revert: Support for SystemMessage in create_agent (#33889)

Reverts langchain-ai/langchain#33640

Introduces lint errors into langchain-anthropic

Should incorporate into 1.1 instead of patch release.

libs/langchain_v1/langchain/agents/factory.py

@@ -516,7 +516,7 @@ def create_agent(  # noqa: PLR0915
     model: str | BaseChatModel,
     tools: Sequence[BaseTool | Callable | dict[str, Any]] | None = None,
     *,
-    system_prompt: str | SystemMessage | None = None,
+    system_prompt: str | None = None,
     middleware: Sequence[AgentMiddleware[StateT_co, ContextT]] = (),
     response_format: ResponseFormat[ResponseT] | type[ResponseT] | None = None,
     state_schema: type[AgentState[ResponseT]] | None = None,
@@ -548,9 +548,11 @@ def create_agent(  # noqa: PLR0915
 
             If `None` or an empty list, the agent will consist of a model node without a
             tool calling loop.
-        system_prompt: An optional system prompt for the LLM or
+        system_prompt: An optional system prompt for the LLM.
-        can already be a [`SystemMessage`][langchain.messages.SystemMessage] object.
 
+            Prompts are converted to a
+            [`SystemMessage`][langchain.messages.SystemMessage] and added to the
+            beginning of the message list.
         middleware: A sequence of middleware instances to apply to the agent.
 
             Middleware can intercept and modify agent behavior at various stages. See
@@ -1038,10 +1040,8 @@ def create_agent(  # noqa: PLR0915
         # Get the bound model (with auto-detection if needed)
         model_, effective_response_format = _get_bound_model(request)
         messages = request.messages
-        if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
+        if request.system_prompt:
-            messages = [SystemMessage(content=request.system_prompt), *messages]
+            messages = [SystemMessage(request.system_prompt), *messages]
-        elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
-            messages = [request.system_prompt, *messages]
 
         output = model_.invoke(messages)
 
@@ -1093,10 +1093,8 @@ def create_agent(  # noqa: PLR0915
         # Get the bound model (with auto-detection if needed)
         model_, effective_response_format = _get_bound_model(request)
         messages = request.messages
-        if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
+        if request.system_prompt:
-            messages = [SystemMessage(content=request.system_prompt), *messages]
+            messages = [SystemMessage(request.system_prompt), *messages]
-        elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
-            messages = [request.system_prompt, *messages]
 
         output = await model_.ainvoke(messages)
 

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

@@ -225,11 +225,9 @@ class ContextEditingMiddleware(AgentMiddleware):
             def count_tokens(messages: Sequence[BaseMessage]) -> int:
                 return count_tokens_approximately(messages)
         else:
-            system_msg = []
+            system_msg = (
-            if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
+                [SystemMessage(content=request.system_prompt)] if request.system_prompt else []
-                system_msg = [SystemMessage(content=request.system_prompt)]
+            )
-            elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
-                system_msg = [request.system_prompt]
 
             def count_tokens(messages: Sequence[BaseMessage]) -> int:
                 return request.model.get_num_tokens_from_messages(
@@ -255,12 +253,9 @@ class ContextEditingMiddleware(AgentMiddleware):
             def count_tokens(messages: Sequence[BaseMessage]) -> int:
                 return count_tokens_approximately(messages)
         else:
-            system_msg = []
+            system_msg = (
-
+                [SystemMessage(content=request.system_prompt)] if request.system_prompt else []
-            if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
+            )
-                system_msg = [SystemMessage(content=request.system_prompt)]
-            elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
-                system_msg = [request.system_prompt]
 
             def count_tokens(messages: Sequence[BaseMessage]) -> int:
                 return request.model.get_num_tokens_from_messages(

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

@@ -8,7 +8,7 @@ from typing import TYPE_CHECKING, Annotated, Literal
 if TYPE_CHECKING:
     from collections.abc import Awaitable, Callable
 
-from langchain_core.messages import SystemMessage, ToolMessage
+from langchain_core.messages import ToolMessage
 from langchain_core.tools import tool
 from langgraph.types import Command
 from typing_extensions import NotRequired, TypedDict
@@ -199,22 +199,11 @@ class TodoListMiddleware(AgentMiddleware):
         handler: Callable[[ModelRequest], ModelResponse],
     ) -> ModelCallResult:
         """Update the system prompt to include the todo system prompt."""
-        if request.system_prompt is None:
+        request.system_prompt = (
-            request.system_prompt = self.system_prompt
+            request.system_prompt + "\n\n" + self.system_prompt
-        elif isinstance(request.system_prompt, str):
+            if request.system_prompt
-            request.system_prompt = request.system_prompt + "\n\n" + self.system_prompt
+            else self.system_prompt
-        elif isinstance(request.system_prompt, SystemMessage) and isinstance(
+        )
-            request.system_prompt.content, str
-        ):
-            request.system_prompt = SystemMessage(
-                content=request.system_prompt.content + self.system_prompt
-            )
-        elif isinstance(request.system_prompt, SystemMessage) and isinstance(
-            request.system_prompt.content, list
-        ):
-            request.system_prompt = SystemMessage(
-                content=[*request.system_prompt.content, self.system_prompt]
-            )
         return handler(request)
 
