hgzero/ai-python/app/services/transcript_service.py
Minseo-Jo 143721d106 feat: Meeting Service AI 통합 개발
 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>
2025-10-28 16:42:09 +09:00

115 lines
3.7 KiB
Python

"""Transcript Service - 회의록 통합 처리"""
import logging
from datetime import datetime
from app.models.transcript import (
ConsolidateRequest,
ConsolidateResponse,
AgendaSummary,
ExtractedTodo
)
from app.services.claude_service import claude_service
from app.prompts.consolidate_prompt import get_consolidate_prompt
logger = logging.getLogger(__name__)
class TranscriptService:
"""회의록 통합 서비스"""
async def consolidate_minutes(
self,
request: ConsolidateRequest
) -> ConsolidateResponse:
"""
참석자별 회의록을 통합하여 AI 요약 생성
"""
logger.info(f"회의록 통합 시작 - Meeting ID: {request.meeting_id}")
logger.info(f"참석자 수: {len(request.participant_minutes)}")
try:
# 1. 프롬프트 생성
participant_data = [
{
"user_name": pm.user_name,
"content": pm.content
}
for pm in request.participant_minutes
]
prompt = get_consolidate_prompt(
participant_minutes=participant_data,
agendas=request.agendas
)
# 2. Claude API 호출
start_time = datetime.utcnow()
ai_result = await claude_service.generate_completion(prompt)
processing_time = (datetime.utcnow() - start_time).total_seconds() * 1000
logger.info(f"AI 처리 완료 - {processing_time:.0f}ms")
# 3. 응답 구성
response = self._build_response(
meeting_id=request.meeting_id,
ai_result=ai_result,
participants_count=len(request.participant_minutes),
duration_minutes=request.duration_minutes
)
logger.info(f"통합 요약 완료 - 안건 수: {len(response.agenda_summaries)}, Todo 수: {response.statistics['todos_count']}")
return response
except Exception as e:
logger.error(f"회의록 통합 실패: {e}", exc_info=True)
raise
def _build_response(
self,
meeting_id: str,
ai_result: dict,
participants_count: int,
duration_minutes: int = None
) -> ConsolidateResponse:
"""AI 응답을 ConsolidateResponse로 변환"""
# 안건별 요약 변환
agenda_summaries = []
for agenda_data in ai_result.get("agenda_summaries", []):
# Todo 변환 (제목만)
todos = [
ExtractedTodo(title=todo.get("title", ""))
for todo in agenda_data.get("todos", [])
]
agenda_summaries.append(
AgendaSummary(
agenda_number=agenda_data.get("agenda_number", 0),
agenda_title=agenda_data.get("agenda_title", ""),
summary_short=agenda_data.get("summary_short", ""),
discussion=agenda_data.get("discussion", ""),
decisions=agenda_data.get("decisions", []),
pending=agenda_data.get("pending", []),
todos=todos
)
)
# 통계 정보
statistics = ai_result.get("statistics", {})
statistics["participants_count"] = participants_count
if duration_minutes:
statistics["duration_minutes"] = duration_minutes
# 응답 생성
return ConsolidateResponse(
meeting_id=meeting_id,
keywords=ai_result.get("keywords", []),
statistics=statistics,
agenda_summaries=agenda_summaries,
generated_at=datetime.utcnow()
)
# 싱글톤 인스턴스
transcript_service = TranscriptService()