create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformes import pipeline
+
+model_id = "Subhajit01/distilbert-base-uncased-finetuned-emotion"
+classifier = pipeline("text-classification", model=model_id)
+labels = ['sadness', 'joy', 'love', 'anger', 'fear', 'surprise']
+
+def predict(text):
+    max_prob_id = 0
+    max_prob = 0
+    preds = classifier(text, return_all_scores=True)
+    for i in range(len(preds[0])):
+        if (preds[0][i]["score"] > max_prob):
+            max_prob = preds[0][i]["score"]
+            max_prob_id = i
+    return labels[max_prob_id]
+
+iface = gr.Interface(fn=predict, 
+                     inputs="text", 
+                     outputs="text",
+                     title="Sentiment Analyzer",
+                     description="Enter text to analyze its sentiment.")
+
+iface.launch()