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.