在 Gemini API 中使用 Veo 3.1 生成视频

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

client = genai.Client()

prompt = """A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.
A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'"""

operation = client.models.generate_videos(
    model="veo-3.1-generate-preview",
    prompt=prompt,
)

# 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, destination="dialogue_example.mp4")
print("Generated video saved to dialogue_example.mp4")

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

const ai = new GoogleGenAI({});

const prompt = `A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.
A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'`;

let operation = await ai.models.generateVideos({
    model: "veo-3.1-generate-preview",
    prompt: prompt,
});

// 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: "dialogue_example.mp4",
});
console.log(`Generated video saved to dialogue_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)
    }

    prompt := `A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.
    A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'`

    operation, _ := client.Models.GenerateVideos(
        ctx,
        "veo-3.1-generate-preview",
        prompt,
        nil,
        nil,
    )

    // 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 := "dialogue_example.mp4"
    _ = os.WriteFile(fname, video.Video.VideoBytes, 0644)
    log.Printf("Generated video saved to %s\n", fname)
}

import com.google.genai.Client;
import com.google.genai.types.GenerateVideosOperation;
import com.google.genai.types.Video;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;

class GenerateVideoFromText {
  public static void main(String[] args) throws Exception {
    Client client = new Client();

    String prompt = "A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.\n" +
"A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'";

    GenerateVideosOperation operation =
        client.models.generateVideos("veo-3.1-generate-preview", prompt, null, null);

    // Poll the operation status until the video is ready.
    while (!operation.done().isPresent() || !operation.done().get()) {
      System.out.println("Waiting for video generation to complete...");
      Thread.sleep(10000);
      operation = client.operations.getVideosOperation(operation, null);
    }

    // Download the generated video.
    Video video = operation.response().get().generatedVideos().get().get(0).video().get();
    Path path = Paths.get("dialogue_example.mp4");
    client.files.download(video, path.toString(), null);
    if (video.videoBytes().isPresent()) {
      Files.write(path, video.videoBytes().get());
      System.out.println("Generated video saved to dialogue_example.mp4");
    }
  }
}

# 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-3.1-generate-preview:predictLongRunning" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -X "POST" \
  -d '{
    "instances": [{
        "prompt": "A close up of two people staring at a cryptic drawing on a wall, torchlight flickering. A man murmurs, \"This must be it. That'\''s the secret code.\" The woman looks at him and whispering excitedly, \"What did you find?\""
      }
    ]
  }' | 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 dialogue_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()

prompt = """Drone shot following a classic red convertible driven by a man along a winding coastal road at sunset, waves crashing against the rocks below.
The convertible accelerates fast and the engine roars loudly."""

operation = client.models.generate_videos(
    model="veo-3.1-generate-preview",
    prompt=prompt,
)

# 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, destination="realism_example.mp4")
print("Generated video saved to realism_example.mp4")

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

const ai = new GoogleGenAI({});

const prompt