2a4950d8a0
소형 건설업체(100억 미만)를 위한 AI 기반 토목공사 통합관리 플랫폼 Backend (FastAPI): - SQLAlchemy 모델 13개 (users, projects, wbs, tasks, daily_reports, reports, inspections, quality, weather, permits, rag, settings) - API 라우터 11개 (auth, projects, tasks, daily_reports, reports, inspections, weather, rag, kakao, permits, settings) - Services: Claude AI 래퍼, CPM Gantt 계산, 기상청 API, RAG(pgvector), 카카오 Skill API - Alembic 마이그레이션 (pgvector 포함) - pytest 테스트 (CPM, 날씨 경보) Frontend (Next.js 15): - 11개 페이지 (대시보드, 프로젝트, Gantt, 일보, 검측, 품질, 날씨, 인허가, RAG, 설정) - TanStack Query + Zustand + Tailwind CSS 인프라: - Docker Compose (PostgreSQL pgvector + backend + frontend) - 한국어 README 및 설치 가이드 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
124 lines
3.7 KiB
Python
124 lines
3.7 KiB
Python
"""
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Kakao Chatbot Skill API service.
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Parses incoming messages and routes to appropriate handlers.
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"""
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import re
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from datetime import date
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# Kakao Skill response builders
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def simple_text(text: str) -> dict:
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return {
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"version": "2.0",
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"template": {
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"outputs": [{"simpleText": {"text": text}}]
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}
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}
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def basic_card(title: str, description: str, buttons: list[dict] | None = None) -> dict:
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card = {"title": title, "description": description}
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if buttons:
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card["buttons"] = buttons
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return {
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"version": "2.0",
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"template": {
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"outputs": [{"basicCard": card}]
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}
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}
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def list_card(header_title: str, items: list[dict], buttons: list[dict] | None = None) -> dict:
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card = {
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"header": {"title": header_title},
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"items": items,
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}
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if buttons:
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card["buttons"] = buttons
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return {
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"version": "2.0",
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"template": {
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"outputs": [{"listCard": card}]
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}
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}
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# Message routing
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class KakaoIntent:
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DAILY_REPORT = "daily_report"
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RAG_QUESTION = "rag_question"
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WEATHER = "weather"
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HELP = "help"
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UNKNOWN = "unknown"
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def detect_intent(utterance: str) -> str:
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"""Detect user intent from utterance."""
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u = utterance.strip()
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# Daily report keywords
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if any(k in u for k in ["일보", "작업일보", "오늘 공사", "금일 공사"]):
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return KakaoIntent.DAILY_REPORT
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# RAG / question keywords
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if any(k in u for k in ["질문", "법규", "시방서", "기준", "KCS", "법령", "산안법", "중대재해", "?", "？"]):
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return KakaoIntent.RAG_QUESTION
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# Weather keywords
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if any(k in u for k in ["날씨", "기상", "비", "눈", "바람"]):
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return KakaoIntent.WEATHER
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# Help
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if any(k in u for k in ["도움말", "메뉴", "help", "사용법"]):
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return KakaoIntent.HELP
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return KakaoIntent.UNKNOWN
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def parse_daily_report_input(utterance: str) -> dict:
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"""
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Parse daily report input from free-form Kakao message.
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Example: "오늘 일보: 콘크리트 5명, 철근 3명, 관로매설 오후 완료"
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"""
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workers = {}
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work_items = []
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issues = None
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# Extract worker counts: "직종 N명" patterns
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worker_pattern = re.findall(r'([가-힣a-zA-Z]+)\s+(\d+)명', utterance)
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for role, count in worker_pattern:
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if role not in ["총", "합계"]:
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workers[role] = int(count)
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# Extract work items after "일보:" or newlines
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lines = utterance.replace("일보:", "").replace("작업일보:", "").split("\n")
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for line in lines:
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line = line.strip().lstrip("-").strip()
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if line and len(line) > 2 and not re.search(r'\d+명', line):
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work_items.append(line)
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# Check for issues
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if "특이" in utterance or "문제" in utterance or "이슈" in utterance:
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issue_match = re.search(r'(특이|문제|이슈)[사항:：\s]*(.+?)(?:\n|$)', utterance)
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if issue_match:
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issues = issue_match.group(2).strip()
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return {
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"workers_count": workers,
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"work_items": work_items if work_items else ["기타 작업"],
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"issues": issues,
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"report_date": str(date.today()),
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}
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def make_help_response() -> dict:
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return list_card(
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header_title="CONAI 현장 도우미",
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items=[
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{"title": "작업일보 작성", "description": "일보: 작업내용 입력"},
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{"title": "법규 질문", "description": "질문: 궁금한 내용 입력"},
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{"title": "날씨 확인", "description": "날씨 입력"},
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],
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buttons=[{"action": "message", "label": "일보 작성", "messageText": "일보:"}],
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)
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