87d9525176
Closes #114, #115, #116, #117. - Deterministic, offline, dependency-free char-ngram embedding backend + config section (semantic.enabled default false, min_similarity, backend). - Committed embedding index (data/kb_embedding_index.json) mapping vectors to real KB entry ids only; built by scripts/build_embedding_index.py, loaded once/cached. - Resolver falls back to the nearest entry on a deterministic miss when enabled, accepting >= min_similarity and emitting SC0020; NSFW-gated neighbours are skipped. Disabled => byte-identical to before. - Guarantee tests: deterministic lookup always wins (exact hit never queries the index), fallback emits only KB tags (no invention), identical input => identical output. SC0020 registered. Co-authored-by: kunail0804 <kunail0804@gmail.com> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
"""Tests for the deterministic offline embedding backend (issue #114, epic #34)."""
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from __future__ import annotations
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import pytest
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from compiler.common.embedding import (
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CharNGramEmbeddingBackend,
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cosine_similarity,
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get_backend,
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)
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def test_embedding_is_deterministic() -> None:
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backend = CharNGramEmbeddingBackend()
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assert backend.embed(["thighhighs"]) == backend.embed(["thighhighs"])
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def test_vectors_are_l2_normalized() -> None:
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(vector,) = CharNGramEmbeddingBackend().embed(["blue eyes"])
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magnitude = sum(weight * weight for weight in vector.values())
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assert magnitude == pytest.approx(1.0)
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def test_identical_text_has_self_similarity_one() -> None:
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(vector,) = CharNGramEmbeddingBackend().embed(["long hair"])
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assert cosine_similarity(vector, vector) == pytest.approx(1.0)
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def test_similar_text_scores_higher_than_dissimilar() -> None:
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backend = CharNGramEmbeddingBackend()
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(thighhighs,) = backend.embed(["thighhighs"])
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(thigh_highs,) = backend.embed(["thigh highs"])
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(unrelated,) = backend.embed(["castle"])
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assert cosine_similarity(thighhighs, thigh_highs) > cosine_similarity(thighhighs, unrelated)
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def test_normalization_ignores_case_and_underscores() -> None:
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backend = CharNGramEmbeddingBackend()
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assert backend.embed(["Long_Hair"]) == backend.embed(["long hair"])
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def test_empty_text_yields_empty_vector() -> None:
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assert CharNGramEmbeddingBackend().embed([""]) == [{}]
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assert cosine_similarity({}, {"abc": 1.0}) == pytest.approx(0.0)
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def test_get_backend_returns_default_and_rejects_unknown() -> None:
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assert isinstance(get_backend("char_ngram"), CharNGramEmbeddingBackend)
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with pytest.raises(ValueError):
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get_backend("nope")
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