pamiq-core

pamiq-core is a minimal machine learning framework for asynchronous execution of inference and training.

🎯 Design Philosophy

• Simplicity — Clean, intuitive APIs that just work
• Lightweight — Minimal dependencies, maximum performance
• Complete Thread Abstraction — Complex threading handled internally, simple interface externally

When you set out to build a dynamic continuous learning system, PAMIQ Core will be your steadfast foundation.

📚 Documentation site is here.

✨ Features

• 🔄 Parallel Architecture: Simultaneous inference and training in separate threads
• ⚡ Real-time Adaptation: Continuously update models during interaction
• 🧵 Thread-safe Design: Robust synchronization mechanisms for parameter sharing and data transfers
• 🔌 Modular Components: Easy-to-extend agent, environment, and model interfaces
• 🛠️ Comprehensive Tools: Built-in state persistence, time control, and monitoring
• 🏋️ Gymnasium Integration: Seamless compatibility with Gymnasium environments
• 🌍 Cross Platform: Linux is the primary focus, but Windows and macOS are also supported. (However, some older macOS and Windows systems may have significantly less accurate time control.)

📋 Requirements

• Python 3.12+
• PyTorch (optional, for torch integration)

🚀 Quick Start

Installation

# Install with pip
pip install pamiq-core

# Optional PyTorch integration
pip install pamiq-core[torch]

# Optional Gymnasium integration
pip install pamiq-core[gym]

Basic Example

from pamiq_core import launch, Interaction, LaunchConfig
from your_agent import YourAgent
from your_environment import YourEnvironment

# Create agent-environment interaction
interaction = Interaction(YourAgent(), YourEnvironment())

# Launch the system
launch(
    interaction=interaction,
    models=your_models,
    buffers=your_data_buffers,
    trainers=your_trainers,
    config=LaunchConfig(
        web_api_address=("localhost", 8391),
        max_uptime=300.0,  # 5 minutes
    ),
)

See the samples directory for complete examples.

Remote CLI Control

Once the system is running, you can connect and control it remotely via the terminal using pamiq-console:

# Connect to local system
pamiq-console --host localhost --port 8391

# Connect to remote system
pamiq-console --host 192.168.1.100 --port 8391

🧩 Architecture

pamiq-core implements a unique architecture that enables autonomous intelligence:

1. Concurrent Threads: Separate threads for control, inference, and training
2. Parameter Sharing: Thread-safe model parameter synchronization
3. Experience Collection: Automatic buffering of data from environments, such as images and audio.
4. Continuous Learning: Training models while simultaneously using them for decision making
5. State Persistence: Saving and loading system state for resumable operation

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines on how to contribute to pamiq-core.

📄 License

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

🔗 Related Projects

• pamiq-recorder: Recording library for P-AMI<Q>
• pamiq-io: I/O library for P-AMI<Q>