Merge pull request #3134 from xinnan-tech/0.9.3

Bump to 0.9.3
2026-07-23 23:53:55 +08:00 · 2026-04-27 12:46:10 +08:00 · 2026-04-27 12:44:02 +08:00 · 2026-04-24 14:38:06 +08:00 · 2026-04-24 14:35:34 +08:00 · 2026-04-24 14:15:27 +08:00
1040 changed files with 183745 additions and 11456 deletions
@@ -0,0 +1,6 @@
+version: 2
+updates:
+  - package-ecosystem: pip
+    directory: /main/xiaozhi-server
+    schedule:
+      interval: weekly
@@ -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"
@@ -5,6 +5,10 @@ on:
    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:
@@ -31,6 +35,9 @@ jobs:

      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v3
+        with:
+          driver-opts: |
+            network=host

      - name: Login to GitHub Container Registry
        uses: docker/login-action@v3
@@ -60,6 +67,10 @@ jobs:
          tags: |
            ${{ 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
@@ -70,4 +81,8 @@ jobs:
          push: true
          tags: |
            ${{ env.IS_VERSION == 'true' && format('ghcr.io/{0}:web_{1},ghcr.io/{0}:web_latest', github.repository, env.VERSION) || format('ghcr.io/{0}:web_latest', github.repository) }}
-          platforms: linux/amd64,linux/arm64
+          platforms: linux/amd64,linux/arm64
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+          build-args: |
+            BUILDKIT_PROGRESS=plain
@@ -3,6 +3,9 @@ __pycache__/
 .idea/
 *.py[cod]
 *$py.class
+.vscode
+.claude
+AGENTS.md

 # C extensions
 *.so
@@ -175,3 +178,12 @@ 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
@@ -1,29 +1,6 @@
-# 第一阶段：构建Python依赖
-FROM python:3.10-slim AS builder
+# 生产镜像，仅包含应用代码
+FROM ghcr.io/xinnan-tech/xiaozhi-esp32-server:server-base

-WORKDIR /app
-
-COPY main/xiaozhi-server/requirements.txt .
-
-# 安装Python依赖
-RUN pip install --no-cache-dir -r requirements.txt
-
-# 第二阶段：生产镜像
-FROM python:3.10-slim
-
-WORKDIR /opt/xiaozhi-esp32-server
-
-# 安装系统依赖
-RUN 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=builder /usr/local/bin/mcp-proxy /usr/local/bin/mcp-proxy
-
-# 复制应用代码
 COPY main/xiaozhi-server .

 # 启动应用
@@ -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
@@ -1,5 +1,5 @@
 # 第一阶段：构建Vue前端
-FROM node:18 as web-builder
+FROM node:18 AS web-builder
 WORKDIR /app
 COPY main/manager-web/package*.json ./
 RUN npm install
@@ -7,7 +7,7 @@ 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
+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
@@ -18,12 +18,19 @@ FROM bellsoft/liberica-runtime-container:jre-21-glibc

 # 安装Nginx和字体库
 RUN apk update && \
-    apk add --no-cache nginx bash && \
-    apk add --no-cache fontconfig ttf-dejavu msttcorefonts-installer && \
-    rm -rf /var/cache/apk/*
+    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 printf 'YES\n' | update-ms-fonts && fc-cache -f -v
+RUN fc-cache -f -v

 # 配置Nginx
 COPY docs/docker/nginx.conf /etc/nginx/nginx.conf
@@ -6,29 +6,25 @@
 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MCP接入点和声纹识别
+支持MQTT+UDP协议、Websocket协议、MCP接入点、声纹识别、知识库
 </p>

 <p align="center">
-<a href="./README_en.md">English</a>
-· <a href="./docs/FAQ.md">常见问题</a>
+<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="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
+  <a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
+  <a href="./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/graphs/contributors">
-    <img alt="GitHub Contributors" src="https://img.shields.io/github/contributors/xinnan-tech/xiaozhi-esp32-server?logo=github" />
-  </a>
-  <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">
-    <img alt="Issues" src="https://img.shields.io/github/issues/xinnan-tech/xiaozhi-esp32-server?color=0088ff" />
-  </a>
-  <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/pulls">
-    <img alt="GitHub pull requests" src="https://img.shields.io/github/issues-pr/xinnan-tech/xiaozhi-esp32-server?color=0088ff" />
-  </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>
@@ -38,9 +34,9 @@
 </p>

 <p align="center">
-By Professor Siyuan Liu Research and Development Group ( South China University of Technology)
+Spearheaded by Professor Siyuan Liu's Team (South China University of Technology)
 </br>
-刘思源教授团队研发（华南理工大学）
+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>
@@ -59,24 +55,40 @@ By Professor Siyuan Liu Research and Development Group ( South China University
    <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/BV1CDKWemEU6" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1vchQzaEse" target="_blank">
         <picture>
-           <img alt="自定义音色" src="docs/images/demo2.png" />
+           <img alt="速度优化秘诀" src="docs/images/demo6.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1C1tCzUEZh" target="_blank">
         <picture>
-           <img alt="使用粤语交流" src="docs/images/demo3.png" />
+           <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>
@@ -85,18 +97,16 @@ By Professor Siyuan Liu Research and Development Group ( South China University
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV1kgA2eYEQ9" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1ZQKUzYExM" target="_blank">
         <picture>
-           <img alt="成本最低配置" src="docs/images/demo4.png" />
+           <img alt="MCP接入点" src="docs/images/demo13.png" />
         </picture>
        </a>
    </td>
-  </tr>
-  <tr>
    <td>
-        <a href="https://www.bilibili.com/video/BV1Vy96YCE3R" target="_blank">
+      <a href="https://www.bilibili.com/video/BV1TJ7WzzEo6" target="_blank">
         <picture>
-           <img alt="自定义音色" src="docs/images/demo6.png" />
+           <img alt="多指令任务" src="docs/images/demo11.png" />
         </picture>
        </a>
    </td>
@@ -114,20 +124,6 @@ By Professor Siyuan Liu Research and Development Group ( South China University
         </picture>
        </a>
    </td>
-    <td>
-        <a href="https://www.bilibili.com/video/BV178XuYfEpi" target="_blank">
-         <picture>
-           <img alt="IOT指令控制设备" src="docs/images/demo9.png" />
-         </picture>
-        </a>
-    </td>
-    <td>
-        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
-         <picture>
-           <img alt="播报新闻" src="docs/images/demo0.png" />
-         </picture>
-        </a>
-    </td>
  </tr>
  <tr>
    <td>
@@ -145,23 +141,23 @@ By Professor Siyuan Liu Research and Development Group ( South China University
        </a>
    </td>
    <td>
-      <a href="https://www.bilibili.com/video/BV1TJ7WzzEo6" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1CDKWemEU6" target="_blank">
         <picture>
-           <img alt="多指令任务" src="docs/images/demo11.png" />
+           <img alt="自定义音色" src="docs/images/demo2.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV1ZQKUzYExM" target="_blank">
+        <a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
         <picture>
-           <img alt="MCP接入点" src="docs/images/demo13.png" />
+           <img alt="使用粤语交流" src="docs/images/demo3.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV1Exu3zqEDe" target="_blank">
+        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
         <picture>
-           <img alt="声纹识别" src="docs/images/demo14.png" />
+           <img alt="播报新闻" src="docs/images/demo0.png" />
         </picture>
        </a>
    </td>
@@ -188,14 +184,16 @@ By Professor Siyuan Liu Research and Development Group ( South China University
 #### 🚀 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、IOT、MCP、视觉感知 | 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、IOT、MCP接入点、声纹识别、视觉感知、OTA、智控台 | 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) | 
+| **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
+> 💡 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/
@@ -214,73 +212,71 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/

 | 模块名称 | 入门全免费设置 | 流式配置 |
 |:---:|:---:|:---:|
-| ASR(语音识别) | FunASR(本地) | 👍FunASRServer 或 👍DoubaoStreamASR |
-| LLM(大模型) | ChatGLMLLM(智谱glm-4-flash) | 👍DoubaoLLM(火山doubao-1-5-pro-32k-250115) |
-| VLLM(视觉大模型) | ChatGLMVLLM(智谱glm-4v-flash) | 👍QwenVLVLLM(千问qwen2.5-vl-3b-instructh) |
-| TTS(语音合成) | ✅LinkeraiTTS(灵犀流式) | 👍HuoshanDoubleStreamTTS(火山双流式语音合成) 或 👍AliyunStreamTTS(阿里云流式语音合成) |
+| 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》xiaozhi-server》test》test_page.html | 使用谷歌浏览器直接打开 | 测试音频播放和接收功能，验证Python端音频处理是否正常 |
-| 模型响应测试工具1 | main》xiaozhi-server》performance_tester.py | 执行 `python performance_tester.py` | 测试ASR(语音识别)、LLM(大模型)、TTS(语音合成)三个核心模块的响应速度 |
-| 模型响应测试工具2 | main》xiaozhi-server》performance_tester_vllm.py | 执行 `python performance_tester_vllm.py` | 测试VLLM(视觉模型)的响应速度 |
+| 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 ✅
-
+![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WebSocket和HTTP服务器，提供完整的控制台管理和认证系统 |
+| 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LLM意图识别、Function Call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，具备记忆总结功能 |
+| 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 |
-| 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 |
+| 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 🚧

-想了解具体开发计划进度，[请点击这里](https://github.com/users/xinnan-tech/projects/3)
+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
-
-| 项目名称  | 项目地址 | 项目描述 |
-|:---------------------|:--------|:--------|
-| 小智安卓客户端  | [xiaozhi-android-client](https://github.com/TOM88812/xiaozhi-android-client) | 一个基于xiaozhi-server的Android、IOS语音对话应用,支持实时语音交互和文字对话。<br/>现在是flutter版本，打通IOS、Android端。 |
-| 小智电脑客户端  | [py-xiaozhi](https://github.com/Huang-junsen/py-xiaozhi) | 该项目提供了一个基于 Python 实现的小白 AI 客户端，使得在不具备实体硬件条件的情况下，<br/>依然能够体过代码体验小智 AI 的功能。 |
-| 小智Java服务端  | [xiaozhi-esp32-server-java](https://github.com/joey-zhou/xiaozhi-esp32-server-java) | 小智开源后端服务 Java 版本是一个基于 Java 的开源项目。<br/>它包括前后端的服务，旨在为用户提供一个完整的后端服务解决方案。 |
+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)

 ---

 ## 本项目支持的平台/组件列表 📋
-
 ### LLM 语言模型

 | 使用方式 | 支持平台 | 免费平台 |
 |:---:|:---:|:---:|
-| openai 接口调用 | 阿里百炼、火山引擎豆包、深度求索、智谱ChatGLM、Gemini | 智谱ChatGLM、Gemini |
+| 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。

@@ -300,8 +296,8 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/

 | 使用方式 | 支持平台 | 免费平台 |
 |:---:|:---:|:---:|
-| 接口调用 | EdgeTTS、火山引擎豆包TTS、腾讯云、阿里云TTS、CosyVoiceSiliconflow、TTS302AI、CozeCnTTS、GizwitsTTS、ACGNTTS、OpenAITTS、灵犀流式TTS | 灵犀流式TTS、EdgeTTS、CosyVoiceSiliconflow(部分) |
-| 本地服务 | FishSpeech、GPT_SOVITS_V2、GPT_SOVITS_V3、MinimaxTTS | FishSpeech、GPT_SOVITS_V2、GPT_SOVITS_V3、MinimaxTTS |
+| 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 |

 ---

@@ -318,7 +314,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 | 使用方式 | 支持平台 | 免费平台 |
 |:---:|:---:|:---:|
 | 本地使用 | FunASR、SherpaASR | FunASR、SherpaASR |
-| 接口调用 | DoubaoASR、FunASRServer、TencentASR、AliyunASR | FunASRServer |
+| 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 |

 ---

@@ -335,7 +331,9 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 |   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     |    |

 ---

@@ -345,6 +343,15 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 |:------:|:-------------:|:----:|:-------:|:---------------------:|
 | 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     |
+
+---
+
+### Rag 检索增强生成
+
+|   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     |

 ---

@@ -355,8 +362,10 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 | <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">
@@ -0,0 +1,376 @@
+[![Banners](docs/images/banner1.png)](https://github.com/xinnan-tech/xiaozhi-esp32-server)
+
+<h1 align="center">Xiaozhi Backend-Service xiaozhi-esp32-server</h1>
+
+<p align="center">
+Dieses Projekt basiert auf der Theorie und Technologie der Mensch-Maschine-symbiotischen Intelligenz zur Entwicklung intelligenter Terminal-Hardware- und Software-Systeme<br/>und bietet Backend-Dienste für das Open-Source-Hardware-Projekt
+<a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a><br/>
+Implementiert mit Python, Java und Vue gemäß dem <a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">Xiaozhi-Kommunikationsprotokoll</a><br/>
+Unterstützt MQTT+UDP-Protokoll, Websocket-Protokoll, MCP-Endpunkte und Stimmabdruckerkennung
+</p>
+
+<p align="center">
+<a href="./docs/FAQ.md">Häufige Fragen</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">Probleme melden</a>
+· <a href="./README.md#%E9%83%A8%E7%BD%B2%E6%96%87%E6%A1%A3">Deployment-Dokumentation</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">Release-Hinweise</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-DFE0E5"></a>
+  <a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
+  <a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DBEDFA"></a>
+  <a href="./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">
+Geleitet vom Team von Professor Siyuan Liu (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="South China University of Technology" width="50%">
+</p>
+
+---
+
+## Zielgruppe 👥
+
+Dieses Projekt erfordert ESP32-Hardware-Geräte zum Betrieb. Wenn Sie ESP32-bezogene Hardware erworben haben, erfolgreich eine Verbindung zu Brother Xias bereitgestelltem Backend-Service hergestellt haben und Ihren eigenen `xiaozhi-esp32`-Backend-Service unabhängig aufbauen möchten, dann ist dieses Projekt perfekt für Sie.
+
+Möchten Sie die Nutzungseffekte sehen? Klicken Sie auf die Videos unten 🎥
+
+<table>
+  <tr>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1FMFyejExX" target="_blank">
+         <picture>
+           <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>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1CDKWemEU6" target="_blank">
+         <picture>
+           <img alt="自定义音色" src="docs/images/demo2.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
+         <picture>
+           <img alt="使用粤语交流" src="docs/images/demo3.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
+         <picture>
+           <img alt="播报新闻" src="docs/images/demo0.png" />
+         </picture>
+        </a>
+    </td>
+  </tr>
+</table>
+
+---
+
+## Warnungen ⚠️
+
+1. Dieses Projekt ist Open-Source-Software. Diese Software hat keine kommerzielle Partnerschaft mit Drittanbieter-API-Dienstleistern (einschließlich, aber nicht beschränkt auf Spracherkennung, große Modelle, Sprachsynthese und andere Plattformen), mit denen sie sich verbindet, und bietet keine Garantie für deren Servicequalität oder finanzielle Sicherheit. Es wird empfohlen, dass Benutzer Dienstleister mit entsprechenden Geschäftslizenzen bevorzugen und deren Servicevereinbarungen und Datenschutzrichtlinien sorgfältig lesen. Diese Software hostet keine Kontoschlüssel, nimmt nicht an Geldströmen teil und trägt nicht das Risiko von Verlusten bei Guthaben-Aufladungen.
+
+2. Die Funktionalität dieses Projekts ist nicht vollständig und hat keine Netzwerksicherheitsbewertung bestanden. Bitte verwenden Sie es nicht in Produktionsumgebungen. Wenn Sie dieses Projekt zu Lernzwecken in einer öffentlichen Netzwerkumgebung bereitstellen, stellen Sie bitte sicher, dass notwendige Schutzmaßnahmen vorhanden sind.
+
+---
+
+## Deployment-Dokumentation
+
+![Banners](docs/images/banner2.png)
+
+Dieses Projekt bietet zwei Bereitstellungsmethoden. Bitte wählen Sie basierend auf Ihren spezifischen Anforderungen:
+
+#### 🚀 Auswahl der Bereitstellungsmethode
+| Bereitstellungsmethode | Funktionen | Anwendungsszenarien | Deployment-Dokumente | Konfigurationsanforderungen | Video-Tutorials |
+|---------|------|---------|---------|---------|---------|
+| **Vereinfachte Installation** | Intelligenter Dialog, Einzel-Agenten-Verwaltung | Umgebungen mit geringer Konfiguration, Daten in Konfigurationsdateien gespeichert, keine Datenbank erforderlich | [①Docker-Version](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②Quellcode-Deployment](./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)| 2 Kerne 4GB bei Verwendung von `FunASR`, 2 Kerne 2GB bei allen APIs | - |
+| **Vollständige Modulinstallation** | Intelligenter Dialog, Mehrbenutzerverwaltung, Mehr-Agenten-Verwaltung, Intelligente Steuerkonsole-Bedienung | Vollständige Funktionserfahrung, Daten in Datenbank gespeichert |[①Docker-Version](./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) / [②Quellcode-Deployment](./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) / [③Quellcode-Deployment Auto-Update-Tutorial](./docs/dev-ops-integration.md) | 4 Kerne 8GB bei Verwendung von `FunASR`, 2 Kerne 4GB bei allen APIs| [Video-Tutorial für lokalen Quellcode-Start](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
+
+Häufige Fragen und entsprechende Tutorials finden Sie unter [diesem Link](./docs/FAQ.md)
+
+> 💡 Hinweis: Unten ist eine Testplattform, die mit dem neuesten Code bereitgestellt wurde. Sie können bei Bedarf brennen und testen. Gleichzeitige Benutzer: 6, Daten werden täglich gelöscht.
+
+```
+Adresse der intelligenten Steuerkonsole: https://2662r3426b.vicp.fun
+Adresse der intelligenten Steuerkonsole (H5): https://2662r3426b.vicp.fun/h5/index.html
+
+Service-Testtool: https://2662r3426b.vicp.fun/test/
+OTA-Schnittstellenadresse: https://2662r3426b.vicp.fun/xiaozhi/ota/
+Websocket-Schnittstellenadresse: wss://2662r3426b.vicp.fun/xiaozhi/v1/
+```
+
+#### 🚩 Konfigurationsbeschreibung und Empfehlungen
+> [!Note]
+> Dieses Projekt bietet zwei Konfigurationsschemata:
+>
+> 1. `Einstiegslevel Kostenlose Einstellungen`: Geeignet für den persönlichen und privaten Gebrauch, alle Komponenten verwenden kostenlose Lösungen, keine zusätzliche Zahlung erforderlich.
+>
+> 2. `Streaming-Konfiguration`: Geeignet für Demonstrationen, Schulungen, Szenarien mit mehr als 2 gleichzeitigen Benutzern usw. Verwendet Streaming-Verarbeitungstechnologie für schnellere Reaktionsgeschwindigkeit und bessere Erfahrung.
+>
+> Ab Version `0.5.2` unterstützt das Projekt Streaming-Konfiguration. Im Vergleich zu früheren Versionen ist die Reaktionsgeschwindigkeit um ca. `2,5 Sekunden` verbessert, was die Benutzererfahrung erheblich verbessert.
+
+| Modulname | Einstiegslevel Kostenlose Einstellungen | Streaming-Konfiguration |
+|:---:|:---:|:---:|
+| ASR (Spracherkennung) | FunASR (Lokal) | 👍XunfeiStreamASR (Xunfei-Streaming) |
+| LLM (Großes Modell) | glm-4-flash (Zhipu) | 👍qwen-flash (Alibaba Bailian) |
+| VLLM (Vision Large Model) | glm-4v-flash (Zhipu) | 👍qwen3.5-flash (Alibaba Bailian) |
+| TTS (Sprachsynthese) | EdgeTTS (Microsoft) | 👍HuoshanDoubleStreamTTS (Volcano-Streaming) |
+| Intent (Absichtserkennung) | function_call (Funktionsaufruf) | function_call (Funktionsaufruf) |
+| Memory (Gedächtnisfunktion) | mem_local_short (Lokales Kurzzeitgedächtnis) | mem_local_short (Lokales Kurzzeitgedächtnis) |
+
+Wenn Sie sich um die Latenz jeder Komponente kümmern, lesen Sie bitte den [Xiaozhi-Komponenten-Leistungstestbericht](https://github.com/xinnan-tech/xiaozhi-performance-research). Sie können gemäß den Testmethoden im Bericht in Ihrer Umgebung tatsächlich testen.
+
+#### 🔧 Testwerkzeuge
+Dieses Projekt bietet die folgenden Testwerkzeuge, um Ihnen bei der Überprüfung des Systems und der Auswahl geeigneter Modelle zu helfen:
+
+| Werkzeugname | Standort | Verwendungsmethode | Funktionsbeschreibung |
+|:---:|:---|:---:|:---:|
+| Audio-Interaktionstesttool | main》xiaozhi-server》test》test_page.html | Direkt mit Google Chrome öffnen | Testet Audio-Wiedergabe- und Empfangsfunktionen, überprüft, ob die Python-seitige Audioverarbeitung normal ist |
+| Modell-Reaktionstesttool | main》xiaozhi-server》performance_tester.py | Ausführen `python performance_tester.py` | Testet die Reaktionsgeschwindigkeit von ASR (Spracherkennung), LLM (großes Modell), VLLM (Vision-Modell), TTS (Sprachsynthese) drei Kernmodulen |
+
+> 💡 Hinweis: Beim Testen der Modellgeschwindigkeit werden nur Modelle mit konfigurierten Schlüsseln getestet.
+
+---
+## Funktionsliste ✨
+### Implementiert ✅
+![请参考-全模块安装架构图](docs/images/deploy2.png)
+| Funktionsmodul | Beschreibung |
+|:---:|:---|
+| Kernarchitektur | Basierend auf [MQTT+UDP-Gateway](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docs/mqtt-gateway-integration.md), WebSocket und HTTP-Servern, bietet vollständiges Konsolenverwaltungs- und Authentifizierungssystem |
+| Sprachinteraktion | Unterstützt Streaming-ASR (Spracherkennung), Streaming-TTS (Sprachsynthese), VAD (Sprachaktivitätserkennung), unterstützt mehrsprachige Erkennung und Sprachverarbeitung |
+| Stimmabdruckerkennung | Unterstützt Mehrbenutzer-Stimmabdruckregistrierung, -verwaltung und -erkennung, verarbeitet parallel mit ASR, Echtzeit-Sprecheridentitätserkennung und Weitergabe an LLM für personalisierte Antworten |
+| Intelligenter Dialog | Unterstützt mehrere LLM (große Sprachmodelle), implementiert intelligenten Dialog |
+| Visuelle Wahrnehmung | Unterstützt mehrere VLLM (Vision Large Models), implementiert multimodale Interaktion |
+| Absichtserkennung | Unterstützt LLM-Absichtserkennung, Function Call-Funktionsaufruf, bietet plugin-basierten Absichtsverarbeitungsmechanismus |
+| Gedächtnissystem | Unterstützt lokales Kurzzeitgedächtnis, mem0ai-Schnittstellengedächtnis, PowerMem intelligentes Gedächtnis, mit Gedächtniszusammenfassungsfunktion |
+| Wissensdatenbank | Unterstützt RAGFlow-Wissensdatenbank, ermöglicht großem Modell die Bewertung, ob Wissensdatenbank benötigt wird, bevor geantwortet wird |
+| Werkzeugaufruf | Unterstützt Client-IOT-Protokoll, Client-MCP-Protokoll, Server-MCP-Protokoll, MCP-Endpunktprotokoll, benutzerdefinierte Werkzeugfunktionen |
+| Befehlsübermittlung | Basierend auf MQTT-Protokoll, unterstützt die Übermittlung von MCP-Befehlen von der intelligenten Steuerkonsole an ESP32-Geräte |
+| Verwaltungs-Backend | Bietet Web-Verwaltungsoberfläche, unterstützt Benutzerverwaltung, Systemkonfiguration und Geräteverwaltung; Oberfläche unterstützt vereinfachtes Chinesisch, traditionelles Chinesisch und englische Anzeige |
+| Testwerkzeuge | Bietet Leistungstestwerkzeuge, Vision-Modell-Testwerkzeuge und Audio-Interaktionstestwerkzeuge |
+| Deployment-Unterstützung | Unterstützt Docker-Deployment und lokales Deployment, bietet vollständige Konfigurationsdateiverwaltung |
+| Plugin-System | Unterstützt funktionale Plugin-Erweiterungen, benutzerdefinierte Plugin-Entwicklung und Plugin-Hot-Loading |
+
+### In Entwicklung 🚧
+
+Um über spezifische Entwicklungsplanfortschritte zu erfahren, [klicken Sie hier](https://github.com/users/xinnan-tech/projects/3). Häufige Fragen und entsprechende Tutorials finden Sie unter [diesem Link](./docs/FAQ.md)
+
+Wenn Sie ein Softwareentwickler sind, finden Sie hier einen [Offenen Brief an Entwickler](docs/contributor_open_letter.md). Willkommen beim Beitritt!
+
+---
+
+## Produktökosystem 👬
+Xiaozhi ist ein Ökosystem. Wenn Sie dieses Produkt verwenden, können Sie sich auch andere [hervorragende Projekte](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) in diesem Ökosystem ansehen
+
+---
+
+## Liste der von diesem Projekt unterstützten Plattformen/Komponenten 📋
+### LLM-Sprachmodelle
+
+| Verwendungsmethode | Unterstützte Plattformen | Kostenlose Plattformen |
+|:---:|:---:|:---:|
+| OpenAI-Schnittstellenaufrufe | Alibaba Bailian, Volcano Engine Doubao, DeepSeek, Zhipu ChatGLM, Gemini | Zhipu ChatGLM, Gemini |
+| Ollama-Schnittstellenaufrufe | Ollama | - |
+| Dify-Schnittstellenaufrufe | Dify | - |
+| FastGPT-Schnittstellenaufrufe | FastGPT | - |
+| Coze-Schnittstellenaufrufe | Coze | - |
+| Xinference-Schnittstellenaufrufe | Xinference | - |
+| HomeAssistant-Schnittstellenaufrufe | HomeAssistant | - |
+
+Tatsächlich kann jedes LLM, das OpenAI-Schnittstellenaufrufe unterstützt, integriert und verwendet werden.
+
+---
+
+### VLLM-Vision-Modelle
+
+| Verwendungsmethode | Unterstützte Plattformen | Kostenlose Plattformen |
+|:---:|:---:|:---:|
+| OpenAI-Schnittstellenaufrufe | Alibaba Bailian, Zhipu ChatGLMVLLM | Zhipu ChatGLMVLLM |
+
+Tatsächlich kann jedes VLLM, das OpenAI-Schnittstellenaufrufe unterstützt, integriert und verwendet werden.
+
+---
+
+### TTS-Sprachsynthese
+
+| Verwendungsmethode | Unterstützte Plattformen | Kostenlose Plattformen |
+|:---:|:---:|:---:|
+| Schnittstellenaufrufe | EdgeTTS, Volcano Engine Doubao TTS, Tencent Cloud, Alibaba Cloud TTS, AliYun Stream TTS, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi Streaming TTS, MinimaxTTS, Volcano Dual-Stream TTS | Lingxi Streaming TTS, EdgeTTS, CosyVoiceSiliconflow (teilweise) |
+| Lokale Dienste | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, Index-TTS, PaddleSpeech | Index-TTS, PaddleSpeech, FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3 |
+
+---
+
+### VAD-Sprachaktivitätserkennung
+
+| Typ | Plattformname | Verwendungsmethode | Preismodell | Hinweise |
+|:---:|:---------:|:----:|:----:|:--:|
+| VAD | SileroVAD | Lokale Verwendung | Kostenlos | |
+
+---
+
+### ASR-Spracherkennung
+
+| Verwendungsmethode | Unterstützte Plattformen | Kostenlose Plattformen |
+|:---:|:---:|:---:|
+| Lokale Verwendung | FunASR, SherpaASR | FunASR, SherpaASR |
+| Schnittstellenaufrufe | DoubaoASR, Doubao Streaming ASR, FunASRServer, TencentASR, AliyunASR, Aliyun Streaming ASR, Baidu ASR, OpenAI ASR | FunASRServer |
+
+---
+
+### Voiceprint-Stimmabdruckerkennung
+
+| Verwendungsmethode | Unterstützte Plattformen | Kostenlose Plattformen |
+|:---:|:---:|:---:|
+| Lokale Verwendung | 3D-Speaker | 3D-Speaker |
+
+---
+
+### Memory-Gedächtnisspeicher
+
+| Typ | Plattformname | Verwendungsmethode | Preismodell | Hinweise |
+|:------:|:---------------:|:----:|:---------:|:--:|
+| Memory | mem0ai | Schnittstellenaufrufe | 1000 Mal/Monat Kontingent | |
+| Memory | [powermem](./docs/powermem-integration.md) | Lokale Zusammenfassung | Abhängig von LLM und DB | OceanBase Open Source, unterstützt intelligente Abfrage |
+| Memory | mem_local_short | Lokale Zusammenfassung | Kostenlos | |
+| Memory | nomem | Kein Gedächtnismodus | Kostenlos | |
+
+---
+
+### Intent-Absichtserkennung
+
+| Typ | Plattformname | Verwendungsmethode | Preismodell | Hinweise |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Intent | intent_llm | Schnittstellenaufrufe | Basierend auf LLM-Preisen | Erkennt Absicht durch große Modelle, starke Allgemeingültigkeit |
+| Intent | function_call | Schnittstellenaufrufe | Basierend auf LLM-Preisen | Vervollständigt Absicht durch Funktionsaufruf großer Modelle, schnelle Geschwindigkeit, guter Effekt |
+| Intent | nointent | Kein Absichtsmodus | Kostenlos | Führt keine Absichtserkennung durch, gibt direkt Dialogergebnis zurück |
+
+---
+
+### Rag Retrieval Augmented Generation
+
+| Typ | Plattformname | Verwendungsmethode | Preismodell | Hinweise |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Rag | ragflow | Schnittstellenaufrufe | Gebühren basierend auf Token-Verbrauch für Segmentierung und Tokenisierung | Nutzt RAGFlow's Retrieval-Augmented-Generation-Funktion für präzisere Dialogantworten |
+
+---
+
+## Danksagungen 🙏
+
+| Logo | Projekt/Unternehmen | Beschreibung |
+|:---:|:---:|:---|
+| <img src="./docs/images/logo_bailing.png" width="160"> | [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) | Dieses Projekt wurde von [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) inspiriert und auf dessen Basis implementiert |
+| <img src="./docs/images/logo_tenclass.png" width="160"> | [Tenclass](https://www.tenclass.com/) | Dank an [Tenclass](https://www.tenclass.com/) für die Formulierung von Standardkommunikationsprotokollen, Multi-Geräte-Kompatibilitätslösungen und High-Concurrency-Szenario-Praxisdemonstrationen für das Xiaozhi-Ökosystem; für die Bereitstellung vollständiger technischer Dokumentationsunterstützung für dieses Projekt |
+| <img src="./docs/images/logo_xuanfeng.png" width="160"> | [Xuanfeng Technology](https://github.com/Eric0308) | Dank an [Xuanfeng Technology](https://github.com/Eric0308) für den Beitrag des Funktionsaufruf-Frameworks, des MCP-Kommunikationsprotokolls und der plugin-basierten Aufrufmechanismus-Implementierungscode. Durch standardisiertes Befehlsplanungssystem und dynamische Erweiterungsfähigkeiten wird die Interaktionseffizienz und funktionale Erweiterbarkeit von Frontend-Geräten (IoT) erheblich verbessert |
+| <img src="./docs/images/logo_junsen.png" width="160"> | [huangjunsen](https://github.com/huangjunsen0406) | Dank an [huangjunsen](https://github.com/huangjunsen0406) für den Beitrag des `Smart Control Console Mobile`-Moduls, das eine effiziente Steuerung und Echtzeit-Interaktion über mobile Geräte ermöglicht und die Betriebsbequemlichkeit und Verwaltungseffizienz des Systems in mobilen Szenarien erheblich verbessert |
+| <img src="./docs/images/logo_huiyuan.png" width="160"> | [Huiyuan Design](http://ui.kwd988.net/) | Dank an [Huiyuan Design](http://ui.kwd988.net/) für die Bereitstellung professioneller visueller Lösungen für dieses Projekt, unter Verwendung ihrer Design-Praxiserfahrung im Dienst von über tausend Unternehmen, um die Produktbenutzererfahrung dieses Projekts zu stärken |
+| <img src="./docs/images/logo_qinren.png" width="160"> | [Xi'an Qinren Information Technology](https://www.029app.com/) | Dank an [Xi'an Qinren Information Technology](https://www.029app.com/) für die Vertiefung des visuellen Systems dieses Projekts und die Sicherstellung der Konsistenz und Erweiterbarkeit des Gesamtdesignstils in Multi-Szenario-Anwendungen |
+| <img src="./docs/images/logo_contributors.png" width="160"> | [Code-Mitwirkende](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors) | Dank an [alle Code-Mitwirkenden](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors), Ihre Bemühungen haben das Projekt robuster und leistungsfähiger gemacht. |
+
+
+<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>
@@ -6,29 +6,25 @@
 This project is based on human-machine symbiotic intelligence theory and technology to develop intelligent terminal hardware and software systems<br/>providing backend services for the open-source intelligent hardware project
 <a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a><br/>
 Implemented using Python, Java, and Vue according to the <a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">Xiaozhi Communication Protocol</a><br/>
-Supports MCP endpoints and voiceprint recognition
+Support for MQTT+UDP protocol, Websocket protocol, MCP access point, voiceprint recognition, and knowledge base
 </p>

 <p align="center">
-<a href="./README.md">中文</a>
-· <a href="./docs/FAQ.md">FAQ</a>
+<a href="./docs/FAQ.md">FAQ</a>
 · <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">Report Issues</a>
 · <a href="./README.md#%E9%83%A8%E7%BD%B2%E6%96%87%E6%A1%A3">Deployment Docs</a>
 · <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">Release Notes</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-DFE0E5"></a>
+  <a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DBEDFA"></a>
+  <a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
+  <a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
+  <a href="./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/graphs/contributors">
-    <img alt="GitHub Contributors" src="https://img.shields.io/github/contributors/xinnan-tech/xiaozhi-esp32-server?logo=github" />
-  </a>
-  <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">
-    <img alt="Issues" src="https://img.shields.io/github/issues/xinnan-tech/xiaozhi-esp32-server?color=0088ff" />
-  </a>
-  <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/pulls">
-    <img alt="GitHub pull requests" src="https://img.shields.io/github/issues-pr/xinnan-tech/xiaozhi-esp32-server?color=0088ff" />
-  </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>
@@ -38,9 +34,9 @@ Supports MCP endpoints and voiceprint recognition
 </p>

