Files
langgraph/libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/__init__.py
T
Elior Nataf LackritzandGitHub a5dbacae0d fix(checkpoint-postgres,checkpoint-sqlite): treat an empty checkpoint_id as the latest in delta history (#9262)
`PostgresSaver` and `SqliteSaver`, sync and async, read a DeltaChannel's
history from the latest checkpoint only when the config's
`checkpoint_id` was missing or `None`. An empty one was looked up as an
id, matched nothing, and came back with no seed and no writes, while
their own `get_tuple` treats an empty id as the latest checkpoint, as
the default implementation does. They now check for a missing or empty
id the way `get_tuple` does. The in-memory saver gets the same in #9257.

Graphs always pass the id of a saved checkpoint, so only direct callers
of the saver API hit this.

## Tests

-
`test_{sync,async}_empty_checkpoint_id_reads_from_the_latest_checkpoint`
in `checkpoint-postgres/tests/test_delta_pagination.py` and
`checkpoint-sqlite/tests/test_delta_parent_walk.py`: all four fail on
main.
- The `checkpoint-postgres` (Postgres 16) and `checkpoint-sqlite` suites
pass, and `lint_package` and `lint_tests` are clean in both.
2026-10-09 13:44:51 -04:00

662 lines
25 KiB
Python

from __future__ import annotations
import json
import random
import sqlite3
import threading
from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
from contextlib import closing, contextmanager
from typing import Any, cast
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
BaseCheckpointSaver,
ChannelVersions,
Checkpoint,
CheckpointMetadata,
CheckpointTuple,
DeltaChannelHistory,
SerializerProtocol,
get_checkpoint_id,
get_checkpoint_metadata,
)
from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
from langgraph.checkpoint.sqlite._delta import (
DELTA_STAGE1_SQL,
build_delta_channels_writes_history,
build_delta_stage2_sql,
step_walk_with_row,
)
from langgraph.checkpoint.sqlite.utils import (
load_pending_writes,
pending_writes_sql,
search_where,
)
_AIO_ERROR_MSG = (
"The SqliteSaver does not support async methods. "
"Consider using AsyncSqliteSaver instead.\n"
"from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver\n"
"Note: AsyncSqliteSaver requires the aiosqlite package to use.\n"
"Install with:\n`pip install aiosqlite`\n"
"See https://langchain-ai.github.io/langgraph/reference/checkpoints/#langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver"
"for more information."
)
class SqliteSaver(BaseCheckpointSaver[str]):
"""A checkpoint saver that stores checkpoints in a SQLite database.
Note:
This class is meant for lightweight, synchronous use cases
(demos and small projects) and does not
scale to multiple threads.
For a similar sqlite saver with `async` support,
consider using [AsyncSqliteSaver][langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver].
Args:
conn (sqlite3.Connection): The SQLite database connection.
serde (Optional[SerializerProtocol]): The serializer to use for serializing and deserializing checkpoints. Defaults to JsonPlusSerializerCompat.
Examples:
>>> import sqlite3
>>> from langgraph.checkpoint.sqlite import SqliteSaver
>>> from langgraph.graph import StateGraph
>>>
>>> builder = StateGraph(int)
>>> builder.add_node("add_one", lambda x: x + 1)
>>> builder.set_entry_point("add_one")
>>> builder.set_finish_point("add_one")
>>> # Create a new SqliteSaver instance
>>> # Note: check_same_thread=False is OK as the implementation uses a lock
>>> # to ensure thread safety.
>>> conn = sqlite3.connect("checkpoints.sqlite", check_same_thread=False)
>>> memory = SqliteSaver(conn)
>>> graph = builder.compile(checkpointer=memory)
>>> config = {"configurable": {"thread_id": "1"}}
>>> graph.get_state(config)
>>> result = graph.invoke(3, config)
>>> graph.get_state(config)
StateSnapshot(values=4, next=(), config={'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '0c62ca34-ac19-445d-bbb0-5b4984975b2a'}}, parent_config=None)
"""
conn: sqlite3.Connection
is_setup: bool
_has_task_path: bool = True
def __init__(
self,
conn: sqlite3.Connection,
*,
serde: SerializerProtocol | None = None,
) -> None:
super().__init__(serde=serde)
self.jsonplus_serde = JsonPlusSerializer()
self.conn = conn
self.is_setup = False
self.lock = threading.Lock()
@classmethod
@contextmanager
def from_conn_string(cls, conn_string: str) -> Iterator[SqliteSaver]:
"""Create a new SqliteSaver instance from a connection string.
Args:
conn_string: The SQLite connection string.
Yields:
SqliteSaver: A new SqliteSaver instance.
Examples:
In memory:
with SqliteSaver.from_conn_string(":memory:") as memory:
...
