PDF 里的复选框、批注、矢量图，LiteParse 免费开源毫秒级提取，复杂页面自动转交 LlamaParse。
LiteParse 现在可在毫秒级从 PDF 中提取复选框状态、标注、矢量图形和词级边界框。它是目前功能最全的免费开源文档处理器，可接入编码智能体，提供源文档的上下文和引用回归。对于扫描页、多栏文本、表格等复杂文档，LiteParse 会通过内置路由器转向 VLM 方案（如 LlamaParse）。LiteParse 还输出复杂度信号，告诉用户哪些页面需要视觉模型处理。
LiteParse can now extract structured data from your PDF in milliseconds: ✅ checkbox states ✅ annota...
LiteParse can now extract structured data from your PDF in milliseconds: ✅ checkbox states ✅ annotations ✅ vector graphics ✅ word-level bounding boxes It is the most comprehensive, accurate (and fast) free/open-source document processor out there. If you plug it into a coding agent to process digitalized PDFs, you will not only be able to give it the right context, but also give it grounding back to the source. For more complex docs that require VLM processing, you can always use the in-built router to route it to a VLM based solution, like LlamaParse. Come check it out: developers.llamaindex.ai/liteparse/guid… LiteParse: github.com/run-llama/lite… Complexity guide: developers.llamaindex.ai/liteparse/guid… LlamaIndex 🦙 @llama_index You shouldn't need a vision model to know your PDF has checkboxes. LiteParse can now pull structured data directly from your PDFs: form field values, checkbox states, annotations, embedded images, vector graphics, tagged document structure, and word-level bounding boxes, all running in ms per page. For pages that do need a model, new complexity signals tell you why. Scanned pages, multi-column text, tables (ruled and borderless), and dense figures help you route your parsing to the best tools (like LlamaParse!) Docs 👉️ : developers.llamaindex.ai/liteparse/guid… U developers.llamaindex.ai/liteparse/guid… V 👩💻 Try i github.com/run-llama/pars… 8qn 🔗 View Quoted Tweet 💬 2 🔄 0 ❤️ 11 👀 887 📊 4 ⚡