| Name | privacy-prompt-library JSON |
| Version |
1.2.0
JSON |
| download |
| home_page | None |
| Summary | A privacy-preserving prompt transformation library with smart multiple key combinations that reduce redundancy by 50%+ while maintaining complete accessibility context. |
| upload_time | 2025-09-18 14:05:21 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License
Copyright (c) 2025 Accessibility Team
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| keywords |
accessibility
ai
disability
nlp
privacy
prompt
redaction
transformation
|
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# Privacy-Preserving Prompt Library
A comprehensive Python library that transforms user prompts to protect disability privacy while maintaining functional context for AI interactions. **Now with smart combination technology that reduces description length by 50%+ while preserving complete accessibility information.**
## ✨ Key Features
🔒 **Privacy Protection** - Removes medical terms while preserving functional needs
🎯 **Smart Combinations** - Combines multiple accessibility needs into optimized single descriptions
⚡ **50%+ More Efficient** - Dramatically reduces word count without losing information
🧠 **AI-Ready** - Perfect single-string descriptions for prompt engineering
📚 **14 Categories** - Comprehensive coverage of disability and accessibility needs
## 🎯 Purpose
This library helps users interact with AI models without disclosing specific medical conditions by:
- **Detecting** disability mentions in prompts
- **Redacting** medical/diagnostic terms
- **Adding** functional context for better AI responses
- **Preserving** user privacy and intent
- **Smart Combining** multiple accessibility needs into efficient single descriptions
## 🔄 How It Works
```
Input: "I'm paralyzed and need help finding accessible restaurants"
↓
Output: "I use mobility equipment and need help finding accessible restaurants. I need step-free access to buildings and accessible parking close to entrances."
```
## ⚡ Smart Multiple Keys (v1.2.0)
```python
# Instead of 179 words across 3 separate descriptions...
keys = ["visual-impairment", "hearing-impairment", "physical-disability"]
result = transform_multiple_keys(keys)
# Get 1 optimized 76-word description (57% more efficient!)
print(result['output'])
# "I have comprehensive accessibility needs requiring screen reader
# compatibility with detailed text descriptions... [complete single description]"
```
## 🏗️ Architecture
- **14 Disability Categories** with comprehensive subgroups
- **Pattern Detection Engine** for identifying disability mentions
- **Redaction Engine** for replacing medical terms
- **Context Enrichment** for adding functional needs
- **Privacy Validation** to ensure no medical data leaks
- **Smart Combination Engine** for optimizing multiple accessibility descriptions
## 📦 Installation
```bash
pip install privacy-prompt-library
```
## 🚀 Quick Start
### Basic Usage - Transform Personal Prompts
```python
from prompt_library import transform_prompt
# Protect your privacy while getting AI help
result = transform_prompt("I'm blind and need coding help")
print(result['output'])
# "I use screen readers and need coding help. Please ensure any visual content
# includes text descriptions and is compatible with screen readers."
```
### Key-Based Descriptions
```python
from prompt_library import transform_by_key, get_supported_keys
# See what accessibility categories are available
print("Available categories:", get_supported_keys())
# Get a detailed 60-word accessibility description
description = transform_by_key("visual-impairment")
print(description['output'])
# Returns comprehensive visual accessibility needs without medical terms
# Use in your AI prompts
ai_prompt = f"{description['output']} Help me learn web development."
```
### Smart Multiple Keys (Most Efficient!)
```python
from prompt_library import transform_multiple_keys
# Get 1 optimized description instead of 3 separate ones
keys = ["visual-impairment", "hearing-impairment", "physical-disability"]
result = transform_multiple_keys(keys) # Smart combination by default
print(f"Efficiency: {result['validation']['efficiency_gain']} space saved!")
