Router cooldowns and the global TPM/RPM counters move behind two Python stores backed by the new redis-store crate. The read-through memory tier lives in redis-store as MemoryTier, so crates/cache keeps no Redis dependency. Folds in the Python-only encapsulation step that used to be its own PR
native_client takes the NativeRedisSettings a RedisCache captures when it is built, the kwargs, namespace and default TTL, instead of reading those attributes off the cache. A stand-in that skips the RedisCache constructor leaves the native stores on memory, and a test double that wants them on Redis builds the settings itself
The stores send the commands main does: one MGET for the cooldown and usage
reads instead of a GET per key, and a deployment's tpm and rpm increments on
their own async_increment_pipeline round trip instead of the request's
post-call batch.
A credential_provider object reaches the resolver as a ProviderHandle, so it
resolves to Auth::Provider and two RedisCaches share a client only when they
share the provider. The process registry of native clients now holds each
client weakly, so a discarded Router drops its client and its provider
instead of keeping them for the life of the process.
NativeRedisClient resolves a RedisCache's redis_kwargs through the RedisCache
kwargs surface and hands every native store in the process one shared client,
breaker and ServiceLogging event sink. A setting Rust ignores is logged with
its consequence, and a config it cannot use leaves the stores on memory
NativeRequestRedis carries one request's pre-call and post-call batches from
RequestRedisBatches into the stores. The keyspaces that use these land in the
PRs above
RedisSpec carries RedisCache.redis_kwargs into the resolver as plain values
plus the names of keys whose value is a Python object, instead of replacing
each object with its type name. ConfiguredRedis::with_host_objects takes those
names, so the resolver reports them in Resolution::host_objects, warns for the
ones Rust cannot honor and lets each hide its REDIS_* value. A
credential_provider object without a ProviderHandle fails with
ProviderWithoutHandle, so the stores stay on memory instead of connecting
without auth
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Every cache setter now takes a pydantic model or plain data (str, number, bool,
None, sequences, str-keyed mappings), which is what Redis can hold and what the
Rust auth cache accepts. No production writer passes anything else, and pyright
rejects a new caller that does
redis_py_kwargs.py reads each redis-py version's signatures in a throwaway uv
environment and the REDIS_* names from litellm._redis under the locked
version, then writes the catalog. Run on this branch it reproduces every arg row
of the hand-made file, so only the meta text changes.
test_redis.py now loads the script's arg_signatures instead of keeping its own
copy of the introspection, so the code that writes the file is the code that
checks it in every redis-compat CI job
Both ask for X.509 checks such as CRL revocation that rustls cannot perform,
and redis-py 5.3.1's async client already refuses them with a TypeError, so a
set value now fails with Error::Unenforceable like the OCSP settings instead of
connecting without the check. An empty list asks for nothing.
A Reject row now says which values ask for its check: true for the OCSP flags,
any present value for the verify flag lists. tests/catalog.rs fails if the
locked redis-py's async, cluster or connection signature accepts a Reject row,
so a redis-py bump forces the decision again
Each row now carries its handling with the warning's consequence, whether the
value is plain data or a Python object, whether a url query carries it, its
REDIS_* name and its get_secret fallbacks. HOST_OBJECTS, consequence(),
is_met_by_rustls and the url setting lists in tls.rs fold into those columns.
The 29 kwargs that had no row get one, so setting them now warns instead of
passing through silently. redis-py-kwargs.json keeps only the Python facts:
which redis-py versions name each kwarg and whether Python reads its REDIS_*
name. tests/catalog.rs fails until SETTINGS has exactly one row per kwarg in
it with the same REDIS_* flag, and test_redis.py checks the file against the
redis-py each redis-compat CI job installs
config now only deserializes the Redis YAML. The new litellm-redis-resolve crate
turns an already merged redis-py kwargs dict into a Resolution without reading the
environment or secrets, so both hosts can share it. The REDIS_* layering, the
get_secret fallbacks and the Azure REDIS_USERNAME read move to gateway, the only
host that needs a Rust copy of the merge.
litellm/_redis.py gets _merge_redis_kwargs, the merge stage of
_get_redis_client_logic, and the contract cases gain a merged column that pins
the Python merge, the Rust merge and the Rust interpret step to the same dict.
ssl_validate_ocsp and ssl_validate_ocsp_stapled were dropped with a warning, so
a config that asked for revocation checks connected without them. rustls has no
client-side OCSP, so a true value from the kwargs, REDIS_* or a url query now
fails resolution with RedisError::Unenforceable. redis-py 5.3.1's async client
refuses both with a TypeError, so this matches the proxy's path. A false value
asks for nothing and is dropped silently
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
rustls only reads unencrypted keys, so ssl_password was dropped with a warning
and the TLS handshake failed. The resolver now reads it into TlsOptions and
redis-client decrypts a PKCS#8 ENCRYPTED PRIVATE KEY before handing it to
redis-rs, like the sync redis-py client's load_cert_chain(password=...). A
missing or wrong password, or a legacy Proc-Type encrypted PEM key, fails at
client build with a TlsKey error naming the file
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
A Redis setting the Rust client cannot honor is now warned and dropped with
what that means, so a config that works on Python never fails to build on
Rust. health_check_interval, unix_socket_path, ssl_ca_data and ssl_ca_path
are read and applied like redis-py.
health_check_interval resolves to a three-state HealthCheck, so 0 stays off
on a cluster instead of turning on Python's 25 second cluster default, which
only an unset interval takes. unix_socket_path resolves to Target::Unix. A
url's ?db=, ?username= and ?password= are read like parse_url reads them
instead of being dropped, and ssl_min_version no longer warns at TLS 1.2 or
lower, which rustls already meets.
Each config surface now turns its Redis section into a ConfiguredRedis
(coordination, cache_params, or a RedisCache.redis_kwargs dict), and one
resolve returns the ResolvedRedis plus the ignored settings by source, so
hosts log gaps instead of the resolver. The resolve/resolve_cache flag and
the coordination ssl normalization are gone
Resolution reads the layered kwargs into a typed Options struct once, and
endpoint and auth selection work from that struct alone. An empty value is
unset everywhere, and a flag Python surfaces read differently is an error
ResolvedRedis and RedisAuth move to redis-types, so redis-connect no longer
depends on litellm-config
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* feat(billing): support Cognito bearer auth for metrics
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): refetch billing token on 401 and require https
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): import Unpack from typing_extensions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(proxy): make billing metrics bearer only and drop mtls
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(proxy): format billing metrics module
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The bridge moves leading system messages into the Responses instructions
field. With response_format json_object, Azure requires the word json in
input and ignores instructions, so a request that follows the documented
rule 400s after translation. Send the system text as a system input item
when json_object is requested, the same shape already used for
system-only requests
Resolves LIT-10426
* chore(cost-map): set openai gpt-5.6-cyber and Daybreak Red max input to 272K and source the sora-2-pro-high-res deprecation
* Absorb GovCloud Bedrock, Azure GPT-6 Flex and GMI registry rows
Roll the verified registry data and Azure Flex cost coverage into the rolling price sync
Co-authored-by: kerry-berri <326648561+kerry-berri@users.noreply.github.com>
Co-authored-by: dguthruf <102602010+danielguthruf@users.noreply.github.com>
Co-authored-by: hisamotodev <hisamotodev@users.noreply.github.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: hisamotodev <hisamotodev@users.noreply.github.com>
* fix(azure): answer 401 when Entra rejects the deployment's credential
A ClientAuthenticationError from the Entra token provider (wrong, expired or rotated client secret) used to surface as a retryable 500 carrying the app's client id and Entra trace ids. Map it to a 401 AuthenticationError that keeps the AADSTS code and first sentence with GUIDs redacted, on both the direct token fetch and the provider handed to the OpenAI SDK client. Network failures stay 500.
* fix(azure): keep network failures to Entra a retryable 500
azure-identity wraps a transport failure in ClientAuthenticationError, so the
401 mapping now skips errors whose cause chain holds ServiceRequestError or
ServiceResponseError
* fix(azure): cover async token providers and Entra 5xx, and scope caller-sent Entra credentials
* fix(azure): map only AADSTS-coded Entra rejections to 401 and keep caller credential failures out of cooldown
An Entra ClientAuthenticationError now answers 401 only when its message carries an AADSTS code, its HTTP
status is not 429 or 5xx, and the code is not the AADSTS50196 throttle, so a chained credential's outage or
throttle stays a retryable error. Caller-sent Entra fields no longer change the deployment id; a 401 from a
value the caller sent skips the shared deployment's cooldown instead. The Azure AI Foundry agent token fetch
maps the same rejection, and the A2A endpoint answers it with HTTP 401.
* fix(router): count router default_litellm_params as configured Entra credentials when deciding cooldown
* fix(azure): keep transient Entra codes retryable and scope 401 handling to Entra rejections
ClientSecretCredential drops Entra's HTTP status, so throttling and transient
codes (AADSTS50033, 50196, 90006, 90024, 90033, 90055) now stay retryable
instead of mapping to 401.
The A2A endpoint answers 401 only for an AuthenticationError caused by an
Entra token rejection, and the router skips cooldown for a caller-sent Entra
field only on Azure-family deployments. The azure/ Decisions route and the
Bing grounding search tool now map an environment-credential rejection to the
same 401.
* fix(azure): map only known Entra credential rejections to 401 and cover the OIDC token exchange
Unlisted AADSTS codes keep the retryable 500, the router skips the 401 cooldown only when an Entra rejection caused it, and a federated token Entra rejects answers the same 401 on Azure chat, Responses and A2A agents
* fix(azure): answer 401 for Entra rejections on the /azure passthrough and token counting
The fallback hop skips cooldown when Entra rejected a credential the caller sent,
Prometheus counts a deployment's own Entra rejection as a deployment failure again,
and an OIDC exchange error keeps Entra's headers so Retry-After reaches the router.
* fix(azure): keep a no-op caller Entra field from skipping cooldown and redact the passthrough 401 message
A caller-sent Entra field now skips the deployment's cooldown only when it
differs from the deployment, its named credential, the router defaults, the
AZURE_* environment variables and the default scope. An empty value counts as
unset, so a deployment whose own secret is wrong still cools down when the
caller's field changes nothing about the token request.
The /azure passthrough's Entra 401 message goes through the same internal
hostname redaction as other client-facing errors.
* fix(router): compare a caller's Entra field with the value the deployment uses
A caller-sent Entra field skipped the cooldown only when it matched no
configured source, so a value equal to an environment default the deployment
overrides (a stale AZURE_CLIENT_SECRET, say) counted as the deployment's own
and let a caller's rejected credential cool down a working deployment.
The check now resolves the value the deployment would use without the caller,
in order from the router defaults, the deployment, its named credential, the
AZURE_* environment variables and the default scope, and skips the cooldown
only when the caller's value differs from it.
* fix(azure): follow the settings merge for empty Entra fields and keep non-rejection OIDC exchange errors unchanged
* fix(azure): count only the failed attempt's Entra rejection and ignore a non-callable token provider
* fix(azure): keep the streaming Entra rejection inside the failed attempt
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(guardrails): check Anthropic-format request tools in tool_permission pre_call
The pre_call hook only collected tools shaped as {"type": "function", "function": {...}},
so flat tools from /v1/messages ({"name", "input_schema"}) and /v1/responses
({"type": "function", "name"}) were never checked and deny rules silently passed.
Reuse the shared anthropic_tool_names helper so every request tool name is checked,
and handle Anthropic tool_choice {"type": "tool"} in both block and rewrite modes.
Fixes#40583
* fix(guardrails): detect Responses API named tool_choice in tool_permission
Responses API named choices put the name at the top level ({"type": "function", "name": ...}),
so rewrite mode removed the denied tool but left a tool_choice pointing at it.
* test(guardrails): run tool_permission pre_call tests through real default_on gating
Build the guardrail as an always-on pre_call guardrail instead of patching should_run_guardrail.
* test(guardrails): type the new tool_permission pre_call test parameters
* fix(guardrails): keep the Responses API custom tool type distinct
Anthropic's user-defined tools carry type "custom", so pre_call mapped
that to "function" for tool_type rules. The Responses API has its own
custom tool type, and mapping it let a custom tool slip past a
tool_type deny rule when the default action is allow.
