diff --git a/db_scripts/partition_spend_logs.sql b/db_scripts/partition_spend_logs.sql index 4e4a93539d7..c153a67eaec 100644 --- a/db_scripts/partition_spend_logs.sql +++ b/db_scripts/partition_spend_logs.sql @@ -53,6 +53,8 @@ ALTER INDEX IF EXISTS "LiteLLM_SpendLogs_end_user_idx" RENAME TO "LiteLLM_SpendLogs_legacy_end_user_idx"; ALTER INDEX IF EXISTS "LiteLLM_SpendLogs_session_id_idx" RENAME TO "LiteLLM_SpendLogs_legacy_session_id_idx"; +ALTER INDEX IF EXISTS "LiteLLM_SpendLogs_api_key_startTime_idx" + RENAME TO "LiteLLM_SpendLogs_legacy_api_key_startTime_idx"; CREATE TABLE "LiteLLM_SpendLogs" ( LIKE "LiteLLM_SpendLogs_legacy" INCLUDING DEFAULTS INCLUDING GENERATED @@ -78,6 +80,9 @@ CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_end_user_idx" CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_session_id_idx" ON "LiteLLM_SpendLogs" ("session_id"); +CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_api_key_startTime_idx" + ON "LiteLLM_SpendLogs" ("api_key", "startTime"); + -- Safety net: any row whose startTime has no explicit partition lands here so -- writes never fail. The cleanup job never drops the DEFAULT partition. CREATE TABLE IF NOT EXISTS "LiteLLM_SpendLogs_pdefault" diff --git a/db_scripts/unpartition_spend_logs.sql b/db_scripts/unpartition_spend_logs.sql index 0bd82513e4a..2555eca212b 100644 --- a/db_scripts/unpartition_spend_logs.sql +++ b/db_scripts/unpartition_spend_logs.sql @@ -40,6 +40,8 @@ ALTER INDEX IF EXISTS "LiteLLM_SpendLogs_end_user_idx" RENAME TO "LiteLLM_SpendLogs_partitioned_end_user_idx"; ALTER INDEX IF EXISTS "LiteLLM_SpendLogs_session_id_idx" RENAME TO "LiteLLM_SpendLogs_partitioned_session_id_idx"; +ALTER INDEX IF EXISTS "LiteLLM_SpendLogs_api_key_startTime_idx" + RENAME TO "LiteLLM_SpendLogs_partitioned_api_key_startTime_idx"; CREATE TABLE "LiteLLM_SpendLogs" ( LIKE "LiteLLM_SpendLogs_partitioned" INCLUDING DEFAULTS INCLUDING GENERATED @@ -60,6 +62,9 @@ CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_end_user_idx" CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_session_id_idx" ON "LiteLLM_SpendLogs" ("session_id"); +CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_api_key_startTime_idx" + ON "LiteLLM_SpendLogs" ("api_key", "startTime"); + INSERT INTO "LiteLLM_SpendLogs" SELECT * FROM "LiteLLM_SpendLogs_partitioned" ON CONFLICT ("request_id") DO NOTHING; diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260823000000_add_spend_logs_api_key_starttime_index/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260823000000_add_spend_logs_api_key_starttime_index/migration.sql new file mode 100644 index 00000000000..9a061aaed43 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260823000000_add_spend_logs_api_key_starttime_index/migration.sql @@ -0,0 +1,2 @@ +-- CreateIndex +CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_api_key_startTime_idx" ON "LiteLLM_SpendLogs"("api_key", "startTime"); diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma index 139fb031671..c0c528bc743 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma +++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma @@ -678,6 +678,7 @@ model LiteLLM_SpendLogs { @@index([end_user]) @@index([session_id]) @@index([litellm_call_id]) + @@index([api_key, startTime]) } model LiteLLM_BudgetWindowSpend { diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml index 914b9c5a14b..604ffc3abd4 100644 --- a/litellm-proxy-extras/pyproject.toml +++ b/litellm-proxy-extras/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm-proxy-extras" -version = "0.4.98" +version = "0.4.99" description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package." readme = "README.md" requires-python = ">=3.9" @@ -26,7 +26,7 @@ required-version = ">=0.10.9" module-root = "" [tool.commitizen] -version = "0.4.98" +version = "0.4.99" version_files = [ "pyproject.toml:^version", "../pyproject.toml:litellm-proxy-extras==", diff --git a/litellm/caching/dual_cache.py b/litellm/caching/dual_cache.py index 81e2af45686..66be77dbb40 100644 --- a/litellm/caching/dual_cache.py +++ b/litellm/caching/dual_cache.py @@ -521,6 +521,18 @@ class DualCache(BaseCache): if self.redis_cache is not None: await self.redis_cache.async_delete_cache(key) + async def async_delete_cache_keys(self, keys: Sequence[str]) -> None: + """Batch twin of ``async_delete_cache``, chunked because Redis takes the + whole list as one DELETE command.""" + if not keys: + return + for key in keys: + self.in_memory_cache.delete_cache(key) + if self.redis_cache is None: + return + for start in range(0, len(keys), DEFAULT_MAX_REDIS_BATCH_CACHE_SIZE): + await self.redis_cache.delete_cache_keys(keys[start : start + DEFAULT_MAX_REDIS_BATCH_CACHE_SIZE]) + async def async_get_ttl(self, key: str) -> int | None: """ Get the remaining TTL of a key in in-memory cache or redis diff --git a/litellm/constants.py b/litellm/constants.py index 6babf6afae3..b9523921e3d 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -321,6 +321,8 @@ WEBSOCKET_CLOSE_REASON_MAX_BYTES: Final = 123 BEDROCK_REALTIME_PENDING_SESSION_UPDATE_SCOPE_KEY: Final = "litellm.bedrock_realtime.pending_session_update" BEDROCK_REALTIME_SESSION_COMMITTED_SCOPE_KEY: Final = "litellm.bedrock_realtime.session_committed" BEDROCK_REALTIME_COMMITTED_FAILURE_SCOPE_KEY: Final = "litellm.bedrock_realtime.committed_failure" +BEDROCK_REALTIME_SDK_DISTRIBUTION: Final = "aws-sdk-bedrock-runtime" +BEDROCK_REALTIME_SDK_SUPPORTED_RANGE: Final = ">=0.10.0,<0.12.0" CLIENT_REQUESTED_MODEL_SCOPE_KEY: Final = "litellm.client_requested_model" MODEL_GROUP_ALIAS_RESOLVED_SCOPE_KEY: Final = "litellm.model_group_alias_resolved" REALTIME_SESSION_SUCCESS_LOGGED_KEY: Final = "realtime_session_success_logged" diff --git a/litellm/llms/anthropic/chat/guardrail_translation/handler.py b/litellm/llms/anthropic/chat/guardrail_translation/handler.py index 95099924dcf..373435fa4ee 100644 --- a/litellm/llms/anthropic/chat/guardrail_translation/handler.py +++ b/litellm/llms/anthropic/chat/guardrail_translation/handler.py @@ -508,7 +508,8 @@ class AnthropicMessagesHandler(BaseTranslation): chat_completion_compatible_request, _tool_name_mapping, ) = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai( - anthropic_message_request=cast(AnthropicMessagesRequest, data.copy()) + anthropic_message_request=cast(AnthropicMessagesRequest, data.copy()), + preserve_midturn_system=True, ) return chat_completion_compatible_request diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py index ed01d16bd1b..7eb56ae55d3 100644 --- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py +++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py @@ -118,6 +118,10 @@ from litellm.llms.anthropic.common_utils import ( from litellm.llms.anthropic.experimental_pass_through.context_management import ( PolyfillResult, ) +from litellm.llms.anthropic.experimental_pass_through.messages.mid_conversation_system import ( + convert_mid_conversation_system_turns, + is_system_role_message, +) from litellm.llms.anthropic.experimental_pass_through.messages.utils import ( openai_chat_refusal_text, refusal_stop_details, @@ -176,6 +180,7 @@ from litellm.types.llms.openai import ( ToolMessageContentPart, ) from litellm.types.utils import Choices, ModelResponse, StreamingChoices, Usage +from litellm.utils import supports_mid_conversation_system from .streaming_iterator import AnthropicStreamWrapper @@ -186,6 +191,12 @@ if TYPE_CHECKING: ToolResultContent: TypeAlias = str | list[ToolMessageContentPart] +def target_supports_mid_conversation_system(model: str | None, custom_llm_provider: str | None) -> bool: + if not model: + return False + return supports_mid_conversation_system(model=model, custom_llm_provider=custom_llm_provider) + + class AnthropicAdapter: def __init__(self) -> None: pass @@ -418,10 +429,28 @@ class LiteLLMAnthropicMessagesAdapter: self, messages: list[AllAnthropicPassThroughMessageValues], model: str | None = None, + *, + custom_llm_provider: str | None = None, + preserve_midturn_system: bool = False, ) -> list: new_messages: Final[list[AllMessageValues]] = [] replayable_messages: Final = strip_encrypted_reasoning_blocks_from_anthropic_messages(messages) - for m in replayable_messages: + leading_count: Final = next( + (i for i, m in enumerate(replayable_messages) if not is_system_role_message(m)), + len(replayable_messages), + ) + trailing_messages: Final = replayable_messages[leading_count:] + keeps_midturn_system: Final = ( + preserve_midturn_system + or not any(is_system_role_message(m) for m in trailing_messages) + or target_supports_mid_conversation_system(model, custom_llm_provider) + ) + ordered_messages: Final = ( + replayable_messages + if keeps_midturn_system + else (*replayable_messages[:leading_count], *convert_mid_conversation_system_turns(trailing_messages)) + ) + for m in ordered_messages: user_message: ChatCompletionUserMessage | None = None tool_message_list: list[ChatCompletionToolMessage] = [] new_user_content_list: list[ChatCompletionTextObject | ChatCompletionImageObject] = [] @@ -494,7 +523,7 @@ class LiteLLMAnthropicMessagesAdapter: if isinstance(m.get("content"), str): assistant_message_str = str(m.get("content", "")) elif isinstance(m.get("content"), list): - for content in m.get("content", []): + for content in cast(list, m.get("content", [])): # cast-ok: untrusted client payload if isinstance(content, str): assistant_message_str = str(content) elif isinstance(content, dict): @@ -1154,6 +1183,7 @@ class LiteLLMAnthropicMessagesAdapter: anthropic_message_request: AnthropicMessagesRequest, *, custom_llm_provider: str | None = None, + preserve_midturn_system: bool = False, ) -> tuple[ChatCompletionRequest, dict[str, str]]: """ This is used by the beta Anthropic Adapter, for translating anthropic `/v1/messages` requests to the openai format. @@ -1175,6 +1205,8 @@ class LiteLLMAnthropicMessagesAdapter: new_messages = self.translate_anthropic_messages_to_openai( messages=messages_list, model=anthropic_message_request.get("model"), + custom_llm_provider=custom_llm_provider, + preserve_midturn_system=preserve_midturn_system, ) ## ADD SYSTEM MESSAGE TO MESSAGES self._add_system_message_to_messages(new_messages, anthropic_message_request) diff --git a/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py b/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py index ecaf8f2e7e1..ebd0342b10c 100644 --- a/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py +++ b/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py @@ -765,7 +765,8 @@ def _count_effective_tokens( messages=cast( "list[AllAnthropicPassThroughMessageValues]", messages_without_compaction, - ) + ), + preserve_midturn_system=True, ) except Exception as e: verbose_logger.debug( @@ -920,7 +921,8 @@ def _build_summary_messages( messages=cast( "list[AllAnthropicPassThroughMessageValues]", stripped, - ) + ), + preserve_midturn_system=True, ) except Exception as e: verbose_logger.warning( diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/mid_conversation_system.py b/litellm/llms/anthropic/experimental_pass_through/messages/mid_conversation_system.py new file mode 100644 index 00000000000..ddefec6bac9 --- /dev/null +++ b/litellm/llms/anthropic/experimental_pass_through/messages/mid_conversation_system.py @@ -0,0 +1,77 @@ +from collections.abc import Mapping, Sequence +from itertools import groupby +from typing import Final + +CONVERTED_SYSTEM_NOTE: Final = ( + "Operator note (not from the user): the following was originally a mid-conversation system-role reminder." +) + + +def as_system_content_blocks(value: object) -> list[object]: + if value is None: + return [] + if isinstance(value, list): + return list(value) + if isinstance(value, str): + return [{"type": "text", "text": value}] + return [value] + + +def is_system_role_message(message: object) -> bool: + return isinstance(message, dict) and message.get("role") == "system" + + +def system_role_message_as_user(message: Mapping[str, object]) -> Mapping[str, object]: + return { + "role": "user", + "content": as_system_content_blocks(CONVERTED_SYSTEM_NOTE) + as_system_content_blocks(message.get("content")), + } + + +def opens_with_tool_results(message: object) -> bool: + if not isinstance(message, dict) or message.get("role") != "user": + return False + content: Final = message.get("content") + return ( + isinstance(content, list) + and len(content) > 0 + and isinstance(content[0], dict) + and content[0].get("type") == "tool_result" + ) + + +def system_run_placed_after_tool_results( + system_run: Sequence[Mapping[str, object]], follower_run: Sequence[Mapping[str, object]] +) -> tuple[Mapping[str, object], ...]: + if follower_run and opens_with_tool_results(follower_run[0]): + return (follower_run[0], *system_run, *follower_run[1:]) + return (*system_run, *follower_run) + + +def system_turns_after_tool_results( + messages: Sequence[Mapping[str, object]], +) -> tuple[Mapping[str, object], ...]: + runs: Final = tuple(tuple(run) for _, run in groupby(messages, key=is_system_role_message)) + if not runs: + return () + first_system_run: Final = 0 if is_system_role_message(runs[0][0]) else 1 + paired_runs: Final = tuple( + (runs[i], runs[i + 1] if i + 1 < len(runs) else ()) for i in range(first_system_run, len(runs), 2) + ) + return ( + *(runs[0] if first_system_run else ()), + *( + m + for system_run, follower_run in paired_runs + for m in system_run_placed_after_tool_results(system_run, follower_run) + ), + ) + + +def convert_mid_conversation_system_turns( + messages: Sequence[Mapping[str, object]], +) -> tuple[Mapping[str, object], ...]: + return tuple( + system_role_message_as_user(m) if is_system_role_message(m) else m + for m in system_turns_after_tool_results(messages) + ) diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py index 27cdac34116..5fa686b7560 100644 --- a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py +++ b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py @@ -27,6 +27,11 @@ from ...common_utils import ( strip_advisor_blocks_from_messages, strip_encrypted_reasoning_blocks_from_anthropic_messages, ) +from .mid_conversation_system import ( + as_system_content_blocks, + convert_mid_conversation_system_turns, + is_system_role_message, +) DEFAULT_ANTHROPIC_API_VERSION: Final = "2023-06-01" @@ -151,73 +156,6 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig): else: return system_param - @staticmethod - def _as_system_content_blocks(value: object) -> list: - if value is None: - return [] - if isinstance(value, list): - return list(value) - if isinstance(value, str): - return [{"type": "text", "text": value}] - return [value] - - @staticmethod - def _is_system_role_message(message: object) -> bool: - return isinstance(message, dict) and message.get("role") == "system" - - _CONVERTED_SYSTEM_NOTE: Final = ( - "Operator note (not from the user): the following was originally a mid-conversation system-role reminder." - ) - - def _system_role_message_as_user(self, message: Mapping) -> Mapping: - return { - "role": "user", - "content": self._as_system_content_blocks(self._CONVERTED_SYSTEM_NOTE) - + self._as_system_content_blocks(message.get("content")), - } - - @staticmethod - def _opens_with_tool_results(message: object) -> bool: - if not isinstance(message, dict) or message.get("role") != "user": - return False - content: Final = message.get("content") - return ( - isinstance(content, list) - and len(content) > 0 - and isinstance(content[0], dict) - and content[0].get("type") == "tool_result" - ) - - def _system_run_before(self, messages: Sequence, index: int) -> Sequence: - start: Final = next( - (j + 1 for j in range(index - 1, -1, -1) if not self._is_system_role_message(messages[j])), - 0, - ) - return messages[start:index] - - def _system_run_end(self, messages: Sequence, index: int) -> int: - return next( - (j for j in range(index, len(messages)) if not self._is_system_role_message(messages[j])), - len(messages), - ) - - def _reordered_around_tool_results(self, messages: Sequence, index: int) -> tuple: - message: Final = messages[index] - if self._opens_with_tool_results(message): - return (message, *self._system_run_before(messages, index)) - if not self._is_system_role_message(message): - return (message,) - run_end: Final = self._system_run_end(messages, index) - follower: Final = messages[run_end] if run_end < len(messages) else None - return () if self._opens_with_tool_results(follower) else (message,) - - def _system_turns_after_tool_results(self, messages: Sequence) -> tuple: - return tuple( - message - for index in range(len(messages)) - for message in self._reordered_around_tool_results(messages, index) - ) - def _normalize_system_role_messages(self, anthropic_messages_request: dict, model: str) -> None: """Normalize ``role: "system"`` entries in ``messages`` per the Anthropic ``/v1/messages`` contract, which the first-party API, Bedrock Invoke, @@ -254,7 +192,7 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig): if not isinstance(messages, list): return leading_count: Final = next( - (i for i, m in enumerate(messages) if not self._is_system_role_message(m)), + (i for i, m in enumerate(messages) if not is_system_role_message(m)), len(messages), ) hoisted: Final = messages[:leading_count] @@ -265,10 +203,7 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig): custom_llm_provider=self.custom_llm_provider, key="supports_mid_conversation_system", ) - else [ - self._system_role_message_as_user(m) if self._is_system_role_message(m) else m - for m in self._system_turns_after_tool_results(messages[leading_count:]) - ] + else list(convert_mid_conversation_system_turns(messages[leading_count:])) ) if hoisted or remaining != messages: anthropic_messages_request["messages"] = remaining @@ -278,7 +213,7 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig): anthropic_messages_request.get("system"), *(m.get("content") for m in hoisted), ) - for block in self._as_system_content_blocks(source) + for block in as_system_content_blocks(source) ] filtered_system: Final = self._filter_billing_headers_from_system(system_content) if filtered_system: diff --git a/litellm/llms/bedrock/realtime/handler.py b/litellm/llms/bedrock/realtime/handler.py index 2c1ce6068b2..fe3822629a7 100644 --- a/litellm/llms/bedrock/realtime/handler.py +++ b/litellm/llms/bedrock/realtime/handler.py @@ -6,11 +6,12 @@ This uses aws_sdk_bedrock_runtime for bidirectional streaming with Nova Sonic. import asyncio import contextlib +import importlib.metadata import json -from collections.abc import AsyncIterator, Mapping, MutableMapping +from collections.abc import AsyncIterator, Awaitable, Callable, Mapping, MutableMapping from dataclasses import dataclass from types import MappingProxyType -from typing import Final, NoReturn, Protocol +from typing import Final, NoReturn, Protocol, runtime_checkable from pydantic import JsonValue, TypeAdapter @@ -19,6 +20,8 @@ from litellm._logging import _redact_string, verbose_proxy_logger from litellm.constants import ( BEDROCK_REALTIME_COMMITTED_FAILURE_SCOPE_KEY, BEDROCK_REALTIME_PENDING_SESSION_UPDATE_SCOPE_KEY, + BEDROCK_REALTIME_SDK_DISTRIBUTION, + BEDROCK_REALTIME_SDK_SUPPORTED_RANGE, BEDROCK_REALTIME_SESSION_COMMITTED_SCOPE_KEY, REALTIME_SESSION_SUCCESS_LOGGED_KEY, ) @@ -121,6 +124,38 @@ class BedrockBidirectionalStream(Protocol): async def await_output(self) -> tuple[object, BedrockOutputStream]: ... +@runtime_checkable +class ClosableBedrockRuntimeClient(Protocol): + async def close(self) -> None: ... + + +def _installed_sdk_version() -> str | None: + try: + return importlib.metadata.version(BEDROCK_REALTIME_SDK_DISTRIBUTION) + except importlib.metadata.PackageNotFoundError: + return None + + +def _sdk_import_error(installed_version: str | None, cause: ImportError) -> ImportError: + install_hint: Final = "pip install 'litellm[bedrock-realtime]'" + requirement: Final = f"{BEDROCK_REALTIME_SDK_DISTRIBUTION}[awscrt]{BEDROCK_REALTIME_SDK_SUPPORTED_RANGE}" + verbose_proxy_logger.error("Bedrock Realtime: SDK import failed (installed=%s): %s", installed_version, cause) + if installed_version is None: + return ImportError(f"Missing aws_sdk_bedrock_runtime: {install_hint} ({requirement})") + return ImportError( + f"{BEDROCK_REALTIME_SDK_DISTRIBUTION} {installed_version} is installed but Bedrock realtime needs " + f"[awscrt]{BEDROCK_REALTIME_SDK_SUPPORTED_RANGE}: {install_hint}" + ) + + +async def _close_bedrock_client(bedrock_client: object) -> None: + if not isinstance(bedrock_client, ClosableBedrockRuntimeClient): + return + with contextlib.suppress(Exception): + await bedrock_client.close() + verbose_proxy_logger.debug("Bedrock Realtime: closed SDK client") + + @dataclass(frozen=True, slots=True) class _BridgeOutcome: logged_events: tuple[OpenAIRealtimeEvents, ...] @@ -199,8 +234,9 @@ async def _ack_session_update( class BedrockRealtime(BaseAWSLLM): """Handler for Bedrock Nova Sonic realtime speech-to-speech API.""" - def __init__(self): + def __init__(self, sdk_version_lookup: Callable[[], str | None] = _installed_sdk_version): super().__init__() + self._sdk_version_lookup: Final = sdk_version_lookup async def async_realtime( self, @@ -234,14 +270,13 @@ class BedrockRealtime(BaseAWSLLM): Various AWS authentication parameters """ try: - from aws_sdk_bedrock_runtime.client import ( - BedrockRuntimeClient, - InvokeModelWithBidirectionalStreamOperationInput, - ) - from aws_sdk_bedrock_runtime.config import Config - from smithy_aws_core.identity import StaticCredentialsResolver - except ImportError: - raise ImportError("Missing aws_sdk_bedrock_runtime. Install with: pip install aws-sdk-bedrock-runtime") + from aws_sdk_bedrock_runtime.client import AsyncBedrockRuntimeClient + from aws_sdk_bedrock_runtime.config import AsyncBedrockRuntimeConfig + from aws_sdk_bedrock_runtime.models import InvokeModelWithBidirectionalStreamOperationInput + from smithy_aws_core.identity import AWSCredentialsIdentity, StaticCredentialsResolver + from smithy_http.aio.crt import AWSCRTHTTPClient + except ImportError as e: + raise _sdk_import_error(self._sdk_version_lookup(), e) from e pending_session_update: Final = _pending_session_update(websocket.scope) @@ -285,22 +320,37 @@ class BedrockRealtime(BaseAWSLLM): ) frozen_credentials: Final = await run_aws_signing(credentials.get_frozen_credentials) - # Initialize Bedrock client with aws_sdk_bedrock_runtime - config: Final = Config( + credentials_identity: Final = AWSCredentialsIdentity( + access_key_id=frozen_credentials.access_key, + secret_access_key=frozen_credentials.secret_key, + session_token=frozen_credentials.token, + ) + config: Final = await AsyncBedrockRuntimeConfig.resolve( endpoint_uri=endpoint_uri, region=aws_region_name, - aws_access_key_id=frozen_credentials.access_key, - aws_secret_access_key=frozen_credentials.secret_key, - aws_session_token=frozen_credentials.token, - aws_credentials_identity_resolver=StaticCredentialsResolver(), + aws_credentials_identity_resolver=StaticCredentialsResolver(identity=credentials_identity), + transport=AWSCRTHTTPClient(), ) - bedrock_client: Final = BedrockRuntimeClient(config=config) + bedrock_client: Final = AsyncBedrockRuntimeClient(config=config) async def open_bidirectional_stream() -> BedrockBidirectionalStream: return await bedrock_client.invoke_model_with_bidirectional_stream( InvokeModelWithBidirectionalStreamOperationInput(model_id=model) ) + try: + await self._run_session(websocket, open_bidirectional_stream, model, logging_obj, pending_session_update) + finally: + await _close_bedrock_client(bedrock_client) + + async def _run_session( + self, + websocket: RealtimeClientWebSocket, + open_bidirectional_stream: Callable[[], Awaitable[BedrockBidirectionalStream]], + model: str, + logging_obj: LiteLLMLogging, + pending_session_update: str | None, + ) -> None: transformation_config: Final = BedrockRealtimeConfig() bedrock_stream: Final = await open_bidirectional_stream() diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index c565b6ecc4b..96cdbcffd90 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -7605,7 +7605,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -7733,7 +7733,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -7887,7 +7887,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/gpt-6-astra": { "cache_creation_input_token_cost": 1.25e-05, @@ -7956,7 +7956,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -8856,7 +8856,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -8955,7 +8955,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -9054,7 +9054,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/gpt-5.5-pro": { "cache_read_input_token_cost": 3e-06, @@ -10987,14 +10987,14 @@ "supports_vision": true }, "azure_ai/FW-Kimi-K3": { - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.5e-05, "reasoning_effort_levels": [ "low", "high", @@ -23788,7 +23788,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": false }, "fireworks_ai/accounts/fireworks/models/mixtral-8x22b-instruct-hf": { "input_cost_per_token": 1.2e-06, @@ -24114,7 +24114,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": false }, "fireworks_ai/qwen3p7-plus": { "cache_read_input_token_cost": 8e-08, @@ -45245,7 +45245,7 @@ "supports_tool_choice": true }, "together_ai/openai/gpt-oss-20b": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "input_cost_per_token": 5e-08, "litellm_provider": "together_ai", "max_input_tokens": 131072, @@ -45482,6 +45482,7 @@ }, "together_ai/deepseek-ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 3e-08, + "deprecation_date": "2026-09-29", "input_cost_per_token": 1.4e-07, "litellm_provider": "together_ai", "max_input_tokens": 1048576, @@ -45503,7 +45504,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://api.together.xyz/v1/models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_response_schema": true, @@ -45528,6 +45529,7 @@ }, "together_ai/deepseek-ai/DeepSeek-V4-Pro-0813": { "cache_read_input_token_cost": 1.3e-07, + "deprecation_date": "2026-09-29", "input_cost_per_token": 1.32e-06, "litellm_provider": "together_ai", "max_input_tokens": 1048576, @@ -45552,7 +45554,7 @@ "source": "https://docs.together.ai/docs/serverless-models" }, "together_ai/google/gemma-4-31B-it": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "input_cost_per_token": 3.9e-07, "litellm_provider": "together_ai", "max_input_tokens": 262144, @@ -45567,7 +45569,7 @@ "supports_vision": true }, "together_ai/intfloat/multilingual-e5-large-instruct": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "input_cost_per_token": 2e-08, "litellm_provider": "together_ai", "max_input_tokens": 514, @@ -45680,7 +45682,7 @@ "supports_tool_choice": true }, "together_ai/thinkingmachines/Inkling-Small": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 5e-07, "litellm_provider": "together_ai", @@ -50573,7 +50575,7 @@ "wandb/openai/gpt-oss-120b": { "supports_reasoning": true, "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "max_output_tokens": 131072, "input_cost_per_token": 3e-08, "output_cost_per_token": 1.7e-07, @@ -50584,7 +50586,7 @@ "wandb/openai/gpt-oss-20b": { "supports_reasoning": true, "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "max_output_tokens": 131072, "input_cost_per_token": 3e-08, "output_cost_per_token": 1.3e-07, @@ -50593,6 +50595,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/zai-org/GLM-4.5": { + "deprecation_date": "2026-03-04", "supports_reasoning": true, "max_tokens": 131072, "max_input_tokens": 131072, @@ -50603,6 +50606,7 @@ "mode": "chat" }, "wandb/Qwen/Qwen3-235B-A22B-Instruct-2507": { + "deprecation_date": "2026-08-04", "max_tokens": 262144, "max_input_tokens": 262144, "max_output_tokens": 262144, @@ -50612,6 +50616,7 @@ "mode": "chat" }, "wandb/Qwen/Qwen3-Coder-480B-A35B-Instruct": { + "deprecation_date": "2026-08-25", "max_tokens": 262144, "max_input_tokens": 262144, "max_output_tokens": 262144, @@ -50622,6 +50627,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/Qwen/Qwen3-235B-A22B-Thinking-2507": { + "deprecation_date": "2026-08-04", "supports_reasoning": true, "max_tokens": 262144, "max_input_tokens": 262144, @@ -50632,6 +50638,7 @@ "mode": "chat" }, "wandb/moonshotai/Kimi-K2-Instruct": { + "deprecation_date": "2026-03-04", "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, @@ -50656,6 +50663,7 @@ "supports_vision": true }, "wandb/MiniMaxAI/MiniMax-M2.5": { + "deprecation_date": "2026-08-25", "max_tokens": 197000, "max_input_tokens": 197000, "max_output_tokens": 197000, @@ -50670,7 +50678,7 @@ }, "wandb/meta-llama/Llama-3.1-8B-Instruct": { "max_tokens": 128000, - "max_input_tokens": 128000, + "max_input_tokens": 131000, "max_output_tokens": 128000, "input_cost_per_token": 2.2e-07, "output_cost_per_token": 2.2e-07, @@ -50690,6 +50698,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/deepseek-ai/DeepSeek-R1-0528": { + "deprecation_date": "2026-03-04", "supports_reasoning": true, "max_tokens": 161000, "max_input_tokens": 161000, @@ -50700,6 +50709,7 @@ "mode": "chat" }, "wandb/deepseek-ai/DeepSeek-V3-0324": { + "deprecation_date": "2026-03-04", "max_tokens": 161000, "max_input_tokens": 161000, "max_output_tokens": 161000, @@ -50719,6 +50729,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/meta-llama/Llama-4-Scout-17B-16E-Instruct": { + "deprecation_date": "2026-04-21", "max_tokens": 64000, "max_input_tokens": 64000, "max_output_tokens": 64000, @@ -50728,6 +50739,7 @@ "mode": "chat" }, "wandb/microsoft/Phi-4-mini-instruct": { + "deprecation_date": "2026-08-04", "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, @@ -56692,7 +56704,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_web_search": true, - "gemini_audio_only_live": true + "gemini_audio_only_live": true, + "supports_response_schema": false }, "gemini-3.8-live-extended-thinking": { "input_cost_per_audio_token": 3e-06, @@ -56726,7 +56739,8 @@ "supports_vision": true, "supports_web_search": true, "gemini_audio_only_live": true, - "supports_reasoning": true + "supports_reasoning": true, + "supports_response_schema": false }, "gemini/gemini-2.5-flash-native-audio-latest": { "input_cost_per_audio_token": 3e-06, @@ -60970,10 +60984,11 @@ "wandb/deepseek-ai/DeepSeek-V4-Flash": { "supports_reasoning": true, "max_tokens": 1048576, - "max_input_tokens": 1048576, + "max_input_tokens": 1049000, "input_cost_per_token": 1.4e-07, "output_cost_per_token": 2.8e-07, "cache_read_input_token_cost": 7e-08, + "deprecation_date": "2026-10-05", "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -60983,7 +60998,7 @@ "wandb/deepseek-ai/DeepSeek-V4-Flash-0731": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 1.3e-07, "output_cost_per_token": 2.8e-07, "cache_read_input_token_cost": 7e-08, @@ -60996,10 +61011,11 @@ "wandb/deepseek-ai/DeepSeek-V4-Pro": { "supports_reasoning": true, "max_tokens": 1048576, - "max_input_tokens": 1048576, + "max_input_tokens": 1049000, "input_cost_per_token": 1.15e-06, "output_cost_per_token": 2.55e-06, "cache_read_input_token_cost": 2e-07, + "deprecation_date": "2026-10-05", "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61009,7 +61025,7 @@ "wandb/google/gemma-4-31B-it": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 1e-07, "output_cost_per_token": 3.4e-07, "litellm_provider": "wandb", @@ -61018,8 +61034,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/ibm-granite/granite-4.1-8b": { + "deprecation_date": "2026-10-05", "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "input_cost_per_token": 5e-08, "output_cost_per_token": 1e-07, "litellm_provider": "wandb", @@ -61028,8 +61045,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/JetBrains/Mellum2-12B-A2.5B-Instruct": { + "deprecation_date": "2026-10-05", "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "input_cost_per_token": 5e-08, "output_cost_per_token": 1e-07, "litellm_provider": "wandb", @@ -61038,8 +61056,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/meta-llama/Llama-3.1-70B-Instruct": { + "deprecation_date": "2026-10-05", "max_tokens": 128000, - "max_input_tokens": 128000, + "max_input_tokens": 131000, "input_cost_per_token": 8e-07, "output_cost_per_token": 8e-07, "litellm_provider": "wandb", @@ -61050,7 +61069,7 @@ "wandb/MiniMaxAI/MiniMax-M3": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 2.3e-07, "output_cost_per_token": 9.6e-07, "cache_read_input_token_cost": 5e-08, @@ -61063,7 +61082,7 @@ "wandb/moonshotai/Kimi-K2.7-Code": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 7.1e-07, "output_cost_per_token": 3.5e-06, "cache_read_input_token_cost": 1.5e-07, @@ -61076,7 +61095,7 @@ "wandb/moonshotai/Kimi-K2.6": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 6.5e-07, "output_cost_per_token": 3.41e-06, "cache_read_input_token_cost": 1.5e-07, @@ -61089,10 +61108,10 @@ "wandb/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, - "input_cost_per_token": 1e-07, - "output_cost_per_token": 2.5e-07, - "cache_read_input_token_cost": 5e-08, + "max_input_tokens": 262000, + "input_cost_per_token": 7e-08, + "output_cost_per_token": 2e-07, + "cache_read_input_token_cost": 4e-08, "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61102,10 +61121,10 @@ "wandb/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, - "input_cost_per_token": 7.5e-07, - "output_cost_per_token": 2.75e-06, - "cache_read_input_token_cost": 1.5e-07, + "max_input_tokens": 262000, + "input_cost_per_token": 5e-07, + "output_cost_per_token": 2.15e-06, + "cache_read_input_token_cost": 1e-07, "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61113,8 +61132,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/OpenPipe/Qwen3-14B-Instruct": { + "deprecation_date": "2026-10-05", "max_tokens": 32768, - "max_input_tokens": 32768, + "max_input_tokens": 32800, "input_cost_per_token": 5e-08, "output_cost_per_token": 2.2e-07, "litellm_provider": "wandb", @@ -61125,7 +61145,7 @@ "wandb/Qwen/Qwen3.8-27B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 4e-07, "output_cost_per_token": 3e-06, "cache_read_input_token_cost": 1.5e-07, @@ -61138,7 +61158,7 @@ "wandb/Qwen/Qwen3.6-35B-A3B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 2.5e-07, "output_cost_per_token": 1.25e-06, "litellm_provider": "wandb", @@ -61149,10 +61169,11 @@ "wandb/Qwen/Qwen3.6-27B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 6e-07, "output_cost_per_token": 3.6e-06, "cache_read_input_token_cost": 1.2e-07, + "deprecation_date": "2026-10-05", "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61160,9 +61181,10 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/Qwen/Qwen3.5-35B-A3B": { + "deprecation_date": "2026-10-05", "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 2.5e-07, "output_cost_per_token": 1.25e-06, "litellm_provider": "wandb", @@ -61171,8 +61193,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/Qwen/Qwen3-30B-A3B-Instruct-2507": { + "deprecation_date": "2026-10-05", "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 1e-07, "output_cost_per_token": 3e-07, "litellm_provider": "wandb", @@ -61187,6 +61210,7 @@ "input_cost_per_token": 1.31e-06, "output_cost_per_token": 3.96e-06, "cache_read_input_token_cost": 4.4e-08, + "max_input_tokens": 1049000, "supports_prompt_caching": true, "source": "https://wandb.ai/site/pricing/tokens/" }, @@ -61197,13 +61221,14 @@ "input_cost_per_token": 1e-07, "output_cost_per_token": 1.5e-07, "cache_read_input_token_cost": 5e-08, + "max_input_tokens": 131000, "supports_prompt_caching": true, "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/zai-org/GLM-5.2": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 1049000, "input_cost_per_token": 7.6e-07, "output_cost_per_token": 2.42e-06, "cache_read_input_token_cost": 1.4e-07, @@ -62866,7 +62891,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 6.6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -69158,5 +69183,19 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_vision": true + }, + "wandb/zai-org/GLM-5.3-Flash": { + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "wandb", + "max_input_tokens": 1049000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://wandb.ai/site/pricing/tokens/", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true } } diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py index 2f39e6c71bc..f650b6d0b28 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -1937,6 +1937,14 @@ class ProxyBaseLLMRequestProcessing: ) -> tuple[dict, LiteLLMLoggingObj]: start_time: Final = datetime.now() # start before calling guardrail hooks + requested_model: Final = self.data.get("model") + if requested_model is not None and not isinstance(requested_model, str): + raise ProxyException( + message="'model' must be a string.", + type=ProxyErrorTypes.bad_request_error, + param="model", + code=status.HTTP_400_BAD_REQUEST, + ) self.data = await add_litellm_data_to_request( data=self.data, request=request, diff --git a/litellm/proxy/common_utils/reset_budget_job.py b/litellm/proxy/common_utils/reset_budget_job.py index acb51e73daf..1299a4df243 100644 --- a/litellm/proxy/common_utils/reset_budget_job.py +++ b/litellm/proxy/common_utils/reset_budget_job.py @@ -26,7 +26,6 @@ from litellm.litellm_core_utils.duration_parser import duration_in_seconds from litellm.proxy._types import ( DB_RETRY_SAFE_ERROR_TYPES, LiteLLM_BudgetTableFull, - LiteLLM_EndUserTable, Litellm_EntityType, LiteLLM_TeamTable, LiteLLM_UserTable, @@ -193,13 +192,6 @@ def _enduser_cache_keys(row: _EndUserRow) -> tuple[str, ...]: return (end_user_cache_key(row.user_id),) -def _enduser_carried_spend(row: _EndUserRow, caps: Mapping[str, float]) -> float: - if not caps: - return 0.0 - effective_budget_id: Final[str | None] = row.budget_id or litellm.max_end_user_budget_id - return _carried_spend(row.spend, caps.get(effective_budget_id) if effective_budget_id is not None else None) - - def _budget_link_where( budget_ids: Sequence[str], extra: Mapping[str, object] = MappingProxyType({}), @@ -207,6 +199,19 @@ def _budget_link_where( return {"budget_id": {"in": list(budget_ids)}, **extra} +def _enduser_invalidation_where(budget_ids: Sequence[str]) -> dict[str, object]: + """Customers whose cached spend a committed reset of these tiers invalidated. + + Mirrors ``_queue_enduser_resets`` without its ``spend > 0`` filter, which + post-commit would match nobody. + """ + linked: Final = _budget_link_where(budget_ids) + default_budget_id: Final = litellm.max_end_user_budget_id + if default_budget_id is None or default_budget_id not in budget_ids: + return linked + return {"OR": [linked, {"budget_id": None}]} # mutable-ok: prisma where filter must be a dict + + def _queue_budget_linked_resets( writes: LinkedSpendResetWrites, cascade: "_BudgetCascade", @@ -265,16 +270,29 @@ class _BudgetCascade: budgets: tuple[LiteLLM_BudgetTableFull, ...] = () budget_ids: tuple[str, ...] = () budget_resets: tuple[tuple[str, datetime], ...] = () - endusers: tuple[_EndUserRow, ...] = () counter_resets: tuple[tuple[str, float], ...] = () cache_keys: tuple[str, ...] = () rollover_caps: Mapping[str, float] = field(default_factory=lambda: MappingProxyType({})) +@dataclass(frozen=True, slots=True) +class _EndUserWalk: + """Where the customer walk stands. ``cursor`` is None once it is done, and + ``truncated`` says a failed page read cut it short of the tail.""" + + cursor: str | None = "" + invalidated: int = 0 + truncated: bool = False + + +_ENDUSER_WALK_DONE: Final = _EndUserWalk(cursor=None) + + @dataclass(frozen=True, slots=True) class _BudgetCascadeCommitted: cascade: _BudgetCascade advanced: int + endusers: _EndUserWalk @dataclass(frozen=True, slots=True) @@ -285,6 +303,8 @@ class _BudgetCascadeFailed: _EMPTY_CASCADE: Final = _BudgetCascade() +_InvalidatedCache = Literal["spend counter", "user_api_key_cache"] + @dataclass(frozen=True, slots=True) class _ChunkOutcome: @@ -416,10 +436,12 @@ _WINDOW_SOURCES: Final[tuple[_WindowSource, ...]] = ( ) -def _budget_cascade_event_metadata(cascade: _BudgetCascade) -> dict[str, object]: +def _budget_cascade_event_metadata( + cascade: _BudgetCascade, endusers: _EndUserWalk = _ENDUSER_WALK_DONE +) -> dict[str, object]: return { "num_budgets_found": len(cascade.budgets), - "num_endusers_found": len(cascade.endusers), + "num_endusers_found": endusers.invalidated, } @@ -593,6 +615,38 @@ class ResetBudgetJob: e, ) + @staticmethod + async def _invalidate_caches(counter_keys: Sequence[str], cache_keys: Sequence[str]) -> None: + """Batch twin of ``_invalidate_spend_counter`` and + ``_invalidate_user_api_key_cache_entry``, after the commit like both: + one round trip per chunk where a tier's dependents are unbounded.""" + await ResetBudgetJob._invalidate_cache("spend counter", counter_keys) + await ResetBudgetJob._invalidate_cache("user_api_key_cache", cache_keys) + + @staticmethod + async def _invalidate_cache(cache: _InvalidatedCache, keys: Sequence[str]) -> None: + """One cache's share of a batch, awaited separately so either failing + still leaves the other invalidated.""" + if not keys: + return + try: + from litellm.proxy.proxy_server import spend_counter_cache, user_api_key_cache + + match cache: + case "spend counter": + await spend_counter_cache.async_delete_cache_keys(keys) + case "user_api_key_cache": + await user_api_key_cache.async_delete_cache_keys(keys) + case _: + assert_never(cache) + except Exception as e: + verbose_proxy_logger.warning( + "Failed to invalidate %d %s entries: %s. Budgets may be over-enforced until they expire.", + len(keys), + cache, + e, + ) + async def _fetch_linked_rows( self, table: SpendLinkedTable[_RowT], @@ -612,18 +666,57 @@ class ResetBudgetJob: verbose_proxy_logger.warning("Failed to fetch %s for counter invalidation: %s", log_subject, e) return () - async def _collect_endusers_to_reset(self, budget_ids: Sequence[str]) -> tuple[_EndUserRow, ...]: - linked: Final[Sequence[_EndUserRow] | None] = await self._with_db_retry( - lambda: self.prisma_client.get_data( - table_name="enduser", - query_type="find_all", - budget_id_list=list(budget_ids), - ), - reason="reset_budget_read_endusers_failure", + async def _invalidate_enduser_caches(self, budget_ids: Sequence[str]) -> _EndUserWalk: + """Drop the cached spend of every customer the committed tier reset zeroed. + + Paged like ``_reset_windows_for``, and capless for its reason too: the + customers on one tier are unbounded, and a cap cannot keep its position + across pod elections, so it would restart at the first customer forever. + """ + if not budget_ids: + return _ENDUSER_WALK_DONE + where: Final = _enduser_invalidation_where(budget_ids) + walk = _EndUserWalk() + while walk.cursor is not None: + walk = await self._invalidate_enduser_page(where=where, cursor=walk.cursor, reached=walk.invalidated) + return walk + + async def _invalidate_enduser_page(self, where: Mapping[str, object], cursor: str, reached: int) -> _EndUserWalk: + """Invalidate one page of customers and say where the walk goes next.""" + try: + rows: Final = await self._fetch_enduser_page(where=where, cursor=cursor) + except Exception as e: + verbose_proxy_logger.warning( + "Failed to fetch end users for cache invalidation after %s customers (cursor %r): %s. " + "The customers past that page keep their cached spend until it expires.", + reached, + cursor, + e, + ) + return _EndUserWalk(cursor=None, invalidated=reached, truncated=True) + if not rows: + return _EndUserWalk(cursor=None, invalidated=reached) + await self._invalidate_caches( + counter_keys=tuple(_enduser_counter_key(row) for row in rows), + cache_keys=tuple(key for row in rows for key in _enduser_cache_keys(row)), + ) + walked: Final = reached + len(rows) + if len(rows) < RESET_BUDGET_JOB_BATCH_SIZE: + return _EndUserWalk(cursor=None, invalidated=walked) + return _EndUserWalk(cursor=rows[-1].user_id, invalidated=walked) + + async def _fetch_enduser_page(self, where: Mapping[str, object], cursor: str) -> tuple[_EndUserRow, ...]: + """One keyset page of customers, ordered by primary key so the cursor never repeats a row.""" + return tuple( + await self._with_db_retry( + lambda: EndUserRepository(self.prisma_client).table.find_many( + where={**where, "user_id": {"gt": cursor}}, # mutable-ok: prisma where filter must be a dict + order={"user_id": "asc"}, # mutable-ok: prisma order filter must be a dict + take=RESET_BUDGET_JOB_BATCH_SIZE, + ), + reason="reset_budget_read_endusers_failure", + ) ) - if litellm.max_end_user_budget_id is None or litellm.max_end_user_budget_id not in budget_ids: - return tuple(linked or ()) - return (*(linked or ()), *await self._get_endusers_with_no_budget_id()) async def _collect_budget_cascade(self, budgets_to_reset: Sequence[LiteLLM_BudgetTableFull]) -> _BudgetCascade: """Resolve every row the expiring budget tiers gate, before any write. @@ -670,7 +763,6 @@ class ResetBudgetJob: if _rollover_enabled() else {} # mutable-ok: empty sentinel immediately frozen by MappingProxyType ) - endusers: Final[tuple[_EndUserRow, ...]] = await self._collect_endusers_to_reset(budget_ids) return _BudgetCascade( budgets=tuple(budgets_to_reset), budget_ids=budget_ids, @@ -682,7 +774,6 @@ class ResetBudgetJob: for b in budgets_to_reset if b.budget_id is not None and b.budget_duration is not None ), - endusers=endusers, counter_resets=( *( (_team_membership_counter_key(row), _row_carried_spend(row, rollover_caps)) @@ -695,7 +786,6 @@ class ResetBudgetJob: (_model_access_group_counter_key(row), _row_carried_spend(row, rollover_caps)) for row in model_access_groups ), - *((_enduser_counter_key(row), _enduser_carried_spend(row, rollover_caps)) for row in endusers), ), rollover_caps=rollover_caps, cache_keys=( @@ -704,7 +794,6 @@ class ResetBudgetJob: *(key for row in orgs for key in _org_cache_keys(row)), *(key for row in tags for key in _tag_cache_keys(row)), *(key for row in model_access_groups for key in _model_access_group_cache_keys(row)), - *(key for row in endusers for key in _enduser_cache_keys(row)), ), ) @@ -736,10 +825,10 @@ class ResetBudgetJob: uow.budgets.queue_window_advance(budget_id=budget_id, budget_reset_at=budget_reset_at) async def _invalidate_budget_cascade_caches(self, cascade: _BudgetCascade) -> None: - for counter_key, _ in cascade.counter_resets: - await self._invalidate_spend_counter(counter_key) - for cache_key in cascade.cache_keys: - await self._invalidate_user_api_key_cache_entry(cache_key) + await self._invalidate_caches( + counter_keys=tuple(counter_key for counter_key, _ in cascade.counter_resets), + cache_keys=cascade.cache_keys, + ) async def _reset_expired_budget_cascade(self) -> _BudgetCascadeCommitted | _BudgetCascadeFailed: now: Final = datetime.now(timezone.utc) @@ -769,6 +858,7 @@ class ResetBudgetJob: (reset_at for _, reset_at in cascade.budget_resets), cutoff=datetime.now(timezone.utc), ), + endusers=await self._invalidate_enduser_caches(cascade.budget_ids), ) async def reset_budget_for_litellm_budget_table(self) -> None: @@ -788,7 +878,7 @@ class ResetBudgetJob: end_time: Final = time.time() match outcome: - case _BudgetCascadeCommitted(cascade=cascade, advanced=advanced): + case _BudgetCascadeCommitted() as committed: asyncio.create_task( self.proxy_logging_obj.service_logging_obj.async_service_success_hook( service=ServiceTypes.RESET_BUDGET_JOB, @@ -797,13 +887,14 @@ class ResetBudgetJob: start_time=start_time, end_time=end_time, event_metadata={ - **_budget_cascade_event_metadata(cascade), - "num_endusers_updated": len(cascade.endusers), + **_budget_cascade_event_metadata(committed.cascade, committed.endusers), + "num_endusers_updated": committed.endusers.invalidated, "num_endusers_failed": 0, + "enduser_invalidation_truncated": committed.endusers.truncated, }, ) ) - return _ChunkOutcome(fetched=len(cascade.budgets), advanced=advanced) + return _ChunkOutcome(fetched=len(committed.cascade.budgets), advanced=committed.advanced) case _BudgetCascadeFailed(cascade=cascade, error=error): verbose_proxy_logger.exception( "Failed to reset the budget table cascade (team member, enduser, org, tag and model access " @@ -827,27 +918,6 @@ class ResetBudgetJob: case _: assert_never(outcome) - async def _get_endusers_with_no_budget_id( - self, - ) -> list[LiteLLM_EndUserTable]: - """ - Fetch end users that have no explicit budget_id set (NULL) and have - accumulated spend > 0. These are implicitly-created end users that - rely on the default budget (litellm.max_end_user_budget_id) applied - in-memory during auth checks. - """ - table: Final = EndUserRepository(self.prisma_client).table - rows: Final = await self._with_db_retry( - lambda: table.find_many( - where={ - "budget_id": None, - "spend": {"gt": 0}, - }, - ), - reason="reset_budget_read_endusers_without_budget_id_failure", - ) - return [LiteLLM_EndUserTable.model_validate(row.model_dump()) for row in rows] - async def _write_key_reset_updates(self, updated_keys: Sequence[_RowReset[LiteLLM_VerificationToken]]) -> None: """ Write per-row {spend, budget_reset_at} updates for keys. diff --git a/litellm/proxy/common_utils/user_api_key_cache.py b/litellm/proxy/common_utils/user_api_key_cache.py index 1c7a379897f..89ff113c6d3 100644 --- a/litellm/proxy/common_utils/user_api_key_cache.py +++ b/litellm/proxy/common_utils/user_api_key_cache.py @@ -1,5 +1,6 @@ from __future__ import annotations +import asyncio import re from collections.abc import Sequence from typing import TYPE_CHECKING, Any, Final, TypeVar, cast, overload @@ -221,6 +222,24 @@ class UserApiKeyCache(DualCache): return await super().async_delete_cache(key) + async def async_delete_cache_keys(self, keys: Sequence[str]) -> None: + """Batch twin of ``async_delete_cache``, partitioned like + ``async_set_cache_pipeline``. + + Both partitions are cleared even when one raises, because a caller + batching these has already committed the rows they cache. + """ + key_object_keys: Final = tuple(key for key in keys if is_user_key_cache_key(key)) + other_keys: Final = tuple(key for key in keys if not is_user_key_cache_key(key)) + outcomes: Final = await asyncio.gather( + self.key_object_cache.async_delete_cache_keys(key_object_keys), + super().async_delete_cache_keys(other_keys), + return_exceptions=True, + ) + failed: Final = tuple(outcome for outcome in outcomes if isinstance(outcome, BaseException)) + if failed: + raise failed[0] + def flush_cache(self) -> None: super().flush_cache() self.key_object_cache.in_memory_cache.flush_cache() diff --git a/litellm/proxy/schema.prisma b/litellm/proxy/schema.prisma index 139fb031671..c0c528bc743 100644 --- a/litellm/proxy/schema.prisma +++ b/litellm/proxy/schema.prisma @@ -678,6 +678,7 @@ model LiteLLM_SpendLogs { @@index([end_user]) @@index([session_id]) @@index([litellm_call_id]) + @@index([api_key, startTime]) } model LiteLLM_BudgetWindowSpend { diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py index 52900c33745..09d719202ca 100644 --- a/litellm/proxy/spend_tracking/spend_tracking_utils.py +++ b/litellm/proxy/spend_tracking/spend_tracking_utils.py @@ -485,10 +485,13 @@ def get_logging_payload( or None ) custom_llm_provider: Final = logged_provider or _model_group_provider(_model_group, llm_router) - raw_model: Final = cast(str, kwargs.get("model") or "") - resolved_model: Final = ( - standard_logging_payload.get("model") if standard_logging_payload is not None else None - ) or reconstruct_model_name(raw_model, logged_provider, metadata or {}) + requested_model: Final = cast(object, kwargs.get("model")) + raw_model: Final = requested_model if isinstance(requested_model, str) else "" + model_is_malformed: Final = requested_model is not None and not isinstance(requested_model, str) + logged_model: Final = standard_logging_payload.get("model") if standard_logging_payload is not None else None + resolved_model: Final = (logged_model if isinstance(logged_model, str) else None) or reconstruct_model_name( + raw_model, logged_provider, metadata or {} + ) failed_with_prompt_shaped_model: Final = ( _get_status_for_spend_log(metadata=metadata) == "failure" and not _model_group @@ -496,7 +499,7 @@ def get_logging_payload( ) model_name: Final = ( UNKNOWN_MODEL_SPEND_LOG_MODEL - if