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94 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
yucheng-berri
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ffbbb6366b
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feat(proxy): add general_settings.fips_mode startup gate (#48600)
* feat(proxy): add LITELLM_FIPS_MODE startup gate With LITELLM_FIPS_MODE=true the proxy refuses to start when TLS verification is off, when Python's OpenSSL does not enforce FIPS, or when the startup password migration fails. A value that is not true/false also refuses. * feat(proxy): refuse FIPS mode when cryptography's OpenSSL is not FIPS The stock cryptography wheel bundles its own non-FIPS OpenSSL, which serves JWT, Fernet and AES-GCM even when Python's OpenSSL enforces FIPS. * fix(proxy): refuse FIPS mode when cryptography's FIPS provider cannot hash The stock cryptography wheel reads the host's FIPS config and reports FIPS on, but its bundled OpenSSL cannot load the host's FIPS provider, so every operation fails. Require a working SHA-256 alongside the FIPS flag. * fix(proxy): refuse TLS verification off anywhere in FIPS mode A model's own ssl_verify: false reached the HTTP client after the startup check passed. get_ssl_verify now raises in FIPS mode whenever verification resolves to off, which also covers the startup check. * refactor(proxy): return FIPS boot refusals as values and harden the FIPS tests * fix(proxy): stop refusing TLS verification off in FIPS mode Skipping certificate verification is a security choice, not a FIPS one: the TLS connection still only uses algorithms the FIPS provider allows. * feat(fips): refuse a database used without FIPS mode, drop the password migration change FIPS mode marks a new database with a fips_mode row in LiteLLM_Config and refuses one that already holds LiteLLM rows without it. Without FIPS mode, the proxy refuses a database carrying the marker. * test(fips): close the database test clients with aclose so the engine stops * feat(fips): read FIPS mode from general_settings.fips_mode instead of LITELLM_FIPS_MODE * refactor(fips): keep fips_mode out of the API-writable general settings, it is read from the config file only * fix(fips): retry the startup marker and state reads once after a dropped connection A dropped connection during the non-FIPS marker read used to count as an unmarked database, so a blip at boot let a non-FIPS proxy start on a FIPS database. Both reads now go through call_with_db_reconnect_retry, the reconnect-and-retry the other startup reads use. A read that still fails keeps its old outcome. * fix(fips): refuse a fips_mode key that has no value fips_mode: os.environ/X with X unset, or a bare fips_mode: / null, resolved to None and started without FIPS mode and without a message, while an empty string refused. A key that is present now has to be a boolean; only a config without the key means off. * refactor(fips): move the database check out of the boot gate The boot gate keeps the setting and the two OpenSSL checks. The check that a database matches the FIPS setting moves to its own PR, so a boot without the flag runs no extra database read. * test(fips): pin how a fips_mode string is read through enforce_fips_mode |
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Emerson Gomes
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ecb8ef5ca8
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feat(realtime)!: support latest OpenAI audio models (#35600)
* feat(realtime): support latest OpenAI audio models * fix(transcription): type SDK stream duration metadata explicitly * fix(realtime): preserve transport settings and translation duration * refactor(realtime): reuse SDK client initialization * fix(audio): bill finalized streams and authorize transcription models * refactor(audio): keep transcription pricing selection together * fix(realtime): reconcile model metadata and test contracts * fix(realtime): preserve provider duration and model capabilities * fix(realtime): keep transcription validation compatible with cost map guard * fix(realtime): address transcription and billing review findings * fix(realtime): preserve input usage and provider routing * fix(realtime): bill retained output and route Azure aliases * fix(realtime): reject malformed provider durations * fix(realtime): preserve batch cache rates and Azure v1 routes * fix(transcription): reject nonfinite provider durations * refactor(realtime): align annotations with current lint rules * fix(realtime): preserve translation deployment pricing and input usage * test(transcription): verify synchronous stream finalization * fix(realtime): retain missing translation input usage at close * fix(transcription): reject streams that bypass output guardrails * fix(realtime): reconcile audio protocols billing and current CI * fix(realtime): trust confirmed formats and authorize default models * fix(realtime): preserve absent models and reject unsupported guardrails * fix(realtime): reject translation policy pipelines * chore(ci): rerun transient infrastructure timing failure * fix(realtime): reconcile audio protocols with current upstream * fix(audio): validate provider responses at SDK boundaries * fix(realtime): preserve minimum OpenAI SDK compatibility * fix(realtime): preserve deferred Live session authorization * fix(realtime): preserve upstream authentication and transcription behavior * fix(audio): scope provider duration precedence to configured models * fix(typing): avoid Final declarations inside transcription cost loop * refactor(audio): reuse transcription mapping and duration resolution * fix(realtime): enforce model budgets and preserve translation routing * fix(audio): log streamed transcripts whose done event reports detected languages * fix(audio): pass stream, languages and keywords through unchecked for non-OpenAI transcription providers Providers without a streaming transcription handler got UnsupportedParamsError for stream=True, languages and keywords, where the merge base forwarded them as provider-specific params. Only openai and azure validate them now. * fix(audio): bill streamed gpt-transcribe from the provider's reported duration The stream path computed cost after logging had replaced the transcription's duration usage, so it fell back to the measured file length while the unstreamed call billed the provider's seconds. * fix(transcription): log streamed transcription usage from the provider response The stream logging path built the spend payload from the response after its duration usage was transformed away, so whisper-1 with stream=true and streamed gpt-transcribe logged an empty usage object. Bill and log from the provider's TranscriptionResponse in both the sync and async paths. * fix(realtime): keep main's routing, protocol and transport behavior around the new translation routes - Send OpenAI realtime and translation client_secrets and calls through litellm's httpx client again, so ssl_verify and custom CA settings apply and upstream errors keep main's shape - Use the input transcription model as the session model only for transcription sessions - Drop the new /openai/v1 translation aliases and record each lazy feature's own routes, so the /openai pass-through and the MCP routes resolve as on main - Let a configured Azure realtime_protocol win for every model, with GA as the default only when none is set - Return x-litellm headers on streamed transcriptions and mark the request done - Refuse translation sessions before connecting upstream when realtime guardrails apply or the provider is not OpenAI or Azure - Accept json and text for gpt-transcribe, and drop other formats under drop_params instead of failing - Bill translation sessions on output audio seconds only, at the single published rate - Document the 201 SDP answer on the translation calls routes and the transcription 200 response * fix(realtime): restore main behavior for guardrails, Azure transcription, and realtime clients Streamed transcription runs unstreamed when a deployment post_call guardrail applies, so the guardrail still sees the transcript. Azure transcription maps v1, latest and preview to the default dated version on the deployments route for every model. The SDK client secret keeps session.model ahead of model, realtime WebSockets connect to api_base again, realtime metadata keeps only guardrails, and managed agents need an explicit transcription model. Reverts the two unrelated streamed Responses error codes and the duplicate cached_tokens_details field, and the gpt-transcribe format check only reads the request provider's cost map entry. * fix(realtime): keep main's transcription, client secret and route behavior where the PR changed it Transcription reaches every provider as on main again, sends stream only when asked, forwards language and languages together, keeps form key order, bills provider seconds only when above zero, honors base_model for the new flags, keeps main's Azure api_version on the proxy path, and streams carry chat's headers, an error event on a mid-stream failure, and a spend row when the stream ends early. Translation cost reads both per-second rates from one source and spend rows carry the billed seconds. Realtime transcription WebSockets keep model in the upstream URL outside OpenAI's hosts, client secrets forward explicit nulls, accept conversation and delay, and answer 400 on a malformed body, the /openai translation paths are back to main, translation refuses only for guardrails realtime sessions run, nested aliases resolve and later session.update models are authorized, translation client secrets run per-model auth, beta clients bridged to GA get beta-shaped session events, and transcription sessions send the deployment model in both shapes. * fix(realtime): address review findings on transcription billing, streaming and realtime auth Per-second pricing replaces token billing only when the priced entry sets no token rates, translation rates fall back per key to the cost map, transcription cache keys include languages and keywords, a stream request a post_call guardrail forces unstreamed comes back as redacted SSE, Azure beta clients are bridged only for GA-only deployments, nested transcription models on the realtime WebSocket are checked against the key, and translation spend carries key and team metadata * fix(azure): pick the GA realtime protocol for deployments whose model_info.base_model is GA-only * fix(realtime): preserve prior merge resolutions after rebase * fix(realtime): enforce translation policies and normalize Azure transcription URLs * fix(cookbook): stop translation once output idles after the upload ends * fix(realtime): bill translation on input audio and drop pre-read stream cost headers Translation spend now uses the input audio seconds the session sent, priced through input_cost_per_second, instead of the translated output duration. A streamed transcription no longer returns cost headers before the stream is read, since the cost is only known after the last event. Also removes an unused realtime guardrail helper. * fix(realtime): drop top-level session nulls, bill dropped transcription streams, and bridge beta response fields Client secret, translation and transcription session bodies drop top-level nulls again, as main did, while nested nulls such as turn_detection still pass through. Transcription client secrets send the deployment model as session.model. A streamed transcription the client drops still runs its success callbacks, and the stream ends with data: [DONE] like OpenAI's. The beta to GA bridge maps max_response_output_tokens, speed and noise reduction, remaps response.create, and drops temperature under drop_params. The Entra token for realtime HTTP routes is fetched off the event loop * test(e2e): cover realtime translation, live transcription, client secrets, and streamed transcription * fix(realtime): close review gaps in translation billing, transcription streams, and Azure GA Bill translation sessions from the deployment's own per-second rates, add per-second prices for Azure gpt-4o transcribe models, keep stream-scoped guardrails seeing the caller's stream flag, map mid-stream transcription errors to LiteLLM exceptions with a [DONE] frame, map GA responses back to the beta shape for bridged beta clients, honor the minting key's guardrail opt-out on translation calls, restore the Azure transcription session URL, and flag GA-only Azure realtime models * fix(realtime): bill a translation rate the deployment omits from the session model * test(e2e): check translated speech is not English instead of exact French wording * fix(realtime): keep main's behavior for non-bridged backends, stream error frames, gateway URLs and Azure transcribe prices Remap beta events to GA only for bridged beta clients and translation sessions, bridge beta clients on GA-pinned Azure deployments, log error-only upstream sessions as failures, flag dated Azure GA realtime models, drop the unpublished Azure per-second transcribe rates, log a mid-stream transcription failure once, keep main's SSE error frame outside transcription, drop unsupported transcription params under drop_params, keep the caller's Azure auth headers, keep a gateway /v1 path, let key opt-outs release string-callback guardrails on translation, and keep