from langchain.schema.runnable import RunnablePassthrough from langchain.prompts import ChatPromptTemplate from langchain.chat_models import ChatOpenAI from langchain_core.output_parsers import StrOutputParser class chatgpt(object): def __init__(self, api_key, max_new_tokens=5): OpenAIChatModel = ChatOpenAI( temperature=0, max_tokens=max_new_tokens, openai_api_key=api_key, model_name="gpt-3.5-turbo-1106" ) self.api_key = api_key self.max_new_tokens = max_new_tokens self._init_chain(OpenAIChatModel) def _init_chain(self, chat_model): common_prompt = ChatPromptTemplate.from_messages( [ "{question}" ] ) self.common_chain = ( {"question": RunnablePassthrough()} | common_prompt | chat_model | StrOutputParser() ) def generate(self, code: str, max_new_tokens: int): if max_new_tokens is not None and max_new_tokens!=self.max_new_tokens: OpenAIChatModel = ChatOpenAI( temperature=0, max_tokens=max_new_tokens, openai_api_key=self.api_key, model_name="gpt-3.5-turbo-1106" ) self.max_new_tokens = max_new_tokens self._init_chain(OpenAIChatModel) return self.common_chain.invoke(code) if __name__=='__main__': model = chatgpt() print(model.generate("Yesterday was Thursday, today is Friday, so tomorrow is ", 5)) print(model.generate("Yesterday was 2022-01-01, today is 2022-01-02, so tomorrow is ", 20))