Universal document parsing in AILANG. Extracts structured content from DOCX, PPTX, XLSX, PDF, and image files into JSON and 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.
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/docparseUse 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# 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
# 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"Every run produces:
docparse/data/output.json— Structured JSON with typed blocksdocparse/data/output.md— LLM-ready markdown
| 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.
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)
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.docxWhat 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.
docparse/
├── types/document.ail # Block ADT (9 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.
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 # AnthropicAI usage is bounded by capability budgets (AI @limit=200 on main), so costs are predictable.
docparse --check # Type-check all modules
docparse --test # Run inline tests
docparse --prove # Static Z3 contract verificationuv 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.
Apache 2.0