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| Author | SHA1 | Message | Date | |
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yuneng-jiang
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6ff668c7aa
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[Infra] Promote internal staging to main (#27245)
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* default requested_model to empty string on litellm-side rejects * Update litellm/router.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix: scope key access_group_ids override by team's assigned groups A team member could set any access_group_ids on their key (e.g. a group assigned only to a different team) and override the team's model restriction. Intersect the key's access_group_ids with team_object.access_group_ids in _key_access_group_grants_model so foreign groups are dropped before model expansion. Adds a regression test that asserts expansion is never called for foreign groups. * [Fix] Proxy: Skip Personal Budget Hook When Reservation Covers Counter The reservation path (PR #26845) atomically pre-fills `spend:user:{user_id}` and admits at the strict-`<` boundary. The legacy `_PROXY_MaxBudgetLimiter` pre-call hook re-reads the same counter with `>=`, so a reservation that fills the counter to exactly `max_budget` (e.g. a request without a `max_tokens` cap that falls back to reserving the smallest remaining headroom) is rejected by the hook even though the reservation already admitted it. Skip the hook when the request's active `budget_reservation` covers `spend:user:{user_id}`. The reservation is the source of truth for that counter cross-pod; the legacy `>=` path remains in place for requests without a reservation (e.g. paths that bypass the reservation entirely). Reproduces as `tests/otel_tests/test_prometheus.py::test_user_budget_metrics` on a fresh user with `max_budget=10` calling `fake-openai-endpoint` without `max_tokens`. Adds focused unit coverage in `tests/test_litellm/proxy/hooks/test_max_budget_limiter.py`. * harden bedrock file bucket validation * Fix syntax errors from botched merge in router.py * Fix Vertex batch output edge cases * [Fix] RBAC: Drop management_routes Write Fallback for Admin Viewer Greptile P1: the unsafe-method branch of `_check_proxy_admin_viewer_access` ended with a blanket `if route in management_routes: return`. That set is a mix of reads (info/list — handled via the safe-method GET branch above) and writes. The fallback let Admin Viewer POST to write endpoints not enumerated in `_ADMIN_VIEWER_BLOCKED_WRITE_ROUTES`, including: - /team/block, /team/unblock, /team/permissions_update - /jwt/key/mapping/{new,update,delete} - /key/bulk_update - /key/{key_id}/reset_spend Remove the fallback. The two remaining allow sets (admin_viewer_routes and global_spend_tracking_routes) are both read-only, so removal does not affect the legitimate POST-as-read cases (e.g. /spend/calculate, which is in spend_tracking_routes ⊂ admin_viewer_routes). Tests: - 8 new parametrized cases pinning each previously-leaking management write endpoint to 403 on POST for PROXY_ADMIN_VIEW_ONLY. * fix(tests): anchor VCR redis cassette key to repo root `os.path.relpath` with no `start` arg uses the current working directory, so running pytest from a subdirectory produced a different Redis key than running from the repo root. CI-recorded cassettes and locally-replayed runs would silently miss each other's cache. Anchor the path to the repo root (derived from `__file__`) so the key is stable regardless of CWD. https://claude.ai/code/session_018uCx7pcrkdUJZrCVMaTdPx * fix: gate key access_group override on group's own assignment Replaces the previous intersect-with-team.access_group_ids check, which made the override unreachable in practice (the team-gate fallback already covered every case the intersection allowed). The override now resolves each of the key's access_group_ids via get_access_object and accepts the group only if its assigned_team_ids includes the key's team_id, or its assigned_key_ids includes the key's token. This fulfills the original ask (a key can extend a team's allow-list via a group the admin granted to that team or that specific key) while still rejecting foreign groups referenced by team members of other teams. * [Fix] Proxy/Key Management: Honor team_member_permissions /key/list In /key/list Endpoint When a team grants /key/list via team_member_permissions, non-admin members should see all keys for that team — same as a team admin. Previously the classification in list_keys() only checked admin status, so permitted members fell into the service-account-only path and could not see other members' personal keys. Routes those members into the full-visibility set. * Fix access-group bypass via litellm-model fallback path When _get_all_deployments returns 0 candidates and the litellm-model fallback branch (_get_deployment_by_litellm_model) finds deployments that the access-group filter then empties, _access_group_filter_emptied_candidates remained False (it was captured before that branch ran). The router would then proceed to default fallbacks; the fallback model could have no access_groups and short-circuit the filter, silently serving a caller blocked by access-group restrictions. Update the flag inside the litellm-model branch when filtering empties a non-empty candidate set so the default-fallback guard still triggers. * fix(proxy): redact MCP server URL and headers for non-admin viewers (VERIA-8) Many MCP integrations (Zapier, etc.) embed an upstream API key directly in the server URL, e.g. ``https://actions.zapier.com/mcp/<api-key>/sse``. The list and single-server endpoints were returning the full URL to any authenticated user — `_redact_mcp_credentials` only stripped the explicit ``credentials`` field, and `_sanitize_mcp_server_for_virtual_key` only ran for restricted virtual keys. Non-admin internal users could read the dashboard, click the unmask toggle, and exfiltrate the raw token. Add `_sanitize_mcp_server_for_non_admin` that runs on top of the existing credential redaction and clears the credential-bearing fields: - ``url`` (the primary leak vector) - ``spec_path`` (OpenAPI spec URLs that may carry tokens) - ``static_headers`` / ``extra_headers`` (Authorization) - ``env`` (arbitrary secrets) - ``authorization_url`` / ``token_url`` / ``registration_url`` Identity fields (``server_id``, ``alias``, ``mcp_info``, etc.) are preserved so the UI can still list servers a non-admin's team has access to. Apply the new sanitizer in `fetch_all_mcp_servers` and the per-server fetch path right after the existing virtual-key branch. Update the existing `test_list_mcp_servers_non_admin_user_filtered` assertions that previously checked URL visibility. Frontend defense-in-depth: hide the URL unmask toggle on `mcp_server_view.tsx` unless the viewer is a proxy admin. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * Fix runtime policy attachment initialization Mark runtime-created policies and attachments initialized so global policy attachments created from the policy builder apply immediately without requiring a restart. Co-authored-by: Cursor <cursoragent@cursor.com> * test(router): cover _try_early_resolve_deployments_for_model_not_in_names The router_code_coverage CI check requires every function in router.py to be referenced by at least one test under tests/{local_testing, router_unit_tests,test_litellm} in a file with "router" in its name. The recently-extracted helper had no direct test, so the check failed with "0.45% of functions in router.py are not tested". Add a focused test that exercises the four return paths: model already in self.model_names, no fallback applies, pattern-router match, and default_deployment substitution (also asserting the stored default isn't mutated). https://claude.ai/code/session_019AVp1XL7RT9RxRe4qRLkay * Fix policy registry teardown in tests Reset the policy ID index during policy engine test cleanup so stale policy versions cannot leak between tests. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(batches): count non-chat tokens, validate batch-file model access (VERIA-39) (#27015) * fix(batches): count non-chat tokens and validate every model in batch file Two security control bypasses on POST /v1/batches: 1. `_get_batch_job_input_file_usage` only summed tokens for `body.messages` (chat completions). Embedding (`input`) and text completion (`prompt`) batches reported zero, letting massive non-chat workloads slip past TPM rate limits. Extend the counter to handle string and list shapes for both fields. 