def __init__(self, configuration: BrainConfiguration):
self._configuration = configuration
self._aiml_parser = AIMLParser(self)
self._denormal_collection = DenormalCollection()
self._normal_collection = NormalCollection()
self._gender_collection = GenderCollection()
self._person_collection = PersonCollection()
self._person2_collection = PersonCollection()
self._predicates_collection = PredicatesCollection()
self._pronouns_collection = PronounsCollection()
self._triples_collection = TriplesCollection()
self._sets_collection = SetCollection()
self._maps_collection = MapCollection()
self._properties_collection = PropertiesCollection()
self._preprocessors = ProcessorLoader()
self._postprocessors = ProcessorLoader()
self._authentication = None
self._authorisation = None
self._default_oob = None
self._oob = {}
self.load(self._configuration)
def test_collection(self):
collection = PronounsCollection()
self.assertIsNotNone(collection)
count = collection.load_from_text("""
he
she
it
they
we
""")
self.assertEqual(count, 5)
self.assertTrue(collection.is_pronoun("he"))
def test_collection(self):
collection = PronounsCollection()
self.assertIsNotNone(collection)
count = collection.load_from_text("""
he
she
it
they
we
""")
self.assertEqual(count, 5)
self.assertTrue(collection.is_pronoun("he"))
def __init__(self, configuration: BrainConfiguration):
self._configuration = configuration
self._aiml_parser = AIMLParser()
self._denormal_collection = DenormalCollection()
self._normal_collection = NormalCollection()
self._gender_collection = GenderCollection()
self._person_collection = PersonCollection()
self._person2_collection = PersonCollection()
self._predicates_collection = PredicatesCollection()
self._pronouns_collection = PronounsCollection()
self._triples_collection = TriplesCollection()
self._sets_collection = SetCollection()
self._maps_collection = MapCollection()
self._properties_collection = PropertiesCollection()
self._preprocessors = ProcessorLoader()
self._postprocessors = ProcessorLoader()
self.load(self._configuration)
class Brain(object):
def __init__(self, configuration: BrainConfiguration):
self._configuration = configuration
self._aiml_parser = AIMLParser()
self._denormal_collection = DenormalCollection()
self._normal_collection = NormalCollection()
self._gender_collection = GenderCollection()
self._person_collection = PersonCollection()
self._person2_collection = PersonCollection()
self._predicates_collection = PredicatesCollection()
self._pronouns_collection = PronounsCollection()
self._triples_collection = TriplesCollection()
self._sets_collection = SetCollection()
self._maps_collection = MapCollection()
self._properties_collection = PropertiesCollection()
self._preprocessors = ProcessorLoader()
self._postprocessors = ProcessorLoader()
self.load(self._configuration)
@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 predicates(self):
return self._predicates_collection
@property
def pronounds(self):
return self._pronouns_collection
@property
def triples(self):
return self._triples_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 preprocessors(self):
return self._preprocessors
@property
def postprocessors(self):
return self._postprocessors
def load(self, brain_configuration: BrainConfiguration):
self._aiml_parser.load_aiml(brain_configuration)
self.load_collections(brain_configuration)
self.load_services(brain_configuration)
def _load_denormals(self, brain_configuration):
if brain_configuration.denormal is not None:
total = self._denormal_collection.load_from_filename(
brain_configuration.denormal)
logging.info("Loaded a total of %d denormalisations", total)
else:
logging.warning("No configuration setting for denormal")
def _load_normals(self, brain_configuration):
if brain_configuration.normal is not None:
total = self._normal_collection.load_from_filename(
brain_configuration.normal)
logging.info("Loaded a total of %d normalisations", total)
else:
logging.warning("No configuration setting for normal")
def _load_genders(self, brain_configuration):
if brain_configuration.gender is not None:
total = self._gender_collection.load_from_filename(
brain_configuration.gender)
logging.info("Loaded a total of %d genderisations", total)
else:
logging.warning("No configuration setting for gender")
def _load_persons(self, brain_configuration):
if brain_configuration.person is not None:
total = self._person_collection.load_from_filename(
brain_configuration.person)
logging.info("Loaded a total of %d persons", total)
else:
logging.warning("No configuration setting for person")
def _load_person2s(self, brain_configuration):