     async def awrap_model_call(
@@ -223,20 +212,9 @@ class TodoListMiddleware(AgentMiddleware):
         handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
     ) -> ModelCallResult:
         """Update the system prompt to include the todo system prompt (async version)."""
-        if request.system_prompt is None:
+        request.system_prompt = (
-            request.system_prompt = self.system_prompt
+            request.system_prompt + "\n\n" + self.system_prompt
-        elif isinstance(request.system_prompt, str):
+            if request.system_prompt
-            request.system_prompt = request.system_prompt + "\n\n" + self.system_prompt
+            else self.system_prompt
-        elif isinstance(request.system_prompt, SystemMessage) and isinstance(
+        )
-            request.system_prompt.content, str
-        ):
-            request.system_prompt = SystemMessage(
-                content=request.system_prompt.content + self.system_prompt
-            )
-        elif isinstance(request.system_prompt, SystemMessage) and isinstance(
-            request.system_prompt.content, list
-        ):
-            request.system_prompt = SystemMessage(
-                content=[*request.system_prompt.content, self.system_prompt]
-            )
         return await handler(request)

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

@@ -26,7 +26,6 @@ from langchain_core.messages import (  # noqa: TC002
     AIMessage,
     AnyMessage,
     BaseMessage,
-    SystemMessage,
     ToolMessage,
 )
 from langgraph.channels.ephemeral_value import EphemeralValue
@@ -86,7 +85,7 @@ class ModelRequest:
     """Model request information for the agent."""
 
     model: BaseChatModel
-    system_prompt: str | SystemMessage | None
+    system_prompt: str | None
     messages: list[AnyMessage]  # excluding system prompt
     tool_choice: Any | None
     tools: list[BaseTool | dict]
@@ -104,7 +103,7 @@ class ModelRequest:
         Args:
             **overrides: Keyword arguments for attributes to override. Supported keys:
                 - model: BaseChatModel instance
-                - system_prompt: Optional system prompt string or SystemMessage object
+                - system_prompt: Optional system prompt string
                 - messages: List of messages
                 - tool_choice: Tool choice configuration
                 - tools: List of available tools
@@ -1257,7 +1256,7 @@ def dynamic_prompt(
             request: ModelRequest,
             handler: Callable[[ModelRequest], ModelResponse],
         ) -> ModelCallResult:
-            prompt = cast("str | SystemMessage", func(request))
+            prompt = cast("str", func(request))
             request.system_prompt = prompt
             return handler(request)
 
@@ -1267,7 +1266,7 @@ def dynamic_prompt(
             handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
         ) -> ModelCallResult:
             # Delegate to sync function
-            prompt = cast("str | SystemMessage", func(request))
+            prompt = cast("str", func(request))
             request.system_prompt = prompt
             return await handler(request)
 

libs/langchain_v1/tests/unit_tests/agents/test_context_editing_middleware.py

@@ -13,7 +13,6 @@ from langchain_core.language_models.fake_chat_models import FakeChatModel
 from langchain_core.messages import (
     AIMessage,
     MessageLikeRepresentation,
-    SystemMessage,
     ToolMessage,
 )
 from langgraph.runtime import Runtime
@@ -400,126 +399,3 @@ async def test_exclude_tools_prevents_clearing_async() -> None:
 
