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""" | |
Transformation logic from OpenAI /v1/embeddings format to Bedrock Cohere /invoke format. | |
Why separate file? Make it easy to see how transformation works | |
""" | |
from typing import List | |
from litellm.llms.cohere.embed.transformation import CohereEmbeddingConfig | |
from litellm.types.llms.bedrock import CohereEmbeddingRequest | |
class BedrockCohereEmbeddingConfig: | |
def __init__(self) -> None: | |
pass | |
def get_supported_openai_params(self) -> List[str]: | |
return ["encoding_format"] | |
def map_openai_params( | |
self, non_default_params: dict, optional_params: dict | |
) -> dict: | |
for k, v in non_default_params.items(): | |
if k == "encoding_format": | |
optional_params["embedding_types"] = v | |
return optional_params | |
def _is_v3_model(self, model: str) -> bool: | |
return "3" in model | |
def _transform_request( | |
self, model: str, input: List[str], inference_params: dict | |
) -> CohereEmbeddingRequest: | |
transformed_request = CohereEmbeddingConfig()._transform_request( | |
model, input, inference_params | |
) | |
new_transformed_request = CohereEmbeddingRequest( | |
input_type=transformed_request["input_type"], | |
) | |
for k in CohereEmbeddingRequest.__annotations__.keys(): | |
if k in transformed_request: | |
new_transformed_request[k] = transformed_request[k] # type: ignore | |
return new_transformed_request | |