undocx

Fast, accurate DOCX to Markdown converter built for LLM/RAG pipelines. Written in Rust with Python bindings.

• 16.5x faster than pandoc — 3.3ms per file average
• LLM-optimized — Clean Markdown output ready for embeddings, chunking, and retrieval
• Full fidelity — Tables, footnotes, track changes, images, nested lists, and more

For Humans • For Agents • Benchmarks • Features • Contributing

Conversion Demo

Click images to see full GitHub-rendered files.

Benchmarks

Measured on 39 DOCX files × 10 iterations (reproduce it yourself):

undocx is 16.5x faster than pandoc and 5.5x faster than markitdown.

For Humans

Install and convert — that's it.

pip install undocx          # Python
cargo install undocx        # CLI

CLI

undocx report.docx output.md              # convert to file
undocx report.docx                         # print to stdout
undocx report.docx -o out.md --images-dir ./img  # extract images

Python

import undocx

markdown = undocx.convert_docx("report.docx")

For Agents

Designed for document preprocessing in LLM/RAG pipelines.

Python — RAG ingestion

import undocx

# Skip images for text-only RAG ingestion
md = undocx.convert_docx("report.docx", image_handling="skip")

# Process bytes from S3, HTTP, or any byte stream
md = undocx.convert_docx(doc_bytes, image_handling="skip")

Rust — One-liner

let md = undocx::convert("report.docx")?;
let md = undocx::convert_bytes(&bytes)?;

Rust — Builder (optimal for RAG)

let md = undocx::builder()
    .skip_images()
    .convert("report.docx")?;

Rust — Pluggable architecture

let converter = DocxToMarkdown::with_components(
    ConvertOptions::default(),
    MyExtractor,    // impl AstExtractor
    MyRenderer,     // impl Renderer
);

See docs/API_POLICY.md for stability guarantees on these traits.

# Cargo.toml
[dependencies]
undocx = "0.4"

Tips for RAG pipelines:

• Use image_handling="skip" to reduce token count
• Output is clean Markdown — split on ## headers for semantic chunking
• Footnotes and comments are preserved as [^ref] for full context

Supported Features

Options

Development

cargo test --all-features                                  # test
cargo clippy --all-features --tests -- -D warnings         # lint
python examples/benchmark_comparison.py ./tests/pandoc 10  # bench

See CONTRIBUTING.md for development setup and guidelines.

License

MIT — see LICENSE