Try Gemini 1.5 Pro, our most advanced multimodal model in Vertex AI, and see what you can build with a 1M token context window. Try Gemini 1.5 Pro, our most advanced multimodal model in Vertex AI, and see what you can build with a 1M token context window.

Create and update a warehouse asset

A connected Vision Warehouse (corpus) in a data-ingesting deployed app has one or more media object resources (for example, video resources). These media objects (asset resources) contain metadata and resource annotations. Use the following commands to create and update these media objects.

Create a streaming video warehouse asset

After you have created a warehouse (corpus resource), you can add one or more video asset resources to the warehouse.

REST & CMD LINE

The following code creates a new asset under the given warehouse (corpus) with the option to specify the asset's ID and a TTL.

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

REGIONALIZED_ENDPOINT: Endpoint might include a prefix matching the LOCATION_ID such as europe-west4-. See more about regionalized endpoints.
PROJECT_NUMBER: Your Google Cloud project number.
LOCATION_ID: The region where you are using Vertex AI Vision. For example: us-central1, europe-west4. See available regions.
CORPUS_ID: The ID of your target corpus.
ASSET_ID: (Optional) A user-provided value for the asset ID. In this request, the value is added to the request URL in the form:
- https://ENDPOINT/v1/[...]/corpora/CORPUS_ID/assets?asset_id=ASSET_ID
TIME_TO_LIVE: The amount of time to live (TTL) for all assets under a corpus, or the TTL of a specific asset. For example, for a corpus with assets with a TTL of 100 days, provide the value 8640000 (seconds).

HTTP method and URL:

POST https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets

Request JSON body:

{
  "ttl": {
    "seconds": TIME_TO_LIVE
  }
}

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://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets"

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://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID",
  "ttl": "TIME_TO_LIVEs"
}

Vertex AI Vision SDK

To send a request to read a model output stream you must install the Vertex AI Vision SDK.

When using the vaictl command line tool to create an asset you are not able to specify an asset ID or TTL.

Make the following variable substitutions:

PROJECT_NUMBER: Your Google Cloud project number.
LOCATION_ID: Your location ID. For example, us-central1. Supported regions. More information.
CORPUS_ID: The ID of the target warehouse (corpus resource).

vaictl --project-id=PROJECT_NUMBER \
--location-id=LOCATION_ID \
--service-endpoint=warehouse-visionai.googleapis.com \
create asset CORPUS_ID

After an asset is created you can ingest video data directly into the warehouse for that asset by using the vaictl command line tool.

Update a streaming video warehouse asset

Use the following code sample to update an asset's time-to-live (TTL). You can only update the TTL field.

Use the updateMask query parameter in the following code sample to update an asset's TTL. You can use a query parameter to update the TTL field only. The updateMask works as follows:

If specified, only the fields in the updateMask are updated.
If update mask value is *, the request updates all the fields.
If the update mask is not specified, only the fields in the request URL with a value provided in the request body are updated.

REST & CMD LINE

The following code samples modify an asset's TTL using the projects.locations.corpora.assets.patch method.

Change a TTL value

This sample uses ?updateMask=ttl in the request URL, and includes a new ttl.seconds value in the request body to update the asset.

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

REGIONALIZED_ENDPOINT: Endpoint might include a prefix matching the LOCATION_ID such as europe-west4-. See more about regionalized endpoints.
PROJECT_NUMBER: Your Google Cloud project number.
LOCATION_ID: The region where you are using Vertex AI Vision. For example: us-central1, europe-west4. See available regions.
CORPUS_ID: The ID of your target corpus.
ASSET_ID: The ID of your target asset.
?updateMask=fieldToUpdate: One of the available fields you can apply an updateMask to. Available fields:
- Time-to-live (TTL): ?updateMask=ttl
- Update all fields: ?updateMask=*

HTTP method and URL:

PATCH https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID?updateMask=ttl

Request JSON body:

{
  "ttl": {
    "seconds": "1"
  }
}

To send your request, choose one of these options:

curl

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

curl -X PATCH \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID?updateMask=ttl"

PowerShell

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 PATCH `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID?updateMask=ttl" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID"
}

Remove a TTL value

This sample uses ?updateMask=ttl in the request URL, and includes an empty request body to clear the asset's TTL value.

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

REGIONALIZED_ENDPOINT: Endpoint might include a prefix matching the LOCATION_ID such as europe-west4-. See more about regionalized endpoints.
PROJECT_NUMBER: Your Google Cloud project number.
LOCATION_ID: The region where you are using Vertex AI Vision. For example: us-central1, europe-west4. See available regions.
CORPUS_ID: The ID of your target corpus.
ASSET_ID: The ID of your target asset.
?updateMask=fieldToUpdate: One of the available fields you can apply an updateMask to. Available fields:
- Time-to-live (TTL): ?updateMask=ttl
- Update all fields: ?updateMask=*

HTTP method and URL:

PATCH https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID?updateMask=ttl

Request JSON body:

{}

To send your request, choose one of these options:

curl

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

curl -X PATCH \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID?updateMask=ttl"

PowerShell

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 PATCH `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID?updateMask=ttl" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/assets/ASSET_ID"
}