- MLX(맥미니 27B) 우선 → Ollama(조립컴 9B) fallback 구조 - pydantic-settings 기반 config 전환 - health check에 MLX 상태 추가 - 텍스트 모델 qwen3:8b → qwen3.5:9b-q8_0 변경 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
48 lines
1.5 KiB
Python
48 lines
1.5 KiB
Python
from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from services.classification_service import (
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classify_issue,
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summarize_issue,
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classify_and_summarize,
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)
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router = APIRouter(tags=["classification"])
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class ClassifyRequest(BaseModel):
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description: str
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detail_notes: str = ""
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class SummarizeRequest(BaseModel):
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description: str
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detail_notes: str = ""
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solution: str = ""
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@router.post("/classify")
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async def classify(req: ClassifyRequest):
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try:
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result = await classify_issue(req.description, req.detail_notes)
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return {"available": True, **result}
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except Exception as e:
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raise HTTPException(status_code=500, detail="AI 서비스 처리 중 오류가 발생했습니다")
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@router.post("/summarize")
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async def summarize(req: SummarizeRequest):
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try:
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result = await summarize_issue(req.description, req.detail_notes, req.solution)
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return {"available": True, **result}
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except Exception as e:
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raise HTTPException(status_code=500, detail="AI 서비스 처리 중 오류가 발생했습니다")
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@router.post("/classify-and-summarize")
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async def classify_and_summarize_endpoint(req: ClassifyRequest):
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try:
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result = await classify_and_summarize(req.description, req.detail_notes)
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return {"available": True, **result}
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except Exception as e:
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raise HTTPException(status_code=500, detail="AI 서비스 처리 중 오류가 발생했습니다")
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