Update app.py

app.py

@@ -8,21 +8,6 @@ import json
 import dateutil.parser as dp
 import pandas as pd
 
-title = "Stoclholm Highway E4 Real Time Traffic Prediction"
-description = "Stockholm E4 (59°23'44.7"" N 17°59'00.4""E) highway real time traffic prediction"
-
-inputs = [gr.Dataframe(row_count = (1, "fixed"), col_count=(7,"fixed"), 
-                       headers=["referenceTime", "t", "ws", "prec1h", "fesn1h", "vis", "confidence"], 
-                       # datatype=["timestamp", "float", "float", "float", "float", "float"],
-                       label="Input Data", interactive=1)]
-
-outputs = [gr.Dataframe(row_count = (1, "fixed"), col_count=(1, "fixed"), label="Predictions", headers=["Congestion Level"])]
-
-model = joblib.load("./traffic_model.pkl")
-
-
-def infer(input_dataframe):
-  return pd.DataFrame(model.predict(input_dataframe))
 
 def get_row():
     response_tomtom = requests.get(
@@ -65,4 +50,19 @@ def get_row():
 
     return row
 
+model = joblib.load("./traffic_model.pkl")
+
+def infer(input_dataframe):
+  return pd.DataFrame(model.predict(input_dataframe))
+
+title = "Stoclholm Highway E4 Real Time Traffic Prediction"
+description = "Stockholm E4 (59°23'44.7"" N 17°59'00.4""E) highway real time traffic prediction"
+
+inputs = [gr.Dataframe(row_count = (1, "fixed"), col_count=(7,"fixed"), 
+                       headers=["referenceTime", "t", "ws", "prec1h", "fesn1h", "vis", "confidence"], 
+                       # datatype=["timestamp", "float", "float", "float", "float", "float"],
+                       label="Input Data", interactive=1)]
+
+outputs = [gr.Dataframe(row_count = (1, "fixed"), col_count=(1, "fixed"), label="Predictions", headers=["Congestion Level"])]
+
 gr.Interface(fn = infer, inputs = inputs, outputs = outputs, title=title, description=description, examples=[get_row()]).launch()