Robust LoRA load: fall back to UNet-only keys when kohya TE conversion fails

pipeline_manager.py

@@ -234,14 +234,29 @@ def _build_base_pipeline(cfg):
     # Apply LoRA if this entry is a LoRA model.
     if cfg.get("type") == "lora":
         scale = float(cfg.get("lora_scale", 0.8))
+        # Resolve to a local .safetensors path (HF repo or direct/Civitai URL).
         if cfg.get("lora_repo_id"):
-            kwargs = {}
-            if cfg.get("lora_weight_name"):
-                kwargs["weight_name"] = cfg["lora_weight_name"]
-            pipe.load_lora_weights(cfg["lora_repo_id"], **kwargs)
-        elif cfg.get("lora_url"):
-            local = _download_url(cfg["lora_url"])
-            pipe.load_lora_weights(local)
+            from huggingface_hub import hf_hub_download
+            local = hf_hub_download(cfg["lora_repo_id"], cfg["lora_weight_name"]) \
+                if cfg.get("lora_weight_name") else None
+            if local is None:
+                pipe.load_lora_weights(cfg["lora_repo_id"])
+                local = "__loaded__"
+        else:
+            local = _download_url(cfg.get("lora_url"))
+
+        if local and local != "__loaded__":
+            try:
+                pipe.load_lora_weights(local)
+            except Exception as e:  # noqa
+                # Some Civitai/kohya LoRAs carry text-encoder keys diffusers can't
+                # convert ("list index out of range"). Retry with UNet-only keys —
+                # the UNet holds most of the character/style effect.
+                print(f"[lora] full load failed ({e}); retrying UNet-only")
+                from safetensors.torch import load_file
+                sd = load_file(local)
+                sd = {k: v for k, v in sd.items() if not k.startswith("lora_te")}
+                pipe.load_lora_weights(sd)
         try:
             pipe.fuse_lora(lora_scale=scale)
         except Exception as e:  # noqa