def personality_insight(dicto,email):
db=crud()
new_dicto={}
flag=0
for i in dicto:
if i["trait_name"] == "Openness" and (i["percentile"] > 0.55 and i["percentile"] < 0.9):
flag +=1
elif i["trait_name"] == "Conscientiousness" and (i["percentile"] > 0.5 and i["percentile"] < 0.9) :
flag +=1
elif i["trait_name"] == "Extraversion" and (i["percentile"] >0.45 and i["percentile"] < 0.85) :
flag +=1
elif i["trait_name"]=="Agreeableness" and (i["percentile"]>0.40 and i["percentile"]<0.85) :
flag +=1
elif i["trait_name"]=="Emotional range" and (i["percentile"]>0.40 and i["percentile"]<0.75) :
flag +=1
if flag >= 4:
new_dicto = {"Personality": dicto}
db.search_and_insert(email,'candidate_features',new_dicto,"single")
rest = "Congratulations!, you have been shortlisted for the interview process, further information will be mailed to you."
return rest
else:
new_dicto = {"Personality": dicto}
db.search_and_insert(email,'candidate_features',new_dicto,"single")
rest = "We regret to inform you that you were not shortlisted for the job, we hope you find success in your life, Thank you."
return rest
def hobbi_scoring(score,username):
db = crud()
dicto = {}
dicto = db.search_feature(username, 'candidate_features')
hobbi = dicto["Hobbies"]
score = score+len(hobbi)*30
return score
def achievement_scoring(score,username):
db = crud()
dicto = {}
dicto = db.search_feature(username, 'candidate_features')
achivement = dicto["Achievement"]
score = score+len(achivement)*50
return score
def gettestdata(key, dbname, c):
db = crud()
doc = db.search_feature(key, 'test_question')
print(type(doc))
print(doc)
l = doc['questions']
shuffled_doc = random.sample(l, k=c)
doc = shuffled_doc
return doc
def score_skills(score,username):
db=crud()
dicto={}
dicto = db.search_feature(username, 'candidate_features')
skill = ["c", "cpp", "c++", "java", "python","SQL"]
skills=dicto["Skill"]
for i in skills:
if i.lower() in skill:
score=score+100
else:
score = score+200
return score
def score_internships(score,username):
db = crud()
companies1 = ['amazon','google','iisc','microsoft','apple']
companies2 = ['tcs','wipro','infosys','mindtree','l&t infotec']
intern = {}
dicto = {}
company =[]
dicto = db.search_feature(username,'candidate_features')
intern = dicto["Internship"]
for i in intern:
company.append(list(i.keys())[0])
for i in company:
if i.lower() in companies1:
score = score+300
elif i.lower() in companies2:
score = score+200
else:
score = score+100
return score
def project_scoring(score,username):
db = crud()
proj={}
dicto={}
tecnologies1 = ["ai","ml","deep learning","neural network","clojure"]
tecnologies2 = ["flask","django","node js","angular js","react js","ruby","R"]
dicto = db.search_feature(username,'candidate_features')
proj = dicto["Project"]
for i in proj:
tech = list(i.values())
print(tech)
tech = tech[0][0].split(",")
for j in tech:
if j.lower() in tecnologies1:
score=score+300
elif j.lower() in tecnologies2:
score=score+200
else:
score=score+100
return score
def second_conversation(self, data, email):
assistant = wh.get_assistant()
db = crud()
result_dict = {}
context = {
"skills": {
"main skill": {
"user_defined": {
"flag": 1,
}
}
}
}
response, contextvariable = wh.watson_request(data['session_id'], assistant,
data['message'], context)
print(contextvariable)
if (('second_round_flag' in contextvariable.keys()) and ('cand_result' not in contextvariable.keys())):
data1 = unpack_response(response, data)
print("In if")
return(data1)
elif(('second_round_flag' in contextvariable.keys()) and ('hr1' in contextvariable['cand_result'].keys())):
ans = contextvariable['cand_result']['hr1']
result = {'ans1':ans}
print(result)
db.search_and_insert(email,'hr_question',result, flag='single')
data1 = unpack_response(response, data)
return(data1)
elif(('second_round_flag' in contextvariable) and ('hr2' in contextvariable['cand_result'])):
ans = contextvariable['cand_result']['hr2']
result = {'ans2': ans}
db.search_and_insert(email, 'hr_question', result, flag = 'single')
data1 = unpack_response(response, data)
return(data1)
elif(('second_round_flag' in contextvariable) and ('hr3' in contextvariable['cand_result'])):