To disk:
with SqliteSaver.from_conn_string("checkpoints.sqlite") as memory:
...
"""
with closing(
sqlite3.connect(
conn_string,
# https://ricardoanderegg.com/posts/python-sqlite-thread-safety/
check_same_thread=False,
)
) as conn:
yield cls(conn)
def setup(self) -> None:
"""Set up the checkpoint database.
This method creates the necessary tables in the SQLite database if they don't
already exist. It is called automatically when needed and should not be called
directly by the user.
"""
if self.is_setup:
return
self.conn.executescript(
"""
PRAGMA journal_mode=WAL;
CREATE TABLE IF NOT EXISTS checkpoints (
thread_id TEXT NOT NULL,
checkpoint_ns TEXT NOT NULL DEFAULT '',
checkpoint_id TEXT NOT NULL,
parent_checkpoint_id TEXT,
type TEXT,
checkpoint BLOB,
metadata BLOB,
PRIMARY KEY (thread_id, checkpoint_ns, checkpoint_id)
);
CREATE TABLE IF NOT EXISTS writes (
thread_id TEXT NOT NULL,
checkpoint_ns TEXT NOT NULL DEFAULT '',
checkpoint_id TEXT NOT NULL,
task_id TEXT NOT NULL,
task_path TEXT NOT NULL DEFAULT '',
idx INTEGER NOT NULL,
channel TEXT NOT NULL,
type TEXT,
value BLOB,
PRIMARY KEY (thread_id, checkpoint_ns, checkpoint_id, task_id, idx)
);
"""
)
# sqlite has no ADD COLUMN IF NOT EXISTS; this migrates databases
# created before `task_path` existed and is a no-op on the rest.
try:
self.conn.execute(
"ALTER TABLE writes ADD COLUMN task_path TEXT NOT NULL DEFAULT ''"
)
except sqlite3.OperationalError as e:
# A read-only database from before the column can still be read;
# its rows would all read back as '' anyway.
if "readonly database" in str(e):
self._has_task_path = False
elif "duplicate column name" not in str(e):
raise
self.is_setup = True
@contextmanager
def cursor(self, transaction: bool = True) -> Iterator[sqlite3.Cursor]:
"""Get a cursor for the SQLite database.
This method returns a cursor for the SQLite database. It is used internally
by the SqliteSaver and should not be called directly by the user.
Args:
transaction (bool): Whether to commit the transaction when the cursor is closed. Defaults to True.
Yields:
sqlite3.Cursor: A cursor for the SQLite database.
"""
with self.lock:
self.setup()
cur = self.conn.cursor()
try:
yield cur
finally:
if transaction:
self.conn.commit()
cur.close()
def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the SQLite 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.
Examples:
Basic:
>>> config = {"configurable": {"thread_id": "1"}}
>>> checkpoint_tuple = memory.get_tuple(config)
>>> print(checkpoint_tuple)
CheckpointTuple(...)
With checkpoint ID:
>>> config = {
... "configurable": {
... "thread_id": "1",
... "checkpoint_ns": "",
... "checkpoint_id": "1ef4f797-8335-6428-8001-8a1503f9b875",
... }
... }
>>> checkpoint_tuple = memory.get_tuple(config)
>>> print(checkpoint_tuple)
CheckpointTuple(...)
"""
checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
with self.cursor(transaction=False) as cur:
# find the latest checkpoint for the thread_id
if checkpoint_id := get_checkpoint_id(config):
cur.execute(
"SELECT thread_id, checkpoint_id, parent_checkpoint_id, type, checkpoint, metadata FROM checkpoints WHERE thread_id = ? AND checkpoint_ns = ? AND checkpoint_id = ?",
(
str(config["configurable"]["thread_id"]),
checkpoint_ns,
checkpoint_id,
),
)
else:
cur.execute(
"SELECT thread_id, checkpoint_id, parent_checkpoint_id, type, checkpoint, metadata FROM checkpoints WHERE thread_id = ? AND checkpoint_ns = ? ORDER BY checkpoint_id DESC LIMIT 1",
(str(config["configurable"]["thread_id"]), checkpoint_ns),
)
# if a checkpoint is found, return it
if value := cur.fetchone():
(
thread_id,
checkpoint_id,
parent_checkpoint_id,
type,
checkpoint,
metadata,
) = value
if not get_checkpoint_id(config):
config = {
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": checkpoint_ns,
"checkpoint_id": checkpoint_id,
}
}
# find any pending writes
cur.execute(
pending_writes_sql(self._has_task_path),
(
str(config["configurable"]["thread_id"]),
checkpoint_ns,
str(config["configurable"]["checkpoint_id"]),
),
)
# deserialize the checkpoint and metadata
return CheckpointTuple(
config,
self.serde.loads_typed((type, checkpoint)),
cast(
CheckpointMetadata,
json.loads(metadata) if metadata is not None else {},
),
(
{
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": checkpoint_ns,
"checkpoint_id": parent_checkpoint_id,
}
}
if parent_checkpoint_id
else None
),
load_pending_writes(cur, self.serde),
)
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 SQLite database based
on the provided config. The checkpoints are ordered by checkpoint ID in descending order (newest first).
