187 commits

Author	SHA1	Message	Date
Mateo Wang	0e24bbb8a2	fix(responses): bill every round of a streamed MCP auto-execute on one spend row (#47445) ... * test(responses): cover billing every round of a streamed MCP auto-execute * fix(responses): bill every round of a streamed MCP auto-execute on one spend row * fix(responses): bill every round of a streamed MCP auto-execute on bridged providers A streamed /v1/responses MCP auto-execute on a provider bridged through chat completions (for example Anthropic) billed only round 1, because each round's chat stream dispatched on the shared logging object and the first dispatch won. Bridged rounds now go through the same one-row billing as native rounds. A round is billed as soon as its chat stream ends, before its closing events reach the client. The row carries the final response, usage and cost summed over every round, and the fixed margin once. A round served from the response cache is billed at zero. A follow-up chat stream that breaks bills the paid rounds on its failure row. A single-round stream logs exactly as before. * fix(responses): charge one fixed margin and keep bridged usage fields on streamed MCP rounds A follow-up round that fails after earlier rounds were billed now charges the per-request fixed margin once, and its failure row carries no cost breakdown that would disagree with the summed cost. A bridged multi-round stream logs a plain cache_hit flag like a single-round stream does, and its usage keeps the summed provider usage fields of every round. A new test covers a stream dropped after its event loop closed, which must release its parked log without an unawaited coroutine warning. * fix(responses): price each streamed MCP round on its own and bill every round when a guardrail blocks Each round of a streamed MCP auto-execute is now priced from its own uncached cost, so a provider that states its cost (xAI) charges the stated cost of every round plus the fixed margin once, and the cost breakdown always agrees with the billed cost. Summed usage goes through a JSON-safe dump, so a nested provider field such as xAI's context_details no longer breaks a failed stream's response.failed event. A post-call guardrail that blocks a multi-round bridged stream now drops the parked success log and bills every round on the failure row, and a failed follow-up round's failure row carries the summed breakdown of both rounds. * fix(responses): keep earlier MCP rounds on their success row when a later round fails When a later round of a streamed MCP auto-execute fails, the rounds before it are now logged on their success row, and the failure row bills only the failed round with no second fixed margin. That failure log runs on its own copy of the request's logging state, so its usage and cost never leak into the earlier rounds' row. A post-call guardrail that blocks a native multi-round stream keeps the summed success row beside the $0 failure row, as at the merge base, while a bridged stream still bills every round on its failure row. * fix(responses): keep a failed later MCP round on its own failure row A streamed MCP auto-execute whose later round failed wrote only the earlier rounds' success row. The failure was logged on a copy of the logging state, while the proxy builds its failure row from the request's own state, which by then held the success payload, so the failure row took the success row's id and was dropped. Now the failure is logged on the request's own state as at the merge base, and once a later round starts, the success row for the rounds before it is logged from a copy of the state taken at that moment, so the two rows never mix. * fix(proxy): let an MCP tool call reuse its request's max_parallel_requests slot * test(proxy): create the other-request task in a way Python 3.10 supports and mark its bindings Final * fix(proxy): keep a reused max_parallel slot until the request's last round An MCP tool call that reuses its request's max_parallel_requests slot no longer loses it to the first round's late success callback, so the key stays counted for the rounds still to run. The reused call also stops replacing the request's rate limit headers. * fix(responses): keep an unpriced streamed MCP round unpriced instead of billing it as free * fix(responses): log a bridged MCP stream as a chat completion with every round's usage	2026-10-21 02:56:38 +00:00
Kazuki Hashimoto	c8ed5ccca8	fix(router): unregister strategy selectors from global callbacks on discard (#45795) ... * fix(router): unregister strategy selectors from global callbacks on discard Router.discard only removed its own bound methods from litellm's callback lists, so the strategy selectors it registered (least-busy, usage-based, latency-based, cost-based and routing group selectors) stayed behind and kept receiving events after the router was gone. Reuse the identity based unregister that update_settings already uses so a discarded router takes only its own selectors with it * fix(router): purge discarded selectors from every event callback list function_setup copies litellm.callbacks into the success and failure lists on every request, so a router that served traffic still leaked its selectors there after discard. Route the cleanup through remove_callback_from_all_lists, which now also covers input_callback, and fold the selector gathering into discard so the router coverage check sees no untested helper * fix(router): keep live routers, in-flight hooks and user_config limits intact on discard discard() now rebuilds every global callback list without the router's selectors, optional pre-call checks and own usage callbacks instead of removing them in place, so a callback loop already running never skips a hook. It then re-registers what the remaining live routers need, so a same-strategy survivor keeps its deduped handler. The proxy's per-request user_config router is discarded only after its call returns. * fix(router): bind user_config handlers to the request and tighten discard When a user_config request carries a logging object, its router is discarded before the request runs and its handlers ride on that logging object, so v1 rpm and v2 tpm limits count every request and concurrent requests count once. Without one, the router is discarded after the request as before. The router's pre-call loops also read the request-scoped handlers. discard() now refills only the handler keys it vacated, guards the callback lists and the live-router set with a lock, covers routers built without a model_list, and drops its Slack alerting, adaptive router hook and budget limiter sync task * fix(proxy): reuse one user_config router per config and bind its handlers to each request Every user_config request now goes through a cached router built once per config. Its strategy handlers leave the global callback lists and are bound to the request's logging object instead, so limits count each request once and nothing is left behind after the request. * fix(router): keep the proxy budget limiter on user_config requests A user_config router now swaps in only its strategy selectors, so the proxy's RouterBudgetLimiting stays on the request and keeps counting its spend. Usage logged after a strategy is retired, such as a request still in flight when its user_config router is evicted, now schedules one more push to Redis. * fix(proxy): init the retire fields on the key model budget limiter The key model budget limiter builds its own state instead of calling the base init, so with the proxy's Redis attached every spend increment raised on the missing retire flag and the key's model budget never counted spend. * fix(router): bind the deployment callbacks to user_config requests A cached user_config router serves requests through each request's logging object but bound only its selectors and policies there, so a failing deployment was never cooled down and its usage counters missed requests. * fix(router): retry an evicted router's budget writes and keep the adaptive header on user_config requests A retired budget limiter now keeps retrying its queued Redis increments every sync interval until Redis accepts them, instead of giving up after one failed write. The x-litellm-adaptive-router-model header now comes from one stateless hook in litellm.callbacks that holds no router, so user_config adaptive routers, whose per-router hooks are request-scoped, still answer with the header. * fix(router): lock request callback setup against router cleanup and drain in-flight budget writes on retire function_setup now edits the global callback lists under the same lock that router cleanup uses, so a router dropping its callbacks on another thread can no longer shift the indexes function_setup pops or put a dropped handler back. A budget limiter retired while a Redis write is still in flight now keeps retrying that batch if the write fails, instead of leaving the spend queued with no task left to send it. * fix(utils): set up loggers after releasing the callback lists lock function_setup held the callback lists lock while set_callbacks ran its one-time logger setup, which can block on a Slack package install, so other threads and Router.discard waited on it. The lock now covers only the list reads and writes. * test(router): annotate the retire test's locals as Final * fix(logging): skip replaced global callbacks on the input path too replace_global_callback already kept a same-key global logger out of success and failure dispatch. pre_call and post_call still sent it the input events, so a logger with an input hook could count a request start it never saw finish. Both now share one filter with the success path * test(logging): type the input-path regression test --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-21 02:39:36 +00:00
alberto	f768fb32ef	fix(streaming)!: send the include_usage chunk with an empty choices array (#47109) ... * fix: Send the include_usage chunk with an empty choices array Signed-off-by: Alberto Perdomo <aperdomo@redhat.com> * test: Skip chunks with no choices when reading streams Signed-off-by: Alberto Perdomo <aperdomo@redhat.com> * fix: Strip usage from plain-iterator async stream chunks Signed-off-by: Alberto Perdomo <aperdomo@redhat.com> * test: Expect empty choices on the usage chunk in the gemma tracing test Signed-off-by: Alberto Perdomo <aperdomo@redhat.com> * fix(streaming): send the empty-choices usage chunk only to callers that asked for include_usage The usage chunk now has choices=[] only when the caller set stream_options.include_usage itself. When the OpenAI handler, the proxy's always_include_stream_usage setting, or the harness added include_usage on the caller's behalf, the chunk keeps its legacy single empty-delta choice, so clients that read choices[0] on every chunk keep working. The proxy and harness mark their injection with the private _litellm_stream_usage_injected flag, and the proxy scrubs a client-sent copy. Plain-iterator streams keep usage on their chunk when usage was not requested, and the LLM Shield trailing flush ignores chunks with no choices. * fix(proxy): mark the default stream usage injection so hooks keep the legacy usage chunk shape The proxy's default strip-mode injection adds include_usage for clients that did not ask and drops the usage chunk before it reaches them, but streaming iterator hooks still saw it with choices=[]. Marking that injection with _litellm_stream_usage_injected keeps the old single empty choice for them. * fix(router): treat deployment and router-default stream_options as injected, and drop the client flag on the queue route * refactor(router): move the stream usage injection check into router_utils * fix(router): read stream_options from pydantic deployment params when marking injected usage Update the mantle, openinference, and text-completion integration tests to expect the include_usage chunk with empty choices. * fix(proxy): keep the stream usage injection marker out of stored request bodies * test(streaming): cover who asked for stream usage on chat, queue, deployment and spend log paths * test: type the queue flag test, pin the logging start time, and build the deployment usage config without mutation --------- Signed-off-by: Alberto Perdomo <aperdomo@redhat.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-21 02:26:05 +00:00
