app.py

import gradio as gr
from transformers import pipeline

# Initialize the model pipeline
pipe = pipeline("text-generation", model="unsloth/gemma-2b-it")

# Define a function to handle user input and generate model output
def generate_response(user_input):
    # Create a conversation format if necessary (based on the input model)
    messages = [{"role": "user", "content": user_input}]
    
    # Generate response using the pipeline
    result = pipe(messages)
    return result[0]['generated_text']  # Adjust based on the exact output format

# Create a Gradio interface for user input and model output
gr.Interface(fn=generate_response, inputs="text", outputs="text").launch()