if brain_configuration.person2 is not None:
total = self._person2_collection.load_from_filename(
brain_configuration.person2)
logging.info("Loaded a total of %d person2s", total)
else:
logging.warning("No configuration setting for person2")
def _load_predicates(self, brain_configuration):
if brain_configuration.predicates is not None:
total = self._predicates_collection.load_from_filename(
brain_configuration.predicates)
logging.info("Loaded a total of %d predicates", total)
else:
logging.warning("No configuration setting for predicates")
def _load_pronouns(self, brain_configuration):
if brain_configuration.pronouns is not None:
total = self._pronouns_collection.load_from_filename(
brain_configuration.pronouns)
logging.info("Loaded a total of %d pronouns", total)
else:
logging.warning("No configuration setting for pronouns")
def _load_properties(self, brain_configuration):
if brain_configuration.properties is not None:
total = self._properties_collection.load_from_filename(
brain_configuration.properties)
logging.info("Loaded a total of %d properties", total)
else:
logging.warning("No configuration setting for properties")
def _load_triples(self, brain_configuration):
if brain_configuration.triples is not None:
total = self._properties_collection.load_from_filename(
brain_configuration.triples)
logging.info("Loaded a total of %d triples", total)
else:
logging.warning("No configuration setting for triples")
def _load_sets(self, brain_configuration):
if brain_configuration.set_files is not None:
total = self._sets_collection.load(brain_configuration.set_files)
logging.info("Loaded a total of %d sets files", total)
else:
logging.warning("No configuration setting for set files")
def _load_maps(self, brain_configuration):
if brain_configuration.map_files is not None:
total = self._maps_collection.load(brain_configuration.map_files)
logging.info("Loaded a total of %d maps files", total)
else:
logging.warning("No configuration setting for map files")
def _load_preprocessors(self, brain_configuration):
if brain_configuration.preprocessors is not None:
total = self._preprocessors.load(brain_configuration.preprocessors)
logging.info("Loaded a total of %d pre processors", total)
else:
logging.warning("No configuration setting for pre processors")
def _load_postprocessors(self, brain_configuration):
if brain_configuration.postprocessors is not None:
total = self._postprocessors.load(
brain_configuration.postprocessors)
logging.info("Loaded a total of %d post processors", total)
else:
logging.warning("No configuration setting for post processors")
def load_collections(self, brain_configuration):
self._load_denormals(brain_configuration)
self._load_normals(brain_configuration)
self._load_genders(brain_configuration)
self._load_persons(brain_configuration)
self._load_person2s(brain_configuration)
self._load_predicates(brain_configuration)
self._load_pronouns(brain_configuration)
self._load_properties(brain_configuration)
self._load_triples(brain_configuration)
self._load_sets(brain_configuration)
self._load_maps(brain_configuration)
self._load_preprocessors(brain_configuration)
self._load_postprocessors(brain_configuration)
def load_services(self, brain_configuration):
ServiceFactory.preload_services(brain_configuration.services)
def pre_process_question(self, bot, clientid, question):
return self.preprocessors.process(bot, clientid, question)
def ask_question(self, bot, clientid, sentence) -> str:
conversation = bot.get_conversation(clientid)
topic_pattern = conversation.predicate("topic")
if topic_pattern is None:
logging.info("No Topic pattern default to [*]")
topic_pattern = "*"
else:
logging.info("Topic pattern = [%s]", topic_pattern)
try:
that_question = conversation.nth_question(2)
that_sentence = that_question.current_sentence()
# If the last response was valid, i.e not none and not empty string, then use
# that as the that_pattern, otherwise we default to '*' as pattern
if that_sentence.response is not None and that_sentence.response != '':
that_pattern = that_sentence.response
logging.info("That pattern = [%s]", that_pattern)
else:
logging.info("That pattern, no response, default to [*]")
that_pattern = "*"
except Exception:
logging.info("No That pattern default to [*]")
that_pattern = "*"
match_context = self._aiml_parser.match_sentence(
bot,
clientid,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
if match_context is not None:
template_node = match_context.template_node()
logging.debug("AIML Parser evaluating template [%s]",
template_node.to_string())
