Files
langgraph/libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py
T
2b93e8b79f fix: order delta channel replay by task path (#8544)
Fixes langchain-ai/langgraph#8382

`DeltaChannel` rebuilds its value by replaying ancestor writes through
the reducer. Every saver ordered a checkpoint's writes by `(task_id,
idx)`, but live execution applies a super-step's writes in task-path
order (`apply_writes` sorts tasks by `task_path_str(task.path[:3])`).
`task_id` is a hash of the path, so when two or more tasks write one
`DeltaChannel` in the same super-step, replay applies them in an
arbitrary permutation.

Reducers must be batching-invariant, not order-invariant, so the
permutation changes the value: `get_state` disagrees with what `invoke`
returned, and continuing the thread saves the reordered value as the
base for every later write.

## Fix

Replay orders by `(task_path, task_id, idx)`, the order
`SELECT_PENDING_SENDS_SQL` already uses for sends. `apply_writes` and
every saver now sort with one `writes_sort_key` from
`langgraph.checkpoint.base`, in Python, so live and replay can't drift
apart and don't depend on a database collation. `apply_writes` sorts by
the full task path, the string `put_writes` stores, instead of
`path[:3]`. The paths that reach `apply_writes` no longer carry task
ids, so the live order doesn't change.

`BaseCheckpointSaver`'s default `get_delta_channel_history` can't sort
by path, since `PendingWrite` has no task path, so it replays each
checkpoint's writes in `get_tuple` order. `get_tuple` now has to return
`pending_writes` in `writes_sort_key` order, and memory, SQLite and
Postgres do, so the default walk is right for any saver that follows
that. `AsyncPostgresSaver` also gets the sync
`get_delta_channel_history` that `AsyncSqliteSaver` already had; sync
reads used to fall back to the default walk.

Memory and Postgres already stored `task_path`. SQLite accepted it on
`put_writes` and dropped it, so `writes` gains the column and `setup()`
adds it to existing databases.

Writes without a task path (graph input, `update_state` updates, rows
written before the column existed) sort first by `task_id`, which is
also where live execution applies input.

## Compatibility

- Memory and Postgres already had `task_path` on disk, so existing
threads replay in the corrected order after upgrade.
- On SQLite, rows from before the upgrade read back as `''` and keep
their old order. Only new writes get the corrected order, since there is
no stored path to recover.
- SQLite has no `ADD COLUMN IF NOT EXISTS`, so `setup()` runs the
`ALTER` and treats `duplicate column name` as success, which also covers
two processes migrating one file. That error comes while SQLite prepares
the statement, before it asks for the write lock, so `setup()` on an
up-to-date database doesn't wait on other writers. A read-only database
from before the column is read with empty paths instead of failing
setup.
- Downgrade is safe: older code's `INSERT` omits the column and the
column has a default.
- `get_tuple` and `list` return `pending_writes` in `writes_sort_key`
order instead of task id order (SQLite, Postgres) or put order (memory).
Nothing in langgraph depends on the old order.
- Postgres reads `task_path` and `idx` with each pending write, so a
subclass that pairs `SELECT_SQL` with its own `_load_writes`, or the
other way round, has to match the new row shape.
- A third-party saver has to replay in `writes_sort_key` order: in its
own `get_delta_channel_history` if it has one, otherwise by returning
`pending_writes` from `get_tuple` in that order. Otherwise it fails the
new conformance tests; the `get_tuple` one is a base test, so it runs
for every saver.
- langgraph, checkpoint-sqlite and checkpoint-postgres import
`writes_sort_key` from langgraph-checkpoint, so this bumps
langgraph-checkpoint to 4.3.0 and requires it there. 4.3.0 has to be
released first.

## Limits

- Several updates in one `bulk_update_state` super-step share a task id,
so the saver keeps only the first one's writes and the `DeltaChannel`
loses the rest (plain channels are fine). That's on main too; #9128
fixes it and stores a task path per update, so with this PR those
updates also replay in the order given.
- Exit durability stores its writes differently; resume ordering there
is fixed in #9114, stacked on this PR.
- langgraphjs applies `DeltaChannel` writes in task id order, live and
on replay (langchain-ai/langgraphjs#2544), so its reads match too.
Moving JS to task path order is a follow-up.

