fluxhive 0.1.0

FlowHive User Server Agent

FlowHive Agent

User Server Agent - The compute node component of FlowHive distributed GPU task scheduling platform

Overview

FlowHive Agent is the compute node component that runs on GPU servers. It connects to the Control Server via WebSocket and handles:

• Node Registration & Heartbeat: Automatically registers with Control Server and maintains connection health
• Task Execution: Receives and executes tasks (Python scripts, shell commands, distributed training jobs)
• GPU Monitoring: Real-time GPU metrics collection (utilization, memory, processes) via NVML
• Log Streaming: Streams stdout/stderr logs back to Control Server in real-time
• Resource Management: Intelligent task scheduling based on GPU memory availability and priorities

Directory Structure

agent/
├── fluxhive/
│   ├── core/              # Core agent logic
│   │   ├── task.py        # Task models and state machine
│   │   ├── executor.py    # Task execution engine (subprocess, torchrun)
│   │   ├── task_manager.py # Task scheduler and manager
│   │   └── gpu_monitor.py # GPU monitoring via NVML
│   ├── cli/               # Command-line interface
│   │   └── fluxhive.py    # Main CLI entry point
│   └── __init__.py
├── scripts/               # Demo and testing scripts
│   ├── demo_task_manager.py
│   └── demo_shell_test.py
├── tests/                 # Pytest test cases
├── pyproject.toml         # Package configuration
├── requirements.txt       # Python dependencies
└── README.md

Installation

Option 1: Install from PyPI (Recommended)

pip install fluxhive

Option 2: Install from Source

# Clone the repository
git clone https://github.com/Dramwig/FlowHive.git
cd FlowHive/agent

# Create virtual environment
python -m venv

# Activate virtual environment
# On Windows:
.venv\Scripts\activate
# On Linux/macOS:
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Install in development mode
pip install -e .

Requirements

• Python 3.10 or higher
• NVIDIA GPU with CUDA drivers (for GPU monitoring)
• Operating System: Linux, Windows, or macOS

Quick Start

1. Configure Agent

After installation, configure the agent to connect to your Control Server:

# Set user credentials
fluxhive config user.username "your-username"
fluxhive config user.email "[e-mail]"
fluxhive config user.password "your-password"

# Set Control Server URL
fluxhive config control_base_url "http://127.0.0.1:8001"

# Set agent label (optional, for identification)
fluxhive config label "gpu-server-01"

# Verify configuration
fluxhive config

2. Start Agent

fluxhive run

The agent will:

• Automatically register with the Control Server
• Start GPU monitoring (if NVIDIA GPU is available)
• Begin listening for task assignments
• Send periodic heartbeats

3. Test Locally (Without Control Server)

For quick testing of task execution without a Control Server:

cd agent
python scripts/demo_task_manager.py

Run custom commands:

python scripts/demo_task_manager.py "python -c \"print('Hello FlowHive!')\"" --timeout 10

Logs will be saved to .agent_logs/ directory.

Configuration

WebSocket Connection

The agent communicates with Control Server via WebSocket. The protocol is automatically determined from the control_base_url:

• http:// → ws:// (Plain WebSocket)
• https:// → wss:// (Secure WebSocket, recommended for production)

Production Configuration Example

# Use HTTPS/WSS for secure communication (recommended)
fluxhive config control_base_url "https://your-control-server.com"
fluxhive config user.username "prod-user"
fluxhive config user.password "secure-password"
fluxhive config label "prod-gpu-node-01"

Configuration File Location

Configuration is stored in:

• Linux/macOS: ~/.config/fluxhive/config.toml
• Windows: %USERPROFILE%\.config\fluxhive\config.toml

Environment Variables

You can also use environment variables (they override config file):

export FLOWHIVE_CONTROL_URL="http://127.0.0.1:8001"
export FLOWHIVE_USERNAME="your-username"
export FLOWHIVE_PASSWORD="your-password"
fluxhive run

Key Features

GPU Monitoring

• Real-time Metrics: GPU utilization, memory usage, temperature, power consumption
• Process Tracking: Per-process GPU memory allocation
• NVML Integration: Direct access to NVIDIA Management Library
• Multi-GPU Support: Automatic detection and monitoring of all available GPUs

Task Scheduling

• Memory-Aware Scheduling: Tasks scheduled based on available GPU memory
• Priority Queue: Support for task priorities and fair scheduling
• Concurrent Execution: Multiple tasks can run simultaneously if resources allow
• Retry Mechanism: Automatic retry for failed tasks with configurable policies

Task Execution

• Multiple Executors: Support for subprocess, torchrun, and shell commands
• Environment Variables: Inject custom environment variables per task
• Container Support: Execute tasks in containerized environments
• Distributed Training: Native support for PyTorch distributed training via torchrun

Reliability

• OOM Recovery: Automatic detection and handling of out-of-memory errors
• Heartbeat Service: Periodic health checks (1-5s interval) with Control Server
• Graceful Shutdown: Proper cleanup of running tasks on agent shutdown
• Log Streaming: Real-time stdout/stderr streaming to Control Server

Architecture

┌─────────────────────────────────────────────────────────────┐
│                      FlowHive Agent                         │
├─────────────────────────────────────────────────────────────┤
│  ┌──────────────┐   ┌──────────────┐   ┌─────────────────┐  │
│  │   CLI Tool   │   │ Task Manager │   │  GPU Monitor    │  │
│  │  (fluxhive)  │   │              │   │   (NVML)        │  │
│  └──────┬───────┘   └──────┬───────┘   └────────┬────────┘  │
│         │                  │                    │           │
│         └──────────────────┼────────────────────┘           │
│                            │                                │
│                   ┌────────▼────────┐                       │
│                   │  WebSocket      │                       │
│                   │  Client         │                       │
│                   └────────┬────────┘                       │
└────────────────────────────┼────────────────────────────────┘
                             │
                             │ ws:// or wss://
                             │
                   ┌─────────▼──────────┐
                   │  Control Server    │
                   │  (FastAPI + WS)    │
                   └────────────────────┘

CLI Commands

# Configuration management
fluxhive config                          # Show all configuration
fluxhive config <key> <value>            # Set configuration value
fluxhive config <key>                    # Get configuration value

# Run agent
fluxhive run                             # Start agent and connect to Control Server

# Examples
fluxhive config user.username "alice"
fluxhive config control_base_url "https://control.example.com"
fluxhive run

Development

Running Tests

# Install test dependencies
pip install pytest pytest-asyncio

# Run all tests
pytest tests/

# Run specific test
pytest tests/test_task_manager.py

# Run with coverage
pytest --cov=fluxhive tests/

Building Package

# Install build tools
pip install build twine

# Build distribution
python -m build

# Upload to PyPI (maintainers only)
twine upload dist/*

License

This Agent component is licensed under the FlowHive Agent Non-Commercial Copyleft License v1.0. See LICENSE for details.

License Highlights

• ✅ Open Source: You may view, modify, and distribute the source code
• ❌ Non-Commercial: Commercial use is prohibited (separate commercial license required)
• 🔒 Copyleft: Modifications and derivative works must remain open source; closed-source distribution is prohibited
• 📋 Copyleft Mechanism: Similar to Linux's GPL license, ensuring code remains open source

Note: This applies only to the Agent component. The Control Server and Web Client are proprietary software and not covered by this license.

---

Made with ❤️ by the FlowHive Team