Update app.py

app.py

@@ -1,16 +1,13 @@
 import streamlit as st
-from transformers import pipeline
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
 from gtts import gTTS
-from pytube import Search
-import os
+import torch
 
-# Initialize conversational model for empathetic dialogue
-conversational_bot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
+# Load GPT-2 model and tokenizer from Hugging Face
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
 
-# Initialize sentiment analysis
-sentiment_analysis = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
-
-# Set up Streamlit page
+# Set up Streamlit page configuration
 st.set_page_config(page_title="Grief and Loss Support Bot", page_icon="🌿", layout="centered")
 st.markdown("""
     <style>
@@ -23,43 +20,64 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-# Title
+# Title and introduction to the bot
 st.title("Grief and Loss Support Bot 🌿")
 st.subheader("Your compassionate companion in tough times 💚")
 
-# Get user input
+# User input
 user_input = st.text_input("Share what's on your mind...", placeholder="Type here...", max_chars=500)
 
-# Check if user has entered text
-if user_input:
-    # Run sentiment analysis to check for distress
-    sentiment = sentiment_analysis(user_input)[0]
-    # Generate empathetic response
-    response = conversational_bot(user_input, max_length=250, temperature=0.95, top_k=60)[0]['generated_text']
+# Store previous responses to check for repetition
+if 'previous_responses' not in st.session_state:
+    st.session_state.previous_responses = []
+
+# Function to generate a more empathetic and focused response
+def generate_response(user_input):
+    # Tokenize input and set parameters for text generation
+    inputs = tokenizer.encode(user_input, return_tensors="pt")
+    outputs = model.generate(
+        inputs, 
+        max_length=200, 
+        temperature=0.8, 
+        top_k=50, 
+        num_return_sequences=1,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    # Add a suggestion for coping activity based on keywords in user input
+    if "angry" in user_input.lower() or "frustrated" in user_input.lower():
+        activity_suggestion = (
+            "Sometimes, deep breathing exercises can help calm your mind. "
+            "Try taking slow, deep breaths to regain a sense of calm and focus."
+        )
+    elif "sad" in user_input.lower() or "lonely" in user_input.lower():
+        activity_suggestion = (
+            "Writing about your feelings can be very therapeutic. "
+            "Try journaling as a way to process and release some of your emotions."
+        )
+    else:
+        activity_suggestion = (
+            "Finding a creative outlet like drawing or painting can help. "
+            "Art is a way to express feelings that might be difficult to put into words."
+        )
+    
+    # Append the activity suggestion to the generated response
+    response = f"{response_text}\n\nHere's something you could try to help cope with how you're feeling:\n{activity_suggestion}"
+    
+    return response
 
-    # Display response
-    st.text_area("Bot's Response:", response, height=200)
+# Check if the user has typed something
+if user_input:
+    # Generate the empathetic response
+    response = generate_response(user_input)
+    
+    # Store and show the new response
+    st.session_state.previous_responses.append(response)
+    st.text_area("Bot's Response:", response, height=250)
 
-    # Text-to-speech output
+    # Text-to-speech output (optional)
     tts = gTTS(response, lang='en')
     audio_file = "response.mp3"
     tts.save(audio_file)
     st.audio(audio_file, format="audio/mp3")
-
-    # Suggest a productive activity based on detected keywords
-    if any(keyword in user_input.lower() for keyword in ["lonely", "lost", "sad", "overwhelmed"]):
-        st.info("Here's a suggestion to help you cope:")
-        activities = ["journaling", "yoga", "painting"]
-        selected_activity = st.selectbox("Choose an activity you'd like to try:", activities)
-        
-        # Search YouTube for videos related to the selected activity
-        search = Search(selected_activity)
-        search_results = search.results[:3]  # limit results to 3 videos 
-        for video in search_results:
-            st.write(f"[{video.title}]({video.watch_url})")
-
-    # Crisis resources
-    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.")
-        st.write("[Find emergency resources here](https://www.helpguide.org/find-help.htm)")