diff --git a/libs/checkpoint/tests/test_jsonplus.py b/libs/checkpoint/tests/test_jsonplus.py
index c880f5045..4c3fa2949 100644
--- a/libs/checkpoint/tests/test_jsonplus.py
+++ b/libs/checkpoint/tests/test_jsonplus.py
@@ -275,7 +275,11 @@ def test_serde_jsonplus_json_mode() -> None:
     }
 
     if sys.version_info < (3, 14):
-        expected_result["my_pydantic_v1"] = {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}}
+        expected_result["my_pydantic_v1"] = {
+            "foo": "foo",
+            "bar": 1,
+            "inner": {"hello": "hello"},
+        }
         expected_result["my_secret_str_v1"] = "meow"
 
     assert result == expected_result
@@ -381,7 +385,12 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
                 "str_col": ["a", None, "c"],
             }
         ),
-        pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
+        pytest.param(
+            pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
+        ),
         pd.DataFrame(
             {
                 "int8": pd.array([1, 2, 3], dtype="int8"),
@@ -409,11 +418,25 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
                 "col3": np.random.rand(1000),
             }
         ),
-        pd.DataFrame(
-            {"tz_datetime": pd.date_range("2024-01-01", periods=3, freq="D", tz="UTC")}
+        pytest.param(
+            pd.DataFrame(
+                {
+                    "tz_datetime": pd.date_range(
+                        "2024-01-01", periods=3, freq="D", tz="UTC"
+                    )
+                }
+            ),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
         ),
         pd.DataFrame({"timedelta": pd.to_timedelta([1, 2, 3], unit="D")}),
-        pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
+        pytest.param(
+            pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
+        ),
         pd.DataFrame({"interval": pd.interval_range(start=0, end=3, periods=3)}),
         pd.DataFrame({"unicode": ["Hello 🌍", "Python 🐍", "Data 📊"]}),
         pd.DataFrame({"mixed": [1, "string", [1, 2, 3], {"key": "value"}]}),
@@ -450,7 +473,12 @@ def test_serde_jsonplus_pandas_dataframe(df: pd.DataFrame) -> None:
         pd.Series([1, 2, None]),
         pd.Series([1.1, None, 3.3]),
         pd.Series(["a", None, "c"]),
-        pd.Series(pd.Categorical(["a", "b", "a", "c"])),
+        pytest.param(
+            pd.Series(pd.Categorical(["a", "b", "a", "c"])),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
+        ),
         pd.Series([1, 2, 3], dtype="int8"),
         pd.Series([10, 20, 30], dtype="int16"),
         pd.Series([100, 200, 300], dtype="int32"),
diff --git a/libs/langgraph/pyproject.toml b/libs/langgraph/pyproject.toml
index 6776b4558..427d343ca 100644
--- a/libs/langgraph/pyproject.toml
+++ b/libs/langgraph/pyproject.toml
@@ -46,7 +46,7 @@ test = [
     "pytest-watcher",
     "pytest-xdist[psutil]",
     "pytest-repeat",
-    "langchain-core==1.0.0a1",
+    "langchain-core>=1.0.0",
     "langgraph-prebuilt",
     "langgraph-checkpoint",
     "langgraph-checkpoint-sqlite",
diff --git a/libs/langgraph/tests/__snapshots__/test_large_cases.ambr b/libs/langgraph/tests/__snapshots__/test_large_cases.ambr
index e4b6f346c..eb7f206ad 100644
--- a/libs/langgraph/tests/__snapshots__/test_large_cases.ambr
+++ b/libs/langgraph/tests/__snapshots__/test_large_cases.ambr
@@ -88,10 +88,10 @@
   '''
 # ---
 # name: test_message_graph[memory]
-  '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAIMessage is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model together standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nFunctionMessage are an older version of the ToolMessage schema, and\\ndo not contain the tool_call_id field.\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from a human.\\n\\nHumanMessages are messages that are passed in from a human to the model.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import HumanMessage, SystemMessage\\n\\n        messages = [\\n            SystemMessage(\\n                content=\\"You are a helpful assistant! Your name is Bob.\\"\\n            ),\\n            HumanMessage(\\n                content=\\"What is your name?\\"\\n            )\\n        ]\\n\\n        # Instantiate a chat model and invoke it with the messages\\n        model = ...