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Operator's call, and it corrects a scope error rather than a bug: "this is a path for a user to go from a rulebook to a design system. we don't need to build this path in the app itself ... you should be the one that does the import ... going forward no one else should have to do such a migration." Right. Nobody starting from a design system will ever go rulebook -> system, so the whole path was permanent product code serving a single act on one install. Rule #22: remove it, don't flag it off. Gone from the service, the REST route, the MCP tool, the UI panel, the API client and its tests. There is a second consequence I had missed, and it is the better argument. The parser was WORSE at this than doing it by hand. `propose_tokens` leaves radius steps and type sizes valueless because "Small 4px" is not a hex and nothing here parses it — a limitation I documented carefully and shipped anyway. But that limitation only exists because the importer had to run unattended. Done as work rather than as a feature, those values are just read and written, and the result is a complete design system instead of one with a dozen blanks and a count explaining them. Scaffolding built around my own absence from the loop, when I am the loop. KEPT: `extract_expectations` and `design_expectations` in services/design_rulebook_import.py. The live drift panel still reads them until it is repointed at a resolved design system (#2295), and removing them now would take the /design page's only content with it. They go with that change, not this one.
233 lines
8.8 KiB
Python
233 lines
8.8 KiB
Python
"""Design-system expectations — turning rulebook prose into checkable claims.
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Milestone #251 step 2. The drift panel compares what the design rulebook SAYS
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against what the stylesheet and components actually DO. This module owns the
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first half: reading a rulebook's rules and extracting the claims that can be
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mechanically checked.
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WHY THIS LIVES SERVER-SIDE. The frontend has no test runner — `vue-tsc --noEmit`
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is the entire check — and this is the one genuinely fiddly piece of the feature.
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Extraction happens here where pytest can assert on it; the comparison itself is
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set arithmetic and stays in the browser, where the live token values are.
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WHY NOT NLP. Rule statements are prose written for humans, and they should stay
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that way — they are read by people far more often than they are parsed. So this
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extracts only what is unambiguous in ANY prose: the hex colours and CSS custom
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property names a rule mentions. Everything subtler (padding scales, type ramps)
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needs a rule author to opt into a structured form, which is deliberately left for
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when someone wants it rather than invented up front.
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RULE #115. Nothing here assumes a design rulebook exists, or that it is this
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operator's. An install designates one; an install that hasn't gets an empty
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result and a panel that explains itself.
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"""
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from __future__ import annotations
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import logging
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import re
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from dataclasses import dataclass, field
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from scribe.models.rulebook import Rule
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from scribe.services.settings import get_setting
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logger = logging.getLogger(__name__)
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# Which rulebook describes this install's design system. A plain setting rather
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# than a column: no migration, discoverable in the Settings UI (rule #25), and
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# honest about being a per-install choice rather than a property of the rulebook.
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DESIGN_RULEBOOK_SETTING = "design_rulebook_id"
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# `#abc` and `#aabbcc`, plus the 4/8-digit alpha forms.
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_HEX = re.compile(r"#([0-9a-fA-F]{3,8})\b")
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# A custom-property name as written in prose, including the slash shorthand the
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# rulebook uses: `--fs-radius-sm/md/lg/xl`, `--fs-obsidian/iron/slate/pewter`.
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_TOKEN = re.compile(r"(--[a-zA-Z][\w-]*(?:/[\w-]+)*)")
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# Sentence-ish split. Rules use semicolons as hard breaks as often as periods.
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_SENTENCE_SPLIT = re.compile(r"(?<=[.;])\s+|\n+")
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# Negation markers. Checked PER SENTENCE, which is the whole trick — see
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# _extract_from_sentence.
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_NEGATIONS = ("never", "not ", "no ", "avoid", "don't", "must not", "excluded")
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@dataclass
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class Expectation:
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"""One mechanically-checkable claim a rule makes."""
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kind: str # "token" | "color" | "prohibited_color"
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value: str # "--fs-obsidian" | "#14171a"
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rule_id: int
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rule_title: str
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context: str # the sentence it came from, for showing your work
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def as_dict(self) -> dict:
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return {
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"kind": self.kind,
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"value": self.value,
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"rule_id": self.rule_id,
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"rule_title": self.rule_title,
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"context": self.context,
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}
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@dataclass
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class ExpectationSet:
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rulebook_id: int | None = None
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expectations: list[Expectation] = field(default_factory=list)
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def as_dict(self) -> dict:
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return {
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"rulebook_id": self.rulebook_id,
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"expectations": [e.as_dict() for e in self.expectations],
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}
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def normalize_hex(value: str) -> str | None:
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"""Fold a hex colour to a comparable form, or None if it isn't one.
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Load-bearing for the whole comparison: the rulebook writes `#FFFFFF` and the
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code writes `#fff`, and those must compare equal or the single largest drift
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finding (#2275) reads as zero. Expands 3-digit shorthand and lowercases.
