Upraviť

Zdieľať cez

Cache responses to large language model API requests

  • Článok

APPLIES TO: All API Management tiers

The llm-semantic-cache-store policy caches responses to chat completion API and completion API requests to a configured external cache. Response caching reduces bandwidth and processing requirements imposed on the backend Azure OpenAI API and lowers latency perceived by API consumers.

Note

Note

Set the policy's elements and child elements in the order provided in the policy statement. Learn more about how to set or edit API Management policies.

Supported models

Use the policy with LLM APIs added to Azure API Management that are available through the Azure AI Model Inference API.

Policy statement

<llm-semantic-cache-store duration="seconds"/>

Attributes

Attribute Description Required Default
duration Time-to-live of the cached entries, specified in seconds. Policy expressions are allowed. Yes N/A

Usage

Usage notes

  • This policy can only be used once in a policy section.
  • If the cache lookup fails, the API call that uses the cache-related operation doesn't raise an error, and the cache operation completes successfully.

Examples

Example with corresponding llm-semantic-cache-lookup policy

<policies>
    <inbound>
        <base />
        <llm-semantic-cache-lookup
            score-threshold="0.05"
            embeddings-backend-id ="llm-backend"
            embeddings-backend-auth ="system-assigned" >
            <vary-by>@(context.Subscription.Id)</vary-by>
        </llm-semantic-cache-lookup>
    </inbound>
    <outbound>
        <llm-semantic-cache-store duration="60" />
        <base />
    </outbound>
</policies>

Related content

For more information about working with policies, see: