PDF Query Chrome Extension

A Chrome extension to answer queries based on information provided in uploaded PDF files.

Introduction

This project introduces a Chrome extension that facilitates query-based interactions with PDF files. Users can upload PDF documents, and the extension will analyze the content to provide relevant answers to queries.

Features

• PDF Parsing: Automatically extracts text and relevant information from uploaded PDF files using PyPDFLoader.
• Query Handling: Processes user queries and provides accurate responses based on the content of the PDF documents.
• Language Processing: Utilizes Google Generative AI embeddings and chat functionalities through langchain_google_genai for document analysis and question answering.
• Seamless Integration: Integrated directly into the Chrome browser for convenient usage.

Input Data

• Uploaded PDF Files: Users can upload PDF files containing information to query.
• Query Handling: Queries from users are processed to generate accurate responses based on the content of the PDF documents.

Functionality

1. PDF Parsing: The extension parses the uploaded PDF files to extract relevant information using PyPDFLoader.
2. Query Handling: Queries from users are processed to generate accurate responses based on the content of the PDF documents.
3. Gemini AI Model: Utilizes Google Generative AI model Gemini-pro for generating responses to user queries.
4. Embeddings and Vector Index: Utilizes GoogleGenerativeAIEmbeddings and Chroma from long-chain for creating embeddings and vector index.
5. QA Chain: Utilizes RetrievalQA from langchain to perform question answering based on the embeddings and vector index.

Future Enhancements

• Improved Query Understanding: Enhance natural language processing capabilities for a better understanding of user queries.
• Enhanced User Interface: Improve the user interface for a more intuitive and user-friendly experience.
• Support for More File Formats: Extend support for parsing and analyzing various file formats beyond PDF.
• Form Filling Capability: Develop a form-filling capability to automatically fill forms based on extracted information from PDF files.

Dependencies

• Flask: Micro web framework for Python.
• langchain_community: Library for loading documents.
• langchain: Library for text splitting and chains.
• langchain_google_genai: Library for Google Generative AI embeddings and chat functionalities.
• google.generativeai: Google's Generative AI library.

Contributor

• Pramit De (email: [email protected]/[email protected]) (Department of CSE, Techno International New Town, West Bengal, India)