rejected_as_unknown_model or failed_with_prompt_shaped_model + if rejected_as_unknown_model or failed_with_prompt_shaped_model or model_is_malformed else resolved_model ) litellm_call_id: Final = cast( diff --git a/litellm/utils.py b/litellm/utils.py index 073aa2e8bb5..2c9200fbad7 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -2916,6 +2916,15 @@ def supports_none_reasoning_effort(model: str, custom_llm_provider: str | None = return _supports_factory(model=model, custom_llm_provider=custom_llm_provider, key="supports_none_reasoning_effort") +def supports_mid_conversation_system(model: str, custom_llm_provider: str | None = None) -> bool: + """ + Check if the given model accepts a system role message after the leading system block and return a boolean value. + """ + return _supports_factory( + model=model, custom_llm_provider=custom_llm_provider, key="supports_mid_conversation_system" + ) + + def supports_native_structured_output(model: str, custom_llm_provider: str | None = None) -> bool: """ Check if the given model supports native structured outputs and return a boolean value. diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index c565b6ecc4b..96cdbcffd90 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -7605,7 +7605,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -7733,7 +7733,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -7887,7 +7887,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/gpt-6-astra": { "cache_creation_input_token_cost": 1.25e-05, @@ -7956,7 +7956,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -8856,7 +8856,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -8955,7 +8955,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -9054,7 +9054,7 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/gpt-5.5-pro": { "cache_read_input_token_cost": 3e-06, @@ -10987,14 +10987,14 @@ "supports_vision": true }, "azure_ai/FW-Kimi-K3": { - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.5e-05, "reasoning_effort_levels": [ "low", "high", @@ -23788,7 +23788,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": false }, "fireworks_ai/accounts/fireworks/models/mixtral-8x22b-instruct-hf": { "input_cost_per_token": 1.2e-06, @@ -24114,7 +24114,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": false }, "fireworks_ai/qwen3p7-plus": { "cache_read_input_token_cost": 8e-08, @@ -45245,7 +45245,7 @@ "supports_tool_choice": true }, "together_ai/openai/gpt-oss-20b": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "input_cost_per_token": 5e-08, "litellm_provider": "together_ai", "max_input_tokens": 131072, @@ -45482,6 +45482,7 @@ }, "together_ai/deepseek-ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 3e-08, + "deprecation_date": "2026-09-29", "input_cost_per_token": 1.4e-07, "litellm_provider": "together_ai", "max_input_tokens": 1048576, @@ -45503,7 +45504,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://api.together.xyz/v1/models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_response_schema": true, @@ -45528,6 +45529,7 @@ }, "together_ai/deepseek-ai/DeepSeek-V4-Pro-0813": { "cache_read_input_token_cost": 1.3e-07, + "deprecation_date": "2026-09-29", "input_cost_per_token": 1.32e-06, "litellm_provider": "together_ai", "max_input_tokens": 1048576, @@ -45552,7 +45554,7 @@ "source": "https://docs.together.ai/docs/serverless-models" }, "together_ai/google/gemma-4-31B-it": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "input_cost_per_token": 3.9e-07, "litellm_provider": "together_ai", "max_input_tokens": 262144, @@ -45567,7 +45569,7 @@ "supports_vision": true }, "together_ai/intfloat/multilingual-e5-large-instruct": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "input_cost_per_token": 2e-08, "litellm_provider": "together_ai", "max_input_tokens": 514, @@ -45680,7 +45682,7 @@ "supports_tool_choice": true }, "together_ai/thinkingmachines/Inkling-Small": { - "deprecation_date": "2026-09-15", + "deprecation_date": "2026-09-14", "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 5e-07, "litellm_provider": "together_ai", @@ -50573,7 +50575,7 @@ "wandb/openai/gpt-oss-120b": { "supports_reasoning": true, "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "max_output_tokens": 131072, "input_cost_per_token": 3e-08, "output_cost_per_token": 1.7e-07, @@ -50584,7 +50586,7 @@ "wandb/openai/gpt-oss-20b": { "supports_reasoning": true, "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "max_output_tokens": 131072, "input_cost_per_token": 3e-08, "output_cost_per_token": 1.3e-07, @@ -50593,6 +50595,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/zai-org/GLM-4.5": { + "deprecation_date": "2026-03-04", "supports_reasoning": true, "max_tokens": 131072, "max_input_tokens": 131072, @@ -50603,6 +50606,7 @@ "mode": "chat" }, "wandb/Qwen/Qwen3-235B-A22B-Instruct-2507": { + "deprecation_date": "2026-08-04", "max_tokens": 262144, "max_input_tokens": 262144, "max_output_tokens": 262144, @@ -50612,6 +50616,7 @@ "mode": "chat" }, "wandb/Qwen/Qwen3-Coder-480B-A35B-Instruct": { + "deprecation_date": "2026-08-25", "max_tokens": 262144, "max_input_tokens": 262144, "max_output_tokens": 262144, @@ -50622,6 +50627,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/Qwen/Qwen3-235B-A22B-Thinking-2507": { + "deprecation_date": "2026-08-04", "supports_reasoning": true, "max_tokens": 262144, "max_input_tokens": 262144, @@ -50632,6 +50638,7 @@ "mode": "chat" }, "wandb/moonshotai/Kimi-K2-Instruct": { + "deprecation_date": "2026-03-04", "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, @@ -50656,6 +50663,7 @@ "supports_vision": true }, "wandb/MiniMaxAI/MiniMax-M2.5": { + "deprecation_date": "2026-08-25", "max_tokens": 197000, "max_input_tokens": 197000, "max_output_tokens": 197000, @@ -50670,7 +50678,7 @@ }, "wandb/meta-llama/Llama-3.1-8B-Instruct": { "max_tokens": 128000, - "max_input_tokens": 128000, + "max_input_tokens": 131000, "max_output_tokens": 128000, "input_cost_per_token": 2.2e-07, "output_cost_per_token": 2.2e-07, @@ -50690,6 +50698,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/deepseek-ai/DeepSeek-R1-0528": { + "deprecation_date": "2026-03-04", "supports_reasoning": true, "max_tokens": 161000, "max_input_tokens": 161000, @@ -50700,6 +50709,7 @@ "mode": "chat" }, "wandb/deepseek-ai/DeepSeek-V3-0324": { + "deprecation_date": "2026-03-04", "max_tokens": 161000, "max_input_tokens": 161000, "max_output_tokens": 161000, @@ -50719,6 +50729,7 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/meta-llama/Llama-4-Scout-17B-16E-Instruct": { + "deprecation_date": "2026-04-21", "max_tokens": 64000, "max_input_tokens": 64000, "max_output_tokens": 64000, @@ -50728,6 +50739,7 @@ "mode": "chat" }, "wandb/microsoft/Phi-4-mini-instruct": { + "deprecation_date": "2026-08-04", "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, @@ -56692,7 +56704,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_web_search": true, - "gemini_audio_only_live": true + "gemini_audio_only_live": true, + "supports_response_schema": false }, "gemini-3.8-live-extended-thinking": { "input_cost_per_audio_token": 3e-06, @@ -56726,7 +56739,8 @@ "supports_vision": true, "supports_web_search": true, "gemini_audio_only_live": true, - "supports_reasoning": true + "supports_reasoning": true, + "supports_response_schema": false }, "gemini/gemini-2.5-flash-native-audio-latest": { "input_cost_per_audio_token": 3e-06, @@ -60970,10 +60984,11 @@ "wandb/deepseek-ai/DeepSeek-V4-Flash": { "supports_reasoning": true, "max_tokens": 1048576, - "max_input_tokens": 1048576, + "max_input_tokens": 1049000, "input_cost_per_token": 1.4e-07, "output_cost_per_token": 2.8e-07, "cache_read_input_token_cost": 7e-08, + "deprecation_date": "2026-10-05", "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -60983,7 +60998,7 @@ "wandb/deepseek-ai/DeepSeek-V4-Flash-0731": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 1.3e-07, "output_cost_per_token": 2.8e-07, "cache_read_input_token_cost": 7e-08, @@ -60996,10 +61011,11 @@ "wandb/deepseek-ai/DeepSeek-V4-Pro": { "supports_reasoning": true, "max_tokens": 1048576, - "max_input_tokens": 1048576, + "max_input_tokens": 1049000, "input_cost_per_token": 1.15e-06, "output_cost_per_token": 2.55e-06, "cache_read_input_token_cost": 2e-07, + "deprecation_date": "2026-10-05", "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61009,7 +61025,7 @@ "wandb/google/gemma-4-31B-it": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 1e-07, "output_cost_per_token": 3.4e-07, "litellm_provider": "wandb", @@ -61018,8 +61034,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/ibm-granite/granite-4.1-8b": { + "deprecation_date": "2026-10-05", "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "input_cost_per_token": 5e-08, "output_cost_per_token": 1e-07, "litellm_provider": "wandb", @@ -61028,8 +61045,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/JetBrains/Mellum2-12B-A2.5B-Instruct": { + "deprecation_date": "2026-10-05", "max_tokens": 131072, - "max_input_tokens": 131072, + "max_input_tokens": 131000, "input_cost_per_token": 5e-08, "output_cost_per_token": 1e-07, "litellm_provider": "wandb", @@ -61038,8 +61056,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/meta-llama/Llama-3.1-70B-Instruct": { + "deprecation_date": "2026-10-05", "max_tokens": 128000, - "max_input_tokens": 128000, + "max_input_tokens": 131000, "input_cost_per_token": 8e-07, "output_cost_per_token": 8e-07, "litellm_provider": "wandb", @@ -61050,7 +61069,7 @@ "wandb/MiniMaxAI/MiniMax-M3": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 2.3e-07, "output_cost_per_token": 9.6e-07, "cache_read_input_token_cost": 5e-08, @@ -61063,7 +61082,7 @@ "wandb/moonshotai/Kimi-K2.7-Code": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 7.1e-07, "output_cost_per_token": 3.5e-06, "cache_read_input_token_cost": 1.5e-07, @@ -61076,7 +61095,7 @@ "wandb/moonshotai/Kimi-K2.6": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 6.5e-07, "output_cost_per_token": 3.41e-06, "cache_read_input_token_cost": 1.5e-07, @@ -61089,10 +61108,10 @@ "wandb/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, - "input_cost_per_token": 1e-07, - "output_cost_per_token": 2.5e-07, - "cache_read_input_token_cost": 5e-08, + "max_input_tokens": 262000, + "input_cost_per_token": 7e-08, + "output_cost_per_token": 2e-07, + "cache_read_input_token_cost": 4e-08, "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61102,10 +61121,10 @@ "wandb/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, - "input_cost_per_token": 7.5e-07, - "output_cost_per_token": 2.75e-06, - "cache_read_input_token_cost": 1.5e-07, + "max_input_tokens": 262000, + "input_cost_per_token": 5e-07, + "output_cost_per_token": 2.15e-06, + "cache_read_input_token_cost": 1e-07, "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61113,8 +61132,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/OpenPipe/Qwen3-14B-Instruct": { + "deprecation_date": "2026-10-05", "max_tokens": 32768, - "max_input_tokens": 32768, + "max_input_tokens": 32800, "input_cost_per_token": 5e-08, "output_cost_per_token": 2.2e-07, "litellm_provider": "wandb", @@ -61125,7 +61145,7 @@ "wandb/Qwen/Qwen3.8-27B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 4e-07, "output_cost_per_token": 3e-06, "cache_read_input_token_cost": 1.5e-07, @@ -61138,7 +61158,7 @@ "wandb/Qwen/Qwen3.6-35B-A3B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 2.5e-07, "output_cost_per_token": 1.25e-06, "litellm_provider": "wandb", @@ -61149,10 +61169,11 @@ "wandb/Qwen/Qwen3.6-27B": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 6e-07, "output_cost_per_token": 3.6e-06, "cache_read_input_token_cost": 1.2e-07, + "deprecation_date": "2026-10-05", "supports_prompt_caching": true, "litellm_provider": "wandb", "mode": "chat", @@ -61160,9 +61181,10 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/Qwen/Qwen3.5-35B-A3B": { + "deprecation_date": "2026-10-05", "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 2.5e-07, "output_cost_per_token": 1.25e-06, "litellm_provider": "wandb", @@ -61171,8 +61193,9 @@ "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/Qwen/Qwen3-30B-A3B-Instruct-2507": { + "deprecation_date": "2026-10-05", "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 262000, "input_cost_per_token": 1e-07, "output_cost_per_token": 3e-07, "litellm_provider": "wandb", @@ -61187,6 +61210,7 @@ "input_cost_per_token": 1.31e-06, "output_cost_per_token": 3.96e-06, "cache_read_input_token_cost": 4.4e-08, + "max_input_tokens": 1049000, "supports_prompt_caching": true, "source": "https://wandb.ai/site/pricing/tokens/" }, @@ -61197,13 +61221,14 @@ "input_cost_per_token": 1e-07, "output_cost_per_token": 1.5e-07, "cache_read_input_token_cost": 5e-08, + "max_input_tokens": 131000, "supports_prompt_caching": true, "source": "https://wandb.ai/site/pricing/tokens/" }, "wandb/zai-org/GLM-5.2": { "supports_reasoning": true, "max_tokens": 262144, - "max_input_tokens": 262144, + "max_input_tokens": 1049000, "input_cost_per_token": 7.6e-07, "output_cost_per_token": 2.42e-06, "cache_read_input_token_cost": 1.4e-07, @@ -62866,7 +62891,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 6.6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -69158,5 +69183,19 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_vision": true + }, + "wandb/zai-org/GLM-5.3-Flash": { + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "wandb", + "max_input_tokens": 1049000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://wandb.ai/site/pricing/tokens/", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true } } diff --git a/pyproject.toml b/pyproject.toml index 93ff55c4069..615f4b8d0ab 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -67,7 +67,7 @@ proxy = [ "azure-identity>=1.25.2,<2.0", "azure-storage-blob>=12.28.0,<13.0", "mcp>=1.28.1,<2.0", - "litellm-proxy-extras==0.4.98", + "litellm-proxy-extras==0.4.99", "litellm-enterprise==0.1.68", "RestrictedPython>=8.5,<9.0", "rich>=13.9.4,<14.0", @@ -143,8 +143,9 @@ bedrock-realtime = [ # InvokeModelWithBidirectionalStream API, which boto3 cannot do. This # experimental AWS SDK (with its smithy-* deps, pulled transitively) # provides the bidirectional stream; imported lazily in the realtime - # handler so litellm core stays usable without it. - "aws-sdk-bedrock-runtime>=0.7.0,<0.8.0; python_version >= '3.12'", + # handler so litellm core stays usable without it. The awscrt extra is + # required: the SDK's default aiohttp transport has no duplex streaming. + "aws-sdk-bedrock-runtime[awscrt]>=0.10.0,<0.12.0; python_version >= '3.12'", ] proxy-runtime = [ # Historically bundled in the proxy Docker images via requirements.txt. diff --git a/schema.prisma b/schema.prisma index 139fb031671..c0c528bc743 100644 --- a/schema.prisma +++ b/schema.prisma @@ -678,6 +678,7 @@ model LiteLLM_SpendLogs { @@index([end_user]) @@index([session_id]) @@index([litellm_call_id]) + @@index([api_key, startTime]) } model LiteLLM_BudgetWindowSpend { diff --git a/tests/integration/_support/client.py b/tests/integration/_support/client.py index 8fd1efff0da..97522e5728c 100644 --- a/tests/integration/_support/client.py +++ b/tests/integration/_support/client.py @@ -10,9 +10,10 @@ from hashlib import sha256 from typing import Final, TypeVar import httpx -from integration._support.database import read_rows from pydantic import JsonValue, TypeAdapter +from tests.integration._support.database import read_rows + JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) T = TypeVar("T") diff --git a/tests/integration/_support/generation.py b/tests/integration/_support/generation.py index afb3ec2e768..50c1a6f2ad4 100644 --- a/tests/integration/_support/generation.py +++ b/tests/integration/_support/generation.py @@ -6,7 +6,7 @@ from contextlib import contextmanager import httpx from hypothesis import Phase, settings -from integration._support.client import Gateway +from tests.integration._support.client import Gateway LIFECYCLE_SETTINGS: Final = settings( max_examples=20, diff --git a/tests/integration/authorization/test_warmed_policy.py b/tests/integration/authorization/test_warmed_policy.py index 8dbf364f69f..a9bee196ddd 100644 --- a/tests/integration/authorization/test_warmed_policy.py +++ b/tests/integration/authorization/test_warmed_policy.py @@ -10,9 +10,9 @@ from pydantic import JsonValue from hypothesis import strategies as st from hypothesis.stateful import RuleBasedStateMachine, invariant, rule, run_state_machine_as_test -from integration._support.client import Gateway, eventually, object_value -from integration._support.database import read_rows -from integration._support.generation import LIFECYCLE_SETTINGS, bounded_http_requests +from tests.integration._support.client import Gateway, eventually, object_value +from tests.integration._support.database import read_rows +from tests.integration._support.generation import LIFECYCLE_SETTINGS, bounded_http_requests def assert_serving(gateway: Gateway, model: str, key: str, status: int, error_type: str = "auth_error") -> None: diff --git a/tests/integration/configuration/test_effective_settings.py b/tests/integration/configuration/test_effective_settings.py index 7fa440d1d8d..8e164acbe03 100644 --- a/tests/integration/configuration/test_effective_settings.py +++ b/tests/integration/configuration/test_effective_settings.py @@ -4,8 +4,8 @@ from typing import Final import httpx import pytest -from integration._support.client import Gateway, object_value, string_value -from integration._support.database import read_rows +from tests.integration._support.client import Gateway, object_value, string_value +from tests.integration._support.database import read_rows def model_identity(gateway: Gateway, alias: str) -> str: diff --git a/tests/integration/conftest.py b/tests/integration/conftest.py index adb9fcd57f3..342952d44d4 100644 --- a/tests/integration/conftest.py +++ b/tests/integration/conftest.py @@ -12,9 +12,9 @@ import pytest import httpx from redis import Redis -from integration._support.client import Gateway, eventually, gateway_from_environment -from integration._support.manifest import OWNED_DIRECTORIES, contracts -from integration._support.generation import LIFECYCLE_SETTINGS +from tests.integration._support.client import Gateway, eventually, gateway_from_environment +from tests.integration._support.manifest import OWNED_DIRECTORIES, contracts +from tests.integration._support.generation import LIFECYCLE_SETTINGS COLLECTED: Final = pytest.StashKey[tuple[str, ...]]