import gradio as gr

# Create a pipeline
gpt2 = pipeline('text-generation', model=model, tokenizer=tokenizer)

def predict(prompt):
    generated_text = gpt2(prompt, max_length=100)[0]['generated_text']  
    return generated_text

title = "GPT-Guide: London"
description = """

<img src="https://drive.google.com/uc?export=view&id=1GTsFsjgDFjcKVNgQ4I1C4QCvfhGDUs53">
This model is trained to provide recommendations for exploring London. Ask it about places to visit, eat, and experience in London!
"""

article = "Want more tips? Check out [Visit London](https://www.visitlondon.com/) for comprehensive guides and ideas."

gr.Interface(
    fn=predict,
    inputs="textbox",
    outputs="text",
    title=title,
    description=description,
    article=article,
    examples=[["Can you recommend an activity in London?"],["What are the best museums in London?"], ["Where can I find the best food in London?"],["What is the significance of pubs in London?"]],
).launch(share=True)