import logging
import uuid6
from fastapi import APIRouter, BackgroundTasks, Depends, File, Form, HTTPException, UploadFile, status
from common.deps import verify_api_key
from common.db.hospital import select_hospital
from common.db.source import select_source_mainpage, insert_source, insert_raw_info
from common.db.run import insert_run, select_run_status
from models.analysis import AnalysisCreate, AnalysisStartResponse, AnalysisStatusResponse
from models.file import FileListItem, FileType, FileUploadResponse
from models.status import AnalysisStatus, SourceType
from services.pipeline import run_pipeline
from services.file_data import get_analysis_files_response, handle_analysis_file_upload, soft_delete_analysis_file

router = APIRouter(prefix="/api/analysis", tags=["analysis"], dependencies=[Depends(verify_api_key)])
logger = logging.getLogger(__name__)


@router.post("", status_code=status.HTTP_202_ACCEPTED, response_model=AnalysisStartResponse)
async def start_analysis(body: AnalysisCreate, background_tasks: BackgroundTasks):
    logger.info("POST /api/analysis clinic_id=%s", body.clinic_id)
    analysis_run_id = str(uuid6.uuid7())
    hospital_id = body.clinic_id

    # 사실 hospital과 owner_user_id 비교 후 검증이 필요한 거지만 일단 PoC 니까. 나중에 바꿉니다.
    hospital = await select_hospital(hospital_id)
    if not hospital:
        raise HTTPException(status_code=409, detail="Clinic not found")

    analysis_run_id = await insert_run(analysis_run_id, hospital_id, hospital["owner_user_id"])

    mainpage = await select_source_mainpage(hospital_id)
    if mainpage:
        await insert_raw_info(mainpage["source_id"], analysis_run_id, data_tag=SourceType.MAINPAGE)

    channels = [
        (SourceType.INSTAGRAM,    body.channels.instagram),
        (SourceType.FACEBOOK,     body.channels.facebook),
        (SourceType.NAVER_BLOG,   body.channels.naver_blog),
        (SourceType.YOUTUBE,      body.channels.youtube),
        (SourceType.GANGNAM_UNNI, body.channels.gangnam_unni),
    ]
    for source_type, url in channels:
        if url:
            source_id = await insert_source(hospital_id, source_type, url)
            await insert_raw_info(source_id, analysis_run_id, data_tag=source_type)

    background_tasks.add_task(run_pipeline, analysis_run_id)

    return AnalysisStartResponse(
        analysis_run_id=analysis_run_id,
        clinic_id=hospital_id,
        status=AnalysisStatus.DISCOVERING,
        estimated_seconds=90,
        poll_url=f"/api/analysis/{analysis_run_id}/status",
    )


@router.post("/{run_id}/files", status_code=status.HTTP_201_CREATED, response_model=FileUploadResponse)
async def upload_analysis_run_file(
    run_id: str,
    file: UploadFile = File(..., description="업로드할 파일"),
    file_type: FileType = Form(default=FileType.FILE, description="파일 타입 (image/video/audio/document/file)"),
) -> FileUploadResponse:
    logger.info("POST /api/analysis/%s/files name=%s file_type=%s", run_id, file.filename, file_type.value)
    return await handle_analysis_file_upload(run_id, file, file_type)


@router.get("/{run_id}/files", response_model=list[FileListItem])
async def get_analysis_run_files(run_id: str) -> list[FileListItem]:
    logger.info("GET /api/analysis/%s/files", run_id)
    return await get_analysis_files_response(run_id)


@router.delete("/{run_id}/files/{file_id}", status_code=status.HTTP_204_NO_CONTENT)
async def delete_analysis_run_file(run_id: str, file_id: int) -> None:
    logger.info("DELETE /api/analysis/%s/files/%s", run_id, file_id)
    await soft_delete_analysis_file(analysis_run_id=run_id, file_id=file_id)
    return None


@router.get("/{run_id}/status", response_model=AnalysisStatusResponse)
async def get_analysis_status(run_id: str):
    logger.info("GET /api/analysis/%s/status", run_id)
    run_status = await select_run_status(run_id)
    if run_status is None:
        raise HTTPException(status_code=404, detail="Run not found")
    return AnalysisStatusResponse(
        analysis_run_id=run_id,
        status=AnalysisStatus(run_status),
        progress=50.0,
        current_step="",
        channel_errors={},
        completed_at=None,
    )