// Backfill: LLM-extract atomic, reusable facts from raw daily conversation logs and store them
// in the daily_extracts Chroma collection (separate from memory_write's clean user_facts
// collection — see project_vector_memory_chroma memory for why). Naive paragraph-chunking of
// raw transcripts was tried first and abandoned (too noisy, see migrate-memory-to-chroma.ts) —
// this replaces that approach with real extraction.
import fs from 'fs';
import path from 'path';
import { addVector, hasAnyVector, DAILY_EXTRACTS_COLLECTION } from '../src/gateway/memory/memory-vector';

const WORKSPACES: { workspace: string; label: string }[] = [
  { workspace: '/srv/homeclaw/.smallclaw/users/papa/workspace', label: 'papa' },
  { workspace: '/srv/homeclaw/.smallclaw/users/jasmine/workspace', label: 'jasmine' },
  { workspace: '/srv/homeclaw/.smallclaw/users/cherry/workspace', label: 'cherry' },
  { workspace: '/srv/homeclaw/.smallclaw/workspace', label: 'global' },
];

const OLLAMA_ENDPOINT = 'http://localhost:11434';
const EXTRACT_MODEL = 'gemma4:31b-cloud'; // matches homeclaw's configured primary model

async function extractFacts(dayContent: string): Promise<string[]> {
  const prompt = `다음은 하루치 대화 로그입니다. 이 중에서 나중에 다시 참고할 가치가 있는 사실만 뽑아줘.

규칙:
- 재사용 가능한 구체적 정보만 (하드웨어 스펙, 설정값, 결정사항, 프로젝트 진행상황, 사용자의 취향/제약사항 등)
- 일회성 질문-답변, 잡담, 이미 끝난 계산/설명은 제외
- 각 사실은 한 줄에 하나씩, 문맥 없이도 이해되는 완결된 문장으로 작성 (예: "클로서버는 RTX 3060 12GB 2개를 사용한다" 처럼 — 어느 대상 얘기인지 반드시 명시)
- 뽑을 게 없으면 "없음"이라고만 답해
- 사실 목록 외의 설명이나 서두는 쓰지 마

--- 로그 시작 ---
${dayContent}
--- 로그 끝 ---`;

  const res = await fetch(`${OLLAMA_ENDPOINT}/api/chat`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      model: EXTRACT_MODEL,
      messages: [{ role: 'user', content: prompt }],
      stream: false,
    }),
    signal: AbortSignal.timeout(120_000),
  });
  if (!res.ok) throw new Error(`extract HTTP ${res.status}`);
  const data: any = await res.json();
  const raw = String(data?.message?.content || '').trim();
  if (!raw || raw === '없음') return [];

  return raw
    .split('\n')
    .map(l => l.trim().replace(/^[-*]\s*/, ''))
    .filter(l => l && l !== '없음');
}

async function processWorkspace(workspace: string, label: string) {
  const memDir = path.join(workspace, 'memory');
  if (!fs.existsSync(memDir)) {
    console.log(`[${label}] no memory dir, skip`);
    return;
  }
  // Never process today's file — it's still being written to during the day, so extracting
  // it early would capture a partial day and then skip it forever (hasAnyVector marks it
  // "done"). A nightly cron run naturally picks up "yesterday" once it's actually complete.
  const today = new Date().toISOString().slice(0, 10);
  const dailyFiles = fs.readdirSync(memDir)
    .filter(f => /^\d{4}-\d{2}-\d{2}\.md$/.test(f))
    .filter(f => f.replace('.md', '') < today)
    .sort();
  let totalFacts = 0, daysProcessed = 0, daysSkipped = 0, daysFailed = 0;

  for (const f of dailyFiles) {
    const date = f.replace('.md', '');
    const content = fs.readFileSync(path.join(memDir, f), 'utf-8').trim();
    if (!content) { daysSkipped++; continue; }

    if (await hasAnyVector(DAILY_EXTRACTS_COLLECTION, { workspace, date })) {
      daysSkipped++;
      continue;
    }

    try {
      const facts = await extractFacts(content);
      if (facts.length === 0) {
        // Record a sentinel so hasAnyVector() sees this date as processed on future reruns —
        // otherwise a legitimately fact-free day gets re-sent to the LLM every single rerun.
        await addVector(DAILY_EXTRACTS_COLLECTION, {
          id: `${workspace}:daily-extract:${date}:none`,
          text: '(해당 날짜에 재사용 가치 있는 사실 없음)',
          metadata: { workspace, date, source: 'daily-extract', empty: true },
        });
      } else {
        for (let i = 0; i < facts.length; i++) {
          const id = `${workspace}:daily-extract:${date}:${i}`;
          await addVector(DAILY_EXTRACTS_COLLECTION, {
            id,
            text: facts[i],
            metadata: { workspace, date, source: 'daily-extract' },
          });
        }
      }
      totalFacts += facts.length;
      daysProcessed++;
      console.log(`[${label}] ${date}: ${facts.length}개 추출`);
    } catch (err: any) {
      daysFailed++;
      console.warn(`[${label}] ${date} 실패: ${err.message}`);
    }
  }

  console.log(`[${label}] 완료 — ${daysProcessed}일 처리, ${totalFacts}개 사실, ${daysSkipped}일 스킵(빈파일), ${daysFailed}일 실패`);
}

async function main() {
  for (const { workspace, label } of WORKSPACES) {
    await processWorkspace(workspace, label);
  }
}

main().then(() => process.exit(0)).catch(err => { console.error(err); process.exit(1); });