Delete a context cache

Python

To learn how to install or update the Vertex AI SDK for Python, see Install the Vertex AI SDK for Python. For more information, see the Vertex AI SDK for Python API reference documentation.

Streaming and non-streaming responses

You can choose whether the model generates streaming responses or non-streaming responses. For streaming responses, you receive each response as soon as its output token is generated. For non-streaming responses, you receive all responses after all of the output tokens are generated.

For a streaming response, use the stream parameter in generate_content.

  response = model.generate_content(contents=[...], stream = True)
  

For a non-streaming response, remove the parameter, or set the parameter to False.

Sample code

import vertexai

from vertexai.preview import caching

# TODO(developer): Update and un-comment below lines
# PROJECT_ID = "your-project-id"
# cache_id = "your-cache-id"

vertexai.init(project=PROJECT_ID, location="us-central1")

cached_content = caching.CachedContent(cached_content_name=cache_id)
cached_content.delete()

Go

Before trying this sample, follow the Go setup instructions in the Vertex AI quickstart. For more information, see the Vertex AI Go SDK for Gemini reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up ADC for a local development environment.

Streaming and non-streaming responses

You can choose whether the model generates streaming responses or non-streaming responses. For streaming responses, you receive each response as soon as its output token is generated. For non-streaming responses, you receive all responses after all of the output tokens are generated.

For a streaming response, use the GenerateContentStream method.

  iter := model.GenerateContentStream(ctx, genai.Text("Tell me a story about a lumberjack and his giant ox. Keep it very short."))
  

For a non-streaming response, use the GenerateContent method.

  resp, err := model.GenerateContent(ctx, genai.Text("What is the average size of a swallow?"))
  

Sample code

import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/vertexai/genai"
)

// deleteContextCache shows how to delete a cached content
// contentName is the ID of the cached content
func deleteContextCache(w io.Writer, contentName string, projectID, location string) error {
	// location := "us-central1"
	ctx := context.Background()

	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		return fmt.Errorf("unable to create client: %w", err)
	}
	defer client.Close()

	err = client.DeleteCachedContent(ctx, contentName)
	if err != nil {
		return fmt.Errorf("DeleteCachedContent: %w", err)
	}
	fmt.Fprintf(w, "Deleted cached content %q", contentName)
	return nil
}

REST

The following shows how to use REST to delete a context cache associated with a Google Cloud project by sending a DELETE request to the publisher model endpoint.

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

• PROJECT_ID: Your project ID.
• LOCATION: The region where the request to create the context cache was processed and where the cached content is stored.
• CACHE_ID: The ID of the context cache to delete. The context cache ID is returned when you create the context cache. You can also find context cache IDs by listing the context caches for a Google Cloud project using. For more information, see create a context cache and list context caches.

HTTP method and URL:

DELETE https://LOCATION-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION/cachedContents/CACHE_ID

To send your request, choose one of these options:

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://LOCATION-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION/cachedContents/CACHE_ID"

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

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://LOCATION-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION/cachedContents/CACHE_ID" | Select-Object -Expand Content

If the delete operation succeeds, the response is empty:

{ }

Example curl command

LOCATION="us-central1"
PROJECT_ID="PROJECT_ID"
CACHE_ID="CACHE_ID"

curl \
-X DELETE \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
https://${LOCATION}-aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/${LOCATION}/${CACHE_ID}