Swastik AI

Swastik AI is a Flask-based AI chat web application with user authentication, chat session storage, and support for multiple AI providers.

Key Features

• User registration and login with password hashing
• Persistent chat sessions and message history using PostgreSQL
• Multi-model AI routing across Gemini, Groq, SambaNova, and GitHub-hosted models
• Simple command handling for opening common websites from chat input
• Single-page web interface served by Flask

Technology Stack

• Python
• Flask
• Flask-CORS
• Flask-SQLAlchemy
• Flask-Bcrypt
• PostgreSQL
• OpenAI SDK (for compatible providers)
• Google Generative AI SDK
• Gunicorn

Project Structure

• app.py - Main Flask application, API routes, model routing, and database models
• swastik_f.html - Frontend UI template
• requirements.txt - Python dependencies

API Endpoints

• GET / - Loads the web interface
• POST /register - Creates a new user account
• POST /login - Authenticates an existing user
• POST /agent - Processes user input and returns model or system-command responses

Environment Variables

Set these in a .env file or environment:

• DB_PASSWORD - PostgreSQL password
• DB_PORT - PostgreSQL port
• GEMINI_API_KEY - Google Gemini API key
• GROQ_API_KEY - Groq API key
• SAMBANOVA_KEY - SambaNova API key
• GITHUB_TOKEN - GitHub models inference token
• MISTRAL_KEY - Mistral API key
• HF_TOKEN - Hugging Face token

Setup and Run

1. Clone the repository.
2. Create and activate a Python virtual environment.
3. Install dependencies:

pip install -r requirements.txt

4. Ensure PostgreSQL is running.
5. Create the required database. The app currently expects the database name swastik_data because it is hardcoded in app.py.

createdb swastik_data

6. Configure environment variables.
7. Start the app:

python app.py

The application runs on http://localhost:5001 by default.

Notes

• Database tables are created automatically at startup using db.create_all() once the PostgreSQL database exists.
• In development mode, Flask debug is enabled in app.py.
• Never enable debug mode in production because it can expose sensitive data and remote code execution paths through the debugger.
• For production, use Gunicorn with debug disabled.