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FabledGrimoire/src/scribe/services/shape_ledger.py
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bvandeusenandClaude Fable 5 942edd1eb5
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feat(ledger): classify_shapes + list_shapes MCP tools; get_snippet carries the consumer map (#2789, milestone 294 step 3)
The judgment write path. classify_shapes applies a batch of classifications
to a project's live ledger rows — all-or-nothing (#2709's lesson: the whole
batch is validated, write-ACL'd, and every snippet target proven readable
before any row is touched); rows match by exact (path, symbol), kind narrows,
and shapes no live row matches come back as 'unmatched' rather than errors.
variant/exempt REQUIRE the reason — the why is the record (note 2786) — and
'unclassified' deliberately withdraws a judgment back to the todo. The 'via'
channel is caller-restricted to agent|audit|import; hook and mechanical stay
server-internal so a caller can't launder judgment as machinery.

list_shapes is the todo query (status=unclassified) with composable filters:
path is exact-or-under like recorded locations, snippet_id reads a consumer
map, include_vanished reads history; paged with the true total.

get_snippet now attaches  and  — the structured consumer
map, filtered to projects the CALLER can read so a shared snippet never side-
channels another project's file layout; attached only when non-empty (#2483).

Integration tests pin the batch atomicity, ACL gates, filter composition, the
consumer map on the MCP pull, and the SET NULL companion: a judgment whose
snippet was purged rejoins the todo on the next sync.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-19 19:55:47 -04:00

