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app.py

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+from transformers import pipeline
+import gradio as gr
+from gtts import gTTS
+
+# Sentiment Analysis
+sentiment = pipeline("sentiment-analysis")
+
+def get_sentiment(text):
+    result = sentiment(text)[0]
+    return result["label"], result["score"]
+
+sentiment_tab = gr.Interface(
+    fn=get_sentiment,
+    inputs=gr.Textbox(label="Enter your review: "),
+    outputs=[gr.Textbox(label="Sentiment"), gr.Number(label="Score")],
+    title="Reviews Sentiment Analysis"
+)
+
+# Summarization
+summarize = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def summarization(text):
+    return summarize(text)[0]["summary_text"]
+
+summary_tab = gr.Interface(
+    fn=summarization,
+    inputs=gr.Textbox(label="Enter your text: "),
+    outputs=gr.Textbox(label="Summarization"),
+    title="Summarizer"
+)
+
+# Text to Speech
+def convert(text):
+    tts = gTTS(text)
+    file_path = "output.mp3"
+    tts.save(file_path)
+    return file_path
+
+text_to_speech_tab = gr.Interface(
+    fn=convert,
+    inputs=gr.Textbox(label="Enter your text to turn into audio:"),
+    outputs=gr.Audio(label="Generated Audio", type="filepath"),
+    title="Text to Speech Converter"
+)
+
+# Combine all in Tabs
+demo = gr.TabbedInterface(
+    [sentiment_tab, summary_tab, text_to_speech_tab],
+    ["Sentiment", "Summarizer", "Text-To-Speech"],
+    theme="soft"
+)
+
+if __name__ == "__main__":
+    demo.launch()
+

requirements.txt

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+gradio
+transformers
+gtts