mirror of https://github.com/razor-ai/soup.git
feat(brain-rot): per-language low-effort + clickbait bundles for es/fr/de/ru (#234)
Extends v0.69.0 Part E score_triviality + score_popularity_signal to non-English corpora. New utils/brain_rot_lang.py ships a MappingProxyType registry of frozen BrainRotLangBundle for en/es/fr/de/ru. Every public scorer accepts an optional lang kwarg (default None preserves v0.69.0 English behaviour). The "auto" sentinel routes through the v0.53.10 [data-pro] langdetect helper with silent fallback to English on missing-package / detector-exception / unsupported-code. soup data brain-rot gains --lang en|es|fr|de|ru|auto, strictly validated at the CLI boundary (exit 2 on typos). Per-row resolution backed by eager _validate_lang_arg on dataset scorers so empty rows cannot bypass shape checks. Closes #234. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Alpamys
parent
95f9a7116d
commit
525a0e1114
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@ -2659,13 +2659,24 @@ def brain_rot_cmd(
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max_major_fraction: float = typer.Option(
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0.25, "--max-major-fraction", help="Strict-mode MAJOR-row fraction cap [0, 1]"
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),
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lang: str = typer.Option(
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"en",
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"--lang",
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help=(
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"Per-language heuristic bundle: "
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"en | es | fr | de | ru | auto. Closes issue #234."
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),
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),
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) -> None:
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"""Score a dataset for brain-rot per arXiv 2510.13928 (v0.69.0 Part E).
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Reports a per-row OK/MINOR/MAJOR verdict + an aggregate verdict. With
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``--strict`` the command exits 3 when the MAJOR fraction exceeds
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``--max-major-fraction`` (default 25%), so CI pipelines can refuse
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training on excessive slop.
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training on excessive slop. ``--lang`` selects a per-language
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low-effort-token + clickbait-phrase bundle (closes #234); ``--lang auto``
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routes through the optional ``langdetect`` package (``[data-pro]`` extras)
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and falls back silently to English when detection is unavailable.
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"""
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import math as _math
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import os
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@ -2677,6 +2688,7 @@ def brain_rot_cmd(
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refuse_if_rotten,
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score_dataset_brain_rot,
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)
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from soup_cli.utils.brain_rot_lang import validate_lang_code
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from soup_cli.utils.paths import enforce_under_cwd_and_no_symlink
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max_brain_rot_bytes = 1_073_741_824 # 1 GiB
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@ -2698,6 +2710,15 @@ def brain_rot_cmd(
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console.print("[red]--max-major-fraction must be in [0.0, 1.0][/]")
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raise typer.Exit(2)
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# Validate --lang at the CLI boundary so unknown ISO codes / typos
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# fail fast with exit 2 (matches v0.41.0 / v0.51.0 / v0.65.0 strict
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# CLI-boundary policy; closes #234).
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try:
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lang_canonical = validate_lang_code(lang)
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except (TypeError, ValueError) as exc:
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console.print(f"[red]{_escape(str(exc))}[/]")
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raise typer.Exit(2) from exc
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if not isinstance(data, str) or not data:
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console.print("[red]data path must be a non-empty string[/]")
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raise typer.Exit(2)
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@ -2737,7 +2758,7 @@ def brain_rot_cmd(
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if isinstance(row, dict):
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rows.append(row)
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report = score_dataset_brain_rot(rows)
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report = score_dataset_brain_rot(rows, lang=lang_canonical)
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table = Table(title="Brain-rot report")
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table.add_column("Metric")
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@ -2748,11 +2769,16 @@ def brain_rot_cmd(
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table.add_row("Verdict MINOR", str(report.num_minor))
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table.add_row("Verdict MAJOR", str(report.num_major))
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table.add_row("Overall", report.overall_verdict)
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table.add_row("Lang", _escape(lang_canonical))
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console.print(table)
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if strict:
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try:
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refuse_if_rotten(rows, max_major_fraction=max_major_fraction)
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refuse_if_rotten(
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rows,
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max_major_fraction=max_major_fraction,
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lang=lang_canonical,
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)
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except (TypeError, ValueError) as exc:
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console.print(f"[red]{_escape(str(exc))}[/]")
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raise typer.Exit(3) from exc
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@ -21,7 +21,13 @@ import math
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import re
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from collections import Counter
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from dataclasses import dataclass
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from typing import Any, Iterable, List, Mapping
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from typing import Any, Iterable, List, Mapping, Optional
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from soup_cli.utils.brain_rot_lang import (
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SUPPORTED_LANGS,
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BrainRotLangBundle,
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get_lang_bundle,
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)
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BRAIN_ROT_VERDICTS = ("OK", "MINOR", "MAJOR")
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@ -29,22 +35,6 @@ _OK_THRESHOLD = 0.85
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_MINOR_THRESHOLD = 0.60
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_MAX_TEXT_LEN = 65_536
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_CLICKBAIT_PHRASES = (
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"you won't believe",
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"you wont believe",
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"won't believe what happened",
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"top 10",
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"top ten",
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"click here",
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"this one weird trick",
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"what happened next",
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"the rest is history",
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"shocked the world",
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"doctors hate",
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"gone wrong",
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"gone viral",
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)
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_LOW_EFFORT_TOKENS = ("lol", "omg", "lmao", "rofl", "smh", "tbh", "idk")
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_PUNCT_PATTERN = re.compile(r"[!]{2,}|[?]{2,}")
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_TEXT_FIELDS = ("text", "content", "output", "prompt", "instruction", "response")
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@ -133,15 +123,78 @@ def _require_str(text: object, *, field: str = "text") -> str:
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return text
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def score_triviality(text: object) -> float:
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def _validate_lang_arg(lang: object) -> None:
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"""Eager boundary check for ``lang`` kwarg on dataset-level scorers.
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Closes a gap surfaced in python-review: per-row resolution rejects a
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bool / null-byte / oversize lang, but only on the first iteration —
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an empty ``rows`` list would silently fall through. Validating upfront
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also catches operator typos before any scoring work happens.
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"""
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if lang is None:
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return
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if isinstance(lang, bool):
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raise TypeError("lang must be str, not bool")
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if not isinstance(lang, str):
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raise TypeError(f"lang must be str, got {type(lang).__name__}")
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if "\x00" in lang:
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raise ValueError("lang must not contain null bytes")
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if len(lang) > 64:
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raise ValueError("lang must be <= 64 chars")
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def _resolve_bundle(lang: Optional[str], *, text: str = "") -> BrainRotLangBundle:
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"""Resolve a ``lang`` kwarg (incl. the ``"auto"`` sentinel) to a bundle.
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- ``None`` -> English bundle (backward-compat with the v0.69.0 surface).
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- ``"auto"`` -> probabilistic detection via :func:`data_score._langdetect_fast`;
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silent fallback to English when the optional ``[data-pro]`` ``langdetect``
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package is missing OR the detector returns ``unknown`` / a code not in
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:data:`SUPPORTED_LANGS`. This matches the issue acceptance criterion
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"``--lang auto`` falls back to English when language detection returns
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``unknown`` or ``[data-pro]`` not installed".
