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a77an commited on Apr 18

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f4b426e

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templates/app.py +107 -0
templates/index.html +200 -0

templates/app.py ADDED Viewed

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+import torch
+import pandas as pd
+import re
+from flask import Flask, render_template, request, jsonify
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from sklearn.metrics import classification_report
+import io
+import sys
+# Define model names
+bert_model_name = "bert-base-uncased"
+hatebert_model_name = "GroNLP/hateBERT"
+# Initialize Flask app
+app = Flask(__name__)
+class CyberbullyingDetector:
+    def __init__(self, model_type="bert"):
+        if model_type == "bert":
+            self.tokenizer = AutoTokenizer.from_pretrained(bert_model_name)
+            self.model = AutoModelForSequenceClassification.from_pretrained(bert_model_name)
+        elif model_type == "hatebert":
+            self.tokenizer = AutoTokenizer.from_pretrained(hatebert_model_name)
+            self.model = AutoModelForSequenceClassification.from_pretrained(hatebert_model_name)
+        else:
+            raise ValueError("Invalid model_type. Choose 'bert' or 'hatebert'.")
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        self.model.to(self.device)
+        self.cyberbullying_threshold = 0.7
+        self.borderline_threshold = 0.4
+        self.trigger_words = [
+            'buang', 'pokpok', 'bogo', 'linte', 'tanga', 'diputa', 'salamat', 'Padayon lang', 'mayo gid', 'Nagapasalamat',
+            'gago', 'law-ay', 'bilatibay', 'yudipota', 'pangit', 'tikalon', 'tinikal', 'hambog',
+            'batinggilan', 'biga-on', 'bulay-ug', 'agi', 'agitot', 'alpot', 'hangag'
+        ]
+    def find_triggers(self, text):
+        text_lower = text.lower()
+        return [word for word in self.trigger_words if word in text_lower]
+    def predict(self, text):
+        triggers = self.find_triggers(text)
+        inputs = self.tokenizer(
+            text,
+            return_tensors="pt",
+            truncation=True,
+            max_length=128,
+            padding=True
+        ).to(self.device)
+        with torch.no_grad():
+            outputs = self.model(**inputs)
+        probs = torch.nn.functional.softmax(outputs.logits, dim=1)
+        pred_class = torch.argmax(probs).item()
+        confidence = probs[0][pred_class].item()
+        if confidence >= self.cyberbullying_threshold or (pred_class == 1) or (len(triggers) > 0):
+            label = "Cyberbullying"
+            is_cyberbullying = True
+        elif confidence >= self.borderline_threshold:
+            label = "Borderline"
+            is_cyberbullying = False
+        else:
+            label = "Safe"
+            is_cyberbullying = False
+        return {
+            "text": text,
+            "label": label,
+            "confidence": confidence,
+            "language": "hil",
+            "triggers": triggers,
+            "is_cyberbullying": is_cyberbullying
+        }
+# Initialize the detector
+detector = CyberbullyingDetector(model_type="bert")
+@app.route('/')
+def index():
+    return render_template('index.html', classification_report="Loading...")
+@app.route('/predict', methods=['POST'])
+def predict():
+    data = request.get_json()
+    text = data.get('text', '')
+    if not text:
+        return jsonify({"error": "No text provided"}), 400
+    # Make prediction using the model
+    result = detector.predict(text)
+    # Generate the classification report
+    true_labels = ["Cyberbullying" if "cyberbullying" in text else "Safe" for text in [text]]
+    predicted_labels = [result['label']]
+    report = classification_report(true_labels, predicted_labels, zero_division=0)
+    # Render the template with the classification report
+    return render_template('index.html', classification_report=report)
+if __name__ == '__main__':
+    app.run(debug=True)

