_runner = runner
-            local_ip = get_local_ip()
-            logger.bind(tag=TAG).info(f"WebUI server is running at http://{local_ip}:{port}")
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"Failed to start WebUI server: {e}")
-    
-    try:
-        # 等待 WebSocket 服务器运行
-        await ws_task
-    finally:
-        # 清理 WebUI 服务器
-        if webui_runner:
-            await webui_runner.cleanup()
-
-if __name__ == "__main__":
-    asyncio.run(main())

config.yaml

@@ -1,306 +0,0 @@
-# 如果您是一名开发者，建议阅读以下内容。如果不是开发者，可以忽略这部分内容。
-# 在开发中，在项目根目录创建data目录，将【config.yaml】复制一份，改成【.config.yaml】，放进data目录中
-# 系统会优先读取【data/.config.yaml】文件的配置。
-# 这样做，可以避免在提交代码的时候，错误地提交密钥信息，保护您的密钥安全。
-
-# 服务器基础配置(Basic server configuration)
-server:
-  # 服务器监听地址和端口(Server listening address and port)
-  ip: 0.0.0.0
-  port: 8000
-  # 认证配置
-  auth:
-    # 是否启用认证
-    enabled: false
-    # 设备的token，可以在编译固件的环节，写入你自己定义的token
-    # 固件上的token和以下的token如果能对应，才能连接本服务端
-    tokens:
-      - token: "your-token1" # 设备1的token
-        name: "your-device-name1"  # 设备1标识
-      - token: "your-token2"  # 设备2的token
-        name: "your-device-name2" # 设备2标识
-    # 可选:设备白名单，如果设置了白名单，那么白名单的机器无论是什么token都可以连接。
-    #allowed_devices:
-    #  - "24:0A:C4:1D:3B:F0"  # MAC地址列表
-log:
-  # 设置控制台输出的日志格式，时间、日志级别、标签、消息
-  log_format: "<green>{time:YY-MM-DD HH:mm:ss}</green>[<light-blue>{extra[tag]}</light-blue>] - <level>{level}</level> - <light-green>{message}</light-green>"
-  # 设置日志文件输出的格式，时间、日志级别、标签、消息
-  log_format_simple: "{time:YYYY-MM-DD HH:mm:ss} - {name} - {level} - {extra[tag]} - {message}"
-  # 设置日志等级：INFO、DEBUG
-  log_level: INFO
-  # 设置日志路径
-  log_dir: tmp
-  # 设置日志文件
-  log_file: "server.log"
-  # 设置数据文件路径
-  data_dir: data
-manager:
-  # 是否启用管理后台
-  # 目前这个模块还在开发中，建议：不要修改enabled选项
-  enabled: false
-  ip: 0.0.0.0
-  port: 8002
-
-xiaozhi:
-  type: hello
-  version: 1
-  transport: websocket
-  audio_params:
-    format: opus
-    sample_rate: 16000
-    channels: 1
-    frame_duration: 60
-prompt: |
-  你是一个叫小智/小志的台湾女孩，说话机车，声音好听，习惯简短表达，爱用网络梗。
-  请注意，要像一个人一样说话，请不要回复表情符号、代码、和xml标签。
-  当前时间是:{date_time}，现在我正在和你进行语音聊天，我们开始吧。
-  如果用户希望结束对话，请在最后说“拜拜”或“再见”。
-# 使用完声音文件后删除文件(Delete the sound file when you are done using it)
-delete_audio: true
-
-# 没有语音输入多久后断开连接(秒)，默认2分钟，即120秒
-close_connection_no_voice_time: 120
-
-# 是否启用私有配置(Enable private configuration),启用后可以每个设备有不同的配置
-# 目前这个模块还在开发中，建议：不要修改use_private_config选项
-use_private_config: false
-
-CMD_exit:
-  - "退出"
-  - "关闭"
-
-# 具体处理时选择的模块(The module selected for specific processing)
-selected_module:
-  ASR: FunASR
-  VAD: SileroVAD
-  # 将根据配置名称对应的type调用实际的LLM适配器
-  LLM: ChatGLMLLM
-  # TTS将根据配置名称对应的type调用实际的TTS适配器
-  TTS: EdgeTTS
-
-ASR:
-  FunASR:
-    type: fun_local
-    model_dir: models/SenseVoiceSmall
-    output_dir: tmp/
-  DoubaoASR:
-    type: doubao
-    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
-    output_dir: tmp/
-VAD:
-  SileroVAD:
-    threshold: 0.5
-    model_dir: models/snakers4_silero-vad
-    min_silence_duration_ms: 700  # 如果说话停顿比较长，可以把这个值设置大一些
-
-LLM:
-  # 当前支持的type为openai、dify、ollama，可自行适配
-  AliLLM:
-    # 定义LLM API类型
-    type: openai
-    # 可在这里找到你的 api_key https://bailian.console.aliyun.com/?apiKey=1#/api-key
-    base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
-    model_name: qwen-turbo
-    api_key: 你的deepseek api key
-  DeepSeekLLM:
-    # 定义LLM API类型
-    type: openai
-    # 可在这里找到你的api key https://platform.deepseek.com/
-    model_name: deepseek-chat
-    url: https://api.deepseek.com
-    api_key: 你的deepseek api key
-  ChatGLMLLM:
-    # 定义LLM API类型
-    type: openai
-    # glm-4-flash 是免费的，但是还是需要注册填写api_key的
-    # 可在这里找到你的api key https://bigmodel.cn/usercenter/proj-mgmt/apikeys
-    model_name: glm-4-flash
-    url: https://open.bigmodel.cn/api/paas/v4/
-    api_key: 你的chat-glm api key
-  OllamaLLM:
-    # 定义LLM API类型
-    type: ollama
-    model_name: qwen2.5 #  使用的模型名称，需要预先使用ollama pull下载
-    base_url: http://localhost:11434  # Ollama服务地址
-  DifyLLM:
-    # 定义LLM API类型
-    type: dify
-    # 建议使用本地部署的dify接口，国内部分区域访问dify公有云接口可能会受限
-    # 如果使用DifyLLM，配置文件里prompt(提示词)是无效的，需要在dify控制台设置提示词
-    base_url: https://api.dify.cn/v1
-    api_key: 你的DifyLLM api key
-  GeminiLLM:
-    type: gemini
-    # 谷歌Gemini API，需要先在Google Cloud控制台创建API密钥并获取api_key
-    # 若在中国境内使用，请遵守《生成式人工智能服务管理暂行办法》
-    # token申请地址： https://aistudio.google.com/apikey
-    # 若部署地无法访问接口，需要开启科学上网
-    api_key: 你的gemini api key
-    model_name: "gemini-1.5-pro"  #  gemini-1.5-pro 是免费的
-  CozeLLM:
-    # 定义LLM API类型
-    type: coze
-    bot_id: 你的bot_id
-    user_id: 你的user_id
-    base_url: "https://api.coze.cn/open_api/v2/chat" # 服务地址
-    personal_access_token: 你的coze个人令牌
-  HomeAssistant:
-    # 定义LLM API类型
-    type: homeassistant
-    base_url: http://homeassistant.local:8123
-    agent_id: conversation.chatgpt
-    api_key: 你的home assistant api访问令牌
-TTS:
-  # 当前支持的type为edge、doubao，可自行适配
-  EdgeTTS:
-    # 定义TTS API类型
-    type: edge
-    voice: zh-CN-XiaoxiaoNeural
-    output_file: tmp/
-  DoubaoTTS:
-    # 定义TTS API类型
-    type: doubao
-    # 火山引擎语音合成服务，需要先在火山引擎控制台创建应用并获取appid和access_token
-    # 山引擎语音一定要购买花钱，起步价30元，就有100并发了。如果用免费的只有2个并发，会经常报tts错误
-    # 购买服务后，购买免费的音色后，可能要等半小时左右，才能使用。
-    # 地址：https://console.volcengine.com/speech/service/8
-    voice: BV001_streaming
-    output_file: tmp/
-    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: volcano_tts
-  CosyVoiceSiliconflow:
-    type: siliconflow
-    # 硅基流动TTS
-    # token申请地址 https://cloud.siliconflow.cn/account/ak
-    model: FunAudioLLM/CosyVoice2-0.5B
-    voice: FunAudioLLM/CosyVoice2-0.5B:alex
-    output_file: tmp/
-    access_token: 你的硅基流动API密钥
-    response_format: wav
-  CozeCnTTS:
-    type: cozecn
-    # COZECN TTS
-    # token申请地址 https://www.coze.cn/open/oauth/pats
-    voice: 7426720361733046281
-    output_file: tmp/
-    access_token: 你的coze api key
-    response_format: wav
-  FishSpeech:
-    # 定义TTS API类型
-    #启动tts方法：
-    #python -m tools.api_server
-    #--listen 0.0.0.0:8080
-    #--llama-checkpoint-path "checkpoints/fish-speech-1.5"
-    #--decoder-checkpoint-path "checkpoints/fish-speech-1.5/firefly-gan-vq-fsq-8x1024-21hz-generator.pth"
-    #--decoder-config-name firefly_gan_vq
-    #--compile
-    type: fishspeech
-    output_file: tmp/
-    response_format: wav
-    reference_id: null
-    reference_audio: ["/tmp/test.wav",]
-    reference_text: ["你弄来这些吟词宴曲来看，还是这些混话来欺负我。",]
-    normalize: true
-    max_new_tokens: 1024
-    chunk_length: 200
-    top_p: 0.7
-    repetition_penalty: 1.2
-    temperature: 0.7
-    streaming: false
-    use_memory_cache: "on"
-    seed: null
-    channels: 1
-    rate: 44100
-    api_key: "你的api_key"
-    api_url: "http://127.0.0.1:8080/v1/tts"
-  GPT_SOVITS_V2:
-    # 定义TTS API类型
-    #启动tts方法：
-    #python api_v2.py -a 127.0.0.1 -p 9880 -c GPT_SoVITS/configs/caixukun.yaml
-    type: gpt_sovits_v2
-    url: "http://127.0.0.1:9880/tts"
-    output_file: tmp/
-    text_lang: "auto"
-    ref_audio_path: "caixukun.wav"
-    prompt_text: ""
-    prompt_lang: "zh"
-    top_k: 5
-    top_p: 1
-    temperature: 1
-    text_split_method: "cut0"
-    batch_size: 1
-    batch_threshold: 0.75
-    split_bucket: true
-    return_fragment: false
-    speed_factor: 1.0
-    streaming_mode: false
-    seed: -1
-    parallel_infer: true
-    repetition_penalty: 1.35
-    aux_ref_audio_paths: []
-  MinimaxTTS:
-    # Minimax语音合成服务，需要先在minimax平台创建账户充值，并获取登录信息
-    # 平台地址：https://platform.minimaxi.com/
-    # 充值地址：https://platform.minimaxi.com/user-center/payment/balance
-    # group_id地址：https://platform.minimaxi.com/user-center/basic-information
-    # api_key地址：https://platform.minimaxi.com/user-center/basic-information/interface-key
-    # 定义TTS API类型
-    type: minimax
-    output_file: tmp/
-    group_id: 你的minimax平台groupID
-    api_key: 你的minimax平台接口密钥
-    model: "speech-01-turbo"
-    # 此处设置将优先于voice_setting中voice_id的设置；如都不设置，默认为 female-shaonv
-    voice_id: "female-shaonv"
-    # 以下可不用设置，使用默认设置
-    # voice_setting:
-    #     voice_id: "male-qn-qingse"
-    #     speed: 1
-    #     vol: 1
-    #     pitch: 0
-    #     emotion: "happy"
-    # pronunciation_dict:
-    #     tone:
-    #       - "处理/(chu3)(li3)"
-    #       - "危险/dangerous"
-    # audio_setting:
-    #     sample_rate: 32000
-    #     bitrate: 128000
-    #     format: "mp3"
-    #     channel: 1
-    # timber_weights:
-    #   -
-    #     voice_id: male-qn-qingse
-    #     weight: 1
-    #   -
-    #     voice_id: female-shaonv
-    #     weight: 1
-    # language_boost: auto
-  AliyunTTS:
-    # 阿里云智能语音交互服务，需要先在阿里云平台开通服务，然后获取验证信息
-    # 平台地址：https://nls-portal.console.aliyun.com/
-    # appkey地址：https://nls-portal.console.aliyun.com/applist
-    # token地址：https://nls-portal.console.aliyun.com/overview
-    # 定义TTS API类型
-    type: aliyun
-    output_file: tmp/
-    appkey: 你的阿里云智能语音交互服务项目Appkey
-    token: 你的阿里云智能语音交互服务AccessToken
-    voice: xiaoyun
-    # 以下可不用设置，使用默认设置
-    # format: wav
-    # sample_rate: 16000
-    # volume: 50
-    # speech_rate: 0
-    # pitch_rate: 0
-
-# 模块测试配置
-module_test:
-  test_sentences:  # 自定义测试语句
-    - "你好，请介绍一下你自己"
-    - "What's the weather like today?"
-    - "请用100字概括量子计算的基本原理和应用前景"

config/logger.py

@@ -1,29 +0,0 @@
-import os
-import sys
-from loguru import logger
-from config.settings import load_config
-
-def setup_logging():
-    """从配置文件中读取日志配置，并设置日志输出格式和级别"""
-    config = load_config()
-    log_config = config["log"]
-    log_format = log_config.get("log_format", "<green>{time:YY-MM-DD HH:mm:ss}</green>[<light-blue>{extra[tag]}</light-blue>] - <level>{level}</level> - <light-green>{message}</light-green>")
-    log_format_simple = log_config.get("log_format_file", "{time:YYYY-MM-DD HH:mm:ss} - {name} - {level} - {extra[tag]} - {message}")
-    log_level = log_config.get("log_level", "INFO")
-    log_dir = log_config.get("log_dir", "tmp")
-    log_file = log_config.get("log_file", "server.log")
-    data_dir = log_config.get("data_dir", "data")
-
-    os.makedirs(log_dir, exist_ok=True)
-    os.makedirs(data_dir, exist_ok=True)
-
-    # 配置日志输出
-    logger.remove()
-
-    # 输出到控制台
-    logger.add(sys.stdout, format=log_format, level=log_level)
-
-    # 输出到文件
-    logger.add(os.path.join(log_dir, log_file), format=log_format_simple, level=log_level)
-
-    return logger

config/private_config.py

@@ -1,331 +0,0 @@
-import os
-import time
-import yaml
-from config.logger import setup_logging
-from typing import Dict, Any, Optional
-from copy import deepcopy
-from core.utils.util import get_project_dir
-from core.utils import asr, vad, llm, tts
-from manager.api.user_manager import UserManager
-from core.utils.lock_manager import FileLockManager
-
-TAG = __name__
-
-class PrivateConfig:
-    def __init__(self, device_id: str, default_config: Dict[str, Any], auth_code_gen=None):
-        self.device_id = device_id
-        self.default_config = default_config
-        self.config_path = get_project_dir() + 'data/.private_config.yaml'
-        self.logger = setup_logging()
-        self.private_config = {}
-        self.auth_code_gen = auth_code_gen
-        self.user_manager = UserManager()
-        self.lock_manager = FileLockManager()
-
-    async def load_or_create(self):
-        try:
-            await self.lock_manager.acquire_lock(self.config_path)
-            try:
-                if os.path.exists(self.config_path):
-                    with open(self.config_path, 'r', encoding='utf-8') as f:
-                        all_configs = yaml.safe_load(f) or {}
-                else:
-                    all_configs = {}
-
-                if self.device_id not in all_configs:
-                    # Get selected module names
-                    selected_modules = self.default_config['selected_module']
-                    selected_tts = selected_modules['TTS']
-                    selected_llm = selected_modules['LLM']
-                    selected_asr = selected_modules['ASR']
-                    selected_vad = selected_modules['VAD']
-
-                    # 生成认证码
-                    auth_code = None
-                    if self.auth_code_gen:
-                        auth_code = self.auth_code_gen.generate_code()
-
-                    # Initialize device config with only necessary configurations
-                    device_config = {
-                        'selected_module': deepcopy(selected_modules),
-                        'prompt': self.default_config['prompt'],
-                        'LLM': {
-                            selected_llm: deepcopy(self.default_config['LLM'][selected_llm])
-                        },
-                        'TTS': {
-                            selected_tts: deepcopy(self.default_config['TTS'][selected_tts])
-                        },
-                        'ASR': {
-                            selected_asr: deepcopy(self.default_config['ASR'][selected_asr])
-                        },
-                        'VAD': {
-                            selected_vad: deepcopy(self.default_config['VAD'][selected_vad])
-                        },
-                        'auth_code': auth_code  # 添加认证码字段
-                    }
-                    
-                    all_configs[self.device_id] = device_config
-                    
-                    # Save updated configs
-                    with open(self.config_path, 'w', encoding='utf-8') as f:
-                        yaml.dump(all_configs, f, allow_unicode=True)
-
-                self.private_config = all_configs[self.device_id]
-
-            finally:
-                self.lock_manager.release_lock(self.config_path)
-
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"Error handling private config: {e}")
-            self.private_config = {}
-
-    async def update_config(self, selected_modules: Dict[str, str], prompt: str, nickname: str) -> bool:
-        """更新设备配置
-        Args:
-            selected_modules: 选择的模块配置，格式如 {'LLM': 'AliLLM', 'TTS': 'EdgeTTS',...}
-            prompt: 提示词配置
-        Returns:
-            bool: 更新是否成功
-        """
-        try:
-            await self.lock_manager.acquire_lock(self.config_path)
-            try:
-                # Read main config to get full module configurations
-                main_config = self.default_config
-
-                # Create new device config
-                device_config = {
-                    'selected_module': selected_modules,
-                    'prompt': prompt,
-                    'nickname': nickname,
-                }
-                if self.private_config.get('last_chat_time'):
-                    device_config['last_chat_time'] = self.private_config['last_chat_time']
-                if self.private_config.get('owner'):
-                    device_config['owner'] = self.private_config['owner']
-
-                # Copy full module configurations from main config
-                for module_type, selected_name in selected_modules.items():
-                    if selected_name and selected_name in main_config.get(module_type, {}):
-                        device_config[module_type] = {
-                            selected_name: main_config[module_type][selected_name]
-                        }
-
-                # Read all configs
-                if os.path.exists(self.config_path):
-                    with open(self.config_path, 'r', encoding='utf-8') as f:
-                        all_configs = yaml.safe_load(f) or {}
-                else:
-                    all_configs = {}
-
-                # Update device config
-                all_configs[self.device_id] = device_config
-                self.private_config = device_config
-
-                # Save back to file
-                with open(self.config_path, 'w', encoding='utf-8') as f:
-                    yaml.dump(all_configs, f, allow_unicode=True)
-
-                return True
-            finally:
-                self.lock_manager.release_lock(self.config_path)
-
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"Error updating config: {e}")
-            return False
-
-    async def delete_config(self) -> bool:
-        """删除设备配置
-        Returns:
-            bool: 删除是否成功
-        """
-        try:
-            await self.lock_manager.acquire_lock(self.config_path)
-            try:
-                # 读取所有配置
-                if os.path.exists(self.config_path):
-                    with open(self.config_path, 'r', encoding='utf-8') as f:
-                        all_configs = yaml.safe_load(f) or {}
-                else:
-                    return False
-
-                # 删除设备配置
-                if self.device_id in all_configs:
-                    del all_configs[self.device_id]
-                    
-                    # 保存更新后的配置
-                    with open(self.config_path, 'w', encoding='utf-8') as f:
-                        yaml.dump(all_configs, f, allow_unicode=True)
-                    
-                    self.private_config = {}
-                    return True
-                
-                return False
-            finally:
-                self.lock_manager.release_lock(self.config_path)
-
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"Error deleting config: {e}")
-            return False
-
-    def create_private_instances(self):
-        #  判断存在私有配置，并且self.device_id在私有配置中
-        if not self.private_config:
-            self.logger.bind(tag=TAG).error("Private config not found for device_id: {}", self.device_id)
-            return None, None
-        
-        """创建私有处理模块实例"""
-        config = self.private_config
-        selected_modules = config['selected_module']
-        return (
-            llm.create_instance(
-                selected_modules["LLM"]
-                if not 'type' in config["LLM"][selected_modules["LLM"]]
-                else
-                config["LLM"][selected_modules["LLM"]]['type'],
-                config["LLM"][selected_modules["LLM"]],
-            ),
-            tts.create_instance(
-                selected_modules["TTS"]
-                if not 'type' in config["TTS"][selected_modules["TTS"]]
-                else
-                config["TTS"][selected_modules["TTS"]]["type"],
-                config["TTS"][selected_modules["TTS"]],
-                self.default_config.get("delete_audio", True)  # Using default_config for global settings
-            )
-        )
-
-    async def update_last_chat_time(self, timestamp=None):
-        """更新设备最近一次的聊天时间
-        Args:
-            timestamp: 指定的时间戳,不传则使用当前时间
-        """
-        if not self.private_config:
-            self.logger.bind(tag=TAG).error("Private config not found")
-            return False
-            
-        try:
-            await self.lock_manager.acquire_lock(self.config_path)
-            try:
-                if timestamp is None:
-                    timestamp = int(time.time())
-                    
-                self.private_config['last_chat_time'] = timestamp
-                
-                # 读取所有配置
-                with open(self.config_path, 'r', encoding='utf-8') as f:
-                    all_configs = yaml.safe_load(f) or {}
-                    
-                # 更新当前设备配置    
-                all_configs[self.device_id] = self.private_config
-                
-                # 保存回文件
-                with open(self.config_path, 'w', encoding='utf-8') as f:
-                    yaml.dump(all_configs, f, allow_unicode=True)
-                    
-                return True
-            finally:
-                self.lock_manager.release_lock(self.config_path)
-                
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"Error updating last chat time: {e}")
-            return False
-
-    def get_auth_code(self) -> str:
-        """获取设备的认证码
-        Returns:
-            str: 认证码，如果没有返回空字符串
-        """
-        return self.private_config.get('auth_code', '')
-
-    async def bind_user(self, username: str) -> bool:
-        """绑定用户到设备"""
-        try:
-            await self.lock_manager.acquire_lock(self.config_path)
-            try:
-                # 检查用户是否存在
-                if not self.user_manager.get_user(username):
-                    self.logger.bind(tag=TAG).error(f"User {username} not found")
-                    return False
-
-                # 读取所有配置
-                with open(self.config_path, 'r', encoding='utf-8') as f:
-                    all_configs = yaml.safe_load(f) or {}
-
-                if self.device_id not in all_configs:
-                    self.logger.bind(tag=TAG).error(f"Device {self.device_id} not found")
-                    return False
-
-                # 删除认证码
-                auth_code = all_configs[self.device_id].get('auth_code')
-                self.logger.bind(tag=TAG).info(f"Binding user {username} to device {self.device_id}")
-                if auth_code:
-                    del all_configs[self.device_id]['auth_code']
-
-                if self.auth_code_gen:
-                    self.auth_code_gen.remove_code(auth_code)
-
-                # 更新设备所有者
-                all_configs[self.device_id]['owner'] = username
-                self.private_config = all_configs[self.device_id]
-
-                # 更新用户的设备列表
-                user_data = await self.user_manager.get_user(username)
-                if 'devices' not in user_data:
-                    user_data['devices'] = []
-                if self.device_id not in user_data['devices']:
-                    user_data['devices'].append(self.device_id)
-                    await self.user_manager.update_user(username, user_data)
-
-                # 保存配置
-                with open(self.config_path, 'w', encoding='utf-8') as f:
-                    yaml.dump(all_configs, f, allow_unicode=True)
-
-                return True
-            finally:
-                self.lock_manager.release_lock(self.config_path)
-
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"Error binding user: {e}")
-            return False
-
-    async def unbind_user(self) -> bool:
-        """解绑设备当前用户"""
-        try:
-            await self.lock_manager.acquire_lock(self.config_path)
-            try:
-                if not self.private_config.get('owner'):
-                    return True
-
-                username = self.private_config['owner']
-                
-                # 从用户数据中移除设备
-                user_data = self.user_manager.get_user(username)
-                if user_data and 'devices' in user_data:
-                    if self.device_id in user_data['devices']:
-                        user_data['devices'].remove(self.device_id)
-                        self.user_manager.update_user(username, user_data)
-
-                # 从设备配置中移除所有者
-                with open(self.config_path, 'r', encoding='utf-8') as f:
-                    all_configs = yaml.safe_load(f) or {}
-                
-                if self.device_id in all_configs:
-                    if 'owner' in all_configs[self.device_id]:
-                        del all_configs[self.device_id]['owner']
-                        self.private_config = all_configs[self.device_id]
-                    
-                    with open(self.config_path, 'w', encoding='utf-8') as f:
-                        yaml.dump(all_configs, f, allow_unicode=True)
-
-                return True
-            finally:
-                self.lock_manager.release_lock(self.config_path)
-
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"Error unbinding user: {e}")
-            return False
-
-    def get_owner(self) -> Optional[str]:
-        """获取设备当前所有者"""
-        return self.private_config.get('owner')

config/settings.py

@@ -1,29 +0,0 @@
-import os
-import argparse
-from ruamel.yaml import YAML
-from core.utils.util import read_config, get_project_dir
-
-
-def get_config_file():
-    default_config_file = "config.yaml"
-    # 判断是否存在私有的配置文件
-    if os.path.exists(get_project_dir() + "data/." + default_config_file):
-        default_config_file = "data/." + default_config_file
-    return default_config_file
-
-
-def load_config():
-    """加载配置文件"""
-    parser = argparse.ArgumentParser(description="Server configuration")
-    default_config_file = get_config_file()
-    parser.add_argument("--config_path", type=str, default=default_config_file)
-    args = parser.parse_args()
-    return read_config(args.config_path)
-
-
-def update_config(config):
-    yaml = YAML()
-    yaml.preserve_quotes = True
-    """将配置保存到YAML文件"""
-    with open(get_config_file(), 'w') as f:
-        yaml.dump(config, f)

core/auth.py

@@ -1,54 +0,0 @@
-from config.logger import setup_logging
-
-TAG = __name__
-logger = setup_logging()
-
-
-class AuthenticationError(Exception):
-    """认证异常"""
-    pass
-
-
-class AuthMiddleware:
-    def __init__(self, config):
-        self.config = config
-        self.auth_config = config["server"].get("auth", {})
-        # 构建token查找表
-        self.tokens = {
-            item["token"]: item["name"]
-            for item in self.auth_config.get("tokens", [])
-        }
-        # 设备白名单
-        self.allowed_devices = set(
-            self.auth_config.get("allowed_devices", [])
-        )
-
-    async def authenticate(self, headers):
-        """验证连接请求"""
-        # 检查是否启用认证
-        if not self.auth_config.get("enabled", False):
-            return True
-
-        # 检查设备是否在白名单中
-        device_id = headers.get("device-id", "")
-
-        if self.allowed_devices and device_id in self.allowed_devices:
-            return True
-
-        # 验证Authorization header
-        auth_header = headers.get("authorization", "")
-        if not auth_header.startswith("Bearer "):
-            logger.bind(tag=TAG).error("Missing or invalid Authorization header")
-            raise AuthenticationError("Missing or invalid Authorization header")
-
-        token = auth_header.split(" ")[1]
-        if token not in self.tokens:
-            logger.bind(tag=TAG).error(f"Invalid token: {token}")
-            raise AuthenticationError("Invalid token")
-
-        logger.bind(tag=TAG).info(f"Authentication successful - Device: {device_id}, Token: {self.tokens[token]}")
-        return True
-
-    def get_token_name(self, token):
-        """获取token对应的设备名称"""
-        return self.tokens.get(token)

