app.py

import gradio as gr
from transformers import pipeline

# Sentiment Analysis
sentiment = pipeline("sentiment-analysis")

def get_sentiment(input_text):
    return sentiment(input_text)

iface_sentiment = gr.Interface(get_sentiment, inputs="text", outputs="text", title="Sentiment Analysis")

# Text to Speech Translation
tts_title = "Text to Speech Translation"
tts_examples = [
    "I love learning machine learning",
    "How do you do?",
]

tts_demo = gr.Interface.load(
    "huggingface/facebook/fastspeech2-en-ljspeech",
    title=tts_title,
    examples=tts_examples,
    description="Give me something to say!",
)

# Launching both interfaces
demo = gr.TabbedInterface([iface_sentiment, tts_demo], ["Sentiment Analysis", "Text to Speech"])

if __name__ == "__main__":
    demo.launch(share=True)