 <p align="center">
-By Professor Siyuan Liu Research and Development Group (South China University of Technology)
+Spearheaded by Professor Siyuan Liu's Team (South China University of Technology)
 </br>
-刘思源教授团队研发（华南理工大学）
+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="South China University of Technology" width="50%">
 </p>
@@ -58,72 +54,72 @@ Want to see the usage effects? Click the videos below 🎥
    <td>
        <a href="https://www.bilibili.com/video/BV1FMFyejExX" target="_blank">
         <picture>
-           <img alt="Xiaozhi ESP32 connecting to own backend model" 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/BV1CDKWemEU6" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1vchQzaEse" target="_blank">
         <picture>
-           <img alt="Custom voice timbre" src="docs/images/demo2.png" />
+           <img alt="速度优化秘诀" src="docs/images/demo6.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1C1tCzUEZh" target="_blank">
         <picture>
-           <img alt="Using Cantonese for communication" src="docs/images/demo3.png" />
+           <img alt="复杂医疗场景" src="docs/images/demo1.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV1pNXWYGEx1" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1zUW5zJEkq" target="_blank">
         <picture>
-           <img alt="Controlling home appliances" src="docs/images/demo5.png" />
+           <img alt="MQTT指令下发" src="docs/images/demo4.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV1kgA2eYEQ9" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1Exu3zqEDe" target="_blank">
         <picture>
-           <img alt="Lowest cost configuration" src="docs/images/demo4.png" />
+           <img alt="声纹识别" src="docs/images/demo14.png" />
         </picture>
        </a>
    </td>
  </tr>
  <tr>
    <td>
-        <a href="https://www.bilibili.com/video/BV1Vy96YCE3R" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1pNXWYGEx1" target="_blank">
         <picture>
-           <img alt="Custom voice timbre" src="docs/images/demo6.png" />
+           <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="Playing music" src="docs/images/demo7.png" />
+           <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="Weather plugin" src="docs/images/demo8.png" />
-         </picture>
-        </a>
-    </td>
-    <td>
-        <a href="https://www.bilibili.com/video/BV178XuYfEpi" target="_blank">
-         <picture>
-           <img alt="IOT command control devices" src="docs/images/demo9.png" />
-         </picture>
-        </a>
-    </td>
-    <td>
-        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
-         <picture>
-           <img alt="News broadcasting" src="docs/images/demo0.png" />
+           <img alt="天气插件" src="docs/images/demo8.png" />
         </picture>
        </a>
    </td>
@@ -132,35 +128,35 @@ Want to see the usage effects? Click the videos below 🎥
    <td>
      <a href="https://www.bilibili.com/video/BV12J7WzBEaH" target="_blank">
         <picture>
-           <img alt="Real-time interruption" src="docs/images/demo10.png" />
+           <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="Photo recognition of objects" src="docs/images/demo12.png" />
+           <img alt="拍照识物品" src="docs/images/demo12.png" />
         </picture>
        </a>
    </td>
    <td>
-      <a href="https://www.bilibili.com/video/BV1TJ7WzzEo6" target="_blank">
+        <a href="https://www.bilibili.com/video/BV1CDKWemEU6" target="_blank">
         <picture>
-           <img alt="Multi-command tasks" src="docs/images/demo11.png" />
+           <img alt="自定义音色" src="docs/images/demo2.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV1ZQKUzYExM" target="_blank">
+        <a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
         <picture>
-           <img alt="MCP endpoint" src="docs/images/demo13.png" />
+           <img alt="使用粤语交流" src="docs/images/demo3.png" />
         </picture>
        </a>
    </td>
    <td>
-        <a href="https://www.bilibili.com/video/BV1Exu3zqEDe" target="_blank">
+        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
         <picture>
-           <img alt="Voiceprint recognition" src="docs/images/demo14.png" />
+           <img alt="播报新闻" src="docs/images/demo0.png" />
         </picture>
        </a>
    </td>
@@ -186,14 +182,16 @@ This project provides two deployment methods. Please choose based on your specif
 #### 🚀 Deployment Method Selection
 | Deployment Method | Features | Applicable Scenarios | Deployment Docs | Configuration Requirements | Video Tutorials | 
 |---------|------|---------|---------|---------|---------|
-| **Simplified Installation** | Intelligent dialogue, IOT, MCP, visual perception | Low-configuration environments, data stored in config files, no database required | [①Docker Version](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②Source Code Deployment](./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)| 2 cores 4GB if using `FunASR`, 2 cores 2GB if all APIs | - | 
-| **Full Module Installation** | Intelligent dialogue, IOT, MCP endpoints, voiceprint recognition, visual perception, OTA, intelligent control console | Complete functionality experience, data stored in database |[①Docker Version](./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) / [②Source Code Deployment](./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) / [③Source Code Deployment Auto-Update Tutorial](./docs/dev-ops-integration.md) | 4 cores 8GB if using `FunASR`, 2 cores 4GB if all APIs| [Local Source Code Startup Video Tutorial](https://www.bilibili.com/video/BV1wBJhz4Ewe) | 
+| **Simplified Installation** | Intelligent dialogue, single agent management | Low-configuration environments, data stored in config files, no database required | [①Docker Version](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②Source Code Deployment](./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)| 2 cores 4GB if using `FunASR`, 2 cores 2GB if all APIs | - | 
+| **Full Module Installation** | Intelligent dialogue, multi-user management, multi-agent management, intelligent console interface operation | Complete functionality experience, data stored in database |[①Docker Version](./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) / [②Source Code Deployment](./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) / [③Source Code Deployment Auto-Update Tutorial](./docs/dev-ops-integration.md) | 4 cores 8GB if using `FunASR`, 2 cores 4GB if all APIs| [Local Source Code Startup Video Tutorial](https://www.bilibili.com/video/BV1wBJhz4Ewe) |

+For frequently asked questions and related tutorials, please refer to [this link](./docs/FAQ.md)

 > 💡 Note: Below is a test platform deployed with the latest code. You can burn and test if needed. Concurrent users: 6, data will be cleared daily.

 ```
 Intelligent Control Console Address: https://2662r3426b.vicp.fun
+Intelligent Control Console Address (H5): https://2662r3426b.vicp.fun/h5/index.html

 Service Test Tool: https://2662r3426b.vicp.fun/test/
 OTA Interface Address: https://2662r3426b.vicp.fun/xiaozhi/ota/
@@ -212,73 +210,71 @@ Websocket Interface Address: wss://2662r3426b.vicp.fun/xiaozhi/v1/

 | Module Name | Entry Level Free Settings | Streaming Configuration |
 |:---:|:---:|:---:|
-| ASR(Speech Recognition) | FunASR(Local) | 👍FunASRServer or 👍DoubaoStreamASR |
-| LLM(Large Model) | ChatGLMLLM(Zhipu glm-4-flash) | 👍DoubaoLLM(Volcano doubao-1-5-pro-32k-250115) |
-| VLLM(Vision Large Model) | ChatGLMVLLM(Zhipu glm-4v-flash) | 👍QwenVLVLLM(Qwen qwen2.5-vl-3b-instructh) |
-| TTS(Speech Synthesis) | ✅LinkeraiTTS(Lingxi streaming) | 👍HuoshanDoubleStreamTTS(Volcano dual-stream speech synthesis) |
+| ASR(Speech Recognition) | FunASR(Local) | 👍XunfeiStreamASR(Xunfei Streaming) |
+| LLM(Large Model) | glm-4-flash(Zhipu) | 👍qwen-flash(Alibaba Bailian) |
+| VLLM(Vision Large Model) | glm-4v-flash(Zhipu) | 👍qwen3.5-flash(Alibaba Bailian) |
+| TTS(Speech Synthesis) | EdgeTTS(Microsoft) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
 | Intent(Intent Recognition) | function_call(Function calling) | function_call(Function calling) |
 | Memory(Memory function) | mem_local_short(Local short-term memory) | mem_local_short(Local short-term memory) |

+If you are concerned about the latency of each component, please refer to the [Xiaozhi Component Performance Test Report](https://github.com/xinnan-tech/xiaozhi-performance-research), and test in your own environment following the test methods in the report.
+
 #### 🔧 Testing Tools
 This project provides the following testing tools to help you verify the system and choose suitable models:

 | Tool Name | Location | Usage Method | Function Description |
 |:---:|:---|:---:|:---:|
 | Audio Interaction Test Tool | main》xiaozhi-server》test》test_page.html | Open directly with Google Chrome | Tests audio playback and reception functions, verifies if Python-side audio processing is normal |
-| Model Response Test Tool 1 | main》xiaozhi-server》performance_tester.py | Execute `python performance_tester.py` | Tests response speed of three core modules: ASR(speech recognition), LLM(large model), TTS(speech synthesis) |
-| Model Response Test Tool 2 | main》xiaozhi-server》performance_tester_vllm.py | Execute `python performance_tester_vllm.py` | Tests VLLM(vision model) response speed |
+| Model Response Test Tool | main》xiaozhi-server》performance_tester.py | Execute `python performance_tester.py` | Tests response speed of three core modules: ASR(speech recognition), LLM(large model), VLLM(vision model), TTS(speech synthesis) |

 > 💡 Note: When testing model speed, only models with configured keys will be tested.

 ---
 ## Feature List ✨
 ### Implemented ✅
-
+![请参考-全模块安装架构图](docs/images/deploy2.png)
 | Feature Module | Description |
 |:---:|:---|
-| Core Architecture | Based on WebSocket and HTTP servers, provides complete console management and authentication system |
+| Core Architecture | Based on [MQTT+UDP gateway](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docs/mqtt-gateway-integration.md), WebSocket and HTTP servers, provides complete console management and authentication system |
 | Voice Interaction | Supports streaming ASR(speech recognition), streaming TTS(speech synthesis), VAD(voice activity detection), supports multi-language recognition and voice processing |
 | Voiceprint Recognition | Supports multi-user voiceprint registration, management, and recognition, processes in parallel with ASR, real-time speaker identity recognition and passes to LLM for personalized responses |
 | Intelligent Dialogue | Supports multiple LLM(large language models), implements intelligent dialogue |
 | Visual Perception | Supports multiple VLLM(vision large models), implements multimodal interaction |
 | Intent Recognition | Supports LLM intent recognition, Function Call function calling, provides plugin-based intent processing mechanism |
-| Memory System | Supports local short-term memory, mem0ai interface memory, with memory summarization functionality |
+| Memory System | Supports local short-term memory, mem0ai interface memory, PowerMem intelligent memory, with memory summarization functionality |
+| Knowledge Base | Supports RAGFlow knowledge base, enabling LLM to judge whether to schedule the knowledge base after receiving the user's question, and then answer the question |
 | Tool Calling | Supports client IOT protocol, client MCP protocol, server MCP protocol, MCP endpoint protocol, custom tool functions |
-| Management Backend | Provides Web management interface, supports user management, system configuration, and device management |
+| Command Delivery | Supports MCP command delivery to ESP32 devices via MQTT protocol from Smart Console |
+| Management Backend | Provides Web management interface, supports user management, system configuration and device management; Supports Simplified Chinese, Traditional Chinese and English display |
 | Testing Tools | Provides performance testing tools, vision model testing tools, and audio interaction testing tools |
 | Deployment Support | Supports Docker deployment and local deployment, provides complete configuration file management |
 | Plugin System | Supports functional plugin extensions, custom plugin development, and plugin hot-loading |

 ### Under Development 🚧

-To learn about specific development plan progress, [click here](https://github.com/users/xinnan-tech/projects/3)
+To learn about specific development plan progress, [click here](https://github.com/users/xinnan-tech/projects/3). For frequently asked questions and related tutorials, please refer to [this link](./docs/FAQ.md)

 If you are a software developer, here is an [Open Letter to Developers](docs/contributor_open_letter.md). Welcome to join!

 ---

 ## Product Ecosystem 👬
-Xiaozhi is an ecosystem. When using this product, you can also check out other excellent projects in this ecosystem
-
-| Project Name | Project Address | Project Description |
-|:---------------------|:--------|:--------|
-| Xiaozhi Android Client | [xiaozhi-android-client](https://github.com/TOM88812/xiaozhi-android-client) | An Android and iOS voice dialogue application based on xiaozhi-server, supporting real-time voice interaction and text dialogue.<br/>Currently a Flutter version, connecting iOS and Android platforms. |
-| Xiaozhi Desktop Client | [py-xiaozhi](https://github.com/Huang-junsen/py-xiaozhi) | This project provides a Python-based AI client for beginners, allowing users to experience Xiaozhi AI functionality through code even without physical hardware conditions. |
-| Xiaozhi Java Server | [xiaozhi-esp32-server-java](https://github.com/joey-zhou/xiaozhi-esp32-server-java) | Xiaozhi open-source backend service Java version is a Java-based open-source project.<br/>It includes frontend and backend services, aiming to provide users with a complete backend service solution. |
+Xiaozhi is an ecosystem. When using this product, you can also check out other [excellent projects](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) in this ecosystem

 ---

 ## Supported Platforms/Components List 📋
-
 ### LLM Language Models

 | Usage Method | Supported Platforms | Free Platforms |
 |:---:|:---:|:---:|
-| OpenAI interface calls | Alibaba Bailian, Volcano Engine Doubao, DeepSeek, Zhipu ChatGLM, Gemini | Zhipu ChatGLM, Gemini |
+| OpenAI interface calls | Alibaba Bailian, Volcano Engine, DeepSeek, Zhipu, Gemini, iFLYTEK | Zhipu, Gemini |
 | Ollama interface calls | Ollama | - |
 | Dify interface calls | Dify | - |
 | FastGPT interface calls | FastGPT | - |
 | Coze interface calls | Coze | - |
+| Xinference interface calls | Xinference | - |
+| HomeAssistant interface calls | HomeAssistant | - |

 In fact, any LLM that supports OpenAI interface calls can be integrated and used.

@@ -298,8 +294,8 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use

 | Usage Method | Supported Platforms | Free Platforms |
 |:---:|:---:|:---:|
-| Interface calls | EdgeTTS, Volcano Engine Doubao TTS, Tencent Cloud, Alibaba Cloud TTS, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi Streaming TTS | Lingxi Streaming TTS, EdgeTTS, CosyVoiceSiliconflow(partial) |
-| Local services | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS |
+| Interface calls | EdgeTTS, iFLYTEK, Volcano Engine, Tencent Cloud, Alibaba Cloud and Bailian, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi Streaming TTS, MinimaxTTS | Lingxi Streaming TTS, EdgeTTS, CosyVoiceSiliconflow(partial) |
+| Local services | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, Index-TTS, PaddleSpeech | Index-TTS, PaddleSpeech, FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3 |

 ---

@@ -316,7 +312,7 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
 | Usage Method | Supported Platforms | Free Platforms |
 |:---:|:---:|:---:|
 | Local use | FunASR, SherpaASR | FunASR, SherpaASR |
-| Interface calls | DoubaoASR, FunASRServer, TencentASR, AliyunASR | FunASRServer |
+| Interface calls | FunASRServer, Volcano Engine, iFLYTEK, Tencent Cloud, Alibaba Cloud, Baidu Cloud, OpenAI ASR | FunASRServer |

 ---

@@ -333,7 +329,9 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
 | Type | Platform Name | Usage Method | Pricing Model | Notes |
 |:------:|:---------------:|:----:|:---------:|:--:|
 | Memory | mem0ai | Interface calls | 1000 times/month quota | |
+| Memory | [powermem](./docs/powermem-integration.md) | Local summarization | Depends on LLM and DB | OceanBase open source, supports intelligent retrieval |
 | Memory | mem_local_short | Local summarization | Free | |
+| Memory | nomem | No memory mode | Free | |

 ---

@@ -343,6 +341,15 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
 |:------:|:-------------:|:----:|:-------:|:---------------------:|
 | Intent | intent_llm | Interface calls | Based on LLM pricing | Recognizes intent through large models, strong generalization |
 | Intent | function_call | Interface calls | Based on LLM pricing | Completes intent through large model function calling, fast speed, good effect |
+| Intent | nointent | No intent mode | Free | Does not perform intent recognition, directly returns dialogue result |
+
+---
+
+### Rag Retrieval-Augmented Generation
+
+| Type | Platform Name | Usage Method | Pricing Model | Notes |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Rag | ragflow | Interface calls | Charged based on tokens consumed for slicing and word segmentation | Utilizes RagFlow's retrieval-augmented generation feature to provide more accurate dialog responses |

 ---

@@ -353,8 +360,10 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
 | <img src="./docs/images/logo_bailing.png" width="160"> | [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) | This project is inspired by [Bailing Voice Dialogue Robot](https://github.com/wwbin2017/bailing) and implemented on its basis |
 | <img src="./docs/images/logo_tenclass.png" width="160"> | [Tenclass](https://www.tenclass.com/) | Thanks to [Tenclass](https://www.tenclass.com/) for formulating standard communication protocols, multi-device compatibility solutions, and high-concurrency scenario practice demonstrations for the Xiaozhi ecosystem; providing full-link technical documentation support for this project |
 | <img src="./docs/images/logo_xuanfeng.png" width="160"> | [Xuanfeng Technology](https://github.com/Eric0308) | Thanks to [Xuanfeng Technology](https://github.com/Eric0308) for contributing function calling framework, MCP communication protocol, and plugin-based calling mechanism implementation code. Through standardized instruction scheduling system and dynamic expansion capabilities, it significantly improves the interaction efficiency and functional extensibility of frontend devices (IoT) |
+| <img src="./docs/images/logo_junsen.png" width="160"> | [huangjunsen](https://github.com/huangjunsen0406) | Thanks to [huangjunsen](https://github.com/huangjunsen0406) for contributing the `Smart Control Console Mobile` module, which enables efficient control and real-time interaction across mobile devices, significantly enhancing the system's operational convenience and management efficiency in mobile scenarios. |
 | <img src="./docs/images/logo_huiyuan.png" width="160"> | [Huiyuan Design](http://ui.kwd988.net/) | Thanks to [Huiyuan Design](http://ui.kwd988.net/) for providing professional visual solutions for this project, using their design practical experience serving over a thousand enterprises to empower this project's product user experience |
 | <img src="./docs/images/logo_qinren.png" width="160"> | [Xi'an Qinren Information Technology](https://www.029app.com/) | Thanks to [Xi'an Qinren Information Technology](https://www.029app.com/) for deepening this project's visual system, ensuring consistency and extensibility of overall design style in multi-scenario applications |
+| <img src="./docs/images/logo_contributors.png" width="160"> | [Code Contributors](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors) | Thanks to [all code contributors](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors), your efforts have made the project more robust and powerful. |


 <a href="https://star-history.com/#xinnan-tech/xiaozhi-esp32-server&Date">
@@ -0,0 +1,376 @@
+[![Banners](docs/images/banner1.png)](https://github.com/xinnan-tech/xiaozhi-esp32-server)
+
+<h1 align="center">Serviço Backend Xiaozhi xiaozhi-esp32-server</h1>
+
+<p align="center">
+Este projeto é baseado na teoria e tecnologia de inteligência simbiótica humano-máquina para desenvolver sistemas inteligentes de hardware e software para terminais<br/>fornecendo serviços de backend para o projeto de hardware inteligente de código aberto
+<a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a><br/>
+Implementado usando Python, Java e Vue de acordo com o <a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">Protocolo de Comunicação Xiaozhi</a><br/>
+Suporte ao protocolo MQTT+UDP, protocolo WebSocket, ponto de acesso MCP, reconhecimento de impressão vocal e base de conhecimento
+</p>
+
+<p align="center">
+<a href="./docs/FAQ.md">Perguntas Frequentes</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">Reportar Problemas</a>
+· <a href="./README.md#%E9%83%A8%E7%BD%B2%E6%96%87%E6%A1%A3">Documentação de Implantação</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">Notas de Lançamento</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-DFE0E5"></a>
+  <a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
+  <a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
+  <a href="./README_pt_BR.md"><img alt="Português (Brasil)" src="https://img.shields.io/badge/Português (Brasil)-DBEDFA"></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">
+Liderado pela Equipe do Professor Siyuan Liu (Universidade de Tecnologia do Sul da China)
+</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="Universidade de Tecnologia do Sul da China (华南理工大学)" width="50%">
+</p>
+
+---
+
+## Público-Alvo 👥
+
+Este projeto requer dispositivos de hardware ESP32 para funcionar. Se você adquiriu hardware relacionado ao ESP32, conectou-se com sucesso ao serviço backend implantado pelo Brother Xia e deseja construir seu próprio serviço backend `xiaozhi-esp32` de forma independente, então este projeto é perfeito para você.
+
+Quer ver os efeitos de uso? Clique nos vídeos abaixo 🎥
+
+<table>
+  <tr>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1FMFyejExX" target="_blank">
+         <picture>
+           <img alt="Experiência de velocidade de resposta" src="docs/images/demo9.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1vchQzaEse" target="_blank">
+         <picture>
+           <img alt="Segredo da otimização de velocidade" src="docs/images/demo6.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1C1tCzUEZh" target="_blank">
+         <picture>
+           <img alt="Cenário médico complexo" src="docs/images/demo1.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1zUW5zJEkq" target="_blank">
+         <picture>
+           <img alt="Envio de comandos MQTT" src="docs/images/demo4.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1Exu3zqEDe" target="_blank">
+         <picture>
+           <img alt="Reconhecimento de impressão vocal" src="docs/images/demo14.png" />
+         </picture>
+        </a>
+    </td>
+  </tr>
+  <tr>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1pNXWYGEx1" target="_blank">
+         <picture>
+           <img alt="Controle de interruptores de eletrodomésticos" src="docs/images/demo5.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1ZQKUzYExM" target="_blank">
+         <picture>
+           <img alt="Ponto de acesso MCP" src="docs/images/demo13.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+      <a href="https://www.bilibili.com/video/BV1TJ7WzzEo6" target="_blank">
+         <picture>
+           <img alt="Tarefas com múltiplos comandos" src="docs/images/demo11.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1VC96Y5EMH" target="_blank">
+         <picture>
+           <img alt="Reproduzir música" src="docs/images/demo7.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1Z8XuYZEAS" target="_blank">
+         <picture>
+           <img alt="Plugin de clima" src="docs/images/demo8.png" />
+         </picture>
+        </a>
+    </td>
+  </tr>
+  <tr>
+    <td>
+      <a href="https://www.bilibili.com/video/BV12J7WzBEaH" target="_blank">
+         <picture>
+           <img alt="Interrupção em tempo real" src="docs/images/demo10.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+      <a href="https://www.bilibili.com/video/BV1Co76z7EvK" target="_blank">
+         <picture>
+           <img alt="Fotografar e identificar objetos" src="docs/images/demo12.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1CDKWemEU6" target="_blank">
+         <picture>
+           <img alt="Timbre de voz personalizado" src="docs/images/demo2.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
+         <picture>
+           <img alt="Comunicação em cantonês" src="docs/images/demo3.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
+         <picture>
+           <img alt="Transmissão de notícias" src="docs/images/demo0.png" />
+         </picture>
+        </a>
+    </td>
+  </tr>
+</table>
+
+---
+
+## Avisos ⚠️
+
+1. Este projeto é um software de código aberto. Este software não possui parceria comercial com nenhum provedor de serviços de API de terceiros (incluindo, mas não se limitando a reconhecimento de fala, modelos de linguagem, síntese de voz e outras plataformas) com os quais se conecta, e não fornece nenhuma forma de garantia quanto à qualidade de serviço ou segurança financeira desses provedores. Recomenda-se que os usuários priorizem provedores de serviço com licenças comerciais relevantes e leiam cuidadosamente seus termos de serviço e políticas de privacidade. Este software não armazena nenhuma chave de conta, não participa de fluxos de fundos e não assume o risco de perda de fundos recarregados.
+
+2. A funcionalidade deste projeto não está completa e não passou por avaliação de segurança de rede. Por favor, não o utilize em ambientes de produção. Se você implantar este projeto para fins de aprendizado em um ambiente de rede pública, certifique-se de que as medidas de proteção necessárias estejam em vigor.
+
+---
+
+## Documentação de Implantação
+
+![Banners](docs/images/banner2.png)
+
+Este projeto oferece dois métodos de implantação. Por favor, escolha de acordo com suas necessidades específicas:
+
+#### 🚀 Seleção do Método de Implantação
+| Método de Implantação | Funcionalidades | Cenários Aplicáveis | Documentação de Implantação | Requisitos de Configuração | Tutoriais em Vídeo |
+|---------|------|---------|---------|---------|---------|
+| **Instalação Simplificada** | Diálogo inteligente, gerenciamento de agente único | Ambientes de baixa configuração, dados armazenados em arquivos de configuração, sem necessidade de banco de dados | [①Versão Docker](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②Implantação via Código-Fonte](./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)| 2 núcleos 4GB se usar `FunASR`, 2 núcleos 2GB se todas APIs | - |
+| **Instalação de Módulo Completo** | Diálogo inteligente, gerenciamento multiusuário, gerenciamento de múltiplos agentes, operação de interface do console inteligente | Experiência com funcionalidade completa, dados armazenados em banco de dados |[①Versão Docker](./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) / [②Implantação via Código-Fonte](./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) / [③Tutorial de Atualização Automática via Código-Fonte](./docs/dev-ops-integration.md) | 4 núcleos 8GB se usar `FunASR`, 2 núcleos 4GB se todas APIs| [Tutorial em Vídeo de Inicialização via Código-Fonte Local](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
+
+Perguntas frequentes e tutoriais relacionados podem ser consultados [neste link](./docs/FAQ.md)
+
+> 💡 Nota: Abaixo está uma plataforma de teste implantada com o código mais recente. Você pode gravar e testar se necessário. Usuários simultâneos: 6, os dados serão limpos diariamente.
+
+```
+Endereço do Console de Controle Inteligente: https://2662r3426b.vicp.fun
+Endereço do Console de Controle Inteligente (H5): https://2662r3426b.vicp.fun/h5/index.html
+
+Ferramenta de Teste de Serviço: https://2662r3426b.vicp.fun/test/
+Endereço da Interface OTA: https://2662r3426b.vicp.fun/xiaozhi/ota/
+Endereço da Interface WebSocket: wss://2662r3426b.vicp.fun/xiaozhi/v1/
+```
+
+#### 🚩 Descrição e Recomendações de Configuração
+> [!Note]
+> Este projeto oferece dois esquemas de configuração:
+>
+> 1. `Configurações Gratuitas Nível Básico`: Adequado para uso pessoal e doméstico, todos os componentes utilizam soluções gratuitas, sem necessidade de pagamento adicional.
+>
+> 2. `Configuração de Streaming`: Adequado para demonstrações, treinamentos, cenários com mais de 2 usuários simultâneos, etc. Utiliza tecnologia de processamento em streaming para velocidade de resposta mais rápida e melhor experiência.
+>
+> A partir da versão `0.5.2`, o projeto suporta configuração de streaming. Em comparação com versões anteriores, a velocidade de resposta é melhorada em aproximadamente `2,5 segundos`, melhorando significativamente a experiência do usuário.
+
+| Nome do Módulo | Configurações Gratuitas Nível Básico | Configuração de Streaming |
+|:---:|:---:|:---:|
+| ASR(Reconhecimento de Fala) | FunASR(Local) | 👍XunfeiStreamASR(Xunfei Streaming) |
+| LLM(Modelo de Linguagem) | glm-4-flash(Zhipu) | 👍qwen-flash(Alibaba Bailian) |
+| VLLM(Modelo de Visão) | glm-4v-flash(Zhipu) | 👍qwen3.5-flash(Alibaba Bailian) |
+| TTS(Síntese de Voz) | EdgeTTS(Microsoft) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
+| Intent(Reconhecimento de Intenção) | function_call(Chamada de função) | function_call(Chamada de função) |
+| Memory(Função de Memória) | mem_local_short(Memória local de curto prazo) | mem_local_short(Memória local de curto prazo) |
+
+Se você está preocupado com o tempo de resposta de cada componente, consulte o [Relatório de Teste de Desempenho dos Componentes Xiaozhi](https://github.com/xinnan-tech/xiaozhi-performance-research), e teste em seu próprio ambiente seguindo os métodos de teste do relatório.
+
+#### 🔧 Ferramentas de Teste
+Este projeto fornece as seguintes ferramentas de teste para ajudá-lo a verificar o sistema e escolher modelos adequados:
+
+| Nome da Ferramenta | Localização | Método de Uso | Descrição da Função |
+|:---:|:---|:---:|:---:|
+| Ferramenta de Teste de Interação por Áudio | main》xiaozhi-server》test》test_page.html | Abrir diretamente com Google Chrome | Testa as funções de reprodução e recepção de áudio, verifica se o processamento de áudio no lado Python está normal |
+| Ferramenta de Teste de Resposta de Modelo | main》xiaozhi-server》performance_tester.py | Execute `python performance_tester.py` | Testa a velocidade de resposta dos três módulos principais: ASR(reconhecimento de fala), LLM(modelo de linguagem), VLLM(modelo de visão), TTS(síntese de voz) |
+
+> 💡 Nota: Ao testar a velocidade dos modelos, apenas os modelos com chaves configuradas serão testados.
+
+---
+## Lista de Funcionalidades ✨
+### Implementado ✅
+![请参考-全模块安装架构图](docs/images/deploy2.png)
+| Módulo de Funcionalidade | Descrição |
+|:---:|:---|
+| Arquitetura Principal | Baseado em [gateway MQTT+UDP](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docs/mqtt-gateway-integration.md), servidores WebSocket e HTTP, fornece sistema completo de gerenciamento de console e autenticação |
+| Interação por Voz | Suporta ASR em streaming (reconhecimento de fala), TTS em streaming (síntese de voz), VAD (detecção de atividade vocal), suporta reconhecimento multilíngue e processamento de voz |
+| Reconhecimento de Impressão Vocal | Suporta registro, gerenciamento e reconhecimento de impressão vocal de múltiplos usuários, processa em paralelo com o ASR, reconhecimento de identidade do falante em tempo real e repassa ao LLM para respostas personalizadas |
+| Diálogo Inteligente | Suporta múltiplos LLM (modelos de linguagem de grande porte), implementa diálogo inteligente |
+| Percepção Visual | Suporta múltiplos VLLM (modelos de visão de grande porte), implementa interação multimodal |
+| Reconhecimento de Intenção | Suporta reconhecimento de intenção por LLM, Function Call (chamada de função), fornece mecanismo de processamento de intenção baseado em plugins |
+| Sistema de Memória | Suporta memória local de curto prazo, memória via interface mem0ai, memória inteligente PowerMem, com funcionalidade de resumo de memória |
+| Base de Conhecimento | Suporta base de conhecimento RAGFlow, permitindo que o LLM julgue se deve acionar a base de conhecimento após receber a pergunta do usuário, e então responda à pergunta |
+| Chamada de Ferramentas | Suporta protocolo IOT do cliente, protocolo MCP do cliente, protocolo MCP do servidor, protocolo de endpoint MCP, funções de ferramentas personalizadas |
+| Envio de Comandos | Suporta envio de comandos MCP para dispositivos ESP32 via protocolo MQTT a partir do Console Inteligente |
+| Backend de Gerenciamento | Fornece interface de gerenciamento Web, suporta gerenciamento de usuários, configuração do sistema e gerenciamento de dispositivos; Suporta exibição em Chinês Simplificado, Chinês Tradicional e Inglês |
+| Ferramentas de Teste | Fornece ferramentas de teste de desempenho, ferramentas de teste de modelo de visão e ferramentas de teste de interação por áudio |
+| Suporte à Implantação | Suporta implantação via Docker e implantação local, fornece gerenciamento completo de arquivos de configuração |
+| Sistema de Plugins | Suporta extensões de plugins funcionais, desenvolvimento de plugins personalizados e carregamento dinâmico de plugins |
+
+### Em Desenvolvimento 🚧
+
+Para conhecer o progresso específico do plano de desenvolvimento, [clique aqui](https://github.com/users/xinnan-tech/projects/3). Perguntas frequentes e tutoriais relacionados podem ser consultados [neste link](./docs/FAQ.md)
+
+Se você é um desenvolvedor de software, aqui está uma [Carta Aberta aos Desenvolvedores](docs/contributor_open_letter.md). Seja bem-vindo a participar!
+
+---
+
+## Ecossistema do Produto 👬
+Xiaozhi é um ecossistema. Ao utilizar este produto, você também pode conferir outros [projetos excelentes](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) neste ecossistema
+
+---
+
+## Lista de Plataformas/Componentes Suportados 📋
+### LLM Modelos de Linguagem
+
+| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
+|:---:|:---:|:---:|
+| Chamadas via interface OpenAI | Alibaba Bailian, Volcano Engine, DeepSeek, Zhipu, Gemini, iFLYTEK | Zhipu, Gemini |
+| Chamadas via interface Ollama | Ollama | - |
+| Chamadas via interface Dify | Dify | - |
+| Chamadas via interface FastGPT | FastGPT | - |
+| Chamadas via interface Coze | Coze | - |
+| Chamadas via interface Xinference | Xinference | - |
+| Chamadas via interface HomeAssistant | HomeAssistant | - |
+
+Na verdade, qualquer LLM que suporte chamadas via interface openai pode ser integrado e utilizado.
+
+---
+
+### VLLM Modelos de Visão
+
+| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
+|:---:|:---:|:---:|
+| Chamadas via interface OpenAI | Alibaba Bailian, Zhipu ChatGLMVLLM | Zhipu ChatGLMVLLM |
+
+Na verdade, qualquer VLLM que suporte chamadas via interface OpenAI pode ser integrado e utilizado.
+
+---
+
+### TTS Síntese de Voz
+
+| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
+|:---:|:---:|:---:|
+| Chamadas via interface | EdgeTTS, iFLYTEK, Volcano Engine, Tencent Cloud, Alibaba Cloud e Bailian, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi Streaming TTS, MinimaxTTS | Lingxi Streaming TTS, EdgeTTS, CosyVoiceSiliconflow(parcial) |
+| Serviços locais | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, Index-TTS, PaddleSpeech | Index-TTS, PaddleSpeech, FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3 |
+
+---
+
+### VAD Detecção de Atividade Vocal
+
+| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
+|:---:|:---------:|:----:|:----:|:--:|
+| VAD | SileroVAD | Uso local | Gratuito | |
+
+---
+
+### ASR Reconhecimento de Fala
+
+| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
+|:---:|:---:|:---:|
+| Uso local | FunASR, SherpaASR | FunASR, SherpaASR |
+| Chamadas via interface | FunASRServer, Volcano Engine, iFLYTEK, Tencent Cloud, Alibaba Cloud, Baidu Cloud, OpenAI ASR | FunASRServer |
+
+---
+
+### Reconhecimento de Impressão Vocal
+
+| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
+|:---:|:---:|:---:|
+| Uso local | 3D-Speaker | 3D-Speaker |
+
+---
+
+### Armazenamento de Memória
+
+| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
+|:------:|:---------------:|:----:|:---------:|:--:|
+| Memória | mem0ai | Chamadas via interface | Cota de 1000 vezes/mês | |
+| Memória | [powermem](./docs/powermem-integration.md) | Resumo local | Depende do LLM e BD | OceanBase de código aberto, suporta busca inteligente |
+| Memória | mem_local_short | Resumo local | Gratuito | |
+| Memória | nomem | Modo sem memória | Gratuito | |
+
+---
+
+### Reconhecimento de Intenção
+
+| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Intenção | intent_llm | Chamadas via interface | Baseado no preço do LLM | Reconhece intenção através de modelos de linguagem, forte generalização |
+| Intenção | function_call | Chamadas via interface | Baseado no preço do LLM | Completa a intenção através de chamada de função do modelo de linguagem, velocidade rápida, bom resultado |
+| Intenção | nointent | Modo sem intenção | Gratuito | Não realiza reconhecimento de intenção, retorna diretamente o resultado do diálogo |
+
+---
+
+### RAG Geração Aumentada por Recuperação
+
+| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| RAG | ragflow | Chamadas via interface | Cobrado com base nos tokens consumidos para fatiamento e segmentação de palavras | Utiliza o recurso de geração aumentada por recuperação do RagFlow para fornecer respostas de diálogo mais precisas |
+
+---
+
+## Agradecimentos 🙏
+
+| Logo | Projeto/Empresa | Descrição |
+|:---:|:---:|:---|
+| <img src="./docs/images/logo_bailing.png" width="160"> | [Robô de Diálogo por Voz Bailing](https://github.com/wwbin2017/bailing) | Este projeto foi inspirado pelo [Robô de Diálogo por Voz Bailing](https://github.com/wwbin2017/bailing) e implementado com base nele |
+| <img src="./docs/images/logo_tenclass.png" width="160"> | [Tenclass](https://www.tenclass.com/) | Agradecimentos à [Tenclass](https://www.tenclass.com/) por formular protocolos de comunicação padrão, soluções de compatibilidade multidispositivo e demonstrações práticas de cenários de alta concorrência para o ecossistema Xiaozhi; fornecendo suporte completo de documentação técnica para este projeto |
+| <img src="./docs/images/logo_xuanfeng.png" width="160"> | [Xuanfeng Technology (玄凤科技)](https://github.com/Eric0308) | Agradecimentos à [Xuanfeng Technology](https://github.com/Eric0308) por contribuir com o framework de chamada de função, protocolo de comunicação MCP e implementação do mecanismo de chamada baseado em plugins. Através de um sistema padronizado de agendamento de instruções e capacidades de expansão dinâmica, melhora significativamente a eficiência de interação e extensibilidade funcional dos dispositivos de frontend (IoT) |
+| <img src="./docs/images/logo_junsen.png" width="160"> | [huangjunsen](https://github.com/huangjunsen0406) | Agradecimentos a [huangjunsen](https://github.com/huangjunsen0406) por contribuir com o módulo `Console de Controle Inteligente Mobile`, que permite controle eficiente e interação em tempo real em dispositivos móveis, melhorando significativamente a conveniência operacional e a eficiência de gerenciamento do sistema em cenários móveis. |
+| <img src="./docs/images/logo_huiyuan.png" width="160"> | [Huiyuan Design (汇远设计)](http://ui.kwd988.net/) | Agradecimentos à [Huiyuan Design](http://ui.kwd988.net/) por fornecer soluções visuais profissionais para este projeto, utilizando sua experiência prática de design atendendo mais de mil empresas para potencializar a experiência do usuário deste produto |
+| <img src="./docs/images/logo_qinren.png" width="160"> | [Xi'an Qinren Information Technology (西安勤人信息科技)](https://www.029app.com/) | Agradecimentos à [Xi'an Qinren Information Technology](https://www.029app.com/) por aprofundar o sistema visual deste projeto, garantindo consistência e extensibilidade do estilo de design geral em aplicações de múltiplos cenários |
+| <img src="./docs/images/logo_contributors.png" width="160"> | [Contribuidores de Código](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors) | Agradecimentos a [todos os contribuidores de código](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors), seus esforços tornaram o projeto mais robusto e poderoso. |
+
+
+<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>
@@ -0,0 +1,377 @@
+[![Banners](docs/images/banner1.png)](https://github.com/xinnan-tech/xiaozhi-esp32-server)
+
+<h1 align="center">Dịch vụ Backend Xiaozhi xiaozhi-esp32-server</h1>
+
+<p align="center">
+Dự án này dựa trên lý thuyết và công nghệ trí tuệ cộng sinh người-máy để phát triển hệ thống phần mềm và phần cứng thiết bị đầu cuối thông minh<br/>Cung cấp dịch vụ backend cho dự án phần cứng thông minh mã nguồn mở
+<a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a><br/>
+Được triển khai bằng Python, Java, Vue theo <a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">giao thức truyền thông Xiaozhi</a><br/>
+Hỗ trợ giao thức MQTT+UDP, giao thức Websocket, điểm truy cập MCP, nhận dạng giọng nói và kho tri thức
+</p>
+
+<p align="center">
+<a href="./docs/FAQ.md">Câu hỏi thường gặp</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">Báo cáo vấn đề</a>
+· <a href="./README.md#%E9%83%A8%E7%BD%B2%E6%96%87%E6%A1%A3">Tài liệu triển khai</a>
+· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">Nhật ký cập nhật</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-DFE0E5"></a>
+  <a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DBEDFA"></a>
+  <a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
+  <a href="./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>
+Được dẫn dắt bởi nhóm Giáo sư Lưu Tư Nguyên (Đại học Bách khoa Nam Trung Quốc)
+</br>
+<img src="./docs/images/hnlg.jpg" alt="华南理工大学" width="50%">
+</p>
+
+---
+
+## Người dùng phù hợp 👥
+
+Dự án này cần được sử dụng cùng với thiết bị phần cứng ESP32. Nếu bạn đã mua phần cứng liên quan đến ESP32, đã thành công kết nối với dịch vụ backend do anh Xia triển khai, và muốn xây dựng dịch vụ backend `xiaozhi-esp32` riêng của mình, thì dự án này rất phù hợp với bạn.
+
+Muốn xem hiệu quả sử dụng? Hãy xem video 🎥
+
+<table>
+  <tr>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1FMFyejExX" target="_blank">
+         <picture>
+           <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>
+    <td>
+        <a href="https://www.bilibili.com/video/BV1CDKWemEU6" target="_blank">
+         <picture>
+           <img alt="自定义音色" src="docs/images/demo2.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
+         <picture>
+           <img alt="使用粤语交流" src="docs/images/demo3.png" />
+         </picture>
+        </a>
+    </td>
+    <td>
+        <a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
+         <picture>
+           <img alt="播报新闻" src="docs/images/demo0.png" />
+         </picture>
+        </a>
+    </td>
+  </tr>
+</table>
+
+---
+
+## Cảnh báo ⚠️
+
+1. Dự án này là phần mềm mã nguồn mở, phần mềm này không có quan hệ hợp tác thương mại với bất kỳ nhà cung cấp dịch vụ API bên thứ ba nào (bao gồm nhưng không giới hạn ở các nền tảng nhận dạng giọng nói, mô hình lớn, tổng hợp giọng nói, v.v.), và không đảm bảo chất lượng dịch vụ cũng như an toàn tài chính của họ.
+Khuyến nghị người dùng ưu tiên lựa chọn nhà cung cấp dịch vụ có giấy phép kinh doanh liên quan và đọc kỹ thỏa thuận dịch vụ và chính sách bảo mật của họ. Phần mềm này không lưu trữ bất kỳ khóa tài khoản nào, không tham gia vào luồng tiền và không chịu rủi ro mất tiền nạp.
+
+2. Chức năng của dự án này chưa hoàn thiện và chưa qua đánh giá bảo mật mạng, vui lòng không sử dụng trong môi trường sản xuất. Nếu bạn triển khai dự án này trong môi trường mạng công cộng để học tập, vui lòng thực hiện các biện pháp bảo vệ cần thiết.
+
+---
+
+## Tài liệu triển khai
+
+![Banners](docs/images/banner2.png)
+
+Dự án này cung cấp hai phương pháp triển khai, vui lòng chọn theo nhu cầu cụ thể của bạn:
+
+#### 🚀 Lựa chọn phương pháp triển khai
+| Phương pháp triển khai | Đặc điểm | Tình huống áp dụng | Tài liệu triển khai | Yêu cầu cấu hình | Video hướng dẫn |
+|---------|------|---------|---------|---------|---------|
+| **Cài đặt tối giản** | Đối thoại thông minh, quản lý đơn tác nhân | Môi trường cấu hình thấp, dữ liệu lưu trong tệp cấu hình, không cần cơ sở dữ liệu | [①Phiên bản Docker](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②Triển khai mã nguồn](./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)| 2 nhân 4GB nếu dùng `FunASR`, 2 nhân 2GB nếu toàn API | - |
+| **Cài đặt toàn bộ module** | Đối thoại thông minh, quản lý đa người dùng, quản lý đa tác nhân, bảng điều khiển thông minh | Trải nghiệm đầy đủ tính năng, dữ liệu lưu trong cơ sở dữ liệu |[①Phiên bản Docker](./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) / [②Triển khai mã nguồn](./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) / [③Hướng dẫn tự động cập nhật triển khai mã nguồn](./docs/dev-ops-integration.md) | 4 nhân 8GB nếu dùng `FunASR`, 2 nhân 4GB nếu toàn API| [Video hướng dẫn khởi động mã nguồn cục bộ](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
+
+Câu hỏi thường gặp và hướng dẫn liên quan, vui lòng tham khảo [liên kết này](./docs/FAQ.md)
+
+> 💡 Gợi ý: Dưới đây là nền tảng thử nghiệm được triển khai theo mã mới nhất, có thể flash để thử nghiệm nếu cần, đồng thời là 6, dữ liệu sẽ được xóa mỗi ngày,
+
+```
+Địa chỉ bảng điều khiển thông minh: https://2662r3426b.vicp.fun
+Bảng điều khiển thông minh (phiên bản h5): https://2662r3426b.vicp.fun/h5/index.html
+
+Công cụ kiểm tra dịch vụ: https://2662r3426b.vicp.fun/test/
+Địa chỉ giao diện OTA: https://2662r3426b.vicp.fun/xiaozhi/ota/
+Địa chỉ giao diện Websocket: wss://2662r3426b.vicp.fun/xiaozhi/v1/
+```
+
+#### 🚩 Mô tả và khuyến nghị cấu hình
+> [!Note]
+> Dự án này cung cấp hai phương án cấu hình:
+>
+> 1. Cấu hình `Miễn phí hoàn toàn cho người mới`: Phù hợp với sử dụng gia đình cá nhân, tất cả các thành phần đều sử dụng phương án miễn phí, không cần thanh toán thêm.
+>
+> 2. `Cấu hình streaming`: Phù hợp với demo, đào tạo, hơn 2 đồng thời, v.v., sử dụng công nghệ xử lý streaming, tốc độ phản hồi nhanh hơn, trải nghiệm tốt hơn.
+>
+> Từ phiên bản `0.5.2`, dự án hỗ trợ cấu hình streaming, so với phiên bản đầu, tốc độ phản hồi cải thiện khoảng `2.5 giây`, cải thiện đáng kể trải nghiệm người dùng.
+
+| Tên module | Cài đặt miễn phí cho người mới | Cấu hình streaming |
+|:---:|:---:|:---:|
+| ASR(Nhận dạng giọng nói) | FunASR(Local) | 👍XunfeiStreamASR(Xunfei Streaming) |
+| LLM(Mô hình lớn) | glm-4-flash(Zhipu) | 👍qwen-flash(Alibaba Bailian) |
+| VLLM(Mô hình lớn thị giác) | glm-4v-flash(Zhipu) | 👍qwen3.5-flash(Alibaba Bailian) |
+| TTS(Tổng hợp giọng nói) | EdgeTTS(Microsoft) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
+| Intent(Nhận dạng ý định) | function_call(Gọi hàm) | function_call(Gọi hàm) |
+| Memory(Chức năng bộ nhớ) | mem_local_short(Bộ nhớ ngắn hạn cục bộ) | mem_local_short(Bộ nhớ ngắn hạn cục bộ) |
+
+Nếu bạn quan tâm đến thời gian của từng thành phần, vui lòng xem [Báo cáo kiểm tra hiệu suất các thành phần Xiaozhi](https://github.com/xinnan-tech/xiaozhi-performance-research), có thể kiểm tra thực tế trong môi trường của bạn theo phương pháp kiểm tra trong báo cáo.
+
+#### 🔧 Công cụ kiểm tra
+Dự án này cung cấp các công cụ kiểm tra sau để giúp bạn xác minh hệ thống và chọn mô hình phù hợp:
+
+| Tên công cụ | Vị trí | Phương pháp sử dụng | Mô tả chức năng |
+|:---:|:---|:---:|:---:|
+| Công cụ kiểm tra tương tác âm thanh | main》xiaozhi-server》test》test_page.html | Mở trực tiếp bằng trình duyệt Google Chrome | Kiểm tra chức năng phát và nhận âm thanh, xác minh xử lý âm thanh phía Python có bình thường không |
+| Công cụ kiểm tra phản hồi mô hình | main》xiaozhi-server》performance_tester.py | Thực hiện `python performance_tester.py` | Kiểm tra tốc độ phản hồi của ba module cốt lõi ASR(Nhận dạng giọng nói), LLM(Mô hình lớn), VLLM(Mô hình thị giác), TTS(Tổng hợp giọng nói) |
+
+> 💡 Gợi ý: Khi kiểm tra tốc độ mô hình, chỉ kiểm tra các mô hình đã cấu hình khóa.
+
+---
+## Danh sách tính năng ✨
+### Đã thực hiện ✅
+![请参考-全模块安装架构图](docs/images/deploy2.png)
+| Module chức năng | Mô tả |
+|:---:|:---|
+| Kiến trúc cốt lõi | Dựa trên [cổng MQTT+UDP](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docs/mqtt-gateway-integration.md), WebSocket, máy chủ HTTP, cung cấp hệ thống quản lý bảng điều khiển và xác thực hoàn chỉnh |
+| Tương tác giọng nói | Hỗ trợ ASR streaming(Nhận dạng giọng nói), TTS streaming(Tổng hợp giọng nói), VAD(Phát hiện hoạt động giọng nói), hỗ trợ nhận dạng đa ngôn ngữ và xử lý giọng nói |
+| Nhận dạng vân giọng | Hỗ trợ đăng ký, quản lý và nhận dạng vân giọng đa người dùng, xử lý song song với ASR, nhận dạng danh tính người nói theo thời gian thực và truyền cho LLM để phản hồi cá nhân hóa |
+| Đối thoại thông minh | Hỗ trợ nhiều LLM(Mô hình ngôn ngữ lớn), thực hiện đối thoại thông minh |
+| Cảm nhận thị giác | Hỗ trợ nhiều VLLM(Mô hình lớn thị giác), thực hiện tương tác đa phương thức |
+| Nhận dạng ý định | Hỗ trợ nhận dạng ý định mô hình lớn gắn ngoài, gọi hàm tự chủ mô hình lớn, cung cấp cơ chế xử lý ý định dạng plugin |
+| Hệ thống bộ nhớ | Hỗ trợ bộ nhớ ngắn hạn cục bộ, bộ nhớ giao diện mem0ai, bộ nhớ thông minh PowerMem, có chức năng tóm tắt bộ nhớ |
+| Kho tri thức | Hỗ trợ kho tri thức RAGFlow, cho phép mô hình lớn đánh giá cần gọi kho tri thức trước khi trả lời |
+| Gọi công cụ | Hỗ trợ giao thức IOT phía client, giao thức MCP phía client, giao thức MCP phía server, giao thức điểm truy cập MCP, hàm công cụ tùy chỉnh |
+| Gửi lệnh | Dựa vào giao thức MQTT, hỗ trợ gửi lệnh MCP từ bảng điều khiển thông minh xuống thiết bị ESP32 |
+| Backend quản lý | Cung cấp giao diện quản lý Web, hỗ trợ quản lý người dùng, cấu hình hệ thống và quản lý thiết bị; giao diện hỗ trợ hiển thị tiếng Trung giản thể, tiếng Trung phồn thể, tiếng Anh |
+| Công cụ kiểm tra | Cung cấp công cụ kiểm tra hiệu suất, công cụ kiểm tra mô hình thị giác và công cụ kiểm tra tương tác âm thanh |
+| Hỗ trợ triển khai | Hỗ trợ triển khai Docker và triển khai cục bộ, cung cấp quản lý tệp cấu hình hoàn chỉnh |
+| Hệ thống plugin | Hỗ trợ mở rộng plugin chức năng, phát triển plugin tùy chỉnh và hot loading plugin |
+
+### Đang phát triển 🚧
+
+Muốn hiểu tiến độ kế hoạch phát triển cụ thể, [vui lòng nhấp vào đây](https://github.com/users/xinnan-tech/projects/3). Câu hỏi thường gặp và hướng dẫn liên quan, vui lòng tham khảo [liên kết này](./docs/FAQ.md)
+
+Nếu bạn là một nhà phát triển phần mềm, đây có một [Lá thư mở gửi các nhà phát triển](docs/contributor_open_letter.md), chào mừng tham gia!
+
+---
+
+## Hệ sinh thái sản phẩm 👬
+Xiaozhi là một hệ sinh thái, khi bạn sử dụng sản phẩm này, bạn cũng có thể xem các [dự án xuất sắc](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) khác trong hệ sinh thái này
+
+---
+
+## Danh sách nền tảng/thành phần được dự án này hỗ trợ 📋
+### LLM Mô hình ngôn ngữ
+
+| Phương pháp sử dụng | Nền tảng hỗ trợ | Nền tảng miễn phí |
+|:---:|:---:|:---:|
+| Gọi giao diện openai | Alibaba Bailian, Volcano Engine, DeepSeek, Zhipu, Gemini, iFlytek | Zhipu, Gemini |
+| Gọi giao diện ollama | Ollama | - |
+| Gọi giao diện dify | Dify | - |
+| Gọi giao diện fastgpt | Fastgpt | - |
+| Gọi giao diện coze | Coze | - |
+| Gọi giao diện xinference | Xinference | - |
+| Gọi giao diện homeassistant | HomeAssistant | - |
+
+Trên thực tế, bất kỳ LLM nào hỗ trợ gọi giao diện openai đều có thể truy cập sử dụng.
+
+---
+
+### VLLM Mô hình thị giác
+
+| Phương pháp sử dụng | Nền tảng hỗ trợ | Nền tảng miễn phí |
+|:---:|:---:|:---:|
+| Gọi giao diện openai | Alibaba Bailian, Zhipu ChatGLMVLLM | Zhipu ChatGLMVLLM |
+
+Trên thực tế, bất kỳ VLLM nào hỗ trợ gọi giao diện openai đều có thể truy cập sử dụng.
+
+---
+
+### TTS Tổng hợp giọng nói
+
+| Phương pháp sử dụng | Nền tảng hỗ trợ | Nền tảng miễn phí |
+|:---:|:---:|:---:|
+| Gọi giao diện | EdgeTTS, iFlytek, Volcano Engine, Tencent Cloud, Alibaba Cloud và Bailian, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi streaming TTS, MinimaxTTS | Lingxi streaming TTS, EdgeTTS, CosyVoiceSiliconflow(một phần) |
+| Dịch vụ cục bộ | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, Index-TTS, PaddleSpeech | Index-TTS, PaddleSpeech, FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3 |
+
+---
+
+### VAD Phát hiện hoạt động giọng nói
+
+| Loại  |   Tên nền tảng    | Phương pháp sử dụng | Mô hình thu phí | Ghi chú |
+|:---:|:---------:|:----:|:----:|:--:|
+| VAD | SileroVAD | Sử dụng cục bộ |  Miễn phí  |    |
+
+---
+
+### ASR Nhận dạng giọng nói
+
+| Phương pháp sử dụng | Nền tảng hỗ trợ | Nền tảng miễn phí |
+|:---:|:---:|:---:|
+| Sử dụng cục bộ | FunASR, SherpaASR | FunASR, SherpaASR |
+| Gọi giao diện | FunASRServer, Volcano Engine, iFlytek, Tencent Cloud, Alibaba Cloud, Baidu Cloud, OpenAI ASR | FunASRServer |
+
+---
+
+### Voiceprint Nhận dạng vân giọng
+
+| Phương pháp sử dụng | Nền tảng hỗ trợ | Nền tảng miễn phí |
+|:---:|:---:|:---:|
+| Sử dụng cục bộ | 3D-Speaker | 3D-Speaker |
+
+---
+
+### Memory Lưu trữ bộ nhớ
+
+|   Loại   |      Tên nền tảng       | Phương pháp sử dụng |   Mô hình thu phí    | Ghi chú |
+|:------:|:---------------:|:----:|:---------:|:--:|
+| Memory |     mem0ai      | Gọi giao diện | Hạn mức 1000 lần/tháng |    |
+| Memory |     [powermem](./docs/powermem-integration.md)    | Tóm tắt cục bộ | Phụ thuộc vào LLM và DB |  OceanBase mã nguồn mở, hỗ trợ tìm kiếm thông minh  |
+| Memory | mem_local_short | Tóm tắt cục bộ |    Miễn phí     |    |
+| Memory |     nomem       | Chế độ không có bộ nhớ |    Miễn phí     |    |
+
+---
+
+### Intent Nhận dạng ý định
+
+|   Loại   |     Tên nền tảng      | Phương pháp sử dụng |  Mô hình thu phí   |          Ghi chú           |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Intent |  intent_llm   | Gọi giao diện | Thu phí theo LLM |    Nhận dạng ý định qua mô hình lớn, tính tổng quát mạnh     |
+| Intent | function_call | Gọi giao diện | Thu phí theo LLM | Hoàn thành ý định qua gọi hàm mô hình lớn, tốc độ nhanh, hiệu quả tốt |
+| Intent |    nointent   | Chế độ không có ý định |    Miễn phí     |    Không thực hiện nhận dạng ý định, trả về trực tiếp kết quả đối thoại     |
+
+---
+
+### Rag Tăng cường truy xuất thông tin
+
+|   Loại   |     Tên nền tảng      | Phương pháp sử dụng |  Mô hình thu phí   |          Ghi chú           |
+|:------:|:-------------:|:----:|:-------:|:---------------------:|
+| Rag |  ragflow   | Gọi giao diện | Thu phí theo token tiêu tốn của phân đoạn, phân từ |    Sử dụng chức năng tăng cường truy xuất của RagFlow, cung cấp phản hồi đối thoại chính xác hơn     |
+
+---
+
+## Lời cảm ơn 🙏
+
+| Logo | Dự án/Công ty | Mô tả |
+|:---:|:---:|:---|
+| <img src="./docs/images/logo_bailing.png" width="160"> | [Robot đối thoại giọng nói Bailing](https://github.com/wwbin2017/bailing) | Dự án này được lấy cảm hứng từ [Robot đối thoại giọng nói Bailing](https://github.com/wwbin2017/bailing) và được triển khai trên cơ sở đó |
+| <img src="./docs/images/logo_tenclass.png" width="160"> | [Shifang Ronghai](https://www.tenclass.com/) | Cảm ơn [Shifang Ronghai](https://www.tenclass.com/) đã xây dựng giao thức truyền thông tiêu chuẩn, phương án tương thích đa thiết bị và mô phạm thực hành tình huống đồng thời cao cho hệ sinh thái Xiaozhi; cung cấp tài liệu hỗ trợ kỹ thuật toàn diện cho dự án này |
+| <img src="./docs/images/logo_xuanfeng.png" width="160"> | [Xuanfeng Technology](https://github.com/Eric0308) | Cảm ơn [Xuanfeng Technology](https://github.com/Eric0308) đã đóng góp khung gọi hàm, giao thức truyền thông MCP và mã triển khai cơ chế gọi dạng plugin, thông qua hệ thống điều phối lệnh tiêu chuẩn hóa và khả năng mở rộng động, đã cải thiện đáng kể hiệu suất tương tác và khả năng mở rộng chức năng của thiết bị front-end(IoT) |
+| <img src="./docs/images/logo_junsen.png" width="160"> | [huangjunsen](https://github.com/huangjunsen0406) | Cảm ơn [huangjunsen](https://github.com/huangjunsen0406) đã đóng góp module `Bảng điều khiển thông minh di động`, thực hiện điều khiển hiệu quả và tương tác thời gian thực trên thiết bị di động đa nền tảng, cải thiện đáng kể sự tiện lợi vận hành và hiệu quả quản lý của hệ thống trong tình huống di động |
+| <img src="./docs/images/logo_huiyuan.png" width="160"> | [Huiyuan Design](http://ui.kwd988.net/) | Cảm ơn [Huiyuan Design](http://ui.kwd988.net/) đã cung cấp giải pháp thị giác chuyên nghiệp cho dự án này, sử dụng kinh nghiệm thực tế thiết kế phục vụ hơn nghìn doanh nghiệp, trao quyền cho trải nghiệm người dùng sản phẩm của dự án này |
+| <img src="./docs/images/logo_qinren.png" width="160"> | [Xi'an Qinren Information Technology](https://www.029app.com/) | Cảm ơn [Xi'an Qinren Information Technology](https://www.029app.com/) đã làm sâu sắc hệ thống thị giác của dự án này, đảm bảo tính nhất quán và khả năng mở rộng của phong cách thiết kế tổng thể trong ứng dụng đa tình huống |
+| <img src="./docs/images/logo_contributors.png" width="160"> | [Người đóng góp mã](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors) | Cảm ơn [tất cả người đóng góp mã](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors), sự cống hiến của bạn khiến dự án mạnh mẽ và vững chắc hơn. |
+
+
+<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>
@@ -1,105 +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
-# 所需条件（否则无法使用）：
-# 1、请确保你的环境可以正常访问 GitHub 否则无法下载脚本
-#
-# 检测操作系统类型
-case "$(uname -s)" in
-    Linux*)     OS=Linux;;
-    Darwin*)    OS=Mac;;
-    CYGWIN*)    OS=Windows;;
-    MINGW*)     OS=Windows;;
-    MSYS*)      OS=Windows;;
-    *)          OS=UNKNOWN;;
+# 暂且只支持X86版本的Ubuntu系统，其他系统未测试
+
+# 定义中断处理函数
+handle_interrupt() {
+    echo ""
+    echo "安装已被用户中断(Ctrl+C或Esc)"
+    echo "如需重新安装，请再次运行脚本"
+    exit 1
+}
+
+# 设置信号捕获，处理Ctrl+C
+trap handle_interrupt SIGINT
+
+# 处理Esc键
+# 保存终端设置
+old_stty_settings=$(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

-# 设置颜色（Windows CMD 不支持，但不影响使用）
-if [ "$OS" = "Windows" ]; then
-    GREEN=""
-    RED=""
-    NC=""
-else
-    GREEN='\033[0;32m'
-    RED='\033[0;31m'
-    NC='\033[0m'
-fi
-
-echo "${GREEN}开始安装小智服务端...${NC}"
-
-# 创建必要的目录
-echo "创建目录结构..."
-mkdir -p xiaozhi-server/data xiaozhi-server/models/SenseVoiceSmall
-cd xiaozhi-server || exit
-
-# 根据操作系统选择下载命令
-if [ "$OS" = "Windows" ]; then
-    DOWNLOAD_CMD="curl -L -o"
-    if ! command -v curl >/dev/null 2>&1; then
-        DOWNLOAD_CMD="powershell -Command Invoke-WebRequest -Uri"
-        DOWNLOAD_CMD_SUFFIX="-OutFile"
-    fi
-else
-    if command -v curl >/dev/null 2>&1; then
-        DOWNLOAD_CMD="curl -L -o"
-    elif command -v wget >/dev/null 2>&1; then
-        DOWNLOAD_CMD="wget -O"
-    else
-        echo "${RED}错误: 需要安装 curl 或 wget${NC}"
-        exit 1
-    fi
-fi
-
-# 下载语音识别模型
-echo "下载语音识别模型..."
-if [ "$DOWNLOAD_CMD" = "powershell -Command Invoke-WebRequest -Uri" ]; then
-    $DOWNLOAD_CMD "https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt" $DOWNLOAD_CMD_SUFFIX "models/SenseVoiceSmall/model.pt"
-else
-    $DOWNLOAD_CMD "models/SenseVoiceSmall/model.pt" "https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt"
-fi
-
-if [ $? -ne 0 ]; then
-    echo "${RED}模型下载失败。请手动从以下地址下载：${NC}"
-    echo "1. https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt"
-    echo "2. 百度网盘: https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg (提取码: qvna)"
-    echo "下载后请将文件放置在 models/SenseVoiceSmall/model.pt"
-fi
-
-# 下载配置文件
-echo "下载配置文件..."
-if [ "$DOWNLOAD_CMD" = "powershell -Command Invoke-WebRequest -Uri" ]; then
-    $DOWNLOAD_CMD "https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/main/main/xiaozhi-server/docker-compose.yml" $DOWNLOAD_CMD_SUFFIX "docker-compose.yml"
-    $DOWNLOAD_CMD "https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/main/main/xiaozhi-server/config.yaml" $DOWNLOAD_CMD_SUFFIX "data/.config.yaml"
-else
-    $DOWNLOAD_CMD "docker-compose.yml" "https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/main/main/xiaozhi-server/docker-compose.yml"
-    $DOWNLOAD_CMD "data/.config.yaml" "https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/main/main/xiaozhi-server/config.yaml"
-fi
-
-# 检查文件是否存在
-echo "检查文件完整性..."
-FILES_TO_CHECK="docker-compose.yml data/.config.yaml models/SenseVoiceSmall/model.pt"
-ALL_FILES_EXIST=true
-
-for FILE in $FILES_TO_CHECK; do
-    if [ ! -f "$FILE" ]; then
-        echo "${RED}错误: $FILE 不存在${NC}"
-        ALL_FILES_EXIST=false
-    fi
-done
-
-if [ "$ALL_FILES_EXIST" = false ]; then
-    echo "${RED}某些文件下载失败，请检查上述错误信息并手动下载缺失的文件。${NC}"
+# 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

-echo "${GREEN}文件下载完成！${NC}"
-echo "请编辑 data/.config.yaml 文件配置你的API密钥。"
-echo "配置完成后，运行以下命令启动服务："
-echo "${GREEN}docker-compose up -d${NC}"
-echo "查看日志请运行："
-echo "${GREEN}docker logs -f xiaozhi-esp32-server${NC}"
+# 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

-# 提示用户编辑配置文件
-echo "\n${RED}重要提示：${NC}"
-echo "1. 请确保编辑 data/.config.yaml 文件，配置必要的API密钥"
-echo "2. 特别是 ChatGLM 和 mem0ai 的密钥必须配置"
-echo "3. 配置完成后再启动 docker 服务"
+# 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
@@ -2,53 +2,19 @@
 ![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)

-如果你已经安装好docker，你可以[1.1使用懒人脚本](#11-懒人脚本)自动帮你下载所需的文件和配置文件，你可以使用docker[1.2手动部署](#12-手动部署)。
+安装好docker后，进继续。

-### 1.1 懒人脚本
+### 1.1 手动部署

-你可以使用以下命令一键下载并执行部署脚本：
-请确保你的环境可以正常访问 GitHub 否则无法下载脚本。
-```bash
-curl -L -o docker-setup.sh https://raw.githubusercontent.com/xinnan-tech/xiaozhi-esp32-server/main/docker-setup.sh
-```
+#### 1.1.1 创建目录

-如果您的电脑是windows系统，请使用使用 Git Bash、WSL、PowerShell 或 CMD 运行以下命令：
-```bash
-# Git Bash 或 WSL
-sh docker-setup.sh
-# PowerShell 或 CMD
-.\docker-setup.sh
-```
-
-如果您的电脑是linux 或者 macos 系统，请使用终端运行以下命令：
-```bash
-chmod +x docker-setup.sh
-./docker-setup.sh
-```
-
-脚本会自动完成以下操作：
-> 1. 创建必要的目录结构
-> 2. 下载语音识别模型
-> 3. 下载配置文件
-> 4. 检查文件完整性
->
-> 执行完成后，请按照提示配置 API 密钥。
-
-当你一切顺利完成以上操作后，继续操作[配置项目文件](#2-配置项目文件)
-
-### 1.2 手动部署
-
-如果懒人脚本无法正常运行，请按本章节1.2进行手动部署。
-
-#### 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`。
+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。

@@ -61,18 +27,18 @@ xiaozhi-server
     ├─ SenseVoiceSmall
 ```

-#### 1.2.2 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。

-#### 1.2.3 下载配置文件
+#### 1.1.3 下载配置文件

 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。

-##### 1.2.3.1 下载 docker-compose.yaml
+##### 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)。

@@ -81,7 +47,7 @@ xiaozhi-server

 下载完后，回到本教程继续往下。

-##### 1.2.3.2 创建 config.yaml
+##### 1.1.3.2 创建 config.yaml

 用浏览器打开[这个链接](../main/xiaozhi-server/config.yaml)。

@@ -114,7 +80,7 @@ xiaozhi-server
 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。
@@ -173,6 +139,9 @@ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/

 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。
@@ -260,7 +229,7 @@ LLM:
 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`

@@ -290,19 +259,33 @@ LLM:

 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)
-
-[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)
+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/>
@@ -1,13 +1,40 @@
 # 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
-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)

-#### 1.1 创建目录
+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`。

@@ -22,22 +49,22 @@ xiaozhi-server
     ├─ SenseVoiceSmall
 ```

-#### 1.2 下载语音识别模型文件
+#### 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`


-#### 1.3 下载配置文件
+#### 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。

-##### 1.3.1 下载 docker-compose_all.yaml
+##### 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)。

@@ -48,7 +75,7 @@ xiaozhi-server

 下载完后，回到本教程继续往下。

-##### 1.3.2 下载 config_from_api.yaml
+##### 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)。

@@ -179,12 +206,12 @@ docker logs -f xiaozhi-esp32-server

 OTA接口：
 ```
-http://你电脑局域网的ip:8002/xiaozhi/ota/
+http://你宿主机局域网的ip:8002/xiaozhi/ota/
 ```

 Websocket接口：
 ```
-ws://你电脑局域网的ip:8000/xiaozhi/v1/
+ws://你宿主机的ip:8000/xiaozhi/v1/
 ```

 ### 第三件重要的事情
@@ -328,6 +355,9 @@ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/

 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。
@@ -358,7 +388,7 @@ pip install -r requirements.txt
 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`

@@ -431,19 +461,32 @@ ws://你电脑局域网的ip:8000/xiaozhi/v1/
 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)
-
-[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)
+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/>
@@ -34,59 +34,18 @@ conda install conda-forge::ffmpeg
 ### 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。以下为各组件的响应速度测试数据（仅供参考，不构成承诺）：
+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。

-| 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       |
+| 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） |

-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  |
-
-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`
+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 🗣️

@@ -100,30 +59,42 @@ VAD:
    min_silence_duration_ms: 700  # 如果说话停顿较长，可将此值调大
 ```

-### 7、我想通过小智控制电灯、空调、远程开关机等操作 💡
+### 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/>

-参考教程[ESP32设备与HomeAssistant集成指南](./homeassistant-integration.md)
+### 9、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/>

-### 8、如何开启手机注册智控台 📱
+### 10、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/>

-参考教程[阿里云短信集成指南](./ali-sms-integration.md)
+### 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/>

-### 9、如何开启视觉模型实现拍照识物 📷
-
-参考教程[视觉模型使用指南](./mcp-vision-integration.md)
-
-### 10、如何开启MCP接入点 🔧
-
-1、先参考教程[MCP 接入点部署使用指南](./mcp-endpoint-enable.md)
-
-2、再参考教程[MCP 接入点使用指南](./mcp-endpoint-integration.md)
-
-### 12、如何开启声纹识别 🔊
-
-参考教程[声纹识别启用指南](./voiceprint-integration.md)
+### 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。
-
-也可以发邮件我们取得联系：huangrongzhuang@xin-nan.com
+可以在[issues](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues)提交您的问题。
@@ -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")
+```
@@ -105,6 +105,8 @@ else
 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
@@ -134,8 +136,12 @@ else
  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
@@ -149,8 +155,6 @@ chmod 777 update_8000.sh
 以上的脚本都建立好后，日常更新，我们只要依次执行以下命令就可以做到自动更新和启动

 ```
-# 进入pyhton环境
-conda activate xiaozhi-esp32-server
 cd /home/system/xiaozhi
 # 更新并启动Java程序
 ./update_8001.sh
@@ -158,9 +162,11 @@ cd /home/system/xiaozhi
 ./update_8002.sh
 # 更新并启动python程序
 ./update_8000.sh
-# 查看Java日志
+
+
+# 后期想查看java日志，执行以下命令
 tail -f nohup.out
-# 查看Python日志
+# 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
 ```

