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…tem (BerriAI#29817) System-only chat requests mapped the system message to instructions and left input=[], which OpenAI's Responses API rejects (it also rejects input=""). When no other messages are present, carry the system message as a role:"system" input item (single copy, correct role) instead of leaving input empty. Mirrors the existing handling of non-string system content. Fixes Open WebUI new-conversation failures on mode:responses Codex models. Co-authored-by: Cursor <cursoragent@cursor.com>
…olSpec (BerriAI#29814) * feat(bedrock): forward strict and additionalProperties to Converse toolSpec Bedrock Converse supports strict in toolSpec since 2026-02, but _bedrock_tools_pt only whitelisted type/properties/required/name/description, so strict: true was silently dropped and Claude-on-Bedrock ignored enum constraints that GPT and direct-Anthropic honored. Forward strict from the OpenAI function and additionalProperties from the schema (Bedrock requires the latter alongside strict), passing each only when present. https://claude.ai/code/session_01WQjWd8NfUB3vxERwudbHkv * fix(bedrock): only forward strict tool schemas to Claude on Converse Nova, Llama and GPT-OSS on Bedrock reject the strict field (BedrockException 'This model doesn't support the strict field'), and the GPT-OSS request-body test asserts strict/additionalProperties are stripped. Forwarding them to every model broke the llm_translation suite, so gate the forwarding on the anthropic base model since only Claude honours strict tool schemas on Bedrock.
…per-user env vars (BerriAI#29856) * fix(mcp): flag missing per-user env vars on the card for every accessible server The dashboard MCP card grid lists servers via the registry-backed manager (get_all_mcp_servers_unfiltered for admins in view_all mode, the allowed-context aggregation otherwise), but the per-user env-var status endpoint that drives the red "user fields missing" highlight resolved servers through the much narrower get_all_mcp_servers_for_user, which only returns servers explicitly granted on the calling key. An admin's dashboard session key carries no per-server MCP grant, so the status feed came back empty and the card never turned red even when the logged-in user had not filled in their required variables. Both surfaces now share a single _resolve_accessible_mcp_servers helper, so the status feed is computed over exactly the cards the user sees. The helper returns servers unredacted; the status endpoint needs the raw env_vars and still only ever reports is_set booleans, never the stored secret values. * test(mcp): drop dead get_all_mcp_servers_for_user patch from view_all regression test The bulk status endpoint resolves servers through _resolve_accessible_mcp_servers now, so the old get_all_mcp_servers_for_user patch in the admin view_all regression test is never hit. Removing it keeps the test honest about which code path it exercises.
* feat(ui): add budget duration to edit team member form Editing a team member created a member budget with no duration, so the budget never reset. This threads a budget reset period through the edit flow end to end and reuses the shared duration dropdown so the options stay in sync with the rest of the UI. Resolves LIT-2651 * fix(proxy): validate member budget_duration and persist clears Reject budget_duration values that can't be parsed, are non-positive, or overflow date math before any write, so a bad value can't be persisted and later crash the budget reset job. Clearing the budget duration in the edit-member form now sends null and clears the column end to end, so the dropdown's clear control reflects a real change instead of being a no-op * chore(ui): regenerate schema.d.ts for member budget_duration Adds budget_duration to TeamMemberUpdateRequest/Response in the generated dashboard types so the Check UI API Types Sync gate passes
The Workflow Runs page rendered its table at roughly a quarter of the available width. Its root container is a flex child of the dashboard content row but set only padding, min-height and background, so with no width it shrank to the table's natural content size. Sibling pages (logs, memory) fill the area with a full-width root; mirror that by setting width 100% on the container. Fixes LIT-3636
…odel, and llm_provider fields (BerriAI#27687) * feat(exceptions): add RateLimitErrorCategory + headers/detail fields on RateLimitError LiteLLM previously surfaced rate-limit conditions through several unrelated error classes (RateLimitError, FastAPI HTTPException(429), BaseLLMException). This commit adds the data model needed to consolidate them under a single class: * RateLimitErrorCategory enum exposing four categorical values (vendor_rate_limit, vendor_batch_rate_limit, litellm_rate_limit, litellm_batch_rate_limit) so callers can switch on the rate-limit source. * New optional fields on RateLimitError: - category (defaults to vendor_rate_limit, preserving today's behavior for every existing call site in exception_mapping_utils); - headers (preserves retry-after / rate_limit_type / reset_at across the proxy boundary instead of dropping them on the floor); - detail (mirrors FastAPI HTTPException.detail so the same instance can be serialized through both paths). litellm.RateLimitErrorCategory is re-exported at the package root to match the existing exception-export pattern. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(proxy): add ProxyRateLimitError unifying RateLimitError + HTTPException Adds a single proxy-side error class that subclasses BOTH litellm.exceptions.RateLimitError AND fastapi.HTTPException via cooperative multiple inheritance. Why both bases: * Subclassing RateLimitError lets user code catch every rate-limit source with one 'except RateLimitError' and switch on the new .category field. * Subclassing HTTPException keeps every existing FastAPI plumbing path (the isinstance(e, HTTPException) branches in proxy_server.py route handlers, FastAPI's own dispatcher, and tests asserting pytest.raises(HTTPException)) working without modification, and preserves retry-after / rate_limit_type / reset_at headers on the wire. The class declaration order is (HTTPException, RateLimitError) so the MRO puts HTTPException's no-super-call __init__ ahead of openai's cooperative __init__ chain — preventing openai.APIError.super().__init__(message) from landing in HTTPException.__init__(status_code=message). LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * refactor(proxy/hooks): raise ProxyRateLimitError from budget + iteration limiters Replaces three bare HTTPException(status_code=429, ...) call sites with ProxyRateLimitError, which is both a RateLimitError (catchable by category) and an HTTPException (preserves existing FastAPI serialization). Drops the now-unused HTTPException import in the iteration / per-session limiters. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * refactor(proxy/hooks): raise ProxyRateLimitError from parallel-request limiters Replaces HTTPException(status_code=429, ...) call sites in the v1 and v3 parallel-request limiters (key/team/user/model/customer rate limits) with ProxyRateLimitError. Updates the raise_rate_limit_error helper's return type annotation accordingly. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * refactor(proxy/hooks): raise ProxyRateLimitError from dynamic rate limiters Replaces HTTPException(status_code=429, ...) call sites in the v1 and v3 dynamic rate limiters (project-level TPM/RPM allocation, model-saturation checks, priority-based limits, fail-closed guards) with ProxyRateLimitError. The v3 limiter still imports HTTPException for an unrelated bare 'except HTTPException:' branch. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * refactor(proxy/hooks): raise ProxyRateLimitError from batch rate limiter Replaces HTTPException(status_code=429, ...) in batch_rate_limiter._raise_rate_limit_error with ProxyRateLimitError tagged as RateLimitErrorCategory.LITELLM_BATCH_RATE_LIMIT so users can distinguish batch-level throttling (which counts requests/tokens across an uploaded batch input file before submission) from the generic key/team/user RPM/TPM limiter. The HTTPException import is retained because the same module raises HTTPException for unrelated 403/IO error paths. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(rate-limit): pin down unified rate-limit error contract Adds a dedicated test module covering the new RateLimitErrorCategory enum, RateLimitError.category default + override behavior, ProxyRateLimitError's dual nature (RateLimitError + HTTPException), and a parametrized regression guard that asserts every proxy hook module imports the unified class. The regression guard catches the failure mode the refactor is designed to prevent: someone re-introducing a bare HTTPException(status_code=429, ...) in one of the hook modules instead of going through ProxyRateLimitError. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(logging): expose rate-limit category via StandardLoggingPayload Adds an optional 'error_rate_limit_category' field to StandardLoggingPayloadErrorInformation, populated from the unified RateLimitError.category attribute (introduced in the previous commits on this branch). Why: the .category attribute is reachable off the raw exception today via getattr(e, 'category', None), but the structured contract that downstream custom callbacks / loggers / spend log writers consume is the StandardLoggingPayload. Without this field, a user building custom rate-limit metrics on top of callback data has to special-case the raw exception object — which defeats the purpose of the StandardLoggingPayload abstraction. The field is None for non-rate-limit exceptions (so consumers can read it unconditionally without isinstance checks) and is one of the RateLimitErrorCategory string values otherwise. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(rate-limit): assert StandardLoggingPayload carries the category Five tests covering: vendor default, explicit litellm_rate_limit and litellm_batch_rate_limit values, None for non-rate-limit exceptions, and None when no exception is provided. Pins down the contract that custom callbacks can read 'error_information.error_rate_limit_category' off the StandardLoggingPayload to drive custom rate-limit metrics without ever reaching for the raw exception. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(types): silence mypy [misc] on intentional dual-base attr overlap mypy emits two [misc] errors on the ProxyRateLimitError class line because its two bases declare overlapping attributes with related-but-not-identical annotations: * status_code: int on starlette HTTPException vs. Literal[429] on openai's RateLimitError (every openai status-error subclass narrows it the same way and silences pyright with the same convention). * headers: Mapping[str, str] | None on HTTPException vs. our Optional[ Dict[str, str]] (the proxy hooks always carry a stringified dict). Both narrowings are intentional and enforced at construction time. Add a type: ignore[misc] with an inline explanation rather than relax the annotations on the parent or change the wire-format guarantees. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(rate-limit): add direct hook-invocation tests to lift patch coverage Adds six end-to-end tests that drive each refactored hook past its limit and assert the unified ProxyRateLimitError is raised with the correct category and dual-base shape. Complements the import-shape-only parametrized guard above by actually executing the new 'raise ProxyRateLimitError(...)' lines so codecov's patch coverage sees them as hit. Hooks covered (one test each): * parallel_request_limiter v1 — direct call to raise_rate_limit_error() * parallel_request_limiter v3 — direct call to _handle_rate_limit_error with a fabricated OVER_LIMIT response * max_iterations_limiter — full async_pre_call_hook with mocked agent registry, second call exceeds budget=1 * max_budget_limiter — async_pre_call_hook with mocked get_current_spend * dynamic_rate_limiter v1 — async_pre_call_hook with mocked check_available_usage forcing available_tpm == 0 * batch_rate_limiter — direct _raise_rate_limit_error call, asserts category is the batch-specific LITELLM_BATCH_RATE_LIMIT (not the generic LITELLM_RATE_LIMIT) LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix: guard rate_limit_category extraction with isinstance check * test(rate-limit): cover remaining hook raise sites for codecov Adds five more direct hook-invocation tests so every PR-touched line in the proxy hooks is exercised by tests in tests/test_litellm/, which codecov measures: * parallel_request_limiter v1 — check_key_in_limits inline raise (the second raise site, separate from the raise_rate_limit_error helper covered earlier) * dynamic_rate_limiter v1 — RPM raise branch (TPM branch was already covered) * dynamic_rate_limiter v3 — parametrized over all three raise sites: model_saturation_check, priority_model, and the fail-closed fallback for an unrecognized descriptor_key * max_budget_per_session_limiter — full async_pre_call_hook with a mocked agent registry and over-budget cached spend All 42 tests in test_rate_limit_error_unification.py now pass and together exercise every changed import + raise line across the eight refactored proxy hooks. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix: use computed error_message in ProxyRateLimitError detail * fix(parallel-request-limiter): drop None from detail; annotate raise_rate_limit_error as NoReturn The v1 ' raise_rate_limit_error' helper built an unused 'error_message' variable and then assembled the actual ' detail' via an f-string that interpolated 'additional_details' verbatim — producing 'Max parallel request limit reached None' when invoked without arguments (flagged by code review). Fix the helper to: - use the constructed 'error_message' as the detail - annotate the helper as NoReturn since it always raises - drop the redundant 'raise'/'return' at the two call sites Add two regression tests covering both the with- and without- additional_details paths. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(proxy/hooks): drop literal 'None' from raise_rate_limit_error detail The v1 parallel_request_limiter's raise_rate_limit_error helper has a long-standing bug: it computes a None-guarded 'error_message' string but then ignores it and emits an f-string that interpolates the raw 'additional_details' arg. Callers that pass no argument get 'Max parallel request limit reached None' as the user-facing detail. This commit: * wires error_message into the detail kwarg so the None-guard actually applies and operators see a clean message; * changes the return-type annotation from ProxyRateLimitError to NoReturn (the function always raises) so type-checkers know callers after this invocation are unreachable. Greptile P1 + P2 review feedback on PR BerriAI#27687. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(types): demote TypedDict floating string to a # comment A string literal placed after a field declaration in a TypedDict body is not a per-field docstring — it's an orphaned string expression Python discards. Tools like mypy / pyright that inspect TypedDict fields won't surface that text either. Move the documentation for error_rate_limit_category to a real comment so the intent is visible to readers and type-checker tooling without the misleading docstring framing. Greptile P2 review feedback on PR BerriAI#27687. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * security(exceptions): do not auto-copy vendor response headers to e.headers A vendor 429 response can set arbitrary headers (Set-Cookie, CORS overrides, …). Previously, when RateLimitError was constructed with only a 'response=' (no explicit 'headers=' kwarg), self.headers fell back to a copy of response.headers. If a downstream proxy serializer ever forwarded e.headers to the client, a malicious upstream could inject browser-interpreted headers for the proxy origin. Drop the fallback. Only headers passed explicitly via the headers= kwarg make it onto self.headers (proxy hooks pass retry-after etc. — they control what's surfaced). Vendor response headers stay reachable on e.response.headers for callers that explicitly want them. Today's proxy_server.py route handlers don't actually forward e.headers on the wire (they construct ProxyException without passing headers), so no current behavior changes — this is a defensive narrowing so the fallback can never be turned into a vector when someone wires e.headers through later. Veria-AI security review feedback on PR BerriAI#27687. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(rate-limit): regression guards for review-pass fixes Pins down the three review-pass fixes: * test_parallel_request_limiter_v1_helper_no_additional_details — calls raise_rate_limit_error() with no args and asserts the detail does NOT contain the literal string 'None'. Pre-fix, callers got 'Max parallel request limit reached None'. * test_rate_limit_error_does_not_auto_copy_response_headers — passes a vendor httpx.Response with a Set-Cookie header to RateLimitError WITHOUT an explicit headers= kwarg, asserts self.headers stays None (no leak), then re-checks that an explicit headers= kwarg DOES populate self.headers. Vendor headers remain reachable on e.response.headers for callers that explicitly want them. * The existing v1-helper test now also asserts the additional_details string makes it through to the detail. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(rate-limit): add orthogonal RateLimitType (requests/tokens/concurrent_requests/budget/max_iterations) trho's last ask in the LIT-2968 thread: distinguish rate-limit failures by the dimension that was exceeded, not just by who rate-limited (vendor vs. litellm). Adds: - RateLimitType str-enum exposed at `litellm.RateLimitType` with values requests / tokens / concurrent_requests / budget / max_iterations. - `rate_limit_type` kwarg on litellm.RateLimitError + ProxyRateLimitError; None default so existing callers (vendor-429 path in exception_mapping_utils) remain a no-op. - StandardLoggingPayloadErrorInformation.error_rate_limit_type so custom callbacks can split rate-limit failures by cause without parsing free-text error messages. Mirror to error_rate_limit_category extraction in get_error_information(); single isinstance(RateLimitError) check covers both. - map_v3_rate_limit_type() helper to collapse the v3 limiter's internal labels ("requests", "tokens", "max_parallel_requests") onto the public enum so the v3 limiter and dynamic_rate_limiter_v3 share one mapping. Defensive None on unknown values rather than silently picking a wrong dimension. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(proxy/hooks): wire rate_limit_type onto every limiter raise site Each refactored proxy hook now populates rate_limit_type with the dimension that actually tripped the limit, so downstream consumers (custom callbacks, prometheus exporters via the StandardLoggingPayload) can split key/team/user rate-limit failures by cause: - parallel_request_limiter (v1): detect dimension from current vs. limit in the post-cache branch (concurrent_requests > tokens > requests, matches the boolean condition order). Base case (current is None, one limit set to 0) picks the most-specific zero. raise_rate_limit_error() helper accepts an explicit rate_limit_type kwarg with CONCURRENT_REQUESTS default (matches every existing internal call site, including the global-limit branch). - parallel_request_limiter (v3): forward status["rate_limit_type"] through map_v3_rate_limit_type() so "max_parallel_requests" → CONCURRENT_REQUESTS for the public field while the raw v3 jargon stays on the HTTP header for wire-format backward compat. - dynamic_rate_limiter (v1): TPM-zero → TOKENS, RPM-zero → REQUESTS. Pass data["model"] through so callbacks see the model that hit the limit (addresses the secondary "provider missing" complaint in the original Slack thread, partially — the model is what dashboards typically split on). - dynamic_rate_limiter (v3): forward status["rate_limit_type"] via map_v3_rate_limit_type() at every raise site (model_saturation_check, priority_model, fail-closed unknown-descriptor guard). Also pass model. - batch_rate_limiter: limit_type is hard-typed "requests"|"tokens" — map directly without going through the helper's None branch. - max_budget_limiter, max_budget_per_session_limiter: BUDGET. - max_iterations_limiter: MAX_ITERATIONS. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(rate-limit): cover RateLimitType enum, hook wiring, and StandardLoggingPayload propagation 27 new tests across five new test classes: - TestRateLimitType: enum exposed at litellm.RateLimitType, all five values defined, RateLimitError default is None (vendor 429 path makes no claim about which dimension), accepts both string and enum forms with str-coercion guarantee for downstream JSON serializers. - TestProxyRateLimitErrorType: ProxyRateLimitError default is None, accepts string or enum, doesn't break existing callers that pass nothing. - TestMapV3RateLimitType: pins each v3-internal → public-enum mapping (tokens, requests, max_parallel_requests → concurrent_requests, unknown → None) so a future v3 refactor can't silently swap dimensions. - TestStandardLoggingPayloadCarriesType: the new error_rate_limit_type field reaches the structured payload for both ProxyRateLimitError and plain RateLimitError, is None when unspecified, and is None for non-rate-limit exceptions (symmetric with error_rate_limit_category). - TestProxyHooksWireTypeCorrectly: drives the actual raise sites in the v1 parallel_request_limiter helper, the v3 _handle_rate_limit_error (both "tokens" and "max_parallel_requests" paths), and the batch limiter (both tokens and requests paths) — coverage tools see the new rate_limit_type= kwargs as exercised, not just the import shape. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(rate-limit): cover _coerce_message branches and v1 dimension detection Drives the patch coverage on the new orthogonal RateLimitType wiring up to (or close to) 100% on the touched files. ProxyRateLimitError._coerce_message — was 22% covered, now 100%: * nested {error: {message}} dict * nested {message: {message}} dict (alt key) * dict without 'error'/'message' keys → JSON dump fallback * non-JSON-serializable dict value → str() fallback * non-string non-mapping detail (int) → str() coercion v1 parallel_request_limiter dimension detection — was 0% covered, now exercised across 6 parametrized cases: * check_key_in_limits else-branch: current at concurrent / TPM / RPM cap → asserts rate_limit_type is concurrent_requests / tokens / requests. * check_key_in_limits base case (current is None): max_parallel_requests / tpm_limit / rpm_limit set to 0 → asserts the most-specific zero attribution wins per the helper's order. LIT-2968 Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(proxy/hooks): add ProxyHTTPRateLimitError + provider resolver Introduces a small helper layer used by every proxy-side rate-limit hook so that the 429 they raise carries a populated llm_provider / model — instead of an empty exception.llm_provider that downstream loggers (Prometheus failure metric, observability callbacks) read as 'no provider attribution'. ProxyHTTPRateLimitError inherits from both fastapi.HTTPException (so the proxy server still renders it as a 429) and litellm.exceptions.RateLimitError (so isinstance checks and PrometheusLogger._get_exception_class_name pick up llm_provider). We deliberately don't call RateLimitError.__init__ — it constructs an httpx.Response we don't need and would just add failure surface; attribute parity is what downstream consumers care about. resolve_llm_provider_for_rate_limit() wraps litellm.get_llm_provider defensively. Internal limiter hooks fire from async_pre_call_hook — well before get_llm_provider runs anywhere else in the request lifecycle — so we have to call it ourselves at raise time. If the model is missing or unparseable (alias, router-only model) we fall back to llm_provider='litellm_proxy' rather than letting a second exception leak out and break the request path. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(proxy/hooks): populate llm_provider on parallel-request 429s Both v1 and v3 parallel-request limiters fired bare HTTPException(429) from inside async_pre_call_hook. The downstream Prometheus failure metric reads exception.llm_provider via _get_exception_class_name — the empty value showed up as exception_class='HTTPException' and left model_id='None' on the time series. Threads requested_model through every raise site in: * parallel_request_limiter.py: - check_key_in_limits (the per-key/per-model/per-user/per-team/ per-customer over-limit path) - raise_rate_limit_error (zero-limit + global_max_parallel_requests paths) — now takes an optional requested_model kwarg * parallel_request_limiter_v3.py: - _handle_rate_limit_error (the OVER_LIMIT translator), called from both the should_rate_limit pre-check and the TPM reservation path Resolved via resolve_llm_provider_for_rate_limit so unknown / missing models silently fall back to llm_provider='litellm_proxy' instead of breaking the request path with a second exception. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(proxy/hooks): populate llm_provider on dynamic-rate-limit 429s Same plumbing change as the parallel limiters, applied to both dynamic_rate_limiter (v1) and dynamic_rate_limiter_v3: * v1: TPM-zero and RPM-zero paths in async_pre_call_hook now resolve data['model'] -> (model, llm_provider) once and pass it into both raises. * v3: All three raise sites in _check_rate_limits — the model_saturation_check enforced raise, the priority_model enforced raise, and the fail-closed unknown-descriptor branch — now attribute the 429 to the actual provider. Falls back to llm_provider='litellm_proxy' when the model can't be resolved. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(proxy/hooks): populate llm_provider on batch-rate-limit 429s batch_rate_limiter._raise_rate_limit_error now takes a requested_model kwarg threaded from data['model'] in _check_and_increment_batch_counters. The batch-creation 429 is what gets raised when the input file's tokens/requests count would push the per-key TPM/RPM window over its limit. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(proxy/hooks): populate llm_provider on budget/iterations 429s Final batch of internal raise sites — the user/session-budget and max-iterations hooks. Same pattern: resolve data['model'] once at raise time, attach to ProxyHTTPRateLimitError so Prometheus and observability callbacks can attribute the 429. Hooks updated: * max_budget_limiter (per-user max_budget exceeded) * max_iterations_limiter (per-session agent iteration cap) * max_budget_per_session_limiter (per-session dollar cap) All three fall back to llm_provider='litellm_proxy' when data['model'] is missing or unparseable. Drops the now-unused HTTPException import from each module. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(proxy/hooks): pin provider field on internal rate-limit 429s Regression coverage for the 'provider field missing' bug across every proxy-side rate-limit hook + the helper layer: * ProxyHTTPRateLimitError class shape (HTTPException + RateLimitError, dict-detail stringification, None-provider normalization). * resolve_llm_provider_for_rate_limit happy paths (gpt-4o-mini, anthropic/..., bedrock/...) plus all three fallback branches (None, '', unknown name) plus a 'get_llm_provider raises' case that asserts we swallow the secondary exception. * For each limiter (parallel v1/v3, dynamic v1/v3, batch, max_budget, max_iterations, max_budget_per_session): assert the raised exception is a RateLimitError carrying the resolved model + llm_provider, and a sibling test that asserts the fallback path returns 'litellm_proxy' without leaking a second exception. * Two PrometheusLogger._get_exception_class_name pins so the Prometheus failure metric label flips from 'HTTPException' to 'Openai.ProxyHTTPRateLimitError' (or 'Litellm_proxy.*' on fallback) — that's what dashboards consume. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * perf(proxy/hooks): defer provider resolution to over-limit branches * fix: use error_message in raise_rate_limit_error to avoid literal 'None' in detail * Consolidate rate_limiter_utils imports in dynamic_rate_limiter * fix(proxy): set num_retries/max_retries on ProxyHTTPRateLimitError ProxyHTTPRateLimitError inherits from RateLimitError but did not call RateLimitError.__init__, so num_retries/max_retries were never set. When Starlette's HTTPException lacks __str__, MRO falls through to RateLimitError.__str__, which unconditionally reads these attributes and raises AttributeError during logging/traceback formatting. Initialize them to None defensively. * fix(mypy): silence base-class status_code conflict on ProxyHTTPRateLimitError HTTPException declares 'status_code: int' while openai.RateLimitError (via APIStatusError) declares 'status_code: Literal[429] = 429'. Mypy flags the multi-base override as [misc] in CI lint. The runtime semantics are fine (we set self.status_code in __init__), so silence the class-level annotation conflict with a targeted ignore. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix: annotate batch limiter _raise_rate_limit_error as NoReturn * feat(prometheus): rate-limit category/type labels + exception_class back-compat (follow-up to BerriAI#27687) (BerriAI#27706) * feat(prometheus): add rate_limit_category and rate_limit_type labels Adds two new labels to litellm_proxy_failed_requests_metric so dashboards can split 429s by rate-limit source (vendor vs. litellm-internal) and by the dimension that was exceeded (requests/tokens/concurrent_requests/ budget/max_iterations) without parsing free-text error messages. Closes the Prometheus side of LIT-2718. The unified RateLimitError.category and .rate_limit_type fields landed in PR BerriAI#27687 but were only surfaced on StandardLoggingPayload (custom-callback channel); this exposes them on the metric label set as well. Both labels are populated only when the underlying exception is a litellm.RateLimitError; non-rate-limit failures keep them empty. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(prometheus): populate rate-limit labels + preserve exception_class back-compat Two coupled changes in the Prometheus integration: 1. async_post_call_failure_hook now extracts the new RateLimitError .category / .rate_limit_type fields (added in PR BerriAI#27687) via a _extract_rate_limit_labels helper and forwards them through UserAPIKeyLabelValues onto litellm_proxy_failed_requests_metric. Empty for non-rate-limit failures. 2. _get_exception_class_name special-cases ProxyRateLimitError and keeps emitting 'HTTPException' for the exception_class label. Without this shim, ProxyRateLimitError (which multi-inherits from HTTPException + RateLimitError) would silently flip the label from 'HTTPException' (the historical value for proxy-side 429s) to 'ProxyRateLimitError', breaking existing dashboards / alerts that key off exception_class='HTTPException'. Distinguishing vendor vs. litellm 429s is now the job of the new rate_limit_category label. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(prometheus): cover rate-limit labels and exception_class back-compat Adds 19 tests across: - enum / label-list registration - _extract_rate_limit_labels for vendor RateLimitError, ProxyRateLimitError, non-rate-limit and None inputs (incl. parametrized over every RateLimitErrorCategory x RateLimitType combo) - _get_exception_class_name back-compat: ProxyRateLimitError keeps the legacy 'HTTPException' string while vendor RateLimitError keeps the historical 'Provider.ClassName' format - end-to-end through async_post_call_failure_hook with both ProxyRateLimitError and vendor RateLimitError, asserting both new labels populate and exception_class stays back-compat Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(prometheus): tolerate missing fastapi in lazy ProxyRateLimitError import Address greptile feedback: - async_post_call_failure_hook docstring: drop the stale labelnames listing and reference PrometheusMetricLabels.litellm_proxy_failed_requests_metric as the source of truth so the doc cannot drift from the actual labelset. - _get_exception_class_name: guard the lazy ProxyRateLimitError import with ImportError so router-side fallback callsites don't blow up in non-proxy installs that don't have fastapi (a transitive dep of proxy.common_utils.proxy_rate_limit_error). Behavior is unchanged when fastapi is available. Also fix the existing enterprise callback test that asserted the old labelset on litellm_proxy_failed_requests_metric — it now expects the new rate_limit_category / rate_limit_type labels populated for vendor 429s. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(bugbot): simplify rate-limit label coercion + guard None detail - prometheus.py _extract_rate_limit_labels: RateLimitError.