() REPORTS: Final = pytest.StashKey[list[pytest.TestReport]]() diff --git a/tests/integration/management/test_key_updates.py b/tests/integration/management/test_key_updates.py index 6f2e850b17a..b460190f0ba 100644 --- a/tests/integration/management/test_key_updates.py +++ b/tests/integration/management/test_key_updates.py @@ -3,8 +3,8 @@ from hashlib import sha256 import pytest -from integration._support.client import Gateway, object_value -from integration._support.database import read_rows +from tests.integration._support.client import Gateway, object_value +from tests.integration._support.database import read_rows @pytest.mark.covers("mgmt.key.update.preserves_independent_fields") diff --git a/tests/integration/management/test_partial_update_sequences.py b/tests/integration/management/test_partial_update_sequences.py index 3d1ef1374e1..d79c145a685 100644 --- a/tests/integration/management/test_partial_update_sequences.py +++ b/tests/integration/management/test_partial_update_sequences.py @@ -5,11 +5,12 @@ from typing import Final import pytest from hypothesis import strategies as st from hypothesis.stateful import RuleBasedStateMachine, invariant, rule, run_state_machine_as_test -from integration._support.client import Gateway, object_value -from integration._support.database import read_rows -from integration._support.generation import LIFECYCLE_SETTINGS, bounded_http_requests from pydantic import JsonValue +from tests.integration._support.client import Gateway, object_value +from tests.integration._support.database import read_rows +from tests.integration._support.generation import LIFECYCLE_SETTINGS, bounded_http_requests + def _key_rows(digest: str) -> list[dict[str, JsonValue]]: return read_rows( diff --git a/tests/integration/pricing/test_configured_prices.py b/tests/integration/pricing/test_configured_prices.py index b1df012e870..655d74c1402 100644 --- a/tests/integration/pricing/test_configured_prices.py +++ b/tests/integration/pricing/test_configured_prices.py @@ -6,8 +6,8 @@ import uuid import pytest import yaml -from integration._support.client import Gateway, eventually, object_value, string_value -from integration._support.database import read_rows +from tests.integration._support.client import Gateway, eventually, object_value, string_value +from tests.integration._support.database import read_rows @pytest.mark.covers("quota_management.spend_tracking.custom_price.matches_input_rates") diff --git a/tests/integration/providers/test_request_boundary.py b/tests/integration/providers/test_request_boundary.py index aad10843642..33663cd4c59 100644 --- a/tests/integration/providers/test_request_boundary.py +++ b/tests/integration/providers/test_request_boundary.py @@ -3,7 +3,7 @@ from typing import Final import httpx import pytest -from integration._support.client import Gateway, JSON_OBJECT, object_value +from tests.integration._support.client import Gateway, JSON_OBJECT, object_value @pytest.mark.covers("other.provider_wire.internal_parameters_filtered") diff --git a/tests/litellm_utils_tests/test_proxy_budget_reset.py b/tests/litellm_utils_tests/test_proxy_budget_reset.py index fe3c38a771f..32bcee7cb2a 100644 --- a/tests/litellm_utils_tests/test_proxy_budget_reset.py +++ b/tests/litellm_utils_tests/test_proxy_budget_reset.py @@ -102,21 +102,24 @@ def _wire_batcher_for_test(prisma_client, fail_commit=False): return batch_calls -def _wire_cascade_reads_for_test(prisma_client): +def _wire_cascade_reads_for_test(prisma_client, endusers=()): """ The budget tier's cascade reads the rows it is about to zero, so their spend counters can be invalidated after the commit. Give each of those tables an awaitable find_many so the reads resolve instead of falling into the job's warn-and-continue path. + + End users are read by the post-commit invalidation walk rather than by + ``get_data``, so callers that care about customers pass them here. """ for table in ( "litellm_teammembership", "litellm_verificationtoken", "litellm_organizationtable", "litellm_tagtable", - "litellm_endusertable", ): getattr(prisma_client.db, table).find_many = AsyncMock(return_value=[]) + prisma_client.db.litellm_endusertable.find_many = AsyncMock(return_value=list(endusers)) @pytest.mark.asyncio @@ -556,7 +559,7 @@ async def test_reset_budget_continues_other_categories_on_failure(): **{u["user_id"]: u["spend"] for u in [user2]}, **{t["team_id"]: t["spend"] for t in [team1, team2]}, } - _wire_cascade_reads_for_test(prisma_client) + _wire_cascade_reads_for_test(prisma_client, endusers=[enduser1]) proxy_logging_obj = MagicMock() proxy_logging_obj.service_logging_obj = MagicMock() @@ -607,7 +610,10 @@ async def test_reset_budget_continues_other_categories_on_failure(): called_tables = { call.kwargs.get("table_name") for call in prisma_client.get_data.await_args_list } - assert called_tables == {"key", "user", "team", "budget", "enduser"} + assert called_tables == {"key", "user", "team", "budget"} + # Customers are not part of that set: the cascade zeroes them by budget link + # and reads them only afterwards, to invalidate their cached spend. + prisma_client.db.litellm_endusertable.find_many.assert_awaited() # Every category writes through the batch path now, so update_data is unused. prisma_client.update_data.assert_not_awaited() @@ -1029,7 +1035,7 @@ async def test_service_logger_endusers_success(): prisma_client.get_data = AsyncMock(side_effect=fake_get_data) prisma_client.update_data = AsyncMock() batch_calls = _wire_batcher_for_test(prisma_client) - _wire_cascade_reads_for_test(prisma_client) + _wire_cascade_reads_for_test(prisma_client, endusers=endusers) proxy_logging_obj = MagicMock() proxy_logging_obj.service_logging_obj = MagicMock() @@ -1094,7 +1100,7 @@ async def test_service_logger_endusers_failure(): prisma_client.get_data = AsyncMock(side_effect=fake_get_data) prisma_client.update_data = AsyncMock() _wire_batcher_for_test(prisma_client, fail_commit=True) - _wire_cascade_reads_for_test(prisma_client) + _wire_cascade_reads_for_test(prisma_client, endusers=endusers) proxy_logging_obj = MagicMock() proxy_logging_obj.service_logging_obj = MagicMock() @@ -1121,7 +1127,9 @@ async def test_service_logger_endusers_failure(): ) = proxy_logging_obj.service_logging_obj.async_service_failure_hook.call_args event_metadata = kwargs.get("event_metadata", {}) assert event_metadata.get("num_budgets_found") == len(budgets) - assert event_metadata.get("num_endusers_found") == len(endusers) + # Customers are read by the post-commit invalidation walk, which a failed + # commit never reaches, so a failure reports none touched. + assert event_metadata.get("num_endusers_found") == 0 assert "endusers_found" not in event_metadata assert "budgets_found" not in event_metadata proxy_logging_obj.service_logging_obj.async_service_success_hook.assert_not_called() diff --git a/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py b/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py index ed21734c5fc..e0f99835b44 100644 --- a/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py +++ b/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py @@ -20,7 +20,9 @@ import pytest IMAGE: Final = os.getenv("LITELLM_IMAGE") NON_ROOT_UID: Final = "12345:0" -IMPORT_PROBE: Final = "import aws_sdk_bedrock_runtime, smithy_aws_core; print('bedrock-realtime ok')" +IMPORT_PROBE: Final = ( + "import aws_sdk_bedrock_runtime, smithy_aws_core, smithy_http.aio.crt; print('bedrock-realtime ok')" +) pytestmark = [ pytest.mark.skipif(IMAGE is None, reason="requires a built image (set LITELLM_IMAGE)"), @@ -52,7 +54,7 @@ def test_image_imports_bedrock_realtime_sdk(): ) assert probe.returncode == 0 and "bedrock-realtime ok" in probe.stdout, ( - f"{IMAGE} cannot import aws_sdk_bedrock_runtime as uid {NON_ROOT_UID}, so Bedrock Nova Sonic " - "/v1/realtime sessions fail with 'Missing aws_sdk_bedrock_runtime'. Is `--extra bedrock-realtime` " + f"{IMAGE} cannot import aws_sdk_bedrock_runtime with its awscrt transport as uid {NON_ROOT_UID}, so " + "Bedrock Nova Sonic /v1/realtime sessions fail at SDK import. Is `--extra bedrock-realtime` " f"passed to every `uv sync` in its Dockerfile?\nstdout:\n{probe.stdout}\nstderr:\n{probe.stderr}" ) diff --git a/tests/test_litellm/caching/test_dual_cache.py b/tests/test_litellm/caching/test_dual_cache.py index 95395878c25..5f59de9cca5 100644 --- a/tests/test_litellm/caching/test_dual_cache.py +++ b/tests/test_litellm/caching/test_dual_cache.py @@ -6,6 +6,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest +from litellm.constants import DEFAULT_MAX_REDIS_BATCH_CACHE_SIZE from litellm.caching.dual_cache import DualCache from litellm.caching.in_memory_cache import InMemoryCache from litellm.caching.redis_cache import RedisCache, _redis_circuit_breaker_guard, _redis_circuit_breaker_guard_sync @@ -759,3 +760,34 @@ async def test_redis_timeouts_falling_back_to_memory_log_once_per_interval(caplo " (199 more Redis timeouts since the previous Redis timeout line were logged at DEBUG)", ) ] + + +@pytest.mark.asyncio +async def test_async_delete_cache_keys_drops_memory_and_chunks_redis(): + """Batch delete clears both layers, and chunks Redis so one caller's large + key list cannot become a single oversized DELETE command.""" + redis_cache = MagicMock(spec=RedisCache) + redis_cache.delete_cache_keys = AsyncMock() + dual_cache = DualCache(in_memory_cache=InMemoryCache(), redis_cache=redis_cache) + keys = [f"key-{i}" for i in range(DEFAULT_MAX_REDIS_BATCH_CACHE_SIZE + 7)] + for key in keys: + dual_cache.in_memory_cache.set_cache(key=key, value=1) + + await dual_cache.async_delete_cache_keys(keys) + + assert all(dual_cache.in_memory_cache.get_cache(key=key) is None for key in keys) + sent = [call.args[0] for call in redis_cache.delete_cache_keys.await_args_list] + assert [len(chunk) for chunk in sent] == [DEFAULT_MAX_REDIS_BATCH_CACHE_SIZE, 7] + assert [key for chunk in sent for key in chunk] == keys + + +@pytest.mark.asyncio +async def test_async_delete_cache_keys_on_empty_list_touches_no_backend(): + """An empty page must not reach Redis: DELETE with no arguments is an error.""" + redis_cache = MagicMock(spec=RedisCache) + redis_cache.delete_cache_keys = AsyncMock() + dual_cache = DualCache(in_memory_cache=InMemoryCache(), redis_cache=redis_cache) + + await dual_cache.async_delete_cache_keys([]) + + redis_cache.delete_cache_keys.assert_not_awaited() diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py index 03b9840b1c3..e6782b70d3e 100644 --- a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py @@ -23,6 +23,9 @@ from litellm.llms.anthropic.experimental_pass_through.adapters.transformation im create_tool_name_mapping, truncate_tool_name, ) +from litellm.llms.anthropic.experimental_pass_through.messages.mid_conversation_system import ( + CONVERTED_SYSTEM_NOTE, +) from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig from litellm.types.llms.anthropic import ( AnthopicMessagesAssistantMessageParam, @@ -563,10 +566,19 @@ def test_translate_anthropic_messages_to_openai_tool_message_placement(): @pytest.mark.parametrize( ("system_content", "expected_content"), [ - ("Use the corrected result.", "Use the corrected result."), + ( + "Use the corrected result.", + [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, + {"type": "text", "text": "Use the corrected result."}, + ], + ), ( [{"type": "text", "text": "Use the corrected result."}], - [{"type": "text", "text": "Use the corrected result."}], + [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, + {"type": "text", "text": "Use the corrected result."}, + ], ), ( [ @@ -576,7 +588,11 @@ def test_translate_anthropic_messages_to_openai_tool_message_placement(): }, {"type": "text", "text": "Use the corrected result."}, ], - [{"type": "text", "text": "Use the corrected result."}], + [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, + {"type": "image_url", "image_url": {"url": "https://example.com/a.png"}}, + {"type": "text", "text": "Use the corrected result."}, + ], ), ( [ @@ -584,13 +600,14 @@ def test_translate_anthropic_messages_to_openai_tool_message_placement(): {"type": "text", "text": "Second correction."}, ], [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, {"type": "text", "text": "First correction."}, {"type": "text", "text": "Second correction."}, ], ), ], ) -def test_translate_anthropic_messages_to_openai_preserves_midturn_system_correction( +def test_translate_anthropic_messages_to_openai_converts_midturn_system_correction( system_content: object, expected_content: object, ): @@ -646,7 +663,7 @@ def test_translate_anthropic_messages_to_openai_preserves_midturn_system_correct "tool_call_id": "toolu_01234", "content": "Rainy, 55°F", }, - {"role": "system", "content": expected_content}, + {"role": "user", "content": expected_content}, {"role": "user", "content": "Continue."}, ] @@ -752,8 +769,8 @@ def test_translate_anthropic_messages_to_openai_drops_empty_midturn_system( def test_translate_anthropic_to_openai_orders_top_level_and_midturn_system(): """ Request level: the trusted top-level prompt is hoisted to index 0 exactly once and the - in-sequence correction keeps its own position and `role: "system"` -- no duplication of - either, and no reordering of the surrounding turns. + in-sequence correction keeps its own position as a user turn prefixed with the operator + note -- no duplication of either, and no reordering of the surrounding turns. """ openai_request, _ = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai( anthropic_message_request={ @@ -773,11 +790,140 @@ def test_translate_anthropic_to_openai_orders_top_level_and_midturn_system(): {"role": "system", "content": "Trusted top-level prompt."}, {"role": "user", "content": "First question."}, {"role": "assistant", "content": "First answer.", "thinking_blocks": None}, - {"role": "system", "content": "Use the corrected result."}, + { + "role": "user", + "content": [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, + {"type": "text", "text": "Use the corrected result."}, + ], + }, {"role": "user", "content": "Continue."}, ] +_CLAUDE_CODE_MIDTURN_SYSTEM_REQUEST: Final = { + "max_tokens": 128, + "system": [{"type": "text", "text": "You are Claude Code."}], + "messages": [ + {"role": "user", "content": "say hi"}, + { + "role": "system", + "content": [{"type": "text", "text": "Keep answers to one sentence."}], + }, + {"role": "assistant", "content": "Hi."}, + {"role": "user", "content": "say bye"}, + ], +} + + +@pytest.mark.parametrize("custom_llm_provider", [None, "hosted_vllm"]) +def test_translate_anthropic_to_openai_converts_claude_code_midturn_system_turn(custom_llm_provider: str | None): + """ + Claude Code appends a system-role harness reminder after the user turn. On a chat-completions + target that does not declare ``supports_mid_conversation_system`` (a self-hosted model the cost + map knows nothing about) the outbound request must have exactly one system message, at index 0, + and the converted turn must carry the operator note first. + """ + openai_request, _ = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai( + anthropic_message_request={"model": "qwen3.8-27B", **_CLAUDE_CODE_MIDTURN_SYSTEM_REQUEST}, + custom_llm_provider=custom_llm_provider, + ) + + roles = [m["role"] for m in openai_request["messages"]] + assert roles == ["system", "user", "user", "assistant", "user"] + converted = openai_request["messages"][2] + assert converted["content"][0]["text"] == CONVERTED_SYSTEM_NOTE + assert converted["content"][1]["text"] == "Keep answers to one sentence." + + +def test_translate_anthropic_to_openai_keeps_midturn_system_when_target_declares_support(monkeypatch): + """ + A chat-completions target flagged ``supports_mid_conversation_system`` in the cost map accepts + the role anywhere, so the harness reminder is forwarded in place with its role and content + untouched, the same rule the native Anthropic Messages path applies. + """ + model: Final = "system-role-anywhere-chat-model" + monkeypatch.setitem( + litellm.model_cost, + model, + {"litellm_provider": "openai", "mode": "chat", "supports_mid_conversation_system": True}, + ) + + openai_request, _ = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai( + anthropic_message_request={"model": model, **_CLAUDE_CODE_MIDTURN_SYSTEM_REQUEST}, + custom_llm_provider="openai", + ) + + assert openai_request["messages"] == [ + {"role": "system", "content": [{"type": "text", "text": "You are Claude Code."