ganjihong
95cae203f4
Phase 7 of the decoupling refactor (behavior-preserving move): - legacy/llm_compiler.py, legacy/llm_engine.py: frozen build_pack path (unused by run_cdsl_only), moved with git mv for history - legacy/exact_rebuild.py: _run_parameterized / _run_exact / _apply_geometric_compensations moved out of rebuild.py, including the part-specific compensation table - rebuild.py keeps run_rebuild / run_cdsl_only / compare_with_gold and imports the moved functions - llm_compiler.py / llm_engine.py become compatibility shims Frozen zone: new capability belongs in executors/ + schema contracts. The project-specific compensation no longer sits in the main pipeline.
288 lines
12 KiB
Python
288 lines
12 KiB
Python
"""通用编译器：瘦 CDSL → build_pack；线性阵列在此展开为重复步骤。"""
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from __future__ import annotations
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import json
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from copy import deepcopy
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from pathlib import Path
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from typing import Any
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try:
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from ..sketch_solver import resolve_all_sketches
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except ImportError:
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from sketch_solver import resolve_all_sketches
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REQUIRED = {
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"revolve_add": ["angle_deg", "axis"],
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"revolve_cut": ["angle_deg", "axis"],
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"extrude_add_blind": ["distance_mm"],
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"extrude_add_two_sided": ["distance_mm"],
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"extrude_cut_blind": ["distance_mm"],
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"hole_blind": ["diameter_mm", "depth_mm"],
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"hole_countersink": ["diameter_mm", "depth_mm"],
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"hole_counterbore": ["diameter_mm", "depth_mm"],
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"sphere_add": ["radius_mm", "center_mm"],
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}
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def _load(path: Path) -> dict[str, Any]:
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return json.loads(path.read_text(encoding="utf-8"))
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def _offset_sketch(sketch: dict[str, Any] | None, dx: float, dy: float, dz: float) -> dict[str, Any] | None:
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if sketch is None:
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return None
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s = deepcopy(sketch)
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wp = s.get("workplane") or {}
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o = list(wp.get("origin_mm") or [0, 0, 0])
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wp["origin_mm"] = [o[0] + dx, o[1] + dy, o[2] + dz]
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s["workplane"] = wp
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edges = []
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for e in s.get("contour_edges_mm") or []:
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ne = deepcopy(e)
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for key in ("start_mm", "end_mm", "center_mm"):
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if key in ne:
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p = ne[key]
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ne[key] = [p[0] + dx, p[1] + dy, p[2] + dz]
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edges.append(ne)
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if edges:
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s["contour_edges_mm"] = edges
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# 2D entities: shift in plane if offset has in-plane components only — skip for world offset patterns
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return s
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def _offset_params_positions(params: dict[str, Any], dx: float, dy: float, dz: float) -> dict[str, Any]:
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p = deepcopy(params)
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if "positions" in p:
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for pos in p["positions"]:
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mm = pos.get("mm")
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if mm:
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pos["mm"] = [mm[0] + dx, mm[1] + dy, mm[2] + dz]
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if "axis" in p and isinstance(p["axis"], dict):
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o = list(p["axis"].get("origin_mm") or [0, 0, 0])
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p["axis"]["origin_mm"] = [o[0] + dx, o[1] + dy, o[2] + dz]
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return p
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def compile_cdsl(
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cdsl: dict[str, Any],
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atoms_catalog: dict[str, Any] | None = None,
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techniques_catalog: dict[str, Any] | None = None,
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) -> dict[str, Any]:
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allowed = set()
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if atoms_catalog:
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allowed = {a["atomic_id"] for a in atoms_catalog.get("atoms") or []}
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techniques = {
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item["technique_id"]: item
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for item in (techniques_catalog or {}).get("techniques") or []
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}
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sketches = {s["id"]: s for s in (cdsl.get("geometry") or {}).get("sketches") or []}
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# 参数化轮廓求解：将 profile 字段展开为精确的 entities + contour_edges_mm
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cdsl = resolve_all_sketches(cdsl)
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sketches = {s["id"]: s for s in (cdsl.get("geometry") or {}).get("sketches") or []}
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steps: list[dict[str, Any]] = []
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seen_ids: set[str] = set()
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# feature_id -> list of emitted step dicts (for pattern source)
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emitted: dict[str, list[dict[str, Any]]] = {}
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def emit(feature: dict[str, Any], params: dict[str, Any], sketch: dict[str, Any] | None, step_id: str) -> dict[str, Any]:
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atomic = feature["atomic_id"]
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if allowed and atomic not in allowed:
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raise ValueError(f"{step_id}: atomic_id {atomic!r} is not admitted by catalog")
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for dep in feature.get("depends_on") or []:
