# PDF to Text per Page – with Page Numbers for Citations

**Use case:** 

Extract the text of a PDF as one record per page, each with its page number, so your LLM app or search index can cite the exact page. Example uses an arXiv paper; replace it with any public PDF link.

## Input

```json
{
  "pdfUrls": [
    {
      "url": "https://arxiv.org/pdf/1706.03762"
    }
  ],
  "outputMode": "page",
  "chunkSize": 2000,
  "chunkOverlap": 200,
  "maxPages": 0,
  "maxFileSizeMb": 50,
  "includeMetadata": true,
  "maxConcurrency": 4
}
```

## Output

```json
{
  "url": {
    "label": "PDF",
    "format": "link"
  },
  "status": {
    "label": "Status"
  },
  "pageNumber": {
    "label": "Page"
  },
  "chunkIndex": {
    "label": "Chunk"
  },
  "charCount": {
    "label": "Chars",
    "format": "number"
  },
  "isLikelyScanned": {
    "label": "Scanned?",
    "format": "boolean"
  },
  "title": {
    "label": "Title"
  },
  "totalPages": {
    "label": "Pages",
    "format": "number"
  },
  "text": {
    "label": "Text"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The PDF to Text & RAG Chunks – PDF Text Extractor for LLMs Actor is ready to run with the inputs already set for "PDF to Text per Page – with Page Numbers for Citations". [Sign up or log in](https://console.apify.com/create-task-from-example/fyioZsb2V4nrlvp3x) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "PDF to Text per Page – with Page Numbers for Citations" task

The PDF to Text & RAG Chunks – PDF Text Extractor for LLMs Actor will start running based on the input automatically. You can also change all the input fields, like PDF URLs, output mode, and more, to match your specific use case.

### 3. Receive the "PDF to Text per Page – with Page Numbers for Citations" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as PDF, status, page, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "PDF to Text per Page – with Page Numbers for Citations" task via API](https://apify.com/mabun/pdf-text-extractor-rag.md).

## About this Actor

This example demonstrates how to use [PDF to Text & RAG Chunks – PDF Text Extractor for LLMs](https://apify.com/mabun/pdf-text-extractor-rag.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/mabun/pdf-text-extractor-rag.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/mabun/pdf-text-extractor-rag.md

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`).