anytomd 0.6.1

Pure Rust library that converts various document formats into Markdown
Documentation

anytomd

A pure Rust tool and library that converts various document formats into Markdown — designed for LLM consumption.

CI Crates.io License

Why?

MarkItDown is a great Python library for converting documents to Markdown. But integrating Python into Rust applications means bundling a Python runtime (~50 MB), dealing with cross-platform compatibility issues, and managing dependency hell.

anytomd solves this with a single cargo add anytomd — zero external runtime, no C bindings, no subprocess calls. Just pure Rust.

Supported Formats

Format Extensions Notes
DOCX .docx Headings, tables, lists, bold/italic, hyperlinks, images
PPTX .pptx Slides, tables, speaker notes, images
XLSX .xlsx Multi-sheet, date/time handling, images
XLS .xls Legacy Excel (via calamine)
HTML .html, .htm Full DOM: headings, tables, lists, links, blockquotes, code blocks
CSV .csv Converted to Markdown tables
JSON .json Pretty-printed in fenced code blocks
XML .xml Pretty-printed in fenced code blocks
Images .png, .jpg, .gif, .webp, .bmp, .tiff, .svg, .heic, .avif Optional LLM-based alt text via ImageDescriber
Plain Text .txt, .md, .rst, .log, .toml, .yaml, .ini, etc. Passthrough with encoding detection (UTF-8, UTF-16, Windows-1252)

Note on PDF: PDF conversion is intentionally out of scope. Gemini, ChatGPT, and Claude already provide native PDF support (with plan/model-specific limits), so anytomd focuses on formats that still benefit from dedicated Markdown conversion.

Format is auto-detected from magic bytes and file extension. ZIP-based formats (DOCX/PPTX/XLSX) are distinguished by inspecting internal archive structure.

Installation

cargo add anytomd

Feature Flags

Feature Dependencies Description
(default) Sync API only
async futures-util Async API (convert_file_async, convert_bytes_async, AsyncImageDescriber trait)
async-gemini async + reqwest AsyncGeminiDescriber for concurrent image descriptions via Gemini
# Async image descriptions with Gemini
cargo add anytomd --features async-gemini

CLI

Install

cargo install anytomd

Usage

# Convert a single file
anytomd document.docx > output.md

# Convert multiple files (separated by <!-- source: path --> comments)
anytomd report.docx data.csv slides.pptx > combined.md

# Write output to a file
anytomd document.docx -o output.md

# Read from stdin (--format is required)
cat data.csv | anytomd --format csv

# Override format detection
anytomd --format html page.dat

# Strict mode: treat recoverable errors as hard errors
anytomd --strict document.docx

# Auto image descriptions (just set GEMINI_API_KEY)
export GEMINI_API_KEY=your-key
anytomd presentation.pptx

Exit Codes

Code Meaning
0 Success
1 Conversion failure
2 Invalid arguments

Quick Start (Library)

use anytomd::{convert_file, convert_bytes, ConversionOptions};

// Convert a file (format auto-detected from extension and magic bytes)
let options = ConversionOptions::default();
let result = convert_file("document.docx", &options).unwrap();
println!("{}", result.markdown);

// Convert raw bytes with an explicit format
let csv_data = b"Name,Age\nAlice,30\nBob,25";
let result = convert_bytes(csv_data, "csv", &options).unwrap();
println!("{}", result.markdown);

Extracting Embedded Images

use anytomd::{convert_file, ConversionOptions};

let options = ConversionOptions {
    extract_images: true,
    ..Default::default()
};
let result = convert_file("presentation.pptx", &options).unwrap();

for (filename, bytes) in &result.images {
    std::fs::write(filename, bytes).unwrap();
}

LLM-Based Image Descriptions

anytomd can generate alt text for images using any LLM backend via the ImageDescriber trait. A built-in Google Gemini implementation is included.

use std::sync::Arc;
use anytomd::{convert_file, ConversionOptions, ImageDescriber, ConvertError};
use anytomd::gemini::GeminiDescriber;