print(f"Single optimized description:\n{result['output']}")
```
### Library Information
```python
from prompt_library import get_library_info
info = get_library_info()
print(f"Version: {info['version']}")
print(f"Features: {', '.join(info['features'])}")
```
## ⭐ What's New in v1.2.0: Smart Combination
Transform multiple accessibility needs into **one optimized description** instead of handling separate strings:
```python
# OLD WAY: Get 3 separate 60-word descriptions (180 words total)
desc1 = transform_by_key("visual-impairment") # 60 words
desc2 = transform_by_key("hearing-impairment") # 60 words
desc3 = transform_by_key("physical-disability") # 60 words
# Total: 180 words, lots of redundancy
# NEW WAY: Get 1 smart combined description (76 words total)
result = transform_multiple_keys(["visual-impairment", "hearing-impairment", "physical-disability"])
print(f"Efficiency gain: {result['validation']['efficiency_gain']}") # "57.5%"
print(result['output']) # One cohesive, optimized description
```
**Benefits:**
- 🎯 **50-60% more efficient** - Dramatically reduced word count
- 🔄 **No redundancy** - Removes repeated accessibility terminology
- 📝 **Better readability** - Flows as one natural description
- ⚡ **Perfect for AI** - Single string ready for prompts
Input: "I'm paralyzed and need help finding accessible restaurants"
↓
Output: "I use mobility equipment and need help finding accessible restaurants. I need step-free access to buildings and accessible parking close to entrances."
```
## 🔑 Key-Based Descriptions
Generate detailed 60-word accessibility descriptions from simple category keys:
```python
from prompt_library import transform_by_key, get_supported_keys
# Get all available category keys
supported_keys = get_supported_keys()
print("Available keys:", supported_keys)
# Generate a functional description from a key
description = transform_by_key("visual-impairment")
print(description['output'])
# Output: "I have specific visual accessibility needs requiring comprehensive
# screen reader compatibility, high contrast display options with customizable
# color schemes, detailed text descriptions for all visual content including
# images, alternative format documents in accessible formats, large print
# materials when needed, audio descriptions for multimedia content, tactile
# feedback options, keyboard navigation support, and accessible navigation
# systems that work seamlessly with assistive technology."
# Example usage for different needs:
mobility_desc = transform_by_key("physical-disability")
hearing_desc = transform_by_key("hearing-impairment")
speech_desc = transform_by_key("speech-language-communication-and-swallowing-disability")
print(f"Word count: {len(mobility_desc['output'].split())} words") # Always 60 words
```
**Available Keys:**
- `visual-impairment` - Visual accessibility needs and assistive technology
- `hearing-impairment` - Hearing accessibility and communication needs
- `physical-disability` - Mobility and physical accessibility requirements
- `speech-language-communication-and-swallowing-disability` - Communication support needs
- `speech-intellectual-autism-spectrum-disorders` - Cognitive and sensory support
- `maxillofacial-disabilities` - Facial and oral function considerations
- `progressive-chronic-disorders` - Adaptive and flexible accommodation needs
## 🚀 Why Use Smart Combinations?
**Problem**: Traditional approach requires handling multiple separate descriptions
```python
# Old way: 3 separate descriptions = 180 words + manual combining
visual_desc = transform_by_key("visual-impairment") # 60 words
hearing_desc = transform_by_key("hearing-impairment") # 60 words
mobility_desc = transform_by_key("physical-disability") # 60 words
# You have to manually combine and remove redundancy
```
**Solution**: Smart combination gives you one optimized description
```python
# New way: 1 smart description = 76 words, ready to use
result = transform_multiple_keys(["visual-impairment", "hearing-impairment", "physical-disability"])
ai_prompt = f"{result['output']} Help me plan a conference presentation."
# 57% more efficient, no redundancy, perfect for AI prompts
```
### 🔗 Multiple Keys (New in v1.2.0)
Process multiple accessibility categories at once with intelligent combination:
```python
from prompt_library import transform_multiple_keys
# Smart combination (default) - Intelligently merges descriptions, removes redundancy
keys = ["visual-impairment", "hearing-impairment", "physical-disability"]
result = transform_multiple_keys(keys) # Uses smart_combined by default
print(f"Original total: {sum(result['transformation']['individual_word_counts'])} words")
print(f"Smart combined: {result['transformation']['total_word_count']} words")
print(f"Efficiency gain: {result['validation']['efficiency_gain']}")
print(f"\nCombined description:\n{result['output']}")
# Alternative methods if needed:
separate_result = transform_multiple_keys(keys, combine_method="separate")
simple_combined = transform_multiple_keys(keys, combine_method="simple_combined")
prioritized = transform_multiple_keys(keys, combine_method="prioritized")
```
**Combination Methods:**
- `"smart_combined"` - **Default**: Intelligently merges while avoiding redundancy (57% more efficient!)
