Starting April 29, 2025, Gemini 1.5 Pro and Gemini 1.5 Flash models are not available in projects that have no prior usage of these models, including new projects. For details, see Model versions and lifecycle.

Veo | AI Video Generator
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You can use Veo on Vertex AI to generate new videos from a text prompt or an image prompt that you provide in the Google Cloud console or send in a request to the Vertex AI API.

Try Veo on Vertex AI Media Studio

Try Veo in a Colab

Request access: Experimental features

Model versions

There are multiple video generation models that you can use. For more information, see Veo models.

Locations

A location is a region you can specify in a request to control where data is stored at rest. For a list of available regions, see Generative AI on Vertex AI locations.

Responsible AI

Veo generates realistic and high quality videos from natural language text and image prompts, including images of people of all ages. Veo may provide you an error that indicates that your Google Cloud project needs to be approved for person or child generation, depending on the context of your text or image prompt.

If you require approval, please contact your Google account representative.

Before you begin

Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Go to project selector

Enable the Vertex AI API.

Enable the API

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Go to project selector

Enable the Vertex AI API.

Enable the API

Set up authentication for your environment.

Select the tab for how you plan to use the samples on this page:
Console

When you use the Google Cloud console to access Google Cloud services and APIs, you don't need to set up authentication.
REST

To use the REST API samples on this page in a local development environment, you use the credentials you provide to the gcloud CLI.
For more information, see Authenticate for using REST in the Google Cloud authentication documentation.

Generate videos from text

You can generate novel videos using only descriptive text as an input. The following samples show you basic instructions to generate videos.

Console

In the Google Cloud console, go to the Vertex AI Studio > Media Studio page.

Media Studio
Click Video.
Optional: In the Settings pane, configure the following settings:
- Model: choose a model from the available options.
- Aspect ratio: choose either 16:9 or 9:16.
  
  Note: The 9:16 aspect ratio isn't supported by veo-3.0-generate-preview.
- Number of results: adjust the slider or enter a value between 1 and 4.
- Video length: select a length between 5 seconds and 8 seconds.
- Output directory: click Browse to create or select a Cloud Storage bucket to store output files.
Optional: In the Safety section, select one of the following Person generation settings:
- Allow (Adults only): default value. Generate adult people or faces only. Don't generate youth or children people or faces.
- Don't allow: don't generate people or faces.
Optional: In the Advanced options section, enter a Seed value for randomizing video generation.
In the Write your prompt box, enter your text prompt that describes the videos to generate.
Click Generate.

REST

After you set up your environment, you can use REST to test a text prompt. The following sample sends a request to the publisher model endpoint.

For more information about the Veo API, see the Veo on Vertex AI API.

Use the following command to send a video generation request. This request begins a long-running operation and stores output to a Cloud Storage bucket you specify.

Before using any of the request data, make the following replacements:
- PROJECT_ID: Your Google Cloud project ID.
- MODEL_ID: The model ID to use. Available values:
  - veo-2.0-generate-001 (GA allowlist)
  - veo-3.0-generate-preview (Preview)
- TEXT_PROMPT: The text prompt used to guide video generation.
- OUTPUT_STORAGE_URI: Optional: The Cloud Storage bucket to store the output videos. If not provided, video bytes are returned in the response. For example: gs://video-bucket/output/.
- RESPONSE_COUNT: The number of video files you want to generate. Accepted integer values: 1-4.
- DURATION: The length of video files that you want to generate. Accepted integer values are 5-8.
- Additional optional parameters
  
  Use the following optional variables depending on your use case. Add some or all of the following parameters in the "parameters": {} object.
```
"parameters": {
  "aspectRatio": "ASPECT_RATIO",
  "negativePrompt": "NEGATIVE_PROMPT",
  "personGeneration": "PERSON_SAFETY_SETTING",
  "sampleCount": RESPONSE_COUNT,
  "seed": SEED_NUMBER
}
```
  - ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated videos. Values: 16:9 (default, landscape) or 9:16 (portrait).
  - NEGATIVE_PROMPT: string. Optional. A text string that describes what you want to discourage the model from generating.
  - PERSON_SAFETY_SETTING: string. Optional. The safety setting that controls whether people or face generation is allowed. Values:
    - allow_adult (default value): Allow generation of adults only.
    - disallow: Disallows inclusion of people or faces in images.
  - RESPONSE_COUNT: int. Optional. The number of output images requested. Values: 1-4.
  - SEED_NUMBER: uint32. Optional. A number to make generated videos deterministic. Specifying a seed number with your request without changing other parameters guides the model to produce the same videos. Values: 0 - 4294967295.
HTTP method and URL:
```
POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning
```
Request JSON body:
```
{
  "instances": [
    {
      "prompt": "TEXT_PROMPT"
    }
  ],
  "parameters": {
    "storageUri": "OUTPUT_STORAGE_URI",
    "sampleCount": "RESPONSE_COUNT"
  }
}
```
To send your request, choose one of these options:
curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning"
PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning" | Select-Object -Expand Content
This request returns a full operation name with a unique operation ID. Use this full operation name to poll that status of the video generation request.
```
{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/a1b07c8e-7b5a-4aba-bb34-3e1ccb8afcc8"
}
```

Optional: Check the status of the video generation long-running operation.

