agentfootprint/dist/types/injection-engine/llmClassifier.d.ts

The explainable agent framework — backtrack a wrong answer to the exact context that caused it (evidence, not guesses). Built on footprintjs.

/**
 * llmClassifier — an {@link IntentScorer} that asks a model which declared
 * intent the new message is (SG-C tier 2). ONE call per turn, off the hot
 * loop, in the RouteTurn stage — never inside the ReAct iterations.
 *
 * **Constrained enum, never free text.** The pick runs through
 * {@link constrainedEnumPick} (extracted from this module in 9.19.0 so the
 * tier-3 decider shares the same discipline): when the provider declares
 * forced-tool support for that model it rides a forced synthetic tool whose single
 * argument is `enum: [...candidateIds, 'none']` (the same machinery the
 * `'tool-forced'` output strategy uses); on any other provider it is a
 * strict single-line parse validated against the enum, ONE structured
 * re-ask, then `'none'`. An off-enum answer is a parse failure, not a route
 * — this scorer can never emit an id it wasn't given.
 *
 * Output maps to scores the framework can judge: picked id → 1, others → 0;
 * `'none'` → all 0. `floor: 0` (so `'none'` is honestly "unmatched") and
 * `categorical: true` (one id or none — a pick is decisive by construction,
 * never diluted by the near-tie margin; see `routingPolicy.ts`).
 *
 * One of the two injection-engine scorer modules that import
 * `provider-contract/types` (the other is `constrainedEnumPick`, its machinery) —
 * kept out of `entryScorer.ts` so the keyword/embedding paths stay
 * adapter-free.
 */
import type { LLMProvider } from '../provider-contract/types.js';
import type { IntentScorer } from './intentScorer.js';
export interface LlmClassifierOptions {
    /** Model to classify with. Name it for any real provider — left unset, the
     *  request carries an empty model id, which only the mock tolerates. */
    readonly model?: string;
    /** Recent-turns window (count of prior conversational turns shown to the
     *  classifier). Absent = current message only. */
    readonly window?: number;
    /** Prompt budget: examples listed per intent. Default 5. */
    readonly maxExamplesPerIntent?: number;
}
/** Build the classifier. See the module header for the enum discipline. */
export declare function llmClassifier(provider: LLMProvider, options?: LlmClassifierOptions): IntentScorer;
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