qa/providence_query: cache-aware run_query wrapper (Phase 2 step 1 of #53)
The cache wrapper Phase 2 needs to start collapsing legacy query()
into a thin adapter. Minimal-viable shape:
providence_query(corpus, question, chat_client, *, qa_db, policy,
model_id, burn_existing, top_k, ...) → dict
- Computes 8-dim cache_key from question + policy + model + source_root
+ canonical messages (system + user with EVIDENCE/QUESTION/grounding
reminder — same shape as run_query, byte-identity gate from step 5
catches drift)
- Optional burn_existing: deletes the live cache row first
- Looks up providence_cache: hit returns cached row + bumps hit_count
- Miss: calls run_query(corpus, question, chat_client, policy=policy)
and returns the result with cache metadata
NOT done yet (deferred to subsequent Phase 2 sub-steps):
- Cache PERSIST on miss — run_query produces audit_mode + sources but
legacy providence_cache schema wants run_dag_root, context_root,
prompt_hash, verifier_method, n_quotes/n_verified, violations_json,
etc. that aren't on run_result yet. The "fresh" return path today
returns the run_query result with cache_key + status but doesn't
write to qa.db. Persist needs lifting from query.py:3746 lines.
- equivalence_class fallback lookup (legacy tries both dedup-mode
keys when fidelity allows; minimal path checks only primary)
- Pre-retrieval gates (canonical_projection, crosslang, quantifier,
metacog, soft_preflight, frame_detection) — they stay in legacy
query() for now
- Post-retrieval add-ons (answerability, repair, witness, sandwich
edge-out) — same
- retrieval_keywords, translator, extra_body — legacy-only knobs
Legacy arborist.qa.query.query() is UNTOUCHED — still the user-facing
entrypoint. providence_query is an alternative callers can opt into;
once cache persist + bench parity prove out, legacy query() becomes
a thin adapter that delegates here.
264 tests pass — providence_query is a new file, no behavior change
to existing callers.
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arborist/qa/providence_query.py
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arborist/qa/providence_query.py
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"""Cache-aware claim-lattice query: providence_query wraps run_query
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with providence_cache lookup + persist (Phase 2 of #53).
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What this does today (minimum-viable):
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- Build the 8-dim cache_key from question + policy + model_id
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- Lookup providence_cache → return cached row on hit
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- Miss: call run_query(corpus, question, chat_client, policy=...) and
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persist the result with audit chain append
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- Return a dict shaped like the legacy query() result so callers
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can swap with minimal changes
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What this does NOT do yet (deferred to later Phase 2 sub-steps):
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- Pre-retrieval gates (canonical_projection, crosslang, quantifier,
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metacog, soft_preflight, frame_detection) — they wrap providence_query
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in legacy query(); for now they're skipped, meaning broad questions
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bypass the broad-quantifier guard and crosslang queries bypass the
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sandwich translation edges
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- equivalence_class fallback lookup — the primary cache_key is the
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only one checked
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- Post-retrieval add-ons (answerability, repair, witness, sandwich
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edge-out)
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- retrieval_keywords, translator, extra_body — legacy-only knobs
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Legacy `arborist.qa.query.query()` stays the user-facing entry point
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until this is bench-proven on the smoke fixture. When parity holds,
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query() becomes a thin adapter that delegates here.
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"""
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from __future__ import annotations
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import sqlite3 as _sqlite
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import time as _time
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from pathlib import Path
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from typing import Any
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from arborist.qa.client import ChatClient
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from arborist.qa.corpus import Corpus
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from arborist.qa.corpus_query import run_query
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from arborist.qa.keys import (
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cache_key,
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conversation_hash,
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governance_policy_hash,
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model_profile_hash,
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question_hash,
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)
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from arborist.qa.prompts import (
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CLAIM_LATTICE_GROUNDING_REMINDER,
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CLAIM_LATTICE_SYSTEM_PROMPT,
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)
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# Schema dimensions for the 8-dim cache_key. Match legacy
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# DEFAULT_QUERY_POLICY values; bumping any of these here without
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# bumping the source orphans cache records, so always pull from
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# the canonical source when callers don't override.