- `"separate"` - Returns individual descriptions for each key
- `"simple_combined"` - Basic concatenation of all descriptions
- `"prioritized"` - Emphasizes first key, adds others as supplementary needs
**Smart Combination Benefits:**
- 🎯 **Efficiency**: Reduces word count by ~50-60% while preserving all key information
- 🔄 **Deduplication**: Removes redundant terms like "accessibility needs" and "screen reader"
- 📝 **Coherence**: Creates flowing, natural language instead of repetitive chunks
- ⚡ **Performance**: Single cohesive description instead of multiple separate strings
## 💡 Usage Examples
### Scenario 1: Getting a Functional Description for AI Prompts
```python
from prompt_library import transform_by_key
# Instead of saying "I'm blind", use a functional description
visual_needs = transform_by_key("visual-impairment")
prompt = f"{visual_needs['output']} Can you help me learn Python programming?"
# This gives the AI detailed context about your accessibility needs
# without revealing medical information
```
### Scenario 2: Multiple Accessibility Needs
```python
from prompt_library import transform_multiple_keys
# Smart combination automatically optimizes for efficiency
multiple_needs = transform_multiple_keys(
["visual-impairment", "physical-disability"]
)
# Result is a single, optimized 58-word description instead of 120 words
ai_prompt = f"{multiple_needs['output']} Help me set up a home office workspace."
print(f"Efficiency: {multiple_needs['validation']['efficiency_gain']} space saved!")
```
### Scenario 3: Building Accessibility Profiles
```python
# Create comprehensive accessibility descriptions
keys = ["visual-impairment", "hearing-impairment", "physical-disability"]
accessibility_profile = []
for key in keys:
description = transform_by_key(key)
accessibility_profile.append(description['output'])
combined_profile = " ".join(accessibility_profile)
print(f"Complete accessibility profile: {combined_profile}")
```
### Scenario 3: Privacy-Safe Prompt Enhancement
```python
# Transform personal prompts to be privacy-safe
personal_prompt = "I have multiple sclerosis and need help with work accommodations"
safe_prompt = transform_prompt(personal_prompt)
print("Original:", personal_prompt)
print("Safe version:", safe_prompt['output'])
# Result protects medical info while preserving functional needs
```
### Command Line Interface
```bash
# Transform a prompt via CLI
privacy-prompt "I have ADHD and need focus strategies"
# Get library information
privacy-prompt --info
# Custom privacy level
privacy-prompt --privacy-level medium "Your prompt here"
```
### Async Support
```python
from prompt_library import PromptLibrary
library = PromptLibrary()
await library.initialize()
result = await library.transform_prompt("I'm autistic and need help with social situations")
print(result['output'])
```
## 📋 Categories Supported
1. Physical Disabilities
2. Visual Impairments
3. Hearing Impairments
4. Speech & Language
5. Intellectual Disabilities
6. Learning Disabilities
7. Autism Spectrum
8. Developmental Disabilities
9. Mental Health
10. Emotional & Behavioral
11. Invisible Disabilities
12. Multiple Disabilities
13. Neurological
14. Genetic & Rare Disorders
## 🔒 Privacy Guarantee
- ✅ No medical terms in output
- ✅ No diagnostic language
- ✅ Functional descriptions only
- ✅ Complete user anonymity
## 🐍 Python Package Features
This repository now includes a fully-featured Python package with:
- **Modern Packaging**: Uses `pyproject.toml` and is available on PyPI
- **Async Support**: Full async/await compatibility
- **CLI Tool**: Command-line interface for easy integration
- **Type Hints**: Complete typing for better development experience
- **Testing**: Comprehensive test suite with pytest
### Python Installation & Usage
```bash
# Install from PyPI
pip install privacy-prompt-library
# Basic usage
python -c "from prompt_library import transform_prompt; print(transform_prompt('I have autism and need help'))"
# CLI usage
privacy-prompt --info
privacy-prompt "I'm deaf and need communication help"
```
### Development Setup
```bash
# Clone repository
git clone https://github.com/git-markkuria/kanuni-layer-sdk.git
cd kanuni-layer-sdk
# Install in development mode
pip install -e .
# Run tests
pytest tests/
```
## 📁 Repository Structure
```
├── prompt_library/ # Python package
│ ├── core/ # Core processing engines
│ ├── engines/ # Context and redaction engines
│ ├── data/ # JSON data files
│ └── cli.py # Command-line interface
├── src/ # JavaScript/Node.js version
├── tests/ # Python tests
├── pyproject.toml # Python packaging config
└── package.json # Node.js config
```
## 🤝 Contributing
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
Raw data
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"author_email": "Accessibility Team <accessibility@example.com>",
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"description": "# Privacy-Preserving Prompt Library\n\nA comprehensive Python library that transforms user prompts to protect disability privacy while maintaining functional context for AI interactions. **Now with smart combination technology that reduces description length by 50%+ while preserving complete accessibility information.**\n\n## \u2728 Key Features\n\n\ud83d\udd12 **Privacy Protection** - Removes medical terms while preserving functional needs \n\ud83c\udfaf **Smart Combinations** - Combines multiple accessibility needs into optimized single descriptions \n\u26a1 **50%+ More Efficient** - Dramatically reduces word count without losing information \n\ud83e\udde0 **AI-Ready** - Perfect single-string descriptions for prompt engineering \n\ud83d\udcda **14 Categories** - Comprehensive coverage of disability and accessibility needs \n\n## \ud83c\udfaf Purpose\n\nThis library helps users interact with AI models without disclosing specific medical conditions by:\n- **Detecting** disability mentions in prompts\n- **Redacting** medical/diagnostic terms\n- **Adding** functional context for better AI responses\n- **Preserving** user privacy and intent\n- **Smart Combining** multiple accessibility needs into efficient single descriptions\n\n## \ud83d\udd04 How It Works\n\n```\nInput: \"I'm paralyzed and need help finding accessible restaurants\"\n\u2193\nOutput: \"I use mobility equipment and need help finding accessible restaurants. I need step-free access to buildings and accessible parking close to entrances.\"\n```\n\n## \u26a1 Smart Multiple Keys (v1.2.0)\n\n```python\n# Instead of 179 words across 3 separate descriptions...\nkeys = [\"visual-impairment\", \"hearing-impairment\", \"physical-disability\"]\nresult = transform_multiple_keys(keys)\n\n# Get 1 optimized 76-word description (57% more efficient!)\nprint(result['output'])\n# \"I have comprehensive accessibility needs requiring screen reader \n# compatibility with detailed text descriptions... [complete single description]\"\n```\n\n## \ud83c\udfd7\ufe0f Architecture\n\n- **14 Disability Categories** with comprehensive subgroups\n- **Pattern Detection Engine** for identifying disability mentions\n- **Redaction Engine** for replacing medical terms\n- **Context Enrichment** for adding functional needs\n- **Privacy Validation** to ensure no medical data leaks\n- **Smart Combination Engine** for optimizing multiple accessibility descriptions\n\n## \ud83d\udce6 Installation\n\n```bash\npip install privacy-prompt-library\n```\n\n## \ud83d\ude80 Quick Start\n\n### Basic Usage - Transform Personal Prompts\n```python\nfrom prompt_library import transform_prompt\n\n# Protect your privacy while getting AI help\nresult = transform_prompt(\"I'm blind and need coding help\")\nprint(result['output'])\n# \"I use screen readers and need coding help. Please ensure any visual content \n# includes text descriptions and is compatible with screen readers.\"\n```\n\n### Key-Based Descriptions \n```python\nfrom prompt_library import transform_by_key, get_supported_keys\n\n# See what accessibility categories are available\nprint(\"Available categories:\", get_supported_keys())\n\n# Get a detailed 60-word accessibility description\ndescription = transform_by_key(\"visual-impairment\") \nprint(description['output'])\n# Returns comprehensive visual accessibility needs without medical terms\n\n# Use in your AI prompts\nai_prompt = f\"{description['output']} Help me learn web development.\"\n```\n\n### Smart Multiple Keys (Most Efficient!)\n```python\nfrom prompt_library import transform_multiple_keys\n\n# Get 1 optimized description instead of 3 separate ones\nkeys = [\"visual-impairment\", \"hearing-impairment\", \"physical-disability\"] \nresult = transform_multiple_keys(keys) # Smart combination by default\n\nprint(f\"Efficiency: {result['validation']['efficiency_gain']} space saved!\")\nprint(f\"Single optimized description:\\n{result['output']}\")\n```\n\n### Library Information\n```python\nfrom prompt_library import get_library_info\ninfo = get_library_info()\nprint(f\"Version: {info['version']}\")\nprint(f\"Features: {', '.join(info['features'])}\")\n```\n\n## \u2b50 What's New in v1.2.0: Smart Combination\n\nTransform multiple accessibility needs into **one optimized description** instead of handling separate strings:\n\n```python\n# OLD WAY: Get 3 separate 60-word descriptions (180 words total)\ndesc1 = transform_by_key(\"visual-impairment\") # 60 words\ndesc2 = transform_by_key(\"hearing-impairment\") # 60 words \ndesc3 = transform_by_key(\"physical-disability\") # 60 words\n# Total: 180 words, lots of redundancy\n\n# NEW WAY: Get 1 smart combined description (76 words total)\nresult = transform_multiple_keys([\"visual-impairment\", \"hearing-impairment\", \"physical-disability\"])\nprint(f\"Efficiency gain: {result['validation']['efficiency_gain']}\") # \"57.5%\"\nprint(result['output']) # One cohesive, optimized description\n```\n\n**Benefits:**\n- \ud83c\udfaf **50-60% more efficient** - Dramatically reduced word count\n- \ud83d\udd04 **No redundancy** - Removes repeated accessibility terminology \n- \ud83d\udcdd **Better readability** - Flows as one natural description\n- \u26a1 **Perfect for AI** - Single string ready for prompts\n\nInput: \"I'm paralyzed and need help finding accessible restaurants\"\n\u2193\nOutput: \"I use mobility equipment and need help finding accessible restaurants. I need step-free access to buildings and accessible parking close to entrances.\"\n```\n\n## \ud83d\udd11 Key-Based Descriptions\nGenerate detailed 60-word accessibility descriptions from simple category keys:\n\n```python\nfrom prompt_library import transform_by_key, get_supported_keys\n\n# Get all available category keys\nsupported_keys = get_supported_keys()\nprint(\"Available keys:\", supported_keys)\n\n# Generate a functional description from a key\ndescription = transform_by_key(\"visual-impairment\")\nprint(description['output'])\n# Output: \"I have specific visual accessibility needs requiring comprehensive \n# screen reader compatibility, high contrast display options with customizable \n# color schemes, detailed text descriptions for all visual content including \n# images, alternative format documents in accessible formats, large print \n# materials when needed, audio descriptions for multimedia content, tactile \n# feedback options, keyboard navigation support, and accessible navigation \n# systems that work seamlessly with assistive technology.\"\n\n# Example usage for different needs:\nmobility_desc = transform_by_key(\"physical-disability\")\nhearing_desc = transform_by_key(\"hearing-impairment\")\nspeech_desc = transform_by_key(\"speech-language-communication-and-swallowing-disability\")\n\nprint(f\"Word count: {len(mobility_desc['output'].split())} words\") # Always 60 words\n```\n\n**Available Keys:**\n- `visual-impairment` - Visual accessibility needs and assistive technology\n- `hearing-impairment` - Hearing accessibility and communication needs \n- `physical-disability` - Mobility and physical accessibility requirements\n- `speech-language-communication-and-swallowing-disability` - Communication support needs\n- `speech-intellectual-autism-spectrum-disorders` - Cognitive and sensory support\n- `maxillofacial-disabilities` - Facial and oral function considerations\n- `progressive-chronic-disorders` - Adaptive and flexible accommodation needs\n\n## \ud83d\ude80 Why Use Smart Combinations?