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00f7361f11
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Day 0 support : Gemini 3.5 Flash (#28268)
* Add day 0 support for gemini 3.5 flash
* Fix pricing
* Fix greptile review
* Fix failing test
* Fix tests
* Fix: revert tool removing logic
* fix greptile and test
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Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
(cherry picked from commit
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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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3f5c589255
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fix(bedrock): add 1-hour cache write tier for Claude 4.5/4.6/4.7 (Global, US)
AWS Bedrock pricing publishes a separate 1-hour prompt-cache write rate for
Claude 4.5 / 4.6 / 4.7 (1.6x the 5-minute rate). Without
`cache_creation_input_token_cost_above_1hr`, cost tracking for 1-hour-TTL
prompt caching on Bedrock falls back to the 5-minute rate and undercounts
spend by ~60%.
Adds the field to the spot-checked Global and US-region entries:
- anthropic.claude-opus-4-7 (Global $10.00 / MTok)
- anthropic.claude-opus-4-6-v1 (Global $10.00 / MTok)
- anthropic.claude-opus-4-5-... (Global $10.00 / MTok)
- anthropic.claude-sonnet-4-6 (Global $6.00 / MTok)
- anthropic.claude-sonnet-4-5-... (Global $6.00 / MTok regular,
$12.00 / MTok long-context >200K)
- anthropic.claude-haiku-4-5-... (Global $2.00 / MTok)
- global.anthropic.* mirrors of the above
- us.anthropic.* mirrors at the US +10% premium
Also updates the long-context (>200K) variants of Sonnet 4.5 with
`cache_creation_input_token_cost_above_1hr_above_200k_tokens`.
The mirrored entries in `litellm/model_prices_and_context_window_backup.json`
are updated in lockstep.
EU / AU / APAC / JP / us-gov regional variants are out of scope for this
change pending separate verification against AWS Bedrock pricing for those
regions.
Adds tests/test_litellm/test_bedrock_anthropic_1hr_cache_pricing.py to lock
in the expected values and the 1.6x ratio invariant.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
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4ae2996f08
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Add gpt-image-2 support (#26644) (#26705)
* Add gpt-image-2 support * Address gpt-image-2 PR feedback Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com> |
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503c3921c8 | Fix gpt-5.5-pro pricing | ||
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319193604c
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[Feat] Add azure/gpt-5.5 + azure/gpt-5.5-pro entries (+ dated variants) (#26361)
* feat(azure): add azure/gpt-5.5 + azure/gpt-5.5-pro entries (+ dated variants) Azure variants of OpenAI's GPT-5.5 family. Microsoft has not yet shipped GPT-5.5 on Azure OpenAI (latest GA on the Foundry models page is GPT-5.4 as of 2026-04-24), but adding the entries day-0 mirrors the established precedent for azure/gpt-5.4* (which were in the cost map before the Azure rollout) so cost tracking and capability flags work the moment customers deploy. Schema follows the existing azure/gpt-5.4* shape: - Same base/long-context pricing as openai/gpt-5.5*: $5/$30 chat, $60/$360 pro per 1M, with priority tier 2x base - Azure variants drop the flex/batches keys (Azure has no flex tier) but keep priority pricing, matching gpt-5.4* precedent - mode=chat for the thinking model, mode=responses for pro reasoning_effort capability flags mirror the OpenAI variants exactly since Azure proxies the same API contract: minimal rejection on both chat and pro, low/none rejection on pro. Once #26456 (which sets supports_low_reasoning_effort + minimal=false on openai/gpt-5.5*) lands, OpenAI and Azure flag profiles align. Tests pin entry presence + pricing for all four Azure variants and verify the live-API-derived reasoning_effort flags. * test: register supports_low_reasoning_effort in cost-map JSON schema azure/gpt-5.5-pro and azure/gpt-5.5-pro-2026-04-23 added in this branch carry supports_low_reasoning_effort=false. The strict 'additionalProperties: false' schema in test_aaamodel_prices_and_context_window_json_is_valid rejected the new key. Register it alongside the other supports_*_reasoning_effort entries. Note: the runtime side of this flag (code that reads it) lands in #26456. Until that PR merges the flag is inert for both Azure and OpenAI pro entries, but having the schema accept it lets cost-map tests pass on either merge order. |
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ebe16072f2 |
Merge remote-tracking branch 'upstream/litellm_internal_staging' into litellm_staging_03_23_2026
# Conflicts: # model_prices_and_context_window.json # tests/test_litellm/llms/vertex_ai/multimodal_embeddings/test_vertex_ai_multimodal_embedding_transformation.py |
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384cfdad47 |
Revert "Merge pull request #24164 from dongyu-turo/feat/update-bedrock-claude-price-above-200k"
This reverts commit |
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70492cee42
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feat(proxy): add /v1/memory CRUD endpoints (#26218)
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* feat(proxy): add /v1/memory CRUD endpoints with user/team scoping
New LiteLLM_MemoryTable stores user/team-scoped key/value entries with
optional JSON metadata. Value is a String (LLM-readable text) and metadata
is an optional Json? envelope, matching the Letta + mem0 hybrid model so
future structured fields can be added without a schema migration.
