DocJev Document Splitting Library
Developers working with document processing can use DocJev as a faster alternative to Luna with similar accuracy, especially for digitalized documents.
DocJev is an open-source library for document classification and splitting. It matches Luna in splitting complex documents along semantic boundaries. The library is 6x faster than GPT-5.6-Luna with equivalent accuracy. It supports two OCR backends: liteparse for digitalized documents and LlamaParse for complex documents.
you can find a nice interactive visualization of docjev splitting in action here. it matches luna in being able to split complex document text along the right semantic boundaries jerryjliu.github.io/docjev/ Jerry Liu @jerryjliu0 Introducing DocJev - a lightning-fast OSS library for document classification and splitting with jev ⚡️ Give a document alongside some natural language category rules. Jev will predict the document category (classify) or the boundaries between sub-documents (split). It is 6x faster than gpt-5.6-luna with equivalent accuracy. You can choose between different OCR backends: liteparse: the fastest/most accurate free+OSS text parser out there. Perfect for digitalized documents. The speedups vs. luna above are inclusive of liteparse times. LlamaParse: the most advanced VLM-based solution for complex docs. Using this will of course add latency on document preprocessing. But it’s a good option if you want to cache the digitalized representations of documents for a variety of downstream tasks. Check it out: github.com/jerryjliu/docj… If you want to dive deeper into liteparse or LlamaParse check the links below: liteparse: github.com/run-llama/lite… LlamaParse: cloud.llamaindex.ai Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 4 🔄 2 ❤️ 23 👀 2399 📊 9 ⚡
