Bench-max sprint 1a + sprint 3 + speed audit. Five wins, none of
them traded calibration.
UTF-16 surrogate fix (sprint 1a)
================================
Hermes occasionally emits text with lone UTF-16 surrogates. Bare
.encode('utf-8') raises UnicodeEncodeError on those, which aborted
the run with no Merkle root. Two errors per lattice mode in the
2026-05-02 bench were this exact path on the 'tell me about the
roman empire' question.
Fix: errors='surrogatepass' on the four sha256 helpers that hash
model-derived text, plus the two audit-chain encode sites in
store.py for defense-in-depth (audit body could carry user text in
some flows). The hash stays deterministic because WTF-8 bytes are
reversible & unique per input.
Touched:
aborist/qa/dag.py:_sha256_hex (the loud one)
aborist/qa/keys.py:_sha256
aborist/qa/evidence.py:_sha256_hex
aborist/store.py: chain_audit_events + append_audit
Predicted Δ on next bench: +1pp on lattice modes (the 2 errors
become valid runs).
Smoke fixture (sprint 3)
========================
bench/qa_questions_smoke.txt — 5 questions, all anchor classes,
each currently failing pointer mode 100% while JSON aces 100% per
the 2026-05-02 bench. Wired as 'make bench-qa-smoke', --n 1
--concurrency 4, ~30-90s wall-clock depending on vLLM warmth. The
inner loop for prompt iteration; the full 71-question sweep stays
the scoreboard.
Smoke verified: pointer=0/5 STRICT, JSON=5/5, quote=2/5. Confirms
the gap pattern from the journal.
Concurrency default
===================
Makefile bench-qa now defaults to BENCH_QA_CONCURRENCY=4 (was
sequential). Override via BENCH_QA_CONCURRENCY=N. Combined with
the --concurrency landing in 0870af6, full sweep drops from ~107
min projected to ~51 min actual.
pytest-xdist (test-speed)
=========================
Added pytest-xdist>=3.5 to dev extras. 'make test' now uses
-n auto (= one worker per logical CPU). Measured: 36s → 10s on
the 641-test suite. 3.6× speedup, no test changes required.
Bench-max scoreboard (predicted lift from this commit alone):
+1pp lattice modes (UTF fix)
+cycle-time enabler (smoke fixture, xdist)
no calibration cost — none of the verifier checks moved.
284 lines
11 KiB
Python
284 lines
11 KiB
Python
"""The 8-dim Merkle-AGI v9.8 cache_key.
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v9.8 invariant: no answer is reused unless all eight match and the
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record is live (not failed/stale/quarantined):
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1. source_root — content fingerprint of the document
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2. question_hash — SHA-256 of normalized question text
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3. model_profile_hash — model_id + revision + quantization
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4. conversation_hash — full canonical OpenAI messages array
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5. governance_policy_hash — sampling/policy parameters dict
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6. schema_version — aborist DB schema version
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7. canonicalization_version — text normalization rules
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8. chunking_version — chunker name & parameters
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Bumping ANY of these eight dimensions yields a distinct cache_key, so
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prior records cannot be served. This is the runtime drift detection
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the providence whitepaper compresses into "cache_key = source_root +
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':' + question_hash" — that's a simplification; the rigorous form is
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all eight dimensions hashed together.
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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 aborist.document import canonicalize
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def _sha256(s: str) -> str:
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# ``errors='surrogatepass'`` survives lone UTF-16 surrogates from
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# model output; same rationale as ``aborist.qa.dag._sha256_hex``.
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return hashlib.sha256(s.encode("utf-8", errors="surrogatepass")).hexdigest()
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def _canonical_json(obj) -> str:
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return json.dumps(obj, sort_keys=True, separators=(",", ":"), ensure_ascii=False)
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QUESTION_DEDUP_MODES = ("strict", "equivalence_class")
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DEFAULT_QUESTION_DEDUP = "equivalence_class"
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# Lookup-time fidelity. Decoupled from write-time `question_dedup`:
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# write determines under which `cache_key` a record lands; fidelity
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# determines which `cache_key`s a lookup will check.
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#
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# strict only the cache_key matching the agent's policy
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# is checked. No fallback. Audit-grade behavior.
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# equivalence_class primary cache_key checked first; if miss AND the
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# OTHER dedup mode produces a different cache_key,
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# the alternate is also checked. Lets a fast-cache
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# agent reuse records written under either mode.
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FIDELITY_MODES = ("strict", "equivalence_class")
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DEFAULT_FIDELITY = "equivalence_class"
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def canonical_question(
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question: str, *, mode: str = DEFAULT_QUESTION_DEDUP
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) -> str:
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"""Canonical form of `question` for the given dedup ``mode``.
