import gradio as gr
from transformers import pipeline

# Pretrained model load karo (direct original repo se)
model_name = "ByteDance-Seed/UI-TARS-1.5-7B"  # ← Replace karo actual model path se
generator = pipeline("text-generation", model=model_name)

# Text generate karne ka function
def generate_text(prompt):
    result = generator(prompt, max_new_tokens=100, do_sample=True)
    return result[0]["generated_text"]

# Gradio Interface
gr.Interface(
    fn=generate_text,
    inputs=gr.Textbox(lines=2, placeholder="Enter your prompt..."),
    outputs="text",
    title="UITARS 1.5 Text Generator"
).launch()