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yuneng-jiang
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6ff668c7aa
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[Infra] Promote internal staging to main (#27245)
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* default requested_model to empty string on litellm-side rejects * Update litellm/router.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix: scope key access_group_ids override by team's assigned groups A team member could set any access_group_ids on their key (e.g. a group assigned only to a different team) and override the team's model restriction. Intersect the key's access_group_ids with team_object.access_group_ids in _key_access_group_grants_model so foreign groups are dropped before model expansion. Adds a regression test that asserts expansion is never called for foreign groups. * [Fix] Proxy: Skip Personal Budget Hook When Reservation Covers Counter The reservation path (PR #26845) atomically pre-fills `spend:user:{user_id}` and admits at the strict-`<` boundary. The legacy `_PROXY_MaxBudgetLimiter` pre-call hook re-reads the same counter with `>=`, so a reservation that fills the counter to exactly `max_budget` (e.g. a request without a `max_tokens` cap that falls back to reserving the smallest remaining headroom) is rejected by the hook even though the reservation already admitted it. Skip the hook when the request's active `budget_reservation` covers `spend:user:{user_id}`. The reservation is the source of truth for that counter cross-pod; the legacy `>=` path remains in place for requests without a reservation (e.g. paths that bypass the reservation entirely). Reproduces as `tests/otel_tests/test_prometheus.py::test_user_budget_metrics` on a fresh user with `max_budget=10` calling `fake-openai-endpoint` without `max_tokens`. Adds focused unit coverage in `tests/test_litellm/proxy/hooks/test_max_budget_limiter.py`. * harden bedrock file bucket validation * Fix syntax errors from botched merge in router.py * Fix Vertex batch output edge cases * [Fix] RBAC: Drop management_routes Write Fallback for Admin Viewer Greptile P1: the unsafe-method branch of `_check_proxy_admin_viewer_access` ended with a blanket `if route in management_routes: return`. That set is a mix of reads (info/list — handled via the safe-method GET branch above) and writes. The fallback let Admin Viewer POST to write endpoints not enumerated in `_ADMIN_VIEWER_BLOCKED_WRITE_ROUTES`, including: - /team/block, /team/unblock, /team/permissions_update - /jwt/key/mapping/{new,update,delete} - /key/bulk_update - /key/{key_id}/reset_spend Remove the fallback. The two remaining allow sets (admin_viewer_routes and global_spend_tracking_routes) are both read-only, so removal does not affect the legitimate POST-as-read cases (e.g. /spend/calculate, which is in spend_tracking_routes ⊂ admin_viewer_routes). Tests: - 8 new parametrized cases pinning each previously-leaking management write endpoint to 403 on POST for PROXY_ADMIN_VIEW_ONLY. * fix(tests): anchor VCR redis cassette key to repo root `os.path.relpath` with no `start` arg uses the current working directory, so running pytest from a subdirectory produced a different Redis key than running from the repo root. CI-recorded cassettes and locally-replayed runs would silently miss each other's cache. Anchor the path to the repo root (derived from `__file__`) so the key is stable regardless of CWD. https://claude.ai/code/session_018uCx7pcrkdUJZrCVMaTdPx * fix: gate key access_group override on group's own assignment Replaces the previous intersect-with-team.access_group_ids check, which made the override unreachable in practice (the team-gate fallback already covered every case the intersection allowed). The override now resolves each of the key's access_group_ids via get_access_object and accepts the group only if its assigned_team_ids includes the key's team_id, or its assigned_key_ids includes the key's token. This fulfills the original ask (a key can extend a team's allow-list via a group the admin granted to that team or that specific key) while still rejecting foreign groups referenced by team members of other teams. * [Fix] Proxy/Key Management: Honor team_member_permissions /key/list In /key/list Endpoint When a team grants /key/list via team_member_permissions, non-admin members should see all keys for that team — same as a team admin. Previously the classification in list_keys() only checked admin status, so permitted members fell into the service-account-only path and could not see other members' personal keys. Routes those members into the full-visibility set. * Fix access-group bypass via litellm-model fallback path When _get_all_deployments returns 0 candidates and the litellm-model fallback branch (_get_deployment_by_litellm_model) finds deployments that the access-group filter then empties, _access_group_filter_emptied_candidates remained False (it was captured before that branch ran). The router would then proceed to default fallbacks; the fallback model could have no access_groups and short-circuit the filter, silently serving a caller blocked by access-group restrictions. Update the flag inside the litellm-model branch when filtering empties a non-empty candidate set so the default-fallback guard still triggers. * fix(proxy): redact MCP server URL and headers for non-admin viewers (VERIA-8) Many MCP integrations (Zapier, etc.) embed an upstream API key directly in the server URL, e.g. ``https://actions.zapier.com/mcp/<api-key>/sse``. The list and single-server endpoints were returning the full URL to any authenticated user — `_redact_mcp_credentials` only stripped the explicit ``credentials`` field, and `_sanitize_mcp_server_for_virtual_key` only ran for restricted virtual keys. Non-admin internal users could read the dashboard, click the unmask toggle, and exfiltrate the raw token. Add `_sanitize_mcp_server_for_non_admin` that runs on top of the existing credential redaction and clears the credential-bearing fields: - ``url`` (the primary leak vector) - ``spec_path`` (OpenAPI spec URLs that may carry tokens) - ``static_headers`` / ``extra_headers`` (Authorization) - ``env`` (arbitrary secrets) - ``authorization_url`` / ``token_url`` / ``registration_url`` Identity fields (``server_id``, ``alias``, ``mcp_info``, etc.) are preserved so the UI can still list servers a non-admin's team has access to. Apply the new sanitizer in `fetch_all_mcp_servers` and the per-server fetch path right after the existing virtual-key branch. Update the existing `test_list_mcp_servers_non_admin_user_filtered` assertions that previously checked URL visibility. Frontend defense-in-depth: hide the URL unmask toggle on `mcp_server_view.tsx` unless the viewer is a proxy admin. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * Fix runtime policy attachment initialization Mark runtime-created policies and attachments initialized so global policy attachments created from the policy builder apply immediately without requiring a restart. Co-authored-by: Cursor <cursoragent@cursor.com> * test(router): cover _try_early_resolve_deployments_for_model_not_in_names The router_code_coverage CI check requires every function in router.py to be referenced by at least one test under tests/{local_testing, router_unit_tests,test_litellm} in a file with "router" in its name. The recently-extracted helper had no direct test, so the check failed with "0.45% of functions in router.py are not tested". Add a focused test that exercises the four return paths: model already in self.model_names, no fallback applies, pattern-router match, and default_deployment substitution (also asserting the stored default isn't mutated). https://claude.ai/code/session_019AVp1XL7RT9RxRe4qRLkay * Fix policy registry teardown in tests Reset the policy ID index during policy engine test cleanup so stale policy versions cannot leak between tests. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(batches): count non-chat tokens, validate batch-file model access (VERIA-39) (#27015) * fix(batches): count non-chat tokens and validate every model in batch file Two security control bypasses on POST /v1/batches: 1. `_get_batch_job_input_file_usage` only summed tokens for `body.messages` (chat completions). Embedding (`input`) and text completion (`prompt`) batches reported zero, letting massive non-chat workloads slip past TPM rate limits. Extend the counter to handle string and list shapes for both fields. 2. The batch input file was forwarded to the upstream provider without inspecting the models named inside the JSONL — only the outer `model` query parameter was checked against the caller's allowlist. A caller restricted to gpt-3.5 could submit a batch targeting gpt-4o and the upstream would execute it under the proxy's shared API key. Add `_get_models_from_batch_input_file_content` (returns the distinct `body.model` values) and call it from `_enforce_batch_file_model_access` in the pre-call hook, which runs each model through `can_key_call_model` so the same allowlist semantics (wildcards, access groups, all-proxy-models, team aliases) the proxy enforces on `/chat/completions` apply here too. Any unauthorized model raises a 403 before the file is forwarded. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(batches): count pre-tokenized prompt/input shapes, classify 403 logs Two follow-ups from the Greptile review on the batch validation PR: 1. P1 TPM bypass via integer token arrays. The OpenAI batch schema accepts ``prompt`` and ``input`` as ``list[int]`` (a single pre-tokenized prompt) or ``list[list[int]]`` (multiple) in addition to the string and ``list[str]`` shapes. Pre-fix only the string shapes were counted, so a caller could submit a batch with hundreds of millions of pre-tokenized tokens and the rate limiter would record zero. Extract the per-field logic into ``_count_prompt_or_input_tokens`` and count each int as one token. 2. P2 access-denial logs were indistinguishable from I/O failures. ``count_input_file_usage`` caught every exception under a generic "Error counting input file usage" message, so an intentional 403 from ``_enforce_batch_file_model_access`` looked the same in the logs as a missing file or a Prisma timeout. Catch ``HTTPException`` separately and log 403s at WARNING level with a security-relevant message before re-raising. Tests cover the new shapes: single ``list[int]``, ``list[list[int]]`` (the worst-case bypass vector), and embeddings ``input`` with pre-tokenized arrays. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(proxy): re-validate user_id after /user/info re-parses query (#27009) * fix(proxy): re-validate user_id ownership after /user/info re-parses query The route-level access check in `RouteChecks.non_proxy_admin_allowed_routes_check` reads `request.query_params.get("user_id")`, which decodes literal `+` to spaces. The endpoint then re-parses the raw query string with `urllib.unquote` in `get_user_id_from_request` to preserve `+` characters (so plus-addressed emails work as user_ids). Those two paths produce different ids: a caller who registered a user_id containing a literal space could pass the route check and then read another user's row by sending the encoded `+` form. Add `_enforce_user_info_access` and call it after `_normalize_user_info_user_id` returns the final id. Proxy admin / view-only admin still bypass; everyone else must match the resolved user_id (or have no user_id, which falls back to the caller's own id later in the handler). Tests cover the admin bypass, owner-match path, and the cross-user lookup that this change blocks. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(proxy): apply user_info ownership check to PROXY_ADMIN_VIEW_ONLY `_enforce_user_info_access` was bypassing both PROXY_ADMIN and PROXY_ADMIN_VIEW_ONLY, but the upstream route check in `RouteChecks.non_proxy_admin_allowed_routes_check` only treats PROXY_ADMIN as a true admin for the `/user/info` route — view-only admins go through the `user_id == valid_token.user_id` enforcement along with regular users. Mirroring that asymmetry left the same encoded-`+` bypass open for view-only admins whose user_id contains a literal space. Drop the PROXY_ADMIN_VIEW_ONLY exemption so the post-decode re-check matches the upstream rule. Update tests: a view-only admin must now be blocked from cross-user lookups but still allowed to read their own row. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(spend-logs): opt-in suppression of stack traces in spend-tracking error logs Adds LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS env var. When set to true and the proxy log level is INFO or above, spend-tracking error paths emit a single ERROR line without the full traceback. Stack traces are preserved at DEBUG and the Sentry / proxy_logging_obj.failure_handler path is unchanged. The new spend_log_error helper is wired through the spend write hot path: - DBSpendUpdateWriter (update_database, _update_*_db, batch upsert, redis-commit fallbacks) - _ProxyDBLogger._PROXY_track_cost_callback - get_logging_payload exception path - update_spend / update_daily_tag_spend / spend logs queue monitor Resolves LIT-2704. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend This call site previously logged a single-line error via verbose_proxy_logger.error() with no traceback. Switching it to spend_log_error(..., exc=e) caused a full stack trace to render by default (when LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS is unset), which contradicts the PR goal of leaving default behavior unchanged. Revert this specific site to the original error log call. * fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend Bugbot caught a regression: the previous error log here was a single-line verbose_proxy_logger.error(...) with no traceback. spend_log_error attaches the active exception's traceback by default (when the suppression env var is unset), so swapping it in changed default behavior. Revert this one site to its original .error() call to keep the PR strictly opt-in. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(spend-logs): suppress traceback in SpendLogs error_information row Extend LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS to the failure callback so the per-row Metadata pane in the UI no longer shows the stack trace when the opt-in env var is set, matching the existing console-side suppression. https://claude.ai/code/session_014dztoRbRnRvq54HL9EyHx6 * [Fix] Proxy: Repair Merge Fallout In Router-Override Fallback Auth Conflict resolution for #26968 dropped the `Iterator` typing import (NameError at module load), left a dead `fallback_models = cast(...)` block, and the new tests called `_enforce_key_and_fallback_model_access` without the now-required `request` kwarg. * isolate dual OTEL handlers * harden cloud file compatibility path * harden cloud file compatibility path * [Fix] Proxy/Key Management: Align Key-Org Membership Checks On Generate And Regenerate Mirrors the membership rule on /key/update so that /key/generate and /key/{key}/regenerate apply the same `_validate_caller_can_assign_key_org` gate when the caller specifies an `organization_id`. Proxy admins bypass. The check no-ops when `organization_id` is not being set. * thread trusted params through vertex file content * trust only server legacy file flag * chore(proxy): keep public AI hub unauthenticated * fix(proxy): preserve low-detail readiness status * [Test] Anthropic: Replace Legacy Claude-4-Sonnet Alias With Haiku 4.5 Three live-API tests pinned to claude-4-sonnet-20250514, which is a non-canonical alias of claude-sonnet-4-20250514. Anthropic's main API no longer resolves the legacy form under freshly issued keys, so the tests fail with not_found_error. The token counter test pinned to claude-sonnet-4-20250514 itself (deprecation_date 2026-05-14, two weeks out) was on borrowed time too. Bump all four to claude-haiku-4-5-20251001 — capability superset for what these tests exercise (streaming, parallel tool calling, extended thinking, token counting), no upcoming deprecation, cheaper per-token. * chore(proxy): move URL-valued model/file_id guard from SDK to proxy The previous per-provider guards in HuggingFace, Oobabooga, and Gemini files lived in the SDK layer, breaking SDK callers who legitimately pass URL-valued model identifiers. Move the check to the proxy boundary in add_litellm_data_to_request so SDK users keep working while proxy users default-deny URL-valued model and file_id, with admin opt-in via litellm.provider_url_destination_allowed_hosts. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * [Chore] Proxy/UI: Drop stray _experimental/out/chat/index.html This file is a regenerable UI build artifact that should not be tracked in source. Removing so the merge into litellm_internal_staging stays clean. * [Test] Anthropic Passthrough: Bump Streaming Cost-Injection Test To Haiku 4.5 test_anthropic_messages_streaming_cost_injection hits the proxy's /v1/messages route, which routes via the anthropic/* wildcard to api.anthropic.com. The 404 surfaced in the test was Anthropic's own not_found_error propagated back through the proxy (visible from the x-litellm-model-id hash on the response — the proxy did route). Same root cause as the prior commit: the legacy claude-4-sonnet-20250514 alias is no longer recognized by Anthropic's main API under the new key. Swap to claude-haiku-4-5-20251001 — same routing path, canonical model. * fix(proxy): handle ownership-recording failures after upstream create If record_container_owner raises after the upstream container is created, the user previously got a 500 with no usable container — they were billed for an unreachable resource. Move ownership recording into the create path's exception handling and split the two failure modes: - HTTPException from the recorder (auth conflicts) propagates verbatim so the client sees the real status code, not a generic LLM error. - Unexpected exceptions are logged and swallowed; the response is returned to the caller so they aren't billed for a container they can't address. The DB row stays untracked until an operator reconciles. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(guardrails): close post-call coverage gaps * fix(types): add /team/permissions_bulk_update to management_routes The blocklist check in _check_proxy_admin_viewer_access only fires for routes that match LiteLLMRoutes.management_routes — the bulk-update endpoint was missing from that list, so the test for view-only admins on /team/permissions_bulk_update fell through to "allow." Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * [Test] Anthropic Passthrough: Bump Thinking Tests Off Legacy Sonnet 4 Alias base_anthropic_messages_test.test_anthropic_messages_with_thinking and test_anthropic_streaming_with_thinking still pinned to claude-4-sonnet-20250514 — the same legacy alias Anthropic no longer recognizes under freshly issued keys. The other four tests in this base class already use claude-sonnet-4-5-20250929; these two were missed. Bump to claude-haiku-4-5-20251001 (supports_reasoning=true, no upcoming deprecation). Subclasses including TestAnthropicPassthroughBasic inherit these methods. * fix(guardrails): cover multi-choice output variants * fix(proxy): preserve public ai hub ui setting * fix(scim): cascade FK cleanup on user delete and surface block status in UI SCIM DELETE /Users/{id} previously called litellm_usertable.delete without clearing rows that FK back to the user, so Postgres rejected the delete with LiteLLM_InvitationLink_user_id_fkey and the SCIM caller saw a 500. Add a helper to drop invitation_link, organization_membership, and team_membership rows before the user delete (mirrors /user/delete in internal_user_endpoints). Also add a Status column to the Virtual Keys and Internal Users tables so admins can see at a glance which keys are blocked and which users SCIM has deactivated. SCIM-blocked keys carry a tooltip explaining the origin. Pin the dashboard's Node version to 20 via .nvmrc to match CI. * chore: update Next.js build artifacts (2026-05-02 03:21 UTC, node v20.20.2) * perf(proxy): cache container/skill ownership reads on the hot path Container ownership and skill rows are looked up on every retrieve / delete / list / file-content / chat-completion-with-skill call. The new stores wrapped raw Prisma queries with no cache, putting one DB round-trip on each request. Add an in-process TTL'd cache mirroring the _byok_cred_cache pattern in mcp_server/server.py: per-key (value, monotonic_timestamp), 60s TTL, 10000-entry cap with full-clear on overflow, invalidated by every write. Negative results (`None`) are cached too so untracked-resource checks also skip the DB. Tests cover: cache-after-first-hit, negative caching, write invalidation, no-caching-on-DB-error, TTL expiry, capacity eviction. 56 tests pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore: update Next.js build artifacts (2026-05-02 03:39 UTC, node v20.20.2) * fix: remove traceback key instead of it being "" * fix: linting error * fix(scim): preserve scim_active on PUT when client omits the field A SCIM PUT may legally omit `active` (full-replace with the field absent). Pydantic fills the SCIMUser.active default of True, so the PUT handler was overwriting metadata.scim_active with True even when the client never sent it — silently reactivating a previously SCIM-blocked user and unblocking their keys. Use model_fields_set to detect whether the client actually sent `active`. If omitted, preserve the prior scim_active value and skip the cascade to virtual keys. Also drop comments added in this PR that just narrate what the code does; keep only the docstrings and the SQL-NULL pitfall note that explain non-obvious behaviour. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(proxy): use set lookup for permitted agent filters * fix(mcp): redact command fields for non-admin server views * fix(proxy): forward decoded container ids after ownership checks * fix(caching): handle stale isolated Redis semantic index * fix(cloudflare): support response_text in streaming chunk parser Newer Cloudflare Workers AI models (e.g. Nemotron) emit 'response_text' instead of 'response' on streamed chunks. The non-streaming path was already updated to fall back to 'response_text' (#26385), but the streaming chunk parser still only read 'response', which caused streaming requests against those models to silently produce empty content. Mirror the non-streaming fallback in CloudflareChatResponseIterator.chunk_parser and add a streaming test for the response_text shape. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * Fix code qa * Address bugbot: drop dead encode/decode helpers; preserve empty custom_id - Remove unused _encode_gcp_label_value / _decode_gcp_label_value singular helpers; only the _chunks variants are actually called. - Use 'is not None' check for custom_id so empty-string custom_ids are still labeled and round-trip through batch outputs. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * Forward Vertex file content logging context * test vertex file content logging forwarding Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * Fix Vertex batch output logging mutation * fix: don't mutate caller's logging_obj in _try_transform_vertex_batch_output_to_openai The method was overwriting logging_obj.optional_params, logging_obj.model, and logging_obj.start_time on the caller's Logging instance. When invoked from llm_http_handler.py's generic framework path, the framework's own logging_obj (which already went through pre_call) had its properties clobbered, causing model and start_time to reflect the last batch line's values rather than the original call context. Fix: create a fresh local Logging instance for the per-line transformation instead of mutating the incoming logging_obj. The caller's object is now left entirely untouched regardless of whether a logging_obj was passed in or not. Regression tests added to verify model, start_time, and optional_params are not mutated on the caller's logging_obj. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * feat: add opt-out flag for Vertex batch output transformation Adds litellm.disable_vertex_batch_output_transformation (default False). When True, afile_content returns raw Vertex predictions.jsonl untouched so users that parse candidates/modelVersion directly are not broken. * fix(anthropic,bedrock): omit thinking/output_config when reasoning_effort="none" Setting reasoning_effort="none" on Anthropic chat models (direct, Bedrock Invoke, Bedrock Converse, Vertex AI Anthropic, Azure AI Anthropic) crashed LiteLLM with: litellm.APIConnectionError: 'NoneType' object has no attribute 'get' Both the Anthropic chat transformation and Bedrock Converse called ``AnthropicConfig._map_reasoning_effort`` and assigned the ``None`` it returns for ``"none"`` directly to ``optional_params["thinking"]``. Downstream ``is_thinking_enabled`` then did ``optional_params["thinking"].get("type")`` and crashed. Pop ``thinking`` (and on Claude 4.6/4.7, ``output_config``) instead of assigning ``None``, restoring the documented contract that ``reasoning_effort="none"`` means "do not enable thinking". This also prevents downstream Anthropic 400s ("thinking: Input should be an object", "output_config.effort: Input should be ...") if the bug were ever masked. Verified end-to-end against the live Anthropic API and Bedrock Converse on claude-opus-4-{5,6,7} and claude-sonnet-4-6, plus Bedrock Invoke for Claude 4.5/4.6. Vertex AI Anthropic and Azure AI Anthropic inherit the fixed ``map_openai_params`` from ``AnthropicConfig`` and need no further changes. * fix(vertex-ai): set response=null on batch error entries per OpenAI spec The Vertex batch output transformer was emitting both a populated 'response' and 'error' for failed batch entries. The OpenAI Batch output spec defines them as mutually exclusive: on error 'response' MUST be null. This broke any consumer using 'result["response"] is None' to detect failures. * test(vertex-ai): cover transformation_error path emits response=null * fix(security): sandbox jinja2 in gitlab/arize/bitbucket prompt managers DotpromptManager was hardened to render through ImmutableSandboxedEnvironment. The three sibling managers (gitlab, arize, bitbucket) were missed and still instantiate plain jinja2.Environment(), leaving the same attribute-traversal SSTI primitive open: a template fetched from a GitLab/BitBucket repo or Arize Phoenix workspace can reach __class__.__init__.__globals__ and execute arbitrary Python on the proxy host. Match the dotprompt pattern by switching all three to ImmutableSandboxedEnvironment. The sandbox blocks the dunder-traversal chain while leaving normal {{ var }} substitution intact, so the template surface is unchanged for legitimate use. Adds tests/test_litellm/integrations/test_prompt_manager_ssti.py (18 cases) verifying each manager's jinja_env is a sandbox, that classic SSTI payloads raise SecurityError, and that ordinary variable rendering still works. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(proxy): drop client-supplied pricing fields from request bodies The proxy currently forwards request-body pricing parameters (the fields on `CustomPricingLiteLLMParams`, plus `metadata.model_info`) into the core call path. Those fields belong to deployment configuration, not to per-request input — sending them from a client mutates the request's recorded cost and, via `litellm.completion` → `register_model`, the process-wide `litellm.model_cost` map for every later caller in the worker. Strip them at the boundary. The strip set is built from `CustomPricingLiteLLMParams.model_fields` so pricing fields added later are covered automatically. Operators who do want clients to supply per-request pricing can opt back in per key or team via `metadata.allow_client_pricing_override = true`, mirroring the existing `allow_client_mock_response` and `allow_client_message_redaction_opt_out` flags. Tests cover the strip set's coverage, root and metadata strips, the opt-in skip on both key and team metadata, and a regression check that the global `litellm.model_cost` map is unmutated after a stripped request. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(proxy): log stripped pricing fields at debug for operator visibility Operators upgrading would otherwise see client-supplied pricing overrides silently stop applying with no diagnostic. Emit a debug-level line listing the dropped fields and pointing at the opt-in flag when any are stripped; stay silent on the no-op path so the log isn't filled with noise. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(proxy): move pricing strip below the litellm_metadata JSON-string parse The strip ran before the proxy parses ``litellm_metadata`` from a JSON string into a dict (a path used by multipart/form-data and ``extra_body`` callers), so ``isinstance(metadata, dict)`` was False and ``model_info`` survived the strip. Move the call to the same post-parse position the ``user_api_key_*`` strip already uses for the same reason. Adds a regression test exercising the JSON-string ``litellm_metadata`` path. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(responses): replace legacy claude-4-sonnet alias in multiturn tool-call test Anthropic's main API no longer resolves the non-canonical 'claude-4-sonnet-20250514' alias for freshly issued keys, returning 404 not_found_error. PR #27031 already swept three other live tests pinned to this alias to claude-haiku-4-5-20251001 but missed test_multiturn_tool_calls in the responses API suite, which is now failing reliably on PR CI runs (e.g. PR #27074, job 1603363). Bump the two model references in test_multiturn_tool_calls to the same claude-haiku-4-5-20251001 snapshot used by PR #27031 -- it covers everything this test exercises (tool calling, multi-turn) and isn't on a deprecation schedule. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * chore(proxy): close callback-config and observability-credential side channels Two related gaps in the proxy's request bouncer: 1. ``is_request_body_safe`` (auth_utils.py) walked the request-body root and the ``litellm_embedding_config`` nested dict, but not ``metadata`` or ``litellm_metadata``. The same fields it bans at root — Langfuse / Langsmith / Arize / PostHog / Braintrust / Phoenix / W&B Weave / GCS / Humanloop / Lunary credentials and routing — were silently accepted when the caller put them inside metadata, retargeting observability callbacks to a caller-controlled host with caller-supplied creds. Walk both metadata containers (and parse the JSON-string form sent via multipart / ``extra_body``) through the same banned-params helper, so the existing ``allow_client_side_credentials`` opt-in covers both paths consistently. 2. The banned-params list was hand-maintained and lagged the canonical ``_supported_callback_params`` allow-list in ``initialize_dynamic_callback_params``. Derive the observability bans from that allow-list (minus a small ``_SAFE_CLIENT_CALLBACK_PARAMS`` set for informational fields like ``langfuse_prompt_version`` and ``langsmith_sampling_rate``) so future integrations are covered automatically; ``_EXTRA_BANNED_OBSERVABILITY_PARAMS`` carries the handful of fields integrations read but the allow-list hasn't caught up to. A guard test fails CI if a new entry is added to ``_supported_callback_params`` without an explicit safe-list decision. Separately in ``litellm_pre_call_utils.py``: add ``callbacks``, ``service_callback``, ``logger_fn``, and ``litellm_disabled_callbacks`` to ``_UNTRUSTED_ROOT_CONTROL_FIELDS``. The first three are appended to worker-wide ``litellm.{input,success,failure,_async_*,service}_callback`` lists / ``litellm.user_logger_fn`` from inside ``function_setup`` — one request poisons every subsequent caller in that worker. The last is the inverse primitive: the legitimate path reads it from key/team metadata, the request-body version silently disables admin-configured audit / observability for the call. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(auth): per-param allow must continue, not return early A pre-existing logic bug in ``_check_banned_params``: when the deployment-level ``configurable_clientside_auth_params`` permitted one banned field, the loop ``return``-ed on the first match instead of ``continue``-ing, so any other banned param later in the same body or metadata dict was never checked. This PR's metadata walk multiplies the surface where that bypass matters — a body pairing an allowed ``api_base`` with an observability credential like ``langfuse_host`` would silently pass. Proxy-wide ``allow_client_side_credentials`` keeps ``return`` (it's a global opt-in for every banned param). The per-param branch becomes ``continue`` so only the one explicitly-permitted field is skipped. Adds a regression test that exercises the api_base + langfuse_host pair. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(vector_store): resolve embedding config at request time, never persist creds The vector store create/update path previously called ``_resolve_embedding_config`` against the admin-configured router/DB model and persisted the resolved ``litellm_embedding_config`` dict (``api_key`` / ``api_base`` / ``api_version``) into the ``litellm_managedvectorstorestable.litellm_params`` column. Because the resolver expanded ``os.environ/...`` references via ``get_secret``, the DB row carried cleartext provider credentials, and the ``/vector_store/{new,info,update,list}`` responses returned them to any authenticated caller who could supply a known admin model name. Move the auto-resolve out of ``create_vector_store_in_db`` and out of the update path. Persist only the user-supplied ``litellm_embedding_model`` reference. Resolve at request-handling time inside ``_update_request_data_with_litellm_managed_vector_store_registry`` so the resolved config lives in the per-request ``data`` dict and is garbage-collected after the response. Legacy rows that were created by an earlier proxy version and already carry a resolved ``litellm_embedding_config`` skip the re-resolution and pass through unchanged so embedding calls keep working. The ``new_vector_store`` response now also runs the existing ``_redact_sensitive_litellm_params`` masker (already used by ``info``, ``update``, and ``list``), defending against caller-supplied cleartext on the create path and against legacy rows whose persisted credentials are still in the database. Existing tests that asserted the old write-time-resolve behaviour are updated to assert the new persistence shape (no embedding config stored, just the model reference). Two new tests cover the use-time path: one asserting fresh resolution happens when a row carries only the model reference, the other asserting legacy rows with persisted config skip re-resolution and continue to work. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(vector_store): tighten registry-mutation comment and dedupe test helpers * fix(vector_store): cache use-time embedding-config resolution Hold the resolved config in a process-memory TTL cache so the request-handling path doesn't run litellm_proxymodeltable.find_first on every vector-store call. * fix(anthropic,bedrock,vertex): forward output_config.effort + 400 on garbage reasoning_effort Follow-up bugs surfaced by the QA sweep on PR #27039 (https://github.com/BerriAI/litellm/pull/27039#issuecomment-4363363610). 1. Stop stripping output_config.effort on Bedrock + Vertex adaptive routes. - Vertex AI Claude 4.6/4.7 accepts output_config.effort on rawPredict (verified end-to-end against us-east5 / global). The strip helper now no-ops for effort. - Bedrock Converse routes output_config into additionalModelRequestFields for anthropic base models so the requested adaptive tier (low/medium/ high/xhigh/max) actually reaches the wire instead of all collapsing to identical thinking. - Bedrock Invoke chat transformation (AmazonAnthropicClaudeConfig) stops popping output_config from the post-AnthropicConfig request body. - Bedrock Invoke /v1/messages allowlist (BedrockInvokeAnthropicMessagesRequest) now lists output_config so the runtime allowlist filter forwards it. 2. Validate effort across Bedrock Converse so 'disabled' / 'invalid' / '' / unsupported tiers (xhigh/max on Sonnet 4.6 or budget-mode 4.5 models) surface as a clean 400 BadRequestError instead of 500. 3. ValueError -> BadRequestError throughout (AnthropicConfig.map_openai_params, _apply_output_config, AmazonConverseConfig._handle_reasoning_effort_parameter). Empty-string effort is now rejected (was silently passing the 'if effort and ...' short-circuit). 4. Floor reasoning_effort='minimal' at the Anthropic provider minimum (1024 budget_tokens) via new ANTHROPIC_MIN_THINKING_BUDGET_TOKENS so it's a usable tier on direct Anthropic / Azure AI Anthropic / Vertex AI Anthropic / Bedrock Invoke (all of which 400 below 1024). 5. model_prices: dedupe duplicate supports_max_reasoning_effort key on claude-opus-4-7 / claude-opus-4-7-20260416. Adds regression tests across all five affected paths; existing tests asserting the silent-strip behavior were updated to reflect the new pass-through and clean 400 surfaces. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(constants): make ANTHROPIC_MIN_THINKING_BUDGET_TOKENS a plain constant The documentation CI test (tests/documentation_tests/test_env_keys.py) asserts every os.getenv() key in the source has a matching entry in the litellm-docs config_settings.md table. ANTHROPIC_MIN_THINKING_BUDGET_TOKENS tracks Anthropic's published wire-protocol minimum (1024) — it's not a user-tunable, so making it env-overridable was wrong anyway. Drop the os.getenv() wrapper; the value is now a plain literal. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(anthropic,bedrock): correct effort error message and dedupe effort_map - Remove 'none' from the Bedrock _validate_anthropic_adaptive_effort error message; it was listed as a valid value but rejected by the membership check, leaving users in a feedback loop if they tried 'none'. - Hoist the duplicated reasoning_effort -> output_config.effort mapping out of AnthropicConfig.map_openai_params and AmazonConverseConfig._handle_reasoning_effort_parameter into a single AnthropicConfig.REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT class constant so the two routes cannot drift. * fix(anthropic): translate reasoning_effort on /v1/messages route Closes the remaining QA-sweep gap on PR #27074: Bedrock Invoke /v1/messages was silently ignoring ``reasoning_effort`` because the shared param filter only kept native Anthropic keys, so every effort tier collapsed to the same behavior on the wire (27/231 cells failing across opus-4-5 / opus-4-6 / sonnet-4-6). Map ``reasoning_effort`` to native Anthropic ``thinking`` / ``output_config.effort`` at the ``AnthropicMessagesConfig`` layer so all four /v1/messages routes (direct Anthropic, Azure AI, Vertex AI, Bedrock Invoke) inherit the same translation: - Add ``reasoning_effort`` to ``AnthropicMessagesRequestOptionalParams`` so the param filter in ``AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param`` no longer drops it before the transformation runs. - Add ``_translate_reasoning_effort_to_anthropic`` and call it from ``transform_anthropic_messages_request``. Mirrors ``AnthropicConfig.map_openai_params`` on the chat completion path (re-uses ``_map_reasoning_effort`` and ``REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT``) so the two routes cannot drift. Pops ``reasoning_effort`` so it never reaches the wire. - Caller-supplied native ``thinking`` / ``output_config.effort`` always win — same precedence as ``_translate_legacy_thinking_for_adaptive_model``. - Garbage values (``""``, ``"disabled"``, ``"invalid"``) raise ``AnthropicError(status_code=400)`` instead of falling through and surfacing as 500s from the provider. - ``"none"`` clears thinking + output_config so callers can opt out per request. Also restores the non-adaptive-model test coverage on Bedrock Invoke /v1/messages that the previous commit lost when ``test_bedrock_messages_strips_output_config`` was renamed to the ``forwards`` variant on Opus 4.7. Adds a new test file ``test_reasoning_effort_translation.py`` covering the translation at the shared config level (adaptive + non-adaptive models, none, garbage, caller precedence) so all four /v1/messages routes are exercised by a single suite. Adds parametrized + behavioral tests on the Bedrock Invoke /v1/messages suite covering: minimal/low/medium/high/xhigh/max mapping for adaptive models, thinking-budget mapping for non-adaptive Opus 4.5, ``none`` clears both, garbage raises 400, explicit ``output_config`` wins. Refs: https://github.com/BerriAI/litellm/pull/27074 * fix(anthropic,bedrock): reject unmapped reasoning_effort at mapping site Both the chat completion path (AnthropicConfig.map_openai_params) and the Bedrock Converse path (_handle_reasoning_effort_parameter) used REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT.get(value, value) which falls back to the raw input on unmapped keys. Combined with _map_reasoning_effort returning type='adaptive' for any string on Claude 4.6/4.7, garbage values (e.g. 'disabled') could leak into optional_params['output_config']['effort'] unvalidated if map_openai_params ran without the downstream transform_request or _validate_anthropic_adaptive_effort check. Mirror the /v1/messages pattern: use .get(value) (no fallback) and raise BadRequestError immediately when the value is unmapped, co-locating validation with the mapping for defense in depth. * style: black formatting Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(anthropic): stop class-attr leak; gate xhigh/max on every route The reasoning-effort mapping dict was a public class attribute on AnthropicConfig, so BaseConfig.get_config returned it as a request parameter and every Anthropic-backed call (Anthropic / Azure / Vertex / Bedrock Invoke) hit a 400 'REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT: Extra inputs are not permitted' from the provider. Move the mapping to a module-level constant. _supports_effort_level only looked the model up under custom_llm_provider='anthropic', so bedrock-prefixed model ids (e.g. bedrock/invoke/us.anthropic.claude-opus-4-7) returned False for both 'max' and 'xhigh' even when the underlying model entry has the flag set. Strip known provider prefixes and retry the lookup against litellm.model_cost directly so per-model gating works on every route. Mirror the per-model xhigh/max gate from AnthropicConfig._apply_output_config in AnthropicMessagesConfig._translate_reasoning_effort_to_anthropic so the /v1/messages route also raises a clean 400 instead of forwarding the unsupported tier. * feat(anthropic,bedrock): strip output_config under drop_params for non-effort models When a proxy fronts Claude Code (which always sends `output_config.effort`) at a pre-4.5 Anthropic model — haiku-3, sonnet-3.5, opus-3, sonnet-4 — the forwarded knob causes a forced 400 the client can't fix. Gating a strip behind the existing `drop_params` flag lets operators opt into silent fixup once and stop worrying about per-model param hygiene. Default (`drop_params=False`) still forwards and surfaces the provider's error, preserving the strict, debuggable contract from #27074. Per https://platform.claude.com/docs/en/build-with-claude/effort the supporting set is Opus 4.5+, Sonnet 4.6+, and Mythos Preview; everything else is dropped (with a verbose_logger warning so the strip is visible). Recognition uses model-name patterns plus a fallback to any `supports_*_reasoning_effort` flag in the model map for forward compatibility with new entries. https://claude.ai/code/session_01WjHq31rvXT6xYNdVmSJvRp (cherry picked from commit |
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Ryan Crabbe
