Module Smaws_Client_Kendra

kendra client library built on EIO.

Types

type data_source_to_index_field_mapping = {
  1. index_field_name : string;
    (*

    The name of the index field to map to the data source field. The index field type must match the data source field type.

    *)
  2. date_field_format : string option;
    (*

    The format for date fields in the data source. If the field specified in DataSourceFieldName is a date field, you must specify the date format. If the field is not a date field, an exception is thrown.

    *)
  3. data_source_field_name : string;
    (*

    The name of the field in the data source. You must first create the index field using the UpdateIndex API.

    *)
}

Maps attributes or field names of the documents synced from the data source to Amazon Kendra index field names. You can set up field mappings for each data source when calling CreateDataSource or UpdateDataSource API. To create custom fields, use the UpdateIndex API to first create an index field and then map to the data source field. For more information, see Mapping data source fields.

type work_docs_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map Amazon WorkDocs data source attributes or field names to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Amazon WorkDocs fields. For more information, see Mapping data source fields. The Amazon WorkDocs data source field names must exist in your Amazon WorkDocs custom metadata.

    *)
  2. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain files in your Amazon WorkDocs site repository. Files that match the patterns are excluded from the index. Files that don’t match the patterns are included in the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  3. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain files in your Amazon WorkDocs site repository. Files that match the patterns are included in the index. Files that don't match the patterns are excluded from the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  4. use_change_log : bool option;
    (*

    TRUE to use the Amazon WorkDocs change log to determine which documents require updating in the index. Depending on the change log's size, it may take longer for Amazon Kendra to use the change log than to scan all of your documents in Amazon WorkDocs.

    *)
  5. crawl_comments : bool option;
    (*

    TRUE to include comments on documents in your index. Including comments in your index means each comment is a document that can be searched on.

    The default is set to FALSE.

    *)
  6. organization_id : string;
    (*

    The identifier of the directory corresponding to your Amazon WorkDocs site repository.

    You can find the organization ID in the Directory Service by going to Active Directory, then Directories. Your Amazon WorkDocs site directory has an ID, which is the organization ID. You can also set up a new Amazon WorkDocs directory in the Directory Service console and enable a Amazon WorkDocs site for the directory in the Amazon WorkDocs console.

    *)
}

Provides the configuration information to connect to Amazon WorkDocs as your data source.

Amazon WorkDocs connector is available in Oregon, North Virginia, Sydney, Singapore and Ireland regions.

type web_crawler_mode =
  1. | EVERYTHING
  2. | SUBDOMAINS
  3. | HOST_ONLY
type seed_url_configuration = {
  1. web_crawler_mode : web_crawler_mode option;
    (*

    You can choose one of the following modes:

    • HOST_ONLY—crawl only the website host names. For example, if the seed URL is "abc.example.com", then only URLs with host name "abc.example.com" are crawled.
    • SUBDOMAINS—crawl the website host names with subdomains. For example, if the seed URL is "abc.example.com", then "a.abc.example.com" and "b.abc.example.com" are also crawled.
    • EVERYTHING—crawl the website host names with subdomains and other domains that the web pages link to.

    The default mode is set to HOST_ONLY.

    *)
  2. seed_urls : string list;
    (*

    The list of seed or starting point URLs of the websites you want to crawl.

    The list can include a maximum of 100 seed URLs.

    *)
}

Provides the configuration information for the seed or starting point URLs to crawl.

When selecting websites to index, you must adhere to the Amazon Acceptable Use Policy and all other Amazon terms. Remember that you must only use Amazon Kendra Web Crawler to index your own web pages, or web pages that you have authorization to index.

type site_maps_configuration = {
  1. site_maps : string list;
    (*

    The list of sitemap URLs of the websites you want to crawl.

    The list can include a maximum of three sitemap URLs.

    *)
}

Provides the configuration information for the sitemap URLs to crawl.

When selecting websites to index, you must adhere to the Amazon Acceptable Use Policy and all other Amazon terms. Remember that you must only use Amazon Kendra Web Crawler to index your own web pages, or web pages that you have authorization to index.

type urls = {
  1. site_maps_configuration : site_maps_configuration option;
    (*

    Configuration of the sitemap URLs of the websites you want to crawl.

    Only URLs belonging to the same website host names are crawled. You can list up to three sitemap URLs.

    *)
  2. seed_url_configuration : seed_url_configuration option;
    (*

    Configuration of the seed or starting point URLs of the websites you want to crawl.

    You can choose to crawl only the website host names, or the website host names with subdomains, or the website host names with subdomains and other domains that the web pages link to.

    You can list up to 100 seed URLs.

    *)
}

Provides the configuration information of the URLs to crawl.

You can only crawl websites that use the secure communication protocol, Hypertext Transfer Protocol Secure (HTTPS). If you receive an error when crawling a website, it could be that the website is blocked from crawling.

When selecting websites to index, you must adhere to the Amazon Acceptable Use Policy and all other Amazon terms. Remember that you must only use Amazon Kendra Web Crawler to index your own web pages, or web pages that you have authorization to index.

type proxy_configuration = {
  1. credentials : string option;
    (*

    Your secret ARN, which you can create in Secrets Manager

    The credentials are optional. You use a secret if web proxy credentials are required to connect to a website host. Amazon Kendra currently support basic authentication to connect to a web proxy server. The secret stores your credentials.

    *)
  2. port : int;
    (*

    The port number of the website host you want to connect to via a web proxy server.

    For example, the port for https://a.example.com/page1.html is 443, the standard port for HTTPS.

    *)
  3. host : string;
    (*

    The name of the website host you want to connect to via a web proxy server.

    For example, the host name of https://a.example.com/page1.html is "a.example.com".

    *)
}

Provides the configuration information for a web proxy to connect to website hosts.

type basic_authentication_configuration = {
  1. credentials : string;
    (*

    Your secret ARN, which you can create in Secrets Manager

    You use a secret if basic authentication credentials are required to connect to a website. The secret stores your credentials of user name and password.

    *)
  2. port : int;
    (*

    The port number of the website host you want to connect to using authentication credentials.

    For example, the port for https://a.example.com/page1.html is 443, the standard port for HTTPS.

    *)
  3. host : string;
    (*

    The name of the website host you want to connect to using authentication credentials.

    For example, the host name of https://a.example.com/page1.html is "a.example.com".

    *)
}

Provides the configuration information to connect to websites that require basic user authentication.

type authentication_configuration = {
  1. basic_authentication : basic_authentication_configuration list option;
    (*

    The list of configuration information that's required to connect to and crawl a website host using basic authentication credentials.

    The list includes the name and port number of the website host.

    *)
}

Provides the configuration information to connect to websites that require user authentication.

type web_crawler_configuration = {
  1. authentication_configuration : authentication_configuration option;
    (*

    Configuration information required to connect to websites using authentication.

    You can connect to websites using basic authentication of user name and password. You use a secret in Secrets Manager to store your authentication credentials.

    You must provide the website host name and port number. For example, the host name of https://a.example.com/page1.html is "a.example.com" and the port is 443, the standard port for HTTPS.

    *)
  2. proxy_configuration : proxy_configuration option;
    (*

    Configuration information required to connect to your internal websites via a web proxy.

    You must provide the website host name and port number. For example, the host name of https://a.example.com/page1.html is "a.example.com" and the port is 443, the standard port for HTTPS.

    Web proxy credentials are optional and you can use them to connect to a web proxy server that requires basic authentication. To store web proxy credentials, you use a secret in Secrets Manager.

    *)
  3. url_exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain URLs to crawl. URLs that match the patterns are excluded from the index. URLs that don't match the patterns are included in the index. If a URL matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the URL file isn't included in the index.

    *)
  4. url_inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain URLs to crawl. URLs that match the patterns are included in the index. URLs that don't match the patterns are excluded from the index. If a URL matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the URL file isn't included in the index.

    *)
  5. max_urls_per_minute_crawl_rate : int option;
    (*

    The maximum number of URLs crawled per website host per minute.

    A minimum of one URL is required.

    The default maximum number of URLs crawled per website host per minute is 300.

    *)
  6. max_content_size_per_page_in_mega_bytes : float option;
    (*

    The maximum size (in MB) of a web page or attachment to crawl.

    Files larger than this size (in MB) are skipped/not crawled.

    The default maximum size of a web page or attachment is set to 50 MB.

    *)
  7. max_links_per_page : int option;
    (*

    The maximum number of URLs on a web page to include when crawling a website. This number is per web page.

    As a website’s web pages are crawled, any URLs the web pages link to are also crawled. URLs on a web page are crawled in order of appearance.

    The default maximum links per page is 100.

    *)
  8. crawl_depth : int option;
    (*

    The 'depth' or number of levels from the seed level to crawl. For example, the seed URL page is depth 1 and any hyperlinks on this page that are also crawled are depth 2.

    *)
  9. urls : urls;
    (*

    Specifies the seed or starting point URLs of the websites or the sitemap URLs of the websites you want to crawl.

    You can include website subdomains. You can list up to 100 seed URLs and up to three sitemap URLs.

    You can only crawl websites that use the secure communication protocol, Hypertext Transfer Protocol Secure (HTTPS). If you receive an error when crawling a website, it could be that the website is blocked from crawling.

    When selecting websites to index, you must adhere to the Amazon Acceptable Use Policy and all other Amazon terms. Remember that you must only use Amazon Kendra Web Crawler to index your own web pages, or web pages that you have authorization to index.

    *)
}

Provides the configuration information required for Amazon Kendra Web Crawler.

type warning_code =
  1. | QUERY_LANGUAGE_INVALID_SYNTAX
type warning = {
  1. code : warning_code option;
    (*

    The code used to show the type of warning for the query.

    *)
  2. message : string option;
    (*

    The message that explains the problem with the query.

    *)
}

The warning code and message that explains a problem with a query.

type validation_exception = {
  1. message : string option;
}

The input fails to satisfy the constraints set by the Amazon Kendra service. Please provide the correct input and try again.

type key_location =
  1. | SECRET_MANAGER
  2. | URL
type jwt_token_type_configuration = {
  1. claim_regex : string option;
    (*

    The regular expression that identifies the claim.

    *)
  2. issuer : string option;
    (*

    The issuer of the token.

    *)
  3. group_attribute_field : string option;
    (*

    The group attribute field.

    *)
  4. user_name_attribute_field : string option;
    (*

    The user name attribute field.

    *)
  5. secret_manager_arn : string option;
    (*

    The Amazon Resource Name (arn) of the secret.

    *)
  6. ur_l : string option;
    (*

    The signing key URL.

    *)
  7. key_location : key_location;
    (*

    The location of the key.

    *)
}

Provides the configuration information for the JWT token type.

type json_token_type_configuration = {
  1. group_attribute_field : string;
    (*

    The group attribute field.

    *)
  2. user_name_attribute_field : string;
    (*

    The user name attribute field.

    *)
}

Provides the configuration information for the JSON token type.

type user_token_configuration = {
  1. json_token_type_configuration : json_token_type_configuration option;
    (*

    Information about the JSON token type configuration.

    *)
  2. jwt_token_type_configuration : jwt_token_type_configuration option;
    (*

    Information about the JWT token type configuration.

    *)
}

Provides the configuration information for a token.

type user_identity_configuration = {
  1. identity_attribute_name : string option;
    (*

    The IAM Identity Center field name that contains the identifiers of your users, such as their emails. This is used for user context filtering and for granting access to your Amazon Kendra experience. You must set up IAM Identity Center with Amazon Kendra. You must include your users and groups in your Access Control List when you ingest documents into your index. For more information, see Getting started with an IAM Identity Center identity source.

    *)
}

Provides the configuration information for the identifiers of your users.

type user_group_resolution_mode =
  1. | NONE
  2. | AWS_SSO
type user_group_resolution_configuration = {
  1. user_group_resolution_mode : user_group_resolution_mode;
    (*

    The identity store provider (mode) you want to use to get users and groups. IAM Identity Center is currently the only available mode. Your users and groups must exist in an IAM Identity Center identity source in order to use this mode.

    *)
}

Provides the configuration information to get users and groups from an IAM Identity Center identity source. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents. You can also use the PutPrincipalMapping API to map users to their groups so that you only need to provide the user ID when you issue the query.

To set up an IAM Identity Center identity source in the console to use with Amazon Kendra, see Getting started with an IAM Identity Center identity source. You must also grant the required permissions to use IAM Identity Center with Amazon Kendra. For more information, see IAM roles for IAM Identity Center.

Amazon Kendra currently does not support using UserGroupResolutionConfiguration with an Amazon Web Services organization member account for your IAM Identity Center identify source. You must create your index in the management account for the organization in order to use UserGroupResolutionConfiguration.

type user_context_policy =
  1. | USER_TOKEN
  2. | ATTRIBUTE_FILTER
type data_source_group = {
  1. data_source_id : string;
    (*

    The identifier of the data source group you want to add to your list of data source groups. This is for filtering search results based on the groups' access to documents in that data source.

    *)
  2. group_id : string;
    (*

    The identifier of the group you want to add to your list of groups. This is for filtering search results based on the groups' access to documents.

    *)
}

Data source information for user context filtering.

type user_context = {
  1. data_source_groups : data_source_group list option;
    (*

    The list of data source groups you want to filter search results based on groups' access to documents in that data source.

    *)
  2. groups : string list option;
    (*

    The list of groups you want to filter search results based on the groups' access to documents.

    *)
  3. user_id : string option;
    (*

    The identifier of the user you want to filter search results based on their access to documents.

    *)
  4. token : string option;
    (*

    The user context token for filtering search results for a user. It must be a JWT or a JSON token.

    *)
}

Provides information about the user context for an Amazon Kendra index.

User context filtering is a kind of personalized search with the benefit of controlling access to documents. For example, not all teams that search the company portal for information should access top-secret company documents, nor are these documents relevant to all users. Only specific users or groups of teams given access to top-secret documents should see these documents in their search results.

You provide one of the following:

  • User token
  • User ID, the groups the user belongs to, and any data sources the groups can access.

If you provide both, an exception is thrown.

type s3_path = {
  1. key : string;
    (*

    The name of the file.

    *)
  2. bucket : string;
    (*

    The name of the S3 bucket that contains the file.

    *)
}

Information required to find a specific file in an Amazon S3 bucket.

type update_thesaurus_request = {
  1. source_s3_path : s3_path option;
  2. role_arn : string option;
    (*

    An IAM role that gives Amazon Kendra permissions to access thesaurus file specified in SourceS3Path.

    *)
  3. description : string option;
    (*

    A new description for the thesaurus.

    *)
  4. index_id : string;
    (*

    The identifier of the index for the thesaurus.

    *)
  5. name : string option;
    (*

    A new name for the thesaurus.

    *)
  6. id : string;
    (*

    The identifier of the thesaurus you want to update.

    *)
}
type throttling_exception = {
  1. message : string option;
}

The request was denied due to request throttling. Please reduce the number of requests and try again.

type resource_not_found_exception = {
  1. message : string option;
}

The resource you want to use doesn’t exist. Please check you have provided the correct resource and try again.

type internal_server_exception = {
  1. message : string option;
}

An issue occurred with the internal server used for your Amazon Kendra service. Please wait a few minutes and try again, or contact Support for help.

type conflict_exception = {
  1. message : string option;
}

A conflict occurred with the request. Please fix any inconsistences with your resources and try again.

type access_denied_exception = {
  1. message : string option;
}

You don't have sufficient access to perform this action. Please ensure you have the required permission policies and user accounts and try again.

type mode =
  1. | LEARN_ONLY
  2. | ENABLED
type suggestable_config = {
  1. suggestable : bool option;
    (*

    TRUE means the document field/attribute is suggestible, so the contents within the field can be used for query suggestions.

    *)
  2. attribute_name : string option;
    (*

    The name of the document field/attribute.

    *)
}

Provides the configuration information for a document field/attribute that you want to base query suggestions on.

type attribute_suggestions_mode =
  1. | INACTIVE
  2. | ACTIVE
type attribute_suggestions_update_config = {
  1. attribute_suggestions_mode : attribute_suggestions_mode option;
    (*

    You can set the mode to ACTIVE or INACTIVE. You must also set SuggestionTypes as either QUERY or DOCUMENT_ATTRIBUTES and then call GetQuerySuggestions. If Mode to use query history is set to ENABLED when calling UpdateQuerySuggestionsConfig and AttributeSuggestionsMode to use fields/attributes is set to ACTIVE, and you haven't set your SuggestionTypes preference to DOCUMENT_ATTRIBUTES, then Amazon Kendra uses the query history.

    *)
  2. suggestable_config_list : suggestable_config list option;
    (*

    The list of fields/attributes that you want to set as suggestible for query suggestions.

    *)
}

Updates the configuration information for the document fields/attributes that you want to base query suggestions on.

To deactivate using documents fields for query suggestions, set the mode to INACTIVE. You must also set SuggestionTypes as either QUERY or DOCUMENT_ATTRIBUTES and then call GetQuerySuggestions. If you set to QUERY, then Amazon Kendra uses the query history to base suggestions on. If you set to DOCUMENT_ATTRIBUTES, then Amazon Kendra uses the contents of document fields to base suggestions on.

type update_query_suggestions_config_request = {
  1. attribute_suggestions_config : attribute_suggestions_update_config option;
    (*

    Configuration information for the document fields/attributes that you want to base query suggestions on.

    *)
  2. minimum_query_count : int option;
    (*

    The the minimum number of times a query must be searched in order to be eligible to suggest to your users.

    Decreasing this number increases the number of suggestions. However, this affects the quality of suggestions as it sets a low bar for a query to be considered popular to suggest to users.

    How you tune this setting depends on your specific needs.

    *)
  3. minimum_number_of_querying_users : int option;
    (*

    The minimum number of unique users who must search a query in order for the query to be eligible to suggest to your users.

    Increasing this number might decrease the number of suggestions. However, this ensures a query is searched by many users and is truly popular to suggest to users.

    How you tune this setting depends on your specific needs.

    *)
  4. include_queries_without_user_information : bool option;
    (*

    TRUE to include queries without user information (i.e. all queries, irrespective of the user), otherwise FALSE to only include queries with user information.

    If you pass user information to Amazon Kendra along with the queries, you can set this flag to FALSE and instruct Amazon Kendra to only consider queries with user information.

    If you set to FALSE, Amazon Kendra only considers queries searched at least MinimumQueryCount times across MinimumNumberOfQueryingUsers unique users for suggestions.

    If you set to TRUE, Amazon Kendra ignores all user information and learns from all queries.

    *)
  5. query_log_look_back_window_in_days : int option;
    (*

    How recent your queries are in your query log time window.

    The time window is the number of days from current day to past days.

    By default, Amazon Kendra sets this to 180.

    *)
  6. mode : mode option;
    (*

    Set the mode to ENABLED or LEARN_ONLY.

    By default, Amazon Kendra enables query suggestions. LEARN_ONLY mode allows you to turn off query suggestions. You can to update this at any time.

    In LEARN_ONLY mode, Amazon Kendra continues to learn from new queries to keep suggestions up to date for when you are ready to switch to ENABLED mode again.

    *)
  7. index_id : string;
    (*

    The identifier of the index with query suggestions you want to update.

    *)
}
type update_query_suggestions_block_list_request = {
  1. role_arn : string option;
    (*

    The IAM (Identity and Access Management) role used to access the block list text file in S3.

    *)
  2. source_s3_path : s3_path option;
    (*

    The S3 path where your block list text file sits in S3.

    If you update your block list and provide the same path to the block list text file in S3, then Amazon Kendra reloads the file to refresh the block list. Amazon Kendra does not automatically refresh your block list. You need to call the UpdateQuerySuggestionsBlockList API to refresh you block list.

    If you update your block list, then Amazon Kendra asynchronously refreshes all query suggestions with the latest content in the S3 file. This means changes might not take effect immediately.

    *)
  3. description : string option;
    (*

    A new description for the block list.

    *)
  4. name : string option;
    (*

    A new name for the block list.

    *)
  5. id : string;
    (*

    The identifier of the block list you want to update.

    *)
  6. index_id : string;
    (*

    The identifier of the index for the block list.

    *)
}
type document_attribute_value_type =
  1. | DATE_VALUE
  2. | LONG_VALUE
  3. | STRING_LIST_VALUE
  4. | STRING_VALUE
type order =
  1. | DESCENDING
  2. | ASCENDING
type relevance = {
  1. value_importance_map : (string * int) list option;
    (*

    A list of values that should be given a different boost when they appear in the result list. For example, if you are boosting a field called "department", query terms that match the department field are boosted in the result. However, you can add entries from the department field to boost documents with those values higher.

    For example, you can add entries to the map with names of departments. If you add "HR",5 and "Legal",3 those departments are given special attention when they appear in the metadata of a document. When those terms appear they are given the specified importance instead of the regular importance for the boost.

    *)
  2. rank_order : order option;
    (*

    Determines how values should be interpreted.

    When the RankOrder field is ASCENDING, higher numbers are better. For example, a document with a rating score of 10 is higher ranking than a document with a rating score of 1.

    When the RankOrder field is DESCENDING, lower numbers are better. For example, in a task tracking application, a priority 1 task is more important than a priority 5 task.

    Only applies to LONG fields.

    *)
  3. duration : string option;
    (*

    Specifies the time period that the boost applies to. For example, to make the boost apply to documents with the field value within the last month, you would use "2628000s". Once the field value is beyond the specified range, the effect of the boost drops off. The higher the importance, the faster the effect drops off. If you don't specify a value, the default is 3 months. The value of the field is a numeric string followed by the character "s", for example "86400s" for one day, or "604800s" for one week.

    Only applies to DATE fields.

    *)
  4. importance : int option;
    (*

    The relative importance of the field in the search. Larger numbers provide more of a boost than smaller numbers.

    *)
  5. freshness : bool option;
    (*

    Indicates that this field determines how "fresh" a document is. For example, if document 1 was created on November 5, and document 2 was created on October 31, document 1 is "fresher" than document 2. Only applies to DATE fields.

    *)
}

Provides information for tuning the relevance of a field in a search. When a query includes terms that match the field, the results are given a boost in the response based on these tuning parameters.

Provides information about how a custom index field is used during a search.

type document_metadata_configuration = {
  1. search : search option;
    (*

    Provides information about how the field is used during a search.

    *)
  2. relevance : relevance option;
    (*

    Provides tuning parameters to determine how the field affects the search results.

    *)
  3. type_ : document_attribute_value_type;
    (*

    The data type of the index field.

    *)
  4. name : string;
    (*

    The name of the index field.

    *)
}

Specifies the properties, such as relevance tuning and searchability, of an index field.

type capacity_units_configuration = {
  1. query_capacity_units : int;
    (*

    The amount of extra query capacity for an index and GetQuerySuggestions capacity.

    A single extra capacity unit for an index provides 0.1 queries per second or approximately 8,000 queries per day. You can add up to 100 extra capacity units.

    GetQuerySuggestions capacity is five times the provisioned query capacity for an index, or the base capacity of 2.5 calls per second, whichever is higher. For example, the base capacity for an index is 0.1 queries per second, and GetQuerySuggestions capacity has a base of 2.5 calls per second. If you add another 0.1 queries per second to total 0.2 queries per second for an index, the GetQuerySuggestions capacity is 2.5 calls per second (higher than five times 0.2 queries per second).

    *)
  2. storage_capacity_units : int;
    (*

    The amount of extra storage capacity for an index. A single capacity unit provides 30 GB of storage space or 100,000 documents, whichever is reached first. You can add up to 100 extra capacity units.

    *)
}

Specifies additional capacity units configured for your Enterprise Edition index. You can add and remove capacity units to fit your usage requirements.

type update_index_request = {
  1. user_group_resolution_configuration : user_group_resolution_configuration option;
    (*

    Gets users and groups from IAM Identity Center identity source. To configure this, see UserGroupResolutionConfiguration. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    *)
  2. user_context_policy : user_context_policy option;
    (*

    The user context policy.

    *)
  3. user_token_configurations : user_token_configuration list option;
    (*

    The user token configuration.

    *)
  4. capacity_units : capacity_units_configuration option;
    (*

    Sets the number of additional document storage and query capacity units that should be used by the index. You can change the capacity of the index up to 5 times per day, or make 5 API calls.

    If you are using extra storage units, you can't reduce the storage capacity below what is required to meet the storage needs for your index.

    *)
  5. document_metadata_configuration_updates : document_metadata_configuration list option;
    (*

    The document metadata configuration you want to update for the index. Document metadata are fields or attributes associated with your documents. For example, the company department name associated with each document.

    *)
  6. description : string option;
    (*

    A new description for the index.

    *)
  7. role_arn : string option;
    (*

    An Identity and Access Management (IAM) role that gives Amazon Kendra permission to access Amazon CloudWatch logs and metrics.

    *)
  8. name : string option;
    (*

    A new name for the index.

    *)
  9. id : string;
    (*

    The identifier of the index you want to update.

    *)
}
type service_quota_exceeded_exception = {
  1. message : string option;
}

You have exceeded the set limits for your Amazon Kendra service. Please see Quotas for more information, or contact Support to inquire about an increase of limits.

A featured document. This document is displayed at the top of the search results page, placed above all other results for certain queries. If there's an exact match of a query, then the document is featured in the search results.

A set of featured results that are displayed at the top of your search results. Featured results are placed above all other results for certain queries. If there's an exact match of a query, then one or more specific documents are featured in the search results.

type conflicting_item = {
  1. set_id : string option;
    (*

    The identifier of the set of featured results that the conflicting query belongs to.

    *)
  2. set_name : string option;
    (*

    The name for the set of featured results that the conflicting query belongs to.

    *)
  3. query_text : string option;
    (*

    The text of the conflicting query.

    *)
}

Information about a conflicting query used across different sets of featured results. When you create a featured results set, you must check that the queries are unique per featured results set for each index.

An error message with a list of conflicting queries used across different sets of featured results. This occurred with the request for a new featured results set. Check that the queries you specified for featured results are unique per featured results set for each index.

type content_source_configuration = {
  1. direct_put_content : bool option;
    (*

    TRUE to use documents you indexed directly using the BatchPutDocument API.

    *)
  2. faq_ids : string list option;
    (*

    The identifier of the FAQs that you want to use for your Amazon Kendra experience.

    *)
  3. data_source_ids : string list option;
    (*

    The identifier of the data sources you want to use for your Amazon Kendra experience.

    *)
}

Provides the configuration information for your content sources, such as data sources, FAQs, and content indexed directly via BatchPutDocument.

type experience_configuration = {
  1. user_identity_configuration : user_identity_configuration option;
    (*

    The IAM Identity Center field name that contains the identifiers of your users, such as their emails.

    *)
  2. content_source_configuration : content_source_configuration option;
    (*

    The identifiers of your data sources and FAQs. Or, you can specify that you want to use documents indexed via the BatchPutDocument API. This is the content you want to use for your Amazon Kendra experience.

    *)
}

Provides the configuration information for your Amazon Kendra experience. This includes the data source IDs and/or FAQ IDs, and user or group information to grant access to your Amazon Kendra experience.

type update_experience_request = {
  1. description : string option;
    (*

    A new description for your Amazon Kendra experience.

    *)
  2. configuration : experience_configuration option;
    (*

    Configuration information you want to update for your Amazon Kendra experience.

    *)
  3. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of a role with permission to access Query API, QuerySuggestions API, SubmitFeedback API, and IAM Identity Center that stores your user and group information. For more information, see IAM roles for Amazon Kendra.

    *)
  4. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  5. name : string option;
    (*

    A new name for your Amazon Kendra experience.

    *)
  6. id : string;
    (*

    The identifier of your Amazon Kendra experience you want to update.

    *)
}
type documents_metadata_configuration = {
  1. s3_prefix : string option;
    (*

    A prefix used to filter metadata configuration files in the Amazon Web Services S3 bucket. The S3 bucket might contain multiple metadata files. Use S3Prefix to include only the desired metadata files.

    *)
}

Document metadata files that contain information such as the document access control information, source URI, document author, and custom attributes. Each metadata file contains metadata about a single document.

type access_control_list_configuration = {
  1. key_path : string option;
    (*

    Path to the Amazon S3 bucket that contains the ACL files.

    *)
}

Access Control List files for the documents in a data source. For the format of the file, see Access control for S3 data sources.

type s3_data_source_configuration = {
  1. access_control_list_configuration : access_control_list_configuration option;
    (*

    Provides the path to the S3 bucket that contains the user context filtering files for the data source. For the format of the file, see Access control for S3 data sources.

    *)
  2. documents_metadata_configuration : documents_metadata_configuration option;
  3. exclusion_patterns : string list option;
    (*

    A list of glob patterns (patterns that can expand a wildcard pattern into a list of path names that match the given pattern) for certain file names and file types to exclude from your index. If a document matches both an inclusion and exclusion prefix or pattern, the exclusion prefix takes precendence and the document is not indexed. Examples of glob patterns include:

    • /myapp/config/*—All files inside config directory.
    • **/*.png—All .png files in all directories.
    • **/*.{png, ico, md}—All .png, .ico or .md files in all directories.
    • /myapp/src/**/*.ts—All .ts files inside src directory (and all its subdirectories).
    • **/!(*.module).ts—All .ts files but not .module.ts
    • *.png , *.jpg—All PNG and JPEG image files in a directory (files with the extensions .png and .jpg).
    • *internal*—All files in a directory that contain 'internal' in the file name, such as 'internal', 'internal_only', 'company_internal'.
    • **/*internal*—All internal-related files in a directory and its subdirectories.

    For more examples, see Use of Exclude and Include Filters in the Amazon Web Services CLI Command Reference.

    *)
  4. inclusion_patterns : string list option;
    (*

    A list of glob patterns (patterns that can expand a wildcard pattern into a list of path names that match the given pattern) for certain file names and file types to include in your index. If a document matches both an inclusion and exclusion prefix or pattern, the exclusion prefix takes precendence and the document is not indexed. Examples of glob patterns include:

    • /myapp/config/*—All files inside config directory.
    • **/*.png—All .png files in all directories.
    • **/*.{png, ico, md}—All .png, .ico or .md files in all directories.
    • /myapp/src/**/*.ts—All .ts files inside src directory (and all its subdirectories).
    • **/!(*.module).ts—All .ts files but not .module.ts
    • *.png , *.jpg—All PNG and JPEG image files in a directory (files with the extensions .png and .jpg).
    • *internal*—All files in a directory that contain 'internal' in the file name, such as 'internal', 'internal_only', 'company_internal'.
    • **/*internal*—All internal-related files in a directory and its subdirectories.

    For more examples, see Use of Exclude and Include Filters in the Amazon Web Services CLI Command Reference.

    *)
  5. inclusion_prefixes : string list option;
    (*

    A list of S3 prefixes for the documents that should be included in the index.