@@ -17,5 +17,5 @@ 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
+docker compose up -d
 ```
@@ -97,7 +97,7 @@ http://homeassistant.local:8123

 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`函数调用`或`LLM意图识别`。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。
+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`。

@@ -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。
@@ -0,0 +1,195 @@
+# IndexStreamTTS 使用指南
+
+## 环境准备
+### 1. 克隆项目 
+```bash 
+git clone https://github.com/Ksuriuri/index-tts-vllm.git
+```
+进入解压后的目录
+```bash
+cd index-tts-vllm
+```
+切换到指定版本 (使用VLLM-0.10.2的历史版本)
+```bash
+git checkout 224e8d5e5c8f66801845c66b30fa765328fd0be3
+```
+
+### 2. 创建并激活 conda 环境
+```bash 
+conda create -n index-tts-vllm python=3.12
+conda activate index-tts-vllm
+```
+
+### 3. 安装PyTorch 需要版本为2.8.0（最新版）
+#### 查看显卡最高支持的版本和实际安装的版本
+```bash
+nvidia-smi
+nvcc --version
+``` 
+#### 驱动支持的最高 CUDA 版本
+```bash
+CUDA Version: 12.8
+```
+#### 实际安装的 CUDA 编译器版本
+```bash
+Cuda compilation tools, release 12.8, V12.8.89
+```
+#### 那么对应的安装命令（pytorch默认给的是12.8的驱动版本）
+```bash
+pip install torch torchvision
+```
+需要 pytorch 版本 2.8.0（对应 vllm 0.10.2），具体安装指令请参考：[pytorch 官网](https://pytorch.org/get-started/locally/)
+
+### 4. 安装依赖
+```bash 
+pip install -r requirements.txt
+```
+
+### 5. 下载模型权重
+### 方案一：下载官方权重文件后转换
+此为官方权重文件，下载到本地任意路径即可，支持 IndexTTS-1.5 的权重  
+| HuggingFace                                                   | ModelScope                                                          |
+|---------------------------------------------------------------|---------------------------------------------------------------------|
+| [IndexTTS](https://huggingface.co/IndexTeam/Index-TTS)        | [IndexTTS](https://modelscope.cn/models/IndexTeam/Index-TTS)        |
+| [IndexTTS-1.5](https://huggingface.co/IndexTeam/IndexTTS-1.5) | [IndexTTS-1.5](https://modelscope.cn/models/IndexTeam/IndexTTS-1.5) |
+
+下面以ModelScope的安装方法为例  
+#### 请注意：git需要安装并初始化启用lfs（如已安装可以跳过）
+```bash
+sudo apt-get install git-lfs
+git lfs install
+```
+创建模型目录，并拉取模型
+```bash 
+mkdir model_dir
+cd model_dir
+git clone https://www.modelscope.cn/IndexTeam/IndexTTS-1.5.git
+```
+
+#### 模型权重转换
+```bash 
+bash convert_hf_format.sh /path/to/your/model_dir
+```
+例如：你下载的IndexTTS-1.5模型存放在model_dir目录下，则执行以下命令
+```bash
+bash convert_hf_format.sh model_dir/IndexTTS-1.5
+```
+此操作会将官方的模型权重转换为 transformers 库兼容的版本，保存在模型权重路径下的 vllm 文件夹中，方便后续 vllm 库加载模型权重
+
+### 6. 更改接口适配一下项目
+接口返回数据与项目不适配需要调整一下，使其直接返回音频数据
+```bash
+vi api_server.py
+```
+```bash 
+@app.post("/tts", responses={
+    200: {"content": {"application/octet-stream": {}}},
+    500: {"content": {"application/json": {}}}
+})
+async def tts_api(request: Request):
+    try:
+        data = await request.json()
+        text = data["text"]
+        character = data["character"]
+
+        global tts
+        sr, wav = await tts.infer_with_ref_audio_embed(character, text)
+
+        return Response(content=wav.tobytes(), media_type="application/octet-stream")
+        
+    except Exception as ex:
+        tb_str = ''.join(traceback.format_exception(type(ex), ex, ex.__traceback__))
+        print(tb_str)
+        return JSONResponse(
+            status_code=500,
+            content={
+                "status": "error",
+                "error": str(tb_str)
+            }
+        )
+```
+
+### 7.编写sh启动脚本（请注意要在相应的conda环境下运行）
+```bash 
+vi start_api.sh
+```
+### 将下面内容粘贴进去并按:输入wq保存  
+#### 脚本中的/home/system/index-tts-vllm/model_dir/IndexTTS-1.5 请自行修改为实际路径
+```bash
+# 激活conda环境
+conda activate index-tts-vllm 
+echo "激活项目conda环境"
+sleep 2
+# 查找占用11996端口的进程号
+PID_VLLM=$(sudo netstat -tulnp | grep 11996 | awk '{print $7}' | cut -d'/' -f1)
+
+# 检查是否找到进程号
+if [ -z "$PID_VLLM" ]; then
+  echo "没有找到占用11996端口的进程"
+else
+  echo "找到占用11996端口的进程，进程号为: $PID_VLLM"
+  # 先尝试普通kill，等待2秒
+  kill $PID_VLLM
+  sleep 2
+  # 检查进程是否还在
+  if ps -p $PID_VLLM > /dev/null; then
+    echo "进程仍在运行，强制终止..."
+    kill -9 $PID_VLLM
+  fi
+  echo "已终止进程 $PID_VLLM"
+fi
+
+# 查找占用VLLM::EngineCore进程
+GPU_PIDS=$(ps aux | grep -E "VLLM|EngineCore" | grep -v grep | awk '{print $2}')
+
+# 检查是否找到进程号
+if [ -z "$GPU_PIDS" ]; then
+  echo "没有找到VLLM相关进程"
+else
+  echo "找到VLLM相关进程，进程号为: $GPU_PIDS"
+  # 先尝试普通kill，等待2秒
+  kill $GPU_PIDS
+  sleep 2
+  # 检查进程是否还在
+  if ps -p $GPU_PIDS > /dev/null; then
+    echo "进程仍在运行，强制终止..."
+    kill -9 $GPU_PIDS
+  fi
+  echo "已终止进程 $GPU_PIDS"
+fi
+
+# 创建tmp目录（如果不存在）
+mkdir -p tmp
+
+# 后台运行api_server.py，日志重定向到tmp/server.log
+nohup python api_server.py --model_dir /home/system/index-tts-vllm/model_dir/IndexTTS-1.5 --port 11996 > tmp/server.log 2>&1 &
+echo "api_server.py 已在后台运行，日志请查看 tmp/server.log"
+```
+给脚本执行权限并运行脚本
+```bash 
+chmod +x start_api.sh
+./start_api.sh
+```
+日志会在tmp/server.log中输出，可以通过以下命令查看日志情况
+```bash
+tail -f tmp/server.log
+```
+如果显卡内存足够，可在脚本中添加启动参数 ----gpu_memory_utilization 来调整显存占用比例，默认值为 0.25
+
+## 音色配置
+index-tts-vllm支持通过配置文件注册自定义音色，支持单音色和混合音色配置。  
+在项目根目录下的assets/speaker.json文件中配置自定义音色
+### 配置格式说明
+```bash
+{
+    "说话人名称1": [
+        "音频文件路径1.wav",
+        "音频文件路径2.wav"
+    ],
+    "说话人名称2": [
+        "音频文件路径3.wav"
+    ]
+}
+```
+### 注意 （配置角色后需重启服务进行音色注册）
+添加后需在智控台中添加相应的说话人（单模块则更换相应的voice）
@@ -71,6 +71,7 @@ docker logs -f mcp-endpoint-server
 请你保留好上面两个`接口地址`，下一步要用到。

 # 2、全模块部署时，怎么配置MCP接入点
+首先，你要开启MCP接入点功能。在智控台，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`MCP接入点`，点击`保存配置`。在`角色配置`页面，点击`编辑功能`按钮，即可看到`mcp接入点`功能。

 如果你是全模块部署，使用管理员账号，登录智控台，点击顶部`参数字典`，选择`参数管理`功能。

@@ -0,0 +1,40 @@
+# MCP 方法如何获取设备信息
+
+本教程将指导你如何使用MCP方法获取设备信息。
+
+第一步：自定义你的`agent-base-prompt.txt`文件
+
+把xiaozhi-server目录的`agent-base-prompt.txt`文件内容复制到你的`data`目录下，并重命名为`.agent-base-prompt.txt`。
+
+第二步：修改`data/.agent-base-prompt.txt`文件，找到`<context>`标签，在标签内容中添加以下代码内容：
+```
+- **设备ID：** {{device_id}}
+```
+
+添加完成后，你的`data/.agent-base-prompt.txt`文件的`<context>`标签内容大致如下：
+```
+<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}}
+- **今天日期：** {{today_date}} ({{today_weekday}})
+- **今天农历：** {{lunar_date}}
+- **用户所在城市：** {{local_address}}
+- **当地未来7天天气：** {{weather_info}}
+</context>
+```
+
+第三步：修改`data/.config.yaml`文件，找到`agent-base-prompt`配置，修改前内容如下：
+```
+prompt_template: agent-base-prompt.txt
+```
+修改成
+```
+prompt_template: data/.agent-base-prompt.txt
+```
+
+第四步：重启你的xiaozhi-server服务。
+
+第五步：在你的mcp方法增加名称为`device_id`,类型为`string`,描述为`设备ID`的参数。
+
+第六步：重新唤醒小智，让他调用mcp方法，查看你的mcp方法是否可以获取`设备ID`。
@@ -0,0 +1,187 @@
+# MQTT 网关部署教程
+
+`xiaozhi-esp32-server`项目，可结合虾哥开源的[xiaozhi-mqtt-gateway](https://github.com/78/xiaozhi-mqtt-gateway) 项目进行简单改造，即可实现小智硬件MQTT+UDP连接。
+本教程分为三部分，你可以根据你是全模块部署还是单模块部署，选择对应的部分接入MQTT网关：
+- 第一部分：部署MQTT网关
+- 第二部分：全模块运行实现小智硬件MQTT+UDP连接
+- 第三部分：单模块运行xiaozhi-server实现小智硬件MQTT+UDP连接
+
+## 准备阶段
+准备好你的`xiaozhi-server`的`mqtt-websocket`连接地址。在你原来的`websocket地址`基础上，添加`?from=mqtt_gateway`字符，就可以得到`mqtt-websocket`连接地址
+
+1、如果你是源码部署，你的`mqtt-websocket`地址是：
+```
+ws://127.0.0.1:8000/xiaozhi/v1/?from=mqtt_gateway
+```
+
+2、如果你是docker部署，你的`mqtt-websocket`地址是
+```
+ws://你宿主机局域网IP:8000/xiaozhi/v1/?from=mqtt_gateway
+```
+
+## 重要提示
+
+如果你是服务器部署，需要确保服务器`1883`、`8884`、`8007`端口都对外开放。`8884`选择的协议类型是`UDP`，其他是`TCP`。
+
+如果你是服务器部署，需要确保服务器`1883`、`8884`、`8007`端口都对外开放。`8884`选择的协议类型是`UDP`，其他是`TCP`。
+
+如果你是服务器部署，需要确保服务器`1883`、`8884`、`8007`端口都对外开放。`8884`选择的协议类型是`UDP`，其他是`TCP`。
+
+
+## 第一部分：部署MQTT网关
+
+1. 克隆[改造后的xiaozhi-mqtt-gateway项目](https://github.com/xinnan-tech/xiaozhi-mqtt-gateway.git)：
+```bash
+git clone https://ghfast.top/https://github.com/xinnan-tech/xiaozhi-mqtt-gateway.git
+cd xiaozhi-mqtt-gateway
+```
+
+2. 安装依赖：
+```bash
+npm install
+npm install -g pm2
+```
+
+3. 配置 `config.json`：
+```bash
+cp config/mqtt.json.example config/mqtt.json
+```
+
+4. 编辑配置文件 config/mqtt.json，把你在`本文准备阶段`的`mqtt-websocket`地址替换到`chat_servers`里。例如源码部署的`xiaozhi-server`就是如下配置：
+
+``` 
+{
+    "production": {
+        "chat_servers": [
+            "ws://127.0.0.1:8000/xiaozhi/v1/?from=mqtt_gateway"
+        ]
+    },
+    "debug": false,
+    "max_mqtt_payload_size": 8192,
+    "mcp_client": {
+        "capabilities": {
+        },
+        "client_info": {
+            "name": "xiaozhi-mqtt-client",
+            "version": "1.0.0"
+        },
+        "max_tools_count": 128
+    }
+}
+```
+5. 在项目根目录创建下`.env`文件，并设置以下环境变量:
+```
+PUBLIC_IP=your-ip         # 服务器公网IP
+MQTT_PORT=1883            # MQTT服务器端口
+UDP_PORT=8884             # UDP服务器端口
+API_PORT=8007             # 管理API端口
+MQTT_SIGNATURE_KEY=test   # MQTT签名密钥
+SERVER_SECRET=Te1st12134  # 服务器密钥，请保持和智控台（server.secret）一致或者和xiaozhi-server里（server.auth_key）保持一致
+```
+请注意`PUBLIC_IP`配置，确保其与实际公网IP一致，如果有域名就填域名。
+
+`MQTT_SIGNATURE_KEY` 是用于MQTT连接认证的密钥，最好设置成复杂一点的，最好是设置成8个字符以上且同时包含大小写字母，这个密钥稍后还会用到。
+
+- 注意不要用简单的密码，比如`123456`、`test`等。
+- 注意不要用简单的密码，比如`123456`、`test`等。
+- 注意不要用简单的密码，比如`123456`、`test`等。
+
+`SERVER_SECRET` 是用生成websocket连接的认证信息。
+
+1、如果你是全模块部署，且你的智控台的参数管理里`server.auth.enabled`设置成了`true`，那么，`SERVER_SECRET`需要和智控台（`server.secret`）保持一致。
+
+2、如果你是单模块部署，且你在配置文件里把`server.auth.enabled`设置成了`true`，那么，`SERVER_SECRET`需要和配置文件里（`server.auth_key`）保持一致。
+
+
+6. 启动MQTT网关
+```
+# 启动服务
+pm2 start ecosystem.config.js
+
+# 查看日志
+pm2 logs xz-mqtt
+```
+
+当你看到如下日志，说明MQTT网关启动成功：
+```
+0|xz-mqtt  | 2025-09-11T12:14:48: MQTT 服务器正在监听端口 1883
+0|xz-mqtt  | 2025-09-11T12:14:48: UDP 服务器正在监听 x.x.x.x:8884
+```
+
+如果需要重启MQTT网关，执行如下命令：
+```
+pm2 restart xz-mqtt
+```
+
+## 第二部分：全模块运行实现小智硬件MQTT+UDP连接
+
+查看你智控台首页底部的版本号，确认你的智控台版本是否是`0.7.7`及以上版本。如果不是，需要升级智控台。
+
+1. 在智控台顶部，点击`参数管理`，搜索`server.mqtt_gateway`，点击编辑，填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`MQTT_PORT`。类似这样
+```
+192.168.0.7:1883
+```
+2. 在智控台顶部，点击`参数管理`，搜索`server.mqtt_signature_key`，点击编辑，填入你在`.env`文件中设置的`MQTT_SIGNATURE_KEY`。
+
+3. 在智控台顶部，点击`参数管理`，搜索`server.udp_gateway`，点击编辑，填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`UDP_PORT`。类似这样
+```
+192.168.0.7:8884
+```
+4. 在智控台顶部，点击`参数管理`，搜索`server.mqtt_manager_api`，点击编辑，填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`API_PORT`。类似这样
+```
+192.168.0.7:8007
+```
+
+上面的配置完成后，你可以使用curl命令，验证你的ota地址是否会下发mqtt配置，把下面的`http://localhost:8002/xiaozhi/ota/`改成你的ota地址
+```
+curl 'http://localhost:8002/xiaozhi/ota/' \
+  -H 'Content-Type: application/json' \
+  -H 'Client-Id: 7b94d69a-9808-4c59-9c9b-704333b38aff' \
+  -H 'Device-Id: 11:22:33:44:55:66' \
+  --data-raw $'{\n  "application": {\n    "version": "1.0.1",\n    "elf_sha256": "1"\n  },\n  "board": {\n    "mac": "11:22:33:44:55:66"\n  }\n}'
+```
+
+如果返回的内容包含`mqtt`相关的配置，说明配置成功。类似这样
+
+```
+{"server_time":{"timestamp":1757567894012,"timeZone":"Asia/Shanghai","timezone_offset":480},"activation":{"code":"460609","message":"http://xiaozhi.server.com\n460609","challenge":"11:22:33:44:55:66"},"firmware":{"version":"1.0.1","url":"http://xiaozhi.server.com:8002/xiaozhi/otaMag/download/NOT_ACTIVATED_FIRMWARE_THIS_IS_A_INVALID_URL"},"websocket":{"url":"ws://192.168.4.23:8000/xiaozhi/v1/"},"mqtt":{"endpoint":"192.168.0.7:1883","client_id":"GID_default@@@11_22_33_44_55_66@@@7b94d69a-9808-4c59-9c9b-704333b38aff","username":"eyJpcCI6IjA6MDowOjA6MDowOjA6MSJ9","password":"Y8XP9xcUhVIN9OmbCHT9ETBiYNE3l3Z07Wk46wV9PE8=","publish_topic":"device-server","subscribe_topic":"devices/p2p/11_22_33_44_55_66"}}
+```
+
+由于MQTT信息是需要靠OTA地址下发的，因此只有你保证能正常连接服务器的OTA地址，重启唤醒即可。
+
+唤醒后留意mqtt-gateway的日志，确认是否有连接成功的日志。
+```
+pm2 logs xz-mqtt
+```
+
+## 第三部分：单模块运行xiaozhi-server实现小智硬件MQTT+UDP连接
+
+打开你的`data/.config.yaml`文件，在`server`下找到`mqtt_gateway`填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`MQTT_PORT`。类似这样
+```
+192.168.0.7:1883
+```
+在`server`下找到`mqtt_signature_key`填入你在`.env`文件中设置的`MQTT_SIGNATURE_KEY`。
+
+在`server`下找到`udp_gateway`填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`UDP_PORT`。类似这样
+```
+192.168.0.7:8884
+```
+
+上面的配置完成后，你可以使用curl命令，验证你的ota地址是否会下发mqtt配置，把下面的`http://localhost:8002/xiaozhi/ota/`改成你的ota地址
+```
+curl 'http://localhost:8002/xiaozhi/ota/' \
+  -H 'Device-Id: 11:22:33:44:55:66' \
+  --data-raw $'{\n  "application": {\n    "version": "1.0.1",\n    "elf_sha256": "1"\n  },\n  "board": {\n    "mac": "11:22:33:44:55:66"\n  }\n}'
+```
+
+如果返回的内容包含`mqtt`相关的配置，说明配置成功。类似这样
+```
+{"server_time":{"timestamp":1758781561083,"timeZone":"GMT+08:00","timezone_offset":480},"activation":{"code":"527111","message":"http://xiaozhi.server.com\n527111","challenge":"11:22:33:44:55:66"},"firmware":{"version":"1.0.1","url":"http://xiaozhi.server.com:8002/xiaozhi/otaMag/download/NOT_ACTIVATED_FIRMWARE_THIS_IS_A_INVALID_URL"},"websocket":{"url":"ws://192.168.1.15:8000/xiaozhi/v1/"},"mqtt":{"endpoint":"192.168.1.15:1883","client_id":"GID_default@@@11_22_33_44_55_66@@@11_22_33_44_55_66","username":"eyJpcCI6IjE5Mi4xNjguMS4xNSJ9","password":"fjAYs49zTJecWqJ3jBt+kqxVn/x7vkXRAc85ak/va7Y=","publish_topic":"device-server","subscribe_topic":"devices/p2p/11_22_33_44_55_66"}}
+```
+
+由于MQTT信息是需要靠OTA地址下发的，因此只有你保证能正常连接服务器的OTA地址，重启唤醒即可。
+
+唤醒后留意mqtt-gateway的日志，确认是否有连接成功的日志。
+```
+pm2 logs xz-mqtt
+```
@@ -0,0 +1,142 @@
+# 单模块部署固件OTA自动升级配置指南
+
+本教程将指导你如何在**单模块部署**场景下配置固件OTA自动升级功能，实现设备固件的自动更新。
+
+如果你已经使用**全模块部署**，请忽略本教程。
+
+## 功能介绍
+
+在单模块部署中，xiaozhi-server内置了OTA固件管理功能，可以自动检测设备版本并下发升级固件。系统会根据设备型号和当前版本，自动匹配并推送最新的固件版本。
+
+## 前提条件
+
+- 你已经成功进行**单模块部署**并运行xiaozhi-server
+- 设备能够正常连接到服务器
+
+## 第一步 准备固件文件
+
+### 1. 创建固件存放目录
+
+固件文件需要放在`data/bin/`目录下。如果该目录不存在，请手动创建：
+
+```bash
+mkdir -p data/bin
+```
+
+### 2. 固件文件命名规则
+
+固件文件必须遵循以下命名格式：
+
+```
+{设备型号}_{版本号}.bin
+```
+
+**命名规则说明：**
+- `设备型号`：设备的型号名称，例如 `lichuang-dev`、`bread-compact-wifi` 等
+- `版本号`：固件版本号，必须以数字开头，支持数字、字母、点号、下划线和短横线，例如 `1.6.6`、`2.0.0` 等
+- 文件扩展名必须是 `.bin`
+
+**命名示例：**
+```
+bread-compact-wifi_1.6.6.bin
+lichuang-dev_2.0.0.bin
+```
+
+### 3. 放置固件文件
+
+将准备好的固件文件（.bin文件）复制到`data/bin/`目录下：
+
+重要的事情说三遍：升级的bin文件是`xiaozhi.bin`，不是全量固件文件`merged-binary.bin`!
+
+重要的事情说三遍：升级的bin文件是`xiaozhi.bin`，不是全量固件文件`merged-binary.bin`!
+
+重要的事情说三遍：升级的bin文件是`xiaozhi.bin`，不是全量固件文件`merged-binary.bin`!
+
+```bash
+cp xiaozhi.bin data/bin/设备型号_版本号.bin
+```
+
+例如：
+```bash
+cp xiaozhi.bin data/bin/bread-compact-wifi_1.6.6.bin
+```
+
+## 第二步 配置公网访问地址（仅公网部署需要）
+
+**注意：此步骤仅适用于单模块公网部署的场景。**
+
+如果你的xiaozhi-server是公网部署（使用公网IP或域名），**必须**配置`server.vision_explain`参数，因为OTA固件下载地址会使用该配置的域名和端口。
+
+如果你是局域网部署，可以跳过此步骤。
+
+### 为什么要配置这个参数？
+
+在单模块部署中，系统生成固件下载地址时，会使用`vision_explain`配置的域名和端口作为基础地址。如果不配置或配置错误，设备将无法访问固件下载地址。
+
+### 配置方法
+
+打开`data/.config.yaml`文件，找到`server`配置段，设置`vision_explain`参数：
+
+```yaml
+server:
+  vision_explain: http://你的域名或IP:端口号/mcp/vision/explain
+```
+
+**配置示例：**
+
+局域网部署（默认）：
+```yaml
+server:
+  vision_explain: http://192.168.1.100:8003/mcp/vision/explain
+```
+
+公网域名部署：
+```yaml
+server:
+  vision_explain: http://yourdomain.com:8003/mcp/vision/explain
+```
+
+### 注意事项
+
+- 域名或IP必须是设备能够访问的地址
+- 如果使用Docker部署，不能使用Docker内部地址（如127.0.0.1或localhost）
+- 如果你使用了nginx反向代理，请填写对外的地址和端口号，不是本项目运行的端口号
+
+
+## 常见问题
+
+### 1. 设备收不到固件更新
+
+**可能原因和解决方法：**
+
+- 检查固件文件命名是否符合规则：`{型号}_{版本号}.bin`
+- 检查固件文件是否正确放置在`data/bin/`目录
+- 检查设备型号是否与固件文件名中的型号匹配
+- 检查固件版本号是否高于设备当前版本
+- 查看服务器日志，确认OTA请求是否正常处理
+
+### 2. 设备报告下载地址无法访问
+
+**可能原因和解决方法：**
+
+- 检查`server.vision_explain`配置的域名或IP是否正确
+- 确认端口号配置正确（默认8003）
+- 如果是公网部署，确保设备能够访问该公网地址
+- 如果是Docker部署，确保不是使用了内部地址（127.0.0.1）
+- 检查防火墙是否开放了对应端口
+- 如果你使用了nginx反向代理，请填写对外的地址和端口号，不是本项目运行的端口号
+
+### 3. 如何确认设备当前版本
+
+查看OTA请求日志，日志中会显示设备上报的版本号：
+
+```
+[ota_handler] - 设备 AA:BB:CC:DD:EE:FF 固件已是最新: 1.6.6
+```
+
+### 4. 固件文件放置后没有生效
+
+系统有30秒的缓存时间（默认），可以：
+- 等待30秒后再让设备发起OTA请求
+- 重启xiaozhi-server服务
+- 调整`firmware_cache_ttl`配置为更短的时间
@@ -0,0 +1,109 @@
+# PaddleSpeechTTS集成xiaozhi服务
+
+## 重点说明
+- 优点：本地离线部署、速度快
+- 缺点：截止2025年9月25日，默认的模型是中文模型，不支持英文转语音。如果含英文会发不出声音，如需同时支持中英文需要自己训练。
+
+## 一、基础环境要求
+操作系统：Windows / Linux / WSL 2
+
+Python 版本：3.9以上（请根据Paddle官方教程调整）
+
+Paddle 版本：官方最新版本   ```https://www.paddlepaddle.org.cn/install```
+
+依赖管理工具：conda 或 venv
+
+## 二、启动paddlespeech服务
+### 1.从paddlespeech官方仓库拉取源码
+```bash 
+git clone https://github.com/PaddlePaddle/PaddleSpeech.git
+```
+### 2.建立虚拟环境
+```bash
+
+conda create -n paddle_env python=3.10 -y
+conda activate paddle_env
+```
+### 3.安装paddle
+因CPU架构、GPU架构不同，请根据Paddle官方支持的python版本建立环境  
+```
+https://www.paddlepaddle.org.cn/install
+```
+
+### 4.进入paddlespeech目录
+```bash
+cd PaddleSpeech
+```
+### 5.安装paddlespeech
+```bash
+pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+#以下命令使用任意一个
+pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
+pip install paddlespeech -i https://pypi.tuna.tsinghua.edu.cn/simple
+```
+### 6.使用命令自动下载语音模型
+```bash
+paddlespeech tts --input "你好，这是一次测试"
+```
+此步骤会自动下载模型缓存至本地 .paddlespeech/models 目录
+
+### 7.修改tts_online_application.yaml配置
+参考目录 ```"PaddleSpeech\demos\streaming_tts_server\conf\tts_online_application.yaml"```
+选择```tts_online_application.yaml```文件用编辑器打开，设置```protocol```为```websocket```
+
+### 8.启动服务
+```yaml
+paddlespeech_server start --config_file ./demos/streaming_tts_server/conf/tts_online_application.yaml
+#官方默认启动命令：
+paddlespeech_server start --config_file ./conf/tts_online_application.yaml
+```
+请根据你的```tts_online_application.yaml```的实际目录来启动命令，看到如下日志即启动成功
+```
+Prefix dict has been built successfully.
+[2025-08-07 10:03:11,312] [   DEBUG] __init__.py:166 - Prefix dict has been built successfully.
+INFO:     Started server process [2298]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit)
+```
+
+## 三、修改小智的配置文件
+### 1.```main/xiaozhi-server/core/providers/tts/paddle_speech.py```
+
+### 2.```main/xiaozhi-server/data/.config.yaml```
+使用单模块部署
+```yaml
+selected_module:
+  TTS: PaddleSpeechTTS
+TTS:
+  PaddleSpeechTTS:
+      type: paddle_speech
+      protocol: websocket 
+      url:  ws://127.0.0.1:8092/paddlespeech/tts/streaming  # TTS 服务的 URL 地址，指向本地服务器 [websocket默认ws://127.0.0.1:8092/paddlespeech/tts/streaming]
+      spk_id: 0  # 发音人 ID，0 通常表示默认的发音人
+      sample_rate: 24000  # 采样率 [websocket默认24000，http默认0 自动选择]
+      speed: 1.0  # 语速，1.0 表示正常语速，>1 表示加快，<1 表示减慢
+      volume: 1.0  # 音量，1.0 表示正常音量，>1 表示增大，<1 表示减小
+      save_path:   # 保存路径
+```
+### 3.启动xiaozhi服务
+```py
+python app.py
+```
+打开test目录下的test_page.html，测试连接和发送消息时paddlespeech端是否有输出日志
+
+输出日志参考：
+```
+INFO:     127.0.0.1:44312 - "WebSocket /paddlespeech/tts/streaming" [accepted]
+INFO:     connection open
+[2025-08-07 11:16:33,355] [    INFO] - sentence: 哈哈，怎么突然找我聊天啦？
+[2025-08-07 11:16:33,356] [    INFO] - The durations of audio is: 2.4625 s
+[2025-08-07 11:16:33,356] [    INFO] - first response time: 0.1143045425415039 s
+[2025-08-07 11:16:33,356] [    INFO] - final response time: 0.4777836799621582 s
+[2025-08-07 11:16:33,356] [    INFO] - RTF: 0.19402382942625715
+[2025-08-07 11:16:33,356] [    INFO] - Other info: front time: 0.06514096260070801 s, first am infer time: 0.008037090301513672 s, first voc infer time: 0.04112648963928223 s,
+[2025-08-07 11:16:33,356] [    INFO] - Complete the synthesis of the audio streams
+INFO:     connection closed
+
+```
@@ -0,0 +1,27 @@
+# 语音识别、大语言模型、非流式语音合成、流式语音合成、视觉模型的性能测试工具使用指南
+
+1.在main/xiaozhi-server目录下创建data目录
+2.在data目录下创建.config.yaml文件
+3.在.data/config.yaml中，写入你的语音识别、大语言模型、流式语音合成、视觉模型的参数
+例如：
+```
+LLM:
+  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 web key
+
+TTS:
+
+VLLM:
+
+ASR:
+```
+4.在main/xiaozhi-server目录下运行performance_tester.py: 
+```
+python performance_tester.py
+```
@@ -0,0 +1,345 @@
+# PowerMem 记忆组件集成指南
+
+## 简介
+
+[PowerMem](https://www.powermem.ai/) 是由 OceanBase 开源的 Agent 记忆组件，通过本地 LLM 进行记忆总结和智能检索，为 AI 代理提供高效的记忆管理功能。
+
+费用说明：PowerMem 本身开源免费，实际费用取决于您选择的 LLM 和数据库：
+- 使用 SQLite + 免费 LLM（如智谱 glm-4-flash）= **完全免费**
+- 使用云端 LLM 或云端数据库 = 按对应服务收费
+
+> 💡 **最佳性能提示**：PowerMem 配合 OceanBase 使用可实现最大性能释放，SQLite 仅建议在资源不足的情况下使用。
+
+- **GitHub**: https://github.com/oceanbase/powermem
+- **官网**: https://www.powermem.ai/
+- **使用示例**: https://github.com/oceanbase/powermem/tree/main/examples
+
+## 功能特性
+
+- **本地总结**：通过 LLM 在本地进行记忆总结和提取
+- **用户画像**：通过 `UserMemory` 自动提取用户信息（姓名、职业、兴趣等），持续更新用户画像
+- **智能遗忘**：基于艾宾浩斯遗忘曲线，自动"遗忘"过时噪声信息
+- **多种存储后端**：支持 OceanBase（推荐，最佳性能）、SeekDB（推荐，AI应用存储一体）、PostgreSQL、SQLite（轻量备选）
+- **多种 LLM 支持**：通义千问、智谱（glm-4-flash 免费）、OpenAI 等
+- **智能检索**：基于向量搜索的语义检索能力
+- **私有部署**：完全支持本地私有化部署
+- **异步操作**：高效的异步记忆管理
+
+## 安装
+
+PowerMem 已添加到项目依赖中，如果需要手动安装：
+
+```bash
+pip install powermem
+```
+
+## 配置说明
+
+### 基础配置
+
+在 `config.yaml` 中配置 PowerMem：
+
+```yaml
+selected_module:
+  Memory: powermem
+
+Memory:
+  powermem:
+    type: powermem
+    # 是否启用用户画像功能
+    # 用户画像支持: oceanbase、seekdb、sqlite (powermem 0.3.0+)
+    enable_user_profile: true
+    
+    # ========== LLM 配置 ==========
+    llm:
+      provider: openai  # 可选: qwen, openai, zhipu 等
+      config:
+        api_key: 你的LLM API密钥
+        model: qwen-plus
+        # openai_base_url: https://api.openai.com/v1  # 可选，自定义服务地址
+    
+    # ========== Embedding 配置 ==========
+    embedder:
+      provider: openai  # 可选: qwen, openai 等
+      config:
+        api_key: 你的嵌入模型API密钥
+        model: text-embedding-v4
+        openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
+        # embedding_dims: 1024  # 向量维度，非1536时需配置
+    
+    # ========== Database 配置 ==========
+    vector_store:
+      provider: sqlite  # 可选: oceanbase(推荐), seekdb(推荐), postgres, sqlite(轻量)
+      config: {}  # SQLite 无需额外配置
+```
+
+### 配置参数详解
+
+#### LLM 配置
+
+| 参数 | 说明 | 可选值 |
+|------|------|--------|
+| `llm.provider` | LLM 提供商 | `qwen`, `openai`, `zhipu` 等 |
+| `llm.config.api_key` | API 密钥 | - |
+| `llm.config.model` | 模型名称 | 根据提供商选择 |
+| `llm.config.openai_base_url` | 自定义服务地址（可选） | - |
+
+#### Embedding 配置
+
+| 参数 | 说明 | 可选值 |
+|------|------|--------|
+| `embedder.provider` | 嵌入模型提供商 | `qwen`, `openai` 等 |
+| `embedder.config.api_key` | API 密钥 | - |
+| `embedder.config.model` | 模型名称 | 根据提供商选择 |
+| `embedder.config.openai_base_url` | 自定义服务地址（可选） | - |
+
+#### Database 配置
+
+| 参数 | 说明 | 可选值 |
+|------|------|--------|
+| `vector_store.provider` | 存储后端类型 | `oceanbase`(推荐), `seekdb`(推荐), `postgres`, `sqlite`(轻量) |
+| `vector_store.config` | 数据库连接配置 | 根据 provider 设置 |
+
+### 记忆模式说明
+
+PowerMem 支持两种记忆模式：
+
+| 模式 | 配置 | 功能 | 存储要求 |
+|------|------|------|----------|
+| **普通记忆** | `enable_user_profile: false` | 对话记忆存储与检索 | 支持所有数据库 |
+| **用户画像** | `enable_user_profile: true` | 记忆 + 自动提取用户画像 | oceanbase、seekdb、sqlite |
+
+> 📌 **版本说明**：PowerMem 0.3.0+ 版本，用户画像功能支持 OceanBase、SeekDB、SQLite 三种存储后端。
+
+### 使用通义千问（推荐）
+
+1. 访问 [阿里云百炼平台](https://bailian.console.aliyun.com/) 注册账号
+2. 在 [API Key 管理](https://bailian.console.aliyun.com/?apiKey=1#/api-key) 页面获取 API 密钥
+3. 配置如下：
+
+```yaml
+Memory:
+  powermem:
+    type: powermem
+    enable_user_profile: true
+    llm:
+      provider: qwen
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: qwen-plus
+    embedder:
+      provider: openai
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: text-embedding-v4
+        openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
+    vector_store:
+      provider: sqlite
+      config: {}
+```
+
+### 使用智谱免费 LLM（完全免费方案）
+
+智谱提供免费的 glm-4-flash 模型，配合 SQLite 可实现完全免费使用：
+
+1. 访问 [智谱AI开放平台](https://bigmodel.cn/) 注册账号
+2. 在 [API Keys](https://bigmodel.cn/usercenter/proj-mgmt/apikeys) 页面获取 API 密钥
+3. 配置如下：
+
+```yaml
+Memory:
+  powermem:
+    type: powermem
+    enable_user_profile: true
+    llm:
+      provider: openai  # 使用 openai 兼容模式
+      config:
+        api_key: xxxxxxxxxxxxxxxx.xxxxxxxxxxxxxxxx
+        model: glm-4-flash
+        openai_base_url: https://open.bigmodel.cn/api/paas/v4/
+    embedder:
+      provider: openai
+      config:
+        api_key: xxxxxxxxxxxxxxxx.xxxxxxxxxxxxxxxx
+        model: embedding-3
+        openai_base_url: https://open.bigmodel.cn/api/paas/v4/
+    vector_store:
+      provider: sqlite
+      config: {}
+```
+
+### 使用 OpenAI
+
+```yaml
+Memory:
+  powermem:
+    type: powermem
+    enable_user_profile: true
+    llm:
+      provider: openai
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: gpt-4o-mini
+        openai_base_url: https://api.openai.com/v1
+    embedder:
+      provider: openai
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: text-embedding-3-small
+        openai_base_url: https://api.openai.com/v1
+    vector_store:
+      provider: sqlite
+      config: {}
+```
+
+### 使用 OceanBase（最佳性能方案）
+
+OceanBase 是 PowerMem 的最佳搭档，可实现最大性能释放：
+
+1. 部署 OceanBase 数据库（支持开源本地部署或使用云服务）
+   - 开源部署：https://github.com/oceanbase/oceanbase
+   - 云服务：https://www.oceanbase.com/
+2. 配置如下：
+
+```yaml
+Memory:
+  powermem:
+    type: powermem
+    enable_user_profile: true
+    llm:
+      provider: qwen
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: qwen-plus
+    embedder:
+      provider: openai
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: text-embedding-v4
+        openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
+    vector_store:
+      provider: oceanbase
+      config:
+        host: 127.0.0.1
+        port: 2881
+        user: root@test
+        password: your_password
+        db_name: powermem
+        collection_name: memories  # 默认值
+        embedding_model_dims: 1536  # 嵌入向量维度，必需参数
+```
+
+## 设备记忆隔离
+
+PowerMem 会自动使用设备 ID（`device_id`）作为 `user_id` 进行记忆隔离。这意味着：
+
+- 每个设备拥有独立的记忆空间
+- 不同设备之间的记忆完全隔离
+- 同一设备的多次对话可以共享记忆上下文
+
+## 用户画像（UserMemory）
+
+PowerMem 提供 `UserMemory` 类，可自动从对话中提取用户画像信息。
+
+> 📌 **版本说明**：PowerMem 0.3.0+ 版本，用户画像功能支持 OceanBase、SeekDB、SQLite 三种存储后端。
+
+### 启用用户画像
+
+在配置中设置 `enable_user_profile: true` 即可启用：
+
+```yaml
+Memory:
+  powermem:
+    type: powermem
+    enable_user_profile: true  # 启用用户画像
+    llm:
+      provider: qwen
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: qwen-plus
+    embedder:
+      provider: openai
+      config:
+        api_key: sk-xxxxxxxxxxxxxxxx
+        model: text-embedding-v4
+        openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
+    vector_store:
+      provider: sqlite  # 用户画像支持: oceanbase、seekdb、sqlite
+      config: {}
+```
+
+### 用户画像能力
+
+| 能力 | 说明 |
+|------|------|
+| **信息提取** | 自动从对话中提取姓名、年龄、职业、兴趣等 |
+| **持续更新** | 随着对话进行，不断完善用户画像 |
+| **画像检索** | 将用户画像与记忆搜索结合，提升检索相关性 |
+| **智能遗忘** | 基于艾宾浩斯遗忘曲线，淡化过时信息 |
+
+### 工作原理
+
+启用用户画像后，小智在查询记忆时会自动返回：
+1. **用户画像**：用户的基本信息、兴趣爱好等
+2. **相关记忆**：与当前对话相关的历史记忆
+
+> ✅ **版本说明**：PowerMem 0.3.0+ 版本，用户画像功能支持 OceanBase、SeekDB、SQLite 三种存储后端。
+
+## 与其他记忆组件的对比
+
+| 特性 | PowerMem | mem0ai | mem_local_short |
+|------|----------|--------|-----------------|
+| 工作方式 | 本地总结 | 云端接口 | 本地总结 |
+| 存储位置 | 本地/云端DB | 云端 | 本地YAML |
+| 费用 | 取决于LLM和DB | 1000次/月免费 | 完全免费 |
+| 智能检索 | ✅ 向量搜索 | ✅ 向量搜索 | ❌ 全量返回 |
+| 用户画像 | ✅ UserMemory | ❌ | ❌ |
+| 智能遗忘 | ✅ 遗忘曲线 | ❌ | ❌ |
+| 私有部署 | ✅ 支持 | ❌ 仅云端 | ✅ 支持 |
+| 数据库支持 | OceanBase(推荐)/SeekDB/PostgreSQL/SQLite | - | YAML 文件 |
+
+## 常见问题
+
+### 1. API 密钥错误
+
+如果出现 `API key is required` 错误，请检查：
+- `llm_api_key` 和 `embedding_api_key` 是否正确填写
+- API 密钥是否有效
+
+### 2. 模型不存在
+
+如果出现模型不存在的错误，请确认：
+- `llm_model` 和 `embedding_model` 名称是否正确
+- 对应的模型服务是否已开通
+
+### 3. 连接超时
+
+如果出现连接超时，可以尝试：
+- 检查网络连接
+- 如果使用代理，配置 `llm_base_url` 和 `embedding_base_url`
+
+## 测试验证
+
+可以在虚拟环境中测试 PowerMem 是否正常工作：
+
+```bash
+# 激活虚拟环境
+source .venv/bin/activate
+
+# 测试 PowerMem 导入
+python -c "from powermem import AsyncMemory; print('PowerMem 导入成功')"
+
+# 测试 UserMemory 导入（用户画像功能）
+python -c "from powermem import UserMemory; print('UserMemory 导入成功')"
+```
+
+## 更多资源
+
+- [PowerMem 官方文档](https://www.powermem.ai/)
+- [PowerMem GitHub 仓库](https://github.com/oceanbase/powermem)
+- [PowerMem 使用示例](https://github.com/oceanbase/powermem/tree/main/examples)
+- [OceanBase 官网](https://www.oceanbase.com/)
+- [OceanBase GitHub](https://github.com/oceanbase/oceanbase)
+- [SeekDB GitHub](https://github.com/oceanbase/seekdb)（AI原生搜索数据库）
+- [阿里云百炼平台](https://bailian.console.aliyun.com/)
+
@@ -0,0 +1,269 @@
+# ragflow 集成指南
+
+本教程主要是是两部分
+
+- 一、如何部署ragflow
+- 二、如何在智控台配置ragflow接口
+
+如果您对ragflow很熟悉，且已经部署了ragflow，可直接跳过第一部分，直接进入第二部分。但是如果你希望有人指导你部署ragflow，让它能够和`xiaozhi-esp32-server`共同使用`mysql`、`redis`基础服务，以减少资源成本，你需要从第一部分开始。
+
+# 第一部分 如何部署ragflow
+## 第一步， 确认mysql、redis是否可用
+
+ragflow需要依赖`mysql`数据库。如果你之前已经部署`智控台`，说明你已经安装了`mysql`。你可以共用它。
+
+你可以你试一下在宿主机使用`telnet`命令，看看能不能正常访问`mysql`的`3306`端口。
+``` shell
+telnet 127.0.0.1 3306
+
+telnet 127.0.0.1 6379
+```
+如果能访问到`3306`端口和`6379`端口，请忽略以下的内容，直接进入第二步。
+
+如果不能访问，你需要回忆一下，你的`mysql`是怎么安装的。
+
+如果你的mysql是通过自己使用安装包安装的，说明你的`mysql`做了网络隔离。你可能先解决访问`mysql`的`3306`端口这个问题。
+
+如果你`mysql`是通过本项目的`docker-compose_all.yml`安装的。你需要找一下你当时创建数据库的`docker-compose_all.yml`文件，修改以下的内容
+
+修改前
+``` yaml
+  xiaozhi-esp32-server-db:
+    ...
+    networks:
+      - default
+    expose:
+      - "3306:3306"
+  xiaozhi-esp32-server-redis:
+    ...
+    expose:
+      - 6379
+```
+
+修改后
+``` yaml
+  xiaozhi-esp32-server-db:
+    ...
+    networks:
+      - default
+    ports:
+      - "3306:3306"
+  xiaozhi-esp32-server-redis:
+    ...
+    ports:
+      - "6379:6379"
+```
+
+注意是将`xiaozhi-esp32-server-db`和`xiaozhi-esp32-server-redis`下面的`expose`改成`ports`。改完后，需要重新启动。以下是重启mysql的命令：
+
+``` shell
+# 进入你docker-compose_all.yml所在的文件夹，例如我的是xiaozhi-server
+cd xiaozhi-server
+docker compose -f docker-compose_all.yml down
+docker compose -f docker-compose.yml up -d
+```
+
+启动完后，在宿主机再使用`telnet`命令，看看能不能正常访问`mysql`的`3306`端口。
+``` shell
+telnet 127.0.0.1 3306
+
+telnet 127.0.0.1 6379
+```
+正常来说这样就可以访问的了。
+
+## 第二步， 创建数据库和表
+如果你的宿主机，能正常访问mysql数据库，那就在mysql上创建一个名字为`rag_flow`的数据库和`rag_flow`用户，密码为`infini_rag_flow`。
+
+``` sql
+-- 创建数据库
+CREATE DATABASE IF NOT EXISTS rag_flow CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
+
+-- 创建用户并授权
+CREATE USER IF NOT EXISTS 'rag_flow'@'%' IDENTIFIED BY 'infini_rag_flow';
+GRANT ALL PRIVILEGES ON rag_flow.* TO 'rag_flow'@'%';
+
+-- 刷新权限
+FLUSH PRIVILEGES;
+```
+
+## 第三步， 下载ragflow项目
+
+你需要在你电脑找一个文件夹，用来存放ragflow项目。例如我在`/home/system/xiaozhi`文件夹。
+
+你可以使用`git`命令，将ragflow项目下载到这个文件夹，本教程使用的是`v0.22.0`版本进行安装部署。
+```
+git clone https://ghfast.top/https://github.com/infiniflow/ragflow.git
+cd ragflow
+git checkout v0.22.0
+```
+下载完后，进入`docker`文件夹。
+``` shell
+cd docker
+```
+修改`ragflow/docker`文件夹下的`docker-compose.yml`文件，将`ragflow-cpu`和`ragflow-gpu`服务的`depends_on`配置去掉，用于解除`ragflow-cpu`服务对`mysql`的依赖。
+
+这是修改前：
+``` yaml
+  ragflow-cpu:
+    depends_on:
+      mysql:
+        condition: service_healthy
+    profiles:
+      - cpu
+  ...
+  ragflow-gpu:
+    depends_on:
+      mysql:
+        condition: service_healthy
+    profiles:
+      - gpu
+```
+这是修改后：
+``` yaml
+  ragflow-cpu:
+    profiles:
+      - cpu
+  ...
+  ragflow-gpu:
+    profiles:
+      - gpu
+```
+
+接着，修改`ragflow/docker`文件夹下的`docker-compose-base.yml`文件，去掉`mysql`和`redis`的配置。
+
+例如，删除前：
+``` yaml
+services:
+  minio:
+    image: quay.io/minio/minio:RELEASE.2025-06-13T11-33-47Z
+    ...
+  mysql:
+    image: mysql:8.0
+    ...
+  redis:
+    image: redis:6.2-alpine
+    ...
+```
+
+删除后
+``` yaml
+services:
+  minio:
+    image: quay.io/minio/minio:RELEASE.2025-06-13T11-33-47Z
+    ...
+```
+## 第四步，修改环境变量配置
+
+编辑`ragflow/docker`文件夹下的`.env`文件,找到以下配置，逐个搜索，逐个修改！逐个搜索，逐个修改！
+
+下面对于`.env`文件的修改，60%的人会忽略`MYSQL_USER`配置导致ragflow启动不成功，因此，需要强调三次：
+
+强调第一次：如果你的`.env`文件如果没有`MYSQL_USER`配置，请在配置文件增加这项！
+
+强调第二次：如果你的`.env`文件如果没有`MYSQL_USER`配置，请在配置文件增加这项！
+
+强调第三次：如果你的`.env`文件如果没有`MYSQL_USER`配置，请在配置文件增加这项！
+
+``` env
+# 端口设置
+SVR_WEB_HTTP_PORT=8008           # HTTP端口
+SVR_WEB_HTTPS_PORT=8009          # HTTPS端口
+# MySQL配置 - 修改为您本地MySQL的信息
+MYSQL_HOST=host.docker.internal  # 使用host.docker.internal让容器访问主机服务
+MYSQL_PORT=3306                  # 本地MySQL端口
+MYSQL_USER=rag_flow              # 上面创建的用户名，如果没有这项就增加这一项
+MYSQL_PASSWORD=infini_rag_flow   # 上面设置的密码
+MYSQL_DBNAME=rag_flow            # 数据库名称
+
+# Redis配置 - 修改为您本地Redis的信息
+REDIS_HOST=host.docker.internal  # 使用host.docker.internal让容器访问主机服务
+REDIS_PORT=6379                  # 本地Redis端口
+REDIS_PASSWORD=                  # 如果你的Redis没有设置密码，就按这样子填写，否则填写密码
+```
+
+注意，如果你的Redis没有设置密码，还要修改`ragflow/docker`文件夹下`service_conf.yaml.template`，将`infini_rag_flow`替换成空字符串。
+
+修改前
+``` shell
+redis:
+  db: 1
+  password: '${REDIS_PASSWORD:-infini_rag_flow}'
+  host: '${REDIS_HOST:-redis}:6379'
+```
+修改后
+``` shell
+redis:
+  db: 1
+  password: '${REDIS_PASSWORD:-}'
+  host: '${REDIS_HOST:-redis}:6379'
+```
+
+## 第五步，启动ragflow服务
+执行命令：
+``` shell
+docker-compose -f docker-compose.yml up -d
+```
+执行成功后，你可以使用`docker logs -n 20 -f docker-ragflow-cpu-1`命令，查看`docker-ragflow-cpu-1`服务的日志。
+
+如果日志中没有报错，说明ragflow服务启动成功。
+
+# 第五步，注册账号
+你可以在浏览器中访问`http://127.0.0.1:8008`，点击`Sign Up`，注册一个账号。
+
+注册成功后，你可以点击`Sign In`，登录到ragflow服务。如果你想关闭ragflow服务的注册服务，不想让其他人注册账号，你可以在`ragflow/docker`文件夹下的`.env`文件中，将`REGISTER_ENABLED`配置项设置为`0`。
+
+``` dotenv
+REGISTER_ENABLED=0
+```
+修改后，重启启动ragflow服务。
+``` shell
+docker-compose -f docker-compose.yml down
+docker-compose -f docker-compose.yml up -d
+```
+
+# 第六步，配置ragflow服务的模型
+你可以在浏览器中访问`http://127.0.0.1:8008`，点击`Sign In`，登录到ragflow服务。点击页面右上角的`头像`，进入设置页面。
+首先，在左侧导航栏中，点击`模型供应商`，进入到模型配置页面。在右侧的`可选模型`搜索框下，选择`LLM`，在列表选择你使用的模型供应商，点击`添加`，输入你的密钥；
+然后，选择`TEXT EMBEDDING`，在列表选择你使用的模型供应商，点击`添加`，输入你的密钥。
+最后，刷新一下页面，分别点击`设置默认模型`列表的LLM和Embedding，选择你使用的模型即可。请确认你的密钥开通了相应的服务，比如我是用的Embedding模型是xxx供应商的，需要去这个供应商官网查看这个模型是否需要购买资源包才能使用。
+
+
+# 第二部分 配置ragflow服务
+
+# 第一步 登录ragflow服务
+你可以在浏览器中访问`http://127.0.0.1:8008`，点击`Sign In`，登录到ragflow服务。
+
+然后点击右上角的`头像`，进入设置页面。在左侧导航栏中，点击`API`功能，然后点击"API Key"按钮。出现一个弹框，
+
+在弹框中，点击"Create new Key"按钮，生成一个API Key。复制这个`API Key`，你稍后会用到。
+
+# 第二步 配置到智控台
+确保你的智控台版本是`0.8.7`或以上。使用超级管理员账号登录到智控台。
+
+首先，你要先开启知识库功能。在顶部导航栏中，点击`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`知识库`，点击`保存配置`。即可在导航栏看到`知识库`功能。
+
+在顶部导航栏中，点击`模型配置`，在左侧导航栏中，点击`知识库`。在列表中找到`RAG_RAGFlow`，点击`编辑`按钮。
+
+在`服务地址`中，填写`http://你的ragflow服务的局域网IP:8008`，例如我的ragflow服务的局域网IP是`192.168.1.100`，那么我就填写`http://192.168.1.100:8008`。
+
+在`API密钥`中，填写之前复制的`API Key`。
+
+最后点击保存按钮。
+
+# 第二步 创建一个知识库
+使用超级管理员账号登录到智控台。在顶部导航栏中，点击`知识库`，在列表左下脚，点击`新增`按钮。填写一个知识库的名字和描述。点击保存。
+
+为了提高大模型对知识库的理解和召回能力，建议在创建知识库时，填写一个有意义的名字和描述。例如，如果你要创建一个关于`公司介绍`的知识库，那么知识库的名字可以是`公司介绍`，描述可以是`关于公司的相关信息例如公司基本信息、服务项目、联系电话、地址等。`。
+
+保存后，你可以在知识库列表中看到这个知识库。点击刚才创建的知识库的`查看`按钮，进入知识库详情页面。
+
+在知识库详情页面中，左下角点击`新增`按钮，可以上传文档到知识库。
+
+上传后，你可以在知识库详情页面中，看到上传的文档。此时可以点击文档的`解析`按钮，解析文档。
+
+解析完成后，你可以查看解析后的切片信息。你可以在知识库详情页面中，点击`召回测试`按钮，可以测试知识库的召回/检索功能。
+
+# 第三步 让小智使用ragflow知识库
+登录到智控台。在顶部导航栏中，点击`智能体`，找到你要配置的智能体，点击`配置角色`按钮。
+
+在意图识别左侧，点击`编辑功能`按钮，弹出一个弹框。在弹框中选择你要添加的知识库。保存即可。
@@ -28,7 +28,7 @@ telnet 127.0.0.1 3306

 如果不能访问，你需要回忆一下，你的`mysql`是怎么安装的。

-如果你的mysql是通过自己使用安装包安装的，说明你的`mysql`做了网络隔离。你可能先解访问`mysql`的`3306`端口这个问题。
+如果你的mysql是通过自己使用安装包安装的，说明你的`mysql`做了网络隔离。你可能先解决访问`mysql`的`3306`端口这个问题。

 如果你`mysql`是通过本项目的`docker-compose_all.yml`安装的。你需要找一下你当时创建数据库的`docker-compose_all.yml`文件，修改以下的内容

@@ -164,6 +164,8 @@ http://192.168.1.25:8005/voiceprint/health?key=abcd
 # 2、全模块部署时，怎么配置声纹识别

 ## 第一步 配置接口
+首先，你要开启声纹识别功能。在智控台，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`声纹识别`，点击`保存配置`。即可在新建智能体的卡片上看到`声纹识别`按钮。
+
 如果你是全模块部署，使用管理员账号，登录智控台，点击顶部`参数字典`，选择`参数管理`功能。

 然后搜索参数`server.voice_print`，此时，它的值应该是`null`值。
@@ -0,0 +1,64 @@
+# 天气插件使用指南
+
+## 概述
+
+天气插件 `get_weather` 是小智ESP32语音助手的核心功能之一，支持通过语音查询全国各地的天气信息。插件基于和风天气API，提供实时天气和7天天气预报功能。
+
+## API Key 申请指南
+
+### 1. 注册和风天气账号
+
+1. 访问 [和风天气控制台](https://console.qweather.com/)
+2. 注册账号并完成邮箱验证
+3. 登录控制台
+
+### 2. 创建应用获取API Key
+
+1. 进入控制台后，点击右侧["项目管理"](https://console.qweather.com/project?lang=zh) → "创建项目"
+2. 填写项目信息：
+   - **项目名称**：如"小智语音助手"
+3. 点击保存
+4. 项目创建完成后，在该项目中点击"创建凭据"
+5. 填写凭据信息：
+    - **凭据名称**：如"小智语音助手"
+    - **身份认证方式**：选择"API Key"
+6. 点击保存
+7. 在凭据中复制`API Key`，这是第一个关键的配置信息
+
+### 3. 获取API Host
+
+1. 在控制台中点击["设置"](https://console.qweather.com/setting?lang=zh) → "API Host"
+2. 查看分配给你的专属`API Host`地址，这个是第二个关键的配置信息
+
+以上操作，会得到两个重要的配置信息:`API Key`和`API Host`
+
+## 配置方式(任选一种)
+
+### 方式1. 如果你使用了智控台部署（推荐）
+
+1. 登录智控台
+2. 进入"角色配置"页面
+3. 选择要配置的智能体
+4. 点击"编辑功能"按钮
+5. 在右侧参数配置区域找到"天气查询"插件
+6. 勾选"天气查询"
+7. 将复制过来的第一个关键配置`API Key`,填入到`天气插件 API 密钥`里
+8. 将复制过来的第二个关键配置`API Host`,填入到`开发者 API Host`里
+9. 保存配置，再保存智能体配置
+
+### 方式2. 如果你只是单模块xiaozhi-server部署
+
+在 `data/.config.yaml` 中配置：
+
+1. 将复制过来的第一个关键配置`API Key`,填入到`api_key`里
+2. 将复制过来的第二个关键配置`API Host`,填入到`api_host`里
+3. 将你所在的城市填入到`default_location`里，例如`广州`
+
+```yaml
+plugins:
+  get_weather:
+    api_key: "你的和风天气API密钥"
+    api_host: "你的和风天气API主机地址"
+    default_location: "你的默认查询城市"
+```
+
@@ -8,6 +8,7 @@
    *   [3.1. `xiaozhi-server` (核心AI引擎 - Python实现)](#31-xiaozhi-server-核心ai引擎---python实现)
    *   [3.2. `manager-api` (管理后端 - Java Spring Boot实现)](#32-manager-api-管理后端---java-spring-boot实现)
    *   [3.3. `manager-web` (Web管理前端 - Vue.js实现)](#33-manager-web-web管理前端---vuejs实现)
+    *   [3.4. `manager-mobile` (移动管理端 - uni-app+Vue3实现)](#34-manager-mobile-移动管理端---uni-appvue3实现)
 4.  [数据流与交互机制](#4-数据流与交互机制)
 5.  [核心功能概要](#5-核心功能概要)
 6.  [部署与配置概述](#6-部署与配置概述)
@@ -58,6 +59,14 @@
    *   （潜在功能）监控系统运行状态、查看日志、进行故障排查等。
    *   与 `manager-api` 提供的所有后端管理功能进行全面的交互。

+5.  **`manager-mobile` (智控台移动版 - uni-app实现):**
+    这是一个基于uni-app v3 + Vue 3 + Vite的跨端移动管理端，支持App（Android & iOS）和微信小程序。其主要能力包括：
+    *   提供移动设备上的便捷管理界面，与manager-web功能类似但针对移动端进行了优化。
+    *   支持用户登录、设备管理、AI服务配置等核心功能。
+    *   跨平台适配，一套代码可同时运行在iOS、Android和微信小程序上。
+    *   基于alova + @alova/adapter-uniapp实现网络请求，与manager-api无缝集成。
+    *   使用pinia进行状态管理，确保数据一致性。
+
 **高层交互流程概述:**

 *   **语音交互主线:** **ESP32设备**捕捉到用户语音后，通过**WebSocket**将音频数据实时传输给**`xiaozhi-server`**。`xiaozhi-server`完成一系列AI处理（VAD、ASR、LLM交互、TTS）后，再通过WebSocket将合成的语音回复发送回ESP32设备进行播放。所有与语音直接相关的实时交互均在此链路完成。
@@ -71,6 +80,7 @@ xiaozhi-esp32-server
  ├─ xiaozhi-server 8000 端口 Python语言开发 负责与esp32通信
  ├─ manager-web 8001 端口 Node.js+Vue开发 负责提供控制台的web界面
  ├─ manager-api 8002 端口 Java语言开发 负责提供控制台的api
+  └─ manager-mobile 跨平台移动应用 uni-app+Vue3开发 负责提供移动版智控台管理
 ```

