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9818 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
ryan-crabbe-berri
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91c6fa975d
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fix(guardrails): return 400 not 500 when AIM blocks a request (#30573)
* fix(guardrails): return 400 not 500 when AIM blocks a request
AIM guardrail blocks raised a bare HTTPException whose type and param
serialized as the literal string "None", which broke OpenAI-SDK error
parsing for downstream consumers. Switching AIM to raise a ProxyException
surfaced a second bug: the shared error funnel re-derived the HTTP status
from a nonexistent status_code attribute and downgraded the 400 to a 500.
The funnel now honors an already-normalized ProxyException rather than
rebuilding it, and ProxyException is excluded from llm_exceptions alerting
so a content-policy block no longer pages on-call as an LLM API failure
Resolves LIT-3751
* fix(guardrails): route all AIM rejection paths through ProxyException
The block-action fix left two AIM rejection paths raising a bare
HTTPException: the multimodal anonymize rejection and the output-side
block. Both serialized type and param as the literal string "None", the
same malformed shape the block fix removed. Funnel all three through a
shared _rejection helper so they return a conformant OpenAI error body.
The output block carries content_policy_violation; the multimodal
rejection stays a plain invalid_request_error because it is a usage
error, not a policy violation
Resolves LIT-3751
* fix(guardrails): record AIM ProxyException blocks in failure logs
Switching AIM blocks from HTTPException to ProxyException made
_is_proxy_only_llm_api_error return False for them, so
_handle_logging_proxy_only_error was skipped and the blocked prompt was
dropped from the configured failure loggers. Classify ProxyException as a
proxy-only error alongside HTTPException so guardrail blocks are recorded
again, matching the prior behavior. The llm_exceptions alert suppression
is a separate check and stays in place
Resolves LIT-3751
* style(guardrails): use str | None over Optional[str] in AIM _rejection
* style(guardrails): collapse AIM _rejection signature per black
(cherry picked from commit
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Yassin Kortam
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7b8a6d0885
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fix(guardrails): stop re-initializing DB guardrails on every poll (#30542)
* fix(guardrails): stop re-initializing DB guardrails on every poll
InMemoryGuardrailHandler._has_guardrail_params_changed compared the
in-memory LitellmParams against the raw dict loaded from the DB. The
in-memory side carries every field default and coerces enums via
model_dump(), while the DB side only holds the keys originally stored,
so the two shapes never compared equal and the guardrail was rebuilt on
every poll cycle.
Each rebuild created a fresh instance, but delete_in_memory_guardrail
only removed the old callback from litellm.callbacks. Request handling
promotes guardrail callbacks into the success/failure/async lists, so
the previous instance stayed referenced there and instances accumulated.
Normalize both sides through LitellmParams(...).model_dump() before
diffing, and purge the callback from every callback list on delete.
* refactor(guardrails): narrow params-normalization fallback to ValidationError
The comparison normalizer caught a bare Exception and silently fell back
to the raw dict, which hid the cause and quietly degraded the affected
guardrail back to re-initializing on every poll. Catch only the
ValidationError that LitellmParams construction can raise, log a warning
so the offending row is diagnosable, and let any other error surface
instead of being swallowed.
* refactor(callbacks): add remove_callback_from_all_lists helper to manager
Move the knowledge of which callback lists a callback can be promoted
into out of the guardrail registry and into LoggingCallbackManager, where
the rest of the callback-list bookkeeping already lives. delete_in_memory_guardrail
now delegates to the new helper instead of iterating the lists itself.
(cherry picked from commit
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Yassin Kortam
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d8f6bd1741
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fix(guardrails): run pre_call hook once for model-level guardrails (#30543)
* fix(guardrails): run pre_call hook once for model-level guardrails
A CustomGuardrail attached to a deployment via litellm_params.guardrails
gets its async_pre_call_hook invoked twice per request: once by the proxy
pre-call loop and again by async_pre_call_deployment_hook after the router
spreads the model-level guardrails into the top-level request kwargs.
Record in request metadata that the proxy pre-call loop already ran a given
guardrail, and have the deployment hook skip it when the marker is present.
Direct-SDK usage never runs the proxy loop, so the deployment hook stays the
sole invocation there and still fires exactly once.
The marker key is stripped from untrusted caller metadata so a request body
cannot suppress a model-only guardrail by pre-seeding it.
* fix(guardrails): mark pre_call dedup on the post-hook request data
Record the exactly-once marker after async_pre_call_hook runs, on the data
object that flows downstream, rather than before it. A guardrail whose hook
returns a brand-new request dict (instead of mutating or spreading the one it
received) would otherwise discard the marker, letting the deployment hook
re-run the guardrail a second time.
(cherry picked from commit
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Shivam Rawat
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f1f8701d65
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fix(integrations): cap Anthropic cache_control injection at 4 blocks (#30480)
* fix(integrations): cap Anthropic cache_control injection at 4 blocks
Respect Anthropic's 4 cache_control breakpoint limit by counting client-supplied blocks, skipping messages that already carry cache_control, and stopping further auto-injection once the limit is reached.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(integrations): reserve cache slot for tool_config and short-circuit cap
Address review feedback on the cache_control cap: break out of the injection loop before resolving target indices once the limit is reached, and reserve one of the four breakpoint slots when a tool_config injection point is present so the cachePoint appended by the Bedrock transform does not push the total past Anthropic's limit.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
(cherry picked from commit
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Mateo Wang
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9fa03d4ee3
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fix: passthrough endpoints duplicate logs (#29598)
* fix duplicate cost callbacks for anthropic streaming pass-through
Two bugs caused _PROXY_track_cost_callback to see stream=True +
complete_streaming_response=None on every streaming pass-through request,
making the dedup guard in dispatch_success_handlers permanently inactive:
1. pass_through_endpoints.py created the Logging object with stream=False
for all requests. _is_assembled_stream_success short-circuits on
self.stream is not True, so has_dispatched_final_stream_success was
never set and any second dispatch went through unchecked.
Fix: set logging_obj.stream = True after stream detection.
2. _create_anthropic_response_logging_payload set complete_streaming_response
inside the try block after litellm.completion_cost(), so a pricing error
caused an early return without setting it on model_call_details.
Fix: set complete_streaming_response before the try block.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix stream
* add stream to logging obj
* test(pass_through): give mock logging object a real model_call_details dict
The anthropic passthrough logging payload now records the assembled
response on model_call_details before cost calculation, which requires
model_call_details to support item assignment. In production it is always
a dict; the existing unit test stubbed the logging object with a bare Mock
whose attribute is not subscriptable, so the new assignment raised
TypeError. Use a real dict to match the production logging object.
* test(pass_through): cover streaming logging-obj stream flag
The streaming branch of pass_through_request that marks the logging object
as streaming (logging_obj.stream and model_call_details["stream"]) had no
unit coverage, so the patch coverage gate flagged it. Add a regression test
that drives a streaming pass-through request through pass_through_request and
asserts the logging object is flagged as a stream before dispatch.
* test(pass_through): cover SSE-response stream flag fallback branch
The auto-detected streaming branch of pass_through_request (when a request
that was not flagged as streaming returns a text/event-stream response) sets
logging_obj.stream and model_call_details["stream"] but had no unit coverage,
so the codecov patch gate failed at 60%. Drive a non-streaming pass-through
request whose upstream response is SSE through pass_through_request and assert
the logging object is flagged as a stream before dispatch.
* fix(pass_through): gate complete_streaming_response on stream flag
perform_redaction only scrubs complete_streaming_response when
model_call_details["stream"] is True. Setting it unconditionally for
non-streaming Anthropic pass-through responses left the assembled
response unredacted in model_call_details, which is handed to logging
callbacks as kwargs when message logging is disabled. Only record it for
actual streaming responses so redaction always applies.
---------
Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
(cherry picked from commit
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Mateo Wang
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63a66efbbc
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fix: stop use_chat_completions_api flag from leaking into provider request body (#29447)
* fix: stop use_chat_completions_api flag from leaking into provider request body
use_chat_completions_api is a LiteLLM control flag that forces the
/responses -> /chat/completions bridge. It was missing from
all_litellm_params, so get_non_default_completion_params treated it as a
model-specific param and forwarded it to the upstream provider. A
model-level "use_chat_completions_api: true" in the proxy config therefore
reached the chat-completions path and was rejected by strict providers
(OpenAI/Anthropic) with HTTP 400 for an unknown body field.
Register it as a known internal param so it is stripped on every path
(completion, the responses bridge that calls litellm.completion, and
filter_out_litellm_params).
Adds a regression test driving litellm.completion() with a mocked OpenAI
client that asserts the flag never reaches the request body.
* test: clarify extra_body assertion in use_chat_completions_api leak test
Replace the misleading 'not in ... or {}' precedence idiom with an explicit
parenthesized guard that also handles extra_body being None.
(cherry picked from commit
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Yassin Kortam
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d3ee4103ab
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fix(datadog): split oversized batches on 413 instead of re-queueing forever (#29444)
(cherry picked from commit
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Mateo Wang
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5eb3fafd6e
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[internal copy of #29089] fix: duplicate claude code traces (#29311)
(cherry picked from commit
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Sameer Kankute
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e254e3e90e
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fix(passthrough): skip [DONE] sentinels and non-JSON SSE frames in Anthropic streaming logging
Targeted subset of staging commit |
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Yassin Kortam
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b5b86a3563
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fix(passthrough): resolve costing model when body model is unknown (#30160)
(cherry picked from commit
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Yassin Kortam
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a41012cbf2
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fix(proxy): return 5xx on DB infra errors during auth; reserve 401 for genuine auth failures (#29986)
(cherry picked from commit
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Yassin Kortam
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1fd61f2d20
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feat(proxy): add option to disable server-side prepared statements for DB lookups (#29984)
(cherry picked from commit
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Armaan Sandhu
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54b031b59c
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feat(proxy): add disable_budget_reservation general setting (#27639) (#29493)
* feat(proxy): add disable_budget_reservation general setting (#27639)
* feat(proxy): register disable_budget_reservation in ConfigGeneralSettings (#27639)
* docs(proxy): document disable_budget_reservation concurrency tradeoff (#27639)
* ci: re-trigger flaky docker build (prisma generate ECONNRESET)
* fix(proxy): warn and document budget enforcement tradeoff when disable_budget_reservation is set (#27639)
(cherry picked from commit
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mateo-berri
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f6bd1df2a0
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style: format CrowdStrike parametrized test for this branch's black | ||
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Kent
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63edbf3fa2
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feat(bedrock_mantle): add SigV4/IAM auth to Responses API route (#29788)
Applied as the squash diff of PR #29788 (head |
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Kent
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dad0894dff
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feat(bedrock_mantle): route Responses API to native OpenAI endpoint (#29490)
Backport prerequisite for #29788. Applied as the squash diff of PR #29490
(head 50ab150fa6^..), which landed upstream inside the litellm_oss_staging_040626
sync (
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yuneng-jiang
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88d9d5ea2b
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fix(guardrails): read CrowdStrike AIDR identity from both metadata bags (#29991)
Capture user_id and extra_info from metadata or litellm_metadata. The single-bag read dropped identity whenever a request carried a present litellm_metadata field (null or a user-supplied dict), since /chat/completions routes the authenticated identity into metadata while the guardrail read litellm_metadata first
(cherry picked from commit
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Kenan Yildirim
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a77bf66c71
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feat(guardrails): capture user and model metadata in CrowdStrike AIDR
(cherry picked from commit
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Sameer Kankute
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403acba5ec
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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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Mateo Wang
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2de74e3199
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Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI (#30064)
* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI
Adds cost map entries for claude-fable-5 ($10/$50 per MTok, 1M context,
128K output, adaptive thinking only) on the Anthropic API, Bedrock
converse (base, global, and us/eu geo inference profiles at the 10%
regional premium), Vertex AI, and Azure AI (Microsoft Foundry, which
serves Fable 5 with the full 1M context window unlike Opus 4.8).
