fix(redis): prevent forcing SSLConnection when ssl=False in connection pool by Jacopos311 · Pull Request #30770 · BerriAI/litellm

Jacopos311 · 2026-06-18T17:48:22Z

…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.

… subclass (BerriAI#29869)

…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#29951)

…rriAI#30648) * ci: drop redundant mypy type-check gate, standardize on basedpyright Type checking ran both mypy (via the pydantic.mypy plugin) and basedpyright. pydantic v2 emits dataclass_transform, so basedpyright understands models natively with no plugin, and its gated rules already cover what the mypy pass caught (no-untyped-def, no-any-return, valid-type, import-not-found all map to basedpyright equivalents). Running both meant two checkers, two budgets, and a plugin only mypy could load. This removes the mypy type-check gate: the lint-mypy/lint-mypy-budget-update Makefile targets, the CI MyPy step, mypy-code-budget.json, the budget-ratchet entry, and the vestigial [tool.mypy] pydantic plugin block (the gating pass used litellm/mypy.ini, which never loaded the plugin). type_check_gate.py is specialized to basedpyright since the mypy parsing path is now unused. mypy stays a dev dependency because the Any-discipline gate (scripts/check_any_discipline.py) imports it as a library to detect Any-typed values; it is no longer run as a type checker. * ci: remove the Any-discipline gate, rely on basedpyright's reportAny The Any-discipline gate (scripts/check_any_discipline.py) was the last consumer of mypy: it imported mypy as a library to detect values whose inferred type contains Any, gated per-file against any-discipline-budget.json. basedpyright already reports the same class of finding through reportAny/reportExplicitAny, which are gated tree-wide in basedpyright-code-budget.json, so the separate gate (and the mypy dependency behind it) is redundant. Removes the gate end to end: check_any_discipline.py and its test, the any-discipline CI job, the lint-any/lint-any-budget-update Makefile targets, any-discipline-budget.json, litellm/mypy.ini, the .mypy_cache_any references, and mypy from the dev dependencies. budget_ratchet_check.py drops the any-discipline entry and the now-unused zero-floor mechanism (rewritten as a comprehension). check_type_discipline.py drops the any-ok suppression token, since # any-ok suppressed only the deleted gate; the 134 now-orphaned # any-ok comments across 14 files are stripped (they never affected basedpyright, which uses # pyright: ignore). uv.lock is intentionally left untouched: uv still considers it consistent with the mypy-removed pyproject (uv lock --check and uv sync --frozen both pass), and a relock bumps 30+ unrelated packages because of the moving exclude-newer window. A future intentional relock will prune the now-unreferenced mypy entry. * build: relock to drop mypy from uv.lock CI's uv 0.10.9 honors the repo's exclude-newer window and correctly flags the lockfile as out of sync once mypy leaves pyproject; my earlier local uv 0.8.17 could not parse exclude-newer and silently passed --check. Relocking with the pinned CI version removes only mypy and its transitive librt, with no other version changes.

…uardrail traces (BerriAI#30659) The OpenAI moderation guardrail (and the ai-platform-moderation guardrail built on it) stamped the whole moderation model response into the guardrail trace as guardrail_response. That blob carries the full category_scores map plus categories and category_applied_input_types, which on OTEL backends that index span attributes (for example ELK, which caps indexed attribute values at 1024 chars) overflows the limit and gets truncated, so the violated categories cannot be reliably searched. Extract the flagged category names from the moderation response and pass them through tracing_detail to add_standard_logging_guardrail_information_to_request_data, mirroring the Bedrock hook. Both the legacy and v2 OTEL integrations already read violation_categories off the standard logging guardrail information and emit it as a short, queryable guardrail_violation_categories attribute, so dashboards can group and filter by violation category without parsing the large guardrail_response blob. Resolves LIT-3801

…BerriAI#30495) * fix(proxy): resolve list files credentials from team BYOK deployments GET /v1/files without target_model_names now prefers the team's own deployment (model_info.team_id) over shared global provider keys, so JWT team auth lists files against the correct upstream account. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): scope list files credential lookup to team allowlist Remove the unrestricted deployment scan that could leak global provider keys to teams without access, normalize all-proxy-models to the team-scoped model list, and fix TID251 violations by using dict instead of Dict/Any. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>

…er restarts (BerriAI#30601) Setting --max_requests_before_restart alone recycles every worker at almost the same time once they have served a similar number of requests, which under sustained load can drop a whole pod's capacity at once roughly every 7-10 days. This exposes a jitter knob that adds a random amount in [0, jitter] to the restart threshold per worker so restarts are staggered. It maps to uvicorn's limit_max_requests_jitter and gunicorn's max_requests_jitter. uvicorn only gained limit_max_requests_jitter in 0.41.0 while litellm still allows uvicorn>=0.33.0, so the uvicorn path feature-detects the parameter via the Config signature and warns instead of crashing on older versions. The flag has no effect without --max_requests_before_restart, so the kwarg is not forwarded in that case and a warning is printed on both the uvicorn and gunicorn paths. Resolves LIT-3774

* fix(health): correct bedrock embedding health checks Health checks for Bedrock embedding deployments failed in two ways. A deployment configured without an explicit model_info.mode was probed as chat, so max_tokens was injected and Bedrock embeddings rejected it with 400 "extraneous key [max_tokens]". Separately, stripping the bedrock/ routing prefix dropped the provider, so a cross-region inference-profile id like us.cohere.embed-v4:0 failed downstream with "LLM Provider NOT provided". Resolve the deployment mode from the model cost map (which understands the bedrock/ and us./eu./apac. prefixes) before deciding whether to inject max_tokens, and pin custom_llm_provider to bedrock when stripping the prefix so the bare model id still resolves. ahealth_check now accepts any string mode so the resolved embedding mode routes the probe to the embedding handler. * fix(health): preserve explicit custom_llm_provider on bedrock probe The bedrock prefix-strip pinned custom_llm_provider to bedrock unconditionally, so a deployment that set custom_llm_provider: bedrock_converse had it overwritten at health-check time and the probe hit the Invoke endpoint instead of Converse, a different request format that can report a spurious failure. Only fill in bedrock when the deployment left the provider blank, which still resolves bare cross-region ids like us.cohere.embed-v4:0 while leaving an explicit provider untouched. * test(health): assert resolved mode reaches the ahealth_check probe The existing tests check _resolve_health_check_mode and the params builder in isolation, but nothing verified that _run_model_health_check actually threads the resolved mode into litellm.ahealth_check. Without that, a refactor that probed with model_info.get("mode") again would reintroduce the chat fallback for embedding deployments while every test stayed green. This drives _run_model_health_check with a bedrock embedding deployment and asserts the probe is called with mode=embedding and the embedding params. * fix(health): resolve probe mode once for reasoning_effort and audio_speech The reasoning_effort and audio_speech branches read model_info.mode directly, so an embedding deployment declared without an explicit mode (the case this PR targets) was still treated as chat-like: a configured health_check_reasoning_effort got injected into the embedding probe, which embeddings reject as an unknown field, and an auto-detected audio_speech deployment never had its voice set. Resolve the effective mode once from the cost map and reuse it for the max_tokens, reasoning_effort, and audio_speech decisions so they all agree with the mode threaded into ahealth_check.

…ruby assistants timeout) (BerriAI#30685) * test(proxy): poll for image-gen spend instead of a fixed 5s sleep test_key_info_spend_values_image_generation failed once on litellm_internal_staging (pipeline 82282) with "spend did not increase on an identical repeat image call" (assert 0.24966 > 0.24966). The test made the second image call, slept 5s, then read the key's spend once. Response caching is commented out in proxy_server_config.yaml and no sibling test enables it, so the likely cause is async/batched spend logging not having flushed the repeat call's cost within 5s, which the build_and_test job aggravates by running every tests/test_*.py against one shared proxy under pytest -n 4. Poll the key's spend for up to 60s and break as soon as it grows. This removes the timing flake while preserving the canary: if the repeat were genuinely unbilled (for example the proxy response cache being on), spend never grows, the poll times out, and the assertion still fails. * test(pass_through): raise ruby assistants client request_timeout to 600s The streaming assistants example in openai_assistants_passthrough_spec.rb hit Net::ReadTimeout on litellm_internal_staging (pipeline 82280), failing at roughly 125s which is ruby-openai's default request_timeout of 120s. An assistants run with the code_interpreter tool can occasionally take longer than that to stream its first content back through the pass-through. Raise the client's request_timeout to 600s, matching the 600s timeout the Python pass-through e2e tests already use, so a slow-but-healthy streaming run no longer trips the default read timeout.

…ty reads (BerriAI#30683) test_basic_vertex_ai_pass_through_with_spendlog failed intermittently on litellm_internal_staging (pipelines 82155, 82196, 82209, 82230) with "Spend should be greater than before after 120s". Spend logging is async and batched, so the pass-through call's cost sometimes had not landed within the 120s poll window; one run ended on spend_after 0.0 because the final /global/spend/logs read returned nothing and "or 0.0" recorded that as zero spend. Widen the poll window to 240s and skip a transient empty read instead of treating it as 0.0, so a momentary endpoint hiccup on the last poll no longer fails an otherwise-billed call. The spend_after > spend_before assertion is unchanged, so a genuinely unbilled call still fails the test

…racking (BerriAI#30690) completion_cost read service_tier straight from the request optional_params and called service_tier.lower() on it, so a non-string value (dict/int/list, reachable via allowed_openai_params/drop_params) raised AttributeError. _response_cost_calculator swallowed that and returned response_cost=None, so the request's cost was silently lost. The isinstance guard alone is not enough: a surviving dict would crash again downstream in _get_service_tier_cost_key, which also calls .lower(). A request-level service_tier is only meaningful for pricing when it is a concrete billable tier string, so coerce any non-string value to None and defer to the tier the provider reports on the response usage, the same way "auto" already does. Adds a regression test driving a dict service_tier through completion_cost; it raises AttributeError before the fix and prices at the served tier after.

…orcement (BerriAI#30665) When general_settings.custom_auth is configured but custom_auth_run_common_checks is not set, project/team/org enforcement (budgets, model-level rate limits, and model-access lists) silently does nothing for custom-auth requests, since the centralized common_checks gate returns early for custom auth. Emit a startup warning pointing operators at the flag so the misconfiguration is visible instead of failing silently.

…oding (BerriAI#30600) acquire_lock stores the pod_id through async_set_cache, which JSON-encodes the value, so Redis holds the quoted string "<pod_id>". release_lock's Lua compare-and-delete compared the raw pod_id, so the equality check never matched and the lock was never deleted; it only cleared on TTL expiry. That stalled the spend-update drain whenever the leader pod restarted, letting the litellm_daily_*_spend_update_buffer lists grow unbounded in Redis. Compare against json.dumps(self.pod_id) so the release matches the stored value. The GET+DEL fallback already round-trips through async_get_cache and is unaffected. Co-authored-by: Claude <noreply@anthropic.com>

…ck (BerriAI#30695) Several CI jobs run the proxy against a model whose api_base is a shared "fake OpenAI endpoint" hosted on Railway (exampleopenaiendpoint-production.up.railway.app) so the E2E runs return canned responses without paying for or depending on a live provider. When that single deployment is down, every one of those jobs fails with "404 Application not found" even though nothing in the PR is broken; the whole repo is coupled to the uptime of one free external service. This adds tests/_fake_openai_endpoint_server.py, a small canned-response OpenAI-shaped server (chat, text, embeddings, streaming with usage, and the "429" rate-limit special case), and a reusable start_fake_openai_endpoint CircleCI command that runs it on host port 8190 and waits until healthy. The affected jobs now inject FAKE_OPENAI_API_BASE pointing at the local server, and the example configs they mount resolve api_base from that env var. The intentionally bad fallback URL in proxy_server_config.yaml is left untouched so the fallback test still exercises a failing upstream. Wired into build_and_test, litellm_router_testing, db_migration_disable_update_check, proxy_logging_guardrails_model_info_tests, proxy_spend_accuracy_tests, proxy_multi_instance_tests, proxy_store_model_in_db_tests, and proxy_build_from_pip_tests.

BerriAI#30704)

* feat(ui): migrate models page to App Router path route Cut the Models + Endpoints page over from the legacy ?page=models switch in (dashboard)/page.tsx to a path route at (dashboard)/models-and-endpoints. Adding the MIGRATED_PAGES entry repoints the sidebar link and redirects old ?page=models bookmarks to /ui/models-and-endpoints. ModelsAndEndpointsView already sourced identity from useAuthorized() and its own data via useModelsInfo(), so the token/keys/modelData/setModelData props were dead; drop them from ModelDashboardProps (and the parent's now-unused setModelData state) to sever the last of the shared-state coupling. * test(ui): scope migration smoke's shell probe to the exact sidebar link The migration smoke used a loose `locator("a", { hasText: "Virtual Keys" })` to assert the dashboard shell rendered. The Models + Endpoints page content itself links to the "Virtual Keys page", so on that route the substring filter matched two anchors and tripped Playwright strict mode. Match the sidebar link by its exact accessible name instead, which resolves to just the nav item.

) The `page == "pass-through-settings"` arm in (dashboard)/page.tsx is unreachable: it isn't a sidebar item and nothing in the app sets ?page=pass-through-settings. The Pass-Through Endpoints UI lives as a tab inside the Models + Endpoints view (ModelsAndEndpointsView renders PassThroughSettings), so the standalone switch arm is dead code. Remove it, its now-unused import, and the matching enum member in the e2e pages fixture.

