COMP 10261 The FAQ Bot Phase 0
An FAQ Bot answers questions about a particular topic. It is a
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conversational interface to a stock set of questions and answers.
When an FAQ Bot receives an utterance, it determines the
user’s intent by matching that utterance to one of its stored
question and answer pairs. If it succeeds in determining intent in
this way, it uses the answer as its response. In the example on
the right (from Vajjala et al.’s Practical Natural Language
Processing) the FAQ Bot has determined that the first two
utterances have the same intent and has responded with the
same text in both cases.
If an FAQ Bot fails to determine intent, it usually outputs a
standard message to let the user know that it does not know the
This is Phase 0 of the project – getting started.
THE FAQ DOMAIN
In this phase, the goal is to make sure you have a basis to start
from. You will prepare the data for your FAQ Bot and implement a very simple string-matching FAQ bot
using faq_bot_skeleton.py on Canvas.
1. Determine your FAQ Bot’s knowledge domain and prepare a set of 20 question and answer
pairs. One easy way to do this is to find a long Wikipedia page and copy sections of 1 to 3
sentences as each answer (the more text the better), then generate a question to go with each
answer. Make sure you reference all online sources in comments. (Reminder: The topic
“Mohawk College” is not allowed, but any other topic is fair game.)
2. Store your questions and answers in text files.
3. Create a python program that loads the answers and questions from your file(s), then allows the
user to make utterances. Use string matching to find a match between for user’s utterance in
your list of questions, then output the corresponding answer as a response. You can adapt
faq_bot_skeleton.py and file_input.py for this purpose, or you can write your code from
4. The bot should also respond to “hello” by greeting the user, and “goodbye” or “quit” by ending
the program.
5. If the bot fails to match an utterance, it should politely let the user know that it did not
recognize their question.
Are there limits to the size of
dataset I can use for training?
Amazon Machine Learning can
train models on datasets up to
100GB in size.
What is the maximum size of
training dataset?
Amazon Machine Learning can
train models on datasets up to
100GB in size.
What algorithm does Amazon
Machine Learning use to
generate models?
Amazon Machine Learning
currently uses an industry
standard logistic regression
algorithm to generate models.
6. You should incorporate some basic string processing (see the Strings handout and strings.py on
canvas) to make your intent matching a bit more forgiving. At the very least, try to be forgiving
with case matching, whitespace, and punctuation.
DISCORD INTEGRATION
Once the bot is working well in the Python shell, you should make it available as a Discord bot and
include a link to add the bot to a server when you hand in. You can use the simple_discord_faq_bot.py
file on Canvas as a starting point to turn your chat bot into a discord bot.
OPTIONAL: HOSTING AND KEEPING THE BOT ALIVE
If you hand in your Discord token along with your code, the instructor will be able to fire up the bot, so
there’s no need to do anything further. But one challenge of bot development is how to host and keep
the bot alive and running all the time.
The solution is to find a server that is always running, start up the bot on that server, and then monitor
to keep it running. If you have access to a server of your own and the ability to set up python on that
server, you might be able to use it for this. If not, there are cheap hosting services that specialize in
discord bots. For example, SparkedHost charges only $1 (US) per month for its hosting services.
https://sparkedhost.com/discord-bot-hosting
HANDING IN
You should start your bot and make sure it’s accessible from Discord. Then place all the following into a
single project folder, then zip it up and hand it in on Canvas.
1. A folder containing all the code and supporting files for the Python shell and Discord versions of
your bot. It should be possible to run the bot from this folder (both standalone and Discord
versions).
2. A test file called “instructions.txt”. This file should contain the link to the discord version of your
bot along with any special instructions required to talk to it (prefixes, etc.). If your bot does
anything clever or unusual that you want me to notice, you should write about it here.
See Canvas for the due date.
https://sparkedhost.com/discord-bot-hosting
EVALUATION
This assignment will be marked out of 5 using the following Rubric. It will be worth 5% of your grade.
Category Level 4: 100% Level 3: 75% Level 2: 50% Level 1:
(2 points)
Content consists of 20 or
more questions and
answers. Each answer
consists of 1 or more
complete sentences. The
questions are a good
match for the answers.
Content consists
of 20 or more
questions and
answers. Most
answers consist
of 1 or more
sentences. Most
questions are a
good match for
the answers.
Content consists of
some questions
and answers. Most
answers consist of
sentences. Most
questions are a
good match for the
consists of
String Matching
Use string matching
effectively to answer all
questions identified by
the developer. Offer
meaningful responses to
other utterances (“hello”,
“goodbye”, “I don’t know
the answer to that”, etc.)
Use string
matching to
answer some
questions correctly.
Discord Hosting
Bot can be added to a
discord server and
functions as well as the
Python shell version.
Bot can be added
to a discord server
and responds to
utterances.
Documentation
Commenting and naming
conventions are
consistent with course
standards (based on the
PEP-8 and PEP-257). All
files contain a docstring
with a description, author
information, and links to
original sources. All
functions contain a
docstring with description
of behavior, parameters,
and return values.
Commenting and
conventions are
consistent with
course standards
and/or docstrings
are missing or
incomplete for
some files.
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