Langchain-Chatchat/server/chat/utils.py

import asyncio
from pydantic import BaseModel, Field
from langchain.prompts.chat import ChatMessagePromptTemplate
from configs import logger, log_verbose
from server.utils import get_model_worker_config, fschat_openai_api_address
from langchain.chat_models import ChatOpenAI
from typing import Awaitable, List, Tuple, Dict, Union, Callable


def get_ChatOpenAI(
    model_name: str,
    temperature: float,
    callbacks: List[Callable] = [],
) -> ChatOpenAI:
    config = get_model_worker_config(model_name)
    model = ChatOpenAI(
        streaming=True,
        verbose=True,
        callbacks=callbacks,
        openai_api_key=config.get("api_key", "EMPTY"),
        openai_api_base=fschat_openai_api_address(),
        model_name=model_name,
        temperature=temperature,
        openai_proxy=config.get("openai_proxy")
    )
    return model


async def wrap_done(fn: Awaitable, event: asyncio.Event):
    """Wrap an awaitable with a event to signal when it's done or an exception is raised."""
    try:
        await fn
    except Exception as e:
        # TODO: handle exception
        msg = f"Caught exception: {e}"
        logger.error(f'{e.__class__.__name__}: {msg}',
                     exc_info=e if log_verbose else None)
    finally:
        # Signal the aiter to stop.
        event.set()


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,
        )

    @classmethod
    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