Update app.py

app.py

@@ -1,22 +1,33 @@
-from transformers import pipeline
-
 import gradio as gr
 
-tts = pipeline("text-to-speech", "facebook/wav2vec2-base-960h")
-
-def text_to_speech(text):
-    audio = tts(text)[0]["audio"]
-    return audio
-
-demo = gr.Blocks()
-
-with demo:
-    text_input = gr.Textbox()
-    audio_output = gr.Audio()
-
-    b1 = gr.Button("Convert to Speech")
-
-    b1.click(text_to_speech, inputs=text_input, outputs=audio_output)
+# Text to Speech Interface
+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!",
+)
+
+# Sentiment Analysis Interface
+sentiment_title = "Sentiment Analysis"
+sentiment_examples = [
+    "I love learning machine learning",
+    "How do you do?",
+]
+sentiment_demo = gr.Interface.load(
+    "huggingface/nlp-sentiment-analysis",
+    title=sentiment_title,
+    examples=sentiment_examples,
+    description="Analyze the sentiment of the text!",
+)
+
+# Tabbed Interface
+demo = gr.TabbedInterface([tts_demo, sentiment_demo], ["Text to Speech", "Sentiment Analysis"])
 
 if __name__ == "__main__":
     demo.launch()