mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-08-17 21:25:46 +02:00
@@ -143,11 +143,13 @@ class PostgresSaver(BasePostgresSaver):
|
||||
"""
|
||||
where, args = self._search_where(config, filter, before)
|
||||
query = self.SELECT_SQL + where + " ORDER BY checkpoint_id DESC"
|
||||
if limit:
|
||||
query += f" LIMIT {limit}"
|
||||
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
|
||||
with self._cursor() as cur:
|
||||
cur.execute(query, args)
|
||||
cur.execute(query, params)
|
||||
values = cur.fetchall()
|
||||
if not values:
|
||||
return
|
||||
|
||||
@@ -132,11 +132,13 @@ class AsyncPostgresSaver(BasePostgresSaver):
|
||||
"""
|
||||
where, args = self._search_where(config, filter, before)
|
||||
query = self.SELECT_SQL + where + " ORDER BY checkpoint_id DESC"
|
||||
if limit:
|
||||
query += f" LIMIT {limit}"
|
||||
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, args, binary=True)
|
||||
await cur.execute(query, params, binary=True)
|
||||
values = await cur.fetchall()
|
||||
if not values:
|
||||
return
|
||||
|
||||
@@ -272,10 +272,12 @@ class ShallowPostgresSaver(BasePostgresSaver):
|
||||
"""
|
||||
where, args = self._search_where(config, filter, before)
|
||||
query = self.SELECT_SQL + where
|
||||
if limit:
|
||||
query += f" LIMIT {limit}"
|
||||
params = list(args)
|
||||
if limit is not None:
|
||||
query += " LIMIT %s"
|
||||
params.append(int(limit))
|
||||
with self._cursor() as cur:
|
||||
cur.execute(self.SELECT_SQL + where, args, binary=True)
|
||||
cur.execute(query, params, binary=True)
|
||||
for value in cur:
|
||||
checkpoint: Checkpoint = {
|
||||
**value["checkpoint"],
|
||||
@@ -636,10 +638,12 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
|
||||
"""
|
||||
where, args = self._search_where(config, filter, before)
|
||||
query = self.SELECT_SQL + where
|
||||
if limit:
|
||||
query += f" LIMIT {limit}"
|
||||
params = list(args)
|
||||
if limit is not None:
|
||||
query += " LIMIT %s"
|
||||
params.append(int(limit))
|
||||
async with self._cursor() as cur:
|
||||
await cur.execute(self.SELECT_SQL + where, args, binary=True)
|
||||
await cur.execute(query, params, binary=True)
|
||||
async for value in cur:
|
||||
checkpoint: Checkpoint = {
|
||||
**value["checkpoint"],
|
||||
|
||||
@@ -266,6 +266,27 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
|
||||
k: v(self) if v is not None and callable(v) else v
|
||||
for k, v in migration.params.items()
|
||||
}
|
||||
if "dims" in params:
|
||||
try:
|
||||
params["dims"] = int(params["dims"])
|
||||
except Exception as e:
|
||||
raise ValueError(
|
||||
f"Invalid dims for vector index: {params['dims']}"
|
||||
) from e
|
||||
if "vector_type" in params:
|
||||
vt = str(params["vector_type"])
|
||||
if vt not in ("vector", "halfvec"):
|
||||
raise ValueError(
|
||||
f"Invalid vector_type for pgvector: {vt}"
|
||||
)
|
||||
params["vector_type"] = vt
|
||||
if "index_type" in params:
|
||||
it = str(params["index_type"])
|
||||
if it not in ("hnsw", "ivfflat"):
|
||||
raise ValueError(
|
||||
