Update app.py

app.py

@@ -2,17 +2,8 @@ import streamlit as st
 import PyPDF2
 import io
 import os
-import re
-import nltk
-from nltk.corpus import words
 
-# Download the words corpus if not already downloaded
-nltk.download('words')
 
-# Create a set of English words for quick lookup
-english_words_set = set(words.words())
-
-# Your existing mappings
 unicodeatoz = ["ब", "द", "अ", "म", "भ", "ा", "न", "ज", "ष्", "व", "प", "ि", "फ", "ल", "य", "उ", "त्र", "च", "क", "त", "ग", "ख", "ध", "ह", "थ", "श"]
 unicodeAtoZ = ["ब्", "ध", "ऋ", "म्", "भ्", "ँ", "न्", "ज्", "क्ष्", "व्", "प्", "ी", "ः", "ल्", "इ", "ए", "त्त", "च्", "क्", "त्", "ग्", "ख्", "ध्", "ह्", "थ्", "श्"]
 unicode0to9 = ["ण्", "ज्ञ", "द्द", "घ", "द्ध", "छ", "ट", "ठ", "ड", "ढ"]
@@ -90,43 +81,22 @@ def normalizePreeti(preetitxt):
             previoussymbol = ''
     return normalized
 
-def is_english_word(word):
-    # Remove punctuation and convert to lowercase
-    word_clean = re.sub(r'\W+', '', word).lower()
-    return word_clean in english_words_set
-
 def convert(preeti):
     converted = ''
     normalizedpreeti = normalizePreeti(preeti)
-    
-    # Split the text into tokens (words and non-words)
-    tokens = re.findall(r'\w+|\W+', normalizedpreeti)
-    
-    for token in tokens:
-        if re.match(r'\w+', token):
-            # This is a word
-            if is_english_word(token):
-                # English word, skip conversion
-                converted += token
+    for index, character in enumerate(normalizedpreeti):
+        try:
+            if ord(character) >= 97 and ord(character) <= 122:
+                converted += unicodeatoz[ord(character) - 97]
+            elif ord(character) >= 65 and ord(character) <= 90:
+                converted += unicodeAtoZ[ord(character) - 65]
+            elif ord(character) >= 48 and ord(character) <= 57:
+                converted += unicode0to9[ord(character) - 48]
             else:
-                # Convert the word
-                converted_word = ''
-                for index, character in enumerate(token):
-                    try:
-                        if ord(character) >= 97 and ord(character) <= 122:
-                            converted_word += unicodeatoz[ord(character) - 97]
-                        elif ord(character) >= 65 and ord(character) <= 90:
-                            converted_word += unicodeAtoZ[ord(character) - 65]
-                        elif ord(character) >= 48 and ord(character) <= 57:
-                            converted_word += unicode0to9[ord(character) - 48]
-                        else:
-                            converted_word += symbolsDict[character]
-                    except KeyError:
-                        converted_word += character
-                converted += converted_word
-        else:
-            # Non-word token (punctuation, whitespace)
-            converted += token
+                converted += symbolsDict[character]
+        except KeyError:
+            converted += character
+
     return converted
 
 def extract_text_from_pdf(pdf_file):
@@ -179,4 +149,4 @@ def main():
         )
 
 if __name__ == "__main__":
-    main()
+    main()