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Litellm oss 090626 (#30021)
* fix(mcp): report scoped server name during initialize (#29865) * fix mcp scoped server name * Update litellm/proxy/_experimental/mcp_server/mcp_context.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * test(mcp): cover scoped server name in the SSE initialize handler --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(ui): show all session logs in the drawer, not just the first 50 (#29795) * fix(ui): show newest session logs first * test(ui): keep session log pagination coverage * fix(ui): show all session logs in the drawer, not just the first page The session detail drawer fetched session logs via sessionSpendLogsCall without page/page_size, so it only ever received the backend default of one page (50 rows). Sessions with more than 50 calls had the rest unreachable in the UI (#29153). sessionSpendLogsCall now takes page/page_size, and the drawer fetches the first page, reads total_pages, then fetches the remaining pages and accumulates them before the existing client-side sort. This keeps the single continuous list (and the selected-log lookup and keyboard navigation, which all assume the full session) correct. Fetching is bounded by a page cap, and the sidebar shows a "showing most recent N" note if a session exceeds it. The rows are lightweight metadata (the endpoint excludes messages/response), so the full set is small; request/response bodies are still loaded per log on demand. * fix(ui): default session drawer to most recent log, newest first Open a session with its most recent log selected, and order the sidebar newest-first to match the all-sessions logs overview. MCP calls stay grouped last. The latest log by time is computed explicitly, since the MCP grouping means it is not always the first row. * Apply fetching pages in batches suggestion from @greptile-apps[bot] Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(ui): derive session total from accumulated rows when backend omits it Compute the session total after all pages are fetched, falling back to the accumulated row count rather than the first page's. Guards the truncation note against a backend response that omits total but spans multiple pages. --------- Co-authored-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(proxy): handle Mistral multipart passthrough (#29927) * fix(proxy): handle Mistral multipart passthrough * chore: satisfy passthrough ci formatting * test(proxy): cover Mistral passthrough in CI shard * fix(vertex_ai): use REP host for context caching on eu/us multi-region endpoints (#29573) Context caching built the cachedContents URL as https://{location}-aiplatform.googleapis.com, which is an invalid host for the eu/us multi-region endpoints and returns 404. The inference path already resolves these to the REP host (https://aiplatform.{geo}.rep.googleapis.com) via get_vertex_base_url(); reuse that helper in _get_token_and_url_context_caching so caching uses the same host as inference. Adds tests covering the eu/us multi-region cachedContents URLs (v1 and v1beta1). Fixes #29571 * Support per-model encrypted content affinity config (#29760) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix: propagate upstream status code in proxy API exception handler (#29402) * fix: propagate upstream status code in proxy API exception handler When Google GenAI / Vertex returns a 404 for deprecated or missing models via streamGenerateContent, the exception was falling through to a generic handler that defaulted to 500. Now provider exceptions carrying a valid HTTP status_code correctly propagate it through to the ProxyException. * fix: apply black formatting to common_request_processing.py * fix: tighten status code range to 400-599 and deduplicate ProxyException raise * fix(tests): use valid vertex_location in context caching tests Replace "test_location" (contains underscore) with "us-central1" so tests pass the regex validation added in get_vertex_base_url(). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(sdk): add xAI OAuth provider (#29866) * Add xAI OAuth provider * Update oauth.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * Fix xAI OAuth CI failures * Add xAI OAuth coverage tests * Move xAI OAuth coverage tests to core utils * Address xAI OAuth review comments * Prevent xAI OAuth api_base token exfiltration * Treat blank xAI OAuth api keys as absent * Wrap invalid xAI OAuth JSON responses * Use xAI OAuth behind explicit flag --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(proxy) #27734 allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update (#27751) * fix(proxy): allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update Fixes #27734 Sending null for budget_duration, team_member_budget, team_member_budget_duration, team_member_rpm_limit, or team_member_tpm_limit via /key/update or /team/update returned 200 OK but silently ignored the null value. The fields remained unchanged in the database. Root causes: - /key/update: prepare_key_update_data() popped budget_duration from the update dict but never re-added it (or budget_reset_at) when the value was None. - /team/update: _set_budget_reset_at() only acted when budget_duration was non-None, leaving a stale budget_reset_at in the DB. - /team/update: team_member_* null values bypassed the budget table update entirely because should_create_budget() requires at least one non-None field. * test(proxy): cover no-budget-row path in clear_team_member_budget_fields * fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes (#30028) * fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes When output_parse_pii=true on the Anthropic native path (anthropic/claude-*), response chunks arrive as raw bytes in SSE format. _stream_pii_unmasking was yielding those bytes unchanged, so <PERSON_1> tokens were never replaced with the original values before reaching the caller. Add _unmask_sse_bytes_chunk to parse each data: line, find content_block_delta / text_delta events, and apply _unmask_pii_text before re-encoding. Wire it into _stream_pii_unmasking so bytes chunks are unmasked when pii_tokens exist. * fix(presidio): handle CRLF line endings and non-ASCII PII in SSE unmask Strip trailing \r before the [DONE] guard so CRLF-terminated SSE chunks don't bypass it and silently swallow a JSONDecodeError. Add ensure_ascii=False to json.dumps so non-ASCII replacement values like accented