vania-janet/multiturn-rag-retrieval-data huggingface dataset:
* body - If the body of the POST request uses form encoding (UTF-8), then you can create layer 7 rules to route traffic based on the parameter name and value in the body. The Content-Type in the request is ignored.



If you use these new rule types, be aware that existing client applications will be exposed to those new values in the existing properties. To avoid disruption, check that client applications are written to gracefully handle unexpected values for these properties before using these new rule types for an application load balancer.







 19 March 2021 



 For all version dates 

Bring your own license. You can now [bring your own license](https://cloud.ibm.com/docs/vpc?topic=vpc-byol-vpc-about) (BYOL) for custom images that you create and import to IBM Cloud VPC. When you import a custom image, you can choose from new byol Red Hat Enterprise Linux (RHEL) and Windows operating systems.

A new dedicated_host_only property has been added to operating system resources. Any instance with a boot volume created from an image with operating_system.dedicated_host_only set to true must be placed on a dedicated host (or into a dedicated host group). Because Windows BYOL images have dedicated_host_only set to true, they must be placed on a dedicated host (or into a dedicated host group). There are no restrictions on placing instances using RHEL BYOL images.

Every operation that returns an OperatingSystem resource now includes a dedicated_host_only property.







 9 March 2021 



 For all version dates 

Additional VPN for VPC IKEv2 encryption/hash/Diffie Hellman (DH) group support. For enhanced security, VPN for VPC now supports SHA2-512 (a Secure Hash Algorithm) and DH group 19 (a 256-bit elliptic curve algorithm) to generate a symmetric key.

If you use these new algorithms, be aware that existing client applications will be exposed to those new values in the existing authentication_algorithm and dh_group properties. To avoid disruption, check that client applications are written to gracefully handle unexpected values for these properties before using these new algorithms.

The following VPN for VPC methods have been updated:
Specify a name for your action. Action names must be unique within namespaces.
2. Specify a package for your action. [Packages](https://cloud.ibm.com/docs/openwhisk?topic=openwhisk-pkg_ov) group actions and feeds together. You can select an existing package or create a new one.
3. Specify a runtime for your action. Java, .Net, and Docker actions can be [created from the CLI only](https://cloud.ibm.com/docs/openwhisk?topic=openwhisk-prepprep_docker). You can change the runtime for your action after you create it.
4. Click Create.



2. Paste in your code. Note that code field toggles between Edit and View modes. You can test your code by clicking Invoke.



From the Actions page, you can add parameters, change the runtime, create endpoints, and more.





 Creating actions from binaries 

You can create and deploy an executable that runs inside the standard Docker action SDK as an action. By creating this type of action, you can develop by using Rust or even C and C++, so that you can use the right language for the task at hand while you build complex serverless applications. These types of actions can also be created as [web actions](https://cloud.ibm.com/docs/openwhisk?topic=openwhisk-actions_web).

The executable must conform to the following conventions:



* The program can accept only a single command-line argument as input. The argument is a JSON object that is encoded as a string. The object represents the input argument to the function.
* The program must return a JSON object as a JSON formatted string, sent to stdout as the final log line before the program completes.
* The program can also log to stdout and stderr.
* The program must be called exec and should be self-contained or all dependencies must be packaged with it.
Road 
 Rocket 
 RocketEngine 
 RocketEngineFuel 
 RocketFuel 
 RocketFunction 
 RocketManufacturer 
 Saint 
 Satellite 
 School 
 SchoolDistrict 
 SchoolMascot 
 SchoolNewspaper 
 SchoolSportsTeam 
 Scientist 
 ShipBuilder 
 ShoppingCenter 
 ShortStory 
 SkiArea 
 Skyscraper 
 SoccerClub 
 Software 
 SoftwareDeveloper 
 SoftwareLicense 
 Soundtrack 
 SpaceAgency 
 Spacecraft 
 SpaceMission 
 Spaceport 
 Sport 
 SportsAssociation 
 SportsEquipment 
 SportsLeagueChampionship 
 SportsLeagueChampionshipEvent 
 SportsLeagueDraft 
 SportsOfficial 
 SportsTeam 
 Stadium 
 Star 
 StarSystem 
 StarSystemBody 
 Station 
 Supercouple 
 Symptom 
 Synthesizer 
 Telescope 
 TelescopePlatform 
 TelevisionShow 
 TennisPlayer 
 TennisTournament 
 Theater 
 TheaterCharacter 
 TheaterProduction 
 TopLevelDomainRegistry 
 TouristAttraction 
 Tower 
 TradeUnion 
 TransitLine 
 TransportOperator 
 TransportTerminus 
 TropicalCyclone 
 TVActor 
 TVCharacter 
 TVCrewRole 
 TVEpisode 
 TVNetwork 
 TVPersonality 
 TVProducer 
 TVSeason 
 TVWriter 
 TypeOfPlaceOfWorship 
 UnfinishedWork 
 UnitOfMass 
 UnitOfVolume 
 University 
 U.S.Congressperson 
 Vein 
 VideoGame 
 VideoGameDesigner 
 VideoGameDeveloper 
 VideoGameEngine 
 VideoGamePlatform 
 VideoGamePublisher 
 VisualArtist 
 WebBrowserExtension 
 Website 
 WineProducer 
 WineRegion 
 WorkOfFiction 
 Writer 







