mlsentinel 0.1.2.dev1

Python SDK for monitoring and validating Machine Learning models.

MLSentinel

MLSentinel is a Python SDK for monitoring, validating, and analyzing Machine Learning models.

🚧 Developer Preview

MLSentinel is currently under active development. This release provides the SDK architecture, validation system, data models, and transport layer. Backend integration and AI-powered analysis will be added in future releases.

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Features

• Clean Python SDK
• Input validation
• Report data models
• HTTP transport layer
• Simple developer API
• Lightweight and easy to integrate

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Reference

Check out the PyPi Readme for verification!1

Installation

pip install mlsentinel

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Quick Start

from mlsentinel import MLDoc

doctor = MLDoc("YOUR_API_KEY")

doctor.doc_report(
    project="Spam Detector",
    model="Random Forest",
    metrics={
        "accuracy": 0.95,
        "precision": 0.94,
        "recall": 0.93,
        "f1_score": 0.935,
        "val_loss": 0.18
    }
)

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Current SDK Architecture

Developer
      │
      ▼
MLDoc
      │
      ▼
Validators
      │
      ▼
Report Model
      │
      ▼
Transport
      │
      ▼
MLSentinel Backend (Coming Soon)

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Project Structure

src/
└── mlsentinel/
    ├── __init__.py
    ├── client.py
    ├── config.py
    ├── exceptions.py
    ├── models.py
    ├── transport.py
    ├── validators.py
    └── version.py

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Roadmap

• ✅ SDK Foundation
• ✅ Validation Engine
• ✅ Transport Layer
• ⏳ Backend API
• ⏳ AI Analysis Engine
• ⏳ Dashboard
• ⏳ Web Platform

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Requirements

• Python 3.9+
• requests

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Author

Adari Narasimha Dhoni

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License

This project is licensed under the MIT License.