rag-parse

name	rag-parse
description	Convertir des documents non-structurés (PDF, DOCX, PPTX, XLSX, images, etc.) en markdown ou JSON localement, sans dépendances cloud. Utiliser quand l'utilisateur demande de parser des fichiers, convertir des documents, ou extraire du texte de PDFs.
provider	liteparse
available-providers	["liteparse"]

rag-parse Skill

Parse unstructured documents (PDF, DOCX, PPTX, XLSX, images, and more) locally. This skill uses LiteParse (lit CLI) under the hood — fast, lightweight, no cloud dependencies or LLM required.

Initial Setup

When this skill is invoked, respond with:

I'm ready to use LiteParse to parse files locally. Before we begin, please confirm that:

- `@llamaindex/liteparse` is installed globally (`npm i -g @llamaindex/liteparse`)
- The `lit` CLI command is available in your terminal

If both are set, please provide:

1. One or more files to parse (PDF, DOCX, PPTX, XLSX, images, etc.)
2. Any specific options: output format (json/text), page ranges, OCR preferences, DPI, etc.
3. What you'd like to do with the parsed content.

I will produce the appropriate `lit` CLI command or TypeScript script, and once approved, report the results.

Then wait for the user's input.

---

Step 0 — Install LiteParse (if needed)

If liteparse is not yet installed, install it globally:

npm i -g @llamaindex/liteparse

Verify installation:

lit --version

For Office document support (DOCX, PPTX, XLSX), LibreOffice is required:

# macOS
brew install --cask libreoffice

# Ubuntu/Debian
apt-get install libreoffice

For image parsing, ImageMagick is required:

# macOS
brew install imagemagick

# Ubuntu/Debian
apt-get install imagemagick

---

Step 1 — Produce the CLI Command or Script

Parse a Single File

# Basic text extraction
lit parse document.pdf

# JSON output saved to a file
lit parse document.pdf --format json -o output.json

# Specific page range
lit parse document.pdf --target-pages "1-5,10,15-20"

# Disable OCR (faster, text-only PDFs)
lit parse document.pdf --no-ocr

# Use an external HTTP OCR server for higher accuracy
lit parse document.pdf --ocr-server-url http://localhost:8828/ocr

# Higher DPI for better quality
lit parse document.pdf --dpi 300

Batch Parse a Directory

lit batch-parse ./input-directory ./output-directory

# Only process PDFs, recursively
lit batch-parse ./input ./output --extension .pdf --recursive

Generate Page Screenshots

Screenshots are useful for LLM agents that need to see visual layout.

# All pages
lit screenshot document.pdf -o ./screenshots

# Specific pages
lit screenshot document.pdf --pages "1,3,5" -o ./screenshots

# High-DPI PNG
lit screenshot document.pdf --dpi 300 --format png -o ./screenshots

# Page range
lit screenshot document.pdf --pages "1-10" -o ./screenshots

---

Step 2 — Key Options Reference

OCR Options

Option	Description
(default)	Tesseract.js — zero setup, built-in
--ocr-language fra	Set OCR language (ISO code)
--ocr-server-url <url>	Use external HTTP OCR server (EasyOCR, PaddleOCR, custom)
--no-ocr	Disable OCR entirely

Output Options

Option	Description
--format json	Structured JSON with bounding boxes
--format text	Plain text (default)
-o <file>	Save output to file

Performance / Quality Options

Option	Description
--dpi <n>	Rendering DPI (default: 150; use 300 for high quality)
--max-pages <n>	Limit pages parsed
--target-pages <pages>	Parse specific pages (e.g. "1-5,10")
--no-precise-bbox	Disable precise bounding boxes (faster)
--skip-diagonal-text	Ignore rotated/diagonal text
--preserve-small-text	Keep very small text that would otherwise be dropped

---

Step 4 — Using a Config File

For repeated use with consistent options, generate a liteparse.config.json:

{
  "ocrLanguage": "en",
  "ocrEnabled": true,
  "maxPages": 1000,
  "dpi": 150,
  "outputFormat": "json",
  "preciseBoundingBox": true,
  "skipDiagonalText": false,
  "preserveVerySmallText": false
}

For an HTTP OCR server:

{
  "ocrServerUrl": "http://localhost:8828/ocr",
  "ocrLanguage": "en",
  "outputFormat": "json"
}

Use with:

lit parse document.pdf --config liteparse.config.json

---

Step 5 — HTTP OCR Server API (Advanced)

If the user wants to plug in a custom OCR backend, the server must implement:

• Endpoint: POST /ocr
• Accepts: file (multipart) and language (string) parameters
• Returns:

{
  "results": [
    { "text": "Hello", "bbox": [x1, y1, x2, y2], "confidence": 0.98 }
  ]
}

Ready-to-use wrappers exist for EasyOCR and PaddleOCR in the LiteParse repo.

---

Supported Input Formats

Category	Formats
PDF	.pdf
Word	.doc, .docx, .docm, .odt, .rtf
PowerPoint	.ppt, .pptx, .pptm, .odp
Spreadsheets	.xls, .xlsx, .xlsm, .ods, .csv, .tsv
Images	.jpg, .jpeg, .png, .gif, .bmp, .tiff, .webp, .svg

Office documents require LibreOffice; images require ImageMagick. LiteParse auto-converts these formats to PDF before parsing.