Update app.py

app.py

@@ -39,13 +39,13 @@ if 'previous_responses' not in st.session_state:
 # Check if user has entered text
 if user_input:
     # Refined prompt for better empathetic responses
-    prompt = f"The user is expressing their feelings of grief, loss, or overwhelm. Respond with empathy and support. User's input: {user_input}"
+    prompt = f"User is feeling overwhelmed with emotional distress and is going through a tough time. Respond empathetically, offering support and understanding. The user's input: {user_input}"
 
     # Run the text generation model to generate a response based on user input
-    generated_responses = generator(prompt, max_length=250, num_return_sequences=3, temperature=0.7)
+    generated_responses = generator(prompt, max_length=200, num_return_sequences=3, temperature=0.7)
 
     # Filter out any responses that are too similar to previous responses or user input
-    new_responses = [response['generated_text'] for response in generated_responses]
+    new_responses = [response['generated_text'].strip() for response in generated_responses]
     new_responses = [resp for resp in new_responses if resp.lower() not in [prev.lower() for prev in st.session_state.previous_responses] and resp.lower() != user_input.lower()]
 
     # If there are valid new responses, pick one, otherwise fallback
@@ -100,8 +100,11 @@ if user_input:
         # Search YouTube for videos related to the selected activity
         search = Search(activity)
         search_results = search.results[:3]  # limit results to 3 videos
-        for video in search_results:
-            st.write(f"[{video.title}]({video.watch_url})")
+        if search_results:
+            for video in search_results:
+                st.write(f"[{video.title}]({video.watch_url})")
+        else:
+            st.write("Sorry, I couldn't find any relevant videos at the moment.")
 
     # Crisis resources
     crisis_keywords = ["help", "suicide", "depressed", "emergency", "hurt", "lost"]