docs: add natural language sentiment analysis ga samples (#292)

* docs: add natural language sentiment analysis ga samples

* update package.json

* lint fix

* Update license headers

Co-authored-by: Benjamin E. Coe <[email protected]>

automl/snippets/language_sentiment_analysis_create_dataset.js

@@ -0,0 +1,67 @@
+// Copyright 2019 Google LLC
+//
+// 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
+//
+//     https://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.
+
+'use strict';
+
+function main(
+  projectId = 'YOUR_PROJECT_ID',
+  location = 'us-central1',
+  displayName = 'YOUR_DISPLAY_NAME'
+) {
+  // [START automl_language_sentiment_analysis_create_dataset]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'YOUR_PROJECT_ID';
+  // const location = 'us-central1';
+  // const displayName = 'YOUR_DISPLAY_NAME';
+
+  // Imports the Google Cloud AutoML library
+  const {AutoMlClient} = require(`@google-cloud/automl`).v1;
+
+  // Instantiates a client
+  const client = new AutoMlClient();
+
+  async function createDataset() {
+    // Construct request
+    const request = {
+      parent: client.locationPath(projectId, location),
+      dataset: {
+        displayName: displayName,
+        textSentimentDatasetMetadata: {
+          sentimentMax: 4, // Possible max sentiment score: 1-10
+        },
+      },
+    };
+
+    // Create dataset
+    const [operation] = await client.createDataset(request);
+
+    // Wait for operation to complete.
+    const [response] = await operation.promise();
+
+    console.log(`Dataset name: ${response.name}`);
+    console.log(`
+      Dataset id: ${
+        response.name
+          .split('/')
+          [response.name.split('/').length - 1].split('\n')[0]
+      }`);
+  }
+
+  createDataset();
+  // [END automl_language_sentiment_analysis_create_dataset]
+}
+
+main(...process.argv.slice(2));

automl/snippets/language_sentiment_analysis_create_model.js

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+// Copyright 2019 Google LLC
+//
+// 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
+//
+//     https://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.
+
+'use strict';
+
+function main(
+  projectId = 'YOUR_PROJECT_ID',
+  location = 'us-central1',
+  datasetId = 'YOUR_DATASET_ID',
+  displayName = 'YOUR_DISPLAY_NAME'
+) {
+  // [START automl_language_sentiment_analysis_create_model]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'YOUR_PROJECT_ID';
+  // const location = 'us-central1';
+  // const dataset_id = 'YOUR_DATASET_ID';
+  // const displayName = 'YOUR_DISPLAY_NAME';
+
+  // Imports the Google Cloud AutoML library
+  const {AutoMlClient} = require(`@google-cloud/automl`).v1;
+
+  // Instantiates a client
+  const client = new AutoMlClient();
+
+  async function createModel() {
+    // Construct request
+    const request = {
+      parent: client.locationPath(projectId, location),
+      model: {
+        displayName: displayName,
+        datasetId: datasetId,
+        textSentimentModelMetadata: {}, // Leave unset, to use the default base model
+      },
+    };
+
+    // Don't wait for the LRO
+    const [operation] = await client.createModel(request);
+    console.log(`Training started... ${operation}`);
+    console.log(`Training operation name: ${operation.name}`);
+  }
+
+  createModel();
+  // [END automl_language_sentiment_analysis_create_model]
+}
+
+main(...process.argv.slice(2));

automl/snippets/language_sentiment_analysis_predict.js

@@ -0,0 +1,64 @@
+// Copyright 2019 Google LLC
+//
+// 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
+//
+//     https://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.
+
+'use strict';
+
+function main(
+  projectId = 'YOUR_PROJECT_ID',
+  location = 'us-central1',
+  modelId = 'YOUR_MODEL_ID',
+  content = 'text to predict'
+) {
+  // [START automl_language_sentiment_analysis_predict]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'YOUR_PROJECT_ID';
+  // const location = 'us-central1';
+  // const modelId = 'YOUR_MODEL_ID';
+  // const content = 'text to predict'
+
+  // Imports the Google Cloud AutoML library
+  const {PredictionServiceClient} = require(`@google-cloud/automl`).v1;
+
+  // Instantiates a client
+  const client = new PredictionServiceClient();
+
+  async function predict() {
+    // Construct request
+    const request = {
+      name: client.modelPath(projectId, location, modelId),
+      payload: {
+        textSnippet: {
+          content: content,
+          mimeType: 'text/plain', // Types: 'test/plain', 'text/html'
+        },
+      },
+    };
+
+    const [response] = await client.predict(request);
+
+    for (const annotationPayload of response.payload) {
+      console.log(`Predicted class name: ${annotationPayload.displayName}`);
+      console.log(
+        `Predicted sentiment score: ${annotationPayload.textSentiment.sentiment}`
+      );
+    }
+  }
+
+  predict();
+  // [END automl_language_sentiment_analysis_predict]
+}
+
+main(...process.argv.slice(2));