Before using any of the request data, make the following replacements:

PROJECT_ID: Your Google Cloud project ID.
MODEL_ID: The model ID to use. Available values:
- veo-2.0-generate-001 (GA allowlist)
- veo-3.0-generate-preview (Preview)
OPERATION_ID: The unique operation ID returned in the original generate video request.

HTTP method and URL:

POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:fetchPredictOperation

Request JSON body:

{
  "operationName": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/OPERATION_ID"
}

To send your request, choose one of these options:

curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:fetchPredictOperation"

PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:fetchPredictOperation" | Select-Object -Expand Content

This request returns information about the operation, including if the operation is still running or is done.

Response

{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/OPERATION_ID",
  "done": true,
  "response": {
    "@type": "type.googleapis.com/cloud.ai.large_models.vision.GenerateVideoResponse",
    "videos": [
      {
        "gcsUri":"gs://BUCKET_NAME/TIMESTAMPED_FOLDER/sample_0.mp4",
        "mimeType": "video/mp4"
      }
    ]
  }
}

Gen AI SDK for Python

Install

pip install --upgrade google-genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_VERTEXAI=True

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

client = genai.Client()

# TODO(developer): Update and un-comment below line
# output_gcs_uri = "gs://your-bucket/your-prefix"

operation = client.models.generate_videos(
    model="veo-2.0-generate-001",
    prompt="a cat reading a book",
    config=GenerateVideosConfig(
        aspect_ratio="16:9",
        output_gcs_uri=output_gcs_uri,
    ),
)

while not operation.done:
    time.sleep(15)
    operation = client.operations.get(operation)
    print(operation)

if operation.response:
    print(operation.result.generated_videos[0].video.uri)

# Example response:
# gs://your-bucket/your-prefix

Generate videos from an image

Sample input	Sample output
Input image¹ Text prompt: the elephant moves around naturally

¹ Image generated using Imagen on Vertex AI from the prompt: A Crochet elephant in intricate patterns walking on the savanna

You can generate novel videos using only an image as an input, or and image and descriptive text as the inputs. The following samples show you basic instructions to generate videos from image and text.

Console

In the Google Cloud console, go to the Vertex AI Studio > Media Studio page.

Media Studio
Click Video.
Optional: In the Settings pane, configure the following settings:
- Model: choose a model from the available options.
- Aspect ratio: choose either 16:9 or 9:16.
  
  Note: The 9:16 aspect ratio isn't supported by veo-3.0-generate-preview.
- Number of results: adjust the slider or enter a value between 1 and 4.
- Video length: select a length between 5 seconds and 8 seconds.
- Output directory: click Browse to create or select a Cloud Storage bucket to store output files.
Optional: In the Safety section, select one of the following Person generation settings:
- Allow (Adults only): default value. Generate adult people or faces only. Don't generate youth or children people or faces.
- Don't allow: don't generate people or faces.
Optional: In the Advanced options section, enter a Seed value for randomizing video generation.
In the Write your prompt prompt box, click Upload.
Choose a local image to upload and click Select.
In the Write your prompt box, enter your text prompt that describes the videos to generate.
Click Generate.

REST

After you set up your environment, you can use REST to test a text prompt. The following sample sends a request to the publisher model endpoint.

For more information about the Veo API, see the Veo on Vertex AI API.

Use the following command to send a video generation request. This request begins a long-running operation and stores output to a Cloud Storage bucket you specify.

Before using any of the request data, make the following replacements:
- PROJECT_ID: Your Google Cloud project ID.
- MODEL_ID: The model ID to use. Available values:
  - veo-2.0-generate-001 (GA allowlist)
  - veo-3.0-generate-preview (Preview)
- TEXT_PROMPT: The text prompt used to guide video generation.
- INPUT_IMAGE: Base64-encoded bytes string representing the input image. To ensure quality, the input image should be 720p or higher (1280 x 720 pixels) and have a 16:9 or 9:16 aspect ratio. Images of other aspect ratios or sizes may be resized or centrally cropped during the upload process.
- MIME_TYPE: The MIME type of the input image. Only the images of the following MIME types are supported: image/jpeg or image/png.
- OUTPUT_STORAGE_URI: Optional: The Cloud Storage bucket to store the output videos. If not provided, video bytes are returned in the response. For example: gs://video-bucket/output/.
- RESPONSE_COUNT: The number of video files you want to generate. Accepted integer values: 1-4.
- DURATION: The length of video files that you want to generate. Accepted integer values are 5-8.
- Additional optional parameters
  