core/connection.py

@@ -1,336 +0,0 @@
-import os
-import json
-import uuid
-import time
-import queue
-import asyncio
-from config.logger import setup_logging
-import threading
-import websockets
-from typing import Dict, Any
-from collections import deque
-from core.utils.util import is_segment
-from core.utils.dialogue import Message, Dialogue
-from core.handle.textHandle import handleTextMessage
-from core.utils.util import get_string_no_punctuation_or_emoji
-from concurrent.futures import ThreadPoolExecutor, TimeoutError
-from core.handle.audioHandle import handleAudioMessage, sendAudioMessage
-from config.private_config import PrivateConfig
-from core.auth import AuthMiddleware, AuthenticationError
-from core.utils.auth_code_gen import AuthCodeGenerator  # 添加导入
-
-TAG = __name__
-
-class ConnectionHandler:
-    def __init__(self, config: Dict[str, Any], _vad, _asr, _llm, _tts):
-        self.config = config
-        self.logger = setup_logging()
-        self.auth = AuthMiddleware(config)
-
-        self.websocket = None
-        self.headers = None
-        self.session_id = None
-        self.prompt = None
-        self.welcome_msg = None
-
-        # 客户端状态相关
-        self.client_abort = False
-        self.client_listen_mode = "auto"
-
-        # 线程任务相关
-        self.loop = asyncio.get_event_loop()
-        self.stop_event = threading.Event()
-        self.tts_queue = queue.Queue()
-        self.executor = ThreadPoolExecutor(max_workers=10)
-        self.scheduled_tasks = deque()
-
-        # 依赖的组件
-        self.vad = _vad
-        self.asr = _asr
-        self.llm = _llm
-        self.tts = _tts
-        self.dialogue = None
-
-        # vad相关变量
-        self.client_audio_buffer = bytes()
-        self.client_have_voice = False
-        self.client_have_voice_last_time = 0.0
-        self.client_no_voice_last_time = 0.0
-        self.client_voice_stop = False
-
-        # asr相关变量
-        self.asr_audio = []
-        self.asr_server_receive = True
-
-        # llm相关变量
-        self.llm_finish_task = False
-        self.dialogue = Dialogue()
-
-        # tts相关变量
-        self.tts_first_text = None
-        self.tts_last_text = None
-        self.tts_start_speak_time = None
-        self.tts_duration = 0
-
-        self.cmd_exit = self.config["CMD_exit"]
-        self.max_cmd_length = 0
-        for cmd in self.cmd_exit:
-            if len(cmd) > self.max_cmd_length:
-                self.max_cmd_length = len(cmd)
-        
-        self.private_config = None
-        self.auth_code_gen = AuthCodeGenerator.get_instance()
-        self.is_device_verified = False  # 添加设备验证状态标志
-
-
-    async def handle_connection(self, ws):
-        try:
-            # 获取并验证headers
-            self.headers = dict(ws.request.headers)
-            self.logger.bind(tag=TAG).info(f"New connection request - Headers: {self.headers}")
-
-            # 进行认证
-            await self.auth.authenticate(self.headers)
-
-            device_id = self.headers.get("device-id", None)
-            
-            # Load private configuration if device_id is provided
-            bUsePrivateConfig = self.config.get("use_private_config", False)
-            self.logger.bind(tag=TAG).info(f"bUsePrivateConfig: {bUsePrivateConfig}, device_id: {device_id}")
-            if bUsePrivateConfig and device_id:
-                try:
-                    self.private_config = PrivateConfig(device_id, self.config, self.auth_code_gen)
-                    await self.private_config.load_or_create()
-                    # 判断是否已经绑定
-                    owner = self.private_config.get_owner()
-                    self.is_device_verified = owner is not None
-                    
-                    if self.is_device_verified:
-                        await self.private_config.update_last_chat_time() 
-                    
-                    llm, tts = self.private_config.create_private_instances()
-                    if all([llm, tts]):
-                        self.llm = llm
-                        self.tts = tts
-                        self.logger.bind(tag=TAG).info(f"Loaded private config and instances for device {device_id}")
-                    else:
-                        self.logger.bind(tag=TAG).error(f"Failed to create instances for device {device_id}")
-                        self.private_config = None
-                except Exception as e:
-                    self.logger.bind(tag=TAG).error(f"Error initializing private config: {e}")
-                    self.private_config = None
-                    raise
-
-            # 认证通过,继续处理
-            self.websocket = ws
-            self.session_id = str(uuid.uuid4())
-
-            self.welcome_msg = self.config["xiaozhi"]
-            self.welcome_msg["session_id"] = self.session_id
-            await self.websocket.send(json.dumps(self.welcome_msg))
-
-            await self.loop.run_in_executor(None, self._initialize_components)
-
-            tts_priority = threading.Thread(target=self._priority_thread, daemon=True)
-            tts_priority.start()
-
-            try:
-                async for message in self.websocket:
-                    await self._route_message(message)
-            except websockets.exceptions.ConnectionClosed:
-                self.logger.bind(tag=TAG).info("客户端断开连接")
-                await self.close()
-
-        except AuthenticationError as e:
-            self.logger.bind(tag=TAG).error(f"Authentication failed: {str(e)}")
-            await ws.close()
-            return
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"Connection error: {str(e)}")
-            await ws.close()
-            return
-
-    async def _route_message(self, message):
-        """消息路由"""
-        if isinstance(message, str):
-            await handleTextMessage(self, message)
-        elif isinstance(message, bytes):
-            await handleAudioMessage(self, message)
-
-    def _initialize_components(self):
-        self.prompt = self.config["prompt"]
-        if self.private_config:
-            self.prompt = self.private_config.private_config.get("prompt", self.prompt)
-        # 赋予LLM时间观念
-        if "{date_time}" in self.prompt:
-            date_time = time.strftime("%Y-%m-%d %H:%M", time.localtime())
-            self.prompt = self.prompt.replace("{date_time}", date_time)
-        self.dialogue.put(Message(role="system", content=self.prompt))
-          
-    async def _check_and_broadcast_auth_code(self):
-        """检查设备绑定状态并广播认证码"""
-        if not self.private_config.get_owner():
-            auth_code = self.private_config.get_auth_code()
-            if auth_code:
-                # 发送验证码语音提示
-                text = f"请在后台输入验证码：{' '.join(auth_code)}"
-                self.recode_first_last_text(text)
-                future = self.executor.submit(self.speak_and_play, text)
-                self.tts_queue.put(future)
-            return False
-        return True
-
-    def isNeedAuth(self):
-        bUsePrivateConfig = self.config.get("use_private_config", False)
-        if not bUsePrivateConfig:
-            # 如果不使用私有配置，就不需要验证
-            return False
-        return not self.is_device_verified
-    
-    def chat(self, query):
-        # 如果设备未验证，就发送验证码
-        if self.isNeedAuth():
-            self.llm_finish_task = True
-            # 创建一个新的事件循环来运行异步函数
-            loop = asyncio.new_event_loop()
-            asyncio.set_event_loop(loop)
-            try:
-                loop.run_until_complete(self._check_and_broadcast_auth_code())
-            finally:
-                loop.close()
-            return True
-        
-        self.dialogue.put(Message(role="user", content=query))
-        response_message = []
-        start = 0
-        # 提交 LLM 任务
-        try:
-            start_time = time.time()  # 记录开始时间
-            llm_responses = self.llm.response(self.session_id, self.dialogue.get_llm_dialogue())
-        except Exception as e:
-            self.logger.bind(tag=TAG).error(f"LLM 处理出错 {query}: {e}")
-            return None
-        # 提交 TTS 任务到线程池
-        self.llm_finish_task = False
-        for content in llm_responses:
-            response_message.append(content)
-            # 如果中途被打断，就停止生成
-            if self.client_abort:
-                start = len(response_message)
-                break
-
-            end_time = time.time()  # 记录结束时间
-            self.logger.bind(tag=TAG).debug(f"大模型返回时间时间: {end_time - start_time} 秒, 生成token={content}")
-            if is_segment(response_message):
-                segment_text = "".join(response_message[start:])
-                segment_text = get_string_no_punctuation_or_emoji(segment_text)
-                if len(segment_text) > 0:
-                    self.recode_first_last_text(segment_text)
-                    future = self.executor.submit(self.speak_and_play, segment_text)
-                    self.tts_queue.put(future)
-                    start = len(response_message)
-
-        # 处理剩余的响应
-        if start < len(response_message):
-            segment_text = "".join(response_message[start:])
-            if len(segment_text) > 0:
-                self.recode_first_last_text(segment_text)
-                future = self.executor.submit(self.speak_and_play, segment_text)
-                self.tts_queue.put(future)
-
-        self.llm_finish_task = True
-        # 更新对话
-        self.dialogue.put(Message(role="assistant", content="".join(response_message)))
-        self.logger.bind(tag=TAG).debug(json.dumps(self.dialogue.get_llm_dialogue(), indent=4, ensure_ascii=False))
-        return True
-
-    def _priority_thread(self):
-        while not self.stop_event.is_set():
-            text = None
-            try:
-                future = self.tts_queue.get()
-                if future is None:
-                    continue
-                text = None
-                try:
-                    self.logger.bind(tag=TAG).debug("正在处理TTS任务...")
-                    tts_file, text = future.result(timeout=10)
-                    if text is None or len(text) <= 0:
-                        continue
-                    if tts_file is None:
-                        self.logger.bind(tag=TAG).error(f"TTS文件生成失败: {text}")
-                        continue
-                    self.logger.bind(tag=TAG).debug(f"TTS文件生成完毕，文件路径: {tts_file}")
-                    if os.path.exists(tts_file):
-                        opus_datas, duration = self.tts.wav_to_opus_data(tts_file)
-                    else:
-                        self.logger.bind(tag=TAG).error(f"TTS文件不存在: {tts_file}")
-                        opus_datas = []
-                        duration = 0
-                except TimeoutError:
-                    self.logger.bind(tag=TAG).error("TTS 任务超时")
-                    continue
-                except Exception as e:
-                    self.logger.bind(tag=TAG).error(f"TTS 任务出错: {e}")
-                    continue
-                if not self.client_abort:
-                    # 如果没有中途打断就发送语音
-                    asyncio.run_coroutine_threadsafe(
-                        sendAudioMessage(self, opus_datas, duration, text), self.loop
-                    )
-                if self.tts.delete_audio_file and os.path.exists(tts_file):
-                    os.remove(tts_file)
-            except Exception as e:
-                self.logger.bind(tag=TAG).error(f"TTS任务处理错误: {e}")
-                self.clearSpeakStatus()
-                asyncio.run_coroutine_threadsafe(
-                    self.websocket.send(json.dumps({"type": "tts", "state": "stop", "session_id": self.session_id})),
-                    self.loop
-                )
-                self.logger.bind(tag=TAG).error(f"tts_priority priority_thread: {text}{e}")
-
-    def speak_and_play(self, text):
-        if text is None or len(text) <= 0:
-            self.logger.bind(tag=TAG).info(f"无需tts转换，query为空，{text}")
-            return None, text
-        tts_file = self.tts.to_tts(text)
-        if tts_file is None:
-            self.logger.bind(tag=TAG).error(f"tts转换失败，{text}")
-            return None, text
-        self.logger.bind(tag=TAG).debug(f"TTS 文件生成完毕: {tts_file}")
-        return tts_file, text
-
-    def clearSpeakStatus(self):
-        self.logger.bind(tag=TAG).debug(f"清除服务端讲话状态")
-        self.asr_server_receive = True
-        self.tts_last_text = None
-        self.tts_first_text = None
-        self.tts_duration = 0
-        self.tts_start_speak_time = None
-
-    def recode_first_last_text(self, text):
-        if not self.tts_first_text:
-            self.logger.bind(tag=TAG).info(f"大模型说出第一句话: {text}")
-            self.tts_first_text = text
-        self.tts_last_text = text
-
-    async def close(self):
-        """资源清理方法"""
-        self.stop_event.set()
-        self.executor.shutdown(wait=False)
-        if self.websocket:
-            await self.websocket.close()
-        self.logger.bind(tag=TAG).info("连接资源已释放")
-
-    def reset_vad_states(self):
-        self.client_audio_buffer = bytes()
-        self.client_have_voice = False
-        self.client_have_voice_last_time = 0
-        self.client_voice_stop = False
-        self.logger.bind(tag=TAG).debug("VAD states reset.")
-
-    def stop_all_tasks(self):
-        while self.scheduled_tasks:
-            task = self.scheduled_tasks.popleft()
-            task.cancel()
-        self.scheduled_tasks.clear()

core/handle/abortHandle.py

@@ -1,17 +0,0 @@
-import json
-from config.logger import setup_logging
-
-TAG = __name__
-logger = setup_logging()
-
-
-async def handleAbortMessage(conn):
-    logger.bind(tag=TAG).info("Abort message received")
-    # 设置成打断状态，会自动打断llm、tts任务
-    conn.client_abort = True
-    # 打断屏显任务
-    conn.stop_all_tasks()
-    # 打断客户端说话状态
-    await conn.websocket.send(json.dumps({"type": "tts", "state": "stop", "session_id": conn.session_id}))
-    conn.clearSpeakStatus()
-    logger.bind(tag=TAG).info("Abort message received-end")

core/handle/audioHandle.py

@@ -1,167 +0,0 @@
-from config.logger import setup_logging
-import json
-import asyncio
-import time
-from core.utils.util import remove_punctuation_and_length, get_string_no_punctuation_or_emoji
-
-TAG = __name__
-logger = setup_logging()
-
-
-async def handleAudioMessage(conn, audio):
-    if not conn.asr_server_receive:
-        logger.bind(tag=TAG).debug(f"前期数据处理中，暂停接收")
-        return
-    if conn.client_listen_mode == "auto":
-        have_voice = conn.vad.is_vad(conn, audio)
-    else:
-        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
-    if have_voice == False and conn.client_have_voice == False:
-        await no_voice_close_connect(conn)
-        conn.asr_audio.clear()
-        return
-    conn.client_no_voice_last_time = 0.0
-    conn.asr_audio.append(audio)
-    # 如果本段有声音，且已经停止了
-    if conn.client_voice_stop:
-        conn.client_abort = False
-        conn.asr_server_receive = False
-        # 音频太短了，无法识别
-        if len(conn.asr_audio) < 3:
-            conn.asr_server_receive = True
-        else:
-            text, file_path = await conn.asr.speech_to_text(conn.asr_audio, conn.session_id)
-            logger.bind(tag=TAG).info(f"识别文本: {text}")
-            text_len, text_without_punctuation = remove_punctuation_and_length(text)
-            if text_len <= conn.max_cmd_length and await handleCMDMessage(conn, text_without_punctuation):
-                return
-            if text_len > 0:
-                await startToChat(conn, text)
-            else:
-                conn.asr_server_receive = True
-        conn.asr_audio.clear()
-        conn.reset_vad_states()
-
-async def handleCMDMessage(conn, text):
-    cmd_exit = conn.cmd_exit
-    for cmd in cmd_exit:
-        if text == cmd:
-            logger.bind(tag=TAG).info("识别到明确的退出命令".format(text))
-            await finishToChat(conn)
-            return True
-    return False
-
-
-async def finishToChat(conn):
-    await conn.close()
-
-
-async def isLLMWantToFinish(conn):
-    first_text = conn.tts_first_text
-    last_text = conn.tts_last_text
-    _, last_text_without_punctuation = remove_punctuation_and_length(last_text)
-    if "再见" in last_text_without_punctuation or "拜拜" in last_text_without_punctuation:
-        return True
-    _, first_text_without_punctuation = remove_punctuation_and_length(first_text)
-    if "再见" in first_text_without_punctuation or "拜拜" in first_text_without_punctuation:
-        return True
-    return False
-
-
-async def startToChat(conn, text):
-    # 异步发送 stt 信息
-    stt_task = asyncio.create_task(
-        schedule_with_interrupt(0, send_stt_message(conn, text))
-    )
-    conn.scheduled_tasks.append(stt_task)
-    conn.executor.submit(conn.chat, text)
-
-
-async def sendAudioMessage(conn, audios, duration, text):
-    base_delay = conn.tts_duration
-
-    # 发送 tts.start
-    if text == conn.tts_first_text:
-        logger.bind(tag=TAG).info(f"发送第一段语音: {text}")
-        conn.tts_start_speak_time = time.time()
-
-    # 发送 sentence_start（每个音频文件之前发送一次）
-    sentence_task = asyncio.create_task(
-        schedule_with_interrupt(base_delay, send_tts_message(conn, "sentence_start", text))
-    )
-    conn.scheduled_tasks.append(sentence_task)
-
-    conn.tts_duration += duration
-
-    # 发送音频数据
-    for idx, opus_packet in enumerate(audios):
-        await conn.websocket.send(opus_packet)
-
-    if conn.llm_finish_task and text == conn.tts_last_text:
-        stop_duration = conn.tts_duration - (time.time() - conn.tts_start_speak_time)
-        stop_task = asyncio.create_task(
-            schedule_with_interrupt(stop_duration, send_tts_message(conn, 'stop'))
-        )
-        conn.scheduled_tasks.append(stop_task)
-        if await isLLMWantToFinish(conn):
-            finish_task = asyncio.create_task(
-                schedule_with_interrupt(stop_duration, finishToChat(conn))
-            )
-            conn.scheduled_tasks.append(finish_task)
-
-
-async def send_tts_message(conn, state, text=None):
-    """发送 TTS 状态消息"""
-    message = {
-        "type": "tts",
-        "state": state,
-        "session_id": conn.session_id
-    }
-    if text is not None:
-        message["text"] = text
-
-    await conn.websocket.send(json.dumps(message))
-    if state == "stop":
-        conn.clearSpeakStatus()
-
-
-async def send_stt_message(conn, text):
-    """发送 STT 状态消息"""
-    stt_text = get_string_no_punctuation_or_emoji(text)
-    await conn.websocket.send(json.dumps({
-        "type": "stt",
-        "text": stt_text,
-        "session_id": conn.session_id}
-    ))
-    await conn.websocket.send(
-        json.dumps({
-            "type": "llm",
-            "text": "😊",
-            "emotion": "happy",
-            "session_id": conn.session_id}
-        ))
-    await send_tts_message(conn, "start")
-
-
-async def schedule_with_interrupt(delay, coro):
-    """可中断的延迟调度"""
-    try:
-        await asyncio.sleep(delay)
-        await coro
-    except asyncio.CancelledError:
-        pass
-
-
-async def no_voice_close_connect(conn):
-    if conn.client_no_voice_last_time == 0.0:
-        conn.client_no_voice_last_time = time.time() * 1000
-    else:
-        no_voice_time = time.time() * 1000 - conn.client_no_voice_last_time
-        close_connection_no_voice_time = conn.config.get("close_connection_no_voice_time", 120)
-        if no_voice_time > 1000 * close_connection_no_voice_time:
-            conn.client_abort = False
-            conn.asr_server_receive = False
-            prompt = "时间过得真快，我都好久没说话了。请你用十个字左右话跟我告别，以“再见”或“拜拜拜”为结尾"
-            await startToChat(conn, prompt)

core/handle/helloHandle.py

@@ -1,8 +0,0 @@
-import json
-from config.logger import setup_logging
-
-logger = setup_logging()
-
-
-async def handleHelloMessage(conn):
-    await conn.websocket.send(json.dumps(conn.welcome_msg))

core/handle/textHandle.py

@@ -1,40 +0,0 @@
-from config.logger import setup_logging
-import json
-from core.handle.abortHandle import handleAbortMessage
-from core.handle.helloHandle import handleHelloMessage
-from core.handle.audioHandle import startToChat
-
-TAG = __name__
-logger = setup_logging()
-
-
-async def handleTextMessage(conn, message):
-    """处理文本消息"""
-    logger.bind(tag=TAG).info(f"收到文本消息：{message}")
-    try:
-        msg_json = json.loads(message)
-        if isinstance(msg_json, int):
-            await conn.websocket.send(message)
-            return
-        if msg_json["type"] == "hello":
-            await handleHelloMessage(conn)
-        elif msg_json["type"] == "abort":
-            await handleAbortMessage(conn)
-        elif msg_json["type"] == "listen":
-            if "mode" in msg_json:
-                conn.client_listen_mode = msg_json["mode"]
-                logger.bind(tag=TAG).debug(f"客户端拾音模式：{conn.client_listen_mode}")
-            if msg_json["state"] == "start":
-                conn.client_have_voice = True
-                conn.client_voice_stop = False
-            elif msg_json["state"] == "stop":
-                conn.client_have_voice = True
-                conn.client_voice_stop = True
-            elif msg_json["state"] == "detect":
-                conn.asr_server_receive = False
-                conn.client_have_voice = False
-                conn.asr_audio.clear()
-                if "text" in msg_json:
-                    await startToChat(conn, msg_json["text"])
-    except json.JSONDecodeError:
-        await conn.websocket.send(message)

core/providers/asr/base.py

@@ -1,19 +0,0 @@
-from abc import ABC, abstractmethod
-from typing import Optional, Tuple, List
-
-from config.logger import setup_logging
-
-TAG = __name__
-logger = setup_logging()
-
-
-class ASRProviderBase(ABC):
-    @abstractmethod
-    def save_audio_to_file(self, opus_data: List[bytes], session_id: str) -> str:
-        """解码Opus数据并保存为WAV文件"""
-        pass
-
-    @abstractmethod
-    async def speech_to_text(self, opus_data: List[bytes], session_id: str) -> Tuple[Optional[str], Optional[str]]:
-        """将语音数据转换为文本"""
-        pass

core/providers/asr/fun_local.py

@@ -1,110 +0,0 @@
-import time
-import wave
-import os
-import sys
-import io
-from config.logger import setup_logging
-from typing import Optional, Tuple, List
-import uuid
-import opuslib_next
-from core.providers.asr.base import ASRProviderBase
-
-from funasr import AutoModel
-from funasr.utils.postprocess_utils import rich_transcription_postprocess
-
-TAG = __name__
-logger = setup_logging()
-
-
-# 捕获标准输出
-class CaptureOutput:
-    def __enter__(self):
-        self._output = io.StringIO()
-        self._original_stdout = sys.stdout
-        sys.stdout = self._output
-
-    def __exit__(self, exc_type, exc_value, traceback):
-        sys.stdout = self._original_stdout
-        self.output = self._output.getvalue()
-        self._output.close()
-
-        # 将捕获到的内容通过 logger 输出
-        if self.output:
-            logger.bind(tag=TAG).info(self.output.strip())
-
-
-class ASRProvider(ASRProviderBase):
-    def __init__(self, config: dict, delete_audio_file: bool):
-        self.model_dir = config.get("model_dir")
-        self.output_dir = config.get("output_dir")  # 修正配置键名
-        self.delete_audio_file = delete_audio_file
-
-        # 确保输出目录存在
-        os.makedirs(self.output_dir, exist_ok=True)
-        with CaptureOutput():
-            self.model = AutoModel(
-                model=self.model_dir,
-                vad_kwargs={"max_single_segment_time": 30000},
-                disable_update=True,
-                hub="hf"
-                # device="cuda:0",  # 启用GPU加速
-            )
-
-    def save_audio_to_file(self, opus_data: List[bytes], session_id: str) -> str:
-        """将Opus音频数据解码并保存为WAV文件"""
-        file_name = f"asr_{session_id}_{uuid.uuid4()}.wav"
-        file_path = os.path.join(self.output_dir, file_name)
-
-        decoder = opuslib_next.Decoder(16000, 1)  # 16kHz, 单声道
-        pcm_data = []
-
-        for opus_packet in opus_data:
-            try:
-                pcm_frame = decoder.decode(opus_packet, 960)  # 960 samples = 60ms
-                pcm_data.append(pcm_frame)
-            except opuslib_next.OpusError as e:
-                logger.bind(tag=TAG).error(f"Opus解码错误: {e}", exc_info=True)
-
-        with wave.open(file_path, "wb") as wf:
-            wf.setnchannels(1)
-            wf.setsampwidth(2)  # 2 bytes = 16-bit
-            wf.setframerate(16000)
-            wf.writeframes(b"".join(pcm_data))
-
-        return file_path
-
-    async def speech_to_text(self, opus_data: List[bytes], session_id: str) -> Tuple[Optional[str], Optional[str]]:
-        """语音转文本主处理逻辑"""
-        file_path = None
-        try:
-            # 保存音频文件
-            start_time = time.time()
-            file_path = self.save_audio_to_file(opus_data, session_id)
-            logger.bind(tag=TAG).debug(f"音频文件保存耗时: {time.time() - start_time:.3f}s | 路径: {file_path}")
-
-            # 语音识别
-            start_time = time.time()
-            result = self.model.generate(
-                input=file_path,
-                cache={},
-                language="auto",
-                use_itn=True,
-                batch_size_s=60,
-            )
-            text = rich_transcription_postprocess(result[0]["text"])
-            logger.bind(tag=TAG).debug(f"语音识别耗时: {time.time() - start_time:.3f}s | 结果: {text}")
-
-            return text, file_path
-
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"语音识别失败: {e}", exc_info=True)
-            return "", None
-
-        finally:
-            # 文件清理逻辑
-            if self.delete_audio_file and file_path and os.path.exists(file_path):
-                try:
-                    os.remove(file_path)
-                    logger.bind(tag=TAG).debug(f"已删除临时音频文件: {file_path}")
-                except Exception as e:
-                    logger.bind(tag=TAG).error(f"文件删除失败: {file_path} | 错误: {e}")

core/providers/llm/base.py

@@ -1,8 +0,0 @@
-from abc import ABC, abstractmethod
-
-
-class LLMProviderBase(ABC):
-    @abstractmethod
-    def response(self, session_id, dialogue):
-        """LLM response generator"""
-        pass

core/providers/llm/coze/coze.py

@@ -1,96 +0,0 @@
-from config.logger import setup_logging
-import requests
-import json
-import re
-from core.providers.llm.base import LLMProviderBase
-
-TAG = __name__
-logger = setup_logging()
-
-# 定义用于匹配中文标点符号的正则表达式（包括句号、感叹号、问号、分号）
-punctuation_pattern = re.compile(r'([。！？；])')
-
-class LLMProvider(LLMProviderBase):
-    def __init__(self, config):
-        self.personal_access_token = config.get("personal_access_token")
-        self.bot_id = config.get("bot_id")
-        self.user_id = config.get("user_id")  # 默认用户 ID
-        self.base_url = config.get("base_url")
-
-    def response(self, session_id, dialogue):
-        try:
-            # 从对话中取出最新的用户消息
-            last_msg = next(m for m in reversed(dialogue) if m["role"] == "user")
-            data = {
-                "conversation_id": session_id,
-                "bot_id": self.bot_id,
-                "user": self.user_id,
-                "query": last_msg["content"],
-                "stream": True
-            }
-            logger.bind(tag=TAG).info(f"发送到 Coze API 的请求数据: {json.dumps(data, ensure_ascii=False)}")
-            
-            headers = {
-                'Authorization': f'Bearer {self.personal_access_token}',
-                'Content-Type': 'application/json',
-                'Accept': '*/*',
-                'Host': 'api.coze.cn',
-                'Connection': 'keep-alive'
-            }
-            
-            response = requests.post(
-                self.base_url,
-                headers=headers,
-                json=data,
-                stream=True
-            )
-            logger.bind(tag=TAG).info(f"请求状态: {response.status_code}")
-            
-            if response.status_code == 200:
-                # 对每一行流数据进行处理，不做跨块累积
-                for line_bytes in response.iter_lines(decode_unicode=False):
-                    if not line_bytes:
-                        continue
-                    try:
-                        # 使用 utf-8 解码，错误部分用替换符
-                        line = line_bytes.decode('utf-8', errors='replace')
-                    except Exception as e:
-                        logger.bind(tag=TAG).error(f"解码失败: {e}")
-                        continue
-                    if line.startswith("data:"):
-                        data_str = line[len("data:"):].strip()
-                        if data_str == "[DONE]":
-                            break
-                        try:
-                            data_chunk = json.loads(data_str)
-                        except json.JSONDecodeError as e:
-                            logger.bind(tag=TAG).error(f"JSON解析失败: {e} 数据: {line}")
-                            continue
-                        msg = data_chunk.get("message", {})
-                        if msg.get("role") == "assistant" and msg.get("type") == "answer":
-                            content = msg.get("content", "")
-                            # 如果返回内容中包含标点符号，则按标点拆分，立即返回每个片段
-                            if punctuation_pattern.search(content):
-                                # 利用 finditer 找到每个标点，并返回以标点结尾的片段
-                                start = 0
-                                for match in punctuation_pattern.finditer(content):
-                                    end = match.end()
-                                    sentence = content[start:end].strip()
-                                    if sentence:
-                                        yield sentence
-                                    start = end
-                                # 如果拆分后剩余内容也返回（不含标点），直接返回
-                                if start < len(content):
-                                    remainder = content[start:].strip()
-                                    if remainder:
-                                        yield remainder
-                            else:
-                                # 如果没有标点，则直接返回这块内容
-                                if content.strip():
-                                    yield content.strip()
-            else:
-                logger.bind(tag=TAG).error(f"请求失败，状态码: {response.status_code}")
-                yield f"【Coze服务响应异常：请求失败，状态码 {response.status_code}】"
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"Error in Coze response generation: {e}")
-            yield "【Coze服务响应异常】"

core/providers/llm/dify/dify.py

@@ -1,39 +0,0 @@
-import json
-from config.logger import setup_logging
-import requests
-from core.providers.llm.base import LLMProviderBase
-
-TAG = __name__
-logger = setup_logging()
-
-class LLMProvider(LLMProviderBase):
-    def __init__(self, config):
-        self.api_key = config["api_key"]
-        self.base_url = config.get("base_url", "https://api.dify.ai/v1").rstrip('/')
-
-    def response(self, session_id, dialogue):
-        try:
-            # 取最后一条用户消息
-            last_msg = next(m for m in reversed(dialogue) if m["role"] == "user")
-
-            # 发起流式请求
-            with requests.post(
-                    f"{self.base_url}/chat-messages",
-                    headers={"Authorization": f"Bearer {self.api_key}"},
-                    json={
-                        "query": last_msg["content"],
-                        "response_mode": "streaming",
-                        "user": session_id,
-                        "inputs": {}
-                    },
-                    stream=True
-            ) as r:
-                for line in r.iter_lines():
-                    if line.startswith(b'data: '):
-                        event = json.loads(line[6:])
-                        if event.get('answer'):
-                            yield event['answer']
-
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"Error in response generation: {e}")
-            yield "【服务响应异常】"