 Relations entity types 

For languages that use the Version 1 entity type system that also support relations, relations results contain entity types that are different from the entity types returned in entities results.
Collecting information from your customers 

Many actions require multiple steps to collect all of the information that is required to complete the customer's request. When a step asks the customer for more information, the customer response type defines what type of response is expected.

In the step editor user interface, the middle portion of the step configuration defines the interaction between the assistant and the customer.

Zoom

![Step editor with middle part highlighted](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/step-assistant-says.png)

Step editor

The Assistant says field specifies the output that the assistant sends to the customer. If this output is a question that the user is expected to answer, that answer might be a number, a date, a name, or something else. You use the Define customer response field to specify what type of response is expected, based on the kind of information the assistant is asking for and how the customer is expected to specify it.



 Choosing a response type 

To choose the customer response type for a step, click Define customer response to expand the field. You can then select one of the following response types:



Response types

 Response type Description Example input 

 [Options](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-collect-infocustomer-response-type-options) A list of predefined choices that customers can select from. At run time, the web chat integration shows an options response as a set of clickable buttons or as a drop-down list, depending on the number of choices. SmallMediumLarge 
 [Confirmation](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-collect-infocustomer-response-type-confirmation) A choice of either Yes or No. At run time, the web chat integration shows the Yes and No options as clickable buttons. Yes, No
Not all rule types support all comparison types. For example, if you are using FILE_TYPE, it is best to use comparison types REGEX and ENDS_WITH.





 Layer 7 rule properties 



 Property Description 

 Type Specifies the type of rule. Rule types can be HOST_NAME, FILE_TYPE, HEADER, COOKIE, or PATH. 
 Comparison Type Comparison types are used in association with the rule type, key, and value to define a rule and classify traffic. Comparison types can be: REGEX, STARTS_WITH, ENDS_WITH, CONTAINS, and EQUAL_TO. 
 Key The description key for the rule types HEADER and COOKIE. 
 Value For the rule types HEADER and COOKIE, the value is compared against the key. 
 Invert If you set the value to 1, the value of this L7 rule comparison is set to true whenever the specified rule is not matched. 
 Layer 7 Policy ID The unique identifier of the policy to which the rules are attached.
"name": "endpointType",
"value": "private"
}
]
}
]
}





 Creating rules from the CLI 



1. To create rules from the CLI, [install the CBR CLI plug-in](https://cloud.ibm.com/docs/cli?topic=cli-cbr-plugininstall-cbr-plugin).
2. You can use the ibmcloud cbr rule-create[command](https://cloud.ibm.com/docs/cli?topic=cli-cbr-plugincbr-cli-rule-create-command) to create CBR rules. For more information, see the CBR [CLI reference](https://cloud.ibm.com/docs/cli?topic=cli-cbr-plugincbr-zones-cli). Note that the service_name for Red Hat OpenShift on IBM Cloud is containers-kubernetes. To find a list of service names, run the ibmcloud cbr service-ref-targets command. To find a list of API types for a service, run the ibmcloud cbr api-types --service-name SERVICE command.



Example command to create a rule that uses the addresses key and the cluster API type and the ipAddress type.

ibmcloud cbr rule-create my-rule-1 --service-name containers-kubernetes --api-type crn:v1:bluemix:public:containers-kubernetes::::api-type:cluster --zone-id ZONE-ID

The following command creates a rule that protects the CLUSTER-ID cluster. Only resources in the NETWORK-ZONE-ID network zone can access the cluster. This rule includes both the cluster and management API types.

ibmcloud cbr rule-create my-rule-2 --service-name containers-kubernetes --service-instance CLUSTER-ID --zone-id NETWORK-ZONE-ID
Japanese [Version 2](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-2) 
 Korean [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1) 
 Brazilian Portuguese [Version 2](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-2) 
 Russian [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1) 
 Spanish [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1) 
 Swedish [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1) 







 Entity type systems for version 2018-03-16 

The following entity type systems are used when you set the version parameter to 2018-03-16.



 Language Entity type system 

 English [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1) 
 French [Version 2](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-2) 
 German [Version 2](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-2) 
 Italian [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1) 
 Japanese [Version 2](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-2) 
 Korean [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1) 
 Brazilian Portuguese [Version 1](https://cloud.ibm.com/docs/discovery?topic=discovery-entity-types-version-1)
[Overview of the process to build a machine learning model](https://cloud.ibm.com/docs-content/v1/content/148d3bd95f946aa1bb53ea1540475f522e6b61c9/watson-knowledge-studio-data/images/wks-ovw-anno.svg) Figure 1. Overview of the process to build a machine learning model



1. Based on a set of domain-specific source documents, the team creates a type system that defines entity types and relation types for the information of interest to the application that will use the model.
2. A group of two or more human annotators annotates a small set of source documents to label words that represent entity types, to identify relation types where the text identifies relationships between entity mentions, and to define coreferences, which identify different mentions that refer to the same thing, that is, the same entity. Any inconsistencies in annotation are resolved, and one set of optimally annotated documents is built, which forms the ground truth.
3. Knowledge Studio uses the ground truth to train a model.
4. The trained model is used to find entities, relations, and coreferences in new, never-seen-before documents.



See [Creating a machine learning model](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-ml_annotator) for more details.





 Build a rule-based model 

Knowledge Studio provides a rules editor that simplifies the process of finding and capturing common patterns in your documents as rules. You can then create a model that recognizes the rule patterns, and deploy it for use in other services.

See [Creating a rule-based model](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-rule-annotator) for more details.







 Analyze text with advanced rules 

The advanced rules feature is Beta. The feature is in a trial stage of development and is not recommended for use in production environments.
"type": "bool",
"secure": false,
"description":"<description>"
},
{
"name": "<variable_name_x>",
"value": "<variable_value_x>",
"type": "list(string)",
"secure": false,
"description":"<description>"
},
{
"name": "<variable_name_x>",
"value": "<variable_value_x>",
"type": "map(number)",
"secure": false,
"description":"<description>"
},
{
"name": "<variable_name_x>",
"value": "<variable_value_x>",
"type": "tuple(string, list(string), number, bool])",
"secure": false,
"description":"<description>"
},
{
"name": "<variable_name_x>",
"value": "<variable_value_x>",
"type": "any",
"secure": false,
"description":"<description>"
}
]
}
]
}
Show more



JSON file component description

 Parameter Required / Optional Description 

 workspace_name Optional Enter a name for your workspace. The maximum length of character limit is set to less than 1 MB. For more information, see [Designing your workspace structure](https://cloud.ibm.com/docs/schematics?topic=schematics-workspaces-planstructure-workspace). 
 terraform_version Optional The Terraform version that you want to use to run your Terraform code.
Currently, you can import a custom image in the following formats: .ova, .ova.gz, .tar, .tar.gz and .tgz.
* What are the available storage types in the storage area network (SAN)?

All regions use Tier 1 or Tier 3 storage types. The Tier 1 storage type is best for customers who require higher throughput. Customers who do not require exceptionally high throughput and are looking to minimize costs want to select Tier 3. A VM cannot have disks from both storage types while provisioning. But, you can add a volume of the other storage types after the VM has been provisioned. For more information, see [Storage tiers](https://cloud.ibm.com/docs/power-iaas?topic=power-iaas-about-virtual-serverstorage-tiers).

