How to Fix 'state not updating during development' in AutoGen (Python)

What the error means

If you’re seeing state not updating during development in AutoGen, it usually means your agent or tool state is being recreated on every run instead of being persisted across turns. In practice, this shows up when you’re using AssistantAgent, UserProxyAgent, or a custom agent wrapper in a dev loop and expecting memory, chat history, or tool state to survive reloads.

The symptom is simple: the code runs, but the agent behaves like it forgot everything between iterations. You’ll often notice it after editing a file, restarting a notebook cell, or re-instantiating agents inside a function.

The Most Common Cause

The #1 cause is creating your AutoGen agents inside a function or rerunning setup code during development. That gives you fresh Python objects every time, so anything stored in instance state is lost.

Here’s the broken pattern:

# broken.py
from autogen import AssistantAgent, UserProxyAgent

def run_chat():
    assistant = AssistantAgent(
        name="assistant",
        llm_config={"config_list": [{"model": "gpt-4o-mini", "api_key": "YOUR_KEY"}]},
    )
    user = UserProxyAgent(name="user", human_input_mode="NEVER")

    user.initiate_chat(
        assistant,
        message="Remember my account number is 12345."
    )

if __name__ == "__main__":
    run_chat()

# fixed.py
from autogen import AssistantAgent, UserProxyAgent

assistant = AssistantAgent(
    name="assistant",
    llm_config={"config_list": [{"model": "gpt-4o-mini", "api_key": "YOUR_KEY"}]},
)

user = UserProxyAgent(name="user", human_input_mode="NEVER")

def run_chat(message: str):
    user.initiate_chat(assistant, message=message)

if __name__ == "__main__":
    run_chat("Remember my account number is 12345.")

If you need persistence across process restarts, don’t rely on Python object memory at all. Save chat history or state to disk or a database, then reload it before resuming.

# explicit persistence pattern
import json

with open("chat_state.json", "w") as f:
    json.dump(user.chat_messages[assistant], f)

with open("chat_state.json") as f:
    history = json.load(f)

Other Possible Causes

1) You’re using notebook cells out of order

In Jupyter, rerunning the cell that defines the agent will create a new instance and wipe previous state.

# Cell 1
assistant = AssistantAgent(name="assistant", llm_config=llm_config)

# Cell 2
assistant = AssistantAgent(name="assistant", llm_config=llm_config)  # resets state

Fix: keep one initialization cell and avoid re-executing it unless you want a reset.

2) Your custom agent overrides stateful methods incorrectly

If you subclass AssistantAgent or ConversableAgent and forget to call super(), internal message handling can break.

from autogen import ConversableAgent

class MyAgent(ConversableAgent):
    def receive(self, message, sender, request_reply=None, silent=False):
        return {"content": "ok"}  # breaks base behavior

Fix:

class MyAgent(ConversableAgent):
    def receive(self, message, sender, request_reply=None, silent=False):
        result = super().receive(message, sender, request_reply=request_reply, silent=silent)
        return result

3) You disabled or bypassed conversation history

Some setups manually pass empty messages or rebuild context each turn.

# bad: new empty context every time
messages = []
messages.append({"role": "user", "content": prompt})

Fix: keep one shared history object per conversation thread.

messages.append({"role": "user", "content": prompt})
reply = assistant.generate_reply(messages=messages)

4) Your dev server reloads the process on file changes

If you’re running FastAPI/Flask/Streamlit with auto-reload, every code change restarts Python. That looks like “state not updating” when the real issue is process restart.

uvicorn app:app --reload

For debugging stateful AutoGen flows, disable reload temporarily:

uvicorn app:app --no-reload

How to Debug It

1. •

   Print object identities Check whether your agents are being recreated.

   print("assistant id:", id(assistant))
   print("user id:", id(user))
   

   If these change between turns, you found the problem.

2. •

   Inspect message history Verify whether AutoGen still has prior turns.

   print(user.chat_messages.get(assistant, []))
   

   If this comes back empty after each turn, your state isn’t being preserved.

3. •

   Check where initialization happens Search for AssistantAgent(...), UserProxyAgent(...), or your subclass constructor inside request handlers, loops, notebook cells, or startup hooks.

   • •Bad places: route handlers, task runners, hot-reloaded modules
   • •Good places: app startup singleton registry
4. •

   Turn off reload and rerun If the bug disappears with reload disabled, the issue is process recreation rather than AutoGen itself.

   • •uvicorn --no-reload
   • •stop rerunning notebook setup cells
   • •avoid spawning fresh worker processes for each task

Prevention

• •Create agents once per conversation scope. If you need multiple conversations, create one agent set per thread ID and store them in a registry.
• •Persist anything important outside Python memory:
  • •chat history in JSON/SQLite/Postgres
  • •tool outputs in durable storage
  • •session metadata keyed by conversation ID
• •In development:
  • •avoid auto-reload while testing stateful flows
  • •log agent IDs and message counts on every turn

If you want reliable AutoGen behavior in production-like dev environments, treat agent memory as disposable unless you explicitly persist it.

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.