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- Any other string -> :func:`get_lang_bundle` lookup (silent fallback to
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English on unknown codes; keeps the detector working on under-resourced
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corpora rather than crashing).
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"""
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if lang is None:
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return get_lang_bundle(None)
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# Shape-check via get_lang_bundle's _check_lang_arg_shape for the
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# non-"auto" path; for "auto" we just inspect the canonical form.
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if not isinstance(lang, str) or isinstance(lang, bool):
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# get_lang_bundle would raise TypeError — preserve that.
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return get_lang_bundle(lang) # raises TypeError
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canonical = lang.lower()
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if canonical != "auto":
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return get_lang_bundle(lang)
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# auto: probe via langdetect; lazy-import so a bare install still works.
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detected: Optional[str] = None
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if text:
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try:
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from soup_cli.utils.data_score import _langdetect_fast # noqa: PLC0415
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detected = _langdetect_fast(text)
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except Exception: # noqa: BLE001 — silent fallback per issue spec
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detected = None
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if detected and detected in SUPPORTED_LANGS:
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return get_lang_bundle(detected)
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return get_lang_bundle("en")
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def score_triviality(text: object, *, lang: Optional[str] = None) -> float:
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"""Higher = more trivial / repetitive / exclamation-heavy.
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Heuristic: punctuation-runs density + short-text penalty + token diversity
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inversion. Returns 1.0 for empty/unparseable input (worst case).
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``lang`` selects a per-language token bundle (en / es / fr / de / ru) or
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``"auto"`` for langdetect-driven detection. Default (``None``) preserves
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v0.69.0 English behaviour for backward-compat.
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"""
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s = _require_str(text)
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if not s.strip():
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return 1.0
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bundle = _resolve_bundle(lang, text=s)
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tokens = s.lower().split()
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n = len(tokens)
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if n == 0:
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@ -153,8 +206,11 @@ def score_triviality(text: object) -> float:
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# Punctuation: long !!!! / ???? runs are slop markers.
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punct_hits = len(_PUNCT_PATTERN.findall(s))
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punct_density = min(1.0, punct_hits / max(1, n / 10))
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# Low-effort token density.
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low_effort = sum(1 for tok in tokens if tok.strip("!?.,") in _LOW_EFFORT_TOKENS)
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# Low-effort token density (per-language bundle).
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low_effort_set = set(bundle.low_effort_tokens)
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low_effort = sum(
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1 for tok in tokens if tok.strip("!?.,") in low_effort_set
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)
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low_effort_density = min(1.0, low_effort / max(1, n / 5))
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triviality = (
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0.2 * (1.0 - diversity)
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@ -165,17 +221,24 @@ def score_triviality(text: object) -> float:
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return max(0.0, min(1.0, triviality))
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def score_popularity_signal(text: object) -> float:
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def score_popularity_signal(
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text: object, *, lang: Optional[str] = None
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) -> float:
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"""Higher = clickbait / engagement-bait / popularity-optimised slop.
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Heuristic: substring scan against ``_CLICKBAIT_PHRASES`` + emoji density.
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Returns 0.0 for empty input.
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Heuristic: substring scan against the per-language clickbait phrase
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bundle + emoji density. Returns 0.0 for empty input.
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``lang`` selects a per-language phrase bundle (en / es / fr / de / ru)
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or ``"auto"`` for langdetect-driven detection. Default (``None``)
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preserves v0.69.0 English behaviour for backward-compat.
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"""
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s = _require_str(text)
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if not s.strip():
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return 0.0
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bundle = _resolve_bundle(lang, text=s)
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lower = s.lower()
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hits = sum(1 for phrase in _CLICKBAIT_PHRASES if phrase in lower)
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hits = sum(1 for phrase in bundle.clickbait_phrases if phrase in lower)
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# Emoji density: count non-ASCII chars in [U+1F300, U+1FAFF] range
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# (covers most pictographs without importing emoji libs).
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emoji_hits = sum(1 for c in s if 0x1F300 <= ord(c) <= 0x1FAFF)
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@ -201,11 +264,15 @@ def _row_text(row: Mapping[str, Any]) -> str:
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return "\n".join(parts)
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def score_row_brain_rot(row: Any) -> float:
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def score_row_brain_rot(row: Any, *, lang: Optional[str] = None) -> float:
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"""Return a per-row score in [0, 1]; 1.0 = healthy, 0.0 = pure slop.
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Composite: ``1 - 0.5 * triviality - 0.5 * popularity_signal``. Rows with
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no text fields return ``0.0`` (treat unjudgeable as worst-case).
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Composite: ``1 - max(triviality, popularity_signal)`` (worst-signal
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wins). Rows with no text fields return ``0.0`` (unjudgeable = worst).
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``lang`` selects a per-language token + phrase bundle (en / es / fr /
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de / ru) or ``"auto"`` for langdetect-driven detection. Default
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(``None``) preserves v0.69.0 English behaviour for backward-compat.
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"""
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if not isinstance(row, Mapping):
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raise TypeError(
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@ -214,26 +281,31 @@ def score_row_brain_rot(row: Any) -> float:
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text = _row_text(row)
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if not text:
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return 0.0
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triviality = score_triviality(text)
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popularity = score_popularity_signal(text)
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triviality = score_triviality(text, lang=lang)
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popularity = score_popularity_signal(text, lang=lang)
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# Worst-signal composite: a single strong slop signal drives the score
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# down hard (mirrors v0.56.0 ``overall_verdict`` worst-case policy).
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score = 1.0 - max(triviality, popularity)
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return max(0.0, min(1.0, score))
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def score_dataset_brain_rot(rows: Any) -> BrainRotReport:
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def score_dataset_brain_rot(
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rows: Any, *, lang: Optional[str] = None
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) -> BrainRotReport:
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"""Score a dataset and return a frozen ``BrainRotReport``.
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Empty inputs return ``MAJOR`` (no signal = treat as broken).
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``lang`` is threaded through to :func:`score_row_brain_rot` so the
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per-language token / phrase bundle is applied to every row.
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"""
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if isinstance(rows, (str, bytes)) or not hasattr(rows, "__iter__"):
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raise TypeError("rows must be iterable")
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_validate_lang_arg(lang)
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scores: List[float] = []
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for row in rows:
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if not isinstance(row, Mapping):
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continue
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scores.append(score_row_brain_rot(row))
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scores.append(score_row_brain_rot(row, lang=lang))
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if not scores:
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return BrainRotReport(
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num_rows=0,
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@ -260,11 +332,13 @@ def refuse_if_rotten(
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rows: Iterable[Mapping[str, Any]],
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*,
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max_major_fraction: float = 0.25,
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lang: Optional[str] = None,
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) -> None:
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"""Raise ``ValueError`` when too many rows score MAJOR brain-rot.
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Composes with v0.69.0 Part A's build pipeline so a transform can refuse to
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produce a tokenised dataset that's mostly slop.
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produce a tokenised dataset that's mostly slop. ``lang`` is threaded
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through to :func:`score_dataset_brain_rot` (per-language bundle picker).
