778e8526d4
- 누적 작업트리 커밋: 회기 평가 복구·durable 저장, 라이브 코치 이력/근거, 교수자 학생분석, 음성 비언어 메타, PII 마스킹, 운영 티켓/헬스 등 - 문서: 완료 기록 docs/archive/ 냉동 보관, docs/ 단일 인덱스(docs/README.md)+통합 TODO(docs/TODO.md)로 정리 - 리팩터(행위 보존): Stage enum SSOT(taxonomy 소유·state_machine re-export), store recent/masked_turns 중복 제거, speaker_ko_label 단일 헬퍼, _list_sessions N+1 제거(state/turns 배치 + 턴평가 하이드레이션 배치) - 검증: 백엔드 pytest 352 passed, _list_sessions E2E chromium-single-run 2 passed
325 lines
11 KiB
Python
325 lines
11 KiB
Python
from __future__ import annotations
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import argparse
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import asyncio
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import json
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import os
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import sys
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from datetime import UTC, datetime
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from pathlib import Path
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from typing import Any
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REPO_ROOT = Path(__file__).resolve().parents[1]
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API_ROOT = REPO_ROOT / "apps" / "api"
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sys.path.insert(0, str(API_ROOT))
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import asyncpg # noqa: E402
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from app.services.dataset_export import ( # noqa: E402
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APPROVED_EXPORT_STATUS,
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DRY_RUN_EXPORT_STATUS,
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ExportKeyMaps,
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build_dataset_record,
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build_manifest,
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cohen_kappa,
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intraclass_correlation,
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scan_for_pii,
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sha256_file,
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validate_manifest_gate,
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write_jsonl,
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)
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TURN_QUERY = """
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SELECT
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s.id::text AS session_id,
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s.learner_id::text AS learner_id,
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COALESCE(pc.code, s.persona_id::text, 'unknown') AS persona_code,
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s.started_at AS session_started_at,
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s.ended_at AS session_ended_at,
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t.id::text AS turn_id,
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t.seq,
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t.speaker,
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t.stage,
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t.text_masked,
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t.created_at,
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COALESCE(
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jsonb_agg(DISTINCT jsonb_build_object(
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'dimension', fs.dimension,
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'score', fs.score,
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'rationale', fs.rationale,
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'loop', fs.loop
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)) FILTER (WHERE fs.dimension IS NOT NULL),
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'[]'::jsonb
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) AS feedback_scores,
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COALESCE(
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jsonb_agg(DISTINCT jsonb_build_object(
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'code', tech.code,
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'display_name', tech.display_name,
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'category', tech.category
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)) FILTER (WHERE tech.code IS NOT NULL),
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'[]'::jsonb
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) AS techniques,
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COALESCE(
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jsonb_agg(DISTINCT jsonb_build_object(
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'code', cs.code,
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'display_name', cs.display_name
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)) FILTER (WHERE cs.code IS NOT NULL),
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'[]'::jsonb
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) AS client_states,
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COALESCE(
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jsonb_agg(DISTINCT jsonb_build_object(
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'kind', sc.kind,
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'intent_deviation', sc.intent_deviation
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)) FILTER (WHERE sc.id IS NOT NULL),
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'[]'::jsonb
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) AS supervisor_comments
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FROM app.turns t
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JOIN app.sessions s ON s.id = t.session_id
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JOIN app.app_user u ON u.user_id = s.learner_id
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LEFT JOIN app.persona_card pc
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ON pc.persona_id = s.persona_id AND pc.version = s.persona_version
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LEFT JOIN app.feedback_scores fs ON fs.turn_id = t.id
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LEFT JOIN app.turn_technique tt ON tt.turn_id = t.id
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LEFT JOIN app.technique_label_def tech ON tech.label_id = tt.label_id
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LEFT JOIN app.turn_client_state tcs ON tcs.turn_id = t.id
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LEFT JOIN app.client_state_def cs ON cs.label_id = tcs.label_id
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LEFT JOIN app.supervisor_comment sc ON sc.turn_id = t.id
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WHERE u.is_active
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AND u.consent_at IS NOT NULL
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AND t.text_masked IS NOT NULL
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AND btrim(t.text_masked) <> ''
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AND 'client' = ANY(t.visible_to)
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AND ($1::timestamptz IS NULL OR t.created_at >= $1::timestamptz)
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AND ($2::timestamptz IS NULL OR t.created_at < $2::timestamptz)
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AND ($4::boolean = false OR u.cohort = $3::text)
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GROUP BY s.id, s.learner_id, pc.code, t.id, t.seq, t.speaker, t.stage, t.text_masked, t.created_at
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ORDER BY t.created_at, s.id, t.seq
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LIMIT $5
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"""
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ANNOTATION_QUERY = """
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SELECT
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di.item_id::text AS item_id,
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ar.round_id::text AS round_id,
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a.annotator,
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a.labels
