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diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/databricks/embed/transformation.py b/.venv/lib/python3.12/site-packages/litellm/llms/databricks/embed/transformation.py
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+++ b/.venv/lib/python3.12/site-packages/litellm/llms/databricks/embed/transformation.py
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+"""
+Translates from OpenAI's `/v1/embeddings` to Databricks' `/embeddings`
+"""
+
+import types
+from typing import Optional
+
+
+class DatabricksEmbeddingConfig:
+ """
+ Reference: https://learn.microsoft.com/en-us/azure/databricks/machine-learning/foundation-models/api-reference#--embedding-task
+ """
+
+ instruction: Optional[str] = (
+ None # An optional instruction to pass to the embedding model. BGE Authors recommend 'Represent this sentence for searching relevant passages:' for retrieval queries
+ )
+
+ def __init__(self, instruction: Optional[str] = None) -> None:
+ locals_ = locals().copy()
+ for key, value in locals_.items():
+ if key != "self" and value is not None:
+ setattr(self.__class__, key, value)
+
+ @classmethod
+ def get_config(cls):
+ return {
+ k: v
+ for k, v in cls.__dict__.items()
+ if not k.startswith("__")
+ and not isinstance(
+ v,
+ (
+ types.FunctionType,
+ types.BuiltinFunctionType,
+ classmethod,
+ staticmethod,
+ ),
+ )
+ and v is not None
+ }
+
+ def get_supported_openai_params(
+ self,
+ ): # no optional openai embedding params supported
+ return []
+
+ def map_openai_params(self, non_default_params: dict, optional_params: dict):
+ return optional_params