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54699 commits
| Author | SHA1 | Message | Date | |
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yuneng-jiang
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53ef63145b
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test(ui): wait for the logout navigation before checking the session is gone (#47008) | ||
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yuneng-jiang
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e9a8581a02
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test(e2e): fix MCP tool search hit matching and the retired Bedrock image model (#46998)
* test(e2e): compare parsed MCP tool search hit names instead of raw text * test(e2e): move Bedrock image generation off the retired Nova Canvas model |
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yuneng-jiang
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910c30381b
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test(integration): fix seven CircleCI integration tests that race or assume a worker spread (#47001)
* test(integration): expect the tool search call replayed beside the function call for Anthropic targets * test(integration): wait for the team spend flush before killing a worker * test(integration): poll for the S3 attempt the batch sinks write concurrently * test(integration): queue the terminal object and its sibling into the same s3_v2 flush * test(integration): time the long Bedrock version against an equally long unversioned name * test(integration): pin each half of a burst to one worker instead of hoping the kernel spreads it * test(integration): assert parsed SSE events for live pings instead of transport chunk boundaries |
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berriai-litellm-provider-info-sync[bot]
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b6ca57b36d
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fix(bedrock): set supports_none_reasoning_effort on gpt-6-sol and gpt-6-luna (#47000)
Price-Sync: litellm-providers Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> |
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ryan-crabbe-berri
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cc24e7cfa4
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refactor(ui): validate model edit prices in the zod schema (#46978)
Each price field now parses its per 1M text into a per token number or null inside the schema, so the save handler gets clean values and the hand-rolled conversion goes away. Negative or non-numeric prices now show a field error instead of being saved |
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Mateo Wang
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b39eadcb82
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feat(openai)!: honor per-deployment workload identity on non-chat routes (#39966)
* feat(anthropic): workload identity federation and pluggable identity sources Backend half of #38818 (internal copy of the fork PR #38013), rebuilt as one commit on top of litellm_internal_staging without the dashboard changes. Deployments on anthropic/ without a static api_key can exchange an OIDC workload assertion for a short-lived sk-ant-oat01 token through a shared RFC 7523 JWT-bearer engine. The assertion comes from a mounted token file, an env token, a LiteLLM-signed issuer, or Keycloak, chosen per deployment, per named credential, or through ANTHROPIC_IDENTITY_SOURCE. The federation fields are server-owned: refused inline in request bodies and on POST /model/new, proxy-admin only on credentials, and the token exchange is pinned to api.anthropic.com unless LITELLM_ANTHROPIC_WIF_ALLOWED_HOSTS adds a host. GET /credentials/{name}/jwks exports the public key set of a LiteLLM-signed credential for the Claude Console. The OpenAI federation trio from #39613 rides along on the backend side with the same server-owned handling. Fixes #28607 Resolves LIT-6107 Co-authored-by: derhornspieler <15236687+derhornspieler@users.noreply.github.com> * fix(anthropic): let batch-result downloads mint from deployment params and accept host:port allowlist entries The files handler enabled workload identity on batch-result downloads but never received the deployment's litellm_params, so a deployment authenticating through a named credential could only mint from process-wide env vars. It now threads litellm_params through to the auth header the way the batch retrieve path already does. LITELLM_ANTHROPIC_WIF_ALLOWED_HOSTS entries written as host:port were read by urlsplit as a scheme, so the allowlist kept the raw entry while the exchange compared bare hostnames and refused the gateway. Entries are now parsed as network locations whether or not they carry a scheme. * fix(types): move the WIF kwargs key sets to a leaf module so the kwargs funnel imports without a cycle * test(anthropic): pin case-insensitive matching of WIF exchange-host allowlist entries * fix(anthropic): end workload identity federation errors without a period so the router suffix reads cleanly * fix(proxy): decrypt stored litellm_params before the WIF write gate * fix(proxy): hide WIF secret references from /health output * fix(proxy): keep the proxy error shape on credential endpoint refusals * fix(proxy): hide identity token file paths from /health output * feat(openai): honor per-deployment workload identity on non-chat routes Image generation, audio speech and transcription, moderation, text completions, files, batches, and fine-tuning built their OpenAI client from the env vars alone, so a keyless deployment carrying openai_identity_provider_id, openai_service_account_id, and openai_identity_token_file failed with the api_key error on every route other than chat, Responses, and embeddings. Those handlers now build their client through the shared workload identity resolver, and the managed batch file-access credential extraction keeps the trio * fix(openai): cache workload identity clients and let deployment identity outrank process-wide keys Non-chat handlers built a fresh SDK client per call, so files, batches, fine-tuning, text completion and sync moderation exchanged the OIDC token on every request. The builders now reuse the cached workload identity client per identity, base, timeout, retries and organization; static-key clients are still built fresh. A process-wide OPENAI_API_KEY (or litellm.api_key / litellm.openai_key) no longer silently overrides a deployment's openai_identity_* params. An explicit distinct api_key on the deployment or call still wins. * fix(openai): keep shared workload identity clients on the process http session The workload identity client is cached and shared across requests, so it must never borrow the transport a single caller passed in. Static-key clients keep using the caller's http client; federated clients always ride the process-wide session. Also makes the http client helpers on BaseOpenAILLM public since the builder now needs them from outside the class. * test(openai): pin partial deployment identity beating the process key * test(openai): type the managed-object invoke callback * fix(anthropic): rename the federation workspace param so Bedrock's anthropic_workspace_id keeps working The Bedrock Claude Platform route already reads anthropic_workspace_id from optional_params, so banning that spelling as a server-owned federation parameter broke a pre-existing client capability. The federation field is now anthropic_federation_workspace_id (env ANTHROPIC_FEDERATION_WORKSPACE_ID), which restores the base branch's behavior for Bedrock callers, drops the Bedrock-specific hint from the refusal message, and deletes the unconditional ban constant that no longer had a reader * fix(auth): share one exchanged token across workers reading the same assertion Anthropic accepts each identity assertion exactly once, so two uvicorn workers reading the same token file both minting from it means the second exchange is denied with jti_reused. Minted tokens now land in a per-user 0700 cache directory guarded by a file lock, so workers on the same host reuse one exchange until the token expires or the assertion rotates. A 401 is only retried when the re-read assertion actually differs, and the denial hint explains jti_reused. LITELLM_TOKEN_EXCHANGE_CACHE_DIR moves the cache and an empty value disables it * feat(openai): honor deployment workload identity on image edits, vector stores, containers, videos, and evals The httpx-based OpenAI handlers built their Authorization header from the deployment api_key or OPENAI_API_KEY alone, so a keyless deployment carrying openai_identity_provider_id, openai_service_account_id, and openai_identity_token_file sent "Bearer None". They now resolve the bearer through resolve_openai_bearer_token, which exchanges the deployment's identity token the same way the SDK-based routes do. A deployment that carries only part of the identity trio now raises a 500 naming the missing field instead of silently falling back to the process key, and the SDK client builders take a factory for the static-key http client so the federated branch never touches litellm.client_session. * fix: keep anthropic federation from being shadowed or leaked An empty or whitespace-only ANTHROPIC_API_KEY counted as set, so a federated deployment sent an empty x-api-key on every call instead of minting a token. Blank values now read as unset, and a real static key on a federated deployment logs once that it outranks federation and nothing is being federated. The exchange-host allowlist matched hostnames only, so a second process on another port of an allowed host was trusted with the workload's identity token. An entry that names a port now trusts that port alone, while a bare host still trusts every port. The shared token store exists so the workers reading one projected token file do not each spend its single-use jti. A source that mints its own assertion per exchange shares nothing with another worker, so it no longer writes a live token to disk for a lookup that can never hit. * feat(openai): resolve per-deployment workload identity for the assistants routes OpenAIAssistantsAPI built its OpenAI and AsyncOpenAI clients from a locals() scrape, so a deployment carrying openai_identity_provider_id, openai_service_account_id and openai_identity_token_file never exchanged a token. Thread litellm_params through the class and build both clients with the shared workload identity builders. * fix: unlink a staged token file a failed write leaves behind The 401 denial hint now also says federation ignores ANTHROPIC_WORKSPACE_ID, which the Bedrock Claude platform provider already reads. * refactor: move anthropic jwks derivation behind a provider-owned tagged union * feat(openai): resolve per-deployment workload identity for image variations Build the image variations client through the shared workload identity builders instead of scraping locals(), and give the async path the async http session it was missing. Let a federation trio serve the model-less batch fallback, and hold the standard LRU size of exchanged tokens. * fix: unlink the staged token file when its write fails at close A buffered write only reaches the disk when the handle closes, so a full disk surfaces at close and left the staging file behind holding a usable token. * fix(anthropic): close the staging descriptor before writing the shared token file * fix(wif): judge federation writes by what they set, not what is stored The admin gate read the stored deployment, so a team admin lost edit, delete and Test Connection on any deployment carrying federation params. It now returns early unless the submitted fields touch the federation surface, and a Test Connection probe that points the deployment at its own api_base is still refused, with the 403 no longer wrapped into a 500 The rest of the same review pass: POST /model/new refuses only a blocking value of `blocked`, so a client that always sends `blocked: false` is not turned away; a request body can no longer pick which federated identity to mint as by naming a stored credential; an advisory refresh the executor refuses disarms the entry instead of wedging the identity until the follower timeout; the