Update app.py

app.py

@@ -177,39 +177,27 @@ class LangChain_Document_QA:
 
 
 
-    def _text_box(self,customer_emotion,agent_emotion,agent_sentiment_score,customer_sentiment_score):
-        agent_score = ", ".join([f"{key}: {value:.2f}" for key, value in agent_sentiment_score.items()])
+    def _text_box(self,customer_emotion,customer_sentiment_score):
         customer_score = ", ".join([f"{key}: {value:.2f}" for key, value in customer_sentiment_score.items()])
-        return f"customer_emotion:{customer_emotion}\nagent_emotion:{agent_emotion}\nAgent_Sentiment_score:{agent_score}\nCustomer_sentiment_score:{customer_score}"
+        return f"customer_emotion:{customer_emotion}\nCustomer_sentiment_score:{customer_score}"
 
     def _on_sentiment_btn_click(self):
-        client,agent=self._history_of_chat()
+        client=self._history_of_chat()
 
         customer_emotion=sentiment.emotion_analysis(client)
         customer_sentiment_score = sentiment.analyze_sentiment_for_graph(client)
 
-        agent_emotion=sentiment.emotion_analysis(agent)
-        agent_sentiment_score = sentiment.analyze_sentiment_for_graph(agent)
-
-        scores=self._text_box(customer_emotion,agent_emotion,agent_sentiment_score,customer_sentiment_score)
+        scores=self._text_box(customer_emotion,customer_sentiment_score)
 
         customer_fig=self._display_graph(customer_sentiment_score)
         customer_fig.update_layout(title="Sentiment Analysis",width=770)
 
-        agent_fig=self._display_graph(agent_sentiment_score)
-        agent_fig.update_layout(title="Sentiment Analysis",width=770)
-
-        agent_emotion_score = sentiment.emotion_analysis_for_graph(agent_emotion)
-
-        agent_emotion_fig=self._display_graph(agent_emotion_score)
-        agent_emotion_fig.update_layout(title="Emotion Analysis",width=770)
-
         customer_emotion_score = sentiment.emotion_analysis_for_graph(customer_emotion)
 
         customer_emotion_fig=self._display_graph(customer_emotion_score)
         customer_emotion_fig.update_layout(title="Emotion Analysis",width=770)
 
-        return scores,customer_fig,agent_fig,customer_emotion_fig,agent_emotion_fig
+        return scores,customer_fig,customer_emotion_fig
 
 
     def clear_func(self):
@@ -255,7 +243,8 @@ class LangChain_Document_QA:
                       lines=4,
                       placeholder="Sentiment",
                   ).style(container=False)
-          
+          with gr.Row():
+              with gr.Column(scale=0.50, min_width=0):
                   end_btn=gr.Button(
                       value="End",
                       )
@@ -270,11 +259,6 @@ class LangChain_Document_QA:
                   plot =gr.Plot(label="Patient", size=(500, 600))
               with gr.Column(scale=0.50, min_width=0):
                   plot_3 =gr.Plot(label="Patient_Emotion", size=(500, 600))
-          with gr.Row():
-              with gr.Column(scale=0.50, min_width=0):
-                  plot_2 =gr.Plot(label="Psychotherapist", size=(500, 600))
-              with gr.Column(scale=0.50, min_width=0):
-                  plot_4 =gr.Plot(label="Psychotherapist_Emotion", size=(500, 600))
 
 
           txt_msg = txt.submit(self._add_text, [chatbot, txt], [chatbot, txt])
@@ -285,7 +269,7 @@ class LangChain_Document_QA:
           emptyBtn.click(self.clear_func,[],[])
           emptyBtn.click(lambda: None, None, chatbot, queue=False)
 
-          Sentiment_btn.click(self._on_sentiment_btn_click,[],[txt5,plot,plot_2,plot_3,plot_4])
+          Sentiment_btn.click(self._on_sentiment_btn_click,[],[txt5,plot,plot_3])
 
       demo.title = "AI Mental Healthcare ChatBot"
       demo.launch()