Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+import os
+from gtts import gTTS
+
+# Initialize the Hugging Face model pipeline
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-fr")  # Example for English to French translation
+
+# Function to translate text
+def translate_text(text, src_lang, target_lang):
+    # Translate using the Hugging Face pipeline
+    translation = translator(text, src_lang=src_lang, tgt_lang=target_lang)
+    return translation[0]['translation_text']
+
+# Function to convert text to speech
+def text_to_speech(text, lang='en'):
+    tts = gTTS(text=text, lang=lang, slow=False)
+    tts.save("output.mp3")
+    return "output.mp3"
+
+# Streamlit UI
+st.title("Multilingual Text Translator and Text-to-Speech")
+st.write("Enter the text below to translate and convert to speech")
+
+# Text input for the user
+input_text = st.text_area("Enter text to translate:")
+
+# Language selection
+src_lang = st.selectbox("Select source language", ["en", "fr", "es", "de", "it"])
+target_lang = st.selectbox("Select target language", ["fr", "en", "es", "de", "it"])
+
+if st.button("Translate and Convert to Speech"):
+    if input_text:
+        # Translate the text
+        translated_text = translate_text(input_text, src_lang, target_lang)
+        st.write(f"Translated Text: {translated_text}")
+
+        # Convert the translated text to speech
+        audio_file = text_to_speech(translated_text, lang=target_lang)
+        st.audio(audio_file)
+
+        # Remove the generated audio file after use
+        os.remove(audio_file)
+    else:
+        st.error("Please enter text to translate.")