🧠 AI Text Humanizer

Welcome to AI Text Humanizer : an open-source project that transforms robotic or AI-generated writing into fluent, natural, human-like text.

Goal for Hacktoberfest 2025: build a full-scale, industry-level humanizer through community contributions. 🚀

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Overview

This project contains two Python humanizers:

• 🟢 Balanced : preserves meaning and prioritizes grammar & readability.
• 🔴 Aggressive : stronger rephrasing and stylistic variation (more creative).

Both use modern NLP tools (Transformers, spaCy, TextStat, NLTK) to refine grammar and tone.

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Quick start

1. Clone the repo:

git clone https://github.com/Haryaksh1/AI-Text-Humanizer.git
cd AI-Text-Humanizer

2. Install dependencies:

pip install -r requirements.txt
python -m spacy download en_core_web_sm

CLI Usage

The CLI provides a simple command-line interface for humanizing text:

Basic Usage

# Humanize text directly
python cli/humanize_cli.py --model balanced --input "Furthermore, it is important to note that artificial intelligence is transforming industries."

# Use aggressive model for stronger rephrasing
python cli/humanize_cli.py --model aggressive --input "Moreover, the comprehensive analysis demonstrates significant improvements."

# Save output to file
python cli/humanize_cli.py --model balanced --input "Your AI text here" --output humanized.txt

# Process text from file
python cli/humanize_cli.py --model aggressive --file input.txt --output output.txt

# Show detailed statistics
python cli/humanize_cli.py --model balanced --input "Your text" --stats

CLI Options

• --model: Choose humanizer model (balanced or aggressive)
  • balanced: Preserves meaning, focuses on readability
  • aggressive: Stronger rephrasing, more creative transformations
• --input: Input text to humanize (use quotes for multi-word text)
• --file: Input file containing text to humanize
• --output: Output file to save humanized text (optional, prints to stdout if not specified)
• --stats: Show humanization statistics and metrics
• --quiet: Suppress progress messages

API Usage

The Flask API provides RESTful endpoints for integrating humanizers into other applications:

Starting the API Server

python api/app.py

The API will be available at http://localhost:5000

API Endpoints

POST /humanize

Humanize AI-generated text using balanced or aggressive models.

Request:

{
  "model": "balanced",
  "text": "Furthermore, it is important to note that artificial intelligence is transforming industries.",
  "include_stats": true
}

Response:

{
  "humanized_text": "Also, AI is really changing industries in a big way.",
  "model_used": "balanced",
  "processing_time": 0.234,
  "success": true,
  "stats": {
    "initial_ai_score": 2.1,
    "final_ai_score": 0.3,
    "improvement_percentage": 85.7,
    "target_achieved": true,
    "input_length": 89,
    "output_length": 52,
    "quality_metrics": {
      "overall_quality": 78.5,
      "readability_score": 82.3,
      "grade_level": 8.2
    }
  }
}

GET /health

Health check endpoint.

Response:

{
  "status": "healthy",
  "timestamp": "2025-01-22 14:30:15",
  "service": "AI Text Humanizer API"
}

GET /

API documentation with examples and endpoint details.

cURL Examples

# Basic humanization
curl -X POST http://localhost:5000/humanize \
  -H "Content-Type: application/json" \
  -d '{"model": "balanced", "text": "Furthermore, it is important to note that..."}'

# With statistics
curl -X POST http://localhost:5000/humanize \
  -H "Content-Type: application/json" \
  -d '{"model": "aggressive", "text": "Moreover, the comprehensive analysis demonstrates...", "include_stats": true}'

# Health check
curl http://localhost:5000/health

Python Integration Example

import requests

# Humanize text via API
response = requests.post('http://localhost:5000/humanize', json={
    'model': 'balanced',
    'text': 'Your AI-generated text here',
    'include_stats': True
})

result = response.json()
print("Humanized:", result['humanized_text'])
print("Improvement:", result['stats']['improvement_percentage'], "%")

Tech stack

• Python

• Transformers (Hugging Face)

• spaCy

• NLTK

• TextStat

• scikit-learn

• pandas / numpy

Contributing

We welcome all contributions — small fixes or large features. This repo is beginner-friendly.

How to contribute

• Fork the repository.

• Create a branch: git checkout -b feature-name.

• Commit changes: git commit -m "Add ".

• Push and open a pull request.

Please open an issue first if you plan to add a new feature (see “How to open a new issue” below).

How to open a new issue

We encourage issues for:

• New features (UI, new model variant, API)

• Model improvements (grammar, readability)

• Bug reports / performance optimizations

• Research & evaluation

Steps:

1.Go to the Issues tab: https://github.com/Haryaksh1/AI-Text-Humanizer/issues

2.Click New issue.

3.Use the template (title, short description, steps/files changed).

4.Add labels: hacktoberfest, good first issue, python (you can pick them on the right).

5.Comment “I’d like to work on this” and wait to be assigned.

Hacktoberfest 2025

This repo participates in Hacktoberfest 2025. Look for issues labelled:

• hacktoberfest

• good first issue

• python

If your PR is merged or marked hacktoberfest-accepted by a maintainer, it will count.

License

MIT License

Maintainer

Maintained by @Haryaksh1 If you need help, tag me in the issue or PR and I’ll reply quickly.