175 lines
6.6 KiB
Python
175 lines
6.6 KiB
Python
"""Contract tests for the Phase C ratified glosses.
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Pins:
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- Every pack with a ``glosses.jsonl`` file has a matching
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``glosses_checksum`` in its manifest.
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- Every gloss entry references a lemma that is ratified in the
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same pack's ``lexicon.jsonl`` (lexicon-residency invariant —
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re-asserted from the storage layer up).
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- The total ratified gloss count meets a floor (>= 300).
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- At least one gloss resolves end-to-end for the most common
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conversational lemmas (sanity check for the wiring + content).
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"""
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from __future__ import annotations
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import hashlib
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import json
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from pathlib import Path
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from chat.pack_resolver import (
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DEFAULT_RESOLVABLE_PACK_IDS,
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_pack_glosses_for,
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_pack_lexicon_for,
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clear_resolver_cache,
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resolve_gloss,
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)
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_DATA = Path(__file__).resolve().parent.parent / "packs" / "data"
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def _packs_with_glosses() -> list[str]:
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out = []
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for p in DEFAULT_RESOLVABLE_PACK_IDS:
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if (_DATA / p / "glosses.jsonl").exists():
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out.append(p)
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return out
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class TestGlossesPresent:
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def test_at_least_eight_packs_ship_glosses(self) -> None:
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"""Phase C seeds glosses in 9 English content packs."""
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packs = _packs_with_glosses()
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assert len(packs) >= 8, (
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f"expected >=8 packs with glosses, got {len(packs)}: {packs}"
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)
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def test_total_gloss_count_floor(self) -> None:
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"""The Phase C dispatch targeted ~330 glosses; this is the
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regression floor."""
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clear_resolver_cache()
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total = sum(len(_pack_glosses_for(p)) for p in _packs_with_glosses())
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assert total >= 300, f"total gloss count {total} below floor 300"
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class TestManifestChecksumDiscipline:
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def test_every_glossed_pack_has_matching_checksum(self) -> None:
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for pack_id in _packs_with_glosses():
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manifest = json.loads(
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(_DATA / pack_id / "manifest.json").read_text(encoding="utf-8")
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)
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assert "glosses_checksum" in manifest, pack_id
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declared = manifest["glosses_checksum"]
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assert isinstance(declared, str) and len(declared) == 64, (pack_id, declared)
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actual = hashlib.sha256(
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(_DATA / pack_id / "glosses.jsonl").read_bytes()
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).hexdigest()
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assert actual == declared, (
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f"glosses_checksum drift on {pack_id}: "
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f"declared={declared[:16]}… actual={actual[:16]}…"
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)
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def test_lexicon_checksum_unchanged_by_gloss_landing(self) -> None:
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"""Adding glosses must NOT bump the lexicon checksum. The
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lexicon is immutable; only glosses_checksum changes when
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glosses are added or revised."""
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for pack_id in _packs_with_glosses():
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manifest = json.loads(
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(_DATA / pack_id / "manifest.json").read_text(encoding="utf-8")
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)
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actual_lex_checksum = hashlib.sha256(
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(_DATA / pack_id / "lexicon.jsonl").read_bytes()
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).hexdigest()
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assert manifest["checksum"] == actual_lex_checksum, pack_id
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class TestLexiconResidencyAcrossAllGlosses:
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"""Every authored gloss must reference a lemma that exists in the
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same pack's lexicon.jsonl. This is the storage-layer enforcement
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of the resolve_gloss runtime invariant — any drift in glosses.jsonl
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that introduces an unratified lemma fails this test."""
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def test_every_gloss_lemma_is_lexicon_resident(self) -> None:
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clear_resolver_cache()
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for pack_id in _packs_with_glosses():
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lex = _pack_lexicon_for(pack_id)
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glosses = _pack_glosses_for(pack_id)
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for lemma in glosses:
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assert lemma in lex, (
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f"pack {pack_id} ships a gloss for {lemma!r} but the "
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f"lemma is not in its lexicon.jsonl"
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)
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class TestEndToEndSmoke:
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"""Resolve known high-frequency conversational lemmas through
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resolve_gloss and assert the runtime composes a fluent surface."""
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HIGH_FREQ_LEMMAS = (
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# cognition
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"truth", "knowledge", "memory", "evidence", "thought",
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# meta
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"doubt", "fact", "idea", "self", "believe", "know",
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# attitude
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"true", "good", "important", "certain", "necessary",
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# temporal
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"now", "moment", "future", "past", "before",
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# spatial
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"here", "place", "above",
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# action
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"make", "create", "change", "use",
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# causation
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"effect", "outcome",
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# polarity
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"always", "never", "yes",
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)
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def test_high_freq_lemmas_resolve_a_gloss(self) -> None:
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clear_resolver_cache()
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misses = []
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for lemma in self.HIGH_FREQ_LEMMAS:
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entry = resolve_gloss(lemma)
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if entry is None:
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misses.append(lemma)
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assert not misses, (
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f"resolve_gloss returned None for high-frequency lemmas: {misses}"
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)
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def test_fluent_surface_contains_lemma_case_insensitive(self) -> None:
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"""End-to-end: pack_grounded_surface composes a fluent sentence
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for every high-freq lemma; the lemma (lowercase) appears in the
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rendered surface."""
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from chat.pack_grounding import pack_grounded_surface
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clear_resolver_cache()
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for lemma in self.HIGH_FREQ_LEMMAS:
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surface = pack_grounded_surface(lemma)
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assert surface is not None, lemma
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assert lemma in surface.lower(), (lemma, surface)
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assert "pack-grounded" in surface, (lemma, surface)
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# No dotted-domain-inventory in gloss-backed surfaces.
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assert "; " not in surface, (lemma, surface)
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class TestSurfaceFormatInvariants:
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"""A handful of structural invariants the gloss-backed surfaces
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must respect. These are what the deterministic_fluency lane
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checks at scale — repeated here per-pack for tighter attribution."""
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SAMPLE = ("truth", "doubt", "important", "now", "place", "make", "effect", "always")
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def test_surfaces_have_terminal_punctuation(self) -> None:
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from chat.pack_grounding import pack_grounded_surface
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clear_resolver_cache()
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for lemma in self.SAMPLE:
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s = pack_grounded_surface(lemma)
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assert s is not None and s.rstrip().endswith("."), (lemma, s)
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def test_surfaces_contain_no_placeholders(self) -> None:
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from chat.pack_grounding import pack_grounded_surface
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clear_resolver_cache()
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for lemma in self.SAMPLE:
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s = pack_grounded_surface(lemma)
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assert s is not None
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for marker in ("...", "<pending>", "<prior>"):
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assert marker not in s, (lemma, marker, s)
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