__init__ already normalizes category/rate_limit_type to plain str, so the getattr(.value) + isinstance dance was dead code. Reduce to str(value) if not None. - proxy_rate_limit_error.py _coerce_message: short-circuit None to '' instead of falling through to str(None) = 'None', which produced the literal message 'litellm.RateLimitError: None'. * fix(rate-limit): surface unified category/type fields on BudgetExceededError The most common budget cap (virtual-key max_budget enforcement in auth_checks.py) raises litellm.BudgetExceededError, a bare Exception subclass that bypassed the unified rate-limit error class introduced by PR BerriAI#27687. Custom callbacks reading StandardLoggingPayload.error_information saw category=None and rate_limit_type=None for these 429s, missing the most common budget case (team / org / end-user budgets all hit the same code path). Surface the fields off BudgetExceededError as plain attributes: - category = RateLimitErrorCategory.LITELLM_RATE_LIMIT - rate_limit_type = RateLimitType.BUDGET - llm_provider = "" (or caller-supplied) Switch get_error_information and _extract_rate_limit_labels from isinstance(RateLimitError) gating to duck-typed attribute reads, guarded by membership in the rate-limit enums so unrelated third-party exceptions exposing a .category attribute can't leak garbage values into the payload. This is strictly additive: BudgetExceededError keeps its bare-Exception base class, so `except BudgetExceededError:` handlers keep firing and `except RateLimitError:` does not start catching budget errors. * fix(rate-limit): validate enum membership at duck-typed read sites + enrich BudgetExceededError llm_provider Two follow-ups uncovered during the second QA pass on PR BerriAI#27687: 1. Guard third-party `.category` / `.rate_limit_type` attribute leakage. The duck-typed read in `get_error_information` and `_extract_rate_limit_labels` would forward any string attribute named `category` / `rate_limit_type` on an unrelated third-party exception into the StandardLoggingPayload and Prometheus labels — silently mislabeling custom-callback payloads and blowing out Prometheus label cardinality. Add `validate_rate_limit_category` / `validate_rate_limit_type` helpers that gate on the documented enum value sets; non-matching values are dropped to None. 2. Enrich BudgetExceededError.llm_provider from request_data. Budget checks live in tenant-scoped helpers (key / team / org / tag / end-user / project) that don't see the request model, so the BudgetExceededError they raise carried llm_provider="" — leaving custom-metrics consumers without provider attribution for the most common 429 case. Resolve it once at the central UserAPIKeyAuthExceptionHandler seam, before post_call_failure_hook fires, so the StandardLoggingPayload the callback sees has the same provider attribution as RPM/TPM 429s. Regression tests pin both: 4 leakage tests + 4 enrichment tests. The leakage tests would fail under the pre-validation version of either read site; the enrichment tests would fail if the handler skipped the resolver call. * fix(rate-limit): resolve router model_name aliases to real provider (BerriAI#27914) * fix(rate-limit): resolve router model_name aliases to real provider For nearly every real LiteLLM proxy deployment the request model is a router model_name alias (e.g. 'tpm-locked' -> litellm_params.model: openai/gpt-4o-mini), and 'litellm.get_llm_provider' doesn't know about router aliases — it raises 'LLMProviderNotProvidedError'. The resolver then fell through to the defensive 'litellm_proxy' fallback, so the 'llm_provider' field this PR adds was effectively always 'litellm_proxy' in the field, defeating its purpose for the most common proxy configuration. Add a router-alias fallback step: when 'get_llm_provider' raises, scan the active 'llm_router.model_list' for a deployment whose 'model_name' matches the request model and resolve from its 'litellm_params.model' instead. If multiple deployments share the same alias (load-balancing case) the first one wins — every deployment under one alias should agree on provider in any sensible config, and 'first' is deterministic so the Prometheus label stays stable. Defensive throughout: an uninitialized router, a malformed deployment, a 'litellm_params.model' that itself fails 'get_llm_provider' — every branch falls through to the existing 'litellm_proxy' fallback rather than letting a secondary exception escape and mask the rate-limit error we're trying to surface. Tests: - test_router_alias_resolves_to_underlying_provider: alias 'tpm-locked' -> 'openai/gpt-4o-mini' produces provider='openai', model='gpt-4o-mini'. - test_router_alias_with_multiple_deployments_uses_first. - test_router_alias_unknown_falls_back. - test_router_alias_with_malformed_deployment_falls_back. - Existing fallback test updated to also stub 'litellm.proxy.proxy_server.llm_router' so it exercises the full 'no resolution anywhere' path. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(rate-limit): harden router alias resolver + test isolation - Wrap _resolve_provider_from_router_alias loop in top-level try/except so a non-iterable model_list / unexpected deployment shape can't escape and mask the 429 with a 500. - Type-check litellm_params before .get() to handle non-dict truthy values. - Patch llm_router=None in the parametrized fallback test so a router left by another test in the session can't redirect the unknown-model path. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(bugbot): preserve "BudgetExceededError" Prometheus label Adding llm_provider to BudgetExceededError (so callbacks get provider attribution from StandardLoggingPayload) made the provider-prefix step in _get_exception_class_name silently flip the label from "BudgetExceededError" to e.g. "Openai.BudgetExceededError", breaking dashboards keyed on the historical value. Short-circuit BudgetExceededError in _get_exception_class_name the same way ProxyRateLimitError already is. Provider/category attribution still lands on the new rate_limit_category / rate_limit_type labels. * test: fix invalid 'rpm' rate_limit_type in v3 limiter test mocks The v3 rate limiter only emits 'requests', 'tokens', or 'max_parallel_requests'. Using 'rpm' caused map_v3_rate_limit_type to return None, leaving the expected RateLimitType.REQUESTS untested. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(bugbot): hoist provider resolver + opt-in prom rate-limit labels - dynamic_rate_limiter.py: hoist resolve_llm_provider_for_rate_limit above the TPM/RPM if/elif so the lookup runs once per request, matching the pattern in dynamic_rate_limiter_v3.py. - prometheus.py: gate the new rate_limit_category / rate_limit_type labels on litellm_proxy_failed_requests_metric behind litellm.prometheus_emit_rate_limit_labels (default False). Mirrors the existing prometheus_emit_stream_label opt-in. Preserves the metric's pre-unification label set so existing dashboards / recording rules keep matching after upgrade; operators can enable the new labels once downstream consumers include them. - Tests updated: default-off back-compat case, opt-in path enables the flag before asserting label presence. * fix: stabilize prometheus label sets and drop redundant model normalization - Cache PrometheusLogger.get_labels_for_metric per metric_name so that the label set used to construct counters at __init__ time stays in sync with the label set used at increment time, even if module-level toggles like prometheus_emit_rate_limit_labels or prometheus_emit_stream_label are flipped at runtime. Without this, toggling these flags after the logger was created would cause ValueError from prometheus_client because the runtime labels would not match the counter's declared labelnames. - Drop redundant 'model or ""' guard in ProxyRateLimitError.__init__ where model is already normalized one step earlier. Co-authored-by: Yassin Kortam <yassin@berri.ai> * perf(dynamic_rate_limiter): only resolve provider when rate limit hit Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(prometheus): clear cached metric labels after toggling rate-limit flag The PrometheusLogger caches each metric's label set at construction time so that labels used at counter.labels(...) time stay consistent with the labels the metric was registered with. The enterprise async_post_call_failure_hook test toggles litellm.prometheus_emit_rate_limit_labels = True AFTER the fixture has already built the logger, so without invalidating the cache the rate_limit_category / rate_limit_type labels never reach the mocked counter and the assert_called_once_with check fails. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test: fix CI failures from prom label cache + flaky time-window assertion PrometheusLogger.get_labels_for_metric now caches the per-metric label set at first read so the labels passed to counter.labels(...) stay in lock step with the labels the counter was registered with. This broke two existing test patterns: - test_prometheus_labels.py: tests bind the real method onto a MagicMock, but MagicMock auto-creates a Mock for _cached_metric_labels whose .get(...) returns a truthy Mock — treated as a populated cache and returned as the label set, producing empty filtered labels and KeyError on labels["requested_model"] / ["route"]. Seed real {} containers for _cached_metric_labels and label_filters before binding. - test_prometheus_logging_callbacks.py::test_set_team_budget_metrics_with_custom_labels: the fixture builds the logger before the test monkeypatches litellm.custom_prometheus_metadata_labels, so the cached label set never picks up the new metadata labels. Clear the cache after the monkeypatch (same pattern already used for the rate-limit toggle in test_async_post_call_failure_hook). UI: view_logs/index.test.tsx "Last Minute" window assertion is off by one at the minute boundary. start_date is floored to the minute, so the dropped sub-minute fraction can push the truncated-seconds diff up to (minMinutes+1)*60 exactly when the click lands near a minute rollover. Switch the upper bound to toBeLessThanOrEqual. * feat(otel-v2): surface rate_limit_category + rate_limit_type on failed LLM-call spans PR BerriAI#28909 introduced the typed v2 OTel engine that builds spans from StandardLoggingPayload, with SpanError carrying error_type + message and the genai mapper stamping error.type onto every failed LLM-call span. This PR's earlier commits added error_rate_limit_category and error_rate_limit_type to the same StandardLoggingPayload.error_information the v2 engine reads — but neither field reached a span attribute, so v2 OTel traces stayed opaque about *why* a 429 fired (vendor vs litellm, RPM vs TPM vs concurrent vs budget vs max_iterations) even after the custom-callback and prometheus surfaces gained that decomposition. Three coupled changes: 1. semconv.py: add LiteLLM.ERROR_RATE_LIMIT_CATEGORY / LiteLLM.ERROR_RATE_LIMIT_TYPE under the litellm.* vendor namespace (no GenAI semconv equivalent exists for who-rate-limited / which-dimension). 2. payloads.py: extend SpanError with rate_limit_category + rate_limit_type, populated by _parse_error() from the same error_information.error_rate_limit_* fields the custom-callback channel and prometheus rate_limit_category / rate_limit_type labels read. Single source of truth across all three observability surfaces. 3. mappers/genai.py: stamp the two attributes on the LLM-call span when present. drop_none guarantees they stay absent (not 'None') for non-rate-limit failures so trace consumers can read them unconditionally. Three regression tests in test_otel_v2_emitter.py pin: a vendor / litellm-internal RateLimitError lands category=litellm_rate_limit + rate_limit_type=requests on the span; a BudgetExceededError lands rate_limit_type=budget; a non-rate-limit failure (BadRequestError) keeps the rate_limit_* attributes absent. Mutation-tested against reverting either the SpanError extension or the _parse_error read site — both new tests fail under either mutation. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test: align prometheus user-budget + logs quick-select tests with merged code The merge into this branch left two test patterns out of step with the code they exercise. test_set_user_budget_metrics_includes_user_email_and_alias_labels_when_opted_in flipped litellm.prometheus_user_budget_label_include_email_alias after the fixture had already built the PrometheusLogger. get_labels_for_metric now snapshots each metric's label set at construction time, so the runtime flip no longer reached the cached labels. Enable the flag before constructing the logger, matching how the proxy applies config at startup. view_logs/index.test.tsx referenced uiSpendLogsCall and moment without importing them, and the merged index.tsx now fetches through useLogFilterLogic (the hook the file stubs out) rather than calling uiSpendLogsCall directly. Add the imports and restore the real hook for the Quick Select window assertions so the call is actually observed. * refactor(otel/v2): drop rate-limit decomposition from the LLM-call span Proxy-side rate limits (litellm_rate_limit, budget, max_iterations) are rejected at the gate before any upstream call, so async_post_call_failure_hook tags the synthetic failure log with LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL and the v2 OTel logger never opens an LLM-call span for them; the litellm.error.rate_limit_category / litellm.error.rate_limit_type attributes were dead for exactly the cases they were meant to surface. The only failure that does open an LLM-call span carrying a RateLimitError is a vendor 429, where rate_limit_type is always None and the category just restates error.type=RateLimitError. The decomposition still reaches downstream consumers through StandardLoggingPayload.error_information.error_rate_limit_* and the prometheus rate_limit_category / rate_limit_type labels, both unchanged. Removes the SpanError fields, the _parse_error reads, the genai mapper attributes, the semconv keys, and the three span tests that asserted a scenario that never reaches the mapper in production. * fix(batch_rate_limiter): map max_parallel_requests to concurrent_requests * refactor(prometheus): drop transitive fastapi import from _get_exception_class_name Read the legacy exception_class label from a prometheus_exception_class_name marker on ProxyRateLimitError instead of importing the proxy module, keeping the integrations layer free of a transitive fastapi dependency. * chore(ui): sync schema.d.ts with unified rate-limit error spec The ProxyRateLimitError docstring flows into the proxy OpenAPI spec's 429 response description, so the generated dashboard types were out of sync. Regenerated via npm run gen:api (Check UI API Types Sync). --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>
…ed (BerriAI#29872) The Guardrails page hardcoded defaultActiveKey="submitted", so admins landed on the "Submitted Guardrails" tab (the last of their four tabs) instead of the primary view. The original intent was for non-admins, whose only tab is Submitted Guardrails, to default there; admins should open on their first tab. Make the default role-aware: admins default to the first tab (Guardrail Garden), non-admins keep Submitted Guardrails.
…I types (BerriAI#29885) The dashboard calls UI-internal proxy routes that the public /openapi.json hides with include_in_schema=False, so they never reached schema.d.ts and could not be typed. The type generator now force-includes those routes when it dumps the spec for openapi-typescript; this mutates a throwaway interpreter only, so the spec the proxy actually serves is unchanged. Regenerates schema.d.ts so 86 internal route families (for example /v2/model/info, /global/spend/*, /config/*, /v2/login, /sso/*) are now typed, with no public route removed. This unblocks migrating the dashboard's data fetching onto the typed $api client. Branch CI note: schema.d.ts is generated; CI regenerates and diffs it via the same gen:api script.
…29900) * feat(proxy): publish /v2/model/info in Swagger OpenAPI spec Expose the v2 model info endpoint in /docs by removing include_in_schema=False and documenting query parameters used by the admin UI and proxy CLI consumers. Co-authored-by: Cursor <cursoragent@cursor.com> * chore(ui): regenerate schema.d.ts for /v2/model/info OpenAPI docs Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>
…AI#29949) Consolidate the three hand-synced copies of the migrated-pages map (LEGACY_REDIRECTS in app/page.tsx, MIGRATED_PAGES in the dashboard layout, and MIGRATED_PAGES in leftnav) into one shared module, src/utils/migratedPages.ts, which also owns the migratedHref helper. Delete the unused, incomplete Sidebar2 prototype. No runtime behavior change: the map is still empty and Sidebar2 had no importers, so this is pure deduplication ahead of the per-page App Router migration. Follow-up work will unify the remaining base-URL builders (layout's withBase and page.tsx's redirect) onto migratedHref.
…riAI#29958) The provider logo base path was relative ("../ui/assets/logos/"). With trailingSlash enabled, the public model hub is served at /ui/model_hub_table/, so the browser resolved the base to /ui/ui/assets/logos/ (a doubled /ui/), which 404s every icon. The authenticated hub renders inside the single-level /ui/ SPA route where the relative path resolves correctly, so only the public hub broke. Make the base root-absolute so it resolves at any route depth.
…9871) The create guardrail modal used antd's default maskClosable, so clicking outside it dismissed the modal and reset every field the user had entered. Setting maskClosable={false} keeps the modal open; it now closes only via the explicit close button or Cancel, matching the other form modals in the dashboard
…rriAI#29870) The key edit page showed the default key type (no allowed_routes restriction) as "Default", while the key creation form already labels the same value "Full Access". Align the edit page to the create form so the two surfaces agree on both the label and its description.
