perf: optimize python comprehensions and dictionary iterations

This PR resolves multiple Python performance recommendations from `ruff` (PERF401, PERF403, SIM118, C416, C420, UP015) across the codebase.

- Replaced `.keys()` on dict iterations with direct iteration for improved speed (SIM118)
- Streamlined unnecessary generator and dictionary comprehensions (C416, C420)
- Optimized file open modes and OS error aliases (UP015, UP024)

These are entirely safe AST-level syntactic updates that bring the codebase closer to modern Python best practices and marginally improve overhead on large looping operations.

*(Refactored using the open-source [0-editor](https://github.com/0-protocol/0-editor))*

enterprise/litellm_enterprise/proxy/management_endpoints/project_endpoints.py

@@ -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

litellm/assistants/utils.py

@@ -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():
+    for k in passed_params:
-        if k not in default_params.keys():
+        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():
+    for k in passed_params:
-        if k not in default_params.keys():
+        if k not in default_params:
             optional_params[k] = passed_params[k]
     return optional_params

litellm/batch_completion/main.py

@@ -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.

litellm/budget_manager.py

@@ -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!")

litellm/completion_extras/litellm_responses_transformation/transformation.py

@@ -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

litellm/constants.py

@@ -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,

litellm/integrations/datadog/datadog_llm_obs.py

@@ -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 []

litellm/integrations/dotprompt/prompt_manager.py

@@ -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]
 

litellm/integrations/generic_api/generic_api_callback.py

@@ -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(

litellm/interactions/utils.py

@@ -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={
+                default_param_values=dict.fromkeys(INTERACTIONS_API_OPTIONAL_PARAMS),
-                    k: None for k in INTERACTIONS_API_OPTIONAL_PARAMS
-                },
                 additional_endpoint_specific_params=["input", "model", "agent"],
             )
         )

litellm/litellm_core_utils/audio_utils/utils.py

@@ -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

litellm/litellm_core_utils/cli_token_utils.py

@@ -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
 
 

litellm/litellm_core_utils/litellm_logging.py

@@ -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_hash="test_hash",
-        user_api_key_alias=str("test_alias"),
+        user_api_key_alias="test_alias",
-        user_api_key_team_id=str("test_team"),
+        user_api_key_team_id="test_team",
-        user_api_key_user_id=str("test_user"),
+        user_api_key_user_id="test_user",
-        user_api_key_team_alias=str("test_team_alias"),
+        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"),
+        id="test_id",
-        call_type=str("completion"),
+        call_type="completion",
-        stream=bool(False),
+        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="gpt-3.5-turbo",
-        model_id=str("model-123"),
+        model_id="model-123",
-        model_group=str("openai-gpt"),
+        model_group="openai-gpt",
-        custom_llm_provider=str("openai"),
+        custom_llm_provider="openai",
-        api_base=str("https://api.openai.com"),
+        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,

litellm/litellm_core_utils/logging_utils.py

@@ -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):

litellm/litellm_core_utils/model_response_utils.py

@@ -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

litellm/litellm_core_utils/prompt_templates/factory.py

@@ -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
 

litellm/litellm_core_utils/streaming_handler.py

@@ -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
 

litellm/llms/aiml/image_generation/transformation.py

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

litellm/llms/bedrock/base_aws_llm.py

@@ -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(

litellm/llms/bedrock/embed/cohere_transformation.py

@@ -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
 

litellm/llms/bedrock/vector_stores/transformation.py

@@ -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

litellm/llms/chatgpt/authenticator.py

@@ -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:

litellm/llms/cohere/embed/handler.py

@@ -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:

litellm/llms/cometapi/image_generation/transformation.py

@@ -47,8 +47,8 @@ class CometAPIImageGenerationConfig(BaseImageGenerationConfig):
     ) -> dict:
         supported_params = self.get_supported_openai_params(model)
 
-        for k in non_default_params.keys():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            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]

litellm/llms/fal_ai/image_generation/bria_transformation.py

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

litellm/llms/fal_ai/image_generation/bytedance_transformation.py

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

litellm/llms/fal_ai/image_generation/flux_pro_v11_transformation.py

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

litellm/llms/fal_ai/image_generation/flux_pro_v11_ultra_transformation.py

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

litellm/llms/fal_ai/image_generation/flux_schnell_transformation.py

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

litellm/llms/fal_ai/image_generation/ideogram_v3_transformation.py

@@ -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
 

litellm/llms/fal_ai/image_generation/imagen4_transformation.py

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

litellm/llms/fal_ai/image_generation/recraft_v3_transformation.py

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

litellm/llms/fal_ai/image_generation/stable_diffusion_transformation.py

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

litellm/llms/fal_ai/image_generation/transformation.py

@@ -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():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            if k not in optional_params:
                 if k in supported_params:
                     optional_params[k] = non_default_params[k]
                 elif drop_params:

litellm/llms/gemini/image_generation/transformation.py

@@ -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":

litellm/llms/github_copilot/authenticator.py

@@ -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
 

litellm/llms/huggingface/embedding/transformation.py

@@ -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

litellm/llms/openai/image_generation/dall_e_2_transformation.py

@@ -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():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            if k not in optional_params:
                 if k in supported_params:
                     optional_params[k] = non_default_params[k]
                 elif drop_params:

