This example demonstrates how to use AgentScope's ChatRoom class to create a multi-agent real-time voice interaction system where two AI agents can have autonomous conversations without user input.

• 🗣️ Real-time Voice Interaction: Two agents communicate through voice in real-time
• 🤖 Autonomous Conversation: Agents converse with each other without user intervention
• ⚙️ Customizable Configuration: Configure agent names and instructions through the web interface
• 🎨 Modern UI: Clean, shadcn-inspired interface for easy interaction
• 📊 Live Transcript: See the conversation transcripts in real-time

The example uses:

• Backend: FastAPI server with WebSocket support
• Frontend: HTML5 with Web Audio API for audio playback
• AgentScope Components:
  • ChatRoom: Manages multiple RealtimeAgent instances
  • RealtimeAgent: Handles real-time voice interaction with AI models
  • DashScopeRealtimeModel: DashScope's Qwen3-Omni realtime model

1. Python Dependencies:

   pip install agentscope[dashscope]
   pip install fastapi uvicorn

2. DashScope API Key:

   • Set your DashScope API key as an environment variable:

     export DASHSCOPE_API_KEY="your-api-key-here"

1. Start the Server:

   python run_server.py

2. Open the Web Interface:

   • Navigate to http://localhost:8000 in your web browser

3. Configure Agents:

   • Set names and instructions for both Agent 1 and Agent 2
   • Example configurations:
     • Agent 1 (Alice): "You are Alice, a cheerful and optimistic person who loves to share stories and ask questions. Keep your responses brief and conversational."
     • Agent 2 (Bob): "You are Bob, a thoughtful and analytical person who enjoys deep conversations. Keep your responses brief and conversational."

4. Start the Conversation:

   • Click the "▶️ Start Conversation" button
   • The agents will begin conversing autonomously
   • You'll see transcripts and system messages in the message panel
   • Audio playback will stream in real-time

5. Stop the Conversation:

   • Click the "⏹️ Stop Conversation" button when you want to end the session

1. WebSocket Connection: Client connects via WebSocket to /ws/{user_id}/{session_id}
2. Session Creation:
   • Client sends client_session_create event with agent configurations
   • Server creates two RealtimeAgent instances with specified names and instructions
   • Server creates a ChatRoom with both agents
   • Server starts the chat room and returns session_created event
3. Message Broadcasting:
   • ChatRoom automatically broadcasts messages between agents
   • All events (audio, transcripts, etc.) are forwarded to the frontend
4. Session End: Client sends client_session_end event to stop the conversation

1. WebSocket Setup: Establishes connection and waits for server events
2. Session Management: Sends configuration and manages conversation state
3. Audio Playback:
   • Receives base64-encoded PCM16 audio chunks
   • Decodes and queues audio data
   • Uses Web Audio API ScriptProcessorNode for streaming playback at 24kHz
4. Transcript Display: Shows real-time transcripts from both agents

The ChatRoom class manages multiple RealtimeAgent instances:

• Establishes connections for all agents
• Broadcasts messages between agents automatically
• Forwards events to the frontend
• Handles lifecycle management (start/stop)

Each RealtimeAgent:

• Connects to the DashScope realtime API
• Processes audio input from other agents
• Generates voice responses
• Emits events for transcripts, audio, and status updates

To use a different model, modify the DashScopeRealtimeModel configuration in run_server.py:

model=DashScopeRealtimeModel(
    model_name="your-model-name",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
)

To add more agents, modify the agent creation section in run_server.py:

agent3 = RealtimeAgent(
    name=agent3_name,
    sys_prompt=agent3_instructions,
    model=DashScopeRealtimeModel(
        model_name="qwen3-omni-flash-realtime",
        api_key=os.getenv("DASHSCOPE_API_KEY"),
    ),
)

chat_room = ChatRoom(agents=[agent1, agent2, agent3])

And update the frontend to include configuration fields for the additional agents.

• Ensure your browser supports Web Audio API
• Check browser console for audio-related errors
• Verify the audio format matches the expected PCM16 at 24kHz

• Verify your DashScope API key is set correctly
• Check that port 8000 is not blocked by firewall
• Review server logs for error messages

• Ensure both agent configurations have valid instructions
• Check that the instructions encourage conversational behavior
• Review the console logs for API errors

• AgentScope Documentation
• DashScope API Documentation
• FastAPI Documentation
• Web Audio API