Endpoints:
POST /v1/memory - create
GET /v1/memory - list (caller-scoped; admins see all)
GET /v1/memory/{key} - fetch one
PUT /v1/memory/{key} - upsert
DELETE /v1/memory/{key} - delete
Non-admin callers cannot set a user_id/team_id other than their own.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(proxy/memory): omit metadata field when None on create
Prisma's Python client rejects `metadata=None` on a `Json?` field with
"A value is required but not set" — the field must be omitted from the
`data` dict entirely to store SQL NULL. Build the create payload
conditionally in both `create_memory` and the PUT-create branch of
`upsert_memory`.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(ui): add Memory page to view/manage /v1/memory entries
Adds a new "Memory" sidebar item under Tools so users can see what their
agents have stored. Lists all memories visible to the caller (scoped by
the backend), with a key-search filter, preview column, scope tags, and
view/edit/delete actions. Create modal accepts optional JSON metadata.
- networking.tsx: fetchMemoryList / createMemory / updateMemory / deleteMemory
wired to the /v1/memory CRUD endpoints.
- MemoryView + MemoryEditModal: new antd-based components (per CLAUDE.md:
use antd for new UI, not tremor).
- page.tsx + leftnav.tsx: wire the "memory" route + sidebar entry.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(memory): add key_prefix filter + promote Memory to AI GATEWAY nav
Backend:
- GET /v1/memory now accepts `key_prefix` for Redis-style namespace
scans (e.g. `?key_prefix=user:`). When both `key` and `key_prefix`
are passed, `key_prefix` wins.
- Prefix filter sits under the visibility filter in the Prisma where
clause, so it can never leak rows across user/team scopes.
- New tests: prefix match, and cross-scope isolation (another user's
`user:*` rows must not appear in the caller's results).
UI:
- Memory moved from a Tools submenu to a top-level AI GATEWAY item
(alongside Agents, MCP Servers, Skills) — it's an API primitive,
not a tool-management surface.
- Search box now drives prefix search, matching the Redis mental
model ("type the namespace, see everything under it").
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(memory): enforce unique key per scope by using NULLS NOT DISTINCT
The unique constraint `(key, user_id, team_id)` on LiteLLM_MemoryTable
silently allowed duplicates when user_id or team_id was NULL, because
Postgres treats every NULL as distinct by default (ANSI semantics). A
caller with no team_id could POST the same key three times and get
three rows.
Migration:
1. Dedupe existing rows, keeping the most recent per (key, user_id,
team_id), using `IS NOT DISTINCT FROM` so NULL == NULL.
2. Drop the old unique index.
3. Recreate it with `NULLS NOT DISTINCT` (Postgres 15+).
No code change: POST already returns 409 on unique-violation error
messages — it just wasn't firing before because the constraint didn't
catch the NULL-team case.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(memory): make key globally unique, 409 on any duplicate
Switches from the compound unique `(key, user_id, team_id)` to a simple
`key @unique`. The compound form silently allowed duplicates when
user_id or team_id was NULL (Postgres treats each NULL as distinct), so
callers could POST the same key repeatedly. Globally-unique key means
one row per key, period — any duplicate create → 409.
- schema.prisma (×3): `key String @unique`, drop `@@unique(...)`.
- initial add_memory_table migration: unique index on (key) only.
- Remove the now-unused follow-up NULLS NOT DISTINCT migration.
- Endpoint error message simplified ("already exists" — no "for this scope").
- Test fake's create() now enforces global key uniqueness.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(ui/memory): full-width layout + user/teams-style columns
- Add `w-full` to the MemoryView outer div so the page fills the
flex-flex-1 container (was collapsing to intrinsic width).
- Replace the combined "Scope" column with separate User ID / Team ID
columns, matching the layout of the Users / Teams pages: ID, Name,
Preview, User ID, Team ID, Updated, Actions.
- IDs render with a truncated mono label + copy-to-clipboard button,
same pattern as view_users.
- Detail drawer now shows Memory ID / User ID / Team ID as separate
fields instead of stacked color tags.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(ui/memory): use clean MCP-style ID pill, drop copy icons
The ID / User ID / Team ID columns showed a mono text blob with a
copy-to-clipboard icon next to each value — too busy compared to the
MCP Servers page. Swap the renderer for MCP's pill style:
- Truncated mono ID inside a blue Tailwind pill
(`font-mono text-blue-600 bg-blue-50 ... rounded-md border`).
- No copy icon. Full ID surfaces via tooltip.
- ID column is a button that opens the detail drawer on click;
user/team ID pills are static (not clickable).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(memory): address greptile review feedback
Addresses 5 greptile findings (3/5 → higher confidence target):
1. Identity-less orphan rows (P1): non-admin callers with no user_id AND
no team_id could create rows that the visibility filter would never
match again. Now rejected up front with 400 — caller must authenticate
with a scoped key or act as PROXY_ADMIN.
2. Upsert race returning 500 (P1): PUT's check-then-create isn't atomic;
a concurrent writer could slip a row in between the 404-check and the
create call. Now catch unique-violation on create, re-read, and fall
through to update — PUT stays idempotent. If the conflicting row
belongs to a different scope, surface a 409 instead of 500.
3. PUT-create scope inconsistency (P2): PUT's create branch always used
the caller's own user_id/team_id, so admins couldn't bootstrap rows
scoped elsewhere via PUT (only POST). Now PUT-create calls the shared
`_resolve_scope()` helper, matching POST semantics.
4. Stale schema comment (P2): schema said "Keyed by (key, user_id,
team_id)" but `key` is globally unique. Updated all three schema
copies to reflect the actual design.
