diff --git a/litellm/__init__.py b/litellm/__init__.py index 595a0132099..3d40a9b15cf 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -1056,57 +1056,10 @@ from .timeout import timeout from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider from litellm.litellm_core_utils.core_helpers import remove_index_from_tool_calls from litellm.litellm_core_utils.token_counter import get_modified_max_tokens -from .utils import ( - client, - exception_type, - get_optional_params, - get_response_string, - token_counter, - create_pretrained_tokenizer, - create_tokenizer, - supports_function_calling, - supports_web_search, - supports_url_context, - supports_response_schema, - supports_parallel_function_calling, - supports_vision, - supports_audio_input, - supports_audio_output, - supports_system_messages, - supports_reasoning, - get_litellm_params, - acreate, - get_max_tokens, - get_model_info, - register_prompt_template, - validate_environment, - check_valid_key, - register_model, - encode, - decode, - _calculate_retry_after, - _should_retry, - get_supported_openai_params, - get_api_base, - get_first_chars_messages, - ModelResponse, - ModelResponseStream, - EmbeddingResponse, - ImageResponse, - TranscriptionResponse, - TextCompletionResponse, - get_provider_fields, - ModelResponseListIterator, - get_valid_models, -) - -ALL_LITELLM_RESPONSE_TYPES = [ - ModelResponse, - EmbeddingResponse, - ImageResponse, - TranscriptionResponse, - TextCompletionResponse, -] +# client must be imported immediately as it's used as a decorator at function definition time +from .utils import client +# Note: Most other utils imports are lazy-loaded via __getattr__ to avoid loading utils.py +# (which imports tiktoken) at import time from .llms.bytez.chat.transformation import BytezChatConfig from .llms.custom_llm import CustomLLM @@ -1538,56 +1491,6 @@ def set_global_gitlab_config(config: Dict[str, Any]) -> None: # Lazy loading system for heavy modules to reduce initial import time and memory usage -def _lazy_import_cost_calculator(name: str) -> Any: - """Lazy import for cost_calculator functions.""" - from .cost_calculator import ( - completion_cost as _completion_cost, - cost_per_token as _cost_per_token, - response_cost_calculator as _response_cost_calculator, - ) - - _cost_functions = { - "completion_cost": _completion_cost, - "cost_per_token": _cost_per_token, - "response_cost_calculator": _response_cost_calculator, - } - - func = _cost_functions[name] - globals()[name] = func - return func - - -def _lazy_import_litellm_logging(name: str) -> Any: - """Lazy import for litellm_logging module.""" - try: - from litellm.litellm_core_utils.litellm_logging import ( - Logging as _Logging, - modify_integration as _modify_integration, - ) - - _logging_objects = { - "Logging": _Logging, - "modify_integration": _modify_integration, - } - - obj = _logging_objects[name] - globals()[name] = obj - return obj - except Exception as e: - raise AttributeError( - f"module {__name__!r} has no attribute {name!r}. " - f"Lazy import failed: {e}" - ) from e - - -_LAZY_LOAD_REGISTRY: Dict[str, Callable[[str], Any]] = { - "completion_cost": _lazy_import_cost_calculator, - "cost_per_token": _lazy_import_cost_calculator, - "response_cost_calculator": _lazy_import_cost_calculator, - "Logging": _lazy_import_litellm_logging, - "modify_integration": _lazy_import_litellm_logging, -} - if TYPE_CHECKING: cost_per_token: Callable[..., Tuple[float, float]] @@ -1598,7 +1501,45 @@ if TYPE_CHECKING: def __getattr__(name: str) -> Any: """Lazy import handler for cost_calculator and litellm_logging functions.""" - if name in _LAZY_LOAD_REGISTRY: - return _LAZY_LOAD_REGISTRY[name](name) + # Lazy load cost_calculator functions + _cost_calculator_names = ( + "completion_cost", + "cost_per_token", + "response_cost_calculator", + ) + if name in _cost_calculator_names: + from ._lazy_imports import _lazy_import_cost_calculator + return _lazy_import_cost_calculator(name) + + # Lazy load litellm_logging functions + _litellm_logging_names = ( + "Logging", + "modify_integration", + ) + if name in _litellm_logging_names: + from ._lazy_imports import _lazy_import_litellm_logging + return _lazy_import_litellm_logging(name) + + # Lazy load utils functions + _utils_names = ( + "exception_type", "get_optional_params", "get_response_string", "token_counter", + "create_pretrained_tokenizer", "create_tokenizer", "supports_function_calling", + "supports_web_search", "supports_url_context", "supports_response_schema", + "supports_parallel_function_calling", "supports_vision", "supports_audio_input", + "supports_audio_output", "supports_system_messages", "supports_reasoning", + "get_litellm_params", "acreate", "get_max_tokens", "get_model_info", + "register_prompt_template", "validate_environment", "check_valid_key", + "register_model", "encode", "decode", "_calculate_retry_after", "_should_retry", + "get_supported_openai_params", "get_api_base", "get_first_chars_messages", + "ModelResponse", "ModelResponseStream", "EmbeddingResponse", "ImageResponse", + "TranscriptionResponse", "TextCompletionResponse", "get_provider_fields", + "ModelResponseListIterator", "get_valid_models", + ) + if name in _utils_names: + from ._lazy_imports import _lazy_import_utils + return _lazy_import_utils(name) raise AttributeError(f"module {__name__!r} has no attribute {name!r}") + + +# ALL_LITELLM_RESPONSE_TYPES is lazy-loaded via __getattr__ to avoid loading utils at import time diff --git a/litellm/_lazy_imports.py b/litellm/_lazy_imports.py new file mode 100644 index 00000000000..91b16864de1 --- /dev/null +++ b/litellm/_lazy_imports.py @@ -0,0 +1,259 @@ +from typing import Any +import sys + +def _get_litellm_globals() -> dict: + """Helper to get the globals dictionary of the litellm module.""" + return sys.modules["litellm"].__dict__ + +# Lazy import for utils module - imports only the requested item by name. +# Note: PLR0915 (too many statements) is suppressed because the many if statements +# are intentional - each attribute is imported individually only when requested, +# ensuring true lazy imports rather than importing the entire utils module. +def _lazy_import_utils(name: str) -> Any: # noqa: PLR0915 + """Lazy import for utils module - imports only the requested item by name.""" + _globals = _get_litellm_globals() + if name == "exception_type": + from .utils import exception_type as _exception_type + _globals["exception_type"] = _exception_type + return _exception_type + + if name == "get_optional_params": + from .utils import get_optional_params as _get_optional_params + _globals["get_optional_params"] = _get_optional_params + return _get_optional_params + + if name == "get_response_string": + from .utils import get_response_string as _get_response_string + _globals["get_response_string"] = _get_response_string + return _get_response_string + + if name == "token_counter": + from .utils import token_counter as _token_counter + _globals["token_counter"] = _token_counter + return _token_counter + + if name == "create_pretrained_tokenizer": + from .utils import create_pretrained_tokenizer as _create_pretrained_tokenizer + _globals["create_pretrained_tokenizer"] = _create_pretrained_tokenizer + return _create_pretrained_tokenizer + + if name == "create_tokenizer": + from .utils import create_tokenizer as _create_tokenizer + _globals["create_tokenizer"] = _create_tokenizer + return _create_tokenizer + + if name == "supports_function_calling": + from .utils import supports_function_calling as _supports_function_calling + _globals["supports_function_calling"] = _supports_function_calling + return _supports_function_calling + + if name == "supports_web_search": + from .utils import supports_web_search as _supports_web_search + _globals["supports_web_search"] = _supports_web_search + return _supports_web_search + + if name == "supports_url_context": + from .utils import supports_url_context as _supports_url_context + _globals["supports_url_context"] = _supports_url_context + return _supports_url_context + + if name == "supports_response_schema": + from .utils import supports_response_schema as _supports_response_schema + _globals["supports_response_schema"] = _supports_response_schema + return _supports_response_schema + + if name == "supports_parallel_function_calling": + from .utils import supports_parallel_function_calling as _supports_parallel_function_calling + _globals["supports_parallel_function_calling"] = _supports_parallel_function_calling + return _supports_parallel_function_calling + + if name == "supports_vision": + from .utils import supports_vision as _supports_vision + _globals["supports_vision"] = _supports_vision + return _supports_vision + + if name == "supports_audio_input": + from .utils import supports_audio_input as _supports_audio_input + _globals["supports_audio_input"] = _supports_audio_input + return _supports_audio_input + + if name == "supports_audio_output": + from .utils import supports_audio_output as _supports_audio_output + _globals["supports_audio_output"] = _supports_audio_output + return _supports_audio_output + + if name == "supports_system_messages": + from .utils import supports_system_messages as _supports_system_messages + _globals["supports_system_messages"] = _supports_system_messages + return _supports_system_messages + + if name == "supports_reasoning": + from .utils import supports_reasoning as _supports_reasoning + _globals["supports_reasoning"] = _supports_reasoning + return _supports_reasoning + + if name == "get_litellm_params": + from .utils import get_litellm_params as _get_litellm_params + _globals["get_litellm_params"] = _get_litellm_params + return _get_litellm_params + + if name == "acreate": + from .utils import acreate as _acreate + _globals["acreate"] = _acreate + return _acreate + + if name == "get_max_tokens": + from .utils import get_max_tokens as _get_max_tokens + _globals["get_max_tokens"] = _get_max_tokens + return _get_max_tokens + + if name == "get_model_info": + from .utils import get_model_info as _get_model_info + _globals["get_model_info"] = _get_model_info + return _get_model_info + + if name == "register_prompt_template": + from .utils import register_prompt_template as _register_prompt_template + _globals["register_prompt_template"] = _register_prompt_template + return _register_prompt_template + + if name == "validate_environment": + from .utils import validate_environment as _validate_environment + _globals["validate_environment"] = _validate_environment + return _validate_environment + + if name == "check_valid_key": + from .utils import check_valid_key as _check_valid_key + _globals["check_valid_key"] = _check_valid_key + return _check_valid_key + + if name == "register_model": + from .utils import register_model as _register_model + _globals["register_model"] = _register_model + return _register_model + + if name == "encode": + from .utils import encode as _encode + _globals["encode"] = _encode + return _encode + + if name == "decode": + from .utils import decode as _decode + _globals["decode"] = _decode + return _decode + + if name == "_calculate_retry_after": + from .utils import _calculate_retry_after as __calculate_retry_after + _globals["_calculate_retry_after"] = __calculate_retry_after + return __calculate_retry_after + + if name == "_should_retry": + from .utils import _should_retry as __should_retry + _globals["_should_retry"] = __should_retry + return __should_retry + + if name == "get_supported_openai_params": + from .utils import get_supported_openai_params as _get_supported_openai_params + _globals["get_supported_openai_params"] = _get_supported_openai_params + return _get_supported_openai_params + + if name == "get_api_base": + from .utils import get_api_base as _get_api_base + _globals["get_api_base"] = _get_api_base + return _get_api_base + + if name == "get_first_chars_messages": + from .utils import get_first_chars_messages as _get_first_chars_messages + _globals["get_first_chars_messages"] = _get_first_chars_messages + return _get_first_chars_messages + + if name == "ModelResponse": + from .utils import