return template_node.template.resolve(bot, clientid)
return None
def post_process_response(self, bot, clientid, response: str):
return self.postprocessors.process(bot, clientid, response)
def dump_tree(self):
self._aiml_parser.pattern_parser.root.dump(tabs="")
def write_learnf_to_file(self, bot, clientid, pattern, topic, that,
template):
learnf_path = "%s/learnf%s" % (
self._configuration.aiml_files.files,
self._configuration.aiml_files.extension)
logging.debug("Writing learnf to %s", learnf_path)
if os.path.isfile(learnf_path) is False:
file = open(learnf_path, "w+")
file.write('<?xml version="1.0" encoding="UTF-8"?>\n')
file.write('<aiml>\n')
file.write('</aiml>\n')
file.close()
tree = ET.parse(learnf_path)
root = tree.getroot()
# Add our new element
child = ET.Element("category")
child.append(pattern)
child.append(topic)
child.append(that)
child.append(template.xml_tree(bot, clientid))
root.append(child)
tree.write(learnf_path, method="xml")
class Brain(object):
def __init__(self, configuration: BrainConfiguration):
self._configuration = configuration
self._aiml_parser = AIMLParser()
self._denormal_collection = DenormalCollection()
self._normal_collection = NormalCollection()
self._gender_collection = GenderCollection()
self._person_collection = PersonCollection()
self._person2_collection = PersonCollection()
self._predicates_collection = PredicatesCollection()
self._pronouns_collection = PronounsCollection()
self._triples_collection = TriplesCollection()
self._sets_collection = SetCollection()
self._maps_collection = MapCollection()
self._properties_collection = PropertiesCollection()
self._preprocessors = ProcessorLoader()
self._postprocessors = ProcessorLoader()
self.load(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 predicates(self):
return self._predicates_collection
@property
def pronounds(self):
return self._pronouns_collection
@property
def triples(self):
return self._triples_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 preprocessors(self):
return self._preprocessors
@property
def postprocessors(self):
return self._postprocessors
def load(self, brain_configuration: BrainConfiguration):
self._aiml_parser.load_aiml(brain_configuration)
self.load_collections(brain_configuration)
def load_collections(self, brain_configuration):
if brain_configuration.denormal is not None:
total = self._denormal_collection.load_from_filename(
brain_configuration.denormal)
logging.info("Loaded a total of %d denormalisations" % (total))
else:
logging.warning("No configuration setting for denormal")
if brain_configuration.normal is not None:
total = self._normal_collection.load_from_filename(
brain_configuration.normal)
logging.info("Loaded a total of %d normalisations" % (total))
else:
logging.warning("No configuration setting for normal")
if brain_configuration.gender is not None:
total = self._gender_collection.load_from_filename(
brain_configuration.gender)
logging.info("Loaded a total of %d genderisations" % (total))
else:
logging.warning("No configuration setting for gender")
if brain_configuration.person is not None:
total = self._person_collection.load_from_filename(
brain_configuration.person)
logging.info("Loaded a total of %d persons" % (total))
else:
logging.warning("No configuration setting for person")
if brain_configuration.person2 is not None:
total = self._person2_collection.load_from_filename(
brain_configuration.person2)
logging.info("Loaded a total of %d person2s" % (total))
else:
logging.warning("No configuration setting for person2")
if brain_configuration.predicates is not None:
total = self._predicates_collection.load_from_filename(
brain_configuration.predicates)
logging.info("Loaded a total of %d predicates" % (total))
else:
logging.warning("No configuration setting for predicates")
if brain_configuration.pronouns is not None:
total = self._pronouns_collection.load_from_filename(
brain_configuration.pronouns)
logging.info("Loaded a total of %d pronouns" % (total))
else:
logging.warning("No configuration setting for pronouns")
if brain_configuration.properties is not None:
total = self._properties_collection.load_from_filename(
brain_configuration.properties)
logging.info("Loaded a total of %d properties" % (total))
else:
logging.warning("No configuration setting for properties")
if brain_configuration.triples is not None:
total = self._properties_collection.load_from_filename(
brain_configuration.triples)
logging.info("Loaded a total of %d triples" % (total))
else:
logging.warning("No configuration setting for triples")
if brain_configuration.set_files is not None:
