add vertex js sdj example

tests/pass_through_tests/test_vertex.js

@@ -0,0 +1,43 @@
+
+const {
+    FunctionDeclarationSchemaType,
+    HarmBlockThreshold,
+    HarmCategory,
+    VertexAI,
+    RequestOptions
+  } = require('@google-cloud/vertexai');
+  
+  const project = 'adroit-crow-413218';
+  const location = 'us-central1';
+  const textModel =  'gemini-1.0-pro';
+  const visionModel = 'gemini-1.0-pro-vision';
+
+  
+  const vertexAI = new VertexAI({project: project, location: location, apiEndpoint: "localhost:4000/vertex-ai"});
+  
+  // Instantiate Gemini models
+  const generativeModel = vertexAI.getGenerativeModel({
+      model: textModel,
+      // The following parameters are optional
+      // They can also be passed to individual content generation requests
+      safetySettings: [{category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE}],
+      generationConfig: {maxOutputTokens: 256},
+      systemInstruction: {
+        role: 'system',
+        parts: [{"text": `For example, you are a helpful customer service agent. tell me your name. in 5 pages`}]
+      },
+  })
+
+async function streamGenerateContent() {
+    const request = {
+      contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+    };
+    const streamingResult = await generativeModel.generateContentStream(request);
+    for await (const item of streamingResult.stream) {
+      console.log('stream chunk: ', JSON.stringify(item));
+    }
+    const aggregatedResponse = await streamingResult.response;
+    console.log('aggregated response: ', JSON.stringify(aggregatedResponse));
+  };
+  
+  streamGenerateContent();