# app.py import random from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer import gradio as gr # ----------------------------- # Load empathetic model # ----------------------------- MODEL_NAME = "j-hartmann/emotion-english-distilroberta-base" tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME) pipe = pipeline("text-classification", model=model, tokenizer=tokenizer) # ----------------------------- # Empathetic responses # ----------------------------- responses = { "sadness": [ "I’m really sorry you’re feeling sad. It’s okay to feel this way — do you want to talk about what’s been troubling you?", "That sounds really hard. Remember, you don’t have to go through this alone.", "It’s understandable to feel down sometimes. I’m here if you want to share.", "Sadness can feel heavy — would you like to tell me more about it?", "You’re not alone in this. Talking can help lighten the load." ], "joy": [ "I’m so glad to hear that! What’s making you feel happy today?", "That’s wonderful — it’s great to see you in good spirits!", "Your happiness is contagious! Can you share what made your day?", "It’s great to feel joy — I’m happy for you!", "Sounds like a joyful moment! Let’s celebrate it together." ], "anger": [ "It sounds like you’re really upset. Do you want to share what happened?", "That must have been frustrating. Sometimes expressing it helps ease the anger.", "Anger can be intense — would you like to talk about it?", "I hear your frustration. Let’s try to unpack it together.", "It’s okay to feel angry — letting it out can help." ], "fear": [ "It’s normal to feel scared sometimes. I’m here with you — would you like to talk about what’s worrying you?", "That sounds frightening. You’re not alone in this.", "Fear can be overwhelming — want to tell me more about it?", "It’s okay to feel afraid. Sharing your worries can help.", "I understand — facing fear is hard, but I’m here for you." ], "surprise": [ "Oh, that sounds unexpected! How are you feeling about it?", "Wow, that must have caught you off guard. Tell me more!", "That’s surprising! I’d love to hear more about it.", "Unexpected events can feel shocking — how are you handling it?", "I’m here to listen — surprises can bring mixed feelings." ], "disgust": [ "That sounds unpleasant. Want to tell me what caused that feeling?", "It’s okay to feel grossed out sometimes — that emotion is valid too.", "Disgust is a natural reaction. Do you want to share why?", "I hear you — feeling disgusted can be really uncomfortable.", "It’s understandable to feel that way. Talking can help." ], "neutral": [ "I’m here to listen — what’s on your mind today?", "How are you feeling right now?", "I’m ready to hear you out. What would you like to share?", "It’s okay to just talk about anything. What’s happening?", "Feel free to tell me whatever’s on your mind." ] } recent_responses = {k: [] for k in responses.keys()} # ----------------------------- # FAQ responses with emojis # ----------------------------- faq_responses = { "What is depression? 🧠": "Depression is a common mental health condition characterized by persistent sadness, lack of interest in activities, and changes in sleep or appetite. Talking to a professional can help.", "How can I sleep better? 😴": "Good sleep hygiene helps: maintain a regular sleep schedule, avoid caffeine or screens before bed, and create a calm sleeping environment.", "How to deal with stress? 🌿": "Stress can be managed through relaxation techniques like deep breathing, meditation, exercise, and talking to someone you trust.", "What is anxiety? 😰": "Anxiety is a feeling of worry or fear that can be mild or severe. Breathing exercises, mindfulness, and professional guidance can help manage it.", "I feel lonely 😔": "Feeling lonely is normal sometimes. Connecting with friends, family, or support groups can help reduce loneliness.", "How to stay motivated? 💪": "Set small achievable goals, reward yourself, and remember why you started. Motivation can fluctuate — be kind to yourself." } # ----------------------------- # Chat function # ----------------------------- def chat(user_input, chat_history): if not user_input.strip(): return chat_history, "" # clear input # Add user's message to chat chat_history.append({"role": "user", "content": user_input}) user_lower = user_input.lower() # FAQ check for key in faq_responses: if key.lower().split("?")[0] in user_lower: reply = faq_responses[key] chat_history.append({"role": "assistant", "content": reply}) return chat_history, "" # clear input # Empathetic fallback emotions = pipe(user_input, top_k=1) emotion = emotions[0]['label'].lower() options = [r for r in responses.get(emotion, responses["neutral"]) if r not in recent_responses[emotion]] if not options: recent_responses[emotion] = [] options = responses.get(emotion, responses["neutral"]) reply = random.choice(options) recent_responses[emotion].append(reply) chat_history.append({"role": "assistant", "content": reply}) return chat_history, "" # clear input # ----------------------------- # FAQ click function (adds to chat) # ----------------------------- def faq_click(faq_key, chat_history): # Show FAQ question as user message chat_history.append({"role": "user", "content": faq_key}) # Show answer as bot message reply = faq_responses[faq_key] chat_history.append({"role": "assistant", "content": reply}) return chat_history # ----------------------------- # Gradio interface # ----------------------------- with gr.Blocks() as demo: gr.Markdown("

Empathetic Mental Health Bot + FAQ

") with gr.Row(): # FAQ sidebar with gr.Column(scale=1): gr.Markdown("### FAQs 💡") faq_btns = [] for key in faq_responses.keys(): btn = gr.Button(key) faq_btns.append(btn) # Chat area with gr.Column(scale=3): chatbot = gr.Chatbot(type="messages") msg = gr.Textbox(placeholder="Type your message here...") send_btn = gr.Button("Send") clear_btn = gr.Button("Clear") # Event handlers send_btn.click(chat, [msg, chatbot], [chatbot, msg]) msg.submit(chat, [msg, chatbot], [chatbot, msg]) clear_btn.click(lambda: [], None, chatbot) # FAQ button click events for i, btn in enumerate(faq_btns): key = list(faq_responses.keys())[i] btn.click(lambda chat_history, k=key: faq_click(k, chat_history), chatbot, chatbot) # ----------------------------- # Launch # ----------------------------- if __name__ == "__main__": demo.launch()