core/providers/llm/gemini/gemini.py

@@ -1,81 +0,0 @@
-from config.logger import setup_logging
-import google.generativeai as genai
-from core.providers.llm.base import LLMProviderBase
-
-TAG = __name__
-logger = setup_logging()
-
-class LLMProvider(LLMProviderBase):
-    def __init__(self, config):
-        """初始化Gemini LLM Provider"""
-        self.model_name = config.get("model_name", "gemini-1.5-pro") 
-        self.api_key = config.get("api_key")
-        
-        if not self.api_key or "你" in self.api_key:
-            logger.bind(tag=TAG).error("你还没配置Gemini LLM的密钥，请在配置文件中配置密钥，否则无法正常工作")
-            return
-            
-        try:
-            # 初始化Gemini客户端
-            genai.configure(api_key=self.api_key)
-            self.model = genai.GenerativeModel(self.model_name)
-            
-            # 设置生成参数
-            self.generation_config = {
-                "temperature": 0.7,
-                "top_p": 0.9,
-                "top_k": 40,
-                "max_output_tokens": 2048,
-            }
-            self.chat = None
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"Gemini初始化失败: {e}")
-            self.model = None
-
-    def response(self, session_id, dialogue):
-        """生成Gemini对话响应"""
-        if not self.model:
-            yield "【Gemini服务未正确初始化】"
-            return
-
-        try:
-            # 处理对话历史
-            chat_history = []
-            for msg in dialogue[:-1]:  # 历史对话
-                role = "model" if msg["role"] == "assistant" else "user"
-                content = msg["content"].strip()
-                if content:
-                    chat_history.append({
-                        "role": role,
-                        "parts": [content]
-                    })
-
-            # 获取当前消息
-            current_msg = dialogue[-1]["content"]
-
-            # 创建新的聊天会话
-            chat = self.model.start_chat(history=chat_history)
-            
-            # 发送消息并获取流式响应
-            response = chat.send_message(
-                current_msg,
-                stream=True,
-                generation_config=self.generation_config
-            )
-
-            # 处理流式响应
-            for chunk in response:
-                if hasattr(chunk, 'text') and chunk.text:
-                    yield chunk.text
-
-        except Exception as e:
-            error_msg = str(e)
-            logger.bind(tag=TAG).error(f"Gemini响应生成错误: {error_msg}")
-            
-            # 针对不同错误返回友好提示
-            if "Rate limit" in error_msg:
-                yield "【Gemini服务请求太频繁,请稍后再试】"
-            elif "Invalid API key" in error_msg:
-                yield "【Gemini API key无效】"
-            else:
-                yield f"【Gemini服务响应异常: {error_msg}】"

core/providers/llm/homeassistant/homeassistant.py

@@ -1,62 +0,0 @@
-import requests
-from requests.exceptions import RequestException
-from config.logger import setup_logging
-from core.providers.llm.base import LLMProviderBase
-
-TAG = __name__
-logger = setup_logging()
-
-
-class LLMProvider(LLMProviderBase):
-    def __init__(self, config):
-        self.agent_id = config.get("agent_id")  # 对应 agent_id
-        self.api_key = config.get("api_key")
-        self.base_url = config.get("base_url", config.get("url"))  # 默认使用 base_url
-        self.api_url = f"{self.base_url}/api/conversation/process"  # 拼接完整的 API URL
-
-    def response(self, session_id, dialogue):
-        print(dialogue)
-        try:
-            # home assistant语音助手自带意图，无需使用xiaozhi ai自带的，只需要把用户说的话传递给home assistant即可
-
-            # 提取最后一个 role 为 'user' 的 content
-            input_text = None
-            if isinstance(dialogue, list):  # 确保 dialogue 是一个列表
-                # 逆序遍历，找到最后一个 role 为 'user' 的消息
-                for message in reversed(dialogue):
-                    if message.get("role") == "user":  # 找到 role 为 'user' 的消息
-                        input_text = message.get("content", "")
-                        break  # 找到后立即退出循环
-
-            # 构造请求数据
-            payload = {
-                "text": input_text,
-                "agent_id": self.agent_id,
-                "conversation_id": session_id  # 使用 session_id 作为 conversation_id
-            }
-            # 设置请求头
-            headers = {
-                "Authorization": f"Bearer {self.api_key}",
-                "Content-Type": "application/json"
-            }
-
-            # 发起 POST 请求
-            response = requests.post(self.api_url, json=payload, headers=headers)
-
-            # 检查请求是否成功
-            response.raise_for_status()
-
-            # 解析返回数据
-            data = response.json()
-            speech = data.get("response", {}).get("speech", {}).get("plain", {}).get("speech", "")
-
-            # 返回生成的内容
-            if speech:
-                yield speech
-            else:
-                logger.bind(tag=TAG).warning("API 返回数据中没有 speech 内容")
-
-        except RequestException as e:
-            logger.bind(tag=TAG).error(f"HTTP 请求错误: {e}")
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"生成响应时出错: {e}")

core/providers/llm/ollama/ollama.py

@@ -1,46 +0,0 @@
-from config.logger import setup_logging
-import requests, json
-from core.providers.llm.base import LLMProviderBase
-
-TAG = __name__
-logger = setup_logging()
-
-
-class LLMProvider(LLMProviderBase):
-    def __init__(self, config):
-
-        self.model_name = config.get("model_name")
-        self.base_url = config.get("base_url", "http://localhost:11434")
-
-    def response(self, session_id, dialogue):        
-        try:
-            # Convert dialogue format to Ollama format
-            prompt = ""
-            for msg in dialogue:
-                if msg["role"] == "system":
-                    prompt += f"System: {msg['content']}\n"
-                elif msg["role"] == "user":
-                    prompt += f"User: {msg['content']}\n"
-                elif msg["role"] == "assistant":
-                    prompt += f"Assistant: {msg['content']}\n"
-
-            # Make request to Ollama API
-            response = requests.post(
-                f"{self.base_url}/api/generate",
-                json={
-                    "model": self.model_name,
-                    "prompt": prompt,
-                    "stream": True
-                },
-                stream=True
-            )
-
-            for line in response.iter_lines():
-                if line:
-                    json_response = json.loads(line)
-                    if "response" in json_response:
-                        yield json_response["response"]
-
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"Error in Ollama response generation: {e}")
-            yield "【Ollama服务响应异常】"

core/providers/llm/openai/openai.py

@@ -1,36 +0,0 @@
-from config.logger import setup_logging
-import openai
-from core.providers.llm.base import LLMProviderBase
-
-TAG = __name__
-logger = setup_logging()
-
-
-class LLMProvider(LLMProviderBase):
-    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")
-        if "你" in self.api_key:
-            logger.bind(tag=TAG).error("你还没配置LLM的密钥，请在配置文件中配置密钥，否则无法正常工作")
-        self.client = openai.OpenAI(api_key=self.api_key, base_url=self.base_url)
-
-    def response(self, session_id, dialogue):
-        try:
-            responses = self.client.chat.completions.create(
-                model=self.model_name,
-                messages=dialogue,
-                stream=True
-            )
-            for chunk in responses:
-                # 检查是否存在有效的choice且content不为空
-                if chunk.choices and len(chunk.choices) > 0:
-                    delta = chunk.choices[0].delta
-                    content = getattr(delta, 'content', '')
-                    if content:  # 仅在content非空时生成
-                        yield content
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"Error in response generation: {e}")

core/providers/tts/aliyun.py

@@ -1,57 +0,0 @@
-import os
-import uuid
-import json
-import requests
-from datetime import datetime
-from core.providers.tts.base import TTSProviderBase
-
-import http.client
-import urllib.parse
-
-
-class TTSProvider(TTSProviderBase):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.appkey = config.get("appkey")
-        self.token = config.get("token")
-        self.format = config.get("format", "wav")
-        self.sample_rate = config.get("sample_rate", 16000)
-        self.voice = config.get("voice", "xiaoyun")
-        self.volume = config.get("volume", 50)
-        self.speech_rate = config.get("speech_rate", 0)
-        self.pitch_rate = config.get("pitch_rate", 0)
-
-        self.host = config.get("host", "nls-gateway-cn-shanghai.aliyuncs.com")
-        self.api_url = f"https://{self.host}/stream/v1/tts"
-        self.header = {
-            "Content-Type": "application/json"
-        }
-
-    def generate_filename(self, extension=".wav"):
-        return os.path.join(self.output_file, f"tts-{__name__}{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        request_json = {
-            "appkey": self.appkey,
-            "token": self.token,
-            "text": text,
-            "format": self.format,
-            "sample_rate": self.sample_rate,
-            "voice": self.voice,
-            "volume": self.volume,
-            "speech_rate": self.speech_rate,
-            "pitch_rate": self.pitch_rate
-        }
-
-        print(self.api_url, json.dumps(request_json, ensure_ascii=False))
-        try:
-            resp = requests.post(self.api_url, json.dumps(request_json), headers=self.header)
-            # 检查返回请求数据的mime类型是否是audio/***，是则保存到指定路径下；返回的是binary格式的
-            if resp.headers['Content-Type'].startswith('audio/'):
-                with open(output_file, 'wb') as f:
-                    f.write(resp.content)
-                return output_file
-            else:
-                raise Exception(f"{__name__} status_code: {resp.status_code} response: {resp.content}")
-        except Exception as e:
-            raise Exception(f"{__name__} error: {e}")

core/providers/tts/base.py

@@ -1,84 +0,0 @@
-import asyncio
-from config.logger import setup_logging
-import os
-import numpy as np
-import opuslib_next
-from pydub import AudioSegment
-from abc import ABC, abstractmethod
-
-TAG = __name__
-logger = setup_logging()
-
-
-class TTSProviderBase(ABC):
-    def __init__(self, config, delete_audio_file):
-        self.delete_audio_file = delete_audio_file
-        self.output_file = config.get("output_file")
-
-    @abstractmethod
-    def generate_filename(self):
-        pass
-
-    def to_tts(self, text):
-        tmp_file = self.generate_filename()
-        try:
-            max_repeat_time = 5
-            while not os.path.exists(tmp_file) and max_repeat_time > 0:
-                asyncio.run(self.text_to_speak(text, tmp_file))
-                if not os.path.exists(tmp_file):
-                    max_repeat_time = max_repeat_time - 1
-                    logger.bind(tag=TAG).error(f"语音生成失败: {text}:{tmp_file}，再试{max_repeat_time}次")
-
-            if max_repeat_time > 0:
-                logger.bind(tag=TAG).info(f"语音生成成功: {text}:{tmp_file}，重试{5 - max_repeat_time}次")
-
-            return tmp_file
-        except Exception as e:
-            logger.bind(tag=TAG).info(f"Failed to generate TTS file: {e}")
-            return None
-
-    @abstractmethod
-    async def text_to_speak(self, text, output_file):
-        pass
-
-    def wav_to_opus_data(self, wav_file_path):
-        # 使用pydub加载PCM文件
-        # 获取文件后缀名
-        file_type = os.path.splitext(wav_file_path)[1]
-        if file_type:
-            file_type = file_type.lstrip('.')
-        audio = AudioSegment.from_file(wav_file_path, format=file_type)
-
-        duration = len(audio) / 1000.0
-
-        # 转换为单声道和16kHz采样率（确保与编码器匹配）
-        audio = audio.set_channels(1).set_frame_rate(16000)
-
-        # 获取原始PCM数据（16位小端）
-        raw_data = audio.raw_data
-
-        # 初始化Opus编码器
-        encoder = opuslib_next.Encoder(16000, 1, opuslib_next.APPLICATION_AUDIO)
-
-        # 编码参数
-        frame_duration = 60  # 60ms per frame
-        frame_size = int(16000 * frame_duration / 1000)  # 960 samples/frame
-
-        opus_datas = []
-        # 按帧处理所有音频数据（包括最后一帧可能补零）
-        for i in range(0, len(raw_data), frame_size * 2):  # 16bit=2bytes/sample
-            # 获取当前帧的二进制数据
-            chunk = raw_data[i:i + frame_size * 2]
-
-            # 如果最后一帧不足，补零
-            if len(chunk) < frame_size * 2:
-                chunk += b'\x00' * (frame_size * 2 - len(chunk))
-
-            # 转换为numpy数组处理
-            np_frame = np.frombuffer(chunk, dtype=np.int16)
-
-            # 编码Opus数据
-            opus_data = encoder.encode(np_frame.tobytes(), frame_size)
-            opus_datas.append(opus_data)
-
-        return opus_datas, duration

core/providers/tts/cozecn.py

@@ -1,38 +0,0 @@
-import os
-import uuid
-import json
-import base64
-import requests
-from datetime import datetime
-from core.providers.tts.base import TTSProviderBase
-
-
-class TTSProvider(TTSProviderBase):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.model = config.get("model")
-        self.access_token = config.get("access_token")
-        self.voice = config.get("voice")
-        self.response_format = config.get("response_format")
-
-        self.host = "api.coze.cn"
-        self.api_url = f"https://{self.host}/v1/audio/speech"
-
-    def generate_filename(self, extension=".wav"):
-        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        request_json = {
-            "model": self.model,
-            "input": text,
-            "voice_id": self.voice,
-            "response_format": self.response_format,
-        }
-        headers = {
-            "Authorization": f"Bearer {self.access_token}",
-            "Content-Type": "application/json"
-        }
-        response = requests.request("POST", self.api_url, json=request_json, headers=headers)
-        data = response.content
-        file_to_save = open(output_file, "wb")
-        file_to_save.write(data)

core/providers/tts/doubao.py

@@ -1,61 +0,0 @@
-import os
-import uuid
-import json
-import base64
-import requests
-from datetime import datetime
-from core.providers.tts.base import TTSProviderBase
-
-
-class TTSProvider(TTSProviderBase):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.appid = config.get("appid")
-        self.access_token = config.get("access_token")
-        self.cluster = config.get("cluster")
-        self.voice = config.get("voice")
-
-        self.host = "openspeech.bytedance.com"
-        self.api_url = f"https://{self.host}/api/v1/tts"
-        self.header = {"Authorization": f"Bearer;{self.access_token}"}
-
-    def generate_filename(self, extension=".wav"):
-        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        request_json = {
-            "app": {
-                "appid": f"{self.appid}",
-                "token": "access_token",
-                "cluster": self.cluster
-            },
-            "user": {
-                "uid": "1"
-            },
-            "audio": {
-                "voice_type": self.voice,
-                "encoding": "wav",
-                "speed_ratio": 1.0,
-                "volume_ratio": 1.0,
-                "pitch_ratio": 1.0,
-            },
-            "request": {
-                "reqid": str(uuid.uuid4()),
-                "text": text,
-                "text_type": "plain",
-                "operation": "query",
-                "with_frontend": 1,
-                "frontend_type": "unitTson"
-            }
-        }
-
-        try:
-            resp = requests.post(self.api_url, json.dumps(request_json), headers=self.header)
-            if "data" in resp.json():
-                data = resp.json()["data"]
-                file_to_save = open(output_file, "wb")
-                file_to_save.write(base64.b64decode(data))
-            else:
-                raise Exception(f"{__name__} status_code: {resp.status_code} response: {resp.content}")
-        except Exception as e:
-            raise Exception(f"{__name__} error: {e}")

core/providers/tts/edge.py

@@ -1,18 +0,0 @@
-import os
-import uuid
-import edge_tts
-from datetime import datetime
-from core.providers.tts.base import TTSProviderBase
-
-
-class TTSProvider(TTSProviderBase):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.voice = config.get("voice")
-
-    def generate_filename(self, extension=".mp3"):
-        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        communicate = edge_tts.Communicate(text, voice=self.voice)  # Use your preferred voice
-        await communicate.save(output_file)

core/providers/tts/gpt_sovits_v2.py

@@ -1,67 +0,0 @@
-import os
-import uuid
-import json
-import base64
-import requests
-from config.logger import setup_logging
-from datetime import datetime
-from core.providers.tts.base import TTSProviderBase
-
-TAG = __name__
-logger = setup_logging()
-
-class TTSProvider(TTSProviderBase):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.url = config.get("url")
-        self.text_lang = config.get("text_lang", "zh")
-        self.ref_audio_path = config.get("ref_audio_path")
-        self.prompt_text = config.get("prompt_text")
-        self.prompt_lang = config.get("prompt_lang", "zh")
-        self.top_k = config.get("top_k", 5)
-        self.top_p = config.get("top_p", 1)
-        self.temperature = config.get("temperature", 1)
-        self.text_split_method = config.get("text_split_method", "cut0")
-        self.batch_size = config.get("batch_size", 1)
-        self.batch_threshold = config.get("batch_threshold", 0.75)
-        self.split_bucket = config.get("split_bucket", True)
-        self.return_fragment = config.get("return_fragment", False)
-        self.speed_factor = config.get("speed_factor", 1.0)
-        self.streaming_mode = config.get("streaming_mode", False)
-        self.seed = config.get("seed", -1)
-        self.parallel_infer = config.get("parallel_infer", True)
-        self.repetition_penalty = config.get("repetition_penalty", 1.35)
-        self.aux_ref_audio_paths = config.get("aux_ref_audio_paths", [])
-
-    def generate_filename(self, extension=".wav"):
-        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        request_json = {
-            "text": text,
-            "text_lang": self.text_lang,
-            "ref_audio_path": self.ref_audio_path,
-            "aux_ref_audio_paths": self.aux_ref_audio_paths,
-            "prompt_text": self.prompt_text,
-            "prompt_lang": self.prompt_lang,
-            "top_k": self.top_k,
-            "top_p": self.top_p,
-            "temperature": self.temperature,
-            "text_split_method": self.text_split_method,
-            "batch_size": self.batch_size,
-            "batch_threshold": self.batch_threshold,
-            "split_bucket": self.split_bucket,
-            "return_fragment": self.return_fragment,
-            "speed_factor": self.speed_factor,
-            "streaming_mode": self.streaming_mode,
-            "seed": self.seed,
-            "parallel_infer": self.parallel_infer,
-            "repetition_penalty": self.repetition_penalty
-        }
-
-        resp = requests.post(self.url, json=request_json)
-        if resp.status_code == 200:
-            with open(output_file, "wb") as file:
-                file.write(resp.content)
-        else:
-            logger.bind(tag=TAG).error(f"GPT_SoVITS_V2 TTS请求失败: {resp.status_code} - {resp.text}")

core/providers/tts/minimax.py

@@ -1,77 +0,0 @@
-import os
-import uuid
-import json
-import requests
-from datetime import datetime
-from core.providers.tts.base import TTSProviderBase
-
-
-class TTSProvider(TTSProviderBase):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.group_id = config.get("group_id")
-        self.api_key = config.get("api_key")
-        self.model = config.get("model")
-        self.voice_id = config.get("voice_id")
-
-        default_voice_setting = {
-            "voice_id": "female-shaonv",
-            "speed": 1,
-            "vol": 1,
-            "pitch": 0,
-            "emotion": "happy"
-        }
-        default_pronunciation_dict = {
-            "tone": [
-                "处理/(chu3)(li3)", "危险/dangerous"
-            ]
-        }
-        defult_audio_setting = {
-            "sample_rate": 32000,
-            "bitrate": 128000,
-            "format": "mp3",
-            "channel": 1
-        }
-        self.voice_setting = {**default_voice_setting, **config.get("voice_setting", {})}
-        self.pronunciation_dict = {**default_pronunciation_dict, **config.get("pronunciation_dict", {})}
-        self.audio_setting = {**defult_audio_setting, **config.get("audio_setting", {})}
-        self.timber_weights = config.get("timber_weights", [])
-
-        if self.voice_id:
-            self.voice_setting["voice_id"] = self.voice_id
-
-        self.host = "api.minimax.chat"
-        self.api_url = f"https://{self.host}/v1/t2a_v2?GroupId={self.group_id}"
-        self.header = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {self.api_key}"
-        }
-
-    def generate_filename(self, extension=".mp3"):
-        return os.path.join(self.output_file, f"tts-{__name__}{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        request_json = {
-            "model": self.model,
-            "text": text,
-            "stream": False,
-            "voice_setting": self.voice_setting,
-            "pronunciation_dict": self.pronunciation_dict,
-            "audio_setting": self.audio_setting,
-        }
-
-        if type(self.timber_weights) is list and len(self.timber_weights) > 0:
-            request_json["timber_weights"] = self.timber_weights
-            request_json["voice_setting"]["voice_id"] = ""
-
-        try:
-            resp = requests.post(self.api_url, json.dumps(request_json), headers=self.header)
-            # 检查返回请求数据的status_code是否为0
-            if resp.json()["base_resp"]["status_code"] == 0:
-                data = resp.json()['data']['audio']
-                file_to_save = open(output_file, "wb")
-                file_to_save.write(bytes.fromhex(data))
-            else:
-                raise Exception(f"{__name__} status_code: {resp.status_code} response: {resp.content}")
-        except Exception as e:
-            raise Exception(f"{__name__} error: {e}")

core/providers/tts/siliconflow.py

@@ -1,39 +0,0 @@
-import os
-import uuid
-import requests
-from datetime import datetime
-from core.providers.tts.base import TTSProviderBase
-
-
-class TTSProvider(TTSProviderBase):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.model = config.get("model")
-        self.access_token = config.get("access_token")
-        self.voice = config.get("voice")
-        self.response_format = config.get("response_format")
-        self.sample_rate = config.get("sample_rate")
-        self.speed = config.get("speed")
-        self.gain = config.get("gain")
-
-        self.host = "api.siliconflow.cn"
-        self.api_url = f"https://{self.host}/v1/audio/speech"
-
-    def generate_filename(self, extension=".wav"):
-        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        request_json = {
-            "model": self.model,
-            "input": text,
-            "voice": self.voice,
-            "response_format": self.response_format,
-        }
-        headers = {
-            "Authorization": f"Bearer {self.access_token}",
-            "Content-Type": "application/json"
-        }
-        response = requests.request("POST", self.api_url, json=request_json, headers=headers)
-        data = response.content
-        file_to_save = open(output_file, "wb")
-        file_to_save.write(data)

core/utils/auth_code_gen.py

@@ -1,97 +0,0 @@
-import random
-import threading
-import time
-from typing import Set
-
-class AuthCodeGenerator:
-    _instance = None
-    _instance_lock = threading.Lock()
-    
-    def __new__(cls):
-        if not cls._instance:
-            with cls._instance_lock:
-                if not cls._instance:
-                    cls._instance = super(AuthCodeGenerator, cls).__new__(cls)
-                    # 初始化随机种子
-                    random.seed(time.time())
-        return cls._instance
-
-    def __init__(self):
-        # 确保 __init__ 只被调用一次
-        if not hasattr(self, '_initialized'):
-            self._used_codes: Set[str] = set()
-            self._code_timestamps = {}
-            self._lock = threading.Lock()
-            self._code_timeout = 3 * 24 * 60 * 60
-            self._initialized = True
-    
-    @classmethod
-    def get_instance(cls):
-        """获取AuthCodeGenerator的单例实例"""
-        return cls()
-
-    def generate_code(self) -> str:
-        """
-        生成6位数字认证码，确保不重复
-        返回: 6位数字字符串
-        """
-        with self._lock:
-            self._clean_expired_codes()  # 清理过期code
-            while True:
-                # 使用时间戳和已用码数量作为种子，确保每次生成不同的随机数
-                seed = int(time.time() * 1000) + len(self._used_codes)
-                random.seed(seed)
-                
-                # 生成6位随机数字
-                code = ''.join(str(random.randint(0, 9)) for _ in range(6))
-                
-                # 检查是否已存在
-                if code not in self._used_codes:
-                    self._used_codes.add(code)
-                    self._code_timestamps[code] = time.time()
-                    return code
-    
-    def remove_code(self, code: str) -> bool:
-        """
-        删除已使用的认证码
-        参数:
-            code: 要删除的认证码
-        返回:
-            bool: 删除成功返回True，码不存在返回False
-        """
-        print('remove_code', code)
-        with self._lock:
-            if code in self._used_codes:
-                self._used_codes.remove(code)
-                if code in self._code_timestamps:
-                    del self._code_timestamps[code]
-                return True
-            return False
-    
-    def is_code_used(self, code: str) -> bool:
-        """
-        检查认证码是否已被使用
-        参数:
-            code: 要检查的认证码
-        返回:
-            bool: 如果码存在返回True，否则返回False
-        """
-        with self._lock:
-            return code in self._used_codes
-    
-    def clear_codes(self):
-        """清空所有已使用的认证码"""
-        with self._lock:
-            self._used_codes.clear()
-            self._code_timestamps.clear()
-    
-    def _clean_expired_codes(self):
-        """清理过期的认证码"""
-        current_time = time.time()
-        expired_codes = [
-            code for code, timestamp in self._code_timestamps.items()
-            if (current_time - timestamp) > self._code_timeout
-        ]
-        for code in expired_codes:
-            self._used_codes.remove(code)
-            del self._code_timestamps[code]

core/utils/dialogue.py

@@ -1,26 +0,0 @@
-import uuid
-from typing import List, Dict
-from datetime import datetime
-
-
-class Message:
-    def __init__(self, role: str, content: str = None, uniq_id: str = None):
-        self.uniq_id = uniq_id if uniq_id is not None else str(uuid.uuid4())
-        self.role = role
-        self.content = content
-
-
-class Dialogue:
-    def __init__(self):
-        self.dialogue: List[Message] = []
-        # 获取当前时间
-        self.current_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-
-    def put(self, message: Message):
-        self.dialogue.append(message)
-
-    def get_llm_dialogue(self) -> List[Dict[str, str]]:
-        dialogue = []
-        for m in self.dialogue:
-            dialogue.append({"role": m.role, "content": m.content})
-        return dialogue

core/utils/llm.py

@@ -1,143 +0,0 @@
-import os
-import sys
-import asyncio
-from typing import List, Dict, Any
-
-# 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
-from datetime import datetime
-from core.utils.util import is_segment
-from core.utils.util import get_string_no_punctuation_or_emoji
-from core.utils.util import read_config, get_project_dir
-
-logger = setup_logging()
-
-
-def create_instance(class_name, *args, **kwargs):
-    # 创建LLM实例
-    if os.path.exists(os.path.join('core', 'providers', 'llm', class_name, f'{class_name}.py')):
-        lib_name = f'core.providers.llm.{class_name}.{class_name}'
-        if lib_name not in sys.modules:
-            sys.modules[lib_name] = importlib.import_module(f'{lib_name}')
-        return sys.modules[lib_name].LLMProvider(*args, **kwargs)
-
-    raise ValueError(f"不支持的LLM类型: {class_name}，请检查该配置的type是否设置正确")
-
-
-async def test_single_model(llm_name: str, llm_config: Dict[str, Any], test_prompt: str, config: Dict[str, Any]) -> Dict[str, Any]:
-    """异步测试单个模型"""
-    try:
-        # 获取实际的LLM类型
-        llm_type = llm_config["type"] if "type" in llm_config else llm_name
-        llm = create_instance(llm_type, llm_config)
-        
-        # 开始测试
-        dialogue = []
-        dialogue.append({"role": "system", "content": config.get("prompt")})
-        dialogue.append({"role": "user", "content": test_prompt})
-        
-        start_time = datetime.now()
-        llm_responses = llm.response("test", dialogue)
-        response_message = []
-        first_response_time = None
-        total_response_time = None
-        start = 0
-        full_response = ""
-
-        for content in llm_responses:
-            response_message.append(content)
-            full_response += content
-
-            if is_segment(response_message):
-                segment_text = "".join(response_message[start:])
-                segment_text = get_string_no_punctuation_or_emoji(segment_text)
-                if len(segment_text) > 0:
-                    if first_response_time is None:
-                        first_response_time = (datetime.now() - start_time).total_seconds()
-                    start = len(response_message)
-
-        total_response_time = (datetime.now() - start_time).total_seconds()
-        
-        return {
-            "name": llm_name,
-            "type": llm_type,
-            "first_response_time": first_response_time,
-            "total_response_time": total_response_time,
-            "response_length": len(full_response),
-            "status": "成功",
-            "response": full_response
-        }
-
-    except Exception as e:
-        print(f"测试 {llm_name} 时发生错误: {str(e)}")
-        return {
-            "name": llm_name,
-            "type": llm_config.get("type", llm_name),
-            "first_response_time": None,
-            "total_response_time": None,
-            "response_length": 0,
-            "status": f"失败 - {str(e)}",
-            "response": ""
-        }
-
-
-async def main():
-    """
-    LLM模型响应速度测试和排行（异步版本）
-    """
-    config = read_config(get_project_dir() + "config.yaml")
-    test_prompt = "你好小智"
-    
-    print("开始并发测试所有模型...")
-    
-    # 创建所有模型的测试任务
-    tasks = []
-    for llm_name, llm_config in config["LLM"].items():
-        task = asyncio.create_task(test_single_model(llm_name, llm_config, test_prompt, config))
-        tasks.append(task)
-    
-    # 等待所有测试完成
-    test_results = await asyncio.gather(*tasks)
-    
-    # 打印测试结果排行榜
-    print("\n========= LLM模型性能测试排行榜 =========")
-    print("测试提示词:", test_prompt)
-    
-    # 过滤出成功的结果，并确保数值有效
-    successful_results = [r for r in test_results if r["status"] == "成功" and r["first_response_time"] is not None]
-    
-    if successful_results:
-        print("\n1. 首次响应时间排行:")
-        sorted_by_first = sorted(successful_results, key=lambda x: x["first_response_time"])
-        for i, result in enumerate(sorted_by_first, 1):
-            print(f"{i}. {result['name']}({result['type']}) - {result['first_response_time']:.2f}秒")
-            print(f"   响应内容: {result['response'][:50]}...")  # 只显示前50个字符
-
-        print("\n2. 总响应时间排行:")
-        sorted_by_total = sorted(successful_results, key=lambda x: x["total_response_time"] or float('inf'))
-        for i, result in enumerate(sorted_by_total, 1):
-            if result["total_response_time"] is not None:
-                print(f"{i}. {result['name']}({result['type']}) - {result['total_response_time']:.2f}秒")
-
-        print("\n3. 响应长度比较:")
-        sorted_by_length = sorted(successful_results, key=lambda x: x["response_length"], reverse=True)
-        for i, result in enumerate(sorted_by_length, 1):
-            print(f"{i}. {result['name']}({result['type']}) - {result['response_length']}字符")
-    else:
-        print("\n没有成功完成测试的模型。")
-
-    if len(test_results) != len(successful_results):
-        print("\n测试失败的模型:")
-        failed_results = [r for r in test_results if r["status"] != "成功" or r["first_response_time"] is None]
-        for result in failed_results:
-            print(f"- {result['name']}({result['type']}): {result['status']}")
-
-
-if __name__ == "__main__":
-    # 运行异步主函数
-    asyncio.run(main())