Normalize only for the formats where custom means a plain function, and
read tool names directly in the rewrite path, which never needed a type.
* test(guardrails): cover flat tools through Messages and Responses
Add blocked and permitted flat-tool cases through the running proxy, with
endpoint coverage and metadata for the current e2e harness
Require a guardrail policy verdict when checking denied tools so an
unrelated provider error cannot satisfy the regression test
Co-authored-by: Christopher Krah <christopher.krah@plexito.de>
* fix(guardrails): check namespace and nameless tools and relax tool_choice in tool permission rewrite
* fix(guardrails): check forced, grouped, loaded, and hosted tools by their real type
* fix(guardrails): drop references to removed tools and count loaded tools in tool permission rewrite
* fix(guardrails): check tools sent outside top-level tools in tool permission
* fix(guardrails): judge namespace members by their bare name as a fallback and keep rewrites valid for Gemini, Bedrock and hosted tools
A namespace member is checked by namespace__name first, and by its bare name when no rule names the joined one. Rewrite mode now prunes Gemini allowedFunctionNames and turns off forced calling when no function is left, drops a removed hosted tool from allowed_tools, reads Bedrock toolSpec and systemTool blocks by name, skips cachePoint markers, and leaves a tools field that is not a list for the provider to reject instead of failing with a 500
* fix(guardrails): let only name rules decide a namespace member's bare-name fallback
* fix(guardrails): judge malformed tool types, empty Gemini name lists and pass-through Anthropic tools like the endpoints do
A tool or tool_choice whose type is not a string now reads as untyped instead of crashing the guardrail with a 500, and a null type key is never read as a Gemini tool part. An empty allowedFunctionNames list no longer turns off the functions a rewrite kept. An Anthropic custom tool reads as a function by its input_schema on every route, so a pass-through route judges it the same as /v1/messages. A Responses WebSocket frame now forwards the extra_body tools a rewrite stripped
* fix(guardrails): judge a named hosted tool by its type and keep a nested chat custom tool custom
* fix(guardrails): keep judging Anthropic client tools and type-named server tools by their name
* fix(guardrails): judge a named tool by its name alone only when the name is its type's own
* fix(guardrails): judge the function a tool names beside a declaration list or a top-level name
* fix(guardrails): judge Gemini hosted keys whatever the tool type and a namespace's function
* fix(guardrails): judge legacy functions entries like tools and send Gemini a namespace's members
* fix(guardrails): judge a namespace member by every name a provider reads and send Gemini its schema converted
* fix(guardrails): judge a legacy functions entry as a function and relax a tool_choice in extra_body
* fix(gemini): keep a namespace whole when inlining its members would repeat a function name
* fix(guardrails): judge a namespace member by every bare name that shares its qualified name
* fix(vertex_ai): declare a repeated namespace member name once instead of sending namespace names to Gemini
* fix(guardrails): judge a tool_choice sent in extra_body like a top-level one
A forced name only extra_body.tool_choice carried was never checked, so block mode let a denied name through to the provider
* fix(guardrails): judge a Gemini namespace member returned by its bare name and force a named namespace's members
* test: keep formatter churn out of the tool_permission and Gemini test files
* fix(guardrails): judge extra_body.input tools, argument-aware alias rules, and exact forced Gemini functions
Tools loaded in extra_body.input are now checked and stripped like top-level input. A returned
namespace member is judged by the alias whose first name rule its arguments satisfy. A forced
Gemini name that matches a top-level function keeps that function. Alias grouping and Gemini
declaration dedupe now run in one pass instead of quadratic scans.
* fix(guardrails): judge and rewrite every tool field sent inside extra_body
extra_body is merged into the upstream body, so functions, function_call,
mcp_servers and toolConfig nested there reached the model unjudged. Treat
extra_body as a second request layer that is collected and rewritten the
same way as the top-level request.
* fix(guardrails): judge Gemini hosted keys by key and count only the tools a provider receives after extra_body
* fix(guardrails): relax a tool_choice that names a dropped namespace member by its bare name
Gemini and Anthropic chat send namespace members under their bare names, so rewrite mode now treats a dropped member's bare name, and an emptied namespace's own name, as removed when no kept tool still carries it
* fix(gemini,guardrails): keep a top-level function over a same-named namespace member and leave malformed tool values to the provider
Gemini and Vertex chat now declare a top-level function over a namespace member that shares its name, so a forced call gets the top-level schema. post_call judges a returned name a top-level tool carries as that tool, and pre_call no longer raises on an unhashable or non-string tool name, input item type, or function_call name.
* fix(guardrails): judge a returned namespace member named like a hosted MCP server as that member
* fix(gemini,guardrails): send a namespace as main did when another tool has a member's name
Gemini chat inlines a namespace's members only when no other tool, namespace
member, or legacy functions entry declares the same name, and otherwise sends the
namespace by its own name as main did. A tool_choice naming such a namespace
forces the namespace itself. The tool permission post_call reads top-level names
the way Gemini declares them and judges a call the Responses bridge tags with a
namespace as that member.
* fix(gemini): send colliding namespace members as namespace__name functions and judge them in post_call
When a namespace member shares a name with another tool, Gemini chat now gets that namespace's members as namespace__name functions instead of one function named after the namespace, so every function it can call is a name the rules judged. Declared names are counted once, and a forced member maps to each holder's qualified name.
post_call judges a returned namespace__name as that member, by its qualified or bare name the way pre_call does, so a bare-name allowlist or denylist applies to it.
* fix(gemini): keep generated member names unique and let a top-level function own its exact name
A namespace that listed a member twice, or a generated namespace__name that
repeated a top-level function, sent Gemini two declarations with one name, and
Gemini answered 400 where main answered 200. A name a namespace lists twice is
now one member, and a top-level function keeps its exact name.
post_call now judges a returned name a top-level function declares as that
function, never as the namespace member the name could also mean.
* fix(gemini): qualify namespace members by the namespace's top-level name
The guardrail judges a member as `name__member` from the namespace's top-level
name. Gemini built the name from `function.name` when the tool also carried one,
so a request could pass pre-call and reach Gemini under a name no rule judged.
