239 lines
8.9 KiB
Python

from __future__ import annotations
from collections.abc import Callable, Mapping
from datetime import datetime, timezone
from typing import Any, cast
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
BaseCheckpointSaver,
Checkpoint,
)
from langgraph.checkpoint.base.id import uuid6
from langgraph.checkpoint.serde.types import _DeltaSnapshot
from langgraph._internal._config import DELTA_MAX_SUPERSTEPS_SINCE_SNAPSHOT
from langgraph._internal._typing import MISSING
from langgraph.channels.base import BaseChannel
from langgraph.channels.delta import DeltaChannel
from langgraph.managed.base import ManagedValueMapping, ManagedValueSpec
LATEST_VERSION = 4
GetNextVersion = Callable[[Any, None], Any]
def empty_checkpoint() -> Checkpoint:
return Checkpoint(
v=LATEST_VERSION,
id=str(uuid6(clock_seq=-2)),
ts=datetime.now(timezone.utc).isoformat(),
channel_values={},
channel_versions={},
versions_seen={},
)
def delta_channels_to_snapshot(
channels: Mapping[str, BaseChannel],
counters_since_delta_snapshot: Mapping[str, tuple[int, int]],
) -> set[str]:
"""Return the set of DeltaChannel names that should snapshot now.
A channel snapshots when EITHER its accumulated update count reaches
`snapshot_frequency` OR the total supersteps since its last snapshot
reaches `DELTA_MAX_SUPERSTEPS_SINCE_SNAPSHOT`. This is a pure
predicate — no mutation.
"""
result: set[str] = set()
for name, ch in channels.items():
if not isinstance(ch, DeltaChannel) or not ch.is_available():
continue
updates, supersteps = counters_since_delta_snapshot.get(name, (0, 0))
if (
updates >= ch.snapshot_frequency
or supersteps >= DELTA_MAX_SUPERSTEPS_SINCE_SNAPSHOT
):
result.add(name)
return result
def create_checkpoint(
checkpoint: Checkpoint,
channels: Mapping[str, BaseChannel] | None,
step: int,
*,
id: str | None = None,
updated_channels: set[str] | None = None,
get_next_version: GetNextVersion | None = None,
channels_to_snapshot: set[str] | None = None,
) -> Checkpoint:
"""Build a new Checkpoint from the previous one and live channel state.
For each name in `channels_to_snapshot`, a `_DeltaSnapshot(value)` blob
is written into `channel_values[k]`. Other delta channels are omitted
from `channel_values` — the ancestor walk reconstructs their state
from `checkpoint_writes`. Callers compute the set via
`delta_channels_to_snapshot(channels, counters)`; defaults to empty
(no snapshots) when not provided.
"""
ts = datetime.now(timezone.utc).isoformat()
channels_to_snapshot = channels_to_snapshot or set()
if channels is None:
values = checkpoint["channel_values"]
channel_versions = checkpoint["channel_versions"]
else:
values = {}
channel_versions = dict(checkpoint["channel_versions"])
for k in channels:
if k not in channel_versions:
continue
ch = channels[k]
if k in channels_to_snapshot:
# In exit mode, the snapshot decision is deferred to exit
# time (intermediate steps have do_checkpoint=False). The
# channel's count may have reached snapshot_frequency over
# several supersteps, but the LAST superstep may not have
# written to this channel. In that case apply_writes()
# (in _algo.py) didn't bump this channel's version, so
# saver.put() wouldn't include it in new_versions and
# the snapshot blob would be silently dropped. The manual
# bump below closes the gap. In sync/async durability this
# branch is effectively dead code (the step that pushes
# the count to freq always writes the channel).
if get_next_version is not None and (
updated_channels is None or k not in updated_channels
):
channel_versions[k] = get_next_version(channel_versions[k], None)
values[k] = _DeltaSnapshot(ch.get())
else:
v = ch.checkpoint()
if v is not MISSING:
values[k] = v
return Checkpoint(
v=LATEST_VERSION,
ts=ts,
id=id or str(uuid6(clock_seq=step)),
channel_values=values,
channel_versions=channel_versions,
versions_seen=checkpoint["versions_seen"],
updated_channels=None if updated_channels is None else sorted(updated_channels),
)
def _needs_replay(spec: BaseChannel, stored: object) -> bool:
"""True if `spec` is a `DeltaChannel` and no value is stored at this
checkpoint, requiring an ancestor walk to reconstruct.