names are preserved as UTF-8 on the wire rather than being \uXXXX-escaped. Add regression tests for both cases. * feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses) (#29925) * feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses) Bedrock Mantle serves the Responses API on two upstream paths: - gpt frontier models (gpt-5.5 / gpt-5.4) on /openai/v1/responses - every other Responses-capable model (e.g. gpt-oss) on the standard /v1/responses BedrockMantleResponsesAPIConfig gains a `use_openai_path` flag; the provider gate in utils.py picks the path per model: openai.gpt-* (non gpt-oss) -> /openai/v1/responses; any model declared mode=responses (price-map entry or user model_info) -> /v1/responses; everything else returns None and keeps the existing chat-completions emulation. Adds gpt-5.5 / gpt-5.4 price-map entries, registry wiring, and the routing-matrix tests. * feat(bedrock_mantle): data-driven frontier routing via use_openai_responses_path Addresses the Greptile review point that frontier detection should be a price-map field rather than a hardcoded name match. The gate now routes a model to /openai/v1/responses when its price-map entry declares use_openai_responses_path, so a frontier model whose name does not follow the openai.gpt- convention can be onboarded by JSON alone. The name-convention check is kept as a fallback that needs no price-map entry, which preserves zero-change routing for a future gpt-6 before its entry loads. gpt-5.5 / gpt-5.4 get the flag in both price maps. Adds tests for the data-driven flag path and for the flag presence on the gpt-5.x entries; both branches are mutation-tested. * test(model_prices): allow use_openai_responses_path in price-map schema The model_prices_and_context_window.json schema validator (test_aaamodel_prices_and_context_window_json_is_valid) enforces additionalProperties: false, so the new use_openai_responses_path flag on the gpt-5.5 / gpt-5.4 entries failed validation. Add it to the schema as a boolean, alongside the other supports_* / capability flags. * Add Tensormesh serverless models to the model cost map (#30037) * Add Tensormesh serverless models to the model cost map * Flag reasoning support on the Tensormesh models that expose thinking mode * fix(proxy): invalidate stale key spend counter after budget reset or manual spend update (#30001) * fix(proxy): reconcile stale key spend counter after budget reset * fix(proxy): invalidate stale key spend counter after budget reset or manual spend update * fix(proxy): remove read-time stale counter reconciliation to prevent budget bypass * revert: undo unrelated formatting changes in enterprise directory * test(proxy): add unit test for key spend update invalidating counter * test(proxy): fix mocked update_data and hash token expectations in unit test * fix(proxy): use Responses-API transformer in pass-through cost tracking (#29728) The `elif is_responses:` branch of `openai_passthrough_handler` was calling the chat-completions `transform_response` on a Responses API payload. The chat-completions transformer expects `choices: [...]` in the raw response; the Responses API uses `output: [...]` and `usage.input_tokens` / `usage.output_tokens` (not `prompt_tokens` / `completion_tokens`). The result was a KeyError 'choices' deep inside `convert_to_model_response_object`, swallowed by the surrounding `except Exception` in the handler, and the SpendLogs row was written by the fallback path with zeroed-out tokens, spend, and model. This bug silently undercounts cost for every successful pass-through call to either OpenAI's `/v1/responses` or Azure's `/openai/v1/responses` (deployments configured for the Responses API). Reproduced 2026-06-04 against a real Azure OpenAI Responses API deployment proxied through LiteLLM v1.88.0. Fix: use the dedicated `OpenAIResponsesAPIConfig.transform_response_api_response` for the Responses branch. This transformer already exists in LiteLLM (`litellm/llms/openai/responses/transformation.py`) and knows the Responses-API on-the-wire shape. `litellm.completion_cost` already handles `ResponsesAPIResponse` natively with `call_type="responses"`, so no downstream changes are needed. Tests: test_responses_api_uses_responses_transformer_not_chat_completions NEW. Real regression test — exercises the openai_passthrough_handler with a real-shaped Responses payload (no `choices`, has `output` and Responses-API `usage` keys) and NO mocked `get_provider_config`. Pre-fix: raises KeyError 'choices' inside the chat-completions transformer (the bug). Post-fix: returns a ResponsesAPIResponse, completion_cost is called with call_type="responses" and a ResponsesAPIResponse instance (asserted). Verified to fail on un-fixed handler + pass on fixed handler before commit. test_responses_api_cost_tracking UPDATED. Old test mocked `get_provider_config` (no longer called in the responses branch post-fix). Now mocks the Responses transformer directly (`OpenAIResponsesAPIConfig.transform_response_api_response`) to test the downstream cost-calc contract. Out of scope for this PR (separate followup): - Recognizing *.cognitiveservices.azure.com (the newer Azure OpenAI hostname) in the is_openai_*_route checks. Separate PR. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(skills): execute DB skills by matching the litellm_skill_ tool name prefix (#30116) Skill IDs are generated as litellm_skill_<uuid> and the model-facing tool name is the sanitized skill ID, but the post-call execution gates in SkillsInjectionHook only ran tools whose name starts with "skill_", so DB skills were silently returned to the client as raw tool calls. Fixes #28122. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(anthropic): synthesize content_block_start when Responses stream omits output_item.added (#30115) * fix(team): reserve team budget raises for proxy admins on /team/update (#30030) The caller's PERSONAL max_budget was the wrong yardstick for /team/update: a team's spend ceiling has nothing to do with the admin's own key budget. That comparison was an unintended side effect of reusing _check_user_team_limits() (which exists for the /team/new path) and broke the UI, which re-sends the unchanged budget on every save. New behavior on /team/update for standalone teams: - A team admin (already authorized via _verify_team_access) may freely KEEP or LOWER the team budget, and change models/tpm/rpm, without being gated by their personal limits. - GROWING a team's spend ceiling is a budget-authority action reserved for proxy admins -> 403 for team admins. "Growing" covers both raising max_budget above the team's current finite value and removing the cap entirely (max_budget=null, detected via model_fields_set so an explicit null is distinguished from an omitted field). For a team that currently has no cap, setting a finite value is a restriction and is allowed. - Org-scoped teams remain governed by _check_org_team_limits() (capped by the org budget). Also reverts the #29525 existing_team_max_budget workaround in _check_user_team_limits() back to the create-only form; /team/new still enforces the creator's personal caps. docs(access_control): resolve the contradiction in the team-admin section — team admins can keep/lower the budget and manage rate limits/models, but cannot raise the team budget (proxy-admin only). tests: unit + behavior coverage for raise-blocked, cap-removal-blocked (team admin), raise/removal allowed (proxy admin), uncapped-team restriction allowed, keep/lower/resend allowed, and unchanged create-path guards. Co-authored-by: Cursor <cursoragent@cursor.com> * test(ui): data-driven App Router migration E2E smoke (default + server-root-path) (#29974) * test(ui): add a data-driven App Router migration E2E smoke Add a growing Playwright smoke for migrated pages: for each segment it deep-links to the path route, asserts the URL and that the dashboard shell rendered, then clicks off to a legacy page and asserts navigation still works. Driven by e2e_tests/fixtures/migratedPages.ts, so adding a page is one line. Runs in two situations against the same proxy: the default mount (npm run e2e:migration) and a non-root SERVER_ROOT_PATH mount (npm run e2e:migration:root). globalSetup now logs in at `${SERVER_ROOT_PATH}/ui/login` so the admin storage state is valid under a prefix. Seeded with api-reference; append the rest as their migrations merge. * test(ui): support headed slow-motion + watch pauses in the migration smoke Honor SLOWMO in the server-root-path config (the default config already did), and add an env-gated E2E_WATCH_MS pause so a headed run lingers on each state. Both are no-ops by default, so CI behavior is unchanged. * test(ui): make the migration smoke a sidebar-click user journey Rework the smoke from deep-linking to a real navigation journey: start at the landing page, click the migrated page in the sidebar (expanding submenus for nested items), assert the path route rendered, reload it (the check a wrong server_root_path breaks), bounce to a legacy page and back, and — once two pages are migrated — navigate directly between two migrated pages. Verifies via URL + shell render, driven by the same fixture list. * test(ui): address review on the migration smoke Escape ROOT and segment before interpolating them into RegExp URL matchers so a future segment containing regex metacharacters can't silently widen the match. Make the server-root-path config fail fast when SERVER_ROOT_PATH is unset instead of silently re-running the default mount and passing without exercising the prefix. * test(ui): drop unused watch helper and fix stale smoke README * test(ui): run the migration smoke under a server root path in CI * test(ui): harden + instrument the server-root-path proxy reboot in CI * test(ui): run the server-root-path migration smoke as its own CI job Replace the in-place proxy reboot in e2e_ui_testing with a dedicated e2e_ui_testing_server_root_path job that boots the proxy once with SERVER_ROOT_PATH=/litellm, matching how every other proxy variant in the config gets its own job rather than killing and relaunching the live proxy. The reboot was failing deterministically: after pkill -9 and relaunch the prefixed proxy never came back up on :4000 (connection refused), so the smoke never ran. The readiness step that was supposed to surface the cause could never reach its boot-log tail because CircleCI runs steps under bash -eo pipefail and the preceding `curl -sv ... | tail` aborted the step with curl's exit 7. Booting the proxy as the job's own background step lets any boot crash land in that step's log instead of being swallowed. The default e2e_ui_testing job is unchanged aside from dropping the reboot, prefixed-readiness, and prefixed-smoke steps; the migration smoke still runs at the root mount there via the default Playwright config. * fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through (#24232) * fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through * test: mock post_call_response_headers_hook in audio speech route tests * chore(ui): remove dead App Router route stubs under (dashboard) (#30045) models-and-endpoints, organizations, and virtual-keys each had a page.tsx route under (dashboard)/ that is not in MIGRATED_PAGES, so the sidebar and deep links never resolve to it and the route is unreachable. Each was a thin wrapper that handed the shared view empty or no-op props (empty modelData with a no-op setModelData, hardcoded empty organizations, no-op setUserRole/setUserEmail), so reaching one would render a degraded page in any case. The real wrapper belongs in the PR that flips each page into MIGRATED_PAGES, written with eyes on it and a test This continues the dead-scaffolding cleanup from #28891. The shared components these wrappers rendered (ModelsAndEndpointsView, OrganizationFilters) stay, since the legacy ?page= switch in app/page.tsx and src/components still import them * fix(ui/mcp): reset OAuth state on create-server modal close so a prior server's token no longer leaks into the next add-server session (#30000) * fix(ui/mcp): reset OAuth hook state on modal close so a prior server's token no longer leaks into the next add-server session * fix(ui/mcp): clear in-flight OAuth guard on reset and reset form/tools on modal close so nothing leaks on a parent-driven dismiss * fix(mcp): allow team access-group grants in OAuth authorize/token access check (#30041) * fix(mcp): honor team access-group grants in OAuth authorize/token access check * test(mcp): mock build_effective_auth_contexts in non-admin authorize tests for isolation * docs(security): require a reproduction video for vulnerability reports (#30048) (#30063) With AI models capable of automated vulnerability discovery now publicly available, we expect a large increase in report volume, much of it unverified. Requiring a video of the exploit running against a live instance raises the bar for submissions and keeps triage focused on reproducible issues. Reports without a video will be closed and reopened if one is added later. Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com> * feat(ui): add admin flag to disable in-product UI nudges for everyone (#29796) * feat(ui): add admin flag to disable in-product UI nudges for everyone Admins can now suppress the survey and Claude Code feedback popups for all users via a single disable_ui_nudges UI setting, instead of relying on each user dismissing them individually. * fix(ui): suppress nudges while ui settings are loading Gate nudgesDisabled on the ui-settings loading state so an admin with disable_ui_nudges on doesn't see the survey prompt flash, and the getInProductNudgesCall fetch doesn't fire, on a cold page load before the flag resolves. Falls back to showing nudges if the fetch errors. * test(ui): wrap CreateKeyPage test in QueryClientProvider page.tsx now calls useUISettings (react-query), which needs a QueryClient that layout.tsx supplies in production but the test did not. Add the provider and mock getUiSettings so the query resolves. * chore(ui): remove dead dashboard files and unused dependencies (#30047) * chore(ui): remove dead dashboard files and unused dependencies knip flagged seven orphaned source/config files with no importers and five declared dependencies that nothing in the tree uses. Removing them shrinks the dashboard bundle's source surface and keeps the manifest honest; vite stays installed transitively via vitest, so test tooling is unaffected. * fix(ci): restore serverRootPath.config.ts referenced by SERVER_ROOT_PATH workflow The dead-code sweep removed e2e_tests/serverRootPath.config.ts, but its spec (tests/login/serverRootPathRedirect.spec.ts) and the test_server_root_path.yml workflow step still depend on it, so the redirect e2e job failed to load a config that no longer existed. * fix(proxy): authorize batch files using upload target_model_names (LIT-3593) (#30009) * fix(proxy): authorize batch files using upload target_model_names (LIT-3593) After replace_model_in_jsonl, body.model is a stripped provider id. Reverse-mapping it via resolve_model_name_from_model_id is first-match on model_list and caused false 403s when multiple deployments share the same stripped name. Use target_model_names from the unified file id instead. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593) Restores the reverse-lookup for the JSONL body.model fallback path so that legacy/pre-target_model_names managed files still map stripped provider IDs back to proxy aliases before auth. Also cleans up redundant `or None`. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Revert "fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)" This reverts commit |
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Gemini managed agents support (#28270)
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* Add support for environment variable in interactions api * Add sdk support for gemini create agent * Add agents endpoint support via proxy * Add outputs of each api * Add routing for model and agents param * Remove redundant condition in get_provider_agents_api_config LlmProviders.GEMINI.value is literally the string "gemini", so the second clause of the or was checking the exact same thing as the first. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix: forward query-param credentials to list/get/delete/versions Gemini agent endpoints The list_gemini_agents, get_gemini_agent, delete_gemini_agent, and list_gemini_agent_versions endpoints previously constructed a hardcoded data dict with no mechanism to pass provider credentials. Unlike create_gemini_agent (POST, reads litellm_params_template from body), these GET/DELETE endpoints gave no way for multi-tenant callers to supply a per-request api_key or other LiteLLM params. Fix: - Add _merge_query_params_into_data() helper that reads query parameters from the request and merges them into the data dict without overwriting already-set keys (e.g. path params like 'name'). - Support a JSON-encoded litellm_params_template query parameter (matching the POST body pattern) as well as flat key=value pairs (e.g. api_key=AIza...). - Apply the helper in all four affected endpoints. - Add 13 unit tests covering the helper and each endpoint. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix: pass model=None for managed agent proxy endpoints to prevent agent name polluting data["model"] Endpoints acreate_agent, aget_agent, adelete_agent, and alist_agent_versions were passing model=<agent_name> to base_process_llm_request. This caused common_processing_pre_call_logic to write the agent name into self.data["model"], which then triggered spurious model-alias mapping, rate-limiting lookups, and logging tied to a non-existent model deployment. The agent name is already carried in data["name"] and is passed correctly to the SDK functions (litellm.interactions.agents.*). There is no reason to also set model=<agent_name>; the correct value is model=None for all five managed-agent management routes. Adds tests/test_litellm/proxy/google_endpoints/test_managed_agents_model_param.py to verify all five managed-agent endpoints pass model=None. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix: address greptile P1/P2 review comments P1 (router.py): Restore fallback/retry support for acreate_interaction and create_interaction. Both were silently moved to _init_interactions_api_endpoints (direct call, no fallbacks). Moved them back to _ageneric_api_call_with_fallbacks so users with configured fallback models keep retry behaviour. P1 security (agents_endpoints.py): Remove flat query-param credential path (e.g. ?api_key=AIza...) from _merge_query_params_into_data. Credentials in URL query strings appear verbatim in server access logs, CDN edge logs, and browser history. Only the JSON-encoded litellm_params_template query param (matching the POST body pattern) is retained. P2 (interactions/http_handler.py): Extract _BaseHTTPHandler with shared _handle_error, _sync_client, and _async_client helpers. InteractionsHTTPHandler now extends _BaseHTTPHandler. The _async_client reads the provider from litellm_params instead of hardcoding GEMINI. P2 (interactions/agents/http_handler.py): AgentsHTTPHandler now extends InteractionsHTTPHandler (which inherits _BaseHTTPHandler) so all shared HTTP infrastructure is reused rather than duplicated. Removes the hardcoded LlmProviders.GEMINI from the async client path. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: address CI failures from greptile review fixes - black: format interactions/agents/main.py and utils.py - tests: update test_gemini_agents_endpoints.py to match new _merge_query_params_into_data behaviour (flat credential params are rejected; only JSON-encoded litellm_params_template is accepted) - ci: add test_gemini_agents_endpoints.py to endpoints-and-responses shard in test-unit-proxy-db.yml so assert-shard-coverage passes - tests: add _initialize_managed_agents_endpoints and _init_managed_agents_api_endpoints test coverage so router_code_coverage passes; also fix TestRouterCreateInteractionRouting to reflect that acreate_interaction now correctly routes through _ageneric_api_call_with_fallbacks (restoring fallback support) Co-authored-by: Cursor <cursoragent@cursor.com> * fix: remove InteractionsHTTPHandler._handle_error override to fix type errors AgentsHTTPHandler extends InteractionsHTTPHandler and calls self._handle_error(provider_config=agents_api_config) where agents_api_config is BaseAgentsAPIConfig. Python MRO resolved _handle_error to InteractionsHTTPHandler._handle_error which expected BaseInteractionsAPIConfig, causing 10 mypy arg-type errors in interactions/agents/http_handler.py. Removing the redundant override lets both classes inherit _BaseHTTPHandler._handle_error (provider_config: Any) which is structurally correct for both config types. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: agent-only interactions and managed agents provider routing Resolve None custom_llm_provider in agents HTTP client lookup and set custom_llm_provider on GenericLiteLLMParams for all agent CRUD paths. Stop mapping agent names to proxy model routing; route interactions through _init_interactions_api_endpoints with fallbacks only when model is set. Consolidate duplicate router elif branches for interaction APIs. Co-authored-by: Cursor <cursoragent@cursor.com> * Fix greptile review * test(agents): add unit tests for managed agents SDK and HTTP handler Adds coverage for the new `litellm.interactions.agents` surface area: - main.py: sync/async entry points (create/list/get/delete/list_versions), provider config lookup, logging-obj helper, async error wrapping - http_handler.py: every CRUD method (sync + async paths), `_is_async` dispatch branches, and provider error mapping through GeminiAgentsConfig - utils.py: get_provider_agents_api_config for supported / unsupported providers Brings patch coverage on these files from <25% to ~100% so codecov/patch is satisfied. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * docs(gemini-agents): fix misleading credential-passing examples in GET/DELETE docstrings (#28293) The four GET/DELETE endpoint docstrings (list_gemini_agents, get_gemini_agent, delete_gemini_agent, list_gemini_agent_versions) documented passing per-request credentials as flat query parameters (e.g. ?api_key=AIza...). However, _merge_query_params_into_data only reads the JSON-encoded litellm_params_template query parameter and intentionally ignores flat params (URL query strings appear verbatim in access logs, browser history, and Referer headers). Callers following the documented curl examples would have their credentials silently dropped and hit auth failures against Gemini. Update the examples to use the supported JSON-encoded litellm_params_template query parameter, matching _merge_query_params_into_data's own docstring. Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * refactor(agents): rename provider-agnostic agent response types Move GeminiAgent{ListResponse,DeleteResult,VersionsResponse} to provider-neutral names (AgentListResponse, AgentDeleteResult, AgentVersionsResponse) so the BaseAgentsAPIConfig interface no longer references Gemini-specific type names. * fix(gemini-agents): close veria-flagged credential-escalation gaps Two high-severity findings from the veria-ai PR review are addressed: 1. **api_base override could leak the shared Gemini key** GeminiAgentsConfig.validate_environment falls back to GOOGLE_API_KEY / GEMINI_API_KEY when no api_key is supplied. Combined with caller-controlled api_base on the proxy CRUD endpoints, an authenticated user could redirect the outbound request to an attacker-controlled host and capture the operator's shared Gemini key from the x-goog-api-key header. The config now refuses env-fallback whenever api_base is explicitly overridden. 2. **Managed-agent CRUD exposed to ordinary LLM keys** The new /v1beta/agents routes live in google_routes (i.e. llm_api_routes), so any non-admin LLM key can reach them. Unlike /v1beta/models/...: generateContent these endpoints are NOT model-routed and have no model_list-supplied credentials, so env-fallback would let any LLM key list / create / delete agents inside the operator's Gemini project. Each endpoint now calls _enforce_caller_supplied_provider_key, which requires non-admin callers to supply their own Gemini api_key via litellm_params_template. Proxy admins keep the env-fallback convenience. Tests cover non-admin rejection, admin allow-through, the api_base override guard, and SDK env-fallback when api_base is not overridden. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(router): restore strict assert_called_once_with on interactions default-provider test --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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2e5ebf826f
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fix(responses): register cooldowns on failure + fail fast on stale encrypted_content (#27820) | ||
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40db114a23
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fix(router): accept Pydantic LiteLLM_Params in encryption-boundary key lookup
Greptile flagged that the strict isinstance(dict) guard in
_encryption_boundary_key would silently return None for any non-dict input,
including a LiteLLM_Params Pydantic instance, which exposes a custom .get()
method and is intended to be used dict-style in some router paths. If such
an instance ever flowed into healthy_deployments, the guard would drop every
candidate from boundary matching and fall through to the full deployment
pool, i.e. trigger the exact invalid_encrypted_content failure this check
exists to prevent.
