Chat-Bot-API Documentation

Overview

Chat-Bot-API is a robust FastAPI-based chatbot service designed to provide users with an interactive AI-powered chat experience. This project integrates Retrieval-Augmented Generation (RAG) with OpenAI models, allowing seamless interactions with documents and custom models. Additionally, the project incorporates the free-to-use LLAMA model, making advanced AI technology accessible to all.

The service is modular, scalable, and open source, aiming to deliver efficient AI-driven solutions to users while ensuring flexibility and extensibility.

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What is the Focus?

The primary goal of Chat-Bot-API is to:

• Simplify AI model interaction: By integrating document retrieval and conversational AI.
• Enhance user engagement: With personalized chatbots for every user.
• Democratize AI access: Through open-source implementation and free-to-use models.
• Promote collaboration: By offering a customizable and modular codebase for contributors.

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Features

1. User Authentication:

   • Token-based secure login and registration.
   • Persistent session management.

2. Chatbot Interaction:

   • Personalized chat experiences for users.
   • Support for both OpenAI models and free LLAMA models.
   • Integration of document-based queries via RAG.

3. Model Management:

   • Upload custom models with metadata and visibility options.
   • Delete and manage existing models.

4. Dynamic Chat History:

   • Save, retrieve, and manage chat messages.
   • Efficient handling of large conversations.

5. CORS Middleware:

   • Configured for cross-origin resource sharing to enable broader API usage.

6. Open Source:

   • Fully transparent and modifiable for developers and organizations.

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Installation

Prerequisites

1. Python: Ensure you have Python 3.10 or above installed.
2. MySQL: Set up a MySQL database.
3. Git: Clone the repository.

Steps

1. Clone the Repository:

   git clone https://github.com/UznetDev/Chat-Bot-API.git
   cd Chat-Bot-API

2. Set Up a Virtual Environment:

   python -m venv env
   source env/bin/activate  # For Linux/Mac
   env\Scripts\activate     # For Windows

3. Install Dependencies:

   pip install -r requirements.txt

4. Configure the Environment Variables:

   • Create a .env file in the data directory and add:

     MYSQL_HOST=<Your MySQL Host>
     MYSQL_USER=<Your MySQL User>
     MYSQL_PASSWORD=<Your MySQL Password>
     MYSQL_DATABASE=<Your Database Name>
     REPLECATE_API=<Your Replicate API Key>

5. Run the Application:

   fastapi dev main.py

6. Access the API: Open http://127.0.0.1:8000/docs in your browser for interactive API documentation.

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How It Works

1. User Workflow:

   • Users authenticate using tokens.
   • They can interact with chatbots linked to their accounts.
   • Chatbots process user queries and retrieve AI-generated answers.

2. Model Integration:

   • OpenAI models and LLAMA models are used for RAG and general conversational tasks.
   • Users can upload custom models for tailored experiences.

3. Database Management:

   • Stores user data, chat history, and model metadata in MySQL.

4. CORS Middleware:

   • Enables seamless API access from different domains.

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Project Structure

Chat-Bot-API/
│
├── data/               # Configuration and environment files
│   ├── config.py
│
├── db/                 # Database connection and utility scripts
│   ├── database.py
│
├── models/             # Language model handling
│   ├── llm.py
│
├── routes/             # FastAPI route definitions
│   ├── auth.py
│   ├── promts.py
│   ├── user_page.py
│
├── functions/          # Utility functions
│   ├── functions.py
│
├── main.py             # Entry point of the application
├── loader.py           # Initialization of core components
├── requirements.txt    # Python dependencies
├── README.md           # Documentation (this file)
│
└── .env                # Environment configuration file

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Project Motivation

Chat-Bot-API was developed to address the need for a flexible, scalable, and open-source chatbot service. By integrating RAG and open AI models, it provides users with a robust system for interacting with documents and conversational models. It aims to democratize AI technology by offering free-to-use models and enabling collaboration in the open-source community.

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Contributing

Contributions are welcome! Follow these steps to contribute:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-name

3. Make changes and commit:

   git commit -m "Added a new feature"

4. Push to your fork:

   git push origin feature-name

5. Create a pull request to the main branch.

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License

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

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Contacts

If you have any questions or suggestions, please contact:

• Email: uznetdev@gmail.com
• GitHub Issues: Issues section
• GitHub Profile: UznetDev
• Telegram: UZNet_Dev
• Linkedin: Abdurakhmon Niyozaliev

Thank you for your interest in the project!