 ---
@@ -294,6 +304,68 @@ xiaozhi-esp32-server

 ---

+### 3.4. `manager-mobile` (智控台移动版 - uni-app实现)
+
+`manager-mobile` 组件是一个基于uni-app v3 + Vue 3 + Vite的跨端移动管理端，支持App（Android & iOS）和微信小程序。它为系统管理员提供了移动端的管理界面，使得管理操作更加便捷。
+
+*   **核心目标:**
+    *   提供移动设备上的便捷管理界面，与manager-web功能类似但针对移动端进行了优化。
+    *   支持用户登录、设备管理、AI服务配置等核心功能。
+    *   跨平台适配，一套代码可同时运行在iOS、Android和微信小程序上。
+    *   为移动用户提供流畅、高效的管理体验。
+
+*   **平台兼容性:**
+
+| H5 | iOS | Android | 微信小程序 |
+| -- | --- | ------- | ---------- | 
+| √  | √   | √       | √          | 
+
+*   **核心技术栈:**
+    *   **uni-app v3:** 一个使用Vue.js开发所有前端应用的框架，支持iOS、Android、H5、以及各种小程序。
+    *   **Vue 3:** 用于构建用户界面的渐进式框架，提供了更好的性能和新特性。
+    *   **Vite:** 下一代前端开发与构建工具，提供极速的开发体验。
+    *   **pnpm:** 快速、节省磁盘空间的包管理器。
+    *   **alova:** 轻量级、灵活的请求策略库，搭配@alova/adapter-uniapp适配uni-app环境。
+    *   **pinia:** Vue的状态管理库，替代Vuex，提供更简洁的API和更好的TypeScript支持。
+    *   **UnoCSS:** 具有高性能且极具灵活性的即时原子化CSS引擎。
+    *   **TypeScript:** 提供类型安全的开发体验。
+
+*   **关键实现细节:**
+
+    1.  **跨平台架构:**
+        *   基于uni-app框架，实现了一套代码多端运行的目标，大幅减少了开发和维护成本。
+        *   针对不同平台的特性和限制，通过条件编译进行平台特定的代码处理。
+
+    2.  **项目结构:**
+        *   **`src/App.vue`:** 应用的根组件，定义了全局的样式和配置。
+        *   **`src/main.ts`:** 应用的入口文件，负责初始化Vue实例、注册插件和路由拦截器。
+        *   **`src/pages/`:** 存放应用的页面组件，如登录页、设备管理页等。
+        *   **`src/layouts/`:** 定义应用的布局组件，如默认布局、带tabbar的布局等。
+        *   **`src/api/`:** 封装与后端API的通信逻辑。
+        *   **`src/store/`:** 使用pinia进行状态管理。
+        *   **`src/components/`:** 存放可复用的组件。
+        *   **`src/utils/`:** 提供通用的工具函数。
+
+    3.  **网络请求:**
+        *   基于alova + @alova/adapter-uniapp实现网络请求，统一处理请求头、认证、错误等。
+        *   请求地址和环境配置通过.env文件管理，支持不同环境的切换。
+
+    4.  **路由与鉴权:**
+        *   使用uni-app的路由系统，结合路由拦截器实现页面的登录验证和权限控制。
+        *   未登录用户访问需要认证的页面时，会被重定向到登录页。
+
+    5.  **状态管理:**
+        *   使用pinia管理应用状态，如用户信息、设备列表等。
+        *   通过pinia-plugin-persistedstate插件实现状态的持久化存储。
+
+    6.  **构建与发布:**
+        *   支持多种构建命令，如构建微信小程序、Android和iOS App等。
+        *   使用HBuilderX进行App的云打包，简化了打包流程。
+
+`manager-mobile` 通过这些技术的应用，为用户提供了一个功能完备、体验流畅的移动端管理工具，使得管理员可以随时随地进行系统管理和配置。
+
+---
+
 ## 4. 数据流与交互机制

