# Text splitters

Chunk text smartly, by headings, paragraphs or code functions, with a chosen size and overlap.

AI developers · Part 06: LangChain / LangGraph · Card 4 of 14 · Last updated 2026-10-13

## Analogy

A formatter for chunking: it knows where the natural line breaks are so you don't cut a sentence in half.

## Code example

`split.ts`

```typescript
import { RecursiveCharacterTextSplitter } from "@langchain/textsplitters";

const splitter = new RecursiveCharacterTextSplitter({
  chunkSize: 1000,
  chunkOverlap: 100,
});
const chunks = await splitter.splitText(markdownDoc);
```

## In an agent

Good splits mean the agent retrieves whole ideas, not half-sentences.

## Practice

### Flashcards

- **Interview: how do you pick chunk size?** Start at 500 to 800 tokens with overlap, split on natural boundaries, then tune with retrieval evals.

### Interview questions

**How do you choose chunk size?**

- Start around 500 to 800 tokens with some overlap.
- Split on natural boundaries like headings, paragraphs or functions.
- Tune with retrieval evals instead of guessing.

## Questions people ask

### How do LangChain text splitters work?

A splitter such as RecursiveCharacterTextSplitter cuts text into chunks of a chosen size with a chosen overlap. It tries natural break points first, like headings, paragraphs and lines, before cutting mid-sentence. That keeps each chunk close to one complete idea, which makes retrieval more accurate.

### What chunk size and overlap should I give a text splitter?

A common starting point is a chunk size around 1,000 characters with about 100 characters of overlap, which is roughly in line with 300 to 800 tokens. The overlap keeps sentences that cross a boundary from being lost. Tune both values with retrieval evals on your own questions.

## Related concepts

- [Chunk size](https://studyvisually.com/learn/tech/ai-developers/embeddings-rag/chunking)
- [Document loaders](https://studyvisually.com/learn/tech/ai-developers/langchain-langgraph/document-loaders)
- [Retrievers](https://studyvisually.com/learn/tech/ai-developers/langchain-langgraph/retrievers)
- [Evals](https://studyvisually.com/learn/tech/ai-developers/production/evals)

Web page: https://studyvisually.com/learn/tech/ai-developers/langchain-langgraph/text-splitters
Study this card in the app: https://studyvisually.com/app/learn?category=ai-developers&card=text-splitters