Update main.py

main.py

@@ -143,15 +143,23 @@ async def predict_height(data: SingleAssessment) -> Dict:
         raise HTTPException(status_code=500, detail=str(e))
 
 
-def process_single_row(row, use_predicted_height=False):
+def process_single_row(row, use_predicted_height=False, use_gba_height=False):
     """Process a single row from CSV - used for parallel processing."""
     try:
         lat = row['latitude']
         lon = row['longitude']
         height = row.get('height', 0.0)
         basement = row.get('basement', 0.0)
-
-        if use_predicted_height:
+        if use_gba_height:
+            try:
+                result = gba_getter.get_height_m(lat, lon, buffer_m=5.0)
+                if result.get('status') == 'success' and result.get('predicted_height') is not None:
+                    h = result['predicted_height']
+                    if h >= 0:  # Only use valid positive heights
+                        height = h
+            except Exception as e:
+                print(f"GBA height failed for {lat},{lon}: {e}")
+        elif use_predicted_height:
             try:
                 predictor = get_predictor()
                 pred = predictor.predict_from_coordinates(lat, lon)
@@ -213,7 +221,7 @@ def process_single_row(row, use_predicted_height=False):
 
 
 @app.post("/assess_batch")
-async def assess_batch(file: UploadFile = File(...), use_predicted_height: bool = False) -> StreamingResponse:
+async def assess_batch(file: UploadFile = File(...), use_predicted_height:bool=False, use_gba_height:bool=False) -> StreamingResponse:
     """Assess flood vulnerability for multiple locations from a CSV file."""
     try:
         contents = await file.read()
@@ -239,7 +247,7 @@ async def assess_batch(file: UploadFile = File(...), use_predicted_height: bool
         loop = asyncio.get_event_loop()
         results = await loop.run_in_executor(
             executor,
-            lambda: [process_single_row(row, use_predicted_height) for _, row in df.iterrows()]
+            lambda: [process_single_row(row, use_predicted_height, use_gba_height) for _, row in df.iterrows()]
         )
 
         results_df = pd.DataFrame(results)
@@ -260,7 +268,7 @@ async def assess_batch(file: UploadFile = File(...), use_predicted_height: bool
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Batch processing failed: {str(e)}")
 @app.post("/assess_batch_multihazard")
-async def assess_batch_multihazard(file: UploadFile = File(...), use_predicted_height: bool = False) -> StreamingResponse:
+async def assess_batch_multihazard(file: UploadFile = File(...), use_predicted_height: bool = False, use_gba_height: bool = False) -> StreamingResponse:
     try:
         contents = await file.read()
         df = pd.read_csv(io.StringIO(contents.decode('utf-8')))
@@ -275,7 +283,7 @@ async def assess_batch_multihazard(file: UploadFile = File(...), use_predicted_h
         from vulnerability import calculate_multi_hazard_vulnerability
         results = await loop.run_in_executor(
             executor,
-            lambda: [process_single_row_multihazard(row, use_predicted_height) for _, row in df.iterrows()]
+            lambda: [process_single_row_multihazard(row, use_predicted_height, use_gba_height) for _, row in df.iterrows()]
         )
 
         results_df = pd.DataFrame(results)
@@ -337,7 +345,7 @@ async def explain_assessment(data: SingleAssessment) -> Dict:
         raise HTTPException(status_code=500, detail=f"Assessment failed: {e}")
 
 
-def process_single_row_multihazard(row, use_predicted_height=False):
+def process_single_row_multihazard(row, use_predicted_height=False, use_gba_height=False):
     """Process a single row with multi-hazard assessment."""
     try:
         from vulnerability import calculate_multi_hazard_vulnerability
@@ -347,7 +355,16 @@ def process_single_row_multihazard(row, use_predicted_height=False):
         height = row.get('height', 0.0)
         basement = row.get('basement', 0.0)
 
-        if use_predicted_height:
+        if use_gba_height:
+            try:
+                result = gba_getter.get_height_m(lat, lon, buffer_m=5.0)
+                if result.get('status') == 'success' and result.get('predicted_height') is not None:
+                    h = result['predicted_height']
+                    if h >= 0:  # Only use valid positive heights
+                        height = h
+            except Exception as e:
+                print(f"GBA height failed for {lat},{lon}: {e}")
+        elif use_predicted_height:
              try:
                 predictor = get_predictor()
                 pred = predictor.predict_from_coordinates(lat, lon)
@@ -444,7 +461,7 @@ async def get_height_gba(data: SingleAssessment):
         result = gba_getter.get_height_m(data.latitude, data.longitude, buffer_m=5.0)
 
         if result.get("status") != "success":
-            raise HTTPException(status_code=404, detail="GBA height not found for this location")
+            raise HTTPException(status_code=404, detail="GBA height not found for this location. Please try predicting the height.")
 
         return result
     except HTTPException: