fix: look up custom model postprocessing by resolved name

fastembed/text/custom_text_embedding.py

@@ -50,8 +50,12 @@ def __init__(
             specific_model_path=specific_model_path,
             **kwargs,
         )
-        self._pooling = self.POSTPROCESSING_MAPPING[model_name].pooling
-        self._normalization = self.POSTPROCESSING_MAPPING[model_name].normalization
+        # POSTPROCESSING_MAPPING is keyed by the registered name, while model
+        # lookup is case-insensitive, so the caller's spelling need not match.
+        # Use the resolved description's name rather than the argument.
+        postprocessing = self.POSTPROCESSING_MAPPING[self.model_description.model]
+        self._pooling = postprocessing.pooling
+        self._normalization = postprocessing.normalization
 
     @classmethod
     def _list_supported_models(cls) -> list[DenseModelDescription]:

tests/test_custom_models.py

@@ -21,9 +21,11 @@
 @pytest.fixture(autouse=True)
 def restore_custom_models_fixture():
     CustomTextEmbedding.SUPPORTED_MODELS = []
+    CustomTextEmbedding.POSTPROCESSING_MAPPING = {}
     CustomTextCrossEncoder.SUPPORTED_MODELS = []
     yield
     CustomTextEmbedding.SUPPORTED_MODELS = []
+    CustomTextEmbedding.POSTPROCESSING_MAPPING = {}
     CustomTextCrossEncoder.SUPPORTED_MODELS = []
 
 
@@ -250,3 +252,41 @@ def test_do_not_add_existing_cross_encoder():
         )
 
     CustomTextCrossEncoder.SUPPORTED_MODELS.clear()
+
+
+def test_custom_model_postprocessing_lookup_is_case_insensitive():
+    """A custom model may be registered and instantiated with different casing.
+
+    `TextEmbedding` resolves model names case-insensitively, so
+    `CustomTextEmbedding` has to look its postprocessing config up by the resolved
+    canonical name rather than by whatever string the caller happened to type.
+    """
+    TextEmbedding.add_custom_model(
+        "Org/Model",
+        pooling=PoolingType.MEAN,
+        normalization=True,
+        sources=ModelSource(hf="intfloat/multilingual-e5-small"),
+        dim=384,
+    )
+
+    model = TextEmbedding("org/model", lazy_load=True).model
+
+    assert model.model_description.model == "Org/Model"
+    assert model._pooling == PoolingType.MEAN
+    assert model._normalization is True
+
+
+def test_custom_model_postprocessing_lookup_with_matching_case_still_works():
+    """Control: the exact-casing path worked before and must keep working."""
+    TextEmbedding.add_custom_model(
+        "Org/Model",
+        pooling=PoolingType.CLS,
+        normalization=False,
+        sources=ModelSource(hf="intfloat/multilingual-e5-small"),
+        dim=384,
+    )
+
+    model = TextEmbedding("Org/Model", lazy_load=True).model
+
+    assert model._pooling == PoolingType.CLS
+    assert model._normalization is False