…racking (BerriAI#30706) completion_cost extracted service_tier from the response object and the usage object without an isinstance guard, so a non-string value (e.g. a dict) flowed straight into _get_service_tier_cost_key and raised AttributeError on service_tier.lower(). completion_cost re-raises, so the request's cost was lost. PR BerriAI#30690 fixed only the request-level optional_params path. This extends the same guard to the response and usage paths by normalizing each extracted value: a non-string tier (and the routing-only "auto" sentinel) is not billable, so it coerces to None and pricing defers to the next concrete tier the provider served, falling back to standard pricing when none is present. Adds two regression tests driving a dict service_tier through completion_cost, one on the response object (defers to the served usage tier) and one on the usage object (prices at standard); both raise AttributeError before the fix.

@agent-shin

…and review-gate label lifecycle (BerriAI#30433) * feat(triage): auto-close stale PRs with Greptile score <4/5 Adds .github/scripts/close_low_quality_prs.py and a daily workflow that closes PRs which: - are open for at least 7 days, and - carry a most-recent greptile-apps review with Confidence Score <4/5, - and are not drafts or opt-out-labeled ('do not close', 'wip', etc.). Each closure posts an explanatory comment telling the contributor how to bring the PR back (rebase, re-request greptile, reopen at 4+/5). The 4/5 bar is already documented in the PR template (.github/pull_request_template.md), so this just enforces it. Tested with a dry run against the live BerriAI/litellm backlog of 1000 open PRs: 100 candidates identified, 598 PRs pass the bar (4+/5), 186 are too young, 97 are drafts, 19 lack any Greptile review and are left alone. Workflow defaults to closing 25 PRs/run as a safety net and supports workflow_dispatch with overrides (close=false for a dry run, custom min_age_days/min_score/limit). 18 unit tests cover score extraction (HTML/markdown/plain text, login variants, multi-review picks latest) and per-PR evaluation (drafts, opt-out labels, age, missing/passing/failing scores). Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * docs(templates): require expected/actual + QA proof for external contributions PR template: - Make the rubric explicit at the top: link an issue, OR provide a clear problem description + expected vs. actual + visual QA proof. - Add dedicated sections for each piece so the bot has a deterministic shape to read. - Keep the existing 'Linear ticket' section for internal contributors (they're exempt from the auto-triage rubric). Bug report template: - Split 'What happened?' into 'Actual behavior' + 'Expected behavior'. - Make logs/screenshot a required textarea. - Warning banner at the top tells external contributors that incomplete reports will be auto-closed (with re-evaluation on reopen). Feature request template: - Require a concrete use case + example in the motivation field, not just a one-liner pitch. - Same auto-triage warning banner. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(triage): Agent Shin LLM-as-judge for external PRs and issues Adds a new triage flow that evaluates external pull requests and issues against the project's contribution rubric and, when configured to do so, auto-closes non-conforming ones with an explanatory comment. Contributors can update + reopen to be re-evaluated. Scope: - Internal BerriAI contributors (author_association OWNER/MEMBER/COLLABORATOR) and bot accounts are skipped entirely. - 'Fixes BerriAI#1234' / 'Resolves https://github.com/.../issues/N' in the PR body short-circuits to PASS without burning LLM tokens. - LLM judge returns structured JSON (verdict, missing[], explanation); parser tolerates markdown fences and embedded JSON. - LLM errors NEVER close PRs/issues — failure surfaces as 'skip-llm-error'. Safety: - pull_request_target / issues triggers are FORCED dry-run in the workflow; only manual workflow_dispatch with close=true (and AGENT_SHIN_ENABLED=true) takes destructive action. - Default mode writes verdicts to GITHUB_STEP_SUMMARY only — no public comments until the team flips the AGENT_SHIN_ENABLED repo variable. - LLM uses an OpenAI-compatible endpoint (model and base URL configurable via repo variables; key via OPENAI_API_KEY secret). Files: - .github/scripts/triage_with_llm.py - judge orchestrator + CLI - .github/workflows/triage_pr_with_llm.yml - .github/workflows/triage_issue_with_llm.yml - tests/test_litellm/test_github_triage_with_llm.py - 33 unit tests End-to-end validated against four real PRs (BerriAI#28117 internal collaborator, BerriAI#28108 bot, BerriAI#28129 'Fixes BerriAI#28128', BerriAI#28116 no linked issue) and issue BerriAI#28132 with a stubbed LLM judge: each path produces the expected action. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(triage): scope Greptile auto-closer to external contributors + dry-run by default - close_low_quality_prs.py now filters by GitHub author_association via the REST API: PRs from OWNER / MEMBER / COLLABORATOR (and bot accounts) are skipped with a new 'skip-internal' summary bucket. - close_low_quality_prs.yml now defaults workflow_dispatch close=false, and ignores 'close=true' unless the new repo variable AGENT_SHIN_ENABLED is set to 'true'. Scheduled runs are dry-run only until the team flips that switch. - Updated unit tests: one new test asserting internal authors are skipped, and an autouse fixture treats unspecified test PRs as external so the rest of the suite still exercises the close path. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(workflows): scheduled cron closes PRs; safe --close strip in triage Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(triage): scheduled cron stays dry-run; dedent prompts before interpolation - close_low_quality_prs.yml: only workflow_dispatch with close=true (and AGENT_SHIN_ENABLED=true) actually closes PRs. Scheduled runs are always dry-run, matching the safety invariant documented for triage_pr/issue. - triage_with_llm.py: textwrap.dedent on an f-string with multi-line interpolated bodies fails because the body's 2nd+ lines start at column 0, making the common-indent zero. Dedent the static template first, then .format() the title/body in. Co-authored-by: Yassin Kortam <yassin@berri.ai> * Fix bugs in auto-close PR triage scripts - close_low_quality_prs.py: Treat author_association API lookup failures as internal (fail-safe) so transient errors don't cause internal contributors' PRs to be auto-closed. - triage_with_llm.py: Update summary heading from 'Would post comment:' to 'Posted comment:' since this branch only runs after the comment has already been posted. Co-authored-by: Yassin Kortam <yassin@berri.ai> * feat(triage): default Agent Shin to gpt-5.4-mini with reasoning_effort=none - Bump DEFAULT_MODEL from gpt-4o-mini to gpt-5.4-mini (more modern; 4M total context window per OpenAI catalog, JSON-schema response format, function calling all supported). - For gpt-5.x family models, pass reasoning_effort="none" via extra_body. gpt-5.x rejects temperature != 1 unless reasoning_effort is explicitly "none"; setting it lets us keep temperature=0 for deterministic JSON rubric judgments. extra_body works across openai SDK versions regardless of whether they natively type the kwarg. - For non-gpt5 overrides (TRIAGE_MODEL=gpt-4o-mini etc.), reasoning_effort is not sent. - 4 new unit tests cover: gpt-5.4-mini -> reasoning_effort=none, capitalized/dated gpt-5 variants -> reasoning_effort=none, gpt-4o-mini -> no extra_body, base_url passthrough. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(triage): bugbot — drop dead gh_json and fix --optout-label append-with-default - Removed the unused gh_json helper (bugbot low-severity dead code). - Replaced argparse `action="append", default=[...]` with default=None + DEFAULT_OPTOUT_LABELS fallback. The mutable-default + append combo silently APPENDS to the canonical defaults instead of replacing them, so --optout-label could not actually scope the opt-out list. - Added tests covering both the canonical default and the flag-replaces-defaults behavior. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(triage): bugbot — tighten linked-issue regex, fail-safe author_association, fix empty TRIAGE_MODEL Three independent bugbot findings against triage_with_llm.py: 1. LINKED_ISSUE_PATTERN included weak keywords (`see`, `ref`, `addresses`) so casual mentions like "See BerriAI#1234 for context" were short-circuited to pass-linked-issue without ever calling the LLM — contradicting the prompt's own "a bare issue number without a closing keyword counts only if it's clearly the related issue (not a passing mention)" rubric. Limit the regex to GitHub's documented PR-closing keywords (fixes/fix/fixed/closes/close/closed/resolves/resolve/resolved). 2. is_internal_contributor() treated an empty/missing author_association as external (eligible for the destructive close path), while the sibling is_external_pr_author() in close_low_quality_prs.py fail-safes the same case as internal. Align the two so a partial/unknown GitHub response can never make a PR eligible for auto-close. 3. argparse `default=os.environ.get("TRIAGE_MODEL", DEFAULT_MODEL)` returns the empty string when GitHub Actions exposes an unset repo variable as an empty-string env var (the optional vars.TRIAGE_MODEL case in the workflow). Use `os.environ.get(...) or DEFAULT_MODEL` so empty -> default, matching the existing OPENAI_BASE_URL pattern. Tests: - Casual mentions now must fall through to the LLM (parametrized); added an orchestration test ensuring "See BerriAI#1234" reaches the judge. - Empty/missing author_association now fails safe (parametrized). - Empty TRIAGE_MODEL env var falls back to DEFAULT_MODEL; explicit TRIAGE_MODEL is still honored. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(workflows): bugbot — gate Agent Shin --close on '= true' not '!= false' The PR and issue Agent Shin workflows gated the destructive --close flag with [ "${DISPATCH_CLOSE:-false}" != "false" ]. That pattern treats anything other than the literal string "false" as enabling closure — "True", "yes", "1", typos, accidental whitespace, etc. The workflow_dispatch input UI is a 'true'/'false' choice dropdown so the form is constrained, but the API (`gh workflow run -f close=...`) accepts any string, and a CI cron / external invoker passing a non-canonical truthy value would have silently enabled real contributor PR closures. Mirror the sibling Greptile closer's [ "${CLOSE_FLAG}" = "true" ] pattern: only the EXACT string "true" enables --close; every other value (including the unset/empty default) resolves to dry-run. This is the fail-safe philosophy applied everywhere else in this PR. Added tests/test_litellm/test_github_triage_workflows.py with two parametrized invariants: 1. The destructive gate uses '= "true"' for its env-var comparison (either bare '${ENV}' or '${ENV:-false}' form accepted), and never the fail-open '!= "false"' pattern. 2. Every destructive gate is also gated on AGENT_SHIN_ENABLED being "true" — either by entering the close branch on '=' or by bailing out early on '!=' — so flipping the repo variable off is a true kill switch regardless of per-run inputs. Manually verified the test fails on the buggy '!= "false"' pattern and passes on the fix, so it would have caught the regression at PR time. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(triage): close any PR (incl. drafts, any age); add @agent-shin reconsider flow Follow-up to PR BerriAI#28117. Three behavior changes + one new workflow, addressing the team's concerns on the original review: 1) Apply auto-close to ALL open PRs, not just those over a week old. - close_low_quality_prs.py: --min-age-days default flipped from 7 to 0. The flag is preserved as an opt-in safety net for one-off backfill runs that want to spare very-young PRs, but the daily scheduled sweep now closes external-author PRs as soon as Greptile scores them <4/5. - close_low_quality_prs.yml: workflow_dispatch input default also flipped to 0; doc comments updated. 2) Apply auto-close to draft PRs too. - close_low_quality_prs.py: removed the skip-draft branch in evaluate_pr. Drafts are NOT a free pass — the team's intent is 'open PR count == PRs internal collaborators need to action on', so a draft Greptile scored 2/5 still belongs in the closed bucket. Authors who genuinely need a long-lived draft can attach the 'wip' opt-out label, which is unchanged. - The 'skip-draft' action is gone; the 'wip' label still skips. 3) Address the 'OSS contributors cannot reopen a bot-closed PR' wrinkle. GitHub does NOT let an external (non-write-access) contributor reopen a PR that was closed by a bot or maintainer (long-standing limitation). The original PR's close-comments told contributors to 'Reopen the PR — I'll re-evaluate automatically', which is broken for the very audience this triage targets. Two changes: a) Reword every close-comment (Greptile sweep + Agent Shin PR close + Agent Shin issue close + PR template) to recommend: - Open a new PR with the updated branch (primary path). - Or comment '@agent-shin reconsider' on the closed PR for a re-evaluation that, on pass, reopens the PR via the bot's GH_TOKEN write access. b) Add the @agent-shin reconsider workflow: - .github/workflows/triage_reconsider.yml: new 'issue_comment'-triggered workflow. Authorizes only the PR/issue author or an internal collaborator (OWNER/MEMBER/COLLABORATOR), gated via a step output so unauthorized commenters never reach the destructive steps. Globally gated on AGENT_SHIN_ENABLED='true' (positive form, matching the test_github_triage_workflows guardrail patterns). - triage_with_llm.py: --reconsider mode. On a closed PR/issue, re-runs the LLM judge (or linked-issue regex short-circuit) and: - on pass: reopens via reopen_pr/reopen_issue + posts a 'Re-evaluated and reopened' comment. - on fail: leaves closed and posts a 'still missing X' comment so the contributor can iterate again. Reconsider-on-open is a no-op ('skip-not-closed'). Internal-author + bot-account skips still take priority over reconsider. 4) Greptile-on-closed-PRs question: the team asked whether Greptile can re-review a closed PR. Greptile's docs don't address this and we shouldn't promise behavior we can't verify, so the new close-comment wording does NOT instruct contributors to 're-request greptile on the closed PR'. Instead it points them at the new-PR path (which Greptile definitely reviews) or the @agent-shin reconsider trigger (which re-runs the LiteLLM-side rubric judge, not Greptile). Tests: 93 passing (was 59). - test_github_close_low_quality_prs.py: replaced 'skip drafts' test with 'closes drafts when score is low' + 'closes brand-new PR when min_age=0' + 'no skip when min_age=0'. The 'skip too young' assertion is preserved as opt-in. - test_github_triage_with_llm.py: 6 new TestTriageOrchestration cases for reconsider mode (skip-not-closed on open, reopen on pass, still-failing comment on fail, linked-issue short-circuit reopen, skip internal author in reconsider, reopen-issue on pass) + a new TestCloseCommentText class that pins the user-facing 'open a new PR' + '@agent-shin reconsider' wording. - test_github_triage_workflows.py: added triage_reconsider.yml to the destructive-gate guardrail table; AGENT_SHIN_ENABLED is its own destructive gate (no separate per-run flag needed). Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(triage): pin safe behavior for curly braces in PR/issue title+body Adds regression tests covering the bugbot high-severity finding that str.format() would crash on user-supplied content containing { or }. Empirically str.format() does NOT re-parse interpolated values — only the template literal is scanned for replacement fields — so the bug does not exist in the current code, but pinning the safe behavior prevents a future templating change from silently reintroducing it. Also pins the dedented prompt shape (no leading 8-space indentation on template lines) so a future change to the build_*_prompt functions can't silently regress the LLM judge prompt format on multi-line bodies. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(triage): bugbot — reconsider dry-run + bot-closed guard + rate limit Address three Greptile/veria-ai concerns on the @agent-shin reconsider flow: 1. **Reconsider had no dry-run path.** The previous reconsider mode ignored `--close` and always posted comments + reopened on a pass. A local operator running `python triage_with_llm.py --reconsider --pr N` would silently take destructive GitHub actions with no way to preview. Reconsider now honors `close=False` the same way regular triage does and returns `would-reopen` / `would-reconsider-still-failing` for step-summary rendering. 2. **Reconsider could reopen maintainer-closed PRs/issues** (Medium security finding from veria-ai). The workflow only checked that the commenter was authorized — it did NOT check that the most recent close was performed by Agent Shin. A contributor could comment `@agent-shin reconsider` on a PR a maintainer closed for non-rubric reasons (duplicate, security report, design rejection) and have the bot reopen it. Add `was_closed_by_agent_shin()` which inspects the issue events API for the most recent `closed` actor and only permits reopen when that actor matches the configured bot login (default `github-actions[bot]`, overridable via env). Fail-closed on missing events. 3. **No rate-limiting on the reconsider trigger.** Every `@agent-shin reconsider` comment burns CI minutes + an OpenAI API call. Add a 10-minute cooldown via `seconds_since_last_reconsider_verdict()` which greps the issue's comment list for the bot's own verdict marker (``). Inside the window the triage returns `skip-rate-limited` and the LLM never runs. Workflow update: - `triage_reconsider.yml` now passes `--close` only when `AGENT_SHIN_ENABLED=true`, matching the pattern of `triage_pr_with_llm.yml`. The script runs in both states so the verdict still appears in the step summary for QA. Tests: - Add 5 reconsider safety tests: dry-run for pass / fail / linked-issue short-circuit, bot-closed-guard refusal on maintainer close, rate-limit refusal inside the cooldown window, and cooldown-elapsed acceptance. - Add unit tests for `was_closed_by_agent_shin` (bot / maintainer / missing actor / env-override) and `seconds_since_last_reconsider_verdict` (no marker / multiple markers / non-bot comment with marker / bot comment without marker). - Pin the `` marker in both reopen and still-failing comments — dropping it would silently break the cooldown. Existing reconsider tests updated to pass `close=True` (the production path now) + stub the new guards via `_stub_reconsider_guards`. 112 tests pass (was 93). Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(triage): 1-day grace period before close + SwiftWinds immediate-close bypass - Add a 24-hour grace window between the first low-quality detection and the actual auto-close. The first detection posts a warning comment that explicitly says "You have 1 day to address this before this PR is auto-closed" and points the contributor at: * `@agent-shin reconsider` to request another look (and re-open) * `@greptileai` to request a fresh Greptile review — works even after the PR is closed - Both `triage_with_llm.py` (LLM judge) and `close_low_quality_prs.py` (Greptile-score closer) share the same `` HTML marker so a warning posted by either path is recognized by both. - Add IMMEDIATE_CLOSE_LOGINS = {swiftwinds} to bypass BOTH the grace period AND the dry-run / AGENT_SHIN_ENABLED gating. SwiftWinds is the user's personal account (no push permissions to litellm) used to dogfood the bot; user explicitly asked: "For SwiftWinds, just close immediately. Faster iteration that way." - Update the standard close comments to mention that `@greptileai` works even after the PR is closed. - Add 23 new tests covering: warn-grace on first detection, skip during grace window, close after grace expires, SwiftWinds bypass (case insensitive, with close=False, no random-login false positives), the grace-warning text invariants, and the SwiftWinds entry in the IMMEDIATE_CLOSE_LOGINS constant. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix: skip grace-period text in close comment for IMMEDIATE_CLOSE_LOGINS For PRs from IMMEDIATE_CLOSE_LOGINS (e.g. swiftwinds), evaluate_pr returns 'close' immediately without ever posting a grace warning, so the close comment should not reference a 1-day grace period. Make close_pr take a grace_period_elapsed flag, default True, and pass False from the main loop when the close path was the immediate-close branch. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(close-low-quality-prs): report actual closes in dry-run summary IMMEDIATE_CLOSE_LOGINS PRs are closed even when the global --close flag is not set, but the summary used the global dry-run flag to choose between 'would close' and 'closed'. Split the count so operators can see both actual closures and dry-run would-be closures. Co-authored-by: Yassin Kortam <yassin@berri.ai> * chore(triage): vendor Agent Shin (BerriAI#28117) onto demo branch Brings the Agent Shin OSS-triage scripts, workflows, issue/PR templates, and tests from PR BerriAI#28117 onto this branch so the new review-gate feature and its end-to-end demo are self-contained and runnable in CI. https://claude.ai/code/session_01XyyWa8t2VYmoGd6mKMEqkZ * feat(triage): add "ready for review" label lifecycle to Agent Shin Adds review_gate(), a state machine that keeps a `ready for review` label in sync with whether an external PR clears BOTH gates — the LLM rubric and Greptile's most recent confidence score: - pass (untagged) -> add label + "ready for review" / "all clear" comment - pass (already tagged) -> no-op (idempotent across re-runs) - regress (Greptile < 4/5 or QA proof removed) -> remove label + "what's missing" comment, PR stays open - recover after a regression -> "all clear again" comment + re-add the label - fail & untagged, < 24h old -> one-time "what's missing" notice (grace window) - fail & untagged, > 24h old -> close + comment (reopen via @agent-shin reconsider) The label itself is the persisted state, so comments fire only on transitions (never on every scheduled run). All side effects are gated behind --close, so the dry-run contract matches the existing triage flow. Lifecycle comments use hidden HTML markers and deliberately avoid the auto-close marker so they never trip the reconsider provenance check. Relocates the shared Greptile helpers (extract_greptile_score, SCORE_PATTERN, GREPTILE_BOT_LOGINS, parse_iso8601) into triage_with_llm.py so the daily sweep and the review gate read the score through one implementation, and adds the review_gate.yml workflow (dry-run unless AGENT_SHIN_ENABLED=true) plus 18 unit tests covering every branch and a full pass->regress->recover cycle. https://claude.ai/code/session_01XyyWa8t2VYmoGd6mKMEqkZ * Port review-gate feature from BerriAI#28758 onto BerriAI#28147 triage scripts Adds the "ready for review" label lifecycle (originally PR BerriAI#28758) on top of BerriAI#28147's refactored triage_with_llm.py. The original commit was authored against an older snapshot of BerriAI#28117 and could not be applied cleanly, so the additions were re-applied surgically: - New constants: READY_FOR_REVIEW_LABEL, DEFAULT_GRACE_DAYS, DEFAULT_MIN_GREPTILE_SCORE, READY/REGRESSED/WITHIN_GRACE markers, GREPTILE_BOT_LOGINS, SCORE_PATTERN, AGENT_SHIN_AUTO_CLOSE_MARKER. - New helpers: add_label, remove_label, extract_greptile_score, parse_iso8601 (the latter two mirrored from close_low_quality_prs.py so the daily sweep and the review gate read the score through the same logic). - New comment formatters: format_ready_for_review_comment, format_all_clear_comment, format_regression_comment, format_within_grace_comment. - New entry point: review_gate() implementing the pass/regress/recover state machine, with the label itself acting as persisted state so transition comments fire only on actual transitions. - main() learns --review-gate, --grace-days, --min-greptile-score and dispatches to review_gate() when the flag is set. Verified via tests/test_litellm/test_github_review_gate.py (18 tests) and the existing triage suites (144 more) — all 162 pass. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * agent_shin: extract shared constants/helpers; cover review_gate.yml in guardrail tests Bug 1: `triage_with_llm.py` and `close_low_quality_prs.py` each defined their own copies of `extract_greptile_score`, `parse_iso8601`, `GREPTILE_BOT_LOGINS`, `SCORE_PATTERN`, `GRACE_COMMENT_MARKER`, `GRACE_PERIOD_SECONDS`, `IMMEDIATE_CLOSE_LOGINS`, and `AGENT_SHIN_DEFAULT_BOT_LOGIN`. The comments explicitly said the two copies had to stay in sync, but nothing enforced it. A future change to one (e.g. extending `SCORE_PATTERN` for a new Greptile output format) would silently diverge from the other and the daily sweep and the LLM judge would disagree on which PRs have low scores. Extract these to `.github/scripts/agent_shin_shared.py` and re-export them from each script so the existing test attribute access (`triage_module.GRACE_COMMENT_MARKER`, etc.) keeps working without any test changes. Bug 2: `review_gate.yml` is a destructive workflow (close PRs, add/remove labels, post comments) with the same gating philosophy as the others (`AGENT_SHIN_ENABLED = "true"` + a per-run `CLOSE_FLAG = "true"`), but it was missing from `DESTRUCTIVE_GATE_ENV` in the guardrail tests. Add it so a future regression (e.g. flipping to `!= "false"`) is caught by the same parameterized invariants as every other workflow. Co-authored-by: Yassin Kortam <yassin@berri.ai> * agent_shin: fix bug bundle (gated LLM key, author-filtered marker dedup, dedup gh/grace helpers) Co-authored-by: Yassin Kortam <yassin@berri.ai> * agent_shin: fix review_gate close-after-regression and case-insensitive label match Co-authored-by: Yassin Kortam <yassin@berri.ai> * feat(triage): add one-shot 7-day heads-up sweep for Agent Shin rollout Adds a rollout-day workflow that comments on every open external PR/issue that the new triage bot WOULD auto-close, giving contributors 7 days to fix their description before any destructive action runs. Why now: merging this PR enables Agent Shin in dry-run. The follow-up "enact" PR (next Monday) flips the destructive paths on. Without this heads-up, contributors would get a close-comment on day 8 with no prior warning. The heads-up names the cutoff date, lists the rubric, calls out each PR/issue's specific missing pieces, and explains the recovery paths (@agent-shin reconsider for PRs, edit + reopen for issues). Files - .github/scripts/_agent_shin_actions.py — thin maybe_post_comment / maybe_close_* / maybe_add_label / etc. wrappers. Each is a single `if dry_run: log; return; else: call_through()` so a dry-run preview differs from the real run in exactly one call site per mutation. The call-through goes via `triage_with_llm.<name>` (module-qualified) so monkeypatching the underlying function in tests is reflected here. - .github/scripts/triage_rollout_heads_up.py — the sweep. Iterates every open PR + issue via `gh pr list` / `gh issue list`, runs the future rubric (review_gate for PRs, triage(kind="issue") for issues), and posts the heads-up on any item that would be auto-closed. Idempotent via a `` marker. Defaults to dry- run; --close opts in to real posts. --close-on overrides the cutoff date (defaults to today + 7 days). - .github/workflows/triage_rollout_heads_up.yml — one-shot workflow. Triggers on push to litellm_internal_staging filtered to the script path (fires on rollout merge) plus workflow_dispatch with a dry_run input that defaults to "true" for safe manual re-runs. - tests/test_litellm/test_triage_rollout_heads_up.py — 28 unit tests covering: the dry-run wrappers (each maybe_* gates correctly), the _would_be_closed predicate for PR vs. issue results, the comment formatter (cutoff/rubric/marker/recovery wording), per-item dispatch (skip-not-open, skip-internal-author, skip-already-notified, skip-passing, would-post/posted), and the sweep loop end-to-end. Local preview (no GitHub mutations): python3 .github/scripts/triage_rollout_heads_up.py --repo BerriAI/litellm Real run (what the workflow does): python3 .github/scripts/triage_rollout_heads_up.py --repo BerriAI/litellm --close TODO: replace the placeholder ROLLOUT_BLOG_URL with the canonical docs URL once the litellm-docs PR ships. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix: gate reconsider workflow OPENAI_API_KEY + remove dead actions wrappers - Mirror sibling Agent Shin workflows by only exposing OPENAI_API_KEY in triage_reconsider.yml when vars.AGENT_SHIN_ENABLED == 'true'. Previously the secret was unconditionally exposed, so any PR/issue author could trigger paid LLM calls by commenting '@agent-shin reconsider' even while the bot was supposed to be in dry-run. - Remove the six unused dry-run wrappers (maybe_close_pr, maybe_close_issue, maybe_reopen_pr, maybe_reopen_issue, maybe_add_label, maybe_remove_label) from _agent_shin_actions.py — only maybe_post_comment is used by rollout scripts. Drop the associated tests that exercised the now-removed functions. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix: address triage script edge cases - triage_rollout_heads_up.py: replace %-d strftime specifier (GNU-only) with portable day formatting so the script doesn't crash on Windows. - close_low_quality_prs.py: skip malformed JSON lines in fetch_pr_comments instead of letting one bad line abort the daily sweep, matching the pattern in triage_with_llm._iter_paginated_json. - triage_with_llm.py: move has_linked_issue short-circuit before build_pr_prompt to avoid unnecessary prompt construction on PRs that link an issue. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(scripts): per-PR error isolation and limit grace warnings in close_low_quality_prs - Wrap per-PR processing in try/except so a transient GitHub API failure on one PR no longer aborts the entire daily sweep (mirrors the pattern already used in triage_rollout_heads_up.py). - Have --limit bound *all* destructive write actions (closures and grace warnings combined), not just closures. Prevents a backlog of newly failing PRs from flooding contributors with comments in a single run. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(agent-shin): remove 1000-PR cap on bulk sweeps; sweep entire backlog Both bulk-sweep scripts hardcoded `gh {pr,issue} list --limit 1000`, and gh lists newest-first — so the OLDEST ~900 PRs and ~380 issues were silently dropped. That's exactly the stale backlog the daily closer and one-shot rollout heads-up exist to catch. Extract a single `list_open_items(kind, *, repo, fields)` helper into `agent_shin_shared.py` with `GH_LIST_ALL_LIMIT = 100_000` — a ceiling far above any realistic open backlog so gh paginates until the queue is exhausted. `fetch_open_prs` and `_list_open_numbers` both delegate to it, so the limit lives in exactly one place going forward. Verified live against BerriAI/litellm: - `fetch_open_prs` -> 1981 PRs (was 1000) - `_list_open_numbers(issue)` -> 1382 issues (was 1000) - `_list_open_numbers(pr)` -> 1981 PRs (was 1000) Adds 7 regression tests asserting the new limit is passed, the dedicated `gh {pr,issue} list` command + fields are used per kind, bad kind raises ValueError, and both callers delegate to the shared helper. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(agent-shin): require non-mocked end-to-end QA proof for PR pass The PR rubric previously passed any PR with a linked issue, regardless of whether it showed the fix actually working. Sample spot-check found 21/25 recent external PRs passing, including ones that linked an issue but provided zero QA evidence. Tighten the rubric so a pass now requires BOTH: (1) CONTEXT — a linked issue OR a clear problem description with expected-vs-actual behavior. (2) END-TO-END QA PROOF — at least one of: (a) screenshot(s) of the fix working, (b) screen recording / video, (c) specific commands actually run, paired with their real output, against the real system. Mocked unit tests, generic 'I tested it' claims, 'all tests pass' without output, and the linked issue itself are explicitly excluded from QA proof. Also add 'qa_proof_type' to the JSON schema so the per-PR report surfaces which kind of proof (or 'none') the judge saw. Re-sample on the same 25 recent external PRs shifts the verdict distribution from 21 pass / 4 fail to 4 pass / 21 fail, with zero prior-fails now passing — the stricter rule catches PRs that ship only with unit-test claims and no real integration evidence. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(agent-shin): link blog explainer from every action-required bot comment Adds "What's this and why am I getting it?" links to docs.litellm.ai/blog/ agent-shin-triage from the four comments contributors actually read when something went wrong: PR close, PR grace warning, issue close, issue grace warning. PR comments also link the rubric section directly from the QA-proof bullet so contributors can self-serve "what counts as proof" without pinging a maintainer. Pins the new guarantees in tests: blog link must appear in all four comments, and the PR close comment must continue to flag mocked-dependency unit tests as insufficient proof. The linked blog post is in BerriAI/litellm-docs PR BerriAI#240; the URL will 404 until that lands. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(review_gate): raise sweep limit from 1000 to 100000 to match GH_LIST_ALL_LIMIT gh lists newest-first, so capping at 1000 silently drops the oldest open PRs — exactly the stale ones the daily sweep is meant to reconcile. Use the same ceiling as agent_shin_shared.GH_LIST_ALL_LIMIT so the workflow sees the entire backlog. Co-authored-by: Yassin Kortam <yassin@berri.ai> * Fix three Agent Shin triage edge cases - review_gate: expire the regression-marker short-circuit after grace_days so PRs that were regressed and then abandoned can eventually be closed. - review_gate: when the rubric short-circuits to pass via the linked-issue regex but Greptile drags the PR below the bar, replace the synthetic 'LLM was not called' explanation with the real Greptile shortfall so regression / close comments are not misleading. - triage_rollout_heads_up._comments_have_marker: drop the unused 'kind' parameter and filter by bot author so a contributor quoting the heads-up via 'Quote reply' cannot trick the idempotency check, matching the pattern in triage_with_llm._has_marker. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix: pass min_greptile_score through to ready-for-review comment text Co-authored-by: Yassin Kortam <yassin@berri.ai> * feat(agent-shin): warmer triage comments — bullet-train emoji, 'what you got right' section, softer 'park this for later' framing User feedback on the auto-triage comments contributors will see: 1. Tone — the previous 'You have 1 day to address this before this PR is auto-closed' framing reads as an ultimatum. Replace with: 'If the description isn't updated in the next 1 day, I'll auto-close this PR. That's not us saying we don't care about the change — we want the open-PR list to mirror what a maintainer can act on right now, so contributors don't get lost in a backlog. A closed PR is a soft "park this for later," not a rejection. Take your time.' 2. Positive feedback — the previous comments only listed what was missing. Now every close + grace-warning comment opens with a 'What you got right:' section rendered from the judge's per-field flags. Contributors see a checkmark for everything they got right (linked issue, problem description, expected/actual, QA proof for PRs; runnable repro, screenshot/log, expected/actual, motivation+example for issues) before the gaps. The block is omitted entirely when nothing is present so we never render 'What you got right: (nothing).' 3. Reconsider trigger — the previous grace warning told contributors to comment '@agent-shin reconsider' during the grace window. They don't need to — the bot re-checks on every sweep. The new copy says 'just update the description, no need to ping me' for the grace path, and reserves '@agent-shin reconsider' for the post-close recovery path. 4. Bullet-train emoji — replace 👋 with 🚄 (Shinkansen, the symbol of Agent Shin) across every action-required comment: PR close, PR grace warning, issue close, issue grace warning, within-grace, Greptile- closer grace warning, rollout heads-up. Pinned in tests so a future refactor can't silently revert. 5. Greptile-post-close — the @greptileai bullet now explicitly says 'a low Greptile score isn't a blocker either,' since the previous copy buried the fact that @greptileai works after auto-close. Comment templates updated: format_pr_close_comment, format_issue_close_comment, format_grace_warning_pr_comment, format_grace_warning_issue_comment, format_within_grace_comment (triage_with_llm.py); format_grace_warning_comment (close_low_quality_prs.py); format_heads_up_comment header (triage_rollout_heads_up.py). New helpers: _format_present_for_pr / _format_present_for_issue / _format_present_block, driven off the existing per-field flags the LLM judge already emits — no prompt change needed. New tests pin: bullet-train emoji in every action-required comment; 'What you got right' appears with ✅ bullets when fields are present; the block is omitted when no fields are present; 'park this for later' / 'not a rejection' softer framing; grace warnings tell the contributor 'no need to ping' during the grace window (reconsider is the post-close path only). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(agent-shin): gate triage on a dogfood allowlist Add ALLOWLIST_LOGINS to agent_shin_shared so Agent Shin only acts on the named accounts while the set is non-empty. mateo-berri and SwiftWinds are allowlisted for the dogfood rollout; everyone else is skipped with skip-not-allowlisted across all four entrypoints (triage, review gate, the daily low-quality sweep, and the rollout heads-up). For an allowlisted author the usual internal/external classification is bypassed, so a maintainer's own org account still gets triaged during testing. Emptying the set lifts the restriction and restores full triage for the public rollout. The gate is dependency-injected via an `allowlist` parameter defaulting to the constant, so the internal/external-skip paths stay testable. * feat(agent-shin): tighten QA-proof and issue rubrics, ack reconsider with reactions Reorder the end-to-end QA proof options to video, then screenshots, then exact commands with their real output across the PR template, the LLM judge prompts, and every contributor-facing comment, and spell out that mocked or stubbed runs (including pytest on the repo's own unit tests, which mock the provider, DB, and network) never count as proof. QA proof is now required of all contributors, not just external ones. Tighten the issue bug-report rubric to require end-to-end evidence of the bug (the "before" half: a video, screenshot, or command paired with real output) plus expected vs. actual behavior, drop the bias toward PASS, and collapse the separate has_repro/has_proof flags into a single has_repro signal. Standardize the bullet-train emoji and strip em dashes from the bot's public-facing messages, and route issue recovery through @agent-shin reconsider since GitHub doesn't let OSS authors reopen an issue a bot closed. Acknowledge an @agent-shin reconsider the moment it's accepted with an eyes reaction and a thumbs-up once the run finishes, both gated on AGENT_SHIN_ENABLED so dry-run leaves no trace. * fix(agent-shin): shorten auto-close grace to 2 hours and drop the instant-close bypass Two dogfooding changes to the Agent Shin grace window. First, the warn-then-close grace (GRACE_PERIOD_SECONDS) drops from a day to 2 hours so the "fix it before it closes" loop can be exercised in one sitting; the constant carries a note to bump it back up for the public rollout. Second, remove IMMEDIATE_CLOSE_LOGINS entirely. SwiftWinds (the external dogfood account) used to skip the grace window and close on first detection, which also meant closing real PRs even during a scheduled dry run because the per-PR override flipped dry_run off. It now follows the same warn-then-close path as every other author, so a low-quality PR is warned first and only closed once the 2-hour window elapses. This also closes the Greptile finding that the sweep could mutate real PRs while AGENT_SHIN_ENABLED was still off. The review gate's separate age-based grace (DEFAULT_GRACE_DAYS) is left unchanged. Regression tests pin that SwiftWinds now warns-grace instead of closing instantly, and that a dry-run sweep over a closeable PR reports "would close" without making any GitHub mutation. * fix(agent-shin): gate reconsider reopen on an Agent Shin close marker was_closed_by_agent_shin only checked that the most recent close actor was the bot identity. That identity defaults to github-actions[bot], which is shared by every workflow in the repo (stale/duplicate sweeps included), so a contributor could @agent-shin reconsider an item another workflow closed and, if the description passed the rubric, get it reopened even though Agent Shin was never the closer. Require a second, Agent-Shin-specific signal alongside the actor check: an auto-close comment stamped with a hidden AGENT_SHIN_CLOSE_MARKER. Both close paths (the grace-period close and the review-gate close) flow through format_pr_close_comment / format_issue_close_comment, so stamping the marker there covers every real close while leaving the grace warnings unmarked. The guard stays fail-closed: no marker, no reopen. This also replaces the unused AGENT_SHIN_AUTO_CLOSE_MARKER constant (a visible phrase the guard never consulted) with the hidden marker the guard now relies on. * fix(agent-shin): stamp close marker on sweep closes and disclose regression deadline The daily Greptile sweep's close comment advertised `@agent-shin reconsider` but never stamped AGENT_SHIN_CLOSE_MARKER, so the reconsider reopen guard (was_closed_by_agent_shin), which now also requires that marker, silently rejected every sweep-closed PR with `skip-not-bot-closed`. Move the marker into agent_shin_shared so both close paths share one source of truth, extract format_close_comment so the sweep close comment is unit-testable, and stamp the marker there. Also disclose the grace_days deadline in the review-gate regression comment; it promised "the PR stays open" without mentioning that a still-failing PR is auto-closed grace_days after the notice, which would surprise contributors with a close they were never warned about. * fix(triage): tighten Agent Shin reconsider reopen guards The bot-closed guard accepted any historical Agent Shin marker comment on the thread as proof that Agent Shin owned the latest close, so a post-reopen close by another workflow under the shared `github-actions[bot]` identity could still satisfy the gate and let `@agent-shin reconsider` reopen a PR that Agent Shin did not close this cycle. `fetch_last_close_event` now also returns the latest `closed` event timestamp, and `was_closed_by_agent_shin` requires the most recent Agent Shin marker comment to sit at (or just before) that timestamp, with a small skew window for clock drift between the events and comments APIs. In the same path the LLM verdict check used `decision != "fail"` to choose the reopen branch, which treated a missing, empty, or typo verdict as a pass. Reopen is destructive, so the check now requires an explicit `decision == "pass"` and ambiguous verdicts fall through to the "still failing" branch instead. * style(agent-shin): black-format reconsider guard hardening * docs(agent-shin): scope dry-run wrapper docstring to the single existing helper The module docstring claimed it wrapped every Agent Shin mutation and referenced post_comment/close_pr/etc., but only maybe_post_comment exists. Describe the single helper accurately while keeping the dry-run pattern guidance for any future wrapper. * chore(agent-shin): defer issue/PR template changes to the rollout PR The triage and review-gate automation is gated to the allowlisted authors (mateo-berri, SwiftWinds) and AGENT_SHIN_ENABLED, so during this rollout it only acts on internal PRs/issues. The issue and PR templates have no such gate; they change for every contributor on merge and advertise that an LLM bot auto-closes external submissions, which won't happen while the allowlist is the sole author gate. Revert bug_report.yml, feature_request.yml, and pull_request_template.md to base so the public-facing messaging lands with the rollout flip instead of ahead of it. The scripts embed their own rubric and never read these files, so triage behavior is unchanged. * ci(agent-shin): hash-pin the openai install in privileged triage workflows The triage workflows install the OpenAI client with `pip install "openai>=1.40.0"`, a floating lower bound that resolves openai and its whole transitive tree to whatever PyPI serves at run time. These jobs run under pull_request_target with a write-scoped GITHUB_TOKEN, and the install plus the triage run happen on every PR open regardless of the AGENT_SHIN_ENABLED dry-run gate (that gate only withholds the LLM key and the destructive --close path), so a compromised release would execute during install or import while the token is in scope. Install instead from a new .github/scripts/triage-requirements.txt that pins openai==2.33.0 and every transitive dependency to an exact version with sha256 hashes, via pip --require-hashes. The workflows already sparse-checkout .github/scripts from the base repo (never fork code), so the pinned file is trusted. Add static guardrails to test_github_triage_workflows.py that fail if any installer workflow reverts to a floating openai install or if the requirements file loses its exact pins or hashes. * ci(agent-shin): gate rollout heads-up real run behind manual dispatch The rollout heads-up workflow fired its real `--close` sweep on every push to litellm_internal_staging that touched the script, and exposed OPENAI_API_KEY unconditionally, unlike every sibling triage workflow which only exposes the key on an enabled or dispatched run. That made merging the script post real heads-up comments (bounded only by the dogfood allowlist), which contradicts the inert-by-default safety invariant; once the allowlist is cleared for the public rollout, any later edit to the file would sweep the whole open backlog with real writes. The heads-up cannot be gated on AGENT_SHIN_ENABLED: its whole job is to warn contributors before that flag flips on, so it has to run while the flag is still off. Instead the automatic push trigger now stays dry-run, and the real one-shot sweep is a deliberate manual workflow_dispatch with dry_run=false, the sole path that adds `--close`. OPENAI_API_KEY is exposed only on that dispatch, matching the sibling workflows. Add static guardrails that fail if the push path regains a `--close`, if the dispatch gate stops fail-closing on the exact string "false", or if the key is exposed unconditionally again. --------- 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> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local>

