gradio_app.py

import gradio as gr
from transformers import pipeline

# Step 1: Load the pre-trained model
# You can choose any suitable conversational model from the Hugging Face Model Hub
chatbot = pipeline("conversational", model="EleutherAI/gpt-neo-2.7B")

# Step 2: Define the function that will process user input and return the model's response
def respond(input_text):
    conversation = chatbot([input_text])
    return conversation[0]["generated_text"]

# Step 3: Create a Gradio interface
# This interface will take text input from the user and display the chatbot's response
iface = gr.Interface(
    fn=respond,  # The function to call when the user submits input
    inputs="text",  # The type of input (text)
    outputs="text",  # The type of output (text)
    title="HugChat - Your AI Chatbot",  # The title of your chatbot
    description="Chat with an AI-powered bot based on a pre-trained model."  # A short description
)



# Step 4: Launch the interface
if __name__ == "__main__":
    iface.launch()