Files
ThothII/harness/tht/workflow.py

127 lines
4.4 KiB
Python

"""Reads workflow.yaml -- the SINGLE source of workflow truth (spec F2, §5.3).
phase.py, the gate (tht-gate.js), and the skill all read from here.
No more duplicated constants (the JS/Python drift bug in the reference implementation -- PHASE_NAMES
truncated to 7 in JS -- is structurally impossible because there is one source).
Edit workflow.yaml to change the workflow: add/reorder/merge/skip phases.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
import yaml
_WF_PATH = Path(__file__).resolve().parent.parent / "workflow.yaml"
@dataclass
class PhaseSpec:
id: str
num: int
name: str
advance: str
prerequisites: list[Any]
artifacts_out: list[str] = field(default_factory=list)
emits: list[str] = field(default_factory=list)
@dataclass
class Workflow:
schema_version: int
phases: list[PhaseSpec]
_decision_min_map: dict[str, int] = field(default_factory=dict)
@property
def max_phase(self) -> int:
return len(self.phases)
def phase_by_num(self, n: int) -> PhaseSpec:
return self.phases[n - 1]
def phase_name(self, n: int) -> str:
if 1 <= n <= self.max_phase:
return self.phase_by_num(n).name
return "?"
def decision_min_phase(self, decision_type: str) -> int:
"""A decision type's min phase = the earliest phase that EMITS it (workflow.yaml
`emits`), or that references it in a prerequisite. Defaults to 1 (meta types like
phase_approved/decision_retracted are not phase-gated)."""
return self._decision_min_map.get(decision_type, 1)
def schema_linking_phase(self) -> int:
"""The phase that produces schema_linking.json (artifacts_out). Default 5
(the conventional schema-linking phase) if no phase declares it. Used by the
CLI drift fix in place of the old SCHEMA_LINKING_PHASE constant."""
for p in self.phases:
if "schema_linking.json" in p.artifacts_out:
return p.num
return 5
def _collect_decision_mins(phases: list[PhaseSpec]) -> dict[str, int]:
"""Scan prerequisites for decision_exists / decision_subject_exists mentions.
Supports both forms:
- decision_exists: <type> (scalar)
- decision_exists: [<type>, ...] (list, first element is the type)
- decision_subject_exists: [<type>, <subject>] (list, first element is the type)
"""
mins: dict[str, int] = {}
def scan(node: Any, phase_num: int) -> None:
if isinstance(node, dict):
for key, value in node.items():
if key in ("decision_exists", "decision_subject_exists"):
if isinstance(value, list) and value:
dtype = value[0]
elif isinstance(value, str):
dtype = value
else:
continue
if isinstance(dtype, str) and (
dtype not in mins or phase_num < mins[dtype]
):
mins[dtype] = phase_num
else:
scan(value, phase_num)
elif isinstance(node, list):
for item in node:
scan(item, phase_num)
for p in phases:
scan(p.prerequisites, p.num)
# `emits`: la fase dichiara i decision type che produce -> fonte primaria del
# min phase (copre i tipi non citati nei prerequisites, es. table_promoted,
# value_grounded, concept_formula_*). Vince la fase piu' bassa.
for dtype in p.emits:
if isinstance(dtype, str) and (dtype not in mins or p.num < mins[dtype]):
mins[dtype] = p.num
return mins
def load_workflow(path: Path | str = _WF_PATH) -> Workflow:
path = Path(path)
raw = yaml.safe_load(path.read_text())
phases: list[PhaseSpec] = []
for i, p in enumerate(raw["phases"], start=1):
phases.append(
PhaseSpec(
id=p["id"],
num=i,
name=p["name"],
advance=p["advance"],
prerequisites=p.get("prerequisites", []),
artifacts_out=p.get("artifacts_out", []),
emits=p.get("emits", []),
)
)
return Workflow(
schema_version=raw.get("schema_version", 1),
phases=phases,
_decision_min_map=_collect_decision_mins(phases),
)