PDF to JSON OCR API

API ID 14067

Convert any PDF document with or without images into structured JSON output with built-in OCR features of the API. The API is best suited for LLM training and dataset creation.

623 ms avg response

API Documentation

Endpoints

Request
The "Convert PDF-to-JSON" endpoint is designed to transform PDF documents into structured JSON format, enabling developers and applications to easily extract and manipulate the data contained within these files. This endpoint processes the input PDF by parsing its elements—such as text, images, and metadata—and organizes the extracted information into a JSON object that maintains the context and hierarchy of the original content. Common use cases include transforming PDF reports, invoices, and contracts into a format suitable for integration with web applications, data analysis platforms, or machine learning models, facilitating further data processing and analysis tasks in a streamlined and accessible manner. Turn on OCR forcefully by selecting true for OCR param. By default it is auto.
Endpoint ID: 34500
POST https://zylalabs.com/api/14067/pdf+to+json+ocr+api/34500/convert+pdf-to-json
INPUT PARAMETERS

Convert PDF-to-JSON — Endpoint Features

Object Description
ocr Required true for force OCR, false for no OCR
Request Body Required File Binary

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

ocr
API EXAMPLE RESPONSE
JSON
{
    "success": true,
    "data": {
        "id": "229defbb-0cee-6f02-673a-5cde290d0673",
        "request_id": "eb27e3e4-fdb9-430f-81b1-240d6fa4ef75",
        "file_name": "xf59uBNVuQFZOzFcqztKJBLC5iO7FTFwRZXwxRqH",
        "page_count": 1,
        "total_pages": 1,
        "title": "sample",
        "pages": [
            {
                "page_number": 1,
                "extraction_method": "text",
                "blocks": [
                    {
                        "type": "paragraph",
                        "text": "Sample PDF This is a simple PDF file. Fun fun fun."
                    },
                    {
                        "type": "paragraph",
                        "text": "Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Phasellus facilisis odio sed mi."
                    },
                    {
                        "type": "paragraph",
                        "text": "Curabitur suscipit. Nullam vel nisi. Etiam semper ipsum ut lectus. Proin aliquam, erat eget pharetra commodo, eros mi condimentum quam, sed commodo justo quam ut velit."
                    },
                    {
                        "type": "paragraph",
                        "text": "Integer a erat. Cras laoreet ligula cursus enim. Aenean scelerisque velit et tellus."
                    },
                    {
                        "type": "paragraph",
                        "text": "Vestibulum dictum aliquet sem. Nulla facilisi. Vestibulum accumsan ante vitae elit. Nulla erat dolor, blandit in, rutrum quis, semper pulvinar, enim. Nullam varius congue risus."
                    },
                    {
                        "type": "paragraph",
                        "text": "Vivamus sollicitudin, metus ut interdum eleifend, nisi tellus pellentesque elit, tristique accumsan eros quam et risus. Suspendisse libero odio, mattis sit amet, aliquet eget, hendrerit vel, nulla. Sed vitae augue. Aliquam erat volutpat. Aliquam feugiat vulputate nisl."
                    },
                    {
                        "type": "paragraph",
                        "text": "Suspendisse quis nulla pretium ante pretium mollis. Proin velit ligula, sagittis at, egestas a, pulvinar quis, nisl."
                    },
                    {
                        "type": "paragraph",
                        "text": "Pellentesque sit amet lectus. Praesent pulvinar, nunc quis iaculis sagittis, justo quam lobortis tortor, sed vestibulum dui metus venenatis est. Nunc cursus ligula. Nulla facilisi."
                    },
                    {
                        "type": "paragraph",
                        "text": "Phasellus ullamcorper consectetuer ante. Duis tincidunt, urna id condimentum luctus, nibh ante vulputate sapien, id sagittis massa orci ut enim. Pellentesque vestibulum convallis sem. Nulla consequat quam ut nisl. Nullam est. Curabitur tincidunt dapibus lorem. Proin velit turpis, scelerisque sit amet, iaculis nec, rhoncus ac, ipsum. Phasellus lorem arcu, feugiat eu, gravida eu, consequat molestie, ipsum. Nullam vel est ut ipsum volutpat feugiat. Aenean pellentesque."
                    },
                    {
                        "type": "paragraph",
                        "text": "In mauris. Pellentesque dui nisi, iaculis eu, rhoncus in, venenatis ac, ante. Ut odio justo, scelerisque vel, facilisis non, commodo a, pede. Cras nec massa sit amet tortor volutpat varius. Donec lacinia, neque a luctus aliquet, pede massa imperdiet ante, at varius lorem pede sed sapien. Fusce erat nibh, aliquet in, eleifend eget, commodo eget, erat. Fusce consectetuer. Cras risus tortor, porttitor nec, tristique sed, convallis semper, eros. Fusce vulputate ipsum a mauris. Phasellus mollis. Curabitur sed urna. Aliquam nec sapien non nibh pulvinar convallis. Vivamus facilisis augue quis quam. Proin cursus aliquet metus."
                    },
                    {
                        "type": "paragraph",
                        "text": "Suspendisse lacinia. Nulla at tellus ac turpis eleifend scelerisque. Maecenas a pede vitae enim commodo interdum. Donec odio. Sed sollicitudin dui vitae justo."
                    },
                    {
                        "type": "paragraph",
                        "text": "Morbi elit nunc, facilisis a, mollis a, molestie at, lectus. Suspendisse eget mauris eu tellus molestie cursus. Duis ut magna at justo dignissim condimentum. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Vivamus varius. Ut sit amet diam suscipit mauris ornare aliquam. Sed varius. Duis arcu. Etiam tristique massa eget dui. Phasellus congue. Aenean est erat, tincidunt eget, venenatis quis, commodo at, quam."
                    }
                ]
            }
        ]
    }
}
Convert PDF-to-JSON — CODE SNIPPETS

