ai-python-ui-adapter

Frontend:

const chat = useChat({
  transport: new DefaultChatTransport({ api: "/api/chat" }),
  sendAutomaticallyWhen: lastAssistantMessageIsCompleteWithApprovalResponses,
});

Use chat.sendMessage(...) to send user input. Use chat.addToolApprovalResponse(...) from approval buttons.

Backend request:

class ChatRequest(pydantic.BaseModel):
    messages: list[ai.agents.ui.ai_sdk.UIMessage]

messages, approvals = ai.agents.ui.ai_sdk.to_messages(request.messages)
ai.agents.ui.ai_sdk.apply_approvals(approvals)

Backend stream:

async def body():
    async with agent.run(model, messages) as stream:
        async def events():
            async for event in stream:
                if (
                    isinstance(event, ai.events.HookEvent)
                    and event.hook.status == "pending"
                ):
                    ai.defer_hook(event.hook)
                yield event

        async for chunk in ai.agents.ui.ai_sdk.to_sse(events()):
            yield chunk

return StreamingResponse(
    body(),
    headers=ai.agents.ui.ai_sdk.UI_MESSAGE_STREAM_HEADERS,
)

The adapter handles UIMessage parsing, message IDs, tool state, approvals, subagent MessageBundle values, and AI SDK UI stream events.

You handle the HTTP route, auth, storage, session lookup, frontend rendering, and when to defer hooks.

For saved UI history, use:

ui_messages = ai.agents.ui.ai_sdk.to_ui_messages(messages)