LLM Chatbot

This project demonstrates the development of a chatbot using the Google GEMMA-2B-it model, featuring robust functionalities, a user-friendly interface, and advanced natural language processing capabilities.

Project Overview

The LLM Chatbot is designed to provide intelligent and context-aware responses. It leverages the power of large language models (LLMs) and modern web technologies to deliver a seamless user experience.

- Key Highlights

• Model Used: Google GEMMA-2B-it
• Interface: Built with Streamlit for an intuitive and responsive user experience.
• PDF Interaction: Upload PDFs and ask questions based on their content.

Features

Core Functionalities

• LLM-based Response Generation:
  • Utilized LLM to generate high-quality responses.
  • Fine-tuned using prompt engineering for enhanced performance.
• PDF Upload and Interaction:
  • Upload a PDF and ask questions based on its content.
  • Answers are generated in the correct sequence as per the document.
• Customizable Themes:
  • Light and dark modes for user preference.
• Conversation History:
  • Track conversation history during a session.
  • Download conversations as a .txt file for future reference.
• Custom Commands:
  • /help: Provides guidance on using the chatbot.
  • /clear: Clears the current chat history.
  • /restart: Resets the chatbot for a new session.

Technologies Used

• Google GEMMA-2B-it: For generating accurate and context-aware responses.
• Streamlit: For building an interactive web-based user interface.
• Python: Core programming language for the chatbot logic and backend.
• PyPDF2: For parsing PDF files and extracting text content.

Future Enhancements

• Add multi-language support.
• Implement voice-based input and response.
• Improve PDF parsing for better accuracy with complex documents.