feat: PAAI (Pharmacist Assistant AI) 기능 구현
- PAAI 로그 테이블 스키마 (paai_logs_schema.sql) - PAAI 로거 모듈 (db/paai_logger.py) - /pmr/api/paai/analyze API 엔드포인트 - KIMS API 연동 (KD코드 기반 상호작용 조회) - Clawdbot AI 연동 (HTTP API) - PMR 화면 PAAI 버튼 및 모달 - Admin 페이지 (/admin/paai) - 피드백 수집 기능
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thug0bin
351
backend/db/paai_logger.py
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351
backend/db/paai_logger.py
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"""
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PAAI (Pharmacist Assistant AI) 로깅 모듈
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- API 호출/응답 SQLite 저장
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- 분석 결과 및 피드백 관리
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"""
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import sqlite3
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import json
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import os
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from datetime import datetime, timedelta
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from pathlib import Path
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# DB 파일 경로
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DB_PATH = Path(__file__).parent / 'paai_logs.db'
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def init_db():
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"""DB 초기화 (테이블 생성)"""
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schema_path = Path(__file__).parent / 'paai_logs_schema.sql'
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conn = sqlite3.connect(str(DB_PATH))
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cursor = conn.cursor()
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with open(schema_path, 'r', encoding='utf-8') as f:
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schema = f.read()
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cursor.executescript(schema)
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conn.commit()
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conn.close()
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print(f"PAAI 로그 DB 초기화 완료: {DB_PATH}")
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def create_log(
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pre_serial: str = None,
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patient_code: str = None,
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patient_name: str = None,
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disease_code_1: str = None,
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disease_name_1: str = None,
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disease_code_2: str = None,
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disease_name_2: str = None,
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current_medications: list = None,
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previous_serial: str = None,
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previous_medications: list = None,
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prescription_changes: dict = None,
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otc_history: dict = None
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) -> int:
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"""
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PAAI 분석 로그 생성 (초기 상태)
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Returns:
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log_id: 생성된 로그 ID
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"""
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if not DB_PATH.exists():
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init_db()
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conn = sqlite3.connect(str(DB_PATH))
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cursor = conn.cursor()
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current_medications = current_medications or []
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previous_medications = previous_medications or []
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otc_history = otc_history or {}
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# 환자명 마스킹
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masked_name = None
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if patient_name:
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masked_name = patient_name[0] + '*' * (len(patient_name) - 1) if len(patient_name) > 1 else patient_name
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cursor.execute("""
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INSERT INTO paai_logs (
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pre_serial, patient_code, patient_name,
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disease_code_1, disease_name_1, disease_code_2, disease_name_2,
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current_medications, current_med_count,
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previous_serial, previous_medications, prescription_changes,
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otc_history, otc_visit_count,
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status
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, 'pending')
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""", (
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pre_serial,
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patient_code,
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masked_name,
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disease_code_1,
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disease_name_1,
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disease_code_2,
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disease_name_2,
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json.dumps(current_medications, ensure_ascii=False),
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len(current_medications),
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previous_serial,
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json.dumps(previous_medications, ensure_ascii=False),
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json.dumps(prescription_changes, ensure_ascii=False) if prescription_changes else None,
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json.dumps(otc_history, ensure_ascii=False),
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otc_history.get('visit_count', 0)
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))
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log_id = cursor.lastrowid
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conn.commit()
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conn.close()
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return log_id
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def update_kims_result(
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log_id: int,
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kims_drug_codes: list = None,
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kims_interactions: list = None,
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kims_response_time_ms: int = 0
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):
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"""KIMS 상호작용 결과 업데이트"""
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conn = sqlite3.connect(str(DB_PATH))
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cursor = conn.cursor()
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kims_drug_codes = kims_drug_codes or []
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kims_interactions = kims_interactions or []
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# 심각한 상호작용 여부 (severity 1 또는 2)
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has_severe = any(
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str(i.get('severity', '5')) in ['1', '2']
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for i in kims_interactions
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)
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cursor.execute("""
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UPDATE paai_logs SET
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kims_drug_codes = ?,
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kims_drug_count = ?,
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kims_interactions = ?,
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kims_interaction_count = ?,
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kims_has_severe = ?,
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kims_response_time_ms = ?,
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status = 'kims_done'
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WHERE id = ?
