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app.py

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+import gradio as gr
+import ifcopenshell
+import pandas as pd
+from tempfile import NamedTemporaryFile
+import os
+
+def extract_properties(ifc_file_path, element_class):
+    try:
+        model = ifcopenshell.open(ifc_file_path)
+
+        results = []
+        elements = model.by_type("IfcElement")
+        # Get unique type names
+        element_types = sorted(list(set(elem.is_a() for elem in elements)))
+        classes_to_check = [element_class] if element_class != "" else sorted(list(set(obj.is_a() for obj in element_types)))
+
+        for class_name in classes_to_check:
+            elements = model.by_type(class_name)
+            for element in elements:
+                # Get all properties
+                properties = {}
+                for definition in element.IsDefinedBy:
+                    if definition.is_a("IfcRelDefinesByProperties"):
+                        prop_set = definition.RelatingPropertyDefinition
+                        if prop_set.is_a("IfcPropertySet"):
+                            for prop in prop_set.HasProperties:
+                                properties[f"{prop_set.Name}.{prop.Name}"] = prop.NominalValue.wrappedValue if prop.NominalValue else None
+
+                row = {
+                    "GlobalId": element.GlobalId,
+                    "Type": element.is_a(),
+                    "Name": element.Name,
+                    **properties
+                }
+                results.append(row)
+
+        if not results:
+            return pd.DataFrame({"Message": [f"No {element_class if element_class != '' else ''} elements found"]}), None, None
+
+        df = pd.DataFrame(results)
+        # Create temporary files for downloads
+        with NamedTemporaryFile(delete=False, suffix='.csv') as tmp_csv:
+            df.to_csv(tmp_csv.name, index=False)
+            csv_path = tmp_csv.name
+
+        with NamedTemporaryFile(delete=False, suffix='.xlsx') as tmp_excel:
+            df.to_excel(tmp_excel.name, index=False)
+            excel_path = tmp_excel.name
+
+        return df, csv_path, excel_path
+
+    except Exception as e:
+        return pd.DataFrame({"Error": [f"Processing failed: {str(e)}"]}), None, None
+
+def extract_ifc_types(ifc_file):
+    """Extract all IFC types from uploaded file"""
+    if not ifc_file:
+        return []
+    try:
+        ifc = ifcopenshell.open(ifc_file.name)
+        # Get all elements that are IfcElement or its subtypes
+        elements = ifc.by_type("IfcElement")
+        # Get unique type names
+        element_types = sorted(list(set(elem.is_a() for elem in elements)))
+        return element_types
+    except:
+        return []
+
+def update_dropdown(ifc_file):
+    """Update dropdown options when file is uploaded"""
+    choices = extract_ifc_types(ifc_file)
+    return gr.Dropdown(choices=choices, value="", interactive=True)
+
+# Gradio Interface
+with gr.Blocks(title="IFC Property Extractor") as demo:
+    gr.Markdown("## 🛠️ IFC Property Extractor")
+
+    with gr.Row():
+        ifc_input = gr.File(
+            label="1. Upload IFC File",
+            file_types=[".ifc"],
+            type="filepath"
+        )
+
+    with gr.Row():
+        with gr.Column():
+            class_filter = gr.Dropdown(
+                [""],
+                value="",
+                label="2. Filter by Class",
+                interactive=False
+            )
+            extract_btn = gr.Button("Extract Properties", variant="primary")
+
+        with gr.Column():
+            csv_download = gr.File(label="Download CSV", visible=False)
+            excel_download = gr.File(label="Download Excel", visible=False)
+
+    output_table = gr.Dataframe(
+        label="Extracted Properties",
+        interactive=True,
+        wrap=False,
+    )
+
+    # Update dropdown when file is uploaded
+    ifc_input.change(
+        fn=update_dropdown,
+        inputs=ifc_input,
+        outputs=[class_filter]
+    )
+
+    extract_btn.click(
+        fn=extract_properties,
+        inputs=[ifc_input, class_filter],
+        outputs=[output_table, csv_download, excel_download]
+    )
+
+    # Show download buttons only when files are available
+    extract_btn.click(
+        lambda: [gr.File(visible=True), gr.File(visible=True)],
+        outputs=[csv_download, excel_download]
+    )
+
+demo.launch()