Merge pull request #2789 from xinnan-tech/test_page_token

Bump to 0.8.11

.github/dependabot.yml

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

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

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

.github/workflows/docker-image.yml

@@ -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:

.gitignore

@@ -182,4 +182,5 @@ uploadfile
 # Do not ignore env and json files inside manager-mobile
 !main/manager-mobile/**/env/
 !main/manager-mobile/**/.env*
-!main/manager-mobile/**/*.json
+!main/manager-mobile/**/*.json
+!main/xiaozhi-server/**/*.json

Dockerfile-server

@@ -1,36 +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
-
-# 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
-
-COPY main/xiaozhi-server/requirements.txt .
-
-# 安装Python依赖，使用并行下载
-RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \
-    pip install --no-cache-dir -r requirements.txt --default-timeout=120 --retries 5
-
-# 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

Dockerfile-server-base

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

README.md

@@ -6,29 +6,24 @@
 本项目基于人机共生智能理论和技术研发智能终端软硬件体系<br/>为开源智能硬件项目
 <a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a>提供后端服务<br/>
 根据<a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">小智通信协议</a>使用Python、Java、Vue实现<br/>
-支持MQTT+UDP协议、Websocket协议、MCP接入点、声纹识别
+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="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>
@@ -188,8 +183,8 @@ Spearheaded by Professor Siyuan Liu's Team (South China University of Technology
 #### 🚀 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)
 
@@ -216,10 +211,10 @@ 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) | 👍FunASR(本地GPU模式) |
-| LLM(大模型) | ChatGLMLLM(智谱glm-4-flash) | 👍AliLLM(qwen3-235b-a22b-instruct-2507) 或 👍DoubaoLLM(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) | 👍qwen2.5-vl-3b-instructh(阿里百炼) |
+| TTS(语音合成) | ✅LinkeraiTTS(灵犀流式) | 👍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） |
 
@@ -246,8 +241,9 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 | 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 |
+| 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，具备记忆总结功能 |
+| 知识库 | 支持RAGFlow知识库，让大模型判断需要调度知识库后再回答 |
 | 工具调用 | 支持客户端IOT协议、客户MCP协议、服务端MCP协议、MCP接入点协议、自定义工具函数 |
 | 指令下发 | 依托MQTT协议，支持从智控台将MCP指令下发到ESP32设备 |
 | 管理后台 | 提供Web管理界面，支持用户管理、系统配置和设备管理；界面支持中文简体、中文繁体、英文显示 |
@@ -264,7 +260,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 ---
 
 ## 产品生态 👬
-小智是一个生态，当你使用这个产品时，也可以看看其他在这个生态圈的[优秀项目](https://github.com/78/xiaozhi-esp32?tab=readme-ov-file#%E7%9B%B8%E5%85%B3%E5%BC%80%E6%BA%90%E9%A1%B9%E7%9B%AE)
+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)
 
 ---
 
@@ -273,7 +269,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 
 | 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 | - |
@@ -299,7 +295,7 @@ 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、阿里云流式TTS、CosyVoiceSiliconflow、TTS302AI、CozeCnTTS、GizwitsTTS、ACGNTTS、OpenAITTS、灵犀流式TTS、MinimaxTTS、火山双流式TTS | 灵犀流式TTS、EdgeTTS、CosyVoiceSiliconflow(部分) |
+| 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 |
 
 ---
@@ -317,7 +313,7 @@ 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、Doubao流式ASR、FunASRServer、TencentASR、AliyunASR、Aliyun流式ASR、百度ASR、OpenAI ASR | 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 |
 
 ---
 
@@ -349,6 +345,14 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
 
 ---
 
+### 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     |
+
+---
+
 ## 鸣谢 🙏
 
 | Logo | 项目/公司 | 说明 |

README_de.md

@@ -0,0 +1,374 @@
+[![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="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) | 👍qwen2.5-vl-3b-instructh (Alibaba Bailian) |
+| TTS (Sprachsynthese) | ✅LinkeraiTTS (Lingxi-Streaming) | 👍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, 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?tab=readme-ov-file#related-open-source-projects) 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 | 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>

README_en.md

@@ -6,29 +6,24 @@
 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="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>
@@ -186,8 +181,8 @@ 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) | 
 
 
 > 💡 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.
@@ -213,10 +208,10 @@ 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) | 👍qwen2.5-vl-3b-instructh(Alibaba Bailian) |
+| TTS(Speech Synthesis) | ✅LinkeraiTTS(Lingxi streaming) | 👍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) |
 
@@ -244,6 +239,7 @@ This project provides the following testing tools to help you verify the system
 | 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 |
+| 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 |
 | Command Delivery | Supports MCP command delivery to ESP32 devices via MQTT protocol from Smart Console |
 | 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; Supports Simplified Chinese, Traditional Chinese and English display |
@@ -260,7 +256,7 @@ If you are a software developer, here is an [Open Letter to Developers](docs/con
 ---
 
 ## Product Ecosystem 👬
-Xiaozhi is an ecosystem. When using this product, you can also check out other [excellent projects](https://github.com/78/xiaozhi-esp32?tab=readme-ov-file#%E7%9B%B8%E5%85%B3%E5%BC%80%E6%BA%90%E9%A1%B9%E7%9B%AE) in this ecosystem
+Xiaozhi is an ecosystem. When using this product, you can also check out other [excellent projects](https://github.com/78/xiaozhi-esp32?tab=readme-ov-file#related-open-source-projects) in this ecosystem
 
 | Project Name | Project Address | Project Description |
 |:---------------------|:--------|:--------|
@@ -275,7 +271,7 @@ Xiaozhi is an ecosystem. When using this product, you can also check out other [
 
 | 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 | - |
@@ -299,7 +295,7 @@ 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, AliYun Stream TTS, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi Streaming TTS, MinimaxTTS | Lingxi Streaming TTS, EdgeTTS, CosyVoiceSiliconflow(partial) |
+| 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, MinimaxTTS | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS |
 
 ---
@@ -317,7 +313,7 @@ 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 |
 
 ---
 
@@ -347,6 +343,14 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
 
 ---
 
+### 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 |
+
+---
+
 ## Acknowledgments 🙏
 
 | Logo | Project/Company | Description |

README_vi.md

@@ -0,0 +1,375 @@
+[![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="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) | 👍qwen2.5-vl-3b-instructh(Alibaba Bailian) |
+| TTS(Tổng hợp giọng nói) | ✅LinkeraiTTS(Lingxi streaming) | 👍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, 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?tab=readme-ov-file#related-open-source-projects) 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 | 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>

docs/Deployment.md

@@ -80,7 +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。
@@ -139,6 +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。
@@ -267,7 +270,8 @@ LLM:
 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、[如何与Nginx集成](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)<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/>
@@ -275,11 +279,13 @@ LLM:
 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/>
-10、[新闻插件源配置指南](./newsnow_plugin_config.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、[如何部署集成index-tts本地语音](./index-stream-integration.md)<br/>
-2、[如何部署集成fish-speech本地语音](./fish-speech-integration.md)<br/>
-3、[如何部署集成PaddleSpeech本地语音](./paddlespeech-deploy.md)<br/>
+1、[如何在智控台克隆音色](./huoshan-streamTTS-voice-cloning.md)<br/>
+2、[如何部署集成index-tts本地语音](./index-stream-integration.md)<br/>
+3、[如何部署集成fish-speech本地语音](./fish-speech-integration.md)<br/>
+4、[如何部署集成PaddleSpeech本地语音](./paddlespeech-deploy.md)<br/>
 ## 性能测试教程
 1、[各组件速度测试指南](./performance_tester.md)<br/>
 2、[定期公开测试结果](https://github.com/xinnan-tech/xiaozhi-performance-research)<br/>

docs/Deployment_all.md

@@ -355,6 +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。
@@ -468,7 +471,8 @@ ws://你电脑局域网的ip:8000/xiaozhi/v1/
 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、[如何与Nginx集成](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)<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/>
@@ -479,9 +483,10 @@ ws://你电脑局域网的ip:8000/xiaozhi/v1/
 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、[如何部署集成index-tts本地语音](./index-stream-integration.md)<br/>
-2、[如何部署集成fish-speech本地语音](./fish-speech-integration.md)<br/>
-3、[如何部署集成PaddleSpeech本地语音](./paddlespeech-deploy.md)<br/>
+1、[如何在智控台克隆音色](./huoshan-streamTTS-voice-cloning.md)<br/>
+2、[如何部署集成index-tts本地语音](./index-stream-integration.md)<br/>
+3、[如何部署集成fish-speech本地语音](./fish-speech-integration.md)<br/>
+4、[如何部署集成PaddleSpeech本地语音](./paddlespeech-deploy.md)<br/>
 ## 性能测试教程
 1、[各组件速度测试指南](./performance_tester.md)<br/>
 2、[定期公开测试结果](https://github.com/xinnan-tech/xiaozhi-performance-research)<br/>

docs/FAQ.md

@@ -38,10 +38,10 @@ conda install conda-forge::ffmpeg
 
 | 模块名称 | 入门全免费设置 | 流式配置 |
 |:---:|:---:|:---:|
-| ASR(语音识别) | FunASR(本地) | 👍FunASR(本地GPU模式) |
-| LLM(大模型) | ChatGLMLLM(智谱glm-4-flash) | 👍AliLLM(qwen3-235b-a22b-instruct-2507) 或 👍DoubaoLLM(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) | 👍qwen2.5-vl-3b-instructh(阿里百炼) |
+| TTS(语音合成) | ✅LinkeraiTTS(灵犀流式) | 👍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） |
 
@@ -62,30 +62,34 @@ VAD:
 ### 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/>
-2、[如何部署MQTT网关开启MQTT+UDP协议](./mqtt-gateway-integration.md)<br/>
-3、[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/>
-4、[如何与Nginx集成](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)<br/>
+3、[如何部署MQTT网关开启MQTT+UDP协议](./mqtt-gateway-integration.md)<br/>
+4、[如何自动拉取本项目最新代码自动编译和启动](./dev-ops-integration.md)<br/>
+5、[如何与Nginx集成](https://github.com/xinnan-tech/xiaozhi-esp32-server/issues/791)<br/>
 
-### 8、编译固件相关教程
+### 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、拓展相关教程
+### 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、[如何开启声纹识别](./voiceprint-integration.md)<br/>
-10、[新闻插件源配置指南](./newsnow_plugin_config.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/>
 
-### 9、语音克隆、本地语音部署相关教程
+### 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/>
 
-### 10、性能测试教程
+### 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/>
 

docs/context-provider-integration.md

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

docs/docker-build.md

@@ -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
 ```

docs/homeassistant-integration.md

@@ -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`。
 

docs/huoshan-streamTTS-voice-cloning.md

@@ -1,6 +1,6 @@
 # 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3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。
+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。
@@ -23,6 +23,8 @@
 
 ### 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”；
@@ -46,7 +48,7 @@
 
 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。
 
-## 第三阶段：使用阶段
+## 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。
 

docs/mcp-endpoint-enable.md

@@ -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。
 

docs/mcp-get-device-info.md

@@ -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`。

docs/mqtt-gateway-integration.md

@@ -11,12 +11,12 @@
 
 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
+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
+ws://你宿主机局域网IP:8000/xiaozhi/v1/?from=mqtt_gateway
 ```
 
 ## 重要提示
@@ -53,7 +53,7 @@ cp config/mqtt.json.example config/mqtt.json
 {
     "production": {
         "chat_servers": [
-            "ws://127.0.0.1:8000/xiaozhi/v1?from=mqtt_gateway"
+            "ws://127.0.0.1:8000/xiaozhi/v1/?from=mqtt_gateway"
         ]
     },
     "debug": false,
@@ -76,6 +76,7 @@ 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。
 
@@ -85,6 +86,13 @@ MQTT_SIGNATURE_KEY=test   # MQTT签名密钥
 - 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

docs/ota-upgrade-guide.md

@@ -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

docs/ragflow-integration.md

@@ -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。

docs/voiceprint-integration.md

@@ -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。

main/manager-api/src/main/java/xiaozhi/common/constant/Constant.java

@@ -141,6 +141,11 @@ public interface Constant {
      */
     String SERVER_MQTT_SECRET = "server.mqtt_signature_key";
 
+    /**
+     * WebSocket认证开关
+     */
+    String SERVER_AUTH_ENABLED = "server.auth.enabled";
+
     /**
      * 无记忆
      */
@@ -151,6 +156,11 @@ public interface Constant {
      */
     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
@@ -294,7 +304,7 @@ public interface Constant {
     /**
      * 版本号
      */
-    public static final String VERSION = "0.8.5";
+    public static final String VERSION = "0.8.11";
 
     /**
      * 无效固件URL

main/manager-api/src/main/java/xiaozhi/common/exception/ErrorCode.java

@@ -82,14 +82,6 @@ public interface ErrorCode {
     int DEVICE_ALREADY_ACTIVATED = 10063;
     // 默认模型删除错误
     int DEFAULT_MODEL_DELETE_ERROR = 10064;
-    // 设备相关错误码
-    int MAC_ADDRESS_ALREADY_EXISTS = 10090; // Mac地址已存在
-    // 模型相关错误码
-    int MODEL_PROVIDER_NOT_EXIST = 10091; // 供应器不存在
-    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
-
     // 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
@@ -127,6 +119,10 @@ public interface ErrorCode {
     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
@@ -198,4 +194,50 @@ public interface ErrorCode {
     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
+
 }

main/manager-api/src/main/java/xiaozhi/common/handler/FieldMetaObjectHandler.java

@@ -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());

main/manager-api/src/main/java/xiaozhi/common/redis/RedisKeys.java

@@ -152,4 +152,18 @@ public class RedisKeys {
     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;
+    }
 }

main/manager-api/src/main/java/xiaozhi/common/utils/SensitiveDataUtils.java

@@ -1,14 +1,15 @@
 package xiaozhi.common.utils;
 
-import cn.hutool.json.JSONObject;
-import org.apache.commons.lang3.StringUtils;
-
 import java.util.Arrays;
+import java.util.HashMap;
 import java.util.HashSet;
 import java.util.Map;
-import java.util.HashMap;
 import java.util.Set;
 
+import org.apache.commons.lang3.StringUtils;
+
+import cn.hutool.json.JSONObject;
+
 /**
  * 敏感数据处理工具类
  */
@@ -30,7 +31,7 @@ public class SensitiveDataUtils {
      * 隐藏字符串中间部分
      */
     public static String maskMiddle(String value) {
-        if (StringUtils.isBlank(value)) {
+        if (StringUtils.isBlank(value) || value.length() == 1) {
             return value;
         }
 

main/manager-api/src/main/java/xiaozhi/modules/agent/controller/AgentChatHistoryController.java

@@ -139,14 +139,14 @@ public class AgentChatHistoryController {
         // 从Redis获取agentId和sessionId
         String agentSessionInfo = (String) redisUtils.get(RedisKeys.getChatHistoryKey(uuid));
         if (StringUtils.isBlank(agentSessionInfo)) {
-            throw new RenException("下载链接已过期或无效");
+            throw new RenException(ErrorCode.DOWNLOAD_LINK_EXPIRED);
         }
 
         try {
             // 解析agentId和sessionId
             String[] parts = agentSessionInfo.split(":");
             if (parts.length != 2) {
-                throw new RenException("下载链接无效");
+                throw new RenException(ErrorCode.DOWNLOAD_LINK_INVALID);
             }
             String agentId = parts[0];
             String sessionId = parts[1];

main/manager-api/src/main/java/xiaozhi/modules/agent/controller/AgentController.java

@@ -44,6 +44,8 @@ import xiaozhi.modules.agent.entity.AgentEntity;
 import xiaozhi.modules.agent.entity.AgentTemplateEntity;
 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;
@@ -64,6 +66,8 @@ 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;
 
     @GetMapping("/list")
@@ -117,6 +121,27 @@ 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());
+        }
+    }
+
     @PutMapping("/{id}")
     @Operation(summary = "更新智能体")
     @RequiresPermissions("sys:role:normal")
@@ -135,6 +160,8 @@ 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 +209,7 @@ 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")

main/manager-api/src/main/java/xiaozhi/modules/agent/dao/AgentContextProviderDao.java

@@ -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> {
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/dao/AiAgentChatHistoryDao.java

@@ -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);
 }

main/manager-api/src/main/java/xiaozhi/modules/agent/dto/AgentChatSummaryDTO.java

@@ -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;
+    }
+
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/dto/AgentUpdateDTO.java

@@ -69,6 +69,9 @@ 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 {

main/manager-api/src/main/java/xiaozhi/modules/agent/dto/ContextProviderDTO.java

@@ -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;
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/entity/AgentContextProviderEntity.java

@@ -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;
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/service/AgentChatSummaryService.java

@@ -0,0 +1,15 @@
+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);
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/service/AgentContextProviderService.java

@@ -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);
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/service/biz/impl/AgentChatHistoryBizServiceImpl.java

@@ -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() * 1000
+                : 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)

main/manager-api/src/main/java/xiaozhi/modules/agent/service/impl/AgentChatHistoryServiceImpl.java

@@ -84,7 +84,16 @@ 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 (audioIds != null && !audioIds.isEmpty()) {
+                int batchSize = 1000; // 每批删除1000条
+                for (int i = 0; i < audioIds.size(); i += batchSize) {
+                    int end = Math.min(i + batchSize, audioIds.size());
+                    List<String> batch = audioIds.subList(i, end);
+                    baseMapper.deleteAudioByIds(batch);
+                }
+            }
         }
         if (deleteAudio && !deleteText) {
             baseMapper.deleteAudioIdByAgentId(agentId);
@@ -107,7 +116,7 @@ public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryD
                 // 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); 
+                .orderByDesc(AgentChatHistoryEntity::getId);
 
         // 构建分页查询，查询前50页数据
         Page<AgentChatHistoryEntity> pageParam = new Page<>(0, 50);

main/manager-api/src/main/java/xiaozhi/modules/agent/service/impl/AgentChatSummaryServiceImpl.java

@@ -0,0 +1,423 @@
+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.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.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 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);
+
+            System.out.println("成功生成会话 " + sessionId + " 的聊天记录总结，长度: " + summary.length() + " 字符");
+            return new AgentChatSummaryDTO(sessionId, agentId, summary);
+
+        } catch (Exception e) {
+            System.err.println("生成会话 " + sessionId + " 的聊天记录总结时发生错误: " + e.getMessage());
+            return new AgentChatSummaryDTO(sessionId, "生成总结时发生错误: " + e.getMessage());
+        }
+    }
+
+    @Override
+    public boolean generateAndSaveChatSummary(String sessionId) {
+        try {
+            // 1. 生成总结
+            AgentChatSummaryDTO summaryDTO = generateChatSummary(sessionId);
+            if (!summaryDTO.isSuccess()) {
+                System.err.println("生成总结失败: " + summaryDTO.getErrorMessage());
+                return false;
+            }
+
+            // 2. 获取设备信息（通过会话关联的设备）
+            DeviceEntity device = getDeviceBySessionId(sessionId);
+            if (device == null) {
+                System.err.println("未找到与会话 " + sessionId + " 关联的设备");
+                return false;
+            }
+
+            // 3. 更新智能体记忆
+            AgentMemoryDTO memoryDTO = new AgentMemoryDTO();
+            memoryDTO.setSummaryMemory(summaryDTO.getSummary());
+
+            // 调用现有接口更新记忆
+            agentService.updateAgentById(device.getAgentId(),
+                    new AgentUpdateDTO() {
+                        {
+                            setSummaryMemory(summaryDTO.getSummary());
+                        }
+                    });
+
+            System.out.println("成功保存会话 " + sessionId + " 的聊天记录总结到智能体 " + device.getAgentId());
+            return true;
+
+        } catch (Exception e) {
+            System.err.println("保存会话 " + sessionId + " 的聊天记录总结时发生错误: " + e.getMessage());
+            return false;
+        }
+    }
+
+    /**
+     * 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) {
+            System.err.println("获取会话 " + sessionId + " 的聊天记录失败: " + 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) {
+            System.err.println("根据会话ID " + sessionId + " 查找智能体ID失败: " + 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) {
+            System.err.println("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) {
+            System.err.println("获取智能体历史记忆失败，agentId: " + agentId + ", 错误: " + 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 {
+            // 获取智能体配置，从中提取记忆总结的模型ID
+            String modelId = getMemorySummaryModelId(agentId);
+
+            if (StringUtils.isBlank(modelId)) {
+                System.out.println("未找到记忆总结的LLM模型配置，使用默认LLM服务");
+                return llmService.generateSummaryWithHistory(conversation, historyMemory, null, null);
+            }
+
+            // 使用指定的模型ID调用LLM服务（支持历史记忆合并）
+            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) {
+            System.err.println("调用Java端LLM服务异常，agentId: " + agentId + ", 错误: " + 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 {
+            // 获取智能体配置，从中提取记忆总结的模型ID
+            String modelId = getMemorySummaryModelId(agentId);
+
+            if (StringUtils.isBlank(modelId)) {
+                System.out.println("未找到记忆总结的LLM模型配置，使用默认LLM服务");
+                return llmService.generateSummary(conversation);
+            }
+
+            // 使用指定的模型ID调用LLM服务
+            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) {
+            System.err.println("调用Java端LLM服务异常，agentId: " + agentId + ", 错误: " + 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) {
+            System.err.println("获取记忆总结LLM模型ID失败，agentId: " + agentId + ", 错误: " + 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) {
+            System.err.println("根据会话ID " + sessionId + " 查找设备信息失败: " + e.getMessage());
+            return null;
+        }
+    }
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/service/impl/AgentContextProviderServiceImpl.java

@@ -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));
+    }
+}

main/manager-api/src/main/java/xiaozhi/modules/agent/service/impl/AgentPluginMappingServiceImpl.java

@@ -1,16 +1,26 @@
 package xiaozhi.modules.agent.service.impl;
 
+import java.util.ArrayList;
+import java.util.HashMap;
 import java.util.List;
+import java.util.Map;
 
+import org.apache.commons.lang3.StringUtils;
 import org.springframework.stereotype.Service;
 
 import com.baomidou.mybatisplus.core.conditions.update.UpdateWrapper;
 import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
 
 import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import xiaozhi.common.utils.JsonUtils;
 import xiaozhi.modules.agent.dao.AgentPluginMappingMapper;
 import xiaozhi.modules.agent.entity.AgentPluginMapping;
 import xiaozhi.modules.agent.service.AgentPluginMappingService;
+import xiaozhi.modules.knowledge.entity.KnowledgeBaseEntity;
+import xiaozhi.modules.knowledge.service.KnowledgeBaseService;
+import xiaozhi.modules.model.entity.ModelConfigEntity;
+import xiaozhi.modules.model.service.ModelConfigService;
 
 /**
  * @description 针对表【ai_agent_plugin_mapping(Agent与插件的唯一映射表)】的数据库操作Service实现
@@ -18,13 +28,73 @@ import xiaozhi.modules.agent.service.AgentPluginMappingService;
  */
 @Service
 @RequiredArgsConstructor
+@Slf4j
 public class AgentPluginMappingServiceImpl extends ServiceImpl<AgentPluginMappingMapper, AgentPluginMapping>
         implements AgentPluginMappingService {
     private final AgentPluginMappingMapper agentPluginMappingMapper;
+    private final KnowledgeBaseService knowledgeBaseService;
+    private final ModelConfigService modelConfigService;
 
     @Override
     public List<AgentPluginMapping> agentPluginParamsByAgentId(String agentId) {
-        return agentPluginMappingMapper.selectPluginsByAgentId(agentId);
+        List<AgentPluginMapping> list = agentPluginMappingMapper.selectPluginsByAgentId(agentId);
+        Map<String, List<KnowledgeBaseEntity>> knowledgeBaseMap = new HashMap<>();
+        Map<String, ModelConfigEntity> modelConfigMap = new HashMap<>();
+        for (int i = list.size() - 1; i >= 0; i--) {
+            AgentPluginMapping mapping = list.get(i);
+            if (StringUtils.isBlank(mapping.getProviderCode())) {
+                // 查询知识库插件参数
+                KnowledgeBaseEntity knowledgeBaseEntity = knowledgeBaseService.selectById(mapping.getPluginId());
+                if (knowledgeBaseEntity == null) {
+                    list.remove(i);
+                    continue;
+                }
+                ModelConfigEntity modelConfigEntity = modelConfigService
+                        .getModelByIdFromCache(knowledgeBaseEntity.getRagModelId());
+                if (modelConfigEntity == null) {
+                    list.remove(i);
+                    continue;
+                }
+                List<KnowledgeBaseEntity> knowledgeBaseList = knowledgeBaseMap.get(modelConfigEntity.getModelCode());
+                if (knowledgeBaseList == null) {
+                    knowledgeBaseList = new ArrayList<>();
+                }
+                modelConfigMap.put(modelConfigEntity.getModelCode(), modelConfigEntity);
+                knowledgeBaseList.add(knowledgeBaseEntity);
+                knowledgeBaseMap.put(modelConfigEntity.getModelCode(), knowledgeBaseList);
+                list.remove(i);
+            }
+        }
+        if (knowledgeBaseMap.size() > 0) {
+            for (String pluginCode : knowledgeBaseMap.keySet()) {
+                List<KnowledgeBaseEntity> knowledgeBaseList = knowledgeBaseMap.get(pluginCode);
+                if (knowledgeBaseList == null || knowledgeBaseList.isEmpty()) {
+                    continue;
+                }
+
+                AgentPluginMapping agentPluginMapping = new AgentPluginMapping();
+                agentPluginMapping.setAgentId(agentId);
+                agentPluginMapping.setPluginId(pluginCode);
+                agentPluginMapping.setProviderCode("search_from_" + pluginCode);
+                agentPluginMapping.setId(Long.valueOf(list.size() + 1));
+
+                Map<String, Object> paramInfo = new HashMap<>(4);
+                ModelConfigEntity modelConfigEntity = modelConfigMap.get(pluginCode);
+                paramInfo.put("base_url", modelConfigEntity.getConfigJson().getStr("base_url"));
+                paramInfo.put("api_key", modelConfigEntity.getConfigJson().getStr("api_key"));
+                paramInfo.put("dataset_ids",
+                        knowledgeBaseList.stream().map(KnowledgeBaseEntity::getDatasetId).toList());
+
+                String description = "如果用户询问与【"
+                        + String.join(",", knowledgeBaseList.stream().map(KnowledgeBaseEntity::getName).toList())
+                        + "】涵盖的主体范围相关内容时应调用本方法，用于查询：" + String.join(",",
+                                knowledgeBaseList.stream().map(KnowledgeBaseEntity::getDescription).toList());
+                paramInfo.put("description", description);
+                agentPluginMapping.setParamInfo(JsonUtils.toJsonString(paramInfo));
+                list.add(agentPluginMapping);
+            }
+        }
+        return list;
     }
 
     @Override

main/manager-api/src/main/java/xiaozhi/modules/agent/service/impl/AgentServiceImpl.java

@@ -32,10 +32,12 @@ import xiaozhi.modules.agent.dao.AgentDao;
 import xiaozhi.modules.agent.dto.AgentCreateDTO;
 import xiaozhi.modules.agent.dto.AgentDTO;
 import xiaozhi.modules.agent.dto.AgentUpdateDTO;
+import xiaozhi.modules.agent.entity.AgentContextProviderEntity;
 import xiaozhi.modules.agent.entity.AgentEntity;
 import xiaozhi.modules.agent.entity.AgentPluginMapping;
 import xiaozhi.modules.agent.entity.AgentTemplateEntity;
 import xiaozhi.modules.agent.service.AgentChatHistoryService;
+import xiaozhi.modules.agent.service.AgentContextProviderService;
 import xiaozhi.modules.agent.service.AgentPluginMappingService;
 import xiaozhi.modules.agent.service.AgentService;
 import xiaozhi.modules.agent.service.AgentTemplateService;
@@ -62,6 +64,7 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
     private final AgentChatHistoryService agentChatHistoryService;
     private final AgentTemplateService agentTemplateService;
     private final ModelProviderService modelProviderService;
+    private final AgentContextProviderService agentContextProviderService;
 
