class Brain(object):
NLU_UTTERANCE = 'NLU_Matching'
def __init__(self, bot, configuration: BrainConfiguration):
assert (bot is not None)
assert (configuration is not None)
self._bot = bot
self._configuration = configuration
self._binaries = BinariesManager(configuration.binaries)
self._braintree = BraintreeManager(configuration.braintree)
self._tokenizer = Tokenizer.load_tokenizer(configuration)
if configuration.debugfiles.save_errors_collection is True:
errors_dict = {}
else:
errors_dict = None
self._denormal_collection = DenormalCollection(errors_dict)
self._normal_collection = NormalCollection(errors_dict)
self._gender_collection = GenderCollection(errors_dict)
self._person_collection = PersonCollection(errors_dict)
self._person2_collection = Person2Collection(errors_dict)
self._rdf_collection = RDFCollection(errors_dict)
self._sets_collection = SetCollection(errors_dict)
self._maps_collection = MapCollection(errors_dict)
self._properties_collection = PropertiesCollection(errors_dict)
self._default_variables_collection = DefaultVariablesCollection(
errors_dict)
self._botnames_collection = BotNamesCollection(errors_dict)
self._preprocessors = PreProcessorCollection(errors_dict)
self._postprocessors = PostProcessorCollection(errors_dict)
self._pattern_factory = None
self._template_factory = None
self._security = SecurityManager(configuration.security)
self._oobhandler = OOBHandler(configuration.oob)
self._regex_templates = RegexTemplatesCollection(errors_dict)
self._dynamics_collection = DynamicsCollection()
self._aiml_parser = self.load_aiml_parser()
self._nlu_collection = NluCollection(bot.client, configuration.nlu,
errors_dict)
self._nlu = NluRequest.load_nlu(configuration.nlu)
self._nlu_utterance = None
self.load(self.configuration)
if configuration.debugfiles.save_errors_collection is True:
storage_factory = self.bot.client.storage_factory
if storage_factory.entity_storage_engine_available(
StorageFactory.ERRORS_COLLECTION) is True:
errors_collection_engine = storage_factory.entity_storage_engine(
StorageFactory.ERRORS_COLLECTION)
errors_collection_store = errors_collection_engine.errors_collection_store(
)
errors_collection_store.save_errors_collection(errors_dict)
def ylogger_type(self):
return "brain"
@property
def id(self):
return self._configuration.section_name
@property
def bot(self):
return self._bot
@property
def configuration(self):
return self._configuration
@property
def aiml_parser(self):
return self._aiml_parser
@property
def denormals(self):
return self._denormal_collection
@property
def normals(self):
return self._normal_collection
@property
def genders(self):
return self._gender_collection
@property
def persons(self):
return self._person_collection
@property
def person2s(self):
return self._person2_collection
@property
def rdf(self):
return self._rdf_collection
@property
def sets(self):
return self._sets_collection
@property
def maps(self):
return self._maps_collection
@property
def properties(self):
return self._properties_collection
@property
def default_variables(self):
return self._default_variables_collection
@property
def botnames(self):
return self._botnames_collection
@property
def preprocessors(self):
return self._preprocessors
@property
def postprocessors(self):
return self._postprocessors
@property
def pattern_factory(self):
return self._pattern_factory
@property
def template_factory(self):
return self._template_factory
@property
def regex_templates(self):
return self._regex_templates
@property
def dynamics(self):
return self._dynamics_collection
@property
def tokenizer(self):
return self._tokenizer
@property
def nlu(self):
return self._nlu
@property
def security(self):
return self._security
def load_aiml_parser(self):
self._load_pattern_nodes()
self._load_template_nodes()
return AIMLParser(self)
def load_aiml(self):
YLogger.debug(self, "Loading aiml source brain")
self._aiml_parser.load_aiml()
def reload_aimls(self):
YLogger.debug(self, "Loading aiml source brain")
self._aiml_parser.empty()
self._aiml_parser.load_aiml()
def load(self, configuration: BrainConfiguration):
self._load_properties()
if self.properties.has_property("punctuation_chars") is True:
self.tokenizer.set_configuration_punctuation_chars(
self.properties.property("punctuation_chars"))
if self.properties.has_property("before_concatenation_rule") is True:
self.tokenizer.set_configuration_before_concatenation_rule(
self.properties.property("before_concatenation_rule"))
if self.properties.has_property("after_concatenation_rule") is True:
self.tokenizer.set_configuration_after_concatenation_rule(
