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refigure

Converters where figures survive.

CI Coverage License: Apache 2.0 Python 3.10+

DOCX / XLSX → Markdown converters that treat embedded charts, composite diagrams and infographics as single semantic objects instead of silently dropping or fragmenting them: native OOXML chart-data extraction (no rasterize/OCR/VLM) plus positioned machine-readable markers as the zero-loss floor, optional VLM interpretation (prose + mermaid) on top, cached and reproducible offline.

Demo

Native chart-data extraction — real OOXML numCache, not a screenshot, not OCR:

A real xlsx bar chart converted by refigure.xlsx.convert() into Markdown, shown both as the raw text an LLM reads and as the same data re-rendered as a diagram

Same extraction, from DOCX — Word embeds native charts too, not just Excel; refigure reads the same cached OOXML data either way:

A real docx pie chart from an EU labour-platform survey converted by refigure.docx.convert() into Markdown, shown both as the raw text an LLM reads (mermaid fence + data table) and as the same data re-rendered as a diagram

Composite figures — positioned, zero-loss, even when the figure itself can't be rendered (no incumbent does this — see Docling issue #1287, open >1 year):

A real docx composite figure (a grouped diagram refigure.docx.convert() can't render) converted into a positioned zero-loss marker that keeps the figure's own caption/legend text

Quickstart

pip install "refigure[docx,xlsx]"
refigure report.docx                      # markdown to stdout
from refigure.docx import convert

result = convert("report.docx")
print(result.markdown)
print(f"{result.charts_found} charts, {result.groups_found} composite figures")

Features

  • Native chart-data extraction — reads OOXML numCache/strCache directly; no rasterize/OCR/VLM step for charts, real numbers every time.
  • Positioned zero-loss markers for composite figures (DOCX) — grouped shapes/infographics that mammoth would otherwise silently fragment into disconnected pieces get a clean marker instead, with position and any caption text preserved. Absent even in well-funded incumbents — see Docling issue #1287.
  • Optional VLM interpretation (DOCX composite figures, [vlm] extra) — cloud description + mermaid diagram on top of the zero-loss floor. Implemented and tested, but not active or announced as a v1 feature yet (see Status).
  • Rich, typed resultConversionResult (markdown + warnings + chart/group counts + vlm_used), not a bare string.
  • CLI includedrefigure console command, stdin/stdout-first, native batch mode, typed exit codes (see below).

CLI

refigure installs a console command — a thin wrapper over the same convert() used programmatically, no separate logic:

refigure report.docx                      # markdown to stdout
refigure report.docx -o report.md         # markdown to a file
cat report.docx | refigure --format docx  # stdin, format hint required
refigure reports/ -o out/                 # batch: directory, walked recursively
refigure a.docx b.xlsx -o out/            # batch: 2+ explicit sources

Batch mode (2+ sources, or a single directory) requires -o DIR, keeps going past a failed source by default (--fail-fast aborts on the first one instead), and always prints a summary (N/M converted, K failed) to stderr. --json emits the full result — markdown plus chart/group counts and warnings — instead of plain markdown. -v/-q control verbosity; --strict is forwarded to the same Config.strict the Python API uses.

Exit codes:

Code Meaning
0 success
1 batch mode: 1+ sources failed (keep-going default)
2 usage error (bad arguments/flags)
3 input isn't a valid document of its format
4 input isn't a valid/safe archive
5 the format's extra ([docx]/[xlsx]) isn't installed
6 unexpected internal error

Real examples

Full convert() output on real, openly-licensed documents — not cherry-picked snippets. Each file's own header states its source, license and attribution.

Source Demonstrates Output
hackair-d7.7-pilot-evaluation.docx native chart extraction — 8 charts, 6 render as mermaid diagrams examples/hackair-native-charts.md
swd2018-254-marine-litter-ia-annex.docx combo: 1 chart (table-only — real verify+fallback in action, not every chart maps to mermaid) + 2 composite-figure zero-loss markers examples/swd2018-combo.md
govtech-2025-charts.xlsx XLSX at scale — 55 charts, 33 render as mermaid diagrams examples/govtech-xlsx-charts.md
swd2021-396-platform-work-ia.docx native pie chart — real EU-survey labels, all 8 charts render (3 as mermaid) examples/swd2021-pie-chart.md

Open any of these on GitHub and both views are right there: the raw ```mermaid fence an LLM/RAG pipeline would read, and its native GitHub rendering — no extra step, that's GitHub's own Markdown support.

Status

Pre-release. Tested against 27 real documents (15 DOCX + 12 XLSX) — 407 native charts found (400 rendered), 35 composite figures recovered as positioned zero-loss markers — see tests/integration/fixtures/manifest.yaml for provenance, licenses and attribution. CI gates on a combined unit+integration test-coverage floor of 95%.

The converters are being extracted from a working document-analysis pipeline (government AI-policy corpus); first public release planned for August 2026 as a single package with per-format extras ([docx] / [xlsx]). A [vlm] extra also exists (DOCX-only cloud interpretation of composite figures the chart engine can't reconstruct, Config(use_vlm=True), provider-agnostic — also needs the system soffice/LibreOffice binary, not installable via pip) — implemented and tested, but not active or announced as a v1 feature yet; no CLI flag exposes it.

PDF is out of scope, on purpose — a boundary, not a gap. PDF has no equivalent of OOXML's cached chart data (numCache/strCache) for any mainstream chart generator, so the native, rasterize-free extraction this project is built on doesn't transfer to it — confirmed by research into PDF's own structure and how leading PDF converters handle charts today, not assumed. For mixed-format corpora, route by extension instead of expecting one tool to cover everything — Docling or MarkItDown for PDF, refigure for DOCX/XLSX where the chart data actually survives in the file:

import refigure.docx
import refigure.xlsx

if path.suffix == ".pdf":
    markdown = docling_convert(path)      # or any PDF-capable converter
elif path.suffix == ".docx":
    markdown = refigure.docx.convert(path).markdown
else:
    markdown = refigure.xlsx.convert(path).markdown

v0.1.0 is packaged, CI-verified and ready — trusted publishing (GitHub↔PyPI, no stored tokens) is configured on both ends; publication itself is a separate, deliberate step not yet taken. Until then, PyPI name refigure still shows its 0.0.0 placeholder. refigure-md is a reserved alternate name, not an active release.

License

Apache-2.0 — see LICENSE and NOTICE.

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