Update app.py

app.py

@@ -1,9 +1,10 @@
 import gradio as gr
 from huggingface_hub import hf_hub_download
+from diffusers import StableDiffusionPipeline
+import torch
 import os
-import subprocess
-import sys
 
+print("Downloading model...")
 model_path = hf_hub_download(
     repo_id="calcuis/pony",
     filename="blackmagic-q4_k_m.gguf",
@@ -11,36 +12,34 @@ model_path = hf_hub_download(
 )
 print(f"Model ready at: {model_path}")
 
-def generate(prompt, negative_prompt="bad quality, blurry", steps=20):
-    try:
-        from diffusers import StableDiffusionPipeline
-        import torch
-
-        pipe = StableDiffusionPipeline.from_single_file(
-            model_path,
-            torch_dtype=torch.float32,
-        )
-        pipe.to("cpu")
-
-        image = pipe(
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            num_inference_steps=steps,
-        ).images[0]
-
-        return image
-
-    except Exception as e:
-        return f"Error: {str(e)}"
+print("Loading pipeline...")
+pipe = StableDiffusionPipeline.from_single_file(
+    model_path,
+    torch_dtype=torch.float32,
+)
+pipe.to("cpu")
+print("Pipeline ready!")
+
+def generate(prompt, negative_prompt="bad quality, blurry", steps=5):
+    print(f"Generating: {prompt}")
+    image = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        num_inference_steps=int(steps),
+        height=512,
+        width=512,
+    ).images[0]
+    print("Done!")
+    return image
 
 demo = gr.Interface(
     fn=generate,
     inputs=[
         gr.Textbox(label="Prompt", value="a cute cat sitting on a bench"),
         gr.Textbox(label="Negative Prompt", value="bad quality, blurry"),
-        gr.Slider(minimum=5, maximum=30, value=15, step=1, label="Steps (lower = faster)")
+        gr.Slider(minimum=1, maximum=30, value=5, step=1, label="Steps")
     ],
-    outputs=gr.Image(label="Generated Image"),
+    outputs=gr.Image(label="Generated Image", type="pil"),
     title="Pony Image Generator API"
 )