AutoGen UI

Important

This repo has been updated to use the AutoGen AgentChat interface based on the new AutoGen 0.4x AgentChat api. Also, the API might change, so expect some breaking changes in the future.

The hello world for building a UI interface with AutoGen AgentChat API.

Example UI to demonstrate how to build interfaces using the AutoGen AgentChat API. The UI is built using Next.js and web apis built using FastApi.

What Does the App Do?

• autogenui.manager - provides a simple run method that takes a prompt and returns a response from a predefined agent team. Take a look at the agent team json config file to see how the agents are configured. It gives a general idea on what types of agents are supported etc. Check out the tutorial notebook for an example on how to use the provide class to load a team spec.

• autogenui.web.app.py - FastApi backend that serves a simple /generate endpoint that takes a prompt and returns a response from a predefined agent team.

  • Creates a manager to run tasks
  • Streams results of the task run to the client ui

• frontend - Next.js frontend that provides a simple chat interface to interact with the backend.

What's Next?

This app is clearly just a starting point. Here are some ideas on how to extend it:

• Extend the manager to support multiple team configurations from the UI
• Storing and loading interaction history in a database.
• Security - add authentication and authorization to the app

[!TIP] Note AutoGen Studio is being rewritten on the AgentChat api to address most of the above points. Take a look at the implementation there for a more complete example.

Getting Started

Note that you will have to setup your OPENAI_API_KEY to run the app.

export OPENAI_API_KEY=<your key>

Install dependencies. Python 3.9+ is required. You can install from pypi using pip.

pip install autogenui

or to install from source

git clone [email protected]:victordibia/autogen-ui.git
cd autogenui
pip install -e .

Run ui server.

Set env vars OPENAI_API_KEY

export OPENAI_API_KEY=<your_key>

autogenui # or with --port 8081

Open http://localhost:8081 in your browser.

To modify the source files, make changes in the frontend source files and run npm run build to rebuild the frontend.

Development

To run the app in development mode, you will need to run the backend and frontend separately.

Backend - with hot-reload

autogenui --reload

[!TIP] Tip The UI loaded by this CLI in a pre-complied version by running the frontend build command show blow. That means if you make changes the frontend code or change the hostname or port the backend is running on the frontend updated frontend code needs to be rebuilt for it to load through this command.

Frontend

cd frontend

Install dependencies

yarn install

Run in dev mode - with hot-reload

Set NEXT_PUBLIC_API_SERVER on the command line.

export NEXT_PUBLIC_API_SERVER=http://<your_backend_hostname>/api

Or create a .env file in the frontend folder with the following content.

NEXT_PUBLIC_API_SERVER=http://<your_backend_hostname>/api

where your_backend_hostname - is the hostname that autogenui is running on e.g. localhost:8081

yarn dev

(Re)build

Remember to install dependencies and set NEXT_PUBLIC_API_SERVER before building.

yarn build

Roadmap

There isnt really much of a roadmap for this project. It is meant as a simple example to get started with the AutoGen AgentChat API. For a more complete example, take a look at the AutoGen Studio project.

References

• AutoGen Studio.

@inproceedings{dibia2024autogen,
  title={AutoGen Studio: A No-Code Developer Tool for Building and Debugging Multi-Agent Systems},
  author={Dibia, Victor and Chen, Jingya and Bansal, Gagan and Syed, Suff and Fourney, Adam and Zhu, Erkang and Wang, Chi and Amershi, Saleema},
  journal={EMNLP 2024},
  year={2024}
}

• AutoGen.

@inproceedings{wu2023autogen,
      title={AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework},
      author={Qingyun Wu and Gagan Bansal and Jieyu Zhang and Yiran Wu and Shaokun Zhang and Erkang Zhu and Beibin Li and Li Jiang and Xiaoyun Zhang and Chi Wang},
      year={2023},
      eprint={2308.08155},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}