total = self._sets_collection.load(brain_configuration.set_files)
logging.info("Loaded a total of %d sets files" % (total))
else:
logging.warning("No configuration setting for set files")
if brain_configuration.map_files is not None:
total = self._maps_collection.load(brain_configuration.map_files)
logging.info("Loaded a total of %d maps files" % (total))
else:
logging.warning("No configuration setting for map files")
if brain_configuration.preprocessors is not None:
total = self._preprocessors.load(brain_configuration.preprocessors)
logging.info("Loaded a total of %d pre processors" % (total))
else:
logging.warning("No configuration setting for pre processors")
if brain_configuration.postprocessors is not None:
total = self._postprocessors.load(
brain_configuration.postprocessors)
logging.info("Loaded a total of %d post processors" % (total))
else:
logging.warning("No configuration setting for post processors")
def pre_process_question(self, question):
return self.preprocessors.process(question)
def ask_question(self, bot, clientid, sentence) -> str:
conversation = bot.get_conversation(clientid)
try:
topic_pattern = conversation.predicate("topic")
except:
topic_pattern = "*"
try:
that_question = conversation.nth_question(2)
that_sentence = that_question.current_sentence()
that_pattern = that_sentence.text()
except:
that_pattern = "*"
return self._aiml_parser.match_sentence(bot,
clientid,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
def post_process_response(self, response: str):
return self.postprocessors.process(response)
def dump_tree(self):
self._aiml_parser.pattern_parser.root.dump(tabs="")
def write_learnf_to_file(self, bot, clientid, pattern, topic, that,
template):
learnf_path = "%s/learnf%s" % (
self._configuration.aiml_files.files,
self._configuration.aiml_files.extension)
logging.debug("Writing learnf to %s" % learnf_path)
import os.path
if os.path.isfile(learnf_path) is False:
file = open(learnf_path, "w+")
file.write('<?xml version="1.0" encoding="UTF-8"?>\n')
file.write('<aiml>\n')
file.write('</aiml>\n')
file.close()
tree = ET.parse(learnf_path)
root = tree.getroot()
# Add our new element
child = ET.Element("category")
child.append(pattern)
child.append(topic)
child.append(that)
child.append(template.xml_tree(bot, clientid))
root.append(child)
tree.write(learnf_path, method="xml")
class Brain(object):
def __init__(self, configuration: BrainConfiguration):
self._configuration = configuration
self._aiml_parser = AIMLParser()
self._denormal_collection = DenormalCollection()
self._normal_collection = NormalCollection()
self._gender_collection = GenderCollection()
self._person_collection = PersonCollection()
self._person2_collection = PersonCollection()
self._predicates_collection = PredicatesCollection()
self._pronouns_collection = PronounsCollection()
self._triples_collection = TriplesCollection()
self._sets_collection = SetCollection()
self._maps_collection = MapCollection()
self._properties_collection = PropertiesCollection()
self._preprocessors = ProcessorLoader()
self._postprocessors = ProcessorLoader()
self.load(self._configuration)
@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 predicates(self):
return self._predicates_collection
@property
def pronounds(self):
return self._pronouns_collection
@property
def triples(self):
return self._triples_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 preprocessors(self):
return self._preprocessors
@property
def postprocessors(self):
return self._postprocessors
def load(self, brain_configuration: BrainConfiguration):
self._aiml_parser.load_aiml(brain_configuration)
self.load_collections(brain_configuration)
self.load_services(brain_configuration)
def _load_denormals(self, brain_configuration):
if brain_configuration.denormal is not None:
total = self._denormal_collection.load_from_filename(brain_configuration.denormal)
logging.info("Loaded a total of %d denormalisations", total)
else:
logging.warning("No configuration setting for denormal")
def _load_normals(self, brain_configuration):
if brain_configuration.normal is not None:
total = self._normal_collection.load_from_filename(brain_configuration.normal)
logging.info("Loaded a total of %d normalisations", total)
else:
logging.warning("No configuration setting for normal")
def _load_genders(self, brain_configuration):
if brain_configuration.gender is not None:
total = self._gender_collection.load_from_filename(brain_configuration.gender)
logging.info("Loaded a total of %d genderisations", total)
else:
logging.warning("No configuration setting for gender")
def _load_persons(self, brain_configuration):
