refactor: type RunnerFactory.create_model/agent returns as Optional[Runner]

The factory's downstream consumers (ManagedModel, ManagedAgent) now
take Runner; aligning the factory's return types lets us drop the
type: ignore comments at the ManagedModel/ManagedAgent call sites.
Provider package PRs will update their concrete implementations to
match.

Judge still takes ModelRunner, so its call site picks up the
type: ignore[arg-type] in its place — that's resolved later in the
cleanup PR when Judge migrates to Runner.

Author: jsonbailey

packages/sdk/server-ai/src/ldai/client.py

@@ -339,7 +339,7 @@ def _create_judge_instance(
             if not provider:
                 return None
 
-            return Judge(judge_config, provider, sample_rate=sample_rate)
+            return Judge(judge_config, provider, sample_rate=sample_rate)  # type: ignore[arg-type]
         except Exception as e:
             log.warning('Failed to initialize judge %r: %s', key, e)
             return None
@@ -427,7 +427,7 @@ async def create_model(
         if not runner:
             return None
 
-        return ManagedModel(config, runner)  # type: ignore[arg-type]
+        return ManagedModel(config, runner)
 
     async def create_chat(
         self,
@@ -501,7 +501,7 @@ async def create_agent(
         if not runner:
             return None
 
-        return ManagedAgent(config, runner)  # type: ignore[arg-type]
+        return ManagedAgent(config, runner)
 
     def agent_config(
         self,

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

@@ -4,9 +4,8 @@
 from ldai import log
 from ldai.models import AIConfigKind
 from ldai.providers.agent_graph_runner import AgentGraphRunner
-from ldai.providers.agent_runner import AgentRunner
 from ldai.providers.ai_provider import AIProvider
-from ldai.providers.model_runner import ModelRunner
+from ldai.providers.runner import Runner
 
 T = TypeVar('T')
 
@@ -118,13 +117,13 @@ def _get_providers_to_try(
     def create_model(
         config: AIConfigKind,
         default_ai_provider: Optional[str] = None,
-    ) -> Optional[ModelRunner]:
+    ) -> Optional[Runner]:
         """
         Create a model executor for the given AI completion config.
 
         :param config: LaunchDarkly AI config (completion or judge)
         :param default_ai_provider: Optional provider override ('openai', 'langchain', …)
-        :return: Configured ModelRunner ready to invoke the model, or None
+        :return: Configured Runner ready to invoke the model, or None
         """
         provider_name = config.provider.name.lower() if config.provider else None
         providers = RunnerFactory._get_providers_to_try(default_ai_provider, provider_name)
@@ -135,7 +134,7 @@ def create_agent(
         config: Any,
         tools: Any,
         default_ai_provider: Optional[str] = None,
-    ) -> Optional[AgentRunner]:
+    ) -> Optional[Runner]:
         """
         CAUTION:
         This feature is experimental and should NOT be considered ready for production use.
@@ -147,7 +146,7 @@ def create_agent(
         :param config: LaunchDarkly AI agent config
         :param tools: Tool registry mapping tool names to callables
         :param default_ai_provider: Optional provider override
-        :return: AgentRunner instance, or None
+        :return: Runner instance, or None
         """
         provider_name = config.provider.name.lower() if config.provider else None
         providers = RunnerFactory._get_providers_to_try(default_ai_provider, provider_name)