app.py

import gradio as gr
import torch
import os
import sys
from huggingface_hub import login
from diffusers import StableDiffusionXLPipeline
from PIL import Image

# Force CPU usage if needed
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"Using device: {device}")

# More details about the environment
print(f"Gradio version: {gr.__version__}")
print(f"Python version: {sys.version}")

# Hugging Face API token'ı - önce environment variable olarak ara, 
# sonra Hugging Face Secrets sisteminde ara
hf_token = os.environ.get("HUGGINGFACE_TOKEN")
if hf_token:
    print("Found HUGGINGFACE_TOKEN in environment variables")
    # Token ile giriş yap
    login(token=hf_token)
    print("Logged in with Hugging Face token")
else:
    print("HUGGINGFACE_TOKEN not found in environment variables")

# Global model variable
pipe = None

def load_model():
    global pipe
    try:
        print("Loading SDXL pipeline with 3D render LoRA...")
        
        # Load SDXL base model
        pipe = StableDiffusionXLPipeline.from_pretrained(
            "stabilityai/stable-diffusion-xl-base-1.0",
            torch_dtype=torch.float16 if device == "cuda" else torch.float32,
            use_safetensors=True
        ).to(device)
        
        # Load the 3D render LoRA
        pipe.load_lora_weights("goofyai/3d_render_style_xl")
        
        print("Model loaded successfully!")
        return True
        
    except Exception as e:
        print(f"Error loading model: {str(e)}")
        return False

def generate_3d_icon(prompt):
    global pipe
    try:
        print(f"Generating 3D icon with prompt: {prompt}")
        
        if pipe is None:
            print("Model not loaded, attempting to load...")
            if not load_model():
                raise Exception("Failed to load model")
        
        # Enhance prompt for 3D game icon style
        enhanced_prompt = f"3d style, 3d render, {prompt}, game icon, clean background, vibrant colors, high quality"
        
        # Generate image
        with torch.no_grad():
            image = pipe(
                enhanced_prompt,
                num_inference_steps=30,
                guidance_scale=7.5,
                height=512,
                width=512
            ).images[0]
        
        print("Image generated successfully")
        return image
        
    except Exception as e:
        print(f"Error generating icon: {str(e)}")
        
        # Return error image with red background
        image = Image.new('RGB', (512, 512), color='red')
        from PIL import ImageDraw
        draw = ImageDraw.Draw(image)
        draw.text((200, 250), "Generation Error", fill=(255, 255, 255))
        return image

# Create Gradio interface
def create_interface():
    # Try to load model at startup
    load_model()
    
    interface = gr.Interface(
        fn=generate_3d_icon,
        inputs=[
            gr.Textbox(label="Prompt", placeholder="Describe your game icon", value="galatasaray")
        ],
        outputs=gr.Image(type="pil", label="Generated Game Icon"),
        title="3D Game Icon Generator",
        description="Generate 3D-style game icons using AI"
    )
    
    return interface

# Launch the interface
if __name__ == "__main__":
    try:
        interface = create_interface()
        print("Launching interface...")
        interface.launch(
            share=False,
            server_name="0.0.0.0",
            server_port=7860,
            show_error=True
        )
    except Exception as e:
        print(f"Error launching interface: {str(e)}")