import assert from "node:assert/strict";
import { readFileSync, readdirSync, statSync } from "node:fs";
import { join } from "node:path";
import test from "node:test";

import { answersFromEvidence } from "../src/lib/rectification-agentic/core/build-state.ts";
import {
  classifySnapshotStaleReason,
  storedSnapshotIsCurrent,
  type CandidateSnapshotSource,
} from "../src/lib/rectification-agentic/core/snapshot-source.ts";
import type { ConflictProbe } from "../src/lib/rectification-agentic/core/types.ts";
import { contrastPacketFromLatestResult } from "../src/lib/rectification-agentic/v9/decision-from-dossier.ts";
import {
  parseDiscriminatingEventProbes,
  parseProspectiveProbes,
  prospectiveWindowsNarration,
} from "../src/lib/rectification-agentic/v9/refinement-packet.ts";

const OUTCOMES = [
  { answer_class: "yes" as const, supports: ["05:00"], conflicts: ["05:07"] },
  { answer_class: "no" as const, supports: ["05:07"], conflicts: ["05:00"] },
];

function source(overrides: Partial<CandidateSnapshotSource> = {}): CandidateSnapshotSource {
  return {
    birthProfileFingerprint: "birth-a",
    scoreableEvidenceFingerprint: "score-a",
    inferenceRevision: 3,
    candidateSetVersion: "set-a",
    scoringPolicyVersion: "rectification-candidate-policy-v3",
    ...overrides,
  };
}

function qualityProbe(overrides: Record<string, unknown> = {}) {
  return {
    year: 2016,
    year_label: "2016 年 9 月",
    domain: "education",
    event_family: "学业或考试发挥失常、压力特别大",
    source: "known_event_quality",
    tracks: ["vimshottari", "narayana"],
    tracks_agree: true,
    unique_minute_claim: false,
    user_meaning: "2016 年 9 月那次上大学，更接近哪一种实际体验。",
    role: "distinguish",
    phase: "candidate_discriminator",
    semantic_key: "education.2016.known_event_quality",
    information_gain: 0.42,
    candidate_split_hash: "quality-split",
    candidate_set_version: "set-a",
    candidate_ids: ["05:00", "05:07"],
    expected_outcomes: OUTCOMES,
    choice_kind: "event_quality",
    question_contract_version: "probe-question-v1",
    target_evidence_id: "00000000-0000-4000-8000-000000000001",
    display_date_label: "2016 年 9 月",
    ...overrides,
  };
}

function walkFiles(root: string, suffixes: readonly string[]): string[] {
  const skip = new Set(["node_modules", ".next", "dist"]);
  const out: string[] = [];
  const visit = (dir: string) => {
    for (const name of readdirSync(dir)) {
      if (skip.has(name)) continue;
      const path = join(dir, name);
      const stat = statSync(path);
      if (stat.isDirectory()) visit(path);
      else if (suffixes.some((suffix) => name.endsWith(suffix))) out.push(path);
    }
  };
  visit(root);
  return out;
}

test("scoring policy version changes stale stored snapshots", () => {
  const current = source();
  const previous = source({ scoringPolicyVersion: "rectification-candidate-policy-v2" });
  assert.equal(classifySnapshotStaleReason(previous, current), "scoring_policy_changed");
  assert.equal(storedSnapshotIsCurrent(previous, current), false);
  assert.equal(storedSnapshotIsCurrent(current, current), true);
});

test("anchored known_event_quality distinguish probes stay in the public packet", () => {
  const parsed = parseDiscriminatingEventProbes([qualityProbe()]);
  assert.equal(parsed.length, 1);
  assert.equal(parsed[0]?.source, "known_event_quality");
  assert.equal(parsed[0]?.role, "distinguish");
  assert.equal(parsed[0]?.target_evidence_id, "00000000-0000-4000-8000-000000000001");

  const unanchored = parseDiscriminatingEventProbes([qualityProbe({ target_evidence_id: undefined })]);
  assert.equal(unanchored.length, 0);

  const packet = contrastPacketFromLatestResult({
    resultId: "result-a",
    decisionReceipt: {
      discriminating_event_probes: [qualityProbe()],
      inference_state: {
        probes: [{
          id: "probe:education.2016.known_event_quality:quality-split",
          semantic_key: "education.2016.known_event_quality",
          candidate_split_hash: "quality-split",
          domain: "education",
          year: 2016,
          question: "2016 年 9 月那次上大学，更接近哪一种实际体验。",
          candidate_ids: ["05:00", "05:07"],
          expected_outcomes: OUTCOMES,
          information_gain: 0.42,
          source: "known_event_quality",
          choice_kind: "event_quality",
          target_evidence_id: "00000000-0000-4000-8000-000000000001",
        }],
        answered_probes: [],
      },
    },
  });
  assert.equal(
    packet.probes.some((item) => (
      item.semanticKey === "education.2016.known_event_quality"
      || item.choiceKind === "event_quality"
    )),
    true,
  );
});

test("quality answers are not inferred from event existence alone", () => {
  const probe: ConflictProbe = {
    id: "probe-quality",
    semantic_key: "education.2016.known_event_quality",
    candidate_split_hash: "quality-split",
    domain: "education",
    year: 2016,
    question: "那次上大学更接近哪一种体验",
    candidate_ids: ["05:00", "05:07"],
    expected_outcomes: OUTCOMES,
    information_gain: 0.42,
    source: "known_event_quality",
    choice_kind: "event_quality",
  };
  const answers = answersFromEvidence([probe], [{
    id: "00000000-0000-4000-8000-000000000001",
    domain: "education",
    year: 2016,
    precision: "month",
  }]);
  assert.equal(answers.length, 0);
});

test("prospective probes stay out of scoring copy", () => {
  const parsed = parseProspectiveProbes([{
    candidate_label: "A",
    domain: "career",
    window_label: "2027 年 3 月附近",
    user_meaning: "候选 A 预测下一次事业变动更可能在 2027 年 3 月附近。这是预测窗口，不是承诺；下次发生时回来补一条，可进一步分辨。",
    used_for_scoring: false,
  }]);
  assert.equal(parsed.length, 1);
  const copy = prospectiveWindowsNarration(parsed);
  assert.match(String(copy), /预测窗口/);
  assert.equal(parsed[0]?.used_for_scoring, false);
});

test("scripts and frontend contain no answer-key literals", () => {
  const forbidden = ["target" + "_minute", "pl9_" + "1993", "regression" + "_only"];
  const files = [
    ...walkFiles(join(process.cwd(), "src"), [".ts", ".tsx", ".js"]),
    ...walkFiles(join(process.cwd(), "tests"), [".ts", ".tsx"]),
  ];
  const hits: string[] = [];
  for (const file of files) {
    const text = readFileSync(file, "utf8");
    for (const token of forbidden) {
      if (text.includes(token)) hits.push(`${file}:${token}`);
    }
  }
  assert.deepEqual(hits, []);
});