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Alpha forms (4 and 8 digit) keep their alpha — `#fff` and `#ffff` are not the
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same colour, and silently dropping the alpha would invent equality.
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"""
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match = _HEX.fullmatch(value.strip()) or _HEX.match(value.strip())
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if not match:
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return None
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digits = match.group(1).lower()
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if len(digits) in (3, 4):
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digits = "".join(c * 2 for c in digits)
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if len(digits) not in (6, 8):
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return None
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return f"#{digits}"
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def expand_token_shorthand(raw: str) -> list[str]:
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"""`--fs-radius-sm/md/lg/xl` -> the four names it stands for.
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The rulebook writes token families in a slash shorthand, and both forms it
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uses expand correctly under one rule: take everything up to and including the
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LAST hyphen of the first segment as the prefix, then append each alternative.
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--fs-radius-sm/md/lg/xl prefix `--fs-radius-` -> sm, md, lg, xl
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--fs-obsidian/iron/slate prefix `--fs-` -> obsidian, iron, slate
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--fs-dur-fast/base/slow prefix `--fs-dur-` -> fast, base, slow
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A name with no slash is returned as-is.
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"""
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if "/" not in raw:
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return [raw]
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head, *rest = raw.split("/")
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cut = head.rfind("-")
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if cut <= 1: # no hyphen beyond the leading `--`
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return [head, *rest]
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prefix = head[: cut + 1]
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return [head, *[f"{prefix}{part}" for part in rest if part]]
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def _is_negated(sentence: str) -> bool:
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return any(marker in sentence.lower() for marker in _NEGATIONS)
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def _extract_from_sentence(sentence: str, rule: Rule) -> list[Expectation]:
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"""Claims in ONE sentence, with negation scoped to that sentence.
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Sentence scope is what makes the prohibition detection usable. Rule 52 reads:
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"Text tokens: Parchment #E8E4D8 …, Vellum #C2BFB4 …, Ash #9C9A92 ….
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Pure white #FFFFFF is NEVER used as text color."
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Three colours the palette REQUIRES and one it FORBIDS, in one statement.
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Detecting negation across the whole statement would mark all four as
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forbidden; detecting it per sentence gets all four right.
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"""
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out: list[Expectation] = []
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negated = _is_negated(sentence)
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for match in _HEX.finditer(sentence):
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value = normalize_hex(match.group(0))
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if not value:
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continue
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out.append(Expectation(
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kind="prohibited_color" if negated else "color",
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value=value,
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rule_id=int(rule.id),
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rule_title=rule.title,
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context=sentence.strip(),
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))
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# Token names are not negated in practice — a rule says which tokens should
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# exist, never which must not — so they are recorded as expectations
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# regardless. If that ever changes, it needs its own kind rather than
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# borrowing the colour one.
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for match in _TOKEN.finditer(sentence):
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for name in expand_token_shorthand(match.group(1)):
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out.append(Expectation(
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kind="token",
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value=name,
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rule_id=int(rule.id),
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rule_title=rule.title,
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context=sentence.strip(),
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))
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return out
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def extract_expectations(rules: list[Rule]) -> list[Expectation]:
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"""Every checkable claim across a set of rules, deduped on (kind, value).
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First occurrence wins so the reported rule is the one that introduced the
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claim, which is usually the most specific place to send a reader.
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"""
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seen: set[tuple[str, str]] = set()
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out: list[Expectation] = []
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for rule in rules:
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text = " ".join(filter(None, [rule.statement or "", rule.how_to_apply or ""]))
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for sentence in _SENTENCE_SPLIT.split(text):
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if not sentence.strip():
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continue
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for expectation in _extract_from_sentence(sentence, rule):
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key = (expectation.kind, expectation.value)
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if key in seen:
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continue
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seen.add(key)
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out.append(expectation)
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return out
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async def get_design_rulebook_id(user_id: int) -> int | None:
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"""The rulebook this install designated as its design system, if any."""
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raw = (await get_setting(user_id, DESIGN_RULEBOOK_SETTING, "")).strip()
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if not raw:
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return None
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try:
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value = int(raw)
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except (TypeError, ValueError):
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return None
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return value if value > 0 else None
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async def design_expectations(user_id: int) -> ExpectationSet:
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"""Checkable claims from the designated design rulebook.
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Returns an empty set when no rulebook is designated — the normal case for
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any install but the one that set it up (rule #115). The caller shows an
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explanatory empty state rather than treating this as an error.
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"""
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rulebook_id = await get_design_rulebook_id(user_id)
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if rulebook_id is None:
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return ExpectationSet()
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from scribe.services import rulebooks as rulebooks_svc
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try:
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rules = await rulebooks_svc.list_rules(user_id, rulebook_id=rulebook_id)
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except Exception:
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logger.warning("Design rulebook %s could not be read", rulebook_id, exc_info=True)
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return ExpectationSet(rulebook_id=rulebook_id)
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return ExpectationSet(rulebook_id=rulebook_id, expectations=extract_expectations(rules))
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