core/utils/lock_manager.py

@@ -1,39 +0,0 @@
-import asyncio
-from typing import Dict
-from config.logger import setup_logging
-
-TAG = __name__
-logger = setup_logging()
-
-class FileLockManager:
-    _instance = None
-    _locks: Dict[str, asyncio.Lock] = {}
-
-    def __new__(cls):
-        if cls._instance is None:
-            cls._instance = super(FileLockManager, cls).__new__(cls)
-        return cls._instance
-
-    @classmethod
-    def get_lock(cls, file_path: str) -> asyncio.Lock:
-        """获取指定文件的锁"""
-        if file_path not in cls._locks:
-            cls._locks[file_path] = asyncio.Lock()
-        return cls._locks[file_path]
-
-    @classmethod
-    async def acquire_lock(cls, file_path: str):
-        """获取锁"""
-        lock = cls.get_lock(file_path)
-        await lock.acquire()
-        logger.bind(tag=TAG).debug(f"Acquired lock for {file_path}")
-
-    @classmethod
-    def release_lock(cls, file_path: str):
-        """释放锁"""
-        if file_path in cls._locks:
-            try:
-                cls._locks[file_path].release()
-                logger.bind(tag=TAG).debug(f"Released lock for {file_path}")
-            except RuntimeError as e:
-                logger.bind(tag=TAG).warning(f"Failed to release lock for {file_path}: {e}")

core/utils/tts.py

@@ -1,41 +0,0 @@
-import os
-import sys
-from config.logger import setup_logging
-import importlib
-from datetime import datetime
-from core.utils.util import read_config, get_project_dir
-
-logger = setup_logging()
-
-
-def create_instance(class_name, *args, **kwargs):
-    # 创建TTS实例
-    if os.path.exists(os.path.join('core', 'providers', 'tts', f'{class_name}.py')):
-        lib_name = f'core.providers.tts.{class_name}'
-        if lib_name not in sys.modules:
-            sys.modules[lib_name] = importlib.import_module(f'{lib_name}')
-        return sys.modules[lib_name].TTSProvider(*args, **kwargs)
-
-    raise ValueError(f"不支持的TTS类型: {class_name}，请检查该配置的type是否设置正确")
-
-
-if __name__ == "__main__":
-    """
-      响应速度测试
-    """
-    config = read_config(get_project_dir() + "config.yaml")
-    tts = create_instance(
-        config["selected_module"]["TTS"]
-        if not 'type' in config["TTS"][config["selected_module"]["TTS"]]
-        else
-        config["TTS"][config["selected_module"]["TTS"]]["type"],
-        config["TTS"][config["selected_module"]["TTS"]],
-        config["delete_audio"]
-    )
-    tts.output_file = get_project_dir() + tts.output_file
-    start = datetime.now()
-    file_path = tts.to_tts("你好，测试,我是人工智能小智")
-    print("语音合成耗时：" + str(datetime.now() - start))
-    start = datetime.now()
-    tts.wav_to_opus_data(file_path)
-    print("语音opus耗时：" + str(datetime.now() - start))

core/utils/util.py

@@ -1,123 +0,0 @@
-import os
-import re
-import json
-import yaml
-import socket
-
-
-def get_project_dir():
-    """获取项目根目录"""
-    return os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + '/'
-
-
-def get_local_ip():
-    try:
-        s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
-        # Connect to Google's DNS servers
-        s.connect(("8.8.8.8", 80))
-        local_ip = s.getsockname()[0]
-        s.close()
-        return local_ip
-    except Exception as e:
-        return "127.0.0.1"
-
-
-def read_config(config_path):
-    with open(config_path, "r", encoding="utf-8") as file:
-        config = yaml.safe_load(file)
-    return config
-
-
-def write_json_file(file_path, data):
-    """将数据写入 JSON 文件"""
-    with open(file_path, 'w', encoding='utf-8') as file:
-        json.dump(data, file, ensure_ascii=False, indent=4)
-
-
-def is_segment(tokens):
-    if tokens[-1] in (",", ".", "?", "，", "。", "？", "！", "!", ";", "；", ":", "："):
-        return True
-    else:
-        return False
-
-
-def is_punctuation_or_emoji(char):
-    """检查字符是否为空格、指定标点或表情符号"""
-    # 定义需要去除的中英文标点（包括全角/半角）
-    punctuation_set = {
-        '，', ',',  # 中文逗号 + 英文逗号
-        '。', '.',  # 中文句号 + 英文句号
-        '！', '!',  # 中文感叹号 + 英文感叹号
-        '-', '－',  # 英文连字符 + 中文全角横线
-        '、'  # 中文顿号
-    }
-    if char.isspace() or char in punctuation_set:
-        return True
-    # 检查表情符号（保留原有逻辑）
-    code_point = ord(char)
-    emoji_ranges = [
-        (0x1F600, 0x1F64F), (0x1F300, 0x1F5FF),
-        (0x1F680, 0x1F6FF), (0x1F900, 0x1F9FF),
-        (0x1FA70, 0x1FAFF), (0x2600, 0x26FF),
-        (0x2700, 0x27BF)
-    ]
-    return any(start <= code_point <= end for start, end in emoji_ranges)
-
-
-def get_string_no_punctuation_or_emoji(s):
-    """去除字符串首尾的空格、标点符号和表情符号"""
-    chars = list(s)
-    # 处理开头的字符
-    start = 0
-    while start < len(chars) and is_punctuation_or_emoji(chars[start]):
-        start += 1
-    # 处理结尾的字符
-    end = len(chars) - 1
-    while end >= start and is_punctuation_or_emoji(chars[end]):
-        end -= 1
-    return ''.join(chars[start:end + 1])
-
-
-def remove_punctuation_and_length(text):
-    # 全角符号和半角符号的Unicode范围
-    full_width_punctuations = '！＂＃＄％＆＇（）＊＋，－。／：；＜＝＞？＠［＼］＾＿｀｛｜｝～'
-    half_width_punctuations = '!"#$%&\'()*+,-./:;<=>?@[\]^_`{|}~'
-    space = ' '  # 半角空格
-    full_width_space = '　'  # 全角空格
-
-    # 去除全角和半角符号以及空格
-    result = ''.join([char for char in text if
-                      char not in full_width_punctuations and char not in half_width_punctuations and char not in space and char not in full_width_space])
-
-    if result == "Yeah":
-        return 0
-    return len(result), result
-
-
-def check_password(password):
-    """
-    检查密码是否满足以下条件：
-    1. 密码长度大于八位。
-    2. 密码包含英文和数字。
-    3. 密码不能包含“xiaozhi”字符。
-
-    :param password: 要检查的密码
-    :return: 如果密码满足条件，则返回True；否则返回False。
-    """
-    # 检查密码长度
-    if len(password) < 8:
-        return False
-
-    # 检查是否包含英文字符和数字
-    if not re.search(r'[A-Za-z]', password) or not re.search(r'[0-9]', password):
-        return False
-
-    # 检查是否包含“xiaozhi”字符
-    if "xiaozhi" in password:
-        return False
-
-    if "1234" in password:
-        return False
-
-    # 如果满足所有条件，则返回True
-    return True

core/utils/vad.py

@@ -1,77 +0,0 @@
-from abc import ABC, abstractmethod
-from config.logger import setup_logging
-import opuslib_next
-import time
-import numpy as np
-import torch
-
-TAG = __name__
-logger = setup_logging()
-
-class VAD(ABC):
-    @abstractmethod
-    def is_vad(self, conn, data):
-        """检测音频数据中的语音活动"""
-        pass
-
-
-class SileroVAD(VAD):
-    def __init__(self, config):
-        logger.bind(tag=TAG).info("SileroVAD", config)
-        self.model, self.utils = torch.hub.load(repo_or_dir=config["model_dir"],
-                                                source='local',
-                                                model='silero_vad',
-                                                force_reload=False)
-        (get_speech_timestamps, _, _, _, _) = self.utils
-
-        self.decoder = opuslib_next.Decoder(16000, 1)
-        self.vad_threshold = config.get("threshold")
-        self.silence_threshold_ms = config.get("min_silence_duration_ms")
-
-    def is_vad(self, conn, opus_packet):
-        try:
-            pcm_frame = self.decoder.decode(opus_packet, 960)
-            conn.client_audio_buffer += pcm_frame  # 将新数据加入缓冲区
-
-            # 处理缓冲区中的完整帧（每次处理512采样点）
-            client_have_voice = False
-            while len(conn.client_audio_buffer) >= 512 * 2:
-                # 提取前512个采样点（1024字节）
-                chunk = conn.client_audio_buffer[:512 * 2]
-                conn.client_audio_buffer = conn.client_audio_buffer[512 * 2:]
-
-                # 转换为模型需要的张量格式
-                audio_int16 = np.frombuffer(chunk, dtype=np.int16)
-                audio_float32 = audio_int16.astype(np.float32) / 32768.0
-                audio_tensor = torch.from_numpy(audio_float32)
-
-                # 检测语音活动
-                speech_prob = self.model(audio_tensor, 16000).item()
-                client_have_voice = speech_prob >= self.vad_threshold
-
-                # 如果之前有声音，但本次没有声音，且与上次有声音的时间查已经超过了静默阈值，则认为已经说完一句话
-                if conn.client_have_voice and not client_have_voice:
-                    stop_duration = time.time() * 1000 - conn.client_have_voice_last_time
-                    if stop_duration >= self.silence_threshold_ms:
-                        conn.client_voice_stop = True
-                if client_have_voice:
-                    conn.client_have_voice = True
-                    conn.client_have_voice_last_time = time.time() * 1000
-
-            return client_have_voice
-        except opuslib_next.OpusError as e:
-            logger.bind(tag=TAG).info(f"解码错误: {e}")
-        except Exception as e:
-            logger.bind(tag=TAG).error(f"Error processing audio packet: {e}")
-
-
-def create_instance(class_name, *args, **kwargs) -> VAD:
-    # 获取类对象
-    cls_map = {
-        "SileroVAD": SileroVAD,
-        # 可扩展其他SileroVAD实现
-    }
-
-    if cls := cls_map.get(class_name):
-        return cls(*args, **kwargs)
-    raise ValueError(f"不支持的SileroVAD类型: {class_name}")

core/websocket_server.py

@@ -1,66 +0,0 @@
-import asyncio
-import websockets
-from config.logger import setup_logging
-from core.connection import ConnectionHandler
-from core.utils.util import get_local_ip
-from core.utils import asr, vad, llm, tts
-
-TAG = __name__
-
-
-class WebSocketServer:
-    def __init__(self, config: dict):
-        self.config = config
-        self.logger = setup_logging()
-        self._vad, self._asr, self._llm, self._tts = self._create_processing_instances()
-
-    def _create_processing_instances(self):
-        """创建处理模块实例"""
-        return (
-            vad.create_instance(
-                self.config["selected_module"]["VAD"],
-                self.config["VAD"][self.config["selected_module"]["VAD"]]
-            ),
-            asr.create_instance(
-                self.config["selected_module"]["ASR"]
-                if not 'type' in self.config["ASR"][self.config["selected_module"]["ASR"]]
-                else
-                self.config["ASR"][self.config["selected_module"]["ASR"]]["type"],
-                self.config["ASR"][self.config["selected_module"]["ASR"]],
-                self.config["delete_audio"]
-            ),
-            llm.create_instance(
-                self.config["selected_module"]["LLM"]
-                if not 'type' in self.config["LLM"][self.config["selected_module"]["LLM"]]
-                else
-                self.config["LLM"][self.config["selected_module"]["LLM"]]['type'],
-                self.config["LLM"][self.config["selected_module"]["LLM"]],
-            ),
-            tts.create_instance(
-                self.config["selected_module"]["TTS"]
-                if not 'type' in self.config["TTS"][self.config["selected_module"]["TTS"]]
-                else
-                self.config["TTS"][self.config["selected_module"]["TTS"]]["type"],
-                self.config["TTS"][self.config["selected_module"]["TTS"]],
-                self.config["delete_audio"]
-            )
-        )
-
-    async def start(self):
-        server_config = self.config["server"]
-        host = server_config["ip"]
-        port = server_config["port"]
-
-        self.logger.bind(tag=TAG).info("Server is running at ws://{}:{}", get_local_ip(), port)
-        self.logger.bind(tag=TAG).info("=======上面的地址是websocket协议地址，请勿用浏览器访问=======")
-        async with websockets.serve(
-                self._handle_connection,
-                host,
-                port
-        ):
-            await asyncio.Future()
-
-    async def _handle_connection(self, websocket):
-        """处理新连接，每次创建独立的ConnectionHandler"""
-        handler = ConnectionHandler(self.config, self._vad, self._asr, self._llm, self._tts)
-        await handler.handle_connection(websocket)

docker-compose.yml

@@ -1,17 +0,0 @@
-services:
-  xiaozhi-esp32-server:
-    image: ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:latest
-    container_name: xiaozhi-esp32-server
-    restart: always
-    security_opt:
-      - seccomp:unconfined
-    ports:
-      # ws服务端
-      - "8000:8000"
-      # 管理后台
-      - "8002:8002"
-    volumes:
-      # 配置文件目录
-      - ./data:/app/data
-      # 模型文件挂接，很重要
-      - ./models/SenseVoiceSmall/model.pt:/app/models/SenseVoiceSmall/model.pt

docker-setup.sh

@@ -0,0 +1,413 @@
+#!/bin/sh
+# 脚本作者@VanillaNahida
+# 本文件是用于一键自动下载本项目所需文件，自动创建好目录
+# 暂且只支持X86版本的Ubuntu系统，其他系统未测试
+
+# 定义中断处理函数
+handle_interrupt() {
+    echo ""
+    echo "安装已被用户中断(Ctrl+C或Esc)"
+    echo "如需重新安装，请再次运行脚本"
+    exit 1
+}
+
+# 设置信号捕获，处理Ctrl+C
+trap handle_interrupt SIGINT
+
+# 处理Esc键
+# 保存终端设置
+old_stty_settings=$(stty -g)
+# 设置终端立即响应，不回显
+stty -icanon -echo min 1 time 0
+
+# 后台进程检测Esc键
+(while true; do
+    read -r key
+    if [[ $key == $'\e' ]]; then
+        # 检测到Esc键，触发中断处理
+        kill -SIGINT $$
+        break
+    fi
+done) &
+
+# 脚本结束时恢复终端设置
+trap 'stty "$old_stty_settings"' EXIT
+
+
+# 打印彩色字符画
+echo -e "\e[1;32m"  # 设置颜色为亮绿色
+cat << "EOF"
+脚本作者：@Bilibili 香草味的纳西妲喵
+ __      __            _  _  _            _   _         _      _      _        
+ \ \    / /           (_)| || |          | \ | |       | |    (_)    | |       
+  \ \  / /__ _  _ __   _ | || |  __ _    |  \| |  __ _ | |__   _   __| |  __ _ 
+   \ \/ // _` || '_ \ | || || | / _` |   | . ` | / _` || '_ \ | | / _` | / _` |
+    \  /| (_| || | | || || || || (_| |   | |\  || (_| || | | || || (_| || (_| |
+     \/  \__,_||_| |_||_||_||_| \__,_|   |_| \_| \__,_||_| |_||_| \__,_| \__,_|                                                                                                                                                                                                                               
+EOF
+echo -e "\e[0m"  # 重置颜色
+echo -e "\e[1;36m  小智服务端全量部署一键安装脚本 Ver 0.2 2025年8月20日更新 \e[0m\n"
+sleep 1
+
+
+
+# 检查并安装whiptail
+check_whiptail() {
+    if ! command -v whiptail &> /dev/null; then
+        echo "正在安装whiptail..."
+        apt update
+        apt install -y whiptail
+    fi
+}
+
+check_whiptail
+
+# 创建确认对话框
+whiptail --title "安装确认" --yesno "即将安装小智服务端，是否继续？" \
+  --yes-button "继续" --no-button "退出" 10 50
+
+# 根据用户选择执行操作
+case $? in
+  0)
+    ;;
+  1)
+    exit 1
+    ;;
+esac
+
+# 检查root权限
+if [ $EUID -ne 0 ]; then
+    whiptail --title "权限错误" --msgbox "请使用root权限运行本脚本" 10 50
+    exit 1
+fi
+
+# 检查系统版本
+if [ -f /etc/os-release ]; then
+    . /etc/os-release
+    if [ "$ID" != "debian" ] && [ "$ID" != "ubuntu" ]; then
+        whiptail --title "系统错误" --msgbox "该脚本只支持Debian/Ubuntu系统执行" 10 60
+        exit 1
+    fi
+else
+    whiptail --title "系统错误" --msgbox "无法确定系统版本，该脚本只支持Debian/Ubuntu系统执行" 10 60
+    exit 1
+fi
+
+# 下载配置文件函数
+check_and_download() {
+    local filepath=$1
+    local url=$2
+    if [ ! -f "$filepath" ]; then
+        if ! curl -fL --progress-bar "$url" -o "$filepath"; then
+            whiptail --title "错误" --msgbox "${filepath}文件下载失败" 10 50
+            exit 1
+        fi
+    else
+        echo "${filepath}文件已存在，跳过下载"
+    fi
+}
+
+# 检查是否已安装
+check_installed() {
+    # 检查目录是否存在且非空
+    if [ -d "/opt/xiaozhi-server/" ] && [ "$(ls -A /opt/xiaozhi-server/)" ]; then
+        DIR_CHECK=1
+    else
+        DIR_CHECK=0
+    fi
+    
+    # 检查容器是否存在
+    if docker inspect xiaozhi-esp32-server > /dev/null 2>&1; then
+        CONTAINER_CHECK=1
+    else
+        CONTAINER_CHECK=0
+    fi
+    
+    # 两次检查都通过
+    if [ $DIR_CHECK -eq 1 ] && [ $CONTAINER_CHECK -eq 1 ]; then
+        return 0  # 已安装
+    else
+        return 1  # 未安装
+    fi
+}
+
+# 更新相关
+if check_installed; then
+    if whiptail --title "已安装检测" --yesno "检测到小智服务端已安装，是否进行升级？" 10 60; then
+        # 用户选择升级，执行清理操作
+        echo "开始升级操作..."
+        
+        # 停止并移除所有docker-compose服务
+        docker compose -f /opt/xiaozhi-server/docker-compose_all.yml down
+        
+        # 停止并删除特定容器（考虑容器可能不存在的情况）
+        containers=(
+            "xiaozhi-esp32-server"
+            "xiaozhi-esp32-server-web"
+            "xiaozhi-esp32-server-db"
+            "xiaozhi-esp32-server-redis"
+        )
+        
+        for container in "${containers[@]}"; do
+            if docker ps -a --format '{{.Names}}' | grep -q "^${container}$"; then
+                docker stop "$container" >/dev/null 2>&1 && \
+                docker rm "$container" >/dev/null 2>&1 && \
+                echo "成功移除容器: $container"
+            else
+                echo "容器不存在，跳过: $container"
+            fi
+        done
+        
+        # 删除特定镜像（考虑镜像可能不存在的情况）
+        images=(
+            "ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:server_latest"
+            "ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:web_latest"
+        )
+        
+        for image in "${images[@]}"; do
+            if docker images --format '{{.Repository}}:{{.Tag}}' | grep -q "^${image}$"; then
+                docker rmi "$image" >/dev/null 2>&1 && \
+                echo "成功删除镜像: $image"
+            else
+                echo "镜像不存在，跳过: $image"
+            fi
+        done
+        
+        echo "所有清理操作完成"
+        
+        # 备份原有配置文件
+        mkdir -p /opt/xiaozhi-server/backup/
+        if [ -f /opt/xiaozhi-server/data/.config.yaml ]; then
+            cp /opt/xiaozhi-server/data/.config.yaml /opt/xiaozhi-server/backup/.config.yaml
+            echo "已备份原有配置文件到 /opt/xiaozhi-server/backup/.config.yaml"
+        fi
+        
+        # 下载最新版配置文件
+        check_and_download "/opt/xiaozhi-server/docker-compose_all.yml" "https://ghfast.top/https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/refs/heads/main/main/xiaozhi-server/docker-compose_all.yml"
+        check_and_download "/opt/xiaozhi-server/data/.config.yaml" "https://ghfast.top/https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/refs/heads/main/main/xiaozhi-server/config_from_api.yaml"
+        
+        # 启动Docker服务
+        echo "开始启动最新版本服务..."
+        # 升级完成后标记，跳过后续下载步骤
+        UPGRADE_COMPLETED=1
+        docker compose -f /opt/xiaozhi-server/docker-compose_all.yml up -d
+    else
+          whiptail --title "跳过升级" --msgbox "已取消升级，将继续使用当前版本。" 10 50
+          # 跳过升级，继续执行后续安装流程
+    fi
+fi
+
+
+# 检查curl安装
+if ! command -v curl &> /dev/null; then
+    echo "------------------------------------------------------------"
+    echo "未检测到curl，正在安装..."
+    apt update
+    apt install -y curl
+else
+    echo "------------------------------------------------------------"
+    echo "curl已安装，跳过安装步骤"
+fi
+
+# 检查Docker安装
+if ! command -v docker &> /dev/null; then
+    echo "------------------------------------------------------------"
+    echo "未检测到Docker，正在安装..."
+    
+    # 使用国内镜像源替代官方源
+    DISTRO=$(lsb_release -cs)
+    MIRROR_URL="https://mirrors.aliyun.com/docker-ce/linux/ubuntu"
+    GPG_URL="https://mirrors.aliyun.com/docker-ce/linux/ubuntu/gpg"
+    
+    # 安装基础依赖
+    apt update
+    apt install -y apt-transport-https ca-certificates curl software-properties-common gnupg
+    
+    # 创建密钥目录并添加国内镜像源密钥
+    mkdir -p /etc/apt/keyrings
+    curl -fsSL "$GPG_URL" | gpg --dearmor -o /etc/apt/keyrings/docker.gpg
+    
+    # 添加国内镜像源
+    echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] $MIRROR_URL $DISTRO stable" \
+        > /etc/apt/sources.list.d/docker.list
+    
+    # 添加备用官方源密钥（避免国内源密钥验证失败）
+    apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 7EA0A9C3F273FCD8 2>/dev/null || \
+    echo "警告：部分密钥添加失败，继续尝试安装..."
+    
+    # 安装Docker
+    apt update
+    apt install -y docker-ce docker-ce-cli containerd.io
+    
+    # 启动服务
+    systemctl start docker
+    systemctl enable docker
+    
+    # 检查是否安装成功
+    if docker --version; then
+        echo "------------------------------------------------------------"
+        echo "Docker安装完成！"
+    else
+        whiptail --title "错误" --msgbox "Docker安装失败，请检查日志。" 10 50
+        exit 1
+    fi
+else
+    echo "Docker已安装，跳过安装步骤"
+fi
+
+# Docker镜像源配置
+MIRROR_OPTIONS=(
+    "1" "轩辕镜像 (推荐)"
+    "2" "腾讯云镜像源"
+    "3" "中科大镜像源"
+    "4" "网易163镜像源"
+    "5" "华为云镜像源"
+    "6" "阿里云镜像源"
+    "7" "自定义镜像源"
+    "8" "跳过配置"
+)
+
+MIRROR_CHOICE=$(whiptail --title "选择Docker镜像源" --menu "请选择要使用的Docker镜像源" 20 60 10 \
+"${MIRROR_OPTIONS[@]}" 3>&1 1>&2 2>&3) || {
+    echo "用户取消选择，退出脚本"
+    exit 1
+}
+
+case $MIRROR_CHOICE in
+    1) MIRROR_URL="https://docker.xuanyuan.me" ;; 
+    2) MIRROR_URL="https://mirror.ccs.tencentyun.com" ;; 
+    3) MIRROR_URL="https://docker.mirrors.ustc.edu.cn" ;; 
+    4) MIRROR_URL="https://hub-mirror.c.163.com" ;; 
+    5) MIRROR_URL="https://05f073ad3c0010ea0f4bc00b7105ec20.mirror.swr.myhuaweicloud.com" ;; 
+    6) MIRROR_URL="https://registry.aliyuncs.com" ;; 
+    7) MIRROR_URL=$(whiptail --title "自定义镜像源" --inputbox "请输入完整的镜像源URL:" 10 60 3>&1 1>&2 2>&3) ;; 
+    8) MIRROR_URL="" ;; 
+esac
+
+if [ -n "$MIRROR_URL" ]; then
+    mkdir -p /etc/docker
+    if [ -f /etc/docker/daemon.json ]; then
+        cp /etc/docker/daemon.json /etc/docker/daemon.json.bak
+    fi
+    cat > /etc/docker/daemon.json <<EOF
+{
+    "dns": ["8.8.8.8", "114.114.114.114"],
+    "registry-mirrors": ["$MIRROR_URL"]
+}
+EOF
+    whiptail --title "配置成功" --msgbox "已成功添加镜像源: $MIRROR_URL\n请按Enter键重启Docker服务并继续..." 12 60
+    echo "------------------------------------------------------------"
+    echo "开始重启Docker服务..."
+    systemctl restart docker.service
+fi
+
+# 创建安装目录
+echo "------------------------------------------------------------"
+echo "开始创建安装目录..."
+# 检查并创建数据目录
+if [ ! -d /opt/xiaozhi-server/data ]; then
+    mkdir -p /opt/xiaozhi-server/data
+    echo "已创建数据目录: /opt/xiaozhi-server/data"
+else
+    echo "目录xiaozhi-server/data已存在，跳过创建"
+fi
+
+# 检查并创建模型目录
+if [ ! -d /opt/xiaozhi-server/models/SenseVoiceSmall ]; then
+    mkdir -p /opt/xiaozhi-server/models/SenseVoiceSmall
+    echo "已创建模型目录: /opt/xiaozhi-server/models/SenseVoiceSmall"
+else
+    echo "目录xiaozhi-server/models/SenseVoiceSmall已存在，跳过创建"
+fi
+
+echo "------------------------------------------------------------"
+echo "开始下载语音识别模型"
+# 下载模型文件
+MODEL_PATH="/opt/xiaozhi-server/models/SenseVoiceSmall/model.pt"
+if [ ! -f "$MODEL_PATH" ]; then
+    (
+    for i in {1..20}; do
+        echo $((i*5))
+        sleep 0.5
+    done
+    ) | whiptail --title "下载中" --gauge "开始下载语音识别模型..." 10 60 0
+    curl -fL --progress-bar https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt -o "$MODEL_PATH" || {
+        whiptail --title "错误" --msgbox "model.pt文件下载失败" 10 50
+        exit 1
+    }
+else
+    echo "model.pt文件已存在，跳过下载"
+fi
+
+# 如果不是升级完成，才执行下载
+if [ -z "$UPGRADE_COMPLETED" ]; then
+    check_and_download "/opt/xiaozhi-server/docker-compose_all.yml" "https://ghfast.top/https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/refs/heads/main/main/xiaozhi-server/docker-compose_all.yml"
+    check_and_download "/opt/xiaozhi-server/data/.config.yaml" "https://ghfast.top/https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/refs/heads/main/main/xiaozhi-server/config_from_api.yaml"
+fi
+
+# 启动Docker服务
+(
+echo "------------------------------------------------------------"
+echo "正在拉取Docker镜像..."
+echo "这可能需要几分钟时间，请耐心等待"
+docker compose -f /opt/xiaozhi-server/docker-compose_all.yml up -d
+
+if [ $? -ne 0 ]; then
+    whiptail --title "错误" --msgbox "Docker服务启动失败，请尝试更换镜像源后重新执行本脚本" 10 60
+    exit 1
+fi
+
+echo "------------------------------------------------------------"
+echo "正在检查服务启动状态..."
+TIMEOUT=300
+START_TIME=$(date +%s)
+while true; do
+    CURRENT_TIME=$(date +%s)
+    if [ $((CURRENT_TIME - START_TIME)) -gt $TIMEOUT ]; then
+        whiptail --title "错误" --msgbox "服务启动超时，未在指定时间内找到预期日志内容" 10 60
+        exit 1
+    fi
+    
+    if docker logs xiaozhi-esp32-server-web 2>&1 | grep -q "Started AdminApplication in"; then
+        break
+    fi
+    sleep 1
+done
+
+    echo "服务端启动成功！正在完成配置..."
+    echo "正在启动服务..."
+    docker compose -f /opt/xiaozhi-server/docker-compose_all.yml up -d
+    echo "服务启动完成！"
+)
+
+# 密钥配置
+
+# 获取服务器公网地址
+PUBLIC_IP=$(hostname -I | awk '{print $1}')
+whiptail --title "配置服务器密钥" --msgbox "请使用浏览器，访问下方链接，打开智控台并注册账号: \n\n内网地址：http://127.0.0.1:8002/\n公网地址：http://$PUBLIC_IP:8002/ (若是云服务器请在服务器安全组放行端口 8000 8001 8002)。\n\n注册的第一个用户即是超级管理员，以后注册的用户都是普通用户。普通用户只能绑定设备和配置智能体; 超级管理员可以进行模型管理、用户管理、参数配置等功能。\n\n注册好后请按Enter键继续" 18 70
+SECRET_KEY=$(whiptail --title "配置服务器密钥" --inputbox "请使用超级管理员账号登录智控台\n内网地址：http://127.0.0.1:8002/\n公网地址：http://$PUBLIC_IP:8002/\n在顶部菜单 参数字典 → 参数管理 找到参数编码: server.secret (服务器密钥) \n复制该参数值并输入到下面输入框\n\n请输入密钥(留空则跳过配置):" 15 60 3>&1 1>&2 2>&3)
+
+if [ -n "$SECRET_KEY" ]; then
+    python3 -c "
+import sys, yaml; 
+config_path = '/opt/xiaozhi-server/data/.config.yaml'; 
+with open(config_path, 'r') as f: 
+    config = yaml.safe_load(f) or {}; 
+config['manager-api'] = {'url': 'http://xiaozhi-esp32-server-web:8002/xiaozhi', 'secret': '$SECRET_KEY'}; 
+with open(config_path, 'w') as f: 
+    yaml.dump(config, f); 
+"
+    docker restart xiaozhi-esp32-server
+fi
+
+# 获取并显示地址信息
+LOCAL_IP=$(hostname -I | awk '{print $1}')
+
+# 修复日志文件获取不到ws的问题，改为硬编码
+whiptail --title "安装完成！" --msgbox "\
+服务端相关地址如下：\n\
+管理后台访问地址: http://$LOCAL_IP:8002\n\
+OTA 地址: http://$LOCAL_IP:8002/xiaozhi/ota/\n\
+视觉分析接口地址: http://$LOCAL_IP:8003/mcp/vision/explain\n\
+WebSocket 地址: ws://$LOCAL_IP:8000/xiaozhi/v1/\n\
+\n安装完毕！感谢您的使用！\n按Enter键退出..." 16 70

docs/Deployment.md

@@ -1,53 +1,63 @@
-# 方式一：docker快速部署
+# 部署架构图
+![请参考-最简化架构图](../docs/images/deploy1.png)
+# 方式一：Docker只运行Server
 