Loosen the guard to accept any object exposing a callable .get(): plain
dicts (the common case) and LiteLLM_Params-style Pydantic instances. The
function still returns None for non-dict-like values (None, lists, strings,
ints, bare objects).
Adds regression tests covering:
- LiteLLM_Params Pydantic instance resolves to the same boundary tuple as
an equivalent plain dict
- non-dict-like values and dicts missing required fields still return None
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f3b8aad883
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fix(router): pin Responses API affinity to Azure resource on model-group switch
When a Responses API follow-up switches model_name (e.g. gpt-5.3-codex -> gpt-5.4, or to a LiteLLM-side alias of the same Azure deployment), the router has already filtered healthy_deployments to the new group, so the originating model_id is no longer present. The encrypted_content_affinity check would log "decoded deployment not found" and fall back to the full deployment pool, where simple-shuffle could land on a different Azure resource and trip a 400 invalid_encrypted_content. Fall back to pinning by the originating deployment's encryption boundary (api_base + api_key) when the model_id miss is across model groups. The encrypted_content travels with the Azure resource, not the model_name, so any deployment on the same resource accepts it. LIT-2531 |
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860f6b526e
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Merge branch 'litellm_internal_staging' into litellm_access-group-routing-fix | ||
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e72eac9176
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Fix add_model_file_id_mappings when router returns single deployment dict
When model_info.id equals model_name (common for batch models), the router resolves via has_model_id and returns one deployment dict instead of a list. The dict branch incorrectly iterated deployment keys (model_name, litellm_params, model_info), producing non-string values that broke LiteLLM_ManagedFileTable validation on managed file upload. Normalize list vs dict by wrapping single deployments and extracting model_info.id for each response pair. Add regression tests including the batch model id == model_name case. Made-with: Cursor |
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a3da4721ca
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test(router): add coverage for access-group deployment filter
Add a router utils unit test that directly exercises _filter_deployments_by_model_access_groups for access-group-only key permissions. Made-with: Cursor |
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e8461b5b97
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style: run black formatter on files from main merge | ||
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3a4ed48f54
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fix(router): don't create litellm_metadata for non-Responses API calls in encrypted_content_affinity_check (#25347)
Using setdefault('litellm_metadata', {}) unconditionally created an empty
litellm_metadata key for chat completions and embeddings. This caused
_get_metadata_variable_name_from_kwargs to return 'litellm_metadata' instead
of 'metadata', so tag-based routing looked for tags in the wrong dict and
ignored all tag filters.
Fix: only set the encrypted_content_affinity_enabled flag when litellm_metadata
already exists (Responses API path). Chat completions and embeddings never have
this key, so nothing is created and tag routing works correctly.
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51876292a0
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Litellm ishaan april4 2 (#25150)
* feat(router): integrate allowed_fails_policy into health check failures (#24988) * feat(router): integrate allowed_fails_policy into health check failures Health check failures now increment the same per-deployment failure counters used by allowed_fails_policy, so users can control how many health check failures of each error type are required before a deployment enters cooldown. - ahealth_check() preserves the original exception in its return dict - run_with_timeout() returns a litellm.Timeout on health check timeout - _perform_health_check() propagates exceptions to unhealthy endpoints - _write_health_state_to_router_cache() calls _set_cooldown_deployments for each unhealthy endpoint that has an exception - When allowed_fails_policy is set, the binary health check filter is bypassed so cooldown is the sole routing exclusion mechanism - Safety net: if all deployments are in cooldown with enable_health_check_routing=True, the cooldown filter is bypassed Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(router): add health_check_ignore_transient_errors flag When enabled, health check failures with 429 (rate limit) or 408 (timeout) status codes are skipped from the cooldown pipeline. These are transient load issues, not broken deployments. Auth errors (401), 404, and 5xx errors still increment counters and trigger cooldown as before. Config (general_settings): health_check_ignore_transient_errors: true Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(router): also exclude 429/408 from health state cache when ignore_transient_errors set The previous fix only skipped cooldown counter increments. The health state cache was still marking 429/408 endpoints as is_healthy=False, causing the binary health check filter to exclude them from routing. Now, when health_check_ignore_transient_errors=True, 429/408 endpoints are also excluded from the unhealthy list passed to build_deployment_health_states(), so the binary filter treats them as unaffected (not unhealthy). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs(router): add health check driven routing guide New standalone page covering the full health check routing feature: allowed_fails_policy integration, health_check_ignore_transient_errors, architecture SVG, step-by-step setup, and gotchas (TTL, AllowedFails semantics). Replaces the inline section in health.md with a link to the new page. Added to the Routing & Load Balancing sidebar. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(health-check-routing): fix three CI failures - Add "exception" to ILLEGAL_DISPLAY_PARAMS in health_check.py so the exception object is stripped before the health endpoint serializes results to JSON (fixes TypeError: 'URL' object is not iterable) - Add allowed_fails_policy = None to FakeRouter stubs in test_router_health_check_routing.py (fixes AttributeError) - Add health_check_ignore_transient_errors to config_settings.md router settings reference table (fixes documentation test) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Fix litellm/tests/proxy_unit_tests/test_proxy_server.py * fix(router): address greptile review comments - Narrow cooldown safety-net bypass: only fires when allowed_fails_policy is set (cooldown is health-check driven). Without a policy, cooldowns are from real request failures and must not be bypassed. - Restore cooldown deployments DEBUG log that was accidentally removed. - Fix test_health TypeError: move exception extraction to a separate exceptions_by_model_id dict returned alongside endpoints, so exception objects never appear in the endpoint dicts that get JSON-serialized by the /health response. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(health-check-routing): properly isolate exceptions from health response Return exceptions_by_model_id as a separate third value from _perform_health_check / perform_health_check so exception objects (which contain non-JSON-serializable httpx URL types) never appear in the endpoint dicts that get serialized by the /health response. Callers updated: _health_endpoints.py, shared_health_check_manager.py, proxy_server.py background loop. All use the exceptions dict only for cooldown integration, not for display. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(shared-health-check): fix remaining 2-value return sites and update type annotation * fix(health-check-routing): fix P0 cooldown integration never firing The cooldown loop was reading endpoint.get("exception") which is always None because exceptions are now returned via exceptions_by_model_id, not stored in endpoint dicts. Fixed to use _exceptions.get(model_id). Also fixes the transient-error filter to use _exceptions instead of endpoint.get("exception"), and fixes all remaining 2-value return sites in shared_health_check_manager.py. Tests updated to pass exceptions via exceptions_by_model_id parameter instead of endpoint dicts. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(health-check-routing): fix P1 transient-error filter broken on cache hits When SharedHealthCheckManager returns cached results, exceptions_by_model_id is always {} so the transient-error filter defaulted to status 500 for all endpoints, incorrectly marking 429/408 endpoints as unhealthy. Fix: store integer exception_status on each unhealthy endpoint dict in _perform_health_check. _get_endpoint_exception_status() uses the live exception object when available (direct path) and falls back to the stored integer (cache-hit path). The integer is JSON-serializable and survives the shared cache round-trip. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(health-check-routing): gate cooldown loop behind allowed_fails_policy Without the policy, cooldown is not the routing exclusion mechanism. Firing _set_cooldown_deployments for all enable_health_check_routing users was a backwards-incompatible change — 401s would immediately cooldown deployments that the binary filter would have recovered on the next cycle. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * revert: undo allowed_fails_policy gate on cooldown loop Cooldown integration via health checks is intentional for all enable_health_check_routing users, not just those with allowed_fails_policy. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(docs+tests): fix health_check_ignore_transient_errors doc section and test coverage - Move health_check_ignore_transient_errors from router_settings to general_settings in config_settings.md (code reads it from general_settings) - Remove duplicate enable_health_check_routing / health_check_staleness_threshold entries that were incorrectly listed under router_settings - Replace TestHealthCheckEndpointExceptionPropagation tests with ones that exercise the real _perform_health_check code path via mocked ahealth_check, verifying exceptions appear in exceptions_by_model_id and NOT in endpoint dicts Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(tests+docs): fix tuple unpacking and docs test failures - Update test mocks that return (healthy, unhealthy) to return (healthy, unhealthy, {}) to match the new 3-value signature - Update test unpackings of perform_shared_health_check to use healthy, unhealthy, _ = ... - Add health_check_ignore_transient_errors to router_settings section in config_settings.md (it is a Router constructor param, so the doc test requires it there; it also lives in general_settings for proxy use) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Fix CodeQL errors * fix(tests): fix 2-value unpackings of _perform_health_check in test_health_check.py * fix(tests): fix mock _perform_health_check returning 2-tuple instead of 3 * fix team routing --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: add distributed lock for key rotation job (#23364) * fix: add distributed lock for key rotation job * fix: address Greptile review feedback on key rotation lock (#23834) * fix: address Greptile review feedback on key rotation lock * fix req changes greptile * feat(proxy): Optional on_error for guardrail pipeline (API / technical failures) (#24831) * guardrails fallback * docs * docs: add LITELLM_KEY_ROTATION_LOCK_TTL_SECONDS to environment variables reference * fix(mypy): accept Union[Dict, Any] in _get_deployment_order and use typed list to fix min() type error * fix(mypy): use Optional[str] for api_base in PydanticAI provider to match superclass signature --------- Co-authored-by: Sameer Kankute <sameer@berri.ai> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Harshit Jain <48647625+Harshit28j@users.noreply.github.com> Co-authored-by: Shivam Rawat <shivam@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> |
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fc32f91ffd
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[Fix] Rename test file so router code coverage check detects it
The router_code_coverage.py script only scans test files with "router" in the filename. test_health_check_routing.py was invisible to this check, causing _async_filter_health_check_unhealthy_deployments and _filter_health_check_unhealthy_deployments to appear untested. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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7675488640
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feat(router): add health-check-driven routing behind opt-in flag
Background health checks now feed deployment health state into the router candidate-filtering pipeline. Unhealthy deployments are excluded proactively instead of waiting for request failures to trigger cooldown. Gated by `enable_health_check_routing: true` in general_settings. Off by default — zero behavior change for existing users. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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528daa8cf4 |
feat(router): add per-model-group deployment affinity configuration
Enable deployment_affinity, responses_api_deployment_check, and session_affinity to be configured per model group via router_settings.model_group_affinity_config, falling back to global settings for unconfigured groups. - Add model_group_affinity_config parameter to Router and DeploymentAffinityCheck - Add _get_effective_flags helper to resolve flags per model group - Update async_filter_deployments and async_pre_call_deployment_hook to use per-group config - Add 4 comprehensive tests covering per-group config, fallback, and override scenarios This allows fine-grained control of affinity behavior across model groups, e.g., enabling stickiness only for cross-provider deployments while leaving other groups free to load-balance. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com> |
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1092c17468 |
