Blissey
About Blissey is a Mental Health Chatbot , built with python , it can store and process json data
Tech Stack
Python , Tkinter , Torch
Features
- Interactive Chatbot
- Learn's New Responses
- minimal code
Main.py
from tkinter import *
from chat import get_response, bot_name
BG_GRAY = "#ABB2B9"
BG_COLOR = "#17202A"
TEXT_COLOUR = "#EAECEE"
FONT = "Helvetica 14"
FONT_BOLD = "Helvetica 13 bold"
class ChatApplication:
def __init__(self):
self.window = Tk()
self._setup_main_window()
def run(self):
self.window.mainloop()
def _setup_main_window(self):
self.window.title("Chat")
self.window.resizable(width=False, height=False)
self.window.configure(width=600, height=750, bg=BG_COLOR)
# head label
head_label = Label(self.window, bg=BG_COLOR, fg=TEXT_COLOUR,
text="Welcome", font=FONT_BOLD, pady=10)
head_label.place(relwidth=1)
#tiny divider
line = Label(self.window, width=450, bg=BG_GRAY)
line.place(relwidth=1, rely=0.07, relheight=0.012)
#text widget
self.text_widget = Text(self.window, width=20, height=2, bg=BG_COLOR, fg=TEXT_COLOUR,
font=FONT, padx=5, pady=5)
self.text_widget.place(relheight=0.745, relwidth=1, rely=0.08)
self.text_widget.configure(cursor="arrow", state=DISABLED)
#bottom label
bottom_label = Label(self.window, bg=BG_GRAY, height=80)
bottom_label.place(relwidth=1, rely=0.825)
#message entry box
self.msg_entry = Entry(bottom_label, bg="#2C3E50", fg=TEXT_COLOUR, font=FONT)
self.msg_entry.place(relwidth=0.74, relheight=0.06, rely=0.008, relx=0.011)
self.msg_entry.focus()
self.msg_entry.bind("<Return>", self._on_enter_pressed)
#send button
send_button = Button(bottom_label, text="Send", font=FONT_BOLD, width=20, bg=BG_GRAY,
command= lambda: self._on_enter_pressed(None))
send_button.place(relx=0.77, rely=0.008, relheight=0.06, relwidth=0.22)
def _on_enter_pressed(self, event):
msg = self.msg_entry.get()
self._insert_message(msg, "You")
def _insert_message(self, msg, sender):
if not msg:
return
self.msg_entry.delete(0, END)
msg1 = f"{sender}: {msg}\\n\\n"
self.text_widget.configure(state=NORMAL)
self.text_widget.insert(END, msg1)
self.text_widget.configure(state=DISABLED)
msg2 = f"{bot_name}: {get_response(msg)}\\n\\n"
self.text_widget.configure(state=NORMAL)
self.text_widget.insert(END, msg2)
self.text_widget.configure(state=DISABLED)
self.text_widget.see(END)
if __name__ == "__main__":
app = ChatApplication()
app.run()
Chat.py
import random
import json
import torch
from model import NeuralNet
from nltk_utils import bag_of_words, tokenize
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
with open('intents.json', 'r') as json_data:
intents = json.load(json_data)
FILE = "data.pth"
data = torch.load(FILE)
input_size = data["input_size"]
hidden_size = data["hidden_size"]
output_size = data["output_size"]
all_words = data['all_words']
tags = data['tags']
model_state = data["model_state"]
model = NeuralNet(input_size, hidden_size, output_size).to(device)
model.load_state_dict(model_state)
model.eval()
bot_name = "Aura"
def get_response(msg):
sentence = tokenize(msg)
X = bag_of_words(sentence, all_words)
X = X.reshape(1, X.shape[0])
X = torch.from_numpy(X).to(device)
output = model(X)
_, predicted = torch.max(output, dim=1)
tag = tags[predicted.item()]
probs = torch.softmax(output, dim=1)
prob = probs[0][predicted.item()]
if prob.item() > 0.75:
for intent in intents['intents']:
if tag == intent["tag"]:
return random.choice(intent['responses'])
else:
return "I do not understand..."