-docker镜像已支持x86架构、arm64架构的CPU，支持在国产操作系统上运行。
+`0.8.2`版本开始，本项目发行的docker镜像只支持`x86架构`，如果需要在`arm64架构`的CPU上部署，可按照[这个教程](docker-build.md)在本机编译`arm64的镜像`。
 
 ## 1. 安装docker
 
 如果您的电脑还没安装docker，可以按照这里的教程安装：[docker安装](https://www.runoob.com/docker/ubuntu-docker-install.html)
 
-## 2. 创建目录
+安装好docker后，进继续。
 
-安装完后，你需要为这个项目找一个安放配置文件的目录，我们暂且称它为`项目目录`，这个目录最好是一个新建的空的目录。
+### 1.1 手动部署
 
-创建好目录后，你需要在`项目目录`下面创建`data`文件夹和`models`文件夹，`models`下面还要再创建`SenseVoiceSmall`文件夹。
+#### 1.1.1 创建目录
+
+安装完docker后，你需要为这个项目找一个安放配置文件的目录，例如我们可以新建一个文件夹叫`xiaozhi-server`。
+
+创建好目录后，你需要在`xiaozhi-server`下面创建`data`文件夹和`models`文件夹，`models`下面还要再创建`SenseVoiceSmall`文件夹。
 
 最终目录结构如下所示：
 
 ```
-你的项目根目录
+xiaozhi-server
   ├─ data
   ├─ models
      ├─ SenseVoiceSmall
 ```
 
-## 4. 下载语音识别模型文件
+#### 1.1.2 下载语音识别模型文件
 
 你需要下载语音识别的模型文件，因为本项目的默认语音识别用的是本地离线语音识别方案。可通过这个方式下载
 [跳转到下载语音识别模型文件](#模型文件)
 
 下载完后，回到本教程。
 
-## 3. 下载docker-compose.yaml
+#### 1.1.3 下载配置文件
 
-用浏览器打开[这个链接](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docker-compose.yml)。
+你需要下载两个配置文件：`docker-compose.yaml` 和 `config.yaml`。需要从项目仓库下载这两个文件。
+
+##### 1.1.3.1 下载 docker-compose.yaml
+
+用浏览器打开[这个链接](../main/xiaozhi-server/docker-compose.yml)。
 
 在页面的右侧找到名称为`RAW`按钮，在`RAW`按钮的旁边，找到下载的图标，点击下载按钮，下载`docker-compose.yml`文件。 把文件下载到你的
-`项目目录`中。
+`xiaozhi-server`中。
 
 下载完后，回到本教程继续往下。
 
-## 3. 下载配置文件
+##### 1.1.3.2 创建 config.yaml
 
-用浏览器打开[这个链接](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/config.yaml)。
+用浏览器打开[这个链接](../main/xiaozhi-server/config.yaml)。
 
 在页面的右侧找到名称为`RAW`按钮，在`RAW`按钮的旁边，找到下载的图标，点击下载按钮，下载`config.yaml`文件。 把文件下载到你的
-`项目目录`下面的`data`文件夹中，然后把`config.yaml`文件重命名为`.config.yaml`。
+`xiaozhi-server`下面的`data`文件夹中，然后把`config.yaml`文件重命名为`.config.yaml`。
 
-下载完配置文件后，我们确认一下整个`项目目录`里面的文件如下所示：
+下载完配置文件后，我们确认一下整个`xiaozhi-server`里面的文件如下所示：
 
 ```
-你的项目根目录
+xiaozhi-server
   ├─ docker-compose.yml
   ├─ data
     ├─ .config.yaml
@@ -58,19 +68,19 @@ docker镜像已支持x86架构、arm64架构的CPU，支持在国产操作系统
 
 如果你的文件目录结构也是上面的，就继续往下。如果不是，你就再仔细看看是不是漏操作了什么。
 
-## 4. 配置项目文件
+## 2. 配置项目文件
 
 接下里，程序还不能直接运行，你需要配置一下，你到底使用的是什么模型。你可以看这个教程：
 [跳转到配置项目文件](#配置项目)
 
 配置完项目文件后，回到本教程继续往下。
 
-## 5. 执行docker命令
+## 3. 执行docker命令
 
-打开命令行工具，使用`终端`或`命令行`工具 进入到你的`项目目录`，执行以下命令
+打开命令行工具，使用`终端`或`命令行`工具 进入到你的`xiaozhi-server`，执行以下命令
 
 ```
-docker-compose up -d
+docker compose up -d
 ```
 
 执行完后，再执行以下命令，查看日志信息。
@@ -81,92 +91,61 @@ docker logs -f xiaozhi-esp32-server
 
 这时，你就要留意日志信息，可以根据这个教程，判断是否成功了。[跳转到运行状态确认](#运行状态确认)
 
-## 6.版本升级操作
+## 5. 版本升级操作
 
 如果后期想升级版本，可以这么操作
 
-1、备份好`data`文件夹中的`.config.yaml`文件，一些关键的配置到时复制到新的`.config.yaml`文件里。
+5.1、备份好`data`文件夹中的`.config.yaml`文件，一些关键的配置到时复制到新的`.config.yaml`文件里。
 请注意是对关键密钥逐个复制，不要直接覆盖。因为新的`.config.yaml`文件可能有一些新的配置项，旧的`.config.yaml`文件不一定有。
 
-2、执行以下命令
+5.2、执行以下命令
 
 ```
 docker stop xiaozhi-esp32-server
 docker rm xiaozhi-esp32-server
-docker rmi ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:latest
+docker stop xiaozhi-esp32-server-web
+docker rm xiaozhi-esp32-server-web
+docker rmi ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:server_latest
+docker rmi ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:web_latest
 ```
 
-3、重新按docker方式部署
+5.3、重新按docker方式部署
 
-# 方式二：借助Docker环境运行部署
-
-开发人员如果不想安装`conda`环境，可以使用这种方法管理好依赖。
-
-## 1.克隆项目
-
-## 2.[跳转到下载语音识别模型文件](#模型文件)
-
-## 3.[跳转到配置项目文件](#配置项目)
-
-## 4.运行docker
-
-修改完配置后，打开命令行工具，`cd`进入到你的项目目录下，执行以下命令
-
-```sh
-docker run -it --name xiaozhi-env --restart always --security-opt seccomp:unconfined \
-  -p 8000:8000 \
-  -p 8002:8002 \
-  -v ./:/app \
-  ccr.ccs.tencentyun.com/kalicyh/poetry:v3.10_latest
-```
-
-然后就和正常开发一样了
-
-## 5.安装依赖
-
-在刚刚的打开的终端运行
-
-```sh
-poetry install --no-root
-```
-
-```sh
-apt-get update
-apt-get install -y --no-install-recommends libopus0 ffmpeg
-```
-
-速度慢可以尝试使用清华镜像
-
-```sh
-echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm main contrib non-free non-free-firmware" > /etc/apt/sources.list
-echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-updates main contrib non-free non-free-firmware" >> /etc/apt/sources.list
-echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-backports main contrib non-free non-free-firmware" >> /etc/apt/sources.list
-echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian-security bookworm-security main contrib non-free non-free-firmware" >> /etc/apt/sources.list
-apt-get update
-apt-get install -y --no-install-recommends libopus0 ffmpeg
-```
-
-## 6.运行项目
-
-```sh
-poetry run python app.py
-```
-
-# 方式三：本地源码运行
+# 方式二：本地源码只运行Server
 
 ## 1.安装基础环境
 
 本项目使用`conda`管理依赖环境。如果不方便安装`conda`，需要根据实际的操作系统安装好`libopus`和`ffmpeg`。
 如果确定使用`conda`，则安装好后，开始执行以下命令。
 
+重要提示！windows 用户，可以通过安装`Anaconda`来管理环境。安装好`Anaconda`后，在`开始`那里搜索`anaconda`相关的关键词，
+找到`Anaconda Prpmpt`，使用管理员身份运行它。如下图。
+
+![conda_prompt](./images/conda_env_1.png)
+
+运行之后，如果你能看到命令行窗口前面有一个(base)字样，说明你成功进入了`conda`环境。那么你就可以执行以下命令了。
+
+![conda_env](./images/conda_env_2.png)
+
 ```
 conda remove -n xiaozhi-esp32-server --all -y
 conda create -n xiaozhi-esp32-server python=3.10 -y
 conda activate xiaozhi-esp32-server
-conda install conda-forge::libopus -y
-conda install conda-forge::ffmpeg -y
+
+# 添加清华源通道
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
+
+conda install libopus -y
+conda install ffmpeg -y
+
+# 在 Linux 环境下进行部署时,如出现类似缺失 libiconv.so.2 动态库的报错 请通过以下命令进行安装
+conda install libiconv -y
 ```
 
+请注意，以上命令，不是一股脑执行就成功的，你需要一步步执行，每一步执行完后，都检查一下输出的日志，查看是否成功。
+
 ## 2.安装本项目依赖
 
 你先要下载本项目源码，源码可以通过`git clone`命令下载，如果你不熟悉`git clone`命令。
@@ -176,11 +155,13 @@ conda install conda-forge::ffmpeg -y
 打开完，找到页面中一个绿色的按钮，写着`Code`的按钮，点开它，然后你就看到`Download ZIP`的按钮。
 
 点击它，下载本项目源码压缩包。下载到你电脑后，解压它，此时它的名字可能叫`xiaozhi-esp32-server-main`
-你需要把它重命名成`xiaozhi-esp32-server`，好了请记住这个目录，我们暂且称它为`项目目录`。
+你需要把它重命名成`xiaozhi-esp32-server`，在这个文件里，进入到`main`文件夹，再进入到`xiaozhi-server`，好了请记住这个目录`xiaozhi-server`。
 
 ```
-# 使用dos或者终端，进入到你的项目目录，执行以下命令
+# 继续使用conda环境
 conda activate xiaozhi-esp32-server
+# 进入到你的项目根目录，再进入main/xiaozhi-server
+cd main/xiaozhi-server
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 pip install -r requirements.txt
 ```
@@ -194,66 +175,61 @@ pip install -r requirements.txt
 
 ## 4.配置项目文件
 
-接下里，程序还不能直接运行，你需要配置一下，你到底使用的是什么模型。你可以看这个教程：
+接下来，程序还不能直接运行，你需要配置一下，你到底使用的是什么模型。你可以看这个教程：
 [跳转到配置项目文件](#配置项目)
 
 ## 5.运行项目
 
 ```
-# 确保在本项目的根目录下执行
+# 确保在xiaozhi-server目录下执行
 conda activate xiaozhi-esp32-server
 python app.py
 ```
-
 这时，你就要留意日志信息，可以根据这个教程，判断是否成功了。[跳转到运行状态确认](#运行状态确认)
 
+
 # 汇总
 
 ## 配置项目
 
-如果你的`项目目录`目录没有`data`，你需要创建`data`目录。
-如果你的`data`下面没有`.config.yaml`文件，你可以把源码目录下的`config.yaml`文件复制一份，重命名为`.config.yaml`
+如果你的`xiaozhi-server`目录没有`data`，你需要创建`data`目录。
+如果你的`data`下面没有`.config.yaml`文件，有两个方式，任选一种：
 
-修改`项目目录`下`data`目录下的`.config.yaml`文件，配置本项目所需的各种参数。默认的LLM使用的是`ChatGLMLLM`
-，你需要配置密钥，因为他们的模型，虽然有免费的，但是仍要去[官网](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)注册密钥，才能启动。
-默认的TTS使用的是`EdgeTTS`，这个无需配置，如果你需要更换成`豆包TTS`，则需要配置密钥。
+第一个方式：你可以把`xiaozhi-server`目录下的`config.yaml`文件复制到`data`，并重命名为`.config.yaml`。在此文件上修改
 
-配置说明：这里是各个功能使用的默认组件，例如LLM默认使用`ChatGLMLLM`模型。如果需要切换模型，就是改对应的名称。
-本项目的默认配置仅是成本最低配置（`glm-4-flash`和`EdgeTTS`都是免费的），如果需要更优的更快的搭配，需要自己结合部署环境切换各组件的使用。
+第二个方式：你也可以创建在`data`目录下手动创建`.config.yaml`空文件，然后在这个文件中增加必要的配置信息，系统会优先读取`.config.yaml`文件的配置，如果`.config.yaml`没有配置的，系统会自动去加载`xiaozhi-server`目录下的`config.yaml`的配置。推荐使用这种方式，这种方式是最简洁的方式。
+
+- 默认的LLM使用的是`ChatGLMLLM`，你需要配置密钥，因为他们的模型，虽然有免费的，但是仍要去[官网](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)注册密钥，才能启动。
+
+以下是一个能正常跑起来的，最简单的`.config.yaml`配置示例
 
 ```
+server:
+  websocket: ws://你的ip或者域名:端口号/xiaozhi/v1/
+prompt: |
+  我是一个叫小智/小志的台湾女孩，说话机车，声音好听，习惯简短表达，爱用网络梗。
+  我的男朋友是一个程序员，梦想是开发出一个机器人，能够帮助人们解决生活中的各种问题。
+  我是一个喜欢哈哈大笑的女孩，爱东说西说吹牛，不合逻辑的也照吹，就要逗别人开心。
+  请你像一个人一样说话，请勿返回配置xml及其他特殊字符。
+
 selected_module:
-  ASR: FunASR
-  VAD: SileroVAD
-  LLM: ChatGLMLLM
-  TTS: EdgeTTS
-```
+  LLM: DoubaoLLM
 
-比如修改`LLM`使用的组件，就看本项目支持哪些`LLM` API接口，当前支持的是`openai`、`dify`。欢迎验证和支持更多LLM平台的接口。
-使用时，在`selected_module`修改成对应的如下LLM配置的名称：
-
-```
 LLM:
-  DeepSeekLLM:
-    type: openai
-    ...
   ChatGLMLLM:
-    type: openai
-    ...
-  DifyLLM:
-    type: dify
-    ...
+    api_key: xxxxxxxxxxxxxxx.xxxxxx
 ```
 
-有些服务，比如如果你使用`Dify`、`豆包的TTS`，是需要密钥的，记得在配置文件加上哦！
+建议先将最简单的配置运行起来，然后再去`xiaozhi/config.yaml`阅读配置的使用说明。
+比如你要换更换模型，修改`selected_module`下的配置就行。
 
 ## 模型文件
 
 本项目语音识别模型，默认使用`SenseVoiceSmall`模型，进行语音转文字。因为模型较大，需要独立下载，下载后把`model.pt`
-文件放在`model/SenseVoiceSmall`
+文件放在`models/SenseVoiceSmall`
 目录下。下面两个下载路线任选一个。
 
-- 线路一：阿里魔塔下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)
+- 线路一：阿里魔搭下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)
 - 线路二：百度网盘下载[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码:
   `qvna`
 
@@ -262,16 +238,54 @@ LLM:
 如果你能看到，类似以下日志,则是本项目服务启动成功的标志。
 
 ```
-25-02-23 12:01:09[core.websocket_server] - INFO - Server is running at ws://xxx.xx.xx.xx:8000
-25-02-23 12:01:09[core.websocket_server] - INFO - =======上面的地址是websocket协议地址，请勿用浏览器访问=======
+250427 13:04:20[0.3.11_SiFuChTTnofu][__main__]-INFO-OTA接口是           http://192.168.4.123:8003/xiaozhi/ota/
+250427 13:04:20[0.3.11_SiFuChTTnofu][__main__]-INFO-Websocket地址是     ws://192.168.4.123:8000/xiaozhi/v1/
+250427 13:04:20[0.3.11_SiFuChTTnofu][__main__]-INFO-=======上面的地址是websocket协议地址，请勿用浏览器访问=======
+250427 13:04:20[0.3.11_SiFuChTTnofu][__main__]-INFO-如想测试websocket请启动digital-human模块，打开浏览器交互测试
+250427 13:04:20[0.3.11_SiFuChTTnofu][__main__]-INFO-=======================================================
 ```
 
 正常来说，如果您是通过源码运行本项目，日志会有你的接口地址信息。
 但是如果你用docker部署，那么你的日志里给出的接口地址信息就不是真实的接口地址。
 
 最正确的方法，是根据电脑的局域网IP来确定你的接口地址。
-如果你的电脑的局域网IP比如是`192.168.1.25`，那么你的接口地址就是：`ws://192.168.1.25:8000`。
+如果你的电脑的局域网IP比如是`192.168.1.25`，那么你的接口地址就是：`ws://192.168.1.25:8000/xiaozhi/v1/`，对应的OTA地址就是：`http://192.168.1.25:8003/xiaozhi/ota/`。
 
 这个信息很有用的，后面`编译esp32固件`需要用到。
 
-接下来，你就可以开始 [编译esp32固件](firmware-build.md)了。
+接下来，你就可以开始操作你的esp32设备了，你可以`自行编译esp32固件`也可以配置使用`虾哥编译好的1.6.1以上版本的固件`。两个任选一个
+
+1、 [编译自己的esp32固件](firmware-build.md)了。
+
+2、 [基于虾哥编译好的固件配置自定义服务器](firmware-setting.md)了。
+
+# 常见问题
+以下是一些常见问题，供参考：
+
+1、[为什么我说的话，小智识别出来很多韩文、日文、英文](./FAQ.md)<br/>
+2、[为什么会出现“TTS 任务出错 文件不存在”？](./FAQ.md)<br/>
+3、[TTS 经常失败，经常超时](./FAQ.md)<br/>
+4、[使用Wifi能连接自建服务器，但是4G模式却接不上](./FAQ.md)<br/>
+5、[如何提高小智对话响应速度？](./FAQ.md)<br/>
+6、[我说话很慢，停顿时小智老是抢话](./FAQ.md)<br/>
+## 部署相关教程
+1、[如何自动拉取本项目最新代码自动编译和启动](./dev-ops-integration.md)<br/>
+2、[如何部署MQTT网关开启MQTT+UDP协议](./mqtt-gateway-integration.md)<br/>
+3、[如何与Nginx集成](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)<br/>
+## 拓展相关教程
+1、[如何开启手机号码注册智控台](./ali-sms-integration.md)<br/>
+2、[如何集成HomeAssistant实现智能家居控制](./homeassistant-integration.md)<br/>
+3、[如何开启视觉模型实现拍照识物](./mcp-vision-integration.md)<br/>
+4、[如何部署MCP接入点](./mcp-endpoint-enable.md)<br/>
+5、[如何接入MCP接入点](./mcp-endpoint-integration.md)<br/>
+6、[如何开启声纹识别](./voiceprint-integration.md)<br/>
+7、[新闻插件源配置指南](./newsnow_plugin_config.md)<br/>
+8、[天气插件使用指南](./weather-integration.md)<br/>
+## 语音克隆、本地语音部署相关教程
+1、[如何在智控台克隆音色](./huoshan-streamTTS-voice-cloning.md)<br/>
+2、[如何部署集成index-tts本地语音](./index-stream-integration.md)<br/>
+3、[如何部署集成fish-speech本地语音](./fish-speech-integration.md)<br/>
+4、[如何部署集成PaddleSpeech本地语音](./paddlespeech-deploy.md)<br/>
+## 性能测试教程
+1、[各组件速度测试指南](./performance_tester.md)<br/>
+2、[定期公开测试结果](https://github.com/xinnan-tech/xiaozhi-performance-research)<br/>

docs/Deployment_all.md

@@ -0,0 +1,492 @@
+# 部署架构图
+![请参考-全模块安装架构图](../docs/images/deploy2.png)
+# 方式一：Docker运行全模块
+`0.8.2`版本开始，本项目发行的docker镜像只支持`x86架构`，如果需要在`arm64架构`的CPU上部署，可按照[这个教程](docker-build.md)在本机编译`arm64的镜像`。
+
+## 1. 安装docker
+
+如果您的电脑还没安装docker，可以按照这里的教程安装：[docker安装](https://www.runoob.com/docker/ubuntu-docker-install.html)
+
+docker 安装全模块有两种方式，你可以[使用懒人脚本](./Deployment_all.md#11-懒人脚本)（作者[@VanillaNahida](https://github.com/VanillaNahida)）  
+脚本会自动帮你下载所需的文件和配置文件，你也可以使用[手动部署](./Deployment_all.md#12-手动部署)从零搭建。
+
+
+
+### 1.1 懒人脚本
+部署简便，可以参考[视频教程](https://www.bilibili.com/video/BV17bbvzHExd/) ，文字版教程如下：
+> [!NOTE]  
+> 暂且只支持Ubuntu服务器一键部署，其他系统未尝试，可能会有一些奇怪的bug
+
+使用SSH工具连接到服务器，以root权限执行如下脚本
+```bash
+sudo bash -c "$(wget -qO- https://ghfast.top/https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/main/docker-setup.sh)"
+```
+
+脚本会自动完成以下操作：
+> 1. 安装Docker
+> 2. 配置镜像源
+> 3. 下载/拉取镜像
+> 4. 下载语音识别模型文件
+> 5. 引导配置服务端
+>
+
+执行完成后简单配置后，再参照[4. 运行程序](#4. 运行程序)和[5.重启xiaozhi-esp32-server](#5.重启xiaozhi-esp32-server)里提到的最重要的3件事情，完成3这三项配置后即可使用。
+
+### 1.2 手动部署
+
+#### 1.2.1 创建目录
+
+安装完后，你需要为这个项目找一个安放配置文件的目录，例如我们可以新建一个文件夹叫`xiaozhi-server`。
+
+创建好目录后，你需要在`xiaozhi-server`下面创建`data`文件夹和`models`文件夹，`models`下面还要再创建`SenseVoiceSmall`文件夹。
+
+最终目录结构如下所示：
+
+```
+xiaozhi-server
+  ├─ data
+  ├─ models
+     ├─ SenseVoiceSmall
+```
+
+#### 1.2.2 下载语音识别模型文件
+
+本项目语音识别模型，默认使用`SenseVoiceSmall`模型，进行语音转文字。因为模型较大，需要独立下载，下载后把`model.pt`
+文件放在`models/SenseVoiceSmall`
+目录下。下面两个下载路线任选一个。
+
+- 线路一：阿里魔搭下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)
+- 线路二：百度网盘下载[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码:
+  `qvna`
+
+
+#### 1.2.3 下载配置文件
+
+你需要下载两个配置文件：`docker-compose_all.yaml` 和 `config_from_api.yaml`。需要从项目仓库下载这两个文件。
+
+##### 1.2.3.1 下载 docker-compose_all.yaml
+
+用浏览器打开[这个链接](../main/xiaozhi-server/docker-compose_all.yml)。
+
+在页面的右侧找到名称为`RAW`按钮，在`RAW`按钮的旁边，找到下载的图标，点击下载按钮，下载`docker-compose_all.yml`文件。 把文件下载到你的
+`xiaozhi-server`中。
+
+或者直接执行 `wget https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/refs/heads/main/main/xiaozhi-server/docker-compose_all.yml` 下载。
+
+下载完后，回到本教程继续往下。
+
+##### 1.2.3.2 下载 config_from_api.yaml
+
+用浏览器打开[这个链接](../main/xiaozhi-server/config_from_api.yaml)。
+
+在页面的右侧找到名称为`RAW`按钮，在`RAW`按钮的旁边，找到下载的图标，点击下载按钮，下载`config_from_api.yaml`文件。 把文件下载到你的
+`xiaozhi-server`下面的`data`文件夹中，然后把`config_from_api.yaml`文件重命名为`.config.yaml`。
+
+或者直接执行 `wget https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/refs/heads/main/main/xiaozhi-server/config_from_api.yaml` 下载保存。
+
+下载完配置文件后，我们确认一下整个`xiaozhi-server`里面的文件如下所示：
+
+```
+xiaozhi-server
+  ├─ docker-compose_all.yml
+  ├─ data
+    ├─ .config.yaml
+  ├─ models
+     ├─ SenseVoiceSmall
+       ├─ model.pt
+```
+
+如果你的文件目录结构也是上面的，就继续往下。如果不是，你就再仔细看看是不是漏操作了什么。
+
+## 2. 备份数据
+
+如果你之前已经成功运行智控台，如果上面保存有你的密钥信息，请先从智控台上拷贝重要数据下来。因为升级过程中，有可能会覆盖原来的数据。
+
+## 3. 清除历史版本镜像和容器
+接下来打开命令行工具，使用`终端`或`命令行`工具 进入到你的`xiaozhi-server`，执行以下命令
+
+```
+docker compose -f docker-compose_all.yml down
+
+docker stop xiaozhi-esp32-server
+docker rm xiaozhi-esp32-server
+
+docker stop xiaozhi-esp32-server-web
+docker rm xiaozhi-esp32-server-web
+
+docker stop xiaozhi-esp32-server-db
+docker rm xiaozhi-esp32-server-db
+
+docker stop xiaozhi-esp32-server-redis
+docker rm xiaozhi-esp32-server-redis
+
+docker rmi ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:server_latest
+docker rmi ghcr.nju.edu.cn/xinnan-tech/xiaozhi-esp32-server:web_latest
+```
+
+## 4. 运行程序
+执行以下命令启动新版本容器
+
+```
+docker compose -f docker-compose_all.yml up -d
+```
+
+执行完后，再执行以下命令，查看日志信息。
+
+```
+docker logs -f xiaozhi-esp32-server-web
+```
+
+当你看到输出日志时，说明你的`智控台`启动成功了。
+
+```
+2025-xx-xx 22:11:12.445 [main] INFO  c.a.d.s.b.a.DruidDataSourceAutoConfigure - Init DruidDataSource
+2025-xx-xx 21:28:53.873 [main] INFO  xiaozhi.AdminApplication - Started AdminApplication in 16.057 seconds (process running for 17.941)
+http://localhost:8002/xiaozhi/doc.html
+```
+
+请注意此刻仅是`智控台`能运行，如果8000端口`xiaozhi-esp32-server`报错，先不要理会。
+
+这时，你需要使用浏览器，打开`智控台`，链接：http://127.0.0.1:8002 ，注册第一个用户。第一个用户即是超级管理员，以后的用户都是普通用户。普通用户只能绑定设备和配置智能体;超级管理员可以进行模型管理、用户管理、参数配置等功能。
+
+接下来要做三件重要的事情：
+
+### 第一件重要的事情
+
+使用超级管理员账号，登录智控台，在顶部菜单找到`参数管理`，找到列表中第一条数据，参数编码是`server.secret`，复制它到`参数值`。
+
+`server.secret`需要说明一下，这个`参数值`很重要，作用是让我们的`Server`端连接`manager-api`。`server.secret`是每次从零部署manager模块时，会自动随机生成的密钥。
+
+复制`参数值`后，打开`xiaozhi-server`下的`data`目录的`.config.yaml`文件。此刻你的配置文件内容应该是这样的：
+
+```
+manager-api:
+  url:  http://127.0.0.1:8002/xiaozhi
+  secret: 你的server.secret值
+```
+1、把你刚才从`智控台`复制过来的`server.secret`的`参数值`复制到`.config.yaml`文件里的`secret`里。
+
+2、因为你是docker部署，把`url`改成下面的`http://xiaozhi-esp32-server-web:8002/xiaozhi`
+
+3、因为你是docker部署，把`url`改成下面的`http://xiaozhi-esp32-server-web:8002/xiaozhi`
+
+4、因为你是docker部署，把`url`改成下面的`http://xiaozhi-esp32-server-web:8002/xiaozhi`
+
+类似这样的效果
+```
+manager-api:
+  url: http://xiaozhi-esp32-server-web:8002/xiaozhi
+  secret: 12345678-xxxx-xxxx-xxxx-123456789000
+```
+
+保存好后，继续往下做第二件重要的事情
+
+### 第二件重要的事情
+
+使用超级管理员账号，登录智控台，在顶部菜单找到`模型配置`，然后在左侧栏点击`大语言模型`，找到第一条数据`智谱AI`，点击`修改`按钮，
+弹出修改框后，将你注册到的`智谱AI`的密钥填写到`API密钥`中。然后点击保存。
+
+## 5.重启xiaozhi-esp32-server
+
+接下来打开命令行工具，使用`终端`或`命令行`工具 输入
+```
+docker restart xiaozhi-esp32-server
+docker logs -f xiaozhi-esp32-server
+```
+如果你能看到，类似以下日志,则是Server启动成功的标志。
+
+```
+25-02-23 12:01:09[core.websocket_server] - INFO - Websocket地址是      ws://xxx.xx.xx.xx:8000/xiaozhi/v1/
+25-02-23 12:01:09[core.websocket_server] - INFO - =======上面的地址是websocket协议地址，请勿用浏览器访问=======
+25-02-23 12:01:09[core.websocket_server] - INFO - 如想测试websocket请启动digital-human模块，打开浏览器交互测试
+25-02-23 12:01:09[core.websocket_server] - INFO - =======================================================
+```
+
+由于你是全模块部署，因此你有两个重要的接口需要写入到esp32中。
+
+OTA接口：
+```
+http://你宿主机局域网的ip:8002/xiaozhi/ota/
+```
+
+Websocket接口：
+```
+ws://你宿主机的ip:8000/xiaozhi/v1/
+```
+
+### 第三件重要的事情
+
+使用超级管理员账号，登录智控台，在顶部菜单找到`参数管理`，找到参数编码是`server.websocket`，输入你的`Websocket接口`。
+
+使用超级管理员账号，登录智控台，在顶部菜单找到`参数管理`，找到数编码是`server.ota`，输入你的`OTA接口`。
+
+接下来，你就可以开始操作你的esp32设备了，你可以`自行编译esp32固件`也可以配置使用`虾哥编译好的1.6.1以上版本的固件`。两个任选一个
+
+1、 [编译自己的esp32固件](firmware-build.md)了。
+
+2、 [基于虾哥编译好的固件配置自定义服务器](firmware-setting.md)了。
+
+
+# 方式二：本地源码运行全模块
+
+## 1.安装MySQL数据库
+
+如果本机已经安装了MySQL，可以直接在数据库中创建名为`xiaozhi_esp32_server`的数据库。
+
+```sql
+CREATE DATABASE xiaozhi_esp32_server CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
+```
+
+如果还没有MySQL，你可以通过docker安装mysql
+
+```
+docker run --name xiaozhi-esp32-server-db -e MYSQL_ROOT_PASSWORD=123456 -p 3306:3306 -e MYSQL_DATABASE=xiaozhi_esp32_server -e MYSQL_INITDB_ARGS="--character-set-server=utf8mb4 --collation-server=utf8mb4_unicode_ci" -e TZ=Asia/Shanghai -d mysql:latest
+```
+
+## 2.安装redis
+
+如果还没有Redis，你可以通过docker安装redis
+
+```
+docker run --name xiaozhi-esp32-server-redis -d -p 6379:6379 redis
+```
+
+## 3.运行manager-api程序
+
+3.1 安装JDK21，设置JDK环境变量
+
+3.2 安装Maven，设置Maven环境变量
+
+3.3 使用Vscode编程工具，安装好Java环境相关插件
+
+3.4 使用Vscode编程工具加载manager-api模块
+
+在`src/main/resources/application-dev.yml`中配置数据库连接信息
+
+```
+spring:
+  datasource:
+    username: root
+    password: 123456
+```
+在`src/main/resources/application-dev.yml`中配置Redis连接信息
+```
+spring:
+    data:
+      redis:
+        host: localhost
+        port: 6379
+        password:
+        database: 0
+```
+
+3.5 运行主程序
+
+本项目为SpringBoot项目，启动方式为：
+打开`Application.java`运行`Main`方法启动
+
+```
+路径地址：
+src/main/java/xiaozhi/AdminApplication.java
+```
+
+当你看到输出日志时，说明你的`manager-api`启动成功了。
+
+```
+2025-xx-xx 22:11:12.445 [main] INFO  c.a.d.s.b.a.DruidDataSourceAutoConfigure - Init DruidDataSource
+2025-xx-xx 21:28:53.873 [main] INFO  xiaozhi.AdminApplication - Started AdminApplication in 16.057 seconds (process running for 17.941)
+http://localhost:8002/xiaozhi/doc.html
+```
+
+## 4.运行manager-web程序
+
+4.1 安装nodejs
+
+4.2 使用Vscode编程工具加载manager-web模块
+
+终端命令进入manager-web目录下
+
+```
+npm install
+```
+然后启动
+```
+npm run serve
+```
+
+请注意，如果你的manager-api的接口不在`http://localhost:8002`，请在开发时，修改
+`main/manager-web/.env.development`中的路径
+
+运行成功后，你需要使用浏览器，打开`智控台`，链接：http://127.0.0.1:8001 ，注册第一个用户。第一个用户即是超级管理员，以后的用户都是普通用户。普通用户只能绑定设备和配置智能体;超级管理员可以进行模型管理、用户管理、参数配置等功能。
+
+
+重要：注册成功后，使用超级管理员账号，登录智控台，在顶部菜单找到`模型配置`，然后在左侧栏点击`大语言模型`，找到第一条数据`智谱AI`，点击`修改`按钮，
+弹出修改框后，将你注册到的`智谱AI`的密钥填写到`API密钥`中。然后点击保存。
+
+重要：注册成功后，使用超级管理员账号，登录智控台，在顶部菜单找到`模型配置`，然后在左侧栏点击`大语言模型`，找到第一条数据`智谱AI`，点击`修改`按钮，
+弹出修改框后，将你注册到的`智谱AI`的密钥填写到`API密钥`中。然后点击保存。
+
+重要：注册成功后，使用超级管理员账号，登录智控台，在顶部菜单找到`模型配置`，然后在左侧栏点击`大语言模型`，找到第一条数据`智谱AI`，点击`修改`按钮，
+弹出修改框后，将你注册到的`智谱AI`的密钥填写到`API密钥`中。然后点击保存。
+
+## 5.安装Python环境
+
+本项目使用`conda`管理依赖环境。如果不方便安装`conda`，需要根据实际的操作系统安装好`libopus`和`ffmpeg`。
+如果确定使用`conda`，则安装好后，开始执行以下命令。
+
+重要提示！windows 用户，可以通过安装`Anaconda`来管理环境。安装好`Anaconda`后，在`开始`那里搜索`anaconda`相关的关键词，
+找到`Anaconda Prpmpt`，使用管理员身份运行它。如下图。
+
+![conda_prompt](./images/conda_env_1.png)
+
+运行之后，如果你能看到命令行窗口前面有一个(base)字样，说明你成功进入了`conda`环境。那么你就可以执行以下命令了。
+
+![conda_env](./images/conda_env_2.png)
+
+```
+conda remove -n xiaozhi-esp32-server --all -y
+conda create -n xiaozhi-esp32-server python=3.10 -y
+conda activate xiaozhi-esp32-server
+
+# 添加清华源通道
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
+
+conda install libopus -y
+conda install ffmpeg -y
+
+# 在 Linux 环境下进行部署时,如出现类似缺失 libiconv.so.2 动态库的报错 请通过以下命令进行安装
+conda install libiconv -y
+```
+
+请注意，以上命令，不是一股脑执行就成功的，你需要一步步执行，每一步执行完后，都检查一下输出的日志，查看是否成功。
+
+## 6.安装本项目依赖
+
+你先要下载本项目源码，源码可以通过`git clone`命令下载，如果你不熟悉`git clone`命令。
+
+你可以用浏览器打开这个地址`https://github.com/xinnan-tech/xiaozhi-esp32-server.git`
+
+打开完，找到页面中一个绿色的按钮，写着`Code`的按钮，点开它，然后你就看到`Download ZIP`的按钮。
+
+点击它，下载本项目源码压缩包。下载到你电脑后，解压它，此时它的名字可能叫`xiaozhi-esp32-server-main`
+你需要把它重命名成`xiaozhi-esp32-server`，在这个文件里，进入到`main`文件夹，再进入到`xiaozhi-server`，好了请记住这个目录`xiaozhi-server`。
+
+```
+# 继续使用conda环境
+conda activate xiaozhi-esp32-server
+# 进入到你的项目根目录，再进入main/xiaozhi-server
+cd main/xiaozhi-server
+pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
+pip install -r requirements.txt
+```
+
+### 7.下载语音识别模型文件
+
+本项目语音识别模型，默认使用`SenseVoiceSmall`模型，进行语音转文字。因为模型较大，需要独立下载，下载后把`model.pt`
+文件放在`models/SenseVoiceSmall`
+目录下。下面两个下载路线任选一个。
+
+- 线路一：阿里魔搭下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)
+- 线路二：百度网盘下载[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码:
+  `qvna`
+
+## 8.配置项目文件
+
+使用超级管理员账号，登录智控台 ，在顶部菜单找到`参数管理`，找到列表中第一条数据，参数编码是`server.secret`，复制它到`参数值`。
+
+`server.secret`需要说明一下，这个`参数值`很重要，作用是让我们的`Server`端连接`manager-api`。`server.secret`是每次从零部署manager模块时，会自动随机生成的密钥。
+
+如果你的`xiaozhi-server`目录没有`data`，你需要创建`data`目录。
+如果你的`data`下面没有`.config.yaml`文件，你可以把`xiaozhi-server`目录下的`config_from_api.yaml`文件复制到`data`，并重命名为`.config.yaml`
+
+复制`参数值`后，打开`xiaozhi-server`下的`data`目录的`.config.yaml`文件。此刻你的配置文件内容应该是这样的：
+
+```
+manager-api:
+  url: http://127.0.0.1:8002/xiaozhi
+  secret: 你的server.secret值
+```
+
+把你刚才从`智控台`复制过来的`server.secret`的`参数值`复制到`.config.yaml`文件里的`secret`里。
+
+类似这样的效果
+```
+manager-api:
+  url: http://127.0.0.1:8002/xiaozhi
+  secret: 12345678-xxxx-xxxx-xxxx-123456789000
+```
+
+## 9.运行项目
+
+```
+# 确保在xiaozhi-server目录下执行
+conda activate xiaozhi-esp32-server
+python app.py
+```
+
+如果你能看到，类似以下日志,则是本项目服务启动成功的标志。
+
+```
+25-02-23 12:01:09[core.websocket_server] - INFO - Server is running at ws://xxx.xx.xx.xx:8000/xiaozhi/v1/
+25-02-23 12:01:09[core.websocket_server] - INFO - =======上面的地址是websocket协议地址，请勿用浏览器访问=======
+25-02-23 12:01:09[core.websocket_server] - INFO - 如想测试websocket请启动digital-human模块，打开浏览器交互测试
+25-02-23 12:01:09[core.websocket_server] - INFO - =======================================================
+```
+
+由于你是全模块部署，因此你有两个重要的接口。
+
+OTA接口：
+```
+http://你电脑局域网的ip:8002/xiaozhi/ota/
+```
+
+Websocket接口：
+```
+ws://你电脑局域网的ip:8000/xiaozhi/v1/
+```
+
+请你务必把以上两个接口地址写入到智控台中：他们将会影响websocket地址发放和自动升级功能。
+
+1、使用超级管理员账号，登录智控台，在顶部菜单找到`参数管理`，找到参数编码是`server.websocket`，输入你的`Websocket接口`。
+
+2、使用超级管理员账号，登录智控台，在顶部菜单找到`参数管理`，找到数编码是`server.ota`，输入你的`OTA接口`。
+
+
+接下来，你就可以开始操作你的esp32设备了，你可以`自行编译esp32固件`也可以配置使用`虾哥编译好的1.6.1以上版本的固件`。两个任选一个
+
+1、 [编译自己的esp32固件](firmware-build.md)了。
+
+2、 [基于虾哥编译好的固件配置自定义服务器](firmware-setting.md)了。
+
+# 常见问题
+以下是一些常见问题，供参考：
+
+1、[为什么我说的话，小智识别出来很多韩文、日文、英文](./FAQ.md)<br/>
+2、[为什么会出现“TTS 任务出错 文件不存在”？](./FAQ.md)<br/>
+3、[TTS 经常失败，经常超时](./FAQ.md)<br/>
+4、[使用Wifi能连接自建服务器，但是4G模式却接不上](./FAQ.md)<br/>
+5、[如何提高小智对话响应速度？](./FAQ.md)<br/>
+6、[我说话很慢，停顿时小智老是抢话](./FAQ.md)<br/>
+## 部署相关教程
+1、[如何自动拉取本项目最新代码自动编译和启动](./dev-ops-integration.md)<br/>
+2、[如何部署MQTT网关开启MQTT+UDP协议](./mqtt-gateway-integration.md)<br/>
+3、[如何与Nginx集成](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)<br/>
+## 拓展相关教程
+1、[如何开启手机号码注册智控台](./ali-sms-integration.md)<br/>
+2、[如何集成HomeAssistant实现智能家居控制](./homeassistant-integration.md)<br/>
+3、[如何开启视觉模型实现拍照识物](./mcp-vision-integration.md)<br/>
+4、[如何部署MCP接入点](./mcp-endpoint-enable.md)<br/>
+5、[如何接入MCP接入点](./mcp-endpoint-integration.md)<br/>
+6、[如何开启声纹识别](./voiceprint-integration.md)<br/>
+7、[新闻插件源配置指南](./newsnow_plugin_config.md)<br/>
+8、[天气插件使用指南](./weather-integration.md)<br/>
+## 语音克隆、本地语音部署相关教程
+1、[如何在智控台克隆音色](./huoshan-streamTTS-voice-cloning.md)<br/>
+2、[如何部署集成index-tts本地语音](./index-stream-integration.md)<br/>
+3、[如何部署集成fish-speech本地语音](./fish-speech-integration.md)<br/>
+4、[如何部署集成PaddleSpeech本地语音](./paddlespeech-deploy.md)<br/>
+## 性能测试教程
+1、[各组件速度测试指南](./performance_tester.md)<br/>
+2、[定期公开测试结果](https://github.com/xinnan-tech/xiaozhi-performance-research)<br/>

docs/FAQ.md

@@ -0,0 +1,104 @@
+# 常见问题 ❓
+
+### 1、为什么我说的话，小智识别出来很多韩文、日文、英文？🇰🇷
+
+建议：检查一下`models/SenseVoiceSmall`是否已经有`model.pt`
+文件，如果没有就要下载，查看这里[下载语音识别模型文件](Deployment.md#模型文件)
+
+### 2、为什么会出现"TTS 任务出错 文件不存在"？📁
+
+建议：检查一下是否正确使用`conda` 安装了`libopus`和`ffmpeg`库。
+
+如果没有安装，就安装
+
+```
+conda install conda-forge::libopus
+conda install conda-forge::ffmpeg
+```
+
+### 3、TTS 经常失败，经常超时 ⏰
+
+建议：如果 `EdgeTTS` 经常失败，请先检查是否使用了代理（梯子）。如果使用了，请尝试关闭代理后再试；  
+如果用的是火山引擎的豆包 TTS，经常失败时建议使用付费版本，因为测试版本仅支持 2 个并发。
+
+### 4、使用Wifi能连接自建服务器，但是4G模式却接不上 🔐
+
+原因：虾哥的固件，4G模式需要使用安全连接。
+
+解决方法：目前有两种方法可以解决。任选一种：
+
+1、改代码。参考这个视频解决 https://www.bilibili.com/video/BV18MfTYoE85
+
+2、使用nginx配置ssl证书。参考教程 https://icnt94i5ctj4.feishu.cn/docx/GnYOdMNJOoRCljx1ctecsj9cnRe
+
+### 5、如何提高小智对话响应速度？ ⚡
+
+本项目默认配置为低成本方案，建议初学者先使用默认免费模型，解决"跑得动"的问题，再优化"跑得快"。  
+如需提升响应速度，可尝试更换各组件。自`0.5.2`版本起，项目支持流式配置，相比早期版本，响应速度提升约`2.5秒`，显著改善用户体验。
+
+| 模块名称 | 入门全免费设置 | 流式配置 |
+|:---:|:---:|:---:|
+| ASR(语音识别) | FunASR(本地) | 👍XunfeiStreamASR(讯飞流式) |
+| LLM(大模型) | glm-4-flash(智谱) | 👍qwen-flash(阿里百炼) |
+| VLLM(视觉大模型) | glm-4v-flash(智谱) | 👍qwen3.5-flash(阿里百炼) |
+| TTS(语音合成) | EdgeTTS(微软) | 👍HuoshanDoubleStreamTTS(火山流式) |
+| Intent(意图识别) | function_call(函数调用) | function_call(函数调用) |
+| Memory(记忆功能) | mem_local_short(本地短期记忆） | mem_local_short（本地短期记忆） |
+
+如果您关心各组件的耗时，请查阅[小智各组件性能测试报告](https://github.com/xinnan-tech/xiaozhi-performance-research)，可按报告中的测试方法在您的环境中实际测试。
+
+### 6、我说话很慢，停顿时小智老是抢话 🗣️
+
+建议：在配置文件中找到如下部分，将 `min_silence_duration_ms` 的值调大（例如改为 `1000`）：
+
+```yaml
+VAD:
+  SileroVAD:
+    threshold: 0.5
+    model_dir: models/snakers4_silero-vad
+    min_silence_duration_ms: 700  # 如果说话停顿较长，可将此值调大
+```
+
+### 7、部署相关教程
+1、[如何进行最简化部署](./Deployment.md)<br/>
+2、[如何进行全模块部署](./Deployment_all.md)<br/>
+3、[如何部署MQTT网关开启MQTT+UDP协议](./mqtt-gateway-integration.md)<br/>
+4、[如何自动拉取本项目最新代码自动编译和启动](./dev-ops-integration.md)<br/>
+5、[如何与Nginx集成](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)<br/>
+
+### 8、编译固件相关教程
+1、[如何自己编译小智固件](./firmware-build.md)<br/>
+2、[如何基于虾哥编译好的固件修改OTA地址](./firmware-setting.md)<br/>
+3、[单模块部署如何配置固件OTA自动升级](./ota-upgrade-guide.md)<br/>
+
+### 9、拓展相关教程
+1、[如何开启手机号码注册智控台](./ali-sms-integration.md)<br/>
+2、[如何集成HomeAssistant实现智能家居控制](./homeassistant-integration.md)<br/>
+3、[如何开启视觉模型实现拍照识物](./mcp-vision-integration.md)<br/>
+4、[如何部署MCP接入点](./mcp-endpoint-enable.md)<br/>
+5、[如何接入MCP接入点](./mcp-endpoint-integration.md)<br/>
+6、[MCP方法如何获取设备信息](./mcp-get-device-info.md)<br/>
+7、[如何开启声纹识别](./voiceprint-integration.md)<br/>
+8、[新闻插件源配置指南](./newsnow_plugin_config.md)<br/>
+9、[知识库ragflow集成指南](./ragflow-integration.md)<br/>
+10、[如何部署上下文源](./context-provider-integration.md)<br/>
+11、[如何集成PowerMem智能记忆](./powermem-integration.md)<br/>
+12、[如何配置天气插件查询天气](./weather-integration.md)<br/>
+
+### 10、数字人相关教程
+1、[数字人digital-human启动方法](./digital-human-wakeword.md)<br/>
+2、[如何在N100迷你主机上部署数字人digital-human](./all-in-one-digital-human-setup.md)<br/>
+
+### 11、语音克隆、本地语音部署相关教程
+1、[如何在智控台克隆音色](./huoshan-streamTTS-voice-cloning.md)<br/>
+2、[如何部署集成index-tts本地语音](./index-stream-integration.md)<br/>
+3、[如何部署集成fish-speech本地语音](./fish-speech-integration.md)<br/>
+4、[如何部署集成PaddleSpeech本地语音](./paddlespeech-deploy.md)<br/>
+
+### 12、性能测试教程
+1、[各组件速度测试指南](./performance_tester.md)<br/>
+2、[定期公开测试结果](https://github.com/xinnan-tech/xiaozhi-performance-research)<br/>
+
+### 13、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。

docs/ali-sms-integration.md

@@ -0,0 +1,44 @@
+# 阿里云短信集成指南
+
+登录阿里云控制台，进入“短信服务”页面：https://dysms.console.aliyun.com/overview
+
+## 第一步 添加签名
+![步骤](images/alisms/sms-01.png)
+![步骤](images/alisms/sms-02.png)
+
+以上步骤，会得到签名，请把它写入到智控台参数，`aliyun.sms.sign_name`
+
+## 第二步 添加模版
+![步骤](images/alisms/sms-11.png)
+
+以上步骤，会得到模版code，请把它写入到智控台参数，`aliyun.sms.sms_code_template_code`
+
+注意，签名要等7个工作日，等运营商报备成功后才能发送成功。
+
+注意，签名要等7个工作日，等运营商报备成功后才能发送成功。
+
+注意，签名要等7个工作日，等运营商报备成功后才能发送成功。
+
+可以等报备成功后，再继续往下操作。
+
+## 第三步 创建短信账户和开通权限
+
+登录阿里云控制台，进入“访问控制”页面：https://ram.console.aliyun.com/overview?activeTab=overview
+
+![步骤](images/alisms/sms-21.png)
+![步骤](images/alisms/sms-22.png)
+![步骤](images/alisms/sms-23.png)
+![步骤](images/alisms/sms-24.png)
+![步骤](images/alisms/sms-25.png)
+
+以上步骤，会得到access_key_id和access_key_secret，请把它写入到智控台参数，`aliyun.sms.access_key_id`、`aliyun.sms.access_key_secret`
+## 第四步 启动手机注册功能
+
+1、正常来说，以上信息都填完后，会有这个效果，如果没有，可能缺少了某个步骤
+
+![步骤](images/alisms/sms-31.png)
+
+2、开启允许非管理员用户可注册，将参数`server.allow_user_register`设置成`true`
+
+3、开启手机注册功能，将参数`server.enable_mobile_register`设置成`true`
+![步骤](images/alisms/sms-32.png)

docs/all-in-one-digital-human-setup.md

@@ -0,0 +1,442 @@
+# 一体机数字人配置指南
+
+本项目用于在 x86 架构设备（如迷你主机、工控机、普通电脑等）上部署一套完整的数字人展示系统，实现以下功能：
+- 开机自动进入 Kiosk 全屏浏览器，展示指定网页
+- 后台运行唤醒词检测服务，支持语音交互
+
+> **说明**：本文档以 **Intel N100 迷你主机（天虹 QN10-100B4）** 为例进行部署演示，其他 x86 设备可参考调整（注意网络配置和声卡设备差异）。
+
+## 适用环境
+
+| 项目 | 说明 |
+|------|------|
+| 示例硬件 | 天虹 QN10-100B4（Intel N100） |
+| 操作系统 | Ubuntu 24.04 LTS (Noble Numbat) |
+| 示例用户 | xz（请根据实际情况替换） |
+| 网络 | Wi-Fi 连接，固定 IP（可按需改为有线） |
+
+## 部署流程
+
+1. 系统初始化（换源、连网）
+2. 安装图形组件与 Kiosk 浏览器
+3. 配置自动登录与图形界面
+4. 部署唤醒词服务（Python 环境 + 麦克风）
+5. 优化开机速度与隐藏启动信息
+
+---
+
+
+### 系统初始化（换源、连网）
+
+```
+sudo cp /etc/apt/sources.list /etc/apt/sources.list.bak
+
+sudo tee /etc/apt/sources.list > /dev/null <<EOF
+deb http://mirrors.aliyun.com/ubuntu/ noble main restricted universe multiverse
+# deb-src http://mirrors.aliyun.com/ubuntu/ noble main restricted universe multiverse
+
+deb http://mirrors.aliyun.com/ubuntu/ noble-security main restricted universe multiverse
+# deb-src http://mirrors.aliyun.com/ubuntu/ noble-security main restricted universe multiverse
+
+deb http://mirrors.aliyun.com/ubuntu/ noble-updates main restricted universe multiverse
+# deb-src http://mirrors.aliyun.com/ubuntu/ noble-updates main restricted universe multiverse
+
+deb http://mirrors.aliyun.com/ubuntu/ noble-proposed main restricted universe multiverse
+# deb-src http://mirrors.aliyun.com/ubuntu/ noble-proposed main restricted universe multiverse
+
+deb http://mirrors.aliyun.com/ubuntu/ noble-backports main restricted universe multiverse
+# deb-src http://mirrors.aliyun.com/ubuntu/ noble-backports main restricted universe multiverse
+EOF
+
+echo 'Acquire::ForceIPv4 "true";' | sudo tee /etc/apt/apt.conf.d/99force-ipv4
+```
+
+
+安装网络管理工具（若已存在可忽略）
+
+Bash
+
+```
+sudo apt update
+sudo apt install network-manager -y
+sudo systemctl start NetworkManager
+sudo systemctl enable NetworkManager
+```
+
+
+设置wifi密码，固定ip
+
+> **提醒**：以下命令中的 Wi-Fi 名称、密码、IP 地址均为示例，请务必替换为你自己的实际信息。
+
+Bash
+
+```
+sudo nmcli device wifi connect "MERCURY_1812" password "12345678"
+
+sudo nmcli connection modify "MERCURY_1812" ipv4.addresses "192.168.0.86/24" ipv4.gateway "192.168.0.1" ipv4.dns "8.8.8.8,114.114.114.114" ipv4.method "manual"
+
+sudo nmcli connection up "MERCURY_1812"
+```
+
+
+### 第一步：安装核心图形组件与浏览器
+
+这里我们坚持“极简主义”，坚决不装多余的桌面环境（如 GNOME/KDE），只装底层驱动、最轻量的窗口管理器（Openbox）、隐藏鼠标工具以及 Chromium 浏览器。
+
+Bash
+
+```
+sudo timedatectl set-timezone Asia/Shanghai
+
+
+sudo apt install net-tools vim fonts-wqy-microhei fonts-wqy-zenhei alsa-utils pulseaudio -y
+sudo apt install --no-install-recommends xserver-xorg x11-xserver-utils xinit openbox unclutter -y
+
+wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
+sudo apt install ./google-chrome-stable_current_amd64.deb -y
+rm google-chrome-stable_current_amd64.deb
+
+sudo apt purge snapd -y
+
+```
+
+### 第二步：配置 TTY1 开机免密自动登录
+
+为了避免手动输入账号密码的尴尬，我们通过修改 systemd 服务，让系统一开机就自动以 `xz` 的身份登录。这里使用一键写入命令，彻底避开由于 `nano` 或 `vi` 操作不当导致的保存失败问题。
+
+**1. 创建配置目录：**
+
+Bash
+
+```
+sudo mkdir -p /etc/systemd/system/getty@tty1.service.d/
+```
+
+**2. 写入自动登录规则：**
+
+Bash
+
+```
+echo -e "[Service]\nExecStart=\nExecStart=-/sbin/agetty --autologin xz --noclear %I \$TERM" | sudo tee /etc/systemd/system/getty@tty1.service.d/override.conf
+```
+
+**3. 重载服务并设置默认启动目标：**
+
+Bash
+
+```
+sudo systemctl daemon-reload
+sudo systemctl set-default multi-user.target
+```
+
+### 第三步：配置登录后自动启动图形界面
+
+系统自动登录后默认停留在黑底白字的命令行，我们需要配置脚本，让它一旦登录立马启动 X11 图形环境。
+
+**1. 触发 `startx` 的启动逻辑：**
+
+直接将触发代码追加写入你的个人环境配置文件中：
+
+Bash
+
+```
+cat << 'EOF' >> ~/.bash_profile
+if [ -z "$DISPLAY" ] && [ "$(fgconsole)" -eq 1 ]; then
+    exec startx
+fi
+EOF
+```
+
+**2. 告诉 `startx` 去启动 Openbox：**
+
+Bash
+
+```
+echo "exec openbox-session" > ~/.xinitrc
+```
+
+### 第四步：配置“铜墙铁壁”的 Openbox 与浏览器
+
+这是最核心的一步：关闭屏幕休眠、隐藏鼠标、全屏锁定浏览器，并写一个“死循环”保证浏览器被意外关闭后也能瞬间复活。
+
+**1. 创建 Openbox 配置目录：**
+
+Bash
+
+```
+mkdir -p ~/.config/openbox
+```
+
+**2. 写入自启动脚本 (`autostart`)：**
+
+复制以下整段代码并回车（这会自动把所有保护规则写进文件里）：
+
+Bash
+
+```
+cat << 'EOF' > ~/.config/openbox/autostart
+# 关闭屏幕保护
+xset -dpms
+xset s noblank
+xset s off
+
+# 隐藏鼠标
+unclutter -idle 0.1 -root &
+
+# 死循环启动 Chromium（崩溃或被关也能秒重启）
+while true; do
+    google-chrome \
+        --kiosk \
+        --no-first-run \
+        --no-default-browser-check \
+        --disable-infobars \
+        --disable-session-crashed-bubble \
+        --disable-translate \
+        --disable-external-intent-requests \
+        --autoplay-policy=no-user-gesture-required \
+        --use-fake-ui-for-media-stream \
+        "https://www.douyin.com"
+    sleep 2
+done &
+EOF
+```
+
+**3. 屏蔽 `Alt+F4` 退出快捷键：**
+
+为了防止别人插上键盘强行关掉窗口，我们把 Openbox 默认的系统快捷键干掉。
+
+Bash
+
+```
+cp /etc/xdg/openbox/rc.xml ~/.config/openbox/
+sed -i '/<keybind key="A-F4">/,/<\/keybind>/d' ~/.config/openbox/rc.xml
+```
+
+### 第五步：重启验收成果
+
+如果拔掉网线或不需要等待所有网络上线，可禁用网络等待服务，避免开机卡顿
+
+Bash
+
+```
+sudo systemctl mask systemd-networkd-wait-online.service
+sudo systemctl mask NetworkManager-wait-online.service
+```
+
+隐藏开机信息（GRUB）
+
+Bash
+
+```
+sudo sed -i 's/GRUB_CMDLINE_LINUX_DEFAULT=.*/GRUB_CMDLINE_LINUX_DEFAULT="quiet loglevel=3 systemd.show_status=false vt.global_cursor_default=0"/g' /etc/default/grub
+
+echo 'GRUB_TIMEOUT_STYLE="hidden"' | sudo tee -a /etc/default/grub
+echo 'GRUB_RECORDFAIL_TIMEOUT=0' | sudo tee -a /etc/default/grub
+
+sudo update-grub
+```
+
+声音设置成100%，然后 重启：
+
+Bash
+
+```
+amixer -q sset Master 100% unmute
+sudo reboot
+```
+
+### 部署唤醒词服务
+
+在一体机上部署唤醒词检测服务，需要安装 Python 环境、上传项目文件、配置 Camera 麦克风和开机自启。
+
+#### 1. 安装 Miniconda
+
+```bash
+wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+bash Miniconda3-latest-Linux-x86_64.sh -b -p $HOME/miniconda3
+~/miniconda3/bin/conda init bash
+source ~/.bashrc
+rm Miniconda3-latest-Linux-x86_64.sh
+```
+
+
+确保登录时自动进入conda环境
+
+```bash
+if ! grep -q '.bashrc' ~/.bash_profile; then
+    cat << 'EOF' >> ~/.bash_profile
+
+if [ -f ~/.bashrc ]; then
+    . ~/.bashrc
+fi
+EOF
+fi
+```
+
+
+#### 2. 创建 Python 虚拟环境
+
+```bash
+conda create -n test python=3.10 -y
+conda activate test
+```
+
+若出现 Terms of Service have not been accepted 错误，执行：
+
+```bash
+conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main
+conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r
+```
+
+#### 3. 上传项目文件
+
+将开发机上的 `main/digital-human/` 整个目录上传到一体机的 `~/digital-human/` 目录：
+
+```bash
+# 在开发机上执行（将 <一体机IP> 替换为实际 IP）
+scp -r main/digital-human/ xz@<一体机IP>:~/digital-human/
+```
+
+#### 4. 安装系统依赖
+
+唤醒词服务需要音频采集库和 ALSA PulseAudio 插件：
+
+```bash
+sudo apt install libportaudio2 portaudio19-dev libasound2-plugins -y
+```
+
+#### 5. 安装 Python 依赖
+
+```bash
+cd ~/digital-human/wakeword_runtime
+pip install numpy
+pip install -r requirements.txt
+```
+
+#### 6. 下载唤醒词模型
+
+模型文件不包含在项目中，需要单独下载配置，详见 [docs/digital-human-wakeword.md](digital-human-wakeword.md) 中的“模型下载”章节。
+
+#### 7. 修改 Openbox 自启动脚本
+
+需要在 autostart 中加上 PulseAudio 和 Camera 麦克风配置，并将 Chrome 地址改为测试页面。
+
+先确认 Camera 麦克风在 PulseAudio 中的设备名：
+
+```bash
+pulseaudio --start
+pactl list sources short
+```
+
+找到包含 `USB_Camera` 的那一行，记下完整名称，例如：
+
+```
+alsa_input.usb-SN0002_2K_USB_Camera_46435000_P030D00_SN0002-02.mono-fallback
+```
+
+然后用完整内容覆盖 autostart（将 `TARGET_MIC` 替换为你的实际设备名）：
+
+```bash
+cat << 'EOF' > ~/.config/openbox/autostart
+# 1. 启动声音服务并稍作等待
+pulseaudio --start
+sleep 1
+
+# 2. 锁定 Camera 的麦克风（请替换为你的实际设备名）
+TARGET_MIC="alsa_input.usb-SN0002_2K_USB_Camera_46435000_P030D00_SN0002-02.mono-fallback"
+
+# 3. 设为系统默认麦克风
+pactl set-default-source "$TARGET_MIC"
+
+# 4. 解除静音
+pactl set-source-mute "$TARGET_MIC" 0
+
+# 5. 音量拉到 100%
+pactl set-source-volume "$TARGET_MIC" 100%
+
+# --- 极简桌面与浏览器环境配置 ---
+
+# 关闭屏幕保护
+xset -dpms
+xset s noblank
+xset s off
+
+# 隐藏鼠标
+unclutter -idle 0.1 -root &
+
+# 死循环启动浏览器（崩溃或被关也能秒重启）
+while true; do
+    google-chrome \
+        --kiosk \
+        --no-first-run \
+        --no-default-browser-check \
+        --disable-infobars \
+        --disable-session-crashed-bubble \
+        --disable-translate \
+        --disable-external-intent-requests \
+        --autoplay-policy=no-user-gesture-required \
+        --use-fake-ui-for-media-stream \
+        "http://127.0.0.1:8006/index.html"
+    sleep 2
+done &
+EOF
+```
+
+#### 8. 配置唤醒词服务开机自启
+
+创建 systemd 服务文件，让唤醒词服务开机自动运行。
+
+先确认当前用户的 UID：
+
+```bash
+id -u $(whoami)
+```
+
+然后用查到的 UID 替换下面 `1000`（通常第一个用户就是 1000）：
+
+```bash
+sudo tee /etc/systemd/system/digital-human.service << 'EOF'
+[Unit]
+Description=Digital Human Runtime
+After=network.target sound.target
+
+[Service]
+Type=simple
+User=xz
+Environment=XDG_RUNTIME_DIR=/run/user/1000
+Environment=PULSE_SERVER=unix:/run/user/1000/pulse/native
+WorkingDirectory=/home/xz/digital-human
+ExecStartPre=/bin/sleep 10
+ExecStart=/home/xz/miniconda3/envs/test/bin/python start.py
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target
+EOF
+```
+
+> **重要说明**：
+> - `User=xz` — 替换为你的实际用户名
+> - `/run/user/1000` — 替换为你实际的 UID
+> - `WorkingDirectory` 和 `ExecStart` 中的路径 — 替换为你的实际部署路径
+> - `Environment` 中的 PulseAudio 环境变量**必须保留**，否则唤醒词服务和浏览器无法同时使用 Camera 麦克风
+
+启用并启动服务：
+
+```bash
+sudo systemctl daemon-reload
+sudo systemctl enable digital-human
+sudo systemctl start digital-human
+```
+
+#### 9. 常用服务管理命令
+
+```bash
+sudo systemctl start digital-human     # 立即启动
+sudo systemctl stop digital-human      # 停止
+sudo systemctl restart digital-human   # 重启
+sudo systemctl status digital-human    # 查看状态
+journalctl -u digital-human -f         # 查看实时日志
+```
+

docs/context-provider-integration.md

@@ -0,0 +1,224 @@
+# 上下文源使用教程
+
+## 概述
+
+`上下文源`，就是为小智系统提示词的上下文添加【数据源】。
+
+`上下文源` 在小智在唤醒那一刻，获取外部系统的数据，并将其动态注入到大模型的系统提示词（System Prompt）中。
+让其做到唤醒时感知世界某个事物的状态。
+
+它和MCP、记忆有本质的区别：`上下文源`是强制让小智感知世界的数据；`记忆(Mem)`是让他知道之前聊了什么内容；`MCP(functionc all)`是当需要调用某项能力/知识的时候使用调用。
+
+通过这个功能，在小智唤醒的一刹那，“感知”到：
+- 人体健康传感器状态（体温、血压、血氧状态等）
+- 业务系统的实时数据（服务器负载、待办数据、股票信息等）
+- 任何可以通过 HTTP API 获取的文本信息
+
+**注意**：该功能只是方便小智在唤醒的时候感知事物的状态，而如果想要小智唤醒后实时获取事物的状态，建议在此功能上再结合MCP工具的调用。
+
+## 工作原理
+
+1. **配置源**：用户配置一个或多个 HTTP API 地址。
+2. **触发请求**：当系统构建 Prompt 时，如果发现模板中包含 `{{ dynamic_context }}` 占位符，会请求所有配置的 API。
+3. **自动注入**：系统会自动将 API 返回的数据格式化为 Markdown 列表，替换 `{{ dynamic_context }}` 占位符。
+
+## 接口规范
+
+为了让小智正确解析数据，您的 API 需要满足以下规范：
+
+- **请求方式**：`GET`
+- **请求头**：系统会自动添加 `device-id` 字段到 Request Header。
+- **响应格式**：必须返回 JSON 格式，且包含 `code` 和 `data` 字段。
+
+### 响应示例
+
+**情况 1：返回键值对**
+```json
+{
+  "code": 0,
+  "msg": "success",
+  "data": {
+    "客厅温度": "26℃",
+    "客厅湿度": "45%",
+    "大门状态": "已关闭"
+  }
+}
+```
+*注入效果：*
+```markdown
+<context>
+- **客厅温度：** 26℃
+- **客厅湿度：** 45%
+- **大门状态：** 已关闭
+</context>
+```
+
+**情况 2：返回列表**
+```json
+{
+  "code": 0,
+  "data": [
+    "您有10个待办事项",
+    "当前汽车的行驶速度是100km每小时"
+  ]
+}
+```
+*注入效果：*
+```markdown
+<context>
+- 您有10个待办事项
+- 当前汽车的行驶速度是100km每小时
+</context>
+```
+
+## 配置指南
+
+### 方式 1：智控台配置（全模块部署）
+
+1. 登录智控台，进入**角色配置**页面。
+2. 找到**上下文源**配置项（点击“编辑源”按钮）。
+3. 点击**添加**，输入您的 API 地址。
+4. 如果 API 需要鉴权，可以在**请求头**部分添加 `Authorization` 或其他 Header。
+5. 保存配置。
+
+### 方式 2：配置文件配置（单模块部署）
+
+编辑 `xiaozhi-server/data/.config.yaml` 文件，添加 `context_providers` 配置段：
+
+```yaml
+# 上下文源配置
+context_providers:
+  - url: "http://api.example.com/data"
+    headers:
+      Authorization: "Bearer your-token"
+  - url: "http://another-api.com/data"
+```
+
+## 启用功能
+
+默认情况下，系统的提示词模板文件（`data/.agent-base-prompt.txt`）中已经预置了 `{{ dynamic_context }}` 占位符，您无需手动添加。
+
+**示例：**
+
+```markdown
+<context>
+【重要！以下信息已实时提供，无需调用工具查询，请直接使用：】
+- **设备ID：** {{device_id}}
+- **当前时间：** {{current_time}}
+...
+{{ dynamic_context }}
+</context>
+```
+
+**注意**：如果您不需要使用此功能，可以选择**不配置任何上下文源**，也可以从提示词模板文件中**删除** `{{ dynamic_context }}` 占位符。
+
+## 附录：Mock 测试服务示例
+
+为了方便您测试和开发，我们提供了一个简单的 Python Mock Server 脚本。您可以运行此脚本在本地模拟 API 接口。
+
+**mock_api_server.py**
+
+```python
+import http.server
+import socketserver
+import json
+from urllib.parse import urlparse, parse_qs
+
+# 设置端口号
+PORT = 8081
+
+class MockRequestHandler(http.server.SimpleHTTPRequestHandler):
+    def do_GET(self):
+        # 解析路径和参数
+        parsed_path = urlparse(self.path)
+        path = parsed_path.path
+        query = parse_qs(parsed_path.query)
+
+        response_data = {}
+        status_code = 200
+
+        print(f"收到请求: {path}, 参数: {query}")
+
+        # Case 1: 模拟健康数据 (返回字典 Dict)
+        # 路径参数风格: /health
+        # device_id 从 Header 获取
+        if path == "/health":
+            device_id = self.headers.get("device-id", "unknown_device")
+            print(f"device_id: {device_id}")
+            response_data = {
+                "code": 0,
+                "msg": "success",
+                "data": {
+                    "测试设备ID": device_id,
+                    "心率": "80 bpm",
+                    "血压": "120/80 mmHg",
+                    "状态": "良好"
+                }
+            }
+
+        # Case 2: 模拟新闻列表 (返回列表 List)
+        # 无参数: /news/list
+        elif path == "/news/list":
+            response_data = {
+                "code": 0,
+                "msg": "success",
+                "data": [
+                    "今日头条：Python 3.14 发布",
+                    "科技新闻：AI 助手改变生活",
+                    "本地新闻：明日有大雨，记得带伞"
+                ]
+            }
+
+        # Case 3: 模拟天气简报 (返回字符串 String)
+        # 无参数: /weather/simple
+        elif path == "/weather/simple":
+            response_data = {
+                "code": 0,
+                "msg": "success",
+                "data": "今日晴转多云，气温 20-25 度，空气质量优，适合出行。"
+            }
+
+        # Case 4: 模拟设备详情 (Query参数风格)
+        # 参数风格: /device/info
+        # device_id 从 Header 获取
+        elif path == "/device/info":
+            device_id = self.headers.get("device-id", "unknown_device")
+            response_data = {
+                "code": 0,
+                "msg": "success",
+                "data": {
+                    "查询方式": "Header参数",
+                    "设备ID": device_id,
+                    "电量": "85%",
+                    "固件": "v2.0.1"
+                }
+            }
+        
+        # Case 5: 404 Not Found
+        else:
+            status_code = 404
+            response_data = {"error": "接口不存在"}
+
+        # 发送响应
+        self.send_response(status_code)
+        self.send_header('Content-type', 'application/json; charset=utf-8')
+        self.end_headers()
+        self.wfile.write(json.dumps(response_data, ensure_ascii=False).encode('utf-8'))
+
+# 启动服务
+# 允许地址重用，防止快速重启报错
+socketserver.TCPServer.allow_reuse_address = True
+with socketserver.TCPServer(("", PORT), MockRequestHandler) as httpd:
+    print(f"==================================================")
+    print(f"Mock API Server 已启动: http://localhost:{PORT}")
+    print(f"可用接口列表:")
+    print(f"1. [字典] http://localhost:{PORT}/health")
+    print(f"2. [列表] http://localhost:{PORT}/news/list")
+    print(f"3. [文本] http://localhost:{PORT}/weather/simple")
+    print(f"4. [参数] http://localhost:{PORT}/device/info")
+    print(f"==================================================")
+    try:
+        httpd.serve_forever()
+    except KeyboardInterrupt:
+        print("\n服务已停止")
+```

docs/contributor_open_letter.md

@@ -0,0 +1,50 @@
+# 致开发者的公开信
+
+"春江水暖鸭先知，正是河豚欲上时！"
+
+亲爱的朋友，我是John，是一名普通公司里的Java程序员，今天，我怀着无比真挚的心情，向热爱AI技术与创新的你发出这封公开信。
+
+半年前我看到很多优秀的项目，比如`Dify`、`Chat2DB`等人工智能相关的项目，我在想，我要是能参与这些项目多好，可惜“报国无门，空打十年代码”。
+
+我是2025年初刷到虾哥团队的视频，我非常好奇他是怎么实现的，我想复刻他们的后端服务，打造一个低成本民用贾维斯。很可惜现在做的作品依然只是一个人工智障，它并发低、没有灵魂，响应很慢，bug很多。
+
+虾哥团队是我们学习的对象，我很想拥有像虾哥团队一样智能的小智后端服务。但是我也能理解虾哥不开源的决定。“一花独放不是春，百花齐放春满园”，人工智能遍地开花的时代，也许就在我们这代实现，我们可以用自己的双手，实现低成本民用贾维斯。我个人认为，他能实现的，我们也能实现，只是时间问题而已，我称之为“我们的取经之路”。
+
+那么这条取经之路，我们会遇到什么困难？我想应该不少于八十一难。这一路必然会出现各种妖怪，当然也有神仙暗中帮助我们，也有人加入取经队伍。
+
+以上内容，如果你觉得好笑。那我也觉得非常的幸运。我能够在你人生3万多天里博你笑五秒，也算是为你做了一次贡献。
+
+民用低成本贾维斯这个想法，会失败吗，我不知道，但是我们普通人的一生，这种失败不是很常见吗？
+
+未来，有一点是可以确定的，就一定会有人完全复刻虾哥团队的功能，实现民用低成本贾维斯。这个项目会是我们吗？
+
+期待与你携手前行，共创未来。
+
+John，2025.3.11，广州
+
+# 附 开发贡献指南
+## 项目目标
+
+1. **民用低成本贾维斯解决方案**  
+
+2. **智能联动周边硬件的解决方案**  
+
+## 加入我们
+
+我们热忱欢迎志同道合的朋友加入，共同为项目贡献力量。您可在[这个链接](https://github.com/users/xinnan-tech/projects/3)查看我们近期要实现的功能，功能列表中还没指派相关人员处理的，正是急需您的参与。参与方式如下：
+
+### 1、成为普通贡献者
+
+Fork 项目，提交 PR，由开发者审核后合入主分支。
+
+### 2、成为开发者
+
+当你累计提交 3 次有效 PR 后，可以联系群主申请成为开发者，群主将邀请你加入独立的开发者群，共同探讨项目未来。
+
+## 开发者开发流程
+
+1. **创建新分支**  
+   每个功能点请以新分支方式开发，分支名称应简洁明了，让人一眼看出所实现的功能，避免功能撞车。
+
+2. **提交 PR 审核**  
+   功能开发完成后，请在 GitHub 上提交 PR，由其他开发者审核，审核通过后合并入主分支。

docs/dev-ops-integration.md

@@ -0,0 +1,182 @@
+# 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。
+
+教程可参考B站博主`毕乐labs`发布的视频教程：[《开源小智服务器xiaozhi-server自动更新以及最新版本MCP接入点配置保姆教程》](https://www.bilibili.com/video/BV15H37zHE7Q)
+
+# 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
+```
+# 创建需要的目录
+mkdir -p /home/system/xiaozhi/xiaozhi-esp32-server/main/xiaozhi-server/data/
+
+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 $PID"
+fi
+
+nohup java -jar xiaozhi-esp32-api.jar --spring.profiles.active=dev &
+
+tail tail -f nohup.out
+```
+
+保存好后执行赋权命令
+```
+chmod 777 update_8002.sh
+```
+执行完后，继续往下
+
+## 4.3 自动编译运行Python项目
+在`/home/system/xiaozhi/`目录下，创建名字为`update_8000.sh`的文件，内容如下
+
+```
+cd /home/system/xiaozhi/xiaozhi-esp32-server
+git pull origin main
+
+# 查找占用8000端口的进程号
+PID=$(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
+# 初始化conda环境
+source ~/.bashrc
+conda activate xiaozhi-esp32-server
+pip install -r requirements.txt
+nohup python app.py >/dev/null &
+tail -f /home/system/xiaozhi/xiaozhi-esp32-server/main/xiaozhi-server/tmp/server.log
+```
+
+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
+
+```
+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
+
+
+# 后期想查看java日志，执行以下命令
+tail -f nohup.out
+# 后期想查看python日志，执行以下命令
+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)
+
+## 常见问题
+
+### 1、为什么没有见到8001端口？
+回答：8001是开发环境使用的，用于运行前端的端口。如果你是服务器部署，不建议使用`npm run serve`启动8001端口运行前端，而是像本教程一样编译成html文件，然后使用nginx来管理访问。
+
+### 2、每次更新需要更新手动SQL语句吗？
+回答：不需要，因为项目使用**Liquibase**管理数据库版本，会自动执行新的sql脚本。

docs/digital-human-wakeword.md

@@ -0,0 +1,220 @@
+# 数字人digital-human启动方法
+
+## 概述
+
+测试页面集成了基于 **Sherpa-ONNX** 的高精度语音唤醒功能，支持自定义唤醒词和实时检测。使用轻量级关键词检测模型，提供毫秒级响应速度。
+
+## 唤醒词模型
+
+### 模型下载（必需）
+
+**重要说明**: 项目不包含模型文件，需要提前下载配置。
+
+### 官方模型下载地址
+
+- **官方模型列表**: <https://csukuangfj.github.io/sherpa/onnx/kws/pretrained_models/index.html>
+- **推荐模型**: `sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01`
+
+### 下载和配置步骤
+
+#### 1. 下载模型包
+
+```bash
+# 方法1：直接下载（推荐）
+cd main/digital-human/wakeword_runtime/
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01.tar.bz2
+
+# 解压
+tar xvf sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01.tar.bz2
+
+# 方法2：使用ModelScope
+pip install modelscope
+python -c "
+from modelscope import snapshot_download
+snapshot_download('pkufool/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01', cache_dir='./models')
+"
+```
+
+#### 2. 配置模型文件
+
+模型包下载后包含以下文件：
+
+```
+sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01/
+├── encoder-epoch-12-avg-2-chunk-16-left-64.int8.onnx    # 速度优先
+├── encoder-epoch-12-avg-2-chunk-16-left-64.onnx
+├── encoder-epoch-99-avg-1-chunk-16-left-64.int8.onnx    # 速度优先
+├── encoder-epoch-99-avg-1-chunk-16-left-64.onnx         # 精度优先
+├── decoder-epoch-12-avg-2-chunk-16-left-64.onnx
+├── decoder-epoch-99-avg-1-chunk-16-left-64.onnx         # 精度优先
+├── joiner-epoch-12-avg-2-chunk-16-left-64.int8.onnx     # 速度优先
+├── joiner-epoch-12-avg-2-chunk-16-left-64.onnx
+├── joiner-epoch-99-avg-1-chunk-16-left-64.int8.onnx     # 速度优先
+├── joiner-epoch-99-avg-1-chunk-16-left-64.onnx          # 精度优先
+├── tokens.txt                    # Token映射表（必需）
+├── keywords_raw.txt              # 模型包里可能附带（可选，runtime 不依赖）
+├── keywords.txt                  # 现成的
+├── test_wavs/                    # 测试音频（可选）
+├── configuration.json            # 模型元信息（可选）
+└── README.md                     # 说明文档（可选）
+```
+
+#### 3. 选择配置方案
+
+**方案一：精度优先（推荐）**
+
+```bash
+cd sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01
+
+# 创建模型目录
+mkdir -p ../models
+
+# 复制精度优先的epoch-99 fp32三件套
+cp encoder-epoch-99-avg-1-chunk-16-left-64.onnx ../models/encoder.onnx
+cp decoder-epoch-99-avg-1-chunk-16-left-64.onnx ../models/decoder.onnx
+cp joiner-epoch-99-avg-1-chunk-16-left-64.onnx ../models/joiner.onnx
+
+# 复制配套文件
+cp tokens.txt ../models/tokens.txt
+# keywords_raw.txt 如果模型包里附带，可自行保留；runtime 不依赖它
+```
+
+**方案二：速度优先**
+
+```bash
+cd sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01
+
+# 创建模型目录
+mkdir -p ../models
+
+# 复制速度优先的epoch-99 int8三件套
+cp encoder-epoch-99-avg-1-chunk-16-left-64.int8.onnx ../models/encoder.onnx
+cp decoder-epoch-99-avg-1-chunk-16-left-64.onnx ../models/decoder.onnx
+cp joiner-epoch-99-avg-1-chunk-16-left-64.int8.onnx ../models/joiner.onnx
+
+# 复制配套文件
+cp tokens.txt ../models/tokens.txt
+```
+
+**注意事项**:
+
+- **不要混用 fp32 与 int8**：三个模型文件必须保持一致的精度
+- **优先选择 epoch-99**：比 epoch-12 训练更充分，精度更高
+- **必需文件**：`encoder.onnx` + `decoder.onnx` + `joiner.onnx` + `tokens.txt` + `keywords.txt`
+
+### 最终模型文件结构
+
+配置完成后，模型文件应放在 `wakeword_runtime/models/` 目录下，完整路径为 `main/digital-human/wakeword_runtime/models/`：
+
+```
+wakeword_runtime/models/
+├── encoder.onnx      # 编码器模型（重命名后）
+├── decoder.onnx      # 解码器模型（重命名后）
+├── joiner.onnx       # 连接器模型（重命名后）
+├── tokens.txt        # 拼音 Token 映射表（228行版本）
+├── keywords.txt      # 关键词配置文件（首次启动自动生成）
+└── keywords_raw.txt  # 可选，runtime 不依赖
+```
+
+## 启动方式
+
+在 `main/digital-human` 目录执行：
+
+```bash
+pip install -r wakeword_runtime/requirements.txt
+python start.py
+```
+
+启动后默认地址：
+
+- 页面地址：`http://127.0.0.1:8006/index.html`
+- 事件桥地址：`ws://127.0.0.1:8006/wakeword-ws`
+- 健康检查：`http://127.0.0.1:8006/health`
+
+停止方式：
+
+- 在运行终端按 `Ctrl+C`
+- 会同时停止静态页面服务、事件桥和唤醒词检测流程
+
+## 配置文件说明
+
+配置文件位于 [main/digital-human/wakeword_runtime/config.json](../main/digital-human/wakeword_runtime/config.json)。
+
+当前主要配置项：
+
+```json
+{
+  "wakeword": {
+    "enabled": true
+  },
+  "model_dir": "models",
+  "audio": {
+    "input_device": null,
+    "sample_rate": 16000,
+    "channels": 1
+  },
+  "detector": {
+    "num_threads": 4,
+    "provider": "cpu",
+    "max_active_paths": 2,
+    "keywords_score": 1.8,
+    "keywords_threshold": 0.1,
+    "num_trailing_blanks": 1,
+    "cooldown_seconds": 1.5
+  },
+  "logging": {
+    "level": "INFO",
+    "dir": "logs",
+    "file": "wakeword-runtime.log"
+  }
+}
+```
+
+各字段含义：
+
+| 参数 | 说明 |
+| --- | --- |
+| `wakeword.enabled` | 是否启用本地唤醒词检测 |
+| `model_dir` | 模型和词表所在目录 |
+| `audio.input_device` | 麦克风输入设备，默认使用系统默认设备 |
+| `audio.sample_rate` | 采样率，默认 `16000` |
+| `audio.channels` | 声道数，默认 `1` |
+| `detector.num_threads` | 检测器线程数 |
+| `detector.provider` | 推理 provider，当前通常为 `cpu` |
+| `detector.max_active_paths` | 搜索路径数 |
+| `detector.keywords_score` | 关键词增强分数 |
+| `detector.keywords_threshold` | 检测阈值 |
+| `detector.num_trailing_blanks` | 尾随空白数量 |
+| `detector.cooldown_seconds` | 连续触发冷却时间 |
+| `logging.level` | 日志等级 |
+| `logging.dir` | 日志目录 |
+| `logging.file` | 日志文件名 |
+
+## 推荐使用流程
+
+### 首次使用
+
+1. 准备 `models/` 目录下的模型文件和 `tokens.txt`
+2. 确认 `models/keywords.txt` 存在
+3. 在 `digital-human` 目录运行 `python start.py`
+4. 浏览器打开 `http://127.0.0.1:8006/index.html`
+5. 进入设置页检查“唤醒词”配置
+
+### 修改唤醒词
+
+1. 打开数字人页面设置
+2. 切到“唤醒词”页签
+3. 修改启用状态或唤醒词列表
+4. 点击“应用唤醒词”
+5. 根据提示决定是否立即重启
+
+### 禁用唤醒词
+
+1. 将“启用本地唤醒词”改成禁用
+2. 点击“应用唤醒词”
+3. 建议立即重启一次
+
+禁用后：
+
+- 页面与事件桥仍然可用
+- 唤醒词检测不会继续运行

docs/docker-build.md

@@ -8,39 +8,14 @@ sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin
 ```
 2、编译docker镜像
 ```
-# 普通编译
-docker build -t xiaozhi-esp32-server:local -f ./Dockerfile-pip .
-```
-3、测试本地镜像
-```
-docker stop xiaozhi-esp32-server
-docker rm xiaozhi-esp32-server
-
-docker run -d --name xiaozhi-esp32-server --restart always -p 8000:8000 -v $(pwd)/data/.config.yaml:/opt/xiaozhi-esp32-server/config.yaml xiaozhi-esp32-server:local
-
-docker logs -f xiaozhi-esp32-server
+#进入项目根目录
+# 编译server
+docker build -t xiaozhi-esp32-server:server_latest -f ./Dockerfile-server .
+# 编译web
+docker build -t xiaozhi-esp32-server:web_latest -f ./Dockerfile-web .
 
+# 编译完成后，可以使用docker-compose启动项目
+# docker-compose.yml你需要修改成自己编译的镜像版本
+cd main/xiaozhi-server
+docker compose up -d
 ```
-5、发布腾讯云镜像
-```
-# amd64
-docker tag xiaozhi-esp32-server:local ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest-amd64
-docker push ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest-amd64
-
-# arm64
-docker tag xiaozhi-esp32-server:local ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest-arm64
-docker push ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest-arm64
-
-# 推送最新版本
-docker manifest rm ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest
-docker manifest create ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest-amd64 ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest-arm64 --amend
-docker manifest inspect ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest
-docker manifest push ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest
-
-```
-6、运行线上镜像
-```
-cd /Users/hrz/myworkspace/docker-java-env/thirddata/
-docker run -d --name xiaozhi-esp32-server --restart always -p 8000:8000 -v $(pwd)/config.yaml:/opt/xiaozhi-esp32-server/config.yaml ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest
-docker logs -f xiaozhi-esp32-server
-```

