Transform how you conduct research with AI agents that collaborate, debate, and deliver insights beyond traditional AI capabilities.

Agent Force is a cutting-edge AI research platform that orchestrates multiple specialized AI agents to conduct comprehensive market research, competitive analysis, and strategic business insights in real-time. Built on the revolutionary Coral Protocol, our platform creates a "Society of AI Agents" that collaborate, communicate securely, and scale their efforts across different frameworks.

• 🤝 Multi-Agent Collaboration - Specialized AI agents work together seamlessly
• ⚡ Real-Time Streaming - Watch agents collaborate live through WebSocket streaming
• 🛡️ Enterprise Security - JWT authentication with enterprise-grade security
• 🎨 Modern UI/UX - Beautiful React interface with dark theme and animations
• 🔧 Coral Protocol Integration - Agent communication and orchestration infrastructure
• 📊 Comprehensive Reports - Executive summaries, strategic insights, and data-driven conclusions
• 🔄 LangGraph Orchestration - Advanced workflow management for complex agent interactions
• 📱 Responsive Design - Works perfectly on desktop and mobile devices

• Market Research - Deep market analysis and competitive landscape insights
• Business Strategy - Strategic recommendations and growth opportunities
• Innovation Research - Emerging trends and future predictions
• Competitive Intelligence - Competitor strategies and market positioning
• Industry Analysis - Comprehensive sector overviews and trend analysis

• React 18 - Modern JavaScript framework
• TypeScript - Type-safe development
• Vite - Fast build tool and dev server
• Tailwind CSS - Utility-first CSS framework
• Radix UI - Accessible component primitives
• React Query - Powerful data fetching
• React Router - Client-side routing
• Lucide Icons - Beautiful icon set

• FastAPI - High-performance async web framework
• LangGraph - Multi-agent orchestration and workflows
• SQLAlchemy - Modern ORM with async support
• PostgreSQL - Robust database for data persistence
• JWT Authentication - Secure token-based auth
• WebSockets - Real-time streaming capabilities
• Coral Protocol - Agent communication infrastructure

• OpenAI GPT-4 - Primary LLM for agent intelligence
• LangChain - LLM integration and prompt management
• MCP (Model Context Protocol) - Agent tooling standard
• Custom Agent Architectures - Specialized research agents

• Python 3.13+
• Node.js 18+
• PostgreSQL 15+
• Docker (optional, for containerized deployment)

1. Clone the repository

   git clone https://github.com/yourusername/agent-force.git
   cd agent-force

2. Backend Setup

   # Navigate to backend
   cd MultiAgents_Workflow
   
   # Install Python dependencies
   poetry install
   
   # Set up environment variables
   cp .env.example .env
   # Edit .env with your API keys and database URL
   
   # Run database migrations
   poetry run alembic upgrade head
   
   # Start the backend server
   poetry run uvicorn core.main:app --reload --host 0.0.0.0 --port 8000

3. Frontend Setup

   # Navigate to frontend (in new terminal)
   cd ../Frontend
   
   # Install Node dependencies
   npm install
   
   # Start the development server
   npm run dev

4. Database Setup

   # Create PostgreSQL database
   createdb agentforce_db
   
   # Or use Docker
   docker run --name agentforce-postgres -e POSTGRES_PASSWORD=password -p 5432:5432 -d postgres:15

Create a .env file in the MultiAgents_Workflow directory:

# Database
DATABASE_URL=postgresql://user:password@localhost:5432/agentforce_db

# Authentication
SECRET_KEY=your-secret-key-here
ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30

# OpenAI
AIML_API_KEY=your-openai-api-key

# Coral Protocol (optional)
CORAL_SERVER_URL=http://localhost:5555

# Environment
ENVIRONMENT=development
DEBUG=True

1. Access the Application

   • Frontend: http://localhost:5173 (Built With Lovable)
   • Backend API: http://localhost:8000
   • API Documentation: http://localhost:8000/docs

2. Create an Account

   • Sign up with email and password
   • Verify your email (if configured)

3. Start Research

   • Enter your research topic
   • Choose number of analysts (2-5 recommended)
   • Click "Start Research"
   • Watch agents collaborate in real-time

4. View Results

   • Comprehensive reports with executive summaries
   • Strategic recommendations and insights
   • Download reports in multiple formats

# Build and run with Docker Compose
docker-compose up --build

# Or run individual services
docker build -t agentforce-backend ./MultiAgents_Workflow
docker build -t agentforce-frontend ./Frontend

• POST /auth/login - User authentication
• POST /auth/register - User registration
• GET /auth/me - Get current user profile
• POST /api/v1/run-research - Initiate research session
• GET /api/v1/research-stream - Real-time research streaming
• GET /api/v1/user-sessions - Get user research history

• start - Research session initialized
• event - Agent activity updates
• complete - Research completion with results
• error - Error handling and notifications

We welcome contributions! Here's how you can help:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and add tests
4. Run the test suite: npm test && poetry run pytest
5. Commit your changes: git commit -m 'Add amazing feature'
6. Push to the branch: git push origin feature/amazing-feature
7. Open a Pull Request

• Code Style: Follow PEP 8 for Python, ESLint for JavaScript
• Testing: Add tests for new features
• Documentation: Update docs for API changes
• Commits: Use conventional commit format

agent-force/
├── Frontend/                 # React TypeScript frontend
│   ├── src/
│   │   ├── components/       # Reusable UI components
│   │   ├── pages/           # Page components
│   │   ├── contexts/        # React contexts
│   │   └── api/             # API client code
│   └── package.json
├── MultiAgents_Workflow/     # FastAPI backend
│   ├── core/                 # Core application code
│   │   ├── routes/          # API route handlers
│   │   ├── models.py        # Database models
│   │   └── main.py          # FastAPI app
│   ├── agents/              # AI agent implementations
│   │   ├── ResearchAgent/   # Research agent logic
│   │   └── ReportAgent/     # Report generation agent
│   └── pyproject.toml
├── coral-server/            # Coral Protocol server
├── docker-compose.yml       # Docker orchestration
└── README.md

This project is licensed under the MIT License - see the LICENSE file for details.

• Coral Protocol - Revolutionary agent communication infrastructure
• LangGraph - Powerful multi-agent orchestration framework
• FastAPI - Incredible async web framework
• React - Best frontend framework ever
• AIML API - Cutting-edge language models

If you find Agent Force helpful, please give us a ⭐ on GitHub!