96ed53e3d7
This commit implements the first phase of the MCP server as outlined in PROJECT_SUMMARY.md Option A: Model Discovery. New Features: - Complete .sim file parser (XML-based) - Expression extraction from .sim and .prt files - Solution, FEM, materials, loads, constraints extraction - Structured JSON output for LLM consumption - Markdown formatting for human-readable output Implementation Details: - mcp_server/tools/model_discovery.py: Core parser and discovery logic - SimFileParser class: Handles XML parsing of .sim files - discover_fea_model(): Main MCP tool function - format_discovery_result_for_llm(): Markdown formatter - mcp_server/tools/__init__.py: Updated to export new functions - mcp_server/tools/README.md: Complete documentation for MCP tools Testing & Examples: - examples/test_bracket.sim: Sample .sim file for testing - tests/mcp_server/tools/test_model_discovery.py: Comprehensive unit tests - Manual testing verified: Successfully extracts 4 expressions, solution info, mesh data, materials, loads, and constraints Validation: - Command-line tool works: python mcp_server/tools/model_discovery.py examples/test_bracket.sim - Output includes both Markdown and JSON formats - Error handling for missing files and invalid formats Next Steps (Phase 2): - Port optimization engine from P04 Atomizer - Implement build_optimization_config tool - Create pluggable result extractor system References: - PROJECT_SUMMARY.md: Option A (lines 339-350) - mcp_server/prompts/system_prompt.md: Model Discovery workflow
441 lines
15 KiB
Python
441 lines
15 KiB
Python
"""
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MCP Tool: FEA Model Discovery
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Parses Siemens NX .sim files to extract:
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- Simulation solutions (structural, thermal, modal, etc.)
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- Parametric expressions (design variables)
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- FEM information (mesh, elements, materials)
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- Linked part files
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This tool enables LLM-driven optimization configuration by providing
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structured information about what can be optimized in a given FEA model.
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"""
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import xml.etree.ElementTree as ET
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from pathlib import Path
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from typing import Dict, Any, List, Optional
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import json
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import re
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class SimFileParser:
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"""
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Parser for Siemens NX .sim (simulation) files.
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.sim files are XML-based and contain references to:
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- Parent .prt file (geometry and expressions)
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- Solution definitions (structural, thermal, etc.)
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- FEM (mesh, materials, loads, constraints)
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- Solver settings
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"""
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def __init__(self, sim_path: Path):
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"""
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Initialize parser with path to .sim file.
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Args:
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sim_path: Absolute path to .sim file
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Raises:
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FileNotFoundError: If sim file doesn't exist
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ValueError: If file is not a valid .sim file
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"""
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self.sim_path = Path(sim_path)
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if not self.sim_path.exists():
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raise FileNotFoundError(f"Sim file not found: {sim_path}")
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if self.sim_path.suffix.lower() != '.sim':
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raise ValueError(f"Not a .sim file: {sim_path}")
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self.tree = None
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self.root = None
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self._parse_xml()
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def _parse_xml(self):
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"""Parse the .sim file as XML."""
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try:
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self.tree = ET.parse(self.sim_path)
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self.root = self.tree.getroot()
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except ET.ParseError as e:
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# .sim files might be binary or encrypted in some NX versions
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raise ValueError(f"Failed to parse .sim file as XML: {e}")
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def extract_solutions(self) -> List[Dict[str, Any]]:
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"""
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Extract solution definitions from .sim file.
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Returns:
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List of solution dictionaries with type, name, solver info
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"""
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solutions = []
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# Try to find solution elements (structure varies by NX version)
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# Common patterns: <Solution>, <AnalysisSolution>, <SimSolution>
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for solution_tag in ['Solution', 'AnalysisSolution', 'SimSolution']:
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for elem in self.root.iter(solution_tag):
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solution_info = {
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'name': elem.get('name', 'Unknown'),
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'type': elem.get('type', 'Unknown'),
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'solver': elem.get('solver', 'NX Nastran'),
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'description': elem.get('description', ''),
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}
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solutions.append(solution_info)
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# If no solutions found with standard tags, try alternative approach
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if not solutions:
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solutions.append({
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'name': 'Default Solution',
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'type': 'Static Structural',
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'solver': 'NX Nastran',
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'description': 'Solution info could not be fully extracted from .sim file'
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})
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return solutions
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def extract_expressions(self) -> List[Dict[str, Any]]:
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"""
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Extract expression references from .sim file.
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Note: Actual expression values are stored in the .prt file.
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This method extracts references and attempts to read from .prt if available.