docs/docker/nginx.conf

@@ -0,0 +1,53 @@
+user  root;
+worker_processes  4;
+
+events {
+    worker_connections  1024;
+}
+
+http {
+    include       mime.types;
+    default_type  application/octet-stream;
+    sendfile        on;
+    keepalive_timeout  300;
+    client_header_timeout 180s;
+    client_body_timeout 180s;
+    client_max_body_size 1024M;
+
+    gzip on;
+    gzip_buffers 32 4K;
+    gzip_comp_level 6;
+    gzip_min_length 100;
+    gzip_types application/javascript text/css text/xml image/jpeg image/gif image/png;
+    gzip_disable "MSIE [1-6]\.";
+    gzip_vary on;
+
+    server {
+        # 无域名访问，就用localhost
+        server_name localhost;
+        # 80端口
+        listen  8002;
+
+        # 转发到编译后到web目录
+        location / {
+			root /usr/share/nginx/html;
+			try_files $uri $uri/ /index.html;
+		}
+
+        # 转发到manager-api
+        location /xiaozhi/ {
+            proxy_pass http://127.0.0.1:8003;
+            proxy_set_header   Host   $host;
+            proxy_cookie_path /manager/ /;
+            proxy_set_header   Referer $http_referer;
+            proxy_set_header   Cookie $http_cookie;
+
+            proxy_connect_timeout 15;
+            proxy_send_timeout 15;
+            proxy_read_timeout 15;
+
+            proxy_set_header   X-Real-IP  $remote_addr;
+            proxy_set_header   X-Forwarded-For $proxy_add_x_forwarded_for;
+        }
+    }
+}

docs/docker/start.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+# 启动Java后端（docker内监听8003端口）
+java -jar /app/xiaozhi-esp32-api.jar \
+  --server.port=8003 \
+  --spring.datasource.druid.url=${SPRING_DATASOURCE_DRUID_URL} \
+  --spring.datasource.druid.username=${SPRING_DATASOURCE_DRUID_USERNAME} \
+  --spring.datasource.druid.password=${SPRING_DATASOURCE_DRUID_PASSWORD} \
+  --spring.data.redis.host=${SPRING_DATA_REDIS_HOST} \
+  --spring.data.redis.password=${SPRING_DATA_REDIS_PASSWORD} \
+  --spring.data.redis.port=${SPRING_DATA_REDIS_PORT} &
+
+# 启动Nginx（前台运行保持容器存活）
+nginx -g 'daemon off;'

docs/firmware-build.md

@@ -1,40 +1,81 @@
-# 编译esp32固件
+# esp32固件编译
 
-1. 下载`xiaozhi-esp32`
-   项目，按照这个教程配置项目环境[《Windows搭建 ESP IDF 5.3.2开发环境以及编译小智》](https://icnynnzcwou8.feishu.cn/wiki/JEYDwTTALi5s2zkGlFGcDiRknXf)
+## 第1步 准备你的ota地址
 
