app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# Load the model and tokenizer from Hugging Face
model_name = "fahadMizan/chatbot"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Define the chatbot function
def chatbot(input_text):
    inputs = tokenizer(input_text, return_tensors="pt")
    outputs = model.generate(inputs["input_ids"], max_length=100)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

# Create the Gradio interface
iface = gr.Interface(fn=chatbot, 
                     inputs="text", 
                     outputs="text", 
                     title="Fahad Chatbot",
                     description="A chatbot using the 'fahadMizan/chatbot' model from Hugging Face.")

# Launch the app
if __name__ == "__main__":
    iface.launch()