This README provides information about the Auto Agent
script and instructions for setting up and running the code. The script is designed to facilitate interaction with multiple agents that can generate and execute Python code based on user inputs.
- Setup virtual environment and install dependencies.
- Configure a Streamlit-based user interface to interact with agents.
- Register tools with agents for task planning and execution.
- Facilitate group chats among agents for better task planning.
- Python 3.8+
- Virtual environment tools (
venv
) - Streamlit
- Gevent
- Dotenv
- Virtual Environment Setup
- Create a virtual environment:
python -m venv AutoAgent
- Activate the virtual environment:
- Windows:
.\AutoAgent\Scripts\Activate
- Linux/MacOS:
source AutoAgent/bin/activate
- Windows:
- Create a virtual environment:
- Install Dependencies
- Install the required packages:
pip install -r requirements.txt
- Install the required packages:
- Fix Certificate Issues (if any)
- If you encounter certificate issues, install
python-certifi-win32
:pip install python-certifi-win32
- If you encounter certificate issues, install
- Setup Code Executors
- The code executor is set up to execute code in a local environment.
- Register Tools with Agents
- Different tools are registered with agents to assist in research, PDF creation, and task planning.
The group chat setup allows for communication among different agents while respecting allowed speaker transitions. This ensures that the right agent receives the message.
- The UI is powered by Streamlit and includes:
- A header describing the platform.
- Example use cases to guide users on the capabilities of the platform.
- Sidebar for user configuration.
- User Proxy Agent
TrackableUserProxyAgent
class captures user messages and manages the interactions.
- Group Chat Manager
TrackableGroupChatManager
manages the group chat setup and facilitates smooth interaction.
- Input a question or command in the Streamlit UI.
- Ensure you have selected the right model and provided the OpenAI API key.
- Agents will process the input and provide responses accordingly.
- Ensure all dependencies are installed correctly.
- Verify the OpenAI API key and model configurations.
- Check for specific error messages in the Streamlit UI and address them accordingly.
This project is licensed under the MIT License.