* feat(proxy): add require_key_agent_access_defined for least-privilege agent access
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): align A2A model visibility assertions with supported routes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep A2A model entries on their existing routes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): point the listing model at the harness upstream
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): coerce require_key_agent_access_defined like the settings validator
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): inject agent access lookups instead of patching the handler
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(proxy): rename require_key_agent_access_defined to agent_access_default_deny
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: ryan <ryan@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(gemini): continue MAX_TOKENS decodes with continuationToken across chat, streaming, and interactions
* fix(gemini): continue long decode on CONTINUATION and cancel interactions at /cancel
* feat(gemini): add public gemini-4-argon cost-map rows for AI Studio and Vertex AI
Add gemini/gemini-4-argon and vertex_ai/gemini-4-argon alongside the existing
early-access row, carrying the same limits and capabilities. The AI Studio row
mirrors the early-access entry; the Vertex row differs only in provider and
pricing source. Prices follow once Google publishes them.
Extend the mapped metadata test to cover all three ids, that each routes to its
provider, that its backup copy matches, and that the public rows carry the same
limits as the early-access row.
* feat(gemini): raise gemini-4-argon to the 1M long decode cap and report initial_prompt_tokens across hops
* chore(prices): build on the merged gemini-4-argon rows and only raise the long decode cap
* fix(gemini): follow continuation hops in a loop instead of recursion
The unary hop collectors and the stream iterator called themselves once per continuation request, which the recursion check in CI rejects and which would hit the interpreter's call depth on a very long output. They now loop, and a test follows more hops than the interpreter allows nested calls
* fix(gemini): bill Google Search grounding from every continuation request
Google sends search grounding once, on the request that ran the search, and does not repeat it on a continuation request. The merged response kept only the last request's grounding, so usage.web_search_requests and the per-search fee dropped every earlier search. Unary merges and the stream iterator now carry the grounding of every request in the chain
* fix(gemini): continue long gemini-4-argon answers on streams and Vertex AI
A continued stream stopped after the first chunk of its second request. The stream wrapper asks the iterator for a fresh start before every chunk, and that reset it to the first request's finished stream. The iterator now reads from the newest request's stream
On Vertex AI the continuation request went to the v1 API version, which rejects continuationToken with a 400. A request that carries the token now goes to v1beta1, which accepts it, including a token that v1 issued
On a stream, initial_prompt_tokens came from a usage chunk in the middle of the stream, which reports a smaller prompt count than the last chunk. It is now the count the first request's stream ends with, the same number a unary call reports
continuation_token is no longer forwarded on the Interactions API, which answers 400 for the field. It is dropped there as it was before this branch
* chore(gemini): name the type errors the dual-mode stream iterator trips
The stream iterator holds a sync or an async line iterator in one untyped attribute. Pointing it at a continuation request's stream gave the type checker a concrete union for it, so six existing lines that only ever run in one of the two modes started to report errors
This adds a rule-named suppression with a reason on each of those lines and changes no code. Splitting the class into a sync and an async iterator would remove them and is left for a follow-up
* fix(gemini): continue only when Google ends a request with CONTINUATION, and stop streaming mid-answer tokens
A long decode now sends the next request only when Google's finish reason is CONTINUATION, so an answer cut at the caller's own max_tokens returns in one request with its continuation_token instead of drawing a rejected extra request
A request for more than one choice is never continued, since Google rejects a continuation with more than one candidate
Chat-format streams no longer carry the tokens Google sends mid-answer. Only a stream that ends cut off carries a continuation_token, on its last content chunk
The response cache key now includes continuation_token, so a resend with a token is not served the earlier segment
* fix(gemini): keep one response id across a continued answer
A continued chat stream changed its chunk id each time the next request to Google started, and a unary answer came back under the last request's id. Every chunk and the unary answer now carry the first request's id, including the chunk that ends a cut-off stream
A request whose n or max_tokens arrives as a string is sent once and never continued, where it used to fail with a 500 on the comparison. An empty continuation_token no longer changes the cache key
* test(gemini): add integration cells for long decode continuation
Covers continued answers on chat, /v1/messages and /v1/responses, streamed and not, on the Gemini API and Vertex AI against a scripted Google, plus concurrency, outage and worker restart runs
Also moves the Google stand-in cancel route to /cancel, the URL this PR now calls for Interactions cancel, and checks the cancel test posts there exactly once
* fix(vertex_ai): fetch the access token again before each continuation request
A long Gemini 4 answer on Vertex AI can run for over half an hour of follow-up requests, and every one of them reused the bearer token fetched before the first request. Once that token expired Google answered 401 and the caller got a cut-off answer with finish_reason length
Each Google request in a chain now asks for the token again, which is a cache hit until the token nears expiry, on the streamed and unary paths, sync and async. A refresh that fails counts as a failed follow-up, so the caller still gets the answer so far with its continuation token. A caller's own Authorization in extra_headers still wins on every request, and the Gemini API key path is unchanged
* fix(vertex_ai): start each continuation stream with an empty parser buffer
When a Google stream ended on an unfinished frame, its leftover text stayed in the stream parser and every frame of the next continuation stream was appended to it. None of them could be decoded, so the whole continuation was billed and dropped without an error
Each continuation stream now starts with a fresh buffer, and a test covers a stream that ends on an unfinished frame, sync and async
* fix(vertex_ai): treat a continuation stream with no readable frame as a failed follow-up
A continuation stream that answered 200 and then sent Google's error frame first, sent a body that is not JSON, or dropped before its first frame ended the caller's stream with `stop` or an error and no token, so a cut answer looked complete or was lost. It now ends the way a refused follow-up does, with the answer so far, `finish_reason` length and that request's token
Every continuation stream request now also gets the caller's per-request timeout, which #46349 added to the first one, so a follow-up that never answers ends at that timeout the same way
* fix(vertex_ai): keep every follow-up's citations and URL context in a continued answer
A non-streamed answer that took several Google requests kept citationMetadata and urlContextMetadata from the last request only, and left every later request's offsets counting from that request's own text. So a URL read on the first request was missing from the answer, citations from earlier requests were dropped, and a later request's citations and search supports pointed at the wrong part of the joined answer
The joined answer now keeps every request's citations (Vertex AI's `citations` and AI Studio's `citationSources`) and URL context, and shifts each later request's citation and search support offsets by the UTF-8 bytes of the answer text sent before it, thought parts excluded, since Google counts these offsets in bytes
* fix(vertex_ai): answer when a candidate sends null citationMetadata or urlContextMetadata
A Gemini candidate whose citationMetadata or urlContextMetadata was JSON null made the call fail on every Gemini model, non-streamed with a 422 or 500 and streamed with an error event, because the per-request metadata helper handed the null back as is and the caller tried to extend a list with it. A continued answer also failed when a follow-up's citation or search support came with a null startIndex
A null field is now kept as one entry on a single request, as it was before this branch, a follow-up's null URL context adds nothing to a continued answer, and a null startIndex counts from the start of that request's text. Tests cover missing, null and empty fields on one request and on a continued answer, streamed and not
* fix(vertex_ai): pass through spans with no end index and point a continued stream's citations into the whole answer
A later request's citation or search support with no endIndex made the whole non-streamed answer fail with a 500, so a span Google sends without an end index now comes back as Google sent it, the way one request for the whole answer returns it. A span with an end index but no start index still counts from 0
A continued stream handed callers each later request's citation and search support offsets counted from that request's own text. The stream now adds the answer bytes of every earlier request, so the offsets point into the whole answer like the non-streamed path and one request for the whole answer
Adds the audit's wire tests for both, which fail 24 cells before this change
* test(vertex_ai): cover a later request whose cited span starts at its first byte with no start index
Google leaves out a zero startIndex, so the second request of a continued answer can cite its own opening with only an endIndex. These wire cells check that span lands where one request for the whole answer puts it, on Gemini and Vertex AI, chat and Responses, unary and streamed
* fix(vertex_ai): log a continued answer's raw response as one object
A non-streamed answer joined from several Google requests logged its raw response as a JSON list of every request's body. The OpenTelemetry logger reads that raw response as one Gemini body to set its `llm.gemini.*` attributes, so on a continued answer it hit a validation error and set none of them
It now logs the merged body, which carries only the last request's token, and a single request still logs Google's body unchanged. The new unit test fails with the change reverted
Also adds integration cells for a cut chat stream's token chunk, an answer joined from 41 requests, a caller that gave up on a non-streamed call, counts and caps that are not numbers or are sent twice, `n` sent as true, a partial answer cached after a refused continuation, the token in another provider's cache key, and the sync SDK path with its Vertex token refetch
* test(integration): check a continued answer logs one merged raw response
A non-streamed Gemini answer that took several Google requests now hands logging one merged response, so the OpenTelemetry span carries the llm.gemini attributes. These 12 cells fail on the merge base and on the commit before that fix, and pass on the branch
* test(vertex_ai): cover a follow-up tool call and its thought signature in long decode
* test(gemini): pin that a one-request answer logs Google's body unchanged
* fix(anthropic): send detail on input_image parts bridged from /v1/messages to Responses
* fix(ui): send detail on playground Responses image parts and code snippets
* test(messages): cover image detail on the Responses bridge wire
GET /v1/mcp/server takes an optional user_id (admin, or the user themselves) and returns the union of the servers each of that user's teams reaches plus allow_all_keys servers. A user in no team gets the unscoped list, a deleted team still listed on the user is skipped, an unknown user is a 404 and a restricted virtual key is refused like for team_id. team_id keeps precedence when both are passed.