\\n        print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"additionalProperties": true, "description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"audio\\": 10,\\n            \\"cache_creation\\": 200,\\n            \\"cache_read\\": 100,\\n        }\\n\\n.. versionadded:: 0.3.9\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"additionalProperties": true, "description": "Allowance for errors made by LLM.\\n\\nHere we add an ``error`` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"additionalProperties": true, "description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"audio\\": 10,\\n            \\"reasoning\\": 200,\\n        }\\n\\n.. versionadded:: 0.3.9", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import HumanMessage, SystemMessage\\n\\n        messages = [\\n            SystemMessage(\\n                content=\\"You are a helpful assistant! Your name is Bob.\\"\\n            ),\\n            HumanMessage(\\n                content=\\"What is your name?\\"\\n            )\\n        ]\\n\\n        # Define a chat model and invoke it with the messages\\n        print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"additionalProperties": true, "description": "Represents a request to call a tool.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"name\\": \\"foo\\",\\n            \\"args\\": {\\"a\\": 1},\\n            \\"id\\": \\"123\\"\\n        }\\n\\n    This represents a request to call the tool named \\"foo\\" with arguments {\\"a\\": 1}\\n    and an identifier of \\"123\\".", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"additionalProperties": true, "description": "A chunk of a tool call (e.g., as part of a stream).\\n\\nWhen merging ToolCallChunks (e.g., via AIMessageChunk.__add__),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n\\n.. code-block:: python\\n\\n    left_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\n    right_chunks = [ToolCallChunk(name=None, args=\'1}\', index=0)]\\n\\n    (\\n        AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n        + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n    ).tool_call_chunks == [ToolCallChunk(name=\'foo\', args=\'{\\"a\\":1}\', index=0)]", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nToolMessages contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A ToolMessage representing a result of 42 from a tool call with id\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import ToolMessage\\n\\n        ToolMessage(content=\'42\', tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\')\\n\\n\\nExample: A ToolMessage where only part of the tool output is sent to the model\\n    and the full output is passed in to artifact.\\n\\n    .. versionadded:: 0.2.17\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import ToolMessage\\n\\n        tool_output = {\\n            \\"stdout\\": \\"From the graph we can see that the correlation between x and y is ...\\",\\n            \\"stderr\\": None,\\n            \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n        }\\n\\n        ToolMessage(\\n            content=tool_output[\\"stdout\\"],\\n            artifact=tool_output,\\n            tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\',\\n        )\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"additionalProperties": true, "description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"input_tokens\\": 350,\\n            \\"output_tokens\\": 240,\\n            \\"total_tokens\\": 590,\\n            \\"input_token_details\\": {\\n                \\"audio\\": 10,\\n                \\"cache_creation\\": 200,\\n                \\"cache_read\\": 100,\\n            },\\n            \\"output_token_details\\": {\\n                \\"audio\\": 10,\\n                \\"reasoning\\": 200,\\n            }\\n        }\\n\\n.. versionchanged:: 0.3.9\\n\\n    Added ``input_token_details`` and ``output_token_details``.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphInput", "type": "array"}'
