A deployment whose model_info carried a non-numeric max_input_tokens or
max_output_tokens (for example "128,000" or an empty string) made the
bare int() in get_configured_token_limits raise inside the per-model
/v1/models loop, so one misconfigured deployment turned the entire
listing into a 500. Coerce each configured limit safely and treat
malformed values as absent, matching the graceful degradation the
listing had before the cost-map switch
split_concatenated_json_objects re-raised JSONDecodeError on genuinely
malformed (non-concatenated) tool-call arguments, which propagated out of
_convert_to_bedrock_tool_call_invoke and turned every replayed Bedrock
conversation into a 500. Catch the decode error, keep whatever complete
objects parsed, log a warning, and let the caller fall back to input={}
so the conversation continues.
Fixes#18667
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(messages): route Azure Anthropic /messages through Rust behind rust:true
Adds an opt-in Rust path for non-streaming Azure Anthropic Messages. A
deployment sets rust: true in litellm_params to route litellm.messages()
and the proxy /v1/messages endpoint through the native Rust bridge; a
missing flag or rust: false keeps the existing Python path, and non-Azure
providers, streaming, an unavailable bridge, or a None result all fall
back to Python. Rust-backed responses carry an x-litellm-rust: true
response header so callers can see which path served the request.
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* test(docs): exclude LITELLM_USE_RUST_MESSAGES rollout flag from env-doc check
Mirrors the existing LITELLM_USE_RUST_OCR entry; the flag is an internal
rollout toggle that is intentionally not in the public environment settings
docs yet.
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* fix(rust_bridge): isolate OCR enable flag and drop dead messages global toggle
use_litellm_rust only mutates the OCR enabled flag when configuring OCR (or
called with no bridge kwargs, preserving the legacy contract), so configuring
only the messages bridge no longer flips OCR state.
Remove the vestigial global enabled/env state from the messages bridge. Routing
is controlled per deployment by rust:true in the shared handler gate, so the
messages module never consulted the global toggle; drop it rather than leave a
no-op switch.
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* refactor(rust/messages): split Anthropic config into its own provider file and type the request/response contract
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* feat(messages): route eligible Azure Anthropic streaming through Rust via buffered fake-stream
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* fix(messages): fold system-role messages for Azure Anthropic and fall back to Python on Rust bridge errors
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* fix(rust_bridge): use Python::attach for amessages after pyo3 bump
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* test(proxy): mock get_configured_token_limits in model_info tests
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* ci: run rust_bridge unit tests in misc shard
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* Revert "ci: run rust_bridge unit tests in misc shard"
This reverts commit c86d861a03.
* test(anthropic): move rust messages bridge tests into misc-shard dir
Co-Authored-By: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Ishaan Jaffer <155045088+ishaan-berri@users.noreply.github.com>
* feat(mcp): add ID-JAG egress auth as a v2 outbound-credentials arm
Adds the oauth2_id_jag MCP egress auth mode (draft-ietf-oauth-identity-assertion-authz-grant,
shipped by Okta as "AI agent token exchange") as a first-class arm of the v2
outbound_credentials resolver rather than a standalone v1 handler.
ID-JAG is a two-leg flow: an RFC 8693 token exchange swaps the caller's id_token for an
ID-JAG assertion at the IdP org authorization server, then an RFC 7523 jwt-bearer grant
presents that assertion to the MCP's resource authorization server for the access token
used to call the upstream. The gateway authenticates to both endpoints with a private-key
JWT client_assertion, falling back to client_secret when no key is configured.
The mode is modeled as IdJagConfig in the AuthConfig discriminated union, with client auth
as a ClientAuth tagged union (private_key_jwt or client_secret) so required fields are
enforced at construction and illegal states are unrepresentable. A new token_endpoint
collaborator performs the authenticated OAuth token-endpoint call and caches the result
with per-key single-flight; the resolver's _id_jag arm runs the two legs and returns an
httpx.Auth or a typed CredError. A missing caller identity token fails closed
(precondition_required), so an ID-JAG server never falls back to a static credential. The
v1->v2 adapter maps oauth2_id_jag servers onto IdJagConfig and the existing live v2 path
resolves them, so no standalone handler, has_id_jag_config flag, or resolve_mcp_auth
precedence branch is needed.
The ID-JAG client_private_key is encrypted at rest alongside client_secret.