static-key shadow warning resolves its env fallback inside the cache instead of once per request; credential writes drop nulls before storing them; the token exchange validates the endpoint URL before reading an assertion and keeps refusing redirects across a client heal; /health hides every server-owned federation field from non-admins; and the async create_file and create_batch paths say which setting is missing when the provider resolves no URL * style(tests): keep two blank lines before the batch_cost_is_final block * test(batches): type the workload identity fallback test fixtures * fix(moderation): stop validating unrelated kwargs on the sync workload identity path * fix(auth): refuse server-owned workload identity keys in array form and inside a client router config * fix(openai): keep a deployment's own key ahead of workload identity on every route Thread the caller's own api_key into the identity resolver for embedding, transcription, moderation, image generation, and assistants so a deployment key equal to the process key still wins. A partial identity trio now falls back to a configured static key, unset max_retries keeps the SDK default, and /v1/decisions plus OpenAI count_tokens resolve the exchanged bearer for identity-only deployments * fix(containers): pass deployment params to container file auth headers Container file routes built their auth headers without the deployment's litellm_params, so a keyless deployment with an OpenAI workload identity sent Bearer None on upload, list, retrieve, delete and content calls * fix(openai): keep process-wide key precedence and move token exchange off the event loop Restore the merge base order where an explicit or process-wide OpenAI key wins over federation, so exporting OPENAI_API_KEY keeps working the way it did before. Run the header-building validate_environment calls (image edit, videos, containers, vector stores, vector store files) and the decisions and System One request preparation in a worker thread, so a slow token exchange no longer stalls the loop. Federate realtime websocket sessions, live sessions, realtime client secrets and transcription sessions, and the OpenAI moderation guardrail when no key is set. * fix(openai): answer 401 for a partial identity trio and federate realtime health checks A deployment with part of the workload identity trio and no static key now fails as an auth error naming the missing params, so the router does not retry it as a server error. The realtime health check sends the exchanged bearer for a keyless federated OpenAI deployment, and API token counting reads the same static keys as every other route before minting. * fix(openai): keep local token counting without an identity trio and federate the moderation guardrail from its own config * fix(openai): skip a partial-trio moderation guardrail and let vault keys win in token counting * test(integration): refuse caller-chosen identity params in user_config and bracketed form keys * fix(openai): send the honored secret manager key from SDK client builders A deployment whose OPENAI_API_KEY lives only in the secret manager now sends that key on image, assistants, files, batches, and other SDK-built routes instead of failing with no api_key, matching what the workload identity resolver already treats as a static key * test(openai): check the token exchange runs off the event loop instead of timing the loop --------- Co-authored-by: derhornspieler <15236687+derhornspieler@users.noreply.github.com> |
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ryan-crabbe-berri
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9cf09c18fe
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fix(providers): route Azure Responses past dated api versions, count Grok reasoning tokens on azure_ai, refresh provider sets after register_model, fix gpt-6.1-sol Azure rows (#46377)
* fix(azure): add responses_api_version so the Responses route stops using the deployment chat api_version * fix(azure_ai): fold Grok reasoning tokens into completion_tokens like the xai provider * fix(utils): refresh provider model sets after register_model * fix(cost-map): align azure gpt-6.1-sol reasoning effort flags with the openai row * test(e2e): cover Azure Responses on a deployment pinned to a dated chat api_version * fix(utils): keep router deployment ids out of provider model sets register_model now refreshes the provider sets, so the per-request and router registrations keyed by a deployment id put those opaque ids into wildcard model listings. Those callers now pass add_to_provider_model_sets=False. * fix(azure): carry responses_api_version through the chat to Responses bridge completion() dropped responses_api_version from the litellm_params it hands the Responses bridge, so azure/responses/<model> on a dated chat api_version still built the 404ing /openai/responses URL. Also cover the auto-router marker never forwarding the new param. * fix(azure): stop listing a wrong set of reasoning efforts when none is rejected The message said only low, medium and high are supported, which is wrong for models that also take xhigh such as gpt-6.1-sol. * test(azure): use the latest grok and gpt-5.4 rows in the new azure tests * fix(proxy): list each wildcard-expanded model once A provider set can hold a model both bare and provider-prefixed, which now happens after any priced request registers its openai/<model> key, so the openai/* listing showed that model twice. * fix(azure): route Responses past dated GA api_versions by default A deployment pinned to a dated GA api_version such as 2024-10-21 for chat now sends Responses calls (create, get, delete, cancel, input_items and the azure/responses/ bridge) to the default Responses version, because those dated versions have no Responses route on Azure and 404. responses_api_version still overrides it, -preview, v1, latest and preview versions are kept, an api-version in the api_base query still wins, and chat keeps api_version as before * chore(azure_ai): mark the grok chunk_parser dict as an override contract * fix(azure): rewrite only the route's /openai segment when moving a call to v1 The v1 rewrite in the Azure URL builder replaced every "/openai" substring in the path, so a gateway api_base like https://apim.example.com/openai-gw/team turned into /openai/v1-gw/team/openai/v1/responses. Dated GA Responses calls now land on the v1 route by default, which made this reachable for them too, so the rewrite now only touches the last /openai path segment. The Responses version resolver no longer duplicates the builder's default for an unset api_version. Tests cover the gateway api_base case, the env AZURE_API_BASE query-string precedence, and the e2e suite now has one test for the dated GA default and one where only responses_api_version can make the call work * test(integration): cover Azure Responses api_version, Grok reasoning spend, wildcard listing and reasoning_effort none Wire tests pin the Azure route and query for chat, Responses and the azure/responses bridge on a dated GA api_version, and check responses_api_version never reaches the request body. Cost cases check azure_ai Grok folds reasoning tokens into completion_tokens and spend, streaming and not. A config-driven proxy checks /v1/models next to an openai/* wildcard lists each id once and never a deployment id. Azure gpt-6.1-sol rejects reasoning_effort none before reaching upstream and drops it with drop_params * fix(utils): list ai21 chat and vertex code models under their provider wildcard register_model now files ai21 chat models into ai21_chat_models, which models_by_provider never read, so a registered ai21 chat model dropped out of ai21/* listings. models_by_provider now reads ai21_chat_models and the vertex code chat and code text sets too. * fix(main): keep caller-chosen model names out of provider wildcard listings --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> |
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yuneng-jiang
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0403f8953e
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fix(cost): bill bridged /v1/messages Responses replies like native /v1/responses for reasoning tokens and service tier (#46975)
* fix(cost): price reasoning tokens of /v1/messages bridged onto the Responses API in the cost header and breakdown * fix(cost): record the bridged Responses API result only after the served body is built * fix(cost): keep the served service tier when a bridged Responses reply has no message item |
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litellm-stampbot
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1c317e3e61
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feat(cost-map): add baseten and nebius rows for Reflection Beam 1.0 (#46991)
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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berriai-litellm-provider-info-sync[bot]
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87f959798d
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fix(bedrock): backfill Priority and Batch prices from the AWS offer index (#46987)
Price-Sync: litellm-providers Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> |
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Mateo Wang
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29cd11bec6
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fix(sso): concurrent first sign-ins land on the winner's account, worker-kill test stops waiting on the reap (#46855)
* fix(sso): concurrent first sign-ins land on the account the winner created, worker-kill test pins half its streams to each worker * test(integration): a worker kill returns once the worker is dead, the reap waits at block exit uvicorn can take a full worker healthcheck to reap a worker that died mid-ping, so kill() held the caller that long and peers held on the surviving worker hit their client timeout * fix(sso): a sign-in that loses the first-insert race joins the default teams The losing sign-in could read the winner's row before new_user added the default teams, so its CLI key was minted with no team. The race tests now run the real new_user against a fake user table |
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Mateo Wang
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d76ec3a47e
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fix(proxy)!: answer 400 for malformed tools on count_tokens instead of crashing (#46583)
