9811 Commits

Author	SHA1	Message	Date
Sameer Kankute	3d0e0cee56	[Feat] Add tool calling support for gemini and vertex ai live api (#26590) ... * Add tool calling support for gemini and vertex ai live api * Fix greptile reviews * Add new functionality behind flag * fix greptile issues * Fix greptile review * Fix greptile review * Fix greptile review * Fix greptile review * Fix greptile review * fix lint * fix(realtime): address P1 issues - guardrail timing and inputAudioTranscription default - Remove early guardrail turn-detection update that consumed first setup slot - Add inputAudioTranscription default in Gemini deferred-mode setup - Add tests for both fixes Made-with: Cursor * fix(realtime): inject turn_detection into first session.update for deferred mode - Instead of sending turn_detection as separate message (which gets dropped), inject it into the first client session.update - This ensures guardrails work correctly in deferred mode - Add test for turn_detection injection in deferred mode Made-with: Cursor * fix(realtime): emit response.created preamble before tool-call events - Emit response.created, output_item.added, and conversation.item.created for function calls - Ensures OpenAI Realtime API spec compliance - Add test for preamble emission Made-with: Cursor * fix(realtime): add response.output_item.done to complete tool-call sequence - Emit response.output_item.done between function_call_arguments.done and conversation.item.created - Required by OpenAI Realtime spec to finalize function-call items - Update test to verify complete event sequence Made-with: Cursor * fix(realtime): emit response.done after tool-call sequence (P0 CRITICAL) - Add response.done event after tool-call loop to signal response completion - Required by OpenAI SDK clients to submit tool results - Without this, clients stall indefinitely waiting for response completion - Update test to verify complete 6-event sequence including response.done Made-with: Cursor * fix(realtime): include function name in toolResponse (P1) - Store call_id → name mapping when receiving toolCall from Gemini - Look up and include name in functionResponses when sending tool results - Required by Gemini Live API spec for proper tool call routing - Add test to verify name field is included in round-trip Made-with: Cursor * fix: resolve merge conflict markers in UI build chunk Take litellm_internal_staging version of e1a670efcb966aaa.js after incomplete merge left conflict markers in the committed artifact. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(vertex_ai/realtime): call super().__init__() to initialize tool call state Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): correct guardrail flag and event-mapping fallback - realtime_streaming: only mark _guardrail_turn_detection_update_sent when the message was actually delivered to the backend. The provider transformation (e.g. Gemini after initial setup) may silently drop session.update; previously we set the flag anyway, falsely claiming the disable was sent and preventing any retry on subsequent session.created events. _send_to_backend now returns whether at least one transformed message was sent. - gemini realtime transformation: avoid shadowing the outer openai_event variable in map_openai_event's fallback loop. With the new toolCall entry now last in MAP_GEMINI_FIELD_TO_OPENAI_EVENT, an unmatched key would otherwise leak FUNCTION_CALL_ARGUMENTS_DONE and skip the ValueError raise. Use a distinct loop variable so the is-None check correctly raises for unknown Gemini messages. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini/realtime): reset response IDs after tool-call response.done After closing a tool-call response, clear current_output_item_id and current_response_id so post-tool model turns emit a fresh response.created preamble. Add regression tests and align guardrail turn_detection test with GA session shape; apply Black formatting. Co-authored-by: Cursor <cursoragent@cursor.com> * fix lint * fix(realtime): log injected message and forward guardrail VAD-disable on Gemini - Move store_input() after the guardrail turn_detection injection in client_ack_messages so audit logs reflect what is actually forwarded to the backend (previously the unmodified pre-injection message was logged). - In Gemini's _handle_session_update, allow a session.update that only carries a turn_detection change to be forwarded as a follow-up Gemini setup with realtimeInputConfig.automaticActivityDetection set, even after the initial setup. This restores the guardrail layer's ability to disable VAD auto-response in non-deferred mode (the default Gemini flow), which was a regression after _handle_session_update started silently dropping subsequent session.update messages. Both flat beta-style and nested GA-style turn_detection payloads are accepted. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini/realtime): resolve mypy TypedDict errors in transformation Align realtime event payloads and setup types with OpenAI/Gemini TypedDicts so mypy passes and tool-call events type-check correctly. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(realtime): forward turn_detection updates for Vertex; respect partial VAD config; cache setup after send Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): consolidate send-and-cache, guard session.update lookup, preserve client turn_detection in GA remap - Replace duplicated transform/send/cache logic in client_ack_messages with a call to _send_to_backend so future changes stay in one place. - VertexAIRealtimeConfig.transform_realtime_request now uses .get('session') or {} for the first session.update so a malformed client payload no longer crashes the connection. - Move the audio-transcription guardrail turn_detection injection to run BEFORE the beta->GA session remap. This lets the injected create_response ride along with any client-provided turn_detection fields (e.g. silence_duration_ms) into the nested audio.input.turn_detection path produced by the remap instead of being stranded as a separate root-level dict. - Update the deferred-mode injection test to assert the GA-shaped location. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): pop tool_call_id mapping after use to bound memory Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): correct deferred-setup session.created modalities and reset IDs after response.done - Convert provider's real session.created to session.updated when a synthetic one was already forwarded so clients receive the authoritative modalities derived from their session.update instead of the synthetic placeholder. - Reset current_response_id / current_output_item_id after Gemini RESPONSE_DONE so a toolCall arriving in a later frame starts a fresh response instead of reusing the completed response's ID and emitting a duplicate response.done. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini-realtime): preserve nested turn_detection through map_openai_params After the GA remap moves session.turn_detection into session.audio.input.turn_detection, Gemini's map_openai_params only looks at top-level keys and silently drops it. Normalize the extracted turn_detection back to the top level on first session.update so the guardrail create_response:False (and any client-provided VAD settings) reach the Gemini setup. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): normalize Vertex AI nested turn_detection and unify session.created guardrail ordering - Vertex AI _build_vertex_ai_setup_config now lifts nested audio.input.turn_detection to the top level before calling map_openai_params, mirroring the parent GeminiRealtimeConfig behavior. Without this, guardrail-injected create_response: False was silently dropped for GA-protocol Vertex AI clients. - realtime_streaming session.created handling now sends the (possibly re-typed) event first and then triggers the guardrail turn-detection update for both first and duplicate cases, removing the inconsistent guardrail-then-event ordering for duplicates. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): tolerate non-dict turn_detection in guardrail injection When a client sends a session.update whose turn_detection field is None or a non-dict value (e.g. "auto"), the guardrail injection used setdefault followed by item assignment on the returned value, raising TypeError. The inner except only caught JSONDecodeError/AttributeError, so the TypeError escaped to the outer Exception handler that wraps the entire client_ack loop, killing the connection. Replace non-dict turn_detection with a fresh dict carrying create_response=False so the guardrail still applies without crashing the loop. * fix(gemini realtime): default synthetic session.created modalities to AUDIO The synthetic session.created event emitted in deferred setup mode used TEXT as the default for responseModalities, while _handle_session_update defaults to AUDIO. Align the default so clients reading modalities from the initial session.created see the correct value for live sessions. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(vertex_ai/realtime): drop follow-up session.update to avoid 1007 close Vertex AI Live treats setup as a first-and-only client message; emitting a second setup with realtimeInputConfig only closes the websocket with a 1007 policy error. Reverting the follow-up-setup branch restores the pre-existing no-op behavior for subsequent session.update messages. * fix(gemini realtime): default responseModalities to AUDIO in delta events Align return_new_content_delta_events with the AUDIO defaults used in _handle_session_update and transform_session_created_event so deferred session config does not produce TEXT-typed delta events for audio data. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): default response.done modalities to AUDIO and correct audio-done test * fix(realtime): set guardrail turn_detection flag only after successful send Previously the _guardrail_turn_detection_update_sent flag was set inline during message rewriting in client_ack_messages, before the modified session.update was forwarded to the backend. If _send_to_backend raised (e.g. backend WebSocket disconnect), the exception was caught and the loop continued, but the flag remained True — permanently disabling the guardrail create_response=False injection for the rest of the session. Neither the client_ack_messages path nor the _maybe_send_guardrail_turn_detection_update backup path would retry. Track the injection locally and only set the flag after _send_to_backend returns a truthy sent result, matching the pattern used by _maybe_send_guardrail_turn_detection_update. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(vertex_ai realtime): keep VAD enabled when guardrails inject create_response: False map_automatic_turn_detection sets disabled=True whenever create_response is absent OR False. Transcription guardrails inject create_response: False to suppress auto-responses while expecting VAD to stay active, but the previous override in _build_vertex_ai_setup_config only fired when create_response was absent, leaving disabled=True and silently breaking speech detection and transcription events. Vertex Live has no 'VAD on, no auto-response' mode, so always keep VAD active in the setup config. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): normalize GA-remapped session fields before mapping map_openai_params only recognises the flat OpenAI-beta keys (modalities, input_audio_transcription, turn_detection). For GA clients the upstream shim renames these into the nested GA schema (output_modalities, audio.input.transcription, audio.input.turn_detection), causing them to be silently dropped in _handle_session_update. Add a normalization helper that surfaces the GA-remapped values back at the top level so the existing mapping logic picks them up. Without this, a GA client explicitly requesting modalities=['text'] would still default to audio output. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(vertex_ai/realtime): normalize all GA-remapped session fields before mapping Previously _build_vertex_ai_setup_config only lifted nested turn_detection back to the top level. GA clients' output_modalities and audio.input.transcription were silently dropped because map_openai_params only recognises the flat OpenAI-beta keys. Use the parent's _normalize_session_payload_for_mapping so modalities, transcription, and turn_detection are all surfaced before mapping. * fix(realtime): force create_response=False in all client session.update turn_detection when audio guardrails active Prevents a client from re-enabling Gemini/GA VAD auto-response (and thereby bypassing the audio transcription guardrail) by sending a later session.update with turn_detection.create_response: true. * fix(lint): silence PLR0915 on client_ack_messages The function exceeded the 50-statement limit (64 > 50) after recent realtime guardrail additions. Matches the existing project pattern for inherently complex event/message-mapping methods (see _process_event, translate_messages_to_responses_input, transform_realtime_response, _arealtime, etc.). * fix(gemini realtime): preserve original setup config on follow-up session.update Gemini Live treats a second BidiGenerateContentSetup as a full session replacement, not a partial merge. The guardrail-driven turn_detection-only session.update was emitting a setup containing only model + realtimeInputConfig, which would silently drop tools, generationConfig, inputAudioTranscription, and systemInstruction from the original setup. Carry forward the cached original setup and only override realtimeInputConfig. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): avoid double-serialization and normalize non-dict turn_detection in guardrail override - Skip the force-override block when the injection block already ran for the same session.update to avoid redundant JSON re-serialization. - Normalize non-dict client-provided turn_detection values (flat and nested audio.input.turn_detection) to a dict before enforcing create_response=False, matching the injection block's behavior and preventing potential bypass on backends that accept non-dict values. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(gemini realtime): exercise toolCall → function_call_output name round-trip Update test_gemini_realtime_function_call_output_transformation to pre-load the call_id → name mapping by transforming a Gemini toolCall first, then assert that the resulting Gemini toolResponse functionResponses entry carries the function name. This pins the production round-trip rather than the degenerate 'name missing' branch. * fix(realtime): correct conversation_id, VAD disable, modality state, empty toolCall - Gemini tool-call response.done now includes conversation_id so clients can match it against the preceding response.created. - Vertex AI setup no longer overrides an explicit guardrail-injected create_response: False back to disabled: False; the guardrail's intent to disable VAD auto-response is now respected. - Modality handler is now passed the locally-updated response/item IDs rather than the original input snapshot, preventing stale IDs after a prior tool-call/response.done in the same JSON message resets them. - Skip emitting orphaned response.created/response.done events when Gemini sends an empty functionCalls array. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): preserve client session.update fields on follow-up Gemini setup In non-deferred mode the auto-setup pre-populates session_configuration_request, so a later client session.update carrying tools or instructions used to fall into the subsequent path and only forward turn_detection. Rebuild a merged follow-up setup that overlays the new client fields on top of the original setup so tools/instructions/etc. are no longer silently dropped. * fix(gemini realtime): include usage on tool-call response.done; coerce non-dict tool output to struct - Tool-call response.done now includes an empty usage object, matching the non-tool-call path so OpenAI-compatible clients always see usage. - _handle_function_call_output wraps non-dict JSON parses under a 'result' key so Gemini's functionResponses[].response (a Struct) always receives a mapping. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): deep-merge nested config in follow-up session update Previously, the follow-up setup performed a shallow merge between the original setup and new overrides. If a session.update touched any field inside generationConfig (e.g. modalities), the entire generationConfig would be replaced, silently dropping unrelated sub-keys like temperature or maxOutputTokens. Apply the same deep-merge to realtimeInputConfig so partial automatic-activity-detection updates don't drop other realtime input config fields either. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): default conversation_id before tool-call response.done mypy flagged that response.done's conversation_id (str on the TypedDict) could be None when current_response_id was already set on entry. Ensure the fallback runs unconditionally before the response is constructed. * fix(realtime): deep-merge generationConfig and refresh cache on follow-up setup A subsequent Gemini session.update that touches any generationConfig sub-field (e.g. just temperature) was clobbering the original generationConfig — silently dropping responseModalities and switching the session to text-only. Deep-merge generationConfig so existing keys (responseModalities, maxOutputTokens, ...) are preserved when the client updates only a subset. Also drop the early-return in _cache_session_configuration_request so the cached payload tracks the latest setup sent to the backend. Without this, downstream readers (transform_session_created_event, modality lookup in return_new_content_delta_events) keep reading stale modalities/system instruction after a follow-up setup. * fix(gemini realtime): mirror modalities/temperature/max_output_tokens on tool-call response.created The audio/text response.created preamble includes modalities, temperature, and max_output_tokens on the response object so spec-compliant clients can initialise per-response state. The tool-call response.created was missing these fields, leaving clients without consistent response metadata when a response starts with a tool call instead of content. Read them from the cached session_configuration_request the same way the audio/text path does. * fix(gemini realtime): keep call_id→name mapping across function_call_output retries A client SDK that retries function_call_output (or sends the same result twice) would previously hit a missing-name lookup on the second send because _handle_function_call_output popped the call_id → name entry. Without name, Gemini may silently reject the response. Use dict.get so the mapping persists for the lifetime of the session. * fix(gemini realtime): empty toolCall must not terminate the WebSocket If Gemini sends a toolCall whose functionCalls list is empty (or absent), the previous `continue` left returned_message empty and the "Unknown message type" guard fired, killing the WebSocket session. Return a normal (empty) result instead so the session keeps going. * fix(vertex realtime): warn when dropping guardrail turn-detection update In non-deferred mode the auto-setup is sent on connect, so the audio-transcription guardrail's subsequent session.update carrying turn_detection.create_response=False cannot be forwarded as a second setup (Vertex Live closes the WebSocket with 1007). Surface a warning when this specific drop happens so operators know the model will auto-respond before the guardrail can gate it, instead of failing silently at debug level. * fix(gemini realtime): deep-merge automaticActivityDetection on follow-up session.update The follow-up setup merge already deep-merged generationConfig and realtimeInputConfig, but realtimeInputConfig.automaticActivityDetection itself is a nested dict. A partial VAD update (e.g. the guardrail-injected disabled=True from create_response=False) silently dropped unrelated knobs such as silenceDurationMs and prefixPaddingMs from the original setup. Deep-merge that block too so partial overrides only touch the fields they specify. * fix(realtime): record synthetic session.created in deferred-setup mode The deferred-setup path emits a synthetic session.created directly to the client websocket but did not run it through RealTimeStreaming's store_message, so the event was missing from the session log used by success_handler / async_success_handler. Call store_message before forwarding so the synthetic event lands in the same log stream as provider-driven events. * fix(gemini realtime): bound _tool_call_id_to_name with an LRU; exercise modality forwarding test Two minor follow-ups from review: * Switch _tool_call_id_to_name to a 256-entry LRU OrderedDict so a long session with many tool calls doesn't grow the dict without bound, while retried function_call_output lookups still hit for recently-seen call_ids. * Fix test_gemini_realtime_transformation_session_created to wrap the cached session config in {"setup": ...} so the modality lookup in transform_session_created_event actually exercises responseModalities forwarding (the prior payload was silently treated as empty). * test(gemini realtime): wrap remaining cached session configs in setup envelope The session_configuration_request the proxy caches is always serialized as {"setup": ...}; three modality-related tests dumped a bare config dict instead, so transform_session_created_event's `.get('setup', {})` quietly returned an empty dict and the responseModalities lookup ran against the default rather than the fixture. Wrap the remaining tests in the same shape the production cache uses so any regression in modality forwarding actually trips. * fix(gemini realtime): cast merged realtimeInputConfig for typeddict assignment mypy flagged the assignment of the merged dict into BidiGenerateContentSetup.realtimeInputConfig with [typeddict-item]: the intermediate variable widens to dict[Any, Any], losing the TypedDict narrowing the previous dict-literal form had. * test(gemini realtime): wrap test_gemini_tool_call_resets_ids fixture in setup envelope The cached session_configuration_request the proxy stores is always serialized as {"setup": ...}; this test passed a bare config dict, so transform_session_created_event's .get('setup', {}) returned an empty dict and the responseModalities lookup ran against the default rather than the fixture. Wrap the fixture in the same shape the production cache uses. * fix(gemini realtime): skip unknown sibling keys in transform loop Gemini realtime messages can include sibling metadata keys like usageMetadata alongside primary payload keys (toolCall, serverContent). Previously, the transform loop called map_openai_event for every top-level key, raising ValueError for unknown ones and terminating the WebSocket session. Skip top-level keys not present in MAP_GEMINI_FIELD_TO_OPENAI_EVENT to keep the session alive when Gemini emits usage metadata with a toolCall response. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): scope dotted-key event lookup and propagate session metadata to tool-call response.done - map_openai_event: only check the current key/value pair when resolving dotted map entries (e.g. serverContent.turnComplete) so a sibling key in the same frame can't misclassify the event being processed (e.g. toolCall returning RESPONSE_DONE). - tool-call path: extract generationConfig once and include modalities, temperature, and max_output_tokens on response.done so its shape matches response.created and the non-tool-call response.done. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): cast maxOutputTokens to int for typeddict assignment * fix(gemini realtime): use camelCase maxOutputTokens in response.done Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): cast maxOutputTokens to int for typeddict assignment * fix(realtime): inject guardrail turn_detection on subsequent session.update without one Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): tolerate sibling-only frames (e.g. standalone usageMetadata) A Gemini Live frame that contains only metadata keys outside _KNOWN_GEMINI_TOP_LEVEL_KEYS (e.g. a bare {"usageMetadata": {...}} emitted between turns) leaves returned_message empty after the transform loop and was tripping the 'Unknown message type' guard, which raised ValueError and terminated the WebSocket session. Treat such frames as no-ops and return the unchanged state instead. * fix(gemini realtime): preserve sibling toolCall when serverContent has only transcription Previously, when a Gemini frame contained both a transcription-only serverContent and a sibling toolCall, the transcription handler would early-return and silently drop the toolCall. Instead, mark serverContent as handled and fall through so the main loop still processes siblings like toolCall, while preserving the prior no-op behavior for empty/ transcription-only frames. Co-authored-by: Yassin Kortam <yassin@berri.ai> * refactor(gemini realtime): drop unused json_message arg from map_openai_event Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): promote nested turn_detection when flat value is not a dict When the session payload had `turn_detection: None` (or any non-dict value), the normalizer skipped promoting the GA nested `audio.input.turn_detection` because it only checked key presence. The stale None then flowed into `map_automatic_turn_detection` and raised TypeError on `'create_response' in value`. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(realtime): run guardrails on function_call_output content Tool result outputs are client-controlled and fed to the model, so they must pass the same content checks as user text messages. Otherwise an attacker can smuggle blocked content into a function_call_output and have the model process it. * fix(gemini realtime): emit function_call_arguments.delta before .done Gemini delivers the full function-call arguments in a single toolCall frame. The OpenAI Realtime spec orders the streaming events as output_item.added -> function_call_arguments.delta(+) -> function_call_arguments.done -> output_item.done. Emit a single delta carrying the complete arguments string before the matching .done so spec-compliant SDK clients that accumulate deltas and gate finalisation on at least one delta arriving do not stall on Gemini tool calls. * fix(realtime): avoid stale session.created flag triggering guardrail re-injection Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(ci): restore guardrail injection on duplicate session.created and cast realtime delta event - Re-enable the one-time guardrail turn_detection update on duplicate session.created. `_maybe_send_guardrail_turn_detection_update` is already idempotent via `_guardrail_turn_detection_update_sent`, so the previous guard was unnecessary and broke the deferred-setup path where the synthetic session.created is emitted by llm_http_handler outside this loop (no prior chance to inject). - Cast the response.function_call_arguments.delta dict appended to `returned_message: List[OpenAIRealtimeEvents]` so mypy is satisfied. * fix(realtime): forward sanitized function_call_output on guardrail block Providers that pair every toolCall with a toolResponse (e.g. Gemini and Vertex Live) stay in the awaiting-tool-call state until a toolResponse arrives. Dropping a blocked function_call_output outright left those providers stalled — the subsequent guardrail clientContent and response.create were ignored because the prior toolCall had no matching toolResponse. When the client-supplied tool output fails the realtime guardrail check, forward a sanitized placeholder function_call_output (same call_id, generic policy marker as output) instead of dropping the message entirely. The placeholder carries no blocked content, so the model never sees it, while still completing the provider's tool-call cycle so the session can recover and the violation message reaches the user. * fix(gemini realtime): preserve sibling keys on empty toolCall no-op Replace the early return on `functionCalls` empty/absent with a `continue` plus a `tool_call_handled` flag that mirrors the existing `server_content_handled` pattern. The post-loop guard already distinguishes intentionally-consumed known keys from genuinely-unknown messages, so adding `toolCall` to that exclusion list lets the loop continue iterating over any sibling top-level keys in the same Gemini frame instead of short-circuiting on the first empty toolCall. In practice Gemini's protobuf places `toolCall`/`serverContent`/ `setupComplete` in a `oneof` so the only realistic sibling is `usageMetadata` (already filtered as unknown-top-level), but the uniform handling avoids silently discarding any future sibling key should the wire format grow. * fix(gemini realtime): redact realtime payloads from debug logs The transform_realtime_response debug logs were dumping the raw inbound Gemini frame and each outbound OpenAI event payload (up to 500 chars). Realtime frames carry transcripts, model output, and tool-call arguments, so those strings ended up in application logs whenever DEBUG was enabled. Replace the inbound dump with just the top-level frame keys and the outbound dump with just the event type. * fix(realtime): check function_call_output before user role to prevent guardrail bypass Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): propagate usageMetadata on tool-call response.done Gemini Live emits usageMetadata as a sibling top-level key alongside the toolCall frame; the tool-call branch was unconditionally building response.done from get_empty_usage(), so tokens consumed by tool-call turns were recorded as zero spend and bypassed LiteLLM budget accounting. Mirror the non-tool-call RESPONSE_DONE path: when the same frame carries usageMetadata, run VertexGeminiConfig._calculate_usage and forward the real token counts. * fix(realtime): send sanitized toolResponse before guardrail clientContent Two related fixes for the function_call_output blocked-by-guardrail path: 1. Ordering: Gemini Live requires a matching toolResponse immediately after a toolCall before any other client message. Previously we ran the guardrail first (which sends clientContent/cancel) and only then forwarded the sanitized function_call_output. Add an optional pre_block_backend_message arg to run_realtime_guardrails so the sanitized toolResponse is emitted before the guardrail's own backend messages. 2. Stale pending flag: stop setting _pending_guardrail_message in the tool-output block. That flag exists to swallow the reflexive response.create an OpenAI client sends right after a user text message. In tool-calling flows the client may never send a response.create (e.g. Gemini SDKs auto-respond), so leaving the flag set would consume an unrelated response.create from a later turn. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(model_prices): allow audio_transcription_config in schema * fix(gemini realtime): event_id, item copy, and dict guard for tool-call events - Emit event_id on response.output_item.added for tool calls so spec-compliant OpenAI Realtime SDK clients can index/deduplicate the event like every other server-sent event in the sequence. - Pass a shallow copy of function_call_item to response.output_item.done and conversation.item.created so downstream handlers (e.g. the beta-protocol translator) that mutate the item dict don't corrupt sibling events sharing the same reference. - Guard map_openai_event against non-dict values (e.g. Gemini's 'setupComplete: true' boolean payload) so the WebSocket session doesn't die with an AttributeError on the unguarded .get() call. Add NotRequired event_id field on OpenAIRealtimeStreamResponseOutputItemAdded to keep existing call-sites that don't set event_id compatible. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(gemini realtime): buffer standalone usageMetadata for next response.done Gemini Live can emit usageMetadata as a standalone WebSocket frame between turns. The previous transformer treated those frames as no-ops, so token counts arriving outside the closing turnComplete/toolCall frame were dropped from spend and budget accounting. An authenticated client could drive turns whose usage was recorded as zero, bypassing budgets. Buffer any standalone usageMetadata on the config instance and attribute the deferred counts to the next emitted response.done (tool-call or normal). In-frame usageMetadata remains authoritative and clears the buffer. * merge main (#28839) * fix(helm): drop main- prefix from default image tag (#28710) * fix(helm): drop main- prefix from default image tag The default image tag in the deployment + migrations-job templates was `main-{{ .Chart.AppVersion }}`. The current release pipeline publishes content tags without the `main-` prefix (e.g. `v1.85.1` / `1.85.1`, `v1.86.0-rc.1` / `1.86.0-rc.1`), so the rendered ref points at a tag that does not exist on GHCR or DockerHub and installs fail with ImagePullBackOff. - templates/deployment.yaml, templates/migrations-job.yaml: render `.Chart.AppVersion` directly instead of `main-<AppVersion>`. - Chart.yaml: bump stale `appVersion: v1.80.12` (not on either registry) to `v1.85.1` so local-checkout installs also resolve. - values.yaml: update the commented tag-override hint to match. * fix(helm): use :latest in tag override example, not pinned version Per review: ghcr.io/berriai/litellm-database:latest is a floating alias for the most recent stable (same digest as :main-stable), maintained by the release pipeline's UPDATE_LATEST advance step. Better example than a pinned version that goes stale. * test(model_prices): allow audio_transcription_config in schema (#28708) The schema in test_aaamodel_prices_and_context_window_json_is_valid uses additionalProperties: false. The azure/speech/azure-stt entry added in #27482 introduced an audio_transcription_config field that the schema did not whitelist, so the test fails on every branch built on top of staging. Add the field as a string property. * fix(team): refresh team cache on team_model_add/delete (LIT-3244) (#28683) * fix(team): refresh team cache on team_model_add/delete (LIT-3244) team_model_add and team_model_delete wrote to the DB but did not invalidate the in-memory LiteLLM_TeamTableCachedObj used by common_checks. After the v1.83.14 common_checks centralization made team.models authoritative on /v1/files and /v1/vector_stores/*, adding a Team-BYOK model silently failed to grant the new public model name to team members until the cache TTL expired (and a removed model kept working until then on the symmetric path). Extract the cache-refresh snippet from update_team into a small helper and apply it consistently at all three team-write sites. * test: also assert updated models in team-cache-refresh pin Strengthens the LIT-3244 regression test to also assert `call_kwargs["team_table"].models` matches the updated row, not just `team_id`. Both `existing_team` and `updated_team` share `team_id` in the test setup, so the previous assertion would have passed even if the implementation accidentally cached the pre-mutation row. Greptile review feedback. * fix(team): hydrate object_permission on cache-refreshing team updates The Prisma update calls in update_team, team_model_add, and team_model_delete returned a team row with object_permission_id set but object_permission=None (the relation was not requested via include=). _refresh_cached_team then wrote that to the in-memory LiteLLM_TeamTableCachedObj, and the cache-hit path in get_team_object returns the cached object without re-hydrating. Downstream consumers (validate_key_search_tools_against_team, the MCP/agent authz paths) treat a missing object_permission as no team-level restriction, so a team-write op silently dropped object-permission enforcement until the cache TTL expired or a DB-fetch path re-hydrated it. Add include={"object_permission": True} to all three updates so the refresh writes a complete cached team. Extend the LIT-3244 regression test to pin both the cached object_permission and the include shape on the Prisma call. Surfaced in PR review of LIT-3244. * fix(ui/add-model): stop vertex_ai-anthropic_models from leaking under Anthropic (#28723) `getProviderModels()` matched a model into a provider's dropdown when the model's `litellm_provider` string *contained* the provider key as a substring. The intent was to admit suffix variants (e.g. `anthropic_text`, `bedrock_converse`), but the substring check is too loose: it also pulls in unrelated providers whose name happens to contain the key, most visibly `vertex_ai-anthropic_models` matching `anthropic` and `vertex_ai-openai_models` matching `openai`. Replace `.includes()` with separator-anchored prefix matching (`startsWith(provider + "_")` / `startsWith(provider + "-")`). All legitimate variants in `model_prices_and_context_window.json` still match (`anthropic_text`, `azure_text`, `azure_ai`, `bedrock_converse`, `bedrock_mantle`, `cohere_chat`, `fireworks_ai-embedding-models`, `vertex_ai-*`, `vertex_ai_beta`), and the cross-provider leak is closed. Tests: update one assertion that pinned the buggy substring behavior (`custom_openai_endpoint` matching `openai` — not a real provider value); add 6 new tests covering the leak regressions and the variant-preservation contract for vertex_ai/bedrock/fireworks. * Fix spend logs v2 route permissions (#28705) Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * fix(proxy): Bedrock Knowledge Base pass-through: preserve SigV4 headers and signed request body (#27526) * Fix Bedrock KB pass-through SigV4 headers and signed body Coerce botocore HeadersDict to a dict for pass-through routes. When forward_headers is true, drop request headers that collide case-insensitively with signed headers so client Bearer auth does not shadow AWS SigV4. Send prepped.body as raw content so the outbound payload matches the signature after logging hooks mutate the parsed dict. Co-authored-by: Cursor <cursoragent@cursor.com> * Simplify pass-through raw body handling Read the SigV4-signed bytes directly from request.state inside pass_through_request instead of threading a custom_raw_body argument through three functions. Helper methods are restored to their original signatures, and the new branch lives in one place at each httpx call site. Co-authored-by: Cursor <cursoragent@cursor.com> * Harden pass-through raw body read from request.state Guard missing request.state (test fixtures) and ignore non-bytes/str values so MagicMock does not trigger the SigV4 raw-body path. Co-authored-by: Cursor <cursoragent@cursor.com> * Test pass_through_request state_raw_body uses httpx content= Cover non-streaming (async_client.request) and streaming (build_request) paths so SigV4 bytes on request.state are not replaced by json= of a hook-mutated dict. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> * chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728) * chore(tests): migrate Bedrock CI from AWS account 888602223428 to 941277531214 The original account (888602223428) was put under a security restriction by AWS after a root access key leaked in a PR comment. While that account works its way through the AWS Support unlock process, Bedrock-touching CI tests have been migrated to a fresh account (941277531214). Changes: - Replace 26 hardcoded references to 888602223428 with 941277531214 across 8 files (provisioned-model ARNs, imported-model ARNs, AgentCore runtime ARNs, batch execution role ARN, and example proxy config). - The provisioned-model and imported-model ARNs are referenced only from mocked unit tests — no AWS resources to recreate. - The batch execution IAM role has been recreated in the new account with the same name and equivalent permissions. - The two AgentCore runtimes (hosted_agent_r9jvp-3ySZuRHjLC, hosted_agent_13sf6-cALnp38iZD) are being recreated in the new account under the same names — see tools/agentcore-deploy/ in a follow-up. CircleCI env vars AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION_NAME were updated separately via the CircleCI API to point at the new account. Smoke-tested locally against the new account: aws bedrock-runtime converse --region us-west-2 \ --model-id us.anthropic.claude-sonnet-4-5-20250929-v1:0 \ --messages '[{"role":"user","content":[{"text":"ping"}]}]' → 200, model returned 'pong' Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): refresh AgentCore ARN suffixes to match newly-deployed runtimes The first migration commit replaced just the account ID, but AgentCore auto-assigns a random 10-char suffix to every runtime on creation — we can't reuse the original suffixes (`3ySZuRHjLC`, `cALnp38iZD`) in the new account. Updated the AgentCore-runtime ARNs in the three files that reference real runtime IDs (not the mock-based unit-test ARNs). Deployed runtimes: arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_r9jvp-Rq79QFC2fp arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_13sf6-4046UzHSwy Both runtimes are status=READY and pass a smoke invoke: $ aws bedrock-agentcore invoke-agent-runtime --agent-runtime-arn ... --payload '{"prompt":"ping"}' → 200, {"result": "echo: ping"} The agent is a minimal echo (see /tmp/agentcore_deploy/agent.py for the deploy artifacts). Tests that only verify the SDK wiring will pass; if any test asserts on agent output content, swap the echo for the real agent. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): point Bedrock batch tests at new-account S3 bucket The account migration (888602223428 -> 941277531214) was a flat account-ID swap, which only rewrites ARNs that embed the account number. S3 bucket names carry no account ID, so the live Bedrock batch tests still uploaded to `litellm-proxy` — a bucket that lives in the old account. S3 names are globally unique, and the old account still holds that name, so it can't be recreated in the new account. Rename to `litellm-proxy-941277531214` (account-ID suffix guarantees global uniqueness). The bucket must be created in 941277531214 and the batch execution role granted s3:GetObject/PutObject/ListBucket on it before this job is run in CI. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): point live S3 logging test at new-account bucket Same account-ID-free blind spot as the batch bucket: `load-testing-oct` lives in the old account and its name can't be reused globally. The `logging_testing` CI job is wired into the workflow and runs test_basic_s3_logging, which uploads to this bucket with the CI env creds, then lists and deletes objects — a live dependency. Rename to `load-testing-oct-941277531214`. The bucket must exist in the new account with the CI IAM principal granted s3:PutObject/GetObject/ListBucket/DeleteObject before this job runs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): repoint Bedrock guardrail IDs to new-account guardrails The migration left guardrail IDs untouched (no account ID in them), so all live guardrail tests failed with "guardrail identifier or version does not exist" against 941277531214. Recreated both guardrails in the new account and updated the hardcoded IDs: - wf0hkdb5x07f -> zgkmukebruil (PII mask: PHONE + CREDIT_DEBIT_CARD, with explicit inputAction=ANONYMIZE so masking applies to INPUT, which is the source litellm's moderation hook sends) - ff6ujrregl1q -> 4w3d1di3snt5 (blocks "coffee"; blocked message set to the exact string the tests assert on) Updated test_bedrock_guardrails.py, otel_test_config.yaml, and the guardrailConfig in test_bedrock_completion.py. Verified locally: the 5 previously-failing guardrail tests now pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): migrate legacy models to current inference profiles The new CI account (941277531214) cannot invoke legacy Bedrock models (AWS gates them: "marked by provider as Legacy... not actively using in the last 30 days"). Migrated the live-call tests: - anthropic.claude-3-sonnet-20240229 -> us.anthropic.claude-sonnet-4-5-20250929-v1:0 - anthropic.claude-3-haiku-20240307 -> us.anthropic.claude-haiku-4-5-20251001-v1:0 Current Claude models on Bedrock require the us. inference-profile prefix (bare on-demand ids are rejected). cohere.command-r-plus has no working replacement (all Cohere is legacy- gated in the new account): swapped to claude-haiku-4-5 in provider- agnostic param lists. amazon.titan-image-generator skipped (no working replacement). Mocked/transformation/cost tests that reference the legacy strings are intentionally left unchanged. Verified live against the new account. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): repoint SageMaker + Knowledge Base to new-account resources These referenced account-scoped resources by hardcoded id that only existed in the old account, so the migration's account-ID swap missed them. Recreated in 941277531214 and repointed: - SageMaker endpoint jumpstart-dft-hf-textgeneration1-mp-20240815-185614 -> litellm-ci-textgen (gpt2 on a TGI container, ml.g5.xlarge) - Bedrock Knowledge Base T37J8R4WTM -> LCYXFBR2TU (OpenSearch Serverless vector store + titan-embed-text-v2, seeded with a LiteLLM doc) Verified live: test_sagemaker.py (12 passed) and test_bedrock_knowledgebase_hook.py (12 passed). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(reasoning_effort_grid): skip bedrock claude-opus-4-7 cells (not entitled on 941277531214) claude-opus-4-7 is listed in the new Bedrock CI account's foundation models but invoke is denied (AccessDeniedException: "not available for this account"). Bedrock access to the flagship Opus requires an AWS Sales request, not the self-serve model-access toggle, so it can't be enabled inline with the rest of the account migration. Add an optional `skip_reason` to ModelEntry and set it on the bedrock-claude-opus-4-7 entry; the grid test honors it via pytest.skip. Cell count (231) and route coverage are unchanged, so the structural asserts still pass. Restore coverage by deleting the one skip_reason line once access is granted. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): swap/skip legacy-gated models unavailable on new CI account The migrated AWS account (941277531214) cannot access several models that the old account could, so the remaining red CI jobs were hitting real Bedrock "Access denied / Legacy" and "account not authorized" errors: - image_gen: skip both Nova Canvas test classes (amazon.nova-canvas-v1:0 is legacy-gated), matching the existing titan skip. - batches: skip test_async_file_and_batch (Bedrock batch inference is not authorized on the new account; requires an AWS support case). - litellm_overhead: swap legacy claude-3-5-haiku for the active us.anthropic.claude-haiku-4-5 inference profile. - test_completion_claude_3_function_call: swap legacy claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): fix remaining e2e legacy-model + batch failures on new CI account - e2e_openai_endpoints: skip test_bedrock_batches_api (Bedrock batch inference is not authorized on account 941277531214) and migrate the missed s3_bucket_name in oai_misc_config.yaml to litellm-proxy-941277531214. - build_and_test: swap legacy bedrock claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile in the proxy structured output e2e test. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): make opus-4-7 + batch cells fail loudly and mock image-gen (#28791) Replace the silent skips added for the new CI account with noisier behavior: - reasoning-effort grid: opus-4-7 cells now fail (when AWS creds are present) instead of skipping, so the missing entitlement stays visible in CI; they still skip when AWS creds are absent (local dev) - Bedrock batch inference tests: drop the skip so they run and fail until batch access is granted - Titan + Nova Canvas image-gen tests: mock the Bedrock HTTP call so the transform + cost-tracking path stays under test without live model access https://claude.ai/code/session_01MT7SWDnXUjv6e6EPG7BDjT Co-authored-by: Claude <noreply@anthropic.com> * test(bedrock): use pytest.xfail for known-failing opus-4-7 cells Replace pytest.fail with pytest.xfail when a model has a fail_reason, so known-broken cells stay visible as XFAIL without keeping CI red. Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(otel): export SERVER span on management-endpoint success without http_request (#28794) Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> * chore(ci): merge dev branch (#28801) * chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> * chore(ci): merge dev branch (#28657) * feat(dashboard): navbar hierarchy + Agent Platform notifications (#27543) * feat(dashboard): refine navbar zones and Agent Platform notice Restructure the admin navbar for production users: clear product vs community vs personal columns with vertical dividers, icon-only Slack/GitHub in a shared chip, and Docs/Blog typography aligned on an 8px rhythm. Add a notifications bell with popover linking to the LiteLLM Agent Platform repo and optional mark-as-read persistence. Promote the account control with initials avatar, single-line display name, and navDisplayName mapping for placeholder user ids (e.g. default_user_id). Co-authored-by: Cursor <cursoragent@cursor.com> * fix(dashboard): address PR review — AntD buttons, public page guard, dedupe regex - Replace raw <button> with AntD Button in BlogDropdown, NotificationsBell, UserDropdown, and test mock - Guard NotificationsBell + container behind !isPublicPage to avoid rendering on public pages - Remove redundant equality checks in navDisplayName (regex already covers them) - Remove unused `lower` variable after simplification Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(dashboard): drop dead useHealthReadiness import in navbar The module was removed in #27896 (replaced by useHealthReadinessDetails), but the import survived the rebase. The symbol is unused — only useHealthReadinessDetails is consumed in the file. Removing the dead import unblocks the UI TypeScript build. * fix(dashboard): align CommunityEngagementButtons test with icon-only aria-labels The component was refactored to an icon-only chip with aria-label='LiteLLM on GitHub' (squash #27543), but the test still asserted /star us on github/i. Update the query to match the rendered accessible name. * refactor(dashboard): drop unused props from NavbarProps The navbar refactor moved user identity + dark-mode state to internal hooks (useAuthorized, useWorker), but the NavbarProps interface still declared userID, userEmail, userRole, premiumUser, isDarkMode, and toggleDarkMode as required, forcing every caller to thread them through. Drop them from the interface and all four call sites (page.tsx, (dashboard)/layout.tsx, public_model_hub.tsx, navbar.test.tsx). Also shrinks the destructure in layout.tsx so the now-unused locals stop being pulled out of useAuthorized(). * refactor(dashboard): use useSyncExternalStore for NotificationsBell dismiss flag Reads/writes of the litellmHideAgentPlatformBanner key were done directly inside NotificationsBell via a useEffect + useState pair. Every other localStorage-backed flag in the dashboard (Disable ShowPrompts, DisableBouncingIcon, DisableShowNewBadge, DisableUsageIndicator, DisableBlogPosts) is wrapped in a useSyncExternalStore hook over localStorageUtils so all mounted components stay in sync. Extract useHideAgentPlatformBanner to follow the same shape, swap NotificationsBell to consume it, and add a regression test that two sibling bells stay in sync without a remount when one is dismissed. * refactor: mask credential fields in proxy settings GET responses (#28682) * refactor: mask credential fields in proxy settings GET responses Brings SSO settings, cache settings, and the email/Slack alerting view in /get/config/callbacks in line with the HashiCorp Vault config-override pattern, so persisted credentials are not transported back to the UI in plaintext. * refactor: harden short-value masking and hoist alerting var constant Closes two review observations: - mask_sensitive_keys now replaces short values (below the visible prefix+suffix length) with an all-mask string instead of returning them unchanged, so a 1-7 character credential is no longer round-tripped verbatim. - _ALERTING_SENSITIVE_VARS is moved out of get_config() to a module-level constant, matching the analogous _SSO_SENSITIVE_FIELDS and _CACHE_SENSITIVE_FIELDS in the SSO and cache endpoint files. --------- Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * fix(ui): show 2-decimal precision for max_budget on key overview (#28809) The Key Info Overview tab's Spend card truncated sub-dollar budgets to "$0" because formatNumberWithCommas defaults to 0 decimals. The Settings tab passes 2; align the overview so a $0.10 budget renders as "$0.10". Resolves LIT-2845 * feat(proxy): allow `llm_api_routes` virtual keys to list MCP servers (#28442) * feat(proxy): allow llm_api_routes virtual keys to list MCP servers Add a new `mcp_discovery_routes` group (GET /v1/mcp/server and GET /v1/mcp/server/{server_id}) and include it in `llm_api_routes` so that virtual keys configured with `allowed_routes=["llm_api_routes"]` can discover the MCP servers they have access to. Previously these calls failed with 'Virtual key is not allowed to call this route. Only allowed to call routes: [llm_api_routes]'. The GET handlers already sanitize the response for restricted virtual keys via `_sanitize_mcp_server_list_for_virtual_key`, stripping credential-bearing fields (url, headers, env). Write methods (POST/PUT/DELETE) on the same paths remain gated by the existing handler-level admin role checks. The new discovery list is intentionally kept OUT of `mcp_inference_routes`, so `is_llm_api_route()` still returns False for these paths — this preserves the existing contract that DISABLE_LLM_API_ENDPOINTS must not block the Admin UI from listing MCP servers. Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * refactor(proxy): make MCP discovery carve-out method-aware Replace the `mcp_discovery_routes` group in `llm_api_routes` with a method-aware special case inside `is_virtual_key_allowed_to_call_route`. Virtual keys with allowed_routes=["llm_api_routes"] are now permitted to call only GET /v1/mcp/server and GET /v1/mcp/server/{server_id} — non-GET methods and multi-segment admin sub-paths fall through to the existing 403. This keeps the general llm_api_routes list free of management paths and avoids accidentally exposing POST/PUT/DELETE writes through the route-check layer. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * chore(ci): merge dev branch (#28807) * chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> * fix(team): keep team_alias cache in sync on _cache_team_object writes (#28737) * fix(team): keep team_alias cache in sync on _cache_team_object writes _cache_team_object wrote only to the team_id:<id> cache key, but the JWT auth path that uses team_alias_jwt_field reads from a separate team_alias:<alias> key (get_team_object_by_alias caches under both keys on miss, but reads only the alias-keyed one). After any team-mutation endpoint (team_model_add, team_model_delete, update_team, the two access-group writes) the team_id cache was refreshed but the team_alias cache stayed stale until TTL — JWT callers using team_alias_jwt_field kept seeing the pre-mutation team for the full cache window. Mirror the write under the alias key inside _cache_team_object so every existing caller stays in sync without further changes. Skip the alias write when team_alias is None/empty so we don't collide across alias-less teams. Surfaced testing the LIT-3244 cherry-pick on patch/1.86.0: the LIT-3244 fix correctly invalidated the team_id cache but the customer's JWT used team_alias_jwt_field, so they kept hitting the stale alias-keyed entry. * fix(team): delete (not overwrite) team_alias cache on _cache_team_object The prior shape of this PR wrote both team_id:<id> AND team_alias:<alias> from _cache_team_object. team_alias is NOT unique in the schema (no @unique on LiteLLM_TeamTable.team_alias), and get_team_object_by_alias enforces uniqueness on its own DB-fetch path (len(teams) > 1 raises). Writing the alias-keyed cache from the generic refresh path bypassed that check: a team admin renaming their team to collide with another team's alias could silently overwrite the cached team for JWT-by-alias auth, swapping the resolved team under that alias for the cache window. Switch the alias-keyed operation from a write to a delete (mirroring the dual-cache delete pattern in _delete_cache_key_object). After every team write, the next JWT-by-alias reader cache-misses and falls through to get_team_object_by_alias, which (a) re-fetches the fresh team from DB, closing the LIT-3244 staleness gap that motivated this PR, and (b) enforces alias uniqueness before populating either cache key. team_id:<id> writes are unchanged — team_id is the table PK and is guaranteed unique. Surfaced in veria-ai review on #28739. * fix(managed-files): anchor model_id regex so it doesn't match llm_output_file_model_id extract_model_id_from_unified_id used `re.search(r"model_id,([^;]+)", ...)` which substring-matches the `model_id,` inside the file-ID encoding's `llm_output_file_model_id,<deployment_uuid>` field. parse_unified_id then fed that deployment UUID back into the auth path as a model candidate via _extract_models_from_managed_resource_id, and every team-BYOK file attach 403'd with: team not allowed to access model. This team can only access models=['openai/*']. Tried to access <deployment-uuid> The team's models list correctly contains the public name (`openai/*`) that target_model_names matches, but the bogus UUID candidate fails the wildcard check first. Anchor the regex to a field boundary (`(?:^|;)model_id,`) so it matches the legitimate top-level `model_id,<value>` field on vector_store unified IDs and skips substring matches inside other fields. File-IDs (which have no top-level `model_id` field) now return None and contribute no spurious UUID candidate. Surfaced reproducing LIT-3244 on patch/1.86.0 with the customer's exact flow: team with openai/* BYOK deployment, JWT-scoped user, POST /v1/vector_stores/{id}/files attaching a file uploaded with target_model_names=openai/gpt-4o. * fix(proxy): hydrate wildcard discovery credentials (#28284) (#28822) * fix(proxy): hydrate wildcard discovery credentials * fix(proxy): constrain wildcard credential hydration Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> * ci: add daily oss-agent-shin branch creation workflow (#28829) Creates litellm_oss_agent_shin_MM_DD_YYYY from main every day at 00:00 UTC. Lets us retarget oss-agent-shin fork PRs onto a canonical branch so CircleCI runs with secrets, without granting the agent write access. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> * test(proxy): add harness for proxy_server.py behavior-pinning (#28827) * test(proxy): add harness for proxy_server.py behavior-pinning Creates tests/test_litellm/proxy/proxy_server/ with: - conftest.py: 11 shared fixtures (app, client, mock_prisma, auth_as, mock_router with parametrized response builders, normalize, etc.) - _coverage_check.py: per-PR coverage gate (line + branch) against a baseline, self-selects target by inspecting which placeholder files have been filled - _pin_check.py: AST-based gate that verifies every pin-list item has >=1 happy + >=1 error test with a real assertion (no status-only) - test_harness_smoke.py: 19 smoke tests covering every fixture + both scripts end-to-end - 26 placeholder test files (one docstring each) reserved for follow-up PRs per the directory ownership in the Notion plan - .coverage_baseline pinned at 0% so future PRs measure deltas against new-tests-only and aren't entangled with the broader scattered test suite Adds a dedicated proxy-server job to test-unit-proxy-endpoints.yml so this directory's runtime + coverage are tracked independently. Plan: https://www.notion.so/36c43b8acdab81ee845fd5365128a2fc * ci(proxy-endpoints): allow workflow_dispatch Lets the workflow be triggered manually on a branch via `gh workflow run`, which is needed for the verify-first flow on workflow changes before opening a PR. * test(proxy): address review feedback on proxy_server harness - conftest.py: anchor sys.path insert to __file__ (Path(__file__).resolve().parents[4]) instead of CWD-relative os.path.abspath("../../../../") which resolved to the wrong directory when pytest is launched from the repo root. - _coverage_check.py: actually read .coverage_baseline and use it as the floor (line_min = max(target, baseline)). Closes the gap between the PR description's "delta semantics" and what the script was doing. With baseline=0.0 today this is a no-op; future PRs that update the baseline cause regressions (test deletions etc.) to trip the gate even if the static PR target is still met. - _pin_check.py: drop unreachable startswith("_") guard (test_*.py glob never yields underscore-prefixed names) and read each test file once instead of twice. * feat(openai): apply regional-processing cost uplift for EU/US data residency (#28626) * feat(openai): apply regional-processing cost uplift for EU/US data residency OpenAI charges a 10% uplift on the latest GPT models when requests are served from a regionalized hostname (eu./us.api.openai.com). Infer the region from `api_base`, expose it on `kwargs["litellm_params"]["data_residency"]`, and multiply the computed cost by a per-model `regional_processing_uplift_multiplier_<region>` field. https://claude.ai/code/session_012ebH44s7ohYxjoix5CXzTW * test: allow regional_processing_uplift_multiplier_{eu,us} in model_prices schema * fix(cost): tighten data_residency inference and restore model_cost in tests - Only infer OpenAI data_residency when custom_llm_provider == "openai"; drop the implicit None fallback so non-OpenAI callers can't accidentally pick up a regional tag from a stray OpenAI hostname. - _local_model_cost_map fixture now snapshots and restores litellm.model_cost and LITELLM_LOCAL_MODEL_COST_MAP so tests don't leak state across the session. * refactor(openai): move data_residency helper under llms/openai * fix: thread data_residency through realtime stream cost calculation Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(cost): thread data_residency through batch_cost_calculator Apply the OpenAI regional-processing uplift multiplier to retrieve_batch cost paths so Batch API requests served via eu./us.api.openai.com are priced at the same uplifted token rates as completions/transcriptions. * refactor(openai): encapsulate provider check inside infer_openai_data_residency Move the custom_llm_provider == "openai" guard from get_litellm_params into the helper itself so the core utility no longer carries provider-specific dispatch logic. Callers pass through the provider unconditionally; the helper returns None for any non-OpenAI provider. * fix(responses): thread data_residency through Responses logging params The Responses API paths build their logging litellm_params dict after provider resolution but did not include data_residency, so cost calc saw None even when the effective api_base was a regional OpenAI host. --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> * Revert "merge main (#28839)" This reverts commit fa956e8c42ea975a452665fedd5c4ecebaab9be8. * fix(gemini-realtime): prevent double-attribution of usageMetadata in multi-key frames Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>	2026-05-26 14:40:42 -07:00
michelligabriele	9c0a98c9f1	fix(proxy): exclude proxy_server_request from its own body snapshot (#28618)	2026-05-26 14:16:12 -07:00
Sameer Kankute	f25648cdad	fix(galileo): support hosted v2 spans API and string output extraction (#28771) ... * fix(galileo): support hosted v2 spans API and string output extraction Use GALILEO_API_KEY with /v2/projects/{id}/spans for Galileo Cloud, keep legacy observe/ingest for username/password deployments, and extract assistant content as a string instead of a message dict. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(galileo): address review — async enterprise auth and message input Use async httpx for enterprise login to avoid blocking the event loop, preserve multi-turn messages in v2 span input, and clean up tests. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(galileo): handle negative TZ offsets, 2xx success, and Pydantic ImageObject serialization Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(galileo): treat any 2xx ingest response as success Use response.is_success so 201 Created clears in_memory_records and avoids duplicate span submissions on subsequent flushes. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(galileo): cast message dict for mypy in convert_content_list_to_str Co-authored-by: Cursor <cursoragent@cursor.com> * merge main (#28835) * fix(proxy): Bedrock Knowledge Base pass-through: preserve SigV4 headers and signed request body (#27526) * Fix Bedrock KB pass-through SigV4 headers and signed body Coerce botocore HeadersDict to a dict for pass-through routes. When forward_headers is true, drop request headers that collide case-insensitively with signed headers so client Bearer auth does not shadow AWS SigV4. Send prepped.body as raw content so the outbound payload matches the signature after logging hooks mutate the parsed dict. Co-authored-by: Cursor <cursoragent@cursor.com> * Simplify pass-through raw body handling Read the SigV4-signed bytes directly from request.state inside pass_through_request instead of threading a custom_raw_body argument through three functions. Helper methods are restored to their original signatures, and the new branch lives in one place at each httpx call site. Co-authored-by: Cursor <cursoragent@cursor.com> * Harden pass-through raw body read from request.state Guard missing request.state (test fixtures) and ignore non-bytes/str values so MagicMock does not trigger the SigV4 raw-body path. Co-authored-by: Cursor <cursoragent@cursor.com> * Test pass_through_request state_raw_body uses httpx content= Cover non-streaming (async_client.request) and streaming (build_request) paths so SigV4 bytes on request.state are not replaced by json= of a hook-mutated dict. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> * chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728) * chore(tests): migrate Bedrock CI from AWS account 888602223428 to 941277531214 The original account (888602223428) was put under a security restriction by AWS after a root access key leaked in a PR comment. While that account works its way through the AWS Support unlock process, Bedrock-touching CI tests have been migrated to a fresh account (941277531214). Changes: - Replace 26 hardcoded references to 888602223428 with 941277531214 across 8 files (provisioned-model ARNs, imported-model ARNs, AgentCore runtime ARNs, batch execution role ARN, and example proxy config). - The provisioned-model and imported-model ARNs are referenced only from mocked unit tests — no AWS resources to recreate. - The batch execution IAM role has been recreated in the new account with the same name and equivalent permissions. - The two AgentCore runtimes (hosted_agent_r9jvp-3ySZuRHjLC, hosted_agent_13sf6-cALnp38iZD) are being recreated in the new account under the same names — see tools/agentcore-deploy/ in a follow-up. CircleCI env vars AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION_NAME were updated separately via the CircleCI API to point at the new account. Smoke-tested locally against the new account: aws bedrock-runtime converse --region us-west-2 \ --model-id us.anthropic.claude-sonnet-4-5-20250929-v1:0 \ --messages '[{"role":"user","content":[{"text":"ping"}]}]' → 200, model returned 'pong' Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): refresh AgentCore ARN suffixes to match newly-deployed runtimes The first migration commit replaced just the account ID, but AgentCore auto-assigns a random 10-char suffix to every runtime on creation — we can't reuse the original suffixes (`3ySZuRHjLC`, `cALnp38iZD`) in the new account. Updated the AgentCore-runtime ARNs in the three files that reference real runtime IDs (not the mock-based unit-test ARNs). Deployed runtimes: arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_r9jvp-Rq79QFC2fp arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_13sf6-4046UzHSwy Both runtimes are status=READY and pass a smoke invoke: $ aws bedrock-agentcore invoke-agent-runtime --agent-runtime-arn ... --payload '{"prompt":"ping"}' → 200, {"result": "echo: ping"} The agent is a minimal echo (see /tmp/agentcore_deploy/agent.py for the deploy artifacts). Tests that only verify the SDK wiring will pass; if any test asserts on agent output content, swap the echo for the real agent. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): point Bedrock batch tests at new-account S3 bucket The account migration (888602223428 -> 941277531214) was a flat account-ID swap, which only rewrites ARNs that embed the account number. S3 bucket names carry no account ID, so the live Bedrock batch tests still uploaded to `litellm-proxy` — a bucket that lives in the old account. S3 names are globally unique, and the old account still holds that name, so it can't be recreated in the new account. Rename to `litellm-proxy-941277531214` (account-ID suffix guarantees global uniqueness). The bucket must be created in 941277531214 and the batch execution role granted s3:GetObject/PutObject/ListBucket on it before this job is run in CI. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): point live S3 logging test at new-account bucket Same account-ID-free blind spot as the batch bucket: `load-testing-oct` lives in the old account and its name can't be reused globally. The `logging_testing` CI job is wired into the workflow and runs test_basic_s3_logging, which uploads to this bucket with the CI env creds, then lists and deletes objects — a live dependency. Rename to `load-testing-oct-941277531214`. The bucket must exist in the new account with the CI IAM principal granted s3:PutObject/GetObject/ListBucket/DeleteObject before this job runs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): repoint Bedrock guardrail IDs to new-account guardrails The migration left guardrail IDs untouched (no account ID in them), so all live guardrail tests failed with "guardrail identifier or version does not exist" against 941277531214. Recreated both guardrails in the new account and updated the hardcoded IDs: - wf0hkdb5x07f -> zgkmukebruil (PII mask: PHONE + CREDIT_DEBIT_CARD, with explicit inputAction=ANONYMIZE so masking applies to INPUT, which is the source litellm's moderation hook sends) - ff6ujrregl1q -> 4w3d1di3snt5 (blocks "coffee"; blocked message set to the exact string the tests assert on) Updated test_bedrock_guardrails.py, otel_test_config.yaml, and the guardrailConfig in test_bedrock_completion.py. Verified locally: the 5 previously-failing guardrail tests now pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): migrate legacy models to current inference profiles The new CI account (941277531214) cannot invoke legacy Bedrock models (AWS gates them: "marked by provider as Legacy... not actively using in the last 30 days"). Migrated the live-call tests: - anthropic.claude-3-sonnet-20240229 -> us.anthropic.claude-sonnet-4-5-20250929-v1:0 - anthropic.claude-3-haiku-20240307 -> us.anthropic.claude-haiku-4-5-20251001-v1:0 Current Claude models on Bedrock require the us. inference-profile prefix (bare on-demand ids are rejected). cohere.command-r-plus has no working replacement (all Cohere is legacy- gated in the new account): swapped to claude-haiku-4-5 in provider- agnostic param lists. amazon.titan-image-generator skipped (no working replacement). Mocked/transformation/cost tests that reference the legacy strings are intentionally left unchanged. Verified live against the new account. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): repoint SageMaker + Knowledge Base to new-account resources These referenced account-scoped resources by hardcoded id that only existed in the old account, so the migration's account-ID swap missed them. Recreated in 941277531214 and repointed: - SageMaker endpoint jumpstart-dft-hf-textgeneration1-mp-20240815-185614 -> litellm-ci-textgen (gpt2 on a TGI container, ml.g5.xlarge) - Bedrock Knowledge Base T37J8R4WTM -> LCYXFBR2TU (OpenSearch Serverless vector store + titan-embed-text-v2, seeded with a LiteLLM doc) Verified live: test_sagemaker.py (12 passed) and test_bedrock_knowledgebase_hook.py (12 passed). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(reasoning_effort_grid): skip bedrock claude-opus-4-7 cells (not entitled on 941277531214) claude-opus-4-7 is listed in the new Bedrock CI account's foundation models but invoke is denied (AccessDeniedException: "not available for this account"). Bedrock access to the flagship Opus requires an AWS Sales request, not the self-serve model-access toggle, so it can't be enabled inline with the rest of the account migration. Add an optional `skip_reason` to ModelEntry and set it on the bedrock-claude-opus-4-7 entry; the grid test honors it via pytest.skip. Cell count (231) and route coverage are unchanged, so the structural asserts still pass. Restore coverage by deleting the one skip_reason line once access is granted. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): swap/skip legacy-gated models unavailable on new CI account The migrated AWS account (941277531214) cannot access several models that the old account could, so the remaining red CI jobs were hitting real Bedrock "Access denied / Legacy" and "account not authorized" errors: - image_gen: skip both Nova Canvas test classes (amazon.nova-canvas-v1:0 is legacy-gated), matching the existing titan skip. - batches: skip test_async_file_and_batch (Bedrock batch inference is not authorized on the new account; requires an AWS support case). - litellm_overhead: swap legacy claude-3-5-haiku for the active us.anthropic.claude-haiku-4-5 inference profile. - test_completion_claude_3_function_call: swap legacy claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): fix remaining e2e legacy-model + batch failures on new CI account - e2e_openai_endpoints: skip test_bedrock_batches_api (Bedrock batch inference is not authorized on account 941277531214) and migrate the missed s3_bucket_name in oai_misc_config.yaml to litellm-proxy-941277531214. - build_and_test: swap legacy bedrock claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile in the proxy structured output e2e test. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): make opus-4-7 + batch cells fail loudly and mock image-gen (#28791) Replace the silent skips added for the new CI account with noisier behavior: - reasoning-effort grid: opus-4-7 cells now fail (when AWS creds are present) instead of skipping, so the missing entitlement stays visible in CI; they still skip when AWS creds are absent (local dev) - Bedrock batch inference tests: drop the skip so they run and fail until batch access is granted - Titan + Nova Canvas image-gen tests: mock the Bedrock HTTP call so the transform + cost-tracking path stays under test without live model access https://claude.ai/code/session_01MT7SWDnXUjv6e6EPG7BDjT Co-authored-by: Claude <noreply@anthropic.com> * test(bedrock): use pytest.xfail for known-failing opus-4-7 cells Replace pytest.fail with pytest.xfail when a model has a fail_reason, so known-broken cells stay visible as XFAIL without keeping CI red. Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(otel): export SERVER span on management-endpoint success without http_request (#28794) Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> * chore(ci): merge dev branch (#28801) * chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> * chore(ci): merge dev branch (#28657) * feat(dashboard): navbar hierarchy + Agent Platform notifications (#27543) * feat(dashboard): refine navbar zones and Agent Platform notice Restructure the admin navbar for production users: clear product vs community vs personal columns with vertical dividers, icon-only Slack/GitHub in a shared chip, and Docs/Blog typography aligned on an 8px rhythm. Add a notifications bell with popover linking to the LiteLLM Agent Platform repo and optional mark-as-read persistence. Promote the account control with initials avatar, single-line display name, and navDisplayName mapping for placeholder user ids (e.g. default_user_id). Co-authored-by: Cursor <cursoragent@cursor.com> * fix(dashboard): address PR review — AntD buttons, public page guard, dedupe regex - Replace raw <button> with AntD Button in BlogDropdown, NotificationsBell, UserDropdown, and test mock - Guard NotificationsBell + container behind !isPublicPage to avoid rendering on public pages - Remove redundant equality checks in navDisplayName (regex already covers them) - Remove unused `lower` variable after simplification Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(dashboard): drop dead useHealthReadiness import in navbar The module was removed in #27896 (replaced by useHealthReadinessDetails), but the import survived the rebase. The symbol is unused — only useHealthReadinessDetails is consumed in the file. Removing the dead import unblocks the UI TypeScript build. * fix(dashboard): align CommunityEngagementButtons test with icon-only aria-labels The component was refactored to an icon-only chip with aria-label='LiteLLM on GitHub' (squash #27543), but the test still asserted /star us on github/i. Update the query to match the rendered accessible name. * refactor(dashboard): drop unused props from NavbarProps The navbar refactor moved user identity + dark-mode state to internal hooks (useAuthorized, useWorker), but the NavbarProps interface still declared userID, userEmail, userRole, premiumUser, isDarkMode, and toggleDarkMode as required, forcing every caller to thread them through. Drop them from the interface and all four call sites (page.tsx, (dashboard)/layout.tsx, public_model_hub.tsx, navbar.test.tsx). Also shrinks the destructure in layout.tsx so the now-unused locals stop being pulled out of useAuthorized(). * refactor(dashboard): use useSyncExternalStore for NotificationsBell dismiss flag Reads/writes of the litellmHideAgentPlatformBanner key were done directly inside NotificationsBell via a useEffect + useState pair. Every other localStorage-backed flag in the dashboard (Disable ShowPrompts, DisableBouncingIcon, DisableShowNewBadge, DisableUsageIndicator, DisableBlogPosts) is wrapped in a useSyncExternalStore hook over localStorageUtils so all mounted components stay in sync. Extract useHideAgentPlatformBanner to follow the same shape, swap NotificationsBell to consume it, and add a regression test that two sibling bells stay in sync without a remount when one is dismissed. * refactor: mask credential fields in proxy settings GET responses (#28682) * refactor: mask credential fields in proxy settings GET responses Brings SSO settings, cache settings, and the email/Slack alerting view in /get/config/callbacks in line with the HashiCorp Vault config-override pattern, so persisted credentials are not transported back to the UI in plaintext. * refactor: harden short-value masking and hoist alerting var constant Closes two review observations: - mask_sensitive_keys now replaces short values (below the visible prefix+suffix length) with an all-mask string instead of returning them unchanged, so a 1-7 character credential is no longer round-tripped verbatim. - _ALERTING_SENSITIVE_VARS is moved out of get_config() to a module-level constant, matching the analogous _SSO_SENSITIVE_FIELDS and _CACHE_SENSITIVE_FIELDS in the SSO and cache endpoint files. --------- Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * fix(ui): show 2-decimal precision for max_budget on key overview (#28809) The Key Info Overview tab's Spend card truncated sub-dollar budgets to "$0" because formatNumberWithCommas defaults to 0 decimals. The Settings tab passes 2; align the overview so a $0.10 budget renders as "$0.10". Resolves LIT-2845 * feat(proxy): allow `llm_api_routes` virtual keys to list MCP servers (#28442) * feat(proxy): allow llm_api_routes virtual keys to list MCP servers Add a new `mcp_discovery_routes` group (GET /v1/mcp/server and GET /v1/mcp/server/{server_id}) and include it in `llm_api_routes` so that virtual keys configured with `allowed_routes=["llm_api_routes"]` can discover the MCP servers they have access to. Previously these calls failed with 'Virtual key is not allowed to call this route. Only allowed to call routes: [llm_api_routes]'. The GET handlers already sanitize the response for restricted virtual keys via `_sanitize_mcp_server_list_for_virtual_key`, stripping credential-bearing fields (url, headers, env). Write methods (POST/PUT/DELETE) on the same paths remain gated by the existing handler-level admin role checks. The new discovery list is intentionally kept OUT of `mcp_inference_routes`, so `is_llm_api_route()` still returns False for these paths — this preserves the existing contract that DISABLE_LLM_API_ENDPOINTS must not block the Admin UI from listing MCP servers. Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * refactor(proxy): make MCP discovery carve-out method-aware Replace the `mcp_discovery_routes` group in `llm_api_routes` with a method-aware special case inside `is_virtual_key_allowed_to_call_route`. Virtual keys with allowed_routes=["llm_api_routes"] are now permitted to call only GET /v1/mcp/server and GET /v1/mcp/server/{server_id} — non-GET methods and multi-segment admin sub-paths fall through to the existing 403. This keeps the general llm_api_routes list free of management paths and avoids accidentally exposing POST/PUT/DELETE writes through the route-check layer. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * chore(ci): merge dev branch (#28807) * chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> * fix(team): keep team_alias cache in sync on _cache_team_object writes (#28737) * fix(team): keep team_alias cache in sync on _cache_team_object writes _cache_team_object wrote only to the team_id:<id> cache key, but the JWT auth path that uses team_alias_jwt_field reads from a separate team_alias:<alias> key (get_team_object_by_alias caches under both keys on miss, but reads only the alias-keyed one). After any team-mutation endpoint (team_model_add, team_model_delete, update_team, the two access-group writes) the team_id cache was refreshed but the team_alias cache stayed stale until TTL — JWT callers using team_alias_jwt_field kept seeing the pre-mutation team for the full cache window. Mirror the write under the alias key inside _cache_team_object so every existing caller stays in sync without further changes. Skip the alias write when team_alias is None/empty so we don't collide across alias-less teams. Surfaced testing the LIT-3244 cherry-pick on patch/1.86.0: the LIT-3244 fix correctly invalidated the team_id cache but the customer's JWT used team_alias_jwt_field, so they kept hitting the stale alias-keyed entry. * fix(team): delete (not overwrite) team_alias cache on _cache_team_object The prior shape of this PR wrote both team_id:<id> AND team_alias:<alias> from _cache_team_object. team_alias is NOT unique in the schema (no @unique on LiteLLM_TeamTable.team_alias), and get_team_object_by_alias enforces uniqueness on its own DB-fetch path (len(teams) > 1 raises). Writing the alias-keyed cache from the generic refresh path bypassed that check: a team admin renaming their team to collide with another team's alias could silently overwrite the cached team for JWT-by-alias auth, swapping the resolved team under that alias for the cache window. Switch the alias-keyed operation from a write to a delete (mirroring the dual-cache delete pattern in _delete_cache_key_object). After every team write, the next JWT-by-alias reader cache-misses and falls through to get_team_object_by_alias, which (a) re-fetches the fresh team from DB, closing the LIT-3244 staleness gap that motivated this PR, and (b) enforces alias uniqueness before populating either cache key. team_id:<id> writes are unchanged — team_id is the table PK and is guaranteed unique. Surfaced in veria-ai review on #28739. * fix(managed-files): anchor model_id regex so it doesn't match llm_output_file_model_id extract_model_id_from_unified_id used `re.search(r"model_id,([^;]+)", ...)` which substring-matches the `model_id,` inside the file-ID encoding's `llm_output_file_model_id,<deployment_uuid>` field. parse_unified_id then fed that deployment UUID back into the auth path as a model candidate via _extract_models_from_managed_resource_id, and every team-BYOK file attach 403'd with: team not allowed to access model. This team can only access models=['openai/*']. Tried to access <deployment-uuid> The team's models list correctly contains the public name (`openai/*`) that target_model_names matches, but the bogus UUID candidate fails the wildcard check first. Anchor the regex to a field boundary (`(?:^|;)model_id,`) so it matches the legitimate top-level `model_id,<value>` field on vector_store unified IDs and skips substring matches inside other fields. File-IDs (which have no top-level `model_id` field) now return None and contribute no spurious UUID candidate. Surfaced reproducing LIT-3244 on patch/1.86.0 with the customer's exact flow: team with openai/* BYOK deployment, JWT-scoped user, POST /v1/vector_stores/{id}/files attaching a file uploaded with target_model_names=openai/gpt-4o. * fix(proxy): hydrate wildcard discovery credentials (#28284) (#28822) * fix(proxy): hydrate wildcard discovery credentials * fix(proxy): constrain wildcard credential hydration Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> * ci: add daily oss-agent-shin branch creation workflow (#28829) Creates litellm_oss_agent_shin_MM_DD_YYYY from main every day at 00:00 UTC. Lets us retarget oss-agent-shin fork PRs onto a canonical branch so CircleCI runs with secrets, without granting the agent write access. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> * test(proxy): add harness for proxy_server.py behavior-pinning (#28827) * test(proxy): add harness for proxy_server.py behavior-pinning Creates tests/test_litellm/proxy/proxy_server/ with: - conftest.py: 11 shared fixtures (app, client, mock_prisma, auth_as, mock_router with parametrized response builders, normalize, etc.) - _coverage_check.py: per-PR coverage gate (line + branch) against a baseline, self-selects target by inspecting which placeholder files have been filled - _pin_check.py: AST-based gate that verifies every pin-list item has >=1 happy + >=1 error test with a real assertion (no status-only) - test_harness_smoke.py: 19 smoke tests covering every fixture + both scripts end-to-end - 26 placeholder test files (one docstring each) reserved for follow-up PRs per the directory ownership in the Notion plan - .coverage_baseline pinned at 0% so future PRs measure deltas against new-tests-only and aren't entangled with the broader scattered test suite Adds a dedicated proxy-server job to test-unit-proxy-endpoints.yml so this directory's runtime + coverage are tracked independently. Plan: https://www.notion.so/36c43b8acdab81ee845fd5365128a2fc * ci(proxy-endpoints): allow workflow_dispatch Lets the workflow be triggered manually on a branch via `gh workflow run`, which is needed for the verify-first flow on workflow changes before opening a PR. * test(proxy): address review feedback on proxy_server harness - conftest.py: anchor sys.path insert to __file__ (Path(__file__).resolve().parents[4]) instead of CWD-relative os.path.abspath("../../../../") which resolved to the wrong directory when pytest is launched from the repo root. - _coverage_check.py: actually read .coverage_baseline and use it as the floor (line_min = max(target, baseline)). Closes the gap between the PR description's "delta semantics" and what the script was doing. With baseline=0.0 today this is a no-op; future PRs that update the baseline cause regressions (test deletions etc.) to trip the gate even if the static PR target is still met. - _pin_check.py: drop unreachable startswith("_") guard (test_*.py glob never yields underscore-prefixed names) and read each test file once instead of twice. * feat(openai): apply regional-processing cost uplift for EU/US data residency (#28626) * feat(openai): apply regional-processing cost uplift for EU/US data residency OpenAI charges a 10% uplift on the latest GPT models when requests are served from a regionalized hostname (eu./us.api.openai.com). Infer the region from `api_base`, expose it on `kwargs["litellm_params"]["data_residency"]`, and multiply the computed cost by a per-model `regional_processing_uplift_multiplier_<region>` field. https://claude.ai/code/session_012ebH44s7ohYxjoix5CXzTW * test: allow regional_processing_uplift_multiplier_{eu,us} in model_prices schema * fix(cost): tighten data_residency inference and restore model_cost in tests - Only infer OpenAI data_residency when custom_llm_provider == "openai"; drop the implicit None fallback so non-OpenAI callers can't accidentally pick up a regional tag from a stray OpenAI hostname. - _local_model_cost_map fixture now snapshots and restores litellm.model_cost and LITELLM_LOCAL_MODEL_COST_MAP so tests don't leak state across the session. * refactor(openai): move data_residency helper under llms/openai * fix: thread data_residency through realtime stream cost calculation Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(cost): thread data_residency through batch_cost_calculator Apply the OpenAI regional-processing uplift multiplier to retrieve_batch cost paths so Batch API requests served via eu./us.api.openai.com are priced at the same uplifted token rates as completions/transcriptions. * refactor(openai): encapsulate provider check inside infer_openai_data_residency Move the custom_llm_provider == "openai" guard from get_litellm_params into the helper itself so the core utility no longer carries provider-specific dispatch logic. Callers pass through the provider unconditionally; the helper returns None for any non-OpenAI provider. * fix(responses): thread data_residency through Responses logging params The Responses API paths build their logging litellm_params dict after provider resolution but did not include data_residency, so cost calc saw None even when the effective api_base was a regional OpenAI host. --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> * fix: preserve OTEL response payload and remove duplicate constant - Remove duplicate _CREDENTIAL_LITELLM_PARAM_FIELDS assignment in model_checks - Restore response=dict(result) in _emit_management_endpoint_otel_span so OTEL spans for successful management endpoint calls include response data Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix: harden OTEL failure path and cap Galileo in-memory buffer - Wrap _emit_management_endpoint_otel_span in try/except on the failure path of management_endpoint_wrapper so OTEL errors cannot swallow the original management-endpoint exception. - Bound GalileoObserve.in_memory_records at GALILEO_MAX_IN_MEMORY_RECORDS to prevent unbounded memory growth when flushes persistently fail. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(galileo): reset stale bearer token on auth error; preserve records under concurrency - Snapshot record count before await so concurrent appends during the network round-trip aren't silently dropped when clearing the buffer. - Build payload from a snapshot list so the legacy path no longer shares a live reference with self.in_memory_records. - On legacy enterprise auth (username/password), drop cached bearer-token headers when the upstream rejects the request (401/403) so the next flush re-authenticates instead of failing forever on a stale token. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(galileo): expand v2 coverage for config, ingest, headers, and flush paths --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>	2026-05-26 14:10:33 -07:00
