สร้างวิดีโอโดยใช้ Veo

import time from google import genai from google.genai import types  client = genai.Client()  # read API key from GOOGLE_API_KEY  operation = client.models.generate_videos(     model="veo-2.0-generate-001",     prompt="Panning wide shot of a calico kitten sleeping in the sunshine",     config=types.GenerateVideosConfig(         person_generation="dont_allow",  # "dont_allow" or "allow_adult"         aspect_ratio="16:9",  # "16:9" or "9:16"     ), )  while not operation.done:     time.sleep(20)     operation = client.operations.get(operation)  for n, generated_video in enumerate(operation.response.generated_videos):     client.files.download(file=generated_video.video)     generated_video.video.save(f"video{n}.mp4")  # save the video  

import { GoogleGenAI } from "@google/genai"; import { createWriteStream } from "fs"; import { Readable } from "stream";  const ai = new GoogleGenAI({ apiKey: "GOOGLE_API_KEY" });  async function main() {   let operation = await ai.models.generateVideos({     model: "veo-2.0-generate-001",     prompt: "Panning wide shot of a calico kitten sleeping in the sunshine",     config: {       personGeneration: "dont_allow",       aspectRatio: "16:9",     },   });    while (!operation.done) {     await new Promise((resolve) => setTimeout(resolve, 10000));     operation = await ai.operations.getVideosOperation({       operation: operation,     });   }    operation.response?.generatedVideos?.forEach(async (generatedVideo, n) => {     const resp = await fetch(`${generatedVideo.video?.uri}&key=GOOGLE_API_KEY`); // append your API key     const writer = createWriteStream(`video${n}.mp4`);     Readable.fromWeb(resp.body).pipe(writer);   }); }  main(); 

package main  import (   "context"   "fmt"   "os"   "time"   "google.golang.org/genai" )  func main() {    ctx := context.Background()   client, _ := genai.NewClient(ctx, &genai.ClientConfig{       APIKey:  os.Getenv("GEMINI_API_KEY"),       Backend: genai.BackendGeminiAPI,   })    videoConfig := &genai.GenerateVideosConfig{       AspectRatio:      "16:9",       PersonGeneration: "dont_allow",   }    operation, _ := client.Models.GenerateVideos(       ctx,       "veo-2.0-generate-001",       "Panning wide shot of a calico kitten sleeping in the sunshine",       nil,       videoConfig,   )    for !operation.Done {       time.Sleep(20 * time.Second)       operation, _ = client.Operations.GetVideosOperation(ctx, operation, nil)   }    for n, video := range operation.Response.GeneratedVideos {       client.Files.Download(ctx, video.Video, nil)       fname := fmt.Sprintf("video_%d.mp4", n)       _ = os.WriteFile(fname, video.Video.VideoBytes, 0644)   } } 

# Use curl to send a POST request to the predictLongRunning endpoint. # The request body includes the prompt for video generation. curl "${BASE_URL}/models/veo-2.0-generate-001:predictLongRunning?key=${GOOGLE_API_KEY}" \   -H "Content-Type: application/json" \   -X "POST" \   -d '{     "instances": [{         "prompt": "Panning wide shot of a calico kitten sleeping in the sunshine"       }     ],     "parameters": {       "aspectRatio": "16:9",       "personGeneration": "dont_allow",     }   }' | tee result.json | jq .name | sed 's/"//g' > op_name  # Obtain operation name to download video. op_name=$(cat op_name)  # Check against status of operation. while true; do   is_done=$(curl "${BASE_URL}/${op_name}?key=${GOOGLE_API_KEY}" | tee op_check.json | jq .done)    if [ "${is_done}" = "true" ]; then     cat op_check.json     echo "** Attach API_KEY to download video, or examine error message."     break   fi    echo "** Video ${op_name} has not downloaded yet!  Check again after 5 seconds..."    # Wait for 5 seoncds to check again.   sleep 5  done 

