Open Source LLM ChatBot 🩺🤖

Introduction

Welcome to the LLM using LLA-Ma 2 ChatBot repository! This sophisticated tool is engineered to provide prompt Chat information in response to user queries. Leveraging cutting-edge language models and vector stores, Llama2 Chat Bot stands as a beacon in digital healthcare assistance.

Table of Contents

• Introduction
• Prerequisites
• Installation
• Getting Started
• Usage
• Contributing
• License

Prerequisites

Before diving into the Llama2 Chat Bot, ensure your system is equipped with:

• Python 3.6 or higher
• Necessary Python packages (installable via pip):
  • langchain
  • chainlit
  • sentence-transformers
  • faiss
  • PyPDF2 (for PDF document loading)
  • huggingface_hub
  • ctransformers
  • chainlit

Installation

1. Clone the Repository:

   git clone https://github.com/atulX7/ChatBot.git
   cd Chatbot
   

2. **Install the dependencies:

   pip install -r requirements.txt
   

3. Download Language Models and Data:

• Refer to the Langchain documentation for instructions on downloading and setting up the language model and vector store from the code file.

5. Configure Paths and Settings:

• Set DB_FAISS_PATH and other configurations as required for your project.

Getting Started

To kickstart your journey with the Llama2 Chat Bot:

1. Set up your environment and install packages as outlined in Installation.
2. Configure the project (DB_FAISS_PATH and other custom configurations).
3. Prepare the language model and data following the Langchain documentation.

Usage

Use the Chat Bot to get answers to Chat queries:

1. Train the Chatbot using your custom data: a. Place your PDF files in DATA_PATH path. b. Run:

   python ingest.py
   

2. To Query the Chatbot, run

   python Chatbot.py -q <query>
   

3. To run locally (ChatBot using Chainlit)

   chainlit run chainlit.py -w
   

4. Customize the bot's responses based on specific queries and contexts.

Contributing

We welcome contributions to the Chat ChatBot! 🌟 Here's how you can contribute:

1. Fork the repository to your account.
2. Create a new branch for your feature or bug fix.
3. Implement your changes and ensure all tests pass.
4. Submit a pull request detailing your changes.
5. After review, your contributions may be merged into the main codebase.

License

This project is licensed under the MIT License.

For detailed guidance on usage, configuration, and extension, please refer to the Langchain documentation or contact the project maintainers.

🚀 Happy coding! 🚀