468 lines
21 KiB
Python
468 lines
21 KiB
Python
from __future__ import annotations
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import copy
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from functools import lru_cache
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import json
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import math
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import re
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import sys
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from pathlib import Path
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from typing import Any
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from jsonschema import Draft202012Validator
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from jsonschema.exceptions import SchemaError
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from vendor.cdsl_preview_runtime import step_to_glb
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from app.settings import Settings
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def load_engine(settings: Settings) -> Any:
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parent = str(settings.engine_root.parent)
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if parent not in sys.path:
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sys.path.insert(0, parent)
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import cdsl_engine
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return cdsl_engine
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def _walk(value: Any) -> list[tuple[str, Any]]:
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result: list[tuple[str, Any]] = []
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if isinstance(value, dict):
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for key, child in value.items():
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result.append((str(key), child))
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result.extend(_walk(child))
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elif isinstance(value, list):
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for child in value:
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result.extend(_walk(child))
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return result
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@lru_cache(maxsize=16)
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def _read_schema_document(path_value: str, modified_ns: int) -> dict[str, Any]:
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"""Load an immutable runtime schema once per on-disk version."""
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del modified_ns # The mtime is intentionally part of the cache key.
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schema_path = Path(path_value)
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try:
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schema = json.loads(schema_path.read_text(encoding="utf-8"))
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except (OSError, json.JSONDecodeError) as error:
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raise RuntimeError("The local engine schema document is unavailable or invalid") from error
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if not isinstance(schema, dict) or not isinstance(schema.get("feature_atomic_ids"), dict):
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raise RuntimeError("The local engine schema has no feature_atomic_ids contract")
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return schema
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def _engine_schema(engine: Any) -> dict[str, Any]:
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schema_path = Path(str(engine.__file__)).with_name("profile_schema.json")
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try:
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modified_ns = schema_path.stat().st_mtime_ns
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except OSError as error:
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raise RuntimeError("The local engine schema document is unavailable or invalid") from error
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return _read_schema_document(str(schema_path), modified_ns)
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def feature_atomic_contract(engine: Any, atomic_id: str) -> dict[str, Any]:
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"""Return the runtime-supported parameter contract for one atomic feature."""
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schema = _engine_schema(engine)
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normalized_id = str(atomic_id or "").strip()
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contracts = schema["feature_atomic_ids"]
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contract = contracts.get(normalized_id)
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registered = {str(item) for item in getattr(engine, "SUPPORTED_ATOMIC_IDS", ())}
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declared = {str(item) for item in schema.get("runtime_supported_atomic_ids") or ()}
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if normalized_id not in registered or normalized_id not in declared or not isinstance(contract, dict):
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raise ValueError(f"Unsupported runtime atomic_id: {normalized_id}")
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required = contract.get("required_params") or []
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optional = contract.get("optional_params") or []
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if not all(isinstance(item, str) and item for item in [*required, *optional]):
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raise RuntimeError(f"Runtime feature contract is invalid for {normalized_id}")
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return {
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"atomic_id": normalized_id,
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"summary": str(contract.get("summary") or ""),
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"required_params": list(dict.fromkeys(required)),
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"optional_params": [item for item in dict.fromkeys(optional) if item not in required],
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"position_format": str(contract.get("position_format") or ""),
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"requires_sketch": contract.get("requires_sketch") is True,
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"selector_slot": copy.deepcopy(contract.get("selector_slot")) if isinstance(contract.get("selector_slot"), dict) else None,
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}
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@lru_cache(maxsize=16)
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def _cdsl_validator(path_value: str, modified_ns: int) -> Draft202012Validator:
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"""Compile the JSON Schema once per runtime schema revision."""