\n\n**Problem**: Traditional approach requires handling multiple separate descriptions\n```python\n# Old way: 3 separate descriptions = 180 words + manual combining\nvisual_desc = transform_by_key(\"visual-impairment\") # 60 words\nhearing_desc = transform_by_key(\"hearing-impairment\") # 60 words \nmobility_desc = transform_by_key(\"physical-disability\") # 60 words\n# You have to manually combine and remove redundancy\n```\n\n**Solution**: Smart combination gives you one optimized description\n```python\n# New way: 1 smart description = 76 words, ready to use\nresult = transform_multiple_keys([\"visual-impairment\", \"hearing-impairment\", \"physical-disability\"])\nai_prompt = f\"{result['output']} Help me plan a conference presentation.\"\n# 57% more efficient, no redundancy, perfect for AI prompts\n```\n\n### \ud83d\udd17 Multiple Keys (New in v1.2.0)\nProcess multiple accessibility categories at once with intelligent combination:\n\n```python\nfrom prompt_library import transform_multiple_keys\n\n# Smart combination (default) - Intelligently merges descriptions, removes redundancy\nkeys = [\"visual-impairment\", \"hearing-impairment\", \"physical-disability\"]\nresult = transform_multiple_keys(keys) # Uses smart_combined by default\n\nprint(f\"Original total: {sum(result['transformation']['individual_word_counts'])} words\")\nprint(f\"Smart combined: {result['transformation']['total_word_count']} words\")\nprint(f\"Efficiency gain: {result['validation']['efficiency_gain']}\")\nprint(f\"\\nCombined description:\\n{result['output']}\")\n\n# Alternative methods if needed:\nseparate_result = transform_multiple_keys(keys, combine_method=\"separate\")\nsimple_combined = transform_multiple_keys(keys, combine_method=\"simple_combined\")\nprioritized = transform_multiple_keys(keys, combine_method=\"prioritized\")\n```\n\n**Combination Methods:**\n- `\"smart_combined\"` - **Default**: Intelligently merges while avoiding redundancy (57% more efficient!)\n- `\"separate\"` - Returns individual descriptions for each key\n- `\"simple_combined\"` - Basic concatenation of all descriptions\n- `\"prioritized\"` - Emphasizes first key, adds others as supplementary needs\n\n**Smart Combination Benefits:**\n- \ud83c\udfaf **Efficiency**: Reduces word count by ~50-60% while preserving all key information\n- \ud83d\udd04 **Deduplication**: Removes redundant terms like \"accessibility needs\" and \"screen reader\"\n- \ud83d\udcdd **Coherence**: Creates flowing, natural language instead of repetitive chunks\n- \u26a1 **Performance**: Single cohesive description instead of multiple separate strings\n\n## \ud83d\udca1 Usage Examples\n\n### Scenario 1: Getting a Functional Description for AI Prompts\n```python\nfrom prompt_library import transform_by_key\n\n# Instead of saying \"I'm blind\", use a functional description\nvisual_needs = transform_by_key(\"visual-impairment\")\nprompt = f\"{visual_needs['output']} Can you help me learn Python programming?\"\n\n# This gives the AI detailed context about your accessibility needs\n# without revealing medical information\n```\n\n### Scenario 2: Multiple Accessibility Needs\n```python\nfrom prompt_library import transform_multiple_keys\n\n# Smart combination automatically optimizes for efficiency\nmultiple_needs = transform_multiple_keys(\n [\"visual-impairment\", \"physical-disability\"]\n)\n# Result is a single, optimized 58-word description instead of 120 words\n\nai_prompt = f\"{multiple_needs['output']} Help me set up a home office workspace.\"\nprint(f\"Efficiency: {multiple_needs['validation']['efficiency_gain']} space saved!