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* refactor: initial commit moving watsonx_text to base_llm_http_handler + clarifying new provider directory structure * refactor(watsonx/completion/handler.py): move to using base llm http handler removes 'requests' library usage * fix(watsonx_text/transformation.py): fix result transformation migrates to transformation.py, for usage with base llm http handler * fix(streaming_handler.py): migrate watsonx streaming to transformation.py ensures streaming works with base llm http handler * fix(streaming_handler.py): fix streaming linting errors and remove watsonx conditional logic * fix(watsonx/): fix chat route post completion route refactor * refactor(watsonx/embed): refactor watsonx to use base llm http handler for embedding calls as well * refactor(base.py): remove requests library usage from litellm * build(pyproject.toml): remove requests library usage * fix: fix linting errors * fix: fix linting errors * fix(types/utils.py): fix validation errors for modelresponsestream * fix(replicate/handler.py): fix linting errors * fix(litellm_logging.py): handle modelresponsestream object * fix(streaming_handler.py): fix modelresponsestream args * fix: remove unused imports * test: fix test * fix: fix test * test: fix test * test: fix tests * test: fix test * test: fix patch target * test: fix test
90 lines
2.6 KiB
Python
90 lines
2.6 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 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: 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: 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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