app.py

import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer
from gtts import gTTS
import torch
import tempfile
import random
from pytube import Search

# Load DialoGPT model and tokenizer from Hugging Face
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")

# Set up Streamlit page configuration
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 and introduction to the bot
st.title("Grief and Loss Support Bot 🌿")
st.subheader("Your compassionate companion in tough times 💚")

# Initialize session state for chat history
if 'chat_history_ids' not in st.session_state:
    st.session_state.chat_history_ids = None
if 'bot_messages' not in st.session_state:
    st.session_state.bot_messages = []

# User input
user_input = st.text_input("Share what's on your mind...", placeholder="Type here...", max_chars=500)

# Function to generate a response using DialoGPT
def generate_response(user_input):
    if not user_input:
        return "I'm here whenever you're ready to talk."

    # Encode the user input and append to chat history
    new_user_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
    bot_input_ids = new_user_input_ids if st.session_state.chat_history_ids is None else torch.cat([st.session_state.chat_history_ids, new_user_input_ids], dim=-1)

    # Generate the bot's response
    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
    )

    # Update the chat history
    st.session_state.chat_history_ids = chat_history_ids
    bot_response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)

    bot_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 overwhelming."

    return bot_response

# Generate and display bot response if there's user input
if user_input:
    response = generate_response(user_input)
    st.session_state.bot_messages.append(response)

    # Display bot's response
    for message in st.session_state.bot_messages:
        st.text_area("Bot's Response:", message, height=150)

    # Text-to-speech output
    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
        tts = gTTS(response, lang='en')
        tts.save(tmp_file.name)
        st.audio(tmp_file.name, format="audio/mp3")

    # Activity suggestion 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:")

        # 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 suggest an activity
        activity = random.choice(list(activities.keys()))
        st.write(f"How about {activity}? {activities[activity]}")

        # Search YouTube for related videos using pytube
        search = Search(activity)
        search_results = search.results[:3]  # Limit results to 3 videos
        if search_results:
            for video in search_results:
                st.write(f"[{video.title}]({video.watch_url})")
        else:
            st.write("Sorry, I couldn't find any relevant videos at the moment.")

    # Crisis resources for distress signals
    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)")