Update app.py

app.py

@@ -4,19 +4,17 @@ import pandas as pd
 import plotly.express as px
 
 # ------------------------------
-# Load pretrained models (CPU)
+# Load pretrained models
 # ------------------------------
 text_classifier = pipeline(
     "text-classification",
     model="j-hartmann/emotion-english-distilroberta-base",
-    return_all_scores=True,
-    device=-1  # CPU
+    return_all_scores=True
 )
 
 audio_classifier = pipeline(
     "audio-classification",
-    model="mrm8488/wav2vec2-small-xlsr-53-english-emotion",
-    device=-1  # CPU
+    model="superb/wav2vec2-base-superb-er"
 )
 
 # ------------------------------
@@ -30,7 +28,7 @@ EMOJI_MAP = {
     "neutral": "😐",
     "sadness": "😢",
     "surprise": "😲",
-    "hap": "😄",
+    "hap": "😄",  # for audio model
     "neu": "😐",
     "sad": "😢",
     "ang": "😡"
@@ -108,7 +106,7 @@ def predict(text, audio, w_text, w_audio):
 # Build Gradio interface
 # ------------------------------
 with gr.Blocks() as demo:
-    gr.Markdown("## 🎭 CPU-Friendly Multimodal Emotion Classification")
+    gr.Markdown("## 🎭 Multimodal Emotion Classification (Text + Speech)")
 
     with gr.Row():
         with gr.Column():
@@ -121,6 +119,7 @@ with gr.Blocks() as demo:
             final_label = gr.Markdown(label="Predicted Emotion")
             chart_output = gr.Plot(label="Emotion Scores")
 
+    # Button click triggers prediction
     btn.click(fn=predict, inputs=[txt, aud, w1, w2], outputs=[final_label, chart_output])
 
-demo.launch()
+demo.launch()