LiteParse: Local Document Parsing for AI Agents

LiteParse is a newly open-sourced, CLI and TypeScript-native library designed for fast and local document parsing, specifically optimized for AI agents and real-time pipelines. Unlike many existing tools, LiteParse does not rely on Python dependencies and is focused on preserving the spatial layout of text from PDFs, Office documents, and images, rather than converting them into complex structured formats. This approach allows AI agents to quickly extract and understand text while providing screenshots for more detailed analysis when necessary. While LiteParse offers real-time processing benefits, its output is limited to basic text and spatial data, making it ideal for applications that prioritize speed and simplicity over comprehensive document intelligence. For more complex document processing needs, the proprietary LlamaParse service remains available, offering higher accuracy and structured output capabilities. LiteParse supports various formats by converting all inputs to PDFs, utilizing built-in Tesseract.js for OCR, and offers flexibility to integrate any OCR model. The library has been rigorously benchmarked against other text extraction tools, showing improved page-based QA accuracy and low latency.