PSY-RAG-App

A sophisticated RAG (Retrieval-Augmented Generation) application built with TypeScript, Express.js, and LangChain. This application allows users to process PDF documents and perform intelligent question-answering using advanced language models.

Features

• 📄 PDF Document Processing
• 🔍 Intelligent Document Search
• 💡 Question-Answering System
• 🚀 Built with LangChain and TypeScript
• 🔒 Secure API Endpoints
• 🎯 Efficient Document Chunking and Embedding

Prerequisites

• Node.js (v16 or higher)
• TypeScript
• Ollama (for local embeddings)
• HuggingFace API key (for language model access)

Installation

1. Clone the repository:

git clone https://github.com/yourusername/psy-rag-app.git
cd psy-rag-app

2. Install dependencies:

npm install

3. Create a .env file in the root directory and add your configuration:

HUGGINGFACE_API_KEY=your_api_key_here
PORT=3000

Running the Application

For development:

npm run dev

The server will start on the configured port (default: 3000).

Project Structure

src/
├── app.ts          # Express application setup
├── server.ts       # Server initialization
├── helper.ts       # Utility functions
├── data/          # PDF storage directory
└── services/
    ├── rag.service.ts    # RAG implementation
    └── ai.service.ts     # AI model integration

API Endpoints

• POST /upload - Upload PDF documents
• POST /query - Query the documents with questions

Technologies Used

• TypeScript
• Express.js
• LangChain
• HuggingFace
• Ollama
• PDF-Parse

License

ISC

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.