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docs: Rename pgvector upgrade page to active voice #498

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2 changes: 1 addition & 1 deletion docs/06-concepts/02-models/03-vector-fields.md
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Expand Up @@ -13,7 +13,7 @@ All vector types support specialized distance operations for similarity search a
To ensure optimal performance with vector similarity searches, consider creating specialized vector indexes on your vector fields. See the [Vector indexes](../database/indexing#vector-indexes) section for more details.

:::info
The usage of Vector fields requires the pgvector PostgreSQL extension to be installed, which comes by default on new Serverpod projects. To upgrade an existing project, see the [Upgrading to pgvector support](../../upgrading/upgrade-to-pgvector) guide.
The usage of Vector fields requires the pgvector PostgreSQL extension to be installed, which comes by default on new Serverpod projects. To upgrade an existing project, see the [Upgrade to pgvector](../../upgrading/upgrade-to-pgvector) guide.
:::

## Vector
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4 changes: 2 additions & 2 deletions docs/09-upgrading/03-upgrade-to-pgvector.md
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@@ -1,4 +1,4 @@
# Upgrading to pgvector support
# Upgrade to pgvector

New Serverpod projects automatically include pgvector support through the `pgvector/pgvector` PostgreSQL Docker image. However, existing projects need to be upgraded to use vector functionality.

Expand All @@ -12,7 +12,7 @@ If trying to use vector fields without upgrading, you will encounter an error wh

## For Docker-based environments

1. Update your `docker-compose.yml` to use a PostgreSQL image with pgvector (e.g., `pgvector/pgvector:pg16`):
1. Update your `docker-compose.yaml` to use a PostgreSQL image with pgvector (e.g., `pgvector/pgvector:pg16`):

```yaml
services:
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