Update app.py

app.py

@@ -1,30 +1,40 @@
 import gradio as gr
 from transformers import pipeline
 
-# Sentiment Analysis
-sentiment = pipeline("sentiment-analysis")
-
-def get_sentiment(input_text):
-    return sentiment(input_text)
+# Emotion Text Classification
+title_emotion = "Classify text according to emotion"
+description_emotion = "Emotion text classification via bert-base finetuned by bhadresh-savani"
+examples_emotion = [
+    ["Remember before Twitter when you took a photo of food, got the film developed, then drove around showing everyone the pic? No? Me neither."],
+    ['''"We are all here because we're committed to the biggest question of all: What's out there?" Take your first steps toward answering that question by watching our Gameplay Reveal from the #XboxBethesda Showcase. '''],
+    ["A STUNNER IN KNOXVILLE! 😱 Notre Dame takes down No. 1 Tennessee for its first trip to Omaha in 20 years‼️"],
+    ["you and I best moment is yet to come 💜 #BTS9thAnniversary"]
+]
 
-iface_sentiment = gr.Interface(get_sentiment, inputs="text", outputs="text", title="Sentiment Analysis")
+interface_emotion = gr.Interface.load(
+    "huggingface/bhadresh-savani/bert-base-go-emotion",
+    title=title_emotion,
+    description=description_emotion,
+    examples=examples_emotion
+)
 
 # Text to Speech Translation
-tts_title = "Text to Speech Translation"
-tts_examples = [
+title_tts = "Text to Speech Translation"
+examples_tts = [
     "I love learning machine learning",
     "How do you do?",
 ]
 
-tts_demo = gr.Interface.load(
+interface_tts = gr.Interface.load(
     "huggingface/facebook/fastspeech2-en-ljspeech",
-    title=tts_title,
-    examples=tts_examples,
+    title=title_tts,
+    examples=examples_tts,
     description="Give me something to say!",
 )
 
-# Launching both interfaces
-demo = gr.TabbedInterface([iface_sentiment, tts_demo], ["Sentiment Analysis", "Text to Speech"])
+# Launching both interfaces with tabs
+demo = gr.TabbedInterface([interface_emotion, interface_tts], ["Emotion Classification", "Text to Speech"])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(share=True, enable_queue=True)
+