If you previously deployed a VM on an old storage type (SSD or standard), no action is required. Your VM continues to run by using the old storage type. You can also add new disks from those legacy tiers.

The boot image storage type is predefined and cannot be chosen.
* How do I extend my AIX rootvg?

By default, the system deploys 20 GBs for the AIX rootvg. You can extend the AIX rootvg by using the [extendvg](https://www.ibm.com/support/knowledgecenter/ssw_aix_72/e_commands/extendvg.html) command to add a physical volume.
* What's the difference between capped and uncapped shared processor performance? How do they compare to dedicated processor performance?

When deploying a VM, customers can choose between dedicated, capped shared, or uncapped shared processors for their virtual CPUs (vCPUs). The following list provides a simplified breakdown of their differences:



* Dedicated: resources are allocated for a specific client (used for specific third-party considerations)
* Uncapped shared: shared among other clients
* Capped shared: shared, but resources do not expand beyond those that are requested (used mostly for licensing)
"value": "169.23.56.234"
    },
    {
      "type": "ipRange",
      "value": "169.23.22.0-169.23.22.255"
    },
    {
      "type": "subnet",
      "value": "192.0.2.0/24"
    },
    {
      "type": "vpc",
      "value": "crn:v1:bluemix:public:is:us-south:a/12ab34cd56ef78ab90cd12ef34ab56cd::vpc:r134-d98a1702-b39a-449a-86d4-ef8dbacf281e"
    }
  ],
  "excluded": [
    {
      "type": "ipAddress",
      "value": "169.23.22.127"
    }
  ]
}
Show more

You can determine which services are available by checking for [reference targets](https://cloud.ibm.com/apidocs/context-based-restrictionslist-available-serviceref-targets).

After creating zones, you can also [update](https://cloud.ibm.com/apidocs/context-based-restrictionsreplace-zone) and [delete](https://cloud.ibm.com/docs/account?topic=account-context-restrictions-remove) them.





 Create Network Zones using the CBR UI 

With the prerequisites and requirements in place, you can follow the steps to [create zones in the UI](https://cloud.ibm.com/docs/account?topic=account-context-restrictions-createnetwork-zones-create).

Instead of creating a zone by using UI inputs, you can use the JSON code form to directly enter JSON to create a zone by clicking Enter as JSON code.
"type":"TXT",
"rdata": {
    "text": "text information"
}
}



* For type MX: Extra required fields are name, rdata.



* name: Resource record name.
* rdata: The content of type-MX resource record.



* exchange: Hostname of Exchange server.
* preference: Preference of the MX record





* Extra optional fields are ttl.



* ttl: Time to live in seconds. Default value is 900. Valid values: 60, 120, 300, 600, 900, 1800, 3600, 7200, 18000, 43200.





Sample JSON data:

{
   "name": "testMX",
   "type": "MX",
   "rdata": {
        "preference": 10,
        "exchange": "mailserver.example.com"
    }
}



* For type SRV: Extra required fields are name, rdata, service, protocol.



* name: Resource record name.
* rdata: The content of type-SRV resource record.



* priority: Priority of the SRV record.
* weight: Weight of distributing queries among multiple target servers.
* port: Port number of the target server.
* target: Hostname of the target server.



* service: The symbolic name of the desired service, start with an underscore _.
* protocol: The symbolic name of the desired protocol.



* Extra option fields are ttl.



* ttl: Time to live in seconds. Default value is 900. Valid values: 60, 120, 300, 600, 900, 1800, 3600, 7200, 18000, 43200.