     @Override
     public PageData<AgentEntity> adminAgentList(Map<String, Object> params) {
@@ -85,6 +88,13 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
                 agent.setChatHistoryConf(Constant.ChatHistoryConfEnum.RECORD_TEXT_AUDIO.getCode());
             }
         }
+        
+        // 查询上下文源配置
+        AgentContextProviderEntity contextProviderEntity = agentContextProviderService.getByAgentId(id);
+        if (contextProviderEntity != null) {
+            agent.setContextProviders(contextProviderEntity.getContextProviders());
+        }
+        
         // 无需额外查询插件列表，已通过SQL查询出来
         return agent;
     }
@@ -331,6 +341,14 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
             agentChatHistoryService.deleteByAgentId(existingEntity.getId(), true, false);
         }
 
+        // 更新上下文源配置
+        if (dto.getContextProviders() != null) {
+            AgentContextProviderEntity contextEntity = new AgentContextProviderEntity();
+            contextEntity.setAgentId(agentId);
+            contextEntity.setContextProviders(dto.getContextProviders());
+            agentContextProviderService.saveOrUpdateByAgentId(contextEntity);
+        }
+
         boolean b = validateLLMIntentParams(dto.getLlmModelId(), dto.getIntentModelId());
         if (!b) {
             throw new RenException(ErrorCode.LLM_INTENT_PARAMS_MISMATCH);
@@ -395,7 +413,20 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
             entity.setIntentModelId(template.getIntentModelId());
             entity.setSystemPrompt(template.getSystemPrompt());
             entity.setSummaryMemory(template.getSummaryMemory());
-            entity.setChatHistoryConf(template.getChatHistoryConf());
+
+            // 根据记忆模型类型设置默认的chatHistoryConf值
+            if (template.getMemModelId() != null) {
+                if (template.getMemModelId().equals("Memory_nomem")) {
+                    // 无记忆功能的模型，默认不记录聊天记录
+                    entity.setChatHistoryConf(0);
+                } else {
+                    // 有记忆功能的模型，默认记录文本和语音
+                    entity.setChatHistoryConf(2);
+                }
+            } else {
+                entity.setChatHistoryConf(template.getChatHistoryConf());
+            }
+
             entity.setLangCode(template.getLangCode());
             entity.setLanguage(template.getLanguage());
         }

main/manager-api/src/main/java/xiaozhi/modules/agent/service/impl/AgentTemplateServiceImpl.java

@@ -45,6 +45,10 @@ public class AgentTemplateServiceImpl extends ServiceImpl<AgentTemplateDao, Agen
     @Override
     public void updateDefaultTemplateModelId(String modelType, String modelId) {
         modelType = modelType.toUpperCase();
+        // 如果是rag模型，不需要更新
+        if (modelType.equals("RAG")) {
+            return;
+        }
 
         UpdateWrapper<AgentTemplateEntity> wrapper = new UpdateWrapper<>();
         switch (modelType) {

main/manager-api/src/main/java/xiaozhi/modules/agent/vo/AgentInfoVO.java

@@ -5,6 +5,7 @@ import com.baomidou.mybatisplus.extension.handlers.JacksonTypeHandler;
 import io.swagger.v3.oas.annotations.media.Schema;
 import lombok.Data;
 import lombok.EqualsAndHashCode;
+import xiaozhi.modules.agent.dto.ContextProviderDTO;
 import xiaozhi.modules.agent.entity.AgentEntity;
 import xiaozhi.modules.agent.entity.AgentPluginMapping;
 
@@ -21,4 +22,7 @@ public class AgentInfoVO extends AgentEntity
     @Schema(description = "插件列表Id")
     @TableField(typeHandler = JacksonTypeHandler.class)
     private List<AgentPluginMapping> functions;
+
+    @Schema(description = "上下文源配置")
+    private List<ContextProviderDTO> contextProviders;
 }

main/manager-api/src/main/java/xiaozhi/modules/config/service/impl/ConfigServiceImpl.java

@@ -20,10 +20,12 @@ import xiaozhi.common.redis.RedisUtils;
 import xiaozhi.common.utils.ConvertUtils;
 import xiaozhi.common.utils.JsonUtils;
 import xiaozhi.modules.agent.dao.AgentVoicePrintDao;
+import xiaozhi.modules.agent.entity.AgentContextProviderEntity;
 import xiaozhi.modules.agent.entity.AgentEntity;
 import xiaozhi.modules.agent.entity.AgentPluginMapping;
 import xiaozhi.modules.agent.entity.AgentTemplateEntity;
 import xiaozhi.modules.agent.entity.AgentVoicePrintEntity;
+import xiaozhi.modules.agent.service.AgentContextProviderService;
 import xiaozhi.modules.agent.service.AgentMcpAccessPointService;
 import xiaozhi.modules.agent.service.AgentPluginMappingService;
 import xiaozhi.modules.agent.service.AgentService;
@@ -53,6 +55,7 @@ public class ConfigServiceImpl implements ConfigService {
     private final TimbreService timbreService;
     private final AgentPluginMappingService agentPluginMappingService;
     private final AgentMcpAccessPointService agentMcpAccessPointService;
+    private final AgentContextProviderService agentContextProviderService;
     private final VoiceCloneService cloneVoiceService;
     private final AgentVoicePrintDao agentVoicePrintDao;
 
@@ -73,7 +76,7 @@ public class ConfigServiceImpl implements ConfigService {
         // 查询默认智能体
         AgentTemplateEntity agent = agentTemplateService.getDefaultTemplate();
         if (agent == null) {
-            throw new RenException("默认智能体未找到");
+            throw new RenException(ErrorCode.AGENT_TEMPLATE_NOT_FOUND);
         }
 
         // 构建模块配置
@@ -91,6 +94,7 @@ public class ConfigServiceImpl implements ConfigService {
                 null,
                 null,
                 null,
+                null,
                 result,
                 isCache);
 
@@ -102,6 +106,15 @@ public class ConfigServiceImpl implements ConfigService {
 
     @Override
     public Map<String, Object> getAgentModels(String macAddress, Map<String, String> selectedModule) {
+        // 检查是否为管理控制台请求
+        String redisKey = RedisKeys.getTmpRegisterMacKey(macAddress);
+        Object isAdminRequest = redisUtils.get(redisKey);
+        
+        if (isAdminRequest != null && "true".equals(isAdminRequest)) {
+            // 管理控制台请求，返回getConfig的结果
+            redisUtils.delete(redisKey); // 使用后清理
+            return (Map<String, Object>) getConfig(true);
+        }
         // 根据MAC地址查找设备
         DeviceEntity device = deviceService.getDeviceByMacAddress(macAddress);
         if (device == null) {
@@ -110,13 +123,13 @@ public class ConfigServiceImpl implements ConfigService {
             if (StringUtils.isNotBlank(cachedCode)) {
                 throw new RenException(ErrorCode.OTA_DEVICE_NEED_BIND, cachedCode);
             }
-            throw new RenException(ErrorCode.OTA_DEVICE_NOT_FOUND, "not found device");
+            throw new RenException(ErrorCode.OTA_DEVICE_NOT_FOUND);
         }
 
         // 获取智能体信息
         AgentEntity agent = agentService.getAgentById(device.getAgentId());
         if (agent == null) {
-            throw new RenException("智能体未找到");
+            throw new RenException(ErrorCode.AGENT_NOT_FOUND);
         }
         // 获取音色信息
         String voice = null;
@@ -177,6 +190,13 @@ public class ConfigServiceImpl implements ConfigService {
             mcpEndpoint = mcpEndpoint.replace("/mcp/", "/call/");
             result.put("mcp_endpoint", mcpEndpoint);
         }
+        
+        // 获取上下文源配置
+        AgentContextProviderEntity contextProviderEntity = agentContextProviderService.getByAgentId(agent.getId());
+        if (contextProviderEntity != null && contextProviderEntity.getContextProviders() != null && !contextProviderEntity.getContextProviders().isEmpty()) {
+            result.put("context_providers", contextProviderEntity.getContextProviders());
+        }
+
         // 获取声纹信息
         buildVoiceprintConfig(agent.getId(), result);
 
@@ -195,6 +215,7 @@ public class ConfigServiceImpl implements ConfigService {
                 agent.getTtsModelId(),
                 agent.getMemModelId(),
                 agent.getIntentModelId(),
+                null,
                 result,
                 true);
 
@@ -371,12 +392,14 @@ public class ConfigServiceImpl implements ConfigService {
             String ttsModelId,
             String memModelId,
             String intentModelId,
+            String ragModelId,
             Map<String, Object> result,
             boolean isCache) {
         Map<String, String> selectedModule = new HashMap<>();
 
-        String[] modelTypes = { "VAD", "ASR", "TTS", "Memory", "Intent", "LLM", "VLLM" };
-        String[] modelIds = { vadModelId, asrModelId, ttsModelId, memModelId, intentModelId, llmModelId, vllmModelId };
+        String[] modelTypes = { "VAD", "ASR", "TTS", "Memory", "Intent", "LLM", "VLLM", "RAG" };
+        String[] modelIds = { vadModelId, asrModelId, ttsModelId, memModelId, intentModelId, llmModelId, vllmModelId,
+                ragModelId };
         String intentLLMModelId = null;
         String memLocalShortLLMModelId = null;
 

main/manager-api/src/main/java/xiaozhi/modules/device/controller/DeviceController.java

@@ -69,13 +69,15 @@ public class DeviceController {
     public Result<String> registerDevice(@RequestBody DeviceRegisterDTO deviceRegisterDTO) {
         String macAddress = deviceRegisterDTO.getMacAddress();
         if (StringUtils.isBlank(macAddress)) {
-            return new Result<String>().error(ErrorCode.NOT_NULL, "mac地址不能为空");
+            return new Result<String>().error(ErrorCode.MCA_NOT_NULL);
         }
         // 生成六位验证码
-        String code = String.valueOf(Math.random()).substring(2, 8);
-        String key = RedisKeys.getDeviceCaptchaKey(code);
+        String code;
+        String key;
         String existsMac = null;
         do {
+            code = String.valueOf(Math.random()).substring(2, 8);
+            key = RedisKeys.getDeviceCaptchaKey(code);
             existsMac = (String) redisUtils.get(key);
         } while (StringUtils.isNotBlank(existsMac));
 
@@ -93,7 +95,7 @@ public class DeviceController {
     }
 
     @PostMapping("/bind/{agentId}")
-    @Operation(summary = "转发POST请求到MQTT网关")
+    @Operation(summary = "设备在线接口")
     @RequiresPermissions("sys:role:normal")
     public Result<String> forwardToMqttGateway(@PathVariable String agentId, @RequestBody String requestBody) {
         try {
@@ -208,63 +210,4 @@ public class DeviceController {
         deviceService.manualAddDevice(user.getId(), dto);
         return new Result<>();
     }
-
-    @PostMapping("/commands/{deviceId}")
-    @Operation(summary = "发送设备指令")
-    @RequiresPermissions("sys:role:normal")
-    public Result<String> sendDeviceCommand(@PathVariable String deviceId, @RequestBody String command) {
-        try {
-            // 从系统参数中获取MQTT网关地址
-            String mqttGatewayUrl = sysParamsService.getValue("server.mqtt_manager_api", true);
-            if (StringUtils.isBlank(mqttGatewayUrl) || "null".equals(mqttGatewayUrl)) {
-                return new Result<String>().error("MQTT网关地址未配置");
-            }
-
-            // 构建完整的URL
-            // 获取设备信息以构建mqttClientId
-            DeviceEntity deviceById = deviceService.selectById(deviceId);
-
-            if (!deviceById.getUserId().equals(SecurityUser.getUser().getId())) {
-                return new Result<String>().error("设备不存在");
-            }
-            String macAddress = deviceById != null ? deviceById.getMacAddress() : "unknown";
-            String groupId = deviceById != null ? deviceById.getBoard() : null;
-            if (groupId == null) {
-                groupId = "GID_default";
-            }
-            groupId = groupId.replace(":", "_");
-            macAddress = macAddress.replace(":", "_");
-
-            // 拼接为groupId@@@macAddress@@@deviceId格式
-            String mqttClientId = groupId + "@@@" + macAddress + "@@@" + macAddress;
-
-            String url = "http://" + mqttGatewayUrl + "/api/commands/" + mqttClientId;
-
-            // 设置请求头
-            HttpHeaders headers = new HttpHeaders();
-            headers.set("Content-Type", "application/json");
-
-            // 生成Bearer令牌
-            String dateStr = java.time.LocalDate.now()
-                    .format(java.time.format.DateTimeFormatter.ofPattern("yyyy-MM-dd"));
-            String signatureKey = sysParamsService.getValue("server.mqtt_signature_key", false);
-            if (StringUtils.isBlank(signatureKey)) {
-                return new Result<String>().error("MQTT签名密钥未配置");
-            }
-            String tokenContent = dateStr + signatureKey;
-            String token = org.apache.commons.codec.digest.DigestUtils.sha256Hex(tokenContent);
-            headers.set("Authorization", "Bearer " + token);
-
-            // 构建请求体
-            HttpEntity<String> requestEntity = new HttpEntity<>(command, headers);
-
-            // 发送POST请求
-            ResponseEntity<String> response = restTemplate.exchange(url, HttpMethod.POST, requestEntity, String.class);
-
-            // 返回响应
-            return new Result<String>().ok(response.getBody());
-        } catch (Exception e) {
-            return new Result<String>().error("发送指令失败: " + e.getMessage());
-        }
-    }
 }

main/manager-api/src/main/java/xiaozhi/modules/device/service/DeviceService.java

@@ -98,4 +98,14 @@ public interface DeviceService extends BaseService<DeviceEntity> {
      */
     void updateDeviceConnectionInfo(String agentId, String deviceId, String appVersion);
 
+    /**
+     * 生成WebSocket认证token
+     *
+     * @param clientId 客户端ID
+     * @param username 用户名(通常为deviceId)
+     * @return 认证token字符串
+     * @throws Exception 生成token时的异常
+     */
+    String generateWebSocketToken(String clientId, String username) throws Exception;
+
 }

main/manager-api/src/main/java/xiaozhi/modules/device/service/impl/DeviceServiceImpl.java

@@ -1,6 +1,8 @@
 package xiaozhi.modules.device.service.impl;
 
 import java.nio.charset.StandardCharsets;
+import java.security.InvalidKeyException;
+import java.security.NoSuchAlgorithmException;
 import java.time.Instant;
 import java.util.Base64;
 import java.util.Date;
@@ -169,7 +171,22 @@ public class DeviceServiceImpl extends BaseServiceImpl<DeviceDao, DeviceEntity>
         DeviceReportRespDTO.Websocket websocket = new DeviceReportRespDTO.Websocket();
         // 从系统参数获取WebSocket URL，如果未配置则使用默认值
         String wsUrl = sysParamsService.getValue(Constant.SERVER_WEBSOCKET, true);
-        websocket.setToken("");
+
+        // 检查是否启用认证并生成token
+        String authEnabled = sysParamsService.getValue(Constant.SERVER_AUTH_ENABLED, true);
+        if ("true".equalsIgnoreCase(authEnabled)) {
+            try {
+                // 生成token
+                String token = generateWebSocketToken(clientId, macAddress);
+                websocket.setToken(token);
+            } catch (Exception e) {
+                log.error("生成WebSocket token失败: {}", e.getMessage());
+                websocket.setToken("");
+            }
+        } else {
+            websocket.setToken("");
+        }
+
         if (StringUtils.isBlank(wsUrl) || wsUrl.equals("null")) {
             log.error("WebSocket地址未配置，请登录智控台，在参数管理找到【server.websocket】配置");
             wsUrl = "ws://xiaozhi.server.com:8000/xiaozhi/v1/";
@@ -189,7 +206,7 @@ public class DeviceServiceImpl extends BaseServiceImpl<DeviceDao, DeviceEntity>
 
         // 添加MQTT UDP配置
         // 从系统参数获取MQTT Gateway地址，仅在配置有效时使用
-        String mqttUdpConfig = sysParamsService.getValue(Constant.SERVER_MQTT_GATEWAY, false);
+        String mqttUdpConfig = sysParamsService.getValue(Constant.SERVER_MQTT_GATEWAY, true);
         if (mqttUdpConfig != null && !mqttUdpConfig.equals("null") && !mqttUdpConfig.isEmpty()) {
             try {
                 String groupId = deviceById != null && deviceById.getBoard() != null ? deviceById.getBoard()
@@ -494,6 +511,40 @@ public class DeviceServiceImpl extends BaseServiceImpl<DeviceDao, DeviceEntity>
         return Base64.getEncoder().encodeToString(signature);
     }
 
+    /**
+     * 生成WebSocket认证token 遵循Python端AuthManager的实现逻辑：token = signature.timestamp
+     * 
+     * @param clientId 客户端ID
+     * @param username 用户名 (通常为deviceId/macAddress)
+     * @return 认证token字符串
+     */
+    public String generateWebSocketToken(String clientId, String username)
+            throws NoSuchAlgorithmException, InvalidKeyException {
+        // 从系统参数获取密钥
+        String secretKey = sysParamsService.getValue(Constant.SERVER_SECRET, false);
+        if (StringUtils.isBlank(secretKey)) {
+            throw new IllegalStateException("WebSocket认证密钥未配置(server.secret)");
+        }
+
+        // 获取当前时间戳(秒)
+        long timestamp = System.currentTimeMillis() / 1000;
+
+        // 构建签名内容: clientId|username|timestamp
+        String content = String.format("%s|%s|%d", clientId, username, timestamp);
+
+        // 生成HMAC-SHA256签名
+        Mac hmac = Mac.getInstance("HmacSHA256");
+        SecretKeySpec keySpec = new SecretKeySpec(secretKey.getBytes(StandardCharsets.UTF_8), "HmacSHA256");
+        hmac.init(keySpec);
+        byte[] signature = hmac.doFinal(content.getBytes(StandardCharsets.UTF_8));
+
+        // Base64 URL-safe编码签名(去除填充符=)
+        String signatureBase64 = Base64.getUrlEncoder().withoutPadding().encodeToString(signature);
+
+        // 返回格式: signature.timestamp
+        return String.format("%s.%d", signatureBase64, timestamp);
+    }
+
     /**
      * 构建MQTT配置信息
      * 
@@ -504,7 +555,7 @@ public class DeviceServiceImpl extends BaseServiceImpl<DeviceDao, DeviceEntity>
     private DeviceReportRespDTO.MQTT buildMqttConfig(String macAddress, String groupId)
             throws Exception {
         // 从环境变量或系统参数获取签名密钥
-        String signatureKey = sysParamsService.getValue("server.mqtt_signature_key", false);
+        String signatureKey = sysParamsService.getValue("server.mqtt_signature_key", true);
         if (StringUtils.isBlank(signatureKey)) {
             log.warn("缺少MQTT_SIGNATURE_KEY，跳过MQTT配置生成");
             return null;

main/manager-api/src/main/java/xiaozhi/modules/knowledge/config/KnowledgeBaseConfig.java

@@ -0,0 +1,22 @@
+package xiaozhi.modules.knowledge.config;
+
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import xiaozhi.modules.knowledge.rag.KnowledgeBaseAdapterFactory;
+
+/**
+ * 知识库配置类
+ * 配置知识库相关的Bean
+ */
+@Configuration
+public class KnowledgeBaseConfig {
+
+    /**
+     * 提供KnowledgeBaseAdapterFactory的Bean实例
+     * @return KnowledgeBaseAdapterFactory实例
+     */
+    @Bean
+    public KnowledgeBaseAdapterFactory knowledgeBaseAdapterFactory() {
+        return new KnowledgeBaseAdapterFactory();
+    }
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/controller/KnowledgeBaseController.java

@@ -0,0 +1,159 @@
+package xiaozhi.modules.knowledge.controller;
+
+import java.util.List;
+import java.util.Map;
+
+import org.apache.commons.lang3.StringUtils;
+import org.apache.shiro.authz.annotation.RequiresPermissions;
+import org.springframework.validation.annotation.Validated;
+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 io.swagger.v3.oas.annotations.Operation;
+import io.swagger.v3.oas.annotations.Parameter;
+import io.swagger.v3.oas.annotations.tags.Tag;
+import lombok.AllArgsConstructor;
+import xiaozhi.common.exception.ErrorCode;
+import xiaozhi.common.exception.RenException;
+import xiaozhi.common.page.PageData;
+import xiaozhi.common.utils.Result;
+import xiaozhi.modules.knowledge.dto.KnowledgeBaseDTO;
+import xiaozhi.modules.knowledge.service.KnowledgeBaseService;
+import xiaozhi.modules.security.user.SecurityUser;
+
+@AllArgsConstructor
+@RestController
+@RequestMapping("/datasets")
+@Tag(name = "知识库管理")
+public class KnowledgeBaseController {
+
+    private final KnowledgeBaseService knowledgeBaseService;
+
+    @GetMapping
+    @Operation(summary = "分页查询知识库列表")
+    @RequiresPermissions("sys:role:normal")
+    public Result<PageData<KnowledgeBaseDTO>> getPageList(
+            @RequestParam(required = false) String name,
+            @RequestParam(required = false, defaultValue = "1") Integer page,
+            @RequestParam(required = false, defaultValue = "10") Integer page_size) {
+        // 获取当前登录用户ID
+        Long currentUserId = SecurityUser.getUserId();
+
+        KnowledgeBaseDTO knowledgeBaseDTO = new KnowledgeBaseDTO();
+        knowledgeBaseDTO.setName(name);
+        knowledgeBaseDTO.setCreator(currentUserId); // 设置创建者ID，用于权限过滤
+
+        PageData<KnowledgeBaseDTO> pageData = knowledgeBaseService.getPageList(knowledgeBaseDTO, page, page_size);
+        return new Result<PageData<KnowledgeBaseDTO>>().ok(pageData);
+    }
+
+    @GetMapping("/{dataset_id}")
+    @Operation(summary = "根据知识库ID获取知识库详情")
+    @RequiresPermissions("sys:role:normal")
+    public Result<KnowledgeBaseDTO> getByDatasetId(@PathVariable("dataset_id") String datasetId) {
+        // 获取当前登录用户ID
+        Long currentUserId = SecurityUser.getUserId();
+
+        KnowledgeBaseDTO knowledgeBaseDTO = knowledgeBaseService.getByDatasetId(datasetId);
+
+        // 检查权限：用户只能查看自己创建的知识库
+        if (knowledgeBaseDTO.getCreator() == null || !knowledgeBaseDTO.getCreator().equals(currentUserId)) {
+            throw new RenException(ErrorCode.NO_PERMISSION);
+        }
+
+        return new Result<KnowledgeBaseDTO>().ok(knowledgeBaseDTO);
+    }
+
+    @PostMapping
+    @Operation(summary = "创建知识库")
+    @RequiresPermissions("sys:role:normal")
+    public Result<KnowledgeBaseDTO> save(@RequestBody @Validated KnowledgeBaseDTO knowledgeBaseDTO) {
+        KnowledgeBaseDTO resp = knowledgeBaseService.save(knowledgeBaseDTO);
+        return new Result<KnowledgeBaseDTO>().ok(resp);
+    }
+
+    @PutMapping("/{dataset_id}")
+    @Operation(summary = "更新知识库")
+    @RequiresPermissions("sys:role:normal")
+    public Result<KnowledgeBaseDTO> update(@PathVariable("dataset_id") String datasetId,
+            @RequestBody @Validated KnowledgeBaseDTO knowledgeBaseDTO) {
+        // 获取当前登录用户ID
+        Long currentUserId = SecurityUser.getUserId();
+
+        // 先获取现有知识库信息以检查权限
+        KnowledgeBaseDTO existingKnowledgeBase = knowledgeBaseService.getByDatasetId(datasetId);
+
+        // 检查权限：用户只能更新自己创建的知识库
+        if (existingKnowledgeBase.getCreator() == null || !existingKnowledgeBase.getCreator().equals(currentUserId)) {
+            throw new RenException(ErrorCode.NO_PERMISSION);
+        }
+
+        knowledgeBaseDTO.setDatasetId(datasetId);
+        KnowledgeBaseDTO resp = knowledgeBaseService.update(knowledgeBaseDTO);
+        return new Result<KnowledgeBaseDTO>().ok(resp);
+    }
+
+    @DeleteMapping("/{dataset_id}")
+    @Operation(summary = "删除单个知识库")
+    @Parameter(name = "dataset_id", description = "知识库ID", required = true)
+    @RequiresPermissions("sys:role:normal")
+    public Result<Void> delete(@PathVariable("dataset_id") String datasetId) {
+        // 获取当前登录用户ID
+        Long currentUserId = SecurityUser.getUserId();
+
+        // 先获取现有知识库信息以检查权限
+        KnowledgeBaseDTO existingKnowledgeBase = knowledgeBaseService.getByDatasetId(datasetId);
+
+        // 检查权限：用户只能删除自己创建的知识库
+        if (existingKnowledgeBase.getCreator() == null || !existingKnowledgeBase.getCreator().equals(currentUserId)) {
+            throw new RenException(ErrorCode.NO_PERMISSION);
+        }
+
+        knowledgeBaseService.deleteByDatasetId(datasetId);
+        return new Result<>();
+    }
+
+    @DeleteMapping("/batch")
+    @Operation(summary = "批量删除知识库")
+    @Parameter(name = "ids", description = "知识库ID列表，用逗号分隔", required = true)
+    @RequiresPermissions("sys:role:normal")
+    public Result<Void> deleteBatch(@RequestParam("ids") String ids) {
+        if (StringUtils.isBlank(ids)) {
+            throw new RenException(ErrorCode.PARAMS_GET_ERROR);
+        }
+
+        // 获取当前登录用户ID
+        Long currentUserId = SecurityUser.getUserId();
+        String[] idArray = ids.split(",");
+        for (String datasetId : idArray) {
+            if (StringUtils.isNotBlank(datasetId)) {
+                // 先获取现有知识库信息以检查权限
+                KnowledgeBaseDTO existingKnowledgeBase = knowledgeBaseService.getByDatasetId(datasetId.trim());
+
+                // 检查权限：用户只能删除自己创建的知识库
+                if (existingKnowledgeBase.getCreator() == null
+                        || !existingKnowledgeBase.getCreator().equals(currentUserId)) {
+                    throw new RenException(ErrorCode.NO_PERMISSION);
+                }
+
+                knowledgeBaseService.deleteByDatasetId(datasetId.trim());
+            }
+        }
+        return new Result<>();
+    }
+
+    @GetMapping("/rag-models")
+    @Operation(summary = "获取RAG模型列表")
+    @RequiresPermissions("sys:role:normal")
+    public Result<List<Map<String, Object>>> getRAGModels() {
+        List<Map<String, Object>> result = knowledgeBaseService.getRAGModels();
+        return new Result<List<Map<String, Object>>>().ok(result);
+    }
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/controller/KnowledgeFilesController.java