2. The batch input file was forwarded to the upstream provider without inspecting the models named inside the JSONL — only the outer `model` query parameter was checked against the caller's allowlist. A caller restricted to gpt-3.5 could submit a batch targeting gpt-4o and the upstream would execute it under the proxy's shared API key. Add `_get_models_from_batch_input_file_content` (returns the distinct `body.model` values) and call it from `_enforce_batch_file_model_access` in the pre-call hook, which runs each model through `can_key_call_model` so the same allowlist semantics (wildcards, access groups, all-proxy-models, team aliases) the proxy enforces on `/chat/completions` apply here too. Any unauthorized model raises a 403 before the file is forwarded. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(batches): count pre-tokenized prompt/input shapes, classify 403 logs Two follow-ups from the Greptile review on the batch validation PR: 1. P1 TPM bypass via integer token arrays. The OpenAI batch schema accepts ``prompt`` and ``input`` as ``list[int]`` (a single pre-tokenized prompt) or ``list[list[int]]`` (multiple) in addition to the string and ``list[str]`` shapes. Pre-fix only the string shapes were counted, so a caller could submit a batch with hundreds of millions of pre-tokenized tokens and the rate limiter would record zero. Extract the per-field logic into ``_count_prompt_or_input_tokens`` and count each int as one token. 2. P2 access-denial logs were indistinguishable from I/O failures. ``count_input_file_usage`` caught every exception under a generic "Error counting input file usage" message, so an intentional 403 from ``_enforce_batch_file_model_access`` looked the same in the logs as a missing file or a Prisma timeout. Catch ``HTTPException`` separately and log 403s at WARNING level with a security-relevant message before re-raising. Tests cover the new shapes: single ``list[int]``, ``list[list[int]]`` (the worst-case bypass vector), and embeddings ``input`` with pre-tokenized arrays. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(proxy): re-validate user_id after /user/info re-parses query (#27009) * fix(proxy): re-validate user_id ownership after /user/info re-parses query The route-level access check in `RouteChecks.non_proxy_admin_allowed_routes_check` reads `request.query_params.get("user_id")`, which decodes literal `+` to spaces. The endpoint then re-parses the raw query string with `urllib.unquote` in `get_user_id_from_request` to preserve `+` characters (so plus-addressed emails work as user_ids). Those two paths produce different ids: a caller who registered a user_id containing a literal space could pass the route check and then read another user's row by sending the encoded `+` form. Add `_enforce_user_info_access` and call it after `_normalize_user_info_user_id` returns the final id. Proxy admin / view-only admin still bypass; everyone else must match the resolved user_id (or have no user_id, which falls back to the caller's own id later in the handler). Tests cover the admin bypass, owner-match path, and the cross-user lookup that this change blocks. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(proxy): apply user_info ownership check to PROXY_ADMIN_VIEW_ONLY `_enforce_user_info_access` was bypassing both PROXY_ADMIN and PROXY_ADMIN_VIEW_ONLY, but the upstream route check in `RouteChecks.non_proxy_admin_allowed_routes_check` only treats PROXY_ADMIN as a true admin for the `/user/info` route — view-only admins go through the `user_id == valid_token.user_id` enforcement along with regular users. Mirroring that asymmetry left the same encoded-`+` bypass open for view-only admins whose user_id contains a literal space. Drop the PROXY_ADMIN_VIEW_ONLY exemption so the post-decode re-check matches the upstream rule. Update tests: a view-only admin must now be blocked from cross-user lookups but still allowed to read their own row. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(spend-logs): opt-in suppression of stack traces in spend-tracking error logs Adds LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS env var. When set to true and the proxy log level is INFO or above, spend-tracking error paths emit a single ERROR line without the full traceback. Stack traces are preserved at DEBUG and the Sentry / proxy_logging_obj.failure_handler path is unchanged. The new spend_log_error helper is wired through the spend write hot path: - DBSpendUpdateWriter (update_database, _update_*_db, batch upsert, redis-commit fallbacks) - _ProxyDBLogger._PROXY_track_cost_callback - get_logging_payload exception path - update_spend / update_daily_tag_spend / spend logs queue monitor Resolves LIT-2704. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend This call site previously logged a single-line error via verbose_proxy_logger.error() with no traceback. Switching it to spend_log_error(..., exc=e) caused a full stack trace to render by default (when LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS is unset), which contradicts the PR goal of leaving default behavior unchanged. Revert this specific site to the original error log call. * fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend Bugbot caught a regression: the previous error log here was a single-line verbose_proxy_logger.error(...) with no traceback. spend_log_error attaches the active exception's traceback by default (when the suppression env var is unset), so swapping it in changed default behavior. Revert this one site to its original .error() call to keep the PR strictly opt-in. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * feat(spend-logs): suppress traceback in SpendLogs error_information row Extend LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS to the failure callback so the per-row Metadata pane in the UI no longer shows the stack trace when the opt-in env var is set, matching the existing console-side suppression. https://claude.ai/code/session_014dztoRbRnRvq54HL9EyHx6 * [Fix] Proxy: Repair Merge Fallout In Router-Override Fallback Auth Conflict resolution for #26968 dropped the `Iterator` typing import (NameError at module load), left a dead `fallback_models = cast(...)` block, and the new tests called `_enforce_key_and_fallback_model_access` without the now-required `request` kwarg. * isolate dual OTEL handlers * harden cloud file compatibility path * harden cloud file compatibility path * [Fix] Proxy/Key Management: Align Key-Org Membership Checks On Generate And Regenerate Mirrors the membership rule on /key/update so that /key/generate and /key/{key}/regenerate apply the same `_validate_caller_can_assign_key_org` gate when the caller specifies an `organization_id`. Proxy admins bypass. The check no-ops when `organization_id` is not being set. * thread trusted params through vertex file content * trust only server legacy file flag * chore(proxy): keep public AI hub unauthenticated * fix(proxy): preserve low-detail readiness status * [Test] Anthropic: Replace Legacy Claude-4-Sonnet Alias With Haiku 4.5 Three live-API tests pinned to claude-4-sonnet-20250514, which is a non-canonical alias of claude-sonnet-4-20250514. Anthropic's main API no longer resolves the legacy form under freshly issued keys, so the tests fail with not_found_error. The token counter test pinned to claude-sonnet-4-20250514 itself (deprecation_date 2026-05-14, two weeks out) was on borrowed time too. Bump all four to claude-haiku-4-5-20251001 — capability superset for what these tests exercise (streaming, parallel tool calling, extended thinking, token counting), no upcoming deprecation, cheaper per-token. * chore(proxy): move URL-valued model/file_id guard from SDK to proxy The previous per-provider guards in HuggingFace, Oobabooga, and Gemini files lived in the SDK layer, breaking SDK callers who legitimately pass URL-valued model identifiers. Move the check to the proxy boundary in add_litellm_data_to_request so SDK users keep working while proxy users default-deny URL-valued model and file_id, with admin opt-in via litellm.provider_url_destination_allowed_hosts. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * [Chore] Proxy/UI: Drop stray _experimental/out/chat/index.html This file is a regenerable UI build artifact that should not be tracked in source. Removing so the merge into litellm_internal_staging stays clean. * [Test] Anthropic Passthrough: Bump Streaming Cost-Injection Test To Haiku 4.5 test_anthropic_messages_streaming_cost_injection hits the proxy's /v1/messages route, which routes via the anthropic/* wildcard to api.anthropic.com. The 404 surfaced in the test was Anthropic's own not_found_error propagated back through the proxy (visible from the x-litellm-model-id hash on the response — the proxy did route). Same root cause as the prior commit: the legacy claude-4-sonnet-20250514 alias is no longer recognized by Anthropic's main API under the new key. Swap to claude-haiku-4-5-20251001 — same routing path, canonical model. * fix(proxy): handle ownership-recording failures after upstream create If record_container_owner raises after the upstream container is created, the user previously got a 500 with no usable container — they were billed for an unreachable resource. Move ownership recording into the create path's exception handling and split the two failure modes: - HTTPException from the recorder (auth conflicts) propagates verbatim so the client sees the real status code, not a generic LLM error. - Unexpected exceptions are logged and swallowed; the response is returned to the caller so they aren't billed for a container they can't address. The DB row stays untracked until an operator reconciles. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(guardrails): close post-call coverage gaps * fix(types): add /team/permissions_bulk_update to management_routes The blocklist check in _check_proxy_admin_viewer_access only fires for routes that match LiteLLMRoutes.management_routes — the bulk-update endpoint was missing from that list, so the test for view-only admins on /team/permissions_bulk_update fell through to "allow." Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * [Test] Anthropic Passthrough: Bump Thinking Tests Off Legacy Sonnet 4 Alias base_anthropic_messages_test.test_anthropic_messages_with_thinking and test_anthropic_streaming_with_thinking still pinned to claude-4-sonnet-20250514 — the same legacy alias Anthropic no longer recognizes under freshly issued keys. The other four tests in this base class already use claude-sonnet-4-5-20250929; these two were missed. Bump to claude-haiku-4-5-20251001 (supports_reasoning=true, no upcoming deprecation). Subclasses including TestAnthropicPassthroughBasic inherit these methods. * fix(guardrails): cover multi-choice output variants * fix(proxy): preserve public ai hub ui setting * fix(scim): cascade FK cleanup on user delete and surface block status in UI SCIM DELETE /Users/{id} previously called litellm_usertable.delete without clearing rows that FK back to the user, so Postgres rejected the delete with LiteLLM_InvitationLink_user_id_fkey and the SCIM caller saw a 500. Add a helper to drop invitation_link, organization_membership, and team_membership rows before the user delete (mirrors /user/delete in internal_user_endpoints). Also add a Status column to the Virtual Keys and Internal Users tables so admins can see at a glance which keys are blocked and which users SCIM has deactivated. SCIM-blocked keys carry a tooltip explaining the origin. Pin the dashboard's Node version to 20 via .nvmrc to match CI. * chore: update Next.js build artifacts (2026-05-02 03:21 UTC, node v20.20.2) * perf(proxy): cache container/skill ownership reads on the hot path Container ownership and skill rows are looked up on every retrieve / delete / list / file-content / chat-completion-with-skill call. The new stores wrapped raw Prisma queries with no cache, putting one DB round-trip on each request. Add an in-process TTL'd cache mirroring the _byok_cred_cache pattern in mcp_server/server.py: per-key (value, monotonic_timestamp), 60s TTL, 10000-entry cap with full-clear on overflow, invalidated by every write. Negative results (`None`) are cached too so untracked-resource checks also skip the DB. Tests cover: cache-after-first-hit, negative caching, write invalidation, no-caching-on-DB-error, TTL expiry, capacity eviction. 56 tests pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore: update Next.js build artifacts (2026-05-02 03:39 UTC, node v20.20.2) * fix: remove traceback key instead of it being "" * fix: linting error * fix(scim): preserve scim_active on PUT when client omits the field A SCIM PUT may legally omit `active` (full-replace with the field absent). Pydantic fills the SCIMUser.active default of True, so the PUT handler was overwriting metadata.scim_active with True even when the client never sent it — silently reactivating a previously SCIM-blocked user and unblocking their keys. Use model_fields_set to detect whether the client actually sent `active`. If omitted, preserve the prior scim_active value and skip the cascade to virtual keys. Also drop comments added in this PR that just narrate what the code does; keep only the docstrings and the SQL-NULL pitfall note that explain non-obvious behaviour. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(proxy): use set lookup for permitted agent filters * fix(mcp): redact command fields for non-admin server views * fix(proxy): forward decoded container ids after ownership checks * fix(caching): handle stale isolated Redis semantic index * fix(cloudflare): support response_text in streaming chunk parser Newer Cloudflare Workers AI models (e.g. Nemotron) emit 'response_text' instead of 'response' on streamed chunks. The non-streaming path was already updated to fall back to 'response_text' (#26385), but the streaming chunk parser still only read 'response', which caused streaming requests against those models to silently produce empty content. Mirror the non-streaming fallback in CloudflareChatResponseIterator.chunk_parser and add a streaming test for the response_text shape. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * Fix code qa * Address bugbot: drop dead encode/decode helpers; preserve empty custom_id - Remove unused _encode_gcp_label_value / _decode_gcp_label_value singular helpers; only the _chunks variants are actually called. - Use 'is not None' check for custom_id so empty-string custom_ids are still labeled and round-trip through batch outputs. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * Forward Vertex file content logging context * test vertex file content logging forwarding Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * Fix Vertex batch output logging mutation * fix: don't mutate caller's logging_obj in _try_transform_vertex_batch_output_to_openai The method was overwriting logging_obj.optional_params, logging_obj.model, and logging_obj.start_time on the caller's Logging instance. When invoked from llm_http_handler.py's generic framework path, the framework's own logging_obj (which already went through pre_call) had its properties clobbered, causing model and start_time to reflect the last batch line's values rather than the original call context. Fix: create a fresh local Logging instance for the per-line transformation instead of mutating the incoming logging_obj. The caller's object is now left entirely untouched regardless of whether a logging_obj was passed in or not. Regression tests added to verify model, start_time, and optional_params are not mutated on the caller's logging_obj. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * feat: add opt-out flag for Vertex batch output transformation Adds litellm.disable_vertex_batch_output_transformation (default False). When True, afile_content returns raw Vertex predictions.jsonl untouched so users that parse candidates/modelVersion directly are not broken. * fix(anthropic,bedrock): omit thinking/output_config when reasoning_effort="none" Setting reasoning_effort="none" on Anthropic chat models (direct, Bedrock Invoke, Bedrock Converse, Vertex AI Anthropic, Azure AI Anthropic) crashed LiteLLM with: litellm.APIConnectionError: 'NoneType' object has no attribute 'get' Both the Anthropic chat transformation and Bedrock Converse called ``AnthropicConfig._map_reasoning_effort`` and assigned the ``None`` it returns for ``"none"`` directly to ``optional_params["thinking"]``. Downstream ``is_thinking_enabled`` then did ``optional_params["thinking"].get("type")`` and crashed. Pop ``thinking`` (and on Claude 4.6/4.7, ``output_config``) instead of assigning ``None``, restoring the documented contract that ``reasoning_effort="none"`` means "do not enable thinking". This also prevents downstream Anthropic 400s ("thinking: Input should be an object", "output_config.effort: Input should be ...") if the bug were ever masked. Verified end-to-end against the live Anthropic API and Bedrock Converse on claude-opus-4-{5,6,7} and claude-sonnet-4-6, plus Bedrock Invoke for Claude 4.5/4.6. Vertex AI Anthropic and Azure AI Anthropic inherit the fixed ``map_openai_params`` from ``AnthropicConfig`` and need no further changes. * fix(vertex-ai): set response=null on batch error entries per OpenAI spec The Vertex batch output transformer was emitting both a populated 'response' and 'error' for failed batch entries. The OpenAI Batch output spec defines them as mutually exclusive: on error 'response' MUST be null. This broke any consumer using 'result["response"] is None' to detect failures. * test(vertex-ai): cover transformation_error path emits response=null * fix(security): sandbox jinja2 in gitlab/arize/bitbucket prompt managers DotpromptManager was hardened to render through ImmutableSandboxedEnvironment. The three sibling managers (gitlab, arize, bitbucket) were missed and still instantiate plain jinja2.Environment(), leaving the same attribute-traversal SSTI primitive open: a template fetched from a GitLab/BitBucket repo or Arize Phoenix workspace can reach __class__.__init__.