core/workbench/journal.py
Shay bdb294eac3 feat(workbench): land B3.5-b/c/d/e — calibration evidence subject, B4a leeway gate, docs; runner-reproducible practice artifact
Completes the Wave M B3.5 consolidation slice (b–e), built on #728.

B3.5-b — calibration as a first-class evidence subject (`calibration_class`,
address `calibration:<class_name>`): RightInspector projection + Evidence
Chain Rail semantics (serving-discipline evidence, not runtime truth).

B3.5-c / B4a — nullable `LeewayEvidence` read model threaded through turn,
replay, cognition-proposal, and math-proposal surfaces, with a shared
absence-honest card. B4 is gated correctly: the tuple exists in typed data but
no producer populates it, so the card renders absence (verified: no non-null
producer in workbench/core/chat).

B3.5-d/e — UI-UX-GUIDE.md, b4-leeway-feasibility-gate.md, phase-a-residue-ledger.md.

Practice artifact — earn-it-for-real (runner-reproducible). The committed
`report.json` (additive earns PROPOSE @0.861, 95/5/50) is now emitted by a
deterministic runner rather than copied from the queue. `propose_runner`
gains `regenerate_practice_artifacts()`, which runs ONE sealed `resolve_pooled`
practice pass and writes BOTH report.json (the per-class ledger the calibration
reader consumes) and ratification_queue.json — two projections of one ledger,
coherent by construction and byte-reproducible. `runner.main()` delegates to
it (lazy import, no cycle), so both entry points produce the identical pair.
This closes the gap where a hand-copied report.json agreed with the queue but
no runner produced it. `resolve_pooled` is the aggressive sealed PROPOSE-regime
scorer (proposal-only/HITL, unsafe for serving, legitimate for
attempt-and-eliminate); wrong=5 is the sealed-practice learning signal, NOT the
serving wrong=0. No serving/derivation/reliability_gate source touched; the
practice lane is not in the serving-frozen SHA gate.

Validated:
- python -m pytest tests/test_workbench_{calibration,journal,replay,schemas}.py -> 31 passed
- python -m pytest tests/ -k "workbench or propose or learning_arena or practice"
  -> 190 passed (3 failing tests in test_adr_0175_phase2_practice_lane.py are
  PRE-EXISTING reds on clean origin/main: stale 4/0/46 assertions on build_report,
  which this change does not touch)
- report.json + ratification_queue.json: deterministic (run1==run2) and
  reproduced byte-identically by both `python -m ...runner` and `...propose_runner`
- pnpm build green; 144 UI tests across calibration/leeway/evidence/replay/
  doctrine-gates/routes-docs-drift all pass
2026-06-13 07:36:44 -07:00

196 lines
6.7 KiB
Python

"""Append-only Workbench turn evidence journal."""
from __future__ import annotations
import hashlib
import json
import threading
from dataclasses import dataclass, replace
from pathlib import Path
from typing import Any
from workbench.schemas import ChatTurnResult, TraceIntegrity, to_data, utc_now
REPO_ROOT = Path(__file__).resolve().parents[1]
DEFAULT_JOURNAL_DIR = REPO_ROOT / "workbench_data"
JOURNAL_FILENAME = "turn_journal.jsonl"
PROMPT_EXCERPT_CHARS = 120
SURFACE_EXCERPT_CHARS = 120
@dataclass(frozen=True, slots=True)
class TurnJournalSummary:
turn_id: int
timestamp: str
prompt_excerpt: str
surface_excerpt: str
trace_hash: str | None
grounding_source: str
trace_integrity: TraceIntegrity
@dataclass(frozen=True, slots=True)
class TurnJournalEntry:
turn_id: int
timestamp: str
trace_hash: str | None
prompt: str
surface: str
articulation_surface: str | None
walk_surface: str | None
grounding_source: str
epistemic_state: str
normative_clearance: str
verdicts: dict[str, Any]
refusal_emitted: bool
hedge_injected: bool
proposal_candidates: list[dict[str, Any]]
turn_cost_ms: int
checkpoint_emitted: bool
leeway_evidence: dict[str, Any] | None = None
trace_integrity: TraceIntegrity | None = None
journal_digest: str = ""
def __post_init__(self) -> None:
integrity = self.trace_integrity or _trace_integrity_for_hash(self.trace_hash)
object.__setattr__(self, "trace_integrity", integrity)
@classmethod
def from_chat_turn(
cls,
result: ChatTurnResult,
*,
turn_id: int,
timestamp: str | None = None,
) -> "TurnJournalEntry":
return cls(
turn_id=turn_id,
timestamp=timestamp or utc_now(),
trace_hash=result.trace_hash,
prompt=result.prompt,
surface=result.surface,
articulation_surface=result.articulation_surface,
walk_surface=result.walk_surface,
grounding_source=result.grounding_source,
epistemic_state=result.epistemic_state,
normative_clearance=result.normative_clearance,
verdicts={
"identity": to_data(result.identity_verdict),
"safety": to_data(result.safety_verdict),
"ethics": to_data(result.ethics_verdict),
},
refusal_emitted=result.refusal_emitted,
hedge_injected=result.hedge_injected,
proposal_candidates=[
candidate for candidate in to_data(result.proposal_candidates)
],
turn_cost_ms=result.turn_cost_ms,
checkpoint_emitted=result.checkpoint_emitted,
leeway_evidence=to_data(result.leeway_evidence),
trace_integrity=_trace_integrity_for_hash(result.trace_hash),
)
def summary(self) -> TurnJournalSummary:
return TurnJournalSummary(
turn_id=self.turn_id,
timestamp=self.timestamp,
prompt_excerpt=self.prompt[:PROMPT_EXCERPT_CHARS],
surface_excerpt=self.surface[:SURFACE_EXCERPT_CHARS],
trace_hash=self.trace_hash,
grounding_source=self.grounding_source,
trace_integrity=self.trace_integrity or _trace_integrity_for_hash(self.trace_hash),
)
class TurnJournal:
"""Pure JSONL append/read model for Workbench chat evidence."""
def __init__(self, journal_dir: Path = DEFAULT_JOURNAL_DIR) -> None:
self._journal_dir = _validate_journal_dir(journal_dir)
self._path = self._journal_dir / JOURNAL_FILENAME
self._lock = threading.Lock()
@property
def journal_dir(self) -> Path:
return self._journal_dir
@property
def path(self) -> Path:
return self._path
def next_turn_id(self) -> int:
entries = self._read_entries()
if not entries:
return 1
return max(entry.turn_id for entry in entries) + 1
def append(self, entry: TurnJournalEntry) -> TurnJournalEntry:
with self._lock:
expected = self.next_turn_id()
if entry.turn_id != expected:
raise ValueError(
f"turn_id must be next sequential id {expected}, got {entry.turn_id}"
)
sealed = replace(entry, journal_digest=_journal_digest(entry))
self._journal_dir.mkdir(parents=True, exist_ok=True)
with self._path.open("a", encoding="utf-8") as fh:
fh.write(_canonical_json(to_data(sealed)))
fh.write("\n")
return sealed
def list_summaries(self, *, limit: int = 50, offset: int = 0) -> list[TurnJournalSummary]:
if limit < 0:
raise ValueError("limit must be non-negative")
if offset < 0:
raise ValueError("offset must be non-negative")
entries = self._read_entries()
return [entry.summary() for entry in entries[offset : offset + limit]]
def list_entries(self, *, limit: int = 50, offset: int = 0) -> list[TurnJournalEntry]:
if limit < 0:
raise ValueError("limit must be non-negative")
if offset < 0:
raise ValueError("offset must be non-negative")
entries = self._read_entries()
return entries[offset : offset + limit]
def get_entry(self, turn_id: int) -> TurnJournalEntry:
for entry in self._read_entries():
if entry.turn_id == turn_id:
return entry
raise FileNotFoundError(str(turn_id))
def _read_entries(self) -> list[TurnJournalEntry]:
if not self._path.exists():
return []
entries: list[TurnJournalEntry] = []
with self._path.open("r", encoding="utf-8") as fh:
for line in fh:
if not line.strip():
continue
payload = json.loads(line)
entries.append(TurnJournalEntry(**payload))
return entries
def _validate_journal_dir(journal_dir: Path) -> Path:
resolved = journal_dir.resolve()
if resolved.name != "workbench_data":
raise ValueError("journal directory must be named workbench_data")
return resolved
def _canonical_json(payload: dict[str, Any]) -> str:
return json.dumps(payload, ensure_ascii=False, sort_keys=True, separators=(",", ":"))
def _trace_integrity_for_hash(trace_hash: str | None) -> TraceIntegrity:
return "pipeline_trace" if str(trace_hash or "").strip() else "legacy_unhashed"
def _journal_digest(entry: TurnJournalEntry) -> str:
payload = to_data(replace(entry, journal_digest=""))
payload.pop("journal_digest", None)
raw = _canonical_json(payload).encode("utf-8")
return "sha256:" + hashlib.sha256(raw).hexdigest()