+  '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAn `AIMessage` is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model and standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI (yielded when streaming).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`FunctionMessage` are an older version of the `ToolMessage` schema, and\\ndo not contain the `tool_call_id` field.\\n\\nThe `tool_call_id` field is used to associate the tool call request with the\\ntool call response. Useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from the user.\\n\\nA `HumanMessage` is a message that is passed in from a user to the model.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Instantiate a chat model and invoke it with the messages\\n    model = ...\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"additionalProperties": true, "description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"cache_creation\\": 200,\\n        \\"cache_read\\": 100,\\n    }\\n    ```\\n\\n!!! version-added \\"Added in version 0.3.9\\"\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"additionalProperties": true, "description": "Allowance for errors made by LLM.\\n\\nHere we add an `error` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"additionalProperties": true, "description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"reasoning\\": 200,\\n    }\\n    ```\\n\\n!!! version-added \\"Added in version 0.3.9\\"", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Define a chat model and invoke it with the messages\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"additionalProperties": true, "description": "Represents an AI\'s request to call a tool.\\n\\nExample:\\n    ```python\\n    {\\"name\\": \\"foo\\", \\"args\\": {\\"a\\": 1}, \\"id\\": \\"123\\"}\\n    ```\\n\\n    This represents a request to call the tool named `\'foo\'` with arguments\\n    `{\\"a\\": 1}` and an identifier of `\'123\'`.", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"additionalProperties": true, "description": "A chunk of a tool call (yielded when streaming).\\n\\nWhen merging `ToolCallChunk`s (e.g., via `AIMessageChunk.__add__`),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n```python\\nleft_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\nright_chunks = [ToolCallChunk(name=None, args=\\"1}\\", index=0)]\\n\\n(\\n    AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n    + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n).tool_call_chunks == [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":1}\', index=0)]\\n```", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`ToolMessage` objects contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A `ToolMessage` representing a result of `42` from a tool call with id\\n\\n```python\\nfrom langchain_core.messages import ToolMessage\\n\\nToolMessage(content=\\"42\\", tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\")\\n```\\n\\nExample: A `ToolMessage` where only part of the tool output is sent to the model\\nand the full output is passed in to artifact.\\n\\n```python\\nfrom langchain_core.messages import ToolMessage\\n\\ntool_output = {\\n    \\"stdout\\": \\"From the graph we can see that the correlation between \\"\\n    \\"x and y is ...\\",\\n    \\"stderr\\": None,\\n    \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n}\\n\\nToolMessage(\\n    content=tool_output[\\"stdout\\"],\\n    artifact=tool_output,\\n    tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\",\\n)\\n```\\n\\nThe `tool_call_id` field is used to associate the tool call request with the\\ntool call response. Useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"additionalProperties": true, "description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n    ```python\\n    {\\n        \\"input_tokens\\": 350,\\n        \\"output_tokens\\": 240,\\n        \\"total_tokens\\": 590,\\n        \\"input_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"cache_creation\\": 200,\\n            \\"cache_read\\": 100,\\n        },\\n        \\"output_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"reasoning\\": 200,\\n        },\\n    }\\n    ```\\n\\n!!! warning \\"Behavior changed in 0.3.9\\"\\n    Added `input_token_details` and `output_token_details`.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphInput", "type": "array"}'
