import gradio as gr
from transformers import pipeline

# Load a text-generation model.
# For demonstration, we're using GPT-2.
# For an adult-novel style, consider a fine-tuned model or adjust parameters.
generator = pipeline("text-generation", model="gpt2")

def generate_text(prompt, max_length):
    try:
        # Generate text based on the prompt.
        results = generator(prompt, max_length=max_length, do_sample=True, temperature=0.8)
        return results[0]["generated_text"]
    except Exception as e:
        # Log the exception details for debugging
        print("Error during text generation:", e)
        # Return an error message for the user
        return "An error occurred while generating text. Please try again with a shorter prompt or lower max length."

# Create the Gradio interface.
iface = gr.Interface(
    fn=generate_text,
    inputs=[
        gr.Textbox(lines=5, label="Enter your prompt here..."),
        gr.Slider(minimum=50, maximum=500, step=10, value=200, label="Max Length")
    ],
    outputs="text",
    title="Adult Novel Generator",
    description=(
        "This application generates text in the style of an adult novel. "
        "Provide a prompt to start the narrative and see the generated continuation."
    )
)

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