Videos mit Veo 3 erstellen

import time
from google import genai

client = genai.Client()

prompt = "Panning wide shot of a calico kitten sleeping in the sunshine"

# Step 1: Generate an image with Imagen.
imagen = client.models.generate_images(
    model="imagen-3.0-generate-002",
    prompt=prompt,
)

# Step 2: Generate video with Veo 3 using the image.
operation = client.models.generate_videos(
    model="veo-3.0-generate-preview",
    prompt=prompt,
    image=imagen.generated_images[0].image,
)

# Poll the operation status until the video is ready.
while not operation.done:
    print("Waiting for video generation to complete...")
    time.sleep(10)
    operation = client.operations.get(operation)

# Download the video.
video = operation.response.generated_videos[0]
client.files.download(file=video.video)
video.video.save("veo3_with_image_input.mp4")
print("Generated video saved to veo3_with_image_input.mp4")

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const prompt = "Panning wide shot of a calico kitten sleeping in the sunshine";

// Step 1: Generate an image with Imagen.
const imagenResponse = await ai.models.generateImages({
  model: "imagen-3.0-generate-002",
  prompt: prompt,
});

// Step 2: Generate video with Veo 3 using the image.
let operation = await ai.models.generateVideos({
  model: "veo-3.0-generate-preview",
  prompt: prompt,
  image: {
    imageBytes: imagenResponse.generatedImages[0].image.imageBytes,
    mimeType: "image/png",
  },
});

// Poll the operation status until the video is ready.
while (!operation.done) {
  console.log("Waiting for video generation to complete...")
  await new Promise((resolve) => setTimeout(resolve, 10000));
  operation = await ai.operations.getVideosOperation({
    operation: operation,
  });
}

// Download the video.
ai.files.download({
    file: operation.response.generatedVideos[0].video,
    downloadPath: "veo3_with_image_input.mp4",
});
console.log(`Generated video saved to veo3_with_image_input.mp4`);

package main

import (
    "context"
    "log"
    "os"
    "time"

    "google.golang.org/genai"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    prompt := "Panning wide shot of a calico kitten sleeping in the sunshine"

    // Step 1: Generate an image with Imagen.
    imagenResponse, err := client.Models.GenerateImages(
        ctx,
        "imagen-3.0-generate-002",
        prompt,
        nil, // GenerateImagesConfig
    )
    if err != nil {
        log.Fatal(err)
    }

    // Step 2: Generate video with Veo 3 using the image.
    operation, err := client.Models.GenerateVideos(
        ctx,
        "veo-3.0-generate-preview",
        prompt,
        imagenResponse.GeneratedImages[0].Image,
        nil, // GenerateVideosConfig
    )
    if err != nil {
        log.Fatal(err)
    }

    // Poll the operation status until the video is ready.
    for !operation.Done {
        log.Println("Waiting for video generation to complete...")
        time.Sleep(10 * time.Second)
        operation, _ = client.Operations.GetVideosOperation(ctx, operation, nil)
    }

    // Download the video.
    video := operation.Response.GeneratedVideos[0]
    client.Files.Download(ctx, video.Video, nil)
    fname := "veo3_with_image_input.mp4"
    _ = os.WriteFile(fname, video.Video.VideoBytes, 0644)
    log.Printf("Generated video saved to %s\n", fname)
}

import time
from google import genai
from google.genai import types

client = genai.Client()

operation = client.models.generate_videos(
    model="veo-3.0-generate-preview",
    prompt="A cinematic shot of a majestic lion in the savannah.",
    config=types.GenerateVideosConfig(negative_prompt="cartoon, drawing, low quality"),
)

# Poll the operation status until the video is ready.
while not operation.done:
    print("Waiting for video generation to complete...")
    time.sleep(10)
    operation = client.operations.get(operation)

# Download the generated video.
generated_video = operation.response.generated_videos[0]
client.files.download(file=generated_video.video)
generated_video.video.save("parameters_example.mp4")
print("Generated video saved to parameters_example.mp4")

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

let operation = await ai.models.generateVideos({
  model: "veo-3.0-generate-preview",
  prompt: "A cinematic shot of a majestic lion in the savannah.",
  config: {
    aspectRatio: "16:9",
    negativePrompt: "cartoon, drawing, low quality"
  },
});

