app.py

import gradio as gr
from transformers import BlenderbotForConditionalGeneration, BlenderbotTokenizer

# Load the pre-trained Blenderbot model and tokenizer
model = BlenderbotForConditionalGeneration.from_pretrained("facebook/blenderbot-400M-distill")
tokenizer = BlenderbotTokenizer.from_pretrained("facebook/blenderbot-400M-distill")

# Define the chatbot function
def chatbot(input_text):
    input_ids = tokenizer.encode(input_text, return_tensors="pt")
    bot_input_ids = input_ids
    chatbot_response = model.generate(bot_input_ids, max_length=1000, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
    response_text = tokenizer.decode(chatbot_response[0], skip_special_tokens=True)
    return response_text

# Create the Gradio interface
iface = gr.Interface(fn=chatbot, 
                     inputs="text",
                     outputs="text",
                     title="Chatbot using Hugging Face Transformers",
                     description="Ask me anything!")
iface.launch(share=True)