ans = contextvariable['cand_result']['hr3']
result = {'ans3': ans}
db.search_and_insert(email, 'hr_question', result, flag = 'single')
data1 = unpack_response(response, data)
return(data1)
elif(('second_round_flag' in contextvariable) and ('hr4' in contextvariable['cand_result'])):
ans = contextvariable['cand_result']['hr4']
result = {'ans4': ans}
db.search_and_insert(email, 'hr_question', result, flag = 'single')
data1 = unpack_response(response, data)
return(data1)
elif(('second_round_flag' in contextvariable) and ('hr5' in contextvariable['cand_result'])):
ans = contextvariable['cand_result']['hr5']
result = {'ans5': ans}
db.search_and_insert(email, 'hr_question', result, flag = 'single')
data1 = unpack_response(response, data)
return(data1)
elif(('second_round_flag' in contextvariable) and ('hr6' in contextvariable['cand_result'])):
ans = contextvariable['cand_result']['hr6']
result = {'ans6': ans}
db.search_and_insert(email, 'hr_question', result, flag = 'single')
data1 = unpack_response(response, data)
return(data1)
else:
data1 = unpack_response(response, data)
return(data1)
print("In else")
def server_convo_handler(self, data, email):
assistant = wh.get_assistant()
db = crud()
result_dict = {}
db_doc = db.search_feature(email, 'candidate_features')
context = {
"skills":{
"main skill": {
"user_defined": {
"flag": 1,
"first_round_flag": db_doc['first_round_flag'],
'test_link_share':db_doc['test_link_share']
}
}
}
}
response, contextvariable = wh.watson_request(data['session_id'], assistant,
data['message'], context)
if 'dob' not in contextvariable.keys():
data1 = unpack_response(response, data)
return(data1)
elif ('dob' in contextvariable.keys()) and ('cand_result' not in contextvariable.keys()):
dob = contextvariable['dob']
result = {'dob': dob}
db.search_and_insert(email, 'candidate_features', result, 'single')
data1 = unpack_response(response, data)
return data1
elif ('dob' in contextvariable.keys()) and ('10th' in contextvariable['cand_result']):
result = e.split_and_compile(contextvariable['cand_result']['10th'])
for index, val in enumerate(result):
if index == 2:
result[index] = float(result[index])
result_dict = {'Education': {'UG': result}}
result_dict = {'Education': {'10th standard': result}}
db.search_and_insert(email, 'candidate_features', result_dict,'double')
data1 = unpack_response(response, data)
return data1
elif ('dob' in contextvariable.keys()) and ('12th' in contextvariable['cand_result']):
result = e.split_and_compile(contextvariable['cand_result']['12th'])
for index, val in enumerate(result):
if index == 2:
result[index] = float(result[index])
result_dict = {'Education': {'UG': result}}
result_dict = {'Education': {'12th standard': result}}
db.search_and_insert(email, 'candidate_features', result_dict,'double')
data1 = unpack_response(response, data)
return data1
elif ('dob' in contextvariable.keys()) and ('UG' in contextvariable['cand_result']):
result = e.split_and_compile(contextvariable['cand_result']['UG'])
for index, val in enumerate(result):
if index == 2:
result[index] = float(result[index])
result_dict = {'Education': {'UG': result}}
db.search_and_insert(email, 'candidate_features', result_dict,'double')
data1 = unpack_response(response, data)
return data1
elif ('dob' in contextvariable.keys()) and ('Skill' in contextvariable['cand_result']):
##ensure lowercase for skills
result = e.split_and_compile(contextvariable['cand_result']['Skill'])
result = [i.lower() for i in result]
result_dict = {'Skill': result}
db.search_and_insert(email, 'candidate_features', result_dict, flag= 'single')
data1 = unpack_response(response, data)
return data1
elif ('dob' in contextvariable.keys()) and ('Hobbies' in contextvariable['cand_result']):
result = e.split_and_compile(contextvariable['cand_result']['Hobbies'])
result_dict = {'Hobbies': result}
db.search_and_insert(email, 'candidate_features', result_dict, flag= 'single')
data1 = unpack_response(response,data)
return data1
elif ('dob' in contextvariable.keys()) and ('Project' in contextvariable['cand_result']):
if not contextvariable['cand_result']['Project']:
data1 = unpack_response(response, data)