    *)
  6. bucket_name : string;
    (*

    The name of the bucket that contains the documents.

    *)
}

Provides the configuration information to connect to an Amazon S3 bucket.

Amazon Kendra now supports an upgraded Amazon S3 connector.

You must now use the TemplateConfiguration object instead of the S3DataSourceConfiguration object to configure your connector.

Connectors configured using the older console and API architecture will continue to function as configured. However, you won't be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

type share_point_version =
  1. | SHAREPOINT_2019
  2. | SHAREPOINT_ONLINE
  3. | SHAREPOINT_2016
  4. | SHAREPOINT_2013
type data_source_vpc_configuration = {
  1. security_group_ids : string list;
    (*

    A list of identifiers of security groups within your Amazon VPC. The security groups should enable Amazon Kendra to connect to the data source.

    *)
  2. subnet_ids : string list;
    (*

    A list of identifiers for subnets within your Amazon VPC. The subnets should be able to connect to each other in the VPC, and they should have outgoing access to the Internet through a NAT device.

    *)
}

Provides the configuration information to connect to an Amazon VPC.

type share_point_online_authentication_type =
  1. | OAUTH2
  2. | HTTP_BASIC
type share_point_configuration = {
  1. proxy_configuration : proxy_configuration option;
    (*

    Configuration information to connect to your Microsoft SharePoint site URLs via instance via a web proxy. You can use this option for SharePoint Server.

    You must provide the website host name and port number. For example, the host name of https://a.example.com/page1.html is "a.example.com" and the port is 443, the standard port for HTTPS.

    Web proxy credentials are optional and you can use them to connect to a web proxy server that requires basic authentication of user name and password. To store web proxy credentials, you use a secret in Secrets Manager.

    It is recommended that you follow best security practices when configuring your web proxy. This includes setting up throttling, setting up logging and monitoring, and applying security patches on a regular basis. If you use your web proxy with multiple data sources, sync jobs that occur at the same time could strain the load on your proxy. It is recommended you prepare your proxy beforehand for any security and load requirements.

    *)
  2. authentication_type : share_point_online_authentication_type option;
    (*

    Whether you want to connect to SharePoint Online using basic authentication of user name and password, or OAuth authentication of user name, password, client ID, and client secret, or AD App-only authentication of client secret.

    *)
  3. ssl_certificate_s3_path : s3_path option;
    (*

    The path to the SSL certificate stored in an Amazon S3 bucket. You use this to connect to SharePoint Server if you require a secure SSL connection.

    You can generate a self-signed X509 certificate on any computer using OpenSSL. For an example of using OpenSSL to create an X509 certificate, see Create and sign an X509 certificate.

    *)
  4. disable_local_groups : bool option;
    (*

    TRUE to disable local groups information.

    *)
  5. document_title_field_name : string option;
    (*

    The Microsoft SharePoint attribute field that contains the title of the document.

    *)
  6. field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map SharePoint data source attributes or field names to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to SharePoint fields. For more information, see Mapping data source fields. The SharePoint data source field names must exist in your SharePoint custom metadata.

    *)
  7. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your Microsoft SharePoint. For more information, see Configuring a VPC.

    *)
  8. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain documents in your SharePoint. Documents that match the patterns are excluded from the index. Documents that don't match the patterns are included in the index. If a document matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the document isn't included in the index.

    The regex applies to the display URL of the SharePoint document.

    *)
  9. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain documents in your SharePoint. Documents that match the patterns are included in the index. Documents that don't match the patterns are excluded from the index. If a document matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the document isn't included in the index.

    The regex applies to the display URL of the SharePoint document.

    *)
  10. use_change_log : bool option;
    (*

    TRUE to use the SharePoint change log to determine which documents require updating in the index. Depending on the change log's size, it may take longer for Amazon Kendra to use the change log than to scan all of your documents in SharePoint.

    *)
  11. crawl_attachments : bool option;
    (*

    TRUE to index document attachments.

    *)
  12. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the user name and password required to connect to the SharePoint instance. For more information, see Microsoft SharePoint.

    *)
  13. urls : string list;
    (*

    The Microsoft SharePoint site URLs for the documents you want to index.

    *)
  14. share_point_version : share_point_version;
    (*

    The version of Microsoft SharePoint that you use.

    *)
}

Provides the configuration information to connect to Microsoft SharePoint as your data source.

type database_engine_type =
  1. | RDS_POSTGRESQL
  2. | RDS_MYSQL
  3. | RDS_AURORA_POSTGRESQL
  4. | RDS_AURORA_MYSQL
type connection_configuration = {
  1. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of credentials stored in Secrets Manager. The credentials should be a user/password pair. For more information, see Using a Database Data Source. For more information about Secrets Manager, see What Is Secrets Manager in the Secrets Manager user guide.

    *)
  2. table_name : string;
    (*

    The name of the table that contains the document data.

    *)
  3. database_name : string;
    (*

    The name of the database containing the document data.

    *)
  4. database_port : int;
    (*

    The port that the database uses for connections.

    *)
  5. database_host : string;
    (*

    The name of the host for the database. Can be either a string (host.subdomain.domain.tld) or an IPv4 or IPv6 address.

    *)
}

Provides the configuration information that's required to connect to a database.

type column_configuration = {
  1. change_detecting_columns : string list;
    (*

    One to five columns that indicate when a document in the database has changed.

    *)
  2. field_mappings : data_source_to_index_field_mapping list option;
    (*

    An array of objects that map database column names to the corresponding fields in an index. You must first create the fields in the index using the UpdateIndex API.

    *)
  3. document_title_column_name : string option;
    (*

    The column that contains the title of the document.

    *)
  4. document_data_column_name : string;
    (*

    The column that contains the contents of the document.

    *)
  5. document_id_column_name : string;
    (*

    The column that provides the document's identifier.

    *)
}

Provides information about how Amazon Kendra should use the columns of a database in an index.

type acl_configuration = {
  1. allowed_groups_column_name : string;
    (*

    A list of groups, separated by semi-colons, that filters a query response based on user context. The document is only returned to users that are in one of the groups specified in the UserContext field of the Query API.

    *)
}

Provides information about the column that should be used for filtering the query response by groups.

type query_identifiers_enclosing_option =
  1. | NONE
  2. | DOUBLE_QUOTES
type sql_configuration = {
  1. query_identifiers_enclosing_option : query_identifiers_enclosing_option option;
    (*

    Determines whether Amazon Kendra encloses SQL identifiers for tables and column names in double quotes (") when making a database query.

    By default, Amazon Kendra passes SQL identifiers the way that they are entered into the data source configuration. It does not change the case of identifiers or enclose them in quotes.

    PostgreSQL internally converts uppercase characters to lower case characters in identifiers unless they are quoted. Choosing this option encloses identifiers in quotes so that PostgreSQL does not convert the character's case.

    For MySQL databases, you must enable the ansi_quotes option when you set this field to DOUBLE_QUOTES.

    *)
}

Provides the configuration information to use a SQL database.

type database_configuration = {
  1. sql_configuration : sql_configuration option;
    (*

    Provides information about how Amazon Kendra uses quote marks around SQL identifiers when querying a database data source.

    *)
  2. acl_configuration : acl_configuration option;
    (*

    Information about the database column that provides information for user context filtering.

    *)
  3. column_configuration : column_configuration;
    (*

    Information about where the index should get the document information from the database.

    *)
  4. vpc_configuration : data_source_vpc_configuration option;
  5. connection_configuration : connection_configuration;
    (*

    Configuration information that's required to connect to a database.

    *)
  6. database_engine_type : database_engine_type;
    (*

    The type of database engine that runs the database.

    *)
}

Provides the configuration information to an Amazon Kendra supported database.

type salesforce_standard_object_name =
  1. | USER
  2. | TASK
  3. | SOLUTION
  4. | PROFILE
  5. | PRODUCT
  6. | PRICEBOOK
  7. | PARTNER
  8. | OPPORTUNITY
  9. | LEAD
  10. | IDEA
  11. | GROUP
  12. | DOCUMENT
  13. | CONTRACT
  14. | CONTACT
  15. | CASE
  16. | CAMPAIGN
  17. | ACCOUNT
type salesforce_standard_object_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    Maps attributes or field names of the standard object to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Salesforce fields. For more information, see Mapping data source fields. The Salesforce data source field names must exist in your Salesforce custom metadata.

    *)
  2. document_title_field_name : string option;
    (*

    The name of the field in the standard object table that contains the document title.

    *)
  3. document_data_field_name : string;
    (*

    The name of the field in the standard object table that contains the document contents.

    *)
  4. name : salesforce_standard_object_name;
    (*

    The name of the standard object.

    *)
}

Provides the configuration information for indexing a single standard object.

type salesforce_knowledge_article_state =
  1. | ARCHIVED
  2. | PUBLISHED
  3. | DRAFT
type salesforce_standard_knowledge_article_type_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    Maps attributes or field names of the knowledge article to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Salesforce fields. For more information, see Mapping data source fields. The Salesforce data source field names must exist in your Salesforce custom metadata.

    *)
  2. document_title_field_name : string option;
    (*

    The name of the field that contains the document title.

    *)
  3. document_data_field_name : string;
    (*

    The name of the field that contains the document data to index.

    *)
}

Provides the configuration information for standard Salesforce knowledge articles.

type salesforce_custom_knowledge_article_type_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    Maps attributes or field names of the custom knowledge article to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Salesforce fields. For more information, see Mapping data source fields. The Salesforce data source field names must exist in your Salesforce custom metadata.

    *)
  2. document_title_field_name : string option;
    (*

    The name of the field in the custom knowledge article that contains the document title.

    *)
  3. document_data_field_name : string;
    (*

    The name of the field in the custom knowledge article that contains the document data to index.

    *)
  4. name : string;
    (*

    The name of the configuration.

    *)
}

Provides the configuration information for indexing Salesforce custom articles.

type salesforce_knowledge_article_configuration = {
  1. custom_knowledge_article_type_configurations : salesforce_custom_knowledge_article_type_configuration list option;
    (*

    Configuration information for custom Salesforce knowledge articles.

    *)
  2. standard_knowledge_article_type_configuration : salesforce_standard_knowledge_article_type_configuration option;
    (*

    Configuration information for standard Salesforce knowledge articles.

    *)
  3. included_states : salesforce_knowledge_article_state list;
    (*

    Specifies the document states that should be included when Amazon Kendra indexes knowledge articles. You must specify at least one state.

    *)
}

Provides the configuration information for the knowledge article types that Amazon Kendra indexes. Amazon Kendra indexes standard knowledge articles and the standard fields of knowledge articles, or the custom fields of custom knowledge articles, but not both

type salesforce_chatter_feed_include_filter_type =
  1. | STANDARD_USER
  2. | ACTIVE_USER
type salesforce_chatter_feed_configuration = {
  1. include_filter_types : salesforce_chatter_feed_include_filter_type list option;
    (*

    Filters the documents in the feed based on status of the user. When you specify ACTIVE_USERS only documents from users who have an active account are indexed. When you specify STANDARD_USER only documents for Salesforce standard users are documented. You can specify both.

    *)
  2. field_mappings : data_source_to_index_field_mapping list option;
    (*

    Maps fields from a Salesforce chatter feed into Amazon Kendra index fields.

    *)
  3. document_title_field_name : string option;
    (*

    The name of the column in the Salesforce FeedItem table that contains the title of the document. This is typically the Title column.

    *)
  4. document_data_field_name : string;
    (*

    The name of the column in the Salesforce FeedItem table that contains the content to index. Typically this is the Body column.

    *)
}

The configuration information for syncing a Salesforce chatter feed. The contents of the object comes from the Salesforce FeedItem table.

type salesforce_standard_object_attachment_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    One or more objects that map fields in attachments to Amazon Kendra index fields.

    *)
  2. document_title_field_name : string option;
    (*

    The name of the field used for the document title.

    *)
}

Provides the configuration information for processing attachments to Salesforce standard objects.

type salesforce_configuration = {
  1. exclude_attachment_file_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain documents in your Salesforce. Documents that match the patterns are excluded from the index. Documents that don't match the patterns are included in the index. If a document matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the document isn't included in the index.

    The pattern is applied to the name of the attached file.

    *)
  2. include_attachment_file_patterns : string list option;
    (*

    A list of regular expression patterns to include certain documents in your Salesforce. Documents that match the patterns are included in the index. Documents that don't match the patterns are excluded from the index. If a document matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the document isn't included in the index.

    The pattern is applied to the name of the attached file.

    *)
  3. standard_object_attachment_configuration : salesforce_standard_object_attachment_configuration option;
    (*

    Configuration information for processing attachments to Salesforce standard objects.

    *)
  4. crawl_attachments : bool option;
    (*

    Indicates whether Amazon Kendra should index attachments to Salesforce objects.

    *)
  5. chatter_feed_configuration : salesforce_chatter_feed_configuration option;
    (*

    Configuration information for Salesforce chatter feeds.

    *)
  6. knowledge_article_configuration : salesforce_knowledge_article_configuration option;
    (*

    Configuration information for the knowledge article types that Amazon Kendra indexes. Amazon Kendra indexes standard knowledge articles and the standard fields of knowledge articles, or the custom fields of custom knowledge articles, but not both.

    *)
  7. standard_object_configurations : salesforce_standard_object_configuration list option;
    (*

    Configuration of the Salesforce standard objects that Amazon Kendra indexes.

    *)
  8. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Managersecret that contains the key/value pairs required to connect to your Salesforce instance. The secret must contain a JSON structure with the following keys:

    • authenticationUrl - The OAUTH endpoint that Amazon Kendra connects to get an OAUTH token.
    • consumerKey - The application public key generated when you created your Salesforce application.
    • consumerSecret - The application private key generated when you created your Salesforce application.
    • password - The password associated with the user logging in to the Salesforce instance.
    • securityToken - The token associated with the user logging in to the Salesforce instance.
    • username - The user name of the user logging in to the Salesforce instance.
    *)
  9. server_url : string;
    (*

    The instance URL for the Salesforce site that you want to index.

    *)
}

Provides the configuration information to connect to Salesforce as your data source.

type one_drive_users = {
  1. one_drive_user_s3_path : s3_path option;
    (*

    The S3 bucket location of a file containing a list of users whose documents should be indexed.

    *)
  2. one_drive_user_list : string list option;
    (*

    A list of users whose documents should be indexed. Specify the user names in email format, for example, username@tenantdomain. If you need to index the documents of more than 100 users, use the OneDriveUserS3Path field to specify the location of a file containing a list of users.

    *)
}

User accounts whose documents should be indexed.

type one_drive_configuration = {
  1. disable_local_groups : bool option;
    (*

    TRUE to disable local groups information.

    *)
  2. field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map OneDrive data source attributes or field names to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to OneDrive fields. For more information, see Mapping data source fields. The OneDrive data source field names must exist in your OneDrive custom metadata.

    *)
  3. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain documents in your OneDrive. Documents that match the patterns are excluded from the index. Documents that don't match the patterns are included in the index. If a document matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the document isn't included in the index.

    The pattern is applied to the file name.

    *)
  4. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain documents in your OneDrive. Documents that match the patterns are included in the index. Documents that don't match the patterns are excluded from the index. If a document matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the document isn't included in the index.

    The pattern is applied to the file name.

    *)
  5. one_drive_users : one_drive_users;
    (*

    A list of user accounts whose documents should be indexed.

    *)
  6. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Managersecret that contains the user name and password to connect to OneDrive. The user name should be the application ID for the OneDrive application, and the password is the application key for the OneDrive application.

    *)
  7. tenant_domain : string;
    (*

    The Azure Active Directory domain of the organization.

    *)
}

Provides the configuration information to connect to OneDrive as your data source.

type service_now_build_version_type =
  1. | OTHERS
  2. | LONDON
type service_now_knowledge_article_configuration = {
  1. filter_query : string option;
    (*

    A query that selects the knowledge articles to index. The query can return articles from multiple knowledge bases, and the knowledge bases can be public or private.

    The query string must be one generated by the ServiceNow console. For more information, see Specifying documents to index with a query.

    *)
  2. field_mappings : data_source_to_index_field_mapping list option;
    (*

    Maps attributes or field names of knoweldge articles to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to ServiceNow fields. For more information, see Mapping data source fields. The ServiceNow data source field names must exist in your ServiceNow custom metadata.

    *)
  3. document_title_field_name : string option;
    (*

    The name of the ServiceNow field that is mapped to the index document title field.

    *)
  4. document_data_field_name : string;
    (*

    The name of the ServiceNow field that is mapped to the index document contents field in the Amazon Kendra index.

    *)
  5. exclude_attachment_file_patterns : string list option;
    (*

    A list of regular expression patterns applied to exclude certain knowledge article attachments. Attachments that match the patterns are excluded from the index. Items that don't match the patterns are included in the index. If an item matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the item isn't included in the index.

    *)
  6. include_attachment_file_patterns : string list option;
    (*

    A list of regular expression patterns applied to include knowledge article attachments. Attachments that match the patterns are included in the index. Items that don't match the patterns are excluded from the index. If an item matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the item isn't included in the index.

    *)
  7. crawl_attachments : bool option;
    (*

    TRUE to index attachments to knowledge articles.

    *)
}

Provides the configuration information for crawling knowledge articles in the ServiceNow site.

type service_now_service_catalog_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    Maps attributes or field names of catalogs to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to ServiceNow fields. For more information, see Mapping data source fields. The ServiceNow data source field names must exist in your ServiceNow custom metadata.

    *)
  2. document_title_field_name : string option;
    (*

    The name of the ServiceNow field that is mapped to the index document title field.

    *)
  3. document_data_field_name : string;
    (*

    The name of the ServiceNow field that is mapped to the index document contents field in the Amazon Kendra index.

    *)
  4. exclude_attachment_file_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain attachments of catalogs in your ServiceNow. Item that match the patterns are excluded from the index. Items that don't match the patterns are included in the index. If an item matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the item isn't included in the index.

    The regex is applied to the file name of the attachment.

    *)
  5. include_attachment_file_patterns : string list option;
    (*

    A list of regular expression patterns to include certain attachments of catalogs in your ServiceNow. Item that match the patterns are included in the index. Items that don't match the patterns are excluded from the index. If an item matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the item isn't included in the index.

    The regex is applied to the file name of the attachment.

    *)
  6. crawl_attachments : bool option;
    (*

    TRUE to index attachments to service catalog items.

    *)
}

Provides the configuration information for crawling service catalog items in the ServiceNow site

type service_now_authentication_type =
  1. | OAUTH2
  2. | HTTP_BASIC
type service_now_configuration = {
  1. authentication_type : service_now_authentication_type option;
    (*

    The type of authentication used to connect to the ServiceNow instance. If you choose HTTP_BASIC, Amazon Kendra is authenticated using the user name and password provided in the Secrets Manager secret in the SecretArn field. If you choose OAUTH2, Amazon Kendra is authenticated using the credentials of client ID, client secret, user name and password.

    When you use OAUTH2 authentication, you must generate a token and a client secret using the ServiceNow console. For more information, see Using a ServiceNow data source.

    *)
  2. service_catalog_configuration : service_now_service_catalog_configuration option;
    (*

    Configuration information for crawling service catalogs in the ServiceNow site.

    *)
  3. knowledge_article_configuration : service_now_knowledge_article_configuration option;
    (*

    Configuration information for crawling knowledge articles in the ServiceNow site.

    *)
  4. service_now_build_version : service_now_build_version_type;
    (*

    The identifier of the release that the ServiceNow host is running. If the host is not running the LONDON release, use OTHERS.

    *)
  5. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of the Secrets Manager secret that contains the user name and password required to connect to the ServiceNow instance. You can also provide OAuth authentication credentials of user name, password, client ID, and client secret. For more information, see Using a ServiceNow data source.

    *)
  6. host_url : string;
    (*

    The ServiceNow instance that the data source connects to. The host endpoint should look like the following: {instance}.service-now.com.

    *)
}

Provides the configuration information to connect to ServiceNow as your data source.

type confluence_version =
  1. | SERVER
  2. | CLOUD
type confluence_space_field_name =
  1. | URL
  2. | SPACE_KEY
  3. | ITEM_TYPE
  4. | DISPLAY_URL
type confluence_space_to_index_field_mapping = {
  1. index_field_name : string option;
    (*

    The name of the index field to map to the Confluence data source field. The index field type must match the Confluence field type.

    *)
  2. date_field_format : string option;
    (*

    The format for date fields in the data source. If the field specified in DataSourceFieldName is a date field you must specify the date format. If the field is not a date field, an exception is thrown.

    *)
  3. data_source_field_name : confluence_space_field_name option;
    (*

    The name of the field in the data source.

    *)
}

Maps attributes or field names of Confluence spaces to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confluence data source field names must exist in your Confluence custom metadata.

type confluence_space_configuration = {
  1. space_field_mappings : confluence_space_to_index_field_mapping list option;
    (*

    Maps attributes or field names of Confluence spaces to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confluence data source field names must exist in your Confluence custom metadata.

    If you specify the SpaceFieldMappings parameter, you must specify at least one field mapping.

    *)
  2. exclude_spaces : string list option;
    (*

    A list of space keys of Confluence spaces. If you include a key, the blogs, documents, and attachments in the space are not indexed. If a space is in both the ExcludeSpaces and the IncludeSpaces list, the space is excluded.

    *)
  3. include_spaces : string list option;
    (*

    A list of space keys for Confluence spaces. If you include a key, the blogs, documents, and attachments in the space are indexed. Spaces that aren't in the list aren't indexed. A space in the list must exist. Otherwise, Amazon Kendra logs an error when the data source is synchronized. If a space is in both the IncludeSpaces and the ExcludeSpaces list, the space is excluded.

    *)
  4. crawl_archived_spaces : bool option;
    (*

    TRUE to index archived spaces.

    *)
  5. crawl_personal_spaces : bool option;
    (*

    TRUE to index personal spaces. You can add restrictions to items in personal spaces. If personal spaces are indexed, queries without user context information may return restricted items from a personal space in their results. For more information, see Filtering on user context.

    *)
}

Configuration information for indexing Confluence spaces.

type confluence_page_field_name =
  1. | VERSION
  2. | URL
  3. | SPACE_NAME
  4. | SPACE_KEY
  5. | PARENT_ID
  6. | MODIFIED_DATE
  7. | LABELS
  8. | ITEM_TYPE
  9. | DISPLAY_URL
  10. | CREATED_DATE
  11. | CONTENT_STATUS
  12. | AUTHOR
type confluence_page_to_index_field_mapping = {
  1. index_field_name : string option;
    (*

    The name of the index field to map to the Confluence data source field. The index field type must match the Confluence field type.

    *)
  2. date_field_format : string option;
    (*

    The format for date fields in the data source. If the field specified in DataSourceFieldName is a date field you must specify the date format. If the field is not a date field, an exception is thrown.

    *)
  3. data_source_field_name : confluence_page_field_name option;
    (*

    The name of the field in the data source.

    *)
}

Maps attributes or field names of Confluence pages to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confluence data source field names must exist in your Confluence custom metadata.

type confluence_page_configuration = {
  1. page_field_mappings : confluence_page_to_index_field_mapping list option;
    (*

    Maps attributes or field names of Confluence pages to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confluence data source field names must exist in your Confluence custom metadata.

    If you specify the PageFieldMappings parameter, you must specify at least one field mapping.

    *)
}

Configuration of the page settings for the Confluence data source.

type confluence_blog_field_name =
  1. | VERSION
  2. | URL
  3. | SPACE_NAME
  4. | SPACE_KEY
  5. | PUBLISH_DATE
  6. | LABELS
  7. | ITEM_TYPE
  8. | DISPLAY_URL
  9. | AUTHOR
type confluence_blog_to_index_field_mapping = {
  1. index_field_name : string option;
    (*

    The name of the index field to map to the Confluence data source field. The index field type must match the Confluence field type.

    *)
  2. date_field_format : string option;
    (*

    The format for date fields in the data source. If the field specified in DataSourceFieldName is a date field you must specify the date format. If the field is not a date field, an exception is thrown.

    *)
  3. data_source_field_name : confluence_blog_field_name option;
    (*

    The name of the field in the data source.

    *)
}

Maps attributes or field names of Confluence blog to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confluence data source field names must exist in your Confluence custom metadata.

type confluence_blog_configuration = {
  1. blog_field_mappings : confluence_blog_to_index_field_mapping list option;
    (*

    Maps attributes or field names of Confluence blogs to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confluence data source field names must exist in your Confluence custom metadata.

    If you specify the BlogFieldMappings parameter, you must specify at least one field mapping.

    *)
}

Configuration of blog settings for the Confluence data source. Blogs are always indexed unless filtered from the index by the ExclusionPatterns or InclusionPatterns fields in the ConfluenceConfiguration object.

type confluence_attachment_field_name =
  1. | VERSION
  2. | URL
  3. | SPACE_NAME
  4. | SPACE_KEY
  5. | PARENT_ID
  6. | ITEM_TYPE
  7. | FILE_SIZE
  8. | DISPLAY_URL
  9. | CREATED_DATE
  10. | CONTENT_TYPE
  11. | AUTHOR
type confluence_attachment_to_index_field_mapping = {
  1. index_field_name : string option;
    (*

    The name of the index field to map to the Confluence data source field. The index field type must match the Confluence field type.

    *)
  2. date_field_format : string option;
    (*

    The format for date fields in the data source. If the field specified in DataSourceFieldName is a date field you must specify the date format. If the field is not a date field, an exception is thrown.

    *)
  3. data_source_field_name : confluence_attachment_field_name option;
    (*

    The name of the field in the data source.

    You must first create the index field using the UpdateIndex API.

    *)
}

Maps attributes or field names of Confluence attachments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confuence data source field names must exist in your Confluence custom metadata.

type confluence_attachment_configuration = {
  1. attachment_field_mappings : confluence_attachment_to_index_field_mapping list option;
    (*

    Maps attributes or field names of Confluence attachments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Confluence fields. For more information, see Mapping data source fields. The Confluence data source field names must exist in your Confluence custom metadata.

    If you specify the AttachentFieldMappings parameter, you must specify at least one field mapping.

    *)
  2. crawl_attachments : bool option;
    (*

    TRUE to index attachments of pages and blogs in Confluence.

    *)
}

Configuration of attachment settings for the Confluence data source. Attachment settings are optional, if you don't specify settings attachments, Amazon Kendra won't index them.

type confluence_authentication_type =
  1. | PAT
  2. | HTTP_BASIC
type confluence_configuration = {
  1. authentication_type : confluence_authentication_type option;
    (*

    Whether you want to connect to Confluence using basic authentication of user name and password, or a personal access token. You can use a personal access token for Confluence Server.

    *)
  2. proxy_configuration : proxy_configuration option;
    (*

    Configuration information to connect to your Confluence URL instance via a web proxy. You can use this option for Confluence Server.

    You must provide the website host name and port number. For example, the host name of https://a.example.com/page1.html is "a.example.com" and the port is 443, the standard port for HTTPS.

    Web proxy credentials are optional and you can use them to connect to a web proxy server that requires basic authentication of user name and password. To store web proxy credentials, you use a secret in Secrets Manager.

    It is recommended that you follow best security practices when configuring your web proxy. This includes setting up throttling, setting up logging and monitoring, and applying security patches on a regular basis. If you use your web proxy with multiple data sources, sync jobs that occur at the same time could strain the load on your proxy. It is recommended you prepare your proxy beforehand for any security and load requirements.

    *)
  3. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain blog posts, pages, spaces, or attachments in your Confluence. Content that matches the patterns are excluded from the index. Content that doesn't match the patterns is included in the index. If content matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the content isn't included in the index.

    *)
  4. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain blog posts, pages, spaces, or attachments in your Confluence. Content that matches the patterns are included in the index. Content that doesn't match the patterns is excluded from the index. If content matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the content isn't included in the index.

    *)
  5. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your Confluence. For more information, see Configuring a VPC.

    *)
  6. attachment_configuration : confluence_attachment_configuration option;
    (*

    Configuration information for indexing attachments to Confluence blogs and pages.

    *)
  7. blog_configuration : confluence_blog_configuration option;
    (*

    Configuration information for indexing Confluence blogs.

    *)
  8. page_configuration : confluence_page_configuration option;
    (*

    Configuration information for indexing Confluence pages.

    *)
  9. space_configuration : confluence_space_configuration option;
    (*

    Configuration information for indexing Confluence spaces.

    *)
  10. version : confluence_version;
    (*

    The version or the type of Confluence installation to connect to.

    *)
  11. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the user name and password required to connect to the Confluence instance. If you use Confluence Cloud, you use a generated API token as the password.

    You can also provide authentication credentials in the form of a personal access token. For more information, see Using a Confluence data source.

    *)
  12. server_url : string;
    (*

    The URL of your Confluence instance. Use the full URL of the server. For example, https://server.example.com:port/. You can also use an IP address, for example, https://192.168.1.113/.

    *)
}

Provides the configuration information to connect to Confluence as your data source.

type google_drive_configuration = {
  1. exclude_shared_drives : string list option;
    (*

    A list of identifiers or shared drives to exclude from the index. All files and folders stored on the shared drive are excluded.

    *)
  2. exclude_user_accounts : string list option;
    (*

    A list of email addresses of the users. Documents owned by these users are excluded from the index. Documents shared with excluded users are indexed unless they are excluded in another way.

    *)
  3. exclude_mime_types : string list option;
    (*

    A list of MIME types to exclude from the index. All documents matching the specified MIME type are excluded.

    For a list of MIME types, see Using a Google Workspace Drive data source.

    *)
  4. field_mappings : data_source_to_index_field_mapping list option;
    (*

    Maps Google Drive data source attributes or field names to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Google Drive fields. For more information, see Mapping data source fields. The Google Drive data source field names must exist in your Google Drive custom metadata.

    *)
  5. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain items in your Google Drive, including shared drives and users' My Drives. Items that match the patterns are excluded from the index. Items that don't match the patterns are included in the index. If an item matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the item isn't included in the index.

    *)
  6. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain items in your Google Drive, including shared drives and users' My Drives. Items that match the patterns are included in the index. Items that don't match the patterns are excluded from the index. If an item matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the item isn't included in the index.

    *)
  7. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of a Secrets Managersecret that contains the credentials required to connect to Google Drive. For more information, see Using a Google Workspace Drive data source.

    *)
}

Provides the configuration information to connect to Google Drive as your data source.

type fsx_file_system_type =
  1. | WINDOWS
type fsx_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map Amazon FSx data source attributes or field names to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Amazon FSx fields. For more information, see Mapping data source fields. The Amazon FSx data source field names must exist in your Amazon FSx custom metadata.