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""", (
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json.dumps(kims_drug_codes, ensure_ascii=False),
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len(kims_drug_codes),
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json.dumps(kims_interactions, ensure_ascii=False),
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len(kims_interactions),
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1 if has_severe else 0,
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kims_response_time_ms,
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log_id
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))
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conn.commit()
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conn.close()
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def update_ai_result(
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log_id: int,
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ai_prompt: str = None,
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ai_model: str = None,
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ai_response: dict = None,
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ai_response_time_ms: int = 0,
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ai_token_count: int = None
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):
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"""AI 분석 결과 업데이트"""
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conn = sqlite3.connect(str(DB_PATH))
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cursor = conn.cursor()
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cursor.execute("""
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UPDATE paai_logs SET
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ai_prompt = ?,
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ai_model = ?,
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ai_response = ?,
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ai_response_time_ms = ?,
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ai_token_count = ?,
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status = 'success'
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WHERE id = ?
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""", (
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ai_prompt,
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ai_model,
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json.dumps(ai_response, ensure_ascii=False) if ai_response else None,
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ai_response_time_ms,
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ai_token_count,
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log_id
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))
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conn.commit()
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conn.close()
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def update_error(log_id: int, error_message: str):
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"""에러 상태 업데이트"""
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conn = sqlite3.connect(str(DB_PATH))
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cursor = conn.cursor()
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cursor.execute("""
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UPDATE paai_logs SET
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status = 'error',
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error_message = ?
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WHERE id = ?
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""", (error_message, log_id))
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conn.commit()
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conn.close()
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def update_feedback(log_id: int, useful: bool, comment: str = None):
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"""피드백 업데이트"""
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conn = sqlite3.connect(str(DB_PATH))
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cursor = conn.cursor()
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cursor.execute("""
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UPDATE paai_logs SET
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feedback_useful = ?,
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feedback_comment = ?
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WHERE id = ?
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""", (1 if useful else 0, comment, log_id))
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conn.commit()
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conn.close()
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def get_recent_logs(
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limit: int = 100,
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status: str = None,
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has_severe: bool = None,
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date: str = None
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) -> list:
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"""최근 로그 조회"""
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if not DB_PATH.exists():
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return []
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conn = sqlite3.connect(str(DB_PATH))
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conn.row_factory = sqlite3.Row
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cursor = conn.cursor()
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query = "SELECT * FROM paai_logs WHERE 1=1"
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params = []
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if status:
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query += " AND status = ?"
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params.append(status)
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if has_severe is not None:
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query += " AND kims_has_severe = ?"
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params.append(1 if has_severe else 0)
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if date:
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query += " AND DATE(created_at) = ?"
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params.append(date)
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query += " ORDER BY created_at DESC LIMIT ?"
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params.append(limit)
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cursor.execute(query, params)
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rows = cursor.fetchall()
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result = []
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for row in rows:
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log = dict(row)
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# JSON 필드 파싱
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for field in ['current_medications', 'previous_medications', 'prescription_changes',
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'otc_history', 'kims_drug_codes', 'kims_interactions', 'ai_response']:
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if log.get(field):
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try:
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log[field] = json.loads(log[field])
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except:
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pass
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result.append(log)
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conn.close()
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return result
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def get_log_detail(log_id: int) -> dict:
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"""로그 상세 조회"""
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if not DB_PATH.exists():
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return None
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conn = sqlite3.connect(str(DB_PATH))
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conn.row_factory = sqlite3.Row
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cursor = conn.cursor()
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cursor.execute("SELECT * FROM paai_logs WHERE id = ?", (log_id,))
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row = cursor.fetchone()
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if not row:
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conn.close()
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return None
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log = dict(row)
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# JSON 필드 파싱
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for field in ['current_medications', 'previous_medications', 'prescription_changes',
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'otc_history', 'kims_drug_codes', 'kims_interactions', 'ai_response']:
