Request metadata carries the whole UserAPIKeyAuth object, whose team_metadata
holds the customer's own langfuse callback_vars. The only filter on the emitted
blob was a four key deny list written as a circular reference crash guard, so
those credentials reached the customer's own langfuse traces.
The emitted blob is now the StandardLoggingPayload allowlist plus the litellm
computed enrichments, and nothing is copied across from raw request metadata.
That makes the credential exclusion structural rather than a filter someone has
to keep correct. Steering keys keep reading raw metadata, matching literal_ai.
Proxy callers are unaffected: their request metadata already rides under the
allowlisted requester_metadata key, nesting intact.
debug_langfuse dumped raw request metadata into the trace as a second copy of
the same leak. It now emits caller scalars only.
When StandardLoggingPayload is absent the trace is still emitted with the
existing trace_id fallback, so failure traces survive.
langfuse_* request headers land in metadata as strings, but the trace path reads
mask_input/mask_output with a bare truthiness check and iterates update_trace_keys
directly. A header saying mask_input: false redacted the payload it was asked to
keep, and update_trace_keys was walked one character at a time so every requested
key silently failed to match
* fix(langfuse): emit otel trace version and release on the keys langfuse v4 reads
The langfuse_otel exporter wrote version to langfuse.generation.version and
langfuse.trace.version, and release to langfuse.trace.release. Langfuse v4
recognizes neither, so both landed in the generic span attribute bag and every
trace reported version and release as null. v4 has a single langfuse.version
key, lifted to the trace when it sits on the root span, plus langfuse.release.
Also routes the otel v2 preset's per-request headers through the shared builder
so key-scoped and team-scoped exports carry x-langfuse-ingestion-version like
the other three exporter paths already do.
* fix(langfuse): give trace_version precedence over version on the shared v4 key
Matches the documented contract in docs/observability/langfuse_integration.md
and the legacy langfuse SDK callback, which both treat trace_version as the
authoritative trace version with version as its fallback.
Python keeps only the last binding for a name, so when a file defines the same
test twice the earlier one is unreachable. pytest cannot collect a function that
no longer exists, so nothing reports it and the file still looks like it covers
the scenario.
These ten are cases where the two definitions have different bodies, meaning a
real test was replaced rather than duplicated. Each is renamed to say what it
actually covers, which makes it reachable again:
- test_gemini_frequency_penalty: the dead copy checks the parameter is listed in
get_supported_openai_params for vertex_ai; the survivor checks get_optional_params
maps a value for gemini. Different function and different provider.
- test_async_log_success_event_adds_to_queue and the failure variant: the dead
copies run without mocking asyncio.create_task, so they exercise the real task
path the survivors mock out.
- test_async_send_batch_triggers_tasks: the dead copy asserts send is not awaited
directly; the survivor asserts create_task was called.
- test_model_id_in_required_metrics: the dead copy checks the model_id label on
twelve further metrics the survivor dropped.
- test_anthropic_messages_pt_file_block_preserves_cache_control: the dead copy
passes model and llm_provider explicitly and uses real base64 PDF content.
- test_translate_streaming_openai_chunk_to_anthropic_with_thinking: the dead copy
covers thinking_delta; the survivor covers signature_delta.
- test_client_initialization and test_client_without_api_key: the dead copies
assert the resource clients are wired with the right base URL and key; the
survivors only construct the object.
- test_client_initialization_strips_trailing_slash: the dead copy constructs
ModelsManagementClient directly rather than going through Client.
Verification: collecting the seven touched files gives 401 node IDs before and
411 after, the ten new names and nothing else, with nothing lost. All ten pass.
Running the touched files in full gives 299 passed, and test_optional_params.py
goes from 111 passed to 112.
Two further shadowed definitions were left alone rather than renamed: the dead
copies of test_prompt_caching and test_cost_calculator_with_base_model_with_router
have no assertions at all, one being a bare pass and the other a lone import, so
restoring them would add tests that cannot fail.
Three groups, all verified by running the suite rather than by inspection.
18 files whose every test function carries an unconditional @pytest.mark.skip,
39 test functions in total. They are collected on every CI run and always skip,
so they advertise coverage the suite does not have. Reasons on the marks include
"AWS Suspended Account", "lakera deprecated their v1 endpoint" and "moved to
using 'otel' for logging"; 26 of the marks predate 2025.
30 test functions with a byte-identical body and identical decorators to a
sibling in the same file and class, differing only in name. Deleting one of each
pair removes no coverage. Four further candidates were excluded because they
override an inherited test, where deleting the override un-shadows the base
class implementation instead of removing a duplicate.
9 test functions that a later definition of the same name shadows, so Python
never binds them and pytest cannot collect them.
One file that is a demo script rather than a test; its own docstring says to run
it with python.
Verification: collecting the 26 edited files gives 2,492 node IDs before and
2,462 after. The 30 duplicate deletions account for exactly 30 removals, the 9
shadowed deletions account for 0 (confirming at runtime that they were never
collectable), nothing unexplained disappeared, and nothing new appeared. No
other test or module imports any deleted symbol.
A capped pre-wait still burns the first daily pass when the router takes
longer than the cap to appear (a >10 minute boot), and reads the router
in two places. Folding the poll into the loop makes the first alert
unconditional on boot duration and keeps a single read per pass.
* fix(alerting): dedupe scheduled Slack spend reports across pods
Every pod ran its own weekly/monthly spend report jobs, prometheus
fallback stats cron, and daily report loop, so deployments with
multiple replicas or uvicorn workers received one copy per pod.
Gate each scheduled send behind the shared PodLockManager redis lock.
