app.py

import streamlit as st
from transformers import pipeline
from gtts import gTTS
from pytube import Search
import os

# Initialize models
conversational_bot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
sentiment_analysis = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")

# 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("How are you feeling today?", placeholder="Share what's on your mind...", max_chars=500)

# Check if user has entered text
if user_input:
    # Run sentiment analysis to assess mood
    try:
        sentiment = sentiment_analysis(user_input)[0]
        sentiment_label = sentiment['label'].lower()
        st.write(f"Sentiment detected: {sentiment_label}")  # Debugging line
    except Exception as e:
        st.write(f"Error in sentiment analysis: {e}")  # Error handling

    # Generate empathetic response from the conversational bot
    try:
        bot_response = conversational_bot(user_input, max_length=150)[0]['generated_text']
        st.write(f"Bot Response: {bot_response}")  # Debugging line
    except Exception as e:
        st.write(f"Error generating bot response: {e}")  # Error handling

    # Display response
    st.text_area("Bot's Response:", bot_response, height=150)

    # Text-to-speech output
    tts = gTTS(bot_response, lang='en')
    audio_file = "response.mp3"
    tts.save(audio_file)
    st.audio(audio_file, format="audio/mp3")

    # Suggest an activity
    if sentiment_label == "negative":
        st.info("Here's a suggestion to help lift your spirits:")
        activities = {
            "relaxation": ["mindful breathing", "yoga"],
            "creative": ["painting", "writing in a journal"],
            "exercise": ["a short walk", "stretching"],
            "self-care": ["listening to calming music", "meditation"]
        }
        
        # Choose activity based on keyword in input
        if any(keyword in user_input.lower() for keyword in ["lonely", "lost", "sad", "down"]):
            activity_category = "self-care"
        elif any(keyword in user_input.lower() for keyword in ["stress", "pressure", "overwhelmed"]):
            activity_category = "relaxation"
        else:
            activity_category = "creative"
        
        suggested_activity = activities[activity_category]
        st.write(f"Activity Suggestion: {suggested_activity}")

        # Search YouTube for videos related to the selected activity
        search = Search(suggested_activity[0])
        search_results = search.results[:2]  # limit results to 2 videos
        for video in search_results:
            st.write(f"[{video.title}]({video.watch_url})")

    # Crisis resources for critical keywords
    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)")