templates/index.html ADDED Viewed

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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>Cyberbullying Detection</title>
+  <style>
+    * {
+      box-sizing: border-box;
+    }
+    body {
+      margin: 0;
+      font-family: Arial, sans-serif;
+      background-color: black;
+      color: white;
+      display: flex;
+      flex-direction: column;
+      min-height: 100vh;
+    }
+    header {
+      background-color: #000;
+      color: red;
+      padding: 15px 20px;
+      font-size: 24px;
+      text-align: center;
+    }
+    main {
+      flex: 1;
+      display: flex;
+      justify-content: center;
+      align-items: center;
+      padding: 20px;
+    }
+    .container {
+      width: 100%;
+      max-width: 700px;
+      background-color: #1e1e1e;
+      padding: 30px;
+      border-radius: 8px;
+      box-shadow: 0 4px 8px rgba(255, 255, 255, 0.1);
+    }
+    h1 {
+      text-align: center;
+      margin-top: 0;
+      color: #fff;
+    }
+    textarea {
+      width: 100%;
+      height: 150px;
+      padding: 10px;
+      margin: 10px 0;
+      border-radius: 5px;
+      border: 1px solid #ccc;
+      font-family: Arial, sans-serif;
+      resize: vertical;
+    }
+    .button-group {
+      display: flex;
+      justify-content: space-between;
+      gap: 10px;
+    }
+    button {
+      padding: 10px 20px;
+      font-size: 16px;
+      background-color: #4CAF50;
+      color: white;
+      border: none;
+      border-radius: 5px;
+      cursor: pointer;
+      width: 48%;
+    }
+    #clearBtn {
+      background-color: #f44336;
+    }
+    button:hover {
+      opacity: 0.9;
+    }
+    #result {
+      margin-top: 20px;
+      display: none;
+    }
+    #error {
+      color: #f44336;
+      margin-top: 10px;
+    }
+    footer {
+      background-color: #000;
+      color: red;
+      text-align: center;
+      padding: 10px 0;
+    }
+  </style>
+</head>
+<body>
+  <header>
+    Paculan & Coloso
+  </header>
+  <main>
+    <div class="container">
+      <h1>Cyberbullying Detection</h1>
+      <form id="predictionForm" method="post">
+        <textarea id="inputText" placeholder="Enter text here..."></textarea>
+        <div class="button-group">
+          <button type="submit">Get Prediction</button>
+          <button type="button" id="clearBtn">Clear</button>
+        </div>
+      </form>
+      <!-- Error message section -->
+      <div id="error"></div>
+      <!-- Prediction result section -->
+      <div id="result">
+        <h3>Prediction Result:</h3>
+        <p id="prediction"></p>
+        <p id="confidence"></p>
+        <p id="triggers"></p>
+      </div>
+    </div>
+  </main>
+  <footer>
+    &copy; 2025 Paculan & Coloso Research Worx.
+  </footer>
+  <script>
+    const form = document.getElementById('predictionForm');
+    const inputText = document.getElementById('inputText');
+    const predictionEl = document.getElementById('prediction');
+    const confidenceEl = document.getElementById('confidence');
+    const triggersEl = document.getElementById('triggers');
+    const resultBox = document.getElementById('result');
+    const errorBox = document.getElementById('error');
+    // Handle form submission
+    form.addEventListener('submit', function(e) {
+      e.preventDefault();
+      const text = inputText.value.trim();
+      if (!text) {
+        errorBox.textContent = "Please enter text before submitting.";
+        resultBox.style.display = "none";
+        return;
+      }
+      // Clear previous error messages
+      errorBox.textContent = "";
+      // Fetch prediction from Flask backend
+      fetch('http://127.0.0.1:5000/predict', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ text: text })
+      })
+      .then(response => {
+        if (!response.ok) throw new Error("Server error");
+        return response.json();
+      })
+      .then(data => {
+        // Update the result section
+        predictionEl.textContent = "Label: " + data.label;
+        confidenceEl.textContent = "Confidence: " + data.confidence;
+        triggersEl.textContent = "Detected Triggers: " + (data.triggers.length ? data.triggers.join(', ') : "None");
+        resultBox.style.display = "block";
+      })
+      .catch(error => {
+        errorBox.textContent = "Something went wrong. Please try again.";
+        console.error(error);
+        resultBox.style.display = "none";
+      });
+    });
+    // Handle clearing the form
+    document.getElementById('clearBtn').addEventListener('click', function () {
+      inputText.value = '';
+      predictionEl.textContent = '';
+      confidenceEl.textContent = '';
+      triggersEl.textContent = '';
+      resultBox.style.display = 'none';
+      errorBox.textContent = '';
+    });
+  </script>
+</body>
+</html>