The lock is never released: its TTL (the full reporting window for the
weekly interval job, whose per-pod anchors drift by boot time and
jitter) doubles as a sent-this-window marker. acquire_lock returning
None (no redis wired) proceeds, preserving single-pod behavior.
Also generalize the pod lock could-not-acquire log line, which claimed
to be about spend tracking for every consumer.
Fixes#14809
* fix(alerting): harden spend report locks after adversarial review
Weekly lock TTL gets an hour haircut: with ttl equal to the interval,
the winner re-fires just before its own key expires, reacquires without
a TTL refresh, and the key then lapses in time for a trailing pod to
re-send. Job/lock ids move to litellm/constants.py per convention, and
spend_report_frequency now rejects non-positive day counts, which
previously coerced to an every-second schedule and would now compute a
negative lock TTL that silently never sends.
Adds the missing test coverage the review flagged: startup_event's
pod_lock_manager wiring (identity-asserted), the prometheus closure's
positive path, and the ungated immediate prometheus send pinned to
exactly one await.
* test(alerting): consolidate spend_report_frequency validator coverage
Drops a duplicate non-positive-days test and parametrizes the survivor
over the suffix half of the validator too
* fix(alerting): route the startup prometheus fallback send through the pod lock
Greptile caught that the boot-time send still ran once per pod when
PROMETHEUS_URL is set, the same duplication class this PR removes
* fix(alerting): make report lock acquisition non-reentrant
Greptile caught that a pod booting within an hour of the fallback stats
cron sent twice: the startup send takes the lock, then the cron fire
hits acquire_lock's reacquire branch, which returns True for the
holder. Window-marker gates now pass allow_reentrant=False so a live
lock blocks everyone including its holder; leader-election consumers
keep the reentrant default
* test(proxy): give spec'd ProxyLogging mocks a db_spend_update_writer
_initialize_slack_alerting_jobs now reads it for the pod lock manager,
and spec=ProxyLogging blocks instance-only attributes
* feat(proxy): per-key prompt caching auto-injection via enable_prompt_caching
Adds a key-level enable_prompt_caching toggle that auto-injects Anthropic
cache_control breakpoints on requests made with that key, without requiring
the gateway-wide enable_anthropic_prompt_caching flag. The flag lives in key
metadata, is stamped onto the request root by add_key_level_controls, rides
kwargs into both the /chat/completions seeding path and the native
/v1/messages path, and reuses every existing gate (anthropic/bedrock only,
supports_prompt_caching, client markers win). Client-supplied body values are
stripped as an untrusted root control field. Includes the Admin UI switch on
key create and key edit plus a read-only settings row, and dedupes the key
edit view's drifted initial-values objects.
* fix(proxy): drop section comment and suppress LIT011 on key-level prompt caching stamp
The daily loop no longer captures the startup Router or bails when the alert type is off at startup, so config reloads take effect
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* 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>
Surfaces deprecation_date metadata that is already shipped in
model_prices_and_context_window.json so operators get lead time to
migrate before a provider sunsets a model.
- New helper litellm.proxy.common_utils.model_deprecation classifies the
router's configured models into deprecated / imminent / upcoming
buckets. Resolution order: explicit model_info.deprecation_date >
model_info.base_model > litellm_params.model.
- New GET /model/deprecations (and /v1/model/deprecations) endpoint
returns a ModelDeprecationResponse, gated by user_api_key_auth.
- New AlertType.model_deprecation_warnings (in DEFAULT_ALERT_TYPES) plus
SlackAlerting.send_model_deprecation_alert dispatches a Slack message
for deprecated/imminent models. Severity is High when any model is
already past its date, Medium when only imminent.
- ProxyLogging.startup_event schedules a daily background task
(_run_scheduled_deprecation_check) when the alert type is enabled. The
interval is configurable via LITELLM_MODEL_DEPRECATION_CHECK_INTERVAL
and the warn window via LITELLM_MODEL_DEPRECATION_WARN_DAYS.
- Tests: 16 unit tests for the helper plus 4 for the Slack hook in
tests/test_litellm/.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(otel): mark v2 server spans as failed for pre-call errors (LIT-4780)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): authenticate malformed-body requests before rejecting them (LIT-4780)
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(auth): cover malformed-body rejection when auth error is recovered
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(auth): skip authorization for a request whose body never parsed
Deferring the parse failure ran the full auth phase, including budget reservation, whose reserved amount is only released by the endpoint's post call path; the endpoint never runs, so malformed requests leaked reservations and locked a budgeted key out. Authorization now runs only when the body parsed, and a parse failure with a rejected key keeps returning the 400 it returned before.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: shivam <shivam@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): name the RPC system and upstream on MCP tool-call spans
An MCP tool-call span carried only gen_ai.*, mcp.* and litellm.* attributes. A
CLIENT span holding none of the http/db/messaging/rpc families is
unclassifiable, so Elastic APM indexed these spans as span.type=unknown with no
span.subtype at all, and its span-links API then rejected the whole trace with
"Missing required fields (span.subtype)".
MCP frames every message as JSON-RPC 2.0, so the tool-call span now names
rpc.system. It names server.address and server.port alongside it, derived from
the already-redacted mcp_server_resource origin: naming the RPC system makes a
consumer treat the span as a downstream dependency and key that dependency off
the server address, so emitting one without the other labels the dependency
":0".
The tools/list span is left alone. It reaches the callbacks with no upstream
identity, and a listing can span several upstreams, so it has no address to
attach and would produce exactly that ":0" node.
The wire is untouched: streamable MCP still returns HTTP 200 with isError: true.