@@ -0,0 +1,224 @@
+package xiaozhi.modules.knowledge.controller;
+
+import java.util.List;
+import java.util.Map;
+
+import org.apache.shiro.authz.annotation.RequiresPermissions;
+import org.springframework.web.bind.annotation.*;
+import org.springframework.web.multipart.MultipartFile;
+
+import com.fasterxml.jackson.core.type.TypeReference;
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import io.swagger.v3.oas.annotations.Operation;
+import io.swagger.v3.oas.annotations.Parameter;
+import io.swagger.v3.oas.annotations.tags.Tag;
+import lombok.AllArgsConstructor;
+import xiaozhi.common.exception.ErrorCode;
+import xiaozhi.common.exception.RenException;
+import xiaozhi.common.page.PageData;
+import xiaozhi.common.utils.Result;
+import xiaozhi.modules.knowledge.dto.KnowledgeBaseDTO;
+import xiaozhi.modules.knowledge.dto.KnowledgeFilesDTO;
+import xiaozhi.modules.knowledge.service.KnowledgeBaseService;
+import xiaozhi.modules.knowledge.service.KnowledgeFilesService;
+import xiaozhi.modules.security.user.SecurityUser;
+
+@AllArgsConstructor
+@RestController
+@RequestMapping("/datasets/{dataset_id}")
+@Tag(name = "知识库文档管理")
+public class KnowledgeFilesController {
+
+    private final KnowledgeFilesService knowledgeFilesService;
+    private final KnowledgeBaseService knowledgeBaseService;
+
+    /**
+     * 验证当前用户是否有权限操作指定知识库
+     * 
+     * @param datasetId 知识库ID
+     */
+    private void validateKnowledgeBasePermission(String datasetId) {
+        // 获取当前登录用户ID
+        Long currentUserId = SecurityUser.getUserId();
+
+        // 获取知识库信息
+        KnowledgeBaseDTO knowledgeBase = knowledgeBaseService.getByDatasetId(datasetId);
+
+        // 检查权限：用户只能操作自己创建的知识库
+        if (knowledgeBase.getCreator() == null || !knowledgeBase.getCreator().equals(currentUserId)) {
+            throw new RenException(ErrorCode.NO_PERMISSION);
+        }
+    }
+
+    @GetMapping("/documents")
+    @Operation(summary = "分页查询文档列表")
+    @RequiresPermissions("sys:role:normal")
+    public Result<PageData<KnowledgeFilesDTO>> getPageList(
+            @PathVariable("dataset_id") String datasetId,
+            @RequestParam(required = false) String name,
+            @RequestParam(required = false) Integer status,
+            @RequestParam(required = false, defaultValue = "1") Integer page,
+            @RequestParam(required = false, defaultValue = "10") Integer page_size) {
+        // 验证知识库权限
+        validateKnowledgeBasePermission(datasetId);
+
+        // 如果指定了状态参数，使用状态查询接口
+        if (status != null) {
+            PageData<KnowledgeFilesDTO> pageData = knowledgeFilesService.getPageListByStatus(datasetId, status, page, page_size);
+            return new Result<PageData<KnowledgeFilesDTO>>().ok(pageData);
+        }
+
+        // 否则使用通用查询接口
+        KnowledgeFilesDTO knowledgeFilesDTO = new KnowledgeFilesDTO();
+        knowledgeFilesDTO.setDatasetId(datasetId);
+        knowledgeFilesDTO.setName(name);
+        PageData<KnowledgeFilesDTO> pageData = knowledgeFilesService.getPageList(knowledgeFilesDTO, page, page_size);
+        return new Result<PageData<KnowledgeFilesDTO>>().ok(pageData);
+    }
+
+    @GetMapping("/documents/status/{status}")
+    @Operation(summary = "根据状态分页查询文档列表")
+    @RequiresPermissions("sys:role:normal")
+    public Result<PageData<KnowledgeFilesDTO>> getPageListByStatus(
+            @PathVariable("dataset_id") String datasetId,
+            @PathVariable("status") Integer status,
+            @RequestParam(required = false, defaultValue = "1") Integer page,
+            @RequestParam(required = false, defaultValue = "10") Integer page_size) {
+        // 验证知识库权限
+        validateKnowledgeBasePermission(datasetId);
+
+        PageData<KnowledgeFilesDTO> pageData = knowledgeFilesService.getPageListByStatus(datasetId, status, page, page_size);
+        return new Result<PageData<KnowledgeFilesDTO>>().ok(pageData);
+    }
+
+    @PostMapping("/documents")
+    @Operation(summary = "上传文档到知识库")
+    @RequiresPermissions("sys:role:normal")
+    public Result<KnowledgeFilesDTO> uploadDocument(
+            @PathVariable("dataset_id") String datasetId,
+            @RequestParam("file") MultipartFile file,
+            @RequestParam(required = false) String name,
+            @RequestParam(required = false) String chunkMethod,
+            @RequestParam(required = false) String metaFields,
+            @RequestParam(required = false) String parserConfig) {
+
+        // 验证知识库权限
+        validateKnowledgeBasePermission(datasetId);
+
+        KnowledgeFilesDTO resp = knowledgeFilesService.uploadDocument(datasetId, file, name,
+                metaFields != null ? parseJsonMap(metaFields) : null,
+                chunkMethod,
+                parserConfig != null ? parseJsonMap(parserConfig) : null);
+        return new Result<KnowledgeFilesDTO>().ok(resp);
+    }
+
+    @DeleteMapping("/documents/{document_id}")
+    @Operation(summary = "删除单个文档")
+    @Parameter(name = "document_id", description = "文档ID", required = true)
+    @RequiresPermissions("sys:role:normal")
+    public Result<Void> delete(@PathVariable("dataset_id") String datasetId,
+            @PathVariable("document_id") String documentId) {
+        // 验证知识库权限
+        validateKnowledgeBasePermission(datasetId);
+
+        knowledgeFilesService.deleteByDocumentId(documentId, datasetId);
+        return new Result<>();
+    }
+
+    @PostMapping("/chunks")
+    @Operation(summary = "解析文档（切块）")
+    @RequiresPermissions("sys:role:normal")
+    public Result<Void> parseDocuments(@PathVariable("dataset_id") String datasetId,
+            @RequestBody Map<String, List<String>> requestBody) {
+        // 验证知识库权限
+        validateKnowledgeBasePermission(datasetId);
+
+        List<String> documentIds = requestBody.get("document_ids");
+        if (documentIds == null || documentIds.isEmpty()) {
+            return new Result<Void>().error("document_ids参数不能为空");
+        }
+
+        boolean success = knowledgeFilesService.parseDocuments(datasetId, documentIds);
+        if (success) {
+            return new Result<Void>();
+        } else {
+            return new Result<Void>().error("文档解析失败，文档可能正在处理中");
+        }
+    }
+
+    @GetMapping("/documents/{document_id}/chunks")
+    @Operation(summary = "列出指定文档的切片")
+    @RequiresPermissions("sys:role:normal")
+    public Result<Map<String, Object>> listChunks(@PathVariable("dataset_id") String datasetId,
+            @PathVariable("document_id") String documentId,
+            @RequestParam(required = false) String keywords,
+            @RequestParam(required = false, defaultValue = "1") Integer page,
+            @RequestParam(required = false, defaultValue = "1024") Integer page_size,
+            @RequestParam(required = false) String id) {
+        // 验证知识库权限
+        validateKnowledgeBasePermission(datasetId);
+
+        Map<String, Object> result = knowledgeFilesService.listChunks(datasetId, documentId, keywords, page, page_size,
+                id);
+        return new Result<Map<String, Object>>().ok(result);
+    }
+
+    /**
+     * 召回测试
+     */
+    @PostMapping("/retrieval-test")
+    @Operation(summary = "召回测试")
+    @RequiresPermissions("sys:role:normal")
+    public Result<Map<String, Object>> retrievalTest(@PathVariable("dataset_id") String datasetId,
+            @RequestBody Map<String, Object> params) {
+        // 验证知识库权限
+        validateKnowledgeBasePermission(datasetId);
+
+        try {
+            // 提取参数
+            String question = (String) params.get("question");
+            if (question == null || question.trim().isEmpty()) {
+                return new Result<Map<String, Object>>().error("问题不能为空");
+            }
+
+            List<String> datasetIds = (List<String>) params.get("dataset_ids");
+            List<String> documentIds = (List<String>) params.get("document_ids");
+            Integer page = (Integer) params.get("page");
+            Integer pageSize = (Integer) params.get("page_size");
+            Float similarityThreshold = (Float) params.get("similarity_threshold");
+            Float vectorSimilarityWeight = (Float) params.get("vector_similarity_weight");
+            Integer topK = (Integer) params.get("top_k");
+            String rerankId = (String) params.get("rerank_id");
+            Boolean keyword = (Boolean) params.get("keyword");
+            Boolean highlight = (Boolean) params.get("highlight");
+            List<String> crossLanguages = (List<String>) params.get("cross_languages");
+            Map<String, Object> metadataCondition = (Map<String, Object>) params.get("metadata_condition");
+
+            // 如果未指定数据集ID，使用当前数据集
+            if (datasetIds == null || datasetIds.isEmpty()) {
+                datasetIds = java.util.Arrays.asList(datasetId);
+            }
+
+            Map<String, Object> result = knowledgeFilesService.retrievalTest(
+                    question, datasetIds, documentIds, page, pageSize, similarityThreshold,
+                    vectorSimilarityWeight, topK, rerankId, keyword, highlight, crossLanguages, metadataCondition);
+
+            return new Result<Map<String, Object>>().ok(result);
+        } catch (Exception e) {
+            return new Result<Map<String, Object>>().error("召回测试失败: " + e.getMessage());
+        }
+    }
+    /**
+     * 解析JSON字符串为Map对象
+     */
+    private Map<String, Object> parseJsonMap(String jsonString) {
+        try {
+            ObjectMapper objectMapper = new ObjectMapper();
+            return objectMapper.readValue(jsonString, new TypeReference<Map<String, Object>>() {
+            });
+        } catch (Exception e) {
+            throw new RuntimeException("解析JSON字符串失败: " + jsonString, e);
+        }
+    }
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/dao/KnowledgeBaseDao.java

@@ -0,0 +1,22 @@
+package xiaozhi.modules.knowledge.dao;
+
+import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
+
+import xiaozhi.common.dao.BaseDao;
+import xiaozhi.modules.knowledge.entity.KnowledgeBaseEntity;
+
+/**
+ * 知识库知识库
+ */
+@Mapper
+public interface KnowledgeBaseDao extends BaseDao<KnowledgeBaseEntity> {
+
+    /**
+     * 根据知识库ID删除相关的插件映射记录
+     * 
+     * @param knowledgeBaseId 知识库ID
+     */
+    void deletePluginMappingByKnowledgeBaseId(@Param("knowledgeBaseId") String knowledgeBaseId);
+
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/dto/KnowledgeBaseDTO.java

@@ -0,0 +1,49 @@
+package xiaozhi.modules.knowledge.dto;
+
+import java.io.Serial;
+import java.io.Serializable;
+import java.util.Date;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+@Data
+@Schema(description = "知识库知识库")
+public class KnowledgeBaseDTO implements Serializable {
+
+    @Serial
+    private static final long serialVersionUID = 1L;
+
+    @Schema(description = "唯一标识")
+    private String id;
+
+    @Schema(description = "知识库ID")
+    private String datasetId;
+
+    @Schema(description = "RAG模型配置ID")
+    private String ragModelId;
+
+    @Schema(description = "知识库名称")
+    private String name;
+
+    @Schema(description = "知识库描述")
+    private String description;
+
+    @Schema(description = "状态(0:禁用 1:启用)")
+    private Integer status;
+
+    @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 = "文档数量")
+    private Integer documentCount;
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/dto/KnowledgeFilesDTO.java

@@ -0,0 +1,96 @@
+package xiaozhi.modules.knowledge.dto;
+
+import java.io.Serial;
+import java.io.Serializable;
+import java.util.Date;
+import java.util.Map;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+@Data
+@Schema(description = "知识库文档")
+public class KnowledgeFilesDTO implements Serializable {
+
+    @Serial
+    private static final long serialVersionUID = 1L;
+    @Schema(description = "唯一标识")
+    private String id;
+
+    @Schema(description = "文档ID")
+    private String documentId;
+
+    @Schema(description = "知识库ID")
+    private String datasetId;
+
+    @Schema(description = "文档名称")
+    private String name;
+
+    @Schema(description = "文档类型")
+    private String fileType;
+
+    @Schema(description = "文件大小（字节）")
+    private Long fileSize;
+
+    @Schema(description = "文件路径")
+    private String filePath;
+
+    @Schema(description = "元数据字段")
+    private Map<String, Object> metaFields;
+
+    @Schema(description = "分块方法")
+    private String chunkMethod;
+
+    @Schema(description = "解析器配置")
+    private Map<String, Object> parserConfig;
+
+    @Schema(description = "状态")
+    private Integer status;
+
+    @Schema(description = "文档解析状态")
+    private String run;
+
+    @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;
+
+    // 文档解析状态常量定义
+    private static final Integer STATUS_UNSTART = 0;
+    private static final Integer STATUS_RUNNING = 1;
+    private static final Integer STATUS_CANCEL = 2;
+    private static final Integer STATUS_DONE = 3;
+    private static final Integer STATUS_FAIL = 4;
+
+    /**
+     * 获取文档解析状态码（基于run字段转换）
+     */
+    public Integer getParseStatusCode() {
+        if (run == null) {
+            return STATUS_UNSTART;
+        }
+
+        // RAGFlow根据run字段的值直接映射到对应的状态码
+        switch (run.toUpperCase()) {
+            case "RUNNING":
+                return STATUS_RUNNING;
+            case "CANCEL":
+                return STATUS_CANCEL;
+            case "DONE":
+                return STATUS_DONE;
+            case "FAIL":
+                return STATUS_FAIL;
+            case "UNSTART":
+            default:
+                return STATUS_UNSTART;
+        }
+    }
+
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/entity/KnowledgeBaseEntity.java

@@ -0,0 +1,53 @@
+package xiaozhi.modules.knowledge.entity;
+
+import java.util.Date;
+
+import com.baomidou.mybatisplus.annotation.FieldFill;
+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 io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+
+@Data
+@TableName(value = "ai_rag_dataset", autoResultMap = true)
+@Schema(description = "知识库知识库表")
+public class KnowledgeBaseEntity {
+
+    @TableId(type = IdType.ASSIGN_UUID)
+    @Schema(description = "唯一标识")
+    private String id;
+
+    @Schema(description = "知识库ID")
+    private String datasetId;
+
+    @Schema(description = "RAG模型配置ID")
+    private String ragModelId;
+
+    @Schema(description = "知识库名称")
+    private String name;
+
+    @Schema(description = "知识库描述")
+    private String description;
+
+    @Schema(description = "状态(0:禁用 1:启用)")
+    private Integer status;
+
+    @Schema(description = "创建者")
+    @TableField(fill = FieldFill.INSERT)
+    private Long creator;
+
+    @Schema(description = "创建时间")
+    @TableField(fill = FieldFill.INSERT)
+    private Date createdAt;
+
+    @Schema(description = "更新者")
+    @TableField(fill = FieldFill.UPDATE)
+    private Long updater;
+
+    @Schema(description = "更新时间")
+    @TableField(fill = FieldFill.UPDATE)
+    private Date updatedAt;
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/rag/KnowledgeBaseAdapter.java

@@ -0,0 +1,200 @@
+package xiaozhi.modules.knowledge.rag;
+
+import java.util.List;
+import java.util.Map;
+
+import org.springframework.web.multipart.MultipartFile;
+
+import xiaozhi.common.page.PageData;
+import xiaozhi.modules.knowledge.dto.KnowledgeFilesDTO;
+
+/**
+ * 知识库API适配器抽象基类
+ * 定义通用的知识库操作接口，支持多种后端API实现
+ */
+public abstract class KnowledgeBaseAdapter {
+
+        /**
+         * 获取适配器类型标识
+         * 
+         * @return 适配器类型（如：ragflow, milvus, pinecone等）
+         */
+        public abstract String getAdapterType();
+
+        /**
+         * 初始化适配器配置
+         * 
+         * @param config 配置参数
+         */
+        public abstract void initialize(Map<String, Object> config);
+
+        /**
+         * 验证配置是否有效
+         * 
+         * @param config 配置参数
+         * @return 验证结果
+         */
+        public abstract boolean validateConfig(Map<String, Object> config);
+
+        /**
+         * 分页查询文档列表
+         * 
+         * @param datasetId   知识库ID
+         * @param queryParams 查询参数
+         * @param page        页码
+         * @param limit       每页数量
+         * @return 分页数据
+         */
+        public abstract PageData<KnowledgeFilesDTO> getDocumentList(String datasetId,
+                        Map<String, Object> queryParams,
+                        Integer page,
+                        Integer limit);
+
+        /**
+         * 根据文档ID获取文档详情
+         * 
+         * @param datasetId 知识库ID
+         * @return 文档详情
+         */
+        public abstract KnowledgeFilesDTO getDocumentById(String datasetId, String documentId);
+
+        /**
+         * 上传文档到知识库
+         * 
+         * @param datasetId    知识库ID
+         * @param file         上传的文件
+         * @param name         文档名称
+         * @param metaFields   元数据字段
+         * @param chunkMethod  分块方法
+         * @param parserConfig 解析器配置
+         * @return 上传的文档信息
+         */
+        public abstract KnowledgeFilesDTO uploadDocument(String datasetId,
+                        MultipartFile file,
+                        String name,
+                        Map<String, Object> metaFields,
+                        String chunkMethod,
+                        Map<String, Object> parserConfig);
+
+        /**
+         * 根据状态分页查询文档列表
+         * 
+         * @param datasetId 知识库ID
+         * @param status    文档解析状态
+         * @param page      页码
+         * @param limit     每页数量
+         * @return 分页数据
+         */
+        public abstract PageData<KnowledgeFilesDTO> getDocumentListByStatus(String datasetId,
+                        Integer status,
+                        Integer page,
+                        Integer limit);
+
+        /**
+         * 删除文档
+         * 
+         * @param datasetId  知识库ID
+         * @param documentId 文档ID
+         */
+        public abstract void deleteDocument(String datasetId, String documentId);
+
+        /**
+         * 解析文档（切块）
+         * 
+         * @param datasetId   知识库ID
+         * @param documentIds 文档ID列表
+         * @return 解析结果
+         */
+        public abstract boolean parseDocuments(String datasetId, List<String> documentIds);
+
+        /**
+         * 列出指定文档的切片
+         * 
+         * @param datasetId  知识库ID
+         * @param documentId 文档ID
+         * @param keywords   关键词过滤
+         * @param page       页码
+         * @param pageSize   每页数量
+         * @param chunkId    切片ID
+         * @return 切片列表信息
+         */
+        public abstract Map<String, Object> listChunks(String datasetId,
+                        String documentId,
+                        String keywords,
+                        Integer page,
+                        Integer pageSize,
+                        String chunkId);
+
+        /**
+         * 召回测试 - 从知识库中检索相关切片
+         * 
+         * @param question        用户查询
+         * @param datasetIds      数据集ID列表
+         * @param documentIds     文档ID列表
+         * @param retrievalParams 检索参数
+         * @return 召回测试结果
+         */
+        public abstract Map<String, Object> retrievalTest(String question,
+                        List<String> datasetIds,
+                        List<String> documentIds,
+                        Map<String, Object> retrievalParams);
+
+        /**
+         * 测试连接
+         * 
+         * @return 连接测试结果
+         */
+        public abstract boolean testConnection();
+
+        /**
+         * 获取适配器状态信息
+         * 
+         * @return 状态信息
+         */
+        public abstract Map<String, Object> getStatus();
+
+        /**
+         * 获取支持的配置参数
+         * 
+         * @return 配置参数说明
+         */
+        public abstract Map<String, Object> getSupportedConfig();
+
+        /**
+         * 获取默认配置
+         * 
+         * @return 默认配置
+         */
+        public abstract Map<String, Object> getDefaultConfig();
+
+        /**
+         * 创建数据集
+         * 
+         * @param createParams 创建参数
+         * @return 数据集ID
+         */
+        public abstract String createDataset(Map<String, Object> createParams);
+
+        /**
+         * 更新数据集
+         * 
+         * @param datasetId    数据集ID
+         * @param updateParams 更新参数
+         */
+        public abstract void updateDataset(String datasetId, Map<String, Object> updateParams);
+
+        /**
+         * 删除数据集
+         * 
+         * @param datasetId 数据集ID
+         */
+        public abstract void deleteDataset(String datasetId);
+
+        /**
+         * 获取数据集的文档数量
+         * 
+         * @param datasetId 数据集ID
+         * @return 文档数量
+         */
+        public abstract Integer getDocumentCount(String datasetId);
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/rag/KnowledgeBaseAdapterFactory.java

@@ -0,0 +1,197 @@
+package xiaozhi.modules.knowledge.rag;
+
+import java.util.HashMap;
+import java.util.Map;
+import java.util.Set;
+import java.util.concurrent.ConcurrentHashMap;
+
+import lombok.extern.slf4j.Slf4j;
+import xiaozhi.common.exception.ErrorCode;
+import xiaozhi.common.exception.RenException;
+
+/**
+ * 知识库适配器工厂类
+ * 负责创建和管理不同类型的知识库API适配器
+ */
+@Slf4j
+public class KnowledgeBaseAdapterFactory {
+
+    // 注册的适配器类型映射
+    private static final Map<String, Class<? extends KnowledgeBaseAdapter>> adapterRegistry = new HashMap<>();
+
+    // 适配器实例缓存
+    private static final Map<String, KnowledgeBaseAdapter> adapterCache = new ConcurrentHashMap<>();
+
+    static {
+        // 注册内置适配器类型
+        registerAdapter("ragflow", xiaozhi.modules.knowledge.rag.impl.RAGFlowAdapter.class);
+        // 可以在这里注册更多适配器类型
+    }
+
+    /**
+     * 注册新的适配器类型
+     * 
+     * @param adapterType  适配器类型标识
+     * @param adapterClass 适配器类
+     */
+    public static void registerAdapter(String adapterType, Class<? extends KnowledgeBaseAdapter> adapterClass) {
+        if (adapterRegistry.containsKey(adapterType)) {
+            log.warn("适配器类型 '{}' 已存在，将被覆盖", adapterType);
+        }
+        adapterRegistry.put(adapterType, adapterClass);
+        log.info("注册适配器类型: {} -> {}", adapterType, adapterClass.getSimpleName());
+    }
+
+    /**
+     * 获取适配器实例
+     * 
+     * @param adapterType 适配器类型
+     * @param config      配置参数
+     * @return 适配器实例
+     */
+    public static KnowledgeBaseAdapter getAdapter(String adapterType, Map<String, Object> config) {
+        String cacheKey = buildCacheKey(adapterType, config);
+
+        // 检查缓存中是否已存在实例
+        if (adapterCache.containsKey(cacheKey)) {
+            log.debug("从缓存获取适配器实例: {}", cacheKey);
+            return adapterCache.get(cacheKey);
+        }
+
+        // 创建新的适配器实例
+        KnowledgeBaseAdapter adapter = createAdapter(adapterType, config);
+
+        // 缓存适配器实例
+        adapterCache.put(cacheKey, adapter);
+        log.info("创建并缓存适配器实例: {}", cacheKey);
+
+        return adapter;
+    }
+
+    /**
+     * 获取适配器实例（无配置）
+     * 
+     * @param adapterType 适配器类型
+     * @return 适配器实例
+     */
+    public static KnowledgeBaseAdapter getAdapter(String adapterType) {
+        return getAdapter(adapterType, null);
+    }
+
+    /**
+     * 获取所有已注册的适配器类型
+     * 
+     * @return 适配器类型集合
+     */
+    public static Set<String> getRegisteredAdapterTypes() {
+        return adapterRegistry.keySet();
+    }
+
+    /**
+     * 检查适配器类型是否已注册
+     * 
+     * @param adapterType 适配器类型
+     * @return 是否已注册
+     */
+    public static boolean isAdapterTypeRegistered(String adapterType) {
+        return adapterRegistry.containsKey(adapterType);
+    }
+
+    /**
+     * 清除适配器缓存
+     */
+    public static void clearCache() {
+        int cacheSize = adapterCache.size();
+        adapterCache.clear();
+        log.info("清除适配器缓存，共清除 {} 个实例", cacheSize);
+    }
+
+    /**
+     * 移除特定适配器类型的缓存
+     * 
+     * @param adapterType 适配器类型
+     */
+    public static void removeCacheByType(String adapterType) {
+        int removedCount = 0;
+        for (String cacheKey : adapterCache.keySet()) {
+            if (cacheKey.startsWith(adapterType + "@")) {
+                adapterCache.remove(cacheKey);
+                removedCount++;
+            }
+        }
+        log.info("移除适配器类型 '{}' 的缓存，共移除 {} 个实例", adapterType, removedCount);
+    }
+
+    /**
+     * 获取适配器工厂状态信息
+     * 
+     * @return 状态信息
+     */
+    public static Map<String, Object> getFactoryStatus() {
+        Map<String, Object> status = new HashMap<>();
+        status.put("registeredAdapterTypes", adapterRegistry.keySet());
+        status.put("cachedAdapterCount", adapterCache.size());
+        status.put("cacheKeys", adapterCache.keySet());
+        return status;
+    }
+
+    /**
+     * 创建适配器实例
+     * 
+     * @param adapterType 适配器类型
+     * @param config      配置参数
+     * @return 适配器实例
+     */
+    private static KnowledgeBaseAdapter createAdapter(String adapterType, Map<String, Object> config) {
+        if (!adapterRegistry.containsKey(adapterType)) {
+            throw new RenException(ErrorCode.RAG_ADAPTER_TYPE_NOT_SUPPORTED,
+                    "不支持的适配器类型: " + adapterType);
+        }
+
+        try {
+            Class<? extends KnowledgeBaseAdapter> adapterClass = adapterRegistry.get(adapterType);
+            KnowledgeBaseAdapter adapter = adapterClass.getDeclaredConstructor().newInstance();
+
+            // 初始化适配器
+            if (config != null) {
+                adapter.initialize(config);
+
+                // 验证配置
+                if (!adapter.validateConfig(config)) {
+                    throw new RenException(ErrorCode.RAG_CONFIG_VALIDATION_FAILED,
+                            "适配器配置验证失败: " + adapterType);
+                }
+            }
+
+            log.info("成功创建适配器实例: {}", adapterType);
+            return adapter;
+
+        } catch (Exception e) {
+            log.error("创建适配器实例失败: {}", adapterType, e);
+            throw new RenException(ErrorCode.RAG_ADAPTER_CREATION_FAILED,
+                    "创建适配器失败: " + adapterType + ", 错误: " + e.getMessage());
+        }
+    }
+
+    /**
+     * 构建缓存键
+     * 
+     * @param adapterType 适配器类型
+     * @param config      配置参数
+     * @return 缓存键
+     */
+    private static String buildCacheKey(String adapterType, Map<String, Object> config) {
+        if (config == null || config.isEmpty()) {
+            return adapterType + "@default";
+        }
+
+        // 基于配置参数生成缓存键
+        StringBuilder keyBuilder = new StringBuilder(adapterType + "@");
+
+        // 使用配置的哈希值作为缓存键的一部分
+        int configHash = config.hashCode();
+        keyBuilder.append(configHash);
+
+        return keyBuilder.toString();
+    }
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/service/KnowledgeBaseService.java

@@ -0,0 +1,87 @@
+package xiaozhi.modules.knowledge.service;
+
+import java.util.List;
+import java.util.Map;
+
+import xiaozhi.common.page.PageData;
+import xiaozhi.common.service.BaseService;
+import xiaozhi.modules.knowledge.dto.KnowledgeBaseDTO;
+import xiaozhi.modules.knowledge.entity.KnowledgeBaseEntity;
+
+/**
+ * 知识库知识库服务接口
+ */
+public interface KnowledgeBaseService extends BaseService<KnowledgeBaseEntity> {
+
+    /**
+     * 分页查询知识库列表
+     * 
+     * @param knowledgeBaseDTO 查询条件
+     * @param page             页码
+     * @param limit            每页数量
+     * @return 分页数据
+     */
+    PageData<KnowledgeBaseDTO> getPageList(KnowledgeBaseDTO knowledgeBaseDTO, Integer page, Integer limit);
+
+    /**
+     * 根据ID获取知识库详情
+     * 
+     * @param id 知识库ID
+     * @return 知识库详情
+     */
+    KnowledgeBaseDTO getById(String id);
+
+    /**
+     * 新增知识库
+     * 
+     * @param knowledgeBaseDTO 知识库信息
+     * @return 新增的知识库
+     */
+    KnowledgeBaseDTO save(KnowledgeBaseDTO knowledgeBaseDTO);
+
+    /**
+     * 更新知识库
+     * 
+     * @param knowledgeBaseDTO 知识库信息
+     * @return 更新的知识库
+     */
+    KnowledgeBaseDTO update(KnowledgeBaseDTO knowledgeBaseDTO);
+
+    /**
+     * 根据知识库ID查询知识库
+     * 
+     * @param datasetId 知识库ID
+     * @return 知识库详情
+     */
+    KnowledgeBaseDTO getByDatasetId(String datasetId);
+
+    /**
+     * 根据知识库ID删除知识库
+     * 
+     * @param datasetId 知识库ID
+     */
+    void deleteByDatasetId(String datasetId);
+
+    /**
+     * 获取RAG配置信息
+     * 
+     * @param ragModelId RAG模型配置ID
+     * @return RAG配置信息
+     */
+    Map<String, Object> getRAGConfig(String ragModelId);
+
+    /**
+     * 根据知识库ID获取对应的RAG配置
+     * 
+     * @param datasetId 知识库ID
+     * @return RAG配置
+     */
+    Map<String, Object> getRAGConfigByDatasetId(String datasetId);
+
+    /**
+     * 获取RAG模型列表
+     * 
+     * @return RAG模型列表
+     */
+    List<Map<String, Object>> getRAGModels();
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/service/KnowledgeFilesService.java