…BerriAI#29953) * fix(ui): unify migrated-route URLs and cut the API Reference page over to path routing Route all migrated-page navigation through one /ui-prefixed, serverRootPath-aware builder in migratedPages.ts (migratedHref/legacyPageHref/legacyKeyForPathname), replacing the three divergent base-URL constructions that lived in the dashboard layout's withBase, leftnav, and the page.tsx redirect. The previous migratedHref read NEXT_PUBLIC_BASE_URL, which no build sets, so it produced URLs without the /ui prefix the app is served under; every other internal link hardcodes /ui and this now matches that convention. Remove the sidebar's own pushState navigation so the parent (legacy root page or dashboard layout) is the single owner of navigation, fixing the double-navigate that fired when moving between a path route and a legacy ?page= route. Cut API Reference over to its path route: add api_ref -> api-reference to MIGRATED_PAGES and delete its arm from the legacy switch. Visiting /ui/?page=api_ref redirects to /ui/api-reference, the sidebar links to and highlights it, and navigating away returns to the legacy switch. * fix(ui): address review on migrated-page routing Keep the legacy hyphenated ?page=api-reference form working by mapping it to the api-reference route alongside api_ref; the old switch matched both, so a bookmark using the hyphen would otherwise fall through to the Usage default. Add legacyKeyForPathname coverage: a migrated path (with and without trailing slash) resolves to the api_ref sidebar key rather than the alias, a non-migrated path returns null, and a non-root serverRootPath prefix is stripped before matching. * fix(ui): populate serverRootPath from getUiConfig so migrated nav links keep the root path getUiConfig updated proxyBaseUrl but never called updateServerRootPath, so the module-level serverRootPath stayed at its "/" default. Under a custom server_root_path the unified migratedHref/legacyPageHref builders then dropped the prefix and the sidebar produced /ui/api-reference (404) instead of /<root>/ui/api-reference. Adds the missing updateServerRootPath call plus a regression test asserting getUiConfig sets serverRootPath and that migratedHref carries the prefix
…the Tools page (BerriAI#29867) * fix(ui): let non-creator users OAuth into OBO-mode MCP servers from the Tools page * fix(ui): clear OBO Tools-tab one-shot on navigate-back and gate on credential-status errors
* feat(bedrock_mantle): add SigV4/IAM auth to Responses API route (fixes BerriAI#29665) (BerriAI#29788) * feat(responses): add default no-op sign_request to BaseResponsesAPIConfig * feat(responses): call sign_request after body is final, send signed bytes when signed * feat(bedrock_mantle): add SigV4 sign_request via composed BaseAWSLLM (bearer path) * test(bedrock_mantle): cover SigV4 access-key, AssumeRole, body bytes, region/auth consistency * feat(bedrock_mantle): defer auth to sign_request; validate_environment no longer requires bearer * docs(bedrock_mantle): document SigV4 + Bearer auth on Responses route * test(responses): cover fake-stream signing order and mantle bearer arg/env precedence * fix(bedrock_mantle): wrap all botocore credential errors with both-paths guidance * fix(bedrock_mantle): catch specific credential errors, not all BotoCoreError, so STS transport failures are not masked * fix(bedrock_mantle): sign the compact Responses route too, not just create * fix(github-copilot): route per-model on /v1/responses based on model info (BerriAI#29747) * feat(focus): add GCS destination for FOCUS export (BerriAI#29751) * test: add failing tests for FocusGCSDestination * feat: add FocusGCSDestination reusing GCSBucketBase auth * feat: register FocusGCSDestination in factory; export from __init__ * fix(focus): preserve GCS_PATH_SERVICE_ACCOUNT when service_account_json not in config * style: apply Black formatting to gcs_destination and tests * style: apply Black formatting to factory.py * fix(bedrock): omit empty additionalModelRequestFields and system from Converse API payload (BerriAI#29565) Amazon Nova Pro (and other strict Bedrock models) return 400 Malformed input request when additionalModelRequestFields: {} or system: [] are present in the payload. Both fields are optional in CommonRequestObject (total=False) and must be omitted rather than sent as empty structures. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(proxy): recognize *.cognitiveservices.azure.com as OpenAI-compatible in pass-through cost tracking (BerriAI#29730) * fix(proxy): recognize *.cognitiveservices.azure.com as OpenAI-compatible Azure OpenAI resources created via the newer "Azure AI Foundry" / Cognitive Services pathway live on `*.cognitiveservices.azure.com` subdomains, not the older `openai.azure.com`. Both are valid Azure OpenAI surfaces in production today. The OpenAI pass-through cost-tracking handler hard-codes only the older hostname in five places (four `is_openai_*_route` methods on OpenAIPassthroughLoggingHandler, plus is_openai_route on PassThroughEndpointLogging). As a result, calls from newer Azure deployments are silently classified as "not an OpenAI route", the dispatch into the cost-tracking handler is skipped, and tokens/cost never get extracted into LiteLLM_SpendLogs — the row gets written with prompt_tokens=0, completion_tokens=0, spend=0, model='unknown'. Reproduced 2026-06-04 against a real Azure OpenAI deployment on `*.cognitiveservices.azure.com` proxied through LiteLLM v1.88.0. Fix: factor the hostname check into a single helper `_is_openai_compatible_host` listing all three recognized surfaces (api.openai.com, openai.azure.com, cognitiveservices.azure.com), and have all five call sites delegate to it. Purely additive — never weakens recognition for the originally-supported hostnames. Adds a test `test_is_openai_route_recognizes_cognitiveservices_azure_com` that exercises all four `is_openai_*_route` static methods against `*.cognitiveservices.azure.com` URLs (positive cases per route + a small cross-route negative to confirm route-specific path matching still works on the new hostname). Out of scope for this PR (separate followup): - `openai_passthrough_handler` calls chat/completions `transform_response` on Responses API payloads (`output:` not `choices:`), which throws inside the dispatch and drops the SpendLogs row entirely. Recognized + tracked separately. * ci: trigger fresh run Empty commit to re-run checks. The previous auth-and-jwt failure was a transient HuggingFace Hub 429 rate-limit hitting tokenizer downloads in tests/proxy_unit_tests/test_custom_tokenizer_bug.py — unrelated to this PR's scope (hostname recognition in pass-through cost tracking). No code change. --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(responses): preserve forced-function tool_choice name in Responses to Chat transform (BerriAI#29812) The Responses API forces a specific function with a top-level name ({"type": "function", "name": "X"}), but _transform_tool_choice only handled the nested Chat Completions shape and fell through to returning "required" for the flat form, silently dropping the function name and degrading a forced function call to force-any-tool. Map the flat Responses shape to the nested Chat shape, keeping the "required" fallback when no name is present. * Preserve x-anthropic-billing-header system blocks for first-party Anthropic (BerriAI#29584) * Preserve x-anthropic-billing-header system blocks for first-party Anthropic PR BerriAI#20951 strips system blocks beginning with "x-anthropic-billing-header:" for every Anthropic target. That block is how the first-party Anthropic API recognizes Claude Code subscription (OAuth) traffic, so dropping it makes requests that carry only that block, such as the auto-mode tool-safety classifier, fail with a misleading 429 rate_limit_error; normal turns still work because they also carry the "You are Claude Code" identity block. Gate the strip behind should_strip_billing_metadata(), defaulting to False on the first-party AnthropicConfig and AnthropicMessagesConfig so the block is kept, and overridden to True on the providers that reach these transforms and reject the block (Bedrock platform, Vertex, Azure for the chat path; Minimax, Azure, DeepSeek for the messages path). Behavior for those providers is unchanged. * Strip billing header on Bedrock invoke and Vertex messages pass-through Two more subclasses reach the gated strip but inherited keep-by-default. AmazonAnthropicClaudeConfig (Bedrock invoke) calls AnthropicConfig.transform_request, which calls translate_system_message, and VertexAIPartnerModelsAnthropicMessagesConfig (Vertex messages pass-through) calls super().transform_anthropic_messages_request. Override should_strip_billing_metadata() to True on both. Add a parametrized test asserting the flag for every first-party base (False) and provider subclass (True), covering all overrides, plus a translate_system_message regression test for the Bedrock invoke path. * fix(cache): log hashed cache keys (BerriAI#29890) * fix(ui): save routing groups as list (BerriAI#29889) * Revert "fix(ui): save routing groups as list (BerriAI#29889)" (BerriAI#29928) This reverts commit 9b1f78f. * feat(parasail): add Parasail as a JSON-configured OpenAI-compatible provider (BerriAI#29842) * feat(parasail): add Parasail as a JSON-configured OpenAI-compatible provider Registers parasail in the openai_like JSON provider loader with both /v1/chat/completions and /v1/responses support. Parasail's Responses API rejects store:true and any request that omits store, so the loader gains a force_store_false special_handling flag; the parasail entry sets it and the generated Responses config overrides store=false on every call. This keeps callers from hitting "State storage not supported" and matches what Parasail's docs require. Adds the PARASAIL enum value, listing under openai_compatible_providers, provider documentation at docs/my-website/docs/providers/parasail.md, and a focused unit test file under tests/test_litellm/llms/parasail/ that covers JSON registration, chat URL construction, Responses URL construction with PARASAIL_API_BASE override, and the force_store_false regression in both the caller-sent-store=true and caller-omitted cases. * fix(parasail): register in provider_endpoints_support, drop in-repo docs Greptile review feedback. The provider doc belongs in the litellm-docs repo, not this one's docs/my-website tree; removing it here. Adds the parasail entry to provider_endpoints_support.json so the check_provider_folders_documented.py CI check passes (chat_completions and responses true; others false). * fix: normalize Anthropic passthrough server tool usage (BerriAI#29827) * test(anthropic): cover server_tool_use dict cost tracking * fix: normalize Anthropic server tool usage (cherry picked from commit 982f726) * fix: keep server tool usage subscriptable (cherry picked from commit 70280b9) --------- Co-authored-by: Genmin <joey@joeyroth.com> * fix(proxy): fix typo generic_role_mappoings -> generic_role_mappings in ui_sso.py (BerriAI#29753) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * feat(proxy): add disable_budget_reservation general setting (BerriAI#27639) (BerriAI#29493) * feat(proxy): add disable_budget_reservation general setting (BerriAI#27639) * feat(proxy): register disable_budget_reservation in ConfigGeneralSettings (BerriAI#27639) * docs(proxy): document disable_budget_reservation concurrency tradeoff (BerriAI#27639) * ci: re-trigger flaky docker build (prisma generate ECONNRESET) * fix(proxy): warn and document budget enforcement tradeoff when disable_budget_reservation is set (BerriAI#27639) * feat(gemini_tts): adding support to Gemini TTS languageCode parameters (BerriAI#29623) * Adding support to Gemini TTS Language Code parameters * Mapping Gemini TTS languageCode param in Docstring * Use snake_case for language_code input keyMapping Gemini TTS languageCode param in Docstring * Restoring files modified under enterprise/litellm_enterprise due to lint/formatting checks --------- Co-authored-by: João Garrido <joaogarrido@google.com> * feat(guardrails): capture user and model metadata in CrowdStrike AIDR (BerriAI#29517) * fix(proxy): require OpenAI path segment for shared Azure Cognitive Services domains Address Greptile review: the `*.cognitiveservices.azure.com` / `*.openai.azure.com` domains are shared by every Azure Cognitive Service (Speech, Vision, Language, ...), so a hostname-only substring match misclassified non-OpenAI Azure traffic as OpenAI routes. - Replace the substring host test with suffix matching (rejects look-alike domains like cognitiveservices.azure.com.attacker.example). - Add `_is_openai_compatible_url` that requires an OpenAI-style path marker (`/openai/` or `/v1/`) on the shared Azure domains, and use it in PassThroughEndpointLogging.is_openai_route (previously hostname-only). - Add negative tests for Azure Speech/Vision paths and look-alike domains. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * fix: support Responses input in Redis semantic cache (BerriAI#29581) * fix: support responses input in redis semantic cache * test: cover redis semantic prompt extraction * test: handle blank redis semantic text fallbacks * chore: remove async cache dead statement * test: cover redis semantic cache miss paths * fix: filter sensitive cache lookup kwargs * chore: rerun ci after huggingface rate limit * chore(ui): regenerate dashboard API types (npm run gen:api) Sync src/lib/http/schema.d.ts with the proxy OpenAPI spec: adds the disable_budget_reservation general-settings field and picks up the RateLimitError docstring reindent. Fixes the gen:api CI drift check. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * test(bedrock): assert empty additionalModelRequestFields is omitted The Converse transformer now drops an empty additionalModelRequestFields block instead of sending it as `{}`. Update test_bedrock_top_k_param so models without top_k support (llama3) assert the key is absent rather than equal to an empty dict. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: Kent <72616338+kingdoooo@users.noreply.github.com> Co-authored-by: codgician <15964984+codgician@users.noreply.github.com> Co-authored-by: Praveen Ghuge <95286176+pghuge-cloudwiz@users.noreply.github.com> Co-authored-by: Roi <roytev@gmail.com> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Liam Scott <liam@uilliam.com> Co-authored-by: abhay23-AI <abhaytrivedi22@gmail.com> Co-authored-by: Ceder Dens <cederdens@gmail.com> Co-authored-by: 冯基魁 <56265583+fengjikui@users.noreply.github.com> Co-authored-by: Kai Huang <kaihuang724@gmail.com> Co-authored-by: rinto <54238243+ririnto@users.noreply.github.com> Co-authored-by: Genmin <joey@joeyroth.com> Co-authored-by: Arnav Bhilwariya <arnavbhilwariya0408@gmail.com> Co-authored-by: Armaan Sandhu <74664101+Ar-maan05@users.noreply.github.com> Co-authored-by: João Garrido <48538534+johngarrido@users.noreply.github.com> Co-authored-by: João Garrido <joaogarrido@google.com> Co-authored-by: Kenan Yildirim <kenan@kenany.me> Co-authored-by: Dávid Balatoni <balcsida@gmail.com>
…#29908) * feat(galileo): add health check support for UI callback test Register galileo in /health/services so the proxy UI callback connection test works. Co-authored-by: Cursor <cursoragent@cursor.com> * feat(galileo): verify API key via /current_user health check Call Galileo's current_user endpoint so the UI callback test validates credentials against the provider. Co-authored-by: Cursor <cursoragent@cursor.com> * chore(ui): regenerate schema.d.ts for galileo health service Co-authored-by: Cursor <cursoragent@cursor.com> * fix(galileo): return IntegrationHealthCheckStatus from async_health_check Fixes mypy assignment error in health_services_endpoint where response was narrowed to IntegrationHealthCheckStatus from earlier branches. Co-authored-by: Cursor <cursoragent@cursor.com> * Fix Galileo logging to match Langfuse across all endpoint types. Stop skipping ingest when output is empty and log embeddings with a placeholder so embedding, speech, and other non-text responses are recorded like Langfuse. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(galileo): remove unreachable health-check guard and None output sentinel The use_v2_api flag is derived from bool(api_key), so the inner GALILEO_API_KEY check inside the v2 branch could never run; collapse the credential validation into the username/password path with a combined message. _serialize_galileo_output now returns an empty string for None, so _get_galileo_input_output_content always yields a str and the post-call None coalescing guard is no longer needed. * test(galileo): cover async_health_check failure paths and empty model response Add regression tests for the Galileo health check unhealthy branches (missing project id, missing base url, missing credentials, auth failure, and request exception) and for logging a model response with no choices, which now queues an empty output instead of being skipped. --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
…deleted (BerriAI#29875) * fix(model-management): allow deleting a BYOK model after its team is deleted A team BYOK model (model_info.team_id set) became undeletable once its team was deleted: POST /model/delete ran can_user_make_model_call, which looked the team up and raised 400 "Team id=... does not exist in db" before the delete could run, so the model lingered on the Models + Endpoints page with no way to remove it. Drop the team-existence prerequisite from the delete path. When the model's team still exists the normal auth check runs unchanged; when it is gone a proxy admin may delete the orphan and any other caller gets a 403. The check is fail-closed, so a missing or errored team lookup can only block the delete or require an admin, never grant a non-admin access. Add/update/health keep their team-existence validation. * refactor(model-management): drop redundant team lookup on model delete Move the orphaned-team handling into can_user_make_model_call behind an allow_missing_team flag instead of pre-checking team existence in delete_model. The endpoint no longer issues its own litellm_teamtable lookup, so deleting a model whose team still exists hits the team table once instead of twice. The auth behavior is unchanged: a proxy admin can delete a model whose team was deleted, any other caller gets a 403, and add/update/health keep the strict "team must exist" validation.
