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Jarvis_old.py
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import random
import json
import re
from flask import current_app
import torch
from Brain import NeuralNet
from NeauralNetwork import bag_of_words, tokenize
from datetime import datetime
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()
#####################################
Name = "JARVIS"
from Listen import Suno
from Speak import Bol
from Task import NonInputExecution, wishMe
from Task import InputExecution
class JARVIS:
def PROCESS_(self):
sentence = Suno()
result = str(sentence)
if sentence == "bye":
exit()
sentence = tokenize(sentence)
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"]:
reply = random.choice(intent["responses"])
if "time" in reply:
NonInputExecution(reply)
elif "date" in reply:
NonInputExecution(reply)
elif "day" in reply:
NonInputExecution(reply)
elif "wikipedia" in reply:
InputExecution(reply, sentence)
elif "google" in reply:
InputExecution(reply, result)
elif "joke" in reply:
NonInputExecution(reply)
else:
Bol(reply)
while True:
self.PROCESS_()