feat: genai sample base

.github/auto-label.yaml

@@ -45,6 +45,7 @@ path:
         eventarc: "eventarc"
         error-reporting: "clouderrorreporting"
         functions: "cloudfunctions"
+        generative-ai: "genai"
         game-servers: "gameservices"
         healthcare: "healhcare"
         iam: "iam"

.github/workflows/generative-ai-snippets.yaml

@@ -0,0 +1,106 @@
+# 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.
+
+name: generative-ai-snippets
+on:
+  push:
+    branches:
+    - main
+    paths:
+    - 'generative-ai/snippets/**'
+    - '.github/workflows/generative-ai-snippets.yaml'
+  pull_request:
+    paths:
+    - 'generative-ai/snippets/**'
+    - '.github/workflows/generative-ai-snippets.yaml'
+  pull_request_target:
+    types: [labeled]
+    paths:
+    - 'generative-ai/snippets/**'
+    - '.github/workflows/generative-ai-snippets.yaml'
+  schedule:
+  - cron:  '0 0 * * 0'
+jobs:
+  test:
+    if: github.event.action != 'labeled' || github.event.label.name == 'actions:force-run'
+    runs-on: ubuntu-latest
+    timeout-minutes: 120
+    permissions:
+      contents: 'read'
+      id-token: 'write'
+    defaults:
+      run:
+        working-directory: 'generative-ai/snippets'
+    steps:
+    - uses: actions/checkout@v4.1.0
+      with:
+        ref: ${{github.event.pull_request.head.sha}}
+    - uses: 'google-github-actions/auth@v1.1.1'
+      with:
+        workload_identity_provider: 'projects/1046198160504/locations/global/workloadIdentityPools/github-actions-pool/providers/github-actions-provider'
+        service_account: 'kokoro-system-test@long-door-651.iam.gserviceaccount.com'
+        create_credentials_file: 'true'
+        access_token_lifetime: 600s
+    - id: secrets
+      uses: 'google-github-actions/get-secretmanager-secrets@v1'
+      with:
+        secrets: |-
+          caip_id:nodejs-docs-samples-tests/nodejs-docs-samples-ai-platform-caip-project-id
+          location:nodejs-docs-samples-tests/nodejs-docs-samples-ai-platform-location
+    - uses: actions/setup-node@v4.0.0
+      with:
+        node-version: 16
+    - name: Get npm cache directory
+      id: npm-cache-dir
+      shell: bash
+      run: echo "dir=$(npm config get cache)" >> ${GITHUB_OUTPUT}        
+    - uses: actions/cache@v3
+      id: npm-cache
+      with:
+        path: ${{ steps.npm-cache-dir.outputs.dir }}
+        key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}
+        restore-keys: |
+          ${{ runner.os }}-node-   
+    - name: install repo dependencies
+      run: npm install
+      working-directory: .
+    - name: install directory dependencies
+      run: npm install
+    - run: npm run build --if-present
+    - name: set env vars for scheduled run
+      if: github.event.action == 'schedule'
+      run: |
+        echo "MOCHA_REPORTER_SUITENAME=generative-ai-snippets" >> $GITHUB_ENV
+        echo "MOCHA_REPORTER_OUTPUT=${{github.run_id}}_sponge_log.xml" >> $GITHUB_ENV
+        echo "MOCHA_REPORTER=xunit" >> $GITHUB_ENV
+    - run: npm test
+      env:
+        LOCATION: ${{ steps.secrets.outputs.location }}
+        CAIP_PROJECT_ID: ${{ steps.secrets.outputs.caip_id }}      
+    - name: upload test results for FlakyBot workflow
+      if: github.event.action == 'schedule' && always()
+      uses: actions/upload-artifact@v3
+      env:
+        MOCHA_REPORTER_OUTPUT: "${{github.run_id}}_sponge_log.xml"
+      with:
+        name: test-results
+        path: generative-ai/snippets/${{ env.MOCHA_REPORTER_OUTPUT }}
+        retention-days: 1        
+  flakybot:
+    permissions:
+      contents: 'read'
+      id-token: 'write'
+    if: github.event_name == 'schedule' && always() # always() submits logs even if tests fail
+    uses: ./.github/workflows/flakybot.yaml
+    needs: [test]

