chat_document

langroid/agent/chat_document.py

StatusCode

Bases: str, Enum

Codes meant to be returned by task.run(). Some are not used yet.

ChatDocument

Bases: Document

get_json_tools()

Get names of attempted JSON tool usages in the content of the message. Returns: List[str]: list of JSON tool names

Source code in langroid/agent/chat_document.py

def get_json_tools(self) -> List[str]:
    """
    Get names of attempted JSON tool usages in the content
        of the message.
    Returns:
        List[str]: list of JSON tool names
    """
    jsons = extract_top_level_json(self.content)
    tools = []
    for j in jsons:
        json_data = json.loads(j)
        tool = json_data.get("request")
        if tool is not None:
            tools.append(str(tool))
    return tools

log_fields()

Fields for logging in csv/tsv logger Returns: List[str]: list of fields

Source code in langroid/agent/chat_document.py

def log_fields(self) -> ChatDocLoggerFields:
    """
    Fields for logging in csv/tsv logger
    Returns:
        List[str]: list of fields
    """
    tool_type = ""  # FUNC or TOOL
    tool = ""  # tool name or function name
    if self.function_call is not None:
        tool_type = "FUNC"
        tool = self.function_call.name
    elif self.get_json_tools() != []:
        tool_type = "TOOL"
        tool = self.get_json_tools()[0]
    recipient = self.metadata.recipient
    content = self.content
    sender_entity = self.metadata.sender
    sender_name = self.metadata.sender_name
    if tool_type == "FUNC":
        content += str(self.function_call)
    return ChatDocLoggerFields(
        sender_entity=sender_entity,
        sender_name=sender_name,
        recipient=recipient,
        block=self.metadata.block,
        tool_type=tool_type,
        tool=tool,
        content=content,
    )

pop_tool_ids()

Pop the last tool_id from the stack of tool_ids.

Source code in langroid/agent/chat_document.py

def pop_tool_ids(self) -> None:
    """
    Pop the last tool_id from the stack of tool_ids.
    """
    if len(self.metadata.tool_ids) > 0:
        self.metadata.tool_ids.pop()

from_LLMResponse(response, displayed=False) staticmethod

Convert LLMResponse to ChatDocument. Args: response (LLMResponse): LLMResponse to convert. displayed (bool): Whether this response was displayed to the user. Returns: ChatDocument: ChatDocument representation of this LLMResponse.

Source code in langroid/agent/chat_document.py

@staticmethod
def from_LLMResponse(
    response: LLMResponse,
    displayed: bool = False,
) -> "ChatDocument":
    """
    Convert LLMResponse to ChatDocument.
    Args:
        response (LLMResponse): LLMResponse to convert.
        displayed (bool): Whether this response was displayed to the user.
    Returns:
        ChatDocument: ChatDocument representation of this LLMResponse.
    """
    recipient, message = response.get_recipient_and_message()
    message = message.strip()
    if message in ["''", '""']:
        message = ""
    return ChatDocument(
        content=message,
        function_call=response.function_call,
        metadata=ChatDocMetaData(
            source=Entity.LLM,
            sender=Entity.LLM,
            usage=response.usage,
            displayed=displayed,
            cached=response.cached,
            recipient=recipient,
        ),
    )

to_LLMMessage(message) staticmethod

Convert to LLMMessage for use with LLM.

Parameters:

Name	Type	Description	Default
message	str | ChatDocument	Message to convert.	required

Returns: LLMMessage: LLMMessage representation of this str or ChatDocument.

Source code in langroid/agent/chat_document.py

@staticmethod
def to_LLMMessage(message: Union[str, "ChatDocument"]) -> LLMMessage:
    """
    Convert to LLMMessage for use with LLM.

    Args:
        message (str|ChatDocument): Message to convert.
    Returns:
        LLMMessage: LLMMessage representation of this str or ChatDocument.

    """
    sender_name = None
    sender_role = Role.USER
    fun_call = None
    tool_id = ""
    if isinstance(message, ChatDocument):
        content = message.content
        fun_call = message.function_call
        if message.metadata.sender == Entity.USER and fun_call is not None:
            # This may happen when a (parent agent's) LLM generates a
            # a Function-call, and it ends up being sent to the current task's
            # LLM (possibly because the function-call is mis-named or has other
            # issues and couldn't be handled by handler methods).
            # But a function-call can only be generated by an entity with
            # Role.ASSISTANT, so we instead put the content of the function-call
            # in the content of the message.
            content += " " + str(fun_call)
            fun_call = None
        sender_name = message.metadata.sender_name
        tool_ids = message.metadata.tool_ids
        tool_id = tool_ids[-1] if len(tool_ids) > 0 else ""
        if message.metadata.sender == Entity.SYSTEM:
            sender_role = Role.SYSTEM
        if (
            message.metadata.parent is not None
            and message.metadata.parent.function_call is not None
        ):
            sender_role = Role.FUNCTION
            sender_name = message.metadata.parent.function_call.name
        elif message.metadata.sender == Entity.LLM:
            sender_role = Role.ASSISTANT
    else:
        # LLM can only respond to text content, so extract it
        content = message

    return LLMMessage(
        role=sender_role,
        tool_id=tool_id,
        content=content,
        function_call=fun_call,
        name=sender_name,
    )