LangChain调用ChatGLM

from langchain.llms.base import LLM
from zhipuai import ZhipuAI
from langchain_core.messages.ai import AIMessage


class ChatGLM4(LLM):
    history = []
    client:object = None
    
    def __init__(self):
        super().__init__()
        zhipuai_api_key = os.getenv('ZHUPU_API_KEY')
        self.client = ZhipuAI(api_key=zhipuai_api_key)
    
    @property
    def _llm_type(self):
        return "ChatGLM4"
    
    def invoke(self,prompt,config={},history=[]):
        if history is None:
            history=[]
        if not isinstance(prompt, str):
            prompt = prompt.to_string()
        history.append({"role":"user","content":prompt })
        response = self.client.chat.completions.create(
            model="glm-4",
            messages=history
        )

        result = response.choices[0].message.content
        return AIMessage(content=result)
        
    def _call(self,prompt,config,history=[]):
        return self.invoke(prompt,history)
        
    def stream(self,prompt,config,history=[]):
        if history is None:
            history=[]
        if not isinstance(prompt, str):
            prompt = prompt.to_string()
        history.append({"role":"user","content":prompt})
        response = self.client.chat.completions.create(
            model="glm-4",
            messages=history,
            stream=True
        )
        for chunk in response:
            yield chunk.choices[0].delta.content