self.properties.property("after_concatenation_rule"))
YLogger.debug(self, "Loading collections")
self.load_collections()
YLogger.debug(self, "Loading dynamics sets, maps and vars")
self.load_dynamics()
YLogger.debug(self, "Loading services")
self.load_services(configuration)
load_aiml = True
if self.configuration.binaries.load_binary is True:
load_aiml = self._binaries.load_binary(
self.bot.client.storage_factory)
if load_aiml is False:
self._aiml_parser = self._binaries.get_aiml_parser()
if load_aiml is True:
self.load_aiml()
self._binaries.set_aiml_parser(self._aiml_parser)
if configuration.binaries.save_binary is True:
self._binaries.save_binary(self.bot.client.storage_factory)
YLogger.debug(self, "Loading security services")
self.load_security_services()
YLogger.debug(self, "Loading oob processors")
self._oobhandler.load_oob_processors()
def dump_brain_tree(self, client_context):
self._braintree.dump_brain_tree(client_context)
def _load_denormals(self):
self._denormal_collection.empty()
self._denormal_collection.load(self.bot.client.storage_factory)
def _load_normals(self):
self._normal_collection.empty()
self._normal_collection.load(self.bot.client.storage_factory)
def _load_genders(self):
self._gender_collection.empty()
self._gender_collection.load(self.bot.client.storage_factory)
def _load_persons(self):
self._person_collection.empty()
self._person_collection.load(self.bot.client.storage_factory)
def _load_person2s(self):
self._person2_collection.empty()
self._person2_collection.load(self.bot.client.storage_factory)
def _load_botnames(self):
self._botnames_collection.empty()
self._botnames_collection.load(self.bot.client.storage_factory)
def _load_properties(self):
self._properties_collection.empty()
self._properties_collection.load(self.bot.client.storage_factory)
def _load_default_variables(self):
self._default_variables_collection.empty()
self._default_variables_collection.load(
self.bot.client.storage_factory)
self._set_system_defined()
def _set_system_defined(self):
self.set_sentiment_scores(0.0, 0.5)
def set_sentiment_scores(self, positivity, subjectivity):
if self._default_variables_collection.has_variable(
"positivity") is False:
self._default_variables_collection.set_value(
"positivity", str(positivity))
if self._default_variables_collection.has_variable(
"subjectivity") is False:
self._default_variables_collection.set_value(
"subjectivity", str(subjectivity))
def _load_maps(self):
self._maps_collection.empty()
self._maps_collection.load(self.bot.client.storage_factory)
def reload_map(self, mapname):
if self._maps_collection.contains(mapname):
self._maps_collection.reload(self.bot.client.storage_factory,
mapname)
def _load_sets(self):
self._sets_collection.empty()
self._sets_collection.load(self.bot.client.storage_factory)
def reload_set(self, setname):
if self._sets_collection.contains(setname):
self._sets_collection.reload(self.bot.client.storage_factory,
setname)
def _load_rdfs(self):
self._rdf_collection.empty()
self._rdf_collection.load(self.bot.client.storage_factory)
def reload_rdf(self, rdfname):
if self._rdf_collection.contains(rdfname):
self._rdf_collection.reload(self.bot.client.storage_factory,
rdfname)
def _load_regex_templates(self):
self._regex_templates.load(self.bot.client.storage_factory)
def _load_preprocessors(self):
self._preprocessors.empty()
self._preprocessors.load(self.bot.client.storage_factory)
def _load_postprocessors(self):
self._postprocessors.empty()
self._postprocessors.load(self.bot.client.storage_factory)
def _load_pattern_nodes(self):
self._pattern_factory = PatternNodeFactory()
self._pattern_factory.load(self.bot.client.storage_factory)
def _load_template_nodes(self):
self._template_factory = TemplateNodeFactory()
self._template_factory.load(self.bot.client.storage_factory)
def load_collections(self):
self._load_denormals()
self._load_normals()
self._load_genders()
self._load_persons()
self._load_person2s()
self._load_default_variables()
self._load_botnames()
self._load_rdfs()
self._load_sets()
self._load_maps()
self._load_regex_templates()
self._load_preprocessors()
self._load_postprocessors()
def load_services(self, configuration):
ServiceFactory.preload_services(configuration.services)
def load_security_services(self):
self._security.load_security_services(self.bot.client)
def load_dynamics(self):
if self.configuration.dynamics is not None:
self._dynamics_collection.load_from_configuration(
self.configuration.dynamics)
else:
YLogger.debug(self, "No dynamics configuration defined...")