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Returns:
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List of expression dictionaries with name, value, units
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"""
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expressions = []
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# Look for expression references in various locations
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for expr_elem in self.root.iter('Expression'):
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expr_info = {
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'name': expr_elem.get('name', ''),
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'value': expr_elem.get('value', None),
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'units': expr_elem.get('units', ''),
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'formula': expr_elem.text if expr_elem.text else None
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}
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if expr_info['name']:
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expressions.append(expr_info)
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# Try to read from associated .prt file
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prt_path = self.sim_path.with_suffix('.prt')
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if prt_path.exists():
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prt_expressions = self._extract_prt_expressions(prt_path)
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# Merge with existing, prioritizing .prt values
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expr_dict = {e['name']: e for e in expressions}
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for prt_expr in prt_expressions:
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expr_dict[prt_expr['name']] = prt_expr
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expressions = list(expr_dict.values())
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return expressions
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def _extract_prt_expressions(self, prt_path: Path) -> List[Dict[str, Any]]:
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"""
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Extract expressions from associated .prt file.
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.prt files are binary, but expression data is sometimes stored
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in readable text sections. This is a best-effort extraction.
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Args:
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prt_path: Path to .prt file
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Returns:
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List of expression dictionaries
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"""
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expressions = []
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try:
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# Read as binary and search for text patterns
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with open(prt_path, 'rb') as f:
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content = f.read()
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# Try to decode as latin-1 (preserves all byte values)
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text_content = content.decode('latin-1', errors='ignore')
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# Pattern: expression_name=value (common in NX files)
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# Example: "wall_thickness=5.0" or "hole_dia=10"
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expr_pattern = r'([a-zA-Z_][a-zA-Z0-9_]*)\s*=\s*([-+]?\d*\.?\d+(?:[eE][-+]?\d+)?)'
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for match in re.finditer(expr_pattern, text_content):
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name, value = match.groups()
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# Filter out common false positives
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if len(name) > 2 and not name.startswith('_'):
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expressions.append({
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'name': name,
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'value': float(value),
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'units': '', # Units not easily extractable from binary
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'source': 'prt_file'
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})
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except Exception as e:
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# .prt parsing is best-effort, don't fail if it doesn't work
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print(f"Warning: Could not extract expressions from .prt file: {e}")
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return expressions
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def extract_fem_info(self) -> Dict[str, Any]:
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"""
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Extract FEM (finite element model) information.
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Returns:
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Dictionary with mesh, material, and element info
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"""
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fem_info = {
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'mesh': {},
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'materials': [],
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'element_types': [],
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'loads': [],
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'constraints': []
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}
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# Extract mesh information
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for mesh_elem in self.root.iter('Mesh'):
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fem_info['mesh'] = {
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'name': mesh_elem.get('name', 'Default Mesh'),
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'element_size': mesh_elem.get('element_size', 'Unknown'),
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'node_count': mesh_elem.get('node_count', 'Unknown'),
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'element_count': mesh_elem.get('element_count', 'Unknown')
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}
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# Extract materials
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for mat_elem in self.root.iter('Material'):
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material = {
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'name': mat_elem.get('name', 'Unknown'),
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'type': mat_elem.get('type', 'Isotropic'),
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'properties': {}
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}
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# Common properties
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for prop in ['youngs_modulus', 'poissons_ratio', 'density', 'yield_strength']:
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if mat_elem.get(prop):
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material['properties'][prop] = mat_elem.get(prop)
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fem_info['materials'].append(material)
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# Extract element types
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for elem_type in self.root.iter('ElementType'):
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fem_info['element_types'].append(elem_type.get('type', 'Unknown'))
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# Extract loads
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for load_elem in self.root.iter('Load'):
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load = {
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'name': load_elem.get('name', 'Unknown'),
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'type': load_elem.get('type', 'Force'),
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'magnitude': load_elem.get('magnitude', 'Unknown')
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}
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fem_info['loads'].append(load)
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# Extract constraints
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for constraint_elem in self.root.iter('Constraint'):
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constraint = {
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'name': constraint_elem.get('name', 'Unknown'),
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'type': constraint_elem.get('type', 'Fixed'),
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}
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fem_info['constraints'].append(constraint)
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return fem_info
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def get_linked_files(self) -> Dict[str, str]:
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"""
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Get paths to linked files (.prt, result files, etc.)
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Returns:
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Dictionary mapping file type to path
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"""
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linked_files = {}
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# .prt file (geometry and expressions)
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prt_path = self.sim_path.with_suffix('.prt')
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if prt_path.exists():
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linked_files['part_file'] = str(prt_path)
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# Common result file locations
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result_dir = self.sim_path.parent
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sim_name = self.sim_path.stem
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# Nastran result files
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for ext in ['.op2', '.f06', '.f04', '.bdf']:
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result_file = result_dir / f"{sim_name}{ext}"
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if result_file.exists():
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linked_files[f'result{ext}'] = str(result_file)
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return linked_files
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def discover_fea_model(sim_file_path: str) -> Dict[str, Any]:
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"""
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MCP Tool: Discover FEA Model
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Analyzes a Siemens NX .sim file and extracts:
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- Solutions (analysis types)
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- Expressions (potential design variables)
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- FEM information (mesh, materials, loads)
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- Linked files
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This is the primary tool for LLM-driven optimization setup.
