Create app.py

app.py

@@ -0,0 +1,95 @@
+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline
+from PIL import Image
+
+# Tiny model that fits in free tier memory
+MODEL_NAME = "OFA-Sys/small-stable-diffusion-v0"
+
+# Load model (will cache after first run)
+@gr.cache()
+def load_model():
+    return StableDiffusionPipeline.from_pretrained(
+        MODEL_NAME,
+        torch_dtype=torch.float16,
+        safety_checker=None
+    ).to("cpu")
+
+def generate_character(description, seed=42):
+    try:
+        pipe = load_model()
+        
+        # Reduce memory usage
+        torch.manual_seed(seed)
+        with torch.inference_mode():
+            image = pipe(
+                prompt=f"pixel art character, {description}",
+                num_inference_steps=15,  # Fewer steps = less memory
+                guidance_scale=7.0,
+                width=256,  # Smaller resolution
+                height=256
+            ).images[0]
+        
+        return image
+    except Exception as e:
+        return f"Error: {str(e)}\nTry a simpler description or different words."
+
+# Create simple animation effect by generating variations
+def generate_animation(description, frames=3):
+    images = []
+    for i in range(frames):
+        img = generate_character(description, seed=i)
+        if isinstance(img, str):  # If error returned
+            return img
+        images.append(img)
+    
+    # Create simple animation (GIF)
+    images[0].save(
+        "animation.gif",
+        save_all=True,
+        append_images=images[1:],
+        duration=500,
+        loop=0
+    )
+    return "animation.gif"
+
+# Minimal interface
+with gr.Blocks(title="Tiny Character Animator") as demo:
+    gr.Markdown("""
+    # 🎮 Tiny Character Animator
+    *Free-tier optimized for Hugging Face Spaces*
+    """)
+    
+    with gr.Row():
+        desc = gr.Textbox(
+            label="Describe your character",
+            placeholder="e.g., 'blue robot with antennae'",
+            max_lines=2
+        )
+    
+    with gr.Row():
+        btn_still = gr.Button("Generate Still", variant="secondary")
+        btn_animate = gr.Button("Generate Animation", variant="primary")
+    
+    with gr.Row():
+        output_still = gr.Image(label="Character", shape=(256, 256))
+        output_anim = gr.Image(label="Animation", format="gif", visible=False)
+    
+    # Button actions
+    btn_still.click(
+        generate_character,
+        inputs=desc,
+        outputs=output_still
+    )
+    
+    btn_animate.click(
+        lambda: (gr.Image(visible=False), gr.Image(visible=True)),  # Toggle visibility
+        None,
+        [output_still, output_anim]
+    ).then(
+        generate_animation,
+        inputs=desc,
+        outputs=output_anim
+    )
+
+demo.launch(debug=False)