Upload app.py

app.py

@@ -1,13 +1,13 @@
 import gradio as gr
 import requests
 import os
-
+from PIL import Image
+from io import BytesIO
 api_key = os.getenv("HF_API_KEY")
-# Define the Hugging Face API endpoint and your API key
+
 api_url = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
 headers = {"Authorization": f"Bearer {api_key}"}
 
-# Define the inference function using the Hugging Face API
 def generate_image(prompt):
     payload = {
         "inputs": prompt
@@ -17,17 +17,18 @@ def generate_image(prompt):
     if response.status_code == 200:
         # If the response is successful, return the image
         image = response.content
-        return image
+        return Image.open(BytesIO(response.content))
     else:
         print(response.text)
         return "Error: " + response.text
-# Create the Gradio interface
+
 iface = gr.Interface(fn=generate_image, 
                      inputs=gr.Textbox(label="Enter your prompt", placeholder="Type your prompt here..."), 
                      outputs="image", 
-                     live=False,  # live=False ensures the image is generated only after clicking the button
+                     live=False,  
+                     flagging_mode="never",
                      title="Stable Diffusion Image Generator",
-                     description="Generate images using the Stable Diffusion XL model from Hugging Face API.")
+                     description="Using State of the Art Stable Diffusion model")
+
 
-# Launch the Gradio app
 iface.launch()