chore: initial snapshot for gitea/github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/databricks/embed/transformation.py

@@ -0,0 +1,48 @@
+"""
+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