Upload gradio_implementation.py

gradio_implementation.py

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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()