Create app.py

app.py

@@ -0,0 +1,215 @@
+import gradio as gr
+from datasets import load_dataset
+import re
+import numpy as np
+
+dataset = load_dataset("mohamedabdullah/Arabic-unique-words",  data_files="ar_vocab.txt")
+word_l = re.findall('[^a-zA-Z0-9\s\W]{2,25}', dataset['train']['text'][0])
+vocab = set(word_l)
+
+def delete_letter(word):
+    return  [word[:i]+word[i+1:] for i in range(len(word))]
+    
+def switch_letter(word):
+    switch_l = []
+
+    for i in range(len(word)-1):
+        w_l = re.findall('\w', word)
+        if i-1 < 0:
+            w_l[i:i+2] = w_l[i+1::-1]
+        else:
+            w_l[i:i+2] = w_l[i+1:i-1:-1]
+            
+        switch_l.append(''.join(w_l))
+    
+    return switch_l
+    
+def replace_letter(word):
+    letters = 'ابتةثجحخدذرزسشصضطظعغفقكلمنهويءآأؤإئ'
+    
+    replace_set = set()
+
+    for i in range(len(word)):
+        for l in letters:
+            new_word = word[:i]+l+word[i+1:]
+            if new_word == word:
+                continue
+            replace_set.add(new_word)
+
+    replace_l = sorted(list(replace_set))
+    
+    return replace_l
+    
+def insert_letter(word):
+    letters = 'ابتةثجحخدذرزسشصضطظعغفقكلمنهويءآأؤإئ'
+    insert_l = []
+
+    for i in range(len(word)+1):
+        for l in letters:
+            new_word = word[:i]+l+word[i:]
+            insert_l.append(new_word)
+    
+    return insert_l
+    
+def edit_one_letter(word, allow_switches = True):
+    edit_one_set = delete_letter(word)+insert_letter(word)+replace_letter(word)
+
+    if allow_switches:
+        edit_one_set += switch_letter(word)
+
+    return set(edit_one_set)
+    
+def edit_two_letters(word, allow_switches = True):
+    edit_two_set = []
+    edit_one_set = edit_one_letter(word)
+    
+    for edit in edit_one_set:
+        edit_two_set += edit_one_letter(edit)
+        
+    return set(edit_two_set) | set(edit_one_set)
+    
+def get_corrections(word, vocab):
+    suggestions = []
+    
+    correct_word_suggest = [word] if word in vocab else []
+    edit_one_letter_suggest = list(filter(lambda item: item in vocab, list(edit_one_letter(word))))
+    edit_two_letter_suggest = list(filter(lambda item: item in vocab, list(edit_two_letters(word))))
+    
+    suggestions = correct_word_suggest or edit_one_letter_suggest or edit_two_letter_suggest or ['لم يتم العثور علي إقتراحات مناسبة لهذه الكلمة']
+
+    return set(suggestions) 
+    
+def min_edit_distance(source, target, ins_cost = 1, del_cost = 1, rep_cost = 2):
+    m = len(source) 
+    n = len(target) 
+    D = np.zeros((m+1, n+1), dtype=int) 
+  
+    for row in range(1, m+1):
+        D[row,0] =  D[row-1,0]+del_cost
+        
+    for col in range(1, n+1):
+        D[0,col] = D[0, col-1]+ins_cost
+        
+    for row in range(1, m+1):
+        for col in range(1, n+1):
+            r_cost = rep_cost
+
+            if source[row-1] == target[col-1]:
+                r_cost = 0
+                
+            D[row,col] = np.min([D[row-1,col]+del_cost, D[row,col-1]+ins_cost, D[row-1,col-1]+r_cost])
+
+    med = D[m,n]
+    
+    return med
+    
+def get_suggestions(corrections, word):
+  distance = []
+  suggest = []
+  
+  for correction in corrections:
+    source = word
+    target = correction
+    min_edits = min_edit_distance(source, target)
+
+    distance.append(min_edits)
+    suggest.append(correction)
+
+  suggest_result = list(map(lambda idx: suggest[idx], np.argsort(distance))) 
+  return suggest_result  
+  
+def ar_spelling_checker(text):
+  word_l = re.findall('\w{3,}', text)
+  result = {}
+
+  for word in word_l:
+    tmp_corrections = []
+    if not word in vocab:
+      tmp_corrections = get_corrections(word, vocab)
+      if len(tmp_corrections) == 0:
+        continue
+      result[word] = get_suggestions(tmp_corrections, word)
+
+  output = '''<style>
+    .content{
+      direction: rtl;
+    }
+    .word{
+            color: #842029;
+            background-color: #f8d7da;
+            border-color: #f5c2c7;
+            padding: 10px 20px;
+            display: inline-block;
+            direction: rtl;
+            font-size: 15px;
+            font-weight: 500;
+            margin-bottom: 15px;
+            box-sizing: border-box;
+            border: 1px solid transparent;
+            border-radius: 0.25rem;
+    }
+    .suggest{
+      color: #0f5132;
+      background-color: #d1e7dd;
+      border-color: #badbcc;
+      display: inline-block;
+      margin-right: 5px;
+    }
+    .separator{
+      height:3px;
+      background: #CCC;
+      margin-bottom: 15px;
+    }
+    .msg{
+      color: #0f5132;
+      background-color: #d1e7dd;
+      border-color: #badbcc;
+      border: 1px solid transparent;
+      border-radius: 0.25rem;
+      padding: 15px 20px;
+      direction: rtl;
+      font-size: 20px;
+      font-weight: 500;
+      text-align: center;
+    }
+    </style>'''
+
+  output += '<div class="content">' 
+
+  if len(result.keys()) == 0:
+    output += '<div class="msg">لا توجد أخطاء إملائية 🤗</div>'
+
+  for word in result.keys():
+    output += f'<div class="word">{word}</div><br />'
+    for suggest in result[word]:
+      output += f'<div class="word suggest">{suggest}</div>'
+
+    output += '<div class="separator"></div>'
+
+  output += '</div>' 
+  
+  return output
+  
+with gr.Blocks(css="""
+ #input{direction: rtl;}
+ #component-112{height: 30px;}
+ .gr-form{margin-top: 15px;}
+ .gr-text-input{font-size: 17px; height:50px; padding: 0.725rem;} 
+ .text-gray-500{font-size: 16px; margin-bottom: 13px;}
+ .gr-button{color: #084298; background-color: #cfe2ff; border-color: #b6d4fe;
+  border: 1px solid transparent; border-radius: 0.25rem; 
+  padding: 15px 20px; font-size: 20px; font-weight: 500; font-family: 'IBM Plex Mono';}
+  .output-html{min-height: 2rem;}          
+  .title{text-align: center;font-size: 25px;margin-top: 13px;position: absolute;width:100%;
+  line-height: 1.5;font-family: 'IBM Plex Mono';}
+  .desc{text-align: center; font-size: 17px; font-family: 'IBM Plex Mono'; margin-top: 46px;}""") as demo:
+
+    intro =  gr.HTML('<h1 class="title">Arabic Spelling Checker 🤗</h1>')
+    description = gr.HTML('<p class="desc">Web-based app to detect spelling mistakes in Arabic words using dynamic programming</p>')
+    text = gr.Textbox(label="النص", elem_id="input")
+    btn = gr.Button("Spelling Check")
+    output = gr.HTML()
+
+    btn.click(ar_spelling_checker, [text], output)
+
+demo.launch(inline=False)