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# -*- coding: utf-8 -*-
"""gradio-implementation.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1sWjE9rMmM4iMx2Gy5880k53D7yaRfDge
"""
pip install gradio
pip install gTTS
pip install translate
pip install transformers
import gradio as gr
from transformers import pipeline
from gtts import gTTS
from translate import Translator
# Initialize the text summarization pipeline
summarizer = pipeline("summarization")
# Define the Gradio interface
def summarize_and_translate(article, target_language):
# Summarize the input article
summary = summarizer(article, max_length=130, min_length=30, do_sample=False)[0]['summary_text']
# Translate the summary to the target language
translator = Translator(to_lang=target_language)
translated_summary = translator.translate(summary)
# Convert the translated summary to speech
tts = gTTS(text=translated_summary, lang=target_language)
tts.save("speech.mp3")
# Return the summarized text and the path to the generated speech
return translated_summary, "speech.mp3"
# Create a Gradio interface
iface = gr.Interface(
fn=summarize_and_translate,
inputs=["text", "text"],
outputs=["text", "audio"],
layout="vertical",
title="Text Summarization and Translation",
description="Summarize text and translate it into another language.",
)
# Start the Gradio interface
iface.launch() |