Agent Control Hub

A centralized hub for multi-agent code creation, enhancement, and deployment using Streamlit UI and FastAPI backend. Build complete applications with AI-powered agents that handle everything from prompt enhancement to deployment.

🚀 Features

• 🤖 Multi-Agent Code Generation: Collaborative AI agents for prompt enhancement, file planning, code generation, testing, and deployment
• 🌐 Language Support: Python, Node.js, React+TypeScript, Three.js, Go, Rust, Java
• 🔧 Virtual Environment Management: Per-project virtual environments with setup automation
• 💻 Modern UI: Streamlit-based web interface with real-time project management
• ⚡ FastAPI Backend: RESTful API with automatic documentation
• 📁 File Generation: Guaranteed file creation with fallback scaffolding
• 🔄 Real-time Monitoring: Live project status and progress tracking
• 📦 One-Click Deployment: Complete project packaging and download

🏗️ Architecture

graph TB
    A[User Input] --> B[Streamlit UI]
    B --> C[FastAPI Backend]
    C --> D[Agent Pipeline]
    D --> E[Prompt Enhancer]
    D --> F[File Planner]
    D --> G[Code Generator]
    D --> H[Environment Setup]
    E --> I[LLM Provider]
    F --> I
    G --> I
    I --> J[Generated Project]
    J --> K[Download/Deploy]

📁 Project Structure

Agent_Control_Hub/
├── src/                    # Main source code
│   ├── llm/               # LLM provider abstraction
│   ├── ui/                # User interface components
│   └── main.py            # Main entry point
├── agents/                # Agent definitions and factory
├── services/              # Business logic services
├── core/                  # Core configuration
├── models/                # Pydantic response models
├── routers/               # FastAPI routers
├── server/                # FastAPI application
├── utils/                 # Utility functions
├── tests/                 # Test files
├── examples/              # Example files
├── config/                # Configuration files
├── docs/                  # Documentation
├── prompts/               # Externalized prompts
├── templates/             # HTML templates
├── workspace/             # Agent workspace
└── logs/                  # Log files

🚀 Quick Start

Prerequisites

• Python 3.8 or higher
• Git

📖 New to Agent Control Hub? Check out our Complete Setup Guide for detailed step-by-step instructions with screenshots!

Installation

1. Clone the repository:

   git clone https://github.com/Dzg0507/AgentHub.git
   cd AgentHub
   

2. Create 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. Set up environment variables:

   # Copy the example environment file
   cp config/env.example .env
   
   # Edit .env with your API keys
   nano .env  # or use your preferred editor
   

   Example .env file:

   # LLM Provider Configuration
   LLM_PROVIDER=gemini
   GOOGLE_API_KEY=your_google_api_key_here
   TOGETHER_API_KEY=your_together_api_key_here
   OPENROUTER_API_KEY=your_openrouter_api_key_here
   LLM_MODEL=gemini-1.5-flash
   

🎯 One-Command Startup (Recommended)

Start everything with one command:

# Quick launcher (recommended)
python run.py both

# Or use the full script
python scripts/start_hub.py

Or use the platform-specific scripts:

• Windows: Double-click scripts/start_hub.bat or run scripts/start_hub.bat
• Unix/Linux/Mac: ./scripts/start_hub.sh

This will automatically:

• ✅ Start the FastAPI server on http://127.0.0.1:8000
• ✅ Start the Streamlit UI on http://localhost:8501
• ✅ Monitor both processes and restart if needed
• ✅ Provide unified shutdown with Ctrl+C

🎨 UI Features

📸 Want to see what it looks like? Check out our Visual Guide with detailed screenshots of every feature!

🏠 Dashboard

• Welcome page with project creation
• Recent projects overview
• Quick start templates

📋 Project Management

• Comprehensive project listing
• Filtering and sorting capabilities
• Real-time status updates
• Project download and management

🏥 Server Status

• Real-time server health monitoring
• Server management controls
• Process monitoring and restart

🛠️ Debug Tools

• Testing and debugging utilities
• Log viewing and analysis
• Error tracking and resolution

🚀 Pipeline Visualization

• Step-by-step process tracking
• Progress indicators
• Real-time status updates

🔌 API Endpoints

Projects

• POST /projects - Create a new project
• GET /projects - List all projects
• GET /projects/{id} - Get project details
• DELETE /projects/{id} - Delete a project
• GET /projects/{id}/download - Download project as ZIP
• GET /projects/{id}/files - List project files
• GET /projects/{id}/logs - Get execution logs
• POST /projects/{id}/retry - Retry project processing
• POST /projects/{id}/force-scaffold - Force create minimal scaffold
• POST /projects/{id}/venv - Create virtual environment
• POST /projects/{id}/setup - Run setup commands

System

• GET / - Root endpoint with server info
• GET /health - Health check
• GET /ui - Built-in web interface
• GET /docs - Interactive API documentation

🌐 Supported Languages

Language	Framework	Package Manager	Status
Python	Standard Library	pip	✅ Full Support
Node.js	Express/Fastify	npm	✅ Full Support
React	TypeScript	npm/yarn	✅ Full Support
Three.js	WebGL	npm	✅ Full Support
Go	Standard Library	go mod	✅ Full Support
Rust	Cargo	cargo	✅ Full Support
Java	Spring Boot	Gradle	✅ Full Support

🔄 Project Workflow

graph LR
    A[User Prompt] --> B[Prompt Enhancement]
    B --> C[File Planning]
    C --> D[Code Generation]
    D --> E[Environment Setup]
    E --> F[Testing]
    F --> G[Deployment]
    G --> H[Download]

1. 📝 Create Project: Submit a prompt describing what you want to build
2. ✨ Prompt Enhancement: AI enhances your prompt with technical requirements
3. 📋 File Planning: AI creates a structured file plan for the project
4. 💻 Code Generation: AI generates complete, runnable code
5. 🔧 Environment Setup: Virtual environment and dependencies are configured
6. 🧪 Testing: Generated code is tested for functionality
7. 🚀 Deployment: Project is packaged and ready for deployment
8. 📦 Download: Get your complete project as a ZIP file

⚙️ Configuration

Environment Variables

Variable	Description	Default	Required
LLM_PROVIDER	LLM provider to use	gemini	Yes
GOOGLE_API_KEY	Google API key for Gemini	-	If using Gemini
TOGETHER_API_KEY	Together.ai API key	-	If using Together
OPENROUTER_API_KEY	OpenRouter API key	-	If using OpenRouter
LLM_MODEL	Model to use	gemini-1.5-flash	No
LLM_API_BASE	Custom API base URL	-	No

Server Configuration

Key configuration options in core/config.py:

• SERVER_HOST and SERVER_PORT: Server binding address
• WORKSPACE_DIR: Directory for generated projects
• TEMP_TTL_MINUTES: Project retention time
• LLM_CONFIG: Language model configuration
• SUPPORTED_LANGUAGES: Available programming languages

🧪 Development

Running Tests

# Run all tests
python -m pytest tests/ -v

# Run specific test categories
python -m pytest tests/test_basic.py -v
python -m pytest tests/test_llm_provider.py -v
python -m pytest tests/test_utils.py -v

# Run with coverage
python -m pytest tests/ --cov=src --cov-report=html

Code Quality

# Format code
black .

# Lint code
flake8 .

# Type checking
mypy src/

Adding New Languages

1. Add language to SUPPORTED_LANGUAGES in core/config.py
2. Update _write_language_scaffold() in services/pipeline.py
3. Add setup commands in setup_project() function
4. Update language selector in streamlit_app.py

Adding New Agents

1. Define agent in agents/factory.py
2. Add agent to the returned dictionary
3. Use agent in pipeline functions in services/pipeline.py

🐛 Troubleshooting

Common Issues

1. Import Errors: Ensure all dependencies are installed and virtual environment is activated
2. API Key Issues: Verify API keys are set in .env file
3. Port Conflicts: Change SERVER_PORT in core/config.py if port 8000 is in use
4. File Generation Failures: Use the "Force Scaffold" button to create minimal files
5. Memory Issues: Reduce TEMP_TTL_MINUTES to clean up old projects

Logs

• Server logs: logs/agent_hub.log
• Project execution logs: Available via /projects/{id}/logs endpoint
• Streamlit logs: Check terminal output
• CI/CD logs: Available in GitHub Actions tab

Getting Help

• 📖 Check the documentation
• 🐛 Report issues on GitHub Issues
• 💬 Start a discussion in GitHub Discussions

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Quick Contribution Steps

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests if applicable
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

Development Setup

# Install development dependencies
pip install -e ".[dev]"

# Run pre-commit hooks
pre-commit install

# Run tests
pytest

# Format code
black .

📄 License

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

🙏 Acknowledgments

• Streamlit for the amazing UI framework
• FastAPI for the high-performance API framework
• Google Gemini for the AI capabilities
• Together.ai for additional AI model access
• OpenRouter for model aggregation

📊 Project Status

• ✅ Core Features: Complete
• ✅ Multi-Language Support: Complete
• ✅ UI/UX: Complete
• ✅ API: Complete
• ✅ Testing: Complete
• ✅ CI/CD: Complete
• 🔄 Documentation: Ongoing
• 🔄 Performance Optimization: Ongoing

🚀 Roadmap

• Plugin System: Extensible agent architecture
• Database Integration: Persistent project storage
• User Authentication: Multi-user support
• Cloud Deployment: One-click cloud deployment
• Advanced Analytics: Project metrics and insights
• Team Collaboration: Real-time collaborative editing

---

#\x00 \x00T\x00e\x00s\x00t\x00 \x00t\x00r\x00i\x00g\x00g\x00e\x00r\x00 \x00 \x00