The LLM classifier's cost was recorded on the routing decision but never
reached any savings surface: per-request autorouter_savings stayed gross
and the session rollup recorded only the served request's spend, so
/auto_router/benchmarks overstated savings and understated routed spend.
Net the classifier cost into the savings figure at its one computation
owner and fold it into the rollup turn's spend, keeping
baseline_spend = spend + saved_spend. The response header's numeric
guard now shares the same reader.
Fixes#38816
* fix(proxy): run SMTP send_email off the event loop with a connection timeout
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): format utils.py and update _create_smtp_connection tests for timeout
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep malformed SMTP_TIMEOUT inside the email error boundary
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: retrigger ci
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: exclude misaligned circleci coverage flag from merged codecov report
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: retrigger ci for codecov and benchmarks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: disable carryforward for the circleci codecov flag
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: exclude carried-forward coverage from the codecov patch status
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: stop carrying forward the dead circleci codecov flag
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Four cases in tests/e2e/quota_management/budgets, driving real OpenAI calls
through a group whose shared pool is drained to exhaustion: the spender key
stays blocked, a key that spent nothing of its own is blocked by the same
pool, a sibling group with no budget keeps serving, and the budget read
reports the spend drawn against the group.
Adds set/get/delete access group budget to BudgetClient and the four
matching rows to the coverage registry.
The Together catalog exposes only context_length, so the sync was recording
every chat model's context window as its output ceiling. New entries now carry
max_input_tokens and the legacy max_tokens from the catalog and get an output
ceiling only from a reviewed capability rule. GLM-5.2 and GLM-5.3-Flash rules
carry the documented 128K ceiling, and the 26 other inflated together_ai chat
entries drop max_output_tokens in both registry copies.
A deployment carrying reasoning_effort in its litellm_params on the
/v1/messages passthrough mapped the effort to a legacy thinking block
whose budget_tokens was forwarded as is, so any request whose max_tokens
sat at or below that budget was rejected upstream with a 400. The mapped
budget now runs through the same cap the adaptive-to-legacy branch and
the chat path already use: it is clamped to max_tokens - 1, and dropped
with a warning when even the minimum budget cannot fit.
The cap helper becomes public since three call sites outside
AnthropicConfig use it.
A pool whose recorded spend has reached max_budget has nothing left to give, so
the next request is refused rather than admitted. This departs from the tag
check it otherwise mirrors and matches where keys and organizations already
draw the line.
A non-positive budget now means no budget here too, so the read-time check and
the reservation path agree on what counts as unbudgeted.
The four model access group callback tests now share one helper, so nine
patches of proxy_server internals become three, and both mock-echo assertions
go with them. The delete_access_group tests share a context manager for the
same reason.
test_group_exactly_at_its_max_budget_passes gained the assertion it was
missing: it now proves the group reached the spend comparison, which a group
skipped for a missing budget row would not. The route-allowed patch beside it
was dead, so it is gone.
What is left is suppressed with the collaborator each one cannot inject.
GPT-5 and later accept a top-level anyOf natively and call tools better with it intact, so the flattening now runs only for the gpt-4, gpt-3.5, chatgpt-4o, o1, o3, and o4 families. Non-dict tool entries pass through untouched, a typeless root that carries properties counts as an object, and the bounded $ref walker is listed in the recursion detector allowlist.
The database writer already intersects the auth-matched groups with the ones
the served deployment declares, but the live spend counters got the unnarrowed
set. A caller granted two pools that both cover a model group debited both
counters while only one row moved, so the in-memory ceiling could block a pool
its persisted spend never touched.
Narrow once at the callback so both consumers read the same set.
The cache TTL for a group's budget row was a new
DEFAULT_MODEL_ACCESS_GROUP_CACHE_TTL env var defaulting to 600 seconds, which
nobody asked for and which the docs gate rightly rejected as undocumented.
Every other management object cached in auth_checks, tags included, already
reads get_management_object_ttl, so it honors general_settings
user_api_key_cache_ttl and falls back to the shared default. Group budgets now
do the same, which drops a constant, drops an env var, and makes the row expire
on the same operator knob as keys and teams.
Also formats ModelAccessGroupBudgetRepository, and teaches the FakeBatch double
in the unit of work tests about the new table. That double is read while the
cascade unit of work is constructed rather than inside the block, so three tests
that never mention access groups were failing at the async with. The new test
alongside it walks the dataclass fields, so the next dependent added to the
cascade is covered without anyone remembering to update a list.
Budget enforcement trusts a current LiteLLM_BudgetWindowSpend row without
reconciling it against LiteLLM_SpendLogs, so an increment dropped after a
failed commit let the entity spend past its window limit after the next
counter reseed. Failed increments now go back on the in-memory queue, or
back to the Redis buffer, and retry on the next scheduler tick like every
other spend category.
* feat(proxy): CyberArk Conjur secret manager configuration via Admin UI
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(ui): mock networking base-url helpers in AdminPanel test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): restore deployment CyberArk env config on delete and roll back on persist failure
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): reinit env-configured hashicorp vault manager after cyberark persist rollback
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The keys, credentials, models, model groups, and chat clients still sent
requests with no timeout, so a proxy that accepts the connection and
never answers pinned the caller forever. They now default to the same
30 seconds as their teams and users siblings, with chat on the OpenAI
SDK's 600 second default, and Client wires its timeout through to all of
them. S113 cannot see Session methods, so each client gets a
hanging-server regression test instead.
Reprice ten more retired xAI slugs (grok-3 and grok-3-mini families,
grok-4-1-fast) to the grok-4.3 rates they now bill at, with family-correct
deprecation dates. Restore cache_read_input_token_cost on the Bedrock Grok 4.6
entries so implicit cache hits bill at the cache-read rate while explicit
cachePoint stays unsupported. Drop the unsourced 1080p video rate and the
gemini/ live native-audio entry the Gemini API 404s on. Add Groq qwen3.8-27b
tool-use flags per Groq docs. Extend the xai and gemini tests to lock all of
this in
OpenAI's function-calling validator rejects tool parameters carrying
oneOf/anyOf/allOf/enum/const/not at the top level, while the ChatGPT
backend Codex talks to natively accepts them, so an MCP tool declaring a
top-level union 400s through the proxy. Merge the branches into the
object schema for OpenAI itself only, walking the namespace-nested tools
current Codex builds send, on both /v1/responses and /v1/responses/compact