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if dep not in seen_ids and not any(dep in emitted):
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# dependency may be ok if earlier
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if dep not in seen_ids:
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raise ValueError(f"{step_id}: depends_on {dep} not yet defined")
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step = {
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"step_id": step_id,
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"atomic_id": atomic,
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"depends_on": list(feature.get("depends_on") or []),
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"params": params,
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"sketch": sketch,
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"source_name": feature.get("name"),
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}
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steps.append(step)
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seen_ids.add(step_id)
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return step
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for feat in cdsl.get("features") or []:
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fid = feat["id"]
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atomic = feat.get("atomic_id")
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technique_id = feat.get("technique_id")
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if technique_id:
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technique = techniques.get(technique_id)
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if technique is None:
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raise ValueError(f"{fid}: technique_id {technique_id!r} is not admitted by catalog")
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groups = feat.get("params") or {}
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expanded: list[dict[str, Any]] = []
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previous_step_id: str | None = None
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for index, internal in enumerate(technique.get("internal_steps") or [], start=1):
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group_name = internal.get("params_from")
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group = deepcopy(groups.get(group_name) or {})
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if not isinstance(group, dict):
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raise ValueError(f"{fid}: parameter group {group_name!r} must be an object")
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params = deepcopy(group.get("params") if isinstance(group.get("params"), dict) else group)
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sketch_id = group.get("sketch_id") or params.pop("sketch_id", None)
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sketch = deepcopy(sketches[sketch_id]) if sketch_id and sketch_id in sketches else None
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internal_atomic = internal.get("atomic_id")
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if not internal_atomic:
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raise ValueError(f"{fid}: technique {technique_id!r} has an invalid internal step")
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for key in REQUIRED.get(internal_atomic, []):
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if params.get(key) is None:
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raise ValueError(
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f"{fid}: technique {technique_id!r} group {group_name!r} missing {key}"
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)
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internal_feature = {
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"atomic_id": internal_atomic,
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"depends_on": [previous_step_id] if previous_step_id else list(feat.get("depends_on") or []),
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"name": f"{feat.get('name') or technique_id}:{group_name or index}",
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}
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step_id = f"{fid}.t{index}"
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expanded.append(emit(internal_feature, params, sketch, step_id))
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previous_step_id = step_id
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if len(expanded) < 2:
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raise ValueError(f"{fid}: technique {technique_id!r} must expand to at least two steps")
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emitted[fid] = expanded
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seen_ids.add(fid)
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continue
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if not atomic:
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raise ValueError(f"{fid}: missing atomic_id")
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if atomic == "pattern_linear":
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params = feat.get("params") or {}
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src_ids = params.get("source_feature_ids") or []
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c1 = int(params.get("pattern_count_1") or 1)
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c2 = int(params.get("pattern_count_2") or 1)
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s1 = float(params.get("spacing_1_mm") or 0)
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s2 = float(params.get("spacing_2_mm") or 0)
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d1 = params.get("direction_1") or [1, 0, 0]
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d2 = params.get("direction_2") or [0, 1, 0]
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if params.get("direction_1_reverse"):
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d1 = [-d1[0], -d1[1], -d1[2]]
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if params.get("direction_2_reverse"):
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d2 = [-d2[0], -d2[1], -d2[2]]
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src_steps: list[dict[str, Any]] = []
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for sid in src_ids:
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src_steps.extend(emitted.get(sid) or [])
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if not src_steps:
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# 无源则跳过并记录
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steps.append(
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{
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"step_id": fid,
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"atomic_id": "noop_pattern",
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"depends_on": list(feat.get("depends_on") or []),
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"params": params,
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"sketch": None,
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"note": "pattern source steps missing",
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}
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)
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seen_ids.add(fid)
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continue
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clone_steps = []
