Update app.py

app.py

@@ -1,3 +1,11 @@
+# app.py
+
+import subprocess
+
+# Install dependencies
+subprocess.run(["pip", "install", "-r", "requirements.txt"])
+
+# Rest of your code
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
@@ -7,11 +15,11 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForSequenceClassification.from_pretrained(model_name)
 
 # Define emotion labels used by the model
-emotion_labels = ["admiration", "amusement", "anger", "annoyance", "approval",
-                  "caring", "confusion", "curiosity", "desire", "disappointment",
-                  "disapproval", "disgust", "embarrassment", "excitement",
-                  "fear", "gratitude", "grief", "joy", "love", "nervousness",
-                  "optimism", "pride", "realization", "relief", "remorse",
+emotion_labels = ["admiration", "amusement", "anger", "annoyance", "approval", 
+                  "caring", "confusion", "curiosity", "desire", "disappointment", 
+                  "disapproval", "disgust", "embarrassment", "excitement", 
+                  "fear", "gratitude", "grief", "joy", "love", "nervousness", 
+                  "optimism", "pride", "realization", "relief", "remorse", 
                   "sadness", "surprise", "neutral"]
 
 def predict_emotion(text):
@@ -21,34 +29,15 @@ def predict_emotion(text):
     predicted_class = logits.argmax().item()
 
     predicted_emotion = emotion_labels[predicted_class]
-    confidence = logits.softmax(dim=1).squeeze()[predicted_class].item()
-    return predicted_emotion, confidence  # Return the predicted emotion and confidence
-
-def get_confidence_color(confidence):
-    # Define a color scale based on confidence
-    if confidence >= 0.8:
-        return "green"
-    elif confidence >= 0.5:
-        return "orange"
-    else:
-        return "red"
+    return predicted_emotion  # Return the predicted emotion directly
 
 iface = gr.Interface(
     fn=predict_emotion,
     inputs=gr.Textbox(),
-    outputs=[
-        gr.Textbox(),
-        "text",
-        gr.Textbox("Confidence Score:", default=""),
-    ],
+    outputs="text",
     live=True,
     title="Emotion Prediction",
     description="Enter a sentence for emotion prediction.",
 )
 
-# Customize the interface appearance
-iface.style(
-    confidence_score=get_confidence_color
-)
-
-iface.launch()
+iface.launch()