"""chat/pack_grounding.py — pack-grounded surface for cold-start DEFINITION and RECALL intents (ADR-0048). When the ``UnknownDomainGate`` fires with ``source="empty_vault"`` — i.e. the runtime has no session evidence yet — the runtime would otherwise emit the universal ``_UNKNOWN_DOMAIN_SURFACE`` disclosure on every turn, including for terms that are explicitly compiled into the ratified cognition pack. This module supplies a narrow, auditable alternative: when the input's intent is ``DEFINITION`` or ``RECALL`` AND the intent's subject lemma is present in ``en_core_cognition_v1``, return a deterministic surface composed from the pack lexicon's ``semantic_domains`` for that lemma, explicitly tagged as pack-sourced. Design constraints (matching the seven axioms): - Geometry-first: the pack lookup is by lemma surface, but the ``semantic_domains`` were curated against the same versors the vocabulary carries; the surface refers only to the lemma and its curated descriptors — no synthesis, no LLM fallback. - Reconstruction-over-storage: the surface is reconstructed from the pack at call time; the lexicon is loaded once and cached because ratified packs are immutable. - Dual-correction: any lemma not in the pack returns ``None``; callers fall through to ``_UNKNOWN_DOMAIN_SURFACE`` unchanged. - Compilation-last: no tensors, no kernels — JSONL read and string formatting only. - Trust boundary: every surface produced here is explicitly tagged ``pack:en_core_cognition_v1`` so the audit contract distinguishes pack-grounded surfaces from vault-grounded surfaces and from the universal disclosure. """ from __future__ import annotations import json from functools import lru_cache from pathlib import Path PACK_ID: str = "en_core_cognition_v1" _PACK_LEXICON_PATH = ( Path(__file__).resolve().parent.parent / "language_packs" / "data" / PACK_ID / "lexicon.jsonl" ) @lru_cache(maxsize=1) def _pack_index() -> dict[str, tuple[str, ...]]: """Load the cognition pack lexicon once and return ``{lemma: semantic_domains}``. Ratified packs are immutable; safe to cache for the process lifetime. Returns an empty dict if the pack is unavailable — callers must treat a missing pack as "no pack-grounded surface available." """ if not _PACK_LEXICON_PATH.exists(): return {} out: dict[str, tuple[str, ...]] = {} for line in _PACK_LEXICON_PATH.read_text(encoding="utf-8").splitlines(): line = line.strip() if not line: continue try: entry = json.loads(line) except json.JSONDecodeError: continue lemma = entry.get("lemma") or entry.get("surface") if not lemma: continue domains = tuple(entry.get("semantic_domains", ())) if domains: out[lemma.lower()] = domains return out def pack_grounded_surface(lemma: str) -> str | None: """Return a deterministic pack-grounded surface for *lemma*, or ``None``. The surface format is fixed: "{lemma} — pack-grounded ({pack_id}): {d1}; {d2}; {d3}. No session evidence yet." Only the lemma and up to three semantic_domains from the pack are emitted; both come directly from the ratified pack lexicon, with no rewording. The trailing disclosure is the constant trust-boundary label that distinguishes pack-grounded surfaces from vault-grounded surfaces (which would carry session evidence) and from the universal "insufficient grounding" disclosure (which carries neither). Returns ``None`` when: - the lemma is empty or not a string, - the pack lexicon file is unavailable, - the lemma is not present in the pack, - the pack entry has no ``semantic_domains``. """ if not lemma or not isinstance(lemma, str): return None key = lemma.strip().lower() if not key: return None index = _pack_index() domains = index.get(key) if not domains: return None head = "; ".join(domains[:3]) return ( f"{key} — pack-grounded ({PACK_ID}): {head}. " f"No session evidence yet." ) def is_pack_lemma(lemma: str) -> bool: """Return True iff *lemma* has an entry with ``semantic_domains`` in the pack.""" if not lemma or not isinstance(lemma, str): return False return lemma.strip().lower() in _pack_index() _CORRECTION_TOPIC_STOPWORDS: frozenset[str] = frozenset({ # The meta-cognition lemma itself — we never echo it as the topic # because it's