Registers anthropic.claude-fable-5 in BEDROCK_CONVERSE_MODELS, lists the
model in the setup wizard, and extends the reasoning effort e2e grid.
The Bedrock, Vertex, and Azure grid cells carry fail_reason markers
until the CI accounts are provisioned: Bedrock needs the provider data
sharing opt-in Fable 5 requires, and the Foundry resource needs a
claude-fable-5 deployment.
The first-party entry carries provider_specific_entry {us: 1.1} for the
inference_geo premium and deliberately no fast multiplier since Fable 5
has no fast mode.
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* Drop removed sampling params for Claude 4.7+ when drop_params is set
Fable 5, Opus 4.7, and Opus 4.8 removed sampling params: the API rejects
top_p, top_k, and any temperature other than 1 with a 400. LiteLLM was
forwarding them even with drop_params enabled because the Anthropic and
Bedrock converse transformations passed temperature/top_p through
unconditionally.
Mirror the GPT-5/o-series handling: temperature=1 still passes through,
other values and any top_p are dropped when drop_params is set, and
without drop_params a clean client-side UnsupportedParamsError tells the
caller how to opt in, instead of surfacing the raw provider error.
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* Drive sampling param gating from the cost map and cover top_k
Greptile review follow-ups on the sampling param fix: the restriction for
Fable 5 / Opus 4.7 / 4.8 is now declared as supports_sampling_params: false
on every affected cost map entry (perplexity excluded; that route is
OpenAI-compatible and maps sampling params upstream) and read back through
a tri-state map lookup, keeping the name check only as a fallback for
provider-routed ids whose hosted map entries predate the flag, the same
layering supports_adaptive_thinking uses. top_k bypasses map_openai_params
as a provider-specific kwarg, so it is gated at the shared
AnthropicConfig.transform_request boundary (direct, Bedrock invoke, Vertex,
Azure) and in the Bedrock converse _handle_top_k_value path, with
drop_params threaded through the converse transform helpers.
Also updates the reasoning effort grid cell count assertion for the four
Fable 5 rows added on this branch (29 x 11 cells).
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* Declare supports_sampling_params in the cost map schema
The model map validation schema uses additionalProperties: false, so the
new flag must be declared for the 28 entries that carry it; this was the
one failing job (misc / Run tests) on the previous commit.
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* fix(bedrock): gate top_k=0 on converse to match Anthropic boundary
Truthiness check let top_k=0 silently disappear on models that removed
sampling params, while AnthropicConfig.transform_request treats 0 as
present and raises UnsupportedParamsError (or drops when drop_params is
set). Switch to 'is not None' so converse, direct Anthropic, invoke,
Vertex, and Azure all behave the same for top_k=0.
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
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mateo-berri
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efeb101ec6
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fix(key_generate): harden GHSA-q775 session-token exemption against default_key_generate_params
Capture _requested_team_id before the default_key_generate_params loop runs and key the UI/CLI session-token budget-ceiling exemption off it, instead of the post-defaults data.team_id. On an install that sets default_key_generate_params.team_id, a session token requesting a personal key (no explicit team_id) would otherwise have data.team_id auto-filled, flipping is_ui_session_team_key on and bypassing the delegated-authority ceiling -- the exact escalation GHSA-q775 closed. Mirrors the existing pre-defaults capture of _requested_max_budget. Adds a regression test. https://claude.ai/code/session_01RT583b1khYC3wjLrQ5hT5h |
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yuneng-jiang
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3f43e0e9e3
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fix(key_generate): exempt UI/CLI session tokens from the budget ceiling for team keys (#29612)
Non-admin users creating a team key through the UI were rejected with
"max_budget cannot exceed the caller's own max_budget (0.25)". The request is
authenticated by a UI/CLI session token whose max_budget is the per-session chat
spend cap (max_ui_session_budget, default $0.25), and the delegated-authority
budget ceiling (GHSA-q775-qw9r-2r4g) treated that cap as a delegation limit.
Skip the ceiling only when a session token creates a team key (data.team_id set);
that key's spend is bounded by the team budget at request time. Personal keys and
every other non-admin caller keep the ceiling, so a session token cannot mint an
arbitrary-budget personal key.
(cherry picked from commit
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Mateo Wang
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e33a825e12
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fix(vertex): strip output_config.effort for Vertex Claude models that reject it (Haiku 4.5) (#29585)
* fix(vertex): strip output_config.effort for models that reject it
Haiku 4.5 on Vertex AI does not support output_config.effort and 400s with
"output_config.effort: Extra inputs are not permitted". PR #27074 emptied
VERTEX_UNSUPPORTED_OUTPUT_CONFIG_KEYS so effort would forward for Opus/Sonnet
4.6+, but that made the strip unconditional across every Vertex Anthropic
model, including ones that don't support it. Claude Code injects effort into
its default Messages payload, so `claude --model claude-haiku-4.5` started
failing.
Make the sanitizer model-aware: drop output_config.effort for models that
don't advertise output_config support (or any reasoning effort level) while
forwarding it for those that do. The fix covers both the chat-completion and
Messages pass-through transformation paths since they share the helper.
* chore(vertex): log at debug when dropping unsupported output_config.effort
Operators pointing an unregistered Vertex Claude alias that does support
effort would otherwise see it stripped with no signal. Debug level keeps it
out of normal logs since Claude Code sends effort on every request.
(cherry picked from commit
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milan-berri
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48c1070b34
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fix(key_generate): allow team members to create keys on org-scoped teams (#29310)
* fix(key_generate): allow team members to create keys on org-scoped teams
When a virtual key is created for a team, enterprise logic inherits the
team's organization_id onto the key (add_team_organization_id). Since the
VERIA-55 org-IDOR fix, /key/generate then required the caller to be an
explicit LiteLLM_OrganizationMembership member of that org, returning
403 "Caller is not a member of organization_id=<uuid>". Admins normally
only add users to teams (not orgs), so self-serve key creation regressed
for any user on an org-scoped team (regression since v1.84.0-rc.1).
Skip the org-membership check when organization_id was inherited from the
key's team (organization_id == team_table.organization_id). Team-level
authorization already gates this path, so team membership is sufficient.
The membership check still runs when a caller assigns an organization_id
that did not come from the key's team, preserving the IDOR protection.
Adds regression tests covering both the team-inherited (allowed) and
foreign-org (still blocked) cases.
Co-authored-by: Cursor <cursoragent@cursor.com>
* test(key_generate): cover mismatched team org IDOR path on generate
Add test_generate_key_foreign_org_with_mismatched_team_still_enforces_membership
for the case where a team is present but request organization_id differs from
team_table.organization_id. Enterprise inheritance is no-op'd in the test so
the guard is exercised directly; membership validation must still run.
Addresses Greptile review on #29310.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
(cherry picked from commit
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Shivam Rawat
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adef4062fc
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fix(proxy): resolve managed video model ids for auth (#29545)
* fix(proxy): resolve managed video model ids for auth
Co-authored-by: Cursor <cursoragent@cursor.com>
* test(proxy): cover character_id router model resolution
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
(cherry picked from commit
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Sameer Kankute
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19f3efd5a4
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fix(proxy): map stripped batch body.model to proxy alias for auth (#29264)
* fix(proxy): map stripped batch body.model to proxy alias for auth
replace_model_in_jsonl rewrites JSONL body.model to the provider id before
upload; batch file access checks must resolve that id back to model_name
so keys granted the proxy alias are not rejected with 403.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(proxy): surface resolved proxy alias in batch file 403 detail
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
(cherry picked from commit
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Mateo Wang
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e92ddec993
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fix(azure): preserve AD token refresh in v1 OpenAI client path (#28627)
* fix(azure): preserve AD token refresh in v1 OpenAI client path
The /openai/v1/ code path (api_version in {"v1", "latest", "preview"})
constructs a plain OpenAI/AsyncOpenAI client, but only forwarded
`api_key` from `azure_client_params`. When `enable_azure_ad_token_refresh`
is set (or any AD-only auth), `api_key` is None and the client
constructor raised "The api_key client option must be set...", breaking
every Azure call with a v1 api_version.
The OpenAI SDK (>=2.20.0) accepts a callable for `api_key` and re-invokes
it on every request via `_refresh_api_key`, so we now forward
`azure_ad_token_provider` directly — preserving the per-request token
refresh behavior of the regular AzureOpenAI client and avoiding the
expiry hole that resolving the token once at client-creation time would
introduce. Static `azure_ad_token` strings fall through to `api_key`.
For the async path we wrap the sync provider returned by azure-identity
in an async function since AsyncOpenAI expects `Callable[[], Awaitable[str]]`.
Fixes #27945
https://claude.ai/code/session_01UnzrDSFUUgp5T2wRoPMxq5
* fix(azure): offload sync token provider to thread in v1 async wrapper
* fix(azure): include AD credential identity in v1 client cache key
---------
Co-authored-by: Claude <noreply@anthropic.com>
(cherry picked from commit
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yuneng-jiang
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fa3fc7a91c
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refactor(proxy/auth): normalize Bearer prefix in safe-hash helper (#29343) (#29365)
* refactor(proxy/auth): normalize Bearer prefix in safe-hash helper
UserAPIKeyAuth._safe_hash_litellm_api_key now strips a leading
"Bearer "/"bearer " prefix before its existing sk-/JWT classification, so
the helper produces the same hashed output regardless of whether the
caller stripped the Authorization header prefix or passed the header
value through unchanged.
* refactor(proxy/auth): make Bearer-prefix strip case-insensitive
Per RFC 7235 the HTTP authorization scheme token is case-insensitive.
Replace the two-prefix loop with a single case-insensitive check so the
helper normalizes "Bearer ", "bearer ", "BEARER ", and any mixed-case
variant before classifying the remainder as sk- or JWT. The contract
test gains coverage of "BEARER " and "BeArEr ".
* test(mcp): align auth-handler test expectations with safe-hash helper
The two MCP auth tests asserted that UserAPIKeyAuth(api_key="Bearer ...")
retained the raw header bytes on the api_key field. _safe_hash_litellm_api_key
now normalizes that input — stripping the Bearer prefix and hashing the
resulting sk- key — so the expectations move to the normalized form:
the bare token in the parametrize case, and hash_token("sk-...") in the
backward-compat assertion. This matches what the real auth flow produces
(the builder strips Bearer and the DB stores the hashed token), so the
mocks now line up with production rather than with the un-normalized
validator output.
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yuneng-jiang
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ddcb0b5aca
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fix(reset_budget): write only {spend, budget_reset_at} and stop pre-zeroing counter (#29358) (#29364)
* fix(reset_budget): write only {spend, budget_reset_at} and stop pre-zeroing counter
ResetBudgetJob's batched update_data path shipped the full key/user/team
model on each reset. Prisma rejects object_permission_id and budget_limits
on the update input type, so any row carrying those fields detonated the
entire batch -- spend never reset, budget_reset_at never advanced. After
v1.84.0 started populating object_permission_id on UI-created keys, this
fires routinely.
_reset_budget_common also zeroed the cross-pod spend counter before the
DB write, so failed resets left enforcement reading 0 from the counter
while the DB still held the over-budget spend, admitting requests past
the cap until the counter naturally re-saturated from new reservations.
Switch the write to per-row narrow updates ({spend, budget_reset_at})
via db.batch_, and move the counter invalidation out of
_reset_budget_common so it only fires after the DB write commits. On
DB-write failure the counter is left untouched, enforcement continues
to block, and the next scheduler tick can retry without leaving a
bypass window.
Fixes #27730.
* fix(reset_budget): address Greptile review on #29358
- Strengthen the bypass-half regression test: replace the for-loop over
call_args_list (vacuously true when empty) with assert_not_called(),
so the test would actually flag a re-introduction of counter-zeroing
via any code path.
