【LangChain】使用LangChain的提示词模板：技巧与总结

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​​前言：

这里是关于LangChain框架中的提示词模板使用的技巧，希望可以帮助到大家，欢迎大家的补充和纠正

一、使用LangChain的提示词模板：技巧与总结

1、格式化示例集

我们可以使用使用FewShotPromptTemplate来格式化示例集

const examples = [
  {
    question: "Who lived longer, Muhammad Ali or Alan Turing?",
    answer: `
  Are follow up questions needed here: Yes.
  Follow up: How old was Muhammad Ali when he died?
  Intermediate answer: Muhammad Ali was 74 years old when he died.
  Follow up: How old was Alan Turing when he died?
  Intermediate answer: Alan Turing was 41 years old when he died.
  So the final answer is: Muhammad Ali
  `,
  },
  {
    question: "When was the founder of craigslist born?",
    answer: `
  Are follow up questions needed here: Yes.
  Follow up: Who was the founder of craigslist?
  Intermediate answer: Craigslist was founded by Craig Newmark.
  Follow up: When was Craig Newmark born?
  Intermediate answer: Craig Newmark was born on December 6, 1952.
  So the final answer is: December 6, 1952
  `,
  },
  {
    question: "Who was the maternal grandfather of George Washington?",
    answer: `
  Are follow up questions needed here: Yes.
  Follow up: Who was the mother of George Washington?
  Intermediate answer: The mother of George Washington was Mary Ball Washington.
  Follow up: Who was the father of Mary Ball Washington?
  Intermediate answer: The father of Mary Ball Washington was Joseph Ball.
  So the final answer is: Joseph Ball
  `,
  },
  {
    question:
      "Are both the directors of Jaws and Casino Royale from the same country?",
    answer: `
  Are follow up questions needed here: Yes.
  Follow up: Who is the director of Jaws?
  Intermediate Answer: The director of Jaws is Steven Spielberg.
  Follow up: Where is Steven Spielberg from?
  Intermediate Answer: The United States.
  Follow up: Who is the director of Casino Royale?
  Intermediate Answer: The director of Casino Royale is Martin Campbell.
  Follow up: Where is Martin Campbell from?
  Intermediate Answer: New Zealand.
  So the final answer is: No
  `,
  },
];

const examplePrompt = PromptTemplate.fromTemplate(
  "Question:{question} \n {answer}"
)

const prompt = new FewShotPromptTemplate({
  examples,
  examplePrompt,
  suffix: "Question:{input}",
  inputVariables: ["input"]
})

const formatted = await prompt.format({
  input: "Who was the father of Mary Ball Washington?"
})

console.log(formatted)

最后输出的示例中，会将examples中的示例加入到提示词模板的前面，组合成为完整的示例

//提示词模板输出结果
Question:Who lived longer, Muhammad Ali or Alan Turing? 
 
  Are follow up questions needed here: Yes.
  Follow up: How old was Muhammad Ali when he died?
  Intermediate answer: Muhammad Ali was 74 years old when he died.
  Follow up: How old was Alan Turing when he died?
  Intermediate answer: Alan Turing was 41 years old when he died.
  So the final answer is: Muhammad Ali
  

Question:When was the founder of craigslist born? 
 
  Are follow up questions needed here: Yes.
  Follow up: Who was the founder of craigslist?
  Intermediate answer: Craigslist was founded by Craig Newmark.
  Follow up: When was Craig Newmark born?
  Intermediate answer: Craig Newmark was born on December 6, 1952.
  So the final answer is: December 6, 1952
  

Question:Who was the maternal grandfather of George Washington? 
 
  Are follow up questions needed here: Yes.
  Follow up: Who was the mother of George Washington?
  Intermediate answer: The mother of George Washington was Mary Ball Washington.
  Follow up: Who was the father of Mary Ball Washington?
  Intermediate answer: The father of Mary Ball Washington was Joseph Ball.
  So the final answer is: Joseph Ball
  

Question:Are both the directors of Jaws and Casino Royale from the same country? 
 
  Are follow up questions needed here: Yes.
  Follow up: Who is the director of Jaws?
  Intermediate Answer: The director of Jaws is Steven Spielberg.
  Follow up: Where is Steven Spielberg from?
  Intermediate Answer: The United States.
  Follow up: Who is the director of Casino Royale?
  Intermediate Answer: The director of Casino Royale is Martin Campbell.
  Follow up: Where is Martin Campbell from?
  Intermediate Answer: New Zealand.
  So the final answer is: No
  

Question:Who was the father of Mary Ball Washington?

