from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Union
from langchain_core.load.serializable import Serializable
from langchain_core.pydantic_v1 import Extra, Field
from langchain_core.utils import get_bolded_text
from langchain_core.utils._merge import merge_dicts
from langchain_core.utils.interactive_env import is_interactive_env
if TYPE_CHECKING:
from langchain_core.prompts.chat import ChatPromptTemplate
[docs]class BaseMessage(Serializable):
"""基础抽象消息类。
消息是ChatModels的输入和输出。
"""
content: Union[str, List[Union[str, Dict]]]
"""消息的字符串内容。"""
additional_kwargs: dict = Field(default_factory=dict)
"""为与消息相关的附加有效负载数据保留。
例如，对于来自人工智能的消息，这可能包括工具调用。"""
response_metadata: dict = Field(default_factory=dict)
"""响应元数据。例如：响应头、日志概率、令牌计数。"""
type: str
name: Optional[str] = None
id: Optional[str] = None
"""消息的可选唯一标识符。最好由创建消息的提供程序/模型提供。"""
class Config:
extra = Extra.allow
def __init__(
self, content: Union[str, List[Union[str, Dict]]], **kwargs: Any
) -> None:
"""将内容作为位置参数传递。"""
return super().__init__(content=content, **kwargs)
[docs] @classmethod
def is_lc_serializable(cls) -> bool:
"""返回此类是否可序列化。"""
return True
[docs] @classmethod
def get_lc_namespace(cls) -> List[str]:
"""获取langchain对象的命名空间。"""
return ["langchain", "schema", "messages"]
def __add__(self, other: Any) -> ChatPromptTemplate:
from langchain_core.prompts.chat import ChatPromptTemplate
prompt = ChatPromptTemplate(messages=[self]) # type: ignore[call-arg]
return prompt + other
[docs] def pretty_repr(self, html: bool = False) -> str:
title = get_msg_title_repr(self.type.title() + " Message", bold=html)
# TODO: handle non-string content.
if self.name is not None:
title += f"\nName: {self.name}"
return f"{title}\n\n{self.content}"
[docs] def pretty_print(self) -> None:
print(self.pretty_repr(html=is_interactive_env())) # noqa: T201
[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]]]:
"""合并两个消息内容。
参数：
first_content：第一个内容。
second_content：第二个内容。
返回：
合并后的内容。
"""
# 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):
"""消息块，可以与其他消息块连接。"""
[docs] @classmethod
def get_lc_namespace(cls) -> List[str]:
"""获取langchain对象的命名空间。"""
return ["langchain", "schema", "messages"]
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__( # type: ignore[call-arg]
id=self.id,
content=merge_content(self.content, other.content),
additional_kwargs=merge_dicts(
self.additional_kwargs, other.additional_kwargs
),
response_metadata=merge_dicts(
self.response_metadata, other.response_metadata
),
)
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:
"""将消息转换为字典。
参数：
message：要转换的消息。
返回：
作为字典的消息。
"""
return {"type": message.type, "data": message.dict()}
[docs]def messages_to_dict(messages: Sequence[BaseMessage]) -> List[dict]:
"""将消息序列转换为字典列表。
参数：
messages：要转换的消息序列（作为BaseMessages）。
返回：
作为字典的消息列表。
"""
return [message_to_dict(m) for m in messages]
[docs]def get_msg_title_repr(title: str, *, bold: bool = False) -> str:
"""获取消息的标题表示。
参数：
title: 标题。
bold: 是否加粗标题。
返回：
标题表示。
"""
padded = " " + title + " "
sep_len = (80 - len(padded)) // 2
sep = "=" * sep_len
second_sep = sep + "=" if len(padded) % 2 else sep
if bold:
padded = get_bolded_text(padded)
return f"{sep}{padded}{second_sep}"