scriptoriumadmin/litellm
1
0
Fork 0
mirror of https://github.com/BerriAI/litellm.git synced 2026-10-03 02:22:24 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 81

Merge aebb0d04eb into 5be0797d24

Browse source
This commit is contained in:
7. Sun 2026-06-03 16:45:53 +00:00 • committed by GitHub
commit f07ce7107f
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
87 changed files with 182 additions and 190 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

2
enterprise/litellm_enterprise/proxy/management_endpoints/project_endpoints.py
View file

@ -661,7 +661,7 @@ async def update_project( # noqa: PLR0915
},
)
# Remove budget fields from project update
for field in budget_updates.keys():
for field in budget_updates:
update_data.pop(field, None)
# Handle object permissions

8
litellm/assistants/utils.py
View file

@ -78,8 +78,8 @@ def get_optional_params_add_message(
optional_params = litellm.AzureOpenAIAssistantsAPIConfig().map_openai_params_create_message_params(
non_default_params=non_default_params, optional_params=optional_params
)
for k in passed_params.keys():
if k not in default_params.keys():
for k in passed_params:
if k not in default_params:
optional_params[k] = passed_params[k]
return optional_params
@ -155,7 +155,7 @@ def get_optional_params_image_gen(
if n is not None:
optional_params["sampleCount"] = int(n)
for k in passed_params.keys():
if k not in default_params.keys():
for k in passed_params:
if k not in default_params:
optional_params[k] = passed_params[k]
return optional_params

2
litellm/batch_completion/main.py
View file

@ -170,7 +170,7 @@ def batch_completion_models(*args, **kwargs):
futures = {}
with ThreadPoolExecutor(max_workers=len(deployments)) as executor:
for deployment in deployments:
for key in kwargs.keys():
for key in kwargs:
if (
key not in deployment
): # don't override deployment values e.g. model name, api base, etc.

2
litellm/budget_manager.py
View file

@ -52,7 +52,7 @@ class BudgetManager:
# Check if user dict file exists
if os.path.isfile("user_cost.json"):
# Load the user dict
with open("user_cost.json", "r") as json_file:
with open("user_cost.json") as json_file:
self.user_dict = json.load(json_file)
else:
self.print_verbose("User Dictionary not found!")

2
litellm/completion_extras/litellm_responses_transformation/transformation.py
View file

@ -332,7 +332,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
responses_api_request["tool_choice"] = ( # type: ignore[assignment]
self._normalize_tool_choice_for_responses_api(value)
)
elif key in ResponsesAPIOptionalRequestParams.__annotations__.keys():
elif key in ResponsesAPIOptionalRequestParams.__annotations__:
responses_api_request[key] = value # type: ignore
elif key == "previous_response_id":
responses_api_request["previous_response_id"] = value

2
litellm/constants.py
View file

@ -693,7 +693,7 @@ OPENAI_TRANSCRIPTION_PARAMS = [
OPENAI_EMBEDDING_PARAMS = ["dimensions", "encoding_format", "user"]
DEFAULT_EMBEDDING_PARAM_VALUES = {
**{k: None for k in OPENAI_EMBEDDING_PARAMS},
**dict.fromkeys(OPENAI_EMBEDDING_PARAMS),
"model": None,
"custom_llm_provider": "",
"input": None,

2
litellm/integrations/datadog/datadog_llm_obs.py
View file

@ -546,7 +546,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
if isinstance(messages, str):
return [messages]
elif isinstance(messages, list):
return [message for message in messages]
return list(messages)
elif isinstance(messages, dict):
return [str(messages.get("content", ""))]
return []

2
litellm/integrations/dotprompt/prompt_manager.py
View file

@ -31,7 +31,7 @@ class PromptTemplate:
self.output_format = self.metadata.get("output", {}).get("format")
self.output_schema = self.metadata.get("output", {}).get("schema", {})
self.optional_params = {}
for key in self.metadata.keys():
for key in self.metadata:
if key not in restricted_keys:
self.optional_params[key] = self.metadata[key]

2
litellm/integrations/generic_api/generic_api_callback.py
View file

@ -40,7 +40,7 @@ def load_compatible_callbacks() -> Dict:
json_path = os.path.join(
os.path.dirname(__file__), "generic_api_compatible_callbacks.json"
)
with open(json_path, "r") as f:
with open(json_path) as f:
return json.load(f)
except Exception as e:
verbose_logger.warning(

4
litellm/interactions/utils.py
View file

@ -78,9 +78,7 @@ class InteractionsAPIRequestUtils:
special_params=special_params,
custom_llm_provider=custom_llm_provider,
additional_drop_params=additional_drop_params,
default_param_values={
k: None for k in INTERACTIONS_API_OPTIONAL_PARAMS
},
default_param_values=dict.fromkeys(INTERACTIONS_API_OPTIONAL_PARAMS),
additional_endpoint_specific_params=["input", "model", "agent"],
)
)

4
litellm/litellm_core_utils/audio_utils/utils.py
View file

@ -179,7 +179,7 @@ def get_audio_file_content_hash(file_obj: FileTypes) -> str:
file_content = f.read()
if fallback_filename is None:
fallback_filename = str(file_content_obj)
except (OSError, IOError):
except OSError:
fallback_filename = str(file_content_obj)
file_content = None
elif hasattr(file_content_obj, "read"):
@ -194,7 +194,7 @@ def get_audio_file_content_hash(file_obj: FileTypes) -> str:
file_content = file_content_obj.read() # type: ignore
if current_position is not None and hasattr(file_content_obj, "seek"):
file_content_obj.seek(current_position) # type: ignore
except (OSError, IOError, AttributeError):
except (OSError, AttributeError):
file_content = None
else:
file_content = None

4
litellm/litellm_core_utils/cli_token_utils.py
View file

@ -25,9 +25,9 @@ def load_cli_token() -> Optional[dict]:
return None
try:
with open(token_file, "r") as f:
with open(token_file) as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
except (OSError, json.JSONDecodeError):
return None

42
litellm/litellm_core_utils/litellm_logging.py
View file

@ -5154,7 +5154,7 @@ class StandardLoggingPayloadSetup:
# Populate well-known typed fields with int/str coercion where needed
typed_keys: dict = {}
for key in StandardLoggingAdditionalHeaders.__annotations__.keys():
for key in StandardLoggingAdditionalHeaders.__annotations__:
_key = key.lower().replace("_", "-")
typed_keys[_key] = key
if _key in additiona_headers:
@ -5186,7 +5186,7 @@ class StandardLoggingPayloadSetup:
usage_object=None,
)
if hidden_params is not None:
for key in StandardLoggingHiddenParams.__annotations__.keys():
for key in StandardLoggingHiddenParams.__annotations__:
if key in hidden_params:
if key == "additional_headers":
clean_hidden_params["additional_headers"] = (
@ -5811,7 +5811,7 @@ def get_standard_logging_metadata(
)
if isinstance(metadata, dict):
# Update the clean_metadata with values from input metadata that match StandardLoggingMetadata fields
for key in StandardLoggingMetadata.__annotations__.keys():
for key in StandardLoggingMetadata.__annotations__:
if key in metadata:
clean_metadata[key] = metadata[key] # type: ignore
@ -5886,16 +5886,16 @@ def create_dummy_standard_logging_payload() -> StandardLoggingPayload:
)
metadata = StandardLoggingMetadata( # type: ignore
user_api_key_hash=str("test_hash"),
user_api_key_alias=str("test_alias"),
user_api_key_team_id=str("test_team"),
user_api_key_user_id=str("test_user"),
user_api_key_team_alias=str("test_team_alias"),
user_api_key_hash="test_hash",
user_api_key_alias="test_alias",
user_api_key_team_id="test_team",
user_api_key_user_id="test_user",
user_api_key_team_alias="test_team_alias",
user_api_key_org_id=None,
spend_logs_metadata=None,
requester_ip_address=str("127.0.0.1"),
requester_ip_address="127.0.0.1",
requester_metadata=None,
user_api_key_end_user_id=str("test_end_user"),
user_api_key_end_user_id="test_end_user",
)
hidden_params = StandardLoggingHiddenParams(
@ -5925,12 +5925,12 @@ def create_dummy_standard_logging_payload() -> StandardLoggingPayload:
# Main payload initialization
return StandardLoggingPayload( # type: ignore
id=str("test_id"),
call_type=str("completion"),
stream=bool(False),
id="test_id",
call_type="completion",
stream=False,
response_cost=response_cost,
response_cost_failure_debug_info=None,
status=str("success"),
status="success",
total_tokens=int(
DEFAULT_MOCK_RESPONSE_PROMPT_TOKEN_COUNT
+ DEFAULT_MOCK_RESPONSE_COMPLETION_TOKEN_COUNT
@ -5941,18 +5941,18 @@ def create_dummy_standard_logging_payload() -> StandardLoggingPayload:
endTime=end_time,
completionStartTime=completion_start_time,
model_map_information=model_info,
model=str("gpt-3.5-turbo"),
model_id=str("model-123"),
model_group=str("openai-gpt"),
custom_llm_provider=str("openai"),
api_base=str("https://api.openai.com"),
model="gpt-3.5-turbo",
model_id="model-123",
model_group="openai-gpt",
custom_llm_provider="openai",
api_base="https://api.openai.com",
metadata=metadata,
cache_hit=bool(False),
cache_hit=False,
cache_key=None,
saved_cache_cost=saved_cache_cost,
request_tags=[],
end_user=None,
requester_ip_address=str("127.0.0.1"),
requester_ip_address="127.0.0.1",
messages=messages,
response=response,
error_str=None,

6
litellm/litellm_core_utils/logging_utils.py
View file

@ -89,7 +89,7 @@ def _truncate_base64_in_value(value: Any) -> Any:
return value
# Shallow-copy the root so we don't mutate the caller's data.
root = {k: v for k, v in value.items()} if isinstance(value, dict) else list(value)
root = dict(value.items()) if isinstance(value, dict) else list(value)
stack: list = [(root, 0)]
while stack:
@ -101,7 +101,7 @@ def _truncate_base64_in_value(value: Any) -> Any:
if isinstance(v, str):
container[k] = _truncate_base64_in_string(v)
elif isinstance(v, dict):
copy: Union[dict, list] = {ck: cv for ck, cv in v.items()}
copy: Union[dict, list] = dict(v.items())
container[k] = copy
stack.append((copy, depth + 1))
elif isinstance(v, list):
@ -113,7 +113,7 @@ def _truncate_base64_in_value(value: Any) -> Any:
if isinstance(v, str):
container[i] = _truncate_base64_in_string(v)
elif isinstance(v, dict):
copy = {ck: cv for ck, cv in v.items()}
copy = dict(v.items())
container[i] = copy
stack.append((copy, depth + 1))
elif isinstance(v, list):

2
litellm/litellm_core_utils/model_response_utils.py
View file

@ -47,7 +47,7 @@ def is_model_response_stream_empty(model_response: ModelResponseStream) -> bool:
# Check for any non-base fields that are set
# Access model_fields on the class, not the instance, to avoid Pydantic 2.11+ deprecation warnings
for model_response_field in type(model_response).model_fields.keys():
for model_response_field in type(model_response).model_fields:
# Skip base fields that are always set
if model_response_field in BASE_FIELDS:
continue

2
litellm/litellm_core_utils/prompt_templates/factory.py
View file

@ -849,7 +849,7 @@ def construct_tool_use_system_prompt(
"</function_calls>\n"
"\n"
"Here are the tools available:\n"
"<tools>\n" + "\n".join([tool_str for tool_str in tool_str_list]) + "\n</tools>"
"<tools>\n" + "\n".join(list(tool_str_list)) + "\n</tools>"
)
return tool_use_system_prompt

2
litellm/litellm_core_utils/streaming_handler.py
View file

@ -1280,7 +1280,7 @@ class CustomStreamWrapper:
proto.marshal.collections.repeated.RepeatedComposite, # type: ignore
):
# If so, convert to list
args_dict[key] = [v for v in val]
args_dict[key] = list(val)
else:
args_dict[key] = val

4
litellm/llms/aiml/image_generation/transformation.py
View file

@ -42,8 +42,8 @@ class AimlImageGenerationConfig(BaseImageGenerationConfig):
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
# Map OpenAI params to AI/ML params
if k == "n":

2
litellm/llms/bedrock/base_aws_llm.py
View file

@ -911,7 +911,7 @@ class BaseAWSLLM:
verbose_logger.debug("Cross-account role assumption detected")
# Read the web identity token
with open(web_identity_token_file, "r") as f:
with open(web_identity_token_file) as f:
web_identity_token = f.read().strip()
irsa_sts_kwargs = self._build_sts_client_kwargs(

2
litellm/llms/bedrock/embed/cohere_transformation.py
View file

@ -40,7 +40,7 @@ class BedrockCohereEmbeddingConfig:
new_transformed_request = CohereEmbeddingRequest(
input_type=transformed_request["input_type"],
)
for k in CohereEmbeddingRequest.__annotations__.keys():
for k in CohereEmbeddingRequest.__annotations__:
if k in transformed_request:
new_transformed_request[k] = transformed_request[k] # type: ignore

4
litellm/llms/bedrock/vector_stores/transformation.py
View file

@ -164,10 +164,10 @@ class BedrockVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
aws_filters: Optional[Dict] = None
if isinstance(value, dict):
if "operator" in value.keys():
if "operator" in value:
# Single operator - map directly (no wrapping needed)
aws_filters = self._map_operator_filter(value)
elif "and" in value.keys() or "or" in value.keys():
elif "and" in value or "or" in value:
aws_filters = self._map_and_or_filters(value)
else:
# Assume it's already in AWS KB format

