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 Gemini 1.5 Pro 處理圖片、影片、音訊和文字
透過集合功能整理內容
你可以依據偏好儲存及分類內容。
這個範例說明如何同時處理圖片、影片、音訊和文字。這個範例僅適用於 Gemini 1.5 Pro。
程式碼範例
除非另有註明,否則本頁面中的內容是採用創用 CC 姓名標示 4.0 授權,程式碼範例則為阿帕契 2.0 授權。詳情請參閱《Google Developers 網站政策》。Java 是 Oracle 和/或其關聯企業的註冊商標。
[[["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,["# Process images, video, audio, and text with Gemini 1.5 Pro\n\nThis sample shows you how to process images, video, audio, and text at the same time. This sample works with Gemini 1.5 Pro only.\n\nCode sample\n-----------\n\n### C#\n\n\nBefore trying this sample, follow the C# 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 C# API\nreference documentation](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/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\n using https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.html;\n using System;\n using System.Threading.Tasks;\n\n public class MultimodalAllInput\n {\n public async Task\u003cstring\u003e AnswerFromMultimodalInput(\n string projectId = \"your-project-id\",\n string location = \"us-central1\",\n string publisher = \"google\",\n string model = \"gemini-2.0-flash-001\")\n {\n\n var predictionServiceClient = new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.PredictionServiceClientBuilder.html\n {\n Endpoint = $\"{location}-aiplatform.googleapis.com\"\n }.Build();\n\n string prompt = \"Watch each frame in the video carefully and answer the questions.\\n\"\n + \"Only base your answers strictly on what information is available in \"\n + \"the video attached. Do not make up any information that is not part \"\n + \"of the video and do not be too verbose, be to the point.\\n\\n\"\n + \"Questions:\\n\"\n + \"- When is the moment in the image happening in the video? \"\n + \"Provide a timestamp.\\n\"\n + \"- What is the context of the moment and what does the narrator say about it?\";\n\n var generateContentRequest = new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerateContentRequest.html\n {\n Model = $\"projects/{projectId}/locations/{location}/publishers/{publisher}/models/{model}\",\n Contents =\n {\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Content.html\n {\n Role = \"USER\",\n Parts =\n {\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Part.html { Text = prompt },\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Part.html { FileData = new() { MimeType = \"video/mp4\", FileUri = \"gs://cloud-samples-data/generative-ai/video/behind_the_scenes_pixel.mp4\" } },\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Part.html { FileData = new() { MimeType = \"image/png\", FileUri = \"gs://cloud-samples-data/generative-ai/image/a-man-and-a-dog.png\" } }\n }\n }\n }\n };\n\n https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerateContentResponse.html response = await predictionServiceClient.GenerateContentAsync(generateContentRequest);\n\n string responseText = response.https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerateContentResponse.html#Google_Cloud_AIPlatform_V1_GenerateContentResponse_Candidates[0].https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Content.html.Parts[0].Text;\n Console.WriteLine(responseText);\n\n return responseText;\n }\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 analyze_all_modalities(projectId = 'PROJECT_ID') {\n const vertexAI = new https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/vertexai.html({project: projectId, location: 'us-central1'});\n\n const generativeModel = vertexAI.https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/vertexai.html({\n model: 'gemini-2.0-flash-001',\n });\n\n const videoFilePart = {\n file_data: {\n file_uri:\n 'gs://cloud-samples-data/generative-ai/video/behind_the_scenes_pixel.mp4',\n mime_type: 'video/mp4',\n },\n };\n const imageFilePart = {\n file_data: {\n file_uri:\n 'gs://cloud-samples-data/generative-ai/image/a-man-and-a-dog.png',\n mime_type: 'image/png',\n },\n };\n\n const textPart = {\n text: `\n Watch each frame in the video carefully and answer the questions.\n Only base your answers strictly on what information is available in the video attached.\n Do not make up any information that is not part of the video and do not be too\n verbose, be to the point.\n\n Questions:\n - When is the moment in the image happening in the video? Provide a timestamp.\n - What is the context of the moment and what does the narrator say about it?`,\n };\n\n const request = {\n contents: [{role: 'user', parts: [videoFilePart, imageFilePart, textPart]}],\n };\n\n const resp = await generativeModel.generateContent(request);\n const contentResponse = await resp.response;\n console.log(JSON.stringify(contentResponse));\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)."]]