Update app.py

app.py

@@ -2,14 +2,22 @@ import streamlit as st
 from transformers import pipeline
 from gtts import gTTS
 from pytube import Search
+import random
 import os
 
-# Initialize conversational model for empathetic dialogue
+# Initialize conversational models
 conversational_bot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
-
-# Initialize sentiment analysis
 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."
+]
+
 # Set up Streamlit page
 st.set_page_config(page_title="Grief and Loss Support Bot", page_icon="🌿", layout="centered")
 st.markdown("""
@@ -32,34 +40,42 @@ user_input = st.text_input("Share what's on your mind...", placeholder="Type her
 
 # Check if user has entered text
 if user_input:
-    # Run sentiment analysis to check for distress
+    # Run sentiment analysis for crisis detection
     sentiment = sentiment_analysis(user_input)[0]
 
-    # Generate empathetic response (model generates responses with empathy)
+    # Use conversational bot for responses
     response = conversational_bot(user_input, max_length=150)[0]['generated_text']
 
-    # 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."
-
     # Display response
     st.text_area("Bot's Response:", response, height=150)
 
+    # Motivational quote
+    quote = random.choice(motivational_quotes)
+    st.markdown(f"### 💬 Motivation: _{quote}_")
+
     # Text-to-speech output
-    tts = gTTS(response, lang='en')
+    tts = gTTS(f"{response} {quote}", lang='en')
     audio_file = "response.mp3"
     tts.save(audio_file)
-    st.audio(audio_file, format="audio/mp3")
+    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"]):
-        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)
-        
+    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}")
+
         # Search YouTube for videos related to the selected activity
         search = Search(activity)
-        search_results = search.results[:3]  # limit results to 2 videos
+        search_results = search.results[:2]  # limit results to 2 videos
         for video in search_results:
             st.write(f"[{video.title}]({video.watch_url})")