📄 Document Retrieval System 🔍

🌟 Project Overview

A powerful Django-based document retrieval system leveraging cutting-edge technologies including LangChain, FAISS, and Groq for intelligent document processing and querying.

✨ Features

• 📤 Seamless Document Upload and Processing
• 🧩 Advanced Text Splitting and Vectorization
• 🤖 Intelligent Querying with Groq LLM
• 🌐 CORS-Enabled API Endpoints

🛠️ Prerequisites

Before you begin, ensure you have the following installed:

• Python 3.8+
• Django
• Node.js and npm
• Ollama
• React

🚀 Installation and Setup

1. Clone the Repository

git clone https://github.com/your-username/document-retrieval-system.git
cd document-retrieval-system

2. Backend Setup

# Navigate to the Django project directory
cd document_retrival

# Create a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

# Install Python dependencies
pip install -r requirements.txt

# Install Ollama
# Visit https://ollama.ai/ for installation instructions specific to your OS

3. Frontend Setup

# Navigate to the frontend directory
cd ../document-retrieval-frontend

# Install npm packages
npm install
npm install react-icons

🖥️ Running the Application

Open 4 separate terminal windows and run the following commands:

Terminal 1: Django Server

cd document_retrival
python manage.py runserver

Terminal 2: Ollama Service

ollama serve

Terminal 3: Pull Llama2 Model

ollama pull llama2

Terminal 4: React Frontend

cd document-retrieval-frontend
$env:NODE_OPTIONS="--openssl-legacy-provider"
npm start

🤝 Contributing

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

📜 License

[Add your license information here]

🙌 Acknowledgments

• Django
• LangChain
• FAISS
• Groq
• Ollama