vania-janet/multiturn-rag-retrieval-data huggingface dataset:
You can filter the list by:

Severity
: The severity that is assigned to the control: high (H), medium (M), or low (L).

Type
: The infrastructure type. For example, cluster, host, identity, or resource.

Target
: The specfic platforms or distributions that a control evaluates resources against.

You can also search on any word, or part of a word, in the control name.

Multiple filters can be specified to create more specific filter expressions.
4. Click Link for the control to link to the policy.
5. Repeat these steps to link more controls as needed.



If you need to unlink a control, hover over the linked control and click Unlink.





 Step 5. Publish the policy 

After configuring your policy, you need to publish the policy so that it is used in compliance evaluations.

These steps are only available for policies in draft state. The publish option is not available for policies that are already published.



1. Open your policy by [accessing the Posture Policies view](https://cloud.ibm.com/docs/workload-protection?topic=workload-protection-posture-policy-create-templateaccess-posture-controls) and clicking the policy that you want to publish.
2. Click Publish and confirm that you want your policy published.



The date published is the date that the policy is activated.

If you change a published policy, the policy is reevaluated in the environment, and new results are displayed in the [Compliance view](https://cloud.ibm.com/docs/workload-protection?topic=workload-protection-compliance). It can take a few minutes for the reevaluation to run and results to be refreshed.
"filter": "myddoc/myfilter",
"query_params": {
"key": "value"
}
}

The selector option provides performance benefits when compared with using the filter option. Use the selector option whenever possible. For more information, see the [selector](https://cloud.ibm.com/apidocs/cloudantpostfind) documentation.



 Eliminating conflicts that use replication 

Use the winning_revs_only: true option to replicate winning document revisions only. These revisions are the revisions that would be returned by the GET $ACCOUNT/$DATABASE/$DOCID API endpoint by default, or appear in the _changes feed with the default parameters.

{
"source": "https://$USERNAME:$PASSWORD@example.org/example-database",
"target": "https://$USERNAME:$PASSWORD@$ACCOUNT.cloudant.com/example-database",
"winning_revs_only": true
}

Replication with this mode discards conflicting revisions, so it might be one way to remove conflicts through replication.

Replication IDs and checkpoint IDs, generated by winning_revs_only: true replications are different than those replications generated by default, so it is possible to first replicate the winning revisions, then later, to backfill the rest of the revisions with a regular replication job.

The winning_revs_only: true option can be combined with filters or other options like continuous: true or create_target: true.







 Named document replication 

Sometimes you don't want to replicate documents. For simple replications, you don't need to write a filter function. Instead, to replicate specific documents, add the list of keys as an array in the doc_ids field.

See the following example replication of specific documents:

{
"source": "https://$USERNAME:$PASSWORD@example.org/example-database",
"target": "https://$USERNAME:$PASSWORD@127.0.0.1:5984/example-database",
Targets and inclusion filters are defined in API calls by using rules. The rules are defined in a JSON structure.

For example, the following example creates a route that is named my-route and sends metrics from atracker, and containers-registry in the us-east region to targets 11111111-1111-1111-1111-111111111111 and 22222222-2222-2222-2222-222222222222.

curl -X POST https://private.<REGION>.metrics-router.cloud.ibm.com/api/v3/routes -H "Authorization: Bearer <IAM_TOKEN>" -H 'content-type: application/json' -d '{
"name": "my-route",
"rules": [
{
"action":"send",
"targets": {"id":"11111111-1111-1111-1111-111111111111"}, {"id":"22222222-2222-2222-2222-222222222222"}],
"inclusion_filters":
{
"operand": "location",
"operator": "is",
"values": "us-east"]
},
{
"operand": "service_name",
"operator": "in",
"values": "atracker","containers-registry"]
}
]
}
]
}'

For more information, see the [API reference.](https://cloud.ibm.com/apidocs/metrics-router/metrics-router-v3)
5. From the Observability > Activity Tracker tab in the console navigation, verify the information for the instance that you created.
6. Click Open Dashboard. When the dashboard loads, you see an overall view of all the activity in your account. You can use the search operators to filter your results by tags, sources, apps, or levels. You can also search for specific events or jump to a specific timeframe.
7. From the All Apps drop-down, select the instance of App ID that you want to track events for.









