Event loop is Close? How to fix

[keingkrai]

What happened?

import os
import asyncio
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_core.models import ModelInfo, ModelFamily
from autogen_agentchat.agents import AssistantAgent, SocietyOfMindAgent
from autogen_agentchat.ui import Console
from autogen_agentchat.conditions import MaxMessageTermination, TextMentionTermination
from autogen_agentchat.teams import RoundRobinGroupChat, BaseGroupChat
from autogenstudio.teammanager import TeamManager
from flask import Flask, request, jsonify
from transformers import AutoTokenizer, AutoModel
from sklearn.metrics.pairwise import cosine_similarity
import torch
import numpy as np
import json

app = Flask(name)

@app.route("/autogenprocess", methods=["POST"])
async def autogen():
manager = TeamManager()
team_config = json.load(open("team.json"))

try:
    
    data = request.get_json()
    teacher_question = data.get("teacher_question", [])
    teacher_answer = data.get("teacher_answer", [])
    student_answer = data.get("student_answer", [])
    maxscore = data.get("maxscore", [])
    room_id = data.get("room", [])
    
    if isinstance(teacher_question, str):
        teacher_question = [teacher_question]
    if  isinstance(teacher_answer, str):
        teacher_answer = [teacher_answer]
    if isinstance(student_answer, str):
        student_answer = [student_answer]
    if isinstance(maxscore, str):
        maxscore = [maxscore]
        
    print("teacher_question :", teacher_question)
    print("teacher_answer :", teacher_answer)
    print("student_answer :", student_answer)
    print("maxscore :", maxscore)
        
    if len(teacher_question) != len(teacher_answer) or len(teacher_question) != len(student_answer) or len(teacher_question) != len(maxscore):
        return jsonify({"error": "The number of teacher's questions and student's answers must be the same"}), 400
    
    # Now you can iterate over the messages and extract their content
    response_content = []
    
    """if os.path.exists(f"./state/stateroom_{room_id}.json"):
        with open(f"./state/stateroom_{room_id}.json", "r") as f:
            state = json.load(f)
            await TeamManager.load_from_file(state)"""
    
    print(len(teacher_question))
    for i in range(len(teacher_question)):
        
        task_text = (
            f"จงตรวจสอบและให้คะแนนคำตอบของนักเรียน ({student_answer[i]}) "
            f"โดยพิจารณาจากความถูกต้อง ความสมเหตุสมผล และความสอดคล้องกับคำถาม ({teacher_question[i]}) "
            f"อย่าใช้คำตอบของอาจารย์ ({teacher_answer[i]}) เป็นเกณฑ์เปรียบเทียบโดยตรง แต่ให้ใช้เป็นแนวทางว่าคำตอบที่เหมาะสมควรมีลักษณะอย่างไร "
            f"ให้คะแนนนักเรียนในช่วง 0 ถึง {maxscore[i]} คะแนน และอธิบายเหตุผลของคะแนนที่ให้"
        )
        
        response = await manager.run(
            team_config="team.json",
            task=task_text,
        )

                    
        # Extract the task_result from the response
        task_result = response.task_result

        # Extract the messages from the task_result
        messages = task_result.messages

        for message in messages:
            response_content.append({
                "source": message.source,
                "content": message.content if isinstance(message.content, str) else str(message.content)
            })

        # Convert response content into a JSON-formatted string
        final_response = json.dumps(response_content, indent=4, ensure_ascii=False)
        
        print(final_response)
        
        """with open(f"./state/stateroom_{room_id}.json", "w") as f:
                team_state = await team.save_state()
                json.dump(team_state, f, indent=4)"""
        

    return jsonify({"model_results": response_content})

except Exception as e:
    return jsonify({"error": str(e)})

@app.route("/autogenprocessfeedback", methods=["POST"])
async def autogen_feedback():
manager = TeamManager()
team_config = json.load(open("team.json"))

try:
    
    data = request.get_json()
    teacher_question = data.get("question", [])
    teacher_answer = data.get("answer_teacher", [])
    student_answer = data.get("answer_student", [])
    teacher_score = data.get("score_ai", [])
    print("teacher_question :", teacher_question)
    
    if isinstance(teacher_question, str):
        teacher_question = [teacher_question]
    if  isinstance(teacher_answer, str):
        teacher_answer = [teacher_answer]
    if isinstance(student_answer, str):
        student_answer = [student_answer]
    if isinstance(teacher_score, str):
        teacher_score = [teacher_score]

        
    print("teacher_question :", teacher_question)
    print("teacher_answer :", teacher_answer)
    print("student_answer :", student_answer)
    print("teacher_score :", teacher_score)
    