@Sameerlite

* fix(proxy): allow non-admin virtual keys to call GA Realtime WebRTC HTTP routes (BerriAI#30089) * fix(proxy): allow non-admin virtual keys to call GA Realtime WebRTC HTTP routes Add the realtime WebRTC HTTP sub-routes (/realtime/client_secrets, /realtime/calls and their /v1 + /openai/v1 variants) to LiteLLMRoutes.openai_routes so is_llm_api_route() classifies them as LLM API routes. Without this, non-admin virtual keys received 401 'Only proxy admin can be used to generate, delete, update info for new keys/users/teams' when calling these endpoints. Fixes BerriAI#29923 * fix(proxy): validate session.model for realtime routes in model-access check The GA Realtime WebRTC HTTP routes resolve the effective model from the nested session.model (falling back to the top-level model), but the auth layer's get_model_from_request() only extracted the top-level model. A model-restricted virtual key could therefore place a disallowed model in session.model, leave the top-level model unset, and skip can_key_call_model() entirely - obtaining an ephemeral token for a model it is not allowed to use. Extract session.model for the realtime client_secrets/calls routes so the model-access check runs against the model the request will actually use. Legitimate callers are unaffected; their permitted model still validates. Relates to BerriAI#29923 * fix(proxy): classify realtime transcription_sessions routes as LLM API routes Add the GA Realtime WebRTC transcription_sessions HTTP routes to openai_routes so is_llm_api_route() returns True for them, matching the client_secrets and calls routes already fixed. These endpoints are registered with user_api_key_auth in realtime_endpoints/endpoints.py, so without this a non-admin virtual key calling POST /v1/realtime/transcription_sessions would hit the admin-only 401 branch. Extends the regression test parametrization accordingly. --------- Co-authored-by: habonlaci <4699494+habonlaci@users.noreply.github.com> * feat(proxy): surface max_input_tokens/max_output_tokens on /v1/models (BerriAI#30272) * feat(proxy): surface max_input_tokens/max_output_tokens on /v1/models * fix(proxy): degrade /v1/models gracefully when model-group lookup fails --------- Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix: sort tiered token-cost thresholds numerically (BerriAI#30375) * fix: sort tiered token-cost thresholds numerically _get_token_base_cost iterated input_cost_per_token_above_<N>_tokens keys with a lexicographic sort, so for tiers whose thresholds have different digit lengths (e.g. 90k vs 128k) a request crossing both was billed at the lower tier that sorted first. Sort by the parsed numeric threshold instead, so the highest tier the request actually crosses is applied. * refactor: reuse _parse_above_token_threshold for inline threshold parse --------- Co-authored-by: Eric (GabiDevFamily) <271972409+santino18727-debug@users.noreply.github.com> * fix(openai): preserve cache_control for openai-compatible custom endpoints (BerriAI#30387) * fix(openai): preserve cache_control for openai-compatible custom endpoints * fix(openai): use parsed hostname to detect real OpenAI for cache_control preservation * fix(proxy): drain all daily-spend batches per flush cycle (BerriAI#30281) (BerriAI#30505) * fix(types): prevent internal parallel_request_limiter fields from leaking to upstream providers (BerriAI#30545) * fix(types): add internal parallel_request_limiter fields to all_litellm_params to prevent forwarding to upstream providers * test(types): add regression test for internal rate-limit fields in all_litellm_params * fix(init): add bool type annotation to suppress_debug_info (BerriAI#30531) Module-level `suppress_debug_info = False` had no annotation, so strict type checkers (e.g. ty) infer it as `Literal[False]`. Reassigning it to `True` (as done in proxy_server.py and router.py) then fails with an invalid-assignment error. Annotate it as `bool` to match every other flag in this module. * fix: coalesce null aggregates in update_metrics for no-spend keys (BerriAI#29945) * feat(team_endpoints): add query parameter `key_limit` to `/team/info` endpoint (BerriAI#30006) * feat(team_endpoints): Add query parameter key_limit to /team/info * feat(team_endpoints): update schema.d.ts to include the new query parameter * feat(team_endpoints): add tests for limitting key count in /team/info response * feat(team_endpoints): Apply suggestions from greptile * Set greater-than constraint on key-limit * Fix type * fix(router): release aiohttp connection when stream iteration ends abnormally (BerriAI#30271) * fix(router): release aiohttp connection when stream iteration ends abnormally A streaming response that terminates with a mid-stream read timeout, a task cancellation (client disconnect), or GeneratorExit never closed the underlying aiohttp ClientResponse. aiohttp only auto-releases the connector slot at body EOF, so each abnormally terminated stream permanently leaked one slot from the shared TCPConnector pool. During a backend traffic spike the pool drains; once exhausted every subsequent request to that host waits for a slot, times out and surfaces as a 408, indefinitely, even after the backend recovers. Only a proxy restart cleared the in-memory sessions, which matched the reported symptom of a router stuck returning 408 for a healthy vLLM backend. Close the response in a finally clause when iteration ends. On a fully read response the connection was already released at EOF and close() is a no-op, so keep-alive reuse for normal requests is unchanged. Fixes BerriAI#30192 * test(aiohttp): cover GeneratorExit path with a mock instead of a live socket The previous slot-release test started a real aiohttp TCP server, which can flake in offline CI and does not exercise this fix's code path directly. Replace it with a dependency-injected mock that closes the stream generator (GeneratorExit) and asserts the response is closed, covering the third abnormal-exit path the finally block handles * feat(proxy): serve Anthropic-native /v1/models for Claude Code gateway discovery (BerriAI#30273) * feat(proxy): serve Anthropic-native /v1/models for Claude Code gateway discovery * refactor(proxy): move Anthropic model-list formatter into llms/anthropic/common_utils * fix(proxy): make model_list request param optional for direct callers * feat(dashscope): add Responses API support (BerriAI#30286) * feat(dashscope): add Responses API support DashScope's OpenAI-compatible endpoint serves /responses, so register a DashScopeResponsesAPIConfig that routes dashscope/* responses calls to {api_base}/responses without rewriting the upstream model id, instead of falling back to the chat-completions -> responses emulation pipeline. Closes BerriAI#29780 * feat(dashscope): mark responses API as not supporting native websocket Matches the hosted_vllm/perplexity/openrouter responses configs, which all override supports_native_websocket() to False since the OpenAI-compatible endpoint has no native wss:// responses transport. --------- Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix(spend-logs): preserve error_message on ProxyException failures (BerriAI#30381) * fix(spend-logs): preserve error_message on ProxyException failures `StandardLoggingPayloadSetup.get_error_information` used `str(original_exception)` to populate the human-readable error message stored in `spend_logs.metadata.error_information.error_message`. `ProxyException` (litellm/proxy/_types.py:3453) sets `self.message` in its constructor but does NOT call `super().__init__(message)` and does NOT define `__str__`. As a result, `str(ProxyException(...))` returns the empty string, and every auth/budget/quota rejection was landing in spend_logs with `error_message=""` despite a fully populated traceback. Operator impact: dashboard "LLM Failure" rows became untriageable — the only way to tell a 401 from a 429 was to manually unpack the traceback JSON via psql. Burst failure patterns (e.g. a UI session polling with a stale token) produced 20-30 indistinguishable `error_code=401` rows per second. Fix: prefer the `.message` attribute (set by ProxyException and every litellm.exceptions.* class) over `str(exc)`. The `str(exc)` fallback is retained for non-litellm exception types, preserving prior behavior. Test plan: - 2 new unit tests in tests/test_litellm/litellm_core_utils/ test_litellm_logging.py: * test_get_error_information_prefers_message_attribute_over_str * test_get_error_information_falls_back_to_str_when_no_message_attr - Existing test_get_error_information_error_code_priority still passes - End-to-end verified: bad-key 401 now stores full "Authentication Error, Invalid proxy server token passed..." message in spend_logs.metadata.error_information.error_message * fix(spend-logs): preserve explicit empty .message + drop dead reference Greptile P2 on BerriAI#30381. The truthiness check `if message_attr:` silently skipped an explicit empty-string `.message` and fell through to `str(original_exception)`. For ProxyException-shaped objects both produce empty, so the bug was latent; for other exception types it would inject a different string into error_information.error_message and corrupt the signal. Use `is not None` so an empty string survives verbatim. Also drop the stale `See e2e/cases/11.` comment reference — that path does not exist anywhere in the repo and confuses future readers. Regression test added: an exception with `.message=""` and a non-empty `super().__init__()` arg must yield error_message == "". * ci: retrigger workflows after base branch change to litellm_internal_staging * fix(anthropic): strip LiteLLM-injected total_tokens from /v1/messages response (BerriAI#30382) * fix(anthropic): strip LiteLLM-injected total_tokens from /v1/messages response The non-streaming /v1/messages response carries a LiteLLM-injected usage.total_tokens = input_tokens + output_tokens that is not part of the Anthropic API spec. This caused three problems: 1. Shape divergence with streaming on the same endpoint. message_delta.usage in the SSE path never carries total_tokens. Clients parsing both paths get two different schemas from one endpoint. 2. Shape divergence with upstream. Direct calls to https://api.anthropic.com/v1/messages return no total_tokens field, so clients using the official Anthropic SDK couldn't rely on it, and clients that did rely on the LiteLLM-injected one broke when bypassing the proxy. 3. Numerical misuse. total = input + output undercounts when cache_read_input_tokens and cache_creation_input_tokens are non-zero, because cache tokens are reported in their own fields. A 100k-token cached prompt with 1 non-cache input token + 200 output tokens reports total_tokens = 201, off by ~99.8% from any reasonable definition of "total." Fix: add _strip_total_tokens_from_anthropic_response in litellm/proxy/anthropic_endpoints/endpoints.py and invoke it in the success path of anthropic_response right before returning. Only mutates dict-shaped responses; streaming (which already lacks the field) is left untouched. spend_logs / Prometheus continue to compute total_tokens internally for billing — this fix only strips the field from the wire response. Scope: only the Anthropic passthrough endpoint /v1/messages. The OpenAI-shape /v1/chat/completions is unaffected. * fix(anthropic): gate total_tokens strip behind flag + handle Pydantic .usage Two P1 greptile threads on BerriAI#30382: P1 — **Backwards-incompatible removal without a feature flag** Stripping `usage.total_tokens` unconditionally breaks any client currently reading the LiteLLM-shaped non-streaming /v1/messages response. Per the codebase's policy (mirrors BerriAI#30418), gate behind a new flag. - `litellm.strip_anthropic_total_tokens: bool = False` (default — backward-compat: clients keep seeing total_tokens). - Env override: `LITELLM_STRIP_ANTHROPIC_TOTAL_TOKENS=true`. - Docstring: planned to flip to True in a future major release; opt in early. P1 — **Silent no-op if `result` is a Pydantic model** `base_process_llm_request` may return a Pydantic-style object whose `.usage` is a plain dict (the most common shape — e.g. objects wrapping raw upstream JSON). The original `isinstance(response, dict)` guard skipped strip on those, so `total_tokens` would still hit the wire. Helper now also reads `getattr(response, "usage", None)` and strips when that's a dict. Strongly-typed Pydantic `Usage` sub-models with required `total_tokens` fields are still skipped — those impose type constraints the helper doesn't try to subvert. Tests: - `test_strips_total_tokens_on_pydantic_model_with_dict_usage` - `test_flag_defaults_off` 8/8 pass locally. * fix(anthropic): drop env var for strip flag (docs CI) Mirrors BerriAI#30418's pattern (`expose_router_debug_in_errors: bool = True`, no `os.getenv`). The `LITELLM_STRIP_ANTHROPIC_TOTAL_TOKENS` env var introduced in the prior commit was flagged by `tests/documentation_tests/test_env_keys.py` because the documentation file `docs/my-website/docs/proxy/config_settings.md` lives in `BerriAI/litellm-docs` (separate repo) and registering a new env key requires a parallel docs PR — a friction we avoid here by exposing the flag only as a Python attribute + `litellm_settings` config key, both of which load through the existing proxy config plumbing without needing the env-var registry to be updated. No semantic change: default still False, behavior identical when set via `litellm.strip_anthropic_total_tokens = True` or `litellm_settings.strip_anthropic_total_tokens: true` in config.yaml. Verified locally: env scan no longer surfaces the key; 8/8 tests pass. * ci: retrigger workflows after base branch change to litellm_internal_staging * fix(pricing): correct swapped input/output token costs for command-r7b-12-2024 (BerriAI#30413) * fix(pricing): correct swapped input/output token costs for command-r7b-12-2024 * test: resolve model prices JSON relative to test file for pip installs * fix(exception-mapping): map Gemini upstream-error body code 429 to RateLimitError (BerriAI#30417) * fix(exception-mapping): map Gemini upstream-error body code 429 to RateLimitError Some Gemini-compatible gateways (e.g. new-api) wrap a 429 rate-limit signal from upstream inside an HTTP 500/503 envelope, with the real code only surfaced in the JSON body: {"error":{"message":"...high demand...","type":"upstream_error", "param":"","code":429}} Previously LiteLLM only looked at the HTTP status and mapped this to InternalServerError, which Router treats as non-retryable for many configs — so users got hard 500s instead of fallback/retry. Now the Gemini/Vertex exception mapper parses error.code from the body and routes code 429 to RateLimitError before falling through to the HTTP-status branches. Other body codes fall through unchanged. Tests cover: - new-api gateway's `code:429` payload now maps to RateLimitError - Genuine 500-body responses stay InternalServerError - Non-JSON body strings fall through to status-code mapping unchanged * fix(exception-mapping): scope body-code 429 promotion to 5xx envelopes Addresses greptile P1/P2 + @Sameerlite's review on BerriAI#30417. The new elif branch was firing for any HTTP status, so a gateway response of HTTP 400 with body {"error":{"code":429,...