## Tests

Each fails on main and passes here:

- `test_delta_channel_parallel_order.py`, across memory, SQLite and
Postgres: parallel writers and a `Send` fan-out, comparing `get_state`
with the live result, including sync `get_state` on the async savers.
- Three conformance tests whose task ids sort opposite to their task
paths, so they cannot pass by chance: two on
`get_delta_channel_history`, one on `get_tuple`'s `pending_writes`
order.
- SQLite migration tests from a pre-column database, sync and async,
including a read-only file.

One more that passes on main too: SQLite `setup()` while another
connection holds the write lock, with no busy timeout, sync and async.
It keeps the `ALTER` from waiting on that lock.

Thanks to @ErenAta16 for the report, the reproduction, and for tracing
`task_path` through all three backends, and to @ragnarok268 for the
conformance-test design with task ids ordered opposite to their paths.

---------

Co-authored-by: ErenAta16 <149434812+ErenAta16@users.noreply.github.com>
Co-authored-by: ragnarok268 <58264829+ragnarok268@users.noreply.github.com>
2026-10-06 17:55:04 -04:00

710 lines
28 KiB
Python

from __future__ import annotations
import asyncio
from collections import defaultdict
from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
from contextlib import asynccontextmanager
from typing import Any, cast
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
ChannelVersions,
Checkpoint,
CheckpointMetadata,
CheckpointTuple,
DeltaChannelHistory,
get_checkpoint_id,
get_serializable_checkpoint_metadata,
)
from langgraph.checkpoint.serde.base import SerializerProtocol
from langgraph.checkpoint.serde.types import _DeltaSnapshot
from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import AsyncConnectionPool
from langgraph.checkpoint.postgres import _ainternal
from langgraph.checkpoint.postgres.base import (
_DELTA_PAGE_SIZE,
BasePostgresSaver,
_build_delta_stage1_sql,
_build_delta_stage2_sql,
_DeltaStage2Row,
)
from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver
Conn = _ainternal.Conn # For backward compatibility
class AsyncPostgresSaver(BasePostgresSaver):
"""Asynchronous checkpointer that stores checkpoints in a Postgres database."""
lock: asyncio.Lock
def __init__(
self,
conn: _ainternal.Conn,
pipe: AsyncPipeline | None = None,
serde: SerializerProtocol | None = None,
) -> None:
super().__init__(serde=serde)
if isinstance(conn, AsyncConnectionPool) and pipe is not None:
raise ValueError(
"Pipeline should be used only with a single AsyncConnection, not AsyncConnectionPool."
)
self.conn = conn
self.pipe = pipe
self.lock = asyncio.Lock()
self.loop = asyncio.get_running_loop()
self.supports_pipeline = Capabilities().has_pipeline()
@classmethod
@asynccontextmanager
async def from_conn_string(
cls,
conn_string: str,
*,
pipeline: bool = False,
serde: SerializerProtocol | None = None,
) -> AsyncIterator[AsyncPostgresSaver]:
"""Create a new AsyncPostgresSaver instance from a connection string.
Args:
conn_string: The Postgres connection info string.
pipeline: whether to use AsyncPipeline
Returns:
AsyncPostgresSaver: A new AsyncPostgresSaver instance.
"""
async with await AsyncConnection.connect(
conn_string, autocommit=True, prepare_threshold=0, row_factory=dict_row
) as conn:
if pipeline:
async with conn.pipeline() as pipe:
yield cls(conn=conn, pipe=pipe, serde=serde)
else:
yield cls(conn=conn, serde=serde)
async def setup(self) -> None:
"""Set up the checkpoint database asynchronously.
This method creates the necessary tables in the Postgres database if they don't
already exist and runs database migrations. It MUST be called directly by the user
the first time checkpointer is used.
"""
async with self._cursor() as cur:
await cur.execute(self.MIGRATIONS[0])
results = await cur.execute(
"SELECT v FROM checkpoint_migrations ORDER BY v DESC LIMIT 1"
)
row = await results.fetchone()
if row is None:
version = -1
else:
version = row["v"]
for v, migration in zip(
range(version + 1, len(self.MIGRATIONS)),
self.MIGRATIONS[version + 1 :],
strict=False,
):
await cur.execute(migration)
await cur.execute(
"INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,)
)
