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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
89 lines
2.8 KiB
Python
89 lines
2.8 KiB
Python
from typing import Callable, Optional, Union
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import httpx
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
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from litellm.types.utils import CustomStreamingDecoder, ModelResponse
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from ...openai_like.chat.handler import OpenAILikeChatHandler
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from ..common_utils import _get_api_params
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from .transformation import IBMWatsonXChatConfig
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watsonx_chat_transformation = IBMWatsonXChatConfig()
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class WatsonXChatHandler(OpenAILikeChatHandler):
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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def completion(
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self,
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*,
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model: str,
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messages: list,
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api_base: str,
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custom_llm_provider: str,
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custom_prompt_dict: dict,
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model_response: ModelResponse,
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print_verbose: Callable,
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encoding,
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api_key: Optional[str],
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logging_obj,
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optional_params: dict,
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acompletion=None,
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litellm_params=None,
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headers: Optional[dict] = None,
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logger_fn=None,
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timeout: Optional[Union[float, httpx.Timeout]] = None,
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client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
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custom_endpoint: Optional[bool] = None,
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streaming_decoder: Optional[CustomStreamingDecoder] = None,
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fake_stream: bool = False,
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):
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api_params = _get_api_params(params=optional_params)
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## UPDATE HEADERS
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headers = watsonx_chat_transformation.validate_environment(
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headers=headers or {},
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model=model,
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messages=messages,
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optional_params=optional_params,
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api_key=api_key,
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)
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## GET API URL
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api_base = watsonx_chat_transformation.get_complete_url(
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api_base=api_base,
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model=model,
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optional_params=optional_params,
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stream=optional_params.get("stream", False),
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)
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## UPDATE PAYLOAD (optional params)
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watsonx_auth_payload = watsonx_chat_transformation._prepare_payload(
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model=model,
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api_params=api_params,
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)
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optional_params.update(watsonx_auth_payload)
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return super().completion(
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model=model,
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messages=messages,
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api_base=api_base,
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custom_llm_provider=custom_llm_provider,
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custom_prompt_dict=custom_prompt_dict,
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model_response=model_response,
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print_verbose=print_verbose,
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encoding=encoding,
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api_key=api_key,
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logging_obj=logging_obj,
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optional_params=optional_params,
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acompletion=acompletion,
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litellm_params=litellm_params,
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logger_fn=logger_fn,
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headers=headers,
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timeout=timeout,
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client=client,
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custom_endpoint=True,
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streaming_decoder=streaming_decoder,
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)
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