5. UI silently truncated at 200 (P2): MemoryView fetched pageSize=200
with no load-more. Swapped to real server-side pagination driven by
`data.total`; page size is now 50 and the pager is a real AntD
control.
Also extracts a shared `_resolve_scope()` helper and `_is_unique_violation()`
from create_memory so POST and PUT don't drift on the scope/error logic.
Tests: +3 new (identity-less 400, PUT admin bootstrap, PUT race →
update), 18/18 pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(memory): typed Prisma error + explicit-null metadata on PUT
Two more greptile threads from the last review:
- Unique-violation detection was string-matching "Unique"/"UniqueViolation"
in the exception message, fragile across Prisma/driver versions. Now
check the typed error `code == "P2002"` first, with string fallback.
- PUT could not distinguish "metadata omitted" from "metadata: null" —
both parsed as `None`, so callers had no way to clear stored metadata.
Switch to Pydantic v2's `model_fields_set` to tell which fields the
caller actually sent; explicit null now clears the column.
New tests:
- explicit null clears metadata
- omitted metadata preserves existing value
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(ui/memory): send explicit null when user clears metadata
Addresses the remaining P1 from the last greptile review:
When the edit modal's metadata textarea was cleared and saved,
`metadataParsed` stayed `undefined`, `JSON.stringify` dropped the key
entirely, and the backend's `model_fields_set` guard therefore left
the stored metadata untouched — UI showed success but nothing changed.
Now: empty textarea on edit → send explicit `null` so the backend
sees `metadata` in `model_fields_set` and clears the column.
Empty textarea on create still maps to `undefined` (field omitted)
to avoid Prisma's `Json? = None` quirk on insert.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(ui/memory): preserve slashes in key path encoding
The backend route `/v1/memory/{key:path}` supports keys with slashes,
but `encodeURIComponent` encoded `/` as `%2F`. Some proxies (nginx
default, CloudFlare, AWS ALB) reject or re-decode `%2F` mid-flight,
so UI update/delete calls on slash-containing keys could fail or
silently misroute.
New helper `encodeMemoryKeyForPath` splits by `/`, URL-encodes each
segment, then rejoins with literal `/`. Every other unsafe char
(spaces, `?`, `#`, `%`) stays encoded per-segment; slashes stay as
path delimiters, matching what the `:path` converter expects.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(ui/memory): drop misleading client-side column sorters
With server-side pagination, client sorters on `key` and `updated_at`
only reorder the current page while pretending to sort the full
dataset — users would see "sorted by name" but only the visible 50
rows would actually be sorted.
Remove the sorters. The backend already returns rows in
`updated_at DESC` order (sensible default for a memory view), and
users can narrow the result with the key-prefix filter.
Greptile also flagged missing `@@map` on the new model as a
"consistency" issue, but only 1 of 59 tables in this repo uses
`@@map` — the dominant pattern is to rely on Prisma's default
(model name == table name). Skipping that finding as a
false-positive on convention.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(memory): compose visibility + key filters via explicit AND
Greptile P1 (filter-fragility): `where.update(vis)` was semantically
correct today, but dict-merging by key meant any future visibility
filter that grew a new top-level "OR" would silently clobber the
existing key filter.
Compose explicitly instead:
where = {"AND": [key_filter, vis]}
Applied to both `list_memory` and `_find_memory_for_caller`. When
either side is empty (admin has no visibility filter; list has no
key filter), skip the wrapper and use the non-empty side directly
to keep the generated SQL clean.
Test fake's `_matches` now understands top-level `AND` too.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* refactor(ui/memory): wrap write helpers with react-query useMutation
Previously the Memory view read via `useQuery` but called the raw
create/update/delete fetch helpers directly in handlers, tracking
loading state with a local `submitting` flag and invalidating state
via `refetch()`. That mixes two concerns:
- it skips react-query's mutation state (isPending / isError / isSuccess)
- `refetch()` only retouches the currently-mounted query instance, not
other cached pages, so navigating back to an older page could show
stale rows
Switch the three write paths to `useMutation`:
- `createMutation`, `updateMutation`, `deleteMutation` — each owns
the mutation fn, success toast, and error toast.
- Success handlers invalidate the whole `["memoryList", ...]` prefix
via `queryClient.invalidateQueries`, so every cached page refetches
(pagination + filter-aware).
- Refresh button now invalidates instead of `refetch()`, keeping all
behavior consistent.
- handleSave/handleDelete become thin adapters that call `.mutateAsync`;
their errors are swallowed locally since the mutation's onError has
already surfaced the toast.
Also tightened the edit modal's key-field tooltip to reflect the
actual global-unique semantics (was "Unique per user/team scope").
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(memory): close cross-user write gap + sanitize 500 errors (Veria)
Addresses two Veria findings:
**High — cross-user memory tampering via team membership.** The
visibility filter uses an OR (`user_id == caller OR team_id == caller`)
so team members can SEE each other's team-scoped rows. That's
intentional for list/get. But because PUT/DELETE used the same filter
to find the target row, any team member could overwrite or delete a
teammate's *personal* row whenever both `user_id` and `team_id` were
stamped on it — broader visibility was being silently treated as
broader authority.
New `_assert_write_access(row, caller)` enforces ownership for
mutations. Non-admin rules:
- The row's `user_id` must match the caller (personal ownership), OR
- The row has no `user_id` and its `team_id` matches the caller's
team (a "pure team row" intended for shared writes).
