import { TraceRecordInsertType, ObservationRecordInsertType, ScoreRecordInsertType, DatasetRunItemRecordInsertType } from "../../../src/server";
import { InsertResult } from "@clickhouse/client";
/**
 * Builds or executes ClickHouse SQL INSERT queries for seeding test data.
 *
 * Use executeXxxInsert() for custom curated data with detailed control.
 * Use buildBulkXxxInsert() for large datasets (>1000 items) for random distribution of data.
 */
export declare class ClickHouseQueryBuilder {
    private escapeString;
    /**
     * Creates INSERT query for trace data using VALUES syntax.
     * Use for: Small datasets, detailed trace objects with all fields populated.
     */
    executeTracesInsert(traces: TraceRecordInsertType[]): Promise<InsertResult>;
    /**
     * Creates INSERT query for observation data using VALUES syntax.
     * Use for: Small datasets, observations that link to postgres data (e.g. dataset runs)
     */
    executeObservationsInsert(observations: ObservationRecordInsertType[]): Promise<InsertResult>;
    /**
     * Creates INSERT query for dataset run items data using VALUES syntax.
     * Use for: Small datasets, dataset run items that link to postgres data (e.g. dataset runs)
     */
    executeDatasetRunItemsInsert(datasetRunItems: DatasetRunItemRecordInsertType[]): Promise<InsertResult>;
    /**
     * Creates INSERT query for score data using VALUES syntax.
     * Use for: Small datasets, scores with custom values and metadata.
     */
    executeScoresInsert(scores: ScoreRecordInsertType[]): Promise<InsertResult>;
    /**
     * Creates INSERT using ClickHouse numbers() function.
     * Use for: Large datasets (>1000 traces), realistic timestamps, bulk generation.
     */
    buildBulkTracesInsert(projectId: string, count: number, environment?: string, fileContent?: {
        heavyMarkdown: string;
        nestedJson: any;
        chatMlJson: any;
    }, opts?: {
        numberOfDays: number;
    }): string;
    /**
     * Creates observations with automatic prompt linking (10% rate).
     * Use for: Large datasets, hierarchical observations, cost/latency variation.
     */
    buildBulkObservationsInsert(projectId: string, tracesCount: number, observationsPerTrace?: number, environment?: string, fileContent?: {
        heavyMarkdown: string;
        nestedJson: any;
        chatMlJson: any;
    }, opts?: {
        numberOfDays: number;
    }): string;
    /**
     * Creates scores with mixed data types (NUMERIC/BOOLEAN/CATEGORICAL).
     * Use for: Large datasets, varied score distributions, synthetic metrics.
     */
    buildBulkScoresInsert(projectId: string, tracesCount: number, scoresPerTrace?: number, environment?: string, opts?: {
        numberOfDays: number;
    }): string;
}
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