DEEPaaS is a REST API to expose a machine learning model.
Project description
# DEEPaaS
[![GitHub license](https://img.shields.io/github/license/indigo-dc/DEEPaaS.svg)](https://github.com/indigo-dc/DEEPaaS/blob/master/LICENSE) [![GitHub release](https://img.shields.io/github/release/indigo-dc/DEEPaaS.svg)](https://github.com/indigo-dc/DEEPaaS/releases) [![PyPI](https://img.shields.io/pypi/v/deepaas.svg)](https://pypi.python.org/pypi/deepaas) [![Python versions](https://img.shields.io/pypi/pyversions/deepaas.svg)](https://pypi.python.org/pypi/deepaas) [![Build Status](https://jenkins.indigo-datacloud.eu/buildStatus/icon?job=Pipeline-as-code%2FDEEPaaS%2Fmaster)](https://jenkins.indigo-datacloud.eu/job/Pipeline-as-code/job/DEEPaaS/job/master/)
DEEP as a Service (DEEPaaS) is a REST API that is focused on providing access to machine learning models. By using DEEPaaS users can easily run a REST API in front of their model, thus accessing its functionality via HTTP calls.
## Quickstart
The best way to quickly try the DEEPaaS API is through:
make run
This command will install a virtualenv (in the virtualenv directory) with DEEPaaS and all its dependencies and will run the DEEPaaS REST API, listening on 127.0.0.1:5000. If you browse to http://127.0.0.1:5000 you will get the swagger documentation page.
### Develop mode
If you want to run the code in develop mode (i.e. pip install -e), you can issue the following command before:
make develop
# Documentation
The DEEPaaS documentation is hosted on [Read the Docs](https://deepaas.readthedocs.io/).
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