fixed web page bugs

django-backend/mlApi/bert_darkp.py

@@ -1,4 +1,4 @@
-# Implementing TowardsDS's BERT model for dark pattern detection
+# Implementing TowardsDS's BERT model for dark pattern detection traning for mulit-class classification
 
 import torch
 from tqdm import tqdm
@@ -151,7 +151,7 @@ def accuracy_per_class(preds, labels):
 
 ## TraningLoop for BERT
 
-# for loading cpu model on gpu   
+# for loading model on gpu   
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 
@@ -163,6 +163,8 @@ def accuracy_per_class(preds, labels):
 torch.manual_seed(seed_val)
 torch.cuda.manual_seed_all(seed_val)
 
+# evaluating the model
+
 def evaluate(dataloader_val):
 
     model.eval()
@@ -230,6 +232,7 @@ def evaluate(dataloader_val):
         progress_bar.set_postfix({'training_loss': '{:.3f}'.format(loss.item()/len(batch))})
 
 
+    # saving the model after each epoch (name as per your choice)
     torch.save(model.state_dict(), f'fine_tuned_bert/finetuned_BERT_epoch_{epoch}.model')
 
     tqdm.write(f'\nEpoch {epoch}')

django-backend/mlApi/data_preprocess.py

@@ -36,37 +36,6 @@
 
 print(dark_pattern_counts3)
 
-# Alternatively, you can use df.isnull().sum()
-
-# Print or use the information about NaN values
-# print(nan_values)
-
-# print(uniqueVal1)
-# print(uniqueVal3)
-
-# new_df = df[['text', 'Pattern Category']]
-# new_df.to_csv('F:/backup-kali/codeFiles/projects/cognigaurd/api/datasets/new_dp_dataset.csv',sep="\t", index=False)
-
-
-# import pandas as pd
-
-# output_file_path = "F:/backup-kali/codeFiles/projects/cognigaurd/api/datasets/new_dp_dataset.csv"
-
-# # Read the TSV file
-# df = pd.read_csv(file_path2, sep='\t')
-
-# # Write the DataFrame to a CSV file
-# df.to_csv(output_file_path, index=False)
-
-# print("TSV file converted to CSV successfully!")
-
-# df3 = pd.read_csv(output_file_path)
-# dark_pattern_counts3 = df3['Category'].value_counts()
-# print(dark_pattern_counts3)
-
-
-##3 checking for incosistency in dataset
-
 
 import csv
 

django-backend/mlApi/models.py

@@ -2,7 +2,7 @@
 
 # Create your models here.
 
-
+# beta feature - saving the transparency score to the database
 class WebsiteTransparencyScore(models.Model):
     website_name = models.CharField(max_length=255, unique=True)
     transparency_score = models.FloatField()
@@ -12,7 +12,7 @@ class WebsiteTransparencyScore(models.Model):
     def __str__(self):
         return f"{self.website_name} - Transparency Score: {self.transparency_score}"
 
-
+# saving dark pattern data to the database
 class DarkPatternsData(models.Model):
 
     website_url = models.URLField()
@@ -23,6 +23,7 @@ def __str__(self):
         return f"{self.website_url} - Dark Pattern: {self.dark_pattern_label}"
 
 
+# saving each request to the database
 class DpRequest(models.Model):
 
 

django-backend/mlApi/predict_darkp.py

@@ -50,7 +50,7 @@ def find_dark_pattern(text_predict):
 
 
 
-# # text_to_predict = "Hello my name is adarsh and my friend name is aman , he is only on sale for the next two days. "
+# # text_to_predict = "Hello my name is adarsh and my friend name is aman  "
 # welcomeMsg = """******* Welcome to Dark Pattern Detector ********"""
 
 # text_to_predict = input("Enter the the text to find Dark Pattern : ")

django-backend/mlApi/scrapingTerms.py

@@ -1,3 +1,5 @@
+# This script scrapes the terms and conditions of the websites mentioned in the 'websites' list and saves the data to a CSV file.
+
 import requests
 from bs4 import BeautifulSoup
 import csv

django-backend/mlApi/views.py

@@ -105,13 +105,13 @@ class MessageListView(generics.ListAPIView):
 ## You need to ensure that it doesn't call the dpData function if the dpCond is False
 
     # Fetching urls from model
-    # dpUrls = DpRequest.objects.all()
-    # urlLen = len(dpUrls)
-    # myDpUrl = dpUrls[urlLen-1].url
-    # print(dpUrls)
-    # myOutput = dpData(myDpUrl)
-    # print(myOutput)
-    # dpCond = False
+    dpUrls = DpRequest.objects.all()
+    urlLen = len(dpUrls)
+    myDpUrl = dpUrls[urlLen-1].url
+    print(dpUrls)
+    myOutput = dpData(myDpUrl)
+    print(myOutput)
+    dpCond = False
 
