/liteparse

name: liteparse
scope: common
description: "Parse local document files into LLM-ready content on the daemon itself — PDFs → Markdown / structured JSON (with bounding boxes) / page screenshots via the bundled `lit` CLI. PDF works out of the box, offline, zero external deps (Tesseract + PDFium are bundled): digital PDFs use a near-instant native text path (`--no-ocr`), scanned PDFs fall back to bundled OCR. Image files (PNG/JPG) additionally need ImageMagick, and Office files (DOCX/XLSX/PPTX) need LibreOffice — install those on demand only when required. Use whenever the user attaches or points to a local file that must be read before reasoning, or asks to extract text / tables / page images from a file on disk. For web URLs and search, use the `ingest` skill instead."

LiteParse (local-first document parsing)

LiteParse turns document files into text the model can read — **on the daemon machine, offline, zero cloud dependency**. It ships as the `@llamaindex/liteparse` npm package (CLI: `lit`) with **PDFium and Tesseract bundled inside the package** — the digital-PDF and scanned-OCR paths need no external system dependencies.

> Upstream: [`run-llama/liteparse`](https://github.com/run-llama/liteparse) > + skill [`run-llama/llamaparse-agent-skills`](https://github.com/run-llama/llamaparse-agent-skills/blob/main/skills/liteparse/SKILL.md). > Apache-2.0 (core) / MIT (skill), © LlamaIndex. Vendored as a Prismer > built-in.

Capability tiers — what works where

| Tier | Inputs | External dep | Status | | --- | --- | --- | --- | | **1 — PDF** | digital + scanned PDF | **none** (Tesseract + PDFium bundled) | **Default, out of the box** — `lit` is baked into the daemon image | | **2 — Images** | PNG / JPG / TIFF / … | **ImageMagick** | Install on demand | | **3 — Office** | DOCX / XLSX / PPTX / ODT | **LibreOffice** (~1GB) | Install on demand |

Only Tier 1 is guaranteed present. Tiers 2 and 3 pull large system dependencies that are **deliberately not baked into the daemon image** — install them yourself, only when the actual input requires it (see below). Do not assume they are already installed.

Tier 1 — PDF (default, ready to use)

`lit` is available on the daemon. Sanity-check once, quietly:

command -v lit && lit --version    # baked into the image

If (and only if) it is somehow missing, install the package locally — it is ~38MB with the OCR/render binaries bundled and installs in a few seconds:

npm i @llamaindex/liteparse && npx lit --version

> Do **not** rely on the CLI "self-installing on first use" — that path > is unreliable (npm permission / cache conflicts). Either it is baked > in, or you install the package explicitly as above.

Native text path vs OCR — pick deliberately, cost differs ~10×

• **Digital PDF (has an embedded text layer): use `--no-ocr`.** PDFium

extracts the text directly — **near-instant (~0.35s/page)**, no OCR. This is the fast, cheap path; prefer it whenever the PDF is computer-generated.

• **Scanned / image-only PDF: leave OCR on (default).** The bundled

Tesseract OCRs each page — **~5s/page**, an order of magnitude slower. Only pay this when there is no real text layer.

If unsure which kind you have, run `--no-ocr` first: empty/garbled output means it's a scan → re-run without `--no-ocr` to OCR it.

lit parse report.pdf --no-ocr                       # digital PDF → fast native text
lit parse scan.pdf                                   # scanned PDF → bundled OCR
lit parse report.pdf --format markdown -o out.md     # Markdown output to a file
lit parse report.pdf --format json -o out.json       # structured JSON + bounding boxes
lit parse report.pdf --target-pages "1-5,10,15-20"   # page subset (huge speedup on OCR path)

`--format` accepts `markdown` (default) or `json` (adds per-block bounding boxes). Other useful flags: `-o/--output`, `--target-pages "1-5,10"`, `--dpi <n>` (render DPI, default 150 — bump to 300 for small scanned text), `--ocr-language eng+chi_sim` (Tesseract lang codes for the OCR path), `--password '****'` (encrypted PDFs), `-q/--quiet`.

Page screenshots (for figures/charts text can't capture)

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

Tier 2 — Image files (install ImageMagick on demand)

Parsing standalone image files (PNG/JPG/TIFF/…) needs **ImageMagick**, which is not in the daemon image. Install it the first time you actually have an image input:

apt-get update && apt-get install -y imagemagick   # Debian/Ubuntu (daemon image)
brew install imagemagick                            # macOS (local dev)
lit parse diagram.png --format markdown

If ImageMagick can't be installed (no network / no apt), report `ImageMagick unavailable` and stop — don't fabricate the image's contents.

Tier 3 — Office documents (install LibreOffice on demand)

DOCX / XLSX / PPTX / ODT conversion needs **LibreOffice (~1GB)**, which is **intentionally not baked into the daemon image**. Install it only when you genuinely need to parse an Office file (it's a big download — don't do it speculatively):

apt-get update && apt-get install -y libreoffice   # Debian/Ubuntu (daemon image)
brew install --cask libreoffice                     # macOS (local dev)
lit parse deck.pptx --format markdown

If LibreOffice can't be installed, say so and ask the user for a PDF export of the document instead of guessing.

> A shared **cloud parse service for heavy formats** (offloading Office / > hi-res OCR to a hosted backend so agents don't install 1GB deps) is a > future TODO — it is **not** running today. Don't route to a cloud OCR > endpoint.

Scope — liteparse vs `ingest`

Two skills, clean split by **source location**:

• **`liteparse` (this skill)** — **local files on disk.** PDF / image /

Office files alr