[Bugfix][gpt-oss] fix tool-call leak under tool_choice="required"#42031
[Bugfix][gpt-oss] fix tool-call leak under tool_choice="required"#42031ankrovv wants to merge 2 commits into
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Code Review
This pull request simplifies the reasoning parser by activating the structured-output matcher upon detecting the <|end|> token in the generated stream, while disabling prompt-side detection. However, the review identifies several critical issues: always returning False in is_reasoning_end breaks support for request continuations with pre-existing reasoning; the logic fails to account for cases where the model skips the analysis channel entirely; and the streaming implementation is fragile regarding iterator consumption and multi-token deltas during speculative decoding.
| # commentary triggers (and at_least_one:true) mask logits to force | ||
| # the commentary channel via real special tokens, rather than | ||
| # byte-imitating the tool-call frame inside final-channel content. | ||
| return self._analysis_close_token_id in delta_ids |
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In is_reasoning_end_streaming, delta_ids is an Iterable[int]. If it is an iterator (e.g., from itertools.islice as used in vllm/v1/structured_output/__init__.py), using the in operator will consume it. While the current implementation only performs one check, this is fragile and will lead to bugs if additional checks are added.
Furthermore, if delta_ids contains multiple tokens (e.g., during speculative decoding) and <|end|> is not the last token, vllm's should_advance logic will skip advancing the grammar for the entire delta in the current step, but will then attempt to advance the grammar with the entire delta (including the <|end|> token) in the next step. This will likely cause a grammar failure if the structured output grammar (e.g., JSON) does not expect the reasoning end marker. Consider converting delta_ids to a tuple and ensuring the trigger only matches if it's at the end of the sequence, or handling the transition more robustly.
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Activate the structured-output matcher for GPT-OSS on the FIRST generated
<|end|> token that closes the analysis channel, BEFORE the model emits the
next channel-selection token. The previous trigger
(<|channel|>final<|message|>) fires AFTER the model has already chosen the
final channel, leaving only byte-imitation as a path to satisfy a
structural_tag with commentary triggers (and at_least_one:true) — which
produces the well-known harmony marker leak in message.content /
output_text.
Path-A streaming gate: is_reasoning_end_streaming returns True iff
delta_ids contains <|end|> AND the most recent <|channel|> header in
input_ids was the analysis channel. Channel verification
(_last_channel_was_analysis) prevents false fires from non-analysis
<|end|> tokens (tool results, intermediate finals).
is_reasoning_end is unchanged from upstream — preserves continuation /
prefix-fill / multi-turn behavior. Streaming and non-streaming now answer
different questions ("did reasoning just end in delta" vs "has reasoning
ended overall"), so the previous parameterized tests that asserted
streaming agree with non-streaming on every test case have been removed
and replaced with three new tests that target the actual behavior change.
Known limitations documented in the streaming docstring:
- Final-first generation (no analysis block) does not fire this gate.
- Speculative decoding with multi-token <|end|> deltas is not addressed
here; needs verifier-level batch truncation, filed as follow-up.
Signed-off-by: Aniruddh Krovvidi <aniruddh.krovvidi@oracle.com>
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ankrovv
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ankrovv
requested review from
aarnphm,
bbrowning,
chaunceyjiang and
sfeng33
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The semantics we follow for other models when passing tool_choice="required" is to ignore any client-supplied structured output params and instead replace with one generated server-side from the tool schema. I do agree that it doesn't look like we're doing the right thing here for gpt-oss models, but I also don't think the behavior you want from the gRPC endpoint matches what we do for other models. |
2 participants
Purpose
Fix harmony control token leak under
tool_choice="required"on gpt-oss when the caller passes astructural_tagwith harmony-marker triggers (e.g. SMG → vLLM gRPC).Bug:
is_reasoning_end_streamingactivates the matcher when<|channel|>final<|message|>lands ininput_ids. By then the channel is already chosen. Matcher cannot redirect. Model satisfies thestructural_tag by byte-imitating the commentary frame inside final-channel content:
"message": {
"content": "<|channel|>commentary to=functions.X<|message|>{...}",
"tool_calls": null
}
Fix: activate on the first generated
<|end|>(analysis close), before the next channel-selection token.Matcher can now mask
finaland forcecommentary. Model emits a real tool call.is_reasoning_endis unchanged._last_channel_was_analysisrejects<|end|>tokens that closenon-analysis messages (tool result, intermediate final close).
Test Plan