* fix(otel): drop rpc.system when no MCP upstream address resolved
server.address and server.port come from mcp_server_resource, which is absent
whenever the tool name resolves to no registered server, is None for a stdio
transport that has no host to log, and parses to no host for an IPv6 origin the
redactor rebuilds without its brackets. rpc.system was stamped unconditionally,
so each of those paths emitted it alone and named the dependency ":0", the
outcome the address pair exists to prevent.
Gating the system attribute on a resolved address makes the pairing structural
rather than leaving it to the two extractors happening to agree.
* fix(otel): require a full MCP destination before naming the RPC system
The gate gave rpc.system a resolved address, but not a resolved port. A
host-bearing scheme outside the HTTP(S) default-port map resolves an address
alone, and mcp_servers[].url is not scheme-validated, so an origin like
mcp://host or ws://host reaches the mapper and names the dependency host:0
instead of the :0 the previous commit removed.
Gating on the complete pair closes it, and covers a port of 0 as well.
_upstream_address_port also gets a direct contract test, including the IPv6
origin the redactor rebuilds without brackets.
* fix(otel): do not raise when an MCP origin has an unparseable port
_redact_mcp_resource_url rebuilds the origin without its IPv6 brackets, so a
zone-scoped address leaves a truthy hostname behind that the host check admits:
http://[fe80::1%25eth0]:80 becomes http://fe80::1%25eth0:80, whose hostname is
fe80 and whose port raises ValueError. That propagated out of
MCPToolCallSpanData.from_standard_logging_payload and cost the span.
Reading both halves inside a guard degrades an unparseable origin to no address,
which is already how the mapper treats an unresolvable upstream, and matches the
guard the redactor puts around the same split. The scheme default port drops the
dict literal so the LIT002 ceiling stays put.
* fix(websearch): restore snippet text in native web_search_tool_result blocks (LIT-5315)
The build_web_search_tool_result_block method copied url/title/page_age but
hardcoded encrypted_content to empty string, never reading SearchResult.snippet.
This left every native block content-free, forcing clients to web_fetch each
result to recover evidence—the reported symptom.
The Anthropic spec carries page text only in encrypted_content (an opaque
server-issued blob we cannot mint), so snippet is emitted as an additive key
alongside the spec fields. encrypted_content stays empty rather than holding
plaintext, which would assert encryption semantics that don't hold.
The anthropic SDK's BaseModel sets extra='allow', so the additive snippet key
survives SDK parsing. litellm has no typed model for web_search_result at all,
so nothing drops it internally. Turn-2 replay behavior is unaffected: the
empty encrypted_content already exists today.
Tests:
- Updated test_shape_with_results to assert snippet present
- Added test_snippet_carried_for_every_result to cover multi-result ordering
- Added test_missing_snippet_degrades_to_empty_string for edge case
- Mutation check: reverting source-only yields 3 test failures, restored to 117 passed
Fixes: LIT-5315
Co-Authored-By: Claude <noreply@anthropic.com>
* fix(websearch): make synthesized web_search blocks replayable by native clients
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(websearch): flatten a resultless replayed search block so Bedrock accepts the next turn
The flatten added for LIT-5315 bails when the replayed web_search_tool_result
carries an empty content list, but that is exactly what the interceptor emits
when a search legitimately returns nothing and when a search raises. The block
survived into the outbound body, Bedrock rejected the tag, and the conversation
died on the following turn just as it did before the flatten existed.
An empty content list has no encrypted_content to respect and no evidence to
preserve, so it flattens safely, and its paired server_tool_use goes with it.
The rendered text now says so explicitly rather than emitting a bare header.
Adds the multi-turn replay coverage that existed nowhere: the outbound Bedrock
invoke body is asserted free of both block types, parametrized over the
results-present and resultless cases, and built from the interceptor's own
builder so the fixture cannot drift from what it emits.
Resolves LIT-5320
* test(websearch): pin flatten idempotency for the agentic-loop re-entry
The agentic loop re-enters the same /v1/messages entry point for its follow-up
call and hands it the original client history, so the flatten runs again over
already-flattened messages once per iteration. Bedrock always takes that path,
since its config reports web search as natively handled and the short-circuit
is skipped.
A pass that appended the rendered text instead of replacing the block would
duplicate the evidence on every iteration and re-ship the unsupported tag, and
no existing single-pass test sees it. Mutation checked: keeping the original
block alongside the rendered text fails this test on its own.
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Making Sentinel follow AZURE_AUTHORITY_HOST is a breaking change for a
deployment that sets that variable for Azure OpenAI or the azure_storage
callback while keeping a commercial Sentinel workspace. That deployment had no
opt-out, because the proxy constructs the logger with no arguments and the
authority_host parameter is reachable only from the SDK.
Resolve the authority from AZURE_SENTINEL_AUTHORITY_HOST before falling back to
AZURE_AUTHORITY_HOST, matching how tenant id, client id and client secret
already resolve in this constructor.
The Azure Sentinel logger hardcoded the commercial Entra authority and the
commercial Azure Monitor audience, so Log Analytics ingestion could not work in
Azure Government even when the ingestion endpoint pointed at a sovereign Data
Collection Endpoint.
Resolve the authority from AZURE_AUTHORITY_HOST and derive the matching Logs
Ingestion audience from it. Moving only the token URL is not enough: sovereign
Entra would then be asked for a token scoped to the commercial audience, which
the sovereign endpoint rejects.
An intercepted web search called litellm.asearch() with only the search tool's litellm_params, so the search request carried no owner. The proxy's spend hook skips any call with no key, user or team attached, so the search's provider cost never reached SpendLogs; it was missing from the Logs page and never counted against the caller's budget. The same path never ran the rate limiter either, so an intercepted search was free of the key's RPM/TPM limits.