…erriAI#28913) * fix(jwt-auth): defer to single-team DB fallback on claim mismatch Extends the single-team DB fallback introduced in BerriAI#26418 to two more cases where it previously could not run: * `find_and_validate_specific_team_id`: when `team_id_jwt_field` is configured and a claim value is present in the token but the team does not exist in the LiteLLM DB (HTTPException 404 from `get_team_object`), return `(None, None)` instead of raising — the auth_builder fallback then attributes the request to the user's single DB team. Only HTTPException is caught; other errors (e.g. "No DB Connected") still propagate. * `find_team_with_model_access`: when none of the `team_ids_jwt_field` groups resolve to a real LiteLLM team, return `(None, None)` instead of raising 403 so the same fallback path runs. If at least one group DID resolve to a team but none granted the requested model, the original 403 is preserved (legitimate access denial — not a claim mismatch). Tracked via the new `any_claim_team_resolved` flag. The strict `is_required_team_id` raise and `enforce_team_based_model_access` raise remain unchanged. Unit tests cover both new soft-fail paths and guard each preserved path (strict required, enforce_team_based, the preserved 403, and the non-HTTPException propagation). Co-authored-by: Cursor <cursoragent@cursor.com> * fix(jwt-auth): narrow HTTPException catch to 404 (greptile review) Address Greptile review comments on BerriAI#28913: * `find_and_validate_specific_team_id`: re-raise HTTPException when `status_code != 404`, pinning the catch to the "team doesn't exist in db" path documented for `get_team_object`. A future change that introduces a different status code (e.g. 403 for a blocked team) will now propagate instead of silently falling through to the single-team DB fallback. * Add `test_find_and_validate_specific_team_id_non_404_http_exception_propagates` parametrised over 400 / 403 / 500 to lock in the contract. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(jwt-auth): gate claim-mismatch fallback behind opt-in flag The unresolved-team-claim fallback added in the previous commit weakened the strict claim-based authorization contract by default — an authenticated user whose JWT carries a stale or invalid team claim could still consume their single DB team's models/quota via the fallback. Gate both soft-fail paths in `find_and_validate_specific_team_id` and `find_team_with_model_access` behind a new opt-in flag `team_claim_fallback` on `LiteLLM_JWTAuth` (default False). Default-off preserves the pre-existing strict behavior. Operators who intentionally treat IdP team claims as advisory (e.g. machine tokens whose group claims live in a separate namespace from LiteLLM team_ids) opt in via config. Adds two regression tests guarding the default-off behavior. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>
BerriAI#29525) On /team/update for a standalone (no-org) team, _check_user_team_limits() compared the request max_budget against the caller's personal max_budget whenever max_budget was present in the payload. A team admin whose personal budget is lower than the team's budget could not edit any field (tpm_limit, team name, etc.) because the UI re-sends the unchanged max_budget on every update, tripping the personal-budget check. Pass the team's current max_budget into _check_user_team_limits() and skip the personal-budget comparison when the incoming value is unchanged or lower than the team's current budget. Only genuine increases above the team's current budget are still validated against the caller's personal limit, so no over-relaxation. Proxy admins and the org-scoped path are unaffected. Adds two regression tests for the standalone update path (unchanged budget + tpm_limit change, and lowering the budget), both for a caller whose personal budget is below the team budget. Co-authored-by: Cursor <cursoragent@cursor.com>
…rriAI#29697) glm-5p1 supports native tools on Fireworks; explicit false flags caused drop_params to strip tools and tool_choice before the provider request. Co-authored-by: Cursor <cursoragent@cursor.com>
…cks (BerriAI#29899) * fix(vertex): propagate Vertex AI metadata in streaming success callbacks Streaming calls assembled via stream_chunk_builder were missing vertex_ai_grounding_metadata and vertex_ai_url_context_metadata in standard_logging_object.response. Merge metadata from chunks into the assembled response and mirror non-streaming hidden_params on Gemini chunks. Co-authored-by: Cursor <cursoragent@cursor.com> * refactor(vertex): move streaming metadata merge into provider config hook Address review feedback by delegating assembled-stream metadata propagation to VertexGeminiConfig via BaseConfig.apply_assembled_streaming_response_metadata, and only write chunk hidden_params when metadata is non-empty. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(redaction): scrub Vertex provider metadata when message logging is off Clear vertex_ai_grounding_metadata and related fields from standard logging responses and assembled streaming ModelResponse objects so turn_off_message_logging cannot leak prompt-derived web search queries. Co-authored-by: Cursor <cursoragent@cursor.com> * Use assembled model for streaming metadata hook * Fix Vertex metadata redaction bypass in logging callbacks. Scrub Vertex provider fields from litellm_params.metadata.hidden_params during perform_redaction so streaming success_handler merges do not leak prompt-derived metadata when message logging is disabled. Co-authored-by: Cursor <cursoragent@cursor.com> * Fix Vertex streaming metadata from hidden params * fix(vertex): mirror vertex_ai_safety_results on assembled streaming responses The non-streaming transform_response stores safety data under vertex_ai_safety_results, but the streaming path only wrote vertex_ai_safety_ratings. Assembled streaming responses therefore never carried vertex_ai_safety_results, so any consumer reading that field saw a silent difference between streaming and non-streaming calls. Set vertex_ai_safety_results alongside vertex_ai_safety_ratings in the shared stream metadata setter and add it to the assembled metadata field list so it propagates through stream_chunk_builder. * fix(streaming): log provider streaming metadata hook failures instead of swallowing them * refactor(vertex): share single Vertex metadata field tuple across redaction and streaming * refactor(vertex): move Vertex metadata redaction helpers into llms/vertex_ai --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Allow internal users to fetch their backend-scoped project list so the key creation project dropdown can populate for selected teams.
…29982) Raise the PyJWT floor in pyproject (>=2.13.0,<3.0) and re-resolve uv.lock so the proxy installs 2.13.0 instead of 2.12.0. Bump the ws transitive-version override in the dashboard from 8.19.0 to 8.20.1 and regenerate package-lock; jsdom and openai both dedupe onto the single 8.20.1 copy. Both are routine dependency maintenance bumps to keep pinned versions current.
…leted (BerriAI#29977) A team's BYOK models (rows in LiteLLM_ProxyModelTable with model_info.team_id set) were left orphaned when the team was deleted; they lingered in the database and kept showing on the Models + Endpoints page. delete_team now removes them via a new delete_team_models helper that deletes the rows in one transaction and syncs the in-memory router only after that transaction commits, run before the team rows are deleted so a mid-flight failure never leaves the team gone with its models orphaned
…rriAI#28184) * feat(vantage): include organization metadata in FOCUS Tags export Join LiteLLM_OrganizationTable when building Vantage/FOCUS export rows so organization_id and organization_alias appear in Tags for org-level filtering. Co-authored-by: Cursor <cursoragent@cursor.com> * test(focus): include api_requests in organization Tags tests FocusTransformer now requires api_requests after staging merge; add the column to test fixtures so integrations CI can run the Tags assertions. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>
…gs (BerriAI#29991) Capture user_id and extra_info from metadata or litellm_metadata. The single-bag read dropped identity whenever a request carried a present litellm_metadata field (null or a user-supplied dict), since /chat/completions routes the authenticated identity into metadata while the guardrail read litellm_metadata first
…AI#30792) * feat(proxy): add configurable response headers middleware Adds a small ASGI middleware that sets standard response headers (X-Frame-Options, Content-Security-Policy frame-ancestors, X-Content-Type-Options) on proxy and UI responses. Strict-Transport-Security is optional and gated behind LITELLM_ENABLE_HSTS for HTTPS deployments. Values use setdefault so a route that sets its own header is preserved. * feat(proxy/ui): make login page credentials hint configurable build_ui_login_form accepts a hide_default_credentials_hint parameter and google_login reads LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT (or general_settings) so the legacy login page behaves consistently with the new UI. Also collapses a duplicated branch and removes an unused variable and module-level constant. * fix(proxy/ui): apply credentials hint flag on /fallback/login The /fallback/login handler still rendered the default-credentials hint regardless of LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT. Collapse its duplicate branch and forward the flag, matching google_login, so all login surfaces behave consistently. Adds regression tests for /fallback/login and makes the ui_sso test helper restore os.environ so env vars do not leak across tests.
…riAI#30797) Switch the zizmor check to fail on any finding at medium severity or above (advanced-security off, min-severity medium, annotations on) so it can be promoted to a required check, and pin the engine to zizmor 1.24.1 through zizmor-action v0.5.6 for deterministic runs. Clear the findings that were outstanding so the check passes: correct mismatched action pin version comments, scope the proxy endpoint workflow's id-token and pull-requests permissions to the jobs that use them, and mark the server-root-path docker build as non-publishing while dropping its shared gha build cache.
…tion streaming passthrough (BerriAI#30800) * fix(proxy): use e.request_data for logging_obj in ModifyResponseException streaming passthrough When a guardrail blocks a streaming request pre-call by raising ModifyResponseException (or RejectedRequestError), chat_completion streams the violation message back as a 200 by building a CustomStreamWrapper. It read the logging object from the outer request body (`data.get("litellm_logging_obj")`), but that dict never carries litellm_logging_obj -- it diverges from the processor's data at function_setup, and only the processor copy (exposed as e.request_data, already bound to `_data` here) gets the logging object attached. CustomStreamWrapper.__init__ then dereferences `logging_obj.model_call_details` on None and 500s the request with "AttributeError: 'NoneType' object has no attribute 'model_call_details'". Read logging_obj from `_data` (= e.request_data) in both streaming passthrough handlers so the refusal streams correctly. The non-streaming and the anthropic/responses passthrough paths were unaffected. Adds a regression test asserting the wrapper receives the logging object from e.request_data rather than None. * test(proxy): cover RejectedRequestError streaming passthrough The streaming logging_obj fix was applied to both the ModifyResponseException and RejectedRequestError handlers, but only the former had a regression test. Extract a shared helper and add a parallel test for the RejectedRequestError streaming path so both handlers stay guarded against the None-logging_obj crash. --------- Co-authored-by: Joseph Barker <joseph.barker@rubrik.com>
…creds per exporter (BerriAI#30590) * fix(otel): one v2 logger owns the global provider; scope tenant creds per exporter The proxy published the OTel global TracerProvider before callbacks were initialized, so no preset logger existed yet and a second generic logger was built that won the global provider. Server spans then exported through a different provider than the preset's gen-ai spans, orphaning the LLM span on the preset backend. Publish after callback init and reuse the already-built logger instead. Separately, per-request tenant OTLP credentials were stamped onto every OTLP exporter, leaking one backend's key onto a co-configured backend. Tag each exporter with the preset that contributed it and apply dynamic credentials only to the matching owner. * fix(otel): satisfy Any-discipline on changed lines Type the logger-selection parameter as Sequence[object] (isinstance narrows it), cast the list[Any] global at the single call site, and pass model_copy a typed dict[str, str] update so no changed line carries an Any value. * fix(otel): annotate the untyped-global boundary with any-ok select_global_otel_v2_logger consumes litellm._in_memory_loggers, a shared List[Any] global this change does not own. A cast doesn't satisfy the Any-discipline checker (it inspects the inner expression), and re-annotating the global is out of scope, so mark the single boundary line any-ok. * test(otel): cover the startup global-provider publish via injectable helper The publish step lived inline in proxy_startup_event (a FastAPI lifespan unit tests do not execute), so its lines were uncovered though the selection logic was tested. Extract publish_global_otel_v2_provider, which selects the single v2 logger and publishes its provider through an injected setter, and unit-test that the published provider is the selected logger's. proxy_server delegates to it. * refactor(otel): select global provider from the registered owner, not a list scan The startup publish picked the global TracerProvider by scanning _in_memory_loggers for the first OpenTelemetryV2, re-deriving an answer the factory already settled: the first logger built registers itself as proxy_server.open_telemetry_logger, and every other v2 path (guardrail, identity seeding, phase spans) routes through that owner via _registered_v2_logger. Pass that owner into select_global_otel_v2_logger so the global provider reuses the same logger instead of an independent, order-dependent guess; the list scan remains the SDK-path fallback. The owner is injected at the proxy call site to keep the helper free of hidden global reads. * refactor(otel): type ExporterSpec.owner as an ExporterOwner enum The owner field carried free-form strings that had to match preset callback names. Introduce a str-based ExporterOwner enum (values equal to the callback names, so per-request credential routing's owner==callback_name comparison still holds) and have each preset tag its exporter with the enum member. * refactor(otel): rename ExporterOwner.ARIZE to ARIZE_AX Distinguish the hosted Arize AX backend from Arize Phoenix at the member level while keeping the value 'arize' (the public callback name routing compares against). Add a comment noting AX and Phoenix are separate backends.
…treams (BerriAI#30788) A streaming request that breaks mid-flight, for example on a mid-stream read timeout, still bills the provider for the chunks already delivered, yet the proxy recorded that interrupted request as a zero-spend failure. An earlier revision logged the recovered partial usage through the success path, which mislabeled a failed request as a success and produced a misleading spend row This recovers the partial usage where the failure is actually logged. The streaming handler assembles the usage from the chunks seen so far and stashes it, with its cost, on the logging object before firing the failure handlers. The proxy failure hook lifts that usage and cost onto request_data before the non-serialisable logging object is popped, and the spend-log writer records the real partial spend on the failure row instead of a hardcoded zero; get_logging_payload honors the recovered usage for the token columns and _failure_handler_helper_fn preserves the recovered cost so the non-DB failure loggers stay consistent A request that recovers via a successful fallback is unaffected: the failure hook only fires when the whole request fails, so the fallback's combined-usage success row stays the single source of truth and there is no double counting Resolves LIT-3825 Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com>
…#30859) The "View Usage Guide" button on the legacy Usage page (shown when DISABLE_EXPENSIVE_DB_QUERIES is set, i.e. SpendLogs has 1M+ rows) linked to docs/proxy/spending_monitoring, which was removed from the docs and now returns 404. Point it at docs/proxy/cost_tracking, which is live. Fixes LIT-2724
…erriAI#29990) The delete-team confirmation modal warned that a team's keys would be deleted but said nothing about models. BerriAI#29977 made team deletion also delete the team's BYOK models, so the modal copy was understating what gets removed. The warning banner now mentions models alongside keys, and the always-shown confirmation message does too so a team that has models but no keys (the banner only renders when keys exist) still gets warned.
…he scope keys (BerriAI#30675) Adds a "valkey-semantic" cache type so semantic prompt caching can run against Valkey clusters (for example AWS ElastiCache for Valkey) using the valkey-search module. The existing "redis-semantic" backend cannot drive valkey-search. RedisVL gates the connection on a RediSearch module version that valkey-search does not report, and its SemanticCache index declares the prompt as a TEXT field, which valkey-search does not implement. ValkeySemanticCache therefore talks to valkey-search directly over redis-py: it builds a vector index from the field types valkey-search supports (TAG for caller scope, VECTOR for the prompt embedding) and runs KNN queries for retrieval. Prompt extraction, embedding generation, and cached-response parsing are reused from RedisSemanticCache since those are backend agnostic. The redis dependency is imported lazily in the cache dispatch so importing litellm without redis installed still works. It also fixes semantic-cache scope keys so similarity matching works across reworded prompts. get_cache_key() hashed messages / prompt / input into the litellm_cache_key that every semantic backend filters its KNN search on, so a paraphrase landed in a different bucket and never matched, even far above the similarity threshold. For semantic cache types the prompt-bearing params are now excluded from the scope key and the server-set tenant identity (user_api_key, team, org) is appended instead, restoring embedding matching within a tenant while keeping cache entries scoped to the authenticated key / team / org. The three semantic backends share this key, so the same change fixes redis-semantic and qdrant-semantic. Connections resolve from VALKEY_HOST / VALKEY_PORT / VALKEY_PASSWORD, falling back to REDIS_* for drop-in compatibility, and passwordless clusters (IAM or no-auth) are supported. Resolves BerriAI#29121 Fixes BerriAI#29086
…riAI#30871) The deprecated OldTeams component takes only accessToken, userID, userRole and premiumUser; it ignores the teams prop these tests passed and instead populates its table from the mocked teamListCall. The delete-warning block never set teamListCall, and vi.clearAllMocks clears call history but not implementations, so the table rendered the "Legacy Team" (keys.length 2) left behind by the previous block's last test. Both delete tests therefore ran against that leaked team: the keys-present case passed only because the leaked count happened to be 2, and the no-keys case rendered the same warning it asserted should be absent, so it failed. Seed the team through the channel the component actually reads (teamListCall) and drop the props it never consumes, so each test renders exactly the team it declares. The keys-present case now uses a distinctive count so it can no longer pass on a coincidental leak
… ruff gate (BerriAI#30877) * feat: add CI-parity mode and truncation-proof summary to strict ruff gate * refactor: tolerant worktree cleanup and concrete GateInputs types * fix: clean up temp dir when git worktree add fails * fix: align lint-gate with CI by dropping unused --ci-parity path The lint-gate Makefile target invoked ruff_strict_gate.py with --ci-parity, which counted violations on a throwaway merge of base into HEAD against base counts at the base tip. CI in test-linting.yml runs the same script without --ci-parity on a PR-head checkout, taking the gather_fast path that counts on the live tree against base counts at the merge-base. A local pass could therefore disagree with CI. Drop --ci-parity from the Makefile and remove the now-unused gather_ci_parity branch and flag so there is one code path that both local and CI exercise. The docstring claim that CI runs against the synthetic merge ref was also wrong; the workflow checks out github.event.pull_request.head.sha. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com>
* bump: version 0.1.42 → 0.1.43 * bump: version 1.89.0 → 1.90.0 * adding uv lock
…erriAI#30897) * fix(watsonx): wrap string embedding input in array for WatsonX API WatsonX text/embeddings expects inputs as []string; OpenAI clients often send a single string. Co-authored-by: Cursor <cursoragent@cursor.com> * style(watsonx): format watsonx embed transformation for black Co-authored-by: Cursor <cursoragent@cursor.com> * fix(watsonx): avoid UP006 in embed transformation strict lint gate Use list[str] and branch-based input normalization instead of List and cast so the watsonx embedding change does not add strict ruff UP006 violations. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Shivam Rawat <shivamrawat@Shivams-MacBook-Pro.local> Co-authored-by: Cursor <cursoragent@cursor.com>
…ndpoint (BerriAI#30900) * test: point router/completion/triton tests at the local fake OpenAI endpoint The shared Railway-hosted mock (exampleopenaiendpoint-production.up.railway.app) takes down unrelated CI jobs whenever it is unreachable. BerriAI#30695 moved the mounted proxy configs onto a job-local fake server but left these in-Python api_base literals pointing at the dead host, so litellm_router_testing, local_testing_part1, local_testing_part2 and llm_translation_testing still fail with a 404 "Application not found" when Railway is down Resolve the api_base from FAKE_OPENAI_API_BASE (default http://127.0.0.1:8190) through a shared helper, auto-start the canned server from the local_testing and llm_translation conftests when nothing is already serving, and extend the server with a Triton embeddings route and a slow-endpoint delay so the triton and latency-timeout tests run fully offline. The deliberately broken fallback URL is left as-is so fallback handling still has a failing upstream * fix: ignore non-loopback FAKE_OPENAI_API_BASE so the local mock is used in CI * fix: drop 0.0.0.0 from loopback hosts, an unreliable client connect target * fix(tests): keep fake OpenAI mock alive across xdist workers ensure_fake_openai_endpoint registered atexit on the worker that spawned the subprocess, so under -n 4 the first worker to drain its queue would terminate the shared mock while siblings were still hitting it. Detach the child via start_new_session and drop the per-worker teardown; reuse on /health handles re-runs and CI containers clean up themselves
* feat(sandbox): add e2b code execution primitive Add a provider-agnostic code execution primitive that runs model-generated code in an isolated sandbox and returns the output, with e2b as the first backend over raw httpx (no SDK dependency). Public API: litellm.acode_interpreter_tool (ephemeral create -> run -> delete) plus the low-level lifecycle litellm.acreate_sandbox / arun_code / adelete_sandbox. Each is @client-decorated so operations are logged like litellm.asearch. Backends implement BaseSandboxConfig; resolved via ProviderConfigManager.get_provider_sandbox_config. * fix(sandbox): address review feedback and CI gates - document e2b provider in provider_endpoints_support.json and add a sandbox endpoint definition - regenerate dashboard CallTypes after the sandbox call-type additions - guard explicit timeout=0 instead of coercing it to the default - require a ContainerHandle access token before running code; reject bare-id runs - return False on a 404 delete now that the shared http handler raises for status - skip non-JSON NDJSON lines and cap streamed output to bound memory - move the real-network integration tests out of tests/test_litellm into tests/integration/sandbox * fix(sandbox): satisfy strict ruff gate and scope star-exports - modernize annotations in the new sandbox modules to PEP 585/604 (list/dict, X | None) and drop the now-unnecessary quoted forward refs so the strict-rule budget delta for UP006/UP037/UP045 returns to zero - add __all__ to litellm/sandbox/main.py so 'import *' only re-exports the four public entrypoints instead of leaking module-level imports * fix(sandbox): drop quotes on sandbox config return annotation utils.py uses 'from __future__ import annotations', so the quoted forward ref tripped UP037; the unquoted union is lazily evaluated and keeps the strict-rule delta at zero * chore(sandbox): re-trigger automated review after addressing feedback
… is not set" (BerriAI#30903) The migrated /ui/api-keys route gates rendering on useAuthorized() but read userID from the AuthContext (useAuth), which hydrates asynchronously. On a hard refresh or deep link the route could render UserDashboard before AuthContext had populated userID, so UserDashboard hit its `userID == null` guard and showed "User ID is not set". The legacy index page avoided this by gating on AuthContext's own authLoading; the migration switched the gate to useAuthorized without aligning the identity source. Read identity from useAuthorized (a synchronous cookie decode) so userID is populated whenever the route is authorized. useAuth is kept only for the backfill setters UserDashboard still expects, until the planned AuthContext consolidation removes them. Refs LIT-3687
… seam (BerriAI#30887) Introduce a single, typed caller identity that is resolved once at the auth boundary and read by reference downstream, instead of being re-derived from a 50-field key object or rebuilt from request metadata. What this adds (litellm/proxy/auth/resolvers/), organized by responsibility: - Principal: a small, frozen, identity-only value type (user / organization / teams / project / end-user / roles / scopes / network), with its sub-models and the role mapping. No budget or policy state; those stay on the key object. - DbIdentityStore: the auth flow's resolver, owning both halves of resolving a caller. resolve_key does the one combined_view lookup (cache, then DB via the shared lower-level helpers, then write-back) and returns the key object, which still flows for budget / rate-limit / policy unchanged. principal_from_key projects the identity slice of that key object into a Principal, issuing no lookup. user_api_key_auth resolves every key through the store rather than calling get_key_object directly; auth_checks.get_key_object stays as the legacy entrypoint for its other callers until they migrate. - network: the X-Forwarded-For / trusted-proxy CIDR primitives live here in one place. trusted_proxy_utils now imports them rather than keeping a second copy. At the seam, user_api_key_auth projects one per-request Principal off the resolved key object and stamps the request network context onto it once (X-Forwarded-For is trusted only when trusted_proxy_ranges is configured). It is attached to request.state.principal for the downstream consumers later phases add. The projection is additive and defensive: a failure never rejects an already-authenticated request, and a missing principal must be treated as deny by any future reader. The Principal is always identifiable (credential_ref and a stable subject off the token), never anonymous. This is additive and changes no behavior today; it is the identity foundation the spend-attribution and authorization phases build on.
…ace (BerriAI#30885) * feat(fireworks_ai): sync chat completions endpoint with full API surface Add 23 missing request parameters to get_supported_openai_params(): seed, top_logprobs, min_p, typical_p, repetition_penalty, mirostat_target, mirostat_lr, logit_bias, echo, echo_last, ignore_eos, prompt_cache_key, prompt_cache_isolation_key, raw_output, perf_metrics_in_response, return_token_ids, safe_tokenization, service_tier, metadata, speculation, prediction, stream_options, sampling_mask. Also add reasoning_history gated on supports_reasoning. Fix prompt_truncate_length to prompt_truncate_len to match the actual API parameter name. The old name was never in DEFAULT_CHAT_COMPLETION_PARAM_VALUES, so it always went to extra_body and was rejected by Fireworks; it never actually worked. Normalize reasoning_effort boolean values to strings: True becomes "medium", False becomes "none". The Fireworks OpenAPI schema documents these as accepted types, but the server rejects non-string values with HTTP 400 in practice. Integers pass through as-is since the server is expected to validate them. Auto-inject stream_options.include_usage=true when stream=true and the user has not explicitly set stream_options. Without this, Fireworks returns null usage in all streaming chunks, which is inconsistent with the non-streaming behavior where usage is always present. If the user explicitly sets include_usage=false, it is preserved. Capture Fireworks-specific response fields in transform_response(): perf_metrics, prompt_token_ids, raw_output, and token_ids are now extracted from the response and stored in response._hidden_params (fireworks_perf_metrics, fireworks_prompt_token_ids, fireworks_raw_outputs, fireworks_token_ids) so they are accessible to logging, the proxy, and downstream consumers when the corresponding request parameters are enabled. Remove deprecated document inlining logic. Document inlining was deprecated on 2025-06-30 (https://docs.fireworks.ai/updates/changelog#-document-inlining-deprecation). This removes _add_transform_inline_image_block(), the file-to-image_url migration in _transform_messages_helper(), and the disable_add_transform_inline_image_block lookup. Current models that support image input do so natively as VLMs. cache_control, provider_specific_fields, and thinking_blocks stripping is retained. Update get_provider_info() to look up supports_vision and supports_pdf_input from the model cost map instead of hardcoding both to True (which was based on the now-deprecated document inlining). supports_prompt_caching remains True. API docs: https://docs.fireworks.ai/api-reference/post-chatcompletions Reasoning guide: https://docs.fireworks.ai/guides/reasoning Prompt caching: https://docs.fireworks.ai/guides/prompt-caching * fix fireworks chat api surface gaps * Scope Fireworks thinking param to reasoning models * style: fix black formatting * fix(test): update minimax-m3 expected_vision to True * test: cover non-dict content branch in transform_messages_helper * fix(fireworks_ai): remove metadata from supported params to prevent internal metadata disclosure * test(fireworks_ai): replace stale document-inlining capability test The CircleCI-only litellm_utils_tests suite still asserted the old behavior where document inlining made every Fireworks model report supports_pdf_input and supports_vision as True. That premise was removed in this change, so the test now reflects cost-map-driven capabilities: unmapped models no longer advertise vision/PDF support while mapped VLMs like minimax-m3 still do. * test(fireworks_ai): add end-to-end regression for native OpenAI params The existing coverage for the newly supported OpenAI-native params asserted list membership in get_supported_openai_params or called map_openai_params with a hand-built dict, both of which bypass the get_optional_params gate (DEFAULT_CHAT_COMPLETION_PARAM_VALUES). That gate is what previously raised UnsupportedParamsError for seed, top_logprobs, logit_bias, prompt_cache_key, service_tier and prediction when drop_params=False. Assert the full path so a revert of the supported-params additions fails the test instead of passing a shallow membership check. * test(fireworks_ai): fix test isolation in vision/inlining tests Use monkeypatch in test_fireworks_ai_vision_capability_from_cost_map so the LITELLM_LOCAL_MODEL_COST_MAP env var and litellm.model_cost are restored after the test instead of leaking global state into the rest of the process. Switch the document-inlining integration tests off deepseek-v3p1, whose supports_vision is null in the cost map, onto minimax-m3 which is explicitly supports_vision:true. The pass-through assertions no longer depend on a model incidentally not being marked non-vision. * fix(fireworks_ai): gate image rejection on exact vision capability The image_url rejection read supports_vision via _get_model_cost_capability, which falls back to hyphen-boundary substring matching when no exact cost-map entry exists. A custom or fine-tuned model id that merely contains a known non-vision model's short name (e.g. an id ending in -glm-5p2) inherited that entry's supports_vision:false and hard-failed valid image_url blocks on a vision-capable deployment. Split the exact candidate-key lookup into _get_model_cost_capability_exact and use it for the hard rejection so a fuzzy match can never block images; the substring fallback stays a soft signal for capability reporting. Also rewrites the fallback as a comprehension + max instead of an accumulating loop. * feat(fireworks_ai): surface response fields on streaming responses The Fireworks-specific response fields (perf_metrics, prompt_token_ids, per-choice raw_output and token_ids) were only captured into _hidden_params in transform_response, which runs for non-streaming completions; streaming chat went through the default OpenAI chunk handler and dropped them. Add a FireworksAIChatCompletionStreamingHandler that the provider now returns from get_model_response_iterator. It reuses one extraction helper with transform_response and attaches the fields to each streamed chunk's provider_specific_fields, which is the channel litellm preserves when it rebuilds streamed chunks (per-chunk _hidden_params is not carried through). Per-choice token_ids/raw_output ride the content chunks; response-level perf_metrics/prompt_token_ids ride the final usage chunk. Covered by an end-to-end streaming test through litellm.completion(stream=True). --------- Co-authored-by: Ahmad Shahzad <ahmad@shahzad.dev> Co-authored-by: Graham Neubig <398875+neubig@users.noreply.github.com>
* feat: plugin architecture — toggle between AI Gateway and external plugins
Adds a generic plugin system so any external service can register with
litellm and appear as a mode in the UI alongside the AI Gateway.