the cookbook waiting while a long upload is still sending * fix(realtime): keep the proxy's realtime session gate off translation sessions A key that opts out of a legacy callback guardrail now gets a working translation session, since the transcription-guardrail gate no longer sends a realtime session.update the translation upstream rejects * fix(realtime): keep websocket model limits, bill measured transcription length, route transcription sessions on the allowed model A WebSocket opened without a query model now authorizes as an empty model, transcription cost prefers the measured upload length over the provider's reported seconds, transcription sessions overwrite nested models with the authorized top-level model again, and a non-boolean transcription stream value answers 400 or is dropped under drop_params. * fix(ci): copy the rust bridge extension into the openapi docs gate's base worktree * fix(model-catalog): accept the realtime translation endpoints in the cost map * fix(cookbook): close the translation session and read until session.closed * fix(realtime): treat an empty transcription stream as unset and pass the cost-map guard An empty `stream` form value runs the transcription unstreamed again, as OpenAI does, instead of answering 400. The four translate cost-map entries drop the translation routes from supported_endpoints until the main branch's catalog parser accepts them, and the nested transcription model lookup uses the router registry entry point. * test(proxy): drop the mid-stream error frame pin that main's error shape change replaced * fix(transcription): bill uploaded seconds when a stream fails mid-transcript * fix(proxy): bill uploaded seconds when a streamed transcription breaks mid-stream * fix(audio): keep transcription's positional arguments and redact streamed error details - Move the new languages, keywords and stream options to the end of transcription's parameters, so a prompt or format passed by position keeps its meaning - Redact internal hostnames, paths and tracebacks from a streamed transcription's mid-stream error event, as chat streams already do - Move the CA-bundle check for the realtime HTTP routes, which serves real TLS on loopback, from the unit suite to the SDK integration suite * fix(audio): stream the guarded transcript to SDK callers that asked for a stream * fix(logging): keep a streamed transcript out of callbacks that turned off message logging A streamed transcription's assembled response reached success callbacks with its text intact under turn_off_message_logging or a callback's message_logging=False, because the shared streaming redactor had no transcription branch. It now redacts the text, as the unstreamed call already does * fix(proxy): stream a transcription the deployment streamed when the client sent no stream field --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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zoveki
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704e73d6fe
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fix(cost-map): give the bare gpt-4o, gpt-4o-mini, gpt-4.1 and gpt-4.1-mini aliases their 2027-01-14 shutdown date (#49707)
* fix(cost-map): give the bare gpt-4o, gpt-4o-mini, gpt-4.1 and gpt-4.1-mini aliases their 2027-01-14 shutdown date * fix(proxy): report a deployment's own provider retirement date before the bare model's An Azure deployment declared as model gpt-4o with custom_llm_provider azure, or as azure/<deployment> with base_model gpt-4o, now resolves azure/gpt-4o's date instead of the bare OpenAI row's. The GPT-4 series alias test now reads both cost maps with typed rows * fix(proxy): read Azure's retirement schedule for azure_ai deployments An azure_ai deployment with no azure_ai row of its own now reports the azure/<model> date, and a cost-map row wins over the provider-less copy the router registers under the deployment's key, which carries the bare model's date. * fix(proxy): let custom and registered base_model rows keep their deprecation date Only the copy the router writes at startup, which has no provider and inherits the bare row's date, gives way to a later candidate * fix(proxy): report a pinned snapshot's own earlier deprecation date over its base_model's * fix(proxy): recognize the router's copied cost-map rows by the loaded catalog * fix(proxy): read Azure's schedule for a provider-prefixed azure_ai base_model --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Etienne Chabert
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523b87ec71
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fix(proxy): charge budget windows when the cached key or team expired before the request ended (#47608)
* fix(proxy): charge budget windows when the cached key or team expired before the request ended The post-call spend update reads a key's or team's budget_limits from user_api_key_cache and returned early on a miss, skipping both the window counter increment and the LiteLLM_BudgetWindowSpend row. The cached object expires after user_api_key_cache_ttl (60s by default), so any request that ran longer than that without another request refreshing the entry was counted in the key's lifetime spend but never in its budget windows. With budget reservation disabled nothing else charges the windows, so keys kept running past their window caps On a miss the update now reads budget_limits straight from the key or team row. It does not re-cache the object, since a write from the spend path could race a /key/delete and put a just-deleted key back into the auth cache * test(proxy): assert the budget window fallback never re-caches the key or team * fix(proxy): read a missing key or team row once per cache TTL in the budget window fallback The master key and UI session tokens are logged under names no key row carries, so every one of their requests missed the auth cache and read the database. A missing row is now remembered for the cache TTL in this process only. A failed read is not remembered, and a row that exists is read fresh on every miss so a key update is never served stale. * fix(proxy): skip the budget window row read for a key or team with no windows The fallback remembered only a missing row, so a key or team that exists but holds no budget_limits was read from the database on every request that outlived the key cache. It now remembers both cases under one cache key built in user_api_key_cache.py, for the same TTL as the auth cache * fix(proxy): keep no-window markers in their own cache and clear them when an update adds windows Markers for keys and teams with no budget windows lived in the shared 200-entry auth cache, so a burst of late costs could evict cached teams and users. They now live in a dedicated in-memory cache on UserApiKeyCache, reached by local and broadcast evictions. /key/update and /team/update now evict the marker on every worker, so a late cost after an update charges the windows the update added. * test(proxy): give the spend counter tests the proxy's real key cache and type the window spend helper * fix(proxy): keep a row read that an update outran from restoring the no-window marker * fix(proxy): clear finished no-window reads and evict a marker-shaped user id from both caches * fix(proxy): apply other spend counters before a window row read and let no-window notes follow the key cache settings --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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tessellark
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c720b23238
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feat(proxy)!: honor model_info.max_input_tokens in the Codex catalog for stock models (#49701)
* feat(proxy): honor model_info.max_input_tokens in the Codex catalog for stock models A Codex model catalog entry copied from Codex's stock entry (a stock slug, or an alias whose upstream is one) now takes the max_input_tokens every routable deployment of the group sets as its context_window, capped at the stock entry's max_context_window like Codex's own model_context_window. With nothing set, the stock window stays. * feat(proxy): honor the smallest max_input_tokens a group's deployments set in the Codex catalog A deployment without a limit counts as Codex's own window, so a limit on only some deployments can lower the window but never raise it * fix(proxy): skip a zero or negative max_input_tokens when sizing a Codex catalog window * test(proxy): stub the max_input_tokens group field and type the Codex window tests * fix(proxy): skip a max_input_tokens a saved /model/info response copied from the cost map --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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tavren27
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a4de720144
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fix(count_tokens): count grok-4-1, grok-4.3 and DeepSeek V4.1 tool requests the way their hosts bill them (#49074)
* fix(count_tokens): count grok-4-1, grok-4.3 and DeepSeek V4.1 tool requests like their chat templates Render grok-4-1, grok-4.3 and DeepSeek V4.1 tool schemas the way each chat template does, and add a per-deployment token_count_tool_framing next to token_count_framing for the hidden tool preamble a host bills. The Azure AI Foundry grok-4-1, xAI grok-4.3 and Fireworks DeepSeek V4.1 cost map rows carry the measured framing, overridable in model_info * fix(count_tokens): count Azure grok-4-1 Responses requests with their own framing and use the tool framing in place of the base framing * fix(count_tokens): keep operator framing on tool and Responses counts, frame bridged Responses like chat, follow base_model for tool rendering, count grok tool_choice * fix(token_counter): count Azure Responses strict default, skip false strict and built-in-only tools, per-kind operator framing * fix(token_counter): count an explicit null strict like false on Azure Responses * fix(count_tokens): follow the chat completions bridge flag and Azure's strict default on azure/ deployments Keep Azure grok-4-1 chat tool counts at or over the bill by raising its tool framing to 302 * fix(token_counter): keep strict false for non-grok templates, coerce the bridge flag, frame DeepSeek API counts * fix(proxy): frame Responses counts for the api_base router defaults send inference to * fix(proxy): keep the api_base helper's name so main's /v1/messages count caller resolves --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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zoveki
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33457d3ac9
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fix(proxy): check the model in every OpenAI websocket passthrough frame (#48979)
* test(proxy): cover per-frame model checks and session pricing on the OpenAI websocket passthrough * fix(proxy): check the model in every OpenAI websocket passthrough frame and price the session * fix(proxy): bill each OpenAI websocket turn on its own row and run full auth per frame Each finished turn (completed, incomplete, or failed) now logs its own spend row under the model and access groups that allowed it, so group budgets see spend as turns end instead of at close. Every model a frame names goes through the key's full auth, and a stored prompt reference with no model is refused for a key held to some models. A frame still in flight when the client leaves is recorded before the relay gives up on the send * fix(proxy): keep the stored prompt refusal's first sentence inside the websocket close reason The close reason carries the refusal's first sentence, and the stored prompt sentence ran past the 123 bytes a close frame allows, so it was cut mid-word. The sentence is shorter now and the rest of the explanation stays in the error event. * fix(proxy): bill pipelined websocket turns to their own frame and close the review gaps * fix(proxy): log no extra websocket spend row for frames after the last turn * fix(proxy): price websocket Responses turns by served tier and hosted tools, and bill turns a client walked out of A websocket Responses turn is now priced through the same Responses cost path the HTTP passthrough uses, so a priority-tier answer and a hosted web search cost what they cost over HTTP. When the client leaves mid-answer, the gateway keeps reading the provider's socket until that turn ends, up to 10 minutes, so the turn the provider still bills reaches spend * fix(proxy): bill websocket turns by lane, skip turns OpenAI refuses, and stop frame checks counting the session's own reservation An error event refuses a queued response.create, so the next turn is no longer charged to the refused frame's model. Turns on separate stream_id lanes are charged to the frame that started each one. The frame model gate settles the connect reservation before it re-runs auth, so a key with less budget left than one turn's max cost is no longer refused on its first frame. * fix(proxy): bill each websocket lane cut off at session end on its own row When a client leaves while turns on several stream_id lanes are still running, each unfinished turn now gets its own spend row under the groups and model its own frame asked for, instead of one merged row. Also pins the PR's new single-assigned test variables as Final and swaps datetime.now() in the logging-handler and success-handler fixtures for fixed timestamps. * test(proxy): mark the remaining new websocket test variables Final Builds the logging mocks with model_call_details in the constructor instead of setting it afterwards. * fix(proxy): check every model the realtime URL names before the OpenAI websocket relay connects * fix(proxy): keep reading running answers after a refused websocket frame so they are billed * fix(proxy): bill realtime transcription sessions on the OpenAI websocket passthrough A transcription session names its model only in session.updated under audio.input.transcription, and reports usage on each completed transcription instead of response.done, so its row logged unknown at $0 and a budgeted key never spent. * test(proxy): mark the turn-taking client's delivered list Final * fix(proxy): hold a websocket session's parallel slot until the socket closes Each finished turn logged its spend row under the session's own call id, so the first turn's success callback freed the key's max_parallel_requests slot while the socket was still open, and a key limited to one session could open several at once. The session now claims its slot under its own call id, every turn row logs under a call id of its own, and the slot is released when the session ends, as before Priced turn rows also take their row's call id as their id, so two turns that start in the same instant no longer share a spend log id and drop one row * fix(proxy): bill realtime transcription clips that finish outside an answer A conversation.item.input_audio_transcription.completed frame that arrived after a session's last response.done was never billed, because the session end only owes a row for a turn still running. A clip that completes while no answer is running now logs its own row, and a clip inside a running answer stays in that answer's row Each row also carries the session's latest session.updated frame, since later rows lost the transcription model it names and priced clips against the realtime model. A newer session.updated replaces the older one, so the stale model is never read first It also drops the docstrings this PR had added, since the names already say what each helper does * fix(cost): price a realtime transcription clip at the transcription model the session set A realtime conversation session opens with session.created naming the realtime model and no transcription model, and the client sets the transcription model later in session.update. The cost code took the first session frame and fell back to its session model, so a clip was priced at the realtime model. That model has no per-second rate, so a gpt-transcribe clip cost $0, and a token-billed clip used the realtime model's audio rate instead of the transcription model's. Now the newest session frame that names a transcription model sets the price, and the first session model is only the fallback when no frame names one, as before * fix(cost): price each realtime transcription clip at the model set when it ran A session that changes its transcription model mid-way kept every logged clip on the newest model. Each clip now takes the transcription model from the last session event before it, and falls back to the session's own model * fix(passthrough): keep the session update a buffered clip ran under until its answer is billed A transcription that completes while an answer streams waits in the buffer for that answer's response.done. A session.updated in between used to drop the earlier update, so the clip was priced at the opening configuration. An earlier update now stays while an unbilled clip follows it, and drops at the next update once that clip is billed. * fix(passthrough): keep reading a websocket turn the client left before OpenAI started it A client that sends response.create and hangs up before OpenAI answers with response.created made the walkout checks see no turn in flight, so the gateway closed the provider socket and the turn OpenAI still ran and billed never reached spend. The relay now counts every forwarded create until the provider starts or refuses it, and keeps draining while one is owed * fix(passthrough): settle a websocket turn that ends without its start frame A turn the provider ended without sending response.created first left its create counted as not started, so a client leaving later held the provider socket for the whole walkout drain with nothing left to bill. A turn's end now settles one waiting create when its lane saw no start frame * fix(proxy): refuse unparseable and unroutable websocket frames and hold legacy slots per socket A client frame too deep or too long for the JSON parser closed the provider socket mid-turn, so the turn in flight was never billed. The gate now refuses that frame with an error event and keeps draining the open turn. A stream_id OpenAI rejects comes back as an error that names no lane, which dropped another turn's authorization. The gate now refuses those frames before they reach OpenAI. With the legacy parallel request limiter, each per-turn spend row freed the key's slot while the socket stayed open. Websocket passthrough rows now free nothing, and the socket frees its slot once when it closes. --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Nate Armstrong
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87d91d78b7
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refactor(router): route the router family through RoutingContext and close the outside surface (#49118)
Strategies, pre-call checks, cooldown and fallback helpers, and the auto, complexity and quality sub-routers now take a RoutingContext instead of the Router, and read the router only through registry(), settings(), health() and the context's forwarding methods. Router-free helpers move from router_utils to litellm_core_utils, outside callers of router state switch to entry points, and the surface allowlist shrinks to the endpoint methods plus the entry points |
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Kerry Lu
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298911d61b
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fix(batches): cost an unmanaged gs:// batch through the deployment that created it (#49301)
* fix(batches): cost an unmanaged gs:// batch through the deployment that created it The create now stores the router deployment id as model_id inside the managed object row's file_object JSON and CheckBatchCost reads it before falling back to the first deployment matching the base model in the gs:// path. Rows without the field keep the old lookup * fix(batches): tolerate a non-string or malformed file_object when reading the stored deployment * fix(batches): read the stored creating deployment from the writer, not a lagging read replica * fix(batches): resolve the writer database once so the type gate count does not grow * fix(batches): decode a dict-shaped file_object when reading the stored deployment, accumulate wire samples, annotate test locals --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Mateo Wang
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cbfb1abdb3
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fix(proxy)!: label shared-handler errors the way the route catch-alls do (#39555)
* fix(proxy): name shared-handler errors by the status they answer
handle_exception_on_proxy pinned type=internal_server_error on every
exception it wrapped, so a management route rejecting a caller's own
argument answered {"type":"internal_server_error","code":"400"} and an
SDK branching on the type read its own bad request as a gateway outage.
Derive the type from the status the response actually carries, keeping
a type the exception already names.
* test(proxy): pin a 500 for exceptions whose status is None
* fix(proxy): keep internal_server_error for timeouts and 5xx, redact hosts in shared handler errors
Provider 5xx and timeouts keep internal_server_error so retry loops still retry them,
the shared handler redacts internal hosts from raw exception messages, and /key/list
routes its HTTPException through the shared handler instead of its own copy of the
old label.
* fix(proxy): label shared-handler errors like the chat route, pick the status before the type, redact only gateway failures
* fix(proxy): pass shared-handler error messages through as on main
Redacting timeout and 5xx messages changed what every shared-handler route
returns, which relabeling the error type does not need, so messages go back
to the verbatim text main sends.
* fix(proxy): redact only the status-less failure main never sent
* fix(proxy): answer a generic 500 for a status-less failure and expect auth_error on the /user/new 403
A failure with no status now answers "Internal server error" instead of its own text, since that text can
name a guardrail's private host and pattern redaction misses cluster DNS names and IPv6 addresses. The
/user/new integration test now expects the auth_error type main's route catch-alls give a 403 the proxy raises
* fix(proxy): answer only a 4xx or 5xx carried status and fall back to the route default otherwise
A numeric-string status outside 400 to 599 made /v1/messages, images, rerank and the OpenAI pass-through answer HTTP 200 with an error body or drop the connection, and non-ASCII digits or a 5000-digit string slipped through isdecimal. error_status_code now accepts an int or a three-digit ASCII string in 400 to 599, the range the chat route already enforces
* refactor(proxy): parse a three-digit string status without recursing
|
||
|
tessellark
|
080e643edc
|
fix(proxy): apply new model rows on every worker as soon as they are written (#49034)
* fix(proxy): apply published model rows on every worker before the debounced resync Config sync messages now carry the ids of model rows a create, update, or upsert wrote. Every worker that receives one loads those rows by id right away, including while its debounced full resync is still waiting, so a group added one deployment at a time is complete on every worker as soon as the write returns. Deletes, bulk writes, and messages from older pods carry no ids and keep the full resync path * fix(proxy): load published model rows from the primary under the reconcile lock Read the by-id rows through the writer so a lagging read replica cannot put an old row back, and read them inside MODEL_RECONCILE_LOCK so a concurrent delete or reload stays the last word. Look the ids up in bounded chunks, reload DB credentials only when a row names one this worker lacks, and leave auto-router rows to the debounced full resync. Add an integration test that boots two proxies and needs the peer to fall back to a just-added backup within 4 s. * test(proxy): cover a published model row that names no credential * fix(proxy): keep the unknown model name read-through on the replica and outside the lock Only the by-id load that follows a published write reads the primary inside the reconcile lock. A request for a model name a worker does not know reads through the replica routing before taking the lock again, as on main, so unknown names put no load on the primary and do not wait behind a reload. * fix(proxy): keep access group edits from dropping staying deployments and batch published config ids * fix(proxy): read access group rows from the primary so quick edits are not lost to a lagging replica * fix(proxy): install ordinary rows queued with an auto router and check access group edits before writing A batch of published model ids that held one auto router skipped every row in it, so ordinary rows written at the same moment waited for the full reload. The by-id load now leaves only the auto router rows to that reload. An access group update now reads every deployment from the primary, answers 404 for an unknown group and 400 for an unknown model id or name before it writes anything, then removes the group from the deployments that leave before it adds it to the ones that join, so a failed write leaves the group narrower than asked, never wider. * fix(proxy): write an access group update in one transaction after a fresh read The update now checks model names first, reads every deployment from the primary, and commits every join and leave in one batch right after that read, so a failed write changes nothing and a field another admin set during validation is kept. Other workers hear about the rows only after the commit. * fix(proxy): lock the model rows while an access group update reads and rewrites them * test(proxy): run the model resync tests on the real installer and a real router The by-id resync tests now install rows through ProxyConfig's real installer and credential loader on a real Router, faking only the database, and the config sync test row model is frozen. * fix(proxy): lock only the rows an access group update touches and answer 404 before 400 An access group update locked every model row, so a lock on any unrelated row stalled it for 30 s and then failed it with a 500, and unrelated model edits on other proxies waited behind it. It now takes a per-group advisory lock, locks only the rows that carry the group or that it selects, and reads them again once locked. The group existence check runs before the model name check again, so a missing group answers 404 as on main. * fix(proxy): never wait on a locked row in an access group update The update now takes its row locks with NOWAIT. When another edit holds one of the group's rows, it rolls back, holding nothing, and tries again for about 10 s before answering 409. Holding rows while waiting deadlocked against team deletes and let a concurrent model edit undo the update's change. The per-group lock also moves to the two-key advisory space, apart from team ids. * fix(proxy): retry access group row locks for 30 s with SKIP LOCKED and lock only the rows model_ids select * fix(proxy): take the access group lock with pg_try_advisory_xact_lock and retry while another edit holds it --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
Mateo Wang
|
326f17594e
|
fix(batches): return real batch token counts next to OpenAI's batch usage fields (#47740)
* fix(batches): read OpenAI batch usage into the batch token counts * fix(batches): serve OpenAI's batch usage shape from retrieve and the cost poller * fix(batches): keep the chat usage keys next to OpenAI's batch usage fields Batch usage now carries every chat key it had plus OpenAI's five batch fields with the same counts, so poller-billed batches keep prompt_tokens and cache-write tokens, and older proxies still read the new rows. Usage with missing or null detail counts reads its real input and output counts. * test(batches): check the batch usage counts in the e2e terminal-state test * fix(types): apply nested include and exclude to both batch usage shapes * fix(batches): log no cost for a batch retrieve that is not final yet A retrieve now reads OpenAI's batch usage into the chat counts, so a retrieve that saw the batch completed before its output file arrived priced those counts for the logging callbacks, and the final retrieve priced the whole batch again. A batch that is not final now logs no cost, as it did before. Batch usage dumps also pass exclude_unset and exclude_defaults through to the usage keys. * fix(batches): pass through every usage detail field the provider sends Batch dumps rebuilt input_tokens_details and output_tokens_details from the chat keys, which dropped any detail field past cached_tokens and reasoning_tokens that the merge base passed through. The dump now starts from the provider's stored details and only sets the two counts derived from the chat keys * fix(batches): skip sync loggers on the cost poller's own retrieve and honor exclude_none on provider details * fix(batches): keep sync logger events at $0 on poller-owned retrieves, pass unparsed provider counts through, log batch usage in chat shape * fix(batches): store only chat usage extras on batch spend rows Spend rows for batch retrieves copied OpenAI's batch fields (input_tokens, output_tokens and their details) into metadata.additional_usage_values next to the chat counts they duplicate. Build the row from the batch's chat usage, shared with the logging payload through batch_chat_usage. |
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|
quietjules
|
d302096b5a
|
feat(lite): offer each model group's reasoning efforts in pi, OpenCode and Codex (#48949)
* feat(lite): offer each model group's reasoning efforts in pi, OpenCode and Codex lite pi, lite opencode and lite codex now read supported_reasoning_efforts from /model_group/info and write them into each client's model config. pi gets reasoning and a thinkingLevelMap, OpenCode gets reasoning_options plus one variant per effort, and Codex fallback entries get supported_reasoning_levels with a default level. The proxy-served Codex catalog on /v1/models?client_version= offers the same levels Codex before 0.138.0 fails the whole catalog on an effort it cannot name, so those releases, and an unreadable version, get only the six efforts every release parses. A group with unknown efforts keeps today's output, and a group with none is written as non-reasoning The strength order and nearest_declared_reasoning_effort move to an SDK-free module so the lite CLI, which loads without initializing the SDK, can import the Codex catalog * fix(lite): describe team models by their public name and keep Codex's none default /model_group/info now looks up a team's own deployments when the caller's team serves the requested name, so a team model reports its reasoning levels. Codex fallback entries default to none when the group lists it, and the proxy builds the Codex catalog in a worker thread * fix(lite): round Codex's default level down and describe a team's shared-name model from its own deployments Move the reasoning strength helper to litellm_core_utils so lite and the Codex catalog import it without the SDK or the router, and let make lint-format-check-changed diff the working tree so a staged rename passes. * fix(lite): keep pi's system role on reasoning model groups pi switches its system prompt to the developer role for any model marked reasoning, so an operator's cache_control_injection_points entry for role system stopped matching on Claude groups. lite pi now sets compat.supportsDeveloperRole false on those entries, so pi sends system as it did before. * fix(codex): treat a client_version too long to parse as an old Codex and keep undescribed stock levels A client_version past Python's integer digit limit made the Codex catalog answer 500. It now gets the levels every Codex parses. A stock Codex level with no description validates again, as on base, and lite codex treats undecodable codex --version output as an unknown version * fix(lite): keep REASONING_EFFORT_STRENGTH_ORDER importable from router_utils and skip the Codex sync on undecodable debug models output --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
Nate Armstrong
|
ead221995e
|
refactor(router): move router callers onto the entry points and invert the proxy imports (#48847)
Code outside the router now reaches it only through the entry points (registry, settings, health, select, apply, observe, register_plugin, retire) or the endpoint methods; the outside-member allowlist shrinks from 139 to 45. litellm/router.py no longer imports litellm.proxy: it asks the installed RouterHost (litellm/router_host.py) for vertex pass-through credentials, member auto-router authorization and auto-router prompt compression, and the proxy installs its host on import. Call sites where a model name can be missing keep the old answer instead of reaching an entry point with None. |
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|
Mateo Wang
|
6cdb9959df
|
feat(router): opt in to non-chat deployment filtering (#46257)
* feat(proxy): reject chat routes on models declared non-chat via model_info.supported_endpoints A model whose every deployment sets a non-chat model_info.mode and a supported_endpoints list with no chat endpoint now answers /v1/chat/completions, /v1/messages and /v1/responses with a 400 before any provider call. Models without both fields keep today's behavior. * fix(proxy): let fallbacks answer and cover more chat routes in the non-chat model check The check now steps aside when a request, key, team or router fallback would answer, skips such models in the rate-limit fallback loop, ignores mode and supported_endpoints copied from the cost map by old Admin UI saves, treats a blank mode as unset, and also covers /v1/completions, the Responses WebSocket, Gemini generateContent and /v1beta/interactions * fix(proxy): only step aside for fallbacks that can answer chat, gate the Responses WebSocket after alias resolution, and compare declarations to the loaded catalog * fix(proxy): gate the Responses WebSocket with the router after aliases resolve, and ignore client-set internal fallback flags * fix(proxy): walk fallback groups breadth first and release reservations on a rejected WebSocket Each fallback group is looked up once however often the request repeats it, and a WebSocket closed by the endpoint gate runs the failure hook so rate-limit reservations are released * fix(proxy): walk fallback layers without recursion and gate the compact Responses route The fallback walk now folds one layer at a time, so the recursion check passes, and /v1/responses/compact on a model declared non-chat gets the same 400 as the other chat-shaped routes * fix(proxy): keep chat on rows whose cost map entry serves chat A row that carries the cost map key of an entry that serves chat counts as declaring nothing, so a catalog edit that adds a chat path never turns old Admin UI copies into 400s * fix(proxy): check chat sent to a deployment id or backend model name * fix(proxy): check a model the read-through loads from the database * fix(proxy): step aside for fallbacks the check cannot follow and wildcards that serve a backend name A fallback target with no deployments of its own, a client routing stamp, and a wildcard that does not match the requested backend name no longer turn a working request into a 400 * fix(proxy): ignore a client model_group that is not a string when building rate-limit headers A client metadata.model_group sent as an int or a list crashed the error handler with a 500 once the embedding-only check rejected the call before routing. The header helper now treats a non-string stamp as no model group. Drops the pattern clause in the backend-name lookup, since the group lookup already returns wildcard matches. Adds the third audit round's routing-stamp cells. * fix(proxy): keep a non-string client model_group out of spend rows * fix(proxy): validate standard fallbacks before the typed fallback-group lookup * feat(router): opt in to non-chat deployment filtering * fix(router): skip unresolved local rate-limit fallbacks * fix(router): ignore caller-provided endpoint selector values * fix(router): normalize declared chat endpoint prefixes * test(router): cover preflight error-value behavior * test(router): derive replay metadata defaults from model info * fix(router): preserve fallback aliases and check synchronous text calls * test(routing): rewrite the WebSocket model with a pre-call callback, since main no longer runs guardrails at socket admission * test(routing): keep the endpoint gate's owned proxies on the worker's database * fix(router): keep the endpoint gate on model_info patches that omit it and on same-group stream retries A partial PATCH of model_info reset a stored enforce_supported_endpoints true back to false, because the field defaulted to False and the update merges model_dump(exclude_none=True). The field now defaults to None so an omitted flag keeps the stored value The same-group retry of a stream dropped before content called the provider without the endpoint selection context, so it could land on an enforced embedding-only deployment of the same group. It now runs inside endpoint_selection like every other router attempt * fix(router): probe rate-limit fallbacks through get_routable_deployments so the router surface does not grow Main's router fence lets code outside the router use only listed Router members and router_utils modules. The proxy's fallback probe now calls the listed get_routable_deployments with the request's call type, and the gate's 400 moves to litellm.exceptions as EndpointNotSupportedByModelError. It stays separate from main's UnsupportedEndpointError, which the router retries on the group's other deployments, while the gate refuses the whole group * test(responses): cover the WebSocket error frame for a model that refuses the endpoint * fix(proxy): let the rate-limit fallback probe try a fallback this worker has not loaded yet The probe now skips a fallback only when the endpoint check removed every deployment it has, so a model added on another worker still reaches route_request and its database lookup * fix(proxy): keep key router settings off the Responses WebSocket, read unrooted or single-string endpoint lists, and add status to the refusal frame * fix(router): warn when enforce_supported_endpoints has no usable list and match chat endpoints regardless of case, trailing slash, or Gemini path * test(router): type the load-warning test's caplog and router * test(routing): match the endpoint gate's integration tests to base fallback behavior on unloaded fallbacks and the Responses WebSocket --------- Co-authored-by: Mateo <mateo@Mateos-MBP-2.localdomain> |
||
|
paveln83
|
032342d2b7
|
fix(responses): resume background response streams with stream and starting_after (#48819)
* fix(responses): resume background response streams with stream and starting_after
Retrieving a response with stream=true and starting_after=N now returns the
replayed event stream from OpenAI and Azure instead of one JSON object, on the
SDK (get_responses / aget_responses) and on the proxy's GET /v1/responses/{id}
Providers that cannot replay a stored stream drop the params under drop_params
and raise UnsupportedParamsError without it. Malformed values answer 400 with
the param named. A replay that reaches its terminal event settles the
background response's bill once and passes the provider's usage through
without estimating one. An empty replay (cursor at the end) ends normally
* fix(responses): encrypt replayed stream ids and resume Azure AI Foundry streams
A replayed background stream now gets the same response id encryption as a
created one, so the key that made the response can reuse the id. Azure AI
Foundry deployments resume streams like Azure ones, and the chat-bridged
Responses iterator closes its wrapped stream instead of raising.
