Ask Racha

A web application that provides an AI-powered interface to interact with Storacha's documentation. The application uses advanced language models and RAG (Retrieval-Augmented Generation) to provide accurate and contextual responses.

Features

• Interactive chat interface
• Integration with Google's Gemini AI model
• Web-based documentation retrieval
• Real-time response generation
• Modern UI built with Next.js and Tailwind CSS

Tech Stack

Frontend

• Next.js 15.3.3
• React 19
• TypeScript
• Tailwind CSS
• Lucide React (for icons)

Backend

• Python Flask
• LlamaIndex
• Google Gemini AI
• BeautifulSoup4 (for web scraping)

Prerequisites

• Node.js (Latest LTS version)
• Python 3.8+
• Gemini API key

Installation

1. Clone the repository:

git clone https://github.com/Dhruv-Varshney-developer/ask-racha.git
cd ask-racha

2. Install frontend dependencies:

cd askracha
npm install

3. Install backend dependencies:

cd backend
pip install -r requirements.txt

4. Set up environment variables:

For the frontend:

cd askracha
cp .env.example .env

For the backend:

cd askracha/backend
cp .env.example .env

Then edit both .env files and add your Gemini API key:

GEMINI_API_KEY=your_api_key_here

Vector Store Setup

Local Development

1. Make sure Docker is installed and running
2. Start Qdrant:

cd askracha/backend/storage
docker compose up -d

3. Verify the setup:

cd askracha/backend
python -m unittest storage/tests/test_vector_store.py -v

Environment Variables

For local development:

• No additional env vars needed, uses Qdrant Local by default
• Qdrant runs on port 6343 (configurable via QDRANT_PORT)

For production:

QDRANT_HOST=your_qdrant_host
QDRANT_PORT=6333
QDRANT_API_KEY=your_api_key

Running the Application

Development Mode

To run both frontend and backend concurrently:

npm run dev:full

Or run them separately:

Frontend:

npm run dev

Backend:

npm run backend

Production Build

1. Build the frontend:

npm run build

2. Start the production server:

npm run start

Available Scripts

• npm run dev - Start the Next.js development server with Turbopack
• npm run build - Build the application for production
• npm run start - Start the production server
• npm run lint - Run ESLint for code linting
• npm run backend - Start the Python backend server
• npm run dev:full - Run both frontend and backend concurrently

Project Structure

askracha/
├── backend/           # Python Flask backend
│   ├── app.py        # Main Flask application
│   ├── rag.py        # RAG implementation
│   └── requirements.txt
├── src/              # Frontend source code
├── public/           # Static assets
└── package.json      # Frontend dependencies and scripts

License

This project is licensed under the terms of the license included in the repository.

Contributing

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