| import streamlit as st |
| from deep_translator import GoogleTranslator |
| import datetime |
|
|
| def translate_word(word): |
| |
| now_utc = datetime.datetime.utcnow() |
| now_ist = now_utc + datetime.timedelta(hours=5, minutes=30) |
|
|
| |
| if word[0].lower() in 'aeiou': |
| if now_ist.hour == 21 and now_ist.minute < 60: |
|
|
| return "Error: Words starting with vowels cannot be translated between 9 PM and 10 PM IST" |
| |
| |
| |
| try: |
| translation = GoogleTranslator(source='en', target='hi').translate(word) |
| return translation |
| except Exception as e: |
| return f"Error: {str(e)}" |
|
|
| |
| st.title('English to Hindi Translator') |
|
|
| word = st.text_input('Enter a word:') |
|
|
| if st.button('Translate'): |
| translation = translate_word(word) |
| st.write(f"Translation: {translation}") |
|
|
|
|
| train_data = [ |
| {"english": "hello", "hindi": "नमस्ते"}, |
| {"english": "world", "hindi": "दुनिया"}, |
| {"english": "apple", "hindi": "सेब"}, |
| {"english": "book", "hindi": "किताब"}, |
| {"english": "computer", "hindi": "कंप्यूटर"} |
| ] |
|
|
| def translate_and_evaluate(train_data): |
| correct = 0 |
| total = len(train_data) |
|
|
| for item in train_data: |
| translated_word = translate_word(item["english"]) |
| if translated_word == item["hindi"]: |
| correct += 1 |
|
|
| accuracy = (correct / total) * 100 |
| return accuracy |
|
|
| |
| accuracy = translate_and_evaluate(train_data) |
| print(f"Accuracy: {accuracy:.2f}%") |
|
|
|
|
