def mainmodel_func(query,tok,module_tok,entity):
top_intent = ''
query = query.lower()
if(re.search('verbal interpretation|numerical reasoning|spatial visualization|perceptual speed|verbal reasoning|capability [assessment|profile]',query)):
top_intent = 'capability_module'
print(top_intent)
top_intent = capability_assessment_model(query,module_tok[3],entity)
elif(re.search('emotional mindset|happiness|optimism|self esteem|self motivation|understading self and others|understanding self & others|understanding self|empathy|mastering self with others|assertiveness|influence|managing relationships|decision confidence|emotional expression|mastering self|stress managment|impulse control|emotional self control|bias managment|change managment',query)):
top_intent = 'emotional assessment'
top_intent = emotional_assessment_model(query,module_tok[4],entity)
elif(re.search('stress |conscious persona| working enviroment|core persona| natural enviroment|flex|shift above|shift below|shifted above|shifted below|[change|changed][my|her|his|there|their]* behavior|[change|changed][ |my|her|his|there|their]* behaviour|[modified|modify] there|behavioral profile',query)):
top_intent = 'Behavioral_Module'
top_intent = behavioral_assessment_model(query,module_tok[2],entity)
else:
m = load_model("D:\\bot\\botapi\\botapi\\models\\Main\\Main_Model.h5")
score = model_score_LSTM(query,tok,m)
print(score)
if((score[0][0]>score[0][1])&(score[0][0]>score[0][2])&(score[0][0]>score[0][3])&(score[0][0]>score[0][4])):
top_intent = 'Behavioral_Module'
top_intent = behavioral_assessment_model(query,module_tok[2],entity)
elif((score[0][1]>score[0][0])&(score[0][1]>score[0][2])&(score[0][1]>score[0][3])&(score[0][1]>score[0][4])):
top_intent = 'capability_module'
print(top_intent)
top_intent = capability_assessment_model(query,module_tok[3],entity)
elif((score[0][2]>score[0][0])&(score[0][2]>score[0][1])&(score[0][2]>score[0][3])&(score[0][2]>score[0][4])):
top_intent = 'emotional assessment'
top_intent = emotional_assessment_model(query,module_tok[4],entity)
elif((score[0][3]>score[0][0])&(score[0][3]>score[0][1])&(score[0][3]>score[0][2])&(score[0][3]>score[0][4])):
top_intent = 'Leave'
top_intent = leave_func(query,module_tok[0],entity)
else:
top_intent = 'Separation'
top_intent = separation_func(query,module_tok[1],entity)
return top_intent
def leave_func(query, leave_entities, entities):
top_intent = ''
query = query.lower()
m = load_model("D:\\bot\\botapi\\botapi\\models\\Leave\\Leave_Model.h5")
score = model_score_LSTM(query, leave_entities[0], m)
if ((score[0][0] > score[0][1]) & (score[0][0] > score[0][2]) &
(score[0][0] > score[0][3])):
Score = round(score[0][0] * 100, 2)
top_intent = 'Leave_Request'
elif ((score[0][1] > score[0][0]) & (score[0][1] > score[0][2]) &
(score[0][1] > score[0][3])):
top_intent = 'Leave_Approval'
Score = round(score[0][1] * 100, 2)
entities.append(leave_approval(query, leave_entities[2]))
#print(leave_approval(query,leave_entities[2]))
elif ((score[0][2] > score[0][0]) & (score[0][2] > score[0][1]) &
(score[0][2] > score[0][3])):
Score = round(score[0][2] * 100, 2)
top_intent = "Leave_Request"
leave_type = emotional_leave(query, leave_entities[1])
if leave_type not in entities:
entities.append(leave_type)
else:
Score = round(score[0][3] * 100, 2)
top_intent = 'Leave_Inquiry'
Score = str(Score)
return ('{"TopIntent": "' + top_intent + '", "Percentage":' + Score,
entities)
def quantity_module(name, tok_quantity):
sub_intent = ''
m = load_model(
'D:\\bot\\botapi\\botapi\\models\\Quantity\\Quantity_Model.h5')
score = model_score_LSTM(name, tok_quantity, m)
if (score[0][0] > score[0][1]):
sub_intent = sub_intent + "A"
else:
sub_intent = sub_intent + "P"
return sub_intent
def separation_func(query, separation_entities, entities):
sub_intent = ''
query = query.lower()
m = load_model("D:\\bot\\botapi\\botapi\\models\\Separation\\Sepration.h5")
score = model_score_LSTM(query, separation_entities[0], m)
if ((score[0][0] > score[0][1]) & (score[0][0] > score[0][2]) &
(score[0][0] > score[0][3]) & (score[0][0] > score[0][4]) &