6
litellm/llms/chatgpt/authenticator.py
View file

@ -92,9 +92,9 @@ class Authenticator:
def _read_auth_file(self) -> Optional[Dict[str, Any]]:
try:
with open(self.auth_file, "r") as f:
with open(self.auth_file) as f:
return json.load(f)
except IOError:
except OSError:
return None
except json.JSONDecodeError as exc:
verbose_logger.warning("Invalid ChatGPT auth file: %s", exc)
@ -104,7 +104,7 @@ class Authenticator:
try:
with open(self.auth_file, "w") as f:
json.dump(data, f)
except IOError as exc:
except OSError as exc:
verbose_logger.error("Failed to write ChatGPT auth file: %s", exc)
def _is_token_expired(self, auth_data: Dict[str, Any], access_token: str) -> bool:

2
litellm/llms/cohere/embed/handler.py
View file

@ -23,7 +23,7 @@ from .v1_transformation import CohereEmbeddingConfig
def validate_environment(api_key, headers: dict):
# Create a lowercase key lookup to avoid duplicate headers with different cases
# This is important when headers come from AWS signed requests (which use Title-Case)
existing_keys_lower = {k.lower(): k for k in headers.keys()}
existing_keys_lower = {k.lower(): k for k in headers}
# Only add headers if they don't already exist (case-insensitive check)
if "request-source" not in existing_keys_lower:

4
litellm/llms/cometapi/image_generation/transformation.py
View file

@ -47,8 +47,8 @@ class CometAPIImageGenerationConfig(BaseImageGenerationConfig):
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
# CometAPI uses OpenAI-compatible parameters, so we can pass them directly
optional_params[k] = non_default_params[k]

4
litellm/llms/fal_ai/image_generation/bria_transformation.py
View file

@ -62,8 +62,8 @@ class FalAIBriaConfig(FalAIBaseConfig):
"size": "aspect_ratio",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
# Use mapped parameter name if exists
mapped_key = param_mapping.get(k, k)

4
litellm/llms/fal_ai/image_generation/bytedance_transformation.py
View file

@ -36,8 +36,8 @@ class FalAIBytedanceBaseConfig(FalAIFluxProV11UltraConfig):
"size": "image_size",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
mapped_key = param_mapping.get(k, k)
mapped_value = non_default_params[k]

4
litellm/llms/fal_ai/image_generation/flux_pro_v11_transformation.py
View file

@ -44,8 +44,8 @@ class FalAIFluxProV11Config(FalAIFluxProV11UltraConfig):
"size": "image_size",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
mapped_key = param_mapping.get(k, k)
mapped_value = non_default_params[k]

4
litellm/llms/fal_ai/image_generation/flux_pro_v11_ultra_transformation.py
View file

@ -64,8 +64,8 @@ class FalAIFluxProV11UltraConfig(FalAIBaseConfig):
"size": "aspect_ratio",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
# Use mapped parameter name if exists
mapped_key = param_mapping.get(k, k)

4
litellm/llms/fal_ai/image_generation/flux_schnell_transformation.py
View file

@ -41,8 +41,8 @@ class FalAIFluxSchnellConfig(FalAIFluxProV11UltraConfig):
"size": "image_size",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
mapped_key = param_mapping.get(k, k)
mapped_value = non_default_params[k]

2
litellm/llms/fal_ai/image_generation/ideogram_v3_transformation.py
View file

@ -64,7 +64,7 @@ class FalAIIdeogramV3Config(FalAIBaseConfig):
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
for k in non_default_params:
if k in optional_params:
continue

4
litellm/llms/fal_ai/image_generation/imagen4_transformation.py
View file

@ -66,8 +66,8 @@ class FalAIImagen4Config(FalAIBaseConfig):
"size": "aspect_ratio",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
# Use mapped parameter name if exists
mapped_key = param_mapping.get(k, k)

4
litellm/llms/fal_ai/image_generation/recraft_v3_transformation.py
View file

@ -62,8 +62,8 @@ class FalAIRecraftV3Config(FalAIBaseConfig):
"size": "image_size",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
# Use mapped parameter name if exists
mapped_key = param_mapping.get(k, k)

4
litellm/llms/fal_ai/image_generation/stable_diffusion_transformation.py
View file

@ -101,8 +101,8 @@ class FalAIStableDiffusionConfig(FalAIBaseConfig):
"size": "image_size",
}
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
# Use mapped parameter name if exists
mapped_key = param_mapping.get(k, k)

4
litellm/llms/fal_ai/image_generation/transformation.py
View file

@ -144,8 +144,8 @@ class FalAIImageGenerationConfig(FalAIBaseConfig):
drop_params: bool,
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
optional_params[k] = non_default_params[k]
elif drop_params:

2
litellm/llms/gemini/image_generation/transformation.py
View file

@ -49,7 +49,7 @@ class GoogleImageGenConfig(BaseImageGenerationConfig):
mapped_params = {}
for k, v in non_default_params.items():
if k not in optional_params.keys():
if k not in optional_params:
if k in supported_params:
# Map OpenAI parameters to Google format
if k == "n":

16
litellm/llms/github_copilot/authenticator.py
View file

@ -52,11 +52,11 @@ class Authenticator:
GetAccessTokenError: If unable to obtain an access token after retries.
"""
try:
with open(self.access_token_file, "r") as f:
with open(self.access_token_file) as f:
access_token = f.read().strip()
if access_token:
return access_token
except IOError:
except OSError:
verbose_logger.warning(
"No existing access token found or error reading file"
)
@ -68,7 +68,7 @@ class Authenticator:
try:
with open(self.access_token_file, "w") as f:
f.write(access_token)
except IOError:
except OSError:
verbose_logger.error("Error saving access token to file")
return access_token
except (GetDeviceCodeError, GetAccessTokenError, RefreshAPIKeyError) as e:
@ -91,7 +91,7 @@ class Authenticator:
GetAPIKeyError: If unable to obtain an API key.
"""
try:
with open(self.api_key_file, "r") as f:
with open(self.api_key_file) as f:
api_key_info = json.load(f)
if api_key_info.get("expires_at", 0) > datetime.now().timestamp():
return api_key_info.get("token")
@ -101,7 +101,7 @@ class Authenticator:
message="API key expired",
status_code=401,
)
except IOError:
except OSError:
verbose_logger.warning("No API key file found or error opening file")
except (json.JSONDecodeError, KeyError) as e:
verbose_logger.warning(f"Error reading API key from file: {str(e)}")
@ -120,7 +120,7 @@ class Authenticator:
message="API key response missing token",
status_code=401,
)
except IOError as e:
except OSError as e:
verbose_logger.error(f"Error saving API key to file: {str(e)}")
raise GetAPIKeyError(
message=f"Failed to save API key: {str(e)}",
@ -140,12 +140,12 @@ class Authenticator:
Optional[str]: The GitHub Copilot API endpoint, or None if not found.
"""
try:
with open(self.api_key_file, "r") as f:
with open(self.api_key_file) as f:
api_key_info = json.load(f)
endpoints = api_key_info.get("endpoints", {})
api_endpoint = endpoints.get("api")
return api_endpoint
except (IOError, json.JSONDecodeError, KeyError) as e:
except (OSError, json.JSONDecodeError, KeyError) as e:
verbose_logger.warning(f"Error reading API endpoint from file: {str(e)}")
return None

