model commit

.idea/.gitignore

+# Default ignored files
+/shelf/
+/workspace.xml

.idea/AI Chatbot.iml

+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.11 (Child Flask App)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>
\ No newline at end of file

.idea/inspectionProfiles/Project_Default.xml

+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="1">
+            <item index="0" class="java.lang.String" itemvalue="Keras" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+    <inspection_tool class="PyPep8NamingInspection" enabled="true" level="WEAK WARNING" enabled_by_default="true">
+      <option name="ignoredErrors">
+        <list>
+          <option value="N806" />
+        </list>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>
\ No newline at end of file

.idea/inspectionProfiles/profiles_settings.xml

+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>
\ No newline at end of file

.idea/misc.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (Child Flask App)" project-jdk-type="Python SDK" />
+  <component name="PyCharmProfessionalAdvertiser">
+    <option name="shown" value="true" />
+  </component>
+</project>
\ No newline at end of file

.idea/modules.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/AI Chatbot.iml" filepath="$PROJECT_DIR$/.idea/AI Chatbot.iml" />
+    </modules>
+  </component>
+</project>
\ No newline at end of file

.idea/vcs.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$/.." vcs="Git" />
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>
\ No newline at end of file

app.py

+import webbrowser
+
+import nltk
+import requests
+
+nltk.download('popular')
+from nltk.stem import WordNetLemmatizer
+
+lemmatizer = WordNetLemmatizer()
+import pickle
+import numpy as np
+
+from keras.models import load_model
+import json
+import random
+
+model = load_model('model.h5')
+intents = json.loads(open('data.json').read())
+words = pickle.load(open('texts.pkl', 'rb'))
+classes = pickle.load(open('labels.pkl', 'rb'))
+
+
+def clean_up_sentence(sentence):
+    # tokenize the pattern - split words into array
+    sentence_words = nltk.word_tokenize(sentence)
+    # stem each word - create short form for word
+    sentence_words = [lemmatizer.lemmatize(word.lower()) for word in sentence_words]
+    return sentence_words
+
+
+# return bag of words array: 0 or 1 for each word in the bag that exists in the sentence
+
+def bow(sentence, words, show_details=True):
+    # tokenize the pattern
+    sentence_words = clean_up_sentence(sentence)
+    # bag of words - matrix of N words, vocabulary matrix
+    bag = [0] * len(words)
+    for s in sentence_words:
+        for i, w in enumerate(words):
+            if w == s:
+                # assign 1 if current word is in the vocabulary position
+                bag[i] = 1
+                if show_details:
+                    print("found in bag: %s" % w)
+    return (np.array(bag))
+
+
+def predict_class(sentence, model):
+    # filter out predictions below a threshold
+    p = bow(sentence, words, show_details=False)
+    res = model.predict(np.array([p]))[0]
+    ERROR_THRESHOLD = 0.25
+    results = [[i, r] for i, r in enumerate(res) if r > ERROR_THRESHOLD]
+    # sort by strength of probability
+    results.sort(key=lambda x: x[1], reverse=True)
+    return_list = []
+    for r in results:
+        return_list.append({"intent": classes[r[0]], "probability": str(r[1])})
+    return return_list
+
+
+def getResponse(ints, intents_json):
+    tag = ints[0]['intent']
+    list_of_intents = intents_json['intents']
+    for i in list_of_intents:
+        if (i['tag'] == tag):
+            result = random.choice(i['responses'])
+            break
+    return result
+
+
+def chatbot_response(msg):
+    ints = predict_class(msg, model)
+    res = getResponse(ints, intents)
+    return res
+
+
+from flask import Flask, render_template, request
+from flask import Flask, request, jsonify
+import joblib
+import pandas as pd
+
+app = Flask(__name__)
+app.static_folder = 'static'
+
+# Load the saved model
+loaded_model = joblib.load('rf_model_learning_style.pkl')
+
+
+@app.route("/")
+def home():
+    return render_template("index.html")
+
+@app.route("/learning_style")
+def learningStyle():
+    return render_template("learningStyle.html")
+
+@app.route("/teaching_style")
+def teachingStyle():
+    return render_template("teachingStyle.html")
+
+@app.route("/behavior")
+def behavior():
+    return render_template("behavior.html")
+
+
+@app.route("/get")
+def get_bot_response():
+    userText = request.args.get('msg')
+    return chatbot_response(userText)
+
+
+
+@app.route('/predict_learning_style', methods=['POST'])
+def predict_learning_style():
+    try:
+        # Get the input data from the POST request
+        data = request.json
+        input_list = data['input']
+
+        # Prepare the input data for prediction
+        input_df = pd.DataFrame([input_list])
+
+        # Make predictions using the loaded model
+        predictions = loaded_model.predict(input_df)
+
+        # Define a label mapping
+        label_mapping = {0: 'Auditory', 1: 'Kinesthetic', 2: 'Read/Write', 3: 'Read/Write', 4: 'Visual'}
+
+        # Map the predictions to labels
+        predicted_labels = [label_mapping[prediction] for prediction in predictions]
+
+        print(predicted_labels)
+
+        # Return the predicted labels as JSON response
+        return jsonify({'predicted_labels': predicted_labels})
+
+    except Exception as e:
+        return jsonify({'error': str(e)}), 400
+
+loaded_modelT = joblib.load('predicting_teaching_style.pkl')
+
+@app.route('/predict_teaching_style', methods=['POST'])
+def predict_teaching_style():
+    try:
+        # Get the input data from the POST request
+        data = request.json
+        input_list = data['input']
+
+        # Prepare the input data for prediction
+        input_df = pd.DataFrame([input_list])
+
+        # Make predictions using the loaded model
+        predictions = loaded_modelT.predict(input_df)
+
+        # Define a label mapping
+        label_mapping = {
+            0: 'HANDS ON EXPERIENCE',
+            1: 'INDIVIDUALIZED SUPPORT',
+            2: 'MULTISENSORY INSTRUCTION',
+            3: 'PLAY BASED LEARNING',
+            4: 'WHOLE GROUP AND SMALL GROUP INSTRUCTION'
+        }
+
+        # Map the predictions to labels
+        predicted_labels = [label_mapping[prediction] for prediction in predictions]
+
+        # Return the predicted labels as JSON response
+        return jsonify({'predicted_labels': predicted_labels})
+
+    except Exception as e:
+        return jsonify({'error': str(e)}), 400
+
+loaded_modelB = joblib.load('behaviour_prediction.pkl')
+
+@app.route('/predict_behavior', methods=['POST'])
+def predict_behavior():
+    try:
+        # Get the input data from the POST request
+        data = request.json
+        input_list = data['input']
+
+        # Prepare the input data for prediction
+        input_df = pd.DataFrame([input_list])
+
+        # Make predictions using the loaded model
+        predictions = loaded_modelB.predict(input_df)
+
+        # Define a label mapping
+        label_mapping = {
+            0: 'Aggressive',
+            1: 'Hyperactive',
+            2: 'Oppositional',
+            3: 'Tantrum',
+            4: 'Withdrawal'
+        }
+
+        # Map the predictions to labels
+        predicted_labels = [label_mapping[prediction] for prediction in predictions]
+
+        # Return the predicted labels as JSON response
+        return jsonify({'predicted_labels': predicted_labels})
+
+    except Exception as e:
+        return jsonify({'error': str(e)}), 400
+
+
+
+if __name__ == "__main__":
+    app.run()