* fix(proxy): answer 400 for malformed tools on count_tokens instead of crashing A non-list tools value crashed the vector store lookup during auth and the built-in tool cost lookup in the failure logging path, so the proxy answered an unhandled 500 and closed the keep-alive connection. count_tokens now answers a 400 invalid_request_error for a malformed body, drops malformed tools when drop_params is on, and both lookups skip values of the wrong shape. * fix(proxy): skip non-list tools in the tool allowlist check Also validate the count_tokens body without recursion, which the recursion detector rejects. * test(integration): restore the int tools case on count_tokens The proxy now answers a non-list tools value with a 400, so the case is deterministic again. * fix(proxy): reject malformed tools at the LLM route entry and keep vector store checks on malformed ids * fix(proxy): apply drop_params like core when dropping malformed tools, and reject malformed tool vector store ids Check tools after request setup so the Claude Code default and the logged call type apply, read the request, global, and model group drop_params the way core does, drop tool_choice and friends with tools, cover Gemini generateContent, and answer 400 for a malformed tools[].vector_store_ids with the strict flag off * fix(proxy): keep the request's call type when logging a gate rejection after request setup The body-shape fallback relabeled a /v1/messages rejection as acompletion and a list-input /v1/responses rejection as aembedding, so it now only applies when the logging object carries no known call type * fix(proxy): share the malformed tools check across tool routes and honor drop_params per entry * fix(proxy): accept null vector_store_ids, read every named store id in auth, check the responses websocket * refactor(proxy): leave the responses websocket out of the request-level tool check * fix(proxy): let a request's additional_drop_params replace the deployment list and keep compact's call type on rejections * fix(proxy): read router default drop lists and deployment ids in the malformed tools check * fix(proxy): leave malformed tools to the router when it can pick another deployment Fallbacks, auto-routers, model strings, comma batches and team model names let the router pick a deployment after the proxy checks the request, so the proxy now forwards a malformed tools field there as main does, and only rejects it when the deployment it checks is the one that serves. Token counting never reroutes, so count_tokens and input_tokens keep reading the group they count with. additional_drop_params names are read the way core reads them, so a list with a non-string entry still names its strings. * test(integration): cover malformed tools on reroutable models, router defaults and deployment ids * fix(proxy): resolve malformed tools at the deployment the router picks * fix(proxy): keep provider-repaired tool schemas, honor fallback_on_unsupported_params, skip cooldown on malformed tools Empty schemas and JSON-string schemas pass the tools check the way litellm's provider paths already read them. The rejection is a BadRequestError subclass carrying the deployment's provider, so fallback_on_unsupported_params: false keeps the 400, and the router never cools a deployment down for a request litellm rejected before calling it. Adds the audit's pre_call guardrail and cross-provider bridge cells. * test(integration): expect a 400 for an empty-string tools field on /v1/messages Real Anthropic rejects tools "" with a 400 on main too, so the case joins the malformed tools test * fix(router): keep web search routing for tools passed as a tuple * fix(router): keep a deployment's own tools when drop_params drops a malformed request tools * test(router): list _merged_tools as covered through the deployment tools merge tests * fix(router): drop the request's tool settings with its malformed tools when deployment tools replace them * fix(router): skip a tool whose type is not a string in the web search filter instead of raising TypeError * fix(prometheus): keep deployment health metrics clean on a malformed tools rejection * test: type the new malformed tools tests * test: mark new test locals Final and type kwargs dicts |
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Mateo Wang
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57e69ce713
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docs(agents): keep directory rules in nested AGENTS.md and pin integration tests to CircleCI (#46796)
* docs(agents): keep directory rules in nested AGENTS.md and pin integration tests to CircleCI * docs(agents): scope the CircleCI rule to the files it covers and ask agents to read nested AGENTS.md * ci(coverage): reject GITHUB_FILES integration contracts run from a test-unit.yml shard * ci(coverage): report integration ownership findings under their own header * ci(coverage): flag GITHUB_FILES contracts run from any non-dedicated workflow * docs(integration): say a pre-merge run is no reason to route an integration file to GitHub * ci(coverage): tie each dedicated integration workflow to the directory it owns |
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ryan-crabbe-berri
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0dac61a555
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fix(guardrails): accept Gemini tools in generic_guardrail_api, add opt-in forward_messages_as_sent, name the error type on fail-open (#46338)
* fix(guardrails): accept Gemini tools and Anthropic content blocks in generic_guardrail_api, name the error type on fail-open GuardrailToolParam required a type key, so Gemini native tools (function_declarations, googleSearch) failed validation inside the hook and either returned a 500 or skipped the scan when fail_on_error was false. The type key is now optional and left out of the forwarded tool when absent, so an echoing guardrail server cannot write type: null into the provider request. structured_messages was re-validated against the chat completion message types, which silently emptied tool_result, tool_use, image and document content blocks to content: [] and dropped undeclared keys before the guardrail saw them. The request model now forwards rows as opaque mappings, which also retires the write-back shim that restored the original rows for echoed-back entries. The fail-open critical log line now carries error_type so a timeout, a refused connection and an upstream HTTP status can be told apart without the traceback. * fix(httpx): retry aiohttp server disconnects the way httpx does aiohttp raises ServerDisconnectedError when a kept-alive connection is closed by the peer before a response arrives, which is what a load balancer idle timeout shorter than AIOHTTP_KEEPALIVE_TIMEOUT produces. The transport mapped it to httpx.ReadError, which the handler's connection-error retry does not cover, so the request failed instead of being resent on a fresh connection. It now maps to httpx.RemoteProtocolError, the error httpx itself raises for the same condition, so the existing retry fires. * test(httpx): build the stub server reply in one bytes literal * fix(httpx): resend a dropped connection's request as sent and keep a streamed resend readable The connection-error retry closed its fresh client before a streamed body was read, so an aiohttp disconnect now billed a second upstream request and still failed. It also skipped masking on a status error from the resend, resent PATCH and DELETE as POST, dropped multipart files and ignored the handler's ssl_verify. The retry now resends the request the first attempt built, on a client with the handler's TLS settings, closes that client when a streamed body is closed, and masks a status error the same way the first attempt does. * fix(guardrails): log HTTPStatusError, not the masking wrapper, as the fail-open error_type * fix(guardrails): resend a generic guardrail check cut before any response A load balancer that closes an idle keepalive connection made the guardrail POST fail with "Server disconnected", because #46336 only resends POST on ConnectError. AsyncHTTPHandler.post now takes a keyword-only idempotent flag, defaulting to False, that gives a RemoteProtocolError the same single fresh-client resend PUT and DELETE get. Only GenericGuardrailAPI.apply_guardrail opts in, since a guardrail check is a pure verdict over the request. Every other POST keeps the #46336 rule The fail-open log line now puts error_type at the end so the pre-PR text stays contiguous for existing alert matchers test_rows_reach_the_guardrail_verbatim now reads the body off a real local guardrail server instead of mock call args * fix(http): keep a mid-body server disconnect a ReadError and move socket tests to integration A ServerDisconnectedError raised while reading a response body now stays httpx.ReadError, as it was before this PR. Only a disconnect before any response maps to RemoteProtocolError, which is the case the resend rule is about. Stream readers that end on ReadError, like the SAP stream iterator, keep their old behavior The loopback-server disconnect, TLS and guardrail resend tests move to tests/integration/sdk/test_disconnect_resend_wire.py, since tests/unit is in-process only. Unit keeps in-process MockTransport checks for the idempotent POST resend, masking on the resend, streamed and buffered client closing, the guardrail resend, and the guardrail receiving rows verbatim * fix(guardrails): resend a reset guardrail check and keep typed echoes on texts An idempotent POST now resends once on any network error after connect (ReadError, WriteError, RemoteProtocolError), so a guardrail behind a load balancer that answers a stale keepalive with a TCP reset rides it out too. That makes the aiohttp ServerDisconnectedError remap unnecessary, so it goes back to ReadError. This stops PUT and DELETE from stacking litellm's resend on top of aiohttp's own idempotent retry (4 sends instead of 2) and stops Vigil Guard from replaying its analyze POST on a disconnect Every resend now runs inside the method's own error mapping, so a timeout on the resend is a litellm.Timeout like the first attempt and a status error is masked once by the caller A guardrail server that parses rows with its own message types and echoes them back without the keys those types lack (annotations, tool_calls[].index) is read as an echo again, so its texts redaction reaches the LLM. A row only counts as an echo when no value changed and every key the chat completion types declare is kept The wire tests for the PUT/DELETE resend, its masking and its TLS settings now run on the httpx transport, where litellm's resend is the only retry, and the POST and guardrail tests cover both transports and both cut styles * test(guardrails): black box wire tests for generic guardrail shapes, fail-open error type and idle cut resend Integration tests against an owned proxy and scripted peers. Gemini native tools reach the guardrail and Gemini as sent, the guardrail sees chat rows and an Anthropic image block as sent, an echoing guardrail leaves a /v1/messages request unchanged, the fail-open log line names ConnectError, Timeout or HTTPStatusError, and a guardrail check cut on an idle pooled connection is resent once on each worker. Each fails at the merge base and passes at the head * fix(guardrails): check echoed rows without recursion and keep pytest.raises to one statement * refactor(guardrails): move the dropped-connection guardrail resend out of this PR The resend on a dropped or hung generic guardrail call, and the shared AsyncHTTPHandler retry rework behind it, move to a follow-up PR that adds a per-guardrail num_retries setting. This PR keeps the request and response shape fixes and the error_type on the fail-open log line * test(guardrails): pick the closed guardrail port from the integration port allocator Reading a port back from a port-0 bind trips TQ012, so the fail-open connect error case now takes its unused port from allocate_port * feat(guardrails): forward structured_messages as sent only behind forward_messages_as_sent generic_guardrail_api keeps main's OpenAI-format rows and echo comparison by default. Setting forward_messages_as_sent: true on the guardrail sends rows as the client sent them and treats an echo that only drops undeclared keys as unchanged --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Yassin Kortam
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3637dd711f
|
feat(ui): add Authorization URL, Token URL and Scopes fields for OAuth Delegate and True Passthrough MCP servers (#46941)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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|
yuneng-jiang
|
6530b329f4
|
fix(proxy): give /team/delete transactions a 30s timeout (#46979)
Both interactive transactions in /team/delete used Prisma's 5s default. A lock wait or a short database stall past 5s expired the transaction after the keys were already deleted, so the call returned 503 and left the team row, memberships and team models behind |
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|
yuneng-jiang
|
ac6300f380
|
fix(mcp): stop proxy-started legacy listeners from consuming server rpm (#46968)
* fix(mcp): stop proxy-started legacy listeners from consuming server rpm The listener the proxy opens on notifications/initialized for legacy MCP sessions ran the server rate-limit admission once per target, so every session spent an rpm slot before the client sent anything. Admission is now injected into the listener and applied only to client-initiated subscriptions (subscriptions/listen and resources/subscribe). Authorization and its periodic recheck still run on every path. * test(mcp): key the fake admission window by caller and server * fix(mcp): stop subscription catalog refreshes from consuming server rpm A subscription listener lists the caller's catalog to diff list_changed events, at setup and on every upstream event. Those listings went through the normal per-server admission, so against an upstream that declares listChanged each legacy session spent several rpm slots before the client asked for anything. The listener now marks its targets as already admitted for its own lifetime, so its refreshes reuse the subscription's admission. Client requests on the session are still metered. * test(mcp): exercise subscription admission through the proxy rate limiter |
