From da2804bcc863285c10204cfad17f83be936cdd5f Mon Sep 17 00:00:00 2001 From: kalicyh <34980061+kaliCYH@users.noreply.github.com> Date: Mon, 17 Feb 2025 02:44:05 +0800 Subject: [PATCH 1/4] =?UTF-8?q?=F0=9F=8E=88=20perf:=20=E4=BC=98=E5=8C=96?= =?UTF-8?q?=E6=89=93=E5=8C=85=E9=80=9F=E5=BA=A6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Dockerfile | 32 +-- ZhiKongTaiWeb/yarn.lock | 475 ++++++++++++++++++++++++++++++++++++++++ 2 files changed, 482 insertions(+), 25 deletions(-) create mode 100644 ZhiKongTaiWeb/yarn.lock diff --git a/Dockerfile b/Dockerfile index 5ae890f2..19f6f31f 100644 --- a/Dockerfile +++ b/Dockerfile @@ -3,38 +3,22 @@ FROM node:18 AS frontend-builder WORKDIR /app/ZhiKongTaiWeb -# 配置npm使用淘宝源 -RUN npm config set registry https://registry.npmmirror.com +RUN corepack enable && yarn config set registry https://registry.npmmirror.com -COPY ZhiKongTaiWeb/package*.json ./ +COPY ZhiKongTaiWeb/package.json ZhiKongTaiWeb/yarn.lock ./ -RUN npm install +RUN mkdir node_modules && yarn install --frozen-lockfile -COPY ZhiKongTaiWeb . +COPY ZhiKongTaiWeb . +RUN yarn build -RUN npm run build - -# 第二阶段：构建Python依赖 +# 第二阶段：构建 Python 依赖 FROM python:3.10-slim AS builder WORKDIR /app COPY requirements.txt . -# 使用清华源加速apt安装 -RUN rm -rf /etc/apt/sources.list.d/* && \ - echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm main contrib non-free non-free-firmware" > /etc/apt/sources.list && \ - echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-updates main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \ - echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-backports main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \ - echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian-security bookworm-security main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \ - apt-get clean && \ - apt-get update && \ - apt-get install -y --no-install-recommends \ - gcc \ - libopus-dev \ - ffmpeg && \ - rm -rf /var/lib/apt/lists/* - # 安装Python依赖到虚拟环境 RUN python -m venv /opt/venv ENV PATH="/opt/venv/bin:$PATH" @@ -53,9 +37,7 @@ RUN rm -rf /etc/apt/sources.list.d/* && \ echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian-security bookworm-security main contrib non-free non-free-firmware" >> /etc/apt/sources.list && \ apt-get clean && \ apt-get update && \ - apt-get install -y --no-install-recommends \ - libopus0 \ - ffmpeg && \ + apt-get install -y --no-install-recommends libopus0 ffmpeg && \ apt-get clean && \ rm -rf /var/lib/apt/lists/* diff --git a/ZhiKongTaiWeb/yarn.lock b/ZhiKongTaiWeb/yarn.lock new file mode 100644 index 00000000..593b431c --- /dev/null +++ b/ZhiKongTaiWeb/yarn.lock @@ -0,0 +1,475 @@ +# THIS IS AN AUTOGENERATED FILE. 