def post(self):
f = request.files['file-name']
basepath = os.path.dirname(__file__)
file_path = os.path.join('uploads', secure_filename(f.filename))
print(file_path)
f.save(file_path)
sents_in_summary = 5
summary_string = extract(file_path)
doc = nlp(summary_string)
text = generate_summary(doc, sents_in_summary)
print(text)
headers = {'Content-Type': 'text/html'}
try:
if (request.form["param"] == "1"):
return jsonify({
"data": {
"summary": text,
},
"from": "summarizer",
})
except:
return make_response(
render_template('summarizer.html',
text_data=text,
user_name=session['user_name'],
initials=session['initials'],
title="Summarize Text"), 200, headers)
def post(self):
f = request.files['file-name']
basepath = os.path.dirname(__file__)
file_path = os.path.join('uploads', secure_filename(f.filename))
print(file_path)
f.save(file_path)
reg_dic = extract(file_path)
senti_output = predict(reg_dic, True)
print(senti_output)
headers = {'Content-Type': 'text/html'}
try:
if (request.form["param"] == "1"):
return jsonify({
"data": {
"sentiment_analysis": senti_output,
},
"from": "sentiment_analysis",
})
except:
return make_response(
render_template('sentimental.html',
text_data=senti_output,
user_name=session['user_name'],
initials=session['initials'],
title="Feedback Form"), 200, headers)
def post(self):
print(type(request))
f = request.files['file-name']
# print(request.form["param"])
# print(type(request.form['param']))
basepath = os.path.dirname(__file__)
file_path = os.path.join('uploads', secure_filename(f.filename))
print(file_path)
f.save(file_path)
resume_string = extract(file_path)
dic = dict()
nlp = spacy.load('en')
dic = transform(dic, nlp, resume_string)
for x in dic[0]:
if type(dic[0][x]) == set:
dic[0][x] = list(dic[0][x])
# dic[0] is tuple of lists(which contains key-value pair)
print('DATA CONTENT OF DIC[0]', dic[0])
headers = {'Content-Type': 'text/html'}
keys = []
values = []
count = 0
with open('top_skills.csv', 'r') as csvfile:
csvreader = csv.reader(csvfile)
for row in csvreader:
if count == 0:
keys = row
count = count + 1
else:
values = row
print('keys', keys)
print('values', values)
skills = []
for i in range(len(keys)):
skills.append([keys[i], values[i]])
print('skills', skills)
try:
if (request.form["param"] is not None
and request.form["param"] == "1"):
return jsonify({
"data": {
"resume_data": dic[0],
"top_skills": skills,
},
"from": "resume"
})
except:
return make_response(
render_template('resume.html',
text_data=dic[0],
skills=skills,
user_name=session['user_name'],
initials=session['initials'],
title="Resume"), 200, headers)
def post(self):
f = request.files['file-name']
basepath = os.path.dirname(__file__)
file_path = os.path.join('uploads', secure_filename(f.filename))
print(file_path)
f.save(file_path)
reg_dic = extract(file_path)
senti_output = predict(reg_dic, True)
print(senti_output)
headers = {'Content-Type': 'text/html'}
return make_response(
render_template('sentimental.html', text_data=senti_output), 200,
headers)
def post(self):
f = request.files['file-name']
basepath = os.path.dirname(__file__)
file_path = os.path.join('uploads', secure_filename(f.filename))
print(file_path)
f.save(file_path)
reg_dic = extract(file_path)
if classify(reg_dic) == 1:
senti_output = predict(reg_dic, True)
print(senti_output)
headers = {'Content-Type': 'text/html'}
# return make_response(render_template('sentimental.html',text_data=senti_output),200,headers)
return redirect(url_for('sentimental', text_data=senti_output),
code=307)
elif classify(reg_dic) == 2:
dic = dict()
nlp = spacy.load('en')
dic = transform(dic, nlp, reg_dic)
for x in dic[0]:
if type(dic[0][x]) == set:
dic[0][x] = list(dic[0][x])
# dic[0] is tuple of lists(which contains key-value pair)
print('DATA CONTENT OF DIC[0]', dic[0])
headers = {'Content-Type': 'text/html'}
keys = []
values = []
count = 0
with open('top_skills.csv', 'r') as csvfile:
csvreader = csv.reader(csvfile)
for row in csvreader:
if count == 0:
keys = row
count = count + 1
else:
values = row
print('keys', keys)
print('values', values)
skills = []
for i in range(len(keys)):
skills.append([keys[i], values[i]])
print('skills', skills)
# return make_response(render_template('resume.html',text_data=dic[0],skills=skills),200,headers)
return redirect(url_for('resume', text_data=dic[0], skills=skills),
code=307)
else:
output = 3
headers = {'Content-Type': 'text/html'}
return make_response(
render_template('classifier.html', text_data=output), 200,
headers)
def post(self):
f = request.files['file-name']
basepath = os.path.dirname(__file__)
file_path = os.path.join('uploads', secure_filename(f.filename))
print(file_path)
f.save(file_path)
sents_in_summary = 5
summary_string = extract(file_path)
doc = nlp(summary_string)
text = generate_summary(doc, sents_in_summary)
print(text)
headers = {'Content-Type': 'text/html'}
return make_response(
render_template('summarizer.html', text_data=text), 200, headers)
def post(self):
f = request.files['file-name']
basepath = os.path.dirname(__file__)
file_path = os.path.join('uploads', secure_filename(f.filename))
print(file_path)
f.save(file_path)
reg_dic = extract(file_path)
if classify(reg_dic) == 1:
senti_output = predict(reg_dic, True)
print(senti_output)
headers = {'Content-Type': 'text/html'}
try:
if (request.form["param"] == "1"):
return jsonify({
"data": {
"sentiment_analysis": senti_output,
},
"from": "sentiment_analysis",
})
except:
return redirect(url_for('sentimental',
text_data=senti_output,
user_name=session['user_name'],
initials=session['initials'],
title="Feedback Form"),
code=307)
elif classify(reg_dic) == 2:
dic = dict()
nlp = spacy.load('en')
dic = transform(dic, nlp, reg_dic)
for x in dic[0]:
if type(dic[0][x]) == set:
dic[0][x] = list(dic[0][x])
print('DATA CONTENT OF DIC[0]', dic[0])
headers = {'Content-Type': 'text/html'}
keys = []
values = []
count = 0
with open('top_skills.csv', 'r') as csvfile:
csvreader = csv.reader(csvfile)
for row in csvreader:
if count == 0:
keys = row
count = count + 1
else:
values = row
print('keys', keys)
print('values', values)
skills = []
for i in range(len(keys)):
skills.append([keys[i], values[i]])
print('skills', skills)
try:
if (request.form["param"] == "1"):
return jsonify({
"data": {
"resume_data": dic[0],
"top_skills": skills,
},
"from": "resume"
})
except:
return redirect(url_for('resume',
text_data=dic[0],
skills=skills,
user_name=session['user_name'],
initials=session['initials'],
title="Resume"),
code=307)
else:
output = 3
headers = {'Content-Type': 'text/html'}
try:
if request.form["param"] == "1":
return jsonify({
"data": {
"classifier_data": output
},
"from": "classifier"
})
except:
return make_response(
render_template('classifier.html',
text_data=output,
user_name=session['user_name'],
initials=session['initials'],
title="Classify Form"), 200, headers)