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    Interface RelationshipDiscoveryConfig

    interface RelationshipDiscoveryConfig {
        backpropagation: { enabled: boolean; maxIterations: number };
        confidence: {
            foreignKeyMinimum: number;
            llmValidationThreshold: number;
            primaryKeyMinimum: number;
        };
        enabled: boolean;
        indexBackedCandidates?: boolean;
        llmValidation: { batchSize: number; enabled: boolean };
        patterns: {
            compositeKeyIndicators: string[];
            foreignKeyNames: string[];
            primaryKeyNames: string[];
        };
        sampling: {
            maxRowsPerTable: number;
            statisticalSignificance: number;
            valueOverlapSampleSize: number;
        };
        tokenBudget: { maxTokens?: number; ratioOfTotal?: number };
        triggers: {
            fkDeficitThreshold: number;
            runOnInsufficientFKs: boolean;
            runOnMissingPKs: boolean;
        };
    }
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    Properties

    backpropagation confidence enabled indexBackedCandidates? llmValidation patterns sampling tokenBudget triggers

    Properties

    backpropagation: { enabled: boolean; maxIterations: number }
    confidence: {
        foreignKeyMinimum: number;
        llmValidationThreshold: number;
        primaryKeyMinimum: number;
    }
    enabled: boolean
    indexBackedCandidates?: boolean

    Use existing unique indexes as PK evidence for tables with no declared primary key (default true): a unique index on NOT NULL columns becomes a candidate even when the statistics can't show uniqueness (e.g. an empty table), and composite unique indexes are considered when no single column qualifies (next to a qualifying single-column key they are alternate keys and are not added). Needs analysis.useExistingIndexes (also default true).

    llmValidation: { batchSize: number; enabled: boolean }
    patterns: {
        compositeKeyIndicators: string[];
        foreignKeyNames: string[];
        primaryKeyNames: string[];
    }
    sampling: {
        maxRowsPerTable: number;
        statisticalSignificance: number;
        valueOverlapSampleSize: number;
    }
    tokenBudget: { maxTokens?: number; ratioOfTotal?: number }
    triggers: {
        fkDeficitThreshold: number;
        runOnInsufficientFKs: boolean;
        runOnMissingPKs: boolean;
    }

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