38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
from __future__ import annotations
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from algebra.cga import cga_inner
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from generate.proposition import FrameRegistry, Proposition, propose
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from ingest.gate import inject
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from language_packs.compiler import load_mounted_packs
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from vault.store import VaultStore
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def test_light_prompt_generates_structured_proposition_near_prompt():
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vocab = load_mounted_packs(
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("en_minimal_v1", "he_logos_micro_v1", "grc_logos_micro_v1")
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)
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state = inject(["light", "אוֹר", "φῶς"], vocab)
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vault = VaultStore()
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random_idx = vault.store(vocab.get_versor("λόγος"), {"kind": "random"})
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registry = FrameRegistry.from_pack("grc", vocab)
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proposition = propose(state, vault, vocab, registry)
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assert isinstance(proposition, Proposition)
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assert proposition.subject
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assert proposition.predicate
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assert proposition.surface
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random_entry = vault.recall(vocab.get_versor("λόγος"), top_k=1)[0]["versor"]
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prompt = state.F
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assert cga_inner(proposition.subject_versor, prompt) > cga_inner(
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proposition.subject_versor,
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random_entry,
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)
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assert cga_inner(proposition.predicate_versor, prompt) > cga_inner(
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proposition.predicate_versor,
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random_entry,
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)
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stored = vault.recall(state.F, top_k=2)
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assert any(hit["metadata"].get("kind") == "proposition" for hit in stored)
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assert random_idx == 0
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