* fix(proxy): load db credentials inside the model reconcile so a worker never serves a model before its credential
* fix(proxy): load db credentials in the model read-through so a request miss never adds a model before its credential
* fix(proxy): read credentials from the writer db before the router update and look a credential up once
* test(proxy): assert the credential is loaded when db models reach the router instead of the call order
Resolve the conflicts in utils.py, types/router.py, and the tests, and collapse the 56 per-provider isinstance(drop_params, bool) gates to bool(drop_params) now that get_optional_params normalizes the flag once at the top
`vertex_ai/lyria-3-clip-preview` and `vertex_ai/lyria-3-pro-preview` were
registered with `supports_vision`, `supports_image_input`, and an `image`
modality, which contradicts their `gemini/lyria-3-*` siblings and makes
/model/info advertise image input on text-to-music models.
Google prices Lyria per generated clip, so every Vertex Lyria entry in the
price map now carries a single output_cost_per_image and both the speech
and the passthrough cost paths read that one field. The old
output_cost_per_second and audio_seconds_per_prediction pair assumed a
30 second clip, which does not match the 32.768 second WAV Vertex returns,
and no other model in the map priced audio that way
Drops max_audio_length_hours and max_audio_per_prompt from the price map,
its schema, the generator, and ModelInfo, since nothing reads them, and
drops the audio_mime_type hidden param for the same reason: the response
already carries the resolved content type on its own header
Folds the per-model bundled catalog lookups into one cached parse of the
local cost map, validated with a TypeAdapter over a ReadOnly TypedDict
A live cost map older than this release, or a proxy whose map fetch lags, could
strip `reasoning` from a model this release knows accepts it. The bundled map is
now the floor: any OpenAI entry it flags as reasoning keeps the param whatever
the live map says. Fine-tuned ids with an empty suffix (`ft:gpt-4o-2024-08-06:org::id`)
now resolve to their base entry instead of failing open, `chat-latest` carries
the flag, and the schema test keeps every codex, deep-research, and chat-latest
entry flagged. The none-effort check goes through a public wrapper so the
responses config stops importing a private helper.
The "Final returned optional params" line printed whatever the caller nested inside
extra_body, so a credential tucked in there reached stdout in plaintext one line after
the request line that already redacts it.
The call site now runs redact_credentials_in_payload behind a guard reading both of
print_verbose's consumers, litellm.set_verbose and the LiteLLM logger's DEBUG level, so
the line prints in exactly the cases it did before and the walk costs nothing when
nothing would read it.
redact_credentials_in_payload only recursed into mappings, so a
credential-named key one level inside a list or tuple, the shape
extra_body and metadata routinely carry, still reached stdout under
set_verbose. Rebuild sequences element by element too, keeping the
container's own type so the printed repr is unchanged apart from the
secret.
`litellm.set_verbose = True` printed the caller's kwargs verbatim to stdout, so
`api_key` and its siblings landed in terminals and container log drains in
plaintext while the same statement's logger emission was already redacted.
Mask the kwargs at the source with a shared helper in
`litellm_core_utils/sensitive_data_masker.py`, reusing the existing
`SensitiveDataMasker` key classification and the `REDACTED` marker
`secret_redaction.py` already owns, so both debug surfaces agree.
get_api_key had no callers. main.py imported it without using it, and
because main.py declares no __all__, the star import in __init__.py
published it as litellm.get_api_key. It duplicated key resolution that
get_llm_provider_logic already performs, which is how a misspelled env
var survived in it unnoticed until #35985. Drop the definition, the
unused import, the test that pinned the ai21 branch, and ratchet the
lint budgets down by the violations it carried.
Resolves LIT-5245
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Gemini 3.8 Flash launches today with the same promotional pricing, limits,
and thinking settings as Gemini 3.7 Flash, so the gemini/, vertex_ai/, and
bare cost map entries mirror the 3.7 Flash ones. Regression tests lock the
launch prices, the 4096-token cache minimum, and the gemini-3 thought
signature gate in for the new model.
Any registered guardrail made provider_specific_fields.search_results
vanish from /v1/chat/completions vector store responses, even when the
guardrail never ran. Two defects combined:
- CustomGuardrail.async_post_call_success_deployment_hook returned the
response instead of None when it did not run, claiming a modification
it never made
- the async_post_call_success_deployment_hook dispatcher in utils.py
returned at the first non-None callback result, so the lazily appended
VectorStorePreCallHook never got a chance to attach search_results
The hook now returns None when it does not run, and the dispatcher
chains non-None results through the remaining callbacks, matching the
pre-call dispatcher's behavior
