liteparse

# LiteParse Local document parser built on PDF.js + Tesseract.js. Zero cloud dependencies. **Binary:** `lit` (installed globally via npm) **Docs:** https://developers.llamaindex.ai/liteparse/ ## Quick Reference ```bash # Parse a PDF to text (stdout) lit parse document.pdf # Parse to file lit parse document.pdf -o output.txt # Parse to JSON (includes bounding boxes) lit parse document.pdf --format json -o output.json # Specific pages only lit parse document.pdf --target-pages "1-5,10,15-20" # No OCR (faster, text-layer PDFs only) lit parse document.pdf --no-ocr # Batch parse a directory lit batch-parse ./input-dir ./output-dir # Screenshot pages (for vision model input) lit screenshot document.pdf -o ./screenshots lit screenshot document.pdf --target-pages "1,3,5" --dpi 300 -o ./screenshots ``` ## Output Formats | Format | Use case | |--------|----------| | `text` (default) | Plain text extraction, feeding into prompts | | `json` | Structured output with bounding boxes, useful for layout-aware tasks | ## OCR Behavior - OCR is **on by default** via Tesseract.js (downloads ~10MB English data on first run) - First run will be slow; subsequent runs use cached data - `--no-ocr` for pure text-layer PDFs (faster, no network needed) - For multi-language: `--ocr-language fra+eng` ## Supported File Types Works natively: **PDF** Requires **LibreOffice** (`brew install --cask libreoffice`): .docx, .doc, .xlsx, .xls, .pptx, .ppt, .odt, .csv Requires **ImageMagick** (`brew install imagemagick`): .jpg, .png, .gif, .bmp, .tiff, .webp ## Installation Notes - Installed via npm: `npm install -g @llamaindex/liteparse` - Brew formula exists (`brew tap run-llama/liteparse`) but requires current macOS CLT — use npm as primary install path on this machine - Binary path: `/opt/homebrew/bin/lit` ## Workflow Tips - For **VA forms, job description PDFs, military docs**: `lit parse file.pdf -o /tmp/output.txt` then read into context - For **scanned PDFs** (no text layer): OCR is required; complex layouts may degrade — consider LlamaParse cloud for critical docs - For **vision model workflows**: use `lit screenshot` to generate page images, then pass to `image` tool or similar - For **batch jobs**: use `lit batch-parse` — it reuses the PDF engine across files for efficiency ## Limitations - Complex tables, multi-column layouts, and scanned government forms may produce imperfect output - LlamaParse (cloud) handles the hard cases: https://cloud.llamaindex.ai - Max recommended DPI for screenshots: 300 (higher = slower, larger files) ## Reference See `references/output-examples.md` for sample JSON/text output structure.