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tessl/npm-langchain--textsplitters

Various implementations of LangChain.js text splitters for retrieval-augmented generation (RAG) pipelines

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LangChain Text Splitters

LangChain Text Splitters provides various implementations of text splitting functionality for LangChain.js, most commonly used as part of retrieval-augmented generation (RAG) pipelines. The library offers abstract base classes and concrete implementations for splitting text documents into smaller chunks with configurable size, overlap, and length functions.

Package Information

  • Package Name: @langchain/textsplitters
  • Package Type: npm
  • Language: TypeScript
  • Installation: npm install @langchain/textsplitters @langchain/core js-tiktoken

Core Imports

import {
  // Classes
  TextSplitter,
  CharacterTextSplitter,
  RecursiveCharacterTextSplitter,
  TokenTextSplitter,
  MarkdownTextSplitter,
  LatexTextSplitter,
  
  // Interfaces and Types
  TextSplitterParams,
  TextSplitterChunkHeaderOptions,
  CharacterTextSplitterParams,
  RecursiveCharacterTextSplitterParams,
  TokenTextSplitterParams,
  MarkdownTextSplitterParams,
  LatexTextSplitterParams,
  SupportedTextSplitterLanguage,
  SupportedTextSplitterLanguages
} from "@langchain/textsplitters";

// Required imports for tiktoken functionality
import type * as tiktoken from "js-tiktoken";
import { Document } from "@langchain/core/documents";

For CommonJS:

const {
  // Classes
  TextSplitter,
  CharacterTextSplitter,
  RecursiveCharacterTextSplitter,
  TokenTextSplitter,
  MarkdownTextSplitter,
  LatexTextSplitter,
  
  // Interfaces and Types
  TextSplitterParams,
  TextSplitterChunkHeaderOptions,
  CharacterTextSplitterParams,
  RecursiveCharacterTextSplitterParams,
  TokenTextSplitterParams,
  MarkdownTextSplitterParams,
  LatexTextSplitterParams,
  SupportedTextSplitterLanguage,
  SupportedTextSplitterLanguages
} = require("@langchain/textsplitters");

// Required for document processing
const { Document } = require("@langchain/core/documents");

Basic Usage

import { RecursiveCharacterTextSplitter } from "@langchain/textsplitters";
import { Document } from "@langchain/core/documents";

// Create a text splitter with custom configuration
const splitter = new RecursiveCharacterTextSplitter({
  chunkSize: 1000,
  chunkOverlap: 200,
});

// Split text into chunks
const text = "Your long text content here...";
const chunks = await splitter.splitText(text);

// Create documents from text with metadata
const docs = await splitter.createDocuments(
  [text],
  [{ source: "example.txt" }]
);

// Split existing documents
const existingDocs = [
  new Document({ pageContent: text, metadata: { source: "doc1" } })
];
const splitDocs = await splitter.splitDocuments(existingDocs);

Architecture

LangChain Text Splitters is built around several key components:

  • Abstract Base Class: TextSplitter provides core splitting functionality and document transformation interface
  • Concrete Implementations: Specialized splitters for different splitting strategies (character-based, recursive, token-based)
  • Document Integration: Full integration with LangChain's Document ecosystem via BaseDocumentTransformer
  • Metadata Preservation: Automatic line number tracking and metadata propagation through splitting operations
  • Language-Aware Splitting: Support for 18 programming languages with language-specific separators

Capabilities

Basic Text Splitting

Core text splitting functionality using simple character-based separators. Ideal for basic document chunking with predictable separator patterns.

class CharacterTextSplitter extends TextSplitter {
  constructor(fields?: Partial<CharacterTextSplitterParams>);
  splitText(text: string): Promise<string[]>;
}

interface CharacterTextSplitterParams extends TextSplitterParams {
  separator: string;
}

Character Text Splitting

Recursive Text Splitting

Advanced recursive splitting using a hierarchy of separators. Perfect for intelligent document chunking that preserves semantic structure and supports code-aware splitting.

