// kb_index — generic on-the-fly aggregation over append-only JSONL
// scratchpads (audit_lessons, scrum_reviews, outcomes, observer ops).
//
// The mem0 insight: raw rows are CHEAP and tell the full story, but
// downstream prompts need a DEFINITION, not a log. A definition is
// the aggregate: "this signature has fired N times across M distinct
// scopes, first_seen=X, last_seen=Y, confidence=M/N."
//
// This library is the single shared aggregator. Every KB writer keeps
// appending raw rows; every KB reader uses aggregate() instead of
// tailing the raw stream. No second file to sync, no ADD/UPDATE/NOOP
// routing — the stats roll up from the raw rows every time.
//
// Why this works past hundreds of runs:
//   - aggregate() is bounded by distinct_signatures, not total_rows.
//   - confidence = distinct_scopes / count — low for same-scope noise,
//     high for cross-scope patterns. Downstream severity ramps on
//     confidence × count, not raw count, so one unfixed PR can't
//     inflate its own recurrence score (the classic mem0 failure).
//   - rotation (later) moves old raw to archive files; aggregate()
//     can still read both to compute lifetime counts when needed.

import { readFile } from "node:fs/promises";

export interface AggregateRow {
  signature: string;
  count: number;
  distinct_scopes: number;
  first_seen: string;
  last_seen: string;
  confidence: number;        // distinct_scopes / count — capped at 1.0
  representative_summary: string;  // most-recent summary for this signature
  scopes: string[];          // up to 20 most-recent scopes for debugging
  checks: string[];          // distinct `check` values (audit_lessons-specific)
}

export interface AggregateOptions<T> {
  /** How to extract the dedup key from a row. */
  keyFn: (row: T) => string | undefined;
  /** How to extract the "scope" — distinct scopes count gives confidence. */
  scopeFn: (row: T) => string | undefined;
  /** How to extract the timestamp (defaults to row.audited_at / row.reviewed_at / row.timestamp). */
  timeFn?: (row: T) => string | undefined;
  /** How to extract a representative summary (defaults to row.summary). */
  summaryFn?: (row: T) => string | undefined;
  /** Max rows to read from the JSONL tail; 0 = read all. */
  tailLimit?: number;
  /** Include per-row check field (for multi-check aggregates). */
  checkFn?: (row: T) => string | undefined;
}

/**
 * Read a JSONL file and produce the aggregate map keyed by signature.
 * Safe on missing or malformed files — returns empty map.
 */
export async function aggregate<T = any>(
  jsonlPath: string,
  opts: AggregateOptions<T>,
): Promise<Map<string, AggregateRow>> {
  const out = new Map<string, AggregateRow>();
  let raw: string;
  try { raw = await readFile(jsonlPath, "utf8"); } catch { return out; }
  const lines = raw.split("\n").filter(l => l.length > 0);
  const sliceFrom = opts.tailLimit && opts.tailLimit > 0 ? Math.max(0, lines.length - opts.tailLimit) : 0;

  const timeFn = opts.timeFn ?? ((r: any) => r?.audited_at ?? r?.reviewed_at ?? r?.timestamp ?? r?.ran_at);
  const summaryFn = opts.summaryFn ?? ((r: any) => r?.summary ?? r?.representative_summary);

  // Per-signature scope tracking — need counts by scope to compute
  // distinct_scopes without double-counting a scope that appears 50
  // times. Using a Set<scope> per signature.
  const scopeSets = new Map<string, Set<string>>();
  const checkSets = new Map<string, Set<string>>();

  for (let i = sliceFrom; i < lines.length; i++) {
    let row: T;
    try { row = JSON.parse(lines[i]) as T; } catch { continue; }
    const sig = opts.keyFn(row);
    if (!sig) continue;

    let agg = out.get(sig);
    if (!agg) {
      agg = {
        signature: sig,
        count: 0,
        distinct_scopes: 0,
        first_seen: "",
        last_seen: "",
        confidence: 0,
        representative_summary: "",
        scopes: [],
        checks: [],
      };
      out.set(sig, agg);
      scopeSets.set(sig, new Set<string>());
      checkSets.set(sig, new Set<string>());
    }

    agg.count += 1;

    const scope = opts.scopeFn(row);
    if (scope !== undefined && scope !== null && scope !== "") {
      scopeSets.get(sig)!.add(String(scope));
      // Keep scopes array ordered by recency (newest wins — shift
      // oldest when at cap).
      const arr = agg.scopes;
      const s = String(scope);
      const existing = arr.indexOf(s);
      if (existing >= 0) arr.splice(existing, 1);
      arr.push(s);
      if (arr.length > 20) arr.shift();
    }

    if (opts.checkFn) {
      const c = opts.checkFn(row);
      if (c) checkSets.get(sig)!.add(String(c));
    }

    const t = timeFn(row);
    if (t) {
      if (!agg.first_seen || t < agg.first_seen) agg.first_seen = t;
      if (!agg.last_seen  || t > agg.last_seen)  agg.last_seen = t;
    }

    const s = summaryFn(row);
    if (s) agg.representative_summary = String(s);
  }

  // Finalize derived fields.
  for (const [sig, agg] of out) {
    const scopes = scopeSets.get(sig) ?? new Set<string>();
    agg.distinct_scopes = scopes.size;
    agg.confidence = agg.count > 0 ? Math.min(1, agg.distinct_scopes / agg.count) : 0;
    const checks = checkSets.get(sig);
    if (checks) agg.checks = Array.from(checks).sort();
  }
  return out;
}

/**
 * Severity policy derived from aggregate stats. The rating lives here
 * (not in each check) so all KB readers ramp severity consistently.
 *
 *   - confidence × count product is the real signal.
 *   - Low confidence (< 0.3) = same-scope noise → info regardless of count.
 *   - Mid confidence (0.3-0.6) = mixed signal → warn at count ≥ 3.
 *   - High confidence (> 0.6) with count ≥ 5 = block-worthy cross-cutting pattern.
 *
 * Callers can override by reading agg directly; this is the default
 * policy that matches the "don't escalate one unfixed PR" discipline.
 */
export function ratingSeverity(agg: AggregateRow): "info" | "warn" | "block" {
  if (agg.confidence >= 0.6 && agg.count >= 5) return "block";
  if (agg.confidence >= 0.3 && agg.count >= 3) return "warn";
  return "info";
}

/** Human-friendly one-line summary of an aggregate row for finding evidence. */
export function formatAgg(agg: AggregateRow): string {
  return `count=${agg.count} distinct_scopes=${agg.distinct_scopes} confidence=${agg.confidence.toFixed(2)} seen=[${agg.first_seen.slice(0, 10)}..${agg.last_seen.slice(0, 10)}]`;
}