Update app.py

app.py

@@ -2,21 +2,12 @@ import streamlit as st
 from transformers import pipeline
 from gtts import gTTS
 from pytube import Search
-import random
 import os
 
 # Initialize conversational models
 conversational_bot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
 sentiment_analysis = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
-
-# Motivational quotes list
-motivational_quotes = [
-    "You are stronger than you think. Keep going, one step at a time.",
-    "It's okay to take a break. Your mental health matters too.",
-    "This moment is tough, but it will pass. Stay strong.",
-    "Believe in yourself. You've faced challenges before and overcome them.",
-    "Don't give up. Progress is progress, no matter how small."
-]
+motivational_response = pipeline("text-generation", model="huggingtweets/motivational")
 
 # Set up Streamlit page
 st.set_page_config(page_title="Grief and Loss Support Bot", page_icon="🌿", layout="centered")
@@ -42,40 +33,32 @@ user_input = st.text_input("Share what's on your mind...", placeholder="Type her
 if user_input:
     # Run sentiment analysis for crisis detection
     sentiment = sentiment_analysis(user_input)[0]
-
+    
     # Use conversational bot for responses
     response = conversational_bot(user_input, max_length=150)[0]['generated_text']
-
+    
     # Display response
     st.text_area("Bot's Response:", response, height=150)
 
-    # Motivational quote
-    quote = random.choice(motivational_quotes)
-    st.markdown(f"### 💬 Motivation: _{quote}_")
+    # Generate motivational message
+    motivation = motivational_response(user_input, max_length=150)[0]['generated_text']
+    st.text_area("Motivational Response:", motivation, height=150)
 
-    # Text-to-speech output
-    tts = gTTS(f"{response} {quote}", lang='en')
+    # Text-to-speech output for both responses
+    tts = gTTS(response + " " + motivation, lang='en')
     audio_file = "response.mp3"
     tts.save(audio_file)
     st.audio(audio_file, format="audio/mp3")  # Removed use_container_width=True
 
     # Suggest a productive activity based on detected keywords
-    if any(keyword in user_input.lower() for keyword in ["lonely", "lost", "sad", "overwhelmed", "stressed"]):
-        st.info("Here's a suggestion to help lift your spirits:")
-        activities = {
-            "relaxation": ["listening to calming music", "meditation", "deep breathing exercises"],
-            "creative": ["journaling", "painting", "writing poetry"],
-            "exercise": ["light yoga", "stretching", "taking a walk outside"],
-            "self-care": ["taking a warm bath", "getting a good night's sleep", "reading a book"]
-        }
-        category = st.selectbox("Choose an activity category:", ["relaxation", "creative", "exercise", "self-care"])
-        activity = random.choice(activities[category])
-
-        st.write(f"Activity Suggestion: {activity}")
-
+    if any(keyword in user_input.lower() for keyword in ["lonely", "lost", "sad"]):
+        st.info("Here's a suggestion to help you cope:")
+        hobbies = ["journaling", "yoga", "painting"]
+        activity = st.selectbox("Choose an activity you'd like to try:", hobbies)
+        
         # Search YouTube for videos related to the selected activity
         search = Search(activity)
-        search_results = search.results[:2]  # limit results to 2 videos
+        search_results = search.results[:3]  # limit results to 2 videos
         for video in search_results:
             st.write(f"[{video.title}]({video.watch_url})")