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LukeSchlangenpattishin
LukeSchlangen
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pattishin
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feat: genai sample base (#3587)
* feat: initial base for generative-ai * # This is a combination of 16 commits. # This is the 1st commit message: refactor: updating codeowners # This is the commit message #2: add chat functions # This is the commit message #3: use correct testing project # This is the commit message #4: refactor: adding system tests + updating corresponding chat samples # This is the commit message #5: add countTokens sample # This is the commit message #6: refactor: adding in region tags, abstracting out mimetype, adding new image ur # This is the commit message #7: refactor: updating gs url in test, fix to args getting passed to sample functions # This is the commit message #8: refactor: resolving file paths in tests, adding wait helper function # This is the commit message #9: add warning about safety concerns # This is the commit message #10: refactor:filling out nonstreamingchat and streamcontent tests # This is the commit message #11: add countTokens test # This is the commit message #12: refactor: filling out more streaming tests # This is the commit message #13: add safety settings test # This is the commit message #14: refactor: adding in stream content and multipart content tests # This is the commit message #15: feat: add new sendMultiModalPromptWithImage sample # This is the commit message #16: refactor: adding region tags * refactor: updating codeowners add chat functions use correct testing project refactor: adding system tests + updating corresponding chat samples add countTokens sample refactor: adding in region tags, abstracting out mimetype, adding new image ur refactor: updating gs url in test, fix to args getting passed to sample functions refactor: resolving file paths in tests, adding wait helper function add warning about safety concerns refactor:filling out nonstreamingchat and streamcontent tests add countTokens test refactor: filling out more streaming tests add safety settings test refactor: adding in stream content and multipart content tests feat: add new sendMultiModalPromptWithImage sample refactor: adding region tags update to common prompt fix: resolve linting * refactor: remove index file --------- Co-authored-by: [email protected] <[email protected]>
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‎.github/auto-label.yaml

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eventarc: "eventarc"
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error-reporting: "clouderrorreporting"
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functions: "cloudfunctions"
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generative-ai: "genai"
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game-servers: "gameservices"
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healthcare: "healhcare"
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iam: "iam"

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

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# Copyright 2023 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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name: generative-ai-snippets
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on:
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push:
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branches:
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- main
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paths:
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- 'generative-ai/snippets/**'
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- '.github/workflows/generative-ai-snippets.yaml'
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pull_request:
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paths:
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- 'generative-ai/snippets/**'
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- '.github/workflows/generative-ai-snippets.yaml'
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pull_request_target:
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types: [labeled]
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paths:
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- 'generative-ai/snippets/**'
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- '.github/workflows/generative-ai-snippets.yaml'
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schedule:
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- cron: '0 0 * * 0'
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jobs:
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test:
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if: github.event.action != 'labeled' || github.event.label.name == 'actions:force-run'
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runs-on: ubuntu-latest
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timeout-minutes: 120
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permissions:
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contents: 'read'
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id-token: 'write'
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defaults:
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run:
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working-directory: 'generative-ai/snippets'
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steps:
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- uses: actions/[email protected]
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with:
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ref: ${{github.event.pull_request.head.sha}}
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- uses: 'google-github-actions/[email protected]'
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with:
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workload_identity_provider: 'projects/1046198160504/locations/global/workloadIdentityPools/github-actions-pool/providers/github-actions-provider'
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service_account: '[email protected]'
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create_credentials_file: 'true'
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access_token_lifetime: 600s
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- id: secrets
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uses: 'google-github-actions/get-secretmanager-secrets@v1'
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with:
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secrets: |-
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caip_id:nodejs-docs-samples-tests/nodejs-docs-samples-ai-platform-caip-project-id
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location:nodejs-docs-samples-tests/nodejs-docs-samples-ai-platform-location
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- uses: actions/[email protected]
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with:
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node-version: 16
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- name: Get npm cache directory
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id: npm-cache-dir
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shell: bash
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run: echo "dir=$(npm config get cache)" >> ${GITHUB_OUTPUT}
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- uses: actions/cache@v3
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id: npm-cache
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with:
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path: ${{ steps.npm-cache-dir.outputs.dir }}
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key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}
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restore-keys: |
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${{ runner.os }}-node-
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- name: install repo dependencies
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run: npm install
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working-directory: .
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- name: install directory dependencies
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run: npm install
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- run: npm run build --if-present
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- name: set env vars for scheduled run
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if: github.event.action == 'schedule'
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run: |
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echo "MOCHA_REPORTER_SUITENAME=generative-ai-snippets" >> $GITHUB_ENV
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echo "MOCHA_REPORTER_OUTPUT=${{github.run_id}}_sponge_log.xml" >> $GITHUB_ENV
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echo "MOCHA_REPORTER=xunit" >> $GITHUB_ENV
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- run: npm test
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env:
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LOCATION: ${{ steps.secrets.outputs.location }}
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CAIP_PROJECT_ID: ${{ steps.secrets.outputs.caip_id }}
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- name: upload test results for FlakyBot workflow
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if: github.event.action == 'schedule' && always()
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uses: actions/upload-artifact@v3
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env:
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MOCHA_REPORTER_OUTPUT: "${{github.run_id}}_sponge_log.xml"
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with:
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name: test-results
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path: generative-ai/snippets/${{ env.MOCHA_REPORTER_OUTPUT }}
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retention-days: 1
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flakybot:
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permissions:
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contents: 'read'
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id-token: 'write'
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if: github.event_name == 'schedule' && always() # always() submits logs even if tests fail
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uses: ./.github/workflows/flakybot.yaml
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needs: [test]