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Two modes:
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- ``"equivalence_class"`` (default): four-step canonicalization —
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``canonicalize()`` (NFC + ws-collapse + strip ends), then
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lowercase, then trailing-punctuation strip, then standalone-article
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filter (``the``, ``a``, ``an``). All variants of "Who is THE
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Batman?" / "who is batman" / "who is X." collapse to one form.
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The default for chat-style agents that prefer fast cache hits.
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- ``"strict"``: only ``canonicalize()`` — NFC + ws-collapse + strip
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ends. Case-sensitive, punctuation-sensitive, article-sensitive.
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Maximum granularity. The choice for audit-grade agents that want
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every distinct phrasing to get its own answer.
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Exposed as a function so callers can dedup BEFORE hashing — e.g.
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inject the canonical form into the user message used for
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``conversation_hash``, while still sending the verbatim question to
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the LLM. Without this split ``"who is batman"``, ``"who is
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batman?"``, and ``"who is the batman?"`` collapse on
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``question_hash`` (under equivalence_class) but each hits
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``conversation_hash`` differently, missing cache.
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The choice of mode flows through ``policy["question_dedup"]`` into
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``governance_policy_hash`` so two agents under different modes
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write records under different ``cache_key``s — they coexist in
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parallel namespaces, never collide.
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"""
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if mode not in QUESTION_DEDUP_MODES:
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raise ValueError(
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f"question dedup mode must be one of {QUESTION_DEDUP_MODES}, got {mode!r}"
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)
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canon = canonicalize(question)
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if mode == "strict":
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return canon
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canon = canon.lower().rstrip(_QUESTION_TRAILING_STRIP)
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tokens = [t for t in canon.split() if t not in _QUESTION_ARTICLE_STRIP]
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return " ".join(tokens)
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def question_hash(
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question: str, *, mode: str = DEFAULT_QUESTION_DEDUP
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) -> str:
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"""SHA-256 of the dedup-mode-canonicalized question.
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See ``canonical_question`` for what each mode does. The hash is the
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SHA-256 of the canonical form. Bumping
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``_QUESTION_TRAILING_STRIP`` or ``_QUESTION_ARTICLE_STRIP`` (the
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equivalence-class strip sets) orphans prior cache records whose
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canonical question contained newly-stripped tokens; they live as
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history but won't be re-hit on lookup.
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Equivalence class examples (mode="equivalence_class")::
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"who is X" |
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"who is X?" |
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"Who Is X." | -> same question_hash
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"who is the X" |
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"who is a X" |
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"who is an X?" | (CJK question mark)
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Strict mode (mode="strict") distinguishes all of those.
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What's IN the trailing-strip set: ``.?!,;:`` (ASCII), ``?!。、``
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(CJK full-width), ``…`` (ellipsis). Pairs like ``"`` ``'`` ``)``
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``]`` ``}`` are NOT — naive one-sided stripping breaks balance.
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Apostrophes aren't either — ``X's`` is a different question from
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``X``.
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"""
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return _sha256(canonical_question(question, mode=mode))
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# Trailing punctuation that carries no semantic difference at the end
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# of a question. Order doesn't matter (rstrip walks char-by-char from
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# the right). Repeats handled trivially: ``X???`` → ``X``.
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#
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# ASCII: . ? ! , ; :
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# CJK: ? U+FF1F full-width question mark
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# ! U+FF01 full-width exclamation
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# 。 U+3002 ideographic full stop
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# 、 U+3001 ideographic comma
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# Other: … U+2026 horizontal ellipsis
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_QUESTION_TRAILING_STRIP = ".?!,;:?!。、…"
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# English articles stripped as standalone tokens after lowercasing. The
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# question equivalence class treats "the foo" and "foo" as the same
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# question — fox's 2026-04-29 catch: `who is the batman` & `who is
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# batman` produced different cache records under earlier rules. Tokens
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# are matched as EXACT lowercase strings, so substrings like "thesis"
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# (contains "the") stay untouched.
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#
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# Conservative on purpose: only ASCII English articles. "El", "la",
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# "los", "le", "les", "der", "die", "das" etc. are not stripped today.
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# Adding them when needed flows through the same equivalence-class
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# expansion the trailing-punctuation set went through.
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_QUESTION_ARTICLE_STRIP = frozenset({"the", "a", "an"})
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def model_profile_hash(
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model_id: str, revision: str = "", quantization: str = ""
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) -> str:
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"""SHA-256 of model identity. Bumping any field bumps the cache key."""
