feat(api): add embeddings encoding_format

Author: stainless-bot

src/openai/resources/embeddings.py

@@ -20,6 +20,7 @@ def create(
         *,
         input: Union[str, List[str], List[int], List[List[int]]],
         model: Union[str, Literal["text-embedding-ada-002"]],
+        encoding_format: Literal["float", "base64"] | NotGiven = NOT_GIVEN,
         user: str | NotGiven = NOT_GIVEN,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.
@@ -45,6 +46,9 @@ def create(
               [Model overview](https://platform.openai.com/docs/models/overview) for
               descriptions of them.
 
+          encoding_format: The format to return the embeddings in. Can be either `float` or
+              [`base64`](https://pypi.org/project/pybase64/).
+
           user: A unique identifier representing your end-user, which can help OpenAI to monitor
               and detect abuse.
               [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
@@ -63,6 +67,7 @@ def create(
                 {
                     "input": input,
                     "model": model,
+                    "encoding_format": encoding_format,
                     "user": user,
                 },
                 embedding_create_params.EmbeddingCreateParams,
@@ -80,6 +85,7 @@ async def create(
         *,
         input: Union[str, List[str], List[int], List[List[int]]],
         model: Union[str, Literal["text-embedding-ada-002"]],
+        encoding_format: Literal["float", "base64"] | NotGiven = NOT_GIVEN,
         user: str | NotGiven = NOT_GIVEN,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.
@@ -105,6 +111,9 @@ async def create(
               [Model overview](https://platform.openai.com/docs/models/overview) for
               descriptions of them.
 
+          encoding_format: The format to return the embeddings in. Can be either `float` or
+              [`base64`](https://pypi.org/project/pybase64/).
+
           user: A unique identifier representing your end-user, which can help OpenAI to monitor
               and detect abuse.
               [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
@@ -123,6 +132,7 @@ async def create(
                 {
                     "input": input,
                     "model": model,
+                    "encoding_format": encoding_format,
                     "user": user,
                 },
                 embedding_create_params.EmbeddingCreateParams,

src/openai/types/embedding_create_params.py

@@ -29,6 +29,12 @@ class EmbeddingCreateParams(TypedDict, total=False):
     descriptions of them.
     """
 
+    encoding_format: Literal["float", "base64"]
+    """The format to return the embeddings in.
+
+    Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).
+    """
+
     user: str
     """
     A unique identifier representing your end-user, which can help OpenAI to monitor

tests/api_resources/test_embeddings.py

@@ -32,6 +32,7 @@ def test_method_create_with_all_params(self, client: OpenAI) -> None:
         embedding = client.embeddings.create(
             input="The quick brown fox jumped over the lazy dog",
             model="text-embedding-ada-002",
+            encoding_format="float",
             user="user-1234",
         )
         assert_matches_type(CreateEmbeddingResponse, embedding, path=["response"])
@@ -55,6 +56,7 @@ async def test_method_create_with_all_params(self, client: AsyncOpenAI) -> None:
         embedding = await client.embeddings.create(
             input="The quick brown fox jumped over the lazy dog",
             model="text-embedding-ada-002",
+            encoding_format="float",
             user="user-1234",
         )
         assert_matches_type(CreateEmbeddingResponse, embedding, path=["response"])