* fix(responses): drop malformed resume params under drop_params and keep JSON answers to a streamed retrieve
A bad stream flag drops to a plain retrieve and a bad cursor to a full replay when drop_params is on, and a cursor without stream is ignored even when malformed. A streamed retrieve that the upstream answers with JSON returns the response object instead of an empty stream. get_responses forwards only the include keys from extra_query.
* fix(responses): give proxy stream resumes the deployment stream_timeout and document retrieve query params
* fix(responses): keep deployment stream off retrieves and reject oversized cursors
* fix(responses): keep router default stream off plain retrieves
* test(responses): black box coverage for resume refusals, drop_params, stream timeout and billing
* test(responses): replay a real stream in the billing test and type the fake wrapper chunks
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>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
|
||
|
Mateo Wang
|
65d912fc2e
|
feat(responses): support Codex client tool_search on Anthropic and other bridged providers (#48972)
* feat(responses): support Codex client tool_search on Anthropic and other bridged providers * test(router): cover get_search_tool_support provider defaults and model_info overrides * fix(responses): keep tools loaded by earlier Codex tool searches across previous_response_id * perf(responses): read stored turns once on client tool search continuations * fix(router): avoid OAuth refreshes when listing search capabilities * test(cli): expect disabled search on fallback Codex models |
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|
tavren27
|
cbf4e40d38
|
fix(proxy)!: stop labelling management and health rejections as auth failures (#48739)
* test(proxy): cover management and health routes labelling rejections as auth failures * fix(proxy): name management and health route errors by their status instead of auth_error * fix(proxy): keep auth_error for 401 and 403 and answer database outages with 503 in route catch-alls /key/list and /key/aliases now share the catch-all helper too, so they stop adding the Authentication Error prefix and typing a 400 as internal_server_error * fix(proxy): answer 503 when the database drops mid-query and prisma fails to name the error A real outage surfaces from prisma's query engine as a builtin AttributeError, which the prisma-module check skipped, so the route catch-alls still answered 500 or 400 * fix(proxy): report wrapped and stalled database outages as 503 and label upstream failures by their own status * fix(proxy): answer the upstream status on the catch-all, keep auth_error on tag denials, report model insert outages as 503 * fix(proxy): answer 503 for database failovers and label provider auth errors like chat A database that refuses connections while starting up, shutting down, in recovery, or read-only after a failover now answers 503 no_db_connection instead of 400. A provider's 401 or 403 keeps the type /chat/completions gives it, while a 401 or 403 the proxy raises keeps auth_error. An exception with no message is named by its type. * fix(proxy): scope failover 503s to management route errors and keep a re-raised error's cause * test(proxy): expect the OpenAI error shape from management route refusals Team-not-found 404s now answer invalid_request_error, and every handler-raised refusal answers param null instead of the string None. --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
tessellark
|
5bd47442fb
|
fix(cli): give lite codex aliases of a Codex-known model that model's catalog entry (#48894)
* fix(cli): give lite codex aliases of a Codex-known model that model's catalog entry lite codex built its Codex model catalog from /v1/models ids only, so a proxy alias of a model Codex knows (api-gpt-6-luna for openai/gpt-6-luna) got the fallback entry. That entry has no supports_search_tool or tool_mode, so Codex sent every MCP and app tool inline and each turn cost far more input tokens. lite now reads each listed model's upstream from the proxy's /v1/model/info (team_public_model_name when set, else model_name, first deployment wins) and passes it to the shared catalog builder, the same way the proxy's own Codex route does. If that request fails, the catalog is built as before. * fix(cli): give a lite codex alias an upstream only when all its deployments route to one OpenAI model * fix(cli): cap a lite codex alias's context window at its listed max_input_tokens and count only OpenAI-hosted deployments * fix(cli): keep Codex's tier, upgrade and reasoning defaults off lite codex aliases * fix(cli): keep Codex's own effort, verbosity and promo off lite codex aliases and skip credential-hosted deployments --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
||
|
tessellark
|
a0c9a5993b
|
fix(batches): stop unbillable batches from blocking file deletes and new-batch polling (#48752)
* test(batches): cover the batch cost poller gaps left after #47190 * fix(batches): keep unbillable batches from blocking file deletes and new-batch polling The file delete check now ignores batches past MANAGED_OBJECT_STALENESS_CUTOFF_DAYS, a provider 404 for the output object retires the batch, each poll page takes the arrival lane first, a batch expires only after the poller visits it past the cutoff, and the compare-and-swap matches batch_processed instead of updated_at * test(batches): cover the full arrival page and a failed expiry write in the batch cost poller Old batches still get polled every other cycle while new batches fill the page, old batches that fill a page never push a new batch out after boot, and a failed stale_expired write no longer stops the rest of the page from being polled * fix(batches): share the poll page between old and new batches and hold output files until billed Each lane now gets at least half of the poll page, a lane with nothing left gives its half to the other, and a lane read that resumed mid-lane wraps to the start, so neither old nor new batches can starve the other. The delete guard applies the 7 day cutoff to input files only. Output and error files stay locked until the batch is billed or retired, and stale_expired rows no longer lock anything. Only a lasting provider failure expires a batch past the cutoff, so a timeout or a 5xx no longer gives up on a batch that may still bill. Past the cutoff a lasting failure, a lasting cost-tracking failure, or an output file id that never appeared retires a finished row instead of polling it forever. * fix(batches): retry refused finished batches past 7 days, expire unfinished ones on a failed retrieve A finished batch the provider refuses after 7 days (rotated key, bucket 403, a 404 that does not name the batch) now keeps retrying so its spend is written once the config is fixed, instead of retiring unbilled. A batch the provider still reports running keeps polling. A batch that is not finished in the database becomes stale_expired once a retrieve fails after 7 days, so an unreachable provider is not polled forever. An S3 NoSuchKey for the output object now counts as gone. * fix(batches): expire an unfinished old batch only after 3 failed retrieves in a row * fix(batches): keep retrying an unfinished old batch through timeouts, 429 and 5xx * fix(batches): wait 3 polls before expiring an old batch whose output id lags * fix(batches): match a resource id in a 404 message followed by punctuation * fix(batches): keep refusal and pending-output expiry streaks apart, and void a pending-output retirement on a client write * fix(batches): give up on unsettled batches past twice the staleness cutoff Replace the per-reason refusal and pending-output streaks with one give-up age, and inject a clock into the poller and the delete check so tests pin exact age boundaries * fix(batches): keep polling finished batches past the give-up age so their spend stays recoverable * test(batches): expect a restarted poller's first page to split between old and new batches * test(batches): pin the delete-guard tests to a fixed clock and type a new journal list * test(batches): type the provider helper and the storage 404 cases --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
tessellark
|
43ce3e22aa
|
fix(responses)!: answer 400 before counting a lone Responses built-in tool on Claude (#48798)
* test(responses): audit #47363 Adds integration cells for the input token count paths #47363 changed: the provider id of a managed file and the 403 for another team's file on OpenAI, file_search and additional_tools parity plus cache-mark stripping and untranslatable tools on Claude, and the Bedrock runtime count leaving out the options it refuses. * fix(count-tokens): reject a lone tool with no chat equivalent before the Claude count call A Claude input token count whose only tool was mcp or computer_use_preview skipped the pre-call check and went to the provider, so the caller got the provider error instead of the 400 naming the tool. The check now runs whenever a tool would get a placeholder name. * fix(responses): count a lone Anthropic toolset and name the uncountable tool The lone-tool 400 now fires only for OpenAI Responses built-in tool types, so a nameless Anthropic toolset still counts. The error says LiteLLM cannot count that tool type for the model. Adds a Bedrock unit cell for the lone-tool 400 and pins the runtime wire test's tool shape per request type. * fix(responses): take the uncountable tool types from the OpenAI SDK and keep the region hint off LiteLLM's 400 The Responses built-in tool types now come from openai's ToolParam union, so a type the SDK adds is refused before the count call too. The AWS region hint no longer lands on an error LiteLLM raised before calling the provider. Tests cover two more lone types and the hint. * fix(responses): keep LiteLLM's own list of uncountable tool types and pass a non-string tool type through * fix(responses): count tool_search and namespace tools the way Claude chat inference sends them The count refused a lone tool_search with LiteLLM's 400 and sent a lone namespace raw or squashed it into an empty tool, while Claude chat inference maps tool_search to Anthropic's tool search tool and unpacks a namespace into its function tools. Both now go through the deployment's own map_openai_params, so the count sends what inference sends, and tool_search leaves the list of uncountable types. * fix(bedrock): count a Claude request with its deployment's own chat translation Bedrock invoke and Mantle inference turn a chat tool_search tool into Bedrock's tool search tool, but the Bedrock counter always translated with the Anthropic config, so the count answered 400 for a request inference serves. --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
rj-cairn
|
ff5bf4826d
|
fix(count_tokens)!: audit #47441 and keep the framed estimate for Bedrock count models from the cost map (#48805)
* fix(count_tokens): keep the framed estimate when a region-less token_count_model cannot count (audit #47441) * fix(count_tokens): let framing stand in for a shipped token_count_model, keep a configured one's error The framed local estimate now replaces a 400/404 from any count model the cost map ships, Mantle-pinned rows included, and an admin-set token_count_model keeps its error as the docs say. * fix(count_tokens): warn with the region when framing stands in for a pinned count model Test a Mantle row #47441 pinned in its own region, and keep the region hint check on an admin-set count model. * fix(count_tokens): name the deployment in the framing stand-in warning * fix(count_tokens): let framing stand in when a cost map count model's region denies the account A count model the cost map pins to a region can answer 401 or 403 when the account has not enabled that region or lacks Mantle count access there. With framing set, the estimate now stands in, as it does for 400 and 404. An admin set count model and a count model with no pinned region keep the error. The warning now names the model group, the count model and its region, and says the proxy falls back to the estimate. * test(count_tokens): cover framed 401 and 403 from a shipped count model region on the wire --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
||
|
Mateo Wang
|
ea6dbd2109
|
feat(proxy): log one line per token count call (#47657)
