Seat Create

.history/sub_delete_all_seat_details_20211007214918.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215138.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215214.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE 0"
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215215.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE 0";
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215234.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215245.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result25 = mysqli_query($con,$sql25) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215246.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result25 = mysqli_query($con,$sql25) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215250.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215251.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215256.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215302.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    $sql2 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result2 = mysqli_query($con,$sql2) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215303.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    $sql2 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result2 = mysqli_query($con,$sql2) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_delete_all_seat_details_20211007215311.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    $sql2 = "DELETE FROM `best_seat` WHERE logUserid = $logUserid ";
+    $result2 = mysqli_query($con,$sql2) or die(mysqli_error($con));
\ No newline at end of file

.history/sub_update_date_20211003122139.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+    $startTime = mysqli_real_escape_string($con,$_POST['startTime']);
+    $endTime = mysqli_real_escape_string($con,$_POST['endTime']);
+
+    $sql1 = "UPDATE `user_details` SET `start`='$startTime',`end`='$endTime' WHERE `logUserid`='$logUserid'";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    if($result1){
+        echo 1;
+    } else {
+        echo 0;
+    }
\ No newline at end of file

.history/sub_update_date_20211007215219.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+    $startTime = mysqli_real_escape_string($con,$_POST['startTime']);
+    $endTime = mysqli_real_escape_string($con,$_POST['endTime']);
+
+    $sql1 = "UPDATE `user_details` SET `start`='$startTime',`end`='$endTime' WHERE `logUserid`='$logUserid'";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    if($result1){
+        echo 1;
+    } else {
+        echo 0;
+    }
\ No newline at end of file

.history/sub_update_date_20211007215222.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+    $startTime = mysqli_real_escape_string($con,$_POST['startTime']);
+    $endTime = mysqli_real_escape_string($con,$_POST['endTime']);
+
+    $sql1 = "UPDATE `user_details` SET `start`='$startTime',`end`='$endTime' WHERE `logUserid`='$logUserid'";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    if($result1){
+        echo 1;
+    } else {
+        echo 0;
+    }
\ No newline at end of file

chatbot/api.py

+from flask import Flask
+app = Flask(__name__)
+import random
+import json
+
+import torch
+
+from model import NeuralNet
+from nltk_utils import bag_of_words, tokenize
+
+@app.route('/<string:name>/')
+def hello(name):
+	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 = "TravellChatty"
+	
+	while True:
+    # sentence = "do you use credit cards?"
+		sentence =name
+		if sentence == "quit":
+			break
+
+		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"]:
+					return (f" {random.choice(intent['responses'])}")
+				
+					#print(f"{bot_name}: {random.choice(intent['responses'])}")
+		else:
+			return (f" I do not understand...")
+			#print(f"{bot_name}: I do not understand...")
+	
+app.run()

chatbot/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 = "TravellChatty"
+print("Let's chat! (type 'quit' to exit)")
+while True:
+    # sentence = "do you use credit cards?"
+    sentence = input("You: ")
+    if sentence == "quit":
+        break
+
+    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"]:
+                print(f"{bot_name}: {random.choice(intent['responses'])}")
+    else:
+        print(f"{bot_name}: I do not understand...")