2、示例选择器来组合提示词模板

我们可以使用 SemanticSimilarityExampleSelector类来使用嵌入模型来计算输入样本和少数样本之间的相似性，并使用向量存储来执行最近邻搜索

let AzureOpenAIEmbedding = await getAzureEmbeddings()

const exampleSelecttor = await SemanticSimilarityExampleSelector.fromExamples(
  examples,
  AzureOpenAIEmbedding,
  MemoryVectorStore,
  {
    k: 1
  }
)
const question = "Who was the father of Mary Ball Washington?"
const selectedExamples = await exampleSelecttor.selectExamples({ question })
console.log(" ~ mainScript2 ~ selectedExamples:", selectedExamples)、

/**
 ~ mainScript2 ~ selectedExamples: [
  {
    question: 'Who was the maternal grandfather of George Washington?',
    answer: '\n' +
      '  Are follow up questions needed here: Yes.\n' +
      '  Follow up: Who was the mother of George Washington?\n' +
      '  Intermediate answer: The mother of George Washington was Mary Ball Washington.\n' +
      '  Follow up: Who was the father of Mary Ball Washington?\n' +
      '  Intermediate answer: The father of Mary Ball Washington was Joseph Ball.\n' +
      '  So the final answer is: Joseph Ball\n' +
      '  '
  }
]
**/

当调用exampleSelecttor中的selectExamples方法的时候，它会根据输入的question来使用向量搜索从示例集中找出与输入的问题最相似的示例集

3、在聊天模型中使用合适的少数示例

在提示词结构中有一个重要的概念是示例，给大模型的输入中提供示例会让输出结果更加精准，而示例选择器可以实现一个效果：根据用户的输入选择合适的示例

在langchian中是可以实现这个功能的，使用SemanticSimilarityExampleSelector示例选择器，根据用户的输入使用向量数据库匹配更加合适的例子

实现步骤：

• 先准备一些示例数据-最好是数组形式的
• 然后再实例化向量大模型
• 创建好向量数据库
• 使用模型选择器

完整的代码如下：

  //1、先准备一个例子，这个例子是数组对象类型的，对象需要拥有input哥output
  const examples = [
    { input: "2+2", output: "4" },
    { input: "2+3", output: "5" },
    { input: "2+4", output: "6" },
    { input: "What did the cow say to the moon?", output: "nothing at all" },
    {
      input: "Write me a poem about the moon",
      output:
        "One for the moon, and one for me, who are we to talk about the moon?",
    },
  ];

  //2、从例子中格式化数据，准备好插入到向量数据库中
  const toVectorize=examples.map(
    (examples)=>`${examples.input}${examples.output}`
  )

  //3、实例化向量数据库的查询
  const vectorStore=await MemoryVectorStore.fromTexts(
    toVectorize,
    examples,
    await getAzureEmbeddings()
  )

  //4、创建一个选择器
  const exampleSelect=new SemanticSimilarityExampleSelector({
    vectorStore,
    k:1
  })

  //5、使用
  const result=await exampleSelect.selectExamples({input:"hourse"})
  // console.log(" ~ mainScript4 ~ result:", result)

  //6、和动态模版添加方法组合
  const messsageTemplate=ChatPromptTemplate.fromMessages([
    ["user","{input}"],
    ["ai","{output}"]
  ])
  const fewPrompt=new FewShotChatMessagePromptTemplate({
    examplePrompt:messsageTemplate,
    // examples:result,
    exampleSelector:exampleSelect,
    inputVariables:['input']
  })

  //  //原文档有bug，这里是修复的，不可以直接传入fewShotPrompt，而是需要实例化一下，封装成为消息类型
  const finalPrompt=ChatPromptTemplate.fromMessages([
    ["system","You are a wondrous wizard of math."],
    ChatPromptTemplate.fromMessages((await fewPrompt.invoke({})).toChatMessages()),
    ["user","{input}"],
  ])

  //7、模型结合使用
  const azureModel=await getAzureModel()
  const chain = finalPrompt.pipe(azureModel);

  console.log(await chain.invoke({ input: "What's 3+3?" }))

4、如何部分格式化提示词模板

想要对提示模板进行部分分配的一个常见用例是，如果您在其他变量之前访问提示中的某些变量。例如，假设您有一个需要两个变量（foo 和 baz）的提示模板。如果你在链的早期获得 foo 值，但后来获得 baz 值，那么在链中完全传递这两个变量可能会很不方便。相反，你可以用 foo 值对 prompt 模板进行部分化处理，然后传递部分 prompt 模板并使用它

// 第一种使用，在partial方法中进行实例化
const prompt = new PromptTemplate({
    template: "{foo}{bar}",
    inputVariables: ["foo", "bar"]
})

const partialPrompt = await prompt.partial({
    foo: "foo"
})

const fromattedPrompt = await partialPrompt.format({
    bar: "baz"
})

console.log(fromattedPrompt)

// 第二种使用，在模板初始化中进行实例化
const prompt = new PromptTemplate({
  template: "{foo}{bar}",
  inputVariables: ["bar"],
  partialVariables: {
      foo: "foo"
  }
})

const formattedPrompt = await prompt.format({
  bar: "baz",
})
// console.log(" ~ mainScript2 ~ formattedPrompt:", formattedPrompt)