AI Agent Management Platform

A fullstack application that creates and manages AI agents to handle tasks and jobs delegated by users. The platform features a secretary agent that determines task delegation and a hiring manager agent that creates new specialized agents when needed.

🏗️ Architecture

• Backend: FastAPI (Python) with RESTful APIs
• Frontend: Next.js 14 with TypeScript, Tailwind CSS, and shadcn/ui
• AI Integration: Ready for OpenAI/LangChain integration
• Database: PostgreSQL (configured, not yet implemented)
• Caching: Redis (configured, not yet implemented)

Features

Current Implementation

• Dashboard: Modern UI with agent and task overview
• Chat Interface: Interactive chatbot for task delegation
• Agent Management: View and manage AI agents in your workspace
• Task Tracking: Monitor task status and assignments
• Responsive Design: Mobile-friendly interface

Planned Features

• AI-powered task analysis and delegation
• Dynamic agent creation based on task requirements
• Real-time task updates
• Agent performance analytics
• Multi-user workspaces

🛠️ Tech Stack

Backend

• FastAPI: Modern, fast web framework for APIs
• Pydantic: Data validation and serialization
• SQLAlchemy: Database ORM (ready for implementation)
• Alembic: Database migrations
• Redis: Caching and task queues
• OpenAI/LangChain: AI integration

Frontend

• Next.js 14: React framework with App Router
• TypeScript: Type safety and better development experience
• Tailwind CSS: Utility-first CSS framework
• shadcn/ui: High-quality UI components
• Lucide React: Beautiful icons

📦 Project Structure

shellhacks25/
├── backend/
│   ├── main.py              # FastAPI application
│   ├── requirements.txt     # Python dependencies
│   └── env.example         # Environment variables template
├── frontend/
│   ├── src/
│   │   ├── app/            # Next.js App Router
│   │   └── components/     # React components
│   │       ├── Dashboard.tsx
│   │       ├── ChatBot.tsx
│   │       ├── AgentsList.tsx
│   │       └── TasksList.tsx
│   ├── components.json     # shadcn/ui configuration
│   └── package.json
└── README.md

Getting Started

Prerequisites

• Python 3.8+
• Node.js 18+
• npm or yarn

Backend Setup

1. Navigate to the backend directory:

cd backend

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Create environment file:

cp env.example .env
# Edit .env with your configuration

5. Start the FastAPI server:

python main.py
# Or use uvicorn directly:
# uvicorn main:app --reload

The API will be available at http://localhost:8000 API documentation: http://localhost:8000/docs

Frontend Setup

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start the development server:

npm run dev

The application will be available at http://localhost:3000

🔌 API Endpoints

Agents

• GET /agents - Get all agents
• POST /agents - Create a new agent
• GET /agents/{agent_id} - Get specific agent

Tasks

• GET /tasks - Get all tasks
• POST /tasks - Create a new task

Chat

• POST /chat - Send message to secretary agent

Health

• GET /health - Health check endpoint

🤖 Default Agents

The platform comes with two pre-configured agents:

1. Executive Secretary (secretary-001)

   • Role: Secretary
   • Capabilities: Task delegation, communication, scheduling
   • Purpose: Main interface for users, handles task analysis and delegation

2. Hiring Manager (hiring-manager-001)

   • Role: Hiring Manager
   • Capabilities: Agent creation, skill assessment, recruitment
   • Purpose: Creates new specialized agents when existing ones can't handle tasks

Workflow Example

1. User sends a message: "I need to analyze our sales data and create a report"
2. Secretary Agent receives the message and analyzes the task
3. Secretary checks if any existing agent can handle data analysis and reporting
4. If no suitable agent exists, Secretary delegates to Hiring Manager
5. Hiring Manager creates a new "Data Analyst" agent with required capabilities
6. New Agent is assigned the task and begins work

🔧 Development

Adding New Components

The project uses shadcn/ui components. To add new components:

cd frontend
npx shadcn@latest add [component-name]

Database Setup (Future)

When ready to implement persistent storage:

1. Set up PostgreSQL
2. Update DATABASE_URL in .env
3. Create database models
4. Run migrations with Alembic

AI Integration (Future)

To integrate with AI services:

1. Add OpenAI API key to .env
2. Implement agent logic in backend
3. Connect to LangChain for advanced workflows

🤝 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 licensed under the MIT License.

🎉 Acknowledgments

• Built for ShellHacks 2025
• Uses shadcn/ui for beautiful components
• Powered by FastAPI and Next.js