__globals__ and execute arbitrary Python on the proxy host. Match the dotprompt pattern by switching all three to ImmutableSandboxedEnvironment. The sandbox blocks the dunder-traversal chain while leaving normal {{ var }} substitution intact, so the template surface is unchanged for legitimate use. Adds tests/test_litellm/integrations/test_prompt_manager_ssti.py (18 cases) verifying each manager's jinja_env is a sandbox, that classic SSTI payloads raise SecurityError, and that ordinary variable rendering still works. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(proxy): drop client-supplied pricing fields from request bodies The proxy currently forwards request-body pricing parameters (the fields on `CustomPricingLiteLLMParams`, plus `metadata.model_info`) into the core call path. Those fields belong to deployment configuration, not to per-request input — sending them from a client mutates the request's recorded cost and, via `litellm.completion` → `register_model`, the process-wide `litellm.model_cost` map for every later caller in the worker. Strip them at the boundary. The strip set is built from `CustomPricingLiteLLMParams.model_fields` so pricing fields added later are covered automatically. Operators who do want clients to supply per-request pricing can opt back in per key or team via `metadata.allow_client_pricing_override = true`, mirroring the existing `allow_client_mock_response` and `allow_client_message_redaction_opt_out` flags. Tests cover the strip set's coverage, root and metadata strips, the opt-in skip on both key and team metadata, and a regression check that the global `litellm.model_cost` map is unmutated after a stripped request. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(proxy): log stripped pricing fields at debug for operator visibility Operators upgrading would otherwise see client-supplied pricing overrides silently stop applying with no diagnostic. Emit a debug-level line listing the dropped fields and pointing at the opt-in flag when any are stripped; stay silent on the no-op path so the log isn't filled with noise. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(proxy): move pricing strip below the litellm_metadata JSON-string parse The strip ran before the proxy parses ``litellm_metadata`` from a JSON string into a dict (a path used by multipart/form-data and ``extra_body`` callers), so ``isinstance(metadata, dict)`` was False and ``model_info`` survived the strip. Move the call to the same post-parse position the ``user_api_key_*`` strip already uses for the same reason. Adds a regression test exercising the JSON-string ``litellm_metadata`` path. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(responses): replace legacy claude-4-sonnet alias in multiturn tool-call test Anthropic's main API no longer resolves the non-canonical 'claude-4-sonnet-20250514' alias for freshly issued keys, returning 404 not_found_error. PR #27031 already swept three other live tests pinned to this alias to claude-haiku-4-5-20251001 but missed test_multiturn_tool_calls in the responses API suite, which is now failing reliably on PR CI runs (e.g. PR #27074, job 1603363). Bump the two model references in test_multiturn_tool_calls to the same claude-haiku-4-5-20251001 snapshot used by PR #27031 -- it covers everything this test exercises (tool calling, multi-turn) and isn't on a deprecation schedule. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * chore(proxy): close callback-config and observability-credential side channels Two related gaps in the proxy's request bouncer: 1. ``is_request_body_safe`` (auth_utils.py) walked the request-body root and the ``litellm_embedding_config`` nested dict, but not ``metadata`` or ``litellm_metadata``. The same fields it bans at root — Langfuse / Langsmith / Arize / PostHog / Braintrust / Phoenix / W&B Weave / GCS / Humanloop / Lunary credentials and routing — were silently accepted when the caller put them inside metadata, retargeting observability callbacks to a caller-controlled host with caller-supplied creds. Walk both metadata containers (and parse the JSON-string form sent via multipart / ``extra_body``) through the same banned-params helper, so the existing ``allow_client_side_credentials`` opt-in covers both paths consistently. 2. The banned-params list was hand-maintained and lagged the canonical ``_supported_callback_params`` allow-list in ``initialize_dynamic_callback_params``. Derive the observability bans from that allow-list (minus a small ``_SAFE_CLIENT_CALLBACK_PARAMS`` set for informational fields like ``langfuse_prompt_version`` and ``langsmith_sampling_rate``) so future integrations are covered automatically; ``_EXTRA_BANNED_OBSERVABILITY_PARAMS`` carries the handful of fields integrations read but the allow-list hasn't caught up to. A guard test fails CI if a new entry is added to ``_supported_callback_params`` without an explicit safe-list decision. Separately in ``litellm_pre_call_utils.py``: add ``callbacks``, ``service_callback``, ``logger_fn``, and ``litellm_disabled_callbacks`` to ``_UNTRUSTED_ROOT_CONTROL_FIELDS``. The first three are appended to worker-wide ``litellm.{input,success,failure,_async_*,service}_callback`` lists / ``litellm.user_logger_fn`` from inside ``function_setup`` — one request poisons every subsequent caller in that worker. The last is the inverse primitive: the legitimate path reads it from key/team metadata, the request-body version silently disables admin-configured audit / observability for the call. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(auth): per-param allow must continue, not return early A pre-existing logic bug in ``_check_banned_params``: when the deployment-level ``configurable_clientside_auth_params`` permitted one banned field, the loop ``return``-ed on the first match instead of ``continue``-ing, so any other banned param later in the same body or metadata dict was never checked. This PR's metadata walk multiplies the surface where that bypass matters — a body pairing an allowed ``api_base`` with an observability credential like ``langfuse_host`` would silently pass. Proxy-wide ``allow_client_side_credentials`` keeps ``return`` (it's a global opt-in for every banned param). The per-param branch becomes ``continue`` so only the one explicitly-permitted field is skipped. Adds a regression test that exercises the api_base + langfuse_host pair. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(vector_store): resolve embedding config at request time, never persist creds The vector store create/update path previously called ``_resolve_embedding_config`` against the admin-configured router/DB model and persisted the resolved ``litellm_embedding_config`` dict (``api_key`` / ``api_base`` / ``api_version``) into the ``litellm_managedvectorstorestable.litellm_params`` column. Because the resolver expanded ``os.environ/...`` references via ``get_secret``, the DB row carried cleartext provider credentials, and the ``/vector_store/{new,info,update,list}`` responses returned them to any authenticated caller who could supply a known admin model name. Move the auto-resolve out of ``create_vector_store_in_db`` and out of the update path. Persist only the user-supplied ``litellm_embedding_model`` reference. Resolve at request-handling time inside ``_update_request_data_with_litellm_managed_vector_store_registry`` so the resolved config lives in the per-request ``data`` dict and is garbage-collected after the response. Legacy rows that were created by an earlier proxy version and already carry a resolved ``litellm_embedding_config`` skip the re-resolution and pass through unchanged so embedding calls keep working. The ``new_vector_store`` response now also runs the existing ``_redact_sensitive_litellm_params`` masker (already used by ``info``, ``update``, and ``list``), defending against caller-supplied cleartext on the create path and against legacy rows whose persisted credentials are still in the database. Existing tests that asserted the old write-time-resolve behaviour are updated to assert the new persistence shape (no embedding config stored, just the model reference). Two new tests cover the use-time path: one asserting fresh resolution happens when a row carries only the model reference, the other asserting legacy rows with persisted config skip re-resolution and continue to work. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(vector_store): tighten registry-mutation comment and dedupe test helpers * fix(vector_store): cache use-time embedding-config resolution Hold the resolved config in a process-memory TTL cache so the request-handling path doesn't run litellm_proxymodeltable.find_first on every vector-store call. * fix(anthropic,bedrock,vertex): forward output_config.effort + 400 on garbage reasoning_effort Follow-up bugs surfaced by the QA sweep on PR #27039 (https://github.com/BerriAI/litellm/pull/27039#issuecomment-4363363610). 