# Document to Markdown for LLMs and RAG (no file retention) (`hushvert/document-to-markdown`) Actor

Convert PDF, DOCX, PPTX, XLSX, HTML, EPUB, RST and LaTeX to clean Markdown for LLM context windows, RAG ingestion and agent pipelines. The Markdown rides inline in the dataset item - no second fetch. Privacy-first: inputs deleted at conversion end, outputs within an hour, failed runs never charge.

- **URL**: https://apify.com/hushvert/document-to-markdown.md
- **Developed by:** [Nir Diamant](https://apify.com/hushvert) (community)
- **Categories:** AI, Agents, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$150.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Document to Markdown for LLMs and RAG (no file retention)

One actor, eight input formats: PDF, DOCX, PPTX, XLSX, HTML, EPUB, RST, and
LaTeX in; clean Markdown out. Built for RAG ingestion and agent pipelines: the
Markdown also rides INLINE in the dataset item (`markdown` field), so the next
step of your pipeline reads it straight from the dataset with no second fetch.

### Why this converter

- **The whole intake funnel, one listing.** Point your pipeline at this actor
  and feed it whatever your users upload; the format is picked from the file
  extension. No per-format actor zoo.
- **Reading order that survives two-column PDFs.** The PDF path runs a layout
  pass first, then a structured conversion, keeping multi-column pages in true
  reading order instead of interleaving the columns line by line - the failure
  mode that silently poisons RAG chunks.
- **Inline output.** One dataset row per document with the Markdown in it
  (capped at 1 MB inline; bigger outputs set `markdownTruncated: true` and the
  full file is always in the key-value store).
- **No file retention.** The input is deleted the moment the conversion
  finishes. The output file is kept for about an hour, then deleted. Your
  documents are not stored, mined, or used for anything.
- **Failed runs never charge.** One dataset item per successful conversion; a
  failure produces no item and no charge.

### How do I convert documents to Markdown on Apify?

1. Press **Start** with the prefilled sample, or paste your own direct file URL
   (any of the eight formats).
2. Wait for the run to finish; a typical document takes 10 to 20 seconds.
3. Read the `markdown` field straight from the dataset row, or download the
   .md file from the run's **Storage** tab (the `OUTPUT` record).

### Input

```json
{
  "fileUrl": "https://example.com/report.docx"
}
```

- `fileUrl` (required): direct http(s) URL of the document, up to 50 MB. The
  format comes from the extension (`.pdf`, `.docx`, `.pptx`, `.xlsx`, `.html`,
  `.epub`, `.rst`, `.tex`).
- `fileName` (optional): set it when the URL has no usable extension; it picks
  the input format and names the output.
- `maxWaitSeconds` (optional): how long to wait before failing, default 300.

### Output

- One dataset row per successful conversion: `pair`, `fileName`,
  `outputFileName`, `inputBytes`, `outputBytes`, `durationSeconds`,
  `outputUrl`, plus the converted `markdown` inline (and `markdownTruncated`).
- The full .md file is stored as the `OUTPUT` record of the run's key-value
  store (the dataset row carries its direct `outputUrl`).

### How much does it cost?

$0.15 per successful conversion, platform usage included - the price you see
is the whole price. A failed run produces no dataset item and no charge. A free
Apify account is enough to use it; conversions bill against your Apify usage
balance.

### Run it from code

JavaScript ([apify-client](https://docs.apify.com/api/client/js/)):

```js
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hushvert/document-to-markdown').call({
  fileUrl: 'https://example.com/report.docx',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0].markdown); // the converted Markdown, inline
```

Python ([apify-client](https://docs.apify.com/api/client/python/)):

```python
from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('hushvert/document-to-markdown').call(
    run_input={'fileUrl': 'https://example.com/report.docx'})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items[0]['markdown'])
```

Plain HTTP (one call, returns the dataset row with the Markdown inline):

```bash
curl -X POST \
  'https://api.apify.com/v2/acts/hushvert~document-to-markdown/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN' \
  -H 'content-type: application/json' \
  -d '{"fileUrl": "https://example.com/report.docx"}'
```

### Can I use it from n8n, Make, Zapier, or LangChain?

Yes. Like any Apify actor, it plugs into
[n8n](https://docs.apify.com/platform/integrations/n8n),
[Make](https://docs.apify.com/platform/integrations/make),
[Zapier](https://docs.apify.com/platform/integrations/zapier), and
[LangChain](https://docs.apify.com/platform/integrations/langchain) through
Apify's official integrations; select the actor by name,
`hushvert/document-to-markdown`. AI agents can also call it as a tool through
[Apify's MCP server](https://docs.apify.com/platform/integrations/mcp), which
makes it a natural document-intake step for agent pipelines: file URL in,
Markdown out, straight from the dataset.

### Is it private?

- The conversion runs on hushvert's server lane, not inside this actor. PDF
  rides a layout pass + structured pandoc chain; DOCX/HTML/EPUB/RST/LaTeX ride
  pandoc; PPTX/XLSX ride markitdown. Retention: inputs deleted at conversion
  end, outputs auto-deleted after about an hour.
- Your documents are never stored beyond that window, never mined, and never
  used to train anything.

### FAQ

#### Does it OCR scanned PDFs?

No, and it says so instead of guessing: scanned or image-only PDFs fail loudly
with `no_ocr` and are never charged. There is no OCR step.

#### Which format should I send when the URL has no extension?

Set `fileName` with the right extension (for example `report.pdf`); it picks
the input format and names the output.

#### How big can the inline `markdown` field get?

Up to 1 MB inline. Bigger outputs set `markdownTruncated: true` and the full
file is always in the key-value store at `outputUrl`.

#### What is the file size limit?

50 MB per file.

#### What happens when a conversion fails?

The run fails with the converter's real error message, produces no dataset
item, and charges nothing.

### More private converters from hushvert

- [PDF to Markdown](https://apify.com/hushvert/pdf-to-markdown): the dedicated
  PDF lane with the same reading-order guarantee.
- [PDF to DOCX](https://apify.com/hushvert/pdf-to-docx): PDF back to editable
  Word, real text and tables, correct Hebrew/Arabic reading order.
- [DOCX to PDF](https://apify.com/hushvert/docx-to-pdf): Word to PDF.
- [Office to PDF](https://apify.com/hushvert/office-to-pdf): Word, Excel,
  PowerPoint, OpenDocument, RTF, HTML in; PDF out.
- [HTML to PDF](https://apify.com/hushvert/html-to-pdf): real Chromium render,
  paste HTML inline for invoices and reports.
- [Video to MP4](https://apify.com/hushvert/video-to-mp4): MOV, MKV, WEBM, AVI,
  GIF to universal MP4, files up to 500 MB.

### Who is behind this actor?

Built by the hushvert founder. The browser-side conversion engine is MIT open
source (`@hushvert/engine` on npm); formats a browser can convert (images, HEIC,
audio, archives, PDF page ops) are free and client-side at
https://hushvert.com and are deliberately not sold here. Developer API docs:
https://hushvert.com/for-developers

# Actor input Schema

## `fileUrl` (type: `string`):

Direct http(s) download URL of the document. The format is inferred from the file extension. The file is fetched once, converted, and the input is deleted the moment the conversion finishes.

## `fileName` (type: `string`):

Set this when the URL has no usable extension, e.g. report.docx; it picks the input format and names the output.

## `maxWaitSeconds` (type: `integer`):

How long to wait for the conversion before failing. Default 300.

## Actor input object example

```json
{
  "fileUrl": "https://hushvert.com/samples/sample.pdf"
}
```

# Actor output Schema

## `convertedFile` (type: `string`):

The converted Markdown, stored as the OUTPUT record of the run's key-value store (also inline in the dataset row as `markdown`).

## `conversions` (type: `string`):

One dataset row per successful conversion: file names, byte counts, duration.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "fileUrl": "https://hushvert.com/samples/sample.pdf"
};

// Run the Actor and wait for it to finish
const run = await client.actor("hushvert/document-to-markdown").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "fileUrl": "https://hushvert.com/samples/sample.pdf" }

# Run the Actor and wait for it to finish
run = client.actor("hushvert/document-to-markdown").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "fileUrl": "https://hushvert.com/samples/sample.pdf"
}' |
apify call hushvert/document-to-markdown --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,hushvert/document-to-markdown"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/XHzPawnJz4yt3C1Hg/builds/R9mWGkauTv6y0PVw3/openapi.json