app.py

import os
import random
import gradio as gr
import torch
from torchvision import transforms
from PIL import Image
import numpy as np
from diffusers import StableDiffusionPipeline, EulerAncestralDiscreteScheduler
from io import BytesIO

# Set up model cache directory
MODEL_CACHE = "model_cache"
os.makedirs(MODEL_CACHE, exist_ok=True)

# Initialize model pipeline
def get_pipeline():
    model_id = "OFA-Sys/small-stable-diffusion-v0"
    scheduler = EulerAncestralDiscreteScheduler.from_pretrained(
        model_id, 
        subfolder="scheduler",
        cache_dir=MODEL_CACHE
    )
    
    return StableDiffusionPipeline.from_pretrained(
        model_id,
        scheduler=scheduler,
        torch_dtype=torch.float32,
        cache_dir=MODEL_CACHE,
        safety_checker=None
    ).to("cpu")

# Load model once at startup
pipeline = get_pipeline()

def generate_image(
    prompt: str,
    width: int,
    height: int,
    seed: int,
    randomize_seed: bool,
    guidance_scale: float,
    num_inference_steps: int
):
    # Handle seed randomization
    if randomize_seed:
        seed = random.randint(0, 2147483647)
    generator = torch.Generator(device="cpu").manual_seed(seed)
    
    # Generate image
    image = pipeline(
        prompt,
        width=width,
        height=height,
        guidance_scale=guidance_scale,
        num_inference_steps=num_inference_steps,
        generator=generator
    ).images[0]
    
    return image, seed

# Style presets
STYLE_PRESETS = {
    "Realistic": "photorealistic, 8k, detailed, sharp focus",
    "Anime": "anime style, vibrant colors, cel shading",
    "Oil Painting": "oil painting, brush strokes, textured",
    "Cyberpunk": "neon lights, cyberpunk, futuristic, rain",
    "Minimalist": "minimalist, simple shapes, flat colors"
}

def apply_style(prompt, style_name):
    return f"{STYLE_PRESETS[style_name]}, {prompt}"

# UI Components
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # ⚡ FLUX Turbo Generator
    **CPU-Optimized Image Generation** · No APIs · No Limits
    """)
    
    with gr.Row():
        with gr.Column(scale=3):
            prompt = gr.Textbox(
                label="Prompt",
                placeholder="Describe what you want to create...",
                lines=3
            )
            style = gr.Dropdown(
                label="Style Preset",
                choices=list(STYLE_PRESETS.keys()),
                value="Realistic"
            )
            generate_btn = gr.Button("Generate", variant="primary")
            
            with gr.Accordion("Advanced Settings", open=False):
                with gr.Row():
                    width = gr.Slider(384, 768, value=512, step=64, label="Width")
                    height = gr.Slider(384, 768, value=512, step=64, label="Height")
                guidance = gr.Slider(1.0, 20.0, value=7.5, step=0.5, label="Creativity")
                steps = gr.Slider(5, 50, value=20, step=5, label="Generation Steps")
                
                with gr.Row():
                    seed = gr.Number(label="Seed", value=0)
                    random_seed = gr.Checkbox(label="Random Seed", value=True)
        
        with gr.Column(scale=2):
            output_image = gr.Image(label="Generated Image", type="pil")
            used_seed = gr.Textbox(label="Used Seed", interactive=False)
            gr.Markdown("**Tip:** Use specific descriptions for better results")
    
    # Style application
    style.change(
        fn=apply_style,
        inputs=[prompt, style],
        outputs=prompt
    )
    
    # Generation handler
    generate_btn.click(
        fn=generate_image,
        inputs=[prompt, width, height, seed, random_seed, guidance, steps],
        outputs=[output_image, used_seed]
    )
    
    # Examples
    gr.Examples(
        examples=[
            ["majestic mountain landscape at sunset, snow-capped peaks", "Realistic", 512, 512],
            ["cyberpunk city street at night, neon signs, rain puddles", "Cyberpunk", 512, 512],
            ["cute anime cat warrior wearing armor, fantasy setting", "Anime", 512, 512]
        ],
        inputs=[prompt, style, width, height],
        label="Example Prompts"
    )

# Launch settings
if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=int(os.getenv("PORT", 7860)),
        enable_queue=True
    )