85bf1341f3
Frontend Enhancements: - Complete React TypeScript frontend with modern UI components - Distributed workflows management interface with real-time updates - Socket.IO integration for live agent status monitoring - Agent management dashboard with cluster visualization - Project management interface with metrics and task tracking - Responsive design with proper error handling and loading states Backend Infrastructure: - Distributed coordinator for multi-agent workflow orchestration - Cluster management API with comprehensive agent operations - Enhanced database models for agents and projects - Project service for filesystem-based project discovery - Performance monitoring and metrics collection - Comprehensive API documentation and error handling Documentation: - Complete distributed development guide (README_DISTRIBUTED.md) - Comprehensive development report with architecture insights - System configuration templates and deployment guides The platform now provides a complete web interface for managing the distributed AI cluster with real-time monitoring, workflow orchestration, and agent coordination capabilities. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
105 lines
3.3 KiB
Markdown
105 lines
3.3 KiB
Markdown
# fast-levenshtein - Levenshtein algorithm in Javascript
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[](http://travis-ci.org/hiddentao/fast-levenshtein)
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[](https://badge.fury.io/js/fast-levenshtein)
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[](https://www.npmjs.com/package/fast-levenshtein)
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[](https://twitter.com/hiddentao)
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An efficient Javascript implementation of the [Levenshtein algorithm](http://en.wikipedia.org/wiki/Levenshtein_distance) with locale-specific collator support.
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## Features
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* Works in node.js and in the browser.
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* Better performance than other implementations by not needing to store the whole matrix ([more info](http://www.codeproject.com/Articles/13525/Fast-memory-efficient-Levenshtein-algorithm)).
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* Locale-sensitive string comparisions if needed.
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* Comprehensive test suite and performance benchmark.
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* Small: <1 KB minified and gzipped
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## Installation
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### node.js
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Install using [npm](http://npmjs.org/):
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```bash
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$ npm install fast-levenshtein
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```
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### Browser
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Using bower:
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```bash
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$ bower install fast-levenshtein
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```
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If you are not using any module loader system then the API will then be accessible via the `window.Levenshtein` object.
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## Examples
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**Default usage**
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```javascript
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var levenshtein = require('fast-levenshtein');
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var distance = levenshtein.get('back', 'book'); // 2
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var distance = levenshtein.get('我愛你', '我叫你'); // 1
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```
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**Locale-sensitive string comparisons**
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It supports using [Intl.Collator](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Collator) for locale-sensitive string comparisons:
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```javascript
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var levenshtein = require('fast-levenshtein');
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levenshtein.get('mikailovitch', 'Mikhaïlovitch', { useCollator: true});
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// 1
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```
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## Building and Testing
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To build the code and run the tests:
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```bash
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$ npm install -g grunt-cli
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$ npm install
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$ npm run build
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```
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## Performance
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_Thanks to [Titus Wormer](https://github.com/wooorm) for [encouraging me](https://github.com/hiddentao/fast-levenshtein/issues/1) to do this._
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Benchmarked against other node.js levenshtein distance modules (on Macbook Air 2012, Core i7, 8GB RAM):
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```bash
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Running suite Implementation comparison [benchmark/speed.js]...
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>> levenshtein-edit-distance x 234 ops/sec ±3.02% (73 runs sampled)
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>> levenshtein-component x 422 ops/sec ±4.38% (83 runs sampled)
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>> levenshtein-deltas x 283 ops/sec ±3.83% (78 runs sampled)
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>> natural x 255 ops/sec ±0.76% (88 runs sampled)
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>> levenshtein x 180 ops/sec ±3.55% (86 runs sampled)
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>> fast-levenshtein x 1,792 ops/sec ±2.72% (95 runs sampled)
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Benchmark done.
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Fastest test is fast-levenshtein at 4.2x faster than levenshtein-component
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```
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You can run this benchmark yourself by doing:
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```bash
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$ npm install
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$ npm run build
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$ npm run benchmark
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```
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## Contributing
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If you wish to submit a pull request please update and/or create new tests for any changes you make and ensure the grunt build passes.
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See [CONTRIBUTING.md](https://github.com/hiddentao/fast-levenshtein/blob/master/CONTRIBUTING.md) for details.
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## License
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MIT - see [LICENSE.md](https://github.com/hiddentao/fast-levenshtein/blob/master/LICENSE.md)
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