🚀 CoreAI - Enterprise Multi-Agent AI Assistant

An enterprise-level AI assistant powered by a sophisticated multi-agent system. CoreAI coordinates specialized agents to handle your daily tasks including calendar management, email handling, meeting scheduling, weather updates, news aggregation, and task management.

✨ Features

🤖 Specialized AI Agents

• 📅 Calendar Agent: Google Calendar integration for scheduling and availability checks
• 🎥 Meeting Agent: Google Meet video conference management
• 📧 Email Agent: Gmail operations - send, read, search, and organize
• 🌤️ Weather Agent: Real-time weather data and forecasts
• 📰 News Agent: News aggregation from multiple sources
• ✅ Task Agent: Task and to-do list management

🎯 Supervisor Coordination

The Supervisor Agent intelligently:

• Routes requests to appropriate specialist agents
• Coordinates multi-step workflows (e.g., calendar check → meeting creation → calendar booking)
• Manages agent communication and data flow
• Provides unified response formatting

🎨 Enterprise Frontend

• Modern Design: Glassmorphism UI with animated gradients
• Real-time Updates: Live agent status monitoring
• Responsive Dashboard: Activity feeds and analytics
• Multi-page Navigation: Dashboard, Chat, Agents, Connections, Memory, Settings

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                        Frontend (Next.js)                    │
│  Dashboard • Chat • Agents • Connections • Memory • Settings │
└──────────────────────┬──────────────────────────────────────┘
                       │ HTTP/REST
┌──────────────────────┴──────────────────────────────────────┐
│                   Node.js Proxy Server                       │
│                      (Port 3001)                             │
└──────────────────────┬──────────────────────────────────────┘
                       │ Forward/Stream
┌──────────────────────┴──────────────────────────────────────┐
│              Python Flask Server (Port 5001)                 │
│                                                              │
│  ┌────────────────────────────────────────────────────┐    │
│  │            Supervisor Agent                        │    │
│  │  (Coordinates all specialist agents)               │    │
│  └──────┬──────────────────────────────────────┬──────┘    │
│         │                                       │            │
│  ┌──────┴───────┐  ┌──────────────┐  ┌────────┴──────┐    │
│  │  Calendar    │  │   Meeting    │  │    Email      │    │
│  │    Agent     │  │    Agent     │  │    Agent      │    │
│  └──────────────┘  └──────────────┘  └───────────────┘    │
│  ┌──────────────┐  ┌──────────────┐  ┌───────────────┐    │
│  │   Weather    │  │    News      │  │     Task      │    │
│  │    Agent     │  │    Agent     │  │     Agent     │    │
│  └──────────────┘  └──────────────┘  └───────────────┘    │
└────────────────────────────────────────────────────────────┘

🚀 Quick Start

Prerequisites

• Node.js 18+ and npm
• Python 3.9+
• Git

1. Clone Repository

git clone https://github.com/Tanaybaviskar/CoreAI.git
cd CoreAI

2. Backend Setup

Install Python Dependencies

cd backend/agentic

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Configure Environment Variables

# Copy example environment file
cp .env.example .env

# Edit .env and add your API keys
# At minimum, you need:
# - GOOGLE_API_KEY (from Google AI Studio)
# - SERPER_API_KEY (for web search)

Start Python Server

python main.py
# Server will start on http://localhost:5001

3. Node.js Proxy Setup

cd ../../backend

# Install dependencies
npm install

# Start proxy server
node index.js
# Server will start on http://localhost:3001

4. Frontend Setup

cd ../frontend

# Install dependencies
npm install

# Start development server
npm run dev
# Frontend will start on http://localhost:3000

5. Access CoreAI

Open your browser to http://localhost:3000

🔑 API Keys & Integration

Required APIs

1. Google AI API (Required)

   • Get from: https://aistudio.google.com/apikey
   • Used for: AI model (Gemini)

2. Serper API (Required for search)

   • Get from: https://serper.dev
   • Used for: Web search functionality

Optional APIs (for full functionality)

3. Google Calendar API

   • Get from: https://console.cloud.google.com
   • Enable: Google Calendar API
   • Used for: Calendar management

