PromptPDF

A modern web application that leverages AI to process and interact with PDF documents. Built with Next.js, TypeScript, and cutting-edge AI/ML technologies.

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Core Features

• PDF Processing: Upload and process PDF documents
• AI-Powered Chat: Interactive chat interface for document-based Q&A
• Authentication: Secure user authentication system
• File Management: Organize and manage uploaded PDFs
• Responsive Design: Works across desktop and mobile devices

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Technology Stack

Frontend

• Next.js 15 – React framework for modern web apps
• TypeScript – Strongly-typed JavaScript for scalability
• Tailwind CSS – Utility-first styling framework
• shadcn/ui – Accessible and customizable UI components
• TanStack Query – State and data-fetching management
• Framer Motion – Smooth, modern animations

Backend

• Next.js API Routes – Serverless API endpoints
• Drizzle ORM – Type-safe database client
• PostgreSQL (Neon) – Scalable cloud database
• AWS S3 – File storage for PDF uploads

AI/ML

• LangChain – Framework for building LLM-driven apps
• Google Generative AI – Model integration for contextual chat
• Pinecone – Vector database for semantic document search

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Agile Development Overview

PromptPDF was developed following Agile methodology to ensure adaptability, collaboration, and rapid iteration between May 30 and July 14.

Development Summary

Role	Developer	Duration	Methodology	Key Focus Areas
Lead Developer	Jeevakrishna Vetrivel	May 30 – July 14, 2025	Agile (Scrum + Kanban Hybrid)	PDF ingestion, RAG integration, UI/UX design, AI pipeline optimization

Agile Workflow Highlights

• Sprint Planning: Organized work into 3 major sprints (Core App, AI System, UI Polish)
• Daily Standups (Async): Used GitHub Issues & Projects for task updates
• CI/CD Integration: Automated builds and testing through GitHub Actions
• Iterative Testing: Continuous feedback loop for performance and UX refinement
• Documentation: Maintained changelogs, retrospectives, and sprint notes

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RAG (Retrieval-Augmented Generation) Architecture

PromptPDF integrates a RAG system to enhance the accuracy and contextuality of AI-generated responses.

Workflow:

1. Document Ingestion → PDFs parsed and chunked into semantic units
2. Vectorization → Chunks embedded using Google Generative AI embeddings
3. Vector Storage → Stored in Pinecone for efficient semantic search
4. Context Retrieval → Relevant chunks retrieved for each user query
5. Response Generation → LangChain sends context to LLM for accurate answers

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Getting Started

Prerequisites

• Node.js 18+
• PostgreSQL Database
• AWS S3 Bucket
• Google AI API Key
• Pinecone API Key

Installation

1. Clone the repository

git clone https://github.com/your-username/PromptPDF.git
cd PromptPDF

2. Install dependencies

   npm install
   # or
   yarn install
   # or
   pnpm install

3. Set up environment variables Create a .env.local file in the root directory with the following variables:

   DATABASE_URL=your_postgres_connection_string
   AWS_ACCESS_KEY_ID=your_aws_access_key
   AWS_SECRET_ACCESS_KEY=your_aws_secret_key
   AWS_REGION=your_aws_region
   AWS_BUCKET_NAME=your_s3_bucket_name
   GOOGLE_AI_API_KEY=your_google_ai_api_key
   PINECONE_API_KEY=your_pinecone_api_key
   NEXTAUTH_SECRET=your_nextauth_secret
   NEXTAUTH_URL=http://localhost:3000

4. Run database migrations

   npx drizzle-kit push:pg

5. Start the development server

   npm run dev
   # or
   yarn dev
   # or
   pnpm dev

6. Open http://localhost:3000 in your browser

Project Structure

src/
├── app/                    # App router pages and layouts
│   ├── api/               # API routes
│   │   ├── chat/          # Chat API endpoints
│   │   └── create-chat/   # Chat creation endpoints
│   └── chat/              # Chat interface
│       └── [chatId]/      # Individual chat sessions
├── components/            # Reusable UI components
├── lib/                   # Utility functions and configurations
└── drizzle/               # Database schema and migrations

Development Workflow

1. Branching Strategy

   • main - Production-ready code
   • develop - Development integration branch
   • feature/* - New features
   • bugfix/* - Bug fixes

2. Code Style

   • Follow the Next.js style guide
   • Use TypeScript for type safety
   • Follow the existing code style and patterns

3. Commits

   • Write clear, descriptive commit messages
   • Reference issues when applicable

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Next.js - The React Framework for Production
• LangChain - Building applications with LLMs
• shadcn/ui - Beautifully designed components
• Tailwind CSS - A utility-first CSS framework

Author

Jeevakrishna Vetrivel

• GitHub: @Jeevakrishna
• LinkedIn: Jeevakrishna Vetrivel
• Portfolio: Jeevakrishna Vetrivel