app.py

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

# Load the model and tokenizer
model_name = "google/gemma-2b-it"
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, num_return_sequences=1)
    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="AI Chatbot",
    description="A chatbot using the google/gemma-2b-it model."
)

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