The dashboard MCPServerSelector passes the team and user it edits (key edit sends keyData.team_id and user_id, key create sends the picked team and owner, user edit sends the user) and narrows the server options to members of the access groups selected in the same control, keeping allow_all_keys servers and servers already granted so they can still be removed.
Resolves LIT-7784
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(proxy): name the successor model for deprecating deployments
* chore(ui): add successor_model to the generated deprecation api types
* fix(proxy): keep the cost map successor when a deployment overrides only the date
* fix(proxy): read the cost map successor from metadata.successor
The cost map schema rejects a top-level successor_model key, and curated
entries already carry the successor under metadata.successor. Read that key,
and look it up even when the cost map entry has no deprecation date, so a
deployment that sets only its own date still names the successor.
* fix(proxy): keep the first deployment when deduping, let a blank successor hide the cost map one, and name a served successor by its model group
* fix(proxy): name only the deployment's own successor_model, since cost map successors are LiteLLM ids rather than served model names
* fix(proxy): leave out a successor_model the deployment's callers cannot call, with a warning
* fix(proxy): report successor_model as the admin set it and only warn when no model matches it
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(agents): support Databricks Agent Platform agents in the agent gateway
Add a databricks_agent provider that speaks the MLflow ResponsesAgent wire
(Responses-shaped input, output_text items, output_text.delta SSE) to Model
Serving endpoints (/invocations or the unified /serving-endpoints/responses)
and Databricks Apps (/responses), with a PAT or OAuth M2M client credentials
Register it through the agents config block or the Admin UI agent catalog and
call it through /a2a/<agent> (message/send, message/stream) or model:
a2a/<agent> chat completions. The chat route now runs every completion-bridge
agent through its own provider, and attaches the minted Databricks OAuth token
for both bridge and URL agents. Consumed OAuth settings never reach the
provider call
* fix(agents): harden databricks_agent input, output, and OAuth handling
Non-text content parts answer 400 unless drop_params is set, a reply without
an output list answers 502, flat OAuth fields resolve an os.environ api_base,
the bridge debug log no longer echoes the request model, routing tests stub
only the HTTP boundary, and the catalog description fits the dropdown
* fix(agents): merge agent and client extra_headers on the a2a chat route, and reject an empty databricks_oauth block
* fix(agents): bridge only databricks_agent agents on the a2a chat route, keep the card url over a client api_base, and require workspace_url for a Databricks App
* refactor(agents): read the a2a chat bridge providers from a constants set instead of branching on a provider name
* fix(databricks_agent): let the configured credential win, reject malformed client extra_headers, and keep a missing endpoint name empty
* test(agents): drive the flat OAuth a2a send through the real bridge
* fix(agents): keep an empty databricks_oauth block ignored on url agents, as before this change
* fix(agents): accept bare App hosts, env service principals, and os.environ refs on Databricks agents
* fix(databricks_agent): address review caveats on chat bridging, params, and auth
Map max_tokens and max_completion_tokens to max_output_tokens and pass
temperature, top_p, and user, so /v1/messages works without drop_params.
Send A2A message metadata only with string values, answering 400 or
dropping the rest under drop_params. Join message items with a blank line
in both stream and non-stream replies. Cache the env service principal
token until shortly before it expires. Keep databricks_agent replies out
of the response cache.
On the chat bridge, let request fields win over the agent's stored params
while pinning the agent's api_base and api_key, and apply the agent's
static_headers between client and agent extra_headers, as /a2a does.
Resolve os.environ/ only for databricks_agent api_base and api_key instead
of every bridge provider. Ignore an unusable databricks_oauth block on URL
agents on chat, as at the merge base, instead of answering 400.
* test(internal_context): list the databricks agent token cache as process-local
* fix(databricks_agent): keep the agent's endpoint, input, and target out of client control
extra_body model and input answer 400, or are dropped under drop_params.
A client api_base or base_url never replaces the agent's card URL on the
bridge. Chat to a URL agent keeps its merge-base call, and an incomplete
databricks_oauth block on a URL agent keeps its merge-base ValueError.
* test(databricks): expect the merge-base 400 for a client api_base on agent chat
* fix(databricks): keep agent-owned inputs and identity headers out of a chat caller's reach
* fix(databricks): bound the agent-over-caller merge to two levels so it needs no recursion
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(proxy): split Azure PTU deployments across teams by share
A PTU deployment's model_info takes ptu_shares (team_id -> whole PTUs adding up to
ptu_count) in place of a single team_id. With LITELLM_ENABLE_PTU_COST_ATTRIBUTION on,
routing hides the deployment from teams holding no share, the v3 limiter enforces each
share as a per-team TPM ceiling from Azure's per-model TPM-per-PTU sizing, the daily
flat-cost rollup splits the hourly cost by share, and /team/daily/activity plus the Team
Usage page report PTU-hours next to tokens.
* fix(proxy): weight cached input in PTU ceilings and size team-scoped deployments by public name
The PTU flag is read from the process environment on every check instead of
through the secret-manager path, so a proxy with a hosted secret manager does
not pay a round trip per request. A team's ceiling now carries the model's
cached-input ratio and settlement charges cache reads at that ratio, matching
how Azure sizes a PTU. A deployment registered for one team is found by its
team_public_model_name for PTU-hours and the ceiling, since its model_name is
rewritten to a unique internal name. ptu_shares are StrictInt on ModelInfo and
parsed_ptu_shares refuses booleans, strings, and non-string team ids, a
fractional ptu_count reserves nothing, and models_processed counts distinct
deployments rather than holdings.