 # ---
 # name: test_message_graph[memory].1
-  '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAIMessage is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model together standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nFunctionMessage are an older version of the ToolMessage schema, and\\ndo not contain the tool_call_id field.\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from a human.\\n\\nHumanMessages are messages that are passed in from a human to the model.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import HumanMessage, SystemMessage\\n\\n        messages = [\\n            SystemMessage(\\n                content=\\"You are a helpful assistant! Your name is Bob.\\"\\n            ),\\n            HumanMessage(\\n                content=\\"What is your name?\\"\\n            )\\n        ]\\n\\n        # Instantiate a chat model and invoke it with the messages\\n        model = ...\\n        print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"additionalProperties": true, "description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"audio\\": 10,\\n            \\"cache_creation\\": 200,\\n            \\"cache_read\\": 100,\\n        }\\n\\n.. versionadded:: 0.3.9\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"additionalProperties": true, "description": "Allowance for errors made by LLM.\\n\\nHere we add an ``error`` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"additionalProperties": true, "description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"audio\\": 10,\\n            \\"reasoning\\": 200,\\n        }\\n\\n.. versionadded:: 0.3.9", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import HumanMessage, SystemMessage\\n\\n        messages = [\\n            SystemMessage(\\n                content=\\"You are a helpful assistant! Your name is Bob.\\"\\n            ),\\n            HumanMessage(\\n                content=\\"What is your name?\\"\\n            )\\n        ]\\n\\n        # Define a chat model and invoke it with the messages\\n        print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"additionalProperties": true, "description": "Represents a request to call a tool.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"name\\": \\"foo\\",\\n            \\"args\\": {\\"a\\": 1},\\n            \\"id\\": \\"123\\"\\n        }\\n\\n    This represents a request to call the tool named \\"foo\\" with arguments {\\"a\\": 1}\\n    and an identifier of \\"123\\".", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"additionalProperties": true, "description": "A chunk of a tool call (e.g., as part of a stream).\\n\\nWhen merging ToolCallChunks (e.g., via AIMessageChunk.__add__),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n\\n.. code-block:: python\\n\\n    left_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\n    right_chunks = [ToolCallChunk(name=None, args=\'1}\', index=0)]\\n\\n    (\\n        AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n        + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n    ).tool_call_chunks == [ToolCallChunk(name=\'foo\', args=\'{\\"a\\":1}\', index=0)]", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nToolMessages contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A ToolMessage representing a result of 42 from a tool call with id\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import ToolMessage\\n\\n        ToolMessage(content=\'42\', tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\')\\n\\n\\nExample: A ToolMessage where only part of the tool output is sent to the model\\n    and the full output is passed in to artifact.\\n\\n    .. versionadded:: 0.2.17\\n\\n    .. code-block:: python\\n\\n        from langchain_core.messages import ToolMessage\\n\\n        tool_output = {\\n            \\"stdout\\": \\"From the graph we can see that the correlation between x and y is ...\\",\\n            \\"stderr\\": None,\\n            \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n        }\\n\\n        ToolMessage(\\n            content=tool_output[\\"stdout\\"],\\n            artifact=tool_output,\\n            tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\',\\n        )\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"additionalProperties": true, "description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n\\n    .. code-block:: python\\n\\n        {\\n            \\"input_tokens\\": 350,\\n            \\"output_tokens\\": 240,\\n            \\"total_tokens\\": 590,\\n            \\"input_token_details\\": {\\n                \\"audio\\": 10,\\n                \\"cache_creation\\": 200,\\n                \\"cache_read\\": 100,\\n            },\\n            \\"output_token_details\\": {\\n                \\"audio\\": 10,\\n                \\"reasoning\\": 200,\\n            }\\n        }\\n\\n.. versionchanged:: 0.3.9\\n\\n    Added ``input_token_details`` and ``output_token_details``.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphOutput", "type": "array"}'
