Update app.py

app.py

@@ -1,9 +1,10 @@
 import streamlit as st
-import deepl  # DeepL API client library
+from googletrans import Translator  # Free Google Translate API
+from transformers import pipeline
+import requests
 
-# Initialize the DeepL Translator with your API key
-DEEPL_API_KEY = "your_deepL_api_key"  # Replace with your DeepL API key
-translator = deepl.Translator(DEEPL_API_KEY)
+# Initialize the Google Translator
+translator = Translator()
 
 # Streamlit UI setup
 st.set_page_config(page_title="AI-Powered Language Learning Assistant", page_icon="🧠", layout="wide")
@@ -14,40 +15,53 @@ st.markdown("""
 Welcome to your AI-powered language assistant! Here you can:
 - Translate words or sentences to different languages
 - Learn and practice new vocabulary
-- Get pronunciation tips and grammar feedback.
+- Get grammar feedback.
 """)
 
 # Input field for text
 text_input = st.text_input("Enter the text you want to translate or practice", "")
 
 # Select target language for translation
-language = st.selectbox("Select the language to translate to", ["ES", "FR", "DE", "IT", "PT", "RU"])
+language = st.selectbox("Select the language to translate to", ["es", "fr", "de", "it", "pt", "ru"])
 
 if text_input:
-    # Translate text using DeepL API
+    # Translate text using googletrans
     st.subheader(f"Original Text: {text_input}")
-    translated_text = translator.translate_text(text_input, target_lang=language)
+    translated_text = translator.translate(text_input, dest=language).text
 
     # Display translation
     st.markdown(f"### Translated Text to {language.upper()}:")
-    st.write(translated_text.text)
+    st.write(translated_text)
 
     # Show pronunciation tip
     st.subheader("Pronunciation Tip:")
-    st.write("Use an app like Forvo or Google Translate to practice pronunciation. You can also use DeepL for listening practice on the translated text.")
+    st.write("Use Google Translate or Forvo to practice pronunciation.")
 
-    # Grammar Check (simple demo)
+    # Grammar Check (using LanguageTool)
     st.subheader("Grammar Feedback:")
-    st.write("For advanced grammar feedback, use grammar-checking tools like LanguageTool.")
+    grammar_check_url = "https://api.languagetool.org/v2/check"
+    params = {
+        "text": text_input,
+        "language": "en-US"
+    }
+    response = requests.post(grammar_check_url, data=params)
+    if response.status_code == 200:
+        result = response.json()
+        if result['matches']:
+            st.write("### Grammar Issues Found:")
+            for match in result['matches']:
+                st.write(f"- **{match['message']}** at position {match['offset']}-{match['offset']+match['length']}")
+        else:
+            st.write("No grammar issues found!")
+    else:
+        st.write("Grammar check failed. Try again later.")
 
-# Vocabulary practice section
+# Vocabulary practice section using Hugging Face's BERT
 st.markdown("---")
 st.header("Vocabulary Practice")
 word_input = st.text_input("Enter a word to get its definition and synonyms", "")
 if word_input:
-    # For vocabulary practice, let's use the Hugging Face BERT model for related words
-    from transformers import pipeline
-
+    # Using Hugging Face's BERT model for related words (synonyms)
     try:
         word_model = pipeline("fill-mask", model="bert-base-uncased")  # Using BERT to predict related words
         result = word_model(f"The synonym of {word_input} is [MASK].")
@@ -58,5 +72,5 @@ if word_input:
 # Footer for engagement
 st.markdown("""
 ---
-**Need more practice?** Visit [DeepL](https://www.deepl.com) for real-time translations and pronunciation!
+**Need more practice?** Visit [Google Translate](https://translate.google.com) for real-time translations and pronunciation!
 """)