* fix(mcp): sort token_endpoint imports to satisfy the I001 budget gate
* fix(mcp): give token_endpoint pyright suppressions reasons for the LIT004 budget
The freshly-merged base ratcheted the LIT004 ceiling down, so the six
unexplained pyright suppressions in token_endpoint.py went over budget.
Annotate each with why the boundary is untyped (litellm http handler and
InMemoryCache are untyped; response.json() is validated by
_TokenEndpointResponse in fetch) so the gate counts them as explained.
* fix(mcp): enforce ID-JAG exchange over caller auth overrides and redact token endpoint from client errors
For oauth2_id_jag servers the v2 resolver mints the upstream assertion from the caller's identity token; a caller-supplied x-mcp-auth / x-mcp-<alias>-authorization override or a conflicting injected Authorization must not disable that exchange and forward an arbitrary bearer, so IdJagConfig now joins authorization_code and token_exchange as a resolver-owned mode that keeps the v2 spec and ignores the override.
The token endpoint error branches previously returned the configured endpoint URL in the client-visible 503 detail. The endpoint now stays in server-side logs and clients get a generic token-exchange failure.
* fix(mcp): bind the ID-JAG token cache to the exchange config and map token endpoint network errors to typed CredErrors
* fix(mcp): fail closed when an oauth2_id_jag server is half-configured instead of deferring to v1 static credentials
* fix(mcp): evict the cached ID-JAG bearer on an upstream 401 so the retry re-exchanges
* fix(mcp): map an unsignable client assertion to a typed misconfigured error instead of an unhandled 500
* fix(mcp): redact credential fields from the server-registry debug dump
* fix(router): enforce context-window pre-call checks for Responses API input
* test(router): cover _count_pre_call_check_tokens across API surfaces
* fix(router): count Responses instructions and skip pre-call token count when no input
* fix(router): forward Responses input into deployment selection for context-window checks
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat: add Straiker guardrail integration
Implements LLM security guardrails via Straiker with prompt and response inspection, multi-mode execution (pre_call, post_call), and configurable blocking or redaction of flagged content across providers, streaming, images, and tool calls.
* fix(guardrails): harden straiker source attribution and error-path consistency
Use the operator-configured source for Straiker application attribution instead of a caller-supplied agent_id metadata value, so a caller cannot spoof which application a detection is attributed to. Make _fail reuse _block so a post_call error raises ModifyResponseException like a deliberate post_call block rather than GuardrailRaisedException, and type the blocking helper as NoReturn so the type checker enforces that execution never falls through the BLOCKED branch. Serialize the webhook payload once and send it as raw content to avoid re-serializing on the size check and on every retry.
* fix(guardrails): read straiker config and metadata from all supported shapes
Handle a dict optional_params in _get_config_value so nested guardrail
settings loaded from YAML or the DB (timeout, unreachable_fallback, and
the rest) are applied instead of silently falling back to defaults;
previously only attribute-style access was supported. Build the webhook
metadata bag from the merged metadata so client tags stored under
litellm_metadata on routes like /v1/messages reach Straiker the same way
identity and application fields already do, and widen the internal-key
skip prefix to user_api so proxy-injected budget values are not
forwarded.
* fix(guardrails): fail safe on straiker interventions without redactions
Block instead of passing content through when Straiker returns
GUARDRAIL_INTERVENED without replacement texts, so a positive
intervention verdict can never silently forward the original flagged
content. Fix the streamed-request detection to read the request body
from proxy_server_request.body, where the proxy stores it, instead of a
top-level body key that is never populated; the previous fallback was
dead, so a streamed response whose stream flag was not lifted to the top
level would have been redacted rather than blocked while buffering
replayed the original chunks.
* revert(guardrails): restore straiker caller agent_id application attribution
Restore the original behavior where a request-scoped agent_id in metadata
sets the Straiker application source, falling back to the configured
source. This is the integration's intended per-application attribution;
litellm already resolves a key-owned agent_id ahead of any caller-supplied
value, so a configured key cannot be spoofed.
* revert(guardrails): restore straiker webhook metadata scoping
Restore the original behavior where the Straiker webhook metadata bag is
built from request-scoped metadata only. Forwarding litellm_metadata was
a scope change to what the integration sends to Straiker; keep the
author's intended scoping.
