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]