    *)
  2. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain files in your Amazon FSx file system. Files that match the patterns are excluded from the index. Files that don't match the patterns are included in the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  3. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain files in your Amazon FSx file system. Files that match the patterns are included in the index. Files that don't match the patterns are excluded from the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  4. secret_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the key-value pairs required to connect to your Amazon FSx file system. Windows is currently the only supported type. The secret must contain a JSON structure with the following keys:

    • username—The Active Directory user name, along with the Domain Name System (DNS) domain name. For example, user@corp.example.com. The Active Directory user account must have read and mounting access to the Amazon FSx file system for Windows.
    • password—The password of the Active Directory user account with read and mounting access to the Amazon FSx Windows file system.
    *)
  5. vpc_configuration : data_source_vpc_configuration;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your Amazon FSx. Your Amazon FSx instance must reside inside your VPC.

    *)
  6. file_system_type : fsx_file_system_type;
    (*

    The Amazon FSx file system type. Windows is currently the only supported type.

    *)
  7. file_system_id : string;
    (*

    The identifier of the Amazon FSx file system.

    You can find your file system ID on the file system dashboard in the Amazon FSx console. For information on how to create a file system in Amazon FSx console, using Windows File Server as an example, see Amazon FSx Getting started guide.

    *)
}

Provides the configuration information to connect to Amazon FSx as your data source.

Amazon Kendra now supports an upgraded Amazon FSx Windows connector.

You must now use the TemplateConfiguration object instead of the FsxConfiguration object to configure your connector.

Connectors configured using the older console and API architecture will continue to function as configured. However, you won't be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

type slack_entity =
  1. | DIRECT_MESSAGE
  2. | GROUP_MESSAGE
  3. | PRIVATE_CHANNEL
  4. | PUBLIC_CHANNEL
type slack_configuration = {
  1. field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map Slack data source attributes or field names to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Slack fields. For more information, see Mapping data source fields. The Slack data source field names must exist in your Slack custom metadata.

    *)
  2. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain attached files in your Slack workspace team. Files that match the patterns are excluded from the index. Files that don’t match the patterns are included in the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  3. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain attached files in your Slack workspace team. Files that match the patterns are included in the index. Files that don't match the patterns are excluded from the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  4. public_channel_filter : string list option;
    (*

    The list of public channel names to index from your Slack workspace team. You use this if you want to index specific public channels, not all public channels. You can also use regular expression patterns to filter public channels.

    *)
  5. private_channel_filter : string list option;
    (*

    The list of private channel names from your Slack workspace team. You use this if you want to index specific private channels, not all private channels. You can also use regular expression patterns to filter private channels.

    *)
  6. look_back_period : int option;
    (*

    The number of hours for change log to look back from when you last synchronized your data. You can look back up to 7 days or 168 hours.

    Change log updates your index only if new content was added since you last synced your data. Updated or deleted content from before you last synced does not get updated in your index. To capture updated or deleted content before you last synced, set the LookBackPeriod to the number of hours you want change log to look back.

    *)
  7. since_crawl_date : string;
    (*

    The date to start crawling your data from your Slack workspace team. The date must follow this format: yyyy-mm-dd.

    *)
  8. exclude_archived : bool option;
    (*

    TRUE to exclude archived messages to index from your Slack workspace team.

    *)
  9. crawl_bot_message : bool option;
    (*

    TRUE to index bot messages from your Slack workspace team.

    *)
  10. use_change_log : bool option;
    (*

    TRUE to use the Slack change log to determine which documents require updating in the index. Depending on the Slack change log's size, it may take longer for Amazon Kendra to use the change log than to scan all of your documents in Slack.

    *)
  11. slack_entity_list : slack_entity list;
    (*

    Specify whether to index public channels, private channels, group messages, and direct messages. You can specify one or more of these options.

    *)
  12. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your Slack. For more information, see Configuring a VPC.

    *)
  13. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the key-value pairs required to connect to your Slack workspace team. The secret must contain a JSON structure with the following keys:

    *)
  14. team_id : string;
    (*

    The identifier of the team in the Slack workspace. For example, T0123456789.

    You can find your team ID in the URL of the main page of your Slack workspace. When you log in to Slack via a browser, you are directed to the URL of the main page. For example, https://app.slack.com/client/T0123456789/....

    *)
}

Provides the configuration information to connect to Slack as your data source.

Amazon Kendra now supports an upgraded Slack connector.

You must now use the TemplateConfiguration object instead of the SlackConfiguration object to configure your connector.

Connectors configured using the older console and API architecture will continue to function as configured. However, you won’t be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

type box_configuration = {
  1. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon VPC to connect to your Box. For more information, see Configuring a VPC.

    *)
  2. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain files and folders from your Box platform. Files and folders that match the patterns are excluded from the index.Files and folders that don't match the patterns are included in the index. If a file or folder matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file or folder isn't included in the index.

    *)
  3. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain files and folders in your Box platform. Files and folders that match the patterns are included in the index. Files and folders that don't match the patterns are excluded from the index. If a file or folder matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file or folder isn't included in the index.

    *)
  4. comment_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Box comments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Box fields. For more information, see Mapping data source fields. The Box field names must exist in your Box custom metadata.

    *)
  5. task_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Box tasks to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Box fields. For more information, see Mapping data source fields. The Box field names must exist in your Box custom metadata.

    *)
  6. file_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Box files to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Box fields. For more information, see Mapping data source fields. The Box field names must exist in your Box custom metadata.

    *)
  7. crawl_tasks : bool option;
    (*

    TRUE to index the contents of tasks.

    *)
  8. crawl_comments : bool option;
    (*

    TRUE to index comments.

    *)
  9. use_change_log : bool option;
    (*

    TRUE to use the Slack change log to determine which documents require updating in the index. Depending on the data source change log's size, it may take longer for Amazon Kendra to use the change log than to scan all of your documents.

    *)
  10. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the key-value pairs required to connect to your Box platform. The secret must contain a JSON structure with the following keys:

    • clientID—The identifier of the client OAuth 2.0 authentication application created in Box.
    • clientSecret—A set of characters known only to the OAuth 2.0 authentication application created in Box.
    • publicKeyId—The identifier of the public key contained within an identity certificate.
    • privateKey—A set of characters that make up an encryption key.
    • passphrase—A set of characters that act like a password.

    You create an application in Box to generate the keys or credentials required for the secret. For more information, see Using a Box data source.

    *)
  11. enterprise_id : string;
    (*

    The identifier of the Box Enterprise platform. You can find the enterprise ID in the Box Developer Console settings or when you create an app in Box and download your authentication credentials. For example, 801234567.

    *)
}

Provides the configuration information to connect to Box as your data source.

type quip_configuration = {
  1. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud (VPC) to connect to your Quip. For more information, see Configuring a VPC.

    *)
  2. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain files in your Quip file system. Files that match the patterns are excluded from the index. Files that don’t match the patterns are included in the index. If a file matches both an inclusion pattern and an exclusion pattern, the exclusion pattern takes precedence, and the file isn't included in the index.

    *)
  3. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain files in your Quip file system. Files that match the patterns are included in the index. Files that don't match the patterns are excluded from the index. If a file matches both an inclusion pattern and an exclusion pattern, the exclusion pattern takes precedence, and the file isn't included in the index.

    *)
  4. attachment_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Quip attachments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Quip fields. For more information, see Mapping data source fields. The Quip field names must exist in your Quip custom metadata.

    *)
  5. message_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Quip messages to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Quip fields. For more information, see Mapping data source fields. The Quip field names must exist in your Quip custom metadata.

    *)
  6. thread_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Quip threads to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Quip fields. For more information, see Mapping data source fields. The Quip field names must exist in your Quip custom metadata.

    *)
  7. folder_ids : string list option;
    (*

    The identifiers of the Quip folders you want to index. You can find the folder ID in your browser URL when you access your folder in Quip. For example, https://quip-company.quipdomain.com/zlLuOVNSarTL/folder-name. The folder ID in this example is "zlLuOVNSarTL".

    *)
  8. crawl_attachments : bool option;
    (*

    TRUE to index attachments.

    *)
  9. crawl_chat_rooms : bool option;
    (*

    TRUE to index the contents of chat rooms.

    *)
  10. crawl_file_comments : bool option;
    (*

    TRUE to index file comments.

    *)
  11. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the key-value pairs that are required to connect to your Quip. The secret must contain a JSON structure with the following keys:

    *)
  12. domain : string;
    (*

    The Quip site domain. For example, https://quip-company.quipdomain.com/browse. The domain in this example is "quipdomain".

    *)
}

Provides the configuration information to connect to Quip as your data source.

type issue_sub_entity =
  1. | WORKLOGS
  2. | ATTACHMENTS
  3. | COMMENTS
type jira_configuration = {
  1. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your Jira. For more information, see Configuring a VPC.

    *)
  2. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain file paths, file names, and file types in your Jira data source. Files that match the patterns are excluded from the index. Files that don’t match the patterns are included in the index. If a file matches both an inclusion pattern and an exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  3. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain file paths, file names, and file types in your Jira data source. Files that match the patterns are included in the index. Files that don't match the patterns are excluded from the index. If a file matches both an inclusion pattern and an exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  4. work_log_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Jira work logs to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Jira fields. For more information, see Mapping data source fields. The Jira data source field names must exist in your Jira custom metadata.

    *)
  5. project_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Jira projects to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Jira fields. For more information, see Mapping data source fields. The Jira data source field names must exist in your Jira custom metadata.

    *)
  6. issue_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Jira issues to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Jira fields. For more information, see Mapping data source fields. The Jira data source field names must exist in your Jira custom metadata.

    *)
  7. comment_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Jira comments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Jira fields. For more information, see Mapping data source fields. The Jira data source field names must exist in your Jira custom metadata.

    *)
  8. attachment_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Jira attachments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Jira fields. For more information, see Mapping data source fields. The Jira data source field names must exist in your Jira custom metadata.

    *)
  9. issue_sub_entity_filter : issue_sub_entity list option;
    (*

    Specify whether to crawl comments, attachments, and work logs. You can specify one or more of these options.

    *)
  10. status : string list option;
    (*

    Specify which statuses to crawl in your Jira data source. You can specify one or more of these options to crawl.

    *)
  11. issue_type : string list option;
    (*

    Specify which issue types to crawl in your Jira data source. You can specify one or more of these options to crawl.

    *)
  12. project : string list option;
    (*

    Specify which projects to crawl in your Jira data source. You can specify one or more Jira project IDs.

    *)
  13. use_change_log : bool option;
    (*

    TRUE to use the Jira change log to determine which documents require updating in the index. Depending on the change log's size, it may take longer for Amazon Kendra to use the change log than to scan all of your documents in Jira.

    *)
  14. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of a secret in Secrets Manager contains the key-value pairs required to connect to your Jira data source. The secret must contain a JSON structure with the following keys:

    • jiraId—The Jira user name or email.
    • jiraCredentials—The Jira API token. For more information, see Using a Jira data source.
    *)
  15. jira_account_url : string;
    (*

    The URL of the Jira account. For example, company.atlassian.net.

    *)
}

Provides the configuration information to connect to Jira as your data source.

type saa_s_configuration = {
  1. host_url : string;
    (*

    The GitHub host URL or API endpoint URL. For example, https://api.github.com.

    *)
  2. organization_name : string;
    (*

    The name of the organization of the GitHub Enterprise Cloud (SaaS) account you want to connect to. You can find your organization name by logging into GitHub desktop and selecting Your organizations under your profile picture dropdown.

    *)
}

Provides the configuration information to connect to GitHub Enterprise Cloud (SaaS).

type on_premise_configuration = {
  1. ssl_certificate_s3_path : s3_path;
    (*

    The path to the SSL certificate stored in an Amazon S3 bucket. You use this to connect to GitHub if you require a secure SSL connection.

    You can simply generate a self-signed X509 certificate on any computer using OpenSSL. For an example of using OpenSSL to create an X509 certificate, see Create and sign an X509 certificate.

    *)
  2. organization_name : string;
    (*

    The name of the organization of the GitHub Enterprise Server (on-premises) account you want to connect to. You can find your organization name by logging into GitHub desktop and selecting Your organizations under your profile picture dropdown.

    *)
  3. host_url : string;
    (*

    The GitHub host URL or API endpoint URL. For example, https://on-prem-host-url/api/v3/

    *)
}

Provides the configuration information to connect to GitHub Enterprise Server (on premises).

type type_ =
  1. | ON_PREMISE
  2. | SAAS
type git_hub_document_crawl_properties = {
  1. crawl_pull_request_comment_attachment : bool option;
    (*

    TRUE to include all comment attachments for pull requests.

    *)
  2. crawl_pull_request_comment : bool option;
    (*

    TRUE to index all comments on pull requests.

    *)
  3. crawl_pull_request : bool option;
    (*

    TRUE to index all pull requests within a repository.

    *)
  4. crawl_issue_comment_attachment : bool option;
    (*

    TRUE to include all comment attachments for issues.

    *)
  5. crawl_issue_comment : bool option;
    (*

    TRUE to index all comments on issues.

    *)
  6. crawl_issue : bool option;
    (*

    TRUE to index all issues within a repository.

    *)
  7. crawl_repository_documents : bool option;
    (*

    TRUE to index all files with a repository.

    *)
}

Provides the configuration information to include certain types of GitHub content. You can configure to index repository files only, or also include issues and pull requests, comments, and comment attachments.

type git_hub_configuration = {
  1. git_hub_pull_request_document_attachment_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of GitHub pull request attachments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  2. git_hub_pull_request_document_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of GitHub pull requests to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  3. git_hub_pull_request_comment_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of GitHub pull request comments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  4. git_hub_issue_attachment_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of GitHub issue attachments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  5. git_hub_issue_comment_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of GitHub issue comments to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  6. git_hub_issue_document_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of GitHub issues to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  7. git_hub_commit_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of GitHub commits to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  8. git_hub_repository_configuration_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map GitHub repository attributes or field names to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to GitHub fields. For more information, see Mapping data source fields. The GitHub data source field names must exist in your GitHub custom metadata.

    *)
  9. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information of an Amazon Virtual Private Cloud to connect to your GitHub. For more information, see Configuring a VPC.

    *)
  10. exclusion_file_name_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain file names in your GitHub repository or repositories. File names that match the patterns are excluded from the index. File names that don't match the patterns are included in the index. If a file matches both an exclusion and inclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  11. exclusion_file_type_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain file types in your GitHub repository or repositories. File types that match the patterns are excluded from the index. File types that don't match the patterns are included in the index. If a file matches both an exclusion and inclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  12. exclusion_folder_name_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain folder names in your GitHub repository or repositories. Folder names that match the patterns are excluded from the index. Folder names that don't match the patterns are included in the index. If a folder matches both an exclusion and inclusion pattern, the exclusion pattern takes precedence and the folder isn't included in the index.

    *)
  13. inclusion_file_name_patterns : string list option;
    (*

    A list of regular expression patterns to include certain file names in your GitHub repository or repositories. File names that match the patterns are included in the index. File names that don't match the patterns are excluded from the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  14. inclusion_file_type_patterns : string list option;
    (*

    A list of regular expression patterns to include certain file types in your GitHub repository or repositories. File types that match the patterns are included in the index. File types that don't match the patterns are excluded from the index. If a file matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  15. inclusion_folder_name_patterns : string list option;
    (*

    A list of regular expression patterns to include certain folder names in your GitHub repository or repositories. Folder names that match the patterns are included in the index. Folder names that don't match the patterns are excluded from the index. If a folder matches both an inclusion and exclusion pattern, the exclusion pattern takes precedence and the folder isn't included in the index.

    *)
  16. repository_filter : string list option;
    (*

    A list of names of the specific repositories you want to index.

    *)
  17. git_hub_document_crawl_properties : git_hub_document_crawl_properties option;
    (*

    Configuration information to include certain types of GitHub content. You can configure to index repository files only, or also include issues and pull requests, comments, and comment attachments.

    *)
  18. use_change_log : bool option;
    (*

    TRUE to use the GitHub change log to determine which documents require updating in the index. Depending on the GitHub change log's size, it may take longer for Amazon Kendra to use the change log than to scan all of your documents in GitHub.

    *)
  19. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the key-value pairs required to connect to your GitHub. The secret must contain a JSON structure with the following keys:

    • personalToken—The access token created in GitHub. For more information on creating a token in GitHub, see Using a GitHub data source.
    *)
  20. type_ : type_ option;
    (*

    The type of GitHub service you want to connect to—GitHub Enterprise Cloud (SaaS) or GitHub Enterprise Server (on premises).

    *)
  21. on_premise_configuration : on_premise_configuration option;
    (*

    Configuration information to connect to GitHub Enterprise Server (on premises).

    *)
  22. saa_s_configuration : saa_s_configuration option;
    (*

    Configuration information to connect to GitHub Enterprise Cloud (SaaS).

    *)
}

Provides the configuration information to connect to GitHub as your data source.

Amazon Kendra now supports an upgraded GitHub connector.

You must now use the TemplateConfiguration object instead of the GitHubConfiguration object to configure your connector.

Connectors configured using the older console and API architecture will continue to function as configured. However, you won’t be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

type alfresco_entity =
  1. | DocumentLibrary
  2. | Blog
  3. | Wiki
type alfresco_configuration = {
  1. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your Alfresco. For more information, see Configuring a VPC.

    *)
  2. exclusion_patterns : string list option;
    (*

    A list of regular expression patterns to exclude certain files in your Alfresco data source. Files that match the patterns are excluded from the index. Files that don't match the patterns are included in the index. If a file matches both an inclusion pattern and an exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  3. inclusion_patterns : string list option;
    (*

    A list of regular expression patterns to include certain files in your Alfresco data source. Files that match the patterns are included in the index. Files that don't match the patterns are excluded from the index. If a file matches both an inclusion pattern and an exclusion pattern, the exclusion pattern takes precedence and the file isn't included in the index.

    *)
  4. wiki_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Alfresco wikis to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Alfresco fields. For more information, see Mapping data source fields. The Alfresco data source field names must exist in your Alfresco custom metadata.

    *)
  5. blog_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Alfresco blogs to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Alfresco fields. For more information, see Mapping data source fields. The Alfresco data source field names must exist in your Alfresco custom metadata.

    *)
  6. document_library_field_mappings : data_source_to_index_field_mapping list option;
    (*

    A list of DataSourceToIndexFieldMapping objects that map attributes or field names of Alfresco document libraries to Amazon Kendra index field names. To create custom fields, use the UpdateIndex API before you map to Alfresco fields. For more information, see Mapping data source fields. The Alfresco data source field names must exist in your Alfresco custom metadata.

    *)
  7. entity_filter : alfresco_entity list option;
    (*

    Specify whether to index document libraries, wikis, or blogs. You can specify one or more of these options.

    *)
  8. crawl_comments : bool option;
    (*

    TRUE to index comments of blogs and other content.

    *)
  9. crawl_system_folders : bool option;
    (*

    TRUE to index shared files.

    *)
  10. ssl_certificate_s3_path : s3_path;
    (*

    The path to the SSL certificate stored in an Amazon S3 bucket. You use this to connect to Alfresco if you require a secure SSL connection.

    You can simply generate a self-signed X509 certificate on any computer using OpenSSL. For an example of using OpenSSL to create an X509 certificate, see Create and sign an X509 certificate.

    *)
  11. secret_arn : string;
    (*

    The Amazon Resource Name (ARN) of an Secrets Manager secret that contains the key-value pairs required to connect to your Alfresco data source. The secret must contain a JSON structure with the following keys:

    • username—The user name of the Alfresco account.
    • password—The password of the Alfresco account.
    *)
  12. site_id : string;
    (*

    The identifier of the Alfresco site. For example, my-site.

    *)
  13. site_url : string;
    (*

    The URL of the Alfresco site. For example, https://hostname:8080.

    *)
}

Provides the configuration information to connect to Alfresco as your data source.

Support for AlfrescoConfiguration ended May 2023. We recommend migrating to or using the Alfresco data source template schema / TemplateConfiguration API.

type template = Smaws_Lib.Json.t
type template_configuration = {
  1. template : template option;
    (*

    The template schema used for the data source, where templates schemas are supported.

    See Data source template schemas.

    *)
}

Provides a template for the configuration information to connect to your data source.

type data_source_configuration = {
  1. template_configuration : template_configuration option;
    (*

    Provides a template for the configuration information to connect to your data source.

    *)
  2. alfresco_configuration : alfresco_configuration option;
    (*

    Provides the configuration information to connect to Alfresco as your data source.

    Support for AlfrescoConfiguration ended May 2023. We recommend migrating to or using the Alfresco data source template schema / TemplateConfiguration API.

    *)
  3. git_hub_configuration : git_hub_configuration option;
    (*

    Provides the configuration information to connect to GitHub as your data source.

    Amazon Kendra now supports an upgraded GitHub connector.

    You must now use the TemplateConfiguration object instead of the GitHubConfiguration object to configure your connector.

    Connectors configured using the older console and API architecture will continue to function as configured. However, you won’t be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

    We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

    *)
  4. jira_configuration : jira_configuration option;
    (*

    Provides the configuration information to connect to Jira as your data source.

    *)
  5. quip_configuration : quip_configuration option;
    (*

    Provides the configuration information to connect to Quip as your data source.

    *)
  6. box_configuration : box_configuration option;
    (*

    Provides the configuration information to connect to Box as your data source.

    *)
  7. slack_configuration : slack_configuration option;
    (*

    Provides the configuration information to connect to Slack as your data source.

    Amazon Kendra now supports an upgraded Slack connector.

    You must now use the TemplateConfiguration object instead of the SlackConfiguration object to configure your connector.

    Connectors configured using the older console and API architecture will continue to function as configured. However, you won't be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

    We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

    *)
  8. fsx_configuration : fsx_configuration option;
    (*

    Provides the configuration information to connect to Amazon FSx as your data source.

    Amazon Kendra now supports an upgraded Amazon FSx Windows connector.

    You must now use the TemplateConfiguration object instead of the FsxConfiguration object to configure your connector.

    Connectors configured using the older console and API architecture will continue to function as configured. However, you won't be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

    We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

    *)
  9. work_docs_configuration : work_docs_configuration option;
    (*

    Provides the configuration information to connect to Amazon WorkDocs as your data source.

    *)
  10. web_crawler_configuration : web_crawler_configuration option;
  11. google_drive_configuration : google_drive_configuration option;
    (*

    Provides the configuration information to connect to Google Drive as your data source.

    *)
  12. confluence_configuration : confluence_configuration option;
    (*

    Provides the configuration information to connect to Confluence as your data source.

    *)
  13. service_now_configuration : service_now_configuration option;
    (*

    Provides the configuration information to connect to ServiceNow as your data source.

    *)
  14. one_drive_configuration : one_drive_configuration option;
    (*

    Provides the configuration information to connect to Microsoft OneDrive as your data source.

    *)
  15. salesforce_configuration : salesforce_configuration option;
    (*

    Provides the configuration information to connect to Salesforce as your data source.

    *)
  16. database_configuration : database_configuration option;
    (*

    Provides the configuration information to connect to a database as your data source.

    *)
  17. share_point_configuration : share_point_configuration option;
    (*

    Provides the configuration information to connect to Microsoft SharePoint as your data source.

    *)
  18. s3_configuration : s3_data_source_configuration option;
    (*

    Provides the configuration information to connect to an Amazon S3 bucket as your data source.

    Amazon Kendra now supports an upgraded Amazon S3 connector.

    You must now use the TemplateConfiguration object instead of the S3DataSourceConfiguration object to configure your connector.

    Connectors configured using the older console and API architecture will continue to function as configured. However, you won't be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector.

    We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024.

    *)
}

Provides the configuration information for an Amazon Kendra data source.

type condition_operator =
  1. | BeginsWith
  2. | NotExists
  3. | Exists
  4. | NotContains
  5. | Contains
  6. | NotEquals
  7. | Equals
  8. | LessThanOrEquals
  9. | LessThan
  10. | GreaterThanOrEquals
  11. | GreaterThan
type document_attribute_value = {
  1. date_value : float option;
    (*

    A date expressed as an ISO 8601 string.

    It is important for the time zone to be included in the ISO 8601 date-time format. For example, 2012-03-25T12:30:10+01:00 is the ISO 8601 date-time format for March 25th 2012 at 12:30PM (plus 10 seconds) in Central European Time.

    *)
  2. long_value : int option;
    (*

    A long integer value.

    *)
  3. string_list_value : string list option;
    (*

    A list of strings. The default maximum length or number of strings is 10.

    *)
  4. string_value : string option;
    (*

    A string, such as "department".

    *)
}

The value of a document attribute. You can only provide one value for a document attribute.

type document_attribute_condition = {
  1. condition_on_value : document_attribute_value option;
    (*

    The value used by the operator.

    For example, you can specify the value 'financial' for strings in the 'Source_URI' field that partially match or contain this value.

    *)
  2. operator : condition_operator;
    (*

    The condition operator.

    For example, you can use 'Contains' to partially match a string.

    *)
  3. condition_document_attribute_key : string;
    (*

    The identifier of the document attribute used for the condition.

    For example, 'Source_URI' could be an identifier for the attribute or metadata field that contains source URIs associated with the documents.

    Amazon Kendra currently does not support _document_body as an attribute key used for the condition.

    *)
}

The condition used for the target document attribute or metadata field when ingesting documents into Amazon Kendra. You use this with DocumentAttributeTarget to apply the condition.

For example, you can create the 'Department' target field and have it prefill department names associated with the documents based on information in the 'Source_URI' field. Set the condition that if the 'Source_URI' field contains 'financial' in its URI value, then prefill the target field 'Department' with the target value 'Finance' for the document.

Amazon Kendra cannot create a target field if it has not already been created as an index field. After you create your index field, you can create a document metadata field using DocumentAttributeTarget. Amazon Kendra then will map your newly created metadata field to your index field.

type document_attribute_target = {
  1. target_document_attribute_value : document_attribute_value option;
    (*

    The target value you want to create for the target attribute.

    For example, 'Finance' could be the target value for the target attribute key 'Department'.

    *)
  2. target_document_attribute_value_deletion : bool option;
    (*

    TRUE to delete the existing target value for your specified target attribute key. You cannot create a target value and set this to TRUE. To create a target value (TargetDocumentAttributeValue), set this to FALSE.

    *)
  3. target_document_attribute_key : string option;
    (*

    The identifier of the target document attribute or metadata field.

    For example, 'Department' could be an identifier for the target attribute or metadata field that includes the department names associated with the documents.

    *)
}

The target document attribute or metadata field you want to alter when ingesting documents into Amazon Kendra.

For example, you can delete customer identification numbers associated with the documents, stored in the document metadata field called 'Customer_ID'. You set the target key as 'Customer_ID' and the deletion flag to TRUE. This removes all customer ID values in the field 'Customer_ID'. This would scrub personally identifiable information from each document's metadata.

Amazon Kendra cannot create a target field if it has not already been created as an index field. After you create your index field, you can create a document metadata field using DocumentAttributeTarget. Amazon Kendra then will map your newly created metadata field to your index field.

You can also use this with DocumentAttributeCondition.

type inline_custom_document_enrichment_configuration = {
  1. document_content_deletion : bool option;
    (*

    TRUE to delete content if the condition used for the target attribute is met.

    *)
  2. target : document_attribute_target option;
    (*

    Configuration of the target document attribute or metadata field when ingesting documents into Amazon Kendra. You can also include a value.

    *)
  3. condition : document_attribute_condition option;
    (*

    Configuration of the condition used for the target document attribute or metadata field when ingesting documents into Amazon Kendra.

    *)
}

Provides the configuration information for applying basic logic to alter document metadata and content when ingesting documents into Amazon Kendra. To apply advanced logic, to go beyond what you can do with basic logic, see HookConfiguration.

For more information, see Customizing document metadata during the ingestion process.

type hook_configuration = {
  1. s3_bucket : string;
    (*

    Stores the original, raw documents or the structured, parsed documents before and after altering them. For more information, see Data contracts for Lambda functions.

    *)
  2. lambda_arn : string;
    (*

    The Amazon Resource Name (ARN) of a role with permission to run a Lambda function during ingestion. For more information, see IAM roles for Amazon Kendra.

    *)
  3. invocation_condition : document_attribute_condition option;
    (*

    The condition used for when a Lambda function should be invoked.

    For example, you can specify a condition that if there are empty date-time values, then Amazon Kendra should invoke a function that inserts the current date-time.

    *)
}

Provides the configuration information for invoking a Lambda function in Lambda to alter document metadata and content when ingesting documents into Amazon Kendra. You can configure your Lambda function using PreExtractionHookConfiguration if you want to apply advanced alterations on the original or raw documents. If you want to apply advanced alterations on the Amazon Kendra structured documents, you must configure your Lambda function using PostExtractionHookConfiguration. You can only invoke one Lambda function. However, this function can invoke other functions it requires.

For more information, see Customizing document metadata during the ingestion process.

type custom_document_enrichment_configuration = {
  1. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of a role with permission to run PreExtractionHookConfiguration and PostExtractionHookConfiguration for altering document metadata and content during the document ingestion process. For more information, see IAM roles for Amazon Kendra.

    *)
  2. post_extraction_hook_configuration : hook_configuration option;
    (*

    Configuration information for invoking a Lambda function in Lambda on the structured documents with their metadata and text extracted. You can use a Lambda function to apply advanced logic for creating, modifying, or deleting document metadata and content. For more information, see Advanced data manipulation.

    *)
  3. pre_extraction_hook_configuration : hook_configuration option;
    (*

    Configuration information for invoking a Lambda function in Lambda on the original or raw documents before extracting their metadata and text. You can use a Lambda function to apply advanced logic for creating, modifying, or deleting document metadata and content. For more information, see Advanced data manipulation.

    *)
  4. inline_configurations : inline_custom_document_enrichment_configuration list option;
    (*

    Configuration information to alter document attributes or metadata fields and content when ingesting documents into Amazon Kendra.

    *)
}

Provides the configuration information for altering document metadata and content during the document ingestion process.

For more information, see Customizing document metadata during the ingestion process.

type update_data_source_request = {
  1. custom_document_enrichment_configuration : custom_document_enrichment_configuration option;
    (*

    Configuration information you want to update for altering document metadata and content during the document ingestion process.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

    *)
  2. language_code : string option;
    (*

    The code for a language you want to update for the data source connector. This allows you to support a language for all documents when updating the data source. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    *)
  3. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of a role with permission to access the data source and required resources. For more information, see IAM roles for Amazon Kendra.

    *)
  4. schedule : string option;
    (*

    The sync schedule you want to update for the data source connector.

    *)
  5. description : string option;
    (*

    A new description for the data source connector.

    *)
  6. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your data source. For more information, see Configuring a VPC.

    *)
  7. configuration : data_source_configuration option;
    (*

    Configuration information you want to update for the data source connector.

    *)
  8. index_id : string;
    (*

    The identifier of the index used with the data source connector.

    *)
  9. name : string option;
    (*

    A new name for the data source connector.

    *)
  10. id : string;
    (*

    The identifier of the data source connector you want to update.

    *)
}
type update_access_control_configuration_response = unit
type principal_type =
  1. | GROUP
  2. | USER
type read_access_type =
  1. | DENY
  2. | ALLOW
type principal = {
  1. data_source_id : string option;
    (*

    The identifier of the data source the principal should access documents from.

    *)
  2. access : read_access_type;
    (*

    Whether to allow or deny document access to the principal.

    *)
  3. type_ : principal_type;
    (*

    The type of principal.

    *)
  4. name : string;
    (*

    The name of the user or group.

    *)
}

Provides user and group information for user context filtering.

type hierarchical_principal = {
  1. principal_list : principal list;
    (*

    A list of principal lists that define the hierarchy for which documents users should have access to. Each hierarchical list specifies which user or group has allow or deny access for each document.

    *)
}

Information to define the hierarchy for which documents users should have access to.

type update_access_control_configuration_request = {
  1. hierarchical_access_control_list : hierarchical_principal list option;
    (*

    The updated list of principal lists that define the hierarchy for which documents users should have access to.

    *)
  2. access_control_list : principal list option;
    (*

    Information you want to update on principals (users and/or groups) and which documents they should have access to. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    *)
  3. description : string option;
    (*

    A new description for the access control configuration.

    *)
  4. name : string option;
    (*

    A new name for the access control configuration.

    *)
  5. id : string;
    (*

    The identifier of the access control configuration you want to update.

    *)
  6. index_id : string;
    (*

    The identifier of the index for an access control configuration.

    *)
}
type untag_resource_response = unit
type untag_resource_request = {
  1. tag_keys : string list;
    (*

    A list of tag keys to remove from the index, FAQ, or data source. If a tag key does not exist on the resource, it is ignored.

    *)
  2. resource_ar_n : string;
    (*

    The Amazon Resource Name (ARN) of the index, FAQ, or data source to remove the tag from.

    *)
}
type resource_unavailable_exception = {
  1. message : string option;
}

The resource you want to use isn't available. Please check you have provided the correct resource and try again.

type time_range = {
  1. end_time : float option;
    (*

    The Unix timestamp for the end of the time range.

    *)
  2. start_time : float option;
    (*

    The Unix timestamp for the beginning of the time range.

    *)
}

Provides a range of time.

type thesaurus_status =
  1. | FAILED
  2. | ACTIVE_BUT_UPDATE_FAILED
  3. | UPDATING
  4. | DELETING
  5. | ACTIVE
  6. | CREATING
type thesaurus_summary = {
  1. updated_at : float option;
    (*

    The Unix timestamp when the thesaurus was last updated.

    *)
  2. created_at : float option;
    (*

    The Unix timestamp when the thesaurus was created.

    *)
  3. status : thesaurus_status option;
    (*

    The status of the thesaurus.

    *)
  4. name : string option;
    (*

    The name of the thesaurus.

    *)
  5. id : string option;
    (*

    The identifier of the thesaurus.

    *)
}

An array of summary information for a thesaurus or multiple thesauri.

type highlight_type =
  1. | THESAURUS_SYNONYM
  2. | STANDARD
type highlight = {
  1. type_ : highlight_type option;
    (*

    The highlight type.

    *)
  2. top_answer : bool option;
    (*

    Indicates whether the response is the best response. True if this is the best response; otherwise, false.

    *)
  3. end_offset : int;
    (*

    The zero-based location in the response string where the highlight ends.

    *)
  4. begin_offset : int;
    (*

    The zero-based location in the response string where the highlight starts.

    *)
}

Provides information that you can use to highlight a search result so that your users can quickly identify terms in the response.

type text_with_highlights = {
  1. highlights : highlight list option;
    (*

    The beginning and end of the text that should be highlighted.

    *)
  2. text : string option;
    (*

    The text to display to the user.

    *)
}

Provides text and information about where to highlight the text.

type text_document_statistics = {
  1. indexed_text_bytes : int;
    (*

    The total size, in bytes, of the indexed documents.

    *)
  2. indexed_text_documents_count : int;
    (*

    The number of text documents indexed.

    *)
}

Provides information about text documents indexed in an index.

type tag_resource_response = unit
type tag = {
  1. value : string;
    (*

    The value associated with the tag. The value may be an empty string but it can't be null.

    *)
  2. key : string;
    (*

    The key for the tag. Keys are not case sensitive and must be unique for the index, FAQ, or data source.

    *)
}

A list of key/value pairs that identify an index, FAQ, or data source. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

type tag_resource_request = {
  1. tags : tag list;
    (*

    A list of tag keys to add to the index, FAQ, or data source. If a tag already exists, the existing value is replaced with the new value.

    *)
  2. resource_ar_n : string;
    (*

    The Amazon Resource Name (ARN) of the index, FAQ, or data source to tag.

    *)
}
type table_cell = {
  1. header : bool option;
    (*

    TRUE means that the table cell should be treated as a header.

    *)
  2. highlighted : bool option;
    (*

    TRUE means that the table cell has a high enough confidence and is relevant to the query, so the value or content should be highlighted.

    *)
  3. top_answer : bool option;
    (*

    TRUE if the response of the table cell is the top answer. This is the cell value or content with the highest confidence score or is the most relevant to the query.

    *)
  4. value : string option;
    (*

    The actual value or content within a table cell. A table cell could contain a date value of a year, or a string value of text, for example.

    *)
}

Provides information about a table cell in a table excerpt.

type table_row = {
  1. cells : table_cell list option;
    (*

    A list of table cells in a row.

    *)
}

Information about a row in a table excerpt.

type table_excerpt = {
  1. total_number_of_rows : int option;
    (*

    A count of the number of rows in the original table within the document.

    *)
  2. rows : table_row list option;
    (*

    A list of rows in the table excerpt.

    *)
}

An excerpt from a table within a document. The table excerpt displays up to five columns and three rows, depending on how many table cells are relevant to the query and how many columns are available in the original table. The top most relevant cell is displayed in the table excerpt, along with the next most relevant cells.

type suggestion_highlight = {
  1. end_offset : int option;
    (*

    The zero-based location in the response string where the highlight ends.

    *)
  2. begin_offset : int option;
    (*

    The zero-based location in the response string where the highlight starts.

    *)
}

The text highlights for a single query suggestion.

type suggestion_text_with_highlights = {
  1. highlights : suggestion_highlight list option;
    (*

    The beginning and end of the query suggestion text that should be highlighted.

    *)
  2. text : string option;
    (*

    The query suggestion text to display to the user.

    *)
}

Provides text and information about where to highlight the query suggestion text.

type suggestion_value = {
  1. text : suggestion_text_with_highlights option;
    (*

    The SuggestionTextWithHighlights structure that contains the query suggestion text and highlights.

    *)
}

The SuggestionTextWithHighlights structure information.

type suggestion_type =
  1. | DOCUMENT_ATTRIBUTES
  2. | QUERY
type document_attribute = {
  1. value : document_attribute_value;
    (*

    The value of the attribute.

    *)
  2. key : string;
    (*

    The identifier for the attribute.

    *)
}

A document attribute or metadata field. To create custom document attributes, see Custom attributes.

type source_document = {
  1. additional_attributes : document_attribute list option;
    (*

    The additional fields/attributes to include in the response. You can use additional fields to provide extra information in the response. Additional fields are not used to based suggestions on.

    *)
  2. suggestion_attributes : string list option;
    (*

    The document fields/attributes used for a query suggestion.

    *)
  3. document_id : string option;
    (*

    The identifier of the document used for a query suggestion.

    *)
}

The document ID and its fields/attributes that are used for a query suggestion, if document fields set to use for query suggestions.

type suggestion = {
  1. source_documents : source_document list option;
    (*

    The list of document IDs and their fields/attributes that are used for a single query suggestion, if document fields set to use for query suggestions.

    *)
  2. value : suggestion_value option;
    (*

    The value for the UUID (universally unique identifier) of a single query suggestion.

    The value is the text string of a suggestion.

    *)
  3. id : string option;
    (*

    The UUID (universally unique identifier) of a single query suggestion.

    *)
}

A single query suggestion.

type click_feedback = {
  1. click_time : float;
    (*

    The Unix timestamp when the result was clicked.

    *)
  2. result_id : string;
    (*

    The identifier of the search result that was clicked.

    *)
}

Gathers information about when a particular result was clicked by a user. Your application uses the SubmitFeedback API to provide click information.

type relevance_type =
  1. | NOT_RELEVANT
  2. | RELEVANT
type relevance_feedback = {
  1. relevance_value : relevance_type;
    (*

    Whether the document was relevant or not relevant to the search.

    *)
  2. result_id : string;
    (*

    The identifier of the search result that the user provided relevance feedback for.

    *)
}

Provides feedback on how relevant a document is to a search. Your application uses the SubmitFeedback API to provide relevance information.

type submit_feedback_request = {
  1. relevance_feedback_items : relevance_feedback list option;
    (*

    Provides Amazon Kendra with relevant or not relevant feedback for whether a particular item was relevant to the search.

    *)
  2. click_feedback_items : click_feedback list option;
    (*

    Tells Amazon Kendra that a particular search result link was chosen by the user.

    *)
  3. query_id : string;
    (*

    The identifier of the specific query for which you are submitting feedback. The query ID is returned in the response to the Query API.

    *)
  4. index_id : string;
    (*

    The identifier of the index that was queried.

    *)
}
type stop_data_source_sync_job_request = {
  1. index_id : string;
    (*

    The identifier of the index used with the data source connector.

    *)
  2. id : string;
    (*

    The identifier of the data source connector for which to stop the synchronization jobs.

    *)
}
type document_status =
  1. | UPDATE_FAILED
  2. | FAILED
  3. | UPDATED
  4. | INDEXED
  5. | PROCESSING
  6. | NOT_FOUND
type status = {
  1. failure_reason : string option;
    (*

    Provides detailed information about why the document couldn't be indexed. Use this information to correct the error before you resubmit the document for indexing.

    *)
  2. failure_code : string option;
    (*

    Indicates the source of the error.

    *)
  3. document_status : document_status option;
    (*

    The current status of a document.

    If the document was submitted for deletion, the status is NOT_FOUND after the document is deleted.

    *)
  4. document_id : string option;
    (*

    The identifier of the document.

    *)
}

Provides information about the status of documents submitted for indexing.

type start_data_source_sync_job_response = {
  1. execution_id : string option;
    (*

    Identifies a particular synchronization job.

    *)
}
type start_data_source_sync_job_request = {
  1. index_id : string;
    (*

    The identifier of the index used with the data source connector.

    *)
  2. id : string;
    (*

    The identifier of the data source connector to synchronize.

    *)
}
type resource_in_use_exception = {
  1. message : string option;
}

The resource you want to use is currently in use. Please check you have provided the correct resource and try again.

type spell_correction_configuration = {
  1. include_query_spell_check_suggestions : bool;
    (*

    TRUE to suggest spell corrections for queries.

    *)
}

Provides the configuration information for suggested query spell corrections.

Suggested spell corrections are based on words that appear in your indexed documents and how closely a corrected word matches a misspelled word.

This feature is designed with certain defaults or limits. For information on the current limits and how to request more support for some limits, see the Spell Checker documentation.

type correction = {
  1. corrected_term : string option;
    (*

    The string or text of a corrected misspelled word in a query.

    *)
  2. term : string option;
    (*

    The string or text of a misspelled word in a query.

    *)
  3. end_offset : int option;
    (*

    The zero-based location in the response string or text where the corrected word ends.

    *)
  4. begin_offset : int option;
    (*

    The zero-based location in the response string or text where the corrected word starts.

    *)
}

A corrected misspelled word in a query.

type spell_corrected_query = {
  1. corrections : correction list option;
    (*

    The corrected misspelled word or words in a query.

    *)
  2. suggested_query_text : string option;
    (*

    The query with the suggested spell corrections.

    *)
}

A query with suggested spell corrections.

type sort_order =
  1. | ASC
  2. | DESC
type sorting_configuration = {
  1. sort_order : sort_order;
    (*

    The order that the results should be returned in. In case of ties, the relevance assigned to the result by Amazon Kendra is used as the tie-breaker.

    *)
  2. document_attribute_key : string;
    (*

    The name of the document attribute used to sort the response. You can use any field that has the Sortable flag set to true.

    You can also sort by any of the following built-in attributes:

    • _category
    • _created_at
    • _last_updated_at
    • _version
    • _view_count
    *)
}

Specifies the document attribute to use to sort the response to a Amazon Kendra query. You can specify a single attribute for sorting. The attribute must have the Sortable flag set to true, otherwise Amazon Kendra returns an exception.

You can sort attributes of the following types.

  • Date value
  • Long value
  • String value

You can't sort attributes of the following type.

  • String list value
type server_side_encryption_configuration = {
  1. kms_key_id : string option;
    (*

    The identifier of the KMS key. Amazon Kendra doesn't support asymmetric keys.

    *)
}

Provides the identifier of the KMS key used to encrypt data indexed by Amazon Kendra. Amazon Kendra doesn't support asymmetric keys.

type score_confidence =
  1. | NOT_AVAILABLE
  2. | LOW
  3. | MEDIUM
  4. | HIGH
  5. | VERY_HIGH

Enumeration for query score confidence.

type score_attributes = {
  1. score_confidence : score_confidence option;
    (*

    A relative ranking for how relevant the response is to the query.

    *)
}

Provides a relative ranking that indicates how confident Amazon Kendra is that the response is relevant to the query.

type retrieve_result_item = {
  1. score_attributes : score_attributes option;
    (*

    The confidence score bucket for a retrieved passage result. The confidence bucket provides a relative ranking that indicates how confident Amazon Kendra is that the response is relevant to the query.

    *)
  2. document_attributes : document_attribute list option;
    (*

    An array of document fields/attributes assigned to a document in the search results. For example, the document author (_author) or the source URI (_source_uri) of the document.

    *)
  3. document_ur_i : string option;
    (*

    The URI of the original location of the document.

    *)
  4. content : string option;
    (*

    The contents of the relevant passage.

    *)
  5. document_title : string option;
    (*

    The title of the document.

    *)
  6. document_id : string option;
    (*

    The identifier of the document.

    *)
  7. id : string option;
    (*

    The identifier of the relevant passage result.

    *)
}

A single retrieved relevant passage result.

type retrieve_result = {
  1. result_items : retrieve_result_item list option;
    (*

    The results of the retrieved relevant passages for the search.

    *)
  2. query_id : string option;
    (*

    The identifier of query used for the search. You also use QueryId to identify the search when using the Submitfeedback API.

    *)
}
type attribute_filter = {
  1. less_than_or_equals : document_attribute option;
    (*

    Performs a less than or equals operation on document attributes/fields and their values. Use with the document attribute type Date or Long.

    *)
  2. less_than : document_attribute option;
    (*

    Performs a less than operation on document attributes/fields and their values. Use with the document attribute type Date or Long.

    *)
  3. greater_than_or_equals : document_attribute option;
    (*

    Performs a greater or equals than operation on document attributes/fields and their values. Use with the document attribute type Date or Long.

    *)
  4. greater_than : document_attribute option;
    (*

    Performs a greater than operation on document attributes/fields and their values. Use with the document attribute type Date or Long.

    *)
  5. contains_any : document_attribute option;
    (*

    Returns true when a document contains any of the specified document attributes/fields. This filter is only applicable to StringListValue.

    *)
  6. contains_all : document_attribute option;
    (*

    Returns true when a document contains all of the specified document attributes/fields. This filter is only applicable to StringListValue.

    *)
  7. equals_to : document_attribute option;
    (*

    Performs an equals operation on document attributes/fields and their values.

    *)
  8. not_filter : attribute_filter option;
    (*

    Performs a logical NOT operation on all filters that you specify.

    *)
  9. or_all_filters : attribute_filter list option;
    (*

    Performs a logical OR operation on all filters that you specify.

    *)
  10. and_all_filters : attribute_filter list option;
    (*

    Performs a logical AND operation on all filters that you specify.

    *)
}
type document_relevance_configuration = {
  1. relevance : relevance;
    (*

    Provides information for tuning the relevance of a field in a search. When a query includes terms that match the field, the results are given a boost in the response based on these tuning parameters.

    *)
  2. name : string;
    (*

    The name of the index field.

    *)
}

Overrides the document relevance properties of a custom index field.

type retrieve_request = {
  1. user_context : user_context option;
    (*

    The user context token or user and group information.

    *)
  2. page_size : int option;
    (*

    Sets the number of retrieved relevant passages that are returned in each page of results. The default page size is 10. The maximum number of results returned is 100. If you ask for more than 100 results, only 100 are returned.

    *)
  3. page_number : int option;
    (*

    Retrieved relevant passages are returned in pages the size of the PageSize parameter. By default, Amazon Kendra returns the first page of results. Use this parameter to get result pages after the first one.

    *)
  4. document_relevance_override_configurations : document_relevance_configuration list option;
    (*

    Overrides relevance tuning configurations of fields/attributes set at the index level.

    If you use this API to override the relevance tuning configured at the index level, but there is no relevance tuning configured at the index level, then Amazon Kendra does not apply any relevance tuning.

    If there is relevance tuning configured for fields at the index level, and you use this API to override only some of these fields, then for the fields you did not override, the importance is set to 1.

    *)
  5. requested_document_attributes : string list option;
    (*

    A list of document fields/attributes to include in the response. You can limit the response to include certain document fields. By default, all document fields are included in the response.

    *)
  6. attribute_filter : attribute_filter option;
    (*

    Filters search results by document fields/attributes. You can only provide one attribute filter; however, the AndAllFilters, NotFilter, and OrAllFilters parameters contain a list of other filters.

    The AttributeFilter parameter means you can create a set of filtering rules that a document must satisfy to be included in the query results.

    *)
  7. query_text : string;
    (*

    The input query text to retrieve relevant passages for the search. Amazon Kendra truncates queries at 30 token words, which excludes punctuation and stop words. Truncation still applies if you use Boolean or more advanced, complex queries. For example, Timeoff AND October AND Category:HR is counted as 3 tokens: timeoff, october, hr. For more information, see Searching with advanced query syntax in the Amazon Kendra Developer Guide.

    *)
  8. index_id : string;
    (*

    The identifier of the index to retrieve relevant passages for the search.

    *)
}
type resource_already_exist_exception = {
  1. message : string option;
}

The resource you want to use already exists. Please check you have provided the correct resource and try again.

type query_suggestions_status =
  1. | UPDATING
  2. | ACTIVE
type query_suggestions_block_list_status =
  1. | FAILED
  2. | ACTIVE_BUT_UPDATE_FAILED
  3. | UPDATING
  4. | DELETING
  5. | CREATING
  6. | ACTIVE
type query_suggestions_block_list_summary = {
  1. item_count : int option;
    (*

    The number of items in the block list file.

    *)
  2. updated_at : float option;
    (*

    The Unix timestamp when the block list was last updated.

    *)
  3. created_at : float option;
    (*

    The Unix timestamp when the block list was created.

    *)
  4. status : query_suggestions_block_list_status option;
    (*

    The status of the block list.

    *)
  5. name : string option;
    (*

    The name of the block list.

    *)
  6. id : string option;
    (*

    The identifier of a block list.

    *)
}

Summary information on a query suggestions block list.

This includes information on the block list ID, block list name, when the block list was created, when the block list was last updated, and the count of block words/phrases in the block list.

For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

type query_result_type =
  1. | ANSWER
  2. | QUESTION_ANSWER
  3. | DOCUMENT
type query_result_format =
  1. | TEXT
  2. | TABLE
type additional_result_attribute_value_type =
  1. | TEXT_WITH_HIGHLIGHTS_VALUE
type additional_result_attribute_value = {
  1. text_with_highlights_value : text_with_highlights option;
    (*

    The text associated with the attribute and information about the highlight to apply to the text.

    *)
}

An attribute returned with a document from a search.

type additional_result_attribute = {
  1. value : additional_result_attribute_value;
    (*

    An object that contains the attribute value.

    *)
  2. value_type : additional_result_attribute_value_type;
    (*

    The data type of the Value property.

    *)
  3. key : string;
    (*

    The key that identifies the attribute.

    *)
}

An attribute returned from an index query.

type expanded_result_item = {
  1. document_attributes : document_attribute list option;
    (*

    An array of document attributes assigned to a document in the search results. For example, the document author ("_author") or the source URI ("_source_uri") of the document.

    *)
  2. document_ur_i : string option;
    (*

    The URI of the original location of the document.

    *)
  3. document_excerpt : text_with_highlights option;
  4. document_title : text_with_highlights option;
  5. document_id : string option;
    (*

    The idenitifier of the document.

    *)
  6. id : string option;
    (*

    The identifier for the expanded result.

    *)
}

A single expanded result in a collapsed group of search results.

An expanded result item contains information about an expanded result document within a collapsed group of search results. This includes the original location of the document, a list of attributes assigned to the document, and relevant text from the document that satisfies the query.

type collapsed_result_detail = {
  1. expanded_results : expanded_result_item list option;
    (*

    A list of results in the collapsed group.

    *)
  2. document_attribute : document_attribute;
    (*

    The value of the document attribute that results are collapsed on.

    *)
}

Provides details about a collapsed group of search results.

type query_result_item = {
  1. collapsed_result_detail : collapsed_result_detail option;
    (*

    Provides details about a collapsed group of search results.

    *)
  2. table_excerpt : table_excerpt option;
    (*

    An excerpt from a table within a document.

    *)
  3. feedback_token : string option;
    (*

    A token that identifies a particular result from a particular query. Use this token to provide click-through feedback for the result. For more information, see Submitting feedback.

    *)
  4. score_attributes : score_attributes option;
    (*

    Indicates the confidence level of Amazon Kendra providing a relevant result for the query. Each result is placed into a bin that indicates the confidence, VERY_HIGH, HIGH, MEDIUM and LOW. You can use the score to determine if a response meets the confidence needed for your application.

    The field is only set to LOW when the Type field is set to DOCUMENT and Amazon Kendra is not confident that the result is relevant to the query.

    *)
  5. document_attributes : document_attribute list option;
    (*

    An array of document fields/attributes assigned to a document in the search results. For example, the document author (_author) or the source URI (_source_uri) of the document.

    *)
  6. document_ur_i : string option;
    (*

    The URI of the original location of the document.

    *)
  7. document_excerpt : text_with_highlights option;
    (*

    An extract of the text in the document. Contains information about highlighting the relevant terms in the excerpt.

    *)
  8. document_title : text_with_highlights option;
    (*

    The title of the document. Contains the text of the title and information for highlighting the relevant terms in the title.

    *)
  9. document_id : string option;
    (*

    The identifier for the document.

    *)
  10. additional_attributes : additional_result_attribute list option;
    (*

    One or more additional fields/attributes associated with the query result.

    *)
  11. format : query_result_format option;
    (*

    If the Type of document within the response is ANSWER, then it is either a TABLE answer or TEXT answer. If it's a table answer, a table excerpt is returned in TableExcerpt. If it's a text answer, a text excerpt is returned in DocumentExcerpt.

    *)
  12. type_ : query_result_type option;
    (*

    The type of document within the response. For example, a response could include a question-answer that's relevant to the query.

    *)
  13. id : string option;
    (*

    The unique identifier for the query result item id (Id) and the query result item document id (DocumentId) combined. The value of this field changes with every request, even when you have the same documents.

    *)
}

A single query result.

A query result contains information about a document returned by the query. This includes the original location of the document, a list of attributes assigned to the document, and relevant text from the document that satisfies the query.

type document_attribute_value_count_pair = {
  1. facet_results : facet_result list option;
    (*

    Contains the results of a document attribute/field that is a nested facet. A FacetResult contains the counts for each facet nested within a facet.

    For example, the document attribute or facet "Department" includes a value called "Engineering". In addition, the document attribute or facet "SubDepartment" includes the values "Frontend" and "Backend" for documents assigned to "Engineering". You can display nested facets in the search results so that documents can be searched not only by department but also by a sub department within a department. The counts for documents that belong to "Frontend" and "Backend" within "Engineering" are returned for a query.

    *)
  2. count : int option;
    (*

    The number of documents in the response that have the attribute/field value for the key.

    *)
  3. document_attribute_value : document_attribute_value option;
    (*

    The value of the attribute/field. For example, "HR".

    *)
}
and facet_result = {
  1. document_attribute_value_count_pairs : document_attribute_value_count_pair list option;
    (*

    An array of key/value pairs, where the key is the value of the attribute and the count is the number of documents that share the key value.

    *)
  2. document_attribute_value_type : document_attribute_value_type option;
    (*

    The data type of the facet value. This is the same as the type defined for the index field when it was created.

    *)
  3. document_attribute_key : string option;
    (*

    The key for the facet values. This is the same as the DocumentAttributeKey provided in the query.

    *)
}

A single featured result item. A featured result is displayed at the top of the search results page, placed above all other results for certain queries. If there's an exact match of a query, then certain documents are featured in the search results.

type query_result = {
  1. featured_results_items : featured_results_item list option;
    (*

    The list of featured result items. Featured results are displayed at the top of the search results page, placed above all other results for certain queries. If there's an exact match of a query, then certain documents are featured in the search results.

    *)
  2. spell_corrected_queries : spell_corrected_query list option;
    (*

    A list of information related to suggested spell corrections for a query.

    *)
  3. warnings : warning list option;
    (*

    A list of warning codes and their messages on problems with your query.

    Amazon Kendra currently only supports one type of warning, which is a warning on invalid syntax used in the query. For examples of invalid query syntax, see Searching with advanced query syntax.

    *)
  4. total_number_of_results : int option;
    (*

    The total number of items found by the search. However, you can only retrieve up to 100 items. For example, if the search found 192 items, you can only retrieve the first 100 of the items.

    *)
  5. facet_results : facet_result list option;
    (*

    Contains the facet results. A FacetResult contains the counts for each field/attribute key that was specified in the Facets input parameter.

    *)
  6. result_items : query_result_item list option;
    (*

    The results of the search.

    *)
  7. query_id : string option;
    (*

    The identifier for the search. You also use QueryId to identify the search when using the SubmitFeedback API.

    *)
}
type facet = {
  1. max_results : int option;
    (*

    Maximum number of facet values per facet. The default is 10. You can use this to limit the number of facet values to less than 10. If you want to increase the default, contact Support.

    *)
  2. facets : facet list option;
    (*

    An array of document attributes that are nested facets within a facet.

    For example, the document attribute or facet "Department" includes a value called "Engineering". In addition, the document attribute or facet "SubDepartment" includes the values "Frontend" and "Backend" for documents assigned to "Engineering". You can display nested facets in the search results so that documents can be searched not only by department but also by a sub department within a department. This helps your users further narrow their search.

    You can only have one nested facet within a facet. If you want to increase this limit, contact Support.

    *)
  3. document_attribute_key : string option;
    (*

    The unique key for the document attribute.

    *)
}
type missing_attribute_key_strategy =
  1. | EXPAND
  2. | COLLAPSE
  3. | IGNORE
type expand_configuration = {
  1. max_expanded_results_per_item : int option;
    (*

    The number of expanded results to show per collapsed primary document. For instance, if you set this value to 3, then at most 3 results per collapsed group will be displayed.

    *)
  2. max_result_items_to_expand : int option;
    (*

    The number of collapsed search result groups to expand. If you set this value to 10, for example, only the first 10 out of 100 result groups will have expand functionality.

    *)
}

Specifies the configuration information needed to customize how collapsed search result groups expand.

type collapse_configuration = {
  1. expand_configuration : expand_configuration option;
    (*

    Provides configuration information to customize expansion options for a collapsed group.

    *)
  2. expand : bool option;
    (*

    Specifies whether to expand the collapsed results.

    *)
  3. missing_attribute_key_strategy : missing_attribute_key_strategy option;
    (*

    Specifies the behavior for documents without a value for the collapse attribute.

    Amazon Kendra offers three customization options:

    • Choose to COLLAPSE all documents with null or missing values in one group. This is the default configuration.
    • Choose to IGNORE documents with null or missing values. Ignored documents will not appear in query results.
    • Choose to EXPAND each document with a null or missing value into a group of its own.
    *)
  4. sorting_configurations : sorting_configuration list option;
    (*

    A prioritized list of document attributes/fields that determine the primary document among those in a collapsed group.

    *)
  5. document_attribute_key : string;
    (*

    The document attribute used to group search results. You can use any attribute that has the Sortable flag set to true. You can also sort by any of the following built-in attributes:"_category","_created_at", "_last_updated_at", "_version", "_view_count".

    *)
}

Specifies how to group results by document attribute value, and how to display them collapsed/expanded under a designated primary document for each group.

type query_request = {
  1. collapse_configuration : collapse_configuration option;
    (*

    Provides configuration to determine how to group results by document attribute value, and how to display them (collapsed or expanded) under a designated primary document for each group.

    *)
  2. spell_correction_configuration : spell_correction_configuration option;
    (*

    Enables suggested spell corrections for queries.

    *)
  3. visitor_id : string option;
    (*

    Provides an identifier for a specific user. The VisitorId should be a unique identifier, such as a GUID. Don't use personally identifiable information, such as the user's email address, as the VisitorId.

    *)
  4. user_context : user_context option;
    (*

    The user context token or user and group information.

    *)
  5. sorting_configurations : sorting_configuration list option;
    (*

    Provides configuration information to determine how the results of a query are sorted.

    You can set upto 3 fields that Amazon Kendra should sort the results on, and specify whether the results should be sorted in ascending or descending order. The sort field quota can be increased.

    If you don't provide a sorting configuration, the results are sorted by the relevance that Amazon Kendra determines for the result. In the case of ties in sorting the results, the results are sorted by relevance.

    *)
  6. sorting_configuration : sorting_configuration option;
    (*

    Provides information that determines how the results of the query are sorted. You can set the field that Amazon Kendra should sort the results on, and specify whether the results should be sorted in ascending or descending order. In the case of ties in sorting the results, the results are sorted by relevance.

    If you don't provide sorting configuration, the results are sorted by the relevance that Amazon Kendra determines for the result.

    *)
  7. page_size : int option;
    (*

    Sets the number of results that are returned in each page of results. The default page size is 10. The maximum number of results returned is 100. If you ask for more than 100 results, only 100 are returned.

    *)
  8. page_number : int option;
    (*

    Query results are returned in pages the size of the PageSize parameter. By default, Amazon Kendra returns the first page of results. Use this parameter to get result pages after the first one.