if brain_configuration.person is not None:
total = self._person_collection.load_from_filename(brain_configuration.person)
logging.info("Loaded a total of %d persons", total)
else:
logging.warning("No configuration setting for person")
def _load_person2s(self, brain_configuration):
if brain_configuration.person2 is not None:
total = self._person2_collection.load_from_filename(brain_configuration.person2)
logging.info("Loaded a total of %d person2s", total)
else:
logging.warning("No configuration setting for person2")
def _load_predicates(self, brain_configuration):
if brain_configuration.predicates is not None:
total = self._predicates_collection.load_from_filename(brain_configuration.predicates)
logging.info("Loaded a total of %d predicates", total)
else:
logging.warning("No configuration setting for predicates")
def _load_pronouns(self, brain_configuration):
if brain_configuration.pronouns is not None:
total = self._pronouns_collection.load_from_filename(brain_configuration.pronouns)
logging.info("Loaded a total of %d pronouns", total)
else:
logging.warning("No configuration setting for pronouns")
def _load_properties(self, brain_configuration):
if brain_configuration.properties is not None:
total = self._properties_collection.load_from_filename(brain_configuration.properties)
logging.info("Loaded a total of %d properties", total)
else:
logging.warning("No configuration setting for properties")
def _load_triples(self, brain_configuration):
if brain_configuration.triples is not None:
total = self._properties_collection.load_from_filename(brain_configuration.triples)
logging.info("Loaded a total of %d triples", total)
else:
logging.warning("No configuration setting for triples")
def _load_sets(self, brain_configuration):
if brain_configuration.set_files is not None:
total = self._sets_collection.load(brain_configuration.set_files)
logging.info("Loaded a total of %d sets files", total)
else:
logging.warning("No configuration setting for set files")
def _load_maps(self, brain_configuration):
if brain_configuration.map_files is not None:
total = self._maps_collection.load(brain_configuration.map_files)
logging.info("Loaded a total of %d maps files", total)
else:
logging.warning("No configuration setting for map files")
def _load_preprocessors(self, brain_configuration):
if brain_configuration.preprocessors is not None:
total = self._preprocessors.load(brain_configuration.preprocessors)
logging.info("Loaded a total of %d pre processors", total)
else:
logging.warning("No configuration setting for pre processors")
def _load_postprocessors(self, brain_configuration):
if brain_configuration.postprocessors is not None:
total = self._postprocessors.load(brain_configuration.postprocessors)
logging.info("Loaded a total of %d post processors", total)
else:
logging.warning("No configuration setting for post processors")
def load_collections(self, brain_configuration):
self._load_denormals(brain_configuration)
self._load_normals(brain_configuration)
self._load_genders(brain_configuration)
self._load_persons(brain_configuration)
self._load_person2s(brain_configuration)
self._load_predicates(brain_configuration)
self._load_pronouns(brain_configuration)
self._load_properties(brain_configuration)
self._load_triples(brain_configuration)
self._load_sets(brain_configuration)
self._load_maps(brain_configuration)
self._load_preprocessors(brain_configuration)
self._load_postprocessors(brain_configuration)
def load_services(self, brain_configuration):
ServiceFactory.preload_services(brain_configuration.services)
def pre_process_question(self, bot, clientid, question):
return self.preprocessors.process(bot, clientid, question)
def ask_question(self, bot, clientid, sentence) -> str:
conversation = bot.get_conversation(clientid)
topic_pattern = conversation.predicate("topic")
if topic_pattern is None:
logging.info("No Topic pattern default to [*]")
topic_pattern = "*"
else:
logging.info("Topic pattern = [%s]", topic_pattern)
try:
that_question = conversation.nth_question(2)
that_sentence = that_question.current_sentence()
# If the last response was valid, i.e not none and not empty string, then use
# that as the that_pattern, otherwise we default to '*' as pattern
if that_sentence.response is not None and that_sentence.response != '':
that_pattern = TextUtils.strip_all_punctuation(that_sentence.response)
logging.info("That pattern = [%s]", that_pattern)
else:
logging.info("That pattern, no response, default to [*]")
that_pattern = "*"
except Exception:
logging.info("No That pattern default to [*]")
that_pattern = "*"