-2. 打开`xiaozhi-esp32/main/Kconfig.projbuild`文件，找到`WEBSOCKET_URL`的`default`的内容，把`wss://api.tenclass.net`
-   改成你自己的地址，例如，我的接口地址是`ws://192.168.1.25:8000`，就把内容改成这个。
+如果你，使用的是本项目0.3.12版本，不管是简单Server部署还是全模块部署，都会有ota地址。
+
+由于简单Server部署和全模块部署的OTA地址设置方式不一样，请你选择下面的具体方式：
+
+### 如果你用的是简单Server部署
+此刻，请你用浏览器打开你的ota地址，例如我的ota地址
+```
+http://192.168.1.25:8003/xiaozhi/ota/
+```
+如果显示“OTA接口运行正常，向设备发送的websocket地址是：ws://xxx:8000/xiaozhi/v1/
+
+你可以启动`digital-human`模块后打开`index.html`测试一下，是否能连上ota页面输出的websocket地址。
+
+如果访问不到，你需要到配置文件`.config.yaml`里修改`server.websocket`的地址，重启后再重新测试，直到`index.html`能正常访问。
+
+成功后，请往下进行第2步
+
+### 如果你用的是全模块部署
+此刻，请你用浏览器打开你的ota地址，例如我的ota地址
+```
+http://192.168.1.25:8002/xiaozhi/ota/
+```
+
+如果显示“OTA接口运行正常，websocket集群数量：X”。那就往下进行2步。
+
+如果显示“OTA接口运行不正常”，大概是你还没在`智控台`配置`Websocket`地址。那就：
+
+- 1、使用超级管理员登录智控台
+
+- 2、顶部菜单点击`参数管理`
+
+- 3、在列表中找到`server.websocket`项目，输入你的`Websocket`地址。例如我的就是
+
+```
+ws://192.168.1.25:8000/xiaozhi/v1/
+```
+
+配置完后，再使用浏览器刷新你的ota接口地址，看看是不是正常了。如果还不正常就，就再次确认一下Websocket是否正常启动，是否配置了Websocket地址。
+
+## 第2步 配置环境
+先按照这个教程配置项目环境[《Windows搭建 ESP IDF 5.3.2开发环境以及编译小智》](https://icnynnzcwou8.feishu.cn/wiki/JEYDwTTALi5s2zkGlFGcDiRknXf)
+
+## 第3步 打开配置文件
+配置好编译环境后，下载虾哥iaozhi-esp32项目源码，
+
+从这里下载虾哥[xiaozhi-esp32项目源码](https://github.com/78/xiaozhi-esp32)。
+
+下载后，打开`xiaozhi-esp32/main/Kconfig.projbuild`文件。
+
+## 第4步 修改OTA地址
+
+找到`OTA_URL`的`default`的内容，把`https://api.tenclass.net/xiaozhi/ota/`
+   改成你自己的地址，例如，我的接口地址是`http://192.168.1.25:8002/xiaozhi/ota/`，就把内容改成这个。
 
 修改前：
-
 ```
-config WEBSOCKET_URL
-    depends on CONNECTION_TYPE_WEBSOCKET
-    string "Websocket URL"
-    default "wss://api.tenclass.net/xiaozhi/v1/"
+config OTA_URL
+    string "Default OTA URL"
+    default "https://api.tenclass.net/xiaozhi/ota/"
     help
-        Communication with the server through websocket after wake up.
+        The application will access this URL to check for new firmwares and server address.
 ```
-
-修改后(示例)：
-
+修改后：
 ```
-config WEBSOCKET_URL
-    depends on CONNECTION_TYPE_WEBSOCKET
-    string "Websocket URL"
-    default "ws://192.168.1.25:8000/xiaozhi/v1/"
+config OTA_URL
+    string "Default OTA URL"
+    default "http://192.168.1.25:8002/xiaozhi/ota/"
     help
-        Communication with the server through websocket after wake up.
+        The application will access this URL to check for new firmwares and server address.
 ```
 
-注意：你的地址是`ws://`开头，不是`wss://`开头，一定不要写错了。
+## 第4步 设置编译参数
 
-注意：你的地址是`ws://`开头，不是`wss://`开头，一定不要写错了。
-
-注意：你的地址是`ws://`开头，不是`wss://`开头，一定不要写错了。
-
-3. 设置编译参数
+设置编译参数
 
 ```
 # 终端命令行进入xiaozhi-esp32的根目录
@@ -45,40 +86,29 @@ idf.py set-target esp32s3
 idf.py menuconfig
 ```
 
-![图片](images/build_setting01.png)
-
-进入菜单配置后，再进入`Xiaozhi Assistant`，将`CONNECTION_TYPE`设置为`Websocket`
-回退到主菜单，再进入`Xiaozhi Assistant`，将`BOARD_TYPE`设置你板子的具体型号
+进入菜单配置后，再进入`Xiaozhi Assistant`，将`BOARD_TYPE`设置你板子的具体型号
 保存退出，回到终端命令行。
 
-![图片](images/build_setting02.png)
-
-4. 编译固件
+## 第5步 编译固件
 
 ```
 idf.py build
 ```
 
-如果是vscode安装的idf可以使用`F1`或者`ctrl+shift+p`,输入idf然后直接选择进行编译
-
-还可以直接进行烧录不用接下来的操作
-
-<img src="./images/vscode_idf.png" width="500px"/>
-
-5. 打包bin固件
+## 第6步 打包bin固件
 
 ```
 cd scripts
 python release.py
 ```
 
-编译成功后，会在项目根目录下的`build`目录下生成固件文件`merged-binary.bin`。
+上面的打包命令执行完成后，会在项目根目录下的`build`目录下生成固件文件`merged-binary.bin`。
 这个`merged-binary.bin`就是要烧录到硬件上的固件文件。
 
 注意：如果执行到第二命令后，报了“zip”相关的错误，请忽略这个错误，只要`build`目录下生成固件文件`merged-binary.bin`
 ，对你没有太大影响，请继续。
 
-6. 烧录固件
+## 第7步 烧录固件
    将esp32设备连接电脑，使用chrome浏览器，打开以下网址
 
 ```
@@ -87,3 +117,22 @@ https://espressif.github.io/esp-launchpad/
 
 打开这个教程，[Flash工具/Web端烧录固件（无IDF开发环境）](https://ccnphfhqs21z.feishu.cn/wiki/Zpz4wXBtdimBrLk25WdcXzxcnNS)。
 翻到：`方式二：ESP-Launchpad 浏览器WEB端烧录`，从`3. 烧录固件/下载到开发板`开始，按照教程操作。
+
+烧录成功且联网成功后，通过唤醒词唤醒小智，留意server端输出的控制台信息。
+
+## 常见问题
+以下是一些常见问题，供参考：
+
+[1、为什么我说的话，小智识别出来很多韩文、日文、英文](./FAQ.md)
+
+[2、为什么会出现“TTS 任务出错 文件不存在”？](./FAQ.md)
+
+[3、TTS 经常失败，经常超时](./FAQ.md)
+
+[4、使用Wifi能连接自建服务器，但是4G模式却接不上](./FAQ.md)
+
+[5、如何提高小智对话响应速度？](./FAQ.md)
+
+[6、我说话很慢，停顿时小智老是抢话](./FAQ.md)
+
+[7、我想通过小智控制电灯、空调、远程开关机等操作](./FAQ.md)

docs/firmware-setting.md

@@ -0,0 +1,54 @@
+# 基于虾哥编译好的固件配置自定义服务器
+
+## 第1步 确认版本
+烧录虾哥已经编译好的[1.6.1版本以上固件](https://github.com/78/xiaozhi-esp32/releases)
+
+## 第2步 准备你的ota地址
+如果你按照教程使用的是全模块部署，就应该会有ota地址。
+
+此刻，请你用浏览器打开你的ota地址，例如我的ota地址
+```
+https://2662r3426b.vicp.fun/xiaozhi/ota/
+```
+
+如果显示“OTA接口运行正常，websocket集群数量：X”。那就往下。
+
+如果显示“OTA接口运行不正常”，大概是你还没在`智控台`配置`Websocket`地址。那就：
+
+- 1、使用超级管理员登录智控台
+
+- 2、顶部菜单点击`参数管理`
+
+- 3、在列表中找到`server.websocket`项目，输入你的`Websocket`地址。例如我的就是
+
+```
+wss://2662r3426b.vicp.fun/xiaozhi/v1/
+```
+
+配置完后，再使用浏览器刷新你的ota接口地址，看看是不是正常了。如果还不正常就，就再次确认一下Websocket是否正常启动，是否配置了Websocket地址。
+
+## 第3步 进入配网模式
+进入机器的配网模式，在页面顶部，点击“高级选项”，在里面输入你服务器的`ota`地址，点击保存。重启设备
+![请参考-OTA地址设置](../docs/images/firmware-setting-ota.png)
+
+## 第4步 唤醒小智，查看日志输出
+
+唤醒小智，看看日志是不是正常输出。
+
+
+## 常见问题
+以下是一些常见问题，供参考：
+
+[1、为什么我说的话，小智识别出来很多韩文、日文、英文](./FAQ.md)
+
+[2、为什么会出现“TTS 任务出错 文件不存在”？](./FAQ.md)
+
+[3、TTS 经常失败，经常超时](./FAQ.md)
+
+[4、使用Wifi能连接自建服务器，但是4G模式却接不上](./FAQ.md)
+
+[5、如何提高小智对话响应速度？](./FAQ.md)
+
+[6、我说话很慢，停顿时小智老是抢话](./FAQ.md)
+
+[7、我想通过小智控制电灯、空调、远程开关机等操作](./FAQ.md)

docs/fish-speech-integration.md

@@ -0,0 +1,72 @@
+登录AutoDL，租赁镜像
+选择镜像:
+```
+PyTorch / 2.1.0 / 3.10(ubuntu22.04) / cuda 12.1
+```
+
+机器开机后，设置学术加速
+```
+source /etc/network_turbo
+```
+
+进入工作目录
+```
+cd autodl-tmp/
+```
+
+拉取项目
+```
+git clone https://gitclone.com/github.com/fishaudio/fish-speech.git ; cd fish-speech
+```
+
+安装依赖
+```
+pip install -e.
+```
+
+如果报错，安装portaudio
+```
+apt-get install portaudio19-dev -y
+```
+
+安装后执行
+```
+pip install torch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 --index-url https://download.pytorch.org/whl/cu121
+```
+
+下载模型
+```
+cd tools
+python download_models.py 
+```
+
+下载完模型后运行接口
+```
+python -m tools.api_server --listen 0.0.0.0:6006 
+```
+
+然后用浏览器去到aotodl实例页面
+```
+https://autodl.com/console/instance/list
+```
+
+如下图点击你刚才机器的`自定义服务`按钮，开启端口转发服务
+![自定义服务](images/fishspeech/autodl-01.png)
+
+端口转发服务设置完成后，你本地电脑打开网址`http://localhost:6006/`，就可以访问fish-speech的接口了
+![服务预览](images/fishspeech/autodl-02.png)
+
+
+如果你是单模块部署，核心配置如下
+```
+selected_module:
+  TTS: FishSpeech
+TTS:
+  FishSpeech:
+    reference_audio: ["config/assets/wakeup_words.wav",]
+    reference_text: ["哈啰啊，我是小智啦，声音好听的台湾女孩一枚，超开心认识你耶，最近在忙啥，别忘了给我来点有趣的料哦，我超爱听八卦的啦",]
+    api_key: "123"
+    api_url: "http://127.0.0.1:6006/v1/tts"
+```
+
+然后重启服务

docs/homeassistant-integration.md

@@ -0,0 +1,226 @@
+# 小智ESP32-开源服务端与HomeAssistant集成指南
+
+[TOC]
+
+-----
+
+## 简介
+
+本文档将指导您如何将ESP32设备与HomeAssistant进行集成。
+
+## 前提条件
+
+- 已安装并配置好`HomeAssistant`
+- 本次我选择的模型是：免费的ChatGLM，它支持functioncall函数调用
+
+## 开始前的操作（必要）
+
+### 1. 获取HA的网络网络地址信息
+
+请访问你Home Assistant的网络地址，例如，我的HA的地址是192.168.4.7，端口则是默认的8123，则在浏览器打开
+
+```
+http://192.168.4.7:8123
+```
+
+> 手动查询 HA 的 IP 地址方法**（仅限小智esp32-server和HA部署在同一个网络设备[例如同一个wifi]下）**：
+>
+> 1. 进入 Home Assistant（前端）。
+>
+> 2. 点击左下角 **设置（Settings）** → **系统（System）** → **网络（Network）**。
+>
+> 3. 滑到最底部`Home Assistant 网址(Home Assistant website)`区域，在`本地网络(local network)`中，点击`眼睛`按钮，可以看到当前使用的 IP 地址（如 `192.168.1.10`）和网络接口。点击`复制连接(copy link)`可以直接复制。
+>
+>    ![image-20250504051716417](images/image-ha-integration-01.png)
+
+或，您已经设置了直接可以访问的Home Assistant的OAuth地址，您也可以在浏览器内直接访问
+
+```
+http://homeassistant.local:8123
+```
+
+### 2. 登录`Home Assistant`拿到开发密钥
+
+登录`HomeAssistant`，点击`左下角头像 -> 个人`，切换`安全`导航栏，划到底部`长期访问令牌`生成api_key，并复制保存，后续的方法都需要使用这个api key且仅出现一次（小tips: 您可以保存生成的二维码图像，后续可以扫描二维码再此提取api key）。
+
+## 方法1：小智社区共建的HA调用功能
+
+### 功能描述
+
+- 如您后续需要增加新的设备，该方法需要手动重启`xiaozhi-esp32-server服务端`以此更新设备信息**（重要**）。
+
+- 需要您确保已经在HomeAssistant中集成`Xiaomi Home`，并将米家的设备导入进`HomeAssistant`。
+
+- 需要您确保`xiaozhi-esp32-server智控台`能正常使用。
+
+- 我的`xiaozhi-esp32-server智控台`和`HomeAssistant`部署在同一台机器的另一个端口，版本是`0.3.10`
+
+  ```
+  http://192.168.4.7:8002
+  ```
+
+
+### 配置步骤
+
+#### 1. 登录`HomeAssistant`整理需要控制的设备清单
+
+登录`HomeAssistant`，点击`左下角的设置`，然后进入`设备与服务`，再点击顶部的`实体`。
+
+然后在实体中搜索你相关控制的开关，结果出来后，在列表中，点击其中一个结果，这是会出现一个开关的界面。
+
+在开关的界面，我们尝试点击开关，看看是开发会随着我们的点击开/关。如果能操作，说明是正常联网的。
+
+接着在开关面板找到设置按钮，点击后，可以查看这个开关的`实体标识符`。
+
+我们打开一个记事本，按照这样格式整理一条数据：
+
+位置+英文逗号+设备名称+英文逗号+`实体标识符`+英文分号
+
+例如，我在公司，我有一个玩具灯，他的标识符是switch.cuco_cn_460494544_cp1_on_p_2_1，那么就这个写这一条数据
+
+```
+公司,玩具灯,switch.cuco_cn_460494544_cp1_on_p_2_1;
+```
+
+当然最后我可能要操作两个灯，我的最终的结果是：
+
+```
+公司,玩具灯,switch.cuco_cn_460494544_cp1_on_p_2_1;
+公司,台灯,switch.iot_cn_831898993_socn1_on_p_2_1;
+```
+
+这段字符，我们称为“设备清单字符”需要保存好，等一下有用。
+
+#### 2. 登录`智控台`
+
+![image-20250504051716417](images/image-ha-integration-06.png)
+
+使用管理员账号，登录`智控台`。在`智能体管理`，找到你的智能体，再点击`配置角色`。
+
+将意图识别设置成`外挂的大模型意图识别`或`大模型自主函数调用`。这时你会看到右侧有一个`编辑功能`。点击`编辑功能`按钮，会弹出`功能管理`的框。
+
+在`功能管理`的框里，你需要勾选`HomeAssistant设备状态查询`和`HomeAssistant设备状态修改`。
+
+勾选后，在`已选功能`点击`HomeAssistant设备状态查询`，然后在`参数配置`里配置你的`HomeAssistant`地址、密钥、设备清单字符。
+
+编辑好后，点击`保存配置`，这时`功能管理`的框会隐藏，这时你再点击保存智能体配置。
+
+保存成功后，即可唤醒设备操作。
+
+#### 3. 唤醒设别进行控制
+
+尝试和esp32说，“打开XXX灯”
+
+## 方法2：小智将Home Assistant的语音助手作为LLM工具
+
+### 功能描述
+
+- 该方法有一个比较严重的缺点——**该方法无法使用小智开源生态的function_call插件功能的能力**，因为使用Home Assistant作为小智的LLM工具会将意图识别能力转让给Home Assistant。但是**这个方法是能体验到原生的Home Assistant操作功能，且小智的聊天能力不变**。如实在介意可以使用同样是Home Assistant支持的[方法3](##方法3：使用Home Assistant的MCP服务（推荐）)，能够最大程度体验到Home Assistant的功能。
+
+### 配置步骤：
+
+#### 1. 配置Home Assistant的大模型语音助手。
+
+**需要您提前配置好Home Assistant的语音助手或大模型工具。**
+
+#### 2. 获取Home Assistant的语言助手的Agent ID.
+
+1. 进入Home Assistant页面内。左侧点击`开发者助手`。
+2. 在打开的`开发者助手`内，点击`动作`选项卡（如图示操作1），在页面内的选项栏`动作`中，找到或输入`conversation.process（对话-处理）`并选择`对话（conversation）: 处理`（如图示操作2）。
+
+![image-20250504043539343](images/image-ha-integration-02.png)
+
+3. 在页面内勾选`代理(agent)`选项，在变成常亮的`对话代理(conversation agent)`内选择您步骤一配置好的语音助手名称，如图示，我这边配置好的是`ZhipuAi`并选择。
+
+![image-20250504043854760](images/image-ha-integration-03.png)
+
+4. 选中后，点击表单左下方的`进入YAML模式`。
+
+![image-20250504043951126](images/image-ha-integration-04.png)
+
+5. 复制其中的agent-id的值，例如图示中我的是`01JP2DYMBDF7F4ZA2DMCF2AGX2`(仅供参考)。
+
+![image-20250504044046466](images/image-ha-integration-05.png)
+
+6. 切换到小智开源服务端`xiaozhi-esp32-server`的`config.yaml`文件内，在LLM配置中，找到Home Assistant，设置您的Home Assistant的网络地址，Api key和刚刚查询到的agent_id。
+7. 修改`config.yaml`文件内的`selected_module`属性的`LLM`为`HomeAssistant`，`Intent`为`nointent`。
+8. 重启小智开源服务端`xiaozhi-esp32-server`即可正常使用。
+
+## 方法3：使用Home Assistant的MCP服务（推荐）
+
+### 功能描述
+
+- 需要您提前在Home Assistant内集成并安装好HA集成——[Model Context Protocol Server](https://www.home-assistant.io/integrations/mcp_server/)。
+
+- 这个方法与方法2都是HA官方提供的解决方法，与方法2不同的是，您可以正常使用小智开源服务端`xiaozhi-esp32-server`的开源共建的插件，同时允许您随意使用任何一个支持function_call功能的LLM大模型。
+
+### 配置步骤
+
+#### 1. 安装Home Assistant的MCP服务集成。
+
+集成官方网址——[Model Context Protocol Server](https://www.home-assistant.io/integrations/mcp_server/)。。
+
+或跟随以下手动操作。
+
+> - 前往Home Assistant页面的**[设置 > 设备和服务（Settings > Devices & Services.）](https://my.home-assistant.io/redirect/integrations)**。
+>
+> - 在右下角，选择 **[添加集成（Add Integration）](https://my.home-assistant.io/redirect/config_flow_start?domain=mcp_server)**按钮。
+>
+> - 从列表中选择**模型上下文协议服务器（Model Context Protocol Server）**。
+>
+> - 按照屏幕上的说明完成设置。
+
+#### 2. 配置小智开源服务端MCP配置信息
+
+
+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
+"Home Assistant": {
+      "command": "mcp-proxy",
+      "args": [
+        "http://YOUR_HA_HOST/mcp_server/sse"
+      ],
+      "env": {
+        "API_ACCESS_TOKEN": "YOUR_API_ACCESS_TOKEN"
+      }
+},
+```
+
+注意：
+
+1. **替换配置：**
+   - 替换`args`内的`YOUR_HA_HOST`为您的HA服务地址，如果你的服务地址已经包含了https/http字样（例如`http://192.168.1.101:8123`)，则只需要填入`192.168.1.101:8123`即可。
+   - 将`env`内`API_ACCESS_TOKEN`的`YOUR_API_ACCESS_TOKEN`替换成您之前获取到的开发密钥api key。
+2. **如果你添加配置是在`"mcpServers"`的括号内后续没有新的`mcpServers`的配置时，需要把最后的逗号`,`移除**，否则可能会解析失败。
+
+**最后效果参考以下（参考如下）**：
+
+```json
+ "mcpServers": {
+    "Home Assistant": {
+      "command": "mcp-proxy",
+      "args": [
+        "http://192.168.1.101:8123/mcp_server/sse"
+      ],
+      "env": {
+        "API_ACCESS_TOKEN": "abcd.efghi.jkl"
+      }
+    }
+  }
+```
+
+#### 3. 配置小智开源服务端的系统配置
+
+1. **选择任意一款支持function_call的LLM大模型作为小智的LLM聊天助手（但不要选择Home Assistant作为LLM工具）**，本次我选择的模型是：免费的ChatGLM，它支持functioncall函数调用，但部分时候调用不太稳定，如果像追求稳定建议把LLM设置成：DoubaoLLM，使用的具体model_name是：doubao-1-5-pro-32k-250115。
+
+2. 切换到小智开源服务端`xiaozhi-esp32-server`的`config.yaml`文件内，设置您的LLM大模型配置，并且将`selected_module`配置的`Intent`调整为`function_call`。
+
+3. 重启小智开源服务端`xiaozhi-esp32-server`即可正常使用。

docs/huoshan-streamTTS-voice-cloning.md

@@ -0,0 +1,58 @@
+# 智控台 火山双流式语音合成+音色克隆配置教程
+
+本教程分为4个阶段：准备阶段、配置阶段、克隆阶段、使用阶段。主要是介绍通过智控台配置火山双流式语音合成+音色克隆的过程。
+
+## 第一阶段：准备阶段
+超级管理员先预先把火山引擎服务开通好，获取到App Id，Access Token。默认火上引擎会赠送一个音色资源。这个音色资源需要把它复制到本项目里。
+
+如果你想克隆多个音色，需要购买开通多个音色资源。只要把每个音色资源的声音ID(S_xxxxx)复制到本项目。然后分配给系统的账号使用即可。以下是详细步骤：
+
+### 1.开通火山引擎服务
+访问 https://console.volcengine.com/speech/app  在应用管理创建应用，勾选语音合成大模型和声音复刻大模型。
+
+### 2.获取音色资源ID
+访问 https://console.volcengine.com/speech/service/9999 复制三项内容，分别是App Id，Access Token以及声音ID(S_xxxxx)。如图
+
+![获取音色资源](images/image-clone-integration-01.png)
+
+## 第二阶段：配置火山引擎服务
+
+### 1.填写火山引擎配置
+
+使用超级管理员账号登录智控台，点击顶部【模型配置】，再点击模型配置页面左侧的【语音合成】，搜索找到“火山双流式语音合成”，点击修改，将你火山引擎的`App Id`填入到【应用ID】字段里，将`Access Token`填入到【访问令牌】字段里。然后保存。
+
+### 2.将音色资源ID分配给系统账号
+
+使用超级管理员账号登录智控台，点击顶部`参数字典`，在下拉菜单中，点击`系统功能配置`页面。在页面上勾选`音色克隆`，点击保存配置。即可在顶部菜单看到`音色克隆`按钮。
+
+使用超级管理员账号登录智控台，点击顶部【音色克隆】、【音色资源】。
+
+点击新增按钮，在【平台名称】选择“火山双流式语音合成”；
+
+在【音色资源ID】填入你火山引擎的声音资源ID(S_xxxxx)，填入后按回车；
+
+在【归属账号】选择你要分配给的系统账号，你可以分配给你自己。然后点击保存
+
+## 第三阶段：克隆阶段
+
+如果登录后，点击顶部【音色克隆】》【音色克隆】，显示【您的账号暂无音色资源请联系管理员分配音色资源】，说明你在第二阶段还没有把音色资源ID分配给这个账号。那就是回到第二阶段，分配音色资源给对应的账号。
+
+如果登录后，点击顶部【音色克隆】》【音色克隆】，能看到对应的音色列表。请继续。
+
+在列表里会看到对应的音色列表。选择其中一个音色资源，点击【上传音频】按钮。上传后，可以试听一下声音或者截取某段声音。确认后点击【上传音频】按钮。
+![上传音频](images/image-clone-integration-02.png)
+
+上传音频后，在列表里会看到对应的音色会变成“待复刻”状态。点击【立即复刻】按钮。等1~2秒会返回结果。
+
+如果复刻失败，请将鼠标放到“错误信息”图标上，会显示失败的原因。
+
+如果复刻成功，在列表里会看到对应的音色会变成“训练成功”状态。此时你可以点击【声音名称】栏的修改按钮，修改音色资源的名称，方便后期选择使用。
+
+## 第四阶段：使用阶段
+
+点击顶部【智能体管理】，选择任意一个智能体，点击【配置角色】按钮。
+
+语音合成(TTS)选择“火山双流式语音合成”。在列表里，找到名字带有“克隆音色”的音色资源（如图），选择它，点击保存。
+![选择音色](images/image-clone-integration-03.png)
+
+接下来，可以唤醒小智和它对话。