    *)
  9. document_relevance_override_configurations : document_relevance_configuration list option;
    (*

    Overrides relevance tuning configurations of fields/attributes set at the index level.

    If you use this API to override the relevance tuning configured at the index level, but there is no relevance tuning configured at the index level, then Amazon Kendra does not apply any relevance tuning.

    If there is relevance tuning configured for fields at the index level, and you use this API to override only some of these fields, then for the fields you did not override, the importance is set to 1.

    *)
  10. query_result_type_filter : query_result_type option;
    (*

    Sets the type of query result or response. Only results for the specified type are returned.

    *)
  11. requested_document_attributes : string list option;
    (*

    An array of document fields/attributes to include in the response. You can limit the response to include certain document fields. By default, all document attributes are included in the response.

    *)
  12. facets : facet list option;
    (*

    An array of documents fields/attributes for faceted search. Amazon Kendra returns a count for each field key specified. This helps your users narrow their search.

    *)
  13. attribute_filter : attribute_filter option;
    (*

    Filters search results by document fields/attributes. You can only provide one attribute filter; however, the AndAllFilters, NotFilter, and OrAllFilters parameters contain a list of other filters.

    The AttributeFilter parameter means you can create a set of filtering rules that a document must satisfy to be included in the query results.

    *)
  14. query_text : string option;
    (*

    The input query text for the search. Amazon Kendra truncates queries at 30 token words, which excludes punctuation and stop words. Truncation still applies if you use Boolean or more advanced, complex queries. For example, Timeoff AND October AND Category:HR is counted as 3 tokens: timeoff, october, hr. For more information, see Searching with advanced query syntax in the Amazon Kendra Developer Guide.

    *)
  15. index_id : string;
    (*

    The identifier of the index for the search.

    *)
}
type member_group = {
  1. data_source_id : string option;
    (*

    The identifier of the data source for the sub group you want to map to a group.

    *)
  2. group_id : string;
    (*

    The identifier of the sub group you want to map to a group.

    *)
}

The sub groups that belong to a group.

type member_user = {
  1. user_id : string;
    (*

    The identifier of the user you want to map to a group.

    *)
}

The users that belong to a group.

type group_members = {
  1. s3_pathfor_group_members : s3_path option;
    (*

    If you have more than 1000 users and/or sub groups for a single group, you need to provide the path to the S3 file that lists your users and sub groups for a group. Your sub groups can contain more than 1000 users, but the list of sub groups that belong to a group (and/or users) must be no more than 1000.

    You can download this example S3 file that uses the correct format for listing group members. Note, dataSourceId is optional. The value of type for a group is always GROUP and for a user it is always USER.

    *)
  2. member_users : member_user list option;
    (*

    A list of users that belong to a group. For example, a list of interns all belong to the "Interns" group.

    *)
  3. member_groups : member_group list option;
    (*

    A list of sub groups that belong to a group. For example, the sub groups "Research", "Engineering", and "Sales and Marketing" all belong to the group "Company".

    *)
}

A list of users or sub groups that belong to a group. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

type put_principal_mapping_request = {
  1. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of a role that has access to the S3 file that contains your list of users or sub groups that belong to a group.

    For more information, see IAM roles for Amazon Kendra.

    *)
  2. ordering_id : int option;
    (*

    The timestamp identifier you specify to ensure Amazon Kendra does not override the latest PUT action with previous actions. The highest number ID, which is the ordering ID, is the latest action you want to process and apply on top of other actions with lower number IDs. This prevents previous actions with lower number IDs from possibly overriding the latest action.

    The ordering ID can be the Unix time of the last update you made to a group members list. You would then provide this list when calling PutPrincipalMapping. This ensures your PUT action for that updated group with the latest members list doesn't get overwritten by earlier PUT actions for the same group which are yet to be processed.

    The default ordering ID is the current Unix time in milliseconds that the action was received by Amazon Kendra.

    *)
  3. group_members : group_members;
    (*

    The list that contains your users or sub groups that belong the same group.

    For example, the group "Company" includes the user "CEO" and the sub groups "Research", "Engineering", and "Sales and Marketing".

    If you have more than 1000 users and/or sub groups for a single group, you need to provide the path to the S3 file that lists your users and sub groups for a group. Your sub groups can contain more than 1000 users, but the list of sub groups that belong to a group (and/or users) must be no more than 1000.

    *)
  4. group_id : string;
    (*

    The identifier of the group you want to map its users to.

    *)
  5. data_source_id : string option;
    (*

    The identifier of the data source you want to map users to their groups.

    This is useful if a group is tied to multiple data sources, but you only want the group to access documents of a certain data source. For example, the groups "Research", "Engineering", and "Sales and Marketing" are all tied to the company's documents stored in the data sources Confluence and Salesforce. However, "Sales and Marketing" team only needs access to customer-related documents stored in Salesforce.

    *)
  6. index_id : string;
    (*

    The identifier of the index you want to map users to their groups.

    *)
}
type principal_mapping_status =
  1. | DELETED
  2. | DELETING
  3. | PROCESSING
  4. | SUCCEEDED
  5. | FAILED
type persona =
  1. | VIEWER
  2. | OWNER
type personas_summary = {
  1. updated_at : float option;
    (*

    The Unix timestamp when the summary information was last updated.

    *)
  2. created_at : float option;
    (*

    The Unix timestamp when the summary information was created.

    *)
  3. persona : persona option;
    (*

    The persona that defines the specific permissions of the user or group in your IAM Identity Center identity source. The available personas or access roles are Owner and Viewer. For more information on these personas, see Providing access to your search page.

    *)
  4. entity_id : string option;
    (*

    The identifier of a user or group in your IAM Identity Center identity source. For example, a user ID could be an email.

    *)
}

Summary information for users or groups in your IAM Identity Center identity source. This applies to users and groups with specific permissions that define their level of access to your Amazon Kendra experience. You can create an Amazon Kendra experience such as a search application. For more information on creating a search application experience, see Building a search experience with no code.

type metric_type =
  1. | TREND_QUERY_DOC_METRICS
  2. | AGG_QUERY_DOC_METRICS
  3. | DOCS_BY_CLICK_COUNT
  4. | QUERIES_BY_ZERO_RESULT_RATE
  5. | QUERIES_BY_ZERO_CLICK_RATE
  6. | QUERIES_BY_COUNT
type list_thesauri_response = {
  1. thesaurus_summary_items : thesaurus_summary list option;
    (*

    An array of summary information for a thesaurus or multiple thesauri.

    *)
  2. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of thesauri.

    *)
}
type list_thesauri_request = {
  1. max_results : int option;
    (*

    The maximum number of thesauri to return.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of thesauri (ThesaurusSummaryItems).

    *)
  3. index_id : string;
    (*

    The identifier of the index with one or more thesauri.

    *)
}
type list_tags_for_resource_response = {
  1. tags : tag list option;
    (*

    A list of tags associated with the index, FAQ, or data source.

    *)
}
type list_tags_for_resource_request = {
  1. resource_ar_n : string;
    (*

    The Amazon Resource Name (ARN) of the index, FAQ, or data source to get a list of tags for.

    *)
}
type list_query_suggestions_block_lists_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of block lists.

    *)
  2. block_list_summary_items : query_suggestions_block_list_summary list option;
    (*

    Summary items for a block list.

    This includes summary items on the block list ID, block list name, when the block list was created, when the block list was last updated, and the count of block words/phrases in the block list.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

    *)
}
type list_query_suggestions_block_lists_request = {
  1. max_results : int option;
    (*

    The maximum number of block lists to return.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of block lists (BlockListSummaryItems).

    *)
  3. index_id : string;
    (*

    The identifier of the index for a list of all block lists that exist for that index.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

    *)
}
type group_summary = {
  1. ordering_id : int option;
    (*

    The timestamp identifier used for the latest PUT or DELETE action.

    *)
  2. group_id : string option;
    (*

    The identifier of the group you want group summary information on.

    *)
}

Summary information for groups.

type index_edition =
  1. | ENTERPRISE_EDITION
  2. | DEVELOPER_EDITION
type index_status =
  1. | SYSTEM_UPDATING
  2. | UPDATING
  3. | FAILED
  4. | DELETING
  5. | ACTIVE
  6. | CREATING
type index_configuration_summary = {
  1. status : index_status;
    (*

    The current status of the index. When the status is ACTIVE, the index is ready to search.

    *)
  2. updated_at : float;
    (*

    The Unix timestamp when the index was last updated.

    *)
  3. created_at : float;
    (*

    The Unix timestamp when the index was created.

    *)
  4. edition : index_edition option;
    (*

    Indicates whether the index is a Enterprise Edition index or a Developer Edition index.

    *)
  5. id : string option;
    (*

    A identifier for the index. Use this to identify the index when you are using APIs such as Query, DescribeIndex, UpdateIndex, and DeleteIndex.

    *)
  6. name : string option;
    (*

    The name of the index.

    *)
}

Summary information on the configuration of an index.

type list_indices_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of indexes.

    *)
  2. index_configuration_summary_items : index_configuration_summary list option;
    (*

    An array of summary information on the configuration of one or more indexes.

    *)
}
type list_indices_request = {
  1. max_results : int option;
    (*

    The maximum number of indices to return.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of indexes.

    *)
}
type list_groups_older_than_ordering_id_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of groups that are mapped to users before a given ordering or timestamp identifier.

    *)
  2. groups_summaries : group_summary list option;
    (*

    Summary information for list of groups that are mapped to users before a given ordering or timestamp identifier.

    *)
}
type list_groups_older_than_ordering_id_request = {
  1. max_results : int option;
    (*

    The maximum number of returned groups that are mapped to users before a given ordering or timestamp identifier.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of groups that are mapped to users before a given ordering or timestamp identifier.

    *)
  3. ordering_id : int;
    (*

    The timestamp identifier used for the latest PUT or DELETE action for mapping users to their groups.

    *)
  4. data_source_id : string option;
    (*

    The identifier of the data source for getting a list of groups mapped to users before a given ordering timestamp identifier.

    *)
  5. index_id : string;
    (*

    The identifier of the index for getting a list of groups mapped to users before a given ordering or timestamp identifier.

    *)
}

Summary information for a set of featured results. Featured results are placed above all other results for certain queries. If there's an exact match of a query, then one or more specific documents are featured in the search results.

type faq_status =
  1. | FAILED
  2. | DELETING
  3. | ACTIVE
  4. | UPDATING
  5. | CREATING
type faq_file_format =
  1. | JSON
  2. | CSV_WITH_HEADER
  3. | CSV
type faq_summary = {
  1. language_code : string option;
    (*

    The code for a language. This shows a supported language for the FAQ document as part of the summary information for FAQs. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    *)
  2. file_format : faq_file_format option;
    (*

    The file type used to create the FAQ.

    *)
  3. updated_at : float option;
    (*

    The Unix timestamp when the FAQ was last updated.

    *)
  4. created_at : float option;
    (*

    The Unix timestamp when the FAQ was created.

    *)
  5. status : faq_status option;
    (*

    The current status of the FAQ. When the status is ACTIVE the FAQ is ready for use.

    *)
  6. name : string option;
    (*

    The name that you assigned the FAQ when you created or updated the FAQ.

    *)
  7. id : string option;
    (*

    The identifier of the FAQ.

    *)
}

Summary information for frequently asked questions and answers included in an index.

type list_faqs_response = {
  1. faq_summary_items : faq_summary list option;
    (*

    information about the FAQs associated with the specified index.

    *)
  2. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of FAQs.

    *)
}
type list_faqs_request = {
  1. max_results : int option;
    (*

    The maximum number of FAQs to return in the response. If there are fewer results in the list, this response contains only the actual results.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of FAQs.

    *)
  3. index_id : string;
    (*

    The index that contains the FAQ lists.

    *)
}
type experience_status =
  1. | FAILED
  2. | DELETING
  3. | ACTIVE
  4. | CREATING
type endpoint_type =
  1. | HOME
type experience_endpoint = {
  1. endpoint : string option;
    (*

    The endpoint of your Amazon Kendra experience.

    *)
  2. endpoint_type : endpoint_type option;
    (*

    The type of endpoint for your Amazon Kendra experience. The type currently available is HOME, which is a unique and fully hosted URL to the home page of your Amazon Kendra experience.

    *)
}

Provides the configuration information for the endpoint for your Amazon Kendra experience.

type experiences_summary = {
  1. endpoints : experience_endpoint list option;
    (*

    The endpoint URLs for your Amazon Kendra experiences. The URLs are unique and fully hosted by Amazon Web Services.

    *)
  2. status : experience_status option;
    (*

    The processing status of your Amazon Kendra experience.

    *)
  3. created_at : float option;
    (*

    The Unix timestamp when your Amazon Kendra experience was created.

    *)
  4. id : string option;
    (*

    The identifier of your Amazon Kendra experience.

    *)
  5. name : string option;
    (*

    The name of your Amazon Kendra experience.

    *)
}

Summary information for your Amazon Kendra experience. You can create an Amazon Kendra experience such as a search application. For more information on creating a search application experience, see Building a search experience with no code.

type list_experiences_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of Amazon Kendra experiences.

    *)
  2. summary_items : experiences_summary list option;
    (*

    An array of summary information for one or more Amazon Kendra experiences.

    *)
}
type list_experiences_request = {
  1. max_results : int option;
    (*

    The maximum number of returned Amazon Kendra experiences.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of Amazon Kendra experiences.

    *)
  3. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
}
type entity_type =
  1. | GROUP
  2. | USER
type entity_display_data = {
  1. last_name : string option;
    (*

    The last name of the user.

    *)
  2. first_name : string option;
    (*

    The first name of the user.

    *)
  3. identified_user_name : string option;
    (*

    The user name of the user.

    *)
  4. group_name : string option;
    (*

    The name of the group.

    *)
  5. user_name : string option;
    (*

    The name of the user.

    *)
}

Information about the user entity.

type experience_entities_summary = {
  1. display_data : entity_display_data option;
    (*

    Information about the user entity.

    *)
  2. entity_type : entity_type option;
    (*

    Shows the type as User or Group.

    *)
  3. entity_id : string option;
    (*

    The identifier of a user or group in your IAM Identity Center identity source. For example, a user ID could be an email.

    *)
}

Summary information for users or groups in your IAM Identity Center identity source with granted access to your Amazon Kendra experience. You can create an Amazon Kendra experience such as a search application. For more information on creating a search application experience, see Building a search experience with no code.

type list_experience_entities_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of users or groups.

    *)
  2. summary_items : experience_entities_summary list option;
    (*

    An array of summary information for one or more users or groups.

    *)
}
type list_experience_entities_request = {
  1. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of users or groups.

    *)
  2. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  3. id : string;
    (*

    The identifier of your Amazon Kendra experience.

    *)
}
type list_entity_personas_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of users or groups.

    *)
  2. summary_items : personas_summary list option;
    (*

    An array of summary information for one or more users or groups.

    *)
}
type list_entity_personas_request = {
  1. max_results : int option;
    (*

    The maximum number of returned users or groups.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of users or groups.

    *)
  3. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  4. id : string;
    (*

    The identifier of your Amazon Kendra experience.

    *)
}
type data_source_type =
  1. | TEMPLATE
  2. | ALFRESCO
  3. | GITHUB
  4. | JIRA
  5. | QUIP
  6. | BOX
  7. | SLACK
  8. | FSX
  9. | WORKDOCS
  10. | WEBCRAWLER
  11. | GOOGLEDRIVE
  12. | CONFLUENCE
  13. | CUSTOM
  14. | SERVICENOW
  15. | ONEDRIVE
  16. | SALESFORCE
  17. | DATABASE
  18. | SHAREPOINT
  19. | S3
type data_source_status =
  1. | ACTIVE
  2. | UPDATING
  3. | FAILED
  4. | DELETING
  5. | CREATING
type data_source_summary = {
  1. language_code : string option;
    (*

    The code for a language. This shows a supported language for all documents in the data source. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    *)
  2. status : data_source_status option;
    (*

    The status of the data source. When the status is ACTIVE the data source is ready to use.

    *)
  3. updated_at : float option;
    (*

    The Unix timestamp when the data source connector was last updated.

    *)
  4. created_at : float option;
    (*

    The Unix timestamp when the data source connector was created.

    *)
  5. type_ : data_source_type option;
    (*

    The type of the data source.

    *)
  6. id : string option;
    (*

    The identifier for the data source.

    *)
  7. name : string option;
    (*

    The name of the data source.

    *)
}

Summary information for a Amazon Kendra data source.

type list_data_sources_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of data source connectors.

    *)
  2. summary_items : data_source_summary list option;
    (*

    An array of summary information for one or more data source connector.

    *)
}
type list_data_sources_request = {
  1. max_results : int option;
    (*

    The maximum number of data source connectors to return.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of data source connectors.

    *)
  3. index_id : string;
    (*

    The identifier of the index used with one or more data source connectors.

    *)
}
type data_source_sync_job_status =
  1. | SYNCING_INDEXING
  2. | ABORTED
  3. | STOPPING
  4. | INCOMPLETE
  5. | SYNCING
  6. | SUCCEEDED
  7. | FAILED
type error_code =
  1. | INVALID_REQUEST
  2. | INTERNAL_ERROR
type data_source_sync_job_metrics = {
  1. documents_scanned : string option;
    (*

    The current number of documents crawled by the current sync job in the data source.

    *)
  2. documents_failed : string option;
    (*

    The number of documents that failed to sync from the data source up to now in the data source sync run.

    *)
  3. documents_deleted : string option;
    (*

    The number of documents deleted from the data source up to now in the data source sync run.

    *)
  4. documents_modified : string option;
    (*

    The number of documents modified in the data source up to now in the data source sync run.

    *)
  5. documents_added : string option;
    (*

    The number of documents added from the data source up to now in the data source sync.

    *)
}

Maps a batch delete document request to a specific data source sync job. This is optional and should only be supplied when documents are deleted by a data source connector.

type data_source_sync_job = {
  1. metrics : data_source_sync_job_metrics option;
    (*

    Maps a batch delete document request to a specific data source sync job. This is optional and should only be supplied when documents are deleted by a data source connector.

    *)
  2. data_source_error_code : string option;
    (*

    If the reason that the synchronization failed is due to an error with the underlying data source, this field contains a code that identifies the error.

    *)
  3. error_code : error_code option;
    (*

    If the Status field is set to FAILED, the ErrorCode field indicates the reason the synchronization failed.

    *)
  4. error_message : string option;
    (*

    If the Status field is set to ERROR, the ErrorMessage field contains a description of the error that caused the synchronization to fail.

    *)
  5. status : data_source_sync_job_status option;
    (*

    The execution status of the synchronization job. When the Status field is set to SUCCEEDED, the synchronization job is done. If the status code is set to FAILED, the ErrorCode and ErrorMessage fields give you the reason for the failure.

    *)
  6. end_time : float option;
    (*

    The Unix timestamp when the synchronization job completed.

    *)
  7. start_time : float option;
    (*

    The Unix timestamp when the synchronization job started.

    *)
  8. execution_id : string option;
    (*

    A identifier for the synchronization job.

    *)
}

Provides information about a data source synchronization job.

type list_data_source_sync_jobs_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of jobs.

    *)
  2. history : data_source_sync_job list option;
    (*

    A history of synchronization jobs for the data source connector.

    *)
}
type list_data_source_sync_jobs_request = {
  1. status_filter : data_source_sync_job_status option;
    (*

    Only returns synchronization jobs with the Status field equal to the specified status.

    *)
  2. start_time_filter : time_range option;
    (*

    When specified, the synchronization jobs returned in the list are limited to jobs between the specified dates.

    *)
  3. max_results : int option;
    (*

    The maximum number of synchronization jobs to return in the response. If there are fewer results in the list, this response contains only the actual results.

    *)
  4. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of jobs.

    *)
  5. index_id : string;
    (*

    The identifier of the index used with the data source connector.

    *)
  6. id : string;
    (*

    The identifier of the data source connector.

    *)
}
type access_control_configuration_summary = {
  1. id : string;
    (*

    The identifier of the access control configuration.

    *)
}

Summary information on an access control configuration that you created for your documents in an index.

type list_access_control_configurations_response = {
  1. access_control_configurations : access_control_configuration_summary list;
    (*

    The details of your access control configurations.

    *)
  2. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token, which you can use in the subsequent request to retrieve the next set of access control configurations.

    *)
}
type list_access_control_configurations_request = {
  1. max_results : int option;
    (*

    The maximum number of access control configurations to return.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there's more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of access control configurations.

    *)
  3. index_id : string;
    (*

    The identifier of the index for the access control configuration.

    *)
}
type invalid_request_exception = {
  1. message : string option;
}

The input to the request is not valid. Please provide the correct input and try again.

type interval =
  1. | TWO_MONTHS_AGO
  2. | ONE_MONTH_AGO
  3. | TWO_WEEKS_AGO
  4. | ONE_WEEK_AGO
  5. | THIS_WEEK
  6. | THIS_MONTH
type faq_statistics = {
  1. indexed_question_answers_count : int;
    (*

    The total number of FAQ questions and answers contained in the index.

    *)
}

Provides statistical information about the FAQ questions and answers contained in an index.

type index_statistics = {
  1. text_document_statistics : text_document_statistics;
    (*

    The number of text documents indexed.

    *)
  2. faq_statistics : faq_statistics;
    (*

    The number of question and answer topics in the index.

    *)
}

Provides information about the number of documents and the number of questions and answers in an index.

type group_ordering_id_summary = {
  1. failure_reason : string option;
    (*

    The reason an action could not be processed. An action can be a PUT or DELETE action for mapping users to their groups.

    *)
  2. ordering_id : int option;
    (*

    The order in which actions should complete processing. An action can be a PUT or DELETE action for mapping users to their groups.

    *)
  3. received_at : float option;
    (*

    The Unix timestamp when an action was received by Amazon Kendra. An action can be a PUT or DELETE action for mapping users to their groups.

    *)
  4. last_updated_at : float option;
    (*

    The Unix timestamp when an action was last updated. An action can be a PUT or DELETE action for mapping users to their groups.

    *)
  5. status : principal_mapping_status option;
    (*

    The current processing status of actions for mapping users to their groups. The status can be either PROCESSING, SUCCEEDED, DELETING, DELETED, or FAILED.

    *)
}

Summary information on the processing of PUT and DELETE actions for mapping users to their groups.

type get_snapshots_response = {
  1. next_token : string option;
    (*

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of search metrics data.

    *)
  2. snapshots_data : string list list option;
    (*

    The search metrics data. The data returned depends on the metric type you requested.

    *)
  3. snapshots_data_header : string list option;
    (*

    The column headers for the search metrics data.

    *)
  4. snap_shot_time_filter : time_range option;
    (*

    The Unix timestamp for the beginning and end of the time window for the search metrics data.

    *)
}
type get_snapshots_request = {
  1. max_results : int option;
    (*

    The maximum number of returned data for the metric.

    *)
  2. next_token : string option;
    (*

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of search metrics data.

    *)
  3. metric_type : metric_type;
    (*

    The metric you want to retrieve. You can specify only one metric per call.

    For more information about the metrics you can view, see Gaining insights with search analytics.

    *)
  4. interval : interval;
    (*

    The time interval or time window to get search metrics data. The time interval uses the time zone of your index. You can view data in the following time windows:

    • THIS_WEEK: The current week, starting on the Sunday and ending on the day before the current date.
    • ONE_WEEK_AGO: The previous week, starting on the Sunday and ending on the following Saturday.
    • TWO_WEEKS_AGO: The week before the previous week, starting on the Sunday and ending on the following Saturday.
    • THIS_MONTH: The current month, starting on the first day of the month and ending on the day before the current date.
    • ONE_MONTH_AGO: The previous month, starting on the first day of the month and ending on the last day of the month.
    • TWO_MONTHS_AGO: The month before the previous month, starting on the first day of the month and ending on last day of the month.
    *)
  5. index_id : string;
    (*

    The identifier of the index to get search metrics data.

    *)
}
type get_query_suggestions_response = {
  1. suggestions : suggestion list option;
    (*

    A list of query suggestions for an index.

    *)
  2. query_suggestions_id : string option;
    (*

    The identifier for a list of query suggestions for an index.

    *)
}
type attribute_suggestions_get_config = {
  1. user_context : user_context option;
    (*

    Applies user context filtering so that only users who are given access to certain documents see these document in their search results.

    *)
  2. attribute_filter : attribute_filter option;
    (*

    Filters the search results based on document fields/attributes.

    *)
  3. additional_response_attributes : string list option;
    (*

    The list of additional document field/attribute keys or field names to include in the response. You can use additional fields to provide extra information in the response. Additional fields are not used to based suggestions on.

    *)
  4. suggestion_attributes : string list option;
    (*

    The list of document field/attribute keys or field names to use for query suggestions. If the content within any of the fields match what your user starts typing as their query, then the field content is returned as a query suggestion.

    *)
}

Provides the configuration information for the document fields/attributes that you want to base query suggestions on.

type get_query_suggestions_request = {
  1. attribute_suggestions_config : attribute_suggestions_get_config option;
    (*

    Configuration information for the document fields/attributes that you want to base query suggestions on.

    *)
  2. suggestion_types : suggestion_type list option;
    (*

    The suggestions type to base query suggestions on. The suggestion types are query history or document fields/attributes. You can set one type or the other.

    If you set query history as your suggestions type, Amazon Kendra suggests queries relevant to your users based on popular queries in the query history.

    If you set document fields/attributes as your suggestions type, Amazon Kendra suggests queries relevant to your users based on the contents of document fields.

    *)
  3. max_suggestions_count : int option;
    (*

    The maximum number of query suggestions you want to show to your users.

    *)
  4. query_text : string;
    (*

    The text of a user's query to generate query suggestions.

    A query is suggested if the query prefix matches what a user starts to type as their query.

    Amazon Kendra does not show any suggestions if a user types fewer than two characters or more than 60 characters. A query must also have at least one search result and contain at least one word of more than four characters.

    *)
  5. index_id : string;
    (*

    The identifier of the index you want to get query suggestions from.

    *)
}

A featured document with its metadata information. This document is displayed at the top of the search results page, placed above all other results for certain queries. If there's an exact match of a query, then the document is featured in the search results.

A document ID doesn't exist but you have specified as a featured document. Amazon Kendra cannot feature the document if it doesn't exist in the index. You can check the status of a document and its ID or check for documents with status errors using the BatchGetDocumentStatus API.

type failed_entity = {
  1. error_message : string option;
    (*

    The reason the user or group in your IAM Identity Center identity source failed to properly configure with your Amazon Kendra experience.

    *)
  2. entity_id : string option;
    (*

    The identifier of the user or group in your IAM Identity Center identity source. For example, a user ID could be an email.

    *)
}

Information on the users or groups in your IAM Identity Center identity source that failed to properly configure with your Amazon Kendra experience.

type entity_persona_configuration = {
  1. persona : persona;
    (*

    The persona that defines the specific permissions of the user or group in your IAM Identity Center identity source. The available personas or access roles are Owner and Viewer. For more information on these personas, see Providing access to your search page.

    *)
  2. entity_id : string;
    (*

    The identifier of a user or group in your IAM Identity Center identity source. For example, a user ID could be an email.

    *)
}

Provides the configuration information for users or groups in your IAM Identity Center identity source for access to your Amazon Kendra experience. Specific permissions are defined for each user or group once they are granted access to your Amazon Kendra experience.

type entity_configuration = {
  1. entity_type : entity_type;
    (*

    Specifies whether you are configuring a User or a Group.

    *)
  2. entity_id : string;
    (*

    The identifier of a user or group in your IAM Identity Center identity source. For example, a user ID could be an email.

    *)
}

Provides the configuration information for users or groups in your IAM Identity Center identity source to grant access your Amazon Kendra experience.

type content_type =
  1. | MD
  2. | JSON
  3. | CSV
  4. | MS_EXCEL
  5. | XSLT
  6. | XML
  7. | RTF
  8. | PPT
  9. | PLAIN_TEXT
  10. | MS_WORD
  11. | HTML
  12. | PDF
type document = {
  1. access_control_configuration_id : string option;
    (*

    The identifier of the access control configuration that you want to apply to the document.

    *)
  2. content_type : content_type option;
    (*

    The file type of the document in the Blob field.

    If you want to index snippets or subsets of HTML documents instead of the entirety of the HTML documents, you must add the HTML start and closing tags (content) around the content.

    *)
  3. hierarchical_access_control_list : hierarchical_principal list option;
    (*

    The list of principal lists that define the hierarchy for which documents users should have access to.

    *)
  4. access_control_list : principal list option;
    (*

    Information on principals (users and/or groups) and which documents they should have access to. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    *)
  5. attributes : document_attribute list option;
    (*

    Custom attributes to apply to the document. Use the custom attributes to provide additional information for searching, to provide facets for refining searches, and to provide additional information in the query response.

    For example, 'DataSourceId' and 'DataSourceSyncJobId' are custom attributes that provide information on the synchronization of documents running on a data source. Note, 'DataSourceSyncJobId' could be an optional custom attribute as Amazon Kendra will use the ID of a running sync job.

    *)
  6. s3_path : s3_path option;
  7. blob : bytes option;
    (*

    The contents of the document.

    Documents passed to the Blob parameter must be base64 encoded. Your code might not need to encode the document file bytes if you're using an Amazon Web Services SDK to call Amazon Kendra APIs. If you are calling the Amazon Kendra endpoint directly using REST, you must base64 encode the contents before sending.

    *)
  8. title : string option;
    (*

    The title of the document.

    *)
  9. id : string;
    (*

    A identifier of the document in the index.

    Note, each document ID must be unique per index. You cannot create a data source to index your documents with their unique IDs and then use the BatchPutDocument API to index the same documents, or vice versa. You can delete a data source and then use the BatchPutDocument API to index the same documents, or vice versa.

    *)
}

A document in an index.

type document_info = {
  1. attributes : document_attribute list option;
    (*

    Attributes that identify a specific version of a document to check.

    The only valid attributes are:

    • version
    • datasourceId
    • jobExecutionId

    The attributes follow these rules:

    • dataSourceId and jobExecutionId must be used together.
    • version is ignored if dataSourceId and jobExecutionId are not provided.
    • If dataSourceId and jobExecutionId are provided, but version is not, the version defaults to "0".
    *)
  2. document_id : string;
    (*

    The identifier of the document.

    *)
}

Identifies a document for which to retrieve status information

type disassociate_personas_from_entities_response = {
  1. failed_entity_list : failed_entity list option;
    (*

    Lists the users or groups in your IAM Identity Center identity source that failed to properly remove access to your Amazon Kendra experience.