4
litellm/llms/huggingface/embedding/transformation.py
View file

@ -161,7 +161,7 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
"hf_text_generation_models.txt",
)
with open(file_path, "r") as file:
with open(file_path) as file:
for line in file:
tgi_models.add(line.strip())
@ -175,7 +175,7 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
"hf_conversational_models.txt",
)
conv_models = set()
with open(file_path, "r") as file:
with open(file_path) as file:
for line in file:
conv_models.add(line.strip())
# Cache the set for future use

4
litellm/llms/openai/image_generation/dall_e_2_transformation.py
View file

@ -31,8 +31,8 @@ class DallE2ImageGenerationConfig(BaseImageGenerationConfig):
drop_params: bool,
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
optional_params[k] = non_default_params[k]
elif drop_params:

4
litellm/llms/openai/image_generation/dall_e_3_transformation.py
View file

@ -31,8 +31,8 @@ class DallE3ImageGenerationConfig(BaseImageGenerationConfig):
drop_params: bool,
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
optional_params[k] = non_default_params[k]
elif drop_params:

4
litellm/llms/openai/image_generation/gpt_transformation.py
View file

@ -40,8 +40,8 @@ class GPTImageGenerationConfig(BaseImageGenerationConfig):
drop_params: bool,
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
optional_params[k] = non_default_params[k]
elif drop_params:

2
litellm/llms/openai/transcriptions/whisper_transformation.py
View file

@ -140,7 +140,7 @@ class OpenAIWhisperAudioTranscriptionConfig(BaseAudioTranscriptionConfig):
if any(
key in raw_response_json
for key in TranscriptionResponse.model_fields.keys()
for key in TranscriptionResponse.model_fields
):
return TranscriptionResponse(**raw_response_json)
else:

4
litellm/llms/recraft/image_generation/transformation.py
View file

@ -41,8 +41,8 @@ class RecraftImageGenerationConfig(BaseImageGenerationConfig):
drop_params: bool,
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
optional_params[k] = non_default_params[k]
elif drop_params:

4
litellm/llms/runwayml/image_generation/transformation.py
View file

@ -466,8 +466,8 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
}
optional_params["ratio"] = size_to_ratio_map.get(size, "1920:1080")
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
optional_params[k] = non_default_params[k]
elif drop_params:

2
litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
View file

@ -2561,7 +2561,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
)
if (
"finishReason" in _candidates[0]
and _candidates[0]["finishReason"] in content_policy_violations.keys()
and _candidates[0]["finishReason"] in content_policy_violations
):
return self._handle_content_policy_violation(
model_response=model_response,

2
litellm/llms/vertex_ai/image_generation/vertex_gemini_transformation.py
View file

@ -65,7 +65,7 @@ class VertexAIGeminiImageGenerationConfig(BaseImageGenerationConfig, VertexLLM):
mapped_params = {}
for k, v in non_default_params.items():
if k not in optional_params.keys():
if k not in optional_params:
if k in supported_params:
# Map OpenAI parameters to Gemini format
if k == "n":

2
litellm/llms/vertex_ai/image_generation/vertex_imagen_transformation.py
View file

@ -58,7 +58,7 @@ class VertexAIImagenImageGenerationConfig(BaseImageGenerationConfig, VertexLLM):
mapped_params = {}
for k, v in non_default_params.items():
if k not in optional_params.keys():
if k not in optional_params:
if k in supported_params:
# Map OpenAI parameters to Imagen format
if k == "n":

4
litellm/llms/xinference/image_generation/transformation.py
View file

@ -26,8 +26,8 @@ class XInferenceImageGenerationConfig(BaseImageGenerationConfig):
drop_params: bool,
) -> dict:
supported_params = self.get_supported_openai_params(model)
for k in non_default_params.keys():
if k not in optional_params.keys():
for k in non_default_params:
if k not in optional_params:
if k in supported_params:
optional_params[k] = non_default_params[k]
elif drop_params:

2
litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
View file

@ -2480,7 +2480,7 @@ class MCPServerManager:
# Filter arguments to only include allowed parameters
disallowed_params = [
param for param in arguments.keys() if param not in allowed_params_list
param for param in arguments if param not in allowed_params_list
]
if disallowed_params:

2
litellm/proxy/_experimental/mcp_server/openapi_to_mcp_generator.py
View file

@ -115,7 +115,7 @@ async def load_openapi_spec_async(filepath: str) -> Dict[str, Any]:
# Local filesystem path
if not os.path.exists(filepath):
raise FileNotFoundError(f"OpenAPI spec not found at {filepath}")
with open(filepath, "r", encoding="utf-8") as f:
with open(filepath, encoding="utf-8") as f:
return json.load(f)

2
litellm/proxy/_types.py
View file

@ -3951,7 +3951,7 @@ class OrgMemberAddRequest(LiteLLMPydanticObjectBase):
if all(isinstance(item, dict) for item in member_data):
members = [OrgMember(**item) for item in member_data]
else:
members = [item for item in member_data]
members = list(member_data)
# Replace member_data with the list of Member objects
data["member"] = members
elif isinstance(member_data, dict):

4
litellm/proxy/client/cli/commands/auth.py
View file

@ -40,9 +40,9 @@ def load_token() -> Optional[Dict[str, Any]]:
return None
try:
with open(token_file, "r") as f:
with open(token_file) as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
except (OSError, json.JSONDecodeError):
return None

2
litellm/proxy/client/cli/commands/chat.py
View file

@ -305,7 +305,7 @@ def _load_conversation(
filename += ".json"
try:
with open(filename, "r") as f:
with open(filename) as f:
messages = json.load(f)
console.print(f"[green]Conversation loaded from {filename}[/green]")
return messages

2
litellm/proxy/client/cli/commands/models.py
View file

@ -392,7 +392,7 @@ def _print_summary_table(provider_counts):
def get_model_list_from_yaml_file(yaml_file: str) -> list[dict[str, Any]]:
"""Load and validate the model list from a YAML file."""
with open(yaml_file, "r") as f:
with open(yaml_file) as f:
data = yaml.safe_load(f)
if not data or "model_list" not in data:
raise click.ClickException(

