AGDebugger is an interactive system to help you debug your agent teams. It offers interactions to:
- Send and step through agent messages
- Edit previously sent agent messages and revert to earlier points in a conversation
- Navigate agent conversations with an interactive visualization
You can install AGDebugger locally by cloning the repo and installing the python package.
# Install & build frontend
cd frontend
npm install
npm run build
# Install & build agdebugger python package
cd ..
pip install .
AGDebugger is built on top of AutoGen. To use AGDebugger, you provide a python file that exposes a function that creates an AutoGen AgentChat team for debugging. You can then launch AgDebugger with this agent team.
For example, the script below creates a simple agent team with a single WebSurfer agent.
# scenario.py
from autogen_agentchat.teams import MagenticOneGroupChat
from autogen_agentchat.ui import Console
from autogen_ext.agents.web_surfer import MultimodalWebSurfer
from autogen_ext.models.openai import OpenAIChatCompletionClient
async def get_agent_team():
model_client = OpenAIChatCompletionClient(model="gpt-4o")
surfer = MultimodalWebSurfer(
"WebSurfer",
model_client=model_client,
)
team = MagenticOneGroupChat([surfer], model_client=model_client)
return team
We can then launch the interface with:
agdebugger scenario:get_agent_team
Once in the interface, you can send a GroupChatStart message to the start the agent conversation and begin debugging!
See our CHI 2025 paper for more details on the design and evaluation of AGDebugger.
@inproceedings{epperson25agdebugger,
title={Interactive Debugging and Steering of Multi-Agent AI Systems},
author={Will Epperson and Gagan Bansal and Victor Dibia and Adam Fourney and Jack Gerrits and Erkang Zhu and Saleema Amershi},
year={2025},
publisher = {Association for Computing Machinery},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
series = {CHI '25}
}