The search now carries the originating key's attribution metadata (key hash, alias, user, team, org, plus model_group set to the resolved search tool) and runs the caller's rate limit checks before hitting the provider, matching what a direct /v1/search request gets. SDK calls with no proxy auth context are unchanged.
Resolves LIT-5033
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
A cached HTTPHandler hands its raw httpx.Client out to consumers that keep it
for the process lifetime. When the shared client cache expires the entry on its
TTL or evicts it under the 200-entry cap, nothing references the handler, so it
is collected and its finalizer closed the client those consumers still hold.
Langfuse ingestion then failed silently on the SDK's background flush thread
until the process restarted.
A finalizer running proves only that nothing references the handler; it proves
nothing about the client. Both handlers now close the client during finalization
only when they built it and are still its sole referrer, so an unshared client is
still released promptly and a handed-out one is left alone. That keeps the
pooled-socket reclamation the finalizer was providing, which measures identical
to base over 2000 handler create-and-drop cycles.
Explicit close() stays, now gated on _owns_client so the wrapper never closes a
caller-injected client, and __aexit__ routes through it.
LangFuseLogger also keeps a reference to the handler whose client it hands the
SDK. Previously that handler was a local that went out of scope immediately,
leaving the client reachable only from the SDK. It still shares the cached
client, so no extra clients are created per logger.
Generic SigV4 double-encodes the canonical URI while S3 canonicalizes the wire path with single encoding, so any object key containing a character that percent-encodes (a team alias, key alias or s3_path with a space) was signed over %2520 while the request carried %20; S3 recomputed a different signature and answered 403.
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: yucheng <yucheng@berri.ai>
The azure_storage logging callback and the azure blob files backend built every
storage URL against the hardcoded commercial host, so an Azure Government account
was unreachable with no way to override it.
Read AZURE_STORAGE_ENDPOINT_SUFFIX (default core.windows.net) once in
AzureBlobStorageLogger and derive the Data Lake and Blob hosts from it, so all
seven previously hardcoded sites follow the configured cloud. Parse stored blob
URLs with urlparse instead of matching the commercial host, so URLs persisted
before the suffix was configured still resolve, and pin the resulting
host-validation boundary with tests.
* feat(otel): stamp service tier attributes on inference spans
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): bound requested service tier to known values
The requested tier is caller-controlled and reaches the span verbatim, so an
arbitrary string lands on every litellm_request span on success and on failure.
A 100k character value was stamped uncapped; safe_set_attribute does not
truncate and no span limits are configured.
Apply KNOWN_REQUEST_SERVICE_TIERS in get_requested_service_tier so both the
span attribute and the Prometheus label bound the value the same way. The
served tier stays unrestricted since it comes from the provider, so a tier a
provider adds later is still reported.
Prometheus label behavior is unchanged.
* fix: derive known service tiers from the ServiceTier enum
The allowlist omitted "fast", which litellm models as a real tier and prices
through the priority cost key, so a request naming it resolved to no tier on
the span and no Prometheus label.
Deriving the set from ServiceTier keeps the two in sync, so a tier added there
for cost calculation cannot go missing here.
Behavior change: a request with service_tier "fast" now carries the tier on the
span and on the Prometheus service_tier label, where it previously resolved to
none. Every other value resolves as before.
* refactor: build the known service tiers without a mutable intermediate
The set comprehension and set literal tripped LIT002, which bounds mutable
collections. Concatenating tuples keeps the derivation from ServiceTier while
every intermediate stays immutable; the resulting frozenset is unchanged.
---------
Co-authored-by: milan <milan@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Yucheng Zhu <yucheng@berri.ai>
The block event Rubrik receives sourced caller identity from
model_call_details[metadata], where the enriched litellm metadata never
lives; it sits under litellm_params. Every block therefore reported
user_api_key_hash as an empty string, so a security block could not be
traced to a key, user, or team.
Read identity off the authenticated UserAPIKeyAuth the failure hook is
already handed, via the same mapper the success path and the proxy spend
logger use, so a block log and a success log describe their caller with an
identical key set.
* feat(guardrails/rubrik): prompt moderation, response-text blocking, streaming buffer, failure logging (#34019)
* feat(guardrails/rubrik): add prompt moderation, response-text blocking, streaming buffer, failure logging
- Add `pre_call` prompt moderation via `/v1/before_prompt/openai/v1` webhook:
structured messages are flattened and sent before the LLM is called; blocked
prompts surface a `ModifyResponseException` with the refusal text.
- Extend `post_call` response moderation to cover assistant text in addition to
tool calls; text blocks (wholesale replacement) are distinguished from
tool-block explanations (appended) via `startswith` diffing.
- Add `streaming_end_of_stream_only = True` and `streaming_buffer_until_moderated = True`
so streamed responses are withheld until end-of-stream moderation passes
(requires litellm >= BerriAI/litellm#31389; older versions fall back to
detect-only).
- Add `_MalformedToolBlockingResponseError` for structurally invalid service
responses; `_guarded` logs at CRITICAL so operators notice misconfiguration.
- Add `max_queue_size = 10_000`, `_enforce_max_queue_size`, and drop-oldest
backpressure so a webhook outage cannot grow the retry queue unboundedly.
- Add `flush_queue` override that snapshots once for both send and drain,
preventing duplicate delivery on concurrent flush calls.
- Make `_log_batch_to_rubrik` re-raise on error so `flush_queue` preserves
undelivered events for the next retry.
- Add `async_post_call_failure_hook` to log blocked requests
(`ModifyResponseException`) with a best-effort fallback payload for prompt
blocks (where no `standard_logging_object` exists yet).
