Update app.py

app.py

@@ -129,7 +129,7 @@ def predict_single_text(text):
     predicted_prob = [round(a_, 3) for a_ in probabilities.cpu().numpy().tolist() if a_ > threshold]
 
     # Create a dictionary containing the top predicted IEQ labels and their corresponding probabilities
-    top_prediction = predicted_labels
+    top_prediction = (dict(zip(predicted_labels, predicted_prob)))
 
     # Create a bar chart showing the likelihood of each IEQ label
     # Make dataframe for plotly bar chart
@@ -141,14 +141,14 @@ def predict_single_text(text):
     df2['Likelihood'] = n
 
     # plot graph of predictions
-    fig = px.bar(df2, x="Likelihood", y="IEQ", orientation="v")
+    fig = px.bar(df2, x="Likelihood", y="IEQ", orientation="h")
 
     fig.update_layout(
         # barmode='stack',
         template='seaborn', font=dict(family="Arial", size=12, color="black"),
         autosize=True,
-        # width=800,
-        # height=500,
+        width=800,
+        height=500,
         xaxis_title="Likelihood of IEQ",
         yaxis_title="Indoor environmental quality (IEQ)",
         # legend_title="Topics"