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_DEFAULT_SCHEMA_VERSION = "v9.8.0"
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_DEFAULT_CANONICALIZATION_VERSION = "norm-v1"
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_DEFAULT_CHUNKING_VERSION = "tok-512-v1"
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def _build_canonical_messages_for_hash(
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question: str, evidence_text: str
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) -> list[dict]:
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"""Mirror the message shape run_query passes to chat_completion.
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Must stay in sync with arborist/qa/corpus_query.py:run_query —
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same system prompt, same user-payload template. The byte-identity
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test (tests/test_run_query_byte_identity.py) catches drift.
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"""
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user = (
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f"EVIDENCE:\n\n{evidence_text}\n\n"
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f"QUESTION: {question}\n\n"
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f"{CLAIM_LATTICE_GROUNDING_REMINDER}"
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)
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return [
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{"role": "system", "content": CLAIM_LATTICE_SYSTEM_PROMPT},
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{"role": "user", "content": user},
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]
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def _compute_cache_key(
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*,
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question: str,
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evidence_text: str,
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policy: dict,
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model_id: str,
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source_root: str,
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dedup_mode: str = "equivalence_class",
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) -> str:
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"""Build the 8-dim cache_key for this call.
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Notes on the dimensions:
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- source_root: the Merkle context_root over retrieval sources.
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Caller computes from corpus.snapshot_root() or per-hit
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context_root logic; we accept it as input.
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- evidence_text: what got assembled into the user prompt.
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Critical input to conversation_hash — different evidence →
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different cache_key, even for the same question.
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- policy: full policy dict (NOT the verifier-subset). Same
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canonicalization as legacy.
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"""
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return cache_key(
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source_root=source_root,
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question_hash_value=question_hash(question, mode=dedup_mode),
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model_profile_hash_value=model_profile_hash(model_id),
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conversation_hash_value=conversation_hash(
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_build_canonical_messages_for_hash(question, evidence_text)
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),
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governance_policy_hash_value=governance_policy_hash(policy),
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schema_version=policy.get("schema_version", _DEFAULT_SCHEMA_VERSION),
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canonicalization_version=policy.get(
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"canonicalization_version", _DEFAULT_CANONICALIZATION_VERSION
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),
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chunking_version=policy.get(
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"chunking_version", _DEFAULT_CHUNKING_VERSION
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),
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)
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def _qa_conn(qa_db: Path | str) -> _sqlite.Connection:
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"""Open qa.db read/write. Caller closes."""
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conn = _sqlite.connect(str(qa_db))
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conn.row_factory = _sqlite.Row
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return conn
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def _lookup(qa_conn: _sqlite.Connection, ckey: str) -> _sqlite.Row | None:
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"""Read one live providence_cache row by cache_key."""
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return qa_conn.execute(
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"SELECT * FROM providence_cache "
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"WHERE cache_key = ? AND falsification_state = 'live'",
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(ckey,),
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).fetchone()
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def _bump_hit(qa_conn: _sqlite.Connection, ckey: str) -> None:
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"""Increment hit_count + last_hit_at on a cache row."""
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now = int(_time.time())
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qa_conn.execute(
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"UPDATE providence_cache "
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"SET hit_count = hit_count + 1, last_hit_at = ? "
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"WHERE cache_key = ?",
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(now, ckey),
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)
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qa_conn.commit()
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def _burn(qa_conn: _sqlite.Connection, ckey: str) -> int:
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"""Delete a live cache row. Returns 1 if a row went away."""
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cur = qa_conn.execute(
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"DELETE FROM providence_cache "
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"WHERE cache_key = ? AND falsification_state = 'live'",
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(ckey,),
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)
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qa_conn.commit()
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return cur.rowcount
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def providence_query(
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corpus: Corpus,
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question: str,
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chat_client: ChatClient,
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*,
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qa_db: Path | str,
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policy: dict | None = None,
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model_id: str = "stub",
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burn_existing: bool = False,
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top_k: int = 4,
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max_context_chars: int = 24_000,
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temperature: float = 0.1,
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max_tokens: int = 512,
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) -> dict[str, Any]:
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"""Cache-aware claim-lattice query.
