Bentoml

Latest version: v1.2.19

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0.4.7

* Fixed an issue where SQLAlchemy alembic files are not found in PyPI distribution
* Fixed an issue with SQLAlchemy alembic overwriting BentoML default logging configuration

0.4.5

* Improved BentoML module import time by around 3-4x
* List deployments command now shows "age" column denoting how long the deployment has been created
* Fixed a bug where serverless deployment failed to install required plugins

Docs:
* Updated documentation site https://bentoml.readthedocs.io/

0.4.4

New Features:
* Support for both Keras and tensorflow.keras module in KerasModelArtifact
* New serialization option for KerasModelArtifact that stores model in json and weights files (by ghunkins )
* `bentoml list deployments` provides clean table outputs now
* Support for AWS S3 based BentoML repository (Beta)

Bug fixes:
* Fixed error with old click version 335
* Fixed REST API Server issue on Windows platform 333

0.4.3

* Enhancement to Serverless deployment and SageMaker deployment
* Updated default version string format for user-defined BentoService
* Added the `versioneer` interface on BentoService for users to define a customized versioning format
* Added '--force' option to `bentoml deployment delete` command
* Updated clipper base image to 0.4.1

For BentoML developers:
* BentoML now packages local BentoML dev branch when bundling a BentoService for deployment

0.4.2

* Introduced SklearnModelArtifact, adding more scikit-learn specific optimizations over previous general PickleArtifact
* Fixed a number of issues with AWS Lambda Serverless deployment
* Improved error message and CLI outputs of AWS SageMaker deployment

0.4.1

* Fixed an issue with initializing BentoML logging and repository file direcotry

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