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| import streamlit as st | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| from gtts import gTTS | |
| import torch | |
| # 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 💚") | |
| # 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=150, 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) | |
| # Add empathetic and coping suggestions | |
| response = f"{bot_output}\n\nHere's something you could try to help cope with how you're feeling:\n" | |
| if "crying" in user_input.lower(): | |
| response += "Sometimes letting yourself cry is a necessary release. It’s okay to feel what you're feeling. Also, trying to reach out to a friend or family member for support can be really comforting." | |
| elif "overwhelmed" in user_input.lower(): | |
| response += "Overwhelm can often feel like too much to handle, but try taking it one step at a time. Break your tasks down into small pieces and remember to take breaks. You don't have to do it all at once." | |
| else: | |
| response += "Taking a moment to breathe deeply, meditate, or even take a short walk can help you regain some balance in this difficult moment." | |
| 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") | |