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deletions(-) create mode 100644 docs/Deployment-silm.md diff --git a/docs/Deployment-silm.md b/docs/Deployment-silm.md new file mode 100644 index 00000000..45b121ff --- /dev/null +++ b/docs/Deployment-silm.md @@ -0,0 +1,188 @@ +# 部署指南 + +本项目支持 **x86** 和 **arm64** 架构，可运行于国产操作系统。 + +## 方式一：快速部署（推荐） + +### 1. 安装 Docker + +如果未安装 Docker，可参考 [Docker 安装教程](https://www.runoob.com/docker/ubuntu-docker-install.html)。 + +### 2. 创建项目目录 + +选择一个空目录作为 **项目目录**。 + +### 3. 下载配置文件 + +访问 [config.yaml](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/config.yaml)，点击 `RAW` 旁的下载按钮，保存到 **项目目录**。 + +### 4. 运行 Docker + +打开终端，`cd` 进入 **项目目录**，执行： + +```sh +docker run -d --name xiaozhi-esp32-server --restart always --security-opt seccomp:unconfined \ + -p 8000:8000 \ + -v $(pwd)/config.yaml:/opt/xiaozhi-esp32-server/config.yaml \ + ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest +``` + +### 5. 确认运行状态 + +```sh +docker ps # 查看容器状态 +docker logs -f xiaozhi-esp32-server # 查看日志 +``` + +## 方式二：使用 Docker Compose 部署 + +### 1. 创建 `docker-compose.yml` +在 `项目目录` 下创建 `docker-compose.yml` 文件，内容如下： + +```yaml +version: '3' +services: + xiaozhi-esp32-server: + image: ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest + container_name: xiaozhi-esp32-server + restart: always + security_opt: + - seccomp:unconfined + ports: + - "8000:8000" + volumes: + - ./config.yaml:/opt/xiaozhi-esp32-server/config.yaml +``` + +### 2. 启动服务 +```sh +docker-compose up -d +``` + +### 3. 确认运行状态 +```sh +docker-compose ps +docker-compose logs -f +``` + +### 4. 停止和删除容器 +```sh +docker-compose down +``` + +### 5. 版本升级 + +#### 备份配置文件 +```sh +cp config.yaml config_backup.yaml +``` + +#### 更新 Docker 镜像 +```sh +docker-compose pull +docker-compose down +docker-compose up -d +``` + + +## 方式三：源码部署（免环境部署/可修改代码） + +### 1. 下载源码 + +```sh +git clone https://github.com/xinnan-tech/xiaozhi-esp32-server.git +cd xiaozhi-esp32-server +``` + +或手动下载 [ZIP 包](https://github.com/xinnan-tech/xiaozhi-esp32-server/archive/refs/heads/main.zip)，解压后重命名为 `xiaozhi-esp32-server`。 + +### 2. 运行 Docker + +```sh +docker run -d --name xiaozhi-esp32-server --restart always --security-opt seccomp:unconfined \ + -p 8000:8000 \ + -v ./:/opt/xiaozhi-esp32-server \ + ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest +``` + +### 3. 修改代码 & 重启 Docker + +```sh +docker restart xiaozhi-esp32-server +``` + +## 方式三：本地运行（适用于开发） + +### 1. 安装环境 + +```sh +conda create -n xiaozhi-esp32-server python=3.10 -y +conda activate xiaozhi-esp32-server +``` + +#### Mac/Windows: + +```sh +conda install conda-forge::libopus conda-forge::ffmpeg +``` + +#### Ubuntu: + +```sh +apt-get install libopus0 ffmpeg +``` + +### 2. 下载源码 & 安装依赖 + +```sh +git clone https://github.com/xinnan-tech/xiaozhi-esp32-server.git +cd xiaozhi-esp32-server +pip install -r requirements.txt +``` + +### 3. 