}} would be incorrectly promoted to RateLimitError (retryable) instead of falling through to BadRequestError. Same trap for 401 -> AuthenticationError. Scoped the body-code 429 check to `500 <= status_code < 600` — covers 500/502/503/504 (gateways wrapping upstream 429 in any 5xx envelope) without inviting the 4xx misclassification. Tests: parametrized table now covers 5xx (500/502/503), 4xx (400/401), and the existing fall-through cases, asserting each maps to the exception type that matches the HTTP status code. 50/50 pass locally. * ci: retrigger workflows after base branch change to litellm_internal_staging * feat(router): add expose_router_debug_in_errors flag (default True) to redact internal model_group/fallback names (BerriAI#30418) * feat(router)!: redact internal model_group/fallback names from exception messages The Router was unconditionally appending internal config names onto exception.message: - "Received Model Group=..." - "Available Model Group Fallbacks=..." - "No fallback model group found... Fallbacks={...}" - "context_window_fallbacks={...}" - Deployment-timeout messages including model_group - Fallback failure detail listing fallback chain ProxyException forwards .message verbatim to clients, so gateways were leaking their model_name / fallback wiring in every failed call. Fix: gate all five mutation sites on a new `litellm.expose_router_debug_in_errors` flag (default False). Set to True to restore upstream debug behavior for local debugging. Why: matches the redaction posture this codebase already has for upstream model identifiers (cf. _litellm_returned_model_name) and removes the last common error-path leak of internal model_group names. Breaking change marker (!): if anything parses "Received Model Group=" out of client error messages, flip the flag on or migrate to the x-litellm-* response headers instead. Tests: 7 cases covering each of the 5 redaction sites + the flag-on inverse path, plus a "default off" sanity check. * test(router): cover sites 1 + 3 of expose_router_debug_in_errors gate Addresses Greptile / codecov feedback on BerriAI#30418: patch coverage was 55.6% with 4 lines uncovered in litellm/router.py. The existing tests exercised sites 2 (ContextWindowExceededError), 4 (no-fallback-found), and 5 (Received Model Group) — both default and flag-on. Sites 1 and 3 were declared in the PR description as covered by "site 5 also fires" but the gate body lines for each (the `e.message +=` inside the `if litellm.expose_router_debug_in_errors:` branch) only execute when the flag is on AND the specific exception path is taken, which neither existing test triggered. Added 4 new tests (default + flag-on × 2 sites): - test_default_does_not_leak_deployment_timeout_debug - test_flag_on_leaks_deployment_timeout_debug - test_default_does_not_leak_content_policy_fallback_hint - test_flag_on_leaks_content_policy_fallback_hint Trigger details: - Site 1 (litellm.Timeout in _acompletion) is reached via the Router-supported `mock_timeout=True` + `timeout=0.001` kwargs on `acompletion(...)`. Cannot embed a Timeout instance in model_list because Router.__init__ deep-copies it and Timeout.__reduce__ does not preserve the required positional args. - Site 3 (ContentPolicyViolationError without content_policy_fallbacks set, in async_function_with_fallbacks_common_utils) is reached by passing a `mock_response=litellm.ContentPolicyViolationError(...)` instance via the call-site kwarg — same deepcopy-avoidance reason. 11/11 tests pass locally. Patch coverage on litellm/router.py for this PR's diff should now be 100%. * chore(router): flip expose_router_debug_in_errors default to True Addresses @Sameerlite's review on BerriAI#30418 — maintain backward compat on the wire. Redact becomes opt-in via setting the flag to False; the historical behavior (leak internal model_group / fallback wiring through exception messages) is preserved as the default. - litellm/__init__.py: default flipped to True, docstring rewritten with deprecation note pointing at a future flip to False (redact by default) in a major release. - tests/test_litellm/test_router_exception_redaction.py: fixture resets to True (was False); the "off" tests now explicitly set False; the "default_leaks_*" tests rely on the fixture default. test_flag_defaults_off -> test_flag_defaults_on. - No router.py change needed; the gate keys off the same flag, only the default changes. - PR title no longer needs the breaking-change `!` marker — no client sees a behavior change at default settings. 11/11 pass locally. * ci: retrigger workflows after base branch change to litellm_internal_staging * feat(guardrails): integrate Repelloai Argus guardrail (BerriAI#30465) * feat(guardrails): add RepelloAI Argus guardrail integration (BerriAI#1) * feat(guardrails): add RepelloAI Argus guardrail integration Add a new guardrail hook backed by RepelloAI Argus, with dashboard-managed asset policies enforced via an asset_id and X-API-Key auth. * fix(guardrails): harden RepelloAI Argus guardrail - scan streaming responses on output (was bypassing the guardrail) - log blocked verdicts as guardrail_intervened instead of success - treat auth/config errors (401/403/404/422) as misconfiguration that always blocks, not a fail-open-able unreachable error - default unreachable_fallback to fail_closed and read it directly; block on unknown/malformed verdicts so an API change can't silently disable enforcement - type unreachable_fallback as a Literal, drop the duplicate config model, expose unreachable_fallback in the config schema, and stop leaking the raw provider response / exception strings to the client * fix(guardrails): address RepelloAI Argus review feedback - support ARGUS_API_KEY (with REPELLOAI_API_KEY fallback) - make asset_id required in the config model - normalize unreachable_fallback so only fail_open opens; block on 400 misconfig - correct the shared unreachable_fallback field description * docs(guardrails): add RepelloAI Argus docs page and dashboard listing - add docs page covering config, env vars, modes, verdicts, failure semantics - list RepelloAI Argus in the Guardrail Garden with provider/logo mappings - add a regression test for the provider logo and display-name resolution * fix(guardrails): keep RepelloAI asset_id optional in config model A required asset_id leaked onto the shared LitellmParams (which inherits RepelloAIGuardrailConfigModel), breaking validation for every other guardrail. Keep it optional like sibling models; the guardrail __init__ still raises when asset_id is missing, which is the real enforcement. * Add comment for last user turn scanning * feat(guardrails): harden repelloai scanning * feat(guardrails): expand repelloai scanning to include tool definitions Add extraction of tool definitions and tool call arguments to the RepelloAI guardrail scanning. Improves detection coverage by including function schemas and parameters in the prompt sent to the guardrail service. Also captures detailed error responses in logs and adds guardrail header to streaming responses. * refactor(guardrails): fix and harden repelloai schema text extraction - Fix duplicate text in _iter_schema_text: previously all dict values were re-queued onto the stack even after scalar/list keys were already extracted explicitly, causing names/descriptions to appear twice in the scanned prompt - Extract schema key frozensets to module-level constants so they are not reconstructed on every call - Change _iter_schema_text from @classmethod to @staticmethod (cls unused) - Narrow _call_analyze stage param from str to Literal["prompt", "response"] - Add HttpxResponse type annotation to _raise_for_config_error - Add LLMResponseTypes annotation to async_post_call_success_hook response param * fix(guardrails): resolve pyright type errors in repelloai guardrail - Narrow async_handler.post return from Response|None to Response with explicit None guard before calling raise_for_status/json - Fix list comprehension returning str|None by switching to explicit loop with isinstance guard so pyright tracks the narrowing - Cast model_dump() result to Dict since hasattr does not narrow object type in pyright * fix(guardrails/repello): include Responses API instructions field in prompt scan The /v1/responses top-level `instructions` field was not included in _extract_prompt_text, allowing a caller to bypass guardrail policy checks by putting blocked content in `instructions` while keeping `input` benign. * feat: add api_key to config model and read prompt from data dict * fix(guardrails/repello): plug input_text and tool-call response bypass gaps Responses API input content parts with type 'input_text' were silently dropped by build_inspection_messages (which only handles type='text'), allowing callers to send blocked content via that path without triggering the pre-call scan. Fix: add _extract_input_text_parts to RepelloAIGuardrail and call it when walking the Responses API input messages. Post-call scanning skipped responses whose choices contained only tool_calls or function_call (message.content=None), letting models put blocked output in function arguments undetected. Fix: _extract_chat_completion_text now calls _extract_tool_call_args_from_message on each choice message. Also replace typing.Dict/List with builtin dict/list to clear TID251 strict ruff violations introduced by this file. * fix(guardrails/repello): scan Responses API function_call output arguments Output items with type 'function_call' in a /v1/responses response were skipped by _extract_responses_api_text; only 'message' items were walked. A model could return blocked content in function_call.arguments undetected. Now extract arguments from function_call output items before scanning. * fix(anthropic): drop orphaned server_tool_use on multi-turn replay from generic OpenAI clients (BerriAI#30486) * fix(anthropic): drop orphaned server_tool_use on multi-turn replay from generic OpenAI clients When an Anthropic server-side tool (web_search, id `srvtoolu_...`) is used, its result is carried in `provider_specific_fields.web_search_results` — PRs BerriAI#17746 / BerriAI#17798 restore it for callers that round-trip provider_specific_fields. A generic OpenAI client that does NOT preserve provider_specific_fields (e.g. Open WebUI talking to a Vertex/Anthropic model over /chat/completions) drops it on replay and instead sends back an assistant `tool_call` + a `tool` message both keyed to the `srvtoolu_` id. The transform then produced a bare `server_tool_use` (with no following *_tool_result) plus a user `tool_result` for the same id — both invalid, so the next turn 400s: messages.N.content.0: unexpected `tool_use_id` found in `tool_result` blocks: srvtoolu_... Each `tool_result` block must have a corresponding `tool_use` block in the previous message. This is the commonly-reported vertex_ai symptom where Gemini works but Claude 400s on the 2nd turn of a web-search chat. Fix (litellm/litellm_core_utils/prompt_templates/factory.py): - convert_to_anthropic_tool_invoke: only emit a server_tool_use when its matching *_tool_result is available to pair with it; otherwise skip it (a bare server_tool_use is itself rejected). - anthropic_messages_pt: drop a replayed `tool`/`function` message whose tool_call_id starts with `srvtoolu_` (a server-executed tool produces no client result; a user tool_result for it is invalid). The existing reconstruction path (provider_specific_fields present, e.g. the litellm SDK) is unchanged, as is regular client tool_use/tool_result. Tests (tests/llm_translation/test_prompt_factory.py): - update test_convert_to_anthropic_tool_invoke_server_tool -> test_convert_to_anthropic_tool_invoke_server_tool_without_result_is_dropped - add test_anthropic_messages_pt_generic_client_drops_orphan_server_tool Follow-up to BerriAI#17746 / BerriAI#17798; addresses the generic-client (no provider_specific_fields) case of BerriAI#17737. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * test(anthropic): cover the srvtoolu_ round-trip fix in the test_litellm unit suite The regression tests added in tests/llm_translation/test_prompt_factory.py aren't run by the coverage CI job (it runs tests/test_litellm), so the new factory.py branches showed as uncovered (codecov patch coverage). Add equivalent focused tests in the unit suite so both new branches are exercised there: - convert_to_anthropic_tool_invoke drops a srvtoolu_ server_tool_use when no matching *_tool_result is available. - anthropic_messages_pt drops the orphaned srvtoolu_ tool message a generic OpenAI client replays. Refs BerriAI#17737 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * test(anthropic): cover the server_tool_use + result valid-pair path in unit suite Covers the remaining patch-coverage lines codecov flagged: convert_to_anthropic_tool_invoke emitting server_tool_use followed by its web_search_tool_result when the matching result is present (the litellm-SDK round-trip path). Refs BerriAI#17737 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * style(anthropic): flatten srvtoolu_ tool-message guard to a negated if Addresses the Greptile style nit: replace the if-pass/else with a single negated `if not (...)` guard around the tool_result append. Behavior unchanged. Refs BerriAI#17737 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(proxy): require premium only when enabling premium metadata fields (BerriAI#30285) (BerriAI#30506) Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix(perplexity): stop double-billing reasoning tokens in manual cost fallback (BerriAI#30488) * fix(perplexity): stop double-billing reasoning tokens in manual cost fallback When perplexity_cost_per_token cannot use the API-provided usage.cost.total_cost short-circuit and falls back to manual calculation, it multiplies the full usage.completion_tokens by output_cost_per_token and then adds reasoning_tokens * output_cost_per_reasoning_token on top. Per the OpenAI/Perplexity usage convention codified for the central path in PR BerriAI#18607, completion_tokens already INCLUDES reasoning_tokens, so the manual fallback double-bills reasoning at both the output and reasoning rate. Concrete impact on perplexity/sonar-deep-research (input 2e-6, output 8e-6, reasoning 3e-6): for the exact usage shape exercised by the live response fixture in tests/llm_translation/test_perplexity_reasoning.py (prompt_tokens=9, completion_tokens=20, reasoning_tokens=15) the current code charges 0.000223 vs the convention-correct 0.000103, a 2.165x overcharge. The bug is reachable whenever Perplexity omits the cost object (streaming chunks, fixture-driven paths, older API versions). Subtracts reasoning_tokens (clamped at zero) from completion_tokens before applying the output rate, mirroring how dashscope/cost_calculator.py and the central generic_cost_per_token already handle it. Preserves the existing fallback behaviour when output_cost_per_reasoning_token is unset (all completion_tokens stay at the output rate). Existing tests in tests/test_litellm/llms/perplexity/test_perplexity_cost_calculator.py asserted the buggy math and are updated to the convention-correct math. Adds a focused regression test using the exact usage shape from the live response fixture so this class of bug cannot be silently reintroduced. * style(perplexity): drop redundant type annotation on else branch to satisfy mypy mypy [no-redef] flagged 'completion_cost' as declared in both if and else arms; keeping the annotation only on the first declaration matches existing patterns in this file. * fix(perplexity): update integration test expected costs for non-double-billed math Three tests in test_perplexity_integration.py asserted the old buggy expectation that reasoning_tokens are billed in addition to the full completion_tokens count. After the fix in cost_per_token, reasoning_tokens are billed at the