Mock ML server for Semantic Search

Mock API server that simulates the NLP server that processes documents for semantic search

Installation

yarn install

Running the server

node server.js

The server runs on port 5000.

USAGE

The server has a single endpoint that accepts a JSON request and returns a JSON response. The request contains thee contents of the document to process and the response contains the results.

POST /semanticSearch/searchOneDoc

Request body schema

The request body is an object with the following properties

Property	Description
searchTerm	The concept to search for
contents	An object where each key is a page number and the value is the contents of the page. This is the same shape as the fullText property in Uwazi documents

Sample request:

{   
    "searchTerm": "This is the concept to search for",
    "contents": {
        "1": "This is the content of the first page",
        "2": "This is the content of the second page"
    }
}

Response body schema

The response body is an array of result items, where each result is an object of the following properties

Property	description
text	The text snipped that was matched
score	The score of the selected text snippet
page	The page where the snippet comes from

Sample response:

[
    {
        "page": 2, "text": "This is the content", "score": 0.7
    },
    {
        "page": 1, "text": "This is the content", "score": 0.7
    },
    {
        "page": 1, "text": "of the first page", "score": 0.4
    },
    {
        "page": 2, "text": "of the second page", "score": 0.3
    }
]

The mock server does not actually process the documents it receives, instead it simulates the process by splitting the sentences in each page (using . as a separator) and assigns each sentence a random score.