generative-ai/snippets/inference/streamMultiModalityBasic.js (39 lines of code) (raw):

// Copyright 2024 Google LLC // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // https://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // [START generativeaionvertexai_stream_multimodality_basic] const {VertexAI} = require('@google-cloud/vertexai'); /** * TODO(developer): Update these variables before running the sample. */ const PROJECT_ID = process.env.CAIP_PROJECT_ID; const LOCATION = process.env.LOCATION; const MODEL = 'gemini-2.0-flash-001'; async function generateContent() { // Initialize Vertex AI const vertexAI = new VertexAI({project: PROJECT_ID, location: LOCATION}); const generativeModel = vertexAI.getGenerativeModel({model: MODEL}); const request = { contents: [ { role: 'user', parts: [ { file_data: { file_uri: 'gs://cloud-samples-data/video/animals.mp4', mime_type: 'video/mp4', }, }, { file_data: { file_uri: 'gs://cloud-samples-data/generative-ai/image/character.jpg', mime_type: 'image/jpeg', }, }, {text: 'Are this video and image correlated?'}, ], }, ], }; const result = await generativeModel.generateContentStream(request); for await (const item of result.stream) { console.log(item.candidates[0].content.parts[0].text); } } // [END generativeaionvertexai_stream_multimodality_basic] generateContent().catch(err => { console.error(err.message); process.exitCode = 1; });