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FROM ds.annotation a
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JOIN ds.annotation_round ar ON ar.round_id = a.round_id
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JOIN ds.dataset_item di ON di.item_id = a.item_id
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WHERE ar.dataset_id = $1
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ORDER BY di.item_id, ar.round_id, a.annotation_id
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"""
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def parse_time(value: str | None) -> datetime | None:
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if not value:
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return None
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normalized = value.replace("Z", "+00:00")
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parsed = datetime.fromisoformat(normalized)
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if parsed.tzinfo is None:
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parsed = parsed.replace(tzinfo=UTC)
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return parsed
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def make_export_id() -> str:
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return f"phase3-rl-seed-{datetime.now(UTC).strftime('%Y%m%d')}-001"
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def row_to_dict(row: asyncpg.Record) -> dict[str, Any]:
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return {key: row[key] for key in row.keys()}
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async def fetch_rows(conn: asyncpg.Connection, args: argparse.Namespace) -> list[dict[str, Any]]:
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rows = await conn.fetch(
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TURN_QUERY,
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parse_time(args.started_at),
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parse_time(args.ended_at),
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args.cohort_id,
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args.apply_cohort_filter,
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args.limit,
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)
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return [row_to_dict(row) for row in rows]
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async def write_dataset_rows(
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conn: asyncpg.Connection,
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*,
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dataset_name: str,
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purpose: str,
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raw_rows: list[dict[str, Any]],
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records: list[dict[str, Any]],
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) -> int:
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dataset_id = await conn.fetchval(
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"INSERT INTO ds.dataset (name, purpose) VALUES ($1, $2) RETURNING dataset_id",
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dataset_name,
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purpose,
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)
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for raw_row, record in zip(raw_rows, records):
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await conn.execute(
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"INSERT INTO ds.dataset_item (dataset_id, turn_id, payload) VALUES ($1, $2::uuid, $3::jsonb)",
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dataset_id,
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raw_row["turn_id"],
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json.dumps(record, ensure_ascii=False),
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)
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return int(dataset_id)
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async def fetch_agreement(conn: asyncpg.Connection, dataset_id: int | None, args: argparse.Namespace) -> dict[str, Any]:
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if dataset_id is None:
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return {"kappa": None, "icc": None, "gold_status": "not_gold"}
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rows = [row_to_dict(row) for row in await conn.fetch(ANNOTATION_QUERY, dataset_id)]
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kappa = cohen_kappa(rows, args.kappa_label)
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icc = intraclass_correlation(rows, args.icc_label)
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gold_status = "gold_candidate" if kappa is not None and kappa >= 0.70 and icc is not None and icc >= 0.75 else "not_gold"
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return {"kappa": kappa, "icc": icc, "gold_status": gold_status}
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async def insert_manifest_row(
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conn: asyncpg.Connection,
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*,
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dataset_id: int,
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agreement: dict[str, Any],
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jsonl_path: str,
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) -> None:
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await conn.execute(
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"""
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INSERT INTO ds.export_manifest (dataset_id, iaa_kappa, iaa_icc, jsonl_path)
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VALUES ($1, $2, $3, $4)
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""",
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dataset_id,
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agreement.get("kappa"),
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agreement.get("icc"),
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jsonl_path,
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)
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async def run(args: argparse.Namespace) -> int:
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if args.export_status == APPROVED_EXPORT_STATUS and not args.allow_approved:
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raise SystemExit("--export-status approved_for_recursive_learning_seed requires --allow-approved")
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if args.write_manifest_row and not args.write_dataset:
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raise SystemExit("--write-manifest-row requires --write-dataset")
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output_root = Path(args.output_root).resolve()
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export_dir = output_root / "03-export"
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jsonl_path = export_dir / "anonymized_dataset.jsonl"
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manifest_path = export_dir / "export_manifest.json"
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conn = await asyncpg.connect(args.database_url)
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try:
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raw_rows = await fetch_rows(conn, args)
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keys = ExportKeyMaps()
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records = [
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build_dataset_record(
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row,
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item_index=index,
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export_manifest_id=args.export_id,
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keys=keys,
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pii_scan_status="pending",
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)
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for index, row in enumerate(raw_rows, start=1)
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]
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pii_findings: list[dict[str, Any]] = []
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for record in records:
