import os
from fastapi import FastAPI, UploadFile, File, Header, HTTPException, status
from fastapi.middleware.cors import CORSMiddleware
from typing import Optional
from backend.services.openai_service import extract_receipt_data
from backend.schemas import ExtractionResponse
from dotenv import load_dotenv

load_dotenv()

app = FastAPI(title="AI-Assisted Data Entry API")

# Configure CORS
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Adjust as needed for Angular frontend
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.get("/health")
async def health_check():
    return {"status": "healthy"}

@app.post("/api/v1/extract", response_model=ExtractionResponse)
async def extract_receipt(
    file: UploadFile = File(...),
    user_id: Optional[str] = Header(None),
    user_name: str = "Unknown Employee",
    department: str = "Unknown Department"
):
    if not file.content_type.startswith("image/"):
        raise HTTPException(
            status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
            detail="File provided is not an image."
        )
    
    try:
        content = await file.read()
        extraction_result = await extract_receipt_data(content, user_name, department)
        
        if extraction_result is None:
             raise HTTPException(
                status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
                detail="Could not extract data from the provided image."
            )
            
        return extraction_result
    except Exception as e:
        raise HTTPException(
            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
            detail=f"An error occurred during extraction: {str(e)}"
        )

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)