     assert isinstance(calc_tool, ToolMessage)
     assert calc_tool.content == "[cleared]"
-
-
-# ==============================================================================
-# SystemMessage Tests
-# ==============================================================================
-
-
-def test_handles_system_message_prompt() -> None:
-    """Test that middleware handles SystemMessage as system_prompt correctly."""
-    tool_call_id = "call-1"
-    ai_message = AIMessage(
-        content="",
-        tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
-    )
-    tool_message = ToolMessage(content="12345", tool_call_id=tool_call_id)
-
-    system_prompt = SystemMessage(content="You are a helpful assistant.")
-    state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
-    # Manually set SystemMessage as system_prompt
-    request.system_prompt = system_prompt
-
-    middleware = ContextEditingMiddleware(
-        edits=[ClearToolUsesEdit(trigger=50)],
-        token_count_method="model",
-    )
-
-    def mock_handler(req: ModelRequest) -> AIMessage:
-        return AIMessage(content="mock response")
-
-    # Call wrap_model_call - should not fail with SystemMessage
-    middleware.wrap_model_call(request, mock_handler)
-
-    # Request should have processed without errors
-    assert request.system_prompt == system_prompt
-    assert isinstance(request.system_prompt, SystemMessage)
-
-
-def test_does_not_double_wrap_system_message() -> None:
-    """Test that middleware doesn't wrap SystemMessage in another SystemMessage."""
-    tool_call_id = "call-1"
-    ai_message = AIMessage(
-        content="",
-        tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
-    )
-    tool_message = ToolMessage(content="x" * 100, tool_call_id=tool_call_id)
-
-    system_prompt = SystemMessage(content="Original system prompt")
-    state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
-    request.system_prompt = system_prompt
-
-    middleware = ContextEditingMiddleware(
-        edits=[ClearToolUsesEdit(trigger=50)],
-        token_count_method="model",
-    )
-
-    def mock_handler(req: ModelRequest) -> AIMessage:
-        return AIMessage(content="mock response")
-
-    middleware.wrap_model_call(request, mock_handler)
-
-    # System prompt should still be the same SystemMessage, not wrapped
-    assert request.system_prompt == system_prompt
-    assert isinstance(request.system_prompt, SystemMessage)
-    assert request.system_prompt.content == "Original system prompt"
-
-
-async def test_handles_system_message_prompt_async() -> None:
-    """Test async version - middleware handles SystemMessage as system_prompt correctly."""
-    tool_call_id = "call-1"
-    ai_message = AIMessage(
-        content="",
-        tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
-    )
-    tool_message = ToolMessage(content="12345", tool_call_id=tool_call_id)
-
-    system_prompt = SystemMessage(content="You are a helpful assistant.")
-    state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
-    # Manually set SystemMessage as system_prompt
-    request.system_prompt = system_prompt
-
-    middleware = ContextEditingMiddleware(
-        edits=[ClearToolUsesEdit(trigger=50)],
-        token_count_method="model",
-    )
-
-    async def mock_handler(req: ModelRequest) -> AIMessage:
-        return AIMessage(content="mock response")
-
-    # Call awrap_model_call - should not fail with SystemMessage
-    await middleware.awrap_model_call(request, mock_handler)
-
-    # Request should have processed without errors
-    assert request.system_prompt == system_prompt
-    assert isinstance(request.system_prompt, SystemMessage)
-
-
-async def test_does_not_double_wrap_system_message_async() -> None:
-    """Test async version - middleware doesn't wrap SystemMessage in another SystemMessage."""
-    tool_call_id = "call-1"
-    ai_message = AIMessage(
-        content="",
-        tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
-    )
-    tool_message = ToolMessage(content="x" * 100, tool_call_id=tool_call_id)
-
-    system_prompt = SystemMessage(content="Original system prompt")
-    state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
-    request.system_prompt = system_prompt
-
-    middleware = ContextEditingMiddleware(
-        edits=[ClearToolUsesEdit(trigger=50)],
-        token_count_method="model",
-    )
-
-    async def mock_handler(req: ModelRequest) -> AIMessage:
-        return AIMessage(content="mock response")
-
-    await middleware.awrap_model_call(request, mock_handler)
-
-    # System prompt should still be the same SystemMessage, not wrapped
-    assert request.system_prompt == system_prompt
-    assert isinstance(request.system_prompt, SystemMessage)
-    assert request.system_prompt.content == "Original system prompt"

libs/langchain_v1/tests/unit_tests/agents/test_todo_middleware.py

@@ -5,7 +5,7 @@ from __future__ import annotations
 from typing import cast
 
 from langchain_core.language_models.fake_chat_models import GenericFakeChatModel
-from langchain_core.messages import AIMessage, SystemMessage
+from langchain_core.messages import AIMessage
 