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"""
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if isinstance(max_major_fraction, bool):
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raise TypeError("max_major_fraction must be float, not bool")
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@ -274,7 +348,8 @@ def refuse_if_rotten(
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raise ValueError("max_major_fraction must be finite")
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if not (0.0 <= float(max_major_fraction) <= 1.0):
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raise ValueError("max_major_fraction must be in [0.0, 1.0]")
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report = score_dataset_brain_rot(rows)
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_validate_lang_arg(lang)
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report = score_dataset_brain_rot(rows, lang=lang)
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if report.num_rows == 0:
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return # no data → nothing to refuse
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fraction = report.num_major / report.num_rows
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|
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@ -0,0 +1,272 @@
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"""Per-language brain-rot heuristic bundles (closes issue #234).
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Extends v0.69.0 Part E ``score_triviality`` + ``score_popularity_signal``
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to non-English corpora. The Shannon-entropy + punctuation-run signals in
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``brain_rot.py`` stay language-agnostic; the keyword half is what goes
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silent on non-English text. This module ships a small closed-allowlist
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registry of per-language token + phrase bundles so the keyword half
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keeps working on es / fr / de / ru without a heavyweight dependency.
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Design (Option A from the issue — preferred over the operator-supplied
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JSON form because it composes with the project's bundled-resources
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policy from v0.65.0 behavior batteries + v0.68.0 local-rl fixtures):
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- ``BrainRotLangBundle`` is a frozen dataclass with token / phrase tuples.
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- ``_LANG_BUNDLES`` is a ``MappingProxyType`` so callers can't mutate it
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at runtime (matches v0.51.0 hubs / v0.60.0 license_matrix policy).
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- ``SUPPORTED_LANGS`` is a frozenset of canonical ISO 639-1 codes.
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- ``get_lang_bundle`` is the lookup path used by the scorers: unknown
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codes silently fall back to the English bundle (no exception — the
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detector should keep working even on weakly-resourced languages).
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- ``validate_lang_code`` is the strict CLI-boundary validator that
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rejects unknown codes loudly (matches v0.41.0 ``validate_optimizer_name``
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policy).
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The token + phrase lists are intentionally small seed sets — operators
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who want richer per-language coverage can either extend them upstream
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or pass a custom bundle via a v0.69.x follow-up flag.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from types import MappingProxyType
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from typing import Mapping, Tuple
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_MAX_LANG_CODE_LEN = 64
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@dataclass(frozen=True)
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class BrainRotLangBundle:
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"""Frozen per-language low-effort + clickbait token bundle.
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``code`` is the ISO 639-1 identifier. ``low_effort_tokens`` are
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whitespace-tokenised lowercase strings matched against the per-token
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body (with surrounding punctuation stripped). ``clickbait_phrases``
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are lowercase substrings matched against the lowercased input text.
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"""
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code: str
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low_effort_tokens: Tuple[str, ...]
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clickbait_phrases: Tuple[str, ...]
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def __post_init__(self) -> None:
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if not isinstance(self.code, str) or not self.code:
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raise ValueError("code must be a non-empty string")
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if "\x00" in self.code:
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raise ValueError("code must not contain null bytes")
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if not isinstance(self.low_effort_tokens, tuple):
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raise TypeError("low_effort_tokens must be a tuple")
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if not isinstance(self.clickbait_phrases, tuple):
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raise TypeError("clickbait_phrases must be a tuple")
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for entries, name in (
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(self.low_effort_tokens, "low_effort_tokens"),
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(self.clickbait_phrases, "clickbait_phrases"),
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):
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for entry in entries:
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if not isinstance(entry, str):
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raise TypeError(f"{name} entries must be strings")
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if not entry:
|
||||
raise ValueError(f"{name} entries must be non-empty")
|
||||
if "\x00" in entry:
|
||||
raise ValueError(
|
||||
f"{name} entries must not contain null bytes"
|
||||
)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Bundles. Each list is a small seed set (≈ 8-14 tokens + 6-10 phrases).
|
||||
# Phrases are lowercased upfront so the substring scan in
|
||||
# ``score_popularity_signal`` matches reliably against ``text.lower()``.
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
_EN_BUNDLE = BrainRotLangBundle(
|
||||
code="en",
|
||||
low_effort_tokens=(
|
||||
"lol", "omg", "lmao", "rofl", "smh", "tbh", "idk",
|
||||
"wtf", "ikr", "tldr", "fml", "yolo",
|
||||
),
|
||||
clickbait_phrases=(
|
||||
"you won't believe",
|
||||
"you wont believe",
|
||||
"won't believe what happened",
|
||||
"top 10",
|
||||
"top ten",
|
||||
"click here",
|
||||
"this one weird trick",
|
||||
"what happened next",
|
||||
"the rest is history",
|
||||
"shocked the world",
|
||||
"doctors hate",
|
||||
"gone wrong",
|
||||
"gone viral",
|
||||
),
|
||||
)
|
||||
|
||||
_ES_BUNDLE = BrainRotLangBundle(
|
||||
code="es",
|
||||
low_effort_tokens=(
|
||||
"jaja", "jajaja", "jeje", "jiji", "lol", "omg",
|
||||
"xd", "wtf", "ojalá", "ay",
|
||||
),
|
||||
clickbait_phrases=(
|
||||
"no creerás",
|
||||
"no vas a creer",
|
||||
"haz clic aquí",
|
||||
"click aquí",
|
||||
"lo que pasó después",
|
||||
"lo que pasó a continuación",
|
||||
"top 10",
|
||||
"top diez",
|
||||
"no podrás creer",
|
||||
"te dejará sin palabras",
|
||||
"te sorprenderá",
|
||||
"los médicos odian",
|
||||
),
|
||||
)
|
||||
|
||||
_FR_BUNDLE = BrainRotLangBundle(
|
||||
code="fr",
|
||||
low_effort_tokens=(
|
||||
"mdr", "ptdr", "lol", "omg", "xd", "jpp", "tkt",
|
||||
"wtf", "rofl", "lmao",
|
||||
),
|
||||
clickbait_phrases=(
|
||||
"vous n'allez pas le croire",
|
||||
"vous n'allez pas y croire",
|
||||
"n'allez pas le croire",
|
||||
"cliquez ici",
|
||||
"ce qui se passe ensuite",
|
||||
"top 10",
|
||||
"top dix",
|
||||
"ce qu'il s'est passé",
|
||||
"ce qu'il s'est passé ensuite",
|
||||
"incroyable mais vrai",
|
||||
"les médecins détestent",
|
||||
"vous serez choqué",
|
||||
),
|
||||
)
|
||||
|
||||
_DE_BUNDLE = BrainRotLangBundle(
|
||||
code="de",
|
||||
low_effort_tokens=(
|
||||
"krass", "omg", "lol", "wtf", "xd", "hä", "alter",
|
||||
"boah", "ehh", "rofl", "lmao",
|
||||
),
|
||||
clickbait_phrases=(
|
||||
"du wirst es nicht glauben",
|
||||
"du wirst nicht glauben",
|
||||
"ihr werdet nicht glauben",
|
||||
"hier klicken",
|
||||
"klick hier",
|
||||
"top 10",
|
||||
"top zehn",
|
||||
"was als nächstes passiert",
|
||||
"was dann geschah",
|
||||
"schockierend",
|
||||
"ärzte hassen",
|
||||
"der eine geheime trick",
|
||||
),
|
||||
)
|
||||
|
||||
_RU_BUNDLE = BrainRotLangBundle(
|
||||
code="ru",
|
||||
low_effort_tokens=(
|
||||
"ааа", "ххх", "лол", "ржу", "кек", "ыыы", "омг",
|
||||
"пиздец", "жесть", "капец",
|
||||
),
|
||||
clickbait_phrases=(
|
||||
"вы не поверите",
|
||||
"вы не поверите что",
|
||||
"не поверите что",
|
||||
"нажмите здесь",
|
||||
"кликните здесь",
|
||||
"топ 10",
|
||||
"топ десять",
|
||||
"что произошло дальше",
|
||||
"что случилось дальше",
|
||||
"шокировало весь мир",
|
||||
"врачи ненавидят",
|
||||
"один странный трюк",
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
_LANG_BUNDLES: Mapping[str, BrainRotLangBundle] = MappingProxyType(
|
||||
{
|
||||
"en": _EN_BUNDLE,
|
||||
"es": _ES_BUNDLE,
|
||||
"fr": _FR_BUNDLE,
|
||||
"de": _DE_BUNDLE,
|
||||
"ru": _RU_BUNDLE,
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
SUPPORTED_LANGS: frozenset = frozenset(_LANG_BUNDLES.keys())
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Public lookup + validation surface
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def _check_lang_arg_shape(value: object) -> None:
|
||||
"""Common shape check for ``code``-typed inputs."""
