39ada91fe7
* feat: add loading indicator when creating new agent * feat: reorder front page to avoid overflow and always show add button * feat: display function calls * feat: set up proxy during development & remove explicit inclusion of host/port in backend calls * fix: introduce api prefix, split up fastapi server to become more modular, use app directly instead of subprocess the api prefix allows us to create a proxy for frontend development that relays all /api requests to our fastapi, while serving the development files for other paths. splitting up the fastapi server will allow us to branch out and divide up the work better in the future. using the application directly in our cli instead of a subprocess makes debugging a thing in development and overall this python native way just seems cleaner. we can discuss if we should keep the api prefix or if we should distinguish between a REST only mode and one that also serves the static files for the GUI. This is just my initial take on things * chore: build latest frontend
63 lines
2.3 KiB
Python
63 lines
2.3 KiB
Python
import asyncio
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import json
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from starlette.responses import StreamingResponse
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from memgpt.server.rest_api.interface import QueuingInterface
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from memgpt.server.server import SyncServer
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router = APIRouter()
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class UserMessage(BaseModel):
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user_id: str
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agent_id: str
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message: str
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stream: bool = False
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def setup_agents_message_router(server: SyncServer, interface: QueuingInterface):
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@router.post("/agents/message")
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async def user_message(body: UserMessage):
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if body.stream:
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# For streaming response
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try:
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# Start the generation process (similar to the non-streaming case)
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# This should be a non-blocking call or run in a background task
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# Check if server.user_message is an async function
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if asyncio.iscoroutinefunction(server.user_message):
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# Start the async task
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await asyncio.create_task(server.user_message(user_id=body.user_id, agent_id=body.agent_id, message=body.message))
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else:
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# Run the synchronous function in a thread pool
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loop = asyncio.get_event_loop()
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loop.run_in_executor(None, server.user_message, body.user_id, body.agent_id, body.message)
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async def formatted_message_generator():
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async for message in interface.message_generator():
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formatted_message = f"data: {json.dumps(message)}\n\n"
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yield formatted_message
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await asyncio.sleep(1)
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# Return the streaming response using the generator
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return StreamingResponse(formatted_message_generator(), media_type="text/event-stream")
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except HTTPException:
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raise
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"{e}")
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else:
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interface.clear()
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try:
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server.user_message(user_id=body.user_id, agent_id=body.agent_id, message=body.message)
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except HTTPException:
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raise
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"{e}")
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return {"messages": interface.to_list()}
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return router
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