Docling Chunking

What problem does it solve?

Docling Chunking addresses the difficulty of extracting meaningful, navigable chunks from long documents while preserving document structure, provenance, and metadata for robust retrieval and analysis.

Core Features & Use Cases

• HybridChunker provides balanced structure-aware chunking optimized for embeddings and RAG workflows.
• HierarchicalChunker preserves exact document structure for precise citations and hierarchical knowledge representations.
• Rich per-chunk metadata (pages, section headings, provenance) supports high-quality search, auditing, and traceability.
• Export options enable JSONL and Markdown outputs for ingestion by vector stores, databases, and knowledge bases.
• Use cases include building document QA pipelines, knowledge bases, and compliant citation trails across multi-document corpora.

Quick Start

Run the example workflow to convert a document and generate hierarchical chunks ready for RAG pipelines.