import streamlit as st
import PyPDF2
import openai
from io import BytesIO
import io
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter, A4
from reportlab.pdfbase import pdfmetrics
from reportlab.pdfbase.ttfonts import TTFont
from weasyprint import HTML, CSS
from weasyprint.text.fonts import FontConfiguration
import arabic_reshaper
from bidi.algorithm import get_display
import os
import tempfile
# Get API key from Hugging Face secrets
api_key = os.environ.get('OPENAI_API_KEY')
def register_fonts():
"""Register fonts for different languages"""
try:
# Using Noto Nastaliq Urdu for Urdu
pdfmetrics.registerFont(TTFont('NotoNastaliqUrdu', 'NafeesNastaleeqXX.ttf'))
# Using Noto Naskh Arabic for Arabic
pdfmetrics.registerFont(TTFont('NotoNaskhArabic', 'NotoNaskhArabic-Regular.ttf'))
# Using Noto Sans for other languages
pdfmetrics.registerFont(TTFont('NotoSans', 'NotoSans-Regular.ttf'))
except Exception as e:
st.warning(f"Font files not found. Default fonts will be used. Error: {str(e)}")
def extract_text_from_pdf(pdf_file):
"""Extract text from uploaded PDF file"""
pdf_reader = PyPDF2.PdfReader(pdf_file)
text = ""
for page in pdf_reader.pages:
text += page.extract_text()
return text
def create_pdf(text, target_language):
if target_language == "Urdu":
font_config = FontConfiguration()
# Process text to handle English and numbers differently
processed_lines = []
for line in text.split('\n'):
# Split line into Urdu and non-Urdu parts
processed_line = ""
current_text = ""
is_urdu = True
for char in line:
if '\u0600' <= char <= '\u06FF' or char in ['۔', '،']: # Urdu character range
if not is_urdu:
if current_text:
processed_line += f'{current_text}'
current_text = ""
is_urdu = True
current_text += char
else:
if is_urdu:
if current_text:
processed_line += current_text
current_text = ""
is_urdu = False
current_text += char
if current_text:
if is_urdu:
processed_line += current_text
else:
processed_line += f'{current_text}'
processed_lines.append(f'{processed_line}
')
processed_text = '\n'.join(processed_lines)
html_content = f"""
{processed_text}
"""
# Create a temporary HTML file
with tempfile.NamedTemporaryFile(suffix='.html', mode='w', encoding='utf-8', delete=False) as f:
f.write(html_content)
temp_html = f.name
# Convert HTML to PDF using WeasyPrint with improved settings
buffer = BytesIO()
HTML(temp_html).write_pdf(
buffer,
font_config=font_config,
stylesheets=[CSS(string='''
@page {
size: A4;
margin: 3cm 2.5cm;
@top-right {
content: "";
margin: 1cm 0;
}
@bottom-center {
content: counter(page);
font-family: Arial, sans-serif;
}
}
''')]
)
buffer.seek(0)
# Clean up temporary file
os.unlink(temp_html)
return buffer
else:
# Use ReportLab for other languages
buffer = BytesIO()
c = canvas.Canvas(buffer, pagesize=A4)
width, height = A4
y = height - 50
margin = 50
if target_language == "Arabic":
try:
c.setFont('NotoNaskhArabic', 14)
text = arabic_reshaper.reshape(text)
text = get_display(text)
lines = text.split('\n')
line_height = c._fontsize * 1.5
for line in lines:
if y < 50:
c.showPage()
y = height - 50
c.setFont('NotoNaskhArabic', 14)
line_width = c.stringWidth(line, c._fontname, c._fontsize)
x = width - margin - line_width
c.drawString(x, y, line)
y -= line_height
except Exception as e:
st.warning(f"Arabic rendering error: {str(e)}")
c.setFont('Helvetica', 12)
else:
try:
c.setFont('NotoSans', 12)
lines = text.split('\n')
line_height = c._fontsize * 1.5
for line in lines:
if y < 50:
c.showPage()
y = height - 50
c.setFont('NotoSans', 12)
c.drawString(margin, y, line)
y -= line_height
except Exception as e:
st.warning(f"Text rendering error: {str(e)}")
c.setFont('Helvetica', 12)
c.save()
buffer.seek(0)
return buffer
def translate_text(text, target_language, api_key):
"""Translate text using OpenAI API with improved prompting"""
try:
client = openai.OpenAI(api_key=api_key)
# Enhanced prompt for better translation
system_prompt = f"""You are a professional translator specializing in {target_language}.
Translate the following text to {target_language}, ensuring:
1. Technical terms are accurately translated
2. Maintain formal language and proper grammar
3. Preserve formatting and structure
4. Keep proper nouns and technical terms like 'AI', 'LLMs', 'Python' in English where appropriate
5. Use culturally appropriate expressions
6. For Urdu/Arabic, ensure proper character connections and diacritics
7. Maintain professional and accurate technical translations
8. Preserve line breaks and paragraph structure
"""
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": text}
],
temperature=0.3
)
return response.choices[0].message.content
except Exception as e:
return f"Translation error: {str(e)}"
# Set page config
st.set_page_config(page_title="PDF Translator", layout="wide")
# Try to register fonts at startup
register_fonts()
# Main app interface
st.title("PDF Document Translator")
# Add custom CSS for better text display
st.markdown("""
""", unsafe_allow_html=True)
# Language selection
languages = {
"English": "English",
"Urdu": "Urdu",
"Arabic": "Arabic",
"Roman English": "Roman English",
"Roman Urdu": "Roman Urdu",
"Hindi": "Hindi",
"Spanish": "Spanish",
"French": "French"
}
# File uploader
uploaded_file = st.file_uploader("Upload your PDF file", type="pdf")
# API Key input field
api_key_input = st.text_input("Enter OpenAI API Key:", type="password", key="api_key_input")
if api_key_input:
api_key = api_key_input
# Language selector
target_language = st.selectbox(
"Select target language",
options=list(languages.keys())
)
# Create two columns for original and translated text
col1, col2 = st.columns(2)
if uploaded_file is not None and api_key:
# Extract text from PDF
with st.spinner("Extracting text from PDF..."):
text = extract_text_from_pdf(uploaded_file)
# Show original text
with col1:
st.subheader("Original Text")
st.text_area("", value=text, height=400, key="original_text")
# Initialize session state for translated text
if 'translated_text' not in st.session_state:
st.session_state.translated_text = None
# Translate button
if st.button("Translate"):
with st.spinner("Translating..."):
translated_text = translate_text(text, languages[target_language], api_key)
st.session_state.translated_text = translated_text
# Show translated text
with col2:
st.subheader(f"Translated Text ({target_language})")
st.text_area("", value=translated_text, height=400, key="translated_text")
# Show download button if translation exists
if st.session_state.translated_text:
# Create PDF button
if st.download_button(
label="Download Translated PDF",
data=create_pdf(st.session_state.translated_text, target_language),
file_name=f"translated_{target_language}.pdf",
mime="application/pdf"
):
st.success("PDF downloaded successfully!")
elif not api_key:
st.warning("Please enter your OpenAI API key to proceed.")
# Add instructions and notes
st.markdown("""
### Instructions:
1. Enter your OpenAI API key
2. Upload your PDF file
3. Select your target language
4. Click 'Translate' to get your translation
5. Review the translation
6. Click 'Download Translated PDF' to save as PDF
""")