Update app.py

app.py

@@ -4,91 +4,105 @@ from gtts import gTTS
 from pytube import Search
 import random
 import os
-import datetime
-import torch
+import time
 
-# Load models
+# Load pretrained models
 tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
 model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
-emotion_analyzer = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base")
+emotion_classifier = pipeline("text-classification", model="bhadresh-savani/distilbert-base-uncased-emotion", return_all_scores=True)
 
-# Set up Streamlit page configuration
-st.set_page_config(page_title="Grief and Loss Support Bot", page_icon="🌿", layout="centered")
+# Streamlit page configuration
+st.set_page_config(page_title="Grief and Loss Support Bot 🌿", page_icon="🌿", layout="centered")
+st.markdown("<style>.css-1d391kg { background-color: #F3F7F6; }</style>", unsafe_allow_html=True)
 
-st.markdown("""
-    <style>
-    .css-1d391kg { background-color: #F3F7F6; }
-    .css-ffhzg2 { font-size: 1.5em; font-weight: 500; color: #4C6D7D; }
-    .stTextInput>div>div>input { background-color: #D8E3E2; }
-    .stButton>button { background-color: #A9D0B6; color: white; border-radius: 5px; }
-    .stButton>button:hover { background-color: #8FB79A; }
-    .stTextInput>div>label { color: #4C6D7D; }
-    </style>
-""", unsafe_allow_html=True)
-
-# Title and introduction
+# Title and welcome text
 st.title("Grief and Loss Support Bot 🌿")
 st.subheader("Your compassionate companion in tough times 💚")
 
-# Function to generate a response
-def generate_response(user_input):
-    input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
-    chat_history_ids = model.generate(input_ids, max_length=200, pad_token_id=tokenizer.eos_token_id, temperature=0.7, top_k=50, repetition_penalty=1.2)
-    bot_output = tokenizer.decode(chat_history_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
-    return bot_output
-
-# Function to generate a comforting story based on a theme
-def generate_story(theme):
-    prompt = f"Tell me a short, comforting story about {theme}."
-    input_ids = tokenizer.encode(prompt + tokenizer.eos_token, return_tensors='pt')
+# Sidebar for additional features
+with st.sidebar:
+    st.header("🧘 Guided Meditation")
+    if st.button("Play Meditation"):
+        meditation_audio = "meditation.mp3"
+        if not os.path.exists(meditation_audio):
+            tts = gTTS("Take a deep breath. Relax and let go of any tension...", lang='en')
+            tts.save(meditation_audio)
+        st.audio(meditation_audio, format="audio/mp3")
     
-    # Generate story
-    story_ids = model.generate(input_ids, max_length=150, temperature=0.7, top_p=0.9, repetition_penalty=1.2, do_sample=True, num_return_sequences=1)
-    story = tokenizer.decode(story_ids[0], skip_special_tokens=True)
-    return story
+    st.header("📖 Short Comforting Story")
+    story_theme = st.selectbox("Choose a theme for your story:", ["courage", "healing", "hope"])
+    if st.button("Generate Story"):
+        story_prompt = f"Tell me a comforting story about {story_theme}."
+        input_ids = tokenizer.encode(story_prompt, return_tensors='pt')
+        story_ids = model.generate(input_ids, max_length=150, temperature=0.8, repetition_penalty=1.1)
+        story = tokenizer.decode(story_ids[0], skip_special_tokens=True)
+        st.text_area("Here's your story:", story, height=200)
 
-# Mindfulness Meditation
-st.write("### 🧘 Guided Meditation")
-if st.button("Play a 5-minute Guided Meditation"):
-    meditation_text = "Focus on your breath. Inhale deeply, hold for a moment, and exhale slowly. Let go of any tension."
-    tts_meditation = gTTS(meditation_text, lang='en')
-    tts_meditation.save("meditation.mp3")
-    st.audio("meditation.mp3", format="audio/mp3")
+# User input section
+user_input = st.text_input("Share what's on your mind...", placeholder="Type here...", max_chars=500)
 
