Description
Describe the bug
When using the stream endpoint in the normal_v2 router, the server throws an exception during the streaming process. The error occurs when processing the stream_events method in the Agent's Runner. The client receives partial responses before the connection is abruptly closed with the error: curl: (18) transfer closed with outstanding read data remaining.
Debug information
- Agents SDK version: (e.g.
v0.0.7) - Python version (e.g. Python 3.11)
Repro steps
Set up the normal_v2 router with the provided code.
Send a POST request to the /normal_v2/stream endpoint with the following payload:
{
"chat_history": [{"role": "system", "content": "You are a helpful assistant."}],
"user_query": "What is the weather today?"
}
Observe the server logs and client response.
Expected behavior
The server should stream the response without errors, and the client should receive the full response in a properly formatted streaming format (e.g., application/x-ndjson).
Server logs: The server throws the following exception:
ERROR: Exception in ASGI application
+ Exception Group Traceback (most recent call last):
...lib/python3.12/site-packages/agents/tracing/scope.py", line 45, in reset_current_trace
| _current_trace.reset(token)
ValueError: <Token var=<ContextVar name='current_trace' default=None at 0x1462a79c0> at 0x169dfec80> was created in a different Context
Client response: The client receives partial responses:
{"event_type":"data","data":{"answer":" those"}}
{"event_type":"data","data":{"answer":"!"}}
Followed by the error:
curl: (18) transfer closed with outstanding read data remaining
Additional context
Code snippets
Router code:
import uuid
from fastapi import APIRouter
from agents import Agent, Runner
from app.core.chat_interface.base import ChatInterface
from app.core.models.human_input import NormalQueryInput
from app.core.services.openai.model import openai_model, openai_model_settings
from starlette.responses import StreamingResponse
router = APIRouter(prefix="/normal_v2", tags=["normal_v2"])
agent = Agent(
name="Assistant",
instructions="You are a helpful assistant.",
model=openai_model,
model_settings=openai_model_settings,
)
@router.post("/stream")
async def stream(query_input: NormalQueryInput):
full_history = query_input.chat_history + [{"role": "user", "content": query_input.user_query}]
result = Runner.run_streamed(agent, input=full_history)
chat_interface = ChatInterface(result.stream_events(), trace_id=str(uuid.uuid4()))
return StreamingResponse(chat_interface.process_stream(), media_type="application/x-ndjson")
ChatInterface code:
from enum import Enum
from typing import Optional, AsyncIterator
from openai.types.responses import ResponseTextDeltaEvent
from pydantic import BaseModel
class EventType(Enum):
DATA = "data"
METADATA = "metadata"
class EventData(BaseModel):
answer: Optional[str] = None
trace_id: Optional[str] = None
class EventStreamOutput(BaseModel):
event_type: EventType
data: EventData
class ChatInterface:
def __init__(self, result: AsyncIterator, trace_id: Optional[str]):
self.stream_result = result
self.trace_id = trace_id
async def process_stream(self):
if self.trace_id:
ted = EventStreamOutput(
event_type=EventType.METADATA,
data=EventData(trace_id=self.trace_id)
)
yield f"{ted.json(exclude_none=True)}\n\n"
async for event in self.stream_result:
if event.type == "raw_response_event" and isinstance(event.data, ResponseTextDeltaEvent):
eed = EventStreamOutput(
event_type=EventType.DATA,
data=EventData(answer=event.data.delta)
)
yield f"{eed.json(exclude_none=True)}\n\n"