Welcome to PAMIQ-Core Documentation!¶

PAMIQ-Core is a framework for building AI agents with real-time learning capabilities through parallel training and inference.

✨ 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
🌍 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.)

System Architecture

Installation¶

# Basic installation
pip install pamiq-core

# With PyTorch support
pip install pamiq-core[torch]

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,
    data=your_data_buffers,
    trainers=your_trainers,
    config=LaunchConfig(
        web_api_address=("localhost", 8391),
        max_uptime=300.0,  # 5 minutes
    ),
)

See the samples on GitHub 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

Documentation¶

User Guide: Describes information for working with PAMIQ-Core.
API Reference

Contribution¶

See CONTRIBUTING.md on GitHub