|
||||
if isinstance(value, bool):
|
||||
raise TypeError("lang must be str, not bool")
|
||||
if not isinstance(value, str):
|
||||
raise TypeError(f"lang must be str, got {type(value).__name__}")
|
||||
if "\x00" in value:
|
||||
raise ValueError("lang must not contain null bytes")
|
||||
if len(value) > _MAX_LANG_CODE_LEN:
|
||||
raise ValueError(
|
||||
f"lang must be <= {_MAX_LANG_CODE_LEN} chars"
|
||||
)
|
||||
|
||||
|
||||
def get_lang_bundle(lang: object) -> BrainRotLangBundle:
|
||||
"""Return the bundle for ``lang`` (silent fallback to English).
|
||||
|
||||
``lang=None`` is accepted and resolves to the English bundle so callers
|
||||
can pass it through from optional kwargs without branching. Unknown
|
||||
codes fall back silently — the brain-rot detector should keep
|
||||
producing a result rather than raising on weakly-resourced languages.
|
||||
For a strict surface (e.g. the CLI), use :func:`validate_lang_code`.
|
||||
"""
|
||||
if lang is None:
|
||||
return _EN_BUNDLE
|
||||
_check_lang_arg_shape(lang)
|
||||
canonical = lang.lower() # type: ignore[union-attr]
|
||||
return _LANG_BUNDLES.get(canonical, _EN_BUNDLE)
|
||||
|
||||
|
||||
def validate_lang_code(value: object) -> str:
|
||||
"""Strict validator (CLI boundary): return canonical lower-case code.
|
||||
|
||||
Accepts every entry in :data:`SUPPORTED_LANGS` plus the literal
|
||||
``"auto"`` sentinel (which the scorer surface resolves via
|
||||
``langdetect`` per v0.53.10 #113 ``[data-pro]`` extras). Unknown
|
||||
codes raise ``ValueError`` so the CLI fails fast on typos.
|
||||
"""
|
||||
_check_lang_arg_shape(value)
|
||||
canonical = value.lower() # type: ignore[union-attr]
|
||||
if not canonical:
|
||||
raise ValueError("lang must be non-empty")
|
||||
if canonical == "auto":
|
||||
return canonical
|
||||
if canonical not in SUPPORTED_LANGS:
|
||||
raise ValueError(
|
||||
f"lang {canonical!r} not in supported set "
|
||||
f"{sorted(SUPPORTED_LANGS) + ['auto']}"
|
||||
)
|
||||
return canonical
|
||||
|
||||
|
||||
__all__ = [
|
||||
"BrainRotLangBundle",
|
||||
"SUPPORTED_LANGS",
|
||||
"get_lang_bundle",
|
||||
"validate_lang_code",
|
||||
]
|
||||
|
|
@ -0,0 +1,695 @@
|
|||
"""Multilingual brain-rot heuristics — closes issue #234.
|
||||
|
||||
Extends v0.69.0 Part E ``score_triviality`` + ``score_popularity_signal`` with
|
||||
per-language token + phrase bundles (en/es/fr/de/ru). Option A from the issue:
|
||||
per-language registry under ``soup_cli/utils/brain_rot_lang.py`` plus an
|
||||
optional ``lang`` parameter on the public scorers (default ``"en"`` so the
|
||||
v0.69.0 surface stays backward-compat).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import dataclasses
|
||||
import json
|
||||
from pathlib import Path
|
||||
from types import MappingProxyType
|
||||
|
||||
import pytest
|
||||
from typer.testing import CliRunner
|
||||
|
||||
from soup_cli.cli import app
|
||||
from soup_cli.utils import brain_rot, brain_rot_lang
|
||||
|
||||
|
||||
def _write(path: Path, text: str) -> Path:
|
||||
path.write_text(text, encoding="utf-8")
|
||||
return path
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Bundle registry
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestSupportedLangs:
|
||||
def test_minimum_five_languages(self) -> None:
|
||||
# Acceptance criteria: en + es + fr + de + ru.
|
||||
for code in ("en", "es", "fr", "de", "ru"):
|
||||
assert code in brain_rot_lang.SUPPORTED_LANGS
|
||||
|
||||
def test_supported_langs_is_frozenset(self) -> None:
|
||||
assert isinstance(brain_rot_lang.SUPPORTED_LANGS, frozenset)
|
||||
|
||||
def test_lang_bundles_is_mapping_proxy(self) -> None:
|
||||
assert isinstance(brain_rot_lang._LANG_BUNDLES, MappingProxyType)
|
||||
|
||||
def test_lang_bundles_immutable(self) -> None:
