GoogleCloudPlatform · angelcaamal · Jun 4, 2026 · Jun 4, 2026 · Jun 4, 2026 · Jun 4, 2026
@@ -13,30 +13,33 @@
 // limitations under the License.
 
 // [START generativeaionvertexai_gemini_all_modalities]
-const {VertexAI} = require('@google-cloud/vertexai');
+const {GoogleGenAI} = require('@google/genai');
 
 /**
  * TODO(developer): Update these variables before running the sample.
  */
-async function analyze_all_modalities(projectId = 'PROJECT_ID') {
-  const vertexAI = new VertexAI({project: projectId, location: 'us-central1'});
-
-  const generativeModel = vertexAI.getGenerativeModel({
-    model: 'gemini-2.0-flash-001',
+async function analyze_all_modalities(
+  projectId = 'PROJECT_ID',
+  model = 'gemini-2.5-flash'
+) {
+  const client = new GoogleGenAI({
+    vertexai: true,
+    project: projectId,
+    location: 'us-central1',
   });
 
   const videoFilePart = {
-    file_data: {
-      file_uri:
+    fileData: {
+      fileUri:
         'gs://cloud-samples-data/generative-ai/video/behind_the_scenes_pixel.mp4',
-      mime_type: 'video/mp4',
+      mimeType: 'video/mp4',
     },
   };
   const imageFilePart = {
-    file_data: {
-      file_uri:
+    fileData: {
+      fileUri:
         'gs://cloud-samples-data/generative-ai/image/a-man-and-a-dog.png',
-      mime_type: 'image/png',
+      mimeType: 'image/png',
     },
   };
 
@@ -52,13 +55,12 @@ async function analyze_all_modalities(projectId = 'PROJECT_ID') {
     - What is the context of the moment and what does the narrator say about it?`,
   };
 
-  const request = {
-    contents: [{role: 'user', parts: [videoFilePart, imageFilePart, textPart]}],
-  };
+  const response = await client.models.generateContent({
+    model: model,
+    contents: [videoFilePart, imageFilePart, textPart],
+  });
 
-  const resp = await generativeModel.generateContent(request);
-  const contentResponse = await resp.response;
-  console.log(JSON.stringify(contentResponse));
+  console.log(response.text);
 }
 // [END generativeaionvertexai_gemini_all_modalities]
 

@@ -13,22 +13,24 @@
 // limitations under the License.
 
 // [START generativeaionvertexai_gemini_audio_summarization]
-const {VertexAI} = require('@google-cloud/vertexai');
-
+const {GoogleGenAI} = require('@google/genai');
 /**
  * TODO(developer): Update these variables before running the sample.
  */
-async function summarize_audio(projectId = 'PROJECT_ID') {
-  const vertexAI = new VertexAI({project: projectId, location: 'us-central1'});
-
-  const generativeModel = vertexAI.getGenerativeModel({
-    model: 'gemini-2.0-flash-001',
+async function summarize_audio(
+  projectId = 'PROJECT_ID',
+  model = 'gemini-2.5-flash'
+) {
+  const client = new GoogleGenAI({
+    vertexai: true,
+    project: projectId,
+    location: 'us-central1',
   });
 
   const filePart = {
-    file_data: {
-      file_uri: 'gs://cloud-samples-data/generative-ai/audio/pixel.mp3',
-      mime_type: 'audio/mpeg',
+    fileData: {
+      fileUri: 'gs://cloud-samples-data/generative-ai/audio/pixel.mp3',
+      mimeType: 'audio/mpeg',
     },
   };
   const textPart = {
@@ -38,13 +40,12 @@ async function summarize_audio(projectId = 'PROJECT_ID') {
     Do not make up any information that is not part of the audio and do not be verbose.`,
   };
 
-  const request = {
-    contents: [{role: 'user', parts: [filePart, textPart]}],
-  };
+  const response = await client.models.generateContent({
+    model: model,
+    contents: [filePart, textPart],
+  });
 
-  const resp = await generativeModel.generateContent(request);
-  const contentResponse = await resp.response;
-  console.log(JSON.stringify(contentResponse));
+  console.log(response.text);
 }
 // [END generativeaionvertexai_gemini_audio_summarization]
 

@@ -13,22 +13,25 @@
 // limitations under the License.
 
 // [START generativeaionvertexai_gemini_audio_transcription]
-const {VertexAI} = require('@google-cloud/vertexai');
+const {GoogleGenAI} = require('@google/genai');
 
 /**
  * TODO(developer): Update these variables before running the sample.
  */
-async function transcript_audio(projectId = 'PROJECT_ID') {
-  const vertexAI = new VertexAI({project: projectId, location: 'us-central1'});
-
-  const generativeModel = vertexAI.getGenerativeModel({
-    model: 'gemini-2.0-flash-001',
+async function transcript_audio(
+  projectId = 'PROJECT_ID',
+  model = 'gemini-2.5-flash'
+) {
+  const client = new GoogleGenAI({
+    vertexai: true,
+    project: projectId,
+    location: 'us-central1',
   });
 
   const filePart = {
-    file_data: {
-      file_uri: 'gs://cloud-samples-data/generative-ai/audio/pixel.mp3',
-      mime_type: 'audio/mpeg',
+    fileData: {
+      fileUri: 'gs://cloud-samples-data/generative-ai/audio/pixel.mp3',
+      mimeType: 'audio/mpeg',
     },
   };
   const textPart = {
@@ -37,13 +40,12 @@ async function transcript_audio(projectId = 'PROJECT_ID') {
     Use speaker A, speaker B, etc. to identify speakers.`,
   };
 
-  const request = {
-    contents: [{role: 'user', parts: [filePart, textPart]}],
-  };
+  const response = await client.models.generateContent({
+    model: model,
+    contents: [filePart, textPart],
+  });
 
-  const resp = await generativeModel.generateContent(request);
-  const contentResponse = await resp.response;
-  console.log(JSON.stringify(contentResponse));
+  console.log(response.text);
 }
 // [END generativeaionvertexai_gemini_audio_transcription]
 

@@ -13,16 +13,19 @@
 // limitations under the License.
 