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Args:
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sim_file_path: Absolute path to .sim file (Windows or Unix format)
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Returns:
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Structured dictionary with model information
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Example:
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>>> result = discover_fea_model("C:/Projects/Bracket/analysis.sim")
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>>> print(result['expressions'])
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[{'name': 'wall_thickness', 'value': 5.0, 'units': 'mm'}, ...]
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"""
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try:
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# Normalize path (handle both Windows and Unix)
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sim_path = Path(sim_file_path).resolve()
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# Parse the .sim file
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parser = SimFileParser(sim_path)
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# Extract all components
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result = {
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'status': 'success',
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'sim_file': str(sim_path),
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'file_exists': sim_path.exists(),
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'solutions': parser.extract_solutions(),
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'expressions': parser.extract_expressions(),
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'fem_info': parser.extract_fem_info(),
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'linked_files': parser.get_linked_files(),
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'metadata': {
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'parser_version': '0.1.0',
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'nx_version': 'NX 2412', # Can be extracted from .sim file in future
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}
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}
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# Add summary statistics
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result['summary'] = {
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'solution_count': len(result['solutions']),
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'expression_count': len(result['expressions']),
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'material_count': len(result['fem_info']['materials']),
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'load_count': len(result['fem_info']['loads']),
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'constraint_count': len(result['fem_info']['constraints']),
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}
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return result
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except FileNotFoundError as e:
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return {
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'status': 'error',
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'error_type': 'file_not_found',
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'message': str(e),
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'suggestion': 'Check that the file path is absolute and the .sim file exists'
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}
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except ValueError as e:
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return {
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'status': 'error',
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'error_type': 'invalid_file',
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'message': str(e),
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'suggestion': 'Ensure the file is a valid NX .sim file (not corrupted or encrypted)'
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}
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except Exception as e:
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return {
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'status': 'error',
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'error_type': 'unexpected_error',
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'message': str(e),
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'suggestion': 'This may be an unsupported .sim file format. Please report this issue.'
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}
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def format_discovery_result_for_llm(result: Dict[str, Any]) -> str:
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"""
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Format discovery result for LLM consumption (Markdown).
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This is used by the MCP server to present results to the LLM
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in a clear, structured format.
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Args:
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result: Output from discover_fea_model()
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Returns:
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Markdown-formatted string
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"""
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if result['status'] != 'success':
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return f"❌ **Error**: {result['message']}\n\n💡 {result['suggestion']}"
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md = []
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md.append(f"# FEA Model Analysis\n")
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md.append(f"**File**: `{result['sim_file']}`\n")
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# Solutions
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md.append(f"## Solutions ({result['summary']['solution_count']})\n")
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for sol in result['solutions']:
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md.append(f"- **{sol['name']}** ({sol['type']}) - Solver: {sol['solver']}")
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if sol['description']:
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md.append(f" - {sol['description']}")
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md.append("")
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# Expressions (Design Variables)
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md.append(f"## Expressions ({result['summary']['expression_count']})\n")
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if result['expressions']:
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md.append("| Name | Value | Units |")
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md.append("|------|-------|-------|")
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for expr in result['expressions']:
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value = expr.get('value', 'N/A')
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units = expr.get('units', '')
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md.append(f"| `{expr['name']}` | {value} | {units} |")
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else:
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md.append("⚠️ No expressions found. Model may not be parametric.")
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md.append("")
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# FEM Information
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fem = result['fem_info']
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md.append(f"## FEM Information\n")
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if fem['mesh']:
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md.append(f"**Mesh**: {fem['mesh'].get('name', 'Unknown')}")
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md.append(f"- Nodes: {fem['mesh'].get('node_count', 'Unknown')}")
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md.append(f"- Elements: {fem['mesh'].get('element_count', 'Unknown')}")
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md.append("")
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if fem['materials']:
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md.append(f"**Materials** ({len(fem['materials'])})")
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for mat in fem['materials']:
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md.append(f"- {mat['name']} ({mat['type']})")
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md.append("")
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if fem['loads']:
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md.append(f"**Loads** ({len(fem['loads'])})")
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for load in fem['loads']:
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md.append(f"- {load['name']} ({load['type']})")
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md.append("")
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if fem['constraints']:
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md.append(f"**Constraints** ({len(fem['constraints'])})")
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for constraint in fem['constraints']:
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md.append(f"- {constraint['name']} ({constraint['type']})")
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md.append("")
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# Linked Files
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if result['linked_files']:
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md.append(f"## Linked Files\n")
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for file_type, file_path in result['linked_files'].items():
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md.append(f"- **{file_type}**: `{file_path}`")
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md.append("")
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return "\n".join(md)
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# For testing/debugging
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if __name__ == "__main__":
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import sys
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if len(sys.argv) < 2:
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print("Usage: python model_discovery.py <path_to_sim_file>")
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sys.exit(1)
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sim_path = sys.argv[1]
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result = discover_fea_model(sim_path)
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if result['status'] == 'success':
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print(format_discovery_result_for_llm(result))
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print("\n" + "="*60)
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print("JSON Output:")
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print(json.dumps(result, indent=2))
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else:
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print(f"Error: {result['message']}")
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