AILANG Parse
Universal document parsing and generation in AILANG. Extracts structured content from DOCX, PPTX, XLSX, PDF, and image files into JSON and markdown — and writes documents back out in 9 formats. To author a document, write Markdown and convert it; see Writing documents in Markdown.
Office formats (DOCX, PPTX, XLSX) use deterministic XML parsing — no AI, no cloud, instant results. PDFs default to the deterministic pdftotext backend (poppler) — also no AI, no cloud — with docling and liteparse as local alternatives and pluggable AI (Gemini, Claude, local Ollama) for scanned/image-only pages via --pdf-backend ai. Images delegate to whatever AI model you plug in. AILANG Parse is AI-agnostic: swap --pdf-backend/--ai to change the backend, zero code changes.
Install
Requires AILANG CLI.
# Clone and symlink
git clone https://github.com/sunholo-data/ailang-parse.git
ln -s "$(pwd)/ailang-parse/bin/docparse" /usr/local/bin/docparse
SDKs
Use AILANG Parse from your language of choice:
pip install ailang-parse # Python
npm install @ailang/parse # JavaScript/TypeScript
go get github.com/sunholo-data/ailang-parse-go # Go
Quick Start
# Office documents (deterministic, no AI needed)
docparse report.docx
docparse slides.pptx
docparse spreadsheet.xlsx
# PDF (deterministic pdftotext by default — no AI); images (AI auto-enabled)
docparse document.pdf
docparse photo.png
# Options
docparse report.docx describe # AI image descriptions
docparse report.docx summarize # AI document summary
docparse contract.pdf # PDF: deterministic pdftotext (default)
docparse scan.pdf --pdf-backend ai --ai gemini-2.5-flash # Scanned PDF needs AI
# Format conversion
docparse report.docx --convert output.html
docparse data.csv --convert report.docx
docparse notes.md --convert slides.pptx
docparse notes.md --convert offer.docx --reference-doc letterhead.docx
# AI document generation
ailang run --entry main --caps IO,FS,Env,AI --ai gemini-2.5-flash \
docparse/main.ail --generate report.docx --prompt "Q1 sales report with tables"
Output
Every run produces:
docparse/data/output.json— Structured JSON with typed blocksdocparse/data/output.md— LLM-ready markdown
What AILANG Parse Extracts
| Feature | DOCX | PPTX | XLSX | Best Competitor |
|---|---|---|---|---|
| Tables with merged cells | Yes | Yes | Yes | Raw OOXML only |
| Track changes (redlining) | Yes | — | — | Pandoc (3/3) |
| Comments (interleaved) | Yes | — | — | Raw OOXML (2/2) |
| Headers/footers | Yes | — | — | Kreuzberg (2/3) |
| Text boxes / VML shapes | Yes | Yes | — | Raw OOXML (1/2) |
| Equations (§22.1) | Yes | — | — | None |
| Field codes (§17.16) | Yes | — | — | Kreuzberg, OOXML |
| Speaker notes | — | Yes | — | None |
| Multi-sheet extraction | — | — | Yes | Kreuzberg |
OfficeDocBench (69 files, 11 formats, 7 metrics): AILANG Parse 93.9% composite with 100% coverage vs nearest competitor 68.0% coverage-adjusted. 8 parsers compared including Raw OOXML, Pandoc, Kreuzberg, MarkItDown, Unstructured, Docling. Scores include aspirational ECMA-376 spec targets that intentionally lower our score.
Supported Formats
Parsing (16 formats): DOCX, PPTX, XLSX, ODT, ODP, ODS, HTML, Markdown, CSV, EPUB, EML, MBOX, TEX, RTF, PDF, images (JPG/PNG)
Generation (9 formats): DOCX, PPTX, XLSX, ODT, ODP, ODS, HTML, Markdown, QMD (Quarto)
Writing documents in Markdown
Markdown is the input an LLM can write, so it is the practical way to generate a document: write markdown, convert to any of the nine output formats.
docparse report.md --convert report.docx
What survives the trip: YAML front matter (title/author/date → document
properties), bold/italic/code/strike as real character formatting,
links as real hyperlinks, images (local paths are read and embedded), fenced
code blocks, blockquotes, nested lists, thematic breaks, and tables with
alignment and column spans.
