Update app.py

app.py

@@ -158,12 +158,30 @@ def load_models() -> str | None:
         # request asks for them. `load_lora_adapter` is the model-level loader (`PeftAdapterMixin`), used because
         # `MiniMaxH3ModularPipeline` has no pipeline-level `load_lora_weights` of its own.
         if LORA_REPO.lower() not in ("", "off", "none"):
+            from peft.tuners.tuners_utils import BaseTunerLayer
+
             try:
+                counts = {}
                 for name, filename in LORA_FILES.items():
-                    pipe.transformer.load_lora_adapter(LORA_REPO, weight_name=filename, adapter_name=name)
+                    pipe.transformer.load_lora_adapter(
+                        LORA_REPO, weight_name=filename, adapter_name=name, prefix=None
+                    )
+                    # `load_lora_adapter` warns-and-continues on a zero-key match instead of raising, so count
+                    # matched layers ourselves and fail loudly if a file attached nothing.
+                    counts[name] = sum(
+                        1
+                        for module in pipe.transformer.modules()
+                        if isinstance(module, BaseTunerLayer) and name in module.lora_A
+                    )
+                    if counts[name] == 0:
+                        raise RuntimeError(
+                            f"'{filename}' matched 0 target modules on MiniMaxH3Transformer3DModel — its LoRA "
+                            f"keys don't line up with this transformer's naming. Inspect its safetensors keys."
+                        )
                 pipe.transformer.set_adapters(list(LORA_FILES), weights=[0.0] * len(LORA_FILES))
                 LORA_STATUS = "LoRAs loaded: " + ", ".join(
-                    f"`{name}` ({LORA_REPO}/{filename})" for name, filename in LORA_FILES.items()
+                    f"`{name}` ({LORA_REPO}/{filename}, {counts[name]} layers)"
+                    for name, filename in LORA_FILES.items()
                 )
             except Exception as error:
                 LORA_STATUS = f"LoRA load failed: {type(error).__name__}: {error}"