def pre_process_question(self, client_context, question):
return self.preprocessors.process(client_context, question)
def post_process_response(self, client_context, response: str):
return self.postprocessors.process(client_context, response)
def failed_authentication(self, client_context):
return self._security.failed_authentication(client_context)
def authenticate_user(self, client_context):
return self._security.authenticate_user(client_context)
def resolve_matched_template(self, client_context, match_context):
assert (client_context is not None)
assert (match_context is not None)
template_node = match_context.template_node()
YLogger.debug(client_context, "AIML Parser evaluating template [%s]",
template_node.to_string())
response = template_node.template.resolve(client_context)
if self._oobhandler.oob_in_response(response) is True:
if client_context.brain.template_factory.exists('oob') is True:
response = self._oobhandler.handle(client_context, response)
else:
YLogger.debug(client_context, "OOB function is disable [%s]",
response)
return response
def ask_question(self,
client_context,
sentence,
srai=False,
default_srai=False):
assert (client_context is not None)
assert (client_context.bot is not None)
assert (self._aiml_parser is not None)
client_context.brain = self
authenticated = self.authenticate_user(client_context)
if authenticated is not None:
return authenticated
conversation = client_context.bot.get_conversation(client_context)
answer = None
if conversation is not None:
if srai is False and default_srai is False:
self._nlu_utterance = None
try:
client_context.userInfo.userInfoPreProcessor(
client_context, srai)
except Exception:
pass
topic_pattern = conversation.get_topic_pattern(client_context)
that_pattern = conversation.get_that_pattern(client_context, srai)
original_base = None
if default_srai is True and conversation.internal_base is not None:
original_base = conversation.internal_base
base = original_base
if 'srai_histories' not in base:
base['srai_histories'] = []
default_srai_root = base['srai_histories']
default_srai_root.append({})
conversation.internal_base = default_srai_root[-1]
conversation.add_internal_data(conversation.internal_base,
'default_srai', True)
elif srai is False:
conversation.internal_data.append({})
conversation.internal_base = conversation.internal_data[-1]
base = conversation.internal_base
texts = self.tokenizer.words_to_texts(sentence.words)
conversation.add_internal_data(base, 'question', texts)
conversation.add_internal_data(base, 'topic', topic_pattern)
conversation.add_internal_data(base, 'that', that_pattern)
current_variables = ConversationVariables(conversation)
match_context = self._aiml_parser.match_sentence(
client_context,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
if match_context is not None:
if len(match_context.matched_nodes
) == 3 and match_context.matched_nodes[
0].matched_node.is_wildcard() is True:
if self._aiml_parser.pattern_parser.use_nlu is False:
YLogger.debug(
client_context,
"Matched Catgeory (*): file[%s] line[%s-%s]",
match_context._template_node._filename,
match_context._template_node._start_line,
match_context._template_node._end_line)
conversation.add_internal_matched(
base, match_context._template_node)
answer = self.resolve_matched_template(
client_context, match_context)
else:
YLogger.debug(client_context,
"Matched Catgeory : file[%s] line[%s-%s]",
match_context._template_node._filename,
match_context._template_node._start_line,
match_context._template_node._end_line)
try:
conversation.add_internal_matched(
base, match_context._template_node)
answer = self.resolve_matched_template(
client_context, match_context)
except Exception:
self.set_match_context_info(conversation,
match_context)
before, after = current_variables.different_variables(
conversation)
conversation.add_internal_data(base,
'before_variables',
before)
conversation.add_internal_data(base, 'after_variables',
after)
raise
if answer is None and self._aiml_parser.pattern_parser.use_nlu is True:
assert (self._nlu is not None)
try:
utterance = client_context.brain.tokenizer.words_to_texts(
sentence.words)
if default_srai is False or self.bot.configuration.default_response_srai != utterance:
nluResult = conversation.current_question().property(
"__SYSTEM_NLUDATA__")
if nluResult is None or nluResult == "" or self._nlu_utterance != utterance:
self._nlu_utterance = utterance
match_context = self.multi_nlu_match(
client_context, conversation, topic_pattern,
that_pattern)
