/**
 * LLM-based reranker ("judge").
 *
 * Takes a small pool of search candidates and asks an LLM to score each
 * for semantic relevance to the query. Blends the LLM score with the
 * underlying retrieval score so a poorly-calibrated LLM call can't
 * catastrophically drop a high-confidence retrieval result.
 *
 * Optional — only used when `ai_curation.enabled` is true.
 */
import type { LLMProvider } from '../../core/llm-provider.js';
import type { SearchResult } from '../../core/types.js';
export interface LLMJudgeCandidate {
    id: string;
    content: string;
    retrievalScore: number;
}
export interface LLMJudgeOptions {
    /** Maximum characters of content passed per candidate to the LLM. */
    contentSnippetChars?: number;
    /** Maximum candidates sent to the LLM in one call. */
    maxCandidates?: number;
    /** Weight blend: retrieval_weight + llm_weight must equal 1. */
    retrievalWeight?: number;
    llmWeight?: number;
    /** Minimum milliseconds between LLM calls (simple rate limiting). */
    minRequestIntervalMs?: number;
}
/**
 * LLMJudge — minimalist reranker that asks an LLM to score candidates 0..10.
 * Blends the normalized LLM score with the retrieval score.
 */
export declare class LLMJudge {
    private provider;
    private opts;
    private lastRequestAt;
    constructor(provider: LLMProvider, opts?: LLMJudgeOptions);
    private rateLimit;
    /**
     * Score each candidate from 0..10 for relevance to the query.
     * Returns a score array aligned to the input candidates.
     * Returns null on failure (caller should fall back to retrieval scores).
     */
    private scoreCandidates;
    /**
     * Rerank search results using the LLM as a semantic judge.
     * Blends LLM scores with retrieval scores so a bad LLM call can't drop correct docs.
     */
    rerank(query: string, results: SearchResult[], contentLookup: (id: string) => string | undefined, limit: number): Promise<SearchResult[]>;
}
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