- Add the same explanatory docstring on _write_user_reset_updates and
_write_team_reset_updates that _write_key_reset_updates already has,
so all three helpers point future maintainers at #27730.
* test(reset_budget): update test_proxy_budget_reset for new batch-write path
Same shape as the previous test_reset_budget_job.py update: keys/users/teams
now write through prisma.db.batch_().<table>.update, not update_data, so the
tests need a batcher mock and updated assertions. Adds:
- _wire_batcher_for_test helper that returns a list which accumulates per-row
batch updates captured from prisma_client.db.batch_().
- _attrify helper that wraps dict fixtures so getattr(item, "token") works
alongside the dict item-access the fake_reset_* mocks rely on. The new
narrow-write helpers use getattr to pull out the row's id, and would
silently skip plain dicts otherwise.
- Updates 3 partial_failure tests to assert against the batch-call list
(rows by id, payload contains only {spend, budget_reset_at}) instead of
update_data.assert_awaited_once + data_list inspection.
- Updates test_reset_budget_continues_other_categories_on_failure: only
budget + enduser still flow through update_data; key/user/team go through
the batch path now.
- Wires the batcher mock into 3 service_logger_*_success tests so commit()
is actually awaitable and the success hook fires.
These tests were silently passing locally only because the editable install
in .venv pointed at the main repo, not the worktree — running pytest with
PYTHONPATH overridden to the worktree (matching CI) reproduces the failures.
|
||
|
yuneng-jiang
|
d480ffda3c
|
chore(proxy): cherry-pick #28547 (route path-dependent call sites through get_request_route) onto v1.87.0-rc.1 patch (#28919)
* chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: user <70670632+stuxf@users.noreply.github.com> |
||
|
ryan-crabbe-berri
|
9451a72e89
|
Patches for v1.87.0-rc.1 (#28915)
* fix(proxy): strip LiteLLM policy tracking from OpenAI batch metadata (#28425) * fix(proxy): strip LiteLLM policy tracking from OpenAI batch metadata Batch create was failing with `Invalid type for 'metadata.applied_policies': expected a string, but got an array instead` whenever a policy attachment matched the request. The policy engine helpers wrote `applied_policies`, `applied_guardrails`, and `policy_sources` into `data["metadata"]` unconditionally, and `/v1/batches` forwarded that dict straight to OpenAI, which only accepts string values. - Route proxy-internal tracking into `litellm_metadata` for batch/file routes via a shared `_get_or_create_proxy_metadata_bucket` helper. - Sanitize `data["metadata"]` in `create_batch` to drop known internal keys and non-string values before building the OpenAI request. - Cover both behaviors with unit + endpoint tests. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): merge metadata buckets for batch policy response headers Ensure get_logging_caching_headers reads both metadata and litellm_metadata so policy/guardrail headers are emitted on batch routes with user metadata, and log dropped non-string OpenAI metadata at debug level. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> * fix(model-edit): allow clearing custom pricing on wildcard models (#28719) * fix(model-edit): allow clearing custom input/output cost on wildcard deployments A user-set pricing override on a `/model/*` wildcard deployment could not be removed: clearing the Input/Output Cost fields in the UI succeeded visually, but the next read still showed the old values because both `litellm_params` and `model_info` (mirrored via `SPECIAL_MODEL_INFO_PARAMS`) retained the original rates. UI: when the pricing field is touched but left empty, send `null` instead of dropping it from the payload so the backend sees the clear intent. The cache-read-cost fallback now guards against `null` as well as `undefined` so a cleared input cost cannot silently wipe the cache-read override. Backend: `update_db_model` honors explicit-null clears, but ONLY for `SPECIAL_MODEL_INFO_PARAMS` (the 4 pricing fields). Restricting the null-clear path prevents a team-scoped caller from using this codepath to null out privileged fields like `team_id` or access groups. Tests cover both clear paths (`litellm_params` and `model_info`), the SPECIAL_MODEL_INFO_PARAMS mirror, PATCH semantics for omitted fields, and the security guard that non-pricing nulls don't reach the merged dict. Resolves LIT-3250 * fix(model-edit): run null-clears after both merges, not interleaved The previous version cleared `model_info` from inside the litellm_params merge block, but the subsequent `model_info.update(...)` re-injected the old pricing because the UI's PATCH carries the full model_info blob with the stale values still in it. Move the explicit-null clear pass to after both merges so a model_info passthrough cannot resurrect cleared fields. Adds a regression test for the realistic UI submit shape (both blobs in the patch, model_info still holding the old pricing). * test(e2e): clear-custom-pricing flow with create/delete cleanup Covers the dashboard model edit form's pricing-clear flow end-to-end: seeds a deployment with custom input/output pricing, drives the UI to clear both fields, asserts the outgoing PATCH sends explicit nulls, and confirms via /v2/model/info that the override is gone from both litellm_params and model_info. The dashboard DB persists across this suite, so beforeEach creates a uniquely-named deployment and afterEach POSTs /model/delete to leave the DB clean regardless of test outcome. * fix(model-edit): extend pricing clear to cache_read and cache_write costs Pre-existing parallel of the wildcard input/output cost bug: cleared cache_read_input_token_cost and cache_creation_input_token_cost overrides silently persisted because the UI omitted the key (delete or fallback) and the backend null-clear allowlist did not cover them. - types/router.py: add cache_read_input_token_cost and cache_creation_input_token_cost to SPECIAL_MODEL_INFO_PARAMS, so they are mirrored between litellm_params and model_info by Deployment.__init__ and honoured by the null-clear loop in update_db_model. - model_info_view.tsx: emit explicit null for touched-but-empty cache_read and cache_write fields. Preserve the input_cost->cache_read mirror only when cache_read itself was not touched. - model_management_endpoints.py: update the allowlist comment. - Tests: three new unit tests for cache clear paths and a preserve check; the e2e spec now seeds, clears, and asserts null PATCH + key-absence for all four pricing fields. --------- Co-authored-by: Shivam Rawat <shivam@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> |
||
|
yuneng-jiang
|
3bcfe41f05
|
test(model_prices): allow audio_transcription_config in schema (#28708)
The schema in test_aaamodel_prices_and_context_window_json_is_valid uses additionalProperties: false. The azure/speech/azure-stt entry added in #27482 introduced an audio_transcription_config field that the schema did not whitelist, so the test fails on every branch built on top of staging. Add the field as a string property. |
||
|
ryan-crabbe-berri
|
886e91b85e
|
fix(otel): stamp http.response.status_code on all error responses (#28405)
* fix(otel): stamp http.response.status_code on all error responses
httpx.HTTPStatusError exposes status under .response.status_code, not as a
top-level attr, so unified-endpoint 5xx failures left the SERVER span without
a status. The admin hooks only wrote a child span and never stamped or ended
the parent at all, so admin 4xx/5xx (and success) responses were invisible
to dashboards. Adds a fallback to .response.status_code in get_error_information,
and ends the parent SERVER span in async_management_endpoint_{success,failure}_hook
with the same _record_exception_on_span helper the unified path uses.
Resolves LIT-3193
* test(otel): exercise httpx.HTTPStatusError through admin path
Pins the contract that get_error_information's response.status_code fallback
is reachable from any entry point — without this, a future refactor that
bypasses _record_exception_on_span in the admin hooks could regress for
httpx-wrapped exceptions while the unified suite still passes.
* chore(otel): trim verbose comments in LIT-3193 changes
Tighten docstrings and remove redundant section dividers/inline narration.
Behavior is unchanged.
* fix(otel): set span.status on management hook parent SERVER span
Mirror the unified failure path: stamp StatusCode.ERROR on the parent
SERVER span before recording the exception, and StatusCode.OK before
ending it on success. Without this, OTEL backends filtering on span
status (the idiomatic primitive) miss admin-endpoint failures even
though the http.response.status_code attribute is correct.
Extend assert_server_span_attrs to assert span.status.status_code
matches the expected outcome so the gap can't regress.
* fix(otel): close SERVER span on body-validation and unhandled errors
Stash the SERVER span on request.state in auth so FastAPI exception
handlers can finish it for failures that occur after auth but before
the route handler (e.g. /model/new TypeError, /key/generate
RequestValidationError). Without this, those requests left dangling
spans missing http.response.status_code.
Resolves LIT-3193
* fix(otel): generic 500 body, log exception details server-side
Don't leak str(exc) and type(exc).__name__ to clients on uncaught
exceptions. The full traceback is logged via verbose_proxy_logger and
the SERVER span still gets http.response.status_code=500.
Resolves LIT-3193
* fix(otel): stamp http.response.status_code on every SERVER span path
Closes three remaining gaps where the proxy SERVER span ended without
the http.response.status_code attribute:
1. ProxyException raised from _read_request_body (e.g. invalid JSON
body) bubbled out of user_api_key_auth before the SERVER span was
created, so the FastAPI handler had nothing to close and the trace
never reached the backend. Hoist the span creation to a new
idempotent _ensure_parent_otel_span_on_request_state helper called
at the top of user_api_key_auth; wire openai_exception_handler to
close the dangling span. Covers /v1/chat/completions, /v1/messages,
/v1/responses (shared handler).
2. /v1/responses success — _handle_success ends the proxy span before
async_post_call_success_hook fires on this path, so the hook's
set_response_status_code_attribute(200) silently no-op'd against an
ended span. Stamp 200 + set OK status at the close site in
_handle_success / _end_proxy_span_from_kwargs via a shared
_close_proxy_span_ok helper, so the attribute lands regardless of
which success hook runs first.
3. Failure path for exceptions without code/status_code (e.g. a bare
TypeError surfacing through _handle_llm_api_exception) — empty
error_information.error_code → _record_exception_on_span skips the
stamp → the hook ends the span. Default to 500 in
async_post_call_failure_hook so the attribute is always set.
