fix: don't trace conditional edges and no todos in input state (#33842)

while experimenting w/ todo middleware

| Before | After |
|--------|-------|
| ![Screenshot 2025-11-05 at 1 56 21
PM](https://github.com/user-attachments/assets/63195ae4-8122-4662-8246-0fbc16cb1e22)
| ![Screenshot 2025-11-05 at 1 56 03
PM](https://github.com/user-attachments/assets/255e2fa8-e52d-4d1a-949a-33df52ee6668)
|
| Tracing conditional edges (verbose) | Not tracing conditional edges
(cleaner) |
| ![Screenshot 2025-11-05 at 1 57 56
PM](https://github.com/user-attachments/assets/449ccfe9-4c21-4c87-8e0e-6e89d7a97611)
| ![Screenshot 2025-11-05 at 1 56 58
PM](https://github.com/user-attachments/assets/c5c28d0e-2153-4572-af29-b2528761fec6)
|
| Todos in input state (cluttered) | No todos in input state (cleaner) |

Author: sydney-runkle

libs/langchain_v1/langchain/agents/factory.py

@@ -1268,11 +1268,14 @@ async def amodel_node(state: AgentState, runtime: Runtime[ContextT]) -> dict[str
 
         graph.add_conditional_edges(
             "tools",
-            _make_tools_to_model_edge(
-                tool_node=tool_node,
-                model_destination=loop_entry_node,
-                structured_output_tools=structured_output_tools,
-                end_destination=exit_node,
+            RunnableCallable(
+                _make_tools_to_model_edge(
+                    tool_node=tool_node,
+                    model_destination=loop_entry_node,
+                    structured_output_tools=structured_output_tools,
+                    end_destination=exit_node,
+                ),
+                trace=False,
             ),
             tools_to_model_destinations,
         )
@@ -1289,19 +1292,25 @@ async def amodel_node(state: AgentState, runtime: Runtime[ContextT]) -> dict[str
 
         graph.add_conditional_edges(
             loop_exit_node,
-            _make_model_to_tools_edge(
-                model_destination=loop_entry_node,
-                structured_output_tools=structured_output_tools,
-                end_destination=exit_node,
+            RunnableCallable(
+                _make_model_to_tools_edge(
+                    model_destination=loop_entry_node,
+                    structured_output_tools=structured_output_tools,
+                    end_destination=exit_node,
+                ),
+                trace=False,
             ),
             model_to_tools_destinations,
         )
     elif len(structured_output_tools) > 0:
         graph.add_conditional_edges(
             loop_exit_node,
-            _make_model_to_model_edge(
-                model_destination=loop_entry_node,
-                end_destination=exit_node,
+            RunnableCallable(
+                _make_model_to_model_edge(
+                    model_destination=loop_entry_node,
+                    end_destination=exit_node,
+                ),
+                trace=False,
             ),
             [loop_entry_node, exit_node],
         )
@@ -1602,7 +1611,7 @@ def jump_edge(state: dict[str, Any]) -> str:
         if "model" in can_jump_to and name != model_destination:
             destinations.append(model_destination)
 
-        graph.add_conditional_edges(name, jump_edge, destinations)
+        graph.add_conditional_edges(name, RunnableCallable(jump_edge, trace=False), destinations)
 
     else:
         graph.add_edge(name, default_destination)

libs/langchain_v1/langchain/agents/middleware/todo.py

@@ -19,6 +19,7 @@
     ModelCallResult,
     ModelRequest,
     ModelResponse,
+    OmitFromInput,
 )
 from langchain.tools import InjectedToolCallId
 
@@ -36,7 +37,7 @@ class Todo(TypedDict):
 class PlanningState(AgentState):
     """State schema for the todo middleware."""
 
-    todos: NotRequired[list[Todo]]
+    todos: Annotated[NotRequired[list[Todo]], OmitFromInput]
     """List of todo items for tracking task progress."""