else:
client_context.match_nlu = True
sentence = Sentence(client_context.brain.tokenizer,
self.NLU_UTTERANCE)
match_context = self._aiml_parser.match_sentence(
client_context,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
client_context.match_nlu = False
if match_context is not None:
YLogger.debug(
client_context,
"Matched Catgeory (NLU): file[%s] line[%s-%s]",
match_context._template_node._filename,
match_context._template_node._start_line,
match_context._template_node._end_line)
conversation.add_internal_matched(
base, match_context._template_node)
answer = self.resolve_matched_template(
client_context, match_context)
except NotImplementedError:
if match_context is not None:
YLogger.debug(
client_context,
"Matched Catgeory (*): file[%s] line[%s-%s]",
match_context._template_node._filename,
match_context._template_node._start_line,
match_context._template_node._end_line)
conversation.add_internal_matched(
base, match_context._template_node)
answer = self.resolve_matched_template(
client_context, match_context)
except Exception:
self.set_match_context_info(conversation, match_context)
before, after = current_variables.different_variables(
conversation)
conversation.add_internal_data(base, 'before_variables',
before)
conversation.add_internal_data(base, 'after_variables',
after)
raise
self.set_match_context_info(conversation, match_context)
before, after = current_variables.different_variables(conversation)
conversation.add_internal_data(base, 'before_variables', before)
conversation.add_internal_data(base, 'after_variables', after)
conversation.add_internal_data(base, 'processing_result', answer)
if original_base is not None:
conversation.internal_base = original_base
base = conversation.internal_base
conversation.add_internal_data(base, 'response', answer)
try:
client_context.userInfo.userInfoPostProcessor(client_context)
except Exception:
pass
return answer
def set_match_context_info(self, conversation, match_context):
if match_context is not None:
json_matchedNode = {
'file_name': match_context._template_node._filename,
'start_line': match_context._template_node._start_line,
'end_line': match_context._template_node._end_line
}
question = conversation.current_question()
if question is not None:
question.sentences[
question.
_current_sentence_no].matched_node = json_matchedNode
def multi_nlu_match(self, client_context, conversation, topic_pattern,
that_pattern):
nlu_list = self._nlu_collection.servers
match_context = None
for server_name in nlu_list:
try:
server = self._nlu_collection.server_info(server_name)
nluResult = self._nlu.nluCall(client_context, server.url,
server.apikey,
self._nlu_utterance)
except NotImplementedError:
raise
conversation.current_question().set_property(
"__SYSTEM_NLUDATA__", nluResult)
if nluResult is not None:
client_context.match_nlu = True
sentence = Sentence(client_context.brain.tokenizer,
self.NLU_UTTERANCE)
match_context = self._aiml_parser.match_sentence(
client_context,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
client_context.match_nlu = False
if match_context is not None:
if len(match_context.matched_nodes) != 3 or \
match_context.matched_nodes[0].matched_node.is_wildcard() is False:
break
if match_context is None:
conversation.current_question().set_property(
"__SYSTEM_NLUDATA__", None)
try:
client_context.userInfo.userInfoPostProcessor(client_context)
except Exception:
pass
return match_context
class Brain(object):
def __init__(self, bot, configuration: BrainConfiguration):
assert (bot is not None)
assert (configuration is not None)
self._questions = 0
self._bot = bot
self._configuration = configuration
self._binaries = BinariesManager(configuration.binaries)
self._braintree = BraintreeManager(configuration.braintree)
self._tokenizer = Tokenizer.load_tokenizer(configuration)
self._denormal_collection = DenormalCollection()
self._normal_collection = NormalCollection()
self._gender_collection = GenderCollection()
self._person_collection = PersonCollection()
self._person2_collection = Person2Collection()
self._rdf_collection = RDFCollection()
self._sets_collection = SetCollection()
self._maps_collection = MapCollection()
self._properties_collection = PropertiesCollection()
self._default_variables_collection = DefaultVariablesCollection()
self._preprocessors = PreProcessorCollection()
self._postprocessors = PostProcessorCollection()
self._postquestionprocessors = PostQuestionProcessorCollection()
self._pattern_factory = None
self._template_factory = None
