List Vectors

List documents in a vector store with cursor-based pagination.

Use Cases: Browse documents, export content, audit stored data, or retrieve documents by metadata without semantic search.

Ordering: Documents are returned in storage order (insertion order), not ranked by similarity. For similarity-based retrieval, use the query endpoint.

Filtering: Apply metadata filters to narrow results to specific subsets (e.g., all documents where category: "research"). Only indexed fields can be used for filtering.

Pagination: Uses cursor-based pagination for efficient traversal of large datasets. Pass the next_cursor from each response as starting_after to retrieve the next page, or prev_cursor as ending_before to retrieve the previous page. A null cursor indicates no further pages exist.

Embedding Vectors: Setting include_vectors=true includes the full embedding vector arrays in the response. This significantly increases payload size and reduces the maximum page size from 1000 to 100 documents. Enable only when raw vectors are required for external processing.