Rename OpenAIProvider → OpenAIRunnerFactory

Completes the rename that was done for the file (openai_provider.py →
openai_runner_factory.py) but missed the class itself. Updates all
references in __init__.py, runner_factory.py, and tests.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: jsonbailey

packages/ai-providers/server-ai-openai/src/ldai_openai/__init__.py

@@ -1,5 +1,5 @@
-from ldai_openai.openai_runner_factory import OpenAIProvider
+from ldai_openai.openai_runner_factory import OpenAIRunnerFactory
 
 __all__ = [
-    'OpenAIProvider',
+    'OpenAIRunnerFactory',
 ]

packages/ai-providers/server-ai-openai/src/ldai_openai/openai_runner_factory.py

@@ -11,7 +11,7 @@
 from openai.types.chat import ChatCompletionMessageParam
 
 
-class OpenAIProvider(AIProvider):
+class OpenAIRunnerFactory(AIProvider):
     """
     OpenAI provider for the LaunchDarkly AI SDK.
 
@@ -50,21 +50,21 @@ def __init__(
 
     # --- AIProvider factory methods ---
 
-    def create_model(self, config: AIConfigKind) -> 'OpenAIProvider':
+    def create_model(self, config: AIConfigKind) -> 'OpenAIRunnerFactory':
         """
         Create a configured OpenAI model provider for the given AI config.
 
         Reuses the underlying AsyncOpenAI client so that connection pooling is
         preserved across calls.
 
         :param config: The LaunchDarkly AI configuration
-        :return: Configured OpenAIProvider ready to invoke the model
+        :return: Configured OpenAIRunnerFactory ready to invoke the model
         """
         config_dict = config.to_dict()
         model_dict = config_dict.get('model') or {}
         model_name = model_dict.get('name', '')
         parameters = model_dict.get('parameters') or {}
-        return OpenAIProvider(self._client, model_name, parameters)
+        return OpenAIRunnerFactory(self._client, model_name, parameters)
 
     # --- Model invocation ---
 
@@ -87,7 +87,7 @@ async def invoke_model(self, messages: List[LDMessage]) -> ChatResponse:
                 **self._parameters,
             )
 
-            metrics = OpenAIProvider.get_ai_metrics_from_response(response)
+            metrics = OpenAIRunnerFactory.get_ai_metrics_from_response(response)
 
             content = ''
             if response.choices and len(response.choices) > 0:
@@ -143,7 +143,7 @@ async def invoke_structured_model(
                 **self._parameters,
             )
 
-            metrics = OpenAIProvider.get_ai_metrics_from_response(response)
+            metrics = OpenAIRunnerFactory.get_ai_metrics_from_response(response)
 
             content = ''
             if response.choices and len(response.choices) > 0:
@@ -206,7 +206,7 @@ def get_ai_metrics_from_response(response: Any) -> LDAIMetrics:
 
             response = await tracker.track_metrics_of(
                 lambda: client.chat.completions.create(config),
-                OpenAIProvider.get_ai_metrics_from_response
+                OpenAIRunnerFactory.get_ai_metrics_from_response
             )
         """
         usage: Optional[TokenUsage] = None

packages/ai-providers/server-ai-openai/tests/test_openai_provider.py

@@ -5,7 +5,7 @@
 
 from ldai import LDMessage
 
-from ldai_openai import OpenAIProvider
+from ldai_openai import OpenAIRunnerFactory
 
 
 class TestGetAIMetricsFromResponse:
@@ -19,7 +19,7 @@ def test_creates_metrics_with_success_true_and_token_usage(self):
         mock_response.usage.completion_tokens = 50
         mock_response.usage.total_tokens = 100
 
-        result = OpenAIProvider.get_ai_metrics_from_response(mock_response)
+        result = OpenAIRunnerFactory.get_ai_metrics_from_response(mock_response)
 
         assert result.success is True
         assert result.usage is not None
@@ -32,7 +32,7 @@ def test_creates_metrics_with_success_true_and_no_usage_when_usage_missing(self)
         mock_response = MagicMock()
         mock_response.usage = None
 
-        result = OpenAIProvider.get_ai_metrics_from_response(mock_response)
+        result = OpenAIRunnerFactory.get_ai_metrics_from_response(mock_response)
 
         assert result.success is True
         assert result.usage is None
@@ -45,7 +45,7 @@ def test_handles_partial_usage_data(self):
         mock_response.usage.completion_tokens = None
         mock_response.usage.total_tokens = None
 
-        result = OpenAIProvider.get_ai_metrics_from_response(mock_response)
+        result = OpenAIRunnerFactory.get_ai_metrics_from_response(mock_response)
 
         assert result.success is True
         assert result.usage is not None
@@ -78,7 +78,7 @@ async def test_invokes_openai_chat_completions_and_returns_response(self, mock_c
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(return_value=mock_response)
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Hello!')]
         result = await provider.invoke_model(messages)
 
@@ -108,7 +108,7 @@ async def test_returns_unsuccessful_response_when_no_content(self, mock_client):
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(return_value=mock_response)
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Hello!')]
         result = await provider.invoke_model(messages)
 
@@ -127,7 +127,7 @@ async def test_returns_unsuccessful_response_when_choices_empty(self, mock_clien
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(return_value=mock_response)
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Hello!')]
         result = await provider.invoke_model(messages)
 
@@ -142,7 +142,7 @@ async def test_returns_unsuccessful_response_when_exception_thrown(self, mock_cl
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(side_effect=Exception('API Error'))
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Hello!')]
         result = await provider.invoke_model(messages)
 
@@ -175,7 +175,7 @@ async def test_invokes_openai_with_structured_output(self, mock_client):
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(return_value=mock_response)
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Tell me about a person')]
         response_structure = {
             'type': 'object',
@@ -210,7 +210,7 @@ async def test_returns_unsuccessful_when_no_content_in_structured_response(self,
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(return_value=mock_response)
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Tell me about a person')]
         response_structure = {'type': 'object'}
 
@@ -236,7 +236,7 @@ async def test_handles_json_parsing_errors(self, mock_client):
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(return_value=mock_response)
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Tell me about a person')]
         response_structure = {'type': 'object'}
 
@@ -255,7 +255,7 @@ async def test_returns_unsuccessful_response_when_exception_thrown(self, mock_cl
         mock_client.chat.completions = MagicMock()
         mock_client.chat.completions.create = AsyncMock(side_effect=Exception('API Error'))
 
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
         messages = [LDMessage(role='user', content='Tell me about a person')]
         response_structure = {'type': 'object'}
 
@@ -272,7 +272,7 @@ class TestGetClient:
     def test_returns_underlying_client(self):
         """Should return the underlying OpenAI client."""
         mock_client = MagicMock()
-        provider = OpenAIProvider(mock_client, 'gpt-3.5-turbo', {})
+        provider = OpenAIRunnerFactory(mock_client, 'gpt-3.5-turbo', {})
 
         assert provider.get_client() is mock_client
 
@@ -281,7 +281,7 @@ class TestCreateModel:
     """Tests for create_model instance method."""
 
     def test_creates_connector_with_correct_model_and_parameters(self):
-        """Should create OpenAIProvider with correct model and parameters."""
+        """Should create OpenAIRunnerFactory with correct model and parameters."""
         mock_ai_config = MagicMock()
         mock_ai_config.to_dict.return_value = {
             'model': {
@@ -298,9 +298,9 @@ def test_creates_connector_with_correct_model_and_parameters(self):
             mock_client = MagicMock()
             mock_openai_class.return_value = mock_client
 
-            result = OpenAIProvider().create_model(mock_ai_config)
+            result = OpenAIRunnerFactory().create_model(mock_ai_config)
 
-            assert isinstance(result, OpenAIProvider)
+            assert isinstance(result, OpenAIRunnerFactory)
             assert result._model_name == 'gpt-4'
             assert result._parameters == {'temperature': 0.7, 'max_tokens': 1000}
 
@@ -313,9 +313,9 @@ def test_handles_missing_model_config(self):
             mock_client = MagicMock()
             mock_openai_class.return_value = mock_client
 
-            result = OpenAIProvider().create_model(mock_ai_config)
+            result = OpenAIRunnerFactory().create_model(mock_ai_config)
 
-            assert isinstance(result, OpenAIProvider)
+            assert isinstance(result, OpenAIRunnerFactory)
             assert result._model_name == ''
             assert result._parameters == {}
 

packages/sdk/server-ai/src/ldai/providers/runner_factory.py

@@ -40,8 +40,8 @@ def _get_provider_factory(provider_type: str) -> Optional[AIProvider]:
 
             if provider_type == 'openai':
                 RunnerFactory._pkg_exists('ldai_openai')
-                from ldai_openai import OpenAIProvider
-                return OpenAIProvider()
+                from ldai_openai import OpenAIRunnerFactory
+                return OpenAIRunnerFactory()
 
             log.warning(
                 f"Provider '{provider_type}' is not supported. "