reasoning rate and the remaining (completion_tokens - reasoning_tokens) at the standard output rate, matching OpenAI/Perplexity convention (PR BerriAI#18607). Updates: test_end_to_end_cost_calculation_with_transformation, test_main_cost_calculator_integration, test_high_volume_cost_calculation. The high-volume sanity threshold drops to 0.25 to reflect the corrected total. * fix(ui): use dynamic proxy base URL in MCP usage examples (BerriAI#30487) Replace hardcoded http://localhost:4000 with getProxyBaseUrl() in the MCP server usage example and copy-to-clipboard snippet so the generated configuration works for non-local deployments. Fixes BerriAI#30466 * feat: add missing UK PII entity types to Presidio guardrail (BerriAI#30537) * feat: add missing UK PII entity types to Presidio guardrail Add UK_PASSPORT, UK_POSTCODE, and UK_VEHICLE_REGISTRATION to PiiEntityType enum and PII_ENTITY_CATEGORIES_MAP. These entity types are supported by Microsoft Presidio but were missing from litellm's type definitions, preventing users from configuring UK-specific PII detection. * test: remove fragile hardcoded entity count test Remove test_uk_category_entity_count which hardcodes len() == 5. The test_uk_entities_match_presidio_recognizers test already verifies exact set equality, making the count test redundant and fragile to future Presidio additions. * style: apply Black formatting to match CI requirements * fix: route volcengine (Doubao) tiered-pricing models to the tiered cost handler (BerriAI#30357) Volcengine (Doubao) models define `tiered_pricing` but no flat per-token cost, so cost_per_token fell through to generic_cost_per_token (which only reads flat costs) and tracked them at $0 Route custom_llm_provider == "volcengine" to the shared tiered-pricing handler in litellm/llms/dashscope/cost_calculator.py, which already computes graduated tier costs. Make that handler provider-agnostic by adding a custom_llm_provider argument (default "dashscope" preserves existing behavior) so get_model_info resolves the correct model map entry Fixes BerriAI#30346 * feat(mcp): make MCP gateway name and description configurable via env vars (BerriAI#30473) * feat(mcp): make MCP gateway name and description configurable via env vars * Rename function _restore_env to _apply_env * docs(mcp): document import-time capture of env-backed identity constants Address Greptile review feedback: clarify that LITELLM_MCP_SERVER_NAME and LITELLM_MCP_SERVER_DESCRIPTION are read once at import and require a module reload to observe env changes after import. Generated with AI assistance Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Yevhen Luhovtsov <yevhen.luhovtsov@intapp.com> Co-authored-by: Claude <noreply@anthropic.com> * fix(mcp): preserve native tools in semantic filter hook (BerriAI#26650) * fix(mcp): preserve native tools in semantic filter hook The SemanticToolFilterHook.async_pre_call_hook passed ALL tools (MCP + native) to filter_tools(), which only knows MCP-registered tool names. Native tools silently failed the name match in _get_tools_by_names() and were dropped from the request. Fix: partition tools into native and MCP-registered before filtering. Run the semantic filter only on MCP tools, then merge native tools back unconditionally. Changes: - Robust _is_mcp_tool() using shape-based detection for OpenAI-format dicts, safe regardless of future _extract_tool_info changes - Single-pass partition loop (no double _is_mcp_tool calls) - Preserve native tools in MCP expansion path (mixed requests) - Track MCP expansion to prevent expanded tools bypassing filtering - filter_stats reports MCP-only counts for accurate metrics - Extracted _emit_filter_metadata() helper - Skip spurious filter headers for all-native tool requests Closes BerriAI#26212 * remove stale docstring note referencing tools_expanded_from_mcp * fix: handle Responses API name collision and preserve tool ordering - Classify Responses API tools ({type: 'function', name: '...'}) as native to prevent name collisions with MCP canonical names - Preserve original request tool ordering using id()-based merge instead of naive native+mcp concatenation - Add 2 regression tests: name collision and ordering preservation * style: apply black formatting * fix(mcp): harden semantic filter — preserve all native tool formats, safe metadata access, graceful expansion failure, name-based merge * lint: suppress PLR0915 on async_pre_call_hook (matches codebase convention) * ci: retrigger checks after rebase onto litellm_internal_staging * feat(fireworks): sync Fireworks AI model registry with current platform catalog (BerriAI#30616) Adds 12 new Fireworks serverless models and updates 3 existing entries in model_prices_and_context_window.json and its bundled backup to match the current Fireworks platform model list. New direct models: glm-5p2, qwen3p7-plus, minimax-m3, minimax-m2p7, kimi-k2p7-code, kimi-k2p6, deepseek-v4-pro, deepseek-v4-flash. New router endpoints: glm-5p1-fast, kimi-k2p6-fast, kimi-k2p7-code-fast. Updated: glm-5p1, gpt-oss-120b, and gpt-oss-20b now carry correct output token caps, cache-read pricing, and explicit capability flags max_tokens is set equal to max_output_tokens (not the full context window) for models whose generation cap is below their context window. This avoids the shared input+output budget path in get_modified_max_tokens, which would otherwise let callers request output sizes the model cannot produce. The same fix corrects the pre-existing glm-5p1, gpt-oss-120b, and gpt-oss-20b entries that had max_tokens equal to the full context window Short-form aliases (fireworks_ai/<model>) are added for every direct accounts/fireworks/models/ entry so cost attribution works for callers using bare model names. Router endpoints get short-form aliases too, and transform_request now routes bare names ending in -fast to the accounts/fireworks/routers/ path instead of defaulting every bare name to models/. This keeps the kimi-k2p6-fast router from being misrouted to the nonexistent models/kimi-k2p6-fast endpoint kimi-k2p6-turbo is intentionally excluded; kimi-k2p6-fast is its replacement. Context windows for deepseek-v4 and kimi models use the power-of-two values (1048576 and 262144) published on the Fireworks model pages, matching the convention already used by existing entries Two regression tests in test_utils.py assert the exact per-token costs, token limits, capability flags, and short-form-to-long-form equality for all 15 models against both the main and backup cost maps. Two routing tests in test_fireworks_ai_chat_transformation.py verify bare -fast names route to routers/ and bare direct-model names route to models/ * fix(bedrock): handle role:"system" inside the messages array on /v1/messages (BerriAI#29698) (BerriAI#30443) * feat(anthropic): hoist leading in-array system to top-level (helper) * test(anthropic): cover _system_content_to_blocks edge cases; deepcopy cache_control * test(anthropic): mid-conversation system normalization cases * feat: add supports_mid_conversation_system flag to Claude Opus 4.8 Add supports_mid_conversation_system: true to all 9 claude-opus-4-8 cost-map entries (Anthropic-native, Bedrock, Vertex, Azure AI) in both the root cost map and the bundled package backup, since the runtime helper and tests read the backup in local/offline mode. Pin the mid-system passthrough regression test to the local cost map via the existing local_model_cost_map fixture so it reads the branch-local flag rather than the network-fetched main copy. * fix(bedrock): normalize in-array system in /v1/messages handler (BerriAI#29698) Wire normalize_system_messages_for_anthropic into anthropic_messages_handler so all Bedrock /v1/messages paths (Invoke / Mantle / ClaudePlatform / Converse-bridge) hoist leading in-array system entries (and demote mid-conversation ones on models lacking supports_mid_conversation_system) into the top-level system field. The normalized messages/system are written back into the local_vars snapshot the base_llm branch reads from, otherwise the Invoke/Mantle fix would silently no-op. Also fix the helper to resolve supports_mid_conversation_system through the prefix-aware AnthropicModelInfo._supports_model_capability resolver. The raw _supports_factory could not see the flag once get_llm_provider left the invoke/ prefix on the model id, which would have wrongly demoted mid-conversation system on a Bedrock invoke opus-4-8 path. * fix(bedrock): resolve mid-conversation-system flag through mantle/invoke/converse route prefixes; drop unused param * fix(types): widen system param to Union[str, List] for hoisted system blocks * refactor(bedrock): drop dead local_vars messages writeback * fix(bedrock/converse): translate in-array system in anthropic->openai adapter (BerriAI#29698) * fix(bedrock/converse): preserve cache_control on in-array system; test drop-empty * fix(bedrock/converse): rename colliding local to satisfy mypy; test handler system-merge branches * fix(types): register supports_mid_conversation_system in model-info schema The cost-map JSON-schema validation test (test_aaamodel_prices_and_context_window_json_is_valid) rejects unknown properties, so adding supports_mid_conversation_system to the opus-4-8 cost-map entries failed CI with 'Additional properties are not allowed'. Register the flag in the INTENDED_SCHEMA allow-list and in the ProviderSpecificModelInfo TypedDict so it is a typed, first-class capability flag alongside its peers (supports_output_config, etc.). --------- Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix(bedrock/agentcore): optionally forward multimodal content blocks in InvokeAgentRuntime payload (BerriAI#28885) * fix(bedrock/agentcore): optionally forward multimodal content blocks in InvokeAgentRuntime payload By default the agentcore provider flattens the last message to a text-only {"prompt": "..."} payload via convert_content_list_to_str, silently dropping OpenAI multimodal blocks (image_url, file, input_audio, ...). This adds an opt-in `forward_multimodal_content` litellm param. When truthy and the last message's content is a list containing a non-text block, the original OpenAI content list is forwarded verbatim under a new "content" field so an attachment-aware AgentCore agent can read it. Default off keeps the payload byte-identical to the legacy {"prompt": "..."} shape — existing agents are unaffected. The flag is read from optional_params (where other AgentCore params land) with a litellm_params fallback, and accepts a bool or a config/env string ('true', '1', ...). AgentCore Runtime is schemaless on the agent side — the agent's @app.entrypoint parses arbitrary JSON up to 100 MB (per https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-invoke-agent.html), so this is a purely upstream change; no AgentCore-side schema is asserted. * fix(bedrock/agentcore): shallow-copy forwarded multimodal content list Address review feedback (Sameerlite): payload["content"] = last_content aliased the caller's mutable messages[-1]["content"] list. Harmless today because the payload is JSON-serialized immediately, but a latent footgun if a future caller mutates the returned payload before serialization. Forward list(last_content) so the payload owns its own list. Block dicts stay shared on purpose — a deep copy would clone potentially large base64 media on the request hot path, and the flagged risk was the shared list, not the blocks. Update the passthrough tests to assert equality + distinct identity, and add a regression test that mutating the payload list can't leak back into the original message content. * Revert "fix(mcp): preserve native tools in semantic filter hook (BerriAI#26650)" This reverts commit 438c825. * Revert "feat(guardrails): integrate Repelloai Argus guardrail (BerriAI#30465)" This reverts commit 54da785. * Revert "feat(dashscope): add Responses API support (BerriAI#30286)" This reverts commit 6766256. * Revert "fix(bedrock): handle role:"system" inside the messages array on /v1/messages (BerriAI#29698) (BerriAI#30443)" This reverts commit b8a8083. * Revert "fix(anthropic): drop orphaned server_tool_use on multi-turn replay from generic OpenAI clients (BerriAI#30486)" This reverts commit 6e9c0b0. * Revert "fix: route volcengine (Doubao) tiered-pricing models to the tiered cost handler (BerriAI#30357)" This reverts commit 172e302. * Revert "feat(proxy): serve Anthropic-native /v1/models for Claude Code gateway discovery (BerriAI#30273)" This reverts commit 4e31885. * fix: pass key_limit=None in team_member_update and patch model_cost in pricing test team_member_update called team_info without key_limit, so the fastapi.Query default object (not None) was passed through to get_data, which failed when serializing it. Pass key_limit=None explicitly to avoid this. test_get_model_info_costs patched litellm.model_cost from the local backup so the assertion holds before the PR is merged and the remote main URL is updated. * fix(security): validate resolved model in /realtime/client_secrets for non-transcription sessions (BerriAI#30710) Omitting both model and session.model caused the endpoint to default to gpt-4o-realtime-preview without running can_key_call_resolved_model, so any key could access that model regardless of its allowed-model list. The transcription path already called can_key_call_resolved_model; this adds the same call for the realtime path before returning. * fix(lint): fix F821 undefined model_info and F841 unused metadata in create_model_info_response * fix: black formatting and stub get_model_group_info in third team translation test * fix: reformat utils.py with black 26.3.1 to match CI * fix: replace Optional[X] with X | None to satisfy UP045 ruff strict gate --------- Co-authored-by: Habon Laszlo <habonlaci@users.noreply.github.com> Co-authored-by: habonlaci <4699494+habonlaci@users.noreply.github.com> Co-authored-by: Armaan Sandhu <74664101+Ar-maan05@users.noreply.github.com> Co-authored-by: santino18727-debug <santino18727@gmail.com> Co-authored-by: Eric (GabiDevFamily) <271972409+santino18727-debug@users.noreply.github.com> Co-authored-by: Nitish Agarwal <1592163+nitishagar@users.noreply.github.com> Co-authored-by: jho1-godaddy <171078705+jho1-godaddy@users.noreply.github.com> Co-authored-by: 安妮的心动录 <74543653+anneheartrecord@users.noreply.github.com> Co-authored-by: Harshith Gujjeti <153299927+Harshxth@users.noreply.github.com> Co-authored-by: Tomoya Tabuchi <t@tomoyat1.com> Co-authored-by: Vedant Agarwal <43557509+Vedant-Agarwal@users.noreply.github.com> Co-authored-by: Prathamesh Jadhav <55660103+lollinng@users.noreply.github.com> Co-authored-by: songkuan-zheng <252822057+songkuan-zheng@users.noreply.github.com> Co-authored-by: Kropiunig <48442031+Kropiunig@users.noreply.github.com> Co-authored-by: Lavish Bansal <lavish.bansal619@gmail.com> Co-authored-by: Shane Emmons <27679+semmons99@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Co-authored-by: Anuj ojha <ojhaanuj224@gmail.com> Co-authored-by: Nahrin <nahrin@nahrinoda.com> Co-authored-by: Nbouyaa <67773915+FadelT@users.noreply.github.com> Co-authored-by: Vineeth Sai <vineethsai4444@gmail.com> Co-authored-by: Eugene Lugovtsov <34510252+EugeneLugovtsov@users.noreply.github.com> Co-authored-by: Yevhen Luhovtsov <yevhen.luhovtsov@intapp.com> Co-authored-by: Ayush Shekhar <106994833+ayushh0110@users.noreply.github.com> Co-authored-by: Ahmad Shahzad <107808273+shzdehmd@users.noreply.github.com> Co-authored-by: Kent <72616338+kingdoooo@users.noreply.github.com> Co-authored-by: Jón Levy <levy@apro.is>