Headers, footers, comments and tracked changes have no Markdown syntax; those are preserved when converting from a document that already contains them.
Styling a generated DOCX from a template
--reference-doc is the Quarto/Pandoc reference-doc feature: an existing
.docx supplies the look, the Markdown supplies the content.
docparse annex.md --convert annex.docx --reference-doc letterhead.docx
The template's styles.xml, numbering.xml, theme, embedded fonts, headers,
footers and page setup are applied to the new content. Everything the merge does
not regenerate is carried through byte-for-byte, so the letterhead, logo and
licensed fonts come out exactly as they went in.
What comes from where:
| Template | page size, margins, headers, footers, page numbering, fonts, theme, colours |
| Your document | the body content, and docProps/core.xml (title/author) |
| Merged | styles.xml (ours fill only the styleIds the template lacks), numbering.xml (our list definitions take ids above the template's), [Content_Types].xml, both .rels |
Two consequences worth knowing:
- The template's headers and footers win. A source document's own headers are
dropped rather than mixed with the letterhead. The page furniture all lives in
the template's body
<w:sectPr>, which is lifted whole. - The template's comments are dropped along with its body, and so are
commentsExtended.xmlandpeople.xml. Comments in the source document still come through.
Two flags refine a multi-section template:
--reference-section Npicks which of the template's sections supplies the page setup, headers and footers — 1 is the first section, Word's numbering. The default is the last section (the body-level one, what the flag-less behaviour has always lifted). A multi-section template's wanted furniture is often an earlier section's — the master agreement's CONFIDENTIAL footer, not the Annex's missing one.--table-style NAMEbinds generated tables to a table style the template defines (matched on styleId, then style name). Without it, the style namedTableis used if the template has one, else the first table style that is not the implicit Normal Table. Under a bound style the generator stops emitting its own hardcoded borders — the style carries them.
An unreadable or non-DOCX reference is an error and writes nothing — a silent fallback to the built-in styling would produce a plausible file missing exactly the letterhead it was asked for. DOCX output only.
Architecture
docparse/
├── types/document.ail # Block ADT (11 variants)
├── services/
│ ├── format_router.ail # Format detection (36 inline tests)
│ ├── zip_extract.ail # ZIP layer (9 inline tests)
│ ├── docx_parser.ail # DOCX XML → Blocks (6 inline tests)
│ ├── pptx_parser.ail # PPTX slides → Blocks
│ ├── xlsx_parser.ail # XLSX worksheets → Blocks
│ ├── direct_ai_parser.ail # PDF/image → Blocks (AI)
│ ├── layout_ai.ail # AI self-healing (optional)
│ ├── output_formatter.ail # JSON + markdown output
│ └── docparse_browser.ail # WASM browser adapter
└── main.ail # CLI entry point
91 contracts, 50+ inline tests. Of the 91, Z3 proves 14 outright; the rest are
checked at runtime under --prove/--verify-contracts in CI, and skip statically
because parser code is recursive and higher-order, which is outside Z3's
decidable fragment.
AI Configuration
AILANG Parse uses AILANG's AI effect — any model AILANG supports works:
docparse scan.pdf --ai gemini-2.5-flash # Google (default; fast)
docparse scan.pdf --ai gemini-3-flash-preview # Google (slower; thinking model)
docparse scan.pdf --ai granite-docling # Local Ollama (free)
docparse scan.pdf --ai claude-haiku-4-5 # Anthropic
AI usage is bounded by capability budgets (AI @limit=200 on main), so costs are predictable.
Dev Commands
docparse --check # Type-check all modules
docparse --test # Run inline tests
docparse --prove # Static Z3 contract verification
Benchmarks
uv run benchmarks/run_benchmarks.py --suite office # Structural (no API, instant)
uv run benchmarks/run_benchmarks.py --suite pdf # PDF extraction (needs AI)
uv run benchmarks/run_benchmarks.py --competitors # Compare to Docling etc.
See benchmarks/ for details.
License
Apache 2.0