327 lines
13 KiB
Python
327 lines
13 KiB
Python
"""Check the numeric claims in public texts (README, blog posts, guide, drafts) against the validation reports.
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Code finds the claims and the candidate evidence; a TypeSafe System One model (Jev) only judges whether a passage
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supports, contradicts or says nothing about a claim (the "double checking citations" pattern,
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https://docs.typesafe.ai/cookbooks/citation_check). Only this repository's own documentation text is sent; no data,
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no sample sheets, no vendor files. Needs ``TYPESAFE_API_KEY`` in the environment, or in
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``~/.config/typesafe/credentials`` (mode 600), for the judgment step.
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python scripts/docs/check_claims.py README.md blog/*.md # check, write claims_report.md
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python scripts/docs/check_claims.py --dry-run linkedin_draft.txt # extraction and retrieval only, no API calls
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Verdicts: verified (a passage supports the claim, confidence >= threshold), contradicted, unsupported (passages found
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but none addresses the claim), no_source (no passage contains any of the claim's numbers), review (low confidence).
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Exit code 1 when any claim is contradicted or has no source, so the script can gate a publishing step.
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"""
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from __future__ import annotations
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import argparse
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import re
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import sys
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from dataclasses import dataclass, field
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "jev"))
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from client import MODEL, api_key, system_one
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ROOT = Path(__file__).resolve().parents[2]
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AUTO_ACCEPT = 0.8 # cookbook default; evaluate on our own claims before trusting it
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TOP_K = 3
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DEFAULT_SOURCES = ["docs/validation", "docs/known_unknowns.md", "SIMURGARRAY_FUNCTIONAL_SPEC.md"]
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RELATION = {
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"type": "choice",
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"criteria": {
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"supports": "The section states the claim's numbers and meaning, or directly implies that the claim is true",
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"contradicts": "The section gives a different value for the same quantity, or implies the claim is false",
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"says_nothing": "The section does not address what the claim asserts, either way",
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},
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}
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# ------------------------------------------------------------------ numbers
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_NUM = re.compile(r"(?<![\w.])(\d{1,3}(?:[ ,]\d{3})+|\d+(?:\.\d+)?)(\s?%)?")
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def numbers(text: str) -> set[str]:
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"""Normalised number tokens of a text, with percent/fraction twins: '99.34%' -> {'99.34', '0.9934'}."""
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out: set[str] = set()
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for m in _NUM.finditer(text):
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raw, pct = m.group(1), m.group(2)
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v = raw.replace(",", "").replace(" ", "")
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try:
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f = float(v)
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except ValueError:
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continue
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out.add(_fmt(f))
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if pct:
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out.add(_fmt(f / 100))
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elif 0 < f < 1:
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out.add(_fmt(f * 100))
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return out
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def _fmt(f: float) -> str:
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s = f"{f:.6f}".rstrip("0").rstrip(".")
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return s or "0"
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_MONTHS = "January|February|March|April|May|June|July|August|September|October|November|December"
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_DATE = re.compile(
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rf"\b({_MONTHS})\s+\d{{4}}\b|\b({_MONTHS})\s+\d{{1,2}}(,\s*\d{{4}})?|\b(19|20)\d{{2}}\b|\d{{4}}-\d{{2}}-\d{{2}}"
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r"|\b(version|v)\s?\d+(\.\d+)+\b"
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)
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def significant(nums: set[str]) -> set[str]:
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"""Numbers worth matching: drop tiny integers that appear everywhere (0 to 12)."""
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return {n for n in nums if not (n.isdigit() and int(n) <= 12)}
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def claim_numbers(text: str) -> set[str]:
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"""Significant numbers of a claim; dates and years are context, not claims."""
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return significant(numbers(_DATE.sub(" ", text)))
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# ------------------------------------------------------------------ claims
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@dataclass
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class Claim:
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path: str
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line: int
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text: str
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context: str
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nums: set[str]
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def _strip_md(s: str) -> str:
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s = re.sub(r"<[^>]+>", " ", s)
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s = re.sub(r"!\[[^\]]*\]\([^)]*\)", " ", s)
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s = re.sub(r"\[([^\]]*)\]\([^)]*\)", r"\1", s)
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s = re.sub(r"https?://\S+", " ", s)
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return re.sub(r"\s+", " ", s.replace("**", "").replace("`", "")).strip()
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def extract_claims(path: Path, text: str) -> list[Claim]:
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"""Sentences of paragraphs and bullets, and table rows, that carry significant numbers. Lines of one paragraph
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or bullet are joined first, so a sentence wrapped over several lines stays whole. Code blocks and commands are
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skipped."""
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claims: list[Claim] = []
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heading, table_head, in_code = "", "", False
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buf: list[str] = []
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start = 0
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def add(unit: str, line: int) -> None:
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nums = claim_numbers(unit)
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if nums and not re.search(r"\b(simurg|uv|pip|bash|docker|conda) ", unit):
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ctx = " / ".join(x for x in (heading, table_head) if x)
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claims.append(Claim(str(path), line, unit, ctx, nums))
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def flush() -> None:
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if buf:
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para = _strip_md(" ".join(buf))
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for u in re.split(r"(?<=[.!?])\s+(?=[A-Z])", para):
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if u:
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add(u, start)
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buf.clear()
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for i, raw in enumerate([*text.splitlines(), ""], 1):
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ln = raw.rstrip()
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if ln.lstrip().startswith("```"):
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flush()
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in_code = not in_code
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continue
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if in_code:
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continue
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if not ln.strip():
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flush()
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table_head = ""
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continue
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if ln.startswith("#"):
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flush()
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heading = _strip_md(ln.lstrip("#"))
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continue
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if ln.lstrip().startswith("|"):
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flush()
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if re.fullmatch(r"\s*\|[\s:|-]+\|?\s*", ln):
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continue
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if not table_head:
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table_head = _strip_md(ln)
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continue
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add(_strip_md(ln), i)
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continue
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bullet = re.match(r"\s*([*>-]|\d+\.)\s+", ln)
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if bullet:
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flush()
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ln = ln[bullet.end() :]
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if not buf:
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start = i
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buf.append(ln.strip())
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return claims
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# ------------------------------------------------------------------ evidence
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@dataclass
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class Passage:
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path: str
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line: int
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text: str
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nums: set[str] = field(default_factory=set)
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def load_passages(sources: list[Path]) -> list[Passage]:
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"""Paragraphs and table rows (with their header) of the source documents."""
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out: list[Passage] = []
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files = [p for s in sources for p in (sorted(s.rglob("*.md")) if s.is_dir() else [s])]
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for f in files:
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rel = str(f.relative_to(ROOT)) if f.is_relative_to(ROOT) else str(f)
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heading, table_head = "", ""
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buf: list[str] = []
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start = 0
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for i, ln in enumerate([*f.read_text(encoding="utf-8").splitlines(), ""], 1):
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is_row = ln.lstrip().startswith("|")
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if (ln.startswith("#") or is_row or not ln.strip()) and buf:
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t = (heading + ": " if heading else "") + " ".join(buf)
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out.append(Passage(rel, start, t, numbers(t)))
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buf = []
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if ln.startswith("#"):
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heading, table_head = _strip_md(ln.lstrip("#")), ""
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elif is_row:
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if re.fullmatch(r"\s*\|[\s:|-]+\|?\s*", ln):
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continue
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if not table_head:
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table_head = _strip_md(ln)
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continue
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t = f"{heading}: {table_head} || {_strip_md(ln)}"
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out.append(Passage(rel, i, t, numbers(t)))
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elif not ln.strip():
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table_head = ""
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else:
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if not buf:
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start = i
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buf.append(_strip_md(ln))
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return out
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def _shared(a: set[str], b: set[str], tol: float = 0.03) -> int:
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"""Numbers of ``a`` found in ``b`` exactly, or within 3 % for values of 10 and more (rounded figures such as
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'about 550 MB' for 545 and 551 MB)."""
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fb = [float(x) for x in b]
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n = 0
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for x in a:
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if x in b:
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n += 1
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continue
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v = float(x)
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if v >= 10 and any(w >= 10 and abs(v - w) <= tol * max(v, w) for w in fb):
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n += 1
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return n
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def candidates(claim: Claim, passages: list[Passage], k: int = TOP_K) -> list[Passage]:
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"""Passages sharing the most of the claim's numbers (exactly or approximately), then the most words."""
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words = set(re.findall(r"[a-z]{4,}", claim.text.lower()))
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scored = []
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for p in passages:
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shared = _shared(claim.nums, p.nums)
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if shared:
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overlap = len(words & set(re.findall(r"[a-z]{4,}", p.text.lower())))
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scored.append((shared, overlap, p))
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scored.sort(key=lambda t: (-t[0], -t[1], t[2].path, t[2].line))
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return [p for _, _, p in scored[:k]]
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# ------------------------------------------------------------------ judgment
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def build_request(claim: Claim, cands: list[Passage]) -> dict[str, object]:
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state = {
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"claim": claim.text,
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"claim_context": claim.context,
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"sections": [{"source": f"{p.path}:{p.line}", "text": p.text[:1500]} for p in cands],
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}
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ask = "How does `sections[{i}].text` relate to `claim` (read `claim` together with `claim_context`)?"
