mirror of
https://github.com/BerriAI/litellm.git
synced 2026-09-07 08:26:10 +00:00
fix: reformat with Black 23.x to match CI
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
parent
2905d47bd4
commit
b2c3334c88
5 changed files with 91 additions and 83 deletions
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@ -2085,9 +2085,9 @@ class PrometheusLogger(CustomLogger):
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):
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try:
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verbose_logger.debug("setting remaining tokens requests metric")
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standard_logging_payload: Optional[StandardLoggingPayload] = (
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request_kwargs.get("standard_logging_object")
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)
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standard_logging_payload: Optional[
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StandardLoggingPayload
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] = request_kwargs.get("standard_logging_object")
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if standard_logging_payload is None:
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return
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@ -2720,7 +2720,9 @@ class PrometheusLogger(CustomLogger):
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)
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return
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async def fetch_keys(page_size: int, page: int) -> Tuple[
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async def fetch_keys(
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page_size: int, page: int
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) -> Tuple[
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List[Union[str, UserAPIKeyAuth, LiteLLM_DeletedVerificationToken]],
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Optional[int],
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]:
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@ -3397,10 +3399,10 @@ class PrometheusLogger(CustomLogger):
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from litellm.constants import PROMETHEUS_BUDGET_METRICS_REFRESH_INTERVAL_MINUTES
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from litellm.integrations.custom_logger import CustomLogger
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prometheus_loggers: List[CustomLogger] = (
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litellm.logging_callback_manager.get_custom_loggers_for_type(
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callback_type=PrometheusLogger
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)
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prometheus_loggers: List[
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CustomLogger
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] = litellm.logging_callback_manager.get_custom_loggers_for_type(
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callback_type=PrometheusLogger
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)
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# we need to get the initialized prometheus logger instance(s) and call logger.initialize_remaining_budget_metrics() on them
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verbose_logger.debug("found %s prometheus loggers", len(prometheus_loggers))
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@ -1744,7 +1744,9 @@ class AmazonConverseConfig(BaseConfig):
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return message, returned_finish_reason
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def _translate_message_content(self, content_blocks: List[ContentBlock]) -> Tuple[
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def _translate_message_content(
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self, content_blocks: List[ContentBlock]
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) -> Tuple[
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str,
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List[ChatCompletionToolCallChunk],
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Optional[List[BedrockConverseReasoningContentBlock]],
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@ -1761,9 +1763,9 @@ class AmazonConverseConfig(BaseConfig):
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"""
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content_str = ""
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tools: List[ChatCompletionToolCallChunk] = []
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reasoningContentBlocks: Optional[List[BedrockConverseReasoningContentBlock]] = (
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None
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)
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reasoningContentBlocks: Optional[
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List[BedrockConverseReasoningContentBlock]
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] = None
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citationsContentBlocks: Optional[List[CitationsContentBlock]] = None
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for idx, content in enumerate(content_blocks):
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"""
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@ -1974,9 +1976,9 @@ class AmazonConverseConfig(BaseConfig):
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chat_completion_message: ChatCompletionResponseMessage = {"role": "assistant"}
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content_str = ""
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tools: List[ChatCompletionToolCallChunk] = []
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reasoningContentBlocks: Optional[List[BedrockConverseReasoningContentBlock]] = (
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None
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)
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reasoningContentBlocks: Optional[
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List[BedrockConverseReasoningContentBlock]
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] = None
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citationsContentBlocks: Optional[List[CitationsContentBlock]] = None
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if message is not None:
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@ -1995,17 +1997,17 @@ class AmazonConverseConfig(BaseConfig):
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provider_specific_fields["citationsContent"] = citationsContentBlocks
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if provider_specific_fields:
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chat_completion_message["provider_specific_fields"] = (
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provider_specific_fields
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)
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chat_completion_message[
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"provider_specific_fields"
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] = provider_specific_fields
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if reasoningContentBlocks is not None:
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chat_completion_message["reasoning_content"] = (
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self._transform_reasoning_content(reasoningContentBlocks)
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)
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chat_completion_message["thinking_blocks"] = (
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self._transform_thinking_blocks(reasoningContentBlocks)
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)
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chat_completion_message[
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"reasoning_content"
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] = self._transform_reasoning_content(reasoningContentBlocks)
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chat_completion_message[
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"thinking_blocks"
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] = self._transform_thinking_blocks(reasoningContentBlocks)
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chat_completion_message["content"] = content_str
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filtered_tools = self._filter_json_mode_tools(
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json_mode=json_mode,
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@ -86,9 +86,9 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
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if tool_calls_to_check:
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inputs["tool_calls"] = tool_calls_to_check # type: ignore
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if messages:
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inputs["structured_messages"] = (
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messages # pass the openai /chat/completions messages to the guardrail, as-is
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)
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inputs[
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"structured_messages"
