- Implemented PluginBlocks component to render various plugin UI elements. - Created SuitePicker for selecting test suites and questions. - Introduced usePluginUI hook for managing plugin UI state and manifest. - Developed DocsPage for comprehensive plugin framework documentation. - Added PluginPage to render pages declared by plugins based on the current path.
613 lines
23 KiB
Python
613 lines
23 KiB
Python
"""General-purpose instruction-compliance grader.
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Scores *any* answer, not just code. The suite prompts state their own
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requirements — "return a markdown table", "output only valid JSON", "exactly 40
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words", "if it is impossible, say so", numbered lists of deliverables — so the
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rubric can be derived from the prompt itself rather than hard-coded per
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question. Nothing here is language- or domain-specific.
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Ten check families, each contributing a fractional score:
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=========================== ==================================================
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``structure/json`` A required JSON object is present and parses.
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``structure/table`` A required markdown table is present.
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``structure/code`` A required fenced code block is present (or, when
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the prompt forbids fences, that none appears).
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``coverage/enumerated`` Fraction of the prompt's numbered deliverables the
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answer visibly addresses.
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``coverage/keyterms`` Required literals — backticked symbols, short
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quoted headings and keys — actually appear.
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``constraint/forbidden`` Symbols the prompt bans are absent.
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``constraint/length`` A stated word budget is respected.
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``behaviour/abstention`` When a prompt demands "say so" / "do not guess" /
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"do not comply", the answer actually does.
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``quality/degeneration`` Not empty, not looping, not truncated mid-sentence.
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``quality/substance`` Length is proportional to what was asked for.
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=========================== ==================================================
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Design notes
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------------
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* **Checks are fractional, not pass/fail.** Answering four of five numbered
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parts scores 0.8 on that check rather than zero, so partial work is visible.
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* **Only applicable checks count.** A prompt that never mentions JSON is not
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scored on JSON. The divisor is the weight of the checks that actually fired.
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* **Ambiguity abstains rather than punishes.** A word budget is only enforced
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when it unambiguously applies to the whole answer — a prompt asking for two
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summaries of different lengths skips the check instead of failing it.
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* **Negation is handled everywhere.** "Do not use ``INIntent``" names a symbol
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that must be *absent*; "no markdown code fence" inverts the code-block check.
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Treating every requirement as positive would penalise correct answers.
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* **Degeneration is always checkable**, so unlike the previous version this
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grader effectively never abstains on a non-empty answer.
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"""
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from __future__ import annotations
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import json
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import re
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from dataclasses import dataclass
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from typing import Dict, List, Optional, Tuple
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from plugin_api import Grade, RunRecord, TestRecord
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NAME = "Instruction compliance"
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VERSION = "2.0.1"
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DESCRIPTION = "Grades any answer against the constraints its own prompt states."
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ENABLED = True
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# --------------------------------------------------------------------------
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# Check primitive
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# --------------------------------------------------------------------------
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@dataclass
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class Check:
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"""One graded dimension. ``value`` is 0.0-1.0, not a bool."""
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name: str
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value: float
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weight: float
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detail: str = ""
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@property
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def passed(self) -> bool:
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return self.value >= 0.999
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# --------------------------------------------------------------------------
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# Prompt parsing
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# --------------------------------------------------------------------------
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_BACKTICK = re.compile(r"`([^`\n]{2,120})`")
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# Single-token quoted spans are output requirements — JSON keys, headings,
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# field names ("Origins", "sections", "key_term"). Multi-word quoted spans are
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# almost always material being *discussed*: a line from the source text, or a
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# manipulative phrase the answer is asked to identify and quote back. Treating
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# those as requirements (or, when the sentence is negated, as prohibitions)
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# punishes exactly the answers that do the right thing.
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_QUOTED = re.compile(r"\"([^\"\n]{3,32})\"")
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_QUOTED_STOPWORDS = frozenset(
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{"she", "her", "hers", "his", "him", "they", "them", "the", "and", "but", "for", "you", "its"}
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)
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_NEGATION_RE = re.compile(
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r"\b(?:do|does|did|should|shall|must|will|would|can|could|may)\s*(?:n[o']t|not|never)\b"
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r"|\bn't\b",
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re.IGNORECASE,
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)
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_NEGATION_PHRASES = (
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"avoid",
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"instead of",
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"rather than",
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"without using",
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"no longer",
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"deprecated",
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"stop using",
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"get rid of",
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"remove the",
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"not the old",
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"old system",
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)
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# Language nouns rather than the bare word "code": a prompt saying "no markdown
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# code fence" must not read as a request for code. "function" is excluded too —
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# it is just as often a verb ("phrases that function to lower your guard"), and
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# every real code question here is caught by a language name or a `def name(`.
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_CODE_NOUNS = re.compile(
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r"\b(?:python|javascript|typescript|java|swift|rust|sql|regex|signature|algorithm)\b"
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r"|\bdef\s+\w+\s*\(",
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re.IGNORECASE,
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)
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_NO_FENCE = re.compile(
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r"no (?:markdown )?(?:code )?fence|without a code fence|no fenced code|do not (?:use|include) a (?:markdown )?code fence",
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re.IGNORECASE,
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)
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_JSON_REQUIRED = re.compile(r"\bvalid JSON\b|\bJSON object\b|\bas JSON\b|\bJSON format\b", re.IGNORECASE)
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_JSON_ONLY = re.compile(
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r"only (?:a |one )?(?:single )?valid json|no prose before or after|output only", re.IGNORECASE
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)
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_TABLE_REQUIRED = re.compile(r"\btable\b", re.IGNORECASE)
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_EXACT_WORDS = re.compile(r"exactly (\d[\d,]*)\s+words", re.IGNORECASE)
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_RANGE_WORDS = re.compile(
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r"(?:between\s+)?(\d[\d,]*)\s*(?:to|and|-|–|—)\s*(\d[\d,]*)\s+words", re.IGNORECASE
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)
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# Phrases that mean a length constraint applies per-item, not to the whole answer.
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_MULTI_OUTPUT = re.compile(r"\btwice\b|\btwo summaries\b|\beach\b.{0,40}\bwords\b", re.IGNORECASE)
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# An abstention demand is only gradeable when it is unconditional. "If the
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# constraints are contradictory, say so" does not require an abstention — it
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# requires one *only if* the condition holds, and whether it holds is exactly
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# what the grader cannot determine. Scoring those would fail every correct
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# answer to a solvable puzzle, so conditional demands are skipped instead.
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_ABSTENTION_EXPECTED = re.compile(
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r"do not (?:simply )?guess|don't guess|do not invent|do not fabricate"
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r"|do not (?:simply )?comply|state your refusal|admission of ignorance"
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r"|rather than (?:making up|inventing|guessing)",
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re.IGNORECASE,
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)
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_CONDITIONAL = re.compile(r"\b(?:if|where|when|unless|should)\b", re.IGNORECASE)
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# A second gate. "Do not invent an assignment that satisfies only some clues"
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# is an unconditional instruction, but the question is a solvable logic puzzle —
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# a correct answer states the solution and never abstains. Requiring the prompt
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# to be *about* refusal or ignorance keeps the check on the questions where
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# abstaining is the right answer, not merely a permitted one.
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_ABSTENTION_TOPIC = re.compile(
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r"unanswerable|ignorance|do not (?:simply )?comply|jailbreak|refusal|refuse"
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r"|declines?|not determinable|fabricated premise|knowledge cutoff|do not (?:simply )?guess",
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re.IGNORECASE,
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)
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_ABSTENTION_MARKERS = (
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"not determinable",
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"cannot be determined",
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"cannot determine",
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"not possible to determine",
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"no information",
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"not available",
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"does not exist",
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"do not have",
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"don't have",
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"i cannot",
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"i can't",
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"i won't",
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"i will not",
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"unable to",
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"i do not know",
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"i don't know",
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"fabricated",
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"no such",
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"decline",
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"refuse",
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"not answerable",
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"beyond my",
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"knowledge cutoff",
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"physically impossible",
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"inconsistent",
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"contradictory",
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"not verifiable",
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)
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_SENTENCE_SPLIT = re.compile(r"(?<=[.!?:])\s+|\n+")
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_NUMBERED_LINE = re.compile(r"^\s{0,6}(\d{1,2})[.)]\s+\S", re.MULTILINE)
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# PART/STAGE label deliverables. SECTION is deliberately excluded: prompts use
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# it to label supplied source material, which is not something to answer.
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_LABELLED_SECTION = re.compile(r"^\s*(?:PART|STAGE)\s+([A-Z]|\d{1,2})\b", re.MULTILINE)
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_HEADING_LINE = re.compile(r"^\s*(?:#{1,6}\s+\S|\*\*[^*\n]{2,60}\*\*\s*:?\s*$)", re.MULTILINE)
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# Prompt-side matching stays line-anchored. Response-side is deliberately
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# looser: it also accepts a marker after a sentence break (models run numbered
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# answers together in a paragraph) and one wrapped in markdown emphasis or a
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# heading — "**1. …**" and "### 1. …" are how most models number their sections,
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# and missing those undercounts coverage badly.
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_RESPONSE_MARKER = re.compile(r"(?:^|[\n.!?]\s*)[*_#>\s-]{0,8}(\d{1,2})[.)]\s+\S", re.MULTILINE)
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_FENCE = re.compile(r"```")
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def _sentences(text: str) -> List[str]:
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return [s for s in _SENTENCE_SPLIT.split(text) if s.strip()]
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def _is_negated(sentence: str) -> bool:
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lowered = sentence.lower()
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return bool(_NEGATION_RE.search(lowered)) or any(p in lowered for p in _NEGATION_PHRASES)
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def _literal_requirements(prompt: str) -> Tuple[List[str], List[str]]:
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"""Split backticked and short-quoted spans into (required, forbidden)."""
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required: List[str] = []
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forbidden: List[str] = []
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for sentence in _sentences(prompt):
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bucket = forbidden if _is_negated(sentence) else required
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for raw in _BACKTICK.findall(sentence):
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symbol = raw.strip()
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if _usable_literal(symbol):
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_add(bucket, symbol)
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for raw in _QUOTED.findall(sentence):
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symbol = raw.strip().rstrip(".,;:")
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if " " in symbol or symbol.lower() in _QUOTED_STOPWORDS:
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continue # prose being discussed, not a required output token
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if _usable_literal(symbol):
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_add(bucket, symbol)
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# A literal demanded in one place and banned in another is ambiguous.
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contested = set(required) & set(forbidden)
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return (
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[s for s in required if s not in contested],
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[s for s in forbidden if s not in contested],
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)
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def _usable_literal(symbol: str) -> bool:
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"""Reject punctuation-only spans and single characters.
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Single characters matter: ``must not contain the letter "z"`` would
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otherwise ban every 'z' in the answer, including the one in the sentence
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explaining the rule.
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"""
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if len(symbol) < 2:
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return False
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return any(ch.isalnum() or ch in "@\\/_" for ch in symbol)
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def _add(bucket: List[str], symbol: str) -> None:
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if symbol not in bucket:
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bucket.append(symbol)
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def _requires_abstention(prompt: str) -> bool:
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"""True only for an *unconditional* demand to refuse or admit ignorance."""
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if not _ABSTENTION_TOPIC.search(prompt):
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return False
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return any(
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_ABSTENTION_EXPECTED.search(s) and not _CONDITIONAL.search(s) for s in _sentences(prompt)
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)
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def _enumerated_demands(prompt: str) -> int:
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"""How many numbered deliverables the prompt asks for.
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Counts the longest run starting at 1, so an inline reference to "step 3"
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does not inflate the total.
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"""
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seen = {int(n) for n in _NUMBERED_LINE.findall(prompt)}
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count = 0
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while count + 1 in seen:
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count += 1
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# Some prompts structure their deliverables as "PART A / PART B" or
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# "STAGE 1 / STAGE 2" instead of a numbered list.
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labelled = len({m.upper() for m in _LABELLED_SECTION.findall(prompt)})
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return max(count, labelled)
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def _word_budget(prompt: str) -> Optional[Tuple[int, int]]:
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"""A (low, high) word range for the whole answer, or None if ambiguous.
