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9 changes: 6 additions & 3 deletions examplecode/tools/s3-vectors.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -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:<region-id>:<account>:bucket/<bucket-name>/index/<index-name>`.
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:<region-id>:<account>:bucket/<bucket-name>/index/<index-name>`.

## Step 3: Add the source JSON output files' contents to the vector index

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