LibreAI / Áudio / xiaozhi-esp32-server
// audio · xinnan-tech/xiaozhi-esp32-server

xiaozhi-esp32-server

xiaozhi-esp32-server é um projeto de áudio de código aberto de xinnan-tech (xinnan-tech/xiaozhi-esp32-server no GitHub). Tem 10.756 estrelas no GitHub e 3.670 forks, é publicado sob a licença MIT e foi atualizado pela última vez no GitHub em 8 de outubro de 2026.

Self-hosted backend that gives ESP32 'Xiaozhi' devices streaming voice chat, memory and tool control.

★ 10,8 mil estrelas⑂ 3,7 mil forksMITatualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto

Dados do projeto

Estrelas no GitHub
10.756
Forks
3.670
Licença
MIT
Última atualização no GitHub
8 de outubro de 2026
Categoria
Áudio
Tipo de ficha
Guia de instalação completo
Site oficial
Official site
// como funciona

Como funciona

  1. Get your ESP32 device talking first

    Flash or buy a Xiaozhi ESP32 device and confirm it works against a public test backend, so you know the hardware side is fine before self-hosting.

  2. Choose an install tier

    Pick the minimal install (single agent, config-file storage, no database) or the full-module install (multi-user, multi-agent, web control console, database) - each is offered as Docker or source deployment in the docs.

  3. Configure the AI pipeline

    Select ASR, LLM, vision and TTS providers in the config; the documented all-free starter setup uses local FunASR, EdgeTTS and free-tier cloud models.

  4. Point devices at your server

    Set your firmware to your server's OTA and WebSocket endpoints, then watch it answer, recognize speakers and run tools through the control console.

// recursos

Por que as pessoas gostam tanto

Streaming voice pipeline

Streaming ASR, streaming TTS and voice-activity detection give low-latency, interruptible conversations in multiple languages.

Voiceprint recognition

Multiple users can register voiceprints; the server identifies who is speaking in parallel with recognition and passes that to the LLM for personalized replies.

Many model providers

LLMs connect via OpenAI-compatible APIs, Ollama, Dify, FastGPT, Coze, Xinference or Home Assistant; ASR, TTS and vision models include local options like FunASR, FishSpeech and GPT-SoVITS as well as major cloud providers.

MCP and IoT tool calling

Supports client IoT protocols, client and server MCP, and MCP access points, and can push MCP commands from the console down to ESP32 devices over MQTT.

Memory and knowledge base

Choose local short-term memory, mem0ai or PowerMem for conversation memory, and plug in a RAGFlow knowledge base the model can consult before answering.

Web management console

The full-module install adds a web admin for users, system configuration and devices (in Simplified/Traditional Chinese and English), plus performance and audio test tools.

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// execute você mesmo

Execute você mesmo

  1. Clone the repository

    Get the server source; deployment itself is covered by the project's step-by-step deployment docs.

    git clone https://github.com/xinnan-tech/xiaozhi-esp32-server.git
    cd xiaozhi-esp32-server
  2. Pick a deployment route

    Follow the deployment document for your tier - Docker or source, minimal or full-module - linked from the README's deployment section.

    # see the deployment docs linked from the README for the exact commands
  3. Connect a device and test

    Point your ESP32 firmware at the server's OTA/WebSocket endpoints and use the bundled test tools to check ASR, LLM and TTS latency.

    # verify with the performance tester and audio test tool described in the README
// casos de uso

O que você pode criar

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// perguntas frequentes

Perguntas frequentes

Who maintains xiaozhi-esp32-server?

The xinnan-tech team maintains it; the project is spearheaded by Professor Siyuan Liu's team at South China University of Technology and a large contributor community.

Is it free to use?

Yes. The server is MIT-licensed, and the README documents an all-free configuration (local FunASR recognition, EdgeTTS, free-tier models) for home use.

Does it need a paid API key?

Not necessarily. You can run every module with local or free-tier components; paid cloud ASR, LLM or TTS providers are optional upgrades for speed and quality.

How does it compare with using the public Xiaozhi backend?

The public service is zero-setup but shared and third-party-run; self-hosting gives you your own data, your own model choices, multi-user management and no dependence on someone else's server.

How do I get started?

Clone the repo, follow the deployment doc for the minimal Docker install, then point one ESP32 device at your server's WebSocket endpoint.

// continue explorando

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// alternativas

Alternativas em Áudio

Os outros projetos de Áudio com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se xiaozhi-esp32-server não for o ideal para você.

// mais em audio

Mais em Áudio

Projetos de Áudio próximos no catálogo, os mais próximos em estrelas de xiaozhi-esp32-server: continue explorando dos dois lados dele.

Baixe o xiaozhi-esp32-server

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