Admins bypass the check. The same gate runs in PUT (both regular
and post-race-recovery branches) and DELETE.
**Medium — DB internals leaked through 500 detail.** Every `except`
block was raising `HTTPException(500, detail=str(e))`, which surfaces
Prisma error strings (table/column names, host:port, error class
names) to API callers. New `_internal_error()` helper logs the real
exception server-side and returns a generic, caller-safe `detail`.
Applied to create, list, upsert (general fallthrough), and delete.
Also tightened the race-recovery 409 message to drop the "in a
different scope" wording — the caller never needs to know whose
scope it lives in.
Tests (+5):
- teammate cannot overwrite personal row → 403
- teammate cannot delete personal row → 403
- teammate CAN modify pure team row (no user_id stamped) → 200
- admin bypasses write-auth → 200
- 500 response never echoes Prisma internals (table/host/class names)
25/25 unit tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(memory): require team admin to modify pure team rows
Tightens the write-authorization rule for "pure team rows" (rows with
no user_id stamped, only team_id) to match the pattern used by
team-management endpoints (`_is_user_team_admin` + `_is_user_org_admin_for_team`):
- Plain team members can READ team rows via the OR visibility filter
(intentional, unchanged).
- Only PROXY_ADMIN, team admins of the row's team_id, or org admins
for the team's organization may MODIFY them. Plain members get 403.
`_assert_write_access` is now async and takes the prisma_client so it
can fetch the team and run the existing `_is_user_team_admin` /
`_is_user_org_admin_for_team` helpers from
`litellm.proxy.management_endpoints.common_utils`. The org-admin path
is best-effort: it calls `get_user_object`, which depends on the
proxy_server module being initialized, so any exception there is
treated as "not an org admin" rather than crashing the request.
Tests:
- team admin can modify pure team row → 200
- plain team member cannot modify pure team row → 403
- plain team member cannot delete pure team row → 403
Updates the test fake to add a tiny `litellm_teamtable.find_unique`
implementation and a `_make_team(team_id, admin_user_ids=[...])`
helper.
27/27 unit tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix: mypy + UI page-metadata sync for memory page
Two CI failures:
1. mypy: `_find_memory_for_caller` had `key_filter` inferred as
`dict[str, str]` (literal type) and the conditional `{"AND": [key_filter, vis]}`
returned `dict[str, list[...]]`, so the join site failed
`dict-item` typing. Annotate both intermediates as `dict` so mypy
widens the value type.
2. UI test (`page_utils.test.ts > should have descriptions for all
pages`): every leftnav entry must have a description in
`page_metadata.ts`, and `memory` was missing. Added a one-line
description, matching the style of neighboring entries.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* [Feat] Day-0 support for GPT-5.5 and GPT-5.5 Pro (#26449)
* feat(openai): day-0 support for GPT-5.5 and GPT-5.5 Pro
Add pricing + capability entries for the new GPT-5.5 family launched by
OpenAI on 2026-04-24:
- gpt-5.5 / gpt-5.5-2026-04-23 (chat): $5/$30/$0.50 per 1M
input/output/cached input
- gpt-5.5-pro / gpt-5.5-pro-2026-04-23 (responses-only): $60/$360/$6
per 1M input/output/cached input
Other fees (long-context >272k, flex, batches, priority, cache
discounts) follow the same ratios as GPT-5.4, with context window
retained at 1.05M input / 128K output.
No transformation / classifier code changes are required:
OpenAIGPT5Config.is_model_gpt_5_4_plus_model() already matches 5.5+ via
numeric version parsing, and model registration is driven from the
JSON. The existing responses-API bridge for tools + reasoning_effort
(litellm/main.py:970) already covers gpt-5.5-pro.
Tests:
- GPT5_MODELS regression list now covers gpt-5.5-pro and dated variants
- New test_generic_cost_per_token_gpt55_pro cost-calc test
- Updated test_generic_cost_per_token_gpt55 for long-context fields
* fix(openai): mirror reasoning_effort flags onto gpt-5.5 dated variants
gpt-5.5-2026-04-23 and gpt-5.5-pro-2026-04-23 were missing the
supports_none_reasoning_effort, supports_xhigh_reasoning_effort, and
supports_minimal_reasoning_effort flags that their non-dated
counterparts define. Reasoning-effort routing in OpenAIGPT5Config is
fully capability-driven from these JSON flags — since an absent flag
is treated as False for opt-in levels (xhigh), users pinning to a
dated snapshot would silently lose xhigh support and diverge from the
base alias on logprobs + flexible temperature handling.
Copy the flags onto both dated variants so every dated snapshot
inherits the base model's reasoning-effort capability profile.
Adds a parametrized regression test that asserts
supports_{none,minimal,xhigh}_reasoning_effort parity between each
dated variant and its non-dated counterpart, preventing future drift
when new snapshots are added.
* fix(schema): close LiteLLM_MemoryTable model brace dropped during merge
The rebase against `litellm_internal_staging` (which added
`LiteLLM_AdaptiveRouterState` / `LiteLLM_AdaptiveRouterSession`) left
the closing brace of `LiteLLM_MemoryTable` missing in all three
schema copies — the next model declaration ended up parsed as a field
of the memory table, surfacing as the CI prisma error:
error: This line is not a valid field or attribute definition.
--> schema.prisma:1250
|
1249 | // Per-(router, request_type, model) Beta posterior for the adaptive router.