.github/workflows/utils/workflows-secrets.json

@@ -5,5 +5,6 @@
   "iam/deny",
   "security-center/snippets",
   "storagetransfer",
+  "generative-ai/snippets",
   "vision"
 ]

CODEOWNERS

@@ -50,6 +50,7 @@ monitoring/opencensus @GoogleCloudPlatform/nodejs-samples-reviewers
 
 # Data & AI
 ai-platform @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
+generative-ai @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
 automl @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
 cloud-language @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
 contact-center-insights @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers

generative-ai/snippets/countTokens.js

@@ -0,0 +1,52 @@
+// 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.
+
+const {VertexAI} = require('@google-cloud/vertexai');
+
+async function countTokens(
+  projectId = 'PROJECT_ID',
+  location = 'LOCATION_ID',
+  model = 'MODEL'
+) {
+  // [START aiplatform_gemini_token_count]
+
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'your-project-id';
+  // const location = 'us-central1';
+  // const model = 'gemini-pro';
+
+  // Initialize Vertex with your Cloud project and location
+  const vertex_ai = new VertexAI({project: projectId, location: location});
+
+  // Instantiate the model
+  const generativeModel = vertex_ai.preview.getGenerativeModel({
+    model: model,
+  });
+
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const countTokensResp = await generativeModel.countTokens(req);
+  console.log('count tokens response: ', countTokensResp);
+
+  // [END aiplatform_gemini_token_count]
+}
+
+countTokens(...process.argv.slice(2)).catch(err => {
+  console.error(err.message);
+  process.exitCode = 1;
+});

generative-ai/snippets/index.js

@@ -0,0 +1,124 @@
+const {
+  VertexAI,
+  HarmBlockThreshold,
+  HarmCategory,
+} = require('@google-cloud/vertexai');
+
+const project = 'cloud-llm-preview1';
+const location = 'us-central1';
+
+// Initialize Vertex with your Cloud project and location
+const vertex_ai = new VertexAI({project: project, location: location});
+
+// Instantiate the models
+const generativeModel = vertex_ai.preview.getGenerativeModel({
+  model: 'gemini-pro',
+  // The following parameters are optional
+  // They can also be passed to individual content generation requests
+  safety_settings: [
+    {
+      category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
+      threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
+    },
+  ],
+  generation_config: {max_output_tokens: 256},
+});
+
+const generativeVisionModel = vertex_ai.preview.getGenerativeModel({
+  model: 'gemini-pro-vision',
+});
+
+async function streamContentTextOnly() {
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const streamingResp = await generativeModel.generateContentStream(req);
+
+  for await (const item of streamingResp.stream) {
+    console.log('stream chunk:', item);
+  }
+
+  console.log('aggregated response: ', await streamingResp.response);
+}
+
+async function nonStreamingTextOnly() {
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const nonstreamingResp = await generativeModel.generateContent(req);
+  console.log('non-streaming response: ', await nonstreamingResp.response);
+}
+
+async function countTokens() {
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const countTokensResp = await generativeModel.countTokens(req);
+  console.log('count tokens response: ', countTokensResp);
+}
+
+async function nonStreamingChat() {
+  const chat = generativeModel.startChat({});
+  const result1 = await chat.sendMessage('hello');
+  console.log('send message result1: ', result1);
+  const resp1 = result1.response;
+  console.log('send message response1: ', resp1);
+  const result2 = await chat.sendMessage('what day is it today?');
+  console.log('result2: ', result2);
+  const resp2 = result2.response;
+  console.log('send message response2: ', resp2);
+  const result3 = await chat.sendMessage('what day is it tomorrow?');
+  console.log('result3: ', result3);
+  const resp3 = result3.response;
+  console.log('send message response3: ', resp3);
+}
+
+async function streamingChat() {
+  const chat = generativeModel.startChat({});
+  const streamResult1 = await chat.sendMessageStream('hello again');
+  console.log('stream result1: ', streamResult1);
+  const streamResp1 = await streamResult1.response;
+  console.log('stream send message response1: ', streamResp1);
+  const streamResult2 = await chat.sendMessageStream('what is the date today?');
+  console.log('stream result2: ', streamResult2);
+  const streamResp2 = await streamResult2.response;
+  console.log('stream send message response2: ', streamResp2);
+  const streamResult3 = await chat.sendMessageStream(
+    'what is the date tomorrow?'
+  );
+  console.log('stream result3: ', streamResult3);
+  const streamResp3 = await streamResult3.response;
+  console.log('stream send message response3: ', streamResp3);
+}
+
+async function multiPartContent() {
+  const filePart = {
+    file_data: {
+      file_uri: 'gs://sararob_imagegeneration_test/kitten.jpeg',
+      mime_type: 'image/jpeg',
+    },
+  };
+  const textPart = {text: 'What is this a picture of?'};
+
+  const request = {
+    contents: [{role: 'user', parts: [textPart, filePart]}],
+  };
+
+  const generativeVisionModel = vertex_ai.preview.getGenerativeModel({
+    model: 'gemini-pro-vision',
+  });
+
+  const resp = await generativeVisionModel.generateContentStream(request);
+  const contentResponse = await resp.response;
+  console.log(contentResponse.candidates[0].content);
+}
+
+nonStreamingTextOnly();
+streamContentTextOnly();
+countTokens();
+nonStreamingChat();
+streamingChat();
+multiPartContent();