+  '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAn `AIMessage` is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model and standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI (yielded when streaming).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`FunctionMessage` are an older version of the `ToolMessage` schema, and\\ndo not contain the `tool_call_id` field.\\n\\nThe `tool_call_id` field is used to associate the tool call request with the\\ntool call response. Useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from the user.\\n\\nA `HumanMessage` is a message that is passed in from a user to the model.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Instantiate a chat model and invoke it with the messages\\n    model = ...\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"additionalProperties": true, "description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"cache_creation\\": 200,\\n        \\"cache_read\\": 100,\\n    }\\n    ```\\n\\n!!! version-added \\"Added in version 0.3.9\\"\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"additionalProperties": true, "description": "Allowance for errors made by LLM.\\n\\nHere we add an `error` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"additionalProperties": true, "description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"reasoning\\": 200,\\n    }\\n    ```\\n\\n!!! version-added \\"Added in version 0.3.9\\"", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Define a chat model and invoke it with the messages\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"additionalProperties": true, "description": "Represents an AI\'s request to call a tool.\\n\\nExample:\\n    ```python\\n    {\\"name\\": \\"foo\\", \\"args\\": {\\"a\\": 1}, \\"id\\": \\"123\\"}\\n    ```\\n\\n    This represents a request to call the tool named `\'foo\'` with arguments\\n    `{\\"a\\": 1}` and an identifier of `\'123\'`.", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"additionalProperties": true, "description": "A chunk of a tool call (yielded when streaming).\\n\\nWhen merging `ToolCallChunk`s (e.g., via `AIMessageChunk.__add__`),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n```python\\nleft_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\nright_chunks = [ToolCallChunk(name=None, args=\\"1}\\", index=0)]\\n\\n(\\n    AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n    + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n).tool_call_chunks == [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":1}\', index=0)]\\n```", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`ToolMessage` objects contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A `ToolMessage` representing a result of `42` from a tool call with id\\n\\n```python\\nfrom langchain_core.messages import ToolMessage\\n\\nToolMessage(content=\\"42\\", tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\")\\n```\\n\\nExample: A `ToolMessage` where only part of the tool output is sent to the model\\nand the full output is passed in to artifact.\\n\\n```python\\nfrom langchain_core.messages import ToolMessage\\n\\ntool_output = {\\n    \\"stdout\\": \\"From the graph we can see that the correlation between \\"\\n    \\"x and y is ...\\",\\n    \\"stderr\\": None,\\n    \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n}\\n\\nToolMessage(\\n    content=tool_output[\\"stdout\\"],\\n    artifact=tool_output,\\n    tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\",\\n)\\n```\\n\\nThe `tool_call_id` field is used to associate the tool call request with the\\ntool call response. Useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"additionalProperties": true, "description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n    ```python\\n    {\\n        \\"input_tokens\\": 350,\\n        \\"output_tokens\\": 240,\\n        \\"total_tokens\\": 590,\\n        \\"input_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"cache_creation\\": 200,\\n            \\"cache_read\\": 100,\\n        },\\n        \\"output_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"reasoning\\": 200,\\n        },\\n    }\\n    ```\\n\\n!!! warning \\"Behavior changed in 0.3.9\\"\\n    Added `input_token_details` and `output_token_details`.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphOutput", "type": "array"}'
