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>
66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
"""Tests for the Knowledge Base embedding index (issue #115, epic #34)."""
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from __future__ import annotations
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from pathlib import Path
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from compiler.common.embedding_index import EmbeddingIndex, build_index_rows, load_index
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from compiler.common.knowledge_base import KnowledgeBase, KnowledgeBaseEntry, load_knowledge_base
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REPO_ROOT = Path(__file__).resolve().parent.parent
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KB_DIR = REPO_ROOT / "knowledge_base"
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INDEX_FILE = REPO_ROOT / "data" / "kb_embedding_index.json"
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def _entry(id_, tags, aliases=()):
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return KnowledgeBaseEntry(id=id_, tags=tuple(tags), category="clothing", aliases=tuple(aliases))
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# --- committed reference index ---------------------------------------------
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def test_committed_index_maps_known_concept_to_expected_entry() -> None:
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index = load_index(INDEX_FILE)
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match = index.nearest("stockings")
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assert match.entry_id == "thighhighs" # via the ingested alias surface
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assert match.score > 0.99 # near-exact (weights are rounded in the snapshot)
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def test_index_only_references_real_kb_entries() -> None:
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kb = load_knowledge_base(KB_DIR)
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index = load_index(INDEX_FILE)
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# Every row id is a real entry: a fallback can never invent a tag.
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match = index.nearest("blue eyes")
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assert kb.get(match.entry_id) is not None
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# --- build determinism ------------------------------------------------------
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def test_build_is_deterministic() -> None:
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kb = KnowledgeBase(
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[
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_entry("thighhighs", ["thighhighs"], aliases=["thigh highs", "stockings"]),
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_entry("pantyhose", ["pantyhose"], aliases=["tights"]),
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]
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)
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assert build_index_rows(kb) == build_index_rows(kb)
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def test_nearest_returns_expected_surface() -> None:
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kb = KnowledgeBase(
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[
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_entry("thighhighs", ["thighhighs"], aliases=["stockings"]),
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_entry("dress", ["dress"]),
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]
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)
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index = EmbeddingIndex(build_index_rows(kb))
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match = index.nearest("stockings")
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assert match.entry_id == "thighhighs"
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assert match.surface == "stockings"
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def test_empty_query_has_no_neighbour() -> None:
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index = EmbeddingIndex(build_index_rows(KnowledgeBase([_entry("dress", ["dress"])])))
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assert index.nearest("") is None
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