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chore(langchain): Support for SystemMessage in create_agent (#33640)
- **Description:** Updated Function Signature of `create_agent`, the system prompt can be both a list and string. I see no harm in doing this, since SystemMessage accepts both. - **Issue:** #33630 --------- Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>
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@@ -516,7 +516,7 @@ def create_agent( # noqa: PLR0915
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model: str | BaseChatModel,
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tools: Sequence[BaseTool | Callable | dict[str, Any]] | None = None,
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*,
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system_prompt: str | None = None,
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system_prompt: str | SystemMessage | None = None,
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middleware: Sequence[AgentMiddleware[StateT_co, ContextT]] = (),
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response_format: ResponseFormat[ResponseT] | type[ResponseT] | None = None,
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state_schema: type[AgentState[ResponseT]] | None = None,
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@@ -548,11 +548,9 @@ def create_agent( # noqa: PLR0915
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If `None` or an empty list, the agent will consist of a model node without a
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tool calling loop.
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system_prompt: An optional system prompt for the LLM.
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system_prompt: An optional system prompt for the LLM or
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can already be a [`SystemMessage`][langchain.messages.SystemMessage] object.
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Prompts are converted to a
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[`SystemMessage`][langchain.messages.SystemMessage] and added to the
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beginning of the message list.
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middleware: A sequence of middleware instances to apply to the agent.
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Middleware can intercept and modify agent behavior at various stages. See
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@@ -1040,8 +1038,10 @@ def create_agent( # noqa: PLR0915
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# Get the bound model (with auto-detection if needed)
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model_, effective_response_format = _get_bound_model(request)
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messages = request.messages
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if request.system_prompt:
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messages = [SystemMessage(request.system_prompt), *messages]
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if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
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messages = [SystemMessage(content=request.system_prompt), *messages]
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elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
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messages = [request.system_prompt, *messages]
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output = model_.invoke(messages)
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@@ -1093,8 +1093,10 @@ def create_agent( # noqa: PLR0915
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# Get the bound model (with auto-detection if needed)
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model_, effective_response_format = _get_bound_model(request)
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messages = request.messages
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if request.system_prompt:
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messages = [SystemMessage(request.system_prompt), *messages]
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if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
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messages = [SystemMessage(content=request.system_prompt), *messages]
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elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
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messages = [request.system_prompt, *messages]
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output = await model_.ainvoke(messages)
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@@ -225,9 +225,11 @@ class ContextEditingMiddleware(AgentMiddleware):
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def count_tokens(messages: Sequence[BaseMessage]) -> int:
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return count_tokens_approximately(messages)
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else:
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system_msg = (
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[SystemMessage(content=request.system_prompt)] if request.system_prompt else []
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)
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system_msg = []
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if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
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system_msg = [SystemMessage(content=request.system_prompt)]
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elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
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system_msg = [request.system_prompt]
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def count_tokens(messages: Sequence[BaseMessage]) -> int:
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return request.model.get_num_tokens_from_messages(
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@@ -253,9 +255,12 @@ class ContextEditingMiddleware(AgentMiddleware):
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def count_tokens(messages: Sequence[BaseMessage]) -> int:
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return count_tokens_approximately(messages)
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else:
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system_msg = (
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[SystemMessage(content=request.system_prompt)] if request.system_prompt else []
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)
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system_msg = []
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if request.system_prompt and not isinstance(request.system_prompt, SystemMessage):
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system_msg = [SystemMessage(content=request.system_prompt)]
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elif request.system_prompt and isinstance(request.system_prompt, SystemMessage):
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system_msg = [request.system_prompt]
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def count_tokens(messages: Sequence[BaseMessage]) -> int:
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return request.model.get_num_tokens_from_messages(
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@@ -8,7 +8,7 @@ from typing import TYPE_CHECKING, Annotated, Literal
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if TYPE_CHECKING:
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from collections.abc import Awaitable, Callable
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from langchain_core.messages import ToolMessage
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from langchain_core.messages import SystemMessage, ToolMessage
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from langchain_core.tools import tool
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from langgraph.types import Command
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from typing_extensions import NotRequired, TypedDict
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@@ -199,11 +199,22 @@ class TodoListMiddleware(AgentMiddleware):
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handler: Callable[[ModelRequest], ModelResponse],
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) -> ModelCallResult:
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"""Update the system prompt to include the todo system prompt."""
