* refactor: clear fresh tech debt from the last 24 hours (2026-09-05, 2026-09-06)
Drop the TID251 cast import and both cast-ok casts from the refusal
message_delta rebuild by narrowing the TypedDict union on its type literal,
drop the redundant Mapping cast after the isinstance check in
_mapping_field, and type the Lyria predict read-only helpers as
Mapping[str, object] instead of a bare dict with mutable-ok.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clear fresh tech debt from the last 24 hours (2026-09-09)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clear fresh tech debt from the last 24 hours (2026-09-10)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: keep the pre-existing cost-estimate comment and usage cost read out of the cleanup
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clear fresh tech debt from the last 24 hours (2026-09-13)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: keep the model info pricing helper out of the cleanup
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: drop suppressions that no longer suppress anything (2026-09-16)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: keep the rebind-ok reason inside the line limit
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic): rebuild the refusal message_delta by spreading the chunk
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clear fresh tech debt from the last 24 hours (2026-09-17)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clear fresh tech debt from the last 24 hours (2026-09-18)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clear fresh tech debt from the last 24 hours (2026-09-19)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: keep the pre-existing protected-resource return type out of the cleanup
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: clear fresh tech debt from the last 24 hours (2026-09-20)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor: type fresh getattr, Any, and bare dict debt from 2026-09-22
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(mcp): keep the string guard on tools/list next_cursor
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(vercel_ai_gateway): type the embedding error headers dict
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(techdebt): fix inert suppressions and missing Final in 2026-09-22 changes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(techdebt): shorten suppression reason to fit line length
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(techdebt): format provider spread so its suppression sits on the literal
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(techdebt): drop the logger extras suppression that LIT013 now flags as inert
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(techdebt): clear fresh suppressions, Any aliases and slop from the 24h window
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(vercel): take a read-only headers mapping in get_error_class
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: mateo <mateo@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(arize): per-team success and error sampling rates for the Arize AX callback
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(arize): fail open on invalid sampling rates and type the new sampling code
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(arize): type the sampling test helpers and parametrized fixture
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Zeroes the remaining violations for 12 rules so they can hard-fail
in the main ruff config instead of being budget-ratcheted, and drops
their strict-gate budgets to 0:
- B021: drop useless f-prefix on the Javelin docstring
- C404 / C419: dict()/any() around unnecessary list comprehension
- PLR0124: replace the 'value == value' NaN idiom (and the separate
+/-inf exclusion) with math.isfinite in _validate_response_time
- SIM201: 'not X == "function"' -> 'X != "function"'
- SIM211: 'False if x is False else True' -> 'x is not False'
- SIM222: drop literal 'None or' before "success"
- UP036: remove the dead sys.version_info < (3, 8) branch (and the
now-unused sys import) in the weights_biases TYPE_CHECKING block
- B018 x2: keep the deliberate property side-effect access but assign
it ('_ = self.prompt_manager') as the rule requires
- PLR0206: the unusable '@property def api_version(self, api_version)'
(a property getter cannot take extra args) becomes a @staticmethod
matching its siblings get_api_base/get_api_key; it had no callers
- PLR1704: rename the loop variable (and the nested helper parameter)
that shadowed abatch_completion_fastest_response's 'model' argument
- B004 x2: scoped noqa with rationale — both sites retrieve __call__
to unwrap functors for iscoroutinefunction, which is a value use,
not the callability test B004 assumes; the callable() autofix would
break them
N999 intentionally stays on the ratchet (limit 1): it flags the
'litellm/proxy/lambda.py' filename, which needs a module rename.
Verified: full-tree 'ruff check litellm' green with the graduated
rules enforced; ruff-strict counts for all 12 rules are 0; budget
JSON regenerated in the gate script's json.dumps style.
Second pass over the highest-Any-density modules that the first pass left
untouched: guardrail hooks, the gemini and anthropic transformation layers,
the proxy spend-tracking and pass-through endpoints, and the caching clients.
Untyped `response.json()` bodies and `dict[str, Any]` request payloads are
described once at their boundary with a TypedDict or Protocol, so the fields
read downstream resolve to real types instead of Any. No cast, no type: ignore,
no noqa, and no new Any annotations.
Arize Phoenix claimed it could run without a prompt_id while its compiler
requires one, so the no-prompt_id fallback could select it and fail instead
of reaching the vector-store hook. It now declines like the other managers.
* fix(arize): stop MCP CallToolResult from aborting span attribute setting
`call_mcp_tool` logs the MCP SDK's `CallToolResult`, a Pydantic model with
no `.get`. `_coerce_response_obj_for_attrs` left it untouched and
`_set_request_attributes` then raised AttributeError, which aborted the rest
of the attribute block, so MCP tool spans lost their invocation params,
input messages, and outputs.
Dump Pydantic models that lack `.get` to a dict, and guard the response
id/model reads the same way `_set_response_attributes` already does so any
other uncoercible response object degrades instead of crashing.
* feat(arize): render MCP tool calls as OpenInference TOOL spans
`call_mcp_tool` spans carry neither `messages` nor `choices`, so every
generic extraction path left Input and Output blank and the span showed only
provider/model metadata.
Emit `tool.name` from `metadata.mcp_tool_call_metadata`, `input.value` from
the tool arguments, and `output.value` from the `CallToolResult` content
(text parts when present, JSON otherwise). Arguments and results are user
content, so the input/output emit is gated on the same
`should_redact_message_logging` check the passthrough normalizer uses.
Reuse `_to_plain_dict` for the Pydantic coercion instead of the local
BaseModel branch added in the previous commit.
* fix(arize): annotate the new MCP helper parameters
The strict-rule gate flagged three new ANN001 violations. Type the payload
as StandardLoggingPayload | None and the coerced response as object, which
the isinstance guards already narrow.
* fix(arize): annotate the MCP helper against the type-discipline gate
LIT001 bans mutable collections in annotations, so the kwargs parameter
becomes Mapping[str, object]. should_redact_message_logging still declares a
dict it only ever reads, and widening it would cascade into core_helpers, so
the call carries a scoped ignore instead. Narrow the payload by None rather
than isinstance now that it is typed, and annotate the values read out of the
untyped logging payload.
* fix(arize): record empty MCP arguments and results instead of dropping them
Zero-argument tools record arguments={} and successful calls can return
content=[]; both were skipped by truthiness, leaving the generic placeholder
on Input and nothing on Output. Read structuredContent when content yields
no text, and cover the list_mcp_tools response shape.
* fix(arize): keep media parts in mixed MCP results
A result mixing text and media returned the text alone, so Arize showed
text/plain and dropped the image or resource parts.
---------
Co-authored-by: Sean Lee <yihsean@gmail.com>
Every ruff-strict rule that sat above its budget limit (FURB188, RUF022,
SIM118, UP007, UP032, UP037) is now at zero, LIT001 and LIT006 are back
under their ceilings, and the freed headroom is ratcheted out of
ruff-strict-budget.json, type-discipline-budget.json, and
basedpyright-code-budget.json so the gates take the fast path again
About 35,000 fixes ruff marks safe across 32 rules (UP006/UP045/UP007
modern annotations, UP032 f-strings, SIM114/SIM118, RET501, and
friends), removal of the 1,296 typing imports the rewrite orphaned, and
hand fixes for what the fixers could not see: five star-import
freeloaders of typing names, two F823 late-import annotations, the
/get/config/list introspection crash on types.UnionType, redundant
function-local RoleMappings imports in ui_sso.py that shadowed the
module-level name once the annotation lost its quotes, and one FURB168
tautology.
B009/B010/PIE804/RUF019 are excluded on purpose: their safe fixes
rewrite getattr/setattr/**-splat/key-in-dict escape hatches into forms
basedpyright then rejects (283 new errors measured), so their budgets
stay at base values.
ruff-strict-budget.json drops by 39,579 this commit (39,968 across the
branch) with 28 rules at an actual 0 and 9 more sharply down.
type-discipline-budget.json ratchets LIT002/LIT006/LIT009 down; LIT001
moves to the now-honest total: the checker matches the spelling `set`
but not the alias `Set`, so the 160 typing.Set annotations rewritten to
set[...] were always mutable-set annotations and only now count.