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del modified_ns
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schema_path = Path(path_value)
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try:
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schema = json.loads(schema_path.read_text(encoding="utf-8"))
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Draft202012Validator.check_schema(schema)
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except (OSError, json.JSONDecodeError, SchemaError) as error:
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raise RuntimeError("The local CDSL JSON Schema is unavailable or invalid") from error
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return Draft202012Validator(schema)
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def _cdsl_schema_path(engine: Any) -> Path:
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document = _engine_schema(engine)
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schema_name = str(document.get("cdsl_json_schema_file") or "")
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if not schema_name or Path(schema_name).name != schema_name:
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raise RuntimeError("The local engine schema has an invalid CDSL JSON Schema path")
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return Path(str(engine.__file__)).with_name(schema_name)
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def load_cdsl_json_schema(engine: Any) -> dict[str, Any]:
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schema_path = _cdsl_schema_path(engine)
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try:
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schema = json.loads(schema_path.read_text(encoding="utf-8"))
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Draft202012Validator.check_schema(schema)
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except (OSError, json.JSONDecodeError, SchemaError) as error:
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raise RuntimeError("The local CDSL JSON Schema is unavailable or invalid") from error
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return schema
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def _validate_cdsl_json_schema(cdsl: dict[str, Any], engine: Any) -> None:
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schema_path = _cdsl_schema_path(engine)
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try:
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validator = _cdsl_validator(str(schema_path), schema_path.stat().st_mtime_ns)
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except OSError as error:
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raise RuntimeError("The local CDSL JSON Schema is unavailable or invalid") from error
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errors = sorted(validator.iter_errors(cdsl), key=lambda error: (list(error.absolute_path), error.message))
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if not errors:
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return
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error = errors[0]
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location = "$" + "".join(
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f"[{item}]" if isinstance(item, int) else f".{item}"
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for item in error.absolute_path
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)
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raise ValueError(f"CDSL schema violation at {location}: {error.message}")
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def validate_cdsl(cdsl: dict[str, Any], engine: Any) -> None:
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if not isinstance(cdsl, dict):
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raise ValueError("CDSL must be a JSON object")
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if cdsl.get("schema") != "cad.cdsl.llm.v1":
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raise ValueError("Unsupported CDSL schema")
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_validate_cdsl_json_schema(cdsl, engine)
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part_id = str(cdsl.get("part_id") or "")
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if not re.fullmatch(r"[a-zA-Z0-9_-]{3,80}", part_id):
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raise ValueError("part_id must use letters, numbers, underscores, or hyphens")
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forbidden = {"compiler_context", "unknown_shape", "complex_arc_shape", "contour_edges_mm", "contour_regions_mm", "entities"}
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for key, value in _walk(cdsl):
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if key in forbidden or (isinstance(value, str) and value in {"unknown_shape", "complex_arc_shape"}):
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raise ValueError(f"Training-unsafe CDSL field: {key}")
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features = cdsl.get("features")
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sketches = cdsl.get("geometry", {}).get("sketches")
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if not isinstance(features, list) or not features or not isinstance(sketches, list):
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raise ValueError("CDSL requires a feature list and a geometry.sketches array")
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sketch_ids = {str(sketch.get("id")) for sketch in sketches}
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semantic_contract = _engine_schema(engine)
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atomic_contracts = semantic_contract["feature_atomic_ids"]
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declared_atomic_ids = {
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str(atomic_id)
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for atomic_id in semantic_contract.get("runtime_supported_atomic_ids", atomic_contracts)
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}
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registered_atomic_ids = {str(atomic_id) for atomic_id in getattr(engine, "SUPPORTED_ATOMIC_IDS", ())}
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supported_atomic_ids = sorted(declared_atomic_ids & registered_atomic_ids)
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feature_ids: set[str] = set()
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for feature in features:
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fid = str(feature.get("id") or "")
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if not fid or fid in feature_ids:
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raise ValueError("Feature ids must be unique")
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feature_ids.add(fid)
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atomic_id = str(feature.get("atomic_id") or "")
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if not atomic_id:
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raise ValueError(f"Feature {fid} has no atomic_id")
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contract = atomic_contracts.get(atomic_id)
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if atomic_id not in supported_atomic_ids or not isinstance(contract, dict):
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if feature.get("execution_status") == "deferred":
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raise ValueError(f"Feature {fid} is deferred and cannot be rebuilt by the current engine")
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raise ValueError(
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f"Unsupported CDSL atomic_id: {atomic_id}. Supported: {', '.join(supported_atomic_ids)}"
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)
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params = feature.get("params")
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if not isinstance(params, dict):
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raise ValueError(f"Feature {fid} params must be an object")
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for parameter_name in contract.get("required_params") or []:
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if params.get(parameter_name) is None:
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raise ValueError(f"Feature {fid} ({atomic_id}) is missing required parameter: {parameter_name}")
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if atomic_id.startswith("extrude_") and float(params.get("distance_mm") or 0) <= 0:
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raise ValueError(f"Feature {fid} ({atomic_id}) requires distance_mm > 0 for runtime rebuild")
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if atomic_id.startswith("revolve_") and float(params.get("angle_deg") or 0) <= 0:
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raise ValueError(f"Feature {fid} ({atomic_id}) requires angle_deg > 0 for runtime rebuild")
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if contract.get("requires_sketch") and str(feature.get("sketch_id") or "") not in sketch_ids:
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raise ValueError(f"Feature {fid} ({atomic_id}) requires a valid sketch_id")
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for dependency in feature.get("depends_on") or []:
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if dependency not in feature_ids:
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raise ValueError(f"Feature {fid} has a forward or missing dependency")
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for sketch in sketches:
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profile = sketch.get("profile")
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if sketch.get("profile_from"):
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continue
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if not isinstance(profile, dict):
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raise ValueError(f"Sketch {sketch.get('id')} has no self-contained profile")
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profile_type = str(profile.get("type") or "")
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if profile_type == "polygon":
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if not profile.get("vertices"):
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raise ValueError("Polygon profiles require vertices")
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elif profile_type not in engine.SHAPE_GENERATORS:
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raise ValueError(f"Unsupported CDSL profile: {profile_type}")
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try:
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analysis = engine.analyze_cdsl(copy.deepcopy(cdsl))
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except Exception as error:
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raise ValueError(f"CDSL engine runtime preflight failed: {error}") from error
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if not analysis.runtime_eligible:
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first = next((result for result in analysis.feature_results if not result.executable), None)
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if first is None:
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raise ValueError(f"CDSL engine runtime preflight failed: {analysis.document_blockers[0].code}")
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blockers = ", ".join(blocker.code for blocker in first.blockers)
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raise ValueError(f"CDSL engine runtime preflight failed: feature {first.feature_id}: {blockers}")
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def _parameter_id(path: list[str]) -> str:
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return "param_" + "_".join(re.sub(r"[^a-zA-Z0-9]+", "_", item).strip("_") for item in path)
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def _parameter_label(path: list[str]) -> str:
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return " / ".join(path[-2:]).replace("_mm", " (mm)").replace("_", " ")
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def _derived_parameters(cdsl: dict[str, Any]) -> list[dict[str, Any]]:
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parameters: list[dict[str, Any]] = []
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def add(path: list[str], value: Any, group: str) -> None:
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if isinstance(value, bool) or not isinstance(value, (int, float)) or not math.isfinite(float(value)):
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return
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number = float(value)
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magnitude = max(abs(number), 1.0)
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parameters.append({
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"id": _parameter_id(path),
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"name": ".".join(path),
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"display_name": _parameter_label(path),
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"path": path,
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"value": number,
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"default_value": number,
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"minimum": 0.01 if number >= 0 else -magnitude * 10,
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"maximum": magnitude * 10,
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"step": 0.1 if abs(number) < 100 else 1.0,
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"precision": 2,
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"unit": "mm" if path[-1].endswith("_mm") else "",
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"group": group,
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"editable": True,
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})
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for feature_index, feature in enumerate(cdsl.get("features") or []):
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for key, value in (feature.get("params") or {}).items():
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add(["features", str(feature_index), "params", str(key)], value, "Features")
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for sketch_index, sketch in enumerate(cdsl.get("geometry", {}).get("sketches") or []):
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profile = sketch.get("profile") or {}
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def walk_profile(value: Any, path: list[str]) -> None:
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if isinstance(value, dict):
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for key, child in value.items():
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walk_profile(child, [*path, str(key)])
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elif isinstance(value, list):
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# Coordinates are topology anchors, not user-facing dimensions.
