Fix #29759: Use local chunk_size_ for looping in embed_documents (#29761)

This fix ensures that the chunk size is correctly determined when
processing text embeddings. Previously, the code did not properly handle
cases where chunk_size was None, potentially leading to incorrect
chunking behavior.

Now, chunk_size_ is explicitly set to either the provided chunk_size or
the default self.chunk_size, ensuring consistent chunking. This update
improves reliability when processing large text inputs in batches and
prevents unintended behavior when chunk_size is not specified.

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>

libs/partners/openai/langchain_openai/embeddings/base.py

@@ -573,7 +573,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
         chunk_size_ = chunk_size or self.chunk_size
         if not self.check_embedding_ctx_length:
             embeddings: List[List[float]] = []
-            for i in range(0, len(texts), self.chunk_size):
+            for i in range(0, len(texts), chunk_size_):
                 response = self.client.create(
                     input=texts[i : i + chunk_size_], **self._invocation_params
                 )

libs/partners/openai/tests/unit_tests/embeddings/test_base.py

@@ -1,4 +1,5 @@
 import os
+from unittest.mock import patch
 
 import pytest
 
@@ -16,3 +17,23 @@ def test_openai_incorrect_field() -> None:
     with pytest.warns(match="not default parameter"):
         llm = OpenAIEmbeddings(foo="bar")  # type: ignore[call-arg]
     assert llm.model_kwargs == {"foo": "bar"}
+
+
+def test_embed_documents_with_custom_chunk_size() -> None:
+    embeddings = OpenAIEmbeddings(chunk_size=2, check_embedding_ctx_length=False)
+    texts = ["text1", "text2", "text3", "text4"]
+    custom_chunk_size = 3
+
+    with patch.object(embeddings.client, "create") as mock_create:
+        mock_create.side_effect = [
+            {"data": [{"embedding": [0.1, 0.2]}, {"embedding": [0.3, 0.4]}]},
+            {"data": [{"embedding": [0.5, 0.6]}, {"embedding": [0.7, 0.8]}]},
+        ]
+
+        result = embeddings.embed_documents(texts, chunk_size=custom_chunk_size)
+
+        mock_create.call_args
+        mock_create.assert_any_call(input=texts[0:3], **embeddings._invocation_params)
+        mock_create.assert_any_call(input=texts[3:4], **embeddings._invocation_params)
+
+    assert result == [[0.1, 0.2], [0.3, 0.4], [0.5, 0.6], [0.7, 0.8]]