Create train.py

ai-auditor-module/train.py

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+# ai-auditor-module/train.py
+import pandas as pd
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.model_selection import train_test_split
+
+# Load dataset
+dataset = pd.read_csv('smart_contract_data.csv')
+
+# Preprocess data
+X = dataset.drop(['label'], axis=1)
+y = dataset['label']
+
+# Split data into training and testing sets
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+# Train the model
+model = RandomForestClassifier(n_estimators=100, random_state=42)
+model.fit(X_train, y_train)
+
+# Evaluate the model
+accuracy = model.score(X_test, y_test)
+print(f'Model accuracy: {accuracy:.3f}')
+
+# Save the model
+import joblib
+joblib.dump(model, 'ai_model.joblib')