* fix(health): correct bedrock embedding health checks
Health checks for Bedrock embedding deployments failed in two ways. A
deployment configured without an explicit model_info.mode was probed as
chat, so max_tokens was injected and Bedrock embeddings rejected it with
400 "extraneous key [max_tokens]". Separately, stripping the bedrock/
routing prefix dropped the provider, so a cross-region inference-profile
id like us.cohere.embed-v4:0 failed downstream with "LLM Provider NOT
provided".
Resolve the deployment mode from the model cost map (which understands
the bedrock/ and us./eu./apac. prefixes) before deciding whether to
inject max_tokens, and pin custom_llm_provider to bedrock when stripping
the prefix so the bare model id still resolves. ahealth_check now accepts
any string mode so the resolved embedding mode routes the probe to the
embedding handler.
* fix(health): preserve explicit custom_llm_provider on bedrock probe
The bedrock prefix-strip pinned custom_llm_provider to bedrock
unconditionally, so a deployment that set custom_llm_provider:
bedrock_converse had it overwritten at health-check time and the probe
hit the Invoke endpoint instead of Converse, a different request format
that can report a spurious failure. Only fill in bedrock when the
deployment left the provider blank, which still resolves bare
cross-region ids like us.cohere.embed-v4:0 while leaving an explicit
provider untouched.
* test(health): assert resolved mode reaches the ahealth_check probe
The existing tests check _resolve_health_check_mode and the params builder
in isolation, but nothing verified that _run_model_health_check actually
threads the resolved mode into litellm.ahealth_check. Without that, a
refactor that probed with model_info.get("mode") again would reintroduce
the chat fallback for embedding deployments while every test stayed green.
This drives _run_model_health_check with a bedrock embedding deployment and
asserts the probe is called with mode=embedding and the embedding params.
* fix(health): resolve probe mode once for reasoning_effort and audio_speech
The reasoning_effort and audio_speech branches read model_info.mode
directly, so an embedding deployment declared without an explicit mode (the
case this PR targets) was still treated as chat-like: a configured
health_check_reasoning_effort got injected into the embedding probe, which
embeddings reject as an unknown field, and an auto-detected audio_speech
deployment never had its voice set. Resolve the effective mode once from the
cost map and reuse it for the max_tokens, reasoning_effort, and audio_speech
decisions so they all agree with the mode threaded into ahealth_check.
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