- name
- liteparse
- description
- Parse, extract text from, and screenshot PDF and document files locally using the LiteParse CLI (
lit). Use when asked to extract text from a PDF, parse a Word/Excel/PowerPoint file, batch-process a folder of documents, or generate page screenshots for LLM vision workflows. Runs entirely offline — no cloud, no API key. Supports PDF, DOCX, XLSX, PPTX, images (jpg/png/webp), and more. Triggers on phrases like "extract text from this PDF", "parse this document", "get the text out of", "screenshot this PDF page", or any request to read/extract content from a file.
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
# 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 ./screenshotsOutput 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-ocrfor 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.txtthen 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 screenshotto generate page images, then pass toimagetool 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.