* fix(guardrails): keep proxy key material out of straiker webhook metadata
Widen the internal-key skip prefix from user_api_key_ to user_api so the
proxy-injected user_api_key hash and user_api_end_user_max_budget are not
copied into the Straiker webhook metadata bag. The narrower prefix missed
the bare user_api_key name, leaking the hashed key to the vendor. Keeps
the request-scoped metadata source unchanged.
---------
Co-authored-by: cs-mehta <chandra@straiker.ai>
The proxy already returns x-litellm-model-id (the deployment id) and x-litellm-model-group (the requested model-group alias), but never surfaces the concrete underlying model that served the request; the router rewrites the response model field to the group alias, so callers had no way to read the actual deployment model like anthropic/claude-haiku-4-5. Expose it as x-litellm-model-name, sourced from the deployment recorded in litellm_params metadata.
Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): source /v1/models token limits from cost map instead of Router.get_model_group_info
Resolves the per-model get_model_group_info fan-out on GET /v1/models
(and /models) that pegged the event loop on wildcard listings (#33636).
create_model_info_response now reads max_input_tokens/max_output_tokens
from litellm.get_model_info (the static cost map) rather than the router,
which aggregated and deepcopied every deployment in a group per listed
model.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): inject model-info lookup into create_model_info_response for deterministic coverage
Inject the cost-map lookup (defaulting to litellm.get_model_info) so the
except and max_output_tokens branches are exercised deterministically and
the token-limit tests no longer hardcode mutable cost-map values.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(proxy): surface custom deployment token limits on /v1/models via cheap index lookup
Add Router.get_configured_token_limits, an O(1) model-name index lookup that
reads a concrete deployment's configured max_input_tokens/max_output_tokens
without triggering pattern matching or deep copies. create_model_info_response
layers this over the cost map so custom deployments absent from the cost map
still surface their limits, and admin-configured limits override cost-map
defaults, while wildcard-expanded names stay on the fast path.
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>
test_get_model_info_reports_realtime_mode resolved gpt-realtime-mini through
litellm.get_model_info, which reads the cost map litellm fetches at import from
raw.githubusercontent.com/BerriAI/litellm/main. The mode=realtime retag from
#33728 is in this repo's json and its bundled backup but has not reached main
yet, so the test failed whenever the fetch succeeded and passed whenever the
runner was rate limited and litellm fell back to the backup, flapping the
Unit Tests: MCP, Secrets, Containers & Misc job on unrelated PRs
Resolve the lookup against the bundled backup instead, the way
tests/test_litellm/test_cost_calculator.py already does: force
LITELLM_LOCAL_MODEL_COST_MAP, rebind litellm.model_cost, and clear the
get_model_info lru cache before asserting so a remote-backed entry cached
earlier in the same worker cannot leak through, then clear it again afterwards
so no locally-backed entry outlives the test
Config.yaml-declared OAuth2 MCP servers using Dynamic Client Registration have no LiteLLM_MCPServerTable row, so the DCR persist path called update_mcp_server, which returns None for a missing row, then update_server(None), which dereferenced .approval_status and raised AttributeError. The exception was swallowed to a warning while /register still returned 200, so the minted client was never stored and every access-token expiry forced a full re-authorization
Persist the acquired DCR client (client_id, client_secret, token_endpoint_auth_method, redirect_uris, encrypted at rest) in a dedicated LiteLLM_MCPServerOAuthClient store keyed by server_id when the server has no row, overlay it onto the in-memory config server so the refresh_token grant can authenticate within the process, and rehydrate it when the registry syncs from the database (which runs after the DB connects, unlike config load) so restarts and other pods pick it up. The store is encrypted at rest and is re-encrypted by the master-key rotation path alongside the server rows, through a shared helper so the two sites cannot diverge. The DB-backed server path is unchanged, and guarding the None return removes the swallowed-crash footgun
Resolves the config.yaml DCR persistence regression introduced in v1.92.0 by #31912
enable_anthropic_prompt_caching and anthropic_prompt_caching_ttl are set as live
litellm attributes on the worker that handles the UI save, exactly like
budget_exceeded_throttle_percentage, but they were missing from
LITELLM_SETTINGS_SAFE_DB_OVERRIDES, so a peer worker's config reload merged the DB
value without applying it to the live attribute and stayed stale.
Add both to the allowlist so they behave like the sibling field, and add
test_general_settings_ui_fields_are_db_overridable so the UI registry and the
override allowlist cannot drift again (the exact omission that caused this), plus
a regression test that the flag flips on a simulated peer-worker reload.
