Source code for langchain_core.messages.base

from __future__ import annotations

from typing import TYPE_CHECKING, Any, Dict, List, Sequence, Union

from langchain_core.load.serializable import Serializable
from langchain_core.pydantic_v1 import Extra, Field

if TYPE_CHECKING:
    from langchain_core.prompts.chat import ChatPromptTemplate


[docs]class BaseMessage(Serializable): """The base abstract Message class. Messages are the inputs and outputs of ChatModels. """ content: Union[str, List[Union[str, Dict]]] """The string contents of the message.""" additional_kwargs: dict = Field(default_factory=dict) """Any additional information.""" type: str class Config: extra = Extra.allow
[docs] @classmethod def is_lc_serializable(cls) -> bool: """Return whether this class is serializable.""" return True
[docs] @classmethod def get_lc_namespace(cls) -> List[str]: """Get the namespace of the langchain object.""" return ["langchain", "schema", "messages"]
def __add__(self, other: Any) -> ChatPromptTemplate: from langchain_core.prompts.chat import ChatPromptTemplate prompt = ChatPromptTemplate(messages=[self]) return prompt + other
[docs]def merge_content( first_content: Union[str, List[Union[str, Dict]]], second_content: Union[str, List[Union[str, Dict]]], ) -> Union[str, List[Union[str, Dict]]]: # If first chunk is a string if isinstance(first_content, str): # If the second chunk is also a string, then merge them naively if isinstance(second_content, str): return first_content + second_content # If the second chunk is a list, add the first chunk to the start of the list else: return_list: List[Union[str, Dict]] = [first_content] return return_list + second_content # If both are lists, merge them naively elif isinstance(second_content, List): return first_content + second_content # If the first content is a list, and the second content is a string else: # If the last element of the first content is a string # Add the second content to the last element if isinstance(first_content[-1], str): return first_content[:-1] + [first_content[-1] + second_content] else: # Otherwise, add the second content as a new element of the list return first_content + [second_content]
[docs]class BaseMessageChunk(BaseMessage): """A Message chunk, which can be concatenated with other Message chunks."""
[docs] @classmethod def get_lc_namespace(cls) -> List[str]: """Get the namespace of the langchain object.""" return ["langchain", "schema", "messages"]
def _merge_kwargs_dict( self, left: Dict[str, Any], right: Dict[str, Any] ) -> Dict[str, Any]: """Merge additional_kwargs from another BaseMessageChunk into this one, handling specific scenarios where a key exists in both dictionaries but has a value of None in 'left'. In such cases, the method uses the value from 'right' for that key in the merged dictionary. Example: If left = {"function_call": {"arguments": None}} and right = {"function_call": {"arguments": "{\n"}} then, after merging, for the key "function_call", the value from 'right' is used, resulting in merged = {"function_call": {"arguments": "{\n"}}. """ merged = left.copy() for k, v in right.items(): if k not in merged: merged[k] = v elif merged[k] is None and v: merged[k] = v elif type(merged[k]) != type(v): raise ValueError( f'additional_kwargs["{k}"] already exists in this message,' " but with a different type." ) elif isinstance(merged[k], str): merged[k] += v elif isinstance(merged[k], dict): merged[k] = self._merge_kwargs_dict(merged[k], v) else: raise ValueError( f"Additional kwargs key {k} already exists in this message." ) return merged def __add__(self, other: Any) -> BaseMessageChunk: # type: ignore if isinstance(other, BaseMessageChunk): # If both are (subclasses of) BaseMessageChunk, # concat into a single BaseMessageChunk return self.__class__( content=merge_content(self.content, other.content), additional_kwargs=self._merge_kwargs_dict( self.additional_kwargs, other.additional_kwargs ), ) else: raise TypeError( 'unsupported operand type(s) for +: "' f"{self.__class__.__name__}" f'" and "{other.__class__.__name__}"' )
[docs]def message_to_dict(message: BaseMessage) -> dict: return {"type": message.type, "data": message.dict()}
[docs]def messages_to_dict(messages: Sequence[BaseMessage]) -> List[dict]: """Convert a sequence of Messages to a list of dictionaries. Args: messages: Sequence of messages (as BaseMessages) to convert. Returns: List of messages as dicts. """ return [message_to_dict(m) for m in messages]