@@ -0,0 +1,123 @@
+package xiaozhi.modules.knowledge.service;
+
+import java.util.List;
+import java.util.Map;
+
+import org.springframework.web.multipart.MultipartFile;
+
+import xiaozhi.common.page.PageData;
+import xiaozhi.modules.knowledge.dto.KnowledgeFilesDTO;
+
+/**
+ * 知识库文档服务接口
+ */
+public interface KnowledgeFilesService {
+
+        /**
+         * 分页查询文档列表
+         * 
+         * @param knowledgeFilesDTO 查询条件
+         * @param page              页码
+         * @param limit             每页数量
+         * @return 分页数据
+         */
+        PageData<KnowledgeFilesDTO> getPageList(KnowledgeFilesDTO knowledgeFilesDTO, Integer page, Integer limit);
+
+        /**
+         * 根据文档ID和知识库ID获取文档详情
+         * 
+         * @param documentId 文档ID
+         * @param datasetId  知识库ID
+         * @return 文档详情
+         */
+        KnowledgeFilesDTO getByDocumentId(String documentId, String datasetId);
+
+        /**
+         * 上传文档到知识库
+         * 
+         * @param datasetId    知识库ID
+         * @param file         上传的文件
+         * @param name         文档名称
+         * @param metaFields   元数据字段
+         * @param chunkMethod  分块方法
+         * @param parserConfig 解析器配置
+         * @return 上传的文档信息
+         */
+        KnowledgeFilesDTO uploadDocument(String datasetId, MultipartFile file, String name,
+                        Map<String, Object> metaFields, String chunkMethod,
+                        Map<String, Object> parserConfig);
+
+        /**
+         * 根据状态分页查询文档列表
+         * 
+         * @param datasetId 知识库ID
+         * @param status    文档解析状态（0-未开始，1-进行中，2-已取消，3-已完成，4-失败）
+         * @param page      页码
+         * @param limit     每页数量
+         * @return 分页数据
+         */
+        PageData<KnowledgeFilesDTO> getPageListByStatus(String datasetId, Integer status, Integer page, Integer limit);
+
+        /**
+         * 根据文档ID和知识库ID删除文档
+         * 
+         * @param documentId 文档ID
+         * @param datasetId  知识库ID
+         */
+        void deleteByDocumentId(String documentId, String datasetId);
+
+        /**
+         * 获取RAG配置信息
+         * 
+         * @param ragModelId RAG模型配置ID
+         * @return RAG配置信息
+         */
+        Map<String, Object> getRAGConfig(String ragModelId);
+
+        /**
+         * 解析文档（切块）
+         * 
+         * @param datasetId   知识库ID
+         * @param documentIds 文档ID列表
+         * @return 解析结果
+         */
+        boolean parseDocuments(String datasetId, List<String> documentIds);
+
+        /**
+         * 列出指定文档的切片
+         * 
+         * @param datasetId  知识库ID
+         * @param documentId 文档ID
+         * @param keywords   关键词过滤
+         * @param page       页码
+         * @param pageSize   每页数量
+         * @param chunkId    切片ID
+         * @return 切片列表信息
+         */
+        Map<String, Object> listChunks(String datasetId, String documentId, String keywords,
+                        Integer page, Integer pageSize, String chunkId);
+
+        /**
+         * 召回测试 - 从指定数据集或文档中检索相关切片
+         * 
+         * @param question               用户查询或查询关键词
+         * @param datasetIds             数据集ID列表
+         * @param documentIds            文档ID列表
+         * @param page                   页码
+         * @param pageSize               每页数量
+         * @param similarityThreshold    最小相似度阈值
+         * @param vectorSimilarityWeight 向量相似度权重
+         * @param topK                   参与向量余弦计算的切片数量
+         * @param rerankId               重排模型ID
+         * @param keyword                是否启用关键词匹配
+         * @param highlight              是否启用高亮显示
+         * @param crossLanguages         跨语言翻译列表
+         * @param metadataCondition      元数据过滤条件
+         * @return 召回测试结果
+         */
+        Map<String, Object> retrievalTest(String question, List<String> datasetIds, List<String> documentIds,
+                        Integer page, Integer pageSize, Float similarityThreshold,
+                        Float vectorSimilarityWeight, Integer topK, String rerankId,
+                        Boolean keyword, Boolean highlight, List<String> crossLanguages,
+                        Map<String, Object> metadataCondition);
+}

main/manager-api/src/main/java/xiaozhi/modules/knowledge/service/impl/KnowledgeBaseServiceImpl.java

@@ -0,0 +1,644 @@
+package xiaozhi.modules.knowledge.service.impl;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import org.apache.commons.lang3.StringUtils;
+import org.springframework.http.HttpEntity;
+import org.springframework.http.HttpHeaders;
+import org.springframework.http.HttpMethod;
+import org.springframework.http.MediaType;
+import org.springframework.http.ResponseEntity;
+import org.springframework.stereotype.Service;
+import org.springframework.web.client.RestTemplate;
+
+import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
+import com.baomidou.mybatisplus.core.metadata.IPage;
+import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import lombok.AllArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+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.service.impl.BaseServiceImpl;
+import xiaozhi.common.utils.ConvertUtils;
+import xiaozhi.common.utils.MessageUtils;
+import xiaozhi.modules.knowledge.dao.KnowledgeBaseDao;
+import xiaozhi.modules.knowledge.dto.KnowledgeBaseDTO;
+import xiaozhi.modules.knowledge.entity.KnowledgeBaseEntity;
+import xiaozhi.modules.knowledge.rag.KnowledgeBaseAdapter;
+import xiaozhi.modules.knowledge.rag.KnowledgeBaseAdapterFactory;
+import xiaozhi.modules.knowledge.service.KnowledgeBaseService;
+import xiaozhi.modules.model.dao.ModelConfigDao;
+import xiaozhi.modules.model.entity.ModelConfigEntity;
+import xiaozhi.modules.model.service.ModelConfigService;
+import xiaozhi.modules.security.user.SecurityUser;
+
+@Service
+@AllArgsConstructor
+@Slf4j
+public class KnowledgeBaseServiceImpl extends BaseServiceImpl<KnowledgeBaseDao, KnowledgeBaseEntity>
+        implements KnowledgeBaseService {
+
+    private final KnowledgeBaseDao knowledgeBaseDao;
+    private final ModelConfigService modelConfigService;
+    private final ModelConfigDao modelConfigDao;
+    private final RedisUtils redisUtils;
+    private RestTemplate restTemplate = new RestTemplate();
+    private final ObjectMapper objectMapper = new ObjectMapper();
+
+    @Override
+    public KnowledgeBaseEntity selectById(Serializable datasetId) {
+        if (datasetId == null) {
+            return null;
+        }
+
+        // 先从Redis获取缓存
+        String key = RedisKeys.getKnowledgeBaseCacheKey(datasetId.toString());
+        KnowledgeBaseEntity cachedEntity = (KnowledgeBaseEntity) redisUtils.get(key);
+        if (cachedEntity != null) {
+            return cachedEntity;
+        }
+
+        // 如果缓存中没有，则从数据库获取
+        KnowledgeBaseEntity entity = knowledgeBaseDao.selectById(datasetId);
+        if (entity == null) {
+            return null;
+        }
+
+        // 存入Redis缓存
+        redisUtils.set(key, entity);
+
+        return entity;
+    }
+
+    @Override
+    public PageData<KnowledgeBaseDTO> getPageList(KnowledgeBaseDTO knowledgeBaseDTO, Integer page, Integer limit) {
+        long curPage = page;
+        long pageSize = limit;
+        Page<KnowledgeBaseEntity> pageInfo = new Page<>(curPage, pageSize);
+
+        QueryWrapper<KnowledgeBaseEntity> queryWrapper = new QueryWrapper<>();
+
+        // 添加查询条件
+        if (knowledgeBaseDTO != null) {
+            queryWrapper.like(StringUtils.isNotBlank(knowledgeBaseDTO.getName()), "name", knowledgeBaseDTO.getName());
+            queryWrapper.eq(knowledgeBaseDTO.getStatus() != null, "status", knowledgeBaseDTO.getStatus());
+            queryWrapper.eq("creator", knowledgeBaseDTO.getCreator());
+        }
+
+        // 添加排序规则：按创建时间降序
+        queryWrapper.orderByDesc("created_at");
+
+        IPage<KnowledgeBaseEntity> knowledgeBaseEntityIPage = knowledgeBaseDao.selectPage(pageInfo, queryWrapper);
+
+        // 获取分页数据
+        PageData<KnowledgeBaseDTO> pageData = getPageData(knowledgeBaseEntityIPage, KnowledgeBaseDTO.class);
+
+        // 为每个知识库获取文档数量
+        if (pageData != null && pageData.getList() != null) {
+            for (KnowledgeBaseDTO knowledgeBase : pageData.getList()) {
+                try {
+                    Integer documentCount = getDocumentCountFromRAG(knowledgeBase.getDatasetId(),
+                            knowledgeBase.getRagModelId());
+                    knowledgeBase.setDocumentCount(documentCount);
+                } catch (Exception e) {
+                    // 构建详细的错误信息，包含异常类型和消息
+                    String baseErrorMessage = e.getClass().getSimpleName() + " - 获取知识库文档数量失败";
+                    String errorMessage = baseErrorMessage + (e.getMessage() != null ? ": " + e.getMessage() : "");
+                    log.warn("知识库 {} {}", knowledgeBase.getDatasetId(), errorMessage);
+                    knowledgeBase.setDocumentCount(0); // 设置默认值
+                }
+            }
+        }
+
+        return pageData;
+    }
+
+    @Override
+    public KnowledgeBaseDTO getById(String id) {
+        if (StringUtils.isBlank(id)) {
+            throw new RenException(ErrorCode.IDENTIFIER_NOT_NULL);
+        }
+
+        KnowledgeBaseEntity entity = knowledgeBaseDao.selectById(id);
+        if (entity == null) {
+            throw new RenException(ErrorCode.Knowledge_Base_RECORD_NOT_EXISTS);
+        }
+
+        return ConvertUtils.sourceToTarget(entity, KnowledgeBaseDTO.class);
+    }
+
+    @Override
+    public KnowledgeBaseDTO save(KnowledgeBaseDTO knowledgeBaseDTO) {
+        if (knowledgeBaseDTO == null) {
+            throw new RenException(ErrorCode.PARAMS_GET_ERROR);
+        }
+
+        // 检查是否存在同名知识库
+        checkDuplicateKnowledgeBaseName(knowledgeBaseDTO, null);
+
+        String datasetId = null;
+        // 调用RAG API创建数据集
+        try {
+            Map<String, Object> ragConfig = getValidatedRAGConfig(knowledgeBaseDTO.getRagModelId());
+            datasetId = createDatasetInRAG(
+                    knowledgeBaseDTO.getName(),
+                    knowledgeBaseDTO.getDescription(),
+                    ragConfig);
+        } catch (Exception e) {
+            // 如果RAG API调用失败，直接抛出异常
+            throw e;
+        }
+
+        // 验证数据集ID是否已存在
+        KnowledgeBaseEntity existingEntity = knowledgeBaseDao.selectOne(
+                new QueryWrapper<KnowledgeBaseEntity>().eq("dataset_id", datasetId));
+        if (existingEntity != null) {
+            // 如果datasetId已存在，删除RAG中的数据集并抛出异常
+            try {
+                Map<String, Object> ragConfig = getValidatedRAGConfig(knowledgeBaseDTO.getRagModelId());
+                deleteDatasetInRAG(datasetId, ragConfig);
+            } catch (Exception deleteException) {
+                // 提供更详细的错误信息，包括异常类型和消息
+                String errorMessage = "删除重复datasetId的RAG数据集失败: " + deleteException.getClass().getSimpleName();
+                if (deleteException.getMessage() != null) {
+                    errorMessage += " - " + deleteException.getMessage();
+                }
+                log.warn(errorMessage, deleteException);
+            }
+            throw new RenException(ErrorCode.DB_RECORD_EXISTS);
+        }
+
+        // 创建本地实体并保存
+        KnowledgeBaseEntity entity = ConvertUtils.sourceToTarget(knowledgeBaseDTO, KnowledgeBaseEntity.class);
+        entity.setDatasetId(datasetId);
+        knowledgeBaseDao.insert(entity);
+
+        return ConvertUtils.sourceToTarget(entity, KnowledgeBaseDTO.class);
+    }
+
+    @Override
+    public KnowledgeBaseDTO update(KnowledgeBaseDTO knowledgeBaseDTO) {
+        if (knowledgeBaseDTO == null || StringUtils.isBlank(knowledgeBaseDTO.getId())) {
+            throw new RenException(ErrorCode.IDENTIFIER_NOT_NULL);
+        }
+
+        // 检查记录是否存在
+        KnowledgeBaseEntity existingEntity = knowledgeBaseDao.selectById(knowledgeBaseDTO.getId());
+        if (existingEntity == null) {
+            throw new RenException(ErrorCode.Knowledge_Base_RECORD_NOT_EXISTS);
+        }
+
+        // 检查是否存在同名知识库（排除当前记录）
+        checkDuplicateKnowledgeBaseName(knowledgeBaseDTO, knowledgeBaseDTO.getId());
+
+        // 验证数据集ID是否与其他记录冲突
+        if (StringUtils.isNotBlank(knowledgeBaseDTO.getDatasetId())) {
+            KnowledgeBaseEntity conflictEntity = knowledgeBaseDao.selectOne(
+                    new QueryWrapper<KnowledgeBaseEntity>()
+                            .eq("dataset_id", knowledgeBaseDTO.getDatasetId())
+                            .ne("id", knowledgeBaseDTO.getId()));
+            if (conflictEntity != null) {
+                throw new RenException(ErrorCode.DB_RECORD_EXISTS);
+            }
+        }
+
+        boolean needRagValidation = StringUtils.isNotBlank(knowledgeBaseDTO.getDatasetId())
+                && StringUtils.isNotBlank(knowledgeBaseDTO.getRagModelId());
+
+        if (needRagValidation) {
+            try {
+                // 先校验RAG配置
+                Map<String, Object> ragConfig = getValidatedRAGConfig(knowledgeBaseDTO.getRagModelId());
+
+                // 调用RAG API更新数据集
+                updateDatasetInRAG(
+                        knowledgeBaseDTO.getDatasetId(),
+                        knowledgeBaseDTO.getName(),
+                        knowledgeBaseDTO.getDescription(),
+                        ragConfig);
+
+                log.info("RAG API更新成功，datasetId: {}", knowledgeBaseDTO.getDatasetId());
+            } catch (Exception e) {
+                // 提供更详细的错误信息，包括异常类型和消息
+                String errorMessage = "更新RAG数据集失败: " + e.getClass().getSimpleName();
+                if (e.getMessage() != null) {
+                    errorMessage += " - " + e.getMessage();
+                }
+                log.error(errorMessage, e);
+                throw e;
+            }
+        } else {
+            log.warn("datasetId或ragModelId为空，跳过RAG更新");
+        }
+
+        KnowledgeBaseEntity entity = ConvertUtils.sourceToTarget(knowledgeBaseDTO, KnowledgeBaseEntity.class);
+        knowledgeBaseDao.updateById(entity);
+
+        // 删除缓存
+        if (entity.getDatasetId() != null) {
+            redisUtils.delete(RedisKeys.getKnowledgeBaseCacheKey(entity.getId()));
+        }
+
+        return ConvertUtils.sourceToTarget(entity, KnowledgeBaseDTO.class);
+    }
+
+    @Override
+    public KnowledgeBaseDTO getByDatasetId(String datasetId) {
+        if (StringUtils.isBlank(datasetId)) {
+            throw new RenException(ErrorCode.PARAMS_GET_ERROR);
+        }
+
+        KnowledgeBaseEntity entity = knowledgeBaseDao.selectOne(
+                new QueryWrapper<KnowledgeBaseEntity>().eq("dataset_id", datasetId));
+
+        if (entity == null) {
+            throw new RenException(ErrorCode.Knowledge_Base_RECORD_NOT_EXISTS);
+        }
+
+        return ConvertUtils.sourceToTarget(entity, KnowledgeBaseDTO.class);
+    }
+
+    @Override
+    public void deleteByDatasetId(String datasetId) {
+        if (StringUtils.isBlank(datasetId)) {
+            throw new RenException(ErrorCode.PARAMS_GET_ERROR);
+        }
+
+        log.info("=== 开始通过datasetId删除操作 ===");
+        log.info("删除datasetId: {}", datasetId);
+
+        KnowledgeBaseEntity entity = knowledgeBaseDao.selectOne(
+                new QueryWrapper<KnowledgeBaseEntity>().eq("dataset_id", datasetId));
+
+        if (entity == null) {
+            log.warn("记录不存在，datasetId: {}", datasetId);
+            throw new RenException(ErrorCode.Knowledge_Base_RECORD_NOT_EXISTS);
+        }
+        redisUtils.delete(RedisKeys.getKnowledgeBaseCacheKey(entity.getId()));
+
+        log.info("找到记录: ID={}, datasetId={}, ragModelId={}",
+                entity.getId(), entity.getDatasetId(), entity.getRagModelId());
+
+        // 先调用RAG API删除数据集
+        boolean apiDeleteSuccess = false;
+        if (StringUtils.isNotBlank(entity.getDatasetId()) && StringUtils.isNotBlank(entity.getRagModelId())) {
+            try {
+                log.info("开始调用RAG API删除数据集");
+                // 在删除前进行RAG配置校验
+                Map<String, Object> ragConfig = getValidatedRAGConfig(entity.getRagModelId());
+                deleteDatasetInRAG(entity.getDatasetId(), ragConfig);
+                log.info("RAG API删除调用完成");
+                apiDeleteSuccess = true;
+            } catch (Exception e) {
+                // 提供更详细的错误信息，包括异常类型和消息
+                String errorMessage = "删除RAG数据集失败: " + e.getClass().getSimpleName();
+                if (e.getMessage() != null) {
+                    errorMessage += " - " + e.getMessage();
+                }
+                log.error(errorMessage, e);
+                throw e;
+            }
+        } else {
+            log.warn("datasetId或ragModelId为空，跳过RAG删除");
+            apiDeleteSuccess = true; // 没有RAG数据集，视为成功
+        }
+
+        // API删除成功后再删除本地记录
+        if (apiDeleteSuccess) {
+            log.info("开始删除ai_agent_plugin_mapping表中与知识库ID '{}' 相关的映射记录", entity.getId());
+
+            // 先删除相关的插件映射记录
+            knowledgeBaseDao.deletePluginMappingByKnowledgeBaseId(entity.getId());
+            log.info("插件映射记录删除完成");
+
+            int deleteCount = knowledgeBaseDao.deleteById(entity.getId());
+            log.info("本地数据库删除结果: {}", deleteCount > 0 ? "成功" : "失败");
+        }
+
+        log.info("=== 通过datasetId删除操作结束 ===");
+    }
+
+    @Override
+    public Map<String, Object> getRAGConfig(String ragModelId) {
+        if (StringUtils.isBlank(ragModelId)) {
+            throw new RenException(ErrorCode.PARAMS_GET_ERROR);
+        }
+
+        // 从缓存获取模型配置
+        ModelConfigEntity modelConfig = modelConfigService.getModelByIdFromCache(ragModelId);
+        if (modelConfig == null || modelConfig.getConfigJson() == null) {
+            throw new RenException(ErrorCode.RAG_CONFIG_NOT_FOUND);
+        }
+
+        // 验证是否为RAG类型配置
+        if (!Constant.RAG_CONFIG_TYPE.equals(modelConfig.getModelType().toUpperCase())) {
+            throw new RenException(ErrorCode.RAG_CONFIG_TYPE_ERROR);
+        }
+
+        Map<String, Object> config = modelConfig.getConfigJson();
+
+        // 验证必要的配置参数
+        validateRagConfig(config);
+
+        // 返回配置信息
+        return config;
+    }
+
+    @Override
+    public Map<String, Object> getRAGConfigByDatasetId(String datasetId) {
+        if (StringUtils.isBlank(datasetId)) {
+            throw new RenException(ErrorCode.RAG_DATASET_ID_NOT_NULL);
+        }
+
+        // 根据datasetId查询知识库信息
+        KnowledgeBaseDTO knowledgeBase = getByDatasetId(datasetId);
+        if (knowledgeBase == null) {
+            log.warn("未找到datasetId为{}的知识库", datasetId);
+            throw new RenException(ErrorCode.Knowledge_Base_RECORD_NOT_EXISTS);
+        }
+
+        // 如果知识库指定了ragModelId，使用该配置
+        String ragModelId = knowledgeBase.getRagModelId();
+        if (StringUtils.isBlank(ragModelId)) {
+            log.warn("知识库datasetId为{}未配置ragModelId", datasetId);
+            throw new RenException(ErrorCode.RAG_CONFIG_NOT_FOUND);
+        }
+
+        // 获取并返回RAG配置
+        return getRAGConfig(ragModelId);
+    }
+
+    @Override
+    public List<Map<String, Object>> getRAGModels() {
+        // 查询RAG类型的模型配置
+        QueryWrapper<ModelConfigEntity> queryWrapper = new QueryWrapper<>();
+        queryWrapper.eq("model_type", Constant.RAG_CONFIG_TYPE)
+                .eq("is_enabled", 1)
+                .orderByDesc("is_default")
+                .orderByDesc("create_date");
+
+        List<ModelConfigEntity> modelConfigs = modelConfigDao.selectList(queryWrapper);
+
+        List<Map<String, Object>> modelList = new ArrayList<>();
+        for (ModelConfigEntity modelConfig : modelConfigs) {
+            Map<String, Object> modelInfo = new HashMap<>();
+            modelInfo.put("id", modelConfig.getId());
+            modelInfo.put("modelName", modelConfig.getModelName());
+            modelList.add(modelInfo);
+        }
+        return modelList;
+    }
+
+    /**
+     * 验证RAG配置中是否包含必要的参数
+     */
+    private void validateRagConfig(Map<String, Object> config) {
+        if (config == null) {
+            throw new RenException(ErrorCode.RAG_CONFIG_NOT_FOUND);
+        }
+
+        // 从配置中提取必要的参数
+        String baseUrl = (String) config.get("base_url");
+        String apiKey = (String) config.get("api_key");
+
+        // 验证base_url是否存在且非空
+        if (StringUtils.isBlank(baseUrl)) {
+            throw new RenException(ErrorCode.RAG_API_ERROR_URL_NULL);
+        }
+
+        // 验证api_key是否存在且非空
+        if (StringUtils.isBlank(apiKey)) {
+            throw new RenException(ErrorCode.RAG_API_ERROR_API_KEY_NULL);
+        }
+
+        // 检查api_key是否包含占位符
+        if (apiKey.contains("你")) {
+            throw new RenException(ErrorCode.RAG_API_ERROR_API_KEY_INVALID);
+        }
+
+        // 验证base_url格式
+        if (!baseUrl.startsWith("http://") && !baseUrl.startsWith("https://")) {
+            throw new RenException(ErrorCode.RAG_API_ERROR_URL_INVALID);
+        }
+    }
+
+    /**
+     * 从RAG配置中提取适配器类型
+     * 
+     * @param config RAG配置
+     * @return 适配器类型
+     */
+    private String extractAdapterType(Map<String, Object> config) {
+        if (config == null) {
+            throw new RenException(ErrorCode.RAG_CONFIG_NOT_FOUND);
+        }
+
+        // 从配置中提取适配器类型
+        String adapterType = (String) config.get("type");
+
+        // 验证适配器类型是否存在且非空
+        if (StringUtils.isBlank(adapterType)) {
+            throw new RenException(ErrorCode.RAG_ADAPTER_TYPE_NOT_FOUND);
+        }
+
+        // 验证适配器类型是否已注册
+        if (!KnowledgeBaseAdapterFactory.isAdapterTypeRegistered(adapterType)) {
+            throw new RenException(ErrorCode.RAG_ADAPTER_TYPE_NOT_SUPPORTED,
+                    "不支持的适配器类型: " + adapterType);
+        }
+
+        return adapterType;
+    }
+
+    /**
+     * 使用适配器创建数据集
+     */
+    private String createDatasetInRAG(String name, String description, Map<String, Object> ragConfig) {
+        log.info("开始使用适配器创建数据集, name: {}", name);
+
+        try {
+            // 从RAG配置中提取适配器类型
+            String adapterType = extractAdapterType(ragConfig);
+
+            // 使用适配器工厂获取适配器实例
+            KnowledgeBaseAdapter adapter = KnowledgeBaseAdapterFactory.getAdapter(adapterType, ragConfig);
+
+            // 构建数据集创建参数
+            Map<String, Object> createParams = new HashMap<>();
+            String username = SecurityUser.getUser().getUsername();
+            createParams.put("name", username + "_" + name);
+            if (StringUtils.isNotBlank(description)) {
+                createParams.put("description", description);
+            }
+
+            // 调用适配器的创建数据集方法
+            String datasetId = adapter.createDataset(createParams);
+
+            log.info("数据集创建成功，datasetId: {}", datasetId);
+            return datasetId;
+
+        } catch (Exception e) {
+            // 直接传递底层适配器的详细错误信息
+            log.error("创建数据集失败", e);
+            if (e instanceof RenException) {
+                throw (RenException) e;
+            }
+            throw new RenException(ErrorCode.RAG_API_ERROR, e.getMessage());
+        }
+    }
+
+    /**
+     * 使用适配器更新数据集
+     */
+    private void updateDatasetInRAG(String datasetId, String name, String description,
+            Map<String, Object> ragConfig) {
+        log.info("开始使用适配器更新数据集，datasetId: {}, name: {}", datasetId, name);
+
+        try {
+            // 从RAG配置中提取适配器类型
+            String adapterType = extractAdapterType(ragConfig);
+
+            // 使用适配器工厂获取适配器实例
+            KnowledgeBaseAdapter adapter = KnowledgeBaseAdapterFactory.getAdapter(adapterType, ragConfig);
+
+            // 构建数据集更新参数
+            Map<String, Object> updateParams = new HashMap<>();
+            String username = SecurityUser.getUser().getUsername();
+            updateParams.put("name", username + "_" + name);
+            if (StringUtils.isNotBlank(description)) {
+                updateParams.put("description", description);
+            }
+
+            // 调用适配器的更新数据集方法
+            adapter.updateDataset(datasetId, updateParams);
+
+            log.info("数据集更新成功，datasetId: {}", datasetId);
+
+        } catch (Exception e) {
+            // 直接传递底层适配器的详细错误信息
+            log.error("更新数据集失败", e);
+            if (e instanceof RenException) {
+                throw (RenException) e;
+            }
+            throw new RenException(ErrorCode.RAG_API_ERROR, e.getMessage());
+        }
+    }
+
+    /**
+     * 使用适配器删除数据集
+     */
+    private void deleteDatasetInRAG(String datasetId, Map<String, Object> ragConfig) {
+        log.info("开始使用适配器删除数据集，datasetId: {}", datasetId);
+
+        try {
+            // 从RAG配置中提取适配器类型
+            String adapterType = extractAdapterType(ragConfig);
+
+            // 使用适配器工厂获取适配器实例
+            KnowledgeBaseAdapter adapter = KnowledgeBaseAdapterFactory.getAdapter(adapterType, ragConfig);
+
+            // 调用适配器的删除数据集方法
+            adapter.deleteDataset(datasetId);
+
+            log.info("数据集删除成功，datasetId: {}", datasetId);
+
+        } catch (Exception e) {
+            // 直接传递底层适配器的详细错误信息
+            log.error("删除数据集失败", e);
+            if (e instanceof RenException) {
+                throw (RenException) e;
+            }
+            throw new RenException(ErrorCode.RAG_API_ERROR, e.getMessage());
+        }
+    }
+
+    /**
+     * 获取RAG配置并验证
+     */
+    private Map<String, Object> getValidatedRAGConfig(String ragModelId) {
+        if (StringUtils.isBlank(ragModelId)) {
+            throw new RenException(ErrorCode.RAG_MODEL_ID_NOT_NULL);
+        }
+
+        Map<String, Object> ragConfig = getRAGConfig(ragModelId);
+
+        // 验证RAG配置参数
+        validateRagConfig(ragConfig);
+
+        return ragConfig;
+    }
+
+    /**
+     * 检查是否存在同名知识库
+     * 
+     * @param knowledgeBaseDTO 知识库DTO
+     * @param excludeId        排除的ID（更新时使用）
+     */
+    private void checkDuplicateKnowledgeBaseName(KnowledgeBaseDTO knowledgeBaseDTO, String excludeId) {
+        if (StringUtils.isNotBlank(knowledgeBaseDTO.getName())) {
+            Long currentUserId = SecurityUser.getUserId();
+            QueryWrapper<KnowledgeBaseEntity> queryWrapper = new QueryWrapper<KnowledgeBaseEntity>()
+                    .eq("name", knowledgeBaseDTO.getName())
+                    .eq("creator", currentUserId);
+
+            // 如果提供了排除ID，则排除该记录
+            if (StringUtils.isNotBlank(excludeId)) {
+                queryWrapper.ne("id", excludeId);
+            }
+
+            long count = knowledgeBaseDao.selectCount(queryWrapper);
+            if (count > 0) {
+                throw new RenException(ErrorCode.KNOWLEDGE_BASE_NAME_EXISTS,
+                        MessageUtils.getMessage(ErrorCode.KNOWLEDGE_BASE_NAME_EXISTS));
+            }
+        }
+    }
+
+    /**
+     * 从适配器获取知识库的文档数量
+     */
+    private Integer getDocumentCountFromRAG(String datasetId, String ragModelId) {
+        if (StringUtils.isBlank(datasetId) || StringUtils.isBlank(ragModelId)) {
+            log.warn("datasetId或ragModelId为空，无法获取文档数量");
+            return 0;
+        }
+
+        log.info("开始获取知识库 {} 的文档数量", datasetId);
+
+        try {
+            // 获取RAG配置
+            Map<String, Object> ragConfig = getValidatedRAGConfig(ragModelId);
+
+            // 从RAG配置中提取适配器类型
+            String adapterType = extractAdapterType(ragConfig);
+
+            // 使用适配器工厂获取适配器实例
+            KnowledgeBaseAdapter adapter = KnowledgeBaseAdapterFactory.getAdapter(adapterType, ragConfig);
+
+            // 调用适配器的获取文档数量方法
+            Integer documentCount = adapter.getDocumentCount(datasetId);
+
+            log.info("获取知识库 {} 的文档数量成功: {}", datasetId, documentCount);
+            return documentCount;
+
+        } catch (Exception e) {
+            // 构建详细的错误信息，包含异常类型和消息
+            String baseErrorMessage = e.getClass().getSimpleName() + " - 获取知识库文档数量失败";
+            String errorMessage = baseErrorMessage + (e.getMessage() != null ? ": " + e.getMessage() : "");
+            log.error(errorMessage, e);
+            return 0;
+        }
+    }
+
+}

