from fastapi import APIRouter, Depends, UploadFile, File, HTTPException
from sqlalchemy.ext.asyncio import AsyncSession

from app.database import get_db
from app.core.deps import get_current_user, require_role
from app.models.user import User
from app.config import settings

router = APIRouter()


@router.post("/recognize-medicine")
async def recognize_medicine(
    file: UploadFile = File(...),
    db: AsyncSession = Depends(get_db),
    current_user: User = Depends(require_role(["admin", "user"]))
):
    from app.ai.manager import ai_manager

    if not file.content_type.startswith("image/"):
        raise HTTPException(status_code=400, detail="请上传图片文件")

    image_bytes = await file.read()
    if len(image_bytes) > settings.MAX_UPLOAD_SIZE:
        raise HTTPException(status_code=413, detail="文件过大")

    vision_provider = ai_manager.get_vision_provider(settings.AI_PROVIDER)
    if not vision_provider:
        raise HTTPException(status_code=500, detail="AI 服务未配置")

    try:
        result = await vision_provider.recognize_medicine(image_bytes)
        return result.model_dump()
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"识别失败: {str(e)}")


@router.post("/recognize-dates")
async def recognize_dates(
    file: UploadFile = File(...),
    db: AsyncSession = Depends(get_db),
    current_user: User = Depends(require_role(["admin", "user"]))
):
    from app.ai.manager import ai_manager

    if not file.content_type.startswith("image/"):
        raise HTTPException(status_code=400, detail="请上传图片文件")

    image_bytes = await file.read()
    if len(image_bytes) > settings.MAX_UPLOAD_SIZE:
        raise HTTPException(status_code=413, detail="文件过大")

    vision_provider = ai_manager.get_vision_provider(settings.AI_PROVIDER)
    if not vision_provider:
        raise HTTPException(status_code=500, detail="AI 服务未配置")

    try:
        result = await vision_provider.recognize_dates(image_bytes)
        return result.model_dump()
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"识别失败: {str(e)}")


@router.post("/recognize-leaflet")
async def recognize_leaflet(
    file: UploadFile = File(...),
    db: AsyncSession = Depends(get_db),
    current_user: User = Depends(require_role(["admin", "user"]))
):
    from app.ai.manager import ai_manager

    if not file.content_type.startswith("image/"):
        raise HTTPException(status_code=400, detail="请上传图片文件")

    image_bytes = await file.read()
    if len(image_bytes) > settings.MAX_UPLOAD_SIZE:
        raise HTTPException(status_code=413, detail="文件过大")

    text_provider = ai_manager.get_text_provider(settings.AI_PROVIDER)
    if not text_provider:
        raise HTTPException(status_code=500, detail="AI 服务未配置")

    try:
        import base64
        base64_image = base64.b64encode(image_bytes).decode('utf-8')

        from openai import AsyncOpenAI
        client = AsyncOpenAI(api_key=settings.OPENAI_API_KEY)

        response = await client.chat.completions.create(
            model=settings.OPENAI_MODEL,
            messages=[
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "text",
                            "text": "请识别这张说明书图片中的文字内容，返回纯文本。"
                        },
                        {
                            "type": "image_url",
                            "image_url": {
                                "url": f"data:image/jpeg;base64,{base64_image}"
                            }
                        }
                    ]
                }
            ]
        )

        ocr_text = response.choices[0].message.content
        result = await text_provider.summarize_leaflet(ocr_text)
        return result.model_dump()
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"识别失败: {str(e)}")