data.json

+{"intents": [
+        {
+            "tag": "childBehavior",
+            "patterns": [
+                "How do I handle tantrums?",
+                "Dealing with a stubborn child",
+                "How to discipline a child?",
+                "Help with child's aggression",
+                "Managing child's hyperactivity",
+                "Teaching manners to a child"
+            ],
+            "responses": [
+                "Dealing with tantrums can be challenging. It's important to stay calm and offer comfort.",
+                "Stubbornness is common in children. Try offering choices to give them a sense of control.",
+                "Discipline should be consistent and focused on teaching rather than punishment.",
+                "Aggression in children might stem from frustration. Teach them healthy ways to express themselves.",
+                "Hyperactivity can be managed through regular physical activity and setting clear routines.",
+                "Teaching manners is an ongoing process. Lead by example and use positive reinforcement."
+            ],
+            "context_set": ""
+        },
+        {
+            "tag": "childDevelopment",
+            "patterns": [
+                "What are typical milestones for a toddler?",
+                "Child development stages",
+                "When do children start talking?",
+                "Signs of a learning disability in kids",
+                "Helping kids with social skills",
+                "Encouraging creativity in children"
+            ],
+            "responses": [
+                "Toddlers typically start walking around 12-15 months and saying words around 18-24 months.",
+                "Child development involves physical, cognitive, and emotional growth. Each child is unique.",
+                "Children usually start talking by the age of 2, but it varies. Encourage language through interaction.",
+                "Learning disabilities might show in difficulties with reading, writing, or math. Early intervention is key.",
+                "Social skills can be nurtured through playdates, group activities, and modeling positive interactions.",
+                "Encourage creativity by providing art supplies, allowing imaginative play, and praising their efforts."
+            ],
+            "context_set": ""
+        },
+        {
+          "tag": "confidence",
+          "patterns": [
+            "How confident are you in identifying and understanding different behavior patterns in nursery students?",
+            "How well do you think you can identify and understand different behavior patterns in nursery students?",
+            "What is your level of confidence in identifying and understanding different behavior patterns in nursery students?"
+          ],
+          "responses": [
+            "I am very confident in identifying and understanding different behavior patterns in nursery students.",
+            "I am moderately confident in identifying and understanding different behavior patterns in nursery students.",
+            "I am not very confident in identifying and understanding different behavior patterns in nursery students."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "importantBehaviors",
+          "patterns": [
+            "What are the most important behaviors to address in nursery students?",
+            "What behaviors do you think are the most important to address in nursery students?",
+            "What are some of the most important behaviors to address in nursery students?"
+          ],
+          "responses": [
+            "The most important behaviors to address in nursery students are aggression, tantrums, withdrawal, hyperactivity, and oppositional behavior.",
+            "Other important behaviors to address in nursery students include attention deficit, anxiety, and depression.",
+            "It is important to address all of these behaviors in a timely and effective manner to ensure the healthy development of nursery students."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "behaviorManagement",
+          "patterns": [
+            "What are some effective ways to manage behavior in nursery students?",
+            "How can I manage behavior in nursery students?",
+            "What are the best practices for managing behavior in nursery students?"
+          ],
+          "responses": [
+            "There are many effective ways to manage behavior in nursery students. Some of the most common methods include positive reinforcement, time-out, and redirection.",
+            "It is important to choose the right method for each individual student and to be consistent with the implementation of the method.",
+            "It is also important to be patient and understanding when managing behavior in nursery students. They are still learning how to control their emotions and behavior."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "parentalInvolvement",
+          "patterns": [
+            "How important is parental involvement in behavior management?",
+            "How can parents help to manage behavior in nursery students?",
+            "What can parents do to support behavior management in nursery students?"
+          ],
+          "responses": [
+            "Parental involvement is essential for effective behavior management. Parents can help to set clear expectations, provide positive reinforcement, and consistently implement discipline.",
+            "They can also teach their children coping skills and help them to develop self-control.",
+            "Parental involvement is one of the most important factors in the success of behavior management."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "activityAggression",
+          "patterns": [
+            "What are some activities that can help to reduce aggression in nursery students?",
+            "How can I help nursery students to express their aggression in a healthy way?",
+            "What are some games that can help to teach nursery students about conflict resolution?"
+          ],
+          "responses": [
+            "Some activities that can help to reduce aggression in nursery students include: \r\n * Building a tower together as a cooperative activity. \r\n * Playing games that involve turn-taking and sharing. \r\n * Teaching children how to express their emotions in a healthy way.\r\n * Providing children with opportunities to exercise and burn off energy. \r\n * Setting clear expectations and consequences for aggressive behavior. \r\n * Ignoring minor aggressive behaviors. \r\n * Providing positive reinforcement for prosocial behavior."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "activityTantrums",
+          "patterns": [
+            "What are some activities that can help to calm down nursery students during tantrums?",
+            "How can I help nursery students to learn how to manage their tantrums?",
+            "What are some things that I should avoid doing when a nursery student is having a tantrum?"
+          ],
+          "responses": [
+            "Some activities that can help to calm down nursery students during tantrums include: \r\n* Taking the child to a quiet place. \r\n * Talking to the child in a calm voice.\r\n * Offering the child a hug or other physical comfort.\r\n * Practicing deep breathing exercises or simple yoga poses.\r\n * Singing a calming song.\r\n * Reading a soothing story. \r\n * Setting clear expectations and consequences for tantrums.",
