Files
chat/chat/services/snapshot.py
T

246 lines
9.2 KiB
Python

"""Snapshot service — write a JSON dump of all projected tables to disk.
Two snapshot kinds, both covered by this module:
* ``rewind`` (T28, Requirements §10.1): pre-rewind safety snapshot so the
user can recover if a rewind was a mistake. Retention: 14 days.
* ``periodic`` (T31, Requirements §10.4): full-state checkpoint taken
every 100 events OR every 30 minutes since the last one. Retention:
the most recent 5 are kept; older ones are pruned on write.
Both kinds live under ``data/snapshots/{kind}/`` with a UTC timestamp
filename so chronological listing matches creation order.
The dump captures the event log (so the original event sequence is
preserved verbatim), every projected table, and a top-level
``last_event_id`` recording the highest ``event_log.id`` at snapshot
time. The ``last_event_id`` is what the cold-load fast-path uses to
replay only events past the snapshot rather than the entire log.
The FTS shadow table ``memories_fts`` is intentionally skipped — it's a
virtual table maintained by the ``memories_ai/au/ad`` triggers, so it
rebuilds itself on a memories re-load. Snapshotting it would also fail
``PRAGMA table_info`` cleanly since FTS5 reports its columns differently.
"""
from __future__ import annotations
import json
import time
from datetime import datetime, timezone
from pathlib import Path
from sqlite3 import Connection
# Periodic snapshot triggers (Requirements §10.4): "every 100 events OR
# every 30 minutes since last snapshot". Module-level so tests can read
# them and so the values stay together with the policy that uses them.
EVENT_COUNT_THRESHOLD = 100
TIME_THRESHOLD_SECONDS = 30 * 60 # 30 minutes
# Order doesn't affect correctness for snapshotting (we read, not write),
# but listing tables explicitly keeps the snapshot stable across schema
# evolution: a new table won't silently change the dump shape until it's
# added here.
PROJECTED_TABLES = [
"bots",
"you_entity",
"edges",
"memories",
"memories_fts",
"chats",
"chat_state",
"containers",
"scenes",
"activity",
"classifier_failures",
]
def take_snapshot(
conn: Connection, *, data_dir: Path, kind: str = "rewind"
) -> Path:
"""Write a JSON dump of the event log and projected tables.
Returns the path to the written snapshot file. Creates parent
directories as needed. Filename is a UTC timestamp in
``YYYYMMDDTHHMMSSZ`` form so chronological listing matches creation
order.
The dump's top-level ``last_event_id`` is the highest ``event_log.id``
at snapshot time (0 if the log is empty). This is what the cold-load
fast-path uses to know which suffix of the log to replay.
"""
snapshot_dir = data_dir / "snapshots" / kind
snapshot_dir.mkdir(parents=True, exist_ok=True)
timestamp = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
path = snapshot_dir / f"{timestamp}.json"
dump: dict = {}
# Record the high-water-mark id up front so cold-load can replay
# only events past it. ``MAX(id)`` is None on an empty log; treat
# that as 0 (i.e. "replay everything").
cur = conn.execute("SELECT MAX(id) FROM event_log")
max_id_row = cur.fetchone()
dump["last_event_id"] = max_id_row[0] if max_id_row[0] is not None else 0
# Event log: pull every column we care about. ``ts`` and the
# superseded/hidden flags are needed to faithfully reconstruct the
# log on restore.
cur = conn.execute(
"SELECT id, branch_id, ts, kind, payload_json, superseded_by, hidden "
"FROM event_log ORDER BY id"
)
dump["event_log"] = [
{
"id": r[0],
"branch_id": r[1],
"ts": r[2],
"kind": r[3],
"payload_json": r[4],
"superseded_by": r[5],
"hidden": r[6],
}
for r in cur.fetchall()
]
for table in PROJECTED_TABLES:
if table == "memories_fts":
# Virtual FTS5 table — rebuilt by triggers on insert, no need
# to snapshot it (and ``PRAGMA table_info`` reports its
# columns differently).
continue
cur = conn.execute(f"PRAGMA table_info({table})")
cols = [c[1] for c in cur.fetchall()]
if not cols:
# Table not present in this schema version — leave an empty
# list rather than raising, so older snapshots can survive.
dump[table] = []
continue
cur = conn.execute(f"SELECT {', '.join(cols)} FROM {table}")
dump[table] = [dict(zip(cols, row)) for row in cur.fetchall()]
# ``default=str`` covers Path-like or datetime values that might
# sneak through if a column ever stored them; the projected tables
# all use TEXT so this is mostly defensive.
path.write_text(json.dumps(dump, default=str))
return path
def latest_snapshot_path(data_dir: Path, kind: str = "periodic") -> Path | None:
"""Return the most recent snapshot file for ``kind``, or None if none exist.