\")\n```\n\n### Scenario 3: Building Accessibility Profiles\n```python\n# Create comprehensive accessibility descriptions\nkeys = [\"visual-impairment\", \"hearing-impairment\", \"physical-disability\"]\naccessibility_profile = []\n\nfor key in keys:\n description = transform_by_key(key)\n accessibility_profile.append(description['output'])\n\ncombined_profile = \" \".join(accessibility_profile)\nprint(f\"Complete accessibility profile: {combined_profile}\")\n```\n\n### Scenario 3: Privacy-Safe Prompt Enhancement\n```python\n# Transform personal prompts to be privacy-safe\npersonal_prompt = \"I have multiple sclerosis and need help with work accommodations\"\nsafe_prompt = transform_prompt(personal_prompt)\n\nprint(\"Original:\", personal_prompt)\nprint(\"Safe version:\", safe_prompt['output'])\n# Result protects medical info while preserving functional needs\n```\n\n### Command Line Interface\n```bash\n# Transform a prompt via CLI\nprivacy-prompt \"I have ADHD and need focus strategies\"\n\n# Get library information\nprivacy-prompt --info\n\n# Custom privacy level\nprivacy-prompt --privacy-level medium \"Your prompt here\"\n```\n\n### Async Support\n```python\nfrom prompt_library import PromptLibrary\n\nlibrary = PromptLibrary()\nawait library.initialize()\nresult = await library.transform_prompt(\"I'm autistic and need help with social situations\")\nprint(result['output'])\n```\n\n## \ud83d\udccb Categories Supported\n\n1. Physical Disabilities\n2. Visual Impairments \n3. Hearing Impairments\n4. Speech & Language\n5. Intellectual Disabilities\n6. Learning Disabilities\n7. Autism Spectrum\n8. Developmental Disabilities\n9. Mental Health\n10. Emotional & Behavioral\n11. Invisible Disabilities\n12. Multiple Disabilities\n13. Neurological\n14. Genetic & Rare Disorders\n\n## \ud83d\udd12 Privacy Guarantee\n\n- \u2705 No medical terms in output\n- \u2705 No diagnostic language\n- \u2705 Functional descriptions only\n- \u2705 Complete user anonymity\n\n## \ud83d\udc0d Python Package Features\n\nThis repository now includes a fully-featured Python package with:\n\n- **Modern Packaging**: Uses `pyproject.toml` and is available on PyPI\n- **Async Support**: Full async/await compatibility\n- **CLI Tool**: Command-line interface for easy integration\n- **Type Hints**: Complete typing for better development experience\n- **Testing**: Comprehensive test suite with pytest\n\n### Python Installation & Usage\n\n```bash\n# Install from PyPI\npip install privacy-prompt-library\n\n# Basic usage\npython -c \"from prompt_library import transform_prompt; print(transform_prompt('I have autism and need help'))\"\n\n# CLI usage\nprivacy-prompt --info\nprivacy-prompt \"I'm deaf and need communication help\"\n```\n\n### Development Setup\n\n```bash\n# Clone repository\ngit clone https://github.com/git-markkuria/kanuni-layer-sdk.git\ncd kanuni-layer-sdk\n\n# Install in development mode\npip install -e .\n\n# Run tests\npytest tests/\n```\n\n## \ud83d\udcc1 Repository Structure\n\n```\n\u251c\u2500\u2500 prompt_library/ # Python package\n\u2502 \u251c\u2500\u2500 core/ # Core processing engines\n\u2502 \u251c\u2500\u2500 engines/ # Context and redaction engines\n\u2502 \u251c\u2500\u2500 data/ # JSON data files\n\u2502 \u2514\u2500\u2500 cli.py # Command-line interface\n\u251c\u2500\u2500 src/ # JavaScript/Node.js version\n\u251c\u2500\u2500 tests/ # Python tests\n\u251c\u2500\u2500 pyproject.toml # Python packaging config\n\u2514\u2500\u2500 package.json # Node.js config\n```\n\n## \ud83e\udd1d Contributing\n\n1. Fork the repository\n2. Create a feature branch (`git checkout -b feature/amazing-feature`)\n3. Commit your changes (`git commit -m 'Add amazing feature'`)\n4. Push to the branch (`git push origin feature/amazing-feature`)\n5. Open a Pull Request\n\n## \ud83d\udcc4 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.",
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"license": "MIT License\n \n Copyright (c) 2025 Accessibility Team\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.",
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