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refactor(types): replace Any with proven types in 8 files (#43551)
* refactor(types): replace Any with proven types in 8 files Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(types): keep email logger untyped where its alert types differ Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
devin-ai-integration[bot]
GitHub
parent
90e4962c81
commit
2c9b0e00ac
8 changed files with 112 additions and 79 deletions
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@ -2287,7 +2287,7 @@ class Logging(LiteLLMLoggingBaseClass):
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self.completion_start_time = completion_start_time
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self.model_call_details["completion_start_time"] = self.completion_start_time
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def normalize_logging_result(self, result: Any) -> object:
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def normalize_logging_result(self, result: object) -> object:
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"""
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Some endpoints return a different type of result than what is expected by the logging system.
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This function is used to normalize the result to the expected type.
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@ -2736,7 +2736,7 @@ class Logging(LiteLLMLoggingBaseClass):
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start_time: datetime.datetime | None = None,
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end_time: datetime.datetime | None = None,
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cache_hit: bool | None = None,
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**kwargs: Any, # kwargs-ok: forwarded to _success_handler_body
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**kwargs: object, # kwargs-ok: forwarded to _success_handler_body
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) -> None:
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"""Restores trace_id/session_id contextvars once this attempt's own success
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logging (including any nested calls its callbacks trigger) is fully done."""
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@ -3175,7 +3175,7 @@ class Logging(LiteLLMLoggingBaseClass):
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start_time: datetime.datetime | None = None,
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end_time: datetime.datetime | None = None,
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cache_hit: bool | None = None,
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**kwargs: Any, # kwargs-ok: forwarded to _async_success_handler_body
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**kwargs: object, # kwargs-ok: forwarded to _async_success_handler_body
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) -> None:
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"""Restores trace_id/session_id contextvars once this attempt's own success
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logging (including any nested calls its callbacks trigger) is fully done."""
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@ -3554,7 +3554,7 @@ class Logging(LiteLLMLoggingBaseClass):
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)
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self._handle_callback_failure(callback=callback)
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def _handle_callback_failure(self, callback: Any):
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def _handle_callback_failure(self, callback: object):
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"""
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Handle callback logging failures by incrementing Prometheus metrics.
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@ -3959,10 +3959,10 @@ class Logging(LiteLLMLoggingBaseClass):
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def handle_sync_success_callbacks_for_async_calls(
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self,
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result: Any,
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result: object,
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start_time: datetime.datetime,
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end_time: datetime.datetime,
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cache_hit: Any | None = None,
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cache_hit: object | None = None,
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) -> None:
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"""
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Handles calling success callbacks for Async calls.
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@ -4132,10 +4132,10 @@ class Logging(LiteLLMLoggingBaseClass):
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response so cost calculation and spend tracking see one shape.
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"""
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if result.event_type == "interaction.completed" and result.interaction is not None:
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return InteractionsAPIResponse(**result.interaction)
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return InteractionsAPIResponse.model_validate(result.interaction)
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if result.status == "completed":
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return InteractionsAPIResponse(
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**result.model_dump(
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return InteractionsAPIResponse.model_validate(
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result.model_dump(
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exclude={ # mutable-ok: pydantic types exclude as set[str], which a frozenset does not satisfy
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"event_type",
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"delta",
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@ -4165,7 +4165,7 @@ class Logging(LiteLLMLoggingBaseClass):
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return logged
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return logged.model_copy(update={"id": streamed_message_id})
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def _handle_anthropic_messages_response_logging(self, result: Any) -> ModelResponse:
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def _handle_anthropic_messages_response_logging(self, result: object) -> ModelResponse:
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"""
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Handles logging for Anthropic messages responses.
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@ -4274,7 +4274,7 @@ class Logging(LiteLLMLoggingBaseClass):
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)
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return model_response
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def _handle_non_streaming_google_genai_generate_content_response_logging(self, result: Any) -> ModelResponse:
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def _handle_non_streaming_google_genai_generate_content_response_logging(self, result: object) -> ModelResponse:
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"""
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Handles logging for Google GenAI generate content responses.