Sorting by filename works because :func:`take_snapshot` uses a UTC
timestamp in ``YYYYMMDDTHHMMSSZ`` form — lexicographic order matches
chronological order.
"""
snapshot_dir = data_dir / "snapshots" / kind
if not snapshot_dir.exists():
return None
files = sorted(snapshot_dir.glob("*.json"))
return files[-1] if files else None
def should_take_periodic_snapshot(
conn: Connection, data_dir: Path
) -> bool:
"""Decide whether a periodic snapshot is due per Requirements §10.4.
The policy:
* No prior snapshot and at least one event in the log → take one.
* Time since last snapshot ≥ ``TIME_THRESHOLD_SECONDS`` → take one.
* New events since last snapshot's ``last_event_id`` ≥
``EVENT_COUNT_THRESHOLD`` → take one.
"Time since last snapshot" is measured by the file's mtime — we
don't trust the timestamp embedded in the filename for clock drift
reasons.
"""
latest = latest_snapshot_path(data_dir, kind="periodic")
if latest is None:
# No prior snapshot; take one if there are any events to capture.
cur = conn.execute("SELECT COUNT(*) FROM event_log")
return cur.fetchone()[0] > 0
age_seconds = time.time() - latest.stat().st_mtime
if age_seconds >= TIME_THRESHOLD_SECONDS:
return True
# Count events appended since the last snapshot was written. Reading
# ``last_event_id`` from the dump is cheap (a few KB at most for the
# header) but we still avoid loading the full file by parsing once.
last_dump = json.loads(latest.read_text())
last_event_id = last_dump.get("last_event_id", 0)
cur = conn.execute(
"SELECT COUNT(*) FROM event_log WHERE id > ?", (last_event_id,)
)
new_event_count = cur.fetchone()[0]
return new_event_count >= EVENT_COUNT_THRESHOLD
def prune_periodic_snapshots(data_dir: Path, keep: int = 5) -> int:
"""Delete all but the most recent ``keep`` periodic snapshots.
Returns the number of files removed. Safe to call when the directory
doesn't exist (returns 0). Sorting is by filename, which is the UTC
timestamp — same ordering :func:`latest_snapshot_path` uses.
"""
snapshot_dir = data_dir / "snapshots" / "periodic"
if not snapshot_dir.exists():
return 0
files = sorted(snapshot_dir.glob("*.json"))
to_remove = files[:-keep] if len(files) > keep else []
for f in to_remove:
f.unlink()
return len(to_remove)
def restore_from_snapshot(conn: Connection, snapshot_path: Path) -> int:
"""Restore projected tables from ``snapshot_path``.
Returns the snapshot's ``last_event_id`` so callers (the cold-load
fast-path in :func:`chat.app.lifespan`) know what suffix of the
event log still needs replaying.
Projected tables are cleared in the same FK-respecting order as
:func:`chat.services.rewind.execute_rewind`, then re-populated from
the dump. ``memories_fts`` is skipped — it's a virtual FTS5 table
that rebuilds itself when rows hit ``memories``. The event log
itself is *not* touched: cold-load assumes the on-disk log is the
source of truth and the snapshot is just a fast-forward to skip
re-projecting old events.
"""
dump = json.loads(snapshot_path.read_text())
# Same delete order as rewind: child tables before parents so FK
# ON DELETE doesn't fire on referenced rows.
conn.execute("DELETE FROM memories")
conn.execute("DELETE FROM activity")
conn.execute("DELETE FROM scenes")
conn.execute("DELETE FROM containers")
conn.execute("DELETE FROM chat_state")
conn.execute("DELETE FROM chats")
conn.execute("DELETE FROM edges")
conn.execute("DELETE FROM bots")
conn.execute("DELETE FROM you_entity")
conn.execute("DELETE FROM classifier_failures")
for table in PROJECTED_TABLES:
if table == "memories_fts":
# Rebuilt by triggers when memories rows are inserted below.
continue
rows = dump.get(table, [])
if not rows:
continue
cols = list(rows[0].keys())
placeholders = ", ".join("?" * len(cols))
col_list = ", ".join(cols)
for row in rows:
conn.execute(
f"INSERT INTO {table} ({col_list}) VALUES ({placeholders})",
tuple(row[c] for c in cols),
)
return dump.get("last_event_id", 0)