https://github.com/mlshukai/pamiq-core
Framework for building AI agents with real-time adaptive learning capabilities.
https://github.com/mlshukai/pamiq-core
adaptive-learning agent ai ami autonomous-agents autonomous-machine-intelligence framework machine machine-learning ml python real-time
Last synced: 10 months ago
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Framework for building AI agents with real-time adaptive learning capabilities.
- Host: GitHub
- URL: https://github.com/mlshukai/pamiq-core
- Owner: MLShukai
- License: mit
- Created: 2024-12-10T05:45:44.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-10T07:53:36.000Z (10 months ago)
- Last Synced: 2025-06-10T08:35:47.275Z (10 months ago)
- Topics: adaptive-learning, agent, ai, ami, autonomous-agents, autonomous-machine-intelligence, framework, machine, machine-learning, ml, python, real-time
- Language: Python
- Homepage: https://mlshukai.github.io/pamiq-core/
- Size: 2.81 MB
- Stars: 10
- Watchers: 2
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# pamiq-core
[](https://pypi.org/project/pamiq-core/)
[](https://www.python.org/downloads/)
[](LICENSE)
[](https://google.github.io/styleguide/pyguide.html#s3.8-comments-and-docstrings)
[](https://github.com/MLShukai/pamiq-core/actions/workflows/test.yml)
[](https://github.com/MLShukai/pamiq-core/actions/workflows/type-check.yml)
[](https://github.com/MLShukai/pamiq-core/actions/workflows/pre-commit.yml)
**pamiq-core** is a framework for building AI agents. Developed for P-AMI\, it enables train and inference in parallel, allowing agents to adapt continuously during interaction with their environment.
## ✨ 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.)
## 📋 Requirements
- Python 3.12+
- PyTorch (optional, for torch integration)
## 🚀 Quick Start
### Installation
```bash
# Install with pip
pip install pamiq-core
# Optional PyTorch integration
pip install pamiq-core[torch]
```
### Basic Example
```python
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](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`:
```bash
# Connect to local system
pamiq-console --host localhost --port 8391
# Connect to remote system
pamiq-console --host 192.168.1.100 --port 8391
```
## 📚 Documentation
For comprehensive API documentation and detailed tutorials, please visit the [documentation website](https://mlshukai.github.io/pamiq-core/).
## 🧩 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](CONTRIBUTING.md) for guidelines on how to contribute to pamiq-core.
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🔗 Related Projects
- [pamiq-recorder](https://github.com/MLShukai/pamiq-recorder): Recording library for P-AMI\
- [pamiq-io](https://github.com/MLShukai/pamiq-io): I/O library for P-AMI\