LangChain入门(七)-结构化输出

待我称王封你为后i 2024-03-22 12:06 43阅读 0赞

有时候我们希望输出的内容不是文本，而是像 json 那样结构化的数据。

示例：

import os
    
    from langchain.output_parsers import StructuredOutputParser, ResponseSchema
    from langchain.prompts import PromptTemplate
    from langchain.llms import OpenAI
    
    os.environ["OPENAI_API_KEY"] = '***************'
    
    llm = OpenAI(model_name="text-davinci-003")
    
    # 告诉他我们生成的内容需要哪些字段，每个字段类型式啥
    response_schemas = [
        ResponseSchema(name="bad_string", description="This a poorly formatted user input string"),
        ResponseSchema(name="good_string", description="This is your response, a reformatted response")
    ]
    
    # 初始化解析器
    output_parser = StructuredOutputParser.from_response_schemas(response_schemas)
    
    # 生成的格式提示符
    # {
    #	"bad_string": string  // This a poorly formatted user input string
    #	"good_string": string  // This is your response, a reformatted response
    # }
    format_instructions = output_parser.get_format_instructions()
    
    template = """
    You will be given a poorly formatted string from a user.
    Reformat it and make sure all the words are spelled correctly
    
    {format_instructions}
    
    % USER INPUT:
    {user_input}
    
    YOUR RESPONSE:
    """
    
    # 讲我们的格式描述嵌入到 prompt 中去，告诉 llm 我们需要他输出什么样格式的内容
    prompt = PromptTemplate(
        input_variables=["user_input"],
        partial_variables={"format_instructions": format_instructions},
        template=template
    )
    
    promptValue = prompt.format(user_input="welcom to califonya!")
    llm_output = llm(promptValue)
    
    # 使用解析器进行解析生成的内容
    parse = output_parser.parse(llm_output)
    print(parse)