|
||||
# MappingProxyType refuses item assignment with TypeError.
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot_lang._LANG_BUNDLES["en"] = None # type: ignore[index]
|
||||
|
||||
def test_every_bundle_has_non_empty_tuples(self) -> None:
|
||||
for code in brain_rot_lang.SUPPORTED_LANGS:
|
||||
bundle = brain_rot_lang._LANG_BUNDLES[code]
|
||||
assert len(bundle.low_effort_tokens) > 0
|
||||
assert len(bundle.clickbait_phrases) > 0
|
||||
|
||||
|
||||
class TestBrainRotLangBundle:
|
||||
def test_frozen(self) -> None:
|
||||
# tuples-not-lists so the dataclass is genuinely immutable.
|
||||
en = brain_rot_lang._LANG_BUNDLES["en"]
|
||||
with pytest.raises(dataclasses.FrozenInstanceError):
|
||||
en.low_effort_tokens = ("lol",) # type: ignore[misc]
|
||||
|
||||
def test_tokens_are_tuple(self) -> None:
|
||||
for code in brain_rot_lang.SUPPORTED_LANGS:
|
||||
bundle = brain_rot_lang._LANG_BUNDLES[code]
|
||||
assert isinstance(bundle.low_effort_tokens, tuple)
|
||||
assert isinstance(bundle.clickbait_phrases, tuple)
|
||||
|
||||
def test_token_entries_are_strings(self) -> None:
|
||||
for code in brain_rot_lang.SUPPORTED_LANGS:
|
||||
bundle = brain_rot_lang._LANG_BUNDLES[code]
|
||||
for tok in bundle.low_effort_tokens:
|
||||
assert isinstance(tok, str)
|
||||
assert tok # non-empty
|
||||
assert "\x00" not in tok
|
||||
for phrase in bundle.clickbait_phrases:
|
||||
assert isinstance(phrase, str)
|
||||
assert phrase
|
||||
assert "\x00" not in phrase
|
||||
|
||||
def test_construction_rejects_null_byte(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.BrainRotLangBundle(
|
||||
code="en",
|
||||
low_effort_tokens=("lol\x00",),
|
||||
clickbait_phrases=("click here",),
|
||||
)
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.BrainRotLangBundle(
|
||||
code="en",
|
||||
low_effort_tokens=("lol",),
|
||||
clickbait_phrases=("click\x00here",),
|
||||
)
|
||||
|
||||
def test_construction_rejects_empty_token(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.BrainRotLangBundle(
|
||||
code="en",
|
||||
low_effort_tokens=("",),
|
||||
clickbait_phrases=("x",),
|
||||
)
|
||||
|
||||
def test_construction_rejects_non_string(self) -> None:
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot_lang.BrainRotLangBundle(
|
||||
code="en",
|
||||
low_effort_tokens=(42,), # type: ignore[arg-type]
|
||||
clickbait_phrases=("x",),
|
||||
)
|
||||
|
||||
def test_construction_rejects_non_tuple_tokens(self) -> None:
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot_lang.BrainRotLangBundle(
|
||||
code="en",
|
||||
low_effort_tokens=["lol"], # type: ignore[arg-type]
|
||||
clickbait_phrases=("x",),
|
||||
)
|
||||
|
||||
def test_construction_rejects_invalid_code(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.BrainRotLangBundle(
|
||||
code="",
|
||||
low_effort_tokens=("a",),
|
||||
clickbait_phrases=("b",),
|
||||
)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# get_lang_bundle
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestGetLangBundle:
|
||||
def test_known(self) -> None:
|
||||
bundle = brain_rot_lang.get_lang_bundle("en")
|
||||
assert bundle.code == "en"
|
||||
|
||||
def test_case_insensitive(self) -> None:
|
||||
assert brain_rot_lang.get_lang_bundle("EN").code == "en"
|
||||
assert brain_rot_lang.get_lang_bundle("Es").code == "es"
|
||||
|
||||
def test_unknown_falls_back_to_en(self) -> None:
|
||||
# "xx" is not in the bundle set; helper falls back to en.
|
||||
assert brain_rot_lang.get_lang_bundle("xx").code == "en"
|
||||
|
||||
def test_none_falls_back_to_en(self) -> None:
|
||||
assert brain_rot_lang.get_lang_bundle(None).code == "en"
|
||||
|
||||
def test_bool_rejected(self) -> None:
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot_lang.get_lang_bundle(True) # type: ignore[arg-type]
|
||||
|
||||
def test_non_string_rejected(self) -> None:
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot_lang.get_lang_bundle(42) # type: ignore[arg-type]
|
||||
|
||||
def test_null_byte_rejected(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.get_lang_bundle("e\x00n")
|
||||
|
||||
def test_oversize_rejected(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.get_lang_bundle("a" * 65)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# validate_lang_code (CLI surface)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestValidateLangCode:
|
||||
def test_known_lang(self) -> None:
|
||||
assert brain_rot_lang.validate_lang_code("en") == "en"
|
||||
assert brain_rot_lang.validate_lang_code("es") == "es"
|
||||
|
||||
def test_auto_sentinel(self) -> None:
|
||||
# "auto" is the documented sentinel; validate returns it canonical.
|
||||
assert brain_rot_lang.validate_lang_code("auto") == "auto"
|
||||
|
||||
def test_case_insensitive(self) -> None:
|
||||
assert brain_rot_lang.validate_lang_code("EN") == "en"
|
||||
assert brain_rot_lang.validate_lang_code("AUTO") == "auto"
|
||||
|
||||
def test_unknown_rejected(self) -> None:
|
||||
# The strict validator (used by the CLI) rejects unknown codes —
|
||||
# get_lang_bundle's silent fallback is for the scorer surface.
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.validate_lang_code("xx")
|
||||
|
||||
def test_bool_rejected(self) -> None:
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot_lang.validate_lang_code(True) # type: ignore[arg-type]
|
||||
|
||||
def test_non_string_rejected(self) -> None:
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot_lang.validate_lang_code(42) # type: ignore[arg-type]
|
||||
|
||||
def test_empty_rejected(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.validate_lang_code("")
|
||||
|
||||
def test_null_byte_rejected(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.validate_lang_code("e\x00n")
|
||||
|
||||
def test_oversize_rejected(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot_lang.validate_lang_code("a" * 65)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# score_triviality / score_popularity_signal — per-language bundle
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestScoreTrivialityMultilingual:
|
||||
def test_default_en_backward_compat(self) -> None:
|
||||
# Default lang (None) preserves v0.69.0 English behaviour.
|
||||
text = "lol!!!! omg!!!! lol omg!!! lol!!!"
|
||||
assert brain_rot.score_triviality(text) > 0.5
|
||||
|
||||
def test_explicit_en(self) -> None:
|
||||
text = "lol!!!! omg!!!! lol omg!!! lol!!!"
|
||||
assert brain_rot.score_triviality(text, lang="en") > 0.5
|
||||
|
||||
def test_spanish_slop_detected_with_es(self) -> None:
|
||||
# Spanish low-effort tokens repeated → high triviality when lang=es.
|
||||
text = "jaja!!! jeje jaja jiji!!! jaja!!! jeje!!!"
|
||||
score = brain_rot.score_triviality(text, lang="es")
|
||||
assert score > 0.5
|
||||
|
||||
def test_spanish_slop_undetected_with_en(self) -> None:
|
||||
# Same Spanish slop with lang=en gets a lower low-effort signal
|
||||
# (still some punctuation noise, but the keyword half goes silent).
|
||||
text = "jaja!!! jeje jaja jiji!!! jaja!!! jeje!!!"
