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* fix(utils.py): initial commit to remove circular imports - moves llmproviders to utils.py * fix(router.py): fix 'litellm.EmbeddingResponse' import from router.py ' * refactor: fix litellm.ModelResponse import on pass through endpoints * refactor(litellm_logging.py): fix circular import for custom callbacks literal * fix(factory.py): fix circular imports inside prompt factory * fix(cost_calculator.py): fix circular import for 'litellm.Usage' * fix(proxy_server.py): fix potential circular import with `litellm.Router' * fix(proxy/utils.py): fix potential circular import in `litellm.Router` * fix: remove circular imports in 'auth_checks' and 'guardrails/' * fix(prompt_injection_detection.py): fix router impor t * fix(vertex_passthrough_logging_handler.py): fix potential circular imports in vertex pass through * fix(anthropic_pass_through_logging_handler.py): fix potential circular imports * fix(slack_alerting.py-+-ollama_chat.py): fix modelresponse import * fix(base.py): fix potential circular import * fix(handler.py): fix potential circular ref in codestral + cohere handler's * fix(azure.py): fix potential circular imports * fix(gpt_transformation.py): fix modelresponse import * fix(litellm_logging.py): add logging base class - simplify typing makes it easy for other files to type check the logging obj without introducing circular imports * fix(azure_ai/embed): fix potential circular import on handler.py * fix(databricks/): fix potential circular imports in databricks/ * fix(vertex_ai/): fix potential circular imports on vertex ai embeddings * fix(vertex_ai/image_gen): fix import * fix(watsonx-+-bedrock): cleanup imports * refactor(anthropic-pass-through-+-petals): cleanup imports * refactor(huggingface/): cleanup imports * fix(ollama-+-clarifai): cleanup circular imports * fix(openai_like/): fix impor t * fix(openai_like/): fix embedding handler cleanup imports * refactor(openai.py): cleanup imports * fix(sagemaker/transformation.py): fix import * ci(config.yml): add circular import test to ci/cd
91 lines
2.7 KiB
Python
91 lines
2.7 KiB
Python
## This is a template base class to be used for adding new LLM providers via API calls
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from typing import Any, Optional, Union
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import httpx
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import requests
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import litellm
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from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
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from litellm.types.utils import ModelResponse, TextCompletionResponse
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class BaseLLM:
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_client_session: Optional[httpx.Client] = None
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def process_response(
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self,
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model: str,
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response: Union[requests.Response, httpx.Response],
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model_response: ModelResponse,
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stream: bool,
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logging_obj: Any,
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optional_params: dict,
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api_key: str,
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data: Union[dict, str],
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messages: list,
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print_verbose,
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encoding,
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) -> Union[ModelResponse, CustomStreamWrapper]:
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"""
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Helper function to process the response across sync + async completion calls
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"""
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return model_response
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def process_text_completion_response(
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self,
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model: str,
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response: Union[requests.Response, httpx.Response],
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model_response: TextCompletionResponse,
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stream: bool,
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logging_obj: Any,
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optional_params: dict,
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api_key: str,
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data: Union[dict, str],
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messages: list,
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print_verbose,
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encoding,
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) -> Union[TextCompletionResponse, CustomStreamWrapper]:
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"""
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Helper function to process the response across sync + async completion calls
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"""
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return model_response
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def create_client_session(self):
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if litellm.client_session:
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_client_session = litellm.client_session
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else:
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_client_session = httpx.Client()
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return _client_session
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def create_aclient_session(self):
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if litellm.aclient_session:
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_aclient_session = litellm.aclient_session
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else:
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_aclient_session = httpx.AsyncClient()
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return _aclient_session
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def __exit__(self):
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if hasattr(self, "_client_session") and self._client_session is not None:
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self._client_session.close()
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async def __aexit__(self, exc_type, exc_val, exc_tb):
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if hasattr(self, "_aclient_session"):
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await self._aclient_session.aclose() # type: ignore
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def validate_environment(
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self, *args, **kwargs
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) -> Optional[Any]: # set up the environment required to run the model
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return None
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def completion(
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self, *args, **kwargs
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) -> Any: # logic for parsing in - calling - parsing out model completion calls
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return None
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def embedding(
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self, *args, **kwargs
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) -> Any: # logic for parsing in - calling - parsing out model embedding calls
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return None
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