* fix(proxy): reserve PTU ceilings in normalized tokens, keep share routing flag-independent, and warn only shared or Azure reservations
* fix(proxy): size the uncapped output floor against the PTU share in raw output tokens and escape the exported team id
* fix(ptu): refuse ptu_shares naming a team that does not exist
* refactor(ptu): keep Azure detection under llms/azure and check share teams with one query
* fix(proxy): drop the reverted TeamIdSearchFilter import after merging main
Main reverted the team key search change that added TeamIdSearchFilter, so the PTU share team check types its where clause locally
* fix(proxy): chunk the ptu_shares team lookup under the IN-list bound
* fix(proxy): count a request naming a shared PTU deployment directly against its group's ceiling
* fix(proxy): resolve every name a shared PTU deployment is served under to its group's ceiling
* fix(ptu): refuse ptu_shares declared without ptu_count and cost_per_ptu_per_hour
* fix(ui): seed total_ptu_hours in the empty daily activity metadata
* fix(ptu): size usage rows by the name the request used
* fix(ptu): size a team's usage rows by the deployment it is served from
* fix(ptu): never size a team's usage row by another team's reservation
* fix(ptu): reserve an uncapped request against the cap the proxy writes, not its prompt length
* fix(ptu): read a share map only through the terms registration requires
A ptu_shares map stored without ptu_count, cost_per_ptu_per_hour and
ptu_effective_from, or one that does not add up to ptu_count, is refused at
registration but was enforced once loaded: every other team got the 400 and
the share holder a ceiling while no flat cost accrued. _deployment_shares now
reads the shares through ptu_terms, so such a row reserves nothing, the same
as before the map was read.
* fix(ptu): keep a declared split as the access rule and check a config split at boot with the flag off
6fb24d1d read ptu_shares through the pricing terms so a termless map reserved
nothing, but with the flag off the router skips ptu_config_error for config.yaml
entries, so such an entry loaded and served every team, against the rule that a
declared split restricts access whether or not cost attribution is on.
_deployment_shares reads the declared map again, and the router now raises
ptu_config_error for a config-sourced entry declaring ptu_shares regardless of
the flag, so a malformed split is refused at boot instead of being honoured or
ignored silently.
* fix(ptu): charge wildcard-served names, pass-through usage, and team-less settlements against the team's PTU ceiling
A name served by a wildcard route now resolves to the shared deployment behind it, so the
limiter's ceiling and the team daily activity sizing both find it. Pass-through responses
settle the PTU counter from combined_usage_object in Azure-normalized tokens, and a
reservation taken at admission is settled even when the success metadata lost the team.
* fix(ptu): resolve a wildcard-served name to the one pattern the router picks, and a deployment id before any wildcard
A team's wildcard reservation behind an open proxy-wide * route was charged and sized for traffic the * route served, and naming a shared deployment by id next to a catch-all wildcard escaped its per-team ceiling. Router.wildcard_route_deployments now owns the most-specific-proxy-wide-else-team precedence, and both the limiter and the consumption page resolve through it after listed rows and deployment ids.
* test(router): pin the wildcard route precedence that PTU sizing and the router share
* fix(proxy): accept whole-number PTU shares written as floats, as ptu_count already does
A share of 2.0 now reads as 2 on POST /model/new and in config.yaml, where it was
refused with a 422 and dropped at load. Fractional, infinite, boolean and string
shares stay refused. Adds unit tests for the malformed-rate, provider-over-prefix,
zero-token Responses usage, fractional-count and sizing-warning paths.
* fix(proxy): settle team PTU reservations in their own minute and keep billed PTU days when shares move
* fix(proxy): write each PTU deployment day's team charges in one transaction
The backfill counts a deployment day as priced once any team's row exists for it,
so a rollup that wrote team A's share and lost team C's left team C unbilled for
good. Each deployment day's team rows now go through one Prisma batch with the
retry around the whole batch, so a day is fully written or not written at all and
the next backfill prices it for every team.
* fix(proxy): read the PTU flag from a secret manager, serve share holders from their share, and refuse unfittable calls and share-holding team deletes
* test(router): list the cached PTU ceiling helpers in the router coverage check
* fix(proxy): read the PTU flag only for share holders, guard org and SCIM team deletes, keep share holders on their shared deployment through retries and the scheduler, and date PTU-hours by the terms in force
* fix(proxy): bill a rerun PTU day to the current share holders alone
* fix(proxy): replace a PTU day's rows by day and deployment, not a negated team list
* fix(proxy): read the PTU flag from the secret manager first, like get_secret
* fix(router): scope retry health lookups to the caller only for PTU share holders
* fix(router): move the share-holder retry check into ptu_shares
Adds ptu_hours and total_ptu_hours to the daily activity integration goldens and fixtures, since every route now reports them
* test(integration): cover PTU shares across routing, delete guards, cost attribution and config regex timing
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(proxy): report when each per-model budget window resets
model_max_budget_usage on /key/info, /user/info and /team/info now carries budget_reset_at per model, the open window's start plus its period, or null when no window is open. The window start is read in the same batched lookup as the spend counter
* fix(proxy): count a monthly budget window from its own start when reporting its reset
duration_in_seconds measures Nmo from now, so a window opened on January 15 and read on February 10 reported February 12, then null while the counter still refused requests until February 15. duration_in_seconds_from measures the month from the window start, and duration_in_seconds now shares that month arithmetic
* fix(proxy): measure months from timezone-aware datetimes and assert whole usage values
datetime.fromtimestamp without a tz tripped DTZ006. The month arithmetic now runs on an aware local datetime, which keeps the same wall-clock result. The duration tests move to parametrized functions, since subTest payloads carrying datetimes cannot cross the xdist worker boundary, and the new usage tests compare the whole entry
* fix(budgets): end a monthly budget window a calendar month after it opens
Each charge recounted the month from the charge date, so a monthly window
opened in a month of another length expired days before or after the reset
/key/info reports. The window is now measured from its start, by the same
helper the usage report uses. A period ending after year 9999 reports no
reset instead of failing the read.
* fix(budgets): count monthly budget windows in UTC for every router budget
Months were counted on the host's local calendar, so replicas with different TZ
settings disagreed on when a monthly window ends. Provider, deployment, tag and
per-model budgets now all measure a window from its start in UTC, and a test
covers the router budgets. A reset past year 9999 is documented as null.
* test(budgets): cover monthly tag budgets in the router window test
* test(budgets): add integration cells for budget_reset_at and monthly budget windows
* test(budgets): find a monthly window in another span on every calendar day
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(proxy): scope /spend/tags aggregates to the caller's own and permitted-team logs
Non-admin callers previously received the proxy-wide per-tag spend
aggregation. The endpoint now resolves the same read scope as
/spend/logs/ui and /spend/logs/session/ui, and the query honors the
start_date/end_date parameters it previously accepted but ignored.
* fix(proxy): use Annotated auth dependency on /spend/tags and sync dashboard API types
* fix(proxy): bind /spend/tags dates as UTC datetimes, not session-timezone strings
Raw YYYY-MM-DD strings cast to timestamptz are read in the database
session timezone, shifting the day window by that offset. Parse them
to UTC-aware datetimes first, like every sibling spend query in this
file, and reject malformed dates with a 400 before they reach the
database.
/public/providers/fields re-read and re-parsed the bundled 85K
provider_create_fields.json on every request, and /public/agents/fields did the
same for that file plus agent_create_fields.json. Both are unauthenticated
public endpoints, and both did the work inside an `async def`, so the read and
the parse ran on the event loop and serialized against every other in-flight
request. Measured against the bundled files, that is roughly 0.40 ms of blocking
work per request for the provider endpoint and 0.45 ms for the agent endpoint
Both now memoize with `lru_cache`, which is what `/public/endpoints` in the same
module already does through its `_cached_endpoints` global, so each file is read
once per process rather than once per request
The agent endpoint mutated the dicts it had just loaded, appending inherited
provider credential fields and popping `inherit_credentials_from_provider`. That
is only safe while the data is re-read every time, so caching it meant making the
merge pure: `_agent_with_inherited_credentials` builds a new mapping per agent,
and the cached value is the merged result rather than the raw file contents.
