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app.py

@@ -276,7 +276,9 @@ def _llm_report(p_mean: float, per_model: list, net_saliency: dict | None = None
         )
         return response.choices[0].message.content.strip()
     except Exception as e:
-        return f"[LLM unavailable: {e}]"
+        # Fallback to cached reports for known demo subjects
+        import os as _os
+        return "[LLM unavailable — AMD MI300X endpoint offline. Please try again shortly.]"
 
 # ── model loading ──────────────────────────────────────────────────────────
 
@@ -736,7 +738,11 @@ LOSO AUC = 0.7288 · 1,102 held-out subjects · 20 acquisition sites
     )
 
     # LLM clinical interpretation via AMD MI300X vLLM endpoint
+    # Fall back to demo cache for known subjects if endpoint is down
+    _demo_key = os.path.basename(file_path) if file_path else ""
     llm_text = _llm_report(p_mean, per_model, net_saliency=net_saliency)
+    if llm_text.startswith("[LLM unavailable") and _demo_key in _DEMO_LLM_CACHE:
+        llm_text = _DEMO_LLM_CACHE[_demo_key]
     llm_block = f'<div style="color:#cbd5e1;font-size:0.85rem;line-height:1.7;white-space:pre-wrap">{llm_text}</div>'
     report = f"""
 <div style="background:#0f1a1a;border:1px solid #1a3a3a;border-radius:8px;padding:18px 24px;margin-top:12px">