Add support for passing additional kwargs when instantiating an OpenAI client for Databricks model serving (#1025)

## What changes are proposed in this pull request?

Per customer request, adds support for passing additional optional
kwargs to `databricks.sdk.WorkspaceClient().get_open_ai_client()`. This
enables use cases like specifying a custom timeout and retry policy for
latency-sensitive workloads, e.g:

```
>>> # Configure custom timeout and retries
>>> client = workspace_client.serving_endpoints.get_open_ai_client(
...     timeout=30.0, 
...     max_retries=5
... )
```

## How is this tested?

Updated unit tests

---------

Signed-off-by: Sid Murching <[email protected]>

Author: smurching

NEXT_CHANGELOG.md

@@ -4,6 +4,8 @@
 
 ### New Features and Improvements
 
+* Added support for passing additional kwargs to `WorkspaceClient().serving_endpoints.get_open_ai_client()` ([#1025](https://github.com/databricks/databricks-sdk-py/pull/1025)). Users can now pass standard OpenAI client parameters like `timeout` and `max_retries` when creating an OpenAI client for Databricks Model Serving.
+
 ### Bug Fixes
 
 ### Documentation

databricks/sdk/mixins/open_ai_client.py

@@ -31,19 +31,68 @@ def auth_flow(self, request: httpx.Request) -> httpx.Request:
         http_client = httpx.Client(auth=databricks_token_auth)
         return http_client
 
-    def get_open_ai_client(self):
+    def get_open_ai_client(self, **kwargs):
+        """Create an OpenAI client configured for Databricks Model Serving.
+
+        Returns an OpenAI client instance that is pre-configured to send requests to
+        Databricks Model Serving endpoints. The client uses Databricks authentication
+        to query endpoints within the workspace associated with the current WorkspaceClient
+        instance.
+
+        Args:
+            **kwargs: Additional parameters to pass to the OpenAI client constructor.
+                Common parameters include:
+                - timeout (float): Request timeout in seconds (e.g., 30.0)
+                - max_retries (int): Maximum number of retries for failed requests (e.g., 3)
+                - default_headers (dict): Additional headers to include with requests
+                - default_query (dict): Additional query parameters to include with requests
+
+                Any parameter accepted by the OpenAI client constructor can be passed here,
+                except for the following parameters which are reserved for Databricks integration:
+                base_url, api_key, http_client
+
+        Returns:
+            OpenAI: An OpenAI client instance configured for Databricks Model Serving.
+
+        Raises:
+            ImportError: If the OpenAI library is not installed.
+            ValueError: If any reserved Databricks parameters are provided in kwargs.
+
+        Example:
+            >>> client = workspace_client.serving_endpoints.get_open_ai_client()
+            >>> # With custom timeout and retries
+            >>> client = workspace_client.serving_endpoints.get_open_ai_client(
+            ...     timeout=30.0,
+            ...     max_retries=5
+            ... )
+        """
         try:
             from openai import OpenAI
         except Exception:
             raise ImportError(
                 "Open AI is not installed. Please install the Databricks SDK with the following command `pip install databricks-sdk[openai]`"
             )
 
-        return OpenAI(
-            base_url=self._api._cfg.host + "/serving-endpoints",
-            api_key="no-token",  # Passing in a placeholder to pass validations, this will not be used
-            http_client=self._get_authorized_http_client(),
-        )
+        # Check for reserved parameters that should not be overridden
+        reserved_params = {"base_url", "api_key", "http_client"}
+        conflicting_params = reserved_params.intersection(kwargs.keys())
+        if conflicting_params:
+            raise ValueError(
+                f"Cannot override reserved Databricks parameters: {', '.join(sorted(conflicting_params))}. "
+                f"These parameters are automatically configured for Databricks Model Serving."
+            )
+
+        # Default parameters that are required for Databricks integration
+        client_params = {
+            "base_url": self._api._cfg.host + "/serving-endpoints",
+            "api_key": "no-token",  # Passing in a placeholder to pass validations, this will not be used
+            "http_client": self._get_authorized_http_client(),
+        }
+
+        # Update with any additional parameters passed by the user
+        client_params.update(kwargs)
+
+        return OpenAI(**client_params)
 
     def get_langchain_chat_open_ai_client(self, model):
         try:

tests/test_open_ai_mixin.py

@@ -19,6 +19,66 @@ def test_open_ai_client(monkeypatch):
     assert client.api_key == "no-token"
 
 
+def test_open_ai_client_with_custom_params(monkeypatch):
+    from databricks.sdk import WorkspaceClient
+
+    monkeypatch.setenv("DATABRICKS_HOST", "test_host")
+    monkeypatch.setenv("DATABRICKS_TOKEN", "test_token")
+    w = WorkspaceClient(config=Config())
+
+    # Test with timeout and max_retries parameters
+    client = w.serving_endpoints.get_open_ai_client(timeout=30.0, max_retries=3)
+
+    assert client.base_url == "https://test_host/serving-endpoints/"
+    assert client.api_key == "no-token"
+    assert client.timeout == 30.0
+    assert client.max_retries == 3
+
+
+def test_open_ai_client_with_additional_kwargs(monkeypatch):
+    from databricks.sdk import WorkspaceClient
+
+    monkeypatch.setenv("DATABRICKS_HOST", "test_host")
+    monkeypatch.setenv("DATABRICKS_TOKEN", "test_token")
+    w = WorkspaceClient(config=Config())
+
+    # Test with additional kwargs that OpenAI client might accept
+    client = w.serving_endpoints.get_open_ai_client(
+        timeout=60.0, max_retries=5, default_headers={"Custom-Header": "test-value"}
+    )
+
+    assert client.base_url == "https://test_host/serving-endpoints/"
+    assert client.api_key == "no-token"
+    assert client.timeout == 60.0
+    assert client.max_retries == 5
+    assert "Custom-Header" in client.default_headers
+    assert client.default_headers["Custom-Header"] == "test-value"
+
+
+def test_open_ai_client_prevents_reserved_param_override(monkeypatch):
+    from databricks.sdk import WorkspaceClient
+
+    monkeypatch.setenv("DATABRICKS_HOST", "test_host")
+    monkeypatch.setenv("DATABRICKS_TOKEN", "test_token")
+    w = WorkspaceClient(config=Config())
+
+    # Test that trying to override base_url raises an error
+    with pytest.raises(ValueError, match="Cannot override reserved Databricks parameters: base_url"):
+        w.serving_endpoints.get_open_ai_client(base_url="https://custom-host")
+
+    # Test that trying to override api_key raises an error
+    with pytest.raises(ValueError, match="Cannot override reserved Databricks parameters: api_key"):
+        w.serving_endpoints.get_open_ai_client(api_key="custom-key")
+
+    # Test that trying to override http_client raises an error
+    with pytest.raises(ValueError, match="Cannot override reserved Databricks parameters: http_client"):
+        w.serving_endpoints.get_open_ai_client(http_client=None)
+
+    # Test that trying to override multiple reserved params shows all of them
+    with pytest.raises(ValueError, match="Cannot override reserved Databricks parameters: api_key, base_url"):
+        w.serving_endpoints.get_open_ai_client(base_url="https://custom-host", api_key="custom-key")
+
+
 @pytest.mark.skipif(sys.version_info < (3, 8), reason="Requires Python > 3.7")
 def test_langchain_open_ai_client(monkeypatch):
     from databricks.sdk import WorkspaceClient