def match_where_are_you_from_response(user_input):
"""Match user input pattern for task 1.4.
PATTERN MATCHED:
BOT: Where are you from?
USR: [options]
I am from {Place}
I'm from {Place}
{Place}
[/options]
INFO RETURNED:
Where the user is from.
ISSUES:
- What if the respond with an ethnicity: e.g. I'm Taiwanese?
- To really validate this input we need to make sure they
say a place, e.g. "Taiwan", and not something silly like
"Earth".
Args:
user_input: the user input (SpaCy doc).
Returns:
models.Match object.
"""
r = r"^(I'm from |I am from )?%s(.)?$" % common_regex.NAME # same as place
match = False
info = None
pattern_match = re.match(r, user_input.text)
if pattern_match:
match = True
info = pattern_match.group('name')
return models.Match(user_input, match, info)
def match_how_are_you_response(user_input):
"""Match user input pattern for task 1.3.
PATTERN MATCHED:
BOT: How are you today?
USR: [options]
I am {state}(, thank you|thanks)
I'm {state}(, thank you|thanks)
{State}(, thank you|thanks)
I have a cold
Not bad
Not too bad
I feel happy
[/options]
INFO RETURNED:
The user's state.
ISSUES:
- There is a lot of potential variation in the state.
Therefore make this a regex group, extract it, and process
it separately.
Args:
user_input: the user input (SpaCy doc).
Returns:
models.Match object.
"""
match = False
info = None
r1 = r"^(I'm |I am )?" \
r"(very |not )?" \
r"(?P<state>([A-Z]{1}[a-z]*)|[a-z-]*)" \
r"(, thank you|, thanks)?(.)?$"
r2 = r'^I have (?P<state>(a cold|the flu))(.)?$'
cold_flu = ['a cold', 'the flu']
pattern_match1 = re.match(r1, user_input.text)
pattern_match2 = re.match(r2, user_input.text)
if pattern_match1:
modifier = pattern_match1.group(2)
state = pattern_match1.group(3)
# state should be an adjective
info_tok = NLP(state)[0]
if info_tok.tag_ in pos.ADJECTIVES:
match = True
info = state
if modifier:
info = modifier + state
elif pattern_match2:
state = pattern_match2.group(1)
if state in cold_flu:
match = True
info = state
# if we don't have a match thus far... try some more complicated methods.
if not match:
match, info = how_are_you_dep_match(user_input)
# NOTE: these nested if blocks suck. Wrap these as subfunctions and
# return for failing conditions. Cleaner that way...
return models.Match(user_input, match, info)
def match_nice_to_meet_you(user_input):
"""Match user input pattern for task 1.2.
PATTERN MATCHED:
BOT: Nice to meet you.
USR: Nice to meet you, too.
You, too.
Happy|Glad to meet you, too.
INFO RETURNED:
None.
Args:
user_input: the user input (SpaCy doc).
Returns:
models.Match object.
"""
r = r'^Nice to meet you, too(.)?'
match = False
info = None
if re.match(r, user_input.text):
match = True
return models.Match(user_input, match, info)
def match_name(user_input):
"""Match user input pattern for task 1.1.
I look for PRP VBP NNP.
pattern = db.get(...)
PATTERN MATCHED:
BOT: What's your name?
USR:
[option_set]
1: My name's ____.
2: My name is ____.
3: It's ____.
4: It is ____.
5: I'm ____.
6: I am ____.
7: ____.
[/option_set]
INFO RETURNED:
The user's name.
ISSUES:
- Deal with punctuation - i.e. full stop?
- What if they forget to capitalize their name?
Args:
user_input: the user input (SpaCy doc)
Returns:
models.Match object.
"""
regexs = [
r"^My name's %s(.)?$" % common_regex.NAME,
r'^My name is %s(.)?$' % common_regex.NAME,
r"^It's %s(.)?$" % common_regex.NAME,
r'^It is %s(.)?$' % common_regex.NAME,
r"^I'm %s(.)?$" % common_regex.NAME,
r'^I am %s(.)?$' % common_regex.NAME,
r'^%s(.)?$' % common_regex.NAME
]
match = False
info = None
for r in regexs:
pattern_match = re.match(r, user_input.text)
if pattern_match:
info = pattern_match.group('name')
if info not in common.INVALID_NAMES:
match = True
return models.Match(user_input, match, info)
def match_how_old_are_you_response(user_input):
"""Match user input pattern for task 1.5.
PATTERN MATCHES:
BOT: How old are you?
USR: [options]
I am {age} years old
I'm {age} years old
I am {age}
I'm {age}
{age} years old
{age}
[/options]
INFO RETURNED:
The user's age.
ISSUES:
- The age could be given as text or a number.
Args:
user_input: the user input (SpaCy doc).
Returns:
models.Match object.
"""
r = r'^' \
r"(I am |I'm )?" \
r"%s" % common_regex.NUMBER + \
r"( years old)?" \
r'(.)?' \
r'$'
match = False
info = None
pattern_match = re.match(r, user_input.text)
if pattern_match:
info = pattern_match.group('number')
age_match = common_regex.match_number(NLP(info))
match = age_match.match
return models.Match(user_input, match, info)
def match_what_grade_are_you_in_response(user_input):
"""Match user input pattern for task 1.6.
PATTERN MATCHES:
BOT: What grade are you in?
USR: [options]
I am in the {ordinal} grade.
I'm in the {ordinal} grade.
The {ordinal} grade.
[/options]
INFO RETURNED:
The user's grade.
ISSUES:
-
Args:
user_input: the user input (SpaCy doc).
Returns:
models.Match object.
"""
r = r'^' \
r"(I am in |I'm in )?" \
r'(The |the )' \
r"%s" % common_regex.ORDINAL + \
r"( grade)" \
r'(.)?' \
r'$'
match = False
info = None
pattern_match = re.match(r, user_input.text)
if pattern_match:
info = pattern_match.group('ordinal')
ordinal_match = common_regex.match_ordinal(NLP(info))
match = ordinal_match.match
return models.Match(user_input, match, info)
def no_match(user_input):
return models.Match(user_input, False, None)