 `xiaozhi-esp32-server` 系统通过各组件间定义清晰的数据流和交互协议来协同工作。主要的通信方式依赖于针对实时交互优化的WebSocket协议和适用于客户端-服务器请求的RESTful API。
@@ -8,6 +8,7 @@
    *   [3.1. `xiaozhi-server` (Core AI Engine - Python Implementation)](#31-xiaozhi-server-core-ai-engine---python-implementation)
    *   [3.2. `manager-api` (Management Backend - Java Spring Boot Implementation)](#32-manager-api-management-backend---java-spring-boot-implementation)
    *   [3.3. `manager-web` (Web Management Frontend - Vue.js Implementation)](#33-manager-web-web-management-frontend---vuejs-implementation)
+    *   [3.4. `manager-mobile` (Mobile Management Console - uni-app Implementation)](#34-manager-mobile-mobile-management-console---uniapp-implementation)
 4.  [Data Flow and Interaction Mechanisms](#4-data-flow-and-interaction-mechanisms)
 5.  [Key Features Summary](#5-key-features-summary)
 6.  [Deployment and Configuration Overview](#6-deployment-and-configuration-overview)
@@ -72,6 +73,7 @@ xiaozhi-esp32-server
  ├─ xiaozhi-server Port 8000 Python development Responsible for ESP32 communication
  ├─ manager-web Port 8001 Node.js+Vue development Responsible for providing web interface for console
  ├─ manager-api Port 8002 Java development Responsible for providing console API
+  └─ manager-mobile Cross-platform mobile application uni-app+Vue3 development Responsible for providing mobile console management
 ```

 ---
@@ -190,7 +192,70 @@ The `manager-web` is a Single Page Application (SPA) providing the administrativ
    4.  **State Management (`src/store/index.js`):** Vuex manages global state (user info, device lists, etc.) via state, getters, mutations, and actions (often involving API calls).
    5.  **API Communication (`src/apis/`):** Modularized API service files make asynchronous calls to `manager-api`.
    6.  **Build Process & PWA Features:** Vue CLI (Webpack) bundles assets. Workbox enables PWA features like caching.
-    7.  **Environment Configuration (`.env` files):** Manages settings like the `manager-api` base URL for different environments.
+    7.  **Environment Configuration (`.env` files):**
+        *   The `.env` (and `.env.development`, `.env.production`, etc.) files in the project root directory are used to define environment variables. These variables (such as `VUE_APP_API_BASE_URL` to specify the base URL of `manager-api`) can be accessed in the application code through `process.env.VUE_APP_XXX`, allowing configuration of different parameters for different build environments (development, testing, production).
+
+`manager-web` constructs a powerful, maintainable, and user-friendly management interface through the comprehensive application of these technologies, providing solid frontend support for the configuration and monitoring of the `xiaozhi-esp32-server` system.
+
+### 3.4. `manager-mobile` (Mobile Management Console - uni-app Implementation)
+
+The `manager-mobile` component is a cross-platform mobile management application based on uni-app v3 + Vue 3 + Vite, supporting App (Android & iOS) and WeChat Mini Program. It provides system administrators with a mobile management interface, making management operations more convenient.
+
+*   **Core Objectives:**
+    *   Provide a convenient management interface on mobile devices, similar in functionality to manager-web but optimized for mobile platforms.
+    *   Support core functions such as user login, device management, and AI service configuration.
+    *   Cross-platform adaptation, allowing a single codebase to run on iOS, Android, and WeChat Mini Programs.
+    *   Provide mobile users with a smooth and efficient management experience.
+
+*   **Platform Compatibility:**
+
+| H5 | iOS | Android | WeChat Mini Program |
+| -- | --- | ------- | ------------------ | 
+| ×  | √   | √       | √                  | 
+
+*   **Core Technologies:**
+    *   **uni-app v3:** A framework for developing all frontend applications using Vue.js, supporting iOS, Android, H5, and various mini-programs.
+    *   **Vue 3:** A progressive framework for building user interfaces, providing better performance and new features.
+    *   **Vite:** The next generation frontend development and build tool, offering an extremely fast development experience.
+    *   **pnpm:** A fast, disk space-efficient package manager.
+    *   **alova:** A lightweight, flexible request strategy library, paired with @alova/adapter-uniapp to adapt to the uni-app environment.
+    *   **pinia:** State management library for Vue, replacing Vuex, providing a simpler API and better TypeScript support.
+    *   **UnoCSS:** A high-performance and extremely flexible instant atomic CSS engine.
+    *   **TypeScript:** Provides a type-safe development experience.
+
+*   **Key Implementation Details:**
+
+    1.  **Cross-Platform Architecture:**
+        *   Based on the uni-app framework, achieving the goal of "write once, run anywhere," significantly reducing development and maintenance costs.
+        *   Handling platform-specific code through conditional compilation to address the characteristics and limitations of different platforms.
+
+    2.  **Project Structure:**
+        *   **`src/App.vue`:** The root component of the application, defining global styles and configurations.
+        *   **`src/main.ts`:** The entry file of the application, responsible for initializing the Vue instance, registering plugins, and setting up route interceptors.
+        *   **`src/pages/`:** Stores application page components, such as login pages, device management pages, etc.
+        *   **`src/layouts/`:** Defines application layout components, such as default layouts, layouts with tabbar, etc.
+        *   **`src/api/`:** Encapsulates communication logic with backend APIs.
+        *   **`src/store/`:** Uses pinia for state management.
+        *   **`src/components/`:** Stores reusable components.
+        *   **`src/utils/`:** Provides common utility functions.
+
+    3.  **Network Requests:**
+        *   Implements network requests based on alova + @alova/adapter-uniapp, unified handling of request headers, authentication, errors, etc.
+        *   Request addresses and environment configurations are managed through .env files, supporting switching between different environments.
+
+    4.  **Routing and Authentication:**
+        *   Uses uni-app's routing system, combined with route interceptors to implement page login verification and permission control.
+        *   When unlogged users access pages requiring authentication, they are redirected to the login page.
+
+    5.  **State Management:**
+        *   Uses pinia to manage application state, such as user information, device lists, etc.
+        *   Implements persistent storage of state through the pinia-plugin-persistedstate plugin.
+
+    6.  **Build and Release:**
+        *   Supports multiple build commands, such as building WeChat Mini Programs, Android, and iOS Apps.
+        *   Uses HBuilderX for cloud packaging of Apps, simplifying the packaging process.
+
+`manager-mobile` provides users with a fully functional, smooth mobile management tool through the application of these technologies, allowing administrators to perform system management and configuration anytime, anywhere.

 ---

@@ -24,6 +24,8 @@
        <hutool.version>5.8.24</hutool.version>
        <jsoup.version>1.19.1</jsoup.version>
        <knife4j.version>4.6.0</knife4j.version>
+        <springdoc.version>2.8.8</springdoc.version>
+        <commons-lang3.version>3.18.0</commons-lang3.version>
        <shiro.version>2.0.2</shiro.version>
        <captcha.version>1.6.2</captcha.version>
        <guava.version>33.0.0-jre</guava.version>
@@ -75,6 +77,7 @@
            <version>${captcha.version}</version>
        </dependency>

+
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-websocket</artifactId>
@@ -190,11 +193,30 @@
            <artifactId>jsoup</artifactId>
            <version>${jsoup.version}</version>
        </dependency>
+        <!--knife4j -->
        <dependency>
            <groupId>com.github.xingfudeshi</groupId>
            <artifactId>knife4j-openapi3-jakarta-spring-boot-starter</artifactId>
            <version>${knife4j.version}</version>
        </dependency>
+        <!-- BouncyCastle SM2加密 -->
+        <dependency>
+            <groupId>org.bouncycastle</groupId>
+            <artifactId>bcprov-jdk18on</artifactId>
+            <version>1.78</version>
+        </dependency>
+        <!-- springdoc -->
+        <dependency>
+            <groupId>org.springdoc</groupId>
+            <artifactId>springdoc-openapi-starter-webmvc-ui</artifactId>
+            <version>${springdoc.version}</version>
+        </dependency>
+        <!-- 日常工具包 -->
+        <dependency>
+            <groupId>org.apache.commons</groupId>
+            <artifactId>commons-lang3</artifactId>
+            <version>${commons-lang3.version}</version>
+        </dependency>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
@@ -2,7 +2,9 @@ package xiaozhi.common.config;

 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
+import org.springframework.http.client.JdkClientHttpRequestFactory;
 import org.springframework.web.client.RestTemplate;
+import java.time.Duration;

 /**
 * RestTemplate配置
@@ -12,6 +14,8 @@ public class RestTemplateConfig {

    @Bean
    public RestTemplate restTemplate() {
-        return new RestTemplate();
+        JdkClientHttpRequestFactory factory = new JdkClientHttpRequestFactory();
+        factory.setReadTimeout(Duration.ofSeconds(30));
+        return new RestTemplate(factory);
    }
 }
@@ -43,7 +43,7 @@ public class SwaggerConfig {
    public GroupedOpenApi oatApi() {
        return GroupedOpenApi.builder()
                .group("ota")
-                .pathsToMatch("/ota/**")
+                .pathsToMatch("/ota/**", "/otaMag/**")
                .build();
    }

@@ -79,6 +79,22 @@ public class SwaggerConfig {
                .build();
    }

+    @Bean
+    public GroupedOpenApi knowledgeApi() {
+        return GroupedOpenApi.builder()
+                .group("knowledge")
+                .pathsToMatch("/datasets/**")
+                .build();
+    }
+
+    @Bean
+    public GroupedOpenApi botApi() {
+        return GroupedOpenApi.builder()
+                .group("bot")
+                .pathsToMatch("/api/v1/**")
+                .build();
+    }
+
    @Bean
    public OpenAPI customOpenAPI() {
        return new OpenAPI().info(new Info()
@@ -86,11 +86,26 @@ public interface Constant {
     */
    String SERVER_SECRET = "server.secret";

+    /**
+     * SM2公钥
+     */
+    String SM2_PUBLIC_KEY = "server.public_key";
+
+    /**
+     * SM2私钥
+     */
+    String SM2_PRIVATE_KEY = "server.private_key";
+
    /**
     * websocket地址
     */
    String SERVER_WEBSOCKET = "server.websocket";

+    /**
+     * mqtt gateway 配置
+     */
+    String SERVER_MQTT_GATEWAY = "server.mqtt_gateway";
+
    /**
     * ota地址
     */
@@ -121,11 +136,46 @@ public interface Constant {
     */
    String SERVER_VOICE_PRINT = "server.voice_print";

+    /**
+     * mqtt密钥
+     */
+    String SERVER_MQTT_SECRET = "server.mqtt_signature_key";
+
+    /**
+     * WebSocket认证开关
+     */
+    String SERVER_AUTH_ENABLED = "server.auth.enabled";
+
    /**
     * 无记忆
     */
    String MEMORY_NO_MEM = "Memory_nomem";

+    /**
+     * 仅上报聊天记录（不总结记忆）
+     */
+    String MEMORY_MEM_REPORT_ONLY = "Memory_mem_report_only";
+
+    /**
+     * Mem0AI记忆
+     */
+    String MEMORY_MEM0AI = "Memory_mem0ai";
+
+    /**
+     * PowerMem记忆
+     */
+    String MEMORY_POWERMEM = "Memory_powermem";
+
+    /**
+     * 火山引擎双声道语音克隆
+     */
+    String VOICE_CLONE_HUOSHAN_DOUBLE_STREAM = "huoshan_double_stream";
+
+    /**
+     * RAG配置类型
+     */
+    String RAG_CONFIG_TYPE = "RAG";
+
    enum SysBaseParam {
        /**
         * ICP备案号
@@ -151,6 +201,38 @@ public interface Constant {
        }
    }

+    /**
+     * 训练状态
+     */
+    enum TrainStatus {
+        /**
+         * 未训练
+         */
+        NOT_TRAINED(0),
+        /**
+         * 训练中
+         */
+        TRAINING(1),
+        /**
+         * 已训练
+         */
+        TRAINED(2),
+        /**
+         * 训练失败
+         */
+        TRAIN_FAILED(3);
+
+        private final int code;
+
+        TrainStatus(int code) {
+            this.code = code;
+        }
+
+        public int getCode() {
+            return code;
+        }
+    }
+
    /**
     * 系统短信
     */
@@ -237,7 +319,7 @@ public interface Constant {
    /**
     * 版本号
     */
-    public static final String VERSION = "0.7.2";
+    public static final String VERSION = "0.9.3";

    /**
     * 无效固件URL
@@ -55,4 +55,205 @@ public interface ErrorCode {

    int OTA_DEVICE_NOT_FOUND = 10041;
    int OTA_DEVICE_NEED_BIND = 10042;
+
+    // 新增错误编码
+    int DELETE_DATA_FAILED = 10043;
+    int USER_NOT_LOGIN = 10044;
+    int WEB_SOCKET_CONNECT_FAILED = 10045;
+    int VOICE_PRINT_SAVE_ERROR = 10046;
+    int TODAY_SMS_LIMIT_REACHED = 10047;
+    int OLD_PASSWORD_ERROR = 10048;
+    int INVALID_LLM_TYPE = 10049;
+    int TOKEN_GENERATE_ERROR = 10050;
+    int RESOURCE_NOT_FOUND = 10051;
+
+    // 新增错误编码
+    int DEFAULT_AGENT_NOT_FOUND = 10052;
+    int AGENT_NOT_FOUND = 10053;
+    int VOICEPRINT_API_NOT_CONFIGURED = 10054;
+    int SMS_SEND_FAILED = 10055;
+    int SMS_CONNECTION_FAILED = 10056;
+    int AGENT_VOICEPRINT_CREATE_FAILED = 10057;
+    int AGENT_VOICEPRINT_UPDATE_FAILED = 10058;
+    int AGENT_VOICEPRINT_DELETE_FAILED = 10059;
+    int SMS_SEND_TOO_FREQUENTLY = 10060;
+    int ACTIVATION_CODE_EMPTY = 10061;
+    int ACTIVATION_CODE_ERROR = 10062;
+    int DEVICE_ALREADY_ACTIVATED = 10063;
+    // 默认模型删除错误
+    int DEFAULT_MODEL_DELETE_ERROR = 10064;
+    // 登录相关错误码
+    int ADD_DATA_FAILED = 10065; // 新增数据失败
+    int UPDATE_DATA_FAILED = 10066; // 修改数据失败
+    int SMS_CAPTCHA_ERROR = 10067; // 短信验证码错误
+    int MOBILE_REGISTER_DISABLED = 10068; // 未开启手机注册
+    int USERNAME_NOT_PHONE = 10069; // 用户名不是手机号码
+    int PHONE_ALREADY_REGISTERED = 10070; // 手机号码已注册
+    int PHONE_NOT_REGISTERED = 10071; // 手机号码未注册
+    int USER_REGISTER_DISABLED = 10072; // 不允许用户注册
+    int RETRIEVE_PASSWORD_DISABLED = 10073; // 未开启找回密码功能
+    int PHONE_FORMAT_ERROR = 10074; // 手机号码格式不正确
+    int SMS_CODE_ERROR = 10075; // 手机验证码错误
+
+    // 字典类型相关错误码
+    int DICT_TYPE_NOT_EXIST = 10076; // 字典类型不存在
+    int DICT_TYPE_DUPLICATE = 10077; // 字典类型编码重复
+
+    // 资源处理相关错误码
+    int RESOURCE_READ_ERROR = 10078; // 读取资源失败
+
+    // 智能体相关错误码
+    int LLM_INTENT_PARAMS_MISMATCH = 10079; // LLM大模型和Intent意图识别，选择参数不匹配
+
+    // 声纹相关错误码
+    int VOICEPRINT_ALREADY_REGISTERED = 10080; // 此声音声纹已经注册
+    int VOICEPRINT_DELETE_ERROR = 10081; // 删除声纹出现错误
+    int VOICEPRINT_UPDATE_NOT_ALLOWED = 10082; // 声纹修改不允许，声音已注册
+    int VOICEPRINT_UPDATE_ADMIN_ERROR = 10083; // 修改声纹错误，请联系管理员
+    int VOICEPRINT_API_URI_ERROR = 10084; // 声纹接口地址错误
+    int VOICEPRINT_AUDIO_NOT_BELONG_AGENT = 10085; // 音频数据不属于智能体
+    int VOICEPRINT_AUDIO_EMPTY = 10086; // 音频数据为空
+    int VOICEPRINT_REGISTER_REQUEST_ERROR = 10087; // 声纹保存请求失败
+    int VOICEPRINT_REGISTER_PROCESS_ERROR = 10088; // 声纹保存处理失败
+    int VOICEPRINT_UNREGISTER_REQUEST_ERROR = 10089; // 声纹注销请求失败
+    int VOICEPRINT_UNREGISTER_PROCESS_ERROR = 10090; // 声纹注销处理失败
+    int VOICEPRINT_IDENTIFY_REQUEST_ERROR = 10091; // 声纹识别请求失败
+
+    int LLM_NOT_EXIST = 10092; // 设置的LLM不存在
+    int MODEL_REFERENCED_BY_AGENT = 10093; // 该模型配置已被智能体引用，无法删除
+    int LLM_REFERENCED_BY_INTENT = 10094; // 该LLM模型已被意图识别配置引用，无法删除
+
+    // 服务端管理相关错误码
+    int INVALID_SERVER_ACTION = 10095; // 无效服务端操作
+    int SERVER_WEBSOCKET_NOT_CONFIGURED = 10096; // 未配置服务端WebSocket地址
+    int TARGET_WEBSOCKET_NOT_EXIST = 10097; // 目标WebSocket地址不存在
+
+    // 参数验证相关错误码
+    int WEBSOCKET_URLS_EMPTY = 10098; // WebSocket地址列表不能为空
+    int WEBSOCKET_URL_LOCALHOST = 10099; // WebSocket地址不能使用localhost或127.0.0.1
+    int WEBSOCKET_URL_FORMAT_ERROR = 10100; // WebSocket地址格式不正确
+    int WEBSOCKET_CONNECTION_FAILED = 10101; // WebSocket连接测试失败
+    int OTA_URL_EMPTY = 10102; // OTA地址不能为空
+    int OTA_URL_LOCALHOST = 10103; // OTA地址不能使用localhost或127.0.0.1
+    int OTA_URL_PROTOCOL_ERROR = 10104; // OTA地址必须以http或https开头
+    int OTA_URL_FORMAT_ERROR = 10105; // OTA地址必须以/ota/结尾
+    int OTA_INTERFACE_ACCESS_FAILED = 10106; // OTA接口访问失败
+    int OTA_INTERFACE_FORMAT_ERROR = 10107; // OTA接口返回内容格式不正确
+    int OTA_INTERFACE_VALIDATION_FAILED = 10108; // OTA接口验证失败
+    int MCP_URL_EMPTY = 10109; // MCP地址不能为空
+    int MCP_URL_LOCALHOST = 10110; // MCP地址不能使用localhost或127.0.0.1
+    int MCP_URL_INVALID = 10111; // 不是正确的MCP地址
+    int MCP_INTERFACE_ACCESS_FAILED = 10112; // MCP接口访问失败
+    int MCP_INTERFACE_FORMAT_ERROR = 10113; // MCP接口返回内容格式不正确
+    int MCP_INTERFACE_VALIDATION_FAILED = 10114; // MCP接口验证失败
+    int VOICEPRINT_URL_EMPTY = 10115; // 声纹接口地址不能为空
+    int VOICEPRINT_URL_LOCALHOST = 10116; // 声纹接口地址不能使用localhost或127.0.0.1
+    int VOICEPRINT_URL_INVALID = 10117; // 不是正确的声纹接口地址
+    int VOICEPRINT_URL_PROTOCOL_ERROR = 10118; // 声纹接口地址必须以http或https开头
+    int VOICEPRINT_INTERFACE_ACCESS_FAILED = 10119; // 声纹接口访问失败
+    int VOICEPRINT_INTERFACE_FORMAT_ERROR = 10120; // 声纹接口返回内容格式不正确
+    int VOICEPRINT_INTERFACE_VALIDATION_FAILED = 10121; // 声纹接口验证失败
+    int MQTT_SECRET_EMPTY = 10122; // mqtt密钥不能为空
+    int MQTT_SECRET_LENGTH_INSECURE = 10123; // mqtt密钥长度不安全
+    int MQTT_SECRET_CHARACTER_INSECURE = 10124; // mqtt密钥必须同时包含大小写字母
+    int MQTT_SECRET_WEAK_PASSWORD = 10125; // mqtt密钥包含弱密码
+    int DICT_LABEL_DUPLICATE = 10128; // 字典标签重复
+    int SM2_KEY_NOT_CONFIGURED = 10129; // SM2密钥未配置
+    int SM2_DECRYPT_ERROR = 10130; // SM2解密失败
+    int MODEL_TYPE_PROVIDE_CODE_NOT_NULL = 10131; // modelType和provideCode不能为空
+
+    // 聊天记录相关错误码
+    int CHAT_HISTORY_NO_PERMISSION = 10132; // 没有权限查看该智能体的聊天记录
+    int CHAT_HISTORY_SESSION_ID_NOT_NULL = 10133; // 会话ID不能为空
+    int CHAT_HISTORY_AGENT_ID_NOT_NULL = 10134; // 智能体ID不能为空
+    int CHAT_HISTORY_DOWNLOAD_FAILED = 10135; // 聊天记录下载失败
+    int DOWNLOAD_LINK_EXPIRED = 10136; // 下载链接已过期或无效
+    int DOWNLOAD_LINK_INVALID = 10137; // 下载链接无效
+    int CHAT_ROLE_USER = 10138; // 用户角色
+    int CHAT_ROLE_AGENT = 10139; // 智能体角色
+
+    // 声音克隆相关错误码
+    int VOICE_CLONE_AUDIO_EMPTY = 10140; // 音频文件不能为空
+    int VOICE_CLONE_NOT_AUDIO_FILE = 10141; // 只支持音频文件
+    int VOICE_CLONE_AUDIO_TOO_LARGE = 10142; // 音频文件大小不能超过10MB
+    int VOICE_CLONE_UPLOAD_FAILED = 10143; // 上传失败
+    int VOICE_CLONE_RECORD_NOT_EXIST = 10144; // 声音克隆记录不存在
+    int VOICE_RESOURCE_INFO_EMPTY = 10145; // 音色资源信息不能为空
+    int VOICE_RESOURCE_PLATFORM_NAME_EMPTY = 10146; // 平台名称不能为空
+    int VOICE_RESOURCE_ID_EMPTY = 10147; // 音色ID不能为空
+    int VOICE_RESOURCE_ACCOUNT_EMPTY = 10148; // 归属账号不能为空
+    int VOICE_RESOURCE_DELETE_ID_EMPTY = 10149; // 删除的音色资源ID不能为空
+    int VOICE_RESOURCE_NO_PERMISSION = 10150; // 您没有权限操作该记录
+    int VOICE_CLONE_AUDIO_NOT_UPLOADED = 10151; // 请先上传音频文件
+    int VOICE_CLONE_MODEL_CONFIG_NOT_FOUND = 10152; // 模型配置未找到
+    int VOICE_CLONE_MODEL_TYPE_NOT_FOUND = 10153; // 模型类型未找到
+    int VOICE_CLONE_TRAINING_FAILED = 10154; // 训练失败
+    int VOICE_CLONE_HUOSHAN_CONFIG_MISSING = 10155; // 火山引擎缺少配置
+    int VOICE_CLONE_RESPONSE_FORMAT_ERROR = 10156; // 响应格式错误
+    int VOICE_CLONE_REQUEST_FAILED = 10157; // 请求失败
+    int VOICE_CLONE_PREFIX = 10158; // 复刻音色前缀
+    int VOICE_ID_ALREADY_EXISTS = 10159; // 音色ID已存在
+    int VOICE_CLONE_HUOSHAN_VOICE_ID_ERROR = 10160; // 火山引擎音色ID格式错误
+
+    // 设备相关错误码
+    int MAC_ADDRESS_ALREADY_EXISTS = 10161; // Mac地址已存在
+    // 模型相关错误码
+    int MODEL_PROVIDER_NOT_EXIST = 10162; // 供应器不存在
+
+    // 知识库相关错误码
+    int Knowledge_Base_RECORD_NOT_EXISTS = 10163; // 知识库记录不存在
+    int RAG_CONFIG_NOT_FOUND = 10164; // RAG配置未找到
+    int RAG_CONFIG_TYPE_ERROR = 10165; // RAG配置类型错误
+    int RAG_DEFAULT_CONFIG_NOT_FOUND = 10166; // 默认RAG配置未找到
+    int RAG_API_ERROR = 10167; // RAG调用失败
+    int UPLOAD_FILE_ERROR = 10168; // 上传文件失败
+    int NO_PERMISSION = 10169; // 没有权限
+    int KNOWLEDGE_BASE_NAME_EXISTS = 10170; // 同名知识库已存在
+    int RAG_API_ERROR_URL_NULL = 10171; // RAG配置中base_url为空，请完善配置
+    int RAG_API_ERROR_API_KEY_NULL = 10172; // RAG配置中api_key为空，请完善配置
+    int RAG_API_ERROR_API_KEY_INVALID = 10173; // RAG配置中api_key包含占位符，请替换为实际的API密钥
+    int RAG_API_ERROR_URL_INVALID = 10174; // RAG配置中base_url格式不正确，请检查协议是否正确
+    int RAG_DATASET_ID_NOT_NULL = 10176; // RAG配置中dataset_id不能为空
+    int RAG_MODEL_ID_NOT_NULL = 10177; // RAG配置中model_id不能为空
+    int RAG_DATASET_ID_AND_MODEL_ID_NOT_NULL = 10178; // RAG配置中dataset_id和model_id不能为空
+    int RAG_FILE_NAME_NOT_NULL = 10179; // 文件名称不能为空
+    int RAG_FILE_CONTENT_EMPTY = 10180; // 文件内容不能为空
+
+    // 设备相关错误码（补充）
+    int MCA_NOT_NULL = 10175; // mac地址不能为空
+
+    // 音色克隆（补充）
+    int VOICE_CLONE_NAME_NOT_NULL = 10181; // 音色克隆名称不能为空
+    int VOICE_CLONE_AUDIO_NOT_FOUND = 10182; // 音色克隆音频不存在
+
+    // 智能体模板相关错误码(补充)
+    int AGENT_TEMPLATE_NOT_FOUND = 10183; // 默认智能体未找到
+
+    // 知识库适配器相关错误码
+    int RAG_ADAPTER_TYPE_NOT_SUPPORTED = 10184; // 不支持的适配器类型
+    int RAG_CONFIG_VALIDATION_FAILED = 10185; // RAG配置验证失败
+    int RAG_ADAPTER_CREATION_FAILED = 10186; // 适配器创建失败
+    int RAG_ADAPTER_INIT_FAILED = 10187; // 适配器初始化失败
+    int RAG_ADAPTER_CONNECTION_FAILED = 10188; // 适配器连接测试失败
+    int RAG_ADAPTER_OPERATION_FAILED = 10189; // 适配器操作失败
+    int RAG_ADAPTER_NOT_FOUND = 10190; // 适配器未找到
+    int RAG_ADAPTER_CACHE_ERROR = 10191; // 适配器缓存错误
+    int RAG_ADAPTER_TYPE_NOT_FOUND = 10192; // 适配器类型未找到
+
+    // 设备工具相关错误码
+    int DEVICE_ID_NOT_NULL = 10193; // 设备ID不能为空
+    int DEVICE_NOT_EXIST = 10194; // 设备不存在
+    int OTA_UPLOAD_COUNT_EXCEED = 10195; // OTA上传次数超过限制
+
+    // 智能体标签相关错误码
+    int AGENT_TAG_NAME_DUPLICATE = 10196; // 标签名称已存在
+    int AGENT_TAG_NAME_EMPTY = 10197; // 标签名称不能为空
+    int AGENT_TAG_NOT_EXIST = 10198; // 标签不存在
+
+    int RAG_DOCUMENT_PARSING_DELETE_ERROR = 10199; // 文档解析中，禁止删除
+
+    // 智能体MCP相关错误码
+    int MCP_ACCESS_POINT_ADDRESS_NO_PERMISSION = 10200; // 没有权限查看该智能体的MCP接入点地址
+    int MCP_ACCESS_POINT_ADDRESS_NOT_CONFIGURED = 10201; // 请联系管理员进入参数管理配置mcp接入点地址
+    int MCP_ACCESS_POINT_TOOLS_LIST_NO_PERMISSION = 10202; // 没有权限查看该智能体的MCP工具列表
 }
@@ -13,23 +13,25 @@ public class RenException extends RuntimeException {
    private String msg;

    public RenException(int code) {
+        super(MessageUtils.getMessage(code));
        this.code = code;
        this.msg = MessageUtils.getMessage(code);
    }

    public RenException(int code, String... params) {
+        super(MessageUtils.getMessage(code, params));
        this.code = code;
        this.msg = MessageUtils.getMessage(code, params);
    }

    public RenException(int code, Throwable e) {
-        super(e);
+        super(MessageUtils.getMessage(code), e);
        this.code = code;
        this.msg = MessageUtils.getMessage(code);
    }

    public RenException(int code, Throwable e, String... params) {
-        super(e);
+        super(MessageUtils.getMessage(code, params), e);
        this.code = code;
        this.msg = MessageUtils.getMessage(code, params);
    }
@@ -13,6 +13,7 @@ import org.springframework.web.servlet.resource.NoResourceFoundException;

 import lombok.AllArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
+import xiaozhi.common.utils.MessageUtils;
 import xiaozhi.common.utils.Result;

 /**
@@ -62,7 +63,7 @@ public class RenExceptionHandler {
    @ExceptionHandler(NoResourceFoundException.class)
    public Result<Void> handleNoResourceFoundException(NoResourceFoundException ex) {
        log.warn("Resource not found: {}", ex.getMessage());
-        return new Result<Void>().error(404, "资源不存在");
+        return new Result<Void>().error(404, MessageUtils.getMessage(ErrorCode.RESOURCE_NOT_FOUND));
    }

    @ExceptionHandler(MethodArgumentNotValidException.class)
@@ -76,7 +77,7 @@ public class RenExceptionHandler {
                })
                .filter(Objects::nonNull)
                .findFirst()
-                .orElse("请求参数错误！");
+                .orElse(MessageUtils.getMessage(ErrorCode.PARAM_VALUE_NULL));

        return new Result<Void>().error(ErrorCode.PARAM_VALUE_NULL, errorMsg);
    }
@@ -32,13 +32,23 @@ public class FieldMetaObjectHandler implements MetaObjectHandler {

        // 创建者
        strictInsertFill(metaObject, CREATOR, Long.class, user.getId());
-        // 创建时间
-        strictInsertFill(metaObject, CREATE_DATE, Date.class, date);
+        // 创建时间 - 支持createDate和createdAt两种字段名
+        if (metaObject.hasSetter(CREATE_DATE)) {
+            strictInsertFill(metaObject, CREATE_DATE, Date.class, date);
+        }
+        if (metaObject.hasSetter("createdAt")) {
+            strictInsertFill(metaObject, "createdAt", Date.class, date);
+        }

        // 更新者
        strictInsertFill(metaObject, UPDATER, Long.class, user.getId());
-        // 更新时间
-        strictInsertFill(metaObject, UPDATE_DATE, Date.class, date);
+        // 更新时间 - 支持updateDate和updatedAt两种字段名
+        if (metaObject.hasSetter(UPDATE_DATE)) {
+            strictInsertFill(metaObject, UPDATE_DATE, Date.class, date);
+        }
+        if (metaObject.hasSetter("updatedAt")) {
+            strictInsertFill(metaObject, "updatedAt", Date.class, date);
+        }

        // 数据标识
        strictInsertFill(metaObject, DATA_OPERATION, String.class, Constant.DataOperation.INSERT.getValue());
@@ -46,10 +56,17 @@ public class FieldMetaObjectHandler implements MetaObjectHandler {

    @Override
    public void updateFill(MetaObject metaObject) {
+        Date date = new Date();
+
        // 更新者
        strictUpdateFill(metaObject, UPDATER, Long.class, SecurityUser.getUserId());
-        // 更新时间
-        strictUpdateFill(metaObject, UPDATE_DATE, Date.class, new Date());
+        // 更新时间 - 支持updateDate和updatedAt两种字段名
+        if (metaObject.hasSetter(UPDATE_DATE)) {
+            strictUpdateFill(metaObject, UPDATE_DATE, Date.class, date);
+        }
+        if (metaObject.hasSetter("updatedAt")) {
+            strictUpdateFill(metaObject, "updatedAt", Date.class, date);
+        }

        // 数据标识
        strictInsertFill(metaObject, DATA_OPERATION, String.class, Constant.DataOperation.UPDATE.getValue());
@@ -139,4 +139,53 @@ public class RedisKeys {
        return "sms:Validate:Code:" + phone + ":today_count";
    }

+    /**
+     * 聊天记录UUID映射的Key
+     */
+    public static String getChatHistoryKey(String uuid) {
+        return "agent:chat:history:" + uuid;
+    }
+
+    /**
+     * 获取音色克隆音频ID的缓存key
+     */
+    public static String getVoiceCloneAudioIdKey(String uuid) {
+        return "voiceClone:audio:id:" + uuid;
+    }
+
+    /**
+     * 获取知识库缓存key
+     */
+    public static String getKnowledgeBaseCacheKey(String datasetId) {
+        return "knowledge:base:" + datasetId;
+    }
+
+    /**
+     * 获取临时注册设备标记key
+     */
+    public static String getTmpRegisterMacKey(String deviceId) {
+        return "tmp_register_mac:" + deviceId;
+    }
+
+    /**
+     * OTA绑定设备
+     */
+    public static String getOtaActivationCode(String activationCode) {
+        return "ota:activation:code:" + activationCode;
+    }
+
+    /**
+     * OTA获取设备mac相关信息
+     */
+    public static String getOtaDeviceActivationInfo(String deviceId) {
+        return "ota:activation:data:" + deviceId;
+    }
+
+    /**
+     * OTA上传次数
+     */
+    public static String getOtaUploadCountKey(Long username) {
+        return "ota:upload:count:" + username;
+    }
+
 }
@@ -0,0 +1,21 @@
+package xiaozhi.common.utils;
+
+import lombok.Data;
+/**
+ * JSON-RPC2.0 格式规范对象
+ */
+@Data
+public class JsonRpcTwo {
+    private String jsonrpc = "2.0";
+    private String method;
+    private Object params;
+    private Integer id;
+
+    public JsonRpcTwo(String method, Object params, Integer id) {
+        this.method = method;
+        this.params = params;
+        this.id = id;
+    }
+
+
+}
@@ -11,15 +11,15 @@ import org.springframework.context.i18n.LocaleContextHolder;
 public class MessageUtils {
    private static MessageSource messageSource;

-    static {
-        messageSource = (MessageSource) SpringContextUtils.getBean("messageSource");
-    }
-
    public static String getMessage(int code) {
        return getMessage(code, new String[0]);
    }

    public static String getMessage(int code, String... params) {
+        if (messageSource == null) {
+            // 延迟初始化，确保Spring上下文已完全初始化
+            messageSource = (MessageSource) SpringContextUtils.getBean("messageSource");
+        }
        return messageSource.getMessage(code + "", params, LocaleContextHolder.getLocale());
    }
 }
@@ -6,6 +6,7 @@ import org.springframework.core.io.ResourceLoader;
 import org.springframework.core.io.Resource;
 import org.springframework.stereotype.Component;
 import xiaozhi.common.exception.RenException;
+import xiaozhi.common.exception.ErrorCode;


 import java.io.BufferedReader;
@@ -37,7 +38,7 @@ public class ResourcesUtils {
            }
        }  catch (IOException e){
            log.error("方法：loadString()读取资源失败--{}",e.getMessage());
-            throw new RenException("读取资源失败");
+            throw new RenException(ErrorCode.RESOURCE_READ_ERROR);
        }
        return luaScriptBuilder.toString();
    }
@@ -0,0 +1,130 @@
+package xiaozhi.common.utils;
+
+import org.bouncycastle.asn1.gm.GMNamedCurves;
+import org.bouncycastle.asn1.x9.X9ECParameters;
+import org.bouncycastle.crypto.engines.SM2Engine;
+import org.bouncycastle.crypto.params.ECDomainParameters;
+import org.bouncycastle.crypto.params.ECPrivateKeyParameters;
+import org.bouncycastle.crypto.params.ECPublicKeyParameters;
+import org.bouncycastle.crypto.params.ParametersWithRandom;
+import org.bouncycastle.jcajce.provider.asymmetric.ec.BCECPrivateKey;
+import org.bouncycastle.jcajce.provider.asymmetric.ec.BCECPublicKey;
+import org.bouncycastle.jce.provider.BouncyCastleProvider;
+import org.bouncycastle.math.ec.ECPoint;
+import org.bouncycastle.util.encoders.Hex;
+
+import java.math.BigInteger;
+import java.security.*;
+import java.security.spec.ECGenParameterSpec;
+import java.nio.charset.StandardCharsets;
+import java.util.HashMap;
+import java.util.Map;
+
+/**
+ * SM2加密工具类（采用十六进制格式，与chancheng-archive-service项目保持一致）
+ */
+public class SM2Utils {
+
+    /**
+     * 公钥常量
+     */
+    public static final String KEY_PUBLIC_KEY = "publicKey";
+    /**
+     * 私钥返回值常量
+     */
+    public static final String KEY_PRIVATE_KEY = "privateKey";
+
+    static {
+        Security.addProvider(new BouncyCastleProvider());
+    }
+
+    /**
+     * SM2加密算法
+     *
+     * @param publicKey 十六进制公钥
+     * @param data      明文数据
+     * @return 十六进制密文
+     */
+    public static String encrypt(String publicKey, String data) {
+        try {
+            // 获取一条SM2曲线参数
+            X9ECParameters sm2ECParameters = GMNamedCurves.getByName("sm2p256v1");
+            // 构造ECC算法参数，曲线方程、椭圆曲线G点、大整数N
+            ECDomainParameters domainParameters = new ECDomainParameters(sm2ECParameters.getCurve(), sm2ECParameters.getG(), sm2ECParameters.getN());
+            //提取公钥点
+            ECPoint pukPoint = sm2ECParameters.getCurve().decodePoint(Hex.decode(publicKey));
+            // 公钥前面的02或者03表示是压缩公钥，04表示未压缩公钥, 04的时候，可以去掉前面的04
+            ECPublicKeyParameters publicKeyParameters = new ECPublicKeyParameters(pukPoint, domainParameters);
+
+            SM2Engine sm2Engine = new SM2Engine(SM2Engine.Mode.C1C3C2);
+            // 设置sm2为加密模式
+            sm2Engine.init(true, new ParametersWithRandom(publicKeyParameters, new SecureRandom()));
+
+            byte[] in = data.getBytes(StandardCharsets.UTF_8);
+            byte[] arrayOfBytes = sm2Engine.processBlock(in, 0, in.length);
+            return Hex.toHexString(arrayOfBytes);
+        } catch (Exception e) {
+            throw new RuntimeException("SM2加密失败", e);
+        }
+    }
+
+    /**
+     * SM2解密算法
+     *
+     * @param privateKey 十六进制私钥
+     * @param cipherData 十六进制密文数据
+     * @return 明文
+     */
+    public static String decrypt(String privateKey, String cipherData) {
+        try {
+            // 使用BC库加解密时密文以04开头，传入的密文前面没有04则补上
+            if (!cipherData.startsWith("04")) {
+                cipherData = "04" + cipherData;
+            }
+            byte[] cipherDataByte = Hex.decode(cipherData);
+            BigInteger privateKeyD = new BigInteger(privateKey, 16);
+            //获取一条SM2曲线参数
+            X9ECParameters sm2ECParameters = GMNamedCurves.getByName("sm2p256v1");
+            //构造domain参数
+            ECDomainParameters domainParameters = new ECDomainParameters(sm2ECParameters.getCurve(), sm2ECParameters.getG(), sm2ECParameters.getN());
+            ECPrivateKeyParameters privateKeyParameters = new ECPrivateKeyParameters(privateKeyD, domainParameters);
+
+            SM2Engine sm2Engine = new SM2Engine(SM2Engine.Mode.C1C3C2);
+            // 设置sm2为解密模式
+            sm2Engine.init(false, privateKeyParameters);
+
+            byte[] arrayOfBytes = sm2Engine.processBlock(cipherDataByte, 0, cipherDataByte.length);
+            return new String(arrayOfBytes, StandardCharsets.UTF_8);
+        } catch (Exception e) {
+            throw new RuntimeException("SM2解密失败", e);
+        }
+    }
+
+    /**
+     * 生成密钥对
+     */
+    public static Map<String, String> createKey() {
+        try {
+            ECGenParameterSpec sm2Spec = new ECGenParameterSpec("sm2p256v1");
+            // 获取一个椭圆曲线类型的密钥对生成器
+            KeyPairGenerator kpg = KeyPairGenerator.getInstance("EC", new BouncyCastleProvider());
+            // 使用SM2参数初始化生成器
+            kpg.initialize(sm2Spec);
+            // 获取密钥对
+            KeyPair keyPair = kpg.generateKeyPair();
+            PublicKey publicKey = keyPair.getPublic();
+            BCECPublicKey p = (BCECPublicKey) publicKey;
+            PrivateKey privateKey = keyPair.getPrivate();
+            BCECPrivateKey s = (BCECPrivateKey) privateKey;
+            
+            Map<String, String> result = new HashMap<>();
+            result.put(KEY_PUBLIC_KEY, Hex.toHexString(p.getQ().getEncoded(false)));
+            result.put(KEY_PRIVATE_KEY, Hex.toHexString(s.getD().toByteArray()));
+            return result;
+        } catch (Exception e) {
+            throw new RuntimeException("生成SM2密钥对失败", e);
+        }
+    }
+
+
+}
@@ -0,0 +1,165 @@
+package xiaozhi.common.utils;
+
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+
+import org.apache.commons.lang3.StringUtils;
+
+import cn.hutool.json.JSONObject;
+
+/**
+ * 敏感数据处理工具类
+ */
+public class SensitiveDataUtils {
+
+    // 敏感字段列表
+    private static final Set<String> SENSITIVE_FIELDS = new HashSet<>(Arrays.asList(
+            "api_key", "personal_access_token", "access_token", "token",
+            "secret", "access_key_secret", "secret_key"));
+
+    /**
+     * 检查字段是否为敏感字段
+     */
+    public static boolean isSensitiveField(String fieldName) {
+        return StringUtils.isNotBlank(fieldName) && SENSITIVE_FIELDS.contains(fieldName.toLowerCase());
+    }
+
+    /**
+     * 隐藏字符串中间部分
+     */
+    public static String maskMiddle(String value) {
+        if (StringUtils.isBlank(value) || value.length() == 1) {
+            return value;
+        }
+
+        int length = value.length();
+        if (length <= 8) {
+            // 短字符串保留前2后2
+            return value.substring(0, 2) + "****" + value.substring(length - 2);
+        } else {
+            // 长字符串保留前4后4
+            int maskLength = length - 8;
+            StringBuilder maskBuilder = new StringBuilder();
+            for (int i = 0; i < maskLength; i++) {
+                maskBuilder.append('*');
+            }
+            return value.substring(0, 4) + maskBuilder.toString() + value.substring(length - 4);
+        }
+    }
+
+    /**
+     * 判断字符串是否是被掩码处理过的值
+     */
+    public static boolean isMaskedValue(String value) {
+        if (StringUtils.isBlank(value)) {
+            return false;
+        }
+        // 掩码值至少包含4个连续的*
+        return value.contains("****");
+    }
+
+    /**
+     * 处理JSONObject中的敏感字段
+     */
+    public static JSONObject maskSensitiveFields(JSONObject jsonObject) {
+        if (jsonObject == null) {
+            return null;
+        }
+
+        JSONObject result = new JSONObject();
+
+        for (String key : jsonObject.keySet()) {
+            Object value = jsonObject.get(key);
+
+            if (SENSITIVE_FIELDS.contains(key.toLowerCase()) && value instanceof String) {
+                result.put(key, maskMiddle((String) value));
+            } else if (value instanceof JSONObject) {
+                result.put(key, maskSensitiveFields((JSONObject) value));
+            } else {
+                result.put(key, value);
+            }
+        }
+
+        return result;
+    }
+
+    /**
+     * 比较两个JSONObject的敏感字段是否相同
+     * 特别针对api_key等敏感字段进行单独比较
+     */
+    public static boolean isSensitiveDataEqual(JSONObject original, JSONObject updated) {
+        if (original == null && updated == null) {
+            return true;
+        }
+        if (original == null || updated == null) {
+            return false;
+        }
+
+        // 提取并比较特定敏感字段
+        return compareSpecificSensitiveFields(original, updated, "api_key") &&
+                compareSpecificSensitiveFields(original, updated, "personal_access_token") &&
+                compareSpecificSensitiveFields(original, updated, "access_token") &&
+                compareSpecificSensitiveFields(original, updated, "token") &&
+                compareSpecificSensitiveFields(original, updated, "secret") &&
+                compareSpecificSensitiveFields(original, updated, "access_key_secret") &&
+                compareSpecificSensitiveFields(original, updated, "secret_key");
+    }
+
+    /**
+     * 比较两个JSON对象中特定敏感字段是否相同
+     * 遍历整个JSON对象树，查找并比较指定敏感字段
+     */
+    private static boolean compareSpecificSensitiveFields(JSONObject original, JSONObject updated, String fieldName) {
+        // 提取原始对象中的指定敏感字段
+        Map<String, String> originalFields = new HashMap<>();
+        extractSpecificSensitiveField(original, originalFields, fieldName, "");
+
+        // 提取更新对象中的指定敏感字段
+        Map<String, String> updatedFields = new HashMap<>();
+        extractSpecificSensitiveField(updated, updatedFields, fieldName, "");
+
+        // 如果字段数量不同，说明有增删
+        if (originalFields.size() != updatedFields.size()) {
+            return false;
+        }
+
+        // 比较每个字段的值
