feat!: narrow AgentGraphRunner.run input from Any to str

packages/ai-providers/server-ai-langchain/src/ldai_langchain/langgraph_agent_graph_runner.py

@@ -274,7 +274,7 @@ def route(state: WorkflowState) -> str:
         compiled = agent_builder.compile()
         return compiled, fn_name_to_config_key, node_keys
 
-    async def run(self, input: Any) -> AgentGraphRunnerResult:
+    async def run(self, input: str) -> AgentGraphRunnerResult:
         """
         Run the agent graph with the given input.
 
@@ -295,7 +295,7 @@ async def run(self, input: Any) -> AgentGraphRunnerResult:
             handler = LDMetricsCallbackHandler(self._node_keys, self._fn_name_to_config_key)
 
             result = await self._compiled.ainvoke(  # type: ignore[call-overload]
-                {'messages': [HumanMessage(content=str(input))]},
+                {'messages': [HumanMessage(content=input)]},
                 config={'callbacks': [handler], 'recursion_limit': 25},
             )
 

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

@@ -63,7 +63,7 @@ def __init__(
         self._tool_name_map: Dict[str, str] = {}
         self._node_metrics: Dict[str, LDAIMetrics] = {}
 
-    async def run(self, input: Any) -> AgentGraphRunnerResult:
+    async def run(self, input: str) -> AgentGraphRunnerResult:
         """
         Run the agent graph with the given input.
 
@@ -81,15 +81,14 @@ async def run(self, input: Any) -> AgentGraphRunnerResult:
         if root_key:
             path.append(root_key)
 
-        input_str = str(input)
         start_ns = time.perf_counter_ns()
         state = _RunState(last_handoff_ns=start_ns, last_node_key=root_key)
         try:
             from agents import Runner
             root_agent = self._build_agents(path, state)
             if root_key:
                 self._node_metrics[root_key] = LDAIMetrics(success=False)
-            result = await Runner.run(root_agent, input_str)
+            result = await Runner.run(root_agent, input)
             self._flush_final_segment(state, result)
             self._collect_tool_calls(result)
 

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

@@ -1,6 +1,6 @@
 """ManagedAgentGraph — LaunchDarkly managed wrapper for agent graph execution."""
 
-from typing import Any, Dict
+from typing import Dict
 
 from ldai.agent_graph import AgentGraphDefinition
 from ldai.providers import AgentGraphRunner
@@ -38,14 +38,14 @@ def __init__(
         self._graph = graph
         self._runner = runner
 
-    async def run(self, input: Any) -> ManagedGraphResult:
+    async def run(self, input: str) -> ManagedGraphResult:
         """
         Run the agent graph with the given input.
 
         Delegates to the underlying AgentGraphRunner, then drives all
         LaunchDarkly tracking from ``result.metrics``.
 
-        :param input: The input prompt or structured input for the graph
+        :param input: The user input prompt to process through the graph.
         :return: ManagedGraphResult containing the content, metric summary,
             and raw response.
         """

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

@@ -1,4 +1,4 @@
-from typing import Any, Protocol, runtime_checkable
+from typing import Protocol, runtime_checkable
 
 from ldai.providers.types import AgentGraphRunnerResult
 
@@ -18,11 +18,11 @@ class AgentGraphRunner(Protocol):
     the caller just passes input.
     """
 
-    async def run(self, input: Any) -> AgentGraphRunnerResult:
+    async def run(self, input: str) -> AgentGraphRunnerResult:
         """
         Run the agent graph with the given input.
 
-        :param input: The input to the agent graph (string prompt or structured input)
+        :param input: The string prompt to send to the agent graph
         :return: AgentGraphRunnerResult containing the content, raw response, and AIGraphMetrics
         """
         ...