import io
from fastapi import APIRouter, File, UploadFile, HTTPException, Request
from PIL import Image
from api.services.analyzer_service import IncidentAnalyzer

router = APIRouter(prefix="/api/v1/incidents", tags=["Incidents"])

@router.post("/analyze", response_model=dict)
async def analyze_incident_image(request: Request, file: UploadFile = File(...)):
    """
    Accepts an emergency incident image, runs zero-shot object detection using 
    Grounding DINO, and computes an incident type and severity score.
    """
    # Validate uploaded file type
    if not file.content_type or not file.content_type.startswith("image/"):
        raise HTTPException(
            status_code=400,
            detail="Invalid file format. Please upload an image file."
        )

    try:
        # Read file contents and open as PIL Image
        file_bytes = await file.read()
        image = Image.open(io.BytesIO(file_bytes)).convert("RGB")
    except Exception as e:
        raise HTTPException(
            status_code=400,
            detail=f"Failed to process image file: {str(e)}"
        )

    # Get Grounding DINO service instance from app state
    dino_service = getattr(request.app.state, "dino_service", None)
    if dino_service is None:
        raise HTTPException(
            status_code=503,
            detail="Model service is currently initializing. Please try again shortly."
        )

    try:
        # Run inference
        detections = dino_service.detect(image)
    except Exception as e:
        raise HTTPException(
            status_code=500,
            detail=f"Error executing object detection: {str(e)}"
        )

    # Count frequencies of each detected label
    counts = {}
    for detection in detections:
        label = detection["label"]
        counts[label] = counts.get(label, 0) + 1

    # Extract unique labels list
    keywords = list(counts.keys())

    # Analyze incident characteristics (severity and type classification)
    analysis_result = IncidentAnalyzer.analyze(keywords)

    # Return structured API response
    return {
        "success": True,
        "incident_type": analysis_result["incident_type"],
        "severity": analysis_result["severity"],
        "severity_score": analysis_result["severity_score"],
        "keywords": keywords,
        "counts": counts,
        "detections": detections
    }