Add emotion graph

app.py

@@ -378,17 +378,17 @@ def greet(tweet):
         "values": preemotion_list,
     }
 )
-    with gr.Blocks() as bar_plot:
-        bar_plot.load(outputs= gr.BarPlot(
-                simple,
-                x="Emotions",
-                y="Values",
-                title="Simple Bar Plot with made up data",
-                tooltip=["a", "b"],
-                y_lim=[20, 100],
-            ))
-
-    bar_plot.launch()
+    # with gr.Blocks() as bar_plot:
+    #     bar_plot.load(outputs= gr.BarPlot(
+    #             simple,
+    #             x="Emotions",
+    #             y="Values",
+    #             title="Simple Bar Plot with made up data",
+    #             tooltip=["a", "b"],
+    #             y_lim=[20, 100],
+    #         ))
+
+    # bar_plot.launch()
 
     prediction_value = round(prediction.item(),2)
     # features_list = extract_features(tweet)
@@ -405,7 +405,7 @@ def greet(tweet):
         label = "Hate"
     
 
-    return label,str(prediction_value)+"%",str(1-prediction_value)+"%"
+    return label,str(prediction_value)+"%",str(1-prediction_value)+"%",simple
 
 # demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo = gr.Interface(
@@ -415,7 +415,15 @@ demo = gr.Interface(
     allow_flagging = "never",outputs=[
         gr.Label(label="Label"),
         gr.Textbox(label="Hate Speech Percentage"),
-        gr.Textbox(label="Non Hate Speech Percentage")
+        gr.Textbox(label="Non Hate Speech Percentage"),
+        gr.BarPlot(
+                simple,
+                x="Emotions",
+                y="Values",
+                title="Simple Bar Plot with made up data",
+                tooltip=["a", "b"],
+                y_lim=[20, 100],
+            )
     ],
     examples=[
         ["I like you"],