-# Interactive Storytelling
-st.write("### 📖 Short Comforting Story")
+if 'previous_responses' not in st.session_state:
+    st.session_state.previous_responses = []
+if 'badges' not in st.session_state:
+    st.session_state.badges = []
 
-# User selects a theme for the story
-story_theme = st.selectbox("Choose a theme for your story:", ["hope", "courage", "healing", "friendship", "resilience"])
-if st.button("Generate Story"):
-    story = generate_story(story_theme)
-    st.text_area("Here’s your comforting story:", story, height=250)
-    
-    # Convert story to speech
-    tts_story = gTTS(story, lang='en')
-    tts_story.save("story.mp3")
-    st.audio("story.mp3", format="audio/mp3")
+# Generate empathetic response
+def generate_response(user_input):
+    input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
+    chat_history_ids = model.generate(input_ids, max_length=150, temperature=0.7, top_k=50, repetition_penalty=1.2)
+    response = tokenizer.decode(chat_history_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
+    return response
 
-# User input for conversational support
-user_input = st.text_input("Share what's on your mind...", placeholder="Type here...", max_chars=500)
+# Analyze user input for emotional tone
+def get_emotion(user_input):
+    emotions = emotion_classifier(user_input)
+    emotions_sorted = sorted(emotions[0], key=lambda x: x['score'], reverse=True)
+    return emotions_sorted[0]['label']
+
+# Provide a response if user input is provided
 if user_input:
+    emotion = get_emotion(user_input)
     response = generate_response(user_input)
+    
+    # Display the bot's response
+    st.session_state.previous_responses.append(response)
     st.text_area("Bot's Response:", response, height=250)
     
-    # Text-to-speech for response
+    # Assign motivational badges
+    if emotion in ["joy", "optimism"]:
+        badge = "🌟 Positivity Badge"
+        if badge not in st.session_state.badges:
+            st.session_state.badges.append(badge)
+            st.success(f"Congratulations! You've earned a {badge}!")
+    
+    # Suggest coping activities
+    st.info("🎨 Try a New Activity")
+    activities = ["exercise", "yoga", "journaling", "painting", "meditation"]
+    selected_activity = st.selectbox("Pick an activity:", activities)
+    
+    # Fetch YouTube video suggestions
+    if st.button("Find Videos"):
+        search = Search(selected_activity)
+        search_results = search.results[:3]
+        if not search_results:
+            st.write(f"No results found for '{selected_activity}'.")
+        else:
+            for video in search_results:
+                st.write(f"[{video.title}]({video.watch_url})")
+
+    # Crisis resources
+    if any(word in user_input.lower() for word in ["suicide", "help", "depressed"]):
+        st.warning("Please reach out to a crisis hotline for immediate support.")
+        st.write("[Find emergency resources here](https://www.helpguide.org/find-help.htm)")
+
+    # Generate audio response
     tts = gTTS(response, lang='en')
-    tts.save("response.mp3")
-    st.audio("response.mp3", format="audio/mp3")
+    audio_file = "response.mp3"
+    tts.save(audio_file)
+    st.audio(audio_file, format="audio/mp3")
 
-# Enhanced Activity Suggestions
-st.write("### 🎨 Try a New Activity")
-activities = ["journaling", "yoga", "painting", "exercise", "meditation"]
-activity_choice = st.selectbox("Pick an activity:", activities)
-if st.button("Find Videos"):
-    try:
-        search = Search(activity_choice)
-        results = search.results[:3]
-        for video in results:
-            st.write(f"[{video.title}]({video.watch_url})")
-    except Exception as e:
-        st.write("Error fetching videos.")
+# Display badges and achievements
+if st.session_state.badges:
+    st.sidebar.header("🏅 Achievements")
+    for badge in st.session_state.badges:
+        st.sidebar.write(badge)