Update app.py

app.py

@@ -1,142 +1,38 @@
-import gradio as gr
-import spaces
-import numpy as np
-import random
 import torch
+import gradio as gr
 from diffusers import StableDiffusion3Pipeline
 
-# Set device and data type
-device = "cuda" if torch.cuda.is_available() else "cpu"
-dtype = torch.float16
-
-# Load the Stable Diffusion model
-repo = "stabilityai/stable-diffusion-3-medium-diffusers"
-pipe = StableDiffusion3Pipeline.from_pretrained(repo, torch_dtype=dtype).to(device)
+def image_generator(prompt):
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    pipeline = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", 
+                                                         torch_dtype=torch.float16 if device == "cuda" else torch.float32,
+                                                         text_encoder_3=None,
+                                                         tokenizer_3 = None)
+    #pipeline.enable_model_cpu_offload()
+    pipeline.to(device)
 
-# Constants
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1344
+    image = pipeline(
+        prompt=prompt,
+        negative_prompt="blurred, ugly, watermark, low, resolution, blurry",
+        num_inference_steps=40,
+        height=1024,
+        width=1024,
+        guidance_scale=9.0
+    ).images[0]
 
-@spaces.GPU
-def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, progress=gr.Progress(track_tqdm=True)):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-        
-    generator = torch.Generator().manual_seed(seed)
-    
-    try:
-        image = pipe(
-            prompt=prompt, 
-            negative_prompt=negative_prompt,
-            guidance_scale=guidance_scale, 
-            num_inference_steps=num_inference_steps, 
-            width=width, 
-            height=height,
-            generator=generator
-        ).images[0]
-        
-        return image, seed
-    except Exception as e:
-        return str(e), seed  # Return error message if any
+    #image.show()
+    return image
 
-# Example prompts
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
+#image_generator("A magical cat doing spell")
 
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 580px;
-}
-"""
+interface = gr.Interface(
+    fn=image_generator, 
+    inputs=gr.Textbox(lines=2, placeholder = "Enter your prompt..."), 
+    outputs=gr.Image(type = "pil"),
+    title = "Image Generator App",
+    description = "This is a simple image generator app using HuggingFace's Stable Diffusion 3 model.")
 
-# Create Gradio interface
-with gr.Blocks(css=css) as demo:
-    
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""
-        # Demo [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)
-        Learn more about the [Stable Diffusion 3 series](https://stability.ai/news/stable-diffusion-3). Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), [Stable Assistant](https://stability.ai/stable-assistant), or on Discord via [Stable Artisan](https://stability.ai/stable-artisan). Run locally with [ComfyUI](https://github.com/comfyanonymous/ComfyUI) or [diffusers](https://github.com/huggingface/diffusers)
-        """)
-        
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            
-            run_button = gr.Button("Run", scale=0)
-        
-        result = gr.Image(label="Result", show_label=False)
+interface.launch()
 
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-            )
-            
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
-            with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=64,
-                    value=1024,
-                )
-                
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=64,
-                    value=1024,
-                )
-            
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=5.0,
-                )
-                
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=28,
-                )
-        
-        gr.Examples(
-            examples=examples,
-            inputs=[prompt]
-        )
-    
-    gr.on(
-        triggers=[run_button.click, prompt.submit, negative_prompt.submit],
-        fn=infer,
-        inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs=[result, seed]
-    )
 
-# Launch the app
-demo.launch(timeout=10)  # Increase timeout if needed
+print(interface)