DocJev：用 Jev 做文档分类与切分的开源库
给文档加自然语言分类规则，Jev 预测类别或子文档边界，比 gpt-5.6-luna 快 6 倍且精度相当，可选 liteparse/LlamaParse。
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: https://github.com/jerryjliu/docjev If you want to dive deeper into liteparse or LlamaParse check the links below: liteparse: https://github.com/run-llama/liteparse LlamaParse: https://cloud.llamaindex.ai/