* feat(proxy): log one line per token count call Each count call on /v1/messages/count_tokens, /utils/token_counter, /v1/responses/input_tokens and the Gemini countTokens routes now logs one INFO line with the litellm call id, the requested model, the model the count ran against, the count, the count source and the status code, so it joins the inference call that sends the same x-litellm-call-id * test(google_endpoints): give the count test's fake request a headers list * fix(proxy): keep token count log lines one per call and trusted in JSON logs, and log Bedrock native counts Quote log values that carry whitespace, quotes, equals, or control characters so a model name can't split or forge a line. Let JsonFormatter record extras win over a dict parsed from the message. Log the Bedrock native count-tokens route through the same line. * fix(proxy): escape braces in token count log values, log the Bedrock model AWS counts, and skip the line when there is nothing to count * fix(proxy): log the deployment id the count routed to on every token count line * fix(proxy): log count requests rejected before counting with the status they answer A count route that rejects a request before the shared count function runs now logs the same token count line with its 400. An unsupported content block on the Messages count route becomes its 400 inside the logged wrapper, so its line says 400 instead of 500. A count that ends in a BaseException other than cancellation logs a 500. * fix(proxy): compute the Bedrock counted model id only after a successful count * revert(logging): keep the JSON log formatter's field order as on main The count line already escapes braces in its values, so the formatter never parses a dict from it. Changing the order for every logger is a separate decision. |
||
|
Kerry Lu
|
59b8c73930
|
fix(proxy): abort the request with a 499 when the client disconnects during the body upload (#48640)
* fix(proxy): abort the request with a 499 when the client disconnects during the body upload Co-authored-by: Sinfony8838 <Sinfony8838@users.noreply.github.com> Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): half-uploaded body on chat and vector store routes never reaches the provider Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): close the auth-time OTel server span before aborting a half-uploaded body --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: Sinfony8838 <Sinfony8838@users.noreply.github.com> |
||
|
tin-berri
|
e0d1e64591
|
feat(router): respect caller output budgets in complexity routing (#48632)
Co-authored-by: stuti612 <stutiprasad63@gmail.com> |
||
|
devin-ai-integration[bot]
|
189ab85438
|
fix(bedrock): correct gpt max_input_tokens and add Mantle token counting for claude-opus-5-5 (#48479)
* fix(bedrock): set gpt-6.1-terra max_input_tokens to the 1,050,000 Bedrock card context window * fix(bedrock): set gpt-5.x and gpt-6 max_input_tokens to the card context window minus max output * fix(bedrock): add Mantle token_count_model to bedrock_mantle claude-opus-5-5 rows Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: kerry <kerry@berri.ai> |
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devin-ai-integration[bot]
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9873128b42
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fix(team): keep the team reset schedule when a temp budget increase is set on a member inheriting the team default (#48495)
* fix(team): keep the team reset schedule when a temp budget increase is set on a member inheriting the team default Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): expect the temp-only member row to carry the team default cap Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: joshua <joshua@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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tin-berri
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bc0f598db5
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fix(proxy): validate JSON object bodies before request handling (#48438) | ||
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moe-berri
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72f1ac4a27
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revert(proxy): revert large-integer request parsing (#48289)
Reverts
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Jeevan Babu Gotru
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d3b70c42ed
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fix(proxy): keep JSON integers outside the 64-bit range exact when parsing request bodies (#48213)
Preserve oversized JSON integers in proxy requests and model rewrites Parse large bodies in a worker thread to avoid blocking request handling Fixes #47947 Co-authored-by: Jeevan Babu Gotru <114808955+jeevan1098@users.noreply.github.com> Co-authored-by: moe-berri <moe@berri.ai> |
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devin-ai-integration[bot]
|
24a7bf6af7
|
fix(proxy): reconcile team member total_spend with current cycle spend (#48260)
* fix(proxy): reconcile team member total_spend with current cycle spend Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): read /team/list as a list and drain the scripted provider Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(repositories): compose the membership reset writer and drop SQL text asserts Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test: type the cascade repair test and flatten memberships without a stacked comprehension Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test: keep the reset job test file's existing typing untouched Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: joshua <joshua@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Mateo Wang
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464932b1d1
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refactor(typing): clear 1181 basedpyright Any errors across 431 files (#47789)
* refactor(typing): narrow Any sources across providers, proxy and guardrails (wave 1) * refactor(typing): narrow Any sources across hubs, providers and proxy (wave 2) * refactor(typing): validate RunwayML task JSON and let dotprompt loaders accept exported prompts * fix: restore pass-through behavior on paths the typing pass tightened MCP client IP extraction trusts X-Forwarded-For only when use_x_forwarded_for is True, dotprompt skips a malformed JSON prompt entry instead of raising, RunwayML task payloads pass through unvalidated, and a malformed provider body raises the same AttributeError as before at the CompactifAI, Gemini, and mock transport parse sites * fix(runwayml): keep a malformed 2xx task body on the 500 path * fix(edenai,cli): keep a non-object body in the error and fail on a malformed migration report EdenAI's embedding and image generation parse dropped a non-object body from the error they raised, so the message no longer named what the provider sent. A helper now raises with the body in the message, and both paths have a regression test. `lite encryption migrate` exited 0 with no message when the proxy's report was not an object or its residual_legacy was not a number, where base crashed. It now fails with a message naming the value. The CompactifAI and Gemini image-edit non-object body tests accept TypeError or AttributeError, which both base and this branch raise, so they guard against a ValidationError instead of pinning one class. RunwayML's async parse gets the same non-object body test as the sync one. * fix: keep base's error classes, duck-typed checks and fail-closed guardrails the typing pass changed * test: annotate the new regression tests' locals with Final * test: annotate the remaining new test locals with Final |
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Mateo Wang
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480ee653c5
|
fix(responses): send the billed background response cost to the creating key's and team's loggers (#47506)
* test(responses): the billed background response cost reaches the creating key's and team's loggers * fix(responses): send the billed background response cost to the creating key's and team's loggers * fix(responses): bill an unreadable or rejected creator through proxy loggers, redact and honor disabled callbacks on the billed event * fix(responses): follow the creator's message logging setting on the billed event and read team logging for non-key creators The billed event no longer forces redaction. It follows the creating key's or team's turn_off_message_logging, else the proxy's, and redacts when the creator cannot be read or its settings are rejected. A creator without a virtual key hash bills through its team's settings. function_setup keeps its original callback split, and the billed path uses a separate non-mutating helper. * fix(responses): bill rotated, deleted, and custom auth creators through their own logging and retry failed creator lookups * fix(responses): follow a key's whole grace-period rotation chain to the live key for its billed charge's logging * fix(responses): bill a background response whose creator cannot be read, without the creator's settings * docs(enterprise): say the background response row is claimed before its creator is read * fix(responses): keep the loaded creator rows' budgets and aliases when one creator lookup fails |
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Kerry Lu
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2a268951c4
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fix(proxy): strip caller base_model from spend pricing and reject lone surrogates in multipart metadata (#47639)
* fix(proxy): strip caller base_model from spend pricing and reject lone surrogates in multipart metadata * fix(proxy): type the parsed multipart metadata so basedpyright does not grow reportArgumentType --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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joshua-berri
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6564a490f4
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fix(batches): retry confirmed pre-accounting failures (#47625)
* fix(batches): retry confirmed pre-accounting failures * fix(batches): avoid promising retries for unknown accounting outcomes * test(batches): exercise real spend writer during retry recovery * fix(budgets): charge retried batches once per router budget * test(budgets): cover shared batch charge helpers --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> |
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joshua-berri
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0ede0e10e7
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fix(batch): preserve recoverable costs and prevent poll starvation (#47190)
* fix(batch): preserve recoverable costs and rotate polling pages * test(batch): type retirement failure regression * fix(batch): alternate new arrivals with retry polling * test(batch): defer polling row annotation on Python 3.12 * test(batch): reconcile fixtures with atomic metadata claims * refactor(batch): simplify reconciliation to one bounded scan * fix(batch): restore arrival priority during retry scans * fix(batch): preserve recoverable jobs on unrelated resource errors * fix: revisit recent batches before old retry backlog --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> |
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Mateo Wang
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d776277647
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fix(responses): count billed background responses toward the creator's project and per-model budgets (#47504)
* test(responses): billed background responses count toward the creator's project and model budgets
* fix(responses): carry the creator's project and per-model budgets on the billed background response
* fix(responses): count a key's budget tier toward background per-model budgets
* fix(responses): bill a background response's project only while the key stays on its team
* revert(responses): keep billing the creating key's project after a team move
A key can only keep or detach its project, so the billed project always pairs with the team it was created under. This reverts commit
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Mateo Wang
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dfac770e2b
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feat(proxy): map baggage values to budget tags (#47358)
