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added function calling examples
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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 { 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(
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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(
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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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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/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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//
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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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'use strict';
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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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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");
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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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'use strict';
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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 Content', () => {
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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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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 ./functionCallingStreamContent.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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});

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