QueryPDF

Welcome to the QueryPDF! This project aims to create a full-stack application that allows users to upload PDF documents, ask questions about their content, and receive answers generated through natural language processing. Below are the setup instructions, API documentation, and an overview of the application architecture.

Setup Instructions

1. Backend Setup

   • Clone the repository:

     git clone https://github.com/Jai0401/QueryPDF.git
     

   • Navigate to the backend directory:

     cd backend
     

   • Install dependencies:

     pip install -r requirements.txt
     

   • Create a new file named .env in the backend directory
   • Start the FastAPI server:

     uvicorn app:app --reload
     

2. Frontend Setup

   • Navigate to the frontend directory:

     cd frontend
     

   • Install dependencies:

     npm install
     

   • Start the React development server:

     npm run dev
     

API Documentation

• PDF Upload Endpoint

  • POST /upload_pdf
  • Request Body: Form Data
    • file: PDF file
  • Response: { "info": "File <file-name> uploaded and processed successfully" }

• Question-Answer Endpoint

  • POST /ask_question
  • Request Body: { "user_question": <question_text> }
  • Response: { "question": "<question_text>", "answer": "<answer_text>" }

Application Architecture

• Backend (FastAPI)

  • Handles PDF uploads, question processing, and answer generation.
  • Utilizes LangChain for natural language processing.
  • Backend Architecture and Workflow Overview

• Frontend (React.js)

  • Provides interfaces for PDF upload and asking questions.
  • Displays answers and allows for follow-up or new questions on uploaded documents.
  • Implements feedback mechanisms and error handling for user interactions.

Demo

• A live demo of the application can be accessed at https://query-pdf-swart.vercel.app/.
• Demo video.