1. Stop stripping output_config.effort on Bedrock + Vertex adaptive routes. - Vertex AI Claude 4.6/4.7 accepts output_config.effort on rawPredict (verified end-to-end against us-east5 / global). The strip helper now no-ops for effort. - Bedrock Converse routes output_config into additionalModelRequestFields for anthropic base models so the requested adaptive tier (low/medium/ high/xhigh/max) actually reaches the wire instead of all collapsing to identical thinking. - Bedrock Invoke chat transformation (AmazonAnthropicClaudeConfig) stops popping output_config from the post-AnthropicConfig request body. - Bedrock Invoke /v1/messages allowlist (BedrockInvokeAnthropicMessagesRequest) now lists output_config so the runtime allowlist filter forwards it. 2. Validate effort across Bedrock Converse so 'disabled' / 'invalid' / '' / unsupported tiers (xhigh/max on Sonnet 4.6 or budget-mode 4.5 models) surface as a clean 400 BadRequestError instead of 500. 3. ValueError -> BadRequestError throughout (AnthropicConfig.map_openai_params, _apply_output_config, AmazonConverseConfig._handle_reasoning_effort_parameter). Empty-string effort is now rejected (was silently passing the 'if effort and ...' short-circuit). 4. Floor reasoning_effort='minimal' at the Anthropic provider minimum (1024 budget_tokens) via new ANTHROPIC_MIN_THINKING_BUDGET_TOKENS so it's a usable tier on direct Anthropic / Azure AI Anthropic / Vertex AI Anthropic / Bedrock Invoke (all of which 400 below 1024). 5. model_prices: dedupe duplicate supports_max_reasoning_effort key on claude-opus-4-7 / claude-opus-4-7-20260416. Adds regression tests across all five affected paths; existing tests asserting the silent-strip behavior were updated to reflect the new pass-through and clean 400 surfaces. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(constants): make ANTHROPIC_MIN_THINKING_BUDGET_TOKENS a plain constant The documentation CI test (tests/documentation_tests/test_env_keys.py) asserts every os.getenv() key in the source has a matching entry in the litellm-docs config_settings.md table. ANTHROPIC_MIN_THINKING_BUDGET_TOKENS tracks Anthropic's published wire-protocol minimum (1024) — it's not a user-tunable, so making it env-overridable was wrong anyway. Drop the os.getenv() wrapper; the value is now a plain literal. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(anthropic,bedrock): correct effort error message and dedupe effort_map - Remove 'none' from the Bedrock _validate_anthropic_adaptive_effort error message; it was listed as a valid value but rejected by the membership check, leaving users in a feedback loop if they tried 'none'. - Hoist the duplicated reasoning_effort -> output_config.effort mapping out of AnthropicConfig.map_openai_params and AmazonConverseConfig._handle_reasoning_effort_parameter into a single AnthropicConfig.REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT class constant so the two routes cannot drift. * fix(anthropic): translate reasoning_effort on /v1/messages route Closes the remaining QA-sweep gap on PR #27074: Bedrock Invoke /v1/messages was silently ignoring ``reasoning_effort`` because the shared param filter only kept native Anthropic keys, so every effort tier collapsed to the same behavior on the wire (27/231 cells failing across opus-4-5 / opus-4-6 / sonnet-4-6). Map ``reasoning_effort`` to native Anthropic ``thinking`` / ``output_config.effort`` at the ``AnthropicMessagesConfig`` layer so all four /v1/messages routes (direct Anthropic, Azure AI, Vertex AI, Bedrock Invoke) inherit the same translation: - Add ``reasoning_effort`` to ``AnthropicMessagesRequestOptionalParams`` so the param filter in ``AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param`` no longer drops it before the transformation runs. - Add ``_translate_reasoning_effort_to_anthropic`` and call it from ``transform_anthropic_messages_request``. Mirrors ``AnthropicConfig.map_openai_params`` on the chat completion path (re-uses ``_map_reasoning_effort`` and ``REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT``) so the two routes cannot drift. Pops ``reasoning_effort`` so it never reaches the wire. - Caller-supplied native ``thinking`` / ``output_config.effort`` always win — same precedence as ``_translate_legacy_thinking_for_adaptive_model``. - Garbage values (``""``, ``"disabled"``, ``"invalid"``) raise ``AnthropicError(status_code=400)`` instead of falling through and surfacing as 500s from the provider. - ``"none"`` clears thinking + output_config so callers can opt out per request. Also restores the non-adaptive-model test coverage on Bedrock Invoke /v1/messages that the previous commit lost when ``test_bedrock_messages_strips_output_config`` was renamed to the ``forwards`` variant on Opus 4.7. Adds a new test file ``test_reasoning_effort_translation.py`` covering the translation at the shared config level (adaptive + non-adaptive models, none, garbage, caller precedence) so all four /v1/messages routes are exercised by a single suite. Adds parametrized + behavioral tests on the Bedrock Invoke /v1/messages suite covering: minimal/low/medium/high/xhigh/max mapping for adaptive models, thinking-budget mapping for non-adaptive Opus 4.5, ``none`` clears both, garbage raises 400, explicit ``output_config`` wins. Refs: https://github.com/BerriAI/litellm/pull/27074 * fix(anthropic,bedrock): reject unmapped reasoning_effort at mapping site Both the chat completion path (AnthropicConfig.map_openai_params) and the Bedrock Converse path (_handle_reasoning_effort_parameter) used REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT.get(value, value) which falls back to the raw input on unmapped keys. Combined with _map_reasoning_effort returning type='adaptive' for any string on Claude 4.6/4.7, garbage values (e.g. 'disabled') could leak into optional_params['output_config']['effort'] unvalidated if map_openai_params ran without the downstream transform_request or _validate_anthropic_adaptive_effort check. Mirror the /v1/messages pattern: use .get(value) (no fallback) and raise BadRequestError immediately when the value is unmapped, co-locating validation with the mapping for defense in depth. * style: black formatting Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(anthropic): stop class-attr leak; gate xhigh/max on every route The reasoning-effort mapping dict was a public class attribute on AnthropicConfig, so BaseConfig.get_config returned it as a request parameter and every Anthropic-backed call (Anthropic / Azure / Vertex / Bedrock Invoke) hit a 400 'REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT: Extra inputs are not permitted' from the provider. Move the mapping to a module-level constant. _supports_effort_level only looked the model up under custom_llm_provider='anthropic', so bedrock-prefixed model ids (e.g. bedrock/invoke/us.anthropic.claude-opus-4-7) returned False for both 'max' and 'xhigh' even when the underlying model entry has the flag set. Strip known provider prefixes and retry the lookup against litellm.model_cost directly so per-model gating works on every route. Mirror the per-model xhigh/max gate from AnthropicConfig._apply_output_config in AnthropicMessagesConfig._translate_reasoning_effort_to_anthropic so the /v1/messages route also raises a clean 400 instead of forwarding the unsupported tier. * feat(anthropic,bedrock): strip output_config under drop_params for non-effort models When a proxy fronts Claude Code (which always sends `output_config.effort`) at a pre-4.5 Anthropic model — haiku-3, sonnet-3.5, opus-3, sonnet-4 — the forwarded knob causes a forced 400 the client can't fix. Gating a strip behind the existing `drop_params` flag lets operators opt into silent fixup once and stop worrying about per-model param hygiene. Default (`drop_params=False`) still forwards and surfaces the provider's error, preserving the strict, debuggable contract from #27074. Per https://platform.claude.com/docs/en/build-with-claude/effort the supporting set is Opus 4.5+, Sonnet 4.6+, and Mythos Preview; everything else is dropped (with a verbose_logger warning so the strip is visible). Recognition uses model-name patterns plus a fallback to any `supports_*_reasoning_effort` flag in the model map for forward compatibility with new entries. https://claude.ai/code/session_01WjHq31rvXT6xYNdVmSJvRp (cherry picked from commit |
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clyang
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3f5e28fcdc
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Adding Cycraft XecGuard integration (#26011) | ||
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Abhijoy Sarkar
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c688d9d6bc
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Add PromptGuard guardrail integration (#24268)
* Add PromptGuard guardrail integration
Add PromptGuard as a first-class guardrail vendor in LiteLLM's proxy,
supporting prompt injection detection, PII redaction, topic filtering,
entity blocklists, and hallucination detection via PromptGuard's
/api/v1/guard API endpoint.