    *)
}
type disassociate_personas_from_entities_request = {
  1. entity_ids : string list;
    (*

    The identifiers of users or groups in your IAM Identity Center identity source. For example, user IDs could be user emails.

    *)
  2. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  3. id : string;
    (*

    The identifier of your Amazon Kendra experience.

    *)
}
type disassociate_entities_from_experience_response = {
  1. failed_entity_list : failed_entity list option;
    (*

    Lists the users or groups in your IAM Identity Center identity source that failed to properly remove access to your Amazon Kendra experience.

    *)
}
type disassociate_entities_from_experience_request = {
  1. entity_list : entity_configuration list;
    (*

    Lists users or groups in your IAM Identity Center identity source.

    *)
  2. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  3. id : string;
    (*

    The identifier of your Amazon Kendra experience.

    *)
}
type describe_thesaurus_response = {
  1. synonym_rule_count : int option;
    (*

    The number of synonym rules in the thesaurus file.

    *)
  2. term_count : int option;
    (*

    The number of unique terms in the thesaurus file. For example, the synonyms a,b,c and a=>d, the term count would be 4.

    *)
  3. file_size_bytes : int option;
    (*

    The size of the thesaurus file in bytes.

    *)
  4. source_s3_path : s3_path option;
  5. role_arn : string option;
    (*

    An IAM role that gives Amazon Kendra permissions to access thesaurus file specified in SourceS3Path.

    *)
  6. updated_at : float option;
    (*

    The Unix timestamp when the thesaurus was last updated.

    *)
  7. created_at : float option;
    (*

    The Unix timestamp when the thesaurus was created.

    *)
  8. error_message : string option;
    (*

    When the Status field value is FAILED, the ErrorMessage field provides more information.

    *)
  9. status : thesaurus_status option;
    (*

    The current status of the thesaurus. When the value is ACTIVE, queries are able to use the thesaurus. If the Status field value is FAILED, the ErrorMessage field provides more information.

    If the status is ACTIVE_BUT_UPDATE_FAILED, it means that Amazon Kendra could not ingest the new thesaurus file. The old thesaurus file is still active.

    *)
  10. description : string option;
    (*

    The thesaurus description.

    *)
  11. name : string option;
    (*

    The thesaurus name.

    *)
  12. index_id : string option;
    (*

    The identifier of the index for the thesaurus.

    *)
  13. id : string option;
    (*

    The identifier of the thesaurus.

    *)
}
type describe_thesaurus_request = {
  1. index_id : string;
    (*

    The identifier of the index for the thesaurus.

    *)
  2. id : string;
    (*

    The identifier of the thesaurus you want to get information on.

    *)
}
type attribute_suggestions_describe_config = {
  1. attribute_suggestions_mode : attribute_suggestions_mode option;
    (*

    The mode is set to either ACTIVE or INACTIVE. If the Mode for query history is set to ENABLED when calling UpdateQuerySuggestionsConfig and AttributeSuggestionsMode to use fields/attributes is set to ACTIVE, and you haven't set your SuggestionTypes preference to DOCUMENT_ATTRIBUTES, then Amazon Kendra uses the query history.

    *)
  2. suggestable_config_list : suggestable_config list option;
    (*

    The list of fields/attributes that you want to set as suggestible for query suggestions.

    *)
}

Gets information on the configuration of document fields/attributes that you want to base query suggestions on. To change your configuration, use AttributeSuggestionsUpdateConfig and then call UpdateQuerySuggestionsConfig.

type describe_query_suggestions_config_response = {
  1. attribute_suggestions_config : attribute_suggestions_describe_config option;
    (*

    Configuration information for the document fields/attributes that you want to base query suggestions on.

    *)
  2. total_suggestions_count : int option;
    (*

    The current total count of query suggestions for an index.

    This count can change when you update your query suggestions settings, if you filter out certain queries from suggestions using a block list, and as the query log accumulates more queries for Amazon Kendra to learn from.

    If the count is much lower than you expected, it could be because Amazon Kendra needs more queries in the query history to learn from or your current query suggestions settings are too strict.

    *)
  3. last_clear_time : float option;
    (*

    The Unix timestamp when query suggestions for an index was last cleared.

    After you clear suggestions, Amazon Kendra learns new suggestions based on new queries added to the query log from the time you cleared suggestions. Amazon Kendra only considers re-occurences of a query from the time you cleared suggestions.

    *)
  4. last_suggestions_build_time : float option;
    (*

    The Unix timestamp when query suggestions for an index was last updated.

    Amazon Kendra automatically updates suggestions every 24 hours, after you change a setting or after you apply a block list.

    *)
  5. minimum_query_count : int option;
    (*

    The minimum number of times a query must be searched in order for the query to be eligible to suggest to your users.

    *)
  6. minimum_number_of_querying_users : int option;
    (*

    The minimum number of unique users who must search a query in order for the query to be eligible to suggest to your users.

    *)
  7. include_queries_without_user_information : bool option;
    (*

    TRUE to use all queries, otherwise use only queries that include user information to generate the query suggestions.

    *)
  8. query_log_look_back_window_in_days : int option;
    (*

    How recent your queries are in your query log time window (in days).

    *)
  9. status : query_suggestions_status option;
    (*

    Whether the status of query suggestions settings is currently ACTIVE or UPDATING.

    Active means the current settings apply and Updating means your changed settings are in the process of applying.

    *)
  10. mode : mode option;
    (*

    Whether query suggestions are currently in ENABLED mode or LEARN_ONLY mode.

    By default, Amazon Kendra enables query suggestions.LEARN_ONLY turns off query suggestions for your users. You can change the mode using the UpdateQuerySuggestionsConfig API.

    *)
}
type describe_query_suggestions_config_request = {
  1. index_id : string;
    (*

    The identifier of the index with query suggestions that you want to get information on.

    *)
}
type describe_query_suggestions_block_list_response = {
  1. role_arn : string option;
    (*

    The IAM (Identity and Access Management) role used by Amazon Kendra to access the block list text file in S3.

    The role needs S3 read permissions to your file in S3 and needs to give STS (Security Token Service) assume role permissions to Amazon Kendra.

    *)
  2. file_size_bytes : int option;
    (*

    The current size of the block list text file in S3.

    *)
  3. item_count : int option;
    (*

    The current number of valid, non-empty words or phrases in the block list text file.

    *)
  4. source_s3_path : s3_path option;
    (*

    Shows the current S3 path to your block list text file in your S3 bucket.

    Each block word or phrase should be on a separate line in a text file.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

    *)
  5. updated_at : float option;
    (*

    The Unix timestamp when a block list for query suggestions was last updated.

    *)
  6. created_at : float option;
    (*

    The Unix timestamp when a block list for query suggestions was created.

    *)
  7. error_message : string option;
    (*

    The error message containing details if there are issues processing the block list.

    *)
  8. status : query_suggestions_block_list_status option;
    (*

    The current status of the block list. When the value is ACTIVE, the block list is ready for use.

    *)
  9. description : string option;
    (*

    The description for the block list.

    *)
  10. name : string option;
    (*

    The name of the block list.

    *)
  11. id : string option;
    (*

    The identifier of the block list.

    *)
  12. index_id : string option;
    (*

    The identifier of the index for the block list.

    *)
}
type describe_query_suggestions_block_list_request = {
  1. id : string;
    (*

    The identifier of the block list you want to get information on.

    *)
  2. index_id : string;
    (*

    The identifier of the index for the block list.

    *)
}
type describe_principal_mapping_response = {
  1. group_ordering_id_summaries : group_ordering_id_summary list option;
    (*

    Shows the following information on the processing of PUT and DELETE actions for mapping users to their groups:

    • Status—the status can be either PROCESSING, SUCCEEDED, DELETING, DELETED, or FAILED.
    • Last updated—the last date-time an action was updated.
    • Received—the last date-time an action was received or submitted.
    • Ordering ID—the latest action that should process and apply after other actions.
    • Failure reason—the reason an action could not be processed.
    *)
  2. group_id : string option;
    (*

    Shows the identifier of the group to see information on the processing of PUT and DELETE actions for mapping users to their groups.

    *)
  3. data_source_id : string option;
    (*

    Shows the identifier of the data source to see information on the processing of PUT and DELETE actions for mapping users to their groups.

    *)
  4. index_id : string option;
    (*

    Shows the identifier of the index to see information on the processing of PUT and DELETE actions for mapping users to their groups.

    *)
}
type describe_principal_mapping_request = {
  1. group_id : string;
    (*

    The identifier of the group required to check the processing of PUT and DELETE actions for mapping users to their groups.

    *)
  2. data_source_id : string option;
    (*

    The identifier of the data source to check the processing of PUT and DELETE actions for mapping users to their groups.

    *)
  3. index_id : string;
    (*

    The identifier of the index required to check the processing of PUT and DELETE actions for mapping users to their groups.

    *)
}
type describe_index_response = {
  1. user_group_resolution_configuration : user_group_resolution_configuration option;
    (*

    Whether you have enabled IAM Identity Center identity source for your users and groups. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    *)
  2. user_context_policy : user_context_policy option;
    (*

    The user context policy for the Amazon Kendra index.

    *)
  3. user_token_configurations : user_token_configuration list option;
    (*

    The user token configuration for the Amazon Kendra index.

    *)
  4. capacity_units : capacity_units_configuration option;
    (*

    For Enterprise Edition indexes, you can choose to use additional capacity to meet the needs of your application. This contains the capacity units used for the index. A query or document storage capacity of zero indicates that the index is using the default capacity. For more information on the default capacity for an index and adjusting this, see Adjusting capacity.

    *)
  5. error_message : string option;
    (*

    When the Status field value is FAILED, the ErrorMessage field contains a message that explains why.

    *)
  6. index_statistics : index_statistics option;
    (*

    Provides information about the number of FAQ questions and answers and the number of text documents indexed.

    *)
  7. document_metadata_configurations : document_metadata_configuration list option;
    (*

    Configuration information for document metadata or fields. Document metadata are fields or attributes associated with your documents. For example, the company department name associated with each document.

    *)
  8. updated_at : float option;
    (*

    The Unix timestamp when the index was last updated.

    *)
  9. created_at : float option;
    (*

    The Unix timestamp when the index was created.

    *)
  10. description : string option;
    (*

    The description for the index.

    *)
  11. status : index_status option;
    (*

    The current status of the index. When the value is ACTIVE, the index is ready for use. If the Status field value is FAILED, the ErrorMessage field contains a message that explains why.

    *)
  12. server_side_encryption_configuration : server_side_encryption_configuration option;
    (*

    The identifier of the KMS customer master key (CMK) that is used to encrypt your data. Amazon Kendra doesn't support asymmetric CMKs.

    *)
  13. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of the IAM role that gives Amazon Kendra permission to write to your Amazon CloudWatch logs.

    *)
  14. edition : index_edition option;
    (*

    The Amazon Kendra edition used for the index. You decide the edition when you create the index.

    *)
  15. id : string option;
    (*

    The identifier of the index.

    *)
  16. name : string option;
    (*

    The name of the index.

    *)
}
type describe_index_request = {
  1. id : string;
    (*

    The identifier of the index you want to get information on.

    *)
}
type describe_faq_response = {
  1. language_code : string option;
    (*

    The code for a language. This shows a supported language for the FAQ document. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    *)
  2. file_format : faq_file_format option;
    (*

    The file format used by the input files for the FAQ.

    *)
  3. error_message : string option;
    (*

    If the Status field is FAILED, the ErrorMessage field contains the reason why the FAQ failed.

    *)
  4. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of the role that provides access to the S3 bucket containing the input files for the FAQ.

    *)
  5. status : faq_status option;
    (*

    The status of the FAQ. It is ready to use when the status is ACTIVE.

    *)
  6. s3_path : s3_path option;
  7. updated_at : float option;
    (*

    The Unix timestamp when the FAQ was last updated.

    *)
  8. created_at : float option;
    (*

    The Unix timestamp when the FAQ was created.

    *)
  9. description : string option;
    (*

    The description of the FAQ that you provided when it was created.

    *)
  10. name : string option;
    (*

    The name that you gave the FAQ when it was created.

    *)
  11. index_id : string option;
    (*

    The identifier of the index for the FAQ.

    *)
  12. id : string option;
    (*

    The identifier of the FAQ.

    *)
}
type describe_faq_request = {
  1. index_id : string;
    (*

    The identifier of the index for the FAQ.

    *)
  2. id : string;
    (*

    The identifier of the FAQ you want to get information on.

    *)
}
type describe_experience_response = {
  1. error_message : string option;
    (*

    The reason your Amazon Kendra experience could not properly process.

    *)
  2. role_arn : string option;
    (*

    Shows the Amazon Resource Name (ARN) of a role with permission to access Query API, QuerySuggestions API, SubmitFeedback API, and IAM Identity Center that stores your user and group information.

    *)
  3. status : experience_status option;
    (*

    The current processing status of your Amazon Kendra experience. When the status is ACTIVE, your Amazon Kendra experience is ready to use. When the status is FAILED, the ErrorMessage field contains the reason that this failed.

    *)
  4. description : string option;
    (*

    Shows the description for your Amazon Kendra experience.

    *)
  5. updated_at : float option;
    (*

    The Unix timestamp when your Amazon Kendra experience was last updated.

    *)
  6. created_at : float option;
    (*

    The Unix timestamp when your Amazon Kendra experience was created.

    *)
  7. configuration : experience_configuration option;
    (*

    Shows the configuration information for your Amazon Kendra experience. This includes ContentSourceConfiguration, which specifies the data source IDs and/or FAQ IDs, and UserIdentityConfiguration, which specifies the user or group information to grant access to your Amazon Kendra experience.

    *)
  8. endpoints : experience_endpoint list option;
    (*

    Shows the endpoint URLs for your Amazon Kendra experiences. The URLs are unique and fully hosted by Amazon Web Services.

    *)
  9. name : string option;
    (*

    Shows the name of your Amazon Kendra experience.

    *)
  10. index_id : string option;
    (*

    Shows the identifier of the index for your Amazon Kendra experience.

    *)
  11. id : string option;
    (*

    Shows the identifier of your Amazon Kendra experience.

    *)
}
type describe_experience_request = {
  1. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  2. id : string;
    (*

    The identifier of your Amazon Kendra experience you want to get information on.

    *)
}
type describe_data_source_response = {
  1. custom_document_enrichment_configuration : custom_document_enrichment_configuration option;
    (*

    Configuration information for altering document metadata and content during the document ingestion process when you describe a data source.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

    *)
  2. language_code : string option;
    (*

    The code for a language. This shows a supported language for all documents in the data source. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    *)
  3. error_message : string option;
    (*

    When the Status field value is FAILED, the ErrorMessage field contains a description of the error that caused the data source to fail.

    *)
  4. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of the role with permission to access the data source and required resources.

    *)
  5. schedule : string option;
    (*

    The schedule for Amazon Kendra to update the index.

    *)
  6. status : data_source_status option;
    (*

    The current status of the data source connector. When the status is ACTIVE the data source is ready to use. When the status is FAILED, the ErrorMessage field contains the reason that the data source failed.

    *)
  7. description : string option;
    (*

    The description for the data source connector.

    *)
  8. updated_at : float option;
    (*

    The Unix timestamp when the data source connector was last updated.

    *)
  9. created_at : float option;
    (*

    The Unix timestamp when the data source connector was created.

    *)
  10. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your data source. For more information, see Configuring a VPC.

    *)
  11. configuration : data_source_configuration option;
    (*

    Configuration details for the data source connector. This shows how the data source is configured. The configuration options for a data source depend on the data source provider.

    *)
  12. type_ : data_source_type option;
    (*

    The type of the data source. For example, SHAREPOINT.

    *)
  13. name : string option;
    (*

    The name for the data source connector.

    *)
  14. index_id : string option;
    (*

    The identifier of the index used with the data source connector.

    *)
  15. id : string option;
    (*

    The identifier of the data source connector.

    *)
}
type describe_data_source_request = {
  1. index_id : string;
    (*

    The identifier of the index used with the data source connector.

    *)
  2. id : string;
    (*

    The identifier of the data source connector.

    *)
}
type describe_access_control_configuration_response = {
  1. hierarchical_access_control_list : hierarchical_principal list option;
    (*

    The list of principal lists that define the hierarchy for which documents users should have access to.

    *)
  2. access_control_list : principal list option;
    (*

    Information on principals (users and/or groups) and which documents they should have access to. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    *)
  3. error_message : string option;
    (*

    The error message containing details if there are issues processing the access control configuration.

    *)
  4. description : string option;
    (*

    The description for the access control configuration.

    *)
  5. name : string;
    (*

    The name for the access control configuration.

    *)
}
type describe_access_control_configuration_request = {
  1. id : string;
    (*

    The identifier of the access control configuration you want to get information on.

    *)
  2. index_id : string;
    (*

    The identifier of the index for an access control configuration.

    *)
}
type delete_thesaurus_request = {
  1. index_id : string;
    (*

    The identifier of the index for the thesaurus.

    *)
  2. id : string;
    (*

    The identifier of the thesaurus you want to delete.

    *)
}
type delete_query_suggestions_block_list_request = {
  1. id : string;
    (*

    The identifier of the block list you want to delete.

    *)
  2. index_id : string;
    (*

    The identifier of the index for the block list.

    *)
}
type delete_principal_mapping_request = {
  1. ordering_id : int option;
    (*

    The timestamp identifier you specify to ensure Amazon Kendra does not override the latest DELETE action with previous actions. The highest number ID, which is the ordering ID, is the latest action you want to process and apply on top of other actions with lower number IDs. This prevents previous actions with lower number IDs from possibly overriding the latest action.

    The ordering ID can be the Unix time of the last update you made to a group members list. You would then provide this list when calling PutPrincipalMapping. This ensures your DELETE action for that updated group with the latest members list doesn't get overwritten by earlier DELETE actions for the same group which are yet to be processed.

    The default ordering ID is the current Unix time in milliseconds that the action was received by Amazon Kendra.

    *)
  2. group_id : string;
    (*

    The identifier of the group you want to delete.

    *)
  3. data_source_id : string option;
    (*

    The identifier of the data source you want to delete a group from.

    A group can be tied to multiple data sources. You can delete a group from accessing documents in a certain data source. For example, the groups "Research", "Engineering", and "Sales and Marketing" are all tied to the company's documents stored in the data sources Confluence and Salesforce. You want to delete "Research" and "Engineering" groups from Salesforce, so that these groups cannot access customer-related documents stored in Salesforce. Only "Sales and Marketing" should access documents in the Salesforce data source.

    *)
  4. index_id : string;
    (*

    The identifier of the index you want to delete a group from.

    *)
}
type delete_index_request = {
  1. id : string;
    (*

    The identifier of the index you want to delete.

    *)
}
type delete_faq_request = {
  1. index_id : string;
    (*

    The identifier of the index for the FAQ.

    *)
  2. id : string;
    (*

    The identifier of the FAQ you want to remove.

    *)
}
type delete_experience_response = unit
type delete_experience_request = {
  1. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  2. id : string;
    (*

    The identifier of your Amazon Kendra experience you want to delete.

    *)
}
type delete_data_source_request = {
  1. index_id : string;
    (*

    The identifier of the index used with the data source connector.

    *)
  2. id : string;
    (*

    The identifier of the data source connector you want to delete.

    *)
}
type delete_access_control_configuration_response = unit
type delete_access_control_configuration_request = {
  1. id : string;
    (*

    The identifier of the access control configuration you want to delete.

    *)
  2. index_id : string;
    (*

    The identifier of the index for an access control configuration.

    *)
}
type data_source_sync_job_metric_target = {
  1. data_source_sync_job_id : string option;
    (*

    The ID of the sync job that is running on the data source.

    If the ID of a sync job is not provided and there is a sync job running, then the ID of this sync job is used and metrics are generated for this sync job.

    If the ID of a sync job is not provided and there is no sync job running, then no metrics are generated and documents are indexed/deleted at the index level without sync job metrics included.

    *)
  2. data_source_id : string;
    (*

    The ID of the data source that is running the sync job.

    *)
}

Maps a particular data source sync job to a particular data source.

type create_thesaurus_response = {
  1. id : string option;
    (*

    The identifier of the thesaurus.

    *)
}
type create_thesaurus_request = {
  1. client_token : string option;
    (*

    A token that you provide to identify the request to create a thesaurus. Multiple calls to the CreateThesaurus API with the same client token will create only one thesaurus.

    *)
  2. source_s3_path : s3_path;
    (*

    The path to the thesaurus file in S3.

    *)
  3. tags : tag list option;
    (*

    A list of key-value pairs that identify or categorize the thesaurus. You can also use tags to help control access to the thesaurus. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    *)
  4. role_arn : string;
    (*

    The Amazon Resource Name (ARN) of an IAM role with permission to access your S3 bucket that contains the thesaurus file. For more information, see IAM access roles for Amazon Kendra.

    *)
  5. description : string option;
    (*

    A description for the thesaurus.

    *)
  6. name : string;
    (*

    A name for the thesaurus.

    *)
  7. index_id : string;
    (*

    The identifier of the index for the thesaurus.

    *)
}
type create_query_suggestions_block_list_response = {
  1. id : string option;
    (*

    The identifier of the block list.

    *)
}
type create_query_suggestions_block_list_request = {
  1. tags : tag list option;
    (*

    A list of key-value pairs that identify or categorize the block list. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    *)
  2. role_arn : string;
    (*

    The Amazon Resource Name (ARN) of an IAM role with permission to access your S3 bucket that contains the block list text file. For more information, see IAM access roles for Amazon Kendra.

    *)
  3. client_token : string option;
    (*

    A token that you provide to identify the request to create a query suggestions block list.

    *)
  4. source_s3_path : s3_path;
    (*

    The S3 path to your block list text file in your S3 bucket.

    Each block word or phrase should be on a separate line in a text file.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

    *)
  5. description : string option;
    (*

    A description for the block list.

    For example, the description "List of all offensive words that can appear in user queries and need to be blocked from suggestions."

    *)
  6. name : string;
    (*

    A name for the block list.

    For example, the name 'offensive-words', which includes all offensive words that could appear in user queries and need to be blocked from suggestions.

    *)
  7. index_id : string;
    (*

    The identifier of the index you want to create a query suggestions block list for.

    *)
}
type create_index_response = {
  1. id : string option;
    (*

    The identifier of the index. Use this identifier when you query an index, set up a data source, or index a document.

    *)
}
type create_index_request = {
  1. user_group_resolution_configuration : user_group_resolution_configuration option;
    (*

    Gets users and groups from IAM Identity Center identity source. To configure this, see UserGroupResolutionConfiguration. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    *)
  2. user_context_policy : user_context_policy option;
    (*

    The user context policy.

    ATTRIBUTE_FILTER All indexed content is searchable and displayable for all users. If you want to filter search results on user context, you can use the attribute filters of _user_id and _group_ids or you can provide user and group information in UserContext.

    USER_TOKEN Enables token-based user access control to filter search results on user context. All documents with no access control and all documents accessible to the user will be searchable and displayable.

    *)
  3. user_token_configurations : user_token_configuration list option;
    (*

    The user token configuration.

    *)
  4. tags : tag list option;
    (*

    A list of key-value pairs that identify or categorize the index. You can also use tags to help control access to the index. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    *)
  5. client_token : string option;
    (*

    A token that you provide to identify the request to create an index. Multiple calls to the CreateIndex API with the same client token will create only one index.

    *)
  6. description : string option;
    (*

    A description for the index.

    *)
  7. server_side_encryption_configuration : server_side_encryption_configuration option;
    (*

    The identifier of the KMS customer managed key (CMK) that's used to encrypt data indexed by Amazon Kendra. Amazon Kendra doesn't support asymmetric CMKs.

    *)
  8. role_arn : string;
    (*

    The Amazon Resource Name (ARN) of an IAM role with permission to access your Amazon CloudWatch logs and metrics. For more information, see IAM access roles for Amazon Kendra.

    *)
  9. edition : index_edition option;
    (*

    The Amazon Kendra edition to use for the index. Choose DEVELOPER_EDITION for indexes intended for development, testing, or proof of concept. Use ENTERPRISE_EDITION for production. Once you set the edition for an index, it can't be changed.

    The Edition parameter is optional. If you don't supply a value, the default is ENTERPRISE_EDITION.

    For more information on quota limits for Enterprise and Developer editions, see Quotas.

    *)
  10. name : string;
    (*

    A name for the index.

    *)
}
type create_faq_response = {
  1. id : string option;
    (*

    The identifier of the FAQ.

    *)
}
type create_faq_request = {
  1. language_code : string option;
    (*

    The code for a language. This allows you to support a language for the FAQ document. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    *)
  2. client_token : string option;
    (*

    A token that you provide to identify the request to create a FAQ. Multiple calls to the CreateFaqRequest API with the same client token will create only one FAQ.

    *)
  3. file_format : faq_file_format option;
    (*

    The format of the FAQ input file. You can choose between a basic CSV format, a CSV format that includes customs attributes in a header, and a JSON format that includes custom attributes.

    The default format is CSV.

    The format must match the format of the file stored in the S3 bucket identified in the S3Path parameter.

    For more information, see Adding questions and answers.

    *)
  4. tags : tag list option;
    (*

    A list of key-value pairs that identify the FAQ. You can use the tags to identify and organize your resources and to control access to resources.

    *)
  5. role_arn : string;
    (*

    The Amazon Resource Name (ARN) of an IAM role with permission to access the S3 bucket that contains the FAQs. For more information, see IAM access roles for Amazon Kendra.

    *)
  6. s3_path : s3_path;
    (*

    The path to the FAQ file in S3.

    *)
  7. description : string option;
    (*

    A description for the FAQ.

    *)
  8. name : string;
    (*

    A name for the FAQ.

    *)
  9. index_id : string;
    (*

    The identifier of the index for the FAQ.

    *)
}
type create_experience_response = {
  1. id : string;
    (*

    The identifier of your Amazon Kendra experience.

    *)
}
type create_experience_request = {
  1. client_token : string option;
    (*

    A token that you provide to identify the request to create your Amazon Kendra experience. Multiple calls to the CreateExperience API with the same client token creates only one Amazon Kendra experience.

    *)
  2. description : string option;
    (*

    A description for your Amazon Kendra experience.

    *)
  3. configuration : experience_configuration option;
    (*

    Configuration information for your Amazon Kendra experience. This includes ContentSourceConfiguration, which specifies the data source IDs and/or FAQ IDs, and UserIdentityConfiguration, which specifies the user or group information to grant access to your Amazon Kendra experience.

    *)
  4. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role with permission to access Query API, GetQuerySuggestions API, and other required APIs. The role also must include permission to access IAM Identity Center that stores your user and group information. For more information, see IAM access roles for Amazon Kendra.

    *)
  5. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  6. name : string;
    (*

    A name for your Amazon Kendra experience.

    *)
}
type create_data_source_response = {
  1. id : string;
    (*

    The identifier of the data source connector.

    *)
}
type create_data_source_request = {
  1. custom_document_enrichment_configuration : custom_document_enrichment_configuration option;
    (*

    Configuration information for altering document metadata and content during the document ingestion process.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

    *)
  2. language_code : string option;
    (*

    The code for a language. This allows you to support a language for all documents when creating the data source connector. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    *)
  3. client_token : string option;
    (*

    A token that you provide to identify the request to create a data source connector. Multiple calls to the CreateDataSource API with the same client token will create only one data source connector.

    *)
  4. tags : tag list option;
    (*

    A list of key-value pairs that identify or categorize the data source connector. You can also use tags to help control access to the data source connector. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    *)
  5. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role with permission to access the data source and required resources. For more information, see IAM access roles for Amazon Kendra..

    You can't specify the RoleArn parameter when the Type parameter is set to CUSTOM. If you do, you receive a ValidationException exception.

    The RoleArn parameter is required for all other data sources.

    *)
  6. schedule : string option;
    (*

    Sets the frequency for Amazon Kendra to check the documents in your data source repository and update the index. If you don't set a schedule Amazon Kendra will not periodically update the index. You can call the StartDataSourceSyncJob API to update the index.

    Specify a cron- format schedule string or an empty string to indicate that the index is updated on demand.

    You can't specify the Schedule parameter when the Type parameter is set to CUSTOM. If you do, you receive a ValidationException exception.

    *)
  7. description : string option;
    (*

    A description for the data source connector.

    *)
  8. vpc_configuration : data_source_vpc_configuration option;
    (*

    Configuration information for an Amazon Virtual Private Cloud to connect to your data source. For more information, see Configuring a VPC.

    *)
  9. configuration : data_source_configuration option;
    (*

    Configuration information to connect to your data source repository.

    You can't specify the Configuration parameter when the Type parameter is set to CUSTOM. If you do, you receive a ValidationException exception.

    The Configuration parameter is required for all other data sources.

    *)
  10. type_ : data_source_type;
    (*

    The type of data source repository. For example, SHAREPOINT.

    *)
  11. index_id : string;
    (*

    The identifier of the index you want to use with the data source connector.

    *)
  12. name : string;
    (*

    A name for the data source connector.

    *)
}
type create_access_control_configuration_response = {
  1. id : string;
    (*

    The identifier of the access control configuration for your documents in an index.

    *)
}
type create_access_control_configuration_request = {
  1. client_token : string option;
    (*

    A token that you provide to identify the request to create an access control configuration. Multiple calls to the CreateAccessControlConfiguration API with the same client token will create only one access control configuration.

    *)
  2. hierarchical_access_control_list : hierarchical_principal list option;
    (*

    The list of principal lists that define the hierarchy for which documents users should have access to.

    *)
  3. access_control_list : principal list option;
    (*

    Information on principals (users and/or groups) and which documents they should have access to. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    *)
  4. description : string option;
    (*

    A description for the access control configuration.

    *)
  5. name : string;
    (*

    A name for the access control configuration.

    *)
  6. index_id : string;
    (*

    The identifier of the index to create an access control configuration for your documents.

    *)
}
type clear_query_suggestions_request = {
  1. index_id : string;
    (*

    The identifier of the index you want to clear query suggestions from.

    *)
}
type batch_put_document_response_failed_document = {
  1. error_message : string option;
    (*

    A description of the reason why the document could not be indexed.

    *)
  2. error_code : error_code option;
    (*

    The type of error that caused the document to fail to be indexed.

    *)
  3. id : string option;
    (*

    The identifier of the document.

    *)
}

Provides information about a document that could not be indexed.

type batch_put_document_response = {
  1. failed_documents : batch_put_document_response_failed_document list option;
    (*

    A list of documents that were not added to the index because the document failed a validation check. Each document contains an error message that indicates why the document couldn't be added to the index.

    If there was an error adding a document to an index the error is reported in your Amazon Web Services CloudWatch log. For more information, see Monitoring Amazon Kendra with Amazon CloudWatch logs.