The repo linted at 120 (E501, isort) but ran ruff format at 88 via a
--line-length 88 override in the Makefile and CI, leaving the formatter
and the linter disagreeing on wrap width. Drop the override so ruff.toml's
line-length = 120 is the single source of truth and reformat the tree to
match.
* feat(arize): enrich OpenInference attributes for better span rendering
Pure rendering enhancements to the Arize / Arize Phoenix integration. No
existing attribute keys or values are removed or overwritten; every new
emit is independently try/except-wrapped and fires only when its source
data is present so existing behavior is preserved.
What this adds
- Coerce non-dict response objects (e.g. httpx.Response from passthrough
routes) via JSON decode so id/model/usage extraction stops crashing
with "'Response' object has no attribute 'get'". Dicts and Pydantic
objects with .get pass through unchanged.
- Set OPENINFERENCE_SPAN_KIND defensively early so a downstream failure
can't blank the kind; the original late write (incl. TOOL upgrade) is
preserved.
- Add "passthrough" keyword to _infer_open_inference_span_kind so
allm_passthrough_route / llm_passthrough_route resolve to LLM instead
of UNKNOWN.
- Emit cache token breakdown: LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_READ /
_CACHE_WRITE / _AUDIO. Sources covered: OpenAI prompt_tokens_details
and Anthropic / Bedrock cache_{read,creation}_input_tokens.
- Render assistant tool_calls on both input and output messages via
MESSAGE_TOOL_CALLS.* (Pydantic-aware, handles ModelResponse choices).
Tool-result input messages also get MESSAGE_TOOL_CALL_ID and
MESSAGE_NAME.
- Render multimodal list-shaped content via MESSAGE_CONTENTS.* (OpenAI
image_url, Anthropic source.{media_type,data} as data: URI). Legacy
MESSAGE_CONTENT write is unchanged.
- Emit SESSION_ID (end_user_id / trace_id), USER_ID (only when not
already set by optional_params.user or model_params.user), and
litellm.{team_id,team_alias,key_alias} from StandardLoggingPayload
metadata.
- Emit llm.response.cost as float from StandardLoggingPayload.response_cost.
- Bedrock / Anthropic passthrough normalization: extract input from
additional_args.complete_input_dict and output from the coerced
provider response so INPUT_VALUE / OUTPUT_VALUE / LLM_INPUT_MESSAGES /
LLM_OUTPUT_MESSAGES are populated. Only runs when call_type contains
"passthrough" / "pass_through".
Tests
- 15 new unit tests covering each addition plus explicit regression
guards (USER_ID overwrite protection, passthrough normalizer scope,
coerce identity for dicts/.get-bearing objects, no spurious cache
emits).
- Existing test_arize_set_attributes count bumped from 26 to 27 to
account for the additional defensive span.kind write (same value,
written twice).
- tests/test_litellm/integrations/arize/: 70 passed (55 baseline + 15
new). tests/test_litellm/integrations/test_opentelemetry.py: 221
passed.
Co-authored-by: Cursor <cursoragent@cursor.com>
* refactor(arize): collapse additive try/except blocks into _safe_emit helper
The additive attribute emitters all share the same shape: run a callable,
swallow any exception to debug log so it cannot blank the span. Hoisting
that pattern into a single _safe_emit(label, fn, *args, **kwargs) helper
removes 5 repeated try/except blocks. Behavior unchanged; arize test
suite still passes (70/70).
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(arize): emit cost under canonical llm.cost.total key
Arize's "Total Cost" column reads the OpenInference-standard
`llm.cost.total` attribute. The previous custom `llm.response.cost`
key never surfaced in the trace list. Now emits both keys (canonical +
legacy) so renderers + any existing consumers both work.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(arize): keep span.kind=LLM for tool-using completions + render tool_calls in Output
A chat completion that passes `tools=[...]` or returns `tool_calls` is still
an LLM call per the OpenInference spec — TOOL is reserved for actual tool
execution. The previous override demoted these to TOOL, breaking Arize's
LLM-scoped dashboards/evals and skewing token/cost analytics for any
tool-using traffic.
Additionally, when an assistant response had no text content but did
request tool calls, `output.value` was set to the empty string so Arize's
"Output" pane rendered blank. Now serializes the tool_calls into a compact
JSON summary in `output.value` (the structured `MESSAGE_TOOL_CALLS.*`
attributes are still emitted unchanged).
Cleanups:
- extract `_get_tool_calls` and `_normalize_tool_call` helpers,
deduplicating the dict-vs-Pydantic + function-dict logic across
`_set_choice_outputs`, `_emit_message_tool_calls`, and the new
`_summarize_tool_calls_for_output`.
- drop redundant late `OPENINFERENCE_SPAN_KIND` write — the defensive
early write is now the single source of truth.
- remove a dead local re-import of `MessageAttributes`/`SpanAttributes`.
Tests: 73 pass (added regression guard asserting span.kind stays LLM for
completions that pass tools AND return tool_calls; existing call_count
assertion restored to 26).
Co-authored-by: Cursor <cursoragent@cursor.com>
* chore(arize): tighten cleanup — fold _get_tool_calls into _safe_get
Two tiny cleanups, no behavior change:
- collapse `_get_tool_calls` to use `_safe_get`, removing a 7-line
hand-rolled dict-vs-attribute fallback that duplicated existing logic.
- trim the `_set_choice_outputs` tool-call summary comment from 4 lines
to 2 (was over-explaining).
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(arize): address Greptile review — drop session_id=trace_id fallback, remove dead code, fix Black
Three Greptile-flagged issues + the Black formatting CI failure.
1. SESSION_ID no longer falls back to trace_id. Previously every span
without an explicit `user_api_key_end_user_id` would have its
session.id set to the per-request trace_id, which creates one
distinct "session" per request and breaks Arize's Session-grouping
analytics. Now SESSION_ID is emitted only when an explicit end-user
identifier exists, and the trace_id is emitted under its own
`litellm.trace_id` key so spans remain filterable by trace.
2. Removed dead `ArizeOTELAttributes.set_response_output_messages`
override. Confirmed zero callers in the entire repo (the live path
is `_set_choice_outputs` via `_set_response_attributes`). The
override was preexisting dead code, but the expansion of
`_set_choice_outputs` in this PR made the divergence misleading.
3. Removed permanently-dead first branch in cache_write detection.
`_safe_get(prompt_token_details, "cache_creation_tokens")` looks
for a key that neither OpenAI's `prompt_tokens_details` nor
Anthropic's payload ever exposes. Now reads straight off `usage`
for `cache_creation_input_tokens`.
4. Reformatted both files under Black 26.3.1 (the version CI uses
via `uv sync --frozen`). Local previously used 24.10.0.
Tests: 74/74 pass in the arize suite (added
`test_arize_does_not_use_trace_id_as_session_id_fallback`).
Combined arize + opentelemetry suite: 295/295 pass.
End-to-end verified live: tool-call still emits `span.kind=LLM` and
JSON tool_calls in `output.value`; `session.id` is now correctly
unset when no end_user_id is provided; `litellm.trace_id` is
populated; Bedrock passthrough input/output unchanged.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(arize): gate passthrough prompt export on message redaction
- Skip the complete_input_dict bridge in _maybe_normalize_passthrough when
should_redact_message_logging() is true, so enabling redaction no longer
leaks raw passthrough prompts into Arize (Veria security finding).
- Split passthrough input/output rendering into helpers to satisfy PLR0915.
- Remove dead call_type assignment (F841).
