สร้างวิดีโอด้วย Veo 3 ใน Gemini API

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 ...