simsity 0.0.1

Simple Similarity Service

simsity

simsity: it's all about the neighborhood

Simsity is a Super Simple Similarities Service. This repository contains simple tools to help in similarity retreival scenarios. Typical usecases include early stage bulk labelling and duplication discovery.

Warning

Alpha software. Expect things to break. Do not use in production.

Example

This is the basic setup for this package.

from simsity.service import Service
from simsity.indexer import PyNNDescentIndexer
from sklearn.feature_extraction.text import CountVectorizer


# The Indexer handles the nearest neighbor search
# The Encoder handles the encoding of the datapoints
service = Service(
    indexer=PyNNDescentIndexer(metric="euclidean"),
    encoder=CountVectorizer()
)

# Index the datapoints
service.train_from_csv("clinc-data.csv", text_col="text")

# Query the datapoints
service.query("give me directions", n_neighbors=100)

# Save the entire system
service.save("/tmp/simple-model")

# You can also load the model now.
Service.load("/tmp/simple-model")