feat(aiplatform): add sample for Gen AI code model tuning (#3410)

* feat(aiplatform): add sample for Gen AI code model tuning

* udpate comments to make it clear

* fix: skip this test temporary until the service account permission issue is resolved

* fix: skip another pipeline test temporary until the service account permission issue is resolved

* fix(aiplatform): try to get the test to run after IAM role changed

* fix(aiplatform): remove the skip for another pipeline test

* fix: address review comments

---------

Co-authored-by: Patti Shin <[email protected]>

Author: gericdong

ai-platform/snippets/code-model-tuning.js

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+/*
+ * Copyright 2023 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';
+
+async function main(
+  project,
+  pipelineJobId,
+  modelDisplayName,
+  gcsOutputDirectory,
+  location = 'europe-west4',
+  datasetUri = 'gs://cloud-samples-data/ai-platform/generative_ai/sql_create_context.jsonl',
+  trainSteps = 300
+) {
+  // [START aiplatform_genai_code_model_tuning]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.\
+   * (Not necessary if passing values as arguments)
+   */
+  // const project = 'YOUR_PROJECT_ID';
+  // const location = 'YOUR_PROJECT_LOCATION';
+  const aiplatform = require('@google-cloud/aiplatform');
+  const {PipelineServiceClient} = aiplatform.v1;
+
+  // Import the helper module for converting arbitrary protobuf.Value objects.
+  const {helpers} = aiplatform;
+
+  // Specifies the location of the api endpoint
+  const clientOptions = {
+    apiEndpoint: `${location}-aiplatform.googleapis.com`,
+  };
+  const model = 'code-bison@001';
+
+  const pipelineClient = new PipelineServiceClient(clientOptions);
+
+  async function tuneLLM() {
+    // Configure the parent resource
+    const parent = `projects/${project}/locations/${location}`;
+
+    const parameters = {
+      train_steps: helpers.toValue(trainSteps),
+      project: helpers.toValue(project),
+      location: helpers.toValue('us-central1'),
+      dataset_uri: helpers.toValue(datasetUri),
+      large_model_reference: helpers.toValue(model),
+      model_display_name: helpers.toValue(modelDisplayName),
+    };
+
+    const runtimeConfig = {
+      gcsOutputDirectory,
+      parameterValues: parameters,
+    };
+
+    const pipelineJob = {
+      templateUri:
+        'https://us-kfp.pkg.dev/ml-pipeline/large-language-model-pipelines/tune-large-model/v3.0.0',
+      displayName: 'my-tuning-job',
+      runtimeConfig,
+    };
+
+    const createPipelineRequest = {
+      parent,
+      pipelineJob,
+      pipelineJobId,
+    };
+
+    const [response] = await pipelineClient.createPipelineJob(
+      createPipelineRequest
+    );
+
+    console.log('Tuning pipeline job:');
+    console.log(`\tName: ${response.name}`);
+    console.log(
+      `\tCreate time: ${new Date(1970, 0, 1)
+        .setSeconds(response.createTime.seconds)
+        .toLocaleString()}`
+    );
+    console.log(`\tStatus: ${response.status}`);
+  }
+
+  await tuneLLM();
+  // [END aiplatform_genai_code_model_tuning]
+}
+
+exports.tuneModel = main;

ai-platform/snippets/test/code-model-tuning.test.js

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+// Copyright 2023 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
+//
+//      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.
+
+/* eslint-disable */
+
+'use strict';
+
+const {assert} = require('chai');
+const {describe, it} = require('mocha');
+const uuid = require('uuid');
+const sinon = require('sinon');
+
+const projectId = process.env.CAIP_PROJECT_ID;
+const location = 'europe-west4';
+
+const aiplatform = require('@google-cloud/aiplatform');
+const clientOptions = {
+  apiEndpoint: `${location}-aiplatform.googleapis.com`,
+};
+const pipelineClient = new aiplatform.v1.PipelineServiceClient(clientOptions);
+
+const {tuneModel} = require('../code-model-tuning');
+
+const timestampId = `${new Date()
+  .toISOString()
+  .replace(/(:|\.)/g, '-')
+  .toLowerCase()}`;
+const pipelineJobName = `my-tuning-pipeline-${timestampId}`;
+const modelDisplayName = `my-tuned-model-${timestampId}`;
+const bucketName = 'ucaip-samples-europe-west4/training_pipeline_output';
+const bucketUri = `gs://${bucketName}/tune-model-nodejs`;
+
+describe('Tune a code model', () => {
+  const stubConsole = function () {
+    sinon.stub(console, 'error');
+    sinon.stub(console, 'log');
+  };
+
+  const restoreConsole = function () {
+    console.log.restore();
+    console.error.restore();
+  };
+
+  beforeEach(stubConsole);
+  afterEach(restoreConsole);
+
+  it('should prompt-tune an existing code model', async () => {
+    // Act
+    await tuneModel(projectId, pipelineJobName, modelDisplayName, bucketUri);
+
+    // Assert
+    assert.include(console.log.firstCall.args, 'Tuning pipeline job:');
+  });
+
+  after(async () => {
+    // Cancel and delete the pipeline job
+    const name = pipelineClient.pipelineJobPath(
+      projectId,
+      location,
+      pipelineJobName
+    );
+
+    const cancelRequest = {
+      name,
+    };
+
+    pipelineClient.cancelPipelineJob(cancelRequest).then(() => {
+      const deleteRequest = {
+        name,
+      };
+
+      return pipelineClient.deletePipeline(deleteRequest);
+    });
+  });
+});