Quese NPM | npm.io

QUESE

"Quese" allows you implement in an easy way a Search Algoritm, based on Embeddings and Semantic Similarity, in your JavaScripts apps. The package is available in python (pip) as well: https://pypi.org/project/quese/

The module provides:

Searcher: a REACT COMPONENT with a search algoritm and a UI implemented yet. However, you can customize the search algoritm and the UI of the component by pasing diferent props. More information about the Searcher props below.
searchByEmbeddings(): an asynchronous FUNCTION with several params to customize the searching process. More information about the searchByEmbeddings() params below.

COMPATIBILITY

	Create React App	Node
Searcher	YES	NO
searchByEmbeddings	NO	YES

USAGE

1. Searcher component:

Example of an implementation of the Searcher component.

2. searchByEmbeddings function:

Example of an implementation of the searchByEmbeddings function.

PARAMS AND PROPS

1. Seacher props:

Name	Required	Format	Description	Default value
data	true	Array of objects	Represents the data you want to search for	undefined
by	true if not template	String	Represents the key of your objects that is going to be compared with the query in the searching process	undefined
template	true if not by	String, object keys between {}	Similar to the "by" prop, allows you to create a customized sentence for compare with the query	undefined
accuracy	false	Number (0-1)	It represents the minimum similarity rate wich the object must have with the quey to be returned	0.5
defaultStyle	false	Boolean	Boolean value wich indicates if the default style will be charged or the user prefer her own style	true
InputStyle	false	Object	The typical object for stylize your components in react, but in this case to stylize the input of the Searcher component	undefined
ContainerStyle	false	Object	The typical object for stylize your components in react, but in this case to stylize the div of the Searcher component	undefined
inputClassName	false	String	The typical className prop, but in this case to stylize the input of the Searcher component	undefined
ContainerClassname	false	String	The typical className prop, but in this case to stylize the div of the Searcher component	undefined
renderItemFunction	false unless you use the template prop	JSX Function	Function with two params: the item and the index, in wich you can customize the structure and the style of the previous results	undefined
itemLinkFunction	false	Function	Function with two params: the item and the index, in wich you can customize the href of each previous result returning a dinamyc string	undefined
onSearchChange	false	Function	It's a function to handle the results for each change of the input. The first param are this results.	undefined
onSearchSubmit	false	Function	It's a function to handle the results for each submit of the input. The first param are this results.	undefined
iconCancel	false	Boolean	Boolean value to define if the icon for cancel the search will be charged or not	true
iconSearch	false	Boolean	Boolean value to define if the search icon will be charged or not	true
placeholder	false	String	The typical input placeholder...	"Search..."
prevResults	false	String	Boolean value to define if the previous results (the results between the input) will be charged or not	true
maxPrevResults	false	Number	Number that define the maximum number of previous results that will be charged	undefined

2. seachByEmbeddings() params:

Name	Required	Format	Description	Default value
data	true	Array of objects	Represents the data you want to search for	undefined
query	true	String	Represents the query of your searching process	undefined
by	true if not template	String	Represents the key of your objects that is going to be compared with the query in the searching process	undefined
template	true if not by	String, object keys between {}	Similar to the "by" prop, allows you to create a customized sentence for compare with the query	undefined
accuracy	false	Number (0-1)	It represents the minimum similarity rate wich the object must have with the quey to be returned	0.5
model	false	String	The HuggingFace model you want to use to create the embeddings (take care if it works with Transformers.js and if it's able to do the feature-extraction task)	"Xenova/all-MiniLM-L6-v2"