Replace placeholder demo with working SD v1.5 Gradio app

app.py

@@ -1,62 +1,30 @@
-import torch
-from diffusers import StableDiffusionPipeline
 import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch, os
 
-# Pick the fastest device available
-device = (
-    "mps" if torch.backends.mps.is_available()
-    else "cuda" if torch.cuda.is_available()
-    else "cpu"
-)
-
-# Load the model (you can remove safety_checker=None for public deploys)
-model_id = "runwayml/stable-diffusion-v1-5"
+device = "mps" if torch.backends.mps.is_available() else "cpu"
 pipe = StableDiffusionPipeline.from_pretrained(
-    model_id,
-    torch_dtype=torch.float16,
+    "runwayml/stable-diffusion-v1-5",
     safety_checker=None
 ).to(device)
 
-def generate(prompt: str, steps: int, guidance: float, seed: float):
-    """
-    Generate one or more images from a text prompt.
-    """
-    # If seed > 0, use it; else let Diffusers pick a random seed.
-    generator = (
-        torch.Generator(device=device).manual_seed(int(seed))
-        if seed and seed > 0
-        else None
-    )
-    output = pipe(
-        prompt,
-        num_inference_steps=steps,
-        guidance_scale=guidance,
-        generator=generator
-    )
-    # returns a list of PIL images
-    return output.images
-
-# Build the Gradio UI
-demo = gr.Blocks()
+def generate(prompt, steps, guidance, seed):
+    generator = torch.Generator(device).manual_seed(int(seed)) if seed else None
+    img = pipe(prompt, num_inference_steps=int(steps),
+               guidance_scale=float(guidance),
+               generator=generator).images[0]
+    return img
 
-with demo:
+with gr.Blocks() as demo:
     gr.Markdown("# Stable Diffusion Text→Image Generation Demo")
-    with gr.Row():
-        with gr.Column():
-            prompt = gr.Textbox(label="Prompt", placeholder="e.g. ‘A serene forest at dawn’")
-            steps  = gr.Slider(1, 100, value=50, step=1, label="Inference Steps")
-            guidance = gr.Slider(1, 15, value=7.5, step=0.1, label="Guidance Scale")
-            seed   = gr.Number(value=0, label="Random Seed (0 = random)")
-            btn    = gr.Button("Generate")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated Images", columns=2, height="auto")
+    prompt = gr.Textbox(label="Prompt", value="A serene forest at dawn")
+    steps = gr.Slider(1, 100, value=30, label="Inference Steps")
+    cfg   = gr.Slider(1, 15, value=7.5, label="Guidance Scale")
+    seed  = gr.Number(value=0, label="Random Seed (0 = random)")
+    btn   = gr.Button("Generate")
+    gallery = gr.Gallery(label="Generated Images", columns=1, height="auto")
 
-    # wire up the button
-    btn.click(
-        fn=generate,
-        inputs=[prompt, steps, guidance, seed],
-        outputs=gallery,
-    )
+    btn.click(generate, [prompt, steps, cfg, seed], gallery)
 
 if __name__ == "__main__":
     demo.launch()