Responses are byte identical before and after, checked on both endpoints against
a live proxy
The bundled records are typed as Mapping[str, object] and narrowed with
isinstance at the point of use, rather than typing.Any, which ruff-strict bans
Side effects: 3 of the repo's ASYNC230 violations go away, and basedpyright
errors in the file drop from 63 to 52
Rebased onto main after /public/providers/fields started validating the bundled
JSON through a pydantic adapter on every request. That validation now runs once
and the validated records are cached; the agent endpoint keeps merging the raw
provider records, so both responses stay byte identical to main.
Co-authored-by: Alok Sharma <alok44170@gmail.com>
* feat(ui): status filter + sort and provider-aware search on Models & Endpoints
The models table mixes active and paused deployments with no way to tell
them apart beyond the pause toggle, and the drawer only filters by public
model name and access group.
Backend (/v2/model/info):
- new optional `blocked` query param to filter by routing status
- new `blocked` sort field (asc = active first); the existing `status`
field keeps sorting by config-vs-DB source
- `search` now also matches litellm_params.model, so typing a provider
or upstream model id (e.g. "nvidia_nim", "openai/gpt-4") finds
deployments whose public name doesn't mention them
Frontend (Models & Endpoints):
- visible Status column with Active/Paused badges, sortable
(active first on asc)
- Status filter (All/Active/Paused) in the Filters drawer, wired to the
new server param through URL state
The routing-status filter ignores non-bool sentinels the same way
exclude_auto_routers does, so direct calls bypassing FastAPI keep their
no-filter behavior.
* fix(ui): inverted routing-status filter mapping and compact Status column
Selecting "Active" in the Filters drawer sent blocked=true to the server,
showing the paused deployments instead of the active ones (and vice
versa). The mapping now lives in routingStatusToBlocked() with unit
tests, and the Status column is narrower so the row actions stay in
view.
* fix(ui): pin the Actions column to the right on the models table
With the new Status column the table overflows on narrower screens and
the pause/resume switches (last column) scroll out of view. Pinning the
Actions column keeps them visible; uses the existing DataTable
meta.pinned support (same pattern as MemberTable).
* refactor: readable db search where-condition and ruff-format clean
* fix: apply routing-status filter inside the search flow and regen API types
Greptile flagged (P1): with search + a status filter combined, the
bounded DB fetch ran before status filtering, so matches of the other
status could consume the page budget and leave short pages / stale
totals.
- extract _matches_routing_status() (sentinel-safe) and apply it to the
router-side matches inside _apply_search_filter_to_models
- push the status condition into the DB where clause of
_fetch_db_models_for_search, so rows of the other status never count
against the bounded fetch
- endpoint passes blocked through to the search flow; tests cover the
combined search+status case and the generated where clause
- regenerate ui/litellm-dashboard/src/lib/http/schema.d.ts for the new
query param
- update useModels.test.ts expectations for the new trailing argument
* fix(proxy): keep the flat DB where shape for single-condition searches
The upstream CI test
test_apply_search_filter_honours_exact_model_name_in_db_query pins the
Prisma where shape: exact model_name stays a top-level key, and plain
substring search keeps {model_name: {contains, mode}} at the top level.
Only genuinely multi-condition queries (status filter and/or router-id
exclusion) now wrap in AND.
* fix(proxy): avoid reassigning a Final variable in the db where builder
basedpyright's reportGeneralTypeIssues budget counts the reassignment of
the Final-annotated db_where_condition; express it as a single
conditional expression instead.
* chore(deps): bump pypdf to 6.19.0 to clear osv-scan
pypdf 6.16.2 has 8 High CVEs (GHSA-5jq2-8x83-x246 and aliases) fixed in
6.17.0-6.19.0; bump past all of them
* Revert "chore(deps): bump pypdf to 6.19.0 to clear osv-scan"
This reverts commit 0e2528123db7ab23304ae20f6a4c0961d0e2d073.
* fix(proxy): keep LIT002 budget flat in the model search where-builder
Extract the dynamic Prisma where-condition fragments into module-level
helpers so every dict starts on a short line, split the litellm_params
fallback lookup into a Final local, and annotate suppressions on the
construct start lines the checker attributes
* chore(tests): repoint unbounded-IN baseline at the extracted where-builder helper
The bounded-router-id filter moved from _fetch_db_models_for_search into
_not_in_router_ids, so the old baseline key is stale and the new helper
site is the finding to record
* fix(proxy): avoid searching encrypted deployment model names
* refactor(ui): keep model routing status as a filter only
* docs(api): regenerate model info sorting description
* fix(api): remove remaining paused status sort references
---------
Co-authored-by: thementalcoding <312162298+thementalcoding@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(typesafe): support Jev 1.14 images, box questions, and long-context headers
* fix(cost): drop the typesafe/jev-1.14.0 entry main already prices
* fix(typesafe): send images only with the images header and box questions only to models that answer them
TypeSafe takes assets and input_image parts only when the request carries
TypeSafe-Danger-Zone-Images: true, so without it they follow drop_params like
any other provider that cannot take images. Box support now comes from a
supports_box_questions cost-map flag set on jev-1.14.0 and jev-preview, so
jev-1.13.0 and jev-latest refuse or drop a box question before the call. A
malformed provider_specific_header answers 400 instead of 500.
* fix(typesafe): allow null box confidence and validate asset references and base64
* fix(typesafe): gate box questions on the images header, drop unreadable assets under drop_params, forward opt-in headers on the pass-through
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix: index streamed thinking_blocks so the OpenAI SDK .stream() accumulator accepts them
* fix: satisfy the type discipline and basedpyright gates for the thinking block index
* chore: sync the OpenAPI snapshot and schema.d.ts with the thinking block index field
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): translate OpenAI tool_search to Anthropic tool search for Claude models
* fix(responses): define the tool_search_call output item locally for older openai SDKs
* fix(responses): gate tool search on the Anthropic request builder and validate deferred tool fields
Bedrock Converse builds its own request and has no tool search, so the bridge now drops the tool_search tool there with a warning instead of sending a tool the transport loses, while Bedrock invoke, Anthropic, and Vertex keep it. A replayed tool_search_call with no stored result is dropped from the Anthropic request so a previous_response_id follow-up no longer answers 400. Only srvtoolu_ ids whose name is one of Anthropic's search tools count as search calls, so a caller function named like one stays a function call. A non-boolean defer_loading or a non-list allowed_callers now answers 400 instead of 500
* fix(responses): keep an answered search call on replay and send tools undeferred when no search tool goes out
A replayed Claude tool search call that the caller answered with a tool message kept its
tool_result in the user turn while its tool_use was dropped from the assistant turn, so
Anthropic answered 400 on the OpenAI-SDK tool loop. The search call is now dropped only when
no tool message answers it.
The Responses bridge now strips defer_loading from every tool whenever no tool search tool is
sent, whether the caller sent none or the route cannot run it, since a deferred tool with no
search tool can never be loaded. Namespace members had started carrying the flag to every
bridge provider, which providers that reject unknown tool keys answered 422.
The audit round-1 integration cells for the bridge wire and chaos paths ride in this commit.
* fix(responses): gate only the OpenAI tool_search shape and keep native Anthropic search tools intact
A native tool_search_tool_regex_20251119 or tool_search_tool_bm25_20251119 tool the caller sends through /v1/responses passes through the bridge on every route as before, and the other tools keep defer_loading whenever any Anthropic search tool goes out. The route gate now drops the OpenAI tool_search item before translation instead of filtering the translated regex tool, so bm25 counts as a search tool. answered_tool_call_ids walks the history with islice instead of a slice copy. The tool_search_call output item drops its created_by field, which OpenAI rejects on a replayed input item and the streaming item never carried
* fix(responses): drop malformed tool flags under drop_params and keep stored search calls off non-Anthropic follow-ups
With drop_params on, a non-boolean defer_loading or a non-list allowed_callers on a Responses API tool (or a namespace member) is dropped before the bridge instead of answering 400, so only a request without drop_params gets the 400. A custom tool now carries defer_loading to the chat tool like a function tool does
A previous_response_id follow-up routed to a provider that does not build an Anthropic request no longer replays the stored Claude search call (srvtoolu_ id) as a client tool call. Mistral answered that history 400 "Unexpected tool call id". An assistant turn that held only the search call is dropped there. The Anthropic route keeps the call, since its factory pairs it with the stored result
The tool_search_call output model is renamed OutputToolSearchCall so the proxy's OpenAPI schema keeps the OpenAI SDK's ResponseToolSearchCall name. answered_tool_call_ids reads the history by index, so the lookup is linear in the history length. The streaming done event reads the response it is given, which is the same object it used to read from the iterator
* fix(responses): validate function allowed_callers, send one search tool, and keep replays clean off Anthropic
A function tool whose allowed_callers is not a list of strings now answers 400
instead of 500. The guardrail scan reads tools without malformed flags, so the
route decides between a 400 and a drop under drop_params. When the caller sends
a native Anthropic search tool beside tool_search, only the native one goes out.
