Update app.py

app.py

@@ -5,7 +5,157 @@ import pandas as pd
 import pickle
 
 # Ensure the project root is in the Python path
-sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+sys.path.append(os.paimport gradio as gr
+import numpy as np
+import pandas as pd
+from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
+from joblib import dump, load
+from ansys.mapdl.core import launch_mapdl
+import matplotlib.pyplot as plt
+import os
+
+# ========== Train AI Models ==========
+def train_models():
+    # Synthetic training data
+    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],  # 1: Pass, 0: Fail
+    }
+    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")
+
+# Train the models
+train_models()
+
+# Load models
+stress_model = load("stress_model.pkl")
+deformation_model = load("deformation_model.pkl")
+pass_fail_model = load("pass_fail_model.pkl")
+
+# ========== ANSYS Simulation ==========
+def run_ansys_simulation(thickness, hole_diameter, force):
+    mapdl = launch_mapdl()
+    mapdl.clear()
+    mapdl.prep7()
+
+    # Material properties
+    mapdl.mp("EX", 1, 2e11)
+    mapdl.mp("PRXY", 1, 0.3)
+
+    # Geometry
+    mapdl.block(0, 100, 0, 50, 0, thickness)
+    mapdl.cylind(0, hole_diameter / 2, 50, 25, 0, thickness)
+    mapdl.vsubtract("ALL")
+
+    # Meshing
+    mapdl.et(1, "SOLID185")
+    mapdl.esize(5)
+    mapdl.vmesh("ALL")
+
+    # Boundary conditions and force
+    mapdl.nsel("S", "LOC", "X", 0)
+    mapdl.d("ALL", "ALL")
+    mapdl.nsel("S", "LOC", "X", 100)
+    mapdl.f("ALL", "FY", -force)
+
+    # Solve
+    mapdl.run("/SOLU")
+    mapdl.antype("STATIC")
+    mapdl.solve()
+    mapdl.finish()
+
+    # Post-process
+    mapdl.post1()
+    max_stress = mapdl.get_value("NODE", 0, "S", "EQV")
+    max_deformation = mapdl.get_value("NODE", 0, "U", "SUM")
+    mapdl.exit()
+
+    return max_stress, max_deformation
+
+# ========== AI and Simulation Workflow ==========
+def ai_and_simulation_workflow(thickness, hole_diameter, force):
+    # AI pre-screening
+    pre_screen = pass_fail_model.predict([[thickness, hole_diameter, force]])[0]
+    if pre_screen == 0:
+        return {
+            "status": "Fail",
+            "message": "AI predicts failure. Please adjust parameters.",
+            "stress": None,
+            "deformation": None,
+        }
+
+    # Run ANSYS simulation
+    max_stress, max_deformation = run_ansys_simulation(thickness, hole_diameter, force)
+
+    # Validate results with AI
+    validation = "Pass" if max_stress < 250 and max_deformation < 0.3 else "Fail"
+
+    # Generate output
+    return {
+        "status": validation,
+        "message": f"Design {validation}.",
+        "stress": max_stress,
+        "deformation": max_deformation,
+    }
+
+# ========== UI ==========
+def visualize_results(results):
+    fig, ax = plt.subplots()
+    labels = ["Stress", "Deformation"]
+    values = [results["stress"], results["deformation"]]
+    ax.bar(labels, values, color=["#FFA07A", "#20B2AA"])
+    ax.set_title("Simulation Results")
+    plt.tight_layout()
+    image_path = "results.png"
+    plt.savefig(image_path)
+    plt.close(fig)
+    return image_path
+
+def run_ui(thickness, hole_diameter, force):
+    results = ai_and_simulation_workflow(thickness, hole_diameter, force)
+    if results["status"] == "Fail":
+        return results["message"], None
+    else:
+        image_path = visualize_results(results)
+        return results["message"], image_path
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=run_ui,
+    inputs=[
+        gr.Slider(10, 50, step=1, label="Thickness (mm)"),
+        gr.Slider(5, 25, step=1, label="Hole Diameter (mm)"),
+        gr.Slider(1000, 15000, step=500, label="Force (N)"),
+    ],
+    outputs=[
+        gr.Textbox(label="Simulation Status"),
+        gr.Image(label="Simulation Visualization"),
+    ],
+    title="AI-Driven ANSYS Design Validation",
+    description="Interactive tool for design validation using AI and ANSYS.",
+    theme="default",
+    live=True,
+)
+
+# Launch the interface
+interface.launch()
+th.dirname(os.path.abspath(__file__)))
 
 # Import optimization logic
 from models.optimizer import optimize_design