Connect to Amazon S3 for your knowledge base

You can include a separate file that specifies the document metadata fields/attributes for each file in your Amazon S3 data source and whether to include them in the embeddings when indexing the data source into the vector store. For example, you can create a file in the following format, name it example.metadata.json and upload it to your S3 bucket.

{
  "metadataAttributes": {
    "company": {
      "value": {
        "type": "STRING",
        "stringValue": "BioPharm Innovations"
      },
      "includeForEmbedding": true
    },
    "created_date": {
      "value": {
        "type": "NUMBER",
        "numberValue": 20221205
      },
      "includeForEmbedding": true
    },
    "author": {
      "value": {
        "type": "STRING",
        "stringValue": "Lisa Thompson"
      },
      "includeForEmbedding": true
    },
    "origin": {
      "value": {
        "type": "STRING",
        "stringValue": "Overview"
      },
      "includeForEmbedding": true
    }
  }
}

The metadata file must use the same name as its associated source document file, with .metadata.json appended onto the end of the file name. The metadata file must be stored in the same folder or location as the source file in your Amazon S3 bucket. The file must not exceed the limit of 10 KB. For information on the supported attribute/field data types and the filtering operators you can apply to your metadata fields, see Metadata and filtering.

You can include or exclude crawling certain content. For example, you can specify an exclusion prefix/regular expression pattern to skip crawling any file that contains “private” in the file name. You could also specify an inclusion prefix/regular expression pattern to include certain content entities or content types. If you specify an inclusion and exclusion filter and both match a document, the exclusion filter takes precedence and the document isn’t crawled.

An example of a filter pattern to include only PDF files: ".*\\.pdf"

The data source connector crawls new, modified, and deleted content each time your data source syncs with your knowledge base. Amazon Bedrock can use your data source’s mechanism for tracking content changes and crawl content that changed since the last sync. When you sync your data source with your knowledge base for the first time, all content is crawled by default.

To sync your data source with your knowledge base, use the StartIngestionJob API or select your knowledge base in the console and select Sync within the data source overview section.