Fabel

Demo video

https://www.youtube.com/watch?v=L-01TIbkgkE

Team members

Parth Doshi (parthsdoshi), Max Lin (maxlincode)

Goals

Tag files with multiple classes to easily index new downloads. User can train the program as it indexes their files.

Running this repo

1. First, download the Bert pretrained model from https://storage.googleapis.com/bert_models/2018_10_18/uncased_L-12_H-768_A-12.zip
2. Place the unzipped pretrained model in the nn/bert/pretrained/ folder.
3. Navigate to the root of this repo and run pip install -r requirements.txt.
4. Run cd nn/bert/ && python3 bert_server.py.
5. This will load the Bert model and creates a REST API around it to respond to external requests.
6. Next, edit app/server.py and change the value of BERT_SERVER to the appropriate ip address and port.
7. Finally, navigate to ./app and run python3 main.py. This will launch the frontend.
8. Download the chrome extension under ./chrome_extension/src in to chrome which will allow us to automatically run downloaded documents through the app and tag them.

• Open the Extension Management page by navigating to chrome://extensions.
• Enable Developer Mode by clicking the toggle switch next to Developer mode.
• Click the LOAD UNPACKED button and select the extension directory.