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for finding in scan_for_pii(record):
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pii_findings.append({"item_id": record["item_id"], **finding})
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if pii_findings and args.fail_on_pii:
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raise SystemExit(f"PII scan found {len(pii_findings)} finding(s)")
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pii_status = "pass" if not pii_findings else "fail"
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for record in records:
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record["privacy"]["pii_scan_status"] = pii_status
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write_jsonl(records, jsonl_path)
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digest = sha256_file(jsonl_path)
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dataset_id: int | None = None
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if args.write_dataset:
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dataset_id = await write_dataset_rows(
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conn,
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dataset_name=args.dataset_name,
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purpose=args.purpose,
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raw_rows=raw_rows,
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records=records,
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)
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agreement = await fetch_agreement(conn, dataset_id, args)
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approvals = {
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"data_steward": args.data_steward,
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"legal_or_privacy_reviewer": args.legal_or_privacy_reviewer,
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"technical_operator": args.technical_operator or os.environ.get("USERNAME", ""),
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"approved_at": args.approved_at,
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}
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manifest = build_manifest(
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export_id=args.export_id,
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dataset_name=args.dataset_name,
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export_status=args.export_status,
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purpose=args.purpose,
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records=records,
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jsonl_path=str(jsonl_path.relative_to(output_root)).replace("\\", "/"),
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jsonl_sha256=digest,
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pii_findings=pii_findings,
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participants_included=len(keys.participant),
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cohort_id=args.cohort_id,
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consent_version=args.consent_version,
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agreement=agreement,
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approvals=approvals,
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known_limitations=args.known_limitation,
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)
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validate_manifest_gate(manifest)
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manifest_path.write_text(
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json.dumps(manifest, ensure_ascii=False, indent=2, sort_keys=True) + "\n",
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encoding="utf-8",
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)
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if args.write_manifest_row and dataset_id is not None:
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await insert_manifest_row(
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conn,
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dataset_id=dataset_id,
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agreement=agreement,
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jsonl_path=str(jsonl_path),
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)
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finally:
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await conn.close()
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print(json.dumps({"manifest": str(manifest_path), "jsonl": str(jsonl_path), "rows": len(records)}, ensure_ascii=False))
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return 0
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def build_parser() -> argparse.ArgumentParser:
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parser = argparse.ArgumentParser(description="Export a Phase 3 recursive-learning JSONL dry-run dataset.")
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parser.add_argument("--database-url", default=os.environ.get("DATABASE_URL"), required=os.environ.get("DATABASE_URL") is None)
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parser.add_argument("--output-root", default=str(REPO_ROOT / "data" / "phase3-dry-run"))
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parser.add_argument("--export-id", default=make_export_id())
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parser.add_argument("--dataset-name", default="vignette_phase3_recursive_learning_seed")
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parser.add_argument("--purpose", default="recursive-learning seed dataset for education simulator improvement")
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parser.add_argument("--export-status", choices=[DRY_RUN_EXPORT_STATUS, "blocked", APPROVED_EXPORT_STATUS], default=DRY_RUN_EXPORT_STATUS)
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parser.add_argument("--allow-approved", action="store_true")
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parser.add_argument("--started-at")
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parser.add_argument("--ended-at")
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parser.add_argument("--limit", type=int, default=1000)
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parser.add_argument("--cohort-id", default="phase3")
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parser.add_argument("--apply-cohort-filter", action="store_true")
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parser.add_argument("--consent-version", default="")
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parser.add_argument("--data-steward", default="")
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parser.add_argument("--legal-or-privacy-reviewer", default="")
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parser.add_argument("--technical-operator", default="")
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parser.add_argument("--approved-at", default="")
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parser.add_argument("--known-limitation", action="append", default=[])
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parser.add_argument("--fail-on-pii", action="store_true")
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parser.add_argument("--kappa-label", default="appropriateness")
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parser.add_argument("--icc-label", default="rapport_signal")
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parser.add_argument("--write-dataset", action="store_true")
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parser.add_argument("--write-manifest-row", action="store_true")
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return parser
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def main() -> int:
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parser = build_parser()
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args = parser.parse_args()
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return asyncio.run(run(args))
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if __name__ == "__main__":
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raise SystemExit(main())
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