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request.system_prompt = (
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request.system_prompt + "\n\n" + self.system_prompt
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if request.system_prompt
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else self.system_prompt
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)
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if request.system_prompt is None:
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request.system_prompt = self.system_prompt
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elif isinstance(request.system_prompt, str):
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request.system_prompt = request.system_prompt + "\n\n" + self.system_prompt
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elif isinstance(request.system_prompt, SystemMessage) and isinstance(
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request.system_prompt.content, str
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):
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request.system_prompt = SystemMessage(
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content=request.system_prompt.content + self.system_prompt
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)
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elif isinstance(request.system_prompt, SystemMessage) and isinstance(
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request.system_prompt.content, list
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):
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request.system_prompt = SystemMessage(
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content=[*request.system_prompt.content, self.system_prompt]
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)
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return handler(request)
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async def awrap_model_call(
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@@ -212,9 +223,20 @@ class TodoListMiddleware(AgentMiddleware):
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handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
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) -> ModelCallResult:
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"""Update the system prompt to include the todo system prompt (async version)."""
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request.system_prompt = (
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request.system_prompt + "\n\n" + self.system_prompt
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if request.system_prompt
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else self.system_prompt
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)
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if request.system_prompt is None:
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request.system_prompt = self.system_prompt
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elif isinstance(request.system_prompt, str):
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request.system_prompt = request.system_prompt + "\n\n" + self.system_prompt
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elif isinstance(request.system_prompt, SystemMessage) and isinstance(
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request.system_prompt.content, str
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):
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request.system_prompt = SystemMessage(
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content=request.system_prompt.content + self.system_prompt
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)
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elif isinstance(request.system_prompt, SystemMessage) and isinstance(
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request.system_prompt.content, list
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):
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request.system_prompt = SystemMessage(
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content=[*request.system_prompt.content, self.system_prompt]
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)
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return await handler(request)
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@@ -26,6 +26,7 @@ from langchain_core.messages import ( # noqa: TC002
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AIMessage,
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AnyMessage,
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BaseMessage,
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SystemMessage,
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ToolMessage,
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)
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from langgraph.channels.ephemeral_value import EphemeralValue
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@@ -85,7 +86,7 @@ class ModelRequest:
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"""Model request information for the agent."""
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model: BaseChatModel
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system_prompt: str | None
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system_prompt: str | SystemMessage | None
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messages: list[AnyMessage] # excluding system prompt
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tool_choice: Any | None
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tools: list[BaseTool | dict]
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@@ -103,7 +104,7 @@ class ModelRequest:
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Args:
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**overrides: Keyword arguments for attributes to override. Supported keys:
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- model: BaseChatModel instance
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- system_prompt: Optional system prompt string
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- system_prompt: Optional system prompt string or SystemMessage object
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- messages: List of messages
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- tool_choice: Tool choice configuration
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- tools: List of available tools
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@@ -1256,7 +1257,7 @@ def dynamic_prompt(
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request: ModelRequest,
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handler: Callable[[ModelRequest], ModelResponse],
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) -> ModelCallResult:
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prompt = cast("str", func(request))
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prompt = cast("str | SystemMessage", func(request))
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request.system_prompt = prompt
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return handler(request)
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@@ -1266,7 +1267,7 @@ def dynamic_prompt(
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handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
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) -> ModelCallResult:
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# Delegate to sync function
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prompt = cast("str", func(request))
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prompt = cast("str | SystemMessage", func(request))
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request.system_prompt = prompt
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return await handler(request)
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@@ -13,6 +13,7 @@ from langchain_core.language_models.fake_chat_models import FakeChatModel
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from langchain_core.messages import (
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AIMessage,
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MessageLikeRepresentation,
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SystemMessage,
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ToolMessage,
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)
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from langgraph.runtime import Runtime
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@@ -399,3 +400,126 @@ async def test_exclude_tools_prevents_clearing_async() -> None:
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assert isinstance(calc_tool, ToolMessage)
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assert calc_tool.content == "[cleared]"
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# ==============================================================================
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# SystemMessage Tests
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# ==============================================================================
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def test_handles_system_message_prompt() -> None:
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"""Test that middleware handles SystemMessage as system_prompt correctly."""