1250 | model LiteLLM_AdaptiveRouterState {
Add the missing `}` (and the standard blank line) after the memory
table's `@@index([team_id])` in `schema.prisma`,
`litellm/proxy/schema.prisma`, and
`litellm-proxy-extras/litellm_proxy_extras/schema.prisma`.
`prisma generate --schema litellm/proxy/schema.prisma` now runs clean;
27/27 memory unit tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
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ca443a957c
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Merge pull request #24374 from BerriAI/litellm_staging_03_22_2026
Litellm staging 03 22 2026 |
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d73b790cae
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Merge pull request #26248 from BerriAI/litellm_anthropic_messages_call_type_fix
fix(proxy): preserve anthropic_messages call type for /v1/messages logging |
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55ea431c05
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_gpt54_mini_nano_versioned_models | ||
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e1466be825
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feat(pricing): gemini-embedding-2 GA cost map, blog, and test (#26391)
* feat(pricing): gemini-embedding-2 GA cost map, blog, and test - Add model_prices entries for gemini-embedding-2 (Gemini + Vertex paths) - Add docs blog gemini_embedding_2_ga with LiteLLM proxy curl examples - Add test_gemini_embedding_2_ga_in_cost_map in test_utils Made-with: Cursor * Fix greptile reviews |
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8bd58fb82d
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Merge branch 'litellm_internal_staging' into litellm_staging_03_22_2026 | ||
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3950f5ea72
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feat: add gpt-5.5 to model cost map (#26345)
* feat: add gpt-5.5 to model cost map Add gpt-5.5 entry with pricing from OpenAI flagship page: input $5/1M, cached input $0.50/1M, output $30/1M, 272K context. * test: add gpt-5.5 coverage for model cost map and gpt-5 routing - Add gpt-5.5 to GPT5_MODELS parametrized list so both OpenAIGPT5Config and AzureOpenAIGPT5Config routing tests cover the new model. - Add test_generic_cost_per_token_gpt55 verifying the new entry's cost-map values ($5/$0.50/$30 per 1M) and that generic_cost_per_token returns the expected prompt/completion costs. |
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d5449f5b1a
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Merge pull request #26300 from BerriAI/litellm_oss_staging_04_22_2026
Litellm oss staging 04 22 2026 |
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fcf917df6d
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Feat(dashscope): add image generation support for qwen-image-2.0 and qwen-image-2.0-pro (#25672)
* feat: add dashscope/qwen-image-2.0 and qwen-image-2.0-pro to model cost map * feat: implement DashScope image generation transformation class * feat: register DashScope in ProviderConfigManager for image generation * feat: add DashScope to image generation provider routing * feat: auto-route qwen-image /chat/completions requests to /images/generations * test: add unit tests for DashScope image generation (22 cases) * refactor: remove proxy-layer qwen-image auto-routing * feat: auto-redirect image_generation models in acompletion() * test: add acompletion auto-redirect test for image_generation models * fix: remove unused Union import in DashScope transformation * fix: scope acompletion redirect to dashscope and narrow exception handler * fix: move get_str_from_messages to module-level import and forward n param to aimage_generation * refactor: remove acompletion image_generation auto-redirect for dashscope * test: remove acompletion auto-redirect test for dashscope image models --------- Co-authored-by: zark.lin <zark.lin@thinkchina.com> |
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b42b86df7a
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fix(adapter): normalize reasoning effort with graceful degradation (#26111)
* fix(model-info): include reasoning effort support fields in get_model_info _get_model_info_helper constructs ModelInfoBase explicitly but never reads supports_xhigh/minimal/none_reasoning_effort from the cost map JSON. Add the three fields so get_model_info() returns them correctly. Also add supports_minimal_reasoning_effort to the ModelInfo TypedDict (xhigh and none were already declared, minimal was missing). * fix(model-registry): add missing reasoning effort fields for claude 4.6/4.7 Claude Opus 4.7 supports max reasoning effort (above xhigh). The field was present for Opus 4.6 but missing for all Opus 4.7 entries (base, dated, Bedrock, Vertex AI, Azure AI). All Claude 4.6/4.7 models (Opus 4.6, Sonnet 4.6, Opus 4.7) support minimal reasoning effort via adaptive thinking. Add the field to all provider variants. * fix(adapter): map output_config.effort to reasoning_effort (#25079) Anthropic's adaptive thinking (thinking.type="adaptive") and output_config.effort were silently dropped when translating to OpenAI format, resulting in no reasoning_effort on the outgoing request. Adapter changes (format translation): - adapters/transformation.py: add "adaptive" branch to translate_anthropic_thinking_to_reasoning_effort(); pass through output_config.effort as-is in _translate_thinking_to_openai(); add "output_config" to translatable_anthropic_params - adapters/handler.py: extract output_config from extra_kwargs into request_data so it reaches the translation layer - responses_adapters/transformation.py: add "adaptive" branch and output_config param to translate_thinking_to_reasoning() Handler changes (model-aware normalization): - utils.py: add normalize_reasoning_effort_value() that uses get_model_info() to map "max" → "xhigh"/"high" and "minimal" → "minimal"/"low" based on model capabilities - adapters/handler.py: call normalization before responses routing - responses_adapters/handler.py: call normalization after translation Relates to BerriAI/litellm#25079 * test(reasoning-effort): add tests for effort capability fields and normalize logic Test coverage for: - get_model_info returning supports_minimal/max_reasoning_effort fields - JSON registry entries for claude 4.6/4.7 across all providers - normalize_reasoning_effort_value degradation chains and exception fallback - Adapter translation of adaptive thinking + output_config.effort * fix: forward custom_llm_provider to normalize_reasoning_effort_value in responses adapter |
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25c0aa8bfd
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Merge pull request #26283 from BerriAI/litellm_internal_staging
Sync litellm_staging_03_22_2026 with litellm_internal_staging |
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6ebbfe5190
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fix(anthropic): allow output_config effort max for Opus 4.7 and model map
- Validate max effort like xhigh: Opus 4.6/4.7 id patterns or supports_max_reasoning_effort - Set supports_max_reasoning_effort on claude-opus-4-7 entries in model cost JSON - Update tests and add test_max_effort_accepted_for_opus_47 Made-with: Cursor |
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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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e6897f5510
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add moonshot/kimi-k2.6 to model registry (#26203)
* add moonshot/kimi-k2.6 to model registry * add moonshot/kimi-k2.6 to backup model registry * add tests for moonshot/kimi-k2.6 model registry * fix moonshot/kimi-k2.6 pricing and add reasoning support * fix moonshot/kimi-k2.6 pricing and add reasoning support in backup * update kimi-k2.6 tests: fix pricing, add tool_choice and reasoning checks * fix: load kimi-k2.6 registry tests from local backup instead of remote cost map |
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a302613eb5
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feat(bedrock): add support for bedrock-mantle endpoint (Claude Mythos Preview) (#26196)
* add anthropic.claude-mythos-preview to model_prices_and_context_window.json * add mantle route to bedrock common_utils: route detection, chat config, messages config dispatch * add AmazonMantleConfig for bedrock/mantle /chat/completions endpoint * add AmazonMantleMessagesConfig for bedrock/mantle /messages endpoint * register AmazonMantleMessagesConfig in __init__.py and lazy imports registry * add unit tests for bedrock mantle route and config dispatch * add e2e tests for bedrock mantle: URL, body, SigV4 header, region routing |
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4f823cedac
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Add supported providers to prompt caching doc (#26124)
* Add supported providers to prompt caching doc * Move Z.ai / GLM to cache_control marker list * Mark xAI models as supporting prompt caching * Narrow xAI prompt caching flag to models with documented cache pricing * Add prompt caching flag to grok-4, grok-4-0709, grok-4-latest --------- Co-authored-by: Michael Riad Zaky <michaelr@Michaels-MacBook-Air.local> |
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d5cfdcc6ee
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feat(models): add versioned GPT-5.4 mini and nano aliases
Add dated snapshot entries for GPT-5.4 mini and nano (including Azure-prefixed aliases) so users can pin to the 2026-03-17 model versions. |
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57eae8d01c
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Merge branch 'litellm_internal_staging' into litellm_staging_03_22_2026
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3ef362289b
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Add support for grok-4.20-0309-reasoning model | ||
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44c992416c
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Merge pull request #25867 from BerriAI/litellm_day_0_opus_4.7_support
Litellm day 0 opus 4.7 support |
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07d863b8e7
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Remove max support for opus 4.7 | ||
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f94c8dda82
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Fix model names | ||
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0868a82c34
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Add support for opus 4.7 with new effort levels | ||
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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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f82ba6ca6b |
Resolve remaining merge conflicts with upstream/main
- streaming_iterator.py: adopted main's more defensive version of the tool-arg queueing check (.get() instead of [], isinstance guard) — same logic, same behavior, lower crash surface - model_prices_and_context_window.json + backup: combined staging's search_context_cost_per_query fields (PR #24372) with main's new supports_service_tier field — both are independent additions to the same Gemini model entries - test_streaming_handler.py: kept Azure streaming regression test (PR #24354) and added main's two new Gemini legacy vertex finish_reason normalization tests - test_gemini_batch_embeddings.py: kept staging's unsupported-params filtering tests (PR #24370) and added main's index/order test |
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67e4604284 |
Merge upstream/main into litellm_staging_03_22_2026
Resolved conflicts: - streaming_handler.py: combined role check (PR #24354, Azure streaming) with reasoning_items check (new in main) — both are independent OR conditions in is_chunk_non_empty() - CI/CD: accepted main's versions throughout - Redis tests migrated to CircleCI (PR #25354): removed enable-redis from GH Actions workflows - E2E UI tests restructured (PR #25365): simplified CircleCI job - Coverage via Codecov added to all GH Actions unit test workflows - Deleted test-litellm-matrix.yml and test-proxy-e2e-azure-batches.yml (removed in main) |
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db94b4d55c
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fix(cost-map): add us-south1 to vertex qwen3-235b-a22b-instruct-2507-maas (#25382) | ||
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b8f7d61400
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Merge pull request #25589 from BerriAI/litellm_oss_staging_04_11_2026
Litellm oss staging 04 11 2026 |
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4a71583951
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Merge pull request #25348 from BerriAI/litellm_gemini-veo-video-resolution-pricing2
feat(gemini): Veo Lite pricing, video resolution usage and tiered cost |
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ee40da58a2
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Merge branch 'main' into litellm_oss_staging_04_11_2026 | ||
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fa605d85c0
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Merge pull request #25616 from BerriAI/main
merge main |
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ee06b9278a
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feat(model):add wandb model offerings to include kimi-k2.5 and minimax-m2.5 (#25409) | ||
