## Delete Vectors

`vector_stores.delete(strvector_store_name, VectorStoreDeleteParams**kwargs)  -> VectorStoreDeleteResponse`

**post** `/v5/vector-stores/{vector_store_name}/delete`

Delete documents from a vector store by document IDs or metadata filter criteria.

**Delete by IDs:** Provide an array of document IDs to delete specific documents. Non-existent documents
are silently skipped.

**Delete by Filter:** Use metadata filters to delete all documents matching the specified criteria (e.g.,
delete all documents where `status: "archived"`). The filter must specify at least one condition and cannot
be empty. To delete all documents, use the drop endpoint instead.

**Filter Operators:** Supports MongoDB-style operators including equality (`{"field": "value"}`),
comparison (`$gt`, `$gte`, `$lt`, `$lte`, `$eq`, `$ne`), logical (`$and`, `$or`, `$not`),
and membership (`$in`, `$nin`). Only indexed metadata fields can be used for filtering.

**Best Practice:** Use the count endpoint with the same filter to preview the number of documents that
will be deleted before executing the deletion operation.

### Parameters

- `vector_store_name: str`

  The name of the vector store

- `filter: Optional[Dict[str, object]]`

  Metadata filter expression for deletion

- `ids: Optional[Sequence[str]]`

  Array of document IDs to delete

### Returns

- `class VectorStoreDeleteResponse: …`

  Response for delete operation.

  - `deleted_count: int`

    Number of documents deleted

### Example

```python
import os
from scale_gp_beta import SGPClient

client = SGPClient(
    api_key=os.environ.get("SGP_API_KEY"),  # This is the default and can be omitted
)
vector_store = client.vector_stores.delete(
    vector_store_name="vector_store_name",
)
print(vector_store.deleted_count)
```

#### Response

```json
{
  "deleted_count": 0
}
```