+        for (Map.Entry<String, String> entry : originalFields.entrySet()) {
+            String key = entry.getKey();
+            String originalValue = entry.getValue();
+            String updatedValue = updatedFields.get(key);
+
+            if (updatedValue == null || !updatedValue.equals(originalValue)) {
+                return false;
+            }
+        }
+
+        return true;
+    }
+
+    /**
+     * 递归提取JSON对象中指定名称的敏感字段
+     */
+    private static void extractSpecificSensitiveField(JSONObject jsonObject, Map<String, String> fieldsMap,
+            String targetFieldName, String parentPath) {
+        if (jsonObject == null) {
+            return;
+        }
+
+        for (String key : jsonObject.keySet()) {
+            String fullPath = parentPath.isEmpty() ? key : parentPath + "." + key;
+            Object value = jsonObject.get(key);
+
+            if (value instanceof JSONObject) {
+                // 递归处理嵌套JSON对象
+                extractSpecificSensitiveField((JSONObject) value, fieldsMap, targetFieldName, fullPath);
+            } else if (value instanceof String && key.equalsIgnoreCase(targetFieldName)) {
+                // 找到目标敏感字段，保存其路径和值
+                fieldsMap.put(fullPath, (String) value);
+            }
+        }
+    }
+}
@@ -0,0 +1,63 @@
+package xiaozhi.common.utils;
+
+import org.apache.commons.lang3.StringUtils;
+import xiaozhi.common.constant.Constant;
+import xiaozhi.common.exception.ErrorCode;
+import xiaozhi.common.exception.RenException;
+import xiaozhi.modules.security.service.CaptchaService;
+import xiaozhi.modules.sys.service.SysParamsService;
+
+/**
+ * SM2解密和验证码验证工具类
+ * 封装了重复的SM2解密、验证码提取和验证逻辑
+ */
+public class Sm2DecryptUtil {
+
+    /**
+     * 验证码长度
+     */
+    private static final int CAPTCHA_LENGTH = 5;
+
+    /**
+     * 解密SM2加密内容，提取验证码并验证
+     * 
+     * @param encryptedPassword SM2加密的密码字符串
+     * @param captchaId         验证码ID
+     * @param captchaService    验证码服务
+     * @param sysParamsService  系统参数服务
+     * @return 解密后的实际密码
+     */
+    public static String decryptAndValidateCaptcha(String encryptedPassword, String captchaId,
+            CaptchaService captchaService, SysParamsService sysParamsService) {
+        // 获取SM2私钥
+        String privateKeyStr = sysParamsService.getValue(Constant.SM2_PRIVATE_KEY, true);
+        if (StringUtils.isBlank(privateKeyStr)) {
+            throw new RenException(ErrorCode.SM2_KEY_NOT_CONFIGURED);
+        }
+
+        // 使用SM2私钥解密密码
+        String decryptedContent;
+        try {
+            decryptedContent = SM2Utils.decrypt(privateKeyStr, encryptedPassword);
+        } catch (Exception e) {
+            throw new RenException(ErrorCode.SM2_DECRYPT_ERROR);
+        }
+
+        // 分离验证码和密码：前5位是验证码，后面是密码
+        if (decryptedContent.length() > CAPTCHA_LENGTH) {
+            String embeddedCaptcha = decryptedContent.substring(0, CAPTCHA_LENGTH);
+            String actualPassword = decryptedContent.substring(CAPTCHA_LENGTH);
+
+            boolean embeddedCaptchaValid = captchaService.validate(captchaId, embeddedCaptcha, true);
+            if (!embeddedCaptchaValid) {
+                throw new RenException(ErrorCode.SMS_CAPTCHA_ERROR);
+            }
+
+            return actualPassword;
+        } else if (decryptedContent.length() > 0) {
+            throw new RenException(ErrorCode.SMS_CAPTCHA_ERROR);
+        } else {
+            throw new RenException(ErrorCode.SM2_DECRYPT_ERROR);
+        }
+    }
+}
@@ -0,0 +1,89 @@
+package xiaozhi.common.utils;
+
+import cn.hutool.core.util.ReUtil;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.time.LocalDateTime;
+import java.time.ZoneId;
+import java.util.Date;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+/**
+ * 通用工具类
+ */
+public class ToolUtil {
+    private static final Logger logger = LoggerFactory.getLogger(ToolUtil.class);
+
+    /**
+     * 对象是否不为空(新增)
+     */
+    public static boolean isNotEmpty(Object o) {
+        return !isEmpty(o);
+    }
+
+    /**
+     * 对象是否为空
+     */
+    public static boolean isEmpty(Object o) {
+        if (o == null) {
+            return true;
+        }
+        if (o instanceof String) {
+            if (o.toString().trim().equals("")) {
+                return true;
+            }
+        } else if (o instanceof List) {
+            if (((List) o).size() == 0) {
+                return true;
+            }
+        } else if (o instanceof Map) {
+            if (((Map) o).size() == 0) {
+                return true;
+            }
+        } else if (o instanceof Set) {
+            if (((Set) o).size() == 0) {
+                return true;
+            }
+        } else if (o instanceof Object[]) {
+            if (((Object[]) o).length == 0) {
+                return true;
+            }
+        } else if (o instanceof int[]) {
+            if (((int[]) o).length == 0) {
+                return true;
+            }
+        } else if (o instanceof long[]) {
+            if (((long[]) o).length == 0) {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    /**
+     * 对象组中是否存在空对象
+     */
+    public static boolean isOneEmpty(Object... os) {
+        for (Object o : os) {
+            if (isEmpty(o)) {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    /**
+     * 对象组中是否全是空对象
+     */
+    public static boolean isAllEmpty(Object... os) {
+        for (Object o : os) {
+            if (!isEmpty(o)) {
+                return false;
+            }
+        }
+        return true;
+    }
+}
@@ -0,0 +1,44 @@
+package xiaozhi.modules.agent.Enums;
+
+import xiaozhi.common.utils.JsonUtils;
+import xiaozhi.common.utils.JsonRpcTwo;
+
+import java.util.Map;
+
+
+/**
+ * 小智MCP JSON-RPC 请求json
+ */
+public class XiaoZhiMcpJsonRpcJson {
+    //小智初始化mcp请求json
+    private static final String INITIALIZE_JSON;
+    //小智mcp初始化成功，返回通知请求json
+    private static final String NOTIFICATIONS_INITIALIZED_JSON;
+    //小智mcp获取mcp工具集合请求json
+    private static final String TOOLS_LIST_REQUEST;
+    // 延迟加载
+    static {
+        INITIALIZE_JSON = JsonUtils.toJsonString(new JsonRpcTwo("initialize",
+                Map.of(
+                        "protocolVersion", "2024-11-05",
+                        "capabilities", Map.of(
+                                "roots", Map.of("listChanged", false),
+                                "sampling", Map.of()),
+                        "clientInfo", Map.of(
+                                "name", "xz-mcp-broker",
+                                "version", "0.0.1")),
+                1));
+        NOTIFICATIONS_INITIALIZED_JSON = "{\"jsonrpc\":\"2.0\",\"method\":\"notifications/initialized\"}";
+        TOOLS_LIST_REQUEST = JsonUtils.toJsonString(new JsonRpcTwo("tools/list", null, 2));
+    }
+    public static String getInitializeJson(){
+        return INITIALIZE_JSON;
+    }
+    public static String getNotificationsInitializedJson(){
+        return NOTIFICATIONS_INITIALIZED_JSON;
+    }
+    public static String getToolsListJson(){
+        return TOOLS_LIST_REQUEST;
+    }
+
+}
@@ -1,5 +1,19 @@
 package xiaozhi.modules.agent.controller;

+import java.io.IOException;
+import java.io.OutputStream;
+import java.net.URLEncoder;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.Date;
+import java.util.List;
+import java.util.Map;
+import java.util.UUID;
+
+import org.apache.commons.lang3.StringUtils;
+import org.apache.shiro.authz.annotation.RequiresPermissions;
+import org.springframework.web.bind.annotation.GetMapping;
+import org.springframework.web.bind.annotation.PathVariable;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
 import org.springframework.web.bind.annotation.RequestMapping;
@@ -7,11 +21,26 @@ import org.springframework.web.bind.annotation.RestController;

 import io.swagger.v3.oas.annotations.Operation;
 import io.swagger.v3.oas.annotations.tags.Tag;
+import jakarta.servlet.http.HttpServletResponse;
 import jakarta.validation.Valid;
 import lombok.RequiredArgsConstructor;
+import xiaozhi.common.constant.Constant;
+import xiaozhi.common.exception.ErrorCode;
+import xiaozhi.common.exception.RenException;
+import xiaozhi.common.page.PageData;
+import xiaozhi.common.redis.RedisKeys;
+import xiaozhi.common.redis.RedisUtils;
+import xiaozhi.common.user.UserDetail;
+import xiaozhi.common.utils.DateUtils;
+import xiaozhi.common.utils.MessageUtils;
 import xiaozhi.common.utils.Result;
+import xiaozhi.modules.agent.dto.AgentChatHistoryDTO;
 import xiaozhi.modules.agent.dto.AgentChatHistoryReportDTO;
+import xiaozhi.modules.agent.dto.AgentChatSessionDTO;
+import xiaozhi.modules.agent.service.AgentChatHistoryService;
+import xiaozhi.modules.agent.service.AgentService;
 import xiaozhi.modules.agent.service.biz.AgentChatHistoryBizService;
+import xiaozhi.modules.security.user.SecurityUser;

@Tag(name = "智能体聊天历史管理")
@RequiredArgsConstructor
@@ -19,6 +48,9 @@ import xiaozhi.modules.agent.service.biz.AgentChatHistoryBizService;
@RequestMapping("/agent/chat-history")
 public class AgentChatHistoryController {
    private final AgentChatHistoryBizService agentChatHistoryBizService;
+    private final AgentChatHistoryService agentChatHistoryService;
+    private final AgentService agentService;
+    private final RedisUtils redisUtils;

    /**
     * 小智服务聊天上报请求
@@ -33,4 +65,182 @@ public class AgentChatHistoryController {
        Boolean result = agentChatHistoryBizService.report(request);
        return new Result<Boolean>().ok(result);
    }
+
+    /**
+     * 获取聊天记录下载链接
+     * 
+     * @param agentId   智能体ID
+     * @param sessionId 会话ID
+     * @return UUID作为下载标识
+     */
+    @Operation(summary = "获取聊天记录下载链接")
+    @RequiresPermissions("sys:role:normal")
+    @PostMapping("/getDownloadUrl/{agentId}/{sessionId}")
+    public Result<String> getDownloadUrl(@PathVariable("agentId") String agentId,
+            @PathVariable("sessionId") String sessionId) {
+        // 获取当前用户
+        UserDetail user = SecurityUser.getUser();
+        // 检查权限
+        if (!agentService.checkAgentPermission(agentId, user.getId())) {
+            throw new RenException(ErrorCode.CHAT_HISTORY_NO_PERMISSION);
+        }
+
+        // 生成UUID
+        String uuid = UUID.randomUUID().toString();
+        // 存储agentId和sessionId到Redis，格式为agentId:sessionId
+        redisUtils.set(RedisKeys.getChatHistoryKey(uuid), agentId + ":" + sessionId);
+
+        return new Result<String>().ok(uuid);
+    }
+
+    /**
+     * 下载本会话聊天记录
+     * 
+     * @param uuid     下载标识
+     * @param response HTTP响应
+     */
+    @Operation(summary = "下载本会话聊天记录")
+    @GetMapping("/download/{uuid}/current")
+    public void downloadCurrentSession(@PathVariable("uuid") String uuid,
+            HttpServletResponse response) {
+        // 从Redis获取agentId和sessionId
+        String agentSessionInfo = (String) redisUtils.get(RedisKeys.getChatHistoryKey(uuid));
+        if (StringUtils.isBlank(agentSessionInfo)) {
+            throw new RenException(ErrorCode.DOWNLOAD_LINK_EXPIRED);
+        }
+
+        try {
+            // 解析agentId和sessionId
+            String[] parts = agentSessionInfo.split(":");
+            if (parts.length != 2) {
+                throw new RenException(ErrorCode.DOWNLOAD_LINK_INVALID);
+            }
+            String agentId = parts[0];
+            String sessionId = parts[1];
+
+            // 执行下载
+            downloadChatHistory(agentId, List.of(sessionId), response);
+        } finally {
+            // 下载完成后删除UUID，防止盗刷
+            redisUtils.delete(RedisKeys.getChatHistoryKey(uuid));
+        }
+    }
+
+    /**
+     * 下载本会话及前20条会话聊天记录
+     * 
+     * @param uuid     下载标识
+     * @param response HTTP响应
+     */
+    @Operation(summary = "下载本会话及前20条会话聊天记录")
+    @GetMapping("/download/{uuid}/previous")
+    public void downloadCurrentSessionWithPrevious(@PathVariable("uuid") String uuid,
+            HttpServletResponse response) {
+        // 从Redis获取agentId和sessionId
+        String agentSessionInfo = (String) redisUtils.get(RedisKeys.getChatHistoryKey(uuid));
+        if (StringUtils.isBlank(agentSessionInfo)) {
+            throw new RenException(ErrorCode.DOWNLOAD_LINK_EXPIRED);
+        }
+
+        try {
+            // 解析agentId和sessionId
+            String[] parts = agentSessionInfo.split(":");
+            if (parts.length != 2) {
+                throw new RenException(ErrorCode.DOWNLOAD_LINK_INVALID);
+            }
+            String agentId = parts[0];
+            String sessionId = parts[1];
+
+            // 获取所有会话列表
+            Map<String, Object> params = Map.of(
+                    "agentId", agentId,
+                    Constant.PAGE, 1,
+                    Constant.LIMIT, 1000 // 获取足够多的会话
+            );
+            PageData<AgentChatSessionDTO> sessionPage = agentChatHistoryService.getSessionListByAgentId(params);
+            List<AgentChatSessionDTO> allSessions = sessionPage.getList();
+
+            // 查找当前会话在列表中的位置
+            int currentIndex = -1;
+            for (int i = 0; i < allSessions.size(); i++) {
+                if (allSessions.get(i).getSessionId().equals(sessionId)) {
+                    currentIndex = i;
+                    break;
+                }
+            }
+
+            // 如果找到了当前会话，收集当前会话及前20条会话ID
+            List<String> sessionIdsToDownload = new ArrayList<>();
+            if (currentIndex != -1) {
+                // 从当前会话开始，向后（数组后面）取最多20条会话（包括当前会话）
+                int endIndex = Math.min(allSessions.size() - 1, currentIndex + 20); // 确保不越界
+                for (int i = currentIndex; i <= endIndex; i++) {
+                    sessionIdsToDownload.add(allSessions.get(i).getSessionId());
+                }
+            }
+
+            // 如果没有找到当前会话，至少下载当前会话
+            if (sessionIdsToDownload.isEmpty()) {
+                sessionIdsToDownload.add(sessionId);
+            }
+            downloadChatHistory(agentId, sessionIdsToDownload, response);
+        } finally {
+            // 下载完成后删除UUID，防止盗刷
+            redisUtils.delete(RedisKeys.getChatHistoryKey(uuid));
+        }
+    }
+
+    /**
+     * 下载指定会话的聊天记录
+     * 
+     * @param agentId    智能体ID
+     * @param sessionIds 会话ID列表
+     * @param response   HTTP响应
+     */
+    private void downloadChatHistory(String agentId, List<String> sessionIds, HttpServletResponse response) {
+        try {
+            // 设置响应头
+            response.setContentType("text/plain;charset=UTF-8");
+            String fileName = URLEncoder.encode("history.txt", StandardCharsets.UTF_8.toString());
+            response.setHeader("Content-Disposition", "attachment;filename=" + fileName);
+
+            // 获取聊天记录并写入响应流
+            try (OutputStream out = response.getOutputStream()) {
+                // 为每个会话生成聊天记录
+                for (String sessionId : sessionIds) {
+                    // 获取该会话的所有聊天记录
+                    List<AgentChatHistoryDTO> chatHistoryList = agentChatHistoryService
+                            .getChatHistoryBySessionId(agentId, sessionId);
+
+                    // 从聊天记录中获取第一条消息的创建时间作为会话时间
+                    if (!chatHistoryList.isEmpty()) {
+                        Date firstMessageTime = chatHistoryList.get(0).getCreatedAt();
+                        String sessionTimeStr = DateUtils.format(firstMessageTime, DateUtils.DATE_TIME_PATTERN);
+                        out.write((sessionTimeStr + "\n").getBytes(StandardCharsets.UTF_8));
+                    }
+
+                    for (AgentChatHistoryDTO message : chatHistoryList) {
+                        String role = message.getChatType() == 1 ? MessageUtils.getMessage(ErrorCode.CHAT_ROLE_USER)
+                                : MessageUtils.getMessage(ErrorCode.CHAT_ROLE_AGENT);
+                        String direction = message.getChatType() == 1 ? ">>" : "<<";
+                        Date messageTime = message.getCreatedAt();
+                        String messageTimeStr = DateUtils.format(messageTime, DateUtils.DATE_TIME_PATTERN);
+                        String content = message.getContent();
+
+                        String line = "[" + role + "]-[" + messageTimeStr + "]" + direction + ":" + content + "\n";
+                        out.write(line.getBytes(StandardCharsets.UTF_8));
+                    }
+
+                    // 会话之间添加空行分隔
+                    if (sessionIds.indexOf(sessionId) < sessionIds.size() - 1) {
+                        out.write("\n".getBytes(StandardCharsets.UTF_8));
+                    }
+                }
+
+                out.flush();
+            }
+        } catch (IOException e) {
+            e.printStackTrace();
+        }
+    }
 }
@@ -42,8 +42,13 @@ import xiaozhi.modules.agent.dto.AgentMemoryDTO;
 import xiaozhi.modules.agent.dto.AgentUpdateDTO;
 import xiaozhi.modules.agent.entity.AgentEntity;
 import xiaozhi.modules.agent.entity.AgentTemplateEntity;
+import xiaozhi.modules.agent.dto.AgentTagDTO;
+import xiaozhi.modules.agent.entity.AgentTagEntity;
+import xiaozhi.modules.agent.service.AgentTagService;
 import xiaozhi.modules.agent.service.AgentChatAudioService;
 import xiaozhi.modules.agent.service.AgentChatHistoryService;
+import xiaozhi.modules.agent.service.AgentChatSummaryService;
+import xiaozhi.modules.agent.service.AgentContextProviderService;
 import xiaozhi.modules.agent.service.AgentPluginMappingService;
 import xiaozhi.modules.agent.service.AgentService;
 import xiaozhi.modules.agent.service.AgentTemplateService;
@@ -64,14 +69,21 @@ public class AgentController {
    private final AgentChatHistoryService agentChatHistoryService;
    private final AgentChatAudioService agentChatAudioService;
    private final AgentPluginMappingService agentPluginMappingService;
+    private final AgentContextProviderService agentContextProviderService;
+    private final AgentChatSummaryService agentChatSummaryService;
    private final RedisUtils redisUtils;
+    private final AgentTagService agentTagService;

    @GetMapping("/list")
    @Operation(summary = "获取用户智能体列表")
    @RequiresPermissions("sys:role:normal")
-    public Result<List<AgentDTO>> getUserAgents() {
+    public Result<List<AgentDTO>> getUserAgents(
+            @RequestParam(value = "keyword", required = false) String keyword,
+            @RequestParam(value = "searchType", defaultValue = "name") String searchType) {
        UserDetail user = SecurityUser.getUser();
-        List<AgentDTO> agents = agentService.getUserAgents(user.getId());
+
+        // 直接调用整合后的getUserAgents方法，无需再区分搜索和普通查询
+        List<AgentDTO> agents = agentService.getUserAgents(user.getId(), keyword, searchType);
        return new Result<List<AgentDTO>>().ok(agents);
    }

@@ -117,6 +129,34 @@ public class AgentController {
        return new Result<>();
    }

+    @PostMapping("/chat-summary/{sessionId}/save")
+    @Operation(summary = "根据会话ID生成聊天记录总结并保存（异步执行）")
+    public Result<Void> generateAndSaveChatSummary(@PathVariable String sessionId) {
+        try {
+            // 异步执行总结生成任务，立即返回成功响应
+            new Thread(() -> {
+                try {
+                    agentChatSummaryService.generateAndSaveChatSummary(sessionId);
+                    System.out.println("异步执行会话 " + sessionId + " 的聊天记录总结完成");
+                } catch (Exception e) {
+                    System.err.println("异步执行会话 " + sessionId + " 的聊天记录总结失败: " + e.getMessage());
+                }
+            }).start();
+
+            // 立即返回成功响应，不等待总结生成完成
+            return new Result<Void>().ok(null);
+        } catch (Exception e) {
+            return new Result<Void>().error("启动异步总结生成任务失败: " + e.getMessage());
+        }
+    }
+
+    @PostMapping("/chat-title/{sessionId}/generate")
+    @Operation(summary = "根据会话ID生成聊天标题")
+    public Result<Void> generateAndSaveChatTitle(@PathVariable String sessionId) {
+        agentChatSummaryService.generateAndSaveChatTitle(sessionId);
+        return new Result<Void>().ok(null);
+    }
+
    @PutMapping("/{id}")
    @Operation(summary = "更新智能体")
    @RequiresPermissions("sys:role:normal")
@@ -135,6 +175,8 @@ public class AgentController {
        agentChatHistoryService.deleteByAgentId(id, true, true);
        // 删除关联的插件
        agentPluginMappingService.deleteByAgentId(id);
+        // 删除关联的上下文源配置
+        agentContextProviderService.deleteByAgentId(id);
        // 再删除智能体
        agentService.deleteById(id);
        return new Result<>();
@@ -182,6 +224,7 @@ public class AgentController {
        List<AgentChatHistoryDTO> result = agentChatHistoryService.getChatHistoryBySessionId(id, sessionId);
        return new Result<List<AgentChatHistoryDTO>>().ok(result);
    }
+
    @GetMapping("/{id}/chat-history/user")
    @Operation(summary = "获取智能体聊天记录（用户）")
    @RequiresPermissions("sys:role:normal")
@@ -243,4 +286,50 @@ public class AgentController {
                .body(audioData);
    }

+    @PostMapping("/tag")
+    @Operation(summary = "创建标签")
+    @RequiresPermissions("sys:role:normal")
+    public Result<AgentTagEntity> createTag(@RequestBody Map<String, String> params) {
+        String tagName = params.get("tagName");
+        if (StringUtils.isBlank(tagName)) {
+            return new Result<AgentTagEntity>().error("标签名称不能为空");
+        }
+        AgentTagEntity tag = agentTagService.saveTag(tagName);
+        return new Result<AgentTagEntity>().ok(tag);
+    }
+
+    @GetMapping("/tag/list")
+    @Operation(summary = "获取所有标签列表")
+    @RequiresPermissions("sys:role:normal")
+    public Result<List<AgentTagDTO>> getAllTags() {
+        List<AgentTagDTO> tags = agentTagService.getAllTags();
+        return new Result<List<AgentTagDTO>>().ok(tags);
+    }
+
+    @DeleteMapping("/tag/{id}")
+    @Operation(summary = "删除标签")
+    @RequiresPermissions("sys:role:normal")
+    public Result<Void> deleteTag(@PathVariable String id) {
+        agentTagService.deleteTag(id);
+        return new Result<Void>().ok(null);
+    }
+
+    @GetMapping("/{id}/tags")
+    @Operation(summary = "获取智能体的标签")
+    @RequiresPermissions("sys:role:normal")
+    public Result<List<AgentTagDTO>> getAgentTags(@PathVariable String id) {
+        List<AgentTagDTO> tags = agentTagService.getTagsByAgentId(id);
+        return new Result<List<AgentTagDTO>>().ok(tags);
+    }
+
+    @PutMapping("/{id}/tags")
+    @Operation(summary = "保存智能体的标签")
+    @RequiresPermissions("sys:role:normal")
+    public Result<Void> saveAgentTags(@PathVariable String id, @RequestBody Map<String, Object> params) {
+        List<String> tagIds = (List<String>) params.get("tagIds");
+        List<String> tagNames = (List<String>) params.get("tagNames");
+        agentTagService.saveAgentTags(id, tagIds, tagNames);
+        return new Result<Void>().ok(null);
+    }
+
 }
@@ -11,6 +11,7 @@ import org.springframework.web.bind.annotation.RestController;
 import io.swagger.v3.oas.annotations.Operation;
 import io.swagger.v3.oas.annotations.tags.Tag;
 import lombok.RequiredArgsConstructor;
+import xiaozhi.common.exception.ErrorCode;
 import xiaozhi.common.user.UserDetail;
 import xiaozhi.common.utils.Result;
 import xiaozhi.modules.agent.service.AgentMcpAccessPointService;
@@ -28,7 +29,7 @@ public class AgentMcpAccessPointController {
    /**
     * 获取智能体的Mcp接入点地址
     * 
-     * @param audioId 智能体id
+     * @param agentId 智能体id
     * @return 返回错误提醒或者Mcp接入点地址
     */
    @Operation(summary = "获取智能体的Mcp接入点地址")
@@ -40,11 +41,11 @@ public class AgentMcpAccessPointController {

        // 检查权限
        if (!agentService.checkAgentPermission(agentId, user.getId())) {
-            return new Result<String>().error("没有权限查看该智能体的MCP接入点地址");
+            return new Result<String>().error(ErrorCode.MCP_ACCESS_POINT_ADDRESS_NO_PERMISSION);
        }
        String agentMcpAccessAddress = agentMcpAccessPointService.getAgentMcpAccessAddress(agentId);
        if (agentMcpAccessAddress == null) {
-            return new Result<String>().ok("请联系管理员进入参数管理配置mcp接入点地址");
+            return new Result<String>().error(ErrorCode.MCP_ACCESS_POINT_ADDRESS_NOT_CONFIGURED);
        }
        return new Result<String>().ok(agentMcpAccessAddress);
    }
@@ -58,7 +59,7 @@ public class AgentMcpAccessPointController {

        // 检查权限
        if (!agentService.checkAgentPermission(agentId, user.getId())) {
-            return new Result<List<String>>().error("没有权限查看该智能体的MCP工具列表");
+            return new Result<List<String>>().error(ErrorCode.MCP_ACCESS_POINT_TOOLS_LIST_NO_PERMISSION);
        }
        List<String> agentMcpToolsList = agentMcpAccessPointService.getAgentMcpToolsList(agentId);
        return new Result<List<String>>().ok(agentMcpToolsList);
@@ -0,0 +1,158 @@
+package xiaozhi.modules.agent.controller;
+
+import java.util.List;
+import java.util.Map;
+
+import org.apache.shiro.authz.annotation.RequiresPermissions;
+import org.springframework.web.bind.annotation.DeleteMapping;
+import org.springframework.web.bind.annotation.GetMapping;
+import org.springframework.web.bind.annotation.PathVariable;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.PutMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RequestParam;
+import org.springframework.web.bind.annotation.RestController;
+
+import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
+import com.baomidou.mybatisplus.core.metadata.IPage;
+import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
+
+import io.swagger.v3.oas.annotations.Operation;
+import io.swagger.v3.oas.annotations.Parameter;
+import io.swagger.v3.oas.annotations.Parameters;
+import io.swagger.v3.oas.annotations.tags.Tag;
+import jakarta.validation.Valid;
+import lombok.AllArgsConstructor;
+import xiaozhi.common.constant.Constant;
+import xiaozhi.common.page.PageData;
+import xiaozhi.common.utils.ConvertUtils;
+import xiaozhi.common.utils.Result;
+import xiaozhi.common.utils.ResultUtils;
+import xiaozhi.modules.agent.entity.AgentTemplateEntity;
+import xiaozhi.modules.agent.service.AgentTemplateService;
+import xiaozhi.modules.agent.vo.AgentTemplateVO;
+
+@Tag(name = "智能体模板管理")
+@AllArgsConstructor
+@RestController
+@RequestMapping("/agent/template")
+public class AgentTemplateController {
+    
+    private final AgentTemplateService agentTemplateService;
+    
+    @GetMapping("/page")
+    @Operation(summary = "获取模板分页列表")
+    @RequiresPermissions("sys:role:superAdmin")
+    @Parameters({
+            @Parameter(name = Constant.PAGE, description = "当前页码，从1开始", required = true),
+            @Parameter(name = Constant.LIMIT, description = "每页显示记录数", required = true),
+            @Parameter(name = "agentName", description = "模板名称，模糊查询")
+    })
+    public Result<PageData<AgentTemplateVO>> getAgentTemplatesPage(
+            @Parameter(hidden = true) @RequestParam Map<String, Object> params) {
+        
+        // 创建分页对象
+        int page = Integer.parseInt(params.getOrDefault(Constant.PAGE, "1").toString());
+        int limit = Integer.parseInt(params.getOrDefault(Constant.LIMIT, "10").toString());
+        Page<AgentTemplateEntity> pageInfo = new Page<>(page, limit);
+        
+        // 创建查询条件
+        QueryWrapper<AgentTemplateEntity> wrapper = new QueryWrapper<>();
+        String agentName = (String) params.get("agentName");
+        if (agentName != null && !agentName.isEmpty()) {
+            wrapper.like("agent_name", agentName);
+        }
+        wrapper.orderByAsc("sort");
+        
+        // 执行分页查询
+        IPage<AgentTemplateEntity> pageResult = agentTemplateService.page(pageInfo, wrapper);
+        
+        // 使用ConvertUtils转换为VO列表
+        List<AgentTemplateVO> voList = ConvertUtils.sourceToTarget(pageResult.getRecords(), AgentTemplateVO.class);
+
+        // 修复：使用构造函数创建PageData对象，而不是无参构造+setter
+        PageData<AgentTemplateVO> pageData = new PageData<>(voList, pageResult.getTotal());
+
+        return new Result<PageData<AgentTemplateVO>>().ok(pageData);
+    }
+    
+    @GetMapping("/{id}")
+    @Operation(summary = "获取模板详情")
+    @RequiresPermissions("sys:role:superAdmin")
+    public Result<AgentTemplateVO> getAgentTemplateById(@PathVariable("id") String id) {
+        AgentTemplateEntity template = agentTemplateService.getById(id);
+        if (template == null) {
+            return ResultUtils.error("模板不存在");
+        }
+        
+        // 使用ConvertUtils转换为VO
+        AgentTemplateVO vo = ConvertUtils.sourceToTarget(template, AgentTemplateVO.class);
+        
+        return ResultUtils.success(vo);
+    }
+    
+    @PostMapping
+    @Operation(summary = "创建模板")
+    @RequiresPermissions("sys:role:superAdmin")
+    public Result<AgentTemplateEntity> createAgentTemplate(@Valid @RequestBody AgentTemplateEntity template) {
+        // 设置排序值为下一个可用的序号
+        template.setSort(agentTemplateService.getNextAvailableSort());
+        
+        boolean saved = agentTemplateService.save(template);
+        if (saved) {
+            return ResultUtils.success(template);
+        } else {
+            return ResultUtils.error("创建模板失败");
+        }
+    }
+    
+    @PutMapping
+    @Operation(summary = "更新模板")
+    @RequiresPermissions("sys:role:superAdmin")
+    public Result<AgentTemplateEntity> updateAgentTemplate(@Valid @RequestBody AgentTemplateEntity template) {
+        boolean updated = agentTemplateService.updateById(template);
+        if (updated) {
+            return ResultUtils.success(template);
+        } else {
+            return ResultUtils.error("更新模板失败");
+        }
+    }
+    
+    @DeleteMapping("/{id}")
+    @Operation(summary = "删除模板")
+    @RequiresPermissions("sys:role:superAdmin")
+    public Result<String> deleteAgentTemplate(@PathVariable("id") String id) {
+        // 先查询要删除的模板信息，获取其排序值
+        AgentTemplateEntity template = agentTemplateService.getById(id);
+        if (template == null) {
+            return ResultUtils.error("模板不存在");
+        }
+        
+        Integer deletedSort = template.getSort();
+        
+        // 执行删除操作
+        boolean deleted = agentTemplateService.removeById(id);
+        if (deleted) {
+            // 删除成功后，重新排序剩余模板
+            agentTemplateService.reorderTemplatesAfterDelete(deletedSort);
+            return ResultUtils.success("删除模板成功");
+        } else {
+            return ResultUtils.error("删除模板失败");
+        }
+    }
+    
+    
+    // 添加新的批量删除方法，使用不同的URL
+    @PostMapping("/batch-remove")
+    @Operation(summary = "批量删除模板")
+    @RequiresPermissions("sys:role:superAdmin")
+    public Result<String> batchRemoveAgentTemplates(@RequestBody List<String> ids) {
+        boolean deleted = agentTemplateService.removeByIds(ids);
+        if (deleted) {
+            return ResultUtils.success("批量删除成功");
+        } else {
+            return ResultUtils.error("批量删除模板失败");
+        }
+    }
+}
@@ -17,6 +17,7 @@ import io.swagger.v3.oas.annotations.Operation;
 import io.swagger.v3.oas.annotations.tags.Tag;
 import jakarta.validation.Valid;
 import lombok.AllArgsConstructor;
+import xiaozhi.common.exception.ErrorCode;
 import xiaozhi.common.exception.RenException;
 import xiaozhi.common.utils.Result;
 import xiaozhi.modules.agent.dto.AgentVoicePrintSaveDTO;
@@ -42,7 +43,7 @@ public class AgentVoicePrintController {
        if (b) {
            return new Result<>();
        }
-        return new Result<Void>().error("智能体的声纹创建失败");
+        return new Result<Void>().error(ErrorCode.AGENT_VOICEPRINT_CREATE_FAILED);
    }

    @PutMapping
@@ -54,7 +55,7 @@ public class AgentVoicePrintController {
        if (b) {
            return new Result<>();
        }
-        return new Result<Void>().error("智能体的对应声纹更新失败");
+        return new Result<Void>().error(ErrorCode.AGENT_VOICEPRINT_UPDATE_FAILED);
    }

    @DeleteMapping("/{id}")
@@ -67,7 +68,7 @@ public class AgentVoicePrintController {
        if (delete) {
            return new Result<>();
        }
-        return new Result<Void>().error("智能体的对应声纹删除失败");
+        return new Result<Void>().error(ErrorCode.AGENT_VOICEPRINT_DELETE_FAILED);
    }

    @GetMapping("/list/{id}")
@@ -76,7 +77,7 @@ public class AgentVoicePrintController {
    public Result<List<AgentVoicePrintVO>> list(@PathVariable String id) {
        String voiceprintUrl = sysParamsService.getValue("server.voice_print", true);
        if (StringUtils.isBlank(voiceprintUrl) || "null".equals(voiceprintUrl)) {
-            throw new RenException("声纹接口未配置，请先在参数配置中配置声纹接口地址(server.voice_print)");
+            throw new RenException(ErrorCode.VOICEPRINT_API_NOT_CONFIGURED);
        }
        Long userId = SecurityUser.getUserId();
        List<AgentVoicePrintVO> list = agentVoicePrintService.list(userId, id);
@@ -0,0 +1,12 @@
+package xiaozhi.modules.agent.dao;
+
+import org.apache.ibatis.annotations.Mapper;
+
+import com.baomidou.mybatisplus.core.mapper.BaseMapper;
+
+import xiaozhi.modules.agent.entity.AgentChatTitleEntity;
+
+@Mapper
+public interface AgentChatTitleDao extends BaseMapper<AgentChatTitleEntity> {
+
+}
@@ -0,0 +1,9 @@
+package xiaozhi.modules.agent.dao;
+
+import org.apache.ibatis.annotations.Mapper;
+import xiaozhi.common.dao.BaseDao;
+import xiaozhi.modules.agent.entity.AgentContextProviderEntity;
+
+@Mapper
+public interface AgentContextProviderDao extends BaseDao<AgentContextProviderEntity> {
+}
@@ -0,0 +1,24 @@
+package xiaozhi.modules.agent.dao;
+
+import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
+import xiaozhi.common.dao.BaseDao;
+import xiaozhi.modules.agent.entity.AgentTagEntity;
+
+import java.util.List;
+
+@Mapper
+public interface AgentTagDao extends BaseDao<AgentTagEntity> {
+
+    List<AgentTagEntity> selectByAgentId(@Param("agentId") String agentId);
+
+    List<AgentTagEntity> selectByAgentIds(@Param("agentIds") List<String> agentIds);
+
+    List<AgentTagEntity> selectAll();
+
+    List<String> selectAgentIdsByTagName(@Param("tagName") String tagName);
+
+    List<AgentTagEntity> selectByTagNames(@Param("tagNames") List<String> tagNames);
+
+    int batchInsert(@Param("list") List<AgentTagEntity> tagList);
+}
@@ -0,0 +1,18 @@
+package xiaozhi.modules.agent.dao;
+
+import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
+import xiaozhi.common.dao.BaseDao;
+import xiaozhi.modules.agent.entity.AgentTagRelationEntity;
+
+import java.util.List;
+
+@Mapper
+public interface AgentTagRelationDao extends BaseDao<AgentTagRelationEntity> {
+
+    int deleteByAgentId(@Param("agentId") String agentId);
+
+    int insertRelation(AgentTagRelationEntity relation);
+
+    int batchInsertRelation(@Param("list") List<AgentTagRelationEntity> relations);
+}
@@ -1,6 +1,9 @@
 package xiaozhi.modules.agent.dao;

+import java.util.List;
+
 import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;

 import com.baomidou.mybatisplus.core.mapper.BaseMapper;

@@ -15,12 +18,6 @@ import xiaozhi.modules.agent.entity.AgentChatHistoryEntity;
 */
@Mapper
 public interface AiAgentChatHistoryDao extends BaseMapper<AgentChatHistoryEntity> {
-    /**
-     * 根据智能体ID删除音频
-     *
-     * @param agentId 智能体ID
-     */
-    void deleteAudioByAgentId(String agentId);

    /**
     * 根据智能体ID删除聊天历史记录
@@ -35,4 +32,19 @@ public interface AiAgentChatHistoryDao extends BaseMapper<AgentChatHistoryEntity
     * @param agentId 智能体ID
     */
    void deleteAudioIdByAgentId(String agentId);
+
+    /**
+     * 根据智能体ID获取所有音频ID列表
+     *
+     * @param agentId 智能体ID
+     * @return 音频ID列表
+     */
+    List<String> getAudioIdsByAgentId(String agentId);
+
+    /**
+     * 批量删除音频
+     *
+     * @param audioIds 音频ID列表
+     */
+    void deleteAudioByIds(@Param("audioIds") List<String> audioIds);
 }
@@ -23,4 +23,9 @@ public class AgentChatSessionDTO {
     * 聊天条数
     */
    private Integer chatCount;
+
+    /**
+     * 会话标题
+     */
+    private String title;
 }
@@ -0,0 +1,45 @@
+package xiaozhi.modules.agent.dto;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+/**
+ * 智能体聊天记录总结DTO
+ */
+@Data
+@Schema(description = "智能体聊天记录总结对象")
+public class AgentChatSummaryDTO {
+
+    @Schema(description = "会话ID")
+    private String sessionId;
+
+    @Schema(description = "智能体ID")
+    private String agentId;
+
+    @Schema(description = "总结内容")
+    private String summary;
+
+    @Schema(description = "总结状态")
+    private boolean success;
+
+    @Schema(description = "错误信息")
+    private String errorMessage;
+
+    public AgentChatSummaryDTO() {
+        this.success = true;
+    }
+
+    public AgentChatSummaryDTO(String sessionId, String agentId, String summary) {
+        this.sessionId = sessionId;
+        this.agentId = agentId;
+        this.summary = summary;
+        this.success = true;
+    }
+
+    public AgentChatSummaryDTO(String sessionId, String errorMessage) {
+        this.sessionId = sessionId;
+        this.errorMessage = errorMessage;
+        this.success = false;
+    }
+
+}
@@ -1,9 +1,11 @@
 package xiaozhi.modules.agent.dto;

 import java.util.Date;
+import java.util.List;

 import io.swagger.v3.oas.annotations.media.Schema;
 import lombok.Data;
+import xiaozhi.modules.agent.dto.AgentTagDTO;

 /**
 * 智能体数据传输对象
@@ -45,4 +47,7 @@ public class AgentDTO {

    @Schema(description = "设备数量", example = "10")
    private Integer deviceCount;
+
+    @Schema(description = "标签列表")
+    private List<AgentTagDTO> tags;
 }
@@ -0,0 +1,20 @@
+package xiaozhi.modules.agent.dto;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+import java.io.Serializable;
+import java.util.List;
+
+@Data
+@Schema(description = "智能体标签DTO")
+public class AgentTagDTO implements Serializable {
+
+    private static final long serialVersionUID = 1L;
+
+    @Schema(description = "标签ID")
+    private String id;
+
+    @Schema(description = "标签名称")
+    private String tagName;
+}
@@ -1,6 +1,7 @@
 package xiaozhi.modules.agent.dto;

 import java.io.Serializable;
+import java.math.BigDecimal;
 import java.util.HashMap;
 import java.util.List;

@@ -32,6 +33,9 @@ public class AgentUpdateDTO implements Serializable {
    @Schema(description = "大语言模型标识", example = "llm_model_02", nullable = true)
    private String llmModelId;

+    @Schema(description = "小模型标识", example = "slm_model_02", nullable = true)
+    private String slmModelId;
+
    @Schema(description = "VLLM模型标识", example = "vllm_model_02", required = false)
    private String vllmModelId;

@@ -41,6 +45,18 @@ public class AgentUpdateDTO implements Serializable {
    @Schema(description = "音色标识", example = "voice_02", nullable = true)
    private String ttsVoiceId;

