Add personality bar graph

app.py

@@ -176,6 +176,7 @@ def personality_detection(text, threshold=0.05, endpoint= 1.0):
     # # result = {label_names[i]: f"{predictions[i]*100:.0f}%" for i in range(len(label_names))}
     # result = {label_names[i]: f"{probabilities}%" for i in range(len(label_names))}
     # probabilities
+    print(probabilities)
     return [probabilities[0][0].detach().numpy()
             ,probabilities[0][1].detach().numpy()
             ,probabilities[0][2].detach().numpy()
@@ -377,7 +378,14 @@ def greet(tweet):
         "Emotions": ["Anger", "Anticipation", "Disgust", "Fear", "Joy", "Love", "Optimism", "Pessimism", "Sadness","Surprise","Trust"],
         "Values": preemotion_list,
     }
-)
+    )
+    personality_values = pd.DataFrame(
+        {
+            "Personality": ['Agreeableness', 'Conscientiousness', 'Extraversion', 'Neuroticism', 'Openness'],
+            "Values": personality_list,
+        }
+    )
+
     # with gr.Blocks() as bar_plot:
     #     bar_plot.load(outputs= gr.BarPlot(
     #             simple,
@@ -405,7 +413,7 @@ def greet(tweet):
         label = "Hate"
     
 
-    return label,str(prediction_value)+"%",str(1-prediction_value)+"%",simple
+    return label,str(prediction_value)+"%",str(1-prediction_value)+"%",simple,personality_values
 
 # demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo = gr.Interface(
@@ -422,7 +430,17 @@ demo = gr.Interface(
                 y="Values",
                 title="Emotion Analysis",
                 tooltip=["Emotions", "Values"],
-                y_lim=[0, 40],
+                y_lim=[0, 1],
+                label="Emotion bar graph"
+            ),
+            gr.BarPlot(
+                personality_values,
+                x="Personality",
+                y="Values",
+                title="Personality Analysis",
+                tooltip=["Personality", "Values"],
+                y_lim=[0, 1],
+                label="Personality bar graph"
             )
     ],
     examples=[