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Opencode Instructions for CAD2DATA Repository

Repository Overview

CAD2DATA Pipeline - open-source tools for construction data automation. All tools are designed to be integrated into any solution via CLI.

Core Concept

Convert proprietary CAD/BIM files to open formats:

  • Revit (.rvt) -> XLSX, DAE, PDF, IFC
  • IFC (.ifc) -> XLSX, DAE
  • DWG (.dwg) -> XLSX, PDF
  • DGN (.dgn) -> XLSX

No vendor lock-in. No licenses required. Offline processing.

Converters

Converter Input Output
RvtExporter.exe .rvt, .rfa (2015-2026) XLSX + DAE + PDF + Schedules
RVT2IFCconverter.exe .rvt, .rfa IFC2x3, IFC4, IFC4.3, IFCXML, IFCZIP, HDF5
IfcExporter.exe .ifc (2x3, 4, 4x1, 4x3) XLSX + DAE
DwgExporter.exe .dwg (1983-2026) XLSX + PDF
DgnExporter.exe .dgn (V7, V8) XLSX

CLI Examples

# Revit to Excel + 3D
RvtExporter.exe "model.rvt"

# Revit with all options
RvtExporter.exe "model.rvt" complete bbox schedule sheets2pdf

# Revit to IFC
RVT2IFCconverter.exe "model.rvt"

# IFC to Excel + 3D
IfcExporter.exe "model.ifc"

# DWG to Excel + PDF
DwgExporter.exe "drawing.dwg"

# DGN to Excel
DgnExporter.exe "design.dgn"

Output Formats

Format Description
XLSX Excel database - elements as rows, properties as columns
DAE Collada 3D geometry with element IDs matching XLSX
PDF Drawings and sheets
IFC Open BIM standard (multiple versions)
HTML Interactive reports (via n8n workflows)

Philosophy

Read DATA_DRIVEN_CONSTRUCTION_BOOK.txt in this folder - explains data-driven approach to construction automation.

n8n Workflows - Process Logic Templates

The n8n_*.json files are visual representations of process logic - a foundation that can be implemented in any language or application.

# Process Logic
1 Basic conversion flow
2 Advanced settings handling
3 Batch processing + reporting
4 BIM validation rules
5 AI classification (LLM + RAG)
6 Cost estimation pipeline
7 Carbon footprint calculation
8 ETL for LLM preparation
9 QTO report generation

Implement this logic in: Python, JavaScript, C#, Go, Rust, or any language that can call CLI and process XLSX/JSON.

Integration Patterns

Python

import subprocess
import pandas as pd

# Convert
subprocess.run(["RvtExporter.exe", "model.rvt", "complete", "bbox"])

# Analyze
df = pd.read_excel("model_Elements.xlsx")
summary = df.groupby("Category")["Volume"].sum()

PowerShell

Get-ChildItem "*.rvt" | ForEach-Object {
    & "RvtExporter.exe" $_.FullName complete bbox
}

Node.js

const { execSync } = require('child_process');
execSync('RvtExporter.exe "model.rvt" complete bbox');

Best Practices

  1. Use complete mode for full data extraction (1209 categories)
  2. Enable bbox for spatial analysis
  3. Validate XLSX output before downstream processing
  4. DAE element IDs match XLSX for data linking
  5. Use n8n workflows for complex automation

For Code Generation

When generating code for this repository:

  • Use CLI calls with subprocess/execSync
  • Parse XLSX with pandas/openpyxl
  • Generate HTML reports for visualization
  • Follow existing n8n workflow patterns

All tools are open-source (MIT) and can be freely integrated into your solutions.