if self.pipe:
await self.pipe.sync()
async def alist(
self,
config: RunnableConfig | None,
*,
filter: dict[str, Any] | None = None,
before: RunnableConfig | None = None,
limit: int | None = None,
) -> AsyncIterator[CheckpointTuple]:
"""List checkpoints from the database asynchronously.
This method retrieves a list of checkpoint tuples from the Postgres database based
on the provided config. The checkpoints are ordered by checkpoint ID in descending order (newest first).
Args:
config: Base configuration for filtering checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
limit: Maximum number of checkpoints to return.
Yields:
An asynchronous iterator of matching checkpoint tuples.
"""
where, args = self._search_where(config, filter, before)
query = self.SELECT_SQL + where + " ORDER BY checkpoint_id DESC"
params = list(args)
if limit is not None:
query += " LIMIT %s"
params.append(int(limit))
# if we change this to use .stream() we need to make sure to close the cursor
async with self._cursor() as cur:
await cur.execute(query, params, binary=True)
values = await cur.fetchall()
if not values:
return
# migrate pending sends if necessary
if to_migrate := [
v
for v in values
if v["checkpoint"]["v"] < 4 and v["parent_checkpoint_id"]
]:
await cur.execute(
self.SELECT_PENDING_SENDS_SQL,
(
values[0]["thread_id"],
[v["parent_checkpoint_id"] for v in to_migrate],
),
)
grouped_by_parent = defaultdict(list)
for value in to_migrate:
grouped_by_parent[value["parent_checkpoint_id"]].append(value)
async for sends in cur:
for value in grouped_by_parent[sends["checkpoint_id"]]:
if value["channel_values"] is None:
value["channel_values"] = []
self._migrate_pending_sends(
sends["sends"],
value["checkpoint"],
value["channel_values"],
)
for value in values:
yield await self._load_checkpoint_tuple(value)
async def aget_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
"""Get a checkpoint tuple from the database asynchronously.
This method retrieves a checkpoint tuple from the Postgres database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
the matching thread ID and "checkpoint_id" is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
Args:
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
thread_id = config["configurable"]["thread_id"]
checkpoint_id = get_checkpoint_id(config)
checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
if checkpoint_id:
args: tuple[Any, ...] = (thread_id, checkpoint_ns, checkpoint_id)
where = "WHERE thread_id = %s AND checkpoint_ns = %s AND checkpoint_id = %s"
else:
args = (thread_id, checkpoint_ns)
where = "WHERE thread_id = %s AND checkpoint_ns = %s ORDER BY checkpoint_id DESC LIMIT 1"
async with self._cursor() as cur:
await cur.execute(
self.SELECT_SQL + where,
args,
binary=True,
)
value = await cur.fetchone()
if value is None:
return None
# migrate pending sends if necessary
if value["checkpoint"]["v"] < 4 and value["parent_checkpoint_id"]:
await cur.execute(
self.SELECT_PENDING_SENDS_SQL,
(thread_id, [value["parent_checkpoint_id"]]),
)
if sends := await cur.fetchone():
if value["channel_values"] is None:
value["channel_values"] = []
self._migrate_pending_sends(
sends["sends"],
value["checkpoint"],
value["channel_values"],
)
return await self._load_checkpoint_tuple(value)
async def aput(
self,
config: RunnableConfig,
checkpoint: Checkpoint,
metadata: CheckpointMetadata,
new_versions: ChannelVersions,
) -> RunnableConfig:
"""Save a checkpoint to the database asynchronously.
This method saves a checkpoint to the Postgres database. The checkpoint is associated
with the provided config and its parent config (if any).
Args:
config: The config to associate with the checkpoint.
checkpoint: The checkpoint to save.
metadata: Additional metadata to save with the checkpoint.
new_versions: New channel versions as of this write.
Returns:
RunnableConfig: Updated configuration after storing the checkpoint.
"""
configurable = config["configurable"].copy()
thread_id = configurable.pop("thread_id")
checkpoint_ns = configurable.pop("checkpoint_ns")
checkpoint_id = configurable.pop("checkpoint_id", None)
copy = checkpoint.copy()
copy["channel_values"] = copy["channel_values"].copy()