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97f722f558
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feat(cost): add baseten model api pricing entries (#25358)
Add Baseten Model API pricing entries for Nemotron, GLM, Kimi, GPT OSS, and DeepSeek models with validated model slugs. Include a focused regression test to assert provider and per-token pricing values. Made-with: Cursor |
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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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541e81de2f
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fix: expose reasoning effort fields in get_model_info + add together_ai/gpt-oss-120b (#25263)
* fix: expose reasoning effort fields in get_model_info and add together_ai/gpt-oss-120b - litellm/utils.py: pass supports_none_reasoning_effort and supports_xhigh_reasoning_effort through _get_model_info_helper so get_model_info() returns them (previously silently dropped). Fixes #25096. - model_prices_and_context_window.json: add together_ai/openai/gpt-oss-120b with supports_reasoning: true so reasoning_effort is accepted for this model without requiring drop_params. Fixes #25132. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: consolidate duplicate together_ai/openai/gpt-oss-120b entry and sync backup file * fix: link commit to GitHub account for CLA verification --------- Co-authored-by: Austin Varga <austin@knowmi.ai> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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c68a19b883
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feat(gemini): Veo Lite pricing, size→resolution, usage video_resolution for cost tiers
Made-with: Cursor |
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2bb7387a83
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Litellm aws gov cloud mode support (#25254)
* add us gov models * added max tokens * greptile fix --------- Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> |
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b53cfe729a
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Litellm ishaan march30 (#24887) (#25151)
* fix(pricing): add unversioned vertex_ai/claude-haiku-4-5 entry Missing unversioned entry causes cost tracking to return $0.00 for all requests using vertex_ai/claude-haiku-4-5. All other Vertex AI Claude models have both versioned and unversioned entries. * fix(router): skip misleading tags error when no candidates (e.g. cooldown) Return early from get_deployments_for_tag when healthy_deployments is empty so tag-based routing does not raise no_deployments_with_tag_routing after cooldown filters all deployments. Adds regression test. Made-with: Cursor * feat(oci): add embedding support and update model catalog - Add OCIEmbeddingConfig for OCI GenAI embedding models - Add 16 new chat models (Cohere, Meta Llama, xAI Grok, Google Gemini) - Add 8 embedding models (Cohere embed v3.0, v4.0) - Update documentation with embedding examples - Update pricing for all new models * test(oci): add unit tests for OCI embedding support - 17 unit tests covering OCIEmbeddingConfig - Tests for URL generation, param mapping, request/response transform - Tests for model pricing JSON completeness * style(oci): format with black and ruff * fix(oci): correct embedding request body format OCI embedText API expects inputs, truncate, and inputType at the top level of the request body, not nested under embedTextDetails. Fixed transformation and updated tests accordingly. Verified with real OCI API: 3/3 embedding models working. * docs: clarify tag routing early return and test intent Made-with: Cursor * fix(oci): address code review findings from Greptile - P1: Fix signing URL mismatch with custom api_base by accepting api_base parameter in transform_embedding_request - P2: Remove encoding_format from supported params (OCI does not support it, was silently dropped) - P2: Raise ValueError for token-array inputs instead of silently converting to string representation - Add test for token-list rejection * fix(mcp): add STS AssumeRole support for MCP SigV4 authentication MCPSigV4Auth only supported static AWS credentials or the boto3 default credential chain. Production Kubernetes environments typically authenticate via IAM role assumption (sts:AssumeRole), which was not possible. Add aws_role_name and aws_session_name parameters to the MCP SigV4 auth stack. When aws_role_name is provided, MCPSigV4Auth calls sts:AssumeRole to obtain temporary credentials before signing requests. Explicit keys, if also provided, are used as the source identity for the STS call; otherwise ambient credentials (pod role, instance profile) are used. * fix: stop logging credential values and add missing redaction patterns Replaces raw credential values in debug/error log messages with boolean presence checks or type names. Adds PEM block, GCP token, JWT, SAS token, and service-account blob patterns to the redaction filter. Fixes private_key pattern to capture full PEM blocks instead of stopping at the first whitespace. Addresses: Vertex AI credential JSON (including RSA private key) being logged to stderr on health check failures. * fix: log only field names for UserAPIKeyAuth, not full object * style: apply black formatting to experimental_mcp_client/client.py * style: fix black/isort formatting and mypy error in proxy_server.py - Fix black formatting in experimental_mcp_client/client.py (done in prev commit) - Fix black/isort formatting in key_management_endpoints.py, proxy_server.py, transformation.py - Fix mypy: iterate over optional list safely (access_group_ids or []) in proxy_server.py * fix(test): patch check_migration.verbose_logger directly to fix xdist ordering issue When test_proxy_cli.py tests run before test_check_migration.py in the same xdist worker, litellm.proxy.db.check_migration is already in sys.modules. Patching litellm._logging.verbose_logger has no effect on the already-bound reference. Patch the correct target (check_migration.verbose_logger) and import the module before patching so the order doesn't matter. * fix(mypy): make api_base Optional in PydanticAIProviderConfig to match base class signature --------- Co-authored-by: Ihsan Soydemir <soydemir.ihsan@gmail.com> Co-authored-by: Milan <milan@berri.ai> Co-authored-by: Daniel Gandolfi <danielgandolfi@gmail.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: michelligabriele <gabriele.michelli@icloud.com> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> |
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c6aa3ea452
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Litellm ishaan april1 try2 (#25110)
* Litellm ishaan april1 (#25103) * fix(proxy): enforce upperbound key params on key/update and add custom_key_update hook The /key/update endpoint did not enforce upperbound_key_generate_params, allowing users to bypass configured limits (tpm_limit, rpm_limit, max_budget, duration, budget_duration) by updating an existing key instead of generating a new one. Extract the upperbound enforcement logic from _common_key_generation_helper() into a standalone _enforce_upperbound_key_params() function and call it from both the generate and update paths. For updates, None values are skipped (not filled with defaults) since they mean "don't change this field". Also adds a custom_key_update config option and user_custom_key_update global, mirroring the existing custom_key_generate pattern, so custom key validation logic can fire during key updates as well. * fix(proxy): invoke custom_key_update hook in bulk update path The user_custom_key_update hook was only called in update_key_fn (single key update) but not in _process_single_key_update (bulk update path), allowing custom validation to be bypassed via the /key/update/bulk endpoint. Mirror the hook invocation in both paths. * fix(proxy): pass UpdateKeyRequest to hook in bulk path, not BulkUpdateKeyRequestItem Move the custom_key_update hook invocation to after UpdateKeyRequest is constructed so the hook receives the same type in both single and bulk update paths. Previously the bulk path passed BulkUpdateKeyRequestItem (5 fields only), which would cause AttributeError for hooks accessing fields like tpm_limit or models. * fix(bedrock): promote cache usage to message_delta for Claude Code (#24850) Ensure Bedrock/Anthropic-compatible streaming exposes cache usage where Claude Code reads it by promoting message_stop usage onto message_delta and preserving usage fields in fake-streamed message_delta events. Made-with: Cursor * fix(search): Support self-hosted Firecrawl response format in search transform (#24866) The `transform_search_response` method only handled Firecrawl Cloud (v2) response format where `data` is a dict with `web`/`news` keys. Self-hosted Firecrawl (v1) returns `data` as a flat list of result objects, causing an `AttributeError: 'list' object has no attribute 'get'`. Detect the response format by checking if `data` is a list (self-hosted) or dict (cloud) and handle both cases. Cloud format: {"data": {"web": [...], "news": [...]}} Self-hosted: {"success": true, "data": [{"url": "...", "title": "...", ...}]} Co-authored-by: Synergy <synergyoclaw@gmail.com> * feat: add environment and user tracking to prompt management (#24855) * feat: add environment and user tracking to prompt management - Add environment (development/staging/production) and created_by columns to LiteLLM_PromptTable - Update unique constraint to [prompt_id, version, environment] - All CRUD endpoints support environment filtering and user tracking - Redesigned prompt detail page with environment tabs and version history - UI: environment filter on list page, environment selector in editor - 8 new tests for environment and user tracking Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: Black formatting and add environments to PromptInfoResponse TypeScript type Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address Greptile review findings - P1: delete_prompt scopes in-memory cleanup to environment when provided - P2: dotprompt_content parsed directly regardless of environment flag - P2: use distinct for environments query - P2: fix double-fetch on initial mount in prompt_info.tsx - fix: remove unsupported select kwarg from find_many Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address remaining Greptile review comments - Remove unused useCallback import (index.tsx) - Remove unused ENV_COLORS variable (prompt_info.tsx) - P1: in-memory fallback in get_prompt_versions now respects environment filter - P1: reset selectedEnv when promptId changes to avoid stale state - Cyclic imports are pre-existing pattern, not introduced by this PR Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: scope patch_prompt to environment using primary key - Add environment query param to patch_prompt endpoint - Look up target row by composite key (prompt_id + version + environment) - Update by primary key (id) to target exactly one row - Fixes Greptile finding: patch with multiple environments no longer ambiguous Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: use actual start_time for failed request spend logs (#24906) async_post_call_failure_hook set both start_time and end_time to datetime.now(), making all failed requests show duration=0. Use the actual start_time from litellm_logging_obj instead, so spend logs reflect the real request duration on timeout and other failures. Fixes #24888 * feat(bedrock): add nova canvas image edit support (#24869) * feat(bedrock): add nova canvas image edit support * fix(bedrock): support PathLike inputs for nova image edit * chore: sync schema.prisma copies from root * fix(mypy): correct type-ignore code for delta_usage arg-type * fix(mypy): cast status_code to str, suppress intentional str yield * fix(lint): extract _create_content_block_chunks to fix PLR0915 * fix(lint): extract helpers to fix PLR0915 in prompt endpoints --------- Co-authored-by: michelligabriele <gabriele.michelli@icloud.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> Co-authored-by: redhelix <amin.lalji@gmail.com> Co-authored-by: Synergy <synergyoclaw@gmail.com> Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: madhu19991 <madhu@thunkai.com> Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> * fix(test): update model armor streaming test to handle string or int error code --------- Co-authored-by: michelligabriele <gabriele.michelli@icloud.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> Co-authored-by: redhelix <amin.lalji@gmail.com> Co-authored-by: Synergy <synergyoclaw@gmail.com> Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: madhu19991 <madhu@thunkai.com> Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> |
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d4a3a5e530
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fix gpt-5.4 pricing (#24748) | ||
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52a596d2a4
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Bedrock Model Updates 2026-03-26 (#24645)
* add new bedrock models & remove duplicate vertexai entry * adding non-regional entry for minimax-2.5 |
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b7ccc5b691
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[Test Fix] fix gov pricing tests (#25022)
* fix pricing tests * fix mypy * fix cost expectation since us based model is used now. * fix test get model info |