ryan-crabbe-berri	123a9ce487	fix(mcp): extend key access-group union to MCP servers (#28890) ... A key's unified access_group_ids now extend the team's MCP scope instead of being capped by it — mirrors the model-side union from LIT-2404. The group's assigned_team_ids / assigned_key_ids still gate the override, so team members can't pull in MCPs via a foreign team's group. Resolves LIT-3189	2026-05-26 12:55:06 -07:00
Sameer Kankute	79a4909c75	fix(realtime): send TEXT frames and valid guardrail session.update (#28848) ... * fix(realtime): send TEXT frames and valid guardrail session.update Decode backend recv bytes before send_text so clients receive OP_TEXT JSON events. Include turn_detection.type server_vad in injected session.update. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(realtime): skip non-UTF-8 backend binary frames Avoid terminating the forwarding loop on UnicodeDecodeError when the backend sends unexpected binary payloads. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>	2026-05-26 11:58:46 -07:00
Sameer Kankute	f17dfcd869	fix(bedrock): align toolUse/toolSpec names and allow hyphens (#28874) ... * fix(bedrock): align toolUse/toolSpec names and allow hyphens in tool names Sanitize tool names consistently in tool history and tool_choice, and preserve hyphens per current Bedrock [a-zA-Z0-9_-]+ constraint. Co-authored-by: Cursor <cursoragent@cursor.com> * docs(bedrock): docstring matches alpha-first tool name normalization Greptile: pattern is [a-zA-Z][a-zA-Z0-9_-]* to reflect prepend-'a' behavior. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>	2026-05-26 11:58:21 -07:00
Sameer Kankute	d52fbfb458	Litellm oss staging 250526 (#28770) ... * fix(mcp): handle OAuth IdP error responses in /callback (LIT-2750) Per RFC 6749 section 4.1.2.1, when the IdP rejects an OAuth authorization request it redirects back to the client with ?error=...&error_description=... and no code. The MCP /callback handler declared code and state as required query params, so FastAPI rejected such error responses with a 422 before the handler ran -- stranding the MCP client waiting on the loopback. This change: - Makes code and state optional and accepts the RFC-defined error, error_description, and error_uri params. - When state decodes to a trusted client redirect_uri, propagates the error params back to that URI with the client's original (un-wrapped) state preserved, so the client's OAuth library can surface the failure. - When state is missing/undecryptable or the encoded redirect_uri is no longer trusted, renders a 400 HTML page with the (HTML-escaped) error details instead of leaking to an attacker-controlled redirect. - Preserves the existing success path (code + state -> 302 to validated client redirect_uri with original state). Fixes LIT-2750. * test(mcp): regression tests for /callback handling IdP error responses (LIT-2750) Adds a new test module covering the LIT-2750 fix: the MCP OAuth /callback endpoint must accept IdP error responses (e.g. ?error=access_denied) per RFC 6749 section 4.1.2.1 instead of returning a 422 because ``code`` is missing. Coverage: - IdP error with no state -> 400 HTML page surfacing the error. - HTML escaping of user-controlled error / error_description fields. - IdP error with a trusted (loopback) state -> 302 propagating error / error_description / original client state to the client. - IdP error with an untrusted redirect_uri encoded in state -> 400 inline (no open-redirect to attacker-controlled origin). - IdP error with an undecryptable state -> 400 HTML fallback. - Bare GET /callback with no params -> 400 HTML (not Pydantic 422). - Success path (code + state) still 302 to validated client redirect_uri with the original (un-wrapped) state preserved. * refactor(mcp): drop unused _OAUTH_ERROR_PARAMS constant (Greptile P2) The tuple was leftover scaffolding from an earlier draft of the LIT-2750 fix; nothing references it. The explanatory RFC 6749 §4.1.2.1 comment block above the callback handler covers the same intent. * fix(mcp/oauth): preserve empty original_state and clarify missing-param error in /callback Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(thinking): handle None thinking param in is_thinking_enabled (#28598) Squash-merged by litellm-agent from Terrajlz's PR. * feat(helm): support tpl rendering in podAnnotations (#28609) Squash-merged by litellm-agent from devauxbr's PR. * fix: apply black formatting to base_llm chat transformation Fix CI black --check failure on is_thinking_enabled return formatting. Co-authored-by: Cursor <cursoragent@cursor.com> * merge main (#28836) * fix(proxy): Bedrock Knowledge Base pass-through: preserve SigV4 headers and signed request body (#27526) * Fix Bedrock KB pass-through SigV4 headers and signed body Coerce botocore HeadersDict to a dict for pass-through routes. When forward_headers is true, drop request headers that collide case-insensitively with signed headers so client Bearer auth does not shadow AWS SigV4. Send prepped.body as raw content so the outbound payload matches the signature after logging hooks mutate the parsed dict. Co-authored-by: Cursor <cursoragent@cursor.com> * Simplify pass-through raw body handling Read the SigV4-signed bytes directly from request.state inside pass_through_request instead of threading a custom_raw_body argument through three functions. Helper methods are restored to their original signatures, and the new branch lives in one place at each httpx call site. Co-authored-by: Cursor <cursoragent@cursor.com> * Harden pass-through raw body read from request.state Guard missing request.state (test fixtures) and ignore non-bytes/str values so MagicMock does not trigger the SigV4 raw-body path. Co-authored-by: Cursor <cursoragent@cursor.com> * Test pass_through_request state_raw_body uses httpx content= Cover non-streaming (async_client.request) and streaming (build_request) paths so SigV4 bytes on request.state are not replaced by json= of a hook-mutated dict. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> * chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728) * chore(tests): migrate Bedrock CI from AWS account 888602223428 to 941277531214 The original account (888602223428) was put under a security restriction by AWS after a root access key leaked in a PR comment. While that account works its way through the AWS Support unlock process, Bedrock-touching CI tests have been migrated to a fresh account (941277531214). Changes: - Replace 26 hardcoded references to 888602223428 with 941277531214 across 8 files (provisioned-model ARNs, imported-model ARNs, AgentCore runtime ARNs, batch execution role ARN, and example proxy config). - The provisioned-model and imported-model ARNs are referenced only from mocked unit tests — no AWS resources to recreate. - The batch execution IAM role has been recreated in the new account with the same name and equivalent permissions. - The two AgentCore runtimes (hosted_agent_r9jvp-3ySZuRHjLC, hosted_agent_13sf6-cALnp38iZD) are being recreated in the new account under the same names — see tools/agentcore-deploy/ in a follow-up. CircleCI env vars AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION_NAME were updated separately via the CircleCI API to point at the new account. Smoke-tested locally against the new account: aws bedrock-runtime converse --region us-west-2 \ --model-id us.anthropic.claude-sonnet-4-5-20250929-v1:0 \ --messages '[{"role":"user","content":[{"text":"ping"}]}]' → 200, model returned 'pong' Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): refresh AgentCore ARN suffixes to match newly-deployed runtimes The first migration commit replaced just the account ID, but AgentCore auto-assigns a random 10-char suffix to every runtime on creation — we can't reuse the original suffixes (`3ySZuRHjLC`, `cALnp38iZD`) in the new account. Updated the AgentCore-runtime ARNs in the three files that reference real runtime IDs (not the mock-based unit-test ARNs). Deployed runtimes: arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_r9jvp-Rq79QFC2fp arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_13sf6-4046UzHSwy Both runtimes are status=READY and pass a smoke invoke: $ aws bedrock-agentcore invoke-agent-runtime --agent-runtime-arn ... --payload '{"prompt":"ping"}' → 200, {"result": "echo: ping"} The agent is a minimal echo (see /tmp/agentcore_deploy/agent.py for the deploy artifacts). Tests that only verify the SDK wiring will pass; if any test asserts on agent output content, swap the echo for the real agent. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): point Bedrock batch tests at new-account S3 bucket The account migration (888602223428 -> 941277531214) was a flat account-ID swap, which only rewrites ARNs that embed the account number. S3 bucket names carry no account ID, so the live Bedrock batch tests still uploaded to `litellm-proxy` — a bucket that lives in the old account. S3 names are globally unique, and the old account still holds that name, so it can't be recreated in the new account. Rename to `litellm-proxy-941277531214` (account-ID suffix guarantees global uniqueness). The bucket must be created in 941277531214 and the batch execution role granted s3:GetObject/PutObject/ListBucket on it before this job is run in CI. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): point live S3 logging test at new-account bucket Same account-ID-free blind spot as the batch bucket: `load-testing-oct` lives in the old account and its name can't be reused globally. The `logging_testing` CI job is wired into the workflow and runs test_basic_s3_logging, which uploads to this bucket with the CI env creds, then lists and deletes objects — a live dependency. Rename to `load-testing-oct-941277531214`. The bucket must exist in the new account with the CI IAM principal granted s3:PutObject/GetObject/ListBucket/DeleteObject before this job runs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): repoint Bedrock guardrail IDs to new-account guardrails The migration left guardrail IDs untouched (no account ID in them), so all live guardrail tests failed with "guardrail identifier or version does not exist" against 941277531214. Recreated both guardrails in the new account and updated the hardcoded IDs: - wf0hkdb5x07f -> zgkmukebruil (PII mask: PHONE + CREDIT_DEBIT_CARD, with explicit inputAction=ANONYMIZE so masking applies to INPUT, which is the source litellm's moderation hook sends) - ff6ujrregl1q -> 4w3d1di3snt5 (blocks "coffee"; blocked message set to the exact string the tests assert on) Updated test_bedrock_guardrails.py, otel_test_config.yaml, and the guardrailConfig in test_bedrock_completion.py. Verified locally: the 5 previously-failing guardrail tests now pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): migrate legacy models to current inference profiles The new CI account (941277531214) cannot invoke legacy Bedrock models (AWS gates them: "marked by provider as Legacy... not actively using in the last 30 days"). Migrated the live-call tests: - anthropic.claude-3-sonnet-20240229 -> us.anthropic.claude-sonnet-4-5-20250929-v1:0 - anthropic.claude-3-haiku-20240307 -> us.anthropic.claude-haiku-4-5-20251001-v1:0 Current Claude models on Bedrock require the us. inference-profile prefix (bare on-demand ids are rejected). cohere.command-r-plus has no working replacement (all Cohere is legacy- gated in the new account): swapped to claude-haiku-4-5 in provider- agnostic param lists. amazon.titan-image-generator skipped (no working replacement). Mocked/transformation/cost tests that reference the legacy strings are intentionally left unchanged. Verified live against the new account. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): repoint SageMaker + Knowledge Base to new-account resources These referenced account-scoped resources by hardcoded id that only existed in the old account, so the migration's account-ID swap missed them. Recreated in 941277531214 and repointed: - SageMaker endpoint jumpstart-dft-hf-textgeneration1-mp-20240815-185614 -> litellm-ci-textgen (gpt2 on a TGI container, ml.g5.xlarge) - Bedrock Knowledge Base T37J8R4WTM -> LCYXFBR2TU (OpenSearch Serverless vector store + titan-embed-text-v2, seeded with a LiteLLM doc) Verified live: test_sagemaker.py (12 passed) and test_bedrock_knowledgebase_hook.py (12 passed). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(reasoning_effort_grid): skip bedrock claude-opus-4-7 cells (not entitled on 941277531214) claude-opus-4-7 is listed in the new Bedrock CI account's foundation models but invoke is denied (AccessDeniedException: "not available for this account"). Bedrock access to the flagship Opus requires an AWS Sales request, not the self-serve model-access toggle, so it can't be enabled inline with the rest of the account migration. Add an optional `skip_reason` to ModelEntry and set it on the bedrock-claude-opus-4-7 entry; the grid test honors it via pytest.skip. Cell count (231) and route coverage are unchanged, so the structural asserts still pass. Restore coverage by deleting the one skip_reason line once access is granted. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): swap/skip legacy-gated models unavailable on new CI account The migrated AWS account (941277531214) cannot access several models that the old account could, so the remaining red CI jobs were hitting real Bedrock "Access denied / Legacy" and "account not authorized" errors: - image_gen: skip both Nova Canvas test classes (amazon.nova-canvas-v1:0 is legacy-gated), matching the existing titan skip. - batches: skip test_async_file_and_batch (Bedrock batch inference is not authorized on the new account; requires an AWS support case). - litellm_overhead: swap legacy claude-3-5-haiku for the active us.anthropic.claude-haiku-4-5 inference profile. - test_completion_claude_3_function_call: swap legacy claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): fix remaining e2e legacy-model + batch failures on new CI account - e2e_openai_endpoints: skip test_bedrock_batches_api (Bedrock batch inference is not authorized on account 941277531214) and migrate the missed s3_bucket_name in oai_misc_config.yaml to litellm-proxy-941277531214. - build_and_test: swap legacy bedrock claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile in the proxy structured output e2e test. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): make opus-4-7 + batch cells fail loudly and mock image-gen (#28791) Replace the silent skips added for the new CI account with noisier behavior: - reasoning-effort grid: opus-4-7 cells now fail (when AWS creds are present) instead of skipping, so the missing entitlement stays visible in CI; they still skip when AWS creds are absent (local dev) - Bedrock batch inference tests: drop the skip so they run and fail until batch access is granted - Titan + Nova Canvas image-gen tests: mock the Bedrock HTTP call so the transform + cost-tracking path stays under test without live model access https://claude.ai/code/session_01MT7SWDnXUjv6e6EPG7BDjT Co-authored-by: Claude <noreply@anthropic.com> * test(bedrock): use pytest.xfail for known-failing opus-4-7 cells Replace pytest.fail with pytest.xfail when a model has a fail_reason, so known-broken cells stay visible as XFAIL without keeping CI red. Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(otel): export SERVER span on management-endpoint success without http_request (#28794) Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> * chore(ci): merge dev branch (#28801) * chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> * chore(ci): merge dev branch (#28657) * feat(dashboard): navbar hierarchy + Agent Platform notifications (#27543) * feat(dashboard): refine navbar zones and Agent Platform notice Restructure the admin navbar for production users: clear product vs community vs personal columns with vertical dividers, icon-only Slack/GitHub in a shared chip, and Docs/Blog typography aligned on an 8px rhythm. Add a notifications bell with popover linking to the LiteLLM Agent Platform repo and optional mark-as-read persistence. Promote the account control with initials avatar, single-line display name, and navDisplayName mapping for placeholder user ids (e.g. default_user_id). Co-authored-by: Cursor <cursoragent@cursor.com> * fix(dashboard): address PR review — AntD buttons, public page guard, dedupe regex - Replace raw <button> with AntD Button in BlogDropdown, NotificationsBell, UserDropdown, and test mock - Guard NotificationsBell + container behind !isPublicPage to avoid rendering on public pages - Remove redundant equality checks in navDisplayName (regex already covers them) - Remove unused `lower` variable after simplification Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(dashboard): drop dead useHealthReadiness import in navbar The module was removed in #27896 (replaced by useHealthReadinessDetails), but the import survived the rebase. The symbol is unused — only useHealthReadinessDetails is consumed in the file. Removing the dead import unblocks the UI TypeScript build. * fix(dashboard): align CommunityEngagementButtons test with icon-only aria-labels The component was refactored to an icon-only chip with aria-label='LiteLLM on GitHub' (squash #27543), but the test still asserted /star us on github/i. Update the query to match the rendered accessible name. * refactor(dashboard): drop unused props from NavbarProps The navbar refactor moved user identity + dark-mode state to internal hooks (useAuthorized, useWorker), but the NavbarProps interface still declared userID, userEmail, userRole, premiumUser, isDarkMode, and toggleDarkMode as required, forcing every caller to thread them through. Drop them from the interface and all four call sites (page.tsx, (dashboard)/layout.tsx, public_model_hub.tsx, navbar.test.tsx). Also shrinks the destructure in layout.tsx so the now-unused locals stop being pulled out of useAuthorized(). * refactor(dashboard): use useSyncExternalStore for NotificationsBell dismiss flag Reads/writes of the litellmHideAgentPlatformBanner key were done directly inside NotificationsBell via a useEffect + useState pair. Every other localStorage-backed flag in the dashboard (Disable ShowPrompts, DisableBouncingIcon, DisableShowNewBadge, DisableUsageIndicator, DisableBlogPosts) is wrapped in a useSyncExternalStore hook over localStorageUtils so all mounted components stay in sync. Extract useHideAgentPlatformBanner to follow the same shape, swap NotificationsBell to consume it, and add a regression test that two sibling bells stay in sync without a remount when one is dismissed. * refactor: mask credential fields in proxy settings GET responses (#28682) * refactor: mask credential fields in proxy settings GET responses Brings SSO settings, cache settings, and the email/Slack alerting view in /get/config/callbacks in line with the HashiCorp Vault config-override pattern, so persisted credentials are not transported back to the UI in plaintext. * refactor: harden short-value masking and hoist alerting var constant Closes two review observations: - mask_sensitive_keys now replaces short values (below the visible prefix+suffix length) with an all-mask string instead of returning them unchanged, so a 1-7 character credential is no longer round-tripped verbatim. - _ALERTING_SENSITIVE_VARS is moved out of get_config() to a module-level constant, matching the analogous _SSO_SENSITIVE_FIELDS and _CACHE_SENSITIVE_FIELDS in the SSO and cache endpoint files. --------- Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * fix(ui): show 2-decimal precision for max_budget on key overview (#28809) The Key Info Overview tab's Spend card truncated sub-dollar budgets to "$0" because formatNumberWithCommas defaults to 0 decimals. The Settings tab passes 2; align the overview so a $0.10 budget renders as "$0.10". Resolves LIT-2845 * feat(proxy): allow `llm_api_routes` virtual keys to list MCP servers (#28442) * feat(proxy): allow llm_api_routes virtual keys to list MCP servers Add a new `mcp_discovery_routes` group (GET /v1/mcp/server and GET /v1/mcp/server/{server_id}) and include it in `llm_api_routes` so that virtual keys configured with `allowed_routes=["llm_api_routes"]` can discover the MCP servers they have access to. Previously these calls failed with 'Virtual key is not allowed to call this route. Only allowed to call routes: [llm_api_routes]'. The GET handlers already sanitize the response for restricted virtual keys via `_sanitize_mcp_server_list_for_virtual_key`, stripping credential-bearing fields (url, headers, env). Write methods (POST/PUT/DELETE) on the same paths remain gated by the existing handler-level admin role checks. The new discovery list is intentionally kept OUT of `mcp_inference_routes`, so `is_llm_api_route()` still returns False for these paths — this preserves the existing contract that DISABLE_LLM_API_ENDPOINTS must not block the Admin UI from listing MCP servers. Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * refactor(proxy): make MCP discovery carve-out method-aware Replace the `mcp_discovery_routes` group in `llm_api_routes` with a method-aware special case inside `is_virtual_key_allowed_to_call_route`. Virtual keys with allowed_routes=["llm_api_routes"] are now permitted to call only GET /v1/mcp/server and GET /v1/mcp/server/{server_id} — non-GET methods and multi-segment admin sub-paths fall through to the existing 403. This keeps the general llm_api_routes list free of management paths and avoids accidentally exposing POST/PUT/DELETE writes through the route-check layer. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * chore(ci): merge dev branch (#28807) * chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> * fix(team): keep team_alias cache in sync on _cache_team_object writes (#28737) * fix(team): keep team_alias cache in sync on _cache_team_object writes _cache_team_object wrote only to the team_id:<id> cache key, but the JWT auth path that uses team_alias_jwt_field reads from a separate team_alias:<alias> key (get_team_object_by_alias caches under both keys on miss, but reads only the alias-keyed one). After any team-mutation endpoint (team_model_add, team_model_delete, update_team, the two access-group writes) the team_id cache was refreshed but the team_alias cache stayed stale until TTL — JWT callers using team_alias_jwt_field kept seeing the pre-mutation team for the full cache window. Mirror the write under the alias key inside _cache_team_object so every existing caller stays in sync without further changes. Skip the alias write when team_alias is None/empty so we don't collide across alias-less teams. Surfaced testing the LIT-3244 cherry-pick on patch/1.86.0: the LIT-3244 fix correctly invalidated the team_id cache but the customer's JWT used team_alias_jwt_field, so they kept hitting the stale alias-keyed entry. * fix(team): delete (not overwrite) team_alias cache on _cache_team_object The prior shape of this PR wrote both team_id:<id> AND team_alias:<alias> from _cache_team_object. team_alias is NOT unique in the schema (no @unique on LiteLLM_TeamTable.team_alias), and get_team_object_by_alias enforces uniqueness on its own DB-fetch path (len(teams) > 1 raises). Writing the alias-keyed cache from the generic refresh path bypassed that check: a team admin renaming their team to collide with another team's alias could silently overwrite the cached team for JWT-by-alias auth, swapping the resolved team under that alias for the cache window. Switch the alias-keyed operation from a write to a delete (mirroring the dual-cache delete pattern in _delete_cache_key_object). After every team write, the next JWT-by-alias reader cache-misses and falls through to get_team_object_by_alias, which (a) re-fetches the fresh team from DB, closing the LIT-3244 staleness gap that motivated this PR, and (b) enforces alias uniqueness before populating either cache key. team_id:<id> writes are unchanged — team_id is the table PK and is guaranteed unique. Surfaced in veria-ai review on #28739. * fix(managed-files): anchor model_id regex so it doesn't match llm_output_file_model_id extract_model_id_from_unified_id used `re.search(r"model_id,([^;]+)", ...)` which substring-matches the `model_id,` inside the file-ID encoding's `llm_output_file_model_id,<deployment_uuid>` field. parse_unified_id then fed that deployment UUID back into the auth path as a model candidate via _extract_models_from_managed_resource_id, and every team-BYOK file attach 403'd with: team not allowed to access model. This team can only access models=['openai/*']. Tried to access <deployment-uuid> The team's models list correctly contains the public name (`openai/*`) that target_model_names matches, but the bogus UUID candidate fails the wildcard check first. Anchor the regex to a field boundary (`(?:^|;)model_id,`) so it matches the legitimate top-level `model_id,<value>` field on vector_store unified IDs and skips substring matches inside other fields. File-IDs (which have no top-level `model_id` field) now return None and contribute no spurious UUID candidate. Surfaced reproducing LIT-3244 on patch/1.86.0 with the customer's exact flow: team with openai/* BYOK deployment, JWT-scoped user, POST /v1/vector_stores/{id}/files attaching a file uploaded with target_model_names=openai/gpt-4o. * fix(proxy): hydrate wildcard discovery credentials (#28284) (#28822) * fix(proxy): hydrate wildcard discovery credentials * fix(proxy): constrain wildcard credential hydration Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> * ci: add daily oss-agent-shin branch creation workflow (#28829) Creates litellm_oss_agent_shin_MM_DD_YYYY from main every day at 00:00 UTC. Lets us retarget oss-agent-shin fork PRs onto a canonical branch so CircleCI runs with secrets, without granting the agent write access. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> * test(proxy): add harness for proxy_server.py behavior-pinning (#28827) * test(proxy): add harness for proxy_server.py behavior-pinning Creates tests/test_litellm/proxy/proxy_server/ with: - conftest.py: 11 shared fixtures (app, client, mock_prisma, auth_as, mock_router with parametrized response builders, normalize, etc.) - _coverage_check.py: per-PR coverage gate (line + branch) against a baseline, self-selects target by inspecting which placeholder files have been filled - _pin_check.py: AST-based gate that verifies every pin-list item has >=1 happy + >=1 error test with a real assertion (no status-only) - test_harness_smoke.py: 19 smoke tests covering every fixture + both scripts end-to-end - 26 placeholder test files (one docstring each) reserved for follow-up PRs per the directory ownership in the Notion plan - .coverage_baseline pinned at 0% so future PRs measure deltas against new-tests-only and aren't entangled with the broader scattered test suite Adds a dedicated proxy-server job to test-unit-proxy-endpoints.yml so this directory's runtime + coverage are tracked independently. Plan: https://www.notion.so/36c43b8acdab81ee845fd5365128a2fc * ci(proxy-endpoints): allow workflow_dispatch Lets the workflow be triggered manually on a branch via `gh workflow run`, which is needed for the verify-first flow on workflow changes before opening a PR. * test(proxy): address review feedback on proxy_server harness - conftest.py: anchor sys.path insert to __file__ (Path(__file__).resolve().parents[4]) instead of CWD-relative os.path.abspath("../../../../") which resolved to the wrong directory when pytest is launched from the repo root. - _coverage_check.py: actually read .coverage_baseline and use it as the floor (line_min = max(target, baseline)). Closes the gap between the PR description's "delta semantics" and what the script was doing. With baseline=0.0 today this is a no-op; future PRs that update the baseline cause regressions (test deletions etc.) to trip the gate even if the static PR target is still met. - _pin_check.py: drop unreachable startswith("_") guard (test_*.py glob never yields underscore-prefixed names) and read each test file once instead of twice. * feat(openai): apply regional-processing cost uplift for EU/US data residency (#28626) * feat(openai): apply regional-processing cost uplift for EU/US data residency OpenAI charges a 10% uplift on the latest GPT models when requests are served from a regionalized hostname (eu./us.api.openai.com). Infer the region from `api_base`, expose it on `kwargs["litellm_params"]["data_residency"]`, and multiply the computed cost by a per-model `regional_processing_uplift_multiplier_<region>` field. https://claude.ai/code/session_012ebH44s7ohYxjoix5CXzTW * test: allow regional_processing_uplift_multiplier_{eu,us} in model_prices schema * fix(cost): tighten data_residency inference and restore model_cost in tests - Only infer OpenAI data_residency when custom_llm_provider == "openai"; drop the implicit None fallback so non-OpenAI callers can't accidentally pick up a regional tag from a stray OpenAI hostname. - _local_model_cost_map fixture now snapshots and restores litellm.model_cost and LITELLM_LOCAL_MODEL_COST_MAP so tests don't leak state across the session. * refactor(openai): move data_residency helper under llms/openai * fix: thread data_residency through realtime stream cost calculation Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(cost): thread data_residency through batch_cost_calculator Apply the OpenAI regional-processing uplift multiplier to retrieve_batch cost paths so Batch API requests served via eu./us.api.openai.com are priced at the same uplifted token rates as completions/transcriptions. * refactor(openai): encapsulate provider check inside infer_openai_data_residency Move the custom_llm_provider == "openai" guard from get_litellm_params into the helper itself so the core utility no longer carries provider-specific dispatch logic. Callers pass through the provider unconditionally; the helper returns None for any non-OpenAI provider. * fix(responses): thread data_residency through Responses logging params The Responses API paths build their logging litellm_params dict after provider resolution but did not include data_residency, so cost calc saw None even when the effective api_base was a regional OpenAI host. --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> * fix: preserve OTEL response payload and remove duplicate constant - _emit_management_endpoint_otel_span now passes result as response on success - remove duplicate _CREDENTIAL_LITELLM_PARAM_FIELDS assignment in model_checks Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix: address bug detection findings - pass_through_endpoints: use request.method instead of hardcoded POST in streaming SigV4-signed request path for consistency with the non-streaming branch - llm_cost_calc/utils: hoist DataResidency value set to a module-level frozenset to avoid rebuilding it on every cost calculation - example_config_yaml/oai_misc_config: replace real-looking AWS account ID with placeholder 123456789012 in example bucket and role ARN Co-authored-by: Yassin Kortam <yassin@berri.ai> * chore(github_copilot): refresh model catalog from upstream /models API (#28055) Aligns the github_copilot catalog with values returned by Copilot's public /models endpoint (capabilities.limits + capabilities.supports + model.supported_endpoints). - Adds 10 new model entries: claude-opus-4.7, claude-sonnet-4.6, gemini-3-flash-preview, gemini-3.1-pro-preview, gpt-4-0125-preview, gpt-5.2-codex, gpt-5.4, gpt-5.4-mini, gpt-5.5, oswe-vscode-prime. - Updates max_input_tokens for existing entries to reflect each model's true context window (e.g. gpt-4o-mini 64000 -> 128000, gpt-5-mini 128000 -> 264000, gpt-5.3-codex 128000 -> 400000, claude-haiku-4.5 128000 -> 200000). - Adds supports_reasoning, supports_response_schema, supports_function_calling, supports_parallel_function_calling, supports_vision based on capabilities.supports. - Declares supported_endpoints for entries missing it (e.g. gpt-3.5-turbo, gpt-4o, embeddings). - For responses-only models (gpt-5.2-codex, gpt-5.4, gpt-5.4-mini, gpt-5.5), sets mode to 'responses'. - gpt-41-copilot.mode changes from 'completion' to 'chat' because Copilot reports capabilities.type = 'chat'. Revertible on request. Pricing fields and other manually-curated values are preserved. * feat(datadog): emit litellm.overhead.latency as a standalone Datadog metric (#28831) Adds a new `litellm.overhead.latency` gauge metric to `DatadogMetricsLogger` (the `/api/v2/series` path). The value is sourced from `hidden_params["litellm_overhead_time_ms"]` already computed in `ResponseMetadata` and exposed in `StandardLoggingPayload`. Matches the Prometheus integration which exposes the same value via `litellm_overhead_latency_metric`. Emitted in seconds (ms ÷ 1000) for consistency with the other latency series. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Shin <shin@litellm.ai> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> * feat(arize): route Phoenix traces via per-project TracerProviders (#28876) Use LRU-cached TracerProviders with project-scoped OTEL Resources so team/key metadata routes traces correctly. On the proxy, project selection is limited to server-controlled user_api_key_auth_metadata; client metadata fields stay banned. * fix(arize_phoenix): skip _emit_semantic_logs on failure path Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(arize_phoenix): skip raw request logging and metrics on failure path Restores pre-refactor behavior: _handle_failure no longer emits raw-request sub-spans or records OTEL metrics, matching the original _handle_failure that did not call these helpers. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(security): close two medium telemetry trust-boundary issues Issue 1 (arize_phoenix.py — caller-controlled telemetry routing): - _is_proxy_request no longer detects proxy mode by checking user_api_key_auth_metadata in request metadata. That field is user-supplied, so an authenticated caller could fake proxy-mode detection and have _project_from_metadata_dict read their own dict for project selection, routing telemetry to arbitrary Arize/Phoenix projects. Proxy mode is now determined solely by the server-set proxy_server_request field in litellm_params. - auth_utils.py adds user_api_key_auth_metadata to the banned request body params list so the proxy rejects any attempt to supply the field at the HTTP layer. The field is server-reserved: it is written exclusively by add_user_api_key_auth_to_request_metadata from the authenticated key's database record after the ban check runs. Issue 2 (management_helpers/utils.py — API key in OTEL span): - _emit_management_endpoint_otel_span stripped plaintext credential fields (key, token, api_key, secret, …) from the response dict before passing it to the OTEL success hook. dict(result) on a Pydantic GenerateKeyResponse includes the freshly-generated key field, which would previously be written as a span attribute to every configured OTEL collector/backend. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: Terrajlz <info@jouleselectrictech.com> Co-authored-by: Bruno Devaux <devaux.br@gmail.com> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local> Co-authored-by: user <70670632+stuxf@users.noreply.github.com> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> Co-authored-by: rinto <54238243+ririnto@users.noreply.github.com> Co-authored-by: Shin <shin@litellm.ai> Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com>	2026-05-26 11:57:39 -07:00
Shivam Rawat	bd2d0ad519	Litellm OpenAI double prefix bug (#28661) ... * Fix token cost lookup when deployment ids repeat the provider prefix. Router configs may expose models like openai/openai/<model>; normalize those strings before joining provider/model so model_cost resolves correctly. Co-authored-by: Cursor <cursoragent@cursor.com> * scope duplicate-prefix cost fix to explicit providers; isolate test patch state Co-authored-by: Cursor <cursoragent@cursor.com> * fix(mypy): narrow custom_llm_provider after resolution in cost_per_token Co-authored-by: Cursor <cursoragent@cursor.com> * fix(cost_calculator): guard provider-prefix dedup against non-string model The provider-prefix dedup loop assumed `model` is always a string. When a non-string is passed (e.g. a MagicMock from a mocked transport in router tests), `model.startswith(...)` is always truthy and each slice returns a new object, so the loop never terminates — it spins and OOM-kills the test worker (observed as the litellm_router_testing CI regression, e.g. test_router_pattern_match_e2e). Only run the string-based dedup and prefix-join when `model` is actually a str, preserving the previous graceful behavior for non-string inputs. --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>	2026-05-26 11:40:44 -07:00
Shivam Rawat	fbff60e9d9	fix(proxy): strip LiteLLM policy tracking from OpenAI batch metadata (#28425) ... * fix(proxy): strip LiteLLM policy tracking from OpenAI batch metadata Batch create was failing with `Invalid type for 'metadata.applied_policies': expected a string, but got an array instead` whenever a policy attachment matched the request. The policy engine helpers wrote `applied_policies`, `applied_guardrails`, and `policy_sources` into `data["metadata"]` unconditionally, and `/v1/batches` forwarded that dict straight to OpenAI, which only accepts string values. - Route proxy-internal tracking into `litellm_metadata` for batch/file routes via a shared `_get_or_create_proxy_metadata_bucket` helper. - Sanitize `data["metadata"]` in `create_batch` to drop known internal keys and non-string values before building the OpenAI request. - Cover both behaviors with unit + endpoint tests. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): merge metadata buckets for batch policy response headers Ensure get_logging_caching_headers reads both metadata and litellm_metadata so policy/guardrail headers are emitted on batch routes with user metadata, and log dropped non-string OpenAI metadata at debug level. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>	2026-05-26 11:35:42 -07:00
Mateo Wang	533eab4dbd	fix(tests/vcr): make Redis cassette cache replay deterministically (zero VCR misses on consecutive runs) (#28826) ... * test(vcr): make Redis-backed cassettes replay deterministically across runs - Pin LITELLM_LOCAL_MODEL_COST_MAP=True in the shared VCR harness so the per-test importlib.reload(litellm) no longer fetches the model cost map from raw.githubusercontent.com. That live fetch was being recorded into cassettes; for tests that subsequently skip it was the only recorded episode, so the persister refused to save it (skipped tests don't persist) and the test re-recorded it live every run (MISS:NOT_PERSISTED). - Compare-time symmetric matcher tolerance for Google OAuth (ya29.*) tokens, observability/telemetry payloads, credential-exchange bodies, and volatile UUID/timestamp tokens, so existing cassettes select a recorded episode instead of growing past the 50-episode cap and re-recording live. - Don't record fire-and-forget telemetry (langfuse/arize/otel/...) into non-telemetry tests' cassettes. Several modules set litellm.success_callback at import time, so observability logging is globally enabled and an async flush from the background logging worker lands in an unrelated test's VCR window, saved as a spurious MISS:RECORDED (observed: a Langfuse batch from another completion landing on test_lowest_latency_routing_buffer). Such a request now passes through live (telemetry hosts aren't real-spend hosts); tests that actually assert on telemetry keep recording it. - Dedupe + cap the VCR diagnostic dump so the classification summary survives CircleCI's ~400KB step-output truncation. - Stabilize a non-deterministic rate-limit test body; mark AWS Secrets Manager lifecycle tests VCR-incompatible (uniquely-named secrets can't be replayed). - Mark test_router_text_completion_client VCR-incompatible: it fires 300 identical requests to verify async-client reuse, but vcrpy patches the HTTP transport so replay never exercises the real connection pool the test validates, and recording 300 near-identical episodes overflows the 50-episode cap (MISS:OVERFLOW every run). It hits a free mock endpoint. - Mark the Vertex AI MaaS Mistral OCR tests (vertex_ai/mistral-ocr-2505) VCR-incompatible: the MaaS model is not provisioned in the CI GCP project, so the live :rawPredict call fails and the test skips every run, leaving no cassette to record (MISS:NOT_PERSISTED every run). Sibling direct-Mistral and Azure OCR tests are unaffected and still replay from cache. * fix(tests/vcr): refresh cassette TTL on read so replayed cassettes don't expire The Redis VCR persister loaded cassettes with a plain GET, which does not touch the key's TTL. A cassette that is only ever replayed (HIT/NOOP, never re-recorded) therefore expired exactly 24h after its last *write*, no matter how often it was read. Whichever CI run happened to cross that boundary re-recorded the cassette live and surfaced a spurious VCR MISS on otherwise deterministic cassettes — the residual per-run flakiness floor (a different random subset of read-only cassettes expiring each run). Slide the expiry forward on every successful load (best-effort EXPIRE), so any cassette used at least once per TTL window stays alive indefinitely and the 2nd/3rd run of a day replays cleanly. * fix(tests/vcr): recover from spurious GET-None for existing cassette keys Under concurrent CI load, the persister's load GET was observed returning None for a cassette key that demonstrably existed on the (single, non- clustered) Redis master — an external monitor saw the key present with a healthy TTL at the same instant the in-process client read None. Because None is a valid GET result (not a RedisError), the retry-on-error client config never engaged, so the cassette re-recorded live (a phantom MISS:RECORDED); for flaky/networked tests the failed live call then triggered a pytest rerun, which is why a rotating subset of otherwise deterministic tests missed each run. On a None result, re-check EXISTS and re-read once. If the key really exists, use the recovered value and log [vcr-transient-miss-recovered] (also counted in cassette_cache_health). A genuinely absent key (a new cassette) still falls through to CassetteNotFoundError. * chore(tests/vcr): TEMP diagnostic for persistent-miss cassette load path Logs GET/EXISTS at load time for the three cassettes that re-record every run despite being present in Redis, to capture what the in-process client sees. To be reverted before merge. * chore(tests/vcr): write load diagnostic to Redis (truncation-proof) CI stdout truncates to the last ~400KB, dropping the early loaddbg lines for the alphabetically-first failing test. Push the load probe to a Redis list instead so it survives. To be reverted before merge. * fix(tests/vcr): don't drop stored telemetry episodes during cassette load Root cause of the residual per-run misses on present cassettes: vcrpy's Cassette._load() replays each *stored* interaction through Cassette.append(), which runs before_record_request on it — and a None return there silently drops that episode. The telemetry-leak suppressor (_should_drop_telemetry_record) returns None for telemetry requests, so when a non-telemetry-named test (or the alphabetically-first test in a worker, whose _current_test_nodeid is still empty) loaded a cassette containing a Langfuse ingestion episode, the episode was dropped on read — forcing an endless live re-record (a phantom MISS:RECORDED on a cassette that was demonstrably present in Redis). Verified by reproducing Cassette._load() against the real cassette: empty/non-telemetry nodeid -> 0 episodes survive; with the guard -> 1 survives. Fix: guard the suppressor with a thread-local set around Cassette._load (via a small idempotent monkeypatch), so the drop only ever stops *new* incidental telemetry from being recorded and never filters the existing cassette on read. Also drops the speculative GET-None recovery + its diagnostics from the previous commits: the load diagnostic showed GET returns the cassette bytes fine (get=1440B), so the persister never returned a spurious None — the loss happened later in vcrpy's append. The proven TTL-refresh-on-read fix is retained. * fix(tests/vcr): drop incidental telemetry export POSTs to stop rotating async-flush misses litellm's observability loggers flush on a background thread, so a Langfuse ingestion POST scheduled by one telemetry test can fire mid-way through a *later* telemetry-named test (after that test's own httpx mock has exited) and be recorded by VCR as a phantom episode — a non-deterministic MISS:RECORDED / PARTIAL that rotates onto a different telemetry test from run to run. Telemetry export POSTs are fire-and-forget; no test asserts on a *recorded* export response except the pass-through proxy test (which forwards a client POST to Langfuse ingestion and replays its 207). So _should_drop_telemetry_record now drops incidental export POSTs for every test except that one. Dropping returns None (live fire-and-forget, never stored), so it can only turn a phantom miss into a harmless live call, never the reverse; recorded read-back GETs that telemetry tests assert on are matched by method and left untouched. * fix(tests/vcr): restore assertion in test_banner_silent_when_vcr_disabled The assertion that the banner is suppressed when VCR is disabled was inadvertently moved into test_diagnostic_log_silent_when_no_dir when the diagnostic-log tests were added, leaving the disabled-VCR test verifying nothing. Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-26 11:30:44 -07:00
ryan-crabbe-berri	f75a7c6b22	fix(model-edit): allow clearing custom pricing on wildcard models (#28719) ... * fix(model-edit): allow clearing custom input/output cost on wildcard deployments A user-set pricing override on a `/model/*` wildcard deployment could not be removed: clearing the Input/Output Cost fields in the UI succeeded visually, but the next read still showed the old values because both `litellm_params` and `model_info` (mirrored via `SPECIAL_MODEL_INFO_PARAMS`) retained the original rates. UI: when the pricing field is touched but left empty, send `null` instead of dropping it from the payload so the backend sees the clear intent. The cache-read-cost fallback now guards against `null` as well as `undefined` so a cleared input cost cannot silently wipe the cache-read override. Backend: `update_db_model` honors explicit-null clears, but ONLY for `SPECIAL_MODEL_INFO_PARAMS` (the 4 pricing fields). Restricting the null-clear path prevents a team-scoped caller from using this codepath to null out privileged fields like `team_id` or access groups. Tests cover both clear paths (`litellm_params` and `model_info`), the SPECIAL_MODEL_INFO_PARAMS mirror, PATCH semantics for omitted fields, and the security guard that non-pricing nulls don't reach the merged dict. Resolves LIT-3250 * fix(model-edit): run null-clears after both merges, not interleaved The previous version cleared `model_info` from inside the litellm_params merge block, but the subsequent `model_info.update(...)` re-injected the old pricing because the UI's PATCH carries the full model_info blob with the stale values still in it. Move the explicit-null clear pass to after both merges so a model_info passthrough cannot resurrect cleared fields. Adds a regression test for the realistic UI submit shape (both blobs in the patch, model_info still holding the old pricing). * test(e2e): clear-custom-pricing flow with create/delete cleanup Covers the dashboard model edit form's pricing-clear flow end-to-end: seeds a deployment with custom input/output pricing, drives the UI to clear both fields, asserts the outgoing PATCH sends explicit nulls, and confirms via /v2/model/info that the override is gone from both litellm_params and model_info. The dashboard DB persists across this suite, so beforeEach creates a uniquely-named deployment and afterEach POSTs /model/delete to leave the DB clean regardless of test outcome. * fix(model-edit): extend pricing clear to cache_read and cache_write costs Pre-existing parallel of the wildcard input/output cost bug: cleared cache_read_input_token_cost and cache_creation_input_token_cost overrides silently persisted because the UI omitted the key (delete or fallback) and the backend null-clear allowlist did not cover them. - types/router.py: add cache_read_input_token_cost and cache_creation_input_token_cost to SPECIAL_MODEL_INFO_PARAMS, so they are mirrored between litellm_params and model_info by Deployment.__init__ and honoured by the null-clear loop in update_db_model. - model_info_view.tsx: emit explicit null for touched-but-empty cache_read and cache_write fields. Preserve the input_cost->cache_read mirror only when cache_read itself was not touched. - model_management_endpoints.py: update the allowlist comment. - Tests: three new unit tests for cache clear paths and a preserve check; the e2e spec now seeds, clears, and asserts null PATCH + key-absence for all four pricing fields.	2026-05-26 09:37:23 -07:00
Mateo Wang	96a2e8b16d	fix(azure): preserve AD token refresh in v1 OpenAI client path (#28627) ... * fix(azure): preserve AD token refresh in v1 OpenAI client path The /openai/v1/ code path (api_version in {"v1", "latest", "preview"}) constructs a plain OpenAI/AsyncOpenAI client, but only forwarded `api_key` from `azure_client_params`. When `enable_azure_ad_token_refresh` is set (or any AD-only auth), `api_key` is None and the client constructor raised "The api_key client option must be set...", breaking every Azure call with a v1 api_version. The OpenAI SDK (>=2.20.0) accepts a callable for `api_key` and re-invokes it on every request via `_refresh_api_key`, so we now forward `azure_ad_token_provider` directly — preserving the per-request token refresh behavior of the regular AzureOpenAI client and avoiding the expiry hole that resolving the token once at client-creation time would introduce. Static `azure_ad_token` strings fall through to `api_key`. For the async path we wrap the sync provider returned by azure-identity in an async function since AsyncOpenAI expects `Callable[[], Awaitable[str]]`. Fixes #27945 https://claude.ai/code/session_01UnzrDSFUUgp5T2wRoPMxq5 * fix(azure): offload sync token provider to thread in v1 async wrapper * fix(azure): include AD credential identity in v1 client cache key --------- Co-authored-by: Claude <noreply@anthropic.com>	2026-05-25 21:08:52 -07:00
Mateo Wang	48d7e15b83	chore(admin-ui): regenerate static export with trailingSlash: true (#28112) ... * chore(admin-ui): regenerate static export with trailingSlash: true Rebuilds litellm/proxy/_experimental/out/ from ui/litellm-dashboard with `trailingSlash: true` enabled in next.config.mjs. Next.js now emits every route as <dir>/index.html (e.g. mcp/oauth/callback/index.html) instead of <dir>.html with a sibling metadata-only directory, which fixes the 404 on extensionless URLs served through FastAPI's StaticFiles(html=True) mount. This is the build artifact half of the fix; the config change, Dockerfile cleanup, and regression test live in the follow-up source PR that stacks on top of this branch. * fix(admin-ui): emit nested routes as <dir>/index.html (#28106) Linear and other OAuth providers redirect the user back to /ui/mcp/oauth/callback?code=...&state=... after the consent step. The packaged Next.js static export only produced /ui/mcp/oauth/callback.html, so FastAPI's StaticFiles served a 404 on the extensionless URL and the OAuth handshake never completed. The Dockerfile.non_root build step tried to paper over this at image-build time with `for html_file in *.html; do ...`, but that shell glob does not recurse, so nested routes like mcp/oauth/callback.html were left stranded next to an empty mcp/oauth/callback/ directory containing only Next.js metadata. The runtime restructure step in proxy_server.py was then skipped because the .litellm_ui_ready marker had already been dropped. Set trailingSlash: true in the dashboard's Next.js config so the export emits every nested route as <dir>/index.html natively. The Dockerfile loop is now a no-op for the bundled UI and has been removed; the .litellm_ui_ready marker is still written so the proxy keeps skipping the redundant Python restructure step at startup. Stacks on top of the static export regeneration in the parent branch. * chore: restore origin/litellm_internal_staging out files	2026-05-25 21:06:50 -07:00
Mateo Wang	c23b19f09c	feat(openai): apply regional-processing cost uplift for EU/US data residency (#28626) ... * feat(openai): apply regional-processing cost uplift for EU/US data residency OpenAI charges a 10% uplift on the latest GPT models when requests are served from a regionalized hostname (eu./us.api.openai.com). Infer the region from `api_base`, expose it on `kwargs["litellm_params"]["data_residency"]`, and multiply the computed cost by a per-model `regional_processing_uplift_multiplier_<region>` field. https://claude.ai/code/session_012ebH44s7ohYxjoix5CXzTW * test: allow regional_processing_uplift_multiplier_{eu,us} in model_prices schema * fix(cost): tighten data_residency inference and restore model_cost in tests - Only infer OpenAI data_residency when custom_llm_provider == "openai"; drop the implicit None fallback so non-OpenAI callers can't accidentally pick up a regional tag from a stray OpenAI hostname. - _local_model_cost_map fixture now snapshots and restores litellm.model_cost and LITELLM_LOCAL_MODEL_COST_MAP so tests don't leak state across the session. * refactor(openai): move data_residency helper under llms/openai * fix: thread data_residency through realtime stream cost calculation Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(cost): thread data_residency through batch_cost_calculator Apply the OpenAI regional-processing uplift multiplier to retrieve_batch cost paths so Batch API requests served via eu./us.api.openai.com are priced at the same uplifted token rates as completions/transcriptions. * refactor(openai): encapsulate provider check inside infer_openai_data_residency Move the custom_llm_provider == "openai" guard from get_litellm_params into the helper itself so the core utility no longer carries provider-specific dispatch logic. Callers pass through the provider unconditionally; the helper returns None for any non-OpenAI provider. * fix(responses): thread data_residency through Responses logging params The Responses API paths build their logging litellm_params dict after provider resolution but did not include data_residency, so cost calc saw None even when the effective api_base was a regional OpenAI host. --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-25 20:36:14 -07:00
yuneng-jiang	f38c16c71e	test(proxy): add harness for proxy_server.py behavior-pinning (#28827) ... * test(proxy): add harness for proxy_server.py behavior-pinning Creates tests/test_litellm/proxy/proxy_server/ with: - conftest.py: 11 shared fixtures (app, client, mock_prisma, auth_as, mock_router with parametrized response builders, normalize, etc.) - _coverage_check.py: per-PR coverage gate (line + branch) against a baseline, self-selects target by inspecting which placeholder files have been filled - _pin_check.py: AST-based gate that verifies every pin-list item has >=1 happy + >=1 error test with a real assertion (no status-only) - test_harness_smoke.py: 19 smoke tests covering every fixture + both scripts end-to-end - 26 placeholder test files (one docstring each) reserved for follow-up PRs per the directory ownership in the Notion plan - .coverage_baseline pinned at 0% so future PRs measure deltas against new-tests-only and aren't entangled with the broader scattered test suite Adds a dedicated proxy-server job to test-unit-proxy-endpoints.yml so this directory's runtime + coverage are tracked independently. Plan: https://www.notion.so/36c43b8acdab81ee845fd5365128a2fc * ci(proxy-endpoints): allow workflow_dispatch Lets the workflow be triggered manually on a branch via `gh workflow run`, which is needed for the verify-first flow on workflow changes before opening a PR. * test(proxy): address review feedback on proxy_server harness - conftest.py: anchor sys.path insert to __file__ (Path(__file__).resolve().parents[4]) instead of CWD-relative os.path.abspath("../../../../") which resolved to the wrong directory when pytest is launched from the repo root. - _coverage_check.py: actually read .coverage_baseline and use it as the floor (line_min = max(target, baseline)). Closes the gap between the PR description's "delta semantics" and what the script was doing. With baseline=0.0 today this is a no-op; future PRs that update the baseline cause regressions (test deletions etc.) to trip the gate even if the static PR target is still met. - _pin_check.py: drop unreachable startswith("_") guard (test_*.py glob never yields underscore-prefixed names) and read each test file once instead of twice.	2026-05-25 20:26:44 -07:00
yuneng-jiang	7cd98508e7	fix(team): keep team_alias cache in sync on _cache_team_object writes (#28737) ... * fix(team): keep team_alias cache in sync on _cache_team_object writes _cache_team_object wrote only to the team_id:<id> cache key, but the JWT auth path that uses team_alias_jwt_field reads from a separate team_alias:<alias> key (get_team_object_by_alias caches under both keys on miss, but reads only the alias-keyed one). After any team-mutation endpoint (team_model_add, team_model_delete, update_team, the two access-group writes) the team_id cache was refreshed but the team_alias cache stayed stale until TTL — JWT callers using team_alias_jwt_field kept seeing the pre-mutation team for the full cache window. Mirror the write under the alias key inside _cache_team_object so every existing caller stays in sync without further changes. Skip the alias write when team_alias is None/empty so we don't collide across alias-less teams. Surfaced testing the LIT-3244 cherry-pick on patch/1.86.0: the LIT-3244 fix correctly invalidated the team_id cache but the customer's JWT used team_alias_jwt_field, so they kept hitting the stale alias-keyed entry. * fix(team): delete (not overwrite) team_alias cache on _cache_team_object The prior shape of this PR wrote both team_id:<id> AND team_alias:<alias> from _cache_team_object. team_alias is NOT unique in the schema (no @unique on LiteLLM_TeamTable.team_alias), and get_team_object_by_alias enforces uniqueness on its own DB-fetch path (len(teams) > 1 raises). Writing the alias-keyed cache from the generic refresh path bypassed that check: a team admin renaming their team to collide with another team's alias could silently overwrite the cached team for JWT-by-alias auth, swapping the resolved team under that alias for the cache window. Switch the alias-keyed operation from a write to a delete (mirroring the dual-cache delete pattern in _delete_cache_key_object). After every team write, the next JWT-by-alias reader cache-misses and falls through to get_team_object_by_alias, which (a) re-fetches the fresh team from DB, closing the LIT-3244 staleness gap that motivated this PR, and (b) enforces alias uniqueness before populating either cache key. team_id:<id> writes are unchanged — team_id is the table PK and is guaranteed unique. Surfaced in veria-ai review on #28739. * fix(managed-files): anchor model_id regex so it doesn't match llm_output_file_model_id extract_model_id_from_unified_id used `re.search(r"model_id,([^;]+)", ...)` which substring-matches the `model_id,` inside the file-ID encoding's `llm_output_file_model_id,<deployment_uuid>` field. parse_unified_id then fed that deployment UUID back into the auth path as a model candidate via _extract_models_from_managed_resource_id, and every team-BYOK file attach 403'd with: team not allowed to access model. This team can only access models=['openai/*']. Tried to access <deployment-uuid> The team's models list correctly contains the public name (`openai/*`) that target_model_names matches, but the bogus UUID candidate fails the wildcard check first. Anchor the regex to a field boundary (`(?:^|;)model_id,`) so it matches the legitimate top-level `model_id,<value>` field on vector_store unified IDs and skips substring matches inside other fields. File-IDs (which have no top-level `model_id` field) now return None and contribute no spurious UUID candidate. Surfaced reproducing LIT-3244 on patch/1.86.0 with the customer's exact flow: team with openai/* BYOK deployment, JWT-scoped user, POST /v1/vector_stores/{id}/files attaching a file uploaded with target_model_names=openai/gpt-4o.	2026-05-25 19:16:36 -07:00
ryan-crabbe-berri	66f10bceea	feat(proxy): allow llm_api_routes virtual keys to list MCP servers (#28442) ... * feat(proxy): allow llm_api_routes virtual keys to list MCP servers Add a new `mcp_discovery_routes` group (GET /v1/mcp/server and GET /v1/mcp/server/{server_id}) and include it in `llm_api_routes` so that virtual keys configured with `allowed_routes=["llm_api_routes"]` can discover the MCP servers they have access to. Previously these calls failed with 'Virtual key is not allowed to call this route. Only allowed to call routes: [llm_api_routes]'. The GET handlers already sanitize the response for restricted virtual keys via `_sanitize_mcp_server_list_for_virtual_key`, stripping credential-bearing fields (url, headers, env). Write methods (POST/PUT/DELETE) on the same paths remain gated by the existing handler-level admin role checks. The new discovery list is intentionally kept OUT of `mcp_inference_routes`, so `is_llm_api_route()` still returns False for these paths — this preserves the existing contract that DISABLE_LLM_API_ENDPOINTS must not block the Admin UI from listing MCP servers. Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com> * refactor(proxy): make MCP discovery carve-out method-aware Replace the `mcp_discovery_routes` group in `llm_api_routes` with a method-aware special case inside `is_virtual_key_allowed_to_call_route`. Virtual keys with allowed_routes=["llm_api_routes"] are now permitted to call only GET /v1/mcp/server and GET /v1/mcp/server/{server_id} — non-GET methods and multi-segment admin sub-paths fall through to the existing 403. This keeps the general llm_api_routes list free of management paths and avoids accidentally exposing POST/PUT/DELETE writes through the route-check layer. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com>	2026-05-25 16:34:18 -07:00
yuneng-jiang	d98ada8c3f	chore(ci): merge dev branch (#28657) ... * feat(dashboard): navbar hierarchy + Agent Platform notifications (#27543) * feat(dashboard): refine navbar zones and Agent Platform notice Restructure the admin navbar for production users: clear product vs community vs personal columns with vertical dividers, icon-only Slack/GitHub in a shared chip, and Docs/Blog typography aligned on an 8px rhythm. Add a notifications bell with popover linking to the LiteLLM Agent Platform repo and optional mark-as-read persistence. Promote the account control with initials avatar, single-line display name, and navDisplayName mapping for placeholder user ids (e.g. default_user_id). Co-authored-by: Cursor <cursoragent@cursor.com> * fix(dashboard): address PR review — AntD buttons, public page guard, dedupe regex - Replace raw <button> with AntD Button in BlogDropdown, NotificationsBell, UserDropdown, and test mock - Guard NotificationsBell + container behind !isPublicPage to avoid rendering on public pages - Remove redundant equality checks in navDisplayName (regex already covers them) - Remove unused `lower` variable after simplification Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(dashboard): drop dead useHealthReadiness import in navbar The module was removed in #27896 (replaced by useHealthReadinessDetails), but the import survived the rebase. The symbol is unused — only useHealthReadinessDetails is consumed in the file. Removing the dead import unblocks the UI TypeScript build. * fix(dashboard): align CommunityEngagementButtons test with icon-only aria-labels The component was refactored to an icon-only chip with aria-label='LiteLLM on GitHub' (squash #27543), but the test still asserted /star us on github/i. Update the query to match the rendered accessible name. * refactor(dashboard): drop unused props from NavbarProps The navbar refactor moved user identity + dark-mode state to internal hooks (useAuthorized, useWorker), but the NavbarProps interface still declared userID, userEmail, userRole, premiumUser, isDarkMode, and toggleDarkMode as required, forcing every caller to thread them through. Drop them from the interface and all four call sites (page.tsx, (dashboard)/layout.tsx, public_model_hub.tsx, navbar.test.tsx). Also shrinks the destructure in layout.tsx so the now-unused locals stop being pulled out of useAuthorized(). * refactor(dashboard): use useSyncExternalStore for NotificationsBell dismiss flag Reads/writes of the litellmHideAgentPlatformBanner key were done directly inside NotificationsBell via a useEffect + useState pair. Every other localStorage-backed flag in the dashboard (Disable ShowPrompts, DisableBouncingIcon, DisableShowNewBadge, DisableUsageIndicator, DisableBlogPosts) is wrapped in a useSyncExternalStore hook over localStorageUtils so all mounted components stay in sync. Extract useHideAgentPlatformBanner to follow the same shape, swap NotificationsBell to consume it, and add a regression test that two sibling bells stay in sync without a remount when one is dismissed. * refactor: mask credential fields in proxy settings GET responses (#28682) * refactor: mask credential fields in proxy settings GET responses Brings SSO settings, cache settings, and the email/Slack alerting view in /get/config/callbacks in line with the HashiCorp Vault config-override pattern, so persisted credentials are not transported back to the UI in plaintext. * refactor: harden short-value masking and hoist alerting var constant Closes two review observations: - mask_sensitive_keys now replaces short values (below the visible prefix+suffix length) with an all-mask string instead of returning them unchanged, so a 1-7 character credential is no longer round-tripped verbatim. - _ALERTING_SENSITIVE_VARS is moved out of get_config() to a module-level constant, matching the analogous _SSO_SENSITIVE_FIELDS and _CACHE_SENSITIVE_FIELDS in the SSO and cache endpoint files. --------- Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>	2026-05-25 13:48:47 -07:00
yuneng-jiang	5f75be5c1c	chore(ci): merge dev branch (#28801) ... * chore(proxy): route path-dependent call sites through get_request_route Replace direct ``request.url.path`` reads in auth, ACL, routing, and audit-log decisions with ``get_request_route(request)`` — the helper already added in ``auth/auth_utils.py`` that returns the ASGI ``scope["path"]`` with ``root_path`` stripped. Starlette reconstructs ``url.path`` from the Host header; ``scope["path"]`` is uvicorn's parse of the request line and matches what FastAPI dispatches on, so it's the authoritative route for any decision that should agree with the actual handler. Sites: - _experimental/mcp_server/auth/user_api_key_auth_mcp.py - management_endpoints/mcp_management_endpoints.py - vector_store_endpoints/utils.py - pass_through_endpoints/pass_through_endpoints.py - auth/route_checks.py - litellm_pre_call_utils.py - spend_tracking/spend_management_endpoints.py - common_utils/http_parsing_utils.py - management_helpers/utils.py - health_endpoints/_health_endpoints.py Adds regression tests in tests/proxy_unit_tests/test_proxy_routes.py that construct a Request with scope["path"] set to a benign route and the Host header crafted so url.path would resolve differently; each site's decision is asserted against scope["path"]. * chore(proxy): make get_request_route imports lazy at call sites Move the ``from litellm.proxy.auth.auth_utils import get_request_route`` imports added in the prior commit back to the function bodies that use them. The module-level form participates in a long-standing import cycle through ``auth_utils -> _types -> ...`` and was flagged by CodeQL on the PR; the lazy form matches the pattern the proxy already uses for ``user_api_key_auth`` and related helpers elsewhere in these files. Also drop the ``RouteChecks._is_assistants_api_request`` delegation in ``_get_metadata_variable_name`` introduced in the prior commit — the delegation pulled ``RouteChecks`` into the same cycle, and the call site reuses the resolved route for its other branches, so inlining the substring check is both cycle-free and avoids a redundant second ``get_request_route`` call. Comment in test_proxy_routes.py acknowledges that the two MCP table entries exercise ``get_request_route`` directly rather than the full production handler (which needs ASGI scope + MCP state to invoke). --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: user <70670632+stuxf@users.noreply.github.com>	2026-05-25 13:44:49 -07:00
Yassin Kortam	30551de371	fix(otel): export SERVER span on management-endpoint success without http_request (#28794) ... Co-authored-by: Yassin Kortam <yassinkortam@Yassins-MacBook-Pro.local>	2026-05-25 12:13:17 -07:00
Mateo Wang	f9407bc036	chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728) ... * chore(tests): migrate Bedrock CI from AWS account 888602223428 to 941277531214 The original account (888602223428) was put under a security restriction by AWS after a root access key leaked in a PR comment. While that account works its way through the AWS Support unlock process, Bedrock-touching CI tests have been migrated to a fresh account (941277531214). Changes: - Replace 26 hardcoded references to 888602223428 with 941277531214 across 8 files (provisioned-model ARNs, imported-model ARNs, AgentCore runtime ARNs, batch execution role ARN, and example proxy config). - The provisioned-model and imported-model ARNs are referenced only from mocked unit tests — no AWS resources to recreate. - The batch execution IAM role has been recreated in the new account with the same name and equivalent permissions. - The two AgentCore runtimes (hosted_agent_r9jvp-3ySZuRHjLC, hosted_agent_13sf6-cALnp38iZD) are being recreated in the new account under the same names — see tools/agentcore-deploy/ in a follow-up. CircleCI env vars AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION_NAME were updated separately via the CircleCI API to point at the new account. Smoke-tested locally against the new account: aws bedrock-runtime converse --region us-west-2 \ --model-id us.anthropic.claude-sonnet-4-5-20250929-v1:0 \ --messages '[{"role":"user","content":[{"text":"ping"}]}]' → 200, model returned 'pong' Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): refresh AgentCore ARN suffixes to match newly-deployed runtimes The first migration commit replaced just the account ID, but AgentCore auto-assigns a random 10-char suffix to every runtime on creation — we can't reuse the original suffixes (`3ySZuRHjLC`, `cALnp38iZD`) in the new account. Updated the AgentCore-runtime ARNs in the three files that reference real runtime IDs (not the mock-based unit-test ARNs). Deployed runtimes: arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_r9jvp-Rq79QFC2fp arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_13sf6-4046UzHSwy Both runtimes are status=READY and pass a smoke invoke: $ aws bedrock-agentcore invoke-agent-runtime --agent-runtime-arn ... --payload '{"prompt":"ping"}' → 200, {"result": "echo: ping"} The agent is a minimal echo (see /tmp/agentcore_deploy/agent.py for the deploy artifacts). Tests that only verify the SDK wiring will pass; if any test asserts on agent output content, swap the echo for the real agent. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore(tests): point Bedrock batch tests at new-account S3 bucket The account migration (888602223428 -> 941277531214) was a flat account-ID swap, which only rewrites ARNs that embed the account number. S3 bucket names carry no account ID, so the live Bedrock batch tests still uploaded to `litellm-proxy` — a bucket that lives in the old account. S3 names are globally unique, and the old account still holds that name, so it can't be recreated in the new account. Rename to `litellm-proxy-941277531214` (account-ID suffix guarantees global uniqueness). The bucket must be created in 941277531214 and the batch execution role granted s3:GetObject/PutObject/ListBucket on it before this job is run in CI. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): point live S3 logging test at new-account bucket Same account-ID-free blind spot as the batch bucket: `load-testing-oct` lives in the old account and its name can't be reused globally. The `logging_testing` CI job is wired into the workflow and runs test_basic_s3_logging, which uploads to this bucket with the CI env creds, then lists and deletes objects — a live dependency. Rename to `load-testing-oct-941277531214`. The bucket must exist in the new account with the CI IAM principal granted s3:PutObject/GetObject/ListBucket/DeleteObject before this job runs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(tests): repoint Bedrock guardrail IDs to new-account guardrails The migration left guardrail IDs untouched (no account ID in them), so all live guardrail tests failed with "guardrail identifier or version does not exist" against 941277531214. Recreated both guardrails in the new account and updated the hardcoded IDs: - wf0hkdb5x07f -> zgkmukebruil (PII mask: PHONE + CREDIT_DEBIT_CARD, with explicit inputAction=ANONYMIZE so masking applies to INPUT, which is the source litellm's moderation hook sends) - ff6ujrregl1q -> 4w3d1di3snt5 (blocks "coffee"; blocked message set to the exact string the tests assert on) Updated test_bedrock_guardrails.py, otel_test_config.yaml, and the guardrailConfig in test_bedrock_completion.py. Verified locally: the 5 previously-failing guardrail tests now pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): migrate legacy models to current inference profiles The new CI account (941277531214) cannot invoke legacy Bedrock models (AWS gates them: "marked by provider as Legacy... not actively using in the last 30 days"). Migrated the live-call tests: - anthropic.claude-3-sonnet-20240229 -> us.anthropic.claude-sonnet-4-5-20250929-v1:0 - anthropic.claude-3-haiku-20240307 -> us.anthropic.claude-haiku-4-5-20251001-v1:0 Current Claude models on Bedrock require the us. inference-profile prefix (bare on-demand ids are rejected). cohere.command-r-plus has no working replacement (all Cohere is legacy- gated in the new account): swapped to claude-haiku-4-5 in provider- agnostic param lists. amazon.titan-image-generator skipped (no working replacement). Mocked/transformation/cost tests that reference the legacy strings are intentionally left unchanged. Verified live against the new account. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): repoint SageMaker + Knowledge Base to new-account resources These referenced account-scoped resources by hardcoded id that only existed in the old account, so the migration's account-ID swap missed them. Recreated in 941277531214 and repointed: - SageMaker endpoint jumpstart-dft-hf-textgeneration1-mp-20240815-185614 -> litellm-ci-textgen (gpt2 on a TGI container, ml.g5.xlarge) - Bedrock Knowledge Base T37J8R4WTM -> LCYXFBR2TU (OpenSearch Serverless vector store + titan-embed-text-v2, seeded with a LiteLLM doc) Verified live: test_sagemaker.py (12 passed) and test_bedrock_knowledgebase_hook.py (12 passed). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(reasoning_effort_grid): skip bedrock claude-opus-4-7 cells (not entitled on 941277531214) claude-opus-4-7 is listed in the new Bedrock CI account's foundation models but invoke is denied (AccessDeniedException: "not available for this account"). Bedrock access to the flagship Opus requires an AWS Sales request, not the self-serve model-access toggle, so it can't be enabled inline with the rest of the account migration. Add an optional `skip_reason` to ModelEntry and set it on the bedrock-claude-opus-4-7 entry; the grid test honors it via pytest.skip. Cell count (231) and route coverage are unchanged, so the structural asserts still pass. Restore coverage by deleting the one skip_reason line once access is granted. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test(bedrock): swap/skip legacy-gated models unavailable on new CI account The migrated AWS account (941277531214) cannot access several models that the old account could, so the remaining red CI jobs were hitting real Bedrock "Access denied / Legacy" and "account not authorized" errors: - image_gen: skip both Nova Canvas test classes (amazon.nova-canvas-v1:0 is legacy-gated), matching the existing titan skip. - batches: skip test_async_file_and_batch (Bedrock batch inference is not authorized on the new account; requires an AWS support case). - litellm_overhead: swap legacy claude-3-5-haiku for the active us.anthropic.claude-haiku-4-5 inference profile. - test_completion_claude_3_function_call: swap legacy claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): fix remaining e2e legacy-model + batch failures on new CI account - e2e_openai_endpoints: skip test_bedrock_batches_api (Bedrock batch inference is not authorized on account 941277531214) and migrate the missed s3_bucket_name in oai_misc_config.yaml to litellm-proxy-941277531214. - build_and_test: swap legacy bedrock claude-3-sonnet for the active us.anthropic.claude-sonnet-4-5 inference profile in the proxy structured output e2e test. https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa * test(bedrock): make opus-4-7 + batch cells fail loudly and mock image-gen (#28791) Replace the silent skips added for the new CI account with noisier behavior: - reasoning-effort grid: opus-4-7 cells now fail (when AWS creds are present) instead of skipping, so the missing entitlement stays visible in CI; they still skip when AWS creds are absent (local dev) - Bedrock batch inference tests: drop the skip so they run and fail until batch access is granted - Titan + Nova Canvas image-gen tests: mock the Bedrock HTTP call so the transform + cost-tracking path stays under test without live model access https://claude.ai/code/session_01MT7SWDnXUjv6e6EPG7BDjT Co-authored-by: Claude <noreply@anthropic.com> * test(bedrock): use pytest.xfail for known-failing opus-4-7 cells Replace pytest.fail with pytest.xfail when a model has a fail_reason, so known-broken cells stay visible as XFAIL without keeping CI red. Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-25 12:03:17 -07:00
milan-berri	f45909cb81	fix(proxy): Bedrock Knowledge Base pass-through: preserve SigV4 headers and signed request body (#27526) ... * Fix Bedrock KB pass-through SigV4 headers and signed body Coerce botocore HeadersDict to a dict for pass-through routes. When forward_headers is true, drop request headers that collide case-insensitively with signed headers so client Bearer auth does not shadow AWS SigV4. Send prepped.body as raw content so the outbound payload matches the signature after logging hooks mutate the parsed dict. Co-authored-by: Cursor <cursoragent@cursor.com> * Simplify pass-through raw body handling Read the SigV4-signed bytes directly from request.state inside pass_through_request instead of threading a custom_raw_body argument through three functions. Helper methods are restored to their original signatures, and the new branch lives in one place at each httpx call site. Co-authored-by: Cursor <cursoragent@cursor.com> * Harden pass-through raw body read from request.state Guard missing request.state (test fixtures) and ignore non-bytes/str values so MagicMock does not trigger the SigV4 raw-body path. Co-authored-by: Cursor <cursoragent@cursor.com> * Test pass_through_request state_raw_body uses httpx content= Cover non-streaming (async_client.request) and streaming (build_request) paths so SigV4 bytes on request.state are not replaced by json= of a hook-mutated dict. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>	2026-05-25 19:21:55 +05:30
ryan-crabbe-berri	4148667671	Fix spend logs v2 route permissions (#28705) ... Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: ryan-crabbe-berri <ryan-crabbe-berri@users.noreply.github.com>	2026-05-23 16:57:14 -07:00
yuneng-jiang	5f73ad4fe7	fix(team): refresh team cache on team_model_add/delete (LIT-3244) (#28683) ... * fix(team): refresh team cache on team_model_add/delete (LIT-3244) team_model_add and team_model_delete wrote to the DB but did not invalidate the in-memory LiteLLM_TeamTableCachedObj used by common_checks. After the v1.83.14 common_checks centralization made team.models authoritative on /v1/files and /v1/vector_stores/*, adding a Team-BYOK model silently failed to grant the new public model name to team members until the cache TTL expired (and a removed model kept working until then on the symmetric path). Extract the cache-refresh snippet from update_team into a small helper and apply it consistently at all three team-write sites. * test: also assert updated models in team-cache-refresh pin Strengthens the LIT-3244 regression test to also assert `call_kwargs["team_table"].models` matches the updated row, not just `team_id`. Both `existing_team` and `updated_team` share `team_id` in the test setup, so the previous assertion would have passed even if the implementation accidentally cached the pre-mutation row. Greptile review feedback. * fix(team): hydrate object_permission on cache-refreshing team updates The Prisma update calls in update_team, team_model_add, and team_model_delete returned a team row with object_permission_id set but object_permission=None (the relation was not requested via include=). _refresh_cached_team then wrote that to the in-memory LiteLLM_TeamTableCachedObj, and the cache-hit path in get_team_object returns the cached object without re-hydrating. Downstream consumers (validate_key_search_tools_against_team, the MCP/agent authz paths) treat a missing object_permission as no team-level restriction, so a team-write op silently dropped object-permission enforcement until the cache TTL expired or a DB-fetch path re-hydrated it. Add include={"object_permission": True} to all three updates so the refresh writes a complete cached team. Extend the LIT-3244 regression test to pin both the cached object_permission and the include shape on the Prisma call. Surfaced in PR review of LIT-3244.	2026-05-23 16:41:05 -07:00
yuneng-jiang	3bcfe41f05	test(model_prices): allow audio_transcription_config in schema (#28708) ... The schema in test_aaamodel_prices_and_context_window_json_is_valid uses additionalProperties: false. The azure/speech/azure-stt entry added in #27482 introduced an audio_transcription_config field that the schema did not whitelist, so the test fails on every branch built on top of staging. Add the field as a string property.	2026-05-23 16:19:43 -07:00
ryan-crabbe-berri	886e91b85e	fix(otel): stamp http.response.status_code on all error responses (#28405) ... * fix(otel): stamp http.response.status_code on all error responses httpx.HTTPStatusError exposes status under .response.status_code, not as a top-level attr, so unified-endpoint 5xx failures left the SERVER span without a status. The admin hooks only wrote a child span and never stamped or ended the parent at all, so admin 4xx/5xx (and success) responses were invisible to dashboards. Adds a fallback to .response.status_code in get_error_information, and ends the parent SERVER span in async_management_endpoint_{success,failure}_hook with the same _record_exception_on_span helper the unified path uses. Resolves LIT-3193 * test(otel): exercise httpx.HTTPStatusError through admin path Pins the contract that get_error_information's response.status_code fallback is reachable from any entry point — without this, a future refactor that bypasses _record_exception_on_span in the admin hooks could regress for httpx-wrapped exceptions while the unified suite still passes. * chore(otel): trim verbose comments in LIT-3193 changes Tighten docstrings and remove redundant section dividers/inline narration. Behavior is unchanged. * fix(otel): set span.status on management hook parent SERVER span Mirror the unified failure path: stamp StatusCode.ERROR on the parent SERVER span before recording the exception, and StatusCode.OK before ending it on success. Without this, OTEL backends filtering on span status (the idiomatic primitive) miss admin-endpoint failures even though the http.response.status_code attribute is correct. Extend assert_server_span_attrs to assert span.status.status_code matches the expected outcome so the gap can't regress. * fix(otel): close SERVER span on body-validation and unhandled errors Stash the SERVER span on request.state in auth so FastAPI exception handlers can finish it for failures that occur after auth but before the route handler (e.g. /model/new TypeError, /key/generate RequestValidationError). Without this, those requests left dangling spans missing http.response.status_code. Resolves LIT-3193 * fix(otel): generic 500 body, log exception details server-side Don't leak str(exc) and type(exc).__name__ to clients on uncaught exceptions. The full traceback is logged via verbose_proxy_logger and the SERVER span still gets http.response.status_code=500. Resolves LIT-3193 * fix(otel): stamp http.response.status_code on every SERVER span path Closes three remaining gaps where the proxy SERVER span ended without the http.response.status_code attribute: 1. ProxyException raised from _read_request_body (e.g. invalid JSON body) bubbled out of user_api_key_auth before the SERVER span was created, so the FastAPI handler had nothing to close and the trace never reached the backend. Hoist the span creation to a new idempotent _ensure_parent_otel_span_on_request_state helper called at the top of user_api_key_auth; wire openai_exception_handler to close the dangling span. Covers /v1/chat/completions, /v1/messages, /v1/responses (shared handler). 2. /v1/responses success — _handle_success ends the proxy span before async_post_call_success_hook fires on this path, so the hook's set_response_status_code_attribute(200) silently no-op'd against an ended span. Stamp 200 + set OK status at the close site in _handle_success / _end_proxy_span_from_kwargs via a shared _close_proxy_span_ok helper, so the attribute lands regardless of which success hook runs first. 3. Failure path for exceptions without code/status_code (e.g. a bare TypeError surfacing through _handle_llm_api_exception) — empty error_information.error_code → _record_exception_on_span skips the stamp → the hook ends the span. Default to 500 in async_post_call_failure_hook so the attribute is always set. Resolves LIT-3193	2026-05-23 19:21:32 +00:00
ishaan-berri	14c0a2b3e2	feat(prometheus): emit per-token-type detail metrics (LIT-3220) (#28372) (#28378) ... * feat(prometheus): emit per-token-type detail metrics (LIT-3220) (#28372) Adds five sparse counter metrics that break out the token detail fields providers already report in `usage.prompt_tokens_details` and `usage.completion_tokens_details`: - litellm_input_cached_tokens_metric (provider prompt-cache reads) - litellm_input_cache_creation_tokens_metric (Anthropic prompt-cache writes) - litellm_input_audio_tokens_metric (audio input tokens) - litellm_output_reasoning_tokens_metric (reasoning tokens) - litellm_output_audio_tokens_metric (audio output tokens) These are additive — existing input/output/total counters are unchanged, so no dashboards break. Each new counter is only incremented when the underlying detail is populated and > 0, keeping scrape output sparse for providers that don't report a given field. Data is read from the canonical Usage dict that `get_standard_logging_object_payload` already attaches at `standard_logging_payload["metadata"]["usage_object"]`, so no new plumbing through the logging pipeline is required. Tests: 10 new unit tests covering registration, label-set parity, all-types increment, zero/None/negative skip behaviour, and the no-metadata/no-usage_object no-op paths. Closes LIT-3220 Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai> Co-authored-by: Claude <noreply@anthropic.com> * chore: remove proof folder image --------- Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>	2026-05-23 12:17:42 -07:00