// Poll the operation status until the video is ready.
while (!operation.done) {
  console.log("Waiting for video generation to complete...")
  await new Promise((resolve) => setTimeout(resolve, 10000));
  operation = await ai.operations.getVideosOperation({
    operation: operation,
  });
}

// Download the generated video.
ai.files.download({
    file: operation.response.generatedVideos[0].video,
    downloadPath: "parameters_example.mp4",
});
console.log(`Generated video saved to parameters_example.mp4`);

package main

import (
    "context"
    "log"
    "os"
    "time"

    "google.golang.org/genai"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    videoConfig := &genai.GenerateVideosConfig{
        AspectRatio: "16:9",
        NegativePrompt: "cartoon, drawing, low quality",
    }

    operation, _ := client.Models.GenerateVideos(
        ctx,
        "veo-3.0-generate-preview",
        "A cinematic shot of a majestic lion in the savannah.",
        nil,
        videoConfig,
    )

    // Poll the operation status until the video is ready.
    for !operation.Done {
        log.Println("Waiting for video generation to complete...")
        time.Sleep(10 * time.Second)
        operation, _ = client.Operations.GetVideosOperation(ctx, operation, nil)
    }

    // Download the generated video.
    video := operation.Response.GeneratedVideos[0]
    client.Files.Download(ctx, video.Video, nil)
    fname := "parameters_example.mp4"
    _ = os.WriteFile(fname, video.Video.VideoBytes, 0644)
    log.Printf("Generated video saved to %s\n", fname)
}

# Note: This script uses jq to parse the JSON response.
# GEMINI API Base URL
BASE_URL="https://generativelanguage.googleapis.com/v1beta"

# Send request to generate video and capture the operation name into a variable.
operation_name=$(curl -s "${BASE_URL}/models/veo-3.0-generate-preview:predictLongRunning" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -X "POST" \
  -d '{
    "instances": [{
        "prompt": "A cinematic shot of a majestic lion in the savannah."
      }
    ],
    "parameters": {
      "aspectRatio": "16:9",
      "negativePrompt": "cartoon, drawing, low quality"
    }
  }' | jq -r .name)

# Poll the operation status until the video is ready
while true; do
  # Get the full JSON status and store it in a variable.
  status_response=$(curl -s -H "x-goog-api-key: $GEMINI_API_KEY" "${BASE_URL}/${operation_name}")

  # Check the "done" field from the JSON stored in the variable.
  is_done=$(echo "${status_response}" | jq .done)

  if [ "${is_done}" = "true" ]; then
    # Extract the download URI from the final response.
    video_uri=$(echo "${status_response}" | jq -r '.response.generateVideoResponse.generatedSamples[0].video.uri')
    echo "Downloading video from: ${video_uri}"

    # Download the video using the URI and API key and follow redirects.
    curl -L -o parameters_example.mp4 -H "x-goog-api-key: $GEMINI_API_KEY" "${video_uri}"
    break
  fi
  # Wait for 5 seconds before checking again.
  sleep 10
done

import time
from google import genai
from google.genai import types

client = genai.Client()

# After starting the job, you get an operation object.
operation = client.models.generate_videos(
    model="veo-3.0-generate-preview",
    prompt="A cinematic shot of a majestic lion in the savannah.",
)

# Alternatively, you can use operation.name to get the operation.
operation = types.GenerateVideosOperation(name=operation.name)

# This loop checks the job status every 10 seconds.
while not operation.done:
    time.sleep(10)
    # Refresh the operation object to get the latest status.
    operation = client.operations.get(operation)

# Once done, the result is in operation.response.
# ... process and download your video ...

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

// After starting the job, you get an operation object.
let operation = await ai.models.generateVideos({
  model: "veo-3.0-generate-preview",
  prompt: "A cinematic shot of a majestic lion in the savannah.",
});

// Alternatively, you can use operation.name to get the operation.
// operation = types.GenerateVideosOperation(name=operation.name)

// This loop checks the job status every 10 seconds.
while (!operation.done) {
    await new Promise((resolve) => setTimeout(resolve, 1000));
    // Refresh the operation object to get the latest status.
    operation = await ai.operations.getVideosOperation({ operation });
}

// Once done, the result is in operation.response.
// ... process and download your video ...