|
||||
es_score = brain_rot.score_triviality(text, lang="es")
|
||||
en_score = brain_rot.score_triviality(text, lang="en")
|
||||
assert es_score > en_score
|
||||
|
||||
def test_french_slop(self) -> None:
|
||||
text = "mdr!!! mdr ptdr lol!!! mdr ptdr mdr!!!"
|
||||
score = brain_rot.score_triviality(text, lang="fr")
|
||||
assert score > 0.5
|
||||
|
||||
def test_german_slop(self) -> None:
|
||||
# 'krass' / 'omg' / 'lol' are common low-effort tokens in DE chat.
|
||||
text = "krass!!! omg krass!!! lol krass!!! omg!!!"
|
||||
score = brain_rot.score_triviality(text, lang="de")
|
||||
assert score > 0.5
|
||||
|
||||
def test_russian_slop(self) -> None:
|
||||
# Russian low-effort tokens (transliteration of laughter).
|
||||
text = "ааа!!! лол!!! ааа лол ааа!!! ааа!!!"
|
||||
score = brain_rot.score_triviality(text, lang="ru")
|
||||
assert score > 0.5
|
||||
|
||||
def test_unknown_lang_falls_back_to_en(self) -> None:
|
||||
# Unknown ISO code: the silent fallback uses English heuristics,
|
||||
# so behaviour matches the lang=en path.
|
||||
text = "lol!!! omg!!! lol!!!"
|
||||
en_score = brain_rot.score_triviality(text, lang="en")
|
||||
xx_score = brain_rot.score_triviality(text, lang="xx")
|
||||
assert abs(en_score - xx_score) < 1e-9
|
||||
|
||||
def test_substantive_text_unaffected(self) -> None:
|
||||
# Substantive non-English text should NOT score high.
|
||||
text = (
|
||||
"El mitocondria es la central energética de la célula porque "
|
||||
"convierte nutrientes en ATP mediante fosforilación oxidativa."
|
||||
)
|
||||
score = brain_rot.score_triviality(text, lang="es")
|
||||
assert score < 0.5
|
||||
|
||||
|
||||
class TestScorePopularitySignalMultilingual:
|
||||
def test_default_en_backward_compat(self) -> None:
|
||||
text = "click here for the top 10 you won't believe what happened next"
|
||||
assert brain_rot.score_popularity_signal(text) > 0.5
|
||||
|
||||
def test_spanish_clickbait(self) -> None:
|
||||
text = "no creerás lo que pasó después haz clic aquí"
|
||||
score = brain_rot.score_popularity_signal(text, lang="es")
|
||||
assert score > 0.5
|
||||
|
||||
def test_french_clickbait(self) -> None:
|
||||
text = "vous n'allez pas le croire cliquez ici top 10"
|
||||
score = brain_rot.score_popularity_signal(text, lang="fr")
|
||||
assert score > 0.5
|
||||
|
||||
def test_german_clickbait(self) -> None:
|
||||
text = "du wirst nicht glauben hier klicken top 10"
|
||||
score = brain_rot.score_popularity_signal(text, lang="de")
|
||||
assert score > 0.5
|
||||
|
||||
def test_russian_clickbait(self) -> None:
|
||||
text = "вы не поверите что произошло дальше нажмите здесь"
|
||||
score = brain_rot.score_popularity_signal(text, lang="ru")
|
||||
assert score > 0.5
|
||||
|
||||
def test_substantive_unaffected(self) -> None:
|
||||
text = "Explicación científica detallada de la fotosíntesis"
|
||||
assert brain_rot.score_popularity_signal(text, lang="es") < 0.5
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# score_row_brain_rot / score_dataset_brain_rot — lang threading
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestScoreRowLang:
|
||||
def test_default_backward_compat(self) -> None:
|
||||
# The v0.69.0 single-arg form still works.
|
||||
row = {"text": "Long substantive paragraph with diverse vocabulary."}
|
||||
assert brain_rot.score_row_brain_rot(row) > 0.5
|
||||
|
||||
def test_lang_kwarg(self) -> None:
|
||||
row = {"text": "Explicación científica detallada de la fotosíntesis"}
|
||||
score = brain_rot.score_row_brain_rot(row, lang="es")
|
||||
assert 0.0 <= score <= 1.0
|
||||
assert score > 0.5
|
||||
|
||||
def test_auto_falls_back_to_en_when_undetectable(self) -> None:
|
||||
# Too-short row → langdetect returns unknown → falls back to en.
|
||||
# Output stays in [0, 1] and matches the lang=en path.
|
||||
row = {"text": "hi"}
|
||||
score_auto = brain_rot.score_row_brain_rot(row, lang="auto")
|
||||
score_en = brain_rot.score_row_brain_rot(row, lang="en")
|
||||
assert score_auto == score_en
|
||||
|
||||
def test_auto_uses_detected_lang(
|
||||
self, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
# tdd-review HIGH: prove the auto path actually routes to the
|
||||
# detected bundle (not a tautology). Force the detector to return
|
||||
# "es" and assert lang="auto" matches lang="es" byte-for-byte.
|
||||
import soup_cli.utils.data_score as ds
|
||||
|
||||
monkeypatch.setattr(ds, "_langdetect_fast", lambda text: "es")
|
||||
row = {"text": "jaja!!! jeje jaja jiji!!! jaja!!! jeje!!!"}
|
||||
es_score = brain_rot.score_row_brain_rot(row, lang="es")
|
||||
auto_score = brain_rot.score_row_brain_rot(row, lang="auto")
|
||||
assert auto_score == es_score
|
||||
|
||||
def test_auto_silently_falls_back_when_detector_missing(
|
||||
self, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
# tdd-review HIGH: acceptance criterion #3 — exercise the
|
||||
# langdetect-missing path. _langdetect_fast already returns None
|
||||
# on the missing-package path; we patch it to None to simulate
|
||||
# the [data-pro]-not-installed environment without touching
|
||||
# sys.modules.
|
||||
import soup_cli.utils.data_score as ds
|
||||
|
||||
monkeypatch.setattr(ds, "_langdetect_fast", lambda text: None)
|
||||
row = {"text": "lol!!! omg!!! lol!!!"}
|
||||
en_score = brain_rot.score_row_brain_rot(row, lang="en")
|
||||
auto_score = brain_rot.score_row_brain_rot(row, lang="auto")
|
||||
assert auto_score == en_score
|
||||
|
||||
def test_auto_silently_falls_back_on_detector_exception(
|
||||
self, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
# tdd-review HIGH: a detector that raises (e.g. corrupted
|
||||
# langdetect data) must not crash the scoring loop — falls back
|
||||
# to en silently per the issue spec.
|
||||
import soup_cli.utils.data_score as ds
|
||||
|
||||
def _boom(text: str) -> None:
|
||||
raise OSError("simulated detector failure")
|
||||
|
||||
monkeypatch.setattr(ds, "_langdetect_fast", _boom)
|
||||
row = {"text": "lol!!! omg!!! lol!!!"}
|
||||
en_score = brain_rot.score_row_brain_rot(row, lang="en")
|
||||
auto_score = brain_rot.score_row_brain_rot(row, lang="auto")
