Skip to content

Latest commit

 

History

History
12 lines (9 loc) · 1.12 KB

README.md

File metadata and controls

12 lines (9 loc) · 1.12 KB

Rosette API Text Embeddings Sample Code

This is a little python code to show how to calculate the similarity between words by computing the cosine similarity (using numpy) between the words' embeddings, returned from the Rosette API's new /text-embedding endpoint. The call to the API uses the 1.3 version of the python binding, so be sure to install that package via $ pip install rosette-api or --upgrade via pip to get the latest.

To try it out

  1. Clone the repo and open the files in your favorite text editor/python IDE.
  2. In cosine_similarity.py, replace the user_key parameter's value [your key here] with your Rosette API key and save.
  3. Run test_embeddings.py via your python IDE or command line: $ python test_embeddings.py

Customize for your data

Try editing test_embeddings.py to compare words OR longer text you might be interested in to see how their embeddings compare. And if you find anything interesting, let us know! Find us at support.rosette.com or [email protected].