Update app.py

app.py

@@ -1,3 +1,44 @@
 import gradio as gr
+import requests
+from io import BytesIO
+from PIL import Image
+inport os
+# Load Stable Diffusion model
+HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None
+model = gr.load("models/stabilityai/stable-diffusion-3.5-large", hf_token=HF_TOKEN)
 
-gr.load("models/stabilityai/stable-diffusion-3.5-large").launch()
+# Chevereto API details
+CHEVERETO_API_URL = os.environ.get("api_url")  # Replace with your Chevereto API endpoint
+CHEVERETO_API_KEY =  os.environ.get("API_KEY")  # Replace with your API key
+CHEVERETO_ALBUM_ID =  os.environ.get("ALBUM_ID")  # Replace with the album ID where you want to store images
+
+# Upload image to Chevereto
+def upload_to_chevereto(image: Image.Image) -> str:
+    # Convert image to bytes
+    buffered = BytesIO()
+    image.save(buffered, format="PNG")
+    files = {"source": buffered.getvalue()}  # Convert to binary for upload
+    
+    # Set API parameters
+    data = {
+        "key": CHEVERETO_API_KEY,
+        "format": "json",
+        "album": CHEVERETO_ALBUM_ID  # Specify album ID
+    }
+
+    # Upload request
+    response = requests.post(CHEVERETO_API_URL, files=files, data=data)
+
+    if response.status_code == 200:
+        return response.json()["image"]["url"]  # Return public URL of uploaded image
+    return "Error uploading image"
+
+# Generate and upload the image
+def generate_image_and_upload(prompt: str) -> str:
+    img = model.predict(prompt)[0]  # Get generated image
+    return upload_to_chevereto(img)  # Upload and return the URL
+
+# Define Gradio API returning the Chevereto public URL
+iface = gr.Interface(fn=generate_image_and_upload, inputs="text", outputs="text")
+
+iface.launch()