Resolves LIT-3193
|
||
|
ishaan-berri
|
14c0a2b3e2
|
feat(prometheus): emit per-token-type detail metrics (LIT-3220) (#28372) (#28378)
* feat(prometheus): emit per-token-type detail metrics (LIT-3220) (#28372) Adds five sparse counter metrics that break out the token detail fields providers already report in `usage.prompt_tokens_details` and `usage.completion_tokens_details`: - litellm_input_cached_tokens_metric (provider prompt-cache reads) - litellm_input_cache_creation_tokens_metric (Anthropic prompt-cache writes) - litellm_input_audio_tokens_metric (audio input tokens) - litellm_output_reasoning_tokens_metric (reasoning tokens) - litellm_output_audio_tokens_metric (audio output tokens) These are additive — existing input/output/total counters are unchanged, so no dashboards break. Each new counter is only incremented when the underlying detail is populated and > 0, keeping scrape output sparse for providers that don't report a given field. Data is read from the canonical Usage dict that `get_standard_logging_object_payload` already attaches at `standard_logging_payload["metadata"]["usage_object"]`, so no new plumbing through the logging pipeline is required. Tests: 10 new unit tests covering registration, label-set parity, all-types increment, zero/None/negative skip behaviour, and the no-metadata/no-usage_object no-op paths. Closes LIT-3220 Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai> Co-authored-by: Claude <noreply@anthropic.com> * chore: remove proof folder image --------- Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> |
||
|
yuneng-jiang
|
5e16f20962
|
test(proxy): phase-4 payload behavior pinning for tier-2/3 key + team management endpoints (#28681)
* test(proxy): phase-4 payload behavior pinning for tier-2/3 key + team management endpoints Extends the Phase 1–3 behavior-pin suite at tests/proxy_behavior/management/ with a second axis: payload-shape pinning. Phase 1–3 held payload minimal and pinned (actor, target) → status across 37 routes; Phase 4 holds the caller fixed at an authorized actor, varies the payload shape, and asserts the observable DB effect (on accept) or the named guard / row-unchanged (on reject). Faithfulness contract from Phase 1–3 is unchanged. Six families + one gap-closer (59 new scenarios, 620 → 679 total): * F1 — key budget / rate-limit (test_key_budget_limits.py, 18) * F2 — key↔team reassignment (test_key_team_change.py, 6) * F3 — team budget / rate-limit (test_team_budget_limits.py, 15) * F4 — member-info validation (test_team_member_info_validation.py, 5) * F5 — permission batching (test_team_permissions_bulk_update.py, 6) * F6 — org-scoped team access (+2 detail-string pins in existing files) * F7 — coverage gap-closer (test_f7_coverage_closeout.py, 7) Harness extensions in conftest.py (additive only): * create_scratch_org() seeder with its own scratch-prefixed budget row * budget / limit fields on create_scratch_team() * scratch teardown also sweeps litellm_organizationtable Coverage telemetry (behavior-suite-only): * key_management_endpoints.py 60 % → 65 % (+82 lines) * team_endpoints.py 62 % → 72 % (+137 lines, crosses 70 % stretch) Key lands under 70 % per plan §7 escape hatch — the gap is dominated by routes outside F1–F6 scope (key list/info v2 internals) and structurally dead org-budget guards (call sites at lines 889 + 2310 + 985 + 1751 load the org without include_budget_table=True, so org.litellm_budget_table is None at guard time and the aggregate guard no-ops). Pinned as observed no-op behavior so a future fix that flips the flag turns these into reds. Zero source-code changes; pyproject.toml diff is empty; test_route_coverage.py stays green untouched; G3 grep guards still green; local wall-time 14 s for the full suite (no coverage), 22 s with coverage. G4 regression-replay protocol executed against three representative fix-PR parents ( |
||
|
ishaan-berri
|
203b529c9d
|
feat(azure): add speech transcription config support (#27482)
Co-authored-by: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com> Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> |
||
|
Yassin Kortam
|
2eab9ee2c0
|
perf: reduce per-request and per-chunk overhead across Anthropic streaming hot paths (#28289)
* perf: reduce per-request and per-chunk overhead across Anthropic streaming hot paths
- Introduce pure-text fast-path in `_build_complete_streaming_response` that collapses O(N) `content_block_delta` events into a single equivalent SSE event before conversion, eliminating per-output-token Pydantic `ModelResponseStream` construction; non-text streams (tool_use, thinking, citations) fall back to the unchanged legacy path
- Skip agentic streaming wrapper entirely when no callback overrides `async_should_run_agentic_loop`; the wrapper buffered every chunk and rebuilt the SSE response only to call hooks that all return `(False, {})` — a pure no-op for the default config
- Serialize request body once (`json.dumps`) for both the pre-call log input and the wire, instead of twice; avoids a full O(payload) scan per request, significant for long-context Claude Code histories
- Add fast path in `async_streaming_data_generator` that bypasses the per-chunk `async_post_call_streaming_hook` coroutine await, response-string materialization, and cost-injection call when no callback/guardrail/cost-injection is active (the default config)
- Resolve `_DD_STREAMING_TRACE_ENABLED` once at import time; eliminate per-chunk `NullSpan` context manager allocation when Datadog tracing is disabled (the default)
- Memoize `get_type_hints(AnthropicMessagesRequestOptionalParams)` with `@lru_cache(maxsize=1)` — resolves once per process instead of once per `/v1/messages` request (~80µs each)
- Hoist `cost_injection_active` out of the per-chunk loop in `chunk_processor`; eliminates repeated `getattr` + endpoint-type checks on every streamed byte chunk
- Extract `_build_passthrough_logging_result` from `_route_streaming_logging_to_handler` as a standalone static method to facilitate future off-loop dispatch
- Convert `async_sse_data_generator` from an `async for: yield` trampoline to a direct return of the underlying generator, removing one async-generator layer per streamed chunk
- Skip redundant `strip_empty_text_blocks_from_anthropic_messages` scan in `anthropic_messages_handler` when the async wrapper already sanitized (signalled via `_litellm_messages_presanitized` sentinel, popped before reaching provider params)
- Gate debug log `f-string` evaluation behind `isEnabledFor(DEBUG)` in both the streaming generator and the transformation layer to avoid serializing entire message payloads on every request at non-debug log levels
- Add benchmark script (`scripts/benchmark_anthropic_messages_perf.py`) with a local mock Anthropic SSE provider for reproducible TTFT and TPM measurement across commits/branches
- Add parity tests asserting fast-path and legacy-path produce byte-identical logged/billed payloads, plus unit tests for agentic hook detection, pre-serialized body reuse, and memoized key resolution
* perf: address greptile review for anthropic streaming hot path
- Bail to legacy in `_collapse_pure_text_chunks` when content_block_delta
events from different block indexes are observed without an intervening
flush. Anthropic sends blocks strictly sequentially, but defensive bail
prevents silent text-merging if the protocol ever interleaves.
- Replace leaf-class `__dict__` check for `async_post_call_streaming_hook`
in `_callback_capabilities` with a function-identity comparison that
walks the MRO. A vendor base class can carry the override and the
registered class can add nothing else; before this PR the hook was
unconditionally invoked, so an inherited-override miss would silently
drop the hook on the streaming path.
- Add unit tests for both behaviors.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(mypy): narrow model_name to str in cost-injection branch
The hoisted cost_injection_active flag in chunk_processor encodes the
`bool(model_name)` requirement but mypy can't track that invariant
through the local, so the per-chunk `_process_chunk_with_cost_injection(
chunk, model_name)` calls flagged Optional[str] vs str. Pin a typed
non-None local inside the cost-injection branch so mypy narrows
correctly without changing runtime behavior.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
|
||
|
Michael-RZ-Berri
|
3b2ce201d8
|
encrypt callback_vars in key/team metadata at rest (#27141)
Co-authored-by: Michael Riad Zaky <michaelr@Michaels-MacBook-Air.local> Co-authored-by: Yuneng Jiang <yuneng@berri.ai> |
||
|
Mateo Wang
|
492891cad8
|
CI: copy of #25177 (OCI GenAI: embeddings, streaming/reasoning fixes, model catalog) (#28223)
* fix(opentelemetry): JSON-serialize dict metadata fields for OTEL span attributes (#27451) (#27455)
Squash-merged by litellm-agent from Anai-Guo's PR.
* feat(dashscope): add embeddings and reranks(qwen3-rerank) support via OpenAI-compatible endpoint (#27508)
Squash-merged by litellm-agent from yimao's PR.
* fix(vertex_ai/gemini): raise BadRequestError when image_url or url fi… (#24550)
Squash-merged by litellm-agent from krisxia0506's PR.
* fix(vertex_ai): raise error on mid-stream 429/error chunks instead of silently swallowing (#23711)
Squash-merged by litellm-agent from krisxia0506's PR.
* fix: raise BadRequestError for file content blocks missing 'file' sub… (#24503)
Squash-merged by litellm-agent from krisxia0506's PR.
* Fix Gemini MIME detection for extensionless GCS URIs (#27278)
Squash-merged by litellm-agent from krisxia0506's PR.
* fix(vertex_ai/partner_models): drop unused vertexai SDK gate from count_tokens (closes #28084) (#28107)
Squash-merged by litellm-agent from voidborne-d's PR.
* feat(chart): add support for autoscaling behavior in HPA (#27990)
Squash-merged by litellm-agent from FabrizioCafolla's PR.
* feat(proxy): add blocked flag to models for pause/resume from the UI (#27927)
Squash-merged by litellm-agent from Cyberfilo's PR.
* fix: pass socket timeouts to Redis cluster clients (#27920)
Squash-merged by litellm-agent from tomdee's PR.
* Fix/cache token (#28009)
Squash-merged by litellm-agent from escon1004's PR.
* fix(deepseek): forward reasoning_content in multi-turn thinking mode conversations (#28080)
Squash-merged by litellm-agent from Divyansh8321's PR.
* fix(guardrails): return HTTP 400 instead of 500 for blocked requests (#27617)
* fix: reset org and tag budgets (#27326)
* reset org budgets
* reset tag budgets
---------
Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain>
* fix(ui): omit allowed_routes from key edit save when unchanged (#27553)
* fix(ui): omit allowed_routes from key edit save when unchanged
When a team admin opens Edit Settings on a key with key_type=AI APIs and
saves without changing anything, the UI re-sends the existing allowed_routes
value, which the backend's _check_allowed_routes_caller_permission gate
rejects for non-proxy-admins (LIT-2681).
Strip allowed_routes from the patch in handleSubmit when it deep-equals the
original keyData.allowed_routes. The backend treats absence as "leave alone,"
so no-op saves now succeed for non-admins. Admins explicitly editing the
field still send the new value.
* fix(ui): order-insensitive allowed_routes diff + cover null-original case
Address Greptile review:
- Switch the "is allowed_routes unchanged" check to a Set-based comparison so
a server-side reorder of the array doesn't register as a user edit and
re-trigger LIT-2681.
- Add two regression tests: (1) keyData.allowed_routes is null and the form
is untouched — patch should strip the field; (2) server returned routes in
a different order than the user originally entered — patch should still
recognize the value as unchanged.
* chore(ui): strip ticket refs and tighten comments in key edit fix
- Remove internal-tracker references from in-code comments
- Tighten the WHY comment in handleSubmit to two lines
- Drop redundant test-block comments — test names already describe the case
* fix(ui): annotate Set<string> generic in allowed_routes diff to fix tsc
* fix(guardrails): return HTTP 400 instead of 500 for guardrail-blocked requests
GuardrailRaisedException and BlockedPiiEntityError both lacked a
status_code attribute. When these exceptions reached the proxy
exception handler (getattr(e, 'status_code', 500)), the fallback
defaulted to HTTP 500 — making intentional guardrail blocks
indistinguishable from server errors and causing unnecessary client
retries.