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Returns None when the prompt asks for several separately-counted outputs —
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a per-section budget cannot be checked against the total.
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"""
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if _MULTI_OUTPUT.search(prompt):
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return None
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ranges: List[Tuple[int, int]] = []
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for sentence in _sentences(prompt):
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if "each" in sentence.lower():
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continue # per-item, not global
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for match in _RANGE_WORDS.finditer(sentence):
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low, high = (int(g.replace(",", "")) for g in match.groups())
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if low <= high:
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ranges.append((low, high))
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for match in _EXACT_WORDS.finditer(sentence):
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exact = int(match.group(1).replace(",", ""))
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ranges.append((exact, exact))
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# Two different budgets in one prompt means neither is the global one.
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unique = {r for r in ranges}
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if len(unique) != 1:
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return None
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return ranges[0]
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# --------------------------------------------------------------------------
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# Response inspection
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# --------------------------------------------------------------------------
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_TABLE_ROW = re.compile(r"^\s*\|.*\|\s*$", re.MULTILINE)
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_TABLE_RULE = re.compile(r"^\s*\|[\s:|-]*-[\s:|-]*\|\s*$", re.MULTILINE)
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def _has_table(text: str) -> bool:
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return bool(_TABLE_RULE.search(text)) and len(_TABLE_ROW.findall(text)) >= 2
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def _strip_fences(text: str) -> str:
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return re.sub(r"```[a-zA-Z0-9]*\n?|```", "", text)
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def _extract_json(text: str) -> Optional[object]:
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"""Parse the outermost JSON object in a response, fences tolerated."""
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candidate = _strip_fences(text).strip()
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start, end = candidate.find("{"), candidate.rfind("}")
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if start == -1 or end <= start:
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return None
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try:
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return json.loads(candidate[start : end + 1])
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except (json.JSONDecodeError, ValueError):
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return None
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def _word_count(text: str) -> int:
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"""Words outside fenced code blocks — prose length, not payload length."""
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prose = re.sub(r"```.*?```", " ", text, flags=re.DOTALL)
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return len(re.findall(r"\b[\w'’-]+\b", prose))
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def _answered_sections(response: str) -> int:
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"""How many distinct deliverables the answer visibly separates out.
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Matching is looser than on the prompt side: weaker models often run their
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numbered answers together inside a paragraph ("1. Yes. 2. No.") rather than
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on separate lines, and that should still count as having addressed them.
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"""
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numbered = {int(n) for n in _RESPONSE_MARKER.findall(response)}
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consecutive = 0
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while consecutive + 1 in numbered:
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consecutive += 1
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return max(consecutive, len(_HEADING_LINE.findall(response)))
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def _repetition_ratio(text: str) -> float:
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"""Fraction of distinct 6-grams. Low means the model is looping."""
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tokens = re.findall(r"\w+", text.lower())
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if len(tokens) < 60:
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return 1.0
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grams = [tuple(tokens[i : i + 6]) for i in range(len(tokens) - 5)]
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return len(set(grams)) / len(grams)
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def _looks_truncated(text: str) -> bool:
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stripped = text.rstrip()
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if not stripped:
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return True
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if stripped.count("```") % 2 == 1:
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return True # unclosed code fence
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return stripped[-1] not in ".!?)]}\"'`:*"
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# --------------------------------------------------------------------------
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# Grading
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# --------------------------------------------------------------------------
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def _build_checks(prompt: str, response: str) -> List[Check]:
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checks: List[Check] = []
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# --- quality/degeneration --------------------------------------------
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ratio = _repetition_ratio(response)
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truncated = _looks_truncated(response)
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degeneration, notes = 1.0, []
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if ratio < 0.5:
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degeneration -= 0.6
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notes.append(f"repetitive output ({ratio:.0%} distinct 6-grams)")
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elif ratio < 0.7:
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degeneration -= 0.25
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notes.append(f"some looping ({ratio:.0%} distinct 6-grams)")
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if truncated:
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degeneration -= 0.3
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notes.append("ends mid-sentence or leaves a code fence open")
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checks.append(
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Check("quality/degeneration", max(0.0, degeneration), 2.0, "; ".join(notes))
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)
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# --- quality/substance ------------------------------------------------
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demands = _enumerated_demands(prompt)
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words = _word_count(response)
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# ~15 words per deliverable, capped: this guards one-line non-answers, and
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# is not a reward for padding. A terse but complete answer must clear it.
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expected = min(300, 15 * demands) if demands else 80
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substance = min(1.0, words / expected) if expected else 1.0
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checks.append(
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Check(
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"quality/substance",
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substance,
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1.0,
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"" if substance >= 0.999 else f"{words} words for {demands or 'an open'} deliverable(s)",
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)
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)
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# --- coverage/enumerated ---------------------------------------------
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if demands >= 2:
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answered = _answered_sections(response)
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value = min(1.0, answered / demands)
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checks.append(
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Check(
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"coverage/enumerated",
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value,
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2.0,
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"" if value >= 0.999 else f"addressed {answered} of {demands} numbered parts",
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)
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)
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# --- structure/json ---------------------------------------------------
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if _JSON_REQUIRED.search(prompt):
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parsed = _extract_json(response)
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if parsed is None:
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checks.append(Check("structure/json", 0.0, 2.0, "no parseable JSON object"))
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else:
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value, detail = 1.0, ""
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if _JSON_ONLY.search(prompt):
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bare = response.strip()
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if not (bare.startswith("{") and bare.endswith("}")):
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value, detail = 0.6, "JSON present but wrapped in prose or fences"
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checks.append(Check("structure/json", value, 2.0, detail))
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# --- structure/table --------------------------------------------------
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if _TABLE_REQUIRED.search(prompt):
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present = _has_table(response)
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checks.append(
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Check("structure/table", 1.0 if present else 0.0, 1.0, "" if present else "no markdown table")
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)
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# --- structure/code ---------------------------------------------------
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fenced = bool(_FENCE.search(response))
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if _NO_FENCE.search(prompt):
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checks.append(
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Check(
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"structure/code",
|
||
0.0 if fenced else 1.0,
|
||
1.0,
|
||
"used a code fence the prompt forbade" if fenced else "",
|
||
)
|
||
)
|
||
elif _CODE_NOUNS.search(prompt):
|
||
checks.append(
|
||
Check("structure/code", 1.0 if fenced else 0.0, 1.0, "" if fenced else "no fenced code block")
|
||
)
|
||
|
||
# --- coverage/keyterms and constraint/forbidden -----------------------
|
||
required, forbidden = _literal_requirements(prompt)
|
||
if required:
|
||
hits = [s for s in required if s.lower() in response.lower()]
|
||
value = len(hits) / len(required)
|
||
missing = [s for s in required if s not in hits][:5]
|
||
checks.append(
|
||
Check(
|
||
"coverage/keyterms",
|
||
value,
|
||
1.5,
|
||
"" if value >= 0.999 else "missing " + ", ".join(f"`{m}`" for m in missing),
|
||
)
|
||
)
|
||
if forbidden:
|
||
used = [s for s in forbidden if s.lower() in response.lower()]
|
||
value = 1.0 - len(used) / len(forbidden)
|
||
checks.append(
|
||
Check(
|
||
"constraint/forbidden",
|
||
value,
|
||
1.5,
|
||
"" if not used else "used banned " + ", ".join(f"`{u}`" for u in used[:5]),
|
||
)
|
||
)
|
||
|
||
# --- constraint/length ------------------------------------------------
|
||
budget = _word_budget(prompt)
|
||
if budget:
