Pour en savoir plus sur la compréhension des vidéos, consultez le guide Comprendre les vidéos.
Veo 3.1 est un modèle permettant de générer des vidéos de huit secondes (720p, 1 080p ou 4K) avec de l'audio généré de manière native. Vous pouvez accéder à ce modèle de manière programmatique à l'aide de l'API Gemini. Pour en savoir plus sur les variantes de modèles Veo disponibles, consultez la section Versions de modèle.
Veo 3.1 excelle dans un large éventail de styles visuels et cinématographiques, et introduit plusieurs nouvelles fonctionnalités :
- Vidéos en mode Portrait : choisissez entre les vidéos en mode paysage (
16:9) et en mode portrait (9:16). - Extension de vidéo : étendez les vidéos qui ont été générées précédemment à l'aide de Veo.
- Génération spécifique à une image : générez une vidéo en spécifiant la première et la dernière image.
- Direction basée sur des images : utilisez jusqu'à trois images de référence pour guider le contenu de votre vidéo générée.
Pour en savoir plus sur la rédaction de prompts textuels efficaces pour la génération de vidéos, consultez le Guide sur les prompts Veo.
Génération de vidéos à partir de texte
Les exemples suivants montrent comment générer une vidéo avec des dialogues, un réalisme cinématographique ou une animation créative :
Dialogues et effets sonores
Python
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)
generated_video.video.save("dialogue_example.mp4")
print("Generated video saved to dialogue_example.mp4")
JavaScript
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`);
Go
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)
}
Java
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");
}
}
}
REST
# 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