    *)
}
type batch_put_document_request = {
  1. custom_document_enrichment_configuration : custom_document_enrichment_configuration option;
    (*

    Configuration information for altering your document metadata and content during the document ingestion process when you use the BatchPutDocument API.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

    *)
  2. documents : document list;
    (*

    One or more documents to add to the index.

    Documents have the following file size limits.

    • 50 MB total size for any file
    • 5 MB extracted text for any file

    For more information, see Quotas.

    *)
  3. role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role with permission to access your S3 bucket. For more information, see IAM access roles for Amazon Kendra.

    *)
  4. index_id : string;
    (*

    The identifier of the index to add the documents to. You need to create the index first using the CreateIndex API.

    *)
}
type batch_get_document_status_response_error = {
  1. error_message : string option;
    (*

    States that the API could not get the status of a document. This could be because the request is not valid or there is a system error.

    *)
  2. error_code : error_code option;
    (*

    Indicates the source of the error.

    *)
  3. document_id : string option;
    (*

    The identifier of the document whose status could not be retrieved.

    *)
}

Provides a response when the status of a document could not be retrieved.

type batch_get_document_status_response = {
  1. document_status_list : status list option;
    (*

    The status of documents. The status indicates if the document is waiting to be indexed, is in the process of indexing, has completed indexing, or failed indexing. If a document failed indexing, the status provides the reason why.

    *)
  2. errors : batch_get_document_status_response_error list option;
    (*

    A list of documents that Amazon Kendra couldn't get the status for. The list includes the ID of the document and the reason that the status couldn't be found.

    *)
}
type batch_get_document_status_request = {
  1. document_info_list : document_info list;
    (*

    A list of DocumentInfo objects that identify the documents for which to get the status. You identify the documents by their document ID and optional attributes.

    *)
  2. index_id : string;
    (*

    The identifier of the index to add documents to. The index ID is returned by the CreateIndex API.

    *)
}

Provides information about a set of featured results that couldn't be removed from an index by the BatchDeleteFeaturedResultsSet API.

type batch_delete_document_response_failed_document = {
  1. error_message : string option;
    (*

    An explanation for why the document couldn't be removed from the index.

    *)
  2. error_code : error_code option;
    (*

    The error code for why the document couldn't be removed from the index.

    *)
  3. id : string option;
    (*

    The identifier of the document that couldn't be removed from the index.

    *)
}

Provides information about documents that could not be removed from an index by the BatchDeleteDocument API.

type batch_delete_document_response = {
  1. failed_documents : batch_delete_document_response_failed_document list option;
    (*

    A list of documents that could not be removed from the index. Each entry contains an error message that indicates why the document couldn't be removed from the index.

    *)
}
type batch_delete_document_request = {
  1. data_source_sync_job_metric_target : data_source_sync_job_metric_target option;
  2. document_id_list : string list;
    (*

    One or more identifiers for documents to delete from the index.

    *)
  3. index_id : string;
    (*

    The identifier of the index that contains the documents to delete.

    *)
}
type associate_personas_to_entities_response = {
  1. failed_entity_list : failed_entity list option;
    (*

    Lists the users or groups in your IAM Identity Center identity source that failed to properly configure with your Amazon Kendra experience.

    *)
}
type associate_personas_to_entities_request = {
  1. personas : entity_persona_configuration list;
    (*

    The personas that define the specific permissions of users or groups in your IAM Identity Center identity source. The available personas or access roles are Owner and Viewer. For more information on these personas, see Providing access to your search page.

    *)
  2. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  3. id : string;
    (*

    The identifier of your Amazon Kendra experience.

    *)
}
type associate_entities_to_experience_response = {
  1. failed_entity_list : failed_entity list option;
    (*

    Lists the users or groups in your IAM Identity Center identity source that failed to properly configure with your Amazon Kendra experience.

    *)
}
type associate_entities_to_experience_request = {
  1. entity_list : entity_configuration list;
    (*

    Lists users or groups in your IAM Identity Center identity source.

    *)
  2. index_id : string;
    (*

    The identifier of the index for your Amazon Kendra experience.

    *)
  3. id : string;
    (*

    The identifier of your Amazon Kendra experience.

    *)
}

Amazon Kendra is a service for indexing large document sets.

type base_document = Smaws_Lib.Json.t

Builders

val make_data_source_to_index_field_mapping : ?date_field_format:string -> index_field_name:string -> data_source_field_name:string -> unit -> data_source_to_index_field_mapping

Create a data_source_to_index_field_mapping type

val make_work_docs_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?use_change_log:bool -> ?crawl_comments:bool -> organization_id:string -> unit -> work_docs_configuration

Create a work_docs_configuration type

val make_seed_url_configuration : ?web_crawler_mode:web_crawler_mode -> seed_urls:string list -> unit -> seed_url_configuration

Create a seed_url_configuration type

val make_site_maps_configuration : site_maps:string list -> unit -> site_maps_configuration

Create a site_maps_configuration type

val make_urls : ?site_maps_configuration:site_maps_configuration -> ?seed_url_configuration:seed_url_configuration -> unit -> urls

Create a urls type

val make_proxy_configuration : ?credentials:string -> port:int -> host:string -> unit -> proxy_configuration

Create a proxy_configuration type

val make_basic_authentication_configuration : credentials:string -> port:int -> host:string -> unit -> basic_authentication_configuration

Create a basic_authentication_configuration type

val make_authentication_configuration : ?basic_authentication:basic_authentication_configuration list -> unit -> authentication_configuration

Create a authentication_configuration type

val make_web_crawler_configuration : ?authentication_configuration:authentication_configuration -> ?proxy_configuration:proxy_configuration -> ?url_exclusion_patterns:string list -> ?url_inclusion_patterns:string list -> ?max_urls_per_minute_crawl_rate:int -> ?max_content_size_per_page_in_mega_bytes:float -> ?max_links_per_page:int -> ?crawl_depth:int -> urls:urls -> unit -> web_crawler_configuration

Create a web_crawler_configuration type

val make_warning : ?code:warning_code -> ?message:string -> unit -> warning

Create a warning type

val make_jwt_token_type_configuration : ?claim_regex:string -> ?issuer:string -> ?group_attribute_field:string -> ?user_name_attribute_field:string -> ?secret_manager_arn:string -> ?ur_l:string -> key_location:key_location -> unit -> jwt_token_type_configuration

Create a jwt_token_type_configuration type

val make_json_token_type_configuration : group_attribute_field:string -> user_name_attribute_field:string -> unit -> json_token_type_configuration

Create a json_token_type_configuration type

val make_user_token_configuration : ?json_token_type_configuration:json_token_type_configuration -> ?jwt_token_type_configuration:jwt_token_type_configuration -> unit -> user_token_configuration

Create a user_token_configuration type

val make_user_identity_configuration : ?identity_attribute_name:string -> unit -> user_identity_configuration

Create a user_identity_configuration type

val make_user_group_resolution_configuration : user_group_resolution_mode:user_group_resolution_mode -> unit -> user_group_resolution_configuration

Create a user_group_resolution_configuration type

val make_data_source_group : data_source_id:string -> group_id:string -> unit -> data_source_group

Create a data_source_group type

val make_user_context : ?data_source_groups:data_source_group list -> ?groups:string list -> ?user_id:string -> ?token:string -> unit -> user_context

Create a user_context type

val make_s3_path : key:string -> bucket:string -> unit -> s3_path

Create a s3_path type

val make_update_thesaurus_request : ?source_s3_path:s3_path -> ?role_arn:string -> ?description:string -> ?name:string -> index_id:string -> id:string -> unit -> update_thesaurus_request

Create a update_thesaurus_request type

val make_suggestable_config : ?suggestable:bool -> ?attribute_name:string -> unit -> suggestable_config

Create a suggestable_config type

val make_attribute_suggestions_update_config : ?attribute_suggestions_mode:attribute_suggestions_mode -> ?suggestable_config_list:suggestable_config list -> unit -> attribute_suggestions_update_config

Create a attribute_suggestions_update_config type

val make_update_query_suggestions_config_request : ?attribute_suggestions_config:attribute_suggestions_update_config -> ?minimum_query_count:int -> ?minimum_number_of_querying_users:int -> ?include_queries_without_user_information:bool -> ?query_log_look_back_window_in_days:int -> ?mode:mode -> index_id:string -> unit -> update_query_suggestions_config_request

Create a update_query_suggestions_config_request type

val make_update_query_suggestions_block_list_request : ?role_arn:string -> ?source_s3_path:s3_path -> ?description:string -> ?name:string -> id:string -> index_id:string -> unit -> update_query_suggestions_block_list_request

Create a update_query_suggestions_block_list_request type

val make_relevance : ?value_importance_map:(string * int) list -> ?rank_order:order -> ?duration:string -> ?importance:int -> ?freshness:bool -> unit -> relevance

Create a relevance type

Create a search type

val make_document_metadata_configuration : ?search:search -> ?relevance:relevance -> type_:document_attribute_value_type -> name:string -> unit -> document_metadata_configuration

Create a document_metadata_configuration type

val make_capacity_units_configuration : query_capacity_units:int -> storage_capacity_units:int -> unit -> capacity_units_configuration

Create a capacity_units_configuration type

val make_update_index_request : ?user_group_resolution_configuration:user_group_resolution_configuration -> ?user_context_policy:user_context_policy -> ?user_token_configurations:user_token_configuration list -> ?capacity_units:capacity_units_configuration -> ?document_metadata_configuration_updates:document_metadata_configuration list -> ?description:string -> ?role_arn:string -> ?name:string -> id:string -> unit -> update_index_request

Create a update_index_request type

Create a featured_document type

Create a featured_results_set type

Create a update_featured_results_set_response type

Create a update_featured_results_set_request type

val make_conflicting_item : ?set_id:string -> ?set_name:string -> ?query_text:string -> unit -> conflicting_item

Create a conflicting_item type

val make_content_source_configuration : ?direct_put_content:bool -> ?faq_ids:string list -> ?data_source_ids:string list -> unit -> content_source_configuration

Create a content_source_configuration type

val make_experience_configuration : ?user_identity_configuration:user_identity_configuration -> ?content_source_configuration:content_source_configuration -> unit -> experience_configuration

Create a experience_configuration type

val make_update_experience_request : ?description:string -> ?configuration:experience_configuration -> ?role_arn:string -> ?name:string -> index_id:string -> id:string -> unit -> update_experience_request

Create a update_experience_request type

val make_documents_metadata_configuration : ?s3_prefix:string -> unit -> documents_metadata_configuration

Create a documents_metadata_configuration type

val make_access_control_list_configuration : ?key_path:string -> unit -> access_control_list_configuration

Create a access_control_list_configuration type

val make_s3_data_source_configuration : ?access_control_list_configuration:access_control_list_configuration -> ?documents_metadata_configuration:documents_metadata_configuration -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?inclusion_prefixes:string list -> bucket_name:string -> unit -> s3_data_source_configuration

Create a s3_data_source_configuration type

val make_data_source_vpc_configuration : security_group_ids:string list -> subnet_ids:string list -> unit -> data_source_vpc_configuration

Create a data_source_vpc_configuration type

val make_share_point_configuration : ?proxy_configuration:proxy_configuration -> ?authentication_type:share_point_online_authentication_type -> ?ssl_certificate_s3_path:s3_path -> ?disable_local_groups:bool -> ?document_title_field_name:string -> ?field_mappings:data_source_to_index_field_mapping list -> ?vpc_configuration:data_source_vpc_configuration -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?use_change_log:bool -> ?crawl_attachments:bool -> secret_arn:string -> urls:string list -> share_point_version:share_point_version -> unit -> share_point_configuration

Create a share_point_configuration type

val make_connection_configuration : secret_arn:string -> table_name:string -> database_name:string -> database_port:int -> database_host:string -> unit -> connection_configuration

Create a connection_configuration type

val make_column_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_column_name:string -> change_detecting_columns:string list -> document_data_column_name:string -> document_id_column_name:string -> unit -> column_configuration

Create a column_configuration type

val make_acl_configuration : allowed_groups_column_name:string -> unit -> acl_configuration

Create a acl_configuration type

val make_sql_configuration : ?query_identifiers_enclosing_option:query_identifiers_enclosing_option -> unit -> sql_configuration

Create a sql_configuration type

val make_database_configuration : ?sql_configuration:sql_configuration -> ?acl_configuration:acl_configuration -> ?vpc_configuration:data_source_vpc_configuration -> column_configuration:column_configuration -> connection_configuration:connection_configuration -> database_engine_type:database_engine_type -> unit -> database_configuration

Create a database_configuration type

val make_salesforce_standard_object_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_field_name:string -> document_data_field_name:string -> name:salesforce_standard_object_name -> unit -> salesforce_standard_object_configuration

Create a salesforce_standard_object_configuration type

val make_salesforce_standard_knowledge_article_type_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_field_name:string -> document_data_field_name:string -> unit -> salesforce_standard_knowledge_article_type_configuration

Create a salesforce_standard_knowledge_article_type_configuration type

val make_salesforce_custom_knowledge_article_type_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_field_name:string -> document_data_field_name:string -> name:string -> unit -> salesforce_custom_knowledge_article_type_configuration

Create a salesforce_custom_knowledge_article_type_configuration type

val make_salesforce_knowledge_article_configuration : ?custom_knowledge_article_type_configurations: salesforce_custom_knowledge_article_type_configuration list -> ?standard_knowledge_article_type_configuration: salesforce_standard_knowledge_article_type_configuration -> included_states:salesforce_knowledge_article_state list -> unit -> salesforce_knowledge_article_configuration

Create a salesforce_knowledge_article_configuration type

val make_salesforce_chatter_feed_configuration : ?include_filter_types:salesforce_chatter_feed_include_filter_type list -> ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_field_name:string -> document_data_field_name:string -> unit -> salesforce_chatter_feed_configuration

Create a salesforce_chatter_feed_configuration type

val make_salesforce_standard_object_attachment_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_field_name:string -> unit -> salesforce_standard_object_attachment_configuration

Create a salesforce_standard_object_attachment_configuration type

val make_salesforce_configuration : ?exclude_attachment_file_patterns:string list -> ?include_attachment_file_patterns:string list -> ?standard_object_attachment_configuration: salesforce_standard_object_attachment_configuration -> ?crawl_attachments:bool -> ?chatter_feed_configuration:salesforce_chatter_feed_configuration -> ?knowledge_article_configuration:salesforce_knowledge_article_configuration -> ?standard_object_configurations:salesforce_standard_object_configuration list -> secret_arn:string -> server_url:string -> unit -> salesforce_configuration

Create a salesforce_configuration type

val make_one_drive_users : ?one_drive_user_s3_path:s3_path -> ?one_drive_user_list:string list -> unit -> one_drive_users

Create a one_drive_users type

val make_one_drive_configuration : ?disable_local_groups:bool -> ?field_mappings:data_source_to_index_field_mapping list -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> one_drive_users:one_drive_users -> secret_arn:string -> tenant_domain:string -> unit -> one_drive_configuration

Create a one_drive_configuration type

val make_service_now_knowledge_article_configuration : ?filter_query:string -> ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_field_name:string -> ?exclude_attachment_file_patterns:string list -> ?include_attachment_file_patterns:string list -> ?crawl_attachments:bool -> document_data_field_name:string -> unit -> service_now_knowledge_article_configuration

Create a service_now_knowledge_article_configuration type

val make_service_now_service_catalog_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?document_title_field_name:string -> ?exclude_attachment_file_patterns:string list -> ?include_attachment_file_patterns:string list -> ?crawl_attachments:bool -> document_data_field_name:string -> unit -> service_now_service_catalog_configuration

Create a service_now_service_catalog_configuration type

val make_service_now_configuration : ?authentication_type:service_now_authentication_type -> ?service_catalog_configuration:service_now_service_catalog_configuration -> ?knowledge_article_configuration:service_now_knowledge_article_configuration -> service_now_build_version:service_now_build_version_type -> secret_arn:string -> host_url:string -> unit -> service_now_configuration

Create a service_now_configuration type

val make_confluence_space_to_index_field_mapping : ?index_field_name:string -> ?date_field_format:string -> ?data_source_field_name:confluence_space_field_name -> unit -> confluence_space_to_index_field_mapping

Create a confluence_space_to_index_field_mapping type

val make_confluence_space_configuration : ?space_field_mappings:confluence_space_to_index_field_mapping list -> ?exclude_spaces:string list -> ?include_spaces:string list -> ?crawl_archived_spaces:bool -> ?crawl_personal_spaces:bool -> unit -> confluence_space_configuration

Create a confluence_space_configuration type

val make_confluence_page_to_index_field_mapping : ?index_field_name:string -> ?date_field_format:string -> ?data_source_field_name:confluence_page_field_name -> unit -> confluence_page_to_index_field_mapping

Create a confluence_page_to_index_field_mapping type

val make_confluence_page_configuration : ?page_field_mappings:confluence_page_to_index_field_mapping list -> unit -> confluence_page_configuration

Create a confluence_page_configuration type

val make_confluence_blog_to_index_field_mapping : ?index_field_name:string -> ?date_field_format:string -> ?data_source_field_name:confluence_blog_field_name -> unit -> confluence_blog_to_index_field_mapping

Create a confluence_blog_to_index_field_mapping type

val make_confluence_blog_configuration : ?blog_field_mappings:confluence_blog_to_index_field_mapping list -> unit -> confluence_blog_configuration

Create a confluence_blog_configuration type

val make_confluence_attachment_to_index_field_mapping : ?index_field_name:string -> ?date_field_format:string -> ?data_source_field_name:confluence_attachment_field_name -> unit -> confluence_attachment_to_index_field_mapping

Create a confluence_attachment_to_index_field_mapping type

val make_confluence_attachment_configuration : ?attachment_field_mappings:confluence_attachment_to_index_field_mapping list -> ?crawl_attachments:bool -> unit -> confluence_attachment_configuration

Create a confluence_attachment_configuration type

val make_confluence_configuration : ?authentication_type:confluence_authentication_type -> ?proxy_configuration:proxy_configuration -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?vpc_configuration:data_source_vpc_configuration -> ?attachment_configuration:confluence_attachment_configuration -> ?blog_configuration:confluence_blog_configuration -> ?page_configuration:confluence_page_configuration -> ?space_configuration:confluence_space_configuration -> version:confluence_version -> secret_arn:string -> server_url:string -> unit -> confluence_configuration

Create a confluence_configuration type

val make_google_drive_configuration : ?exclude_shared_drives:string list -> ?exclude_user_accounts:string list -> ?exclude_mime_types:string list -> ?field_mappings:data_source_to_index_field_mapping list -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> secret_arn:string -> unit -> google_drive_configuration

Create a google_drive_configuration type

val make_fsx_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?secret_arn:string -> vpc_configuration:data_source_vpc_configuration -> file_system_type:fsx_file_system_type -> file_system_id:string -> unit -> fsx_configuration

Create a fsx_configuration type

val make_slack_configuration : ?field_mappings:data_source_to_index_field_mapping list -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?public_channel_filter:string list -> ?private_channel_filter:string list -> ?look_back_period:int -> ?exclude_archived:bool -> ?crawl_bot_message:bool -> ?use_change_log:bool -> ?vpc_configuration:data_source_vpc_configuration -> since_crawl_date:string -> slack_entity_list:slack_entity list -> secret_arn:string -> team_id:string -> unit -> slack_configuration

Create a slack_configuration type

val make_box_configuration : ?vpc_configuration:data_source_vpc_configuration -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?web_link_field_mappings:data_source_to_index_field_mapping list -> ?comment_field_mappings:data_source_to_index_field_mapping list -> ?task_field_mappings:data_source_to_index_field_mapping list -> ?file_field_mappings:data_source_to_index_field_mapping list -> ?crawl_web_links:bool -> ?crawl_tasks:bool -> ?crawl_comments:bool -> ?use_change_log:bool -> secret_arn:string -> enterprise_id:string -> unit -> box_configuration

Create a box_configuration type

val make_quip_configuration : ?vpc_configuration:data_source_vpc_configuration -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?attachment_field_mappings:data_source_to_index_field_mapping list -> ?message_field_mappings:data_source_to_index_field_mapping list -> ?thread_field_mappings:data_source_to_index_field_mapping list -> ?folder_ids:string list -> ?crawl_attachments:bool -> ?crawl_chat_rooms:bool -> ?crawl_file_comments:bool -> secret_arn:string -> domain:string -> unit -> quip_configuration

Create a quip_configuration type

val make_jira_configuration : ?vpc_configuration:data_source_vpc_configuration -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?work_log_field_mappings:data_source_to_index_field_mapping list -> ?project_field_mappings:data_source_to_index_field_mapping list -> ?issue_field_mappings:data_source_to_index_field_mapping list -> ?comment_field_mappings:data_source_to_index_field_mapping list -> ?attachment_field_mappings:data_source_to_index_field_mapping list -> ?issue_sub_entity_filter:issue_sub_entity list -> ?status:string list -> ?issue_type:string list -> ?project:string list -> ?use_change_log:bool -> secret_arn:string -> jira_account_url:string -> unit -> jira_configuration

Create a jira_configuration type

val make_saa_s_configuration : host_url:string -> organization_name:string -> unit -> saa_s_configuration

Create a saa_s_configuration type

val make_on_premise_configuration : ssl_certificate_s3_path:s3_path -> organization_name:string -> host_url:string -> unit -> on_premise_configuration

Create a on_premise_configuration type

val make_git_hub_document_crawl_properties : ?crawl_pull_request_comment_attachment:bool -> ?crawl_pull_request_comment:bool -> ?crawl_pull_request:bool -> ?crawl_issue_comment_attachment:bool -> ?crawl_issue_comment:bool -> ?crawl_issue:bool -> ?crawl_repository_documents:bool -> unit -> git_hub_document_crawl_properties

Create a git_hub_document_crawl_properties type

val make_git_hub_configuration : ?git_hub_pull_request_document_attachment_configuration_field_mappings: data_source_to_index_field_mapping list -> ?git_hub_pull_request_document_configuration_field_mappings: data_source_to_index_field_mapping list -> ?git_hub_pull_request_comment_configuration_field_mappings: data_source_to_index_field_mapping list -> ?git_hub_issue_attachment_configuration_field_mappings: data_source_to_index_field_mapping list -> ?git_hub_issue_comment_configuration_field_mappings: data_source_to_index_field_mapping list -> ?git_hub_issue_document_configuration_field_mappings: data_source_to_index_field_mapping list -> ?git_hub_commit_configuration_field_mappings: data_source_to_index_field_mapping list -> ?git_hub_repository_configuration_field_mappings: data_source_to_index_field_mapping list -> ?vpc_configuration:data_source_vpc_configuration -> ?exclusion_file_name_patterns:string list -> ?exclusion_file_type_patterns:string list -> ?exclusion_folder_name_patterns:string list -> ?inclusion_file_name_patterns:string list -> ?inclusion_file_type_patterns:string list -> ?inclusion_folder_name_patterns:string list -> ?repository_filter:string list -> ?git_hub_document_crawl_properties:git_hub_document_crawl_properties -> ?use_change_log:bool -> ?type_:type_ -> ?on_premise_configuration:on_premise_configuration -> ?saa_s_configuration:saa_s_configuration -> secret_arn:string -> unit -> git_hub_configuration

Create a git_hub_configuration type

val make_alfresco_configuration : ?vpc_configuration:data_source_vpc_configuration -> ?exclusion_patterns:string list -> ?inclusion_patterns:string list -> ?wiki_field_mappings:data_source_to_index_field_mapping list -> ?blog_field_mappings:data_source_to_index_field_mapping list -> ?document_library_field_mappings:data_source_to_index_field_mapping list -> ?entity_filter:alfresco_entity list -> ?crawl_comments:bool -> ?crawl_system_folders:bool -> ssl_certificate_s3_path:s3_path -> secret_arn:string -> site_id:string -> site_url:string -> unit -> alfresco_configuration

Create a alfresco_configuration type

val make_template_configuration : ?template:template -> unit -> template_configuration

Create a template_configuration type

val make_data_source_configuration : ?template_configuration:template_configuration -> ?alfresco_configuration:alfresco_configuration -> ?git_hub_configuration:git_hub_configuration -> ?jira_configuration:jira_configuration -> ?quip_configuration:quip_configuration -> ?box_configuration:box_configuration -> ?slack_configuration:slack_configuration -> ?fsx_configuration:fsx_configuration -> ?work_docs_configuration:work_docs_configuration -> ?web_crawler_configuration:web_crawler_configuration -> ?google_drive_configuration:google_drive_configuration -> ?confluence_configuration:confluence_configuration -> ?service_now_configuration:service_now_configuration -> ?one_drive_configuration:one_drive_configuration -> ?salesforce_configuration:salesforce_configuration -> ?database_configuration:database_configuration -> ?share_point_configuration:share_point_configuration -> ?s3_configuration:s3_data_source_configuration -> unit -> data_source_configuration

Create a data_source_configuration type

val make_document_attribute_value : ?date_value:float -> ?long_value:int -> ?string_list_value:string list -> ?string_value:string -> unit -> document_attribute_value

Create a document_attribute_value type

val make_document_attribute_condition : ?condition_on_value:document_attribute_value -> operator:condition_operator -> condition_document_attribute_key:string -> unit -> document_attribute_condition

Create a document_attribute_condition type

val make_document_attribute_target : ?target_document_attribute_value:document_attribute_value -> ?target_document_attribute_value_deletion:bool -> ?target_document_attribute_key:string -> unit -> document_attribute_target

Create a document_attribute_target type

val make_inline_custom_document_enrichment_configuration : ?document_content_deletion:bool -> ?target:document_attribute_target -> ?condition:document_attribute_condition -> unit -> inline_custom_document_enrichment_configuration

Create a inline_custom_document_enrichment_configuration type

val make_hook_configuration : ?invocation_condition:document_attribute_condition -> s3_bucket:string -> lambda_arn:string -> unit -> hook_configuration

Create a hook_configuration type

val make_custom_document_enrichment_configuration : ?role_arn:string -> ?post_extraction_hook_configuration:hook_configuration -> ?pre_extraction_hook_configuration:hook_configuration -> ?inline_configurations:inline_custom_document_enrichment_configuration list -> unit -> custom_document_enrichment_configuration

Create a custom_document_enrichment_configuration type

val make_update_data_source_request : ?custom_document_enrichment_configuration: custom_document_enrichment_configuration -> ?language_code:string -> ?role_arn:string -> ?schedule:string -> ?description:string -> ?vpc_configuration:data_source_vpc_configuration -> ?configuration:data_source_configuration -> ?name:string -> index_id:string -> id:string -> unit -> update_data_source_request

Create a update_data_source_request type

val make_update_access_control_configuration_response : unit -> update_access_control_configuration_response

Create a update_access_control_configuration_response type

val make_principal : ?data_source_id:string -> access:read_access_type -> type_:principal_type -> name:string -> unit -> principal

Create a principal type

val make_hierarchical_principal : principal_list:principal list -> unit -> hierarchical_principal

Create a hierarchical_principal type

val make_update_access_control_configuration_request : ?hierarchical_access_control_list:hierarchical_principal list -> ?access_control_list:principal list -> ?description:string -> ?name:string -> id:string -> index_id:string -> unit -> update_access_control_configuration_request

Create a update_access_control_configuration_request type

val make_untag_resource_response : unit -> untag_resource_response

Create a untag_resource_response type

val make_untag_resource_request : tag_keys:string list -> resource_ar_n:string -> unit -> untag_resource_request

Create a untag_resource_request type

val make_time_range : ?end_time:float -> ?start_time:float -> unit -> time_range

Create a time_range type

val make_thesaurus_summary : ?updated_at:float -> ?created_at:float -> ?status:thesaurus_status -> ?name:string -> ?id:string -> unit -> thesaurus_summary

Create a thesaurus_summary type

val make_highlight : ?type_:highlight_type -> ?top_answer:bool -> end_offset:int -> begin_offset:int -> unit -> highlight

Create a highlight type

val make_text_with_highlights : ?highlights:highlight list -> ?text:string -> unit -> text_with_highlights

Create a text_with_highlights type

val make_text_document_statistics : indexed_text_bytes:int -> indexed_text_documents_count:int -> unit -> text_document_statistics

Create a text_document_statistics type

val make_tag_resource_response : unit -> tag_resource_response

Create a tag_resource_response type

val make_tag : value:string -> key:string -> unit -> tag

Create a tag type

val make_tag_resource_request : tags:tag list -> resource_ar_n:string -> unit -> tag_resource_request

Create a tag_resource_request type

val make_table_cell : ?header:bool -> ?highlighted:bool -> ?top_answer:bool -> ?value:string -> unit -> table_cell

Create a table_cell type

val make_table_row : ?cells:table_cell list -> unit -> table_row

Create a table_row type

val make_table_excerpt : ?total_number_of_rows:int -> ?rows:table_row list -> unit -> table_excerpt

Create a table_excerpt type

val make_suggestion_highlight : ?end_offset:int -> ?begin_offset:int -> unit -> suggestion_highlight

Create a suggestion_highlight type

val make_suggestion_text_with_highlights : ?highlights:suggestion_highlight list -> ?text:string -> unit -> suggestion_text_with_highlights

Create a suggestion_text_with_highlights type

val make_suggestion_value : ?text:suggestion_text_with_highlights -> unit -> suggestion_value

Create a suggestion_value type

val make_document_attribute : value:document_attribute_value -> key:string -> unit -> document_attribute

Create a document_attribute type

val make_source_document : ?additional_attributes:document_attribute list -> ?suggestion_attributes:string list -> ?document_id:string -> unit -> source_document

Create a source_document type

val make_suggestion : ?source_documents:source_document list -> ?value:suggestion_value -> ?id:string -> unit -> suggestion

Create a suggestion type

val make_click_feedback : click_time:float -> result_id:string -> unit -> click_feedback

Create a click_feedback type

val make_relevance_feedback : relevance_value:relevance_type -> result_id:string -> unit -> relevance_feedback

Create a relevance_feedback type

val make_submit_feedback_request : ?relevance_feedback_items:relevance_feedback list -> ?click_feedback_items:click_feedback list -> query_id:string -> index_id:string -> unit -> submit_feedback_request

Create a submit_feedback_request type

val make_stop_data_source_sync_job_request : index_id:string -> id:string -> unit -> stop_data_source_sync_job_request

Create a stop_data_source_sync_job_request type

val make_status : ?failure_reason:string -> ?failure_code:string -> ?document_status:document_status -> ?document_id:string -> unit -> status

Create a status type

val make_start_data_source_sync_job_response : ?execution_id:string -> unit -> start_data_source_sync_job_response