match_context = self._aiml_parser.match_sentence(bot, clientid,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
if match_context is not None:
template_node = match_context.template_node()
logging.debug("AIML Parser evaluating template [%s]", template_node.to_string())
return template_node.template.resolve(bot, clientid)
return None
def post_process_response(self, bot, clientid, response: str):
return self.postprocessors.process(bot, clientid, response)
def dump_tree(self):
self._aiml_parser.pattern_parser.root.dump(tabs="")
def write_learnf_to_file(self, bot, clientid, pattern, topic, that, template):
learnf_path = "%s/learnf%s" % (self._configuration.aiml_files.files, self._configuration.aiml_files.extension)
logging.debug("Writing learnf to %s", learnf_path)
if os.path.isfile(learnf_path) is False:
file = open(learnf_path, "w+")
file.write('<?xml version="1.0" encoding="UTF-8"?>\n')
file.write('<aiml>\n')
file.write('</aiml>\n')
file.close()
tree = ET.parse(learnf_path)
root = tree.getroot()
# Add our new element
child = ET.Element("category")
child.append(pattern)
child.append(topic)
child.append(that)
child.append(template.xml_tree(bot, clientid))
root.append(child)
tree.write(learnf_path, method="xml")
class Brain(object):
def __init__(self, configuration: BrainConfiguration):
self._configuration = configuration
self._aiml_parser = AIMLParser(self)
self._denormal_collection = DenormalCollection()
self._normal_collection = NormalCollection()
self._gender_collection = GenderCollection()
self._person_collection = PersonCollection()
self._person2_collection = PersonCollection()
self._predicates_collection = PredicatesCollection()
self._pronouns_collection = PronounsCollection()
self._triples_collection = TriplesCollection()
self._sets_collection = SetCollection()
self._maps_collection = MapCollection()
self._properties_collection = PropertiesCollection()
self._preprocessors = ProcessorLoader()
self._postprocessors = ProcessorLoader()
self._authentication = None
self._authorisation = None
self._default_oob = None
self._oob = {}
self.load(self._configuration)
@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 predicates(self):
return self._predicates_collection
@property
def pronouns(self):
return self._pronouns_collection
@property
def triples(self):
return self._triples_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 preprocessors(self):
return self._preprocessors
@property
def postprocessors(self):
return self._postprocessors
@property
def authentication(self):
return self._authentication
@property
def authorisation(self):
return self._authorisation
@property
def default_oob(self):
return self._default_oob
@property
def oobs(self):
return self._oob
def load_binary(self, brain_configuration):
logging.info("Loading binary brain from [%s]" %
brain_configuration.binaries.binary_filename)
try:
start = datetime.datetime.now()
gc.disable()
f = open(brain_configuration.binaries.binary_filename, "rb")
self._aiml_parser = pickle.load(f)
gc.enable()
f.close()
stop = datetime.datetime.now()
diff = stop - start
logging.info("Brain load took a total of %.2f sec" %
diff.total_seconds())
load_aiml = False
except Exception as e:
logging.exception(e)
if brain_configuration.binaries.load_aiml_on_binary_fail is True:
load_aiml = True
else:
raise e
def load_aiml(self, brain_configuration):
logging.info("Loading aiml source brain")
self._aiml_parser.load_aiml(brain_configuration)
def save_binary(self, brain_configuration):
logging.info("Saving binary brain to [%s]" %
brain_configuration.binaries.binary_filename)
start = datetime.datetime.now()
f = open(brain_configuration.binaries.binary_filename, "wb")
pickle.dump(self._aiml_parser, f)
f.close()
stop = datetime.datetime.now()
diff = stop - start
logging.info("Brain save took a total of %.2f sec" %
diff.total_seconds())
def load(self, brain_configuration: BrainConfiguration):
if brain_configuration.binaries.load_binary is True:
self.load_binary(brain_configuration)
self.load_aiml(brain_configuration)
if brain_configuration.binaries.save_binary is True:
self.save_binary(brain_configuration)
logging.info("Loading collections")
self.load_collections(brain_configuration)
logging.info("Loading services")
self.load_services(brain_configuration)
logging.info("Loading security services")
self.load_security_services(brain_configuration)
logging.info("Loading oob processors")
self.load_oob_processors(brain_configuration)
def _load_denormals(self, brain_configuration):
if brain_configuration.files.denormal is not None:
total = self._denormal_collection.load_from_filename(
brain_configuration.files.denormal)
logging.info("Loaded a total of %d denormalisations", total)
else:
logging.warning("No configuration setting for denormal")
def _load_normals(self, brain_configuration):
if brain_configuration.files.normal is not None:
total = self._normal_collection.load_from_filename(
brain_configuration.files.normal)
logging.info("Loaded a total of %d normalisations", total)
else:
logging.warning("No configuration setting for normal")
def _load_genders(self, brain_configuration):
if brain_configuration.files.gender is not None:
total = self._gender_collection.load_from_filename(
brain_configuration.files.gender)
logging.info("Loaded a total of %d genderisations", total)
else:
logging.warning("No configuration setting for gender")
def _load_persons(self, brain_configuration):
if brain_configuration.files.person is not None:
total = self._person_collection.load_from_filename(
brain_configuration.files.person)
logging.info("Loaded a total of %d persons", total)
else:
logging.warning("No configuration setting for person")
def _load_person2s(self, brain_configuration):
if brain_configuration.files.person2 is not None:
total = self._person2_collection.load_from_filename(
brain_configuration.files.person2)
logging.info("Loaded a total of %d person2s", total)
else:
logging.warning("No configuration setting for person2")
def _load_predicates(self, brain_configuration):
if brain_configuration.files.predicates is not None:
total = self._predicates_collection.load_from_filename(
brain_configuration.files.predicates)
logging.info("Loaded a total of %d predicates", total)
else:
logging.warning("No configuration setting for predicates")
def _load_pronouns(self, brain_configuration):
if brain_configuration.files.pronouns is not None:
total = self._pronouns_collection.load_from_filename(
brain_configuration.files.pronouns)
logging.info("Loaded a total of %d pronouns", total)
else:
logging.warning("No configuration setting for pronouns")
def _load_properties(self, brain_configuration):
if brain_configuration.files.properties is not None:
total = self._properties_collection.load_from_filename(
brain_configuration.files.properties)
logging.info("Loaded a total of %d properties", total)
else:
logging.warning("No configuration setting for properties")
def _load_triples(self, brain_configuration):
if brain_configuration.files.triples is not None:
total = self._properties_collection.load_from_filename(
brain_configuration.files.triples)
logging.info("Loaded a total of %d triples", total)
else:
logging.warning("No configuration setting for triples")
def _load_sets(self, brain_configuration):
total = self._sets_collection.load(brain_configuration.files.set_files)
logging.info("Loaded a total of %d sets files", total)
def _load_maps(self, brain_configuration):
total = self._maps_collection.load(brain_configuration.files.map_files)
logging.info("Loaded a total of %d maps files", total)
def _load_preprocessors(self, brain_configuration):
if brain_configuration.files.preprocessors is not None:
total = self._preprocessors.load(
brain_configuration.files.preprocessors)
logging.info("Loaded a total of %d pre processors", total)
else:
logging.warning("No configuration setting for pre processors")
def _load_postprocessors(self, brain_configuration):
if brain_configuration.files.postprocessors is not None:
total = self._postprocessors.load(
brain_configuration.files.postprocessors)
logging.info("Loaded a total of %d post processors", total)
else:
logging.warning("No configuration setting for post processors")
def load_collections(self, brain_configuration):
self._load_denormals(brain_configuration)
self._load_normals(brain_configuration)
self._load_genders(brain_configuration)
self._load_persons(brain_configuration)
self._load_person2s(brain_configuration)
self._load_predicates(brain_configuration)
self._load_pronouns(brain_configuration)
self._load_properties(brain_configuration)
self._load_triples(brain_configuration)
self._load_sets(brain_configuration)
self._load_maps(brain_configuration)
self._load_preprocessors(brain_configuration)
self._load_postprocessors(brain_configuration)
def load_services(self, brain_configuration):
ServiceFactory.preload_services(brain_configuration.services)
def load_security_services(self, brain_configuration):
if brain_configuration.security is not None:
if brain_configuration.security.authentication is not None:
if brain_configuration.security.authentication.classname is not None:
try:
classobject = ClassLoader.instantiate_class(
brain_configuration.security.authentication.