main/manager-api/src/main/java/xiaozhi/modules/llm/service/LLMService.java

@@ -0,0 +1,70 @@
+package xiaozhi.modules.llm.service;
+
+/**
+ * LLM服务接口
+ * 支持多种大模型调用
+ */
+public interface LLMService {
+
+    /**
+     * 生成聊天记录总结
+     * 
+     * @param conversation   对话内容
+     * @param promptTemplate 提示词模板
+     * @return 总结结果
+     */
+    String generateSummary(String conversation, String promptTemplate);
+
+    /**
+     * 生成聊天记录总结（使用默认提示词）
+     * 
+     * @param conversation 对话内容
+     * @return 总结结果
+     */
+    String generateSummary(String conversation);
+
+    /**
+     * 生成聊天记录总结（指定模型ID）
+     * 
+     * @param conversation 对话内容
+     * @param modelId      模型ID
+     * @return 总结结果
+     */
+    String generateSummaryWithModel(String conversation, String modelId);
+
+    /**
+     * 生成聊天记录总结（指定模型ID和提示词模板）
+     * 
+     * @param conversation   对话内容
+     * @param promptTemplate 提示词模板
+     * @param modelId        模型ID
+     * @return 总结结果
+     */
+    String generateSummary(String conversation, String promptTemplate, String modelId);
+
+    /**
+     * 生成聊天记录总结（包含历史记忆合并）
+     * 
+     * @param conversation   对话内容
+     * @param historyMemory  历史记忆
+     * @param promptTemplate 提示词模板
+     * @param modelId        模型ID
+     * @return 总结结果
+     */
+    String generateSummaryWithHistory(String conversation, String historyMemory, String promptTemplate, String modelId);
+
+    /**
+     * 检查服务是否可用
+     * 
+     * @return 是否可用
+     */
+    boolean isAvailable();
+
+    /**
+     * 检查指定模型的服务是否可用
+     * 
+     * @param modelId 模型ID
+     * @return 是否可用
+     */
+    boolean isAvailable(String modelId);
+}

main/manager-api/src/main/java/xiaozhi/modules/llm/service/impl/OpenAIStyleLLMServiceImpl.java

@@ -0,0 +1,305 @@
+package xiaozhi.modules.llm.service.impl;
+
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import org.apache.commons.lang3.StringUtils;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.http.HttpEntity;
+import org.springframework.http.HttpHeaders;
+import org.springframework.http.HttpMethod;
+import org.springframework.http.MediaType;
+import org.springframework.http.ResponseEntity;
+import org.springframework.stereotype.Service;
+import org.springframework.web.client.RestTemplate;
+
+import cn.hutool.json.JSONArray;
+import cn.hutool.json.JSONObject;
+import cn.hutool.json.JSONUtil;
+import lombok.extern.slf4j.Slf4j;
+import xiaozhi.modules.llm.service.LLMService;
+import xiaozhi.modules.model.entity.ModelConfigEntity;
+import xiaozhi.modules.model.service.ModelConfigService;
+
+/**
+ * OpenAI风格API的LLM服务实现
+ * 支持阿里云、DeepSeek、ChatGLM等兼容OpenAI API的模型
+ */
+@Slf4j
+@Service
+public class OpenAIStyleLLMServiceImpl implements LLMService {
+
+    @Autowired
+    private ModelConfigService modelConfigService;
+
+    private final RestTemplate restTemplate = new RestTemplate();
+
+    private static final String DEFAULT_SUMMARY_PROMPT = "你是一个经验丰富的记忆总结者，擅长将对话内容进行总结摘要，遵循以下规则：\n1、总结用户的重要信息，以便在未来的对话中提供更个性化的服务\n2、不要重复总结，不要遗忘之前记忆，除非原来的记忆超过了1800字，否则不要遗忘、不要压缩用户的历史记忆\n3、用户操控的设备音量、播放音乐、天气、退出、不想对话等和用户本身无关的内容，这些信息不需要加入到总结中\n4、聊天内容中的今天的日期时间、今天的天气情况与用户事件无关的数据，这些信息如果当成记忆存储会影响后续对话，这些信息不需要加入到总结中\n5、不要把设备操控的成果结果和失败结果加入到总结中，也不要把用户的一些废话加入到总结中\n6、不要为了总结而总结，如果用户的聊天没有意义，请返回原来的历史记录也是可以的\n7、只需要返回总结摘要，严格控制在1800字内\n8、不要包含代码、xml，不需要解释、注释和说明，保存记忆时仅从对话提取信息，不要混入示例内容\n9、如果提供了历史记忆，请将新对话内容与历史记忆进行智能合并，保留有价值的历史信息，同时添加新的重要信息\n\n历史记忆：\n{history_memory}\n\n新对话内容：\n{conversation}";
+
+    @Override
+    public String generateSummary(String conversation) {
+        return generateSummary(conversation, null, null);
+    }
+
+    @Override
+    public String generateSummaryWithModel(String conversation, String modelId) {
+        return generateSummary(conversation, null, modelId);
+    }
+
+    @Override
+    public String generateSummary(String conversation, String promptTemplate, String modelId) {
+        if (!isAvailable()) {
+            log.warn("LLM服务不可用，无法生成总结");
+            return "LLM服务不可用，无法生成总结";
+        }
+
+        try {
+            // 从智控台获取LLM模型配置
+            ModelConfigEntity llmConfig;
+            if (modelId != null && !modelId.trim().isEmpty()) {
+                // 通过具体模型ID获取配置
+                llmConfig = modelConfigService.getModelByIdFromCache(modelId);
+            } else {
+                // 保持向后兼容，使用默认配置
+                llmConfig = getDefaultLLMConfig();
+            }
+
+            if (llmConfig == null || llmConfig.getConfigJson() == null) {
+                log.error("未找到可用的LLM模型配置，modelId: {}", modelId);
+                return "未找到可用的LLM模型配置";
+            }
+
+            JSONObject configJson = llmConfig.getConfigJson();
+            String baseUrl = configJson.getStr("base_url");
+            String model = configJson.getStr("model_name");
+            String apiKey = configJson.getStr("api_key");
+            Double temperature = configJson.getDouble("temperature");
+            Integer maxTokens = configJson.getInt("max_tokens");
+
+            if (StringUtils.isBlank(baseUrl) || StringUtils.isBlank(apiKey)) {
+                log.error("LLM配置不完整，baseUrl或apiKey为空");
+                return "LLM配置不完整，无法生成总结";
+            }
+
+            // 构建提示词
+            String prompt = (promptTemplate != null ? promptTemplate : DEFAULT_SUMMARY_PROMPT).replace("{conversation}",
+                    conversation);
+
+            // 构建请求体
+            Map<String, Object> requestBody = new HashMap<>();
+            requestBody.put("model", model != null ? model : "gpt-3.5-turbo");
+
+            Map<String, Object>[] messages = new Map[1];
+            Map<String, Object> message = new HashMap<>();
+            message.put("role", "user");
+            message.put("content", prompt);
+            messages[0] = message;
+
+            requestBody.put("messages", messages);
+            requestBody.put("temperature", temperature != null ? temperature : 0.7);
+            requestBody.put("max_tokens", maxTokens != null ? maxTokens : 2000);
+
+            // 发送HTTP请求
+            HttpHeaders headers = new HttpHeaders();
+            headers.setContentType(MediaType.APPLICATION_JSON);
+            headers.set("Authorization", "Bearer " + apiKey);
+
+            HttpEntity<Map<String, Object>> entity = new HttpEntity<>(requestBody, headers);
+
+            // 构建完整的API URL
+            String apiUrl = baseUrl;
+            if (!apiUrl.endsWith("/chat/completions")) {
+                if (!apiUrl.endsWith("/")) {
+                    apiUrl += "/";
+                }
+                apiUrl += "chat/completions";
+            }
+
+            ResponseEntity<String> response = restTemplate.exchange(
+                    apiUrl, HttpMethod.POST, entity, String.class);
+
+            if (response.getStatusCode().is2xxSuccessful()) {
+                JSONObject responseJson = JSONUtil.parseObj(response.getBody());
+                JSONArray choices = responseJson.getJSONArray("choices");
+                if (choices != null && choices.size() > 0) {
+                    JSONObject choice = choices.getJSONObject(0);
+                    JSONObject messageObj = choice.getJSONObject("message");
+                    return messageObj.getStr("content");
+                }
+            } else {
+                log.error("LLM API调用失败，状态码：{}，响应：{}", response.getStatusCode(), response.getBody());
+            }
+        } catch (Exception e) {
+            log.error("调用LLM服务生成总结时发生异常，modelId: {}", modelId, e);
+        }
+
+        return "生成总结失败，请稍后重试";
+    }
+
+    @Override
+    public String generateSummary(String conversation, String promptTemplate) {
+        return generateSummary(conversation, promptTemplate, null);
+    }
+
+    @Override
+    public String generateSummaryWithHistory(String conversation, String historyMemory, String promptTemplate,
+            String modelId) {
+        if (!isAvailable()) {
+            log.warn("LLM服务不可用，无法生成总结");
+            return "LLM服务不可用，无法生成总结";
+        }
+
+        try {
+            // 从智控台获取LLM模型配置
+            ModelConfigEntity llmConfig;
+            if (modelId != null && !modelId.trim().isEmpty()) {
+                // 通过具体模型ID获取配置
+                llmConfig = modelConfigService.getModelByIdFromCache(modelId);
+            } else {
+                // 保持向后兼容，使用默认配置
+                llmConfig = getDefaultLLMConfig();
+            }
+
+            if (llmConfig == null || llmConfig.getConfigJson() == null) {
+                log.error("未找到可用的LLM模型配置，modelId: {}", modelId);
+                return "未找到可用的LLM模型配置";
+            }
+
+            JSONObject configJson = llmConfig.getConfigJson();
+            String baseUrl = configJson.getStr("base_url");
+            String model = configJson.getStr("model_name");
+            String apiKey = configJson.getStr("api_key");
+
+            if (StringUtils.isBlank(baseUrl) || StringUtils.isBlank(apiKey)) {
+                log.error("LLM配置不完整，baseUrl或apiKey为空");
+                return "LLM配置不完整，无法生成总结";
+            }
+
+            // 构建提示词，包含历史记忆
+            String prompt = (promptTemplate != null ? promptTemplate : DEFAULT_SUMMARY_PROMPT)
+                    .replace("{history_memory}", historyMemory != null ? historyMemory : "无历史记忆")
+                    .replace("{conversation}", conversation);
+
+            // 构建请求体
+            Map<String, Object> requestBody = new HashMap<>();
+            requestBody.put("model", model != null ? model : "gpt-3.5-turbo");
+
+            Map<String, Object>[] messages = new Map[1];
+            Map<String, Object> message = new HashMap<>();
+            message.put("role", "user");
+            message.put("content", prompt);
+            messages[0] = message;
+
+            requestBody.put("messages", messages);
+            requestBody.put("temperature", 0.2);
+            requestBody.put("max_tokens", 2000);
+
+            // 发送HTTP请求
+            HttpHeaders headers = new HttpHeaders();
+            headers.setContentType(MediaType.APPLICATION_JSON);
+            headers.set("Authorization", "Bearer " + apiKey);
+
+            HttpEntity<Map<String, Object>> entity = new HttpEntity<>(requestBody, headers);
+
+            // 构建完整的API URL
+            String apiUrl = baseUrl;
+            if (!apiUrl.endsWith("/chat/completions")) {
+                if (!apiUrl.endsWith("/")) {
+                    apiUrl += "/";
+                }
+                apiUrl += "chat/completions";
+            }
+
+            ResponseEntity<String> response = restTemplate.exchange(
+                    apiUrl, HttpMethod.POST, entity, String.class);
+
+            if (response.getStatusCode().is2xxSuccessful()) {
+                JSONObject responseJson = JSONUtil.parseObj(response.getBody());
+                JSONArray choices = responseJson.getJSONArray("choices");
+                if (choices != null && choices.size() > 0) {
+                    JSONObject choice = choices.getJSONObject(0);
+                    JSONObject messageObj = choice.getJSONObject("message");
+                    return messageObj.getStr("content");
+                }
+            } else {
+                log.error("LLM API调用失败，状态码：{}，响应：{}", response.getStatusCode(), response.getBody());
+            }
+        } catch (Exception e) {
+            log.error("调用LLM服务生成总结时发生异常，modelId: {}", modelId, e);
+        }
+
+        return "生成总结失败，请稍后重试";
+    }
+
+    @Override
+    public boolean isAvailable() {
+        try {
+            ModelConfigEntity defaultLLMConfig = getDefaultLLMConfig();
+            if (defaultLLMConfig == null || defaultLLMConfig.getConfigJson() == null) {
+                return false;
+            }
+
+            JSONObject configJson = defaultLLMConfig.getConfigJson();
+            String baseUrl = configJson.getStr("base_url");
+            String apiKey = configJson.getStr("api_key");
+
+            return baseUrl != null && !baseUrl.trim().isEmpty() &&
+                    apiKey != null && !apiKey.trim().isEmpty();
+        } catch (Exception e) {
+            log.error("检查LLM服务可用性时发生异常：", e);
+            return false;
+        }
+    }
+
+    @Override
+    public boolean isAvailable(String modelId) {
+        try {
+            if (modelId == null || modelId.trim().isEmpty()) {
+                return isAvailable();
+            }
+
+            // 通过具体模型ID获取配置
+            ModelConfigEntity modelConfig = modelConfigService.getModelByIdFromCache(modelId);
+            if (modelConfig == null || modelConfig.getConfigJson() == null) {
+                log.warn("未找到指定的LLM模型配置，modelId: {}", modelId);
+                return false;
+            }
+
+            JSONObject configJson = modelConfig.getConfigJson();
+            String baseUrl = configJson.getStr("base_url");
+            String apiKey = configJson.getStr("api_key");
+
+            return baseUrl != null && !baseUrl.trim().isEmpty() &&
+                    apiKey != null && !apiKey.trim().isEmpty();
+        } catch (Exception e) {
+            log.error("检查LLM服务可用性时发生异常，modelId: {}", modelId, e);
+            return false;
+        }
+    }
+
+    /**
+     * 从智控台获取默认的LLM模型配置
+     */
+    private ModelConfigEntity getDefaultLLMConfig() {
+        try {
+            // 获取所有启用的LLM模型配置
+            List<ModelConfigEntity> llmConfigs = modelConfigService.getEnabledModelsByType("LLM");
+            if (llmConfigs == null || llmConfigs.isEmpty()) {
+                return null;
+            }
+
+            // 优先返回默认配置，如果没有默认配置则返回第一个启用的配置
+            for (ModelConfigEntity config : llmConfigs) {
+                if (config.getIsDefault() != null && config.getIsDefault() == 1) {
+                    return config;
+                }
+            }
+
+            return llmConfigs.get(0);
+        } catch (Exception e) {
+            log.error("获取LLM模型配置时发生异常：", e);
+            return null;
+        }
+    }
+}

main/manager-api/src/main/java/xiaozhi/modules/model/dto/ModelConfigBodyDTO.java

@@ -13,9 +13,9 @@ public class ModelConfigBodyDTO {
     @Serial
     private static final long serialVersionUID = 1L;
 
-    // @Schema(description = "模型类型(Memory/ASR/VAD/LLM/TTS)")
-    // private String modelType;
-    //
+    @Schema(description = "模型ID,未填写将自动生成")
+    private String id;
+
     @Schema(description = "模型编码(如AliLLM、DoubaoTTS)")
     private String modelCode;
 

main/manager-api/src/main/java/xiaozhi/modules/model/dto/VoiceDTO.java

@@ -19,4 +19,15 @@ public class VoiceDTO implements Serializable {
 
     @Schema(description = "音色名称")
     private String name;
+
+    @Schema(description = "音频播放地址")
+    private String voiceDemo;
+
+    // 添加双参数构造函数，保持向后兼容
+    public VoiceDTO(String id, String name) {
+        this.id = id;
+        this.name = name;
+        this.voiceDemo = null;
+    }
+
 }

main/manager-api/src/main/java/xiaozhi/modules/model/entity/ModelConfigEntity.java

@@ -3,9 +3,7 @@ package xiaozhi.modules.model.entity;
 import java.util.Date;
 
 import com.baomidou.mybatisplus.annotation.FieldFill;
-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;
 
@@ -18,7 +16,6 @@ import lombok.Data;
 @Schema(description = "模型配置表")
 public class ModelConfigEntity {
 
-    @TableId(type = IdType.ASSIGN_UUID)
     @Schema(description = "主键")
     private String id;
 

main/manager-api/src/main/java/xiaozhi/modules/model/service/ModelConfigService.java

@@ -55,4 +55,12 @@ public interface ModelConfigService extends BaseService<ModelConfigEntity> {
      * @return TTS平台列表(id和modelName)
      */
     List<Map<String, Object>> getTtsPlatformList();
+
+    /**
+     * 根据模型类型获取所有启用的模型配置
+     *
+     * @param modelType 模型类型（如：LLM, TTS, ASR等）
+     * @return 启用的模型配置列表
+     */
+    List<ModelConfigEntity> getEnabledModelsByType(String modelType);
 }

main/manager-api/src/main/java/xiaozhi/modules/model/service/impl/ModelConfigServiceImpl.java

@@ -11,6 +11,7 @@ import org.springframework.stereotype.Service;
 
 import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
 import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
+import com.baomidou.mybatisplus.core.incrementer.DefaultIdentifierGenerator;
 import com.baomidou.mybatisplus.core.metadata.IPage;
 import com.baomidou.mybatisplus.core.metadata.OrderItem;
 import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
@@ -252,6 +253,12 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
         if (modelConfigBodyDTO == null) {
             throw new RenException(ErrorCode.PARAMS_GET_ERROR);
         }
+        if (StringUtils.isBlank(modelConfigBodyDTO.getId())) {
+            // 参照 MP @TableId AutoUUID 策略使用
+            // com.baomidou.mybatisplus.core.incrementer.DefaultIdentifierGenerator(UUID.replace("-",""))
+            // 进行分配默认模型ID
+            modelConfigBodyDTO.setId(DefaultIdentifierGenerator.getInstance().nextUUID(ModelConfigEntity.class));
+        }
     }
 
     /**
@@ -495,4 +502,22 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
     public List<Map<String, Object>> getTtsPlatformList() {
         return modelConfigDao.getTtsPlatformList();
     }
+
+    /**
+     * 根据模型类型获取所有启用的模型配置
+     */
+    @Override
+    public List<ModelConfigEntity> getEnabledModelsByType(String modelType) {
+        if (StringUtils.isBlank(modelType)) {
+            return null;
+        }
+
+        List<ModelConfigEntity> entities = modelConfigDao.selectList(
+                new QueryWrapper<ModelConfigEntity>()
+                        .eq("model_type", modelType)
+                        .eq("is_enabled", 1)
+                        .orderByAsc("sort"));
+
+        return entities;
+    }
 }

main/manager-api/src/main/java/xiaozhi/modules/model/service/impl/ModelProviderServiceImpl.java

@@ -22,6 +22,8 @@ import xiaozhi.common.page.PageData;
 import xiaozhi.common.service.impl.BaseServiceImpl;
 import xiaozhi.common.user.UserDetail;
 import xiaozhi.common.utils.ConvertUtils;
+import xiaozhi.modules.knowledge.dao.KnowledgeBaseDao;
+import xiaozhi.modules.knowledge.entity.KnowledgeBaseEntity;
 import xiaozhi.modules.model.dao.ModelProviderDao;
 import xiaozhi.modules.model.dto.ModelProviderDTO;
 import xiaozhi.modules.model.entity.ModelProviderEntity;
@@ -34,13 +36,43 @@ public class ModelProviderServiceImpl extends BaseServiceImpl<ModelProviderDao,
         implements ModelProviderService {
 
     private final ModelProviderDao modelProviderDao;
+    private final KnowledgeBaseDao knowledgeBaseDao;
 
     @Override
     public List<ModelProviderDTO> getPluginList() {
+        // 1. 获取插件列表
         LambdaQueryWrapper<ModelProviderEntity> queryWrapper = new LambdaQueryWrapper<>();
         queryWrapper.eq(ModelProviderEntity::getModelType, "Plugin");
         List<ModelProviderEntity> providerEntities = modelProviderDao.selectList(queryWrapper);
-        return ConvertUtils.sourceToTarget(providerEntities, ModelProviderDTO.class);
+        List<ModelProviderDTO> resultList = ConvertUtils.sourceToTarget(providerEntities, ModelProviderDTO.class);
+
+        // 2. 获取当前用户的知识库列表并追加到结果中
+        UserDetail userDetail = SecurityUser.getUser();
+        if (userDetail != null && userDetail.getId() != null) {
+            // 查询当前用户的知识库
+            LambdaQueryWrapper<KnowledgeBaseEntity> kbQueryWrapper = new LambdaQueryWrapper<>();
+            kbQueryWrapper.eq(KnowledgeBaseEntity::getCreator, userDetail.getId());
+            kbQueryWrapper.eq(KnowledgeBaseEntity::getStatus, 1); // 只获取启用状态的知识库
+            List<KnowledgeBaseEntity> knowledgeBases = knowledgeBaseDao.selectList(kbQueryWrapper);
+
+            // 将知识库转换为ModelProviderDTO格式并添加到结果列表
+            for (KnowledgeBaseEntity kb : knowledgeBases) {
+                ModelProviderDTO dto = new ModelProviderDTO();
+                dto.setId(kb.getId());
+                dto.setModelType("Rag");
+                dto.setName("[知识库]" + kb.getName());
+                dto.setProviderCode("ragflow"); // 假设所有RAG都使用ragflow
+                dto.setFields("[]");
+                dto.setSort(0);
+                dto.setCreateDate(kb.getCreatedAt());
+                dto.setUpdateDate(kb.getUpdatedAt());
+                dto.setCreator(0L);
+                dto.setUpdater(0L);
+                resultList.add(dto);
+            }
+        }
+
+        return resultList;
     }
 
     @Override

main/manager-api/src/main/java/xiaozhi/modules/security/config/ShiroConfig.java

@@ -89,7 +89,7 @@ public class ShiroConfig {
         filterMap.put("/config/**", "server");
         filterMap.put("/agent/chat-history/report", "server");
         filterMap.put("/agent/chat-history/download/**", "anon");
-        filterMap.put("/agent/saveMemory/**", "server");
+        filterMap.put("/agent/chat-summary/**", "server");
         filterMap.put("/agent/play/**", "anon");
         filterMap.put("/voiceClone/play/**", "anon");
         filterMap.put("/**", "oauth2");

main/manager-api/src/main/java/xiaozhi/modules/security/config/WebMvcConfig.java

@@ -100,7 +100,7 @@ public class WebMvcConfig implements WebMvcConfigurer {
         converter.setObjectMapper(mapper);
         return converter;
     }
-    
+
     /**
      * 国际化配置 - 根据请求头中的Accept-Language设置语言环境
      */
@@ -113,14 +113,14 @@ public class WebMvcConfig implements WebMvcConfigurer {
                 if (acceptLanguage == null || acceptLanguage.isEmpty()) {
                     return Locale.getDefault();
                 }
-                
+
                 // 解析Accept-Language请求头中的首选语言
                 String[] languages = acceptLanguage.split(",");
                 if (languages.length > 0) {
                     // 提取第一个语言代码，去除可能的质量值(q=...)
                     String[] parts = languages[0].split(";" + "\\s*");
                     String primaryLanguage = parts[0].trim();
-                     
+
                     // 根据前端发送的语言代码直接创建Locale对象
                     if (primaryLanguage.equals("zh-CN")) {
                         return Locale.SIMPLIFIED_CHINESE;
@@ -128,15 +128,25 @@ public class WebMvcConfig implements WebMvcConfigurer {
                         return Locale.TRADITIONAL_CHINESE;
                     } else if (primaryLanguage.equals("en-US")) {
                         return Locale.US;
+                    } else if (primaryLanguage.equals("de-DE")) {
+                        return Locale.GERMANY;
+                    } else if (primaryLanguage.equals("vi-VN")) {
+                        return Locale.forLanguageTag("vi-VN");
                     } else if (primaryLanguage.startsWith("zh")) {
                         // 对于其他中文变体，默认使用简体中文
                         return Locale.SIMPLIFIED_CHINESE;
                     } else if (primaryLanguage.startsWith("en")) {
                         // 对于其他英文变体，默认使用美式英语
                         return Locale.US;
+                    } else if (primaryLanguage.startsWith("de")) {
+                        // 对于其他德语变体，默认使用德语
+                        return Locale.GERMANY;
+                    } else if (primaryLanguage.startsWith("vi")) {
+                        // 对于其他越南语变体，默认使用越南语
+                        return Locale.forLanguageTag("vi-VN");
                     }
                 }
-                
+
                 // 如果没有匹配的语言，使用默认语言
                 return Locale.getDefault();
             }

main/manager-api/src/main/java/xiaozhi/modules/security/controller/LoginController.java