Databricks Claude no longer counts as an Anthropic request route.
A previous_response_id follow-up off Anthropic also drops a search call the
client replayed as a function_call with a srvtoolu_ id, and its output. The
answered tool id scan in the Anthropic message factory runs once per assistant
run instead of once per message. A null created_by on tool_search_call and
tool_search_output output items is left out of the serialized response, so a
cache hit returns the same keys as the first call.
* fix(guardrails): keep OpenAI tool_search out of the Responses guardrail tool scan
The scan translated tool_search into Anthropic's regex search tool on every
route, so a guardrail returning only function tools removed tool_search from
native OpenAI requests and OpenAI answered 400 for the deferred tools
* fix(anthropic): drop answered tool search replays beside client calls, place system before dropped search turns, flag tool search on azure_ai
* fix(anthropic): keep answered tool search replays paired with their answers
* fix(anthropic): place mid-conversation system messages in one pass and scan tool_search_call in output guardrails
* fix(guardrails): send empty incomplete tool_search_call arguments when a rewrite is not a JSON object
* fix(responses): keep the caller's defer_loading on Claude routes when no server tool_search is sent
* fix(guardrails): deliver streamed rewrites when OpenAI's tool_search_call has no call_id
* fix(responses): answer 400 to a tool_search execution that is not server or client
OpenAI's own Responses API answers 400 invalid_value to it. With drop_params the malformed
execution is dropped like the other malformed tool flags, which leaves a server search
* test(responses): cover the 400 and drop_params paths for a malformed tool_search execution
* fix(responses): map Anthropic tool search to OpenAI server tool search
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): sync generated tool search API types
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): type tool search mapping predicates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): validate tool-search mappings
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): use the openai SDK ToolSearchToolParam for the mapped tool search
* fix(responses): keep deferred chat tools beside a tool search on the responses bridge
Restore the hand-rolled OpenAIToolSearchToolParam, since openai 2.20.0 (the
supported floor) has no ToolSearchToolParam, and carry defer_loading from chat
function tools onto the Responses request when a tool search tool is present,
which OpenAI requires for tool_search
* fix(responses): leave the bridge's defer_loading carry to its own PR
#46439 owns keeping defer_loading on chat function tools sent through the
Responses bridge, so this PR keeps only the tool search mapping and the
openai 2.20.0 compatible tool type
* fix(openai): keep tool search mapping to the OpenAI API and drop it where the model or history cannot take it
* fix(openai): narrow the tool search drop to Anthropic's search tool, drop it when nothing is deferred, and run the wire tests against the OpenAI host
* fix(openai): pass malformed tools to OpenAI as sent and keep a caller's own tool_search under drop_params
* perf(openai): scan Responses history for Claude search calls only when Anthropic's search tool is sent
* test(responses): cover the Anthropic tool search mapping to OpenAI Responses across routes, settings, and chaos
* test(integration): define the fallback cell's deployments in the gateway config so both workers load them
* test(integration): keep the worker-kill burst held past the replacement wait
* fix(responses bridge): count an Anthropic search tool as hosted tool search on the chat bridge
main's #46439 refuses defer_loading when no tool_search tool is in the request, and the chat bridge only counted {"type": "tool_search"}, so the Anthropic bm25 or regex tool this PR maps to OpenAI's tool search was refused before the mapping ran
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): expect the chat bridge to map the search tool now that defer_loading survives
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): translate OpenAI tool_search to Anthropic tool search for Claude models
* fix(responses): define the tool_search_call output item locally for older openai SDKs
* fix(responses): gate tool search on the Anthropic request builder and validate deferred tool fields
Bedrock Converse builds its own request and has no tool search, so the bridge now drops the tool_search tool there with a warning instead of sending a tool the transport loses, while Bedrock invoke, Anthropic, and Vertex keep it. A replayed tool_search_call with no stored result is dropped from the Anthropic request so a previous_response_id follow-up no longer answers 400. Only srvtoolu_ ids whose name is one of Anthropic's search tools count as search calls, so a caller function named like one stays a function call. A non-boolean defer_loading or a non-list allowed_callers now answers 400 instead of 500
* fix(responses): keep an answered search call on replay and send tools undeferred when no search tool goes out
A replayed Claude tool search call that the caller answered with a tool message kept its
tool_result in the user turn while its tool_use was dropped from the assistant turn, so
Anthropic answered 400 on the OpenAI-SDK tool loop. The search call is now dropped only when
no tool message answers it.
The Responses bridge now strips defer_loading from every tool whenever no tool search tool is
sent, whether the caller sent none or the route cannot run it, since a deferred tool with no
search tool can never be loaded. Namespace members had started carrying the flag to every
bridge provider, which providers that reject unknown tool keys answered 422.
The audit round-1 integration cells for the bridge wire and chaos paths ride in this commit.
* fix(responses): gate only the OpenAI tool_search shape and keep native Anthropic search tools intact
A native tool_search_tool_regex_20251119 or tool_search_tool_bm25_20251119 tool the caller sends through /v1/responses passes through the bridge on every route as before, and the other tools keep defer_loading whenever any Anthropic search tool goes out. The route gate now drops the OpenAI tool_search item before translation instead of filtering the translated regex tool, so bm25 counts as a search tool. answered_tool_call_ids walks the history with islice instead of a slice copy. The tool_search_call output item drops its created_by field, which OpenAI rejects on a replayed input item and the streaming item never carried
* fix(responses): drop malformed tool flags under drop_params and keep stored search calls off non-Anthropic follow-ups
With drop_params on, a non-boolean defer_loading or a non-list allowed_callers on a Responses API tool (or a namespace member) is dropped before the bridge instead of answering 400, so only a request without drop_params gets the 400. A custom tool now carries defer_loading to the chat tool like a function tool does
A previous_response_id follow-up routed to a provider that does not build an Anthropic request no longer replays the stored Claude search call (srvtoolu_ id) as a client tool call. Mistral answered that history 400 "Unexpected tool call id". An assistant turn that held only the search call is dropped there. The Anthropic route keeps the call, since its factory pairs it with the stored result
The tool_search_call output model is renamed OutputToolSearchCall so the proxy's OpenAPI schema keeps the OpenAI SDK's ResponseToolSearchCall name. answered_tool_call_ids reads the history by index, so the lookup is linear in the history length. The streaming done event reads the response it is given, which is the same object it used to read from the iterator
* fix(responses): validate function allowed_callers, send one search tool, and keep replays clean off Anthropic
A function tool whose allowed_callers is not a list of strings now answers 400
instead of 500. The guardrail scan reads tools without malformed flags, so the
route decides between a 400 and a drop under drop_params. When the caller sends
a native Anthropic search tool beside tool_search, only the native one goes out.
Databricks Claude no longer counts as an Anthropic request route.
