v0.4.64 aimed one layer too high. Measured against the pod directly:

  content           = 'We need answer in Italian... 17 x 23 = ... **391**.'
  reasoning_content = ''
  has </think>      = False          finish = stop

The thought and the answer come back as ONE string with no separator of any
kind. </think> is a SPECIAL TOKEN and vLLM decodes with skip_special_tokens,
so the boundary is deleted before the text exists. No parsing downstream can
split on a boundary that was removed -- the earlier reading, "extraction fails
on the bare </think>", was simply wrong.

coderai never passed --reasoning-parser to vLLM, for any model, ever. With it
vLLM splits the two at the TOKEN level, before the tag is discarded, and
reports reasoning_content as its own field; the v0.4.64 side channel and delta
re-tagging then carry it to the client. Chosen from the template like the tool
parser, and only for a model whose template says it thinks -- a reasoning
parser on a model that does not think waits for a tag that is never coming. An
explicit vllm.reasoning_parser wins, "off" included, per model or globally.

AND A REGRESSION FROM v0.4.64, fixed here: with the gate switched on and no
close tag ever arriving, a streamed reply was held back in full as "thinking"
and the client was sent an empty message -- worse than the leak it replaced
(reasoning=229 chars, content=0, measured on diogene-alpha and qwen38 alike).
An unclosed thought now flushes as CONTENT. A thought truly cut off mid
sentence then reads as the answer, which is untidy; an empty answer is a lost
reply. With the server separating the channel this path stops being reached.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S8LAP3ueNzQJtwzhgVbq66