- Add `_correlation_id` / `_apply_correlation_id` / `_prepend_system_prompt`
helpers; `_prepare_log_payload` now applies them for all providers (not just
Anthropic) so every log correlates by `litellm_call_id`.
- Add `get_supported_event_hooks` classmethod advertising `[pre_call, post_call]`.
- Use dedicated `httpx.AsyncClient` (`moderation_client`) for webhook calls
with explicit pool limits, separate from the shared logging client.
- Drop module-level `rubrik_handler` singleton (inappropriate for a library).
- Update `initialize_guardrail` docstring to explain `pre_call` vs `post_call` mode.
- Update tests: rename `tool_blocking_client` → `moderation_client`,
`tool_blocking_endpoint` → `response_moderation_endpoint`, `_flush_task` →
`_periodic_flush_task`; migrate `TestExtractBlockedTools` to
`TestExtractResponseBlock` for the new combined text+tool block API; add
tests for prompt moderation, text blocking, streaming flags, and failure
payload construction.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* test(guardrails/rubrik): add tests to reach 100% coverage
50 new tests across 18 classes covering previously-untested paths:
- Prompt moderation: passthrough, block, no-messages skip, message
flattening (content-list → string), payload construction with
tools/user/correlation_key/litellm_call_id fallback, refusal extraction
- async_post_call_failure_hook: non-matching exception no-op, missing
stash warning, valid stash → enqueue, AttributeError in payload build,
flush exception handling
- Block payload building: standard_logging_object present vs fallback
path, missing start_time
- async_log_success_event: _rubrik_blocked=True skip path
- aclose: task cancel + moderation_client.aclose()
- Edge cases: sampling rate clamp warning, unknown input_type passthrough,
empty-inputs early return, model_call_details warning, _stash_block_context,
duck-typed tool-call normalization, request_data["tools"] preference over
optional_params, system-prompt exception handler, flush-at-batch-size,
enqueue exception swallowing, queue empty/lock-None guards, non-dict JSON
response TypeError
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): use get_async_httpx_client, ruff format
- Replace bare httpx.AsyncClient with get_async_httpx_client (required
by ensure_async_clients_test; avoids per-request client creation)
- aclose() calls close() (AsyncHTTPHandler interface, not aclose())
- ruff format on rubrik.py and guardrail_hooks/rubrik/__init__.py
- Update 3 tests for AsyncHTTPHandler type (isinstance check, close())
osv-scan and documentation CI failures are pre-existing on the base
branch and unrelated to this PR.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): fix UP006 strict ruff violation
get_supported_event_hooks return type used List[...] (UP006) instead of
list[...]. Replace with the built-in generic and remove the now-unused
List import from typing.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): fix 3 reportArgumentType basedpyright violations
Use `# pyright: ignore[reportArgumentType]` (not `# type: ignore`) to
suppress the three errors basedpyright reports in --outputjson mode:
- convert_content_list_to_str call (dict vs AllMessageValues)
- _apply_correlation_id call (StandardLoggingPayload vs dict[str, Any])
- _prepend_system_prompt call (same)
Also tighten _apply_correlation_id and _prepend_system_prompt signatures
from bare `dict` to `dict[str, Any]`.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): don't close shared HTTP client in aclose()
moderation_client and async_httpx_client both come from LiteLLM's global
HTTP-client cache (get_async_httpx_client keys on llm_provider + params).
Two RubrikLogger instances with the same parameters share the same
underlying AsyncHTTPHandler object. Calling close() in aclose() closed
the shared connection pool for all instances, breaking any subsequent
moderation request on other loggers.
aclose() now only cancels the periodic flush task and lets LiteLLM
manage the shared client lifecycle. Tests updated to assert close() is
NOT called.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): use Counter for duplicate tool-call ID detection
Set-based comparison lost ID multiplicity: two original tool calls with
the same ID both appeared "allowed" even when the service returned only
one (e.g. one allowed + one prohibited sharing an ID). Replace with
Counter so returned_id_counts[id] >= required_id_counts[id] must hold
for every ID. Matches the approach in the original _extract_blocked_tools.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): respect default_on=true when omitted from config
LitellmParams.__init__ converts an omitted default_on to False before
initialize_guardrail receives it, so litellm_params.default_on is always
bool and never None. The is-None guard in RubrikLogger.__init__ therefore
never fired on the proxy path, leaving prompt/response moderation inactive
for any config that omitted default_on.
Fix: read the raw guardrail dict (before LitellmParams coercion) to
distinguish an explicit `default_on: false` from the absent-means-True
default. When the key is absent from the raw config, default_on=True is
used; when it is explicitly set (either True or False), that value wins.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* style: ruff format rubrik.py after Counter import addition
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): detect ID-less tool call removal; fix UP045
ID-less tool calls (tc.id is falsy) were excluded from required_id_counts,
so the Counter comparison never caught their removal. Add a cardinality
check (len(returned) < len(original)) that fires on any removal regardless
of ID presence, combined with the Counter check for duplicate-ID attacks.
Also fix 5 UP045 violations (Optional[X] → X | None) introduced by our
new code against the daily-branch baseline.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): filter optional_params through ModelParamHelper in fallback payload
_build_fallback_payload forwarded the raw optional_params dict as
model_parameters. optional_params can contain extra_headers, api_key,
and other upstream provider credentials that must not reach the Rubrik
webhook. The normal standard_logging_object path already filters through
ModelParamHelper.get_standard_logging_model_parameters(), which
allowlists only safe LLM API parameters. Apply the same filter here.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): scope failure hook by guardrail_name; moderate text-completions
Guard async_post_call_failure_hook by guardrail_name so multiple Rubrik
instances don't cross-log: the failure hook is called for every registered
callback; without the check the first instance pops the stash and the
originating instance finds None and silently skips logging. Now each
instance only handles blocks raised by itself.