+    @Schema(description = "音色语言", example = "普通话", nullable = true)
+    private String ttsLanguage;
+
+    @Schema(description = "TTS音量", example = "50", nullable = true)
+    private Integer ttsVolume;
+
+    @Schema(description = "TTS语速", example = "50", nullable = true)
+    private Integer ttsRate;
+
+    @Schema(description = "TTS音调", example = "50", nullable = true)
+    private Integer ttsPitch;
+
    @Schema(description = "记忆模型标识", example = "mem_model_02", nullable = true)
    private String memModelId;

@@ -69,6 +85,9 @@ public class AgentUpdateDTO implements Serializable {
    @Schema(description = "排序", example = "1", nullable = true)
    private Integer sort;

+    @Schema(description = "上下文源配置", nullable = true)
+    private List<ContextProviderDTO> contextProviders;
+
    @Data
    @Schema(description = "插件函数信息")
    public static class FunctionInfo implements Serializable {
@@ -0,0 +1,19 @@
+package xiaozhi.modules.agent.dto;
+
+import java.io.Serializable;
+import java.util.Map;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+@Data
+@Schema(description = "上下文源配置DTO")
+public class ContextProviderDTO implements Serializable {
+    private static final long serialVersionUID = 1L;
+
+    @Schema(description = "URL地址")
+    private String url;
+
+    @Schema(description = "请求头")
+    private Map<String, Object> headers;
+}
@@ -1,32 +0,0 @@
-package xiaozhi.modules.agent.dto;
-
-import lombok.Data;
-
-/**
- * MCP JSON-RPC 请求 DTO
- */
-@Data
-public class McpJsonRpcRequest {
-    private String jsonrpc = "2.0";
-    private String method;
-    private Object params;
-    private Integer id;
-
-    public McpJsonRpcRequest() {
-    }
-
-    public McpJsonRpcRequest(String method) {
-        this.method = method;
-    }
-
-    public McpJsonRpcRequest(String method, Object params, Integer id) {
-        this.method = method;
-        this.params = params;
-        this.id = id;
-    }
-
-    public McpJsonRpcRequest(String method, Object params) {
-        this.method = method;
-        this.params = params;
-    }
-}
@@ -0,0 +1,36 @@
+package xiaozhi.modules.agent.entity;
+
+import java.util.Date;
+
+import com.baomidou.mybatisplus.annotation.IdType;
+import com.baomidou.mybatisplus.annotation.TableField;
+import com.baomidou.mybatisplus.annotation.TableId;
+import com.baomidou.mybatisplus.annotation.TableName;
+
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+@Data
+@Builder
+@AllArgsConstructor
+@NoArgsConstructor
+@TableName(value = "ai_agent_chat_title")
+public class AgentChatTitleEntity {
+
+    @TableId(type = IdType.ASSIGN_UUID)
+    private String id;
+
+    @TableField(value = "session_id")
+    private String sessionId;
+
+    @TableField(value = "title")
+    private String title;
+
+    @TableField(value = "created_at")
+    private Date createdAt;
+
+    @TableField(value = "updated_at")
+    private Date updatedAt;
+}
@@ -0,0 +1,43 @@
+package xiaozhi.modules.agent.entity;
+
+import java.util.Date;
+import java.util.List;
+
+import com.baomidou.mybatisplus.annotation.IdType;
+import com.baomidou.mybatisplus.annotation.TableField;
+import com.baomidou.mybatisplus.annotation.TableId;
+import com.baomidou.mybatisplus.annotation.TableName;
+import com.baomidou.mybatisplus.extension.handlers.JacksonTypeHandler;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+import xiaozhi.modules.agent.dto.ContextProviderDTO;
+
+@Data
+@TableName(value = "ai_agent_context_provider", autoResultMap = true)
+@Schema(description = "智能体上下文源配置")
+public class AgentContextProviderEntity {
+
+    @TableId(type = IdType.ASSIGN_UUID)
+    @Schema(description = "主键")
+    private String id;
+
+    @Schema(description = "智能体ID")
+    private String agentId;
+
+    @Schema(description = "上下文源配置")
+    @TableField(typeHandler = JacksonTypeHandler.class)
+    private List<ContextProviderDTO> contextProviders;
+
+    @Schema(description = "创建者")
+    private Long creator;
+
+    @Schema(description = "创建时间")
+    private Date createdAt;
+
+    @Schema(description = "更新者")
+    private Long updater;
+
+    @Schema(description = "更新时间")
+    private Date updatedAt;
+}
@@ -1,5 +1,6 @@
 package xiaozhi.modules.agent.entity;

+import java.math.BigDecimal;
 import java.util.Date;

 import com.baomidou.mybatisplus.annotation.IdType;
@@ -36,6 +37,9 @@ public class AgentEntity {
    @Schema(description = "大语言模型标识")
    private String llmModelId;

+    @Schema(description = "小模型标识")
+    private String slmModelId;
+
    @Schema(description = "VLLM模型标识")
    private String vllmModelId;

@@ -45,6 +49,18 @@ public class AgentEntity {
    @Schema(description = "音色标识")
    private String ttsVoiceId;

+    @Schema(description = "音色语言")
+    private String ttsLanguage;
+
+    @Schema(description = "TTS音量")
+    private Integer ttsVolume;
+
+    @Schema(description = "TTS语速")
+    private Integer ttsRate;
+
+    @Schema(description = "TTS音调")
+    private Integer ttsPitch;
+
    @Schema(description = "记忆模型标识")
    private String memModelId;

@@ -0,0 +1,41 @@
+package xiaozhi.modules.agent.entity;
+
+import java.util.Date;
+
+import com.baomidou.mybatisplus.annotation.IdType;
+import com.baomidou.mybatisplus.annotation.TableId;
+import com.baomidou.mybatisplus.annotation.TableName;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+@Data
+@TableName("ai_agent_tag")
+@Schema(description = "智能体标签")
+public class AgentTagEntity {
+
+    @TableId(type = IdType.ASSIGN_UUID)
+    @Schema(description = "主键")
+    private String id;
+
+    @Schema(description = "标签名称")
+    private String tagName;
+
+    @Schema(description = "排序")
+    private Integer sort;
+
+    @Schema(description = "创建者")
+    private Long creator;
+
+    @Schema(description = "创建时间")
+    private Date createdAt;
+
+    @Schema(description = "更新者")
+    private Long updater;
+
+    @Schema(description = "更新时间")
+    private Date updatedAt;
+
+    @Schema(description = "删除标记")
+    private Integer deleted;
+}
@@ -0,0 +1,41 @@
+package xiaozhi.modules.agent.entity;
+
+import java.util.Date;
+
+import com.baomidou.mybatisplus.annotation.IdType;
+import com.baomidou.mybatisplus.annotation.TableId;
+import com.baomidou.mybatisplus.annotation.TableName;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+@Data
+@TableName("ai_agent_tag_relation")
+@Schema(description = "智能体标签关联")
+public class AgentTagRelationEntity {
+
+    @TableId(type = IdType.ASSIGN_UUID)
+    @Schema(description = "主键")
+    private String id;
+
+    @Schema(description = "智能体ID")
+    private String agentId;
+
+    @Schema(description = "标签ID")
+    private String tagId;
+
+    @Schema(description = "排序")
+    private Integer sort;
+
+    @Schema(description = "创建者")
+    private Long creator;
+
+    @Schema(description = "创建时间")
+    private Date createdAt;
+
+    @Schema(description = "更新者")
+    private Long updater;
+
+    @Schema(description = "更新时间")
+    private Date updatedAt;
+}
@@ -1,6 +1,7 @@
 package xiaozhi.modules.agent.entity;

 import java.io.Serializable;
+import java.math.BigDecimal;
 import java.util.Date;

 import com.baomidou.mybatisplus.annotation.IdType;
@@ -64,6 +65,26 @@ public class AgentTemplateEntity implements Serializable {
     */
    private String ttsVoiceId;

+    /**
+     * 音色语言
+     */
+    private String ttsLanguage;
+
+    /**
+     * TTS音量
+     */
+    private Integer ttsVolume;
+
+    /**
+     * TTS语速
+     */
+    private Integer ttsRate;
+
+    /**
+     * TTS音调
+     */
+    private Integer ttsPitch;
+
    /**
     * 记忆模型标识
     */
@@ -0,0 +1,23 @@
+package xiaozhi.modules.agent.service;
+
+/**
+ * 智能体聊天记录总结服务接口
+ */
+public interface AgentChatSummaryService {
+
+    /**
+     * 根据会话ID生成聊天记录总结并保存到智能体记忆
+     * 
+     * @param sessionId 会话ID
+     * @return 保存结果
+     */
+    boolean generateAndSaveChatSummary(String sessionId);
+
+    /**
+     * 根据会话ID生成聊天标题并保存
+     *
+     * @param sessionId 会话ID
+     * @return 是否成功
+     */
+    boolean generateAndSaveChatTitle(String sessionId);
+}
@@ -0,0 +1,10 @@
+package xiaozhi.modules.agent.service;
+
+import xiaozhi.modules.agent.entity.AgentChatTitleEntity;
+
+public interface AgentChatTitleService {
+
+    void saveOrUpdateTitle(String sessionId, String title);
+
+    String getTitleBySessionId(String sessionId);
+}
@@ -0,0 +1,25 @@
+package xiaozhi.modules.agent.service;
+
+import xiaozhi.common.service.BaseService;
+import xiaozhi.modules.agent.entity.AgentContextProviderEntity;
+
+public interface AgentContextProviderService extends BaseService<AgentContextProviderEntity> {
+    /**
+     * 根据智能体ID获取上下文源配置
+     * @param agentId 智能体ID
+     * @return 上下文源配置实体
+     */
+    AgentContextProviderEntity getByAgentId(String agentId);
+
+    /**
+     * 保存或更新上下文源配置
+     * @param entity 实体
+     */
+    void saveOrUpdateByAgentId(AgentContextProviderEntity entity);
+
+    /**
+     * 根据智能体ID删除上下文源配置
+     * @param agentId 智能体ID
+     */
+    void deleteByAgentId(String agentId);
+}
@@ -54,9 +54,11 @@ public interface AgentService extends BaseService<AgentEntity> {
     * 获取用户智能体列表
     *
     * @param userId 用户ID
+     * @param keyword 搜索关键词
+     * @param searchType 搜索类型（name - 按名称搜索，mac - 按MAC地址搜索）
     * @return 智能体列表
     */
-    List<AgentDTO> getUserAgents(Long userId);
+    List<AgentDTO> getUserAgents(Long userId, String keyword, String searchType);

    /**
     * 根据智能体ID获取设备数量
@@ -98,4 +100,6 @@ public interface AgentService extends BaseService<AgentEntity> {
     * @return 创建的智能体ID
     */
    String createAgent(AgentCreateDTO dto);
+
+
 }
@@ -0,0 +1,25 @@
+package xiaozhi.modules.agent.service;
+
+import java.util.List;
+
+import xiaozhi.modules.agent.dto.AgentTagDTO;
+import xiaozhi.modules.agent.entity.AgentTagEntity;
+
+public interface AgentTagService {
+
+    AgentTagEntity saveTag(String tagName);
+
+    void deleteTag(String tagId);
+
+    List<AgentTagDTO> getTagsByAgentId(String agentId);
+
+    void saveAgentTags(String agentId, List<String> tagIds, List<String> tagNames);
+
+    void deleteAgentTags(String agentId);
+
+    List<AgentTagDTO> getTagsByAgentIds(List<String> agentIds);
+
+    List<AgentTagDTO> getAllTags();
+
+    List<String> getAgentIdsByTagName(String tagName);
+}
@@ -25,4 +25,18 @@ public interface AgentTemplateService extends IService<AgentTemplateEntity> {
     * @param modelId   模型ID
     */
    void updateDefaultTemplateModelId(String modelType, String modelId);
+
+    /**
+     * 删除模板后重新排序剩余模板
+     * 
+     * @param deletedSort 被删除模板的排序值
+     */
+    void reorderTemplatesAfterDelete(Integer deletedSort);
+
+    /**
+     * 获取下一个可用的排序序号（寻找最小的未使用序号）
+     * 
+     * @return 下一个可用的排序序号
+     */
+    Integer getNextAvailableSort();
 }
@@ -17,6 +17,7 @@ import xiaozhi.modules.agent.entity.AgentChatHistoryEntity;
 import xiaozhi.modules.agent.entity.AgentEntity;
 import xiaozhi.modules.agent.service.AgentChatAudioService;
 import xiaozhi.modules.agent.service.AgentChatHistoryService;
+import xiaozhi.modules.agent.service.AgentChatSummaryService;
 import xiaozhi.modules.agent.service.AgentService;
 import xiaozhi.modules.agent.service.biz.AgentChatHistoryBizService;
 import xiaozhi.modules.device.entity.DeviceEntity;
@@ -36,6 +37,7 @@ public class AgentChatHistoryBizServiceImpl implements AgentChatHistoryBizServic
    private final AgentService agentService;
    private final AgentChatHistoryService agentChatHistoryService;
    private final AgentChatAudioService agentChatAudioService;
+    private final AgentChatSummaryService agentChatSummaryService;
    private final RedisUtils redisUtils;
    private final DeviceService deviceService;

@@ -50,7 +52,8 @@ public class AgentChatHistoryBizServiceImpl implements AgentChatHistoryBizServic
    public Boolean report(AgentChatHistoryReportDTO report) {
        String macAddress = report.getMacAddress();
        Byte chatType = report.getChatType();
-        Long reportTimeMillis = null != report.getReportTime() ? report.getReportTime() * 1000 : System.currentTimeMillis();
+        Long reportTimeMillis = null != report.getReportTime() ? report.getReportTime()
+                : System.currentTimeMillis();
        log.info("小智设备聊天上报请求: macAddress={}, type={} reportTime={}", macAddress, chatType, reportTimeMillis);

        // 根据设备MAC地址查询对应的默认智能体，判断是否需要上报
@@ -105,7 +108,8 @@ public class AgentChatHistoryBizServiceImpl implements AgentChatHistoryBizServic
    /**
     * 组装上报数据
     */
-    private void saveChatText(AgentChatHistoryReportDTO report, String agentId, String macAddress, String audioId, Long reportTime) {
+    private void saveChatText(AgentChatHistoryReportDTO report, String agentId, String macAddress, String audioId,
+            Long reportTime) {
        // 构建聊天记录实体
        AgentChatHistoryEntity entity = AgentChatHistoryEntity.builder()
                .macAddress(macAddress)
@@ -5,6 +5,8 @@ import java.util.List;
 import java.util.Map;
 import java.util.stream.Collectors;

+import cn.hutool.core.collection.ListUtil;
+import lombok.RequiredArgsConstructor;
 import org.springframework.stereotype.Service;
 import org.springframework.transaction.annotation.Transactional;

@@ -18,12 +20,14 @@ import xiaozhi.common.constant.Constant;
 import xiaozhi.common.page.PageData;
 import xiaozhi.common.utils.ConvertUtils;
 import xiaozhi.common.utils.JsonUtils;
+import xiaozhi.common.utils.ToolUtil;
 import xiaozhi.modules.agent.Enums.AgentChatHistoryType;
 import xiaozhi.modules.agent.dao.AiAgentChatHistoryDao;
 import xiaozhi.modules.agent.dto.AgentChatHistoryDTO;
 import xiaozhi.modules.agent.dto.AgentChatSessionDTO;
 import xiaozhi.modules.agent.entity.AgentChatHistoryEntity;
 import xiaozhi.modules.agent.service.AgentChatHistoryService;
+import xiaozhi.modules.agent.service.AgentChatTitleService;
 import xiaozhi.modules.agent.vo.AgentChatHistoryUserVO;

 /**
@@ -34,9 +38,12 @@ import xiaozhi.modules.agent.vo.AgentChatHistoryUserVO;
 * @since 1.0.0
 */
@Service
+@RequiredArgsConstructor
 public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryDao, AgentChatHistoryEntity>
        implements AgentChatHistoryService {

+    private final AgentChatTitleService agentChatTitleService;
+
    @Override
    public PageData<AgentChatSessionDTO> getSessionListByAgentId(Map<String, Object> params) {
        String agentId = (String) params.get("agentId");
@@ -59,6 +66,7 @@ public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryD
            dto.setSessionId((String) map.get("session_id"));
            dto.setCreatedAt((LocalDateTime) map.get("created_at"));
            dto.setChatCount(((Number) map.get("chat_count")).intValue());
+            dto.setTitle(agentChatTitleService.getTitleBySessionId(dto.getSessionId()));
            return dto;
        }).collect(Collectors.toList());

@@ -84,7 +92,15 @@ public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryD
    @Transactional(rollbackFor = Exception.class)
    public void deleteByAgentId(String agentId, Boolean deleteAudio, Boolean deleteText) {
        if (deleteAudio) {
-            baseMapper.deleteAudioByAgentId(agentId);
+            // 分批删除音频,避免超时
+            List<String> audioIds = baseMapper.getAudioIdsByAgentId(agentId);
+            if (ToolUtil.isNotEmpty(audioIds)) {
+                // 每批删除1000条
+                List<List<String>> batch = ListUtil.split(audioIds, 1000);
+                batch.forEach(dataList -> {
+                    baseMapper.deleteAudioByIds(dataList);
+                });
+            }
        }
        if (deleteAudio && !deleteText) {
            baseMapper.deleteAudioIdByAgentId(agentId);
@@ -103,7 +119,11 @@ public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryD
        wrapper.select(AgentChatHistoryEntity::getContent, AgentChatHistoryEntity::getAudioId)
                .eq(AgentChatHistoryEntity::getAgentId, agentId)
                .eq(AgentChatHistoryEntity::getChatType, AgentChatHistoryType.USER.getValue())
-                .isNotNull(AgentChatHistoryEntity::getAudioId);
+                .isNotNull(AgentChatHistoryEntity::getAudioId)
+                // 添加此行，确保查询结果按照创建时间降序排列
+                // 使用id的原因：数据形式，id越大的创建时间就越晚，所以使用id的结果和创建时间降序排列结果一样
+                // id作为降序排列的优势，性能高，有主键索引，不用在排序的时候重新进行排除扫描比较
+                .orderByDesc(AgentChatHistoryEntity::getId);

        // 构建分页查询，查询前50页数据
        Page<AgentChatHistoryEntity> pageParam = new Page<>(0, 50);
@@ -0,0 +1,521 @@
+package xiaozhi.modules.agent.service.impl;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+import org.apache.commons.lang3.StringUtils;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.stereotype.Service;
+
+import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
+
+import lombok.RequiredArgsConstructor;
+import xiaozhi.common.constant.Constant;
+import xiaozhi.modules.agent.dto.AgentChatHistoryDTO;
+import xiaozhi.modules.agent.dto.AgentChatSummaryDTO;
+import xiaozhi.modules.agent.dto.AgentMemoryDTO;
+import xiaozhi.modules.agent.dto.AgentUpdateDTO;
+import xiaozhi.modules.agent.entity.AgentChatHistoryEntity;
+import xiaozhi.modules.agent.service.AgentChatHistoryService;
+import xiaozhi.modules.agent.service.AgentChatSummaryService;
+import xiaozhi.modules.agent.service.AgentChatTitleService;
+import xiaozhi.modules.agent.service.AgentService;
+import xiaozhi.modules.agent.vo.AgentInfoVO;
+import xiaozhi.modules.device.entity.DeviceEntity;
+import xiaozhi.modules.device.service.DeviceService;
+import xiaozhi.modules.llm.service.LLMService;
+import xiaozhi.modules.model.entity.ModelConfigEntity;
+import xiaozhi.modules.model.service.ModelConfigService;
+
+/**
+ * 智能体聊天记录总结服务实现类
+ * 实现Python端mem_local_short.py中的总结逻辑
+ */
+@Service
+@RequiredArgsConstructor
+public class AgentChatSummaryServiceImpl implements AgentChatSummaryService {
+
+    private static final Logger log = LoggerFactory.getLogger(AgentChatSummaryServiceImpl.class);
+
+    private final AgentChatHistoryService agentChatHistoryService;
+    private final AgentService agentService;
+    private final AgentChatTitleService agentChatTitleService;
+    private final DeviceService deviceService;
+    private final LLMService llmService;
+    private final ModelConfigService modelConfigService;
+
+    // 总结规则常量
+    private static final int MAX_SUMMARY_LENGTH = 1800; // 最大总结长度
+    private static final Pattern JSON_PATTERN = Pattern.compile("\\{.*?\\}", Pattern.DOTALL);
+    private static final Pattern DEVICE_CONTROL_PATTERN = Pattern.compile("设备控制|设备操作|控制设备|设备状态",
+            Pattern.CASE_INSENSITIVE);
+    private static final Pattern WEATHER_PATTERN = Pattern.compile("天气|温度|湿度|降雨|气象", Pattern.CASE_INSENSITIVE);
+    private static final Pattern DATE_PATTERN = Pattern.compile("日期|时间|星期|月份|年份", Pattern.CASE_INSENSITIVE);
+
+    private AgentChatSummaryDTO generateChatSummary(String sessionId) {
+        try {
+            System.out.println("开始生成会话 " + sessionId + " 的聊天记录总结");
+
+            // 1. 根据sessionId获取聊天记录
+            List<AgentChatHistoryDTO> chatHistory = getChatHistoryBySessionId(sessionId);
+            if (chatHistory == null || chatHistory.isEmpty()) {
+                return new AgentChatSummaryDTO(sessionId, "未找到该会话的聊天记录");
+            }
+
+            // 2. 获取智能体信息
+            String agentId = getAgentIdFromSession(sessionId, chatHistory);
+            if (StringUtils.isBlank(agentId)) {
+                return new AgentChatSummaryDTO(sessionId, "无法获取智能体信息");
+            }
+
+            // 3. 提取关键对话内容
+            List<String> meaningfulMessages = extractMeaningfulMessages(chatHistory);
+            if (meaningfulMessages.isEmpty()) {
+                return new AgentChatSummaryDTO(sessionId, "没有有效的对话内容可总结");
+            }
+
+            // 4. 生成总结（generateSummaryFromMessages方法已包含长度限制逻辑）
+            String summary = generateSummaryFromMessages(meaningfulMessages, agentId);
+
+            log.info("成功生成会话 {} 的聊天记录总结，长度: {} 字符", sessionId, summary.length());
+            return new AgentChatSummaryDTO(sessionId, agentId, summary);
+
+        } catch (Exception e) {
+            log.error("生成会话 {} 的聊天记录总结时发生错误: {}", sessionId, e.getMessage());
+            return new AgentChatSummaryDTO(sessionId, "生成总结时发生错误: " + e.getMessage());
+        }
+    }
+
+    @Override
+    public boolean generateAndSaveChatSummary(String sessionId) {
+        try {
+            DeviceEntity device = getDeviceBySessionId(sessionId);
+            if (device == null) {
+                log.info("未找到与会话 {} 关联的设备", sessionId);
+                return false;
+            }
+
+            String agentId = device.getAgentId();
+            String memModelId = agentService.getAgentById(agentId).getMemModelId();
+
+            if (memModelId == null || memModelId.equals(Constant.MEMORY_MEM_REPORT_ONLY)) {
+                log.info("会话 {} 使用仅上报聊天记录模式，跳过记忆总结", sessionId);
+                return true;
+            }
+
+            boolean shouldSummarizeMemory = !memModelId.equals(Constant.MEMORY_NO_MEM)
+                    && !memModelId.equals(Constant.MEMORY_MEM0AI)
+                    && !memModelId.equals(Constant.MEMORY_POWERMEM);
+
+            if (shouldSummarizeMemory) {
+                AgentChatSummaryDTO summaryDTO = generateChatSummary(sessionId);
+                if (summaryDTO.isSuccess()) {
+                    agentService.updateAgentById(agentId, new AgentUpdateDTO() {
+                        {
+                            setSummaryMemory(summaryDTO.getSummary());
+                        }
+                    });
+                    log.info("成功保存会话 {} 的聊天记录总结到智能体 {}", sessionId, agentId);
+                } else {
+                    log.info("生成总结失败: {}", summaryDTO.getErrorMessage());
+                }
+            } else {
+                log.info("会话 {} 使用 {} 模式，跳过记忆总结", sessionId, memModelId);
+            }
+
+            return true;
+
+        } catch (Exception e) {
+            log.error("保存会话 {} 的聊天记录总结时发生错误: {}", sessionId, e.getMessage());
+            return false;
+        }
+    }
+
+    @Override
+    public boolean generateAndSaveChatTitle(String sessionId) {
+        try {
+            // 自动获取agentId
+            String agentId = findAgentIdBySessionId(sessionId);
+            if (StringUtils.isBlank(agentId)) {
+                log.warn("会话 {} 无法获取智能体信息，跳过标题生成", sessionId);
+                return false;
+            }
+
+            List<AgentChatHistoryDTO> chatHistory = getChatHistoryBySessionId(sessionId);
+            if (chatHistory == null || chatHistory.isEmpty()) {
+                return false;
+            }
+
+            List<String> meaningfulMessages = extractMeaningfulMessages(chatHistory);
+            if (meaningfulMessages.isEmpty()) {
+                return false;
+            }
+
+            StringBuilder conversation = new StringBuilder();
+            for (int i = 0; i < meaningfulMessages.size(); i++) {
+                conversation.append("消息").append(i + 1).append(": ").append(meaningfulMessages.get(i)).append("\n");
+            }
+
+            String slmModelId = getSlmModelId(agentId);
+            String title = llmService.generateTitle(conversation.toString(), slmModelId);
+
+            if (StringUtils.isNotBlank(title)) {
+                agentChatTitleService.saveOrUpdateTitle(sessionId, title);
+                log.info("成功保存会话 {} 的标题: {}", sessionId, title);
+                return true;
+            }
+            return false;
+        } catch (Exception e) {
+            log.error("生成会话 {} 的标题时发生错误: {}", sessionId, e.getMessage());
+            return false;
+        }
+    }
+
+    private String getSlmModelId(String agentId) {
+        try {
+            if (StringUtils.isBlank(agentId)) {
+                return null;
+            }
+
+            AgentInfoVO agentInfo = agentService.getAgentById(agentId);
+            if (agentInfo == null) {
+                return null;
+            }
+
+            String slmModelId = agentInfo.getSlmModelId();
+            if (StringUtils.isNotBlank(slmModelId)) {
+                log.info("会话 {} 使用SLM模型: {}", agentId, slmModelId);
+                return slmModelId;
+            }
+
+            ModelConfigEntity defaultLlmConfig = getDefaultLLMConfig();
+            if (defaultLlmConfig != null) {
+                log.info("会话 {} 使用默认LLM模型: {}", agentId, defaultLlmConfig.getId());
+                return defaultLlmConfig.getId();
+            }
+
+            String llmModelId = agentInfo.getLlmModelId();
+            log.info("会话 {} 使用LLM模型(最终回退): {}", agentId, llmModelId);
+            return llmModelId;
+        } catch (Exception e) {
+            log.error("获取智能体slm模型ID失败，agentId: {}, 错误: {}", agentId, e.getMessage());
+            return null;
+        }
+    }
+
+    private ModelConfigEntity getDefaultLLMConfig() {
+        try {
+            List<ModelConfigEntity> llmConfigs = modelConfigService.getEnabledModelsByType("LLM");
+            if (llmConfigs == null || llmConfigs.isEmpty()) {
+                return null;
+            }
+
+            for (ModelConfigEntity config : llmConfigs) {
+                if (config.getIsDefault() != null && config.getIsDefault() == 1) {
+                    return config;
+                }
+            }
+
+            return llmConfigs.get(0);
+        } catch (Exception e) {
+            log.error("获取默认LLM配置失败: {}", e.getMessage());
+            return null;
+        }
+    }
+
+    /**
+     * 根据会话ID获取聊天记录
+     */
+    private List<AgentChatHistoryDTO> getChatHistoryBySessionId(String sessionId) {
+        try {
+            // 这里需要根据sessionId获取聊天记录
+            // 由于现有接口需要agentId，我们需要先找到关联的agentId
+            String agentId = findAgentIdBySessionId(sessionId);
+            if (StringUtils.isBlank(agentId)) {
+                return null;
+            }
+            return agentChatHistoryService.getChatHistoryBySessionId(agentId, sessionId);
+        } catch (Exception e) {
+            log.error("获取会话 {} 的聊天记录失败: {}", sessionId, e.getMessage());
+            return null;
+        }
+    }
+
+    /**
+     * 根据会话ID查找关联的智能体ID
+     */
+    private String findAgentIdBySessionId(String sessionId) {
+        try {
+            // 查询该会话的第一条记录获取agentId
+            QueryWrapper<AgentChatHistoryEntity> wrapper = new QueryWrapper<>();
+            wrapper.select("agent_id")
+                    .eq("session_id", sessionId)
+                    .last("LIMIT 1");
+
+            AgentChatHistoryEntity entity = agentChatHistoryService.getOne(wrapper);
+            return entity != null ? entity.getAgentId() : null;
+        } catch (Exception e) {
+            log.error("根据会话ID {} 查找智能体ID失败: {}", sessionId, e.getMessage());
+            return null;
+        }
+    }
+
+    /**
+     * 从会话中获取智能体ID
+     */
+    private String getAgentIdFromSession(String sessionId, List<AgentChatHistoryDTO> chatHistory) {
+        // 直接从数据库查询智能体ID
+        return findAgentIdBySessionId(sessionId);
+    }
+
+    /**
+     * 提取有意义的对话内容（只提取用户消息，排除AI回复）
+     */
+    private List<String> extractMeaningfulMessages(List<AgentChatHistoryDTO> chatHistory) {
+        List<String> meaningfulMessages = new ArrayList<>();
+
+        for (AgentChatHistoryDTO message : chatHistory) {
+            // 只处理用户消息（chatType = 1）
+            if (message.getChatType() != null && message.getChatType() == 1) {
+                String content = extractContentFromMessage(message);
+                if (isMeaningfulMessage(content)) {
+                    meaningfulMessages.add(content);
+                }
+            }
+        }
+
+        return meaningfulMessages;
+    }
+
+    /**
+     * 从消息中提取内容（处理JSON格式）
+     */
+    private String extractContentFromMessage(AgentChatHistoryDTO message) {
+        String content = message.getContent();
+        if (StringUtils.isBlank(content)) {
+            return "";
+        }
+
+        // 处理JSON格式内容（与前端ChatHistoryDialog.vue逻辑一致）
+        Matcher matcher = JSON_PATTERN.matcher(content);
+        if (matcher.find()) {
+            String jsonContent = matcher.group();
+            // 简化处理：提取JSON中的文本内容
+            return extractTextFromJson(jsonContent);
+        }
+
+        return content;
+    }
+
+    /**
+     * 从JSON中提取文本内容
+     */
+    private String extractTextFromJson(String jsonContent) {
+        // 简化处理：提取"content"字段的值
+        Pattern contentPattern = Pattern.compile("\"content\"\s*:\s*\"([^\"]*)\"");
+        Matcher matcher = contentPattern.matcher(jsonContent);
+        if (matcher.find()) {
+            return matcher.group(1);
+        }
+        return jsonContent;
+    }
+
+    /**
+     * 判断是否为有意义的消息
+     */
+    private boolean isMeaningfulMessage(String content) {
+        if (StringUtils.isBlank(content)) {
+            return false;
+        }
+
+        // 排除设备控制信息
+        if (DEVICE_CONTROL_PATTERN.matcher(content).find()) {
+            return false;
+        }
+
+        // 排除日期天气等无关内容
+        if (WEATHER_PATTERN.matcher(content).find() || DATE_PATTERN.matcher(content).find()) {
+            return false;
+        }
+
+        // 排除过短的消息
+        return content.length() >= 5;
+    }
+
+    /**
+     * 从消息生成总结
+     */
+    private String generateSummaryFromMessages(List<String> messages, String agentId) {
+        if (messages.isEmpty()) {
+            return "本次对话内容较少，没有需要总结的重要信息。";
+        }
+
+        // 构建完整的对话内容
+        StringBuilder conversation = new StringBuilder();
+        for (int i = 0; i < messages.size(); i++) {
+            conversation.append("消息").append(i + 1).append(": ").append(messages.get(i)).append("\n");
+        }
+
+        try {
+            // 获取当前智能体的历史记忆
+            String historyMemory = getCurrentAgentMemory(agentId);
+
+            // 调用LLM服务进行智能总结，传递agentId以获取正确的模型配置
+            String summary = callJavaLLMForSummaryWithHistory(conversation.toString(), historyMemory, agentId);
+
+            // 应用总结规则：限制最大长度
+            if (summary.length() > MAX_SUMMARY_LENGTH) {
+                summary = summary.substring(0, MAX_SUMMARY_LENGTH) + "...";
+            }
+
+            return summary;
+        } catch (Exception e) {
+            log.error("调用Java端LLM服务失败: {}", e.getMessage());
+            throw new RuntimeException("LLM服务不可用，无法生成聊天总结");
+        }
+    }
+
+    /**
+     * 获取当前智能体的历史记忆
+     */
+    private String getCurrentAgentMemory(String agentId) {
+        try {
+            if (StringUtils.isBlank(agentId)) {
+                return null;
+            }
+
+            // 获取智能体信息
+            AgentInfoVO agentInfo = agentService.getAgentById(agentId);
+            if (agentInfo == null) {
+                return null;
+            }
+
+            // 返回智能体的当前总结记忆
+            return agentInfo.getSummaryMemory();
+        } catch (Exception e) {
+            log.error("获取智能体历史记忆失败，agentId: {}, 错误: {}", agentId, e.getMessage());
+            return null;
+        }
+    }
+
+    /**
+     * 调用Java端LLM服务进行智能总结（支持历史记忆合并）
+     */
+    private String callJavaLLMForSummaryWithHistory(String conversation, String historyMemory, String agentId) {
+        try {
+            String modelId = getSlmModelId(agentId);
+
+            if (StringUtils.isBlank(modelId)) {
+                log.info("未找到SLM模型，使用默认LLM服务");
+                return llmService.generateSummaryWithHistory(conversation, historyMemory, null, null);
+            }
+
+            String summary = llmService.generateSummaryWithHistory(conversation, historyMemory, null, modelId);
+
+            if (StringUtils.isNotBlank(summary) && !summary.equals("服务暂不可用") && !summary.equals("总结生成失败")) {
+                return summary;
+            }
+
+            throw new RuntimeException("Java端LLM服务返回异常: " + summary);
+
+        } catch (Exception e) {
+            log.error("调用Java端LLM服务异常，agentId: {}, 错误: {}", agentId, e.getMessage());
+            throw e;
+        }
+    }
+
+    /**
+     * 调用Java端LLM服务进行智能总结
+     */
+    private String callJavaLLMForSummary(String conversation, String agentId) {
+        try {
+            String modelId = getSlmModelId(agentId);
+
+            if (StringUtils.isBlank(modelId)) {
+                log.info("未找到SLM模型，使用默认LLM服务");
+                return llmService.generateSummary(conversation);
+            }
+
+            String summary = llmService.generateSummaryWithModel(conversation, modelId);
+
+            if (StringUtils.isNotBlank(summary) && !summary.equals("服务暂不可用") && !summary.equals("总结生成失败")) {
+                return summary;
+            }
+
+            throw new RuntimeException("Java端LLM服务返回异常: " + summary);
+
+        } catch (Exception e) {
+            log.error("调用Java端LLM服务异常，agentId: {}, 错误: {}", agentId, e.getMessage());
+            throw e;
+        }
+    }
+
+    /**
+     * 获取记忆总结的LLM模型ID
+     */
+    private String getMemorySummaryModelId(String agentId) {
+        try {
+            if (StringUtils.isBlank(agentId)) {
+                return null;
+            }
+
+            // 获取智能体信息
+            AgentInfoVO agentInfo = agentService.getAgentById(agentId);
+            if (agentInfo == null) {
+                return null;
+            }
+
+            // 获取智能体的记忆模型ID
+            String memModelId = agentInfo.getMemModelId();
+            if (StringUtils.isBlank(memModelId)) {
+                return null;
+            }
+
+            // 获取记忆模型配置
+            ModelConfigEntity memModelConfig = modelConfigService.getModelByIdFromCache(memModelId);
+            if (memModelConfig == null || memModelConfig.getConfigJson() == null) {
+                return null;
+            }
+
+            // 从记忆模型配置中提取对应的LLM模型ID
+            Map<String, Object> configMap = memModelConfig.getConfigJson();
+            String llmModelId = (String) configMap.get("llm");
+
+            if (StringUtils.isBlank(llmModelId)) {
+                // 如果记忆模型没有配置独立的LLM，则使用智能体的默认LLM模型
+                return agentInfo.getLlmModelId();
+            }
+
+            return llmModelId;
+        } catch (Exception e) {
+            log.error("获取记忆总结LLM模型ID失败，agentId: {}, 错误: {}", agentId, e.getMessage());
+            return null;
+        }
+    }
+
+    /**
+     * 根据会话ID获取设备信息
+     */
+    private DeviceEntity getDeviceBySessionId(String sessionId) {
+        try {
+            // 查询该会话的第一条记录获取macAddress
+            QueryWrapper<AgentChatHistoryEntity> wrapper = new QueryWrapper<>();
+            wrapper.select("mac_address")
+                    .eq("session_id", sessionId)
+                    .last("LIMIT 1");
+
+            AgentChatHistoryEntity entity = agentChatHistoryService.getOne(wrapper);
+            if (entity != null && StringUtils.isNotBlank(entity.getMacAddress())) {
+                return deviceService.getDeviceByMacAddress(entity.getMacAddress());
+            }
+            return null;
+        } catch (Exception e) {
+            log.error("根据会话ID {} 查找设备信息失败: {}", sessionId, e.getMessage());
+            return null;
+        }
+    }
+}
@@ -0,0 +1,60 @@
+package xiaozhi.modules.agent.service.impl;
+
+import java.util.Date;
+
+import org.apache.commons.lang3.StringUtils;
+import org.springframework.stereotype.Service;
+
+import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
+
+import lombok.RequiredArgsConstructor;
+import xiaozhi.modules.agent.dao.AgentChatTitleDao;
+import xiaozhi.modules.agent.entity.AgentChatTitleEntity;
+import xiaozhi.modules.agent.service.AgentChatTitleService;
+
+@Service
+@RequiredArgsConstructor
+public class AgentChatTitleServiceImpl implements AgentChatTitleService {
+
+    private final AgentChatTitleDao agentChatTitleDao;
+
+    @Override
+    public void saveOrUpdateTitle(String sessionId, String title) {
+        if (StringUtils.isBlank(sessionId) || StringUtils.isBlank(title)) {
+            return;
+        }
+
+        QueryWrapper<AgentChatTitleEntity> wrapper = new QueryWrapper<>();
+        wrapper.eq("session_id", sessionId);
+
+        AgentChatTitleEntity existing = agentChatTitleDao.selectOne(wrapper);
+
+        if (existing != null) {
+            existing.setTitle(title);
+            existing.setUpdatedAt(new Date());
+            agentChatTitleDao.updateById(existing);
+        } else {
+            AgentChatTitleEntity newEntity = AgentChatTitleEntity.builder()
+                    .id(java.util.UUID.randomUUID().toString().replace("-", ""))
+                    .sessionId(sessionId)
+                    .title(title)
+                    .createdAt(new Date())
+                    .updatedAt(new Date())
+                    .build();
+            agentChatTitleDao.insert(newEntity);
+        }
+    }
+
+    @Override
+    public String getTitleBySessionId(String sessionId) {
+        if (StringUtils.isBlank(sessionId)) {
+            return null;
+        }
+
+        QueryWrapper<AgentChatTitleEntity> wrapper = new QueryWrapper<>();
+        wrapper.eq("session_id", sessionId);
+
+        AgentChatTitleEntity entity = agentChatTitleDao.selectOne(wrapper);
+        return entity != null ? entity.getTitle() : null;
+    }
+}
@@ -0,0 +1,35 @@
+package xiaozhi.modules.agent.service.impl;
+
+import org.springframework.stereotype.Service;
+
+import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
+
+import xiaozhi.common.service.impl.BaseServiceImpl;
+import xiaozhi.modules.agent.dao.AgentContextProviderDao;
+import xiaozhi.modules.agent.entity.AgentContextProviderEntity;
+import xiaozhi.modules.agent.service.AgentContextProviderService;
+
+@Service
+public class AgentContextProviderServiceImpl extends BaseServiceImpl<AgentContextProviderDao, AgentContextProviderEntity> implements AgentContextProviderService {
+
+    @Override
+    public AgentContextProviderEntity getByAgentId(String agentId) {
+        return baseDao.selectOne(new QueryWrapper<AgentContextProviderEntity>().eq("agent_id", agentId));
+    }
+
+    @Override
+    public void saveOrUpdateByAgentId(AgentContextProviderEntity entity) {
+        AgentContextProviderEntity exist = getByAgentId(entity.getAgentId());
+        if (exist != null) {
+            entity.setId(exist.getId());
+            updateById(entity);
+        } else {
+            insert(entity);
+        }
+    }
+
+    @Override
+    public void deleteByAgentId(String agentId) {
+        baseDao.delete(new QueryWrapper<AgentContextProviderEntity>().eq("agent_id", agentId));
+    }
+}
--- a/Show More
+++ b/Show More