This is a search engine and language model framework. Its API lets you project a language model onto a search tree.

It supports 64-bit wide vectors that may represent words, phrases, documents, topics, topics of topics or anything else really.

Built-in capabilities include interfacing with your language model through natural language, or by using a structured, boolean query language that supports AND, OR, NOT and (nested (scope)).

Go crazy with your modelling, as long as you have an equally crazy query parser.

There are a number of models included in the package.

The first model is a graph of words embedded as bags-of-characters. This model creates clusters of similar words.

The second model is a graph of documents embedded as continuous bags-of-words. This model creates clusters of similar documents, "topics". Because a document can have many phrases, it can be part of many topics.

The third model is a graph of documents represented as vectors as wide as there are topics in the lexicon, a "bag-of-topics" model.

Find documents with title "Rambo" or "First Blood" but only if the genre isn't "books", will be parsed into

+(title:rambo title:first blood) -(genre:books)

You may host one of these servers yourself, privately or publicly. Or you can use this free search cloud.

HTTPS POST didyougogo.com/io/[collection_name]
Content-Type:application/json
[
	{
		"field1":"value1"
	},
	{
		"field1":"value2"
	}
]

[
	1,
	2
]

HTTPS GET didyougogo.com/io/[collection_name]?id=[document_id]
Accept:application/json

HTTPS GET didyougogo.com/io/[collection_name]?q=[phrase-or-term]&fields=title&skip=0&take=10  
Accept:application/json

HTTPS GET didyougogo.com/io/[collection_name]?&qf=[scoped_query]&skip=0&take=10  
Accept:application/json

HTTPS GET didyougogo.com/?q=[phrase-or-term-query]&fields=title&skip=0&take=10&collection=[collection_name]

HTTPS GET didyougogo.com/queryparser/?q=[phrase-or-term-query]&qf=[scoped_query]&fields=title&skip=0&take=10&collection=[collection_name]

Create distributable readers and writers.
https://github.com/kreeben/resin/tree/master/src/Sir.HttpServer

Execute AND, OR and NOT set operations over local lists of Int64's (e.g. document references).
https://github.com/kreeben/resin/tree/master/src/Sir.Postings

On-disk database and in-memory index. Orchestrates remote set operations.
https://github.com/kreeben/resin/tree/master/src/Sir.Store

• v0.1a - bag-of-characters term vector space language model
• v0.2a - HTTP API comprised of distributable search microservices
• v0.3a - boolean query language with support for AND ('+'), OR (' '), NOT ('-') and scope ('(', ')').
• v0.4a - bag-of-words document vector space language model
• v0.5b - semantic language model
• v0.6b - local join between collections
• v0.7b - distributed join between collections
• v0.8 - voice-to-text
• v0.9 - image search
• v1.0 - text-to-voice
• v2.0 - AI