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tool_call_id = "call-1"
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ai_message = AIMessage(
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content="",
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tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
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)
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tool_message = ToolMessage(content="12345", tool_call_id=tool_call_id)
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system_prompt = SystemMessage(content="You are a helpful assistant.")
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state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
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# Manually set SystemMessage as system_prompt
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request.system_prompt = system_prompt
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middleware = ContextEditingMiddleware(
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edits=[ClearToolUsesEdit(trigger=50)],
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token_count_method="model",
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)
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def mock_handler(req: ModelRequest) -> AIMessage:
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return AIMessage(content="mock response")
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# Call wrap_model_call - should not fail with SystemMessage
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middleware.wrap_model_call(request, mock_handler)
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# Request should have processed without errors
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assert request.system_prompt == system_prompt
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assert isinstance(request.system_prompt, SystemMessage)
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def test_does_not_double_wrap_system_message() -> None:
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"""Test that middleware doesn't wrap SystemMessage in another SystemMessage."""
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tool_call_id = "call-1"
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ai_message = AIMessage(
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content="",
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tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
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)
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tool_message = ToolMessage(content="x" * 100, tool_call_id=tool_call_id)
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system_prompt = SystemMessage(content="Original system prompt")
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state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
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request.system_prompt = system_prompt
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middleware = ContextEditingMiddleware(
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edits=[ClearToolUsesEdit(trigger=50)],
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token_count_method="model",
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)
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def mock_handler(req: ModelRequest) -> AIMessage:
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return AIMessage(content="mock response")
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middleware.wrap_model_call(request, mock_handler)
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# System prompt should still be the same SystemMessage, not wrapped
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assert request.system_prompt == system_prompt
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assert isinstance(request.system_prompt, SystemMessage)
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assert request.system_prompt.content == "Original system prompt"
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async def test_handles_system_message_prompt_async() -> None:
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"""Test async version - middleware handles SystemMessage as system_prompt correctly."""
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tool_call_id = "call-1"
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ai_message = AIMessage(
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content="",
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tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
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)
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tool_message = ToolMessage(content="12345", tool_call_id=tool_call_id)
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system_prompt = SystemMessage(content="You are a helpful assistant.")
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state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
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# Manually set SystemMessage as system_prompt
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request.system_prompt = system_prompt
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middleware = ContextEditingMiddleware(
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edits=[ClearToolUsesEdit(trigger=50)],
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token_count_method="model",
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)
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async def mock_handler(req: ModelRequest) -> AIMessage:
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return AIMessage(content="mock response")
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# Call awrap_model_call - should not fail with SystemMessage
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await middleware.awrap_model_call(request, mock_handler)
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# Request should have processed without errors
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assert request.system_prompt == system_prompt
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assert isinstance(request.system_prompt, SystemMessage)
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async def test_does_not_double_wrap_system_message_async() -> None:
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"""Test async version - middleware doesn't wrap SystemMessage in another SystemMessage."""
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tool_call_id = "call-1"
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ai_message = AIMessage(
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content="",
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tool_calls=[{"id": tool_call_id, "name": "search", "args": {}}],
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)
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tool_message = ToolMessage(content="x" * 100, tool_call_id=tool_call_id)
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system_prompt = SystemMessage(content="Original system prompt")
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state, request = _make_state_and_request([ai_message, tool_message], system_prompt=None)
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request.system_prompt = system_prompt
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middleware = ContextEditingMiddleware(
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edits=[ClearToolUsesEdit(trigger=50)],
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token_count_method="model",
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)
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async def mock_handler(req: ModelRequest) -> AIMessage:
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return AIMessage(content="mock response")
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await middleware.awrap_model_call(request, mock_handler)
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# System prompt should still be the same SystemMessage, not wrapped
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assert request.system_prompt == system_prompt
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assert isinstance(request.system_prompt, SystemMessage)
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assert request.system_prompt.content == "Original system prompt"
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@@ -5,7 +5,7 @@ from __future__ import annotations
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from typing import cast
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from langchain_core.language_models.fake_chat_models import GenericFakeChatModel
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from langchain_core.messages import AIMessage
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from langchain_core.messages import AIMessage, SystemMessage
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from langchain.agents.middleware.todo import TodoListMiddleware
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from langchain.agents.middleware.types import ModelRequest, ModelResponse
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@@ -170,3 +170,131 @@ async def test_handler_called_with_modified_request_async() -> None:
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assert received_prompt["value"] is not None
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assert "Original" in received_prompt["value"]
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assert "write_todos" in received_prompt["value"]
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# ==============================================================================
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# SystemMessage Tests
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# ==============================================================================
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def test_appends_to_system_message_with_list_content() -> None:
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"""Test that middleware appends to SystemMessage with list content."""