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questions = {f"s{i}": {**RELATION, "instructions": ask.format(i=i)} for i in range(len(cands))}
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return {"model": MODEL, "state": state, "questions": questions}
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def verdict(answers: dict[str, dict[str, object]], threshold: float = AUTO_ACCEPT) -> tuple[str, str | None, float]:
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"""Combine per-section answers: any confident 'supports' wins; else a confident 'contradicts'; else a confident
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'says_nothing' from every section; anything else goes to a person."""
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best: dict[str, tuple[float, str]] = {}
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for qid, a in answers.items():
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ch, conf = str(a["choice"]), float(a["confidence"]) # type: ignore[arg-type]
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if conf >= threshold and conf > best.get(ch, (-1.0, ""))[0]:
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best[ch] = (conf, qid)
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if "supports" in best:
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return "verified", best["supports"][1], best["supports"][0]
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support = max((float(a["probabilities"].get("supports", 0.0)) for a in answers.values()), default=0.0) # type: ignore[attr-defined]
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if "contradicts" in best:
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if support >= 0.3: # another section leans towards support: a person decides
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return "review", best["contradicts"][1], best["contradicts"][0]
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return "contradicted", best["contradicts"][1], best["contradicts"][0]
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confident = [float(a["confidence"]) >= threshold and a["choice"] == "says_nothing" for a in answers.values()] # type: ignore[arg-type]
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if confident and all(confident):
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return "unsupported", None, min(float(a["confidence"]) for a in answers.values()) # type: ignore[arg-type]
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return "review", None, max((float(a["confidence"]) for a in answers.values()), default=0.0) # type: ignore[arg-type]
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# ------------------------------------------------------------------ report
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def main(argv: list[str] | None = None) -> int:
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ap = argparse.ArgumentParser(description=__doc__.split("\n\n")[0])
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ap.add_argument("files", nargs="+", type=Path, help="texts to check (markdown or plain text)")
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ap.add_argument("--sources", nargs="+", type=Path, default=[ROOT / s for s in DEFAULT_SOURCES])
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ap.add_argument("--out", type=Path, default=Path("claims_report.md"))
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ap.add_argument("--threshold", type=float, default=AUTO_ACCEPT)
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ap.add_argument("--dry-run", action="store_true", help="extract claims and evidence, no API calls")
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a = ap.parse_args(argv)
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key = api_key()
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if not a.dry_run and not key:
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print("TYPESAFE_API_KEY is not set (use --dry-run to check extraction without the API).", file=sys.stderr)
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return 2
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passages = load_passages(a.sources)
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rows: list[tuple[str, Claim, Passage | None, float, str]] = []
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for f in a.files:
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for c in extract_claims(f, f.read_text(encoding="utf-8")):
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cands = candidates(c, passages)
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if not cands:
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rows.append(("no_source", c, None, 1.0, ""))
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continue
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if a.dry_run:
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rows.append(("planned", c, cands[0], 0.0, f"{len(cands)} candidate(s)"))
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continue
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req = build_request(c, cands)
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answers = system_one(req["state"], req["questions"], key) # type: ignore[arg-type]
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v, qid, conf = verdict(answers, a.threshold) # type: ignore[arg-type]
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src = cands[int(qid[1:])] if qid else cands[0]
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probs = ", ".join(f"{q}: {answers[q]['choice']} {answers[q]['confidence']:.2f}" for q in answers) # type: ignore[index]
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rows.append((v, c, src, conf, probs))
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order = ["contradicted", "no_source", "review", "unsupported", "verified", "planned"]
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counts = {v: sum(r[0] == v for r in rows) for v in order}
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lines = ["# Claim check", "", " · ".join(f"{v} {n}" for v, n in counts.items() if n), ""]
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for v in order:
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sel = [r for r in rows if r[0] == v]
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if not sel:
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continue
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lines += [f"## {v} ({len(sel)})", ""]
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for _, c, src, conf, extra in sel:
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lines.append(f"* `{c.path}:{c.line}` {c.text}")
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if src:
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lines.append(f" * evidence `{src.path}:{src.line}` (confidence {conf:.2f}) {src.text[:220]}")
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if extra:
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lines.append(f" * {extra}")
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lines.append("")
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a.out.write_text("\n".join(lines))
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print(f"{len(rows)} claims: " + ", ".join(f"{v} {n}" for v, n in counts.items() if n) + f" → {a.out}")
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return 1 if counts["contradicted"] or counts["no_source"] else 0
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if __name__ == "__main__":
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sys.exit(main())
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