app.py

import gradio as gr
from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration

# Load the Blenderbot model and tokenizer
MODEL_NAME = "facebook/blenderbot-3B"
tokenizer = BlenderbotTokenizer.from_pretrained(MODEL_NAME)
model = BlenderbotForConditionalGeneration.from_pretrained(MODEL_NAME)

def chatbot_response(user_input, chat_history=[]):
    """Generates a response from Blenderbot based on user input."""
    inputs = tokenizer(user_input, return_tensors="pt")
    reply_ids = model.generate(**inputs)
    response = tokenizer.decode(reply_ids[0], skip_special_tokens=True)
    chat_history.append((user_input, response))
    return response, chat_history

# Set up Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# 🤖 Blenderbot 3B Chatbot")
    chatbot = gr.Chatbot()
    user_input = gr.Textbox(label="Your message")
    submit_btn = gr.Button("Send")
    clear_btn = gr.Button("Clear Chat")
    
    chat_state = gr.State([])
    
    submit_btn.click(chatbot_response, inputs=[user_input, chat_state], outputs=[chatbot, chat_state])
    clear_btn.click(lambda: ([], []), inputs=[], outputs=[chatbot, chat_state])

# Launch the chatbot
demo.launch()