import gradio as gr
from diffusers import AutoPipelineForText2Image
import torch
import os

# Model configuration
MODEL_NAME = "katuni4ka/tiny-random-flex.2-preview"
CACHE_DIR = "./model_cache"

# Create cache directory
os.makedirs(CACHE_DIR, exist_ok=True)

# Load model with optimized settings
pipe = AutoPipelineForText2Image.from_pretrained(
    MODEL_NAME,
    torch_dtype=torch.float16,
    cache_dir=CACHE_DIR
).to("cuda" if torch.cuda.is_available() else "cpu")

# Aspect ratio presets
ASPECT_RATIOS = {
    "Square (1:1)": (512, 512),
    "Landscape (16:9)": (1024, 576),
    "Portrait (9:16)": (576, 1024),
    "A4 (3:4)": (864, 1152)
}

def generate_image(prompt, aspect_ratio, num_inference_steps=25, guidance_scale=4.5):
    """Generate image with optimized inference settings"""
    width, height = ASPECT_RATIOS[aspect_ratio]
    
    with torch.inference_mode():
        image = pipe(
            prompt=prompt,
            width=width,
            height=height,
            num_inference_steps=num_inference_steps,
            guidance_scale=guidance_scale
        ).images[0]
    
    return image

# UI Configuration
with gr.Blocks(theme="huggingface", analytics_enabled=False) as demo:
    gr.Markdown("""
    # Tiny Random Flex Text-to-Image Generator
    Create images from text prompts using the `katuni4ka/tiny-random-flex.2-preview` model
    
    💡 Tip: Try descriptive prompts like "A futuristic cityscape at sunset" or "Abstract watercolor patterns"
    """)
    
    with gr.Row():
        with gr.Column():
            prompt = gr.Textbox(
                label="Prompt",
                placeholder="Describe your image...",
                lines=3
            )
            aspect_ratio = gr.Dropdown(
                label="Aspect Ratio",
                choices=list(ASPECT_RATIOS.keys()),
                value="Square (1:1)"
            )
            generate_btn = gr.Button("🎨 Generate Image", variant="primary")
        
        with gr.Column():
            output_image = gr.Image(label="Generated Image", interactive=False)
    
    generate_btn.click(
        fn=generate_image,
        inputs=[prompt, aspect_ratio],
        outputs=output_image
    )
    
    gr.Examples(
        examples=[
            ["A vibrant neon cityscape at night", "Landscape (16:9)"],
            ["Abstract geometric patterns in pastel colors", "Square (1:1)"],
            ["Mystical forest with glowing plants", "Portrait (9:16)"]
        ],
        inputs=[prompt, aspect_ratio]
    )

if __name__ == "__main__":
    demo.launch()