/**
 * The **Context Router** — Photon AI's token-optimization layer.
 *
 * Before a prompt reaches the LLM, the router classifies it into one or more
 * {@link PhotonAIDomain}s and reports which columns it appears to name. The
 * provider pipeline then sends *only* the capabilities, column fields, state
 * slices, and prompt sections those domains require.
 *
 * ### Why this is not keyword matching
 * Photon AI's design rule is intent detection over keyword lists. The router
 * honours that by deriving its vocabulary from the **live intent registry**:
 * every intent already declares the alias phrases that identify it, and every
 * intent key already maps to a domain. So the router's dictionary *is* the
 * registry — a custom intent registered at runtime becomes routable with no
 * change here, and an alias reworded in a builtin updates routing for free.
 * Nothing in this file enumerates English words for grid concepts.
 *
 * ### Failure mode
 * Under-including is the only dangerous outcome: a filter request that arrives
 * without filter operators cannot be answered. Every ambiguity therefore
 * resolves toward *more* context — an unrecognized prompt falls back to the
 * full payload, exactly matching the pre-router behaviour. The optimization is
 * strictly opportunistic.
 *
 * @packageDocumentation
 */
import type { ColumnDef } from '../../types/column.types';
import type { PhotonAICommandRegistry } from '../photon-ai-registry';
import { PhotonAIDomain, type PhotonAIContextScope } from './ai-provider.types';
/**
 * Resolves the domains one intent key belongs to.
 *
 * Shared with `GridContextBuilder`, which uses it to decide whether a
 * registered intent's capability entry belongs in a scoped context — so the
 * classification that selects domains and the projection that honours them can
 * never disagree about which domain an intent lives in.
 *
 * An empty result means "unattributed", which callers must treat as
 * *always include* rather than *never include*: that is the signature of a
 * host-app custom intent, and withholding it would make it unreachable.
 */
export declare function domainsForIntentKey(key: string): readonly PhotonAIDomain[];
/**
 * Classifies a natural-language prompt into the minimal set of grid domains
 * needed to answer it, and the columns it names.
 *
 * Construct once per service; {@link route} is pure with respect to the
 * registry's contents at call time, so runtime-registered intents are picked up
 * on the next prompt without any invalidation step.
 */
export declare class ContextRouter {
    private readonly registry;
    constructor(registry: PhotonAICommandRegistry);
    /**
     * Classifies `prompt` and returns the context scope to build for it.
     *
     * @param prompt  - The raw user command, exactly as typed.
     * @param columns - The grid's current columns, used to detect column mentions.
     */
    route(prompt: string, columns: readonly ColumnDef[]): PhotonAIContextScope;
    /**
     * Matches the prompt's tokens against every registered intent's alias
     * phrases, collecting the domain of each intent that fires.
     *
     * An intent counts as referenced when *any* of its alias phrases is fully
     * covered by the token set — the same containment rule `IntentParser` uses to
     * pick a command, applied here without the tie-breaking, because routing
     * wants the union of plausible domains rather than a single winner. Sending
     * two domains when the user meant one costs a little; sending the wrong one
     * costs the request.
     */
    private classifyDomains;
    /**
     * Finds columns the prompt names, by exact word match against each column's
     * `colId`, `field`, and `header`.
     *
     * Deliberately exact rather than fuzzy: `EntityResolver` does fuzzy matching
     * when it must resolve *the* target column, but here a wrong guess would
     * silently drop the column the user actually meant from the context. An exact
     * miss just means all columns are sent — correct, only less cheap. Multi-word
     * headers match when every one of their words is present.
     */
    private detectColumns;
    /** Whether any of a column's names appears in the prompt's words. */
    private mentionsColumn;
}
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