Update app.py

app.py

@@ -1,13 +1,18 @@
 import streamlit as st
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import pipeline, GPT2LMHeadModel, GPT2Tokenizer
 from gtts import gTTS
-import torch
+from pytube import Search
+import os
+import random
 
-# Load DialoGPT model and tokenizer from Hugging Face
-tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
-model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
+# Initialize GPT-2 model and tokenizer from Hugging Face
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
 
-# Set up Streamlit page configuration
+# Create a text generation pipeline using GPT-2
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Set up Streamlit page
 st.set_page_config(page_title="Grief and Loss Support Bot", page_icon="🌿", layout="centered")
 st.markdown("""
     <style>
@@ -20,51 +25,83 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-# Title and introduction to the bot
+# Title
 st.title("Grief and Loss Support Bot 🌿")
 st.subheader("Your compassionate companion in tough times 💚")
 
-# User input
+# Get user input
 user_input = st.text_input("Share what's on your mind...", placeholder="Type here...", max_chars=500)
 
 # 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 using DialoGPT
-def generate_response(user_input):
-    # Encode the input text and generate a response
-    new_user_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
-    bot_input_ids = new_user_input_ids
-    chat_history_ids = model.generate(bot_input_ids, max_length=200, pad_token_id=tokenizer.eos_token_id, temperature=0.7, top_k=50, repetition_penalty=1.2)
-    
-    # Decode the response to text
-    chat_history_ids = chat_history_ids[:, bot_input_ids.shape[-1]:]  # remove the input from the response
-    bot_output = tokenizer.decode(chat_history_ids[0], skip_special_tokens=True)
-    
-    # Build a more empathetic and thoughtful response
-    response = f"I’m really sorry you're feeling like this. It’s completely normal to feel overwhelmed when you're facing a heavy workload. It’s important to acknowledge how you feel and not keep it bottled up. Sometimes, stress and emotional exhaustion can build up, and it’s okay to let yourself feel those emotions."
-
-    # Add coping strategies based on the situation
-    if "workload" in user_input.lower():
-        response += "\n\nWhen the workload feels too heavy, it can be helpful to break tasks down into smaller, more manageable steps. Focus on one thing at a time, and remember that it’s okay to take breaks when needed. Asking for support from colleagues or friends is also a good way to lighten the load."
-
-    # Add general supportive message
-    response += "\n\nYou're doing your best, and that’s all anyone can ask for. Please take care of yourself and know that it’s okay to take a step back when things feel too much. Your well-being is the most important thing."
-
-    return response
-
-# Check if the user has typed something
+# Check if user has entered text
 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 (optional)
-    tts = gTTS(response, lang='en')
+    # Run the text generation model to generate a response based on user input
+    generated_responses = generator(user_input, max_length=250, num_return_sequences=3, temperature=0.7)
+
+    # Filter out any responses that are too similar to previous responses or user input
+    new_responses = [response['generated_text'] for response in generated_responses]
+    new_responses = [resp for resp in new_responses if resp.lower() not in [prev.lower() for prev in st.session_state.previous_responses] and resp.lower() != user_input.lower()]
+
+    # If there are valid new responses, pick one, otherwise fallback
+    if new_responses:
+        selected_response = random.choice(new_responses)
+    else:
+        # If no new response, fallback to a more generic empathetic message
+        fallback_responses = [
+            "I understand how you're feeling. You're not alone in this. I'm here to listen and help.",
+            "I'm really sorry you're going through this. Let's take one step at a time. I'm here for you.",
+            "It sounds really tough right now. It's okay to feel overwhelmed. You're doing your best, and that's enough."
+        ]
+        selected_response = random.choice(fallback_responses)
+
+    # Add extra empathetic phrases to the response
+    extra_empathy = [
+        "It’s completely normal to feel this way when things get tough. You're doing great by reaching out.",
+        "I know it can feel like a lot right now, but one step at a time. You're not alone in this.",
+        "Even in the toughest times, remember that there’s always support around you."
+    ]
+    selected_response += " " + random.choice(extra_empathy)
+
+    # Store the new response for future checks
+    st.session_state.previous_responses.append(selected_response)
+
+    # Display response
+    st.text_area("Bot's Response:", selected_response, height=250)
+
+    # Text-to-speech output
+    tts = gTTS(selected_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", "academic", "exam"]):
+        st.info("Here's a suggestion to help you cope:")
+
+        # Providing a variety of activities based on user mood and needs
+        activities = {
+            "journaling": "Express your feelings in writing. Journaling is a great way to process emotions.",
+            "yoga": "Yoga helps you relax and refocus. Try some deep breathing exercises or light stretching.",
+            "painting": "Creative expression through painting or drawing can be soothing and help you release pent-up emotions.",
+            "meditation": "Take a moment to calm your mind. Guided meditation can help reduce stress and anxiety.",
+            "exercise": "Physical activity can lift your mood. Even a short walk in nature can make a big difference."
+        }
+
+        # Randomly select an activity category to suggest
+        activity = random.choice(list(activities.keys()))
+        st.write(f"How about {activity}? {activities[activity]}")
+
+        # Search YouTube for videos related to the selected activity
+        search = Search(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)")