google-cloud-prediction-cli v1.0.1

Introduction

This is a small CLI tool that will allow you to easily insert and check the status of training models with the Google Cloud Prediction API.

Requirements

You must have Node v5+ (this was written with ES6 in mind, so it will not work on older versions of node.)

Installation

$ npm install -g google-cloud-prediction-cli

This will install the command prediction as a symlink to your bash profile.

Usage

Google Cloud Prediction API

  A simple tool to insert and check on the status of training models.

Options

  -i, --insert            Command to insert a new training model.
  -s, --status            Command to check the training status of an existing model.
  -p, --project string    Project ID to use
  -m, --model string      Location of the model in Google Cloud Storage. Example:
                          some_bucket/my_file.txt
  -o, --model-id string   ID to associate with the model to create (can be any unique string that's
                          easy to remember)
  -h, --help

Setup

  You must have an environment variable named GOOGLE_APPLICATION_CREDENTIALS
  set to the location of an credentials JSON file.

Example Commands

Checking Training Status

$ prediction --status --project=some-gapi-project --model-id=my-model-id

kind:             prediction#training
id:               my-model-id
selfLink:         https://www.googleapis.com/prediction/v1.6/projects/some-gapi-project/trainedmodels/my-model-id
created:          2016-07-21T17:58:23.177Z
trainingComplete: 2016-07-21T18:29:32.084Z
modelInfo:
  numberInstances:        57983
  modelType:              classification
  numberLabels:           110
  classificationAccuracy: 0.84
trainingStatus:   DONE

Inserting a new training model

$ prediction --insert --project=some-project --model-id=my-model-id --model=my-bucket/some-file.txt

kind:                prediction#training
id:                  my-model-id
selfLink:            https://www.googleapis.com/prediction/v1.6/projects/some-project/trainedmodels/my-model-id
storageDataLocation: my-bucket/some-file.txt