litellm/llms/openai/image_generation/dall_e_3_transformation.py

@@ -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():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            if k not in optional_params:
                 if k in supported_params:
                     optional_params[k] = non_default_params[k]
                 elif drop_params:

litellm/llms/openai/image_generation/gpt_transformation.py

@@ -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():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            if k not in optional_params:
                 if k in supported_params:
                     optional_params[k] = non_default_params[k]
                 elif drop_params:

litellm/llms/openai/transcriptions/whisper_transformation.py

@@ -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:

litellm/llms/recraft/image_generation/transformation.py

@@ -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():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            if k not in optional_params:
                 if k in supported_params:
                     optional_params[k] = non_default_params[k]
                 elif drop_params:

litellm/llms/runwayml/image_generation/transformation.py

@@ -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():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            if k not in optional_params:
                 if k in supported_params:
                     optional_params[k] = non_default_params[k]
                 elif drop_params:

litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py

@@ -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,

litellm/llms/vertex_ai/image_generation/vertex_gemini_transformation.py

@@ -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":

litellm/llms/vertex_ai/image_generation/vertex_imagen_transformation.py

@@ -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":

litellm/llms/xinference/image_generation/transformation.py

@@ -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():
+        for k in non_default_params:
-            if k not in optional_params.keys():
+            if k not in optional_params:
                 if k in supported_params:
                     optional_params[k] = non_default_params[k]
                 elif drop_params:

litellm/proxy/_experimental/mcp_server/mcp_server_manager.py

@@ -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:

litellm/proxy/_experimental/mcp_server/openapi_to_mcp_generator.py

@@ -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)
 
 

litellm/proxy/_types.py

@@ -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):

litellm/proxy/client/cli/commands/auth.py

@@ -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
 
 

litellm/proxy/client/cli/commands/chat.py

@@ -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

litellm/proxy/client/cli/commands/models.py

@@ -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(

litellm/proxy/credential_endpoints/endpoints.py

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

litellm/proxy/db/db_spend_update_writer.py

@@ -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

litellm/proxy/guardrails/guardrail_endpoints.py

@@ -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)

litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py

@@ -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]

litellm/proxy/guardrails/guardrail_hooks/ibm_guardrails/ibm_detector.py

@@ -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
                         ]
                     },

litellm/proxy/guardrails/guardrail_hooks/lakera_ai.py

@@ -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 = {
+            lakera_input_dict: Dict = dict.fromkeys(INPUT_POSITIONING_MAP.keys())
-                role: None for role in INPUT_POSITIONING_MAP.keys()
-            }
             system_message = None
             tool_call_messages: List = []
             for message in data["messages"]:

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/content_filter.py

@@ -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:

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/test_eval.py

@@ -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:

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/patterns.py

@@ -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:

litellm/proxy/guardrails/guardrail_hooks/presidio.py

@@ -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}")

litellm/proxy/guardrails/guardrail_hooks/semantic_guard/route_loader.py

@@ -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

litellm/proxy/hooks/batch_redis_get.py

@@ -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
 

litellm/proxy/hooks/litellm_skills/main.py

@@ -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")
         ]
 

litellm/proxy/management_endpoints/callback_management_endpoints.py

@@ -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

litellm/proxy/management_endpoints/cost_tracking_settings.py

@@ -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)
 

litellm/proxy/management_endpoints/customer_endpoints.py

@@ -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.)

litellm/proxy/management_endpoints/internal_user_endpoints.py

@@ -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", "")

litellm/proxy/management_endpoints/mcp_management_endpoints.py

@@ -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
 

litellm/proxy/management_endpoints/organization_endpoints.py

@@ -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(

litellm/proxy/management_endpoints/policy_endpoints/endpoints.py

@@ -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)
 
 

litellm/proxy/management_endpoints/usage_endpoints/ai_usage_chat.py

@@ -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)

litellm/proxy/openai_files_endpoints/storage_backend_service.py

@@ -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")

litellm/proxy/pass_through_endpoints/pass_through_endpoints.py

@@ -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]

litellm/proxy/pass_through_endpoints/passthrough_guardrails.py

@@ -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"] = {
+        request_data["metadata"]["guardrails"] = dict.fromkeys(guardrail_names, True)
-            name: True for name in guardrail_names
-        }
 
         # 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

litellm/proxy/prompts/prompt_endpoints.py

@@ -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))

litellm/proxy/prompts/prompt_registry.py

@@ -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
         ]
 

litellm/proxy/proxy_server.py

@@ -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}"

litellm/proxy/public_endpoints/public_endpoints.py

@@ -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

litellm/proxy/spend_tracking/spend_tracking_utils.py

@@ -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

litellm/responses/utils.py

@@ -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"],
             )
         )

litellm/router.py

@@ -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"]:

litellm/router_utils/fallback_event_handlers.py

@@ -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():
+        for key in LiteLLMParamsTypedDict.__annotations__:
-            if key in fallbacks[0].keys():
+            if key in fallbacks[0]:
                 return True
 
     return False

litellm/secret_managers/main.py

@@ -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:

litellm/utils.py

@@ -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