/PDF-ChatBot

Generative AI Mini Project using Google Gemini API

Primary LanguagePython

PDF-ChatBot

Overview

PDF-ChatBot is a powerful web application built using Streamlit that allows users to interact with multiple PDF files using natural language queries. Leveraging the capabilities of Google Generative AI and FAISS for vector-based search, this bot provides accurate responses from the content of uploaded PDFs.

The chatbot uses state-of-the-art machine learning models like Gemini and FAISS to process and retrieve relevant sections from large PDFs, making it an efficient tool for document analysis, research, and information extraction.

Features

  • Multiple PDF Support: Upload and process multiple PDFs simultaneously.
  • Natural Language Interaction: Ask questions in natural language and receive detailed answers from the PDF content.
  • Vector Search: FAISS-based search to find relevant answers efficiently.
  • Google Generative AI Integration: Uses the Gemini model to generate responses based on the extracted content.
  • Fast Processing: Capable of handling large documents and returning results quickly.

How It Works

  1. Upload PDFs: Upload one or more PDF files through the interface.
  2. PDF Parsing: The PDFs are parsed, and text is extracted using PyPDF2.
  3. Text Chunking: The extracted text is split into manageable chunks using Langchain's RecursiveCharacterTextSplitter.
  4. Vectorization: Text chunks are converted into vector representations using Google's Generative AI Embeddings.
  5. Vector Store Creation: A FAISS index is created from these vectors for fast similarity search.
  6. Ask Questions: Users can input questions through the interface, and the chatbot will search the PDFs and respond with relevant information.
  7. Response Generation: Based on the search results, the chatbot generates detailed answers using the Gemini model.

Tech Stack

  • Streamlit: Frontend interface for the PDF-ChatBot.
  • Langchain: Used for chaining models and creating vector-based document retrieval.
  • Google Generative AI: Handles embeddings and conversational model responses.
  • FAISS: Efficient similarity search across large text datasets.
  • PyPDF2: For PDF parsing and text extraction.

Getting Started

Prerequisites

  • Python 3.8+

  • Install dependencies:

    pip install -r requirements.txt

  • Set up a .env file with your Google API key:

    GOOGLE_API_KEY=your_api_key_here

Running the App

  1. Clone the repository:

    git clone https://github.com/NitinYadav1511/PDF-ChatBot.git

  2. Navigate to the project directory:

    cd PDF-ChatBot

  3. Install the required Python libraries:

    pip install -r requirements.txt

  4. Run the Streamlit application:

    streamlit run main.py

  5. Upload PDFs through the sidebar and start asking questions!

Usage

  • Upload PDFs: Click on "Upload your PDF Files" in the sidebar to upload multiple PDF documents.
  • Ask Questions: Enter your question in the text input field, and the bot will search the PDFs and respond with relevant answers.

Future Enhancements

  • Add support for summarizing entire PDFs.
  • Improve the conversational flow and context retention across multiple questions.
  • Implement a feedback mechanism to refine answer quality.

Contributor

This repository is maintained by Nitin Yadav.

Contributing

Contributions are welcome! Feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License.