[twu3202]

Purpose

Fixes #51374. Fixes #51376.

/v1/realtime runs one resumable request per session, and
Scheduler._update_request_as_session() appends the previous chunk's output
tokens to the next chunk's prompt. That is right for models whose realtime
prompt is a running conversation and which consume input_stream. It is wrong
for Qwen3-ASR: buffer_realtime_audio() emits a fresh single-turn ChatML prompt
per 5 s segment and never reads input_stream, so the generic carry-over turns
the session into a growing fake conversation whose assistant turns are the
model's own transcripts. When a segment's acoustic evidence is weak, the decoder
reproduces that history.

Segment N+1's prompt today:

[segment N prompt] + [segment N output tokens] + [segment N+1 single-turn prompt]

This change lets the model class declare whether earlier segments belong in its
context, and rebuilds the session from the new chunk alone when they do not.
Text, multimodal features, KV and block hashes move together, which is the
invariant asked for in #51376.

Measurements

vLLM at 144e79c, Qwen3-ASR-0.6B, one session per row, temperature=0. The
"alone" column is a fresh session containing only that audio, which separates
history contamination from the model's own behaviour on weak input.

English, using the mary_had_lamb and winning_call assets already in the repo:

segment 2 audio	before	after	alone
a different utterance	correct but drifts	correct, matches alone	correct
digital silence	copy of segment 1	Ahora.	Ahora.
white noise	copy of segment 1	empty	empty
1.2 s utterance + silence	copy of segment 1	And they.	And they.
short utterance, reverse order	copy of segment 1	哎呀！	哎呀！

Mandarin (FLEURS cmn_hans_cn, public) behaves the same on all five rows. After
the change every second segment matches its solo control verbatim, and the word
drift in the first row disappears with it.

The default path is unchanged

Flipping realtime_carries_context back to True for the same model on the same
audio reproduces the unpatched baseline byte for byte (diff reports no
difference). A unit test asserts the same at the scheduler level.

Why this is per-model and not a scheduler-wide change

Voxtral realtime consumes input_stream and is built around cross-segment
context. In a separate environment on 0.29.0, applying the reset to it
unconditionally produced three empty segments where the unpatched path
transcribes three consecutive slices as one continuous sentence. I could not
re-run that check for this PR: the checkpoint does not load on either vLLM
version in my environment (VoxtralRealtimeEncoderConfig has no
downsample_factor with transformers 5.16/5.17), identically with and without
this change.

Cost for opted-out models

12 segments: median first delta 53 -> 60 ms, median segment completion
314 -> 534 ms, still about 9x real time for 5 s segments. The "before" figures
are measured on contaminated output, so segment completion is not a
like-for-like comparison; first delta is unaffected by that.

Alternative considered

#51037 keeps same-request KV reuse via a stable-window policy. That is the better
end state; this is the small correctness-first step and does not conflict with it
(a model that gains a stable-window implementation sets the flag back to True).
There was also an offer to investigate #51376 in August; this is meant as a
concrete starting point, not a claim on the issue.

Design question for reviewers

The scheduler resolves the served model class once, lazily, on the first
streaming-session update. The same policy could instead ride on
EngineCoreRequest/Request next to resumable, set where AsyncLLM marks
streaming requests; that avoids the registry lookup in the scheduler at the cost
of touching more files. Happy to switch.

Test Plan

• python -m unittest tests/v1/streaming_input/test_scheduler_streaming.py
• A seven-scenario realtime script on Qwen3-ASR-0.6B, English and Mandarin.

Test Result

10 passed (8 existing, 2 new). Realtime scenarios as tabulated above.

AI assistance: the investigation, patch and tests were drafted with Claude and
re-run and reviewed by me.

[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

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[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @twu3202.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[twu3202]

Update after testing on current main with async scheduling, which is the default now (V2 model runner). Qwen3-ASR-0.6B realtime, one RTX 6000 Ada, mary_had_lamb.wav and winning_call.wav streamed in 4096-byte chunks, temperature=0.

With async scheduling, this PR alone is not enough. When a segment ends, a decode step from that segment is usually still in flight, and its result lands in the rebuilt session, so only the first segment is transcribed. Main has the same symptom for a different reason. #58259 fixes it where the turn stops. With both, async transcripts are byte-identical to no-async, paced and unpaced, and a 60 s stress run that crashes main (#35755) survives.

	segments (mary / winning_call)	transcript
main, async	1 / 1	first segment only
main, no async	4 / 6	every segment repeats the first one
#58259, async	4 / 6	every segment repeats the first one
this PR, no async	4 / 6	each segment transcribed on its own
this PR + #58259, async	4 / 6	same as the row above

I pushed a one-line change here: the restart no longer resets num_in_flight_tokens. With the reset, the two PRs together dropped segments when audio was sent unpaced.

[twu3202]

Now that #58259 is merged, I re-ran this on current main (32cc3f1): Qwen3-ASR-0.6B realtime on one RTX 6000 Ada, winning_call.wav streamed in 4096-byte chunks at real time. With the default async scheduling this PR no longer needs anything else. Its transcripts are the same with --no-async-scheduling and with unpaced input, and a 60 s stress run survives on both builds.

main:

language English<asr_text>And the 0-1 pitch on the way to Edgar Martinez swung on and landed in the left field.language English<asr_text>And the 0-1 pitch on the way to Edgar Martinez swung on and landed in the left field.language English<asr_text>And the 0-1 pitch on the way to Edgar Martinez swung on and landed in the left field.language English<asr_text>And the 0-1 pitch on the way to Edgar Martinez swung on and landed in the left field.language English<asr_text>And the 0-1 pitch on the way to Edgar Martinez swung on and landed in the left field.language English<asr_text>And the 0-1 pitch on the way to Edgar Martinez swung on and landed in the left field.

this PR:

language English<asr_text>And the 0-1 pitch on the way to Edgar Martinez swung on and landed in the left field.language English<asr_text>Base hit! Here comes Joy. Here is Junior to third base. They're gonna win.language English<asr_text>Believe him in. The throw to the plate will be late. The Mariners are going to.language English<asr_text>Play for the American League Championship! I don't.language English<asr_text>Believe it! It just continues. My, oh my!language English<asr_text>It.

[tamerrkanak]

@twu3202 FYI: #61031 (session.update language/prompt for Qwen3-ASR realtime) touches qwen3_asr_realtime.py and SupportsRealtime right next to this change. I checked that the two merge cleanly and ran them together; with both applied, every segment keeps the prompt (LibriSpeech test-clean, 5–15 s: rare-word recall 88.5% → 93.7%). Since you know this path well, a review would be very welcome.

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @twu3202.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[twu3202]

Rebased on main e80b6c6, after #58778. The one conflict was in _update_request_as_session: the opt-out still returns before the carry-over, and the carry-over test now follows #58778's rule that the last output token is not yet computed.

• test_scheduler_streaming.py: 17 passed (15 on main plus the 2 new ones).
• Qwen3-ASR-0.6B realtime, 16 FLEURS clips (en/zh): on main all 13 clips longer than 5 s repeat earlier-segment text, on this branch none do. With only the first 5 s sent, the output matches main for all 16.