classname)
self._authentication = classobject(
brain_configuration.security.authentication)
except Exception as excep:
logging.exception(excep)
else:
logging.debug("No authentication configuration defined")
if brain_configuration.security.authorisation is not None:
if brain_configuration.security.authorisation.classname is not None:
try:
classobject = ClassLoader.instantiate_class(
brain_configuration.security.authorisation.
classname)
self._authorisation = classobject(
brain_configuration.security.authorisation)
except Exception as excep:
logging.exception(excep)
else:
logging.debug("No authorisation configuration defined")
else:
logging.debug("No security configuration defined, running open...")
def pre_process_question(self, bot, clientid, question):
return self.preprocessors.process(bot, clientid, question)
def ask_question(self, bot, clientid, sentence) -> str:
if self.authentication is not None:
if self.authentication.authenticate(clientid) is False:
logging.error("[%s] failed authentication!")
return self.authentication.configuration.denied_srai
conversation = bot.get_conversation(clientid)
topic_pattern = conversation.predicate("topic")
if topic_pattern is None:
logging.info("No Topic pattern default to [*]")
topic_pattern = "*"
else:
logging.info("Topic pattern = [%s]", topic_pattern)
try:
that_question = conversation.nth_question(2)
that_sentence = that_question.current_sentence()
# If the last response was valid, i.e not none and not empty string, then use
# that as the that_pattern, otherwise we default to '*' as pattern
if that_sentence.response is not None and that_sentence.response != '':
that_pattern = TextUtils.strip_all_punctuation(
that_sentence.response)
logging.info("That pattern = [%s]", that_pattern)
else:
logging.info("That pattern, no response, default to [*]")
that_pattern = "*"
except Exception:
logging.info("No That pattern default to [*]")
that_pattern = "*"
match_context = self._aiml_parser.match_sentence(
bot,
clientid,
sentence,
topic_pattern=topic_pattern,
that_pattern=that_pattern)
if match_context is not None:
template_node = match_context.template_node()
logging.debug("AIML Parser evaluating template [%s]",
template_node.to_string())
response = template_node.template.resolve(bot, clientid)
if "<oob>" in response:
response, oob = self.strip_oob(response)
if oob is not None:
oob_response = self.process_oob(bot, clientid, oob)
response = response + " " + oob_response
return response
return None
def load_oob_processors(self, brain_configuration):
if brain_configuration.oob is not None:
if brain_configuration.oob.default() is not None:
try:
logging.info("Loading default oob")
classobject = ClassLoader.instantiate_class(
brain_configuration.oob.default().classname)
self._default_oob = classobject()
except Exception as excep:
logging.exception(excep)
for oob_name in brain_configuration.oob.oobs():
try:
logging.info("Loading oob: %s" % oob_name)
classobject = ClassLoader.instantiate_class(
brain_configuration.oob.oob(oob_name).classname)
self._oob[oob_name] = classobject()
except Exception as excep:
logging.exception(excep)
def strip_oob(self, response):
m = re.compile("(.*)(<\s*oob\s*>.*<\/\s*oob\s*>)(.*)")
g = m.match(response)
if g is not None:
front = g.group(1).strip()
back = g.group(3).strip()
response = ""
if front != "":
response = front + " "
response += back
oob = g.group(2)
return response, oob
return response, None
def process_oob(self, bot, clientid, oob_command):
oob_content = ET.fromstring(oob_command)
if oob_content.tag == 'oob':
for tag in oob_content:
if tag in self._oob:
oob_class = self._oob[tag]
return oob_class.process_out_of_bounds(bot, clientid, tag)
else:
return self._default_oob.process_out_of_bounds(
bot, clientid, tag)
return ""
def post_process_response(self, bot, clientid, response: str):
return self.postprocessors.process(bot, clientid, response)
def dump_tree(self):
self._aiml_parser.pattern_parser.root.dump(tabs="")