Semantic chunking, built for speed.
blazechunk turns messy text and documents into retrieval-ready chunks without sacrificing structure, provenance, or throughput.
The pipeline
From source file to retrieval-ready data.
report.pdf
Unstructured source
DocumentChunker
Structure + provenance preserved
Ready for your index
Text, metadata, and offsets
blazechunk splits text at semantic boundaries and does it stupid fast. It ships nine chunkers: six structural chunkers ( Chunker, RecursiveChunker, SentenceChunker, TokenChunker, TableChunker, CodeChunker), and three embedding-based chunkers ( SemanticChunker, SDPMChunker, LateChunker) — all with matching synchronous and asynchronous methods.
Why blazechunk
Blazing fast
SIMD memchr/lookup-table/Aho-Corasick delimiter search; up to 1 TB/s on the raw primitive.
Correct by construction
Text chunk offsets are real byte offsets into your input; document chunks use offsets into converted Markdown. Multi-byte / CJK text is never split mid-character.
Sync and async everywhere
Every chunker has chunk/chunk_async and chunk_batch/chunk_batch_async, safe to use inside FastAPI/asyncio without blocking the event loop.
Pick a chunker
| Chunker | Best for | Unit | Default |
|---|---|---|---|
| Chunker | max-throughput byte splitting | bytes | 4096 |
| DocumentChunker | PDF, Word, slides, spreadsheets, and more | file | 2048 |
| RecursiveChunker | long, well-structured docs | characters | 2048 |
| SentenceChunker | retrieval where sentence integrity matters | characters | 2048 |
| TokenChunker | fixed-size windows for token-limited models | tokens | 2048 |
| TableChunker | large Markdown/HTML tables | rows | 3 |
| CodeChunker | source code, structure-aware | characters | 2048 |
| SemanticChunker | semantic boundaries via embeddings | characters | 2048 |
| SDPMChunker | semantic + bridging gaps (skip-window merge) | characters | 2048 |
| LateChunker | late-interaction embeddings per chunk | characters | 2048 |
Framework integrations
Use blazechunk directly in your favorite frameworks with official integrations:
Documents
PDF, Word, PowerPoint, Excel and more, with heading-aware chunks.
LangChain
Use BlazechunkTextSplitter directly in LangChain pipelines for semantically-aware document splitting.
pip install "blazechunk[langchain]"Agno
Use BlazechunkChunking to integrate fast chunking into Agno agent workflows.
pip install "blazechunk[agno]"Availability: Python (sync+async)