411 lines
16 KiB
Python

"""The shape ledger's write side — sync and mechanical marking (#2788).
The coverage walk (services/coverage.py) is the only feed that sees every
shape, so it is the ledger's sync point: each refresh upserts one repo's
extracted shapes — new shapes arrive `unclassified` (THE todo state, note
2786), surviving shapes bump their last-seen marker, vanished shapes get
stamped rather than deleted (history is the point). Classifications survive
recompute by construction: the upsert never touches a judgment, with two
deliberate exceptions —
- a judgment whose snippet target is gone (SET NULL on snippet deletion)
is re-filed as unclassified so it rejoins the todo instead of dangling;
- a MECHANICALLY-stamped canonical row whose snippet location no longer
covers it falls back to unclassified. Only mechanical stamps self-heal;
an agent's judgment is never unwound by machinery.
`location_covers` is the one covering predicate — the same doctrine the
recorded-location drift check uses — shared by the sync's canonical marking
and by anything else that must decide whether a recorded location speaks for
an extracted shape.
"""
from __future__ import annotations
from datetime import datetime, timezone
from sqlalchemy import select
from scribe.models import async_session
from scribe.models.code_shape import CodeShape
# Statuses whose meaning requires a snippet target.
_NEEDS_TARGET = ("canonical", "instance", "variant")
def _norm_symbol(kind_or_symbol: str) -> str:
# CSS shapes and recorded CSS symbols may or may not carry the leading
# dot; compare without it so ".btn-primary" and "btn-primary" agree.
return kind_or_symbol.lstrip(".").strip()
def location_covers(loc_path: str, loc_symbol: str, path: str, name: str) -> bool:
"""Does a recorded (path, symbol) location speak for this shape?
Symbol-less locations never cover a shape — a whole-file record makes no
claim about any particular definition inside it. Path semantics are the
drift check's own: exact file, or the recorded path is a directory the
file lives under.
"""
if not (loc_symbol or "").strip():
return False
if _norm_symbol(loc_symbol) != _norm_symbol(name):
return False
if not loc_path:
# Symbol-only record: the symbol match is all the claim there is.
return True
from scribe.services.snippets import _path_touches
return _path_touches(loc_path, path)
async def sync_repo_shapes(
project_id: int,
repo_key: str,
shapes: list[tuple[str, str, str]],
*,
seen_marker: str,
) -> None:
"""Upsert one repo's extracted (path, kind, name) shapes into the ledger.
``seen_marker`` is the commit the archive was read at when the forge can
say, else the ref name — provenance sugar; the row timestamps carry the
when.
"""
now = datetime.now(timezone.utc)
async with async_session() as session:
rows = (
await session.execute(
select(CodeShape).where(
CodeShape.project_id == project_id,
CodeShape.repo_key == repo_key,
)
)
).scalars().all()
by_key = {(r.path, r.symbol, r.kind): r for r in rows}
seen: set[tuple[str, str, str]] = set()
for path, kind, name in shapes:
key = (path, name, kind)
if key in seen:
continue
seen.add(key)
row = by_key.get(key)
if row is None:
session.add(CodeShape(
project_id=project_id, repo_key=repo_key,
path=path, symbol=name, kind=kind,
first_seen_commit=seen_marker, last_seen_commit=seen_marker,
))
continue
row.last_seen_commit = seen_marker
# A shape that vanished and came back is live again — the vanish
# stays visible in history via updated_at, not as a dead flag.
row.vanished_at = None
if row.status in _NEEDS_TARGET and row.snippet_id is None:
row.status = "unclassified"
row.classified_by = None
row.classified_at = None
row.reason = None
for key, row in by_key.items():
if key not in seen and row.vanished_at is None:
row.vanished_at = now
await session.commit()
async def mark_canonicals(
project_id: int, recorded: list[tuple[int, str, str]]
) -> None:
"""Stamp snippet reference locations as `canonical` — the one mechanical
rule that is always safe (the judgment happened when the snippet was
minted; this row just makes it queryable).
``recorded`` is (snippet_note_id, path, symbol) for every live snippet
location in the project. Touches only rows machinery owns: unclassified
rows gain the stamp; mechanically-stamped canonicals no longer covered
fall back to unclassified. Agent judgments are never overwritten.
"""
usable = [(nid, p, s) for nid, p, s in recorded if (s or "").strip()]
now = datetime.now(timezone.utc)
async with async_session() as session:
rows = (
await session.execute(
select(CodeShape).where(
CodeShape.project_id == project_id,
CodeShape.vanished_at.is_(None),
)
)
).scalars().all()
for row in rows:
covering = next(
(
nid for nid, lp, ls in usable
if location_covers(lp, ls, row.path, row.symbol)
),
None,
)
if covering is not None and row.status == "unclassified":
row.status = "canonical"
row.snippet_id = covering
row.classified_by = "mechanical"
row.classified_at = now
elif (
covering is None
and row.status == "canonical"
and row.classified_by == "mechanical"
):
row.status = "unclassified"
row.snippet_id = None
row.classified_by = None
row.classified_at = None
await session.commit()
async def live_rows(project_id: int) -> list[CodeShape]:
"""Every un-vanished ledger row for a project — the accounting readout's
input, across ALL its repos (a repo unreachable this refresh still counts;
accounting is project-wide)."""
async with async_session() as session:
return list(
(
await session.execute(
select(CodeShape).where(
CodeShape.project_id == project_id,
CodeShape.vanished_at.is_(None),
)
)
).scalars().all()
)
# --- classification (#2789): the judgment write path --------------------------
# Statuses an explicit classification may set. All five: setting a row back to
# `unclassified` is how a judgment is deliberately withdrawn.
_SETTABLE = ("canonical", "instance", "variant", "exempt", "unclassified")
# Who may appear as the classifier on this path. `hook` and `mechanical` are
# server-internal feeds (steps 5-6) — a caller claiming them would launder a
# judgment as machinery.
_CALLER_VIAS = ("agent", "audit", "import")
def validate_classifications(items: list[dict]) -> str | None:
"""The structural error a classification batch would earn, or None.
Pure and checked BEFORE anything is touched: a batch either applies or
errors whole — the StrictArgs lesson (#2709), a caller must never learn