return data1
else:
result = e.split_and_compile(contextvariable['cand_result']['Project'])
result_dict = {'Project': {
result[0]: [result[1], result[2]]
}}
db.search_and_insert(email, 'candidate_features', result_dict, flag = 'double')
data1 = unpack_response(response, data)
return data1
elif ('dob' in contextvariable.keys()) and ('Internship' in contextvariable['cand_result']):
if not contextvariable['cand_result']['Internship']:
data1 = unpack_response(response, data)
return data1
else:
result = e.split_and_compile(contextvariable['cand_result']['Internship'])
result_dict = {'Internship': {
result[0]: [result[1], result[2]]
}}
db.search_and_insert(email, 'candidate_features', result_dict, flag = 'double')
data1 = unpack_response(response, data)
return data1
elif ('dob' in contextvariable.keys()) and ('Achievement' in contextvariable['cand_result']):
rek = {}
if not contextvariable['cand_result']['Achievement']:
my_document = db.search_feature(email, 'candidate_features')
if my_document['Education'][2]['UG'][2] >= 7.0:
rek['first_round_flag'] = 'Pass'
rek['test_link_share'] = "http://127.0.0.1:5000/test"
db.search_and_insert(email, 'candidate_features', rek, flag ='single')
else:
my_document['first_round_flag'] = 'Fail'
rek = contextvariable['cand_result']['Achievement']
db.search_and_insert(email, 'candidate_features', rek, flag ='single')
data1 = unpack_response(response, data)
return data1
else:
result_dict = {'Achievement': contextvariable['cand_result']['Achievement']}
db.search_and_insert(email, 'candidate_features', result_dict, flag ='double')
data1 = unpack_response(response, data)
return data1
else:
data1 = unpack_response(response, data)
return data1
from flask import redirect, render_template, session, request, make_response
from app.dbservices import crud
from app import app
from app.machine_learning.watson import watsonhandler
from werkzeug.security import generate_password_hash, check_password_hash
from flask_socketio import SocketIO, join_room
from app.handler import convo_handler
from app.machine_learning.data_extractor import extractor
from app.test_relate import generate_test as gt
from app.candidate_scoring import scoring as sc
from app.machine_learning import pers as pp
import json
import pdfkit
db = crud()
cand = {}
hand = convo_handler()
wh = watsonhandler()
socketio = SocketIO(app)
@app.route('/')
@app.route('/index', methods=['POST', 'GET'])
def index():
return render_template('index.html')
@app.route('/login', methods=['POST', 'GET'])
def login():
if request.method == 'POST':
email = request.form['email']
def gettest(username):
db = crud()
doc = []
docfinal = []
skillss = []
dicto = {}
skill = ["c", "cpp", "c++", "java", "python"]
dicto = db.search_feature(username, 'candidate_features')
skills = dicto["Skill"]
for i in skills:
if i in skill:
skillss.append(i)
length = len(skillss)
if length == 4:
doc = gettestdata("C", 'test_question', 5)
doc1 = gettestdata("CPP", 'test_question', 5)
doc2 = gettestdata("Java", 'test_question', 5)
doc3 = gettestdata("python", 'test_question', 5)
docfinal = doc + doc1 + doc2 + doc3
return (docfinal)
elif length == 3:
j = 0
for i in skillss:
if j == 12:
if i == "c":
doc = gettestdata("C", 'test_question', 8)
elif i == "cpp" or i == "c++":
doc = gettestdata("CPP", 'test_question', 8)
elif i == "java":
doc = gettestdata("Java", 'test_question', 8)
elif i == "python":
doc = gettestdata("python", 'test_question', 8)
else:
if i == "c":
doc = gettestdata("C", 'test_question', 6)
elif i == "cpp" or i == "c++":
doc = gettestdata("CPP", 'test_question', 6)
elif i == "java":
doc = gettestdata("Java", 'test_question', 6)
elif i == "python":
doc = gettestdata("python", 'test_question', 6)
j = j + 6
docfinal += doc
return (docfinal)
elif length == 2:
for i in skillss:
if i == "c":
doc = gettestdata("C", 'test_question', 10)
elif i == "cpp" or i == "c++":
doc = gettestdata("CPP", 'test_question', 10)
elif i == "java":
doc = gettestdata("Java", 'test_question', 10)
elif i == "python":
doc = gettestdata("python", 'test_question', 10)
docfinal += doc
return (docfinal)
else:
doc = gettestdata(skillss[0], 'test_question', 20)
return doc
