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Structured output parser

This output parser can be used when you want to return multiple fields. If you want complex schema returned (i.e. a JSON object with arrays of strings), use the Zod Schema detailed below.

tip

See this section for general instructions on installing integration packages.

npm install @langchain/openai
import { OpenAI } from "@langchain/openai";
import { RunnableSequence } from "@langchain/core/runnables";
import { StructuredOutputParser } from "langchain/output_parsers";
import { PromptTemplate } from "@langchain/core/prompts";

const parser = StructuredOutputParser.fromNamesAndDescriptions({
  answer: "answer to the user's question",
  source: "source used to answer the user's question, should be a website.",
});

const chain = RunnableSequence.from([
  PromptTemplate.fromTemplate(
    "Answer the users question as best as possible.\n{format_instructions}\n{question}"
  ),
  new OpenAI({ temperature: 0 }),
  parser,
]);

console.log(parser.getFormatInstructions());

/*
Answer the users question as best as possible.
You must format your output as a JSON value that adheres to a given "JSON Schema" instance.

"JSON Schema" is a declarative language that allows you to annotate and validate JSON documents.

For example, the example "JSON Schema" instance {{"properties": {{"foo": {{"description": "a list of test words", "type": "array", "items": {{"type": "string"}}}}}}, "required": ["foo"]}}}}
would match an object with one required property, "foo". The "type" property specifies "foo" must be an "array", and the "description" property semantically describes it as "a list of test words". The items within "foo" must be strings.
Thus, the object {{"foo": ["bar", "baz"]}} is a well-formatted instance of this example "JSON Schema". The object {{"properties": {{"foo": ["bar", "baz"]}}}} is not well-formatted.

Your output will be parsed and type-checked according to the provided schema instance, so make sure all fields in your output match the schema exactly and there are no trailing commas!

Here is the JSON Schema instance your output must adhere to. Include the enclosing markdown codeblock:
```
{"type":"object","properties":{"answer":{"type":"string","description":"answer to the user's question"},"sources":{"type":"array","items":{"type":"string"},"description":"sources used to answer the question, should be websites."}},"required":["answer","sources"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"}
```

What is the capital of France?
*/

const response = await chain.invoke({
  question: "What is the capital of France?",
  format_instructions: parser.getFormatInstructions(),
});

console.log(response);
// { answer: 'Paris', source: 'https://en.wikipedia.org/wiki/Paris' }

API Reference:

Structured Output Parser with Zod Schema​

This output parser can be also be used when you want to define the output schema using Zod, a TypeScript validation library. The Zod schema passed in needs be parseable from a JSON string, so eg. z.date() is not allowed.

import { z } from "zod";
import { OpenAI } from "@langchain/openai";
import { RunnableSequence } from "@langchain/core/runnables";
import { StructuredOutputParser } from "langchain/output_parsers";
import { PromptTemplate } from "@langchain/core/prompts";

// We can use zod to define a schema for the output using the `fromZodSchema` method of `StructuredOutputParser`.
const parser = StructuredOutputParser.fromZodSchema(
  z.object({
    answer: z.string().describe("answer to the user's question"),
    sources: z
      .array(z.string())
      .describe("sources used to answer the question, should be websites."),
  })
);

const chain = RunnableSequence.from([
  PromptTemplate.fromTemplate(
    "Answer the users question as best as possible.\n{format_instructions}\n{question}"
  ),
  new OpenAI({ temperature: 0 }),
  parser,
]);

console.log(parser.getFormatInstructions());

/*
Answer the users question as best as possible.
You must format your output as a JSON value that adheres to a given "JSON Schema" instance.

"JSON Schema" is a declarative language that allows you to annotate and validate JSON documents.

For example, the example "JSON Schema" instance {{"properties": {{"foo": {{"description": "a list of test words", "type": "array", "items": {{"type": "string"}}}}}}, "required": ["foo"]}}}}
would match an object with one required property, "foo". The "type" property specifies "foo" must be an "array", and the "description" property semantically describes it as "a list of test words". The items within "foo" must be strings.
Thus, the object {{"foo": ["bar", "baz"]}} is a well-formatted instance of this example "JSON Schema". The object {{"properties": {{"foo": ["bar", "baz"]}}}} is not well-formatted.

Your output will be parsed and type-checked according to the provided schema instance, so make sure all fields in your output match the schema exactly and there are no trailing commas!

Here is the JSON Schema instance your output must adhere to. Include the enclosing markdown codeblock:
```
{"type":"object","properties":{"answer":{"type":"string","description":"answer to the user's question"},"sources":{"type":"array","items":{"type":"string"},"description":"sources used to answer the question, should be websites."}},"required":["answer","sources"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"}
```

What is the capital of France?
*/

const response = await chain.invoke({
  question: "What is the capital of France?",
  format_instructions: parser.getFormatInstructions(),
});

console.log(response);
/*
{ answer: 'Paris', sources: [ 'https://en.wikipedia.org/wiki/Paris' ] }
*/

API Reference:

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