Create app.py

app.py

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+streamlit 
+transformers 
+torch
+sentencepiece
+sacremoses
+
+import streamlit as st
+from transformers import pipeline
+
+# Initialize the translation pipeline
+@st.cache_resource
+def load_translator():
+    return pipeline("translation", model="Helsinki-NLP/opus-mt-en-{target}")
+
+# Supported languages (ISO 639-1 codes mapped to language names)
+supported_languages = {
+    "fr": "French",
+    "es": "Spanish",
+    "de": "German",
+    "zh": "Chinese",
+    "hi": "Hindi",
+    "ar": "Arabic",
+    "ru": "Russian",
+    "ja": "Japanese",
+    "ko": "Korean",
+    "it": "Italian",
+}
+
+# Streamlit App
+st.title("Language Translator App")
+st.write("Translate text from English to a selected target language using Hugging Face models.")
+
+# Input text from user
+input_text = st.text_area("Enter text in English:", placeholder="Type here...")
+
+# Language selection
+target_language = st.selectbox(
+    "Select target language:",
+    options=list(supported_languages.keys()),
+    format_func=lambda lang: supported_languages[lang],
+)
+
+# Translate button
+if st.button("Translate"):
+    if input_text.strip() == "":
+        st.error("Please enter text to translate.")
+    else:
+        translator = load_translator()
+        # Replace `{target}` with the user-selected language in the model
+        translator = pipeline("translation", model=f"Helsinki-NLP/opus-mt-en-{target_language}")
+        translation = translator(input_text)[0]["translation_text"]
+        st.success("Translated Text:")
+        st.write(translation)