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

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"iam/deny",
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"security-center/snippets",
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"storagetransfer",
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"generative-ai/snippets",
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"vision"
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]

‎CODEOWNERS

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# Data & AI
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ai-platform @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
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generative-ai @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
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automl @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
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cloud-language @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
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contact-center-insights @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers

‎generative-ai/snippets/countTokens.js

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// Copyright 2023 Google LLC
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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const {VertexAI} = require('@google-cloud/vertexai');
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async function countTokens(
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projectId = 'PROJECT_ID',
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location = 'LOCATION_ID',
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model = 'MODEL'
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) {
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// [START aiplatform_gemini_token_count]
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/**
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* TODO(developer): Uncomment these variables before running the sample.
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*/
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// const projectId = 'your-project-id';
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// const location = 'us-central1';
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// const model = 'gemini-pro';
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// Initialize Vertex with your Cloud project and location
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const vertex_ai = new VertexAI({project: projectId, location: location});
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// Instantiate the model
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const generativeModel = vertex_ai.preview.getGenerativeModel({
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model: model,
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});
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const req = {
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contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
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};
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const countTokensResp = await generativeModel.countTokens(req);
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console.log('count tokens response: ', countTokensResp);
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// [END aiplatform_gemini_token_count]
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}
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countTokens(...process.argv.slice(2)).catch(err => {
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console.error(err.message);
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process.exitCode = 1;
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});

‎generative-ai/snippets/nonStreamingChat.js

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// Copyright 2023 Google LLC
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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const {VertexAI} = require('@google-cloud/vertexai');
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function wait(time) {
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return new Promise(resolve => {
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setTimeout(resolve, time);
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});
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}
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async function createNonStreamingChat(
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projectId = 'PROJECT_ID',
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location = 'LOCATION_ID',
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model = 'MODEL'
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) {
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// TODO: Find better method. Setting delay to give api time to respond, otherwise it will 404
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// await wait(10);
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// [START aiplatform_gemini_multiturn_chat]
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/**
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* TODO(developer): Uncomment these variables before running the sample.
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*/
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// const projectId = 'your-project-id';
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// const location = 'us-central1';
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// Initialize Vertex with your Cloud project and location
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const vertexAI = new VertexAI({project: projectId, location: location});
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// Instantiate the model
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const generativeModel = vertexAI.preview.getGenerativeModel({
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model: model,
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});
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const chat = generativeModel.startChat({});
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const chatInput1 = 'Hello';
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console.log(`User: ${chatInput1}`);
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const result1 = await chat.sendMessage(chatInput1);
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const response1 = result1.response.candidates[0].content.parts[0].text;
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console.log('Chat bot: ', response1);
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const chatInput2 = 'Can you tell me a scientific fun fact?';
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console.log(`User: ${chatInput2}`);
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const result2 = await chat.sendMessage(chatInput2);
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const response2 = result2.response.candidates[0].content.parts[0].text;
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console.log('Chat bot: ', response2);
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const chatInput3 = 'How can I learn more about that?';
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console.log(`User: ${chatInput3}`);
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const result3 = await chat.sendMessage(chatInput3);
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const response3 = result3.response.candidates[0].content.parts[0].text;
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console.log('Chat bot: ', response3);
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// [END aiplatform_gemini_multiturn_chat]
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}
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createNonStreamingChat(...process.argv.slice(2)).catch(err => {
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console.error(err.message);
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process.exitCode = 1;
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});

‎generative-ai/snippets/nonStreamingContent.js

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// Copyright 2023 Google LLC
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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const {VertexAI} = require('@google-cloud/vertexai');
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async function createNonStreamingContent(
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projectId = 'PROJECT_ID',
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location = 'LOCATION_ID',
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model = 'MODEL'
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) {
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// [START aiplatform_gemini_function_calling]
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/**
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* TODO(developer): Uncomment these variables before running the sample.
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*/
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// const projectId = 'your-project-id';
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// const location = 'us-central1';
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// Initialize Vertex with your Cloud project and location
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const vertexAI = new VertexAI({project: projectId, location: location});
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// Instantiate the model
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const generativeModel = vertexAI.preview.getGenerativeModel({
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model: model,
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});
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const request = {
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contents: [{role: 'user', parts: [{text: 'What is Node.js?'}]}],
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};
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console.log('Prompt:');
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console.log(request.contents[0].parts[0].text);
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console.log('Non-Streaming Response Text:');
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// Create the response stream
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const responseStream = await generativeModel.generateContentStream(request);
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// Wait for the response stream to complete
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const aggregatedResponse = await responseStream.response;
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// Select the text from the response
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const fullTextResponse =
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aggregatedResponse.candidates[0].content.parts[0].text;
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console.log(fullTextResponse);
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// [END aiplatform_gemini_function_calling]
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}
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createNonStreamingContent(...process.argv.slice(2)).catch(err => {
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console.error(err.message);
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process.exitCode = 1;
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});

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