Update app.py

app.py

@@ -29,9 +29,16 @@ from diffusers import (FluxPriorReduxPipeline, FluxInpaintPipeline, FluxFillPipe
 
 
 
-# Login Hugging Face Hub
-HF_TOKEN = os.environ.get("HF_TOKEN")
-login(token=HF_TOKEN)
+from huggingface_hub import login
+
+HF_TOKEN = (os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACEHUB_API_TOKEN") or "").strip()
+
+if HF_TOKEN:
+    login(token=HF_TOKEN, add_to_git_credential=False)
+    print("✅ HF token found; logged in")
+else:
+    print("⚠️ No HF token found. Public repos may work, gated/private models will fail.")
+
 import diffusers
 
 
@@ -49,7 +56,12 @@ base_model = "black-forest-labs/FLUX.1-dev"
 
 
 
-txt2img_pipe = FluxPipeline.from_pretrained(base_model, torch_dtype=dtype)
+txt2img_pipe = FluxPipeline.from_pretrained(
+    base_model,
+    torch_dtype=dtype,
+    token=HF_TOKEN if HF_TOKEN else None,
+)
+
 txt2img_pipe = txt2img_pipe.to(device)
 
 
@@ -200,7 +212,12 @@ def run_lora(
                         print(f"skip invalid lora entry: {lora_info}")
                         continue
                     try:
-                        weight_path = hf_hub_download(repo_id=repo, filename=weights)
+                        weight_path = hf_hub_download(
+                            repo_id=repo,
+                            filename=weights,
+                            token=HF_TOKEN if HF_TOKEN else None,
+                        )
+
                         pipe.load_lora_weights(weight_path, adapter_name=adapter_name, prefix=None)
                         adapter_names.append(adapter_name)
                         adapter_weights.append(weight)