..

backend/node_modules/googleapis/apis/prediction/v1.6.ts

@@ -0,0 +1,889 @@
+/**
+ * Copyright 2015 Google Inc. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/* jshint maxlen: false */
+
+import createAPIRequest from '../../lib/apirequest';
+
+/**
+ * Prediction API
+ *
+ * Lets you access a cloud hosted machine learning service that makes it easy to build smart apps
+ *
+ * @example
+ * const google = require('googleapis');
+ * const prediction = google.prediction('v1.6');
+ *
+ * @namespace prediction
+ * @type {Function}
+ * @version v1.6
+ * @variation v1.6
+ * @param {object=} options Options for Prediction
+ */
+function Prediction(options) { // eslint-disable-line
+  const self = this;
+  self._options = options || {};
+
+  self.hostedmodels = {
+
+    /**
+     * prediction.hostedmodels.predict
+     *
+     * @desc Submit input and request an output against a hosted model.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     // The name of a hosted model.
+     *     hostedModelName: 'my-hosted-model-name',  // TODO: Update placeholder value.
+     *
+     *     resource: {
+     *       // TODO: Add desired properties to the request body.
+     *     },
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   prediction.hostedmodels.predict(request, function(err, response) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *
+     *     // TODO: Change code below to process the `response` object:
+     *     console.log(JSON.stringify(response, null, 2));
+     *   });
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.hostedmodels.predict
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {string} params.hostedModelName The name of a hosted model.
+     * @param {string} params.project The project associated with the model.
+     * @param {prediction(v1.6).Input} params.resource Request body data
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    predict: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/hostedmodels/{hostedModelName}/predict').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'POST'
+        }, options),
+        params: params,
+        requiredParams: ['project', 'hostedModelName'],
+        pathParams: ['hostedModelName', 'project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    }
+
+  };
+
+  self.trainedmodels = {
+
+    /**
+     * prediction.trainedmodels.analyze
+     *
+     * @desc Get analysis of the model and the data the model was trained on.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     // The unique name for the predictive model.
+     *     id: 'my-id',  // TODO: Update placeholder value.
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   prediction.trainedmodels.analyze(request, function(err, response) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *
+     *     // TODO: Change code below to process the `response` object:
+     *     console.log(JSON.stringify(response, null, 2));
+     *   });
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.trainedmodels.analyze
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {string} params.id The unique name for the predictive model.
+     * @param {string} params.project The project associated with the model.
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    analyze: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/trainedmodels/{id}/analyze').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'GET'
+        }, options),
+        params: params,
+        requiredParams: ['project', 'id'],
+        pathParams: ['id', 'project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    },
+
+    /**
+     * prediction.trainedmodels.delete
+     *
+     * @desc Delete a trained model.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     // The unique name for the predictive model.
+     *     id: 'my-id',  // TODO: Update placeholder value.
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   prediction.trainedmodels.delete(request, function(err) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *   });
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.trainedmodels.delete
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {string} params.id The unique name for the predictive model.
+     * @param {string} params.project The project associated with the model.
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    delete: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/trainedmodels/{id}').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'DELETE'
+        }, options),
+        params: params,
+        requiredParams: ['project', 'id'],
+        pathParams: ['id', 'project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    },
+
+    /**
+     * prediction.trainedmodels.get
+     *
+     * @desc Check training status of your model.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     // The unique name for the predictive model.
+     *     id: 'my-id',  // TODO: Update placeholder value.
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   prediction.trainedmodels.get(request, function(err, response) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *
+     *     // TODO: Change code below to process the `response` object:
+     *     console.log(JSON.stringify(response, null, 2));
+     *   });
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.trainedmodels.get
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {string} params.id The unique name for the predictive model.
+     * @param {string} params.project The project associated with the model.
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    get: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/trainedmodels/{id}').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'GET'
+        }, options),
+        params: params,
+        requiredParams: ['project', 'id'],
+        pathParams: ['id', 'project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    },
+
+    /**
+     * prediction.trainedmodels.insert
+     *
+     * @desc Train a Prediction API model.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     resource: {
+     *       // TODO: Add desired properties to the request body.
+     *     },
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   prediction.trainedmodels.insert(request, function(err, response) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *
+     *     // TODO: Change code below to process the `response` object:
+     *     console.log(JSON.stringify(response, null, 2));
+     *   });
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.trainedmodels.insert
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {string} params.project The project associated with the model.