  Use the following optional variables depending on your use case. Add some or all of the following parameters in the "parameters": {} object.
```
"parameters": {
  "aspectRatio": "ASPECT_RATIO",
  "negativePrompt": "NEGATIVE_PROMPT",
  "personGeneration": "PERSON_SAFETY_SETTING",
  "sampleCount": RESPONSE_COUNT,
  "seed": SEED_NUMBER
}
```
  - ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated videos. Values: 16:9 (default, landscape) or 9:16 (portrait).
  - NEGATIVE_PROMPT: string. Optional. A text string that describes what you want to discourage the model from generating.
  - PERSON_SAFETY_SETTING: string. Optional. The safety setting that controls whether people or face generation is allowed. Values:
    - allow_adult (default value): Allow generation of adults only.
    - disallow: Disallows inclusion of people or faces in images.
  - RESPONSE_COUNT: int. Optional. The number of output images requested. Values: 1-4.
  - SEED_NUMBER: uint32. Optional. A number to make generated videos deterministic. Specifying a seed number with your request without changing other parameters guides the model to produce the same videos. Values: 0 - 4294967295.
HTTP method and URL:
```
POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning
```
Request JSON body:
```
{
  "instances": [
    {
      "prompt": "TEXT_PROMPT",
      "image": {
        "bytesBase64Encoded": "INPUT_IMAGE",
        "mimeType": "MIME_TYPE"
      }
    }
  ],
  "parameters": {
    "storageUri": "OUTPUT_STORAGE_URI",
    "sampleCount": RESPONSE_COUNT
  }
}
```
To send your request, choose one of these options:
curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning"
PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning" | Select-Object -Expand Content
This request returns a full operation name with a unique operation ID. Use this full operation name to poll that status of the video generation request.
```
{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/a1b07c8e-7b5a-4aba-bb34-3e1ccb8afcc8"
}
```
Optional: Check the status of the video generation long-running operation.

Before using any of the request data, make the following replacements:
- PROJECT_ID: Your Google Cloud project ID.
- MODEL_ID: The model ID to use. Available values:
  - veo-2.0-generate-001
- TEXT_PROMPT: The text prompt used to guide video generation.
- OUTPUT_STORAGE_URI: Optional: The Cloud Storage bucket to store the output videos. If not provided, video bytes are returned in the response. For example: gs://video-bucket/output/.
- RESPONSE_COUNT: The number of video files you want to generate. Accepted integer values: 1-4.
- Additional optional parameters
  
  Use the following optional variables depending on your use case. Add some or all of the following parameters in the "parameters": {} object.
```
"parameters": {
  "aspectRatio": "ASPECT_RATIO",
  "negativePrompt": "NEGATIVE_PROMPT",
  "personGeneration": "PERSON_SAFETY_SETTING",
  "sampleCount": RESPONSE_COUNT,
  "seed": SEED_NUMBER
}
```
  - ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated videos. Values: 16:9 (default, landscape) or 9:16 (portrait).
  - NEGATIVE_PROMPT: string. Optional. A text string that describes what you want to discourage the model from generating.
  - PERSON_SAFETY_SETTING: string. Optional. The safety setting that controls whether people or face generation is allowed. Values:
    - allow_adult (default value): Allow generation of adults only.
    - disallow: Disallows inclusion of people or faces in images.
  - RESPONSE_COUNT: int. Optional. The number of output images requested. Values: 1-4.
  - SEED_NUMBER: uint32. Optional. A number to make generated videos deterministic. Specifying a seed number with your request without changing other parameters guides the model to produce the same videos. Values: 0 - 4294967295.
HTTP method and URL:
```
POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning
```
Request JSON body:
```
{
  "instances": [
    {
      "prompt": "TEXT_PROMPT"
    }
  ],
  "parameters": {
    "storageUri": "OUTPUT_STORAGE_URI",
    "sampleCount": "RESPONSE_COUNT"
  }
}
```
To send your request, choose one of these options:
curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning"
PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning" | Select-Object -Expand Content
This request returns a full operation name with a unique operation ID. Use this full operation name to poll that status of the video generation request.
```
{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/a1b07c8e-7b5a-4aba-bb34-3e1ccb8afcc8"
}
```

Gen AI SDK for Python

Install

pip install --upgrade google-genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_VERTEXAI=True

import time
from google import genai
from google.genai.types import GenerateVideosConfig, Image

client = genai.Client()