f"Invalid index_type for pgvector: {it}"
|
||||
)
|
||||
params["index_type"] = it
|
||||
sql = sql % params
|
||||
await cur.execute(sql)
|
||||
await cur.execute(
|
||||
|
||||
@@ -327,31 +327,36 @@ class BasePostgresStore(Generic[C]):
|
||||
embedding_request: tuple[str, Sequence[tuple[str, str, str, str]]] | None = None
|
||||
if inserts:
|
||||
values = []
|
||||
insertion_params = []
|
||||
insertion_params: list[Any] = []
|
||||
vector_values = []
|
||||
embedding_request_params = []
|
||||
# Handle TTL expiration
|
||||
|
||||
# First handle main store insertions
|
||||
for op in inserts:
|
||||
if op.ttl is not None:
|
||||
expires_at_str = f"NOW() + INTERVAL '{op.ttl * 60} seconds'"
|
||||
ttl_minutes = op.ttl
|
||||
else:
|
||||
expires_at_str = "NULL"
|
||||
ttl_minutes = None
|
||||
|
||||
values.append(
|
||||
f"(%s, %s, %s, CURRENT_TIMESTAMP, CURRENT_TIMESTAMP, {expires_at_str}, %s)"
|
||||
)
|
||||
insertion_params.extend(
|
||||
[
|
||||
(
|
||||
_namespace_to_text(op.namespace),
|
||||
op.key,
|
||||
Jsonb(cast(dict, op.value)),
|
||||
ttl_minutes,
|
||||
]
|
||||
)
|
||||
)
|
||||
if op.ttl is not None:
|
||||
values.append(
|
||||
"(%s, %s, %s, CURRENT_TIMESTAMP, CURRENT_TIMESTAMP, NOW() + %s::interval, %s)"
|
||||
)
|
||||
ttl_minutes = float(op.ttl)
|
||||
insertion_params.extend(
|
||||
(
|
||||
f"{ttl_minutes * 60} seconds",
|
||||
ttl_minutes,
|
||||
)
|
||||
)
|
||||
else:
|
||||
values.append(
|
||||
"(%s, %s, %s, CURRENT_TIMESTAMP, CURRENT_TIMESTAMP, NULL, %s)"
|
||||
)
|
||||
insertion_params.append(None)
|
||||
|
||||
# Then handle embeddings if configured
|
||||
if self.index_config:
|
||||
@@ -465,6 +470,10 @@ class BasePostgresStore(Generic[C]):
|
||||
cast(dict, self.index_config)["dims"],
|
||||
)
|
||||
else:
|
||||
if vector_type not in ("vector", "halfvec"):
|
||||
raise ValueError(
|
||||
f"Invalid vector_type for pgvector: {vector_type}"
|
||||
)
|
||||
score_operator = score_operator % ("%s", vector_type)
|
||||
|
||||
vectors_per_doc_estimate = cast(dict, self.index_config)[
|
||||
@@ -1122,6 +1131,27 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
|
||||
k: v(self) if v is not None and callable(v) else v
|
||||
for k, v in migration.params.items()
|
||||
}
|
||||
if "dims" in params:
|
||||
try:
|
||||
params["dims"] = int(params["dims"])
|
||||
except Exception as e:
|
||||
raise ValueError(
|
||||
f"Invalid dims for vector index: {params['dims']}"
|
||||
) from e
|
||||
if "vector_type" in params:
|
||||
vt = str(params["vector_type"])
|
||||
if vt not in ("vector", "halfvec"):
|
||||
raise ValueError(
|
||||
f"Invalid vector_type for pgvector: {vt}"
|
||||
)
|
||||
params["vector_type"] = vt
|
||||
if "index_type" in params:
|
||||
it = str(params["index_type"])
|
||||
if it not in ("hnsw", "ivfflat"):
|
||||
raise ValueError(
|
||||
f"Invalid index_type for pgvector: {it}"
|
||||
)
|
||||
params["index_type"] = it
|
||||
sql = sql % params
|
||||
cur.execute(sql)
|
||||
cur.execute("INSERT INTO vector_migrations (v) VALUES (%s)", (v,))
|
||||
|
||||
Reference in New Issue
Block a user