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"""
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@ -4349,7 +4349,7 @@ def _get_masked_values(
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"passwd",
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]
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def _mask_value(v: Any) -> Any:
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def _mask_value(v: object) -> object:
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if isinstance(v, dict):
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if _depth >= _max_depth:
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return v
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@ -1,10 +1,10 @@
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import asyncio
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import json
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import ssl
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from collections.abc import AsyncGenerator, AsyncIterator, Coroutine, Iterator, Mapping, Sequence
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from collections.abc import AsyncGenerator, AsyncIterator, Awaitable, Coroutine, Iterator, Mapping, Sequence
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from contextlib import asynccontextmanager
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from functools import lru_cache
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from types import MappingProxyType, ModuleType
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from types import MappingProxyType
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from typing import (
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TYPE_CHECKING,
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Any,
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@ -239,6 +239,26 @@ class _ResponsesClientWebSocket(Protocol):
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async def close(self, code: int = ..., reason: str | None = ...) -> None: ...
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class _WebsocketsExceptions(Protocol):
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@property
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def WebSocketException(self) -> type[Exception]: ...
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class _WebsocketsModule(Protocol):
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@property
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def exceptions(self) -> _WebsocketsExceptions: ...
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def connect(
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self,
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uri: str,
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*,
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additional_headers: Mapping[str, str],
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max_size: int | None,
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ssl: bool | str | ssl.SSLContext,
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open_timeout: float,
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) -> Awaitable["ClientConnection"]: ...
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_ResponseT = TypeVar("_ResponseT")
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@ -5468,7 +5488,7 @@ class BaseLLMHTTPHandler:
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max_loops: int,
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fingerprints: list[str],
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fingerprint: str,
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) -> Any:
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) -> ModelResponse | CustomStreamWrapper:
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patch: Final = plan.request_patch or AgenticLoopRequestPatch()
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if patch.messages is None:
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raise ValueError("Agentic loop plan missing patched messages")
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@ -5978,7 +5998,7 @@ class BaseLLMHTTPHandler:
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@staticmethod
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async def _open_realtime_backend_ws(
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websockets_module: ModuleType,
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websockets_module: _WebsocketsModule,
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url: str,
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headers: dict,
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ssl_context: bool | str | ssl.SSLContext,
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@ -6037,7 +6057,7 @@ class BaseLLMHTTPHandler:
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headers: dict,
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api_base: str | None = None,
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api_key: str | None = None,
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client: Any | None = None,
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client: object | None = None,
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timeout: float | None = None,
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user_api_key_dict: object | None = None,
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litellm_metadata: dict[str, object] | None = None,
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@ -3,7 +3,7 @@ import contextlib
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import json
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import logging
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import math
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from collections.abc import AsyncGenerator, Awaitable, Callable, Mapping, Sequence
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from collections.abc import AsyncGenerator, Awaitable, Callable, Coroutine, Mapping, Sequence
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from datetime import datetime
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from functools import lru_cache
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from types import MappingProxyType
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@ -974,7 +974,7 @@ _NO_GENERAL_SETTINGS: Final[Mapping[str, object]] = MappingProxyType({})
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async def create_response(
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generator: AsyncGenerator[str, None],
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generator: AsyncGenerator[str, None] | Coroutine[object, object, AsyncGenerator[str, None]],
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media_type: str,
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headers: Mapping[str, str],
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default_status_code: int = status.HTTP_200_OK,
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@ -4166,7 +4166,7 @@ class ProxyBaseLLMRequestProcessing:
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)
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@staticmethod
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def _stream_usage_for_event(obj: Mapping[str, object], usage: Mapping[str, Any]) -> Usage | None:
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def _stream_usage_for_event(obj: Mapping[str, object], usage: Mapping[str, object]) -> Usage | None:
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# Anthropic reports input_tokens excluding cache tokens, so reuse the non-streaming
