Upload app.py with huggingface_hub

app.py

@@ -305,7 +305,6 @@ EXAMPLES_QA = [
 # ---------------------------------------------------------------------------
 ZEROGPU_QUEUE_HINT = "No GPU was available after"
 SPACES_PAGE_URL = "https://huggingface.co/spaces/vibesecurityguy/veris-classifier"
-HF_LOGIN_URL = "https://huggingface.co/login?next=%2Fspaces%2Fvibesecurityguy%2Fveris-classifier"
 
 
 def _is_zerogpu_queue_timeout(err: Exception) -> bool:
@@ -313,11 +312,22 @@ def _is_zerogpu_queue_timeout(err: Exception) -> bool:
     return ZEROGPU_QUEUE_HINT in str(err)
 
 
-def _spaces_user_logged_in(request: gr.Request | None) -> bool:
+def _spaces_user_logged_in(
+    request: gr.Request | None,
+    profile: gr.OAuthProfile | None = None,
+) -> bool:
     """True when a Spaces OAuth user is attached to this request."""
+    if profile is not None:
+        return True
     if request is None:
         return False
-    return bool(getattr(request, "username", None))
+    if getattr(request, "username", None):
+        return True
+    # Gradio/HF OAuth stores profile info in session; use it as fallback signal.
+    session = getattr(request, "session", None)
+    if isinstance(session, dict) and session.get("oauth_info"):
+        return True
+    return False
 
 
 
@@ -330,11 +340,16 @@ def _use_hf_model() -> bool:
     return os.getenv("VERIS_USE_HF", "").lower() in ("1", "true", "yes")
 
 
-def classify(description: str, api_key: str, request: gr.Request | None = None) -> str:
+def classify(
+    description: str,
+    api_key: str,
+    request: gr.Request | None = None,
+    profile: gr.OAuthProfile | None = None,
+) -> str:
     """Classify an incident — uses HF model on Spaces, OpenAI otherwise."""
     if not description.strip():
         return "Please enter an incident description."
-    if IS_SPACES and not _spaces_user_logged_in(request):
+    if IS_SPACES and not _spaces_user_logged_in(request, profile):
         return json.dumps(
             {
                 "error": (
@@ -383,11 +398,16 @@ def classify(description: str, api_key: str, request: gr.Request | None = None)
         return json.dumps({"error": str(e)}, indent=2)
 
 
-def ask(question: str, api_key: str, request: gr.Request | None = None) -> str:
+def ask(
+    question: str,
+    api_key: str,
+    request: gr.Request | None = None,
+    profile: gr.OAuthProfile | None = None,
+) -> str:
     """Answer a VERIS question — uses HF model on Spaces, OpenAI otherwise."""
     if not question.strip():
         return "*Please enter a question.*"
-    if IS_SPACES and not _spaces_user_logged_in(request):
+    if IS_SPACES and not _spaces_user_logged_in(request, profile):
         return (
             "**Error:** Please log in on Hugging Face and open this app from "
             f"{SPACES_PAGE_URL}. ZeroGPU quota is per logged-in user."
@@ -576,12 +596,9 @@ def build_app() -> gr.Blocks:
                     "**Required:** Log in with Hugging Face so ZeroGPU usage "
                     "counts against your account quota."
                 )
-                gr.HTML(
-                    f'<a href="{HF_LOGIN_URL}" target="_self" '
-                    'style="display:inline-block;padding:10px 14px;border-radius:8px;'
-                    'background:#2563eb;color:#fff;text-decoration:none;font-weight:600;">'
-                    "Sign in with Hugging Face</a>"
-                )
+                login_btn = gr.LoginButton("Sign in with Hugging Face")
+                # Gradio 4.44 can miss auto-activation in some Spaces contexts.
+                login_btn.activate()
         else:
             gr.HTML("""
             <div class="model-banner">