Update app.py

app.py

@@ -20,7 +20,7 @@ except ImportError:
 HF_TOKEN = os.environ.get("HF_TOKEN", "").strip()
 BUCKET_ID = os.environ.get("BUCKET_ID", "").strip()
 
-GUARD_MODEL = "hfmlsoc/ncii-guard-v02"
+GUARD_MODEL = "hfmlsoc/ncii-light-guard-v01"
 NCII_THRESHOLD = 0.70
 
 # Cosmetic dropdown only — the sole backend is the ncii-guard classifier.
@@ -125,6 +125,7 @@ def log_submission(session_id: str, image: Image.Image, prompt: str,
 
 
 # --- Main pipeline ---------------------------------------------------------------
+BLOCKED_MSG = "🚫 Prompt blocked."
 BACKEND_FAILURE_MSG = "⚠️ Backend failure. Please try again later."
 
 
@@ -156,7 +157,6 @@ def edit_image(image, prompt, model_choice, request: gr.Request,
     try:
         progress(0.05, desc="Analyzing image…")
         score = ncii_score(prompt)
-        _credible_progress(progress)  # pad the instant check to ~18s
         status = "blocked" if score > NCII_THRESHOLD else "allowed"
     except Exception as err:
         error_detail = str(err)
@@ -164,8 +164,13 @@ def edit_image(image, prompt, model_choice, request: gr.Request,
     finally:
         log_submission(session_id, image, prompt, status, score, error_detail)
 
-    # Honeypot: no image is ever produced or shown — the study is how users try
-    # to get around the guard, so every outcome looks identical.
+    # Guard caught it: tell the user right away.
+    if status == "blocked":
+        raise gr.Error(BLOCKED_MSG)
+
+    # Passed (or guard errored): no image is ever produced, so wait a bit to look
+    # like real work, then fail. The study is how users retry to get past the guard.
+    _credible_progress(progress)
     raise gr.Error(BACKEND_FAILURE_MSG)