Changes:
- Add status_code=400 (keyword-only) to GuardrailRaisedException
- Add status_code=400 (keyword-only) to BlockedPiiEntityError
- Update _is_guardrail_intervention() to recognize both exceptions
so downstream loggers record 'guardrail_intervened' instead of
'guardrail_failed_to_respond'
- Add 6 unit tests for default/custom status codes and getattr pattern
- Strengthen existing blocked-action test with status_code assertion
Fixes #24348
---------
Co-authored-by: Michael-RZ-Berri <michael@berri.ai>
Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
* fix(router/proxy): address Greptile P1+P2 review comments on PR #28161
- router: raise ServiceUnavailableError (503) instead of RouterRateLimitErrorBasic (429)
when a specifically-addressed deployment is administratively blocked; 429 misleads
retry-enabled clients into spinning forever against a paused model
- proxy_server: compute get_fully_blocked_model_names() once before both branches in
model_list() instead of duplicating the call in each branch
- deepseek: upgrade silent debug log to warning when injecting placeholder
reasoning_content so callers are clearly notified of degraded multi-turn quality
- tests: update two blocked-deployment assertions to expect ServiceUnavailableError
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: address bug detection findings (cache token order, mutable defaults)
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix: address bugs in async pass-through, anthropic cache token detection, rerank tests
- async_get_available_deployment_for_pass_through: enforce blocked check on specific deployments
- cost_calculator: detect anthropic-style usage by attribute presence (not truthiness) to avoid mixing OpenAI cached_tokens into anthropic normalization when read=0
- dashscope rerank tests: pass request to httpx.Response constructions for consistency
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix code qa
* fix(vertex_ai/gemini): strip MIME parameters from GCS contentType
GCS object metadata's contentType field can include parameters such as
'text/html; charset=utf-8'. Strip them in _apply_gemini_mime_type_aliases
so downstream get_file_extension_from_mime_type sees a bare MIME type.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(vertex_ai/gemini): clarify mime-type error message string concatenation
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* feat(oci): add embeddings, fix streaming/reasoning, expand model catalog
- Add OCIEmbedConfig with full Cohere embed support (7 models, batch up to 96)
- Fix sync streaming: split SSE events on \n\n before JSON parsing
- Fix reasoning models (Gemini 2.5, xAI Grok): make completionTokens and message
optional in OCIResponseChoice to handle max_tokens exhausted on reasoning
- Fix compartment_id resolution in chat transform to use resolve_oci_credentials
- Fix tool call id: make OCIToolCall.id optional, generate UUID fallback for
providers (Google via OCI) that omit it
- Add OCI_KEY env var support for inline PEM keys
- Fix datetime.utcnow() deprecation in request signing
- Expand model catalog: 29 OCI models including Llama 4, Gemini 2.5, xAI Grok,
Cohere Command A, and all Cohere embed variants
- Add 37 live integration tests: sync/async completions for Meta/Google/xAI/Cohere,
sync/async embeddings, tool use across all vendors, streaming, env var auth
- Add 23 embed unit tests covering all transform and validation paths
* fix(oci): remove dead OCI elif branch in utils.py, align async split_chunks with sync version
* test(oci): add unit tests for split_chunks fix and no-duplicate-OCI-branch guard
* fix(oci): address remaining bugs from issue #25082 — streaming signed body, Cohere stop sequences, hardcoded defaults
- Bug 1: sync and async streaming paths now use signed_json_body when provided
instead of re-serializing data with json.dumps() — the OCI RSA-SHA256 signature
covers the exact request body bytes, so re-serializing produces an invalid sig
- Bug 3: Cohere stop sequences now map to 'stopSequences' (was incorrectly 'stop')
- Bug 4: removed hardcoded Cohere defaults (maxTokens=600, temperature=1, topK=0,
topP=0.75, frequencyPenalty=0) that silently overrode user intent on every call
- Added 6 unit tests covering all three fixes
* fix(oci): comprehensive code quality pass — bugs, tests, schema accuracy
- Fix Cohere tool call IDs (was always call_0; now UUID per call)
- Fix TOOL_CALL finish reason mapping in both sync and streaming paths
- Fix Cohere stop parameter mapping (stop → stopSequences)
- Remove hardcoded Cohere defaults (maxTokens/topK/topP/frequencyPenalty)
- Fix content[0] safety guard against empty content arrays
- Fix streaming signed body used consistently (not re-serialized)
- Raise OCIError (not bare Exception/ValueError) throughout
- Centralize OCI_API_VERSION constant; import uuid at module level
- Fix embed get_complete_url to strip trailing slashes from api_base
- Fix OCIEmbedResponse schema: add inputTextTokenCounts (actual OCI field)
- Fix embed usage computed from inputTextTokenCounts (sum of per-input counts)
- Fix Cohere toolCallId included in tool result messages
- Add OCIToolCall.id as Optional (absent in Google/xAI streaming chunks)
- Update tests to reflect correct behavior (no hardcoded defaults, UUID ids,
deferred credential validation, OCIError vs ValueError, real response schema)
* test(oci): move integration tests to tests/llm_translation/
Addresses greptile P1: tests/test_litellm/ is for mock-only unit tests
(make test-unit target). Real-network OCI tests now live in the correct
location alongside other provider integration tests.
* fix(oci): align types and transformation with official OCI SDK
- Remove OCIVendors.GEMINI — apiFormat="GEMINI" is invalid; all non-Cohere
models use apiFormat="GENERIC"
- Add toolChoice, logitBias, logProbs to OCIChatRequestPayload so params
present in the mapping are no longer silently dropped by Pydantic
- Exclude n→numGenerations from Cohere param map (not a Cohere API field)
- Fix CohereToolResult: change callId/result to call/outputs matching
the OCI SDK's CohereToolResult structure
- Fix CohereToolMessage: replace non-existent toolCallId with toolResults
list; update adapt_messages_to_cohere_standard to build proper tool-result
history entries by resolving tool call name+params from preceding assistant
messages
- Map generic-model stream finish reasons to OpenAI convention
(COMPLETE→stop, MAX_TOKENS→length, TOOL_CALLS→tool_calls), consistent
with the existing Cohere streaming path
- Add optional id field to OCIEmbedResponse so valid API responses
carrying an id are not rejected by the Pydantic model
* fix(oci): use 'output' key in Cohere tool result outputs (matches reference impl)
* fix(oci): port schema/type utilities from langchain-oracle reference impl
- Add resolve_oci_schema_refs: inline $ref/$defs — OCI rejects JSON Schema refs
- Add resolve_oci_schema_anyof: flatten Optional[T] anyOf (Pydantic v2 emits these)
- Add sanitize_oci_schema: strip title, normalise null types, ensure array items
- Add OCI_JSON_TO_PYTHON_TYPES: Cohere expects Python type names (str/int/float),
not JSON Schema names (string/integer/number)
- Add enrich_cohere_param_description: embed enum/format/range/pattern constraints
into description since CohereParameterDefinition has no dedicated fields
- Apply all of the above in adapt_tool_definitions_to_cohere_standard and
adapt_tool_definition_to_oci_standard
- Fix toolChoice conversion: map OpenAI string ('auto','none','required') to OCI
dict form ({"type":"AUTO"} etc.) — the API rejects plain strings
- Update unit test expectations to match correct Python type names and enriched
descriptions
* refactor(oci): split transformation.py into cohere.py and generic.py
transformation.py was 1 243 lines doing too many jobs. Split along the
same boundaries as the langchain-oracle reference (providers/cohere.py,
providers/generic.py):
chat/cohere.py — Cohere message/tool building, response + stream parsing
chat/generic.py — Generic message/tool building, response + stream parsing
transformation.py — thin OCIChatConfig orchestrator + OCIStreamWrapper
Public symbols (OCIChatConfig, OCIStreamWrapper, adapt_messages_to_*,
OCIRequestWrapper, version, …) remain importable from transformation.py
for backward compatibility. OCIStreamWrapper gains delegating shims for
_handle_cohere_stream_chunk and _handle_generic_stream_chunk so existing
test call sites keep working unchanged.
transformation.py: 1 243 → 620 lines
* refactor(oci): principal-level code quality pass
- Remove _extract_text_content duplication — single definition in cohere.py,
imported where needed; instance method on OCIChatConfig eliminated
- Move cryptography imports to module level with _CRYPTOGRAPHY_AVAILABLE flag
and _require_cryptography() guard; no more re-import on every signing call
- Move litellm version import to module level via litellm._version; remove
inline import inside validate_oci_environment
- sign_with_manual_credentials now returns Tuple[dict, bytes] matching
sign_with_oci_signer — asymmetry eliminated, Optional[bytes] guards removed
throughout stream wrappers (signed_json_body: bytes = b"")
- Rename _openai_to_oci_cohere_param_map → openai_to_oci_cohere_param_map
for consistency with openai_to_oci_generic_param_map
- Remove double-key bug in map_openai_params where responseFormat was stored
under both OCI and OpenAI key names simultaneously
- Remove delegating shims (adapt_messages_to_cohere_standard,
adapt_tool_definitions_to_cohere_standard, _handle_generic_stream_chunk)
from OCIChatConfig/OCIStreamWrapper; tests now import directly from
cohere.py and generic.py where symbols live
- Trim __all__ to 7 genuine public symbols; remove the 13-symbol list that
existed only to support test imports
- Collapse per-model integration test classes into pytest.mark.parametrize;
CHAT_MODELS list is the single source of truth for model-specific config
- Black + Ruff clean across all OCI files
* fix(oci): address PR review findings
- types/llms/oci.py: add "TOOL_CALL" to CohereChatResponse.finishReason
Literal so Pydantic does not raise ValidationError on non-streaming
Cohere tool-use calls (Greptile P1)
- test_oci_cohere_tool_calls.py: add test covering TOOL_CALL finish reason
- model_prices_and_context_window.json: remove 6 duplicate oci/cohere.embed-*
keys that were silently overridden by the more complete entries already
present in the file (Greptile P1)
- common_utils.py: move OCI_API_VERSION here from chat/transformation.py
so embed/transformation.py does not need to import chat/transformation;
change Protocol stub body from ... to pass (CodeQL "statement no effect");
add comment to sha256_base64 clarifying it implements OCI HTTP signing
spec, not password hashing (CodeQL false positive)
- chat/transformation.py: import CustomStreamWrapper from
litellm_core_utils.streaming_handler instead of litellm.utils to reduce
import cycle depth (CodeQL cyclic import)
- chat/cohere.py, chat/generic.py: import Usage and
ChatCompletionMessageToolCall from litellm.types.utils instead of
litellm.utils for the same reason
- embed/transformation.py: import OCI_API_VERSION from common_utils
instead of chat/transformation (removes the embed→chat import edge)
* test(oci): add unit tests to improve patch coverage
- test_oci_common_utils.py (new): covers sha256_base64, build_signature_string,
OCIRequestWrapper.path_url, resolve_oci_credentials, get_oci_base_url,
validate_oci_environment, sign_with_oci_signer error paths, sign_oci_request
routing, load_private_key_from_file error paths, resolve_oci_schema_refs
(including circular ref and external $ref), resolve_oci_schema_anyof,
sanitize_oci_schema (all branches), enrich_cohere_param_description
- test_oci_generic_chat.py (new): covers content-message error paths (non-dict
item, unsupported type, non-string text, invalid image_url), tool-call
validation error paths, adapt_messages_to_generic_oci_standard error paths,
handle_generic_response (None message, text content, tool calls),
handle_generic_stream_chunk (finish reasons, streaming tool calls),
OCIStreamWrapper non-string chunk error
- test_oci_chat_transformation.py: add error paths for validate_environment
(empty messages), transform_request (missing compartment_id, Cohere without
user messages), transform_response (error key), map_openai_params
(unsupported param with and without drop_params), tool_choice string mapping
- test_oci_cohere_tool_calls.py: add edge cases for stream chunk finish
reasons (TOOL_CALL, MAX_TOKENS, unknown), _extract_text_content with
non-dict list items and non-string input,
adapt_messages_to_cohere_standard with malformed JSON tool arguments
* fix(oci): rename supports_streaming to supports_native_streaming in model prices
The JSON schema for model_prices_and_context_window.json uses
`supports_native_streaming` (not `supports_streaming`) and has
`additionalProperties: false`. Rename the field across all OCI
entries to pass the schema validation test.
* test(oci): add 67 tests targeting uncovered happy paths for coverage
Boost patch coverage on the four lowest-coverage OCI files:
- common_utils.py: sign_with_manual_credentials (oci_key / oci_key_file
paths), sign_oci_request routing, _require_cryptography
- generic.py: adapt_messages_to_generic_oci_standard (all roles),
adapt_tool_definition_to_oci_standard, adapt_tools_to_openai_standard,
handle_generic_stream_chunk text/finish-reason paths
- cohere.py: _extract_text_content, adapt_messages_to_cohere_standard
(all roles including tool results), handle_cohere_response /
handle_cohere_stream_chunk all finish-reason branches
- transformation.py: get_vendor_from_model, OCIChatConfig._get_optional_params
(toolChoice string→dict, responseFormat, tools for both vendors),
transform_request for GENERIC model, get_sync/async_custom_stream_wrapper
with mocked HTTP, OCIStreamWrapper.chunk_creator happy paths
* fix(oci): suppress CodeQL false positive on sha256_base64 (OCI HTTP signing, not password hashing)
* fix(oci): remove 6 duplicate model price entries and reconcile conflicting values
Six OCI chat model keys appeared twice in model_prices_and_context_window.json
with conflicting pricing/context data (JSON parsers silently discard the first).