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# transformation to total the prompt and keep the 5m/1h cache creation split
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if obj.get("type") == "message_delta":
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@ -2550,7 +2550,7 @@ def general_settings_view() -> Mapping[str, object]:
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return _GENERAL_SETTINGS_VIEW.validate_python(general_settings)
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config_passthrough_endpoints: list[dict[str, Any]] | None = None
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config_passthrough_endpoints: list[dict[str, object]] | None = None
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log_file: Final = "api_log.json"
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worker_config: Final = None
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master_key: str | None = None
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@ -2584,7 +2584,7 @@ use_queue = False
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health_check_interval = None
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health_check_concurrency = None
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health_check_details = None
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health_check_results: dict[str, int | list[dict[str, Any]]] = {}
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health_check_results: dict[str, int | list[dict[str, object]]] = {}
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background_health_check_loop_active = False
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background_health_check_cycle_seq = 0
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queue: Final[list] = []
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@ -13640,7 +13640,7 @@ async def _try_provider_token_count(
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model_to_use: str,
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messages: list | None,
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contents: list | None,
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deployment: dict[str, Any] | None,
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deployment: dict[str, object] | None,
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request_model: str,
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tools: list | None = None,
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system: str | None = None,
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@ -14439,7 +14439,7 @@ async def _fetch_db_models_for_search(
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sort_by: str | None,
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is_byok_outside_caller_teams: Callable[[dict[str, JsonValue]], bool],
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model_name: str | None = None,
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) -> tuple[list[dict[str, Any]], int]:
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) -> tuple[list[dict[str, object]], int]:
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"""
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Run the bounded DB query that backs `/v2/model/info?search=`. Returns
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`(decrypted_models, total_count)` where `total_count` is the cheap
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@ -14586,7 +14586,7 @@ async def _apply_search_filter_to_models(
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router_models_count: Final = config_models_count + db_models_in_router_count
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# Query database for additional models with search term
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db_models: list[dict[str, Any]] = []
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db_models: list[dict[str, object]] = []
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exact_name_can_match: Final = model_name is None or search_lower in model_name.lower()
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if prisma_client is not None and exact_name_can_match:
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try:
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@ -14781,7 +14781,7 @@ def _matches_model_info_filters(
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def _paginate_models_response(
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all_models: list[dict[str, Any]],
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all_models: Sequence[Mapping[str, object]],
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page: int,
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size: int,
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total_count: int | None,
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@ -303,6 +303,29 @@ class _EndUserSpendBatch(Protocol):
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def litellm_endusertable(self) -> _EndUserBatchTable: ...
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class _BatchUpdateTable(Protocol):
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def update(self, *, where: Mapping[str, object], data: Mapping[str, object]) -> None: ...
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class _UpdateManyBatch(Protocol):
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@property
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def litellm_verificationtoken(self) -> _BatchUpdateTable: ...
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@property
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def litellm_usertable(self) -> _EndUserBatchTable: ...
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@property
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def litellm_endusertable(self) -> _EndUserBatchTable: ...
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@property
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def litellm_budgettable(self) -> _EndUserBatchTable: ...
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@property
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def litellm_teamtable(self) -> _EndUserBatchTable: ...
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async def commit(self) -> None: ...
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unified_guardrail: Final = UnifiedLLMGuardrails()
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NON_OPENAI_STREAM_GUARDRAIL_TRANSLATION_CALL_TYPES: "frozenset[CallTypes]" = frozenset({CallTypes.anthropic_messages})
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@ -1111,7 +1134,7 @@ class _CallbackCapabilities:
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# Tuple[(resolved_callback, "override" | "apply_guardrail"), ...]
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# Ordered the same as ``litellm.callbacks``; used to build the streaming
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# iterator chain without re-scanning per request.
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iterator_overrides: tuple[tuple[Any, str], ...] = field(default_factory=tuple)
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iterator_overrides: tuple[tuple[CustomLogger, str], ...] = field(default_factory=tuple)
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# Resolved CustomLogger callbacks in original order. Pre-resolving once
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# avoids the per-request ``get_custom_logger_compatible_class`` walk for
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# every string entry in ``litellm.callbacks``.
