@launchdarkly/mcp-server/src/models/components/aiconfigsmetricdenominatorrep.ts

The local [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server for [LaunchDarkly](https://launchdarkly.com/) federal and European Union (EU) environments.

/*
 * Code generated by Speakeasy (https://speakeasy.com). DO NOT EDIT.
 */

import * as z from "zod/v3";
import { safeParse } from "../../lib/schemas.js";
import { Result as SafeParseResult } from "../../types/fp.js";
import { SDKValidationError } from "../errors/sdkvalidationerror.js";
import {
  AiConfigsFilter,
  AiConfigsFilter$inboundSchema,
  AiConfigsFilter$Outbound,
  AiConfigsFilter$outboundSchema,
} from "./aiconfigsfilter.js";
import {
  AiConfigsMetricDataSourceRefRep,
  AiConfigsMetricDataSourceRefRep$inboundSchema,
  AiConfigsMetricDataSourceRefRep$Outbound,
  AiConfigsMetricDataSourceRefRep$outboundSchema,
} from "./aiconfigsmetricdatasourcerefrep.js";

export type AiConfigsMetricDenominatorRep = {
  /**
   * The warehouse event column for the denominator
   */
  eventName?: string | undefined;
  /**
   * Whether the denominator aggregates a numeric value
   */
  isNumeric?: boolean | undefined;
  /**
   * How individual unit values are aggregated for the denominator
   */
  unitAggregationType?: string | undefined;
  /**
   * The column to count distinct values of; required when unitAggregationType is count_distinct
   */
  unitAggregationField?: string | undefined;
  /**
   * For a numeric denominator, the column holding the numeric value
   */
  valueColumn?: string | undefined;
  dataSource?: AiConfigsMetricDataSourceRefRep | undefined;
  filters?: AiConfigsFilter | undefined;
  /**
   * Start of the measurement window in milliseconds
   */
  windowStartOffset?: number | undefined;
  /**
   * End of the measurement window in milliseconds
   */
  windowEndOffset?: number | undefined;
  /**
   * Lower winsorization percentile in the open interval (0, 100)
   */
  winsorLowerPercentile?: number | undefined;
  /**
   * Upper winsorization percentile in the open interval (0, 100)
   */
  winsorUpperPercentile?: number | undefined;
  /**
   * When true, the percentile bound calculation includes imputed zeros
   */
  winsorIncludeImputed?: boolean | undefined;
};

/** @internal */
export const AiConfigsMetricDenominatorRep$inboundSchema: z.ZodType<
  AiConfigsMetricDenominatorRep,
  z.ZodTypeDef,
  unknown
> = z.object({
  eventName: z.string().optional(),
  isNumeric: z.boolean().optional(),
  unitAggregationType: z.string().optional(),
  unitAggregationField: z.string().optional(),
  valueColumn: z.string().optional(),
  dataSource: AiConfigsMetricDataSourceRefRep$inboundSchema.optional(),
  filters: AiConfigsFilter$inboundSchema.optional(),
  windowStartOffset: z.number().int().optional(),
  windowEndOffset: z.number().int().optional(),
  winsorLowerPercentile: z.number().optional(),
  winsorUpperPercentile: z.number().optional(),
  winsorIncludeImputed: z.boolean().optional(),
});
/** @internal */
export type AiConfigsMetricDenominatorRep$Outbound = {
  eventName?: string | undefined;
  isNumeric?: boolean | undefined;
  unitAggregationType?: string | undefined;
  unitAggregationField?: string | undefined;
  valueColumn?: string | undefined;
  dataSource?: AiConfigsMetricDataSourceRefRep$Outbound | undefined;
  filters?: AiConfigsFilter$Outbound | undefined;
  windowStartOffset?: number | undefined;
  windowEndOffset?: number | undefined;
  winsorLowerPercentile?: number | undefined;
  winsorUpperPercentile?: number | undefined;
  winsorIncludeImputed?: boolean | undefined;
};

/** @internal */
export const AiConfigsMetricDenominatorRep$outboundSchema: z.ZodType<
  AiConfigsMetricDenominatorRep$Outbound,
  z.ZodTypeDef,
  AiConfigsMetricDenominatorRep
> = z.object({
  eventName: z.string().optional(),
  isNumeric: z.boolean().optional(),
  unitAggregationType: z.string().optional(),
  unitAggregationField: z.string().optional(),
  valueColumn: z.string().optional(),
  dataSource: AiConfigsMetricDataSourceRefRep$outboundSchema.optional(),
  filters: AiConfigsFilter$outboundSchema.optional(),
  windowStartOffset: z.number().int().optional(),
  windowEndOffset: z.number().int().optional(),
  winsorLowerPercentile: z.number().optional(),
  winsorUpperPercentile: z.number().optional(),
  winsorIncludeImputed: z.boolean().optional(),
});

export function aiConfigsMetricDenominatorRepToJSON(
  aiConfigsMetricDenominatorRep: AiConfigsMetricDenominatorRep,
): string {
  return JSON.stringify(
    AiConfigsMetricDenominatorRep$outboundSchema.parse(
      aiConfigsMetricDenominatorRep,
    ),
  );
}
export function aiConfigsMetricDenominatorRepFromJSON(
  jsonString: string,
): SafeParseResult<AiConfigsMetricDenominatorRep, SDKValidationError> {
  return safeParse(
    jsonString,
    (x) => AiConfigsMetricDenominatorRep$inboundSchema.parse(JSON.parse(x)),
    `Failed to parse 'AiConfigsMetricDenominatorRep' from JSON`,
  );
}