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Seeed Studio XIAO ESP32-S3 Agora Voice Conversation Project (AI Agent Demo)

简体中文 | English

This repository demonstrates how to use Seeed Studio reSpeaker XVF3800 as an edge voice device, build a real-time voice link via Agora, and connect to an AI Agent backend service to complete a full voice conversation loop.

The key content is in ai_agents/:

Directory Guide (You only need to read these two)

ai_agents/
  esp32-client/   # XIAO ESP32-S3 edge side: audio capture/playback + Agora connection + conversation interaction
  server/         # Backend: AI Agent orchestration / LLM / ASR / TTS, etc. (works together with the edge side)

System Architecture (Brief)

  1. The XIAO ESP32-S3 connects to the network and joins an Agora room
  2. The edge side captures microphone audio and publishes it (or uploads data)
  3. ai_agents/server receives audio/events and performs ASR → LLM → TTS (or other Agent flows)
  4. The backend sends the response audio/commands back, and the edge side plays it, enabling real-time voice conversation

Quick Start (Recommended Workflow)

0. Prerequisites

  • Hardware: Seeed Studio reSpeaker XVF3800 (plus mic/speaker or the corresponding expansion board)
  • Network: Able to access Agora services
  • Software: Install according to the requirements in the subdirectories (see the two links below)

1) Start the backend first (run server first)

Go to: ai_agents/server

Follow the README/docs in that directory:

  • Configure environment variables (Agora / LLM / ASR / TTS, etc.)
  • Start the service

After that, you should see the backend service start successfully and wait for edge connections or room events.

Windows (Docker Desktop recommended) Steps (including a simple Docker installation/config)

Applies to: Windows 10/11 (WSL2 is recommended). The following commands are recommended to run in PowerShell or Windows Terminal.

A. Install / Configure Docker Desktop (one-time)

  1. Download and install Docker Desktop: https://www.docker.com/products/docker-desktop/
  2. During installation, select/enable Use WSL 2 instead of Hyper-V (if available).
  3. After installation, open Docker Desktop and wait until the tray shows Docker is running.
  4. (Optional but recommended) In Docker Desktop: Settings -> Resources -> WSL Integration Enable your commonly used WSL distribution (e.g., Ubuntu).

B. Clone the repo and prepare environment variables

git clone https://github.com/zhannn668/seeed-xiao-agora-client.git
cd seeed-xiao-agora-client
cd ai_agents

Copy the example environment variables to .env (choose one):

  • PowerShell:
Copy-Item .env.example .env
  • Or CMD:
copy .env.example .env

Then open .env in an editor and fill in your keys/config (Agora / LLM / ASR / TTS, etc.):

How to get API Keys:

Agora:

  1. Visit https://console.agora.io/
  2. Register a free account
  3. Create a new project (Project)
  4. Copy the App ID and App Certificate

Deepgram:

  1. Visit https://console.deepgram.com/
  2. Register a free account
  3. Go to the API Keys page
  4. Create a new API Key

OpenAI:

  1. Visit https://platform.openai.com/
  2. Register and add a payment method
  3. Go to the API Keys page
  4. Create a new Secret Key

ElevenLabs:

  1. Visit https://elevenlabs.io/
  2. Register a free account
  3. Go to Profile → API Key
  4. Copy the API Key
# Agora RTC Configuration (Required)
AGORA_APP_ID=your_agora_app_id_here
AGORA_APP_CERTIFICATE=your_agora_certificate_here

# Deepgram ASR Configuration (Required)
DEEPGRAM_API_KEY=your_deepgram_api_key_here

# OpenAI LLM Configuration (Required)
OPENAI_API_KEY=your_openai_api_key_here
OPENAI_MODEL=gpt-4o
OPENAI_PROXY_URL=  # Optional: leave empty if not using proxy

# ElevenLabs TTS Configuration (Required)
ELEVENLABS_TTS_KEY=your_elevenlabs_api_key_here

# Optional: Weather API (for weather tool functionality)
WEATHERAPI_API_KEY=your_weatherapi_api_key_here

Open ai_agents/agents/examples/voice-assistant/tenapp/property.json in an editor, and modify it according to the model you choose. You can refer to: https://docs.agora.io/en/conversational-ai/models/asr/overview

......

"llm": {
    "url": "https://api.openai.com/v1/chat/completions",
    "api_key": "<your_llm_key>",
    "system_messages": [
      {
        "role": "system",
        "content": "You are a helpful chatbot."
      }
    ],
    "max_history": 32,
    "greeting_message": "Hello, how can I assist you",
    "failure_message": "Please hold on a second.",
    "params": {
      "model": "gpt-4o-mini"
    },
  }

"tts": {
  "vendor": "cartesia",
  "params": {
    "api_key": "<your_cartesia_key>",
    "model_id": "sonic-2",
    "voice": {
        "mode": "id",
        "id": "<voice_id>"
    },
    "output_format": {
        "container": "raw",
        "sample_rate": 16000
    },
    "language": "en"
  }
}

......

C. Start the service (Docker Compose)

docker compose up -d

Check container status (optional):

docker compose ps

D. Enter the container and install the sample (Voice Assistant)

Note: The container name may vary depending on the compose configuration. The example below uses ten_agent_dev. If yours differs, use the output of docker compose ps.

docker exec -it ten_agent_dev bash

After entering the container, run:

cd agents/examples/voice-assistant
task install
task run

E. Verify the backend is running

  • You can see the relevant containers are Running in Docker Desktop
  • Or view logs (optional):
docker compose logs -f

To stop the service:

docker compose down

2) Flash and run the ESP32 edge side (then run esp32-client)

Go to: ai_agents/esp32-client

Follow the README/docs in that directory:

  • Configure Wi-Fi / Agora AppID/Token/Channel (or obtain them from the backend)
  • Build and flash to the XIAO ESP32-S3
  • Power on and observe the serial logs

3) Validation

  • Serial logs show the device successfully joined the channel / connected
  • After you speak to the device, the backend receives audio / recognized text
  • The device can play back the AI response audio (or execute commands)

FAQ

  • Q: Which one should I read first? A: Read ai_agents/server first (get the whole pipeline running), then read ai_agents/esp32-client (connect the edge device).
  • Q: What if I only want to modify the edge side? A: Go directly to ai_agents/esp32-client. The backend can be started with the default sample.

References & More

  • Directories outside ai_agents/ are upstream frameworks/toolchains/sample collections. This demo mainly focuses on the edge + backend linkage.