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dc46467235
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fix(tests): replace deprecated Bedrock Claude 3.7 Sonnet model ID
AWS Bedrock has reached end-of-life for `claude-3-7-sonnet-20250219-v1:0`, returning 404s with "This model version has reached the end of its life." Update test references to `claude-sonnet-4-5-20250929-v1:0` (same capability surface: thinking, tools, prompt caching, PDF input, vision, computer use). The bedrock/invoke pass-through tests stay on Sonnet 3.5 since Sonnet 4.5 is converse-only on Bedrock. |
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Milan
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ec735074a2
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fix(proxy): reapply Bedrock guardrail spend logging (#25854)
Restore guardrail spend/UI event_type wiring, request_data on streaming OUTPUT paths, and centralized match redaction after the upstream revert. Made-with: Cursor |
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ishaan-berri
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0e42d4cb08
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April 21st Ishaan Branch (#26213)
* fix(otel): preserve Splunk Observability Cloud trace OTLP endpoint (#26183) * fix(otel): preserve Splunk Observability Cloud trace OTLP URL Splunk ingest uses /v2/trace/otlp; _normalize_otel_endpoint must not append /v1/traces. - Return trace endpoints unchanged when they match Splunk OTLP path patterns - Add unit tests for observability.splunkcloud.com, signalfx.com, and /trace/otlp suffix - Set OTEL_EXPORTER_OTLP_PROTOCOL in protocol selection tests (from_env precedence over OTEL_EXPORTER) Made-with: Cursor * test(otel): use parameterized.expand for Splunk OTLP URL cases Made-with: Cursor * fix(otel): narrow Splunk trace URL guard to /v2/trace/otlp only Made-with: Cursor * test(otel): cover OTEL_EXPORTER fallback when OTLP protocol env unset Made-with: Cursor * Add Openrouter Opus 4.7 Entry (#26130) --------- Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Matt Greathouse <matt5316@gmail.com> |
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ishaan-berri
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8a4a775b1b
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fix(logging): add litellm_call_id to StandardLoggingPayload and OTel span (#26133)
* add litellm_call_id field to StandardLoggingPayload * populate litellm_call_id in get_standard_logging_object_payload * emit litellm.call_id span attribute in OTel integration * test: litellm_call_id is present in StandardLoggingPayload * test: litellm.call_id emitted as OTel span attribute * test: allow litellm. prefix attributes in redacted span validator |
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Krrish Dholakia
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386f334fee
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Prompt Compression - add it to the proxy (#25729)
* refactor: new agentic loop event hook simplifies how to create logic for tool based multi llm calls * fix: compress - make it work on anthropic input as well * fix(compress.py): working prompt compression for claude code ensures claude code messages can run through proxy easily * docs: add agentic loop hook guide * docs: add agentic_loop_hook to sidebar * fix: fix multiple arguments error * fix: fix tool call loop for compression on streaming /v1/messages * fix: fix linting errors * fix: fix ci/cd errors * feat(litellm_pre_call_utils.py): use claude code session for litellm session id allows claude code logs to be stitched together, making it easy to know they were all part of the same conversation * fix: suppress incorrect mypy warning rE: module * revert: drop PR's changes to litellm/proxy/_experimental/out/ Restores the 34 HTML files under _experimental/out/ to their pre-PR paths (X/index.html -> X.html). All renames are R100 (content unchanged); no other files are touched. * fix: address greptile review comments on PR #25729 - Skip ``kwargs["tools"] = []`` injection when compression is a no-op — Anthropic Messages rejects empty tool arrays on requests that did not originally declare tools. - Move agentic-loop safety guards (fingerprint cycle / max depth) out of the per-callback try/except so they propagate instead of being swallowed by the generic exception handler. Extracted _check_agentic_loop_safety. - Gate generic ``x-<vendor>-session-id`` capture behind the LITELLM_CAPTURE_VENDOR_SESSION_HEADERS env var (off by default) to preserve backwards compatibility; explicit x-litellm-* headers are unaffected. - Fix monkeypatch target in pre-call-hook test to patch the actual module-level binding (litellm.integrations.compression_interception.handler.compress). - Add regression tests for empty-tools skip and opt-in session capture. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * revert: drop LITELLM_CAPTURE_VENDOR_SESSION_HEADERS flag Generic x-<vendor>-session-id header capture is a new feature and only runs *after* the explicit x-litellm-trace-id / x-litellm-session-id checks, so it does not change behavior for any existing caller that was already using the LiteLLM headers — no backwards-incompatibility to gate. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor(compress): replace input_type with CallTypes call_type Drop the bespoke ``CompressionInputType`` literal and use the existing ``litellm.types.utils.CallTypes`` enum instead. ``litellm.compress()`` now takes ``call_type: Union[CallTypes, str]`` (default ``CallTypes.completion``) — no new concept to learn, and the enum is already the way the rest of the codebase talks about request shapes. Supported values: ``completion`` / ``acompletion`` (OpenAI chat-completions shape) and ``anthropic_messages`` (Anthropic structured content blocks). Updated: compress(), the compression_interception handler, tests, docs, and the two eval scripts. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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Yuneng Jiang
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11c3270cdc
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_yj_apr17
# Conflicts: # litellm/__init__.py |
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Ishaan Jaffer
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e8461b5b97
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style: run black formatter on files from main merge | ||
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user
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d0601692b8
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fix(proxy): strip user_api_key_metadata injection slots from user input
Expand the pre-call metadata strip to also remove user_api_key_metadata and user_api_key_team_metadata. The proxy writes these fields into data[_metadata_variable_name] with admin-authoritative values, but only into that one metadata key; the caller's value in the OTHER metadata key (metadata vs litellm_metadata) would otherwise persist and be picked up by _get_admin_metadata, letting a caller supply their own 'admin' config to disable guardrails, opt out of global policies, etc. VERIA-28 (High): Security Policy and Guardrail Bypass via Unsanitized Request Metadata. Add regression test at the proxy boundary verifying the strip, and extend the guardrail test to cover the post-strip admin-config path. |
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user
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22572eafaf
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fix: merge admin metadata from both metadata and litellm_metadata
Greptile P2: _get_admin_metadata used 'litellm_metadata or metadata', meaning a caller sending a non-empty litellm_metadata would shadow admin config the proxy had injected into data['metadata']. Admin exemptions would be silently ignored. Check both keys and prefer whichever contains admin fields. Add regression test covering the shadowing scenario. |
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user
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34e9be1ba7
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fix: merge team metadata in admin helper, remove turn_off_message_logging from dynamic params
Include user_api_key_team_metadata alongside user_api_key_metadata in _get_admin_metadata() so team-level guardrail settings are respected. Key-level settings take precedence over team-level. Remove turn_off_message_logging from _supported_callback_params so it cannot be set via request metadata. Admin controls logging globally or via key/team configuration. Update tests to verify user-injected guardrail flags are ignored while admin-configured flags are respected. |
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Tim Ren
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dd4a41951f
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fix(utils): allowed_openai_params must not forward unset params as None (#25777)
* feat(proxy): add NO_OPENAPI env var to disable /openapi.json endpoint (#25696) * feat(proxy): add NO_OPENAPI env var to disable /openapi.json endpoint - Fixes #25538 * test(proxy): add tests for _get_openapi_url --------- Co-authored-by: Progressive-engg <lov.kumari55@gmail.com> * feat(prometheus): add api_provider label to spend metric (#25693) * feat(prometheus): add api_provider label to spend metric Add `api_provider` to `litellm_spend_metric` labels so users can build Grafana dashboards that break down spend by cloud provider (e.g. bedrock, anthropic, openai, azure, vertex_ai). The `api_provider` label already exists in UserAPIKeyLabelValues and is populated from `standard_logging_payload["custom_llm_provider"]`, but was not included in the spend metric's label list. * add api_provider to requests metric + add test Address review feedback: - Add api_provider to litellm_requests_metric too (same call-site as spend metric, keeps label sets in sync) - Add test_api_provider_in_spend_and_requests_metrics following the existing pattern in test_prometheus_labels.py * fix: ensure `litellm_metadata` is attached to `pre_call` guardrail to align with `post_call` guardrail (#25641) * fix: ensure `litellm_metadata` is attached to pre_call to align with post_call * refactor: remove unused BaseTranslation._ensure_litellm_metadata * refactor: module level imports for ensure_litellm_metadata and CodeQL * fix: update based off of Codex comment * revert: undo usage of `_guardrail_litellm_metadata` * feat: add pricing entry for openrouter/google/gemini-3.1-flash-lite-preview (#25610) * fix(bedrock): skip synthetic tool injection for json_object with no schema (#25740) When response_format={"type": "json_object"} is sent without a JSON schema, _create_json_tool_call_for_response_format builds a tool with an empty schema (properties: {}). The model follows the empty schema and returns {} instead of the actual JSON the caller asked for. This patch: - Skips synthetic json_tool_call