Remove the first-occurrence entries and update the surviving entries:
- meta.llama-4-maverick / llama-4-scout: keep updated entries (free preview
pricing, larger context windows, vision support)
- meta.llama-3.1-70b: keep original pricing, restore supports_native_streaming
- google.gemini-2.5-{flash,pro,flash-lite}: keep OCI pricing page values,
restore supports_native_streaming
* fix(oci): route GPT-5 family to maxCompletionTokens
GPT-5 / GPT-5-mini / GPT-5-nano / GPT-5.5 on OCI reject "maxTokens"
with HTTP 400:
Invalid 'maxTokens': Unsupported parameter: 'maxTokens' is not
supported with this model. Use 'maxCompletionTokens' instead.
(Same convention as OpenAI's reasoning-API contract.)
Add a model-aware rename in OCIChatConfig._get_optional_params so the
request payload uses maxCompletionTokens when the model id starts with
openai.gpt-5. Regular Llama / Cohere / Gemini / GPT-4.x continue to use
maxTokens unchanged.
Also widen OCIChatRequestPayload to carry the new optional field so it
survives Pydantic serialization.
Verified live against OCI us-chicago-1:
- openai.gpt-5, gpt-5-mini, gpt-5-nano, gpt-5.5 all return 200
- Full feature sweep on gpt-5.5 (basic, system, multi-turn, streaming,
tools, usage) all green
- meta.llama-3.3-70b-instruct still uses maxTokens (no regression)
4 new unit tests cover the helper, the routing in both pre- and
post-translation states, and Pydantic serialization.
* ci(oci): fix CI failures — black formatting + recursive_detector ignore
- Run black on litellm/llms/oci/common_utils.py + 3 OCI test files
that drifted out of black-compliance during the rebase.
- Add the three bounded recursive functions in oci/common_utils.py
(`_resolve`, `resolve_oci_schema_anyof`, `sanitize_oci_schema`) to
the recursive_detector IGNORE_FUNCTIONS list. All three are bounded:
`_resolve` uses a `resolving_stack` cycle guard; the other two are
bounded by JSON-schema tree depth (no cycles in well-formed input),
matching the pattern of the existing OCI/Vertex schema walkers
already on the list.
* fix(oci): silence MyPy errors in cohere.py — typed-dict access
Two errors flagged by `lint` CI:
llms/oci/chat/cohere.py:73: "object" has no attribute "__iter__"
llms/oci/chat/cohere.py:119: No overload variant of "get" of "dict"
matches argument types "object", "CohereToolCall"
Both stem from `msg.get("tool_calls")` / `msg.get("tool_call_id")`
returning `object` per the AllMessageValues TypedDict union. Bind to
`Any` locally for the iteration and coerce the lookup key with `str()`,
removing the now-unused `# type: ignore` on those lines.
No behaviour change — pure type-narrowing for the type checker.
* fix(oci): silence CodeQL py/weak-sensitive-data-hashing on sha256_base64
CodeQL's taint analysis traces request bodies back to environment-loaded
secrets and flags `hashlib.sha256(body).digest()` as
`py/weak-sensitive-data-hashing` — even though SHA-256 is the algorithm
mandated by the OCI HTTP request signing spec for the
`x-content-sha256` header (not a password/secret hash).
The previous suppression used legacy `# lgtm[...]` syntax which the
modern CodeQL action ignores. Switch to Python's standard
`hashlib.sha256(..., usedforsecurity=False)` (Python 3.9+) which CodeQL
honours as a non-security declaration. Behaviour unchanged.
* feat(oci): add reasoning_effort passthrough — only true missing primitive
OCI's GenericChatRequest exposes a reasoningEffort field
(NONE/MINIMAL/LOW/MEDIUM/HIGH) that's the single biggest cost knob for
reasoning-capable models on the service:
- GPT-5 family
- Gemini 2.5
- Grok reasoning variants (3-mini, 4-fast, 4.20)
- Cohere Command-A-Reasoning
Setting reasoning_effort=LOW typically cuts reasoning-token spend 5-10×
vs the default. Without exposing this, litellm users had no way to tune
cost-vs-quality on these models.
The other GenericChatRequest fields (verbosity, parallel_tool_calls,
logit_bias, n, metadata, web_search_options, prediction) are not
exposed because they are not missing primitives — they either duplicate
prompt-engineering, framework-level controls, or are too niche to
justify the maintenance surface. We only ship what users genuinely
can't accomplish another way.
Excluded from the Cohere v1 param map: CohereChatRequest has no
reasoningEffort field, and Cohere reasoning models
(cohere.command-a-reasoning) use COHEREV2 which is a separate request
type not covered by this PR.
Verified live: GPT-5.5 + reasoning_effort="HIGH" sends
{"reasoningEffort": "HIGH"} on the wire and OCI accepts the request.
* feat(oci): reasoning_effort + reasoning_tokens for OCI GenAI
Three small additions for OCI reasoning models, requested by users
testing the PR in production fork builds:
1. **reasoning_effort param mapping (GENERIC vendors).** OCI expects
uppercase levels ("LOW"/"MEDIUM"/"HIGH"/"NONE") on `reasoningEffort`,
but OpenAI-compatible clients send lowercase. Mapped + uppercased in
`_get_optional_params`. Marked unsupported on Cohere V1/V2 since OCI
Cohere has no reasoning models (avoids Pydantic validation failure
on CohereChatRequest).
2. **"disable" → "NONE" mapping.** OpenAI uses "disable" to turn off
reasoning; OCI uses "NONE". Without this, callers get a 400.
3. **reasoning_tokens propagated to Usage.** OCI returns
`completionTokensDetails.reasoningTokens` but it wasn't being passed
to LiteLLM's Usage object. Now flows through to
`Usage.completion_tokens_details.reasoning_tokens` so callers can
track reasoning token consumption for cost/observability.
Tests: 7 new unit tests in TestOCIReasoningEffort covering upper/lower
case, "disable"→"NONE", Cohere drop/raise paths, and reasoning_tokens
extraction (with and without completionTokensDetails). 5 new live
integration tests against xai.grok-3-mini in us-chicago-1 verifying the
full request/response loop end-to-end. Existing
test_transform_response_simple_text assertion that
completion_tokens_details was None has been updated to assert
reasoning_tokens flows through.
Verified live on xai.grok-3-mini: reasoning_effort=low → OCI accepts
"LOW", returns reasoningTokens=316 in usage. reasoning_effort=disable
→ OCI accepts "NONE". Full suite: 370/370 unit + 51/51 integration.
* fix(codeql): re-scope py/weak-sensitive-data-hashing exclusion to OCI signing file
CodeQL's taint analysis re-fires the `py/weak-sensitive-data-hashing`
alert at `litellm/llms/oci/common_utils.py:103` whenever upstream code
paths into the OCI signing module change (touching `transformation.py`
opens new flow paths that CodeQL re-evaluates from scratch). The
`hashlib.sha256(..., usedforsecurity=False)` declaration silences the
direct-call form of the query but not the taint-flow form.
SHA-256 here is mandated by the OCI HTTP signing specification for the
x-content-sha256 content-integrity header — not for password storage:
https://docs.oracle.com/en-us/iaas/Content/API/Concepts/signingrequests.htm
CodeQL has no per-query path filter and GitHub Code Scanning ignores
inline lgtm/codeql comments, so path-ignoring this single ~560-line
signing utility file is the narrowest available suppression. All other
files retain full coverage of py/weak-sensitive-data-hashing — including
litellm/proxy/utils.py where the rule legitimately applies.
This restores the NEUTRAL CodeQL state the PR had on prior commits
(see `2111c98af7` for the same approach on the previous branch
evolution that the cherry-pick was rebased onto a different baseline).
* fix(oci): drop duplicate text on Cohere streaming terminal chunk
OCI Cohere's terminal SSE event re-sends the full assembled response in
`text` alongside a populated `chatHistory`. Emitting that text as another
delta concatenates the entire response onto the already-streamed output
(e.g. "How can I help?How can I help?").
Use `chatHistory is not None` as the discriminator for the consolidated
terminal event — `finishReason` is a weaker signal that could in principle
appear on a non-consolidated chunk. The two coincide today; this preserves
correctness if OCI ever ships finishReason on an incremental chunk.
Adds a live-OCI integration regression test that compares streamed vs
non-streamed length and asserts the response prefix appears only once.
Verified to fail under the previous code with the exact reported
reproduction: 'Hello! How can I help you today?Hello! How can I help you today?'.
Reported by @gotsysdba on PR #25177.
* fix(oci): buffer SSE stream across HTTP read boundaries
The old split_chunks helper split each individual HTTP read on "\n\n",
which assumed SSE event boundaries always aligned with read boundaries.
In practice the OCI streaming endpoint delivers events that may:
- straddle two reads (chunk_creator gets a truncated JSON and crashes)
- arrive separated by a single "\n" instead of "\n\n"
- share a read with multiple complete events
Replace the inline split with module-level helpers _iter_sse_events
(sync) / _aiter_sse_events (async) that maintain a buffer across reads,
split on any newline, and yield only complete "data:" lines.
Add 25 regression tests covering event-split-across-reads, tiny-chunk
reads, single-newline separators, keepalive/comment lines, trailing
partial events flushed at EOF, "\r\n" line endings, and an end-to-end
smoke test that feeds an awkwardly-chopped payload through the splitter
into OCIStreamWrapper.chunk_creator.
Reported by John Lathouwers.
* test(oci): repoint TestOCIKeyNormalization to sign_with_manual_credentials
The signing helper moved from OCIChatConfig._sign_with_manual_credentials
to a module-level sign_with_manual_credentials in common_utils.py. Four
tests in TestOCIKeyNormalization still called the old method:
- 2 failed outright with AttributeError
- 2 passed by accident because they used pytest.raises(Exception),
which happily caught the AttributeError instead of exercising the
intended OCIError path
Repoint all four to the new module-level function so they exercise the
actual oci_key type-validation branch.
* fix(oci): validate oci_region before URL interpolation to prevent SSRF
Anchor oci_region to ^[a-z][a-z0-9-]{0,30}[a-z0-9]$ inside get_oci_base_url
so user-supplied regions that would redirect the signed request to an
attacker-controlled host (e.g. 'evil.com/#') fail with HTTP 400 before
the URL or signature is built. Empty string still falls back to the
us-ashburn-1 default, so existing callers are unaffected.
* test(audio): skip when gpt-4o-audio-preview is unavailable upstream
OpenAI retired `gpt-4o-audio-preview` (404 model_not_found in CI as of
2026-05-19), and the existing try/except in these tests only re-raised
on 'openai-internal' errors. Other exceptions were silently swallowed,
so the next line ran with an unbound `response`/`completion` and
failed with an unrelated UnboundLocalError that masked the real cause.
Extend the skip condition to also cover model_not_found / 'does not exist'
so the suite reports the upstream outage cleanly, matching the pattern
used in
|
||
|
milan-berri
|
7270f723de
|
fix(mcp): forward upstream initialize instructions on cold gateway init (#28231)
Some checks are pending
Unit Tests: Proxy DB Operations / assert-shard-coverage (push) Waiting to run
Unit Tests: Proxy DB Operations / auth-checks (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / budgets (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / custom-logging (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / db-and-spend (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / endpoints-and-responses (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / guardrails-hooks (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / jwt-and-keys (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / key-generation (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / logging-misc (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / proxy-runtime (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / proxy-server-core (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / schema-migration (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / proxy-utils (push) Blocked by required conditions
Unit Tests: Security / security (push) Waiting to run
Prefetch upstream InitializeResult.instructions before merging gateway initialize options when YAML/DB do not set instructions, so clients receive upstream server text on the first MCP initialize without list_tools. Co-authored-by: Cursor <cursoragent@cursor.com> |
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|
Sameer Kankute
|
f35e7eb2f6
|
feat(guardrails): add Microsoft Purview DLP guardrail (#24966)
* feat(guardrails): add Microsoft Purview DLP guardrail
* fix(guardrails/purview): raise_for_status on HTTP errors, cap scope cache, reuse executor
* fix(guardrails/purview): propagate litellm_call_id as correlation_id to Purview
* chore: fixes
* refactor(guardrails): delegate get_user_prompt to get_last_user_message
PurviewGuardrailBase duplicated AzureGuardrailBase (and OpenAIGuardrailBase)
user-prompt extraction. The same logic already lived in
common_utils.get_last_user_message; wire guardrail bases to that helper,
fix the helper docstring, and drop its redundant self-import of
convert_content_list_to_str.
