Update app.py

app.py

@@ -39,29 +39,43 @@ def generate_images(
     seed: int,
     num_images: int,
 ):
-    # Seed handling (maps to KSampler seed/randomize)
+    run_device = "cuda" if torch.cuda.is_available() else "cpu"
+    pipe.to(run_device)
+
+    num_images = int(num_images)
+    width = int(width)
+    height = int(height)
+    steps = int(steps)
+
+    images = []
+
+    # Base seed logic; if seed < 0, random base, else deterministic series
     if seed < 0:
-        generator = torch.Generator(device=device)
-        seed_value = torch.randint(0, 2**63 - 1, (1,), device=device).item()
-        generator = generator.manual_seed(seed_value)
+        base_seed = torch.randint(0, 2**63 - 1, (1,), device=run_device).item()
     else:
-        generator = torch.Generator(device=device).manual_seed(seed)
-
-    images = pipe(
-        prompt=positive,
-        negative_prompt=negative or None,
-        width=width,
-        height=height,
-        num_inference_steps=steps,
-        guidance_scale=cfg,
-        num_images_per_prompt=num_images,
-        generator=generator,
-    ).images
-
-    # Return list of PIL images (maps to SaveImage → output images)
+        base_seed = int(seed)
+
+    for i in range(num_images):
+        this_seed = base_seed if seed < 0 else base_seed + i
+        generator = torch.Generator(device=run_device).manual_seed(this_seed)
+
+        out = pipe(
+            prompt=positive,
+            negative_prompt=negative or None,
+            width=width,
+            height=height,
+            num_inference_steps=steps,
+            guidance_scale=float(cfg),
+            num_images_per_prompt=1,   # always 1 for AOTI safety
+            generator=generator,
+        ).images[0]
+
+        images.append(out)
+
     return images
 
 
+
 # ---------------------------------------------------------------------
 # Gradio UI (inputs correspond to Comfy node widgets_values)
 # ---------------------------------------------------------------------
@@ -72,12 +86,12 @@ with gr.Blocks() as demo:
         with gr.Column():
             positive = gr.Textbox(
                 label="Positive Prompt",
-                value="Positive Prompts",  # from CLIP Text Encode (Positive Prompt)
+                value="masterpiece, best quality, extremely detailed, high resolution.",  # from CLIP Text Encode (Positive Prompt)
                 lines=5,
             )
             negative = gr.Textbox(
                 label="Negative Prompt",
-                value="Negative Prompts",  # from CLIP Text Encode (Negative Prompt)
+                value="watermark, blurry, ugly, bad anatomy",  # from CLIP Text Encode (Negative Prompt)
                 lines=4,
             )
 
@@ -131,8 +145,12 @@ with gr.Blocks() as demo:
                 show_label=True,
                 columns=3,
                 height=768,
+                object_fit="contain",  # keep full image visible in cell
+                preview=False,         # do not start in zoomed preview mode
+                allow_preview=True,    # still allow zoom when clicked
             )
 
+
     run_btn.click(
         fn=generate_images,
         inputs=[positive, negative, width, height, steps, cfg, seed, num_images],