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return
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else:
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add(path, value, "Sketches")
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walk_profile(profile, ["geometry", "sketches", str(sketch_index), "profile"])
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return parameters
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def parameter_contract(cdsl: dict[str, Any]) -> dict[str, Any]:
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declared = cdsl.get("meta", {}).get("editable_parameters")
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if isinstance(declared, list) and declared:
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values = [item for item in declared if isinstance(item, dict) and isinstance(item.get("path"), list)]
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if values:
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return {"schema_version": "1.0", "parameters": values, "source": "declared"}
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return {"schema_version": "1.0", "parameters": _derived_parameters(cdsl), "source": "derived"}
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def topology_snapshot(
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engine_result: dict[str, Any],
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*,
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task_id: str = "",
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revision_id: str = "",
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preview: dict[str, Any] | None = None,
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) -> dict[str, Any]:
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raw_records = [
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raw for raw in engine_result.get("topology_records") or ()
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if isinstance(raw, dict) and raw.get("record_id") and raw.get("kind")
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]
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active_body_id = next(
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(
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str(result.get("body_id"))
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for result in reversed(engine_result.get("feature_results") or ())
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if isinstance(result, dict) and result.get("body_id")
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),
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"",
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)
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if not active_body_id:
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active_body_id = next(
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(
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str(raw.get("body_id"))
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for raw in reversed(raw_records)
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if raw.get("kind") == "body" and raw.get("body_id")
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),
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"",
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)
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# The runtime retains historical B-rep records for provenance, but only
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# the final body can resolve face, edge, vertex, and body selectors.
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active_records = [
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raw for raw in raw_records
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if not active_body_id
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or raw.get("kind") in {"plane", "axis"}
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or str(raw.get("body_id") or "") == active_body_id
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]
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records: list[dict[str, Any]] = []
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for raw in active_records:
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kind = str(raw.get("kind"))
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records.append({
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"record_id": str(raw["record_id"]),
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"kind": kind,
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"feature_id": str(raw.get("feature_id") or ""),
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"body_id": str(raw.get("body_id") or "") or None,
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"owner_feature_ids": [str(item) for item in raw.get("owner_feature_ids") or () if str(item)],
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"geometry": copy.deepcopy(raw.get("geometry") or {}),
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"executable": kind in {"body", "face", "edge", "vertex", "plane", "axis"},
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"synthetic": False,
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})
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# Preview/B-rep fallback faces are useful for visual explanation only.
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# Keep them in the unified audit snapshot, but never expose them as
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# executable selector candidates.
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if not any(item.get("kind") == "face" for item in records):
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for index, raw in enumerate((preview or {}).get("topology_faces") or ()):
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if not isinstance(raw, dict):
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continue
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record_id = str(raw.get("id") or f"synthetic:face:{index}")
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center = raw.get("center")
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normal = raw.get("normal")
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raw_bbox = raw.get("bbox")
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if isinstance(raw_bbox, dict) and isinstance(raw_bbox.get("min"), list) and isinstance(raw_bbox.get("max"), list):
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raw_bbox = [*raw_bbox["min"], *raw_bbox["max"]]
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geometry = {
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"surface_type": str(raw.get("surface_type") or "unknown"),
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"center_mm": copy.deepcopy(center) if isinstance(center, list) else None,
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"normal": copy.deepcopy(normal) if isinstance(normal, list) else None,
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"bbox_mm": copy.deepcopy(raw_bbox or {}),
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}
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records.append({
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"record_id": record_id,
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"kind": "face",
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"feature_id": "",
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"body_id": None,
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"owner_feature_ids": [],
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"geometry": geometry,
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"executable": False,
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"synthetic": True,