 
 

django-backend/static/css/report.css

@@ -3,7 +3,7 @@
 }
 .content-section {
   gap: 3rem;
-  padding-left: 30rem;
+  /* padding-left: 30rem; */
 }
 .heading-section {
   display: flex;

django-backend/static/css/style.css

@@ -17,16 +17,7 @@
   --font-large: 3rem;
   --font-ex-large: 3.5rem;
 }
-@media (max-width: 768px) {
-  :root {
-    --font-ex-small: 0.25rem;
-    --font-small: 0.5rem;
-    --font-mid-medium: 1rem;
-    --font-medium: 1.25rem;
-    --font-mid-large: 1.75rem;
-    --font-large: 2rem;
-  }
-}
+
 a {
   text-decoration: none;
 }
@@ -110,22 +101,16 @@ a {
   align-items: center;
   gap: 5rem;
   margin: 4rem 0;
-  @media (max-width: 768px) {
-    margin: 5vh 0 !important;
-    flex-direction: column;
-    gap: 3rem;
-  }
+
 }
 .blue-text {
   color: var(--color-primary);
 }
 /* main section */
 .main-section {
   display: flex;
-  justify-content: center;
-  @media (max-width: 768px) {
-    flex-direction: column;
-  }
+  /* justify-content: center; */
+
   /* gap: 2rem;
   padding: 0 2.87rem; */
 }
@@ -136,10 +121,7 @@ a {
   align-items: center;
   margin: 6rem 2rem 2rem 4rem;
   gap: 8rem;
-  @media (max-width: 768px) {
-    margin: 10vh 10vw;
-    gap: 15vh;
-  }
+
 }
 /* navbar */
 .navbar {
@@ -158,45 +140,20 @@ a {
   background: white;
   gap: 2rem;
   height: 558px;
-  @media (max-width: 768px) {
-    flex-direction: row;
-    height: 100px;
-    padding: 0 5vw;
-    /* 
-    width: 100%;
-    position: fixed;
-    top: 0;
-    left: 0;
-    z-index: 100;
-    transform: translateX(-100%);
-    transition: 0.5s; */
-  }
+
 }
 .navbar__logo img {
   height: 5.75rem;
   width: 9.55rem;
-  @media (max-width: 768px) {
-    height: 5rem;
-    width: 8.5rem;
-  }
+
 }
 .navbar__links {
   display: flex;
   flex-direction: column;
   align-items: flex-start;
   gap: 2rem;
   width: 14rem;
-  @media (max-width: 768px) {
-    position: fixed;
-    z-index: 3;
-    background-color: white;
-    padding: 3vh 5vw;
-    border-radius: 10px;
-    right: -100vw;
-    top: 25vh;
-    border: 1px solid black;
-    transition: all 0.5s ease-in-out;
-  }
+
 }
 .show {
   transform: translateX(-100vw);
@@ -217,9 +174,7 @@ a {
 }
 .welcome-img {
   height: 40vh;
-  @media (max-width: 768px) {
-    height: 25vh;
-  }
+
 }
 .welcome-btns {
   display: flex;
@@ -246,9 +201,7 @@ a {
 }
 .cogni-about img {
   height: 50vh;
-  @media (max-width: 768px) {
-    height: 30vh;
-  }
+
 }
 /* footer */
 footer {
@@ -275,11 +228,7 @@ footer {
   color: white;
   justify-content: space-evenly;
   align-items: center;
-  @media (max-width: 768px) {
-    flex-direction: column;
-    align-items: flex-start;
-    gap: 10vh;
-  }
+
 }
 .footer-text a {
   color: white;
@@ -310,9 +259,7 @@ footer {
   width: 50%;
   flex-direction: column;
   gap: 1rem;
-  @media (max-width: 768px) {
-    width: auto;
-  }
+
 }
 .cogni-desc p {
   letter-spacing: 0.5px;
@@ -323,9 +270,7 @@ footer {
   display: flex;
   flex-direction: column;
   gap: 2rem;
-  @media (max-width: 768px) {
-    gap: 1.5rem;
-  }
+
 }
 .cogni-links div:first-child {
   display: flex;
@@ -390,9 +335,7 @@ footer {
   cursor: pointer;
   padding: 0;
   z-index: 10;
-  @media (max-width: 768px) {
-    display: flex;
-  }
+
 }
 
 .line {