devin-ai-integration[bot]	41890bdf64	fix(token_counter): stop re-downloading a HuggingFace tokenizer after a failed download (#47586) ... * fix(token_counter): stop re-downloading a HuggingFace tokenizer after a failed download Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(tokenizer): isolate HuggingFace tokenizer caches Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(token_counter): clear the traceback before re-raising a cached tokenizer load error Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(token_counter): retry failed HuggingFace tokenizer loads after the cache window Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(token_counter): start tokenizer retry TTL after a failure Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(utils): lock every HuggingFace tokenizer load and keep load failures as values Concurrent llama-2, llama-3 and cohere counts each started their own failed download because only the bundled tokenizers took a load lock. Every tokenizer kind now has one, so a burst during an outage makes a single attempt and two counts can no longer read the same expiring entry at once. A failed load is now remembered as a small value with the error message instead of the error object, so re-raising it no longer keeps the first failing request's frames alive. Adds tests for the concurrent outage and for fork-guard errors staying raised and unremembered. * fix(utils): keep Hugging Face tokenizer downloads unlocked and warn once per failed download Reverts the per-kind load lock so concurrent first downloads still run in parallel, as #47353 intends. A short lock around the failure cache read and write stops two counts racing on an expiring entry, and the tiktoken fallback warning now fires only when a download fails, not on every count that reuses the remembered failure. * fix(caching): read an entry another reader just expired as a cache miss Two threads reading the same expiring key in InMemoryCache could both pass the membership check, and the second then raised KeyError after the first removed it. get_cache now treats that key as a miss. This replaces the extra lock the tokenizer failure cache took, and the regression test forces the interleaving without timing. * fix(caching): treat a TTL another reader just removed as not expired InMemoryCache's expiry check read the TTL after a separate membership check, so a reader racing another reader's eviction raised KeyError. It now reads the TTL once and treats a missing one as not expired, and get_cache already reads the vanished entry as a miss. --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-20 18:24:22 -07:00
Mateo Wang	9fbeebc988	feat(extraction): add /v1/extraction with Cloudflare Clairic support (#47473) ... * feat(extraction): add Clairic extraction types and Cloudflare provider config * feat(extraction): add the /v1/extraction route, router wiring, and Clairic billing * fix(extraction): refuse or drop stream, pass unknown keys, run guardrails, keep the requested model name Clairic does not stream, so stream=true answers 400 and is dropped and billed under drop_params. Keys LiteLLM does not know pass through to Cloudflare. Guardrails scan state, field instructions and text answers. Frozen decision and extraction responses now carry the requested model name. List fields must name their item type. /health/test_connection and the Add Model page accept the extraction mode. * fix(extraction): keep upstream model names on decisions, scan images, keep typed values, refuse OpenAI params Scope the frozen-response model stamp to extraction so /v1/decisions and /v1/systemone return the upstream name as on main. Pass request images to guardrails as data URLs and drop answer spans when a response guardrail rewrites state_text. Field spec values keep their JSON type, so a wrong type answers 400 instead of being coerced. OpenAI generation params answer 400 unless drop_params. The Model Hub shows a /v1/extraction snippet for extraction models. * fix(extraction): send only Clairic's request fields, count extraction tokens, keep typed answers typed, drop spans a request guardrail made stale, and honor --max_tokens * fix(extraction): scan number answers in response guardrails, rewrite guardrail fields in linear time, and leave --max_tokens as on main * fix(extraction): scan float answers as whole numbers so fraction digits never trip a response guardrail * fix(extraction): round only mean and median for response guardrails so fractional values keep their decimal text * fix(extraction): count state and fields for budget reservations and scan estimate quantiles in response guardrails * fix(extraction): send each repeated text to guardrails once and keep the context-window budget reservation * test(extraction): type request_data in the guardrail test helpers	2026-10-20 15:51:45 -07:00
Kerry Lu	6b1f4ed46f	fix(logging): spilled over PTU requests without base_model log the served model's rates (#47655) ... * fix(logging): report pay-as-you-go rates for spilled over PTU requests without base_model * fix(logging): keep the provider response model so spilled over PTU payloads price the served model * fix(logging): keep a provider_response_model the response already carries * fix(logging): read the carried provider_response_model through a typed adapter --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-20 22:28:19 +00:00
yucheng-berri	dd511a2b22	fix(logging)!: fire one CustomLogger failure hook per async call outside the async flag list (#47124) ... * fix(logging): fire one CustomLogger hook per async call outside the async flag list aspeech, atranscription, aimage_generation, aimage_edit, aocr and asearch are missing from is_sync_litellm_request's flag list, so the sync success and failure handlers called a CustomLogger's sync hook on top of the async hook the async handler had already called for the same request. The sync handlers now skip a CustomLogger's log_success_event and log_failure_event when that run is paired with an async handler run (for_async_request) and the async handler gives the logger its own async hook. The async client wrapper, dispatch_failure_handlers, the proxy-only failure dispatch and the native bridge's sync failure step for an async call mark their sync failure run as paired. Resolves LIT-9486 * fix(logging): keep the sync CustomLogger hook when no async success runs The async client wrapper skips async success logging for calls carrying a fallbacks kwarg, and the native bridge skips it for internal and fallbacks calls, yet the paired sync success run still dropped a both-hooks logger's sync hook, so that logger got no success event at all. The sync success run now suppresses the sync hook only when the async success handler was actually scheduled for the call: the client wrapper passes async_handler_runs=not is_completion_with_fallbacks, and the native host records per call whether it enqueued or deferred the async success. Tests that pinned the doubled failure hook on native aocr, messages and responses calls and on proxy-rejected requests now expect the async hook alone. The integration test adds /v1/messages and /v1/responses cells and runs the key-auth rejection on every route. * fix(logging): type dispatch_success_handlers kwargs The new async_handler_runs keyword on success_handler made the untyped **kwargs that dispatch_success_handlers forwards an unknown argument for it, which grew the reportUnknownArgumentType count past its merge-base ceiling. Typing the forwarded kwargs as Any, as _success_handler_body already does, removes those diagnostics without changing what is forwarded. * test(integration): cover CustomLogger hook counts across modes, chaos and router strategies Moves the hook count rig into tests/integration/_support/hook_counts.py and extends the cells it drives: - streamed chat, Messages and Responses requests, success and failure - loggers the async handler never reaches (sync-only overrides, sync event lists only) keep one sync hook per request on every surface outside the async flag list, key-auth rejections included - a concurrent burst while the logger's destination stalls and then fails, and a burst while a worker is killed, never give a request two hooks - least-busy keeps counting a request in flight while async speech requests finish around it, and usage-based routing v2 counts an async image request's tokens once * test(integration): Datadog and LangSmith deliver one record per async request Points the built-in Datadog, LangSmith and OpenTelemetry loggers at a local sink and checks every async surface outside the flag list: one Datadog log entry and one LangSmith run per request (two on the merge base), and never two OpenTelemetry spans, which its own emit-once guard already ensured. * fix(logging): give a both-hooks logger its sync hook when the async run never reaches it The sync hook was skipped whenever the logger sat in the async callback list, so a logger the async run never reached got no hook at all: a sibling stalled past the logging worker timeout, a batch poll that skips default logging, or an async failure run cut off. The sync run now holds the hook and the async run hands it back unless it reached the logger * fix(logging): run the held sync success hooks when the proxy drops a blocked response's success A post-call guardrail block drops the parked async success, which left the sync success hook held for it unrun. Base gave a both-hooks logger that hook on these call types, so the drop now ends the pairing and the held hook runs as before * fix(logging): run held sync hooks only after every sync run of the request has closed A held hook released by the async run could run on another thread while the sync run was still walking its other callbacks. The pairing now waits until the async run has ended and every sync run has closed, and the last sync run to close runs the held hooks itself * fix(logging): end the async run when its coroutine is dropped before it starts A logging queue that drops the async success coroutine, or a deferred success that fails to schedule, left the sync hooks held for it unrun. The enqueued async run now ends when its coroutine is discarded, and the proxy ends it when firing the deferred success raises * fix(logging): leave a still-queued async run to the exit flush The discard finalizer ran at interpreter exit before the logging worker's exit flush, so a queued request could get its held sync hook and then its async hook * test: keep the router and file-stream tests in step with main Main gives each owned proxy a private Redis by default, so the router cells share the worker's Redis to read its counters, and the file-stream stub takes the hook pairing the stream now passes * fix(logging): run held sync hooks when a during_call guardrail raises or the exit flush gives up A during_call guardrail that raised after the LLM call parked its deferred success skipped the proxy's flush, and async runs the exit flush never started were never ended, so a both-hooks logger lost its sync hook in both cases * fix(logging): skip the sync failure hook when the async failure run logs to the logger An async call outside is_sync_litellm_request's flag list ran both failure handlers, so a CustomLogger with both failure hooks got both. The sync run of an async request now skips log_failure_event for a logger that overrides async_log_failure_event and is registered for async failures. The four sync runs of async failures (dispatch_failure_handlers, the @client async wrapper, the proxy-only failure thread and the Rust host) pass for_async_request=True. Drops the HookPairing fallback. Successes are left to #47192, which already gives such a logger only async_log_success_event. --------- Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>	2026-10-20 15:19:14 -07:00
Yassin Kortam	db2039b11b	feat(github_copilot): support a GHE.com host on per-user Copilot credentials (#47610) ... Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-20 14:16:35 -07:00
Emerson Gomes	74230b4d50	fix(logging)!: redact Responses instructions and callback output (#43315) ... * fix(logging): redact Responses instructions and callback output * fix(logging): avoid copying Responses output twice * fix(logging): return redacted Responses output without mutation * fix(logging): type Responses redaction payloads * fix(logging): redact streamed Responses instructions * fix(logging): redact request-side Responses instructions in logged params and spend log bodies * fix(redaction): keep per-callback opt-out off shared instructions and skip redacted replays A callback that sets message_logging=False no longer strips instructions from sibling callbacks, the spend log, or the client's response. Dict logging surfaces keep the reasoning config, and previous_response_id no longer sends the redacted placeholder upstream as the system prompt. * fix(redaction): redact instructions in an opted-out callback's own copy A callback with message_logging=False now gets instructions redacted in its kwargs copy and response object, while sibling callbacks and the spend log keep them * fix(redaction): give a message_logging false callback its redacted copy on sync calls The sync log_success_event and log_stream_event branch now hands an opted-out callback the same copy as the async path. * fix(redaction): redact a message_logging false callback's sync copy and keep failure estimates whole Give an opted-out callback a copy with messages, input, prompt, the sync stream's complete_response and its response object redacted, and stop the proxy's failed request estimate from counting the redaction marker in place of real instructions * test(redaction): wait on callback events instead of sleep polls The new redaction tests now wait for each callback to log through an event it sets, so they no longer poll on a timer * test(redaction): expect redacted follow-ups to replay no instructions This PR stops bridged previous_response_id follow-ups from reusing instructions the spend log stored redacted, so the integration test from #45923 that asserted the replay now asserts that neither the original instructions nor the redaction sentinel reach the provider * test(proxy): type the redacted-instructions failure estimate test --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-20 20:38:17 +00:00
