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d5c1c18 5c0fbc8 d5c1c18 5c0fbc8 d5c1c18 5c0fbc8 d5c1c18 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 | import streamlit as st
from transformers import MarianMTModel, MarianTokenizer
# Map of language codes to full language names and flag images
language_dict = {
"en": "English",
"de": "German",
"fr": "French",
"es": "Spanish",
"it": "Italian",
"nl": "Dutch",
"pt": "Portuguese",
"ro": "Romanian",
"ru": "Russian",
"zh": "Chinese"
}
# Reverse map for language selection
language_codes = {v: k for k, v in language_dict.items()}
# Add custom CSS for styling
st.markdown("""
<style>
.stTextInput, .stTextArea {
background-color: #f4f6f8;
padding: 10px;
border-radius: 8px;
}
.stButton {
background-color: #4CAF50;
color: black;
padding: 10px 20px;
border-radius: 5px;
}
.stButton:hover {
background-color: #45a049;
}
.stText {
font-size: 1.2em;
font-family: 'Helvetica', sans-serif;
}
.footer {
padding: 10px;
background-color: #f1f1f1;
text-align: center;
}
h1 {
color: #4CAF50;
}
</style>
""", unsafe_allow_html=True)
# Custom Exception for Same Source and Target Language
class SameLanguageException(Exception):
pass
# Function to load model and tokenizer
def load_translation_model(src_lang, tgt_lang):
model_name = f'Helsinki-NLP/opus-mt-{src_lang}-{tgt_lang}'
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)
return model, tokenizer
# Function to translate text
def translate_text(text, src_lang, tgt_lang):
if src_lang == tgt_lang:
raise SameLanguageException("Source and target languages must be different.")
model, tokenizer = load_translation_model(src_lang, tgt_lang)
# Tokenize the input text
inputs = tokenizer(text, return_tensors="pt", padding=True)
# Translate the text
translated = model.generate(**inputs)
# Decode the translated text
translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
return translated_text
# Language selector with flags and names
def language_selector():
# Use two columns to display the language selectors
col1, col2 = st.columns(2)
with col1:
source_language = st.selectbox(
"Select source language",
list(language_dict.values()),
key="source_language"
)
with col2:
target_language = st.selectbox(
"Select target language",
list(language_dict.values()),
key="target_language"
)
return language_codes[source_language], language_codes[target_language]
# Main application function
def run_app():
st.title("🌍 Interactive Language Translation App")
st.subheader("Translate your text in real-time with ease! 🌐")
# Select source and target languages
src_lang_code, tgt_lang_code = language_selector()
# Text input field with placeholder
text_input = st.text_area("Enter text to translate", placeholder="Type here...", height=150)
# Option to upload a text file for input
uploaded_file = st.file_uploader("Or upload a text file", type=["txt"])
if uploaded_file is not None:
text_input = uploaded_file.read().decode("utf-8")
st.text_area("File content", value=text_input, height=150)
# Button for translation
if st.button("🔄 Translate", key="translate"):
if text_input:
try:
with st.spinner("🔄 Translating... Please wait..."):
# Translate the text
translated_text = translate_text(text_input, src_lang_code, tgt_lang_code)
# Display translated text directly in the success container
st.success(f"✅ Translation: {translated_text}")
st.balloons() # Show animation when translation is complete
except SameLanguageException as e:
st.error(f"❌ Error: {str(e)}")
else:
st.warning("⚠️ Please enter or upload some text to translate.")
# Run the Streamlit app
if __name__ == "__main__":
run_app() |