app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# -----------------------------
# Model setup
# -----------------------------
model_name = "moses132/dailydialog-chatbot"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# -----------------------------
# Chat function
# -----------------------------
chat_history = []

def moses_chat(user_message):
    # Add user message to history
    chat_history.append(f"User: {user_message}")
    
    # Build prompt from chat history
    prompt = "\n".join(chat_history) + "\nAI:"
    
    # Encode input
    inputs = tokenizer.encode(prompt, return_tensors="pt")
    
    # Generate model output
    outputs = model.generate(
        inputs,
        max_length=200,
        do_sample=True,
        top_p=0.9,
        temperature=0.8,
        pad_token_id=tokenizer.eos_token_id
    )
    
    # Decode reply
    reply = tokenizer.decode(outputs[0], skip_special_tokens=True)
    reply_text = reply.replace(prompt, "").strip()
    
    # Add AI reply to history
    chat_history.append(f"AI: {reply_text}")
    
    # Return all messages as chat bubbles
    messages = []
    for i, msg in enumerate(chat_history):
        if msg.startswith("User:"):
            messages.append(("User", msg.replace("User:","").strip()))
        else:
            messages.append(("AI", msg.replace("AI:","").strip()))
    return messages

# -----------------------------
# Gradio Interface
# -----------------------------
with gr.Blocks(title="Moses Chat") as demo:
    gr.Markdown("<h1 style='text-align:center; color:#4B0082;'>Moses Chat</h1>")
    
    with gr.Row():
        chatbot = gr.Chatbot(elem_id="moses-chatbot").style(height=500)
    
    with gr.Row():
        msg = gr.Textbox(placeholder="Type your message here...", lines=1)
        submit = gr.Button("Send")
    
    def respond(message):
        return moses_chat(message)
    
    submit.click(respond, inputs=msg, outputs=chatbot)
    msg.submit(respond, inputs=msg, outputs=chatbot)

# Launch the app
demo.launch()