Update app.py

app.py

@@ -1,67 +1,44 @@
 import streamlit as st
 from datasets import load_dataset
-import cadquery as cq
-import tempfile
-import os
+import json
+from cadquery import exporters, Workplane
 
-# Load the CADBench dataset
-dataset = load_dataset("FreedomIntelligence/CADBench")
+# Load CADBench dataset
+dataset = load_dataset("FreedomIntelligence/CADBench", split="train")
 
-# DFM Analysis Function (Simplified for Demo)
-def perform_dfm_analysis(file):
-    # Add logic to analyze the uploaded CAD file
-    st.write("Performing DFM Analysis...")
-    # Placeholder: Return success message
-    return {"status": "DFM Analysis Complete", "compatible": True}
-
-# Function to dynamically generate CAD model
-def generate_cad_model(template_name, parameters):
-    st.write(f"Generating CAD model for template: {template_name}")
-    # Example CAD model generation using cadquery (simplified)
-    part = cq.Workplane("XY").box(parameters["length"], parameters["width"], parameters["height"])
-    return part
-
-# Streamlit UI
+# Initialize the app
 st.title("Quick CAD Model Generator")
-
-# File Upload for DFM Analysis
-st.subheader("Case 1: Upload a Drawing for DFM Analysis")
-uploaded_file = st.file_uploader("Upload a CAD file (.stl, .step, .dwg)", type=["stl", "step", "dwg"])
-if uploaded_file:
-    with st.spinner("Processing DFM Analysis..."):
-        result = perform_dfm_analysis(uploaded_file)
-    st.write(result)
-
-# Predefined Template Selection
-st.subheader("Case 2: Select a Predefined Template")
-template_names = dataset["train"]["name"]
-template_selection = st.selectbox("Select a template", template_names)
-
-if template_selection:
-    # Get the template criteria
-    selected_template = dataset["train"].filter(lambda x: x["name"] == template_selection)[0]
-    criteria = selected_template["criteria"]  # Assuming criteria is a dictionary
-    user_inputs = {}
-
-    # Dynamic input collection
-    st.write("Please provide the following parameters:")
-    for key, value in criteria.items():
-        user_inputs[key] = st.text_input(f"{key} ({value})")
-
-    if st.button("Generate CAD Model"):
-        try:
-            cad_model = generate_cad_model(template_selection, user_inputs)
-            st.success("CAD Model Generated!")
-            
-            # Save CAD model in different formats
-            with tempfile.TemporaryDirectory() as tmpdir:
-                cad_model.exportStl(os.path.join(tmpdir, "model.stl"))
-                cad_model.exportStep(os.path.join(tmpdir, "model.step"))
-                # Add DWG export if needed
-                
-                # Download links
-                st.download_button("Download STL", open(os.path.join(tmpdir, "model.stl"), "rb").read(), "model.stl")
-                st.download_button("Download STEP", open(os.path.join(tmpdir, "model.step"), "rb").read(), "model.step")
-                # Add DWG download if implemented
-        except Exception as e:
-            st.error(f"Error generating CAD model: {e}")
+st.sidebar.title("Select Case")
+case = st.sidebar.radio("Choose a functionality:", ["DFM Analysis", "Predefined Template Selection"])
+
+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!")
+elif case == "Predefined Template Selection":
+    st.subheader("Case 2: Predefined Template Selection")
+    template_names = dataset["name"]
+    selected_template = st.selectbox("Select a template", template_names)
+
+    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"])
+        
+        responses = {}
+        for criterion, prompt in criteria.items():
+            prefilled_text = f"Enter {criterion} ({prompt}):"
+            response = st.text_input(prefilled_text, key=criterion)
+            if response:
+                responses[criterion] = response
+
+        if st.button("Generate CAD Model"):
+            try:
+                # Placeholder for CAD generation logic
+                st.success("CAD Model Generated Successfully!")
+                st.download_button("Download STL File", data="SampleData", file_name="model.stl")
+            except Exception as e:
+                st.error(f"Error generating CAD model: {e}")