Tellina uses natural language processing (NLP) to translate an English sentence, such as "Find text file in the current folder", into a bash command, such as find . -name "*.txt".
You can try it now at http://tellina.rocks . Or, you can install it locally; this document tells you how.
Tellina uses Tensorflow 2.0.
Follow the instructions on the Tensorflow website. The simplest way is to install using pip3.
pip3 install -r requirements.txt
git submodule update --init --remote
git submodule foreach git pull origin master
make submodule
To update the tellina_learning_module in the future, run:
make submodule
make db
make run
To experiment with the translation model locally, make sure to set following control variables correctly.
WEBSITE_DEVELOP (website/views.py)
- True, start the web server without importing the Tensorflow translation module (no server start delay, suggested setting when testing peripheral website functions)
- False (default), start the web server and translate new queries (5-10 secs server start delay due to Tensorflow graph building)
CACHE_TRANSLATIONS (website/views.py)
- True, cache translation results for natural language queries that were seen
- False (default), run translation model on every query, regardless of whether it has been seen or not
CPU_ONLY (website/backend_interface.py)
- True (default), run Tellina on CPU
- False, run Tellina on GPU if and only if the host machine has GPU installed
Visit http://127.0.0.1:8000 in your browser.
If you used Tellina in your work, please cite
@techreport{LinWPVZE2017:TR,
author = {Xi Victoria Lin and Chenglong Wang and Deric Pang and Kevin Vu and Luke Zettlemoyer and Michael D. Ernst},
title = {Program synthesis from natural language using recurrent neural networks},
institution = {University of Washington Department of Computer Science and Engineering},
number = {UW-CSE-17-03-01},
address = {Seattle, WA, USA},
month = mar,
year = {2017}
}