* fix(vertex_ai): force only the namespace members Gemini is sent
A forced namespace or member on Gemini chat could still allow a generated name that a top-level function or an earlier namespace owns, so tool_choice forced an unrelated function. The forced names now come from the same collision checks the declarations use
* fix(vertex_ai): reject a forced namespace Gemini gets no member of, and resolve forced names in one pass
* fix(guardrails): judge a namespace member by a rule on its namespace's name
---------
Co-authored-by: Christopher Krah <christopher.krah@plexito.de>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(proxy): charge a video's provider-reported cost once, on the first poll that sees it completed
A custom video provider can report a video's cost on the status poll that
sees it completed. Every poll of a video shared the video id as its spend
log request_id, so the paid poll's row was dropped as a duplicate and every
later poll of the finished video charged the cost again.
Video status rows now carry their own `_video_cost` request_id, and a poll
that reports a cost goes through the same settle-once claim batches use, so
the first poll that sees the video completed charges it and writes the row,
and every later poll charges nothing.
* fix(proxy): charge a video's provider-reported cost once on model, router and session budgets too
A video status poll gets the _video_cost row suffix only when it reports a cost, so a $0 poll keeps the bare video id and adds no row of its own, and the spend log writer claims a row by that suffix.
The batch charge-once marker now covers videos, keyed on the video id under {spend_key}:video:{id}, with the batch marker key unchanged. Model and router budgets use it, and per-session budgets now charge a repolled batch or video once and ignore a cost that is not a finite number
* fix(proxy): charge a finished video's own cost once, keyed by the id the client polled
Guardrail cost on a running poll no longer takes the charge-once claim, only a completed poll charges, the session marker TTL refreshes like the others, and two deployments whose provider ids match each keep their own charge.
* fix(proxy): charge repeat poll guardrails, key video charges by canonical id and survive redaction
* fix(proxy): keep video status polls in-process for the collector and give guardrail-only job polls an unclaimable row id
* fix(proxy): keep repeat batch polls free and group guardrail-only batch rows under their batch's trace
* fix(proxy): settle a finished job whose own cost is below its poll's guardrail cost under the job's charge row
* test(proxy): count charged_poll_cost as covered through the finished job guardrail poll tests
* fix(proxy): settle a finished batch that cost nothing itself on its first priced retrieve
* fix(proxy): charge no budget for a batch retrieve before its cost is final, and read the retrieved batch from before redaction
* fix(proxy): charge sessions a poll's guardrail-inclusive cost, count a job cost row's guardrail run, and keep batch_cost_is_final importable from litellm.batches
* fix(proxy): claim a job and charge the session budget in one Redis call
The session limiter claimed the job marker and then raised spend in a second Redis call. A failure between the two left the job claimed while its charge sat only in local memory, so later polls skipped it. One script now does both, and a refused script claims and charges locally
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat: update EmpirioLabs models in model_prices_and_context_window.json
* chore(endpoints): regenerate provider endpoint support for the EmpirioLabs cost map rows
* fix(empiriolabs): drop the retired max_tokens field, route embeddings and remove the unrouted rerank row
The cost map test rejects any row carrying max_tokens, so every EmpirioLabs row keeps max_input_tokens and max_output_tokens only. The provider JSON now lists /v1/embeddings so embedding(model="empiriolabs/text-embedding-v4") reaches the OpenAI-compatible embeddings route instead of failing provider lookup. The qwen3-rerank row goes away because no rerank route exists for the provider. Endpoint support regenerated from the cost map
* fix(empiriolabs): mark audio input and image embedding input on the rows the provider lists as multimodal
The three vision embedding rows get supports_embedding_image_input and the eleven chat rows whose input_modalities on GET https://api.empiriolabs.ai/v1/models include audio get supports_audio_input, so capability checks stop treating them as text only
* fix(empiriolabs): carry the long-context price tiers on the 24 rows the provider bills in bands
EmpirioLabs bills 24 of these models at a higher rate once the prompt passes 32K, 128K, 256K, 272K or 512K tokens, and the rows carried only the first band, so a 300K-token qwen3-7-plus request was priced at a third of the real cost. Each of those rows now carries input_cost_per_token_above_<N>k_tokens, output_cost_per_token_above_<N>k_tokens and, where the row already has cache_read_input_token_cost, cache_read_input_token_cost_above_<N>k_tokens for every band, taken from pricing[].min_context on GET https://api.empiriolabs.ai/v1/models for the base rows and from the Variants rate card on docs.empiriolabs.ai/models/<id> for the six variant rows
* feat(empiriolabs): bill the per-call web search fee reported in usage.tool_usage
EmpirioLabs charges a flat fee per invoked web_search, web_search_image or image_search call and reports the counts in usage.tool_usage on the chat response. The JSON provider config now carries that count as usage.server_tool_use.web_search_requests when providers.json sets special_handling.web_search_requests_from_tool_usage, the per-call web search cost path bills the usage-reported count instead of flooring to one call, and the 39 EmpirioLabs rows the provider lists a per-call search price for carry it as search_context_cost_per_query, from unit_pricing on GET /v1/models for base rows and the Variants rate card on docs.empiriolabs.ai for variant rows
* fix(openai_like): mark the dict signature of transform_parsed_response_dict as matching BaseConfig for LIT001
* fix(openai_like): mark both dict annotations of transform_parsed_response_dict for LIT001
---------
Co-authored-by: Adam Dalloul <47503782+Adam-Dalloul@users.noreply.github.com>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): stamp the failed deployment on every endpoint's attempt
Weighted failover (#27980) re-picks within a model group by excluding the
deployment named in the error's failed_deployment_id. #27980 stamped that id
in only three attempt functions: _completion, _acompletion and
_ageneric_api_call_with_fallbacks_helper. Embedding, image generation,
transcription, speech, text completion, rerank, adapter completion, the sync
generic call and vector store create never stamped it, so with
enable_weighted_failover on, a failure on one of their deployments skipped the
in-group re-pick and went straight to the cross-group fallbacks, or raised.