PR #33736 made the shielded streaming cleanup await
proxy_logging_obj._arelease_max_parallel_requests_on_disconnect on the
client-disconnect path. The four streaming cancel and disconnect tests in
test_budget_reservation.py drive the generator with a bare MagicMock as
proxy_logging_obj, so the cleanup crashed with TypeError: object MagicMock
can't be used in 'await' expression, breaking proxy-infra CI on every PR
Give the mocks an AsyncMock for the release method and assert it is awaited
exactly once on each disconnect path, pinning the single-owner slot release
contract that PR #33736 introduced without test coverage
team_pattern_routers retained deleted/replaced deployments, so team users could
keep resolving stale credentials; now set_model_list resets the registry and
deployment removal prunes it. Also consult the team wildcard router before the
global pattern_router in get_deployment_credentials_with_provider so a global
pattern like "openai/*" no longer shadows the team's own entry
Co-authored-by: Cursor <cursoragent@cursor.com>
glm-5p2 (and its fireworks_ai/glm-5p2 alias) carried cache_read_input_token_cost
of 2.6e-07, the GLM 5.1 rate; the entry was seeded from the wrong row. Fireworks'
standard serverless rate for GLM 5.2 is $0.14/1M = 1.4e-07, so every prompt-cache
hit was billed at nearly double the real rate.
Corrects the value in both the canonical map and the bundled backup. The existing
fireworks cost-calculator test now reads the cached rate from the map instead of
hardcoding it, so it tracks the shipped value.
* fix(embeddings): accept encoding_format='float' for vertex_ai/gemini embeddings (#33617)
OpenAI SDKs (and litellm's own client since ~1.84) send
encoding_format='float' by default, but the vertex embedding config only
supports ['dimensions'], so get_optional_params_embeddings raised
UnsupportedParamsError at the provider default value. Any
OpenAI-compatible client talking to a litellm proxy with vertex
embedding models got a 400 unless the operator set proxy-wide
drop_params: true.
Float lists are exactly what the vertex API returns, so the param is a
no-op: pop it before validation. Other values (e.g. 'base64') keep the
existing unsupported-param behavior (dropped with drop_params, raise
otherwise).
Fixes#33173
Co-authored-by: Mihidum Hettiyahandi <55163074+mihidumh@users.noreply.github.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(guardrails): add Singulr guardrail integration for LiteLLM gateway (#31302)
* singulr guardrail support for litellm gateway
* Update litellm/proxy/guardrails/guardrail_hooks/singulr/singulr.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* fix comments
* improvement
* fix: resolve review comments and implement requested improvements
* fix:Guardrail bypass through uninspected messages
* fix:tool text scanning
* fix: Legacy function definitions bypass scanning by adding indirect message scaning
* chore: remove unintended basedpyright budget file
* fix:Response schema bypasses guardrail scanning (response_format.json_schema)
* chore: restore basedpyright-code-budget.json and update lint baselines
Restores the file deleted in c698b88686 to match upstream litellm_internal_staging.
Regenerates basedpyright and ruff-strict budget baselines via make lint-budget-update.
* fix: scan system messages as indirect prompt injection in Singulr guardrail
* chore: restore lint budget files to upstream baseline
* fix: resolve ruff UP006 and I001 violations in singulr guardrail
* Update litellm/proxy/guardrails/guardrail_hooks/singulr/singulr.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* resolve review comments on Singulr guardrail
* fix: scan tool call results as indirect prompt injection in Singulr guardrail
* Apply suggestion from @greptile-apps[bot]
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* minor
* formating fix
* refactor: shift extraction logic to singulr side
* refactor:keep precall hook only
* fix:formatting
* fix:linting
* improve config description
* Trigger CI
* fix
* fix:field description
* fix:errors due to change in field names
* style: apply ruff line-wrap formatting to singulr guardrail
* fix:exception
* fix:formatting
* fix playground
* improved
* Update litellm/proxy/guardrails/guardrail_hooks/singulr/singulr.py
Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com>
* Update litellm/proxy/guardrails/guardrail_hooks/singulr/singulr.py
Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com>
* fix
* fix ci issues
* remove uv.lock from pr
* fix
* fix:resolved comments
* chore: trigger CI
* remove uv.lock
* fix
* fix linting
* fix linting
* fix linting
* remove doc strings
* remove test fixes
* chore: retrigger CI
* change in singulr api contract
* remove some ut
* send litellm call_id to singulr
---------
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: aniket-kardile <aniket.kardile@singulr.ai>
Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com>
* Fix non-conformant UUIDv7 generation in native Opik integration (#31294)
create_uuid7() encoded the timestamp in units of 16 seconds instead of
milliseconds, so the top 48 bits came out ~4096x the real unix-ms. Opik's
backend validates the embedded UUIDv7 timestamp on ingestion (OPIK-7067);
the bad encoding decoded to ~year 2201 and every trace/span batch was
rejected with HTTP 400.
