Address review comments

Signed-off-by: Bill Murdock <bmurdock@redhat.com>

llama_stack/providers/utils/inference/litellm_openai_mixin.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import base64
+import struct
 from collections.abc import AsyncIterator
 from typing import Any
 
@@ -16,6 +18,7 @@ from llama_stack.apis.inference import (
     OpenAIChatCompletion,
     OpenAIChatCompletionChunk,
     OpenAICompletion,
+    OpenAIEmbeddingData,
     OpenAIEmbeddingsResponse,
     OpenAIEmbeddingUsage,
     OpenAIMessageParam,
@@ -26,7 +29,6 @@ from llama_stack.core.request_headers import NeedsRequestProviderData
 from llama_stack.log import get_logger
 from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper, ProviderModelEntry
 from llama_stack.providers.utils.inference.openai_compat import (
-    b64_encode_openai_embeddings_response,
     convert_message_to_openai_dict_new,
     convert_tooldef_to_openai_tool,
     get_sampling_options,
@@ -334,6 +336,7 @@ class LiteLLMOpenAIMixin(
             api_key=self.get_api_key(),
             api_base=self.api_base,
         )
+        logger.info(f"params to litellm (openai compat): {params}")
         return await litellm.acompletion(**params)
 
     async def check_model_availability(self, model: str) -> bool:
@@ -349,3 +352,28 @@ class LiteLLMOpenAIMixin(
             return False
 
         return model in litellm.models_by_provider[self.litellm_provider_name]
+
+
+def b64_encode_openai_embeddings_response(
+    response_data: list[dict], encoding_format: str | None = "float"
+) -> list[OpenAIEmbeddingData]:
+    """
+    Process the OpenAI embeddings response to encode the embeddings in base64 format if specified.
+    """
+    data = []
+    for i, embedding_data in enumerate(response_data):
+        if encoding_format == "base64":
+            byte_array = bytearray()
+            for embedding_value in embedding_data["embedding"]:
+                byte_array.extend(struct.pack("f", float(embedding_value)))
+
+            response_embedding = base64.b64encode(byte_array).decode("utf-8")
+        else:
+            response_embedding = embedding_data["embedding"]
+        data.append(
+            OpenAIEmbeddingData(
+                embedding=response_embedding,
+                index=i,
+            )
+        )
+    return data