Each of those attempts now stamps the deployment it picked, read from the
model_info that _update_kwargs_with_deployment put on the request (so a
client-side-credential call names its own dynamic deployment, as on
completions). A failed pick stamps nothing. File and batch creation and batch
cancellation are left alone: they are bound to a resource on the deployment
they picked, so re-picking another one cannot help.
* test(router): narrow the failed-pick raise to the no-healthy-deployments error
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_013FDwtoMjnHa4xxazGJJNSm
* fix(router): exclude the configured deployment on failover for client-side credentials
Weighted failover excluded the per-request id that client-supplied credentials
generate, so the failed configured deployment stayed eligible for the re-pick.
Stamp the configured id alongside it and exclude that. Also drop the vector
store create stamp, which no fallback path reads, and redundant test comments.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_013FDwtoMjnHa4xxazGJJNSm
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat(decisions): add EmpirioLabs AI as a decisions provider
empiriolabs/aplomb-1 now works with litellm.decisions and litellm.systemone, the proxy /v1/decisions and /v1/systemone routes, the decision model guardrail and the Admin UI. Requests go to POST /v1/decisions on the EmpirioLabs AI API with the System One body, keyed by EMPIRIOLABS_API_KEY with an optional EMPIRIOLABS_API_BASE
Chat models keep routing through the existing OpenAI-compatible JSON provider, and a test pins that
* ci: run the EmpirioLabs AI decisions tests in the llms unit shard
* fix: align EmpirioLabs registration with CI gates
---------
Co-authored-by: Adam Dalloul <47503782+Adam-Dalloul@users.noreply.github.com>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(accounting): replace event scaffolding with SpendLogs projection
* test: preserve spend timestamps without removed capture callback
* fix: guard accounting event removal across schema update paths
* refactor(accounting): retain schema and prepare durable payloads
* fix(accounting): preserve dates in serialized payloads
* fix(accounting): retain schema push compatibility
* fix(accounting): retain span registration for the legacy schema
* test(accounting): remove obsolete capture acknowledgement test
* fix(accounting): date every daily projection row the way the model rollup does
A space-separated startTime kept the whole timestamp as the daily key, while the model usage rollup took the calendar date. Every daily row now uses the same date helper
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* chore(ui): regenerate dashboard API types after rebasing on main
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(accounting): project only from the stored accounting payload
project() now reads entities only from the payload's accounting_entities, so
the raw SpendLogs fallback branches are gone. build_accounting_payload() builds
the metadata once instead of dumping it to JSON and parsing it back. Guardrail
usage dates use a tolerant UTC parse, so a malformed startTime drops only the
guardrail rows instead of failing the whole projection.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* fix: prevent reasoning field from being copied into provider_specific_fields
* fix: ensure reasoning field in provider_specific_fields is redacted
* fix: redact reasoning_details in provider_specific_fields
* fix: format redact_messages.py
* ci: retrigger
* ci: retrigger
* ci: retrigger
* fix(logging): keep provider_specific_fields.reasoning in chat responses
Redaction already blanks provider_specific_fields.reasoning and reasoning_details in logs, so chat responses can keep the field as they did before.
* fix(logging): redact reasoning_text, citations, and web search results in provider_specific_fields
* fix(logging): redact vector store, RAG, Groq tool, Databricks agent and tool search results in provider_specific_fields
* fix(logging): redact Bedrock streamed reasoningContent and file annotations in provider_specific_fields
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(openai): bill gov.api.openai.com FedRAMP endpoint with 1.1x uplift
* chore(openai): trim FedRAMP uplift diff
* refactor(openai): bill the FedRAMP endpoint through its own fedramp_uplift_multiplier key
* fix(ui): regenerate fedramp_uplift_multiplier doc comment in schema.d.ts
* style: ruff format utils.py and reorder fedramp_uplift_multiplier in schema.d.ts
* fix(openai): infer data_residency from OPENAI_BASE_URL and litellm.api_base when api_base is unset
* test(cost): cover get_fedramp_uplift_multiplier fallback paths
* fix(cost): apply fedramp_uplift_multiplier in batch_cost_calculator
* fix(openai): derive data_residency from a supplied client's base_url
* test: type the supplied-client data_residency test params
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Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in proxy sub-call budget checks, model search and logger init
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in otel baggage metadata, model budget limiter and batch line items
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* Revert "refactor: clean up fresh tech debt in otel baggage metadata, model budget limiter and batch line items"
This reverts commit 68737c457c.
* refactor: clean up fresh tech debt in guardrail init, cost map fetch and stream continuation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in kimi k3 token counting and two slop comments
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in mcp tool call auth fields, messages drop_params, exception chain and spend log noqa
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix: preserve dict-compatible drop params access
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in user list sorting, opencode affinity header and aws polly comment
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in responses bridge check, chatgpt authenticator and image header adapters
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in auth 401 detection, cooldown fallback lookup and bedrock guardrail billing
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* Revert "refactor: clean up fresh tech debt in auth 401 detection, cooldown fallback lookup and bedrock guardrail billing"
This reverts commit d497e02bbf.
* refactor: clean up fresh tech debt in responses stream usage cost, bedrock count tokens comments and router return types
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in messages drop_params reads, auth zero cost comment and two return types
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: keep getattr drop_params reads where callers pass a plain dict
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clean up fresh tech debt in router context signatures, search tool comment and gemini realtime init
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: drop fresh private-alias, getattr and duplicated response id helpers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: bind response id helper to logging instance
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: simplify media guard and spend log reads
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix: satisfy media guard type discipline and formatting
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: keep media guard cast rather than trade it for new suppressions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo <277851410+mateo-berri@users.noreply.github.com>
* fix(agentic): surface a failed agentic follow-up call instead of the pre-loop tool call
* fix(agentic): surface failed follow-ups from the OpenAI chat dispatcher and update pinned integration tests
* fix(agentic): end a capped agentic turn on chat and responses instead of a retried 500
* fix(openai): run agentic hooks after the first call's error handling so a follow-up error keeps its own type and message
* fix(agentic loop): end capped turns on every chat path and bill the first call when a follow-up fails
A turn refused at max_agentic_loops now drops the internal tool calls of every hook that claims calls in it, while a call the client declared survives. The hosted_vllm and openai chat paths now carry the loop depth, fingerprints and max_agentic_loops into the follow-up, so they stop at the cap instead of looping forever.
