tx_flow_analysis/llmops/agents/datadev/llm.py

from langchain_openai import ChatOpenAI
from config import llm_config

# 数据开发全局大模型
global_llm: ChatOpenAI = None


# 初使化模型
def init_llm() -> ChatOpenAI:
    # 读取配置文件，获取大模型的配置信息
    c = llm_config

    global global_llm
    if global_llm is None:
        """
        根据配置，创建大模型实例
        """
        global_llm = ChatOpenAI(
            model = c["model"],
            base_url = c["base_url"],
            api_key = c["api_key"],
            temperature= c["temperature"],
            streaming=True
        )
    return global_llm

# 获取大模型
def get_llm() -> ChatOpenAI:
    if global_llm is None:
        init_llm()
        # raise ValueError("请先调用 initllm(config）方法初始化llm模型")
    return global_llm


# 获取大模型
def get_llm_coder() -> ChatOpenAI:
    c = llm_config
    return ChatOpenAI(
        model=c["coder_model"],
        base_url=c["base_url"],
        api_key=c["api_key"],
        temperature=c["temperature"],
        streaming=True
    )

if __name__ == '__main__':
    llm = get_llm()
    print(f"llm:", llm)
    # llm = get_llm_coder()
    # response = llm.invoke("你好")
    # print(response)

    question = "你好"
    response = llm.invoke(question)
    print(response)