human_in_the_loop.py — langchain Source File

Source Code

"""Human in the loop middleware."""

from typing import Any, Literal, Protocol

from langchain_core.messages import AIMessage, ToolCall, ToolMessage
from langgraph.runtime import Runtime
from langgraph.types import interrupt
from typing_extensions import NotRequired, TypedDict

from langchain.agents.middleware.types import (
    AgentMiddleware,
    AgentState,
    ContextT,
    ResponseT,
    StateT,
)


class Action(TypedDict):
    """Represents an action with a name and args."""

    name: str
    """The type or name of action being requested (e.g., `'add_numbers'`)."""

    args: dict[str, Any]
    """Key-value pairs of args needed for the action (e.g., `{"a": 1, "b": 2}`)."""


class ActionRequest(TypedDict):
    """Represents an action request with a name, args, and description."""

    name: str
    """The name of the action being requested."""

    args: dict[str, Any]
    """Key-value pairs of args needed for the action (e.g., `{"a": 1, "b": 2}`)."""

    description: NotRequired[str]
    """The description of the action to be reviewed."""


DecisionType = Literal["approve", "edit", "reject"]


class ReviewConfig(TypedDict):
    """Policy for reviewing a HITL request."""

    action_name: str
    """Name of the action associated with this review configuration."""

    allowed_decisions: list[DecisionType]
    """The decisions that are allowed for this request."""

    args_schema: NotRequired[dict[str, Any]]
    """JSON schema for the args associated with the action, if edits are allowed."""


class HITLRequest(TypedDict):
    """Request for human feedback on a sequence of actions requested by a model."""

// ... (328 more lines)