# Document Parser — PDF/DOCX to Markdown & JSON for RAG (`genuine_qa/document-parser`) Actor

Convert PDF, DOCX, PPTX, XLSX, HTML and images into clean Markdown or JSON for RAG and LLM pipelines. Powered by IBM's open-source Docling.

- **URL**: https://apify.com/genuine\_qa/document-parser.md
- **Developed by:** [Rahul Bhiwagade](https://apify.com/genuine_qa) (community)
- **Categories:** Agents, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.00001 / actor start

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use 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 Parser — PDF, DOCX & more → Markdown / JSON for RAG & LLMs

Turn messy documents into clean, structured **Markdown** or **JSON** that's ready
to drop straight into RAG pipelines, vector databases, and LLM prompts.

Send one or more document URLs and get back well-structured content with
**headings, lists, reading order, and real tables preserved** — powered by
state-of-the-art open-source document-AI models for layout analysis and table
structure recognition.

No local setup, no GPU, no model wrangling. Just URLs in, clean text out.

---

### ✨ Why use this

- **Built for RAG / LLMs** — Markdown output drops cleanly into prompts and chunkers; JSON output gives you structured elements for custom pipelines.
- **Real table extraction** — tables come back as proper Markdown tables (rows/columns intact), not jumbled text.
- **Layout-aware** — detects headings, lists, captions, and correct reading order across multi-column pages.
- **Many formats, one Actor** — PDF, Word, PowerPoint, Excel, HTML, and images.
- **Robust** — each document is processed independently; one bad URL never fails the whole run, and errors come back with a clear, human-readable reason.
- **Optional OCR** — extract text from scanned or image-only PDFs.

### 📄 Supported formats

| Type | Extensions |
|---|---|
| PDF | `.pdf` |
| Word | `.docx` |
| PowerPoint | `.pptx` |
| Excel | `.xlsx` |
| Web / markup | `.html`, `.md` |
| Images | `.png`, `.jpg`, `.tiff` (with OCR) |

### 💡 Common use cases

- **RAG ingestion** — convert a library of PDFs/Docs into Markdown for chunking and embedding.
- **Knowledge bases & search** — extract clean, structured text from reports, manuals, and contracts.
- **LLM context** — feed papers, datasheets, or filings to a model without copy-paste noise.
- **Dataset building** — turn document collections into structured JSON for training or analysis.
- **Table harvesting** — pull tables out of financial reports or research papers as usable Markdown.

---

### 🚀 How to use

#### From the Apify Console
1. Click **Try for free / Start**.
2. Paste one or more **Document URLs** (direct links to the files).
3. Pick an **Output format** — `markdown`, `json`, or `both`.
4. (Optional) Turn on **OCR** for scanned/image PDFs.
5. Click **Start** and grab the results from the **Dataset** tab (export as JSON, CSV, Excel, or via API).

#### Input

| Field | Type | Required | Description |
|---|---|:---:|---|
| `documentUrls` | array of strings | ✅ | Direct URLs to the documents to convert. |
| `outputFormat` | `markdown` \| `json` \| `both` | | Output format. Default: `markdown`. |
| `doOcr` | boolean | | Run OCR on scanned/image PDFs (slower). Default: `false`. |

**Example input**

```json
{
  "documentUrls": [
    "https://arxiv.org/pdf/2408.09869",
    "https://www.example.com/report.pdf"
  ],
  "outputFormat": "both",
  "doOcr": false
}
````

#### Output

One dataset item per document:

```json
{
  "url": "https://arxiv.org/pdf/2408.09869",
  "status": "success",
  "markdown": "## Abstract\n\nThis technical report introduces ...",
  "json": { "schema_name": "DoclingDocument", "texts": [ ... ], "tables": [ ... ] }
}
```

If a document can't be processed, you get a clear error instead of a crash:

```json
{
  "url": "https://example.com/locked.pdf",
  "status": "error",
  "error": "Download failed with HTTP 403. The URL may be private, expired, or protected (e.g. Cloudflare/login). Provide a direct, publicly accessible document link."
}
```

***

### 🔌 Use the results via API

Run the Actor and read its output from your own code with the
[Apify API client](https://docs.apify.com/api/client/python/):

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("genuine_qa/document-parser").call(run_input={
    "documentUrls": ["https://arxiv.org/pdf/2408.09869"],
    "outputFormat": "markdown",
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    if item["status"] == "success":
        print(item["markdown"])
    else:
        print("Failed:", item["url"], "->", item["error"])
```

You can also export results directly as JSON/CSV/Excel from the dataset's
**Export** button, or pull them from the
[Dataset API](https://docs.apify.com/api/v2#/reference/datasets).

***

### ⚙️ Tips & performance

- **Memory:** the conversion models need room — run with **4 GB+** memory for reliable results, more for large or OCR-heavy documents.
- **First page is slowest:** models load once per run, so converting many documents in a single run is more efficient than one run per document.
- **OCR is heavier:** only enable `doOcr` when documents are scanned or image-based — it's significantly slower than parsing digital text.
- **Use direct links:** point to the actual file URL. Pages behind logins, paywalls, or anti-bot challenges (e.g. Cloudflare) can't be downloaded and will return a clear error.

### ❓ FAQ

**Does it handle scanned PDFs?**
Yes — enable `doOcr`. For digital (text-based) PDFs, leave it off for much faster, higher-fidelity results.

**Are tables preserved?**
Yes. Tables are reconstructed and emitted as Markdown tables, and as structured cells in the JSON output.

**Can I process many documents at once?**
Yes — pass multiple URLs in `documentUrls`. Each becomes its own dataset item.

**What happens if one URL is bad?**
That single document is marked `"status": "error"` with a readable message; the rest of the run continues normally.

**Do my documents leave the run?**
The Actor downloads each URL you provide, converts it inside the run, and writes the result to your dataset. It doesn't send your documents anywhere else.

# Actor input Schema

## `documentUrls` (type: `array`):

Direct URLs to documents to convert. Supports PDF, DOCX, PPTX, XLSX, HTML, Markdown and images.

## `outputFormat` (type: `string`):

Format of the converted output stored in the dataset.

## `doOcr` (type: `boolean`):

Run OCR to read text from scanned or image-based PDFs. Slower and more resource-intensive.

## Actor input object example

```json
{
  "documentUrls": [
    "https://arxiv.org/pdf/2408.09869"
  ],
  "outputFormat": "markdown",
  "doOcr": false
}
```

# 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 = {
    "documentUrls": [
        "https://arxiv.org/pdf/2408.09869"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("genuine_qa/document-parser").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 = { "documentUrls": ["https://arxiv.org/pdf/2408.09869"] }

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

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

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

```

## CLI example

```bash
echo '{
  "documentUrls": [
    "https://arxiv.org/pdf/2408.09869"
  ]
}' |
apify call genuine_qa/document-parser --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=genuine_qa/document-parser",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Document Parser — PDF/DOCX to Markdown & JSON for RAG",
        "description": "Convert PDF, DOCX, PPTX, XLSX, HTML and images into clean Markdown or JSON for RAG and LLM pipelines. Powered by IBM's open-source Docling.",
        "version": "0.1",
        "x-build-id": "HTfdPM2GqGH9oB88L"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/genuine_qa~document-parser/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-genuine_qa-document-parser",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/genuine_qa~document-parser/runs": {
            "post": {
                "operationId": "runs-sync-genuine_qa-document-parser",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/genuine_qa~document-parser/run-sync": {
            "post": {
                "operationId": "run-sync-genuine_qa-document-parser",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "required": [
                    "documentUrls"
                ],
                "properties": {
                    "documentUrls": {
                        "title": "Document URLs",
                        "type": "array",
                        "description": "Direct URLs to documents to convert. Supports PDF, DOCX, PPTX, XLSX, HTML, Markdown and images.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "outputFormat": {
                        "title": "Output format",
                        "enum": [
                            "markdown",
                            "json",
                            "both"
                        ],
                        "type": "string",
                        "description": "Format of the converted output stored in the dataset.",
                        "default": "markdown"
                    },
                    "doOcr": {
                        "title": "Enable OCR (for scanned / image PDFs)",
                        "type": "boolean",
                        "description": "Run OCR to read text from scanned or image-based PDFs. Slower and more resource-intensive.",
                        "default": false
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```