Create app.py

app.py

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+import gradio as gr
+import numpy as np
+from sklearn.linear_model import Perceptron
+import pandas as pd
+
+file_path = "Student-Employability-Datasets (1).xlsx"
+df = pd.read_excel(file_path, sheet_name='Data')
+
+X = df.iloc[:, 1:-2].values  
+y = (df['CLASS'] == 'Employable').astype(int) 
+
+model = Perceptron()
+model.fit(X, y)
+
+def evaluate_employment(name, *ratings):
+    input_data = np.array(ratings).reshape(1, -1)
+    prediction = model.predict(input_data)[0]
+    
+    if prediction == 1:
+        return f"{name}, Congrats! 🎉 You are employable."
+    else:
+        return f"{name}, Try to upgrade yourself! 📚"
+
+def app():
+    with gr.Blocks() as demo:
+        name = gr.Textbox(label="Enter your name")
+        sliders = [gr.Slider(1, 5, step=1, label=col) for col in df.columns[1:-2]]
+        button = gr.Button("Get Yourself Evaluated")
+        output = gr.Textbox(label="Result")
+        
+        button.click(evaluate_employment, inputs=[name] + sliders, outputs=output)
+    
+    return demo
+
+app().launch(share=True)