Over-long inputs produced two different client errors depending on
which bound rejected them: the TokenizerManager pre-check (raw
context_len) returned 413 PayloadTooLargeError ('The input (N tokens)
is longer than the model's context length (M tokens).'), while inputs
between that and the scheduler's stricter effective limit hit
validate_input_length and returned 400 BAD_REQUEST with different
wording (and a confusing 'X exceeds X' message since the check is >=).
Unify on the 413 format end to end:
- validate_input_length wording now matches the TokenizerManager
message, reporting the effective per-request limit.
- set_finish_with_abort takes status_code/err_type; the scheduler
length-rejection sites abort with REQUEST_ENTITY_TOO_LARGE +
PayloadTooLargeError. The batch handler previously queued the
over-long request WITHOUT marking it aborted (it proceeded to
prefill) — also fixed.
- Non-streaming aborts with 413 raise PayloadTooLargeError (now a
ValueError subclass so raw /generate-style endpoints that only
catch ValueError still respond; the OpenAI layer's except clause
is reordered to win and emit the 413 format).
- Streaming abort responses prefer the scheduler-provided err_type
over the HTTPStatus name.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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