Args:
config: The config to use for listing the checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
limit: The maximum number of checkpoints to return.
Yields:
An iterator of checkpoint tuples.
Examples:
>>> from langgraph.checkpoint.sqlite import SqliteSaver
>>> with SqliteSaver.from_conn_string(":memory:") as memory:
... # Run a graph, then list the checkpoints
>>> config = {"configurable": {"thread_id": "1"}}
>>> checkpoints = list(memory.list(config, limit=2))
>>> print(checkpoints)
[CheckpointTuple(...), CheckpointTuple(...)]
>>> config = {"configurable": {"thread_id": "1"}}
>>> before = {"configurable": {"checkpoint_id": "1ef4f797-8335-6428-8001-8a1503f9b875"}}
>>> with SqliteSaver.from_conn_string(":memory:") as memory:
... # Run a graph, then list the checkpoints
>>> checkpoints = list(memory.list(config, before=before))
>>> print(checkpoints)
[CheckpointTuple(...), ...]
"""
where, param_values = search_where(config, filter, before)
query = f"""SELECT thread_id, checkpoint_ns, checkpoint_id, parent_checkpoint_id, type, checkpoint, metadata
FROM checkpoints
{where}
ORDER BY checkpoint_id DESC"""
if limit is not None:
query += " LIMIT ?"
param_values = (*param_values, limit)
with self.cursor(transaction=False) as cur, closing(self.conn.cursor()) as wcur:
cur.execute(query, param_values)
for (
thread_id,
checkpoint_ns,
checkpoint_id,
parent_checkpoint_id,
type,
checkpoint,
metadata,
) in cur:
wcur.execute(
pending_writes_sql(self._has_task_path),
(thread_id, checkpoint_ns, checkpoint_id),
)
yield CheckpointTuple(
{
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": checkpoint_ns,
"checkpoint_id": checkpoint_id,
}
},
self.serde.loads_typed((type, checkpoint)),
cast(
CheckpointMetadata,
json.loads(metadata) if metadata is not None else {},
),
(
{
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": checkpoint_ns,
"checkpoint_id": parent_checkpoint_id,
}
}
if parent_checkpoint_id
else None
),
load_pending_writes(wcur, self.serde),
)
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 SQLite 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.
Examples:
>>> from langgraph.checkpoint.sqlite import SqliteSaver
>>> with SqliteSaver.from_conn_string(":memory:") as memory:
>>> config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
>>> checkpoint = {"ts": "2024-05-04T06:32:42.235444+00:00", "id": "1ef4f797-8335-6428-8001-8a1503f9b875", "channel_values": {"key": "value"}}
>>> saved_config = memory.put(config, checkpoint, {"source": "input", "step": 1, "writes": {"key": "value"}}, {})
>>> print(saved_config)
{'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef4f797-8335-6428-8001-8a1503f9b875'}}
"""
thread_id = config["configurable"]["thread_id"]
checkpoint_ns = config["configurable"]["checkpoint_ns"]
type_, serialized_checkpoint = self.serde.dumps_typed(checkpoint)
serialized_metadata = json.dumps(
get_checkpoint_metadata(config, metadata), ensure_ascii=False
).encode("utf-8", "ignore")
with self.cursor() as cur:
cur.execute(
"INSERT OR REPLACE INTO checkpoints (thread_id, checkpoint_ns, checkpoint_id, parent_checkpoint_id, type, checkpoint, metadata) VALUES (?, ?, ?, ?, ?, ?, ?)",
(
str(config["configurable"]["thread_id"]),
checkpoint_ns,
checkpoint["id"],
config["configurable"].get("checkpoint_id"),
type_,
serialized_checkpoint,
serialized_metadata,
),
)
return {
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": checkpoint_ns,
"checkpoint_id": checkpoint["id"],
}
}
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 SQLite 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.
