Update app.py

app.py

@@ -5,47 +5,37 @@ import base64
 from io import BytesIO
 
 def query_hf_image_generation(api_key, prompt):
-    API_URL = f"https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
+    API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
     headers = {
         "Authorization": f"Bearer {api_key}",
         "Content-Type": "application/json"
     }
-    data = {
-        "inputs": prompt
-    }
+    data = {"inputs": prompt}
 
-    # Make the request
     response = requests.post(API_URL, headers=headers, json=data)
 
-    # Check if the response was successful
     if response.status_code != 200:
-        return f"Error: Received status code {response.status_code} with message: {response.text}"
+        return f"Error: Received HTTP {response.status_code} - {response.text}"
 
-    # Try parsing JSON response
     try:
         result = response.json()
-    except ValueError as e:
-        return f"Error decoding JSON: {e}"
-
-    # Debug output to diagnose the structure of the returned 'result'
-    print("DEBUG:", result)
+    except ValueError:
+        return f"Error decoding JSON: Unexpected response format {response.text}"
 
-    # Check if the API response contains an error message.
     if 'error' in result:
         return f"Error: {result['error']}"
 
-    # Assuming the API returns an image in base64 format.
     if 'data' in result:
         try:
-            base64_image = result['data'][0]
-            base64_data = base64_image.split(',')[1] if ',' in base64_image else base64_image
-            image_bytes = base64.b64decode(base64_data)
-            image = Image.open(BytesIO(image_bytes))
+            base64_string = result['data'][0]
+            base64_data = base64_string.split(",")[1] if "," in base64_string else base64_string
+            image_data = base64.b64decode(base64_data)
+            image = Image.open(BytesIO(image_data))
             return image
         except Exception as e:
             return f"Error processing image data: {e}"
     else:
-        return "Error: 'data' not found in response."
+        return "Error: Missing 'data' in the response."
 
 iface = gr.Interface(
     fn=query_hf_image_generation,
@@ -58,4 +48,4 @@ iface = gr.Interface(
     description="Enter your API Key and a prompt to generate an image using the Stable Diffusion XL model from Hugging Face."
 )
 
-iface.launch()
+iface.launch(share=True)