MemPalace/mempalace · error · CollectionNotInitializedError
{collection_name}
Error message
{collection_name} What it means
Error "{collection_name}" thrown in MemPalace/mempalace.
Source
Thrown at mempalace/backends/pgvector.py:900
raise DimensionMismatchError(
f"pgvector collection {self._collection_name!r} expects "
f"embedding dimension {existing_dim}, got {dimension}"
)
self._known_dimension = existing_dim or dimension
def _scroll(
self,
*,
where=None,
with_embedding=False,
with_document=True,
limit=None,
offset=None,
) -> list[dict]:
self._ensure_open()
if not self._table_exists():
if self._marker_exists():
raise CollectionNotInitializedError(self._collection_name)
return []
return self._client.scroll_rows(
self._table,
where=where,
with_embedding=with_embedding,
with_document=with_document,
limit=limit,
offset=offset,
)
def get_all_metadata(self, where=None) -> list[dict]:
"""Single-pass metadata-only fetch — projects out the document column.
The base implementation pages through ``get(include=["metadatas"])``,
which routes here via ``_scroll`` and (pre-this-override) always sent
the ``document`` text over the wire even when nothing consumed it.
For pgvector deployments where the client is remote (TLS over WAN),
that meant ``mempalace_status`` transferred O(n × document_size)View on GitHub (pinned to 06cb6987f0)
Solutions
- Inspect the pgvector error for the collection; verify the table and index exist and the server is reachable
When it happens
Trigger: Thrown at mempalace/backends/pgvector.py:900 when the library encounters an invalid state.
Common situations: Underlying pgvector operation on the collection failed.
AI-assisted analysis of MemPalace/mempalace@06cb6987f0 (2026-08-15).
Data as JSON: /api/errors/92ba067351db434d.
Report an issue: GitHub.