Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import requests
-import base64
 from PIL import Image
+import base64
 from io import BytesIO
 
 def query_hf_image_generation(api_key, prompt):
@@ -19,20 +19,21 @@ def query_hf_image_generation(api_key, prompt):
     
     # Check if the API response contains an error.
     if 'error' in result:
-        return f"Error: {result['error']}", None
+        return "Error: " + result['error'], None
 
     # Assuming the API returns an image in base64 format.
-    image_data = result['data'][0]  # You might need to adjust this path according to the actual API response
-    image = Image.open(BytesIO(base64.b64decode(image_data)))
+    image_data = result['data'][0]  # Adjust this according to your specific API response structure
+    image_bytes = base64.b64decode(image_data.split(",")[1])
+    image = Image.open(BytesIO(image_bytes))
     return image
 
 iface = gr.Interface(
     fn=query_hf_image_generation,
     inputs=[
         gr.Textbox(label="Hugging Face API Key", placeholder="Enter your Hugging Face API Key here..."),
-        gr.Textbox(lines=2, placeholder="Enter your prompt here...", label="Prompt"),
+        gr.Textbox(lines=2, placeholder="Enter your prompt here...", label="Prompt")
     ],
-    outputs=gr.outputs.Image(label="Generated Image"),
+    outputs=gr.Image(label="Generated Image"),
     title="Stable Diffusion XL Image Generator",
     description="Enter your API Key and a prompt to generate an image using the Stable Diffusion XL model from Hugging Face."
 )