Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| from diffusers import DDPMPipeline | |
| import torch | |
| from PIL import Image, ImageDraw | |
| import os | |
| # --- CONFIGURATION --- | |
| MODEL_ID = "FlameF0X/Stable-Lime-v1.1" | |
| DEVICE = "cuda" if torch.cuda.is_available() else "cpu" | |
| print(f"🍋 Initializing Stable-Lime Protocol on {DEVICE}...") | |
| # --- LOAD MODEL --- | |
| pipeline = None | |
| try: | |
| # Load the pipeline directly from your Hub repo | |
| pipeline = DDPMPipeline.from_pretrained(MODEL_ID) | |
| pipeline.to(DEVICE) | |
| print("✅ Lime Status: ONLINE") | |
| except Exception as e: | |
| print(f"❌ CRITICAL FAILURE: Could not load the Lime. Error: {e}") | |
| pipeline = None | |
| def create_error_image(message): | |
| """Generates a fallback image containing the error message to debug API issues.""" | |
| img = Image.new('RGB', (512, 512), color=(20, 0, 0)) | |
| d = ImageDraw.Draw(img) | |
| try: | |
| # Basic text drawing if font loading fails | |
| d.text((20, 250), f"SYSTEM FAILURE:\n{message}", fill=(255, 50, 50)) | |
| except: | |
| pass | |
| return img | |
| def generate_lime(): | |
| """ | |
| The core inference function. | |
| Summons a lime from the latent void. | |
| """ | |
| if pipeline is None: | |
| # Return a generated error image so the frontend has something to show | |
| # instead of a broken link/null response | |
| return create_error_image("MODEL_LOAD_FAIL") | |
| print("🍋 Generating new specimen...") | |
| try: | |
| # Reduced steps slightly for better responsiveness if on CPU | |
| steps = 50 if DEVICE == "cpu" else 100 | |
| image = pipeline(num_inference_steps=steps).images[0] | |
| return image | |
| except Exception as e: | |
| print(f"Generation Error: {e}") | |
| return create_error_image("INFERENCE_ERR") | |
| # --- CUSTOM CSS --- | |
| custom_css = """ | |
| body { background-color: #0d0d0d; color: #e0e0e0; font-family: 'Courier New', monospace; } | |
| .gradio-container { max-width: 700px !important; margin-top: 40px !important; } | |
| h1 { color: #ff5722; text-align: center; font-weight: bold; letter-spacing: 2px; } | |
| .lime-btn { background-color: #32CD32 !important; color: #000 !important; font-weight: bold; border: 1px solid #32CD32; } | |
| .lime-btn:hover { box-shadow: 0 0 15px #32CD32; } | |
| .footer { text-align: center; margin-top: 20px; font-size: 0.8em; color: #666; } | |
| """ | |
| # --- THE UI --- | |
| with gr.Blocks(css=custom_css, title="Stable-Lime v1.1") as demo: | |
| gr.HTML("<h1>> STABLE-LIME v1.1 <</h1>") | |
| with gr.Row(): | |
| with gr.Column(): | |
| # KEY CHANGE: type="filepath" ensures the API receives a string path | |
| # instead of a complex object or base64 string. | |
| lime_output = gr.Image( | |
| label="Generated Artifact", | |
| type="filepath", | |
| elem_id="lime-out" | |
| ) | |
| generate_btn = gr.Button("INITIALIZE GENERATION", elem_classes="lime-btn") | |
| gr.HTML("<div class='footer'>Running on Unconditional U-Net Architecture | Powered by Limes</div>") | |
| # Wire up the button | |
| generate_btn.click( | |
| fn=generate_lime, | |
| inputs=None, | |
| outputs=[lime_output] | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| demo.launch() |