 # ---
 # name: test_message_graph[memory].2
   '''
@@ -175,10 +175,10 @@
   '''
 # ---
 # name: test_prebuilt_tool_chat
-  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of ChatModels.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "deprecated": true, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
+  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of a chat model.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "deprecated": true, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
 # ---
 # name: test_prebuilt_tool_chat.1
-  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of ChatModels.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "deprecated": true, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
+  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of a chat model.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "deprecated": true, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
 # ---
 # name: test_prebuilt_tool_chat.2
   '''
@@ -295,13 +295,13 @@
   	__end__([<p>__end__</p>]):::last
   	__start__ --> router_node;
   	router_node -.-> normal_llm_node;
-  	router_node -.-> weather_graph_model_node;
+  	router_node -.-> weather_graph\3amodel_node;
   	normal_llm_node --> __end__;
-  	weather_graph_weather_node --> __end__;
+  	weather_graph\3aweather_node --> __end__;
   	subgraph weather_graph
-  	weather_graph_model_node(model_node)
-  	weather_graph_weather_node(weather_node<hr/><small><em>__interrupt = before</em></small>)
-  	weather_graph_model_node --> weather_graph_weather_node;
+  	weather_graph\3amodel_node(model_node)
+  	weather_graph\3aweather_node(weather_node<hr/><small><em>__interrupt = before</em></small>)
+  	weather_graph\3amodel_node --> weather_graph\3aweather_node;
   	end
   	classDef default fill:#f2f0ff,line-height:1.2
   	classDef first fill-opacity:0
diff --git a/libs/langgraph/tests/__snapshots__/test_pregel.ambr b/libs/langgraph/tests/__snapshots__/test_pregel.ambr
index d3808a63a..fded3d0c4 100644
--- a/libs/langgraph/tests/__snapshots__/test_pregel.ambr
+++ b/libs/langgraph/tests/__snapshots__/test_pregel.ambr
@@ -666,18 +666,18 @@
   	__end__([<p>__end__</p>]):::last
   	__start__ --> uno;
   	uno -.-> dos;
-  	uno -.-> subgraph_one;
+  	uno -.-> subgraph\3aone;
   	dos --> __end__;
-  	subgraph___end__ --> __end__;
+  	subgraph\3a__end__ --> __end__;
   	subgraph subgraph
-  	subgraph_one(one)
-  	subgraph_two(two)
-  	subgraph_three(three)
-  	subgraph___end__(<p>__end__</p>)
-  	subgraph_one -.-> subgraph_three;
-  	subgraph_one -.-> subgraph_two;
-  	subgraph_three --> subgraph___end__;
-  	subgraph_two --> subgraph___end__;
+  	subgraph\3aone(one)
+  	subgraph\3atwo(two)
+  	subgraph\3athree(three)
+  	subgraph\3a__end__(<p>__end__</p>)
+  	subgraph\3aone -.-> subgraph\3athree;
+  	subgraph\3aone -.-> subgraph\3atwo;
+  	subgraph\3athree --> subgraph\3a__end__;
+  	subgraph\3atwo --> subgraph\3a__end__;
   	end
   	classDef default fill:#f2f0ff,line-height:1.2
   	classDef first fill-opacity:0
@@ -705,11 +705,11 @@
   	__start__([<p>__start__</p>]):::first
   	side(side)
   	__end__([<p>__end__</p>]):::last
-  	__start__ --> inner_up;
-  	inner_up --> side;
+  	__start__ --> inner\3aup;
+  	inner\3aup --> side;
   	side --> __end__;
   	subgraph inner
-  	inner_up(up)
+  	inner\3aup(up)
   	end
   	classDef default fill:#f2f0ff,line-height:1.2
   	classDef first fill-opacity:0
@@ -868,19 +868,19 @@
   	__end__([<p>__end__</p>]):::last
   	__start__ -.-> tool_one;
   	__start__ -.-> tool_three;
-  	__start__ -.-> tool_two___start__;
+  	__start__ -.-> tool_two\3a__start__;
   	tool_one --> __end__;
   	tool_three --> __end__;
-  	tool_two___end__ --> __end__;
+  	tool_two\3a__end__ --> __end__;
   	subgraph tool_two
-  	tool_two___start__(<p>__start__</p>)
-  	tool_two_tool_two_slow(tool_two_slow)
-  	tool_two_tool_two_fast(tool_two_fast)
-  	tool_two___end__(<p>__end__</p>)
-  	tool_two___start__ -.-> tool_two_tool_two_fast;
-  	tool_two___start__ -.-> tool_two_tool_two_slow;
-  	tool_two_tool_two_fast --> tool_two___end__;
-  	tool_two_tool_two_slow --> tool_two___end__;
+  	tool_two\3a__start__(<p>__start__</p>)
+  	tool_two\3atool_two_slow(tool_two_slow)
+  	tool_two\3atool_two_fast(tool_two_fast)
+  	tool_two\3a__end__(<p>__end__</p>)
+  	tool_two\3a__start__ -.-> tool_two\3atool_two_fast;
+  	tool_two\3a__start__ -.-> tool_two\3atool_two_slow;
+  	tool_two\3atool_two_fast --> tool_two\3a__end__;
+  	tool_two\3atool_two_slow --> tool_two\3a__end__;
   	end
   	classDef default fill:#f2f0ff,line-height:1.2
   	classDef first fill-opacity:0
@@ -891,13 +891,13 @@
 # name: test_repeat_condition
   '''
   graph TD;
-  	Call_Tool -.-> Chart_Generator;
-  	Call_Tool -.-> Researcher;
-  	Chart_Generator -. &nbsp;call_tool&nbsp; .-> Call_Tool;
-  	Chart_Generator -. &nbsp;continue&nbsp; .-> Researcher;
-  	Chart_Generator -. &nbsp;end&nbsp; .-> __end__;
-  	Researcher -. &nbsp;call_tool&nbsp; .-> Call_Tool;
-  	Researcher -. &nbsp;continue&nbsp; .-> Chart_Generator;
+  	Call\20Tool -.-> Chart\20Generator;
+  	Call\20Tool -.-> Researcher;
+  	Chart\20Generator -. &nbsp;call_tool&nbsp; .-> Call\20Tool;
+  	Chart\20Generator -. &nbsp;continue&nbsp; .-> Researcher;
+  	Chart\20Generator -. &nbsp;end&nbsp; .-> __end__;
+  	Researcher -. &nbsp;call_tool&nbsp; .-> Call\20Tool;
+  	Researcher -. &nbsp;continue&nbsp; .-> Chart\20Generator;
   	Researcher -. &nbsp;end&nbsp; .-> __end__;
   	__start__ --> Researcher;
   	Researcher -. &nbsp;redo&nbsp; .-> Researcher;
@@ -939,25 +939,25 @@
   	__end__([<p>__end__</p>]):::last
   	__start__ --> gp_one;
   	gp_one -. &nbsp;1&nbsp; .-> __end__;
-  	gp_one -. &nbsp;0&nbsp; .-> gp_two___start__;
-  	gp_two___end__ --> gp_one;
+  	gp_one -. &nbsp;0&nbsp; .-> gp_two\3a__start__;
+  	gp_two\3a__end__ --> gp_one;
   	subgraph gp_two
-  	gp_two___start__(<p>__start__</p>)
-  	gp_two_p_one(p_one)
-  	gp_two___end__(<p>__end__</p>)
-  	gp_two___start__ --> gp_two_p_one;
-  	gp_two_p_one -. &nbsp;1&nbsp; .-> gp_two___end__;
-  	gp_two_p_one -. &nbsp;0&nbsp; .-> gp_two_p_two___start__;
-  	gp_two_p_two___end__ --> gp_two_p_one;
+  	gp_two\3a__start__(<p>__start__</p>)
+  	gp_two\3ap_one(p_one)
+  	gp_two\3a__end__(<p>__end__</p>)
+  	gp_two\3a__start__ --> gp_two\3ap_one;
+  	gp_two\3ap_one -. &nbsp;1&nbsp; .-> gp_two\3a__end__;
+  	gp_two\3ap_one -. &nbsp;0&nbsp; .-> gp_two\3ap_two\3a__start__;
+  	gp_two\3ap_two\3a__end__ --> gp_two\3ap_one;
   	subgraph p_two
-  	gp_two_p_two___start__(<p>__start__</p>)
-  	gp_two_p_two_c_one(c_one)
-  	gp_two_p_two_c_two(c_two)
-  	gp_two_p_two___end__(<p>__end__</p>)
-  	gp_two_p_two___start__ --> gp_two_p_two_c_one;
-  	gp_two_p_two_c_one -. &nbsp;1&nbsp; .-> gp_two_p_two___end__;
-  	gp_two_p_two_c_one -. &nbsp;0&nbsp; .-> gp_two_p_two_c_two;
-  	gp_two_p_two_c_two --> gp_two_p_two_c_one;
+  	gp_two\3ap_two\3a__start__(<p>__start__</p>)
+  	gp_two\3ap_two\3ac_one(c_one)
+  	gp_two\3ap_two\3ac_two(c_two)
+  	gp_two\3ap_two\3a__end__(<p>__end__</p>)
+  	gp_two\3ap_two\3a__start__ --> gp_two\3ap_two\3ac_one;
+  	gp_two\3ap_two\3ac_one -. &nbsp;1&nbsp; .-> gp_two\3ap_two\3a__end__;
+  	gp_two\3ap_two\3ac_one -. &nbsp;0&nbsp; .-> gp_two\3ap_two\3ac_two;
+  	gp_two\3ap_two\3ac_two --> gp_two\3ap_two\3ac_one;
   	end
   	end
   	classDef default fill:#f2f0ff,line-height:1.2
@@ -979,17 +979,17 @@
   	__end__([<p>__end__</p>]):::last
   	__start__ --> p_one;
   	p_one -. &nbsp;1&nbsp; .-> __end__;
-  	p_one -. &nbsp;0&nbsp; .-> p_two___start__;
-  	p_two___end__ --> p_one;
+  	p_one -. &nbsp;0&nbsp; .-> p_two\3a__start__;
+  	p_two\3a__end__ --> p_one;
   	subgraph p_two
-  	p_two___start__(<p>__start__</p>)
-  	p_two_c_one(c_one)
-  	p_two_c_two(c_two)
-  	p_two___end__(<p>__end__</p>)
-  	p_two___start__ --> p_two_c_one;
-  	p_two_c_one -. &nbsp;1&nbsp; .-> p_two___end__;
-  	p_two_c_one -. &nbsp;0&nbsp; .-> p_two_c_two;
-  	p_two_c_two --> p_two_c_one;
+  	p_two\3a__start__(<p>__start__</p>)
+  	p_two\3ac_one(c_one)
+  	p_two\3ac_two(c_two)
+  	p_two\3a__end__(<p>__end__</p>)
+  	p_two\3a__start__ --> p_two\3ac_one;
+  	p_two\3ac_one -. &nbsp;1&nbsp; .-> p_two\3a__end__;
+  	p_two\3ac_one -. &nbsp;0&nbsp; .-> p_two\3ac_two;
+  	p_two\3ac_two --> p_two\3ac_one;
   	end
   	classDef default fill:#f2f0ff,line-height:1.2
   	classDef first fill-opacity:0
diff --git a/libs/langgraph/tests/test_remote_graph.py b/libs/langgraph/tests/test_remote_graph.py
index d809b5155..f67e898ba 100644
--- a/libs/langgraph/tests/test_remote_graph.py
+++ b/libs/langgraph/tests/test_remote_graph.py
@@ -1124,7 +1124,6 @@ async def test_remote_graph_basic_invoke(remote_graph: RemoteGraph) -> None:
         "type": "ai",
         "name": None,
         "id": "ai3",
-        "example": False,
         "tool_calls": [],
         "invalid_tool_calls": [],
