Rockbot - AI Assistant

A comprehensive AI assistant project with advanced features including Q&A, content generation, translation, autonomous task execution, multi-agent architecture, multi-modal processing, adaptive learning, real-time interaction, conversation sharing and PDF export capabilities.

Features

Core AI Capabilities

• Multi-Agent Architecture: Specialized agents for different tasks (General, Translator, Creative Writer, Problem Solver, Task Executor)
• Question Answering: Intelligent responses to user queries
• Content Generation: Creative writing, brainstorming, and idea generation
• Translation: Multi-language translation capabilities
• Autonomous Task Execution: Step-by-step task planning and execution
• Adaptive Learning: Conversation memory and context awareness

User Interface

• Real-time Chat Interface: Modern, responsive chat UI built with TypeScript
• Conversation Management: Create, save, and manage multiple conversations
• Agent Selection: Choose specific AI agents for different tasks
• Mobile-Friendly: Responsive design for desktop and mobile devices

Advanced Features

• Multi-Modal Processing: Image upload and analysis using OpenAI Vision API
• Document Processing: Support for various file formats (PDF, text, images)
• Conversation Export: Export conversations as PDF or text files
• Conversation Sharing: Share conversations with others
• Search and Filter: Find conversations by content or date

Project Structure

rockbot_assistant/
├── backend/                    # Flask backend API
│   └── rockbot_api/
│       ├── src/
│       │   ├── models/         # Database models
│       │   │   ├── user.py
│       │   │   └── conversation.py
│       │   ├── routes/         # API endpoints
│       │   │   ├── user.py
│       │   │   ├── chat.py
│       │   │   ├── export.py
│       │   │   └── multimodal.py
│       │   ├── services/       # AI service integration
│       │   │   └── ai_service.py
│       │   ├── static/         # Frontend build files
│       │   └── main.py         # Flask application entry point
│       ├── venv/               # Python virtual environment
│       └── requirements.txt    # Python dependencies
├── frontend/                   # TypeScript frontend
│   └── rockbot-ui/
│       ├── src/
│       │   ├── components/     # TypeScript components
│       │   │   ├── ui/         # UI components (shadcn/ui)
│       │   │   └── ChatInterface.tsx
│       │   ├── App.tsx         # Main App component
│       │   └── main.tsx        # TypeScript entry point
│       ├── package.json        # Node.js dependencies
│       └── dist/               # Production build
├── models/                     # AI models directory
├── setup.sh                   # Setup script
├── run_dev.sh                  # Development server script
├── run_prod.sh                 # Production server script
└── README.md                   # This file

Installation

Prerequisites

• Python 3.8 or higher
• Node.js 16 or higher
• npm or pnpm package manager

Quick Setup

1. Clone or download the project

   # If you have the project files, navigate to the directory
   cd rockbot_assistant

2. Run the setup script

   chmod +x setup.sh
   ./setup.sh

   This script will:

   • Set up the Python virtual environment
   • Install backend dependencies
   • Install frontend dependencies
   • Build the frontend for production
   • Copy frontend files to the Flask static directory

Manual Setup

If you prefer to set up manually:

1. Backend Setup

   cd backend/rockbot_api
   python3 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt

2. Frontend Setup

   cd frontend/rockbot-ui
   npm install  # or pnpm install
   npm run build  # or pnpm run build

3. Copy Frontend Build

   cp -r frontend/rockbot-ui/dist/* backend/rockbot_api/src/static/

Configuration

Environment Variables

Create a .env file in the backend/rockbot_api directory with:

OPENAI_API_KEY=your_openai_api_key_here
OPENAI_API_BASE=https://api.openai.com/v1
FLASK_ENV=development
FLASK_DEBUG=1

Note: The OpenAI API key is required for AI functionality. Get your API key from OpenAI Platform.

Running the Application

Development Mode

./run_dev.sh

Production Mode

./run_prod.sh

The application will be available at http://localhost:5000

API Endpoints

Chat Endpoints

• POST /api/chat - Send message to AI
• GET /api/conversations - Get all conversations
• POST /api/conversations - Create new conversation
• GET /api/conversations/{id} - Get specific conversation
• DELETE /api/conversations/{id} - Delete conversation

AI Agent Endpoints

• GET /api/agents - Get available AI agents
• POST /api/translate - Translate text
• POST /api/task - Execute autonomous task

Export Endpoints

• GET /api/conversations/{id}/export - Export conversation as text
• GET /api/conversations/{id}/pdf - Export conversation as PDF
• POST /api/conversations/{id}/share - Create shareable link

Multi-Modal Endpoints

• POST /api/upload - Upload and process files
• POST /api/analyze-image - Analyze image with custom prompt
• POST /api/chat-with-image - Chat about uploaded image

Usage Examples

Basic Chat

// Send a message to the AI
const response = await fetch('/api/chat', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    message: "Hello, how are you?",
    agent_type: "general"
  })
});

Translation

// Translate text
const response = await fetch('/api/translate', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    text: "Hello world",
    target_language: "Spanish"
  })
});

Task Execution

// Execute autonomous task
const response = await fetch('/api/task', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    task_description: "Plan a birthday party for 20 people"
  })
});

AI Agents

Available Agents

1. General Assistant (general)

   • Capabilities: Q&A, explanation, general knowledge
   • Best for: General questions and conversations

2. Translator (translator)

   • Capabilities: Translation, language detection
   • Best for: Multi-language communication

3. Creative Writer (creative)

   • Capabilities: Creative writing, brainstorming, storytelling
   • Best for: Creative projects and idea generation

4. Problem Solver (problem_solver)

   • Capabilities: Problem solving, logical reasoning, step-by-step guidance
   • Best for: Complex problem analysis

5. Task Executor (task_executor)

   • Capabilities: Task planning, autonomous execution, project management
   • Best for: Planning and organizing tasks

Development

Adding New Features

1. Backend: Add new routes in src/routes/
2. Frontend: Add new components in src/components/
3. AI Services: Extend src/services/ai_service.py

Database Models

The application uses SQLite with SQLAlchemy ORM:

• Conversation: Stores conversation metadata
• Message: Stores individual messages with role and content

Frontend Components

Built with TypeScript and modern UI components:

• Tailwind CSS for styling
• shadcn/ui for UI components
• Lucide TypeScript for icons

Deployment

Local Deployment

Use the provided scripts for easy local deployment.

Production Deployment

For production deployment:

1. Set up a proper WSGI server (e.g., Gunicorn)
2. Configure environment variables
3. Set up a reverse proxy (e.g., Nginx)
4. Use a production database (e.g., PostgreSQL)

Troubleshooting

Common Issues

1. OpenAI API Key Error

   • Ensure your API key is set in environment variables
   • Check API key validity and billing status

2. Database Errors

   • Delete src/database/app.db and restart to reset database
   • Check file permissions

3. Frontend Build Issues

   • Clear node_modules and reinstall dependencies
   • Check Node.js version compatibility

4. Port Already in Use

   • Change port in src/main.py or kill existing processes

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

This project is open source and available under the Apache License.

Support

For issues and questions:

1. Check the troubleshooting section
2. Review the API documentation
3. Check console logs for error details

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Rockbot - Your intelligent AI assistant for every task.