* feat(proxy): map baggage values to budget tags * fix(proxy): preserve mapped tags in the parsed request cache * fix(proxy): preserve mapper accounting and tag policy * fix(proxy): preserve baggage tags across native transports * fix(proxy): keep mapper rejection and passthrough logging safe * fix(proxy): scope baggage tag mappings to billed inference and keep them out of tag routing Mapped tags now apply only to billed LLM API routes, skipping token counting, model listing, MCP and A2A. They classify spend and budgets but never select deployments unless a key, team or client set the same tag. WebSocket inference returns 403 only while a required rule exists. A tag created with /tag/new resets its spend counter so its budget counts from creation. The General settings editor keeps a new mapping unsaved until every required field is filled in. * fix(proxy): keep client-tag rejection identical with baggage, map A2A calls, skip request previews * fix(proxy): keep mapped tags out of requester metadata, answer 503 on tag lookup errors, map custom pass-through routes, check the key before the WebSocket 403 * fix(proxy): keep caller-sent tags routable, keep mapped tags out of policy and guardrail matching, honor allow_requests_on_db_unavailable, reject control characters in baggage values * test(proxy): cover baggage tag mappings end to end Adds integration cells for request_tag_mappings across chat, messages, responses, A2A and custom pass-through spend, required and budgeted rules, the WebSocket refusal, unbilled routes, reject_clientside_metadata_tags, tag routing and policy isolation, a dropped tag read with and without allow_requests_on_db_unavailable, and the /tag/new spend counter reset * fix(proxy): keep base tag merges for requests that map nothing, accept JSON-string metadata tags, count litellm_metadata caller tags Requests with no mapped baggage now reuse the cached body exactly as before, so header and key tag merges still normalize metadata for routing. The client body copy is made only when a tag maps, and the base merges are mirrored onto it. A request that maps nothing no longer gets a 400 for non-object metadata. caller_tags now counts tags sent in both metadata and litellm_metadata. Optional mappings no longer reject JSON-string metadata tags under reject_clientside_metadata_tags. * fix(router): keep baggage-mapped tags from selecting tag-scoped pre-routing strategies Auto, complexity, adaptive and quality router selection, the consumed-tags stamp and compression policy lookup now read request tags without baggage-mapped tags, unless the caller sent the tag or the key, team or project carries it, matching deployment tag filtering. * feat(proxy): parse baggage headers into request tag mappings * fix(proxy): match plus-sign baggage keys and keep deployment tags in guardrail modes * fix(proxy): keep baggage-mapped tags behind key, team and deployment tags and serve non-object or invalid DB mapping settings like unset Mapped tags are added after the key, team, deployment and caller tags, so a tag-mode guardrail picks the same mode with or without baggage. A non-object metadata field maps like empty metadata, and an invalid request_tag_mappings value loaded from the DB is ignored with an ERROR log instead of failing every request * fix(router): merge deployment tags in linear time and keep malformed client tags as sent under mapped baggage Merge serving deployment tags into the request tags in one pass, so a large client tag list no longer blocks the event loop. Leave a non-list metadata.tags untouched when baggage maps a tag, so the request gets the same answer as without baggage. Add the C17 integration cell for the team tag's guardrail mode under a mapped deployment tag. * test(spend): cover string metadata.tags under mapped baggage * fix(proxy): check mapped tag budgets when metadata.tags is a non-list or holds non-strings Mapped baggage tags are applied again after the header and key tag merges, so a header or key tag that replaces a string metadata.tags no longer hides the mapped tag from the tag budget check. An empty or false metadata.tags is read like a missing one, and a tags list with non-string items is kept as sent with the mapped tags added after it, instead of failing auth with a 401 |
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Mateo Wang
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7b82b2a3c3
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feat(bedrock): route token counts from model metadata (#47441)
* feat(bedrock): route token counts from model metadata * fix(bedrock): keep counting metadata compatible with older proxies |
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Mateo Wang
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424687ce09
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fix(proxy): build the OpenAPI schema off the event loop so a cold /openapi.json no longer stalls the worker (#47352)
* test(proxy): keep answering requests while a cold /openapi.json builds * fix(proxy): build the OpenAPI schema off the event loop so a cold /openapi.json no longer stalls the worker * perf(proxy): reuse the rendered /openapi.json body until the schema changes * fix(proxy): scope the openapi build's pydantic patch to the build The schema build swapped a process-wide pydantic hook, which live requests saw once the build moved to a thread, and overlapping builds could leave it installed. The hook now checks a context variable set only inside the build. The proxy test counts liveliness answers instead of timing them. * test(proxy): hold the cold openapi build on an event instead of pacing on a clock * fix(proxy): serve a replaced app.openapi like FastAPI's own docs route * test(proxy): build the cold-docs test on the proxy module's current app * test(proxy): freeze the model that holds the cold docs build |
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Emerson Gomes
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b690225956
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fix(proxy): resync configuration after Redis reconnect (#43313)
* fix(proxy): resync configuration after Redis reconnect * chore(ci): rerun checks after upstream documentation fix |
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Kerry Lu
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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> |
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Mateo Wang
|
6c4c134f23
|
fix(secret_managers)!: resolve oidc/file and oidc/env refs in admin-configured api_key per request (#47341)
* fix(secret_managers): resolve oidc/file and oidc/env refs in admin-configured api_key per request An api_key set to oidc/file/<path> or oidc/env/<VAR> in a credential_list entry or a deployment's litellm_params was sent upstream as literal text, so every call answered 401. The SDK client wrapper now reads the referenced file or env var on each call and never writes the token back, so a rotated token is used on the next call. The existing server-owned federation gates treat an oidc/ api_key as server-owned by value, so a request body, a non-admin credential or model write, user_config, fallback targets and routing tier params can never carry or name one. Other oidc/ kinds answer 400 * fix(secret_managers): strip only the leading oidc/ from a secret reference A token file under a directory named oidc resolved to the wrong path, because every oidc/ in the reference was removed * fix(auth): refuse oidc/ api_key refs in advisor tools and scope the route gates to them The advisor tool's own api_key now answers a 400 when it holds an oidc/ reference, since its sub-call runs through the client wrapper that resolves one. Stored fallback targets, auto-router tiers and user_config refuse only an oidc/ api_key, inline or through the credential they name, so their workload identity federation handling stays as it was. Provider model discovery for a wildcard deployment resolves the reference before calling the provider. * fix(auth): allow admin oidc api_key on deployment writes, resolve refs on discovery, batch probe and realtime health, refuse client api_base on oidc deployments * fix(utils): resolve oidc api_key refs only from admin-configured sources Mark an oidc/ api_key read from a proxy-level deployment or a stored credential, and resolve only that marked value. Team deployments, prompt templates, nested configs and a direct SDK api_key send the text as written. An unsupported reference kind raises a 401 so the router fails over to the group's next deployment. * fix(utils): send a credential's oidc token only to its own api_base host A stored credential's oidc/ api_key now resolves only for the scheme, host and port of the credential's own api_base or base_url, so a team model or vector store that names the credential with another api_base gets a 401 and that host gets nothing. Saving a team model with an inline oidc/ api_key answers 400, since team rows never resolve one. * fix(proxy): send an admin oidc api_key only to the hosts configured beside it Every admin oidc/ reference now carries the origins of the host params set beside it, checked for api_base, base_url and the Bedrock, S3, SageMaker and deployment_url params. Token counting reads the reference only when it calls the provider, answering 401 when it cannot, and pass-through 401s redact internal paths. * fix(proxy): redact the token path from token count auth errors * test(security): cover token count, Bedrock endpoint, api_base update and pass-through path redaction for oidc api_key refs * fix(proxy): redact the token path from secret reference errors where they are raised * fix(proxy): keep the secret reference's path out of the error a caller sees The 401 for an unreadable oidc api_key or pass-through credential now names only the reference kind and a fixed reason, so a token path under /run/secrets or a custom credential dir never reaches the caller, while the server log keeps the full reference for the operator * fix(secret_managers): strip line breaks from the logged secret reference A reference holding a newline can no longer forge a server log line * fix(secret_managers): label an unknown oidc reference kind instead of echoing it An api_key such as oidc/env_MY_VAR (a typo for oidc/env/MY_VAR) came back in full in the caller's 401 and in the spend log, since the kind was whatever text followed oidc/. A kind get_secret does not know now reads oidc/<unknown kind>. The relative-path hint uses oidc/file//<absolute path>, which the client-message redaction on chat routes leaves whole. * test(health): run the real model auth check in the oidc test connection test * test(secret_managers): read an oidc/file token stored under a directory named oidc * fix(secret_managers): count a URL in the model name as an upstream host for oidc api_key references A huggingface/* wildcard call could name its own endpoint URL as the model and receive the resolved token. The origin check now treats a URL in the model as a host the reference must allow. The integration contract also reads the proxy's own database instead of the pytest worker's. * fix(secret_managers): treat a default port as explicit when matching an oidc api_key origin A credential on https://api.mistral.ai refused a call to https://api.mistral.ai:443, though both reach the same server. The origin check now compares scheme, host and effective port, as assert_same_origin does, and an unparseable api_base is refused instead of raising. The advisor test sets the real proxy flag instead of replacing our own helpers. * test: type the oidc request-body helpers and drive the tier test through mock_response * fix(secret_managers): refuse an oidc api_key reference whose call drops the configured host |
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joshua-berri
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9c958aff34
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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> |
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Mateo Wang
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75faaeab64
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feat(count_tokens)!: configurable token_count_framing and token_count_model, count source in the response (#46777)
* feat(count_tokens): configurable token_count_framing and token_count_fallback_model, count source in the response
Count endpoints now say where each number came from in litellm_count_source
(provider, fallback_model, local_estimate) and name the fallback model in
litellm_count_fallback_model. When the provider answers 400 or 404 for a model
it cannot count, the proxy counts the same request with token_count_fallback_model.
token_count_framing adds a per-model constant to local estimates. Both settings
ship in the cost map for Bedrock Claude Sonnet/Haiku 5.5, Bedrock Kimi K3, and
Databricks Kimi K3 and DeepSeek V4 Flash, and can be overridden in model_info.
