Split PDF by Text - Content Splitter API

PDF4me Split PDF by Text is a powerful enterprise-grade solution that splits PDF documents by searching for specific text patterns through advanced API integration. This comprehensive PDF splitting service efficiently processes PDF documents with text content, providing intelligent text recognition, automated page filtering, precise document splitting, and advanced PDF processing capabilities for enhanced document management and automated processing workflows. The API processes PDF splitting by receiving source PDF documents through REST API calls, utilizing advanced text recognition technology and intelligent filtering algorithms for accurate document splitting and professional PDF processing. With comprehensive support for text recognition, intelligent page filtering, automated document splitting, and professional PDF processing, this solution is ideal for document management, automated processing, text-based splitting, and enterprise PDF workflows that require reliable document splitting with guaranteed accuracy and consistent output quality. Split PDF by Text documents easily with API for advanced PDF processing and document management.

Authenticating Your API Request

To access the PDF4me REST API, every request must include proper authentication credentials. Authentication ensures secure communication and validates your identity as an authorized user of the REST API.

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Key Features

• Text Recognition: Intelligent text recognition and pattern matching from PDF documents
• Automated Splitting: Split PDF documents based on specific text patterns and filtering criteria
• Page Filtering: Filter pages using text content for precise document splitting
• Quality Preservation: Maintain PDF quality during splitting operations
• Professional Results: High-quality PDF splitting with accurate text recognition
• Seamless API Integration: RESTful API designed for automated PDF processing workflows and enterprise system integration

REST API Endpoint

The PDF4me REST API uses standard HTTP methods to interact with resources. All text-based PDF splitting operations are performed through a single endpoint:

• Method: POST
• Endpoint: /api/v2/SplitByText

Supported PDF Splitting Features

The API provides comprehensive support for various PDF splitting and text processing capabilities:

Text Processing

• Text Recognition: Intelligent text recognition and pattern matching from PDF documents
• Pattern Matching: Search for specific text patterns and content for filtering and splitting operations
• Multiple Formats: Support for various text formats and content types
• Professional Results: High-quality text recognition with accurate pattern matching
• Advanced Processing: Support for complex text structures and recognition requirements

Document Splitting

• Automated Splitting: Split PDF documents based on specific text patterns and filtering criteria
• Page Filtering: Filter pages using text content for precise document splitting
• Intelligent Processing: Smart document splitting with text-based page identification
• Professional Results: High-quality PDF splitting with accurate page separation
• Advanced Processing: Support for complex document structures and splitting requirements

Content Processing

• Quality Preservation: Maintain PDF quality during splitting operations
• Format Support: Support for various PDF formats and document types
• Professional Enhancement: High-quality PDF processing with accurate splitting
• Flexible Options: Customizable processing parameters for specific requirements

REST API Parameters

Complete list of parameters for the Split PDF by Text REST API. Parameters are organized by category for better understanding and implementation.

Important: Parameters marked with an asterisk (*) are required and must be provided for the API to function correctly.

Required Parameters

Parameter	Type	Description	Example
File Content*	Base64	The complete content of the PDF document encoded in Base64 format for text-based splitting processing. This parameter contains the entire PDF file data required for text recognition, page filtering, and document splitting workflows. Essential for secure document handling and API-based PDF splitting operations.	JVBERi...
File Name*	String	The source PDF document filename with proper .pdf extension for text-based splitting operations. This parameter identifies the input document for text recognition, page filtering, and document splitting workflows. Required for document identification and processing pipeline management in PDF splitting operations.	document.pdf
Text*	String	The specific text pattern or content to search for and use as a splitting criterion within the PDF document. This parameter supports text pattern matching for precise page identification and splitting operations. Enables automated document splitting, content management, and text-based processing workflows with exact pattern matching capabilities.	Chapter 1
Split Text Page*	String	Specify the page splitting behavior when text patterns are found. This parameter controls how the PDF is split when text criteria are met, enabling precise control over document splitting logic and page separation for text-based processing workflows.	After
File Naming*	String	Specify the naming convention for split PDF files. This parameter controls how the output files are named, enabling consistent file naming and organization for split documents. Supports various naming patterns for better file management and organization.	document_part_{page}

Output

The PDF4me Split PDF by Text REST API returns a response that can be viewed in multiple formats. Choose the view that best fits your needs:

JSON

JSON Response Format

The raw JSON response from the API:

{
  "File Content": "Output file content from the PDF4me action",
  "File Name": "Output file name from the PDF4me action"
}

Table

Table View

Response data in a structured table format:

Parameter	Value
File Content	Output file content from the PDF4me action
File Name	Output file name from the PDF4me action

Schema

Schema View

The data structure and types of the response:

2 items
File Content: Binary Output file content from the PDF4me action
File Name: String Output file name from the PDF4me action

Type Indicators:

• Binary = Binary data
• String = Text data

Binary

Binary Data View

The actual split PDF file data:

data
─────────────────────────────
File Content: Output file content from the PDF4me action
File Name: Output file name from the PDF4me action

Binary Data Access:

• PDF Content: Ready for download or further processing
• Split PDF: Complete PDF with text-based splitting applied

Request Example

Header

Content-Type: application/json
Authorization:  YOUR_API_KEY

Note: Get your API key from the PDF4me Dashboard

Payload

{
  "docContent": "Please put PDF base64 content",
  "docName": "output.pdf",
  "text": "Nadal, who officially turned professional in 2001",
  "splitTextPage": "before",
  "fileNaming": "NameAsPerOrder"
}

Code Samples

The PDF4me Split PDF by Text REST API provides code samples in multiple programming languages. Choose the language that best fits your development environment:

C#

C# (CSharp) Sample

Complete C# implementation for PDF splitting by text:

View C# Sample

Java

Java Sample

Java implementation with full error handling and response processing:

View Java Sample

JavaScript

JavaScript Sample

Node.js and browser-compatible JavaScript implementation:

View JavaScript Sample

Python

Python Sample

Python implementation with requests library and JSON handling:

View Python Sample

Salesforce

Salesforce Sample

Salesforce Apex implementation for CRM integration:

View Salesforce Sample

n8n

n8n Sample

n8n workflow implementation for automation:

View n8n Sample

Google Script

Google Script Sample

Google Apps Script implementation for Google Workspace integration:

View Google Script Sample

AWS Lambda

AWS Lambda Sample

Serverless AWS Lambda function implementation:

View AWS Lambda Sample

PDF Splitting Features

Text Processing

• Text Recognition: Intelligent text recognition and pattern matching from PDF documents
• Pattern Matching: Search for specific text patterns and content for filtering and splitting operations
• Multiple Formats: Support for various text formats and content types
• Professional Results: High-quality text recognition with accurate pattern matching
• Advanced Processing: Support for complex text structures and recognition requirements

Document Splitting

• Automated Splitting: Split PDF documents based on specific text patterns and filtering criteria
• Page Filtering: Filter pages using text content for precise document splitting
• Intelligent Processing: Smart document splitting with text-based page identification
• Professional Results: High-quality PDF splitting with accurate page separation
• Advanced Processing: Support for complex document structures and splitting requirements

Content Processing

• Quality Preservation: Maintain PDF quality during splitting operations
• Format Support: Support for various PDF formats and document types
• Professional Enhancement: High-quality PDF processing with accurate splitting
• Flexible Options: Customizable processing parameters for specific requirements

Industry Use Cases & Applications

Use Cases

Use Cases

• Document Processing: Split large PDF documents based on text identifiers for automated processing
• Chapter Processing: Split book or document PDFs by chapter headings for automated content management
• Invoice Processing: Split invoice PDFs by text patterns for automated accounting workflows
• Report Processing: Split report PDFs by section headers for automated content organization
• Compliance: Split compliance documents by text identifiers for automated regulatory processing
• Workflow Automation: Automate PDF splitting workflows for enterprise operations
• Content Management: Split content documents by text categories for automated organization
• Batch Processing: Process large volumes of documents with automated text-based splitting

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