Also moderate /v1/completions prompts: _moderate_prompt returned early
when structured_messages was absent. For text-completion requests litellm
supplies inputs["texts"] with no structured_messages. Added a fallback
that synthesises a user-message from texts so the before_prompt webhook
can evaluate text-completion prompts.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(lint): add reason comments to pyright: ignore suppressions
type-discipline budget requires each # pyright: ignore[...] to carry an
explanatory comment. Add reasons to the three bare suppressions on lines
483, 651, 652.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): include tool-call arguments in prompt moderation
_flatten_messages_for_moderation only sent the content field, silently
dropping tool_calls[].function.arguments and function_call.arguments.
An attacker could embed prohibited text in tool-call arguments inside
assistant history turns and bypass prompt moderation entirely.
Now collects all attacker-controlled text per message: text content via
convert_content_list_to_str, plus all tool_calls[].function.arguments
and the deprecated function_call.arguments, joined with newlines before
being sent to the before_prompt webhook.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): tighten append detection to prevent prefix bypass
startswith(sent_content) allowed any replacement whose text shares the
original as a prefix (e.g. "Hello" → "Hello, blocked.") to be classified
as a tool-block append rather than a text block, bypassing detection.
Use startswith(f"{sent_content}\n\n") to require the exact two-newline
separator the webhook uses between original text and appended tool-block
explanations. Also add `returned_content != sent_content` to text_blocked
so an unchanged passthrough is never classified as a block.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix(guardrails/rubrik): default_on=False when omitted (follow existing pattern)
Remove the custom raw-dict lookup that was defaulting default_on to True
when omitted from the guardrail config. Follow the standard litellm
convention: omitted resolves to False (users must explicitly opt in with
default_on: true).
- initialize_guardrail: pass litellm_params.default_on directly
- RubrikLogger.__init__: is-None guard defaults to False not True
- Test updated to assert the correct False default
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* chore(rubrik): keep the ported guardrail within staging lint budgets
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: credit the original author of the rubrik guardrail work
Co-authored-by: Joseph Barker <156112794+seph-barker@users.noreply.github.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: keep this mirror PR's diff limited to the rubrik files
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Joseph Barker <156112794+seph-barker@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: yucheng <yucheng@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Team-scoped DD credentials (dd_api_key, dd_site) set via POST /team/{id}/callback were silently dropped because _request_blocked_callback_params blocks them from standard_callback_dynamic_params. The security block is correct for request-level injection, but team callback_vars are admin-configured and trusted.
Store the raw init kwargs on the Logging instance and read dd_* params from there in _process_dynamic_callback_list instead of from standard_callback_dynamic_params.
Adds an integration test that exercises the full Logging.__init__ flow with team callback_vars to prevent regression.
Co-authored-by: Aanchal Khandelwal <aan2210khandelwal@gmail.com>
An import probe proves nothing about the real SDK: it may be absent (it
lives in the proxy-runtime extra) and the tests/test_litellm/llms/anthropic
test package can shadow it once collection puts that path on sys.path,
which made the test order-sensitive across collection sets
The bridge gate compared reasoning_effort against the string "none", so
litellm's dict form ({"effort": "none"}) wrongly bridged; the gate now
reads the effort value from either form and treats a summary inside the
dict as Responses-only regardless of effort. Helicone and lunary
previously skipped custom tool calls entirely; both now serialize them
(helicone as a tool_use block from the custom payload, lunary with the
custom name and input in its function fields, keeping type custom), with
new mapped tests for both integrations
* feat(s3): support SSE-KMS encryption params on both S3 logging paths
* fix(s3): ignore non-string SSE config values instead of crashing logger init
* Update litellm/integrations/s3.py
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(s3): invalidate only the mistyped SSE field instead of dropping both
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): label retrieval and agent metrics correctly and emit gen_ai.provider.name
The GenAI metric attribute builder mapped only chat, text completion, embedding,
responses and MCP tool calls to an operation name, so vector-store searches and
A2A agent sends fell through to the "chat" default. Their duration and cost then
landed in the same series a Grafana GenAI dashboard reads chat latency off, with
no way to tell them apart. Both now map to the operation names the convention
defines for them, retrieval and invoke_agent, and an unmapped call type says so
at debug instead of silently becoming chat.
The provider label used gen_ai.system, which the convention deprecated in favor
of gen_ai.provider.name; the dashboards built on that vocabulary find nothing
under the old key. Metrics now carry gen_ai.provider.name with the semconv
provider value (bedrock -> aws.bedrock) via the resolve_provider helper the span
path already uses, and keep dual-emitting gen_ai.system with its raw value so a
dashboard already querying it keeps matching. A request litellm cannot attribute
to a provider gets no provider label at all rather than a placeholder "Unknown"
that minted a permanent series nobody can act on.
Resolves LIT-4954
Resolves LIT-4959
* fix(otel): map the rest of the vector-store call types off the chat default
Mapping only the search left the store lifecycle (create, retrieve, list,
update, delete) and the file operations (create, list, retrieve, content,
update, delete) falling through to chat, so vector-store admin traffic kept
polluting the same series a dashboard reads chat latency off. A live run
confirmed it: all 20 metric datapoints from a create, retrieve, list, file-list
and delete came out labelled chat.