generative-ai/snippets/nonStreamingChat.js

@@ -0,0 +1,73 @@
+// 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.
+
+const {VertexAI} = require('@google-cloud/vertexai');
+
+function wait(time) {
+  return new Promise(resolve => {
+    setTimeout(resolve, time);
+  });
+}
+
+async function createNonStreamingChat(
+  projectId = 'PROJECT_ID',
+  location = 'LOCATION_ID',
+  model = 'MODEL'
+) {
+  // TODO: Find better method. Setting delay to give api time to respond, otherwise it will 404
+  // await wait(10);
+
+  // [START aiplatform_gemini_multiturn_chat]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'your-project-id';
+  // const location = 'us-central1';
+
+  // Initialize Vertex with your Cloud project and location
+  const vertexAI = new VertexAI({project: projectId, location: location});
+
+  // Instantiate the model
+  const generativeModel = vertexAI.preview.getGenerativeModel({
+    model: model,
+  });
+
+  const chat = generativeModel.startChat({});
+
+  const chatInput1 = 'Hello';
+  console.log(`User: ${chatInput1}`);
+
+  const result1 = await chat.sendMessage(chatInput1);
+  const response1 = result1.response.candidates[0].content.parts[0].text;
+  console.log('Chat bot: ', response1);
+
+  const chatInput2 = 'Can you tell me a scientific fun fact?';
+  console.log(`User: ${chatInput2}`);
+  const result2 = await chat.sendMessage(chatInput2);
+  const response2 = result2.response.candidates[0].content.parts[0].text;
+  console.log('Chat bot: ', response2);
+
+  const chatInput3 = 'How can I learn more about that?';
+  console.log(`User: ${chatInput3}`);
+  const result3 = await chat.sendMessage(chatInput3);
+  const response3 = result3.response.candidates[0].content.parts[0].text;
+  console.log('Chat bot: ', response3);
+
+  // [END aiplatform_gemini_multiturn_chat]
+}
+
+createNonStreamingChat(...process.argv.slice(2)).catch(err => {
+  console.error(err.message);
+  process.exitCode = 1;
+});