OpenBMB / OpenBMB/VoxCPM

vLLM-Omni crashes on Hindi ref_audio with VoxCPM2 (/v1/audio/speech)

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Python
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Description

Describe the bug

When running vllm-omni with the VoxCPM2 model, the server crashes while processing requests to /v1/audio/speech if the ref_audio contains Hindi speech.

This results in an AssertionError inside the engine (StageEngineCoreProc), causing the entire service to terminate and requiring a manual restart.

The same workflow works correctly when the ref_audio contains English speech, suggesting a language-specific issue.

The same workflow also works correctly when tested using vLLM-Nano.

Root cause (from logs)

AssertionError: voxcpm2 prefill length mismatch: scaffold_len=182 tts_len=22;
caller must pad prompt_token_ids to the full prefill length

Version

vLLM Version: 0.19.0
vllm-omni version: main branch (post PR#2911)

Questions

1.Multilingual Support
Is VoxCPM2 expected to support non-English ref_audio (e.g., Hindi)?
2.Is this a known limitation of VoxCPM2 or an issue in vLLM-Omni?

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reproducing the crash through /v1/audio/speech with VoxCPM2 and Hindi ref_audio, then inspect the StageEngineCoreProc assertion and the reported prefill-length mismatch. Compare the same workflow with English ref_audio and vLLM-Nano. Done means determining whether non-English ref_audio is supported and preventing the service from terminating, with the expected behavior documented.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
audio-video-rtc, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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