Rewrite create_uuid7() to be RFC 9562 conformant (top 48 bits = unix-ms),
using the standard library only so no new dependency is added. Add unit
tests covering UUIDv7 validity and millisecond timestamp encoding.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(proxy): expose uvicorn concurrency limit (#33077)
Expose uvicorn's limit_concurrency as a --limit_concurrency CLI flag and
LIMIT_CONCURRENCY environment variable. Uvicorn counts both active tasks and
accepted connections and returns HTTP 503 once the configured limit is reached.
Reject non-positive limits at CLI parse time and only add the setting to the
uvicorn startup arguments. Because idle connections also consume capacity,
deployments should use upstream connection/header timeouts and per-client
connection limits.
* test: reorder test_utils tail to keep the daily merge conflict-free (#33788)
The daily OSS branch and litellm_internal_staging each appended an
independent test block at the very end of tests/test_litellm/test_utils.py,
so merging the two collides on that shared end-of-file position even though
the additions are unrelated (this branch adds the vertex embedding
encoding-format tests; staging adds the per-model prompt-cache-minimum
tests). Moving this branch's new TestVertexEmbeddingEncodingFormat class
above test_gemini_image_models_do_not_support_reasoning, which both branches
share, gives the two additions different anchors, so git applies both
without a conflict and without pulling staging into this branch. Pure
reorder; no test bodies change
---------
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Mihidum Hettiyahandi <55163074+mihidumh@users.noreply.github.com>
Co-authored-by: madan-singulr <150280287+madan-singulr@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: aniket-kardile <aniket.kardile@singulr.ai>
Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com>
Co-authored-by: Aliaksandr Kuzmik <98702584+alexkuzmik@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Salva Madrid <50212436+salvamadrid@users.noreply.github.com>
Outcome keys in the tools/list _meta, the spend-log outcome and count maps, and the REST error
messages now all use get_server_prefix (alias, or the short prefix when that mode is enabled), the
same naming the caller already sees on tool names. Keying them by canonical server_name let an
authenticated caller enumerate internal server names and their health or auth state that the alias
and short-prefix schemes deliberately hide (Veria finding). One helper decides the key for every
surface; exception messages reaching the multi-server REST error list are mapped to their fault tag
with the display prefix instead of relaying exception text carrying canonical names. Server-side
logs keep the real names
* fix(proxy): bill partial streamed spend when the client disconnects mid-stream
* fix(router): guard FallbackStreamWrapper chunks alias for non-CSW streams
* fix(proxy): await disconnect billing dispatch instead of unrooted create_task
* fix(proxy): make disconnect slot release single-owner to avoid double release
* fix(proxy): use union syntax for disconnect cleanup params (UP045 budget)
Conflict in _list_mcp_tools: staging (#33612) moved toolset-grant expansion into the shared
permission primitives and removed the _merge_toolset_permissions call; resolution applies that
removal to this branch's AggregateToolListing structure
Rather than mixing the flag and its ttl into the generic General settings table
(which also surfaced the confusing Not Set / In Config / In DB provenance badges),
give prompt caching a dedicated tab with a purpose-built toggle and ttl dropdown.
Each registry field gains an optional tab, surfaced as ConfigList.field_tab, so
the General tab renders the ungrouped fields and the caching fields render on
their own tab. The update, persist and reset endpoints are unchanged.
Register enable_anthropic_prompt_caching and anthropic_prompt_caching_ttl on the
General Settings table so caching can be turned on without hand-writing config.
The registry could not express either field: validation was hardcoded to a float in
(0, 1], reset set every field to None (not a bool for a boolean flag), and the listing
reported any non-None value as 'In Config', which a False default would always trip.
