Intermediate LevelAI, LLMs, Embeddings & MCP
Why is Chunk Overlap critical when splitting documents for RAG vector search?
❓ Interview Prompt: Explain chunk boundary slicing errors, sentence fragmentation, and chunk overlap window parameters.
When splitting long documents into chunks (e.g. 500-token chunks), important semantic concepts or sentences frequently cross chunk boundaries.
The Chunk Boundary Problem:
If a key fact ("The refund window is 30 days") is sliced right between two chunks ("...refund window is" and "30 days..."), neither vector embedding will capture the complete semantic meaning!
The Overlap Solution:
Including a sliding overlap window (e.g. 500-token chunks with 50-token overlap) ensures that boundary text appears in both adjacent chunks, guaranteeing semantic continuity.
Code Implementation Example
typescript
// Fixed-size chunking with sliding overlap
function chunkWithOverlap(text: string, chunkSize: number = 500, overlapSize: number = 50): string[] {
const chunks: string[] = [];
let i = 0;
while (i < text.length) {
chunks.push(text.slice(i, i + chunkSize));
i += chunkSize - overlapSize; // Step forward by (size - overlap)
}
return chunks;
}💡Sliding window text chunking with token overlap.
🎯 Interview Key Takeaway
Chunk overlap prevents semantic boundary slicing by duplicating edge text across consecutive document chunks.
#Chunking#Overlap#RAG#Vector Search#Intermediate
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