/**
 * LLM-backed intent classifier — first step of the default pipeline.
 *
 * The framework stays SDK-agnostic. Bots wire in any structured-output LLM
 * call via the `classify` callback (Vercel AI SDK's `generateObject`, OpenAI
 * tool-calling, Anthropic structured output, a regex fallback, etc.).
 *
 * Example:
 *   const intents = ['question', 'booking', 'cancel', 'other'] as const;
 *   const classifier = new LLMIntentClassifier({
 *     intents,
 *     classify: async (text) => {
 *       const { object } = await generateObject({
 *         model: openai('gpt-4o-mini'),
 *         schema: z.object({ intent: z.enum(intents), confidence: z.number() }),
 *         prompt: text,
 *       });
 *       return object;
 *     },
 *     fallback: 'other',
 *   });
 */
import type { PipelineContext, PipelineStep, StepResult } from './types.js';
export interface IntentResult<I extends string> {
    intent: I;
    confidence?: number;
}
export type IntentClassifyFn<I extends string> = (text: string, opts: {
    intents: readonly I[];
    signal?: AbortSignal;
}) => Promise<IntentResult<I>>;
export interface LLMIntentClassifierOptions<I extends string> {
    intents: readonly I[];
    classify: IntentClassifyFn<I>;
    fallback: I;
    stepName?: string;
}
export declare class LLMIntentClassifier<I extends string> implements PipelineStep {
    readonly name: string;
    readonly intents: readonly I[];
    readonly classify: IntentClassifyFn<I>;
    readonly fallback: I;
    constructor({ intents, classify, fallback, stepName }: LLMIntentClassifierOptions<I>);
    run(ctx: PipelineContext, _decision: unknown): Promise<StepResult>;
}
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