next_config = {
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": checkpoint_ns,
"checkpoint_id": checkpoint["id"],
}
}
# inline primitive values in checkpoint table
# others are stored in blobs table
blob_values = {}
for k, v in checkpoint["channel_values"].items():
if isinstance(v, _DeltaSnapshot):
blob_values[k] = copy["channel_values"].pop(k)
copy["channel_values"][k] = True
elif v is None or isinstance(v, (str, int, float, bool)):
pass
else:
blob_values[k] = copy["channel_values"].pop(k)
async with self._cursor(pipeline=True) as cur:
if blob_versions := {
k: v for k, v in new_versions.items() if k in blob_values
}:
await cur.executemany(
self.UPSERT_CHECKPOINT_BLOBS_SQL,
await asyncio.to_thread(
self._dump_blobs,
thread_id,
checkpoint_ns,
blob_values,
blob_versions,
),
)
await cur.execute(
self.UPSERT_CHECKPOINTS_SQL,
(
thread_id,
checkpoint_ns,
checkpoint["id"],
checkpoint_id,
Jsonb(copy),
Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
),
)
return next_config
async def aput_writes(
self,
config: RunnableConfig,
writes: Sequence[tuple[str, Any]],
task_id: str,
task_path: str = "",
) -> None:
"""Store intermediate writes linked to a checkpoint asynchronously.
This method saves intermediate writes associated with a checkpoint to the database.
Args:
config: Configuration of the related checkpoint.
writes: List of writes to store, each as (channel, value) pair.
task_id: Identifier for the task creating the writes.
"""
query = (
self.UPSERT_CHECKPOINT_WRITES_SQL
if all(w[0] in WRITES_IDX_MAP for w in writes)
else self.INSERT_CHECKPOINT_WRITES_SQL
)
params = await asyncio.to_thread(
self._dump_writes,
config["configurable"]["thread_id"],
config["configurable"]["checkpoint_ns"],
config["configurable"]["checkpoint_id"],
task_id,
task_path,
writes,
)
async with self._cursor(pipeline=True) as cur:
await cur.executemany(query, params)
async def adelete_thread(self, thread_id: str) -> None:
"""Delete all checkpoints and writes associated with a thread ID.
Args:
thread_id: The thread ID to delete.
Returns:
None
"""
async with self._cursor(pipeline=True) as cur:
await cur.execute(
"DELETE FROM checkpoints WHERE thread_id = %s",
(str(thread_id),),
)
await cur.execute(
"DELETE FROM checkpoint_blobs WHERE thread_id = %s",
(str(thread_id),),
)
await cur.execute(
"DELETE FROM checkpoint_writes WHERE thread_id = %s",
(str(thread_id),),
)
@asynccontextmanager
async def _cursor(
self, *, pipeline: bool = False
) -> AsyncIterator[AsyncCursor[DictRow]]:
"""Create a database cursor as a context manager.
Args:
pipeline: whether to use pipeline for the DB operations inside the context manager.
Will be applied regardless of whether the AsyncPostgresSaver instance was initialized with a pipeline.
If pipeline mode is not supported, will fall back to using transaction context manager.
"""
async with self.lock, _ainternal.get_connection(self.conn) as conn:
if self.pipe:
# a connection in pipeline mode can be used concurrently
# in multiple threads/coroutines, but only one cursor can be
# used at a time
try:
async with conn.cursor(binary=True, row_factory=dict_row) as cur:
yield cur
finally:
if pipeline:
await self.pipe.sync()
elif pipeline:
# a connection not in pipeline mode can only be used by one
# thread/coroutine at a time, so we acquire a lock
if self.supports_pipeline:
async with (
conn.pipeline(),
conn.cursor(binary=True, row_factory=dict_row) as cur,
):
yield cur
else:
# Use connection's transaction context manager when pipeline mode not supported
async with (
conn.transaction(),
conn.cursor(binary=True, row_factory=dict_row) as cur,
):
yield cur
else:
async with conn.cursor(binary=True, row_factory=dict_row) as cur:
yield cur
async def aget_delta_channel_history(
self, *, config: RunnableConfig, channels: Sequence[str]
) -> Mapping[str, DeltaChannelHistory]:
"""Fast-path override of `BaseCheckpointSaver.aget_delta_channel_history`.
See `PostgresSaver.get_delta_channel_history` for design notes; this is
the async equivalent with internal stage-1 paging and per-channel
UNION ALL stage-2.
"""
if not channels:
return {}
channels = list(channels)
thread_id = config["configurable"]["thread_id"]
checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
checkpoint_id = get_checkpoint_id(config)
if checkpoint_id is None:
target = await self.aget_tuple(config)
if target is None:
return {ch: {"writes": []} for ch in channels}
checkpoint_id = target.config["configurable"]["checkpoint_id"]
stage1_sql = _build_delta_stage1_sql(channels, paged=True)
parent_of: dict[str, str | None] = {}
ver_by_i_by_cid: list[dict[str, str | None]] = [{} for _ in channels]
hb_by_i_by_cid: list[dict[str, bool]] = [{} for _ in channels]
inline_by_i_by_cid: list[dict[str, Any]] = [{} for _ in channels]
chain_by_ch: dict[str, list[str]] = {ch: [] for ch in channels}
seed_ver_by_ch: dict[str, str | None] = {ch: None for ch in channels}
seed_inline_by_ch: dict[str, Any] = {}
walk_cursor_by_ch: dict[str, str | None] = {}
seeded: set[str] = set()
cursor: str | None = None
async with self._cursor() as cur:
while True:
stage1_params: list[Any] = []
for ch in channels:
# ver_i, blob channel, blob version, inline_i
stage1_params.extend([ch, ch, ch, ch])
stage1_params.extend(
[thread_id, checkpoint_ns, cursor, cursor, _DELTA_PAGE_SIZE]
)
await cur.execute(stage1_sql, stage1_params)
page = await cur.fetchall()
if not page:
break
oldest = self._ingest_stage1_page(
cast("list[Mapping[str, Any]]", page),
channels,
parent_of,
ver_by_i_by_cid,
hb_by_i_by_cid,
inline_by_i_by_cid,
)
self._try_advance_walks(
checkpoint_id,
channels,
parent_of,
ver_by_i_by_cid,
hb_by_i_by_cid,
inline_by_i_by_cid,
chain_by_ch,
seed_ver_by_ch,
seed_inline_by_ch,
walk_cursor_by_ch,
seeded,
)
if len(seeded) == len(channels) or len(page) < _DELTA_PAGE_SIZE:
break
cursor = oldest
channels_with_chain = [ch for ch in channels if chain_by_ch[ch]]
channels_with_seed = [ch for ch in channels if seed_ver_by_ch[ch] is not None]
stage2_sql = _build_delta_stage2_sql(
channels_with_chain=channels_with_chain,
channels_with_seed=channels_with_seed,
)
if stage2_sql:
stage2_params: list[Any] = []
for ch in channels_with_chain:
stage2_params.extend([thread_id, checkpoint_ns, ch, chain_by_ch[ch]])
for ch in channels_with_seed:
stage2_params.extend([thread_id, checkpoint_ns, ch, seed_ver_by_ch[ch]])
async with self._cursor() as cur:
await cur.execute(stage2_sql, stage2_params)
stage2_rows = await cur.fetchall()
else:
stage2_rows = []
return self._build_delta_channels_writes_history(
channels=channels,
chain_by_ch=chain_by_ch,
seed_ver_by_ch=seed_ver_by_ch,
seed_inline_by_ch=seed_inline_by_ch,
stage2_rows=cast("list[_DeltaStage2Row]", stage2_rows),
)
async def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
"""
Convert a database row into a CheckpointTuple object.
Args:
value: A row from the database containing checkpoint data.
Returns:
CheckpointTuple: A structured representation of the checkpoint,
including its configuration, metadata, parent checkpoint (if any),
and pending writes.
"""
return CheckpointTuple(
{
"configurable": {
"thread_id": value["thread_id"],
"checkpoint_ns": value["checkpoint_ns"],
"checkpoint_id": value["checkpoint_id"],
}
},
{
**value["checkpoint"],
"channel_values": {
**(value["checkpoint"].get("channel_values") or {}),
**self._load_blobs(value["channel_values"]),
},
},
value["metadata"],
(
{
"configurable": {
"thread_id": value["thread_id"],
"checkpoint_ns": value["checkpoint_ns"],
"checkpoint_id": value["parent_checkpoint_id"],
}
}
if value["parent_checkpoint_id"]
else None
),
await asyncio.to_thread(self._load_writes, value["pending_writes"]),
)
def list(
self,
config: RunnableConfig | None,
*,
filter: dict[str, Any] | None = None,
before: RunnableConfig | None = None,
limit: int | None = None,
) -> Iterator[CheckpointTuple]:
"""List checkpoints from the database.
This method retrieves a list of checkpoint tuples from the Postgres database based
on the provided config. The checkpoints are ordered by checkpoint ID in descending order (newest first).
Args:
config: Base configuration for filtering checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
limit: Maximum number of checkpoints to return.
Yields:
An iterator of matching checkpoint tuples.
"""
try:
# check if we are in the main thread, only bg threads can block
# we don't check in other methods to avoid the overhead
if asyncio.get_running_loop() is self.loop:
