ai-planet Assignment

Brief

This fullstack application allows users to upload PDF documents and ask questions related to their content. The backend processes the documents using FastAPI and LangChain, while the React-based frontend ensures an intuitive user experience.

Features

• PDF Upload: Users can upload PDF documents to the application.
• Question Answering: Users can ask questions based on the content of uploaded PDFs, with answers generated using OpenAI API through LangChain.
• Follow-Up Questions: Ability to ask follow-up or new questions on the same document.
• Database Management: PostgreSQL database to store metadata like filename and upload date.
• Interactive Frontend: Modern UI built with React and styled using Tailwind CSS with ShadCN UI components.

Project Structure

client/
  ├── node_modules/         # Node.js dependencies
  ├── public/               # Public static assets like CSS and images
  │   ├── index.html        # Main HTML file
  │   └── favicon.ico       # Application favicon
  ├── src/                  # Source code for the application
  │   ├── assets/           # Static assets (e.g., images, icons)
  │   ├── components/       # Components for the UI
  │   │   ├── ui/           # UI-specific components
  │   │   │   ├── ChatQA.tsx      # Chat question and answer component
  │   │   │   └── FileUpload.tsx  # File upload component
  │   ├── lib/              # Utility libraries
  │   ├── App.tsx           # Root component
  │   ├── main.tsx          # Entry point
  │   ├── index.css         # Global styles
  │   └── vite-env.d.ts     # TypeScript environment definitions
  ├── dist/                 # Build output directory
  └── .gitignore            # Git ignore file

server/
  ├── main.py               # Entry point for the FastAPI server
  ├── models.py             # Database models
  ├── routes.py             # API endpoints
  ├── utils.py              # Helper functions
  └── requirements.txt      # Python dependencies
  └── .env                  # Environment variables for sensitive data

Setup Instructions

Backend Setup

1. Install Python Dependencies:

   pip install -r requirements.txt

2. Set Up PostgreSQL:

   • Install PostgreSQL.
   • Create a new database for the project.
   • Retrieve the PostgreSQL connection string (format: postgresql://<username>:<password>@<host>:<port>/<database>).

3. Run the Backend Server:

   uvicorn main:app --reload

Frontend Setup

1. Install Node.js and npm: Ensure you have Node.js installed (check using node -v and npm -v).

2. Install Frontend Dependencies: Navigate to the client folder and run:

   npm install

3. Start the Development Server:

   npm run dev

Connect Frontend and Backend

• Update the API endpoint in the frontend configuration to point to the backend server (e.g., http://localhost:8000).

Day 1

Configured the client and servers File uploads and extract text from the uploaded pdf

Day 2

work on the NLP preocessing Q&A

day 3

database part remaining

day 4

deployment

Contact

For any queries, reach out at: gurijalahruday@gmail.com