4. Gmail API

   • Get from: https://console.cloud.google.com
   • Enable: Gmail API
   • Used for: Email operations

5. Google Meet API

   • Part of Google Workspace
   • Used for: Meeting creation

6. Weather API

   • Options: OpenWeatherMap, WeatherAPI
   • Get from: https://openweathermap.org/api
   • Used for: Weather information

7. News API

   • Get from: https://newsapi.org
   • Used for: News aggregation

📁 Project Structure

CoreAI/
├── frontend/                      # Next.js Frontend
│   ├── src/
│   │   └── app/
│   │       ├── page.tsx          # Main application
│   │       ├── layout.tsx        # Root layout
│   │       └── globals.css       # Global styles
│   ├── package.json
│   └── tsconfig.json
│
├── backend/                       # Node.js Proxy Server
│   ├── index.js                  # Express server
│   └── package.json
│
└── backend/agentic/              # Python Multi-Agent System
    ├── agents/                   # Agent implementations
    │   ├── base_agent.py        # Base agent class
    │   ├── supervisor.py        # Supervisor coordinator
    │   ├── calendar_agent.py    # Calendar operations
    │   ├── meeting_agent.py     # Meeting management
    │   ├── email_agent.py       # Email handling
    │   ├── task_agent.py        # Task management
    │   ├── info_agents.py       # Weather & News agents
    │   └── __init__.py
    ├── main.py                   # Flask server
    ├── requirements.txt          # Python dependencies
    └── .env.example             # Environment template

💡 Usage Examples

Example 1: Schedule a Meeting

You: "Schedule a meeting for tomorrow at 2 PM"

CoreAI:

1. Calendar Agent checks availability for 2 PM
2. Meeting Agent creates Google Meet link
3. Calendar Agent books the time slot
4. Returns: Meeting link + Calendar confirmation

Example 2: Check Weather & Read Emails

You: "What's the weather like and do I have any new emails?"

CoreAI:

1. Weather Agent fetches current weather
2. Email Agent checks inbox
3. Returns: Weather summary + Email list

Example 3: Task Management

You: "Add a task to review the project proposal"

CoreAI:

1. Task Agent creates new task
2. Returns: Task confirmation with ID

🎨 Frontend Features

Dashboard

• Real-time clock display
• Agent statistics (conversations, active agents, API calls, success rate)
• Recent activity feed
• Interactive stat cards

Chat Interface

• Streaming responses
• Agent identification in messages
• Message history
• Real-time typing indicators

Agents Page

• Live agent status monitoring
• Success rate visualization
• Last action display
• Performance metrics

Connections

• API integration management
• Connection status indicators
• Quick connect/disconnect

Memory

• Long-term memory storage
• Key-value pairs
• Editable entries

Settings

• User profile customization
• AI persona selection
• System configuration
• Data management

🛠️ Technologies

Frontend

• Next.js 15 - React framework
• React 19 - UI library
• TypeScript - Type safety
• Tailwind CSS 4 - Styling

Backend (Python)

• Flask - Web framework
• LangGraph - Agent workflow orchestration
• LangChain - LLM framework
• Google Gemini - AI model

Backend (Node.js)

• Express - Web server
• Axios - HTTP client
• CORS - Cross-origin support

🔒 Security Notes

• Never commit .env files with real API keys
• Use environment variables for all sensitive data
• Implement rate limiting in production
• Add authentication for deployed applications
• Use HTTPS in production

🚢 Deployment

Frontend (Vercel)

cd frontend
vercel deploy

Backend (Railway/Heroku)

# Deploy Python server
cd backend/agentic
# Follow your platform's deployment guide

# Deploy Node proxy
cd ../
# Follow your platform's deployment guide

📊 Performance

• Response Time: < 2s for most operations
• Agent Coordination: Parallel execution where possible
• Streaming: Real-time response streaming
• Caching: Intelligent API response caching

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

• Google AI for Gemini API
• LangChain & LangGraph teams
• Next.js team
• Open source community

📧 Contact

For questions and support, please open an issue on GitHub.

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