--- name: "specification-extractor" description: "Extract structured data from construction specifications. Parse CSI sections, requirements, submittals, and product data from spec documents." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "📑", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}} ---

Specification Extractor for Construction

Overview

Extract structured data from construction specification documents. Parse CSI MasterFormat sections, identify requirements, submittals, product standards, and compile actionable data for estimating and procurement.

Business Case

Automated spec extraction enables:

• Faster Estimating: Quickly identify scope and requirements
• Procurement Accuracy: Extract exact product specifications
• Submittal Tracking: Identify all required submittals
• Compliance Checking: Verify specs against standards

Technical Implementation

from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional
import re
import pdfplumber
from pathlib import Path

@dataclass
class SpecSection:
    number: str  # e.g., "03 30 00"
    title: str
    part1_general: Dict[str, Any]
    part2_products: Dict[str, Any]
    part3_execution: Dict[str, Any]
    raw_text: str

@dataclass
class ProductRequirement:
    section: str
    manufacturer: str
    product_name: str
    model: str
    standards: List[str]
    properties: Dict[str, str]

@dataclass
class SubmittalRequirement:
    section: str
    submittal_type: str  # shop drawings, samples, product data, etc.
    description: str
    timing: str
    copies: int

@dataclass
class SpecExtractionResult:
    document_name: str
    total_pages: int
    sections: List[SpecSection]
    products: List[ProductRequirement]
    submittals: List[SubmittalRequirement]
    standards_referenced: List[str]

class SpecificationExtractor:
    """Extract structured data from construction specifications."""

    # CSI MasterFormat patterns
    CSI_SECTION_PATTERN = r'^(\d{2}\s?\d{2}\s?\d{2})\s*[-–]\s*(.+?)$'
    PART_PATTERN = r'^PART\s+(\d+)\s*[-–]\s*(.+?)$'
    ARTICLE_PATTERN = r'^(\d+\.\d+)\s+([A-Z][A-Z\s]+)$'

    # Submittal type keywords
    SUBMITTAL_TYPES = {
        'shop drawings': 'Shop Drawings',
        'product data': 'Product Data',
        'samples': 'Samples',
        'certificates': 'Certificates',
        'test reports': 'Test Reports',
        'manufacturer instructions': 'Manufacturer Instructions',
        'warranty': 'Warranty',
        'maintenance data': 'Maintenance Data',
        'mock-ups': 'Mock-ups',
    }

    # Common standard organizations
    STANDARD_PATTERNS = [
        r'ASTM\s+[A-Z]\d+',
        r'ANSI\s+[A-Z]?\d+',
        r'ACI\s+\d+',
        r'AISC\s+\d+',
        r'AWS\s+[A-Z]\d+',
        r'ASCE\s+\d+',
        r'UL\s+\d+',
        r'FM\s+\d+',
        r'NFPA\s+\d+',
        r'IBC\s+\d+',
    ]

    def __init__(self):
        self.sections: Dict[str, SpecSection] = {}

    def extract_from_pdf(self, pdf_path: str) -> SpecExtractionResult:
        """Extract specification data from PDF."""
        path = Path(pdf_path)

        all_text = ""
        page_count = 0

        with pdfplumber.open(pdf_path) as pdf:
            page_count = len(pdf.pages)
            for page in pdf.pages:
                text = page.extract_text() or ""
                all_text += text + "\n\n"

        # Parse sections
        sections = self._parse_sections(all_text)

        # Extract products
        products = self._extract_products(sections)

        # Extract submittals
        submittals = self._extract_submittals(sections)

        # Extract standards
        standards = self._extract_standards(all_text)

        return SpecExtractionResult(
            document_name=path.name,
            total_pages=page_count,
            sections=sections,
            products=products,
            submittals=submittals,
            standards_referenced=standards
        )

    def _parse_sections(self, text: str) -> List[SpecSection]:
        """Parse CSI sections from specification text."""
        sections = []
        lines = text.split('\n')

        current_section = None
        current_part = None
        current_content = []

        for line in lines:
            line = line.strip()
            if not line:
                continue

            # Check for section header
            section_match = re.match(self.CSI_SECTION_PATTERN, line, re.IGNORECASE)
            if section_match:
                # Save previous section
                if current_section:
                    sections.append(self._finalize_section(current_section, current_content))

                current_section = {
                    'number': section_match.group(1).replace(' ', ''),
                    'title': section_match.group(2).strip(),
                    'parts': {}
                }
                current_content = []
                current_part = None
                continue

            # Check for part header
            part_match = re.match(self.PART_PATTERN, line, re.IGNORECASE)
            if part_match and current_section:
                part_num = part_match.group(1)
                part_name = part_match.group(2).strip()
                current_part = f"part{part_num}"
                current_section['parts'][current_part] = {
                    'name': part_name,
                    'content': []
                }
                continue

            # Add content to current part
            if current_section and current_part:
                current_section['parts'][current_part]['content'].append(line)
            elif current_section:
                current_content.append(line)

        # Save last section
        if current_section:
            sections.append(self._finalize_section(current_section, current_content))

        return sections

    def _finalize_section(self, section_data: Dict, general_content: List[str]) -> SpecSection:
        """Finalize a section with parsed parts."""
        parts = section_data.get('parts', {})

        part1 = self._parse_part_content(parts.get('part1', {}).get('content', []))
        part2 = self._parse_part_content(parts.get('part2', {}).get('content', []))
        part3 = self._parse_part_content(parts.get('part3', {}).get('content', []))

        return SpecSection(
            number=section_data['number'],
            title=section_data['title'],
            part1_general=part1,
            part2_products=part2,
            part3_execution=part3,
            raw_text='\n'.join(general_content)
        )

    def _parse_part_content(self, content: List[str]) -> Dict[str, Any]:
        """Parse part content into structured data."""
        result = {
            'articles': {},
            'items': []
        }

        current_article = None

        for line in content:
            # Check for article header
            article_match = re.match(self.ARTICLE_PATTERN, line)
            if article_match:
                current_article = article_match.group(1)
                result['articles'][current_article] = {
                    'title': article_match.group(2),
                    'items': []
                }
                continue

            # Add to current article or general items
            if current_article and current_article in result['articles']:
                result['articles'][current_article]['items'].append(line)
            else:
                result['items'].append(line)

        return result

    def _extract_products(self, sections: List[SpecSection]) -> List[ProductRequirement]:

...