Databricks SDK for JavaScript
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    Interface PutInferenceEndpointAiGatewayRequest

    interface PutInferenceEndpointAiGatewayRequest {
        fallbackConfig?: FallbackConfig;
        guardrails?: AiGuardrails;
        inferenceTableConfig?: InferenceTableConfig;
        name?: string;
        rateLimits?: AiGatewayRateLimit[];
        usageTrackingConfig?: UsageTrackingConfig;
    }
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    Properties

    fallbackConfig? guardrails? inferenceTableConfig? name? rateLimits? usageTrackingConfig?

    Properties

    fallbackConfig?: FallbackConfig

    Configuration for traffic fallback which auto fallbacks to other served entities if the request to a served entity fails with certain error codes, to increase availability.

    guardrails?: AiGuardrails

    Configuration for AI Guardrails to prevent unwanted data and unsafe data in requests and responses.

    inferenceTableConfig?: InferenceTableConfig

    Configuration for payload logging using inference tables. Use these tables to monitor and audit data being sent to and received from model APIs and to improve model quality.

    name?: string

    The name of the serving endpoint whose AI Gateway is being updated. This field is required.

    rateLimits?: AiGatewayRateLimit[]

    Configuration for rate limits which can be set to limit endpoint traffic.

    usageTrackingConfig?: UsageTrackingConfig

    Configuration to enable usage tracking using system tables. These tables allow you to monitor operational usage on endpoints and their associated costs.

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