features/ai_human_image_classifier/routes.py

from fastapi import APIRouter, File, UploadFile, HTTPException, status
from fastapi.responses import JSONResponse
from controller import controller

from fastapi import Request, Depends
from fastapi.security import HTTPBearer
from slowapi import Limiter
from slowapi.util import get_remote_address


router = APIRouter()
limiter = Limiter(key_func=get_remote_address)
security = HTTPBearer()
# Create an API router
router = APIRouter()

@router.post("/classify", summary="Classify an image as Real or Fake")
async def classify_image_endpoint(image: UploadFile = File(...)):
    """
    Accepts an image file and classifies it as 'real' or 'fake'.

    - **image**: The image file to be classified (e.g., JPEG, PNG).

    Returns a JSON object with the classification and a confidence score.
    """
    # Check for a valid image content type
    if not image.content_type.startswith("image/"):
        raise HTTPException(
            status_code=status.HTTP_415_UNSUPPORTED_MEDIA_TYPE,
            detail="Unsupported file type. Please upload an image (e.g., JPEG, PNG)."
        )

    # The controller expects a file-like object, which `image.file` provides
    result = controller.classify_image(image.file)

    if "error" in result:
        # If the controller returned an error, forward it as an HTTP exception
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=result["error"]
        )
    
    return JSONResponse(content=result, status_code=status.HTTP_200_OK)