# TODO(developer): Update and un-comment below line
# output_gcs_uri = "gs://your-bucket/your-prefix"

operation = client.models.generate_videos(
    model="veo-2.0-generate-001",
    image=Image(
        gcs_uri="gs://cloud-samples-data/generative-ai/image/flowers.png",
        mime_type="image/png",
    ),
    config=GenerateVideosConfig(
        aspect_ratio="16:9",
        output_gcs_uri=output_gcs_uri,
    ),
)

while not operation.done:
    time.sleep(15)
    operation = client.operations.get(operation)
    print(operation)

if operation.response:
    print(operation.result.generated_videos[0].video.uri)

# Example response:
# gs://your-bucket/your-prefix

Prompt rewriter

Veo offers an LLM-based prompt enhancement tool, also known as a prompt rewriter. The prompt rewriter offers the option to rewrite your prompts to add video description, camera motions, transcription, and sound effects to your prompt. More detailed prompts result in higher quality videos.

If you disable prompt enhancement, the quality of the videos and how well the output resembles the prompt that you supplied may be impacted. This feature is enabled by default for the following model versions:

veo-2.0-generate-001
veo-3.0-generate-preview (Preview)

Important: You can't disable prompt rewriter when you use veo-3.0-generate-preview

The rewritten prompt is delivered by API response only if the original prompt is fewer than 30 words long.

To turn prompt enhancement off, do the following:

Console

In the Google Cloud console, go to the Vertex AI Studio > Media Studio page.

Go to Media Studio
Click Veo.
In Settings, click the Enable prompt enhancement toggle.
In the Write your prompt box, enter your prompt and then click Generate

REST

For more information about the Veo API, see the Veo on Vertex AI API.

Use the following command to send a video generation request. This request begins a long-running operation and stores output to a Cloud Storage bucket you specify.

Before using any of the request data, make the following replacements:
- PROJECT_ID: Your Google Cloud project ID.
- MODEL_ID: The model ID to use. Available values:
  - veo-2.0-generate-001 (GA allowlist)
  - veo-3.0-generate-preview (Preview)
- TEXT_PROMPT: The text prompt used to guide video generation.
- OUTPUT_STORAGE_URI: Optional: The Cloud Storage bucket to store the output videos. If not provided, video bytes are returned in the response. For example: gs://video-bucket/output/.
- RESPONSE_COUNT: The number of video files you want to generate. Accepted integer values: 1-4.
- DURATION: The length of video files that you want to generate. Accepted integer values are 5-8.
- ENHANCED_PROMPT: Whether to use enhanced prompts or not. You can use one of the following:
  - True: (default) use Gemini to enhance your prompts.
  - False: don't use Gemini to enhance your prompts.
- Additional optional parameters
  
  Use the following optional variables depending on your use case. Add some or all of the following parameters in the "parameters": {} object.
```
"parameters": {
  "aspectRatio": "ASPECT_RATIO",
  "negativePrompt": "NEGATIVE_PROMPT",
  "personGeneration": "PERSON_SAFETY_SETTING",
  "sampleCount": RESPONSE_COUNT,
  "seed": SEED_NUMBER
}
```
  - ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated videos. Values: 16:9 (default, landscape) or 9:16 (portrait).
  - NEGATIVE_PROMPT: string. Optional. A text string that describes what you want to discourage the model from generating.
  - PERSON_SAFETY_SETTING: string. Optional. The safety setting that controls whether people or face generation is allowed. Values:
    - allow_adult (default value): Allow generation of adults only.
    - disallow: Disallows inclusion of people or faces in images.
  - RESPONSE_COUNT: int. Optional. The number of output images requested. Values: 1-4.
  - SEED_NUMBER: uint32. Optional. A number to make generated videos deterministic. Specifying a seed number with your request without changing other parameters guides the model to produce the same videos. Values: 0 - 4294967295.
HTTP method and URL:
```
POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning
```
Request JSON body:
```
{
  "instances": [
    {
      "prompt": "TEXT_PROMPT"
    }
  ],
  "parameters": {
    "storageUri": "OUTPUT_STORAGE_URI",
    "sampleCount": "RESPONSE_COUNT",
    "durationSeconds": "DURATION",
    "enhancePrompt": ENHANCED_PROMPT
  }
}
```
To send your request, choose one of these options:
curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning"
PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning" | Select-Object -Expand Content
This request returns a full operation name with a unique operation ID. Use this full operation name to poll that status of the video generation request.
```
{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/a1b07c8e-7b5a-4aba-bb34-3e1ccb8afcc8"
}
```

What's next

Read Google DeepMind's information on the Veo model.
Read the blog post "Veo and Imagen 3: Announcing new video and image generation models on Vertex AI".
Read the blog post "New generative media models and tools, built with and for creators".

Veo | AI Video Generator Stay organized with collections Save and categorize content based on your preferences.

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Veo | AI Video Generator
Stay organized with collections Save and categorize content based on your preferences.