already the subject of the acknowledgement template. "correction", "correct", # Common dialogue markers / fillers that classify as pack lemmas # but don't carry topical signal in a correction utterance. "be", "have", }) def _extract_correction_topic_lemma(text: str) -> str | None: """Return the first pack-resident, topical lemma in *text*, or None. Deterministic: tokens are processed in left-to-right utterance order; the first token that is pack-resident AND not in the correction-stopword set wins. Stopwords filter out the meta- cognition lemma itself (``correction``) and dialogue fillers (``be``, ``have``) that classify as pack lemmas but carry no topical signal. Used by ``pack_grounded_correction_surface`` to weave the corrected claim's subject into the acknowledgement template. """ if not text or not isinstance(text, str): return None index = _pack_index() # Tokenize: lowercase, strip surrounding punctuation, skip empties. raw = text.lower() # Replace common punctuation with whitespace; preserve word boundaries. for ch in ",.;:!?\"'()[]{}": raw = raw.replace(ch, " ") for token in raw.split(): if not token: continue if token in _CORRECTION_TOPIC_STOPWORDS: continue if token in index: return token return None def pack_grounded_correction_surface(text: str | None = None) -> str | None: """ADR-0053 + ADR-0060 — cold-start CORRECTION acknowledgement. A CORRECTION intent (``"No, that's wrong"``, ``"Actually, X means Y"``) is meta-cognitive: it claims the previous turn was incorrect. On a cold-start session there is no prior turn to apply the correction to, so the doctrine-aligned response is **not** to define what correction is (that would be the DEFINITION path) but to acknowledge receipt and state explicitly that no prior turn exists in this session. Surface format (fixed templates, all atoms pack-sourced): - **Without topic** (text=None or no pack-resident lemma found): "correction received — pack-grounded ({pack_id}): {d1}; {d2}; {d3}. No prior turn in this session to correct yet." - **With topic** (text supplied AND pack lemma found): "correction received — pack-grounded ({pack_id}): {d1}; {d2}; {d3}. Noted topic: {lemma} ({td1}; {td2}). No prior turn in this session to correct yet." Every visible non-template token is either the lemma ``correction``, the corrected-topic lemma, or a verbatim ``semantic_domains`` string from the ratified pack. No inference; no rewording. The trailing disclosure (``No prior turn in this session to correct yet.``) is the constant trust-boundary label distinguishing this cold-start acknowledgement from the post-correction teaching repair path (``teaching/correction.py``) which engages once a prior turn exists. Returns ``None`` if the pack is unavailable or has no entry for ``correction`` — callers fall through to the universal disclosure unchanged. """ index = _pack_index() domains = index.get("correction") if not domains: return None head = "; ".join(domains[:3]) topic_lemma = _extract_correction_topic_lemma(text) if text else None if topic_lemma is not None: topic_domains = index.get(topic_lemma, ()) topic_head = "; ".join(topic_domains[:2]) if topic_domains else "" if topic_head: return ( f"correction received — pack-grounded ({PACK_ID}): {head}. " f"Noted topic: {topic_lemma} ({topic_head}). " f"No prior turn in this session to correct yet." ) return ( f"correction received — pack-grounded ({PACK_ID}): {head}. " f"Noted topic: {topic_lemma}. " f"No prior turn in this session to correct yet." ) return ( f"correction received — pack-grounded ({PACK_ID}): {head}. " f"No prior turn in this session to correct yet." ) _PROCEDURE_TOPIC_STOPWORDS: frozenset[str] = frozenset({ # Pack-resident lemmas that classify but carry no topical signal # in a procedure utterance — dialogue fillers / copulae. "be", "have", }) def _extract_procedure_topic_lemma(subject_text: str) -> str | None: """Return the **last** pack-resident topical lemma in *subject_text*. Procedure subjects emerge from the intent classifier as verb phrases (e.g. ``"define a concept"``, ``"correct an error"``, ``"verify a claim"``). The procedure verb tends to be the first pack-resident lemma; the *topic* of the procedure tends to be the last. Selecting the last pack-resident lemma captures the user's actual subject of interest without requiring POS tagging or syntactic analysis. Deterministic: tokens are processed left-to-right; the *last* token that is pack-resident AND not in the stopword set wins. Stopwords filter only dialogue fillers (``be`` / ``have``); pack-resident verbs (``define``, ``verify``, ``correct``, etc.) are NOT stopworded — when a procedure utterance contains only one pack-resident lemma and that lemma is the verb, the verb is the topical anchor by elimination. """ if not subject_text or not isinstance(subject_text, str): return None index = _pack_index() raw = subject_text.lower() for ch in ",.;:!?\"'()[]{}": raw = raw.replace(ch, " ") last_match: str | None = None for token in raw.split(): if not token: continue if token in _PROCEDURE_TOPIC_STOPWORDS: continue if token in index: last_match = token return last_match def pack_grounded_procedure_surface(subject_text: str) -> str | None: """ADR-0061 — cold-start PROCEDURE pack-grounded surface. A PROCEDURE intent (``"How do I X?"``, ``"How can I Y?"``) requests step-by-step guidance. Procedural chains are not part of the reviewed teaching corpus today (teaching chains cover CAUSE and VERIFICATION intents only — see ``chat.teaching_grounding._VALID_INTENTS``). Rather than fall through to the universal disclosure on every procedure question, this composer emits a pack-grounded acknowledgement that surfaces the topical lemma of the procedure and notes explicitly that step-by-step guidance is not yet ratified — preserving honesty while grounding the user's topic in pack semantics. Surface format (fixed template, all atoms pack-sourced): "procedure-grounded ({pack_id}): {lemma} ({d1}; {d2}). Step-by-step guidance for {lemma} is not yet ratified in this session." The trailing clause is the constant trust-boundary label, analogous to ``"No prior turn in this session to correct yet."`` in the CORRECTION acknowledgement (ADR-0053 / ADR-0060). Returns ``None`` if no pack-resident lemma is found in *subject_text* — callers fall through to the universal disclosure unchanged (preserves the ADR-0053 honesty contract for the fully-unknown case). """ lemma = _extract_procedure_topic_lemma(subject_text) if lemma is None: return None index = _pack_index() domains = index.get(lemma, ()) if not domains: return None head = "; ".join(domains[:2]) return ( f"procedure-grounded ({PACK_ID}): {lemma} ({head}). " f"Step-by-step guidance for {lemma} is not yet ratified in this session." ) def pack_grounded_comparison_surface( lemma_a: str, lemma_b: str ) -> str | None: """ADR-0050 — deterministic pack-grounded surface for COMPARISON intent. Returns a surface that composes each lemma's pack semantic_domains side-by-side, with no rewording or inference: "{a} (d_a1; d_a2) contrasts with {b} (d_b1; d_b2) — pack-grounded ({pack_id}). No session evidence yet." Up to two semantic_domains per side are emitted to keep the surface compact. All visible tokens are either the lemmas themselves or verbatim pack strings; the verb "contrasts with" is the fixed COMPARISON template constant (mirroring the relation predicate `contrasts_with` already humanised by ``humanize_predicate``). Returns ``None`` when: - either lemma is empty or not a string, - either lemma is not present in the pack, - the two lemmas are identical (a comparison between a term and itself carries no contrastive evidence — defer to the single-lemma ``pack_grounded_surface`` path or to the universal disclosure). """ if not lemma_a or not isinstance(lemma_a, str): return None if not lemma_b or not isinstance(lemma_b, str): return None key_a = lemma_a.strip().lower() key_b = lemma_b.strip().lower() if not key_a or not key_b: return None if key_a == key_b: return None index = _pack_index() domains_a = index.get(key_a) domains_b = index.get(key_b) if not domains_a or not domains_b: return None head_a = "; ".join(domains_a[:2]) head_b = "; ".join(domains_b[:2]) return ( f"{key_a} ({head_a}) contrasts with {key_b} ({head_b}) " f"— pack-grounded ({PACK_ID}). No session evidence yet." )