|
||||
assert auto_score == en_score
|
||||
|
||||
def test_auto_falls_back_when_detected_lang_unsupported(
|
||||
self, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
# tdd-review HIGH: detector returns an ISO code we don't have a
|
||||
# bundle for (e.g. "zh") → fall back to en, do not crash.
|
||||
import soup_cli.utils.data_score as ds
|
||||
|
||||
monkeypatch.setattr(ds, "_langdetect_fast", lambda text: "zh")
|
||||
row = {"text": "lol!!! omg!!! lol!!!"}
|
||||
en_score = brain_rot.score_row_brain_rot(row, lang="en")
|
||||
auto_score = brain_rot.score_row_brain_rot(row, lang="auto")
|
||||
assert auto_score == en_score
|
||||
|
||||
|
||||
class TestScoreDatasetLang:
|
||||
def test_lang_threaded(self) -> None:
|
||||
rows = [{"text": "jaja!!! jeje jaja jiji!!! jaja!!!"} for _ in range(5)]
|
||||
report = brain_rot.score_dataset_brain_rot(rows, lang="es")
|
||||
# Spanish slop should drag verdict down.
|
||||
assert report.overall_verdict in ("MAJOR", "MINOR")
|
||||
|
||||
def test_default_backward_compat(self) -> None:
|
||||
# English happy path is unchanged from v0.69.0.
|
||||
rows = [
|
||||
{"text": "Detailed scientific explanation of photosynthesis."}
|
||||
] * 3
|
||||
report = brain_rot.score_dataset_brain_rot(rows)
|
||||
assert report.overall_verdict == "OK"
|
||||
|
||||
|
||||
class TestDatasetLangEagerValidation:
|
||||
"""python-review LOW #2 — empty-rows bypass for bad lang arg."""
|
||||
|
||||
def test_empty_rows_bool_lang_rejected(self) -> None:
|
||||
# Without eager validation, an empty rows list would bypass the
|
||||
# per-row resolver and silently accept any lang value.
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot.score_dataset_brain_rot([], lang=True) # type: ignore[arg-type]
|
||||
|
||||
def test_empty_rows_null_byte_rejected(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot.score_dataset_brain_rot([], lang="e\x00n")
|
||||
|
||||
def test_empty_rows_oversize_rejected(self) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
brain_rot.score_dataset_brain_rot([], lang="a" * 65)
|
||||
|
||||
def test_refuse_empty_rows_bool_lang(self) -> None:
|
||||
with pytest.raises(TypeError):
|
||||
brain_rot.refuse_if_rotten([], lang=True) # type: ignore[arg-type]
|
||||
|
||||
|
||||
class TestRefuseIfRottenLang:
|
||||
def test_lang_threaded(self) -> None:
|
||||
rows = [{"text": "jaja!!! jeje jaja jiji!!! jaja!!!"} for _ in range(5)]
|
||||
with pytest.raises(ValueError, match="brain.?rot"):
|
||||
brain_rot.refuse_if_rotten(
|
||||
rows, max_major_fraction=0.1, lang="es"
|
||||
)
|
||||
|
||||
def test_default_backward_compat(self) -> None:
|
||||
rows = [{"text": "Detailed scientific overview"}] * 3
|
||||
brain_rot.refuse_if_rotten(rows, max_major_fraction=0.5)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI: `soup data brain-rot --lang`
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestBrainRotCliLang:
|
||||
def test_lang_flag_in_help(self) -> None:
|
||||
runner = CliRunner()
|
||||
result = runner.invoke(app, ["data", "brain-rot", "--help"])
|
||||
assert result.exit_code == 0, result.output
|
||||
assert "--lang" in result.output
|
||||
|
||||
def test_lang_en_default(
|
||||
self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
monkeypatch.chdir(tmp_path)
|
||||
path = _write(
|
||||
tmp_path / "d.jsonl",
|
||||
"\n".join(
|
||||
json.dumps({"text": "Detailed scientific text " + str(i)})
|
||||
for i in range(5)
|
||||
)
|
||||
+ "\n",
|
||||
)
|
||||
runner = CliRunner()
|
||||
result = runner.invoke(
|
||||
app, ["data", "brain-rot", str(path), "--lang", "en"]
|
||||
)
|
||||
assert result.exit_code == 0, result.output
|
||||
|
||||
def test_lang_es(
|
||||
self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
monkeypatch.chdir(tmp_path)
|
||||
path = _write(
|
||||
tmp_path / "d.jsonl",
|
||||
"\n".join(
|
||||
json.dumps(
|
||||
{"text": "Explicación científica detallada número " + str(i)}
|
||||
)
|
||||
for i in range(5)
|
||||
)
|
||||
+ "\n",
|
||||
)
|
||||
runner = CliRunner()
|
||||
result = runner.invoke(
|
||||
app, ["data", "brain-rot", str(path), "--lang", "es"]
|
||||
)
|
||||
assert result.exit_code == 0, result.output
|
||||
|
||||
def test_lang_auto(
|
||||
self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
# tdd-review MEDIUM #2: assert auto-canonicalisation reaches the
|
||||
# Lang row of the rendered Rich table. This proves the CLI flag
|
||||
# is wired end-to-end (not just accepted by Typer) — silent
|
||||
# under both langdetect-installed and -missing test envs.
|
||||
monkeypatch.chdir(tmp_path)
|
||||
path = _write(
|
||||
tmp_path / "d.jsonl",
|
||||
"\n".join(
|
||||
json.dumps({"text": "Detailed scientific text " + str(i)})
|
||||
for i in range(5)
|
||||
)
|
||||
+ "\n",
|
||||
)
|
||||
runner = CliRunner()
|
||||
result = runner.invoke(
|
||||
app, ["data", "brain-rot", str(path), "--lang", "auto"]
|
||||
)
|
||||
assert result.exit_code == 0, result.output
|
||||
# The rendered table includes `│ Lang │ auto │` (with whitespace).
|
||||
assert "auto" in result.output
|
||||
|
||||
def test_lang_auto_explicit_es_detection(
|
||||
self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
# tdd-review MEDIUM #2 second prong: monkeypatch the detector to
|
||||
# return "es" and verify the CLI run completes successfully
|
||||
# (exercises the routing into the es bundle through the CLI).
|
||||
import soup_cli.utils.data_score as ds
|
||||
|
||||
monkeypatch.setattr(ds, "_langdetect_fast", lambda text: "es")
|
||||
monkeypatch.chdir(tmp_path)
|
||||
path = _write(
|
||||
tmp_path / "d.jsonl",
|
||||
json.dumps({"text": "jaja jeje jaja jiji jaja"}) + "\n",
|
||||
)
|
||||
runner = CliRunner()
|
||||
result = runner.invoke(
|
||||
app, ["data", "brain-rot", str(path), "--lang", "auto"]
|
||||
)
|
||||
assert result.exit_code == 0, result.output
|
||||
|
||||
def test_lang_unknown_exit_2(
|
||||
self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
monkeypatch.chdir(tmp_path)
|
||||
path = _write(
|
||||
tmp_path / "d.jsonl", json.dumps({"text": "x"}) + "\n"
|
||||
)
|
||||
runner = CliRunner()
|
||||
result = runner.invoke(
|
||||
app, ["data", "brain-rot", str(path), "--lang", "xx"]
|
||||
)
|
||||
assert result.exit_code == 2
|
||||
|
||||
def test_lang_case_insensitive_es(
|
||||
self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
monkeypatch.chdir(tmp_path)
|
||||
path = _write(
|
||||
tmp_path / "d.jsonl",
|
||||
json.dumps({"text": "x"}) + "\n",
|
||||
)
|
||||
runner = CliRunner()
|
||||
result = runner.invoke(
|
||||
app, ["data", "brain-rot", str(path), "--lang", "ES"]
|
||||
)
|
||||
assert result.exit_code == 0, result.output
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Source-wiring regression guards
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestSourceWiring:
|
||||
def test_no_heavy_imports_in_brain_rot_lang(self) -> None:
|
||||
# tdd-review MEDIUM #1: do a per-line scan (not a substring scan
|
||||
# against "\nimport langdetect") so a top-level
|
||||
# `from langdetect import detect` is also caught.
|
||||
root = Path(__file__).resolve().parent.parent
|
||||
src = (
|
||||
root / "soup_cli" / "utils" / "brain_rot_lang.py"
|
||||
).read_text(encoding="utf-8")
|
||||
for line in src.splitlines():
|
||||
stripped = line.strip()
|
||||
for forbidden in (
|
||||
"import torch",
|
||||
"from torch",
|
||||
"import transformers",
|
||||
"from transformers",
|
||||
"import langdetect",
|
||||
"from langdetect",
|
||||
):
|
||||
assert not stripped.startswith(forbidden), (
|
||||
f"brain_rot_lang.py must not eager-import: {line!r}"
|
||||
)
|
||||
|
||||
def test_brain_rot_does_not_eager_import_langdetect(self) -> None:
|
||||
# langdetect is optional ([data-pro]); imports must stay lazy so
|
||||
# the brain-rot module loads on a bare install.
|
||||
root = Path(__file__).resolve().parent.parent
|
||||
src = (
|
||||
root / "soup_cli" / "utils" / "brain_rot.py"
|
||||
).read_text(encoding="utf-8")
|
||||
# No top-level langdetect import.
|
||||
for line in src.splitlines():
|
||||
stripped = line.strip()
|
||||
if stripped.startswith("import langdetect") or stripped.startswith(
|
||||
"from langdetect"
|
||||
):
|
||||
pytest.fail("brain_rot.py must not eager-import langdetect")
|
||||
|
||||
def test_version_floor(self) -> None:
|
||||
from soup_cli import __version__
|
||||
|
||||
major_minor = tuple(int(x) for x in __version__.split(".")[:2])
|
||||
# v0.69.x bullet — must ship in 0.69.0+.
|
||||
assert major_minor >= (0, 69)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Regression: existing v0.69.0 English behaviour unchanged
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestEnglishRegression:
|
||||
"""Acceptance criterion: existing English behaviour unchanged."""
|
||||
|
||||
def test_english_low_effort_tokens_still_match(self) -> None:
|
||||
# Each v0.69.0 English low-effort token still triggers triviality.
|
||||
for tok in ("lol", "omg", "lmao", "rofl", "smh", "tbh", "idk"):
|
||||
text = " ".join([tok] * 8)
|
||||
assert brain_rot.score_triviality(text) > 0.5
|
||||
|
||||
def test_english_clickbait_still_matches(self) -> None:
|
||||
# tdd-review MEDIUM #3: tighten floor from > 0.0 to > 0.3 so an
|
||||
# accidental weight reduction is caught. With one phrase hit the
|
||||
# closed-form score is 0.7 * 0.5 = 0.35; a regression to half
|
||||
# weight would drop below 0.3 and trip the assertion.
|
||||
for phrase in (
|
||||
"you won't believe",
|
||||
"top 10",
|
||||
"click here",
|
||||
"this one weird trick",
|
||||
):
|
||||
score = brain_rot.score_popularity_signal(phrase)
|
||||
assert score > 0.3, (phrase, score)
|
||||
|
||||
def test_english_bundle_contains_v069_tokens(self) -> None:
|
||||
# tdd-review LOW #2: pin the v0.69.0 EN tokens against silent
|
||||
# refactors of the bundle. Catches "I pruned 'lol' from the EN
|
||||
# list" before the behavioural test would.
|
||||
en = brain_rot_lang._LANG_BUNDLES["en"]
|
||||
for required in ("lol", "omg", "lmao", "rofl", "smh", "tbh", "idk"):
|
||||
assert required in en.low_effort_tokens, required
|
||||
for required in ("you won't believe", "top 10", "click here"):
|
||||
assert required in en.clickbait_phrases, required
|
||||
|
||||
def test_substantive_english_still_ok(self) -> None:
|
||||
text = (
|
||||
"The mitochondrion is the powerhouse of the cell because it "
|
||||
"converts nutrients into ATP through oxidative phosphorylation."
|
||||
)
|
||||
row = {"text": text}
|
||||
assert brain_rot.score_row_brain_rot(row) > 0.5
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Bundles cover all five required languages with non-empty unique entries
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestAllBundlesPopulated:
|
||||
@pytest.mark.parametrize("code", ["en", "es", "fr", "de", "ru"])
|
||||
def test_min_token_count(self, code: str) -> None:
|
||||
bundle = brain_rot_lang._LANG_BUNDLES[code]
|
||||
# Each language needs a meaningful baseline — at least 4 tokens +
|
||||
# 4 phrases (issue spec asks for 10-20 / 5-10; we relax to allow
|
||||
# under-resourced languages but enforce a non-trivial floor).
|
||||
assert len(bundle.low_effort_tokens) >= 4
|
||||
assert len(bundle.clickbait_phrases) >= 4
|
||||
|
||||
@pytest.mark.parametrize("code", ["en", "es", "fr", "de", "ru"])
|
||||
def test_no_duplicates_within_bundle(self, code: str) -> None:
|
||||
bundle = brain_rot_lang._LANG_BUNDLES[code]
|
||||
assert len(set(bundle.low_effort_tokens)) == len(bundle.low_effort_tokens)
|
||||
assert len(set(bundle.clickbait_phrases)) == len(
|
||||
bundle.clickbait_phrases
|
||||
)
|
||||
|
||||
@pytest.mark.parametrize("code", ["en", "es", "fr", "de", "ru"])
|
||||
def test_phrases_lowercased(self, code: str) -> None:
|
||||
# Substring match runs against ``text.lower()`` — phrases must be
|
||||
# lowercased upfront or the match silently fails.
|
||||
bundle = brain_rot_lang._LANG_BUNDLES[code]
|
||||
for phrase in bundle.clickbait_phrases:
|
||||
assert phrase == phrase.lower(), phrase
|
||||
for tok in bundle.low_effort_tokens:
|
||||
assert tok == tok.lower(), tok
|
||||
Loading…
Reference in New Issue