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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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Ishaan Jaffer
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e8461b5b97
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style: run black formatter on files from main merge | ||
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Sameer Kankute
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d03ecedba1
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feat(containers): Azure routing, managed container IDs, delete response parsing (#25287)
* feat(containers): Azure container routing, managed IDs, and delete response wire format - Add AzureContainerConfig and safe URL joining for paths with api-version query - Encode/decode managed container IDs in responses, streaming, and proxy handlers - Accept OpenAI delete response object literal container.file.deleted - Tests for Azure URL regression and DeleteContainerFileResponse parsing Made-with: Cursor * fix(responses): gate response id update on parsed_chunk having response Delta stream events do not include a response body; Mock-based tests (and any truthy synthetic .response on transforms) must not trigger _update_responses_api_response_id_with_model_id. Fixes test_stop_async_iteration_not_logged_as_failure (TypeError: Mock not iterable). Made-with: Cursor * feat(containers): encode container IDs in SDK responses for routing - Add ContainerRequestUtils.encode_container_id_in_response utility - Encode container_id in create/retrieve/delete responses (SDK path) - Fix streaming iterator: gate response ID update on parsed_chunk key - Follows responses API pattern (encode after handler, not in handler) Made-with: Cursor * fix(containers): module-level imports and managed cntr_ ID encoding - Move ResponsesAPIRequestUtils imports to module scope (utils, main, handler_factory). - Serialize absent model_id as empty segment instead of literal None; decode empty and legacy "None" segments as missing for router affinity. - Add unit tests for build/decode round-trip and legacy IDs. Made-with: Cursor * fix(containers): decode managed IDs in endpoint_factory SDK path - Add decode_managed_container_id_for_request in containers/utils and reuse from main. - Strip LiteLLM cntr_ wrappers before generic_container_handler (64-char API limit). - Resolve provider for logging/errors; add unit test for decode helper. - Use resolved_custom_llm_provider after decode for mypy-safe provider typing. Made-with: Cursor * Fix p1 concern * Fix p1 concern |
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yuneng-jiang
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23219d9217 | fixing container tests | ||
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Julio Quinteros Pro
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59d3c75462 |
Fix test_error_handling_integration for parallel test execution
The test was making real API calls instead of using mocks because the conftest.py reloads litellm at module scope, causing stale module references. The mock was patching the old reference while the actual code used the new one. Fix: Reload litellm.containers.main inside the test to get a fresh reference to base_llm_http_handler, then re-import create_container after the reload. |
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shin-bot-litellm
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df299d3193
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fix(tests): Fix flaky container and scientific notation tests (#20650)
* fix(tests): Mock async_container_create_handler for async router test The test was mocking container_create_handler (sync), but router.acreate_container uses _is_async=True which calls async_container_create_handler. This caused the test to hit the real OpenAI API. Fixed by using AsyncMock on async_container_create_handler. * fix(tests): Use uuid for unique model name in scientific notation test The test was using a static "unique" model name which could cause conflicts when running tests in parallel (-n 16 in CI). Using uuid ensures truly unique names to prevent test pollution. --------- Co-authored-by: Shin <shin@openclaw.ai> |
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shin-bot-litellm
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0c006794f1
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litellm_fix_mapped_tests_core: fix test isolation and mock injection issues (#20209)
* litellm_fix_mapped_tests_core: fix test isolation and mock injection issues ## Problem Four tests in litellm_mapped_tests_core were failing: 1. test_register_model_with_scientific_notation - KeyError due to test isolation issues 2. test_search_uses_registry_credentials - Mock not being called due to incorrect patch path 3. test_send_email_missing_api_key - Real API calls despite mocking 4. test_stream_transformation_error_sync - Mock not effective, real API called ## Solution ### test_register_model_with_scientific_notation - Use unique model name to avoid conflicts with other tests - Clear LRU caches before test to prevent stale data - Clean up model_cost entry after test ### test_search_uses_registry_credentials - Use patch.object() on the actual base_llm_http_handler instance - String-based patching for instance methods can fail; direct object patching is more reliable ### test_send_email_missing_api_key - Directly inject mock HTTP client into logger instance - This bypasses any caching issues that could cause the fixture mock to be ineffective ### test_stream_transformation_error_sync - Patch litellm.completion directly instead of the handler module's litellm reference - This ensures the mock is effective regardless of import order ## Regression These tests were affected by LRU caching added in #19606 and HTTP client caching. * fix(test): use patch.object for container API tests to fix mock injection ## Problem test_retrieve_container_basic tests were failing because mocks weren't being applied correctly. The tests used string-based patching: patch('litellm.containers.main.base_llm_http_handler') But base_llm_http_handler is imported at module level, so the mock wasn't intercepting the actual handler calls, resulting in real HTTP requests to OpenAI API. ## Solution Use patch.object() to directly mock methods on the imported handler instance. Import base_llm_http_handler in the test file and patch like: patch.object(base_llm_http_handler, 'container_retrieve_handler', ...) This ensures the mock is applied to the actual object being used, regardless of import order or caching. * fix(test): add missing Prometheus metric labels to