Fix flaky encrypted_content_affinity tests: mock at handler level
The 4 integration tests were flaky in CI because the AsyncHTTPHandler.post mock was bypassed when aiohttp transport is used. Mock at the higher BaseLLMHTTPHandler.async_response_api_handler level instead, which bypasses the HTTP layer entirely while still exercising router deployment selection, pre-call checks, and response post-processing (item ID rewriting). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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67e905f0d0 |
Fix flaky encrypted_content_affinity tests: clear HTTP client cache, disable retries
Tests failed intermittently in CI (-n 8 workers) because cached AsyncHTTPHandler instances from other tests bypassed the class-level mock on AsyncHTTPHandler.post, causing real requests to OpenAI with mock API keys. Router retries (default 2) masked the root cause. - Add autouse fixture to flush litellm.in_memory_llm_clients_cache before/after each test so mocks always apply to fresh clients - Set num_retries=0 on all Router instances to surface mock failures immediately instead of silently retrying Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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521f804350 | Fix encrypted content streaming affinity issue | ||
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2bc4da76ce | Update the tests | ||
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18bf3f2df6 | Fix mock github test | ||
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a88a17796b | Fix logging and encrypted content extraction | ||
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9f627c67d8 | Add tests for encrypted_content_affinity | ||
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394c49d303 | Add tests for encrypted_content_affinity | ||
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7cda0e4edd | Fix code qa | ||
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456d8f5524 | feat: add session_id to have better routing | ||
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3dd55a7b61 | Merge main into affinity_callback and address deployment affinity review feedback | ||
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f7726c8950 | Fix wrong keys being used for model sticky entry | ||
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059e75ad88 |
fix(router): scope deployment affinity by model_map_key
- Key affinity by (user_api_key_hash, model_map_key) -> model_id - Ignore OpenAI 'user' param for affinity - Avoid double hashing user_api_key_hash - Add unit tests + docs clarifications |
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e23bd21a28 | Add deployment affinity routing | ||
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539f629eff
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[Feat] New Logging Integration - Azure Sentinel Logger (#18146)
* add AzureSentinelLogger * logging: AzureSentinelLogger * test_azure_sentinel_signature_and_send_batch * docs azure sentinel * fix AzureSentinelLogger * test fix * docs fix * fix: AzureSentinelLogger * docs sentintel * feat: add example SLP * docs sentinel * docs fix * docs fix * docs fix * fix code qa * QA fix * fix test * TestInitializeInteractionsEndpoints |
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7c2e2111c0
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fix(router): handle tools=None in filter_web_search_deployments (#17684)
Fixes #17672 Changed `request_kwargs.get("tools", [])` to `request_kwargs.get("tools") or []` to handle the case where tools is explicitly set to None. |
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72eb4c3a1c
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🆕 feat: support routing to only websearch supported deployments (#17500)
* support routing to only websearch supported deployments * add docs |
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f804ab6de5
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Add LLM provider response headers to Responses API (#16091)
* Add llm headers to responses api * fix mock test |
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d89a2a0797 | test | ||
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c168fff38a | test_cooldown_badrequest_error | ||
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7054067238 | test_cooldown_handlers.py | ||
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3b52545db3
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Merge pull request #13529 from BerriAI/litellm_dev_08_11_2025_p1
[Fix] Cooldowns - don't return raw Azure Exceptions to client |
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76f1064229
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[Bug Fix] litellm incompatible with newest release of openAI v1.100.0 (#13728)
* fix imports OpenAI SDK * ResponseText fixes * fixes ResponseText * fix imports * catch AttributeError * fix import * use openai==1.100.1 * fix build from PIP * fix lint test * Print OpenAI version * fix Install dependencies |
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bc9d0484e4 |
fix(cooldown_cache.py): mask error string to avoid leaking sensitive prompt data
Fixes https://github.com/BerriAI/litellm/issues/13329 |
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39955129f5
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fix mapped tests (#12320)
* fix - use flush llm client cache
* faster mapped tests
* test_async_multiple_response_ids_routing
* fix tests
* test_ateam_member_update_admin_requires_premium
* regular mapped tests
* Revert "Fix: Initialize JSON logging for all loggers when JSON_LOGS=True (#12206)"
This reverts commit
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1a7fd1d1c7
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Litellm dev 06 25 2025 p2 (#12049)
* test(test_router.py): initial unit test confirming router.afile_content uses dynamic api key / api base * fix(managed_files.py): filter deployments for only those within file id mapping ensure call works - only route to models where the file was written * fix(proxy_server.py): fix loading in model ids from config, if config id is int * fix(router.py): return all model file id mappings on create_file if multiple deployments - this ensures all the file id mappings are bubbled up Fixes issue when trying to use loadbalanced deployments - only 1 file id mapping was being stored * feat(router_utils/common_utils.py): filter models by team id when selecting for routing Prevents team only models from being used by other teams * fix(common_utils.py): additional fixes around filtering team-based models * fix(batches_endpoints/endpoints): support list batches with target model names specified * fix(common_utils.py): more testing for team deployment filters |
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ef42461c1e
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Litellm fix GitHub action testing (#11163)
* test: add __init__.py files * refactor: rename test folder to avoid naming conflict * test: update workflows * test: update tests * test: update imports * test: update tests * test: remove unused import * ci(test-litellm.yml): add pytest retry to github workflow * test: fix test |