def start_alice_server(model_config, https=False, ssl_key=None, ssl_cert=None, port=None):
server_config_path = get_settings_path() / SERVER_CONFIG_FILENAME
server_params = get_server_params(server_config_path, model_config)
https = https or server_params['https']
if not https:
ssl_key = ssl_cert = None
else:
ssh_key = Path(ssl_key or server_params['https_key_path']).resolve()
if not ssh_key.is_file():
e = FileNotFoundError('Ssh key file not found: please provide correct path in --key param or '
'https_key_path param in server configuration file')
log.error(e)
raise e
ssh_cert = Path(ssl_cert or server_params['https_cert_path']).resolve()
if not ssh_cert.is_file():
e = FileNotFoundError('Ssh certificate file not found: please provide correct path in --cert param or '
'https_cert_path param in server configuration file')
log.error(e)
raise e
host = server_params['host']
port = port or server_params['port']
model_endpoint = server_params['model_endpoint']
model = build_model(model_config)
skill = DefaultStatelessSkill(model, lang='ru')
agent = DefaultAgent([skill], skills_processor=DefaultRichContentWrapper())
start_agent_server(agent, host, port, model_endpoint, ssl_key, ssl_cert)
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 get_default_agent():
model_config = read_json(model_config_path)
model = build_model_from_config(model_config)
skill = DefaultStatelessSkill(model)
agent = DefaultAgent([skill],
skills_processor=DefaultRichContentWrapper())
return agent
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 interact_model_by_telegram(config, token=None):
server_config_path = Path(get_settings_path(), SERVER_CONFIG_FILENAME)
server_config = read_json(server_config_path)
token = token if token else server_config['telegram_defaults']['token']
if not token:
e = ValueError(
'Telegram token required: initiate -t param or telegram_defaults/token '
'in server configuration file')
log.error(e)
raise e
model = build_model(config)
model_name = type(model.get_main_component()).__name__
skill = DefaultStatelessSkill(model)
agent = DefaultAgent([skill], skills_processor=DefaultRichContentWrapper())
init_bot_for_model(agent, token, model_name)
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 start_alice_server(model_config_path,
https=False,
ssl_key=None,
ssl_cert=None):
if not https:
ssl_key = ssl_cert = None
server_config_dir = Path(__file__).parent
server_config_path = server_config_dir.parent / SERVER_CONFIG_FILENAME
server_params = get_server_params(server_config_path, model_config_path)
host = server_params['host']
port = server_params['port']
model_endpoint = server_params['model_endpoint']
model = init_model(model_config_path)
skill = DefaultStatelessSkill(model, lang='ru')
agent = DefaultAgent([skill], skills_processor=DefaultRichContentWrapper())
start_agent_server(agent, host, port, model_endpoint, ssl_key, ssl_cert)
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())
def __post_init__(self):
self.cells.append(self.fallback)
skills = [cell.get_pattern_matching_skill() for cell in self.cells]
self.agent = DefaultAgent(skills)
def get_default_agent() -> DefaultAgent:
model = build_model(model_config)
skill = DefaultStatelessSkill(model) if default_skill_wrap else model
agent = DefaultAgent([skill],
skills_processor=DefaultRichContentWrapper())
return agent
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.']))
responses=['Добро пожаловать', 'Приветствую тебя, друг мой'],
patterns=['Привет', 'Здравствуйте', 'Здравствуй', 'Здорово', 'Ку'],
default_confidence=0.01)
bye = PatternMatchingSkill(
responses=['На этом прощаюсь с тобой', 'Всего доброго'],
patterns=['До свидания'])
help = PatternMatchingSkill(responses=[
'Вопрос любой задать мне можешь. Мудрый совет постараюсь я дать.'
],
patterns=['Что ты умеешь', 'Помощь'])
welcome = PatternMatchingSkill(responses=[
'Приветствую тебя, друг мой. Вопрос любой задать мне можешь. Мудрый совет постараюсь я дать.'
],
patterns=['^\s*$'],
regex=True,
default_confidence=0.01)
fallback = PatternMatchingSkill(
responses=['Мысль свою изложи подробнее, юный падаван'],
default_confidence=0.01)
faq = SimilarityMatchingSkill(save_load_path='./model', train=False)
agent = DefaultAgent([hello, bye, help, welcome, faq, fallback],
skills_selector=HighestConfidenceSelector())
start_agent_server(agent,
host='0.0.0.0',
port=5000,
endpoint='/faq',
ssl_key='/etc/letsencrypt/live/serg.ml/privkey.pem',
ssl_cert='/etc/letsencrypt/live/serg.ml/fullchain.pem')
from deeppavlov.agents.processors.highest_confidence_selector import HighestConfidenceSelector
# hello = PatternMatchingSkill(responses=["Hello world!"], patterns=["(hi|hello|good day)"], regex = True)
# sorry = PatternMatchingSkill(responses=["don't be sorry", "Please don't"], patterns=["(sorry|excuse)"], regex = True)
# perhaps = PatternMatchingSkill(responses=["Please be more specific"], patterns=["(.*)perhaps(.*)"], regex = True)
hello = PatternMatchingSkill(responses=['Hi, I am a chatbot'],
patterns=['hi', 'hello', 'How are you'],
default_confidence=0.3)
faq = SimilarityMatchingSkill(
data_path='http://files.deeppavlov.ai/faq/dataset.csv',
x_col_name='Question',
y_col_name='Answer',
save_load_path='./model',
config_type='tfidf_autofaq',
edit_dict={},
train=False)
bye = PatternMatchingSkill(responses=['have a nice day'],
patterns=['bye', 'goodbye'],
default_confidence=0.3)
agent = DefaultAgent([hello, bye, faq],
skills_selector=HighestConfidenceSelector())
# agent = DefaultAgent([hello, sorry, perhaps], skills_selector=HighestConfidenceSelector())
# q = agent(['hi, how are you', 'I am sorry', 'perhaps I am not sure'])
q = agent(['Hello', 'How can I get a visa?'])
print(q)