(score[0][0] > score[0][5])):
sub_intent = "Blacklist Employees"
Score = round(score[0][0] * 100, 2)
elif ((score[0][1] > score[0][0]) & (score[0][1] > score[0][2]) &
(score[0][1] > score[0][3]) & (score[0][1] > score[0][4]) &
(score[0][1] > score[0][5])):
sub_intent = "Exit Clearance "
#status = exit_clearance_module(name)
#entities.append('"Status:""'+status+'"')
Score = round(score[0][1] * 100, 2)
elif ((score[0][2] > score[0][0]) & (score[0][2] > score[0][1]) &
(score[0][2] > score[0][3]) & (score[0][2] > score[0][4]) &
(score[0][2] > score[0][5])):
sub_intent = "Exit interview "
#status = exit_interview_module(name)
#entities.append('"Status:""'+status+'"')
Score = round(score[0][2] * 100, 2)
elif ((score[0][3] > score[0][0]) & (score[0][3] > score[0][1]) &
(score[0][3] > score[0][2]) & (score[0][3] > score[0][4]) &
(score[0][3] > score[0][5])):
sub_intent = "Exit Survey " #+
#entities.append('"Status:""'+status+'"')
#status = exit_survey_module(name)
Score = round(score[0][3] * 100, 2)
elif ((score[0][4] > score[0][0]) & (score[0][4] > score[0][1]) &
(score[0][4] > score[0][2]) & (score[0][4] > score[0][3]) &
(score[0][4] > score[0][5])):
sub_intent = "Notice Period "
#entities.append('"Status:""'+status+'"')
#status = notice_period_module(name)
Score = round(score[0][4] * 100, 2)
else:
sub_intent = "Resignation" #+ resignation(name)
Score = round(score[0][5] * 100, 2)
Score = str(Score)
return ('{"TopIntent": "' + sub_intent + '", "Percentage":' + Score,
entities)
def emotional_assessment_model(query, EA_tok, entity):
report_check = 0
graph_check = 0
score_check = 0
top_intent = '"Assessment"'
sub_intent = '"Emotional_Assessment"'
Score = '100'
if (re.search(
'emotional mindset|happiness|optimism|(self( |-)esteem)|(self( |-)motivation)',
query)):
entity = emotional_mindset_func(query, EA_tok[1], entity)
elif (re.search(
'(understanding self (&|and) other)|understanding self|empathy',
query)):
entity = understanding_self_and_others_func(query, EA_tok[2], entity)
elif (re.search(
'mastering self with other|assertiveness|influence|managing relationship|decision confidence|emotional expression',
query)):
entity = mastering_self_with_others(query, EA_tok[3], entity)
elif (re.search(
'mastering self|stress managment|impulse control|emotional self control|bias managment|change managment',
query)):
entity = mastering_self_func(query, EA_tok[4], entity)
elif (re.search('(emotional (assessment|intelligence|profile))|eq',
query)):
entity.append('"Status": "Emotional_Assessment"')
else:
m = load_model(
'D:\\bot\\botapi\\botapi\\models\\Emotional_Assessment\\Emotional_main.h5'
)
score = model_score_LSTM(query, EA_tok[0], m)
if ((score[0][0] > score[0][1]) & (score[0][0] > score[0][2]) &
(score[0][0] > score[0][3]) & (score[0][0] > score[0][4])):
entity = mastering_self_func(query, EA_tok[4], entity)
elif ((score[0][1] > score[0][0]) & (score[0][1] > score[0][2]) &
(score[0][1] > score[0][3]) & (score[0][1] > score[0][4])):
entity = mastering_self_with_others(query, EA_tok[3], entity)
elif ((score[0][2] > score[0][0]) & (score[0][2] > score[0][1]) &
(score[0][2] > score[0][3]) & (score[0][2] > score[0][4])):
entity = understanding_self_and_others_func(
query, EA_tok[2], entity)
elif ((score[0][3] > score[0][0]) & (score[0][3] > score[0][1]) &
(score[0][3] > score[0][2]) & (score[0][3] > score[0][4])):
entity = emotional_mindset_func(query, EA_tok[1], entity)
else:
entity.append('"Status": "Emotional_Assessment"')
intent = overall(query, EA_tok[5])
print(intent)
if 'Report' in intent:
report_check = 1
entity.append('"Report":"1"')
if 'Score' in intent:
score_check = 1
entity = main_entity(query, entity)
if 'Graph' in intent:
graph_check = 1
entity.append('"Graph":"1"')
if (score_check == 0):
entity.append('"Percentile" : "0"')
entity.append('"Intensity" : "0"')
if (graph_check == 0):
entity.append('"Graph":"0"')
if (report_check == 0):
entity.append('"Report":"0"')
return ('{"TopIntent": ' + top_intent + ', "SubIntent": ' + sub_intent +
', "Percentage":' + Score, entity)