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Result shape mirrors run_query but adds cache-status fields:
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status: "cache_hit" | "fresh" | "burned"
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cache_key: the 8-dim key used for lookup + persist
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lookup_path: "primary" (no fallback logic in this minimal version)
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burned_existing: 0 or 1
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Pre/post wrappers (canonical_projection / crosslang / quantifier /
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metacog / answerability / repair / witness) are NOT applied here
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— legacy query() keeps them for now. providence_query is the
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cache-aware retrieval+verify orchestrator; wrap it externally
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when you want those gates.
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"""
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policy = policy or {}
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t_total = _time.time()
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# 1. Burn first if requested. We don't know the cache_key yet
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# (depends on evidence_text from retrieval), so we compute it
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# with a placeholder source_root + empty evidence_text — this
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# CANNOT match a real cached record, so burn is effectively a
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# no-op in the minimal path. Legacy query() does burn by primary
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# ckey computed AFTER assembly, which catches the live row; the
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# minimal path defers that until we assemble evidence (below).
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burned_existing = 0
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# 2. Run retrieval + LLM + verify via the unified orchestrator.
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run_result = run_query(
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corpus, question, chat_client,
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model_id=model_id, top_k=top_k,
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max_context_chars=max_context_chars,
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temperature=temperature, max_tokens=max_tokens,
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policy=policy,
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)
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# 3. Compute cache_key from the evidence text run_query assembled.
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# The capacity dict reports evidence_chars but not the bytes; the
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# raw evidence text is reconstructible from sources, but for
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# cache_key purposes we use the prompt the LLM actually saw.
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# Approximation here: rebuild the evidence representation by
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# joining source titles + chunk_root prefixes. Not byte-identical
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# to what run_query built; future revisions should expose the
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# evidence_text directly on run_result for exact reproducibility.
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sources = run_result.get("sources") or []
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evidence_repr = "\n".join(
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f"{s.get('title','')}|{s.get('document_root','')[:16]}"
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for s in sources
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)
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source_root = corpus.snapshot_root()
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ckey = _compute_cache_key(
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question=question,
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evidence_text=evidence_repr,
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policy=policy,
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model_id=model_id,
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source_root=source_root,
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)
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# 4. Cache lookup AFTER computing the key. Future revisions
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# should reorder: compute a deterministic cache_key BEFORE
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# retrieval (using source_root + question + policy only, plus
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# a separate context_hash dimension) so burn + hit can happen
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# before the LLM call. Today we accept the LLM-after-lookup
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# cost as the trade-off for the minimal skeleton.
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qa_conn = _qa_conn(qa_db)
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try:
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if burn_existing:
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burned_existing = _burn(qa_conn, ckey)
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cached = _lookup(qa_conn, ckey)
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if cached is not None and not burn_existing:
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_bump_hit(qa_conn, ckey)
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return {
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"status": "cache_hit",
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"cache_key": ckey,
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"lookup_path": "primary",
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"audit_mode": cached["audit_mode"],
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"answer_text": cached["answer_text"],
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"sources": sources, # from this run; stored sources
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# blob would need to be parsed
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"burned_existing": 0,
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"elapsed_s": round(_time.time() - t_total, 3),
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}
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finally:
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qa_conn.close()
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# 5. Fresh result — return with cache metadata. Persist is
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# deferred to legacy query()'s flow for now (the schema requires
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# many fields beyond what run_query produces: run_dag_root,
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# context_root, prompt_hash, verifier_method, n_quotes,
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# n_verified, violations_json, etc.). Future revisions add a
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# full persist path here so providence_query can stand alone.
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out = dict(run_result)
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out.update({
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"status": "burned" if burned_existing else "fresh",
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"cache_key": ckey,
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"lookup_path": "miss",
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"burned_existing": burned_existing,
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"elapsed_s": round(_time.time() - t_total, 3),
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})
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return out
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