Add application file

app.py

@@ -0,0 +1,42 @@
+from __future__ import annotations
+import gradio as gr
+import pandas as pd
+import numpy as np
+import pickle
+from tree_decision import Node
+# Load cây đã huấn luyện
+with open("tree.pkl", "rb") as f:
+    tree, feature_names = pickle.load(f)
+
+# Hàm convert dòng dữ liệu thành dict
+def data_dict(row):
+    return {feature_names[i]: row[i] for i in range(len(feature_names))}
+
+# Hàm xử lý CSV
+def predict_csv(file):
+    df = pd.read_csv(file.name)
+    
+    # Kiểm tra cột
+    for name in feature_names:
+        if name not in df.columns:
+            return f"❌ CSV must contain column '{name}'"
+
+    # Predict từng dòng
+    predictions = []
+    for i, row in df[feature_names].iterrows():
+        row_dict = data_dict(row.values)
+        pred = tree.search(row_dict)
+        predictions.append(pred)
+
+    df['prediction'] = predictions
+    return df
+
+# Giao diện Gradio
+demo = gr.Interface(
+    fn=predict_csv,
+    inputs=gr.File(label="Upload CSV"),
+    outputs=gr.Dataframe(label="Predictions")
+)
+
+if __name__ == "__main__":
+    demo.launch(share=True)