         "usage_metadata": None,
diff --git a/libs/langgraph/uv.lock b/libs/langgraph/uv.lock
index 98c646ffa..3fc3ffca1 100644
--- a/libs/langgraph/uv.lock
+++ b/libs/langgraph/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10"
 resolution-markers = [
     "python_full_version >= '3.14'",
@@ -1327,7 +1327,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.0.0a1"
+version = "1.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -1338,9 +1338,9 @@ dependencies = [
     { name = "tenacity" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d9/c8/25d9ff74f8d4184dfce0e5c3332d5a1c9bead5db5fcf9ed1f1d4a826a804/langchain_core-1.0.0a1.tar.gz", hash = "sha256:b1acc3342911c3a95db0e0bbfa600c5a528b2e46d6e8faa90cbc6f154a29c582", size = 603792, upload-time = "2025-08-27T17:41:44.264Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ad/d0/9db6d375ecf8bd498fcc87016e43c3d930ddbfbacf9a1e99018ada4e824f/langchain_core-1.0.0.tar.gz", hash = "sha256:8e81c94a22fa3a362a0f101bbd1271bf3725e50cf1e31c84e8f4a1c731279785", size = 764484, upload-time = "2025-10-17T13:48:24.408Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/3e/41/925fb1f2dfb9d85c492c9d5654cbede160e8e3aab5a91c25b557235e5578/langchain_core-1.0.0a1-py3-none-any.whl", hash = "sha256:83fe163134bc52245962f45f7098ec348eb85c1f02a75eb35d1771f80fa40420", size = 473126, upload-time = "2025-08-27T17:41:42.896Z" },
+    { url = "https://files.pythonhosted.org/packages/68/6a/8dd566cb7379d6e3a921f94713babba2f71cbed65c73c784c649c1fd7d4e/langchain_core-1.0.0-py3-none-any.whl", hash = "sha256:a94561bf75dd097c7d6e3864950f28dadc963f0bd810114de4095f41f634059b", size = 467157, upload-time = "2025-10-17T13:48:23.138Z" },
 ]
 
 [[package]]
@@ -1429,7 +1429,7 @@ requires-dist = [
 dev = [
     { name = "httpx" },
     { name = "jupyter" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1462,7 +1462,7 @@ lint = [
 ]
 test = [
     { name = "httpx" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1719,7 +1719,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.3.67" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]
 
diff --git a/libs/prebuilt/pyproject.toml b/libs/prebuilt/pyproject.toml
index ef033b6f0..50ad837fe 100644
--- a/libs/prebuilt/pyproject.toml
+++ b/libs/prebuilt/pyproject.toml
@@ -25,7 +25,7 @@ classifiers = [
 ]
 dependencies = [
     "langgraph-checkpoint>=2.1.0,<4.0.0",
-    "langchain-core>=0.3.67",
+    "langchain-core>=1.0.0",
 ]
 
 [project.urls]
diff --git a/libs/prebuilt/uv.lock b/libs/prebuilt/uv.lock
index 6bbf242a2..b5b028033 100644
--- a/libs/prebuilt/uv.lock
+++ b/libs/prebuilt/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10"
 
 [[package]]
@@ -228,7 +228,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.76"
+version = "1.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -239,9 +239,9 @@ dependencies = [
     { name = "tenacity" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/4f/4d/5e2ea7754ee0a1f524c412801c6ba9ad49318ecb58b0d524903c3d9efe0a/langchain_core-0.3.76.tar.gz", hash = "sha256:71136a122dd1abae2c289c5809d035cf12b5f2bb682d8a4c1078cd94feae7419", size = 573568, upload-time = "2025-09-10T14:49:39.863Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ad/d0/9db6d375ecf8bd498fcc87016e43c3d930ddbfbacf9a1e99018ada4e824f/langchain_core-1.0.0.tar.gz", hash = "sha256:8e81c94a22fa3a362a0f101bbd1271bf3725e50cf1e31c84e8f4a1c731279785", size = 764484, upload-time = "2025-10-17T13:48:24.408Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/77/b5/501c0ffcb09c734457ceaa86bc7b1dd37b6a261147bd653add03b838aacb/langchain_core-0.3.76-py3-none-any.whl", hash = "sha256:46e0eb48c7ac532432d51f8ca1ece1804c82afe9ae3dcf027b867edadf82b3ec", size = 447508, upload-time = "2025-09-10T14:49:38.179Z" },
+    { url = "https://files.pythonhosted.org/packages/68/6a/8dd566cb7379d6e3a921f94713babba2f71cbed65c73c784c649c1fd7d4e/langchain_core-1.0.0-py3-none-any.whl", hash = "sha256:a94561bf75dd097c7d6e3864950f28dadc963f0bd810114de4095f41f634059b", size = 467157, upload-time = "2025-10-17T13:48:23.138Z" },
 ]
 
 [[package]]
@@ -271,7 +271,7 @@ requires-dist = [
 dev = [
     { name = "httpx" },
     { name = "jupyter" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -304,7 +304,7 @@ lint = [
 ]
 test = [
     { name = "httpx" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -510,7 +510,7 @@ test = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.3.67" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]