Update app.py

app.py

@@ -1,23 +1,20 @@
-import gradio as gr
 from sklearn.datasets import load_iris
 from sklearn.model_selection import train_test_split
 from sklearn.linear_model import LogisticRegression
 from joblib import dump
-import os
 
-def train_model():
-    data = load_iris()
-    X = data.data
-    y = data.target
-    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+# Carregar e dividir o dataset
+data = load_iris()
+X = data.data
+y = data.target
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
 
-    model = LogisticRegression()
-    model.fit(X_train, y_train)
+# Treinando o modelo
+model = LogisticRegression()
+model.fit(X_train, y_train)
 
-    model_filename = "/mnt/data/model.pkl"
-    dump(model, model_filename)
-    
-    return f"Modelo treinado e salvo em: {model_filename}"
+# Salvar o modelo em um arquivo
+model_filename = "model.pkl"
+dump(model, model_filename)
 
-iface = gr.Interface(fn=train_model, inputs=[], outputs=["text"])
-iface.launch()
+print("Modelo treinado e salvo!")