运行项目 + +```sh +python app.py +``` + +## 版本升级 + +```sh +docker stop xiaozhi-esp32-server +docker rm xiaozhi-esp32-server +docker rmi ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest +``` + +然后重新按照 **方式一** 或 **方式二** 运行 Docker。 + +## 重要配置 + +修改 `config.yaml` 以适配不同 LLM 和 TTS 组件。 + +示例： + +```yaml +selected_module: + ASR: FunASR + VAD: SileroVAD + LLM: ChatGLMLLM + TTS: EdgeTTS +``` + +如需使用 `Dify` 或 `DeepSeekLLM`，修改 `LLM` 部分并填写密钥。 + +## 模型文件下载 + +语音转文字默认使用 `SenseVoiceSmall`，需下载 `model.pt` 并存放至 `model/SenseVoiceSmall` 目录。 + +- [阿里魔塔下载](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt) +- [百度网盘下载](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码：`qvna` + +--- + +如遇问题，可参考 `docker logs -f xiaozhi-esp32-server` 进行排查。 + +**至此，部署完成！** 🚀 + + diff --git a/docs/Deployment.md b/docs/Deployment.md index 63911b71..d54dc0e5 100644 --- a/docs/Deployment.md +++ b/docs/Deployment.md @@ -17,46 +17,7 @@ docker镜像已支持x86架构、arm64架构的CPU，支持在国产操作系统 在页面的右侧找到名称为`RAW`按钮，在`RAW`按钮的旁边，找到下载的图标，点击下载按钮，下载`config.yaml`文件。 把文件下载到你的 `项目目录`。 -## 4. 修改配置文件 - -修改刚才你下载的`config.yaml`文件，配置本项目所需的各种参数。默认的LLM使用的是`ChatGLMLLM` -，你需要配置密钥，因为他们的模型，虽然有免费的，但是仍要去[官网](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)注册密钥，才能启动。 - -默认的TTS使用的是`EdgeTTS`，这个无需配置，如果你需要更换成`豆包TTS`，则需要配置密钥。 - -配置说明：这里是各个功能使用的默认组件，例如LLM默认使用`ChatGLMLLM`模型。如果需要切换模型，就是改对应的名称。 - -本项目的默认配置原则是成本最低配置原则（`glm-4-flash`和`EdgeTTS`都是免费的），如果需要更优的更快的搭配，需要自己结合部署环境切换各组件的使用。 - -``` -selected_module: - ASR: FunASR - VAD: SileroVAD - LLM: ChatGLMLLM - TTS: EdgeTTS -``` - -比如修改`LLM`使用的组件，就看本项目支持哪些`LLM` API接口，当前支持的是`openai`、`dify`。欢迎验证和支持更多LLM平台的接口。 - -使用时，在`selected_module`修改成对应的如下LLM配置的名称： - -``` -LLM: - AliLLM: - type: openai - ... - DeepSeekLLM: - type: openai - ... - ChatGLMLLM: - type: openai - ... - DifyLLM: - type: dify - ... -``` - -有些服务，比如如果你使用`Dify`、`豆包的TTS`，是需要密钥的，记得在配置文件加上哦！ +## 4.[跳转到配置项目文件](#配置项目) ## 5. 执行docker命令 @@ -75,47 +36,16 @@ dir docker run -d --name xiaozhi-esp32-server --restart always --security-opt seccomp:unconfined -p 8000:8000 -v $(pwd)/config.yaml:/opt/xiaozhi-esp32-server/config.yaml ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest ``` -如果首次执行，可能需要几分钟时间，你要耐心等待他完成拉取。正常拉取完成后，你可以在命令行执行以下命令查看服务是否启动成功 +## 6.[跳转到运行状态确认](#运行状态确认) -``` -docker ps -``` - -如果你能看到`xiaozhi-server`，说明服务启动成功。那你还可以进一步执行以下命令，查看服务的日志 - -``` -docker logs -f xiaozhi-esp32-server -``` - -如果你能看到，类似以下日志,则是本项目服务启动成功的标志。 - -``` -2025-xx-xx xx:51:59,492 - core.server - INFO - Server is running at ws://xx.xx.xx.xxx:8000 -2025-xx-xx xx:51:59,516 - websockets.server - INFO - server listening on 0.0.0.0:8000 -``` - -接下来，你就可以开始 `编译esp32固件`了，请往下翻，翻到编译`esp32固件`相关章节。那么由于你是用docker部署，你要自己查看自己本机电脑的ip是多少。 -正常来说，假设你的ip是`192.168.1.25`，那么你的接口地址就是：`ws://192.168.1.25:8000`。这个信息很有用的，后面`编译esp32固件` -需要用到。 - -请注意，你的接口地址是`websocket`协议的地址，你可以使用`apifox`等工具调试。但是不能直接用浏览器打开访问，如果用浏览器打开，日志会显示错误，会让你怀疑是否部署成功了。 - -后期如果想升级版本，可以这么操作 - -1、备份好`config.yaml`文件，一些关键的配置到时复制到新的`config.yaml`文件里。 - -2、执行以下命令 - -``` -docker stop xiaozhi-esp32-server -docker rm xiaozhi-esp32-server -docker rmi ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest -``` +## [跳转到版本升级操作](#版本升级操作) 3.按本教程重新来一遍 # 方式二：借助docker环境运行部署 +## 1.克隆项目 + 这个方法的原理，其实是和第一种方式类似。区别在于，第一种方式只要下载一个配置文件，而本方式要下载项目源码。 优点就是源码在你主机躺着，你可以使用本机的代码编辑器加载项目和修改源码。每次修改完项目，想要看效果，那就要重启docker。 @@ -131,15 +61,11 @@ docker rmi ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest 点击它，下载本项目源码压缩包。下载到你电脑后，解压它，此时它的名字可能叫`xiaozhi-esp32-server-main` 你需要把它重命名成`xiaozhi-esp32-server`，好了请记住这个目录，我们暂且称它为`项目目录`。 -下载源码后，需要下载模型文件。 默认使用`SenseVoiceSmall`模型，进行语音转文字。因为模型较大，需要独立下载，下载后把`model.pt` -文件放在`model/SenseVoiceSmall` -目录下。下面两个下载路线任选一个。 +## 2.[跳转到下载语音识别模型文件](#模型文件) -- 线路一：阿里魔塔下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt) -- 线路二：百度网盘下载[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码: - `qvna` +## 3.[跳转到配置项目文件](#配置项目) -下载模型后，需要按照`方式一：docker快速部署`修改配置文件`config.yaml` +## 4.运行docker 修改完配置后，打开命令行工具，`cd`进入到你的项目目录下，执行以下命令 @@ -150,22 +76,7 @@ docker run -d --name xiaozhi-esp32-server --restart always --security-opt seccom ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest ``` -``` -docker logs -f xiaozhi-esp32-server -``` - -如果你能看到，类似以下日志,则是本项目服务启动成功的标志。 - -``` -2025-xx-xx xx:51:59,492 - core.server - INFO - Server is running at ws://xx.xx.xx.xxx:8000 -2025-xx-xx xx:51:59,516 - websockets.server - INFO - server listening on 0.0.0.0:8000 -``` - -接下来，你就可以开始 `编译esp32固件`了，请往下翻，翻到编译`esp32固件`相关章节。那么由于你是用docker部署，你要自己查看自己本机电脑的ip是多少。 -正常来说，假设你的ip是`192.168.1.25`，那么你的接口地址就是：`ws://192.168.1.25:8000`。这个信息很有用的，后面`编译esp32固件` -需要用到。 - -请注意，你的接口地址是`websocket`协议的地址，你可以使用`apifox`等工具调试。但是不能直接用浏览器打开访问，如果用浏览器打开，日志会显示错误，会让你怀疑是否部署成功了。 +## 5.[跳转到运行状态确认](#运行状态确认) 后期，如果你修改了代码，想让新代码跑起来，可以用以下命令让docker容器重启： @@ -219,16 +130,23 @@ pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ pip install -r requirements.txt ``` -## 3.下载语音识别模型 +## 3.[跳转到下载语音识别模型文件](#模型文件) -默认使用`SenseVoiceSmall`模型，进行语音转文字。因为模型较大，需要独立下载，下载后把`model.pt`文件放在`model/SenseVoiceSmall` -目录下。下面两个下载路线任选一个。 +## 4.[跳转到配置项目文件](#配置项目) -- 线路一：阿里魔塔下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt) -- 线路二：百度网盘下载[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码: - `qvna` +## 5.运行项目 -## 4.配置项目 +``` +# 确保在本项目的根目录下执行 +conda activate xiaozhi-esp32-server +python app.py +``` + +## 6.[跳转到运行状态确认](#运行状态确认) + +# 汇总 + +## 配置项目 修改`config.yaml`文件，配置本项目所需的各种参数。默认的LLM使用的是`ChatGLMLLM` ，你需要配置密钥，因为他们的模型，虽然有免费的，但是仍要去[官网](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)注册密钥，才能启动。 @@ -271,23 +189,54 @@ LLM: 有些服务，比如如果你使用`Dify`、`豆包的TTS`，是需要密钥的，记得在配置文件加上哦！ -## 5.运行项目 +## 模型文件 -启动项目 +下载源码后，需要下载模型文件。 默认使用`SenseVoiceSmall`模型，进行语音转文字。因为模型较大，需要独立下载，下载后把`model.pt` +文件放在`model/SenseVoiceSmall` +目录下。下面两个下载路线任选一个。 + +- 线路一：阿里魔塔下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt) +- 线路二：百度网盘下载[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码: + `qvna` + + +## 运行状态确认 + +如果首次执行，可能需要几分钟时间，你要耐心等待他完成拉取。正常拉取完成后，你可以在命令行执行以下命令查看服务是否启动成功 ``` -# 确保在本项目的根目录下执行 -conda activate xiaozhi-esp32-server -python app.py +docker ps ``` -启动后，会看到类似以下日志 +如果你能看到`xiaozhi-server`，说明服务启动成功。那你还可以进一步执行以下命令，查看服务的日志 ``` -2025-xx-xx xx:51:59,492 - core.server - INFO - Server is running at ws://192.168.1.25:8000 +docker logs -f xiaozhi-esp32-server +``` + +如果你能看到，类似以下日志,则是本项目服务启动成功的标志。 + +``` +2025-xx-xx xx:51:59,492 - core.server - INFO - Server is running at ws://xx.xx.xx.xxx:8000 2025-xx-xx xx:51:59,516 - websockets.server - INFO - server listening on 0.0.0.0:8000 ``` -其中上面的`ws://192.168.1.25:8000`就是本项目提供的接口地址了，当然你自己的机器和我的是不一样的，记得要找到自己的地址。 +接下来，你就可以开始 `编译esp32固件`了，请往下翻，翻到编译`esp32固件`相关章节。那么由于你是用docker部署，你要自己查看自己本机电脑的ip是多少。 +正常来说，假设你的ip是`192.168.1.25`，那么你的接口地址就是：`ws://192.168.1.25:8000`。这个信息很有用的，后面`编译esp32固件` +需要用到。 -请注意，你的接口地址是`websocket`协议的地址，你可以使用`apifox`等工具调试。但是不能直接用浏览器打开访问，如果用浏览器打开，日志会显示错误，会让你怀疑是否部署成功了。 \ No newline at end of file +请注意，你的接口地址是`websocket`协议的地址，你可以使用`apifox`等工具调试。但是不能直接用浏览器打开访问，如果用浏览器打开，日志会显示错误，会让你怀疑是否部署成功了。 + +## 版本升级操作 + +如果想升级版本，可以这么操作 + +1、备份好`config.yaml`文件，一些关键的配置到时复制到新的`config.yaml`文件里。 + +2、执行以下命令 + +``` +docker stop xiaozhi-esp32-server +docker rm xiaozhi-esp32-server +docker rmi ccr.ccs.tencentyun.com/xinnan/xiaozhi-esp32-server:latest +``` \ No newline at end of file From e344bd0aee4ce52d15d832253b2602d7833745ac Mon Sep 17 00:00:00 2001 From: kalicyh <34980061+kaliCYH@users.noreply.github.com> Date: Mon, 17 Feb 2025 03:21:22 +0800 Subject: [PATCH 3/4] =?UTF-8?q?=F0=9F=93=83=20docs(readme):=20=E8=A1=A5?= =?UTF-8?q?=E5=85=85?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 8ed3a29c..8f7c8c57 100644 --- a/README.md +++ b/README.md @@ -123,6 +123,8 @@ server: ### 一、[部署文档](./docs/Deployment.md) +[精简版部署文档](./docs/Deployment-silm.md) + 本项目支持以下三种部署方式，您可根据实际需求选择： 1. **[Docker 快速部署](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%BF%AB%E9%80%9F%E9%83%A8%E7%BD%B2)** From f64f578d52766ad4f48f0a3decb0a45cf50a8e1d Mon Sep 17 00:00:00 2001 From: Kevincoooool <33611679+Kevincoooool@users.noreply.github.com> Date: Mon, 17 Feb 2025 12:00:52 +0800 Subject: [PATCH 4/4] Update gpt_sovits_v2.py --- core/providers/tts/gpt_sovits_v2.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/core/providers/tts/gpt_sovits_v2.py b/core/providers/tts/gpt_sovits_v2.py index 486db187..709e5338 100644 --- a/core/providers/tts/gpt_sovits_v2.py +++ b/core/providers/tts/gpt_sovits_v2.py @@ -3,9 +3,10 @@ import uuid import json import base64 import requests +import logging from datetime import datetime from core.providers.tts.base import TTSProviderBase - +logger = logging.getLogger(__name__) class TTSProvider(TTSProviderBase): def __init__(self, config, delete_audio_file):