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|
devin-ai-integration[bot]
|
8bb8ac7f18
|
fix(proxy): keep a retried /v1/messages stream's spend log by logging the superseded attempt as a failure (#45136)
* fix(proxy): keep a retried /v1/messages stream's spend log by logging the superseded attempt as a failure A /v1/messages stream the router retries before any content shares one logging object across both attempts. The superseded attempt's end-of-stream logging ran as a success (a usage-only or placeholder result) and claimed the request's one-shot success log, so the recovered stream's spend row was either missing or written under the superseded attempt's message id. The passthrough logging path now logs an Anthropic stream whose frames carry an `event: error` as a failure with whatever usage the provider reported, the way a dropped stream already does, and the router closes the superseded stream before it opens the retry so that logging is queued first. * fix(proxy): log a provider error frame through an attempt-scoped logging copy The error-frame failure stashed the superseded attempt's usage on the logging object the retry shares, so the retry's success log carried the failed attempt's token counts. The failure now logs through a copy of the logging object with its own model_call_details, and the helper moves into the Anthropic passthrough logging handler so the proxy streaming handler only routes by endpoint type. * fix(proxy): scope the error-frame failure log to streams closed at the frame A stream that ran to its end at the provider's error frame kept logging through the success route before this PR, and the attempt-scoped failure log is now taken only for a stream the router closed at that frame, with the copy made at the close so the retry's deployment never reaches it * chore: drop duplicate litellm import and mark the stream_ended rebind * fix(proxy): log only router-superseded attempts as error-frame failures A client that hangs up at a forwarded error frame closed the stream the same way the router closes a superseded attempt, so a non-retried stream lost its spend. The router now closes a superseded attempt through aclose_superseded_attempt, and only that close routes the attempt to the failure log * test: type the _settle helper's recorded events --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
yuneng-jiang
|
ee6ca049b3
|
build(deps): bump claude-agent-sdk to 0.2.165 to unblock osv-scan (#46971)
OSV started flagging claude-agent-sdk 0.1.44 today, which turns OSV Scan red on every PR. 0.2.165 is the newest release outside the 3-day uv cooldown. The package sits only in the ci dependency group and is only imported by the cookbook |
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|
yuneng-jiang
|
5bcced0187
|
feat(ui): redesign the playground chat around a single composer and inspector (#46934)
* feat(ui): add clean-slate playground chat prototype
* feat(ui): replace the playground chat with the redesigned composer and inspector
* fix(ui): close the playground chat gaps found in self-review
Resend only complete text exchanges, so empty replies, MCP direct calls and
transcriptions no longer leak into chat history. A stopped request can no longer
append output, attach its gateway trace to a newer reply or clear the newer
request's loading state. MCP selections are only pruned once both the server and
toolset lists load. The MCP tool picker lists toolsets again and calls the server
that backs the chosen tool, and a saved model the current key cannot use is
cleared when the model list loads, matching the old chat
Also vendors the scroll-fade-x utility the attachment primitive uses
* fix(ui): resolve playground toolset tools per server and drop late session ids
A toolset now lists only its own tools, each resolved on the server the toolset
names, so the args form and the call always target the same tool. A saved
toolset no longer asks for tools with its own id while the toolset list loads,
and a failed tool list says so instead of claiming the server has no tools
A stopped request can no longer overwrite the Responses session id, starting a
new chat drops a request that is still running, embeddings replies are no longer
resent as chat history, and a saved model missing from an already cached model
list is cleared too. A failing toolset list falls back right away instead of
retrying while the MCP pickers show loading
* fix(ui): guard playground sends and label inspector stats
Pressing Enter twice no longer sends the same message twice, an attachment the
new endpoint cannot take is dropped when the endpoint changes, a stopped
Responses request can no longer show its code output on a newer reply, and a
reply that broke mid-stream is no longer resent as history
The inspector's speed, cost and routing stats get the same icons as the reply
footer, and the footer's metrics now line up with its copy and Inspect buttons
* fix(ui): write playground key settings only through the encoded storage path
Key source, virtual key and custom headers now go through their own write loop, separate from the plain settings, so a key value can never take the plain sessionStorage branch
* fix(ui): restore playground BYOK connect and reconnect
Picking a BYOK server for a direct tool call now shows a key button next to the
server picker, so the key can be connected without leaving the MCP endpoint. A
connected BYOK server gets a Replace key action in the MCP dialog, also shown
when its tools fail to load, and saving a key reloads that server's tool list
* revert: restore the single playground settings storage loop
Reverts
|
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|
berriai-litellm-provider-info-sync[bot]
|
78372b440d
|
feat(cost-map): add together_ai reflection/Beam-1.0-501B-A23B (#46964)
Price-Sync: litellm-providers Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> |
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|
AxelRay
|
388251a5b8
|
fix(bedrock): drop dangerous-tool-use beta without safeguards (#44471)
* fix(bedrock): drop dangerous beta without safeguards * fix(bedrock): drop the dangerous-tool-use beta only next to structured outputs, keep it on Mantle Bedrock rejects the pair with 'invalid beta flag' on Claude models before Opus 4.7, while requests without structured outputs and Bedrock Mantle accept the beta, so the drop now only applies to Invoke requests with output_config.format or a strict tool and no safeguards. * fix(anthropic): keep the AnthropicThinkingParam import that main now uses * fix(bedrock): drop the client's dangerous-tool-use beta whenever safeguards is absent Bedrock rejects the beta with 'invalid beta flag' on Sonnet 4.5, Opus 4.5, and Opus 4.6 even without structured outputs, so dropping it only next to structured outputs left those beta-only requests failing. The beta does nothing without safeguards, so Invoke now drops it in every such request. Mantle keeps it. The thinking display helper goes back to main's version. * fix(bedrock): drop the client's dangerous-tool-use beta on Invoke chat without safeguards * test(bedrock): wire cells for the dangerous-tool-use beta on Invoke messages, chat and responses * test(bedrock): type the new dangerous-tool-use beta tests * test(bedrock_mantle): type the dangerous-tool-use beta Mantle test --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
Mateo Wang
|
60af2c601d
|
fix(proxy): emit spend queue size after updates and flushes (#46956)
Co-authored-by: Mateo <mateo@Mateos-MBP-2.localdomain> |
||
|
ryan-crabbe-berri
|
c7b115b56a
|
feat(ui): add the 1 hour cache write cost to the add model and model edit forms (#46830)
* feat(ui): add the 1 hour cache write cost to the add model and model edit forms Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): cover both cache write tiers in the add model and edit forms Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(ui): hoist the expected pricing payload out of the inline assertion Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(ui): share the per-token conversion between both cache write tiers Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(ui): derive the touched pricing field type from the pricing field list Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(ui): collapse the duplicated pricing source keys into one map Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): convert add model pricing once for all selected models and describe the 1 hour fallback Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): type the cache write tier deployment read back and fill the 1 hour field Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(e2e): keep the cache write tier spec on the dashboard prettier config Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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|
Irvallen Saragih
|
d6b54ae2b0
|
fix(openai)!: route gpt-transcribe to GPT audio transcription config (#44021)
* fix(openai): route gpt-transcribe to GPT audio transcription config * test(openai): move gpt-transcribe tests under tests/unit * fix(openai): bill gpt-transcribe from provider usage seconds when duration is unknown Fall back to the provider-reported usage.seconds when neither a measured file duration nor a response duration is available, so json responses for undecodable uploads are no longer billed at zero. Move the routing test next to the other provider config tests and replace the structure test with a behavior test. * fix(openai): bill provider usage seconds only for gpt transcription models * fix(cost): decide provider-billed transcription seconds from the deployment model, not its pricing id * test(integration): cover gpt-transcribe default request, provider-billed spend, and health probe --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
devin-ai-integration[bot]
|
33b73207e3
|
test(cost): rekey vertex gemini, add bedrock mantle gpt and claude-opus-5-5, drop suite-only price fields (#46962)
* test(cost): remove price fields the real gemini and azure rows do not carry Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): key vertex gemini cases on the vertex_ai prefixed rows and add gemini-4-argon Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): add current gemini and vertex usage keys to stored responses Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): add bedrock mantle claude-opus-5-5 cost tracking cases Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): add bedrock mantle gpt cost tracking cases Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
Mateo Wang
|
d3ed19e369
|
fix(rust): forward Anthropic headers to DeepSeek (#46959)
Co-authored-by: Mateo <mateo@Mateos-MBP-2.localdomain> |
||
|
Kerry Lu
|
8227f9bf20
|
test(perf): cap every background Postgres statement at 0.9 calls per request (#46957)
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
devin-ai-integration[bot]
|
c1a8575e58
|
test(integration): remove BUG skip for 1 test that passes on main (#46937)
test_two_identical_cache_hit_rejects_write_matching_spend_rows passed every run with the skip removed, so the dropped spend row it was guarding against no longer reproduces Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
Kerry Lu
|
1451aed726
|
fix(tests): drain SDK logging before restoring callbacks (#46924)
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
yujonglee
|
a1c9fa951a
|
test(rust-bridge): relocate dispatch tests before routing changes (#46926)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
Yassin Kortam
|
f02449ad38
|
feat(sso): retain the SAML assertion at login as the saml2 subject token for oauth2_id_jag (#46745)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
Yassin Kortam
|
3501e36fa9
|
feat(sso): capture the IdP id_token on Microsoft and Google logins for oauth2_id_jag (#46747)
Resolves LIT-9671 Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
Yassin Kortam
|
bca7650e8f
|
feat(mcp): accept an ID-JAG as an RFC 7523 jwt-bearer grant on the gateway token endpoint (#46748)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
Kerry Lu
|
1dfceccf10
|
test(perf): cap every awaited Postgres statement at 0.5 calls per request (#46944)
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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|
Kerry Lu
|
339fd90836
|
fix(proxy): streaming responses hand the event loop back every 50 ms instead of holding it for the whole buffered stream (#46925)
* fix(proxy): streaming responses hand the event loop back every 50 ms instead of holding it for the whole buffered stream * fix(proxy): yield to the event loop on every streamed chunk, no hold budget or clock * docs(proxy): say why the streaming loop yields on every chunk * fix(proxy): streaming loop yields once it has held the event loop 50 ms, clock read inline * docs(proxy): streaming loop comment names the 50 ms hold * Revert "docs(proxy): streaming loop comment names the 50 ms hold" This reverts commit |
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|
devin-ai-integration[bot]
|
f811a5923e
|
test(cost): bill vertex gemini-3.8-flash reasoning tokens at the reasoning price (#46939)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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|
Mateo Wang
|
f8217d2a03
|
fix(count_tokens): apply context_management edits in the Gemini /v1/messages/count_tokens count (#46843)
* fix(count_tokens): apply context_management edits in the Gemini /v1/messages/count_tokens count /v1/messages runs clear_tool_uses context edits before it sends an Anthropic body to a Gemini or Vertex AI deployment, but /v1/messages/count_tokens counted the body unedited, so a request with older tool results cleared counted about 2.8x what inference bills. The count now runs the same history and context-edit step inference runs, honors additional_drop_params on the deployment, and skips compact edits so a count never makes a paid summary call. * fix(count_tokens): match the Gemini count to inference for compact edits and drop opt-outs Run compact edits in the count without the summary call so trigger checks and history slicing match /v1/messages, honor a request-level additional_drop_params, keep the full body when any deployment in the model group drops context_management, and answer 400 naming a block Gemini cannot count when an edit trigger fails on it * fix(count_tokens): count the unedited body when an edit fails and honor deployment ids in the drop check * fix(count_tokens): log a failed edit in the count at debug, since the send already logs it * fix(count_tokens): resolve a deployment id before wildcard routes in the drop check, as the router does * fix(count_tokens): honor the router-wide additional_drop_params opt-out in the drop check The router merges default_litellm_params between the deployment and the request, so a router-wide context_management opt-out makes /v1/messages send the full history. The count now reads it in the same order. Adds the audit's wire tests for the count's context edits. * fix(count_tokens): read the opt-out of a deployment the router serves by its litellm model name * fix(count_tokens): read the opt-out and drop_params from the deployments the router and completion_model send to * fix(messages): drop an invalid context_management spec under drop_params so the send matches the count * fix(count_tokens): give Claude Code and Codex counts the drop_params default /v1/messages gives them The proxy turns on drop_params for Claude Code and Codex user agents on /v1/messages. The count now applies the same default, so an invalid context_management spec drops on both endpoints instead of the count answering 400 while the send answers 200. The wire test also covers default_fallbacks, model_group_alias, and completion_model routes. * test(count_tokens): cover a coding agent that turns drop_params off and stop two count tests running as Claude Code |
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devin-ai-integration[bot]
|
86a91f35de
|
fix(responses): log and bill every round of non-stream MCP auto-execute (#43667)
* fix(responses): log and bill every round of non-stream MCP auto-execute Both model rounds run as internal sub-calls on the request's logging object, and the outer call logs the response the client received with usage, cost, and cost breakdown summed across the rounds. The internal-call gate now also covers the sync success callbacks, so an inner round no longer takes their first-wins slot * fix(caching): let the parent call log and bill an internal sub-call's cache hit A round of non-stream MCP auto-execute that the response cache served fired the cache-hit callbacks on the shared logging object, so the spend log kept round 1's function_call row and dropped the billed row for the answer. Internal sub-call cache hits now fire no callbacks and carry a zero cost, and the summed cost breakdown leaves out rounds served from the cache * fix(logging): keep a parent row unique when its response came from the response cache A RAG query or an MCP turn whose final round is served from the cache hands back the cached response's id, which already belongs to the row that cached it, so SpendLogs dropped the new row as a duplicate. Such a row now gets the cache-hit id suffix, and it is logged as a cache hit when it cost nothing. * fix(logging): skip the zero-cost warning for a response served from the cache at no charge A non-stream MCP auto-execute request whose rounds the response cache served is priced at $0 before the parent marks it a cache hit, so it logged a false 'priced at $0' warning and counted in litellm_zero_cost_requests_total. The diagnostic now treats a response the cache served at no charge the same as a marked cache hit * fix(responses): bill the paid first MCP round when a later step of the request fails * fix(responses): log each MCP tool call under its own id so a failed follow-up keeps its spend row The non-stream auto-execute path passed the request's call id to the tool call, so the tool's spend row and the request's failure row shared one request_id and the failure row was dropped on insert, leaving the paid first round unbilled. * fix(responses): bill round 1 on a client disconnect, keep MCP tool rows in the request's session, and charge a fixed margin once per request * fix(responses): keep bridged MCP auto-execute in one session and trace and continue its conversation The bridged follow-up no longer chains on round 1, so a thinking model keeps its reasoning and the request stays in one session. The tool call log continues the request trace without renaming it, the tools are fetched once, and a later turn finds the MCP turn under the id the client got, skipping the tool rows. * fix(responses): log the non-stream MCP tool listing in the request's session and trace * fix(responses): find a bridged MCP turn by the id the client holds and log its listing in the bridged trace * fix(responses): derive the MCP tool row id from the request's call id The tool call's spend row now uses <call id>_<tool call id>, so it stays linked to the request without colliding with the request's failure row. Also tighten the internal cache-hit test to a fixed clock and typed params. * fix(responses): bill a retried MCP attempt for its own rounds A router retry or fallback reuses the request's logging object, so a failed attempt's stashed round 1 usage made the next attempt's success row log stale tokens. Each non-stream MCP attempt now starts without that stash. * fix(responses): bill every failed MCP attempt's paid first round on the request failure A retry or fallback now sets a failed attempt's stashed round 1 aside instead of dropping it, and the proxy's failure row adds it to the last attempt's own, so a request whose later attempt fails on its first call still bills the round the provider charged. A cached final round also keeps the paid first round's cost breakdown. * fix(responses): keep MCP tool catalog and results out of the bridged next-turn replay * fix(responses): keep MCP tool spend, client body keys, and Langfuse traces working on auto-execute Count the MCP tools an auto-executed Responses API call ran in the tool spend rollup, accept a client body key named previous_response_client_ids without a 500, and point MCP listing and tool spans at the trace Langfuse gives the parent request, including x-litellm-session-id requests * fix(responses): join MCP spans to the Langfuse trace when the request sends body metadata * test(integration): cover non-stream MCP auto-execute billing, failure rows, and bridged follow-ups --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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devin-ai-integration[bot]
|
ee4860dd84
|
test(cost): add tier 1 cost tracking cases for gpt-5.6-terra, gemini-4-argon and gemini-3.1-pro-preview (#46931)
* test(cost): add tier 1 cost tracking cases for gpt-5.6-terra, gemini-4-argon and gemini-3.1-pro-preview Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): add audit 3 shape cases for vertex_ai and azure_ai claude Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): mark azure gpt-5.6-terra priority case as known bug Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Mateo Wang
|
7ddc9f1c96
|
fix(bedrock)!: keep reasoning, thinking blocks and the json_mode finish_reason on fake streams (#46863)
* fix(bedrock): keep reasoning, thinking blocks and the json_mode finish_reason on fake streams A Bedrock Converse model without native structured output fakes the stream when response_format carries a json_schema. The fake stream transformed the response without json_mode and rebuilt a chunk from text, tool_use and token counts only, so it dropped reasoning_content, the signed thinking_blocks and the reasoning token count, and ended on finish_reason tool_calls. The three fake-stream sites now pass json_mode to _transform_response and stream the resulting ModelResponse through the shared convert_model_response_to_streaming converter, which now numbers each streamed thinking block with its index the way real streams do * fix(bedrock): parse text tool calls on Converse fake streams like the non-stream answer * fix(responses): stream the answer text when one chat chunk carries reasoning and the answer * fix(streaming): keep every field on the OpenAI and openai_like fake streams and split multi-block thinking Azure o-series and openai_like fake streams now use the shared MockResponseIterator, so extra tool calls, reasoning and cached and reasoning tokens survive; the Bedrock-local iterator is deleted. The /v1/responses bridge also splits a chunk whose thinking block is signed or redacted with no reasoning text, and the sync iterator closes the reasoning item before the answer opens, like the async one. The /v1/messages bridge gives each thinking block in a chunk its own content block, starts a new block when the thinking block index changes, and streams redacted thinking as redacted_thinking. Snowflake replays drop the stream index from thinking blocks. * fix(anthropic): stream each thinking block's text once on /v1/messages An unsigned thinking chunk now opens its content block with empty text, since its thinking_delta carries the text. A multi-block chunk keeps each piece's thinking block, so an unsigned block followed by a signed one keeps its own text and index. * docs(anthropic): describe which thinking block start carries its text * fix(streaming): close merged reasoning before the answer when one chunk carries both * test(streaming): cover fake-stream reasoning across the proxy bridges and type the Snowflake replay test |
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Krrish Dholakia
|
e4dc696af8
|
feat(ui): turn the Chat UI on by default (#46918)
Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
|
e45f2737d3
|
fix(proxy)!: delete callbacks configured under callbacks or failure_callback (#42740)
