ToolMessage Class — langchain Architecture

Source Code

libs/core/langchain_core/messages/tool.py lines 26–171

class ToolMessage(BaseMessage, ToolOutputMixin):
    """Message for passing the result of executing a tool back to a model.

    `ToolMessage` objects contain the result of a tool invocation. Typically, the result
    is encoded inside the `content` field.

    `tool_call_id` is used to associate the tool call request with the tool call
    response. Useful in situations where a chat model is able to request multiple tool
    calls in parallel.

    Example:
        A `ToolMessage` representing a result of `42` from a tool call with id

        ```python
        from langchain_core.messages import ToolMessage

        ToolMessage(content="42", tool_call_id="call_Jja7J89XsjrOLA5r!MEOW!SL")
        ```

    Example:
        A `ToolMessage` where only part of the tool output is sent to the model
        and the full output is passed in to artifact.

        ```python
        from langchain_core.messages import ToolMessage

        tool_output = {
            "stdout": "From the graph we can see that the correlation between "
            "x and y is ...",
            "stderr": None,
            "artifacts": {"type": "image", "base64_data": "/9j/4gIcSU..."},
        }

        ToolMessage(
            content=tool_output["stdout"],
            artifact=tool_output,
            tool_call_id="call_Jja7J89XsjrOLA5r!MEOW!SL",
        )
        ```
    """

    tool_call_id: str
    """Tool call that this message is responding to."""

    type: Literal["tool"] = "tool"
    """The type of the message (used for serialization)."""

    artifact: Any = None
    """Artifact of the Tool execution which is not meant to be sent to the model.

    Should only be specified if it is different from the message content, e.g. if only
    a subset of the full tool output is being passed as message content but the full
    output is needed in other parts of the code.

    """

    status: Literal["success", "error"] = "success"
    """Status of the tool invocation."""

    additional_kwargs: dict = Field(default_factory=dict, repr=False)
    """Currently inherited from `BaseMessage`, but not used."""
    response_metadata: dict = Field(default_factory=dict, repr=False)
    """Currently inherited from `BaseMessage`, but not used."""

    @model_validator(mode="before")
    @classmethod
    def coerce_args(cls, values: dict) -> dict:
        """Coerce the model arguments to the correct types.

        Args:
            values: The model arguments.

        """
        content = values["content"]
        if isinstance(content, tuple):
            content = list(content)

        if not isinstance(content, (str, list)):
            try:
                values["content"] = str(content)
            except ValueError as e: