
py-xiaozhi
python版本的小智ai,主要帮助那些没有硬件却想体验小智功能的人,如果可以请点个小星星!
Stars: 2517

py-xiaozhi is a Python-based XiaoZhi voice client designed for learning through code and experiencing AI XiaoZhi's voice functions without hardware conditions. The repository is based on the xiaozhi-esp32 port. It supports AI voice interaction, visual multimodal capabilities, IoT device integration, online music playback, voice wake-up, automatic conversation mode, graphical user interface, command-line mode, cross-platform support, volume control, session management, encrypted audio transmission, automatic captcha handling, automatic MAC address retrieval, code modularization, and stability optimization.
README:
简体中文 | English
py-xiaozhi 是一个使用 Python 实现的小智语音客户端,旨在通过代码学习和在没有硬件条件下体验 AI 小智的语音功能。 本仓库是基于xiaozhi-esp32移植
- AI语音交互:支持语音输入与识别,实现智能人机交互,提供自然流畅的对话体验
- 视觉多模态:支持图像识别和处理,提供多模态交互能力,理解图像内容
- 智能唤醒:支持多种唤醒词激活交互,免去手动操作的烦恼(可配置开启)
- 自动对话模式:实现连续对话体验,提升用户交互流畅度
- 系统控制工具:系统状态监控、应用程序管理、音量控制、设备管理等
- 日程管理工具:全功能日程管理,支持创建、查询、更新、删除事件,智能分类和提醒
- 定时任务工具:倒计时器功能,支持延时执行MCP工具,多任务并行管理
- 音乐播放工具:在线音乐搜索播放,支持播放控制、歌词显示、本地缓存管理
- 12306查询工具:12306铁路票务查询,支持车票查询、中转查询、列车路线查询
- 搜索工具:网络搜索和网页内容获取,支持必应搜索和智能内容解析
- 菜谱工具:丰富菜谱库,支持菜谱搜索、分类查询、智能推荐
- 地图工具:高德地图服务,支持地理编码、路径规划、周边搜索、天气查询
- 八字命理工具:传统八字命理分析,支持八字计算、婚姻分析、黄历查询
- 摄像头工具:图像捕获和AI分析,支持拍照识别和智能问答
- 设备管理架构:基于Thing模式的统一设备管理,支持属性和方法的异步调用
- 智能家居控制:支持灯光、音量、温度传感器等设备控制
- 状态同步机制:实时状态监控,支持增量更新和并发状态获取
- 可扩展设计:模块化设备驱动,易于添加新设备类型
- 多级音频处理:支持Opus编解码、实时重采样
- 语音活动检测:VAD检测器实现智能打断,支持语音活动实时监控
- 唤醒词检测:基于Sherpa-ONNX的离线语音识别,支持多唤醒词和拼音匹配
- 音频流管理:独立输入输出流,支持流重建和错误恢复
- 音频回声消除:集成WebRTC音频处理模块,提供高质量的回声消除功能
- 系统音频录制:支持系统音频录制,实现音频环回处理
- 图形化界面:基于PyQt5的现代GUI,支持小智表情与文本显示,增强视觉体验
- 命令行模式:支持CLI运行,适用于嵌入式设备或无GUI环境
- 系统托盘:后台运行支持,集成系统托盘功能
- 全局快捷键:支持全局快捷键操作,提升使用便捷性
- 设置界面:完整的设置管理界面,支持配置自定义
- 加密音频传输:支持WSS协议,保障音频数据的安全性,防止信息泄露
- 设备激活系统:支持v1/v2双协议激活,自动处理验证码和设备指纹
- 错误恢复:完整的错误处理和恢复机制,支持断线重连
- 系统兼容:兼容Windows 10+、macOS 10.15+和Linux系统
- 协议支持:支持WebSocket和MQTT双协议通信
- 多环境部署:支持GUI和CLI双模式,适应不同部署环境
- 平台优化:针对不同平台的音频和系统控制优化
- 模块化架构:清晰的代码结构和职责分离,便于二次开发
- 异步优先:基于asyncio的事件驱动架构,高性能并发处理
- 配置管理:分层配置系统,支持点记法访问和动态更新
- 日志系统:完整的日志记录和调试支持
- API文档:详细的代码文档和使用指南
- Python版本:3.9 - 3.12
- 操作系统:Windows 10+、macOS 10.15+、Linux
- 音频设备:麦克风和扬声器设备
- 网络连接:稳定的互联网连接(用于AI服务和在线功能)
- 内存:至少4GB RAM(推荐8GB+)
- 处理器:支持AVX指令集的现代CPU
- 存储:至少2GB可用磁盘空间(用于模型文件和缓存)
- 音频:支持16kHz采样率的音频设备
- 语音唤醒:需要下载Sherpa-ONNX语音识别模型
- 摄像头功能:需要摄像头设备和OpenCV支持
- 仔细阅读 项目文档 启动教程和文件说明都在里面了
- main是最新代码,每次更新都需要手动重新安装一次pip依赖防止我新增依赖后你们本地没有
- 事件驱动架构: 基于asyncio的异步事件循环,支持高并发处理
- 分层设计: 清晰的应用层、协议层、设备层、UI层分离
- 单例模式: 核心组件采用单例模式,确保资源统一管理
- 插件化: MCP工具系统和IoT设备支持插件化扩展
- 音频处理: Opus编解码、WebRTC回声消除、实时重采样、系统音频录制
- 语音识别: Sherpa-ONNX离线模型、语音活动检测、唤醒词识别
- 协议通信: WebSocket/MQTT双协议支持、加密传输、自动重连
- 配置系统: 分层配置、点记法访问、动态更新、JSON/YAML支持
- 异步优先: 全系统异步架构,避免阻塞操作
- 内存管理: 智能缓存、垃圾回收
- 音频优化: 5ms低延迟处理、队列管理、流式传输
- 并发控制: 任务池管理、信号量控制、线程安全