Validated live against a Bedrock passthrough proxy exporting to Arize:
non-redacted renders the real prompt on litellm_request; global
turn_off_message_logging yields input.value=redacted-by-litellm with the
raw_gen_ai_request child span suppressed and no SSN/marker leakage.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): handle OAuth IdP error responses in /callback (LIT-2750)
Per RFC 6749 section 4.1.2.1, when the IdP rejects an OAuth authorization
request it redirects back to the client with ?error=...&error_description=...
and no code. The MCP /callback handler declared code and state as required
query params, so FastAPI rejected such error responses with a 422 before
the handler ran -- stranding the MCP client waiting on the loopback.
This change:
- Makes code and state optional and accepts the RFC-defined error,
error_description, and error_uri params.
- When state decodes to a trusted client redirect_uri, propagates the
error params back to that URI with the client's original (un-wrapped)
state preserved, so the client's OAuth library can surface the failure.
- When state is missing/undecryptable or the encoded redirect_uri is no
longer trusted, renders a 400 HTML page with the (HTML-escaped) error
details instead of leaking to an attacker-controlled redirect.
- Preserves the existing success path (code + state -> 302 to validated
client redirect_uri with original state).
Fixes LIT-2750.
* test(mcp): regression tests for /callback handling IdP error responses (LIT-2750)
Adds a new test module covering the LIT-2750 fix: the MCP OAuth /callback
endpoint must accept IdP error responses (e.g. ?error=access_denied) per
RFC 6749 section 4.1.2.1 instead of returning a 422 because ``code`` is missing.
Coverage:
- IdP error with no state -> 400 HTML page surfacing the error.
- HTML escaping of user-controlled error / error_description fields.
- IdP error with a trusted (loopback) state -> 302 propagating
error / error_description / original client state to the client.
- IdP error with an untrusted redirect_uri encoded in state -> 400 inline
(no open-redirect to attacker-controlled origin).
- IdP error with an undecryptable state -> 400 HTML fallback.
- Bare GET /callback with no params -> 400 HTML (not Pydantic 422).
- Success path (code + state) still 302 to validated client redirect_uri
with the original (un-wrapped) state preserved.
* refactor(mcp): drop unused _OAUTH_ERROR_PARAMS constant (Greptile P2)
The tuple was leftover scaffolding from an earlier draft of the LIT-2750
fix; nothing references it. The explanatory RFC 6749 §4.1.2.1 comment block
above the callback handler covers the same intent.
* fix(mcp/oauth): preserve empty original_state and clarify missing-param error in /callback
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(thinking): handle None thinking param in is_thinking_enabled (#28598)
Squash-merged by litellm-agent from Terrajlz's PR.
* feat(helm): support tpl rendering in podAnnotations (#28609)
Squash-merged by litellm-agent from devauxbr's PR.
* fix: apply black formatting to base_llm chat transformation
Fix CI black --check failure on is_thinking_enabled return formatting.
Co-authored-by: Cursor <cursoragent@cursor.com>
* merge main (#28836)
* fix(proxy): Bedrock Knowledge Base pass-through: preserve SigV4 headers and signed request body (#27526)
* Fix Bedrock KB pass-through SigV4 headers and signed body
Coerce botocore HeadersDict to a dict for pass-through routes. When
forward_headers is true, drop request headers that collide case-insensitively
with signed headers so client Bearer auth does not shadow AWS SigV4.
Send prepped.body as raw content so the outbound payload matches the
signature after logging hooks mutate the parsed dict.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Simplify pass-through raw body handling
Read the SigV4-signed bytes directly from request.state inside
pass_through_request instead of threading a custom_raw_body argument
through three functions. Helper methods are restored to their original
signatures, and the new branch lives in one place at each httpx call site.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Harden pass-through raw body read from request.state
Guard missing request.state (test fixtures) and ignore non-bytes/str
values so MagicMock does not trigger the SigV4 raw-body path.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Test pass_through_request state_raw_body uses httpx content=
Cover non-streaming (async_client.request) and streaming (build_request)
paths so SigV4 bytes on request.state are not replaced by json= of a
hook-mutated dict.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
* chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728)
* chore(tests): migrate Bedrock CI from AWS account 888602223428 to 941277531214
The original account (888602223428) was put under a security restriction by
AWS after a root access key leaked in a PR comment. While that account works
its way through the AWS Support unlock process, Bedrock-touching CI tests have
been migrated to a fresh account (941277531214).
Changes:
- Replace 26 hardcoded references to 888602223428 with 941277531214 across
8 files (provisioned-model ARNs, imported-model ARNs, AgentCore runtime
ARNs, batch execution role ARN, and example proxy config).
- The provisioned-model and imported-model ARNs are referenced only from
mocked unit tests — no AWS resources to recreate.
- The batch execution IAM role has been recreated in the new account with
the same name and equivalent permissions.
- The two AgentCore runtimes (hosted_agent_r9jvp-3ySZuRHjLC,
hosted_agent_13sf6-cALnp38iZD) are being recreated in the new account
under the same names — see tools/agentcore-deploy/ in a follow-up.
CircleCI env vars AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION_NAME
were updated separately via the CircleCI API to point at the new account.
Smoke-tested locally against the new account:
aws bedrock-runtime converse --region us-west-2 \
--model-id us.anthropic.claude-sonnet-4-5-20250929-v1:0 \
--messages '[{"role":"user","content":[{"text":"ping"}]}]'
→ 200, model returned 'pong'
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* chore(tests): refresh AgentCore ARN suffixes to match newly-deployed runtimes
The first migration commit replaced just the account ID, but AgentCore
auto-assigns a random 10-char suffix to every runtime on creation — we
can't reuse the original suffixes (`3ySZuRHjLC`, `cALnp38iZD`) in the
new account. Updated the AgentCore-runtime ARNs in the three files that
reference real runtime IDs (not the mock-based unit-test ARNs).
Deployed runtimes:
arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_r9jvp-Rq79QFC2fp
arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_13sf6-4046UzHSwy
Both runtimes are status=READY and pass a smoke invoke:
$ aws bedrock-agentcore invoke-agent-runtime --agent-runtime-arn ... --payload '{"prompt":"ping"}'
→ 200, {"result": "echo: ping"}
The agent is a minimal echo (see /tmp/agentcore_deploy/agent.py for the
deploy artifacts). Tests that only verify the SDK wiring will pass; if any
test asserts on agent output content, swap the echo for the real agent.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* chore(tests): point Bedrock batch tests at new-account S3 bucket
The account migration (888602223428 -> 941277531214) was a flat
account-ID swap, which only rewrites ARNs that embed the account
number. S3 bucket names carry no account ID, so the live Bedrock
batch tests still uploaded to `litellm-proxy` — a bucket that lives
in the old account. S3 names are globally unique, and the old account
still holds that name, so it can't be recreated in the new account.
Rename to `litellm-proxy-941277531214` (account-ID suffix guarantees
global uniqueness). The bucket must be created in 941277531214 and the
batch execution role granted s3:GetObject/PutObject/ListBucket on it
before this job is run in CI.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore(tests): point live S3 logging test at new-account bucket
Same account-ID-free blind spot as the batch bucket: `load-testing-oct`
lives in the old account and its name can't be reused globally. The
`logging_testing` CI job is wired into the workflow and runs
test_basic_s3_logging, which uploads to this bucket with the CI env
creds, then lists and deletes objects — a live dependency.