|
||
low, high = budget
|
||
# 10% grace: a 402-word answer to a "400 word" prompt is compliant.
|
||
slack = max(2, round(low * 0.1))
|
||
if low - slack <= words <= high + slack:
|
||
checks.append(Check("constraint/length", 1.0, 1.0))
|
||
else:
|
||
target = f"{low}" if low == high else f"{low}-{high}"
|
||
over = words - high if words > high else low - words
|
||
value = max(0.0, 1.0 - over / max(low, 1))
|
||
checks.append(
|
||
Check("constraint/length", value, 1.0, f"{words} words against a {target}-word budget")
|
||
)
|
||
|
||
# --- behaviour/abstention ---------------------------------------------
|
||
if _requires_abstention(prompt):
|
||
lowered_response = response.lower()
|
||
found = [m for m in _ABSTENTION_MARKERS if m in lowered_response]
|
||
checks.append(
|
||
Check(
|
||
"behaviour/abstention",
|
||
1.0 if found else 0.0,
|
||
1.5,
|
||
"" if found else "prompt required a refusal or an admission of ignorance; none found",
|
||
)
|
||
)
|
||
|
||
return checks
|
||
|
||
|
||
def grade(test: TestRecord):
|
||
response = (test.response or "").strip()
|
||
if not response:
|
||
return None # nothing to judge
|
||
|
||
checks = _build_checks(test.prompt, response)
|
||
if not checks:
|
||
return None
|
||
|
||
total_weight = sum(c.weight for c in checks)
|
||
score = sum(c.value * c.weight for c in checks) / total_weight
|
||
|
||
failures = [f"{c.name}: {c.detail or 'failed'}" for c in checks if not c.passed]
|
||
passed = sum(1 for c in checks if c.passed)
|
||
|
||
return Grade(
|
||
score=score,
|
||
label=f"{passed}/{len(checks)} checks",
|
||
notes="; ".join(failures) if failures else "All derived constraints met.",
|
||
)
|
||
|
||
|
||
# --------------------------------------------------------------------------
|
||
# Reporting
|
||
# --------------------------------------------------------------------------
|
||
|
||
|
||
def _checks_for(run: RunRecord) -> Dict[int, List[Check]]:
|
||
"""Recompute checks per question so the report can break them down."""
|
||
detail: Dict[int, List[Check]] = {}
|
||
for test in run.tests:
|
||
if test.ok and test.response:
|
||
detail[test.index] = _build_checks(test.prompt, test.response.strip())
|
||
return detail
|
||
|
||
|
||
def report_sections(run: RunRecord):
|
||
detail = _checks_for(run)
|
||
if not detail:
|
||
return None
|
||
|
||
# Which dimensions the model struggled with, across the whole run.
|
||
totals: Dict[str, List[float]] = {}
|
||
for checks in detail.values():
|
||
for check in checks:
|
||
totals.setdefault(check.name, []).append(check.value)
|
||
|
||
summary = [
|
||
"Every score below is derived from constraints the prompt states "
|
||
"explicitly. A low score means the answer did not do what it was told, "
|
||
"which is not the same as being wrong — read the answer before treating "
|
||
"it as a failure.",
|
||
"",
|
||
"| Check | Questions | Mean | Failed outright |",
|
||
"| --- | --- | --- | --- |",
|
||
]
|
||
for name in sorted(totals, key=lambda n: sum(totals[n]) / len(totals[n])):
|
||
values = totals[name]
|
||
mean = sum(values) / len(values)
|
||
zeros = sum(1 for v in values if v < 0.001)
|
||
summary.append(f"| `{name}` | {len(values)} | {mean:.0%} | {zeros} |")
|
||
|
||
misses = []
|
||
for test in run.tests:
|
||
for entry in run.grades.get(test.index, []):
|
||
if entry.grader == NAME and entry.grade.score < 1.0:
|
||
misses.append((test, entry.grade))
|
||
|
||
blocks = [("## Compliance by check", "\n".join(summary))]
|
||
|
||
if misses:
|
||
lines = [
|
||
"| # | Question | Score | What was missed |",
|
||
"| --- | --- | --- | --- |",
|
||
]
|
||
for test, grade_ in misses:
|
||
problem = grade_.notes.replace("|", "\\|").replace("\n", " ")
|
||
title = test.title.replace("|", "\\|")
|
||
lines.append(f"| {test.index} | {title} | {grade_.score:.0%} | {problem} |")
|
||
blocks.append(("## Questions with unmet constraints", "\n".join(lines)))
|
||
|
||
return blocks
|