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Yunare MaiaandSameer Kadam
e12eec40a1
* test(ner): fix NER configuration tests for the typed LLM extraction API Two of the three failing tests tracked in #1059 were still red after #1070 was closed because the mocks targeted the pre-typed provider API: - test_ner_llm_config mocked generate_structured, but the LLM path now goes through generate_typed with a Pydantic schema. Mock the typed response (namespace items with .text/.label/.start/.end/.confidence) and expect extraction_method 'llm_typed'. - test_ner_pattern_config asserted 'Apple Inc' without the trailing dot, but the ORG pattern captures it via (?:\.|\b). Assert 'Apple Inc.' to match current production behavior. Verified locally: 8/8 pass in test_ner_configurations.py; the performance-test failures in tests/semantic_extract/ reproduce on a clean main checkout and are unrelated. Fixes #1059 Signed-off-by: Yunare Maia <yunare@gmail.com> * refactor(ner): remove dead _extract_with_spacy method and unused self.nlp _extract_with_spacy() had no callers: the ML dispatch path goes through get_entity_method('ml') -> extract_entities_ml(), which loads the spaCy model lazily via the process-level cache in methods.py. The instance attribute self.nlp was only read by that dead method, so __init__ now just validates the runtime (keeping the _ml_runtime_usable gate) instead of eagerly loading a model that was never used. Fixes #1058 Signed-off-by: Yunare Maia <yunare@gmail.com> * test(split): rewrite NERExtractor cache tests to not rely on removed .nlp attribute NERExtractor.nlp was removed in this PR as part of dead-code cleanup (the attribute was only used by the equally-dead _extract_with_spacy()). The three affected tests in TestNERExtractorSpacyModelCache previously verified cache behavior through .nlp identity comparisons; rewrite them to use load-call counts and direct se_methods.load_spacy_model() cache queries instead: - test_ner_extractor_reuses_cached_model_across_instances: drop the e1.nlp is e2.nlp is e3.nlp assertion; len(calls)==1 already proves reuse; add a cache query to confirm the cached object is non-None. - test_ner_extractor_distinct_model_names_load_separately: store each mock nlp in a dict keyed by name, then query the cache to assert sm_cached is loaded['en_core_web_sm'] and sm_cached is not lg_cached. - test_ner_extractor_failed_load_not_cached_and_retried: replace extractor.nlp is None/not None with is-not-None construction checks and a final cache query that verifies the recovered model is the exact object returned by working_load. All three tests still exercise the original behavioral contract (no crash on missing model, failures not cached / retried, successful load shared across instances); they just no longer rely on a private instance attribute that no longer exists. --------- Signed-off-by: Yunare Maia <yunare@gmail.com> Co-authored-by: Sameer Kadam <sskadam6305@gmail.com>