自 2025 年 4 月 29 日起,Gemini 1.5 Pro 和 Gemini 1.5 Flash 模型將無法用於先前未使用這些模型的專案,包括新專案。詳情請參閱「
模型版本和生命週期」。
使用聊天機器人產生互動式文字串流
透過集合功能整理內容
你可以依據偏好儲存及分類內容。
這個範例說明如何使用 Gemini 模型以互動方式生成文字串流。
程式碼範例
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[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],[],[],[],null,["# Interactive text stream generation with a chatbot\n\nThis sample demonstrates how to use the Gemini model to generate text stream interactively.\n\nCode sample\n-----------\n\n### Node.js\n\n\nBefore trying this sample, follow the Node.js setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Node.js API\nreference documentation](/nodejs/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n const {VertexAI} = require('https://cloud.google.com/nodejs/docs/reference/vertexai/latest/overview.html');\n\n /**\n * TODO(developer): Update these variables before running the sample.\n */\n async function createStreamChat(\n projectId = 'PROJECT_ID',\n location = 'us-central1',\n model = 'gemini-2.0-flash-001'\n ) {\n // Initialize Vertex with your Cloud project and location\n const vertexAI = new https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/vertexai.html({project: projectId, location: location});\n\n // Instantiate the model\n const generativeModel = vertexAI.https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/vertexai.html({\n model: model,\n });\n\n const chat = generativeModel.startChat({});\n const chatInput1 = 'How can I learn more about that?';\n\n console.log(`User: ${chatInput1}`);\n\n const result1 = await chat.sendMessageStream(chatInput1);\n for await (const item of result1.https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/streamgeneratecontentresult.html) {\n console.log(item.https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/generatecontentresponse.html[0].https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/generatecontentcandidate.html.https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/content.html[0].text);\n }\n }\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=generativeaionvertexai)."]]