+     * @param {prediction(v1.6).Insert} params.resource Request body data
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    insert: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/trainedmodels').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'POST'
+        }, options),
+        params: params,
+        requiredParams: ['project'],
+        pathParams: ['project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    },
+
+    /**
+     * prediction.trainedmodels.list
+     *
+     * @desc List available models.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   var handlePage = function(err, response) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *
+     *     var itemsPage = response['items'];
+     *     if (!itemsPage) {
+     *       return;
+     *     }
+     *     for (var i = 0; i < itemsPage.length; i++) {
+     *       // TODO: Change code below to process each resource in `itemsPage`:
+     *       console.log(JSON.stringify(itemsPage[i], null, 2));
+     *     }
+     *
+     *     if (response.nextPageToken) {
+     *       request.pageToken = response.nextPageToken;
+     *       prediction.trainedmodels.list(request, handlePage);
+     *     }
+     *   };
+     *
+     *   prediction.trainedmodels.list(request, handlePage);
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.trainedmodels.list
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {integer=} params.maxResults Maximum number of results to return.
+     * @param {string=} params.pageToken Pagination token.
+     * @param {string} params.project The project associated with the model.
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    list: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/trainedmodels/list').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'GET'
+        }, options),
+        params: params,
+        requiredParams: ['project'],
+        pathParams: ['project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    },
+
+    /**
+     * prediction.trainedmodels.predict
+     *
+     * @desc Submit model id and request a prediction.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     // The unique name for the predictive model.
+     *     id: 'my-id',  // TODO: Update placeholder value.
+     *
+     *     resource: {
+     *       // TODO: Add desired properties to the request body.
+     *     },
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   prediction.trainedmodels.predict(request, function(err, response) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *
+     *     // TODO: Change code below to process the `response` object:
+     *     console.log(JSON.stringify(response, null, 2));
+     *   });
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.trainedmodels.predict
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {string} params.id The unique name for the predictive model.
+     * @param {string} params.project The project associated with the model.
+     * @param {prediction(v1.6).Input} params.resource Request body data
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    predict: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/trainedmodels/{id}/predict').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'POST'
+        }, options),
+        params: params,
+        requiredParams: ['project', 'id'],
+        pathParams: ['id', 'project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    },
+
+    /**
+     * prediction.trainedmodels.update
+     *
+     * @desc Add new data to a trained model.
+     *
+     * @example
+     * // BEFORE RUNNING:
+     * // ---------------
+     * // 1. If not already done, enable the Prediction API
+     * //    and check the quota for your project at
+     * //    https://console.developers.google.com/apis/api/prediction
+     * // 2. This sample uses Application Default Credentials for authentication.
+     * //    If not already done, install the gcloud CLI from
+     * //    https://cloud.google.com/sdk and run
+     * //    `gcloud beta auth application-default login`.
+     * //    For more information, see
+     * //    https://developers.google.com/identity/protocols/application-default-credentials
+     * // 3. Install the Node.js client library by running
+     * //    `npm install googleapis --save`
+     *
+     * var google = require('googleapis');
+     * var prediction = google.prediction('v1.6');
+     *
+     * authorize(function(authClient) {
+     *   var request = {
+     *     // The project associated with the model.
+     *     project: 'my-project',  // TODO: Update placeholder value.
+     *
+     *     // The unique name for the predictive model.
+     *     id: 'my-id',  // TODO: Update placeholder value.
+     *
+     *     resource: {
+     *       // TODO: Add desired properties to the request body. All existing properties
+     *       // will be replaced.
+     *     },
+     *
+     *     auth: authClient,
+     *   };
+     *
+     *   prediction.trainedmodels.update(request, function(err, response) {
+     *     if (err) {
+     *       console.error(err);
+     *       return;
+     *     }
+     *
+     *     // TODO: Change code below to process the `response` object:
+     *     console.log(JSON.stringify(response, null, 2));
+     *   });
+     * });
+     *
+     * function authorize(callback) {
+     *   google.auth.getApplicationDefault(function(err, authClient) {
+     *     if (err) {
+     *       console.error('authentication failed: ', err);
+     *       return;
+     *     }
+     *     if (authClient.createScopedRequired && authClient.createScopedRequired()) {
+     *       var scopes = ['https://www.googleapis.com/auth/cloud-platform'];
+     *       authClient = authClient.createScoped(scopes);
+     *     }
+     *     callback(authClient);
+     *   });
+     * }
+     *
+     * @alias prediction.trainedmodels.update
+     * @memberOf! prediction(v1.6)
+     *
+     * @param {object} params Parameters for request
+     * @param {string} params.id The unique name for the predictive model.