4
litellm/proxy/credential_endpoints/endpoints.py
View file

@ -285,9 +285,7 @@ def update_db_credential(
# update litellm params
if encrypted_credential.credential_values:
# Encrypt any sensitive values
encrypted_params = {
k: v for k, v in encrypted_credential.credential_values.items()
}
encrypted_params = dict(encrypted_credential.credential_values.items())
merged_credential.credential_values.update(encrypted_params)

6
litellm/proxy/db/db_spend_update_writer.py
View file

@ -1306,7 +1306,7 @@ class DBSpendUpdateWriter:
):
# Track which team memberships will be updated for cache invalidation
team_memberships_to_invalidate: List[tuple[str, str]] = []
for key in team_member_list_transactions.keys():
for key in team_member_list_transactions:
# key is "team_id::<value>::user_id::<value>"
team_id = key.split("::")[1]
user_id = key.split("::")[3]
@ -1786,7 +1786,7 @@ class DBSpendUpdateWriter:
)
# Remove processed transactions
for key in transactions_to_process.keys():
for key in transactions_to_process:
daily_spend_transactions.pop(key, None)
break
@ -1809,7 +1809,7 @@ class DBSpendUpdateWriter:
except Exception as e:
if "transactions_to_process" in locals():
for key in transactions_to_process.keys(): # type: ignore
for key in transactions_to_process: # type: ignore
daily_spend_transactions.pop(key, None)
_raise_failed_update_spend_exception(
e=e, start_time=start_time, proxy_logging_obj=proxy_logging_obj

4
litellm/proxy/guardrails/guardrail_endpoints.py
View file

@ -1443,7 +1443,7 @@ async def get_category_yaml(category_name: str):
try:
# Read and return the raw content
with open(category_file_path, "r") as f:
with open(category_file_path) as f:
content = f.read()
return {
@ -1480,7 +1480,7 @@ async def get_major_airlines():
detail="major_airlines.json not found",
)
try:
with open(airlines_path, "r", encoding="utf-8") as f:
with open(airlines_path, encoding="utf-8") as f:
import json
airlines = json.load(f)

2
litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py
View file

@ -268,7 +268,7 @@ class GenericGuardrailAPI(CustomGuardrail):
# Dynamically iterate through GenericGuardrailAPIMetadata fields
# and extract matching fields from the source metadata
# Fields in metadata are already prefixed with 'user_api_key_'
for field_name in GenericGuardrailAPIMetadata.__annotations__.keys():
for field_name in GenericGuardrailAPIMetadata.__annotations__:
value = metadata_dict.get(field_name)
if value is not None:
result_metadata[field_name] = value # type: ignore[literal-required]

2
litellm/proxy/guardrails/guardrail_hooks/ibm_guardrails/ibm_detector.py
View file

@ -164,7 +164,7 @@ class IBMGuardrailDetector(CustomGuardrail):
guardrail_provider=self.guardrail_provider,
guardrail_json_response={
"detections": [
[detection for detection in message_detections]
list(message_detections)
for message_detections in response_json
]
},

4
litellm/proxy/guardrails/guardrail_hooks/lakera_ai.py
View file

@ -168,9 +168,7 @@ class lakeraAI_Moderation(CustomGuardrail):
stringified_roles.append(role.value)
elif isinstance(role, str):
stringified_roles.append(role)
lakera_input_dict: Dict = {
role: None for role in INPUT_POSITIONING_MAP.keys()
}
lakera_input_dict: Dict = dict.fromkeys(INPUT_POSITIONING_MAP.keys())
system_message = None
tool_call_messages: List = []
for message in data["messages"]:

6
litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/content_filter.py
View file

