Text Extract

Action ID: text_extract

Description

Extract text content from various file formats including PDFs, images, and documents using OCR and document parsing technology.

Connection

Name	Description	Required	Category
PixelML Connection	The PixelML connection to call PixelML API.	✓	pixelml

Input Parameters

Name	Type	Required	Default	Description
file	string	✓	-	URL of the file to extract text from. Supports PDFs, images, and various document formats

View JSON Schema

{
  "description": "Text extract node input.",
  "properties": {
    "file": {
      "description": "File to extract text from",
      "title": "File",
      "type": "string"
    }
  },
  "required": [
    "file"
  ],
  "title": "TextExtractNodeInput",
  "type": "object"
}

Output Parameters

Name	Type	Description
text	string	The extracted text content from the file

View JSON Schema

{
  "description": "Text extract node output.",
  "properties": {
    "text": {
      "description": "Extracted text from the file",
      "title": "Extracted text",
      "type": "string"
    }
  },
  "required": [
    "text"
  ],
  "title": "TextExtractNodeOutput",
  "type": "object"
}

How It Works

This node uses advanced OCR (Optical Character Recognition) and document parsing technology to extract text from various file formats. For PDFs, it extracts embedded text directly when available or applies OCR for scanned PDFs. For images, it uses computer vision to detect and recognize text characters. The extracted text maintains line breaks and paragraph structure when possible, providing clean, readable output.

Usage Examples

Example 1: Extract Text from PDF

Input:

file: "https://example.com/invoice.pdf"

Output:

text: "Invoice #12345
Date: January 15, 2025
Customer: Acme Corp
Total Amount: $1,250.00
..."

Example 2: Extract Text from Image

Input:

file: "https://example.com/business-card.jpg"

Output:

text: "John Doe
Senior Developer
Acme Technology
[email protected]
[phone]"

Example 3: Extract Text from Scanned Document

Input:

file: "https://example.com/scanned-contract.pdf"

Output:

text: "SERVICE AGREEMENT

This agreement is made on January 15, 2025 between...
Terms and Conditions:
1. Service Duration
2. Payment Terms
..."

Common Use Cases

• Invoice Processing: Extract text from invoices for automated accounting and data entry

• Document Digitization: Convert scanned documents and images into searchable, editable text

• Receipt Processing: Extract information from receipts for expense tracking and reporting

• Business Card Scanning: Extract contact information from business card images

• Form Processing: Extract data from filled forms and applications

• Legal Document Processing: Extract text from contracts and legal documents for review

• ID Verification: Extract text from identification documents for verification workflows

Error Handling

Error Type	Cause	Solution
Invalid File URL	URL is malformed or file is inaccessible	Verify the file URL is valid and publicly accessible
Unsupported Format	File format is not supported for text extraction	Convert file to a supported format (PDF, JPG, PNG, etc.)
No Text Found	File contains no readable text	Ensure the file contains visible text and is not blank
File Too Large	File size exceeds maximum allowed	Compress or split the file into smaller parts
Low Image Quality	Image quality is too poor for OCR	Use a higher resolution scan or image
Connection Error	Cannot connect to PixelML API	Check your PixelML connection settings and API key

Notes

• Supported Formats: Works with PDFs, JPG, PNG, JPEG, WebP, and other common image and document formats.

• OCR Accuracy: Accuracy depends on image quality, text clarity, and font legibility. High-resolution images produce best results.

• Language Support: The system supports multiple languages for text extraction. Specify language if detection is inaccurate.

• Text Structure: The node attempts to preserve text structure including paragraphs and line breaks.

• Processing Time: Extraction time varies based on file size and complexity. Large PDFs may take 30-60 seconds.

• Handwriting: OCR works best with printed text. Handwritten text may have lower accuracy rates.