+     * @param {string} params.project The project associated with the model.
+     * @param {prediction(v1.6).Update} params.resource Request body data
+     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
+     * @param {callback} callback The callback that handles the response.
+     * @return {object} Request object
+     */
+    update: function (params, options, callback) {
+      if (typeof options === 'function') {
+        callback = options;
+        options = {};
+      }
+      options || (options = {});
+
+      const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
+
+      const parameters = {
+        options: Object.assign({
+          url: (rootUrl + '/prediction/v1.6/projects/{project}/trainedmodels/{id}').replace(/([^:]\/)\/+/g, '$1'),
+          method: 'PUT'
+        }, options),
+        params: params,
+        requiredParams: ['project', 'id'],
+        pathParams: ['id', 'project'],
+        context: self
+      };
+
+      return createAPIRequest(parameters, callback);
+    }
+
+  };
+}
+
+/**
+ * @typedef Analyze
+ * @memberOf! prediction(v1.6)
+ * @type object
+ * @property {object} dataDescription Description of the data the model was trained on.
+ * @property {object[]} errors List of errors with the data.
+ * @property {string} id The unique name for the predictive model.
+ * @property {string} kind What kind of resource this is.
+ * @property {object} modelDescription Description of the model.
+ * @property {string} selfLink A URL to re-request this resource.
+ */
+
+/**
+ * @typedef Input
+ * @memberOf! prediction(v1.6)
+ * @type object
+ * @property {object} input Input to the model for a prediction.
+ */
+
+/**
+ * @typedef Insert
+ * @memberOf! prediction(v1.6)
+ * @type object
+ * @property {string} id The unique name for the predictive model.
+ * @property {string} modelType Type of predictive model (classification or regression).
+ * @property {string} sourceModel The Id of the model to be copied over.
+ * @property {string} storageDataLocation Google storage location of the training data file.
+ * @property {string} storagePMMLLocation Google storage location of the preprocessing pmml file.
+ * @property {string} storagePMMLModelLocation Google storage location of the pmml model file.
+ * @property {object[]} trainingInstances Instances to train model on.
+ * @property {object[]} utility A class weighting function, which allows the importance weights for class labels to be specified (Categorical models only).
+ */
+
+/**
+ * @typedef Insert2
+ * @memberOf! prediction(v1.6)
+ * @type object
+ * @property {string} created Insert time of the model (as a RFC 3339 timestamp).
+ * @property {string} id The unique name for the predictive model.
+ * @property {string} kind What kind of resource this is.
+ * @property {object} modelInfo Model metadata.
+ * @property {string} modelType Type of predictive model (CLASSIFICATION or REGRESSION).
+ * @property {string} selfLink A URL to re-request this resource.
+ * @property {string} storageDataLocation Google storage location of the training data file.
+ * @property {string} storagePMMLLocation Google storage location of the preprocessing pmml file.
+ * @property {string} storagePMMLModelLocation Google storage location of the pmml model file.
+ * @property {string} trainingComplete Training completion time (as a RFC 3339 timestamp).
+ * @property {string} trainingStatus The current status of the training job. This can be one of following: RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
+ */
+
+/**
+ * @typedef List
+ * @memberOf! prediction(v1.6)
+ * @type object
+ * @property {prediction(v1.6).Insert2[]} items List of models.
+ * @property {string} kind What kind of resource this is.
+ * @property {string} nextPageToken Pagination token to fetch the next page, if one exists.
+ * @property {string} selfLink A URL to re-request this resource.
+ */
+
+/**
+ * @typedef Output
+ * @memberOf! prediction(v1.6)
+ * @type object
+ * @property {string} id The unique name for the predictive model.
+ * @property {string} kind What kind of resource this is.
+ * @property {string} outputLabel The most likely class label (Categorical models only).
+ * @property {object[]} outputMulti A list of class labels with their estimated probabilities (Categorical models only).
+ * @property {string} outputValue The estimated regression value (Regression models only).
+ * @property {string} selfLink A URL to re-request this resource.
+ */
+
+/**
+ * @typedef Update
+ * @memberOf! prediction(v1.6)
+ * @type object
+ * @property {any[]} csvInstance The input features for this instance.
+ * @property {string} output The generic output value - could be regression or class label.
+ */
+export = Prediction;