first pass at patch

test_tool_error_fallback.py

@@ -0,0 +1,106 @@
+"""Test to reproduce the tool error fallback issue.
+
+When using ToolNode(...).with_fallbacks(...) with an error handler that returns
+ToolMessage objects, the messages are losing:
+1. The `name` field (becomes `None` instead of the tool name)
+2. The `status` field (becomes `success` instead of `error`)
+"""
+
+from unittest.mock import Mock
+
+from langchain_core.messages import AIMessage, ToolMessage
+from langchain_core.runnables import RunnableLambda
+from langchain_core.runnables.config import RunnableConfig
+from langchain_core.tools import tool
+
+from langgraph.prebuilt import ToolNode
+
+
+def _create_mock_runtime():
+    """Create a mock Runtime object for testing ToolNode outside of graph context."""
+    mock_runtime = Mock()
+    mock_runtime.store = None
+    mock_runtime.context = None
+    mock_runtime.stream_writer = lambda *args, **kwargs: None
+    return mock_runtime
+
+
+def _create_config_with_runtime() -> RunnableConfig:
+    """Create a RunnableConfig with mock Runtime for testing ToolNode."""
+    return {"configurable": {"__pregel_runtime": _create_mock_runtime()}}
+
+
+@tool
+def failing_tool(x: int) -> str:
+    """A tool that always fails."""
+    raise RuntimeError("This tool always fails!")
+
+
+def handle_tool_error(state) -> dict:
+    """Error handler that returns ToolMessages."""
+    print(f"handle_tool_error called with state: {state}")
+    print(f"State type: {type(state)}")
+    print(f"State keys: {state.keys() if isinstance(state, dict) else 'N/A'}")
+    error = state.get("error")
+    print(f"Error: {error}")
+    tool_calls = state["messages"][-1].tool_calls
+    print(f"Tool calls: {tool_calls}")
+    return {
+        "messages": [
+            ToolMessage(
+                content=f"Error: {repr(error)}\n please fix your mistakes.",
+                tool_call_id=tc["id"],
+            )
+            for tc in tool_calls
+        ]
+    }
+
+
+fallback_runnable = RunnableLambda(handle_tool_error)
+
+
+def test_tool_error_with_fallbacks():
+    """Test that ToolMessages from fallback handlers preserve name and status."""
+    # Create a ToolNode with a fallback
+    tool_node = ToolNode([failing_tool], handle_tool_errors=True).with_fallbacks(
+        [fallback_runnable],
+    )
+
+    # Create an AI message with a tool call
+    messages = [
+        AIMessage(
+            content="",
+            tool_calls=[
+                {
+                    "name": "failing_tool",
+                    "args": {"x": 1},
+                    "id": "call_123",
+                    "type": "tool_call",
+                }
+            ],
+        )
+    ]
+
+    # Invoke the tool node
+    result = tool_node.invoke({"messages": messages}, config=_create_config_with_runtime())
+
+    print("Result:", result)
+    print("Result type:", type(result))
+    print("Result keys:", result.keys() if isinstance(result, dict) else "N/A")
+    print("\nTool messages:")
+    for msg in result["messages"]:
+        if isinstance(msg, ToolMessage):
+            print(f"  - content: {msg.content[:50]}...")
+            print(f"    name: {msg.name}")
+            print(f"    tool_call_id: {msg.tool_call_id}")
+            print(f"    status: {msg.status}")
+            print()
+
+            # Check expectations
+            assert msg.name == "failing_tool", f"Expected name='failing_tool', got {msg.name}"
+            assert msg.status == "error", f"Expected status='error', got {msg.status}"
+            print("✓ Test passed!")
+
+
+if __name__ == "__main__":
+    test_tool_error_with_fallbacks()