Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import pandas as pd
+
+def analyze(text):
+    classifier = pipeline("text-classification", model="ayoubkirouane/BERT-Emotions-Classifier", return_all_scores=True)
+    results = classifier(text)
+    
+    # Extract and format the emotion labels and scores
+    formatted_results = [{"Emotion": item['label'], "Score": item['score']} for item in results[0]]
+    
+    return pd.DataFrame(formatted_results)
+
+examples = ["Walking alone in the dark forest, he couldn't shake the feeling of fear creeping over him." ,
+            "Winning the championship brought tears of joy to the entire team."]
+# Create a Gradio interface
+iface = gr.Interface(fn=analyze, 
+                     inputs="text", 
+                     outputs=gr.outputs.Dataframe(type="pandas"),
+                     allow_flagging=False ,
+                     examples=examples , 
+                     title="BERT Emotion Analysis App" , 
+                     description="Enter a piece of text, and this app will analyze its emotional content using a BERT-Emotions-Classifier model.",
+                     )
+
+# Launch the app
+iface.launch(debug=True)