ModelResponse as _ModelResponse + _globals["ModelResponse"] = _ModelResponse + return _ModelResponse + + if name == "ModelResponseStream": + from .utils import ModelResponseStream as _ModelResponseStream + _globals["ModelResponseStream"] = _ModelResponseStream + return _ModelResponseStream + + if name == "EmbeddingResponse": + from .utils import EmbeddingResponse as _EmbeddingResponse + _globals["EmbeddingResponse"] = _EmbeddingResponse + return _EmbeddingResponse + + if name == "ImageResponse": + from .utils import ImageResponse as _ImageResponse + _globals["ImageResponse"] = _ImageResponse + return _ImageResponse + + if name == "TranscriptionResponse": + from .utils import TranscriptionResponse as _TranscriptionResponse + _globals["TranscriptionResponse"] = _TranscriptionResponse + return _TranscriptionResponse + + if name == "TextCompletionResponse": + from .utils import TextCompletionResponse as _TextCompletionResponse + _globals["TextCompletionResponse"] = _TextCompletionResponse + return _TextCompletionResponse + + if name == "get_provider_fields": + from .utils import get_provider_fields as _get_provider_fields + _globals["get_provider_fields"] = _get_provider_fields + return _get_provider_fields + + if name == "ModelResponseListIterator": + from .utils import ModelResponseListIterator as _ModelResponseListIterator + _globals["ModelResponseListIterator"] = _ModelResponseListIterator + return _ModelResponseListIterator + + if name == "get_valid_models": + from .utils import get_valid_models as _get_valid_models + _globals["get_valid_models"] = _get_valid_models + return _get_valid_models + + raise AttributeError(f"Utils lazy import: unknown attribute {name!r}") + + +def _lazy_import_cost_calculator(name: str) -> Any: + """Lazy import for cost_calculator functions.""" + _globals = _get_litellm_globals() + from .cost_calculator import ( + completion_cost as _completion_cost, + cost_per_token as _cost_per_token, + response_cost_calculator as _response_cost_calculator, + ) + + _cost_functions = { + "completion_cost": _completion_cost, + "cost_per_token": _cost_per_token, + "response_cost_calculator": _response_cost_calculator, + } + + func = _cost_functions[name] + _globals[name] = func + return func + + +def _lazy_import_litellm_logging(name: str) -> Any: + """Lazy import for litellm_logging module.""" + _globals = _get_litellm_globals() + try: + from litellm.litellm_core_utils.litellm_logging import ( + Logging as _Logging, + modify_integration as _modify_integration, + ) + + _logging_objects = { + "Logging": _Logging, + "modify_integration": _modify_integration, + } + + obj = _logging_objects[name] + _globals[name] = obj + return obj + except Exception as e: + raise AttributeError( + f"module 'litellm' has no attribute {name!r}. " + f"Lazy import failed: {e}" + ) from e \ No newline at end of file diff --git a/litellm/images/main.py b/litellm/images/main.py index eacd4778299..770b16c1ed2 100644 --- a/litellm/images/main.py +++ b/litellm/images/main.py @@ -6,7 +6,9 @@ from typing import Any, Coroutine, Dict, List, Literal, Optional, Union, cast, o import httpx import litellm -from litellm import client, exception_type, get_litellm_params +from litellm.utils import exception_type, get_litellm_params +# client is imported from litellm as it's a decorator +from litellm import client from litellm.constants import DEFAULT_IMAGE_ENDPOINT_MODEL from litellm.constants import request_timeout as DEFAULT_REQUEST_TIMEOUT from litellm.exceptions import LiteLLMUnknownProvider diff --git a/litellm/llms/azure/azure.py b/litellm/llms/azure/azure.py index e7aa93ac882..994afa26e9c 100644 --- a/litellm/llms/azure/azure.py +++ b/litellm/llms/azure/azure.py @@ -1020,7 +1020,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): headers: dict, client=None, timeout=None, - ) -> litellm.ImageResponse: + ) -> ImageResponse: response: Optional[dict] = None try: diff --git a/litellm/llms/azure_ai/embed/handler.py b/litellm/llms/azure_ai/embed/handler.py index 13b8cc4cf29..67733d1ccb5 100644 --- a/litellm/llms/azure_ai/embed/handler.py +++ b/litellm/llms/azure_ai/embed/handler.py @@ -58,7 +58,7 @@ class AzureAIEmbedding(OpenAIChatCompletion): data: ImageEmbeddingRequest, timeout: float, logging_obj, - model_response: litellm.EmbeddingResponse, + model_response: EmbeddingResponse, optional_params: dict, api_key: Optional[str], api_base: Optional[str], @@ -138,7 +138,7 @@ class AzureAIEmbedding(OpenAIChatCompletion): input: List, timeout: float, logging_obj, - model_response: litellm.EmbeddingResponse, + model_response: EmbeddingResponse, optional_params: dict, api_key: Optional[str] = None, api_base: Optional[str] = None, diff --git a/litellm/llms/bedrock/chat/invoke_transformations/amazon_nova_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/amazon_nova_transformation.py index a81d55f0ad2..3506c8f1cc0 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/amazon_nova_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/amazon_nova_transformation.py @@ -10,7 +10,6 @@ from typing import Any, List, Optional import httpx -import litellm from litellm.litellm_core_utils.litellm_logging import Logging from litellm.types.llms.bedrock import BedrockInvokeNovaRequest from litellm.types.llms.openai import AllMessageValues @@ -80,7 +79,7 @@ class AmazonInvokeNovaConfig(AmazonInvokeConfig, AmazonConverseConfig): encoding: Any, api_key: Optional[str] = None, json_mode: Optional[bool] = None, - ) -> litellm.ModelResponse: + ) -> ModelResponse: return AmazonConverseConfig.transform_response( self, model, diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index ad115bc7e92..03ca7a5ad29 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -27,6 +27,25 @@ class BedrockError(BaseLLMException): pass +# Lazy import cache to avoid circular imports and performance impact +_get_model_info = None + + +def get_cached_model_info(): + """ + Lazy import and cache get_model_info to avoid circular imports. + + This function is used by bedrock transformation classes that need get_model_info + but cannot import it at module level due to circular import issues. + The function is cached after first use to avoid performance impact. + """ + global _get_model_info + if _get_model_info is None: + from litellm import get_model_info + _get_model_info = get_model_info + return _get_model_info + + class AmazonBedrockGlobalConfig: def __init__(self): pass diff --git a/litellm/llms/bedrock/image/amazon_nova_canvas_transformation.py b/litellm/llms/bedrock/image/amazon_nova_canvas_transformation.py index f2b94b617c0..18366999583 100644 --- a/litellm/llms/bedrock/image/amazon_nova_canvas_transformation.py +++ b/litellm/llms/bedrock/image/amazon_nova_canvas_transformation.py @@ -3,7 +3,6 @@ from typing import Any, Dict, List, Optional from openai.types.image import Image -from litellm import get_model_info from litellm.types.llms.bedrock import ( AmazonNovaCanvasColorGuidedGenerationParams, AmazonNovaCanvasColorGuidedRequest, @@ -15,6 +14,7 @@ from litellm.types.llms.bedrock import ( AmazonNovaCanvasTextToImageRequest, AmazonNovaCanvasTextToImageResponse, ) +from litellm.llms.bedrock.common_utils import get_cached_model_info from litellm.types.utils import ImageResponse @@ -207,6 +207,7 @@ class AmazonNovaCanvasConfig: size: Optional[str] = None, optional_params: Optional[dict] = None, ) -> float: + get_model_info = get_cached_model_info() model_info = get_model_info( model=model, custom_llm_provider="bedrock", diff --git a/litellm/llms/bedrock/image/amazon_stability1_transformation.py b/litellm/llms/bedrock/image/amazon_stability1_transformation.py index 63af32f3f56..07f82cec232 100644 --- a/litellm/llms/bedrock/image/amazon_stability1_transformation.py +++ b/litellm/llms/bedrock/image/amazon_stability1_transformation.py @@ -5,7 +5,7 @@ from typing import List, Optional from openai.types.image import Image -from litellm import get_model_info +from litellm.llms.bedrock.common_utils import get_cached_model_info from litellm.types.utils import ImageResponse @@ -151,6 +151,7 @@ class AmazonStabilityConfig: size = size or "1024-x-1024" model = f"{size}/{steps}/{model}" + get_model_info = get_cached_model_info() model_info = get_model_info( model=model, custom_llm_provider="bedrock", diff --git a/litellm/llms/bedrock/image/amazon_stability3_transformation.py b/litellm/llms/bedrock/image/amazon_stability3_transformation.py index 445a2fe1100..160d0af8e80 100644 --- a/litellm/llms/bedrock/image/amazon_stability3_transformation.py +++ b/litellm/llms/bedrock/image/amazon_stability3_transformation.py @@ -3,12 +3,12 @@ from typing import List, Optional from openai.types.image import Image -from litellm import get_model_info from litellm.llms.bedrock.common_utils import BedrockError from litellm.types.llms.bedrock import ( AmazonStability3TextToImageRequest, AmazonStability3TextToImageResponse, ) +from litellm.llms.bedrock.common_utils import get_cached_model_info from litellm.types.utils import ImageResponse @@ -115,6 +115,7 @@ class AmazonStability3Config: size: Optional[str] = None, optional_params: Optional[dict] = None, ) -> float: + get_model_info = get_cached_model_info() model_info = get_model_info( model=model, custom_llm_provider="bedrock", diff --git a/litellm/llms/bedrock/image/amazon_titan_transformation.py b/litellm/llms/bedrock/image/amazon_titan_transformation.py index bed9ad0c300..65411cabdcf 100644 --- a/litellm/llms/bedrock/image/amazon_titan_transformation.py +++ b/litellm/llms/bedrock/image/amazon_titan_transformation.py @@ -7,7 +7,7 @@ from typing import List, Optional from openai.types.image import Image -from litellm import get_model_info +from litellm.utils import get_model_info from litellm.types.llms.bedrock import ( AmazonNovaCanvasImageGenerationConfig, AmazonTitanImageGenerationRequestBody, diff --git a/litellm/llms/ovhcloud/chat/transformation.py b/litellm/llms/ovhcloud/chat/transformation.py index 6bdc28620ff..e9dc5be3eed 100644 --- a/litellm/llms/ovhcloud/chat/transformation.py +++ b/litellm/llms/ovhcloud/chat/transformation.py @@ -7,7 +7,9 @@ More information on our website: https://endpoints.ai.cloud.ovh.net from typing import Optional, Union, List import httpx -from litellm import ModelResponseStream, OpenAIGPTConfig, get_model_info, verbose_logger +from litellm.utils import ModelResponseStream, get_model_info +from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig +from litellm._logging import verbose_logger from litellm.llms.ovhcloud.utils import OVHCloudException from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator from litellm.llms.base_llm.chat.transformation import BaseLLMException diff --git a/litellm/llms/together_ai/chat.py b/litellm/llms/together_ai/chat.py index 06d33f69750..e8a784d2779 100644 --- a/litellm/llms/together_ai/chat.py +++ b/litellm/llms/together_ai/chat.py @@ -8,7 +8,8 @@ Docs: https://docs.together.ai/reference/completions-1 from typing import Optional -from litellm import get_model_info, verbose_logger +from litellm.utils import get_model_info +from litellm._logging import verbose_logger from ..openai.chat.gpt_transformation import OpenAIGPTConfig diff --git a/litellm/llms/vertex_ai/common_utils.py b/litellm/llms/vertex_ai/common_utils.py index dc6a3170afe..a3ea8afe40d 100644 --- a/litellm/llms/vertex_ai/common_utils.py +++ b/litellm/llms/vertex_ai/common_utils.py @@ -5,7 +5,8 @@ from typing import Any, Dict, List, Literal, Optional, Set, Tuple, Union, get_ty import httpx import litellm -from litellm import supports_response_schema, supports_system_messages, verbose_logger +from litellm.utils import supports_response_schema, supports_system_messages +from litellm._logging import verbose_logger from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH from litellm.litellm_core_utils.prompt_templates.common_utils import unpack_defs from litellm.llms.base_llm.base_utils import BaseLLMModelInfo, BaseTokenCounter diff --git a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_handler.py b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_handler.py index af9af71fef4..859bb0a6984 100644 --- a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_handler.py +++ b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_handler.py @@ -8,7 +8,7 @@ from typing import Any, Literal, Optional, Union import httpx import litellm -from litellm import EmbeddingResponse +from litellm.types.utils import EmbeddingResponse from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, HTTPHandler, diff --git a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py index 2c0f5dad228..455ec1d18f5 100644 --- a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py +++ b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py @@ -6,7 +6,7 @@ Why separate file? Make it easy to see how transformation works from typing import List -from litellm import EmbeddingResponse +from litellm.types.utils import EmbeddingResponse from litellm.types.llms.openai import EmbeddingInput from litellm.types.llms.vertex_ai import ( ContentType, diff --git a/litellm/llms/vertex_ai/image_generation/image_generation_handler.py b/litellm/llms/vertex_ai/image_generation/image_generation_handler.py index 04be4de8e32..e14cfe3be0b 100644 --- a/litellm/llms/vertex_ai/image_generation/image_generation_handler.py +++ b/litellm/llms/vertex_ai/image_generation/image_generation_handler.py @@ -176,7 +176,7 @@ class VertexImageGeneration(VertexLLM): vertex_project: Optional[str], vertex_location: Optional[str], vertex_credentials: Optional[VERTEX_CREDENTIALS_TYPES], - model_response: litellm.ImageResponse, + model_response: ImageResponse, logging_obj: Any, model: str = "imagegeneration", # vertex ai uses imagegeneration as the default model client: Optional[AsyncHTTPHandler] = None, diff --git a/litellm/llms/vertex_ai/multimodal_embeddings/embedding_handler.py b/litellm/llms/vertex_ai/multimodal_embeddings/embedding_handler.py index 582d7a4c569..d0ffc7be0a6 100644 --- a/litellm/llms/vertex_ai/multimodal_embeddings/embedding_handler.py +++ b/litellm/llms/vertex_ai/multimodal_embeddings/embedding_handler.py @@ -147,13 +147,13 @@ class VertexMultimodalEmbedding(VertexLLM): optional_params: dict, litellm_params: dict, data: dict, - model_response: litellm.EmbeddingResponse, + model_response: EmbeddingResponse, timeout: Optional[Union[float, httpx.Timeout]], logging_obj: LiteLLMLoggingObj, headers={}, client: Optional[AsyncHTTPHandler] = None, api_key: Optional[str] = None, - ) -> litellm.EmbeddingResponse: + ) -> EmbeddingResponse: if client is None: _params = {} if timeout is not None: diff --git a/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py b/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py index a170e6cc7f2..aaa6a0bb95f 100644 --- a/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py +++ b/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py @@ -137,7 +137,7 @@ class VertexEmbedding(VertexBase): self, model: str, input: Union[list, str], - model_response: litellm.EmbeddingResponse, + model_response: EmbeddingResponse, logging_obj: LiteLLMLoggingObject, optional_params: dict, custom_llm_provider: Literal[ @@ -152,7 +152,7 @@ class VertexEmbedding(VertexBase): gemini_api_key: Optional[str] = None, extra_headers: Optional[dict] = None, encoding=None, - ) -> litellm.EmbeddingResponse: + ) -> EmbeddingResponse: """ Async embedding implementation """ diff --git a/litellm/main.py b/litellm/main.py index 4f3abab52b7..0e19699309d 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -52,13 +52,10 @@ from pydantic import BaseModel from typing_extensions import overload import litellm -from litellm import ( # type: ignore - client, - exception_type, - get_litellm_params, - get_optional_params, -) - +# client must be imported from litellm as it's a decorator used at function definition time +from litellm import client +# Other utils are imported directly to avoid circular imports +from litellm.utils import exception_type, get_litellm_params, get_optional_params # Logging is imported lazily when needed to avoid loading litellm_logging at import time if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging