The openai gpt-6-astra card carries supports_prompt_cache_breakpoint, so a Foundry deployment
reported it as true until the azure_ai row took over the lookup. The cache control hook still
honours breakpoints for that deployment through the bare name, so /model/info was the only thing
that changed, and it now agrees with the hook again.
`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
Both Azure routes refuse it. A live call to the same deployment through
openai/deployments/gpt-6-astra/chat/completions on api-version 2025-04-01-preview
answers reasoning_effort max with a 400 unsupported_value naming none, low, medium,
high and xhigh as the values it takes, and xhigh returns 200, so azure/gpt-6-astra
and azure/us/gpt-6-astra now match the azure_ai row.
Foundry rejects reasoning_effort max on the gpt-6-astra deployment with a 400 that
names none, low, medium, high, and xhigh as the supported values, so the card no
longer lists max. The request path never gated max (only xhigh is opt-in), so this
only changes /model_group/info and router capability gating. The azure/ twin stays
as is because it was not verified on an Azure OpenAI host
Foundry deployments of gpt-6-astra reached through azure_ai used the bare OpenAI card
for the reasoning_effort none gates, so temperature and top_p were refused while the
azure_ai card says none is supported. AzureAIStudioConfig now dispatches gpt-5 series
params through AzureAIGPT5Config, which looks capabilities up under the azure_ai/
prefix the way the azure route does
Also carries the search_context_cost_per_query block azure/gpt-6-astra has, adds a
flex service tier cost test that fails at the merge base, and keeps the wildcard test
from stripping azure_ai/gpt-6-astra out of the provider set
A gpt-6-astra deployment on a Foundry project reached through the
azure_ai route had no cost map entry of its own, so it resolved to the
OpenAI gpt-6-astra card: missing from the azure_ai/* wildcard listing,
flex and priority prices and /v1/batch it does not sell, and no none
reasoning effort. Add azure_ai/gpt-6-astra mirroring the
azure/gpt-6-astra Standard Global sheet the way azure_ai/gpt-5.5 mirrors
azure/gpt-5.5, and extend the cost, reasoning-effort, and wildcard
listing tests to the Foundry route.
Every model bedrock list-foundation-models and list-inference-profiles
report as live in us-gov-west-1 or us-gov-east-1 now has a priced row:
Claude Fable 5.1 (profile plus in-region), Nemotron Nano 9B (profile plus
in-region), Grok 4.6 (profile plus Mantle in both regions), the us-gov.
Claude 3 Haiku profile in the east, Nova Lite, Micro and the Nova 2
multimodal embeddings in the west, and the Gemma 4 and gpt-oss Mantle
SKUs the GovCloud offer files price. Offer-file rates are used where AWS
publishes them; Claude rows carry the 1.2x GovCloud premium.
OpenAI documents low, medium, high, xhigh, and max for gpt-6-astra, with no none level, so the entry stops advertising none and starts advertising max.
Adds the OpenAI gpt-6-astra entry to both price files with standard, flex, priority (fast mode), batch, and above-272K long-context rates, and regression tests covering each tier and the batch rates.
Resolves the tests/test_litellm/test_main.py collision, where both sides appended a
new test at the end of the file, by keeping both.
Also carries the one-line fix from #39502: staging arrived with a duplicate
embedding_executor kwarg in the Bedrock KB fake handler, which ruff rejects as a
syntax error, so every commit here would otherwise fail lint. The change is byte
identical to #39502, so that PR merges cleanly once it lands.
