Every printed and documented `pip install 'soup-cli[extra]'` was bash / zsh /
PowerShell syntax and failed on Windows cmd.exe:
ERROR: Invalid requirement: "'soup-cli[train]'": Expected package name at
the start of dependency specifier
cmd.exe has no single-quote quoting, so it passes the quotes to pip verbatim
and pip rejects the requirement. Nothing in Soup can fix that once the command
is typed -- pip and the shell own it, and Soup is not installed yet when the
README line runs -- so the fix is the spelling we print.
Migrated 147 sites across 67 files to `pip install "soup-cli[extra]"`:
- 64 in src/ (Rich console hints + plain ImportError text)
- 57 in README.md + docs/
- 22 in src/soup_cli/templates/*.yaml + examples/configs/*.yaml
- 3 in examples/README.md
Double quotes are the only spelling valid in every shell (cmd, PowerShell,
bash, zsh), which is why the repo already used `pip install -e ".[dev]"`.
Measured on Windows: single quotes fail ONLY on cmd; double quotes pass
everywhere; bare passes on Windows but zsh globs `[extra]` and fails.
Method note (the PR #247 class): the hints sit INSIDE double-quoted Python
string literals, so a blind ' -> " sed produces SyntaxError. A tokenize-based
rewriter escaped `\"` in DQUOTE tokens and left bare `"` in TRIPLE / COMMENT
tokens; every touched .py was compile-checked. The full suite (not ruff, not
compile-check) caught two rewriter blind spots: the real YAML templates under
src/soup_cli/templates/ (byte-identical drift test) and examples/README.md.
A regression test (tests/test_v07137.py) scans the package and every docs code
block for the single-quoted form; prose may still name it so a reader from an
older tutorial recognises the error.
Also bundles #315 (@Sanjays2402): eval-gate benchmark tasks now run via
ForgettingDetector instead of a helper that never existed. Closes#310.
Test count: 16283 -> 16288 (+4 in tests/test_v07137.py).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Version 0.71.35 -> 0.71.36 in pyproject.toml + __init__.py.
Docs are written around what the live smoke MEASURED, not what the plan
assumed:
- The semantic-dedup headline is WITHDRAWN. docs/data.md leads with the
measured overlap: paraphrase cosines (0.49-0.76) overlap genuinely-distinct
rows (0.54-0.76), and "Add two numbers"/"Multiply two numbers" (0.759)
scores HIGHER than the true paraphrase "reverse a string"/"invert the order
of characters" (0.491). No threshold separates them, so the page says
plainly that lowering --threshold trades duplicates for silent data loss,
and explains why the 0.8 default is deliberately conservative. The claim it
does make -- catches REWORDINGS MinHash's shingling misses (0.88-0.91) --
is the one the numbers support.
- docs/data.md canary section states the real verdict rule (binomial tail
over the count, not any-single-canary) and why: at K=16 an any-canary rule
fires on a CLEAN model ~15% of the time.
- docs/training.md --replay reports the honest result: 7% better retention
than control, but forgetting without it was only +4% (mild), so it is
proof-of-mechanism at 135M + LoRA, not a production claim.
- CHANGELOG known-limitations carry the same numbers rather than hedging.
- README What's New leads with the two blocking bugs the smoke found (the
hardware-fit gate refusing locally-merged models; the [extra] hints
printing without the extra).
Counts 16001 -> 16254 tests, 313 -> 314 files (CONTRIBUTING).
Add `soup data doctor` and `soup data lint`, killing the top *silent*
fine-tune failures before a single training step: EOS-missing-from-labels
(the #1 "model never stops generating" bug), BOS duplication, no-system-role
templates, and preference-data length bias (the #1 silent DPO degradation) —
none of which any competitor (Unsloth/Axolotl/LlamaFactory) checks for.
- utils/data_doctor.py: 8-check chat-template compat report over a
tokenizer + sampled rows, OK/MINOR/MAJOR taxonomy mirroring diagnose;
--show-mask N renders per-token trained/masked colouring through the
SAME masking dispatch (_build_row_labels) the report itself uses, so
the two can never disagree about what's actually trained.
- utils/data_lint.py: preference-data linter (dpo/orpo/simpo/ipo/bco/kto)
— length bias (Cohen's d), label imbalance, near-duplicates (MinHash),
identical chosen==rejected pairs, prompt leakage.
- commands/data_doctor.py: Typer layer for both commands; strips C0
control bytes before untrusted dataset content reaches the terminal.
- commands/diagnose.py: hardens the --evidence loader against a TOCTOU
symlink swap (O_NOFOLLOW + fstat-on-open-fd), backporting the pattern
soup ship shipped in v0.71.25 (closes v0.71.25 known-limitation (4)).
Live smoke against the real HuggingFaceTB/SmolLM2-135M-Instruct tokenizer
(Windows + RTX 3050) found and fixed two genuine bugs beyond the synthetic
fixtures: the EOS check needed to span-search the whole trained region
(not just the last token), and two apply_chat_template call sites needed
a broad except Exception for jinja2.exceptions.TemplateError.
+173 tests (14788 -> 15042). 5 sequential ECC reviews, every finding fixed.
The README had grown to 5046 lines (195 sections) — roughly one deep-dive per
feature accreted over 70 releases. Split it into a concise front door plus a
public docs/ tree:
- README (5046 -> 238 lines): hero, why, quickstart, config, a Documentation
map, data formats, common commands, models, Docker, requirements, dev.
- docs/*.md: all 185 feature sections preserved verbatim, grouped into 10 themed
guides + an index. Every original line is accounted for (content-conservation
checked); all 235 internal links + anchors verified to resolve.
- un-gitignore docs/ (it was empty); fix a pre-existing dangling
docs/QUANTIZATION.md link; correct the stale `ruff check soup_cli/` ->
`src/soup_cli/` reference in the Development section.
No version bump: docs-only — rides into the 0.71.0 deps-split release.
Alpamys
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