injection when no schema is provided. The model already returns JSON when the prompt asks for it. - Fixes finish_reason: after _filter_json_mode_tools strips all synthetic tool calls, finish_reason stays "tool_calls" instead of "stop". Callers (like the OpenAI SDK) misinterpret this as a pending tool invocation. json_schema requests with an explicit schema are unchanged. Co-authored-by: Claude <noreply@anthropic.com> * fix(utils): allowed_openai_params must not forward unset params as None `_apply_openai_param_overrides` iterated `allowed_openai_params` and unconditionally wrote `optional_params[param] = non_default_params.pop(param, None)` for each entry. If the caller listed a param name but did not actually send that param in the request, the pop returned `None` and `None` was still written to `optional_params`. The openai SDK then rejected it as a top-level kwarg: AsyncCompletions.create() got an unexpected keyword argument 'enable_thinking' Reproducer (from #25697): allowed_openai_params = ["chat_template_kwargs", "enable_thinking"] body = {"chat_template_kwargs": {"enable_thinking": False}} Here `enable_thinking` is only present nested inside `chat_template_kwargs`, so the helper should forward `chat_template_kwargs` and leave `enable_thinking` alone. Instead it wrote `optional_params["enable_thinking"] = None`. Fix: only forward a param if it was actually present in `non_default_params`. Behavior is unchanged for the happy path (param sent → still forwarded), and the explicit `None` leakage is gone. Adds a regression test exercising the helper in isolation so the test does not depend on any provider-specific `map_openai_params` plumbing. Fixes #25697 --------- Co-authored-by: lovek629 <59618812+lovek629@users.noreply.github.com> Co-authored-by: Progressive-engg <lov.kumari55@gmail.com> Co-authored-by: Ori Kotek <ori.k@codium.ai> Co-authored-by: Alexander Grattan <51346343+agrattan0820@users.noreply.github.com> Co-authored-by: Mohana Siddhartha Chivukula <103447836+iamsiddhu3007@users.noreply.github.com> Co-authored-by: Amiram Mizne <amiramm@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com> |
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Sameer Kankute
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1a9a31e4a2
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Merge pull request #25665 from BerriAI/litellm_oss_staging_04_13_2026_p1
litellm oss staging 04/13/2026 |
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Emerson Gomes
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a302b53980
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fix: drain datadog batches safely (#25663)
* fix: drain datadog batches safely * fix: preserve datadog batches on 413 * fix: import time in datadog flush queue * test: cover datadog batching edge cases * fix: only stamp successful datadog flushes * test: use sync mock for datadog payload builder |
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Sameer Kankute
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972e42c7fd
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Merge branch 'main' into litellm_oss_staging_04_04_2026 | ||
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yuneng-jiang
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a306092d47
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Merge pull request #25463 from BerriAI/litellm_oss_staging_04_09_2026
Litellm oss staging 04 09 2026 |
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ryan-crabbe-berri
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65d9fadf45
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Merge pull request #25575 from BerriAI/litellm_feat-per-guardrail-opt-out-for-global-guardrails
feat(guardrails): per-team opt-out for specific global guardrails |
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Ryan Crabbe
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3d72e2a6f3
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fix(guardrails): address PR #25575 review feedback + sync kill switch with opt-out list
Renames the new per-guardrail opt-out field from `disabled_global_guardrails` to `opted_out_global_guardrails` to eliminate the one-character collision with the legacy `disable_global_guardrails` boolean kill switch. Adds a type guard on the new gate so a misnamed bool can't crash the guardrail check. Filters duplicates out of the team-edit guardrail display for legacy teams that have a global name persisted in `metadata.guardrails` from before this PR. Drops the unused `isGuardrailsLoading` and `guardrailsError` destructures left in AddModelForm after the hook refactor. Adds Python tests for the new gate behavior (root, litellm_metadata, metadata, non-matching name, empty list, malformed bool value, opt-in coexistence) and extends useGuardrails.test.ts to exercise the global / optional partition logic that the rebuilt hook performs in its `select` transform. Wires the legacy kill switch and the new opt-out list together in the team edit form so they can never fall out of sync: - Toggling the kill switch reactively updates the Guardrails Select via `onValuesChange` — switch on strips all globals from the selection, switch off re-adds them. Existing opt-in extras are preserved either way. - When the switch is on, global options in the Select are individually disabled (greyed out) so the user can still manage opt-in guardrails but cannot accidentally re-enable a global the kill switch is bypassing. - The save handler writes both fields together: `disable_global_guardrails` reflects the switch, and `opted_out_global_guardrails` is set to either every global (when the switch is on) or the user's explicit opt-outs. - `effectiveGuardrails` for the form's initialValues honors the kill switch on legacy teams so the form opens in a state that matches what the runtime gate is actually doing — fixes the visual lie where chips appeared active while the switch was bypassing them. The backend gate already reads the list as the primary path with the bool as a fallback, so untouched legacy teams keep working until they get edited, at which point they migrate naturally. |
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Ryan Crabbe
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ef38c665ca
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fix(guardrails): use plural key in get_disable_global_guardrail
Rename disable_global_guardrail → disable_global_guardrails to match the key name used by litellm_pre_call_utils.py, the API endpoints, and the UI when propagating key/team metadata. The singular form was introduced in PR #16983 and has never matched the plural form written by the rest of the codebase, so the feature silently did nothing. Re-applies fix originally from #25488. Original commit could not be merged due to missing signature. Co-Authored-By: Remi Mabon <remi.mabon@redcare-pharmacy.com> |
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Yuneng Jiang
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909247785e
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Merge remote-tracking branch 'origin' into litellm_internal_staging_04_11_2026 | ||
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jimmychen-p72
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2fe615b373
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fix(s3): add retry with exponential backoff for transient S3 503/500 errors (#25530)
* fix(s3): add retry with exponential backoff for transient S3 503/500 errors S3 occasionally returns 503 "Slow Down" during PUT operations when request rates spike above partition limits. The current code makes a single upload attempt via httpx — unlike boto3, httpx has no built-in retry for transient S3 errors. Failed uploads permanently lose the request's audit/logging data. Add exponential backoff retry (3 attempts, 1s/2s delays) for S3 500/503 responses in both async_upload_data_to_s3 and upload_data_to_s3. Logs a warning on each retry with the S3 object key for observability. In production we observed ~18 permanent S3 upload failures per day (124 over 7 days) — all transient 503s that would have succeeded on a single retry. * test(s3): add unit tests for S3 upload retry logic Tests cover: - Async retry on 503 (succeeds on second attempt) - Async retry on 500 - Exhausted retries on persistent 503 (calls handle_callback_failure) - No retry on 4xx errors (403) - Sync retry on 503 * style(s3): move time import to module level Address review feedback: move `import time` from inside upload_data_to_s3 to the top-level imports per project style guide. |
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Josh
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7d2f069361
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Reduce default latency histogram bucket cardinality (#25527)
* feat(prometheus): reduce default latency bucket cardinality and make configurable
* test(prometheus): add coverage for PrometheusServicesLogger latency buckets
* Revert "test(prometheus): add coverage for PrometheusServicesLogger latency buckets"
This reverts commit
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stuxf
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a6c30b30bf
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build: migrate packaging, CI, and Docker from Poetry to uv (#25007)
