API serves Word2Vec model pre-trained on about 400M public Venmo transactions posted between 2014 and 2017. The model consists 200-dimensional vectors for 100,000+ words and emojis used on the payment platform. Word2Vec maps words to vectors in such a way that words that have similar meanings or that occur in similar contexts (based on their usage patterns) have vectors that are close together.
This project uses Pipenv to manage dependencies (described in the Pipfile) and Python virtual environments.
To get started, install Pipenv with pip:
$ pip install -U pipenv
On macOS, pipenv can also be installed via Homebrew:
$ brew install pipenv
To install the projects' dependencies, in the project's root folder run:
$ pipenv install --dev
Then run the web service:
pipenv run python -m flask run
Word2Vec automatically learns patterns and relationships in user interactions and the transactions they make.
To interact with the model, visit the http://localhost:5000/w2v_venmo/api/v0.1/most_similar endpoint. It accepts a list of words that contribute positively or negatively to a similarity measure between word vectors and returns the top-N most similar words.
$ curl http://localhost:5000/w2v_venmo/api/v0.1/most_similar \
--request POST \
--header "Content-Type: application/json" \
--data '{"positive": [""], "negative": [""], "topn": 1}'# The word vectors encode associations that reflect the usage patterns of emojis.
# For instance, users most often use the 'eggplant' and 'peach' emojis in the same context.
curl http://localhost:5000/w2v_venmo/api/v0.1/most_similar \
--request POST \
--header "Content-Type: application/json" \
--data '{"positive": ["🍆"]}'
'''
Out:
"similar": [("🍑", 0.777)]
'''
# Word2Vec also learns slang for certain transactions.
curl http://localhost:5000/w2v_venmo/api/v0.1/most_similar \
--request POST \
--header "Content-Type: application/json" \
--data '{"positive": ["marijuana"]}'
'''
Out:
"similar": [("weed", 0.751), ("kush", 0.621)]
'''
# The model also infers concepts related to combinations of words
curl http://localhost:5000/w2v_venmo/api/v0.1/most_similar \
--request POST \
--header "Content-Type: application/json" \
--data '{"positive": ["pizza", "football", "party"]}'
'''
Out:
"similar": [("superbowl", 0.489)]
'''