产品精选73°

LlamaIndex 开源 DocJev,比 gpt-5.6-luna 快6倍

it's awesome to see the reception here 🔥 one of the jev's promises is to make a lot of business o...

精选理由

DocJev 专做文档分类和拆分,比 gpt-5.6-luna 快6倍,跑文档流水线的可以试试。

LlamaIndex 创始人 Jerry Liu 发布开源库 DocJev,用 jev 模型对文档做分类和拆分。输入文档加自然语言类别规则后,DocJev 能预测文档类别或子文档边界,速度比 gpt-5.6-luna 快 6 倍且准确率相当。OCR 后端可选 liteparse,适合数字化文档,上述速度对比已包含其耗时;处理复杂文档可换用 VLM 方案 LlamaParse,代价是预处理延迟增加。代码已放在 GitHub,定位是把轻量业务操作做快,重的智能任务仍交给更大的 agentic 系统。

原文 · Jerry Liu

it's awesome to see the reception here 🔥 one of the jev's promises is to make a lot of business o...

it's awesome to see the reception here 🔥 one of the jev's promises is to make a lot of business operations extremely lightweight and fast, while still saving intelligence-heavy tasks for larger agentic systems docjev is hyperfocused on doc classification and splitting, and it's very good at it. you can see the full visual report from the readme: github.com/jerryjliu/docj… 9 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 💬 8 🔄 1 ❤️ 26 👀 2621 📊 13 ⚡