 // [START generativeaionvertexai_gemini_pdf]
-const {VertexAI} = require('@google-cloud/vertexai');
+const {GoogleGenAI} = require('@google/genai');
 
 /**
  * TODO(developer): Update these variables before running the sample.
  */
-async function analyze_pdf(projectId = 'PROJECT_ID') {
-  const vertexAI = new VertexAI({project: projectId, location: 'us-central1'});
-
-  const generativeModel = vertexAI.getGenerativeModel({
-    model: 'gemini-2.0-flash-001',
+async function analyze_pdf(
+  projectId = 'PROJECT_ID',
+  model = 'gemini-2.5-flash'
+) {
+  const client = new GoogleGenAI({
+    vertexai: true,
+    project: projectId,
+    location: 'us-central1',
   });
 
   const filePart = {
@@ -31,19 +34,19 @@ async function analyze_pdf(projectId = 'PROJECT_ID') {
       mimeType: 'application/pdf',
     },
   };
+
   const textPart = {
     text: `
     You are a very professional document summarization specialist.
     Please summarize the given document.`,
   };
 
-  const request = {
-    contents: [{role: 'user', parts: [filePart, textPart]}],
-  };
+  const response = await client.models.generateContent({
+    model: model,
+    contents: [filePart, textPart],
+  });
 
-  const resp = await generativeModel.generateContent(request);
-  const contentResponse = await resp.response;
-  console.log(JSON.stringify(contentResponse));
+  console.log(response.text);
 }
 // [END generativeaionvertexai_gemini_pdf]
 

@@ -13,22 +13,19 @@
 // limitations under the License.
 
 // [START generativeaionvertexai_gemini_system_instruction]
-const {VertexAI} = require('@google-cloud/vertexai');
+const {GoogleGenAI} = require('@google/genai');
 
 /**
  * TODO(developer): Update these variables before running the sample.
  */
-async function set_system_instruction(projectId = 'PROJECT_ID') {
-  const vertexAI = new VertexAI({project: projectId, location: 'us-central1'});
-
-  const generativeModel = vertexAI.getGenerativeModel({
-    model: 'gemini-2.0-flash-001',
-    systemInstruction: {
-      parts: [
-        {text: 'You are a helpful language translator.'},
-        {text: 'Your mission is to translate text in English to French.'},
-      ],
-    },
+async function set_system_instruction(
+  projectId = 'PROJECT_ID',
+  model = 'gemini-2.5-flash'
+) {
+  const client = new GoogleGenAI({
+    vertexai: true,
+    project: projectId,
+    location: 'us-central1',
   });
 
   const textPart = {
@@ -37,13 +34,20 @@ async function set_system_instruction(projectId = 'PROJECT_ID') {
     Answer:`,
   };
 
-  const request = {
-    contents: [{role: 'user', parts: [textPart]}],
-  };
+  const response = await client.models.generateContent({
+    model: model,
+    contents: [textPart],
+    config: {
+      systemInstruction: {
+        parts: [
+          {text: 'You are a helpful language translator.'},
+          {text: 'Your mission is to translate text in English to French.'},
+        ],
+      },
+    },
+  });
 
-  const resp = await generativeModel.generateContent(request);
-  const contentResponse = await resp.response;
-  console.log(JSON.stringify(contentResponse));
+  console.log(response.text);
 }
 // [END generativeaionvertexai_gemini_system_instruction]
 

@@ -13,24 +13,29 @@
 // limitations under the License.
 
 // [START generativeaionvertexai_gemini_generate_from_text_input]
-const {VertexAI} = require('@google-cloud/vertexai');
-
+const {GoogleGenAI} = require('@google/genai');
 /**
  * TODO(developer): Update these variables before running the sample.
  */
-async function generate_from_text_input(projectId = 'PROJECT_ID') {
-  const vertexAI = new VertexAI({project: projectId, location: 'us-central1'});
-
-  const generativeModel = vertexAI.getGenerativeModel({
-    model: 'gemini-2.0-flash-001',
+async function generate_from_text_input(
+  projectId = 'PROJECT_ID',
+  model = 'gemini-2.5-flash'
+) {
+  const client = new GoogleGenAI({
+    vertexai: true,
+    project: projectId,
+    location: 'us-central1',
   });
 
   const prompt =
     "What's a good name for a flower shop that specializes in selling bouquets of dried flowers?";
 
-  const resp = await generativeModel.generateContent(prompt);
-  const contentResponse = await resp.response;
-  console.log(JSON.stringify(contentResponse));
+  const response = await client.models.generateContent({
+    model: model,
+    contents: prompt,
+  });
+
+  console.log(response.text);
 }
 // [END generativeaionvertexai_gemini_generate_from_text_input]