joshua-berri	02199b670b	fix(proxy): share the billing logger across callback registries (#47510) ... * fix(logging): deduplicate equivalent completed success callbacks * fix(proxy): share the billing logger across callback registries * test(proxy): use fixed timestamps for billing regressions --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>	2026-10-20 08:21:49 -07:00
Mateo Wang	91724bb0a7	fix(responses)!: count input tokens the way inference sends the request (#47363) ... * fix(count-tokens): translate chat tool use before Claude token counts Responses and chat tool use (function tools, function_call items, tool messages) is now converted the way Claude chat inference converts it before the Anthropic, Azure AI and Vertex partner counters call count_tokens. Translation errors answer 400 before any provider call. Anthropic-shaped requests and /v1/messages/count_tokens keep their body as sent. * test(count-tokens): compare Claude count bodies with inference for Responses tool use * fix(responses): forward the caller's Responses body to OpenAI token counts OpenAI deployments now get the caller's /v1/responses/input_tokens body as sent, minus LiteLLM-only fields, so OpenAI's own count and errors come back. previous_response_id is checked for ownership like inference and routes to the deployment that served it * fix(responses)!: count Claude Responses bodies the way inference sends them Non-native Responses counts now run the body through the inference bridge, so text.format, tool_choice, reasoning, built-in tools, and file_search count the way inference sends them on Anthropic, Azure AI, Vertex, and Bedrock. The OpenAI native count body uses the drop_params-resolved tool fields. * fix(responses): honor drop_params and replay previous turns in Claude counts Claude input_tokens counts now read the same drop_params setting inference merges from the deployment, router defaults, and request, so a forced tool_choice downgrades to auto under drop_params. previous_response_id replays the stored turns through inference's session loader, and chat messages carrying fields beyond role and content go through the provider's chat translation * fix(responses): keep proxy-only request keys out of OpenAI counts and map chat tools in Bedrock counts * fix(count-tokens): import on Python 3.11 and keep stored prompts in OpenAI counts under drop_params * fix(responses): leave tool_choice out of counts when drop_params drops every tool * fix(count-tokens): count Mantle options, drop cache marks, and reject input inference cannot send The Bedrock Mantle fallback now counts thinking, tool_choice and output_config like the runtime count. Claude Responses counts leave out cache_control marks again, so more than four marks count instead of failing. Counts answer 400 before any provider call for user blocks chat inference refuses and for Responses tools with no Chat Completions equivalent, instead of dropping the block or counting a placeholder tool. Adds the wire tests for these paths * fix(count-tokens): count Responses tools the way the inference bridge sends them A Claude count now hoists additional_tools input items into tools, strips a malformed tool flag under drop_params and rejects it without, and leaves tools out when the deployment lists tools in additional_drop_params, so the count matches the body Claude inference sends for the same request * fix(count-tokens): keep Bedrock runtime counts option-free and send OpenAI the provider file id * test(count-tokens): capture the Anthropic count request at the HTTP layer instead of patching the handler * fix(count-tokens): ignore a caller-sent file id mapping and keep non-string file ids as sent	2026-10-20 15:13:59 +00:00
Kerry Lu	4222523261	fix(logging): report the pay-as-you-go entry billing used on Azure PTU spillover (#47567) ... get_standard_logging_object_payload decided custom_pricing from litellm_params alone, so on an Azure PTU spillover response model_map_information kept the deployment's zeroed PTU entry while response_cost already used the standard model rate. Reuse the billing side LitellmLogging._custom_pricing_for so both read the same decision Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-20 08:02:23 -07:00
Mateo Wang	9e3d3a87f4	fix(anthropic, bedrock)!: keep a redacted_thinking content item on every Claude route (#47489) ... * test(anthropic, bedrock): cover a redacted_thinking content item on every Claude route * fix(anthropic, bedrock): keep a redacted_thinking content item on every Claude route * fix(anthropic, bedrock): send each replayed thinking block once, without cache_control or blank data * fix(anthropic, bedrock): keep thinking order and gate replay key drops on drop_params A thinking block that only one of content and thinking_blocks carries now goes back in its original place instead of being prepended. cache_control on a thinking block and blank redacted data are dropped only under drop_params and otherwise reach Claude as sent. Converse drops a cachePoint after reasoning under drop_params, skips a thinking_blocks entry that is not a block, and the cache control hook no longer marks a thinking part. * fix(anthropic, snowflake): match a signed thinking block on its signature and send each block once on Snowflake Cortex A signed thinking block in both content and thinking_blocks is the same block when the signatures match, even if the thinking text differs, so it is sent once from content instead of twice. Snowflake Cortex now merges thinking_blocks into content the same way the Anthropic routes do. A redacted_thinking item with blank data no longer counts as sent for system message placement. * fix(anthropic, bedrock): send a thinking block once when consecutive assistant messages both carry it Consecutive assistant messages merge into one Claude turn, so a block one message holds in content and the next holds in thinking_blocks went out twice and Claude answered 400. The merged turn now keeps the first copy of each redacted or signed block on the Anthropic routes and both Bedrock Converse builders. Snowflake Cortex goes back to its previous message building, since its double send cannot be proven live without a Cortex account and is tracked on its own. * test(anthropic, bedrock): cover a redacted block with null data and a non-block part beside a cache breakpoint * fix(anthropic, bedrock): match only text-valued thinking items when merging replayed blocks	2026-10-20 15:00:31 +00:00
Mateo Wang	963333d654	fix(proxy)!: let proxy admin keys read raw cloud storage file ids on GET /files/{id}/content (#40621) ... * fix(proxy): let proxy admin keys read raw cloud storage file ids on GET /files/{id}/content Since #30595 the endpoint answered 400 for every raw gs:// or s3:// id, which broke the documented unmanaged Vertex batch flow at its last step, while a double-encoded id slipped past the guard entirely. Raw ids are now readable by proxy admin keys only, every other key gets 403, and the guard decodes the id fully before deciding, so encoding depth no longer matters * fix(proxy): decode nested percent-encoded file ids iteratively An id percent-encoded a thousand or more times sent the recursive decoder past the interpreter's recursion limit, so a proxy admin key got a 500 instead of a verdict on the id. The decoder now walks the encodings in a loop, so any depth resolves * fix(proxy): cap the decode passes the raw cloud storage file id guard makes Any authenticated key could send a file id wrapped in tens of thousands of percent-encoding layers and the guard would unwrap every one of them, each pass walking the whole id, so a 120 KB request line held a worker for about five seconds and a 2 MB one for minutes. The guard now unwraps at most eight layers, and an id still changing after that is treated as a raw cloud storage id, so it stays admin-only instead of being decoded any further * refactor(proxy): type the decode step the raw cloud storage file id guard folds over * test(proxy): return a streaming result from the admin raw id test mock now that vertex_ai file content streams * test(proxy): send raw cloud ids to the content route the way uvicorn delivers them Starlette's TestClient decodes the path twice, so the twice-encoded cases reached the route fully decoded and never hit the decode loop. The cases now name the id the route receives, and the helper tests take a typed quote helper and Final constants. * test(proxy): mark the raw cloud id test locals Final	2026-10-20 10:58:42 +00:00
Max Azatian	77880a0653	fix(otel)!: leave out span cost when the price lookup failed (#44187) ... * fix(otel): leave out span cost when the price lookup failed A model missing from the price map gets response_cost 0.0 in the standard logging payload, with response_cost_failure_debug_info set. The OpenInference writer (arize, phoenix, langfuse_otel) and the OTel v2 span data copied that 0.0 into llm.cost.total, litellm.cost.total and langfuse.observation.cost_details, so backends showed the call as free. Skip the cost when the lookup failed, except on cache hits, which are free. * test(otel): keep the guardrail charge on the guardrail span for unpriced calls * refactor(otel): type the Arize cost writer input and reuse the cache_hit flag * fix(otel): keep a billed guardrail fee on an unpriced call's Arize span cost Only the placeholder 0 is left out when the price lookup failed, so a guardrail fee LiteLLM billed still reaches Arize, Phoenix, Langfuse OTel and W&B Weave OTel. Adds unit cases for that fee and a malformed cost. * fix(arize): leave out the span cost on any failed price lookup, matching OTel v2 * fix(logging): clear a stale cost failure flag when a later pricing succeeds Stream-start pricing on the request model name can fail and set the cost failure flag even when the final pricing succeeds (OpenRouter usage.cost, an Azure deployment name priced from the response model). The new span gate then dropped a real cost. Each pricing now resets the flag, and uncached_price restores whatever flag it found. * test(logging): pin the start time in the stale cost flag tests --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-20 09:48:47 +00:00
Zuraiz Anjum	66cd1a6516	fix(streaming): restore the token estimate for streams that send no usage (#44230) ... * fix(streaming): restore the token estimate for streams that send no usage A stream without stream_options got a made-up Usage(0, 0) written into its final chunk's hidden params. Since #42323 the chunk builder treats that as a provider-reported zero, so these streams were logged and billed at 0 tokens and $0 instead of the tokenizer estimate. Only attach the summed usage when some chunk actually carried usage. * test(streaming): use a fixed start time and check the estimated cost * fix(streaming): keep reported usage on the synthesized finish chunk and test it * test(streaming): cover explicit zero usage reported by the provider * fix(streaming): set the token estimate on a copy of the final chunk and ignore usage with no counts * fix(streaming): keep final chunk edits in the logged response when the provider sends no usage * fix(streaming): mark the unreported usage placeholder so every chunk rebuild falls back to the estimate * test(streaming): wait on the success callback event instead of sleep-polling --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-20 08:50:29 +00:00
joshua-berri	3124797399	fix(bedrock): resolve profile pricing before applying custom rates (#47419) ... * fix(bedrock): price Converse calls using the invoked model profile * fix(pricing): retain registered rates across metadata updates * fix(pricing): honor temporary registered prices for Bedrock profiles * fix(bedrock): record invocation model ID for each completion attempt * test(bedrock): recalculate fallback cost after metadata updates * fix(pricing): preserve cache-only registered price overrides * fix(bedrock): preserve priced overrides without widening shared pricing * fix(bedrock): retain explicit pricing through token cost lookup * fix(bedrock): layer cache overrides over invoked profile rates * fix(bedrock): keep effective prices consistent across billing * fix(bedrock): share profile pricing and custom rate resolution * fix(router): remove unused pricing suppression * fix(cost): preserve rates across mixed token thresholds * fix(router): share deployment pricing during startup * fix(bedrock): preserve Router pricing inheritance for profiles * fix(bedrock): retain configured pricing for unmapped profiles --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>	2026-10-20 00:10:49 -07:00
Lai Wei	bda4e60f9b	fix(streaming): keep finish_reason and provider usage when rebuilding streamed text completions (#44349) ... * fix(streaming): keep finish_reason and provider usage when rebuilding streamed text completions stream_chunk_builder_text_completion read finish_reason from chunks[-1] and recounted usage from messages. With include_usage the last chunk is a usage-only trailer, so finish_reason came back None (or raised IndexError when the trailer had no choices), and prompt_tokens was 0 because a text-completion prompt is not in messages. Scan for the last finish_reason and prefer the provider-reported usage, as the chat path already does. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(streaming): type the text completion chunk builder so its scans add no basedpyright debt Read chunk fields as typed attributes instead of untyped subscripts, which clears the reportUnknownArgumentType breach the lint gate flagged * fix(streaming): keep the provider's full usage, including token details, when rebuilding text completions Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(streaming): rebuild dict-form text completion chunks again stream_chunk_builder routes dict chunks holding TextChoices to the text completion builder, which now reads attributes. Convert them to TextCompletionResponse at the routing point. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(streaming): accept dict chunks in the text rebuild and derive its usage like the chat path Moves the dict to TextCompletionResponse conversion into stream_chunk_builder_text_completion so direct callers keep working, and builds usage through ChunkProcessor.calculate_usage over the chunks that report counts, so a trailer without total_tokens keeps its prompt and completion counts and the result is a fresh Usage * fix(streaming): read text completion usage through the shared usage extractor so usage dicts on typed chunks rebuild * fix(streaming): merge text completion logprobs across chunks and rebuild dict text chunks as text completions * fix(streaming): rebuild one text completion choice per index and keep null logprobs fields null * fix(streaming): keep dumped chat chunks with a choice-level text on the chat rebuild path Route a dict chunk to the text completion builder only when its choice has `text` and no `delta`. The Responses bridge snapshots chat chunks with model_dump(), and Together's chat choices carry `text` next to `delta`, so streamed /v1/responses calls to Together ended without response.completed. Group text completion choices by index in one sorted pass, so rebuilding an n>1 stream costs about the same as rebuilding an n=1 stream of the same size. * fix(streaming): keep text completion rebuilds working on mixed chunks and unreadable logprobs A chat chunk inside a text completion stream now converts to a text chunk that keeps its finish_reason and adds no text. A dict chunk whose logprobs fail validation is read again with logprobs dropped, and logprobs that are not a Logprobs object keep the last value sent. Each of these inputs raised or lost data at the previous commit, and each now rebuilds without raising Also adds a Purview test showing a multi-choice text stream is blocked like the non-streamed response, and Final annotations on the new test locals * fix(streaming): rebuild text completion choices without an index at index 0 Text completion choices whose index is None now rebuild under index 0, as on the merge base, where the sort by index raised at the previous commit. A chat chunk inside a text completion stream now keeps the usage it reports, and a choice whose logprobs mix a Logprobs object with another shape keeps the last value sent, as on the merge base * fix(streaming): rebuild text completion choices with a string index under that int A text completion choice whose index is a string now rebuilds under the int it names, and one whose index cannot be read as an int rebuilds at index 0, as on the merge base. A string index mixed with an int index raised TypeError at the previous commit, and a string-only index came back as a string * test(streaming): drop a docstring that repeats its test * fix(streaming): fall back to choice 0 for an infinite text completion index A float infinity index made int() raise OverflowError, which the index coercion did not catch, so the rebuild failed where the merge base returned choice 0. --------- Co-authored-by: Lai Wei <8022184+roywei@users.noreply.github.com> Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-20 05:31:39 +00:00
Mateo Wang	2d181e6633	fix(token_counter): count DeepSeek V4 text with DeepSeek's own tokenizer (#47353) ... Local token counts for DeepSeek V3 and V4 model names now use DeepSeek's own bundled tokenizer instead of cl100k_base, and tool definitions on V4 names count with V4's chat-template tool framing	2026-10-20 03:43:35 +00:00
Yassin Kortam	ce4a6cbf5b	perf(streaming): cut per-chunk pydantic round trips on openai-compatible streams (#47030) ... * perf(streaming): skip full-chunk dump and delta rebuild on openai-compatible chunks Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * perf(streaming): reuse the built choice and delta on plain openai-compatible chunks Co-authored-by: yassin <yassin@berri.ai> Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(streaming): copy upstream chunk attributes in upstream key order The scalar fast path iterated a frozenset of keys, so the SSE key order of chunk extras like service_tier and obfuscation changed with each worker's hash seed * test(streaming): count chunk_creator calls with a profiler instead of patching classes * test(streaming): check service_tier still passes through chunk_creator * fix(streaming): reuse the built choice for chunks with upstream choice extras * test(streaming): cover ModelResponseStream chunks on the choice reuse path * fix(streaming): keep main's delta rebuild for deltas with nested values Clearing role in place on a delta that holds tool calls left its nested fields unset, so chunk.model_dump() dropped keys like a custom tool call's name on later chunks. Deltas holding only scalars keep the in-place path. * perf(streaming): build each plain OpenAI chunk's delta once and skip pydantic attribute misses Later plain ChatCompletionChunks now build one Delta and one StreamingChoices, with no full-chunk model_dump, and read stored values instead of attribute probes that raise and catch AttributeError. Nested-value chunks no longer pay the dict(model) misses that made them slower than the merge base. * fix(streaming): read hidden params a chunk carries as a pydantic extra * test(streaming): pin logprobs, Azure filter extras, and audio and image deltas on later OpenAI chunks * test(streaming): cover role, reasoning, choice extras and billing on plain OpenAI SDK chunks --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: mateo <mateo@berri.ai> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-20 02:42:32 +00:00
Kerry Lu	c6c303a618	fix(batches): apply the Vertex regional endpoint uplift to batch cost (#47466) ... * fix(batches): apply the Vertex regional endpoint uplift to batch cost batch_cost_calculator takes vertex_location and multiplies by the model's regional_endpoint_uplift_multiplier through get_vertex_regional_endpoint_uplift, and every batch cost path (aretrieve_batch pricing, completed-batch logging, native Vertex batch rows, the proxy batch cost poll and its per-line items) resolves the deployment's location and passes it down Co-authored-by: Mrun25 <165297479+Mrun25@users.noreply.github.com> * test(logging): point the resolver tests at resolve_vertex_location_for_cost --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: Mrun25 <165297479+Mrun25@users.noreply.github.com>	2026-10-20 01:51:51 +00:00
Kerry Lu	d29200fa05	fix(vertex_ai): bill per-character text embeddings on Google's billableCharacterCount (#47460) ... Vertex text embedding predict responses report metadata.billableCharacterCount, the unit Google bills text-embedding-005 and text-multilingual-embedding-002 on. Carry it into usage.prompt_tokens_details.character_count and, when the model carries input_cost_per_character, bill that count instead of the token count so the prompt is charged under one unit. Per-token embeddings (gemini-embedding-001) are unchanged. Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-19 18:17:29 -07:00
Mateo Wang	8b9cd12a89	test: catch regressions in the validation lines #44798 added (#47420) ... * test: pin the validation lines #44798 kept with failing cases * fix(containers): accept endpoint table entries that omit their param lists * test: keep the endpoint table and xAI adapter as on main The endpoint table ships inside the package, so optional param lists fixed no reachable state and turned a loud failure into silently dropped params. Drops the Gemini case that main's tests already cover. * test: cover the cost map backup and Gemini image config validation lines The cost map backup adapter's hide flag, and the validation itself, could be removed with every test still green. The Gemini imageConfig adapter could be narrowed with only the integration suite noticing, which does not run on PRs. The endpoint table cases now read a real file through the module's location instead of replacing open, so reading the file another way keeps them green. * test: pin the container handler's loud table failure and loosen two pinned drops A container endpoint table entry without path_params or query_params fails the call on main, and no test held that. The new case trims each key from the packaged table and expects the validation error. The Gemini imageConfig case now accepts a drop or UnsupportedParamsError for a non-object value, and the Bedrock beta case checks only that numbers come back as strings, so neither pins behavior the drop_params convention may change. * test: check a numeric beta array is never split as text and use the latest Gemini image model The Bedrock case now also fails when a JSON array of numbers falls through to the comma split, which returns bracketed fragments, while a drop or a string coercion both stay allowed.	2026-10-20 01:06:37 +00:00
Kerry Lu	3fa1587f43	fix(logging): do not stamp a provider handoff when pre_call runs for a proxy-only failure (#47456) ... Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-20 00:59:53 +00:00
Kerry Lu	09e9193514	fix(cost): bill Gemini audio/image/video prompt tokens at the resolved input rate when no modality rate exists (#47373) ... * fix(cost): bill Gemini audio/image/video prompt tokens at the resolved input rate when no modality rate exists Co-authored-by: shivam <shivam@berri.ai> * style(cost): ruff format the modality cost calls --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: shivam <shivam@berri.ai>	2026-10-19 15:14:46 -07:00
Mateo Wang	b51b9b7d43	fix(anthropic)!: answer 400 for a malformed tool_result text on /v1/messages and count_tokens (#47347) ... * fix(anthropic): answer 400 for a malformed tool_result text on the Responses bridge and count_tokens A tool_result text block whose text is null, a number, or missing made /v1/messages and /v1/messages/count_tokens answer 500 on OpenAI and Azure models. Both routes now answer 400 naming the block, and drop the block when drop_params is on. * fix(anthropic): keep a missing tool_result text as empty text, bound the error, honor body drop_params on count_tokens * fix(anthropic): apply the tool_result text check on the chat/completions bridge and every count route The chat/completions bridge used for Azure, Gemini and other providers now answers the same 400 for a null or numeric tool_result text and drops the block under drop_params, so a model group that mixes OpenAI with another provider answers the same way on every deployment. Gemini and Vertex count_tokens apply the same check, count_tokens turns on drop_params for Claude Code and Codex the way /v1/messages does, and a tool_result without a tool_use_id is checked too * fix(proxy): answer 400 for a malformed tool_result text on count_tokens models without a count API Providers with no token counting API fall back to the local tokenizer, which counted a null or numeric tool_result text as fine while /v1/messages on the same model answers 400. The fallback now runs the same check, unless drop_params applies to the deployment or the request * fix(proxy): honor request drop_params on the local count fallback when no deployment resolves * test(integration): cover non-string tool_result text on both /v1/messages bridges and count routes * fix(anthropic): keep a dropped tool_result on Mistral and reject it before a guardrail rewrite Under drop_params a tool_result whose only text block was null or a number became an empty tool message, and Mistral's empty-message filter removed it, so Mistral answered 400 for a missing tool reply. The filter now only removes empty assistant messages, which is what Mistral rejects. A guardrail that rewrites structured_messages wrote the dropped text back as "", so a null or numeric text was silently blanked even without drop_params. The rewrite path now answers the same 400 as the bridges unless the request or global drop_params is set. * test(integration): cover the Mistral empty tool reply and the guardrail rewrite tool_result text check * fix(anthropic): keep a malformed tool_result text through a guardrail rewrite and keep Mistral's null-message drop A guardrail that rewrites structured_messages now writes the caller's null or numeric tool_result text back in place, so the route's bridge and the deployment's drop_params decide after routing, the same as with no guardrail. The rewrite path no longer answers its own 400 before routing. Mistral drops a null-content system or user message again, as main does, and only a tool reply is exempt from that filter so a dropped tool_result keeps its tool call. * test(mistral): expect empty system and user turns dropped and the empty tool reply kept * perf(anthropic): restore kept tool_result text parts in one linear pass * test(integration): cover the tool_result text restore across tool_results, the chat bridge, and a batch upload behind a rewriting guardrail * fix(anthropic): let guardrails scan malformed tool_result text and honor drop_params on native Anthropic A rewriting guardrail now sees a non-string tool_result text as its JSON text and the write-back restores the caller's value by the sanitized tool_use_id when the guardrail left it unchanged. Native Anthropic drops the bad block under drop_params on /v1/messages and count_tokens, and Mistral keeps an empty tool reply only when it answers a tool call, sent as empty text. * fix(anthropic): compare a kept tool_result text to its scanned form once and align the wire tests with drop_params * test(integration): cover native Anthropic drop_params resolution, guardrail scanning of numeric tool_result text, and the Mistral orphan tool message * fix(count_tokens): honor the router's default drop_params when counting a malformed tool_result text * test(count_tokens): send the tool_result count tests through a real request body instead of a mocked parser * test(count_tokens): send the native Claude count test through a real request body * fix(anthropic): keep each non-string tool_result text when tool_use_ids sanitize to the same id * fix(anthropic): keep non-ASCII characters in the guardrail's view of a non-string tool_result text * test(gemini): mock the count_tokens upstream with respx instead of patching the client factory * fix(mistral): keep an empty tool reply only for an open call, and forward non-object message items on the native drop An empty tool reply re-answering a call the conversation already moved past made Mistral reject the request, and a tool call id that is not a string crashed the filter. Native Anthropic under drop_params assumed every message item was an object. * fix(mistral): find answering tool replies in one pass instead of copying the open call set per reply * fix(mistral): ignore dropped empty placeholders when tracking open tool calls * fix(mistral): drop an empty tool reply when another reply to the same call carries the result * refactor(anthropic): share tool_result text helpers to shrink the diff * fix(anthropic): answer 400 for a non-string tool_result text on the OpenAI Responses bridge	2026-10-19 21:13:46 +00:00
Kerry Lu	1212260ab1	fix(logging): report the cost-map entry billing used in model_map_information (#47182) ... * fix(logging): report the cost-map entry billing used in model_map_information Billing resolved the deployment's own cost-map entry and logging ran a second, name-only lookup, so callbacks and spend logs showed the catalog rates for a custom-priced deployment. completion_cost now stores the entry it billed from on the logging object and the standard logging payload reads it, falling back to the old lookup only when billing never ran. * fix(logging): pass the deployment id into the logging cost-map lookup Drop the logging-object plumbing and keep the lookup where it was: get_standard_logging_object_payload now hands the deployment id to get_model_cost_information as router_model_id, the same id billing uses, so the deployment's own cost-map entry is reported instead of the catalog entry. * test(logging): mirror the proxy metadata in the deployment-price regression test * fix(logging): keep the catalog model_map_key, report only the deployment's own rates --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-19 13:38:22 -07:00
Mateo Wang	c0d88b46c9	fix(azure): cache the remaining per-request Entra credentials and keep token refresh off the event loop (#47348) ... * fix(azure): cache the remaining per-request Entra credentials and keep token refresh off the event loop Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(realtime): await the now async azure health-check auth header helper Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(azure): await async azure_ad_token_provider results in the threaded wrapper * fix(azure): keep transport params when validating async Azure client params on pydantic 2.11 * test(azure): assert the token and validation thread hops by thread identity instead of sleeps * fix(azure): give the OIDC token exchange its own short-lived HTTP client The exchange now runs from worker threads, so it no longer shares litellm.module_level_client's connection pool with other threads * test(azure): check the OIDC exchange closes its client through an in-process transport * refactor(responses): merge caller extra_headers into a new dict instead of updating validated headers in place --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-19 20:35:27 +00:00
yucheng-berri	3e18a4b55d	fix(router): record cooled deployments on the all-cooled failure row (#47120) ... * fix(router): record cooled deployments on the all-cooled failure row A RouterRateLimitError now carries the cooled deployments of the route the request resolves to for the caller's team (model group, alias, wildcard or team route), each with its masked api_base. get_error_information copies them into error_information.error_cooldown_deployments so the SpendLogs failure row and every logging callback can tell which deployments were cooling * fix(router): name cooled deployments from the router's own resolved route Use the deployments the router resolved for the request, before health and cooldown filtering, instead of re-deriving the route. Alias chains, the provider-model fallback, wildcards and team filtering now match routing by construction. A routing-strategy refusal records null. * fix(router): name only the cooled deployments tag and region routing allow The refusal's cooled-deployment list now leaves out deployments the request's tags or the end user's allowed region keep it from, so a tenant's refusal row no longer shows another tenant's api_base * fix(router): keep failure logging working for refusal subclasses that skip init A RouterRateLimitError subclass that never calls its parent init now logs a null cooled-deployment list instead of breaking the failure payload * test(router): call the refusal routing helpers directly The router coverage check needs each router function called by name from a unit test --------- Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>	2026-10-19 13:18:20 -07:00
Mateo Wang	c82e8244a5	fix(count_tokens)!: count tools the way DeepSeek V4 and Qwen3.5 chat templates render them (#47173) ... * fix(count_tokens): count tools the way DeepSeek V4 and Qwen3.5 chat templates render them * refactor(count_tokens): hold the tool counting wiring for a follow-up commit * refactor(count_tokens): hold the chat template tool sections for a follow-up commit * fix(count_tokens): count tools the way DeepSeek V4 and Qwen3.5 chat templates render them * fix(count_tokens): skip tool_choice and non-function tools for chat template families, leave out Fireworks V4.1 spelling * fix(count_tokens): count Anthropic tools in the shape the messages bridge sends them A missing description is no longer rendered as null and strict is counted when set, matching what DeepSeek V4 and Qwen3.5 deployments receive. Adds tests that pin each template's schema rendering and its system turn. * test(count_tokens): check the prompt caching threshold agrees with token_counter for DeepSeek V4 and Qwen3.5 tools * fix(count_tokens): skip Anthropic web search tools and count unmapped Anthropic tool keys for chat template families * test(token_counter): cover chat-template tool counts across count routes, budgets, ITPM and context edits Integration cells check that DeepSeek V4 and Qwen3.5 tools are counted the way their chat templates render them on /v1/messages/count_tokens, /utils/token_counter, /v1/responses/input_tokens, strict budget reservation, project ITPM on chat, messages and responses, and the clear_tool_uses trigger, with grok controls keeping OpenAI framing	2026-10-19 17:02:56 +00:00
devin-ai-integration[bot]	f85926a652	feat(router): keep a session on one kubernetes pod (#44393) ... Requests with an explicit session id stick to one discovered pod via rendezvous hashing Requests without a session id keep round robin Pod routing records are included in logs, spend logs, and traces Resolves LIT-9168 Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-19 09:58:19 -07:00
devin-ai-integration[bot]	c80f1c2ec8	fix(router)!: count native Responses WebSocket turns toward deployment limits and budgets (#45727) ... * fix(responses): write one spend-log row per native WebSocket turn Each response.create turn on a native Responses WebSocket connection now logs its own call as it finishes, with its own usage and the resp_ id the client saw as request_id. A failed turn is booked alone and no longer flips the other turns. * fix(responses): bill the usage a failed native WebSocket turn reports * fix(proxy): pin the limiter slot owner to the proxy call id and refund unsettled reservations on disconnect The v3 limiter stashed whichever litellm_call_id the request body carried as the slot owner, so a client-supplied id on a pass-through body left the proxy's own success and failure events unable to release the slot. The owner is now the proxy's logging call id. A WebSocket connection whose turns log under their own ids never settles the TPM, ITPM, or OTPM estimate the connection reserved, so the disconnect release now refunds any reservation no callback settled, once. * fix(proxy): bill failed WebSocket turns and refund only the reserved window on disconnect A failed turn's reported usage now counts toward the key's TPM and the project ITPM/OTPM scopes the same way a success does, and closing the socket hands back only the estimate still unused in the window that holds it, so a window that already rolled is left alone. An id-less error event is booked against the newest pending turn, the one the backend rejected at parse time, and a turn that nests its input under response logs its user message. A connection's one budget reservation goes to the first turn that settles it, every later turn charging its cost directly. * test(proxy): expect the settling call id on a pass-through budget reservation * fix(proxy): charge successful Responses WebSocket turns to TPM and ITPM/OTPM A native Responses WebSocket turn reaches the rate limiter's success callback with its raw event list as the response and no combined_usage_object, so the turn's tokens never reached the key's TPM window or the project's input and output token limits. Read the usage from the turn's events when the call type is a Responses WebSocket turn. * fix(proxy): release a rejected pass-through's slot and count each websocket turn once toward project quotas The limiter's failure hook looked up the parallel slot by the request body's litellm_call_id, while the slot belongs to the proxy's logging call id, so a pass-through request a pre-call hook rejected held its slot for an hour when its body carried an id. Both now resolve the id the same way. Each response.create frame already charges its estimate to project ITPM/OTPM, so the turn's own usage no longer adds a second count. The cost callback's failure hook read the body's litellm_call_id through a strict model and raised on a non-string value, which dropped the failure row. It now reads a string id or none. * fix(proxy): keep per-turn WebSocket limits, request bodies and collector reservations right Free a rejected request's parallel slot through the request it runs in, and skip native Responses WebSocket connections, whose disconnect frees the slot. Count WebSocket turns toward the connection's tag TPM. In collector mode, claim the shared budget reservation before the spend event is built, so only the first turn settles it. Store each turn's own frame as its request body, and send an id-less error to the oldest waiting turn unless an earlier turn is streaming. * fix(proxy): store a failed WebSocket turn's own request and count tag TPM only for calls that carry the tag * fix(responses): log the client's turn frame, keep the payload id and reservation shape for non-WebSocket calls * fix(proxy): keep the legacy limiter's WebSocket slot until the socket closes * fix(router): count native Responses WebSocket turns toward deployment limits and budgets * fix(router): re-check deployment budget and RPM on each Responses WebSocket turn * test(router): list the WebSocket turn admission method as covered through its partial * fix(responses): give a refused WebSocket turn's error frame a 429 status so Codex ends the turn * fix(router): leave ITPM/OTPM to socket open and record a refused WebSocket turn as the socket's failure * fix(proxy): log the routed model group on a WebSocket turn's failure row * fix(router): count WebSocket turn tokens toward TPM and re-run routing strategy checks on each turn * test(integration): cover per-turn admission on Responses WebSockets Adds integration cells for budget, RPM, TPM, a mid-socket TPM edit, usage-based-routing-v2, the project quota frame, and the open-time failure frame on the native and managed relays, plus HTTP controls for TPM counting and the failure row model_group * fix(responses): count WebSocket turn tokens once and end a socket whose turn check fails A native Responses WebSocket turn is now logged as an async call, so a proxy with a sync success callback such as the response cache no longer runs each CustomLogger's sync success hook on top of the async one. That second run counted every turn's tokens twice toward deployment TPM. A turn whose admission check raises an unexpected error now gets a 500 error frame, the socket closes with 1011, and the error becomes the socket's failure, on both the native and the managed relay, instead of the socket dropping with no frame and no failure row. A refused turn's failure row now carries the request's tags from the router's metadata, the same way it already carries the model group. * test(integration): cover a crashed WebSocket turn check and failure-row tags A turn whose admission check raises gets a 500 server_error frame, the socket closes with 1011 and its one failure row carries the error, on both relays. The refused turn's failure row keeps the caller's tags, and HTTP failure rows on chat, responses and messages keep them too. * fix(responses): keep a WebSocket open after a crashed turn check and keep only string tags on failure rows A turn whose admission check raises an unexpected error still gets a 500 error frame, but the socket now stays open, like a refused turn. Closing it cut any turn still streaming on the same socket, which a client that sends its next response.create early would lose. A refused turn's failure row now takes the router's tags only when every tag is a string, so the fallback never copies a caller's unvalidated tags onto the row. * test(integration): cover a turn still streaming when the next WebSocket turn's check crashes A native turn still streaming when the next turn's admission check raises now has its own cell. It must complete and be billed at the turn's price. The crashed-check cell also keeps the fault set for one more turn, so a relay that stopped checking turns after a crash goes red. * fix(responses): run per-turn guardrails before the deployment's turn check on WebSockets A turn after the first now runs the project quota check, then the proxy's pre_call guardrails, then the deployment's turn admission, on both the native and the managed relay, the order HTTP calls use. A turn a guardrail blocks gets the guardrail's error even past the budget and no longer counts toward the deployment's rpm or runs its pre-call checks. * fix(responses): bill a WebSocket turn's guardrail cost when the deployment refuses it A turn the per-turn guardrail passes and the deployment then refuses now writes its own failed spend row with that turn's guardrail information, on both relays, the way a guardrail-blocked frame and an HTTP refusal already do * fix(responses): bill a refused WebSocket turn on one row only A refused turn whose guardrails recorded a cost is already billed on its own row, so it no longer also becomes the connection's close-time failure row * fix(responses): bill a refused WebSocket turn's guardrail cost on the socket's failure row The turns a deployment refuses after their guardrails passed now add their guardrail records to the socket's close-time failure row instead of a row of their own, so that row's failure hooks, model group and call type cover them * fix(responses): bill a WebSocket's refused turns when the session limit closes it * fix(responses): bill refused WebSocket turns when the session limit cancels the relay * fix(responses): free the WebSocket slot at the session limit without waiting on the failure row * fix(responses): keep the session limit's second cancel so a relay that swallows the first frees the slot * fix(responses): free the WebSocket slot before the close-time failure row and drain pending rows at shutdown * fix(proxy): commit spend before waiting on pending logging tasks at shutdown and again after * fix(responses): start the close-time failure row before the slot release so a late cancel cannot drop it * fix(responses): build the close-time failure row inside its task so a bad guardrail record cannot skip the crash close * fix(proxy): always commit spend again after the shutdown wait for pending logging tasks --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-19 15:35:20 +00:00
alexcastgonz	6762d65eb8	fix(vertex_ai): price streamed pass-through calls with the regional uplift (#44795) ... * fix(vertex_ai): price streamed pass-through calls with the regional uplift The streamed Vertex pass-through handler builds the response with stream_chunk_builder, which stamps a cost into _hidden_params without the vertex_location. The handler then prices the response again with the location from the URL, but only into kwargs, and the logger prefers the stamped cost. Streamed calls on a regional endpoint were billed at the global rate. Stamp the location-aware cost on the response in the shared generateContent payload builder so the logger records it. Fixes #44755 * style(vertex_ai): keep the response_cost assignment within the 120-char limit * refactor(vertex_ai): set the passthrough response cost with set_hidden_param Writing _hidden_params directly mutated a parameter and needed a pyright ignore, which the type discipline gate counts as LIT004 and LIT011. set_hidden_param is the shared helper for this. * test(integration): check Vertex pass-through spend rows keep the regional uplift when streamed * fix(proxy): price streamed Vertex pass-through spend like the non-streamed call Drop the location-blind cost stream_chunk_builder stores instead of stamping a cost, so the logger prices streamed generateContent and rawPredict calls with the URL's location and the deployment's custom pricing, the same way it prices non-streamed calls * fix(proxy): price custom-priced Vertex pass-through deployments at their own rates The stamped response_cost from the generateContent logging helper is returned before the logger checks custom pricing, so a deployment with custom input/output rates was billed at the cost-map price. The helper now passes custom_pricing and the deployment id into completion_cost, so the stamp holds the deployment rate for streamed and non-streamed calls, and deployments without custom pricing keep the regional uplift. * fix(proxy): bill Vertex /v1beta and interrupted pass-through streams by the deployment location and price * fix(proxy): give the new pyright ignore a reason for the LIT004 gate * test(integration): bill a custom-priced Vertex pass-through stream at the deployment price, cut-off streams included * fix(proxy): let the logger price non-streamed /gemini pass-through calls so both modes bill the same * fix(proxy): keep a client base_model out of pass-through pricing and price gateway Gemini streams as Gemini A top-level base_model in a pass-through body now reaches the logging params only for a key or team with allow_client_pricing_override, so a plain key cannot pick a cheaper model's price once the logger prices these calls. The test that pinned every litellm-owned body name into the logging params now leaves base_model to its own key-gated test. The Vertex handler now classifies a non-Google upstream host as Vertex only for Vertex resource paths, so a /gemini stream through a GEMINI_API_BASE gateway is priced as Gemini without the regional uplift. Adds the audit's integration spend test for Claude on Vertex, /v1beta, the named custom-priced /gemini deployment, and a cut OpenAI stream. * test(integration): price the gateway /gemini stream case as Gemini and cover client base_model and gateway host pricing The cost harness sends /gemini through GEMINI_API_BASE, which the pass-through now logs and bills as gemini, so the streamed case moves from the Vertex cases to the Gemini cases under the Gemini price. New spend tests cover a body base_model repricing only for keys allowed client pricing, a GEMINI_API_BASE gateway billing as Gemini in both modes, and a configured non-Google gateway picking the provider from the path. * fix(proxy): price pass-through Gemini by the route and ignore a non-string base_model The Vertex pass-through handler picked Gemini pricing from the URL path, so a configured pass-through to a Vertex gateway with a short path (no /projects/ segment) was billed as Gemini, and its Claude streams at $0. The provider now comes from the route: a call through /gemini or to generativelanguage.googleapis.com prices as Gemini, and everything else as Vertex, the same rule main used. Matching the GEMINI_API_BASE host was rejected because one gateway can serve both APIs, and the path rule was rejected because short gateway paths look like Gemini paths. A non-string base_model (a number, list or object) made the cost calculation fail and bill $0 once the stamped stream costs were gone. get_base_model_from_metadata now ignores it and falls back to the deployment's base_model, so the call bills the list price. A 400 was the other option, but the logger runs after the upstream answered. * test(integration): bill a non-string body base_model at the list price on every pass-through route * fix(proxy): bill a non-string model_info base_model at the list price and drop a non-object client model_info A key allowed client pricing can send metadata.model_info in a pass-through body. A non-string model_info.base_model made the cost lookup fail, and once the stamped stream and Gemini costs were gone those calls billed $0 on /gemini and on streamed /vertex_ai and /v1beta. The lookup now ignores a base_model that is not a string, the same rule the root base_model got, so the call bills the list price. A model_info that is not an object (a string or a list) broke several logging steps that read it as a mapping, so a non-streamed /gemini call fired no success callback and no pass-through call wrote a spend row. The pass-through route now leaves a non-object model_info out of the logging metadata, so the call bills the list price. A 400 was the other option, but it would turn calls that answer 200 today into errors, and guarding every reader of model_info would spread the same check over many files. * fix: reject a non-object model_info before the provider call again The previous commit made the base_model lookup return None for a model_info that is not an object. That lookup also runs during call setup on every router route and SDK entrypoint, where such a value used to fail before any provider request. With the early return the call went upstream, the provider billed it, and the request then failed in a later reader that still expects an object. On /v1/messages and /v1/responses the key was also charged for a response the client never got. The lookup again reads base_model from any truthy model_info, so a non-object value fails during setup the way it did before this PR. A non-string base_model inside an object still bills the list price, and the pass-through route still drops a non-object client model_info at intake, so pass-through calls keep billing the list price. * fix: match the Gemini API host exactly when picking the pass-through cost provider The provider check accepted any host ending in generativelanguage.googleapis.com, so a Vertex host such as vertex-generativelanguage.googleapis.com was priced as Gemini and lost the regional uplift. It now accepts that host or a subdomain of it. * test: pin that a subdomain of the Gemini API host keeps the Gemini price --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-19 08:10:52 +00:00
joshua-berri	9c958aff34	fix(logging): deliver completed batch success callbacks consistently (#47192) ... * fix(batches): dispatch configured success callbacks during reconciliation * fix(batches): retain billed job claim when sync dispatch shuts down * fix(batches): finish reconciliation when logging executor is stopped * fix(logging): avoid duplicate custom hooks during async batch dispatch * fix: preserve sync-only custom callback delivery * fix: scope callback deduplication to per-call async recipients * refactor: type per-call async success callbacks * refactor: retain logging constructor callback compatibility * test: support current batch reconciliation metadata * fix(logging): honor per-logger redaction during sync success delivery * fix(logging): centralize completed success callback dispatch * fix(guardrails): avoid duplicate success callback dispatch --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>	2026-10-18 09:19:04 -07:00
Mateo Wang	7e6fb09da3	fix(streaming)!: map stream read timeouts to litellm.Timeout on chat, messages, and responses (#47198) ... * fix(streaming): map stream read timeouts to litellm.Timeout * revert(streaming): move the timeout mapping to a later commit * fix(streaming): map stream read timeouts to litellm.Timeout on chat, messages, and responses * fix(streaming): keep stream fallback and cooldown unchanged for transport timeouts A chat stream served through the Responses bridge now keeps mid-stream fallback on a stall, because the fallback exemption also covers a litellm.Timeout whose cause is an httpx transport timeout. The Responses stream hands the raw transport error to failure callbacks again, so router cooldown sees a stall as it did before. The 408 deployment info now lists stream_timeout. * test(integration): cover a stalled hosted_vllm stream on chat, Responses, and Messages with its spend log row * fix(router): keep a fallback deployment whose stream stalled out of cooldown * test(integration): cover bridged chat, fallback and cooldown for stalled hosted_vllm streams	2026-10-18 13:58:34 +00:00
yucheng-berri	b3c0f3457d	fix: handle missing choice indices in streamed output recording (#46947) ... * fix: handle missing choice indices in streamed output recording * test: verify recorded partial output on client disconnect * test: correlate streaming regressions with persisted request IDs * test: build progress-stream configs without mutation --------- Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>	2026-10-17 14:17:46 -07:00
Kerry Lu	0f007c05fc	fix(logging): run legacy s3 callback for streamed /v1/messages calls (#47156) ... Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-17 13:24:05 -07:00
devin-ai-integration[bot]	84d91bbe87	fix(vertex): match standalone 403 status tokens instead of any substring (#47134) ... * fix(vertex): match standalone 403 status tokens Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(vertex): keep text 403 fallback for wrapped 500 errors Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(vertex): keep BadRequestError for explicit 403 text matches Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(vertex): let structured body codes override the 403 text fallback Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-17 19:17:18 +00:00
devin-ai-integration[bot]	8226b2be9a	fix(otel): report cache hits at zero cost with a cache-hit flag in V1 and V2 spans (#43604) ... * fix(litellm): report zero cost and cache-hit attrs on cache-served spans * fix(litellm): stamp cache-hit marker on HiddenParams carriers and restore probe side effects gauntlet-mini on ace57d25f verified two live gaps. TextCompletionResponse and ResponsesAPIResponse carry _hidden_params as a HiddenParams object, so the dict-gated marker write skipped them and the served hit still stamped the full price. The marker write is now container-agnostic, which it already was for the partial-embedding stamp, and a regression test exercises the carrier end to end. _uncached_response_cost also restores billed_token_rates, zero_cost_warned, and the response_cost_failure_debug_information key alongside cost_breakdown, so the probe leaves no pricing state on the call it reads. * test(caching): cover cache-hit marker on HiddenParams carriers through the caching handler * fix(logging): keep the uncached price probe's restores to the state it can leak * fix(otel): emit V2 LLM-call span for cache hits with explicit cache attributes Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(otel): read cache payload fields defensively without casts Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(otel): clarify pyright suppression reason on cache payload reads Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(otel): build the cache-hit view from typing_extensions.TypedDict so import works on Python 3.10 and 3.11 * fix(otel): report cache hits at zero cost everywhere and mark misses Cache hits now carry a zero cost breakdown and a zero hidden response cost, the /v1/messages hit cost header follows chat and responses hits, every span carries litellm.cache_hit, V2 hit spans drop server.address, an async hit keeps the provider-prefixed model name, and the V2 attribute budget counts preset keys * fix(otel): send a 0 cost header on cache hits and keep hits out of deployment TPM Cache hits now send x-litellm-response-cost: 0.0 on chat, responses and /v1/messages, while a fresh call whose cost is 0 still sends no header. The async hit path stamps the same model name as main again. Stamping the provider-prefixed name made a hit's tokens count toward the deployment's TPM limit, so repeated cached requests hit 429s under usage-based routing. Drop comments that restated fields and annotate new test values as Final. * fix(otel): keep the served pricing basis on a cache hit's cost breakdown A hit's breakdown now keeps service_tier, data_residency, vertex_location, and the discount and margin rates the served call recorded, with every amount at 0, so savings reports still read the basis. The hit header test now drives the live non-streaming header path. * fix(otel): send zero breakdown headers on a cache hit and give hit spans a fresh call's cost keys A hit's x-litellm-response-cost-original, -input, and -output headers now read 0.0 instead of going missing or carrying the full price. A hit's cost breakdown now comes from pricing the response as fresh, so every route exports the same keys, pricing basis, and rates with every amount at 0. * test(integration): assert zero cost and the cache-hit flag on cache-served OTel V1 and V2 spans * test: wait for the cache entry before the cache-hit request and build cost headers without a route_request double * test: annotate the new cache-hit unit test locals with Final --------- Co-authored-by: shrey kharbanda <shreshth@berri.ai> Co-authored-by: jesus <jesus@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-10-17 18:25:32 +00:00
Kerry Lu	3c19b4149b	fix(cost-map): fall back to the bundled map when urlsplit rejects LITELLM_MODEL_COST_MAP_URL (#47133) ... Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-17 17:44:49 +00:00
Mateo Wang	c143954493	fix(streaming): report the deployment's api_base when a stream fails mid-way (#47045) ... * fix(streaming): report the deployment's api_base when a stream fails mid-way * fix(responses): report the deployment's api_base when a native responses stream fails mid-way * fix(streaming): name the deployment's configured api_base in mid-stream errors and keep prompt text out Mid-stream errors on chat and native /v1/responses streams now prefer the router's configured api_base over the logged request URL, websocket turns keep the connection's api_base, and the mid-stream mapping no longer adds the prompt to the debug info. * fix(streaming): keep api_base credentials out of error debug info and leave websocket turn logging unchanged * fix(streaming): name the websocket connection's api_base on turn failures and strip scheme-less userinfo * fix(streaming): strip api_base userinfo before cutting the query so a raw ? or # in a password stays out Adds the audit's integration tests for the mid-stream alert API Base line and the SDK debug info. * fix(streaming): leave the API Base line out when an @ follows the host A raw / ? or # in a password and an @ in a query or path read the same in a malformed api_base, so either guess could show a secret or a wrong host. * fix(streaming): keep the API Base line when an @ sits in a provider path Vertex partner model ids like claude-opus-5-5@default put an @ in the URL path, so the fail-closed rule left out the line main printed. The line is now left out only when the text before the first / ? or # is not a host, and a :// counts as the scheme only after a valid scheme name. * test(streaming): cover a numeric password with a slash in the API Base line The audit found that a password like 1234/function-secret, which looks like a port, had no case. The line is left out on this branch and printed the raw secret on main	2026-10-17 15:41:24 +00:00
yuneng-jiang	a4e0570bea	fix(logging): keep the async request's logging payload when the sync success thread runs late (#47019) ... * fix(logging): keep the async request's logging payload when sync callbacks run late Treat the "cache" success callback as internal when deciding whether to start the sync success thread for async requests. It has no branch in the sync handler, so with `cache: true` that thread did nothing except rebuild and overwrite model_call_details["standard_logging_object"]. When the sync handler does run for an async request (a real sync-only logger is configured), it now builds its own payload and hands it only to its own callbacks. The async handler keeps sole ownership of the shared payload, so edits made by async logging hooks (for example the v3 rate limiter's mirrored x-ratelimit headers that Prometheus reads) are no longer discarded. Sync requests keep their existing behavior. * fix(logging): keep sync cache hits logged and isolate the async-request payload build The sync completion cache-hit path reused handle_sync_success_callbacks_for_async_calls, so treating "cache" as internal silently dropped sync callbacks on sync cache hits. It now submits the sync handler through its own method, as it effectively always did. For async requests the sync handler builds its payload from a copy of the call details, so message redaction cannot rewrite the shared standard_logging_object, and when it builds no payload its callbacks keep the shared one instead of getting None. * test(caching): lock sync cache-hit logging for completion, embedding and text_completion * test(logging): keep sync hook edits off a caller-supplied payload for async requests * fix(logging): give sync hooks a copy of the async payload when the thread builds none * test(logging): check every legacy sync logger gets the thread's own payload * test(logging): cover traceloop and supabase sync logging for async requests	2026-10-17 06:39:35 +00:00
yuneng-jiang	d346d769f0	fix(caching): keep prompt cache usage on streamed cache hits (#47073) ... * fix(caching): keep prompt cache usage on streamed cache hits A stream=true request served from the response cache rebuilt its usage from the prompt, completion and total counts only, so prompt_tokens_details and the cache read and creation counts were dropped on the replayed stream. /v1/messages clients routed to Bedrock Converse saw input_tokens equal to the whole prompt and no cache tokens on a hit. Both replays now build the usage through one helper that also restores prompt_tokens_details and the integer cache read and creation counts, skipping cached values that do not validate. * fix(caching): coerce replayed token counts the way the live usage does The replay accepted only exact ints for the token counts, so an integral float or numeric string in a cached entry became 0 where the previous replay kept it. Counts now go through pydantic int coercion and fall back only when they do not validate.	2026-10-16 23:28:11 -07:00
Mateo Wang	2c5c9b8d84	fix(bedrock): use native structured output on Haiku 5.5 and Sonnet 5.5, and fix Fable 5 and Sonnet 4.6 schema 400s (#46870) ... * fix(bedrock): use native structured output on every Claude model whose Bedrock profiles accept it Bedrock accepts outputConfig structured output on every reachable profile of Claude Opus 4.7, 4.8, 5, 5.5, Sonnet 5, 5.5, Haiku 5.5, and Fable 5.1, so json_schema now goes out natively there instead of as a forced tool, which kept Bedrock from returning adaptive thinking. Fable 5 rejects outputConfig, so its keys go back to the tool path. GovCloud keys keep their flags, and the drift tests let GovCloud lag its commercial base but never lead it. * fix(bedrock): clean Claude schemas for native structured output and keep recursive schemas on the old path Bedrock native output rejects minimum/maximum, minItems, uniqueItems, oneOf, additionalProperties true, and recursive or unresolved $ref, all of which the forced tool accepted. Claude schemas on the Bedrock native paths now go through the cleaner the Anthropic native path already uses, and a schema with a recursive or unresolved $ref keeps the forced tool, inline, or drop path it had. * fix(bedrock): keep older installs on the json tool with a Bedrock-only native output key Older installs fetch the model map from main, so flipping supports_native_structured_output moved them onto native output with their old schema handling. The new supports_bedrock_native_structured_output key is ignored by older code. Schemas native output cannot hold (recursive refs, open objects such as dict fields) keep the json tool on the new key, models on the old key keep their current behavior for those shapes, and the Anthropic API, Vertex AI, and Azure keep their current behavior. * chore(cost-map): regenerate the model prices schema for the Bedrock native output key * fix(bedrock): keep native output to profiles every account accepts and route schemas Bedrock rejects to the json tool Only Opus 5.5, Sonnet 5.5, Haiku 5.5 and Fable 5.1 keep the Bedrock native output key, since Opus 4.8 and Sonnet 5 answer 400 on some accounts and Opus 5 garbles escaped characters. Lookaround patterns and string formats outside Bedrock's list now keep the json tool, objects typed as a union with null are closed, and the cleaner keeps minItems of 0 or 1. * fix(bedrock): keep Opus 5.5 and Fable 5.1 on the json tool, since native output stops their adaptive thinking * fix(bedrock): keep shared $defs in native schemas and send refused schemas to the json tool on every native model Native output now keeps $defs instead of inlining each use, so a submodel reused across a schema counts once against Bedrock's optional and union limits. Schemas native output cannot hold use the json tool on Converse and Invoke chat for both native keys, and minItems is only kept when it is an integer 0 or 1 * fix(bedrock): keep the json tool unless thinking is requested and bound native output schemas The Bedrock native output key now applies only when the call asks for thinking, so calls without thinking keep the json tool as before. Schemas past Bedrock's documented union and optional counts, or past a grammar size estimate fitted to live probes, keep the json tool on both map keys. Open objects keep the json tool on the Anthropic API, Vertex AI and Azure AI, where native output returned them empty. The $ref check no longer expands $defs, so doubling definitions no longer stall the request. * fix(bedrock): resolve root-path $defs refs so nested Pydantic models keep native output on Invoke * test(bedrock): cover native structured output and json tool routing through the proxy Integration cells drive the proxy against a scripted Bedrock peer that enforces Bedrock's structured output schema rules, covering thinking with native output on Converse, Converse streaming, Invoke, /v1/responses and /v1/messages, the deployment opt-in, Fable 5, schema cleaning on every native entry, open objects, and malformed schemas. Vertex, Anthropic and Azure AI cells cover open objects on native-capable models and the cleaner's minItems and nullable object handling. The unit table now covers reasoning_effort none and disabled thinking * fix(bedrock): keep native output for numeric formats and wide old-key schemas, and keep thinking in json mode Check string formats only on nodes that can be strings, apply the 64-field cap only to the Bedrock-only key, carry thinking blocks into the json mode message, and send malformed json tool schemas as object schemas. * fix(anthropic): keep native output for dict fields unless the json tool can be forced * fix(anthropic): keep native output for dict fields when the caller sends tools * test(bedrock): close the dangerous-tool-use test schema, since Bedrock native output requires closed objects * test(anthropic): cover forced and unforced open-object routing, json mode thinking, numeric formats and wide schemas Add proxy cells for open-object schemas that keep native output when the json tool cannot be forced (a model that refuses forced tools on the Anthropic API and Vertex AI, thinking, caller tools), for the thinking block a json mode answer keeps on Vertex AI and Bedrock Invoke, and for integer and number formats and 65-field schemas on each Bedrock map key. Point the forced open-object cells at the Anthropic API and Azure AI only, since no Vertex AI model in the cost map takes both native output and a forced tool * fix(bedrock): keep the native output opt-in on the deployment that sets it, and route effort none open objects to native output * test(bedrock): cover deployment-scoped native output opt-in, register_model and effort none open objects	2026-10-16 20:57:23 -07:00
Kerry Lu	e8550c1454	fix(openai): send chat completions through client.post so the SDK's per-message param transform stops holding the event loop (#46967) ... * fix(openai): send chat completions through client.post so the SDK's per-message param transform stops holding the event loop create() walks every message, content part and tool of the request through openai._utils._transform before posting, 91 ms at 300k tokens and ~300 ms at 1M tokens on the event loop, and returns the same dict for the plain dicts litellm builds. client.post is what create() calls after that walk, same request, headers, retries, raw response and stream objects, so the chat helpers now call it directly through the helper embeddings already used * fix(openai): type the chat client.post result as LegacyAPIResponse so the type gate sees .headers and .parse * fix(openai): assert the chat client.post result is a LegacyAPIResponse instead of casting it * test(openai): stub client.post with a LegacyAPIResponse spec in the empty-response and no-leak tests * test(core-utils): stub client.post with a LegacyAPIResponse spec in the agentic loop leak test * test: every client.post stub on the OpenAI chat path returns a LegacyAPIResponse-spec'd mock --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-16 18:06:01 -07:00
devin-ai-integration[bot]	aa32e4cc88	fix(logging): stop the spend metadata merge from walking a dict the logging thread writes to (#46044)	2026-10-16 17:37:18 -07:00
Mateo Wang	3ef0b35255	fix(bedrock)!: block realtime replay after an input-first start and reject malformed Nova Sonic session settings (#46936) ... * fix(bedrock): block realtime replay after input starts the session and reject non-string instructions and voice * test(bedrock): name the malformed realtime setting test for its string cases * fix(bedrock): replay the opening realtime message until Bedrock accepts the stream and refuse any fallback after commit Also rejects a malformed modalities, input_sample_rate_hertz or tools setting with invalid_type, dropped under drop_params. * fix(bedrock): replay a refused opening message on any fallback and reject OpenAI voices and non-string audio formats * fix(realtime): read the client scope only when the websocket has one and reject any-case OpenAI and empty Bedrock voices * test(bedrock): cover realtime replay, refusal and committed failure through a real proxy Fix the scripted Bedrock peer's port import and the nested tool call cell's stale expected events, so the Nova Sonic integration file collects again	2026-10-17 00:29:50 +00:00
Kerry Lu	40efc6e07e	feat(cost-map): support s3:// URIs for LITELLM_MODEL_COST_MAP_URL (#46972) ... * feat(cost-map): support s3:// URIs for LITELLM_MODEL_COST_MAP_URL * fix(cost-map): handle incomplete S3 ClientError responses * refactor(cost-map): drop S3 retry classification and s3_client argument * test(cost-map): cover non-object remote map fallback --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-10-16 16:00:06 -07:00
yuneng-jiang	0403f8953e	fix(cost): bill bridged /v1/messages Responses replies like native /v1/responses for reasoning tokens and service tier (#46975) ... * fix(cost): price reasoning tokens of /v1/messages bridged onto the Responses API in the cost header and breakdown * fix(cost): record the bridged Responses API result only after the served body is built * fix(cost): keep the served service tier when a bridged Responses reply has no message item	2026-10-16 15:23:11 -07:00
Mateo Wang	d76ec3a47e	fix(proxy)!: answer 400 for malformed tools on count_tokens instead of crashing (#46583) ... * fix(proxy): answer 400 for malformed tools on count_tokens instead of crashing A non-list tools value crashed the vector store lookup during auth and the built-in tool cost lookup in the failure logging path, so the proxy answered an unhandled 500 and closed the keep-alive connection. count_tokens now answers a 400 invalid_request_error for a malformed body, drops malformed tools when drop_params is on, and both lookups skip values of the wrong shape. * fix(proxy): skip non-list tools in the tool allowlist check Also validate the count_tokens body without recursion, which the recursion detector rejects. * test(integration): restore the int tools case on count_tokens The proxy now answers a non-list tools value with a 400, so the case is deterministic again. * fix(proxy): reject malformed tools at the LLM route entry and keep vector store checks on malformed ids * fix(proxy): apply drop_params like core when dropping malformed tools, and reject malformed tool vector store ids Check tools after request setup so the Claude Code default and the logged call type apply, read the request, global, and model group drop_params the way core does, drop tool_choice and friends with tools, cover Gemini generateContent, and answer 400 for a malformed tools[].vector_store_ids with the strict flag off * fix(proxy): keep the request's call type when logging a gate rejection after request setup The body-shape fallback relabeled a /v1/messages rejection as acompletion and a list-input /v1/responses rejection as aembedding, so it now only applies when the logging object carries no known call type * fix(proxy): share the malformed tools check across tool routes and honor drop_params per entry * fix(proxy): accept null vector_store_ids, read every named store id in auth, check the responses websocket * refactor(proxy): leave the responses websocket out of the request-level tool check * fix(proxy): let a request's additional_drop_params replace the deployment list and keep compact's call type on rejections * fix(proxy): read router default drop lists and deployment ids in the malformed tools check * fix(proxy): leave malformed tools to the router when it can pick another deployment Fallbacks, auto-routers, model strings, comma batches and team model names let the router pick a deployment after the proxy checks the request, so the proxy now forwards a malformed tools field there as main does, and only rejects it when the deployment it checks is the one that serves. Token counting never reroutes, so count_tokens and input_tokens keep reading the group they count with. additional_drop_params names are read the way core reads them, so a list with a non-string entry still names its strings. * test(integration): cover malformed tools on reroutable models, router defaults and deployment ids * fix(proxy): resolve malformed tools at the deployment the router picks * fix(proxy): keep provider-repaired tool schemas, honor fallback_on_unsupported_params, skip cooldown on malformed tools Empty schemas and JSON-string schemas pass the tools check the way litellm's provider paths already read them. The rejection is a BadRequestError subclass carrying the deployment's provider, so fallback_on_unsupported_params: false keeps the 400, and the router never cools a deployment down for a request litellm rejected before calling it. Adds the audit's pre_call guardrail and cross-provider bridge cells. * test(integration): expect a 400 for an empty-string tools field on /v1/messages Real Anthropic rejects tools "" with a 400 on main too, so the case joins the malformed tools test * fix(router): keep web search routing for tools passed as a tuple * fix(router): keep a deployment's own tools when drop_params drops a malformed request tools * test(router): list _merged_tools as covered through the deployment tools merge tests * fix(router): drop the request's tool settings with its malformed tools when deployment tools replace them * fix(router): skip a tool whose type is not a string in the web search filter instead of raising TypeError * fix(prometheus): keep deployment health metrics clean on a malformed tools rejection * test: type the new malformed tools tests * test: mark new test locals Final and type kwargs dicts	2026-10-16 14:57:53 -07:00