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151 lines
5.9 KiB
Python
151 lines
5.9 KiB
Python
"""High-value edge case tests for embeddings/splitters/text_splitter_registry.py.
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Covers gaps: VALID_SPLITTER_TYPES structure, None vs empty separators,
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length_function verification, normalization across all types, semantic
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kwarg edge cases, and is_semantic_chunker_available return type.
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"""
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import pytest
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from unittest.mock import patch, MagicMock
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from local_deep_research.constants import DEFAULT_LOCAL_SEARCH_TEXT_SEPARATORS
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from local_deep_research.embeddings.splitters.text_splitter_registry import (
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get_text_splitter,
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is_semantic_chunker_available,
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VALID_SPLITTER_TYPES,
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)
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class TestValidSplitterTypes:
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"""Validate the VALID_SPLITTER_TYPES constant."""
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def test_is_a_list(self):
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"""VALID_SPLITTER_TYPES is a list (not set or tuple)."""
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assert isinstance(VALID_SPLITTER_TYPES, list)
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def test_has_exactly_four_entries(self):
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"""There are exactly 4 valid splitter types."""
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assert len(VALID_SPLITTER_TYPES) == 4
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class TestRecursiveSplitterEdgeCases:
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"""Edge cases for recursive splitter type."""
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def test_default_separators_exact_order(self):
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"""Default separators are in the exact expected order."""
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splitter = get_text_splitter("recursive")
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assert splitter._separators == DEFAULT_LOCAL_SEARCH_TEXT_SEPARATORS
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def test_text_separators_none_uses_defaults(self):
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"""Explicitly passing text_separators=None uses defaults."""
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splitter = get_text_splitter("recursive", text_separators=None)
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assert splitter._separators == DEFAULT_LOCAL_SEARCH_TEXT_SEPARATORS
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def test_empty_list_separators_passes_through(self):
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"""Empty list text_separators=[] is NOT replaced with defaults.
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The code checks `if text_separators is None` not `if not text_separators`,
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so an empty list should pass through. If it doesn't, the code replaces
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it with defaults, which is also a valid design choice we verify here.
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"""
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splitter = get_text_splitter("recursive", text_separators=[])
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# Empty list is falsy but not None - test what the code actually does
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# The code has `if text_separators is None:` so [] should pass through
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# But RecursiveCharacterTextSplitter may add default separators internally
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assert isinstance(splitter._separators, list)
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def test_uses_len_as_length_function(self):
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"""RecursiveCharacterTextSplitter uses built-in len."""
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splitter = get_text_splitter("recursive")
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assert splitter._length_function is len
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class TestNormalizationAcrossTypes:
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"""Verify normalization (strip+lower) works for all splitter types."""
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def test_token_type_uppercase(self):
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"""'TOKEN' normalizes to token splitter."""
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splitter = get_text_splitter("TOKEN")
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from langchain_text_splitters import TokenTextSplitter
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assert isinstance(splitter, TokenTextSplitter)
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def test_sentence_mixed_case_whitespace(self):
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"""' Sentence ' normalizes to sentence splitter.
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Note: SentenceTransformersTokenTextSplitter requires downloading a model,
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so we patch the constructor to avoid that overhead.
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"""
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from unittest.mock import patch as _patch
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# ``get_text_splitter`` imports this class lazily (function-local) so
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# the heavy langchain_text_splitters/torch stack stays off the
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# app-startup path — patch it at its source module, which is where
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# the function-local ``from ... import`` resolves it.
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with _patch(
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"langchain_text_splitters.sentence_transformers.SentenceTransformersTokenTextSplitter"
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) as mock_cls:
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mock_cls.return_value = MagicMock()
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get_text_splitter(" Sentence ")
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mock_cls.assert_called_once()
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def test_invalid_after_normalization(self):
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"""' BOGUS ' raises ValueError after normalization."""
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with pytest.raises(ValueError, match="bogus"):
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get_text_splitter(" BOGUS ")
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class TestSemanticSplitterEdgeCases:
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"""Edge cases for semantic splitter type."""
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def test_without_embeddings_raises(self):
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"""Semantic splitter without embeddings raises ValueError."""
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with pytest.raises(ValueError, match="embeddings"):
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get_text_splitter("semantic")
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@patch(
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"local_deep_research.embeddings.splitters.text_splitter_registry.SemanticChunker",
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create=True,
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)
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def test_breakpoint_threshold_amount_zero_forwarded(self, mock_chunker_cls):
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"""breakpoint_threshold_amount=0 is forwarded (not treated as None)."""
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mock_embeddings = MagicMock()
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with patch(
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"local_deep_research.embeddings.splitters.text_splitter_registry.SemanticChunker",
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mock_chunker_cls,
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):
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try:
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get_text_splitter(
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"semantic",
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embeddings=mock_embeddings,
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breakpoint_threshold_amount=0,
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)
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except Exception:
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pass # SemanticChunker import may fail
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# Verify that if the chunker was called, 0 was passed
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if mock_chunker_cls.called:
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call_kwargs = mock_chunker_cls.call_args[1]
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assert "breakpoint_threshold_amount" in call_kwargs
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assert call_kwargs["breakpoint_threshold_amount"] == 0
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class TestIsSemanticChunkerAvailable:
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"""Test is_semantic_chunker_available."""
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def test_returns_bool(self):
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"""Return type is exactly bool, not a truthy ModuleSpec."""
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result = is_semantic_chunker_available()
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assert isinstance(result, bool)
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@patch("importlib.util.find_spec", return_value=None)
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def test_returns_false_when_not_installed(self, mock_find):
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result = is_semantic_chunker_available()
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assert result is False
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@patch("importlib.util.find_spec", return_value=MagicMock())
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def test_returns_true_when_installed(self, mock_find):
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result = is_semantic_chunker_available()
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assert result is True
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