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fix(server): bound GLiFormer decoded text by characters - #655
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Refs superlinked#378 The other bullets are untouched.
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Priority: ⬇️ Low Merge Risk: ⚪ Minimal · up to The character limits appear ready to merge after normal checks; no actionable issue remains in the supplied review evidence. Security Architecture Review
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Check name Status Explanation Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title clearly and concisely describes the main change: adding character limits to decoded GLiFormer text. Linked Issues check Check skipped because no linked issues were found for this pull request. Out of Scope Changes check Check skipped because no linked issues were found for this pull request.
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krisztian-gajdar
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cap GLiFormer output text by characters: close. The character sum runs even when the word cap already rejects the output, which is costly on adversarial inputs. The 1_048_576 cap has no stated origin and kicks in before the word cap on normal text.
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Inline comments:
Review comments at
@packages/sie_server/src/sie_server/adapters/gliformer/structuring_decoding.py:
- Line 155: Both decoders apply max_chars separately to flattened rows, allowing
groups with the same batch origin to exceed the per-document limit. In
structuring_decoding.py at line 155 and relation_decoding.py at line 137, group
rows by origin and select spans or relations against one shared character budget
per document, then preserve the existing per-group output structure when
unflattening.
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The character total was walked even when the word cap had already rejected the output. Token text is now read only for the best-first prefix that still fits in the word budget. 1_048_576 is four characters a word, so ordinary words hit it before the word cap. The cap is the word cap times 2048, the document length those bounds were measured on. Refs superlinked#378
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The character walk now happens only for text the word cap has not already rejected. On records and relations, a row whose words are over the cap reads token text for the best-first prefix that still fits in the word budget, and does not walk the rejected tail. 1_048_576 was four characters per word of the 262144 word cap, so ordinary words reached it first. The cap is now the word cap times 2048. That 2048 is the document length in words already used for these bounds, and it is the most characters one ordinary token may take. Shorter tokens hit the word cap first. One token longer than that is what the character bound is for.
Refs #378 |
krisztian-gajdar
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Thanks, the word-cap short circuit looks right now, and the tracing tests pin it down nicely.
Two things before this can go in:
- Cap size.
MAX_RELATION_CHARS = MAX_RELATION_WORDS * 2048(relation_decoding.py:40) andMAX_RECORD_CHARS = MAX_RECORD_WORDS * 2048(structuring_decoding.py:52) come to about 512 Mi characters per document, so the cap only binds in the extreme nested case and a single document can still return hundreds of MB. 2048 is a document length in words, but here it is used as characters per word. Something like 16 or 32 characters per word would keep normal text on the word cap first while actually bounding long tokens. - CodeRabbit thread. The open thread on
structuring_decoding.py:160(allowances per flattened row) is valid in principle but out of scope here. It is the separate #378 item "Look up decode allowances throughbatch_origin", and today the adapter produces one group per document. Could you reply on the thread saying so and resolve it?
The earlier nits (sharing _span_chars via span_decoding.py, the default on _row_relations, the _within_word_limit name) are optional.
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The character cap is now 32 characters per word, not 2048: 2048 was a document length in words, used here as characters per word, so the cap was about 512 Mi characters and barely bound a document. 32 is the top of the 16-or-32 range. Many ordinary English words are longer than 16 characters, so 16 would reject ordinary text before the word cap. At 32, an 8-letter word still hits the word cap first (8 < 32): a full word cap of them, plus the joining spaces, stays under the character cap. A token longer than 32 characters is what the character cap is for. The word-cap short circuit is unchanged. Token text the word cap already rejected is not read. The CodeRabbit thread on
Refs #378 |
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Thanks, the 32 characters per word cap looks right and the CodeRabbit thread is resolved. One comment-only change and this is good to go.
The comment above MAX_RECORD_CHARS (structuring_decoding.py:44-49) and the matching one above MAX_RELATION_CHARS (relation_decoding.py) have three problems:
- "Many ordinary English words are longer than 16 characters" is not the case.
- "32 is used instead of 16" describes this review rather than the code.
- "A token longer than 32 characters is what this bound is for" does not match how the cap works. It is a total per document, so a single 40-character token passes. It only binds when the decoded text averages more than about 31 characters per counted word.
Something along these lines would be accurate: "32 characters per counted word, including the joining space. The bound is per document, so text averaging under 31 characters a word reaches the word cap first, and text made of very long tokens reaches this cap."
Optional: the test docstring repeats the per-token wording, and assert ordinary < 32 does not test anything.
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The character cap is a document total of 32 characters per counted word, including the joining space ( |
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Summary
GLiFormer capped decoded record and relation text by word count only (
MAX_RECORD_WORDS/MAX_RELATION_WORDS= 262144). One very long token counts as a single word, so a document could still return a huge string.Decoding now also stops at 1,048,576 characters of field text per document. Spans are dropped in the same lowest-score-first order the word cap already uses. Short spans are unchanged.
The other #378 follow-ups are untouched: the float32 load-time probe,
batch_originallowance lookup, and required-field billing.Compatibility
Responses that were previously accepted only because a long token counted as one word can now drop that span. Word-cap behavior for normal tokens is unchanged. No request schema change.
Tests
pytest packages/sie_server/tests/adapters/test_gliformer_span_decoding.py— 282 passed.Refs #378
Summary by CodeRabbit