Rename to `load-testing-oct-941277531214`. The bucket must exist in the
new account with the CI IAM principal granted
s3:PutObject/GetObject/ListBucket/DeleteObject before this job runs.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore(tests): repoint Bedrock guardrail IDs to new-account guardrails
The migration left guardrail IDs untouched (no account ID in them), so
all live guardrail tests failed with "guardrail identifier or version
does not exist" against 941277531214. Recreated both guardrails in the
new account and updated the hardcoded IDs:
- wf0hkdb5x07f -> zgkmukebruil (PII mask: PHONE + CREDIT_DEBIT_CARD,
with explicit inputAction=ANONYMIZE so masking applies to INPUT,
which is the source litellm's moderation hook sends)
- ff6ujrregl1q -> 4w3d1di3snt5 (blocks "coffee"; blocked message set
to the exact string the tests assert on)
Updated test_bedrock_guardrails.py, otel_test_config.yaml, and the
guardrailConfig in test_bedrock_completion.py. Verified locally: the 5
previously-failing guardrail tests now pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): migrate legacy models to current inference profiles
The new CI account (941277531214) cannot invoke legacy Bedrock models
(AWS gates them: "marked by provider as Legacy... not actively using in
the last 30 days"). Migrated the live-call tests:
- anthropic.claude-3-sonnet-20240229 -> us.anthropic.claude-sonnet-4-5-20250929-v1:0
- anthropic.claude-3-haiku-20240307 -> us.anthropic.claude-haiku-4-5-20251001-v1:0
Current Claude models on Bedrock require the us. inference-profile prefix
(bare on-demand ids are rejected).
cohere.command-r-plus has no working replacement (all Cohere is legacy-
gated in the new account): swapped to claude-haiku-4-5 in provider-
agnostic param lists. amazon.titan-image-generator skipped (no working
replacement). Mocked/transformation/cost tests that reference the legacy
strings are intentionally left unchanged. Verified live against the new
account.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): repoint SageMaker + Knowledge Base to new-account resources
These referenced account-scoped resources by hardcoded id that only
existed in the old account, so the migration's account-ID swap missed
them. Recreated in 941277531214 and repointed:
- SageMaker endpoint jumpstart-dft-hf-textgeneration1-mp-20240815-185614
-> litellm-ci-textgen (gpt2 on a TGI container, ml.g5.xlarge)
- Bedrock Knowledge Base T37J8R4WTM -> LCYXFBR2TU (OpenSearch Serverless
vector store + titan-embed-text-v2, seeded with a LiteLLM doc)
Verified live: test_sagemaker.py (12 passed) and
test_bedrock_knowledgebase_hook.py (12 passed).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(reasoning_effort_grid): skip bedrock claude-opus-4-7 cells (not entitled on 941277531214)
claude-opus-4-7 is listed in the new Bedrock CI account's foundation
models but invoke is denied (AccessDeniedException: "not available for
this account"). Bedrock access to the flagship Opus requires an AWS
Sales request, not the self-serve model-access toggle, so it can't be
enabled inline with the rest of the account migration.
Add an optional `skip_reason` to ModelEntry and set it on the
bedrock-claude-opus-4-7 entry; the grid test honors it via pytest.skip.
Cell count (231) and route coverage are unchanged, so the structural
asserts still pass. Restore coverage by deleting the one skip_reason
line once access is granted.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): swap/skip legacy-gated models unavailable on new CI account
The migrated AWS account (941277531214) cannot access several models that
the old account could, so the remaining red CI jobs were hitting real
Bedrock "Access denied / Legacy" and "account not authorized" errors:
- image_gen: skip both Nova Canvas test classes (amazon.nova-canvas-v1:0 is
legacy-gated), matching the existing titan skip.
- batches: skip test_async_file_and_batch (Bedrock batch inference is not
authorized on the new account; requires an AWS support case).
- litellm_overhead: swap legacy claude-3-5-haiku for the active
us.anthropic.claude-haiku-4-5 inference profile.
- test_completion_claude_3_function_call: swap legacy claude-3-sonnet for the
active us.anthropic.claude-sonnet-4-5 inference profile.
https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa
* test(bedrock): fix remaining e2e legacy-model + batch failures on new CI account
- e2e_openai_endpoints: skip test_bedrock_batches_api (Bedrock batch inference
is not authorized on account 941277531214) and migrate the missed
s3_bucket_name in oai_misc_config.yaml to litellm-proxy-941277531214.
- build_and_test: swap legacy bedrock claude-3-sonnet for the active
us.anthropic.claude-sonnet-4-5 inference profile in the proxy structured
output e2e test.
https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa
* test(bedrock): make opus-4-7 + batch cells fail loudly and mock image-gen (#28791)
Replace the silent skips added for the new CI account with noisier behavior:
- reasoning-effort grid: opus-4-7 cells now fail (when AWS creds are present)
instead of skipping, so the missing entitlement stays visible in CI; they
still skip when AWS creds are absent (local dev)
- Bedrock batch inference tests: drop the skip so they run and fail until
batch access is granted
- Titan + Nova Canvas image-gen tests: mock the Bedrock HTTP call so the
transform + cost-tracking path stays under test without live model access
https://claude.ai/code/session_01MT7SWDnXUjv6e6EPG7BDjT
Co-authored-by: Claude <noreply@anthropic.com>
* test(bedrock): use pytest.xfail for known-failing opus-4-7 cells
Replace pytest.fail with pytest.xfail when a model has a fail_reason,
so known-broken cells stay visible as XFAIL without keeping CI red.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(otel): export SERVER span on management-endpoint success without http_request (#28794)
Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local>
* chore(ci): merge dev branch (#28801)
* 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: shin-berri <shin-laptop@berri.ai>
Co-authored-by: user <70670632+stuxf@users.noreply.github.com>
* chore(ci): merge dev branch (#28657)
* feat(dashboard): navbar hierarchy + Agent Platform notifications (#27543)
* feat(dashboard): refine navbar zones and Agent Platform notice
Restructure the admin navbar for production users: clear product vs community
vs personal columns with vertical dividers, icon-only Slack/GitHub in a
shared chip, and Docs/Blog typography aligned on an 8px rhythm.
Add a notifications bell with popover linking to the LiteLLM Agent Platform
repo and optional mark-as-read persistence.
Promote the account control with initials avatar, single-line display name,
and navDisplayName mapping for placeholder user ids (e.g. default_user_id).
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): address PR review — AntD buttons, public page guard, dedupe regex
- Replace raw <button> with AntD Button in BlogDropdown, NotificationsBell, UserDropdown, and test mock
- Guard NotificationsBell + container behind !isPublicPage to avoid rendering on public pages
- Remove redundant equality checks in navDisplayName (regex already covers them)
- Remove unused `lower` variable after simplification
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
* fix(dashboard): drop dead useHealthReadiness import in navbar
The module was removed in #27896 (replaced by useHealthReadinessDetails),
but the import survived the rebase. The symbol is unused — only
useHealthReadinessDetails is consumed in the file. Removing the dead
import unblocks the UI TypeScript build.
* fix(dashboard): align CommunityEngagementButtons test with icon-only aria-labels
The component was refactored to an icon-only chip with aria-label='LiteLLM
on GitHub' (squash #27543), but the test still asserted /star us on
github/i. Update the query to match the rendered accessible name.
* refactor(dashboard): drop unused props from NavbarProps
The navbar refactor moved user identity + dark-mode state to internal
hooks (useAuthorized, useWorker), but the NavbarProps interface still
declared userID, userEmail, userRole, premiumUser, isDarkMode, and
toggleDarkMode as required, forcing every caller to thread them through.
Drop them from the interface and all four call sites (page.tsx,
(dashboard)/layout.tsx, public_model_hub.tsx, navbar.test.tsx). Also
shrinks the destructure in layout.tsx so the now-unused locals stop
being pulled out of useAuthorized().
* refactor(dashboard): use useSyncExternalStore for NotificationsBell dismiss flag
Reads/writes of the litellmHideAgentPlatformBanner key were done
directly inside NotificationsBell via a useEffect + useState pair.
Every other localStorage-backed flag in the dashboard (Disable
ShowPrompts, DisableBouncingIcon, DisableShowNewBadge,
DisableUsageIndicator, DisableBlogPosts) is wrapped in a
useSyncExternalStore hook over localStorageUtils so all mounted
components stay in sync.
Extract useHideAgentPlatformBanner to follow the same shape, swap
NotificationsBell to consume it, and add a regression test that
two sibling bells stay in sync without a remount when one is
dismissed.
* refactor: mask credential fields in proxy settings GET responses (#28682)
* refactor: mask credential fields in proxy settings GET responses
Brings SSO settings, cache settings, and the email/Slack alerting view in
/get/config/callbacks in line with the HashiCorp Vault config-override
pattern, so persisted credentials are not transported back to the UI in
plaintext.
