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+web: gunicorn app:app

app.py

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+from flask import Flask, request, render_template, redirect, url_for
+from transformers import AutoTokenizer, AutoModel
+import torch
+import os
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+app = Flask(__name__)
+
+# Dictionary to store programs and their courses
+programs = {}
+
+# Default model name
+current_model_name = 'sentence-transformers/all-mpnet-base-v2'
+
+# Function to load the tokenizer and model dynamically
+def load_model_and_tokenizer(model_name):
+    try:
+        tokenizer = AutoTokenizer.from_pretrained(model_name)
+        model = AutoModel.from_pretrained(model_name)
+        return tokenizer, model, None
+    except Exception as e:
+        return None, None, str(e)
+
+# Load the initial model and tokenizer
+tokenizer, model, error = load_model_and_tokenizer(current_model_name)
+
+def mean_pooling(token_embeddings, mask):
+    """Applies mean pooling to token embeddings, considering the mask."""
+    mask = mask.unsqueeze(-1).expand(token_embeddings.size())
+    sum_embeddings = torch.sum(token_embeddings * mask, dim=1)
+    sum_mask = torch.clamp(mask.sum(dim=1), min=1e-9)  # Avoid division by zero
+    return sum_embeddings / sum_mask
+
+def compute_plo_embeddings():
+    """Computes embeddings for the predefined PLOs."""
+    tokens = tokenizer(plos, padding=True, truncation=True, return_tensors='pt')
+    mask = tokens['attention_mask']
+    with torch.no_grad():
+        outputs = model(**tokens)
+        return mean_pooling(outputs.last_hidden_state, mask)
+
+# Predefined Program Learning Outcomes (PLOs)
+plos = [
+    "Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions.",
+    "Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements.",
+    "Communicate effectively in a variety of professional contexts.",
+    "Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.",
+    "Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.",
+    "Support the delivery, use, and management of information systems within an information systems environment."
+]
+
+# Compute PLO embeddings (once at startup)
+plo_embeddings = compute_plo_embeddings()
+
+def get_similarity(input_sentence):
+    """Calculates the similarity between an input sentence and predefined PLOs."""
+    tokens = tokenizer(input_sentence, padding=True, truncation=True, return_tensors='pt')
+    mask = tokens['attention_mask']
+
+    with torch.no_grad():
+        outputs = model(**tokens)
+        input_embedding = mean_pooling(outputs.last_hidden_state, mask)
+
+    similarities = torch.nn.functional.cosine_similarity(input_embedding, plo_embeddings)
+    return similarities
+
+@app.route('/')
+def index():
+    """Home page displaying current programs and model status."""
+    return render_template('index.html', programs=programs, model_name=current_model_name)
+
+@app.route('/set_model', methods=['POST'])
+def set_model():
+    """Allows users to dynamically change the model."""
+    global tokenizer, model, plo_embeddings, current_model_name
+
+    model_name = request.form['model_name']
+    tokenizer, model, error = load_model_and_tokenizer(model_name)
+
+    if error:
+        return render_template('index.html', programs=programs, message=f"Error loading model: {error}")
+
+    # Update the global model name and recompute embeddings
+    current_model_name = model_name
+    plo_embeddings = compute_plo_embeddings()
+    return redirect(url_for('index'))
+
+@app.route('/addprogram', methods=['GET', 'POST'])
+def add_program():
+    """Adds a new program."""
+    if request.method == 'POST':
+        program_name = request.form['program_name']
+        if program_name not in programs:
+            programs[program_name] = {}  # Initialize an empty dictionary for courses
+        return redirect(url_for('index'))
+    return render_template('addprogram.html')
+
+@app.route('/addcourse', methods=['GET', 'POST'])
+def create_course():
+    """Creates a new course under a specific program."""
+    if request.method == 'POST':
+        program_name = request.form['program']
+        course_name = request.form['course_name']
+        outcomes = request.form['course_outcomes'].split('\n')
+
+        if program_name in programs:
+            programs[program_name][course_name] = outcomes  # Add course to the selected program
+
+        return redirect(url_for('index'))
+    return render_template('addcourse.html', programs=programs)
+
+@app.route('/match', methods=['POST'])
+def match_outcomes():
+    """Matches course outcomes with predefined PLOs."""
+    course_name = request.form['course']
+    print(course_name)
+    course_outcomes = request.form['course_outcomes'].split('\n')
+    results = []
+
+    for co in course_outcomes:
+        co = co.strip()
+        if co:  # Ensure the outcome is not empty
+            similarities = get_similarity(co)
+            top_matches_indices = similarities.topk(3).indices.tolist()
+            results.append({
+                'course_outcome': co,
+                'course_name' : course_name,
+                'best_matches': top_matches_indices
+            })
+
+    return render_template('result.html', course_name =course_name,  results=results)
+
+if __name__ == '__main__':
+     app.run(debug=True)