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if log.get(field):
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try:
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log[field] = json.loads(log[field])
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except:
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pass
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conn.close()
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return log
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def get_stats() -> dict:
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"""통계 조회"""
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if not DB_PATH.exists():
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return {
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'total': 0,
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'today': 0,
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'success_rate': 0,
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'avg_response_time': 0,
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'severe_count': 0
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}
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conn = sqlite3.connect(str(DB_PATH))
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cursor = conn.cursor()
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today = datetime.now().strftime('%Y-%m-%d')
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# 전체 건수
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cursor.execute("SELECT COUNT(*) FROM paai_logs")
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total = cursor.fetchone()[0]
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# 오늘 건수
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cursor.execute("SELECT COUNT(*) FROM paai_logs WHERE DATE(created_at) = ?", (today,))
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today_count = cursor.fetchone()[0]
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# 성공률
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cursor.execute("SELECT COUNT(*) FROM paai_logs WHERE status = 'success'")
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success_count = cursor.fetchone()[0]
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success_rate = (success_count / total * 100) if total > 0 else 0
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# 평균 응답시간
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cursor.execute("SELECT AVG(ai_response_time_ms) FROM paai_logs WHERE ai_response_time_ms > 0")
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avg_time = cursor.fetchone()[0] or 0
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# 심각한 상호작용 건수 (오늘)
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cursor.execute("""
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SELECT COUNT(*) FROM paai_logs
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WHERE DATE(created_at) = ? AND kims_has_severe = 1
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""", (today,))
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severe_count = cursor.fetchone()[0]
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# 피드백 통계
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cursor.execute("SELECT COUNT(*) FROM paai_logs WHERE feedback_useful = 1")
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useful_count = cursor.fetchone()[0]
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cursor.execute("SELECT COUNT(*) FROM paai_logs WHERE feedback_useful IS NOT NULL")
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feedback_total = cursor.fetchone()[0]
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conn.close()
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return {
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'total': total,
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'today': today_count,
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'success_rate': round(success_rate, 1),
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'avg_response_time': int(avg_time),
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'severe_count': severe_count,
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'feedback': {
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'useful': useful_count,
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'total': feedback_total,
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'rate': round(useful_count / feedback_total * 100, 1) if feedback_total > 0 else 0
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}
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}
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59
backend/db/paai_logs_schema.sql
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59
backend/db/paai_logs_schema.sql
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@@ -0,0 +1,59 @@
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-- PAAI (Pharmacist Assistant AI) 로그 스키마
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-- 생성일: 2026-03-04
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CREATE TABLE IF NOT EXISTS paai_logs (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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-- 요청 정보
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pre_serial TEXT, -- 처방번호
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patient_code TEXT, -- 환자코드 (CusCode)
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patient_name TEXT, -- 환자명 (마스킹: 김**)
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-- 질병 정보
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disease_code_1 TEXT, -- St1 (상병코드1)
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disease_name_1 TEXT, -- 상병명1
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disease_code_2 TEXT, -- St2 (상병코드2)
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disease_name_2 TEXT, -- 상병명2
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-- 처방 정보
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current_medications TEXT, -- JSON: 현재 처방 [{code, name, dosage, ...}]
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current_med_count INTEGER, -- 현재 처방 약품 수
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previous_serial TEXT, -- 이전 처방번호
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previous_medications TEXT, -- JSON: 이전 처방
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prescription_changes TEXT, -- JSON: {added, removed, changed}
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-- OTC 이력
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otc_history TEXT, -- JSON: {purchases, frequent_items}
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otc_visit_count INTEGER, -- OTC 구매 횟수
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-- KIMS 상호작용
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kims_drug_codes TEXT, -- JSON: 검사한 KD코드 배열
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kims_drug_count INTEGER, -- 검사한 약품 수
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kims_interactions TEXT, -- JSON: 상호작용 결과
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kims_interaction_count INTEGER, -- 상호작용 건수
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kims_has_severe BOOLEAN DEFAULT 0, -- 심각한 상호작용 (severity 1,2)
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kims_response_time_ms INTEGER, -- KIMS API 응답시간
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-- AI 분석
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ai_prompt TEXT, -- AI에 전달한 프롬프트
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ai_model TEXT, -- 사용된 모델
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ai_response TEXT, -- JSON: AI 분석 결과
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ai_response_time_ms INTEGER, -- AI 응답 시간
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ai_token_count INTEGER, -- 토큰 사용량
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-- 상태
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status TEXT DEFAULT 'pending', -- pending, kims_done, success, error
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error_message TEXT,
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-- 피드백
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feedback_useful INTEGER, -- 1=유용, 0=아님, NULL=미응답
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feedback_comment TEXT -- 약사 코멘트
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);
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-- 인덱스
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CREATE INDEX IF NOT EXISTS idx_paai_created ON paai_logs(created_at);
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CREATE INDEX IF NOT EXISTS idx_paai_patient ON paai_logs(patient_code);
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CREATE INDEX IF NOT EXISTS idx_paai_status ON paai_logs(status);
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CREATE INDEX IF NOT EXISTS idx_paai_serial ON paai_logs(pre_serial);
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CREATE INDEX IF NOT EXISTS idx_paai_severe ON paai_logs(kims_has_severe);
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Reference in New Issue
Block a user