app.py

import streamlit as st
from transformers import GPT2LMHeadModel, GPT2Tokenizer
from gtts import gTTS
import torch

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

# 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 💚")

# 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
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

# 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 (optional)
    tts = gTTS(response, lang='en')
    audio_file = "response.mp3"
    tts.save(audio_file)
    st.audio(audio_file, format="audio/mp3")