test_proxy_failure_metrics Add client_ip, user_agent, model_id labels to expected metric patterns. These labels were added in PRs #19717 and #19678 but test wasn't updated. * fix(test_resend_email): use direct mock injection for all email tests Extend the mock injection pattern used in test_send_email_missing_api_key to all other tests in the file: - test_send_email_success - test_send_email_multiple_recipients Instead of relying on fixture-based patching and respx mocks which can fail due to import order and caching issues, directly inject the mock HTTP client into the logger instance. This ensures mocks are always used regardless of test execution order. * fix(test): use patch.object for image_edit and vector_store tests - test_image_edit_merges_headers_and_extra_headers: import base_llm_http_handler and use patch.object instead of string path patching - test_search_uses_registry_credentials: import module and patch via module.base_llm_http_handler to ensure we patch the right instance --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> |
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shin-bot-litellm
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37a45a3295
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litellm_fix_mapped_tests_core: clear client cache and fix isinstance checks (#20196)
## Problem
Tests using mocked HTTP clients were hitting real APIs because:
1. HTTP client cache was returning previously cached real clients
2. isinstance checks failed due to module identity issues from sys.path
### Tests affected:
- test_send_email_missing_api_key
- test_send_email_multiple_recipients (resend & sendgrid)
- test_search_uses_registry_credentials
- test_vector_store_create_with_simple_provider_name
- test_vector_store_create_with_provider_api_type
- test_vector_store_create_with_ragflow_provider
- test_image_edit_merges_headers_and_extra_headers
- test_retrieve_container_basic (container API tests)
## Solution
1. Add clear_client_cache fixture (autouse=True) to clear
litellm.in_memory_llm_clients_cache before each test
2. Fix isinstance checks to use type name comparison
(avoids module identity issues from sys.path.insert)
## Why not disable_aiohttp_transport
The default transport is aiohttp, so tests should work with it.
Clearing the cache ensures mocks are used instead of cached real clients.
## Regression
PR #19829 (commit
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Alexsander Hamir
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f2c3a01a57
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fix: make HTTPHandler mockable in OIDC secret manager tests (#19803)
* fix: make HTTPHandler mockable in OIDC secret manager tests - Add _get_oidc_http_handler() factory function to make HTTPHandler easily mockable in tests - Update test_oidc_github_success to patch factory function instead of HTTPHandler directly - Update Google OIDC tests for consistency - Fixes test_oidc_github_success failure where mock was bypassed This change allows tests to properly mock HTTPHandler instances used for OIDC token requests, fixing the test failure where the mock was not being used. * fix: patch base_llm_http_handler method directly in container tests - Use patch.object to patch container_create_handler method directly on the base_llm_http_handler instance instead of patching the module - Fixes test_provider_support[openai] failure where mock wasn't applied - Also fixes test_error_handling_integration with same approach The issue was that patching 'litellm.containers.main.base_llm_http_handler' didn't work because the module imports it with 'from litellm.main import', creating a local reference. Using patch.object patches the method on the actual object instance, which works regardless of import style. * fix: resolve flaky test_openai_env_base by clearing cache - Add cache clearing at start of test_openai_env_base to prevent cache pollution - Ensures no cached clients from previous tests interfere with respx mocks - Fixes intermittent failures where aiohttp transport was used instead of httpx - Test-only change with low risk, no production code modifications Resolves flaky test marked with @pytest.mark.flaky(retries=3, delay=1) Both parametrized versions (OPENAI_API_BASE and OPENAI_BASE_URL) now pass consistently * test: add explicit mock verification in test_provider_support - Capture mock handler with 'as mock_handler' for explicit validation - Add assert_called_once() to verify mock was actually used - Ensures test verifies no real API calls are made - Follows same pattern as test_openai_env_base validation |
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Ishaan Jaffer
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9f99e8231c | test_retrieve_container_basic | ||
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Ishaan Jaffer
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a62ccd582d | fix flaky tests | ||
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Ishaan Jaff
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e67e9e7054
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[Fix] Containers API - Allow routing to regional endpoints (#19118)
* fix get_complete_url * fix url resolution containers API * TestContainerRegionalApiBase |
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Ishaan Jaffer
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b855ad5541 | test_encode_decode_helpers_roundtrip_in_cache_context | ||
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Ishaan Jaff
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142567e143
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[Fix] Containers API - Allow using LIST, Create Containers using custom-llm-provider (#17740)
* test_router_acreate_container_without_model * _init_containers_api_endpoints * test_init_containers_api_endpoints |
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Sameer Kankute
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0c743e1adc
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Add E2E Container API Support (#16136)
* Add v1 cut of container api * fix lint errors * Add proxy support to container apis & logging support (#16049) * Add proxy support to container apis * Add logging support * Add cost tracking support for containers and documentation * Add new constant documentation * Add container cost in model map * fix failing azure tests * Update tests based on model map changes * fix model map tests * fix model map tests * Container modeshould be container * Container tests fix * Merge branch 'main' into litellm_sameer_oct_staging_2 --------- Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> |