Update app.py

app.py

@@ -2,34 +2,28 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-# Load lightweight DialoGPT
 model_id = "microsoft/DialoGPT-medium"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id)
 
-# Persona
 PERSONA = """
 [System: You are 𝕴 𝖆𝖒 𝖍𝖎𝖒 - a fun, smooth, emotionally intelligent AI.
 You speak like a real person, not a robot. Keep it under 15 words. 😊😏]
 """
 
-# Format history
 def format_context(history):
     context = PERSONA + "\n"
     for user, bot in history[-3:]:
-        context += f"You: {user}\n"
-        context += f"𝕴 𝖆𝖒 𝖍𝖎𝖒: {bot}\n"
+        context += f"You: {user}\n𝕴 𝖆𝖒 𝖍𝖎𝖒: {bot}\n"
     return context
 
-# Humanize response
 def enhance_response(resp, message):
     if any(x in message for x in ["?", "think", "why"]):
         resp += " 🤔"
     elif any(x in resp.lower() for x in ["cool", "great", "love", "fun"]):
         resp += " 😏"
-    return " ".join(resp.split()[:15])  # Limit to 15 words
+    return " ".join(resp.split()[:15])
 
-# Generate AI reply
 def chat(user_input, history):
     context = format_context(history) + f"You: {user_input}\n𝕴 𝖆𝖒 𝖍𝖎𝖒:"
     inputs = tokenizer.encode(context, return_tensors="pt", truncation=True, max_length=1024)
@@ -50,10 +44,9 @@ def chat(user_input, history):
     history.append((user_input, response))
     return history, history
 
-# Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# 𝕴 𝖆𝖒 𝖍𝖎𝖒\n*Smooth • Chill • Emotional*")
-    chatbot = gr.Chatbot(label="Chat").style(height=400)
+    chatbot = gr.Chatbot(height=400, type="messages", label="Chat")  # <-- specify type and height here
     msg = gr.Textbox(placeholder="Type something…", show_label=False)
     state = gr.State([])