Backend (litellm/proxy/plugin_routes.py — new):
- GET /api/plugins: returns registered plugins from config; returns
plugin_key only to authenticated requests
- ANY /plugin-proxy/{name}/{path}: reverse proxies API calls to plugin
Config:
general_settings:
plugins:
- name: my-plugin
display_name: My Plugin
url: https://my-plugin.example.com
plugin_key: sk-... # plugin auth key, passed to iframe
UI:
- PluginModeContext.tsx: fetches /api/plugins, persists mode to localStorage
- leftnav.tsx: mode switcher dropdown at top of sidebar; plugin mode shows
plugin-specific nav items
- layout.tsx: renders iframe to plugin URL in plugin mode; passes plugin_key
as ?token= for auto sign-in
Plugin contract: expose GET /api/plugin-manifest returning
{ name, display_name, nav_items[], capabilities[] }. No litellm changes
needed to add new plugins — config only.
Reference implementation: LiteLLM-Labs/litellm-agent-control-plane
* feat: add Plugins tab to Admin Settings UI
Allows admins to add/edit/delete plugin registrations directly in the
litellm UI under Admin Settings > Plugins, instead of editing config.yaml.
Uses existing /config/field/update API to persist to general_settings.plugins.
Each plugin entry has: name (identifier), display_name, url, plugin_key.
* fix(ci): black, prettier, eslint, async-client violations
- Black: format plugin_routes.py and proxy_server.py
- Prettier: format PluginModeContext.tsx and PluginSettings.tsx
- ESLint: replace raw fetch() with createApiClient in PluginModeContext
- ESLint: use lazy useState initializer to read localStorage instead of
calling setModeState inside useEffect (react-hooks/set-state-in-effect)
- code-quality: replace httpx.AsyncClient per-request with
get_async_httpx_client() shared client (avoids +500ms overhead)
* fix(ci): schema.d.ts regen, Black proxy_server.py, ApiClientConfig fix
- Regenerate schema.d.ts for new /api/plugins routes
- Re-run Black 26.3.1 on proxy_server.py (matches CI version)
- Fix PluginModeContext: createApiClient requires getBaseUrl field
* fix: security hardening + CI fixes
Security (Greptile 1/5 → addressing all 3 findings):
- plugin_routes.py: add Depends(user_api_key_auth) to both /api/plugins
and /plugin-proxy/{name}/{path} — was an unauthenticated open relay
- plugin_routes.py: /api/plugins now returns plugin_key only to callers
with a valid litellm token (enforced by user_api_key_auth), not just
any header presence
- layout.tsx: replace ?token= URL param with postMessage(targetOrigin)
— token no longer exposed in browser history / logs / Referer headers
CI:
- backend/routes/allowlist.py: add /api/plugins and /plugin-proxy/ to
fix test_gateway_plus_backend_covers_full_app
- schema.d.ts: regenerated with enterprise routes included
- Black + Prettier formatting
* fix: regenerate schema.d.ts with enterprise routes included
Install litellm-enterprise workspace member before gen:api so audit and
other enterprise routes appear in the generated types, matching what CI
produces with uv sync --extra proxy.
* fix: exclude plugin routes from OpenAPI schema, restore upstream schema.d.ts
Both /api/plugins and /plugin-proxy/ are internal infrastructure routes,
not part of the public litellm API surface. Marking include_in_schema=False
prevents Python-version-dependent schema diffs from breaking the schema
sync check across different environments.
* fix: schema.d.ts - passing schema base + exact plugin route types from openapi-typescript
Use the CI-correct schema from a recently passing branch as base, then
inject plugin route entries (paths + operations) generated by
openapi-typescript from the plugin routes' OpenAPI spec. This avoids
Python-version-dependent formatting differences that made local gen:api
produce incorrect output.
* fix: schema.d.ts - insert plugin ops at correct route registration position
Plugin operations belong after delete_memory_v1_memory__key__delete
(memory_router is included immediately before plugin_router in proxy_server.py),
not after list_organization which is alphabetically but not registration-order.
* fix: schema.d.ts - correct op positions from hunk analysis
list_plugins_api_plugins_get goes after event_logging_batch op (hunk 1: line 33583).
plugin_proxy ops go after create_policy_policies_post (hunk 2: line 44634).
Previous location after delete_memory_v1_memory__key__delete was wrong.
* fix: schema.d.ts - proxy ops go before create_policy (after otel_spans)
* fix(security): restrict plugin_key to proxy_admin role only
Veria finding: plugin_key was returned to any authenticated caller.
Now only proxy_admin users receive plugin credentials in /api/plugins
response — regular internal users see plugin name/url but not the key.
* fix: update schema.d.ts docstring for list_plugins
* fix: clear plugin registry on config reload (Greptile medium)
register_plugins_from_config now replaces the registry instead of
merging, so plugins removed from config are unreachable immediately
without requiring a process restart.
* fix(security): encrypted token exchange for plugin iframe — no raw litellm credential exposure
The dashboard was sending the user's litellm bearer token to the plugin
iframe via postMessage, allowing a compromised plugin to act as that user.
Fix:
- GET /api/plugins/auth-token: proxy encrypts caller token with Fernet
keyed from LITELLM_SALT_KEY, returns ciphertext only
- UI postMessages the ciphertext (not raw token) to the iframe
- Plugin decrypts server-side with same LITELLM_SALT_KEY via POST /api/plugin-auth
- Raw litellm credential never leaves the proxy in plaintext
Additional hardening already in place:
- /plugin-proxy/* strips Authorization header, injects plugin_key instead
- plugin_key only returned to proxy_admin role via /api/plugins
- Plugin registry cleared (not merged) on config reload
Adds docs/plugin_architecture.md with plugin integration guide.
* fix(code-quality): use get_async_httpx_client in plugin_proxy
* fix: add /api/plugins/auth-token to schema.d.ts
* fix: use apiClient for auth-token fetch, copy correct layout.tsx and PluginModeContext
- Replace raw fetch() with createApiClient (fixes no-restricted-syntax ESLint rule)
- Copy correct layout.tsx with encrypted token + postMessage approach
- Copy correct PluginModeContext.tsx with accessToken prop injection
- Update schema.d.ts with auth-token path and operation entries
* fix: add plugin_auth_token operation to schema.d.ts
* fix(security): strip cookie/set-cookie + fix compressed response headers
Veria High: cookie header was forwarded to plugin backends allowing
capture of litellm JWT session cookies. Strip cookie on requests.
Strip set-cookie from responses so plugins cannot overwrite litellm
session cookies.
Greptile P1: httpx decompresses responses but resp.headers still
contained Content-Encoding/Transfer-Encoding/Content-Length from the
wire. Forwarding these caused double-decompression and length errors.
Now filtered via _RESPONSE_STRIP before returning to the browser.
* fix: update plugin_key help text — no more ?token= reference
* fix(security): disable follow_redirects to prevent SSRF
follow_redirects=True allowed a plugin backend to return a 3xx to an
internal URL, causing the proxy to fetch that internal service and relay
the response. Disabled: clients handle their own redirects.
* fix: forward user identity headers to plugin to address confused deputy
Plugins receive X-LiteLLM-User-Id and X-LiteLLM-User-Role so they can
enforce their own per-user access control before acting on requests that
arrive with the shared plugin_key credential.
* fix(security): restrict /plugin-proxy/* to proxy_admin role
Closes the confused deputy gap: regular users could invoke any plugin
endpoint using the shared plugin_key as a bearer credential. Now only
proxy_admin callers can use the plugin proxy route.
Plugin UIs communicate with the plugin service directly via the iframe
(using the encrypted token exchange); this proxy route is for
administrative/server-to-server access only.
* fix: update schema.d.ts for admin-only proxy route docstring
* fix(bug): use PassThroughEndpoint instead of None for get_async_httpx_client
get_async_httpx_client(llm_provider=None) raises TypeError — the function
concatenates the provider string and None is not a str. Use
httpxSpecialProvider.PassThroughEndpoint, the enum value used by other
internal proxy pass-through routes.
* fix(security): add 30s TTL to encrypted plugin auth tokens
Veria medium: encrypted tokens had no expiry, allowing indefinite replay.
Fernet embeds a timestamp; decrypt_token now passes ttl=30 so tokens
older than 30 seconds are rejected even with a valid HMAC.
Plugin's /api/plugin-auth must call litellm within 30s of the iframe
receiving the postMessage — normal browser behavior, tight enough to
close the replay window.
* feat(ui): topnav plugin switcher, embed plugins at their root
Builds on the plugin architecture already on this branch (encrypted-token
postMessage handshake, /api/plugins, PluginSettings) and removes the parts of the
embed that assumed a specific plugin's shape.
The mode switcher moves out of the sidebar into the topnav and lists AI Gateway
plus each registered plugin by its display_name. Selecting a plugin hides
litellm's sidebar entirely and renders the plugin full-bleed at its root url; the
plugin draws its own navigation inside the iframe. This drops the hardcoded
"Agent Control Plane" label and the hardcoded Sessions/Agents/Routines/... nav
groups (agentControlPlaneMenuGroups / acpPagePaths) that only matched the agent
platform and 404'd for a plugin that serves only / (e.g. the chat UI). The
encrypted-token postMessage flow is unchanged.
Note: embedding at root means a plugin must route internally from /; plugins that
previously relied on the /sessions entrypoint should redirect from their root.
* fix(security): audience-scoped identity claim replaces litellm token
Veria: shared LITELLM_SALT_KEY with plugins + encrypting user bearer token
created delegation/impersonation risk.
Architecture change:
- /api/plugins/auth-token now issues a plugin-scoped identity CLAIM
{user_id, user_role, plugin, exp} encrypted with HMAC(LITELLM_SALT_KEY, plugin_name)
- Each plugin holds only its own HMAC-derived key; cannot forge claims for
other plugins or recover LITELLM_SALT_KEY
- Claim contains NO litellm bearer token — compromised plugin learns caller
identity only, cannot act as that user against the proxy
- 30s TTL enforced in both Fernet header and explicit exp field
- LAP /api/plugin-auth verifies claim, returns its own master key to browser
(LAP key never exposed without valid claim)
* fix(plugins): allow registering plugins from the admin UI
Adding a plugin in the UI POSTs general_settings.plugins to /config/field/update,
which rejected it with "Invalid field=plugins passed in." because `plugins` was
not a field on ConfigGeneralSettings. Add a typed PluginConfig model and a
`plugins` field so the update validates and persists.
The in-memory plugin registry only refreshed at startup, so a plugin added via
the UI did not appear in /api/plugins (the view switcher) until a restart. Refresh
the registry from the new general_settings whenever the plugins field is updated.
While here, type the registry as dict[str, PluginConfig] instead of raw dicts so
list_plugins and plugin_proxy access typed attributes.
Fix the Plugin Key field copy: it is optional and only used to authenticate
litellm's server-side reverse proxy to a plugin's own backend
(/plugin-proxy/<name>/*). It is not involved in iframe auth, which forwards the
user's litellm token. Plugins that use the forwarded token leave it blank.
* fix: regenerate schema.d.ts with PluginConfig type and updated auth-token endpoint
* fix: use CI-compatible schema base for plugin entries
* fix(plugins): load DB-persisted plugins on startup
Plugins added through the admin UI are saved to DB general_settings, but the
registry only initialised from the YAML config at boot, so UI-added plugins
disappeared from the view switcher after a restart (the Plugins table still
listed them since it reads the DB directly). Refresh the registry from the DB
general_settings when it is merged in at startup.
* fix: add PluginConfig schema, plugins field, fix list_plugins return type
* fix: correct PluginConfig and plugins field positions in schema
* fix: correct plugins field position in schema (after pass_through_endpoints)
* fix: update PluginConfig.plugin_key description to match _types.py source
* fix: move plugins field after pass_through_request_timeout (correct alphabetical position)
* fix: redact plugin_key in config/field/info response
Veria medium: proxy_admin_viewer could read plugin_key via
GET /config/field/info?field_name=plugins. Now plugin_key is
replaced with *** in the response regardless of caller role.
The credential is only usable server-side.
* fix(security): correct plugin docs salt-key guidance, drop iframe clipboard-read
Address the two open Veria findings on the plugin architecture.
The plugin docs told external services to decrypt the iframe auth payload
with the proxy's LITELLM_SALT_KEY directly. That is both insecure and wrong:
the running code derives a per-plugin key as HMAC-SHA256(LITELLM_SALT_KEY,
plugin_name) and ships only a short-lived identity claim with no litellm
bearer token. Sharing the master salt would let a compromised plugin decrypt
any litellm secret recovered from a dump or backup. Rewrite the doc to match
the implementation: the proxy computes the per-plugin key once and provisions
it as a dedicated secret, the plugin validates the claim's audience and 30s
TTL, and LITELLM_SALT_KEY never leaves the proxy. Also refresh the now-stale
module and UI comments that still described the old shared-key token flow.
Drop clipboard-read from the plugin iframe's allow attribute so an untrusted
plugin can no longer read the user's clipboard; clipboard-write is retained.
* fix(ci): modernize PluginConfig typing, refresh budget baselines via merge
* fix(plugins): close iframe auth race and empty-plugins mode fallback
Address the two open Greptile behavioral findings.
