def learn(self, train):
h = pd.read_csv('./app/database/hello_skill.csv')
hello = PatternMatchingSkill(responses=[
x for x in h['responses'].tolist() if x != ' ' and x == x
],
patterns=[
x for x in h['patterns'].tolist()
if x != ' ' and x == x
])
b = pd.read_csv('./app/database/bye_skill.csv')
bye = PatternMatchingSkill(responses=[
x for x in b['responses'].tolist() if x != ' ' and x == x
],
patterns=[
x for x in b['patterns'].tolist()
if x != ' ' and x == x
])
f = pd.read_csv('./app/database/fallback_skill.csv')
fallback = PatternMatchingSkill(responses=[
x for x in f['responses'].tolist() if x != ' ' and x == x
],
default_confidence=0.1)
faq = SimilarityMatchingSkill(data_path=self.DATANAME,
x_col_name='Question',
y_col_name='Answer',
save_load_path=self.MODELNAME,
config_type='tfidf_autofaq',
train=train)
self.d = DefaultAgent([hello, bye, faq, fallback],
skills_selector=HighestConfidenceSelector())
def setup(self):
# print(configs.aiml_skill)
config_ref = configs.skills.rasa_skill
install_from_config(config_ref)
# rasa_skill = build_model(
# "/home/alx/Workspace/DeepPavlov/deeppavlov/configs/aiml_skill/rasa_skill.json",
# download=True)
rasa_skill = build_model(config_ref, download=True)
self.agent = DefaultAgent([rasa_skill],
skills_selector=HighestConfidenceSelector())
def __init__(self,
skills: List[Skill],
skills_processor: Optional[Processor] = None,
skills_filter: Optional[Filter] = None,
*args,
**kwargs) -> None:
super(DefaultAgent, self).__init__(skills=skills)
self.skills_filter: Filter = skills_filter or TransparentFilter(
len(skills))
self.skills_processor: Processor = skills_processor or HighestConfidenceSelector(
)
def make_hello_bot_agent() -> DefaultAgent:
"""Builds agent based on PatternMatchingSkill and HighestConfidenceSelector.
This is agent building tutorial. You can use this .py file to check how hello-bot agent works.
Returns:
agent: Agent capable of handling several simple greetings.
"""
skill_hello = PatternMatchingSkill(['Hello world'],
patterns=['hi', 'hello', 'good day'])
skill_bye = PatternMatchingSkill(['Goodbye world', 'See you around'],
patterns=['bye', 'chao', 'see you'])
skill_fallback = PatternMatchingSkill(
['I don\'t understand, sorry', 'I can say "Hello world"'])
agent = DefaultAgent([skill_hello, skill_bye, skill_fallback],
skills_processor=HighestConfidenceSelector())
return agent
def setup(self):
config_ref = configs.skills.aiml_skill
install_from_config(config_ref)
aiml_skill = build_model(config_ref, download=True)
self.agent = DefaultAgent([aiml_skill],
skills_selector=HighestConfidenceSelector())
from deeppavlov.skills.pattern_matching_skill import PatternMatchingSkill from deeppavlov.agents.default_agent.default_agent import DefaultAgent from deeppavlov.agents.processors.highest_confidence_selector import HighestConfidenceSelector hello = PatternMatchingSkill(responses=['Hello world!'], patterns=["hi", "hello", "good day"]) bye = PatternMatchingSkill(['Goodbye world!', 'See you around'], patterns=["bye", "chao", "see you"]) fallback = PatternMatchingSkill(["I don't understand, sorry", 'I can say "Hello world!"']) HelloBot = DefaultAgent([hello, bye, fallback], skills_selector=HighestConfidenceSelector()) print(HelloBot(['Hello!', 'Boo...', 'Bye.']))
from deeppavlov.agents.default_agent.default_agent import DefaultAgent
from deeppavlov.agents.processors.highest_confidence_selector import HighestConfidenceSelector
from deeppavlov.skills.pattern_matching_skill import PatternMatchingSkill
if __name__ == '__main__':
bye = PatternMatchingSkill(['Goodbye world!', 'See you around'],
patterns=['bye', 'ciao', 'see you'])
hello = PatternMatchingSkill(responses=['Hello world!'],
patterns=['good day', 'hello', 'hi'])
fallback = PatternMatchingSkill(['I\'m sorry; I don\'t understand.'])
agent = DefaultAgent([hello, bye, fallback],
skills_selector=HighestConfidenceSelector())
for query in ['Hello', 'Bye', 'Or not']:
response = agent([query])
print('Q: {} A: {}'.format(query, response[0]))