InfiniteRegen

The foundational core for backrooms and swarms, bringing together the smartest KOLs to revolutionize capital allocation, DAOs, funds, and collaborative ecosystems. Stay tuned as we release some good updates coming days. Thanks

Project Status

Completed ✅

• Basic agent profile creation and management
• Document upload and processing system
• Agent knowledge base integration
• Inter-agent conversation system
• Bucket creation and management
• Document generation and summarization
• Core business logic implementation
• Basic API structure

In Progress 🚧

• FastAPI backend completion
• Agent performance metrics
• Enhanced error handling and logging
• User authentication system

Getting Started

Prerequisites

• Python 3.8 or higher
• pip package manager
• Virtual environment support

Setup Instructions

1. Clone the repository:

   git clone https://github.com/infiniteregenAI/infiniteFE.git
   cd infiniteFE

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # Linux/Mac
   # or
   .\venv\Scripts\activate  # Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the project root directory:

     OPENAI_API_KEY=your_openai_api_key_here
     DB_URL=postgres_db_url

Running SwarmSphere

Run Core Backend Application

Run the following command to start the FastAPI backend:

uvicorn api.main:app --reload

Access the API documentation at http://localhost:8000/docs.

Run Corev2 Application

Run the following command to start the Corev2 FastAPI application:

cd corev2

uvicorn main:app --reload

Access the API documentation at http://localhost:8000/docs.

Project Structure

SwarmSphere/
├── core/                   # Core business logic
│   ├── __init__.py
│   ├── models.py           # Data models
│   ├── agent_manager.py    # Agent management logic
│   └── conversation_manager.py
│
├── corev2/                 # Advanced core components
│   ├── agent.json          # Agent configuration template
│   ├── team.json           # Team configuration template
│   ├── agent_manager.py    # Advanced agent management
│   ├── main.py             # Core application logic
│   └── models.py           # Advanced data models
│
├── api/                    # FastAPI implementation
│   ├── __init__.py
│   ├── main.py             # API routes and configuration
│   ├── models.py           # API data models
│   └── routers/            # API route definitions
│
└── requirements.txt        # Project dependencies

Quick Start Guide

1. Create an Agent

• Access the Agent Management page via the UI.
• Define the agent's personality and expertise.
• Upload knowledge documents to the agent's knowledge base.

2. Create a Bucket

• Navigate to the Bucket Management page.
• Set the bucket's goal or purpose.
• Select participating agents and configure conversation parameters.

3. Start Collaboration

• Launch the bucket to initiate agent interactions.
• Monitor agent conversations and progress in real-time.
• Generate and download collaborative documentation.

Future Enhancements

• Agent Market: Allow users to trade pre-configured agents.
• Real-Time Collaboration: Enhance live interaction monitoring.
• Integrations: Add support for external services like Slack and Google Docs.
• Advanced Analytics: Provide detailed insights into agent and bucket performance.

Contributing

We welcome contributions to SwarmSphere! To contribute:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-name).
3. Commit your changes (git commit -m "Add new feature").
4. Push to your branch (git push origin feature-name).
5. Open a pull request.

Contact

For questions or feedback, please reach out to hoomandigital18@gmail.com.