* fix(proxy): delete callbacks configured under callbacks or failure_callback Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): assert on configured callback rows and use a callback absent from CI configs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): follow logging suite conventions for callback delete tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): flatten remaining callbacks with a helper generator Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): type callback delete helpers to satisfy basedpyright budget Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): save callback config without mutating the loaded dict Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): delete callbacks from every litellm_settings list GET shows POST /config/callback/delete only searched success_callback while GET /get/config/callbacks also lists failure_callback and callbacks, so the Admin UI Delete returned 404 for those rows Remove the name from every list that holds it, matching entries case-insensitively, and skip lists the config file owns when the database owns another copy so the save is not refused Replace the e2e test with an integration test: the shared e2e stack config owns litellm_settings.callbacks, so it cannot exercise that list * test(proxy): cover config-owned success_callback on callback delete and wait on runtime state Add the mirror mixed-ownership case where the config file sets success_callback and the database owns failure_callback, which main refused with a 400, plus a string-valued list case Poll GET listings and /active/callbacks instead of reading them once, so a request served by a worker that has not synced yet cannot fail the test, and reuse the existing callback list key map in the route * test(proxy): annotate callback delete test helper locals with Final * fix(proxy): save callback delete through the config it read so concurrent settings edits are kept --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com> |
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ryan-crabbe-berri
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977a581213
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fix(router): stop queueing budget increments for Redis when no Redis is configured (#46831)
* fix(router): stop queueing budget increments for Redis when no Redis is configured Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): assert Redis-less model budget limiter tracks spend locally without queueing Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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859529ccbc
|
fix(realtime)!: keep turn_detection.type when a transcript guardrail disables auto-response (#44939)
* fix(realtime): keep turn_detection.type when a transcript guardrail disables auto-response * test(realtime): type the GA session.update helper and mark its locals Final * test(realtime): expect typed turn_detection on the voice guardrail session updates * test(realtime): accept either gate path for the client's first voice session.update * fix(gemini): drop VAD tuning when the guardrail turns auto-response off * fix(gemini): check create_response without a redundant isinstance * fix(vertex_ai): keep the client's VAD tuning on Vertex when auto-response is off * fix(realtime): keep the transcript-guardrail gate typeless on xAI so it does not auto-answer * fix(realtime): replace any client turn_detection with the untyped gate on xAI xAI answers on its own under a typed server_vad even with create_response off, so a client's typed turn_detection must not reach xAI while the transcript guardrail gates the turn. * fix(realtime): keep a client's early turn_detection and hide the guardrail cancel's error A session.update sent before session.created reached OpenAI ahead of the proxy's own gate, so the gate replaced the client's turn_detection. The proxy now re-sends the client's gated turn_detection after the gate when the two differ. The guardrail's response.cancel now carries a litellm_guardrail_ event_id, and the error OpenAI returns for it (response_cancel_not_active when nothing is answering) no longer reaches the client. * fix(realtime): send the guardrail gate before a client's early session.update and let Muse and Chirp fall back to server_vad under drop_params * fix(realtime): hide only the cancel errors that echo the guardrail's own response.cancel ids Track the event ids of the guardrail cancels this session sent and drop a backend error only when its error.event_id is one of them, so a client's own event id with the same prefix still gets its error. Cover the scripted response.cancel reply in the integration upstream, update the stale list-mode test to the typed gate, and mark the xAI cancel error cell as an expected failure, since xAI replies with its own event id. * test(integration support): deliver the disconnect a real server sends after the client goes away The scripted upstream now keeps reading frames after a reply hits a closed socket, so the unit test's fake ASGI receive has to end with the websocket.disconnect message a real server delivers. * fix(realtime): delete the blocked transcript item before the guardrail's refusal turn OpenAI GA answered the blocked question in some refusal turns because the blocked user item stayed in the conversation. The raw OpenAI-protocol path now sends conversation.item.delete for it right after the cancel. Provider config backends have no such event, so that path no longer passes an item id. Also bound the guardrail integration file by the shared graceful-stop timeout and make the xAI cancel-error xfail require an AssertionError. * fix(realtime): keep the blocked item on xAI, which cannot delete an audio input item * test(realtime): assert the xAI voice block sends no conversation.item.delete upstream --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Rick
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f81e657903
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feat(volcengine): add Doubao-Seedance video generation via the OpenAI /v1/videos surface (#46156)
* feat(volcengine): add Doubao-Seedance video generation via the OpenAI /v1/videos surface
New VolcEngineVideoConfig maps litellm's OpenAI Videos API onto Volcengine
Ark's contents/generations task API: create hits
/api/v3/contents/generations/tasks and returns a cgt-... task id, status and
content poll /api/v3/contents/generations/tasks/{id}, list maps the same
collection (limit -> page_size, Ark's filter.* through extra_query), delete
maps DELETE on the task URL, and edit/extension reuse create with a
reference_video content item since Ark models both as ordinary generation
tasks. Ark's own edit and extension require ratio adaptive (edit also
duration -1), so those are pinned unless the caller overrides them. Remix has
no Ark equivalent and raises.
The body is flat apart from a typed content array: the prompt is a text item
and every image/video/audio input is a url item carrying a role, which is the
only way to express reference-to-video, edit and extension jobs, so a
caller-supplied content array wins outright. input_reference becomes a
first_frame item, base64 encoded into a data URI for file inputs.
OpenAI params translate per Ark's contract: seconds becomes duration and size
yields both a ratio and a named resolution tier, with the ratio snapped onto
the set Ark accepts (854x480 reduces to 427:240, which Ark rejects) and the
tier taken from the shortest side. Emitting only the ratio leaves the request
on the model default and bills at that default's rate.
Billing reads the delivered duration and resolution rather than the requested
ones, because duration -1 and ratio adaptive both let Ark deliver something
else. Ark bills per output token (tokens = width * height * 24 * seconds /
1024), so the cost map carries per-second rates by resolution tier, derived
from the console's CNY per million token list rates (2.5 70, 2.0 46, 2.0-fast
37, 2.0-mini 23 without a video input) at the repo's 7.0 CNY/USD convention.
Requests that do carry a video input bill at the lower rate instead, which
litellm's per-second tiers cannot express, so those are overestimated.
usage.total_tokens rides along for invoice reconciliation.
Ark echoes the delivered geometry only as a resolution tier plus a ratio, and
the 2.0 family's rendered frame does not follow the tier name: its 16:9 "480p"
canvas is 864x496, not the 854x480 the tier implies, and its other ratios
differ from the tier's nominal shortest side too. A size reconstructed from
the tier alone therefore reports pixels the model never produces and scales
the 480p rate against the wrong pixel count, so both the reported size and
the 2.0 480p rates come from the measured frame (a per-family table, sourced
from the Seedance 2.0 Mini model card and re-verified against a live gateway).
The create response reports the requested duration and resolution, since only
the create, edit and remix calls are costed and Ark's create response carries
no usage block, so without it every video logs zero spend. A caller that
leaves seconds off is not free either: Ark runs its own default length, which
is 5s for the 2.0 family, so that is what the create response bills, while
the 2.5 family's default is -1 (Ark picks) and stays unbilled until the
status response. The create response also echoes the requested seconds and
the frame the job will be rendered at.
Editing and extending need the source video as a URL: Ark's task query is a
GET while litellm's edit prefetch hook only POSTs, so a task id cannot be
resolved into one. The model comes from an explicit extra_body.model, else
the encoded video id, else the model the router already resolved, with
litellm's provider prefix dropped.
The credential's api_base is the Anthropic-compat surface
(/api/compatible), so the base is cut at the first /api/ marker rather than
by a /api/v3 suffix before the video paths append their own version.
The cost-map schema test's exception list gains the 2.0 4K tier, whose
$1.28/second rate exceeds its $1 sanity bound, alongside the existing
runwayml/seedance2 entry.
* fix(volcengine): answer 4xx when a Seedance video is downloaded before it finishes
Downloading a task that is still queued or running raised a bare ValueError, which the
video content handler synthesizes into a 500. The proxy then retried the same poll twice
and reported the caller's own early download as a gateway fault, and the router went
looking for a model group fallback for a job that was simply unfinished
The download path now raises VolcEngineVideoError carrying the status the OpenAI videos
API documents for content that is not ready (404), 400 for a task the provider reported
as failed, 404 for an expired task record, and 502 for a succeeded task with no artifact.
None of them are 5xx, so the router stops retrying them
Regression tests drive avideo_content and assert the caller sees NotFoundError or
BadRequestError instead of an internal server error
* fix(volcengine): clear the type-discipline and override findings on the Seedance video path
The module annotated four mutable collections and carried five `# mutable-ok` markers on
lines that suppressed nothing, so the type-discipline gate counted LIT001 x4 and LIT013
x5 against the PR. The content-item and task-dump helpers hand back read-only views of
what they build, so they now say Mapping. VideoObject.error is declared as a dict by the
type it feeds, so that one marker moves onto the annotation it actually suppresses
transform_video_status_retrieve_response also dropped the client keyword the base class
declares, which basedpyright reported as an incompatible override
* fix(volcengine): bill every Seedance video at create and keep its polls on the deployment that made it
Ark bills a task when it finishes while litellm bills it at create, so a request
whose cost is not known then is rejected: Ark-picked length (duration -1), frames,
a video input, and with it edit and extension. An omitted length is sent as 5s,
since the 2.5 family otherwise lets Ark pick it and logged $0.
Video ids now carry the requested and the served model group, read from
litellm_metadata, so polls and downloads go back to the deployment that created
the task. The routing and input_reference helpers move out of the DashScope
config into a shared module both providers use.