yuneng-jiang	5e16f20962	test(proxy): phase-4 payload behavior pinning for tier-2/3 key + team management endpoints (#28681) ... * test(proxy): phase-4 payload behavior pinning for tier-2/3 key + team management endpoints Extends the Phase 1–3 behavior-pin suite at tests/proxy_behavior/management/ with a second axis: payload-shape pinning. Phase 1–3 held payload minimal and pinned (actor, target) → status across 37 routes; Phase 4 holds the caller fixed at an authorized actor, varies the payload shape, and asserts the observable DB effect (on accept) or the named guard / row-unchanged (on reject). Faithfulness contract from Phase 1–3 is unchanged. Six families + one gap-closer (59 new scenarios, 620 → 679 total): * F1 — key budget / rate-limit (test_key_budget_limits.py, 18) * F2 — key↔team reassignment (test_key_team_change.py, 6) * F3 — team budget / rate-limit (test_team_budget_limits.py, 15) * F4 — member-info validation (test_team_member_info_validation.py, 5) * F5 — permission batching (test_team_permissions_bulk_update.py, 6) * F6 — org-scoped team access (+2 detail-string pins in existing files) * F7 — coverage gap-closer (test_f7_coverage_closeout.py, 7) Harness extensions in conftest.py (additive only): * create_scratch_org() seeder with its own scratch-prefixed budget row * budget / limit fields on create_scratch_team() * scratch teardown also sweeps litellm_organizationtable Coverage telemetry (behavior-suite-only): * key_management_endpoints.py 60 % → 65 % (+82 lines) * team_endpoints.py 62 % → 72 % (+137 lines, crosses 70 % stretch) Key lands under 70 % per plan §7 escape hatch — the gap is dominated by routes outside F1–F6 scope (key list/info v2 internals) and structurally dead org-budget guards (call sites at lines 889 + 2310 + 985 + 1751 load the org without include_budget_table=True, so org.litellm_budget_table is None at guard time and the aggregate guard no-ops). Pinned as observed no-op behavior so a future fix that flips the flag turns these into reds. Zero source-code changes; pyproject.toml diff is empty; test_route_coverage.py stays green untouched; G3 grep guards still green; local wall-time 14 s for the full suite (no coverage), 22 s with coverage. G4 regression-replay protocol executed against three representative fix-PR parents (410ce761dc, 0bd49ecb8b, 8bbc61e03c): all Phase 4 tests PASS at pre-fix SHAs — confirming the F1–F7 layer is a helper-body pin, not a regression-replay layer for those specific historical bypass shapes. Targeted RED-bait scenarios for each fix are left for a follow-up PR. * test(proxy): push key_management_endpoints.py past the 70% stretch (F7-extension) Adds 24 more payload-pin scenarios in test_f7_key_coverage_push.py following the same accepted-effect / rejected-guard pattern. Each scenario cites the file:line range it pins; same anti-snapshot rules apply. Target ranges (all reachable via HTTP-boundary payload variation): * 5942-6063 /key/health with metadata.logging → test_key_logging body * 4565-4692 /key/reset_spend happy + 404 + non-admin gate + value validation * 4421-4533 /key/regenerate ghost-404 + happy + new_key + grace_period * 4168-4202 _insert_deprecated_key body via grace_period * 6118-6133 _enforce_unique_key_alias duplicate-alias rejection * 6148-6169 validate_model_max_budget malformed-payload rejection * 4708-4789 validate_key_list_check user/team/org/key_hash branches * 2622-2733 /key/bulk_update mixed success/failure + admin gate + size limits * 2797-2950 /team/key/bulk_update all-keys path + explicit-keys dedupe + 404 * 5108-5207 /key/aliases admin + scoped + search-filter branches * 3253-3303 /key/info ghost + explicit-key + no-key-uses-auth-header * 3427-3436 generate_key_helper_fn budget_limits initialization * 1794-1815 prepare_key_update_data duration + budget_duration paths * 5280-5388 _build_filter_conditions across include_created_by_keys/team/sort/alias Coverage telemetry — full PR4 dataset: key_management_endpoints.py: 60 % → 71 % (+11 pts, +194 lines) team_endpoints.py: 62 % → 72 % (+10 pts, +137 lines) Both files now over the plan §7 PR4.M4 70 % stretch as a side effect of pinning real payload behavior. 721 tests pass in 19 s local (full suite, no coverage); 27 s with coverage. Zero source-code changes; pyproject.toml diff still empty; test_route_coverage.py + G3 grep guards still green. Honest finding (kept from the prior commit's body): four structurally-dead org-budget guards remain pinned as observed no-op behavior — they fire only when get_org_object is called with include_budget_table=True, which none of the four management-endpoint call sites currently do. Pinned so a future change that flips the flag turns these into reds. Two helper guards are honest-ceiling: _validate_reset_spend_value's isinstance check at line 4568 is unreachable from HTTP because Pydantic 422s non-float before the helper runs; same shape for /team/key/bulk_update's missing team_id / no-selector pre-handler guards. * test(proxy): address PR review — try/finally cleanup + loosen 500 envelope pins + Optional annotations Greptile review feedback on PR #28681: 1. Wrap manual budget-row cleanup in try/finally so an assertion failure doesn't leave non-scratch-prefixed budget rows orphaned across CI re-runs (test_team_new_with_team_member_budget_creates_budget_row and test_team_update_team_member_budget_upserts). 2. Loosen the two 500-status pins to in (400, 422, 500) — the named-guard substring is the real pin; the outer ValueError-wrap envelope is an implementation detail that a future improvement should be free to fix to a proper 400/422 without flipping these tests red. 3. Add missing Optional annotations on _seed_token's max_budget / metadata / team_id keyword args (they default to None). Greptile's typo flag on 'read-world' in the conftest comment is declined — 'read-world' is the project's established term for the immutable seeded world fixture (see other usages in conftest.py and actors.py). 721 tests still pass in 17 s.	2026-05-23 12:16:29 -07:00
ishaan-berri	203b529c9d	feat(azure): add speech transcription config support (#27482) ... Co-authored-by: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com> Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com>	2026-05-23 12:16:01 -07:00
Yassin Kortam	2eab9ee2c0	perf: reduce per-request and per-chunk overhead across Anthropic streaming hot paths (#28289) ... * perf: reduce per-request and per-chunk overhead across Anthropic streaming hot paths - Introduce pure-text fast-path in `_build_complete_streaming_response` that collapses O(N) `content_block_delta` events into a single equivalent SSE event before conversion, eliminating per-output-token Pydantic `ModelResponseStream` construction; non-text streams (tool_use, thinking, citations) fall back to the unchanged legacy path - Skip agentic streaming wrapper entirely when no callback overrides `async_should_run_agentic_loop`; the wrapper buffered every chunk and rebuilt the SSE response only to call hooks that all return `(False, {})` — a pure no-op for the default config - Serialize request body once (`json.dumps`) for both the pre-call log input and the wire, instead of twice; avoids a full O(payload) scan per request, significant for long-context Claude Code histories - Add fast path in `async_streaming_data_generator` that bypasses the per-chunk `async_post_call_streaming_hook` coroutine await, response-string materialization, and cost-injection call when no callback/guardrail/cost-injection is active (the default config) - Resolve `_DD_STREAMING_TRACE_ENABLED` once at import time; eliminate per-chunk `NullSpan` context manager allocation when Datadog tracing is disabled (the default) - Memoize `get_type_hints(AnthropicMessagesRequestOptionalParams)` with `@lru_cache(maxsize=1)` — resolves once per process instead of once per `/v1/messages` request (~80µs each) - Hoist `cost_injection_active` out of the per-chunk loop in `chunk_processor`; eliminates repeated `getattr` + endpoint-type checks on every streamed byte chunk - Extract `_build_passthrough_logging_result` from `_route_streaming_logging_to_handler` as a standalone static method to facilitate future off-loop dispatch - Convert `async_sse_data_generator` from an `async for: yield` trampoline to a direct return of the underlying generator, removing one async-generator layer per streamed chunk - Skip redundant `strip_empty_text_blocks_from_anthropic_messages` scan in `anthropic_messages_handler` when the async wrapper already sanitized (signalled via `_litellm_messages_presanitized` sentinel, popped before reaching provider params) - Gate debug log `f-string` evaluation behind `isEnabledFor(DEBUG)` in both the streaming generator and the transformation layer to avoid serializing entire message payloads on every request at non-debug log levels - Add benchmark script (`scripts/benchmark_anthropic_messages_perf.py`) with a local mock Anthropic SSE provider for reproducible TTFT and TPM measurement across commits/branches - Add parity tests asserting fast-path and legacy-path produce byte-identical logged/billed payloads, plus unit tests for agentic hook detection, pre-serialized body reuse, and memoized key resolution * perf: address greptile review for anthropic streaming hot path - Bail to legacy in `_collapse_pure_text_chunks` when content_block_delta events from different block indexes are observed without an intervening flush. Anthropic sends blocks strictly sequentially, but defensive bail prevents silent text-merging if the protocol ever interleaves. - Replace leaf-class `__dict__` check for `async_post_call_streaming_hook` in `_callback_capabilities` with a function-identity comparison that walks the MRO. A vendor base class can carry the override and the registered class can add nothing else; before this PR the hook was unconditionally invoked, so an inherited-override miss would silently drop the hook on the streaming path. - Add unit tests for both behaviors. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(mypy): narrow model_name to str in cost-injection branch The hoisted cost_injection_active flag in chunk_processor encodes the `bool(model_name)` requirement but mypy can't track that invariant through the local, so the per-chunk `_process_chunk_with_cost_injection( chunk, model_name)` calls flagged Optional[str] vs str. Pin a typed non-None local inside the cost-injection branch so mypy narrows correctly without changing runtime behavior. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-23 12:15:59 -07:00
Michael-RZ-Berri	3b2ce201d8	encrypt callback_vars in key/team metadata at rest (#27141) ... Co-authored-by: Michael Riad Zaky <michaelr@Michaels-MacBook-Air.local> Co-authored-by: Yuneng Jiang <yuneng@berri.ai>	2026-05-23 12:15:44 -07:00
Mateo Wang	492891cad8	CI: copy of #25177 (OCI GenAI: embeddings, streaming/reasoning fixes, model catalog) (#28223) ... * fix(opentelemetry): JSON-serialize dict metadata fields for OTEL span attributes (#27451) (#27455) Squash-merged by litellm-agent from Anai-Guo's PR. * feat(dashscope): add embeddings and reranks(qwen3-rerank) support via OpenAI-compatible endpoint (#27508) Squash-merged by litellm-agent from yimao's PR. * fix(vertex_ai/gemini): raise BadRequestError when image_url or url fi… (#24550) Squash-merged by litellm-agent from krisxia0506's PR. * fix(vertex_ai): raise error on mid-stream 429/error chunks instead of silently swallowing (#23711) Squash-merged by litellm-agent from krisxia0506's PR. * fix: raise BadRequestError for file content blocks missing 'file' sub… (#24503) Squash-merged by litellm-agent from krisxia0506's PR. * Fix Gemini MIME detection for extensionless GCS URIs (#27278) Squash-merged by litellm-agent from krisxia0506's PR. * fix(vertex_ai/partner_models): drop unused vertexai SDK gate from count_tokens (closes #28084) (#28107) Squash-merged by litellm-agent from voidborne-d's PR. * feat(chart): add support for autoscaling behavior in HPA (#27990) Squash-merged by litellm-agent from FabrizioCafolla's PR. * feat(proxy): add blocked flag to models for pause/resume from the UI (#27927) Squash-merged by litellm-agent from Cyberfilo's PR. * fix: pass socket timeouts to Redis cluster clients (#27920) Squash-merged by litellm-agent from tomdee's PR. * Fix/cache token (#28009) Squash-merged by litellm-agent from escon1004's PR. * fix(deepseek): forward reasoning_content in multi-turn thinking mode conversations (#28080) Squash-merged by litellm-agent from Divyansh8321's PR. * fix(guardrails): return HTTP 400 instead of 500 for blocked requests (#27617) * fix: reset org and tag budgets (#27326) * reset org budgets * reset tag budgets --------- Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain> * fix(ui): omit allowed_routes from key edit save when unchanged (#27553) * fix(ui): omit allowed_routes from key edit save when unchanged When a team admin opens Edit Settings on a key with key_type=AI APIs and saves without changing anything, the UI re-sends the existing allowed_routes value, which the backend's _check_allowed_routes_caller_permission gate rejects for non-proxy-admins (LIT-2681). Strip allowed_routes from the patch in handleSubmit when it deep-equals the original keyData.allowed_routes. The backend treats absence as "leave alone," so no-op saves now succeed for non-admins. Admins explicitly editing the field still send the new value. * fix(ui): order-insensitive allowed_routes diff + cover null-original case Address Greptile review: - Switch the "is allowed_routes unchanged" check to a Set-based comparison so a server-side reorder of the array doesn't register as a user edit and re-trigger LIT-2681. - Add two regression tests: (1) keyData.allowed_routes is null and the form is untouched — patch should strip the field; (2) server returned routes in a different order than the user originally entered — patch should still recognize the value as unchanged. * chore(ui): strip ticket refs and tighten comments in key edit fix - Remove internal-tracker references from in-code comments - Tighten the WHY comment in handleSubmit to two lines - Drop redundant test-block comments — test names already describe the case * fix(ui): annotate Set<string> generic in allowed_routes diff to fix tsc * fix(guardrails): return HTTP 400 instead of 500 for guardrail-blocked requests GuardrailRaisedException and BlockedPiiEntityError both lacked a status_code attribute. When these exceptions reached the proxy exception handler (getattr(e, 'status_code', 500)), the fallback defaulted to HTTP 500 — making intentional guardrail blocks indistinguishable from server errors and causing unnecessary client retries. Changes: - Add status_code=400 (keyword-only) to GuardrailRaisedException - Add status_code=400 (keyword-only) to BlockedPiiEntityError - Update _is_guardrail_intervention() to recognize both exceptions so downstream loggers record 'guardrail_intervened' instead of 'guardrail_failed_to_respond' - Add 6 unit tests for default/custom status codes and getattr pattern - Strengthen existing blocked-action test with status_code assertion Fixes #24348 --------- Co-authored-by: Michael-RZ-Berri <michael@berri.ai> Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> * fix(router/proxy): address Greptile P1+P2 review comments on PR #28161 - router: raise ServiceUnavailableError (503) instead of RouterRateLimitErrorBasic (429) when a specifically-addressed deployment is administratively blocked; 429 misleads retry-enabled clients into spinning forever against a paused model - proxy_server: compute get_fully_blocked_model_names() once before both branches in model_list() instead of duplicating the call in each branch - deepseek: upgrade silent debug log to warning when injecting placeholder reasoning_content so callers are clearly notified of degraded multi-turn quality - tests: update two blocked-deployment assertions to expect ServiceUnavailableError Co-authored-by: Cursor <cursoragent@cursor.com> * fix: address bug detection findings (cache token order, mutable defaults) Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix: address bugs in async pass-through, anthropic cache token detection, rerank tests - async_get_available_deployment_for_pass_through: enforce blocked check on specific deployments - cost_calculator: detect anthropic-style usage by attribute presence (not truthiness) to avoid mixing OpenAI cached_tokens into anthropic normalization when read=0 - dashscope rerank tests: pass request to httpx.Response constructions for consistency Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix code qa * fix(vertex_ai/gemini): strip MIME parameters from GCS contentType GCS object metadata's contentType field can include parameters such as 'text/html; charset=utf-8'. Strip them in _apply_gemini_mime_type_aliases so downstream get_file_extension_from_mime_type sees a bare MIME type. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(vertex_ai/gemini): clarify mime-type error message string concatenation Co-authored-by: Yassin Kortam <yassin@berri.ai> * feat(oci): add embeddings, fix streaming/reasoning, expand model catalog - Add OCIEmbedConfig with full Cohere embed support (7 models, batch up to 96) - Fix sync streaming: split SSE events on \n\n before JSON parsing - Fix reasoning models (Gemini 2.5, xAI Grok): make completionTokens and message optional in OCIResponseChoice to handle max_tokens exhausted on reasoning - Fix compartment_id resolution in chat transform to use resolve_oci_credentials - Fix tool call id: make OCIToolCall.id optional, generate UUID fallback for providers (Google via OCI) that omit it - Add OCI_KEY env var support for inline PEM keys - Fix datetime.utcnow() deprecation in request signing - Expand model catalog: 29 OCI models including Llama 4, Gemini 2.5, xAI Grok, Cohere Command A, and all Cohere embed variants - Add 37 live integration tests: sync/async completions for Meta/Google/xAI/Cohere, sync/async embeddings, tool use across all vendors, streaming, env var auth - Add 23 embed unit tests covering all transform and validation paths * fix(oci): remove dead OCI elif branch in utils.py, align async split_chunks with sync version * test(oci): add unit tests for split_chunks fix and no-duplicate-OCI-branch guard * fix(oci): address remaining bugs from issue #25082 — streaming signed body, Cohere stop sequences, hardcoded defaults - Bug 1: sync and async streaming paths now use signed_json_body when provided instead of re-serializing data with json.dumps() — the OCI RSA-SHA256 signature covers the exact request body bytes, so re-serializing produces an invalid sig - Bug 3: Cohere stop sequences now map to 'stopSequences' (was incorrectly 'stop') - Bug 4: removed hardcoded Cohere defaults (maxTokens=600, temperature=1, topK=0, topP=0.75, frequencyPenalty=0) that silently overrode user intent on every call - Added 6 unit tests covering all three fixes * fix(oci): comprehensive code quality pass — bugs, tests, schema accuracy - Fix Cohere tool call IDs (was always call_0; now UUID per call) - Fix TOOL_CALL finish reason mapping in both sync and streaming paths - Fix Cohere stop parameter mapping (stop → stopSequences) - Remove hardcoded Cohere defaults (maxTokens/topK/topP/frequencyPenalty) - Fix content[0] safety guard against empty content arrays - Fix streaming signed body used consistently (not re-serialized) - Raise OCIError (not bare Exception/ValueError) throughout - Centralize OCI_API_VERSION constant; import uuid at module level - Fix embed get_complete_url to strip trailing slashes from api_base - Fix OCIEmbedResponse schema: add inputTextTokenCounts (actual OCI field) - Fix embed usage computed from inputTextTokenCounts (sum of per-input counts) - Fix Cohere toolCallId included in tool result messages - Add OCIToolCall.id as Optional (absent in Google/xAI streaming chunks) - Update tests to reflect correct behavior (no hardcoded defaults, UUID ids, deferred credential validation, OCIError vs ValueError, real response schema) * test(oci): move integration tests to tests/llm_translation/ Addresses greptile P1: tests/test_litellm/ is for mock-only unit tests (make test-unit target). Real-network OCI tests now live in the correct location alongside other provider integration tests. * fix(oci): align types and transformation with official OCI SDK - Remove OCIVendors.GEMINI — apiFormat="GEMINI" is invalid; all non-Cohere models use apiFormat="GENERIC" - Add toolChoice, logitBias, logProbs to OCIChatRequestPayload so params present in the mapping are no longer silently dropped by Pydantic - Exclude n→numGenerations from Cohere param map (not a Cohere API field) - Fix CohereToolResult: change callId/result to call/outputs matching the OCI SDK's CohereToolResult structure - Fix CohereToolMessage: replace non-existent toolCallId with toolResults list; update adapt_messages_to_cohere_standard to build proper tool-result history entries by resolving tool call name+params from preceding assistant messages - Map generic-model stream finish reasons to OpenAI convention (COMPLETE→stop, MAX_TOKENS→length, TOOL_CALLS→tool_calls), consistent with the existing Cohere streaming path - Add optional id field to OCIEmbedResponse so valid API responses carrying an id are not rejected by the Pydantic model * fix(oci): use 'output' key in Cohere tool result outputs (matches reference impl) * fix(oci): port schema/type utilities from langchain-oracle reference impl - Add resolve_oci_schema_refs: inline $ref/$defs — OCI rejects JSON Schema refs - Add resolve_oci_schema_anyof: flatten Optional[T] anyOf (Pydantic v2 emits these) - Add sanitize_oci_schema: strip title, normalise null types, ensure array items - Add OCI_JSON_TO_PYTHON_TYPES: Cohere expects Python type names (str/int/float), not JSON Schema names (string/integer/number) - Add enrich_cohere_param_description: embed enum/format/range/pattern constraints into description since CohereParameterDefinition has no dedicated fields - Apply all of the above in adapt_tool_definitions_to_cohere_standard and adapt_tool_definition_to_oci_standard - Fix toolChoice conversion: map OpenAI string ('auto','none','required') to OCI dict form ({"type":"AUTO"} etc.) — the API rejects plain strings - Update unit test expectations to match correct Python type names and enriched descriptions * refactor(oci): split transformation.py into cohere.py and generic.py transformation.py was 1 243 lines doing too many jobs. Split along the same boundaries as the langchain-oracle reference (providers/cohere.py, providers/generic.py): chat/cohere.py — Cohere message/tool building, response + stream parsing chat/generic.py — Generic message/tool building, response + stream parsing transformation.py — thin OCIChatConfig orchestrator + OCIStreamWrapper Public symbols (OCIChatConfig, OCIStreamWrapper, adapt_messages_to_*, OCIRequestWrapper, version, …) remain importable from transformation.py for backward compatibility. OCIStreamWrapper gains delegating shims for _handle_cohere_stream_chunk and _handle_generic_stream_chunk so existing test call sites keep working unchanged. transformation.py: 1 243 → 620 lines * refactor(oci): principal-level code quality pass - Remove _extract_text_content duplication — single definition in cohere.py, imported where needed; instance method on OCIChatConfig eliminated - Move cryptography imports to module level with _CRYPTOGRAPHY_AVAILABLE flag and _require_cryptography() guard; no more re-import on every signing call - Move litellm version import to module level via litellm._version; remove inline import inside validate_oci_environment - sign_with_manual_credentials now returns Tuple[dict, bytes] matching sign_with_oci_signer — asymmetry eliminated, Optional[bytes] guards removed throughout stream wrappers (signed_json_body: bytes = b"") - Rename _openai_to_oci_cohere_param_map → openai_to_oci_cohere_param_map for consistency with openai_to_oci_generic_param_map - Remove double-key bug in map_openai_params where responseFormat was stored under both OCI and OpenAI key names simultaneously - Remove delegating shims (adapt_messages_to_cohere_standard, adapt_tool_definitions_to_cohere_standard, _handle_generic_stream_chunk) from OCIChatConfig/OCIStreamWrapper; tests now import directly from cohere.py and generic.py where symbols live - Trim __all__ to 7 genuine public symbols; remove the 13-symbol list that existed only to support test imports - Collapse per-model integration test classes into pytest.mark.parametrize; CHAT_MODELS list is the single source of truth for model-specific config - Black + Ruff clean across all OCI files * fix(oci): address PR review findings - types/llms/oci.py: add "TOOL_CALL" to CohereChatResponse.finishReason Literal so Pydantic does not raise ValidationError on non-streaming Cohere tool-use calls (Greptile P1) - test_oci_cohere_tool_calls.py: add test covering TOOL_CALL finish reason - model_prices_and_context_window.json: remove 6 duplicate oci/cohere.embed-* keys that were silently overridden by the more complete entries already present in the file (Greptile P1) - common_utils.py: move OCI_API_VERSION here from chat/transformation.py so embed/transformation.py does not need to import chat/transformation; change Protocol stub body from ... to pass (CodeQL "statement no effect"); add comment to sha256_base64 clarifying it implements OCI HTTP signing spec, not password hashing (CodeQL false positive) - chat/transformation.py: import CustomStreamWrapper from litellm_core_utils.streaming_handler instead of litellm.utils to reduce import cycle depth (CodeQL cyclic import) - chat/cohere.py, chat/generic.py: import Usage and ChatCompletionMessageToolCall from litellm.types.utils instead of litellm.utils for the same reason - embed/transformation.py: import OCI_API_VERSION from common_utils instead of chat/transformation (removes the embed→chat import edge) * test(oci): add unit tests to improve patch coverage - test_oci_common_utils.py (new): covers sha256_base64, build_signature_string, OCIRequestWrapper.path_url, resolve_oci_credentials, get_oci_base_url, validate_oci_environment, sign_with_oci_signer error paths, sign_oci_request routing, load_private_key_from_file error paths, resolve_oci_schema_refs (including circular ref and external $ref), resolve_oci_schema_anyof, sanitize_oci_schema (all branches), enrich_cohere_param_description - test_oci_generic_chat.py (new): covers content-message error paths (non-dict item, unsupported type, non-string text, invalid image_url), tool-call validation error paths, adapt_messages_to_generic_oci_standard error paths, handle_generic_response (None message, text content, tool calls), handle_generic_stream_chunk (finish reasons, streaming tool calls), OCIStreamWrapper non-string chunk error - test_oci_chat_transformation.py: add error paths for validate_environment (empty messages), transform_request (missing compartment_id, Cohere without user messages), transform_response (error key), map_openai_params (unsupported param with and without drop_params), tool_choice string mapping - test_oci_cohere_tool_calls.py: add edge cases for stream chunk finish reasons (TOOL_CALL, MAX_TOKENS, unknown), _extract_text_content with non-dict list items and non-string input, adapt_messages_to_cohere_standard with malformed JSON tool arguments * fix(oci): rename supports_streaming to supports_native_streaming in model prices The JSON schema for model_prices_and_context_window.json uses `supports_native_streaming` (not `supports_streaming`) and has `additionalProperties: false`. Rename the field across all OCI entries to pass the schema validation test. * test(oci): add 67 tests targeting uncovered happy paths for coverage Boost patch coverage on the four lowest-coverage OCI files: - common_utils.py: sign_with_manual_credentials (oci_key / oci_key_file paths), sign_oci_request routing, _require_cryptography - generic.py: adapt_messages_to_generic_oci_standard (all roles), adapt_tool_definition_to_oci_standard, adapt_tools_to_openai_standard, handle_generic_stream_chunk text/finish-reason paths - cohere.py: _extract_text_content, adapt_messages_to_cohere_standard (all roles including tool results), handle_cohere_response / handle_cohere_stream_chunk all finish-reason branches - transformation.py: get_vendor_from_model, OCIChatConfig._get_optional_params (toolChoice string→dict, responseFormat, tools for both vendors), transform_request for GENERIC model, get_sync/async_custom_stream_wrapper with mocked HTTP, OCIStreamWrapper.chunk_creator happy paths * fix(oci): suppress CodeQL false positive on sha256_base64 (OCI HTTP signing, not password hashing) * fix(oci): remove 6 duplicate model price entries and reconcile conflicting values Six OCI chat model keys appeared twice in model_prices_and_context_window.json with conflicting pricing/context data (JSON parsers silently discard the first). Remove the first-occurrence entries and update the surviving entries: - meta.llama-4-maverick / llama-4-scout: keep updated entries (free preview pricing, larger context windows, vision support) - meta.llama-3.1-70b: keep original pricing, restore supports_native_streaming - google.gemini-2.5-{flash,pro,flash-lite}: keep OCI pricing page values, restore supports_native_streaming * fix(oci): route GPT-5 family to maxCompletionTokens GPT-5 / GPT-5-mini / GPT-5-nano / GPT-5.5 on OCI reject "maxTokens" with HTTP 400: Invalid 'maxTokens': Unsupported parameter: 'maxTokens' is not supported with this model. Use 'maxCompletionTokens' instead. (Same convention as OpenAI's reasoning-API contract.) Add a model-aware rename in OCIChatConfig._get_optional_params so the request payload uses maxCompletionTokens when the model id starts with openai.gpt-5. Regular Llama / Cohere / Gemini / GPT-4.x continue to use maxTokens unchanged. Also widen OCIChatRequestPayload to carry the new optional field so it survives Pydantic serialization. Verified live against OCI us-chicago-1: - openai.gpt-5, gpt-5-mini, gpt-5-nano, gpt-5.5 all return 200 - Full feature sweep on gpt-5.5 (basic, system, multi-turn, streaming, tools, usage) all green - meta.llama-3.3-70b-instruct still uses maxTokens (no regression) 4 new unit tests cover the helper, the routing in both pre- and post-translation states, and Pydantic serialization. * ci(oci): fix CI failures — black formatting + recursive_detector ignore - Run black on litellm/llms/oci/common_utils.py + 3 OCI test files that drifted out of black-compliance during the rebase. - Add the three bounded recursive functions in oci/common_utils.py (`_resolve`, `resolve_oci_schema_anyof`, `sanitize_oci_schema`) to the recursive_detector IGNORE_FUNCTIONS list. All three are bounded: `_resolve` uses a `resolving_stack` cycle guard; the other two are bounded by JSON-schema tree depth (no cycles in well-formed input), matching the pattern of the existing OCI/Vertex schema walkers already on the list. * fix(oci): silence MyPy errors in cohere.py — typed-dict access Two errors flagged by `lint` CI: llms/oci/chat/cohere.py:73: "object" has no attribute "__iter__" llms/oci/chat/cohere.py:119: No overload variant of "get" of "dict" matches argument types "object", "CohereToolCall" Both stem from `msg.get("tool_calls")` / `msg.get("tool_call_id")` returning `object` per the AllMessageValues TypedDict union. Bind to `Any` locally for the iteration and coerce the lookup key with `str()`, removing the now-unused `# type: ignore` on those lines. No behaviour change — pure type-narrowing for the type checker. * fix(oci): silence CodeQL py/weak-sensitive-data-hashing on sha256_base64 CodeQL's taint analysis traces request bodies back to environment-loaded secrets and flags `hashlib.sha256(body).digest()` as `py/weak-sensitive-data-hashing` — even though SHA-256 is the algorithm mandated by the OCI HTTP request signing spec for the `x-content-sha256` header (not a password/secret hash). The previous suppression used legacy `# lgtm[...]` syntax which the modern CodeQL action ignores. Switch to Python's standard `hashlib.sha256(..., usedforsecurity=False)` (Python 3.9+) which CodeQL honours as a non-security declaration. Behaviour unchanged. * feat(oci): add reasoning_effort passthrough — only true missing primitive OCI's GenericChatRequest exposes a reasoningEffort field (NONE/MINIMAL/LOW/MEDIUM/HIGH) that's the single biggest cost knob for reasoning-capable models on the service: - GPT-5 family - Gemini 2.5 - Grok reasoning variants (3-mini, 4-fast, 4.20) - Cohere Command-A-Reasoning Setting reasoning_effort=LOW typically cuts reasoning-token spend 5-10× vs the default. Without exposing this, litellm users had no way to tune cost-vs-quality on these models. The other GenericChatRequest fields (verbosity, parallel_tool_calls, logit_bias, n, metadata, web_search_options, prediction) are not exposed because they are not missing primitives — they either duplicate prompt-engineering, framework-level controls, or are too niche to justify the maintenance surface. We only ship what users genuinely can't accomplish another way. Excluded from the Cohere v1 param map: CohereChatRequest has no reasoningEffort field, and Cohere reasoning models (cohere.command-a-reasoning) use COHEREV2 which is a separate request type not covered by this PR. Verified live: GPT-5.5 + reasoning_effort="HIGH" sends {"reasoningEffort": "HIGH"} on the wire and OCI accepts the request. * feat(oci): reasoning_effort + reasoning_tokens for OCI GenAI Three small additions for OCI reasoning models, requested by users testing the PR in production fork builds: 1. **reasoning_effort param mapping (GENERIC vendors).** OCI expects uppercase levels ("LOW"/"MEDIUM"/"HIGH"/"NONE") on `reasoningEffort`, but OpenAI-compatible clients send lowercase. Mapped + uppercased in `_get_optional_params`. Marked unsupported on Cohere V1/V2 since OCI Cohere has no reasoning models (avoids Pydantic validation failure on CohereChatRequest). 2. **"disable" → "NONE" mapping.** OpenAI uses "disable" to turn off reasoning; OCI uses "NONE". Without this, callers get a 400. 3. **reasoning_tokens propagated to Usage.** OCI returns `completionTokensDetails.reasoningTokens` but it wasn't being passed to LiteLLM's Usage object. Now flows through to `Usage.completion_tokens_details.reasoning_tokens` so callers can track reasoning token consumption for cost/observability. Tests: 7 new unit tests in TestOCIReasoningEffort covering upper/lower case, "disable"→"NONE", Cohere drop/raise paths, and reasoning_tokens extraction (with and without completionTokensDetails). 5 new live integration tests against xai.grok-3-mini in us-chicago-1 verifying the full request/response loop end-to-end. Existing test_transform_response_simple_text assertion that completion_tokens_details was None has been updated to assert reasoning_tokens flows through. Verified live on xai.grok-3-mini: reasoning_effort=low → OCI accepts "LOW", returns reasoningTokens=316 in usage. reasoning_effort=disable → OCI accepts "NONE". Full suite: 370/370 unit + 51/51 integration. * fix(codeql): re-scope py/weak-sensitive-data-hashing exclusion to OCI signing file CodeQL's taint analysis re-fires the `py/weak-sensitive-data-hashing` alert at `litellm/llms/oci/common_utils.py:103` whenever upstream code paths into the OCI signing module change (touching `transformation.py` opens new flow paths that CodeQL re-evaluates from scratch). The `hashlib.sha256(..., usedforsecurity=False)` declaration silences the direct-call form of the query but not the taint-flow form. SHA-256 here is mandated by the OCI HTTP signing specification for the x-content-sha256 content-integrity header — not for password storage: https://docs.oracle.com/en-us/iaas/Content/API/Concepts/signingrequests.htm CodeQL has no per-query path filter and GitHub Code Scanning ignores inline lgtm/codeql comments, so path-ignoring this single ~560-line signing utility file is the narrowest available suppression. All other files retain full coverage of py/weak-sensitive-data-hashing — including litellm/proxy/utils.py where the rule legitimately applies. This restores the NEUTRAL CodeQL state the PR had on prior commits (see `2111c98af7` for the same approach on the previous branch evolution that the cherry-pick was rebased onto a different baseline). * fix(oci): drop duplicate text on Cohere streaming terminal chunk OCI Cohere's terminal SSE event re-sends the full assembled response in `text` alongside a populated `chatHistory`. Emitting that text as another delta concatenates the entire response onto the already-streamed output (e.g. "How can I help?How can I help?"). Use `chatHistory is not None` as the discriminator for the consolidated terminal event — `finishReason` is a weaker signal that could in principle appear on a non-consolidated chunk. The two coincide today; this preserves correctness if OCI ever ships finishReason on an incremental chunk. Adds a live-OCI integration regression test that compares streamed vs non-streamed length and asserts the response prefix appears only once. Verified to fail under the previous code with the exact reported reproduction: 'Hello! How can I help you today?Hello! How can I help you today?'. Reported by @gotsysdba on PR #25177. * fix(oci): buffer SSE stream across HTTP read boundaries The old split_chunks helper split each individual HTTP read on "\n\n", which assumed SSE event boundaries always aligned with read boundaries. In practice the OCI streaming endpoint delivers events that may: - straddle two reads (chunk_creator gets a truncated JSON and crashes) - arrive separated by a single "\n" instead of "\n\n" - share a read with multiple complete events Replace the inline split with module-level helpers _iter_sse_events (sync) / _aiter_sse_events (async) that maintain a buffer across reads, split on any newline, and yield only complete "data:" lines. Add 25 regression tests covering event-split-across-reads, tiny-chunk reads, single-newline separators, keepalive/comment lines, trailing partial events flushed at EOF, "\r\n" line endings, and an end-to-end smoke test that feeds an awkwardly-chopped payload through the splitter into OCIStreamWrapper.chunk_creator. Reported by John Lathouwers. * test(oci): repoint TestOCIKeyNormalization to sign_with_manual_credentials The signing helper moved from OCIChatConfig._sign_with_manual_credentials to a module-level sign_with_manual_credentials in common_utils.py. Four tests in TestOCIKeyNormalization still called the old method: - 2 failed outright with AttributeError - 2 passed by accident because they used pytest.raises(Exception), which happily caught the AttributeError instead of exercising the intended OCIError path Repoint all four to the new module-level function so they exercise the actual oci_key type-validation branch. * fix(oci): validate oci_region before URL interpolation to prevent SSRF Anchor oci_region to ^[a-z][a-z0-9-]{0,30}[a-z0-9]$ inside get_oci_base_url so user-supplied regions that would redirect the signed request to an attacker-controlled host (e.g. 'evil.com/#') fail with HTTP 400 before the URL or signature is built. Empty string still falls back to the us-ashburn-1 default, so existing callers are unaffected. * test(audio): skip when gpt-4o-audio-preview is unavailable upstream OpenAI retired `gpt-4o-audio-preview` (404 model_not_found in CI as of 2026-05-19), and the existing try/except in these tests only re-raised on 'openai-internal' errors. Other exceptions were silently swallowed, so the next line ran with an unbound `response`/`completion` and failed with an unrelated UnboundLocalError that masked the real cause. Extend the skip condition to also cover model_not_found / 'does not exist' so the suite reports the upstream outage cleanly, matching the pattern used in ce87c41 for the realtime and nvidia_nim rerank tests. Re-raise unknown exceptions instead of falling through. * fix(oci/router): catalog-driven maxCompletionTokens; generic blocked-deployment message - Drive OCI maxCompletionTokens via supports_reasoning from the model catalog instead of a hardcoded openai.gpt-5 prefix. Add OCI GPT-5 family entries (gpt-5, gpt-5-mini, gpt-5-nano) with supports_reasoning: true. Gate the override to non-Cohere vendor so Cohere reasoning models keep maxTokens (Cohere endpoint does not accept maxCompletionTokens). - Replace proxy-specific 'Contact your proxy admin' phrasing in the four Router blocked-deployment ServiceUnavailableError messages with neutral SDK-appropriate text. * fix(oci/cohere): guard handle_cohere_response against missing usage * fix(oci): address bug review findings in chat transformation - Cohere param map: keep tool_choice/n as False (not omitted) so unsupported params are dropped or rejected rather than silently passed through. - get_complete_url: when an explicit api_base/litellm.api_base is provided, use it as-is instead of unconditionally appending /20231130/actions/chat (mirrors the embed config behavior). - Cohere stream: require both chatHistory and finishReason to be present to identify a terminal consolidation chunk, avoiding silent text suppression if chatHistory ever appears on a non-terminal chunk. - Generic usage: use 'is not None' for reasoningTokens so a legitimate value of 0 is preserved instead of being treated as absent. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/cohere): emit tool calls in streaming and null content when text empty handle_cohere_response now sets message.content to None when the Cohere response text is empty, matching the OpenAI convention for tool-call-only responses. handle_cohere_stream_chunk now extracts toolCalls — both directly from the chunk and from the terminal chunk's chatHistory CHATBOT message — and emits them in the delta. Previously, CohereStreamChunk lacked a toolCalls field, so any tool calls in the stream were silently dropped. * fix(oci): preserve tool results, embed URL path, and generic finish reason - Use SerializeAsAny on CohereChatRequest.chatHistory so subclass-specific fields like CohereToolMessage.toolResults are not dropped during Pydantic v2 serialization. - Make OCIEmbedConfig.get_complete_url append the /20231130/actions/embedText action path consistently with chat, so setting litellm.api_base to the region inference base URL no longer posts to the bare hostname. - Map OCI finishReason (COMPLETE / MAX_TOKENS / TOOL_CALLS) to OpenAI finish_reason values in handle_generic_response, mirroring the streaming handler and the Cohere non-streaming handler. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/generic): silence mypy assignment error on dynamic finish_reason * fix(oci/embed): always set usage on embedding response Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/chat): append /20231130/actions/chat to explicit api_base Restore the embed-style behavior so OCIChatConfig.get_complete_url always appends the OCI GenAI chat path. Routing through get_oci_base_url ensures the optional explicit api_base has its trailing slash stripped before the suffix is joined, matching the embed config and the test_respects_explicit_api_base expectation. * fix(oci/cohere): mark logprobs/logit_bias unsupported and normalize unknown stream finish reasons Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/cohere): preserve trailing tool result in chatHistory When the last message in the OpenAI-format input is a tool result (the standard agentic continuation pattern), the prior messages[:-1] slice silently dropped that tool result from chatHistory and the model never saw it. Excluding the last user message by index instead keeps tool results that trail the last user turn intact. * fix(main): remove dead OCI embedding elif block The earlier elif at line 5119 already routes OCI embeddings through the base HTTP handler with the headers None-guard, so the later identical block was unreachable dead code. * test(oci): move integration tests out of llm_translation mock-only folder Greptile flags tests/llm_translation/ as mock-only via a project-specific rule; relocate the live-network OCI integration suite to tests/integration/ and adjust the in-file sys.path / run instructions accordingly. * fix(oci/cohere): suppress tool calls on stream terminal consolidation chunk The terminal SSE event re-sends the full assembled response in both `text` and `chatHistory`. The existing logic already suppresses `text` to avoid double-emit, but tool calls extracted from the terminal chunk (via `typed_chunk.toolCalls` or the `chatHistory` CHATBOT fallback) would still be re-emitted with fresh uuid4 IDs. If OCI Cohere ever streams tool calls progressively in intermediate chunks (now possible since CohereStreamChunk has a toolCalls field), this would cause downstream agentic frameworks to execute each tool call twice. Suppress tool calls on the terminal consolidation chunk for the same reason `text` is suppressed. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci,httpx): normalize finish_reason, preserve response_format, fix sync embed JSON content-type - cohere.py / generic.py: normalize unknown OCI finishReason values (ERROR, ERROR_TOXIC, CONTENT_FILTERED, USER_CANCEL, ...) to 'stop' in non-streaming and streaming generic handlers, matching the streaming Cohere handler so downstream consumers switching on finish_reason aren't broken by raw OCI values. - transformation.py: restore the dual-key alias so optional_params still carries the original 'response_format' key alongside the OCI-mapped 'responseFormat'. Downstream litellm framework code (json_mode detection, logging) inspects 'response_format' after map_openai_params runs. - llm_http_handler.py: make the sync embedding path mirror the async path — when sign_request returns no signed_body, send via json=data (which sets Content-Type: application/json) instead of data=json.dumps(data) which doesn't. Removes a sync/async behavioural asymmetry for non-OCI providers that adopt the sign_request pattern. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): clean up OCIChatConfig init, normalize generic stream finish reasons, correct embed sign_request return type - Replace fragile setattr(self.__class__, ...) pattern in OCIChatConfig.__init__ with a @property for has_custom_stream_wrapper, matching the pattern used by other providers. - Normalize unknown OCI finish reasons (e.g. ERROR, ERROR_TOXIC, USER_CANCEL) to 'stop' in handle_generic_stream_chunk, matching the existing Cohere stream handler behaviour. - Tighten OCIEmbedConfig.sign_request return type from Tuple[dict, Optional[bytes]] to Tuple[dict, bytes] — sign_oci_request never returns None for the body, and this matches OCIChatConfig.sign_request. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): strip trailing action path in get_oci_base_url to avoid URL doubling A fully-formed OCI endpoint URL (e.g. https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/20231130/actions/chat) passed via api_base previously had the action path appended a second time by get_complete_url in both chat and embed configs, yielding a 404. get_oci_base_url now strips a trailing /20231130/actions/<name> so callers can always append the action path safely. * fix(httpx): preserve sync embed data= kwarg to avoid breaking mock-based tests The earlier sync_httpx_client.post() call passed data=json.dumps(data), which downstream embedding tests assert on (e.g. tests for hosted_vllm, jina_ai, watsonx). Switching to json=data changed the kwarg name and broke those tests. The OCI signed_body path keeps using data=signed_body and is unaffected. * fix(oci): stable tool-call ids across stream chunks; lenient Cohere finishReason - Replace random uuid4 per chunk with a deterministic content-derived digest for synthetic tool-call ids in both Cohere and Generic OCI handlers. Previously, when OCI omitted 'id' (always for Cohere, often for Generic streaming deltas), every chunk for the same logical tool call received a new uuid, causing downstream stream-mergers (which key off id) to treat each fragment as a distinct call. - Relax CohereChatResponse.finishReason from a strict Literal[...] to Optional[str], matching CohereStreamChunk.finishReason. The handle_cohere_response 'elif oci_finish_reason is not None' fallback was previously unreachable because Pydantic raised ValidationError on any unknown value before the fallback executed. Now non-streaming responses degrade unknown reasons to 'stop' just like the streaming path. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/embed): validate OCI credentials in validate_environment Mirror OCIChatConfig.validate_environment so embedding requests fail fast with a clear error when oci_user/oci_fingerprint/oci_tenancy/ oci_compartment_id or an oci_key/oci_key_file is missing, instead of deferring the failure until sign_request. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(oci/embed): expect OCIError from validate_environment when credentials are missing OCIEmbedConfig.validate_environment now raises eagerly (mirroring OCIChatConfig) when oci_user/oci_fingerprint/oci_tenancy/oci_compartment_id or oci_key/oci_key_file is missing. Update the test to match. * fix(oci): polish stream chunk handling and signed body default - cohere stream terminal consolidation now emits content=None instead of "" - drop redundant index truthiness check (None is already replaced with 0) - accept both "TOOL_CALL" and "TOOL_CALLS" finish reasons in cohere - signed_json_body defaults to None and uses explicit None check, so an explicitly empty bytes body wouldn't be silently re-serialized Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/chat): catch pydantic ValidationError when parsing OCI responses Pydantic v2 raises ValidationError (not TypeError) when field validation fails, so malformed OCI completion responses or stream chunks would propagate unhandled out of handle_generic_response, handle_generic_stream_chunk, and handle_cohere_stream_chunk. Widen the except clauses to also catch ValidationError so callers get a clean OCIError. * fix(oci/catalog): real prices for Llama 4, drop zero-cost OCI OpenAI entries Zero-cost catalog entries (input_cost_per_token=0, output_cost_per_token=0) make proxy spend tracking silently report $0 for these paid OCI models, so any caller can drive them without decrementing a budget. For Llama 4 Maverick and Scout, OCI charges the same character-based rate as Llama 3.3 70B ($0.0018 per 10,000 characters), so use the same per-token price as the existing oci/meta.llama-3.3-70b-instruct entry (7.2e-07 in/out). For oci/openai.gpt-5, gpt-5-mini, gpt-5-nano, gpt-oss-120b, and gpt-oss-20b, no public per-token pricing is available; drop the entries so operators must register them with explicit custom pricing. The existing GPT-5 reasoning test fixture already injects synthetic entries when the catalog omits them, so the chat transformation's supports_reasoning lookup keeps working in tests. * fix(oci/chat): wrap CohereChatResult construction in try/except Match the handle_generic_response pattern: surface OCIError with the upstream status code instead of letting a raw pydantic.ValidationError propagate when the Cohere response payload is malformed. * fix(oci): harden Cohere stream/finish-reason and dedupe maxTokens param mapping - Cohere stream: track per-stream tool-call emission and only suppress the terminal consolidation chunk's tool calls once they've been seen earlier. Prevents silent drop if tool calls are delivered exclusively on the terminal chunk. - Cohere stream: emit content=None (not "") on non-terminal text-free chunks (e.g. tool-call-only / keep-alive) so downstream consumers that distinguish missing vs explicitly-empty deltas behave correctly. - Generic handlers: accept singular TOOL_CALL finish reason in addition to TOOL_CALLS, matching the Cohere handlers. - _get_optional_params: when both max_tokens and max_completion_tokens are provided, explicitly prefer max_completion_tokens instead of relying on dict iteration order. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): emit content=None instead of empty string for text-free generic stream chunks Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(oci): expect content=None for text-free generic stream chunks handle_generic_stream_chunk now emits content=None instead of empty string when a chunk carries no text parts. Update the corresponding no-message test to match. * codeql: narrow OCI sha256 suppression to query-filter, not whole file paths-ignore was suppressing every CodeQL query on litellm/llms/oci/common_utils.py, hiding all future findings in a security-critical file (private key loading, credential resolution, URL construction, RSA signing). Move the suppression for py/weak-sensitive-data-hashing into query-filters so common_utils.py remains fully analyzed by every other query. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): use locale-independent RFC 7231 date for manual signing email.utils.formatdate(usegmt=True) emits canonical English weekday/ month abbreviations regardless of system locale, so signature verification doesn't break on non-en_US deployments. * fix(oci): strip 'oci/' prefix in get_vendor_from_model Previously, get_vendor_from_model split on '.' without stripping the optional 'oci/' provider prefix, so 'oci/cohere.command-a-03-2025' was routed through the GENERIC pipeline instead of COHERE. Co-authored-by: Yassin Kortam <yassin@berri.ai> * codeql: scope OCI sha256 suppression to common_utils.py via filter-sarif Replace the global query-filters exclude for py/weak-sensitive-data-hashing with a SARIF post-filter that only drops the alert when it originates from litellm/llms/oci/common_utils.py, keeping the rule active on every other SHA-256 callsite in the repository. * Fix OCI chat bugs: tool_calls None key, dead max_tokens dedup, single-event stream text suppression - handle_cohere_response: omit tool_calls key from message dict when None, matching the generic handler's behaviour and avoiding tripping consumers that key off 'tool_calls' in message. - _get_optional_params: remove dead prefer_max_completion branch. By the time this helper runs, map_openai_params has already collapsed max_tokens/max_completion_tokens onto the OCI alias, so the OpenAI-key membership check is unreachable. - handle_cohere_stream_chunk: add prior_text_emitted parameter mirroring prior_tool_calls_emitted. The terminal consolidation chunk's text is only suppressed when prior deltas already emitted text — otherwise (degenerate single-event stream) the text passes through so the response content isn't silently lost. OCIStreamWrapper now tracks emitted text alongside emitted tool calls. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): preserve all text parts in generic response and emit SYSTEM role for Cohere - handle_generic_response: iterate all content parts and concatenate text (matches the streaming handler) so non-leading text parts are not lost and a leading non-text part does not suppress trailing text. - adapt_messages_to_cohere_standard: emit CohereSystemMessage for system messages so direct callers do not silently drop them. The Cohere request builder filters system messages before calling this helper to avoid duplicating preambleOverride content into chatHistory. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): normalise dict-format tool_choice to OCI flat uppercase shape The OCI Generative AI API only accepts toolChoice values of the form {"type": "AUTO"|"NONE"|"REQUIRED"} or {"type": "FUNCTION", "name": "<fn>"}. The previous conversion only handled string tool_choice values, so OpenAI's standard dict shape {"type": "function", "function": {"name": "<fn>"}} passed through unchanged and was rejected by OCI with a 400. Normalise the dict shape by uppercasing the discriminator and hoisting the function name to the top level. Also accept dict variants of the non-function selectors (e.g. {"type": "auto"}). * test(oci): exercise system-message filtering at transform_request boundary adapt_messages_to_cohere_standard now emits SYSTEM-role entries by design so direct callers don't silently drop system content. The Cohere request builder filters system messages before calling the helper and routes them into preambleOverride, so the user-visible 'no SYSTEM in chatHistory' guarantee holds at the transform_request boundary, where the test should live. * fix(oci/chat): extract tool_choice/response_format helpers to satisfy PLR0915 _get_optional_params exceeded ruff's 50-statement cap. The toolChoice and responseFormat normalisation blocks are self-contained mutations, so move them to module-level helpers. * fix(oci): normalize None finishReason in generic non-streaming handler; drop dead Cohere system-role branch Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/generic): silence mypy assignment error on cleared finish_reason * fix(docker): install libatomic in builder for prisma nodeenv binary The prebuilt node binary that prisma-python's nodeenv downloads links against libatomic.so.1, which Wolfi does not pull in via gcc/nodejs. Without this, fresh Docker builds (no GHA cache hit) fail at `prisma generate` with: node: error while loading shared libraries: libatomic.so.1 * fix(oci): raise on invalid tool_choice instead of silently passing OpenAI shape _normalize_tool_choice previously left an OpenAI-format dict in selected_params['toolChoice'] when the type was unrecognized or when 'FUNCTION' was given with a missing/empty name. OCI would then reject the request with a non-obvious error. Raise ValueError with a clear message in these cases. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): raise OCIError instead of ValueError in _normalize_tool_choice Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/generic): declare non-security intent on sha256 for synthetic tool-call id * fix(oci): simplify _get_optional_params and reject invalid tool_choice types - Collapse the two-loop _get_optional_params into a single pass with clear precedence (OpenAI key wins over OCI alias; first OpenAI key reaching a given OCI target wins). Removes the redundant maxTokens special-case in the second loop and makes the map_openai_params / transform_request handoff easier to reason about. - Raise OCIError when _normalize_tool_choice sees an unexpected type (list, bool, int, ...) instead of silently letting it through to the OCI API where it would produce an opaque server-side error. Co-authored-by: Yassin Kortam <yassin@berri.ai> * Remove no-op data['stream'] deletion in OCI stream wrappers Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): always send Cohere isStream field explicitly Match OCIChatRequestPayload by defaulting CohereChatRequest.isStream to False instead of None so model_dump(exclude_none=True) does not silently omit the field on non-streaming requests. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): revert Cohere isStream to Optional[bool]=None to preserve omission semantics Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/generic): raise OCIError on empty choices instead of IndexError Pydantic accepts an empty choices list when validating OCICompletionResponse, so accessing chatResponse.choices[0] could raise an unhandled IndexError. Surface it as OCIError so the response error path is consistent with the existing (TypeError, ValidationError) guard. * fix(oci/cohere): map top_k -> topK so Cohere topK param is settable The Cohere param map (derived from the GENERIC map) had no entry for topK. Since the simplified _get_optional_params only iterates over param_map entries, callers had no way to pass topK to CohereChatRequest (neither via an OpenAI-style key nor via the OCI alias). Add 'top_k': 'topK' to the Cohere map only — OCIChatRequestPayload (GENERIC) has no topK field. _get_optional_params accepts both the OpenAI key (top_k) and the OCI alias (topK) in optional_params, so this covers both calling conventions. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): tighten cohere stream dedup flags and forward stream args in embed signing Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci/chat): reorder dict guard and wrap stream chunk json.loads - Move isinstance(response_json, dict) check before .get("error") so the guard runs before the attribute access it is supposed to protect. - Wrap json.loads in OCIStreamWrapper.chunk_creator with try/except so malformed SSE payloads surface as OCIError instead of a raw JSONDecodeError propagating out of the stream loop. * fix(oci/cohere stream): only flag text emitted on non-empty content An intermediate Cohere SSE chunk carrying text="" was flipping _cohere_text_emitted via the "is not None" check, which then caused the terminal consolidation chunk to drop its real text as a duplicate. Use a truthy check so only actual content marks the stream as having emitted text. * test(oci): end-to-end proxy integration test against real OCI GenAI Spins up the litellm proxy via the console-script entrypoint with a minimal OCI-only config and drives real OpenAI-shaped HTTP requests through it against OCI GenAI. Covers non-streaming chat, streaming chat, embeddings, and /v1/models for Cohere, Llama, Gemini, and Grok. Skips automatically when ~/.oci/config is absent or when the active profile uses session-token auth (the OCI provider currently only consumes OCI_* env vars; session tokens would need an in-process signer). API-key profiles work out of the box. * test(oci): move proxy integration test to tests/integration/ tests/llm_translation/ is mock-only; the OCI proxy integration test spawns a real proxy subprocess and makes live HTTP calls, so move it (and the companion config) to tests/integration/ alongside the existing test_oci_integration.py. * fix(oci): dedupe finish-reason mapping and batch Cohere tool results - Extract _normalize_oci_finish_reason helper so the four chat handlers (Cohere/GENERIC, sync/stream) share one OCI->OpenAI mapping instead of four near-identical if/elif chains. - Merge consecutive OpenAI tool-role messages into a single CohereToolMessage with multiple toolResults entries, matching the OCI Cohere API's expectation for parallel tool calls in one assistant turn. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(oci): drop dead Cohere toolChoice field and emit GENERIC tool-call dicts inline - Remove the unreachable toolChoice field from CohereChatRequest. The Cohere param map explicitly marks tool_choice as unsupported, so the field can never be populated through the normal optional_params flow and only confused the public model surface. - Build GENERIC stream tool-call dicts inline (id/type/function shape) instead of round-tripping through ChatCompletionMessageToolCall and model_dump(). Matches handle_cohere_stream_chunk so downstream stream-mergers see the same minimal payload regardless of which vendor produced the chunk. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(docker): drop redundant libatomic from non_root builder litellm_internal_staging already fixes the prisma `nodeenv` build failure at the root cause by restoring `npm` to the builder (#28519): with npm on PATH, prisma-python uses the system Node and never downloads the nodeenv binary that links against libatomic.so.1. After merging internal_staging the libatomic line is dead weight, so remove it. https://claude.ai/code/session_01SwKzxRxgUhLFyyEf4UV812 * fix(oci/catalog): add openai.gpt-5{,-mini,-nano} entries with supports_reasoning Without these catalog entries, supports_reasoning(model='openai.gpt-5*', custom_llm_provider='oci') returned False, so _model_uses_max_completion_tokens fell back to the default and OCI rejected the request with HTTP 400 ('Use maxCompletionTokens instead.'). Add the three entries so the catalog-driven maxCompletionTokens routing works against a stock LiteLLM install. Also reword the test fixture docstring — the bundled backup now actually ships these entries, so the fixture is only a fallback for environments that loaded their cost map from a stale remote source. --------- Co-authored-by: Tai An <antai12232931@outlook.com> Co-authored-by: Vincent <yimao1231@gmail.com> Co-authored-by: Kris Xia <xiajiayi0506@gmail.com> Co-authored-by: d 🔹 <liusway405@gmail.com> Co-authored-by: Fabrizio Cafolla <developer@fabriziocafolla.com> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Tom Denham <tom@tomdee.co.uk> Co-authored-by: escon1004 <70471150+escon1004@users.noreply.github.com> Co-authored-by: Divyansh Singhal <97736786+Divyansh8321@users.noreply.github.com> Co-authored-by: robin-fiddler <robin@fiddler.ai> Co-authored-by: Michael-RZ-Berri <michael@berri.ai> Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Sameer Kankute <sameer@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: Federico Kamelhar <federico.kamelhar@oracle.com> Co-authored-by: Claude <noreply@anthropic.com>	2026-05-23 12:15:41 -07:00
milan-berri	7270f723de	fix(mcp): forward upstream initialize instructions on cold gateway init (#28231) ... Prefetch upstream InitializeResult.instructions before merging gateway initialize options when YAML/DB do not set instructions, so clients receive upstream server text on the first MCP initialize without list_tools. Co-authored-by: Cursor <cursoragent@cursor.com>	2026-05-22 16:00:47 -07:00
Sameer Kankute	f35e7eb2f6	feat(guardrails): add Microsoft Purview DLP guardrail (#24966) ... * feat(guardrails): add Microsoft Purview DLP guardrail * fix(guardrails/purview): raise_for_status on HTTP errors, cap scope cache, reuse executor * fix(guardrails/purview): propagate litellm_call_id as correlation_id to Purview * chore: fixes * refactor(guardrails): delegate get_user_prompt to get_last_user_message PurviewGuardrailBase duplicated AzureGuardrailBase (and OpenAIGuardrailBase) user-prompt extraction. The same logic already lived in common_utils.get_last_user_message; wire guardrail bases to that helper, fix the helper docstring, and drop its redundant self-import of convert_content_list_to_str. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix(purview): make protection scope cache true LRU on hits OrderedDict.get() does not update insertion order; call move_to_end on TTL-valid cache hits so popitem(last=False) evicts least-recently-used users instead of FIFO by first insert. Add a regression test with a small max cache size. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * Fix mypy * fix(guardrails/purview): harden user-id resolution and broaden DLP text Prefer API key and proxy-injected metadata over client metadata for Entra identity. Scan full message transcript pre-call and all completion choices post-call. Align logging-only hook with the same user-id rules. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(guardrails/purview): scan /v1/completions prompt and TextChoices Normalize text-completion prompts (string or list of strings); skip token-id-only prompts. Run post-call DLP on TextCompletionResponse choices. Extend logging_only hook for text_completion. Add tests and completion_prompt_to_str helper. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(purview-dlp): return data after DLP pass; per-call executor; dedupe text extraction async_pre_call_hook now returns the request dict after a successful check so callers match skip-path behavior. logging_hook uses a fresh ThreadPoolExecutor per invocation like Presidio to avoid single-worker starvation. Response text extraction is centralized in _completion_response_text_parts. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix(purview): fix LRU cache refresh position and add Responses API scanning Two fixes to the Microsoft Purview DLP guardrail: 1. LRU cache bug (base.py): When a stale scope cache entry was re-fetched, the assignment updated the value but Python's OrderedDict.__setitem__ preserves the original insertion order for existing keys. This left the refreshed entry near the front of the dict, making it the first candidate for LRU eviction via popitem(last=False). Fix: call move_to_end(user_id) after every write to an existing key. 2. Responses API coverage gap (purview_dlp.py): Requests to /v1/responses use an 'input' field instead of 'messages' or 'prompt', so the pre-call hook returned without scanning the content. Similarly, post-call hook did not handle ResponsesAPIResponse.output. Fix: add _responses_api_input_to_str() helper and handle 'responses'/'aresponses' call types in async_pre_call_hook, async_post_call_success_hook (via _completion_response_text_parts), and async_logging_hook. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix(purview): message separator, non-blocking logging_hook, TextChoices type error Three bugs fixed in the Microsoft Purview DLP guardrail: 1. get_prompt_text_for_dlp message separator (base.py) - Previously called get_str_from_messages() which concatenated all message texts with NO separator, so 'end of msg1' + 'start of msg2' became 'end of msg1start of msg2'. - Now joins per-message text with '\n\n' via convert_content_list_to_str(), preserving DLP pattern detection accuracy across message boundaries. 2. logging_hook blocking the event loop thread (purview_dlp.py) - Previously called future.result() which blocked the calling thread (often the event loop thread) for the entire round-trip of two sequential Microsoft Graph API calls (_compute_protection_scopes + _process_content). - Now fires and forgets: when called inside a running loop, schedules the coroutine with loop.create_task(); otherwise spawns a daemon thread. Returns (kwargs, result) immediately in both cases. - Removes unused concurrent.futures.ThreadPoolExecutor import; adds threading. 3. Incompatible assignment type error (purview_dlp.py:180) - mypy inferred 'choice' as TextChoices from the first loop body, then flagged the assignment in the second loop as incompatible with Choices. - Fixed by using distinct loop variable names: text_choice (TextChoices) and chat_choice (Choices). Tests: 7 new tests added covering the separator fix (TestGetPromptTextForDlp) and the non-blocking logging_hook (TestLoggingHookNonBlocking). Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix(purview): suppress API errors in logging-only mode and scan tool-call arguments Three issues fixed: 1. _check_content except block re-raised unconditionally even when block_on_violation=False. The docstring promised 'log only - do not raise' but network/API errors always propagated. Fixed by checking block_on_violation before re-raising; when False, log a warning and continue. 2. async_logging_hook used a single try/except wrapping both the prompt and response audit calls. When the first _check_content (uploadText) raised due to an API error the second call (downloadText) was silently skipped. Fixed by giving each audit call its own try/except so both always run independently. 3. convert_content_list_to_str() only reads message.content, so tool_calls[].function.arguments and function_call.arguments were invisible to the Purview pre-call and post-call scans. An authenticated caller could embed sensitive text in tool-call arguments and bypass DLP. Fixed by: - Adding PurviewGuardrailBase._extract_tool_call_args_from_message() which handles both dict and object-style messages, covering both tool_calls[] arrays and the legacy function_call field. - Updating get_prompt_text_for_dlp() to include those arguments alongside message content (request/prompt path). - Changing _completion_response_text_parts() from @staticmethod to an instance method and adding tool-call argument extraction for ModelResponse choices (response path). Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * chore(ui): restructure pre-built Next.js output to directory-based routing Flat page files (e.g. guardrails.html) replaced by directory-based index.html equivalents (e.g. guardrails/index.html) matching the Next.js App Router output format. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix(purview): comprehensive security hardening — identity spoofing, streaming bypass, token-id gap Four security issues addressed: 1. end_user_id kwargs fallback missing in _resolve_user_id_from_logging_kwargs user_id already fell back to kwargs.get("user_api_key_user_id") when absent from metadata, but end_user_id only checked md.get("user_api_key_end_user_id") with no kwargs-level fallback. Added or kwargs.get("user_api_key_end_user_id"). 2. Streaming responses bypassed post_call blocking async_post_call_success_hook only runs on assembled non-streaming responses. For streaming requests the proxy already delivered all content before the hook ran, so raising HTTPException there had no effect. Added async_post_call_streaming_iterator_hook which buffers the entire stream, assembles it via stream_chunk_builder, runs the Purview DLP check, and only then re-yields chunks via MockResponseIterator. If a violation is detected the exception is raised before any bytes reach the client. The proxy automatically skips async_post_call_success_hook for guardrails that define this method, preventing duplicate scans. 3. Caller-controlled Purview user identity in blocking modes When a LiteLLM API key has no bound user_id the guardrail fell back to metadata[user_id_field], which is supplied by the caller. A caller could set this to any Entra object ID whose Purview policies are more permissive and bypass DLP. Added _resolve_trusted_user_id() that only returns identities from the proxy auth system (user_api_key_dict.user_id, end_user_id, or proxy-injected metadata["user_api_key_user_id"]). Added _resolve_user_id_for_blocking() used by all blocking-mode hooks: tries trusted sources first; if only caller-supplied is available, logs a SECURITY WARNING and still proceeds (backward compat); if nothing resolves, skips with a warning. 4. Token-id prompt DLP bypass When /v1/completions received a pure token-id array prompt, completion_prompt_to_str() returned None and the pre_call hook silently skipped the Purview scan. An authenticated caller could tokenize blocked text and send it without DLP evaluation. The hook now detects this case (raw_prompt present but prompt_text None) and logs a WARNING while letting the request pass through — token-id payloads are opaque at the text layer and cannot be scanned. This makes the gap explicit rather than silent. Tests: 94 total, all passing. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * Revert "chore(ui): restructure pre-built Next.js output to directory-based routing" This reverts commit c70c4303b735bb3885732bd4a0e01997e9571f56. * fix(purview): fail closed on identity spoofing, token prompts, and path encoding Encode Entra user IDs in Graph paths, guard caches with asyncio.Lock, scan Responses API instructions with string input, reject caller-only metadata and token-id completion prompts in blocking mode, and revert unrelated UI HTML restructure from the PR branch. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(purview): use threading.Lock and getattr for LitellmParams - Replace asyncio.Lock with threading.Lock in PurviewGuardrailBase. The cache lock is acquired both from the proxy's main event loop and from short-lived event loops created by the logging_hook thread fallback. In Python 3.10+ an asyncio.Lock is bound to the first event loop that acquires it, so the second loop would silently break audit logging with RuntimeError. All critical sections are in-memory dict ops with no awaits, so a synchronous lock is safe. - Use getattr() on LitellmParams in initialize_guardrail() instead of .get(), which does not exist on Pydantic BaseModel instances and would raise AttributeError at runtime. Tests updated to construct Mock objects with spec= so they reflect the real interface. Co-authored-by: Yassin Kortam <yassin@berri.ai> * refactor(purview): dedupe trust-level user resolution and drop dead code - _resolve_user_id now delegates levels 1-3 to _resolve_trusted_user_id so blocking and non-blocking paths share a single source of truth. - Drop redundant event_hook override in MicrosoftPurviewDLPGuardrail.__init__ (initialize_guardrail already forwards event_hook=litellm_params.mode). - Drop unused self._logging_only attribute; blocking is controlled by the block_on_violation argument passed to _check_content. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview): fail-closed on responses API transform error; avoid duplicate audit calls Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview): fail-closed blocking DLP; revert directory-based UI HTML Blocking hooks now require UserAPIKeyAuth user_id/end_user_id only (no spoofable metadata), re-raise Responses API transform errors, scan streamed text completions, and reject requests with no bound identity. Reverts the accidental directory-based Next.js output from cc47081 (c70c4303b7). Co-authored-by: Cursor <cursoragent@cursor.com> * Remove dead code in purview_dlp: _resolve_user_id_for_blocking never returns falsy The method either returns a non-empty trusted user id or raises HTTPException, so the 'if not user_id' guards in async_pre_call_hook and async_post_call_success_hook were unreachable. Tighten the return type to str and drop the dead checks to make the fail-closed behavior explicit. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview): exclude caller-controlled end_user_id from blocking DLP Blocking Purview checks now use only API-key/JWT-bound user_id, not end_user_id populated from request user/metadata/safety_identifier. Co-authored-by: Cursor <cursoragent@cursor.com> * style(purview): apply Black formatting to base.py Co-authored-by: Cursor <cursoragent@cursor.com> * fix(purview): use post-await timestamp for cache TTL Capture the timestamp after the network call completes when storing it as the cache freshness marker, so the effective TTL reflects when the response was actually received rather than when the request started. Under high network latency the previous behavior shortened the effective cache lifetime. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview_dlp): fail closed when stream_chunk_builder returns None stream_chunk_builder can return None (e.g., when ChunkProcessor filters all chunks), causing both isinstance checks to fail and the buffered chunks to be released without DLP scanning. Explicitly fail closed in that case by raising an HTTPException so the streaming DLP guardrail does not bypass policy enforcement. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview_dlp): resolve user_id before buffering stream Co-authored-by: Yassin Kortam <yassin@berri.ai> * merge main (#28629) * test(vcr): classify cache verdicts, detect live calls, surface cost leaks Convert the per-test VCR verdict line from a single 'NOOP / HIT / MISS / PARTIAL' tag into a classified outcome that distinguishes the cases that silently bill the live API on every CI run from the ones that don't: HIT pure replay PARTIAL mixed replay + new recordings MISS:RECORDED new cassette saved to Redis (cached next run) MISS:OVERFLOW cassette > MAX_EPISODES_PER_CASSETTE; persister refused to save; re-bills every run MISS:NOT_PERSISTED test failed; save_cassette skipped; re-bills NOOP VCR-marked but no HTTP traffic (mocked elsewhere) UNMARKED:LIVE_CALL test bypassed VCR AND opened a TCP connection to a known LLM provider host -> wasted spend UNMARKED:NO_TRAFFIC test bypassed VCR but didn't call out The UNMARKED:LIVE_CALL signal is what converts 'this test probably hits live' into 'this test connected to api.openai.com'. We install a socket.connect / socket.create_connection wrapper for the duration of each non-VCR-marked test and record any outbound TCP to a known LLM provider hostname. The probe sits below the httpx layer so vcrpy and respx (which both patch above the socket) are unaffected. Replace the file-level _RESPX_CONFLICTING_FILES blacklists in the llm_translation and local_testing conftests with per-item respx detection in apply_vcr_auto_marker_to_items. A test now skips VCR when it actually carries @pytest.mark.respx or has respx_mock in its fixture chain - not just because some other test in the same file imports MockRouter. Items skipped by skip_files are split into respx_conflict (real conflict, the module wires up respx) vs file_opt_out (dead skip- list entry whose module never touches respx) so the session summary makes pruning obvious. Stabilize the AWS SigV4 fingerprint: the Authorization header on Bedrock requests rotates its Credential date and Signature on every call, which previously pushed every Bedrock test past the 50-episode overflow threshold. Extract the access-key id only ('aws-sigv4:AKIA...') so two requests with the same identity match. Always emit verdict logging when VCR is active (set LITELLM_VCR_VERBOSE=0 to opt back into the legacy quiet mode). Add a session-end classification summary that lists overflow tests, unmarked live-call tests, and the skip-reason breakdown. Wire the live-call probe + summary hook into every test directory that already uses the Redis-backed VCR cache (audio_tests, guardrails_tests, image_gen_tests, litellm_utils_tests, llm_responses_api_testing, llm_translation, local_testing, logging_callback_tests, ocr_tests, pass_through_unit_tests, router_unit_tests, search_tests, unified_google_tests). Add tests/llm_translation/test_vcr_classification.py covering the verdict classifier, skip-reason tagging, AWS SigV4 fingerprint stability, live-host classification, and session summary rendering. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): drop dead 'from respx import MockRouter' imports These seven test files were on _RESPX_CONFLICTING_FILES, which made the auto-marker skip them entirely. Inspecting the source shows the only respx artifact is a top-level 'from respx import MockRouter' that no test ever uses - no @pytest.mark.respx, no respx_mock fixture, no respx.mock context manager. The import is dead code left over from a previous mocking pattern. Now that apply_vcr_auto_marker_to_items detects respx per-item via the marker / fixture chain (b637d9f64a), the file-level skip is no longer needed for these files - they were the reason the OpenAI tests (test_o3_reasoning_effort, test_streaming_response[o1/o3-mini], TestOpenAIO1::test_streaming, TestOpenAIChatCompletion::test_web_search, TestOpenAIO3::test_web_search, etc.) ran live every CI build despite the cassette cache being healthy. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(image_edits): regenerate fixtures per call instead of holding open module-level file handles Module-level TEST_IMAGES = [ open(os.path.join(pwd, 'ishaan_github.png'), 'rb'), open(os.path.join(pwd, 'litellm_site.png'), 'rb'), ] SINGLE_TEST_IMAGE = open(...) opens the file once at import. After the first multipart upload, the file pointer is at EOF, so every subsequent test in the same xdist worker sends an empty multipart body. That non-determinism (a) blows the recorded cassette past MAX_EPISODES_PER_CASSETTE (50) so _RedisPersister.save_cassette refuses to save it, and (b) re-bills the live image edit endpoint on every CI run. Recent CI runs confirm the leak: tests/image_gen_tests/test_image_edits.py shows six tests parking at 51-52 cassette entries (TestOpenAIImageEditGPTImage1::test_openai_image_edit_litellm_sdk[False], TestOpenAIImageEditDallE2::..., test_openai_image_edit_with_bytesio, test_openai_image_edit_litellm_router, test_multiple_vs_single_image_edit[False], test_multiple_image_edit_with_different_formats). Replace the module-level file handles with _make_test_images() / _make_single_test_image() factories that return fresh _RewindableImage (BytesIO subclass) objects whose pointer always starts at 0. The image bytes are read once at import into module-level constants (_ISHAAN_GITHUB_BYTES, _LITELLM_SITE_BYTES), so disk I/O cost is unchanged. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(vcr): match real Bedrock hostnames in live-call probe The suffix '.bedrock-runtime.amazonaws.com' never matched real Bedrock endpoints, which use the format 'bedrock-runtime[-fips].{region}.amazonaws.com' (region between 'bedrock-runtime' and 'amazonaws.com'). Add an explicit host check for that pattern so Bedrock live calls are visible to the probe, and update the unit test accordingly. Also drop the unused '_LIVE_CALL_PROBE_INSTALLED' module variable. * fix(vcr): cover full RFC1918 172.16.0.0/12 range in local prefixes * fix(image_edits): drop _RewindableImage to prevent infinite multipart upload The _RewindableImage(BytesIO) wrapper auto-rewound on every read after EOF, which made the OpenAI SDK's multipart upload writer read the same bytes forever instead of seeing EOF. Workers OOM'd / SIGKILL'd: [gw0] node down: Not properly terminated replacing crashed worker gw0 ... worker 'gw1' crashed while running 'tests/image_gen_tests/test_image_edits.py::TestOpenAIImageEditGPTImage1::test_openai_image_edit_litellm_sdk[False]' The auto-rewind was added defensively for parametrized + flaky-retried tests, but BaseLLMImageEditTest::test_openai_image_edit_litellm_sdk already calls get_base_image_edit_call_args() once per invocation and that helper now constructs fresh streams via _make_test_images(), so rewinding inside the stream is unnecessary. Replace with plain BytesIO seeded with the cached image bytes. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): mark Bedrock prompt-caching cross-call tests VCR-incompatible The pass_through prompt-caching tests (test_prompt_caching_returns_cache_read_tokens_on_second_call, test_prompt_caching_streaming_second_call_returns_cache_read) make a warm-up call and then assert the *second* call sees a non-zero cache_read_input_tokens count from the upstream's prompt-cache. VCR replay can't model cross-call provider state — both calls match the same cassette episode, so the second call returns the first call's pre-warmup response and the assertion fails: AssertionError: Expected cache_read_input_tokens > 0 on second call, but got 0. Full usage: {'input_tokens': 4986, 'cache_creation_input_tokens': 4974, 'cache_read_input_tokens': 0} This started biting after the AWS SigV4 fingerprint stabilization (b637d9f64a): Bedrock requests now produce a stable per-access-key fingerprint instead of a per-request signature, so cassettes successfully replay where they previously always missed and re-recorded live. Opt these tests out via skip_nodeid_suffixes so they run live and match the existing pattern in tests/llm_translation/conftest.py (::test_prompt_caching). Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): tighten OVERFLOW classification and switch respx detection to AST Address two greptile P2 review concerns on PR #27795: 1. MISS:OVERFLOW was firing whenever total > MAX_EPISODES_PER_CASSETTE regardless of cassette state. A cassette that grew past the cap historically but this run only *replayed* (dirty=False) is healthy — the persister never tries to save, so the cache state is stable and the next run will replay too. Only flag OVERFLOW when dirty=True (new episodes were recorded that the persister would refuse to save). Add a regression test covering the dirty=False + large-total case. 2. _module_uses_respx did substring matching on the module source, which false-positives on comments / docstrings / string literals. A comment like # Previously tried respx.mock but switched to vcrpy would keep a file pinned on the opt-out list, defeating the dead-import pruning goal of this PR. Replace the substring scan with an ast.NodeVisitor (_RespxUsageVisitor) that only counts: - @pytest.mark.respx / @respx.mock decorators - with respx.mock(): ... (sync + async) context managers - respx.mock(...) calls outside a with/decorator - function parameters / fixture names equal to respx_mock Add tests for the comment / docstring / string-literal cases plus each real-usage pattern. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix(vcr): aggregate worker stats on the controller so the session summary actually renders under xdist `_session_stats` is a module-level dict mutated inside `_vcr_outcome_gate` — which runs in each xdist worker process. The controller's `pytest_terminal_summary` then reads its own empty `_session_stats` and bails on `if not counts: return`, so the OVERFLOW / LIVE_CALL sections the rest of this PR adds never make it into CI logs in the dist mode CI actually uses. Ship a structured `vcr_outcome` payload via `user_properties` (which xdist round-trips) and add `aggregate_report_outcome` on the controller to fold worker outcomes into `_session_stats`. The recording process tags `vcr_recorded_by` with `PYTEST_XDIST_WORKER` so the controller can tell "single-process — already counted locally" apart from "produced by a worker — needs aggregation here", and not double-count when there's no xdist. Covered by 9 new unit tests in test_vcr_classification.py including the end-to-end summary render path. * fix(guardrails): improve CrowdStrike AIDR input handling (#26658) * feat(lasso): add tool-calling support to LassoGuardrail (#27648) * feat(lasso): extend LassoGuardrail to support tool calling (RND-5748) * fix(lasso): PR review followups for tool-calling guardrail (RND-5748) * fix(lasso): handle object-style tool_calls in _update_tool_calls_from_masked (RND-5748) * fix(lasso): use model role for tool_use blocks (RND-5748) * test(lasso): add round-trip tests for message transformation (RND-5748) * fix(lasso): remove unused imports, handle Responses-API input masking, flatten multimodal content (RND-5748) * fix(lasso): inspect Responses-API input field (RND-5748) * fix(lasso): guard text-cursor remap against Lasso count mismatch (RND-5748) * fix(lasso): flatten list content in tool_result.content (RND-5748) * fix(lasso): remap multimodal list content during masking (RND-5748) Bug: _map_masked_messages_back counted list-content messages in original_text_count but the remap loop only handled isinstance(str). The positional text_cursor never advanced for list messages, causing all subsequent masked texts to be written onto the wrong messages. Fix: added elif isinstance(content, list) branch that replaces the list with the masked text string and advances the cursor — mirrors the existing string-content branch. Also handles the assistant + tool_calls combo for list-content messages. Test: test_map_masked_messages_back_list_content verifies a user message with [text + image_url] followed by an assistant message gets correct masked content on both (cursor stays aligned). * refactor(lasso): extract _get_field and _extract_tool_call_fields helpers (RND-5748) The dict-vs-object access pattern (x.get('y') if isinstance(x, dict) else getattr(x, 'y', None)) was duplicated 14 times across 5 methods. _get_field(obj, field) — single-point dict/Pydantic field access. _extract_tool_call_fields(call) — returns (call_id, name, parsed_input) with JSON argument parsing, replacing ~30 duplicate lines in both async_post_call_success_hook and _expand_messages_for_classification. Also simplified _update_tool_calls_from_masked, _prepare_payload tool mapping, and _apply_masking_to_model_response call_id extraction. Net ~60 lines removed. No behavior change — all 32 tests pass. * fix(lasso): add count guard to _apply_masking_to_model_response (RND-5748) _apply_masking_to_model_response used a bare text_cursor without verifying 1:1 correspondence between text-bearing choices and masked text entries. If Lasso returned a different number of text messages than choices with content, masked text would be applied to the wrong choice or silently skip choices. Added the same count-mismatch guard pattern already used in _map_masked_messages_back: count original text-bearing choices, compare to masked_text length, skip text remap on mismatch with a warning log. Tool_call masking via id-based lookup is unaffected. Tests: - test_apply_masking_to_model_response_multiple_choices: verifies correct per-choice masked text with 2 choices - test_apply_masking_to_model_response_count_mismatch: verifies content is left unchanged when counts disagree * fix(lasso): close two guardrail-bypass paths flagged in review (RND-5748) * tool-call args: when function.arguments is malformed JSON or parses to a non-object, preserve the raw string as {"arguments": <raw>} so Lasso still inspects it instead of receiving input=None. Covers both pre-call and post-call extraction (shared helper). Also resolves the CodeQL empty-except warning since the except body now assigns parsed=None. * Responses-API input: when a request carries both "messages" and "input", inspect both. Previously a benign messages array let the guardrail skip data["input"] entirely. The masking write-back is split via a count boundary so masked messages flow back to data["messages"] and masked input flows back to data["input"] without cross-contamination. Tests: malformed/non-object args round-trip, dual-field classification, dual-field masking write-back split. * chore(lasso): black formatting + comment on expand skip branch (RND-5748) * black: wrap two long expressions in lasso.py and reformat dict literals in test_lasso.py to satisfy CI lint. * add a short comment in _expand_messages_for_classification explaining why empty string and None content are intentionally skipped (None is the OpenAI shape for a pure tool-call turn). * fix(lasso): satisfy mypy in _handle_masking, _update_tool_calls_from_masked, _apply_masking_to_model_response (RND-5748) * Narrow `response.get("messages")` into a local before slicing so mypy doesn't see `Optional[List[Dict[str, str]]]` as non-indexable. * Rename the two write-side `func` bindings in `_update_tool_calls_from_masked` to `func_dict` / `func_obj` so mypy doesn't unify the dict and Any|None branches. * Rename the inner loop variable in `_apply_masking_to_model_response` from `msg` to `masked_msg` to avoid clashing with the `msg = choice.message` rebinding below. No behavior change; resolves the 7 mypy errors from the CI lint job. * perf: eliminate per-request callback scanning on proxy hot path (#27858) - Introduce `_CallbackCapabilities` dataclass and `ProxyLogging._callback_capabilities()` static method that inspects `litellm.callbacks` once and caches capability flags keyed on (list length, member ids); invalidates automatically when the callback list mutates without per-request iteration overhead - Replace O(n) `litellm.callbacks` walks in `async_pre_call_hook`, `during_call_hook`, `async_post_call_streaming_iterator_hook`, `async_post_call_streaming_hook`, and `post_call_response_headers_hook` with fast-path exits when no relevant callbacks are registered - Add `needs_iterator_wrap()` and `needs_per_chunk_streaming_hook()` instance methods to decouple iterator-level wrapping from per-chunk hook execution; avoids `get_response_string` materialization per chunk when no guardrail or chunk-hook callback is active - Introduce `_fast_serialize_simple_model_response_stream()` using `orjson` for common single-choice text streaming chunks, bypassing the full Pydantic serializer; falls back to `model_dump_json` for tool calls, logprobs, usage, and provider-specific fields - Add early-return in `_restamp_streaming_chunk_model` when downstream model already matches the requested model, avoiding unnecessary string comparisons on every chunk - Fix stale zero-cost cache bug in `_is_model_cost_zero`: move the per-router `_zero_cost_cache` dict onto the `Router` instance and clear it in `_invalidate_model_group_info_cache` so in-place pricing updates via `upsert_deployment` immediately resume budget enforcement - Add `scripts/benchmark_chat_completions_perf.py`: standalone async benchmarking tool with a mock OpenAI provider, LiteLLM proxy process management, non-streaming RPS, streaming TTFT, and full-stream latency measurements with repeat/median run support - Add comprehensive unit tests covering capability detection, cache invalidation, fast-path correctness, zero-cost cache regression, and the no-callback streaming fast path Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu> * ci(mutmut): enable mutate_only_covered_lines to fit in CI budget (#27910) The mutation-test workflow timed out at the 350-minute job cap when running whole-folder mutation against litellm/proxy/management_endpoints/ (~30 files, ~1.5 MB of source). Every mutant was running the full test suite, and mutants were generated for lines no test covers — which would survive regardless, just wasting compute. mutmut 3.x's mutate_only_covered_lines setting runs the suite once up front to compute coverage, then skips mutating uncovered lines. This cuts the mutant count dramatically and is the right semantic for the score (no test → no kill possible → uncountable). Per-mutant test filtering by function name is already automatic in mutmut 3.x; no external coverage step is needed. * fix(rate-limit): stop v3 limiter from leaking internal stash to provider body (#27913) * fix(rate-limit): stop v3 limiter from leaking internal stash to provider body PR #27001 (atomic TPM rate limit) introduced a reservation flow that writes four LiteLLM-internal keys onto the request data dict: _litellm_rate_limit_descriptors _litellm_tpm_reserved_tokens _litellm_tpm_reserved_model _litellm_tpm_reserved_scopes _litellm_tpm_reservation_released These keys are forwarded as request body params to the upstream provider, which rejects them as unknown fields: OpenAI -> 400 'Unknown parameter: _litellm_rate_limit_descriptors' (mapped by litellm to RateLimitError / 429, hiding the bug behind a misleading 'throttling_error' code) Anthropic -> 400 '_litellm_rate_limit_descriptors: Extra inputs are not permitted' Net effect: every chat completion against any real provider fails the moment a virtual key has any tpm_limit / rpm_limit set — i.e. v3-enforced key-level TPM/RPM limits are broken end-to-end. The v3 RPM/TPM check itself still runs (raises 429 on over-limit), but the success path poisons the upstream body. Reproduced on litellm_internal_staging HEAD (410ce761dc) against gpt-4o-mini and claude-haiku-4-5 with a 1-RPM/1-TPM key — first request fails with the provider's unknown-field error. Fix: the stash is metadata only. - Add RATE_LIMIT_DESCRIPTORS_KEY constant and a _LITELLM_STASH_KEYS registry so we have a single source of truth for stash keys. - New helper _stash_value_in_metadata_channels writes to data['metadata'] / data['litellm_metadata'] without touching the top level. - _stash_reservation_in_data and the descriptor stash now route through that helper. _mark_reservation_released stops writing top-level. - _lookup_stashed_value also checks kwargs['metadata'] / kwargs['litellm_metadata'] (raw request_data shape) in addition to kwargs['litellm_params']['metadata'] (completion kwargs shape). - async_post_call_failure_hook now reads descriptors via the unified metadata lookup instead of request_data.get(top-level). - Defense in depth: async_pre_call_hook strips any stash key that somehow surfaced at the top level (stale cache, future refactor, test fixture) before returning. Tests: - New regression test asserts no _litellm_* stash key is present at the top level of data after async_pre_call_hook, and that the metadata channel still carries the reservation + descriptors so success / failure reconciliation works. - Existing test_tpm_concurrent.py tests that asserted top-level presence are updated to read from data['metadata'] — the location is an implementation detail; the spec is that post-call callbacks can resolve the stash. Verified end-to-end against OpenAI gpt-4o-mini and Anthropic claude-haiku-4-5 via /v1/chat/completions on a low-rpm key: - With limits not exceeded: HTTP 200, valid completion response, no leaked fields in body. - With RPM exceeded: HTTP 429 from v3 enforcement ('Rate limit exceeded ... Limit type: requests'). - With TPM exceeded: HTTP 429 from v3 enforcement ('Rate limit exceeded ... Limit type: tokens'). Full v3 hook test suite passes (171 tests). Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * chore(rate-limit): use RATE_LIMIT_DESCRIPTORS_KEY constant in test, trim noisy comments Address greptile P2: test fixture now uses the imported constant. Drop comments that re-explain what well-named identifiers already convey. * fix(rate-limit): reject caller-supplied stash values to prevent TPM-refund abuse Strip _LITELLM_STASH_KEYS from data top-level and both metadata channels at the start of async_pre_call_hook. Without this, an authenticated caller can inject _litellm_rate_limit_descriptors plus _litellm_tpm_reserved_tokens in body metadata, trigger a proxy-side rejection, and cause async_post_call_failure_hook to refund TPM counters against attacker-named scopes (e.g. another tenant's api_key). --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * fix: allow for allowlisted redirect URIs (#27761) * fix: allow for allowlisted redirect URIs * github comment addressing * Update litellm/proxy/_experimental/mcp_server/oauth_utils.py Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com> * harden oauth wildcard further * test: cover wildcard entry with dot-leading suffix rejection --------- Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com> * Emit native web_search_tool_result blocks for Anthropic clients (Claude Desktop / Cowork citations) (#27886) * feat(custom_logger): add async_post_agentic_loop_response_hook Lets a CustomLogger shape the response returned by the agentic-loop follow-up call without bypassing the loop's safety / observability machinery (depth tracking, fingerprinting, etc.). Default returns the response unchanged. Used by websearch_interception to inject Anthropic-native web_search_tool_result blocks when the originating client requested a native web_search_* tool. * feat(llm_http_handler): call post-agentic-loop hook on the originating callback In _execute_anthropic_agentic_plan, after anthropic_messages.acreate returns, call the originating callback's async_post_agentic_loop_response_hook so it can mutate the final response (e.g. inject native tool_result blocks). Pass the callback through from _call_agentic_completion_hooks. Exceptions in the post-hook are caught and logged so a buggy callback can't kill the request. * feat(websearch_interception): add is_anthropic_native_web_search_tool Identifies tools the Anthropic-native clients (Claude Desktop, the Anthropic SDK, the Anthropic Console) use to request native search: type starts with "web_search_" (e.g. web_search_20250305). Rejects the LiteLLM standard tool, the OpenAI-function variant, the bare "WebSearch" legacy name, and the bare "web_search" Claude Code shape. This lets us decide per-request whether the client expects web_search_tool_result content blocks in the response, without renaming any existing constants or touching native-provider skip logic. * feat(websearch_interception): add build_web_search_tool_result_block Produces the Anthropic-native web_search_tool_result content block from a structured SearchResponse. Anthropic-native clients use this block to populate citations / source links — the existing text-blob flatten path only feeds readable evidence to the model and discards the structure, so this builder gives us the missing piece. Shape matches https://docs.anthropic.com/en/api/web-search-tool — web_search_result items carry url, title, page_age, encrypted_content (empty string when the search provider doesn't supply one). * feat(websearch_interception): emit native web_search_tool_result blocks When the originating client request carried a native Anthropic web_search_* tool, the final response now also carries web_search_tool_result content blocks alongside the model's text answer — so Claude Desktop / Anthropic SDK clients can populate the citations panel and replay conversation history with structured search evidence. Wiring: - Pre-request hooks (both deployment + Anthropic path) set a flag on kwargs when they see a native web_search_* tool, so the signal survives the conversion-to-litellm_web_search step regardless of which hook fires first. - _execute_search now returns (text, SearchResponse) so the structured results aren't lost when the text is flattened for the follow-up model call. - _build_anthropic_request_patch returns the parallel list of SearchResponse objects. - async_build_agentic_loop_plan pre-builds the web_search_tool_result blocks (one per tool_use_id) and stashes them on plan.metadata when the flag is set. - async_post_agentic_loop_response_hook reads the metadata and prepends the blocks to response.content. - _execute_agentic_loop mirrors the injection for the legacy path so both paths behave identically. Clients that send the LiteLLM standard tool keep the existing text-only behavior — no regression. * test(websearch_interception): cover native web_search_tool_result emission 18 tests across: - detector branches (native vs litellm-standard, OpenAI-function shape, Claude Desktop builtin WebSearch, bare web_search, missing type) - block-builder shape (results, none, empty) - pre-request hook flag-setting (native sets, standard does not) - async_build_agentic_loop_plan attaches blocks to plan.metadata when the flag is present, leaves metadata untouched when absent - post-hook injection into dict and object responses - legacy _execute_agentic_loop mirrors the injection so both paths return the same shape * test(websearch_short_circuit): keep _execute_search mocks in sync with new tuple return * test(websearch_thinking_constraint): keep _execute_search mocks in sync with new tuple return * feat(websearch_interception): emit native blocks from try_short_circuit_search The agentic-loop post-hook only fires when the model returns a tool_use block. Cowork / Claude Desktop on Bedrock actually make TWO requests per user turn: the main /v1/messages with their builtin tool, and a separate standalone /v1/messages whose only tool is web_search_20250305. That second request hits try_short_circuit_search — no agentic loop, no post-hook — and was returning text-only, leaving the citations panel empty. When the short-circuit input carries a native web_search_* tool, build a synthetic server_tool_use + web_search_tool_result pair (using the structured SearchResponse already returned by _execute_search) so the client gets the native shape it expects. The legacy text block is preserved so non-native short-circuit callers (Claude Code, github_copilot, etc.) see the same payload as before. Failure path still emits the native block pair (with empty results) plus the text-error block, so the client gets a well-formed response rather than a malformed half-shape. * test(websearch_native_blocks): cover short-circuit native-block emission Three new cases on top of the existing 18: - native web_search_20250305 short-circuit → [server_tool_use, web_search_tool_result, text], ids paired, urls/titles carried. - litellm_web_search short-circuit → text-only (no regression). - native short-circuit on search failure → still emits the native block pair (empty results) plus the text-error block, so the client never sees a malformed half-shape. * test(websearch_short_circuit): index assertions by block type, not by position Native short-circuit responses now have [server_tool_use, web_search_tool_result, text] when the input carries web_search_20250305 — find the text block by type rather than relying on content[0]. * fix(websearch_interception): gate legacy WebSearch name on schema absence Clients like Cowork / Claude Desktop ship a client-side tool named "WebSearch" with a full input_schema — they handle it themselves and expect to make a separate native web_search_20250305 sub-request for the actual search. Today is_web_search_tool matches the bare name regardless of other fields, which hijacks the client's tool server-side. The agentic loop fires on the main request, the model never gets to emit the client-side tool_use, and the separate native sub-request (where citation data flows) is never made. Net: citations panel empty. Real Anthropic client tools always carry input_schema (the API rejects them otherwise), so a bare {name: "WebSearch"} with no schema is the only thing that could be a legacy interception marker. Gate the match on schema absence: legacy callers (if any) keep working, real client-side WebSearch tools pass through untouched. * fix(websearch_interception): drop "WebSearch" from response-detection lists Post-conversion the model always sees ``litellm_web_search``, so the "WebSearch" entry in the response-side tool_use detection lists was dead at best. If a model ever did return ``tool_use(name="WebSearch")`` it would now (incorrectly) hijack the client's own ``WebSearch`` tool again — same Cowork problem we just fixed on the input side. Drop it. * test(websearch_native_blocks): cover the WebSearch legacy-name schema gate Three new cases: - {name: "WebSearch"} (bare interception marker) → still matched - {name: "WebSearch", input_schema: {...}} (Cowork client tool) → passes through untouched - {name: "WebSearch", description: "..."} (no schema) → still matched on the assumption it's a legacy marker rather than a malformed real client tool. --------- Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> * ci(codecov): restore litellm/ prefix on uploaded coverage paths pytest-cov runs with --cov=litellm, which makes coverage.xml store paths relative to the package root (e.g. `proxy/proxy_server.py` instead of `litellm/proxy/proxy_server.py`). Codecov auto-resolves these only when the basename is unique in the repo. Files like proxy_server.py, router.py, utils.py, main.py, and constants.py — which have duplicates under enterprise/ or other subpackages — get silently dropped during ingest. The `fixes: ["::litellm/"]` rule prepends `litellm/` to every uploaded path so they resolve unambiguously. Confirmed against multiple recent coverage.xml artifacts that no uploader currently emits paths already prefixed with `litellm/`, so the rule is safe to apply universally. This restores Codecov visibility for the highest-fix-rate hotspots: proxy_server.py, router.py, proxy/utils.py, litellm_logging.py, constants.py, key_management_endpoints.py, utils.py, main.py, user_api_key_auth.py, team_endpoints.py, and litellm_pre_call_utils.py. * chore(ci): remove unused GitHub Actions workflows and orphan files Audit of .github/workflows/ via gh run history shows the following have either never run or have been dormant for 10+ weeks. CI coverage that still matters is preserved on CircleCI (e.g. llm_translation_testing). Removed workflows: - test-litellm.yml — workflow_dispatch only, last run 2026-02-12 (cancelled); CCI local_testing_part1/2 covers the same tests - llm-translation-testing.yml — last run 2025-07-10; replaced by CCI llm_translation_testing job (run_llm_translation_tests.py kept for the make test-llm-translation target) - run_observatory_tests.yml — last run 2026-03-03 (cancelled) - scan_duplicate_issues.yml — last run 2026-03-02 (failure) - publish_to_pypi.yml — never run - read_pyproject_version.yml — fires on every push to main but its echoed version output is not consumed by any downstream step Removed orphan files (no callers in workflows, CCI, or Makefile): - .github/workflows/README.md — documented only publish_to_pypi.yml - .github/workflows/update_release.py + results_stats.csv - .github/actions/helm-oci-chart-releaser/ * Revert "ci(codecov): restore litellm/ prefix on uploaded coverage paths" This reverts commit e25a988a3f. The `fixes: ["::litellm/"]` rule turned out to be applied *after* Codecov's auto-resolution, not before. Files with unique basenames (which were auto-resolving correctly to `litellm/<path>`) got an extra `litellm/` prepended, producing `litellm/litellm/<path>` storage. Files with ambiguous basenames (the actual target of the fix) continued to be dropped because the auto-resolution still failed for them. Net result on the verification run: 1375 files now stored under unresolvable `litellm/litellm/...` paths, and the 11 originally-missing hotspots are still missing. Reverting before piling on further changes. * test(ui): preserve global Button/Tooltip mocks in per-file @tremor/react vi.mock Per-file `vi.mock("@tremor/react", ...)` factories fully replace the setup-level mock from `tests/setupTests.ts`, so the global Button/Tooltip overrides are lost in any file that re-mocks `@tremor/react`. Without them, the real Tremor `<Button>` leaks through and its internal `useTooltip(300)` schedules a native 300ms `setTimeout` on pointer events. When the test environment is torn down before the timer fires, the trailing `setState` calls `getCurrentEventPriority`, which reads `window.event` against a destroyed jsdom -> "window is not defined" flake observed on CI. Patches the 7 leaky test files to re-supply `Button` (bare `<button>`) and `Tooltip` (Fragment) overrides matching `setupTests.ts`. Also drops a dead `afterEach` workaround in `user_edit_view.test.tsx` (the fake-timer dance it ran could not drain a real timer scheduled before the swap) and corrects a misleading comment in `MakeMCPPublicForm.test.tsx`. * ci: use --cov=./litellm so coverage paths resolve unambiguously in Codecov pytest-cov treats --cov=<module-name> as a Python package and emits XML paths relative to the package root, stripping the litellm/ prefix (`proxy/proxy_server.py` instead of `litellm/proxy/proxy_server.py`). Codecov's auto-prefix heuristic then drops every file whose basename is ambiguous in the repo — `proxy_server.py` (3 copies under enterprise/), `router.py` (2 copies), `utils.py` (20+), `main.py` (20+), `constants.py` (2). The 11 highest-fix-rate hotspots have never appeared in Codecov. Switching to --cov=./litellm treats the argument as a path, which makes coverage.xml emit repo-relative paths (`litellm/proxy/proxy_server.py`). Each path is unambiguous, so Codecov resolves all files correctly. Verified locally: rerunning a single proxy_unit_tests test with --cov=./litellm produced `filename="litellm/proxy/proxy_server.py"`, `filename="litellm/router.py"`, and `filename="litellm/types/router.py"` as distinct entries — exactly the disambiguation Codecov needs. Touches every workflow that uploads coverage: the two reusable GHA workflows (_test-unit-base.yml, _test-unit-services-base.yml), test-mcp.yml, and all 14 invocations in .circleci/config.yml. * fix(mcp): allow delegate PKCE bypass for internal MCP servers Remove available_on_public_internet gating from delegate-auth-to-upstream paths so oauth2 + delegate_auth_to_upstream interactive servers behave the same when marked internal. Keeps M2M exclusion. Updates tests. * chore(mcp): warn on internal + upstream PKCE delegate Log verbose_logger.warning when loading oauth2 interactive servers with available_on_public_internet=false and delegate_auth_to_upstream=true (config + DB). Dashboard Alert for the same combo. CLAUDE note for operators. Tests for log and M2M skip. * fix(mcp): dedupe load_servers_from_config alias block Removes accidental duplicate alias/mcp_aliases and get_server_prefix logic (fixes PLR0915 and avoids resetting alias after mapping). * fix(mcp): expose delegate_auth_to_upstream in MCP server list rows (#27936) _build_mcp_server_table omitted delegate_auth_to_upstream, so GET /v1/mcp/server always returned the default false while the registry kept the DB value. Co-authored-by: Cursor <cursoragent@cursor.com> * feat(proxy): fix vector store retrieve/list/update/delete without model (#27929) * feat(proxy): fix vector store retrieve/list/update/delete routing without model Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): remove unchecked query-param injection in vector store management endpoints Co-authored-by: Cursor <cursoragent@cursor.com> * test(proxy): use subset assertion for vector store route test to allow extra kwargs like shared_session Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> * fix(managed_batches): convert raw output_file_id to managed ID in CheckBatchCost poller (#27984) * fix(managed_batches): convert raw output_file_id to managed ID in CheckBatchCost poller CheckBatchCost bypasses async_post_call_success_hook, causing raw provider output_file_ids to be persisted in LiteLLM_ManagedObjectTable. This fix converts output_file_id and error_file_id to managed base64 IDs before the DB write. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(check_batch_cost): persist managed file before mutating response and propagate team_id - Move setattr after store_unified_file_id so the response only receives the managed ID once the DB record is successfully written. Avoids serializing an orphaned managed ID into file_object when the store call fails. - Populate team_id on the minimal UserAPIKeyAuth from job.team_id so the managed file record is created with the correct team ownership, allowing other team members to access the batch output file via /files/{id}/content. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(managed_batches): extend test to cover error_file_id conversion Co-authored-by: Cursor <cursoragent@cursor.com> * fix managed file test --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(vertex-ai): fix zero cost/usage on completed Vertex AI batch jobs (#27912) * fix(vertex-ai): fix zero cost/usage on completed Vertex AI batch jobs Vertex batch jobs recorded 0 spend and 0 tokens after PR #25627 added automatic transformation of GCS predictions.jsonl to OpenAI format. Two bugs fixed: 1. batch_utils.py: the Vertex-specific cost/usage reader (calculate_vertex_ai_batch_cost_and_usage) was always invoked and reads raw usageMetadata fields that no longer exist in the OpenAI-shaped output. Now the reader is only used when disable_vertex_batch_output_transformation=True; otherwise the generic path handles the already-transformed OpenAI-shaped content. 2. cost_calculator.py: batch_cost_calculator skipped the global litellm.get_model_info() lookup when a model_info dict was passed in, even when that dict had no pricing fields (e.g. deployment metadata with only id/db_model). It now falls back to the global pricing table when the provided model_info has no pricing data. Co-authored-by: Cursor <cursoragent@cursor.com> * Update litellm/cost_calculator.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(cost-calculator): use not-any guard for pricing fallback in batch_cost_calculator Co-authored-by: Cursor <cursoragent@cursor.com> * fix(cost-calculator): treat explicit zero batch pricing as set in model_info The fallback to litellm.get_model_info() used truthy checks on pricing fields, so 0.0 was treated as missing and replaced by global rates. Use `is not None` like elsewhere in cost calculation. Add regression test. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * feat: add weighted-routing failover (#27980) * Feat: Add Weighted-Routing Failover * test(router): cover weighted failover helper functions Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): align weighted failover deployment list type with mypy Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): address greptile review on weighted failover - Narrow exception swallowing in `_maybe_run_weighted_failover` to `openai.APIError` so model failures defer to the regular fallback while programming bugs (AttributeError/KeyError/TypeError) surface. - Note async-only limitation of `enable_weighted_failover` in the Router constructor docstring. - Make the weighted distribution test less flaky (1000 iterations, looser bound) and make the non-simple-shuffle test deterministic by failing both deployments instead of relying on the latency strategy's first pick. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): ensure weighted failover metadata persists in kwargs The previous `kwargs.setdefault(metadata_variable_name, {}) or {}` returned a brand-new dict whenever the existing metadata was falsy (empty dict or None), so writes to `_failover_excluded_ids` never made it back into `kwargs`. Multi-hop weighted failover then re-selected previously failed deployments and exhausted `max_fallbacks` prematurely. Explicitly assign a fresh dict into kwargs when metadata is missing so mutations are visible to subsequent failover hops. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(router): regression for weighted failover metadata persistence Asserts kwargs["metadata"]["_failover_excluded_ids"] is populated after _maybe_run_weighted_failover, proving the metadata dict written by the helper is the same object that lives in kwargs (no disconnected copy). Pairs with the prior fix that replaced `setdefault(..., {}) or {}` with an explicit get/assign so writes survive across hops. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): harden weighted failover error/state handling - Catch RouterRateLimitError (ValueError) alongside openai.APIError in _maybe_run_weighted_failover so an exhausted intra-group retry falls through to the regular cross-group fallback path instead of bubbling out and bypassing configured fallbacks. - Stop mutating the shared input_kwargs dict; build a local copy with the weighted-failover keys so the entry (with _excluded_deployment_ids) cannot leak into later fallback paths reading the same dict. - _get_excluded_filtered_deployments now returns an empty list when the exclusion filter removes every healthy deployment, instead of falling back to the original list. The original-list behavior risked re-picking the just-failed deployment; callers already handle the empty case by raising their no-deployments error, which weighted failover now catches and converts into a normal cross-group fallback. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(router): fall through to rpm/tpm when total weight is zero When the weight metric's total is zero (e.g. after weighted-failover exclusion leaves only zero-weight backups), continue to the next metric (rpm/tpm) instead of returning a uniform random pick immediately. This lets rpm/tpm still drive routing when present, and only falls back to the uniform random pick at the end if no metric provides a positive total weight. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(router): skip weighted failover when remaining deployments are all in cooldown _maybe_run_weighted_failover was computing 'remaining' from all_deployments (every deployment in the model group, including those in cooldown). This meant that when all non-excluded deployments were in cooldown the method still invoked run_async_fallback unnecessarily, which propagated into async_get_healthy_deployments, found no eligible deployments, and raised RouterRateLimitError — only safely caught thanks to the earlier exception-broadening fix. The fix: before computing 'remaining', fetch the current cooldown set via _async_get_cooldown_deployments and subtract it from all_ids. This allows _maybe_run_weighted_failover to return None immediately (skipping the run_async_fallback call entirely) when every non-failed deployment is in cooldown, letting the caller fall through to the correct cross-group fallback path without the wasteful extra round-trip. Tests added: - unit: _maybe_run_weighted_failover returns None without calling run_async_fallback when all remaining deployments are in cooldown - unit: _maybe_run_weighted_failover still calls run_async_fallback when at least one healthy (non-cooldown) deployment is available - integration: end-to-end fallthrough to cross-group fallback when remaining deployments are in cooldown Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> * fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpo… (#27976) * fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpoint (#27943) * docs: add one-line docstring to _disable_debugging (#27894) Squash-merged by litellm-agent from oss-agent-shin's PR. * Add jp. Bedrock cross-region inference profile for claude-sonnet-4-6 (#27831) Squash-merged by litellm-agent from Cyberfilo's PR. * Sanitize empty text content blocks on /v1/messages (#27832) Squash-merged by litellm-agent from Cyberfilo's PR. * fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpoint The bedrock-mantle gateway (Claude Mythos Preview) serves the Anthropic Messages API at /anthropic/v1/messages; /v1/messages returns 404 Not Found. Both AmazonMantleConfig (chat/completions caller route) and AmazonMantleMessagesConfig (anthropic-messages caller route) hardcoded the wrong path, so every Mantle request 404'd before reaching the model. Per the Anthropic docs: "[Claude in Amazon Bedrock] uses the Messages API at /anthropic/v1/messages with SSE streaming." https://platform.claude.com/docs/en/api/claude-on-amazon-bedrock Confirmed independently against the live endpoint: /v1/chat/completions -> 200 OK /v1/messages -> 404 Not Found (what litellm used) /anthropic/v1/messages -> 200 OK (Claude only) Adds a regression test asserting both Mantle configs build the /anthropic/v1/messages path, and updates the existing assertions that encoded the wrong path. --------- Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> * fix: sanitize empty text blocks in sync anthropic_messages_handler path Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: João Costa <13508071+jpv-costa@users.noreply.github.com> Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(utils): import get_secret at runtime (#28014) * fix(proxy): make /config/update env-var encryption idempotent A single decrypt-then-encrypt chokepoint (_encrypt_env_variables_for_db) now backs both update_config and save_config. Re-submitting a value the Admin UI read back from /get/config/callbacks as ciphertext no longer stacks a second encryption layer, which previously decrypted to garbage and silently broke the callback. The chokepoint decrypts with the pure _decrypt_db_variables (no os.environ mutation on the write path) and encrypts exactly once; update_config merges only the sent keys so untouched env vars keep their stored ciphertext byte-for-byte. * test(proxy): add endpoint-level regression for /config/update double-encryption Adds test_update_config_env_var_round_trip_not_double_encrypted, which drives the real /config/update handler: first write plaintext, then re-POST the stored ciphertext (the Admin UI round-trip) and assert the value is not stacked with a second encryption layer and untouched keys stay byte-identical. Verified to fail against the pre-fix handler and pass after. Also tightens the unit test to exactly three ciphertext re-feeds. * chore(ci): modernize model references in tests and configs (#27856) * test: modernize models used in CircleCI e2e test suites Replaces obsolete models (gpt-4o, gpt-4o-mini, gpt-3.5-turbo, claude-3-5-sonnet-20240620, claude-sonnet-4-20250514) with current equivalents across the e2e_openai_endpoints and proxy_e2e_anthropic_messages_tests CircleCI jobs. - gpt-4o -> gpt-5.5 (responses API e2e tests) - gpt-4o-mini -> gpt-5-mini (websocket responses, oai_misc_config) - gpt-4o-mini-2024-07-18 -> gpt-4.1-mini-2025-04-14 (fine-tuning, still actively fine-tunable) - gpt-4 / gpt-3.5-turbo target_model_names example -> gpt-5.5 / gpt-5-mini - bedrock claude-3-5-sonnet-20240620 batch entry -> haiku-4-5-20251001 (also aligning oai_misc_config model_name with what test_bedrock_batches_api.py actually requests) - bedrock claude-sonnet-4-20250514 (deprecated, retires 2026-06-15) -> claude-sonnet-4-5-20250929 * test: point bedrock-claude-sonnet-4 alias at Sonnet 4.6, not 4.5 Greptile/Cursor flagged that after the previous commit, the bedrock-claude-sonnet-4 alias collided with bedrock-claude-sonnet-4.5 (both pointed to claude-sonnet-4-5-20250929). Rename to bedrock-claude-sonnet-4.6 and point it at the Sonnet 4.6 Bedrock ID (us.anthropic.claude-sonnet-4-6, already in the litellm model registry) so the alias name matches the underlying model version. * test: modernize models across remaining CI-mounted configs & tests Expands the modernization sweep to all CircleCI-mounted proxy configs and to test directories where the model literal is a fixture/route key (not the test's subject). Config changes: - proxy_server_config.yaml: bump gpt-3.5-turbo / gpt-3.5-turbo-1106 / gpt-4o / gemini-1.5-flash / dall-e-3 underlying models; rename gpt-3.5-turbo-end-user-test alias to gpt-5-mini-end-user-test; bump text-embedding-ada-002 underlying to text-embedding-3-small. User- facing aliases (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, etc.) preserved for backward compatibility with tests. - simple_config.yaml, otel_test_config.yaml, spend_tracking_config.yaml: bump gpt-3.5-turbo underlying to gpt-5-mini. - pass_through_config.yaml: claude-3-5-sonnet / claude-3-7-sonnet / claude-3-haiku entries replaced with claude-sonnet-4-5 / claude- haiku-4-5 / claude-opus-4-7. - oai_misc_config.yaml: align alias name with the gpt-5-mini rename. Test changes (proactive: claude-sonnet-4-20250514 / claude-opus-4- 20250514 retire 2026-06-15): - tests/llm_translation/test_anthropic_completion.py: bump 3 references + paired Vertex AI ID to claude-sonnet-4-5. - tests/llm_translation/test_optional_params.py: bump 2 references. - tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py and test_bedrock_anthropic_messages_test.py: bump router fixtures using the deprecated model IDs. - tests/pass_through_unit_tests/base_anthropic_messages_tool_search_test.py: modernize docstring examples. - tests/test_end_users.py: update references to renamed alias. * test: modernize placeholder model literals in router_unit_tests Mass replace_all on fixture/placeholder model literals across the router_unit_tests/ suite (model name is a routing key / label, not the test subject). Sub-agent sweep so far — additional commits will follow for logging_callback_tests/, enterprise/, top-level tests/test_*.py, and other CI-mounted dirs. Mappings applied: - gpt-3.5-turbo -> gpt-5-mini - gpt-4 (bare) -> gpt-5.5 - gpt-4o (bare) -> gpt-5 - text-embedding-ada-002 -> text-embedding-3-small - claude-3-sonnet-20240229 / claude-3-opus-20240229 / claude-3-haiku-20240307 / claude-3-5-sonnet-20240620 -> claude-sonnet-4-5-20250929 / claude-opus-4-7 / claude-haiku-4-5-20251001 as appropriate Explicitly preserved: - gpt-4o-mini-* variants (transcribe, tts, etc.) where they're current - gpt-4-turbo / gpt-4-vision-preview / gpt-4-0613 (subject literals) - JSONL batch body literals - Mock LLM response model fields (must match upstream) - Fake/mock identifiers * test: modernize placeholder model literals across remaining CI suites Sub-agent sweep across logging_callback_tests/, guardrails_tests/, enterprise/, pass_through_unit_tests/, otel_tests/, llm_responses_api_testing/, batches_tests/, spend_tracking_tests/, litellm_utils_tests/, unified_google_tests/, and a few top-level tests/test_*.py files where the model literal is a fixture or placeholder (router model_list, mock standard logging payload, mock callback data) rather than the test's subject. Mappings applied (see scope notes below): - gpt-3.5-turbo -> gpt-5-mini - gpt-4 (bare) -> gpt-5.5 - gpt-4o (bare) -> gpt-5.5 (corrected from initial gpt-5 — bare gpt-5 is not a valid OpenAI alias; only gpt-5.5 / gpt-5.4 / gpt-5.2-codex / gpt-5-mini exist) - gpt-4o-mini (bare) -> gpt-5-mini - text-embedding-ada-002 -> text-embedding-3-small - claude-3-sonnet-20240229 -> claude-sonnet-4-5-20250929 - claude-3-opus-20240229 -> claude-opus-4-7 - claude-3-haiku-20240307 -> claude-haiku-4-5-20251001 - claude-3-5-sonnet-20240620/20241022 -> claude-sonnet-4-5-20250929 - claude-3-7-sonnet-20250219 -> claude-sonnet-4-6 - gemini-1.5-flash -> gemini-2.5-flash - gemini-1.5-pro -> gemini-2.5-pro Explicitly preserved (not modernized): - llm_translation/ tests where model is the SUBJECT (provider-specific translation/transformation logic). Only the deprecated 20250514 references were already bumped in a prior commit. - Cost-calc / tokenizer subject tests in test_utils.py (skip-ranges documented by the sub-agent). - Bedrock model IDs in test_health_check.py path-stripping tests. - JSONL batch request bodies and mock LLM response bodies (must match upstream literal). - Langfuse expected-request-body JSON fixtures (cost values are exact- match-asserted; changing the model would shift response_cost). - gpt-3.5-turbo-instruct (text-completion endpoint; no modern OpenAI equivalent). - Top-level tests calling the proxy through user-facing aliases (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, dall-e-3) — aliases in proxy_server_config.yaml stay; only the underlying model was bumped. - tests/test_gpt5_azure_temperature_support.py (the test's whole point is model-name handling). - Fake / mock / openai/fake identifiers. Notable side fixes: - test_spend_accuracy_tests.py: UPSTREAM_MODEL now matches what spend_tracking_config.yaml's proxy actually routes to (gpt-5-mini), resolving a latent inconsistency. - proxy_server_config.yaml: bare `gpt-5` alias renamed to `gpt-5.5` (bare gpt-5 is not a valid OpenAI alias). - test_batches_logging_unit_tests.py: explicit_models list entries kept distinct (gpt-5-mini + gpt-5.5) after bulk rename. * test: fix CI failures from model modernization sweep CI surfaced 4 categories of regression from the bulk modernization: 1. Azure deployment names are customer-specific. Reverted: - tests/litellm_utils_tests/test_health_check.py: azure/text- embedding-3-small -> azure/text-embedding-ada-002 (the CI Azure account does not have a text-embedding-3-small deployment). - tests/logging_callback_tests/test_custom_callback_router.py: same revert for two router fixtures driving aembedding. 2. gpt-5 family does not accept temperature != 1. Tests that pass a custom temperature swapped from gpt-5-mini to gpt-4.1-mini (modern non-reasoning OpenAI mini that still accepts temperature/logprobs): - tests/logging_callback_tests/test_datadog.py - tests/logging_callback_tests/test_langsmith_unit_test.py - tests/logging_callback_tests/test_otel_logging.py 3. proxy_server_config.yaml's gpt-3.5-turbo-large alias was routing to gpt-5.5 (a reasoning model that rejects logprobs). The proxy test tests/test_openai_endpoints.py::test_chat_completion_streaming exercises logprobs/top_logprobs through that alias. Bumped the underlying model to gpt-4.1 (non-reasoning, still modern). 4. tests/logging_callback_tests/test_gcs_pub_sub.py asserts against a pinned JSON fixture (gcs_pub_sub_body/spend_logs_payload.json) with hardcoded model="gpt-4o" and a model-specific spend value. Reverted the litellm.acompletion calls in the test to model="gpt-4o" so the fixture's exact-match assertions still hold. 5. tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py: anthropic.messages.create routing to openai/gpt-5-mini returned an empty content[0] with max_tokens=100 (reasoning-token consumption). Swapped to openai/gpt-4.1-mini. * test: fix Assistants API model + 2 cursor[bot] review nits 1. pass_through_unit_tests/test_custom_logger_passthrough.py: gpt-5.5 isn't accepted by the /v1/assistants endpoint ("unsupported_model"). Switch to gpt-4.1-mini (modern, Assistants- API-supported, non-reasoning). 2. example_config_yaml/pass_through_config.yaml: the previous sweep bumped the claude-3-7-sonnet alias to claude-opus-4-7, which is a tier change (Sonnet -> Opus). Map to claude-sonnet-4-6 to keep the Sonnet tier intact. (Cursor bugbot review.) 