Update app.py

app.py

@@ -2,20 +2,35 @@ import gradio as gr
 from PIL import Image
 import numpy as np
 import torch
+import os
 from diffusers import DiffusionPipeline  # Changed: Use DiffusionPipeline instead
 from diffusers.utils import load_image
 from huggingface_hub import HfApi, login
 from huggingface_hub.utils import HfHubHTTPError
 from ultralytics import YOLO
 
-try:
-    login(token=token)
-    api = HfApi(token=token)
-    user = api.whoami()
-    print("✅ HuggingFace token valid. Logged in as:", user["name"])
-except HfHubHTTPError as e:
-    print("❌ Invalid or expired HuggingFace token.")
-    print("Error:", e)
+# HuggingFace token setup
+import os
+
+# Option 1: Set your token directly (not recommended for production)
+# token = "hf_your_token_here"  # Replace with your actual token
+
+# Option 2: Use environment variable (recommended)
+token = os.getenv("HF_TOKEN")  # Changed to match your secret name
+
+# Option 3: Skip login if no token (will work for public models)
+if token:
+    try:
+        login(token=token)
+        api = HfApi(token=token)
+        user = api.whoami()
+        print("✅ HuggingFace token valid. Logged in as:", user["name"])
+    except HfHubHTTPError as e:
+        print("❌ Invalid or expired HuggingFace token.")
+        print("Error:", e)
+else:
+    print("⚠️ No HuggingFace token found. Using public access only.")
+    api = HfApi()
 
 # ───── Load FLUX-Kontext Pipeline ─────
 device = "cuda" if torch.cuda.is_available() else "cpu"