requirements.txt

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+Flask
+transformers
+torch
+Gunicorn
+pandas
+openpyxl

templates/addcourse.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <title>Add Course</title>
+</head>
+<body>
+    <h1>Add a New Course</h1>
+    <form action="/addcourse" method="post">
+        <label for="program">Select Program:</label><br>
+        <select id="program" name="program" required>
+            <option value="">--Select a program--</option>
+            {% for program in programs %}
+                <option value="{{ program }}">{{ program }}</option>
+            {% endfor %}
+        </select><br><br>
+
+        <label for="course_name">Course Name:</label><br>
+        <input type="text" id="course_name" name="course_name" required><br><br>
+
+        <label for="course_outcomes">Course Learning Outcomes (one per line):</label><br>
+        <textarea id="course_outcomes" name="course_outcomes" rows="5" cols="50" required></textarea><br><br>
+
+        <input type="submit" value="Add Course">
+    </form>
+    <br>
+    <a href="/">Back to Home</a>
+</body>
+</html>

templates/addprogram.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Add Program</title>
+</head>
+<body>
+    <h1>Add a New Program</h1>
+    <form action="/addprogram" method="post">
+        <label for="program_name">Program Name:</label><br>
+        <input type="text" id="program_name" name="program_name" required><br><br>
+        <input type="submit" value="Add Program">
+    </form>
+    <br>
+    <a href="/">Back to Home</a>
+</body>
+</html>

