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.
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.
* fix(search): forward search-tool params through the router, complete Parallel AI v1 param mapping
SearchAPIRouter dropped every parameter configured on a search tool, forwarding
only per-request kwargs. Any tool-level setting (mode, max_results, ...) was
silently lost on the way to the adapter, for every search provider.
Also completes the Parallel AI v1 search surface: after_date, fetch_policy,
location and include_domains now nest under advanced_settings instead of being
sent as unknown top-level fields, responses preserve search_id / session_id /
warnings / raw excerpts, and search cost is derived from the request mode and
the provider's reported usage rather than a single flat rate.
* fix(parallel_ai): stop a caller from pricing its own search request
`_parallel_ai_usage` carries the provider's reported usage into cost
calculation. It was only written when the response contained a usage block, so
a caller could pass `_parallel_ai_usage=[{"name": "sku_search", "count": 0}]`
and, whenever the provider omitted usage, bill $0.00 instead of $0.005 — the
value also reached the upstream request body as an unknown field.
The key is now stripped from inbound params and written unconditionally from
the parsed response, so only the provider can populate it.
* fix(parallel_ai): price fast search mode correctly
* test(parallel_ai): fake search at HTTP boundary
* fix(parallel_ai): tolerate null search result fields
---------
Co-authored-by: khushishelat <shelatkhushi@gmail.com>
Adds claude-fable-5-1 cost map entries on the Anthropic API, Bedrock converse
(base, global, and us/eu geo inference profiles at the 10% regional premium),
Vertex AI, and Azure AI. Specs match Fable 5 (1M context, 128K output, $10/$50
per MTok, adaptive thinking always on, xhigh and max effort), except cache reads
land at $0.25 per MTok, a quarter of Fable 5's price and 0.025x base input
instead of the usual 0.1x.
Registers anthropic.claude-fable-5-1 in BEDROCK_CONVERSE_MODELS, lists the model
in the setup wizard, and extends the reasoning effort e2e grid. The partner cells
carry fail_reason markers until access on the CI accounts is confirmed.
Partner entries deliberately carry no deprecation_date: Anthropic publishes
retirement no sooner than 2027-09-01 for the first-party model, and the Foundry
and Vertex dates are not published yet.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
