preeti-unicode / app.py
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import streamlit as st
import io
import os
import pdfplumber
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"]
symbolsDict = {
"~": "ञ्", "`": "ञ", "!": "१", "@": "२", "#": "३", "$": "४", "%": "५", "^": "६", "&": "७", "*": "८",
"(": "९", ")": "०", "-": "(", "_": ")", "+": "ं", "[": "ृ", "{": "र्", "]": "े", "}": "ै", "\\": "्",
"|": "्र", ";": "स", ":": "स्", "'": "ु", "\"": "ू", ",": ",", "<": "?", ".": "।", ">": "श्र", "/": "र",
"?": "रु", "=": ".", "ˆ": "फ्", "Î": "ङ्ख", "å": "द्व", "÷": "/"
}
def normalizePreeti(preetitxt):
normalized = ''
previoussymbol = ''
preetitxt = preetitxt.replace('qm', 's|').replace('f]', 'ो').replace('km', 'फ').replace('0f', 'ण').replace('If', 'क्ष').replace('if', 'ष').replace('cf', 'आ')
index = -1
while index + 1 < len(preetitxt):
index += 1
character = preetitxt[index]
try:
if preetitxt[index + 2] == '{':
if preetitxt[index + 1] == 'f' or preetitxt[index + 1] == 'ो':
normalized += '{' + character + preetitxt[index + 1]
index += 2
continue
if preetitxt[index + 1] == '{':
if character != 'f':
normalized += '{' + character
index += 1
continue
except IndexError:
pass
if character == 'l':
previoussymbol = 'l'
continue
else:
normalized += character + previoussymbol
previoussymbol = ''
return normalized
def convert(preeti):
converted = ''
normalizedpreeti = normalizePreeti(preeti)
for character in normalizedpreeti:
try:
if 97 <= ord(character) <= 122:
converted += unicodeatoz[ord(character) - 97]
elif 65 <= ord(character) <= 90:
converted += unicodeAtoZ[ord(character) - 65]
elif 48 <= ord(character) <= 57:
converted += unicode0to9[ord(character) - 48]
else:
converted += symbolsDict[character]
except KeyError:
converted += character
return converted
def extract_text_from_pdf(pdf_file):
text = ''
with pdfplumber.open(pdf_file) as pdf:
for page in pdf.pages:
extracted_text = page.extract_text()
if extracted_text:
text += extracted_text
return handle_vertical_text(text)
def handle_vertical_text(text):
lines = text.split('\n')
vertical_lines = []
horizontal_line = ''
for line in lines:
if len(line) == 1: # Possible vertical arrangement (single character per line)
horizontal_line += line
else:
if horizontal_line: # If we've built a horizontal line, add it.
vertical_lines.append(horizontal_line)
horizontal_line = ''
vertical_lines.append(line) # Add the full line if it's not vertical.
if horizontal_line:
vertical_lines.append(horizontal_line)
return ' '.join(vertical_lines)
def main():
st.title("PDF/TXT to Unicode Converter (Nepali RAG)")
uploaded_file = st.file_uploader("Choose a PDF or TXT file", type=["pdf", "txt"])
if uploaded_file is not None:
file_extension = os.path.splitext(uploaded_file.name)[1].lower()
if file_extension == ".pdf":
text = extract_text_from_pdf(io.BytesIO(uploaded_file.read()))
else: # .txt file
text = uploaded_file.getvalue().decode("utf-8")
converted_text = convert(text)
st.subheader("Original Text")
st.text_area("", value=text, height=200)
st.subheader("Converted Text")
st.text_area("", value=converted_text, height=200)
# Create a download button for the converted text
st.download_button(
label="Download Converted Text",
data=converted_text.encode("utf-8"),
file_name="converted_text.txt",
mime="text/plain"
)
# Write footer
st.markdown("Made with ❤️ by Sumit Yadav(https://sumityadav.com.np)")
if __name__ == "__main__":
main()