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* fix(purview): make protection scope cache true LRU on hits
OrderedDict.get() does not update insertion order; call move_to_end on
TTL-valid cache hits so popitem(last=False) evicts least-recently-used
users instead of FIFO by first insert.
Add a regression test with a small max cache size.
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* Fix mypy
* fix(guardrails/purview): harden user-id resolution and broaden DLP text
Prefer API key and proxy-injected metadata over client metadata for Entra
identity. Scan full message transcript pre-call and all completion choices
post-call. Align logging-only hook with the same user-id rules.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(guardrails/purview): scan /v1/completions prompt and TextChoices
Normalize text-completion prompts (string or list of strings); skip token-id-only
prompts. Run post-call DLP on TextCompletionResponse choices. Extend logging_only
hook for text_completion. Add tests and completion_prompt_to_str helper.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(purview-dlp): return data after DLP pass; per-call executor; dedupe text extraction
async_pre_call_hook now returns the request dict after a successful check so
callers match skip-path behavior. logging_hook uses a fresh ThreadPoolExecutor
per invocation like Presidio to avoid single-worker starvation. Response text
extraction is centralized in _completion_response_text_parts.
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* fix(purview): fix LRU cache refresh position and add Responses API scanning
Two fixes to the Microsoft Purview DLP guardrail:
1. LRU cache bug (base.py): When a stale scope cache entry was re-fetched,
the assignment updated the value but
Python's OrderedDict.__setitem__ preserves the original insertion order for
existing keys. This left the refreshed entry near the front of the dict,
making it the first candidate for LRU eviction via popitem(last=False).
Fix: call move_to_end(user_id) after every write to an existing key.
2. Responses API coverage gap (purview_dlp.py): Requests to /v1/responses use
an 'input' field instead of 'messages' or 'prompt', so the pre-call hook
returned without scanning the content. Similarly, post-call hook did not
handle ResponsesAPIResponse.output. Fix: add _responses_api_input_to_str()
helper and handle 'responses'/'aresponses' call types in async_pre_call_hook,
async_post_call_success_hook (via _completion_response_text_parts), and
async_logging_hook.
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* fix(purview): message separator, non-blocking logging_hook, TextChoices type error
Three bugs fixed in the Microsoft Purview DLP guardrail:
1. get_prompt_text_for_dlp message separator (base.py)
- Previously called get_str_from_messages() which concatenated all message
texts with NO separator, so 'end of msg1' + 'start of msg2' became
'end of msg1start of msg2'.
- Now joins per-message text with '\n\n' via convert_content_list_to_str(),
preserving DLP pattern detection accuracy across message boundaries.
2. logging_hook blocking the event loop thread (purview_dlp.py)
- Previously called future.result() which blocked the calling thread
(often the event loop thread) for the entire round-trip of two sequential
Microsoft Graph API calls (_compute_protection_scopes + _process_content).
- Now fires and forgets: when called inside a running loop, schedules the
coroutine with loop.create_task(); otherwise spawns a daemon thread.
Returns (kwargs, result) immediately in both cases.
- Removes unused concurrent.futures.ThreadPoolExecutor import; adds threading.
3. Incompatible assignment type error (purview_dlp.py:180)
- mypy inferred 'choice' as TextChoices from the first loop body, then
flagged the assignment in the second loop as incompatible with Choices.
- Fixed by using distinct loop variable names: text_choice (TextChoices) and
chat_choice (Choices).
Tests: 7 new tests added covering the separator fix (TestGetPromptTextForDlp)
and the non-blocking logging_hook (TestLoggingHookNonBlocking).
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* fix(purview): suppress API errors in logging-only mode and scan tool-call arguments
Three issues fixed:
1. _check_content except block re-raised unconditionally even when
block_on_violation=False. The docstring promised 'log only - do not
raise' but network/API errors always propagated. Fixed by checking
block_on_violation before re-raising; when False, log a warning and
continue.
2. async_logging_hook used a single try/except wrapping both the prompt
and response audit calls. When the first _check_content (uploadText)
raised due to an API error the second call (downloadText) was silently
skipped. Fixed by giving each audit call its own try/except so both
always run independently.
3. convert_content_list_to_str() only reads message.content, so
tool_calls[].function.arguments and function_call.arguments were
invisible to the Purview pre-call and post-call scans. An authenticated
caller could embed sensitive text in tool-call arguments and bypass DLP.
Fixed by:
- Adding PurviewGuardrailBase._extract_tool_call_args_from_message()
which handles both dict and object-style messages, covering both
tool_calls[] arrays and the legacy function_call field.
- Updating get_prompt_text_for_dlp() to include those arguments
alongside message content (request/prompt path).
- Changing _completion_response_text_parts() from @staticmethod to an
instance method and adding tool-call argument extraction for
ModelResponse choices (response path).
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* chore(ui): restructure pre-built Next.js output to directory-based routing
Flat page files (e.g. guardrails.html) replaced by directory-based
index.html equivalents (e.g. guardrails/index.html) matching the
Next.js App Router output format.
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* fix(purview): comprehensive security hardening — identity spoofing, streaming bypass, token-id gap
Four security issues addressed:
1. end_user_id kwargs fallback missing in _resolve_user_id_from_logging_kwargs
user_id already fell back to kwargs.get("user_api_key_user_id") when absent
from metadata, but end_user_id only checked md.get("user_api_key_end_user_id")
with no kwargs-level fallback. Added or kwargs.get("user_api_key_end_user_id").
2. Streaming responses bypassed post_call blocking
async_post_call_success_hook only runs on assembled non-streaming responses.
For streaming requests the proxy already delivered all content before the
hook ran, so raising HTTPException there had no effect. Added
async_post_call_streaming_iterator_hook which buffers the entire stream,
assembles it via stream_chunk_builder, runs the Purview DLP check, and only
then re-yields chunks via MockResponseIterator. If a violation is detected the
exception is raised before any bytes reach the client. The proxy automatically
skips async_post_call_success_hook for guardrails that define this method,
preventing duplicate scans.
3. Caller-controlled Purview user identity in blocking modes
When a LiteLLM API key has no bound user_id the guardrail fell back to
metadata[user_id_field], which is supplied by the caller. A caller could set
this to any Entra object ID whose Purview policies are more permissive and
bypass DLP. Added _resolve_trusted_user_id() that only returns identities
from the proxy auth system (user_api_key_dict.user_id, end_user_id, or
proxy-injected metadata["user_api_key_user_id"]). Added
_resolve_user_id_for_blocking() used by all blocking-mode hooks: tries
trusted sources first; if only caller-supplied is available, logs a
SECURITY WARNING and still proceeds (backward compat); if nothing resolves,
skips with a warning.
4. Token-id prompt DLP bypass
When /v1/completions received a pure token-id array prompt,
completion_prompt_to_str() returned None and the pre_call hook silently
skipped the Purview scan. An authenticated caller could tokenize blocked
text and send it without DLP evaluation. The hook now detects this case
(raw_prompt present but prompt_text None) and logs a WARNING while letting
the request pass through — token-id payloads are opaque at the text layer
and cannot be scanned. This makes the gap explicit rather than silent.
Tests: 94 total, all passing.
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* Revert "chore(ui): restructure pre-built Next.js output to directory-based routing"
This reverts commit
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yuneng-jiang
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574ee7526d
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test(streaming): tolerate Vertex 429 wrapped in MidStreamFallbackError (#28669)
Streaming 429s are wrapped in MidStreamFallbackError so the Router can fall back; the existing 'except litellm.RateLimitError: pass' in test_vertex_ai_stream no longer matches, causing the generic pytest.fail branch to fire when upstream Vertex returns 429. Add a sibling except for MidStreamFallbackError that only swallows it when e.original_exception is a RateLimitError, so unrelated streaming failures still fail the test. |
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milan-berri
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1b141bc588
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fix(bedrock): decouple STS region from Bedrock aws_region_name (#28245)
* fix(bedrock): decouple STS region from Bedrock aws_region_name STS AssumeRole now resolves signing region from aws_sts_endpoint (parsed host) or AWS_REGION/AWS_DEFAULT_REGION instead of aws_region_name, fixing air-gapped cross-region Bedrock setups and endpoint/signature mismatches. Co-authored-by: Cursor <cursoragent@cursor.com> * test(bedrock): add regression coverage for _build_sts_client_kwargs Parametrize _resolve_sts_region and _build_sts_client_kwargs matrix cases, and assert IRSA/web-identity paths use aligned STS endpoint and region_name. Co-authored-by: Cursor <cursoragent@cursor.com> * refactor(bedrock): tighten STS region helpers and drop redundant web-identity endpoint synthesis Co-authored-by: Cursor <cursoragent@cursor.com> * test(bedrock): cover FIPS, GovCloud, and China STS endpoints Addresses greptile P2: regex sts(?:-fips)? supported sts-fips hosts but was not exercised by the parametrized parse test. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Krrish Dholakia
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a3c953ed4e
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style: apply black formatting to fix lint CI (LIT-3274) (#28639) (#28641)
* fix(bedrock): strip bedrock/ prefix and URL-encode ARNs in get_bedrock_model_id for invoke path
The invoke path (used by /v1/messages → Anthropic SDK / Claude Code) called
get_bedrock_model_id() which, when falling back to the raw model string, did
not strip the 'bedrock/' routing prefix and did not URL-encode ARNs.
For a model like:
bedrock/arn:aws:bedrock:us-east-1:<ACCOUNT>:inference-profile/global.anthropic...
the URL built was:
/model/bedrock/arn:aws:bedrock:…/invoke-with-response-stream ❌
Bedrock returned a JSON error body. LiteLLM's AWSEventStreamDecoder passed
those bytes into botocore's EventStreamBuffer which expects binary event-stream
framing. Checksum validation failed on the JSON prelude (0x223a7b22 == ':{"')
producing a misleading botocore.eventstream.ChecksumMismatch instead of the
actual Bedrock error.
Fix: strip 'bedrock/' (and 'invoke/') routing prefix from model string, then
URL-encode if the result is an ARN — matching what the converse path already
does in converse_handler.py.
Fixes: LIT-3274
* fix(bedrock): use strip_bedrock_routing_prefix to handle compound prefixes
Address greptile review: the original fix used a loop with break, so
bedrock/invoke/arn:... only stripped bedrock/ leaving invoke/arn:...
which is not an ARN → fell through to .replace('invoke/','',1) →
bare unencoded ARN → same malformed-URL bug.
strip_bedrock_routing_prefix() iterates without break, correctly
stripping bedrock/ then invoke/ in sequence. Also adds test case
for the compound-prefix scenario.
* style: apply black formatting to fix lint CI (LIT-3274)
---------
Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai>
Co-authored-by: LiteLLM Bot <bot@berri.ai>
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milan-berri
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9600fda2cc
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fix(sagemaker): send native Cohere embed payload to Cohere SageMaker endpoints (#28613)
* fix(sagemaker): use Cohere embed payload for Marketplace endpoints
SageMaker embedding only special-cased Voyage; every other endpoint received
HuggingFace TGI `{"inputs": [...]}`. AWS Marketplace Cohere containers expect
the native Cohere embed payload (`texts`, `input_type`) and reject the HF
shape with `422 EmbedReqV2.inputs is of type string but should be of type
Object`.
Add `SagemakerCohereEmbeddingConfig` that reuses Bedrock/Cohere request and
response transforms, and route SageMaker endpoint names containing `cohere`
or a Cohere embed model fragment (`embed-multilingual`, `embed-english`,
`embed-v3`, `embed-v4`) to it. Supports `input_type`, `dimensions`, and
`encoding_format`. Voyage and HuggingFace SageMaker endpoints are unchanged.
Co-authored-by: Cursor <cursoragent@cursor.com>
* refactor(sagemaker): simplify cohere detection and align with file conventions
- Detect Cohere SageMaker endpoints with a single `"cohere" in model.lower()`
check, mirroring the existing Voyage branch instead of a separate helper
function and marker constant.
- Drop instance caches of sub-configs; instantiate `BedrockCohereEmbeddingConfig`
/ `CohereEmbeddingConfig` per call to match the existing pattern in
`BedrockCohereEmbeddingConfig._transform_request`.
- Match `SagemakerEmbeddingConfig`'s signatures, defaults, and `Any` typing for
`logging_obj`; collapse the input-normalization helper inline.
- Inline `transform_embedding_response` input lookup; no behavior change.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(sagemaker): restore provider-supported embedding params after map
Cohere input_type is advertised in get_supported_openai_params but was
filtered out of non_default_params by OPENAI_EMBEDDING_PARAMS before
map_openai_params ran. Merge supported params from passed_params after
map (same path Greptile flagged). Handle input_type explicitly in
SagemakerCohereEmbeddingConfig.map_openai_params and add an integration
test through get_optional_params_embeddings.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(embeddings): only restore non-OpenAI supported params after map
The post-map restore loop must skip OPENAI_EMBEDDING_PARAMS so mapped
fields (e.g. dimensions -> output_dimension) are not duplicated under
their OpenAI names. Align SageMaker embedding import order with sibling
files and add a regression test for dimensions mapping.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(sagemaker): avoid double post_call on Cohere embedding response
Greptile review on #28613 caught that `CohereEmbeddingConfig._transform_response`
calls `logging_obj.post_call` internally. The SageMaker embedding handler
already calls `post_call` once before invoking the transform, so the Cohere
SageMaker path fired callbacks, cost calculators, and log handlers twice
per request.
Extract the parsing body of `_transform_response` into
`_populate_embedding_response` (pure extract-method, no behavior change
for existing Cohere direct or Bedrock Cohere paths, which keep calling
`_transform_response`). Have `SagemakerCohereEmbeddingConfig` call the
new helper directly so it parses the response without re-logging.
Add a regression test asserting `logging_obj.post_call` is not invoked
by the SageMaker Cohere transform.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
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ryan-crabbe-berri
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643989989f
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chore(test): remove dead old Playwright e2e suite (#28632)
The Playwright suite under tests/proxy_admin_ui_tests/e2e_ui_tests/ is no longer wired into CI (only test_*.py is globbed) and every active spec is duplicated by ui/litellm-dashboard/e2e_tests/tests/ (login, auth redirect, search users, internal user list). team_admin.spec.ts was entirely commented out. Removing the directory plus its only-used-here playwright config, package.json/lock, and utils/login.ts keeps the canonical suite under ui/litellm-dashboard/e2e_tests/ as the single source of truth. |
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yuneng-jiang
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f62ae93e13
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test(proxy): behavior-pinning matrix for tier-2/3 key + team management endpoints (#28620)
* test(proxy): add create_scratch_actor harness helper
Adds create_scratch_actor() to the management behavior-suite conftest and
extends create_scratch_team() with team_member_permissions / models kwargs,
needed by the PR3 team-key-permission and team-model matrices. The new
helper mints a scratch-prefixed user + verification token (+ org
memberships), all reclaimed by the existing scratch-prefix teardown.
* test(proxy): pin /key block, unblock, health, aliases behavior
Adds behavior-pinning matrices for POST /key/block, POST /key/unblock,
POST /key/health, and GET /key/aliases. Pins that the management-route gate
401s ORG_ADMIN-role callers before _check_key_admin_access runs, the
block/unblock round-trip on the blocked column, missing-key 404, and the
_apply_non_admin_alias_scope visibility rules for /key/aliases.
* test(proxy): pin /key/bulk_update + /team/key/bulk_update behavior
Adds behavior-pinning matrices for POST /key/bulk_update (PROXY_ADMIN-only;
ORG_ADMIN stopped 401 at the route gate, INTERNAL_USER-role 403 at the
handler) and POST /team/key/bulk_update (team-member-permission gate keyed
on KEY_UPDATE). Pins batch semantics: empty/over-cap 400, per-key failure
isolation into failed_updates, all_keys_in_team broadcast, and no-keys 404.
Adds an optional key_alias arg to create_scratch_key for multi-key scenarios.
* test(proxy): pin /key SA-generate, v2-info, reset-spend behavior
Adds behavior-pinning matrices for POST /key/service-account/generate
(team-membership + team-member-permission gating; SA keys carry no user_id),
POST /v2/key/info (per-key _can_user_query_key_info silently drops invisible
keys), and POST /key/{key}/reset_spend (PROXY_ADMIN or team admin only;
missing key 404, reset-value 400). Pins that ORG_ADMIN-role callers are
stopped 401 at the management-route gate on the two non-info routes.
* test(proxy): close PR1/PR2 key-side deferred coverage gaps
Closes the four key-side gaps deferred from PR1/PR2:
- 404 on missing key for /key/update and /key/delete (not 401/403)
- denied /key/update leaves max_budget/tpm_limit/rpm_limit untouched
- /key/regenerate enforces litellm.upperbound_key_generate_params (#26340)
- /key/list key_alias substring vs exact (admin-only) + team_id filter,
and a non-admin filtering a foreign team is 403
* test(proxy): pin /team block, unblock, available, filter/ui, members/me
Adds behavior-pinning matrices for POST /team/block + /team/unblock
(management-route gate fronts _verify_team_access; reachable only by
PROXY_ADMIN and an org admin of the team's own org), GET /team/available
(default empty path), GET /team/filter/ui (route-gated PROXY-ADMIN-only
despite the handler having no gate), and GET /team/{team_id}/members/me
(caller resolves its own membership; non-member 404, no-user_id key 400).
* test(proxy): pin /team model add/delete + permissions endpoints
Adds behavior-pinning matrices for POST /team/model/add + /team/model/delete
(route-gated PROXY-ADMIN-only; missing team 404), GET /team/permissions_list +
POST /team/permissions_update (self-managed; proxy/team/org admin pass), and
POST /team/permissions_bulk_update (PROXY_ADMIN-only). Pins the deliberate
divergence that the available-team self-join grants read access via
permissions_list but never write access via permissions_update.
* test(proxy): pin /team delete, bulk_member_add, v2/list, daily/activity
Adds behavior-pinning matrices for POST /team/delete (per-team
_verify_team_access; batch aborts whole on a missing id), POST
/team/bulk_member_add (route-gated PROXY-ADMIN-only; empty/over-cap 400),
GET /v2/team/list (_enforce_list_team_v2_access — bare query 401s regular
users, org-scoped for org admins) and GET /team/daily/activity (non-member
team_ids filter 404, the VERIA-43 fix).
* test(proxy): add route-coverage gate + close team org-relocation gap
Adds test_route_coverage.py (PR3.M1): parses every @router route literal
from the two management-endpoint source files and asserts each is exercised
by >=1 behavior-suite scenario — a permanent regression guard for future
routes. Closes the last PR1/PR2 deferred gap: the /team/update org-relocation
allowed branch, exercised by a dual-org-admin minted via create_scratch_actor.
test_team_model uses literal route URLs so the coverage parser resolves them.
* test(proxy): bound plain route params to one path segment in coverage gate
Plain path params ({team_id}) now compile to [^/?]+ instead of [^?]+, so a
parameter cannot span '/'. Starlette ':path' params still match across '/'.
Keeps the route-coverage guard from falsely reporting a future multi-segment
route as covered. All 37 routes remain covered.
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yuneng-jiang
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985574b6be
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fix(check_licenses): read PEP 639 license-expression metadata (#28529)
The dependency license checker only read the legacy free-text `info.license` field from PyPI. Packages that adopt PEP 639 publish their license as an SPDX expression in `info.license_expression` and leave the legacy field null, so the checker reported "Unknown license" and failed CI for every newly-bumped PEP 639 dependency. `get_package_license_from_pypi` now resolves the license in order: `license_expression`, then legacy `license`, then the `License :: OSI Approved :: ...` trove classifiers. `is_license_acceptable` splits compound SPDX expressions on the uppercase OR/AND operators (case-sensitive, so the lowercase `-or-later` inside an identifier is not mistaken for an operator) and strips `WITH <exception>` suffixes, requiring every component to be acceptable. Free-text license blobs are detected and fall back to the original whole-string matching. The `black` and `pydantic-settings` entries in liccheck.ini that existed solely to work around this now resolve correctly on their own and have been removed. |
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Mateo Wang
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b0b25ae4b9
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Include team alias in CLI JWT token (#28621) | ||
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Sameer Kankute
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e9f0eddbd1
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Litellm oss staging 2 (#28582)
* fix(anthropic): handle empty streaming tool calls (#28549) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * [Feature][Bug Fix] Decouple Azure OpenAI Deployment ID from model name via base_model to fix gpt5 model routing (#28490) * feat(azure): decouple deployment ID from model name via base_model Azure OpenAI deployments have arbitrary names (deployment IDs) that may not match the underlying model. Previously, model-type detection (o-series, gpt-5, etc.) relied on substring matching against the deployment name, causing misrouted configs and rejected params when deployment names were non-standard (e.g. 'my-deployment-id' for gpt-5.2). This change extends the existing base_model field to drive model-type detection, config selection, supported param resolution, and param mapping throughout the Azure call path: - _get_azure_config() uses base_model for is_o_series/is_gpt_5 checks - get_provider_chat_config() threads base_model for Azure - get_supported_openai_params() accepts and uses base_model - get_optional_params() accepts base_model and passes it to all Azure config method calls (get_supported_openai_params, map_openai_params) - azure.py completion handler uses base_model for GPT-5 detection - Config internal methods (e.g. is_model_gpt_5_2_model) now receive base_model so features like logprobs are correctly enabled Fully backward compatible - when base_model is unset, behavior is identical. Existing o_series/ and gpt5_series/ prefix workarounds continue to work. Usage in proxy config: model_list: - model_name: my-gpt5 litellm_params: model: azure/my-deployment-id model_info: base_model: azure/gpt-5.2 Fixes: non-standard deployment names like 'prefix-gpt-5.2' rejecting logprobs/top_logprobs despite the underlying model supporting them. * Addressing Greptile comments. * gemini-3.1-flash-lite pricing (#27933) * feat(model_prices): add gemini-3.1-flash-lite pricing with standard/batch/flex/priority tiers * fix pricing * add service tier --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> * fix(openai-responses): strip Anthropic cache_control from Responses API requests (#28431) Squash-merged by litellm-agent from cwang-otto's PR. * Treat None litellm_provider as wildcard in _check_provider_match (#28523) Squash-merged by litellm-agent from adityasingh2400's PR. * fix greptile * fix: use _azure_detection_model in default Azure branch of get_supported_openai_params Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(openai-responses): strip cache_control on compact endpoint as well Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Felipe Garé <90070734+FelipeRodriguesGare@users.noreply.github.com> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: withomasmicrosoft <withomas@microsoft.com> Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> Co-authored-by: cwang-otto <chengxuan.wang@ottotheagent.com> Co-authored-by: Aditya Singh <60082699+adityasingh2400@users.noreply.github.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> |