}]}, + {"role": "user", "content": "say hi"}, + { + "role": "system", + "content": [{"type": "text", "text": "Keep answers to one sentence."}], + }, + {"role": "assistant", "content": "Hi.", "thinking_blocks": None}, + {"role": "user", "content": "say bye"}, + ] + + +def test_translate_anthropic_to_openai_moves_midturn_system_after_tool_result(): + """ + A system entry wedged between an assistant tool_use turn and its tool_result turn is + emitted after the role: "tool" message, so the tool call stays paired with its result. + """ + result = LiteLLMAnthropicMessagesAdapter().translate_anthropic_messages_to_openai( + messages=[ + { + "role": "assistant", + "content": [ + { + "type": "tool_use", + "id": "toolu_01234", + "name": "get_weather", + "input": {"location": "Boston"}, + } + ], + }, + {"role": "system", "content": "Use the corrected result."}, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01234", + "content": "Rainy, 55°F", + } + ], + }, + ], + model="claude-3-5-sonnet-20240620", + ) + + assert [m["role"] for m in result] == ["assistant", "tool", "user"] + assert result[2]["content"][0]["text"] == CONVERTED_SYSTEM_NOTE + + +def test_translate_anthropic_messages_to_openai_converts_string_midturn_system(): + result = LiteLLMAnthropicMessagesAdapter().translate_anthropic_messages_to_openai( + messages=[ + {"role": "user", "content": "hi"}, + {"role": "system", "content": "Keep it short."}, + ], + model="claude-3-5-sonnet-20240620", + ) + + assert result == [ + {"role": "user", "content": "hi"}, + { + "role": "user", + "content": [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, + {"type": "text", "text": "Keep it short."}, + ], + }, + ] + + def _claude_code_user_id(session_id: str) -> str: return json.dumps({"device_id": "d" * 64, "account_uuid": "", "session_id": session_id}) diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_mid_conversation_system.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_mid_conversation_system.py new file mode 100644 index 00000000000..40a9f4c2536 --- /dev/null +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_mid_conversation_system.py @@ -0,0 +1,89 @@ +from collections import Counter + +from litellm.llms.anthropic.experimental_pass_through.messages.mid_conversation_system import ( + CONVERTED_SYSTEM_NOTE, + convert_mid_conversation_system_turns, +) + + +class RoleReadCountingMessage(dict): + def __init__(self, role: str, content: object, reads: Counter): + super().__init__(role=role, content=content) + self.reads = reads + + def get(self, key, default=None): + self.reads[key] += 1 + return super().get(key, default) + + +def test_convert_mid_conversation_system_turns_converts_system_to_user_in_place(): + result = convert_mid_conversation_system_turns( + [ + {"role": "user", "content": "hi"}, + {"role": "system", "content": [{"type": "text", "text": "Keep it short."}]}, + {"role": "assistant", "content": "Hi."}, + ] + ) + + assert result == ( + {"role": "user", "content": "hi"}, + { + "role": "user", + "content": [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, + {"type": "text", "text": "Keep it short."}, + ], + }, + {"role": "assistant", "content": "Hi."}, + ) + + +def test_convert_mid_conversation_system_turns_wraps_string_content(): + result = convert_mid_conversation_system_turns( + [ + {"role": "user", "content": "hi"}, + {"role": "system", "content": "Keep it short."}, + ] + ) + + assert result[1] == { + "role": "user", + "content": [ + {"type": "text", "text": CONVERTED_SYSTEM_NOTE}, + {"type": "text", "text": "Keep it short."}, + ], + } + + +def test_convert_mid_conversation_system_turns_moves_system_after_tool_result(): + assistant_tool_use = { + "role": "assistant", + "content": [{"type": "tool_use", "id": "toolu_1", "name": "get_weather", "input": {}}], + } + wedged_system = {"role": "system", "content": "Use the corrected result."} + tool_result = { + "role": "user", + "content": [{"type": "tool_result", "tool_use_id": "toolu_1", "content": "Rainy"}], + } + + result = convert_mid_conversation_system_turns([assistant_tool_use, wedged_system, tool_result]) + + assert result[0] is assistant_tool_use + assert result[1] is tool_result + assert result[2]["role"] == "user" + assert result[2]["content"][0]["text"] == CONVERTED_SYSTEM_NOTE + + +def test_convert_mid_conversation_system_turns_reads_each_role_a_bounded_number_of_times(): + reads = Counter() + system_run = [RoleReadCountingMessage("system", f"reminder {i}", reads) for i in range(2_000)] + tool_result = RoleReadCountingMessage( + "user", [{"type": "tool_result", "tool_use_id": "toolu_1", "content": "Rainy"}], reads + ) + messages = [RoleReadCountingMessage("user", "hi", reads), *system_run, tool_result] + + result = convert_mid_conversation_system_turns(messages) + + assert reads["role"] <= 3 * len(messages) + assert result[1] is tool_result + assert [m["content"][1]["text"] for m in result[2:]] == [m["content"] for m in system_run] diff --git a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py index 09ebc1a3c95..80f917e0578 100644 --- a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py +++ b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py @@ -23,6 +23,9 @@ from litellm.constants import ( DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET, DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET, ) +from litellm.llms.anthropic.experimental_pass_through.messages.mid_conversation_system import ( + as_system_content_blocks, +) from litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation import ( AmazonAnthropicClaudeMessagesConfig, AmazonAnthropicClaudeMessagesStreamDecoder, @@ -2533,20 +2536,16 @@ def test_bedrock_claude_4_8_plus_cost_map_entries_carry_mid_conversation_system_ def test_as_system_content_blocks_handles_each_shape(): - """``_as_system_content_blocks`` normalizes every system shape: ``None`` -> empty, + """``as_system_content_blocks`` normalizes every system shape: ``None`` -> empty, a string -> a single text block, a list -> a shallow copy, and any other value (e.g. a bare content-block dict) -> wrapped in a single-element list.""" block = {"type": "text", "text": "x"} - assert AmazonAnthropicClaudeMessagesConfig._as_system_content_blocks(None) == [] - assert AmazonAnthropicClaudeMessagesConfig._as_system_content_blocks("hello") == [ - {"type": "text", "text": "hello"} - ] + assert as_system_content_blocks(None) == [] + assert as_system_content_blocks("hello") == [{"type": "text", "text": "hello"}] blocks = [block] - out = AmazonAnthropicClaudeMessagesConfig._as_system_content_blocks(blocks) + out = as_system_content_blocks(blocks) assert out == blocks and out is not blocks - assert AmazonAnthropicClaudeMessagesConfig._as_system_content_blocks(block) == [ - block - ] + assert as_system_content_blocks(block) == [block] @pytest.mark.parametrize( diff --git a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py index ac3a43b742f..21838759acd 100644 --- a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py +++ b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py @@ -8,7 +8,11 @@ from unittest.mock import MagicMock import pytest import litellm -from litellm.constants import REALTIME_SESSION_SUCCESS_LOGGED_KEY +from litellm.constants import ( + BEDROCK_REALTIME_SDK_SUPPORTED_RANGE, + REALTIME_SESSION_SUCCESS_LOGGED_KEY, + WEBSOCKET_CLOSE_REASON_MAX_BYTES, +) from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.realtime.handler import BedrockRealtime from litellm.llms.bedrock.realtime.transformation import BedrockRealtimeConfig @@ -207,7 +211,19 @@ class ScriptedBedrockStream: return (None, self._receiver) +class FakeAWSCredentialsIdentity: + def __init__(self, access_key_id, secret_access_key, session_token=None): + self.access_key_id = access_key_id + self.secret_access_key = secret_access_key + self.session_token = session_token + + class FakeStaticCredentialsResolver: + def __init__(self, identity=None): + self.identity = identity + + +class FakeAWSCRTHTTPClient: pass @@ -227,48 +243,32 @@ class StubCredentialsBedrockRealtime(BedrockRealtime): return SimpleNamespace(get_frozen_credentials=lambda: self.frozen_credentials) -@pytest.fixture -def stub_aws_sdk_client(monkeypatch): - captured = {} +class FakeOperationInput: + def __init__(self, model_id): + self.model_id = model_id - class CapturingConfig: - def __init__(self, **kwargs): - captured["config_kwargs"] = kwargs - self.kwargs = kwargs - - class FakeOperationInput: - def __init__(self, model_id): - self.model_id = model_id - - class FakeBedrockRuntimeClient: - def __init__(self, config): - captured["client_config"] = config - - async def invoke_model_with_bidirectional_stream(self, operation_input): - captured["operation_input"] = operation_input - if captured.get("streams"): - stream = captured["streams"].pop(0) - if isinstance(stream, Exception): - raise stream - return stream - return ScriptedBedrockStream(captured.get("scripted_payloads", [])) +def _install_fake_sdk_modules(monkeypatch, client_module, config_module): + """Wire fake aws_sdk_bedrock_runtime / smithy packages into sys.modules for the handler's lazy imports.""" package = types.ModuleType("aws_sdk_bedrock_runtime") - client_module = types.ModuleType("aws_sdk_bedrock_runtime.client") - client_module.BedrockRuntimeClient = FakeBedrockRuntimeClient - client_module.InvokeModelWithBidirectionalStreamOperationInput = FakeOperationInput - config_module = types.ModuleType("aws_sdk_bedrock_runtime.config") - config_module.Config = CapturingConfig models_module = types.ModuleType("aws_sdk_bedrock_runtime.models") models_module.BidirectionalInputPayloadPart = FakePayloadPart models_module.InvokeModelWithBidirectionalStreamInputChunk = FakeInputChunk + models_module.InvokeModelWithBidirectionalStreamOperationInput = FakeOperationInput package.client = client_module package.config = config_module package.models = models_module smithy_package = types.ModuleType("smithy_aws_core") identity_module = types.ModuleType("smithy_aws_core.identity") + identity_module.AWSCredentialsIdentity = FakeAWSCredentialsIdentity identity_module.StaticCredentialsResolver = FakeStaticCredentialsResolver smithy_package.identity = identity_module + smithy_http_package = types.ModuleType("smithy_http") + smithy_http_aio = types.ModuleType("smithy_http.aio") + crt_module = types.ModuleType("smithy_http.aio.crt") + crt_module.AWSCRTHTTPClient = FakeAWSCRTHTTPClient + smithy_http_aio.crt = crt_module + smithy_http_package.aio = smithy_http_aio stubbed_modules = { "aws_sdk_bedrock_runtime": package, @@ -277,10 +277,56 @@ def stub_aws_sdk_client(monkeypatch): "aws_sdk_bedrock_runtime.models": models_module, "smithy_aws_core": smithy_package, "smithy_aws_core.identity": identity_module, + "smithy_http": smithy_http_package, + "smithy_http.aio": smithy_http_aio, + "smithy_http.aio.crt": crt_module, } for module_name, module in stubbed_modules.items(): monkeypatch.setitem(sys.modules, module_name, module) + +@pytest.fixture +def stub_aws_sdk_client(monkeypatch): + """Fake of the aws-sdk-bedrock-runtime 0.10/0.11 surface: async config resolve, async client with close()""" + captured = {} + + class FakeAsyncBedrockRuntimeConfig: + def __init__(self, kwargs): + self.kwargs = kwargs + + @classmethod + async def resolve(cls, **kwargs): + captured["config_kwargs"] = kwargs + return cls(kwargs) + + class FakeAsyncBedrockRuntimeClient: + def __init__(self, config): + captured["client_config"] = config + captured["client_closed"] = False + + async def invoke_model_with_bidirectional_stream(self, operation_input): + captured["operation_input"] = operation_input + if captured.get("streams"): + stream = captured["streams"].pop(0) + if isinstance(stream, Exception): + raise stream + captured["open_stream"] = stream + return stream + stream = ScriptedBedrockStream(captured.get("scripted_payloads", [])) + captured["open_stream"] = stream + return stream + + async def close(self): + open_stream = captured.get("open_stream") + captured["input_closed_before_client_close"] = open_stream is None or open_stream.input_stream.closed + captured["client_closed"] = True + + client_module = types.ModuleType("aws_sdk_bedrock_runtime.client") + client_module.AsyncBedrockRuntimeClient = FakeAsyncBedrockRuntimeClient + config_module = types.ModuleType("aws_sdk_bedrock_runtime.config") + config_module.AsyncBedrockRuntimeConfig = FakeAsyncBedrockRuntimeConfig + _install_fake_sdk_modules(monkeypatch, client_module, config_module) + for env_var in ( "AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY", @@ -764,15 +810,33 @@ class TestBedrockRealtimeAwsAuth: ) config_kwargs = stub_aws_sdk_client["config_kwargs"] - assert config_kwargs["aws_access_key_id"] == "litellm-params-access-key" - assert config_kwargs["aws_secret_access_key"] == "litellm-params-secret-key" - assert config_kwargs["aws_session_token"] == "litellm-params-session-token" - assert isinstance(config_kwargs["aws_credentials_identity_resolver"], FakeStaticCredentialsResolver) + resolver = config_kwargs["aws_credentials_identity_resolver"] + assert isinstance(resolver, FakeStaticCredentialsResolver) + assert resolver.identity.access_key_id == "litellm-params-access-key" + assert resolver.identity.secret_access_key == "litellm-params-secret-key" + assert resolver.identity.session_token == "litellm-params-session-token" assert config_kwargs["region"] == "us-east-1" + assert config_kwargs["endpoint_uri"] == "https://bedrock-runtime.us-east-1.amazonaws.com" + assert isinstance(config_kwargs["transport"], FakeAWSCRTHTTPClient) assert stub_aws_sdk_client["client_config"].kwargs is config_kwargs assert stub_aws_sdk_client["operation_input"].model_id == "amazon.nova-sonic-v1:0" assert websocket.closed + @pytest.mark.asyncio + async def test_api_base_overrides_default_endpoint(self, stub_aws_sdk_client): + await BedrockRealtime().async_realtime( + model="amazon.nova-sonic-v1:0", + websocket=RealtimeClientWS(), + logging_obj=FakeLogging(), + aws_region_name="us-east-1", + aws_access_key_id="k", + aws_secret_access_key="s", + api_base="https://vpce-bedrock.example.internal", + aws_bedrock_runtime_endpoint="https://ignored.example.internal", + ) + + assert stub_aws_sdk_client["config_kwargs"]["endpoint_uri"] == "https://vpce-bedrock.example.internal" + @pytest.mark.asyncio async def test_role_assumption_params_forwarded_to_get_credentials(self, stub_aws_sdk_client): handler = StubCredentialsBedrockRealtime( @@ -805,11 +869,11 @@ class TestBedrockRealtimeAwsAuth: "aws_sts_endpoint": None, "aws_external_id": "realtime-external-id", } - config_kwargs = stub_aws_sdk_client["config_kwargs"] - assert config_kwargs["aws_access_key_id"] == "assumed-access-key" - assert config_kwargs["aws_secret_access_key"] == "assumed-secret-key" - assert config_kwargs["aws_session_token"] == "assumed-session-token" - assert isinstance(config_kwargs["aws_credentials_identity_resolver"], FakeStaticCredentialsResolver) + resolver = stub_aws_sdk_client["config_kwargs"]["aws_credentials_identity_resolver"] + assert isinstance(resolver, FakeStaticCredentialsResolver) + assert resolver.identity.access_key_id == "assumed-access-key" + assert resolver.identity.secret_access_key == "assumed-secret-key" + assert resolver.identity.session_token == "assumed-session-token" @pytest.mark.asyncio async def test_unresolvable_credentials_raise_clear_auth_error(self, stub_aws_sdk_client): @@ -826,5 +890,118 @@ class TestBedrockRealtimeAwsAuth: assert "config_kwargs" not in stub_aws_sdk_client +class TestBedrockRealtimeSdkLifecycle: + """aws-sdk-bedrock-runtime 0.10/0.11: async config, async client, CRT transport, close() (LIT-7938 regression)""" + + AWS_ARGS = { + "model": "amazon.nova-sonic-v1:0", + "aws_region_name": "us-east-1", + "aws_access_key_id": "k", + "aws_secret_access_key": "s", + } + + @pytest.mark.asyncio + async def test_client_closed_after_input_stream_on_normal_completion(self, stub_aws_sdk_client): + await BedrockRealtime().async_realtime(websocket=RealtimeClientWS(), logging_obj=FakeLogging(), **self.AWS_ARGS) + + assert stub_aws_sdk_client["client_closed"] + assert stub_aws_sdk_client["input_closed_before_client_close"] + + @pytest.mark.asyncio + async def test_client_closed_when_stream_open_fails(self, stub_aws_sdk_client): + stub_aws_sdk_client["streams"] = [ServiceUnavailableException("bedrock unavailable")] + + with pytest.raises(ServiceUnavailableException): + await BedrockRealtime().async_realtime( + websocket=RealtimeClientWS(), logging_obj=FakeLogging(), **self.AWS_ARGS + ) + + assert stub_aws_sdk_client["client_closed"] + + @pytest.mark.asyncio + async def test_client_closed_when_provider_stream_fails_mid_session(self, stub_aws_sdk_client): + stub_aws_sdk_client["streams"] = [ScriptedBedrockStream([], receiver_type=BreakingBedrockReceiver)] + + with pytest.raises(BedrockError): + await BedrockRealtime().async_realtime( + websocket=ConnectedClientWS([]), logging_obj=FakeLogging(), **self.AWS_ARGS + ) + + assert stub_aws_sdk_client["client_closed"] + assert stub_aws_sdk_client["input_closed_before_client_close"] + + @pytest.mark.asyncio + async