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✅ 구현 완료 - AI Python Service (FastAPI, Claude API, 8087 포트) - POST /api/v1/transcripts/consolidate - 참석자별 회의록 → AI 통합 분석 - 키워드/안건별 요약/Todo 추출 - Meeting Service AI 통합 - EndMeetingService (@Primary) - AIServiceClient (RestTemplate, 30초 timeout) - AI 분석 결과 저장 (meeting_analysis, todos) - 회의 상태 COMPLETED 처리 - DTO 구조 (간소화) - ConsolidateRequest/Response - MeetingEndDTO - Todo 제목만 포함 (담당자/마감일 제거) 📝 기술스택 - Python: FastAPI, anthropic 0.71.0, psycopg2 - Java: Spring Boot, RestTemplate - Claude: claude-3-5-sonnet-20241022 🔧 주요 이슈 해결 - 포트 충돌: 8086(feature/stt-ai) → 8087(feat/meeting-ai) - Bean 충돌: @Primary 추가 - YAML 문법: ai.service.url 구조 수정 - anthropic 라이브러리 업그레이드 📚 테스트 가이드 및 스크립트 작성 - claude/MEETING-AI-TEST-GUIDE.md - test-meeting-ai.sh 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
115 lines
3.7 KiB
Python
115 lines
3.7 KiB
Python
"""Transcript Service - 회의록 통합 처리"""
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import logging
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from datetime import datetime
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from app.models.transcript import (
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ConsolidateRequest,
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ConsolidateResponse,
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AgendaSummary,
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ExtractedTodo
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)
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from app.services.claude_service import claude_service
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from app.prompts.consolidate_prompt import get_consolidate_prompt
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logger = logging.getLogger(__name__)
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class TranscriptService:
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"""회의록 통합 서비스"""
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async def consolidate_minutes(
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self,
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request: ConsolidateRequest
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) -> ConsolidateResponse:
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"""
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참석자별 회의록을 통합하여 AI 요약 생성
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"""
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logger.info(f"회의록 통합 시작 - Meeting ID: {request.meeting_id}")
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logger.info(f"참석자 수: {len(request.participant_minutes)}")
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try:
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# 1. 프롬프트 생성
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participant_data = [
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{
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"user_name": pm.user_name,
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"content": pm.content
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}
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for pm in request.participant_minutes
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]
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prompt = get_consolidate_prompt(
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participant_minutes=participant_data,
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agendas=request.agendas
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)
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# 2. Claude API 호출
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start_time = datetime.utcnow()
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ai_result = await claude_service.generate_completion(prompt)
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processing_time = (datetime.utcnow() - start_time).total_seconds() * 1000
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logger.info(f"AI 처리 완료 - {processing_time:.0f}ms")
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# 3. 응답 구성
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response = self._build_response(
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meeting_id=request.meeting_id,
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ai_result=ai_result,
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participants_count=len(request.participant_minutes),
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duration_minutes=request.duration_minutes
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)
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logger.info(f"통합 요약 완료 - 안건 수: {len(response.agenda_summaries)}, Todo 수: {response.statistics['todos_count']}")
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return response
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except Exception as e:
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logger.error(f"회의록 통합 실패: {e}", exc_info=True)
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raise
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def _build_response(
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self,
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meeting_id: str,
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ai_result: dict,
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participants_count: int,
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duration_minutes: int = None
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) -> ConsolidateResponse:
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"""AI 응답을 ConsolidateResponse로 변환"""
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# 안건별 요약 변환
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agenda_summaries = []
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for agenda_data in ai_result.get("agenda_summaries", []):
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# Todo 변환 (제목만)
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todos = [
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ExtractedTodo(title=todo.get("title", ""))
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for todo in agenda_data.get("todos", [])
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]
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agenda_summaries.append(
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AgendaSummary(
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agenda_number=agenda_data.get("agenda_number", 0),
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agenda_title=agenda_data.get("agenda_title", ""),
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summary_short=agenda_data.get("summary_short", ""),
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discussion=agenda_data.get("discussion", ""),
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decisions=agenda_data.get("decisions", []),
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pending=agenda_data.get("pending", []),
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todos=todos
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)
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)
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# 통계 정보
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statistics = ai_result.get("statistics", {})
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statistics["participants_count"] = participants_count
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if duration_minutes:
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statistics["duration_minutes"] = duration_minutes
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# 응답 생성
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return ConsolidateResponse(
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meeting_id=meeting_id,
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keywords=ai_result.get("keywords", []),
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statistics=statistics,
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agenda_summaries=agenda_summaries,
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generated_at=datetime.utcnow()
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)
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# 싱글톤 인스턴스
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transcript_service = TranscriptService()
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