* build: migrate packaging metadata to uv * ci: move automation and local tooling to uv * docker: migrate image builds and runtime setup to uv * docs: update install and deployment guidance for uv * chore: align auxiliary scripts and tests with uv * test: harden test_litellm isolation * fix: keep release and health check images self-contained * build: pin uv tooling and health check deps * test: isolate bedrock image request formatting from suite state * test: cover sandbox executor requirements flow * ci: fix circleci no-op command steps * ci: fix circleci publish workflow parsing * fix: stabilize remaining uv migration CI checks * ci: increase matrix test timeout headroom * fix: restore published docker and license coverage * fix: restore proxy runtime build parity * fix: restore proxy extras parity and venv migrations * ci: persist uv path across circleci steps * fix: keep psycopg binary in default test env * docker: preserve prisma cache across stages * test: run local proxy checks through uv python * build: restore runtime deps moved into ci * build: refresh uv lock after upstream merge * fix: restore module import in test_check_migration after merge The conflict resolution imported only the function but the test body references check_migration as a module throughout. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: revert dependency promotions, remove nodejs-wheel-binaries, fix Docker layer caching - Move google-generativeai, Pillow, tenacity back to ci group (they are lazily imported and bloat the base SDK install needlessly) - Remove nodejs-wheel-binaries from extra_proxy and proxy-dev (redundant in Docker where system Node.js is already installed via apk) - Remove all nodejs-wheel node replacement and venv npm patching blocks from Dockerfiles since the wheel is no longer installed - Add --no-default-groups to CodSpeed benchmark workflow so the benchmark environment matches the old minimal pip install footprint - Apply standard uv two-phase Docker pattern: copy metadata first, install deps (cached layer), then copy source and install project - Replace CircleCI enterprise no-op with proper uv sync command Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: regenerate uv.lock after removing nodejs-wheel-binaries Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): use cache/restore instead of cache to prevent cache poisoning The old workflow used actions/cache/restore (read-only). The uv migration changed it to actions/cache (read-write), which zizmor flags as a cache poisoning risk. Restore the safer read-only variant. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): disable setup-uv built-in cache to silence cache-poisoning alert The setup-uv action enables caching by default, which zizmor flags as a cache poisoning risk. Disable it since we already use a read-only cache/restore step. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): disable setup-uv cache in publish workflow Silences zizmor cache-poisoning alert. Publishing workflow runs infrequently on protected branches so caching adds no real benefit. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(test): remove duplicate verbose_logger mock in test_check_migration The logger was patched twice — first via mocker.patch() then via mocker.patch.object(autospec=True). The second call fails because autospec cannot inspect an already-mocked attribute. Remove the redundant first patch. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): free disk space before Docker build in test-server-root-path The Dockerfile.non_root build ran out of disk on the CI runner. Remove Android SDK, .NET, Boost, and GHC toolchains (~12GB) to free space. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Sameer Kankute
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cb057ad44b
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fix(websearch_interception): ensure spend/cost logging runs when stream=True
The deployment hook now converts stream=True→False in wrapper_async's scope so the streaming early-return path is skipped and logging executes. logging_obj.stream is synced after the hook, and the original stream intent is recovered for the short-circuit path. Made-with: Cursor |
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Krrish Dholakia
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f42ffed2bd
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Litellm oss staging 04 02 2026 p1 (#25055)
* fix(vertex_ai): support pluggable (executable) credential_source for WIF auth (#24700) The WIF credential dispatch in load_auth() only handled identity_pool and aws credential types. When credential_source.executable was present (used for Azure Managed Identity via Workload Identity Federation), it fell through to identity_pool.Credentials which rejected it with MalformedError. Add dispatch to google.auth.pluggable.Credentials for executable-type credential sources, following the same pattern as the existing identity_pool and aws helpers. Fixes authentication for Azure Container Apps → GCP Vertex AI via WIF with executable credential sources. * feat(logging): add component and logger fields to JSON logs for 3rd p… (#24447) * feat(logging): add component and logger fields to JSON logs for 3rd party filtering * Let user-supplied extra fields win over auto-generated component/logger, tighten test assertions * Feat - Add organization into the metrics metadata for org_id & org_alias (#24440) * Add org_id and org_alias label names to Prometheus metric definitions * Add user_api_key_org_alias to StandardLoggingUserAPIKeyMetadata * Populate user_api_key_org_alias in pre-call metadata * Pass org_id and org_alias into per-request Prometheus metric labels * Add test for org labels on per-request Prometheus metrics * chore: resolve test mockdata * Address review: populate org_alias from DB view, add feature flag, use .get() for org metadata * Add org labels to failure path and verify flag behavior in test * Fix test: build flag-off enum_values without org fields * Gate org labels behind feature flag in get_labels() instead of static metric lists * Scope org label injection to metrics that carry team context, remove orphaned budget label defs, add test teardown * Use explicit metric allowlist for org label injection instead of team heuristic * Fix duplicate org label guard, move _org_label_metrics to class constant * Reset custom_prometheus_metadata_labels after duplicate label assertion * fix: emit org labels by default, remove flag, fix missing org_alias in all metadata paths * fix: emit org labels by default, no opt-in flag required * fix: write org_alias to metadata unconditionally in proxy_server.py * fix: 429s from batch creation being converted to 500 (#24703) * add us gov models (#24660) * add us gov models * added max tokens * Litellm dev 04 02 2026 p1 (#25052) * fix: replace hardcoded url * fix: Anthropic web search cost not tracked for Chat Completions The ModelResponse branch in response_object_includes_web_search_call() only checked url_citation annotations and prompt_tokens_details, missing Anthropic's server_tool_use.web_search_requests field. This caused _handle_web_search_cost() to never fire for Anthropic Claude models. Also routes vertex_ai/claude-* models to the Anthropic cost calculator instead of the Gemini one, since Claude on Vertex uses the same server_tool_use billing structure as the direct Anthropic API. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * fix(anthropic): pass logging_obj to client.post for litellm_overhead_time_ms (#24071) When LITELLM_DETAILED_TIMING=true, litellm_overhead_time_ms was null for Anthropic because the handler did not pass logging_obj to client.post(), so track_llm_api_timing could not set llm_api_duration_ms. Pass logging_obj=logging_obj at all four post() call sites (make_call, make_sync_call, acompletion, completion). Add test to ensure make_call passes logging_obj to client.post. Made-with: Cursor * sap - add additional parameters for grounding - additional parameter for grounding added for the sap provider * sap - fix models * (sap) add filtering, masking, translation SAP GEN AI Hub modules * (sap) add tests and docs for new SAP modules * (sap) add support of multiple modules config * (sap) code refactoring * (sap) rename file * test(): add safeguard tests * (sap) update tests * (sap) update docs, solve merge conflict in transformation.py * (sap) linter fix * (sap) Align embedding request transformation with current API * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) mock commit * (sap) run black formater * (sap) add literals to models, add negative tests, fix test for tool transformation * (sap) fix formating * (sap) fix models * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) commit for rerun bot review * (sap) minor improve * (sap) fix after bot review * (sap) lint fix * docs(sap): update documentation * fix(sap): change creds priority * fix(sap): change creds priority * fix(sap): fix sap creds unit test * fix(sap): linter fix * fix(sap): linter fix * linter fix * (sap) update logic of fetching creds, add additional tests * (sap) clean up code * (sap) fix after review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) add a possibility to put the service key by both variants * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) update test * (sap) update service key resolve function * (sap) run black formater * (sap) fix validate credentials, add negative tests for credential fetching * (sap) fix validate credentials, add negative tests for credential fetching * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) fix after bot review * (sap) lint fix * (sap) lint fix * feat: support service_tier in gemini * chore: add a service_tier field mapping from openai to gemini * fix: use x-gemini-service-tier header in response * docs: add service_tier to gemini docs * chore: add defaut/standard mapping, and some tests * chore: tidying up some case insensitivity * chore: remove unnecessary guard * fix: remove redundant test file * fix: handle 'auto' case-insensitively * fix: return service_tier on final steamed chunk * chore: black * feat: enable supports_service_tier to gemini models * Fix get_standard_logging_metadata tests * Fix test_get_model_info_bedrock_models * Fix test_get_model_info_bedrock_models * Fix remaining tests * Fix mypy issues * Fix tests * Fix merge conflicts * Fix code qa * Fix code qa * Fix code qa * Fix greptile review --------- Co-authored-by: michelligabriele <gabriele.michelli@icloud.com> Co-authored-by: Josh <36064836+J-Byron@users.noreply.github.com> Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Alperen Kömürcü <alperen.koemuercue@sap.com> Co-authored-by: Vasilisa Parshikova <vasilisa.parshikova@sap.com> Co-authored-by: Lin Xu <lin.xu03@sap.com> Co-authored-by: Mark McDonald <macd@google.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> |
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Neha Prasad
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d6351a3966
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fix(s3_v2): use prepared URL for SigV4-signed S3 requests (#25074) | ||
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David Chen
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d1df4e838b
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Litellm fix update bedrock models (#24947)
* update bedrock models in tests * updated more tests and model_prices_and_context_window * fix model id and pricing * replace more sonnet models * update tests * git push * update pricing * flaky total cost * monkey patch * relax the cost change * fix and revert some changes * revert the pricing * chore: move cost/pricing changes to bedrock-cost-fixes branch * chore: split Bedrock file-api beta stripping to separate branch Removes strip_unsupported_file_api_betas_for_bedrock_invoke from this branch; see litellm_bedrock_invoke_strip_file_api_betas for that fix. Made-with: Cursor |
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Krrish Dholakia
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bc33cf662f
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Merge pull request #24449 from J-Byron/feat/prometheus-org-budget-metrics
Feat/prometheus org budget metrics |
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Josh
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8a58281cbf | Add org budget metrics initialization at startup | ||
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Krrish Dholakia
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dd0e7dcca8 |
test(prometheus): add tests for spend_logs_metadata in custom labels
