30 lines
1.2 KiB
Python
30 lines
1.2 KiB
Python
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from langchain_openai import ChatOpenAI
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from loguru import logger
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from DrGraph.utils.Constant import Constant
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from LLM.llm_model_base import LLM_Model_Base
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class Chat_LLM(LLM_Model_Base):
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def __init__(self, model_name: str = "gpt-4o-mini", temperature: float = 0.7):
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super().__init__(model_name, temperature)
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self.name = '聊天模型'
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self.mode = Constant.LLM_MODE_CHAT
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self.llmModel = ChatOpenAI(
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model_name=self.model_name,
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temperature=self.temperature,
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)
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# 返回消息格式，以便在chatbot中显示
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def invoke(self, prompt: str):
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prompt_template_value = self.buildPromptTemplateValue(
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prompt=prompt,
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methodType=Constant.LLM_PROMPT_TEMPLATE_METHOD_INVOKE,
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valueType=Constant.LLM_PROMPT_VALUE_MESSAGES)
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try:
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response = self.llmModel.invoke(prompt_template_value)
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logger.info(f"{self.name} >>> 2. 助手回复: {type(response)}\n{response}")
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# response = {"role": "assistant", "content": response.content}
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except Exception as e:
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logger.error(e)
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return response
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