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chore: update ai package versions
fix: fix broken tests fix: update dependency to use github over npm feat: change assertion to more common output added function calling examples removed double await, fix linter
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‎generative-ai/snippets/functionCallingStreamChat.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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// [START aiplatform_gemini_function_calling_chat]
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const {
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VertexAI,
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FunctionDeclarationSchemaType
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} = require('@google-cloud/vertexai');
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const functionDeclarations = [
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{
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function_declarations: [
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{
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name: 'get_current_weather',
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description: 'get weather in a given location',
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parameters: {
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type: FunctionDeclarationSchemaType.OBJECT,
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properties: {
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location: { type: FunctionDeclarationSchemaType.STRING },
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unit: {
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type: FunctionDeclarationSchemaType.STRING,
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enum: ['celsius', 'fahrenheit'],
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},
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},
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required: ['location'],
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},
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},
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],
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},
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];
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const functionResponseParts = [
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{
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functionResponse: {
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name: 'get_current_weather',
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response:
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{ name: 'get_current_weather', content: { weather: 'super nice' } },
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},
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},
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];
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/**
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* TODO(developer): Update these variables before running the sample.
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*/
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async function functionCallingStreamChat(
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projectId = 'PROJECT_ID',
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location = 'us-central1',
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model = 'gemini-pro'
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) {
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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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// Create a chat session and pass your function declarations
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const chat = generativeModel.startChat({
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tools: functionDeclarations,
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});
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const chatInput1 = 'What is the weather in Boston?';
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// This should include a functionCall response from the model
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const result1 = await chat.sendMessageStream(chatInput1);
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for await (const item of result1.stream) {
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console.log(item.candidates[0]);
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}
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const response1 = await result1.response;
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// Send a follow up message with a FunctionResponse
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const result2 = await chat.sendMessageStream(functionResponseParts);
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for await (const item of result2.stream) {
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console.log(item.candidates[0]);
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}
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// This should include a text response from the model using the response content
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// provided above
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const response2 = await result2.response;
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console.log(response2.candidates[0].content.parts[0].text);
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}
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// [END aiplatform_gemini_function_calling_chat]
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functionCallingStreamChat(...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/functionCallingStreamContent.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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// [START aiplatform_gemini_function_calling_content]
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const { VertexAI, FunctionDeclarationSchemaType } = require('@google-cloud/vertexai');
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const functionDeclarations = [
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{
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function_declarations: [
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{
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name: 'get_current_weather',
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description: 'get weather in a given location',
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parameters: {
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type: FunctionDeclarationSchemaType.OBJECT,
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properties: {
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location: {type: FunctionDeclarationSchemaType.STRING},
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unit: {
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type: FunctionDeclarationSchemaType.STRING,
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enum: ['celsius', 'fahrenheit'],
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},
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},
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required: ['location'],
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},
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},
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],
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},
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];
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const functionResponseParts = [
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{
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functionResponse: {
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name: 'get_current_weather',
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response:
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{name: 'get_current_weather', content: {weather: 'super nice'}},
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},
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},
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];
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/**
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* TODO(developer): Update these variables before running the sample.
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*/
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async function functionCallingStreamChat(
54+
projectId = 'PROJECT_ID',
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location = 'us-central1',
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model = 'gemini-pro'
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) {
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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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61+
// 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: [
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{role: 'user', parts: [{text: 'What is the weather in Boston?'}]},
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{role: 'model', parts: [{functionCall: {name: 'get_current_weather', args: {'location': 'Boston'}}}]},
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{role: 'function', parts: functionResponseParts}
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],
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tools: functionDeclarations,
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};
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const streamingResp =
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await generativeModel.generateContentStream(request);
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for await (const item of streamingResp.stream) {
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console.log(item.candidates[0].content.parts[0].text);
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}
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}
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// [END aiplatform_gemini_function_calling_content]
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functionCallingStreamChat(...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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@@ -37,20 +37,23 @@ async function createNonStreamingChat(
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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 response1 = result1.response;
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const text1 = response1.candidates[0].content.parts[0].text;
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console.log('Chat bot: ', text1);
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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 response2 = await result2.response;
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const text2 = response2.candidates[0].content.parts[0].text;
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console.log('Chat bot: ', text2);
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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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const response3 = await result3.response;
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const text3 = response3.candidates[0].content.parts[0].text;
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console.log('Chat bot: ', text3);
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}
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// [END aiplatform_gemini_multiturn_chat_nonstreaming]
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‎generative-ai/snippets/nonStreamingMultipartContent.js