@@ -6,6 +6,7 @@ import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 
+import org.apache.commons.lang3.StringUtils;
 import org.springframework.web.bind.annotation.GetMapping;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.PutMapping;
@@ -23,7 +24,9 @@ import xiaozhi.common.exception.ErrorCode;
 import xiaozhi.common.exception.RenException;
 import xiaozhi.common.page.TokenDTO;
 import xiaozhi.common.user.UserDetail;
+import xiaozhi.common.utils.JsonUtils;
 import xiaozhi.common.utils.Result;
+import xiaozhi.common.utils.Sm2DecryptUtil;
 import xiaozhi.common.validator.AssertUtils;
 import xiaozhi.common.validator.ValidatorUtils;
 import xiaozhi.modules.security.dto.LoginDTO;
@@ -32,8 +35,6 @@ import xiaozhi.modules.security.password.PasswordUtils;
 import xiaozhi.modules.security.service.CaptchaService;
 import xiaozhi.modules.security.service.SysUserTokenService;
 import xiaozhi.modules.security.user.SecurityUser;
-import xiaozhi.common.utils.Sm2DecryptUtil;
-import org.apache.commons.lang3.StringUtils;
 import xiaozhi.modules.sys.dto.PasswordDTO;
 import xiaozhi.modules.sys.dto.RetrievePasswordDTO;
 import xiaozhi.modules.sys.dto.SysUserDTO;
@@ -89,13 +90,13 @@ public class LoginController {
     @Operation(summary = "登录")
     public Result<TokenDTO> login(@RequestBody LoginDTO login) {
         String password = login.getPassword();
-        
+
         // 使用工具类解密并验证验证码
         String actualPassword = Sm2DecryptUtil.decryptAndValidateCaptcha(
                 password, login.getCaptchaId(), captchaService, sysParamsService);
-        
+
         login.setPassword(actualPassword);
-        
+
         // 按照用户名获取用户
         SysUserDTO userDTO = sysUserService.getByUsername(login.getUsername());
         // 判断用户是否存在
@@ -108,8 +109,6 @@ public class LoginController {
         }
         return sysUserTokenService.createToken(userDTO.getId());
     }
-    
-
 
     @PostMapping("/register")
     @Operation(summary = "注册")
@@ -117,15 +116,15 @@ public class LoginController {
         if (!sysUserService.getAllowUserRegister()) {
             throw new RenException(ErrorCode.USER_REGISTER_DISABLED);
         }
-        
+
         String password = login.getPassword();
-        
+
         // 使用工具类解密并验证验证码
         String actualPassword = Sm2DecryptUtil.decryptAndValidateCaptcha(
                 password, login.getCaptchaId(), captchaService, sysParamsService);
-        
+
         login.setPassword(actualPassword);
-        
+
         // 是否开启手机注册
         Boolean isMobileRegister = sysParamsService
                 .getValueObject(Constant.SysMSMParam.SERVER_ENABLE_MOBILE_REGISTER.getValue(), Boolean.class);
@@ -204,11 +203,11 @@ public class LoginController {
         }
 
         String password = dto.getPassword();
-        
+
         // 使用工具类解密并验证验证码
         String actualPassword = Sm2DecryptUtil.decryptAndValidateCaptcha(
                 password, dto.getCaptchaId(), captchaService, sysParamsService);
-        
+
         dto.setPassword(actualPassword);
 
         sysUserService.changePasswordDirectly(userDTO.getId(), dto.getPassword());
@@ -229,7 +228,7 @@ public class LoginController {
         config.put("beianIcpNum", sysParamsService.getValue(Constant.SysBaseParam.BEIAN_ICP_NUM.getValue(), true));
         config.put("beianGaNum", sysParamsService.getValue(Constant.SysBaseParam.BEIAN_GA_NUM.getValue(), true));
         config.put("name", sysParamsService.getValue(Constant.SysBaseParam.SERVER_NAME.getValue(), true));
-        
+
         // SM2公钥
         String publicKey = sysParamsService.getValue(Constant.SM2_PUBLIC_KEY, true);
         if (StringUtils.isBlank(publicKey)) {
@@ -237,6 +236,12 @@ public class LoginController {
         }
         config.put("sm2PublicKey", publicKey);
 
+        // 获取system-web.menu参数配置
+        String menuConfig = sysParamsService.getValue("system-web.menu", true);
+        if (StringUtils.isNotBlank(menuConfig)) {
+            config.put("systemWebMenu", JsonUtils.parseObject(menuConfig, Object.class));
+        }
+
         return new Result<Map<String, Object>>().ok(config);
     }
 }

main/manager-api/src/main/java/xiaozhi/modules/sys/controller/ServerSideManageController.java

@@ -31,6 +31,8 @@ import xiaozhi.modules.sys.dto.ServerActionResponseDTO;
 import xiaozhi.modules.sys.enums.ServerActionEnum;
 import xiaozhi.modules.sys.service.SysParamsService;
 import xiaozhi.modules.sys.utils.WebSocketClientManager;
+import xiaozhi.modules.device.service.DeviceService;
+import xiaozhi.common.redis.RedisUtils;
 
 /**
  * 服务端管理控制器
@@ -41,6 +43,8 @@ import xiaozhi.modules.sys.utils.WebSocketClientManager;
 @AllArgsConstructor
 public class ServerSideManageController {
     private final SysParamsService sysParamsService;
+    private final DeviceService deviceService;
+    private final RedisUtils redisUtils;
     private static final ObjectMapper objectMapper;
     static {
         objectMapper = new ObjectMapper();
@@ -85,9 +89,22 @@ public class ServerSideManageController {
             return false;
         }
         String serverSK = sysParamsService.getValue(Constant.SERVER_SECRET, true);
+
+        String deviceId = UUID.randomUUID().toString();
+        String clientId = UUID.randomUUID().toString();
+
+        String redisKey = xiaozhi.common.redis.RedisKeys.getTmpRegisterMacKey(deviceId);
+        redisUtils.set(redisKey, "true", 300); // 5分钟有效期
+
         WebSocketHttpHeaders headers = new WebSocketHttpHeaders();
-        headers.add("device-id", UUID.randomUUID().toString());
-        headers.add("client-id", UUID.randomUUID().toString());
+        headers.add("device-id", deviceId);
+        headers.add("client-id", clientId);
+        try {
+            String token = deviceService.generateWebSocketToken(clientId, deviceId);
+            headers.add("authorization", "Bearer " + token);
+        } catch (Exception e) {
+            throw new RenException(ErrorCode.WEB_SOCKET_CONNECT_FAILED);
+        }
 
         try (WebSocketClientManager client = new WebSocketClientManager.Builder()
                 .connectTimeout(3, TimeUnit.SECONDS)

main/manager-api/src/main/java/xiaozhi/modules/sys/controller/SysParamsController.java

@@ -174,7 +174,7 @@ public class SysParamsController {
             return;
         }
         if (StringUtils.isBlank(url) || url.equals("null")) {
-            throw new RenException(ErrorCode.OTA_URL_EMPTY);
+            return;
         }
 
         // 检查是否包含localhost或127.0.0.1
@@ -211,7 +211,7 @@ public class SysParamsController {
             return;
         }
         if (StringUtils.isBlank(url) || url.equals("null")) {
-            throw new RenException(ErrorCode.MCP_URL_EMPTY);
+            return;
         }
         if (url.contains("localhost") || url.contains("127.0.0.1")) {
             throw new RenException(ErrorCode.MCP_URL_LOCALHOST);
@@ -242,7 +242,7 @@ public class SysParamsController {
             return;
         }
         if (StringUtils.isBlank(url) || url.equals("null")) {
-            throw new RenException(ErrorCode.VOICEPRINT_URL_EMPTY);
+            return;
         }
         if (url.contains("localhost") || url.contains("127.0.0.1")) {
             throw new RenException(ErrorCode.VOICEPRINT_URL_LOCALHOST);

main/manager-api/src/main/java/xiaozhi/modules/timbre/service/impl/TimbreServiceImpl.java

@@ -133,7 +133,11 @@ public class TimbreServiceImpl extends BaseServiceImpl<TimbreDao, TimbreEntity>
             timbreEntities = new ArrayList<>();
         }
         List<VoiceDTO> voiceDTOs = timbreEntities.stream()
-                .map(entity -> new VoiceDTO(entity.getId(), entity.getName()))
+                .map(entity -> {
+                    VoiceDTO dto = new VoiceDTO(entity.getId(), entity.getName());
+                    dto.setVoiceDemo(entity.getVoiceDemo());
+                    return dto;
+                })
                 .collect(Collectors.toList());
 
         // 获取当前登录用户ID
@@ -146,6 +150,8 @@ public class TimbreServiceImpl extends BaseServiceImpl<TimbreDao, TimbreEntity>
                 VoiceDTO voiceDTO = new VoiceDTO();
                 voiceDTO.setId(entity.getId());
                 voiceDTO.setName(MessageUtils.getMessage(ErrorCode.VOICE_CLONE_PREFIX) + entity.getName());
+                // 保留从数据库查询到的voiceDemo字段
+                voiceDTO.setVoiceDemo(entity.getVoiceDemo());
                 redisUtils.set(RedisKeys.getTimbreNameById(voiceDTO.getId()), voiceDTO.getName(),
                         RedisUtils.NOT_EXPIRE);
                 voiceDTOs.add(0, voiceDTO);
@@ -205,6 +211,9 @@ public class TimbreServiceImpl extends BaseServiceImpl<TimbreDao, TimbreEntity>
         if (list.isEmpty()) {
             return null;
         }
-        return new VoiceDTO(list.get(0).getId(), list.get(0).getName());
+        TimbreEntity entity = list.get(0);
+        VoiceDTO dto = new VoiceDTO(entity.getId(), entity.getName());
+        dto.setVoiceDemo(entity.getVoiceDemo());
+        return dto;
     }
 }

main/manager-api/src/main/java/xiaozhi/modules/voiceclone/controller/VoiceCloneController.java

@@ -107,10 +107,10 @@ public class VoiceCloneController {
             String name = params.get("name");
 
             if (id == null || id.isEmpty()) {
-                return new Result<String>().error(ErrorCode.IDENTIFIER_NOT_NULL, "唯一标识不能为空");
+                return new Result<String>().error(ErrorCode.IDENTIFIER_NOT_NULL);
             }
-            if (name == null) {
-                return new Result<String>().error(ErrorCode.NOT_NULL, "名称不能为空");
+            if (name == null || name.isEmpty()) {
+                return new Result<String>().error(ErrorCode.VOICE_CLONE_NAME_NOT_NULL);
             }
             // 检查权限
             checkPermission(id);
@@ -119,7 +119,7 @@ public class VoiceCloneController {
             redisUtils.delete(RedisKeys.getTimbreNameById(id));
             return new Result<String>();
         } catch (Exception e) {
-            return new Result<String>().error(ErrorCode.UPDATE_DATA_FAILED, "更新失败: " + e.getMessage());
+            return new Result<String>().error(ErrorCode.UPDATE_DATA_FAILED, e.getMessage());
         }
     }
 
@@ -131,7 +131,7 @@ public class VoiceCloneController {
         checkPermission(id);
         byte[] audioData = voiceCloneService.getVoiceData(id);
         if (audioData == null) {
-            return new Result<String>().error(ErrorCode.RESOURCE_NOT_FOUND, "音频不存在");
+            return new Result<String>().error(ErrorCode.VOICE_CLONE_AUDIO_NOT_FOUND);
         }
         String uuid = UUID.randomUUID().toString();
         redisUtils.set(RedisKeys.getVoiceCloneAudioIdKey(uuid), id);

main/manager-api/src/main/java/xiaozhi/modules/voiceclone/service/impl/VoiceCloneServiceImpl.java

@@ -100,7 +100,7 @@ public class VoiceCloneServiceImpl extends BaseServiceImpl<VoiceCloneDao, VoiceC
             wrapper.eq("model_id", dto.getModelId());
             Long count = baseDao.selectCount(wrapper);
             if (count > 0) {
-                throw new RenException(ErrorCode.VOICE_ID_ALREADY_EXISTS, "音色ID " + voiceId + " 已存在");
+                throw new RenException(ErrorCode.VOICE_ID_ALREADY_EXISTS);
             }
         }
 
@@ -164,6 +164,9 @@ public class VoiceCloneServiceImpl extends BaseServiceImpl<VoiceCloneDao, VoiceC
         if (entity.getUserId() != null) {
             dto.setUserName(sysUserService.getByUserId(entity.getUserId()).getUsername());
         }
+        
+        // 确保trainStatus字段被正确设置，前端需要这个字段来判断是否为克隆音频
+        dto.setTrainStatus(entity.getTrainStatus());
 
         return dto;
     }
@@ -197,6 +200,9 @@ public class VoiceCloneServiceImpl extends BaseServiceImpl<VoiceCloneDao, VoiceC
             if (entity.getUserId() != null) {
                 dto.setUserName(sysUserService.getByUserId(entity.getUserId()).getUsername());
             }
+            
+            // 确保trainStatus字段被正确设置，前端需要这个字段来判断是否为克隆音频
+            dto.setTrainStatus(entity.getTrainStatus());
 
             // 设置是否有音频数据
             dto.setHasVoice(entity.getVoice() != null);

main/manager-api/src/main/resources/db/changelog/202510250956.sql

@@ -0,0 +1,24 @@
+-- 添加RAG模型供应器和配置
+-- -------------------------------------------------------
+
+-- 添加RAG模型供应器
+delete from `ai_model_provider` where id = 'SYSTEM_RAG_ragflow';
+INSERT INTO `ai_model_provider` (`id`, `model_type`, `provider_code`, `name`, `fields`, `sort`, `creator`, `create_date`, `updater`, `update_date`) VALUES
+('SYSTEM_RAG_ragflow', 'RAG', 'ragflow', 'RAGFlow', '[{"key": "base_url", "type": "string", "label": "服务地址"}, {"key": "api_key", "type": "string", "label": "API密钥"}]', 1, 1, NOW(), 1, NOW());
+
+-- 添加RAG模型配置
+delete from `ai_model_config` where id = 'RAG_RAGFlow';
+INSERT INTO `ai_model_config` VALUES ('RAG_RAGFlow', 'RAG', 'ragflow', 'RAGFlow', 1, 1, '{"type": "ragflow", "base_url": "http://localhost", "api_key": "你的RAG密钥"}', 'https://github.com/infiniflow/ragflow/blob/main/README_zh.md', 'RAGFlow配置说明：
+一、快速部署教程（docker部署）
+1.$ sysctl vm.max_map_count
+2.$ sysctl -w vm.max_map_count=262144
+3.$ git clone https://github.com/infiniflow/ragflow.git
+4.docker compose -f docker-compose.yml up -d
+5.$ docker logs -f docker-ragflow-cpu-1
+6.注冊登录后，点击右上角头像，获得RAGFlow的API KEY和API服务器地址。使用RAGFlow前请在Model Provider中添加模型和设置默认模型。
+二、如果您希望关掉注册功能
+1.停止服务   docker compose down
+2. sed -i ''s/REGISTER_ENABLED=1/REGISTER_ENABLED=0/g'' .env   
+3.cat .env | grep -i register
+4.看到REGISTER_ENABLED=0 重启服务即可。',  1, NULL, NULL, NULL, NULL);
+

main/manager-api/src/main/resources/db/changelog/202510251150.sql

@@ -0,0 +1,19 @@
+-- 知识库表
+DROP TABLE IF EXISTS `ai_rag_dataset`;
+CREATE TABLE `ai_rag_dataset` (
+    `id` VARCHAR(32) NOT NULL COMMENT '唯一标识',
+    `dataset_id` VARCHAR(64) NOT NULL COMMENT '知识库ID',
+    `rag_model_id` VARCHAR(64) COMMENT 'RAG模型配置ID',
+    `name` VARCHAR(100) NOT NULL COMMENT '知识库名称',
+    `description` TEXT COMMENT '知识库描述',
+    `status` TINYINT(1) DEFAULT 1 COMMENT '状态：0停用 1启用',
+    `creator` BIGINT COMMENT '创建者',
+    `created_at` DATETIME COMMENT '创建时间',
+    `updater` BIGINT COMMENT '更新者',
+    `updated_at` DATETIME COMMENT '更新时间',
+    PRIMARY KEY (`id`),
+    UNIQUE KEY `uk_dataset_id` (`dataset_id`),
+    INDEX `idx_ai_rag_dataset_status` (`status`),
+    INDEX `idx_ai_rag_dataset_creator` (`creator`),
+    INDEX `idx_ai_rag_dataset_created_at` (`created_at`)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='知识库表';

main/manager-api/src/main/resources/db/changelog/202511131023.sql

@@ -0,0 +1,62 @@
+UPDATE `ai_model_config` SET 
+`doc_link` = 'https://github.com/infiniflow/ragflow/blob/main/README_zh.md',
+`remark` = '详细部署教程参考：https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docs/ragflow-integration.md
+部署成功，注冊登录后，点击右上角头像，获得RAGFlow的API KEY和API服务器地址。使用RAGFlow前请在Model Provider中添加模型和设置默认模型。' WHERE `id` = 'RAG_RAGFlow';
+
+update `ai_model_config` set `model_name` = '外挂的大模型意图识别' where `id` = 'Intent_intent_llm';
+update `ai_model_config` set `model_name` = '大模型自主函数调用' where `id` = 'Intent_function_call';
+update `ai_model_config` set `model_name` = '百炼智能体应用' where `id` = 'LLM_AliAppLLM';
+
+update `ai_model_provider` set `name` = '外挂的大模型意图识别' , `fields` =  '[{"key":"llm","label":"引用的LLM模型","type":"string"}]' where  id = 'SYSTEM_Intent_intent_llm';
+update `ai_model_provider` set `name` = '大模型自主函数调用' where  id = 'SYSTEM_Intent_function_call';
+
+UPDATE ai_model_config set model_name = 'Linkerai(流式)' where id = 'TTS_LinkeraiTTS';
+UPDATE ai_model_config set model_name = '火山引擎(流式)' where id = 'TTS_HuoshanDoubleStreamTTS';
+UPDATE ai_model_config set model_name = '阿里百炼(流式)' where id = 'TTS_AliBLStreamTTS';
+UPDATE ai_model_config set model_name = '科大讯飞(流式)' where id = 'TTS_XunFeiStreamTTS';
+UPDATE ai_model_config set model_name = 'Minimax(流式)' where id = 'TTS_MinimaxStreamTTS';
+UPDATE ai_model_config set model_name = '阿里云(流式)' where id = 'TTS_AliyunStreamTTS';
+UPDATE ai_model_config set model_name = 'PaddleSpeech(流式)' where id = 'TTS_PaddleSpeechTTS';
+UPDATE ai_model_config set model_name = 'IndexTTS(流式)' where id = 'TTS_IndexStreamTTS';
+
+update ai_model_config SET sort = 2 where id = 'TTS_LinkeraiTTS';
+update ai_model_config SET sort = 3 where id = 'TTS_HuoshanDoubleStreamTTS';
+update ai_model_config SET sort = 4 where id = 'TTS_AliBLStreamTTS';
+update ai_model_config SET sort = 5 where id = 'TTS_XunFeiStreamTTS';
+update ai_model_config SET sort = 6 where id = 'TTS_MinimaxStreamTTS';
+update ai_model_config SET sort = 7 where id = 'TTS_AliyunStreamTTS';
+update ai_model_config SET sort = 8 where id = 'TTS_IndexStreamTTS';
+update ai_model_config SET sort = 9 where id = 'TTS_PaddleSpeechTTS';
+update ai_model_config SET sort = 10 where id = 'TTS_DoubaoTTS';
+update ai_model_config SET sort = 11 where id = 'TTS_TencentTTS';
+update ai_model_config SET sort = 12 where id = 'TTS_AliyunTTS';
+update ai_model_config SET sort = 13 where id = 'TTS_OpenAITTS';
+update ai_model_config SET sort = 14 where id = 'TTS_CosyVoiceSiliconflow';
+update ai_model_config SET sort = 15 where id = 'TTS_CozeCnTTS';
+update ai_model_config SET sort = 16 where id = 'TTS_FishSpeech';
+update ai_model_config SET sort = 17 where id = 'TTS_GPT_SOVITS_V3';
+update ai_model_config SET sort = 18 where id = 'TTS_GPT_SOVITS_V2';
+update ai_model_config SET sort = 19 where id = 'TTS_TTS302AI';
+update ai_model_config SET sort = 20 where id = 'TTS_GizwitsTTS';
+update ai_model_config SET sort = 21 where id = 'TTS_VolcesAiGatewayTTS';
+update ai_model_config SET sort = 22 where id = 'TTS_ACGNTTS';
+update ai_model_config SET sort = 23 where id = 'TTS_CustomTTS';
+
+UPDATE ai_model_config set model_name = '讯飞语音识别(流式)' where id = 'ASR_XunfeiStream';
+UPDATE ai_model_config set model_name = 'Qwen3Flash语音识别' where id = 'ASR_Qwen3Flash';
+
+update ai_model_config SET sort = 2 where id = 'ASR_FunASRServer';
+update ai_model_config SET sort = 3 where id = 'ASR_XunfeiStream';
+update ai_model_config SET sort = 4 where id = 'ASR_AliyunStreamASR';
+update ai_model_config SET sort = 5 where id = 'ASR_DoubaoStreamASR';
+update ai_model_config SET sort = 6 where id = 'ASR_TencentASR';
+update ai_model_config SET sort = 7 where id = 'ASR_BaiduASR';
+update ai_model_config SET sort = 8 where id = 'ASR_DoubaoASR';
+update ai_model_config SET sort = 9 where id = 'ASR_AliyunASR';
+update ai_model_config SET sort = 10 where id = 'ASR_SherpaASR';
+update ai_model_config SET sort = 11 where id = 'ASR_OpenaiASR';
+update ai_model_config SET sort = 12 where id = 'ASR_GroqASR';
+update ai_model_config SET sort = 13 where id = 'ASR_VoskASR';
+update ai_model_config SET sort = 14 where id = 'ASR_Qwen3Flash';
+
+UPDATE ai_model_config SET config_json='{\"type\": \"openai\", \"base_url\": \"https://ark.cn-beijing.volces.com/api/v3\", \"model_name\": \"doubao-1-5-pro-32k-250115\", \"api_key\": \"你的api_key\"}' where id = 'LLM_DoubaoLLM' AND config_json LIKE '%你的api_key"%';

main/manager-api/src/main/resources/db/changelog/202511221450.sql

@@ -0,0 +1,17 @@
+-- 更新HuoshanDoubleStreamTTS供应器配置，增加开启链接复用选项
+UPDATE `ai_model_provider`
+SET fields = '[{"key": "ws_url", "type": "string", "label": "WebSocket地址"}, {"key": "appid", "type": "string", "label": "应用ID"}, {"key": "access_token", "type": "string", "label": "访问令牌"}, {"key": "resource_id", "type": "string", "label": "资源ID"}, {"key": "speaker", "type": "string", "label": "默认音色"}, {"key": "enable_ws_reuse", "type": "boolean", "label": "是否开启链接复用", "default": true}, {"key": "speech_rate", "type": "number", "label": "语速(-50~100)"}, {"key": "loudness_rate", "type": "number", "label": "音量(-50~100)"}, {"key": "pitch", "type": "number", "label": "音高(-12~12)"}]'
+WHERE id = 'SYSTEM_TTS_HSDSTTS';
+
+UPDATE `ai_model_config` SET 
+`doc_link` = 'https://console.volcengine.com/speech/service/10007',
+`remark` = '火山引擎语音合成服务配置说明：
+1. 访问 https://www.volcengine.com/ 注册并开通火山引擎账号
+2. 访问 https://console.volcengine.com/speech/service/10007 开通语音合成大模型，购买音色
+3. 在页面底部获取appid和access_token
+5. 资源ID固定为：volc.service_type.10029（大模型语音合成及混音）
+6. 链接复用：开启WebSocket连接复用，默认true减少链接损耗（注意：复用后设备处于聆听状态时空闲链接会占并发数）
+7. 语速：-50~100，可不填，正常默认值0，可填-50~100
+8. 音量：-50~100，可不填，正常默认值0，可填-50~100
+9. 音高：-12~12，可不填，正常默认值0，可填-12~12
+10. 填入配置文件中' WHERE `id` = 'TTS_HuoshanDoubleStreamTTS';

main/manager-api/src/main/resources/db/changelog/202512031517.sql

@@ -0,0 +1,6 @@
+-- 添加系统功能菜单配置参数
+delete from `sys_params` where param_code = 'system-web.menu';
+
+-- 添加系统功能菜单配置参数
+INSERT INTO `sys_params` (id, param_code, param_value, value_type, param_type, remark) VALUES 
+(600, 'system-web.menu', '{"features":{"voiceprintRecognition":{"name":"feature.voiceprintRecognition.name","enabled":false,"description":"feature.voiceprintRecognition.description"},"voiceClone":{"name":"feature.voiceClone.name","enabled":false,"description":"feature.voiceClone.description"},"knowledgeBase":{"name":"feature.knowledgeBase.name","enabled":false,"description":"feature.knowledgeBase.description"},"mcpAccessPoint":{"name":"feature.mcpAccessPoint.name","enabled":false,"description":"feature.mcpAccessPoint.description"},"vad":{"name":"feature.vad.name","enabled":true,"description":"feature.vad.description"},"asr":{"name":"feature.asr.name","enabled":true,"description":"feature.asr.description"}},"groups":{"featureManagement":["voiceprintRecognition","voiceClone","knowledgeBase","mcpAccessPoint"],"voiceManagement":["vad","asr"]}}', 'json', 1, '系统功能菜单配置');

main/manager-api/src/main/resources/db/changelog/202512041515.sql

@@ -0,0 +1,14 @@
+-- liquibase formatted sql
+
+-- changeset xiaozhi:202512041515
+CREATE TABLE ai_agent_context_provider (
+    id VARCHAR(32) NOT NULL COMMENT '主键',
+    agent_id VARCHAR(32) NOT NULL COMMENT '智能体ID',
+    context_providers JSON COMMENT '上下文源配置',
+    creator BIGINT COMMENT '创建者',
+    created_at DATETIME COMMENT '创建时间',
+    updater BIGINT COMMENT '更新者',
+    updated_at DATETIME COMMENT '更新时间',
+    PRIMARY KEY (id),
+    INDEX idx_agent_id (agent_id)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='智能体上下文源配置表';

main/manager-api/src/main/resources/db/changelog/202512131453.sql

@@ -0,0 +1,6 @@
+-- 删除server模块是否开启token认证参数
+delete from `sys_params` where param_code = 'server.auth.enabled';
+
+-- 添加server模块是否开启token认证参数
+INSERT INTO `sys_params` (id, param_code, param_value, value_type, param_type, remark) VALUES 
+(122, 'server.auth.enabled', 'true', 'boolean', 1, 'server模块是否开启token认证');

main/manager-api/src/main/resources/db/changelog/202512161529.sql

@@ -0,0 +1 @@
+INSERT INTO `sys_params` (id, param_code, param_value, value_type, param_type, remark) VALUES (311, 'enable_websocket_ping', 'false', 'boolean', 1, '是否启用WebSocket心跳保活机制');

main/manager-api/src/main/resources/db/changelog/202512192245.sql

@@ -0,0 +1,2 @@
+-- 为智能体聊天历史记录添加音频ID索引
+ALTER TABLE ai_agent_chat_history ADD INDEX idx_ai_agent_chat_history_audio_id (audio_id);

main/manager-api/src/main/resources/db/changelog/202512221117.sql

@@ -0,0 +1,10 @@
+-- 更新豆包流式ASR供应器，增加end_window_size配置
+delete from `ai_model_provider` where id = 'SYSTEM_ASR_DoubaoStreamASR';
+INSERT INTO `ai_model_provider` (`id`, `model_type`, `provider_code`, `name`, `fields`, `sort`, `creator`, `create_date`, `updater`, `update_date`) VALUES
+('SYSTEM_ASR_DoubaoStreamASR', 'ASR', 'doubao_stream', '火山引擎语音识别(流式)', '[{"key":"appid","label":"应用ID","type":"string"},{"key":"access_token","label":"访问令牌","type":"string"},{"key":"cluster","label":"集群","type":"string"},{"key":"boosting_table_name","label":"热词文件名称","type":"string"},{"key":"correct_table_name","label":"替换词文件名称","type":"string"},{"key":"output_dir","label":"输出目录","type":"string"},{"key":"end_window_size","label":"静音判定时长(ms)","type":"number"}]', 3, 1, NOW(), 1, NOW());
+
+
+-- 更新豆包流式ASR模型配置，增加end_window_size默认值
+UPDATE `ai_model_config` SET
+`config_json` = JSON_SET(`config_json`, '$.end_window_size', 200)
+WHERE `id` = 'ASR_DoubaoStreamASR' AND JSON_EXTRACT(`config_json`, '$.end_window_size') IS NULL;