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k = 0
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for i in range(c1):
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for j in range(c2):
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if i == 0 and j == 0:
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continue
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dx = d1[0] * s1 * i + d2[0] * s2 * j
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dy = d1[1] * s1 * i + d2[1] * s2 * j
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dz = d1[2] * s1 * i + d2[2] * s2 * j
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for src in src_steps:
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k += 1
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clone_id = f"{fid}.p{k}"
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fake_feat = {
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"atomic_id": src["atomic_id"],
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"depends_on": [steps[-1]["step_id"]] if steps else [],
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"name": f"{src.get('source_name')}_pattern",
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}
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st = emit(
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fake_feat,
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_offset_params_positions(src["params"], dx, dy, dz),
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_offset_sketch(src.get("sketch"), dx, dy, dz),
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clone_id,
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)
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clone_steps.append(st)
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emitted[fid] = clone_steps
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seen_ids.add(fid)
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continue
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params = deepcopy(feat.get("params") or {})
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sketch_id = feat.get("sketch_id") or params.get("sketch_id")
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sketch = deepcopy(sketches[sketch_id]) if sketch_id and sketch_id in sketches else None
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if sketch_id:
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params["sketch_id"] = sketch_id
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# Auto-derive revolve axis origin
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if "revolve" in atomic and sketch and "axis" in params:
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ax = params.get("axis") or {}
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# 优先级: from_workplane_origin > from_contour_vertex > origin_mm 裸坐标
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wp = sketch.get("workplane") or {}
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wp_origin = wp.get("origin_mm") or [0.0, 0.0, 0.0]
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if ax.get("from_workplane_origin") and "origin_mm" not in ax:
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params["axis"] = deepcopy(params["axis"])
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params["axis"]["origin_mm"] = list(wp_origin)
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elif "origin_mm" not in ax:
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ce = sketch.get("contour_edges_mm") or []
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if ce:
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idx = int(ax.get("from_contour_vertex", 0))
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vertex = ce[idx % len(ce)]["start_mm"]
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params["axis"] = deepcopy(params["axis"])
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params["axis"]["origin_mm"] = list(vertex)
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for key in REQUIRED.get(atomic, []):
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if key == "axis" and "axis" not in params:
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raise ValueError(f"{fid}: missing axis")
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if key not in ("axis",) and params.get(key) is None and key != "sketch_id":
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# positions can be empty temporarily
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if key in params:
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continue
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if key in ("diameter_mm", "depth_mm", "distance_mm", "angle_deg") and params.get(key) is None:
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raise ValueError(f"{fid}: missing {key}")
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st = emit(feat, params, sketch, fid)
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emitted[fid] = [st]
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# filter noop
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steps = [s for s in steps if s.get("atomic_id") != "noop_pattern"]
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return {
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"schema": "cad.engine_plan.v1",
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"part_id": cdsl.get("part_id"),
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"unit": "mm",
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"steps": steps,
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"compiler_context": deepcopy(cdsl.get("compiler_context")),
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"meta": {
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"from_cdsl_schema": cdsl.get("schema"),
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"compiler": "cad-heard.llm_compiler.v1",
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"n_steps": len(steps),
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},
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}
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def main() -> None:
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import argparse
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ap = argparse.ArgumentParser()
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ap.add_argument("--cdsl", type=Path, required=True)
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ap.add_argument("--catalog", type=Path, default=None)
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ap.add_argument("--techniques", type=Path, default=None)
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ap.add_argument("--out", type=Path, required=True)
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args = ap.parse_args()
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catalog = _load(args.catalog) if args.catalog else None
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techniques = _load(args.techniques) if args.techniques else None
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pack = compile_cdsl(_load(args.cdsl), catalog, techniques)
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args.out.parent.mkdir(parents=True, exist_ok=True)
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args.out.write_text(json.dumps(pack, ensure_ascii=False, indent=2), encoding="utf-8")
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print(f"wrote {args.out} steps={len(pack['steps'])}")
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if __name__ == "__main__":
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main()
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