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README

This interactive package is the code for our paper Naturalizing a programming language through interaction (ACL 2017)

Voxelurn is a language interface to a voxel world. This server handles commands used to learn from definitions, and other interactive queries. In this setting, the system begin with the dependency-based action language (dal.grammar), and gradually expand the language through interacting with it users.

Running the Voxelurn server

Setup SEMPRE dependencies and compile

  ./pull-dependencies core
  ant interactive

Start the server

 ./interactive/run @mode=voxelurn -server -interactive

things in the core language such as add red left, repeat 3 [select left] should work.

Feed the server existing definitions, which should take less than 2 minutes.

 ./interactive/run @mode=simulator @server=local @sandbox=none @task=freebuilddef -maxQueries 2496

try add dancer now.

Interacting with the server

There are 3 ways to interact and try your own commands

Hit Ctrl-D on the terminal running the server, and type add red top, or add green monster
On a browser, type http://localhost:8410/sempre?q=(:q add green monster)
The visual way is to use our client at https://github.com/sidaw/shrdlurn, which has a more detailed README.md. Try [add dancer; front 5] 3 times after you run the client. A live version is at voxelurn.com.

Experiments in ACL2017

Start the server

./interactive/run @mode=voxelurn -server -interactive
Feed the server all the query logs

./interactive/run @mode=simulator @server=local @sandbox=none @task=freebuild -maxQueries 103876

This currently takes just under 30 minutes. Decrease maxQuery for a quicker experiment. This generate plotInfo.json in ../state/execs/${lastExec}.exec/ where lastExec is cat ../state/lastExec.

Taking ../state/execs/${lastExec}.exec/plotInfo.json as input, we can analyze the data and produce some plots using the following ipython notebook
```
ipython notebook analyze_data.ipynb
```

which prints out basic statistics and generates the plots used in our paper. The plots are saved at ../state/execs/${lastExec}.exec/

Misc.

There are some unit tests

./interactive/run @mode=test

To specify a specific test class and verbosity

./interactive/run @mode=test @class=DALExecutorTest -verbose 5

Clean up or backup data

./interactive/run @mode=backup # save previous data logs
./interactive/run @mode=trash # deletes previous data logs

Data, in .gz can be found in queries.

./interactive/queries/freebuildbig-0206.def.json.gz has 2495 definitions combining just over 10k utterances.
./interactive/queries/freebuildbig-0206.json.gz has 103875 queries made during the main experiment.

Client server (optional and in development)

This server helps with client side logging, leaderboard, authentication etc. basically anything that is not directly parsing.

cd interactive
python community-server/install-deps.py
export SEMPRE_JWT_SECRET=sdlfdsaklafsl
export SLACK_SECRET=somekeyyougetfromslack
python community-server/server.py --port 8403

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