self._security = SecurityManager(configuration.security)
self._oobhandler = OOBHandler(configuration.oob)
self._openchatbots = OpenChatBotCollection()
self._regex_templates = RegexTemplatesCollection()
self._dynamics_collection = DynamicsCollection()
self._aiml_parser = self.load_aiml_parser()
self.load(self.configuration)
def ylogger_type(self):
return "brain"
@property
def num_questions(self):
return self._questions
@property
def id(self):
return self._configuration.section_name
@property
def bot(self):
return self._bot
@property
def configuration(self):
return self._configuration
@property
def aiml_parser(self):
return self._aiml_parser
@property
def denormals(self):
return self._denormal_collection
@property
def normals(self):
return self._normal_collection
@property
def genders(self):
return self._gender_collection
@property
def persons(self):
return self._person_collection
@property
def person2s(self):
return self._person2_collection
@property
def rdf(self):
return self._rdf_collection
@property
def sets(self):
return self._sets_collection
@property
def maps(self):
return self._maps_collection
@property
def properties(self):
return self._properties_collection
@property
def default_variables(self):
return self._default_variables_collection
@property
def preprocessors(self):
return self._preprocessors
@property
def postprocessors(self):
return self._postprocessors
@property
def postquestionprocessors(self):
return self._postquestionprocessors
@property
def pattern_factory(self):
return self._pattern_factory
@property
def template_factory(self):
return self._template_factory
@property
def regex_templates(self):
return self._regex_templates
@property
def dynamics(self):
return self._dynamics_collection
@property
def tokenizer(self):
return self._tokenizer
@property
def openchatbots(self):
return self._openchatbots
@property
def security(self):
return self._security
def load_aiml_parser(self):
self._load_pattern_nodes()
self._load_template_nodes()
return AIMLParser(self)
def load_aiml(self):
YLogger.info(self, "Loading aiml source brain")
self._aiml_parser.load_aiml()
def reload_aimls(self):
YLogger.info(self, "Loading aiml source brain")
self._aiml_parser.empty()
self._aiml_parser.load_aiml()
def load(self, configuration: BrainConfiguration):
load_aiml = True
if self.configuration.binaries.load_binary is True:
load_aiml = self._binaries.load_binary(
self.bot.client.storage_factory)
if load_aiml is True:
self.load_aiml()
if configuration.binaries.save_binary is True:
self._binaries.save_binary(self.bot.client.storage_factory)
YLogger.info(self, "Loading collections")
self.load_collections()
YLogger.info(self, "Loading services")
self.load_services(configuration)
YLogger.info(self, "Loading openchat bots")
self.load_openchatbots(configuration)
YLogger.info(self, "Loading security services")
self.load_security_services()
YLogger.info(self, "Loading oob processors")
self._oobhandler.load_oob_processors()
YLogger.info(self, "Loading regex templates")
self.load_regex_templates()
YLogger.info(self, "Loading dynamics sets, maps and vars")
self.load_dynamics()
def dump_brain_tree(self, client_context):
self._braintree.dump_brain_tree(client_context)
def _load_denormals(self):
self._denormal_collection.empty()
self._denormal_collection.load(self.bot.client.storage_factory)
def _load_normals(self):
self._normal_collection.empty()
self._normal_collection.load(self.bot.client.storage_factory)
def _load_genders(self):
self._gender_collection.empty()
self._gender_collection.load(self.bot.client.storage_factory)
def _load_persons(self):
self._person_collection.empty()
self._person_collection.load(self.bot.client.storage_factory)
def _load_person2s(self):
self._person2_collection.empty()
self._person2_collection.load(self.bot.client.storage_factory)
def _load_properties(self):
self._properties_collection.empty()
self._properties_collection.load(self.bot.client.storage_factory)
def _load_default_variables(self):
self._default_variables_collection.empty()
self._default_variables_collection.load(
self.bot.client.storage_factory)
self._set_system_defined()
def _set_system_defined(self):
self.set_sentiment_scores(0.0, 0.5)
def set_sentiment_scores(self, positivity, subjectivity):
if self._default_variables_collection.has_variable(
"positivity") is False:
self._default_variables_collection.set_value(
"positivity", str(positivity))
if self._default_variables_collection.has_variable(
"subjectivity") is False:
self._default_variables_collection.set_value(