automl/snippets/test/language_sentiment_analysis_create_dataset.test.js

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+// Copyright 2019 Google LLC
+//
+// 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
+//
+//     https://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.
+
+'use strict';
+
+const {assert} = require('chai');
+const {AutoMlClient} = require('@google-cloud/automl').v1;
+
+const cp = require('child_process');
+const uuid = require('uuid');
+
+const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
+
+const CREATE_DATASET_REGION_TAG = 'language_sentiment_analysis_create_dataset';
+const LOCATION = 'us-central1';
+
+describe('Automl Natural Language Sentiment Analysis Create Dataset Test', () => {
+  const client = new AutoMlClient();
+  let datasetId;
+
+  it('should create a dataset', async () => {
+    const projectId = await client.getProjectId();
+    const displayName = `test_${uuid
+      .v4()
+      .replace(/-/g, '_')
+      .substring(0, 26)}`;
+
+    // create
+    const create_output = execSync(
+      `node ${CREATE_DATASET_REGION_TAG}.js ${projectId} ${LOCATION} ${displayName}`
+    );
+    assert.match(create_output, /Dataset id:/);
+
+    datasetId = create_output.split('Dataset id: ')[1].split('\n')[0];
+  });
+
+  after('delete created dataset', async () => {
+    const projectId = await client.getProjectId();
+    const request = {
+      name: client.datasetPath(projectId, LOCATION, datasetId),
+    };
+    const [operation] = await client.deleteDataset(request);
+    await operation.promise();
+  });
+});

automl/snippets/test/language_sentiment_analysis_create_model.test.js

@@ -0,0 +1,48 @@
+// Copyright 2019 Google LLC
+//
+// 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
+//
+//     https://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.
+
+'use strict';
+
+const {assert} = require('chai');
+const {AutoMlClient} = require('@google-cloud/automl').v1;
+
+const cp = require('child_process');
+
+const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
+
+const CREATE_MODEL_REGION_TAG = 'language_sentiment_analysis_create_model';
+const LOCATION = 'us-central1';
+const DATASET_ID = 'TST8765214337653538816';
+
+describe('Automl Natural Language Sentiment Analysis Create Model Test', () => {
+  const client = new AutoMlClient();
+  let operationId;
+
+  it('should create a model', async () => {
+    const projectId = await client.getProjectId();
+    const create_output = execSync(
+      `node ${CREATE_MODEL_REGION_TAG}.js ${projectId} ${LOCATION} ${DATASET_ID} sentiment_test_create_model`
+    );
+
+    assert.match(create_output, /Training started/);
+
+    operationId = create_output
+      .split('Training operation name: ')[1]
+      .split('\n')[0];
+  });
+
+  after('cancel model training', async () => {
+    await client.operationsClient.cancelOperation({name: operationId});
+  });
+});

automl/snippets/test/language_sentiment_analysis_predict.test.js

@@ -0,0 +1,59 @@
+// Copyright 2019 Google LLC
+//
+// 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
+//
+//     https://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.
+
+'use strict';
+
+const {assert} = require('chai');
+const {AutoMlClient} = require('@google-cloud/automl').v1;
+
+const cp = require('child_process');
+
+const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
+
+const PREDICT_REGION_TAG = 'language_sentiment_analysis_predict';
+const LOCATION = 'us-central1';
+const MODEL_ID = 'TST3171435737203605504';
+
+describe('Automl Natural Language Sentiment Analysis Predict Test', () => {
+  const client = new AutoMlClient();
+
+  before('should verify the model is deployed', async () => {
+    const projectId = await client.getProjectId();
+    const request = {
+      name: client.modelPath(projectId, LOCATION, MODEL_ID),
+    };
+
+    const [response] = await client.getModel(request);
+    if (response.deploymentState === 'UNDEPLOYED') {
+      const request = {
+        name: client.modelPath(projectId, LOCATION, MODEL_ID),
+      };
+
+      const [operation] = await client.deployModel(request);
+
+      // Wait for operation to complete.
+      await operation.promise();
+    }
+  });
+
+  it('should predict', async () => {
+    const projectId = await client.getProjectId();
+    const content = "'Hopefully this Claritin kicks in soon'";
+
+    const predictOutput = execSync(
+      `node ${PREDICT_REGION_TAG}.js ${projectId} ${LOCATION} ${MODEL_ID} ${content}`
+    );
+    assert.match(predictOutput, /Predicted sentiment score/);
+  });
+});