Micro Levenshtein

Spell check and sanatizer based on contexts where each context has its dictionary.

Getting Started

Requirements

Node >= 8
Yarn | NPM

Installing

Install dependencies

yarn | npm install

Run the project

yarn start | npm start

The service starts on port 3000 by default if you do not set the PORT environment variable

Usage

Send a GET request to http://localhost:3000

Headers

At the moment there are no security validations

Content-Type application/json

Body

You can change the dict parameter for your own dictionary

{
	"text": "chivitooooo comn de jamon con muzarela yyyyyyyy rucula #~#@#~|@#|@ con 1kg de requesoooooon",
	"dict": "chivito"
}

Output

You will get a clean text and the suggestions to the words with possible grammatical errors ordered by best match

{
    "suggestion": {
        "chivito": null,
        "comn": [
            "común",
            "con",
            "lomo"
        ],
        "de": null,
        "jamon": [
            "jamón"
        ],
        "con": null,
        "muzarela": [
            "muzzarella"
        ],
        "y": null,
        "rucula": [
            "rúcula"
        ],
        "": [],
        "1kg": [],
        "requeson": null
    }
}

Add your own dictionary

Add a new .dic file in the dict folder. Each word must be separated by a line break and must not contain spaces at the end of it

TODO

Improve effectiveness and speed and much more

Built With

Micro - Asynchronous HTTP microservices

machester4/micro-levenshtein