    
        
    if len(teacher_question) != len(teacher_answer) or len(teacher_question) != len(student_answer) or len(teacher_question) != len(teacher_score):
        print(len(teacher_question))
        print(len(teacher_answer))
        print(len(student_answer))
        print(len(teacher_score))
        return jsonify({"error": "The number of teacher's questions and student's answers must be the same"}), 400
    
    # Now you can iterate over the messages and extract their content
    response_content = []
    
    """if os.path.exists(f"./state/stateroom_{room_id}.json"):
        with open(f"./state/stateroom_{room_id}.json", "r") as f:
            state = json.load(f)
            await TeamManager.load_from_file(state)"""
    
    print(len(teacher_question))
    for i in range(len(teacher_question)):
        
        task_text =f"จากโจทย์ข้อสอบ ({teacher_question[i]}) และมีคำตอบของอาจารย์ ({teacher_answer[i]}) คำตอบของนักเรียน ({student_answer[i]}) คะแนนที่ที่อาจารย์มอบให้นักเรียนคือ ({teacher_score[i]}) จงอธิบายเหตุผลของคะแนนที่ให้ ในตอนสุดท้ายต้องมีการกล่าวถึงคะแนนและเหตุผลต้องเป็นภาษาไทย"
        
        response = await manager.run(
            team_config="feedbackteam.json",
            task=task_text,
        )
                    
        # Extract the task_result from the response
        task_result = response.task_result

        # Extract the messages from the task_result
        messages = task_result.messages

        for message in messages:
            response_content.append({
                "source": message.source,
                "content": message.content if isinstance(message.content, str) else str(message.content)
            })

        # Convert response content into a JSON-formatted string
        final_response = json.dumps(response_content, indent=4, ensure_ascii=False)
                    
        """with open(f"./state/stateroom_{room_id}.json", "w") as f:
                team_state = await team.save_state()
                json.dump(team_state, f, indent=4)"""
        print(final_response)

    return jsonify({"model_results": response_content})

except Exception as e:
    return jsonify({"error": str(e)})

if name == "main":
app.run(debug=True)

---

Traceback (most recent call last):
File "c:\project.venv\Lib\site-packages\httpx_client.py", line 1985, in aclose
await self._transport.aclose()
File "c:\project.venv\Lib\site-packages\httpx_transports\default.py", line 406, in aclose
await self._pool.aclose()
File "c:\project.venv\Lib\site-packages\httpcore_async\connection_pool.py", line 353, in aclose
await self._close_connections(closing_connections)
File "c:\project.venv\Lib\site-packages\httpcore_async\connection_pool.py", line 345, in _close_connections
await connection.aclose()
File "c:\project.venv\Lib\site-packages\httpcore_async\connection.py", line 173, in aclose
await self._connection.aclose()
File "c:\project.venv\Lib\site-packages\httpcore_async\http11.py", line 258, in aclose
await self._network_stream.aclose()
File "c:\project.venv\Lib\site-packages\httpcore_backends\anyio.py", line 53, in aclose
await self._stream.aclose()
File "c:\project.venv\Lib\site-packages\anyio\streams\tls.py", line 201, in aclose
await self.transport_stream.aclose()
File "c:\project.venv\Lib\site-packages\anyio_backends_asyncio.py", line 1306, in aclose
self._transport.close()
File "C:\Users\griae\AppData\Local\Programs\Python\Python312\Lib\asyncio\proactor_events.py", line 109, in close
self._loop.call_soon(self._call_connection_lost, None)
File "C:\Users\griae\AppData\Local\Programs\Python\Python312\Lib\asyncio\base_events.py", line 792, in call_soon
self._check_closed()
File "C:\Users\griae\AppData\Local\Programs\Python\Python312\Lib\asyncio\base_events.py", line 539, in _check_closed
raise RuntimeError('Event loop is closed')
RuntimeError: Event loop is closed

Which packages was the bug in?

Python AgentChat (autogen-agentchat>=0.4.0)

AutoGen library version.

Python dev (main branch)

Other library version.

No response

Model used

No response

Model provider

None

Other model provider

No response

Python version

None

.NET version

None

Operating system

None

[rysweet]

Hello @keingkrai - the traceback stack you posted is not referencing autogen code - it's in your http stack in the https_client module. It's possible there is another stack trace that does reference autogen that you didn't paste in?