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# 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
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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/index.js

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

‎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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