Fix local LoRA weight auto-discovery in offline mode

src/diffusers/loaders/lora_base.py

@@ -277,15 +277,14 @@ def _fetch_state_dict(
 def _best_guess_weight_name(
     pretrained_model_name_or_path_or_dict, file_extension=".safetensors", local_files_only=False
 ):
-    if local_files_only or HF_HUB_OFFLINE:
-        raise ValueError("When using the offline mode, you must specify a `weight_name`.")
-
     targeted_files = []
 
     if os.path.isfile(pretrained_model_name_or_path_or_dict):
         return
     elif os.path.isdir(pretrained_model_name_or_path_or_dict):
         targeted_files = [f for f in os.listdir(pretrained_model_name_or_path_or_dict) if f.endswith(file_extension)]
+    elif local_files_only or HF_HUB_OFFLINE:
+        raise ValueError("When using the offline mode, you must specify a `weight_name`.")
     else:
         files_in_repo = model_info(pretrained_model_name_or_path_or_dict).siblings
         targeted_files = [f.rfilename for f in files_in_repo if f.rfilename.endswith(file_extension)]

tests/lora/test_lora_loader_utils.py

@@ -0,0 +1,102 @@
+# coding=utf-8
+# Copyright 2026 HuggingFace Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import logging
+from unittest.mock import Mock
+
+import pytest
+import torch
+from safetensors.torch import save_file
+
+from diffusers.loaders import StableDiffusionLoraLoaderMixin, lora_base
+
+
+LORA_KEY = "unet.test.lora_A.weight"
+
+
+def _write_lora_weights(path):
+    save_file({LORA_KEY: torch.ones(1)}, path)
+
+
+@pytest.fixture
+def lora_weight_path(tmp_path):
+    weight_path = tmp_path / "adapter.safetensors"
+    _write_lora_weights(weight_path)
+    return weight_path
+
+
+@pytest.fixture
+def model_info_mock(monkeypatch):
+    model_info_mock = Mock()
+    monkeypatch.setattr(lora_base, "model_info", model_info_mock)
+    return model_info_mock
+
+
+def test_local_directory_in_offline_mode(lora_weight_path, monkeypatch, model_info_mock):
+    monkeypatch.setattr(lora_base, "HF_HUB_OFFLINE", True)
+
+    state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(lora_weight_path.parent)
+
+    assert torch.equal(state_dict[LORA_KEY], torch.ones(1))
+    model_info_mock.assert_not_called()
+
+
+def test_local_directory_with_local_files_only(lora_weight_path, model_info_mock):
+    state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(lora_weight_path.parent, local_files_only=True)
+
+    assert torch.equal(state_dict[LORA_KEY], torch.ones(1))
+    model_info_mock.assert_not_called()
+
+
+def test_local_file_in_offline_mode(lora_weight_path, monkeypatch, model_info_mock):
+    monkeypatch.setattr(lora_base, "HF_HUB_OFFLINE", True)
+
+    state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(lora_weight_path)
+
+    assert torch.equal(state_dict[LORA_KEY], torch.ones(1))
+    model_info_mock.assert_not_called()
+
+
+def test_remote_repository_in_offline_mode_requires_weight_name(monkeypatch, model_info_mock):
+    monkeypatch.setattr(lora_base, "HF_HUB_OFFLINE", True)
+
+    with pytest.raises(ValueError, match="offline mode.*weight_name"):
+        StableDiffusionLoraLoaderMixin.lora_state_dict("organization/repository")
+
+    model_info_mock.assert_not_called()
+
+
+def test_local_directory_without_matching_files_returns_none(tmp_path, monkeypatch):
+    (tmp_path / "notes.txt").touch()
+    monkeypatch.setattr(lora_base, "HF_HUB_OFFLINE", True)
+
+    weight_name = lora_base._best_guess_weight_name(tmp_path)
+
+    assert weight_name is None
+
+
+def test_local_directory_with_multiple_files_warns_and_uses_first(tmp_path, monkeypatch, caplog):
+    first_path = tmp_path / "first.safetensors"
+    second_path = tmp_path / "second.safetensors"
+    first_path.touch()
+    second_path.touch()
+    monkeypatch.setattr(lora_base, "HF_HUB_OFFLINE", True)
+    monkeypatch.setattr(lora_base.os, "listdir", lambda _: [first_path.name, second_path.name])
+    monkeypatch.setattr(lora_base.logger, "propagate", True)
+
+    with caplog.at_level(logging.WARNING, logger="diffusers.loaders.lora_base"):
+        weight_name = lora_base._best_guess_weight_name(tmp_path)
+
+    assert weight_name == first_path.name
+    assert "contains more than one weights file" in caplog.text