From 3bf53e15ffc0e171fd53a44980d35f9d709510f3 Mon Sep 17 00:00:00 2001 From: Paul Cornell Date: Fri, 18 Jul 2025 11:41:24 -0700 Subject: [PATCH] Amazon S3 Vectors and Unstructured: added missing step for non-filterable metadata --- examplecode/tools/s3-vectors.mdx | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/examplecode/tools/s3-vectors.mdx b/examplecode/tools/s3-vectors.mdx index f47ec170..7213dad5 100644 --- a/examplecode/tools/s3-vectors.mdx +++ b/examplecode/tools/s3-vectors.mdx @@ -69,9 +69,12 @@ To use this example, you will need: 5. Select the appropriate **Distance metric** for your embedding model. For example, for the **Titan Text Embeddings V2** (`amazon.titan-embed-text-v2:0`) embedding model, select **Cosine**. If you are not sure which distance metric to use, see your embedding model's documentation. -8. Click **Create vector index**. -9. After the vector index is created, copy the value of the index's **Amazon Resource Name (ARN)**, as you will need it in - later steps. This ARN takes the format `arn:aws:s3vectors:::bucket//index/`. +6. Expand **Additional settings**. +7. Within **Metadata configuration**, under **Non-filterable metadata**, click **Add key**. +8. For **Key**, enter `text`. This allows you to query the vector index by the `text` field within each object that will be coming over into the index from the JSON output files. +9. Click **Create vector index**. +10. After the vector index is created, copy the value of the index's **Amazon Resource Name (ARN)**, as you will need it in + later steps. This ARN takes the format `arn:aws:s3vectors:::bucket//index/`. ## Step 3: Add the source JSON output files' contents to the vector index