* refactor: harden short-value masking and hoist alerting var constant
Closes two review observations:
- mask_sensitive_keys now replaces short values (below the visible
prefix+suffix length) with an all-mask string instead of returning them
unchanged, so a 1-7 character credential is no longer round-tripped
verbatim.
- _ALERTING_SENSITIVE_VARS is moved out of get_config() to a module-level
constant, matching the analogous _SSO_SENSITIVE_FIELDS and
_CACHE_SENSITIVE_FIELDS in the SSO and cache endpoint files.
---------
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* fix(ui): show 2-decimal precision for max_budget on key overview (#28809)
The Key Info Overview tab's Spend card truncated sub-dollar budgets to
"$0" because formatNumberWithCommas defaults to 0 decimals. The Settings
tab passes 2; align the overview so a $0.10 budget renders as "$0.10".
Resolves LIT-2845
* feat(proxy): allow `llm_api_routes` virtual keys to list MCP servers (#28442)
* feat(proxy): allow llm_api_routes virtual keys to list MCP servers
Add a new `mcp_discovery_routes` group (GET /v1/mcp/server and GET
/v1/mcp/server/{server_id}) and include it in `llm_api_routes` so that
virtual keys configured with `allowed_routes=["llm_api_routes"]` can
discover the MCP servers they have access to. Previously these calls
failed with 'Virtual key is not allowed to call this route. Only allowed
to call routes: [llm_api_routes]'.
The GET handlers already sanitize the response for restricted virtual
keys via `_sanitize_mcp_server_list_for_virtual_key`, stripping
credential-bearing fields (url, headers, env). Write methods
(POST/PUT/DELETE) on the same paths remain gated by the existing
handler-level admin role checks.
The new discovery list is intentionally kept OUT of
`mcp_inference_routes`, so `is_llm_api_route()` still returns False
for these paths — this preserves the existing contract that
DISABLE_LLM_API_ENDPOINTS must not block the Admin UI from listing MCP
servers.
Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com>
* refactor(proxy): make MCP discovery carve-out method-aware
Replace the `mcp_discovery_routes` group in `llm_api_routes` with a
method-aware special case inside `is_virtual_key_allowed_to_call_route`.
Virtual keys with allowed_routes=["llm_api_routes"] are now permitted
to call only GET /v1/mcp/server and GET /v1/mcp/server/{server_id} —
non-GET methods and multi-segment admin sub-paths fall through to the
existing 403. This keeps the general llm_api_routes list free of
management paths and avoids accidentally exposing POST/PUT/DELETE
writes through the route-check layer.
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com>
* chore(ci): merge dev branch (#28807)
* 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: shin-berri <shin-laptop@berri.ai>
Co-authored-by: user <70670632+stuxf@users.noreply.github.com>
* fix(team): keep team_alias cache in sync on _cache_team_object writes (#28737)
* fix(team): keep team_alias cache in sync on _cache_team_object writes
_cache_team_object wrote only to the team_id:<id> cache key, but the
JWT auth path that uses team_alias_jwt_field reads from a separate
team_alias:<alias> key (get_team_object_by_alias caches under both
keys on miss, but reads only the alias-keyed one). After any
team-mutation endpoint (team_model_add, team_model_delete,
update_team, the two access-group writes) the team_id cache was
refreshed but the team_alias cache stayed stale until TTL — JWT
callers using team_alias_jwt_field kept seeing the pre-mutation
team for the full cache window.
Mirror the write under the alias key inside _cache_team_object so
every existing caller stays in sync without further changes. Skip
the alias write when team_alias is None/empty so we don't collide
across alias-less teams.
Surfaced testing the LIT-3244 cherry-pick on patch/1.86.0: the
LIT-3244 fix correctly invalidated the team_id cache but the
customer's JWT used team_alias_jwt_field, so they kept hitting the
stale alias-keyed entry.
* fix(team): delete (not overwrite) team_alias cache on _cache_team_object
The prior shape of this PR wrote both team_id:<id> AND team_alias:<alias>
from _cache_team_object. team_alias is NOT unique in the schema
(no @unique on LiteLLM_TeamTable.team_alias), and get_team_object_by_alias
enforces uniqueness on its own DB-fetch path (len(teams) > 1 raises).
Writing the alias-keyed cache from the generic refresh path bypassed
that check: a team admin renaming their team to collide with another
team's alias could silently overwrite the cached team for JWT-by-alias
auth, swapping the resolved team under that alias for the cache window.
Switch the alias-keyed operation from a write to a delete (mirroring
the dual-cache delete pattern in _delete_cache_key_object). After every
team write, the next JWT-by-alias reader cache-misses and falls through
to get_team_object_by_alias, which (a) re-fetches the fresh team from
DB, closing the LIT-3244 staleness gap that motivated this PR, and
(b) enforces alias uniqueness before populating either cache key.
team_id:<id> writes are unchanged — team_id is the table PK and is
guaranteed unique.
Surfaced in veria-ai review on #28739.
* fix(managed-files): anchor model_id regex so it doesn't match llm_output_file_model_id
extract_model_id_from_unified_id used `re.search(r"model_id,([^;]+)", ...)`
which substring-matches the `model_id,` inside the file-ID encoding's
`llm_output_file_model_id,<deployment_uuid>` field. parse_unified_id
then fed that deployment UUID back into the auth path as a model
candidate via _extract_models_from_managed_resource_id, and every
team-BYOK file attach 403'd with:
team not allowed to access model. This team can only access
models=['openai/*']. Tried to access <deployment-uuid>
The team's models list correctly contains the public name (`openai/*`)
that target_model_names matches, but the bogus UUID candidate fails
the wildcard check first.
Anchor the regex to a field boundary (`(?:^|;)model_id,`) so it
matches the legitimate top-level `model_id,<value>` field on
vector_store unified IDs and skips substring matches inside other
fields. File-IDs (which have no top-level `model_id` field) now
return None and contribute no spurious UUID candidate.
Surfaced reproducing LIT-3244 on patch/1.86.0 with the customer's
exact flow: team with openai/* BYOK deployment, JWT-scoped user,
POST /v1/vector_stores/{id}/files attaching a file uploaded with
target_model_names=openai/gpt-4o.
* fix(proxy): hydrate wildcard discovery credentials (#28284) (#28822)
* fix(proxy): hydrate wildcard discovery credentials
* fix(proxy): constrain wildcard credential hydration
Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com>
* ci: add daily oss-agent-shin branch creation workflow (#28829)
Creates litellm_oss_agent_shin_MM_DD_YYYY from main every day at 00:00 UTC.
Lets us retarget oss-agent-shin fork PRs onto a canonical branch so CircleCI runs with secrets, without granting the agent write access.
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
* test(proxy): add harness for proxy_server.py behavior-pinning (#28827)
* test(proxy): add harness for proxy_server.py behavior-pinning
Creates tests/test_litellm/proxy/proxy_server/ with:
- conftest.py: 11 shared fixtures (app, client, mock_prisma, auth_as,
mock_router with parametrized response builders, normalize, etc.)
- _coverage_check.py: per-PR coverage gate (line + branch) against a
baseline, self-selects target by inspecting which placeholder files
have been filled
- _pin_check.py: AST-based gate that verifies every pin-list item has
>=1 happy + >=1 error test with a real assertion (no status-only)
- test_harness_smoke.py: 19 smoke tests covering every fixture +
both scripts end-to-end
- 26 placeholder test files (one docstring each) reserved for
follow-up PRs per the directory ownership in the Notion plan
- .coverage_baseline pinned at 0% so future PRs measure deltas
against new-tests-only and aren't entangled with the broader
scattered test suite
Adds a dedicated proxy-server job to test-unit-proxy-endpoints.yml
so this directory's runtime + coverage are tracked independently.
Plan: https://www.notion.so/36c43b8acdab81ee845fd5365128a2fc
* ci(proxy-endpoints): allow workflow_dispatch
Lets the workflow be triggered manually on a branch via
`gh workflow run`, which is needed for the verify-first
flow on workflow changes before opening a PR.