- 加密通信: WSS/TLS加密、证书验证
- 设备认证: 双协议激活、设备指纹识别
- 权限控制: 工具权限管理、API访问控制
- 错误隔离: 异常隔离、故障恢复、优雅降级
py-xiaozhi/
├── main.py # 应用程序主入口(CLI参数处理)
├── src/
│ ├── application.py # 应用程序核心逻辑
│ ├── audio_codecs/ # 音频编解码器
│ │ ├── aec_processor.py # 音频回声消除处理器
│ │ ├── audio_codec.py # 音频编解码基础类
│ │ └── system_audio_recorder.py # 系统音频录制器
│ ├── audio_processing/ # 音频处理模块
│ │ ├── vad_detector.py # 语音活动检测
│ │ └── wake_word_detect.py # 唤醒词检测
│ ├── core/ # 核心组件
│ │ ├── ota.py # 在线更新模块
│ │ └── system_initializer.py # 系统初始化器
│ ├── display/ # 显示界面抽象层
│ ├── iot/ # IoT设备管理
│ │ ├── thing.py # 设备基类
│ │ ├── thing_manager.py # 设备管理器
│ │ └── things/ # 具体设备实现
│ ├── mcp/ # MCP工具系统
│ │ ├── mcp_server.py # MCP服务器
│ │ └── tools/ # 各种工具模块
│ ├── protocols/ # 通信协议
│ ├── utils/ # 工具函数
│ └── views/ # UI视图组件
├── libs/ # 第三方原生库
│ ├── libopus/ # Opus音频编解码库
│ ├── webrtc_apm/ # WebRTC音频处理模块
│ └── SystemAudioRecorder/ # 系统音频录制工具
├── config/ # 配置文件目录
├── models/ # 语音模型文件
├── assets/ # 静态资源文件
├── scripts/ # 辅助脚本
├── requirements.txt # Python依赖包列表
└── build.json # 构建配置文件
# 克隆项目
git clone https://github.com/huangjunsen0406/py-xiaozhi.git
cd py-xiaozhi
# 安装依赖
pip install -r requirements.txt
# 代码格式化
./format_code.sh
# 运行程序 - GUI模式(默认)
python main.py
# 运行程序 - CLI模式
python main.py --mode cli
# 指定通信协议
python main.py --protocol websocket # WebSocket(默认)
python main.py --protocol mqtt # MQTT协议
-
异步优先: 使用
async/await
语法,避免阻塞操作 - 错误处理: 完整的异常处理和日志记录
-
配置管理: 使用
ConfigManager
统一配置访问 - 测试驱动: 编写单元测试,确保代码质量
-
添加MCP工具: 在
src/mcp/tools/
目录创建新工具模块 -
添加IoT设备: 继承
Thing
基类实现新设备 -
添加协议: 实现
Protocol
抽象基类 -
添加界面: 扩展
BaseDisplay
实现新的UI组件
+----------------+
| |
v |
+------+ 唤醒词/按钮 +------------+ | +------------+
| IDLE | -----------> | CONNECTING | --+-> | LISTENING |
+------+ +------------+ +------------+
^ |
| | 语音识别完成
| +------------+ v
+--------- | SPEAKING | <-----------------+
完成播放 +------------+
欢迎提交问题报告和代码贡献。请确保遵循以下规范:
- 代码风格符合PEP8规范
- 提交的PR包含适当的测试
- 更新相关文档
排名不分前后
Xiaoxia zhh827 四博智联-李洪刚 HonestQiao vonweller 孙卫公 isamu2025 Rain120 kejily 电波bilibili君 赛搏智能
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ESP32_AI_LLM is a project that uses ESP32 to connect to Xunfei Xinghuo, Dou Bao, and Tongyi Qianwen large models to achieve voice chat functions, supporting online voice wake-up, continuous conversation, music playback, and real-time display of conversation content on an external screen. The project requires specific hardware components and provides functionalities such as voice wake-up, voice conversation, convenient network configuration, music playback, volume adjustment, LED control, model switching, and screen display. Users can deploy the project by setting up Xunfei services, cloning the repository, configuring necessary parameters, installing drivers, compiling, and burning the code.

