Create app.py

app.py

@@ -0,0 +1,38 @@
+import gradio as gr
+import requests
+import os
+from PIL import Image
+import io
+
+# Only needed if using Inference API
+HF_API_KEY = os.getenv("HF_API_KEY")  # Set in Space secrets if using API
+API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
+
+def generate_image_api(prompt, negative_prompt, width, height, num_inference_steps, guidance_scale, seed, num_images):
+    """Generate using Hugging Face Inference API (requires API key for heavy use)"""
+    headers = {"Authorization": f"Bearer {HF_API_KEY}"} if HF_API_KEY else {}
+    
+    images = []
+    for i in range(num_images):
+        payload = {
+            "inputs": prompt,
+            "parameters": {
+                "negative_prompt": negative_prompt,
+                "width": width,
+                "height": height,
+                "num_inference_steps": num_inference_steps,
+                "guidance_scale": guidance_scale,
+                "seed": seed if seed != -1 else None
+            }
+        }
+        
+        response = requests.post(API_URL, headers=headers, json=payload)
+        if response.status_code == 200:
+            image = Image.open(io.BytesIO(response.content))
+            images.append(image)
+        else:
+            raise gr.Error(f"API Error: {response.text}")
+    
+    return images
+
+# Rest of the Gradio interface code remains the same...