# Images and scans to text chunks for RAG and vector databases

**Use case:** 

OCR images and scanned PDFs and split the text into chunks with page numbers, ready for a vector database or an AI agent. PDF pages that already have text are read without OCR at a lower price. Replace the example links with your own files.

## Input

```json
{
  "urls": [
    {
      "url": "https://raw.githubusercontent.com/tesseract-ocr/test/main/testing/phototest.tif"
    },
    {
      "url": "https://raw.githubusercontent.com/tesseract-ocr/test/main/testing/8087_054.3B.tif"
    }
  ],
  "languages": [
    "eng"
  ],
  "outputFormat": "chunks",
  "searchablePdf": false,
  "includeWords": false,
  "autoRotate": true,
  "ocrAllPages": false,
  "maxPagesPerDocument": 0,
  "chunkSize": 1000,
  "chunkOverlap": 100
}
```

## Output

```json
{
  "fileName": {
    "label": "File",
    "format": "string"
  },
  "fileType": {
    "label": "Type",
    "format": "string"
  },
  "pageCount": {
    "label": "Pages",
    "format": "integer"
  },
  "pagesOcr": {
    "label": "OCR pages",
    "format": "integer"
  },
  "pagesTextLayer": {
    "label": "Text-layer pages",
    "format": "integer"
  },
  "meanConfidence": {
    "label": "Confidence",
    "format": "number"
  },
  "charCount": {
    "label": "Characters",
    "format": "integer"
  },
  "chunkIndex": {
    "label": "Chunk",
    "format": "integer"
  },
  "pageStart": {
    "label": "From page",
    "format": "integer"
  },
  "pageEnd": {
    "label": "To page",
    "format": "integer"
  },
  "searchablePdfUrl": {
    "label": "Searchable PDF",
    "format": "string"
  },
  "error": {
    "label": "Error",
    "format": "string"
  },
  "url": {
    "label": "URL",
    "format": "string"
  }
}
```

## How it works

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

The PDF OCR: Scanned PDF & Image to Text, Searchable PDF Actor is ready to run with the inputs already set for "Images and scans to text chunks for RAG and vector databases". [Sign up or log in](https://console.apify.com/create-task-from-example/YkuEtYzzl8AIm18xV) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Images and scans to text chunks for RAG and vector databases" task

The PDF OCR: Scanned PDF & Image to Text, Searchable PDF Actor will start running based on the input automatically. You can also change all the input fields, like image or pdf urls, languages, and more, to match your specific use case.

### 3. Receive the "Images and scans to text chunks for RAG and vector databases" 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 file, type, pages, 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 "Images and scans to text chunks for RAG and vector databases" task via API](https://apify.com/tamatama/image-pdf-ocr.md).

## About this Actor

This example demonstrates how to use [PDF OCR: Scanned PDF & Image to Text, Searchable PDF](https://apify.com/tamatama/image-pdf-ocr.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/tamatama/image-pdf-ocr.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/tamatama/image-pdf-ocr.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`).