Update app.py

app.py

@@ -1,7 +1,9 @@
 import streamlit as st
 from datasets import load_dataset
 import json
-from cadquery import exporters, Workplane
+from cadquery import Workplane, exporters
+import tempfile
+import os
 
 # Load CADBench dataset
 dataset = load_dataset("FreedomIntelligence/CADBench", split="train")
@@ -11,13 +13,44 @@ st.title("Quick CAD Model Generator")
 st.sidebar.title("Select Case")
 case = st.sidebar.radio("Choose a functionality:", ["DFM Analysis", "Predefined Template Selection"])
 
+def analyze_dfm(file, file_format):
+    """Perform Design for Manufacturing (DFM) analysis."""
+    try:
+        st.write(f"Analyzing {file_format} file...")
+        # Placeholder: Replace with real DFM logic
+        return "The design is suitable for CNC manufacturing!"
+    except Exception as e:
+        return f"Error analyzing file: {e}"
+
+def generate_cad_model(responses):
+    """Generate CAD model based on user inputs."""
+    try:
+        # Placeholder: CAD generation logic
+        result = Workplane("XY").box(1, 1, 1)  # Example model
+        return result
+    except Exception as e:
+        raise RuntimeError(f"Error generating CAD model: {e}")
+
+def export_cad(model, file_format):
+    """Export CAD model to selected format."""
+    with tempfile.NamedTemporaryFile(delete=False, suffix=f".{file_format}") as temp_file:
+        if file_format == "stl":
+            exporters.exportShape(model, exporters.ExportTypes.STL, temp_file.name)
+        elif file_format == "step":
+            exporters.exportShape(model, exporters.ExportTypes.STEP, temp_file.name)
+        elif file_format == "dwg":
+            # Placeholder: Add DWG export logic
+            pass
+        return temp_file.name
+
 if case == "DFM Analysis":
     st.subheader("Case 1: DFM Analysis")
     cad_file = st.file_uploader("Upload a CAD file (.stl, .step, .dwg)", type=["stl", "step", "dwg"])
     if cad_file:
-        st.write("Analyzing the CAD file...")
-        # Placeholder for DFM analysis
-        st.success("DFM analysis complete. The design is suitable for CNC manufacturing!")
+        file_format = os.path.splitext(cad_file.name)[1][1:]
+        analysis_result = analyze_dfm(cad_file, file_format)
+        st.success(analysis_result)
+
 elif case == "Predefined Template Selection":
     st.subheader("Case 2: Predefined Template Selection")
     template_names = dataset["name"]
@@ -26,8 +59,8 @@ elif case == "Predefined Template Selection":
     if selected_template:
         st.write(f"Selected Template: {selected_template}")
         template_data = dataset.filter(lambda x: x["name"] == selected_template).to_pandas()
-        criteria = json.loads(template_data.iloc[0]["criteria"])
-        
+        criteria = template_data.iloc[0]["criteria"]  # Already a dict
+
         responses = {}
         for criterion, prompt in criteria.items():
             prefilled_text = f"Enter {criterion} ({prompt}):"
@@ -37,8 +70,11 @@ elif case == "Predefined Template Selection":
 
         if st.button("Generate CAD Model"):
             try:
-                # Placeholder for CAD generation logic
+                model = generate_cad_model(responses)
+                file_format = st.selectbox("Select file format for download", ["stl", "step", "dwg"])
+                file_path = export_cad(model, file_format)
                 st.success("CAD Model Generated Successfully!")
-                st.download_button("Download STL File", data="SampleData", file_name="model.stl")
+                with open(file_path, "rb") as f:
+                    st.download_button("Download CAD File", data=f.read(), file_name=f"model.{file_format}")
             except Exception as e:
                 st.error(f"Error generating CAD model: {e}")