def test_client_without_close_completes_session(self, monkeypatch): + class ClientWithoutClose: + def __init__(self, config): + pass + + async def invoke_model_with_bidirectional_stream(self, operation_input): + return ScriptedBedrockStream([]) + + class ConfigWithoutCapture: + @classmethod + async def resolve(cls, **kwargs): + return cls() + + client_module = types.ModuleType("aws_sdk_bedrock_runtime.client") + client_module.AsyncBedrockRuntimeClient = ClientWithoutClose + config_module = types.ModuleType("aws_sdk_bedrock_runtime.config") + config_module.AsyncBedrockRuntimeConfig = ConfigWithoutCapture + _install_fake_sdk_modules(monkeypatch, client_module, config_module) + websocket = RealtimeClientWS() + + await BedrockRealtime().async_realtime(websocket=websocket, logging_obj=FakeLogging(), **self.AWS_ARGS) + + assert websocket.closed + + +class TestBedrockRealtimeSdkImportErrors: + """Init errors must tell 'SDK not installed' apart from 'SDK installed but unsupported version' (LIT-7938)""" + + @pytest.mark.asyncio + async def test_absent_sdk_names_install_extra(self, monkeypatch): + monkeypatch.setitem(sys.modules, "aws_sdk_bedrock_runtime", None) + handler = BedrockRealtime(sdk_version_lookup=lambda: None) + + with pytest.raises(ImportError) as exc_info: + await handler.async_realtime( + model="amazon.nova-sonic-v1:0", websocket=RealtimeClientWS(), logging_obj=FakeLogging() + ) + + message = str(exc_info.value) + assert message.startswith("Missing aws_sdk_bedrock_runtime") + assert "litellm[bedrock-realtime]" in message + assert "is installed but" not in message + close_reason = message.encode()[:WEBSOCKET_CLOSE_REASON_MAX_BYTES].decode() + assert BEDROCK_REALTIME_SDK_SUPPORTED_RANGE in close_reason + assert "pip install 'litellm[bedrock-realtime]'" in close_reason + + @pytest.mark.asyncio + async def test_incompatible_sdk_names_installed_version_and_supported_range(self, monkeypatch): + legacy_client_module = types.ModuleType("aws_sdk_bedrock_runtime.client") + legacy_client_module.BedrockRuntimeClient = object + legacy_config_module = types.ModuleType("aws_sdk_bedrock_runtime.config") + legacy_config_module.Config = object + _install_fake_sdk_modules(monkeypatch, legacy_client_module, legacy_config_module) + handler = BedrockRealtime(sdk_version_lookup=lambda: "0.7.0") + + with pytest.raises(ImportError) as exc_info: + await handler.async_realtime( + model="amazon.nova-sonic-v1:0", websocket=RealtimeClientWS(), logging_obj=FakeLogging() + ) + + message = str(exc_info.value) + assert "aws-sdk-bedrock-runtime 0.7.0 is installed but" in message + assert ">=0.10.0,<0.12.0" in message + assert not message.startswith("Missing aws_sdk_bedrock_runtime") + assert isinstance(exc_info.value.__cause__, ImportError) + assert str(exc_info.value.__cause__) not in message + assert "cannot import name" not in message + close_reason = message.encode()[:WEBSOCKET_CLOSE_REASON_MAX_BYTES].decode() + assert "0.7.0 is installed" in close_reason + assert BEDROCK_REALTIME_SDK_SUPPORTED_RANGE in close_reason + + if __name__ == "__main__": pytest.main([__file__, "-v"]) diff --git a/tests/test_litellm/proxy/common_utils/test_reset_budget_job.py b/tests/test_litellm/proxy/common_utils/test_reset_budget_job.py index 1ccf9be37b9..e96069ffa99 100644 --- a/tests/test_litellm/proxy/common_utils/test_reset_budget_job.py +++ b/tests/test_litellm/proxy/common_utils/test_reset_budget_job.py @@ -4,7 +4,7 @@ import sys import types from datetime import datetime, timedelta, timezone from datetime import time as dt_time -from typing import Any, Dict, Final, List +from typing import Any, Dict, Final, List, Optional from unittest.mock import AsyncMock, MagicMock import httpx @@ -16,6 +16,7 @@ from litellm.proxy._types import LiteLLM_VerificationToken from litellm.proxy.common_utils import reset_budget_job as reset_budget_job_module from litellm.constants import ( PROXY_BUDGET_RESCHEDULER_MIN_TIME, + RESET_BUDGET_JOB_BATCH_SIZE, RESET_BUDGET_JOB_LOCK_TTL_SECONDS, RESET_BUDGET_JOB_NAME, ) @@ -31,13 +32,36 @@ class MockTable: self.find_many_calls: List[Dict[str, Any]] = [] self.update_many_calls: List[Dict[str, Any]] = [] self._find_many_results: List[Any] = [] + self._find_many_error: Optional[tuple[int, Exception]] = None def set_find_many_results(self, results: List[Any]): self._find_many_results = results - async def find_many(self, where: Dict[str, Any]) -> List[Any]: - self.find_many_calls.append({"where": where}) - return self._find_many_results + def set_find_many_error(self, after_reads: int, error: Exception): + """Fail every read past the first ``after_reads``, the way a connection + dropping partway through a paged walk does.""" + self._find_many_error = (after_reads, error) + + async def find_many( + self, + where: Dict[str, Any], + order: Optional[Dict[str, str]] = None, + take: Optional[int] = None, + ) -> List[Any]: + """Replays canned rows, honouring the keyset cursor + ``take`` a paged + caller relies on: without that a paged walk never advances and the + test would hang instead of failing.""" + if self._find_many_error is not None and len(self.find_many_calls) >= self._find_many_error[0]: + raise self._find_many_error[1] + paging = {k: v for k, v in (("order", order), ("take", take)) if v is not None} + self.find_many_calls.append({"where": where, **paging}) + rows = list(self._find_many_results) + for field, condition in where.items(): + if isinstance(condition, dict) and "gt" in condition and field != "spend": + rows = [row for row in rows if getattr(row, field, "") > condition["gt"]] + for field, direction in (order or {}).items(): + rows.sort(key=lambda row: getattr(row, field, ""), reverse=direction == "desc") + return rows[:take] if take is not None else rows async def update_many(self, where: Dict[str, Any], data: Dict[str, Any]) -> Dict[str, Any]: self.update_many_calls.append({"where": where, "data": data}) @@ -801,10 +825,16 @@ def test_reset_budget_resets_endusers_with_null_budget_id(reset_budget_job, mock }, ] - # Verify find_many was called to fetch NULL-budget-id end users + # The post-commit invalidation walk covers both branches, so implicitly + # created customers on the default tier get their cached spend dropped too, + # and it is paged rather than reading the whole customer population. find_many_calls = mock_prisma_client.db.litellm_endusertable.find_many_calls assert len(find_many_calls) == 1 - assert find_many_calls[0]["where"] == {"budget_id": None, "spend": {"gt": 0}} + assert find_many_calls[0]["where"]["OR"] == [ + {"budget_id": {"in": [default_budget_id]}}, + {"budget_id": None}, + ] + assert find_many_calls[0]["take"] == RESET_BUDGET_JOB_BATCH_SIZE litellm.max_end_user_budget_id = None @@ -835,9 +865,12 @@ def test_reset_budget_skips_null_budget_id_endusers_when_default_not_configured( asyncio.run(reset_budget_job.reset_budget_for_litellm_budget_table()) - # Should NOT have queried for NULL-budget-id end users + # The invalidation walk must not reach for NULL-budget-id customers: they + # ride a default tier that is not expiring, so their spend stays put. find_many_calls = mock_prisma_client.db.litellm_endusertable.find_many_calls - assert len(find_many_calls) == 0 + assert [call["where"] for call in find_many_calls] == [ + {"budget_id": {"in": ["some-budget"]}, "user_id": {"gt": ""}} + ] litellm.max_end_user_budget_id = None @@ -872,9 +905,12 @@ def test_reset_budget_skips_null_budget_id_endusers_when_default_not_in_reset_li asyncio.run(reset_budget_job.reset_budget_for_litellm_budget_table()) - # Should NOT have queried for NULL-budget-id end users + # The invalidation walk must not reach for NULL-budget-id customers: they + # ride a default tier that is not expiring, so their spend stays put. find_many_calls = mock_prisma_client.db.litellm_endusertable.find_many_calls - assert len(find_many_calls) == 0 + assert [call["where"] for call in find_many_calls] == [ + {"budget_id": {"in": ["other-budget"]}, "user_id": {"gt": ""}} + ] litellm.max_end_user_budget_id = None @@ -1252,6 +1288,21 @@ def _make_counter_invalidation_job(monkeypatch): user_api_key_cache = MagicMock() user_api_key_cache.async_delete_cache = AsyncMock() + # Batch deletes fan out to the same per-key calls the real DualCache makes, + # so an assertion reads "this key was invalidated" whether the caller went + # one key at a time or a page at a time. + async def _delete_counter_keys(keys): + for key in keys: + spend_counter_cache.in_memory_cache.delete_cache(key=key) + await spend_counter_cache.redis_cache.async_delete_cache(key=key) + + async def _delete_management_keys(keys): + for key in keys: + await user_api_key_cache.async_delete_cache(key=key) + + spend_counter_cache.async_delete_cache_keys = AsyncMock(side_effect=_delete_counter_keys) + user_api_key_cache.async_delete_cache_keys = AsyncMock(side_effect=_delete_management_keys) + fake_module = types.ModuleType("litellm.proxy.proxy_server") fake_module.spend_counter_cache = spend_counter_cache fake_module.user_api_key_cache = user_api_key_cache @@ -1586,7 +1637,7 @@ def test_budget_table_reset_invalidates_enduser_counter_and_cache(reset_budget_j "user_id": "customer-42", }, ) - mock_prisma_client.data["enduser"] = [test_enduser] + mock_prisma_client.db.litellm_endusertable.set_find_many_results([test_enduser]) asyncio.run(reset_budget_job.reset_budget_for_litellm_budget_table()) @@ -1596,6 +1647,107 @@ def test_budget_table_reset_invalidates_enduser_counter_and_cache(reset_budget_j assert "end_user_id:customer-42" in deleted +def test_enduser_invalidation_is_paged_and_batched(reset_budget_job, mock_prisma_client, monkeypatch): + """The post-commit invalidation walk stays bounded in memory and in round trips. + + Reading every customer on an expiring tier into one result set puts a + customer-count-sized list in the proxy's heap on every tick, which is an OOM + on a large enough deployment rather than a slow tick. Awaiting one cache call + per customer makes the last customer wait out every customer ahead of it. + Both regress silently, so pin the page size, the strictly advancing cursor, + and one batched call per page. + """ + counter_cache: Final = _make_counter_invalidation_job(monkeypatch) + mock_prisma_client.data["budget"] = [_budget_row(budget_id="budget-1")] + population: Final = RESET_BUDGET_JOB_BATCH_SIZE * 2 + 3 + mock_prisma_client.db.litellm_endusertable.set_find_many_results( + [ + type("EndUser", (), {"user_id": f"cust-{i:06d}", "spend": 5.0, "budget_id": "budget-1"}) + for i in range(population) + ] + ) + + asyncio.run(reset_budget_job.reset_budget_for_litellm_budget_table()) + + reads: Final = mock_prisma_client.db.litellm_endusertable.find_many_calls + assert [read["take"] for read in reads] == [RESET_BUDGET_JOB_BATCH_SIZE] * 3 + assert [read["where"]["user_id"]["gt"] for read in reads] == [ + "", + f"cust-{RESET_BUDGET_JOB_BATCH_SIZE - 1:06d}", + f"cust-{RESET_BUDGET_JOB_BATCH_SIZE * 2 - 1:06d}", + ] + + assert counter_cache.async_delete_cache_keys.await_count == 3 + assert counter_cache.user_api_key_cache.async_delete_cache_keys.await_count == 3 + counter_cache.async_delete_cache.assert_not_called() + + invalidated: Final = { + key for call in counter_cache.async_delete_cache_keys.await_args_list for key in call.args[0] + } + assert invalidated == {f"spend:end_user:cust-{i:06d}" for i in range(population)} + evicted: Final = { + key for call in counter_cache.user_api_key_cache.async_delete_cache_keys.await_args_list for key in call.args[0] + } + assert evicted == {f"end_user_id:cust-{i:06d}" for i in range(population)} + + + +def test_enduser_invalidation_reports_a_page_read_failure_instead_of_a_clean_finish( + mock_prisma_client, monkeypatch +): + """A page that fails to read is not the end of the customer list. + + The tier's window is already advanced by the time this walk runs, so no later + tick comes back for the customers past the page that failed: their cached + spend goes on rejecting requests until it expires. Returning the same empty + page normal end-of-data returns hid that behind a report of a clean pass. + """ + _make_counter_invalidation_job(monkeypatch) + mock_prisma_client.data["budget"] = [_budget_row(budget_id="budget-1")] + endusers: Final = mock_prisma_client.db.litellm_endusertable + endusers.set_find_many_results( + [ + type("EndUser", (), {"user_id": f"cust-{i:06d}", "spend": 5.0, "budget_id": "budget-1"}) + for i in range(RESET_BUDGET_JOB_BATCH_SIZE + 3) + ] + ) + endusers.set_find_many_error(1, RuntimeError("connection reset while paging customers")) + logging_obj: Final = RecordingProxyLogging() + job: Final = ResetBudgetJob(proxy_logging_obj=logging_obj, prisma_client=mock_prisma_client) + + _run_and_drain_hooks(job.reset_budget_for_litellm_budget_table) + + metadata: Final = logging_obj.service_logging_obj.success_calls[0]["event_metadata"] + assert metadata["enduser_invalidation_truncated"] is True + assert metadata["num_endusers_updated"] == RESET_BUDGET_JOB_BATCH_SIZE + + +def test_a_failed_counter_batch_still_evicts_the_management_cache( + reset_budget_job, mock_prisma_client, monkeypatch +): + """The spend counters and the management cache are invalidated independently. + + Sharing one handler meant a Redis failure on the counters returned before the + management cache was touched at all. The commit has already zeroed those rows + by then, so the cached objects keep authorizing against their pre-reset spend + until they expire. + """ + counter_cache: Final = _make_counter_invalidation_job(monkeypatch) + counter_cache.async_delete_cache_keys = AsyncMock(side_effect=RuntimeError("redis unavailable")) + mock_prisma_client.data["budget"] = [_budget_row(budget_id="budget-1")] + mock_prisma_client.db.litellm_endusertable.set_find_many_results( + [type("EndUser", (), {"user_id": "customer-42", "spend": 5.0, "budget_id": "budget-1"})] + ) + + asyncio.run(reset_budget_job.reset_budget_for_litellm_budget_table()) + + evicted: Final = { + key + for call in counter_cache.user_api_key_cache.async_delete_cache_keys.await_args_list + for key in call.args[0] + } + assert "end_user_id:customer-42" in evicted + def test_budget_table_reset_commits_even_when_cache_eviction_fails(reset_budget_job, mock_prisma_client, monkeypatch): """Eviction runs after the commit, so a broken cache cannot undo the write.""" diff --git a/tests/test_litellm/proxy/common_utils/test_user_api_key_cache.py b/tests/test_litellm/proxy/common_utils/test_user_api_key_cache.py index 2d5d76ed542..f24175a1922 100644 --- a/tests/test_litellm/proxy/common_utils/test_user_api_key_cache.py +++ b/tests/test_litellm/proxy/common_utils/test_user_api_key_cache.py @@ -82,6 +82,19 @@ class FakeRedisCache(RedisCache): async def async_delete_cache(self, key: str): # type: ignore[override] self._store.pop(key, None) + async def delete_cache_keys(self, keys): # type: ignore[override] + for key in keys: + self._store.pop(key, None) + + +class PartitionFailingRedisCache(FakeRedisCache): + """Fails the batch delete for the key-object partition and no other.""" + + async def delete_cache_keys(self, keys): # type: ignore[override] + if any(is_user_key_cache_key(key) for key in keys): + raise ConnectionError("redis unavailable") + await super().delete_cache_keys(keys) + def _make_key_obj(token: str = "tok") -> UserAPIKeyAuth: # Minimal object (UserAPIKeyAuth inherits token from base view). @@ -331,6 +344,46 @@ class TestUserKeyObjectPartition: assert await cache.async_get_cache(HASHED_TOKEN, model_type=UserAPIKeyAuth) is None assert await redis.async_get_cache(HASHED_TOKEN) is None + @pytest.mark.asyncio + async def test_batch_delete_routes_each_key_to_its_partition(self): + """A batch delete has to clear the same partition the single delete does. + + ``DualCache``'s batch delete only knows about the main in-memory cache, so + inheriting it unchanged leaves a key object sitting in ``key_object_cache`` + with its pre-reset spend, and the next request is authorized against that + stale copy until the local entry expires. + """ + redis = FakeRedisCache() + cache = UserApiKeyCache(redis_cache=redis) + await cache.async_set_cache(HASHED_TOKEN, _make_key_obj(HASHED_TOKEN), model_type=UserAPIKeyAuth) + await cache.async_set_cache(end_user_cache_key("u1"), {"user_id": "u1"}) + + await cache.async_delete_cache_keys([HASHED_TOKEN, end_user_cache_key("u1")]) + + assert await cache.async_get_cache(HASHED_TOKEN, model_type=UserAPIKeyAuth) is None + assert await cache.async_get_cache(end_user_cache_key("u1")) is None + assert await redis.async_get_cache(HASHED_TOKEN) is None + assert await redis.async_get_cache(end_user_cache_key("u1")) is None + + @pytest.mark.asyncio + async def test_batch_delete_clears_the_other_partition_when_one_fails(self): + """One partition failing must not cost the other its deletions. + + A caller batching these has already committed the rows they cache, so a + partition that is skipped keeps authorizing against pre-reset spend until + the entry expires. The failure is still raised for the caller to report. + """ + redis = PartitionFailingRedisCache() + cache = UserApiKeyCache(redis_cache=redis) + await cache.async_set_cache(HASHED_TOKEN, _make_key_obj(HASHED_TOKEN), model_type=UserAPIKeyAuth) + await cache.async_set_cache(end_user_cache_key("u1"), {"user_id": "u1"}) + + with pytest.raises(ConnectionError): + await