PDF Proofreader

An API that analyzes PDF documents to detect basic spelling and grammar issues and provides a proofreading quality score.

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Description

PDF Proofreader extracts text content from PDF files and analyzes it to identify common spelling and grammar mistakes. It also calculates a proofreading quality score to help users quickly assess the overall writing quality of their documents.

This API is useful for:

• Students reviewing assignments or reports
• Developers building document analysis tools
• Content teams checking document quality
• Automation workflows that process PDFs at scale

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Features

• Extracts text from PDF files
• Detects common spelling mistakes
• Detects basic grammar issues
• Calculates total word count
• Generates a proofreading quality score
• Returns structured JSON output
• Supports multiple PDF URLs per request

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Tech Stack

• Platform: Apify Actor
• Language: (your implementation language)
• PDF Parsing: (e.g., pdf-parse, PyPDF, etc.)
• Grammar Engine: Rule-based / NLP

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Input Format

The API accepts a JSON input with a list of PDF URLs.

Example input.json

{
  "pdfUrls": [
    {
      "url": "https://raw.githubusercontent.com/Gautamrana14/pdf-test-files/main/DBMS-10%20(1).pdf"
    }
  ]
}

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Usage

Base Endpoint (Apify Actor)

https://api.apify.com/v2/acts/<your-actor-id>/run-sync-get-dataset-items

Example Request (cURL)

curl -X POST \
  -H "Content-Type: application/json" \
  -d @input.json \
  "https://api.apify.com/v2/acts/<your-actor-id>/run-sync-get-dataset-items?token=YOUR_API_TOKEN"

Example using JavaScript

import fetch from "node-fetch";

const response = await fetch("https://api.apify.com/v2/acts/<your-actor-id>/run-sync-get-dataset-items?token=YOUR_API_TOKEN", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    pdfUrls: [
      { url: "https://example.com/sample.pdf" }
    ]
  })
});

const data = await response.json();
console.log(data);

Example using Python

import requests

url = "https://api.apify.com/v2/acts/<your-actor-id>/run-sync-get-dataset-items"
params = {"token": "YOUR_API_TOKEN"}

payload = {
    "pdfUrls": [
        {"url": "https://example.com/sample.pdf"}
    ]
}

response = requests.post(url, params=params, json=payload)
print(response.json())

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Output Format

The API returns a dataset URL containing the proofreading results.

Output Schema

{
  "dataset": "https://api.apify.com/v2/datasets/xxxx/items"
}

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Dataset Schema

Each dataset item has the following structure:

{
  "pdfUrl": "https://example.com/sample.pdf",
  "wordCount": 1520,
  "detectedIssues": [
    "Misspelled word: teh",
    "Incorrect verb tense in paragraph 3",
    "Repeated word: the"
  ],
  "issueCount": 3,
  "proofreadingScore": 92
}

Field Description

Field	Description
pdfUrl	URL of the analyzed PDF file
wordCount	Total number of words extracted
detectedIssues	List of detected spelling/grammar issues
issueCount	Total number of issues found
proofreadingScore	Quality score (0–100)

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Limitations

• Only detects basic grammar and spelling issues
• Accuracy depends on text extraction quality
• Not a replacement for professional proofreading

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Rate Limits

Depends on your Apify plan and actor configuration.

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Roadmap

• Advanced grammar detection
• Language support beyond English
• Issue categorization (spelling vs grammar)
• Suggestions for corrections
• Highlight positions in original PDF

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Contributing

Contributions are welcome.

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Open a pull request

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License

MIT License

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Author

Gautam Rana GitHub: https://github.com/Gautamrana14

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