// Option 1: Use the built-in Gemini describer
let describer = GeminiDescriber::from_env()  // reads GEMINI_API_KEY
    .unwrap()
    .with_model("gemini-3-flash-preview".to_string());

let options = ConversionOptions {
    image_describer: Some(Arc::new(describer)),
    ..Default::default()
};
let result = convert_file("document.docx", &options).unwrap();
// Images now have LLM-generated alt text: ![A chart showing quarterly revenue](chart.png)

// Option 2: Implement your own describer for any backend
struct MyDescriber;

impl ImageDescriber for MyDescriber {
    fn describe(
        &self,
        image_bytes: &[u8],
        mime_type: &str,
        prompt: &str,
    ) -> Result<String, ConvertError> {
        // Call your preferred LLM API here
        Ok("description of the image".to_string())
    }
}

Async Image Descriptions

For documents with many images, the async API resolves all descriptions concurrently. Requires the async feature (or async-gemini for the built-in Gemini describer).

use std::sync::Arc;
use anytomd::{convert_file_async, AsyncConversionOptions, AsyncImageDescriber, ConvertError};
use anytomd::gemini::AsyncGeminiDescriber;  // requires `async-gemini` feature

#[tokio::main]
async fn main() {
    let describer = AsyncGeminiDescriber::from_env().unwrap();

    let options = AsyncConversionOptions {
        async_image_describer: Some(Arc::new(describer)),
        ..Default::default()
    };

    let result = convert_file_async("presentation.pptx", &options).await.unwrap();
    println!("{}", result.markdown);
    // All images described concurrently — significant speedup for multi-image documents
}

The library has no tokio dependency — the caller provides the async runtime. Any runtime (tokio, async-std, etc.) works.

API

convert_file

/// Convert a file at the given path to Markdown.
/// Format is auto-detected from magic bytes and file extension.
pub fn convert_file(
    path: impl AsRef<Path>,
    options: &ConversionOptions,
) -> Result<ConversionResult, ConvertError>

convert_bytes

/// Convert raw bytes to Markdown with an explicit format extension.
pub fn convert_bytes(
    data: &[u8],
    extension: &str,
    options: &ConversionOptions,
) -> Result<ConversionResult, ConvertError>

convert_file_async

Requires the async feature.

/// Convert a file at the given path to Markdown with async image description.
/// If an async_image_describer is set, all image descriptions are resolved concurrently.
pub async fn convert_file_async(
    path: impl AsRef<Path>,
    options: &AsyncConversionOptions,
) -> Result<ConversionResult, ConvertError>

convert_bytes_async

Requires the async feature.

/// Convert raw bytes to Markdown with async image description.
pub async fn convert_bytes_async(
    data: &[u8],
    extension: &str,
    options: &AsyncConversionOptions,
) -> Result<ConversionResult, ConvertError>

ConversionOptions

Field Type Default Description
extract_images bool false Extract embedded images into result.images
max_total_image_bytes usize 50 MB Hard cap for total extracted image bytes
max_input_bytes usize 100 MB Maximum input file size
max_uncompressed_zip_bytes usize 500 MB ZIP bomb guard
strict bool false Error on recoverable failures instead of warnings
image_describer Option<Arc<dyn ImageDescriber>> None LLM backend for image alt text generation

ConversionResult

pub struct ConversionResult {
    pub markdown: String,                  // The converted Markdown
    pub title: Option<String>,             // Document title, if detected
    pub images: Vec<(String, Vec<u8>)>,    // Extracted images (filename, bytes)
    pub warnings: Vec<ConversionWarning>,  // Recoverable issues encountered
}

Error Handling

Conversion is best-effort by default. If a single element fails to parse (e.g., a corrupted table), it is skipped and a warning is added to result.warnings. The rest of the document is still converted.

Set strict: true in ConversionOptions to turn recoverable failures into errors instead.

Warning codes: SkippedElement, UnsupportedFeature, ResourceLimitReached, MalformedSegment.

Development

Build and Test

cargo build && cargo test && cargo clippy -- -D warnings

Docker

A Docker environment is available for reproducible Linux builds:

docker compose run --rm verify    # Full loop: fmt + clippy + test + release build
docker compose run --rm test      # Run all tests
docker compose run --rm lint      # clippy + fmt check
docker compose run --rm shell     # Interactive bash

License

Apache-2.0