htlee
e797beaac6
- Ollama Docker(14b/32b) + Redis 컨텍스트 캐싱 + 대화 히스토리 - Python SSE 채팅 엔드포인트 + 사전 쿼리 + Tool Calling - 도메인 지식(해양법/어업협정/알고리즘) + DB 스키마 가이드 - Frontend SSE 스트리밍 + 타이머 + thinking 접기 + 확장 UI
71 lines
1.8 KiB
Python
71 lines
1.8 KiB
Python
import logging
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import sys
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from contextlib import asynccontextmanager
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from fastapi import BackgroundTasks, FastAPI
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from config import settings
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from db import kcgdb, snpdb
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from scheduler import get_last_run, run_analysis_cycle, start_scheduler, stop_scheduler
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logging.basicConfig(
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level=getattr(logging, settings.LOG_LEVEL, logging.INFO),
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format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
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stream=sys.stdout,
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)
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logger = logging.getLogger(__name__)
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@asynccontextmanager
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async def lifespan(application: FastAPI):
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from cache.vessel_store import vessel_store
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logger.info('starting KCG Prediction Service')
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snpdb.init_pool()
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kcgdb.init_pool()
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# 인메모리 캐시 초기 로드 (24시간)
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logger.info('loading initial vessel data (%dh)...', settings.INITIAL_LOAD_HOURS)
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vessel_store.load_initial(settings.INITIAL_LOAD_HOURS)
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logger.info('initial load complete: %s', vessel_store.stats())
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start_scheduler()
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yield
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stop_scheduler()
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snpdb.close_pool()
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kcgdb.close_pool()
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logger.info('KCG Prediction Service stopped')
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app = FastAPI(
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title='KCG Prediction Service',
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version='2.1.0',
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lifespan=lifespan,
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)
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# AI 해양분석 채팅 라우터
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from chat.router import router as chat_router
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app.include_router(chat_router)
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@app.get('/health')
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def health_check():
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from cache.vessel_store import vessel_store
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return {
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'status': 'ok',
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'snpdb': snpdb.check_health(),
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'kcgdb': kcgdb.check_health(),
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'store': vessel_store.stats(),
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}
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@app.get('/api/v1/analysis/status')
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def analysis_status():
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return get_last_run()
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@app.post('/api/v1/analysis/trigger')
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def trigger_analysis(background_tasks: BackgroundTasks):
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background_tasks.add_task(run_analysis_cycle)
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return {'message': 'analysis cycle triggered'}
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