@ -601,7 +601,7 @@ class ContentFilterGuardrail(CustomGuardrail):
"""
if file_path.lower().endswith(".json"):
return self._load_category_file_json(file_path)
with open(file_path, "r") as f:
with open(file_path) as f:
data = yaml.safe_load(f)
# Handle always_block_keywords if present
@ -627,7 +627,7 @@ class ContentFilterGuardrail(CustomGuardrail):
Each entry has: id, match (pipe-separated phrases), tags, severity (1-4).
Severity mapping: 4,3 -> high; 2 -> medium; 1 -> low.
"""
with open(file_path, "r") as f:
with open(file_path) as f:
entries = json.load(f)
if not isinstance(entries, list):
entries = [entries]
@ -733,7 +733,7 @@ class ContentFilterGuardrail(CustomGuardrail):
```
"""
try:
with open(file_path, "r") as f:
with open(file_path) as f:
data = yaml.safe_load(f)
if not isinstance(data, dict) or "blocked_words" not in data:

2
litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/test_eval.py
View file

@ -37,7 +37,7 @@ def _load_jsonl(filename: str) -> List[dict]:
"""Load eval cases from a JSONL file. One JSON object per line."""
cases = []
path = os.path.join(EVAL_DIR, filename)
with open(path, "r") as f:
with open(path) as f:
for line in f:
line = line.strip()
if not line:

4
litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/patterns.py
View file

@ -15,7 +15,7 @@ from typing import Any, Dict, List, Pattern
def _load_patterns_from_json() -> Dict:
"""Load pattern definitions from patterns.json file"""
json_path = os.path.join(os.path.dirname(__file__), "patterns.json")
with open(json_path, "r") as f:
with open(json_path) as f:
return json.load(f)
@ -158,7 +158,7 @@ def get_available_content_categories() -> List[Dict[str, str]]:
if filename.endswith(".yaml") or filename.endswith(".yml"):
category_file_path = os.path.join(categories_dir, filename)
try:
with open(category_file_path, "r") as f:
with open(category_file_path) as f:
category_data = yaml.safe_load(f)
if category_data and "category_name" in category_data:

2
litellm/proxy/guardrails/guardrail_hooks/presidio.py
View file

@ -142,7 +142,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
ad_hoc_recognizers = presidio_ad_hoc_recognizers
if ad_hoc_recognizers is not None:
try:
with open(ad_hoc_recognizers, "r") as file:
with open(ad_hoc_recognizers) as file:
self.ad_hoc_recognizers = json.load(file)
except FileNotFoundError:
raise Exception(f"File not found. file_path={ad_hoc_recognizers}")

4
litellm/proxy/guardrails/guardrail_hooks/semantic_guard/route_loader.py
View file

@ -35,7 +35,7 @@ class SemanticGuardRouteLoader:
f"SemanticGuard: unknown route template '{template_name}'. "
f"Available templates: {SemanticGuardRouteLoader.list_builtin_templates()}"
)
with open(file_path, "r") as f:
with open(file_path) as f:
return yaml.safe_load(f)
@staticmethod
@ -55,7 +55,7 @@ class SemanticGuardRouteLoader:
raise ValueError(
f"SemanticGuard: custom routes file not found: {file_path}"
)
with open(file_path, "r") as f:
with open(file_path) as f:
data = yaml.safe_load(f)
if isinstance(data, list):
return data

2
litellm/proxy/hooks/batch_redis_get.py
View file

@ -57,7 +57,7 @@ class _PROXY_BatchRedisRequests(CustomLogger):
key_value_dict = {}
in_memory_cache_exists = False
for key in cache.in_memory_cache.cache_dict.keys():
for key in cache.in_memory_cache.cache_dict:
if isinstance(key, str) and key.startswith(cache_key_name):
in_memory_cache_exists = True

6
litellm/proxy/hooks/litellm_skills/main.py
View file

@ -173,7 +173,7 @@ class SkillsInjectionHook(CustomLogger):
skill_files = self.prompt_handler.extract_all_files(skill)
if skill_files:
all_skill_files[skill.skill_id] = skill_files
for path in skill_files.keys():
for path in skill_files:
if path.endswith(".py"):
all_module_paths.append(path)
@ -240,7 +240,7 @@ class SkillsInjectionHook(CustomLogger):
if skill_files:
all_skill_files[skill.skill_id] = skill_files
# Collect Python module paths
for path in skill_files.keys():
for path in skill_files:
if path.endswith(".py"):
all_module_paths.append(path)
@ -637,7 +637,7 @@ class SkillsInjectionHook(CustomLogger):
# Look for Python modules in the skill
python_modules = [
p
for p in skill_files.keys()
for p in skill_files
if p.endswith(".py") and not p.endswith("__init__.py")
]

2
litellm/proxy/management_endpoints/callback_management_endpoints.py
View file

@ -49,7 +49,7 @@ async def get_callback_configs():
"callback_configs.json",
)
with open(config_path, "r") as f:
with open(config_path) as f:
configs = json.load(f)
return configs

4
litellm/proxy/management_endpoints/cost_tracking_settings.py
View file

@ -199,7 +199,7 @@ async def update_cost_discount_config(
# Validate that all providers are valid LiteLLM providers
invalid_providers = []
for provider in cost_discount_config.keys():
for provider in cost_discount_config:
if provider not in LlmProvidersSet:
invalid_providers.append(provider)
@ -343,7 +343,7 @@ async def update_cost_margin_config(
# Validate that all providers are valid LiteLLM providers (except "global")
invalid_providers = []
for provider in cost_margin_config.keys():
for provider in cost_margin_config:
if provider != "global" and provider not in LlmProvidersSet:
invalid_providers.append(provider)

6
litellm/proxy/management_endpoints/customer_endpoints.py
View file

@ -355,7 +355,7 @@ async def new_end_user(
_user_data = data.dict(exclude_none=True)
for k, v in _user_data.items():
if k not in BudgetNewRequest.model_fields.keys():
if k not in BudgetNewRequest.model_fields:
new_end_user_obj[k] = v
## Handle Object Permission - MCP Servers, Vector Stores etc.
@ -595,10 +595,10 @@ async def update_end_user(
# budget_id is for linking to existing budget, not for creating new budget
if k == "budget_id":
update_end_user_table_data[k] = v
elif k in LiteLLM_BudgetTable.model_fields.keys():
elif k in LiteLLM_BudgetTable.model_fields:
budget_table_data[k] = v
elif k in LiteLLM_EndUserTable.model_fields.keys():
elif k in LiteLLM_EndUserTable.model_fields:
update_end_user_table_data[k] = v
## Handle object permission updates (MCP servers, vector stores, etc.)

2
litellm/proxy/management_endpoints/internal_user_endpoints.py
View file

@ -500,7 +500,7 @@ async def new_user(
special_keys = ["token", "token_id"]
response_dict = {}
for key, value in response.items():
if key in NewUserResponse.model_fields.keys() and key not in special_keys:
if key in NewUserResponse.model_fields and key not in special_keys:
response_dict[key] = value
response_dict["key"] = response.get("token", "")

4
litellm/proxy/management_endpoints/mcp_management_endpoints.py
View file

@ -2267,7 +2267,7 @@ if MCP_AVAILABLE:
if _mcp_registry_cache is not None:
return _mcp_registry_cache
try:
with open(_MCP_REGISTRY_PATH, "r") as f:
with open(_MCP_REGISTRY_PATH) as f:
data: Dict[str, Any] = json.load(f)
except Exception as e:
verbose_proxy_logger.warning(
@ -2341,7 +2341,7 @@ if MCP_AVAILABLE:
@functools.lru_cache(maxsize=1)
def _load_openapi_registry() -> Dict[str, Any]:
with open(_OPENAPI_REGISTRY_PATH, "r") as f:
with open(_OPENAPI_REGISTRY_PATH) as f:
data: Dict[str, Any] = json.load(f)
return data

4
litellm/proxy/management_endpoints/organization_endpoints.py
