Duffbot: AI Tool Preference Collector

Overview

Duffbot is an AI agent that collects user preferences about AI tools used in daily operations and displays a real-time scoreboard of the most popular tools. The project aims to help users discover and optimize their AI tool usage based on crowd-sourced preferences. It uses FastAPI for the backend, Gradio for the frontend, LlamaIndex for advanced AI agent capabilities, and PostgreSQL with pgVector for efficient data storage and vector operations.

Features

• User-friendly Gradio interface for submitting AI tool preferences
• Real-time updating scoreboard of top AI tools
• Categorization of tools by use case (e.g., productivity, coding, design)
• Anonymous data collection to protect user privacy
• FastAPI backend for efficient data processing and storage
• LlamaIndex integration for advanced AI agent capabilities

Tech Stack

• Backend: FastAPI
• Frontend: Gradio
• AI Agent: LlamaIndex
• Database: Redis

Prerequisites

• Python 3.7+
• pip
• PostgreSQL 11+
• pgVector extension for PostgreSQL

Project Structure

Components

1. Backend (FastAPI)

   • Main API (main.py)
   • Routers:
     • Chat (chat.py)
     • Scoreboard (scoreboard.py)
   • Services:
     • Agent (agent.py)
     • Tool (tool.py)
   • Schemas (schemas.py)

2. Frontend

   • Scoreboard (React + TypeScript + Vite)
   • Chatbot Interface (Gradio)

Directory Explanation

• backend/: Contains the FastAPI application and related files
  • main.py: Main FastAPI application entry point
  • schemas.py: Pydantic schemas for request/response models
  • routers/: API route handlers
• frontend/: Contains the Gradio interface
  • gradio_app.py: Gradio application for user interaction
• tests/: Unit and integration tests
• config/: Configuration files and environment variables
• requirements.txt: Project dependencies
• README.md: Project documentation (this file)
• .gitignore: Specifies intentionally untracked files to ignore

Installation

git clone https://github.com/montevive/duffbot.git
cd duffbot
pip install -r requirements.txt

Usage

1. Start the FastAPI backend:

uvicorn backend.main:app --reload

2. In a new terminal, start the Gradio frontend:

python frontend/gradio_app.py

3. Open a web browser and navigate to the URL provided by Gradio (typically http://localhost:8001)
4. Submit your AI tool preferences using the Gradio interface
5. View the real-time scoreboard to see the most popular tools

API Documentation

After starting the FastAPI server, you can view the API documentation at http://localhost:8000/docs.

Project Origin

This project was developed by the Montevive team for an activity during the third AiBirras event. AiBirras is a community-driven initiative that brings together AI enthusiasts and professionals to share knowledge, collaborate on projects, and explore new ideas in the field of artificial intelligence.

Montevive is proud to contribute to the AI community through projects like Duffbot, fostering innovation and knowledge sharing in the spirit of AiBirras.

Contributing

We welcome contributions to improve Duffbot! Please follow these steps:

1. Fork the repository
2. Create a new branch: git checkout -b feature/your-feature-name
3. Make your changes and commit them: git commit -m 'Add some feature'
4. Push to the branch: git push origin feature/your-feature-name
5. Submit a pull request

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

If you have any questions or suggestions, please open an issue or contact the maintainer at [email protected].

Acknowledgements

• Thanks to all contributors who have helped shape Duffbot
• FastAPI for providing a modern, fast (high-performance) web framework for building APIs
• Gradio for simplifying the creation of web interfaces for ML models
• LlamaIndex for enhancing our AI agent capabilities
• Inspired by the need for better AI tool discovery and optimization