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refactor(generative-ai): migrate first batch of samples to @google/genai #4330

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aa40ac1
refactor: migrate countTokens samples to @google/genai, update config…
angelcaamal May 29, 2026
b25e80d
refactor(samples): migrate function-calling samples to @google/genai …
angelcaamal May 29, 2026
bc5bfdd
feat(generative-ai): migrate grounding samples to new GenAI SDK
angelcaamal Jun 2, 2026
26802e4
feat(generative-ai): migrate text and multimodal inference samples to…
angelcaamal Jun 2, 2026
e7a3c67
refactor(generative-ai): migrate first batch of inference samples to …
angelcaamal Jun 2, 2026
320b41a
Merge branch 'main' into refactor/migrate-vertexai-to-genai
angelcaamal Jun 2, 2026
01ac864
refactor(generative-ai): update model to gemini-2.5-flash and fix str…
angelcaamal Jun 2, 2026
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33 changes: 19 additions & 14 deletions generative-ai/snippets/count-tokens/countTokens.js
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Original file line number Diff line number Diff line change
Expand Up @@ -13,37 +13,42 @@
// limitations under the License.

// [START generativeaionvertexai_gemini_token_count]
const {VertexAI} = require('@google-cloud/vertexai');
const {GoogleGenAI} = require('@google/genai');

/**
* TODO(developer): Update these variables before running the sample.
*/
async function countTokens(
projectId = 'PROJECT_ID',
location = 'us-central1',
model = 'gemini-2.0-flash-001'
model = 'gemini-2.5-flash'
) {
// Initialize Vertex with your Cloud project and location
const vertexAI = new VertexAI({project: projectId, location: location});

// Instantiate the model
const generativeModel = vertexAI.getGenerativeModel({
model: model,
// Initialize the client with your Cloud project and location
const client = new GoogleGenAI({
vertexai: true,
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@amcolin amcolin Jun 2, 2026

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Out of curiosity why we are keeping this flag?

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@angelcaamal angelcaamal Jun 2, 2026

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The vertexai: true flag is a switch that tells the SDK: Connect to the enterprise version of Google Cloud.
If you leave it out, the code assumes you are a standard user and will ask for a traditional API Key

project: projectId,
location: location,
});

const req = {
contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
};
const contents = [
{role: 'user', parts: [{text: 'How are you doing today?'}]},
];

// Prompt tokens count
const countTokensResp = await generativeModel.countTokens(req);
const countTokensResp = await client.models.countTokens({
model: model,
contents: contents,
});
console.log('Prompt tokens count: ', countTokensResp);

// Send text to gemini
const result = await generativeModel.generateContent(req);
const result = await client.models.generateContent({
model: model,
contents: contents,
});

// Response tokens count
const usageMetadata = result.response.usageMetadata;
const usageMetadata = result.usageMetadata;
console.log('Response tokens count: ', usageMetadata);
}
// [END generativeaionvertexai_gemini_token_count]
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65 changes: 32 additions & 33 deletions generative-ai/snippets/count-tokens/countTokensAdvanced.js
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Original file line number Diff line number Diff line change
Expand Up @@ -13,52 +13,51 @@
// limitations under the License.

// [START generativeaionvertexai_gemini_token_count_advanced]
const {VertexAI} = require('@google-cloud/vertexai');

const {GoogleGenAI} = require('@google/genai');
/**
* TODO(developer): Update these variables before running the sample.
*/
async function countTokens(
projectId = 'PROJECT_ID',
location = 'us-central1',
model = 'gemini-2.0-flash-001'
model = 'gemini-2.5-flash'
) {
// Initialize Vertex with your Cloud project and location
const vertexAI = new VertexAI({project: projectId, location: location});

// Instantiate the model
const generativeModel = vertexAI.getGenerativeModel({
model: model,
// Initialize client with your Cloud project and location
const client = new GoogleGenAI({
vertexai: true,
project: projectId,
location: location,
});

const req = {
contents: [
{
role: 'user',
parts: [
{
file_data: {
file_uri:
'gs://cloud-samples-data/generative-ai/video/pixel8.mp4',
mime_type: 'video/mp4',
},
const contents = [
{
role: 'user',
parts: [
{
fileData: {
fileUri: 'gs://cloud-samples-data/generative-ai/video/pixel8.mp4',
mimeType: 'video/mp4',
},
{text: 'Provide a description of the video.'},
],
},
],
};
},
{text: 'Provide a description of the video.'},
],
},
];

const countTokensResp = await client.models.countTokens({
model: model,
contents: contents,
});

const countTokensResp = await generativeModel.countTokens(req);
console.log('Prompt Token Count:', countTokensResp.totalTokens);
console.log(
'Prompt Character Count:',
countTokensResp.totalBillableCharacters
);

// Sent text to Gemini
const result = await generativeModel.generateContent(req);
const usageMetadata = result.response.usageMetadata;
// Send text to Gemini
const result = await client.models.generateContent({
model: model,
contents: contents,
});

const usageMetadata = result.usageMetadata;

console.log('Prompt Token Count:', usageMetadata.promptTokenCount);
console.log('Candidates Token Count:', usageMetadata.candidatesTokenCount);
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68 changes: 27 additions & 41 deletions generative-ai/snippets/function-calling/functionCallingAdvanced.js
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Original file line number Diff line number Diff line change
Expand Up @@ -13,32 +13,28 @@
// limitations under the License.

// [START generativeaionvertexai_function_calling_advanced]
const {
VertexAI,
FunctionDeclarationSchemaType,
} = require('@google-cloud/vertexai');
const {GoogleGenAI} = require('@google/genai');

const functionDeclarations = [
const tools = [
{
function_declarations: [
functionDeclarations: [
{
name: 'get_product_sku',
description:
'Get the available inventory for a Google products, e.g: Pixel phones, Pixel Watches, Google Home etc',
description: 'Get the available inventory for Google products',
parameters: {
type: FunctionDeclarationSchemaType.OBJECT,
type: 'OBJECT',
properties: {
productName: {type: FunctionDeclarationSchemaType.STRING},
productName: {type: 'STRING'},
},
},
},
{
name: 'get_store_location',
description: 'Get the location of the closest store',
parameters: {
type: FunctionDeclarationSchemaType.OBJECT,
type: 'OBJECT',
properties: {
location: {type: FunctionDeclarationSchemaType.STRING},
location: {type: 'STRING'},
},
},
},
Expand All @@ -47,49 +43,39 @@ const functionDeclarations = [
];

const toolConfig = {
function_calling_config: {
functionCallingConfig: {
mode: 'ANY',
allowed_function_names: ['get_product_sku'],
allowedFunctionNames: ['get_product_sku'],
},
};

const generationConfig = {
temperature: 0.95,
topP: 1.0,
maxOutputTokens: 8192,
};

/**
* TODO(developer): Update these variables before running the sample.
*/
async function functionCallingAdvanced(
projectId = 'PROJECT_ID',
location = 'us-central1',
model = 'gemini-2.0-flash-001'
model = 'gemini-2.5-flash'
) {
// Initialize Vertex with your Cloud project and location
const vertexAI = new VertexAI({project: projectId, location: location});
// Initialize client with your Cloud project and location
const client = new GoogleGenAI({
vertexai: true,
project: projectId,
location: location,
});

// Instantiate the model
const generativeModel = vertexAI.preview.getGenerativeModel({
const result = await client.models.generateContent({
model: model,
contents: 'Do you have the White Pixel 8 Pro 128GB in stock in the US?',
config: {
tools: tools,
toolConfig: toolConfig,
temperature: 0.95,
topP: 1.0,
maxOutputTokens: 8192,
},
});

const request = {
contents: [
{
role: 'user',
parts: [
{text: 'Do you have the White Pixel 8 Pro 128GB in stock in the US?'},
],
},
],
tools: functionDeclarations,
tool_config: toolConfig,
generation_config: generationConfig,
};
const result = await generativeModel.generateContent(request);
console.log(JSON.stringify(result.response.candidates[0].content));
console.log(JSON.stringify(result.functionCalls));
}
// [END generativeaionvertexai_function_calling_advanced]

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42 changes: 19 additions & 23 deletions generative-ai/snippets/function-calling/functionCallingBasic.js
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Original file line number Diff line number Diff line change
Expand Up @@ -13,23 +13,20 @@
// limitations under the License.

// [START generativeaionvertexai_function_calling_basic]
const {
VertexAI,
FunctionDeclarationSchemaType,
} = require('@google-cloud/vertexai');
const {GoogleGenAI} = require('@google/genai');

const functionDeclarations = [
const tools = [
{
function_declarations: [
functionDeclarations: [
{
name: 'get_current_weather',
description: 'get weather in a given location',
parameters: {
type: FunctionDeclarationSchemaType.OBJECT,
type: 'OBJECT',
properties: {
location: {type: FunctionDeclarationSchemaType.STRING},
location: {type: 'STRING'},
unit: {
type: FunctionDeclarationSchemaType.STRING,
type: 'STRING',
enum: ['celsius', 'fahrenheit'],
},
},
Expand All @@ -46,24 +43,23 @@ const functionDeclarations = [
async function functionCallingBasic(
projectId = 'PROJECT_ID',
location = 'us-central1',
model = 'gemini-2.0-flash-001'
model = 'gemini-2.5-flash'
) {
// Initialize Vertex with your Cloud project and location
const vertexAI = new VertexAI({project: projectId, location: location});
// Initialize client with your Cloud project and location
const client = new GoogleGenAI({
vertexai: true,
project: projectId,
location: location,
});

// Instantiate the model
const generativeModel = vertexAI.preview.getGenerativeModel({
const result = await client.models.generateContent({
model: model,
contents: 'What is the weather in Boston?',
config: {
tools: tools,
},
});

const request = {
contents: [
{role: 'user', parts: [{text: 'What is the weather in Boston?'}]},
],
tools: functionDeclarations,
};
const result = await generativeModel.generateContent(request);
console.log(JSON.stringify(result.response.candidates[0].content));
console.log(JSON.stringify(result.functionCalls));
}
// [END generativeaionvertexai_function_calling_basic]

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