When the client disconnects mid-stream, the native adapter now logs success for the chunks it delivered before teardown, so spend, SpendLogs and the key's budget and tpm reservations settle the same way they do on the Python path
The proxy records a client disconnect, with its 499 error information, in the stream generator's cleanup. The native teardown billed the stream before that cleanup, so the row had empty error information. A proxy stream torn down by cancellation now bills from the task's done callback, after the disconnect is recorded
Python logs the requested optional params, taken before the provider transform, as model_parameters. The native handler logged the transformed body, so a reasoning_effort request was logged as thinking and output_config. The request context now carries the requested params
Python updates model_call_details with the transformed request body before pre_call, so the logged messages are what was sent. The native adapter kept the caller's messages and compared params as JSON values, so an int 0 logged as 0.0
Python only records custom_llm_provider in model_call_details. The native adapter also wrote it into litellm_params, and the proxy reuses one logger across router hops, so a fallback hop's pre_call log showed the provider where Python shows null
Python only stamps cache_hit when a result came from the cache. The native adapter wrote False on every provider result
Python calls pre_call with the request body as a json user message, and a stream's spend-log cache_key is computed over that input. The native adapter logged the string Messages, so a streamed call's cache_key differed
* fix(messages): log native messages success once, after the proxy releases it
The proxy defers non-stream success logging past post-call guardrails, but the native host parked its log in its own slot and the release only ran for OCR, so a unary /v1/messages call served by Rust logged no success event, no SpendLogs row and no key, team, user or end-user spend. A deferred native success now parks in enqueue_deferred_logging with deferred_success_result, the same slots Python uses, so the proxy releases it like any other call and its guardrail step pruning and cost preparation see it too
Python runs sync success callbacks inside the deferred logging closure, so a post-call hook that blocks the response drops them. A parked native success now carries its sync callbacks and runs them on release
A refused first attempt and its fallback share one logger. Python logs the async success once, for the first attempt, so the native adapter now claims the async success log once across fallback attempts. Like Python, an attempt that loses the claim runs its sync callbacks only when logging is not deferred, and an internal call logs nothing
* test(messages): cover the deferred native success park and release
* fix(lens): price agent traces by joining gen_ai.response.id to spend logs
Trace spend now joins each model call to spend_logs on one key: the
span's response id (gen_ai.response.id or the id the normalizers read
from OpenInference/LangChain output) against spend_logs.response_id or
the upstream id embedded in a managed resp_ id. The litellm.call_id and
traceparent transport join paths and the per-row ownership gate are
removed; the spend SQL still restricts rows to what the reader can see.
A run with some unpriced calls now reports the sum of its priced calls
plus priced_calls, instead of an unknown total.
* test(lens): cover response id spend join and partial trace totals
* chore(lens): regenerate trace types for priced_calls
* feat(lens): show partial run cost as a lower bound with priced call count
* fix(lens): treat litellm.call_id as the same assigned call id for spend joins
The id LiteLLM assigned to a call is either the response id it returned
(gen_ai.response.id -> spend_logs.response_id) or its gateway call id
(litellm.call_id -> spend_logs.litellm_call_id). Both are exact ids the
gateway mints and logs, so the join stays one rule. Transport span
matching and the ownership gate stay removed.
* test(lens): cover litellm.call_id spend joins and restore captured totals
* feat(lens): link each priced model call to its spend log
Spans gain spend_log_request_id, the spend_logs.request_id the call was
priced from, and spend_match, which says whether a model call matched or
why not (no assigned id on the span, no spend log with that id, or an
ambiguous match). A model call span is priced from the same ids as the
run total, so its cost and the total agree.
* test(lens): cover spend log links on model call spans
* chore(lens): regenerate trace types for spend log links
* feat(lens): open the matched spend log from an LLM step
An LLM step's header now shows a Spend log chip with the matched
request id and cost; clicking it opens the request log drawer over the
run, fetched by the exact spend_logs.request_id instead of the span's
own response id. Unpriced steps say why (no assigned id on the span, or
no spend log with it). Tree rows show each model call's cost, and a
partial run cost shows its priced call count inline.
* test(lens): cover the spend log link and unmatched cost reasons
* feat(lens): show the spend log link as a bordered LiteLLM Spend Log button
* feat(lens): add a back link from the spend log drawer to the agent trace
* feat(lens): label the spend log back link Back to Lens trace with the Lens icon
* fix(lens): ignore assigned ids that name no spend log when pricing a call
An id that names no row no longer vetoes the call, so a span carrying
both a response id and a call id still prices from a spend row logged
before litellm_call_id existed. An id naming two or more rows makes the
call ambiguous, and the match reason comes from the same per-id result,
so a single matched row with no cost is reported as matched.
* fix(lens): price a trace only from spend logs in its own team
A reader with several teams could see the same assigned id in another
team's spend log; only rows from the trace's team now price it. The
user and key ownership gate stays removed.
* perf(lens): resolve each model call's spend once per trace
Model call matches are computed once when the trace is resolved and
looked up by span index, instead of scanning the model call list for
every span and walking the graph again for spans, agents and the run
total.
* fix(lens): hide a step's Cost fact only when its spend log link shows the cost
* chore(lens): drop narrative doc comments from the spend join
* fix(lens): price a model call only when its ids agree on one spend log per span
* fix(lens): keep pricing spend logs written before litellm_call_id by their request id
* fix(lens): price every attempt a model call's ids name when they agree
The legacy callback crate carried two rewrites that have nothing to do with the
Logging contract: litellm_credential_name inheritance and the max_budget and
num_retries_per_request checks. Any later callback host would need them
unchanged, which is the smell the crate's AGENTS.md now names. They are now a
Preflight the driver in litellm-host-python runs on the keyword view begin
returned, before the host projects from it, supplied by python-bridge and passed
through run_legacy_call. The call order is unchanged (setup, deployment hook,
credentials, limits) and a rejection still fails the call as a host failure, so
the failure callbacks run as before. The preflight rewrites the adapter's own
copy in place, so no extra dict copy and no new lifecycle method
Co-authored-by: Yujong Lee <yujong@berri.ai>
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
