app.py

import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the GPT-2 model and tokenizer
model_name = "gpt2"
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)

# Define the sentence completion function
def complete_sentence(sentence):
    input_ids = tokenizer.encode(sentence, return_tensors="pt")
    output = model.generate(input_ids, max_length=50, num_return_sequences=1)
    completed_sentence = tokenizer.decode(output[0], skip_special_tokens=True)
    return completed_sentence

# Create the Gradio interface (adjusted for Gradio 4.5.0)
iface = gr.Interface(
    fn=complete_sentence,
    inputs=gr.inputs.Textbox(placeholder="Enter a sentence here..."),
    outputs=gr.outputs.Textbox(),
    title="Sentence Completion",
    description="Enter a sentence to complete. The model will generate a continuation."
)

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