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Parent Document Retriever

When splitting documents for retrieval, there are often conflicting desires:

  1. You may want to have small documents, so that their embeddings can most accurately reflect their meaning. If too long, then the embeddings can lose meaning.
  2. You want to have long enough documents that the context of each chunk is retained.

The ParentDocumentRetriever strikes that balance by splitting and storing small chunks of data. During retrieval, it first fetches the small chunks but then looks up the parent ids for those chunks and returns those larger documents.

Note that "parent document" refers to the document that a small chunk originated from. This can either be the whole raw document OR a larger chunk.

Usage​

import { OpenAIEmbeddings } from "langchain/embeddings/openai";
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { InMemoryStore } from "langchain/storage/in_memory";
import { ParentDocumentRetriever } from "langchain/retrievers/parent_document";
import { RecursiveCharacterTextSplitter } from "langchain/text_splitter";
import { TextLoader } from "langchain/document_loaders/fs/text";

const vectorstore = new MemoryVectorStore(new OpenAIEmbeddings());
const docstore = new InMemoryStore();
const retriever = new ParentDocumentRetriever({
  vectorstore,
  docstore,
  // Optional, not required if you're already passing in split documents
  parentSplitter: new RecursiveCharacterTextSplitter({
    chunkOverlap: 0,
    chunkSize: 500,
  }),
  childSplitter: new RecursiveCharacterTextSplitter({
    chunkOverlap: 0,
    chunkSize: 50,
  }),
  // Optional `k` parameter to search for more child documents in VectorStore.
  // Note that this does not exactly correspond to the number of final (parent) documents
  // retrieved, as multiple child documents can point to the same parent.
  childK: 20,
  // Optional `k` parameter to limit number of final, parent documents returned from this
  // retriever and sent to LLM. This is an upper-bound, and the final count may be lower than this.
  parentK: 5,
});
const textLoader = new TextLoader("../examples/state_of_the_union.txt");
const parentDocuments = await textLoader.load();

// We must add the parent documents via the retriever's addDocuments method
await retriever.addDocuments(parentDocuments);

const retrievedDocs = await retriever.getRelevantDocuments("justice breyer");

// Retrieved chunks are the larger parent chunks
console.log(retrievedDocs);
/*
  [
    Document {
      pageContent: 'Tonight, I call on the Senate to pass — pass the Freedom to Vote Act. Pass the John Lewis Act — Voting Rights Act. And while you’re at it, pass the DISCLOSE Act so Americans know who is funding our elections.\n' +
        '\n' +
        'Look, tonight, I’d — I’d like to honor someone who has dedicated his life to serve this country: Justice Breyer — an Army veteran, Constitutional scholar, retiring Justice of the United States Supreme Court.',
      metadata: { source: '../examples/state_of_the_union.txt', loc: [Object] }
    },
    Document {
      pageContent: 'As I did four days ago, I’ve nominated a Circuit Court of Appeals — Ketanji Brown Jackson. One of our nation’s top legal minds who will continue in just Brey- — Justice Breyer’s legacy of excellence. A former top litigator in private practice, a former federal public defender from a family of public-school educators and police officers — she’s a consensus builder.',
      metadata: { source: '../examples/state_of_the_union.txt', loc: [Object] }
    },
    Document {
      pageContent: 'Justice Breyer, thank you for your service. Thank you, thank you, thank you. I mean it. Get up. Stand — let me see you. Thank you.\n' +
        '\n' +
        'And we all know — no matter what your ideology, we all know one of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court.',
      metadata: { source: '../examples/state_of_the_union.txt', loc: [Object] }
    }
  ]
*/

API Reference:

With Score Threshold​

By setting the options in scoreThresholdOptions we can force the ParentDocumentRetriever to use the ScoreThresholdRetriever under the hood. This sets the vector store inside ScoreThresholdRetriever as the one we passed when initializing ParentDocumentRetriever, while also allowing us to also set a score threshold for the retriever.

This can be helpful when you're not sure how many documents you want (or if you are sure, just set the maxK option), but you want to make sure that the documents you do get are within a certain relevancy threshold.

Note: if a retriever is passed, ParentDocumentRetriever will default to use it for retrieving small chunks, as well as adding documents via the addDocuments method.

import { OpenAIEmbeddings } from "langchain/embeddings/openai";
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { InMemoryStore } from "langchain/storage/in_memory";
import { ParentDocumentRetriever } from "langchain/retrievers/parent_document";
import { RecursiveCharacterTextSplitter } from "langchain/text_splitter";
import { TextLoader } from "langchain/document_loaders/fs/text";
import { ScoreThresholdRetriever } from "langchain/retrievers/score_threshold";

const vectorstore = new MemoryVectorStore(new OpenAIEmbeddings());
const docstore = new InMemoryStore();
const childDocumentRetriever = ScoreThresholdRetriever.fromVectorStore(
  vectorstore,
  {
    minSimilarityScore: 0.01, // Essentially no threshold
    maxK: 1, // Only return the top result
  }
);
const retriever = new ParentDocumentRetriever({
  vectorstore,
  docstore,
  childDocumentRetriever,
  // Optional, not required if you're already passing in split documents
  parentSplitter: new RecursiveCharacterTextSplitter({
    chunkOverlap: 0,
    chunkSize: 500,
  }),
  childSplitter: new RecursiveCharacterTextSplitter({
    chunkOverlap: 0,
    chunkSize: 50,
  }),
});
const textLoader = new TextLoader("../examples/state_of_the_union.txt");
const parentDocuments = await textLoader.load();

// We must add the parent documents via the retriever's addDocuments method
await retriever.addDocuments(parentDocuments);

const retrievedDocs = await retriever.getRelevantDocuments("justice breyer");

// Retrieved chunk is the larger parent chunk
console.log(retrievedDocs);
/*
  [
    Document {
      pageContent: 'Tonight, I call on the Senate to pass — pass the Freedom to Vote Act. Pass the John Lewis Act — Voting Rights Act. And while you’re at it, pass the DISCLOSE Act so Americans know who is funding our elections.\n' +
        '\n' +
        'Look, tonight, I’d — I’d like to honor someone who has dedicated his life to serve this country: Justice Breyer — an Army veteran, Constitutional scholar, retiring Justice of the United States Supreme Court.',
      metadata: { source: '../examples/state_of_the_union.txt', loc: [Object] }
    },
  ]
*/

API Reference: