Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
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Convert RVT/RFA files to Excel databases. Extract BIM element data, properties, and quantities.
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
BIM data inside RVT files needs to be extracted for:
Convert RVT files to structured Excel databases for analysis and reporting.
RvtExporter.exe <input_path> [export_mode] [options]
| Mode | Categories | Description |
|---|---|---|
basic | 309 | Essential structural elements |
standard | 724 | Standard BIM categories |
complete | 1209 | All Revit categories |
custom | User-defined | Specific categories only |
| Option | Description |
|---|---|
bbox | Include bounding box coordinates |
rooms | Include room associations |
schedules | Export all schedules to sheets |
sheets | Export sheets to PDF |
# Basic export
RvtExporter.exe "C:\Projects\Building.rvt" basic
# Complete with bounding boxes
RvtExporter.exe "C:\Projects\Building.rvt" complete bbox
# Full export with all options
RvtExporter.exe "C:\Projects\Building.rvt" complete bbox rooms schedules sheets
# Batch processing
for /R "C:\Projects" %f in (*.rvt) do RvtExporter.exe "%f" standard bbox
import subprocess
import pandas as pd
from pathlib import Path
from typing import List, Optional
class RevitExporter:
def __init__(self, exporter_path: str = "RvtExporter.exe"):
self.exporter = Path(exporter_path)
if not self.exporter.exists():
raise FileNotFoundError(f"RvtExporter not found: {exporter_path}")
def convert(self, rvt_file: str, mode: str = "complete",
options: List[str] = None) -> Path:
"""Convert Revit file to Excel."""
rvt_path = Path(rvt_file)
if not rvt_path.exists():
raise FileNotFoundError(f"Revit file not found: {rvt_file}")
cmd = [str(self.exporter), str(rvt_path), mode]
if options:
cmd.extend(options)
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode != 0:
raise RuntimeError(f"Export failed: {result.stderr}")
# Output file is same name with .xlsx extension
output_file = rvt_path.with_suffix('.xlsx')
return output_file
def batch_convert(self, folder: str, mode: str = "standard",
pattern: str = "*.rvt") -> List[Path]:
"""Convert all Revit files in folder."""
folder_path = Path(folder)
converted = []
for rvt_file in folder_path.glob(pattern):
try:
output = self.convert(str(rvt_file), mode)
converted.append(output)
print(f"Converted: {rvt_file.name}")
except Exception as e:
print(f"Failed: {rvt_file.name} - {e}")
return converted
def read_elements(self, xlsx_file: str) -> pd.DataFrame:
"""Read converted Excel as DataFrame."""
return pd.read_excel(xlsx_file, sheet_name="Elements")
def get_quantities(self, xlsx_file: str,
group_by: str = "Category") -> pd.DataFrame:
"""Get quantity summary grouped by category."""
df = self.read_elements(xlsx_file)
# Group and count
summary = df.groupby(group_by).agg({
'ElementId': 'count',
'Area': 'sum',
'Volume': 'sum'
}).reset_index()
summary.columns = [group_by, 'Count', 'Total_Area', 'Total_Volume']
return summary
| Sheet | Content |
|---|---|
| Elements | All BIM elements with properties |
| Categories | Element categories summary |
| Levels | Building levels |
| Materials | Material definitions |
| Parameters | Shared parameters |
| Column | Type | Description |
|---|---|---|
| ElementId | int | Unique Revit ID |
| Category | string | Element category |
| Family | string | Family name |
| Type | string | Type name |
| Level | string | Associated level |
| Area | float | Surface area (m²) |
| Volume | float | Volume (m³) |
| BBox_MinX/Y/Z | float | Bounding box min |
| BBox_MaxX/Y/Z | float | Bounding box max |
# Initialize exporter
exporter = RevitExporter("C:/Tools/RvtExporter.exe")
# Convert single file
xlsx = exporter.convert("C:/Projects/Office.rvt", "complete", ["bbox", "rooms"])
# Read and analyze
df = exporter.read_elements(str(xlsx))
print(f"Total elements: {len(df)}")
# Quantity summary
quantities = exporter.get_quantities(str(xlsx))
print(quantities)
# Export to CSV for further processing
df.to_csv("elements.csv", index=False)
# Full pipeline: Revit → Excel → Cost Estimate
from semantic_search import CWICRSemanticSearch
# 1. Convert Revit
exporter = RevitExporter()
xlsx = exporter.convert("project.rvt", "complete", ["bbox"])
# 2. Extract quantities
df = exporter.read_elements(str(xlsx))
quantities = df.groupby('Category')['Volume'].sum().to_dict()
# 3. Search CWICR for pricing
search = CWICRSemanticSearch()
costs = {}
for category, volume in quantities.items():
results = search.search_work_items(category, limit=5)
if not results.empty:
avg_price = results['unit_price'].mean()
costs[category] = volume * avg_price
print(f"Total estimate: ${sum(costs.values()):,.2f}")
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