py-xiaozhi
py-xiaozhi is a Python-based XiaoZhi voice client designed for learning through code and experiencing AI XiaoZhi's voice functions without hardware conditions. The repository is based on the xiaozhi-esp32 port. It supports AI voice interaction, visual multimodal capabilities, IoT device integration, online music playback, voice wake-up, automatic conversation mode, graphical user interface, command-line mode, cross-platform support, volume control, session management, encrypted audio transmission, automatic captcha handling, automatic MAC address retrieval, code modularization, and stability optimization.

hugging-chat-api
Unofficial HuggingChat Python API for creating chatbots, supporting features like image generation, web search, memorizing context, and changing LLMs. Users can log in, chat with the ChatBot, perform web searches, create new conversations, manage conversations, switch models, get conversation info, use assistants, and delete conversations. The API also includes a CLI mode with various commands for interacting with the tool. Users are advised not to use the application for high-stakes decisions or advice and to avoid high-frequency requests to preserve server resources.

elia
Elia is a powerful terminal user interface designed for interacting with large language models. It allows users to chat with models like Claude 3, ChatGPT, Llama 3, Phi 3, Mistral, and Gemma. Conversations are stored locally in a SQLite database, ensuring privacy. Users can run local models through 'ollama' without data leaving their machine. Elia offers easy installation with pipx and supports various environment variables for different models. It provides a quick start to launch chats and manage local models. Configuration options are available to customize default models, system prompts, and add new models. Users can import conversations from ChatGPT and wipe the database when needed. Elia aims to enhance user experience in interacting with language models through a user-friendly interface.

EDDI
E.D.D.I (Enhanced Dialog Driven Interface) is an enterprise-certified chatbot middleware that offers advanced prompt and conversation management for Conversational AI APIs. Developed in Java using Quarkus, it is lean, RESTful, scalable, and cloud-native. E.D.D.I is highly scalable and designed to efficiently manage conversations in AI-driven applications, with seamless API integration capabilities. Notable features include configurable NLP and Behavior rules, support for multiple chatbots running concurrently, and integration with MongoDB, OAuth 2.0, and HTML/CSS/JavaScript for UI. The project requires Java 21, Maven 3.8.4, and MongoDB >= 5.0 to run. It can be built as a Docker image and deployed using Docker or Kubernetes, with additional support for integration testing and monitoring through Prometheus and Kubernetes endpoints.

multi-agent-orchestrator
Multi-Agent Orchestrator is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries to the most suitable agent based on context and content, supports dual language implementation in Python and TypeScript, offers flexible agent responses, context management across agents, extensible architecture for customization, universal deployment options, and pre-built agents and classifiers. It is suitable for various applications, from simple chatbots to sophisticated AI systems, accommodating diverse requirements and scaling efficiently.

gemini-next-chat
Gemini Next Chat is an open-source, extensible high-performance Gemini chatbot framework that supports one-click free deployment of private Gemini web applications. It provides a simple interface with image recognition and voice conversation, supports multi-modal models, talk mode, visual recognition, assistant market, support plugins, conversation list, full Markdown support, privacy and security, PWA support, well-designed UI, fast loading speed, static deployment, and multi-language support.

node-sdk
The ChatBotKit Node SDK is a JavaScript-based platform for building conversational AI bots and agents. It offers easy setup, serverless compatibility, modern framework support, customizability, and multi-platform deployment. With capabilities like multi-modal and multi-language support, conversation management, chat history review, custom datasets, and various integrations, this SDK enables users to create advanced chatbots for websites, mobile apps, and messaging platforms.
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sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.