Data Wizard’s data processing pipeline transforms unstructured documents into structured JSON data ready for use in your applications. This allows it to accept files in various formats without having to worry about the intricacies of each format.

​
Artifact Creation

The data processing begins when you upload files to Data Wizard, either through the embedded UI or programmatically via the API. Data Wizard supports various document formats, including:
  • PDF (.pdf)
  • Word Documents (.docx)
  • Excel Spreadsheets (.xlsx, .xls)
  • Images (.jpeg, .png, etc.)
Upon upload, Data Wizard performs initial pre-processing to create Artifacts. An Artifact is a unified representation of the document’s content, abstracting away the complexities of different file formats.

​
Artifact Structure

Each Artifact is essentially a directory (can be just virtual in memory) containing:
  • metadata.json: Metadata about the source file.
  • contents.json: A JSON file holding the structured content of the document, broken down into Slices.
  • source.<extension>: The original uploaded file.
  • [marked.pdf] (for PDFs): A marked version of the PDF with embedded images highlighted.
  • images/: Directory containing embedded images extracted from the document.
  • images_marked/: Directory containing marked versions of embedded images.
  • pages/: Directory containing screenshots of each page of the document.
  • pages_marked/: Directory containing marked screenshots of each page with highlighted embedded images.

​
contents.json Structure

The contents.json file is crucial. It structures the document content into Slices. A Slice represents a logical part of the document, such as:
  • text: Textual content, like paragraphs.
  • image: Embedded images.
  • page-image: Screenshots of entire pages.
  • page-image-marked: Marked page screenshots with highlighted embedded images.
Each Slice in contents.json includes:
  • page: The page number the slice belongs to.
  • type: The slice type (text, image, etc.).
  • text (for text slices): The text content.
  • path (for image slices): Path to the image file within the Artifact directory.
  • mimetype (for image slices): Image MIME type.
  • x, y, width, height (for image slices): Image dimensions and position on the page (if available).

​
Example contents.json structure

[
  {
    "page": 1,
    "type": "text",
    "text": "This is the text on the first page of the document. Lorem ipsum dolor sit amet..."
  },
  {
    "page": 1,
    "type": "image",
    "mimetype": "image/jpeg",
    "path": "images/image1.jpg",
    "x": 455.0,
    "y": 28.55999755859375,
    "width": 88.32000732421875,
    "height": 688.3200073242188
  },
  {
    "page": 1,
    "type": "page-image",
    "mimetype": "image/jpeg",
    "path": "pages/page1.jpg"
  },
  {
    "page": 1,
    "type": "page-image-marked",
    "mimetype": "image/jpeg",
    "path": "pages_marked/page1.jpg"
  }
]



Next Steps

Learn how to extract some data

Step by step guide to extract data from documents using Data Wizard.

Extractors

Learn how to define and configure data extraction tasks.

Strategies

Understand different data processing strategies.

LLM Provider Configuration

Set up your Large Language Model API keys.

Integration

Embed Data Wizard into other applications using iFrames or APIs.