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@ -2761,7 +2784,7 @@ class ProxyLogging:
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has_pre_call_override = False
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has_content_enforcer = False
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has_moderation_override = False
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iterator_overrides: Final[list[tuple[Any, str]]] = [] # (callback, kind)
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iterator_overrides: Final[list[tuple[CustomLogger, str]]] = [] # (callback, kind)
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resolved_callbacks: Final[list[CustomLogger]] = []
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for callback in callbacks:
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@ -5481,7 +5504,7 @@ class PrismaClient:
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"""
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Batch write update queries
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"""
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batcher = self.db.batch_()
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batcher: _UpdateManyBatch = self.db.batch_()
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for idx, t in enumerate(data_list):
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# check if plain text or hash
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if t.token.startswith("sk-"):
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@ -6638,7 +6661,7 @@ class PrismaClient:
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read-only as a whole (replica, failover in progress) does not get its
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engine killed on every watchdog cycle or failed write."""
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backoff_seconds: Final = min(
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self._db_reconnect_cooldown_seconds * 2 ** min(self._db_read_only_recreate_streak, 10),
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self._db_reconnect_cooldown_seconds * (1 << min(self._db_read_only_recreate_streak, 10)),
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_READ_ONLY_RECREATE_BACKOFF_CAP_SECONDS,
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)
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if time.time() - self._db_read_only_recreate_ts < backoff_seconds:
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@ -7344,7 +7367,7 @@ class ProxyUpdateSpend:
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if i >= n_retry_times:
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await requeue_spend_logs(prisma_client, proxy_logging_obj, logs_to_process)
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raise
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await asyncio.sleep(2**i)
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await asyncio.sleep(1 << i)
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except Exception as e:
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_raise_failed_update_spend_exception(e=e, start_time=start_time, proxy_logging_obj=proxy_logging_obj)
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finally:
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@ -981,7 +981,7 @@ def _responses_try_dispatch_mcp_gateway(
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background: bool | None,
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stream: bool | None,
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temperature: float | None,
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text: Any,
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text: Optional["ResponseText"],
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tool_choice: ToolChoice | None,
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top_p: float | None,
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truncation: Literal["auto", "disabled"] | None,
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@ -1054,7 +1054,7 @@ def _responses_try_dispatch_emulated_file_search(
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background: bool | None,
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stream: bool | None,
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temperature: float | None,
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text: Any,
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text: Optional["ResponseText"],
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tool_choice: ToolChoice | None,
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top_p: float | None,
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truncation: Literal["auto", "disabled"] | None,