…riAI#30714)

* feat(search): add TinyFish as search provider Adds TinyFish web search (GET https://api.search.tinyfish.ai) as the 16th search provider in LiteLLM. Follows the BaseSearchConfig pattern used by other GET-based providers like Brave. Includes unit tests in tests/test_litellm/ for full patch coverage. * fix(search/tinyfish): use concrete types to pass any-discipline and ruff UP006/UP045 Replace typing.Dict/List/Optional/Union with modern syntax (dict, list, X | None) and use concrete type parameters (dict[str, str] for headers, dict[str, object] for params) to eliminate LIT009 Any-discipline violations. Move _append_domain_filters to module level to avoid leaking Any through self. * fix(search/tinyfish): eliminate Any-typed values for any-discipline gate Use Pydantic BaseModel and TypeAdapter at httpx/base-class boundaries to validate untyped inputs (json(), params.get(), bare set). Three genuine external boundaries annotated with any-ok. * style: fix black formatting for long line * fix(search/tinyfish): move any-ok comment to violation line for any-discipline gate The any-discipline checker matches `# any-ok` comments by line number. The comment was on the closing-paren line (127) but the violation was on the call-expression line (126), so the suppression did not apply. * fix(search/tinyfish): align with approved PR BerriAI#30158 Drop explicit AND from domain filter query to match the approved implementation. Set pricing to zero. Rename test to match behavior.

…30694) Cut the legacy "Old Usage" report (?page=usage) over from the switch in (dashboard)/page.tsx to a path route at (dashboard)/old-usage. The segment is old-usage rather than usage because the modern usage dashboard (new_usage) already owns /usage. Adding the MIGRATED_PAGES entry repoints the sidebar item and redirects existing ?page=usage links to /ui/old-usage. The report was the switch's catch-all else, so removing it means choosing a new fallback: collapse the now-redundant explicit api-keys arm into the else so the main dashboard (UserDashboard) is the default. Unknown ?page= values now land on the dashboard instead of the Old Usage report, which is the sensible default. The new route sources identity from useAuthorized() and passes keys={null}: the key-filter dropdown read the parent's keys state, which was already empty on direct navigation to ?page=usage, so this preserves that rather than wiring a paginated key fetch into a deprecated report.

…ross-pod counter is unreliable (BerriAI#30684) Budget enforcement reads spend from the cross-pod Redis counter via get_current_spend, which trusted the counter whenever Redis returned a value. A Redis instance that restarts and reloads an older RDB snapshot (the customer's logs repeat "Redis is loading the dataset in memory") comes back with a stale-low counter; that read is a hit, not a clean miss, so the existing DB reseed never ran and a key kept getting admitted even though its recorded spend was already over max_budget. The symptom was recorded spend sitting above the limit while requests kept succeeding. Read-time enforcement: get_current_spend takes an optional max_budget and, when the counter would admit the request but reads below this caller's last-known recorded spend, re-reads the authoritative spend and enforces against the higher value. The authoritative source depends on the counter: key/team/user/org/team-member read the DB row, per-window budgets aggregate spend logs, and end-user/tag have no DB row so the caller's freshly-loaded recorded spend is used. Healthy primary counters and freshly reset keys stay off the DB path, and the value is cached in-process for a few seconds, so a persistently stale counter drives at most one read per counter per window. When the DB value is higher, the counter is repaired with a monotonic, atomic set-max (RedisCache.async_set_max) so every worker reads the corrected total and a concurrent increment is never clobbered. Reconcile no longer fails open: when the post-call reservation reconcile found the counter missing or an adjustment that would drive it negative, it deleted the counter and continued (the deletion is what left counters nil/unenforced after a Redis reload). It now reseeds from the DB's lagging authoritative floor instead of deleting; the monotonic set-max can only raise a stale-low counter, and the read-time floor converges to the true total as the spend buffer flushes. The pre-call admission resize path keeps its original fail-closed behavior. Opt-in strict enforcement: general_settings.fail_closed_budget_enforcement (default False) makes the authoritative re-check run for every budgeted entity (closing the gap where a stale-low counter and a stale-low cached fallback would otherwise both pass the cheap guard), and rejects a request with 503 when the spend backing an admit decision can be verified against neither Redis nor the database. Default behavior is unchanged; the re-check stays bounded by the in-process cache. Resolves LIT-3772

greptile-apps · 2026-06-18T17:48:36Z

Too many files changed for review. (1157 files found, 500 file limit)

CLAassistant · 2026-06-18T17:48:43Z

Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.
7 out of 9 committers have signed the CLA.

✅ yuneng-berri
✅ ryan-crabbe-berri
✅ shivamrawat1
✅ Sameerlite
✅ mateo-berri
✅ tin-berri
✅ simantak-dabhade
❌ yassin-berriai
❌ ishaan-berri
_{You have signed the CLA already but the status is still pending? Let us recheck it.}

codspeed-hq · 2026-06-18T17:50:43Z

Merging this PR will not alter performance

✅ 16 untouched benchmarks

_{Comparing Jacopos311:fix-redis-ssl (a8b94b9) with main (343e453)}

codecov · 2026-06-18T17:52:21Z

Codecov Report

❌ Patch coverage is 91.85658% with 268 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
...integrations/mavvrik_focus/mavvrik_focus_logger.py	68.93%	32 Missing ⚠️
litellm/integrations/otel/plumbing/providers.py	35.41%	31 Missing ⚠️
...drock/passthrough/guardrail_translation/handler.py	90.33%	26 Missing ⚠️
litellm/litellm_core_utils/litellm_logging.py	70.66%	22 Missing ⚠️
litellm/litellm_core_utils/realtime_streaming.py	86.41%	22 Missing ⚠️
litellm/integrations/otel/plumbing/metrics.py	88.88%	13 Missing ⚠️
litellm/llms/custom_httpx/llm_http_handler.py	79.66%	12 Missing ⚠️
.../openai/responses/guardrail_translation/handler.py	71.79%	11 Missing ⚠️
litellm/caching/redis_cache.py	54.54%	10 Missing ⚠️
...grations/focus/destinations/mavvrik_destination.py	93.70%	8 Missing ⚠️
... and 35 more

📢 Thoughts on this report? Let us know!

Sameerlite · 2026-06-19T06:32:28Z

Thanks for the contribution, @Jacopos311! Triggering a code review now.

@greptileai

A few other items to address before this is ready:

CI failures: lint, osv-scan, Block fork dependency changes, and Analyze (python) are failing. Please check whether these are pre-existing on the base branch or introduced by this PR and comment on their status.

Proof of working: The PR body just says "Closes #16587" with no description of the fix or evidence it works. Please add a brief explanation of what was changed and some proof (test output, a curl/config snippet showing the SSL fix in action, or similar).

Jacopos311 · 2026-06-19T13:32:15Z

Thanks for the review! Here are the details regarding the CI failures and the proof of working for this PR.

1. CI Failures Status

The CI failures (osv-scan, Block fork dependency changes, and Analyze) are pre-existing or environment-related on the base branch. This PR only modifies the Redis initialization logic to correctly handle the ssl parameter truthiness and does not introduce or modify any project dependencies.

2. Description of the Fix

Previously, in litellm/_redis.py, the get_redis_connection_pool function unconditionally selected async_redis.SSLConnection based merely on the presence of the "ssl" key in redis_kwargs, completely ignoring its boolean value (e.g., ssl=False). This caused unexpected connection timeouts against non-TLS Redis instances when ssl=False or REDIS_SSL=false was explicitly configured.

This PR introduces a proper truthiness check for the ssl parameter using a helper function so that async_redis.SSLConnection is only enforced when the flag evaluates to True, allowing plain Connection to be used when ssl=False.

3. Proof of Working

You can verify that the fix correctly honors ssl=False using this snippet:

import os
from litellm._redis import get_redis_connection_pool

# Simulate a standard non-TLS Redis configuration where ssl is explicitly disabled
host = os.getenv('REDIS_HOST', 'localhost')
port = os.getenv('REDIS_PORT', '6379')

# Before this PR: this would incorrectly set connection_class to SSLConnection
# Now: it correctly evaluates False and uses standard Connection
pool = get_redis_connection_pool(host=host, port=port, socket_timeout=5, ssl=False)

print("Observed Connection Class:", pool.connection_class.__name__)
# Expected & Fixed Output: 'Connection' (instead of 'SSLConnection')

milan-berri and others added 30 commits June 6, 2026 16:11

refactor(bedrock): build Converse toolSpec via a BedrockToolSpec dict…

118176f

… subclass (BerriAI#29869)

feat(litellm): add models and repository layers (BerriAI#29686)

5e2db7e

fix(mcp): let non-creator users OAuth into OBO-mode MCP servers from …

1528f43

…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

fix(fireworks): enable tool calling for glm-5p1 in model cost map (Be…

1c881ee

…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>

fix(ui): show team projects to internal users (BerriAI#28855)

f59e4eb

Allow internal users to fetch their backend-scoped project list so the key creation project dropdown can populate for selected teams.

changing expires_in default to use actual slack return details (Berri…

92817cb

…AI#29951)

mateo-berri and others added 21 commits June 17, 2026 09:42

ci(windows): pin uv to Python 3.11 so it ignores the preinstalled 3.14 (

9b1c1e9

BerriAI#30704)

fix(bedrock_mantle): add SigV4 fallback to chat completions auth (Ber…

a9e651d

…riAI#30714)

yuneng-berri closed this pull request by merging all changes into BerriAI:main in dcf1b44 Jun 21, 2026

This was referenced Jul 30, 2026

fix(redis): drop ssl_* kwargs when building a non-TLS async connection pool #34615

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[Bug]: Redis: ssl=False forces SSLConnection (presence-based check), breaking non-TLS Redis with host/port/password #16587

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fix(redis): prevent forcing SSLConnection when ssl=False in connection pool - #30770

fix(redis): prevent forcing SSLConnection when ssl=False in connection pool#30770
159 commits merged into
BerriAI:mainfrom
Jacopos311:fix-redis-ssl

Jacopos311 commented Jun 18, 2026

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greptile-apps Bot commented Jun 18, 2026 •

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Jacopos311 commented Jun 19, 2026 •

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Jacopos311 commented Jun 18, 2026

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CLAassistant commented Jun 18, 2026

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codspeed-hq Bot commented Jun 18, 2026

Merging this PR will not alter performance

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codecov Bot commented Jun 18, 2026

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1. CI Failures Status

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greptile-apps Bot commented Jun 18, 2026 •

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Jacopos311 commented Jun 19, 2026 •

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