/**
 * @license
 * Copyright 2026 Steven Roussey <sroussey@gmail.com>
 * SPDX-License-Identifier: Apache-2.0
 */
import type { ChunkStrategy, IKbAiStrategy, SearchMode } from "@workglow/knowledge-base";
/**
 * Tuning knobs for the standard strategy. Most defaults come straight from
 * the KB (model IDs, chunkStrategy, searchMode); these overrides exist for
 * callers that want different chunker token budgets than the built-in
 * defaults or that need to pin a search mode different from what the KB
 * has stored.
 */
export interface CreateStandardKbStrategyOptions {
    readonly chunker?: {
        readonly maxTokens?: number;
        readonly overlap?: number;
        readonly reservedTokens?: number;
    };
    /** Override KB's chunkStrategy at strategy-build time. */
    readonly chunkStrategy?: ChunkStrategy;
    /** Override KB's searchMode at strategy-build time. */
    readonly searchMode?: SearchMode;
    /**
     * Multiplier applied to `topK` to size the first-stage candidate pool
     * when `searchMode === "rerank"`. The reranker then narrows the pool
     * back down to `topK`. Defaults to `5`, i.e. first stage fetches
     * `topK * 5` candidates. Used together with `firstStageMinimum` —
     * the actual first-stage size is `max(topK * firstStageMultiplier,
     * firstStageMinimum)`, so a tiny `topK` (e.g. `1`) still yields a
     * meaningful candidate pool for the reranker to choose from instead of
     * collapsing to a single candidate.
     */
    readonly firstStageMultiplier?: number;
    /**
     * Minimum first-stage candidate pool size when `searchMode === "rerank"`.
     * Defaults to `20`. Prevents the rerank pool from collapsing to
     * `topK` for very small `topK` values where `topK * firstStageMultiplier`
     * would still be too few candidates for the reranker to do useful work.
     * The effective first-stage size is
     * `max(topK * firstStageMultiplier, firstStageMinimum)`.
     */
    readonly firstStageMinimum?: number;
}
/**
 * The standard KB strategy: hierarchical-by-default chunking + embedding
 * during ingest, and a single search mode for retrieval. Search and ingest
 * read the KB's stored model IDs (`docEmbeddingModel` /
 * `queryEmbeddingModel` / `rerankerModel`) and config fields
 * (`chunkStrategy` / `searchMode`) on every call, so updates to the KB
 * record take effect immediately on the next op.
 *
 * Score semantics: results carry `scoreType` matching the retrieval
 * mode — `"cosine"` for similarity, `"rrf"` for hybrid, `"rerank"` for
 * both reranker-model and heuristic fallback paths. **Cross-encoder
 * rerank scores are raw logits**, not probabilities or similarities, and
 * they are NOT comparable to cosine / BM25 / RRF scores. Always check
 * `scoreType` before applying a score threshold; the strategy itself
 * ignores `ISearchOptions.scoreThreshold` in the rerank branch.
 *
 * For custom RAG flows (per-tenant scoping, alternative chunkers, etc.)
 * write your own `IKbAiStrategy` — this factory is the "good defaults"
 * path, not the only path.
 */
export declare function createStandardKbStrategy(options?: CreateStandardKbStrategyOptions): IKbAiStrategy;
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