+            "It is important to help nursery students to learn how to manage their tantrums. Some ways to do this include: \r\n * Setting clear expectations and consequences for tantrums. \r\n * Ignoring minor tantrums. \r\n * Providing positive reinforcement for prosocial behavior. \r\n * Teaching children how to express their emotions in a healthy way. \r\n * Teaching children how to calm themselves down when they are feeling angry or upset.",
+            "There are some things that you should avoid doing when a nursery student is having a tantrum. These include: * Yelling at the child. \r\n* Ignoring the child.\r\n * Arguing with the child.\r\n * Trying to reason with the child."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "activityWithdrawal",
+          "patterns": [
+            "What are some activities that can help to encourage withdrawn children to engage with their peers?",
+            "How can I help nursery students who are withdrawn to make friends?",
+            "What are some games that can be helpful for withdrawn children?"
+          ],
+          "responses": [
+            "Some activities that can help to encourage withdrawn children to engage with their peers include: \r\n * Offering one-on-one activities with a trusted teacher or mentor.\r\n * Providing opportunities for children to work together on projects or activities.\r\n * Playing games that involve turn-taking and cooperation.\r\n * Encouraging children to join clubs or groups that interest them.\r\n * Praising children when they interact with their peers in a positive way.\r\n * Being patient and understanding, as it may take time for withdrawn children to warm up to others.",
+            "It is important to be patient and understanding when working with withdrawn children. It may take time for them to warm up to others and start to engage in social activities. It is also important to provide them with opportunities to interact with their peers in a safe and supportive environment."
+          ],
+          "context_set": ""
+        },
+        {
+            "tag": "activitySuggestion",
+            "patterns": [
+                "Please provide an activity that you find effective in addressing aggression in nursery students.",
+                "Please provide an activity that you find effective in helping children calm down during tantrums.",
+                "Please provide an activity that you find effective in encouraging withdrawn children to engage with their peers.",
+                "Please provide an activity that you find effective in managing hyperactive children and promoting their focus.",
+                "Please provide an activity that you find effective in addressing oppositional behavior and encouraging compliance with rules."
+            ],
+            "responses": ["Thank you for your input! Your suggested activity will be considered for promoting positive behavior in nursery students."],
+            "context_set": ""
+        },
+        {
+          "tag": "durationExperience",
+          "patterns": [
+            "How long have you been working with nursery students?",
+            "What is your level of experience with nursery students?",
+            "Can you share your background in working with young children?"
+          ],
+          "responses": [
+            "I have been working with nursery students for less than 1 year.",
+            "My experience with nursery students spans less than a year, but I'm continuously learning and growing in this field.",
+            "I'm relatively new to working with nursery students, and I'm enthusiastic about gaining more experience."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "activityEffective",
+          "patterns": [
+            "Which of the provided activities have you found to be the most effective?",
+            "Can you recommend an activity that has consistently yielded positive results?",
+            "What activity has shown the best outcomes in your experience?"
+          ],
+          "responses": [
+            "I have found the activity of introducing collaborative storytelling or group art projects to be particularly effective.",
+            "In my experience, activities like collaborative storytelling and group art projects have consistently shown positive outcomes with nursery students.",
+            "The activity of engaging nursery students in collaborative storytelling or group art projects has proven to be highly effective in promoting their creativity and social skills."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "activityRecommendation",
+          "patterns": [
+            "Can you recommend an activity to improve social skills in nursery students?",
+            "What are some activities that can help nursery students develop better social skills?",
+            "How can I encourage teamwork and social interaction among nursery students?"
+          ],
+          "responses": [
+            "Certainly! Introducing cooperative games or role-playing scenarios can help improve social skills in nursery students.",
+            "To enhance social skills in nursery students, consider activities like group storytelling or collaborative art projects, which encourage interaction and teamwork.",
+            "You can promote teamwork and social interaction among nursery students by organizing activities such as group puzzles, team-building games, or group art projects."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "challengingBehaviors",
+          "patterns": [
+            "What strategies would you suggest for addressing challenging behaviors in nursery students?",
+            "How can I handle aggressive behavior in nursery students?",
+            "What should I do when a nursery student exhibits defiant behavior?"
+          ],
+          "responses": [
+            "Addressing challenging behaviors requires patience and consistency. Using positive reinforcement, clear communication, and providing alternatives can be effective strategies.",
+            "When dealing with aggressive behavior in nursery students, it's important to remain calm, set clear boundaries, and teach them alternative ways to express their emotions.",
+            "In cases of defiant behavior, consider providing choices within limits, offering positive incentives for cooperation, and maintaining a predictable daily routine to help manage and reduce defiance."
+          ],
+          "context_set": ""
+        },
+        {
+          "tag": "parentCommunication",
+          "patterns": [
+            "How do you recommend communicating with parents about their child's behavior?",
+            "What are some effective ways to discuss behavioral concerns with parents?",
+            "Can you provide tips for maintaining a positive and constructive dialogue with parents regarding their child's behavior?"
+          ],
+          "responses": [
+            "Open and respectful communication is key when discussing a child's behavior with parents. Start by sharing your observations and concerns in a non-judgmental manner.",
+            "To maintain a positive dialogue with parents about their child's behavior, actively listen to their perspective, ask for their input, and collaborate on strategies for improvement.",
+            "It's important to involve parents in the process of addressing their child's behavior. Encourage them to share their insights and work together to develop effective solutions."
+          ],
+          "context_set": ""
+        }
+   ]
+}
\ No newline at end of file

