x

libs/core/langchain_core/tools/base.py

@@ -650,8 +650,16 @@ class ChildTool(BaseTool):
         # pass as a positional argument.
         if isinstance(tool_input, str):
             return (tool_input,), {}
+        elif isinstance(tool_input, dict):
+            # Make a shallow copy of the input to allow downstream code
+            # to modify the root level of the input without affecting the
+            # original input.
+            # This is used by the tool to inject run time information like
+            # the callback manager.
+            return (), tool_input.copy()
         else:
-            return (), tool_input
+            # This code path is not expected to be reachable.
+            raise TypeError(f"Invalid tool input type: {type(tool_input)}")
 
     def run(
         self,
@@ -946,14 +954,6 @@ def _prep_run_args(
     else:
         tool_call_id = None
         tool_input = cast(Union[str, dict], input)
-        if not isinstance(tool_input, str):
-            try:
-                tool_input = tool_input.copy()
-            except Exception:
-                import copy
-
-                tool_input = copy.deepcopy(tool_input)
-
     return (
         tool_input,
         dict(

libs/core/tests/unit_tests/test_tools.py

@@ -2,12 +2,16 @@
 
 import inspect
 import json
+import pytest
 import sys
 import textwrap
 import threading
 from datetime import datetime
 from enum import Enum
 from functools import partial
+from pydantic import BaseModel, Field, ValidationError
+from pydantic.v1 import BaseModel as BaseModelV1
+from pydantic.v1 import ValidationError as ValidationErrorV1
 from typing import (
     Annotated,
     Any,
@@ -19,11 +23,6 @@ from typing import (
     Union,
     cast,
 )
-
-import pytest
-from pydantic import BaseModel, Field, ValidationError
-from pydantic.v1 import BaseModel as BaseModelV1
-from pydantic.v1 import ValidationError as ValidationErrorV1
 from typing_extensions import TypedDict
 
 from langchain_core import tools
@@ -35,7 +34,7 @@ from langchain_core.callbacks.manager import (
     CallbackManagerForRetrieverRun,
 )
 from langchain_core.documents import Document
-from langchain_core.messages import AIMessage, ToolCall, ToolMessage
+from langchain_core.messages import ToolCall, ToolMessage
 from langchain_core.messages.tool import ToolOutputMixin
 from langchain_core.retrievers import BaseRetriever
 from langchain_core.runnables import (
@@ -2606,62 +2605,89 @@ def test_title_property_preserved() -> None:
     }
 
 
-@pytest.mark.asyncio
-async def test_ainvoke_input_isolation_from_state_graph_context() -> None:
-    """Test that tool execution works correctly with LangGraph."""
-    import json
+async def test_tool_ainvoke_does_not_mutate_inputs() -> None:
+    """Verify that the inputs are not mutated when invoking a tool asynchronously."""
 
-    from blockbuster.blockbuster import blockbuster_skip
-
-    from langchain_core.messages import (
-        HumanMessage,
-        SystemMessage,
-    )
-
-    blockbuster_skip.set(True)
-
-    # Setup
-    prompt = "Help user with his/her requests"
-
-    # Create test tool
-    async def sleep(**arguments: dict[str, Any]) -> str:
+    def sync_no_op(foo: int) -> str:
         return "good"
 
-    my_tool = [
-        StructuredTool(
-            name="sleep",
-            description="Sleep for a while",
-            args_schema={
-                "type": "object",
-                "required": ["seconds"],
-                "properties": {
-                    "seconds": {"type": "number", "description": "How long to sleep"}
-                },
+    async def async_no_op(foo: int) -> str:
+        return "good"
+
+    tool = StructuredTool(
+        name="sample_tool",
+        description="",
+        args_schema={
+            "type": "object",
+            "required": ["foo"],
+            "properties": {
+                "seconds": {"type": "number", "description": "How big is foo"}
             },
-            coroutine=sleep,
-            func=sleep,
-        )
-    ]
-    _tools = {t.name: t for t in my_tool}
+        },
+        coroutine=async_no_op,
+        func=sync_no_op,
+    )
 
-    tool_calls = """
-    [{
-    "name": "sleep",
-    "args": {"seconds": 2},
-    "id": "call_0_82c17db8-95df-452f-a4c2-03f809022134",
-    "type": "tool_call"}]
-    """
+    tool_call = {
+        "name": "sample_tool",
+        "args": {"foo": 2},
+        "id": "call_0_82c17db8-95df-452f-a4c2-03f809022134",
+        "type": "tool_call",
+    }
 
-    # Test execution
-    messages: list[Any] = []
-    _input = "sleep for 2 seconds!"
-    messages.append(SystemMessage(content=prompt))
-    messages.append(HumanMessage(content=_input))
-    ai_message = AIMessage(tool_calls=json.loads(tool_calls), content="")
-    messages.append(ai_message)
+    assert tool.invoke(tool_call["args"]) == "good"
+    assert tool_call == {
+        "name": "sample_tool",
+        "args": {"foo": 2},
+        "id": "call_0_82c17db8-95df-452f-a4c2-03f809022134",
+        "type": "tool_call",
+    }
 
-    result = await _tools["sleep"].ainvoke(ai_message.tool_calls[0]["args"])
+    assert await tool.ainvoke(tool_call["args"]) == "good"
+
+    assert tool_call == {
+        "name": "sample_tool",
+        "args": {"foo": 2},
+        "id": "call_0_82c17db8-95df-452f-a4c2-03f809022134",
+        "type": "tool_call",
+    }
+
+
+def test_tool_invoke_does_not_mutate_inputs() -> None:
+    """Verify that the inputs are not mutated when invoking a tool synchronously."""
+
+    def sync_no_op(foo: int) -> str:
+        return "good"
+
+    async def async_no_op(foo: int) -> str:
+        return "good"
+
+    tool = StructuredTool(
+        name="sample_tool",
+        description="",
+        args_schema={
+            "type": "object",
+            "required": ["foo"],
+            "properties": {
+                "seconds": {"type": "number", "description": "How big is foo"}
+            },
+        },
+        coroutine=async_no_op,
+        func=sync_no_op,
+    )
+
+    tool_call = {
+        "name": "sample_tool",
+        "args": {"foo": 2},
+        "id": "call_0_82c17db8-95df-452f-a4c2-03f809022134",
+        "type": "tool_call",
+    }
+
+    assert tool.invoke(tool_call["args"]) == "good"
+    assert tool_call == {
+        "name": "sample_tool",
+        "args": {"foo": 2},
+        "id": "call_0_82c17db8-95df-452f-a4c2-03f809022134",
+        "type": "tool_call",
+    }
 
-    # Assertions
-    assert result == "good"
-    assert "run_manager" not in ai_message.tool_calls[0]["args"]