chatbot/flow.drawio

+<mxfile host="app.diagrams.net" modified="2021-07-05T06:13:17.469Z" agent="5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36" etag="0eO2WcAi71hUnJJ3aWHb" version="14.8.4" type="device"><diagram id="C5RBs43oDa-KdzZeNtuy" name="Page-1">7VhZc5swEP41PLbD4WLnsThxktbNJE3aTB9lkEG10FIhfPTXdzHCgPH4aOscnvjBo12vV9J+3x5gOP14filJEn2BgHLDNoO54Zwbtt1ze/idKxaFotM5KxShZEGhsirFPftNtdLU2owFNG0YKgCuWNJU+iAE9VVDR6SEWdNsDLy5a0JC2lLc+4S3tY8sUJG+lt2t9FeUhVG5s+Xq+8WkNNY3SSMSwKymci4Mpy8BVLGK533K89iVcXm8Xjzy4cS9/HSX/iLfvM8PN9/fFc4Gh/xldQVJhfq/ru3C9ZTwTMdL31UtygBKyERAcyem4XiRijkuLVz+pEotNOAkU4AqkCqCEAThQ4BE241BKG1m5TIVwcccWJRHHPxJoRowzvUeKGn7HkqpkjBZYZc7WAGRG3Myotwj/iRcHrQPHCT+JEDQ3FWAZNB3qQ53UWm9PWOrMUghkz7dYudoihMZ0m3+3MIuP1+Npxq5SwoxVXKBBpJyoti0SWaicyJc2VW440JDfwANnBYNrkWSKVTdZTRVDMQWWuSQzCKm6H1ClrGZYSFpUqVOAbylF3KSphrAHfgehs+USkXnWyNa/urqtNZ1zdHirCoSVpn5Ua1AdMwjYdBpYfAD6+ZbNv5LNrp7ZmPZrHamoyZLSYy9s1N7ugUmVM0ExuMUD7ZOndWGf8+mDy023UCLTLvxeNV0eyYydQ/jkvXiueS2uDQkcWLYLscweCOJqzBfJTwLQyQLuhOGM2jXrgjiUZbubhcNjHMGDUjMeB6vK8qnVDGfbGgqhLMQ9z33EW4qN5MHt2QiRMmtpIclWbH+HrHZdJvNZiXXu425odv0jtVtui1MbxG9Ajrb5Et8T6zjO/YaCGfP3fJ7+xTpV12Cn7zjl9V0d8u39izTmj3mewc/DQK9/CngbK+Z8m0MOA7D7FMbBMoT1vjkZXzUngRGmRTLQQDwIfJtEtgyCdibmtCTTgJlIayB+pUmhCGY5vAU54D1J//Osz/6l5WiCQHPY2qbRYadGAbrs5hjHQ8DFKuXtEUprN50Oxd/AA==</diagram></mxfile>
\ No newline at end of file

chatbot/model.py

+import torch
+import torch.nn as nn
+
+class NeuralNet(nn.Module):
+    def __init__(self, input_size, hidden_size, num_classes):
+        super(NeuralNet, self).__init__()
+        self.l1 = nn.Linear(input_size, hidden_size) 
+        self.l2 = nn.Linear(hidden_size, hidden_size) 
+        self.l3 = nn.Linear(hidden_size, num_classes)
+        self.relu = nn.ReLU()
+    def forward(self, x):
+        out = self.l1(x)
+        out = self.relu(out)
+        out = self.l2(out)
+        out = self.relu(out)
+        out = self.l3(out)
+        # no activation and no softmax at the end
+        return out

chatbot/nltk_utils.py

+import numpy as np
+import nltk
+nltk.download('punkt')
+from nltk.stem.porter import PorterStemmer
+stemmer = PorterStemmer()
+
+def tokenize(sentence):
+    """
+    split sentence into array of words/tokens
+    a token can be a word or punctuation character, or number
+    """
+    return nltk.word_tokenize(sentence)
+
+
+def stem(word):
+    """
+    stemming = find the root form of the word
+    examples:
+    words = ["organize", "organizes", "organizing"]
+    words = [stem(w) for w in words]
+    -> ["organ", "organ", "organ"]
+    """
+    return stemmer.stem(word.lower())
+
+
+def bag_of_words(tokenized_sentence, words):
+    """
+    return bag of words array:
+    1 for each known word that exists in the sentence, 0 otherwise
+    example:
+    sentence = ["hello", "how", "are", "you"]
+    words = ["hi", "hello", "I", "you", "bye", "thank", "cool"]
+    bog   = [  0 ,    1 ,    0 ,   1 ,    0 ,    0 ,      0]
+    """
+    # stem each word
+    sentence_words = [stem(word) for word in tokenized_sentence]
+    # initialize bag with 0 for each word
+    bag = np.zeros(len(words), dtype=np.float32)
+    for idx, w in enumerate(words):
+        if w in sentence_words: 
+            bag[idx] = 1
+
+    return bag

