Machine learning prediction serving
Project description
ServeIt lets you deploy your models to a RESTful API for prediction serving in one line of code. Current features include:
Model prediction serving
Supplementary information endpoint creation
Input validation and exception handling
Configurable request and response logging (work in progress)
Installation: Python 2.7 and Python 3.6
Installation is easy with pip: pip install serveit
Usage:
Deploy your model to a production-quality API with one line of code:
from serveit.sklearn_server import SklearnServer
# provide the server with a model and tell it which
# method to use for predictions
SklearnServer(clf, clf.predict).serve()Then check out your new API:
curl -XPOST 'localhost:5000/predictions'\
-H "Content-Type: application/json"\
-d "[[5.6, 2.9, 3.6, 1.3], [4.4, 2.9, 1.4, 0.2], [5.5, 2.4, 3.8, 1.1], [5.0, 3.4, 1.5, 0.2], [5.7, 2.5, 5.0, 2.0]]"
# [1, 0, 1, 0, 2]Please see the examples directory for additional usage samples.
Supported libraries
Scikit-Learn
Coming soon:
TensorFlow
Keras
PyTorch
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