Backend:
- Add PROMPTGUARD to SupportedGuardrailIntegrations enum
- Implement PromptGuardGuardrail (CustomGuardrail subclass) with
apply_guardrail handling allow/block/redact decisions
- Add Pydantic config model with api_key, api_base, ui_friendly_name
- Auto-discovered via guardrail_hooks/promptguard/__init__.py registries
Frontend:
- Add PromptGuard partner card to Guardrail Garden with eval scores
- Add preset configuration for quick setup
- Add logo to guardrailLogoMap
Tests:
- 30 unit tests covering configuration, allow/block/redact actions,
request payload construction, error handling, config model, and
registry wiring
* Fix redact path and init ordering per review feedback
- P1: Update structured_messages (not just texts) when PromptGuard
returns a redact decision, so PII redaction is effective for the
primary LLM message path
- P2: Validate credentials before allocating the HTTPX client so
resources aren't acquired if PromptGuardMissingCredentials is raised
- Add tests for structured_messages redaction and texts-only redaction
* Harden PromptGuard integration: fail-open, event hooks, images, docs
- Add block_on_error config (default fail-closed, configurable fail-open)
- Declare supported_event_hooks (pre_call, post_call) like other vendors
- Forward images from GenericGuardrailAPIInputs to PromptGuard API
- Wrap API call in try/except for resilient error handling
- Add comprehensive documentation page with config examples
- Register docs page in sidebar alongside other guardrail providers
- Expand test suite from 32 to 40 tests covering new functionality
* Fix dict[str, Any] -> Dict[str, Any] for Python 3.8 compat
* Address remaining Greptile feedback: timeout, redact guard
- Add explicit 10s timeout to async_handler.post() to prevent
indefinite hangs when PromptGuard API is unresponsive
- Guard redact path: only update inputs["texts"] when the key
was originally present, avoiding phantom key injection
- Add test: redact with structured_messages only does not create
texts key (41 tests total)
* Fix CI lint: black formatting, add PromptGuardConfigModel to LitellmParams
- Reformat promptguard.py to match CI black version (parenthesization)
- Add PromptGuardConfigModel as base class of LitellmParams for proper
Pydantic schema validation, consistent with all other guardrail vendors
- Use litellm_params.block_on_error directly (now a typed field)
* Address Greptile review: redact path, null decision, error context
- P1: Filter _extract_texts_from_messages to user-role messages only,
preventing system/assistant content from being injected into texts
- P1: Strengthen test_redact_updates_structured_messages assertion from
weak `in` check to strict equality, catching the injection bug
- P2: Use `result.get("decision") or "allow"` to handle explicit null
decision values (not just absent keys)
- P2: Wrap bare exception re-raise in GuardrailRaisedException so the
caller knows which guardrail failed (block_on_error=True path)
- P2: Add static Promptguard entry in guardrail_provider_map so the
preset works before populateGuardrailProviderMap is called
- Add test for explicit null decision treated as allow
* Fix black formatting: collapse f-string in error message
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Rohan
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bed44f5fe5
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Add Akto Guardrails to LiteLLM (#23250)
* akto guardrails support in litellm
* docs(guardrails): add akto to supported values in types/guardrails.py
* frontend changes + fixes
* feat(akto): update Akto guardrail integration with new configuration options and modes
* docs(akto): enhance Akto documentation and configuration descriptions for clarity
* feat(tests): add proxy server request headers to sample request data
* refactor(akto): remove optional account and VXLAN IDs; update documentation and tests
* feat(akto): add event_type parameter for enhanced observability in guardrail logging
* refactor(akto): update environment variable references
* refactor the python codes
* refactor and fix linting
* refactor(akto): remove unused event hook and clean up imports
* refactor(akto): enhance AktoGuardrail with async support and improved logging
* fix: Register DynamoAI guardrail initializer and enum entry (#23752)
* fix: Register DynamoAI guardrail initializer and enum entry
Fix the "Unsupported guardrail: dynamoai" error by:
1. Adding DYNAMOAI to SupportedGuardrailIntegrations enum
2. Implementing initialize_guardrail() and registries in dynamoai/__init__.py
The DynamoAI guardrail was added in PR #15920 but never properly registered
in the initialization system. The __init__.py was missing the
guardrail_initializer_registry and guardrail_class_registry dictionaries
that the dynamic discovery mechanism looks for at module load time.
Fixes #22773
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
* Update litellm/proxy/guardrails/guardrail_hooks/dynamoai/__init__.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update litellm/proxy/guardrails/guardrail_hooks/dynamoai/__init__.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* test: Add tests for DynamoAI guardrail registration
Verifies enum entry, initializer registry, class registry,
instance creation, and global registry discovery.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Haiku 4.5 <noreply@anthropic.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* docs: add v1.82.3 release notes and update provider_endpoints_support.json (#23816)
* Revert "docs: add v1.82.3 release notes and update provider_endpoints_support…" (#23817)
This reverts commit
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Ishaan Jaff
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65842eb7b5
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[Feat] UI - Show logos on MCP Apps page (#23320)
* feat(ui): add MCP server logo support across admin and chat UIs - New MCPLogoSelector component with grid of well-known logos (GitHub, Slack, Notion, Linear, Jira, etc.) and custom URL input - Create MCP Server form: logo picker with preview, OpenAPI presets auto-fill logo from registry icon_url - Edit MCP Server form: logo picker pre-populated from mcp_info.logo_url - Admin table: logos rendered next to server name in Name column - Chat MCPAppsPanel: logos on server cards (list + detail view) with graceful fallback to letter avatars - Chat MCPConnectPicker: logos next to server names in toggle list - Fix pre-existing bug: setTools -> clearTools in create form cancel - All 321 vitest files / 3211 tests pass Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * feat(ui): use local SVG logos for MCP services, fix Chat UI rendering - Add 15 new MCP service logo SVGs (Slack, Notion, Linear, Jira, Figma, Gmail, Stripe, Salesforce, Shopify, HubSpot, Twilio, Sentry, Zapier, GitLab, Google Drive) to both source and pre-built directories - Switch MCPLogoSelector from CDN URLs (cdn.simpleicons.org) to local asset paths (/ui/assets/logos/) for reliable rendering - Logos now served by the proxy itself, working from any page path including /ui/chat/ (absolute paths resolve correctly everywhere) Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> |
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Ishaan Jaff
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500a88f01b
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[UI QA] - Add all provider models + providers on ui (#22461)
* feat(ui): add missing provider logos and map all backend providers to UI - Downloaded 26 SVG logos from lobehub/lobe-icons for providers that were missing visual branding (AI21, Baseten, Cloudflare, GitHub, Huggingface, Hyperbolic, Lambda, LM Studio, Meta Llama, Moonshot, Nebius, Novita, Nvidia NIM, Replicate, Recraft, Topaz, V0, Vercel, Watsonx/IBM, Xinference, Friendli, Morph, Cometapi, Featherless, Langfuse, GitHub Copilot) - Extended Providers enum from 47 to 107 entries to cover all backend providers from provider_create_fields.json - Extended provider_map to map all new enum keys to litellm_provider values - Extended providerLogoMap to assign logos to all providers where available, reusing parent logos for variants (e.g. Anthropic Text -> anthropic.svg) - Fixed SVG currentColor issue: replaced fill='currentColor' with explicit colors since CSS inheritance doesn't work in <img> elements - Updated test reference from Providers.Watsonx to Providers.WATSONX Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * docs(agents): add UI dashboard dev notes to Cursor Cloud instructions Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * refactor(ui): remove non-LLM providers from Add Model dropdown Remove Custom, Custom OpenAI, GitHub, Humanloop, Langfuse, Litellm Proxy, and Milvus from the Providers enum, provider_map, and providerLogoMap. These are not LLM API providers (they are internal tools, vector stores, or observability platforms) and should not appear in the Add Model form. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> |
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Ishaan Jaff
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e3756252a8
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Development environment setup (#22432)
* feat: add Cursor Cloud Agents as a native pass-through provider
- Add CURSOR to LlmProviders enum
- Add /cursor/{endpoint:path} pass-through route with Basic Auth
- Add /cursor to mapped_pass_through_routes for proper routing
- Create CursorPassthroughLoggingHandler for Logs page visibility
- Classifies operations (agent:create, agent:list, models:list, etc.)