A failed follow-up call now records the first call's usage and cost on the request's failure log before the error reaches the client. A code interpreter sandbox that is missing or fails becomes the tool call's output for the model to handle, so the turn completes without a retry.
On native streaming /v1/messages a hook or follow-up failure now reaches the client as an Anthropic error event with the mapped type, and compresr declares its retrieve tool so the stream holds it back. Comments and docstrings the branch added against the repo rule are removed
* fix(agentic loop): bill retried attempts and clean up what failed or capped turns return
The router's retry loop now carries each failed attempt's paid first call into the request's billing, so a request whose follow-up keeps failing bills every first call on its failure row, and one that recovers bills the failed attempt's first call on its success row. A failure row no longer adds unpriced estimated tokens on top of attempts that were billed, so its tokens match its spend
A sandbox failure now answers the model with a fixed sentence and marks the code_interpreter_call as failed, without the sandbox's error text. Code interpreter on /v1/responses with Claude now runs its loop, because the bridged inner call no longer strips the hook's own markers
Dropped internal tool calls leave the kept calls numbered from 0, also on a replayed stream. A capped native /v1/messages stream now says the loop hit its limit and that max_agentic_loops raises it, instead of asking the client to retry
The agentic refusal and hook error logs no longer include the model or the exception text, and the agentic loop helpers take typed messages, params, and read-only fingerprints
* fix(agentic loop): keep a recovered retry's cost breakdown on the response it returns
A retried agentic request that recovers no longer adds the failed attempt's first call to its success row. The proxy keeps the follow-up's own row for that request id, so the added spend never showed up in the stored row, and that duplicate row is tracked separately. When every attempt fails, the failure row still bills each attempt's first call
Pricing a first call for the failure row no longer replaces the request's cost breakdown. Before, a recovered retry answered with x-litellm-response-cost-original, -input, and -output from the failed attempt's first call. Now its headers and logged breakdown match a request that succeeds on its first try
* fix(agentic): stop retrying a request whose agentic follow-up failed and bill every round it served
An error raised by an agentic follow-up after the first call was served now carries a typed mark, so the
router's retry loops, the mid-stream retry, and litellm's num_retries wrapper raise it as is instead of
rerunning the whole request. A failure of the first call itself still retries, and fallbacks still run.
The failure row bills every round the loop served before the failure, at any depth, and a later attempt
that succeeds bills what the failed attempts paid on its success row, with the cost breakdown and the
response cost headers adding up. The error response's x-litellm-response-cost reports the same amount
its failure row bills. Failure rows outside agentic hooks keep the prompt-token estimate they had before.
A refused tool call now matches by id among the refused ids, or by name among refused calls that carry
no id, so a name-only refusal next to an id refusal is no longer kept.
* fix(code_interpreter): delete a session sandbox whose code run failed so the next call starts a fresh one
* fix(code_interpreter): delete only the session sandbox that failed, never its replacement
* test(code_interpreter): type the session sandbox test helpers
* fix(proxy): report what a failed agentic follow-up's failure row bills on /v1/messages errors
* fix(agentic): keep the no-retry mark through error mapping and bill only failed follow-ups on success
An agentic loop error that is not a provider error, such as the streaming chat cap or a crash in a hook's
plan build, now keeps its no-retry mark when litellm maps it to an APIConnectionError, so the router no
longer reruns every paid round. The mark is stored on the exception, so a built-in error can carry it too.
A crash in a hook's plan build on /v1/messages and /v1/responses bills the first call on its failure row.
A recovered attempt adds a failed attempt's usage to its success row only when that attempt was a failed
agentic follow-up. Other failed attempts, such as a dropped stream, log their own row as on main.
A code interpreter sandbox that fails while running the code now says the code may have run but its
result is lost, instead of saying the code did not run.
* test(responses): bill a retried MCP request each attempt on its own row again
Round 4 stopped adding a non-agentic failed attempt to the success row, so this test goes back to main's assertions: the success row bills only its own rounds and the failed attempt's first round stays on its own failure row
* fix(spend): name a failed follow-up attempt the success record already bills
With the usage meter on, a failed agentic follow-up attempt gets its own charge-eligible record, and the request's success record also carries that attempt's usage and cost once the success row bills it. The success record now lists the attempt's record ids in included_attempt_ids, so a reader can tell the success record already covers it. Nothing changes when the meter is off
* fix(spend): count a billed failed follow-up's tokens on the success row
* fix(spend): bill a failed follow-up on a fallback served from cache
* fix(spend): show a billed failed follow-up in a cached fallback's cost breakdown
* fix(spend): keep a failed follow-up's billing state off the request-merged call details
* fix(spend): record the cost breakdown of a successful agentic follow-up
The chat agentic loop returned the follow-up response with the cost its own internal call had already stamped, so the request's logging reused that cost and never recorded cost_breakdown on the spend row. The loop now drops that stamped cost unless the follow-up was served from the cache, and the request prices the response itself
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(anthropic): answer a 503 as 529 overloaded_error on /v1/messages
Anthropic's error contract has no 503, so a client built against it (Claude Code) treats a 503 from /v1/messages as a plain 5xx and retries it ten times instead of taking its overload path. A Bedrock 503 now leaves /v1/messages and /v1/messages/count_tokens as 529 overloaded_error, for both a JSON answer and a stream that fails before its first byte.
An Anthropic 529 overloaded_error now maps to litellm.ServiceUnavailableError (503) instead of InternalServerError (500), so OpenAI-shaped routes answer it as 503, the status OpenAI documents for an overloaded engine, and router retry and allowed-fails policies key it as ServiceUnavailableError.