View file

@ -559,7 +559,7 @@ async def update_organization(
budget_fields = {
k: v
for k, v in data.model_dump().items()
if k in LiteLLM_BudgetTable.model_fields.keys() and v is not None
if k in LiteLLM_BudgetTable.model_fields and v is not None
}
if budget_fields and existing_organization_row.budget_id:
@ -571,7 +571,7 @@ async def update_organization(
)
# Remove budget fields from organization update data
for field in LiteLLM_BudgetTable.model_fields.keys():
for field in LiteLLM_BudgetTable.model_fields:
updated_organization_row.pop(field, None)
response = await prisma_client.db.litellm_organizationtable.update(

2
litellm/proxy/management_endpoints/policy_endpoints/endpoints.py
View file

@ -633,7 +633,7 @@ def _load_policy_templates_from_local_backup() -> list:
path = os.path.abspath(backup_path)
if not os.path.exists(path):
return []
with open(path, "r") as f:
with open(path) as f:
return json.load(f)

2
litellm/proxy/management_endpoints/usage_endpoints/ai_usage_chat.py
View file

@ -312,7 +312,7 @@ def _accumulate_breakdown(
for day in results:
for key, entry in day.get("breakdown", {}).get(dimension, {}).items():
if key not in totals:
totals[key] = {f: 0.0 for f in fields}
totals[key] = dict.fromkeys(fields, 0.0)
m = entry.get("metrics", {})
for f in fields:
totals[key][f] += m.get(f, 0)

2
litellm/proxy/openai_files_endpoints/storage_backend_service.py
View file

@ -223,7 +223,7 @@ class StorageBackendFileService:
managed_files_obj = cast(Any, managed_files_obj)
# Create model mappings using storage URL
model_mappings = {model_name: storage_url for model_name in target_model_names}
model_mappings = dict.fromkeys(target_model_names, storage_url)
# Create unified file ID
file_type = file_data.get("content_type", "application/octet-stream")

4
litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
View file

@ -2499,7 +2499,7 @@ class InitPassThroughEndpointHelpers:
# Keys are in format: "{endpoint_id}:exact:{path}:{methods}" or "{endpoint_id}:subpath:{path}:{methods}"
# For backward compatibility, also support old format: "{endpoint_id}:exact:{path}" or "{endpoint_id}:subpath:{path}"
# Extract unique paths from keys for quick checking
for key in _registered_pass_through_routes.keys():
for key in _registered_pass_through_routes:
parts = key.split(":", 3) # Split into [endpoint_id, type, path, methods?]
if len(parts) >= 3:
route_type = parts[1]
@ -2521,7 +2521,7 @@ class InitPassThroughEndpointHelpers:
route: str, method: Optional[str] = None
) -> Optional[Dict[str, Any]]:
"""Get passthrough params for a given route and optionally filter by HTTP method"""
for key in _registered_pass_through_routes.keys():
for key in _registered_pass_through_routes:
parts = key.split(":", 3) # Split into [endpoint_id, type, path, methods?]
if len(parts) >= 3:
route_type = parts[1]

8
litellm/proxy/pass_through_endpoints/passthrough_guardrails.py
View file

@ -60,7 +60,7 @@ class PassthroughGuardrailHandler:
# List of guardrail names - convert to dict
if isinstance(guardrails_config, list):
return {name: None for name in guardrails_config}
return dict.fromkeys(guardrails_config)
verbose_proxy_logger.debug(
"Passthrough guardrails config is not a dict or list, got: %s",
@ -200,9 +200,7 @@ class PassthroughGuardrailHandler:
request_data["metadata"] = {}
# Set guardrails in metadata using dict format for compatibility
request_data["metadata"]["guardrails"] = {
name: True for name in guardrail_names
}
request_data["metadata"]["guardrails"] = dict.fromkeys(guardrail_names, True)
# Store passthrough guardrails config in request-scoped context
set_passthrough_guardrails_config(guardrails_config)
@ -260,7 +258,7 @@ class PassthroughGuardrailHandler:
guardrails_to_run: Dict[str, bool] = {}
# Add passthrough-specific guardrails
for guardrail_name in normalized_config.keys():
for guardrail_name in normalized_config:
guardrails_to_run[guardrail_name] = True
verbose_proxy_logger.debug(
"Added passthrough-specific guardrail: %s", guardrail_name

2
litellm/proxy/prompts/prompt_endpoints.py
View file

@ -151,7 +151,7 @@ def get_latest_version_prompt_id(prompt_id: str, all_prompt_ids: Dict[str, Any])
# Find all versions of this prompt
matching_versions = []
for stored_prompt_id in all_prompt_ids.keys():
for stored_prompt_id in all_prompt_ids:
if get_base_prompt_id(prompt_id=stored_prompt_id) == base_id:
version_num = get_version_number(prompt_id=stored_prompt_id)
matching_versions.append((version_num, stored_prompt_id))

2
litellm/proxy/prompts/prompt_registry.py
View file

@ -188,7 +188,7 @@ class InMemoryPromptRegistry:
prompts_to_delete = [
pid
for pid in self.IN_MEMORY_PROMPTS.keys()
for pid in self.IN_MEMORY_PROMPTS
if get_base_prompt_id(prompt_id=pid) == base_prompt_id
]

10
litellm/proxy/proxy_server.py
View file

@ -1610,7 +1610,7 @@ try:
):
continue
try:
with open(file_path, "r", encoding="utf-8") as f:
with open(file_path, encoding="utf-8") as f:
content = f.read()
# Replace the asset prefix with the server root path
@ -3432,7 +3432,7 @@ class ProxyConfig:
Load and parse a YAML file
"""
try:
with open(file_path, "r") as file:
with open(file_path) as file:
return yaml.safe_load(file) or {}
except Exception as e:
raise Exception(f"Error loading yaml file {file_path}: {str(e)}")
@ -3455,7 +3455,7 @@ class ProxyConfig:
# Load existing config
## Yaml
if os.path.exists(f"{file_path}"):
with open(f"{file_path}", "r") as config_file:
with open(f"{file_path}") as config_file:
config = yaml.safe_load(config_file)
elif file_path is not None:
raise Exception(f"Config file not found: {file_path}")
@ -6254,7 +6254,7 @@ class ProxyConfig:
# Count providers in config
provider_count = sum(
1
for k in new_config.keys()
for k in new_config
if k != "provider_aliases" and k != "description"
)
verbose_proxy_logger.info(
@ -15311,7 +15311,7 @@ async def reload_anthropic_beta_headers(
await invalidate_config_param("anthropic_beta_headers_reload_config")
provider_count = sum(
1 for k in new_config.keys() if k not in ["provider_aliases", "description"]
1 for k in new_config if k not in ["provider_aliases", "description"]
)
verbose_proxy_logger.info(
f"Anthropic beta headers config reloaded successfully in current pod. Providers: {provider_count}"

6
litellm/proxy/public_endpoints/public_endpoints.py
View file

@ -350,7 +350,7 @@ async def get_provider_fields() -> List[ProviderCreateInfo]:
"provider_create_fields.json",
)
with open(provider_create_fields_path, "r") as f:
with open(provider_create_fields_path) as f:
provider_create_fields = json.load(f)
return provider_create_fields
@ -440,10 +440,10 @@ async def get_agent_fields() -> List[AgentCreateInfo]:
agent_create_fields_path = os.path.join(base_path, "agent_create_fields.json")
provider_create_fields_path = os.path.join(base_path, "provider_create_fields.json")
with open(agent_create_fields_path, "r") as f:
with open(agent_create_fields_path) as f:
agent_create_fields = json.load(f)
with open(provider_create_fields_path, "r") as f:
with open(provider_create_fields_path) as f:
provider_create_fields = json.load(f)
# Build a lookup map for providers by name

2