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|
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@ -433,6 +433,7 @@ def model_info_is_active_for_environment(model_info: Mapping[str, object] | None
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_PreRoutingStrategyT = TypeVar("_PreRoutingStrategyT")
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_CallbackT = TypeVar("_CallbackT")
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_ALIAS_PARAMS_NEVER_FORWARDED: Final = frozenset({"model", "api_base", "api_key", "api_version"})
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_ALIAS_MARKER_FORWARDED_PARAMS_KWARG: Final = "_alias_marker_forwarded_params"
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@ -2217,8 +2218,8 @@ class Router:
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def _add_encrypted_content_affinity_check(self, enable_global_affinity: bool) -> None:
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def _move_before_deployment_affinity(
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callback_list: list[Any],
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callback_to_move: EncryptedContentAffinityCheck,
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callback_list: list[_CallbackT],
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callback_to_move: _CallbackT,
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) -> None:
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if callback_to_move not in callback_list:
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return
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|
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@ -681,7 +681,7 @@ def load_credentials_from_list(kwargs: dict):
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Updates kwargs with the credentials if credential_name in kwarg
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"""
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# Access CredentialAccessor via module to trigger lazy loading if needed
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credential_accessor: Final[type[CredentialAccessor]] = getattr(sys.modules[__name__], "CredentialAccessor")
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credential_accessor: Final[type[CredentialAccessor]] = litellm_utils.CredentialAccessor
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credential_name: Final = kwargs.get("litellm_credential_name")
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if not credential_name:
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@ -1015,9 +1015,7 @@ def function_setup(
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len(litellm.input_callback) > 0 or len(litellm.success_callback) > 0 or len(litellm.failure_callback) > 0
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) and len(callback_list) == 0:
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callback_list = list(set(litellm.input_callback + litellm.success_callback + litellm.failure_callback))
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get_set_callbacks: Final[Callable[[], Callable[..., None]]] = getattr(
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sys.modules[__name__], "get_set_callbacks"
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)
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get_set_callbacks: Final[Callable[[], Callable[..., None]]] = litellm_utils.get_set_callbacks
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get_set_callbacks()(callback_list=callback_list, function_id=function_id)
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## ASYNC CALLBACKS - safety net for callbacks added via direct append
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if len(litellm.input_callback) > 0:
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@ -1262,9 +1260,7 @@ def function_setup(
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call_type=call_type,
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):
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stream = True
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get_litellm_logging_class: Final[_LoggingClassGetter] = getattr(
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sys.modules[__name__], "get_litellm_logging_class"
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)
|
||||
get_litellm_logging_class: Final[_LoggingClassGetter] = litellm_utils.get_litellm_logging_class
|
||||
# Victim for object pool
|
||||
logging_obj = get_litellm_logging_class()( # rebind-ok: 2nd assignment to logging_obj (see initial None above)
|
||||
model=model,
|
||||
|
|
@ -1413,8 +1409,8 @@ def _get_wrapper_num_retries(kwargs: dict[str, Any], exception: Exception) -> tu
|
|||
if num_retries is None:
|
||||
num_retries = litellm.num_retries