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return _sha256(f"{model_id}|{revision}|{quantization}")
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def conversation_hash(messages: list[dict]) -> str:
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"""SHA-256 of canonical JSON of the full OpenAI messages array.
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Order matters: a 6-turn dialogue arriving at the same final question
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produces a different hash than a single-turn ask.
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"""
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return _sha256(_canonical_json(messages))
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def governance_policy_hash(policy: dict) -> str:
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"""SHA-256 of canonical JSON of the sampling/policy dict.
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Includes temperature, top_p, max_tokens, and the system prompt — any
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of those changing means the answer is governed differently and the
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cache must miss.
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"""
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return _sha256(_canonical_json(policy))
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# Verifier-policy fields — the subset of `policy` that names what
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# the deterministic verifier does. Separate from the broader
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# `governance_policy_hash` so an auditor can answer "did the verifier
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# rules change?" with a single hash diff rather than scanning the
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# whole policy. See docs/cti-architecture.md §6 + the de-novo
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# synthesis (2026-05-01) on verifier-policy identity.
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#
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# Adding a field here bumps `verifier_policy_hash` for every cached
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# record on next lookup. Removing a field does the same. Reordering
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# does not (set membership, not list ordering).
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_VERIFIER_POLICY_FIELDS = frozenset({
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# Mode + parser identity
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"answer_mode",
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# Pointer-mode hard checks
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"claim_lattice_max_pointers_per_claim",
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"claim_lattice_min_citation_coverage",
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"claim_lattice_min_claim_content_tokens",
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"claim_lattice_lazy_anchor_demote_threshold",
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"claim_lattice_lazy_anchor_demote_min_pairs",
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"claim_lattice_allowed_source_roles",
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# Retrieval-side knob with verifier consequences
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"claim_lattice_max_chunks_per_source",
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# JSON variant identity
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"claim_lattice_use_guided_json",
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"claim_lattice_json_stop_sequences",
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# Warrant-lite (relation-question hard check, Ticket H, 2026-05-01)
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"claim_lattice_warrant_check_enabled",
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"claim_lattice_deflection_check_enabled",
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# Quote-mode entity policy
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"entity_policy",
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"entity_proximity_n",
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"entity_proximity_window",
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# Wikitext base-prose pinning (changes verifier surface)
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"base_version",
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})
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def verifier_policy_hash(policy: dict) -> str:
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"""SHA-256 of canonical JSON of the verifier-relevant subset of policy.
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Pulls `_VERIFIER_POLICY_FIELDS` out of `policy` and hashes only
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those. Empty dict → constant hash (`sha256("{}")`). Folded into
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`cache_key` as a 9th dimension so a verifier-policy change is
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observable from the cache_key alone, separate from
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`governance_policy_hash` which folds in temperature / top_p /
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prompts.
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The two hashes overlap (verifier fields ARE in the broader policy
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dict and so contribute to governance_policy_hash too). That's
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intentional — bumping a verifier rule bumps BOTH dimensions.
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Bumping a non-verifier field (e.g. temperature) bumps ONLY
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governance_policy_hash. The asymmetry is what makes the audit
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legible: which dimension changed answers a question that scanning
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the whole policy dict cannot.
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"""
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subset = {k: v for k, v in policy.items() if k in _VERIFIER_POLICY_FIELDS}
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return _sha256(_canonical_json(subset))
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def cache_key(
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source_root: str,
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question_hash_value: str,
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model_profile_hash_value: str,
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conversation_hash_value: str,
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governance_policy_hash_value: str,
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schema_version: str,
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canonicalization_version: str,
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chunking_version: str,
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verifier_policy_hash_value: str | None = None,
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) -> str:
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"""SHA-256 of the cache-identity dimensions joined with '|'.
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8-dim form (legacy): omit `verifier_policy_hash_value` (or pass
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None). The result matches pre-2026-05-01 cache identity and
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keeps backward compatibility with cached records written before
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the 9th dimension landed.
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9-dim form: pass `verifier_policy_hash_value` explicitly. Records
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written under the 9-dim form bind to the verifier-policy
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identity; lookups with a different verifier_policy_hash miss.
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The 9th dimension is the explicit "did the verifier rules
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change?" gate.
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Any drift in any dimension produces a distinct cache_key.
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"""
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parts = [
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source_root,
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question_hash_value,
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model_profile_hash_value,
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conversation_hash_value,
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governance_policy_hash_value,
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schema_version,
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canonicalization_version,
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chunking_version,
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]
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if verifier_policy_hash_value is not None:
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parts.append(verifier_policy_hash_value)
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return _sha256(
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"|".join(parts)
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)
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