🤖 Clarus (ExaBytes RAG Demo Application)

A modern web application implementing Retrieval Augmented Generation (RAG) using Flask and Tailwind CSS. Upload documents and get AI-powered answers based on their content.

Features • Quick Start • Installation • Usage • Architecture • Development

✨ Features

• 📄 Document Processing

  • Support for PDF and TXT files
  • Automatic text chunking and embedding
  • Efficient vector storage with ChromaDB

• 🔍 Advanced RAG Implementation

  • Powered by Groq's Mixtral-8x7b model
  • Sentence transformers for embeddings
  • Context-aware question answering

• 🎨 Modern UI/UX

  • Clean, responsive design with Tailwind CSS
  • Real-time loading states
  • Toast notifications for feedback
  • Drag-and-drop file upload

🚀 Quick Start

# Clone the repository
git clone https://github.com/yourusername/clarus.git
cd clarus

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
uv pip install -e .

# Set up environment variables
cp app/.env.example app/.env
# Edit app/.env with your API keys

# Run the application
python main.py

Visit http://localhost:5000 in your browser to start using the application.

🛠️ Installation

Prerequisites

• Python 3.11+
• uv package manager (recommended) or pip
• Groq API key for LLM access

Detailed Setup

1. Environment Setup

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install Dependencies

   Using uv (recommended):

   uv pip install -e .

   Using pip:

   pip install -r requirements.txt

3. Configure Environment Variables

   cp app/.env.example app/.env

   Edit app/.env and add:

   SECRET_KEY=your-secret-key
   GROQ_API_KEY=your-groq-api-key
   

🎯 Usage

1. Upload Documents

   • Click the upload area or drag and drop files
   • Supported formats: PDF, TXT
   • Wait for the success notification

2. Ask Questions

   • Enter your question in the text area
   • Click "Get Answer"
   • View AI-generated response based on your documents

🏗️ Architecture

.
├── app/                  # Application package
│   ├── templates/       # HTML templates
│   ├── static/         # Static files
│   ├── utils/          # Utility modules
│   │   └── rag.py     # RAG implementation
│   └── routes.py       # Flask routes
├── main.py             # Application entry point
├── pyproject.toml      # Project metadata and dependencies
└── requirements.txt    # Direct dependencies

🧪 Development

Tech Stack

• Backend

  • Flask: Web framework
  • LangChain: RAG implementation
  • ChromaDB: Vector storage
  • Sentence Transformers: Text embeddings
  • Groq: LLM provider

• Frontend

  • Tailwind CSS: Styling
  • Vanilla JavaScript: Interactivity

Development Tools

# Install development dependencies
uv pip install -e ".[dev]"

# Format code
black app/
isort app/

# Lint code
flake8 app/

📄 License

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

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Made with ❤️ using Flask, LangChain, and Groq