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Model Jacket

Model Jacket is a lightweight framework that wraps any ML model with a FastAPI server, Docker image, Prometheus metrics, and Kubernetes Helm chart—so you can go from model file ➜ production endpoint in minutes.

Quick Start

pip install -e .
# Train or load a model and save as TorchScript
python export_model.py  # produces model.pt

jacket build --framework torch --model-path model.pt --tag v1

docker run -p 8000:8000 model-jacket:v1
curl -X POST http://localhost:8000/predict -H "Content-Type: application/json" -d '{"input_data": [[1,2,3]]}'

Features

  • 🔌 Framework‑agnostic (Torch & ONNX out of the box)
  • 🐳 One‑command containerization via jacket build
  • Low‑latency FastAPI server with async I/O
  • 📈 Built‑in Prometheus metrics and /healthz endpoint
  • ☸️ Production-ready Helm chart with HPA
  • 🛡️ CI/CD GitHub Action for automatic build & deploy

Feel free to star ⭐, fork 🔱, and contribute! :rocket:

Release files for model-jacket 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for model-jacket 0.2.0
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model_jacket-0.2.0.tar.gz 3.3 kB Details

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Table of built distributions (wheels) for model-jacket 0.2.0
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model_jacket-0.2.0-py3-none-any.whl Python 3 none any Details

Total release size: 7.1 kB

Release files / model_jacket-0.2.0.tar.gz

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Size 3.3 kB
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Release files / model_jacket-0.2.0-py3-none-any.whl

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Size 3.8 kB
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0.2.0 This release

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