litellm/proxy/spend_tracking/spend_tracking_utils.py
View file

@ -118,7 +118,7 @@ def _get_spend_logs_metadata(
# Filter the metadata dictionary to include only the specified keys
clean_metadata = SpendLogsMetadata(
**{ # type: ignore
key: metadata.get(key) for key in SpendLogsMetadata.__annotations__.keys()
key: metadata.get(key) for key in SpendLogsMetadata.__annotations__
}
)
clean_metadata["applied_guardrails"] = applied_guardrails

4
litellm/responses/utils.py
View file

@ -47,7 +47,7 @@ class ResponsesAPIRequestUtils:
if supported_params is None:
return
unsupported_params = {}
for k in non_default_params.keys():
for k in non_default_params:
if k not in supported_params:
unsupported_params[k] = non_default_params[k]
if unsupported_params:
@ -139,7 +139,7 @@ class ResponsesAPIRequestUtils:
special_params=special_params,
custom_llm_provider=custom_llm_provider,
additional_drop_params=additional_drop_params,
default_param_values={k: None for k in valid_keys},
default_param_values=dict.fromkeys(valid_keys),
additional_endpoint_specific_params=["input"],
)
)

6
litellm/router.py
View file

@ -7752,7 +7752,7 @@ class Router:
litellm_params=litellm_params,
model_info=_model_info,
)
for field in CustomPricingLiteLLMParams.model_fields.keys():
for field in CustomPricingLiteLLMParams.model_fields:
if deployment.litellm_params.get(field) is not None:
_model_info[field] = deployment.litellm_params[field]
@ -8490,7 +8490,7 @@ class Router:
self._add_deployment(deployment=deployment)
_model_info_dict: dict = deployment.model_info.model_dump(exclude_none=True)
for field in CustomPricingLiteLLMParams.model_fields.keys():
for field in CustomPricingLiteLLMParams.model_fields:
field_value = deployment.litellm_params.get(field)
if field_value is not None:
_model_info_dict[field] = field_value
@ -9664,7 +9664,7 @@ class Router:
else:
# When model_name is None, return all model IDs
# Use the index map keys for O(n) where n = total deployments
for model_id in self.model_id_to_deployment_index_map.keys():
for model_id in self.model_id_to_deployment_index_map:
idx = self.model_id_to_deployment_index_map[model_id]
model = self.model_list[idx]
if "model_info" in model and "id" in model["model_info"]:

4
litellm/router_utils/fallback_event_handlers.py
View file

@ -244,8 +244,8 @@ def _check_non_standard_fallback_format(fallbacks: Optional[List[Any]]) -> bool:
if all(isinstance(item, str) for item in fallbacks):
return True
elif all(isinstance(item, dict) for item in fallbacks):
for key in LiteLLMParamsTypedDict.__annotations__.keys():
if key in fallbacks[0].keys():
for key in LiteLLMParamsTypedDict.__annotations__:
if key in fallbacks[0]:
return True
return False

6
litellm/secret_managers/main.py
View file

@ -251,13 +251,13 @@ def get_secret( # noqa: PLR0915
error_msg = f"Azure OIDC provider failed: {str(e)}"
verbose_logger.error(error_msg)
raise ValueError(error_msg)
with open(azure_federated_token_file, "r") as f:
with open(azure_federated_token_file) as f:
oidc_token = f.read()
return oidc_token
elif oidc_provider == "file":
# Load token from a file within an allowed credential directory.
safe_path = _resolve_oidc_file_path(oidc_aud)
with open(safe_path, "r") as f:
with open(safe_path) as f:
oidc_token = f.read()
return oidc_token
elif oidc_provider == "env":
@ -271,7 +271,7 @@ def get_secret( # noqa: PLR0915
token_file_path = os.getenv(oidc_aud)
if token_file_path is None:
raise ValueError(f"Environment variable {oidc_aud} not found")
with open(token_file_path, "r") as f:
with open(token_file_path) as f:
oidc_token = f.read()
return oidc_token
else:

22
litellm/utils.py
View file

@ -3303,7 +3303,7 @@ def get_optional_params_embeddings( # noqa: PLR0915
if supported_params is None:
return
unsupported_params = {}
for k in non_default_params.keys():
for k in non_default_params:
if k not in supported_params:
unsupported_params[k] = non_default_params[k]
if unsupported_params:
@ -3371,7 +3371,7 @@ def get_optional_params_embeddings( # noqa: PLR0915
if (
model is not None
and "text-embedding-3" not in model
and "dimensions" in non_default_params.keys()
and "dimensions" in non_default_params
and "dimensions" not in (allowed_openai_params or [])
):
raise UnsupportedParamsError(
@ -3712,7 +3712,7 @@ def _remove_unsupported_params(
remove_keys = []
if supported_openai_params is None:
return {} # no supported params, so no optional openai params to send
for param in non_default_params.keys():
for param in non_default_params:
if param not in supported_openai_params:
remove_keys.append(param)
for key in remove_keys:
@ -3809,7 +3809,7 @@ class PreProcessNonDefaultParams:
special_params=special_params,
custom_llm_provider=custom_llm_provider,
additional_drop_params=additional_drop_params,
default_param_values={k: None for k in OPENAI_EMBEDDING_PARAMS},
default_param_values=dict.fromkeys(OPENAI_EMBEDDING_PARAMS),
additional_endpoint_specific_params=["input"],
)
)
@ -3893,7 +3893,7 @@ def remove_sensitive_keys_from_dict(d: dict) -> dict:
"""
sensitive_key_phrases = ["key", "secret", "access", "credential"]
remove_keys = []
for key in d.keys():
for key in d:
if any(phrase in key.lower() for phrase in sensitive_key_phrases):
remove_keys.append(key)
for key in remove_keys:
@ -4090,7 +4090,7 @@ def get_optional_params( # noqa: PLR0915
f"\nLiteLLM: Non-Default params passed to completion() {non_default_params}"
)
unsupported_params = {}
for k in non_default_params.keys():
for k in non_default_params:
if k not in supported_params:
if k == "user" or k == "stream_options" or k == "stream":
continue
@ -4108,7 +4108,7 @@ def get_optional_params( # noqa: PLR0915
if litellm.drop_params is True or (
drop_params is not None and drop_params is True
):
for k in unsupported_params.keys():
for k in unsupported_params:
non_default_params.pop(k, None)
else:
raise UnsupportedParamsError(
@ -4692,7 +4692,7 @@ def get_optional_params( # noqa: PLR0915
),
)
# WatsonX-text param check
for param in passed_params.keys():
for param in passed_params:
if litellm.IBMWatsonXAIConfig().is_watsonx_text_param(param):
raise ValueError(
f"LiteLLM now defaults to Watsonx's `/text/chat` endpoint. Please use the `watsonx_text` provider instead, to call the `/text/generation` endpoint. Param: {param}"
@ -4853,7 +4853,7 @@ def add_provider_specific_params_to_optional_params(
is False
):
extra_body = passed_params.pop("extra_body", None) or {}
for k in passed_params.keys():
for k in passed_params:
if k not in openai_params and passed_params[k] is not None:
extra_body[k] = passed_params[k]
if not isinstance(optional_params.get("extra_body"), dict):
@ -4879,7 +4879,7 @@ def add_provider_specific_params_to_optional_params(
extra_body=processed_extra_body
)
else:
for k in passed_params.keys():
for k in passed_params:
if k not in openai_params and passed_params[k] is not None:
if _should_drop_param(
k=k, additional_drop_params=additional_drop_params
@ -7153,7 +7153,7 @@ def read_config_args(config_path) -> dict:
import os
os.getcwd()
with open(config_path, "r") as config_file:
with open(config_path) as config_file:
config = json.load(config_file)
# read keys/ values from config file and return them