 List of runtime events 

Check out the following table for a list of the runtime events that are sent to Activity Tracker.

Be sure that you turned on Runtime Activity to see these events.



Table 2. Actions that can be tracked as authentication events at runtime

 Description Action Outcome reason. reasonCode target.id target.name target.typeURI 

 Cloud Directory authentication success appid.user.authenticate success 200 [appid user CRN] cloud_directory:[GUID] appid/user 
 Cloud Directory authentication failure appid.user.authenticate failure 401 [appid user CRN] cloud_directory:[GUID] appid/user 
 Facebook authentication success appid.user.authenticate success 200 [appid user CRN] facebook:[GUID] appid/user 
 Facebook authentication failure appid.user.authenticate failure 401 crn:unknown facebook:unknown appid/user 
 Google authentication success appid.user.authenticate success 200 [appid user CRN] google:[GUID] appid/user 
 Google authentication failure appid.user.authenticate failure 401 crn:unknown google:unknown appid/user 
 SAML authentication success appid.user.authenticate success 200 [appid user CRN] SAML:[GUID] appid/user 
 SAML authentication failure appid.user.authenticate failure 401 crn:unknown SAML:unknown appid/user 
 Client Credentials authentication success appid.application.authenticate success 200 [appid application CRN] client_credentials:client_id appid/application
Editor access is required for creating private catalogs, setting filters at the private catalog level, adding your software to your private catalog, and updating, deprecating, and restoring your software.



1. Go to Access groups, and click Create.
2. Enter private-catalog-editors as the group name, and click Create.
3. Click Access > Assign access.
4. Select Catalog Management from the list of services.
5. Select the catalog that you want users to access.
6. In the Platform access section, select the Editor role.
7. Click Add to add your policy configuration to your policy summary.
8. Select Kubernetes Service from the list of services.
9. Select your cluster, and then select the Administrator and Manager roles.
10. Click Add.
11. Select Schematics from the list of services.
12. Select the Manager role.
13. Click Review.
14. Click Add > Assign.







 Viewer access in the console 

Viewer access is required for viewing private catalogs, the filtered IBM Cloud catalog, and the filter settings.



1. Go to Access groups, and click Create.
2. Enter private-catalog-viewers as the group name, and click Create.
3. Click Access > Assign access.
4. Select Catalog Management from the list of services.
5. Select the catalog that you want users to access.
6. In the Platform access section, select the Viewer role.
7. Click Review.
8. Click Add to add your policy configuration to your policy summary.
9. Click Assign.



You also need to have viewer access on the resource group to which your private catalog is assigned. You can assign your private catalog to a resource group when you complete the steps for creating your private catalog. For more information, see [Customizing the IBM Cloud catalog for all account users](https://cloud.ibm.com/docs/account?topic=account-filter-account).
],
"request": {
"auth": {
"type": "bearer",
"bearer":
{
"key": "token",
"value": "{{iamtoken}}",
"type": "string"
}
]
},
"method": "GET",
"header": ],
"body": {
"mode": "raw",
"raw": ""
},
"url": {
"raw": "https://{{endpoint-region}}cloud-object-storage.appdomain.cloud/{{bucket}}",
"protocol": "https",
"host":
"{{endpoint-region}}",
"objectstorage",
"softlayer",
"net"
],
"path":
"{{bucket}}"
]
},
"description": "Retrieve the list of files available in the bucket"
},
"response": ]
},
{
"name": "Retrieve list of files from bucket (filter by prefix)",
"event":
{
"listen": "test",
"script": {
"id": "aae11dfd-89e5-464d-a6da-44c05652ccec",
"type": "text/javascript",
"exec":
"pm.test("Request was successful", function() {",
" pm.response.to.be.success; ",
"});",
"",
"pm.test("Response contains expected content", function() {",
" pm.expect(pm.response.text()).to.include("ListBucketResult");",
"});"
]
}
}
],
"request": {
Grouping can be helpful if, for example, you want your assistant to ask a user for a phone number, and then use only the area code of the provided number in a response.

To assign the user-entered area code as a context variable, use the following syntax in the dialog node's response section to capture the group match:



Saving a capture group

 Variable Value 

 area_code <? @ContactInfo.groups[1] ?> 



For more information about using capture groups in your dialog, see [Storing and recognizing entity pattern groups in input](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-tipsdialog-tips-get-pattern-groups).







 How fuzzy matching works 

Fuzzy matching is available for languages noted in the [Supported languages](https://cloud.ibm.com/docs/assistant?topic=assistant-language-support) topic.

Fuzzy matching has these components:



* Stemming - The feature recognizes the stem form of entity values that have several grammatical forms. For example, the stem of 'bananas' would be 'banana', while the stem of 'running' would be 'run'.
* Misspelling - The feature is able to map user input to the appropriate corresponding entity despite the presence of misspellings or slight syntactical differences. For example, if you define giraffe as a synonym for an animal entity, and the user input contains the terms giraffes or girafe, the fuzzy match is able to map the term to the animal entity correctly.
* Partial match - With partial matching, the feature automatically suggests substring-based synonyms present in the user-defined entities, and assigns a lower confidence score as compared to the exact entity match.

The partial match component is supported only in English-language dialog skills.



For English, fuzzy matching prevents the capturing of some common, valid English words as fuzzy matches for a given entity. This feature uses standard English dictionary words. You can also define an English entity value/synonym, and fuzzy matching will match only your defined entity value/synonym.
For more information about using IAM tokens with existing and new applications, see the [17 May 2018](https://cloud.ibm.com/docs/discovery?topic=discovery-release-notesdiscovery-17may2018) release update.

New Element Classification contract element : An additional contract element is now supported in Element Classification: Safety and Security. See [Understanding Contract Elements](https://cloud.ibm.com/docs/discovery?topic=discovery-element-classification) for details.





 6 June 2018 

Improved query text display : IBM Watson™ Discovery News queries now display the first 50 words of each article in the text JSON field. [Update](https://cloud.ibm.com/docs/discovery?topic=discovery-release-notesdiscovery-24october2018)





 5 June 2018 

Improved Element Classification : Element Classification is now available to those subscribed to Premium plans. : The assurance rating of Low is no longer available for Element Classification.





 31 May 2018 

New full support for French language : Added full support for French. For more information, see [Language support](https://cloud.ibm.com/docs/discovery?topic=discovery-language-support).





 30 May 2018 

Fixed incorrect count known issue : Previously, when querying Discovery News it was possible to receive an incorrect document count because documents in other languages would be counted along with the language you requested. This is no longer the case.

New query results with special characters in multiple languages : Beginning with collections created on 22 May 2018 and after Discovery now returns query results that include special characters for the following languages: Dutch, English, French, German, Italian, and Portuguese. For example, if you query for aqui, you now receive results for both for aqui and aquí.





 21 May 2018 

New German language support for Discovery News : Released [IBM Watson™ Discovery News](https://cloud.ibm.com/docs/discovery?topic=discovery-watson-discovery-news) in one additional language: German (collection_id: news-de). IBM Watson™ Discovery News is also available in English, Korean, and Spanish.





 17 May 2018
[112-Developer-tools.svg](https://cloud.ibm.com/media/docs/images/homepage/112-Developer-tools.svg)](https://developer.ibm.com/depmodels/cloud/gettingstarted/)[Community<br><br>Join the IBM Cloud community and collaborate with others.<br><br>![35-Connectivity.svg](https://cloud.ibm.com/media/docs/images/homepage/35-Connectivity.svg)](https://community.ibm.com/community/user/cloud/home)

 Latest updates 

[View more](https://cloud.ibm.com/docs/overview?topic=overview-whatsnew)12 April 2023 | Specify language support for community-supported products

If you offer a third-party product that is supported by open source communities, you can select the languages in which support is provided when you're onboarding or managing your product in Partner Center. By providing support in multiple languages, your customers can communicate their issues in their preferred language and get support more efficiently.

04 October 2022 | Catalog integration with Virtual Private Cloud custom images

ISV Partners and IBM Cloud customers can now import custom VPC images directly to their account or enterprise, or sell on the IBM Cloud catalog without depending on Terraform.

08 July 2022 | Streamlined process for updating support information in Partner Center

Update support information by editing your published information and requesting an approval. After your changes are approved, you can publish the updates.
For more information, see the following sections:



* [Supported previous-generation language models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-modelsmodels-supported)
* [Language support for customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support)



FISMA support
: Federal Information Security Management Act (FISMA) support is now available for Speech to Text for IBM Cloud Pak for Data. The service is FISMA High Ready.





 28 June 2019 (Version 1.0.0) 

Version 1.0.0 is available
: Version 1.0.0, the initial release of the service, is now available. Speech to Text for IBM Cloud Pak for Data is based on the IBM Watson® Speech to Text service on the public IBM Cloud. Speech to Text for IBM Cloud Pak for Data differs from the public Speech to Text service in the following ways. You might find this information helpful if you are already familiar with the Speech to Text service on the public IBM Cloud.



* Speech to Text for IBM Cloud Pak for Data uses access tokens for authentication. For more information, see the [API & SDK reference](https://cloud.ibm.com/apidocs/speech-to-text).
* The endpoints for Speech to Text for IBM Cloud Pak for Data are specific to your IBM Cloud Pak for Data cluster. For more information, see the [API & SDK reference](https://cloud.ibm.com/apidocs/speech-to-text).
* Speech to Text for IBM Cloud Pak for Data does not perform any request logging. You do not need to use the X-Watson-Learning-Opt-Out request header.
* Speech to Text for IBM Cloud Pak for Data does not support Watson tokens. You cannot use the X-Watson-Authorization-Token request header to authenticate with the service.
For more information, see [Protecting sensitive information in your Watson service](https://cloud.ibm.com/docs/watson?topic=watson-keyservice).









 13 November 2019 

New Seoul location
: You can now create Language Translator instances in the Seoul, South Korea, location. As with other locations, the IBM Cloud Seoul location uses token-based Identity and Access Management (IAM) authentication.





 11 November 2019 

Customization and identification improvements
: Improved custom model training time. Also, Improved language identification accuracy for English text and for text with more than 100 words.

New translation models
: New translation models are now available.



* English to and from Indonesian (en-id and id-en)
* English to and from Irish (en-ga and ga-en)
* English to and from Lithuanian (en-lt and lt-en)
* English to and from Malay (en-ms and ms-en)
* English to and from Thai (en-th and th-en)



For more information, see [List of supported languages](https://cloud.ibm.com/docs/language-translator?topic=language-translator-translation-modelslist-languages-supported). Note that Indonesian cannot be identified by the service's language identification feature.





 21 August 2019 

New translation models
: New translation models are now available:



* English to and from Bulgarian (en-bg and bg-en)
* English to and from Croatian (en-hr and hr-en)
* English to and from Estonian (en-et and et-en)
* English to and from Romanian (en-ro and ro-en)
* English to and from Slovak (en-sk and sk-en)
* English to and from Slovenian (en-sl and sl-en)



New identifiable languages
: The following languages can now be identified by the service:



* Catalan (ca)
* Croatian (hr)
* Irish (ga)
* Malay (ms)
* Maltese (mt)
* Serbian (sr)
* Slovenian (sl)
* Thai (th)







 14 June 2019 

New translation models
This example shows you how to check the language of the input text, and append the language info to the input text string.

In the premessage webhook configuration page, the following values are specified:



* URL: https://us-south.functions.appdomain.cloud/api/v1/web/e97d2516-5ce4-4fd9-9d05-acc3dd8ennn/default/check_language
* Secret: none
* Header name: Content-Type
* Header value: application/json



The premessage webhook calls an IBM Cloud Functions web action name check_language.

The node.js code in the check_language web action looks as follows.

let rp = require("request-promise");

function main(params) {
console.log(JSON.stringify(params))
if (params.payload.input.text !== '') {
// Send a request to the Watson Language Translator service to check the language of the input text.
const options = { method: 'POST',
url: 'https://api.us-south.language-translator.watson.cloud.ibm.com/instances/572b37be-09f4-4704-b693-3bc63869nnnn/v3/identify?version=2018-05-01',
auth: {
'username': 'apikey',
'password': 'nnn'
},
headers: {
"Content-Type":"text/plain"
},
body: [
params.payload.input.text
],
json: true,
};
return rp(options)
.then(res => {
params.payload.context.skills["main skill"].user_defined["language"] = res.languages[0].language;
console.log(JSON.stringify(params))
For a list of supported languages, see [Language support](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-language-support).
6. Optional: You can change the synchronization schedule.

For more information, see [Crawl schedule options](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-collectionscrawlschedule).
7. Specify the URL of the website that you want to crawl.



* If the site you want to crawl requires a login, set Basic authentication to On, add the URL of the page to the Starting URL field, and then click Add.

Add a username and password with access to the site, and then click Save credentials. You can specify only one set of credentials per collection.

For example, you can specify https://cloud.ibm.com as the starting URL and add your IBMid as the credentials.

If you want to start the crawl from a specific section of the site, specify it in the Starting URLs field. The domain name of the subsection must match the domain in the URL you specified earlier.

For example, you might change the starting URL to https://cloud.ibm.com/unifiedsupport/supportcenter.
* For any public web pages that you want to crawl, add the URL for the root page of the website to the Starting URLs field, and then click Add. You can add more than one starting page.

The final forward slash (/) in the URL determines the subtree to crawl. If you specify https://www.example.com/banking/faqs.html, all URLs that begin with https://www.example.com/banking/ are crawled, for example. If you specify https://www.example.com/banking all URLs that begin with https://www.example.com/ are crawled.

By default, the number of consecutive links that the crawl follows from the starting URL is 2. To change the number of hops or to list website sections to exclude from the crawl, click the edit icon.
Dynamic Faceted Search automatically categorizes your search results into intelligence facets without training by understanding how they are used in the sentences. See [Facets in Document retrieval projects](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-facetsfacetdr).

New reusable components
: You no longer need to build a Discovery application from scratch. We now ship out of the box with reusable, open source, React components. As you configure your Discovery application, you are using the real components. From there you simply deploy to get a custom Discovery application. See [Building and deploying components](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-deploy).

New Domain Vocabulary feature
: You can build a facet for your users without a Dictionary. Use Domain Vocabulary to build a powerful facet with our understanding of how the data is used in as little as 5 minutes. See [Facets](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-facets).

New relevancy training
: You can train at a project level. Discovery ranks the best answer regardless of the data source/collection. See [Improving result relevance with training](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-train).

New built-in spelling corrector
: Discovery has spelling suggestions built in. See [Parameters descriptions](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-query-referenceparameter-descriptions).

Improved Autocomplete
: Discovery includes autocomplete (type-ahead) for searches, as well as a reusable component for providing this feature to your end users.

New support for 12 languages
: Language support for Discovery is now available in 12 additional languages. For the complete list, see [Language support](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-language-support).

Cloud Object Storage connector limitation