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The QueryDocs backend is built with FastAPI, handles PDF uploads, extracts text using PyMuPDF, and processes queries with LangChain's NLP capabilities. It stores document metadata in a SQLite database, ensuring efficient document management and accurate answers to user questions.

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Uzair-Manzoor/query-docs-backend

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Setup Instructions

Backend

  1. Navigate to the backend directory.
  2. Install dependencies: pip install -r requirements.txt
  3. Run the application: uvicorn main:app --reload

Frontend

  1. Navigate to the frontend directory.
  2. Install dependencies: npm install
  3. Run the application: npm start

🔘 Follow the link for Frontend Source Code

API Documentation

Upload PDF

  • Endpoint: /upload
  • Method: POST
  • Body: file (form-data)

Ask Question

  • Endpoint: /ask
  • Method: POST
  • Body: filename, question

Application Overview

The application allows users to upload PDF documents and ask questions about their content. The backend uses FastAPI to handle requests and LangChain for NLP processing. The frontend is built with React.js.

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The QueryDocs backend is built with FastAPI, handles PDF uploads, extracts text using PyMuPDF, and processes queries with LangChain's NLP capabilities. It stores document metadata in a SQLite database, ensuring efficient document management and accurate answers to user questions.

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