# PaddleOCR VL (`yeekal/paddleocr-vl`) Actor

- **URL**: https://apify.com/yeekal/paddleocr-vl.md
- **Developed by:** [yeekal](https://apify.com/yeekal) (community)
- **Categories:** AI, Developer tools
- **Features:** Full permissions
- **Stats:** 11 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $30.00 / 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Paddle OCR Layout Parser

This Apify Actor provides a powerful interface to the Paddle OCR Layout Parsing API. It allows you to submit an image or a PDF file via a URL and receive structured Markdown content, with all embedded images correctly linked via their absolute URLs. It also provides a visual representation of the parsed layout.

### Features

- **Supports Images and PDFs**: Process various image formats (PNG, JPG, etc.) and multi-page PDF documents.
- **Smart File Type Detection**: Automatically determines the file type from the URL, or you can specify it manually.
- **Markdown Content Extraction**: Extracts the full textual content and structure of the document into clean Markdown.
- **Layout Visualization**: Provides a URL to an image that visually highlights the detected layout structure (titles, paragraphs, figures, tables).
- **File Size Limit**: Protects against oversized files by enforcing a 5MB limit.

### Input

The Actor requires the following inputs, which are defined in the `Input` tab.

| Field | Type | Description |
| --- | --- | --- |
| **File URL** (`fileUrl`) | String | **Required.** A publicly accessible URL to the image or PDF file you want to process. The file size must not exceed 5MB. |
| **File Type** (`fileType`) | String | The type of the file. It's recommended to leave this as `Autodetect`. Options: `Autodetect`, `Image`, `PDF`. |

### Output

The Actor stores its results in the Apify default dataset. Each item in the dataset corresponds to a page from the input file.

#### Output Structure (JSON)

````json
[
  {
    "pageNumber": 1,
    "processedMarkdown": "## This is the Title\n\nAnd this is a paragraph of text. Here is an image:\n\n<div style=\"text-align: center;\"><img src=\"https://example.com/path/to/image.jpg\" alt=\"Image\" width=\"50%\" /></div>",
    "layoutImageUrl": "https://example.com/path/to/layout_visualization.jpg",
  }
]```

- `processedMarkdown`: The primary output. Ready-to-render Markdown with absolute image URLs.
- `layoutImageUrl`: A URL to an image visualizing the detected document layout.



# Actor input Schema

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

Publicly accessible URL of the image or PDF file to process. The file size must not exceed 5MB.
## `fileType` (type: `string`):

Specify the type of the file. 'Autodetect' is recommended.
## `fileBase64` (type: `string`):

Base64 buffer string of the image or PDF file to process. The file size must not exceed 5MB.

## Actor input object example

```json
{
  "fileUrl": "https://cdn.deepseekocr.io/home/doc_markdown.webp",
  "fileType": "image"
}
````

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("yeekal/paddleocr-vl").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("yeekal/paddleocr-vl").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 '{}' |
apify call yeekal/paddleocr-vl --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,yeekal/paddleocr-vl"
        }
    }
}
```

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/QUTeruze22OvNLK2a/builds/wrZjfO7N3TaAasJ8W/openapi.json