later that half a batch silently happened.
"""
if not items:
return "classifications is empty — nothing to apply"
for i, item in enumerate(items):
if not isinstance(item, dict):
return f"classifications[{i}] is not an object"
path = (item.get("path") or "").strip()
symbol = (item.get("symbol") or "").strip()
if not path or not symbol:
return f"classifications[{i}] needs both path and symbol"
status = item.get("status") or ""
if status not in _SETTABLE:
return (
f"classifications[{i}] has unknown status {status!r} "
f"(one of: {', '.join(_SETTABLE)})"
)
snippet_id = item.get("snippet_id") or 0
if status in _NEEDS_TARGET and not snippet_id:
return (
f"classifications[{i}]: status {status!r} needs snippet_id — "
"the snippet this shape is (or departs from)"
)
if status in ("variant", "exempt") and not (item.get("reason") or "").strip():
return (
f"classifications[{i}]: status {status!r} needs a reason — "
"the WHY is the record (note 2786)"
)
return None
async def classify_shapes(
user_id: int,
project_id: int,
classifications: list[dict],
*,
via: str = "agent",
) -> dict:
"""Apply a batch of judgments to a project's live ledger rows.
All-or-nothing on errors: the whole batch is validated (structure, write
access, every snippet target readable by the caller) before any row is
touched. Rows are matched by exact (path, symbol) — plus kind when the
item carries one — and a target no live row matches is reported in
``unmatched``, not an error: the tree may simply have moved since the
caller listed. Idempotent by construction.
"""
from scribe.services import access
from scribe.services import snippets as snippets_svc
if via not in _CALLER_VIAS:
raise ValueError(f"via must be one of: {', '.join(_CALLER_VIAS)}")
error = validate_classifications(classifications)
if error:
raise ValueError(error)
if not await access.can_write_project(user_id, project_id):
raise ValueError(f"project {project_id} not found or no write access")
# Snippet targets resolve through the caller's own read access — a
# family-canon snippet in another project counts (note 2786), a snippet
# the caller cannot read does not exist for them.
target_ids = {
int(item["snippet_id"])
for item in classifications
if item.get("status") in _NEEDS_TARGET
}
for sid in sorted(target_ids):
if await snippets_svc.get_snippet(user_id, sid) is None:
raise ValueError(f"snippet {sid} not found (or not readable)")
now = datetime.now(timezone.utc)
classified = 0
unmatched: list[dict] = []
async with async_session() as session:
rows = (
await session.execute(
select(CodeShape).where(
CodeShape.project_id == project_id,
CodeShape.vanished_at.is_(None),
)
)
).scalars().all()
by_key: dict[tuple[str, str], list[CodeShape]] = {}
for row in rows:
by_key.setdefault((row.path, row.symbol), []).append(row)
for item in classifications:
matches = by_key.get(
((item.get("path") or "").strip(), (item.get("symbol") or "").strip())
) or []
kind = (item.get("kind") or "").strip()
if kind:
matches = [r for r in matches if r.kind == kind]
if not matches:
unmatched.append({
"path": item.get("path"), "symbol": item.get("symbol"),
})
continue
status = item["status"]
for row in matches:
row.status = status
if status == "unclassified":
row.snippet_id = None
row.reason = None
row.classified_by = None
row.classified_at = None
else:
row.snippet_id = (
int(item["snippet_id"]) if status in _NEEDS_TARGET else None
)
row.reason = (item.get("reason") or "").strip() or None
row.classified_by = via
row.classified_at = now
classified += 1
await session.commit()
return {"classified": classified, "unmatched": unmatched}
async def list_project_shapes(
user_id: int,
project_id: int,
*,
status: str = "",
path: str = "",
snippet_id: int = 0,
include_vanished: bool = False,
limit: int = 100,
offset: int = 0,
) -> tuple[list[CodeShape], int]:
"""A filtered page of a project's ledger, with the unfiltered-match total.
([], 0) when the caller can't read the project — the same silence every
other project list gives. ``path`` matches the exact file or anything
beneath it, mirroring recorded-location semantics.
"""
from sqlalchemy import func, or_
from scribe.services import access
if not await access.can_read_project(user_id, project_id):
return [], 0
conds = [CodeShape.project_id == project_id]
if not include_vanished:
conds.append(CodeShape.vanished_at.is_(None))
if status:
conds.append(CodeShape.status == status)
if path:
clean = path.strip().strip("/")
conds.append(or_(
CodeShape.path == clean, CodeShape.path.like(clean + "/%")
))
if snippet_id:
conds.append(CodeShape.snippet_id == snippet_id)
async with async_session() as session:
total = (
await session.execute(
select(func.count()).select_from(CodeShape).where(*conds)
)
).scalar_one()
rows = (
await session.execute(
select(CodeShape).where(*conds)
.order_by(CodeShape.path, CodeShape.symbol, CodeShape.kind)
.limit(max(1, min(limit, 500))).offset(max(0, offset))
)
).scalars().all()
return list(rows), int(total)
def _consumer_dict(row: CodeShape) -> dict:
"""The compact shape a snippet's consumer map carries — enough to open
the file, none of the ledger bookkeeping."""
out = {
"project_id": row.project_id,
"repo": row.repo_key,
"path": row.path,
"symbol": row.symbol,
"kind": row.kind,
"classified_by": row.classified_by,
}
if row.reason:
out["reason"] = row.reason
return out
async def snippet_consumers(user_id: int, note_id: int) -> dict:
"""The structured consumer map for one snippet (#2789): its `instances`
(rows judged to conform) and `variants` (named departures, each carrying
its why). Rows are filtered to projects the CALLER can read — a shared
snippet must not become a side channel into someone else's project
layout. Empty lists mean "attach nothing" (#2483)."""
from scribe.services import access
async with async_session() as session:
rows = (
await session.execute(
select(CodeShape).where(
CodeShape.snippet_id == note_id,
CodeShape.status.in_(("instance", "variant")),
CodeShape.vanished_at.is_(None),
)
)
).scalars().all()
readable: dict[int, bool] = {}
out: dict[str, list[dict]] = {"instances": [], "variants": []}
for row in rows:
if row.project_id not in readable:
readable[row.project_id] = await access.can_read_project(
user_id, row.project_id
)
if not readable[row.project_id]:
continue
out["instances" if row.status == "instance" else "variants"].append(
_consumer_dict(row)
)
return out