prompt="Panning wide shot of a calico kitten sleeping in the sunshine",  imagen = client.models.generate_images(     model="imagen-3.0-generate-002",     prompt=prompt,     config=types.GenerateImagesConfig(       aspect_ratio="16:9",       number_of_images=1     ) )  imagen.generated_images[0].image 

import { GoogleGenAI } from "@google/genai";  const ai = new GoogleGenAI({ apiKey: "GOOGLE_API_KEY" }); const response = await ai.models.generateImages({   model: "imagen-3.0-generate-002",   prompt: "Panning wide shot of a calico kitten sleeping in the sunshine",   config: {     numberOfImages: 1,   }, });  // you'll pass response.generatedImages[0].image.imageBytes to Veo 

package main  import (     "context"     "fmt"     "os"     "time"     "google.golang.org/genai" )  func main() {      ctx := context.Background()     client, _ := genai.NewClient(ctx, &genai.ClientConfig{         APIKey:  os.Getenv("GEMINI_API_KEY"),         Backend: genai.BackendGeminiAPI,     })      config := &genai.GenerateImagesConfig{         AspectRatio:    "16:9",         NumberOfImages: 1,     }      response, _ := client.Models.GenerateImages(         ctx,         "imagen-3.0-generate-002",         "Panning wide shot of a calico kitten sleeping in the sunshine",         config,     )      // you'll pass response.GeneratedImages[0].Image to Veo } 

operation = client.models.generate_videos(     model="veo-2.0-generate-001",     prompt=prompt,     image = imagen.generated_images[0].image,     config=types.GenerateVideosConfig(       person_generation="dont_allow",  # "dont_allow" or "allow_adult"       aspect_ratio="16:9",  # "16:9" or "9:16"       number_of_videos=2     ), )  # Wait for videos to generate  while not operation.done:   time.sleep(20)   operation = client.operations.get(operation)  for n, video in enumerate(operation.response.generated_videos):     fname = f'with_image_input{n}.mp4'     print(fname)     client.files.download(file=video.video)     video.video.save(fname) 

import { GoogleGenAI } from "@google/genai"; import { createWriteStream } from "fs"; import { Readable } from "stream";  const ai = new GoogleGenAI({ apiKey: "GOOGLE_API_KEY" });  async function main() {   // get image bytes from Imagen, as shown above    let operation = await ai.models.generateVideos({     model: "veo-2.0-generate-001",     prompt: "Panning wide shot of a calico kitten sleeping in the sunshine",     image: {       imageBytes: response.generatedImages[0].image.imageBytes, // response from Imagen       mimeType: "image/png",     },     config: {       aspectRatio: "16:9",       numberOfVideos: 2,     },   });    while (!operation.done) {     await new Promise((resolve) => setTimeout(resolve, 10000));     operation = await ai.operations.getVideosOperation({       operation: operation,     });   }    operation.response?.generatedVideos?.forEach(async (generatedVideo, n) => {     const resp = await fetch(       `${generatedVideo.video?.uri}&key=GOOGLE_API_KEY`, // append your API key     );     const writer = createWriteStream(`video${n}.mp4`);     Readable.fromWeb(resp.body).pipe(writer);   }); }  main(); 

    image := response.GeneratedImages[0].Image      videoConfig := &genai.GenerateVideosConfig{       AspectRatio:    "16:9",       NumberOfVideos: 2,     }      operation, _ := client.Models.GenerateVideos(         ctx,         "veo-2.0-generate-001",         "A dramatic scene based on the input image",         image,         videoConfig,     )      for !operation.Done {         time.Sleep(20 * time.Second)         operation, _ = client.Operations.GetVideosOperation(ctx, operation, nil)     }      for n, video := range operation.Response.GeneratedVideos {         client.Files.Download(ctx, video.Video, nil)         fname := fmt.Sprintf("video_with_image_input_%d.mp4", n)         _ = os.WriteFile(fname, video.Video.VideoBytes, 0644)     }