word2vec-api

Simple web service providing a word embedding API. The methods are based on Gensim Word2Vec implementation. Models are passed as parameters and must be in the Word2Vec text or binary format.

• Launching the service

python word2vec-api --model path/to/the/model [--host host --port 1234]

• Example calls

curl http://127.0.0.1:5000/word2vec/n_similarity?ws1=Sushi&ws1=Shop&ws2=Japanese&ws2=Restaurant
curl http://127.0.0.1:5000/word2vec/similarity?w1=Sushi&w2=Japanese
curl http://127.0.0.1:5000/word2vec/most_similar?positive=indian&positive=food[&negative=][&topn=]
curl http://127.0.0.1:5000/word2vec/model?word=restaurant

Note: The "model" method returns a base64 encoding of the Word2Vec vector.

Where to get a pretrained model

In case you do not have domain specific data to train, it can be convenient to use a pretrained model. Please feel free to submit additions to this list through a pull request.