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] = messages # pass the openai /chat/completions messages to the guardrail, as-is
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# Pass tools (function definitions) to the guardrail
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tools = data.get("tools")
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if tools:
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@ -722,9 +722,9 @@ async def _setup_role_mappings() -> Optional["RoleMappings"]:
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import ast
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try:
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generic_user_role_mappings_data: Dict[LitellmUserRoles, List[str]] = (
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ast.literal_eval(generic_role_mappings)
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)
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generic_user_role_mappings_data: Dict[
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LitellmUserRoles, List[str]
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] = ast.literal_eval(generic_role_mappings)
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if isinstance(generic_user_role_mappings_data, dict):
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from litellm.types.proxy.management_endpoints.ui_sso import RoleMappings
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@ -881,9 +881,9 @@ async def get_generic_sso_response(
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verbose_proxy_logger.debug("calling generic_sso.verify_and_process")
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additional_generic_sso_headers_dict = _parse_generic_sso_headers()
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code_verifier: Optional[str] = (
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None # assigned inside try; initialized for type tracking
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)
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code_verifier: Optional[
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str
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] = None # assigned inside try; initialized for type tracking
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access_token_payload: Optional[dict] = None # decoded JWT access token claims
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try:
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@ -1263,9 +1263,9 @@ def apply_user_info_values_to_sso_user_defined_values(
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else:
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# SSO didn't provide a valid role, fall back to DB role or default
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if user_info is None or user_info.user_role is None:
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user_defined_values["user_role"] = (
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LitellmUserRoles.INTERNAL_USER_VIEW_ONLY.value
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)
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user_defined_values[
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"user_role"
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] = LitellmUserRoles.INTERNAL_USER_VIEW_ONLY.value
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verbose_proxy_logger.debug(
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"No SSO or DB role found, using default: INTERNAL_USER_VIEW_ONLY"
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)
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@ -1373,14 +1373,16 @@ async def auth_callback(request: Request, state: Optional[str] = None): # noqa:
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)
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elif generic_client_id is not None:
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result, received_response, access_token_payload = (
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await get_generic_sso_response(
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request=request,
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jwt_handler=jwt_handler,
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generic_client_id=generic_client_id,
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redirect_url=redirect_url,
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sso_jwt_handler=sso_jwt_handler,
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)
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(
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result,
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received_response,
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access_token_payload,
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) = await get_generic_sso_response(
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request=request,
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jwt_handler=jwt_handler,
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generic_client_id=generic_client_id,
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redirect_url=redirect_url,
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sso_jwt_handler=sso_jwt_handler,
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)
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if result is None:
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@ -1703,9 +1705,9 @@ async def insert_sso_user(
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if user_defined_values.get("max_budget") is None:
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user_defined_values["max_budget"] = litellm.max_internal_user_budget
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if user_defined_values.get("budget_duration") is None:
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user_defined_values["budget_duration"] = (
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litellm.internal_user_budget_duration
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)
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user_defined_values[
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"budget_duration"
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] = litellm.internal_user_budget_duration
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if user_defined_values["user_role"] is None:
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user_defined_values["user_role"] = LitellmUserRoles.INTERNAL_USER_VIEW_ONLY
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@ -3348,9 +3350,9 @@ class MicrosoftSSOHandler:
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# if user is trying to get the raw sso response for debugging, return the raw sso response
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if return_raw_sso_response:
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original_msft_result[MicrosoftSSOHandler.GRAPH_API_RESPONSE_KEY] = (
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user_team_ids
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)
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original_msft_result[
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MicrosoftSSOHandler.GRAPH_API_RESPONSE_KEY
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] = user_team_ids
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original_msft_result["app_roles"] = app_roles
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return original_msft_result or {}
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@ -3469,9 +3471,9 @@ class MicrosoftSSOHandler:
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# Fetch user membership from Microsoft Graph API
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all_group_ids = []
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next_link: Optional[str] = (
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MicrosoftSSOHandler.graph_api_user_groups_endpoint
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)
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next_link: Optional[
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str
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] = MicrosoftSSOHandler.graph_api_user_groups_endpoint
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auth_headers = {"Authorization": f"Bearer {access_token}"}
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page_count = 0
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@ -639,9 +639,9 @@ except ImportError:
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server_root_path = get_server_root_path()
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_license_check = LicenseCheck()
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premium_user: bool = _license_check.is_premium()
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premium_user_data: Optional["EnterpriseLicenseData"] = (
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_license_check.airgapped_license_data
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)
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premium_user_data: Optional[
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"EnterpriseLicenseData"
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] = _license_check.airgapped_license_data
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global_max_parallel_request_retries_env: Optional[str] = os.getenv(
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"LITELLM_GLOBAL_MAX_PARALLEL_REQUEST_RETRIES"
