def buildModel(storyId):
sequenceLabeler.train(storyId)
IntentClassifier().train()
return buildResponse.sentOk()
def fileupload(botId):
print("Bot Id in file upload", session.__getattribute__('botid'))
if request.method == 'POST':
# check if the post request has the file part
print(request.files)
if 'file' not in request.files:
print('No file part')
return redirect(request.url)
file = request.files['file']
print("File Details", file)
# if user does not select file, browser also
# submit a empty part without filename
if file.filename == '':
print('No selected file')
return redirect(request.url)
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
print("File Name", filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
print("File saved to folder")
#return redirect(url_for('stories_blueprint.fileupload', filename=filename))
csvfile = open(UPLOAD_FOLDER + '/' + filename,
'r',
encoding='utf-8',
errors='ignore')
reader = csv.DictReader(csvfile)
#print(reader)
header = [
"storyName", "intentName", "apiTrigger", "speechResponse",
"labeledSentences", "parameters"
]
parameter1 = []
ls = LabeledSentences()
for each in reader:
row = {}
labelSent = []
ls = LabeledSentences()
for field in header:
#print("Field",field)
list2 = []
if field == "labeledSentences":
#print("Inside labeled send")
#print("Row[fiel}",each[field])
cleanSentences = html2text.html2text(each[field])
#print("After clean Sentences")
#labelSen.data=posTagAndLabel(cleanSentences)
data = nlp.posTagAndLabel(cleanSentences)
print("Type of data", type(data))
ls.data = data
#print("Result ", labelSent)
#print("Type", type(labelSent))
row[field] = each[field]
#print("row field",row[field])
list2.append(ls)
csvStories = Story(storyName=row['storyName'],
intentName=row['intentName'],
apiTrigger=False,
speechResponse=row['speechResponse'],
parameters=parameter1,
labeledSentences=list2,
botId=botId)
csvStories.save()
print(row['storyName'], "Story Saved in DB")
for story in Story.objects():
try:
# print("Object Id",ObjectId(story.id))
sequenceLabeler.train(ObjectId(story.id))
print("Build Successfull")
print(ObjectId(story.id))
except:
print("In sequence labeller excpetion")
IntentClassifier().train()
#return redirect(url_for('stories_blueprint.fileupload', filename=filename))
return ''
def buildModel(storyId):
sequenceLabeler.train(storyId)
IntentClassifier().train()
return buildResponse.sentOk()
def buildModel(storyId):
sequenceLabeler.train(storyId)
intentClassifier = IntentClassifier()
intentClassifier.setBotId(g.botId)
intentClassifier.train()
return buildResponse.sentOk()
