Chunking Strategies for Different Document Types (ANSWERED)
Medium RAG interview question on chunking strategies for different document types — architecture, trade-offs, eval, and production patterns.
TL;DR — Quick Answer
Match chunking to document structure: heading-aware splits for docs, clause hierarchy for legal PDFs, turn-group windows for chat, and schema-aware row batches for CSV. Tune chunk size and overlap per corpus and validate with retrieval recall@k — not fixed token counts alone.
The Interview Question
You ingest API docs, legal PDFs, Slack threads, and CSV exports into one RAG index. How do you choose chunking strategies per type and validate them?
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