chatbot/train.py

+import json
+import numpy as np
+
+import torch
+import torch.nn as nn
+from torch.utils.data import Dataset, DataLoader
+from nltk_utils import bag_of_words, tokenize, stem
+from model import NeuralNet
+
+with open('intents.json', 'r') as f:
+    intents = json.load(f)
+    
+all_words = []
+tags = []
+xy = []
+
+for intent in intents['intents']:
+    tag = intent['tag']
+    # add to tag list
+    tags.append(tag)
+    for pattern in intent['patterns']:
+        # tokenize each word in the sentence
+        w = tokenize(pattern)
+        # add to our words list
+        all_words.extend(w)
+        # add to xy pair
+        xy.append((w, tag))
+        
+ignore_words = ['?', '.', '!']
+all_words = [stem(w) for w in all_words if w not in ignore_words]
+all_words = sorted(set(all_words))
+tags = sorted(set(tags))
+print(tags)
+
+X_train = []
+y_train = []
+
+for (pattern_sentence, tag) in xy:
+    # X: bag of words for each pattern_sentence
+    bag = bag_of_words(pattern_sentence, all_words)
+    X_train.append(bag)
+    # y: PyTorch CrossEntropyLoss needs only class labels, not one-hot
+    label = tags.index(tag)
+    y_train.append(label)
+   
+X_train = np.array(X_train)
+y_train = np.array(y_train)
+
+class ChatDataset(Dataset):
+
+    def __init__(self):
+        self.n_samples = len(X_train)
+        self.x_data = X_train
+        self.y_data = y_train
+
+    # support indexing such that dataset[i] can be used to get i-th sample
+    def __getitem__(self, index):
+        return self.x_data[index], self.y_data[index]
+
+    # we can call len(dataset) to return the size
+    def __len__(self):
+        return self.n_samples
+        
+num_epochs = 1000
+learning_rate = 0.001
+batch_size = 8
+input_size = len(X_train[0])
+hidden_size = 8
+output_size = len(tags)
+print(input_size, output_size)
+
+dataset = ChatDataset()
+train_loader = DataLoader(dataset=dataset,
+                          batch_size=batch_size,
+                          shuffle=True,
+                          num_workers=0)
+
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+model = NeuralNet(input_size, hidden_size, output_size).to(device)
+
+criterion = nn.CrossEntropyLoss()
+optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)
+
+for epoch in range(num_epochs):
+    for (words, labels) in train_loader:
+        words = words.to(device)
+        labels = labels.to(dtype=torch.long).to(device)
+        
+        # Forward pass
+        outputs = model(words)
+        # if y would be one-hot, we must apply
+        # labels = torch.max(labels, 1)[1]
+        loss = criterion(outputs, labels)
+        
+        # Backward and optimize
+        optimizer.zero_grad()
+        loss.backward()
+        optimizer.step()
+    if (epoch+1) % 100 == 0:
+        print (f'Epoch [{epoch+1}/{num_epochs}], Loss: {loss.item():.4f}')
+        
+        
+print(f'final loss: {loss.item():.4f}')
+
+data = {
+"model_state": model.state_dict(),
+"input_size": input_size,
+"hidden_size": hidden_size,
+"output_size": output_size,
+"all_words": all_words,
+"tags": tags
+}
+
+FILE = "data.pth"
+torch.save(data, FILE)
+
+print(f'training complete. file saved to {FILE}')
+
+
+
+
+
+

sub_delete_all_seat_details.php

+<?php
+
+    session_start();
+
+	include "db_connect.php";
+
+    $logUserid = mysqli_real_escape_string($con,$_POST['logUserid']);
+
+    $sql1 = "DELETE FROM `select_seat_temp` WHERE logUserid = $logUserid ";
+    $result1 = mysqli_query($con,$sql1) or die(mysqli_error($con));
+
+    $sql2 = "DELETE FROM `best_seat` WHERE logUserid = $logUserid ";
+    $result2 = mysqli_query($con,$sql2) or die(mysqli_error($con));
\ No newline at end of file

train_planned.php

@@ -131,6 +131,7 @@
 						//   console.log(req.responseText);
 						  document.getElementById(`collapseOne`).innerHTML = req.responseText;
 						  changeLineName();
+						  deleteSeatDetails(logUserid);
                         }            
                 } 
             } 
@@ -140,6 +141,26 @@
             }
 		}
 
+		function deleteSeatDetails(logUserid) {
+			var formData = new FormData();
+			formData.append('logUserid', logUserid);
+
+			var req = getXmlHttpRequestObject();
+            if (req) {
+                req.onreadystatechange = function() {
+                    if (req.readyState == 4) { 
+                        if (req.status == 200) {  
+                        //   alert(req.responseText);
+						//   console.log(req.responseText);
+                        }            
+                } 
+            } 
+
+                req.open("POST", 'sub_delete_all_seat_details.php', true); 
+                req.send(formData); 
+            }
+		}
+
 		function changeLineName(){
 			let logUserid = document.getElementById(`logUserid`).value;