app.py

import gradio as gr
from transformers import pipeline

# Install required packages
import os
os.system("pip install -r requirements.txt")

# Load the pipeline for text generation
pipe = pipeline(
    "text-generation",
    model="Ar4ikov/gpt2-650k-stable-diffusion-prompt-generator",
    tokenizer="gpt2"
)

# Function to generate text based on input prompt
def generate_text(prompt):
    return pipe(prompt, max_length=77)[0]["generated_text"]

# Create a Gradio interface
iface = gr.Interface(
    fn=generate_text,
    inputs=gr.Textbox(lines=5, label="Prompt"),
    outputs=gr.Textbox(label="Output", show_copy_button=True),
    title="<span style='background-image: linear-gradient(to right, #ff7e5f, #feb47b, #ffdb93, #fffbac); -webkit-background-clip: text; -webkit-text-fill-color: transparent;'><center>AI Art Prompt Generator</center></span>",
    description="Art Prompt Generator is a user-friendly interface designed to optimize input for AI Art Generator or Creator. For faster generation speeds, it's recommended to load the model locally with GPUs, as the online demo at Hugging Face Spaces utilizes CPU, resulting in slower processing times.",
    api_name="predict"
)

# Launch the interface
iface.launch(show_api=True)