 from langchain.agents.middleware.todo import TodoListMiddleware
 from langchain.agents.middleware.types import ModelRequest, ModelResponse
@@ -170,131 +170,3 @@ async def test_handler_called_with_modified_request_async() -> None:
     assert received_prompt["value"] is not None
     assert "Original" in received_prompt["value"]
     assert "write_todos" in received_prompt["value"]
-
-
-# ==============================================================================
-# SystemMessage Tests
-# ==============================================================================
-
-
-def test_appends_to_system_message_with_list_content() -> None:
-    """Test that middleware appends to SystemMessage with list content."""
-    existing_prompt = SystemMessage(content=["You are helpful.", "Be concise."])
-    middleware = TodoListMiddleware()
-
-    model = GenericFakeChatModel(messages=iter([AIMessage(content="response")]))
-    request = ModelRequest(
-        model=model,
-        system_prompt=existing_prompt,
-        messages=[],
-        tool_choice=None,
-        tools=[],
-        response_format=None,
-        state=cast("AgentState", {}),  # type: ignore[name-defined]
-        runtime=_fake_runtime(),
-        model_settings={},
-    )
-
-    def mock_handler(req: ModelRequest) -> ModelResponse:
-        return ModelResponse(result=[AIMessage(content="response")])
-
-    middleware.wrap_model_call(request, mock_handler)
-
-    # System prompt should be a SystemMessage with combined content
-    assert isinstance(request.system_prompt, SystemMessage)
-    assert isinstance(request.system_prompt.content, list)
-    assert len(request.system_prompt.content) == 3
-    assert request.system_prompt.content[0] == "You are helpful."
-    assert request.system_prompt.content[1] == "Be concise."
-    assert "write_todos" in request.system_prompt.content[2]
-
-
-async def test_appends_to_system_message_with_string_content_async() -> None:
-    """Test async version - middleware appends to SystemMessage with string content."""
-    existing_prompt = SystemMessage(content="You are a helpful assistant.")
-    middleware = TodoListMiddleware()
-
-    model = GenericFakeChatModel(messages=iter([AIMessage(content="response")]))
-    request = ModelRequest(
-        model=model,
-        system_prompt=existing_prompt,
-        messages=[],
-        tool_choice=None,
-        tools=[],
-        response_format=None,
-        state=cast("AgentState", {}),  # type: ignore[name-defined]
-        runtime=_fake_runtime(),
-        model_settings={},
-    )
-
-    async def mock_handler(req: ModelRequest) -> ModelResponse:
-        return ModelResponse(result=[AIMessage(content="response")])
-
-    await middleware.awrap_model_call(request, mock_handler)
-
-    # System prompt should be a SystemMessage with combined content
-    assert isinstance(request.system_prompt, SystemMessage)
-    assert isinstance(request.system_prompt.content, str)
-    assert "You are a helpful assistant." in request.system_prompt.content
-    assert middleware.system_prompt in request.system_prompt.content
-
-
-async def test_appends_to_system_message_with_list_content_async() -> None:
-    """Test async version - middleware appends to SystemMessage with list content."""
-    existing_prompt = SystemMessage(content=["You are helpful.", "Be concise."])
-    middleware = TodoListMiddleware()
-
-    model = GenericFakeChatModel(messages=iter([AIMessage(content="response")]))
-    request = ModelRequest(
-        model=model,
-        system_prompt=existing_prompt,
-        messages=[],
-        tool_choice=None,
-        tools=[],
-        response_format=None,
-        state=cast("AgentState", {}),  # type: ignore[name-defined]
-        runtime=_fake_runtime(),
-        model_settings={},
-    )
-
-    async def mock_handler(req: ModelRequest) -> ModelResponse:
-        return ModelResponse(result=[AIMessage(content="response")])
-
-    await middleware.awrap_model_call(request, mock_handler)
-
-    # System prompt should be a SystemMessage with combined content
-    assert isinstance(request.system_prompt, SystemMessage)
-    assert isinstance(request.system_prompt.content, list)
-    assert len(request.system_prompt.content) == 3
-    assert request.system_prompt.content[0] == "You are helpful."
-    assert request.system_prompt.content[1] == "Be concise."
-    assert "write_todos" in request.system_prompt.content[2]
-
-
-def test_creates_system_message_when_prompt_is_system_message() -> None:
-    """Test that middleware preserves SystemMessage type."""
-    existing_prompt = SystemMessage(content="Original instructions")
-    middleware = TodoListMiddleware(system_prompt="Todo instructions")
-
-    model = GenericFakeChatModel(messages=iter([AIMessage(content="response")]))
-    request = ModelRequest(
-        model=model,
-        system_prompt=existing_prompt,
-        messages=[],
-        tool_choice=None,
-        tools=[],
-        response_format=None,
-        state=cast("AgentState", {}),  # type: ignore[name-defined]
-        runtime=_fake_runtime(),
-        model_settings={},
-    )
-
-    def mock_handler(req: ModelRequest) -> ModelResponse:
-        return ModelResponse(result=[AIMessage(content="response")])
-
-    result = middleware.wrap_model_call(request, mock_handler)
-
-    # Result should be returned from handler
-    assert isinstance(result, ModelResponse)
-    # System prompt should still be a SystemMessage
-    assert isinstance(request.system_prompt, SystemMessage)