Configuring metadata controls in Amazon Q Business
Important
This section assumes that you understand document attributes in Amazon Q Business.
Note
Before you configure relevance tuning, you must create a Amazon Q Business retriever and index for your application.
An Amazon Q Business index has fields you can map your document attributes to. Once mapped to document attributes and search enabled, these index fields can be used by admin to boost results from specific sources, or by end users to filter and scope their chat results to specific data.
Mapping document attributes from your documents to index fields is a multi-step process that depends on the document upload method you use.
Note
Filtering using document attributes in chat is only supported through the API. Boosting search results using document attributes is supported on both the console and the API.
Topics
Mapping document attributes directly to index fields
When you use the console or the API to directly add documents to your application, you must first create and map your document attributes to index fields before you can use them for filtering in chat or boosting responses. You use the following processes to map document attributes to your index field and mark them searchable.
Important
You can map up to 50 document attributes to index fields. You can mark up to 30 index fields searchable.
Using the console
To map document attributes to index fields using the Amazon Q Business console, complete the following steps:
To create and map document attributes to index fields
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Sign in to the AWS Management Console and open the Amazon Q Business console.
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From the left navigation pane, from Enhancements, choose Metadata controls.
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From Metadata, choose Add metadata field.
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From the Add metadata field dialog box that opens up, do the following:
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For Metadata field name – Add a name for the metadata field you're adding to the index.
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For Data type – Select the data type you want to assign to the metadata field. Supported data types include String, String list, Long (numeric), and Date.
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For Usage type – Select Searchable to mark your field searchable to end users.
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Select Add to finish adding the metadata field to your index.
Repeat the previous step to add create and map more metadata fields. Once you add a metadata field, you can't delete it.
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To save all the metadata fields you added, select Save.
Note
If you leave the page without saving your changes, any metadata fields you added won't be saved.
Any metadata you add and mark searchable can be viewed from the Metadata summary. You can update the searchability of a metadata field at any time.
Using the API
To map document attributes to index fields using the Amazon Q Business API, complete the following steps:
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You create an index by calling the CreateIndex API operation.
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Then, you create index fields using the UpdateIndex operation. You use this method to map both reserved and custom document attributes to index fields.
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Optionally, you can test and view the index fields that you’ve added by using the GetIndex operation.
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Then, when you use the BatchPutDocument operation to ingest documents into your index, Amazon Q Business extracts your reserved or custom document attributes and maps them to the index fields that you have already created.
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To mark mapped attributes searchable, follow the steps outlined in enabling attributes for search using APIs.
After you map document attributes directly to index fields using the API, you
can select specific attributes for your end user to use for filtering chat
responses. With the UpdateIndex
API operation, you add custom
fields or attributes using the documentAttributeConfigurations
parameter.
The following JSON example uses documentAttributeConfigurations
to add a field called "Department" to the index.
"DocumentmetadataConfigurationUpdates": [ { "Name": "Department", "Type": "STRING_VALUE" } ]
Mapping data source document attributes to index fields
If you use an Amazon Q Business data source connector, you can map default document attributes attached to documents in your data source to fields in your Amazon Q Business index during data source configuration. You can use these document attributes to help your end user filter and scope chat responses.
Important
Filtering using data source document attributes in chat is only supported through the API.
Each data source connector is designed to automatically crawl and map specific
document attributes as default from your data source. For example, if you have a
field in your data source named dept
that contains department
information for a document, your data source may automatically map it to an index
field named Department
. You can't change or customize default data
source attributes that are mapped to an index.
If you use the console, you select and map default field mappings or create and
map custom mappings when you configure your connector. On the console, if a default
field or a default field property can’t be edited, it will appear grayed out. If you
use the API, you use the configuration
parameter of the CreateDataSource API operation to
map default document attributes in your data source to index fields.
You can also map any custom document attributes in your data source connector to
Amazon Q Business reserved fields. For example, if your data source has a
custom attribute named creation_date
, you can map this field to the
equivalent Amazon Q reserved field named _created_at
. You
can also choose to add custom document attributes and map them to custom fields that
you create in your index. You do this when you configure and update your data
source, using both the console and the API.
If you want to map custom document attributes in your data source to Amazon Q index fields, use the DocumentAttribute
parameter of
the UpdateIndex operation to first
create the custom field matching the custom document attribute. By doing so, you can
specify and map your reserved or custom data source document attribute to a reserved
or custom index field.
Any metadata you add can be viewed and marked searchable using Metadata controls or using the API. You can update the searchability of a metadata field at any time.
Note
Document attributes mapped to index fields during the data source configuration process must be enabled for search before they can be used for search accuracy improvements, filtering search results, and metadata boosting.
Most data sources support custom field mappings and follow a specific configuration format, except Amazon S3 and database data sources. The following outlines how Amazon S3 and database data sources configure mappings:
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If you store your documents in an Amazon S3 bucket or Amazon S3 data source, you can either use the console to specify field mappings or specify fields using a JSON metadata file.
When you use an Amazon S3 bucket as a data source for your index, you use companion metadata files to add metadata to the documents. You place the metadata JSON files in a directory structure that is parallel to your documents. For more information, see S3 document metadata.
You specify custom fields or attributes in the
Attributes
JSON structure. You can create up to 50 custom fields or attributes. The following example usesAttributes
to define three custom fields or attributes and one reserved field."Attributes": { "brand": "Amazon Basics", "price": 1595, "_category": "sports", "subcategories": ["outdoors", "electronics"] }
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For database data sources, if the name of the database column matches the name of a reserved field, the field and column are mapped automatically.
Ingesting attributes using the BatchPutDocument API operation
When you use the BatchPutDocument API operation to add a document to
your index, you can specify document attributes—both reserved and
custom—as part of Attributes
. You can add multiple fields or
attributes when you call the API operation. You can create up to 50 custom fields or
attributes. The following example is a custom field or attribute that adds
"Department" to a document.
"Attributes": { "Department": "HR", "_category": "Vacation policy" }