templates/index.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <meta http-equiv="X-UA-Compatible" content="ie=edge">
+    <title>Fibrosis</title>
+	<link rel="shortcut icon"
+        href="" />
+	<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
+	<style>
+		body{background-color: #eff2f9;}
+		.iupload h3{color: #1b2d6b;font-size: 30px;font-weight: 700;}
+		.img-part{height:300px;width:300px;margin:0px auto;}
+		.image-part{height:300px;width:300px;border:1px solid #1b2d6b;}
+		.image-part img{position:absolute;height: 300px;width:300px;display:none;padding:5px;}
+		.image-part #video{display:block;height: 300px;width:300px;padding:5px;}
+		.res-part{border:1px solid #dedede;margin-left:20px;height: 310px;width:100%;padding:5px;margin:0px auto;overflow:auto;}
+		.res-part2{border:1px solid #dedede;height: 310px;width:100%;padding:5px;margin:0px auto;}
+		.resp-img{height: 298px;width: 233px;margin:0px auto;}
+		.jsonRes{margin-left:30px;}
+		#send{cursor:pointer;}
+		.btn-part{width:325px;}
+		textarea,
+		select,
+		.form-control,
+		.custom-select,
+		button.btn,
+		.btn-primary,
+		input[type="text"],
+		input[type="url"],
+		.uneditable-input{
+			border: 1px solid #363e75;
+			outline: 0 !important;
+			border-radius:0px;
+			box-shadow: none;
+		   -webkit-box-shadow: none;
+		   -moz-box-shadow: none;
+		   -moz-transition: none;
+		   -webkit-transition: none;
+		}
+		textarea:focus,
+		select:focus,
+		.form-control:focus,
+		.btn:focus,
+		.btn-primary:focus,
+		.custom-select:focus,
+		input[type="text"]:focus,
+		.uneditable-input:focus{
+			border: 1px solid #007bff;
+			outline: 0 !important;
+			border-radius:0px;
+			box-shadow: none;
+		   -webkit-box-shadow: none;
+		   -moz-box-shadow: none;
+		   -moz-transition: none;
+		   -webkit-transition: none;
+		}
+		#loading {
+			position: fixed;
+			left: 0px;
+			top: 0px;
+			width: 100%;
+			height: 100%;
+			z-index: 9999999999;
+			overflow: hidden;
+			background: rgba(255, 255, 255, 0.7);
+		}
+		.loader {
+			border: 8px solid #f3f3f3;
+			border-top: 8px solid #363e75;
+			border-radius: 50%;
+			width: 60px;
+			height: 60px;
+			left: 50%;
+			margin-left: -4em;
+			display: block;
+			animation: spin 2s linear infinite;
+		}
+		.loader,
+		.loader:after {display: block;position: absolute;top: 50%;margin-top: -4.05em;}
+		@keyframes spin {
+			0% {
+				transform: rotate(0deg);
+			}
+			100% {
+				transform: rotate(360deg);
+			}
+		}
+		.right-part{border:1px solid #dedede;padding:5px;}
+		.logo{position:absolute;right:0px;bottom:0px;margin-right:30px;margin-bottom:30px;}
+	</style>
+	 <script>
+        let programs = {{ programs|tojson }};  // Passing programs from the backend as a JSON object
+
+        // Update the courses dropdown when a program is selected
+        function updateCourses() {
+            const programSelect = document.getElementById("program");
+            const courseSelect = document.getElementById("course");
+            const selectedProgram = programSelect.value;
+
+            // Clear existing options in the course dropdown
+            courseSelect.innerHTML = "<option value=''>--Select a course--</option>";
+            document.getElementById("course_outcomes").value = "";  // Clear the course outcomes
+
+            if (selectedProgram && programs[selectedProgram]) {
+                const courses = Object.keys(programs[selectedProgram]);
+                courses.forEach(course => {
+                    let option = document.createElement("option");
+                    option.value = course;
+                    option.text = course;
+                    courseSelect.appendChild(option);
+                });
+            }
+        }
+
+        // Update the course outcomes in the listbox when a course is selected
+        function updateCourseOutcomes() {
+            const programSelect = document.getElementById("program").value;
+            const courseSelect = document.getElementById("course").value;
+            const courseOutcomes = programs[programSelect] ? programs[programSelect][courseSelect] : [];
+
+            const courseOutcomesTextArea = document.getElementById("course_outcomes");
+            courseOutcomesTextArea.value = courseOutcomes ? courseOutcomes.join("\n") : "";
+        }
+    </script>
+</head>
+<body>
+    <div class="main container">
+		<section class="iupload">
+			<h3 class="text-center py-4">CLOs - PLOs Mapping Using Large Language Models  </h3>
+			<div class="row">
+				<div class="img-part col-md-6">
+				  <h1> </h1>
+
+    <!-- Section for Model Selection -->
+    <h5>Select Model</h5>
+    <form action="/set_model" method="post">
+        <label for="model_name">Choose a Model:</label><br>
+        <select id="model_name" name="model_name">
+            <option value="sentence-transformers/all-mpnet-base-v2" selected>all-mpnet-base-v2</option>
+            <option value="sentence-transformers/bert-base-nli-mean-tokens">bert-base-nli-mean-tokens</option>
+            <option value="thuan9889/llama_embedding_model_v1">llama_embedding_model_v1</option>
+            <option value="sembeddings/model_gpt_trained">model_gpt_trained</option>
+        </select>
+        <button type="submit">Set Model</button>
+    </form>
+
+    <h5>Current Model: {{ model_name }}</h5>
+    {% if message %}
+        <p style="color: red;">{{ message }}</p>
+    {% endif %}
+
+    <hr>
+
+    <!-- Section for Course Outcome Matching -->
+    <h5>Select Program and Course</h5>
+    <form action="/match" method="post">
+        <label for="program">Select Program:</label><br>
+        <select id="program" name="program" onChange="updateCourses()">
+            <option value="">--Select a program--</option>
+            {% for program in programs %}
+                <option value="{{ program }}">{{ program }}</option>
+            {% endfor %}
+        </select><br><br>
+
+        <label for="course">Select Course:</label><br>
+        <select id="course" name="course" onChange="updateCourseOutcomes()">
+            <option value="">--Select a course--</option>
+        </select><br><br>
+
+        <label for="course_outcomes">Course Outcomes:</label><br>
+        <textarea id="course_outcomes" name="course_outcomes" rows="10" cols="50" readonly></textarea><br><br>
+
+        <input type="submit" value="Submit">
+    </form>
+			  </div>
+				<div class="col-md-6 col-xs-12 right-part">
+					<h5 class="mb-2"><center>Create a Program or Course</center></h5>
+					<div class="row">
+
+						<div class="res-part col-md-5 col-xs-12"><div class="jsonRes"><h2></h2>
+    <ul>
+        <li><a href="/addprogram">Create Program</a></li>
+        <li><a href="/addcourse">Create Course</a></li>
+    </ul></div></div>
+					</div>
+				</div>
+			</div>
+		</section>
+	</div>
+
+	<img class="logo" src="" />
+
+
+    <div id="loading"></div>
+    <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js" integrity="sha384-ApNbgh9B+Y1QKtv3Rn7W3mgPxhU9K/ScQsAP7hUibX39j7fakFPskvXusvfa0b4Q" crossorigin="anonymous"></script>
+<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js" integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl" crossorigin="anonymous"></script>
+
+<script>
+var mybtn = document.getElementById('startbtn');
+var myvideo = document.getElementById('video');
+var mycanvas = document.getElementById('canvas');
+var myphoto = document.getElementById('photo');
+var base_data = "";
+
+function sendRequest(base64Data){
+	var type = "json";
+	if(base64Data != "" || base64Data != null){
+		if(type == "imgtobase"){
+			$(".res-part").html("");
+			$(".res-part").html(base64Data);
+		}
+		else if(type == "basetoimg"){
+			var imageData = $("#imgstring").val();
+			$(".res-part").html("");
+			$(".res-part").append("<img src='data:image/jpeg;base64," + imageData + "' alt='' />");
+		}
+		else{
+			var url = $("#url").val();
+			$("#loading").show();
+			$.ajax({
+				url : url,
+				type: "post",
+				cache: false,
+				async: true,
+				crossDomain: true,
+				headers: {
+					'Content-Type': 'application/json',
+					'Access-Control-Allow-Origin':'*'
+				},
+				data:JSON.stringify({image:base64Data}),
+				success: function(res){
+					$(".res-part").html("");
+					$(".res-part2").html("");
+					try{
+						var imageData = res[1].image;
+						if(imageData.length > 100){
+							if(imageData.length > 10){$(".res-part2").append("<img class='resp-img' src='data:image/jpeg;base64," + imageData + "' alt='' />");}
+						}
+					}catch(e){}
+					$(".res-part").html("<pre>" + JSON.stringify(res[0], undefined, 2) + "</pre>");
+					$("#loading").hide();
+				}
+			});
+		}
+	}
+}
+
+$(document).ready(function(){
+	$("#loading").hide();
+
+	$('#send').click(function(evt){
+		sendRequest(base_data);
+    });
+
+    $('#uload').click(function(evt) {
+        $('#fileinput').focus().trigger('click');
+    });
+	$("#fileinput").change(function(){
+		if (this.files && this.files[0]){
+			var reader = new FileReader();
+			reader.onload = function (e){
+				var url = e.target.result;
+				var img = new Image();
+				img.crossOrigin = 'Anonymous';
+				img.onload = function(){
+					var canvas = document.createElement('CANVAS');
+					var ctx = canvas.getContext('2d');
+					canvas.height = this.height;
+					canvas.width = this.width;
+					ctx.drawImage(this, 0, 0);
+					base_data = canvas.toDataURL('image/jpeg', 1.0).replace(/^data:image.+;base64,/, '');
+					canvas = null;
+				};
+				img.src = url;
+				$('#photo').attr('src', url);
+				$('#photo').show();
+				$('#video').hide();
+			}
+			reader.readAsDataURL(this.files[0]);
+		}
+	});
+});
+
+</script>
+</body>
+</html>

