samplecode.md

import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import qrcode
from PIL import Image
from wordcloud import WordCloud
import streamlit.components.v1 as components  # For embedding YouTube videos
from gtts import gTTS
import io

tabs = st.tabs(["📈 Welcome", "⏳ TTS"])
with tabs[0]:
    st.caption("To be updated")
# Text-to-Speech tab
with tabs[1]:
    st.subheader("Text-to-Speech Converter (using Google TTS)")
    text_input = st.text_area("Enter the text you want to convert to speech:")
    language = st.selectbox("Choose a language: 🇰🇷 🇺🇸 🇬🇧 🇷🇺 🇫🇷 🇪🇸 🇮🇹 🇯🇵 ", ["Korean", "English (American)", "English (British)", "Russian", "Spanish", "French", "Italian", "Japanese"])

    tts_button = st.button("Convert Text to Speech")
    
    if tts_button and text_input:
        # Map human-readable language selection to language codes and optionally to TLDs for English
        lang_codes = {
            "Korean": ("ko", None),
            "English (American)": ("en", 'com'),
            "English (British)": ("en", 'co.uk'),
            "Russian": ("ru", None),
            "Spanish": ("es", None),
            "French": ("fr", None),
            "Italian": ("it", None),
            "Chinese": ("zh-CN", None),
            "Japanese": ("ja", None)
        }
        language_code, tld = lang_codes[language]

        # Assuming you have a version of gTTS that supports tld or you have modified it:
        # This check ensures that the tld parameter is only used when not None.
        if tld:
            tts = gTTS(text=text_input, lang=language_code, tld=tld, slow=False)
        else:
            tts = gTTS(text=text_input, lang=language_code, slow=False)
        
        speech = io.BytesIO()
        tts.write_to_fp(speech)
        speech.seek(0)

        # Display the audio file
        st.audio(speech.getvalue(), format='audio/mp3')

    st.markdown("---")
    st.caption("🇺🇸 English text: Teacher-designed coding applications create tailored learning experiences, making complex concepts easier to understand through interactive and adaptive tools. They enhance engagement, provide immediate feedback, and support active learning.")
    st.caption("🇰🇷 Korean text: 교사가 직접 만든 코딩 기반 애플리케이션은 학습자의 필요에 맞춘 학습 경험을 제공하고, 복잡한 개념을 쉽게 이해하도록 돕습니다. 또한 학습 몰입도를 높이고 즉각적인 피드백을 제공하며, 능동적인 학습을 지원합니다.")
    st.caption("🇫🇷 French: Les applications de codage conçues par les enseignants offrent une expérience d'apprentissage personnalisée, rendant les concepts complexes plus faciles à comprendre grâce à des outils interactifs et adaptatifs. Elles améliorent l'engagement, fournissent un retour immédiat et soutiennent l'apprentissage actif.")
    st.caption("🇷🇺 Russian: Созданные учителями кодированные приложения предлагают персонализированный опыт обучения, упрощая понимание сложных концепций с помощью интерактивных и адаптивных инструментов. Они повышают вовлеченность, предоставляют мгновенную обратную связь и поддерживают активное обучение.")
    st.caption("🇨🇳 Chinese: 由教师设计的编程应用程序为学习者提供个性化的学习体验，通过互动和适应性工具使复杂的概念更容易理解。它们增强学习参与度，提供即时反馈，并支持主动学习。")
    st.caption("🇯🇵 Japanese: 教師が設計したコーディングアプリケーションは、学習者のニーズに合わせた学習体験を提供し、複雑な概念をインタラクティブで適応性のあるツールを通じて理解しやすくします。また、学習への集中力を高め、即時フィードバックを提供し、主体的な学習をサポートします。")