Stream responses progressively using async generators instead of returning a single message. Enables showing partial results as they're generated.

• How to stream responses using async generators
• The yield pattern for progressive updates
• When streaming improves user experience

• Development environment set up (see main repo README)
• Backend services running: make dev from repository root
• Understanding of basic sync agents (see 000_hello_acp)

cd examples/tutorials/00_sync/020_streaming
uv run agentex agents run --manifest manifest.yaml

@acp.on_message_send
async def handle_message_send(params: SendMessageParams):
    async def stream_response():
        for chunk in response_chunks:
            yield TaskMessageUpdate(content=TextContent(...))

    return stream_response()

Return an async generator instead of a single response - each yield sends an update to the client.

• Streaming LLM responses (OpenAI, Anthropic, etc.)
• Large data processing with progress updates
• Any operation that takes >1 second to complete
• Improving perceived responsiveness

Streaming dramatically improves user experience for longer operations. Instead of waiting 10 seconds for a complete response, users see results immediately as they're generated. This is essential for modern AI agents.

Next: Ready for task management? → 10_async/00_base/000_hello_acp