RegenNexus UAP

Universal Adapter Protocol - Connect devices, robots, apps, and AI agents with minimal latency and maximum security. MCP-compatible for seamless AI integration.

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Installation

pip install regennexus

Or with all features:

pip install regennexus[full]

Quick Start

import asyncio
from regennexus import RegenNexusProtocol

async def main():
    protocol = RegenNexusProtocol()
    await protocol.initialize()

    # Register entities
    await protocol.registry.register_entity(
        entity_id="sensor_01",
        entity_type="device",
        capabilities=["temperature", "humidity"]
    )

    # Send messages
    await protocol.send_message(
        sender="controller",
        recipient="sensor_01",
        intent="read",
        payload={"sensors": ["temperature"]}
    )

    await protocol.shutdown()

asyncio.run(main())

Features

Device Support

Raspberry Pi - GPIO, PWM, camera, sensors
Arduino - Digital/analog I/O, serial commands
NVIDIA Jetson - GPU, CUDA, camera, inference
IoT Devices - MQTT, HTTP, CoAP protocols

Robotic Arms

Amber B1 - 7-DOF control, gripper, trajectory
Lucid One - Cartesian control, force sensing, teach mode

from regennexus.plugins import get_amber_b1_plugin

AmberB1 = get_amber_b1_plugin()
arm = AmberB1(entity_id="arm_001", mock_mode=True)
await arm.initialize()

# Move joints
await arm.move_to([0, 45, -30, 0, 90, 0, 0], duration=2.0)

# Gripper control
await arm.open_gripper()
await arm.close_gripper(force=15.0)

Transport Layers

Transport	Latency	Use Case
IPC	< 0.1ms	Local processes
UDP Multicast	1-5ms	LAN discovery
WebSocket	10-50ms	Remote/internet
Message Queue	Variable	Reliable delivery

Security

Encryption: AES-128/256-GCM
Key Exchange: ECDH-384
Authentication: Tokens, API keys
Rate Limiting: Adaptive throttling

AI Integration (MCP)

Control hardware directly from Claude Desktop or any MCP-compatible AI:

# Start MCP server for Claude Desktop
python -m regennexus.mcp_server

Configure in claude_desktop_config.json:

{
    "mcpServers": {
        "regennexus": {
            "command": "python",
            "args": ["-m", "regennexus.mcp_server"]
        }
    }
}

Now ask Claude:

"Move the robot arm to pick position"
"Turn on GPIO pin 17"
"What's the temperature sensor reading?"

LLM Bridge (Ollama, LM Studio)

Connect local LLMs to hardware:

from regennexus.bridges import LLMBridge, LLMConfig

llm = LLMBridge(LLMConfig(provider="ollama", model="llama3"))
response = await llm.chat("Turn on the lights")

Mesh Networking

Auto-discovery across devices on the network:

from regennexus.core import MeshNetwork, MeshConfig

mesh = MeshNetwork(MeshConfig(
    node_id="controller",
    capabilities=["command"]
))
await mesh.start()

# Devices auto-discovered
for peer in mesh.get_peers():
    print(f"Found: {peer.node_id} ({peer.capabilities})")

Interactive Demos

Try RegenNexus in Google Colab:

Basic Demo - Core communication
Security Demo - Encryption & auth

CLI Usage

# Start server
regen server --host 0.0.0.0 --port 8080

# Run example
regen run examples/robotic_arms/arm_demo.py

# Version info
regen version

Optional Dependencies

pip install regennexus[api]        # FastAPI server
pip install regennexus[mqtt]       # MQTT support
pip install regennexus[robotics]   # Robotic arms
pip install regennexus[arduino]    # Arduino support
pip install regennexus[dev]        # Development tools

Documentation

Examples

examples/
├── simple_connection/    # Basic protocol usage
├── mcp_integration/      # Claude Desktop & LLM demos
├── mesh_network/         # Device auto-discovery
├── llm_integration/      # Ollama/LM Studio demos
├── robotic_arms/         # Amber B1 & Lucid One demos
├── ros_integration/      # ROS 2 bridge examples
├── security/             # Encryption & auth
└── binder/               # Jupyter notebooks

Docker

docker-compose up

See Docker Deployment for details.

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

License

MIT License - see LICENSE for details.

RegenNexus UAP - Connect Everything, Securely.

ReGenNexus UAP