Update app.py

app.py

@@ -1,13 +1,9 @@
 import streamlit as st
+import torch
 from transformers import pipeline
-from gtts import gTTS
-import os
 from youtubesearchpython import VideosSearch
 
-# Initialize the conversational model
-chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
-
-# Streamlit app layout with positive, calming design
+# Set up the page configuration for a welcoming appearance
 st.set_page_config(page_title="Grief and Loss Support Bot", page_icon="🕊️", layout="centered")
 
 # Customizing the app style for a soothing and modern look
@@ -43,42 +39,49 @@ st.markdown("""
 st.title("Grief and Loss Support Bot 🕊️")
 st.subheader("We are here for you. 💚 Your companion in tough times")
 
+# Load the conversational model pipeline
+try:
+    conversational_pipeline = pipeline(task="conversational", model="microsoft/DialoGPT-medium")
+except Exception as e:
+    st.error(f"Error loading the conversational model: {e}")
+
+# Load the TTS pipeline for generating audio
+try:
+    tts = pipeline(task="text-to-audio", model="espnet/kan-bayashi_ljspeech_vits", device=0 if torch.cuda.is_available() else -1)
+except Exception as e:
+    st.error(f"Error loading the TTS model: {e}")
+
 # User input for conversation
 user_input = st.text_input("Share what's on your mind...", placeholder="Type here...", max_chars=500)
 
 if user_input:
-    # Generate a compassionate response from the bot
-    response = chatbot(user_input, max_length=150)[0]['generated_text']
-    st.text_area("Bot's Response:", response, height=150)
-
-    # Empathetic voice output using gTTS
-    tts = gTTS(response, lang='en')
-    audio_file = "response.mp3"
-    tts.save(audio_file)
-    st.audio(audio_file, format="audio/mp3", use_container_width=True)
+    # Generate a conversational response
+    response = conversational_pipeline(user_input)
+    response_text = response[0]['generated_text']
+    
+    st.write("Bot's Response:")
+    st.write(response_text)
 
-    # Crisis keyword detection for emergency help
-    crisis_keywords = ["help", "suicide", "depressed", "emergency", "hurt", "lost"]
-    if any(keyword in user_input.lower() for keyword in crisis_keywords):
-        st.warning("It seems like you might be in distress. Please reach out to a crisis hotline or a trusted individual for support. You're not alone.")
-        st.write("[Find emergency resources here](https://www.helpguide.org/find-help.htm)")
+    # Generate audio from the response text
+    try:
+        audio_output = tts(response_text)
+        audio_file_path = "response_audio.wav"
+        with open(audio_file_path, "wb") as f:
+            f.write(audio_output["audio"])
+        st.audio(audio_file_path)
+    except Exception as e:
+        st.error(f"Error generating audio: {e}")
 
-    # Productive hobby suggestions
-    if st.button("Need something to do? Here are some activities to help you cope:"):
-        st.write("- Journaling your thoughts and emotions 📖")
-        st.write("- Painting or drawing your feelings 🎨")
-        st.write("- Taking a walk in nature 🌳")
-        st.write("- Listening to soothing music 🎶")
-        st.write("- Practicing deep breathing or meditation 🧘")
-        st.write("- Trying out a new hobby like knitting or gardening 🌱")
+    # Provide hobby suggestions
+    st.markdown("### Suggested Hobbies and Activities")
+    hobby_prompt = "Suggest hobbies and activities for emotional well-being:"
+    hobby_response = pipeline("text-generation", model="gpt2")(hobby_prompt, max_length=50, num_return_sequences=1)
+    st.write(hobby_response[0]['generated_text'])
 
-    # YouTube content suggestions for coping with grief
-    if st.button("Here are some videos that may help you:"):
-        videos_search = VideosSearch('coping with grief', limit=3)
-        results = videos_search.result()['result']
-        for i, video in enumerate(results):
-            st.write(f"{i + 1}. [{video['title']}]({video['link']})")
+    # Search for coping videos on YouTube
+    st.markdown("### Informational YouTube Videos")
+    video_search = VideosSearch('productive hobbies and coping with grief', limit=3)
+    results = video_search.result()
+    for video in results['result']:
+        st.write(f"[{video['title']}]({video['link']})")
 
-# Clean up the audio file after playback
-if os.path.exists(audio_file):
-    os.remove(audio_file)