requirements.txt

 absl-py==1.2.0

static/styles/style.css

+:root {
+  --body-bg: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+  --msger-bg: #fff;
+  --border: 2px solid #ddd;
+  --left-msg-bg: #ececec;
+  --right-msg-bg: #579ffb;
+}
+
+html {
+  box-sizing: border-box;
+}
+
+*,
+*:before,
+*:after {
+  margin: 0;
+  padding: 0;
+  box-sizing: inherit;
+}
+
+body {
+  display: flex;
+  justify-content: center;
+  align-items: center;
+  height: 100vh;
+  background-image: var(--body-bg);
+  font-family: Helvetica, sans-serif;
+}
+
+.msger {
+  display: flex;
+  flex-flow: column wrap;
+  justify-content: space-between;
+  width: 100%;
+  max-width: 867px;
+  margin: 25px 10px;
+  height: calc(100% - 50px);
+  border: var(--border);
+  border-radius: 5px;
+  background: var(--msger-bg);
+  box-shadow: 0 15px 15px -5px rgba(0, 0, 0, 0.2);
+}
+
+.msger-header {
+  /* display: flex; */
+  font-size: medium;
+  justify-content: space-between;
+  padding: 10px;
+  text-align: center;
+  border-bottom: var(--border);
+  background: #eee;
+  color: #666;
+}
+
+.msger-chat {
+  flex: 1;
+  overflow-y: auto;
+  padding: 10px;
+}
+.msger-chat::-webkit-scrollbar {
+  width: 6px;
+}
+.msger-chat::-webkit-scrollbar-track {
+  background: #ddd;
+}
+.msger-chat::-webkit-scrollbar-thumb {
+  background: #bdbdbd;
+}
+.msg {
+  display: flex;
+  align-items: flex-end;
+  margin-bottom: 10px;
+}
+
+.msg-img {
+  width: 50px;
+  height: 50px;
+  margin-right: 10px;
+  background: #ddd;
+  background-repeat: no-repeat;
+  background-position: center;
+  background-size: cover;
+  border-radius: 50%;
+}
+.msg-bubble {
+  max-width: 450px;
+  padding: 15px;
+  border-radius: 15px;
+  background: var(--left-msg-bg);
+}
+.msg-info {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  margin-bottom: 10px;
+}
+.msg-info-name {
+  margin-right: 10px;
+  font-weight: bold;
+}
+.msg-info-time {
+  font-size: 0.85em;
+}
+
+.left-msg .msg-bubble {
+  border-bottom-left-radius: 0;
+}
+
+.right-msg {
+  flex-direction: row-reverse;
+}
+.right-msg .msg-bubble {
+  background: var(--right-msg-bg);
+  color: #fff;
+  border-bottom-right-radius: 0;
+}
+.right-msg .msg-img {
+  margin: 0 0 0 10px;
+}
+
+.msger-inputarea {
+  display: flex;
+  padding: 10px;
+  border-top: var(--border);
+  background: #eee;
+}
+.msger-inputarea * {
+  padding: 10px;
+  border: none;
+  border-radius: 3px;
+  font-size: 1em;
+}
+.msger-input {
+  flex: 1;
+  background: #ddd;
+}
+.msger-send-btn {
+  margin-left: 10px;
+  background-color: red;
+  color: #fff;
+  font-weight: bold;
+  cursor: pointer;
+  transition: background 0.23s;
+}
+.msger-send-btn:hover {
+  background: rgb(0, 180, 50);
+}
+
+.msger-chat {
+  background-color: #fcfcfe;
+ }
\ No newline at end of file

