| """Capability stack: linked ingest + stable compose + substrate decoder.""" |
|
|
| from palimseste.lsh import LSHConfig |
| from palimseste.memory import Memory |
| from palimseste.phi import Phi, KernelConfig |
| from palimseste.linked_ingest import LinkedEncoder |
| from palimseste.compose import analogize, compose_chain, ComposeConfig |
| from palimseste.substrate_decoder import SubstrateDecoder |
|
|
|
|
| def _stack(D=1024): |
| mem = Memory(D=D, lsh_config=LSHConfig.tune(D=D, target_radius=0.20, recall=0.95)) |
| enc = LinkedEncoder(mem) |
| phi = Phi(KernelConfig(radius=max(80, D // 8), topk=12, min_weight=1e-6)) |
| dec = SubstrateDecoder(enc, phi) |
| return enc, phi, dec |
|
|
|
|
| CORPUS = { |
| "capitals": ( |
| "Paris is the capital of France. London is the capital of England. " |
| "Rome is the capital of Italy." |
| ), |
| "cortex": ( |
| "Palimpseste is an append-only hypervector cortex. " |
| "Learning is a single write. " |
| "Phi reconstructs values from a Hamming neighborhood." |
| ), |
| } |
|
|
|
|
| def test_ingest_links_not_raw_dump(): |
| enc, phi, dec = _stack() |
| rep = enc.ingest_document("capitals", CORPUS["capitals"], topics=["capital", "city"]) |
| assert rep.n_sentences == 3 |
| assert rep.n_traces > 10 |
| tags = [tr.tag or "" for tr in enc.mem.traces] |
| assert any(t.startswith("NEXT:") for t in tags) |
| assert any(t.startswith("PREV:") for t in tags) |
| assert any(t.startswith("TOPIC:") for t in tags) |
| assert any(t.startswith("IDX:") for t in tags) |
|
|
|
|
| def test_encoder_deterministic(): |
| enc, _, _ = _stack() |
| a = enc.encode_text("Paris is the capital of France") |
| b = enc.encode_text("Paris is the capital of France") |
| assert a == b |
|
|
|
|
| def test_analogize_identity(): |
| enc, _, _ = _stack() |
| a = enc.encode_text("paris") |
| c = enc.encode_text("london") |
| assert analogize(a, a, c) == c |
|
|
|
|
| def test_decoder_recovers_ingested_tokens(): |
| enc, phi, dec = _stack() |
| enc.ingest_document("capitals", CORPUS["capitals"], topics=["capital"]) |
| bag = dec.decode_bag(enc.encode_text("Paris is the capital of France"), n=8, min_sim=-1.0) |
| joined = " ".join(bag.tokens) |
| assert "paris" in joined or "france" in joined or "capital" in joined |
|
|
|
|
| def test_compose_chain_does_not_rot_on_exact_items(): |
| enc, phi, dec = _stack() |
| enc.ingest_document("cortex", CORPUS["cortex"], topics=["palimpseste", "phi"]) |
| start = enc.encode_text("Palimpseste is an append-only hypervector cortex") |
| result = compose_chain( |
| enc.mem, |
| phi, |
| start, |
| steps=[("bundle", enc.encode_text("learning write"), None)], |
| config=ComposeConfig(floor=-0.2, max_hops=2), |
| ) |
| assert result.hv is not None |
| assert result.hops |
|
|
|
|
| def test_answer_uses_substrate_not_llm(): |
| enc, phi, dec = _stack() |
| enc.ingest_document("cortex", CORPUS["cortex"], topics=["palimpseste"]) |
| out = dec.answer("what is palimpseste") |
| assert isinstance(out.text, str) |
| |
| assert out.tokens is not None |
|
|