class RecursiveCharacterTextSplitter extends TextSplitter {
  constructor(fields?: Partial<RecursiveCharacterTextSplitterParams>);
  splitText(text: string): Promise<string[]>;
  static fromLanguage(
    language: SupportedTextSplitterLanguage,
    options?: Partial<RecursiveCharacterTextSplitterParams>
  ): RecursiveCharacterTextSplitter;
  static getSeparatorsForLanguage(language: SupportedTextSplitterLanguage): string[];
}

interface RecursiveCharacterTextSplitterParams extends TextSplitterParams {
  separators: string[];
}

const SupportedTextSplitterLanguages = [
  "cpp", "go", "java", "js", "php", "proto", "python", "rst",
  "ruby", "rust", "scala", "swift", "markdown", "latex", "html", "sol"
] as const;

type SupportedTextSplitterLanguage = (typeof SupportedTextSplitterLanguages)[number];

Recursive Text Splitting

Token-Based Splitting

Token-aware splitting using tiktoken encoding for accurate token count management. Essential for applications that need precise token-based chunking for language models.

class TokenTextSplitter extends TextSplitter {
  constructor(fields?: Partial<TokenTextSplitterParams>);
  splitText(text: string): Promise<string[]>;
}

interface TokenTextSplitterParams extends TextSplitterParams {
  encodingName: tiktoken.TiktokenEncoding;
  allowedSpecial: "all" | Array<string>;
  disallowedSpecial: "all" | Array<string>;
}

// Tiktoken encoding types from js-tiktoken
namespace tiktoken {
  type TiktokenEncoding = "gpt2" | "r50k_base" | "p50k_base" | "cl100k_base";
  
  interface Tiktoken {
    encode(text: string, allowedSpecial?: "all" | Array<string>, disallowedSpecial?: "all" | Array<string>): number[];
    decode(tokens: number[]): string;
  }
}

Token-Based Splitting

Document Format Splitting

Specialized splitters optimized for specific document formats like Markdown and LaTeX. Designed to preserve document structure and formatting semantics.

class MarkdownTextSplitter extends RecursiveCharacterTextSplitter {
  constructor(fields?: Partial<MarkdownTextSplitterParams>);
}

class LatexTextSplitter extends RecursiveCharacterTextSplitter {
  constructor(fields?: Partial<LatexTextSplitterParams>);
}

type MarkdownTextSplitterParams = TextSplitterParams;
type LatexTextSplitterParams = TextSplitterParams;

Document Format Splitting

Core Types

interface TextSplitterParams {
  chunkSize: number;
  chunkOverlap: number;
  keepSeparator: boolean;
  lengthFunction?: ((text: string) => number) | ((text: string) => Promise<number>);
}

type TextSplitterChunkHeaderOptions = {
  chunkHeader?: string;
  chunkOverlapHeader?: string;
  appendChunkOverlapHeader?: boolean;
};

// Base class from @langchain/core/documents
abstract class BaseDocumentTransformer {
  abstract transformDocuments(documents: Document[], ...args: any[]): Promise<Document[]>;
}

abstract class TextSplitter extends BaseDocumentTransformer implements TextSplitterParams {
  lc_namespace: string[];
  chunkSize: number;
  chunkOverlap: number;
  keepSeparator: boolean;
  lengthFunction: ((text: string) => number) | ((text: string) => Promise<number>);
  
  constructor(fields?: Partial<TextSplitterParams>);
  abstract splitText(text: string): Promise<string[]>;
  transformDocuments(
    documents: Document[],
    chunkHeaderOptions?: TextSplitterChunkHeaderOptions
  ): Promise<Document[]>;
  createDocuments(
    texts: string[],
    metadatas?: Record<string, any>[],
    chunkHeaderOptions?: TextSplitterChunkHeaderOptions
  ): Promise<Document[]>;
  splitDocuments(
    documents: Document[],
    chunkHeaderOptions?: TextSplitterChunkHeaderOptions
  ): Promise<Document[]>;
  protected splitOnSeparator(text: string, separator: string): string[];
  mergeSplits(splits: string[], separator: string): Promise<string[]>;
  private numberOfNewLines(text: string, start?: number, end?: number): number;
  private joinDocs(docs: string[], separator: string): string | null;
}
Workspace
tessl
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npmpkg:npm/@langchain/textsplitters@0.1.x
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