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Update Documentation site (#349)

* cleanup setup.py extra dependencies list

* Update index.rst

* Update quickstart.rst

* Update README.md
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parano committed Oct 17, 2019
1 parent 15ec096 commit 9809f64907d8ea9971c148b5b33021e9b790096c
@@ -50,8 +50,9 @@ class IrisClassifier(bentoml.BentoService):
return self.artifacts.model.predict(df)
```

Train a classifier model and pack it with the prediction service
`IrisClassifier` defined above:
Train a classifier model with default Iris dataset and pack the trained model
with the BentoService `IrisClassifier` defined above:

```python
from sklearn import svm
from sklearn import datasets
@@ -65,7 +66,7 @@ clf.fit(X, y)
iris_classifier_service = IrisClassifier.pack(model=clf)
# Save the entire prediction service to file bundle
saved_path = = iris_classifier_service.save()
saved_path = iris_classifier_service.save()
```

A BentoML bundle is a versioned file archive, containing the BentoService you
@@ -170,19 +171,15 @@ To learn more, try out the Getting Started with Bentoml notebook: [![Google Cola

## Project Overview

BentoML has three main components:

* BentoService: High-level API for defining a prediction service by packaging
trained model, preprocessing source code, dependencies, and configurations
into a BentoML bundle file, which can be deployed as containerize REST API
server, PyPI package, CLI tool, or batch/streaming serving job
BentoML provides two set of high-level APIs:

* DeploymentOperator: The enssential module for deploying and managing your
prediction service workloads on Kubernetes cluster and cloud platforms such
as AWS Lambda, SageMaker, Azure ML, and GCP Function etc
* BentoService: Turn your trained ML model into versioned file bundle that can be
deployed as containerize REST API server, PyPI package, CLI tool, or
batch/streaming job

* YataiServer: Web UI and APIs for model management and model serving
deployment process management for teams
* YataiService: Manage and deploy your saved BentoML bundles into prediction
services on Kubernetes cluster or cloud platforms such as AWS Lambda, SageMaker,
Azure ML, and GCP Function etc


## Feature Highlights
@@ -139,14 +139,14 @@ class BentoServiceBase(object):
@abstractmethod
def name(self):
"""
return bento service name
return BentoService name
"""

@property
@abstractmethod
def version(self):
"""
return bento service version str
return BentoService version str
"""

def _config_service_apis(self):
@@ -449,6 +449,8 @@ def name(cls): # pylint:disable=method-hidden
return cls.__name__

def set_version(self, version_str=None):
"""Manually override the version of this BentoService instance
"""
if version_str is None:
version_str = self.versioneer()

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@@ -1,31 +1,36 @@
Artifacts
=========

PickleArtifact
++++++++++++++
.. autoclass:: bentoml.artifact.PickleArtifact

TextFileArtifact
++++++++++++++++
.. autoclass:: bentoml.artifact.TextFileArtifact
SklearnModelArtifact
++++++++++++++++++++
.. autoclass:: bentoml.artifact.SklearnModelArtifact

PytorchModelArtifact
++++++++++++++++++++
.. autoclass:: bentoml.artifact.PytorchModelArtifact

XgboostModelArtifact
KerasModelArtifact
++++++++++++++++++++
.. autoclass:: bentoml.artifact.XgboostModelArtifact
.. autoclass:: bentoml.artifact.KerasModelArtifact

FastaiModelArtifact
+++++++++++++++++++
.. autoclass:: bentoml.artifact.FastaiModelArtifact

XgboostModelArtifact
++++++++++++++++++++
.. autoclass:: bentoml.artifact.XgboostModelArtifact

H2oModelArtifact
++++++++++++++++
.. autoclass:: bentoml.artifact.H2oModelArtifact

KerasModelArtifact
++++++++++++++++++++
.. autoclass:: bentoml.artifact.KerasModelArtifact
PickleArtifact
++++++++++++++
.. autoclass:: bentoml.artifact.PickleArtifact

TextFileArtifact
++++++++++++++++
.. autoclass:: bentoml.artifact.TextFileArtifact


@@ -3,16 +3,16 @@ BentoML

BentoService
++++++++++++
.. autoclass:: bentoml.service.BentoService
.. autoclass:: bentoml.BentoService

.. automethod:: bentoml.service.BentoService.name
.. automethod:: bentoml.BentoService.name

.. automethod:: bentoml.service.BentoService.version
.. automethod:: bentoml.BentoService.versioneer

.. automethod:: bentoml.service.BentoService.get_service_apis
.. automethod:: bentoml.BentoService.set_version

.. automethod:: bentoml.BentoService.get_service_apis

.. autoclass:: bentoml.service.BentoServiceAPI

api
+++
@@ -34,12 +34,10 @@ save
++++
.. autofunction:: bentoml.save

.. _api-load-ref:
save_to_dir
+++++++++++
.. autofunction:: bentoml.save_to_dir

load
++++
.. autofunction:: bentoml.load

config
++++++
.. autofunction:: bentoml.config

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This file was deleted.

@@ -7,6 +7,4 @@ API Reference
bentoml
artifacts
handlers
deployments
exceptions

This file was deleted.

@@ -23,6 +23,7 @@
project = "BentoML"
copyright = "2019, Atalaya"
author = "Atalaya"
version = bentoml.__version__


# -- General configuration ---------------------------------------------------
@@ -50,7 +51,13 @@
#
html_theme_path = ["_themes"]
html_theme = "sphinx_rtd_theme"
html_theme_options = {"navigation_depth": 4}
html_theme_options = {
"collapse_navigation": True,
"navigation_depth": 4,
"display_version": True,
"includehidden": False,
"titles_only": False,
}

# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,

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