main/manager-api/src/main/resources/db/changelog/202512301430.sql

@@ -0,0 +1,94 @@
+-- 添加阿里百炼Paraformer实时语音识别服务配置
+delete from `ai_model_provider` where id = 'SYSTEM_ASR_AliyunBLStream';
+INSERT INTO `ai_model_provider` (`id`, `model_type`, `provider_code`, `name`, `fields`, `sort`, `creator`, `create_date`, `updater`, `update_date`) VALUES
+('SYSTEM_ASR_AliyunBLStream', 'ASR', 'aliyunbl_stream', '阿里百炼Paraformer实时语音识别', '[{"key":"api_key","label":"API密钥","type":"password"},{"key":"model","label":"模型名称","type":"string"},{"key":"format","label":"音频格式","type":"string"},{"key":"sample_rate","label":"采样率","type":"number"},{"key":"output_dir","label":"输出目录","type":"string"}]', 18, 1, NOW(), 1, NOW());
+
+delete from `ai_model_config` where id = 'ASR_AliyunBLStream';
+INSERT INTO `ai_model_config` VALUES ('ASR_AliyunBLStream', 'ASR', 'AliyunBLStream', '阿里百炼Paraformer实时语音识别', 0, 1, '{"type": "aliyunbl_stream", "api_key": "", "model": "paraformer-realtime-v2", "format": "pcm", "sample_rate": 16000, "disfluency_removal_enabled": false, "semantic_punctuation_enabled": false, "max_sentence_silence": 200, "multi_threshold_mode_enabled": false, "punctuation_prediction_enabled": true, "inverse_text_normalization_enabled": true, "output_dir": "tmp/"}', 'https://help.aliyun.com/zh/model-studio/websocket-for-paraformer-real-time-service', '支持多语言、热词定制、语义断句等高级功能', 21, NULL, NULL, NULL, NULL);
+
+-- 更新阿里百炼Paraformer模型配置的说明文档
+UPDATE `ai_model_config` SET
+`doc_link` = 'https://help.aliyun.com/zh/model-studio/websocket-for-paraformer-real-time-service',
+`remark` = '阿里百炼Paraformer实时语音识别配置说明：
+1. 登录阿里云百炼平台 https://bailian.console.aliyun.com/
+2. 创建API-KEY https://bailian.console.aliyun.com/#/api-key
+3. 支持模型：paraformer-realtime-v2(推荐)、paraformer-realtime-8k-v2、paraformer-realtime-v1、paraformer-realtime-8k-v1
+4. 功能特性：
+   - 多语言支持(中文含方言、英文、日语、韩语、德语、法语、俄语)
+   - 热词定制(vocabulary_id参数)，详细说明请参考：https://help.aliyun.com/zh/model-studio/custom-hot-words?
+   - 语义断句/VAD断句(semantic_punctuation_enabled参数)
+   - 自动标点符号、ITN、过滤语气词等
+5. 参数说明：
+   - model: 模型名称，推荐paraformer-realtime-v2
+   - sample_rate: 采样率(Hz)，v2支持任意采样率，v1仅支持16000，8k版本仅支持8000
+   - semantic_punctuation_enabled: false为VAD断句(低延迟)，true为语义断句(高准确)
+   - max_sentence_silence: VAD断句静音时长阈值(200-6000ms)
+' WHERE `id` = 'ASR_AliyunBLStream';
+
+
+-- 更新豆包流式ASR供应器，增加配置
+delete from `ai_model_provider` where id = 'SYSTEM_ASR_DoubaoStreamASR';
+INSERT INTO `ai_model_provider` (`id`, `model_type`, `provider_code`, `name`, `fields`, `sort`, `creator`, `create_date`, `updater`, `update_date`) VALUES
+('SYSTEM_ASR_DoubaoStreamASR', 'ASR', 'doubao_stream', '火山引擎语音识别(流式)', '[{"key":"appid","label":"应用ID","type":"string"},{"key":"access_token","label":"访问令牌","type":"string"},{"key":"cluster","label":"集群","type":"string"},{"key":"boosting_table_name","label":"热词文件名称","type":"string"},{"key":"correct_table_name","label":"替换词文件名称","type":"string"},{"key":"output_dir","label":"输出目录","type":"string"},{"key":"end_window_size","label":"静音判定时长(ms)","type":"number"},{"key":"enable_multilingual","label":"是否开启多语种识别模式","type":"boolean"},{"key":"language","label":"指定语言编码","type":"string"}]', 3, 1, NOW(), 1, NOW());
+UPDATE `ai_model_config` SET 
+`remark` = '豆包ASR配置说明：
+1. 豆包ASR和豆包(流式)ASR的区别是：豆包ASR是按次收费，豆包(流式)ASR是按时收费
+2. 一般来说按次收费的更便宜，但是豆包(流式)ASR使用了大模型技术，效果更好
+3. 需要在火山引擎控制台创建应用并获取appid和access_token
+4. 支持中文语音识别
+5. 需要网络连接
+6. 输出文件保存在tmp/目录
+申请步骤：
+1. 访问 https://console.volcengine.com/speech/app
+2. 创建新应用
+3. 获取appid和access_token
+4. 填入配置文件中
+如需设置热词，请参考：https://www.volcengine.com/docs/6561/155738
+如开启多语种识别模式，请设置language当该键为空时，该模型支持中英文、上海话、闽南语，四川、陕西、粤语识别。其他语种请参考：https://www.volcengine.com/docs/6561/1354869
+' WHERE `id` = 'ASR_DoubaoStreamASR';
+
+-- 更新豆包流式ASR模型配置，增加enable_multilingual默认值
+UPDATE `ai_model_config` SET
+`config_json` = JSON_SET(
+    `config_json`, 
+    '$.enable_multilingual', false,
+    '$.language', 'zh-CN'
+)
+WHERE `id` = 'ASR_DoubaoStreamASR' 
+AND JSON_EXTRACT(`config_json`, '$.enable_multilingual') IS NULL 
+AND JSON_EXTRACT(`config_json`, '$.language') IS NULL;
+
+
+-- 更新HuoshanDoubleStreamTTS供应器配置，增加多情感音色参数
+UPDATE `ai_model_provider`
+SET `fields` = '[{"key": "ws_url", "type": "string", "label": "WebSocket地址"}, {"key": "appid", "type": "string", "label": "应用ID"}, {"key": "access_token", "type": "string", "label": "访问令牌"}, {"key": "resource_id", "type": "string", "label": "资源ID"}, {"key": "speaker", "type": "string", "label": "默认音色"}, {"key": "enable_ws_reuse", "type": "boolean", "label": "是否开启链接复用", "default": true}, {"key": "speech_rate", "type": "number", "label": "语速(-50~100)"}, {"key": "loudness_rate", "type": "number", "label": "音量(-50~100)"}, {"key": "pitch", "type": "number", "label": "音高(-12~12)"}, {"key": "emotion_scale", "type": "number", "label": "情感强度(1-5)"}, {"key": "emotion", "type": "string", "label": "情感类型"}]'
+WHERE `id` = 'SYSTEM_TTS_HSDSTTS';
+
+-- 更新默认值
+UPDATE `ai_model_config` SET
+`config_json` = JSON_SET(
+    `config_json`,
+    '$.emotion', 'neutral',
+    '$.emotion_scale', 4
+)
+WHERE `id` = 'TTS_HuoshanDoubleStreamTTS'
+AND JSON_EXTRACT(`config_json`, '$.emotion') IS NULL 
+AND JSON_EXTRACT(`config_json`, '$.emotion_scale') IS NULL;
+
+-- 增加文档链接和备注
+UPDATE `ai_model_config` SET 
+`doc_link` = 'https://console.volcengine.com/speech/service/10007',
+`remark` = '火山引擎语音合成服务配置说明：
+1. 访问 https://www.volcengine.com/ 注册并开通火山引擎账号
+2. 访问 https://console.volcengine.com/speech/service/10007 开通语音合成大模型，购买音色
+3. 在页面底部获取appid和access_token
+5. 资源ID固定为：volc.service_type.10029（大模型语音合成及混音）
+6. 链接复用：开启WebSocket连接复用，默认true减少链接损耗（注意：复用后设备处于聆听状态时空闲链接会占并发数）
+7. 语速：-50~100，可不填，正常默认值0，可填-50~100
+8. 音量：-50~100，可不填，正常默认值0，可填-50~100
+9. 音高：-12~12，可不填，正常默认值0，可填-12~12
+10. 多情感参数（当前仅部分音色支持设置情感）：
+   相关音色列表：https://www.volcengine.com/docs/6561/1257544
+    - emotion_scale：情感强度，可选值为：1~5，默认值为4
+    - emotion：情感类型，可选值为：neutral、happy、sad、angry、fearful、disgusted、surprised
+' WHERE `id` = 'TTS_HuoshanDoubleStreamTTS';

main/manager-api/src/main/resources/db/changelog/db.changelog-master.yaml

@@ -402,3 +402,81 @@ databaseChangeLog:
         - sqlFile:
             encoding: utf8
             path: classpath:db/changelog/202510191042.sql
+  - changeSet:
+      id: 202510250956
+      author: rainv123
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202510250956.sql
+  - changeSet:
+      id: 202510251150
+      author: rainv123
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202510251150.sql
+  - changeSet:
+      id: 202511131023
+      author: hrz
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202511131023.sql
+  - changeSet:
+      id: 202511221450
+      author: RanChen
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202511221450.sql
+  - changeSet:         
+      id: 202512031517
+      author: rainv123
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202512031517.sql
+    
+  - changeSet:
+      id: 202512041515
+      author: cgd
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202512041515.sql
+  - changeSet:
+      id: 202512131453
+      author: hrz
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202512131453.sql
+  - changeSet:
+      id: 202512161529
+      author: RanChen
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202512161529.sql
+  - changeSet:
+      id: 202512192245
+      author: hrz
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202512192245.sql
+  - changeSet:
+      id: 202512221117
+      author: RanChen
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202512221117.sql
+  - changeSet:
+      id: 202512301430
+      author: RanChen
+      changes:
+        - sqlFile:
+            encoding: utf8
+            path: classpath:db/changelog/202512301430.sql

main/manager-api/src/main/resources/i18n/messages.properties

@@ -160,10 +160,42 @@
 10151=\u8BF7\u5148\u4E0A\u4F20\u97F3\u9891\u6587\u4EF6
 10152=\u6A21\u578B\u914D\u7F6E\u672A\u627E\u5230
 10153=\u6A21\u578B\u7C7B\u578B\u672A\u627E\u5230
-10154=\u8BAD\u7EC3\u5931\u8D25
+10154=\u8BAD\u7EC3\u5931\u8D25: {0}
 10155=\u706B\u5C71\u5F15\u64CE\u7F3A\u5C11\u914D\u7F6E
 10156=\u54CD\u5E94\u683C\u5F0F\u9519\u8BEF\uFF0C\u7F3A\u5C11BaseResp\u5B57\u6BB5
 10157=\u8BF7\u6C42\u5931\u8D25
-10158=\u8BF7\u6C42\u5931\u8D25\uFF0C\u72B6\u6001\u7801{0}
+10158=\u514B\u9686\u97F3\u8272:
 10159=\u97F3\u8272ID\u5DF2\u5B58\u5728
-10160=\u706B\u5C71\u5F15\u64CE\u97F3\u8272ID\u683C\u5F0F\u9519\u8BEF\uFF0C\u5FC5\u987B\u4EE5S_\u5F00\u5934
+10160=\u706B\u5C71\u5F15\u64CE\u97F3\u8272ID\u683C\u5F0F\u9519\u8BEF\uFF0C\u5FC5\u987B\u4EE5S_\u5F00\u5934
+10161=Mac\u5730\u5740\u5DF2\u5B58\u5728
+10162=\u6A21\u578B\u4F9B\u5E94\u5668\u4E0D\u5B58\u5728
+10163=\u77E5\u8BC6\u5E93\u8BB0\u5F55\u4E0D\u5B58\u5728
+10164=RAG\u914D\u7F6E\u672A\u627E\u5230
+10165=RAG\u914D\u7F6E\u7C7B\u578B\u9519\u8BEF
+10166=\u9ED8\u8BA4RAG\u914D\u7F6E\u672A\u627E\u5230
+10167=RAG\u8C03\u7528\u5931\u8D25\uFF0C{0}
+10168=\u4E0A\u4F20\u6587\u4EF6\u5931\u8D25
+10169=\u60A8\u6CA1\u6709\u6743\u9650\u64CD\u4F5C\u8BE5\u8BB0\u5F55
+10170=\u77E5\u8BC6\u5E93\u540D\u79F0\u91CD\u590D
+10171=RAG\u914D\u7F6E\u4F53\u7684base_url\u4E0D\u80FD\u4E3A\u7A7A
+10172=RAG\u914D\u7F6E\u4F53\u7684api_key\u4E0D\u80FD\u4E3A\u7A7A
+10173=RAG\u914D\u7F6E\u4F53\u7684api_key\u4E0D\u80FD\u4E3A\u7A7A\uFF0C\u8BF7\u66F4\u6362\u4E3A\u5728\u53D6\u7684API\u53C2\u6570
+10174=RAG\u914D\u7F6E\u4F53\u7684base_url\u683C\u5F0F\u9519\u8BEF\uFF0C\u5FC5\u987B\u4EE5http\u6216https\u5F00\u5934
+10175=mac\u5730\u5740\u4E0D\u80FD\u4E3A\u7A7A
+10176=RAG\u914D\u7F6E\u4F53\u7684dataset_id\u4E0D\u80FD\u4E3A\u7A7A
+10177=RAG\u914D\u7F6E\u4F53\u7684model_id\u4E0D\u80FD\u4E3A\u7A7A
+10178=RAG\u914D\u7F6E\u4F53\u7684dataset_id\u548Cmodel_id\u4E0D\u80FD\u4E3A\u7A7A
+10179=\u6587\u4EF6\u540D\u79F0\u4E0D\u80FD\u4E3A\u7A7A
+10180=\u6587\u4EF6\u5185\u5BB9\u4E0D\u80FD\u4E3A\u7A7A
+10181=\u97F3\u8272\u514B\u9686\u540D\u79F0\u4E0D\u80FD\u4E3A\u7A7A
+10182=\u97F3\u8272\u514B\u9686\u97F3\u9891\u4E0D\u5B58\u5728
+10183=\u9ED8\u8BA4\u667A\u80FD\u4F53\u672A\u627E\u5230
+10184=\u4E0D\u652F\u6301\u7684\u9002\u914D\u5668\u7C7B\u578B
+10185=RAG\u914D\u7F6E\u9A8C\u8BC1\u5931\u8D25
+10186=\u9002\u914D\u5668\u521B\u5EFA\u5931\u8D25
+10187=\u9002\u914D\u5668\u521D\u59CB\u5316\u5931\u8D25
+10188=\u9002\u914D\u5668\u8FDE\u63A5\u6D4B\u8BD5\u5931\u8D25
+10189=\u9002\u914D\u5668\u64CD\u4F5C\u5931\u8D25
+10190=\u9002\u914D\u5668\u672A\u627E\u5230
+10191=\u9002\u914D\u5668\u7F13\u5B58\u9519\u8BEF
+10192=\u9002\u914D\u5668\u7C7B\u578B\u672A\u627E\u5230

main/manager-api/src/main/resources/i18n/messages_de_DE.properties

@@ -0,0 +1,201 @@
+#Deutsch
+500=Server interne Ausnahme
+401=Nicht autorisiert
+403=Zugriff verweigert, keine Berechtigungen
+10001={0} darf nicht leer sein
+10002=Der Datensatz existiert bereits in der Datenbank
+10003=Parameter abrufen fehlgeschlagen
+10004=Die Kontonummer oder das Passwort ist falsch
+10005=Konto wurde deaktiviert
+10006=Eindeutige ID darf nicht leer sein
+10007=Der Bestätigungscode ist falsch
+10008=Zuerst Untermenü oder Schaltfläche löschen
+10009=Das ursprüngliche Passwort ist falsch
+10010=Das Konto oder Passwort ist falsch, Sie können es noch {0} Mal versuchen
+
+10011=Die übergeordnete Abteilung hat eine falsche Wahl getroffen
+10012=Oberes Menü kann nicht sich selbst sein
+10013=Datenberechtigungsschnittstelle, die nur ein Map-Typ-Parameter sein kann
+10014=Bitte löschen Sie zuerst die untergeordnete Abteilung
+10015=Bitte löschen Sie zuerst den Benutzer unter der Abteilung
+10016=Bereitstellung fehlgeschlagen, kein Prozess
+10017=Das ModellDiagramm ist falsch, bitte überprüfen
+10018=Export fehlgeschlagen, Modell-ID ist {0}
+
+10019=Bitte laden Sie eine Datei hoch
+10020=Token darf nicht leer sein
+10021=Token ist ungültig, bitte melden Sie sich erneut an
+10022=Das Konto wurde gesperrt
+10023=Bitte laden Sie Dateien im Format zip, bar, bpmn, bpmn20.xml hoch
+
+10024=Datei-Upload fehlgeschlagen {0}
+10025=SMS-Sendung fehlgeschlagen {0}
+10026=E-Mail-Vorlage existiert nicht
+
+10027=Redis-Dienstausnahme
+10028=Zeitgesteuerte Aufgabe fehlgeschlagen
+10029=Darf keine illegalen Zeichen enthalten
+
+10030=Das Passwort hat weniger als {0} Ziffern
+10031=Das Passwort muss gleichzeitig aus Zahlen, Groß- und Kleinbuchstaben sowie Sonderzeichen bestehen
+10032=Ausnahme beim Löschen dieser Daten
+10033=Gerätebestätigungscode Fehler
+
+10034=Parameterwert darf nicht leer sein
+10035=Parametertyp darf nicht leer sein
+10036=Nicht unterstützter Parametertyp
+10037=Parameterwert muss eine gültige Zahl sein
+10038=Parameterwert muss true oder false sein
+10039=Parameterwert muss ein gültiges JSON-Array-Format sein
+10040=Parameterwert muss ein gültiges JSON-Format sein
+
+10041=Gerät nicht gefunden
+10042={0}
+10043=Löschen der Daten fehlgeschlagen
+10044=Benutzer nicht angemeldet
+10045=WebSocket-Verbindung fehlgeschlagen oder Zeitüberschreitung
+10046=Stimmabdruck speichern fehlgeschlagen, bitte Administrator kontaktieren
+10047=Tägliches SendeLimit erreicht
+10048=Altes Passwort ist falsch
+10049=Das eingestellte LLM ist nicht openai oder ollama
+10050=Token-Generierung fehlgeschlagen
+10051=Ressource nicht gefunden
+10052=Standard-Agent nicht gefunden
+10053=Agent nicht gefunden
+10054=Stimmabdruck-Schnittstelle nicht konfiguriert, bitte konfigurieren Sie zuerst die Stimmabdruck-Schnittstellenadresse (server.voice_print) in der Parameterkonfiguration
+10055=SMS-Sendung fehlgeschlagen
+10056=SMS-Verbindung konnte nicht hergestellt werden
+10057=Stimmabdruck für Agent konnte nicht erstellt werden
+10058=Stimmabdruck für Agent konnte nicht aktualisiert werden
+10059=Stimmabdruck für Agent konnte nicht gelöscht werden
+10060=Sendung zu häufig, bitte versuchen Sie es nach {0} Sekunden erneut
+10061=Aktivierungscode darf nicht leer sein
+10062=Aktivierungscode Fehler
+10063=Gerät bereits aktiviert
+10064=Dieses Modell ist das Standardmodell, bitte setzen Sie zuerst ein anderes Modell als Standard
+10065=Hinzufügen der Daten fehlgeschlagen
+10066=Aktualisieren der Daten fehlgeschlagen
+10067=Grafischer Bestätigungscode Fehler
+10068=Mobilregistrierung nicht aktiviert, SMS-Bestätigungscode-Funktion kann nicht verwendet werden
+10069=Benutzername ist keine Handynummer, bitte erneut eingeben
+10070=Diese Handynummer wurde bereits registriert
+10071=Die eingegebene Handynummer ist nicht registriert
+10072=Normale Benutzerregistrierung derzeit nicht erlaubt
+10073=Mobilregistrierung nicht aktiviert, Passwort-Wiederherstellungsfunktion kann nicht verwendet werden
+10074=Das Format der eingegebenen Handynummer ist falsch
+10075=Der eingegebene SMS-Bestätigungscode ist falsch
+10076=Wörterbuchtyp existiert nicht
+10077=Wörterbuchtypcode ist dupliziert
+10078=Lesen der Ressource fehlgeschlagen
+10079=LLM-Modell und Absichtserkennung, Parameterauswahl stimmt nicht überein
+10080=Dieser Stimmabdruck gehört zu {0}, der bereits registriert ist, bitte wählen Sie eine andere Stimme
+10081=Fehler beim Löschen des Stimmabdrucks aufgetreten
+10082=Änderung nicht erlaubt, diese Stimme wurde bereits als Stimmabdruck registriert ({0})
+10083=Fehler beim Ändern des Stimmabdrucks, bitte Administrator kontaktieren
+10084=Stimmabdruck-Schnittstellenadresse Fehler, bitte gehen Sie zur Parameterverwaltung, um die Stimmabdruck-Schnittstellenadresse zu ändern
+10085=Audiodaten gehören nicht zu diesem Agent
+10086=Audiodaten sind leer, bitte überprüfen Sie hochgeladene Daten
+10087=Stimmabdruck-Registrierung fehlgeschlagen, Anfrage nicht erfolgreich
+10088=Stimmabdruck-Registrierung fehlgeschlagen, Anfrageverarbeitung fehlgeschlagen
+10089=Stimmabdruck-Stornierung fehlgeschlagen, Anfrage nicht erfolgreich
+10090=Stimmabdruck-Stornierung fehlgeschlagen, Anfrageverarbeitung fehlgeschlagen
+10091=Modellanbieter existiert nicht
+10092=Das konfigurierte LLM existiert nicht
+10093=Diese Modellkonfiguration wird von Agent {0} referenziert und kann nicht gelöscht werden
+10094=Dieses LLM-Modell wird von der Absichtserkennungskonfiguration referenziert und kann nicht gelöscht werden
+10095=Ungültige Serveroperation
+10096=Server WebSocket-Adresse nicht konfiguriert
+10097=Ziel-WebSocket-Adresse existiert nicht
+10098=WebSocket-Adressliste darf nicht leer sein
+10099=WebSocket-Adresse darf nicht localhost oder 127.0.0.1 verwenden
+10100=WebSocket-Adressformat ist falsch
+10101=WebSocket-Verbindungstest fehlgeschlagen
+10102=OTA-Adresse darf nicht leer sein
+10103=OTA-Adresse darf nicht localhost oder 127.0.0.1 verwenden
+10104=OTA-Adresse muss mit http oder https beginnen
+10105=OTA-Adresse muss mit /ota/ enden
+10106=OTA-Schnittstellenzugriff fehlgeschlagen
+10107=OTA-Schnittstelle Rückgabeinhaltformat ist falsch
+10108=OTA-Schnittstellenvalidierung fehlgeschlagen
+10109=MCP-Adresse darf nicht leer sein
+10110=MCP-Adresse darf nicht localhost oder 127.0.0.1 verwenden
+10111=Keine gültige MCP-Adresse
+10112=MCP-Schnittstellenzugriff fehlgeschlagen
+10113=MCP-Schnittstelle Rückgabeinhaltformat ist falsch
+10114=MCP-Schnittstellenvalidierung fehlgeschlagen
+10115=Stimmabdruck-Schnittstellenadresse darf nicht leer sein
+10116=Stimmabdruck-Schnittstellenadresse darf nicht localhost oder 127.0.0.1 verwenden
+10117=Keine gültige Stimmabdruck-Schnittstellenadresse
+10118=Stimmabdruck-Schnittstellenadresse muss mit http oder https beginnen
+10119=Stimmabdruck-Schnittstellenzugriff fehlgeschlagen
+10120=Stimmabdruck-Schnittstelle Rückgabeinhaltformat ist falsch
+10121=Stimmabdruck-Schnittstellenvalidierung fehlgeschlagen
+10122=MQTT-Geheimnis darf nicht leer sein
+10123=Ihr MQTT-Geheimnis ist nicht sicher, es muss mindestens 8 Zeichen lang sein und muss sowohl Groß- als auch Kleinbuchstaben enthalten
+10124=Ihr MQTT-Geheimnis ist nicht sicher, MQTT-Geheimnis muss sowohl Groß- als auch Kleinbuchstaben enthalten
+10125=Ihr MQTT-Geheimnis enthält schwaches Passwort
+10128=Wörterbuchlabel ist dupliziert
+10129=SM2-Schlüssel nicht konfiguriert
+10130=SM2-Entschlüsselung fehlgeschlagen
+10131=modelType und provideCode dürfen nicht leer sein
+10132=Keine Berechtigung, den Chat-Verlauf dieses Agents anzuzeigen
+10133=Sitzungs-ID darf nicht leer sein
+10134=Agent-ID darf nicht leer sein
+10135=Chat-Verlauf-Download fehlgeschlagen
+10136=Download-Link abgelaufen oder ungültig
+10137=Download-Link ungültig
+10138=Benutzer
+10139=Agent
+10140=Audio-Datei darf nicht leer sein
+10141=Nur Audio-Dateien werden unterstützt
+10142=Audio-Dateigröße darf 10MB nicht überschreiten
+10143=Upload fehlgeschlagen
+10144=Stimmenklon-Datensatz existiert nicht
+10145=Stimmressourceninformationen dürfen nicht leer sein
+10146=TTS-Plattformname darf nicht leer sein
+10147=Stimmen-ID darf nicht leer sein
+10148=Kontoinhaber darf nicht leer sein
+10149=Zu löschende Stimmressourcen-ID darf nicht leer sein
+10150=Sie haben keine Berechtigung, diesen Datensatz zu bearbeiten
+10151=Bitte laden Sie zuerst eine Audio-Datei hoch
+10152=Modellkonfiguration nicht gefunden
+10153=Modelltyp nicht gefunden
+10154=Training fehlgeschlagen: {0}
+10155=Huoshan Engine-Konfiguration fehlt
+10156=Antwortformat Fehler, BaseResp-Feld fehlt
+10157=Anfrage fehlgeschlagen
+10158=Stimme klonen:
+10159=Stimmen-ID existiert bereits
+10160=Huoshan Engine-Stimmen-ID-Formatfehler, muss mit S_ beginnen
+10161=Mac-Adresse existiert bereits
+10162=Modellanbieter existiert nicht
+10163=Wissensbasis-Datensatz existiert nicht
+10164=RAG-Konfiguration nicht gefunden
+10165=RAG-Konfigurationstyp Fehler
+10166=Standard-RAG-Konfiguration nicht gefunden
+10167=RAG-API-Aufruf fehlgeschlagen: {0}
+10168=Datei-Upload fehlgeschlagen
+10169=Keine Berechtigung, diese Wissensbasis zu bearbeiten
+10170=Wissensbasis-Name existiert bereits
+10171=RAG-Konfiguration base_url darf nicht leer sein
+10172=RAG-Konfiguration api_key darf nicht leer sein
+10173=RAG-Konfiguration api_key darf keinen Platzhalter enthalten, bitte ersetzen Sie mit tatsächlichem API-Schlüssel
+10174=RAG-Konfiguration base_url-Formatfehler, muss mit http oder https beginnen
+10175=Mac-Adresse darf nicht leer sein
+10176=RAG-Konfiguration dataset_id darf nicht leer sein
+10177=RAG-Konfiguration model_id darf nicht leer sein
+10178=RAG-Konfiguration dataset_id und model_id dürfen nicht leer sein
+10179=Dateiname darf nicht leer sein
+10180=Dateiinhalt darf nicht leer sein
+10181=Stimmenklon-Name darf nicht leer sein
+10182=Stimmenklon-Audio nicht gefunden
+10183=Standard-Agent-Vorlage nicht gefunden
+10184=Nicht unterstützter Adaptertyp
+10185=RAG-Konfigurationsvalidierung fehlgeschlagen
+10186=Adapter-Erstellung fehlgeschlagen
+10187=Adapter-Initialisierung fehlgeschlagen
+10188=Adapter-Verbindungstest fehlgeschlagen
+10189=Adapter-Operation fehlgeschlagen
+10190=Adapter nicht gefunden
+10191=Adapter-Cache-Fehler
+10192=Adaptertyp nicht gefunden