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})
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return {
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"schema_version": "cad.topology.v1",
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"task_id": task_id,
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"revision_id": revision_id,
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"snapshot_id": f"{task_id}/{revision_id}" if task_id and revision_id else "",
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"body_id": active_body_id,
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"records": records,
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}
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def topology_sidecars(
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engine_result: dict[str, Any],
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preview: dict[str, Any] | None = None,
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*,
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snapshot: dict[str, Any] | None = None,
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) -> tuple[dict[str, Any], dict[str, Any]]:
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runtime_records = (snapshot or topology_snapshot(engine_result)).get("records") or []
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runtime_faces = [item for item in runtime_records if item.get("kind") == "face" and item.get("executable", True)]
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runtime_edges = [item for item in runtime_records if item.get("kind") == "edge" and item.get("executable", True)]
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if runtime_faces or runtime_edges:
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references = []
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for record in runtime_faces:
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geometry = record.get("geometry") or {}
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references.append({
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"id": str(record.get("record_id")),
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"selectorType": "face",
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"label": str(geometry.get("surface_type") or "face"),
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"center": geometry.get("center_mm"),
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"normal": geometry.get("normal"),
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"frame": {
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"origin_mm": geometry.get("center_mm"),
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"normal": geometry.get("normal"),
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"x_dir": [1, 0, 0],
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"y_dir": [0, 1, 0],
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},
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"bbox": geometry.get("bbox_mm") or {},
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"surface_type": str(geometry.get("surface_type") or "unknown"),
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"owner_feature_ids": record.get("owner_feature_ids") or [],
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"source": "runtime_snapshot",
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"snapshot_id": (snapshot or {}).get("snapshot_id") or "",
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"executable": True,
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})
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edge_records = [
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{
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**record,
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"selectorType": "edge",
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"source": "runtime_snapshot",
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"snapshot_id": (snapshot or {}).get("snapshot_id") or "",
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}
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for record in runtime_edges
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]
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return (
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{"schema_version": "cad.topology.v1", "references": references, "edges": edge_records},
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{"schema_version": "cad.topology.v1", "edges": edge_records},
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)
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topology_faces = (preview or {}).get("topology_faces")
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if isinstance(topology_faces, list) and topology_faces:
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references = []
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for face in topology_faces:
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if not isinstance(face, dict):
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continue
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frame = face.get("frame")
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center = face.get("center")
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normal = face.get("normal")
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if not isinstance(frame, dict) or not isinstance(center, list) or not isinstance(normal, list):
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continue
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references.append({
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"id": str(face.get("id") or f"face_{len(references):03d}"),
|
|
"selectorType": "face",
|
|
"label": str(face.get("surface_type") or "face"),
|
|
"center": center,
|
|
"normal": normal,
|
|
"frame": frame,
|
|
"bbox": face.get("bbox") or {},
|
|
"surface_type": str(face.get("surface_type") or "unknown"),
|
|
"triangle_start": int(face.get("triangle_start") or 0),
|
|
"triangle_count": int(face.get("triangle_count") or 0),
|
|
"source": "preview",
|
|
"synthetic": True,
|
|
"executable": False,
|
|
})
|
|
if references:
|
|
return ({"schema_version": "1.1", "references": references}, {"schema_version": "1.0", "edges": []})
|
|
|
|
bbox = engine_result.get("bbox_mm") or {}
|
|
minimum = [float(value) for value in bbox.get("min") or [0, 0, 0]]
|
|
maximum = [float(value) for value in bbox.get("max") or [0, 0, 0]]
|
|
if len(minimum) != 3 or len(maximum) != 3:
|
|
raise ValueError("Engine result is missing a valid bounding box")
|
|
center = [(minimum[index] + maximum[index]) / 2 for index in range(3)]
|
|
definitions = [
|
|
("top", [center[0], center[1], maximum[2]], [0, 0, 1], [1, 0, 0], [0, 1, 0]),
|
|
("bottom", [center[0], center[1], minimum[2]], [0, 0, -1], [1, 0, 0], [0, -1, 0]),
|
|
("right", [maximum[0], center[1], center[2]], [1, 0, 0], [0, 1, 0], [0, 0, 1]),
|
|
("left", [minimum[0], center[1], center[2]], [-1, 0, 0], [0, 1, 0], [0, 0, -1]),
|
|
("front", [center[0], maximum[1], center[2]], [0, 1, 0], [1, 0, 0], [0, 0, -1]),
|
|
("back", [center[0], minimum[1], center[2]], [0, -1, 0], [1, 0, 0], [0, 0, 1]),
|
|
]
|
|
references = [
|
|
{
|
|
"id": f"face_{name}", "selectorType": "face", "label": name,
|
|
"center": point, "normal": normal,
|
|
"frame": {"origin_mm": point, "normal": normal, "x_dir": x_dir, "y_dir": y_dir},
|
|
"bbox": {"min": minimum, "max": maximum},
|
|
"source": "bbox_fallback",
|
|
"synthetic": True,
|
|
"executable": False,
|
|
}
|
|
for name, point, normal, x_dir, y_dir in definitions
|
|
]
|
|
return ({"schema_version": "1.0", "references": references}, {"schema_version": "1.0", "edges": []})
|