Update main.py

main.py

@@ -83,21 +83,21 @@ def process_multiple_address(addresses):
 async def predict(address_input: str):
     
     address_input_split = address_input.split(';')
-    results = process_multiple_address(address_input_split)
-    results = pd.concat(results).reset_index(drop=1)
+    # results = process_multiple_address(address_input_split)
+    # results = pd.concat(results).reset_index(drop=1)
     
-    cols_order=['Address Input',  'sqFtFinished', 'totalSqFt', 'yearBuilt', 'propertyTypeName', 'beds', 'baths', 'numStories',
-                'url',
-                'Lat', 'Lon']
-    cols_other=[i for i in results.columns if i not in cols_order ]
-    results=results[cols_order+cols_other].reset_index()
+    # cols_order=['Address Input',  'sqFtFinished', 'totalSqFt', 'yearBuilt', 'propertyTypeName', 'beds', 'baths', 'numStories',
+    #             'url',
+    #             'Lat', 'Lon']
+    # cols_other=[i for i in results.columns if i not in cols_order ]
+    # results=results[cols_order+cols_other].reset_index()
     
-    results['index']=results['index']+1
-    results.index=results.index+1
-    results=results.rename(columns={'index':'Input Position'})
-    prediction['yearBuilt']=results['yearBuilt'].fillna(0).astype(int).astype(str).replace('0','')
+    # results['index']=results['index']+1
+    # results.index=results.index+1
+    # results=results.rename(columns={'index':'Input Position'})
+    # prediction['yearBuilt']=results['yearBuilt'].fillna(0).astype(int).astype(str).replace('0','')
 
-    return prediction.to_json()
+    return address_input_split