diff --git a/graphiti_core/llm_client/openai_client.py b/graphiti_core/llm_client/openai_client.py
index 9ac71a56..a1d9010e 100644
--- a/graphiti_core/llm_client/openai_client.py
+++ b/graphiti_core/llm_client/openai_client.py
@@ -33,13 +33,50 @@ DEFAULT_MODEL = 'gpt-4o-2024-08-06'
 
 
 class OpenAIClient(LLMClient):
-    def __init__(self, config: LLMConfig | None = None, cache: bool = False):
+    """
+    OpenAIClient is a client class for interacting with OpenAI's language models.
+
+    This class extends the LLMClient and provides methods to initialize the client,
+    get an embedder, and generate responses from the language model.
+
+    Attributes:
+        client (AsyncOpenAI): The OpenAI client used to interact with the API.
+        model (str): The model name to use for generating responses.
+        temperature (float): The temperature to use for generating responses.
+        max_tokens (int): The maximum number of tokens to generate in a response.
+
+    Methods:
+        __init__(config: LLMConfig | None = None, cache: bool = False, client: typing.Any = None):
+            Initializes the OpenAIClient with the provided configuration, cache setting, and client.
+
+        get_embedder() -> typing.Any:
+            Returns the embedder from the OpenAI client.
+
+        _generate_response(messages: list[Message]) -> dict[str, typing.Any]:
+            Generates a response from the language model based on the provided messages.
+    """
+
+    def __init__(
+        self, config: LLMConfig | None = None, cache: bool = False, client: typing.Any = None
+    ):
+        """
+        Initialize the OpenAIClient with the provided configuration, cache setting, and client.
+
+        Args:
+            config (LLMConfig | None): The configuration for the LLM client, including API key, model, base URL, temperature, and max tokens.
+            cache (bool): Whether to use caching for responses. Defaults to False.
+            client (Any | None): An optional async client instance to use. If not provided, a new AsyncOpenAI client is created.
+
+        """
         if config is None:
             config = LLMConfig()
 
         super().__init__(config, cache)
 
-        self.client = AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
+        if client is None:
+            self.client = AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
+        else:
+            self.client = client
 
     def get_embedder(self) -> typing.Any:
         return self.client.embeddings