app.py

import openai
import os
import streamlit as st
from PIL import Image
from gtts import gTTS
import tempfile
import shutil
import re

# Language mapping for gTTS
LANGUAGE_MAP = {
    "English": "en",
    "Japanese": "ja",
    "French": "fr",
    "Spanish": "es",
    "German": "de",
    "Chinese": "zh",
    "Italian": "it",
    "Portuguese": "pt",
    "Korean": "ko",
    "Arabic": "ar"
}

def translate_text(api_key, text, target_language):
    """
    Translates English text to the selected target language using OpenAI's API and provides pronunciation.
    """
    # Validate input
    if not api_key:
        return "Error: API key is missing.", None
    if not text:
        return "Error: Input text is empty.", None

    # Set the OpenAI API key
    openai.api_key = api_key
    
    # Define the messages for the chat model
    messages_translation = [
        {"role": "system", "content": "You are a helpful translator."},
        {"role": "user", "content": f"Translate the following English text to {target_language}:\n\n{text}"}
    ]
    
    try:
        # Call the OpenAI API to get the translation
        response_translation = openai.ChatCompletion.create(
            model="gpt-4o",  # Use the correct endpoint for chat models
            messages=messages_translation,
            max_tokens=300,
            temperature=0.5
        )

        # Extract the translation from the response
        translation = response_translation.choices[0].message['content'].strip()

        # Define the messages for the pronunciation request (Romaji or other phonetic systems)
        messages_pronunciation = [
            {"role": "system", "content": "You are a helpful assistant who provides the pronunciation of the translated text."},
            {"role": "user", "content": f"Provide the pronunciation for the following {target_language} text:\n\n{translation}"}
        ]
        
        # Call the OpenAI API to get the pronunciation
        response_pronunciation = openai.ChatCompletion.create(
            model="gpt-4o",
            messages=messages_pronunciation,
            max_tokens=300,
            temperature=0.5
        )

        # Extract the pronunciation from the response
        pronunciation = response_pronunciation.choices[0].message['content'].strip()

        return translation, pronunciation

    except openai.error.OpenAIError as e:
        return f"OpenAI API error: {str(e)}", None
    except Exception as e:
        return f"An unexpected error occurred: {str(e)}", None

# Function to clean pronunciation text
def clean_pronunciation(pronunciation_text):
    # Remove introductory phrases like "Certainly! The pronunciation for the Arabic text..."
    pronunciation_cleaned = re.sub(r"^(Certainly!|Sure!|The pronunciation for the .+? text.*?is[:]*\s*)", "", pronunciation_text).strip()
    return pronunciation_cleaned

# Function to generate audio file from text using gTTS
def generate_audio_from_text(text, language_code):
    tts = gTTS(text, lang=language_code)  # Dynamically use the language code
    # Save audio to a temporary file
    temp_audio_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
    tts.save(temp_audio_file.name)
    return temp_audio_file.name

# Streamlit UI
st.title("Multi-language Translator with Pronunciation")
st.markdown("Translate English text into various languages and get its pronunciation.")

translateimg = Image.open("Untitled.png")  # Ensure the file is in the correct directory
st.image(translateimg, use_container_width=True)  # Adjust the size as per preference

# Access the API key from Hugging Face Secrets
api_key = os.getenv("OPENAI_API_KEY")

# Input field for the text
english_text = st.text_area("Enter the English text to translate")

# Dropdown menu for language selection
language_option = st.selectbox(
    "Select Target Language",
    ["English", "Japanese", "French", "Spanish", "German", "Chinese", "Italian", "Portuguese", "Korean", "Arabic"]
)

# Button to trigger the translation
if st.button("Translate"):
    if api_key and english_text:
        # Initialize the progress bar
        progress_bar = st.progress(0)
        progress_text = st.empty()  # To show the progress text

        try:
            # Step 1: Request translation
            progress_text.text("Translating text...")
            progress_bar.progress(33)  # Update progress bar to 33%

            # Translate text and get pronunciation
            translated_text, pronunciation = translate_text(api_key, english_text, language_option)

            # Step 2: Check if translation was successful
            if pronunciation:
                progress_text.text("Generating pronunciation...")
                progress_bar.progress(66)  # Update progress bar to 66%

                # Clean pronunciation (remove unnecessary parts)
                cleaned_pronunciation = clean_pronunciation(pronunciation)

                st.markdown("### Translation Result:")
                st.write(f"**Original English Text:** {english_text}")
                st.write(f"**Translated Text ({language_option}):** {translated_text}")
                st.write(f"**Pronunciation:** {cleaned_pronunciation}")

                # Save the result in a text file
                result_text = f"Original English Text: {english_text}\n\nTranslated Text ({language_option}): {translated_text}\nPronunciation: {cleaned_pronunciation}"

                # Write to a text file
                with open("translation_result.txt", "w") as file:
                    file.write(result_text)

                # Create a download button for the user to download the file
                with open("translation_result.txt", "rb") as file:
                    st.download_button(
                        label="Download Translation Result",
                        data=file,
                        file_name="translation_result.txt",
                        mime="text/plain"
                    )

                # Step 3: Generate audio for pronunciation
                progress_text.text("Generating pronunciation audio...")
                progress_bar.progress(100)  # Update progress bar to 100%

                audio_file_path = generate_audio_from_text(cleaned_pronunciation, LANGUAGE_MAP[language_option])

                # Provide a button to play the pronunciation audio
                st.audio(audio_file_path, format="audio/mp3")

                translateimg2 = Image.open("v3.png")  # Ensure the file is in the correct directory
                st.image(translateimg2, width=150)  # Adjust the size as per preference

            else:
                st.error(translated_text)  # Display error message if API call fails

        except Exception as e:
            st.error(f"An error occurred: {str(e)}")
    else:
        if not api_key:
            st.error("API key is missing. Please add it as a secret in Hugging Face Settings.")
        else:
            st.error("Please provide text to translate.")