Validation now dispatches on the declared type and reset restores each field's own
default. ConfigList carries field_options so the table can render a Select for enums
instead of no editor at all.
The gpt-realtime family (OpenAI and Azure) only serves /v1/realtime and is rejected by /v1/chat/completions with "This is not a chat model", but the cost map tagged them mode=chat. Retag them mode=realtime (a value already used by gemini-live and handled by the health-check realtime handler) and add realtime to the ModelInfoBase mode literal.
Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Two review findings, both a chat-vs-messages divergence.
transform_mcp_tool_to_anthropic_tool sent the MCP inputSchema to Anthropic almost
as-is, while the chat path (_map_tool_helper) coerces the type to object, inlines
legacy definitions with unpack_legacy_defs, and allow-lists keys to
AnthropicInputSchema. So a tool whose schema carried $schema, legacy definitions
or oneOf worked on /chat/completions and 400d on /v1/messages; a clean-schema
server hid it. Both paths now run the same sanitize_input_schema_for_anthropic,
extracted next to unpack_legacy_defs so they cannot drift again, and the chat
path is refactored onto it rather than keeping its own copy.
buildMcpToolBlocks percent-encoded the server and toolset names inside
litellm_proxy/mcp/... urls, but the gateway resolves the name with a raw
server_url.split("/")[-1] and never url-decodes, so a name with a space failed
lookup. The already-working chat path does not encode; the shared builder now
matches it.
Tests pin both: reverting the transform to the unfiltered schema fails, and
re-adding encodeURIComponent fails the builder test.
* feat(complexity-router): user-triggered escalation keywords
Add an escalation_keywords config option to the complexity router so a user
can force a bump to the next-higher complexity tier by including a phrase in
their message (a stronger model, but not one they get to choose). Defaults to
['LITELLM ESCALATE'] when unset, case-sensitive so it only fires on the
deliberate shouted form; admins can override the list or set [] to disable.
Escalation applies across every routing path: heuristic/LLM classification,
literal and semantic keyword_tier_rules overrides, adaptive routing, and
session affinity (where it bumps relative to the pinned model and persists the
higher tier for the rest of the session). Capped at the highest configured
tier and skips unconfigured intermediate tiers.
Expose it in the Auto-Router v2 UI as an Escalation Keywords field wired into
the complexity_router_config payload.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(complexity-router): validate escalation keywords and pin at tier ceiling
Strip blank/whitespace escalation keywords so an empty phrase can't match every message and escalate all traffic. Keep the exact pinned model when a session escalates at the highest configured tier instead of randomly hopping to a peer in a multi-model pool.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Append-append conflict at the end of test_mcp_server.py between this branch's aggregate-outcome
tests and the mode-aware preemptive-401 tests from staging; both kept
* fix(proxy): stop treating upstream model body field as a LiteLLM model on auth-enforced pass-through routes
An auth: true user-defined pass-through endpoint runs full virtual-key auth, and get_model_from_request unconditionally extracted the request body model field, so key/team/user/project model allowlist checks rejected requests whose model only exists upstream (key_model_access_denied), even when the key was explicitly granted the route via allowed_passthrough_routes.
The pass-through route registry moves to a leaf module (route_registry.py) that the auth layer can import without re-entering the pass_through_endpoints -> user_api_key_auth -> auth_utils import cycle. get_model_from_request now returns None for routes registered as user-defined pass-through endpoints (exact and subpath), which skips model allowlist and per-model budget enforcement on those routes while key auth, allowed_passthrough_routes, and spend/budget checks stay intact. Built-in provider passthrough routes (/vertex_ai, /gemini, ...) keep model enforcement.
Resolves LIT-4299
* fix(proxy): key pass-through model-access skip on the dispatched endpoint, not the request path
Addresses a model-authorization bypass: the first version decided whether to skip
model-allowlist extraction by matching the request path against the pass-through
route registry. That ignored the HTTP method and, more importantly, whether the
request was actually dispatched to a pass-through handler. A custom pass-through
whose path collides with a built-in route (e.g. /v1/chat/completions, or an
include_subpath prefix of one) still writes a registry entry even though FastAPI
serves the built-in handler, so a normal request to that route had its model checks
skipped and could reach a model outside the key/team/user/project allowlist.