The convention names no operation for vector-store management, so these take
vendor values under the litellm. prefix, litellm.vector_store_management and
litellm.vector_store_file_management, one per REST resource. Its note on
gen_ai.operation.name directs instrumentation to use a system-specific name
when no predefined value applies, which is the same allowance resolve_provider
already relies on for unmapped providers. Excluding them from the GenAI metrics
altogether was the alternative; it deletes series an operator may be watching
today and is far harder to reverse than a rename, so it stays available as a
follow-up rather than being decided here. Mapping them onto the semconv memory
store family was rejected: litellm vector stores hold documents, not agent
memory records, and borrowing those names would put document admin calls into
whatever charts agent-memory operations, which is the bug this fixes.
/rag/query reaches the same recorder and is the same operation as a vector-store
search, so query and aquery map to retrieval too; leaving them would have left
the defect alive on a second retrieval surface. /rag/ingest is a write with no
semconv equivalent and no retrieval or agent confusion, so it is left for the
RAG owners to name.
Resolves LIT-4954
* fix(otel): give the streaming A2A path a call type so it labels as invoke_agent
The streaming logging object is built by hand and never runs through
update_environment_variables, the only place call_type reaches
model_call_details, so every streamed agent turn arrived at the recorder
with no call type and fell back to chat. Stamp it, and map the streaming
spelling alongside the non-streaming ones.
* feat(otel): record the GenAI duration metric on failed requests
`_record_metrics` ran only from `async_log_success_event`, so
`gen_ai.client.operation.duration` counted only the requests that worked.
Latency read off it during an incident was the latency of the surviving
traffic, and with no error dimension anywhere there was no way to build a
failure-rate panel or a success/failure split per model.
A failed call now records the same duration histogram, tagged with the
semconv `error.type` (the mapped provider exception's class name, bounded by
construction; the message stays on the span). Success attributes are
untouched, so an existing query can still isolate the old series with
`error_type=""`. The other five instruments describe a completed generation
and are skipped rather than filled with a fabricated zero: litellm hands the
failure callback no `response_obj`, so there is no usage to split and no
completion-token count, and it zeroes `response_cost` on failure. A
proxy-gate rejection (auth / rate limit) records nothing, for the same
reason it gets no span; no upstream call happened.
`error.type` is stamped after the cardinality filter, like
`gen_ai.token.type`, so an `otel.attributes` include/exclude list cannot
strip the discriminator and silently merge failures into the success series.
Resolves LIT-4955
* fix(otel): bound the failure metric's attribute set
The failure datapoint reused the success path's full attribute set, which
carries client-supplied fields (`metadata.requester_metadata`,
`metadata.spend_logs_metadata`, the end-user id taken from the request's
`user` field) and per-request ones (the `hidden_params` blob holding the
provider's response headers). A failed request needs no provider spend, so
nothing rate-limits a caller who puts a unique value in a field they control
and mints one histogram series per request.
A failure now carries a bounded allowlist: the operation enum, provider,
request model, framework, the key/alias/team/org/user identifiers, and
`error.type`. Every entry is a fixed enum or an operator-provisioned
identifier, so the failure series count is bounded by the deployment's own
key, team and user count while the labels still answer which team on which
model is failing and how. The user email is left out as PII duplicating the
user id already on the series. The operator's `otel.attributes` filter layers
on top, so it narrows the allowlist further and never widens it.
* fix(otel): cap metric attributes so series count does not grow with traffic (#35166)
`GenAIMetricRecorder._common_attributes` dumped the whole `hidden_params` object
onto every metric datapoint as one label value. That object is per-request by
construction: `response_cost`, `litellm_overhead_time_ms`, `cache_key`,
`usage_object` and the provider's `additional_headers` rate-limit counters all
move on every call. A unique label value is a new time series, and all six GenAI
instruments share those attributes, so one request minted up to six series that
would never be written to again
That is the steady-state behavior of the feature rather than an abuse case, and
it is wrong twice over. Hosted backends bill on series count, so recommending
metrics be enabled would have meant a bill proportional to traffic. And a
histogram whose every datapoint sits in its own series cannot be aggregated, so
the dashboards would have looked populated while answering nothing
Both paths now cap their attributes at METRIC_ATTRIBUTE_CEILING, which replaces
the failure-only allowlist so the two paths cannot drift. The cap runs before the
operator's `otel.attributes` filter, so an operator can narrow it and never widen
it back to an unbounded label. Client-supplied and per-request metadata
(`requester_metadata`, `spend_logs_metadata`, `user_api_key_end_user_id`,
`requester_ip_address`) is metric-ineligible and stays on the span, which already
carries it and where cardinality is free. `hidden_params` survives as a label but
carries only `model_id` and `api_base`, which are bounded by the router's own
deployment list and are the part a per-deployment panel reads
Four tests fail against the previous behavior, the load-bearing one being that
two requests differing only in per-request fields must land in one series rather
than two
* fix(otel): cap tool-definition attributes so they cannot evict gen_ai.* from the LLM span
The genai and legacy mappers each spelled out every declared tool as
per-index span attributes. A request declaring hundreds of tools produced
roughly 500 attributes against the OTel SDK's default 128-attribute span
limit, which evicts oldest-first, so the canonical gen_ai.* set written
first was discarded and the span exported with only a tail of tool
schemas. Cap the family at 8 tools, shared by both vocabularies, and
carry the declared total on litellm.request.tools.declared so the
truncation is visible rather than silent.
* fix(otel): apply the tool-definition cap to the OpenInference mapper
The OpenInference vocabulary emits its own unbounded llm.tools.{idx}.*
family, which Arize and Phoenix layer on top of the default two, so those
configurations still overran the span attribute limit and evicted the
core gen_ai.* attributes. Route it through the same shared cap and cover
the layered-mapper path with a test.