* test(proxy): expect overloaded_error on a 503 stream error after a keepalive ping
* fix(proxy): record the 529 the Anthropic routes answer and type the chat stream error frame
The messages route stamps the answered status on the exception before post_call_failure_hook runs, so the spend log row, the OTel server span, the failed-request metric, and alerting record the 529 the client saw instead of the deployment's 503, while the deployment failure metric and cooldown keep the deployment's own status. A chat completions stream error frame names the type its status stands for instead of the null .type ServiceUnavailableError carries. An Anthropic-shaped 503 envelope passes through as 529 overloaded_error through a validated TypedDict, and count_tokens answers every ProxyException as the Anthropic envelope. Five integration tests that pinned 503 on the messages route now expect 529
* test(proxy): expect the top-level Anthropic envelope from count_tokens errors
count_tokens now answers a ProxyException as a JSONResponse carrying the
Anthropic error envelope instead of raising HTTPException, which FastAPI
wrapped in {"detail": ...}. The three legacy error-format tests now read
the response body and check that no detail wrap is left.
* test(proxy): cover the 529 overloaded_error answer across routes, cooldown, and retry budgets
* fix(anthropic): keep Anthropic overloads as InternalServerError and answer 529 from the provider status
An upstream Anthropic 529 stays litellm.InternalServerError (status 500) so
InternalServerErrorRetries, InternalServerErrorAllowedFails, SDK handlers,
and the OpenAI-shaped routes behave as on main. The error now carries
provider_status_code, and the /v1/messages routes answer 529
overloaded_error from it.
* refactor(proxy): unwrap a mid-stream fallback error once instead of recursing for the provider status
* fix(anthropic): keep count_tokens' detail body, end keepalive streams with an Anthropic error event, and log any 529 as an overload
* test(integration): cover the audit round 3 cells and expect 529 on the count_tokens 503 cases
* fix(proxy): re-raise an unchanged stream HTTPException as itself and walk nested mid-stream fallbacks for the provider status
* fix(proxy): walk nested mid-stream fallbacks without recursion
* fix(anthropic): preserve 503s and answer upstream 529s on messages routes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic): answer an upstream Anthropic 529 as 529 on count_tokens
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(anthropic): use integration coverage for keepalive errors
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): send only shown SSO fields when editing, and keep env-row SSO values behind a blank stored value
* fix(ui): clear every competing SSO provider when the admin switches provider
Only the detected provider's fields were nulled on a switch, so a second stored
provider (e.g. Microsoft behind Google) kept outranking the new one at sign-in
* chore(cost-map): remove the 52 rows whose provider retired them before 2026
* test(utils): pin the proxy function-calling parity case to azure/gpt-4.1
* test(batches): price the Azure batch-logging regression case against gpt-4.1
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(credentials): preserve stored info when patching credentials
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(credentials): type patch test parameters
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): keep a deployment's token limits off the shared backend cost map key
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): preserve catalog token limits on shared keys
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): use catalog for shared token limits
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(anthropic): drop the class attribute patch from the deployment max_tokens test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): avoid provider auth during catalog key resolution
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: mateo <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): cancel the Admin UI's raw spend-log reads in Postgres after 30s
Prisma's HTTP client gives up on a statement after 30s, so the Logs, Caching,
Cost Optimization and spend report pages already fail at 30s, but Postgres kept
running the scan. Every raw LiteLLM_SpendLogs read behind those pages now runs
under SET LOCAL statement_timeout = 30000 through one shared helper, which
/team/spend/by_user also uses instead of its own copy
* fix(proxy): keep the spend report's 503 and time out the session totals read
The grouped Logs page's session totals query now runs under the same
statement timeout, /global/spend/report re-raises the helper's 503 instead
of turning it into a 400, and the hand-written prisma fakes in the endpoint
tests expose read_db so every guarded route is exercised
* fix(proxy): keep the Logs page when Postgres cancels its session totals read
A cancelled session totals read degrades like any other failed enrichment
read instead of failing the whole page. The span-name test treats the shared
statement-timeout helper as a forwarder, and the spend report test no longer
depends on a license in the environment
* test(proxy): /global/spend/report keeps the 503 hint when Postgres cancels the read
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(main): price per-request custom pricing from the logging object instead of writing litellm.model_cost
* fix(main)!: carry the full per-call price entry on the logging object instead of writing litellm.model_cost
Direct SDK calls build one ModelInfo from the cost map row plus every custom pricing field on the call and price from it, so audio, tiered and directional per-second rates apply without touching litellm.model_cost. Router calls keep their registered deployment entry. completion_cost(completion_response=...) alone no longer sees per-call prices, pass custom_cost_per_second or custom_cost_per_token
* test(cost): assert the exact per-second charge for per-call cost_per_second
* fix(main): price Router request overrides and flat rates over inherited tiers in the per-call entry
A Router call that sets its own price is priced from it over the registered deployment entry, PTU zeroing applied as at registration. Flat token rates on a call drop an inherited tiered_pricing table, which generic_cost_per_token would otherwise prefer
* fix(main): keep tier rates for directions a call does not override and bill per-second-only calls per second
A flat rate set on a call is written into every tier for that direction instead of dropping the tier table, so the other direction keeps its tier price. A call that sets only a per-second rate on a model with catalog token rates clears those token rates for the call so the per-second path applies
* fix(main): apply a call's flat rate to its own tiered_pricing table when it supplies one
* refactor(main): move per-call price entry resolution into litellm_core_utils/per_call_pricing
The resolution logic is pure cost-map work with no dependency on dispatch, so it lives next to ptu_pricing and main.py keeps only the call sites in completion() and embedding()
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): rename per_call_model_info parameter to requested_model_info_override
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* feat(proxy): add LITELLM_FIPS_MODE startup gate
With LITELLM_FIPS_MODE=true the proxy refuses to start when TLS verification
is off, when Python's OpenSSL does not enforce FIPS, or when the startup
password migration fails. A value that is not true/false also refuses.
* feat(proxy): refuse FIPS mode when cryptography's OpenSSL is not FIPS
The stock cryptography wheel bundles its own non-FIPS OpenSSL, which serves
JWT, Fernet and AES-GCM even when Python's OpenSSL enforces FIPS.
* fix(proxy): refuse FIPS mode when cryptography's FIPS provider cannot hash
The stock cryptography wheel reads the host's FIPS config and reports FIPS on,
but its bundled OpenSSL cannot load the host's FIPS provider, so every
operation fails. Require a working SHA-256 alongside the FIPS flag.
* fix(proxy): refuse TLS verification off anywhere in FIPS mode
A model's own ssl_verify: false reached the HTTP client after the startup check
passed. get_ssl_verify now raises in FIPS mode whenever verification resolves
to off, which also covers the startup check.
* refactor(proxy): return FIPS boot refusals as values and harden the FIPS tests
* fix(proxy): stop refusing TLS verification off in FIPS mode
Skipping certificate verification is a security choice, not a FIPS one:
the TLS connection still only uses algorithms the FIPS provider allows.
* feat(fips): refuse a database used without FIPS mode, drop the password migration change
FIPS mode marks a new database with a fips_mode row in LiteLLM_Config and refuses one that already holds
LiteLLM rows without it. Without FIPS mode, the proxy refuses a database carrying the marker.
* test(fips): close the database test clients with aclose so the engine stops
* feat(fips): read FIPS mode from general_settings.fips_mode instead of LITELLM_FIPS_MODE
* refactor(fips): keep fips_mode out of the API-writable general settings, it is read from the config file only
* fix(fips): retry the startup marker and state reads once after a dropped connection
A dropped connection during the non-FIPS marker read used to count as an unmarked
database, so a blip at boot let a non-FIPS proxy start on a FIPS database. Both reads
now go through call_with_db_reconnect_retry, the reconnect-and-retry the other startup
reads use. A read that still fails keeps its old outcome.
* fix(fips): refuse a fips_mode key that has no value
fips_mode: os.environ/X with X unset, or a bare fips_mode: / null, resolved to None and
started without FIPS mode and without a message, while an empty string refused. A key
that is present now has to be a boolean; only a config without the key means off.
* refactor(fips): move the database check out of the boot gate
The boot gate keeps the setting and the two OpenSSL checks. The check that a
database matches the FIPS setting moves to its own PR, so a boot without the flag
runs no extra database read.
* test(fips): pin how a fips_mode string is read through enforce_fips_mode
* fix(rate-limit): estimate embedding image and audio data URIs as media in TPM pre-call checks
* fix(rate-limit): count embedding media as media only on models that embed it
A data URI sent to a text-only embedding model is read as text, so it keeps
the text estimate there. On models flagged supports_embedding_image_input,
image and audio use the chat media estimates and PDF and video count at most
the model's max_input_tokens. The same estimate now feeds project and key
limits, the usage-based, latency and cost routers' deployment tpm, and the
deployment itpm check.
* fix(proxy): count embedding media only where the backend reads it as media
Vertex AI, Gemini, Azure AI and Bedrock count a strict base64 data URI as
media per item. Cohere counts it as media only when the whole batch is
media, and Voyage, OCI and unknown models keep the text estimate. File
blocks carrying a data URI count like the bare URI.
The router context window pre-call check and the batch limiter now use the
same estimate, resolving each deployment or JSONL row model to its
backends. The cost map gains supports_embedding_image_input on
voyage/voyage-multimodal-3 and oci/cohere.embed-multilingual-image-v3.0.
* fix(router): hold each embedding media item to the context window on its own
A PDF or video data URI alone already reserves at most the model's
max_input_tokens, but the context window pre-call check then ran the
blanked input through the Responses transform and added a few framing
tokens, so a PDF that Vertex accepts got a 400. When every input item is
media, the check now returns the largest item's media estimate, since an
embedding request embeds each item separately
* fix(proxy): leave embedding media out of the context check and narrow Bedrock media scope
The router context window check now counts only the text of an embedding input, so Titan image lists no longer 400. Bedrock Marengo and Nova with a PDF keep the text estimate since they read those inputs as text or reject them, async_invoke Nova counts images as media, and the unused batch limiter change is dropped.
* fix(bedrock): bill Cohere embeddings by Bedrock's input token count header
* fix(embeddings): check data URI base64 in place and keep Bedrock Cohere text usage
The strict base64 check now scans the payload in place instead of decoding
and re-encoding a full copy. Bedrock's billed token header is used only for
image requests, so text-only Bedrock Cohere usage matches main. The deployment
itpm estimator change is reverted, since the router never passes embedding
input to that check.
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(proxy): let the Admin UI cancel /team/spend/by_user at 60s with an opt-in statement timeout
GET /team/spend/by_user takes an optional timeout_seconds (1 to 600). When set, the raw
LiteLLM_SpendLogs aggregation runs under SET LOCAL statement_timeout and Postgres cancels it,
and the route returns 503 instead of letting the query run for hours. Callers that omit the
param are unchanged. The Admin UI sends timeout_seconds=60 and the Spend Per User Within Team
card shows the server's error instead of an empty table
* fix(proxy): cancel /team/spend/by_user in Postgres after 30s
Prisma's HTTP client already gives up on the statement at 30s, so the
query now runs under SET LOCAL statement_timeout = 30000 for every caller
and the opt-in timeout_seconds param is gone. The Admin UI card shows the
request error instead of the empty-state text.
* fix(proxy): keep /team/spend/by_user on the read replica inside its timeout transaction
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat: show user names in access group details
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat: show user names on project, org, model and prompt details
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): look up user names by exact id
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): fall back to user list for org admins
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): fall back when /v2/user/info returns a different user id
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): let org admins read their org members in /v2/user/info
Org admins could list a user through /user/list but got a 404 from
/v2/user/info for that same user, so the dashboard fell back to a
substring /user/list lookup that could miss the user. /v2/user/info
now allows an org admin to read users in organizations they administer,
and the dashboard's single-user lookup calls only that endpoint.
Expected 4xx responses from /v2/user/info no longer log a traceback.
* fix(proxy): drop unbounded IN from org admin check in /v2/user/info
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(cost-map): record the provider's recommended replacement as successor_model on deprecating rows and report it from /model/deprecations
* fix(cost-map): pick the alias row's successor by its own shutdown date when the family has several
* chore(ui): regenerate schema.d.ts for the /model/deprecations successor_model wording
* fix(proxy): prefer a configured successor_model over the cost map's when deployments share a name, and keep the cost map's under a hand-set deprecation_date
* test(cost-map): allow successor_model in the cost map row schema
* feat(cost-map): infer successor_model as the next version in the same family for 136 dated rows with no published replacement
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