`_DeltaSnapshot` blobs and plain values (migration) resolve directly via
`from_checkpoint` — only absence (`MISSING`) triggers replay.
"""
if not isinstance(spec, DeltaChannel):
return False
return stored is MISSING
def channels_from_checkpoint(
specs: Mapping[str, BaseChannel | ManagedValueSpec],
checkpoint: Checkpoint,
*,
saver: BaseCheckpointSaver | None = None,
config: RunnableConfig | None = None,
) -> tuple[Mapping[str, BaseChannel], ManagedValueMapping]:
"""Hydrate channels from a checkpoint.
For most channels, `spec.from_checkpoint(checkpoint["channel_values"][k])`
is sufficient. `DeltaChannel` is the exception: when the channel is
absent from `channel_values`, an ancestor walk via
`saver.get_delta_channel_history` is required to find the nearest seed
(`_DeltaSnapshot` blob or pre-migration plain value) and accumulate
the writes between it and the target. All delta channels needing
replay are batched into a single saver call.
"""
channel_specs: dict[str, BaseChannel] = {}
managed_specs: dict[str, ManagedValueSpec] = {}
for k, v in specs.items():
if isinstance(v, BaseChannel):
channel_specs[k] = v
else:
managed_specs[k] = v
delta_channels: list[str] = [
k
for k, spec in channel_specs.items()
if _needs_replay(spec, checkpoint["channel_values"].get(k, MISSING))
]
histories: Mapping[str, Any] = {}
if delta_channels and saver is not None and config is not None:
histories = saver.get_delta_channel_history(
config=config, channels=delta_channels
)
channels: dict[str, BaseChannel] = {}
for k, spec in channel_specs.items():
ch: BaseChannel
if k in histories:
delta_spec = cast(DeltaChannel, spec)
history = histories[k]
replay_ch = delta_spec.from_checkpoint(history.get("seed", MISSING))
replay_ch.replay_writes(history["writes"])
ch = replay_ch
else:
ch = spec.from_checkpoint(checkpoint["channel_values"].get(k, MISSING))
channels[k] = ch
return channels, managed_specs
async def achannels_from_checkpoint(
specs: Mapping[str, BaseChannel | ManagedValueSpec],
checkpoint: Checkpoint,
*,
saver: BaseCheckpointSaver | None = None,
config: RunnableConfig | None = None,
) -> tuple[Mapping[str, BaseChannel], ManagedValueMapping]:
"""Async version of `channels_from_checkpoint`. See docstring there."""
channel_specs: dict[str, BaseChannel] = {}
managed_specs: dict[str, ManagedValueSpec] = {}
for k, v in specs.items():
if isinstance(v, BaseChannel):
channel_specs[k] = v
else:
managed_specs[k] = v
delta_channels: list[str] = [
k
for k, spec in channel_specs.items()
if _needs_replay(spec, checkpoint["channel_values"].get(k, MISSING))
]
histories: Mapping[str, Any] = {}
if delta_channels and saver is not None and config is not None:
histories = await saver.aget_delta_channel_history(
config=config, channels=delta_channels
)
channels: dict[str, BaseChannel] = {}
for k, spec in channel_specs.items():
ch: BaseChannel
if k in histories:
delta_spec = cast(DeltaChannel, spec)
history = histories[k]
replay_ch = delta_spec.from_checkpoint(history.get("seed", MISSING))
replay_ch.replay_writes(history["writes"])
ch = replay_ch
else:
ch = spec.from_checkpoint(checkpoint["channel_values"].get(k, MISSING))
channels[k] = ch
return channels, managed_specs
def copy_checkpoint(checkpoint: Checkpoint) -> Checkpoint:
return Checkpoint(
v=checkpoint["v"],
ts=checkpoint["ts"],
id=checkpoint["id"],
channel_values=checkpoint["channel_values"].copy(),
channel_versions=checkpoint["channel_versions"].copy(),
versions_seen={k: v.copy() for k, v in checkpoint["versions_seen"].items()},
updated_channels=checkpoint.get("updated_channels", None),
)