- Logs model as cursor/cursor:<operation> for clean Logs display
- Tracks cost as $0 (subscription-based, no per-request pricing)
- Add Cursor to UI: provider enum, logo, credential fields
- Add provider_create_fields.json entry for LLM Credentials UI
- Add 18 unit tests covering route, auth, logging, and classification
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix: use correct Cursor logo from lobehub, add documentation page
- Replace placeholder Cursor logo with official hexagonal logo from lobehub
- Add docs/pass_through/cursor.md with full tutorial matching a2a_cost_tracking style
- Quick Start: add creds on UI, start proxy, launch agent, view logs
- Examples: all Cursor Cloud Agents API endpoints
- Advanced: virtual key usage
- Screenshots: credential form, logs page, log detail view
- Add Cursor to sidebars.js under Pass-through Endpoints
- Add screenshots to docs/my-website/img/
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* docs: simplify Cursor doc - UI-only flow, no config.yaml needed
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix: cursor pass-through reads credentials from UI (litellm.credential_list)
The pass-through route now checks litellm.credential_list as a fallback
when CURSOR_API_KEY env var is not set. This means adding credentials
via the UI (Models + Endpoints → LLM Credentials) works without any
config.yaml or environment variable setup.
Credential lookup order:
1. passthrough_endpoint_router (config.yaml with use_in_pass_through)
2. litellm.credential_list (credentials added via UI)
3. CURSOR_API_KEY environment variable
Also respects api_base from UI credentials if set.
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
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datzscaler
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f74fdfbb61
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feat(ui): added UI for Zscaler AI Guard (#21077)
* fix: allow Management keys to access user/daily/activity and team/daily/activity * feat(ui): added UI for Zscaler AI Guard * feat(ui): addressed UI comment * Apply suggestion from @greptile-apps[bot] Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> --------- Co-authored-by: naaa760 <neh6a683@gmail.com> Co-authored-by: yuneng-jiang <yuneng.jiang@gmail.com> Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> |
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Ishaan Jaff
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51339f5ef1
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[Feat] RAG API - Add s3_vectors as provider on /vector_store/search API + UI for creating + PDF support for /rag/ingest (#19895)
* init S3VectorsRAGIngestion as a supported ingestion provider for RAG API * test: TestRAGS3Vectors * init S3VectorsVectorStoreOptions * init s3 vectors * code clean up + QA * fix: get_credentials * S3VectorsRAGIngestion * TestRAGS3Vectors * docs: AWS S3 Vectors * add asyncio QA checks * fix: S3_VECTORS_DEFAULT_DIMENSION * init ui for bedrock s3 vectors * fix add /search support for s3_vectors * init atransform_search_vector_store_request * feat: S3VectorsVectorStoreConfig * TestS3VectorsVectorStoreConfig * atransform_search_vector_store_request * fix: S3VectorsVectorStoreConfig * add validation for bucket name etd * fix UI validation for s3 vector store * init extract_text_from_pdf * add pypdf * fix code QA checks * fix navbar * init s3_vector.png * fix QA code |
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Sameer Kankute
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ec1403ada0
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Merge pull request #18496 from Chesars/feat/add-minimax-provider-ui
feat: Add MiniMax provider support to UI dashboard |
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Chesars
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e31ee9be51 |
feat: Add MiniMax official logo to UI
- Downloaded official MiniMax logo from HuggingFace repository - Added minimax.svg to assets/logos directory - Updated providerLogoMap to reference the logo - Logo source: https://huggingface.co/MiniMaxAI/MiniMax-VL-01 |
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vasilisazayka
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f284fc716d
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fix(sap): add sap as provider for list in add credentials component in proxy ui, add sap logo (#18375) | ||
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yuneng-jiang
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0ee924f91e | Adding svg | ||
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Ishaan Jaff
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a4fb0df028
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[Feat] New provider - Agent Gateway, add pydantic ai agents (#18013)
* init A2AProviderConfigManager * move file * move file * add pydnatic ai folder * init providers * test_pydantic_ai_non_streaming * fix import * INIT pydantic * use_a2a_form_fields * TestPydanticAITransformation |
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Ishaan Jaff
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3054b6ea60
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[Feat] A2A Gateway - allow adding Azure Foundry Agents on UI (#17909)
* add CostConfigFields * add CostConfigFields * add output_cost_per_token * refactor table * add agent cost view * add azure foundry fields * add foundry logo * fix: clean error * fix utils * fix agent edi * add easter egg * fix order * test_handle_streaming_forwards_api_key * fix forward api key down * fix a2a send msg * add A2a comparison on compare playground * fix chat ui * fix bedrock agentcore stream |
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Ishaan Jaff
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4a7437ba5f
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[Feat] Agent Gateway - allow adding langgraph, bedrock agent core agents (#17802)
* fix: langgraph bridge streaming * add public/agents/fields * test_a2a_completion_bridge_non_streaming * TestA2AStreamingTransformation * AgentCredentialFieldMetadata * add new logo * refactor add agent * fix add dynamic fields * feat allow adding langgraph agent * add langgraph provider * stash * add AgentCreateInfo * agent_create_fields * fix fields * test_a2a_completion_bridge_bedrock_agentcore * test_a2a_completion_bridge_bedrock_agentcore * add public endpoints * fix a2a endpoints * fix dynamic fields |
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Ishaan Jaff
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585aee2ae4
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[Feat] Agent Gateway - Allow tracking request / response in "Logs" Page (#17449)
* init litellm A2a client * simpler a2a client interface * test a2a * move a2a invoking tests * test fix * ensure a2a send message is tracked n logs * rename tags * add streaming handlng * add a2a invocation * add a2a invocation i cost calc * test_a2a_logging_payload * update invoke_agent_a2a * test_invoke_agent_a2a_adds_litellm_data * add A2a agent |
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Lior Drihem
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62b84d6aad
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Prompt security litellm (#16365)
* add prompt security guardrails provider * cosmetic * small * add file sanitization and update context window * add pdf and OOXML files support * add system prompt support * add tests and documentation * remove print * fix PLR0915 Too many statements (96 > 50) * cosmetic * fix mypy error * Fix failed tests due to naming conflict of responses directory with same-named pip package * Fix mypy error: use 'aembedding' instead of 'embeddings' for async embedding call type * Fix: Install enterprise package into Poetry virtualenv for tests The GitHub Actions workflow was installing litellm-enterprise to system Python using 'python -m pip install -e .', but tests run in Poetry's virtualenv using 'poetry run pytest'. This caused ImportError for enterprise package types. Changed to 'poetry run pip install -e .' so the package is available in the same virtualenv where pytest executes. Fixes enterprise test collection errors in GitHub Actions CI. * Move Prompt Security guardrail tests to tests/test_litellm/ Per reviewer feedback, move test_prompt_security_guardrails.py from tests/guardrails_tests/ to tests/test_litellm/proxy/guardrails/ so it will be executed by GitHub Actions workflow test-litellm.yml. This ensures the Prompt Security integration tests run in CI. --------- Co-authored-by: Ori Tabac <oritabac@prompt.security> Co-authored-by: Vitaly Neyman <vitaly@prompt.security> |
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Ishaan Jaff
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21ba491656
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[UI] Add RunwayML on Admin UI supported models/providers (#16606)
* add runway.png * add gen4_turbo |
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Ishaan Jaffer
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4621a23a89 | add litellm logo jpg | ||
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Ishaan Jaff
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99feefd614
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[Feat] Add FAL AI Image Generations on LiteLLM (#16067)
* add fal-ai provider * fix image_generation_handler * init FalAIImageGenerationConfig * init cost_calculator * init FAL AI * TestFAL_AI_ImageGeneration * fix load_custom_provider_entrypoints * TestFAL_AI_ImageGeneration * add imagen4 transform FAL AI * add FAL AI imagen 4 transform * BaseImageGenTest * test_fal_ai_image_generation_basic * add BRIA + Recraft img gen * add recraft + BRIA * test_fal_ai_image_generation_basic * tests for flux PRO v11 * Add FAL AI SD * test FAL AI SD * docs FAL AI * docs fal ai * Using Model-Specific Parameters * add fal ai model prices * add fall_ai JPG logo * ui fixes FAL AI * fix linting * fix linting * fix bedrock test_get_request_body_stability3 * test_custom_llm_provider_entrypoint |
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Ishaan Jaff
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5de912375c
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[Feat] UI - Add logos for search providers (#15872)
* add LiteLLM_SearchToolsTable * init SearchToolRegistry * fix add SearchToolRegistry * fix add SearchToolRegistry * fix handling search tool management * fix search imports * fix registry * init search tools in memory * fix init tools in mem * fix TypedDict def * add new SCHEMA * bump proxy extras * add LiteLLM_SearchToolsTable_search_tool_name_key * bump extras with migration * fix working CRUD Ops * fix: _init_search_tools_in_db * add UI friendly name for search providers * add ui friendly name for search providers * add providers available * working layout * better layout * clean add search tool * update_router_search_tools * fix remove in memory registry, since router is in mem store * allow testing search tool connection * clean create search tool * add test_search_tool_connection * fix: _init_search_tools_in_db * add searchToolQueryCall * fix icon * clean tester * add parallel ai logo * add exa ai logo * add google PSE logo * add tavily logo * add dataforseo + perplexity * add parallel ai logo * UI show logos for search |
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Achintya Rajan
|
824517ee37 | updates guardrail provider logos | ||
|
Achintya Rajan
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e2f21beb7f | added Infinity as a provider in the UI | ||
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Ishaan Jaff
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60230e5666
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[Feat] UI - add snowflake on UI (#15083)
* UI - add snowflake on UI * fixes snowflake creds |
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Alexsander Hamir
|
8b9bd9bdb6
|
fix: added oracle to provider's list (#14835) | ||
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Ishaan Jaff
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32d87c242b
|
[Fixes] Using Qwen API Tiered Pricing (#14479)
* fix: use dashscope cost calc * add qwen logo |
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Ishaan Jaff
|
9750374081
|
[Feat] New LLM API - AI/ML API for Image Gen (#13893)
* add LlmProviders.AIML * add AIMLChatConfig * add aiml * fix AimlImageGenerationConfig * add AimlImageGenerationConfig * add cost_calculator * fixes for AI ML API * add known AIML Flux image models * add AIML Cost Calc * add AI/ML API * add aiml_models |
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|
Cherilyn Buren
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60db79583a
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[ui/dashboard] add support for host_vllm (#13885)
Signed-off-by: rentianyue-jk <rentianyue-jk@360shuke.com> |
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tanjiro
|
0af45206a3
|
Added Voyage, Jinai, Deepinfra and VolcEngine providers on the UI (#13131)
* added voyage and jinai and volcengine * deepinfra added and alphabetically ordered |
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Ishaan Jaff
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e5f0a8477b
|
[Feat] New Vector Store - PG Vector (#12667)
* add PGVectorStoreConfig * add PGVectorStoreConfig * test_environment_variable_support * fix code QA check * rename test * add PG vector img * allow adding vector stores * add pg vector * add vector store * TestPGVectorStoreConfig * TestPGVectorStoreConfig |
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Jorge Piedrahita Ortiz
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7fdecffc9f
|
style: update sambanova logos (#12431) | ||
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Ishaan Jaff
|
ca4d886cd0
|
[UI QA] 1.74.0.rc (#12348)
* fix alignment * fix msg * ui qa - use correct input type * fix logo * fix * fix preview * add PremiumLoggingSettingsProps * fix duration * fix img * fix img * ui new build |
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Ishaan Jaff
|
77741b7684
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[Feat] UI - Allow adding team specific logging callbacks (#12261)
* add arize logo * use correct struct * define dynamic params * add arize_space_id * update ui * ui - team logging |
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tanjiro
|
bbc1467d23
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Add logos to callback list (#12244)
* add logos to callback list * added logos * minor * cleanup console.log + remove unused functions + prettier * more cleanup * fix braintrust logo * minor |
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Ishaan Jaff
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ebf6395bc1
|
[Feat] Add Eleven Labs - Speech To Text Support on LiteLLM (#12119)
* add ELEVENLABS as a provider * add deepgram to main.py * add ElevenLabsException * add ElevenLabsAudioTranscriptionConfig * add transform_audio_transcription_response * TestElevenLabsAudioTranscription * add elevenlabs/scribe_v1 to model cost map * add ElevenLabsAudioTranscriptionConfig * add AudioTranscriptionRequestData * add ElevenLabs transform * use AudioTranscriptionRequestData * refactoring fixes * add ProcessedAudioFile util for reading audio files * test_elevenlabs_diarize_parameter_passthrough * docs eleven labs * docs fixes * fix code qa checks * fixes - audio transcription * ui - add ElevenLabs logo * add elevenlabs logo * docs - ElevenLabs * test fix elevenlabs |
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|
tanjiro
|
54b14ac631
|
enterprise feature preview improvement (#11715) | ||
|
Ishaan Jaff
|
52ef96261f
|
[UI] Add Deepgram provider to supported providers list and mappings (#11634)
* Add Deepgram provider to supported providers list and mappings * add logo * Add deepgram to model cost map * ui - require api key for deepgram * fix logo path --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> |
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Ishaan Jaff
|
c9ade3a3a2
|
[UI] Polish New MCP Server Add Form (#11604)
* fixes MCP new form * refactor existing logic * docs add MCP on ui |
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Ishaan Jaff
|
dc16e47df6
|
[UI] Allow adding Bedrock, Presidio, Lakera, AIM guardrails on UI (#10874)
* ui fix bedrock guard * polish: logo should appear after selecting provider * fix ui config bedrock * fix: refactor - use specific configs per provider * fix: refactor - use specific configs per provider * feat: ui, show provider specific params for guardrails * fix: updated type of LiteLLM params for guardrails * fix: updated type of LiteLLM params for guardrails * ui, use endpoint for adding presidio, bedrock guardrails * fix: linting error * add llama guard and secret detector on UI * add aim on ui * allow adding lakera AI on litellm ui * fix: fixes for params to init guardrails * test: test_guardrail_info_response * test: test_initialize_presidio_guardrail * fix: init guardrails * fix: init guardrails * add showSearch * working bedrock guard |
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Ishaan Jaff
|
ee1557afcd
|
[Feat] Add endpoints for adding, deleting, editing guardrails in DB (#10833)
* feat: add DB Add, Edit, Delete for Guardrails * feat: endpoints for guardrail management * add guardrail info helpers * add presidio logo * add createGuardrailCall |
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Ishaan Jaff
|
7c679abe85
|
ui - add nvidia triton models (#10456) | ||
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azdolinski
|
044508e075 | set_local_icons | ||
|
Krrish Dholakia
|
af8b35d556 | build(ui/litellm-dashboard): initial commit of litellm dashboard |