3. example_config_yaml/simple_config.yaml: model_name was left as gpt-3.5-turbo while the underlying was bumped to gpt-5-mini, which muddles the "simple" example. Make both sides gpt-5-mini so the most basic example is a straight 1:1 mapping again. (Cursor bugbot review.) * fix: revert gpt-4/gpt-3.5-turbo alias underlying to non-reasoning models tests/test_openai_endpoints.py::test_completion calls the proxy alias "gpt-4" with temperature=0, and other tests call gpt-3.5-turbo with custom temperature / logprobs / the legacy /v1/completions endpoint. The earlier modernization mapped both aliases to gpt-5.5 / gpt-5-mini, which are reasoning models that reject temperature != 1 and don't expose /v1/completions. Map the aliases to gpt-4.1 / gpt-4.1-mini (modern non-reasoning OpenAI models) instead — keeps user-facing aliases preserved while picking a current underlying that still supports the parameters/endpoints the tests exercise. * test(proxy): isolate run_server CLI tests from prisma DB-setup path test_keepalive_timeout_flag and test_timeout_worker_healthcheck_flag were the only run_server tests in test_proxy_cli.py that neither stripped DATABASE_URL/DIRECT_URL nor mocked the prisma DB path. When a DATABASE_URL is present (CI/env leak), run_server --local enters the DB block and blocks in the un-timeout'd subprocess.run(["prisma"]) at proxy_cli.py:987 plus the ProxyExtrasDBManager migrate-deploy retry loops, ~370s per test on the CI runner. --dist=loadscope pins both to one xdist worker, so the proxy-infra job appears stuck at 99% and hits the 20-min timeout. Apply the same isolation every other run_server test in this file already uses: mock PrismaManager.setup_database + should_update_prisma_schema and strip DATABASE_URL/DIRECT_URL. Full module drops from 31.7s to 2.9s locally; both tests fall off the slow list. * feat: add OTEL GenAI latest-experimental semantic convention support (#27418) - Introduce `OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental` opt-in that switches OTEL traces to conform with the OpenTelemetry GenAI semantic conventions specification - Extract all semconv behavior into a new `OTELGenAISemconvMixin` class in `gen_ai_semconv.py`, mixed into `OpenTelemetry` to keep concerns separated - In semconv mode, span name follows `{operation} {model}` pattern (e.g. `chat gpt-4`) and span kind is set to `CLIENT` instead of legacy `litellm_request` - Replace `gen_ai.system` with `gen_ai.provider.name` and drop `llm.is_streaming` in semconv mode; add `gen_ai.request.{frequency_penalty,presence_penalty,top_k,seed,stop_sequences,stream,choice.count}` and `gen_ai.usage.cache_{creation,read}.input_tokens` attributes - Replace per-message `gen_ai.content.prompt` / per-choice `gen_ai.content.completion` log events with a single consolidated `gen_ai.client.inference.operation.details` event; omit `gen_ai.input/output.messages` when content capture is disabled - Suppress the non-standard `raw_gen_ai_request` child span entirely in semconv mode - Support both programmatic (`OpenTelemetryConfig.semconv_stability_opt_in` field) and environment variable activation; the two sources are unioned so either or both can enable the opt-in - Extract OTEL SDK `LogRecord` / `SeverityNumber` version-compatibility shim into a reusable `_otel_log_types()` static method to deduplicate the `< 1.39.0` / `>= 1.39.0` import branching - Add 30+ unit tests covering opt-in gating, span naming, attribute emission/omission rules, stop sequence normalization, cache token attributes, and the consolidated event lifecycle Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu> * chore: retrigger CI * test(ci): add reasoning_effort grid v4 e2e regression suite Encode the 231-cell QA sweep (21 provider x model combos x 11 effort values) from #27039 / #27074 as an automated CircleCI-gated regression suite. Each cell hits the real provider endpoint, captures the outgoing wire body via a pre-call CustomLogger, and asserts: - thinking.type, output_config.effort, thinking.budget_tokens, max_tokens in the captured request body (regression signal for silent drops/strips in any provider transformation) - HTTP status (200 vs BadRequestError -> 400) returned by litellm (regression signal for clean-error vs leaked-500 mappings) The matrix is encoded as a small rule set keyed by (model_mode, effort) plus per-model xhigh/max capability overrides, then expanded across the five chat-completion routes (Anthropic direct, Azure AI Foundry, Vertex AI, Bedrock Converse, Bedrock Invoke /chat) and the Bedrock Invoke /v1/messages route. Cells skip at runtime when the route's provider env vars are absent, so PR builds without credentials no-op gracefully. Wired into CircleCI as the reasoning_effort_grid_v4_e2e job behind the existing main / litellm_* branch filter. * fix(reasoning_effort_grid_v4): cleanup unused fixture, parse converse body, guard budget tokens - Remove unused vertex_credentials_path fixture (and now-unused os import) from conftest.py. - Parse Bedrock Converse complete_input_dict (logged as a JSON string by converse_handler.py) before passing to _assert_cell, so dict accessors work uniformly across routes. - Extend _BUDGET_TOKENS with xhigh and max entries so the budget-mode branch in expected() cannot KeyError if a future budget model gains the matching cap. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(reasoning_effort_grid_v4): grant sonnet-4-6 entries the max-effort cap The runtime _validate_effort_for_model allows effort='max' for any Claude 4.6 model (opus or sonnet), and model_prices_and_context_window sets supports_max_reasoning_effort: true for claude-sonnet-4-6. The grid spec previously gave sonnet-4-6 entries _CAPS_NONE, so expected() returned status=400 for effort='max', which mismatched the runtime's status=200 and caused 6 cells (one per route) to fail. Rename _CAPS_OPUS_4_6 to _CAPS_4_6 (since the cap set is shared by opus and sonnet 4.6) and assign it to all sonnet-4-6 entries. Co-authored-by: Yassin Kortam <yassin@berri.ai> * refactor(tests): move reasoning_effort grid suite under llm_translation, drop v4 naming - Drop the "v4" suffix throughout: it referred to the QA sweep iteration, not this test suite. There's only one regression suite, so just call it reasoning_effort_grid. - Move tests/test… * Revert "merge main (#28629)" This reverts commit e4870f7bb68cf1dbc43b4bae9e5ee09b86aea481. * refactor(purview): remove unused logging_only constructor param The logging_only kwarg was passed in but only echoed in a log message; behavioral mode is driven by event_hook. Drop the dead parameter and the no-op derivation in the initializer. * fix(purview): log post-call success hook via @log_guardrail_information * fix(purview): raise HTTPException 400 on Responses API transform failure When the Responses API input cannot be transformed in blocking mode, raise an HTTPException with a clear 400 detail instead of re-raising the raw transformation exception. The latter would surface as a 500 and be indistinguishable from a backend provider failure; the former matches the docstring and the existing pre-call HTTPException patterns. * Fix Purview audit prompt extraction for Responses API logging hook The async_logging_hook receives kwargs == litellm_logging_obj.model_call_details, where function_setup mirrors the raw responses input under the 'messages' key (string or list of input items, not chat-format messages). The previous logic took the generic 'messages' branch first, calling get_prompt_text_for_dlp on data that is not in the chat-message format, and the responses-specific extractor was never reached. As a result, the prompt half of the Purview audit was silently skipped (or produced garbage text) for Responses API calls in logging_only mode. Check call_type first and route Responses API calls to _responses_api_input_to_str, which reads the original 'input' and 'instructions' keys that pre_call and update_environment_variables persist on model_call_details. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview_dlp): check call_type for responses before messages in pre-call hook Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview_dlp): don't reject empty-string prompts as token-id prompts completion_prompt_to_str returns None for both token-id lists *and* empty/whitespace-only strings (stripped). The previous check 'raw_prompt is not None and prompt_text is None' conflated these cases, raising the misleading 'Token-id completion prompts cannot be scanned' error for harmless empty-string prompts like {"prompt": ""}. Tighten the check to only reject true token-id prompts (non-empty list of ints). Empty/whitespace string prompts now fall through to the 'no prompt text → skip scan' path. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview_dlp): scan ResponsesAPI streaming completed event for DLP The streaming iterator hook previously routed all assembled streams through stream_chunk_builder, which only knows chat/text-completion deltas. Responses API streams emit typed events (response.created, response.completed, ...) whose final event carries the full ResponsesAPIResponse, so stream_chunk_builder would raise APIError or pass the assembled response through unchanged. Detect Responses API streaming chunks before the chat/text fallthrough and extract the assembled ResponsesAPIResponse from the latest response.completed (or response.failed / response.incomplete) event, then scan its output_text via the same _completion_response_text_parts path used by non-streaming. * fix(purview_dlp): fail closed on incomplete Responses API streams Previously, _assemble_responses_api_from_chunks returned None both when the stream was not a Responses API stream and when it was a Responses API stream but no final ResponsesAPIResponse-bearing event was received. The caller treated both cases identically and fell through to stream_chunk_builder, which does not understand Responses API events. Return a (is_responses_api_stream, assembled) tuple so the caller can fail closed with an accurate error when Responses API events were seen but no final response event arrived, instead of misrouting events to the chat chunk builder. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview_dlp): wrap upstream DLP errors as HTTPException(400) in blocking mode Previously a bare `raise` in `_check_content` re-propagated raw network / HTTP errors (e.g. httpx.HTTPStatusError, ConnectionError) to the client, which would surface as a 500. Now blocking-mode failures from the Graph `processContent` call (and OAuth token / protection-scopes calls) are converted to HTTPException(400) with a structured detail payload, while HTTPException instances raised by upstream layers continue to propagate unchanged. Logging-only mode is unaffected. * test(purview_dlp): cover HTTP error paths for token + Graph POST * fix(purview): include Responses API function_call arguments in DLP scan ResponsesAPIResponse.output_text only aggregates output_text content blocks and ignores function_call items, so sensitive data in model-generated tool-call arguments would bypass the DLP scan. Mirror the ModelResponse path by extracting function_call arguments explicitly from the output list. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(purview_dlp): scan ResponsesAPIResponse in stream_chunk_builder fallback If a Responses API stream slips past _assemble_responses_api_from_chunks (no chunks with type starting with 'response.') and stream_chunk_builder somehow returns a ResponsesAPIResponse, route it through _completion_response_text_parts instead of the 'not a ModelResponse' pass-through that would leak content unscanned. * fix(purview_dlp): preserve upstream Graph status on `_check_content` errors httpx.HTTPStatusError from Graph API (429, 503, etc.) was always wrapped as HTTPException(400), making rate-limits and infrastructure errors indistinguishable from a DLP policy block and stripping retry-after info. Now: - 429 and 5xx pass through with their original status code; the upstream Retry-After header is forwarded. - 401/403 (proxy-side credential/consent issue, not actionable by the client) map to 502 Bad Gateway. - A debug log makes the logging_hook -> async_logging_hook deferral observable so audit failures don't silently disappear if the framework stops dispatching async_logging_hook for some code path. * fix(purview_dlp): reject nested token-id completion prompts OpenAI /v1/completions accepts prompt: [[token, ids]] (multi-prompt token-id batches). The previous blocking-mode check only fired on a flat list[int], so nested or mixed token-id prompts skipped the Purview scan while the model still received the data. Extract the token-id detection into PurviewGuardrailBase.is_token_id_prompt and use it from the pre-call hook so every list shape Purview cannot decode fails closed. * fix(purview): drop caller-influenceable identity fallbacks in audit resolver Logging-only hook now resolves the Purview user from only the proxy-injected user_api_key_user_id (which mirrors UserAPIKeyAuth.user_id after the proxy strips caller-supplied user_api_key_* keys). Skipping the audit when no trusted identity is available prevents a caller from submitting metadata.user_id pointing at a victim's Entra object id and having their prompt/response sent to Purview under that user's identity. --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Yuneng Jiang <yuneng@berri.ai> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> Co-authored-by: claude <claude@anthropic.com> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Kenan Yildirim <kenan@kenany.me> Co-authored-by: vladpolevoi <vladp@lasso.security> Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Dennis Henry <dennis.henry@okta.com> Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com> Co-authored-by: ishaan-berri <155045088+ishaan-berri@users.noreply.github.com> Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: João Costa <13508071+jpv-costa@users.noreply.github.com> Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Michael-RZ-Berri <michael@berri.ai> Co-authored-by: Shivam Rawat <shivam@berri.ai> Co-authored-by: Tai An <antai12232931@outlook.com> Co-authored-by: Vincent <yimao1231@gmail.com> Co-authored-by: Kris Xia <xiajiayi0506@gmail.com> Co-authored-by: d 🔹 <liusway405@gmail.com> Co-authored-by: Fabrizio Cafolla <developer@fabriziocafolla.com> Co-authored-by: Tom Denham <tom@tomdee.co.uk> Co-authored-by: escon1004 <70471150+escon1004@users.noreply.github.com> Co-authored-by: Divyansh Singhal <97736786+Divyansh8321@users.noreply.github.com> Co-authored-by: robin-fiddler <robin@fiddler.ai> Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Noah Nistler <60981020+noahnistler@users.noreply.github.com> Co-authored-by: Felipe Rodrigues Gare Carnielli <felipe.gare@hotmail.com> Co-authored-by: harish-berri <harish@berri.ai> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Ryan <ryan@Ryans-MBP.localdomain> Co-authored-by: Claude (greptile subagent) <claude-greptile-bot@anthropic.com> Co-authored-by: TorvaldUtne <78661304+TorvaldUtne@users.noreply.github.com> Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> Co-authored-by: Isha <72744901+IshaMeera@users.noreply.github.com> Co-authored-by: cwang-otto <chengxuan.wang@ottotheagent.com> Co-authored-by: Roman Pushkin <roman.pushkin@gmail.com> Co-authored-by: boarder7395 <37314943+boarder7395@users.noreply.github.com> Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com> Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com> Co-authored-by: Kevin Zhao <zkm8093@gmail.com> Co-authored-by: Matthew Lapointe <lapointe683@gmail.com> Co-authored-by: Elon Azoulay <elon.azoulay@gmail.com> Co-authored-by: afoninsky <andrey.afoninsky@gmail.com> Co-authored-by: Joseph Barker <156112794+seph-barker@users.noreply.github.com> Co-authored-by: Maruti Agarwal <88403147+marutilai@users.noreply.github.com> Co-authored-by: Cursor Bugbot <bugbot@cursor.com> Co-authored-by: Greptile <greptile-apps[bot]@users.noreply.github.com> Co-authored-by: Greptile Reviewer <greptile-apps@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Felipe Garé <90070734+FelipeRodriguesGare@users.noreply.github.com> Co-authored-by: withomasmicrosoft <withomas@microsoft.com> Co-authored-by: Aditya Singh <60082699+adityasingh2400@users.noreply.github.com>	2026-05-22 15:59:04 -07:00
yuneng-jiang	574ee7526d	test(streaming): tolerate Vertex 429 wrapped in MidStreamFallbackError (#28669) ... Streaming 429s are wrapped in MidStreamFallbackError so the Router can fall back; the existing 'except litellm.RateLimitError: pass' in test_vertex_ai_stream no longer matches, causing the generic pytest.fail branch to fire when upstream Vertex returns 429. Add a sibling except for MidStreamFallbackError that only swallows it when e.original_exception is a RateLimitError, so unrelated streaming failures still fail the test.	2026-05-22 15:57:29 -07:00
milan-berri	1b141bc588	fix(bedrock): decouple STS region from Bedrock aws_region_name (#28245) ... * fix(bedrock): decouple STS region from Bedrock aws_region_name STS AssumeRole now resolves signing region from aws_sts_endpoint (parsed host) or AWS_REGION/AWS_DEFAULT_REGION instead of aws_region_name, fixing air-gapped cross-region Bedrock setups and endpoint/signature mismatches. Co-authored-by: Cursor <cursoragent@cursor.com> * test(bedrock): add regression coverage for _build_sts_client_kwargs Parametrize _resolve_sts_region and _build_sts_client_kwargs matrix cases, and assert IRSA/web-identity paths use aligned STS endpoint and region_name. Co-authored-by: Cursor <cursoragent@cursor.com> * refactor(bedrock): tighten STS region helpers and drop redundant web-identity endpoint synthesis Co-authored-by: Cursor <cursoragent@cursor.com> * test(bedrock): cover FIPS, GovCloud, and China STS endpoints Addresses greptile P2: regex sts(?:-fips)? supported sts-fips hosts but was not exercised by the parametrized parse test. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>	2026-05-23 00:39:24 +03:00
Krrish Dholakia	a3c953ed4e	style: apply black formatting to fix lint CI (LIT-3274) (#28639) (#28641) ... * fix(bedrock): strip bedrock/ prefix and URL-encode ARNs in get_bedrock_model_id for invoke path The invoke path (used by /v1/messages → Anthropic SDK / Claude Code) called get_bedrock_model_id() which, when falling back to the raw model string, did not strip the 'bedrock/' routing prefix and did not URL-encode ARNs. For a model like: bedrock/arn:aws:bedrock:us-east-1:<ACCOUNT>:inference-profile/global.anthropic... the URL built was: /model/bedrock/arn:aws:bedrock:…/invoke-with-response-stream ❌ Bedrock returned a JSON error body. LiteLLM's AWSEventStreamDecoder passed those bytes into botocore's EventStreamBuffer which expects binary event-stream framing. Checksum validation failed on the JSON prelude (0x223a7b22 == ':{"') producing a misleading botocore.eventstream.ChecksumMismatch instead of the actual Bedrock error. Fix: strip 'bedrock/' (and 'invoke/') routing prefix from model string, then URL-encode if the result is an ARN — matching what the converse path already does in converse_handler.py. Fixes: LIT-3274 * fix(bedrock): use strip_bedrock_routing_prefix to handle compound prefixes Address greptile review: the original fix used a loop with break, so bedrock/invoke/arn:... only stripped bedrock/ leaving invoke/arn:... which is not an ARN → fell through to .replace('invoke/','',1) → bare unencoded ARN → same malformed-URL bug. strip_bedrock_routing_prefix() iterates without break, correctly stripping bedrock/ then invoke/ in sequence. Also adds test case for the compound-prefix scenario. * style: apply black formatting to fix lint CI (LIT-3274) --------- Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: LiteLLM Bot <bot@berri.ai>	2026-05-22 12:10:37 -07:00
milan-berri	9600fda2cc	fix(sagemaker): send native Cohere embed payload to Cohere SageMaker endpoints (#28613) ... * fix(sagemaker): use Cohere embed payload for Marketplace endpoints SageMaker embedding only special-cased Voyage; every other endpoint received HuggingFace TGI `{"inputs": [...]}`. AWS Marketplace Cohere containers expect the native Cohere embed payload (`texts`, `input_type`) and reject the HF shape with `422 EmbedReqV2.inputs is of type string but should be of type Object`. Add `SagemakerCohereEmbeddingConfig` that reuses Bedrock/Cohere request and response transforms, and route SageMaker endpoint names containing `cohere` or a Cohere embed model fragment (`embed-multilingual`, `embed-english`, `embed-v3`, `embed-v4`) to it. Supports `input_type`, `dimensions`, and `encoding_format`. Voyage and HuggingFace SageMaker endpoints are unchanged. Co-authored-by: Cursor <cursoragent@cursor.com> * refactor(sagemaker): simplify cohere detection and align with file conventions - Detect Cohere SageMaker endpoints with a single `"cohere" in model.lower()` check, mirroring the existing Voyage branch instead of a separate helper function and marker constant. - Drop instance caches of sub-configs; instantiate `BedrockCohereEmbeddingConfig` / `CohereEmbeddingConfig` per call to match the existing pattern in `BedrockCohereEmbeddingConfig._transform_request`. - Match `SagemakerEmbeddingConfig`'s signatures, defaults, and `Any` typing for `logging_obj`; collapse the input-normalization helper inline. - Inline `transform_embedding_response` input lookup; no behavior change. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(sagemaker): restore provider-supported embedding params after map Cohere input_type is advertised in get_supported_openai_params but was filtered out of non_default_params by OPENAI_EMBEDDING_PARAMS before map_openai_params ran. Merge supported params from passed_params after map (same path Greptile flagged). Handle input_type explicitly in SagemakerCohereEmbeddingConfig.map_openai_params and add an integration test through get_optional_params_embeddings. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(embeddings): only restore non-OpenAI supported params after map The post-map restore loop must skip OPENAI_EMBEDDING_PARAMS so mapped fields (e.g. dimensions -> output_dimension) are not duplicated under their OpenAI names. Align SageMaker embedding import order with sibling files and add a regression test for dimensions mapping. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(sagemaker): avoid double post_call on Cohere embedding response Greptile review on #28613 caught that `CohereEmbeddingConfig._transform_response` calls `logging_obj.post_call` internally. The SageMaker embedding handler already calls `post_call` once before invoking the transform, so the Cohere SageMaker path fired callbacks, cost calculators, and log handlers twice per request. Extract the parsing body of `_transform_response` into `_populate_embedding_response` (pure extract-method, no behavior change for existing Cohere direct or Bedrock Cohere paths, which keep calling `_transform_response`). Have `SagemakerCohereEmbeddingConfig` call the new helper directly so it parses the response without re-logging. Add a regression test asserting `logging_obj.post_call` is not invoked by the SageMaker Cohere transform. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>	2026-05-22 12:00:42 -07:00
ryan-crabbe-berri	643989989f	chore(test): remove dead old Playwright e2e suite (#28632) ... The Playwright suite under tests/proxy_admin_ui_tests/e2e_ui_tests/ is no longer wired into CI (only test_*.py is globbed) and every active spec is duplicated by ui/litellm-dashboard/e2e_tests/tests/ (login, auth redirect, search users, internal user list). team_admin.spec.ts was entirely commented out. Removing the directory plus its only-used-here playwright config, package.json/lock, and utils/login.ts keeps the canonical suite under ui/litellm-dashboard/e2e_tests/ as the single source of truth.	2026-05-22 11:29:17 -07:00
yuneng-jiang	f62ae93e13	test(proxy): behavior-pinning matrix for tier-2/3 key + team management endpoints (#28620) ... * test(proxy): add create_scratch_actor harness helper Adds create_scratch_actor() to the management behavior-suite conftest and extends create_scratch_team() with team_member_permissions / models kwargs, needed by the PR3 team-key-permission and team-model matrices. The new helper mints a scratch-prefixed user + verification token (+ org memberships), all reclaimed by the existing scratch-prefix teardown. * test(proxy): pin /key block, unblock, health, aliases behavior Adds behavior-pinning matrices for POST /key/block, POST /key/unblock, POST /key/health, and GET /key/aliases. Pins that the management-route gate 401s ORG_ADMIN-role callers before _check_key_admin_access runs, the block/unblock round-trip on the blocked column, missing-key 404, and the _apply_non_admin_alias_scope visibility rules for /key/aliases. * test(proxy): pin /key/bulk_update + /team/key/bulk_update behavior Adds behavior-pinning matrices for POST /key/bulk_update (PROXY_ADMIN-only; ORG_ADMIN stopped 401 at the route gate, INTERNAL_USER-role 403 at the handler) and POST /team/key/bulk_update (team-member-permission gate keyed on KEY_UPDATE). Pins batch semantics: empty/over-cap 400, per-key failure isolation into failed_updates, all_keys_in_team broadcast, and no-keys 404. Adds an optional key_alias arg to create_scratch_key for multi-key scenarios. * test(proxy): pin /key SA-generate, v2-info, reset-spend behavior Adds behavior-pinning matrices for POST /key/service-account/generate (team-membership + team-member-permission gating; SA keys carry no user_id), POST /v2/key/info (per-key _can_user_query_key_info silently drops invisible keys), and POST /key/{key}/reset_spend (PROXY_ADMIN or team admin only; missing key 404, reset-value 400). Pins that ORG_ADMIN-role callers are stopped 401 at the management-route gate on the two non-info routes. * test(proxy): close PR1/PR2 key-side deferred coverage gaps Closes the four key-side gaps deferred from PR1/PR2: - 404 on missing key for /key/update and /key/delete (not 401/403) - denied /key/update leaves max_budget/tpm_limit/rpm_limit untouched - /key/regenerate enforces litellm.upperbound_key_generate_params (#26340) - /key/list key_alias substring vs exact (admin-only) + team_id filter, and a non-admin filtering a foreign team is 403 * test(proxy): pin /team block, unblock, available, filter/ui, members/me Adds behavior-pinning matrices for POST /team/block + /team/unblock (management-route gate fronts _verify_team_access; reachable only by PROXY_ADMIN and an org admin of the team's own org), GET /team/available (default empty path), GET /team/filter/ui (route-gated PROXY-ADMIN-only despite the handler having no gate), and GET /team/{team_id}/members/me (caller resolves its own membership; non-member 404, no-user_id key 400). * test(proxy): pin /team model add/delete + permissions endpoints Adds behavior-pinning matrices for POST /team/model/add + /team/model/delete (route-gated PROXY-ADMIN-only; missing team 404), GET /team/permissions_list + POST /team/permissions_update (self-managed; proxy/team/org admin pass), and POST /team/permissions_bulk_update (PROXY_ADMIN-only). Pins the deliberate divergence that the available-team self-join grants read access via permissions_list but never write access via permissions_update. * test(proxy): pin /team delete, bulk_member_add, v2/list, daily/activity Adds behavior-pinning matrices for POST /team/delete (per-team _verify_team_access; batch aborts whole on a missing id), POST /team/bulk_member_add (route-gated PROXY-ADMIN-only; empty/over-cap 400), GET /v2/team/list (_enforce_list_team_v2_access — bare query 401s regular users, org-scoped for org admins) and GET /team/daily/activity (non-member team_ids filter 404, the VERIA-43 fix). * test(proxy): add route-coverage gate + close team org-relocation gap Adds test_route_coverage.py (PR3.M1): parses every @router route literal from the two management-endpoint source files and asserts each is exercised by >=1 behavior-suite scenario — a permanent regression guard for future routes. Closes the last PR1/PR2 deferred gap: the /team/update org-relocation allowed branch, exercised by a dual-org-admin minted via create_scratch_actor. test_team_model uses literal route URLs so the coverage parser resolves them. * test(proxy): bound plain route params to one path segment in coverage gate Plain path params ({team_id}) now compile to [^/?]+ instead of [^?]+, so a parameter cannot span '/'. Starlette ':path' params still match across '/'. Keeps the route-coverage guard from falsely reporting a future multi-segment route as covered. All 37 routes remain covered.	2026-05-22 11:24:41 -07:00
yuneng-jiang	985574b6be	fix(check_licenses): read PEP 639 license-expression metadata (#28529) ... The dependency license checker only read the legacy free-text `info.license` field from PyPI. Packages that adopt PEP 639 publish their license as an SPDX expression in `info.license_expression` and leave the legacy field null, so the checker reported "Unknown license" and failed CI for every newly-bumped PEP 639 dependency. `get_package_license_from_pypi` now resolves the license in order: `license_expression`, then legacy `license`, then the `License :: OSI Approved :: ...` trove classifiers. `is_license_acceptable` splits compound SPDX expressions on the uppercase OR/AND operators (case-sensitive, so the lowercase `-or-later` inside an identifier is not mistaken for an operator) and strips `WITH <exception>` suffixes, requiring every component to be acceptable. Free-text license blobs are detected and fall back to the original whole-string matching. The `black` and `pydantic-settings` entries in liccheck.ini that existed solely to work around this now resolve correctly on their own and have been removed.	2026-05-22 11:22:38 -07:00
Mateo Wang	b0b25ae4b9	Include team alias in CLI JWT token (#28621)	2026-05-22 10:40:59 -07:00
Sameer Kankute	e9f0eddbd1	Litellm oss staging 2 (#28582) ... * fix(anthropic): handle empty streaming tool calls (#28549) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * [Feature][Bug Fix] Decouple Azure OpenAI Deployment ID from model name via base_model to fix gpt5 model routing (#28490) * feat(azure): decouple deployment ID from model name via base_model Azure OpenAI deployments have arbitrary names (deployment IDs) that may not match the underlying model. Previously, model-type detection (o-series, gpt-5, etc.) relied on substring matching against the deployment name, causing misrouted configs and rejected params when deployment names were non-standard (e.g. 'my-deployment-id' for gpt-5.2). This change extends the existing base_model field to drive model-type detection, config selection, supported param resolution, and param mapping throughout the Azure call path: - _get_azure_config() uses base_model for is_o_series/is_gpt_5 checks - get_provider_chat_config() threads base_model for Azure - get_supported_openai_params() accepts and uses base_model - get_optional_params() accepts base_model and passes it to all Azure config method calls (get_supported_openai_params, map_openai_params) - azure.py completion handler uses base_model for GPT-5 detection - Config internal methods (e.g. is_model_gpt_5_2_model) now receive base_model so features like logprobs are correctly enabled Fully backward compatible - when base_model is unset, behavior is identical. Existing o_series/ and gpt5_series/ prefix workarounds continue to work. Usage in proxy config: model_list: - model_name: my-gpt5 litellm_params: model: azure/my-deployment-id model_info: base_model: azure/gpt-5.2 Fixes: non-standard deployment names like 'prefix-gpt-5.2' rejecting logprobs/top_logprobs despite the underlying model supporting them. * Addressing Greptile comments. * gemini-3.1-flash-lite pricing (#27933) * feat(model_prices): add gemini-3.1-flash-lite pricing with standard/batch/flex/priority tiers * fix pricing * add service tier --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> * fix(openai-responses): strip Anthropic cache_control from Responses API requests (#28431) Squash-merged by litellm-agent from cwang-otto's PR. * Treat None litellm_provider as wildcard in _check_provider_match (#28523) Squash-merged by litellm-agent from adityasingh2400's PR. * fix greptile * fix: use _azure_detection_model in default Azure branch of get_supported_openai_params Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(openai-responses): strip cache_control on compact endpoint as well Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Felipe Garé <90070734+FelipeRodriguesGare@users.noreply.github.com> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: withomasmicrosoft <withomas@microsoft.com> Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> Co-authored-by: cwang-otto <chengxuan.wang@ottotheagent.com> Co-authored-by: Aditya Singh <60082699+adityasingh2400@users.noreply.github.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-22 10:04:23 -07:00
Sameer Kankute	21a21e01f7	fix(responses): use OpenAI SSEDecoder for Responses API streaming (#28566) ... * fix(responses): use OpenAI SSEDecoder for Responses API streaming httpx aiter_lines() uses str.splitlines(), which splits on U+2028 inside JSON payloads and silently drops response.completed (no spend log). Use openai._streaming.SSEDecoder (bytes.splitlines before decode) instead. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(responses): drop redundant SSE prefix strip after SSEDecoder switch SSEDecoder already strips the 'data:' field prefix from each event, so the extra call to _strip_sse_data_from_chunk on sse.data was redundant and could incorrectly mangle payloads whose actual content starts with 'data:'. Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-22 10:03:36 -07:00
Sameer Kankute	50a3f10a92	feat(proxy): persist allowlisted OIDC claims in CLI SSO poll (#28463) ... * feat(proxy): persist allowlisted OIDC claims in CLI SSO poll Map CLI_SSO_CLAIM_MAP sources into user metadata and return scalar attribution_metadata from /sso/cli/poll. Build SSOUserDefinedValues in cli_sso_callback so first-time CLI logins can upsert users. Add mock OIDC scripts and tests for claim extraction and poll exposure. Co-authored-by: Cursor <cursoragent@cursor.com> * docs(proxy): document CLI SSO attribution_metadata in client README Co-authored-by: Cursor <cursoragent@cursor.com> * Delete scripts/mock_oidc_server_for_cli_sso.py * Delete scripts/test_cli_sso_claims_e2e.py * fix(ui_sso): preserve claim types and avoid metadata. prefix stripping - Replace _update_dictionary with a local recursive merge so string OIDC claim values that happen to look numeric are not silently coerced to int/float when persisting CLI SSO attribution metadata. - Use a local dot-path resolver in _extract_sso_claim_value so that source claim paths beginning with 'metadata.' are not silently stripped by get_nested_value (which is designed for LiteLLM JWT metadata, not arbitrary OIDC claims). Co-authored-by: Yassin Kortam <yassin@berri.ai> * Remove redundant metadata. prefix strip in _set_nested_metadata_value The _parse_cli_sso_claim_map already strips the metadata. prefix from dest keys before reaching the setter. The duplicate strip in _set_nested_metadata_value was a no-op in normal flow but could mis-place values for dest keys like metadata.metadata.foo. Co-authored-by: Yassin Kortam <yassin@berri.ai> * Fix greptile * Fix ruff * Move CLI SSO user defined values build inside try/except for consistent error handling Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(proxy): enforce restricted SSO group on CLI SSO callback Apply verify_user_in_restricted_sso_group before CLI session completion and user upsert, matching the UI SSO path. Re-raise ProxyException so restricted-group denials return 403 instead of 500. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): replace recursive CLI SSO metadata helpers with iterative merge Use stack-based flatten/merge to satisfy recursive_detector CI. Fix mypy types for UserApiKeyCache and user_id on CLI SSO session completion. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: resolve nested CustomOpenID extra_fields in CLI SSO claim extraction When GENERIC_USER_EXTRA_ATTRIBUTES captures a parent object (e.g. org_info), extra_fields stores it as {"org_info": {"department": "..."}}. A CLI claim map entry using a dotted path like org_info.department would silently fail because the lookup only checked the exact flat key. Fall back to dotted-path resolution on extra_fields before model_dump(). Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(sso): update CLI SSO test for new received_response kwarg and remove redundant 'token' secret fragment Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-22 09:58:50 -07:00
Sameer Kankute	ef36e89638	feat(mcp): Add tool call and tool list support via UI for Oauth mcps (#28454) ... * feat(mcp): cache OAuth token client-side so Tools tab loads without re-auth After a user creates an OAuth MCP server and completes the authorization flow, the resulting access token is now stored in sessionStorage keyed by server_id. The MCP Tools tab reads this cached token and includes it as an MCP auth header when listing and invoking tools, so the user never sees an empty tool list. When the session ends (tab close / new browser) an Authorize button re-triggers the flow without leaving the Tools screen. Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com> * fix(ui/mcp): surface listMCPTools 401 errors so auth gate reappears listMCPTools previously swallowed all errors (including HTTP 401) by returning a synthetic { tools: [], error: 'network_error', ... } payload. That made the useQuery retry-on-401 guard and mcpToolsError dead code, so expired OAuth tokens never re-triggered the auth gate. - Throw an enhanced Error with .status attached on non-2xx responses (still preserves the legacy shape for true network failures so the caller can render a generic message without crashing). - Clear the cached OAuth session token when the tools query fails with 401, mirroring callMCPTool's onError handler so the Authorize button is shown again. - Surface mcpToolsError in the existing error banner. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(mcp-tools): stable onSuccess + reuse parsed flow state - Pass stable setOauthToken setter directly as onSuccess to avoid recreating useToolsOAuthFlow's resumeOAuthFlow on every render. - Reuse the already-parsed FLOW_STATE_KEY value (peeked) instead of re-reading and re-parsing sessionStorage in resumeOAuthFlow. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(ui/mcp): restore listMCPTools never-throws contract The previous fix made listMCPTools throw on HTTP errors while still returning a synthetic object on network errors. This inconsistent contract broke existing callers (MCPToolPermissions, MCPAppsPanel, MCPConnectPicker) which inspect result.error / result.message and expect the function to never throw. - Return a normalized { tools: [], error, message, status, ... } object on HTTP errors (instead of throwing) so all callers see a consistent shape and the user-visible error text from result.message is preserved. - Convert the returned error object into a thrown Error inside the one caller that needs it — the useQuery in mcp_tools.tsx — so the 401 retry/onError handlers still trigger and clear the cached OAuth token. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix greptile * fix(mcp): align OAuth header alias lookup with dashboard sanitization Backend auth header resolution now matches x-mcp-{alias} keys produced by the dashboard sanitizer, and the Tools tab re-syncs OAuth tokens when serverId changes. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(mcp): widen auth header lookup types for list_tools Accept legacy str | dict server auth maps and annotate list_tools server_auth_header as Union[str, dict] for mypy. Co-authored-by: Cursor <cursoragent@cursor.com> * refactor(ui): extract shared buildCallbackUrl/clearStorage for MCP OAuth hooks Hoist the duplicate buildCallbackUrl and clearStorage helpers out of useToolsOAuthFlow and useUserMcpOAuthFlow into a new shared module src/hooks/mcpOAuthUtils.ts so the two hooks cannot drift if the URL construction or storage cleanup logic needs to change. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(ui): don't gate M2M OAuth MCP servers behind interactive authorize M2M (client_credentials) OAuth servers share auth_type="oauth2" with interactive PKCE servers, but the backend fetches their token internally and they typically lack a user authorization endpoint. Gating tool listing on them rendered an Authorize button that would fail or redirect incorrectly. Detect M2M via the presence of token_url (matching the existing heuristic in mcp_server_edit.tsx) and skip the auth gate. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(ui/mcp): return error shape when listMCPTools JSON parse fails Restore the never-throws contract when response.json() fails on a 2xx body so callers do not receive null and crash on result.tools. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-22 09:04:04 -07:00
Sameer Kankute	7a93cceb9f	Add error_description and hint for oauth flows (#28471) ... * Add error_description and hint for oauth flows * Fix tests * fix(mcp-oauth): improve redirect_uri errors without leaking internal config Use NoReturn on _oauth_invalid_request, structured errors for BYOK loopback validation, and refactor validate_trusted_redirect_uri to satisfy PLR0915. Keep PROXY_BASE_URL and raw proxy_base_url in server logs only, not in the HTTP 400 body returned to unauthenticated callers. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(mcp-oauth): stop leaking internal proxy origin in redirect_uri 400 body The trusted-redirect-uri rejection helper included the proxy's resolved scheme/host/port (e.g. http://litellm-internal:4000) in both the error_description and as a top-level proxy_origin field. Since the OAuth /authorize endpoint is unauthenticated, any caller could probe with a crafted redirect_uri and enumerate the internal network topology behind a reverse proxy. Keep full diagnostic detail in the server-side warning log (including the computed proxy base) but omit proxy-side values from the HTTP 400 body. Also drop the duplicated origin computation in _raise_trusted_redirect_uri_rejected now that those values are no longer needed by the response. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(mcp-oauth): remove dead userinfo check in redirect_uri validation The first check combined missing netloc with userinfo presence, making the second userinfo-only check unreachable. Split into two distinct checks so each error message reflects the actual failure mode. Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai>	2026-05-22 09:00:39 -07:00
harish-berri	d04373f4ce	Add granian as a ASGI compliant web server. Provider better throughput stability, (#26027) ... * Add granian as a ASGI compliant web server. Provides better stability, 10-20 RPS improvement under standard LT conditions. TODO: Verify poetry lock details and add locust numbers to PR * Update granian version in license_cache.json and pyproject.toml to 2.5.7 * Enhance proxy CLI tests by adding SSL initialization checks for Granian server. Remove Python version skip conditions and implement tests to ensure SSL certificate and key are required for server initialization. * update uv lock to fix granian import error	2026-05-21 19:08:37 -07:00
yuneng-jiang	9fcd424318	chore(deps): bump deps (#28528) ... * build(deps): bump next from 16.2.4 to 16.2.6 in /ui/litellm-dashboard (#27665) Bumps [next](https://github.com/vercel/next.js) from 16.2.4 to 16.2.6. - [Release notes](https://github.com/vercel/next.js/releases) - [Changelog](https://github.com/vercel/next.js/blob/canary/release.js) - [Commits](https://github.com/vercel/next.js/compare/v16.2.4...v16.2.6) --- updated-dependencies: - dependency-name: next dependency-version: 16.2.6 dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * build(deps): bump protobufjs in /tests/pass_through_tests (#28296) Bumps [protobufjs](https://github.com/protobufjs/protobuf.js) from 7.5.6 to 7.6.0. - [Release notes](https://github.com/protobufjs/protobuf.js/releases) - [Changelog](https://github.com/protobufjs/protobuf.js/blob/protobufjs-v7.6.0/CHANGELOG.md) - [Commits](https://github.com/protobufjs/protobuf.js/compare/protobufjs-v7.5.6...protobufjs-v7.6.0) --- updated-dependencies: - dependency-name: protobufjs dependency-version: 7.6.0 dependency-type: indirect ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * build(deps): bump ws from 8.20.0 to 8.20.1 in /tests/pass_through_tests (#28303) Bumps [ws](https://github.com/websockets/ws) from 8.20.0 to 8.20.1. - [Release notes](https://github.com/websockets/ws/releases) - [Commits](https://github.com/websockets/ws/compare/8.20.0...8.20.1) --- updated-dependencies: - dependency-name: ws dependency-version: 8.20.1 dependency-type: indirect ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>	2026-05-22 00:42:21 +00:00
yuneng-jiang	2a5dfcd5bc	build(deps-dev): bump black to 26.3.1 and apply formatting (#28525) ... * build(deps-dev): bump black 24.10.0 -> 26.3.1 * style: apply black 26.3.1 formatting * chore: authorize black 26.3.1 license in liccheck.ini	2026-05-21 17:24:18 -07:00