/query-docs-frontend

A full-stack app designed to streamline doc analysis and research process. Users can easily upload PDF docs and ask detailed questions about their content. Utilizing advanced natural language processing (NLP) capabilities, DocQ&A provides accurate and contextually relevant answers, making document review and comprehension faster and more efficient.

Primary LanguageJavaScriptMIT LicenseMIT

Setup Instructions

Frontend

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

Backend

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

Follow the link for Backend Source Code

Follow the link for Live Demo

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.