raise asyncio.InvalidStateError(
"Synchronous calls to AsyncPostgresSaver are only allowed from a "
"different thread. From the main thread, use the async interface. "
"For example, use `checkpointer.alist(...)` or `await "
"graph.ainvoke(...)`."
)
except RuntimeError:
pass
aiter_ = self.alist(config, filter=filter, before=before, limit=limit)
while True:
try:
yield asyncio.run_coroutine_threadsafe(
anext(aiter_), # type: ignore[arg-type]
self.loop,
).result()
except StopAsyncIteration:
break
def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the Postgres database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
the matching thread ID and "checkpoint_id" is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
Args:
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
try:
# check if we are in the main thread, only bg threads can block
# we don't check in other methods to avoid the overhead
if asyncio.get_running_loop() is self.loop:
raise asyncio.InvalidStateError(
"Synchronous calls to AsyncPostgresSaver are only allowed from a "
"different thread. From the main thread, use the async interface. "
"For example, use `await checkpointer.aget_tuple(...)` or `await "
"graph.ainvoke(...)`."
)
except RuntimeError:
pass
return asyncio.run_coroutine_threadsafe(
self.aget_tuple(config), self.loop
).result()
def put(
self,
config: RunnableConfig,
checkpoint: Checkpoint,
metadata: CheckpointMetadata,
new_versions: ChannelVersions,
) -> RunnableConfig:
"""Save a checkpoint to the database.
This method saves a checkpoint to the Postgres database. The checkpoint is associated
with the provided config and its parent config (if any).
Args:
config: The config to associate with the checkpoint.
checkpoint: The checkpoint to save.
metadata: Additional metadata to save with the checkpoint.
new_versions: New channel versions as of this write.
Returns:
RunnableConfig: Updated configuration after storing the checkpoint.
"""
return asyncio.run_coroutine_threadsafe(
self.aput(config, checkpoint, metadata, new_versions), self.loop
).result()
def put_writes(
self,
config: RunnableConfig,
writes: Sequence[tuple[str, Any]],
task_id: str,
task_path: str = "",
) -> None:
"""Store intermediate writes linked to a checkpoint.
This method saves intermediate writes associated with a checkpoint to the database.
Args:
config: Configuration of the related checkpoint.
writes: List of writes to store, each as (channel, value) pair.
task_id: Identifier for the task creating the writes.
task_path: Path of the task creating the writes.
"""
return asyncio.run_coroutine_threadsafe(
self.aput_writes(config, writes, task_id, task_path), self.loop
).result()
def delete_thread(self, thread_id: str) -> None:
"""Delete all checkpoints and writes associated with a thread ID.
Args:
thread_id: The thread ID to delete.
Returns:
None
"""
try:
# check if we are in the main thread, only bg threads can block
# we don't check in other methods to avoid the overhead
if asyncio.get_running_loop() is self.loop:
raise asyncio.InvalidStateError(
"Synchronous calls to AsyncPostgresSaver are only allowed from a "
"different thread. From the main thread, use the async interface. "
"For example, use `await checkpointer.aget_tuple(...)` or `await "
"graph.ainvoke(...)`."
)
except RuntimeError:
pass
return asyncio.run_coroutine_threadsafe(
self.adelete_thread(thread_id), self.loop
).result()
def get_delta_channel_history(
self, *, config: RunnableConfig, channels: Sequence[str]
) -> Mapping[str, DeltaChannelHistory]:
"""Sync bridge to `aget_delta_channel_history`, guarded like `get_tuple`."""
try:
if asyncio.get_running_loop() is self.loop:
raise asyncio.InvalidStateError(
"Synchronous calls to AsyncPostgresSaver are only allowed from a "
"different thread. From the main thread, use the async interface. "
"For example, use `await checkpointer.aget_delta_channel_history(...)`."
)
except RuntimeError:
pass
return asyncio.run_coroutine_threadsafe(
self.aget_delta_channel_history(config=config, channels=channels),
self.loop,
).result()
__all__ = ["AsyncPostgresSaver", "AsyncShallowPostgresSaver", "Conn"]