The Schema Endpoint in Flora’s API enables users to define structured data formats for extracting information from unstructured sources like images, PDFs, text, and webpages. This endpoint serves as the foundation for how extracted data is formatted and returned.

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How It Works

  1. Define Your Schema: Create a JSON structure that outlines the fields and data types you want to extract.
  2. Use in Extraction Requests: Include the schema_id when submitting data for processing.
  3. Receive Structured Results: Flora extracts the information and returns it formatted according to your defined schema.

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Creating a Valid Schema

Developers have two options for creating a valid schema in Flora:
  1. Schema Builder Tool: For a visual, user-friendly experience, use our Schema Builder. This intuitive tool allows you to construct your schema graphically, ensuring all requirements are met without needing to write JSON manually.
  2. Manual JSON Creation: For those who prefer direct JSON manipulation or need more complex schemas, follow the guidelines below to craft your schema structure.
Whichever method you choose, ensure your schema adheres to Flora’s requirements for optimal data extraction results.

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Root Structure

Your schema should be a valid JSON object with a type field set to either "array" or "object".

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Array Type Schemas

For "array" type schemas:
  • Include an items field defining the structure of array elements.
  • The items field must be an object with its own type field ("object" or "array").
  • For "object" type items, include a properties field defining the object’s structure.
  • For nested "array" type items, include another items field.
Example: 
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "title": {
        "type": "string",
        "description": "Article title"
      },
      "publishDate": {
        "type": "string",
        "description": "Publication date"
      }
    }
  }
}

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Object Type Schemas

For "object" type schemas:
  • Include a properties field defining the object’s structure.
  • Each property should specify its type and optionally include a description.
Example: 
{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Full name of the person"
    },
    "age": {
      "type": "number",
      "description": "Age in years"
    }
  }
}

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Required Fields

Specify required property in the fields to indicate which fields are required: Example: 
{
  "type": "object",
  "properties": {
    "username": {
      "type": "string",
      "description": "User's unique identifier",
      "required": true
    },
    "email": {
      "type": "string",
      "description": "User's email address",
      "required": false
    }
  }
}

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Best Practices

  • Use clear, descriptive field names.
  • Include description for each field to improve clarity.
  • Keep your schema focused and avoid unnecessary complexity.
  • Test your schema with sample data to ensure it captures all required information.
By following these guidelines, you’ll create robust schemas that effectively structure your extracted data, enhancing the power and flexibility of your Flora API integrations.