Update app.py

app.py

@@ -1,33 +1,39 @@
+import requests
 import gradio as gr
-from diffusers import StableDiffusionPipeline
-import torch
+from PIL import Image
+from io import BytesIO
 import os
-from huggingface_hub import login
 
-# Login using your Hugging Face token
-hf_token = os.getenv("HF_TOKEN")  # This should be set in your Hugging Face Space Secrets
-login(token=hf_token)
+# Replace with your NVIDIA API key
+API_KEY = os.getenv("NVIDIA_API_KEY")  # Ensure the key is set in Space secrets
+invoke_url = "https://ai.api.nvidia.com/v1/genai/stabilityai/sdxl-turbo"
 
-# Access the NVIDIA API key from the environment
-nvidia_api_key = os.getenv("NVIDIA_API_KEY")
+headers = {
+    "Authorization": f"Bearer {API_KEY}",
+    "Accept": "application/json",
+}
 
-# Load the model using the API key and move it to GPU
-def load_model():
-    model_id = "NVIDIA/sdxl-turbo"
-    pipe = StableDiffusionPipeline.from_pretrained(
-        model_id, 
-        torch_dtype=torch.float16, 
-        use_auth_token=nvidia_api_key  # Use the API key here
-    )
-    pipe = pipe.to("cuda")
-    return pipe
-
-pipe = load_model()
-
-# Function to generate a Kindle cover
 def generate_kindle_cover(prompt):
-    image = pipe(prompt).images[0]
-    return image
+    payload = {
+        "text_prompts": [{"text": prompt}],
+        "seed": 0,
+        "sampler": "K_EULER_ANCESTRAL",
+        "steps": 2
+    }
+    
+    response = requests.post(invoke_url, headers=headers, json=payload)
+    
+    if response.status_code == 200:
+        response_body = response.json()
+        image_url = response_body.get('image_url')  # Adjust based on actual response structure
+        if image_url:
+            image_response = requests.get(image_url)
+            image = Image.open(BytesIO(image_response.content))
+            return image
+        else:
+            return "No image URL found in response."
+    else:
+        return f"Error: {response.status_code} - {response.text}"
 
 # Create the Gradio interface
 iface = gr.Interface(
@@ -39,5 +45,4 @@ iface = gr.Interface(
 )
 
 # Launch the Gradio interface
-if __name__ == "__main__":
-    iface.launch()
+iface.launch()