Refactor: Integrate backend API and normalize data

This commit integrates the backend API for fetching and updating report data. It also includes a normalization function to handle data consistency between the API and local storage.

Co-authored-by: anthonymuncher <anthonymuncher@gmail.com>

backend/app/routes/report.py

@@ -0,0 +1,100 @@
+from fastapi import APIRouter, UploadFile, File, Form, Depends, HTTPException
+from fastapi.responses import JSONResponse
+from sqlalchemy.orm import Session
+from app.database import get_db
+from app.services.ticket_service import TicketService, SeverityLevel
+from app.models.ticket_model import User
+from app.services.global_ai import get_ai_service
+import os, uuid, logging
+
+router = APIRouter()
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+
+UPLOAD_DIR = "app/static/uploads"
+os.makedirs(UPLOAD_DIR, exist_ok=True)
+
+@router.post("/report")
+async def report_issue(
+    user_id: str = Form(...),
+    latitude: float = Form(...),
+    longitude: float = Form(...),
+    description: str = Form(""),
+    image: UploadFile = File(...),
+    db: Session = Depends(get_db)
+):
+    logger.debug("Received report request")
+    ticket_service = TicketService(db)
+
+    # Validate user
+    user = db.query(User).filter(User.id == user_id).first()
+    if not user:
+        logger.error(f"User with id {user_id} not found")
+        raise HTTPException(status_code=404, detail=f"User with id {user_id} not found")
+    logger.debug(f"User found: {user.name} ({user.email})")
+
+    # Save uploaded image
+    file_ext = os.path.splitext(image.filename)[1]
+    filename = f"{uuid.uuid4()}{file_ext}"
+    file_path = os.path.join(UPLOAD_DIR, filename)
+    try:
+        content = await image.read()
+        with open(file_path, "wb") as f:
+            f.write(content)
+        logger.debug(f"Saved image to {file_path} ({len(content)} bytes)")
+    except Exception as e:
+        logger.exception("Failed to save uploaded image")
+        raise HTTPException(status_code=500, detail="Failed to save uploaded image")
+
+    # Get initialized AI service
+    ai_service = get_ai_service()
+    logger.debug("AI service ready")
+
+    # Run AI predictions
+    try:
+        category = ai_service.classify_category(file_path)
+        logger.debug(f"Classification: {category}")
+
+        if category.lower() == "pothole":
+            severity_str, annotated_path = ai_service.detect_pothole_severity(file_path)
+            logger.debug(f"Detection: severity={severity_str}, path={annotated_path}")
+            severity = {
+                "High": SeverityLevel.HIGH,
+                "Medium": SeverityLevel.MEDIUM,
+                "Low": SeverityLevel.LOW,
+                "Unknown": SeverityLevel.NA
+            }.get(severity_str, SeverityLevel.NA)
+        else:
+            severity = SeverityLevel.NA
+            logger.debug("No detection needed")
+    except Exception as e:
+        logger.exception("AI prediction failed")
+        category = "Unknown"
+        severity = SeverityLevel.NA
+
+    # Create ticket
+    ticket = ticket_service.create_ticket(
+        user_id=user.id,
+        image_path=file_path,
+        category=category,
+        severity=severity,
+        latitude=latitude,
+        longitude=longitude,
+        description=description
+    )
+    logger.info(f"Ticket created: {ticket.id} for user {user.id}")
+
+    response = {
+        "ticket_id": ticket.id,
+        "user_id": user.id,
+        "user_name": user.name,
+        "user_email": user.email,
+        "category": ticket.category,
+        "severity": ticket.severity.value,
+        "status": ticket.status.value,
+        "description": ticket.description,
+        "image_path": ticket.image_path
+    }
+
+    logger.debug(f"Response: {response}")
+    return JSONResponse(status_code=201, content=response)