(based on original interactive sempre repository https://github.com/sidaw/sempre-interactive)

See SEMPRE-DOCUMENTATION.md.

This specific version of SEMPRE is a modification of the Voxelurn project which uses SEMPRE as the basis for a block-building world where input utterances act as build instructions for the block world (displayed with a browser-based JavaScript application). This version SEMPRE spcifically models a simple environment where a robot can move around a small map and pick/drop colored items. In addition to using the core language to control the robot, a user can define custom commands which are learned by the system improving its ability to understand more natural language-style commands.

You must have the following already installed on your system.

• Java 8 (not 7)
• Ant 1.8.2
• Ruby 1.8.7 or 1.9
• wget

Other dependencies will be downloaded as you need them. SEMPRE has been tested on Ubuntu Linux 16.04, Debian 8, and MacOS X. Your mileage will vary depending on how similar your system is.

1. Clone this GitHub repository:

    git clone https://github.com/mpi-sws-rse/sempre-interactive-flipper.git (https)
    git clone [email protected]:mpi-sws-rse/sempre-interactive-flipper.git (ssh)
   

2. Download the minimal core dependencies (all dependencies will be placed in lib):

    ./pull-dependencies core
   

3. Compile the source code (this produces libsempre/sempre-core.jar):

    ant interactive
   

4. Run server (defaults to port 8410):

    ./interactive/run @mode=voxelurn
   

The command should execute, display some information about the grammar, and wait for input from the browser client (server can be stopeed with Ctrl+D. To go further with running sempre in the context of Robotic world, check Flipper

While rewriting user's definition (option GrammarInducer.useEquivalentRewriting), the rewritings are scored based on both best packing score and the semantic similarity (cosine similarity of average of words in the spec). In order to use semantic similarity (option GrammarInducer.useSemanticSimilarityOfSentences), you have to provide a file with trained vectors (e.g. from GloVe) and give a path to it in the option InteractiveMaster.wordEmbeddingsFilePath.

Here are some general tips for troubleshooting:

• If the browser client is acting weirdly
  • Pull the newest version for the repository (no need to restart yarn)
  • On the panel on the right side, press Clear
• If the code does not compile or immediately fails at runtime
  • Pull newest version of the code
  • Run ant clean and then ant interactive
• If the server throws an error during use with the browser client
  • Open an issue detailing the server-side error and the client-side input
• If all previously learned rules have to be forgotten, one can clean the file sempre-interactive/int-output/grammar.log.json

The corresponding browser-based client to this project can be found here.