Sample JSON data:

{
"type": "SRV",
    "name": "testSRV",
    "rdata": {
        "priority": 100,
        "weight": 100,
        "port": 8000,
        "target": "siphost.com"
    },
    "service": "_sip",
"options": {
"model": "contract"
}
}
]
}
Show more

If you want to create a custom configuration file, configure your collection to meet the following requirements:



* PDF conversion settings are ignored if specified.
* WORD conversion settings can be omitted as Microsoft Word files cannot be ingested when Element Classification is specified.
* html normalization settings are ignored if specified.
* Document segmentation is not supported when the elements enrichment is specified.
* In the Discovery configuration, the html field must be enriched by the elements enrichment and the model specified as contract. In the following example, the destination_field is enriched_html, but any valid name can be used:



"enrichments": [
{
"source_field": "html",
"destination_field": "enriched_html",
"enrichment": "elements",
"options": {
"model": "contract"
}
}
]

After selecting the Default Contract Configuration in the tooling, you can upload your documents. If you are unfamiliar with creating collections and uploading documents, see [Getting started with the tooling](https://cloud.ibm.com/docs/discovery?topic=discovery-getting-started).





 Classified elements 

The Element Classification enrichment is deprecated and will no longer be available, effective 10 July 2020.

After a document is indexed with Element Classification, it is returned with an elements array as part of the searchable document.

Each object in the elements array describes an element of the contract that Discovery identified. The following code represents a typical element:

{
"location" : {
"begin" : 134323,
"end" : 135109
},
"text" : "9. In the event that the Participant's total vested account balance is determined to be less than or equal to $2,000.00 as of the date that the Order is received, the parties will be informed in writing that the QDRO determination fee may potentially liquidate the account.",
"types" : [ {
"label" : {
"type": "list(string)",
"secure": false,
"description":"<description>"
},
{
"name": "<variable_name_x>",
"value": "<variable_value_x>",
"type": "map(number)",
"secure": false,
"description":"<description>"
},
{
"name": "<variable_name_x>",
"value": "<variable_value_x>",
"type": "tuple(string, list(string), number, bool])",
"secure": false,
"description":"<description>"
},
{
"name": "<variable_name_x>",
"value": "<variable_value_x>",
"type": "any",
"secure": false,
"description":"<description>"
}
]
}
]
}
Show more



JSON file component description

 Parameter Required / Optional Description 

 workspace_name Optional Enter a name for your workspace. The maximum length of character limit is set to 1 MB. For more information, see [Designing your workspace structure](https://cloud.ibm.com/docs/schematics?topic=schematics-workspace-setupstructure-workspace). 
 terraform_version Optional The Terraform version that you want to use to run your Terraform code. Enter terraform_v1.1 to use Terraform version 1.1,terraform_v1.0 to use Terraform version 1.0, and similarly, terraform_v0.15, terraform_v0.14, terraform_v0.13, terraform_v0.12. For example, when you specify terraform_v1.1 means users can have template that are of Terraform v1.1.0, v1.1.1, or v1.1.2, so on.
By using the more generic v2 Entities type system together with other features, such as Concepts and Categories, you can achieve similar outcomes with more flexibility. For more information about v2 entity types, see [Entity types (Version 2)](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-entity-types-version-2).





 9 June 2023 

Retired Custom Sentiment Feature
: The Custom Sentiment feature is retired. Custom sentiment models can no longer be created nor can they be used with Analyze API calls. To ensure we continue providing our clients with robust and powerful text classification capabilities, IBM recently announced the general availability of a new [single-label text classification capability](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-classifications). This new feature includes extended language support and training data customizations suited for building a custom sentiment classifier.





 16 February 2023 

Updated training process for Custom Classifications
: Updates were made to the Custom Classifications training process including improvements in the preprocessing stage, updating underlying libraries, and fixing minor bugs.





 2 February 2023 

Sentiment support for additional languages
: Support for sentiment is now available, for all public service instances, for the following languages: Czech, Danish, Finnish, Hebrew, Hindi, Norwegian Bokmål, Norwegian Nynorsk, Polish, Romanian, Slovak, Swedish, Turkish. For details, see [Language support](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-language-support).





 11 January 2023 

Improved English and Korean Entities Model
: Fixed a bug for English and Korean models using Version 2 Entity type system where not all entities are returned properly.





 3 November 2022 

Improved Error Handling and Validation for Sentiment and Custom Sentiment
: If a request contains both an error in the sentiment feature and a valid feature request for another feature, the response returns a 200 with a warning for the sentiment feature.

Requests for Custom Sentiment that include at least one target found in the document will now return a 200 with sentiment analysis for the found targets.