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existing_prompt = SystemMessage(content=["You are helpful.", "Be concise."])
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middleware = TodoListMiddleware()
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model = GenericFakeChatModel(messages=iter([AIMessage(content="response")]))
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request = ModelRequest(
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model=model,
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system_prompt=existing_prompt,
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messages=[],
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tool_choice=None,
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tools=[],
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response_format=None,
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state=cast("AgentState", {}), # type: ignore[name-defined]
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runtime=_fake_runtime(),
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model_settings={},
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)
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def mock_handler(req: ModelRequest) -> ModelResponse:
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return ModelResponse(result=[AIMessage(content="response")])
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middleware.wrap_model_call(request, mock_handler)
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# System prompt should be a SystemMessage with combined content
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assert isinstance(request.system_prompt, SystemMessage)
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assert isinstance(request.system_prompt.content, list)
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assert len(request.system_prompt.content) == 3
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assert request.system_prompt.content[0] == "You are helpful."
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assert request.system_prompt.content[1] == "Be concise."
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assert "write_todos" in request.system_prompt.content[2]
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async def test_appends_to_system_message_with_string_content_async() -> None:
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"""Test async version - middleware appends to SystemMessage with string content."""
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existing_prompt = SystemMessage(content="You are a helpful assistant.")
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middleware = TodoListMiddleware()
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model = GenericFakeChatModel(messages=iter([AIMessage(content="response")]))
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request = ModelRequest(
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model=model,
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system_prompt=existing_prompt,
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messages=[],
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tool_choice=None,
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tools=[],
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response_format=None,
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state=cast("AgentState", {}), # type: ignore[name-defined]
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runtime=_fake_runtime(),
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model_settings={},
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)
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async def mock_handler(req: ModelRequest) -> ModelResponse:
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return ModelResponse(result=[AIMessage(content="response")])
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await middleware.awrap_model_call(request, mock_handler)
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# System prompt should be a SystemMessage with combined content
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assert isinstance(request.system_prompt, SystemMessage)
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assert isinstance(request.system_prompt.content, str)
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assert "You are a helpful assistant." in request.system_prompt.content
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assert middleware.system_prompt in request.system_prompt.content
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async def test_appends_to_system_message_with_list_content_async() -> None:
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"""Test async version - middleware appends to SystemMessage with list content."""
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existing_prompt = SystemMessage(content=["You are helpful.", "Be concise."])
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middleware = TodoListMiddleware()
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model = GenericFakeChatModel(messages=iter([AIMessage(content="response")]))
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request = ModelRequest(
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model=model,
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system_prompt=existing_prompt,
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messages=[],
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tool_choice=None,
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tools=[],
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response_format=None,
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state=cast("AgentState", {}), # type: ignore[name-defined]
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runtime=_fake_runtime(),
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model_settings={},
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)
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async def mock_handler(req: ModelRequest) -> ModelResponse:
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return ModelResponse(result=[AIMessage(content="response")])
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await middleware.awrap_model_call(request, mock_handler)
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# System prompt should be a SystemMessage with combined content
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assert isinstance(request.system_prompt, SystemMessage)
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assert isinstance(request.system_prompt.content, list)
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assert len(request.system_prompt.content) == 3
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assert request.system_prompt.content[0] == "You are helpful."
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assert request.system_prompt.content[1] == "Be concise."
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assert "write_todos" in request.system_prompt.content[2]
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||||
|
||||
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)
|
||||
|
||||
Reference in New Issue
Block a user