* test(proxy): address review feedback on proxy_server harness
- conftest.py: anchor sys.path insert to __file__ (Path(__file__).resolve().parents[4])
instead of CWD-relative os.path.abspath("../../../../") which resolved
to the wrong directory when pytest is launched from the repo root.
- _coverage_check.py: actually read .coverage_baseline and use it as
the floor (line_min = max(target, baseline)). Closes the gap between
the PR description's "delta semantics" and what the script was doing.
With baseline=0.0 today this is a no-op; future PRs that update the
baseline cause regressions (test deletions etc.) to trip the gate
even if the static PR target is still met.
- _pin_check.py: drop unreachable startswith("_") guard
(test_*.py glob never yields underscore-prefixed names) and read
each test file once instead of twice.
* feat(openai): apply regional-processing cost uplift for EU/US data residency (#28626)
* feat(openai): apply regional-processing cost uplift for EU/US data residency
OpenAI charges a 10% uplift on the latest GPT models when requests are
served from a regionalized hostname (eu./us.api.openai.com). Infer the
region from `api_base`, expose it on `kwargs["litellm_params"]["data_residency"]`,
and multiply the computed cost by a per-model
`regional_processing_uplift_multiplier_<region>` field.
https://claude.ai/code/session_012ebH44s7ohYxjoix5CXzTW
* test: allow regional_processing_uplift_multiplier_{eu,us} in model_prices schema
* fix(cost): tighten data_residency inference and restore model_cost in tests
- Only infer OpenAI data_residency when custom_llm_provider == "openai";
drop the implicit None fallback so non-OpenAI callers can't accidentally
pick up a regional tag from a stray OpenAI hostname.
- _local_model_cost_map fixture now snapshots and restores
litellm.model_cost and LITELLM_LOCAL_MODEL_COST_MAP so tests don't leak
state across the session.
* refactor(openai): move data_residency helper under llms/openai
* fix: thread data_residency through realtime stream cost calculation
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(cost): thread data_residency through batch_cost_calculator
Apply the OpenAI regional-processing uplift multiplier to retrieve_batch
cost paths so Batch API requests served via eu./us.api.openai.com are
priced at the same uplifted token rates as completions/transcriptions.
* refactor(openai): encapsulate provider check inside infer_openai_data_residency
Move the custom_llm_provider == "openai" guard from get_litellm_params
into the helper itself so the core utility no longer carries
provider-specific dispatch logic. Callers pass through the provider
unconditionally; the helper returns None for any non-OpenAI provider.
* fix(responses): thread data_residency through Responses logging params
The Responses API paths build their logging litellm_params dict after
provider resolution but did not include data_residency, so cost calc
saw None even when the effective api_base was a regional OpenAI host.
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: user <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com>
Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com>
Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
* fix: preserve OTEL response payload and remove duplicate constant
- _emit_management_endpoint_otel_span now passes result as response on success
- remove duplicate _CREDENTIAL_LITELLM_PARAM_FIELDS assignment in model_checks
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix: address bug detection findings
- pass_through_endpoints: use request.method instead of hardcoded POST
in streaming SigV4-signed request path for consistency with the
non-streaming branch
- llm_cost_calc/utils: hoist DataResidency value set to a module-level
frozenset to avoid rebuilding it on every cost calculation
- example_config_yaml/oai_misc_config: replace real-looking AWS account
ID with placeholder 123456789012 in example bucket and role ARN
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* chore(github_copilot): refresh model catalog from upstream /models API (#28055)
Aligns the github_copilot catalog with values returned by Copilot's
public /models endpoint (capabilities.limits + capabilities.supports +
model.supported_endpoints).
- Adds 10 new model entries: claude-opus-4.7, claude-sonnet-4.6,
gemini-3-flash-preview, gemini-3.1-pro-preview, gpt-4-0125-preview,
gpt-5.2-codex, gpt-5.4, gpt-5.4-mini, gpt-5.5, oswe-vscode-prime.
- Updates max_input_tokens for existing entries to reflect each
model's true context window (e.g. gpt-4o-mini 64000 -> 128000,
gpt-5-mini 128000 -> 264000, gpt-5.3-codex 128000 -> 400000,
claude-haiku-4.5 128000 -> 200000).
- Adds supports_reasoning, supports_response_schema,
supports_function_calling, supports_parallel_function_calling,
supports_vision based on capabilities.supports.
- Declares supported_endpoints for entries missing it
(e.g. gpt-3.5-turbo, gpt-4o, embeddings).
- For responses-only models (gpt-5.2-codex, gpt-5.4, gpt-5.4-mini,
gpt-5.5), sets mode to 'responses'.
- gpt-41-copilot.mode changes from 'completion' to 'chat' because
Copilot reports capabilities.type = 'chat'. Revertible on request.
Pricing fields and other manually-curated values are preserved.
* feat(datadog): emit litellm.overhead.latency as a standalone Datadog metric (#28831)
Adds a new `litellm.overhead.latency` gauge metric to `DatadogMetricsLogger`
(the `/api/v2/series` path). The value is sourced from
`hidden_params["litellm_overhead_time_ms"]` already computed in
`ResponseMetadata` and exposed in `StandardLoggingPayload`.
Matches the Prometheus integration which exposes the same value via
`litellm_overhead_latency_metric`. Emitted in seconds (ms ÷ 1000) for
consistency with the other latency series.
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Shin <shin@litellm.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com>
* feat(arize): route Phoenix traces via per-project TracerProviders (#28876)
Use LRU-cached TracerProviders with project-scoped OTEL Resources so team/key
metadata routes traces correctly. On the proxy, project selection is limited to
server-controlled user_api_key_auth_metadata; client metadata fields stay banned.
* fix(arize_phoenix): skip _emit_semantic_logs on failure path
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(arize_phoenix): skip raw request logging and metrics on failure path
Restores pre-refactor behavior: _handle_failure no longer emits raw-request
sub-spans or records OTEL metrics, matching the original _handle_failure
that did not call these helpers.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(security): close two medium telemetry trust-boundary issues
Issue 1 (arize_phoenix.py — caller-controlled telemetry routing):
- _is_proxy_request no longer detects proxy mode by checking
user_api_key_auth_metadata in request metadata. That field is
user-supplied, so an authenticated caller could fake proxy-mode
detection and have _project_from_metadata_dict read their own dict
for project selection, routing telemetry to arbitrary Arize/Phoenix
projects. Proxy mode is now determined solely by the server-set
proxy_server_request field in litellm_params.
- auth_utils.py adds user_api_key_auth_metadata to the banned request
body params list so the proxy rejects any attempt to supply the field
at the HTTP layer. The field is server-reserved: it is written
exclusively by add_user_api_key_auth_to_request_metadata from the
authenticated key's database record after the ban check runs.
Issue 2 (management_helpers/utils.py — API key in OTEL span):
- _emit_management_endpoint_otel_span stripped plaintext credential
fields (key, token, api_key, secret, …) from the response dict before
passing it to the OTEL success hook. dict(result) on a Pydantic
GenerateKeyResponse includes the freshly-generated key field, which
would previously be written as a span attribute to every configured
OTEL collector/backend.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: Terrajlz <info@jouleselectrictech.com>
Co-authored-by: Bruno Devaux <devaux.br@gmail.com>
Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local>
Co-authored-by: user <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com>
Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com>
Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
Co-authored-by: rinto <54238243+ririnto@users.noreply.github.com>
Co-authored-by: Shin <shin@litellm.ai>
Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com>
DotpromptManager was hardened to render through
ImmutableSandboxedEnvironment. The three sibling managers (gitlab,
arize, bitbucket) were missed and still instantiate plain
jinja2.Environment(), leaving the same attribute-traversal SSTI
primitive open: a template fetched from a GitLab/BitBucket repo or
Arize Phoenix workspace can reach __class__.__init__.__globals__ and
execute arbitrary Python on the proxy host.
Match the dotprompt pattern by switching all three to
ImmutableSandboxedEnvironment. The sandbox blocks the dunder-traversal
chain while leaving normal {{ var }} substitution intact, so the
template surface is unchanged for legitimate use.
Adds tests/test_litellm/integrations/test_prompt_manager_ssti.py
(18 cases) verifying each manager's jinja_env is a sandbox, that
classic SSTI payloads raise SecurityError, and that ordinary variable
rendering still works.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* [Feat] Day-0 support for GPT-5.5 and GPT-5.5 Pro (#26449)
* feat(openai): day-0 support for GPT-5.5 and GPT-5.5 Pro
Add pricing + capability entries for the new GPT-5.5 family launched by
OpenAI on 2026-04-24:
- gpt-5.5 / gpt-5.5-2026-04-23 (chat): $5/$30/$0.50 per 1M
input/output/cached input
- gpt-5.5-pro / gpt-5.5-pro-2026-04-23 (responses-only): $60/$360/$6
per 1M input/output/cached input
Other fees (long-context >272k, flex, batches, priority, cache
discounts) follow the same ratios as GPT-5.4, with context window
retained at 1.05M input / 128K output.
No transformation / classifier code changes are required:
OpenAIGPT5Config.is_model_gpt_5_4_plus_model() already matches 5.5+ via
numeric version parsing, and model registration is driven from the
JSON. The existing responses-API bridge for tools + reasoning_effort
(litellm/main.py:970) already covers gpt-5.5-pro.
Tests:
- GPT5_MODELS regression list now covers gpt-5.5-pro and dated variants
- New test_generic_cost_per_token_gpt55_pro cost-calc test
- Updated test_generic_cost_per_token_gpt55 for long-context fields
* fix(openai): mirror reasoning_effort flags onto gpt-5.5 dated variants
gpt-5.5-2026-04-23 and gpt-5.5-pro-2026-04-23 were missing the
supports_none_reasoning_effort, supports_xhigh_reasoning_effort, and
supports_minimal_reasoning_effort flags that their non-dated
counterparts define. Reasoning-effort routing in OpenAIGPT5Config is
fully capability-driven from these JSON flags — since an absent flag
is treated as False for opt-in levels (xhigh), users pinning to a
dated snapshot would silently lose xhigh support and diverge from the
base alias on logprobs + flexible temperature handling.
Copy the flags onto both dated variants so every dated snapshot
inherits the base model's reasoning-effort capability profile.
Adds a parametrized regression test that asserts
supports_{none,minimal,xhigh}_reasoning_effort parity between each
dated variant and its non-dated counterpart, preventing future drift
when new snapshots are added.
* [Feat] Add azure/gpt-5.5 + azure/gpt-5.5-pro entries (+ dated variants) (#26361)
* feat(azure): add azure/gpt-5.5 + azure/gpt-5.5-pro entries (+ dated variants)
Azure variants of OpenAI's GPT-5.5 family. Microsoft has not yet
shipped GPT-5.5 on Azure OpenAI (latest GA on the Foundry models page
is GPT-5.4 as of 2026-04-24), but adding the entries day-0 mirrors the
established precedent for azure/gpt-5.4* (which were in the cost map
before the Azure rollout) so cost tracking and capability flags work
the moment customers deploy.
Schema follows the existing azure/gpt-5.4* shape:
- Same base/long-context pricing as openai/gpt-5.5*: $5/$30 chat,
$60/$360 pro per 1M, with priority tier 2x base
- Azure variants drop the flex/batches keys (Azure has no flex tier)
but keep priority pricing, matching gpt-5.4* precedent
- mode=chat for the thinking model, mode=responses for pro
reasoning_effort capability flags mirror the OpenAI variants exactly
since Azure proxies the same API contract: minimal rejection on both
chat and pro, low/none rejection on pro. Once #26456 (which sets
supports_low_reasoning_effort + minimal=false on openai/gpt-5.5*)
lands, OpenAI and Azure flag profiles align.
Tests pin entry presence + pricing for all four Azure variants and
verify the live-API-derived reasoning_effort flags.
* test: register supports_low_reasoning_effort in cost-map JSON schema
azure/gpt-5.5-pro and azure/gpt-5.5-pro-2026-04-23 added in this branch
carry supports_low_reasoning_effort=false. The strict
'additionalProperties: false' schema in
test_aaamodel_prices_and_context_window_json_is_valid rejected the new
key. Register it alongside the other supports_*_reasoning_effort
entries.
Note: the runtime side of this flag (code that reads it) lands in
#26456. Until that PR merges the flag is inert for both Azure and
OpenAI pro entries, but having the schema accept it lets cost-map
tests pass on either merge order.
* fix(arize/langfuse_otel): handle Pydantic usage objects without `.get`
`_set_usage_outputs` called `usage.get(...)` and
`usage.get('output_tokens_details', {}).get('reasoning_tokens')`. These
crash with `AttributeError: 'CompletionUsage' object has no attribute
'get'` when `usage` (or the nested token-details object) is a raw OpenAI
Pydantic model rather than a dict / litellm `Usage` wrapper. Reproduces
on the langfuse_otel + arize Responses API logging paths.
Fixes#13672.
Changes:
- Add `_safe_get(obj, key, default)` that prefers dict-style `.get` when
available and otherwise falls back to `getattr`. Works uniformly for
dicts, litellm's `Usage`, and plain Pydantic models like
`openai.types.completion_usage.CompletionUsage` /
`CompletionTokensDetails` / `OutputTokensDetails`.
- Use `_safe_get` for total / completion / prompt / output tokens.
- Look for reasoning tokens in `completion_tokens_details` (Chat
Completions API) before falling back to `output_tokens_details`
(Responses API). Previously reasoning tokens from the Chat Completions
API were silently dropped.
Tests:
- `test_set_usage_outputs_pydantic_completion_usage` — covers the chat
completions path with raw `CompletionUsage` + `CompletionTokensDetails`.
- `test_set_usage_outputs_pydantic_response_api_usage` — covers the
Responses API path with a Pydantic usage object lacking `.get`.
Both tests fail on main before this commit and pass after.
---------
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: alvinttang <alvin@pm.me>
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
- ArizePhoenixLogger now creates spans on its own dedicated TracerProvider
instead of trying to reuse parent spans from the global otel TracerProvider
(which were invisible in Phoenix since they go to a different exporter)
- Auto-initialize ArizePhoenixLogger when otel callback is configured and
Phoenix env vars (PHOENIX_API_KEY, PHOENIX_COLLECTOR_*) are detected
- Use exact type check in get_custom_logger_compatible_class to prevent
ArizePhoenixLogger (subclass) from being returned when looking up otel
- Fix tool_permission guardrail to check non-function tools like
code_interpreter (previously skipped with `type != "function"`)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Arize Phoenix and Arize loggers now create dedicated TracerProviders
instead of fighting over the global singleton, and the otel callback
dedup check no longer incorrectly matches Arize subclasses.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Allow per-request Phoenix project name via `metadata.phoenix_project_name`, falling back to PHOENIX_PROJECT_NAME env var
- Add missing `post_call_success_hook` to `/images/generations` endpoint so guardrails and OTEL tracing apply to image generation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: enforce team member budget check in common_checks
- Add missing team member budget validation in common_checks() function
- Checks team membership budget when team key is used
- Raises BudgetExceededError when team member spend exceeds max_budget_in_team
- Follows same pattern as other budget checks (team, user, end_user)
- Uses cached get_team_membership() for performance
- Fix AttributeError in lowest_tpm_rpm.py
- Add null check for model_info before accessing .get() method
- Prevents 'NoneType' object has no attribute 'get' error
- Add unit tests for team member budget enforcement
- Test budget exceeded scenario
- Test within budget scenario
- Test edge cases (no budget, no membership, personal keys)
- Tests run without requiring proxy server
Fixes failing test: test_users_in_team_budget
* fix: mock get_async_httpx_client in test_langsmith_key_based_logging
- Mock get_async_httpx_client to return a mock AsyncHTTPHandler instance
- Fixes test failure where mock_post was never called
- LangsmithLogger creates its own httpx client instance via get_async_httpx_client,
so we need to mock the factory function rather than the class method
- Use MagicMock for response.raise_for_status (sync method) instead of AsyncMock
* fix: resolve linting errors (PLR0915, F401)
- Remove unused imports (datetime, ServiceLoggerPayload) from arize_phoenix.py
- Extract health ping setup logic from RedisCache.__init__ to reduce statement count
- Extract team member budget check from common_checks to reduce statement count
* fix: resolve type errors in ChatCompletionToolCallChunk construction
- Cast type field to Literal['function'] to satisfy TypedDict requirements
- Ensure arguments field is explicitly str type to match TypedDict signature
- Fixes pyright errors for incompatible types in transformation.py
* Fix duplicate imports in SAP embedding transformation
* fix: add missing prompt_spec parameter to HumanloopLogger.get_chat_completion_prompt
- Add prompt_spec: Optional[PromptSpec] = None parameter to match base class signature
- Import PromptSpec from litellm.types.prompts.init_prompts
- Pass prompt_spec to super().get_chat_completion_prompt() call
- Fixes mypy type error: Signature incompatible with supertype CustomLogger
* fix: add missing parameters to AnthropicCacheControlHook.async_get_chat_completion_prompt
- Add ignore_prompt_manager_model and ignore_prompt_manager_optional_params parameters
- Change litellm_logging_obj type from Any to LiteLLMLoggingObj using TYPE_CHECKING pattern
- Pass all parameters including prompt_spec to get_chat_completion_prompt call
- Fixes mypy type errors: Signature incompatible with supertype CustomLogger and PromptManagementBase
* fix: add missing parameters to DotpromptManager.async_get_chat_completion_prompt
- Add ignore_prompt_manager_model and ignore_prompt_manager_optional_params parameters
- Change litellm_logging_obj type from Any to LiteLLMLoggingObj using TYPE_CHECKING pattern
- Pass all parameters including ignore flags to PromptManagementBase.async_get_chat_completion_prompt
- Fixes mypy type errors: Signature incompatible with supertype CustomLogger and PromptManagementBase
* fix: document envs
* fix: add missing parameters to LangfusePromptManagement.async_get_chat_completion_prompt
- Add ignore_prompt_manager_model and ignore_prompt_manager_optional_params parameters
- Pass all parameters including prompt_spec and ignore flags to get_chat_completion_prompt
- Fixes mypy type errors: Signature incompatible with supertype CustomLogger and PromptManagementBase
* fix: add missing parameters to prompt management async methods (Category 1)
- vector_store_pre_call_hook: add ignore_prompt_manager_model, ignore_prompt_manager_optional_params, prompt_spec
- gitlab_prompt_manager: add ignore parameters, fix litellm_logging_obj type
- bitbucket_prompt_manager: add ignore parameters, fix litellm_logging_obj type
- proxy/custom_prompt_management: add prompt_spec parameter
- Fixes mypy type errors: Signature incompatible with supertype
* fix: fix arize_phoenix_prompt_manager and custom_prompt_management (Category 2)
- arize_phoenix_prompt_manager: add prompt_spec to all methods, fix prompt_id types, implement async_compile_prompt_helper
- custom_prompt_management: implement async_compile_prompt_helper abstract method
- Fixes mypy type errors: Signature incompatible with supertype and abstract method errors
* fix: fix obvious type errors (Category 3 - Quick Wins)
- langfuse: change 'callable' to 'Callable' type annotation
- presidio: add type narrowing check for Choices vs StreamingChoices
- StreamingChoices doesn't have .message attribute, only Choices does
- Add hasattr check before accessing choice.message
- Fixes mypy type errors: callable? not callable and union-attr errors
* fix: handle expires_after None in Azure files handler (Todo 14)
- Extract logic to _prepare_create_file_data helper method
- Remove expires_after from dict if None to match SDK's Omit pattern
- Add type ignore for FileExpiresAfter -> file_create_params.ExpiresAfter mismatch
- Fixes mypy error: Argument expires_after has incompatible type
* fix: change purpose parameter type to OpenAIFilesPurpose (Todo 18)
- Import OpenAIFilesPurpose in storage_backend_service.py
- Change upload_file_to_storage_backend purpose parameter from str to OpenAIFilesPurpose
- Change _create_file_object_with_storage_metadata purpose parameter from str to OpenAIFilesPurpose
- Fixes mypy error: Argument purpose has incompatible type str; expected Literal type
- Purpose is already validated in files_endpoints.py before reaching these functions
* fix: handle UploadFile | str type for expires_after form fields (Todo 19)
- Validate expires_after[anchor] and expires_after[seconds] are strings, not UploadFiles
- Validate anchor equals 'created_at' before using literal in TypedDict
- Use literal 'created_at' (not variable) in FileExpiresAfter to satisfy Literal type
- Add proper error handling for invalid anchor values and int conversion
- Fixes mypy errors: Incompatible types for anchor and seconds in FileExpiresAfter
* fix: add type narrowing for expires_after_seconds_str to fix mypy error
- Add assert statement after UploadFile validation to help mypy narrow type
- Use validated variable with explicit str type annotation
- Fixes: Argument of type 'UploadFile | str' cannot be assigned to int()
* fix: trigger async_success_handler for MCP tool calls to enable cost tracking and logging
- Set call_type to CallTypes.call_mcp_tool.value before calling async_success_handler
- Update mcp_tool_call_metadata with cost info when server is found
- Call async_success_handler to build standard_logging_object and trigger callbacks
- Fixes test_mcp_cost_tracking by ensuring standard_logging_payload is populated
* refactor: use positive isinstance check for safer type narrowing
- Replace assert with positive isinstance(..., str) check
- Matches codebase pattern (see pass_through_endpoints.py)
- Safer than assert: assertions can be disabled with -O flag
- Mypy properly narrows type after positive isinstance check
- More explicit and readable than assert statement
* fix: add missing REDIS_DAILY_AGENT_SPEND_UPDATE_QUEUE to ServiceTypes enum (Todo 17)
- Add REDIS_DAILY_AGENT_SPEND_UPDATE_QUEUE enum value following the pattern of other daily spend queues
- Add corresponding entry to DEFAULT_SERVICE_CONFIGS with GAUGE metrics
- Fixes mypy error: 'type[ServiceTypes]' has no attribute 'REDIS_DAILY_AGENT_SPEND_UPDATE_QUEUE'
- This enum value is already used in redis_update_buffer.py for agent spend tracking
* docs(prompt_management.md): document how to onboard prompts to litellm
* feat(arize_phoenix_prompt_manager.py): support new prompt management integration
allows users to connect arize phoenix prompt manager to litellm
* fix(proxy/utils.py): remove prompt variables to avoid re-processing prompt
* docs(arize_phoenix_prompts.md): document new prompt management integration
* Litellm dev 11 22 2025 p1 (#16975)
* fix(model_armor.py): return response after applying changes
* fix: initial commit adding guardrail span logging to otel on post-call runs
sends it as a separate span right now, need to include in the same llm request/response span
* fix(opentelemetry.py): include guardrail in received request log + set input/ouput fields on parent otel span instead of nesting it
allows request/response to be seen easily on observability tools
* fix(model_armor.py): working model armor logging on post call events
* fix: fix exception message
* fix(opentelemetry.py): add backwards compatibility for litellm_request
allow users building on the spec change to use previous spec
* feat(anthropic/chat/transformations): for claude-4-5-sonnet and opus-4-1 support passing structured output to anthropic api
* docs: document new feature
* fix: fix output format
* fix: cleanup
* fix(transformation.py): conditionally pass in json tool call
* fix: support ARIZE_SPACE_ID instead of ARIZE_SPACE_KEY
* docs(arize_integration.md): cleanup arize docs
* feat(callback_info_helpers.tsx): allow setting arize space id via ui
* fix: fix linting error
* fix(opentelemetry.py): working arize phoenix root span tracing