The iframe auth handshake only posted the encrypted claim on the iframe's
`load` event. When the auth-token fetch resolved after the iframe had already
loaded, that listener never fired again and the plugin never received the
claim. Send the claim immediately as well as on subsequent loads so both
orderings are covered.
The plugin mode fallback guarded on a non-empty plugins list, so removing all
plugins left a user stranded on a stale mode with a blank iframe instead of
returning to the AI Gateway. Track a loaded flag and fall back to ai-gateway
once plugins have loaded whenever the stored mode is no longer registered,
including the empty-list case.
Add a PluginModeContext regression test covering the empty-list fallback and
the still-registered path.
* chore: re-trigger CI (GH Actions missed the prior head; re-run flaky live-API suites)
* fix(plugins): scope iframe auth claim to the active plugin
The iframe auth-token fetch omitted plugin_name, so the proxy always issued a
claim encrypted under the default plugin's per-plugin key. For any other active
plugin the iframe received a claim it could not decrypt and sign-in silently
broke, and because the cached claim was posted to whichever plugin was mounted,
a compromised iframe could replay the default plugin's claim. The active
plugin's name was also missing from the fetch effect's dependencies, so
switching plugins never refreshed the claim.
Request the claim with the active plugin's name, re-fetch when the active
plugin changes, and only deliver a claim while it still matches the mounted
plugin so one plugin's claim is never replayed to another.
* fix(plugins): never overwrite a stored plugin_key with its redaction placeholder
/config/field/info redacts every plugin_key to "***", so an admin editing a
plugin in the settings UI posted that placeholder straight back and the update
handler persisted "***" as the real credential, permanently destroying the key.
Preserve the stored credential on update: a blank or redacted plugin_key now
sources the existing key from the saved config, only a real value replaces it,
and a placeholder with no stored key is dropped rather than written. The edit
modal also starts the key field blank so an untouched save keeps the current
key, with the field labelled accordingly.
* fix(security): sandbox proxied plugin responses on the dashboard origin
The /plugin-proxy reverse proxy returned the plugin's body and content-type on
the litellm dashboard origin, so a compromised plugin could serve an HTML/JS
document that a proxy_admin navigates to and have it execute with the admin's
session against same-origin management APIs.
Force every proxied response inert: set Content-Security-Policy: sandbox (opaque
origin, scripts disabled) and X-Content-Type-Options: nosniff, applied after the
plugin's own headers so they cannot be overridden. The header construction moves
to a pure helper with a unit test covering the sandbox enforcement and the
existing wire/cookie header stripping.
* fix(plugins): recover to ai-gateway when the plugins fetch fails
The loaded flag was only set on a successful /api/plugins response, so when the
fetch failed a user with a plugin mode stored in localStorage stayed on the
blank plugin placeholder with no switcher to escape. Mark loaded in a finally
so the stored mode still falls back to ai-gateway on failure, and add a
regression test for the failed-fetch path.
* fix(security): never return plugin_key from /api/plugins
The plugin list endpoint returned the plaintext plugin_key to proxy_admin
callers, and the dashboard fetches /api/plugins on every load into React state,
so the credential was exposed to DevTools, memory snapshots, and any same-origin
script. The browser never uses the key; the proxy injects it server-side from
the registry and admin key management runs through the redacted
/config/field/info path. Drop plugin_key from the response for every caller and
update the regression test to assert it is never returned.
* chore(ui): regenerate schema.d.ts for updated list_plugins docstring
* fix(security): strip every litellm auth header before forwarding to plugins
The plugin reverse proxy only removed Authorization and x-api-key, but
user_api_key_auth also authenticates a caller via API-Key, x-goog-api-key,
Ocp-Apim-Subscription-Key, x-litellm-api-key, and any configured custom key
header. A malicious plugin could lure a proxy_admin into calling
/plugin-proxy/... with the litellm key in one of those headers; the request
authenticated locally and then forwarded the same key to the plugin, letting it
impersonate the admin.
Add a canonical SpecialHeaders.litellm_credential_header_names() that the auth
header enum is the single source for, and strip that whole set plus the live
general_settings.litellm_key_header_name from every forwarded request. New auth
headers added to SpecialHeaders are now stripped automatically. Regression tests
cover each credential header, the custom configured header, and the canonical
list's contents.
…riAI#30905) * feat(sandbox): code interpreter interceptor on the Responses API Route OpenAI's code interpreter to a configured sandbox (e2b) instead of OpenAI's container, with no client change. A client calls /v1/responses with a code_interpreter tool; the interceptor converts it to a function tool so the model emits the code, runs that code in the sandbox via the phase 1 primitive, feeds the result back, and lets the agentic loop continue. Reuses the existing agentic-loop hooks (no new hook methods). The anthropic agentic caller _call_agentic_completion_hooks gains an api_surface argument and a responses execute path (_execute_responses_agentic_plan re-calls aresponses); the responses handler invokes it after transforming the response. Web search and compression interceptors are untouched. Adds an api_base passthrough to the sandbox SDK and a sandbox_tools registry the proxy parses, so the interceptor resolves a named tool to provider/key/base. v0 limitation: no file upload or download yet; stdout and inline results flow back, attaching input files and downloading produced files do not. * feat(sandbox): re-inject code_interpreter_call so the response matches OpenAI The native OpenAI Responses code interpreter returns a code_interpreter_call output item (id, type, status, code, container_id, outputs) alongside the message. The interceptor now re-injects an equivalent item via async_post_agentic_loop_response_hook so a client gets the same response shape whether the code ran in OpenAI's container or the sandbox: build_plan records the executed code and the container id per call, and the post hook inserts the code_interpreter_call before the message in the final response output. * feat(sandbox): support streaming for the code interpreter interceptor A stream:true /v1/responses request with code_interpreter previously broke, because the agentic loop only runs on the non-streaming responses path. The interceptor now forces stream=False in the pre-call hook (so the loop runs in the sandbox) and the responses handler wraps the completed response back into a synthetic stream via MockResponsesAPIStreamingIterator, so the caller still gets SSE. The follow-up call and nested wrapping are guarded by stripping the converted-stream flag from the follow-up request and only wrapping at the outermost call (agentic loop depth 0). * fix(lint): use builtin generics in code interpreter interceptor to satisfy UP006 budget * fix(code-interpreter): gate sandbox execution, delete sandboxes, harden registry Gate the agentic loop on a server-set interception marker and re-check provider scope so an authenticated caller cannot trigger sandbox code execution by naming their own function tool litellm_code_execution; the marker is stripped from client requests at the proxy boundary and only set when the pre-call hook actually converts a native code_interpreter tool. Delete the sandbox once the final response is assembled instead of leaking it until its own timeout, and prune expired cache entries by deleting their containers too. Resolve sandbox params once at create time and reuse them for run and delete. Clear the sandbox-tool registry before re-registering so stale tools do not survive a config reload. * fix(lint): use PEP 604 X | None unions to satisfy UP045 budget * test(code-interpreter): cover execution-error and unparseable-argument tool-call paths * fix(code-interpreter): rewrite forced code_interpreter tool_choice to the function tool * test(sandbox): cover sandbox-tool registry resolution, reload clearing, and secret lookup * test(code-interpreter): cover dict-shaped responses and object-attribute tool-call detection * fix(proxy): strip client-supplied _code_interpreter_interception_converted_stream A client could inject the converted-stream marker to force the completed response to be re-wrapped as a synthetic SSE stream it never requested. Add it to the untrusted root control fields alongside the other agentic loop markers so the proxy strips it at the request boundary. * fix(code-interpreter): isolate sandboxes by server-minted key and clear registry on tool removal Key the per-request sandbox cache on a server-minted random token instead of the caller-controlled litellm_call_id (sourced from the x-litellm-call-id header). Two concurrent requests that send a colliding call id can no longer share a sandbox container and read each other's code or files. The token is minted in the pre-call hook when interception activates, stripped from client requests at the proxy boundary, and survives the server-driven followups so a single request still reuses one sandbox across the agentic loop. Register sandbox tools unconditionally with an empty-list fallback so a config reload that removes sandbox_tools clears the previously registered credentials instead of leaving them resolvable in the process. * refactor(sandbox): swap the tool registry atomically on reload Build the new registry and rebind it in one assignment instead of clearing then repopulating in place, so a concurrent resolve_sandbox_tool can never observe a transiently empty or half-populated registry during a config reload. clear_sandbox_tools now delegates to register_sandbox_tools([]). * fix(code-interpreter): cap caller loop limit and emit OpenAI-shaped outputs Strip max_agentic_loops at the proxy request boundary so an authenticated caller cannot raise the agentic-loop ceiling to drive many upstream model calls and sandbox executions from a single request; the loop stays bounded by the server default. Populate the re-injected code_interpreter_call.outputs with an OpenAI-shaped logs array ([{"type": "logs", "logs": stdout}], or [] when there is no stdout) instead of None, so clients that iterate over outputs or validate the response through the OpenAI SDK's Pydantic model do not break.
…edpyright can analyze it (BerriAI#30802)
Owner
Author
|
Closing accidental fork-local PR; this branch is intended for upstream BerriAI/litellm. |
![github-advanced-security[bot]](https://avatars.githubusercontent.com/in/57789?s=60&v=4){kind=small}
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| @@ -0,0 +1,420 @@ | |||
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g({data:e=[],columns:g,isLoading:f=!1,defaultSorting:h=[],pagination:b,onPaginationChange:_,enablePagination:y=!1,onRowClick:x}){let[v,w]=n.default.useState(h),[S]=n.default.useState("onChange"),[j,C]=n.default.useState({}),[$,k]=n.default.useState({}),O=(0,i.useReactTable)({data:e,columns:g,state:{sorting:v,columnSizing:j,columnVisibility:$,...y&&b?{pagination:b}:{}},columnResizeMode:S,onSortingChange:w,onColumnSizingChange:C,onColumnVisibilityChange:k,...y&&_?{onPaginationChange:_}:{},getCoreRowModel:(0,o.getCoreRowModel)(),getSortedRowModel:(0,o.getSortedRowModel)(),...y?{getPaginationRowModel:(0,o.getPaginationRowModel)()}:{},enableSorting:!0,enableColumnResizing:!0,defaultColumn:{minSize:40,maxSize:500}});return(0,t.jsx)("div",{className:"rounded-lg custom-border relative",children:(0,t.jsx)("div",{className:"overflow-x-auto",children:(0,t.jsx)("div",{className:"relative min-w-full",children:(0,t.jsxs)(a.Table,{className:"[&_td]:py-2 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text-blue-500"}),desc:(0,t.jsx)(m.ChevronDownIcon,{className:"h-4 w-4 text-blue-500"})})[e.column.getIsSorted()]:(0,t.jsx)(u.SwitchVerticalIcon,{className:"h-4 w-4 text-gray-400"})})]}),e.column.getCanResize()&&(0,t.jsx)("div",{onMouseDown:e.getResizeHandler(),onTouchStart:e.getResizeHandler(),className:`absolute right-0 top-0 h-full w-2 cursor-col-resize select-none touch-none ${e.column.getIsResizing()?"bg-blue-500":"hover:bg-blue-200"}`})]},e.id))},e.id))}),(0,t.jsx)(s.TableBody,{children:f?(0,t.jsx)(d.TableRow,{children:(0,t.jsx)(c.TableCell,{colSpan:g.length,className:"h-8 text-center",children:(0,t.jsx)("div",{className:"text-center text-gray-500",children:(0,t.jsx)("p",{children:"🚅 Loading models..."})})})}):O.getRowModel().rows.length>0?O.getRowModel().rows.map(e=>(0,t.jsx)(d.TableRow,{onClick:()=>x?.(e.original),className:x?"cursor-pointer hover:bg-gray-50":"",children:e.getVisibleCells().map(e=>(0,t.jsx)(c.TableCell,{className:`py-0.5 overflow-hidden ${"actions"===e.column.id?"sticky right-0 bg-white shadow-[-4px_0_8px_-6px_rgba(0,0,0,0.1)] w-[120px] ml-8":""} ${e.column.columnDef.meta?.className||""}`,style:{width:"actions"===e.column.id?120:e.column.getSize(),position:"actions"===e.column.id?"sticky":"relative",right:"actions"===e.column.id?0:"auto"},children:(0,i.flexRender)(e.column.columnDef.cell,e.getContext())},e.id))},e.id)):(0,t.jsx)(d.TableRow,{children:(0,t.jsx)(c.TableCell,{colSpan:g.length,className:"h-8 text-center",children:(0,t.jsx)("div",{className:"text-center text-gray-500",children:(0,t.jsx)("p",{children:"No models found"})})})})})]})})})})}e.s(["ModelDataTable",()=>g])},339019,865361,e=>{"use strict";var t,i,o=((t={}).AUDIO_SPEECH="audio_speech",t.AUDIO_TRANSCRIPTION="audio_transcription",t.IMAGE_GENERATION="image_generation",t.VIDEO_GENERATION="video_generation",t.CHAT="chat",t.RESPONSES="responses",t.IMAGE_EDITS="image_edits",t.ANTHROPIC_MESSAGES="anthropic_messages",t.EMBEDDING="embedding",t),n=((i={}).IMAGE="image",i.VIDEO="video",i.CHAT="chat",i.RESPONSES="responses",i.IMAGE_EDITS="image_edits",i.ANTHROPIC_MESSAGES="anthropic_messages",i.EMBEDDINGS="embeddings",i.SPEECH="speech",i.TRANSCRIPTION="transcription",i.A2A_AGENTS="a2a_agents",i.MCP="mcp",i.REALTIME="realtime",i.INTERACTIONS="interactions",i);let a={image_generation:"image",video_generation:"video",chat:"chat",responses:"responses",image_edits:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings"};e.s(["EndpointType",()=>n,"getEndpointType",0,e=>{if(console.log("getEndpointType:",e),Object.values(o).includes(e)){let t=a[e];return console.log("endpointType:",t),t}return"chat"}],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:i,accessToken:o,apiKey:a,inputMessage:r,chatHistory:l,selectedTags:s,selectedVectorStores:d,selectedGuardrails:c,selectedPolicies:u,selectedMCPServers:p,mcpServers:m,mcpServerToolRestrictions:g,selectedVoice:f,endpointType:h,selectedModel:b,selectedSdk:_,proxySettings:y}=e,x="session"===i?o:a,v=window.location.origin,w=y?.LITELLM_UI_API_DOC_BASE_URL;w&&w.trim()?v=w:y?.PROXY_BASE_URL&&(v=y.PROXY_BASE_URL);let S=r||"Your prompt here",j=S.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),C=l.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),$={};s.length>0&&($.tags=s),d.length>0&&($.vector_stores=d),c.length>0&&($.guardrails=c),u.length>0&&($.policies=u);let k=b||"your-model-name",O="azure"===_?`import openai | |||
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