A download before the render finishes answers 400, unreadable or unmapped task
bodies answer 502, malformed seconds, size, parameters and Ark fields raise
unless drop_params is set, an unpriced resolution tier is refused, and the
rendered frame table moves into the cost map.
Co-Authored-By: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
* fix(volcengine): reject a text item in content so the guarded prompt is the only text sent
Input guardrails scan data["prompt"], so a caller could pass a harmless prompt
for scanning and a different, unscanned text item in content, which this branch
kept and the guarded prompt was dropped. The prompt now always leads the content
array and a second text item answers 400.
Co-Authored-By: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
* fix(volcengine): route video to VOLCENGINE_API_BASE when the deployment sets no api_base
* fix(volcengine): let a model with no tier prices keep its resolution instead of rejecting every tier
* fix(volcengine): answer 400 for malformed or unknown create fields, send a 720p default tier, and stop the list cursor
* fix(volcengine): map size to the closest tier by pixel count, reject draft, remix and list cursors, map user to safety_identifier, read ARK_API_BASE
* fix(volcengine): drop unsupported create values under drop_params, take OpenAI's object input_reference, default to 4 seconds, price endpoint ids by base_model
* fix(videos): unwrap nested file tuples without recursion
* fix(volcengine): price Seedance tiers at Ark's own per-resolution token rates
Ark prices 1080p and 4k per token above and below the 480p/720p rate, so the
single 46 CNY per million tokens the rows were derived from billed 2.0 1080p
and 2.5 1080p about 10% low and 2.0 4k 77% high. Ark's per-resolution table
and its own 16:9 examples agree: 1080p 2.48 CNY/s, 4k 5.05 CNY/s for 2.0 and
3.74 CNY/s for 2.5 1080p, which is 51, 26 and 77 CNY per million tokens.
Rewrites the tier test to check each rate against the rendered pixels at that
tier's own price instead of assuming every tier scales from the base rate,
and drops the 4k cost exception that only existed for the old rate.
Co-Authored-By: Bytechoreographer <noreply@bytechoreographer.com>
Co-Authored-By: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
* fix(volcengine): unpack Ark parameters sent through extra_body
* fix(volcengine): ignore the extra_body keys litellm maps itself
The shared request builder merges the caller's raw extra_body back over the
mapped params, so a key this adapter maps itself comes back a second time as a
field of its own, and the unknown field check turned the supported request
into a 400.
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Ayush Shekhar
|
7930c0e434
|
feat(router): mid-stream fallback continuation for chat completions (#41127)
* feat(router): continue chat streams on fallback after a mid-stream break A chat-completions stream that breaks after content has been delivered was re-raised and the fallback deployment never ran (#40404), while the Responses-API path already continues via a prefilled assistant turn. Add the same for chat completions behind `enable_mid_stream_fallback_continuation` (opt-in, async-only), so a post-content break re-enters the fallback chain with the partial text as an assistant prefill instead of surfacing the error. Continuation is only attempted when it is safe: the stream emitted plain assistant text (no tool/function calls, thinking blocks, reasoning items, audio or images), the request is not constrained output (response_format or a forced tool_choice) and not merge-reasoning mode, and the fallback target's model supports assistant prefill. The target check runs as a deployment pre-call filter, so a chain with no prefill-capable deployment empties and the original error is surfaced rather than a duplicated or rejected request being sent. Plain reasoning_content is treated as out-of-band and does not block a continuation, matching the Responses-API path; Anthropic thinking is excluded because its signed thinking blocks cannot ride a text-only prefill. CustomStreamWrapper now latches whether a disqualifying delta was streamed and carries it on MidStreamFallbackError so the router can decide without re-scanning chunks. Default behavior is unchanged. * fix(router): harden mid-stream continuation eligibility and prefill folding Address review of the mid-stream continuation: - keep response_format={"type": "text"} eligible; only json_object / json_schema and other structured formats decline, since "text" is the unconstrained default - fold a new partial into an existing trailing assistant prefill instead of appending a second one, so a nested mid-stream break stays a single prefill turn even on providers that do not merge consecutive assistant messages - split the deployment prefill-capability lookup into two readable steps - cover the merge_reasoning decline branch, the text response_format pass, and the prefill-folding path with tests * fix(router): address review of mid-stream continuation - register the continuation deployment filter as a process-global singleton instead of tracking it per router, so discarding one router no longer removes the type-deduplicated filter that other live routers still depend on - disqualify reasoning_content: it reaches the caller as visible reasoning that a text-only prefill cannot carry, so a reasoning-capable fallback would re-derive it and produce an incoherent response - move MID_STREAM_CONTINUATION_KWARG to constants and lazy-import the filter class in the router, breaking the module-level import cycle CodeQL flagged - trim the added docstrings to the repository comment policy * fix(router): keep mid-stream continuation within the type-discipline budget The LIT* type-discipline gate counts mutable-collection use the ruff pass does not see. Annotate the reads with read-only Sequence/Mapping views, compare response_format against a frozen MappingProxyType sentinel, and mark the genuinely mutable litellm message and deployment-list boundaries with mutable-ok reasons, so LIT001 and LIT002 stay under their limits. * fix(router): clear basedpyright operator error and the import-cycle alert - narrow the accumulated stream delta content to str before appending, so the shared helper no longer trips reportOperatorIssue (str += object) - keep the continuation marker in the pre-call-check module and lazy-import it at the two router call sites instead of routing it through constants, so the router has no module-level dependency that closes an import cycle * fix(router): make the mid-stream continuation marker unforgeable The deployment filter is process-global and read the continuation marker as a truthy value from request_kwargs. Since the proxy can forward arbitrary request-body fields into the router, a client could send `"_mid_stream_continuation": true` on a normal request to filter a mixed model group down to prefill-capable deployments and steer their prompt onto that provider. Set a private sentinel object internally and check it by type instead of truthiness: a JSON request body cannot construct one, so a forged flag is ignored. Adds a regression test that forged client values (true, "true", 1, a dict) leave the deployment list untouched. * feat(router): honor per-deployment model_info for continuation prefill capability The deployment filter only read supports_assistant_prefill from the cost map, so a model configured with `model_info: {supports_assistant_prefill: true}` on the deployment (the usual way to declare a capability for a model that is not in the cost map, or to override it) was wrongly skipped. Check the deployment's model_info first (True or False both authoritative), then fall back to the cost map. Adds tests for the override in both directions. * fix(router): bound mid-stream continuation to the caller's output allowance A continuation handed the fallback the full max_tokens / max_completion_tokens even though part of the answer had already streamed, so the total could exceed the caller's limit and repeated interruptions could re-grant the allowance on every hop, amplifying spend. Reduce each configured ceiling by the tokens already emitted before re-entry, and decline the continuation (surface the original error) when the allowance is exhausted. The reductions compound across hops because the trimmed ceiling is what the next hop sees. Also add the missing explanatory comment on the model_info fall-through except. * refactor(router): extract mid-stream decline to stay within the complexity budget The output-ceiling branch pushed stream_with_fallbacks past the C901 limit. Both decline paths (ineligible after content, and exhausted allowance) re-raised the original provider error the same way, so pull that into _raise_original_mid_stream_error. It removes the duplicated branching, drops the function back under the complexity ceiling, and reads clearer. * fix(cost-map): mark Claude Sonnet 4.6 as not supporting assistant prefill The Anthropic API and Bedrock both reject an assistant-last message on claude-sonnet-4-6 with "This model does not support assistant message prefill", so the continuation filter must not route a mid-stream continuation to it. Flip the flag on every claude-sonnet-4-6 entry and on databricks' opus-4-6 entry, whose anthropic sibling already says false. The prefill check tests now register synthetic cost-map entries instead of pinning real models, which broke when claude-3-opus left the map. * refactor(router): type the streaming fallback kwargs and drop narration comments Removes an unused mutable-ok marker (LIT013) and the explanatory comments Greptile flagged, and types initial_kwargs on both streaming fallback iterators as dict[str, Any] like their Responses siblings so the new continuation helpers take a typed mapping and the basedpyright budget stays at or below main. * fix(router): run post_call_rules over the joined text of a continued stream Each provider stream wrapper validates only the fragment it produced, so a rule that trips on the primary's prefix plus the continuation's text never fired. The router now feeds litellm.post_call_rules the emitted text plus every continuation chunk before yielding it. Also drops a narrating test-helper docstring. * refactor(router): read a deployment's declared prefill support without an empty except * test(router): cover _raise_original_mid_stream_error directly for the router coverage gate * fix(router): fold the continuation prefill into a trailing assistant turn A request that already ends in an assistant message took the partial output as a second assistant turn, which prefill providers reject. The partial now extends that turn in place, with prefix set, so the continuation request never ends in two assistant messages. * fix(router): keep content blocks on a trailing assistant turn when extending it with the partial output A trailing assistant message whose content is a list of blocks was stringified before the partial output was appended, so the fallback received the Python repr of the blocks as its prefill. The partial now lands as one more text block, and a content shape that cannot be extended surfaces the original stream error instead of a garbled continuation. * fix(router): continue the trailing text block in place when extending a prefill with content blocks Anthropic strips trailing whitespace per content block, so appending the partial output as a new text block after an assistant turn that ends in "Sure, " would send the prefill as "Sure,here". The continuation now extends the last text block itself and only opens a new text block when the trailing block is not text (an image, say), so the prefill reads exactly as the text the caller already received * test(router): type the prefill check's deployment helper * fix(router): keep a continued stream on the primary's identity and widen what can continue Continuation chunks now keep the primary stream's id and created time and drop the fallback's second role delta. Requests with n > 1 no longer continue. Prefill support reads model_info.base_model and litellm_params.base_model before the deployment model. enable_mid_stream_fallback_continuation is runtime-updatable through update_settings and registers the prefill filter. The bridge rebuild of MidStreamFallbackError keeps the inner stream's disqualifier. A fallback that repeats the prefill is not doubled in the continuation input. * fix(router): decline mid-stream continuation after a content filter, merged reasoning, or a plain trailing assistant turn Also count the partial stream's completion tokens in the continued stream's usage, accept string values for enable_mid_stream_fallback_continuation, and list the new router helpers in the router coverage check * fix(router): drop re-emitted whitespace at the continuation join and sum both legs' usage consistently * fix(router): keep the full prefill so a nested break keeps the separator * fix(router): bill both calls of a continued stream and fix Bedrock Converse, Databricks, and Vertex DeepSeek prefill routes * test(router): integration cells for mid-stream fallback continuation Covers the continued stream the caller gets, the prefill turn and reduced max_tokens the fallback receives, the prefill-capability filter, the runtime toggle, repeated requests through the response cache, and the spend row of a continued stream * fix(router): log a continued stream under the caller's id, price each cut on its own prompt, and keep prefill flags per deployment * fix(router): price and log each cut leg before its continuation reuses the logging object Price the cut stream's partial and let its failure log finish (bounded) before the fallback overwrites a shared proxy logging object, and skip continuation when an output guardrail is registered or a request fallback carries its own messages. * test(router): integration cells for the output-guardrail and request-fallback declines and the cut call's failure log Cover a registered post_call guardrail and a request fallback carrying its own messages keeping the original error, an input-only guardrail leaving continuation on, and the cut call's failure event naming its own deployment and price. * fix(router): skip mid-stream continuation when a request fallback overrides request params A request-body fallback entry that sets anything besides model (stream, messages, max_tokens) changes the request the prefill continuation relies on, so a stream: false entry ended the answer with no error. * fix(router): skip mid-stream continuation for a fallback group target that overrides request params The override check read only top-level fallback entries, so a target inside a group's list, such as {"primary": [{"model": "backup", "stream": false}]} in the request, the config, or a key's router settings, still ended the answer with no error. * fix(router): check only the request's own fallback chain for request param overrides Scanning every group's chain turned continuation off for all requests when one unrelated group's target overrode a param. Resolve the chain the router will use for this request, the same way the fallback path does. * fix(router): keep the original error when request fallbacks are malformed The request-param override check resolved a standard-shape chain outside the router's own error handling, so an empty entry or a non-list chain raised StopIteration or TypeError and replaced the original mid-stream error. Skip empty entries and treat a non-list chain as no chain. * fix(router): read deployment-configured constraints, decline deployment-id fallbacks without prefill, strip only the last Bedrock text block * fix(router): read a deployment's tool_choice ahead of router defaults in the continuation check, and restore the renamed prefill test names * fix(router): filter continuation deployments on every routing strategy, read extra_body and fallback deployments' own params The deployment filter now also runs on the sync selection path that usage-based-routing v1 and custom strategies use, one predicate reads n, response_format, tool_choice and merge_reasoning_content_in_choices with extra_body laid over them, fallback deployments whose own config constrains the output are skipped, and continuation declines when the cut deployment's id is not in the router (per-request credential deployments) * fix(router): decline a cut mid-echo, reduce extra_body output limits, and check post_call_rules once on nested continuations --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
Deepanshu Pal
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d5ce7dbb8c
|
fix(proxy)!: honor caller litellm_session_id in spend log session_id (#44199)
* fix(responses): scope session history lookup to the referenced key * Implement SQLite-backed DB for session tests Added a SQLite-backed database class for testing and a new test to ensure session isolation between different API keys. * fix(proxy): honor caller litellm_session_id in spend log session_id Updated docstring to clarify session ID resolution logic for spend log rows. * test(proxy): caller litellm_session_id wins over the trace id * style(proxy): fix blank lines around new tests * fix(proxy): read the caller session from the logging payload for spend logs * fix(responses): match user and team too when replaying session history * fix(proxy): keep bridged Responses chains whole and scope session history by owner * fix(proxy): keep a metadata session next to a trace header and let session headers win * fix(proxy): send the trace-header session only to spend logs and let session headers win beside a trace header * fix(proxy): drop a client-sent caller session and keep it out of requester metadata * fix(proxy): keep the trace id as the spend log session when the caller session contains a NUL byte * fix(responses): keep a continued bridged chain's session under request_correlation_in_logs With the flag on, the caller session outranked the chain session the bridge sets for a continued Responses chain, so a chain whose session changed or first appeared on a later turn split. The continuation now logs under the chain's session and drops the turn's caller session key, as on main. Adds the /audit integration cells for the spend log caller session. * fix(responses): log a continued bridged chain under its session through the spend-log key only The previous commit set the chain session as the turn's litellm_session_id, which also moved the OTel conversation id of a continued turn away from its trace header. The bridge now writes the chain session into the internal spend-log session key of the metadata the spend log reads, so only the spend log session changes, as on main. Adds an OTel cell for a continued chain. * test(spend): cover bridged chains that share one caller session * test(spend): cover the caller session on configured pass-through routes * test(spend): type the SQLite fake and split stacked comprehensions in the caller session tests --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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devin-ai-integration[bot]
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4e2dd65549
|
fix(interactions): keep background interaction bills through crashes, late restarts, and deployment keys (#45743)
* fix(interactions): keep background interaction bills through crashes, late restarts, and deployment keys A settlement claim is now a lease, so a row whose settler died between claim and outcome is claimable again after the lease and boot resumes it. A resumed poll gets the full poll window and fetches with the serving deployment's credentials from the live router. The stored create context keeps the request tags and the request metadata that the creating worker's own spend row used * fix(interactions): bill a lapsed claim's takeover only when no spend row exists A settler that billed and then died, or failed to record the outcome, left the row unsettled, so the replica that took over its lapsed claim billed the interaction a second time. A takeover now looks up the spend row keyed by the interaction id and records the row as billed when it finds one. * fix(interactions): settle Vertex AI and edited deployments, never double bill with spend logs off A takeover with spend logs off records the interaction unsettled instead of billing it again, and a release records its outcome before freeing the budget reservation. A resumed or live fetch carries the deployment's Vertex AI project, location, and credentials, and a stale deployment id falls back to the model group only when one same-provider deployment serves it. A poll stops at the first 400, 401, 403, or 404, string request tags no longer fail the create, and settled_at gets an index built concurrently. * fix(interactions): leave a live replica's interaction to it when a resumed poll cannot read it A replica that boots with credentials unable to read an interaction got a 404 on its resumed poll and settled the row as unsettled at once, so the replica that created it, still polling, found it settled and never billed it. A resumed poll that gets a 400, 401, 403, or 404 now stops fetching and keeps checking the row until its poll window ends, and settles it as unsettled only when no other replica did. * fix(interactions): keep the creator's metadata on a resumed bill and retry outcome writes inside the claim lease A bill another replica writes now carries the metadata the creating worker's own spend row is built from, so a client's metadata.model_group no longer relabels it. A failed outcome write is retried for half the claim lease before the budget reservation is left to a takeover, and the creating replica retries every fetch error for its whole window again, as main does. The resume integration case now checks that a resumed fetch uses the deployment's own key. * fix(interactions): resume background interaction polls only after database models load Boot resume ran before the proxy loaded the models stored in the database, so a resumed poll for a model added through /model/new or the Admin UI fetched with env credentials. A 4xx there stops a resumed poll, so the bill was lost. The settlement now installs after the database models load. The integration test resumes a database model with an eager first fetch and fails with the old startup order. * fix(interactions): renew a settling claim so a slow settle is never taken over and billed twice A settle runs every success callback in turn, and one slow callback could hold it past the 5 minute claim lease. A booting replica or a DELETE then took the live claim over, found no spend row yet, and billed the interaction a second time. The settler now renews its claim every third of the lease until it records the outcome, so only a settler that stopped renewing is taken over. A takeover also read the spend log after writing its claim, so a failed read left the row under the taker's own fresh claim, which its poll then took for another settler's and left unbilled until a reboot. The spend row is now read before the claim is written, so a failed read takes nothing and the claim is retried on the next poll. * test(spend): cover lapsed claim takeovers, rotated deployment keys, late restarts, and resumed bill tags --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Mateo Wang
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2dc6aafa6b
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fix(proxy)!: count prompt-only token_counter requests with the provider when call_endpoint is set (#46839)
* fix(proxy): count prompt-only token_counter requests with the provider when call_endpoint is set * fix(proxy): keep the local count for a prompt-only token_counter request when the provider count fails * fix(proxy): log a prompt-only token count fallback as a one-line warning * fix(proxy): send a prompt-only token_counter request to the provider only on Gemini and Vertex AI * fix(proxy): count a token_counter prompt sent next to an empty messages or contents list * fix(proxy): count a prompt next to messages on the local token count instead of answering 500 * fix(proxy): answer 400 for a token count prompt next to a conversation unless drop_params is set With drop_params the conversation is counted without the prompt. On the local count, a prompt sent with system or tools is counted as a user message with them, like the messages form. * test(proxy): count tools with a prompt in the token counter fallback test * test(proxy): cover prompt counting on /utils/token_counter in the Gemini count wire tests * test(proxy): name the token counter fallback test by what it checks |