    curl --location 'https://zylalabs.com/api/14067/pdf+to+json+ocr+api/34500/convert+pdf-to-json?ocr=auto' \
    --header 'Content-Type: application/json' \ 
    --form 'image=@"FILE_PATH"'

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the PDF to JSON OCR API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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(Save 2 months with annual billing 🎉)

Starts at
$10,000/Year


  • Custom Volume
  • Custom Rate Limit
  • Specialized Customer Support
  • Real-Time API Monitoring

Overview

Convert any PDF document with or without images into structured JSON output with built-in OCR features of the API. The API is best suited for LLM training and dataset creation.

PDF to JSON OCR API FAQs

The Convert PDF-to-JSON endpoint returns structured JSON data that includes extracted text, images, and metadata from the input PDF. It organizes this information into a hierarchical format, making it easy to access and manipulate.

Key fields in the response include "success," "data," "id," "request_id," "file_name," "page_count," "total_pages," and "pages," which contains detailed information about each page's content and structure.

The response data is organized in a JSON object, with a top-level "data" field containing an array of "pages." Each page object includes "page_number," "extraction_method," and "blocks" that detail the content type and text.

The primary parameter is "OCR," which can be set to true to force OCR processing or left as auto for automatic detection. This allows users to customize how text is extracted from image-based PDFs.

The HTML page for conversion endpoint processes raw HTML content and returns it in various formats, such as PDF or DOCX. It extracts text, images, and formatting from the HTML, enabling users to convert web content into structured documents.

Typical use cases include transforming PDF reports, invoices, and contracts into JSON for data analysis, integrating with web applications, and preparing datasets for machine learning model training.

Users can parse the JSON response to extract specific content, such as headings or paragraphs, for further analysis or integration into applications. The structured format allows for easy manipulation and data processing.

The API employs built-in OCR technology to accurately extract text from PDFs, including those with images. Continuous updates and improvements to the OCR algorithms help maintain high data quality and accuracy.

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