|
||||
if kwargs.get("retry_policy", None):
|
||||
get_num_retries_from_retry_policy: Final[Callable[..., int | None]] = getattr(
|
||||
sys.modules[__name__], "get_num_retries_from_retry_policy"
|
||||
get_num_retries_from_retry_policy: Final[Callable[..., int | None]] = (
|
||||
litellm_utils.get_num_retries_from_retry_policy
|
||||
)
|
||||
reset_retry_policy: Final = litellm_utils.reset_retry_policy
|
||||
retry_policy_num_retries: Final[int | None] = get_num_retries_from_retry_policy(
|
||||
|
|
@ -1802,9 +1798,7 @@ def client(original_function):
|
|||
return litellm.stream_chunk_builder(chunks, messages=kwargs.get("messages", None))
|
||||
else:
|
||||
# RETURN RESULT
|
||||
update_response_metadata: _ResponseMetadataUpdater = getattr(
|
||||
sys.modules[__name__], "update_response_metadata"
|
||||
)
|
||||
update_response_metadata: _ResponseMetadataUpdater = litellm_utils.update_response_metadata
|
||||
update_response_metadata(
|
||||
result=result,
|
||||
logging_obj=logging_obj,
|
||||
|
|
@ -1845,9 +1839,7 @@ def client(original_function):
|
|||
kwargs=kwargs,
|
||||
)
|
||||
|
||||
_update_response_metadata: Final[_ResponseMetadataUpdater] = getattr(
|
||||
sys.modules[__name__], "update_response_metadata"
|
||||
)
|
||||
_update_response_metadata: Final[_ResponseMetadataUpdater] = litellm_utils.update_response_metadata
|
||||
_update_response_metadata(
|
||||
result=result,
|
||||
logging_obj=logging_obj,
|
||||
|
|
@ -1877,8 +1869,8 @@ def client(original_function):
|
|||
if call_type == CallTypes.completion.value:
|
||||
num_retries = kwargs.get("num_retries", None) or litellm.num_retries or None
|
||||
if kwargs.get("retry_policy", None):
|
||||
get_num_retries_from_retry_policy: Callable[..., int | None] = getattr(
|
||||
sys.modules[__name__], "get_num_retries_from_retry_policy"
|
||||
get_num_retries_from_retry_policy: Callable[..., int | None] = (
|
||||
litellm_utils.get_num_retries_from_retry_policy
|
||||
)
|
||||
reset_retry_policy = litellm_utils.reset_retry_policy
|
||||
num_retries = get_num_retries_from_retry_policy(
|
||||
|
|
@ -1916,9 +1908,7 @@ def client(original_function):
|
|||
elif call_type == CallTypes.responses.value:
|
||||
num_retries = kwargs.get("num_retries", None) or litellm.num_retries or None
|
||||
if kwargs.get("retry_policy", None):
|
||||
get_num_retries_from_retry_policy = getattr(
|
||||
sys.modules[__name__], "get_num_retries_from_retry_policy"
|
||||
)
|
||||
get_num_retries_from_retry_policy = litellm_utils.get_num_retries_from_retry_policy
|
||||
reset_retry_policy = litellm_utils.reset_retry_policy
|
||||
num_retries = get_num_retries_from_retry_policy(
|
||||
exception=e,
|
||||
|
|
@ -1955,9 +1945,7 @@ def client(original_function):
|
|||
print_args_passed_to_litellm(original_function, args, kwargs)
|
||||
start_time: Final = datetime.datetime.now()
|
||||
result = None
|
||||
_update_response_metadata: Final[_ResponseMetadataUpdater] = getattr(
|
||||
sys.modules[__name__], "update_response_metadata"
|
||||
)
|
||||
_update_response_metadata: Final[_ResponseMetadataUpdater] = litellm_utils.update_response_metadata
|
||||
logging_obj: LiteLLMLoggingObject | None = kwargs.get("litellm_logging_obj", None)
|
||||
LLMCachingHandler: Final = _get_cached_llm_caching_handler()
|
||||
_llm_caching_handler: Final[LLMCachingHandler] = LLMCachingHandler(
|
||||
|
|
@ -3496,7 +3484,8 @@ def get_optional_params_transcription(
|
|||
|
||||
passed_params.pop("OPENAI_TRANSCRIPTION_PARAMS")
|
||||
custom_llm_provider = passed_params.pop("custom_llm_provider")
|
||||
drop_params = normalize_drop_params(passed_params.pop("drop_params"))
|
||||
passed_params.pop("drop_params")
|
||||
drop_params = normalize_drop_params(drop_params)
|
||||
special_params: Final[Mapping[str, object]] = passed_params.pop("kwargs")
|
||||
for k, v in special_params.items():
|
||||
passed_params[k] = v
|
||||
|
|
@ -3597,16 +3586,18 @@ def get_optional_params_image_gen(
|
|||
additional_drop_params: list | None = None,
|
||||
provider_config: BaseImageGenerationConfig | None = None,
|
||||
drop_params: bool | None = None,
|
||||
**kwargs,
|
||||
**kwargs: object,
|
||||
):
|
||||
# retrieve all parameters passed to the function
|
||||
passed_params: Final = locals()
|
||||
model = passed_params.pop("model", None)
|
||||
custom_llm_provider = passed_params.pop("custom_llm_provider")
|
||||
provider_config = passed_params.pop("provider_config", None)
|
||||
drop_params = normalize_drop_params(passed_params.pop("drop_params", None))
|
||||
passed_params.pop("model", None)
|
||||
passed_params.pop("custom_llm_provider")
|
||||
passed_params.pop("provider_config", None)
|
||||
passed_params.pop("drop_params", None)
|
||||
drop_params = normalize_drop_params(drop_params)
|
||||
additional_drop_params = passed_params.pop("additional_drop_params", None)
|
||||
special_params: Final[Mapping[str, object]] = passed_params.pop("kwargs")
|
||||
passed_params.pop("kwargs")
|
||||
special_params: Final[Mapping[str, object]] = kwargs
|
||||
for k, v in special_params.items():
|
||||
if (
|
||||
k.startswith("aws_")
|
||||
|
|
@ -3725,18 +3716,18 @@ def get_optional_params_embeddings(
|
|||
**kwargs,
|
||||
):
|
||||
# Lazy load get_supported_openai_params
|
||||
get_supported_openai_params: Final[_SupportedOpenAIParamsGetter] = getattr(
|
||||
sys.modules[__name__], "get_supported_openai_params"
|
||||
)
|
||||
get_supported_openai_params: Final[_SupportedOpenAIParamsGetter] = litellm_utils.get_supported_openai_params
|
||||
|
||||
# retrieve all parameters passed to the function
|
||||
passed_params: Final = locals()
|
||||
custom_llm_provider = passed_params.pop("custom_llm_provider", None)
|
||||
special_params: Final = passed_params.pop("kwargs")
|
||||
|
||||
drop_params = normalize_drop_params(passed_params.pop("drop_params", None))
|
||||
additional_drop_params = passed_params.pop("additional_drop_params", None)
|
||||
allowed_openai_params = passed_params.pop("allowed_openai_params", None) or []
|
||||
passed_params.pop("drop_params", None)
|
||||
drop_params = normalize_drop_params(drop_params)
|
||||
passed_params.pop("additional_drop_params", None)
|
||||
passed_params.pop("allowed_openai_params", None)
|
||||
allowed_openai_params = allowed_openai_params or []
|
||||
# Remove function objects from passed_params to avoid JSON serialization errors
|
||||
passed_params.pop("get_supported_openai_params", None)
|
||||
|
||||
|
|
@ -4502,9 +4493,7 @@ def get_optional_params(
|
|||
message=f"{custom_llm_provider} does not support parameters: {list(unsupported_params.keys())}, for model={model}. To drop these, set `litellm.drop_params=True` or for proxy:\n\n`litellm_settings:\n drop_params: true`\n. \n If you want to use these params dynamically send allowed_openai_params={list(unsupported_params.keys())} in your request.",
|
||||
)
|
||||
|
||||
get_supported_openai_params: Final[_SupportedOpenAIParamsGetter] = getattr(
|
||||
sys.modules[__name__], "get_supported_openai_params"
|
||||
)
|
||||
get_supported_openai_params: Final[_SupportedOpenAIParamsGetter] = litellm_utils.get_supported_openai_params
|
||||
supported_params = get_supported_openai_params(
|
||||
model=model, custom_llm_provider=custom_llm_provider, base_model=base_model
|
||||
)
|
||||
|
|
@ -4675,7 +4664,7 @@ def get_optional_params(
|
|||
drop_params=bool(drop_params),
|
||||
)
|
||||
elif custom_llm_provider == "bedrock":
|
||||
bedrock_model_info: Final[type[BedrockModelInfo]] = getattr(sys.modules[__name__], "BedrockModelInfo")
|
||||
bedrock_model_info: Final[type[BedrockModelInfo]] = litellm_utils.BedrockModelInfo
|
||||
bedrock_route: Final = bedrock_model_info.get_bedrock_route(model)
|
||||
bedrock_base_model: Final = bedrock_model_info.get_base_model(model)
|
||||
if bedrock_route == "converse" or bedrock_route == "converse_like":
|
||||
|
|
@ -4996,8 +4985,8 @@ def get_optional_params(
|
|||
|
||||
# Apply nested drops from additional_drop_params
|
||||
if additional_drop_params:
|
||||
is_nested_path: Final[_NestedPathChecker] = getattr(sys.modules[__name__], "is_nested_path")
|
||||
delete_nested_value: Final[_NestedValueDeleter] = getattr(sys.modules[__name__], "delete_nested_value")
|
||||
is_nested_path: Final[_NestedPathChecker] = litellm_utils.is_nested_path
|
||||
delete_nested_value: Final[_NestedValueDeleter] = litellm_utils.delete_nested_value
|
||||
nested_paths: Final = [p for p in additional_drop_params if is_nested_path(p)]
|
||||
for path in nested_paths:
|
||||
optional_params = delete_nested_value(optional_params, path)
|
||||
|
|
@ -7328,7 +7317,7 @@ class TextCompletionStreamWrapper:
|
|||
except StopIteration:
|
||||
raise StopIteration
|
||||
except Exception as e:
|
||||
exception_type: Final = getattr(sys.modules[__name__], "exception_type")
|
||||
exception_type: Final = litellm_utils.exception_type
|
||||
raise exception_type(
|
||||
model=self.model,
|
||||
custom_llm_provider=self.custom_llm_provider or "",
|
||||
|
|
@ -9974,7 +9963,7 @@ def get_end_user_id_for_cost_tracking(
|
|||
|
||||
service_type: "litellm_logging" or "prometheus" - used to allow prometheus only disable cost tracking.
|
||||
"""
|
||||
get_litellm_metadata_from_kwargs: Final = getattr(sys.modules[__name__], "get_litellm_metadata_from_kwargs")
|
||||
get_litellm_metadata_from_kwargs: Final = litellm_utils.get_litellm_metadata_from_kwargs
|
||||
_metadata: Final = cast(dict, get_litellm_metadata_from_kwargs(dict(litellm_params=litellm_params)))
|
||||
|
||||
end_user_id: Final = cast(
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue