🚀 Warp Engine - Universal Agent Protocol

Warp Engine is a production-ready, server-based AI agent factory that runs as a persistent service. Create specialized AI agents through natural language commands, with zero manual coding required.

🎯 Core Features

• 🔄 Server-Based Architecture: Persistent daemon with REST API
• 🤖 Agent Factory: Create specialized agents via natural language
• ⚡ Real-Time Processing: WebSocket updates and async job queues
• 🛠️ Production Ready: Docker, health checks, and monitoring
• 🔌 API Integration: REST, WebSocket, and Python client libraries
• 📊 Monitoring: Comprehensive logging and metrics

✨ Features

🤖 Universal Agent Registry

• Single source of truth for all agents
• REST API and CLI access
• Version control and lifecycle management
• Agent templates for common use cases

🏗️ Agent Builder Protocol

• Interactive agent creation via /new-agent command
• Pre-built templates: Research, Code Generation, Data Analysis
• Three-agent workflow pattern: Plan → Execute → Refine
• Automatic code generation, testing, and deployment

🔌 Warp Terminal Integration

• Native integration with Warp's AI features
• Model Context Protocol (MCP) support
• Agent profiles and permissions
• Warp Drive knowledge persistence
• Multi-agent orchestration

🎯 Key Capabilities

• Zero-code agent creation - Build agents through prompts
• Production-ready output - Generated agents include tests and documentation
• Extensible toolkit system - Add custom agent types and capabilities
• OpenAI integration - Powered by GPT-4 and other models
• Local execution - All processing happens on your machine

🚀 Quick Start

Prerequisites

• Python 3.10+
• Warp Terminal (optional but recommended)
• OpenAI API key

Installation

1. Clone the repository:

git clone https://github.com/yourusername/warp-engine.git
cd warp-engine

2. Run the launcher:

./warp-engine

The launcher will:

• Create a virtual environment
• Install dependencies
• Set up configuration
• Launch the interactive menu

3. Configure your API key:

cp env.example .env
# Edit .env and add your OPENAI_API_KEY

📖 Usage

Interactive Mode (Recommended)

Run the launcher for an interactive experience:

./warp-engine

This provides a menu-driven interface with options to:

• Create new agents
• List and run existing agents
• Start the web server
• Access the agent registry

Command Line Interface

Create a New Agent

Interactive mode with templates:

warp-engine new-agent --enhanced

This will present you with agent templates:

1. 🔬 Research Agent - Deep research with multi-page output
2. 💻 Code Generator - Production-ready code with tests
3. 📊 Data Analyst - Data analysis and insights
4. 🎨 Custom Agent - Build from scratch

Non-interactive mode:

warp-engine new-agent \
  --name "Linux Research" \
  --description "Expert Linux system analysis" \
  --plan-prompt "Create a research plan..." \
  --exec-prompt "Execute the research..." \
  --refine-prompt "Polish the output..."

Run an Agent

# List available agents
warp-engine agent list

# Run a specific agent
warp-engine agent run --name research_agent

# Or use the generated binary
./bin/research_agent

Start the Web Server

warp-engine serve --port 8787 --open-browser

Access the UI at http://localhost:8787

API Access

Get Agent Registry

curl http://localhost:8787/api/agents

Create Agent via API

curl -X POST http://localhost:8787/api/agents \
  -H 'Content-Type: application/json' \
  -d '{
    "name": "API Agent",
    "description": "Agent created via API",
    "prompts": {
      "plan": "Plan the task",
      "execute": "Execute the plan",
      "refine": "Refine the output"
    }
  }'

🏗️ Architecture

Directory Structure

warp-engine/
├── config.api.json          # Universal configuration
├── data/
│   ├── registry.json        # Agent registry
│   ├── knowledge/           # Warp Drive cache
│   └── logs/                # Execution logs
├── src/warpengine/
│   ├── agents/              # Generated agents
│   ├── toolkits/            # Agent toolkits
│   ├── warp_integration/    # Warp terminal integration
│   ├── api/                 # API clients (OpenAI, etc.)
│   ├── orchestrator/        # Agent workflow engine
│   └── registry/            # Registry management
├── bin/                     # Executable agent shims
└── tests/                   # Test suite

Agent Lifecycle

Create → Build → Test → Deploy → Monitor → Terminate

1. Create: Define agent via templates or custom prompts
2. Build: Generate code and dependencies
3. Test: Run automated tests
4. Deploy: Create executable and register
5. Monitor: Track usage and performance
6. Terminate: Clean shutdown and resource cleanup

🛠️ Configuration

Environment Variables

Create a .env file with:

# Required
OPENAI_API_KEY=your-api-key-here

# Optional
WARP_ENGINE_HOST=127.0.0.1
WARP_ENGINE_PORT=8787
WARP_ENGINE_MODEL_PLAN=gpt-4-turbo-preview
WARP_ENGINE_MODEL_EXECUTE=gpt-4-turbo-preview
WARP_ENGINE_MODEL_REFINE=gpt-4-turbo-preview

config.api.json

The main configuration file supports:

• Agent templates
• Toolkit definitions
• Model preferences
• Warp integration settings
• Lifecycle configuration

🧪 Testing

Run the test suite:

pytest tests/ -v

Test a specific agent:

pytest src/warpengine/agents/research_agent/test_research_agent.py

🔧 Advanced Features

Custom Agent Toolkits

Create specialized toolkits by extending base templates:

# src/warpengine/toolkits/security_audit.py
from warpengine.agent_builder import AgentTemplate, AgentType

class SecurityAuditToolkit(AgentTemplate):
    name = "Security Audit Agent"
    type = AgentType.CUSTOM
    capabilities = ["vulnerability_scanning", "code_analysis", "report_generation"]
    # ... additional configuration

Warp Terminal Integration

When Warp is installed, the engine automatically:

• Creates agent profiles
• Generates workflows
• Enables voice commands
• Syncs with Warp Drive

Multi-Agent Orchestration

Agents can spawn and coordinate with sub-agents:

# In your agent code
sub_agent_result = run_agent("research_agent", context={"topic": "Linux kernel"})

📚 Examples

Research Agent Example

$ warp-engine new-agent --enhanced
# Select: Research Agent
# Name: Linux Expert

$ echo "Analyze Linux kernel memory management" | ./bin/linux_expert

# Output: Multi-page report with:
# - Executive Summary
# - Technical Analysis
# - Performance Metrics
# - Recommendations
# - References

Code Generator Example

$ warp-engine agent run --name code_generator
# Input: "Create a REST API for user management with authentication"

# Output: Complete API with:
# - FastAPI application
# - User models
# - Authentication middleware
# - Unit tests
# - OpenAPI documentation

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

📄 License

MIT License - see LICENSE for details.

🔗 Links

• Warp Terminal
• OpenAI API
• Documentation
• Issues

🙏 Acknowledgments

Built with ❤️ using:

• Warp Terminal for terminal integration
• OpenAI for AI capabilities
• FastAPI for the web framework
• Rich for beautiful terminal output

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Note: Remember to keep your API keys secure and never commit them to version control!