* fix(otel): share one span-wide tool-definition budget across vocabularies
Capping the tool-definition family per mapper left each active vocabulary
its own allowance, and several vocabularies write to the same span. With
every vendor vocabulary configured, the three that spell tools out per
index still summed past the SDK's 128-attribute span limit, so the core
gen_ai.* set written first was evicted exactly as before: measured at 128
attributes with 7 dropped and gen_ai.request.model gone.
Reserve a quarter of the span for tool detail and split that ceiling
across the distinct tool-emitting vocabularies at mapper-resolution time,
so the family is bounded span-wide no matter how many are configured. The
same worst case now exports 90 attributes with nothing dropped.
Three defects kept LiteLLM's OTel metrics from reaching an OTLP backend.
OTEL_EXPORTER_OTLP_HEADERS is W3C Baggage encoded per the OTLP spec, so its
values are percent-encoded. litellm split the string on "," and "=" and passed
the raw value straight to the exporter, so a vendor that documents
"Authorization=Basic%20<token>" got a literal "%20" on the wire and the backend
rejected the credential. Grafana Cloud documents exactly that shape, which made
its OTLP gateway unreachable. Header parsing now delegates to the OTel SDK's own
W3C Baggage parser in liberal mode, so percent-encoded values decode and values
that were never encoded keep working. It moves from model/utils.py to
plumbing/providers.py because model/ is deliberately free of opentelemetry
imports; providers.parse_headers was already the entry point every caller used.
The OTLP metric exporters then overrode histogram temporality to delta.
Prometheus and Mimir, which back Grafana Cloud's OTLP gateway, reject delta
histograms outright: the gateway answers 400 "invalid temporality and type
combination" and drops the entire batch, so every GenAI metric was silently lost
while traces kept flowing. Backends that prefer delta still accept cumulative, so
the SDK default is the compatible choice in both directions, and the enterprise
billing exporter already relies on it.
Three GenAI instruments also carried names no convention or backend defines, so
nothing downstream could chart them. Time to first token and time per output
token take their semconv names, gen_ai.server.time_to_first_token and
gen_ai.server.time_per_output_token; the gen_ai.client.response.* spellings
litellm used are not conventions at all. Cost has no semconv instrument, so it
takes gen_ai.usage.cost, the name backends already query for spend. All three are
listed verbatim in Grafana Cloud's AI Observability integration reference, so its
prebuilt panels find them. Both engines now read the names from the shared Metric
constants rather than repeating string literals, so v1 and v2 cannot drift.
The renames are breaking for anyone charting the former names; the docs and the
release changelog carry the migration note.
litellm_provider_cache_creation_input_tokens_metric only read the
Anthropic-style top-level usage.cache_creation_input_tokens and had no
prompt_tokens_details fallback, unlike its cache-read twin. OpenAI models
that bill prompt cache writes report them only in
prompt_tokens_details.cache_write_tokens, so the counter never fired for
them. Resolve provider cache read/write tokens through a shared helper
that falls back to prompt_tokens_details.cache_write_tokens (canonical)
then cache_creation_tokens when the explicit top-level field is absent,
and give litellm_input_cache_creation_tokens_metric the same fallback for
raw usage dicts that only carry cache_write_tokens
Both failures are from this branch, not pre-existing
The component allowlist test asserts the gateway and backend route sets union to
the whole app, so any route on neither is a 404 on both pods. Allowlist the
`/management/v1/` prefix on the backend, next to the other control plane
entries, so every resource that moves under it later is covered without a
per-resource edit
The otel handler test builds its request as a SimpleNamespace carrying only
`state`. The validation handler now reads `request.url.path` to decide whether
the caller is on a surface with its own error contract, so the fake needs a url;
a real Request always has one, which is why the handler does not guard for it
The control plane branch returns early, and nothing covered that it still closes
the dangling SERVER span first, so those requests would have leaked a span
apiece. Added a case that pins it; removing the close call fails it
A second mutation batch scored the previously unmapped mirror files on
current staging. These four generate mutants for the module they are
named after, yet no test in the file executes any of them; their
test-context coverage lands on generic shared machinery or, for the
guardrail translation handler remainder, on no litellm line at all.
Eight sibling findings that do exercise a different real module are
kept for retargeting instead of removal.
A failed MCP tool call aimed its error.* attributes at request_root_span(),
a ContextVar written on the ASGI request task. A stateful streamable-HTTP
session runs every message on the single task the session's initialize POST
spawned, so inside the message handler that ContextVar still holds the
initialize request's SERVER span. That span ended long ago, so the SDK
dropped every write (five 'Setting attribute on ended span' warnings plus
set_status and _add_event per failed call) and the POST that actually
failed carried no error at all. The identity attributes seeded onto the
server span went the same way.
Publish the live transport span on the ASGI scope of the request being
handled and read it back in the message handler through req_ctx.request,
the Request the streamable-HTTP transport attaches to each message. That
replaces the session-scoped field with a per-message one: a JSON-RPC
response POST deliberately skips the per-session lock, since it can arrive
while the tool call awaiting it is still in flight, so a field on the
shared auth object could be overwritten mid-call and send the tool call's
telemetry to the response's request. A scope also dies with its request
rather than holding a finished span on idle session state.
Publishing re-anchors the request root for the message so guardrail spans
and identity seeding follow, and only a transport still open for writes is
anchored or stamped: a notification POST can answer before the session task
is done, and moving dropped writes from one finished span to another is no
fix. Live capture goes from seven ended-span warnings and an unmarked
transaction to zero warnings and ERROR on the POST that carried the call.