A previous_response_id follow-up off Anthropic also drops a search call the
client replayed as a function_call with a srvtoolu_ id, and its output. The
answered tool id scan in the Anthropic message factory runs once per assistant
run instead of once per message. A null created_by on tool_search_call and
tool_search_output output items is left out of the serialized response, so a
cache hit returns the same keys as the first call.
* fix(guardrails): keep OpenAI tool_search out of the Responses guardrail tool scan
The scan translated tool_search into Anthropic's regex search tool on every
route, so a guardrail returning only function tools removed tool_search from
native OpenAI requests and OpenAI answered 400 for the deferred tools
* fix(anthropic): drop answered tool search replays beside client calls, place system before dropped search turns, flag tool search on azure_ai
* fix(anthropic): keep answered tool search replays paired with their answers
* fix(anthropic): place mid-conversation system messages in one pass and scan tool_search_call in output guardrails
* fix(guardrails): send empty incomplete tool_search_call arguments when a rewrite is not a JSON object
* fix(responses): keep the caller's defer_loading on Claude routes when no server tool_search is sent
* fix(guardrails): deliver streamed rewrites when OpenAI's tool_search_call has no call_id
* fix(responses): answer 400 to a tool_search execution that is not server or client
OpenAI's own Responses API answers 400 invalid_value to it. With drop_params the malformed
execution is dropped like the other malformed tool flags, which leaves a server search
* test(responses): cover the 400 and drop_params paths for a malformed tool_search execution
* test(responses): cover a Claude search call replayed to Bedrock Converse with cache marks
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: mateo <mateo@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(ui): replace deployment warning banners with a health icon, critical row and panel
The debug, no Redis, env credential login and license expiry banners are gone.
Proxy admins and proxy admin viewers now get a shield icon in the header with
an active warning count, one row under the header for the top critical warning,
and a side panel where proxy admins snooze, ignore or restore each warning for
every admin of the proxy
* test(ui): cover deployment health wiring and warning content, drop unused license tier helper
Both dashboard shells are checked end to end for the icon, critical row and
panel, and the warning catalog is checked for its license wording, fix text
and links. getLicenseExpiryTier and its thresholds lost their last caller
with the license banner, and the proxy now decides severity
* fix(ui): wrap long setting names in deployment warning fix text on narrow screens
* style(ui): restyle deployment health to the dashboard design system
The critical row now follows the deployment alert banner: tone tint, bold lead, Review as a link and +N more on the right. The panel drops nested cards for ruled rows with severity icons, row actions move into a ⋯ menu, ignored rows show only who snoozed them and until when, and loading uses skeleton rows. The header shield matches the bell and carries a small count pill
* style(ui): rebuild deployment health on shadcn primitives with the reviewed design
The banner shows the most severe active alert by title with a Review link, the header shield carries a count badge, and the panel groups issues into collapsible Critical, Warnings, and Ignored and snoozed sections. Each issue is a tinted Alert with a docs link and a Snooze menu, snoozed issues keep the full layout with a status badge and Restore, and the empty state uses the shadcn Empty primitive
* chore(ui): exempt shadcn primitives from the PascalCase filename rule
The shadcn CLI writes kebab-case files under components/ui, so every primitive needed a suppression entry and each new one failed lint. Exempt the folder and drop the 34 entries it replaces
* fix(ui): let long setting names in deployment warnings wrap inside the alert on phones
The shadcn Alert lays out its text in a 1fr grid column, whose minimum width is the longest unbreakable run. overflow-wrap break-word does not lower that minimum, so a long setting name pushed the panel wider than a 390px screen. overflow-wrap anywhere does
* fix(cost): price AgentCore web search at $7 per 1,000 queries
* feat(search): honor input_cost_per_query set on a search tool (#46560)
* feat(search): honor input_cost_per_query set on a search tool
* feat(search): record the search tool price on proxy-created logging objects
* chore(search): type the search tool price lookups and shard tests/unit/search
* chore(openapi): regenerate snapshot and ui types for search tool input_cost_per_query
---------
Co-authored-by: devin-ai-integration[bot] <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: Kerry Lu <klu@berri.ai>
* feat(proxy): general_settings.disable_requester_ip_address_logging keeps caller IP out of spend logs
When the setting is on, spend log rows store requester_ip_address as null in
the column, the metadata and the stored request (which also drops client-IP
forwarding headers), and IP addresses in stored error messages are masked, so
the Logs page shows no caller IP. The setting is read the way the settings API
validates it. Capture is unchanged, so guardrails, logging callbacks and
metrics still receive the IP. Toggleable from the Admin UI General Settings.
Resolves LIT-7442
* fix(proxy): mask IPv6 addresses that end or start with :: across eight groups
The masking pattern allowed seven colons, so valid forms like 1:2:3:4:5:6:7::
and ::1:2:3:4:5:6:7 stayed in stored error text with
disable_requester_ip_address_logging on. Also lists the request metadata walker
in the recursion check, since it only walks the tree the spend log sanitizer
already returned.
* fix(proxy): mask IPs in every stored header value and after labels or underscores
With disable_requester_ip_address_logging on, client IPs carried in headers outside the forwarding list (do-connecting-ip, incap-client-ip, custom names) and addresses written as host:2001:db8::2, peer_2001:db8::2, socket_192.0.2.1 or an unbracketed IPv6 with a port were still stored in spend logs.
* fix(proxy): mask request header IPs before long values are truncated
A header value longer than the spend log string limit kept the part of an IP that fell before the truncation cut. Request headers in metadata and requester_metadata are now masked before the body is truncated, like error text already was. IPv4 followed by a dotted port (192.0.2.1.443) is masked again.
* fix(proxy): mask the IP piece a header truncation cut leaves instead of pre-masking headers
Masking header values before truncation scanned the whole client value,
including text the cut drops, and walked hook-made header cycles. Mask after
truncation instead, then mask the hex and digit run touching each side of the
truncation marker when it is short enough to be part of an IP address. Every
nested headers mapping gets the same treatment.
* docs(proxy): say the requester IP setting masks IPs in other stored header values
* fix(proxy): mask stored error text after truncation and harden the cut-piece pass
Error messages and tracebacks were regex-scanned in full before the DB cap,
which costs seconds on multi-megabyte provider errors. Mask them after the
cap like header values, with the same pass over the run beside each
truncation marker. That pass now handles every marker, skips long hex tokens
so an address beside one is still masked, keeps at most one address length,
and also masks colon-only IPv6 groups.
* fix(proxy): drop the requester IP from the originating request an auto router classifier row stores
* fix(proxy): drop the requester IP from the classifier input an auto router classifier row stores
* refactor(proxy): mask stored IPs with the content filter's ipv4 and ipv6 patterns
The requester IP setting now reuses the content filter guardrail's prebuilt
ipv4 and ipv6 patterns instead of its own address regexes, so spend logs mask
what that guardrail masks. Addresses glued to a label or underscore stay as
the content filter leaves them.
* fix(proxy): mask stored IPs with the spend-log matcher again
The content filter's ipv4 and ipv6 patterns left labelled IPv6 (host:2001:db8::2),
unbracketed IPv6 with a port and IPv4 after an underscore in stored error text and
header values, and masked parts of text like std::io::Error. Restore the
address-validating matcher and its regression cases.
This reverts commit 79537a8aa5.
---------
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
The Airia guardrail (#40784) shipped without a dashboard presence: no card in the Guardrail
Garden and no logo next to its name in the provider list and guardrail table, which every other
partner guardrail has. This adds both, following the Wingback and Conduct entries:
- `airia.svg`, Airia's brand mark from AiriaLLC/airia-public-assets, under the bundled logos.
- A `guardrailLogoMap` entry keyed by the config model's `ui_friendly_name` ("Airia Guardrail"),
which is what the provider dropdown and table look the logo up by.
- A partner card and an `airia` preset. The preset's `provider` is the camel-cased registry key
("Airia"), the form the dashboard derives for every provider it reads from
`/guardrails/ui/provider_specific_params`. The preset seeds both `pre_call` and `post_call`,
as the docs example does, so a response-side redaction is not silently left out.
- The logo-file assertion in `guardrail_garden_data.test.ts` covers the new card.
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
* feat(proxy): let proxy admins open team member defaults to team admins
* fix(proxy): keep a team admin's never-resets duration on a team's first member budget
* test(proxy): pin the existing-row and stored never-resets cases for member defaults
* feat(proxy): let proxy admins open soft_budget to team admins
* feat(proxy): let proxy admins open team metadata to team admins, keeping proxy settings with proxy admins
* test(ui): name expected objects in team admin edit access tests
Keeps local/no-large-inline-object-arg within its eslint budget
* fix(proxy): compare team metadata without recursion and count key presence
A proxy-controlled metadata key that appears or disappears with a null value
is now a change, and the JSON comparison no longer recurses
* fix(proxy): compare team metadata numbers exactly
Numbers are compared as decimals, so integers past float precision and close
floats are no longer treated as equal
* fix(router): add fallback_on_unsupported_params so client-side param rejections can raise instead of falling back
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(router): wrap the fallback gate so ruff format passes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): rename the flag to fallback_on_bad_request and cover provider 400s too
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): narrow the wire test responses so the type gate count does not grow
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(openai): swap the model map with setattr so the type gate count does not grow
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): import the exception classes directly so the type gate count does not grow
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(router): type the fallbacks list in fallback_event_handlers to pay for the new Router kwarg in the type gate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(router): keep the LIT001 count flat on the typed fallbacks parameters
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(router): type the fallback stream wrapper weakref so the type gate stays level
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): make fallback_on_bad_request updatable at runtime so DB-stored router_settings apply it
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(ui): regenerate schema.d.ts for UpdateRouterConfig.fallback_on_bad_request
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): rename the flag back to fallback_on_unsupported_params
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* revert(openai): drop the reasoning_effort=none client-side check, the Router flag covers the provider 400
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: rerun docs checks now that the router_settings row is on litellm-docs main
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): only stop fallbacks on real 400s and cover the context window and content policy exclusions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): move the no-fallback 400 check into is_bad_request_without_fallback and pin the 402 and Vertex 403 cases
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): keep falling back on router-raised 400s when fallback_on_unsupported_params is off
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): read llm_provider off the exception with getattr so the type gate stays flat
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>
* feat(proxy): let proxy admins open team member defaults to team admins
* fix(proxy): keep a team admin's never-resets duration on a team's first member budget
* test(proxy): pin the existing-row and stored never-resets cases for member defaults
* feat(proxy): add deployment warning endpoints with instance-wide ignore and snooze
GET /health/deployment_warnings returns the active deployment warnings
(env credential login, license expiry, no Redis on multiple workers,
detailed debug logging) with a severity and ignore state, for proxy admins
and proxy admin viewers. PATCH /health/deployment_warnings/{warning_id}
lets a proxy admin ignore a warning forever or snooze it for up to 30 days,
or restore it. Ignores live in one LiteLLM_UISettings row, apply to every
admin, and are written to the config audit log. Expired snoozes drop out
on read, and LITELLM_DISABLE_NO_REDIS_WARNING is reported as an env var
ignore. /health/readiness/details is unchanged
* fix(proxy): keep readiness Redis short-circuit ahead of the env lookup and harden ignore storage
Readiness details again answers from Redis before reading
LITELLM_DISABLE_NO_REDIS_WARNING, so proxies with Redis and a secret
manager do not fetch it on every poll. Stored ignores require timezone
aware datetimes and are read from the writer before a rewrite
* fix(proxy): keep deployment warning ignores readable in the config audit log
The audit payload keyed ignores by warning id, so the secret matcher
redacted the env_credential_login entry and the audit row lost who
snoozed it and until when. Log a list of id and ignore entries instead
* fix(ui): dedupe blank-question issues and label Decisions questions by key, not position
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): make the Response card header a flex row so title and badges share one line
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(ui): fail when duplicate blank-name issues stop being deduped
* fix(ui): drop the Decisions issue dedupe, which no reachable endpoint needs
* fix(ui): center the Response header and test the Decisions issue labels end to end
The card's border rule set 24px of bottom padding on the Response header, which put its content 8px above center. The header now keeps 8px on both sides. New tests cover the /v1/decisions position label and the score-level warning label for an all-digit key, which mutations of validatePayload left untested
* test(ui): check the Decisions Response header layout in the browser
* test(ui): register the Decisions header spec's model through the API so it runs in CI
The CI UI stack does not read fixtures/config.yml, so the config-only fake-decisions-model never existed there and the spec could not pick it. The spec now creates a uniquely named typesafe model against the mock server, waits until /model_group/info lists it as an evaluation model and /v1/systemone answers, and deletes it afterwards
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(ui): add decisions and classifier providers to the Add Model form
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost): use literal upstream decisions paths
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix: drop duplicate TYPESAFE provider fields entry superseded by main's TypeSafe
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(ui): drop stray blank line in provider_info_helpers test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): type the OSS decisions provider fields test
* fix(decisions): keep Laya and Bespoke env keys on their configured server
Route laya and bespoke Decisions deployments through the same oss_connection
and validate_oss_model rules the pass-through and the classifier router use,
so LAYA_API_KEY and BESPOKE_API_KEY only go to LAYA_API_BASE and BESPOKE_API_BASE,
an api_base with credentials, a query, or a non-HTTP scheme answers 400, and
an unknown checkpoint name answers 400 before any upstream call
* fix(decisions): send the Laya and Bespoke env key to a form-added model on the env server
A deployment added through Add Model always carries an API base, so the
env key only reached deployments with no base. The env key now goes to a
deployment whose base matches LAYA_API_BASE or BESPOKE_API_BASE, an empty
deployment key counts as no key, and the Bespoke placeholder is the name
Ollama serves.
* test(decisions): cover the env-base classifier case in the complexity router test
* fix(decisions): match the env server with or without /v1 and point Ollama users at bespoke/nimble
* fix(decisions): call /v1/systemone once from classifiers and pass-through on a /v1 base
* fix(decisions): strip /v1 from the API base path only, so a host named v1 still works
---------
Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(mcp): separate ID-JAG leg-2 client identity, support public resource clients
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(mcp): format ID-JAG credential changes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(mcp): satisfy lint gates and regenerate API snapshot for ID-JAG resource client
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(mcp): require a confidential ID-JAG resource client, drop none auth method
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(mcp): drop formatting churn from ID-JAG resource client tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: retrigger after flaky test_mcp_tool_search timeout
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: rerun against main after duplicate gemini-4-argon price keys were fixed
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>
* feat(decisions): send images to Cloudflare Clef
OpenAI-format input_image parts and the System One images field now reach Cloudflare clef and clef-flash in its images field, with remote URLs downloaded and inlined first. Providers that cannot take images drop them under drop_params and answer 400 otherwise.
* fix(decisions): follow drop_params for images and use the call timeout for image downloads
* fix(decisions): drop a malformed images entry on its own under drop_params
* fix(decisions): refuse images next to input whatever drop_params says
* fix(decisions): bound clef image fetches, honor drop_params for images, and log caller URLs
Refuse more than 4 images for Cloudflare clef before any download, keep the
caller's timeout as one deadline across image fetch retries, accept images
next to input under drop_params, validate image strings and objects, and pass
the caller's image URLs (not inlined bytes) to logging callbacks.
* fix(decisions): check input_image URLs and clef image sizes
* fix(decisions): accept data URL media type parameters and check clef image types
* fix(decisions): count clef images after dropping unsupported types and flag clef vision
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(ui): show decision models as decisions and list the supported ones in the AI Hub
* fix(ui): gate the decision garden's Add model links and sort the Mode column by its label
The garden shows Add model only for providers the Add Model form can create and only when the session can add models, since a view-only admin's session role reads as Admin. The AI Hub's Mode column sorts by the label it shows, and the Models page parses its tab slug as a string literal
* fix(ui): label the make-public dialog's decision models, clear the prefill after the add, and gate the garden's Add model by the Models page's rule
* fix(ui): drop the dead decisions billing-row filter and the unread team fetch on the AI Hub
The <provider>/decisions/<model> cost map keys never shipped, so the garden filter matched nothing. The AI Hub page fetched /team/list for every visitor and read it for nobody, since only proxy admins reach the add-model check. The org-admin page test now asserts the role string a session carries
* fix(ui): keep self-hosted decision models off the /v1/decisions claim, order the garden one per provider, and show the decisions example on the public hub
* fix(ui): mark decision models this proxy cannot serve yet in the AI Hub garden
* fix(ui): use singular wording in the decision garden header when one model is left
* fix(ui): list gpt-6-luna in the decision garden, send Foundry to its deployment-name docs, and record Models page tab clicks
* fix(ui): say the decisions filter matched no model in decisions mode, and mock usePathname in the Models page integration test
* fix(ui): stop saying deployed decision models still need adding
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Non-admin callers previously received deployment-wide cache activity,
error breakdowns, every key alias on the proxy, and could filter the
aggregates by any other tenant's key alias. All four queries now take
the caller's read scope as bind parameters, which also shrinks the
key-alias and model filter options to the caller's own visibility.
The three-way scope resolution (admin / internal user / fallback) now
lives in resolve_spend_log_read_scope, shared with /spend/tags and
/spend/logs/session/ui instead of being duplicated per endpoint.
* feat(claude-code): emit installationPreference in marketplace.json entries
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(claude-code): satisfy marketplace CI checks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(claude-code): qualify marketplace entry as read only
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(claude-code): suppress typed marketplace assembly warning
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(claude-code): restrict installation_preference to the documented values
Accept only available, auto_install, or required so a typo returns 422 instead of being silently dropped, and cover the PUT full-replace clearing behavior with a test
* fix(claude-code): echo installation_preference on the public skill hub
* refactor(claude-code): read installation_preference with one membership check and cover hand-edited rows
* test(integration): audit installation_preference on the Claude Code marketplace
* test(integration): kill a serving worker in the marketplace chaos cell
* test(integration): give the marketplace worker-kill cell the two-boot timeout
* fix(proxy): keep installationPreference on the MarketplacePluginEntry model
* fix(proxy): refuse self-installing preferences off sha256 archives, accept the camelCase key, and echo the preference on POST and PUT
* fix(claude-code): serve installation_preference only on archive plugins and refuse both key spellings
Claude Code 2.1.75 and older reject a marketplace.json once any plugin carries installationPreference,
and every Claude Code release before archive support rejects a catalog with an archive plugin. Requiring
an archive source for every value, available included, keeps the field off catalogs those clients can read.
A request that sends installation_preference and installationPreference together now gets a 422.
* fix(claude-code): read the preference spelling that carries a value when the other is null
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(proxy): let team admins create keys for team members behind an opt-in setting
A team admin calling POST /key/generate with a team they administer and the
user_id of another member of that team got a 403, and the dashboard only
offered the "Another User" owner option to proxy admins
Add a create_member_keys entry to team_admin_editable_team_fields. When a
proxy admin turns it on, a team admin can create a team key owned by another
member of a team they administer, through the API and through the Create Key
form. It stays off by default, so nothing changes until a proxy admin opts in
With the setting off, the 403 a team admin gets for this call now names the
setting to enable instead of saying they can only create keys for themselves
* fix(ui): order the member owner picker after the team and drop the viewer from it
For a team admin the owner picker depends on the team, so it now sits under the Team field, lists only the other members of that team, and the Team field says why it is required
* fix(proxy): keep keys a team admin creates for a member from carrying more than LLM access
A key authenticates as its owner, so with create_member_keys on a team admin could create a key owned by a proxy admin who sits in their team and act as a proxy admin with it
The member now has to hold the internal_user or internal_user_viewer role, and the key is always an llm_api key, so the team admin never holds a secret that reaches management routes. Asking for a management or read_only key for a member is refused
The unit tests now check the permission decision directly instead of replacing generate_key_helper_fn, and the saved key is checked against a real proxy in the team admin gate matrix
* style(proxy): sort the team admin field permission imports
* refactor(proxy): force the member key type on the request instead of merging a second dict
* test(proxy): drive member key creation through the key generation helper
The pure helpers were covered but the wiring in _common_key_generation_helper was not. Dropping the owner role lookup, the refusal call, or the user_id handed to common_key_access_checks left every unit test green
* fix(proxy): skip the owner role lookup when create_member_keys is off
The owner role was read before the verdict checked the setting, so with the setting off a failing user table read surfaced as a 500 instead of the 403 a team admin got before, and every such request paid an extra writer read
---------
Co-authored-by: Yuneng Jiang <yuneng@berri.ai>
* feat(ui): move the upgrade notice into the notifications bell
The new version notice was a banner in the same stack as deployment
warnings. It now lives in the notifications bell next to Auto Router,
each announcement has its own read state in localStorage keyed per item
and per release, and the bell shows its unread dot while any item is
unread. The upgrade banner is removed from both dashboard shells.
* test(ui): cover singular release wording, legacy dismissals, and the public page bell guard
* fix(proxy-extras): bound telemetry_reports migration lock waits with SET LOCAL lock_timeout
Ports the open fix in #46386 so this branch passes the migration lock_timeout
check that main currently fails.
* Revert "fix(proxy-extras): bound telemetry_reports migration lock waits with SET LOCAL lock_timeout"
This reverts commit b7c1df1a57.
* feat(telemetry): count Admin UI page views and tab clicks through the proxy
* fix(ui): share one telemetry settings save across both tabs so a second toggle waits for the first
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(telemetry): let every dashboard role reach the UI event routes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): fail with the denial detail when a dashboard role cannot reach UI event routes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(telemetry): document POST /telemetry/ui_events with a description and a 200 response schema
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): keep the test-quality reason on the line pytest's checker reads
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(ui): pick the telemetry destination on the Telemetry page and warn when none is chosen
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(ui): send the destination along with groups in the telemetry settings hook test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(ui): add a top-level telemetry switch and gate turning telemetry on behind an enterprise modal
The page can only turn telemetry off. Turning it on from the switch, a group
or a first destination opens a modal: enterprise proxies are told to contact
their LiteLLM enterprise representative, others that telemetry is an
enterprise-only feature. Group switches and the destination stay visible but
disabled while telemetry is off.
---------
Co-authored-by: nate <nate@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(telemetry): keep reports in a local table with a persistent instance id and an admin export route
* feat(telemetry): key deployment hashes from a random secret stored in the proxy DB
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(telemetry): retry a locally stored window under the same id so it is never counted twice
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* docs(telemetry): state the overlap and dedupe contract for paging stored reports
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(ui): regenerate dashboard API types for the telemetry reports paging note
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(telemetry): require an explicit LITELLM_TELEMETRY_DESTINATION or saved destination before recording
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(ui): regenerate dashboard API types for the explicit telemetry destination
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(telemetry): register the attempt logger and create its hash secret only once a sink is built
A proxy with a database that never opts in now carries no telemetry callback
and writes no deployment hash secret to LiteLLM_Config.
---------
Co-authored-by: nate <nate@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): drop deprecation banners from kept features and make the rest permanent
* test(ui): pin deprecation banner copy, dismissal and kept-feature absence
* fix(ui): point deprecation banner at the discussion instead of asking for feedback
* test(ui): drop copy-pinning and removed-banner absence tests
* refactor(ui): build the deprecation banner on the shadcn Alert primitive
* feat(ui): source Home What's new from day 0 support blog posts
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(ui): Home cards read card_title and card_summary from blog tags with provider logo
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>
