Create app.py

app.py

@@ -0,0 +1,45 @@
+import openai
+import os
+from PIL import Image
+import io
+import requests
+import gradio as gr
+
+# Load OpenAI API key (ensure it's securely set in your environment variables or Hugging Face secrets)
+openai.api_key = os.getenv("OPENAI_API_KEY")  # Replace with your API key if not using secrets
+
+# Define the inference function to use OpenAI's gpt-image-1 model
+def inference(input_image: Image.Image) -> Image.Image:
+    """
+    Enhances the input handwritten sketch to a well-structured design using OpenAI's API.
+    
+    Args:
+        input_image: The input PIL Image (handwritten sketch).
+        
+    Returns:
+        The output PIL Image (enhanced design).
+    """
+    # Convert the PIL image to a byte array (required by the OpenAI API)
+    img_byte_arr = io.BytesIO()
+    input_image.save(img_byte_arr, format="PNG")
+    img_byte_arr = img_byte_arr.getvalue()
+
+    # Send the image to OpenAI's API with the prompt
+    try:
+        response = openai.Image.create(
+            prompt="Enhance this handwritten sketch to well-structured and computer-built design sketch.",
+            images=[img_byte_arr],  # Attach the image
+            n=1,  # Generate 1 result
+            size="1024x1024"  # Specify the output image size
+        )
+        
+        # Assuming the response contains a URL to the generated image (depending on OpenAI's API)
+        enhanced_image_url = response['data'][0]['url']
+        
+        # Fetch the enhanced image from the URL
+        enhanced_image = Image.open(io.BytesIO(requests.get(enhanced_image_url).content))
+        return enhanced_image
+
+    except Exception as e:
+        print(f"Error during image enhancement: {e}")
+        return input_image  # Return the original image if there's an error