Update app.py

app.py

@@ -1,13 +1,15 @@
 import streamlit as st
-from transformers import pipeline
+from llama_cpp import Llama
 from gtts import gTTS
 from pytube import Search
 import random
 import os
 
-# Initialize pretrained Hugging Face models
-empathetic_response = pipeline("text2text-generation", model="mrm8488/t5-base-finetuned-empathy")
-sentiment_analysis = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
+# Initialize the Llama model
+llm = Llama.from_pretrained(
+    repo_id="featherless-ai-quants/HyunCello-KULLM3-empathy-v1.0-GGUF",
+    filename="HyunCello-KULLM3-empathy-v1.0-IQ4_XS.gguf"
+)
 
 # Configure Streamlit page
 st.set_page_config(page_title="Grief & Loss Support Bot", page_icon="🌱", layout="centered")
@@ -28,29 +30,31 @@ st.subheader("Your compassionate companion in tough times 💚")
 # User input
 user_input = st.text_input("How are you feeling today?", placeholder="Share your thoughts here...", max_chars=500)
 
-# Detect user sentiment and respond
+# Generate empathetic response using Llama model
 if user_input:
-    sentiment = sentiment_analysis(user_input)[0]
-    empathy_response = empathetic_response(user_input, max_length=100)[0]['generated_text']
+    response = llm.create_chat_completion(
+        messages=[
+            {"role": "user", "content": user_input}
+        ]
+    )['choices'][0]['message']['content']
     
     # Display empathetic response
-    st.text_area("Bot's Response:", empathy_response, height=150)
-    
+    st.text_area("Bot's Response:", response, height=150)
+
     # Convert text to speech for added comfort
-    tts = gTTS(empathy_response, lang='en')
+    tts = gTTS(response, lang='en')
     audio_file = "response.mp3"
     tts.save(audio_file)
     st.audio(audio_file, format="audio/mp3")
 
-    # Activity Suggestion based on emotions detected
-    mood = sentiment['label'].lower()
+    # Suggested activities based on user input
     activity_suggestions = {
         "positive": ["try journaling your feelings", "practice yoga", "learn a new recipe"],
         "neutral": ["take a short walk", "listen to calming music", "try some mindful breathing"],
         "negative": ["explore creative activities like painting", "watch a motivational video", "write down small goals to feel organized"]
     }
-    activities = activity_suggestions.get(mood, ["try relaxation exercises", "reach out to someone you trust"])
-    
+    activities = activity_suggestions["neutral"]  # Default to "neutral" for simplicity
+
     # Show dynamic activity suggestion
     st.info("Here’s something you could try to lift your spirits:")
     selected_activity = random.choice(activities)
@@ -61,7 +65,7 @@ if user_input:
     st.write("Recommended Videos:")
     for video in search.results[:2]:  # Display top 2 videos
         st.write(f"[{video.title}]({video.watch_url})")
-    
+
     # Crisis response if critical keywords are detected
     crisis_keywords = ["help", "suicide", "depressed", "emergency", "hurt", "lost"]
     if any(keyword in user_input.lower() for keyword in crisis_keywords):