main/manager-api/src/main/resources/i18n/messages_en_US.properties

@@ -166,4 +166,36 @@
 10157=Request failed
 10158=Clone Voice:
 10159=Voice ID already exists
-10160=Huoshan Engine voice ID format error, must start with S_
+10160=Huoshan Engine voice ID format error, must start with S_
+10161=Mac address already exists
+10162=Model provider does not exist
+10163=Knowledge base record does not exist
+10164=RAG configuration not found
+10165=RAG configuration type error
+10166=Default RAG configuration not found
+10167=RAG API call failed: {0}
+10168=Upload file failed
+10169=No permission to operate this knowledge base
+10170=Knowledge base name already exists
+10171=RAG configuration base_url cannot be empty
+10172=RAG configuration api_key cannot be empty
+10173=RAG configuration api_key cannot contain placeholder, please replace with actual API key
+10174=RAG configuration base_url format error, must start with http or https
+10175=Mac address cannot be empty
+10176=RAG configuration dataset_id cannot be empty
+10177=RAG configuration model_id cannot be empty
+10178=RAG configuration dataset_id and model_id cannot be empty
+10179=File name cannot be empty
+10180=File content cannot be empty
+10181=Voice clone name cannot be empty
+10182=Voice clone audio not found
+10183=Default agent template not found
+10184=Unsupported adapter type
+10185=RAG configuration validation failed
+10186=Adapter creation failed
+10187=Adapter initialization failed
+10188=Adapter connection test failed
+10189=Adapter operation failed
+10190=Adapter not found
+10191=Adapter cache error
+10192=Adapter type not found

main/manager-api/src/main/resources/i18n/messages_vi_VN.properties

@@ -0,0 +1,201 @@
+#Tiếng Việt
+500=Ngoại lệ nội bộ máy chủ
+401=Không được ủy quyền
+403=Truy cập bị từ chối, không có quyền
+10001={0} không thể để trống
+10002=Bản ghi đã tồn tại trong cơ sở dữ liệu
+10003=Không thể lấy tham số
+10004=Số tài khoản hoặc mật khẩu không chính xác
+10005=Tài khoản đã bị vô hiệu hóa
+10006=ID duy nhất không thể để trống
+10007=Mã xác minh không chính xác
+10008=Trước tiên hãy xóa menu con hoặc nút
+10009=Mật khẩu gốc không chính xác
+10010=Tài khoản hoặc mật khẩu không chính xác, bạn có thể thử thêm {0} lần nữa
+
+10011=Phòng ban cấp trên đã lựa chọn sai
+10012=Menu trên không thể là chính nó
+10013=Giao diện quyền dữ liệu, chỉ có thể là tham số kiểu Map
+10014=Vui lòng xóa phòng ban cấp dưới trước
+10015=Vui lòng xóa người dùng thuộc phòng ban trước
+10016=Triển khai thất bại, không có quy trình
+10017=Biểu đồ mô hình không chính xác, vui lòng kiểm tra
+10018=Xuất thất bại, ID mô hình là {0}
+
+10019=Vui lòng tải lên tệp
+10020=Token không thể để trống
+10021=Token không hợp lệ, vui lòng đăng nhập lại
+10022=Tài khoản đã bị khóa
+10023=Vui lòng tải lên tệp ở định dạng zip, bar, bpmn, bpmn20.xml
+
+10024=Tải lên tệp {0} thất bại
+10025=Gửi SMS {0} thất bại
+10026=Mẫu email không tồn tại
+
+10027=Ngoại lệ dịch vụ Redis
+10028=Tác vụ hẹn giờ thất bại
+10029=Không thể chứa ký tự không hợp lệ
+
+10030=Mật khẩu ít hơn {0} chữ số
+10031=Mật khẩu phải bao gồm số, chữ hoa, chữ thường và ký tự đặc biệt cùng một lúc
+10032=Ngoại lệ khi xóa dữ liệu này
+10033=Lỗi mã xác minh thiết bị
+
+10034=Giá trị tham số không thể để trống
+10035=Loại tham số không thể để trống
+10036=Loại tham số không được hỗ trợ
+10037=Giá trị tham số phải là số hợp lệ
+10038=Giá trị tham số phải là true hoặc false
+10039=Giá trị tham số phải là định dạng mảng JSON hợp lệ
+10040=Giá trị tham số phải là định dạng JSON hợp lệ
+
+10041=Không tìm thấy thiết bị
+10042={0}
+10043=Xóa dữ liệu thất bại
+10044=Người dùng chưa đăng nhập
+10045=Kết nối WebSocket thất bại hoặc hết thời gian chờ
+10046=Không thể lưu dấu giọng nói, vui lòng liên hệ quản trị viên
+10047=Đạt đến giới hạn gửi hàng ngày
+10048=Mật khẩu cũ không chính xác
+10049=LLM được đặt không phải là openai hoặc ollama
+10050=Không thể tạo token
+10051=Không tìm thấy tài nguyên
+10052=Không tìm thấy agent mặc định
+10053=Không tìm thấy agent
+10054=Giao diện dấu giọng nói chưa được cấu hình, vui lòng cấu hình địa chỉ giao diện dấu giọng nói (server.voice_print) trong cấu hình tham số trước
+10055=Gửi SMS thất bại
+10056=Không thể thiết lập kết nối SMS
+10057=Không thể tạo dấu giọng nói cho agent
+10058=Không thể cập nhật dấu giọng nói cho agent
+10059=Không thể xóa dấu giọng nói cho agent
+10060=Gửi quá thường xuyên, vui lòng thử lại sau {0} giây
+10061=Mã kích hoạt không thể để trống
+10062=Lỗi mã kích hoạt
+10063=Thiết bị đã được kích hoạt
+10064=Mô hình này là mô hình mặc định, vui lòng đặt mô hình khác làm mặc định trước
+10065=Thêm dữ liệu thất bại
+10066=Cập nhật dữ liệu thất bại
+10067=Lỗi mã xác minh đồ họa
+10068=Đăng ký di động không được bật, không thể sử dụng chức năng mã xác minh SMS
+10069=Tên người dùng không phải là số điện thoại di động, vui lòng nhập lại
+10070=Số điện thoại di động này đã được đăng ký
+10071=Số điện thoại di động đã nhập không được đăng ký
+10072=Hiện không cho phép đăng ký người dùng thông thường
+10073=Đăng ký di động không được bật, không thể sử dụng chức năng truy xuất mật khẩu
+10074=Định dạng số điện thoại di động đã nhập không chính xác
+10075=Mã xác minh SMS đã nhập không chính xác
+10076=Loại từ điển không tồn tại
+10077=Mã loại từ điển bị trùng lặp
+10078=Đọc tài nguyên thất bại
+10079=Mô hình LLM và nhận dạng ý định, lựa chọn tham số không khớp
+10080=Dấu giọng nói này thuộc về {0} đã đăng ký, vui lòng chọn giọng nói khác
+10081=Đã xảy ra lỗi khi xóa dấu giọng nói
+10082=Không cho phép sửa đổi, giọng nói này đã được đăng ký làm dấu giọng nói ({0})
+10083=Lỗi sửa đổi dấu giọng nói, vui lòng liên hệ quản trị viên
+10084=Lỗi địa chỉ giao diện dấu giọng nói, vui lòng vào quản lý tham số để sửa đổi địa chỉ giao diện dấu giọng nói
+10085=Dữ liệu âm thanh không thuộc về agent này
+10086=Dữ liệu âm thanh trống, vui lòng kiểm tra dữ liệu đã tải lên
+10087=Đăng ký dấu giọng nói thất bại, yêu cầu không thành công
+10088=Đăng ký dấu giọng nói thất bại, xử lý yêu cầu thất bại
+10089=Hủy dấu giọng nói thất bại, yêu cầu không thành công
+10090=Hủy dấu giọng nói thất bại, xử lý yêu cầu thất bại
+10091=Nhà cung cấp mô hình không tồn tại
+10092=LLM được cấu hình không tồn tại
+10093=Cấu hình mô hình này được tham chiếu bởi agent {0} và không thể xóa
+10094=Mô hình LLM này được tham chiếu bởi cấu hình nhận dạng ý định và không thể xóa
+10095=Thao tác máy chủ không hợp lệ
+10096=Địa chỉ WebSocket máy chủ chưa được cấu hình
+10097=Địa chỉ WebSocket mục tiêu không tồn tại
+10098=Danh sách địa chỉ WebSocket không thể để trống
+10099=Địa chỉ WebSocket không thể sử dụng localhost hoặc 127.0.0.1
+10100=Định dạng địa chỉ WebSocket không chính xác
+10101=Kiểm tra kết nối WebSocket thất bại
+10102=Địa chỉ OTA không thể để trống
+10103=Địa chỉ OTA không thể sử dụng localhost hoặc 127.0.0.1
+10104=Địa chỉ OTA phải bắt đầu bằng http hoặc https
+10105=Địa chỉ OTA phải kết thúc bằng /ota/
+10106=Truy cập giao diện OTA thất bại
+10107=Định dạng nội dung trả về giao diện OTA không chính xác
+10108=Xác thực giao diện OTA thất bại
+10109=Địa chỉ MCP không thể để trống
+10110=Địa chỉ MCP không thể sử dụng localhost hoặc 127.0.0.1
+10111=Không phải địa chỉ MCP hợp lệ
+10112=Truy cập giao diện MCP thất bại
+10113=Định dạng nội dung trả về giao diện MCP không chính xác
+10114=Xác thực giao diện MCP thất bại
+10115=Địa chỉ giao diện dấu giọng nói không thể để trống
+10116=Địa chỉ giao diện dấu giọng nói không thể sử dụng localhost hoặc 127.0.0.1
+10117=Không phải địa chỉ giao diện dấu giọng nói hợp lệ
+10118=Địa chỉ giao diện dấu giọng nói phải bắt đầu bằng http hoặc https
+10119=Truy cập giao diện dấu giọng nói thất bại
+10120=Định dạng nội dung trả về giao diện dấu giọng nói không chính xác
+10121=Xác thực giao diện dấu giọng nói thất bại
+10122=Bí mật MQTT không thể để trống
+10123=Bí mật MQTT của bạn không an toàn, cần ít nhất 8 ký tự và phải chứa cả chữ hoa và chữ thường
+10124=Bí mật MQTT của bạn không an toàn, bí mật MQTT phải chứa cả chữ hoa và chữ thường
+10125=Bí mật MQTT của bạn chứa mật khẩu yếu
+10128=Nhãn từ điển bị trùng lặp
+10129=Khóa SM2 chưa được cấu hình
+10130=Giải mã SM2 thất bại
+10131=modelType và provideCode không thể để trống
+10132=Không có quyền xem lịch sử trò chuyện của agent này
+10133=ID phiên không thể để trống
+10134=ID agent không thể để trống
+10135=Tải xuống lịch sử trò chuyện thất bại
+10136=Liên kết tải xuống đã hết hạn hoặc không hợp lệ
+10137=Liên kết tải xuống không hợp lệ
+10138=Người dùng
+10139=Agent
+10140=Tệp âm thanh không thể để trống
+10141=Chỉ hỗ trợ tệp âm thanh
+10142=Kích thước tệp âm thanh không thể vượt quá 10MB
+10143=Tải lên thất bại
+10144=Bản ghi nhân bản giọng nói không tồn tại
+10145=Thông tin tài nguyên giọng nói không thể để trống
+10146=Tên nền tảng TTS không thể để trống
+10147=ID giọng nói không thể để trống
+10148=Tài khoản chủ sở hữu không thể để trống
+10149=ID tài nguyên giọng nói cần xóa không thể để trống
+10150=Bạn không có quyền thao tác bản ghi này
+10151=Vui lòng tải lên tệp âm thanh trước
+10152=Không tìm thấy cấu hình mô hình
+10153=Không tìm thấy loại mô hình
+10154=Đào tạo thất bại: {0}
+10155=Thiếu cấu hình Huoshan Engine
+10156=Lỗi định dạng phản hồi, thiếu trường BaseResp
+10157=Yêu cầu thất bại
+10158=Nhân bản âm sắc:
+10159=ID giọng nói đã tồn tại
+10160=Lỗi định dạng ID giọng nói Huoshan Engine, phải bắt đầu bằng S_
+10161=Địa chỉ Mac đã tồn tại
+10162=Nhà cung cấp mô hình không tồn tại
+10163=Bản ghi cơ sở kiến thức không tồn tại
+10164=Không tìm thấy cấu hình RAG
+10165=Lỗi loại cấu hình RAG
+10166=Không tìm thấy cấu hình RAG mặc định
+10167=Gọi API RAG thất bại: {0}
+10168=Tải lên tệp thất bại
+10169=Không có quyền thao tác cơ sở kiến thức này
+10170=Tên cơ sở kiến thức đã tồn tại
+10171=Cấu hình RAG base_url không thể để trống
+10172=Cấu hình RAG api_key không thể để trống
+10173=Cấu hình RAG api_key không thể chứa trình giữ chỗ, vui lòng thay thế bằng khóa API thực tế
+10174=Lỗi định dạng cấu hình RAG base_url, phải bắt đầu bằng http hoặc https
+10175=Địa chỉ Mac không thể để trống
+10176=Cấu hình RAG dataset_id không thể để trống
+10177=Cấu hình RAG model_id không thể để trống
+10178=Cấu hình RAG dataset_id và model_id không thể để trống
+10179=Tên tệp không thể để trống
+10180=Nội dung tệp không thể để trống
+10181=Tên nhân bản giọng nói không thể để trống
+10182=Không tìm thấy âm thanh nhân bản giọng nói
+10183=Không tìm thấy mẫu agent mặc định
+10184=Loại bộ chuyển đổi không được hỗ trợ
+10185=Kiểm tra cấu hình RAG thất bại
+10186=Tạo bộ chuyển đổi thất bại
+10187=Khởi tạo bộ chuyển đổi thất bại
+10188=Kiểm tra kết nối bộ chuyển đổi thất bại
+10189=Thao tác bộ chuyển đổi thất bại
+10190=Không tìm thấy bộ chuyển đổi
+10191=Lỗi bộ nhớ đệm bộ chuyển đổi
+10192=Không tìm thấy loại bộ chuyển đổi

main/manager-api/src/main/resources/i18n/messages_zh_CN.properties

@@ -160,10 +160,42 @@
 10151=\u8BF7\u5148\u4E0A\u4F20\u97F3\u9891\u6587\u4EF6
 10152=\u6A21\u578B\u914D\u7F6E\u672A\u627E\u5230
 10153=\u6A21\u578B\u7C7B\u578B\u672A\u627E\u5230
-10154=\u8BAD\u7EC3\u5931\u8D25
+10154=\u8BAD\u7EC3\u5931\u8D25: {0}
 10155=\u706B\u5C71\u5F15\u64CE\u7F3A\u5C11\u914D\u7F6E
 10156=\u54CD\u5E94\u683C\u5F0F\u9519\u8BEF\uFF0C\u7F3A\u5C11BaseResp\u5B57\u6BB5
 10157=\u8BF7\u6C42\u5931\u8D25
-10158=\u514B\u9686\u8272\u97F3:
+10158=\u514B\u9686\u97F3\u8272:
 10159=\u97F3\u8272ID\u5DF2\u5B58\u5728
-10160=\u706B\u5C71\u5F15\u64CE\u97F3\u8272ID\u683C\u5F0F\u9519\u8BEF\uFF0C\u5FC5\u987B\u4EE5S_\u5F00\u5934
+10160=\u706B\u5C71\u5F15\u64CE\u97F3\u8272ID\u683C\u5F0F\u9519\u8BEF\uFF0C\u5FC5\u987B\u4EE5S_\u5F00\u5934
+10161=Mac\u5730\u5740\u5DF2\u5B58\u5728
+10162=\u6A21\u578B\u4F9B\u5E94\u5668\u4E0D\u5B58\u5728
+10163=\u77E5\u8BC6\u5E93\u8BB0\u5F55\u4E0D\u5B58\u5728
+10164=RAG\u914D\u7F6E\u672A\u627E\u5230
+10165=RAG\u914D\u7F6E\u7C7B\u578B\u9519\u8BEF
+10166=\u9ED8\u8BA4RAG\u914D\u7F6E\u672A\u627E\u5230
+10167=RAG\u8C03\u7528\u5931\u8D25\uFF0C{0}
+10168=\u4E0A\u4F20\u6587\u4EF6\u5931\u8D25
+10169=\u60A8\u6CA1\u6709\u6743\u9650\u64CD\u4F5C\u8BE5\u8BB0\u5F55
+10170=\u77E5\u8BC6\u5E93\u540D\u79F0\u91CD\u590D
+10171=RAG\u914D\u7F6E\u4F53\u7684base_url\u4E0D\u80FD\u4E3A\u7A7A
+10172=RAG\u914D\u7F6E\u4F53\u7684api_key\u4E0D\u80FD\u4E3A\u7A7A
+10173=RAG\u914D\u7F6E\u4F53\u7684api_key\u4E0D\u80FD\u4E3A\u7A7A\uFF0C\u8BF7\u66F4\u6362\u4E3A\u5728\u53D6\u7684API\u53C2\u6570
+10174=RAG\u914D\u7F6E\u4F53\u7684base_url\u683C\u5F0F\u9519\u8BEF\uFF0C\u5FC5\u987B\u4EE5http\u6216https\u5F00\u5934
+10175=mac\u5730\u5740\u4E0D\u80FD\u4E3A\u7A7A
+10176=RAG\u914D\u7F6E\u4F53\u7684dataset_id\u4E0D\u80FD\u4E3A\u7A7A
+10177=RAG\u914D\u7F6E\u4F53\u7684model_id\u4E0D\u80FD\u4E3A\u7A7A
+10178=RAG\u914D\u7F6E\u4F53\u7684dataset_id\u548Cmodel_id\u4E0D\u80FD\u4E3A\u7A7A
+10179=\u6587\u4EF6\u540D\u79F0\u4E0D\u80FD\u4E3A\u7A7A
+10180=\u6587\u4EF6\u5185\u5BB9\u4E0D\u80FD\u4E3A\u7A7A
+10181=\u97F3\u8272\u514B\u9686\u540D\u79F0\u4E0D\u80FD\u4E3A\u7A7A
+10182=\u97F3\u8272\u514B\u9686\u97F3\u9891\u4E0D\u5B58\u5728
+10183=\u9ED8\u8BA4\u667A\u80FD\u4F53\u672A\u627E\u5230
+10184=\u4E0D\u652F\u6301\u7684\u9002\u914D\u5668\u7C7B\u578B
+10185=RAG\u914D\u7F6E\u9A8C\u8BC1\u5931\u8D25
+10186=\u9002\u914D\u5668\u521B\u5EFA\u5931\u8D25
+10187=\u9002\u914D\u5668\u521D\u59CB\u5316\u5931\u8D25
+10188=\u9002\u914D\u5668\u8FDE\u63A5\u6D4B\u8BD5\u5931\u8D25
+10189=\u9002\u914D\u5668\u64CD\u4F5C\u5931\u8D25
+10190=\u9002\u914D\u5668\u672A\u627E\u5230
+10191=\u9002\u914D\u5668\u7F13\u5B58\u9519\u8BEF
+10192=\u9002\u914D\u5668\u7C7B\u578B\u672A\u627E\u5230

main/manager-api/src/main/resources/i18n/messages_zh_TW.properties

@@ -164,6 +164,38 @@
 10155=\u706B\u5C71\u5F15\u64CE\u7F3A\u5C11appid\u6216access_token
 10156=\u97FF\u61C9\u683C\u5F0F\u932F\u8AA4\uFF0C\u7F3A\u5C11BaseResp\u5B57\u6BB5
 10157=\u8ACB\u6C42\u5931\u6557
-10158=\u514B\u9686\u8A9E\u97F3:
+10158=\u514b\u9686\u97f3\u8272:
 10159=\u97F3\u8272ID\u5DF2\u5B58\u5728
-10160=\u706B\u5C71\u5F15\u64CE\u97F3\u8272ID\u683C\u5F0F\u932F\u8AA4\uFF0C\u5FC5\u9808\u4EE5S_\u958B\u982D
+10160=\u706B\u5C71\u5F15\u64CE\u97F3\u8272ID\u683C\u5F0F\u932F\u8AA4\uFF0C\u5FC5\u9808\u4EE5S_\u958B\u982D
+10161=Mac\u5730\u5740\u5DF2\u5B58\u5728
+10162=\u6A21\u578B\u63D0\u4F9B\u5546\u4E0D\u5B58\u5728
+10163=\u77E5\u8B58\u5EAB\u8A18\u9304\u4E0D\u5B58\u5728
+10164=RAG\u914D\u7F6E\u672A\u627E\u5230
+10165=RAG\u914D\u7F6E\u985E\u578B\u932F\u8AA4
+10166=\u9810\u8A2DRAG\u914D\u7F6E\u672A\u627E\u5230
+10167=\u0052\u0041\u0047\u8abf\u7528\u5931\u6557\uFF0C{0}
+10168=\u4E0A\u50B3\u6587\u4EF6\u5931\u6557
+10169=\u60A8\u6C92\u6709\u6B0A\u9650\u64CD\u4F5C\u8A72\u8A18\u9304
+10170=\u77E5\u8B58\u5EAB\u540D\u7A31\u91CD\u8907
+10171=\u0052\u0041\u0047\u914D\u7F6E\u4F53\u7684base_url\u4E0D\u80FD\u4E3A\u7A7A
+10172=\u0052\u0041\u0047\u914D\u7F6E\u4F53\u7684api_key\u4E0D\u80FD\u4E3A\u7A7A
+10173=\u0052\u0041\u0047\u914D\u7F6E\u4F53\u7684api_key\u4E0D\u80FD\u4E3A\u7A7A\uFF0C\u8BF7\u66F4\u6362\u4E3A\u5728\u53D6\u7684API\u53C2\u6570
+10174=\u0052\u0041\u0047\u914D\u7F6E\u4F53\u7684base_url\u683C\u5F0F\u9519\u8BEF\uFF0C\u5FC5\u987B\u4EE5http\u6216https\u5F00\u5934
+10175=mac\u5730\u5740\u4E0D\u80FD\u4E3A\u7A7A
+10176=\u0052\u0041\u0047\u914D\u7F6E\u4F53\u7684dataset_id\u4E0D\u80FD\u4E3A\u7A7A
+10177=\u0052\u0041\u0047\u914D\u7F6E\u4F53\u7684model_id\u4E0D\u80FD\u4E3A\u7A7A
+10178=\u0052\u0041\u0047\u914D\u7F6E\u4F53\u7684dataset_id\u548Cmodel_id\u4E0D\u80FD\u4E3A\u7A7A
+10179=\u6587\u4ef6\u540d\u7a31\u4e0d\u80fd\u70ba\u7a7a
+10180=\u6587\u4ef6\u5185\u5bb9\u4e0d\u80fd\u70ba\u7a7a
+10181=\u97f3\u8272\u514b\u9686\u540d\u7a31\u4e0d\u80fd\u70ba\u7a7a
+10182=\u97f3\u8272\u514b\u9686\u97f3\u983b\u4e0d\u5b58\u5728
+10183=\u9ed8\u8ba4\u667a\u80fd\u4f53\u672a\u627e\u5230
+10184=\u4E0D\u652F\u6301\u7684\u9002\u914D\u5668\u985E\u578B
+10185=RAG\u914D\u7F6E\u9A57\u8B49\u5931\u6557
+10186=\u9002\u914D\u5668\u5275\u5EFA\u5931\u6557
+10187=\u9002\u914D\u5668\u521D\u59CB\u5316\u5931\u6557
+10188=\u9002\u914D\u5668\u9023\u63A5\u6E2C\u8A66\u5931\u6557
+10189=\u9002\u914D\u5668\u64CD\u4F5C\u5931\u6557
+10190=\u9002\u914D\u5668\u672A\u627E\u5230
+10191=\u9002\u914D\u5668\u7F13\u5B58\u932F\u8AA4
+10192=\u9002\u914D\u5668\u985E\u578B\u672A\u627E\u5230

main/manager-api/src/main/resources/i18n/validation_de_DE.properties

@@ -0,0 +1,34 @@
+#Deutsch
+id.require=ID darf nicht leer sein
+id.null=ID muss leer sein
+
+sort.number=Der Sortierwert darf nicht kleiner als 0 sein
+page.number=Der Seitenwert darf nicht kleiner als 0 sein
+limit.number=Der Limit-Wert darf nicht kleiner als 0 sein
+
+sysdict.type.require=Der Wörterbuchtyp darf nicht leer sein
+sysdict.name.require=Der Wörterbuchname darf nicht leer sein
+sysdict.label.require=Wörterbuch-Label darf nicht leer sein
+
+sysparams.paramcode.require=Parameter-Code darf nicht leer sein
+sysparams.paramvalue.require=Parameter-Werte dürfen nicht leer sein
+sysparams.valuetype.require=Werttyp darf nicht leer sein
+sysparams.valuetype.pattern=Werttyp muss string, number, boolean oder array sein
+
+sysuser.username.require=Der Benutzername darf nicht leer sein
+sysuser.password.require=Das Passwort darf nicht leer sein
+sysuser.realname.require=Der echte Name darf nicht leer sein
+sysuser.gender.range=Geschlecht liegt im Bereich von 0 bis 2
+sysuser.email.error=Falsches E-Mail-Format
+sysuser.deptId.require=Abteilungen dürfen nicht leer sein
+sysuser.status.range=Status liegt im Bereich von 0 bis 1
+sysuser.captcha.require=Das Captcha darf nicht leer sein
+sysuser.uuid.require=Der eindeutige Identifikator darf nicht leer sein
+
+timbre.languages.require=Die Sprache des Klangs darf nicht leer sein
+timbre.name.require=Der Name des Klangs darf nicht leer sein
+timbre.ttsModelId.require=Die TTS-Modell-ID des Klangs darf nicht leer sein
+timbre.ttsVoice.require=Die TTS-Stimme des Klangs darf nicht leer sein
+
+ota.device.not.found=Gerät nicht gefunden
+ota.device.need.bind={0}

main/manager-api/src/main/resources/i18n/validation_vi_VN.properties

@@ -0,0 +1,34 @@
+# Tiếng Việt
+id.require=ID không được để trống
+id.null=ID phải để trống
+
+sort.number=Giá trị sắp xếp không thể nhỏ hơn 0
+page.number=Giá trị trang không thể nhỏ hơn 0
+limit.number=Giá trị giới hạn không thể nhỏ hơn 0
+
+sysdict.type.require=Loại từ điển không được để trống
+sysdict.name.require=Tên từ điển không được để trống
+sysdict.label.require=Thẻ từ điển không được để trống
+
+sysparams.paramcode.require=Mã tham số không được để trống
+sysparams.paramvalue.require=Giá trị tham số không được để trống
+sysparams.valuetype.require=Loại giá trị không được để trống
+sysparams.valuetype.pattern=Loại giá trị phải là chuỗi, số, boolean hoặc mảng
+
+sysuser.username.require=Tên người dùng không được để trống
+sysuser.password.require=Mật khẩu không được để trống
+sysuser.realname.require=Tên thật không được để trống
+sysuser.gender.range=Giới tính phải từ 0 đến 2
+sysuser.email.error=Định dạng email không chính xác
+sysuser.deptId.require=Phòng ban không được để trống
+sysuser.status.range=Trạng thái phải từ 0 đến 1
+sysuser.captcha.require=Mã xác thực không được để trống
+sysuser.uuid.require=Định danh duy nhất không được để trống
+
+timbre.languages.require=Ngôn ngữ của âm sắc không được để trống
+timbre.name.require=Tên âm sắc không được để trống
+timbre.ttsModelId.require=ID mô hình TTS của âm sắc không được để trống
+timbre.ttsVoice.require=Giọng TTS của âm sắc không được để trống
+
+ota.device.not.found=Không tìm thấy thiết bị
+ota.device.need.bind={0}