"subjectivity", str(subjectivity))
def _load_maps(self):
self._maps_collection.empty()
self._maps_collection.load(self.bot.client.storage_factory)
def reload_map(self, mapname):
if self._maps_collection.contains(mapname):
self._maps_collection.reload(self.bot.client.storage_factory,
mapname)
else:
YLogger.error(self, "Unknown map name [%s], unable to reload ",
mapname)
def _load_sets(self):
self._sets_collection.empty()
self._sets_collection.load(self.bot.client.storage_factory)
def reload_set(self, setname):
if self._sets_collection.contains(setname):
self._sets_collection.reload(self.bot.client.storage_factory,
setname)
else:
YLogger.error(self, "Unknown set name [%s], unable to reload ",
setname)
def _load_rdfs(self):
self._rdf_collection.empty()
self._rdf_collection.load(self.bot.client.storage_factory)
def reload_rdf(self, rdfname):
if self._rdf_collection.contains(rdfname):
self._rdf_collection.reload(self.bot.client.storage_factory,
rdfname)
else:
YLogger.error(self, "Unknown rdf name [%s], unable to reload ",
rdfname)
def _load_preprocessors(self):
self._preprocessors.empty()
self._preprocessors.load(self.bot.client.storage_factory)
def _load_postprocessors(self):
self._postprocessors.empty()
self._postprocessors.load(self.bot.client.storage_factory)
def _load_postquestionprocessors(self):
self._postquestionprocessors.empty()
self._postquestionprocessors.load(self.bot.client.storage_factory)
def _load_pattern_nodes(self):
self._pattern_factory = PatternNodeFactory()
self._pattern_factory.load(self.bot.client.storage_factory)
def _load_template_nodes(self):
self._template_factory = TemplateNodeFactory()
self._template_factory.load(self.bot.client.storage_factory)
def load_collections(self):
self._load_denormals()
self._load_normals()
self._load_genders()
self._load_persons()
self._load_person2s()
self._load_properties()
self._load_default_variables()
self._load_rdfs()
self._load_sets()
self._load_maps()
self._load_preprocessors()
self._load_postprocessors()
self._load_postquestionprocessors()
def load_services(self, configuration):
ServiceFactory.preload_services(configuration.services)
def load_openchatbots(self, configuration):
self._openchatbots.load_from_configuration(configuration.openchatbots)
def load_security_services(self):
self._security.load_security_services(self.bot.client)
def load_dynamics(self):
if self.configuration.dynamics is not None:
self._dynamics_collection.load_from_configuration(
self.configuration.dynamics)
else:
YLogger.debug(self, "No dynamics configuration defined...")
def load_regex_templates(self):
self._regex_templates.load(self.bot.client.storage_factory)
def pre_process_question(self, client_context, question):
return self.preprocessors.process(client_context, question)
def post_process_response(self, client_context, response: str):
return self.postprocessors.process(client_context, response)
def post_process_question(self, client_context, question: str):
return self.postquestionprocessors.process(client_context, question)
def failed_authentication(self, client_context):
return self._security.failed_authentication(client_context)
def authenticate_user(self, client_context):
return self._security.authenticate_user(client_context)
def resolve_matched_template(self, client_context, match_context):
assert (client_context is not None)
assert (match_context is not None)
template_node = match_context.template_node()
YLogger.debug(client_context, "AIML Parser evaluating template [%s]",
template_node.to_string())
response = template_node.template.resolve(client_context)
if self._oobhandler.oob_in_response(response) is True:
response = self._oobhandler.handle(client_context, response)
return response
def ask_question(self, client_context, sentence, srai=False):
assert (client_context is not None)
assert (client_context.bot is not None)
assert (self._aiml_parser is not None)
client_context.brain = self
authenticated = self.authenticate_user(client_context)
if authenticated is not None:
return authenticated
conversation = client_context.bot.get_conversation(client_context)
if conversation is not None:
self._questions += 1
topic_pattern = conversation.get_topic_pattern(client_context)
that_pattern = conversation.get_that_pattern(client_context, srai)
match_context = self._aiml_parser.match_sentence(
client_context,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
if match_context is not None:
return self.resolve_matched_template(client_context,
match_context)
return None