/**
 * Finish-reason constants and helpers.
 *
 * LLM providers emit different keys (`finish_reason`, `stop_reason`,
 * `stopReason`, `finishReason`) and different values for the same concept.
 * This module is the single source of truth for detecting *truncation* —
 * i.e., the model hit its output budget and the response is incomplete.
 *
 * Used by:
 *  - `Graph.ts` — sticky `lastFinishReason` across inner subgraph invokes,
 *    so host's continuation retry can detect truncation that happens
 *    inside a scoped-subgraph child node.
 *  - Any future continuation / auto-retry logic added to agents.
 *
 * Kept as a small utils module (instead of inline in Graph.ts) so that
 * additional callers — e.g., structured output recovery, sub-agent
 * orchestrators — can reuse the exact same detection logic without drift.
 */

/**
 * Canonical set of finish-reason strings that mean "output was truncated".
 *
 * Covers:
 *  - `max_tokens` — Anthropic direct API, Bedrock
 *  - `length`    — OpenAI/Azure
 *  - `MAX_TOKENS` — VertexAI/Google (uppercased enum)
 */
export const TRUNCATION_FINISH_REASONS: ReadonlySet<string> = new Set([
  'max_tokens',
  'length',
  'MAX_TOKENS',
]);

/**
 * @returns true when the given finish/stop reason indicates the response
 *          was cut short by the output token budget.
 */
export function isTruncationReason(reason: string | undefined | null): boolean {
  return reason != null && TRUNCATION_FINISH_REASONS.has(reason);
}