liteparse

name	liteparse
description	Parse documents into LLM-ready content entirely on the local machine — PDF / DOCX / XLSX / PPTX / images → Markdown, structured JSON (with bounding boxes), or page screenshots, via the `lit` CLI. No cloud, no LLM, works offline. Use whenever the user attaches or points to a document that must be read before reasoning, or asks to extract text / tables / page images from a file.

LiteParse (local-first document parsing)

LiteParse is a standalone OSS parser (Rust core, PDFium + Tesseract + LibreOffice) that turns documents into text the model can read — fully local, zero cloud dependency, works with no network. It is the daemon's local-first document-parsing path.

Upstream: run-llama/liteparse

• skill run-llama/llamaparse-agent-skills. Apache-2.0 (core) / MIT (skill), © LlamaIndex. Vendored as a Prismer built-in; the CLI (lit) self-installs on first use (see below).

Scope — liteparse vs ingest

Two document paths coexist; pick by network + fidelity needs:

• liteparse (this skill) — local-first. Local document files → Markdown / JSON / screenshots, fully offline, zero cost, zero cloud. Covers PDF, Word, PowerPoint, spreadsheets, images. Built-in Tesseract OCR for clean scans; LibreOffice for Office formats. Default for: files already on disk, offline / cloud-unreachable situations, digital PDFs, quick extraction, bounding boxes, page screenshots.
• ingest (sibling skill) — cloud-backed. cloud load / cloud search for web URLs (HQCC compression) and cloud parse for hi-res OCR of scans / handwriting / dense tables. Use when: the source is a web page (liteparse can't fetch URLs), or local parsing quality is insufficient (dense tables, multi-column, handwriting, low-quality scans).

Decision rule: local file → try liteparse first (free, offline, fast). Escalate to ingest's cloud parse -m hires only when local fidelity falls short. Web URL / search → ingest (liteparse parses local files and stdin, not remote pages — if you only have a URL, curl -sL <url> -o file then parse the local copy, or route to ingest).

When local parsing is low-confidence (empty pages, garbled OCR), flag the region and consider escalating to ingest; never invent content.

First-use install (self-bootstrapping)

The lit CLI ships via npm/pip/cargo (same CLI). Check, then install if missing. Do this once per environment, quietly.

# 1. Is it already available? (sandbox image may bake it)
command -v lit && lit --version && echo "lit ready" || {
  # 2. Install the CLI
  npm i -g @llamaindex/liteparse && lit --version
}

System dependencies for Office conversion + image handling (only needed for non-PDF inputs):

# LibreOffice — required for DOCX/XLSX/PPTX/ODT/RTF conversion
brew install --cask libreoffice        # macOS
apt-get install -y libreoffice         # Debian/Ubuntu (daemon image)

# ImageMagick — required for some image formats
brew install imagemagick               # macOS
apt-get install -y imagemagick         # Debian/Ubuntu

If install fails (no network, no package manager), do not fabricate parsed content — report lit unavailable (<reason>) and stop.

CLI reference

Parse a file

lit parse document.pdf                                  # → text on stdout
lit parse document.pdf --format json -o out.json        # structured JSON + bounding boxes
lit parse document.pdf --target-pages "1-5,10,15-20"    # page subset
lit parse document.pdf --no-ocr                          # skip OCR (digital PDFs only)
lit parse document.pdf --dpi 300                         # higher render DPI
lit parse scan.pdf --ocr-language eng+chi_sim            # Tesseract lang codes
lit parse secured.pdf --password '****'                  # encrypted docs
curl -sL https://example.com/report.pdf | lit parse -    # stdin (download-then-parse)

Key lit parse options: -o/--output, --format json|text (default text), --no-ocr, --ocr-language <lang>, --ocr-server-url <url> (plug an external OCR HTTP server), --tessdata-path, --target-pages "1-5,10", --max-pages <n> (default 1000), --dpi (default 150), --preserve-small-text, --password, --num-workers, -q/--quiet.

Batch a directory

lit batch-parse ./input-dir ./output-dir
lit batch-parse ./input-dir ./output-dir --recursive --extension .pdf --format json

Page screenshots (for visual content text can't capture)

lit screenshot document.pdf -o ./screenshots                  # all pages → PNG
lit screenshot document.pdf --target-pages "1,3,5" -o ./shots
lit screenshot document.pdf --dpi 300 -o ./shots              # high-res

Supported formats: PDF · Word (DOC/DOCX/DOCM/ODT/RTF) · PowerPoint (PPT/PPTX/PPTM/ODP) · Spreadsheets (XLS/XLSX/ODS/CSV/TSV) · Images (JPG/PNG/GIF/BMP/TIFF/WEBP/SVG).

Workflow

1. Locate the file. If it's a workspace asset, resolve its local path (see assets skill). If it's a URL, curl -sL <url> -o <name> first — lit parses local files (and stdin), not remote pages.
2. Pick mode.
   • Digital PDF / clean doc → lit parse <f> (add --no-ocr to skip OCR and go faster when the PDF has a real text layer).
   • Scan / image / handwriting → leave OCR on; set --ocr-language and bump --dpi 300 if text is small.
   • Need spatial structure / tables with coordinates → --format json (gives bounding boxes).
   • Need to see a chart/figure/signature → lit screenshot, then read the PNG.
3. Read the result as source of truth. Base extraction/summary only on what lit returned. If a page is empty or low-confidence, say so; don't guess.
4. Deliver products, if the parse output itself is the deliverable. Write final files into $PRISMER_ARTIFACTS_DIR (the dispatch's artifacts/ dir — auto-archived as IMAssets by the daemon's artifacts-watcher and attached to your reply). See office-artifacts SKILL.md §Delivery contract for the full delivery rules.

Output reporting

• After a parse: Parsed <filename>: <N> pages, format=<text|json>, ocr=<on|off> — then proceed with the user's actual question.
• Don't dump the entire parsed body into chat unless asked; summarize and cite page numbers.
• After screenshots: Rendered <N> page screenshot(s) → <dir> and read the relevant ones.

HARD RULE — never claim a parse you didn't run

Forbidden unless lit actually ran with exit 0 and produced output: "parsed the document", "the PDF says…", "extracted the table". If lit is unavailable or the parse failed, completion text must start with 无法解析文档 (reason) / Cannot parse document (reason) — do not substitute guessed content.