Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/Link-AGI/AutoAgents
Generate different roles for GPTs to form a collaborative entity for complex tasks.
https://github.com/Link-AGI/AutoAgents
Last synced: 3 months ago
JSON representation
Generate different roles for GPTs to form a collaborative entity for complex tasks.
- Host: GitHub
- URL: https://github.com/Link-AGI/AutoAgents
- Owner: Link-AGI
- License: mit
- Created: 2023-08-21T12:19:36.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2023-11-24T03:17:23.000Z (7 months ago)
- Last Synced: 2024-03-13T18:09:09.901Z (4 months ago)
- Language: Python
- Homepage: https://huggingface.co/spaces/LinkSoul/AutoAgents
- Size: 88 MB
- Stars: 958
- Watchers: 23
- Forks: 117
- Open Issues: 18
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- Awesome-Agents-Research - AutoAgents
- awesome - Link-AGI/AutoAgents - [IJCAI 2024] Generate different roles for GPTs to form a collaborative entity for complex tasks. (Python)
- awesome-stars - AutoAgents - AGI | 1085 | (Python)
- awesome-stars - AutoAgents - AGI | 945 | (Python)
README
# AutoAgents: A Framework for Automatic Agent Generation
Generate different roles for GPTs to form a collaborative entity for complex tasks.
AutoAgents is an experimental open-source application for an Automatic Agents Generation Experiment based on LLM. This program, driven by LLM, autonomously generates multi-agents to achieve whatever goal you set.
## :boom: Updates
- **2023.09.31**: 📝 We're excited to share our paper [AutoAgents: A Framework for Automatic Agent Generation](https://arxiv.org/abs/2309.17288) related to this repository.
- **2023.08.30**: 🚀 Adding a custom agent collection, AgentBank, allows you to add custom agents.
## 🚀 Features
- **Planner**: Determines the expert roles to be added and the specific execution plan according to the problem.
- **Tools**: The set of tools that can be used, currently only compatible with the search tools.
- **Observers**: Responsible for reflecting on whether the planner and the results in the execution process are reasonable, currently including reflection checks on Agents, Plan, and Action.
- **Agents**: Expert role agents generated by the planner, including name, expertise, tools used, and LLM enhancement.
- **Plan**: The execution plan is composed of the generated expert roles, each step of the execution plan has at least one expert role agent.
- **Actions**: The specific actions of the expert roles in the execution plan, such as calling tools or outputting results.
## Demo
Online demo:
- [Demo / HuggingFace Spaces](https://huggingface.co/spaces/LinkSoul/AutoAgents)
Video demo:
- **Rumor Verification**
- **Gluttonous Snake**
## Installation and Usage
### Installation
```bash
git clone https://github.com/LinkSoul-AI/AutoAgents
cd AutoAgents
python setup.py install
```
### Configuration
- Configure your `OPENAI_API_KEY` in any of `config/key.yaml / config/config.yaml / env`
- Priority order: `config/key.yaml > config/config.yaml > env`
```bash
# Copy the configuration file and make the necessary modifications.
cp config/config.yaml config/key.yaml
```
| Variable Name | config/key.yaml | env |
| ------------------------------------------ | ----------------------------------------- | ----------------------------------------------- |
| OPENAI_API_KEY # Replace with your own key | OPENAI_API_KEY: "sk-..." | export OPENAI_API_KEY="sk-..." |
| OPENAI_API_BASE # Optional | OPENAI_API_BASE: "https:///v1" | export OPENAI_API_BASE="https:///v1" |
### Usage
- Commandline mode:
```python
python main.py --mode commandline --llm_api_key YOUR_OPENAI_API_KEY --serpapi_key YOUR_SERPAPI_KEY --idea "Is LK-99 really a room temperature superconducting material?"
```
- Websocket service mode:
```python
python main.py --mode service --host "127.0.0.1" --port 9000
```
### Docker
- Build docker image:
```bash
IMAGE="linksoul.ai/autoagents"
VERSION=1.0
docker build -f docker/Dockerfile -t "${IMAGE}:${VERSION}" .
```
- Start docker container:
```bash
docker run -it --rm -p 7860:7860 "${IMAGE}:${VERSION}"
```
- Open http://127.0.0.1:7860 in the browser.
## Contributing
AutoAgents is dedicated to creating a cutting-edge automated multi-agent environment for large language models. We are actively seeking enthusiastic collaborators to embark with us on this thrilling and innovative journey.
This project exists thanks to all the people who contribute:
## How Can You Contribute?
- **Issue Reporting and Pull Requests**: Encountering difficulties with AutoAgents? Feel free to raise the issue in English. Additionally, you're welcome to take initiative by resolving these issues yourself. Simply request to be assigned the issue, and upon resolution, submit a pull request (PR) with your solution.
- **Software Development Contributions**: As an engineer, your skills can significantly enhance AutoAgents. We are in constant pursuit of skilled developers to refine, optimize, and expand our framework, enriching our feature set and devising new modules.
- **Content Creation for Documentation and Tutorials**: If writing is your forte, join us in improving our documentation and developing tutorials or blog posts. Your contribution will make AutoAgents more user-friendly and accessible to a diverse audience.
- **Innovative Application Exploration**: Intrigued by the prospects of multi-agent systems? If you're keen to experiment with AutoAgents, we're excited to support your endeavors and curious to see your innovative creations.
- **User Feedback and Strategic Suggestions**: We highly value user input. Engage with AutoAgents and share your feedback. Your insights are crucial for ongoing enhancements, ensuring our framework's excellence and relevance.
## Contact Information
If you have any questions or feedback about this project, please feel free to contact us. We highly appreciate your suggestions!
- **Email:** [email protected], [email protected]
- **GitHub Issues:** For more technical inquiries, you can also create a new issue in our [GitHub repository](https://github.com/LinkSoul-AI/AutoAgents/issues).
We will respond to all questions within 2-3 business days.
## License
[MIT license](https://raw.githubusercontent.com/LinkSoul-AI/AutoAgents/main/LICENSE)
## Citation
If you find our work and this repository useful, please consider giving a star :star: and citation :beer::
```bibtex
@article{chen2023auto,
title={AutoAgents: The Automatic Agents Generation Framework},
author={Chen, Guangyao and Dong, Siwei and Shu, Yu and Zhang, Ge and Jaward, Sesay and Börje, Karlsson and Fu, Jie and Shi, Yemin},
journal={arXiv preprint},
year={2023}
}
```
## Wechat Group
## Acknowledgements
The [system](https://github.com/LinkSoul-AI/AutoAgents/tree/main/autoagents/system), [action_bank](https://github.com/LinkSoul-AI/AutoAgents/tree/main/autoagents/actions/action_bank) and [role_bank](https://github.com/LinkSoul-AI/AutoAgents/tree/main/autoagents/roles/role_bank) of this code base is built using [MetaGPT](https://github.com/geekan/MetaGPT)
Icons in the framework made by Darius Dan, Freepik, kmg design, Flat Icons, Vectorslab from [FlatIcon](https://www.flaticon.com)
---
