Skip to content

Latest commit

 

History

History
executable file
·
98 lines (72 loc) · 2.36 KB

README.md

File metadata and controls

executable file
·
98 lines (72 loc) · 2.36 KB
Raw

Open Prediction Service for Watson Machine Learning

This server was generated by the swagger-codegen project. By using the OpenAPI-Spec from a remote server, you can easily generate a server stub.

This example uses the Connexion library on top of Flask.

  1. Getting Started

  2. Open Prediction Service

Getting Started

Prerequisites

Python 3.7

Docker

Run the microservice on a Docker container

To build the microservice image

docker build -t wml-service .

To run the microservice, you will need to provide the following parameters:

  • WML_API_KEY : your Watson Machine Learning service apikey
  • WML_URL : your Watson Machine Learning service url
  • WML_SPACE_ID : your Watson Machine Learning service space id
docker run \
    -p 8080:8080 \
    -e WML_API_KEY=<WML_API_KEY> \
    -e WML_URL=<WML_URL> \
    -e WML_SPACE_ID=<WML_SPACE_ID> \
    --name wml-service \
    wml-service

If you want to run the microservice on another port

docker run \
    -p <PORT>:8080 \
    -e WML_API_KEY=<WML_API_KEY> \
    -e WML_URL=<WML_URL> \
    -e WML_SPACE_ID=<WML_SPACE_ID> \
    --name wml-service \
    wml-service

To check that you have a running container

docker ps -f name=wml-service

Your predictive service is available at http://localhost:8080/.

Swagger UI documentation is available at http://localhost:8080/ui

Or on the port of choice respectively at http://localhost:<PORT>/ and http://localhost:<PORT>/ui

Stop the microservice

To stop the container

docker stop wml-service

Run the microservice without Docker

pip3 install -r requirements.txt
python3 setup.py install
python3 -m swagger_server

Tests

To launch unit tests, use tox:

pip3 install tox
tox

To launch tests on your WML instance:

First, make sure you have a working and configured environment with the following global variables:

  • WML_API_KEY : your Watson Machine Learning service apikey
  • WML_URL : your Watson Machine Learning service url
  • WML_SPACE_ID : your Watson Machine Learning service space id

Then, run tests using tox:

pip3 install tox
tox swagger_server/test