"""
query = (
"INSERT OR REPLACE INTO writes (thread_id, checkpoint_ns, checkpoint_id, task_id, task_path, idx, channel, type, value) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)"
if all(w[0] in WRITES_IDX_MAP for w in writes)
else "INSERT OR IGNORE INTO writes (thread_id, checkpoint_ns, checkpoint_id, task_id, task_path, idx, channel, type, value) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)"
)
with self.cursor() as cur:
cur.executemany(
query,
[
(
str(config["configurable"]["thread_id"]),
str(config["configurable"]["checkpoint_ns"]),
str(config["configurable"]["checkpoint_id"]),
task_id,
task_path,
WRITES_IDX_MAP.get(channel, idx),
channel,
*self.serde.dumps_typed(value),
)
for idx, (channel, value) in enumerate(writes)
],
)
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
"""
with self.cursor() as cur:
cur.execute(
"DELETE FROM checkpoints WHERE thread_id = ?",
(str(thread_id),),
)
cur.execute(
"DELETE FROM writes WHERE thread_id = ?",
(str(thread_id),),
)
def get_delta_channel_history(
self, *, config: RunnableConfig, channels: Sequence[str]
) -> Mapping[str, DeltaChannelHistory]:
"""Fast-path override of `BaseCheckpointSaver.get_delta_channel_history`.
Two-stage query:
* Stage 1 (streamed): recursive CTE over `checkpoints` following
`parent_checkpoint_id` from the target, returning
`(checkpoint_id, type, checkpoint)` per ancestor. Sqlite has no
JSONB, so we ship the full serialized checkpoint blob and inspect
`channel_values` in Python. Stops reading when every channel has
found its seed or the chain is exhausted.
* Stage 2 (per-channel UNION ALL): one branch per channel reading
`writes` filtered to that channel's specific `chain_cids`. No
separate seed-blob fetch — sqlite stores `channel_values` inline
in the checkpoint blob, so seeds come back from stage 1.
"""
if not channels:
return {}
channels = list(channels)
thread_id = str(config["configurable"]["thread_id"])
checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
checkpoint_id = get_checkpoint_id(config)
if not checkpoint_id:
target = self.get_tuple(config)
if target is None:
return {ch: {"writes": []} for ch in channels}
checkpoint_id = target.config["configurable"]["checkpoint_id"]
chain_by_ch: dict[str, list[str]] = {ch: [] for ch in channels}
seed_val_by_ch: dict[str, Any] = {}
walk_state: dict[str, Any] = {}
seeded: set[str] = set()
with self.cursor(transaction=False) as cur:
cur.execute(
DELTA_STAGE1_SQL,
(thread_id, checkpoint_ns, checkpoint_id, thread_id, checkpoint_ns),
)
for row in cur:
cid, type_tag, blob = row
if step_walk_with_row(
cid=cid,
type_tag=type_tag,
blob=blob,
target_id=checkpoint_id,
serde=self.serde,
chain_by_ch=chain_by_ch,
seed_val_by_ch=seed_val_by_ch,
walk_state=walk_state,
seeded=seeded,
channels=channels,
):
break
channels_with_chain = [ch for ch in channels if chain_by_ch[ch]]
stage2_sql = build_delta_stage2_sql(
has_task_path=self._has_task_path,
chain_lens=[len(chain_by_ch[ch]) for ch in channels_with_chain],
)
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]]
)
cur.execute(stage2_sql, stage2_params)
stage2_rows = cast(
"list[tuple[str, str, str, int, str, bytes, str]]", cur.fetchall()
)
else:
stage2_rows = []
return build_delta_channels_writes_history(
channels=channels,
chain_by_ch=chain_by_ch,
seed_val_by_ch=seed_val_by_ch,
seeded=seeded,
stage2_rows=stage2_rows,
serde=self.serde,
)
async def aget_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
"""Get a checkpoint tuple from the database asynchronously.
Note:
This async method is not supported by the SqliteSaver class.
Use get_tuple() instead, or consider using [AsyncSqliteSaver][langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver].
"""
raise NotImplementedError(_AIO_ERROR_MSG)
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.
Note:
This async method is not supported by the SqliteSaver class.
Use list() instead, or consider using [AsyncSqliteSaver][langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver].
"""
raise NotImplementedError(_AIO_ERROR_MSG)
yield
async def aput(
self,
config: RunnableConfig,
checkpoint: Checkpoint,
metadata: CheckpointMetadata,
new_versions: ChannelVersions,
) -> RunnableConfig:
"""Save a checkpoint to the database asynchronously.
Note:
This async method is not supported by the SqliteSaver class.
Use put() instead, or consider using [AsyncSqliteSaver][langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver].
"""
raise NotImplementedError(_AIO_ERROR_MSG)
def get_next_version(self, current: str | None, channel: None) -> str:
"""Generate the next version ID for a channel.
This method creates a new version identifier for a channel based on its current version.
Args:
current (Optional[str]): The current version identifier of the channel.
Returns:
str: The next version identifier, which is guaranteed to be monotonically increasing.
"""
if current is None:
current_v = 0
elif isinstance(current, int):
current_v = current
else:
current_v = int(current.split(".")[0])
next_v = current_v + 1
next_h = random.random()
return f"{next_v:032}.{next_h:016}"