app.py

import streamlit as st
from transformers import pipeline, GPT2LMHeadModel, GPT2Tokenizer
from gtts import gTTS
from pytube import Search
import os
import random

# Initialize GPT-2 model and tokenizer from Hugging Face
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("gpt2")

# 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>
    .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
st.title("Grief and Loss Support Bot 🌿")
st.subheader("Your compassionate companion in tough times 💚")

# 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 = []

# Check if user has entered text
if user_input:
    # Refined prompt for better empathetic responses
    prompt = f"The user is expressing their feelings of grief, loss, or overwhelm. Respond with empathy and support. User's input: {user_input}"

    # Run the text generation model to generate a response based on user input
    generated_responses = generator(prompt, 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)")