Akademisches Studien- und Fristenmanagement mit Quellenprüfung, Datenschutz und realistischer Handlungsplanung.
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Split documents into overlapping token chunks for RAG pipelines and LLM context windows. Zero dependencies.
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Deutsch — Offizielle Deutsch-Version / Documento Oficial en Deutsch.
Splits documents into overlapping token chunks. Optimized for RAG pipelines and LLM context windows. Zero dependencies — Python stdlib + re only.
from document_chunker import DocumentChunker
chunker = DocumentChunker(chunk_size=400, overlap=80)
chunks = chunker.chunk_text("Long text...")
for chunk in chunks:
print(f"Chunk {chunk['chunk_id']}: {chunk['tokens']} tokens")
chunks = chunker.chunk_document("document.md", source="My Project")
from document_chunker import chunk_corpus
chunks = chunk_corpus(["doc1.md", "doc2.txt"], source="Corpus")
python document_chunker.py document.md # Single file
python document_chunker.py ./docs/ # Entire directory
| Parameter | Default | Description |
|---|---|---|
| chunk_size | 400 | Max tokens per chunk |
| overlap | 80 | Overlapping tokens between chunks |
.txt, .md, .py, .sh
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Akademisches Studien- und Fristenmanagement mit Quellenprüfung, Datenschutz und realistischer Handlungsplanung.
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