This guide demonstrates how to integrate a synchronous agent from the smolagents library into an asynchronous Python web application using Starlette.
The example is designed to help users new to async Python and agent integration understand best practices for combining synchronous agent logic with async web servers.
smolagents library capable of programmatically solving tasks.CodeAgent.run() executes Python code synchronously. If called directly in an async endpoint, it would block Starlette’s event loop, reducing performance and scalability. By offloading this operation to a background thread with anyio.to_thread.run_sync, you keep the app responsive and efficient, even under high concurrency.
/run-agent endpoint that accepts a JSON payload with a task string.anyio.to_thread.run_sync.pip install smolagents starlette anyio uvicorn
import anyio.to_thread
from starlette.applications import Starlette
from starlette.requests import Request
from starlette.responses import JSONResponse
from starlette.routing import Route
from smolagents import CodeAgent, InferenceClientModel
agent = CodeAgent(
model=InferenceClientModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
tools=[],
)
async def run_agent(request: Request):
data = await request.json()
task = data.get("task", "")
# Run the agent synchronously in a background thread
result = await anyio.to_thread.run_sync(agent.run, task)
return JSONResponse({"result": result})
app = Starlette(routes=[
Route("/run-agent", run_agent, methods=["POST"]),
])uvicorn async_agent.main:app --reload
curl -X POST http://localhost:8000/run-agent -H 'Content-Type: application/json' -d '{"task": "What is 2+2?"}'Expected Response:
{"result": "4"}For the full code, see examples/async_agent.