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import streamlit as st
from transformers import MarianMTModel, MarianTokenizer
# Define available target languages and their Hugging Face model names
language_options = {
"French": "Helsinki-NLP/opus-mt-en-fr",
"German": "Helsinki-NLP/opus-mt-en-de",
"Spanish": "Helsinki-NLP/opus-mt-en-es",
"Italian": "Helsinki-NLP/opus-mt-en-it",
"Dutch": "Helsinki-NLP/opus-mt-en-nl",
"Urdu": "Helsinki-NLP/opus-mt-en-ur",
"Punjabi": "Helsinki-NLP/opus-mt-en-pa", # Punjabi language model
"Pashto": "Helsinki-NLP/opus-mt-en-ps", # Pashto language model
}
# Function to load the model based on the selected language
@st.cache_resource
def load_model(model_name):
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)
return model, tokenizer
# Function to translate text
def translate_text(model, tokenizer, text):
inputs = tokenizer.encode(text, return_tensors='pt', truncation=True, padding=True)
translated = model.generate(inputs, max_length=512, num_beams=5, early_stopping=True)
translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
return translated_text
# Streamlit app layout with dark gradient colors
st.markdown("""
<style>
body {
background: linear-gradient(135deg, #1f1c2c, #928dab);
color: #e0e0e0;
}
.stApp {
background: linear-gradient(135deg, #1f1c2c, #928dab);
}
.css-1d391kg {
background-color: rgba(31, 28, 44, 0.8);
color: #e0e0e0;
border-radius: 10px;
padding: 20px;
border: 1px solid #333;
}
.stButton > button {
background-color: #333;
background-image: linear-gradient(to right, #4facfe, #00f2fe);
color: #e0e0e0;
border: none;
border-radius: 8px;
padding: 10px 20px;
}
.stButton > button:hover {
background-image: linear-gradient(to right, #00c6ff, #0072ff);
border: none;
}
.stTextArea textarea {
background-color: #333;
background-image: linear-gradient(to right, #4facfe, #00f2fe);
color: #e0e0e0;
border: none;
border-radius: 8px;
}
.stSidebar {
background-color: rgba(31, 28, 44, 0.9);
}
</style>
""", unsafe_allow_html=True)
# App title and subtitle with dark gradient
st.markdown("<h1 style='text-align: center; color: #e0e0e0;'>π Polyglot Translator π</h1>", unsafe_allow_html=True)
st.markdown("<p style='text-align: center; color: #b0b0b0; font-size: 20px;'>Empowering You to Speak Any Language!</p>", unsafe_allow_html=True)
# Sidebar for language selection and instructions
st.sidebar.title("Language Options")
language = st.sidebar.selectbox("Choose target language", list(language_options.keys()))
st.sidebar.markdown("### How to use")
st.sidebar.write("1. Enter English text in the box below.")
st.sidebar.write("2. Select the target language from the options.")
st.sidebar.write("3. Click **Translate** to get the result.")
# Input text
st.markdown("<h3 style='color: #e0e0e0;'>Enter text in English to translate:</h3>", unsafe_allow_html=True)
text = st.text_area("", height=150)
# Character count
st.write(f"<p style='color: #e0e0e0;'>Character count: {len(text)}</p>", unsafe_allow_html=True)
# Button to translate
if st.button("Translate"):
if text:
# Show a spinner during the translation process
with st.spinner('Translating...'):
# Load model and tokenizer based on selected language
model_name = language_options[language]
model, tokenizer = load_model(model_name)
# Perform translation
translated_text = translate_text(model, tokenizer, text)
# Display the translation
st.markdown(f"<h3 style='color: #e0e0e0;'>Translated Text ({language}):</h3>", unsafe_allow_html=True)
st.success(translated_text)
else:
st.error("Please enter text to translate.")
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