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};
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console.log('Prompt Text:');
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console.log(request.contents[0].parts[0].text);
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console.log(request.contents[0].parts[1].text);
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console.log('Non-Streaming Response Text:');
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// Create the response stream

‎generative-ai/snippets/package.json

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"test": "c8 mocha -p -j 2 --timeout 2400000 test/*.test.js"
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},
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"dependencies": {
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"@google-cloud/aiplatform": "^3.0.0",
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"@google-cloud/aiplatform": "^3.12.0",
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"@google-cloud/vertexai": "github:googleapis/nodejs-vertexai",
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"axios": "^1.6.2",
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"supertest": "^6.3.3"

‎generative-ai/snippets/safetySettings.js

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@@ -59,14 +59,15 @@ async function setSafetySettings(
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for await (const item of responseStream.stream) {
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if (item.candidates[0].finishReason === 'SAFETY') {
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console.log('This response stream terminated due to safety concerns.');
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break;
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} else {
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process.stdout.write(item.candidates[0].content.parts[0].text);
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}
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}
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}
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// [END aiplatform_gemini_safety_settings]
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setSafetySettings(...process.argv.slice(3)).catch(err => {
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setSafetySettings(...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/streamMultipartContent.js

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};
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console.log('Prompt Text:');
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console.log(request.contents[0].parts[0].text);
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console.log(request.contents[0].parts[1].text);
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console.log('Streaming Response Text:');
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// Create the response stream

‎generative-ai/snippets/test/functionCallingStreamChat.test.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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//
7+
// https://www.apache.org/licenses/LICENSE-2.0
8+
//
9+
// Unless required by applicable law or agreed to in writing, software
10+
// distributed under the License is distributed on an "AS IS" BASIS,
11+
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
// See the License for the specific language governing permissions and
13+
// limitations under the License.
14+
15+
'use strict';
16+
17+
const {assert} = require('chai');
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const {describe, it} = require('mocha');
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const cp = require('child_process');
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const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
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describe('Generative AI Function Calling Stream Chat', () => {
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const project = 'cloud-llm-preview1';
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const location = 'us-central1';
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const model = 'gemini-pro';
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28+
it('should create stream chat and begin the conversation the same in each instance', async () => {
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const output = execSync(
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`node ./functionCallingStreamChat.js ${project} ${location} ${model}`
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);
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// Assert that the response is what we expect
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assert(output.match(/The weather in Boston is super nice./));
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});
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});

‎generative-ai/snippets/test/functionCallingStreamContent.test.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");
4+
// you may not use this file except in compliance with the License.
5+
// You may obtain a copy of the License at
6+
//
7+
// https://www.apache.org/licenses/LICENSE-2.0
8+
//
9+
// Unless required by applicable law or agreed to in writing, software
10+
// distributed under the License is distributed on an "AS IS" BASIS,
11+
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
// See the License for the specific language governing permissions and
13+
// limitations under the License.
14+
15+
'use strict';
16+
17+
const {assert} = require('chai');
18+
const {describe, it} = require('mocha');
19+
const cp = require('child_process');
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const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
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23+
describe('Generative AI Function Calling Stream Content', () => {
24+
const project = 'cloud-llm-preview1';
25+
const location = 'us-central1';
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const model = 'gemini-pro';
27+
28+
it('should create stream chat and begin the conversation the same in each instance', async () => {
29+
const output = execSync(
30+
`node ./functionCallingStreamContent.js ${project} ${location} ${model}`
31+
);
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33+
// Assert that the response is what we expect
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assert(output.match(/The weather in Boston is super nice./));
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});
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});

‎generative-ai/snippets/test/sendMultiModalPromptWithImage.test.js

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`node ./sendMultiModalPromptWithImage.js ${project} ${location} ${model}`
3131
);
3232
// Ensure that the conversation is what we expect for these images
33-
assert(output.match(/Paris/));
33+
assert(output.match(/city: Rio de Janeiro, Landmark: Christ the Redeemer/));
3434
});
3535
});

‎generative-ai/snippets/test/sendMultiModalPromptWithVideo.test.js

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`node ./sendMultiModalPromptWithVideo.js ${project} ${location} ${model}`
3131
);
3232
// Ensure that the conversation is what we expect for these images
33-
assert(output.match(/advertisement/));
33+
assert(output.match(/Zootopia/));
3434
});
3535
});

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