YouTube-Videos mit Gemini zusammenfassen
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In diesem Beispiel wird gezeigt, wie Sie mit Gemini YouTube-Videos zusammenfassen.
Codebeispiel
Nächste Schritte
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[[["Leicht verständlich","easyToUnderstand","thumb-up"],["Mein Problem wurde gelöst","solvedMyProblem","thumb-up"],["Sonstiges","otherUp","thumb-up"]],[["Schwer verständlich","hardToUnderstand","thumb-down"],["Informationen oder Beispielcode falsch","incorrectInformationOrSampleCode","thumb-down"],["Benötigte Informationen/Beispiele nicht gefunden","missingTheInformationSamplesINeed","thumb-down"],["Problem mit der Übersetzung","translationIssue","thumb-down"],["Sonstiges","otherDown","thumb-down"]],[],[],[],null,["# Use Gemini to summarize YouTube videos\n\nThis sample demonstrates how to use Gemini to summarize YouTube videos.\n\nCode sample\n-----------\n\n### Go\n\n\nBefore trying this sample, follow the Go 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 Go API\nreference documentation](/go/docs/reference/cloud.google.com/go/aiplatform/latest/apiv1).\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 import (\n \t\"context\"\n \t\"fmt\"\n \t\"io\"\n\n \tgenai \"google.golang.org/genai\"\n )\n\n // generateWithYTVideo shows how to generate text using a YouTube video as input.\n func generateWithYTVideo(w io.Writer) error {\n \tctx := context.Background()\n\n \tclient, err := genai.NewClient(ctx, &genai.ClientConfig{\n \t\tHTTPOptions: genai.HTTPOptions{APIVersion: \"v1\"},\n \t})\n \tif err != nil {\n \t\treturn fmt.Errorf(\"failed to create genai client: %w\", err)\n \t}\n\n \tmodelName := \"gemini-2.5-flash\"\n \tcontents := []*genai.Content{\n \t\t{Parts: []*genai.Part{\n \t\t\t{Text: \"Write a short and engaging blog post based on this video.\"},\n \t\t\t{FileData: &genai.FileData{\n \t\t\t\tFileURI: \"https://www.youtube.com/watch?v=3KtWfp0UopM\",\n \t\t\t\tMIMEType: \"video/mp4\",\n \t\t\t}},\n \t\t},\n \t\t\tRole: \"user\"},\n \t}\n\n \tresp, err := client.Models.GenerateContent(ctx, modelName, contents, nil)\n \tif err != nil {\n \t\treturn fmt.Errorf(\"failed to generate content: %w\", err)\n \t}\n\n \trespText := resp.Text()\n\n \tfmt.Fprintln(w, respText)\n\n \t// Example response:\n \t// Okay, here's a short and engaging blog post based on the provided video.\n \t//\n \t// **Google's 25th: A Look Back at What We've Searched**\n \t// ...\n\n \treturn nil\n }\n\n### Python\n\n\nBefore trying this sample, follow the Python 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 Python API\nreference documentation](/python/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 from google import genai\n from google.genai.types import HttpOptions, Part\n\n client = genai.Client(http_options=HttpOptions(api_version=\"v1\"))\n model_id = \"gemini-2.5-flash\"\n\n response = client.models.generate_content(\n model=model_id,\n contents=[\n Part.from_uri(\n file_uri=\"https://www.youtube.com/watch?v=3KtWfp0UopM\",\n mime_type=\"video/mp4\",\n ),\n \"Write a short and engaging blog post based on this video.\",\n ],\n )\n\n print(response.text)\n # Example response:\n # Here's a short blog post based on the video provided:\n #\n # **Google Turns 25: A Quarter Century of Search!**\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=googlegenaisdk)."]]