An intelligent chatbot application that combines text generation with visual output. Users can send prompts to receive AI-generated responses and corresponding images based on the generated text.

• Text Generation: Natural language processing using LangGraph and Neo4j integration
• Image Generation: AI-powered image creation from text prompts
• Movie Database Integration: Specialized endpoints for movie-related questions with Neo4j graph database support
• Real-time Processing: FastAPI backend with CORS support for seamless frontend integration
• Modern UI: Clean, responsive web interface built with Tailwind CSS

• FastAPI: RESTful API server with automatic documentation
• Neo4j Integration: Graph database for movie data queries using Cypher
• LangGraph: Agent-based text generation workflow
• Multiple AI Models: Support for SambaNova, DeepSeek, and Google Gemini models
• Galileo Integration: AI observability and monitoring

• Single Page Application: Modern HTML/CSS/JavaScript interface
• Tailwind CSS: Utility-first styling framework
• Responsive Design: Works across desktop and mobile devices
• Real-time Updates: Dynamic content loading and image display

• GET /health - Health check endpoint
• POST /ask-movie-question - Process movie-related questions and return AI responses
• POST /generate-image - Generate images from text prompts

• FastAPI - Modern, fast web framework for building APIs
• Neo4j - Graph database for movie data
• LangGraph - Framework for building stateful multi-actor applications
• OpenAI/SambaNova APIs - AI model integrations
• Galileo - AI observability platform
• Google Generative AI - Image and text generation
• Python-dotenv - Environment variable management

• Vanilla JavaScript - No framework dependencies
• Tailwind CSS - Utility-first CSS framework
• Modern fetch API - For backend communication

• Python 3.8+
• Neo4j database instance
• API keys for SambaNova, OpenAI, and Google AI services

1. Clone the repository

2. Install backend dependencies:

   cd backend
   pip install -r requirements.txt

3. Set up environment variables:

   • Copy template.env to .env
   • Configure your API keys and database credentials

4. Start the backend server:

   cd backend
   python main.py

5. Open index.html in your browser or serve it via a web server

Create a .env file based on template.env with the following variables:

• SAMBANOVA_API_KEY - SambaNova API key
• NEO4J_URI - Neo4j database URI
• NEO4J_USERNAME - Neo4j username
• NEO4J_PASSWORD - Neo4j password
• GEMINI_API_KEY - Google Gemini API key
• MODEL_FAST - Fast model identifier (default: Meta-Llama-3.3-70B-Instruct)
• MODEL - Primary model identifier (default: Deepseek-V3.1)

1. Open the web interface
2. Enter a prompt in the text area
3. Click "Send" or press Enter
4. View the AI-generated text response
5. See the corresponding generated image based on the text

The application supports both general prompts and movie-specific questions, leveraging the Neo4j database for enhanced movie-related responses.