templates/behavior.html

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Behavior Prediction</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            margin: 0;
+            padding: 0;
+            background-color: #f4f4f4;
+        }
+
+        h1 {
+            text-align: center;
+            background-color: #a00028;
+            color: #fff;
+            padding: 20px;
+        }
+
+        form {
+            max-width: 500px;
+            margin: 0 auto;
+            padding: 20px;
+            background-color: #fff;
+            box-shadow: 0px 0px 10px rgba(0, 0, 0, 0.1);
+            border-radius: 5px;
+        }
+
+        label {
+            display: block;
+            margin-bottom: 5px;
+        }
+
+        input[type="number"],
+        select {
+            width: 95%;
+            padding: 10px;
+            margin-bottom: 10px;
+            border: 1px solid #ccc;
+            border-radius: 5px;
+        }
+
+        button[type="button"] {
+            background-color: #a00028;
+            color: #fff;
+            border: none;
+            padding: 10px 20px;
+            cursor: pointer;
+            border-radius: 5px;
+            margin-left: 40%;
+        }
+
+        #prediction-result {
+            margin-top: 20px;
+            text-align: center;
+        }
+
+        #predicted-labels {
+            font-size: 25px;
+        }
+
+        #activity-info {
+            background-color: #e0e0e0;
+            border: 1px solid #ccc;
+            border-radius: 5px;
+            padding: 10px;
+            font-size: 22px;
+            margin-top: 20px;
+            text-align: left;
+        }
+    </style>
+</head>
+<body>
+    <h1>Behavior Prediction</h1>
+    <form id="prediction-form">
+        <label for="input1">Gender:</label>
+        <select name="input1" id="input1">
+            <option value="0">Female</option>
+            <option value="1">Male</option>
+        </select><br>
+
+        <label for="input2">Colouring a Picture Assessment Score:</label>
+        <input type="number" name="input2" id="input2" step="0.01"><br>
+
+        <label for="input3">Colouring Picture while Playing a Song:</label>
+        <input type="number" name="input3" id="input3" step="0.01"><br>
+
+        <label for="input4">Request and Get the Response - Response Rate:</label>
+        <select name="input4" id="input4">
+            <option value="0">Accepted</option>
+            <option value="1">Denied</option>
+            <option value="2">Moderate</option>
+        </select><br>
+
+
+        <label for="input5">How Much Child Displays Positive Social Interaction - Withdrawal Rate:</label>
+        <select name="input5" id="input5">
+            <option value="0">Always</option>
+            <option value="1">Often</option>
+            <option value="2">Rarely</option>
+            <option value="3">Sometimes</option>
+        </select><br>
+
+
+        <label for="input6">Ability to Follow the Instruction - Oppositional Rate:</label>
+        <select name="input6" id="input6">
+            <option value="0">Average</option>
+            <option value="1">Excellent</option>
+            <option value="2">Good</option>
+            <option value="3">Poor</option>
+        </select><br>
+
+        <label for="input7">Child React to Change in the Classroom Routine - Adapt Rate:</label>
+        <select name="input7" id="input7">
+            <option value="0">Easily</option>
+            <option value="1">Eventually</option>
+            <option value="2">Struggle</option>
+        </select><br>
+
+
+        <label for="input8">Behavior of Children During Their Play Time - Aggressive Rate:</label>
+        <select name="input8" id="input8">
+            <option value="1">Mild</option>
+            <option value="2">Moderate</option>
+            <option value="3">Severe</option>
+        </select><br>
+
+
+        <button type="button" id="predict-button">Predict</button>
+    </form>
+
+    <div id="prediction-result">
+        <h2>Predicted Behavior:</h2>
+        <p id="predicted-labels"></p>
+        <p id="activity-info"></p> <!-- Information about suitable activities -->
+    </div>
+
+    <script>
+        // JavaScript code to handle the prediction
+        document.getElementById('predict-button').addEventListener('click', () => {
+            const inputData = {
+                input1: parseFloat(document.getElementById('input1').value),
+                input2: parseFloat(document.getElementById('input2').value) / 100,
+                input3: parseFloat(document.getElementById('input3').value) / 100,
+                input4: parseFloat(document.getElementById('input4').value),
+                input5: parseFloat(document.getElementById('input5').value),
+                input6: parseFloat(document.getElementById('input6').value),
+                input7: parseFloat(document.getElementById('input7').value),
+                input8: parseFloat(document.getElementById('input8').value),
+            };
+
+            // Send a POST request to your Flask API
+            fetch('/predict_behavior', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({ input: Object.values(inputData) }),
+            })
+            .then((response) => response.json())
+            .then((data) => {
+                const predictedLabels = data.predicted_labels;
+                const predictedLabelsElement = document.getElementById('predicted-labels');
+                predictedLabelsElement.textContent = predictedLabels.join(', ');
+
+                // Add suitable activity information based on predicted behavior
+                const activityInfoElement = document.getElementById('activity-info');
+                activityInfoElement.textContent = getActivityInfo(predictedLabels);
+            })
+            .catch((error) => console.error('Error:', error));
+        });
+
+        // Function to provide suitable activity information based on predicted behavior
+        function getActivityInfo(predictedLabels) {
+            // Define suitable activities based on behavior predictions
+            const behaviorActivities = {
+                    'Aggressive': 'Aggressive behavior may indicate that the child is struggling with self-control and emotional regulation. Engaging in activities that teach anger management, empathy, and conflict resolution can be beneficial. Examples include role-playing scenarios, deep breathing exercises, and mindfulness activities.',
+
+                    'Hyperactive': 'Hyperactive behavior suggests that the child has excess energy to burn. Physical activities that encourage movement and exercise can help channel this energy in a positive way. Consider activities like running, jumping, dancing, or participating in sports.',
+
+                    'Oppositional': 'Oppositional behavior may stem from a desire for independence and control. Activities that promote cooperation, problem-solving, and effective communication can be effective. Encourage group activities that require teamwork, negotiation, and compromise.',
+
+                    'Tantrum': 'Tantrums often indicate frustration or emotional distress. Calming and relaxation activities can help manage these emotions. Try activities like guided meditation, storytelling, or creating a calming sensory corner with soothing objects.',
+
+                    'Withdrawal': 'Withdrawal behavior suggests a reluctance to engage socially. Encourage social interaction activities to help the child build social skills and confidence. Activities like group games, art projects, or collaborative storytelling can be helpful.'
+                };
+
+            // Generate the activity information
+            let activityInfo = 'Suitable Activities: ';
+            predictedLabels.forEach((label, index) => {
+                if (index > 0) {
+                    activityInfo += ', ';
+                }
+                activityInfo += behaviorActivities[label];
+            });
+
+            return activityInfo;
+        }
+    </script>
+</body>
+</html>

templates/index.html

+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+  <meta charset="UTF-8">
+  <title>Chatbot</title>
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1.0">
+  <meta http-equiv="X-UA-Compatible" content="ie=edge">
+  <link rel="stylesheet" href="{{ url_for('static', filename='styles/style.css') }}">
+  <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
+</head>
+
+<body>
+  <!-- partial:index.partial.html -->
+  <section class="msger">
+    <header class="msger-header">
+      <div class="msger-header-title">
+        <i class="fas fa-bug"></i> Chatbot <i class="fas fa-bug"></i>
+      </div>
+    </header>
+
+    <main class="msger-chat">
+      <div class="msg left-msg">
+        <div class="msg-img"></div>
+
+        <div class="msg-bubble">
+          <div class="msg-info">
+            <div class="msg-info-name">Chatbot</div>
+            <div class="msg-info-time">12:45</div>
+          </div>
+
+          <div class="msg-text">
+            Hi, welcome to ChatBot! Go ahead and send me a message. 😄
+          </div>
+        </div>
+      </div>
+
+    </main>
+
+    <form class="msger-inputarea">
+      <input type="text" class="msger-input" id="textInput" placeholder="Enter your message...">
+      <button type="submit" class="msger-send-btn">Send</button>
+    </form>
+  </section>
+  <!-- partial -->
+  <script src='https://use.fontawesome.com/releases/v5.0.13/js/all.js'></script>
+  <script>
+
+    const msgerForm = get(".msger-inputarea");
+    const msgerInput = get(".msger-input");
+    const msgerChat = get(".msger-chat");
+
+
+    // Icons made by Freepik from www.flaticon.com
+    const BOT_IMG = "https://image.flaticon.com/icons/svg/327/327779.svg";
+    const PERSON_IMG = "https://image.flaticon.com/icons/svg/145/145867.svg";
+    const BOT_NAME = "    ChatBot";
+    const PERSON_NAME = "You";
+
+    msgerForm.addEventListener("submit", event => {
+      event.preventDefault();
+
+      const msgText = msgerInput.value;
+      if (!msgText) return;
+
+      appendMessage(PERSON_NAME, PERSON_IMG, "right", msgText);
+      msgerInput.value = "";
+      botResponse(msgText);
+    });
+
+    function appendMessage(name, img, side, text) {
+      //   Simple solution for small apps
+      const msgHTML = `
+<div class="msg ${side}-msg">
+  <div class="msg-img" style="background-image: url(${img})"></div>
+
+  <div class="msg-bubble">
+    <div class="msg-info">
+      <div class="msg-info-name">${name}</div>
+      <div class="msg-info-time">${formatDate(new Date())}</div>
+    </div>
+
+    <div class="msg-text">${text}</div>
+  </div>
+</div>
+`;
+
+      msgerChat.insertAdjacentHTML("beforeend", msgHTML);
+      msgerChat.scrollTop += 500;
+    }
+
+    function botResponse(rawText) {
+
+      // Bot Response
+      $.get("/get", { msg: rawText }).done(function (data) {
+        console.log(rawText);
+        console.log(data);
+        const msgText = data;
+        appendMessage(BOT_NAME, BOT_IMG, "left", msgText);
+
+      });
+
+    }
+
+
+    // Utils
+    function get(selector, root = document) {
+      return root.querySelector(selector);
+    }
+
+    function formatDate(date) {
+      const h = "0" + date.getHours();
+      const m = "0" + date.getMinutes();
+
+      return `${h.slice(-2)}:${m.slice(-2)}`;
+    }
+
+
+
+  </script>
+
+</body>
+
+</html>
\ No newline at end of file

templates/learningStyle.html

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Learning Style Prediction</title>
+    <style>
+        /* Add some basic styling */
+        body {
+            font-family: Arial, sans-serif;
+            margin: 0;
+            padding: 0;
+            background-color: #f4f4f4;
+        }
+
+        h1 {
+            text-align: center;
+            background-color: #a00028;
+            color: #fff;
+            padding: 20px;
+        }
+
+        form {
+            max-width: 500px;
+            margin: 0 auto;
+            padding: 20px;
+            background-color: #fff;
+            box-shadow: 0px 0px 10px rgba(0, 0, 0, 0.1);
+            border-radius: 5px;
+        }
+
+        label {
+            display: block;
+            margin-bottom: 5px;
+        }
+
+        input[type="number"],
+        select {
+            width: 95%;
+            padding: 10px;
+            margin-bottom: 10px;
+            border: 1px solid #ccc;
+            border-radius: 5px;
+        }
+
+        button[type="button"] {
+            background-color: #a00028;
+            color: #fff;
+            border: none;
+            padding: 10px 20px;
+            cursor: pointer;
+            border-radius: 5px;
+            margin-left: 40%;
+        }
+
+        #prediction-result {
+            margin-top: 20px;
+            margin-left: 37%;
+        }
+
+        ul {
+            list-style: none;
+            padding: 0;
+        }
+
+        li {
+            margin-bottom: 5px;
+        }
+    </style>
+</head>
+<body>
+    <h1>Learning Style Prediction</h1>
+    <form id="prediction-form">
+        <label for="feature1">Reading/Writing Assessment Score:</label>
+        <input type="number" name="feature1" id="feature1" step="0.01"><br>
+
+        <label for="feature2">Visual Based Assessment Score:</label>
+        <input type="number" name="feature2" id="feature2" step="0.01"><br>
+
+        <label for="feature3">Listening Assessment score:</label>
+        <input type="number" name="feature3" id="feature3" step="0.01"><br>
+
+        <label for="feature4">Kinesthetic Assessment Score:</label>
+        <input type="number" name="feature4" id="feature4" step="0.01"><br>
+
+        <label for="feature5">Read Likeness</label>
+        <select name="feature5" id="feature5">
+            <option value="0">High</option>
+            <option value="1">Moderate</option>
+            <option value="2">Low</option>
+        </select><br>
+
+        <label for="feature6">Thinking Time:</label>
+        <select name="feature6" id="feature6">
+            <option value="0">Fast</option>
+            <option value="1">Moderate</option>
+            <option value="2">Slow</option>
+        </select><br>
+
+        <label for="feature7">Speaking Rate:</label>
+        <select name="feature7" id="feature7">
+            <option value="0">Fast</option>
+            <option value="1">Medium</option>
+            <option value="2">Slow</option>
+        </select><br>
+
+        <label for="feature8">Activity Enjoyment:</label>
+        <select name="feature8" id="feature8">
+            <option value="0">Better</option>
+            <option value="2">No difference</option>
+            <option value="3">Worse</option>
+        </select><br>
+
+        <label for="feature9">Visual Distraction:</label>
+        <select name="feature9" id="feature9">
+            <option value="0">High</option>
+            <option value="1">Low</option>
+        </select><br>
+
+        <label for="feature10">Auditory Distraction</label>
+        <select name="feature9" id="feature10">
+            <option value="0">High</option>
+            <option value="1">Low</option>
+        </select><br>
+
+        <label for="feature11">Using Verbal Instructions:</label>
+        <select name="feature11" id="feature11">
+            <option value="1">No instructions</option>
+            <option value="2">Verbal Instructions</option>
+        </select><br>
+
+        <button type="button" id="predict-button">Predict</button>
+    </form>
+
+    <div id="prediction-result">
+        <h2>Predicted Learning Style:</h2>
+        <ul id="predicted-labels" style="font-size: 18px;"></ul>
+    </div>
+
+    <script>
+        // JavaScript code to handle the prediction
+        document.getElementById('predict-button').addEventListener('click', () => {
+            const inputData = {
+                feature1: parseFloat(document.getElementById('feature1').value) / 100,
+                feature2: parseFloat(document.getElementById('feature2').value) / 100,
+                feature3: parseFloat(document.getElementById('feature3').value) / 100,
+                feature4: parseFloat(document.getElementById('feature4').value) / 100,
+                feature5: parseFloat(document.getElementById('feature5').value),
+                feature6: parseFloat(document.getElementById('feature6').value),
+                feature7: parseFloat(document.getElementById('feature7').value),
+                feature8: parseFloat(document.getElementById('feature8').value),
+                feature9: parseFloat(document.getElementById('feature9').value),
+                feature10: parseFloat(document.getElementById('feature10').value),
+                feature11: parseFloat(document.getElementById('feature11').value),
+            };
+
+            // Send a POST request to your Flask API
+            fetch('/predict_learning_style', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({ input: Object.values(inputData) }),
+            })
+            .then((response) => response.json())
+            .then((data) => {
+                const predictedLabels = data.predicted_labels;
+                const predictedLabelsList = document.getElementById('predicted-labels');
+                predictedLabelsList.innerHTML = '';
+
+                predictedLabels.forEach((label) => {
+                    const listItem = document.createElement('li');
+                    listItem.textContent = label;
+                    predictedLabelsList.appendChild(listItem);
+                });
+            })
+            .catch((error) => console.error('Error:', error));
+        });
+    </script>
+</body>
+</html>

templates/teachingStyle.html

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Teaching Style Prediction</title>
+    <style>
+        /* Add some basic styling */
+        body {
+            font-family: Arial, sans-serif;
+            margin: 0;
+            padding: 0;
+            background-color: #f4f4f4;
+        }
+
+        h1 {
+            text-align: center;
+            background-color: #a00028;
+            color: #fff;
+            padding: 20px;
+        }
+
+        form {
+            max-width: 500px;
+            margin: 0 auto;
+            padding: 20px;
+            background-color: #fff;
+            box-shadow: 0px 0px 10px rgba(0, 0, 0, 0.1);
+            border-radius: 5px;
+        }
+
+        label {
+            display: block;
+            margin-bottom: 5px;
+        }
+
+        input[type="number"],
+        select {
+            width: 95%;
+            padding: 10px;
+            margin-bottom: 10px;
+            border: 1px solid #ccc;
+            border-radius: 5px;
+        }
+
+        button[type="button"] {
+            background-color: #a00028;
+            color: #fff;
+            border: none;
+            padding: 10px 20px;
+            cursor: pointer;
+            border-radius: 5px;
+            margin-left: 40%;
+        }
+
+        #prediction-result {
+            margin-top: 20px;
+            text-align: center;
+        }
+    </style>
+</head>
+<body>
+    <h1>Teaching Style Prediction</h1>
+    <form id="prediction-form">
+        <label for="input1">TEACHER'S AGE:</label>
+        <input type="number" name="input1" id="input1" step="0.01"><br>
+
+        <label for="input2">GENDER:</label>
+        <select name="input2" id="input2">
+            <option value="0">Female</option>
+            <option value="1">Male</option>
+        </select><br>
+
+        <label for="input3">TEACHING EXPERIENCE:</label>
+        <input type="number" name="input3" id="input3" step="0.01"><br>
+
+        <label for="input4">CHOICE OF TEACHING MATERIALS:</label>
+        <select name="input4" id="input4">
+            <option value="0">ART SUPPLIES</option>
+            <option value="1">GAMES</option>
+            <option value="2">MUSIC AND MOVEMENT PROPS</option>
+            <option value="3">VISUAL AIDS</option>
+            <option value="4">WORK BOOKS</option>
+        </select><br>
+
+        <label for="input5">POSITIVE LEARNING ENVIRONMENT:</label>
+        <select name="input5" id="input5">
+            <option value="0">Average</option>
+            <option value="1">No</option>
+            <option value="2">Yes</option>
+        </select><br>
+
+        <label for="input6">Does the teacher prefer individual or group-based teaching:</label>
+        <select name="input6" id="input6">
+            <option value="0">GROUP</option>
+            <option value="1">INDIVIDUAL</option>
+        </select><br>
+
+        <label for="input7">Does the teacher prefer when questions are raised by children:</label>
+        <select name="input7" id="input7">
+            <option value="0">No</option>
+            <option value="1">Yes</option>
+        </select><br>
+
+        <button type="button" id="predict-button">Predict</button>
+    </form>
+
+    <div id="prediction-result">
+        <h2>Predicted Teaching Style:</h2>
+        <ul id="predicted-labels" style="font-size: 18px;"></ul>
+    </div>
+
+    <script>
+        // JavaScript code to handle the prediction
+        document.getElementById('predict-button').addEventListener('click', () => {
+            const inputData = {
+                input1: parseFloat(document.getElementById('input1').value),
+                input2: parseFloat(document.getElementById('input2').value),
+                input3: parseFloat(document.getElementById('input3').value),
+                input4: parseFloat(document.getElementById('input4').value),
+                input5: parseFloat(document.getElementById('input5').value),
+                input6: parseFloat(document.getElementById('input6').value),
+                input7: parseFloat(document.getElementById('input7').value),
+            };
+
+            // Send a POST request to your Flask API
+            fetch('/predict_teaching_style', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({ input: Object.values(inputData) }),
+            })
+            .then((response) => response.json())
+            .then((data) => {
+                const predictedLabels = data.predicted_labels;
+                const predictedLabelsElement = document.getElementById('predicted-labels');
+                predictedLabelsElement.textContent = predictedLabels.join(', ');
+            })
+            .catch((error) => console.error('Error:', error));
+        });
+    </script>
+</body>
+</html>

training.py

+import nltk
+from nltk.stem import WordNetLemmatizer
+import json
+import pickle
+import numpy as np
+from keras.models import Sequential
+from keras.layers import Dense, Activation, Dropout
+from keras.optimizers import SGD
+import random
+
+
+lemmatizer = WordNetLemmatizer()
+words = []
+classes = []
+documents = []
+ignore_words = ['?', '!']
+data_file = open('data.json').read()
+intents = json.loads(data_file)
+
+for intent in intents['intents']:
+    for pattern in intent['patterns']:
+
+        # tokenize each word
+        w = nltk.word_tokenize(pattern)
+        words.extend(w)
+        # add documents in the corpus
+        documents.append((w, intent['tag']))
+
+        # add to our classes list
+        if intent['tag'] not in classes:
+            classes.append(intent['tag'])
+
+# lemmaztize and lower each word and remove duplicates
+words = [lemmatizer.lemmatize(w.lower()) for w in words if w not in ignore_words]
+words = sorted(list(set(words)))
+# sort classes
+classes = sorted(list(set(classes)))
+# documents = combination between patterns and intents
+print(len(documents), "documents")
+# classes = intents
+print(len(classes), "classes", classes)
+# words = all words, vocabulary
+print(len(words), "unique lemmatized words", words)
+
+pickle.dump(words, open('texts.pkl', 'wb'))
+pickle.dump(classes, open('labels.pkl', 'wb'))
+
+# create our training data
+training = []
+# create an empty array for our output
+output_empty = [0] * len(classes)
+# training set, bag of words for each sentence
+for doc in documents:
+    # initialize our bag of words
+    bag = []
+    # list of tokenized words for the pattern
+    pattern_words = doc[0]
+    # lemmatize each word - create base word, in attempt to represent related words
+    pattern_words = [lemmatizer.lemmatize(word.lower()) for word in pattern_words]
+    # create our bag of words array with 1, if word match found in current pattern
+    for w in words:
+        bag.append(1) if w in pattern_words else bag.append(0)
+
+    # output is a '0' for each tag and '1' for current tag (for each pattern)
+    output_row = list(output_empty)
+    output_row[classes.index(doc[1])] = 1
+
+    training.append([bag, output_row])
+# shuffle our features and turn into np.array
+random.shuffle(training)
+training = np.array(training)
+# create train and test lists. X - patterns, Y - intents
+train_x = list(training[:, 0])
+train_y = list(training[:, 1])
+print("Training data created")
+
+# Create model - 3 layers. First layer 128 neurons, second layer 64 neurons and 3rd output layer contains number of neurons
+# equal to number of intents to predict output intent with softmax
+model = Sequential()
+model.add(Dense(128, input_shape=(len(train_x[0]),), activation='relu'))
+model.add(Dropout(0.5))
+model.add(Dense(64, activation='relu'))
+model.add(Dropout(0.5))
+model.add(Dense(len(train_y[0]), activation='softmax'))
+
+# Compile model. Stochastic gradient descent with Nesterov accelerated gradient gives good results for this model
+sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
+model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy'])
+
+# fitting and saving the model
+hist = model.fit(np.array(train_x), np.array(train_y), epochs=200, batch_size=5, verbose=1)
+model.save('model.h5', hist)
+
+print("model created")
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