Verify that spend_logs_metadata is correctly merged into combined_metadata and flows through to Prometheus custom labels. Tests cover: basic extraction, precedence when keys overlap, all three metadata sources combined, and None handling. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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Josh
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e1481e5dc1 | test(prometheus): add unit tests for org budget metrics | ||
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Krish Dholakia
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a5b7e49713
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Merge branch 'main' into litellm_oss_staging_03_17_2026 | ||
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Sameer Kankute
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784f9431ad
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Merge pull request #24188 from BerriAI/main
merge main 0319 |
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Sameer Kankute
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c545c969f7
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Merge branch 'main' into litellm_oss_staging_03_17_2026 | ||
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Krish Dholakia
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61dde5eb0a
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Merge pull request #24143 from johnib/fix/websearch-short-circuit-copilot
fix: short-circuit websearch for github_copilot provider |
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Krish Dholakia
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8d92d8637d
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Merge branch 'main' into litellm_oss_staging_03_18_2026 | ||
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Jonathan Barazany
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32cb6f0cd9 |
fix: guard short-circuit against providers with native agentic loop
- Skip short-circuit for providers that have a BaseAnthropicMessagesConfig (bedrock, vertex_ai, azure_ai, anthropic) — they use the agentic loop which includes a follow-up LLM synthesis step. Short-circuiting would return raw search text instead of an LLM-synthesized answer. - Add fallback to litellm.get_llm_provider() for custom_llm_provider derivation when litellm_params is overwritten by kwargs. - Add test for bedrock guard. Addresses Greptile review comments #3 and #4. |
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Jonathan Barazany
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141ad04955 |
refactor: reuse get_last_user_message, fix UUID convention, move import
- Replace hand-rolled _extract_search_query with existing get_last_user_message from common_utils - Use full UUID (str(uuid.uuid4())) to match codebase convention - Move uuid import to module level per CLAUDE.md |
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Jonathan Barazany
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3b129260f5 |
fix: use original_stream for short-circuit, propagate derived provider
Addresses Greptile review feedback: - Save original stream flag before pre-request hooks convert it, so streaming callers get SSE events instead of a plain dict - Propagate custom_llm_provider derived inside _execute_pre_request_hooks when it was not explicitly passed by the caller - Add tests covering both scenarios |
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Jonathan Barazany
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b5a775d54e | style: fix Black formatting in test file | ||
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Jonathan Barazany
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6d0763b8ba |
fix: short-circuit websearch for non-Anthropic providers (github_copilot)
For providers like github_copilot that don't natively support web search, Claude Code's search sub-conversations were falling through to the adapter path which strips the web_search tool and has no stream reconversion. Instead of routing search requests through the full LLM pipeline, detect web-search-only requests early (all tools are web_search, simple prompt) and execute the search directly via Tavily/Perplexity, returning a synthetic Anthropic response. No adapter, no backend LLM call needed. Fixes #21733 |
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Ishaan Jaff
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81dadb698a
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Ishaan - March 18th changes (#24056)
* add DD Tracing (#24033) * feat(models): add Azure GPT-5.4 mini and nano variants (#24045) Add `azure/gpt-5.4-mini` and `azure/gpt-5.4-nano` to the model database with official pricing from Azure OpenAI: - GPT-5.4 mini: $0.75/M input, $0.075/M cached, $4.5/M output - GPT-5.4 nano: $0.20/M input, $0.02/M cached, $1.25/M output Both models support: - 1.05M input / 128K output context window - Chat, batch, and responses endpoints - Function calling, tools, vision, reasoning - Prompt caching with automatic tiered pricing Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * Add new model pricing details for volcengine Doubao-Seed-2.0 series (#23871) Add entries for volcengine Doubao-Seed-2.0 series * fix(mcp): support refresh_token grant type in OAuth token endpoint (#23701) * fix(mcp): support refresh_token grant type in OAuth token endpoint (#23700) The .well-known/oauth-authorization-server metadata advertises refresh_token as a supported grant type, but the token endpoint rejected it with HTTP 400. This adds refresh_token grant support so MCP clients can refresh expired tokens without re-authenticating. * test(mcp): add tests for refresh_token grant type in OAuth token endpoint * fix(mcp): move code_verifier guard into authorization_code branch code_verifier is only relevant for authorization_code grants (PKCE). Move it inside the else branch so it doesn't apply to refresh_token. * fix(mcp): guard None client_secret and forward scope in token exchange - Conditionally include client_secret in form data to prevent httpx from sending the literal string "None" (applies to both authorization_code and refresh_token branches) - Forward optional scope parameter per RFC 6749 §6, allowing clients to request a subset of originally-granted scopes on refresh * fix(mcp): validate code param in authorization_code grant Guard against None code being form-encoded as literal string "None" by httpx, symmetric with the existing refresh_token guard. * docs: add incident report for guardrail logging secret exposure (#24059) Add blog post documenting the guardrail logging path exposing internal request data (e.g. Authorization headers) in spend logs and OTEL traces. Fix available in LiteLLM 1.82.3+. Made-with: Cursor * [Fix] Datadog LLM Observability tags format (env, service, version missing) (#23673) * tag fix * greptile comment * fix(ci): stabilize 6 failing CI jobs 1. mypy: remove duplicate type annotation for token_data in discoverable_endpoints.py 2. integrations tests: add parameterized to CI test deps 3. doc quality: document OTEL_IGNORE_CONTEXT_PROPAGATION env key 4. security: allowlist CVE-2026-2673, CVE-2026-3644, CVE-2026-4224 (no fix available) 5. proxy_store_model_in_db: fix missing x-litellm-call-id header on error responses 6. google tests: add --retries 3 for transient Vertex AI rate limits Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(streaming): handle RuntimeError during model_copy in streaming handler The race condition occurs when model_copy(deep=True) tries to deepcopy _hidden_params dict while it's being concurrently modified by logging callbacks. Fall back to shallow copy if the deep copy fails. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(cost): handle non-string traffic_type in cost calculator + add retries 1. Fix AttributeError in _map_traffic_type_to_service_tier when traffic_type is an integer (cast to str before calling .upper()). This was causing pass-through vertex spend logging to fail silently. 2. Add --retries to llm_translation_testing for flaky external API calls. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> --------- Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: ExMatics HydrogenC <33123710+HydrogenC@users.noreply.github.com> Co-authored-by: Jack Venberg <jack.venberg@rover.com> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Shivam Rawat <161387515+shivamrawat1@users.noreply.github.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> |
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Sameer Kankute
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e2e4f9ed33
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Merge branch 'main' into litellm_oss_staging_03_17_2026 | ||
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Krish Dholakia
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5c93c107d9
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Merge pull request #24043 from themavik/fix/24001-langsmith-usage-metadata
fix(langsmith): populate usage_metadata in outputs for Cost column |
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jyeros
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02ebd1302e | Code review | ||
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jyeros
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2b6a32e0cd | Add tests | ||
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jyeros
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bb628e974a | Add otel ignore_context_propagation as opt in | ||
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Avik Kumar
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fcea560682 |
fix(langsmith): populate usage_metadata in outputs for Cost column
LangSmith reads the Cost column from outputs.usage_metadata.total_cost, but LangsmithLogger._prepare_log_data never wrote to that key. The response_cost was already computed in StandardLoggingPayload but was not forwarded to the outputs dict. Inject usage_metadata with input_tokens, output_tokens, total_tokens, and total_cost into the outputs dict so LangSmith can display cost. Fixes #24001 Made-with: Cursor |
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Miguel Miranda Dias
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e9291a97c3
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fix(langsmith): avoid no running event loop during sync init (#23727)
* fix(langsmith): skip periodic flush task without event loop * fix(langsmith): lazily start periodic flush task * test(langsmith): tighten flush task coverage * test(langsmith): cover lazy failure flush startup * refactor(langsmith): keep flush startup private |
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yuneng-jiang
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94eabffe01
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Merge pull request #22390 from Harshit28j/litellm_langfuse-session-trace-fix
Fix Langfuse failure path kwargs inconsistency |