def test():
with open('dataset_new.json', 'r') as f:
dataset = json.load(f)
form = InputForm()
if form.validate_on_submit():
intent = action_predict(str(form.input_data.data))
log(intent)
if intent != "none":
k = dsl(intent)
reply = k.generate()
log(reply)
input_text = form.input_data.data
#print(input_text)
dat = {"question": input_text, "answer": reply}
form.input_data.data = ""
return render_template('index.html',
reply=reply["text"],
form=form,
input_text=input_text)
else:
reply = reply_predict(str(form.input_data.data))
input_text = form.input_data.data
dat = {"question": input_text, "answer": reply}
dataset.append(dat)
with open("dataset_new.json", "w") as w:
json.dump(dataset, w)
form.input_data.data = ""
return render_template('index.html',
reply=reply,
form=form,
input_text=input_text)
return render_template('index.html', form=form)
def test():
form = InputForm()
if form.validate_on_submit():
intent = action_predict(str(form.input_data.data))
log(intent)
if intent != "none":
k = dsl(intent)
reply = k.generate()
log(reply)
input_text = form.input_data.data
#print(input_text)
form.input_data.data = ""
return render_template('index.html',
reply=reply["text"],
form=form,
input_text=input_text)
else:
reply = reply_predict(str(form.input_data.data))
input_text = form.input_data.data
form.input_data.data = ""
return render_template('index.html',
reply=reply,
form=form,
input_text=input_text)
return render_template('index.html', form=form)
def process_msg(message_text):
intent = action_predict(str(message_text)) #predicting action
if intent != "none": #if the message is a command
k = dsl(intent)
reply = k.generate()
return reply
else: #if the message is just chitchat
reply = reply_predict(message_text)
return reply
from torch.autograd import Variable
import torch
training_data = []
with open('action_dataset.json') as data_file:
data = json.load(data_file)
for line in data:
#fetching training data
training_data.append(line)
action_train(20000, training_data) #training the model
#testing with a new input
#print("say wahts tinkerhub")
print("intent:" + action_predict("how is it"))
"""
accuracy= 0 % input= tell me more about RIT actual= website guess= website
accuracy= 0 % input= give me more information actual= website guess= website
accuracy= 1 % input= who is the principal actual= website guess= website
accuracy= 0 % input= give me the phone number actual= contact guess= contact
accuracy= 31 % input= open college website actual= website guess= website
accuracy= 43 % input= open college website actual= website guess= website
accuracy= 0 % input= navigate me to RIT actual= location guess= location
accuracy= 30 % input= give me more information actual= website guess= website
accuracy= 28 % input= good bye actual= goodbye guess= goodbye
accuracy= 69 % input= have a nice day actual= goodbye guess= goodbye
accuracy= 0 % input= navigate me to RIT actual= location guess= location
accuracy= 76 % input= open college website actual= website guess= website
accuracy= 67 % input= i have to go actual= goodbye guess= goodbye
accuracy= 80 % input= open college website actual= website guess= website
from torch.autograd import Variable
import torch
training_data = []
with open('app/datasets/action_dataset.json') as data_file:
data = json.load(data_file)
for line in data:
#fetching training data
training_data.append(line)
action_train(20000, training_data) #training the model
#testing with a new input
#print("say wahts tinkerhub")
print("intent:" + action_predict("hello"))
"""
accuracy= 0 % input= tell me more about RIT actual= website guess= website
accuracy= 0 % input= give me more information actual= website guess= website
accuracy= 1 % input= who is the principal actual= website guess= website
accuracy= 0 % input= give me the phone number actual= contact guess= contact
accuracy= 31 % input= open college website actual= website guess= website
accuracy= 43 % input= open college website actual= website guess= website
accuracy= 0 % input= navigate me to RIT actual= location guess= location
accuracy= 30 % input= give me more information actual= website guess= website
accuracy= 28 % input= good bye actual= goodbye guess= goodbye
accuracy= 69 % input= have a nice day actual= goodbye guess= goodbye
accuracy= 0 % input= navigate me to RIT actual= location guess= location
accuracy= 76 % input= open college website actual= website guess= website
accuracy= 67 % input= i have to go actual= goodbye guess= goodbye
accuracy= 80 % input= open college website actual= website guess= website
from torch.autograd import Variable
import torch
training_data = []
with open('action_dataset.json') as data_file:
data = json.load(data_file)
for line in data:
#fetching training data
training_data.append(line)
action_train(10000, training_data) #training the model
#testing with a new input
print("how can i reach RIT")
print("intent:" + action_predict("how can i reach RIT"))
"""
accuracy= 0 % input= tell me more about RIT actual= website guess= website
accuracy= 0 % input= give me more information actual= website guess= website
accuracy= 1 % input= who is the principal actual= website guess= website
accuracy= 0 % input= give me the phone number actual= contact guess= contact
accuracy= 31 % input= open college website actual= website guess= website
accuracy= 43 % input= open college website actual= website guess= website
accuracy= 0 % input= navigate me to RIT actual= location guess= location
accuracy= 30 % input= give me more information actual= website guess= website
accuracy= 28 % input= good bye actual= goodbye guess= goodbye
accuracy= 69 % input= have a nice day actual= goodbye guess= goodbye
accuracy= 0 % input= navigate me to RIT actual= location guess= location
accuracy= 76 % input= open college website actual= website guess= website
accuracy= 67 % input= i have to go actual= goodbye guess= goodbye
accuracy= 80 % input= open college website actual= website guess= website