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* VoyageEmbeddingConfig * fix voyage logic to get params * add voyage embedding transformation * add get_provider_embedding_config * use BaseEmbeddingConfig * voyage clean up * use llm http handler for embedding transformations * test_voyage_ai_embedding_extra_params * add voyage async * test_voyage_ai_embedding_extra_params * add async for llm http handler * update BaseLLMEmbeddingTest * test_voyage_ai_embedding_extra_params * fix linting * fix get_provider_embedding_config * fix anthropic text test * update location of base/chat/transformation * fix import path * fix IBMWatsonXAIConfig
26 lines
859 B
Python
26 lines
859 B
Python
"""
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Translate from OpenAI's `/v1/chat/completions` to Sagemaker's `/invocations` API
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Called if Sagemaker endpoint supports HF Messages API.
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LiteLLM Docs: https://docs.litellm.ai/docs/providers/aws_sagemaker#sagemaker-messages-api
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Huggingface Docs: https://huggingface.co/docs/text-generation-inference/en/messages_api
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"""
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from typing import Union
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from httpx._models import Headers
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from litellm.llms.base_llm.chat.transformation import BaseLLMException
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from ...openai.chat.gpt_transformation import OpenAIGPTConfig
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from ..common_utils import SagemakerError
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class SagemakerChatConfig(OpenAIGPTConfig):
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def get_error_class(
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self, error_message: str, status_code: int, headers: Union[dict, Headers]
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) -> BaseLLMException:
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return SagemakerError(
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status_code=status_code, message=error_message, headers=headers
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)
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