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ddd66e1d25
DashScope's OpenAI-compatible /embeddings endpoint rejects requests with
more than 10 input items (documented Model Studio cap). The generic
per-recipe max_batch_items field + gateway capBatchItems pre-split
already exist (#1281); the in-tree dashscope recipe just never declared
the cap, so large embed backfills would send oversized batches and get
rejected server-side. Declare max_batch_items: 10 on the dashscope
embedding touchpoint; max_batch_tokens stays as the aggregate
token-size guard.
Test: pins dashscope's max_batch_items === 10 (+ max_batch_tokens
unchanged) and that 25 items pre-split into groups of at most 10 via
capBatchItems, alongside the existing llama-server cap pin.
No new models or recipes; no error-sniffing/halving recovery — the
pre-split makes the failure unreachable. Item-cap concept credited to
declined community PRs #2643 and #2405.
Also verified (no code change needed): #2103's litellm three-way dead
end is already fixed on master by a25209bb (#2271) via trust_custom_dims.
Co-authored-by: Garry Tan <garrytan@gmail.com>
Co-authored-by: Yicong <charlieyiconghuang@gmail.com>
Co-authored-by: Cheng Zijun <robotics.chengzijun@gmail.com>
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>