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| from pydantic import BaseModel, Field | |
| from langchain.prompts.chat import ChatMessagePromptTemplate | |
| from configs import logger, log_verbose | |
| from typing import List, Tuple, Dict, Union | |
| class History(BaseModel): | |
| """ | |
| 对话历史 | |
| 可从dict生成，如 | |
| h = History(**{"role":"user","content":"你好"}) | |
| 也可转换为tuple，如 | |
| h.to_msy_tuple = ("human", "你好") | |
| """ | |
| role: str = Field(...) | |
| content: str = Field(...) | |
| def to_msg_tuple(self): | |
| return "ai" if self.role=="assistant" else "human", self.content | |
| def to_msg_template(self, is_raw=True) -> ChatMessagePromptTemplate: | |
| role_maps = { | |
| "ai": "assistant", | |
| "human": "user", | |
| } | |
| role = role_maps.get(self.role, self.role) | |
| if is_raw: # 当前默认历史消息都是没有input_variable的文本。 | |
| content = "{% raw %}" + self.content + "{% endraw %}" | |
| else: | |
| content = self.content | |
| return ChatMessagePromptTemplate.from_template( | |
| content, | |
| "jinja2", | |
| role=role, | |
| ) | |
| def from_data(cls, h: Union[List, Tuple, Dict]) -> "History": | |
| if isinstance(h, (list,tuple)) and len(h) >= 2: | |
| h = cls(role=h[0], content=h[1]) | |
| elif isinstance(h, dict): | |
| h = cls(**h) | |
| return h | |