templates/result.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Predicted Mapping</title>
+    <style>
+        table, th, td {
+            border: 1px solid black;
+            border-collapse: collapse;
+            padding: 10px;
+            text-align: left;
+        }
+        .top-1 { background-color: red; }
+        .top-2 { background-color: blue; }
+        .top-3 { background-color: green; }
+    </style>
+</head>
+<body>
+    <h1>Predicted Mapping</h1>
+    <h2>Course: {{ course_name }}</h2>
+    <table>
+        <tr>
+            <th>Course Learning Outcome</th>
+            <th>PLO1</th>
+            <th>PLO2</th>
+            <th>PLO3</th>
+            <th>PLO4</th>
+            <th>PLO5</th>
+            <th>PLO6</th>
+        </tr>
+        {% for result in results %}
+        <tr>
+            <td>{{ result.course_outcome }}</td>
+            <td class="{% if 0 in result.best_matches[:1] %}top-1{% elif 0 in result.best_matches[1:2] %}top-2{% elif 0 in result.best_matches[2:3] %}top-3{% endif %}">{{ '√' if 0 in result.best_matches else '' }}</td>
+            <td class="{% if 1 in result.best_matches[:1] %}top-1{% elif 1 in result.best_matches[1:2] %}top-2{% elif 1 in result.best_matches[2:3] %}top-3{% endif %}">{{ '√' if 1 in result.best_matches else '' }}</td>
+            <td class="{% if 2 in result.best_matches[:1] %}top-1{% elif 2 in result.best_matches[1:2] %}top-2{% elif 2 in result.best_matches[2:3] %}top-3{% endif %}">{{ '√' if 2 in result.best_matches else '' }}</td>
+            <td class="{% if 3 in result.best_matches[:1] %}top-1{% elif 3 in result.best_matches[1:2] %}top-2{% elif 3 in result.best_matches[2:3] %}top-3{% endif %}">{{ '√' if 3 in result.best_matches else '' }}</td>
+            <td class="{% if 4 in result.best_matches[:1] %}top-1{% elif 4 in result.best_matches[1:2] %}top-2{% elif 4 in result.best_matches[2:3] %}top-3{% endif %}">{{ '√' if 4 in result.best_matches else '' }}</td>
+            <td class="{% if 5 in result.best_matches[:1] %}top-1{% elif 5 in result.best_matches[1:2] %}top-2{% elif 5 in result.best_matches[2:3] %}top-3{% endif %}">{{ '√' if 5 in result.best_matches else '' }}</td>
+        </tr>
+        {% endfor %}
+    </table>
+    <a href="/">Back to Input</a>
+</body>
+</html>