Create a start_data_source_sync_job_response type

val make_start_data_source_sync_job_request : index_id:string -> id:string -> unit -> start_data_source_sync_job_request

Create a start_data_source_sync_job_request type

val make_spell_correction_configuration : include_query_spell_check_suggestions:bool -> unit -> spell_correction_configuration

Create a spell_correction_configuration type

val make_correction : ?corrected_term:string -> ?term:string -> ?end_offset:int -> ?begin_offset:int -> unit -> correction

Create a correction type

val make_spell_corrected_query : ?corrections:correction list -> ?suggested_query_text:string -> unit -> spell_corrected_query

Create a spell_corrected_query type

val make_sorting_configuration : sort_order:sort_order -> document_attribute_key:string -> unit -> sorting_configuration

Create a sorting_configuration type

val make_server_side_encryption_configuration : ?kms_key_id:string -> unit -> server_side_encryption_configuration

Create a server_side_encryption_configuration type

val make_score_attributes : ?score_confidence:score_confidence -> unit -> score_attributes

Create a score_attributes type

val make_retrieve_result_item : ?score_attributes:score_attributes -> ?document_attributes:document_attribute list -> ?document_ur_i:string -> ?content:string -> ?document_title:string -> ?document_id:string -> ?id:string -> unit -> retrieve_result_item

Create a retrieve_result_item type

val make_attribute_filter : ?less_than_or_equals:document_attribute -> ?less_than:document_attribute -> ?greater_than_or_equals:document_attribute -> ?greater_than:document_attribute -> ?contains_any:document_attribute -> ?contains_all:document_attribute -> ?equals_to:document_attribute -> ?not_filter:attribute_filter -> ?or_all_filters:attribute_filter list -> ?and_all_filters:attribute_filter list -> unit -> attribute_filter

Create a attribute_filter type

val make_document_relevance_configuration : relevance:relevance -> name:string -> unit -> document_relevance_configuration

Create a document_relevance_configuration type

val make_retrieve_request : ?user_context:user_context -> ?page_size:int -> ?page_number:int -> ?document_relevance_override_configurations: document_relevance_configuration list -> ?requested_document_attributes:string list -> ?attribute_filter:attribute_filter -> query_text:string -> index_id:string -> unit -> retrieve_request

Create a retrieve_request type

val make_query_suggestions_block_list_summary : ?item_count:int -> ?updated_at:float -> ?created_at:float -> ?status:query_suggestions_block_list_status -> ?name:string -> ?id:string -> unit -> query_suggestions_block_list_summary

Create a query_suggestions_block_list_summary type

val make_additional_result_attribute_value : ?text_with_highlights_value:text_with_highlights -> unit -> additional_result_attribute_value

Create a additional_result_attribute_value type

val make_additional_result_attribute : value:additional_result_attribute_value -> value_type:additional_result_attribute_value_type -> key:string -> unit -> additional_result_attribute

Create a additional_result_attribute type

val make_expanded_result_item : ?document_attributes:document_attribute list -> ?document_ur_i:string -> ?document_excerpt:text_with_highlights -> ?document_title:text_with_highlights -> ?document_id:string -> ?id:string -> unit -> expanded_result_item

Create a expanded_result_item type

val make_collapsed_result_detail : ?expanded_results:expanded_result_item list -> document_attribute:document_attribute -> unit -> collapsed_result_detail

Create a collapsed_result_detail type

val make_query_result_item : ?collapsed_result_detail:collapsed_result_detail -> ?table_excerpt:table_excerpt -> ?feedback_token:string -> ?score_attributes:score_attributes -> ?document_attributes:document_attribute list -> ?document_ur_i:string -> ?document_excerpt:text_with_highlights -> ?document_title:text_with_highlights -> ?document_id:string -> ?additional_attributes:additional_result_attribute list -> ?format:query_result_format -> ?type_:query_result_type -> ?id:string -> unit -> query_result_item

Create a query_result_item type

val make_document_attribute_value_count_pair : ?facet_results:facet_result list -> ?count:int -> ?document_attribute_value:document_attribute_value -> unit -> document_attribute_value_count_pair

Create a document_attribute_value_count_pair type

Create a featured_results_item type

val make_facet : ?max_results:int -> ?facets:facet list -> ?document_attribute_key:string -> unit -> facet

Create a facet type

val make_expand_configuration : ?max_expanded_results_per_item:int -> ?max_result_items_to_expand:int -> unit -> expand_configuration

Create a expand_configuration type

val make_collapse_configuration : ?expand_configuration:expand_configuration -> ?expand:bool -> ?missing_attribute_key_strategy:missing_attribute_key_strategy -> ?sorting_configurations:sorting_configuration list -> document_attribute_key:string -> unit -> collapse_configuration

Create a collapse_configuration type

val make_query_request : ?collapse_configuration:collapse_configuration -> ?spell_correction_configuration:spell_correction_configuration -> ?visitor_id:string -> ?user_context:user_context -> ?sorting_configurations:sorting_configuration list -> ?sorting_configuration:sorting_configuration -> ?page_size:int -> ?page_number:int -> ?document_relevance_override_configurations: document_relevance_configuration list -> ?query_result_type_filter:query_result_type -> ?requested_document_attributes:string list -> ?facets:facet list -> ?attribute_filter:attribute_filter -> ?query_text:string -> index_id:string -> unit -> query_request

Create a query_request type

val make_member_group : ?data_source_id:string -> group_id:string -> unit -> member_group

Create a member_group type

val make_member_user : user_id:string -> unit -> member_user

Create a member_user type

val make_group_members : ?s3_pathfor_group_members:s3_path -> ?member_users:member_user list -> ?member_groups:member_group list -> unit -> group_members

Create a group_members type

val make_put_principal_mapping_request : ?role_arn:string -> ?ordering_id:int -> ?data_source_id:string -> group_members:group_members -> group_id:string -> index_id:string -> unit -> put_principal_mapping_request

Create a put_principal_mapping_request type

val make_personas_summary : ?updated_at:float -> ?created_at:float -> ?persona:persona -> ?entity_id:string -> unit -> personas_summary

Create a personas_summary type

val make_list_thesauri_response : ?thesaurus_summary_items:thesaurus_summary list -> ?next_token:string -> unit -> list_thesauri_response

Create a list_thesauri_response type

val make_list_thesauri_request : ?max_results:int -> ?next_token:string -> index_id:string -> unit -> list_thesauri_request

Create a list_thesauri_request type

val make_list_tags_for_resource_response : ?tags:tag list -> unit -> list_tags_for_resource_response

Create a list_tags_for_resource_response type

val make_list_tags_for_resource_request : resource_ar_n:string -> unit -> list_tags_for_resource_request

Create a list_tags_for_resource_request type

val make_list_query_suggestions_block_lists_response : ?next_token:string -> ?block_list_summary_items:query_suggestions_block_list_summary list -> unit -> list_query_suggestions_block_lists_response

Create a list_query_suggestions_block_lists_response type

val make_list_query_suggestions_block_lists_request : ?max_results:int -> ?next_token:string -> index_id:string -> unit -> list_query_suggestions_block_lists_request

Create a list_query_suggestions_block_lists_request type

val make_group_summary : ?ordering_id:int -> ?group_id:string -> unit -> group_summary

Create a group_summary type

val make_index_configuration_summary : ?edition:index_edition -> ?id:string -> ?name:string -> status:index_status -> updated_at:float -> created_at:float -> unit -> index_configuration_summary

Create a index_configuration_summary type

val make_list_indices_response : ?next_token:string -> ?index_configuration_summary_items:index_configuration_summary list -> unit -> list_indices_response

Create a list_indices_response type

val make_list_indices_request : ?max_results:int -> ?next_token:string -> unit -> list_indices_request

Create a list_indices_request type

val make_list_groups_older_than_ordering_id_response : ?next_token:string -> ?groups_summaries:group_summary list -> unit -> list_groups_older_than_ordering_id_response

Create a list_groups_older_than_ordering_id_response type

val make_list_groups_older_than_ordering_id_request : ?max_results:int -> ?next_token:string -> ?data_source_id:string -> ordering_id:int -> index_id:string -> unit -> list_groups_older_than_ordering_id_request

Create a list_groups_older_than_ordering_id_request type

Create a featured_results_set_summary type

Create a list_featured_results_sets_response type

Create a list_featured_results_sets_request type

val make_faq_summary : ?language_code:string -> ?file_format:faq_file_format -> ?updated_at:float -> ?created_at:float -> ?status:faq_status -> ?name:string -> ?id:string -> unit -> faq_summary

Create a faq_summary type

val make_list_faqs_response : ?faq_summary_items:faq_summary list -> ?next_token:string -> unit -> list_faqs_response

Create a list_faqs_response type

val make_list_faqs_request : ?max_results:int -> ?next_token:string -> index_id:string -> unit -> list_faqs_request

Create a list_faqs_request type

val make_experience_endpoint : ?endpoint:string -> ?endpoint_type:endpoint_type -> unit -> experience_endpoint

Create a experience_endpoint type

val make_experiences_summary : ?endpoints:experience_endpoint list -> ?status:experience_status -> ?created_at:float -> ?id:string -> ?name:string -> unit -> experiences_summary

Create a experiences_summary type

val make_list_experiences_response : ?next_token:string -> ?summary_items:experiences_summary list -> unit -> list_experiences_response

Create a list_experiences_response type

val make_list_experiences_request : ?max_results:int -> ?next_token:string -> index_id:string -> unit -> list_experiences_request

Create a list_experiences_request type

val make_entity_display_data : ?last_name:string -> ?first_name:string -> ?identified_user_name:string -> ?group_name:string -> ?user_name:string -> unit -> entity_display_data

Create a entity_display_data type

val make_experience_entities_summary : ?display_data:entity_display_data -> ?entity_type:entity_type -> ?entity_id:string -> unit -> experience_entities_summary

Create a experience_entities_summary type

val make_list_experience_entities_response : ?next_token:string -> ?summary_items:experience_entities_summary list -> unit -> list_experience_entities_response

Create a list_experience_entities_response type

val make_list_experience_entities_request : ?next_token:string -> index_id:string -> id:string -> unit -> list_experience_entities_request

Create a list_experience_entities_request type

val make_list_entity_personas_response : ?next_token:string -> ?summary_items:personas_summary list -> unit -> list_entity_personas_response

Create a list_entity_personas_response type

val make_list_entity_personas_request : ?max_results:int -> ?next_token:string -> index_id:string -> id:string -> unit -> list_entity_personas_request

Create a list_entity_personas_request type

val make_data_source_summary : ?language_code:string -> ?status:data_source_status -> ?updated_at:float -> ?created_at:float -> ?type_:data_source_type -> ?id:string -> ?name:string -> unit -> data_source_summary

Create a data_source_summary type

val make_list_data_sources_response : ?next_token:string -> ?summary_items:data_source_summary list -> unit -> list_data_sources_response

Create a list_data_sources_response type

val make_list_data_sources_request : ?max_results:int -> ?next_token:string -> index_id:string -> unit -> list_data_sources_request

Create a list_data_sources_request type

val make_data_source_sync_job_metrics : ?documents_scanned:string -> ?documents_failed:string -> ?documents_deleted:string -> ?documents_modified:string -> ?documents_added:string -> unit -> data_source_sync_job_metrics

Create a data_source_sync_job_metrics type

val make_data_source_sync_job : ?metrics:data_source_sync_job_metrics -> ?data_source_error_code:string -> ?error_code:error_code -> ?error_message:string -> ?status:data_source_sync_job_status -> ?end_time:float -> ?start_time:float -> ?execution_id:string -> unit -> data_source_sync_job

Create a data_source_sync_job type

val make_list_data_source_sync_jobs_response : ?next_token:string -> ?history:data_source_sync_job list -> unit -> list_data_source_sync_jobs_response

Create a list_data_source_sync_jobs_response type

val make_list_data_source_sync_jobs_request : ?status_filter:data_source_sync_job_status -> ?start_time_filter:time_range -> ?max_results:int -> ?next_token:string -> index_id:string -> id:string -> unit -> list_data_source_sync_jobs_request

Create a list_data_source_sync_jobs_request type

val make_access_control_configuration_summary : id:string -> unit -> access_control_configuration_summary

Create a access_control_configuration_summary type

val make_list_access_control_configurations_response : ?next_token:string -> access_control_configurations:access_control_configuration_summary list -> unit -> list_access_control_configurations_response

Create a list_access_control_configurations_response type

val make_list_access_control_configurations_request : ?max_results:int -> ?next_token:string -> index_id:string -> unit -> list_access_control_configurations_request

Create a list_access_control_configurations_request type

val make_faq_statistics : indexed_question_answers_count:int -> unit -> faq_statistics

Create a faq_statistics type

val make_index_statistics : text_document_statistics:text_document_statistics -> faq_statistics:faq_statistics -> unit -> index_statistics

Create a index_statistics type

val make_group_ordering_id_summary : ?failure_reason:string -> ?ordering_id:int -> ?received_at:float -> ?last_updated_at:float -> ?status:principal_mapping_status -> unit -> group_ordering_id_summary

Create a group_ordering_id_summary type

val make_get_snapshots_response : ?next_token:string -> ?snapshots_data:string list list -> ?snapshots_data_header:string list -> ?snap_shot_time_filter:time_range -> unit -> get_snapshots_response

Create a get_snapshots_response type

val make_get_snapshots_request : ?max_results:int -> ?next_token:string -> metric_type:metric_type -> interval:interval -> index_id:string -> unit -> get_snapshots_request

Create a get_snapshots_request type

val make_get_query_suggestions_response : ?suggestions:suggestion list -> ?query_suggestions_id:string -> unit -> get_query_suggestions_response

Create a get_query_suggestions_response type

val make_attribute_suggestions_get_config : ?user_context:user_context -> ?attribute_filter:attribute_filter -> ?additional_response_attributes:string list -> ?suggestion_attributes:string list -> unit -> attribute_suggestions_get_config

Create a attribute_suggestions_get_config type

val make_get_query_suggestions_request : ?attribute_suggestions_config:attribute_suggestions_get_config -> ?suggestion_types:suggestion_type list -> ?max_suggestions_count:int -> query_text:string -> index_id:string -> unit -> get_query_suggestions_request

Create a get_query_suggestions_request type

Create a featured_document_with_metadata type

Create a featured_document_missing type

val make_failed_entity : ?error_message:string -> ?entity_id:string -> unit -> failed_entity

Create a failed_entity type

val make_entity_persona_configuration : persona:persona -> entity_id:string -> unit -> entity_persona_configuration

Create a entity_persona_configuration type

val make_entity_configuration : entity_type:entity_type -> entity_id:string -> unit -> entity_configuration

Create a entity_configuration type

val make_document : ?access_control_configuration_id:string -> ?content_type:content_type -> ?hierarchical_access_control_list:hierarchical_principal list -> ?access_control_list:principal list -> ?attributes:document_attribute list -> ?s3_path:s3_path -> ?blob:bytes -> ?title:string -> id:string -> unit -> document

Create a document type

val make_document_info : ?attributes:document_attribute list -> document_id:string -> unit -> document_info

Create a document_info type

val make_disassociate_personas_from_entities_response : ?failed_entity_list:failed_entity list -> unit -> disassociate_personas_from_entities_response

Create a disassociate_personas_from_entities_response type

val make_disassociate_personas_from_entities_request : entity_ids:string list -> index_id:string -> id:string -> unit -> disassociate_personas_from_entities_request

Create a disassociate_personas_from_entities_request type

val make_disassociate_entities_from_experience_response : ?failed_entity_list:failed_entity list -> unit -> disassociate_entities_from_experience_response

Create a disassociate_entities_from_experience_response type

val make_disassociate_entities_from_experience_request : entity_list:entity_configuration list -> index_id:string -> id:string -> unit -> disassociate_entities_from_experience_request

Create a disassociate_entities_from_experience_request type

val make_describe_thesaurus_response : ?synonym_rule_count:int -> ?term_count:int -> ?file_size_bytes:int -> ?source_s3_path:s3_path -> ?role_arn:string -> ?updated_at:float -> ?created_at:float -> ?error_message:string -> ?status:thesaurus_status -> ?description:string -> ?name:string -> ?index_id:string -> ?id:string -> unit -> describe_thesaurus_response

Create a describe_thesaurus_response type

val make_describe_thesaurus_request : index_id:string -> id:string -> unit -> describe_thesaurus_request

Create a describe_thesaurus_request type

val make_attribute_suggestions_describe_config : ?attribute_suggestions_mode:attribute_suggestions_mode -> ?suggestable_config_list:suggestable_config list -> unit -> attribute_suggestions_describe_config

Create a attribute_suggestions_describe_config type

val make_describe_query_suggestions_config_response : ?attribute_suggestions_config:attribute_suggestions_describe_config -> ?total_suggestions_count:int -> ?last_clear_time:float -> ?last_suggestions_build_time:float -> ?minimum_query_count:int -> ?minimum_number_of_querying_users:int -> ?include_queries_without_user_information:bool -> ?query_log_look_back_window_in_days:int -> ?status:query_suggestions_status -> ?mode:mode -> unit -> describe_query_suggestions_config_response

Create a describe_query_suggestions_config_response type

val make_describe_query_suggestions_config_request : index_id:string -> unit -> describe_query_suggestions_config_request

Create a describe_query_suggestions_config_request type

val make_describe_query_suggestions_block_list_response : ?role_arn:string -> ?file_size_bytes:int -> ?item_count:int -> ?source_s3_path:s3_path -> ?updated_at:float -> ?created_at:float -> ?error_message:string -> ?status:query_suggestions_block_list_status -> ?description:string -> ?name:string -> ?id:string -> ?index_id:string -> unit -> describe_query_suggestions_block_list_response

Create a describe_query_suggestions_block_list_response type

val make_describe_query_suggestions_block_list_request : id:string -> index_id:string -> unit -> describe_query_suggestions_block_list_request

Create a describe_query_suggestions_block_list_request type

val make_describe_principal_mapping_response : ?group_ordering_id_summaries:group_ordering_id_summary list -> ?group_id:string -> ?data_source_id:string -> ?index_id:string -> unit -> describe_principal_mapping_response

Create a describe_principal_mapping_response type

val make_describe_principal_mapping_request : ?data_source_id:string -> group_id:string -> index_id:string -> unit -> describe_principal_mapping_request

Create a describe_principal_mapping_request type

val make_describe_index_response : ?user_group_resolution_configuration:user_group_resolution_configuration -> ?user_context_policy:user_context_policy -> ?user_token_configurations:user_token_configuration list -> ?capacity_units:capacity_units_configuration -> ?error_message:string -> ?index_statistics:index_statistics -> ?document_metadata_configurations:document_metadata_configuration list -> ?updated_at:float -> ?created_at:float -> ?description:string -> ?status:index_status -> ?server_side_encryption_configuration:server_side_encryption_configuration -> ?role_arn:string -> ?edition:index_edition -> ?id:string -> ?name:string -> unit -> describe_index_response

Create a describe_index_response type

val make_describe_index_request : id:string -> unit -> describe_index_request

Create a describe_index_request type

Create a describe_featured_results_set_response type

Create a describe_featured_results_set_request type

val make_describe_faq_response : ?language_code:string -> ?file_format:faq_file_format -> ?error_message:string -> ?role_arn:string -> ?status:faq_status -> ?s3_path:s3_path -> ?updated_at:float -> ?created_at:float -> ?description:string -> ?name:string -> ?index_id:string -> ?id:string -> unit -> describe_faq_response

Create a describe_faq_response type

val make_describe_faq_request : index_id:string -> id:string -> unit -> describe_faq_request

Create a describe_faq_request type

val make_describe_experience_response : ?error_message:string -> ?role_arn:string -> ?status:experience_status -> ?description:string -> ?updated_at:float -> ?created_at:float -> ?configuration:experience_configuration -> ?endpoints:experience_endpoint list -> ?name:string -> ?index_id:string -> ?id:string -> unit -> describe_experience_response

Create a describe_experience_response type

val make_describe_experience_request : index_id:string -> id:string -> unit -> describe_experience_request

Create a describe_experience_request type

val make_describe_data_source_response : ?custom_document_enrichment_configuration: custom_document_enrichment_configuration -> ?language_code:string -> ?error_message:string -> ?role_arn:string -> ?schedule:string -> ?status:data_source_status -> ?description:string -> ?updated_at:float -> ?created_at:float -> ?vpc_configuration:data_source_vpc_configuration -> ?configuration:data_source_configuration -> ?type_:data_source_type -> ?name:string -> ?index_id:string -> ?id:string -> unit -> describe_data_source_response

Create a describe_data_source_response type

val make_describe_data_source_request : index_id:string -> id:string -> unit -> describe_data_source_request

Create a describe_data_source_request type

val make_describe_access_control_configuration_response : ?hierarchical_access_control_list:hierarchical_principal list -> ?access_control_list:principal list -> ?error_message:string -> ?description:string -> name:string -> unit -> describe_access_control_configuration_response

Create a describe_access_control_configuration_response type

val make_describe_access_control_configuration_request : id:string -> index_id:string -> unit -> describe_access_control_configuration_request

Create a describe_access_control_configuration_request type

val make_delete_thesaurus_request : index_id:string -> id:string -> unit -> delete_thesaurus_request

Create a delete_thesaurus_request type

val make_delete_query_suggestions_block_list_request : id:string -> index_id:string -> unit -> delete_query_suggestions_block_list_request

Create a delete_query_suggestions_block_list_request type

val make_delete_principal_mapping_request : ?ordering_id:int -> ?data_source_id:string -> group_id:string -> index_id:string -> unit -> delete_principal_mapping_request

Create a delete_principal_mapping_request type

val make_delete_index_request : id:string -> unit -> delete_index_request

Create a delete_index_request type

val make_delete_faq_request : index_id:string -> id:string -> unit -> delete_faq_request

Create a delete_faq_request type

val make_delete_experience_response : unit -> delete_experience_response

Create a delete_experience_response type

val make_delete_experience_request : index_id:string -> id:string -> unit -> delete_experience_request

Create a delete_experience_request type

val make_delete_data_source_request : index_id:string -> id:string -> unit -> delete_data_source_request

Create a delete_data_source_request type

val make_delete_access_control_configuration_response : unit -> delete_access_control_configuration_response

Create a delete_access_control_configuration_response type

val make_delete_access_control_configuration_request : id:string -> index_id:string -> unit -> delete_access_control_configuration_request

Create a delete_access_control_configuration_request type

val make_data_source_sync_job_metric_target : ?data_source_sync_job_id:string -> data_source_id:string -> unit -> data_source_sync_job_metric_target

Create a data_source_sync_job_metric_target type

val make_create_thesaurus_response : ?id:string -> unit -> create_thesaurus_response

Create a create_thesaurus_response type

val make_create_thesaurus_request : ?client_token:string -> ?tags:tag list -> ?description:string -> source_s3_path:s3_path -> role_arn:string -> name:string -> index_id:string -> unit -> create_thesaurus_request

Create a create_thesaurus_request type

val make_create_query_suggestions_block_list_response : ?id:string -> unit -> create_query_suggestions_block_list_response

Create a create_query_suggestions_block_list_response type

val make_create_query_suggestions_block_list_request : ?tags:tag list -> ?client_token:string -> ?description:string -> role_arn:string -> source_s3_path:s3_path -> name:string -> index_id:string -> unit -> create_query_suggestions_block_list_request

Create a create_query_suggestions_block_list_request type

val make_create_index_response : ?id:string -> unit -> create_index_response

Create a create_index_response type

val make_create_index_request : ?user_group_resolution_configuration:user_group_resolution_configuration -> ?user_context_policy:user_context_policy -> ?user_token_configurations:user_token_configuration list -> ?tags:tag list -> ?client_token:string -> ?description:string -> ?server_side_encryption_configuration:server_side_encryption_configuration -> ?edition:index_edition -> role_arn:string -> name:string -> unit -> create_index_request

Create a create_index_request type

Create a create_featured_results_set_response type

Create a create_featured_results_set_request type

val make_create_faq_response : ?id:string -> unit -> create_faq_response

Create a create_faq_response type

val make_create_faq_request : ?language_code:string -> ?client_token:string -> ?file_format:faq_file_format -> ?tags:tag list -> ?description:string -> role_arn:string -> s3_path:s3_path -> name:string -> index_id:string -> unit -> create_faq_request

Create a create_faq_request type

val make_create_experience_response : id:string -> unit -> create_experience_response

Create a create_experience_response type

val make_create_experience_request : ?client_token:string -> ?description:string -> ?configuration:experience_configuration -> ?role_arn:string -> index_id:string -> name:string -> unit -> create_experience_request

Create a create_experience_request type

val make_create_data_source_response : id:string -> unit -> create_data_source_response

Create a create_data_source_response type

val make_create_data_source_request : ?custom_document_enrichment_configuration: custom_document_enrichment_configuration -> ?language_code:string -> ?client_token:string -> ?tags:tag list -> ?role_arn:string -> ?schedule:string -> ?description:string -> ?vpc_configuration:data_source_vpc_configuration -> ?configuration:data_source_configuration -> type_:data_source_type -> index_id:string -> name:string -> unit -> create_data_source_request

Create a create_data_source_request type

val make_create_access_control_configuration_response : id:string -> unit -> create_access_control_configuration_response

Create a create_access_control_configuration_response type

val make_create_access_control_configuration_request : ?client_token:string -> ?hierarchical_access_control_list:hierarchical_principal list -> ?access_control_list:principal list -> ?description:string -> name:string -> index_id:string -> unit -> create_access_control_configuration_request

Create a create_access_control_configuration_request type

val make_clear_query_suggestions_request : index_id:string -> unit -> clear_query_suggestions_request

Create a clear_query_suggestions_request type

val make_batch_put_document_response_failed_document : ?error_message:string -> ?error_code:error_code -> ?id:string -> unit -> batch_put_document_response_failed_document

Create a batch_put_document_response_failed_document type

val make_batch_put_document_response : ?failed_documents:batch_put_document_response_failed_document list -> unit -> batch_put_document_response

Create a batch_put_document_response type

val make_batch_put_document_request : ?custom_document_enrichment_configuration: custom_document_enrichment_configuration -> ?role_arn:string -> documents:document list -> index_id:string -> unit -> batch_put_document_request

Create a batch_put_document_request type

val make_batch_get_document_status_response_error : ?error_message:string -> ?error_code:error_code -> ?document_id:string -> unit -> batch_get_document_status_response_error

Create a batch_get_document_status_response_error type

val make_batch_get_document_status_response : ?document_status_list:status list -> ?errors:batch_get_document_status_response_error list -> unit -> batch_get_document_status_response

Create a batch_get_document_status_response type

val make_batch_get_document_status_request : document_info_list:document_info list -> index_id:string -> unit -> batch_get_document_status_request

Create a batch_get_document_status_request type

Create a batch_delete_featured_results_set_error type

Create a batch_delete_featured_results_set_response type

Create a batch_delete_featured_results_set_request type

val make_batch_delete_document_response_failed_document : ?error_message:string -> ?error_code:error_code -> ?id:string -> unit -> batch_delete_document_response_failed_document

Create a batch_delete_document_response_failed_document type

val make_batch_delete_document_response : ?failed_documents:batch_delete_document_response_failed_document list -> unit -> batch_delete_document_response

Create a batch_delete_document_response type

val make_batch_delete_document_request : ?data_source_sync_job_metric_target:data_source_sync_job_metric_target -> document_id_list:string list -> index_id:string -> unit -> batch_delete_document_request

Create a batch_delete_document_request type

val make_associate_personas_to_entities_response : ?failed_entity_list:failed_entity list -> unit -> associate_personas_to_entities_response

Create a associate_personas_to_entities_response type

val make_associate_personas_to_entities_request : personas:entity_persona_configuration list -> index_id:string -> id:string -> unit -> associate_personas_to_entities_request

Create a associate_personas_to_entities_request type

val make_associate_entities_to_experience_response : ?failed_entity_list:failed_entity list -> unit -> associate_entities_to_experience_response

Create a associate_entities_to_experience_response type

val make_associate_entities_to_experience_request : entity_list:entity_configuration list -> index_id:string -> id:string -> unit -> associate_entities_to_experience_request

Create a associate_entities_to_experience_request type

Operations

module AssociateEntitiesToExperience : sig ... end
module AssociatePersonasToEntities : sig ... end
module BatchDeleteDocument : sig ... end
module BatchDeleteFeaturedResultsSet : sig ... end
module BatchGetDocumentStatus : sig ... end
module BatchPutDocument : sig ... end
module ClearQuerySuggestions : sig ... end
module CreateDataSource : sig ... end
module CreateExperience : sig ... end
module CreateFaq : sig ... end
module CreateFeaturedResultsSet : sig ... end
module CreateIndex : sig ... end
module CreateQuerySuggestionsBlockList : sig ... end
module CreateThesaurus : sig ... end
module DeleteDataSource : sig ... end
module DeleteExperience : sig ... end
module DeleteFaq : sig ... end
module DeleteIndex : sig ... end
module DeletePrincipalMapping : sig ... end
module DeleteQuerySuggestionsBlockList : sig ... end
module DeleteThesaurus : sig ... end
module DescribeDataSource : sig ... end
module DescribeExperience : sig ... end
module DescribeFaq : sig ... end
module DescribeFeaturedResultsSet : sig ... end
module DescribeIndex : sig ... end
module DescribePrincipalMapping : sig ... end
module DescribeQuerySuggestionsConfig : sig ... end
module DescribeThesaurus : sig ... end
module GetQuerySuggestions : sig ... end
module GetSnapshots : sig ... end
module ListAccessControlConfigurations : sig ... end
module ListDataSourceSyncJobs : sig ... end
module ListDataSources : sig ... end
module ListEntityPersonas : sig ... end
module ListExperienceEntities : sig ... end
module ListExperiences : sig ... end
module ListFaqs : sig ... end
module ListFeaturedResultsSets : sig ... end
module ListGroupsOlderThanOrderingId : sig ... end
module ListIndices : sig ... end
module ListQuerySuggestionsBlockLists : sig ... end
module ListTagsForResource : sig ... end
module ListThesauri : sig ... end
module PutPrincipalMapping : sig ... end
module Query : sig ... end
module Retrieve : sig ... end
module StartDataSourceSyncJob : sig ... end
module StopDataSourceSyncJob : sig ... end
module SubmitFeedback : sig ... end
module TagResource : sig ... end
module UntagResource : sig ... end
module UpdateDataSource : sig ... end
module UpdateExperience : sig ... end
module UpdateFeaturedResultsSet : sig ... end
module UpdateIndex : sig ... end
module UpdateQuerySuggestionsBlockList : sig ... end
module UpdateQuerySuggestionsConfig : sig ... end
module UpdateThesaurus : sig ... end