litellm-mirror/litellm/llms/databricks/embed/transformation.py
Krrish Dholakia 70f7d7e787 feat(databricks/chat): support structured outputs on databricks
Closes https://github.com/BerriAI/litellm/pull/6978

- handles content as list for dbrx, - handles streaming+response_format for dbrx
2024-12-02 23:08:19 -08:00

48 lines
1.4 KiB
Python

"""
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()
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