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)
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@ -1524,9 +1524,9 @@ master_key: Optional[str] = None
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config_agents: Optional[List[AgentConfig]] = None
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otel_logging = False
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prisma_client: Optional[PrismaClient] = None
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shared_aiohttp_session: Optional["ClientSession"] = (
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None # Global shared session for connection reuse
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)
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shared_aiohttp_session: Optional[
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"ClientSession"
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] = None # Global shared session for connection reuse
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user_api_key_cache = DualCache(
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default_in_memory_ttl=UserAPIKeyCacheTTLEnum.in_memory_cache_ttl.value
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)
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@ -1537,13 +1537,13 @@ model_max_budget_limiter = _PROXY_VirtualKeyModelMaxBudgetLimiter(
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dual_cache=user_api_key_cache
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)
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litellm.logging_callback_manager.add_litellm_callback(model_max_budget_limiter)
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redis_usage_cache: Optional[RedisCache] = (
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None # redis cache used for tracking spend, tpm/rpm limits
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)
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redis_usage_cache: Optional[
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RedisCache
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] = None # redis cache used for tracking spend, tpm/rpm limits
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polling_via_cache_enabled: Union[Literal["all"], List[str], bool] = False
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native_background_mode: List[str] = (
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[]
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) # Models that should use native provider background mode instead of polling
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native_background_mode: List[
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str
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] = [] # Models that should use native provider background mode instead of polling
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polling_cache_ttl: int = 3600 # Default 1 hour TTL for polling cache
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user_custom_auth = None
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user_custom_key_generate = None
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@ -2027,9 +2027,9 @@ async def update_cache( # noqa: PLR0915
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_id = "team_id:{}".format(team_id)
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try:
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# Fetch the existing cost for the given user
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existing_spend_obj: Optional[LiteLLM_TeamTable] = (
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await user_api_key_cache.async_get_cache(key=_id)
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)
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existing_spend_obj: Optional[
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LiteLLM_TeamTable
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] = await user_api_key_cache.async_get_cache(key=_id)
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if existing_spend_obj is None:
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# do nothing if team not in api key cache
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return
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@ -2150,9 +2150,11 @@ def run_ollama_serve():
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with open(os.devnull, "w") as devnull:
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subprocess.Popen(command, stdout=devnull, stderr=devnull)
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except Exception as e:
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verbose_proxy_logger.debug(f"""
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verbose_proxy_logger.debug(
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f"""
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LiteLLM Warning: proxy started with `ollama` model\n`ollama serve` failed with Exception{e}. \nEnsure you run `ollama serve`
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""")
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"""
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)
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def _get_process_rss_mb() -> Optional[float]:
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@ -5200,10 +5202,10 @@ class ProxyConfig:
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)
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try:
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guardrails_in_db: List[Guardrail] = (
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await GuardrailRegistry.get_all_guardrails_from_db(
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prisma_client=prisma_client
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)
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guardrails_in_db: List[
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Guardrail
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] = await GuardrailRegistry.get_all_guardrails_from_db(
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prisma_client=prisma_client
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)
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verbose_proxy_logger.debug(
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"guardrails from the DB %s", str(guardrails_in_db)
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@ -5585,9 +5587,9 @@ async def initialize( # noqa: PLR0915
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user_api_base = api_base
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dynamic_config[user_model]["api_base"] = api_base
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if api_version:
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os.environ["AZURE_API_VERSION"] = (
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api_version # set this for azure - litellm can read this from the env
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)
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os.environ[
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"AZURE_API_VERSION"
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] = api_version # set this for azure - litellm can read this from the env
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if max_tokens: # model-specific param
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dynamic_config[user_model]["max_tokens"] = max_tokens
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if temperature: # model-specific param
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@ -5924,9 +5926,9 @@ class ProxyStartupEvent:
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"""
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from litellm.secret_managers.main import str_to_bool
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_use_redis_transaction_buffer: Optional[Union[bool, str]] = (
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general_settings.get("use_redis_transaction_buffer", False)
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)
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_use_redis_transaction_buffer: Optional[
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Union[bool, str]
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] = general_settings.get("use_redis_transaction_buffer", False)
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if isinstance(_use_redis_transaction_buffer, str):
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_use_redis_transaction_buffer = str_to_bool(_use_redis_transaction_buffer)
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@ -12521,9 +12523,9 @@ async def get_config_list(
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hasattr(sub_field_info, "description")
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and sub_field_info.description is not None
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):
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nested_fields[idx].field_description = (
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sub_field_info.description
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)
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nested_fields[
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idx
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].field_description = sub_field_info.description
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idx += 1
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_stored_in_db = None
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