* test(count_tokens): classify the new cost map keys in the schema generator and expect count_source in exact-shape tests
* test(count_tokens): e2e matrix against real inference and integration wire tests for count source, fallback and framing
* fix(count_tokens): keep the provider error when local counting is disabled, name the fallback error, keep settings in cooldown
Moves the cost map lookup off the event loop
* ci(cost map): bound token_count_framing to non-negative and token_count_fallback_model to non-empty
* fix(count_tokens): keep a failed fallback's own status, ship fallbacks only where they count, add system.ai framing
A fallback model that answers 404 returns the requested model's error unchanged, and any other fallback
failure answers with its own status and message. The eu, apac, au and jp Sonnet and Haiku 5.5 entries
no longer ship the Opus 5.5 fallback, which AWS serves only in us-east-1. A configured empty
token_count_fallback_model turns the shipped fallback off. Config framing accepts whole-number floats and
rejects negatives. The Databricks system.ai Kimi K3 and DeepSeek V4 Flash names carry the same framing as
their serving endpoint names, and the e2e matrix runs on Bedrock Haiku 5.5 too.
* test(databricks): list the system.ai Kimi K3 and DeepSeek V4 Flash names with their published DBU rates
* fix(count_tokens): skip a token count fallback model for an hour after it answers 404 on that deployment
A us. or global. Sonnet 5.5 deployment outside us-east-1 paid two extra Bedrock
calls and about 200 ms on every count, since Opus 5.5 cannot count there either.
The Kimi K3 e2e also runs the large system prompt shape now.
* test(count_tokens): use the shared integration port allocator in the fallback wire test
* fix(cost map): keep the Databricks system.ai entries to framing only, so their spend stays as today
* test(count_tokens): cover the fallback 404 skip, inference profile base_model, shipped framing, and deployment-scoped token count settings
Adds integration cells for a fallback model that answers 404, an application inference profile ARN deployment whose base_model carries the shipped fallback, and the shipped Kimi K3 framing with token_count_framing 0 turning it off. Adds unit tests that keep token count settings off the shared backend cost map key and that store a token count setting on PATCH only when the operator changed it
* fix(count_tokens): keep the counter's own 400 and the provider's error when a framed estimate cannot read the body
A 400 the OpenAI or Gemini counter returns before calling the provider is the caller's answer, so it no longer tries the fallback model or a framed estimate. When the framed local estimate cannot read a content block, the client gets the provider's error instead of a 500. Adds /audit round 2's integration tests for the fallback leg's converted body, the Anthropic envelope on fallback failures, and both framing cases.
* fix(count_tokens): answer the provider's error whenever a framed estimate raises
A tool schema the local estimate cannot format, such as a boolean subschema or an array with no items, raised AttributeError or KeyError and answered a 500 on a framed deployment whose provider had already answered 400. Any estimate failure now answers the provider's own error.
* fix(count_tokens): load the custom tokenizer inside the guarded framed estimate
A framed deployment whose custom_tokenizer could not load answered a 500 or 503 where the provider had already answered 400, because the tokenizer was selected outside the estimate's error handling. Selecting it inside answers the provider's error, logs a warning with the estimate's error, and still raises the Rust extension's fork-guard errors.
* fix(count_tokens): look up framing under the deployment's custom_llm_provider
* fix(count_tokens): share one tokenizer download per worker and bound the wait after a provider error
A framed deployment whose custom_tokenizer is not cached locally made every
count wait out the Hugging Face hub's whole retry cycle when the hub could not
be reached, and a burst of those loads held the default thread limiter that
every count's cost map lookup also needs. Counts on a worker now share one
download per minute, a failed download is reused for the rest of that minute,
and after a provider error a count waits at most 5 s before answering the
provider's error. The swallowed-estimate warning logs only the error type.
* fix(count_tokens): keep one tokenizer download per key running and load the local route per request
* test(count_tokens): type the scripted counter and wait on events instead of wall time where possible
* fix(count_tokens): run framed tokenizer loads on their own capped threads and answer a tokenizer panic with the provider error
Framed loads used anyio's default 40 threads, so a hub that drops packets let about 40 hanging loads stall every count on the worker. Loads now run on a per-worker pool of 4, and a count that finds 4 loads running answers the provider's error at once. Any finished load is reused for a minute after it finishes, so a load that fell back to tiktoken is not retried on every count. A pyo3 PanicException from the tokenizer, while loading or counting, now answers the provider's error instead of a plain 500
* feat(proxy): count tokens with token_count_model in its pinned region
token_count_model {model, region} replaces token_count_fallback_model. Bedrock Sonnet and Haiku 5.5 count with Opus 5.5 in us-east-1, or Melbourne for au. profiles, and a failure names the region to enable
* fix(count_tokens): use the renamed count model constant in the e2e test and list token_count_model with the object keys
* fix(proxy): keep the upstream error envelope when adding the region hint
* test(proxy): annotate the token count setting echo test
* ci(cost map): require non-blank token_count_model strings and test the region rules
* fix(count_tokens): answer the token_count_model's error even when framing is set
* fix(count_tokens): keep the provider error for Google contents instead of a framed estimate
* fix(count_tokens): estimate Google contents the route translated to messages
* fix(count_tokens): keep the provider error for Google contents with non-text parts
* test(proxy): drive tokenizer wait and cost map tests by events and a skippable loop clock
* fix(count_tokens): check Google text-only parts without a KeysView comparison basedpyright flags
* feat(proxy): count Bedrock Kimi K3 tokens exactly with its pinned tokenizer
* test(bedrock): keep the Kimi K3 image check in-process
* fix(count_tokens): join the region hint to an upstream message that already ends with a period
Also pins that a blank token_count_model in config falls through to the cost map default
* fix(count_tokens): count Gemini tool-call turns and Responses tools, and stop tokenizer retries from stalling counts
The Google countTokens route estimates contents with functionCall, functionResponse and thoughtSignature parts again, and still answers the provider error for media, thought and unknown parts
The Kimi K3 exact count renders Responses API and Anthropic tools through the chat tool translation the Vertex count already used, now shared from the prompt factory, and falls back to the estimate when the Converse body cannot carry a tool
A failed Kimi K3 tokenizer load is retried in the background without making counts wait, and a load still running after the wait logs a warning
* fix(count_tokens): count Kimi K3 tools the way Bedrock inference sends them
A flat Responses API function or custom tool becomes the chat tool the
Responses route sends to inference, and every other tool goes to the
Converse body as is, so hosted tools Bedrock drops are left out of the
count instead of being counted or turning it into an estimate.
* test(count_tokens): annotate new token counter test locals with Final
* fix(count_tokens): keep shipped count regions inside the deployment's geography
A plain Bedrock Sonnet or Haiku 5.5 deployment in a non-US region no longer sends its count prompt to us-east-1. Global count models and configured token_count_model keep their pinned region. Also expect litellm_count_source in the Vertex Llama count test main added
* fix(count_tokens): resolve count settings off the event loop
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joshua-berri
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3fb95c8fe3
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fix(batches): preserve spend across malformed output and metadata failures (#47184)
* fix(batches): preserve recoverable spend and terminal reconciliation state * fix(batches): narrow validated envelope types * fix(batches): serialize stored metadata when releasing claims * fix(batches): sanitize metadata before claiming completed batches * refactor(batches): expose existing metadata serializer for shared use --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> |
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joshua-berri
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4143e0869e
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fix(batches): handle empty models when logging batch cost (#47155)
Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> |
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Kerry Lu
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0a051efba7
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test(e2e): event_loop_stalls perf case fails on a gateway event-loop hold over 100 ms that is not on its allowlist (#46974)
* test(e2e): event_loop_stalls perf case reads the gateway's asyncio debug log and fails on a loop hold over 100 ms that is not on its allowlist The gateway runs the stdlib loop in debug mode (new LITELLM_EVENT_LOOP=asyncio knob next to PYTHONASYNCIODEBUG=1), the case replays the mixed body mix at 1 rps and groups asyncio's 'Executing <Task ...> took X seconds' lines by coroutine and location. Known holds are listed with the count they show today; anything else, or a known one past its count, fails the case. Opt-in through E2E_PERF_EVENT_LOOP=1 so the nightly build skips it * test(e2e): event_loop_stalls reads the pod list and pod logs through e2e_http instead of a raw httpx client * test(e2e): event_loop_stalls charges a hold to garbage collection when the gateway's debug-mode gc log accounts for it The proxy registers a gc.callbacks hook only when the event loop runs in debug mode and logs every collection over the loop's slow-callback threshold (generation, collected count, seconds). The case parser pairs such a pass with the hold line that follows it and reports the hold under a bounded garbage collection bucket instead of the task asyncio happened to blame, which made 7 of 10 local runs fail on a different task name each time. Holds the collector does not account for keep the strict allowlist, which gains the prisma first-query warm-up and the second pub/sub subscriber * test(e2e): event_loop_stalls allowlist caps set at twice the ten-run maximum --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Kerry Lu
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081cfa2a62
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fix(proxy): reset end-user spend in committed pages so the budget cascade survives a large LiteLLM_EndUserTable (#46502)
* fix(proxy): reset end-user spend in committed pages so the budget cascade survives large LiteLLM_EndUserTable Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(proxy): collapse _enduser_ids_by_tier return to one line for ruff format Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): mark the end-user page IN list as bounded for the unbounded-IN check Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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rameswaran-mohan
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e65e5abc4e
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feat(proxy): name the successor model for deprecating deployments (#41670)
* feat(proxy): name the successor model for deprecating deployments * chore(ui): add successor_model to the generated deprecation api types * fix(proxy): keep the cost map successor when a deployment overrides only the date * fix(proxy): read the cost map successor from metadata.successor The cost map schema rejects a top-level successor_model key, and curated entries already carry the successor under metadata.successor. Read that key, and look it up even when the cost map entry has no deprecation date, so a deployment that sets only its own date still names the successor. * fix(proxy): keep the first deployment when deduping, let a blank successor hide the cost map one, and name a served successor by its model group * fix(proxy): name only the deployment's own successor_model, since cost map successors are LiteLLM ids rather than served model names * fix(proxy): leave out a successor_model the deployment's callers cannot call, with a warning * fix(proxy): report successor_model as the admin set it and only warn when no model matches it --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |