o2o-infinith-backend/app/services/file.py

124 lines
4.3 KiB
Python

import logging
from fastapi import HTTPException, UploadFile
from common.db import execute, fetchall, fetchone, insert_file_row
from integrations.azure_blob import AzureBlobUploader
from models.file import FileListItem, FileType, FileUploadResponse
logger = logging.getLogger(__name__)
_MAX_UPLOAD_BYTES = 50 * 1024 * 1024 # 50MB
async def upload_file_to_blob(
content: bytes,
file_name: str,
group: str,
category: str = "file",
content_type: str | None = None,
) -> str:
"""Azure Blob에 파일을 업로드하고 public URL을 반환. DB는 건드리지 않음."""
uploader = AzureBlobUploader(group=group, category=category)
return await uploader.upload_bytes(content=content, file_name=file_name, content_type=content_type)
async def upload_analysis_file(
analysis_run_id: str,
content: bytes,
file_name: str,
file_type: str = "file",
content_type: str | None = None,
) -> tuple[int, str]:
"""analysis_run에 딸린 파일 업로드. Blob 업로드 + file_data row 생성. (file_id, url) 반환."""
run = await fetchone(
"SELECT hospital_id FROM analysis_runs WHERE analysis_run_id = %s",
(analysis_run_id,),
)
if not run:
raise HTTPException(status_code=404, detail="analysis_run not found")
hospital_id = run["hospital_id"]
public_url = await upload_file_to_blob(
content=content,
file_name=file_name,
group=analysis_run_id,
category=file_type,
content_type=content_type,
)
file_id = await insert_file_row(
analysis_run_id=analysis_run_id,
hospital_id=hospital_id,
file_type=file_type,
file_name=file_name,
file_url=public_url,
size_bytes=len(content),
)
logger.info("uploaded analysis file run=%s file_id=%s url=%s", analysis_run_id, file_id, public_url)
return file_id, public_url
async def list_analysis_files(analysis_run_id: str) -> list[dict]:
"""analysis_run에 딸린 (삭제 안 된) 파일 목록."""
return await fetchall(
"SELECT id, file_type, file_name, file_url, size_bytes, created_at FROM file_data"
" WHERE analysis_run_id = %s AND is_deleted = FALSE"
" ORDER BY created_at DESC",
(analysis_run_id,),
)
async def handle_analysis_file_upload(
analysis_run_id: str,
upload: UploadFile,
file_type: FileType,
) -> FileUploadResponse:
"""multipart UploadFile 검증 + 업로드 + 응답 모델 생성."""
if not upload.filename:
raise HTTPException(status_code=400, detail="filename is required")
content = await upload.read()
if not content:
raise HTTPException(status_code=400, detail="empty file")
if len(content) > _MAX_UPLOAD_BYTES:
raise HTTPException(status_code=413, detail=f"file too large (max {_MAX_UPLOAD_BYTES} bytes)")
file_id, public_url = await upload_analysis_file(
analysis_run_id=analysis_run_id,
content=content,
file_name=upload.filename,
file_type=file_type.value,
content_type=upload.content_type,
)
return FileUploadResponse(
id=file_id,
analysis_run_id=analysis_run_id,
file_type=file_type,
file_name=upload.filename,
file_url=public_url,
size_bytes=len(content),
)
async def get_analysis_files_response(analysis_run_id: str) -> list[FileListItem]:
"""run 존재 확인 + 응답 모델 생성."""
if not await fetchone("SELECT 1 FROM analysis_runs WHERE analysis_run_id = %s", (analysis_run_id,)):
raise HTTPException(status_code=404, detail="analysis_run not found")
rows = await list_analysis_files(analysis_run_id)
return [FileListItem(**{**r, "created_at": str(r["created_at"])}) for r in rows]
async def soft_delete_analysis_file(analysis_run_id: str, file_id: int) -> None:
"""analysis_run에 딸린 파일을 소프트 삭제. 멱등성 보장."""
row = await fetchone(
"SELECT id FROM file_data WHERE id = %s AND analysis_run_id = %s",
(file_id, analysis_run_id),
)
if not row:
raise HTTPException(status_code=404, detail="file not found")
await execute(
"UPDATE file_data SET is_deleted = TRUE WHERE id = %s AND is_deleted = FALSE",
(file_id,),
)
logger.info("soft-deleted analysis file run=%s file_id=%s", analysis_run_id, file_id)