Create ai_models.py

ai_models.py

@@ -0,0 +1,35 @@
+import pandas as pd
+from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
+from joblib import dump, load
+
+def train_models():
+    # Synthetic dataset
+    data = {
+        "Thickness": [10, 15, 20, 25],
+        "Hole_Diameter": [5, 10, 15, 20],
+        "Force": [5000, 7000, 10000, 12000],
+        "Max_Stress": [300, 250, 200, 150],
+        "Max_Deformation": [0.5, 0.4, 0.3, 0.2],
+        "Pass_Fail": [1, 1, 0, 0]
+    }
+    df = pd.DataFrame(data)
+    X = df[["Thickness", "Hole_Diameter", "Force"]]
+
+    # Train regression models
+    stress_model = RandomForestRegressor().fit(X, df["Max_Stress"])
+    deformation_model = RandomForestRegressor().fit(X, df["Max_Deformation"])
+
+    # Train classification model
+    pass_fail_model = RandomForestClassifier().fit(X, df["Pass_Fail"])
+
+    # Save models
+    dump(stress_model, "stress_model.pkl")
+    dump(deformation_model, "deformation_model.pkl")
+    dump(pass_fail_model, "pass_fail_model.pkl")
+
+def load_models():
+    return (
+        load("stress_model.pkl"),
+        load("deformation_model.pkl"),
+        load("pass_fail_model.pkl")
+)