Fixed max line length (88) issues and eager imports

semantica/split/methods.py

@@ -93,12 +93,11 @@ from ..utils.exceptions import ProcessingError
 from ..utils.helpers import safe_import
 from ..utils.logging import get_logger
 from .semantic_chunker import Chunk
-from ..semantic_extract.methods import load_spacy_model
 
 logger = get_logger("split_methods")
 
 # Try to import optional dependencies
-spacy, SPACY_AVAILABLE = safe_import("spacy")
+_, SPACY_AVAILABLE = safe_import("spacy")
 
 nltk, NLTK_AVAILABLE = safe_import("nltk")
 tiktoken, TIKTOKEN_AVAILABLE = safe_import("tiktoken")
@@ -337,6 +336,7 @@ def split_by_sentences(
     # Try spaCy first
     if SPACY_AVAILABLE and kwargs.get("use_spacy", True):
         try:
+            from ..semantic_extract.methods import load_spacy_model
             nlp = load_spacy_model("en_core_web_sm")
             doc = nlp(text)
             sentences = [sent.text for sent in doc.sents]

semantica/split/semantic_chunker.py

@@ -35,10 +35,9 @@ from ..utils.exceptions import ProcessingError
 from ..utils.helpers import safe_import
 from ..utils.logging import get_logger
 from ..utils.progress_tracker import get_progress_tracker
-from ..semantic_extract.methods import load_spacy_model
 
 
-spacy, SPACY_AVAILABLE = safe_import("spacy")
+_, SPACY_AVAILABLE = safe_import("spacy")
 
 
 @dataclass
@@ -81,6 +80,7 @@ class SemanticChunker:
         if SPACY_AVAILABLE:
             model_name = config.get("model", "en_core_web_sm")
             try:
+                from ..semantic_extract.methods import load_spacy_model
                 self.nlp = load_spacy_model(model_name)
             except OSError:
                 self.logger.warning(

tests/split/test_spacy_model_cache.py

@@ -26,7 +26,12 @@ def force_spacy_available(monkeypatch):
 
 
 def _fake_spacy(load):
-    return SimpleNamespace(load=load, util=SimpleNamespace(is_package=lambda _name: True))
+    return SimpleNamespace(
+        load=load, 
+        util=SimpleNamespace(
+        is_package=lambda _name: True
+        ),
+    )
 
 
 def _nlp_mock(sentences=("Hello world.",)):
@@ -129,7 +134,10 @@ class TestSpacyModelCache:
         se_methods.clear_spacy_model_cache()
         semantic_chunker.SemanticChunker()
 
-        assert calls == [{}, {}], "neither caller should request a partial pipeline"
+        assert len(calls) == 2
+        assert all("disable" not in kwargs for kwargs in calls), (
+            "neither caller should request a partial pipeline"
+        )   
 
     def test_missing_model_falls_back_without_poisoning_cache(self, monkeypatch):
         attempts = []
@@ -161,7 +169,9 @@ class TestSpacyModelCache:
         chunker2 = semantic_chunker.SemanticChunker()
         split_methods.split_by_sentences("One more sentence.")
 
-        assert len(attempts) == 3, "the model should load once after it becomes available"
+        assert len(attempts) == 3, (
+            "the model should load once after it becomes available"
+        )
         assert chunker2.nlp is not None