PAL

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Installation & Running

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Requirements

• Python 2.7 with pip
  • Required Python packages in requirements.txt
• PostgreSQL 9.3 required for directory service
• Node.js > v0.10 for pizza service
• Web server capable of running wsgi applications for deployment

Base Installation

We recommend installing PAL in a python virtual environment by using the virtualenv package. Use pip to install virtualenv then create a new virtualenv in the pal directory

virtualenv env

and activate the virtual environment

source env/bin/activate

If not using the directory service and/or PostgreSQL is not installed, remove the line containing psycopg2 from the requirements.txt file. Install the required packages

pip install -r requirements.txt

Next, install the required nltk libraries. Open a python shell and type

>>> import nltk
>>> nltk.download()

and install maxent_ne_chunker, maxent_treebank_pos_tagger, punkt, qc, and words.

Obtain API keys for TMDB, Wolfram, and Yelp and insert them into config.py. Obtain a Facebook app ID and insert it into static/home.js.

PAL is now ready to run locally. Start it by running python server.py. PAL can be accessed by connecting to localhost:5000 in a browser.

Hill Climb Instructions

To ensure that queries are properly sorted into the proper services, hill climbing should be run. From the base directory, run

python -m pal.heuristics/hill_climb.hill_climb

After running hill climbing, updated heuristics values can be found in the pal/heuristics/hill_climb/climbed_values directory, and will be automatically referenced by the rest of PAL. Hill climbing should be re-run whenever a new service is added to PAL.

Pizza Service Installation

The pizza service requires Node.js or io.js. Install one of these and npm. Navigate to the api/dominos directory and run

npm install

Next, install forever with

npm install -g forever

Start the pizza server with

forever start server.js

Scraping the Directory

In order for the directory service to function, the directory must be pre-scraped. Navigate to the api/directory directory. Insert the username and password for the database in the stalkernet_scraper.py file with the format postgresql://username:password@database_url/table_name

Create the database schema by running

python models.py

Populate the buildings, majors, and departments tables by running

python stalkernet_scraper.py -b buildings.txt python stalkernet_scraper.py -m majors.txt python stalkernet_scraper.py -d depts.txt

Finally, scrape the directory with

python stalkernet_scraper.py -s

Installing in Apache

PAL can be run by Apache HTTP Server by using the mod_wsgi module. The Flask documentation has pretty detailed instructions on how to set this up. Please see http://flask.pocoo.org/docs/0.10/deploying/mod_wsgi/

Services

• Bon Appetit (actively scraped from [Bon Appetit website] (http://carleton.cafebonappetit.com/cafe/))

  • Single dining hall, single day, any or all meals

• Dictionary/Thesaurus (actively scraped from [dictionary] (http://dictionary.reference.com/browse/) or [thesaurus] (http://www.thesaurus.com/browse/))

  • Definitions
  • Synonyms
  • Antonyms

• Directory (pre-scraped from [Carleton campus directory] (http://apps.carleton.edu/campus/directory/))

  • Single-person queries
    • Professor offices / Student rooms
    • email addresses (both)
    • phone numbers (both)
    • departments/majors (professors/students)
    • Class year
  • Multi-person queries
    • All students on a floor / in a dorm
    • All students for a given major
    • All professors in a department
    • "Show me all the Brians on campus"

• Dominos (requests to [Dominos online order] (https://order.dominos.com/en/pages/order/))

  • Pizza cost
    • price of a single pizza
    • price of multiple same pizzas
    • price of multiple different pizzas
  • Pizza orders
    • order a single pizza
    • order multiple same pizzas
    • order multiple different pizzas

• Facebook (requests to [Facebook Graph API] (https://developers.facebook.com/docs/graph-api))

  • Post to timeline on behalf of user

• Movies (using the [TMDB API] (https://www.themoviedb.org/documentation/api))

  • What movies was this person involved in (acting, directing, etc.)
  • Was this person involved in this movie?
  • How many movies was this person involved in?
  • When did this movie come out?
  • Who acted/directed/etc. in this movie?
  • Who played this character in this movie?

• Translations (requests through [UltraLingua REST API] (http://api.ultralingua.com/ulapi/rest)

  • From English to {Spanish, French, German, Italian, Portuguese}
  • From {Spanish, French, German, Italian, Portuguese} to English
  • Between {Spanish, French, German, Italian, Portuguese}
  • Use correct SpeechSynthesisVoice for the destination language

• Weather (requests to [Yahoo weather API] (https://query.yahooapis.com/v1/public/yql?))

  • High/low temperatures
  • Snow/rain
  • General forecast
  • Geolocation

• Wolfram|Alpha (requests using [Wolfram|Alpha's API] (http://products.wolframalpha.com/api/))

  • Run queries on natural language and get numerical output
  • Keep track of our limited number of queries (difficult due to concurrency issues)

• Yelp (requests to [Yelp API] (http://www.yelp.com/developers/documentation))

  • Businesses by search terms
  • Ratings, URL, Phone Number
  • Find by location
  • Businesses appear on map