XiaoZhi AI Chatbot - AI Local Apps Tool

Overview

XiaoZhi AI Chatbot is an open-source hardware/software project that turns an ESP32-based board into a voice-first conversational agent. The project integrates SenseVoice for wake-word and microphone input, connects to large language models (examples cited by the project include Qwen and DeepSeek) for chat backends, and provides speech recognition, multi-language chat, and text-to-speech (TTS) support. It targets makers and hobbyists who want a compact, offline-capable interface combined with cloud or local LLM inference to create a personal AI friend on physical devices. The repository bundles firmware, sample prompt configurations, and support for small displays (OLED/LCD) to show chat status, messages, or avatars. It is designed to be extensible: developers can swap LLM endpoints, tweak wake-word or ASR settings, customize TTS voices, and modify prompts to shape persona and dialogue. According to the GitHub repository, XiaoZhi has an active community (23,031 stars, 4,846 forks) and is MIT-licensed, making it suitable for experimentation, education, and prototyping conversational hardware.

GitHub Statistics

• Stars: 23,031
• Forks: 4,846
• Contributors: 97
• License: MIT
• Primary Language: C++
• Last Updated: 2026-01-09T09:19:06Z
• Latest Release: v2.1.0

According to the GitHub repository, XiaoZhi has 23,031 stars, 4,846 forks, and 97 contributors, and is released under the MIT license. The project shows active development with recent commits (last commit recorded on 2026-01-09). The contributor count and fork volume indicate a healthy community of maintainers and integrators; issues and pull requests are the primary channels for contributions and troubleshooting.

Installation

Install via pip:

git clone https://github.com/78/xiaozhi-esp32.git

cd xiaozhi-esp32

pip install -U platformio

platformio run --target upload

Key Features

• Wake-word and voice capture via SenseVoice integration for hands-free activation
• Speech recognition pipeline to convert microphone input into text for LLM queries
• Multi-language chat support enabling conversation in several languages
• TTS output to speak LLM responses through onboard speakers
• OLED/LCD display support for text, status, and simple UI elements
• Configurable prompts and persona controls to customize assistant behavior
• Pluggable LLM backends (examples: Qwen and DeepSeek) via networked endpoints

Community

Community engagement centers on GitHub (issues, pull requests, and discussions). With 97 contributors and more than 23k stars, the project attracts active forks and contributions. Users typically collaborate on hardware adapters, display drivers, wake-word tuning, and integrations with third-party LLM and TTS services. For latest support and usage patterns, consult the repository README, open issues, and pull requests.

Key Information

• Category: Local Apps
• Type: AI Local Apps Tool