feat(embedding): default OpenAI-path encoding_format to float

Made-with: Cursor

litellm/main.py

@@ -4920,11 +4920,12 @@ def embedding(  # noqa: PLR0915
             if headers is not None and headers != {}:
                 optional_params["extra_headers"] = headers
 
-            if encoding_format is not None:
-                optional_params["encoding_format"] = encoding_format
-            else:
-                # Omiting causes openai sdk to add default value of "float"
-                optional_params["encoding_format"] = None
+            optional_params["encoding_format"] = (
+                encoding_format
+                or optional_params.get("encoding_format")
+                or get_secret_str("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT")
+                or "float"
+            )
 
             api_version = None
 

tests/test_litellm/test_openai_embedding_encoding_format_default.py

@@ -0,0 +1,50 @@
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from litellm import embedding
+
+
+@pytest.mark.parametrize(
+    "set_env, env_value, expected",
+    [
+        (False, None, "float"),
+        (True, "base64", "base64"),
+    ],
+)
+def test_openai_embedding_encoding_format_default(
+    monkeypatch, set_env, env_value, expected
+):
+    monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False)
+    if set_env:
+        monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", env_value)
+
+    mock_response = MagicMock()
+    mock_response.parse.return_value = MagicMock(
+        model_dump=lambda: {
+            "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}],
+            "model": "text-embedding-ada-002",
+            "object": "list",
+            "usage": {"prompt_tokens": 1, "total_tokens": 1},
+        }
+    )
+    mock_response.headers = {}
+
+    with patch(
+        "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client"
+    ) as mock_get_client:
+        mock_client_instance = MagicMock()
+        mock_get_client.return_value = mock_client_instance
+        mock_client_instance.embeddings.with_raw_response.create.return_value = (
+            mock_response
+        )
+
+        embedding(
+            model="text-embedding-ada-002",
+            input="Hello world",
+        )
+
+        call_kwargs = (
+            mock_client_instance.embeddings.with_raw_response.create.call_args[1]
+        )
+        assert call_kwargs["encoding_format"] == expected