The skip is now keyed off the FastAPI-resolved endpoint. create_pass_through_route
tags its handler with LITELLM_PASS_THROUGH_ENDPOINT_MARKER, and get_model_from_request
returns None only when request.scope["endpoint"] carries that marker. Because routing
runs before auth dependencies, this reflects the handler that actually serves the
request: on a collision the built-in handler is dispatched and carries no marker, so
model enforcement stays on. This also removes the need for the separate route_registry
module, so that extraction is reverted.
Regression tests cover a pass-through-dispatched request (model suppressed), a
built-in-dispatched request on the same path (model still enforced), and the no-request
budget path.
Resolves LIT-4299
* fix(proxy): enforce max_parallel_requests as a per-slot concurrency gauge
The v3 rate limiter tracked max_parallel_requests with the same
sliding-window machinery as RPM/TPM. A concurrency gauge cannot live on a
windowed counter: every window roll reset the counter to 1 while requests
were still in flight, the completion decrements for those forgotten
requests then drove the counter negative, and rejected requests left
stranded increments that nothing released. Under sustained load a key with
max_parallel_requests=5 let backend concurrency climb to the full client
concurrency (observed 60 on a live proxy) while the proxy kept returning
429s for everyone else
Replace the windowed counter with a per-slot registry (Redis sorted set of
slot ids scored by acquire time, with an asyncio-locked in-memory fallback):
admission atomically prunes expired slots and registers a new slot id only
when in_flight + 1 <= limit, so rejected requests never occupy a slot;
success, failure, and client-disconnect paths release exactly the slot id
this request acquired (stashed in the request metadata channels), so a
release without a matching acquire or a double-fired callback can never
free another request's slot; and a slot leaked by a crashed worker is
pruned individually after its TTL even under continuous traffic
Resolves LIT-4259
Fixes#16011
* fix(proxy): release every acquired gauge and respect mirrored counts in the in-memory fallback
Address review findings on the slot-registry gauge: the acquisition stash
now carries the gauge counter keys alongside the slot id, so the release
paths free the slot from every gauge it was registered under instead of
hardcoding the api_key scope, and the disconnect release keys off the
stashed acquisition instead of the key object's current
max_parallel_requests configuration (which can change mid-request). The
in-memory fallback now treats a cached integer (the count mirrored from
the last successful Redis script call) as real occupancy, carrying it
forward as a floored counter during a Redis outage instead of restarting
from an empty registry
* fix(proxy): release the parallel slot on proxy-level rejections
async_post_call_failure_hook is the only callback that fires when a
downstream hook (guardrail, budget check) rejects a request after the rate
limiter's pre-call hook acquired a slot; async_log_failure_event is a
completion-level callback and never runs for proxy-side rejections.
Release the stashed acquisition at the top of the hook, before the TPM
reservation guard, so those slots do not linger for the full slot TTL and
wedge the key at its limit under moderate rejection rates. Clearing the
acquisition marker keeps the release idempotent when a later failure
callback runs in the same flow
* test(proxy): cover success release, read-only count, Redis release mirror, and TPM rejection release
Four behaviors of the slot-registry gauge had no direct test: a successful
completion releasing exactly its acquired slot, read_only callers counting
in-flight slots through the count script (and degrading to the local
mirror when the script fails) without acquiring, the Redis release script
mirroring returned counts into the local cache, and the TPM reservation
rejection releasing the already-acquired slot before raising
* style(proxy): use builtin generics and union syntax in new rate limiter annotations
The slot-gauge code added Tuple/List/Dict and Optional[...] annotations, pushing
the UP006 and UP045 strict-rule totals past their ceilings in ruff-strict-budget.json.
Convert only the annotations this branch introduces to builtin generics and PEP 604
unions, leaving the rest of the module untouched.
* fix(router): tag-aware pre-routing strategy selection for shared model_name
Complexity/auto/adaptive/quality router registries were keyed by model_name
alone, so a second deployment sharing a model_name but carrying different tags
was rejected and every request used the first config. This made tag-based
routing to distinct provider configs behind one alias impossible, surfacing as
401 'Not allowed to access model due to tags configuration' for the second tag.
Each registry now holds a list of tag-scoped strategies and async_pre_routing_hook
selects the entry whose tags match the request before classification, falling
back to a default-tagged then first-registered entry. A repeat of the same
(model_name, tags) pair is still rejected.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): cover tag-scoped pre-routing strategy registry helpers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: re-trigger CI
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