cache.async_delete_cache_keys([HASHED_TOKEN, end_user_cache_key("u1")]) + + assert await cache.async_get_cache(end_user_cache_key("u1")) is None + assert await redis.async_get_cache(end_user_cache_key("u1")) is None + @pytest.mark.asyncio async def test_pipeline_write_routes_each_entry_to_its_partition(self): cache = UserApiKeyCache(in_memory_cache=InMemoryCache(max_size_in_memory=2)) diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py index 1072e970094..7663bd83790 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py +++ b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py @@ -1049,6 +1049,27 @@ def test_get_logging_payload_replaces_rejected_or_prompt_shaped_models_with_the_ assert payload["model"] == expected_model +@pytest.mark.parametrize("requested_model", [{"bad": "value"}, ["gpt-5.2"], 1]) +def test_get_logging_payload_replaces_a_non_string_model_with_the_placeholder( + requested_model: dict[str, str] | list[str] | int, +): + kwargs: Final = { + "model": requested_model, + "messages": [{"role": "user", "content": "hi"}], + "call_type": "acompletion", + "litellm_params": {"metadata": {"user_api_key": "sk-test", "status": "failure"}}, + } + + payload: Final = get_logging_payload( + kwargs=kwargs, + response_obj=ValueError("model must be a string"), + start_time=datetime.datetime.now(timezone.utc), + end_time=datetime.datetime.now(timezone.utc), + ) + + assert payload["model"] == UNKNOWN_MODEL_SPEND_LOG_MODEL + + @pytest.mark.parametrize( ("metadata", "response_obj"), [ diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py index 4ac687625c2..d465deace15 100644 --- a/tests/test_litellm/proxy/test_common_request_processing.py +++ b/tests/test_litellm/proxy/test_common_request_processing.py @@ -327,6 +327,35 @@ class TestProxyBaseLLMRequestProcessing: pytest.fail("litellm_call_id is not a valid UUID") assert data_passed["litellm_call_id"] == returned_data["litellm_call_id"] + @pytest.mark.asyncio + @pytest.mark.parametrize("requested_model", [{"bad": "value"}, ["gpt-5.2"], 1]) + async def test_common_processing_pre_call_logic_rejects_a_non_string_model_with_400( + self, monkeypatch, requested_model: dict[str, str] | list[str] | int + ): + processing_obj = ProxyBaseLLMRequestProcessing( + data={"model": requested_model, "messages": [{"role": "user", "content": "hi"}]} + ) + mock_request = MagicMock(spec=Request) + mock_request.headers = {} + add_litellm_data_to_request = AsyncMock() + monkeypatch.setattr( + litellm.proxy.common_request_processing, "add_litellm_data_to_request", add_litellm_data_to_request + ) + + with pytest.raises(ProxyException) as exc_info: + await processing_obj.common_processing_pre_call_logic( + request=mock_request, + general_settings={}, + user_api_key_dict=MagicMock(spec=UserAPIKeyAuth), + proxy_logging_obj=MagicMock(spec=ProxyLogging), + proxy_config=MagicMock(spec=ProxyConfig), + route_type="acompletion", + ) + + assert exc_info.value.code == str(status.HTTP_400_BAD_REQUEST) + assert exc_info.value.param == "model" + add_litellm_data_to_request.assert_not_awaited() + @pytest.mark.asyncio async def test_common_processing_pre_call_logic_refreshes_proxy_server_request_body_after_guardrails( self, monkeypatch diff --git a/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py b/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py index 44572aed08e..e157c982105 100644 --- a/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py +++ b/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py @@ -4,15 +4,23 @@ Static checks that every proxy Docker image installs the `bedrock-realtime` extr Bedrock Nova Sonic speech-to-speech (`/v1/realtime`) needs `aws-sdk-bedrock-runtime`, which only ships in the `bedrock-realtime` extra. An image whose `uv sync` stages omit the extra fails every Nova Sonic realtime session with -"Missing aws_sdk_bedrock_runtime. Install with: pip install aws-sdk-bedrock-runtime". +"Missing aws_sdk_bedrock_runtime: pip install 'litellm[bedrock-realtime]' ...". """ import os import re +import sys from typing import Final import pytest +from litellm.constants import BEDROCK_REALTIME_SDK_DISTRIBUTION, BEDROCK_REALTIME_SDK_SUPPORTED_RANGE + +if sys.version_info >= (3, 11): + import tomllib +else: + import tomli as tomllib + REPO_ROOT: Final = os.path.join(os.path.dirname(__file__), "..", "..") PROXY_DOCKERFILES: Final = ( @@ -54,3 +62,16 @@ def test_every_uv_sync_installs_bedrock_realtime_extra(relative_path: str): "`--extra bedrock-realtime`, so aws-sdk-bedrock-runtime is absent and Bedrock Nova Sonic " "/v1/realtime sessions fail with 'Missing aws_sdk_bedrock_runtime'" ) + + +def test_bedrock_realtime_extra_pins_the_range_named_in_the_runtime_error(): + with open(os.path.join(REPO_ROOT, "pyproject.toml"), "rb") as f: + extra_specs: Final = tomllib.load(f)["project"]["optional-dependencies"]["bedrock-realtime"] + + sdk_specs: Final = tuple(spec for spec in extra_specs if spec.startswith(BEDROCK_REALTIME_SDK_DISTRIBUTION)) + assert len(sdk_specs) == 1, f"expected exactly one {BEDROCK_REALTIME_SDK_DISTRIBUTION} spec, got {extra_specs}" + requirement: Final = sdk_specs[0].split(";")[0].strip() + assert requirement == f"{BEDROCK_REALTIME_SDK_DISTRIBUTION}[awscrt]{BEDROCK_REALTIME_SDK_SUPPORTED_RANGE}", ( + f"pyproject pins {requirement!r} but the handler's install hint names " + f"{BEDROCK_REALTIME_SDK_SUPPORTED_RANGE!r} with the awscrt extra; keep them in sync" + ) diff --git a/tests/test_litellm/test_together_ai_model_metadata.py b/tests/test_litellm/test_together_ai_model_metadata.py index 88d6db0d8b0..7176ba4f219 100644 --- a/tests/test_litellm/test_together_ai_model_metadata.py +++ b/tests/test_litellm/test_together_ai_model_metadata.py @@ -95,7 +95,7 @@ def _successor(info: dict[str, object]) -> str | None: return successor if isinstance(successor, str) else None -def test_together_successor_metadata_points_at_live_models(cost_map: CostMap): +def test_together_successor_metadata_points_at_known_models(cost_map: CostMap): successors = { model: successor for model, info in cost_map.items() @@ -103,9 +103,7 @@ def test_together_successor_metadata_points_at_live_models(cost_map: CostMap): } assert len(successors) >= 10 for model, successor in successors.items(): - target = cost_map.get(successor) - assert target is not None, f"{model} names successor {successor} that is not in the map" - assert "deprecation_date" not in target, f"{model} names deprecated successor {successor}" + assert successor in cost_map, f"{model} names successor {successor} that is not in the map" def test_together_backup_cost_map_in_sync(cost_map: CostMap): diff --git a/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.test.tsx b/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.test.tsx index 7f343211596..ff5e736306a 100644 --- a/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.test.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.test.tsx @@ -1,7 +1,7 @@ import React from "react"; import { describe, it, expect, vi, beforeEach } from "vitest"; import userEvent from "@testing-library/user-event"; -import { renderWithProviders, screen, waitFor } from "../../../../tests/test-utils"; +import { renderWithProviders, screen, waitFor, within } from "../../../../tests/test-utils"; import { GuardrailInformation, makeBedrockResponse, @@ -24,6 +24,42 @@ const skippedPreCall: Partial = { duration: null, }; +const untimedPreCall: Partial = { + guardrail_name: "conduct", + guardrail_status: "success", + guardrail_mode: "pre_call", + start_time: null, + end_time: null, + duration: null, +}; + +const timedPreCall: Partial = { + guardrail_name: "timed-pre-rail", + guardrail_status: "success", + guardrail_mode: "pre_call", + start_time: 1_700_000_000, + end_time: 1_700_000_000.1, + duration: 0.1, +}; + +const latePreCall: Partial = { + guardrail_name: "late-pre-rail", + guardrail_status: "success", + guardrail_mode: "pre_call", + start_time: 1_700_000_500, + end_time: 1_700_000_500.1, + duration: 0.1, +}; + +const untimedPostCall: Partial = { + guardrail_name: "untimed-post-rail", + guardrail_status: "success", + guardrail_mode: "post_call", + start_time: null, + end_time: null, + duration: null, +}; + const ranPostCall: Partial = { guardrail_name: "ran-rail", guardrail_status: "success", @@ -98,6 +134,67 @@ describe("GuardrailViewer", () => { expect(screen.getByText("—")).toBeInTheDocument(); }); + it("keeps a guardrail that ran without any timing on the lifecycle", () => { + renderWithProviders(); + + expect(screen.getByText("Request received")).toBeInTheDocument(); + expect(screen.getByText(/Pre-call guardrail: conduct/)).toBeInTheDocument(); + expect(screen.getByText("LLM call")).toBeInTheDocument(); + expect(screen.getByText("Response returned")).toBeInTheDocument(); + expect(screen.queryByText(/^T\+/)).not.toBeInTheDocument(); + }); + + it("keeps an untimed guardrail ahead of a timed one recorded after it in the same phase", () => { + const untimed = makeGuardrailInformation(untimedPreCall); + const timedPre = makeGuardrailInformation(timedPreCall); + renderWithProviders(); + + const rows = screen.getAllByTestId("lifecycle-row"); + const rowIndex = (label: RegExp): number => rows.findIndex((r) => within(r).queryByText(label) !== null); + const untimedIndex = rowIndex(/Pre-call guardrail: conduct/); + const timedIndex = rowIndex(/Pre-call guardrail: timed-pre-rail/); + + expect(untimedIndex).toBeGreaterThanOrEqual(0); + expect(timedIndex).toBeGreaterThanOrEqual(0); + expect(untimedIndex).toBeLessThan(timedIndex); + }); + + it("orders each phase on its own clock when a later pre-call outlives an earlier post-call", () => { + const latePre = makeGuardrailInformation(latePreCall); + const untimedPost = makeGuardrailInformation(untimedPostCall); + const earlyPost = makeGuardrailInformation(ranPostCall); + renderWithProviders(); + + const rows = screen.getAllByTestId("lifecycle-row"); + const rowIndex = (label: RegExp): number => rows.findIndex((r) => within(r).queryByText(label) !== null); + const untimedIndex = rowIndex(/Post-call guardrail: untimed-post-rail/); + const earlyIndex = rowIndex(/Post-call guardrail: ran-rail/); + + expect(untimedIndex).toBeGreaterThanOrEqual(0); + expect(earlyIndex).toBeGreaterThanOrEqual(0); + expect(untimedIndex).toBeLessThan(earlyIndex); + }); + + it("anchors offsets on the timed entries and gives the untimed one no fabricated offset", () => { + const untimed = makeGuardrailInformation(untimedPreCall); + const ran = makeGuardrailInformation(ranPostCall); + renderWithProviders(); + + const lifecycleRow = (label: string | RegExp): HTMLElement => { + const row = screen.getAllByTestId("lifecycle-row").find((r) => within(r).queryByText(label) !== null); + if (row === undefined) throw new Error(`no lifecycle row labelled ${label}`); + return row; + }; + + expect(within(lifecycleRow("Request received")).getByText("T+0ms")).toBeInTheDocument(); + expect(within(lifecycleRow(/Post-call guardrail: ran-rail/)).getByText("T+250ms")).toBeInTheDocument(); + expect(within(lifecycleRow("Response returned")).getByText("T+251ms")).toBeInTheDocument(); + + const untimedRow = within(lifecycleRow(/Pre-call guardrail: conduct/)); + expect(untimedRow.getByText("—")).toBeInTheDocument(); + expect(untimedRow.queryByText(/^T\+/)).not.toBeInTheDocument(); + }); + it("calculates and displays masked entity totals", async () => { const user = userEvent.setup(); const data = makeGuardrailInformation({ diff --git a/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.tsx b/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.tsx index 1de0e3878b2..58076ef6c00 100644 --- a/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/GuardrailViewer/GuardrailViewer.tsx @@ -361,7 +361,7 @@ const GenericGuardrailResponse = ({ response }: { response: any }) => { interface TimelineEntry { type: "request" | "guardrail" | "llm" | "response"; label: string; - offsetMs: number; + offsetMs: number | null; outcome?: EntryOutcome; } @@ -370,73 +370,85 @@ type TimedGuardrailInformation = GuardrailInformation & { start_time: number; en const isTimed = (e: GuardrailInformation): e is TimedGuardrailInformation => typeof e.start_time === "number" && typeof e.end_time === "number"; +const belongsOnLifecycle = (e: GuardrailInformation): boolean => isTimed(e) || getEntryOutcome(e) !== "not_run"; + +// Sorts a phase's timed entries by start time while leaving its untimed entries in the +// slots they were recorded in. Applied per phase, never globally: an entry can land in +// more than one phase bucket, so a global pass can reorder one phase by another's clock. +const orderWithinPhase = (group: GuardrailInformation[]): GuardrailInformation[] => { + const byStart = group.filter(isTimed).sort((a, b) => a.start_time - b.start_time); + const timedSlots = new Map(group.flatMap((e, i) => (isTimed(e) ? [i] : [])).map((slot, k) => [slot, byStart[k]])); + return group.map((e, i) => timedSlots.get(i) ?? e); +}; + const RequestLifecycle = ({ entries }: { entries: GuardrailInformation[] }) => { - const sorted = useMemo(() => entries.filter(isTimed).sort((a, b) => a.start_time - b.start_time), [entries]); + const sorted = useMemo(() => entries.filter(belongsOnLifecycle), [entries]); const timeline = useMemo(() => { if (sorted.length === 0) return []; - const baseTime = sorted[0].start_time; + const timed = sorted.filter(isTimed); + const baseTime = timed.length > 0 ? Math.min(...timed.map((e) => e.start_time)) : null; + const offsetOf = (e: GuardrailInformation): number | null => + baseTime === null || !isTimed(e) ? null : Math.round((e.end_time - baseTime) * 1000); const items: TimelineEntry[] = []; // Request received - items.push({ type: "request", label: "Request received", offsetMs: 0 }); + items.push({ type: "request", label: "Request received", offsetMs: baseTime === null ? null : 0 }); // Pre-call guardrails — use modeMatches so array modes (e.g. ["pre_call", "post_call"]) // place the entry in every matching bucket. - const preCalls = sorted.filter((e) => modeMatches(e.guardrail_mode, "pre_call")); - const postCalls = sorted.filter( - (e) => modeMatches(e.guardrail_mode, "post_call") || modeMatches(e.guardrail_mode, "logging_only"), + const preCalls = orderWithinPhase(sorted.filter((e) => modeMatches(e.guardrail_mode, "pre_call"))); + const postCalls = orderWithinPhase( + sorted.filter((e) => modeMatches(e.guardrail_mode, "post_call") || modeMatches(e.guardrail_mode, "logging_only")), ); - const duringCalls = sorted.filter((e) => modeMatches(e.guardrail_mode, "during_call")); + const duringCalls = orderWithinPhase(sorted.filter((e) => modeMatches(e.guardrail_mode, "during_call"))); for (const e of preCalls) { - const offsetMs = Math.round((e.end_time - baseTime) * 1000); items.push({ type: "guardrail", label: `Pre-call guardrail: ${getDisplayName(e)}`, - offsetMs, + offsetMs: offsetOf(e), outcome: getEntryOutcome(e), }); } // LLM call — infer from gap between pre-call end and post-call start - const lastPreEnd = preCalls.length > 0 ? Math.max(...preCalls.map((e) => e.end_time)) : baseTime; - const firstPostStart = postCalls.length > 0 ? Math.min(...postCalls.map((e) => e.start_time)) : undefined; - const llmEndTime = firstPostStart ?? lastPreEnd + 1; - const llmOffsetMs = Math.round((llmEndTime - baseTime) * 1000); + const timedPre = preCalls.filter(isTimed); + const timedPost = postCalls.filter(isTimed); + const lastPreEnd = timedPre.length > 0 ? Math.max(...timedPre.map((e) => e.end_time)) : baseTime; + const firstPostStart = timedPost.length > 0 ? Math.min(...timedPost.map((e) => e.start_time)) : undefined; + const llmEndTime = firstPostStart ?? (lastPreEnd === null ? null : lastPreEnd + 1); items.push({ type: "llm", label: "LLM call", - offsetMs: llmOffsetMs, + offsetMs: llmEndTime === null || baseTime === null ? null : Math.round((llmEndTime - baseTime) * 1000), }); // During-call guardrails (rare) for (const e of duringCalls) { - const offsetMs = Math.round((e.end_time - baseTime) * 1000); items.push({ type: "guardrail", label: `During-call guardrail: ${getDisplayName(e)}`, - offsetMs, + offsetMs: offsetOf(e), outcome: getEntryOutcome(e), }); } // Post-call guardrails for (const e of postCalls) { - const offsetMs = Math.round((e.end_time - baseTime) * 1000); items.push({ type: "guardrail", label: `Post-call guardrail: ${getDisplayName(e)}`, - offsetMs, + offsetMs: offsetOf(e), outcome: getEntryOutcome(e), }); } // Response returned - const maxEnd = Math.max(...sorted.map((e) => e.end_time)); - const responseOffsetMs = Math.round((maxEnd - baseTime) * 1000) + 1; + const maxEnd = timed.length > 0 ? Math.max(...timed.map((e) => e.end_time)) : null; + const responseOffsetMs = maxEnd === null || baseTime === null ? null : Math.round((maxEnd - baseTime) * 1000) + 1; items.push({ type: "response", label: "Response returned", offsetMs: responseOffsetMs }); return items; @@ -447,7 +459,7 @@ const RequestLifecycle = ({ entries }: { entries: GuardrailInformation[] }) => {

Request Lifecycle

{timeline.map((item, idx) => ( -
+
{/* Vertical line */}
@@ -475,7 +487,9 @@ const RequestLifecycle = ({ entries }: { entries: GuardrailInformation[] }) => { {OUTCOME_LABEL[item.outcome]} )} - T+{item.offsetMs}ms + + {item.offsetMs === null ? "—" : `T+${item.offsetMs}ms`} +
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