Update app.py

app.py

@@ -40,24 +40,27 @@ if user_input:
     sentiment = sentiment_analysis(user_input)[0]
 
     # Generate empathetic response with increased length and more context
-    response = conversational_bot(user_input, max_length=300, num_return_sequences=1, temperature=0.9, top_k=50)[0]['generated_text']
+    response = conversational_bot(user_input, max_length=300, num_return_sequences=3, temperature=0.9, top_k=50)
 
-    # Ensure response does not repeat what the user said, and is supportive
-    if user_input.lower() in response.lower():
-        response = "I understand how you're feeling. You're not alone in this. I'm here to listen and help."
-    
-    # Check if the response is too similar to the previous one, if so, generate a new one
-    if response == st.session_state.previous_response:
-        response = conversational_bot(user_input, max_length=300, num_return_sequences=1, temperature=0.9, top_k=50)[0]['generated_text']
+    # Choose the response that does not repeat what the user said
+    best_response = ""
+    for generated in response:
+        if user_input.lower() not in generated['generated_text'].lower():
+            best_response = generated['generated_text']
+            break
+
+    # If no diverse response was found, generate a default supportive message
+    if not best_response:
+        best_response = "I understand how you're feeling. You're not alone in this. I'm here to listen and help."
     
     # Store the response for future comparison
-    st.session_state.previous_response = response
+    st.session_state.previous_response = best_response
 
     # Display response
-    st.text_area("Bot's Response:", response, height=250)
+    st.text_area("Bot's Response:", best_response, height=250)
 
     # Text-to-speech output
-    tts = gTTS(response, lang='en')
+    tts = gTTS(best_response, lang='en')
     audio_file = "response.mp3"
     tts.save(audio_file)
     st.audio(audio_file, format="audio/mp3")