Update app.py

app.py

@@ -4,9 +4,11 @@ from PIL import Image
 import io
 import gradio as gr
 import requests
+import base64
+from openai import OpenAI
 
-# Load OpenAI API key from environment variable (set this in your Hugging Face Space Secrets or environment)
-openai.api_key = os.getenv("OPENAI_API_KEY")  # Replace with your API key if not using secrets
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+client = OpenAI(api_key=OPENAI_API_KEY)
 
 # Define the inference function to use OpenAI's DALL·E model or another image model
 def inference(input_image: Image.Image) -> Image.Image:
@@ -25,20 +27,23 @@ def inference(input_image: Image.Image) -> Image.Image:
     img_byte_arr = img_byte_arr.getvalue()
 
     try:
-        # Send the image to OpenAI's API to edit/enhance the image with a prompt
-        response = openai.Image.create_edit(
-            image=img_byte_arr,
-            mask=None,  # In case you have a mask image, otherwise set this to None
-            prompt="Enhance this handwritten sketch to well-structured and computer-built design sketch.",
-            n=1,  # Generate 1 result
-            size="1024x1024"  # Specify the output image size
+        prompt = """
+        Enhance this handwritten sketch to well-structured and computer-built design sketch.
+        """
+        
+        result = client.images.edit(
+            model="gpt-image-1",
+            image=[
+                img_byte_arr,
+            ],
+            prompt=prompt
         )
-
-        # Fetch the enhanced image URL from the response
-        enhanced_image_url = response['data'][0]['url']
+        
+        image_base64 = result.data[0].b64_json
+        image_bytes = base64.b64decode(image_base64)
 
         # Download the image from the URL and open it with PIL
-        enhanced_image = Image.open(io.BytesIO(requests.get(enhanced_image_url).content))
+        enhanced_image = Image.open(image_bytes)
 
         return enhanced_image