vania-janet/multiturn-rag-retrieval-data huggingface dataset:
* UI
* CLI
* API
* Terraform







 Provisioning 

To create an IBM Cloud® Databases deployment, first create an IBM Cloud service instance. The service type is determined by the service ID. Specify the appropriate service ID when you create a new Cloud Databases deployment.

Provision a deployment by going to the service's catalog page, or by specifying the service ID in the CLI, API, or Terraform.



Table 1. Cloud Databases deployments

 Deployment Type Service ID 

 [IBM Cloud® Databases for DataStax](https://cloud.ibm.com/catalog/services/databases-for-cassandra) databases-for-datastax 
 [IBM Cloud® Databases for Elasticsearch](https://cloud.ibm.com/catalog/services/databases-for-elasticsearch) databases-for-elasticsearch 
 [IBM Cloud® Databases for EnterpriseDB](https://cloud.ibm.com/catalog/services/databases-for-enterprisedb) databases-for-enterprisedb 
 [IBM Cloud® Databases for etcd](https://cloud.ibm.com/catalog/services/databases-for-etcd) databases-for-etcd 
 [IBM Cloud® Databases for MongoDB](https://cloud.ibm.com/catalog/services/databases-for-mongodb) databases-for-mongodb 
 [IBM Cloud® Databases for PostgreSQL](https://cloud.ibm.com/catalog/services/databases-for-postgresql) databases-for-postgresql 
 [IBM Cloud® Databases for Redis](https://cloud.ibm.com/catalog/services/databases-for-redis) databases-for-redis 
 [IBM Cloud® Databases for MySQL](https://cloud.ibm.com/catalog/services/databases-for-mysql) databases-for-mysql 
 [IBM Cloud® Messages for RabbitMQ](https://cloud.ibm.com/catalog/services/messages-for-rabbitmq) messages-for-rabbitmq 





 Using the catalog
Before you upload documents that include ground truth into a new workspace, you must download the type system from the old workspace and upload it into the new workspace. The type system and documents must originate from the same Knowledge Studio workspace, and the type system must exist in the new workspace before you upload the ground truth annotations.

To upload documents, open the Document Sets tab in the new workspace, click Upload Document Sets and select the corpus ZIP file that you downloaded. Specify whether you want the uploaded documents to include or exclude the ground truth annotations before you click Upload. Only annotations that were promoted to ground truth before the documents were downloaded will be uploaded.

Related concepts:

[Types of artifacts](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-artifacts)

[Adding documents for annotation](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-documents-for-annotation)

[Adding documents for defining rules](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-wks_rule_anno_add)
Before you upload documents that include ground truth into a new workspace, you must download the type system from the old workspace and upload it into the new workspace. The type system and documents must originate from the same Knowledge Studio workspace, and the type system must exist in the new workspace before you upload the ground truth annotations.

To upload documents, open the Document Sets tab in the new workspace, click Upload Document Sets and select the corpus ZIP file that you downloaded. Specify whether you want the uploaded documents to include or exclude the ground truth annotations before you click Upload. Only annotations that were promoted to ground truth before the documents were downloaded will be uploaded.

Related concepts:

[Types of artifacts](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-artifacts)

[Adding documents for annotation](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-documents-for-annotation)

[Adding documents for defining rules](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-wks_rule_anno_add)
You can create only RSH SSH key types. To use an Ed25519 SSH key, that SSH key must be imported. For more information, see [Importing an SSH key by using the UI](https://cloud.ibm.com/docs/vpc?topic=vpc-managing-ssh-keys&interface=uiimporting-ssh-keys-ui).



1. In [IBM Cloud console](https://cloud.ibm.com/login), go to menu icon ![Menu icon](https://cloud.ibm.com/docs-content/v1/content/f02b9c9adcbb7328d95a45e105cec371d50f15eb/icons/icon_hamburger.svg) > VPC Infrastructure > Compute > SSH keys.
2. Click Create and enter the information that is in Table 1.



Table 1. Creating an SSH key for VPC selections

 Field Value 

 Location Locations are composed of regions (specific geographic areas) and zones (fault-tolerant data centers within a region). Select the location where you want to create your SSH key. 
 Name A name is required for your SSH key. 
 Resource group Select a resource group for the SSH key. 
 Tags You can assign a user tag to the SSH key so that you can easily filter a list of SSH keys. For more information, see [Working with tags](https://cloud.ibm.com/docs/account?topic=account-tag&interface=ui). 
 Access management tags Access management tags help you apply flexible access policies on specific resources. For more information, see the [Controlling access to resources by using tags](https://cloud.ibm.com/docs/account?topic=account-access-tags-tutorial) UI tutorial. 
 SSH key type The default value is rsa. 



3. Select Generate a key pair for me.
4. Click Save private key.
5. Click Save public key.
6.
This type must match the vlan.

--vlan VLAN_ID
: The ID of the VLAN to create the ALB on. This VLAN must match the ALB type and must be in the same zone as the ALB that you want to create.

--zone ZONE
: The zone to create the ALB in.

--ip IP
: Optional: An IP address to assign to the ALB. This IP must be on the vlan that you specified and must be in the same zone as the ALB that you want to create. This IP address must not be in use by another load balancer or ALB in the cluster. To see the IP addresses that are currently in use, run oc get svc --all-namespaces.

--version IMAGE_VERSION
: Optional: The version of the image that you want the ALB to run. To list available versions, run ibmcloud oc ingress alb versions. To specify a version other than the default, you must first disable automatic updates by running the ibmcloud oc ingress alb autoupdate disable command. If you omit this option, the ALB runs the default version of the Kubernetes Ingress image type.

-q
: Optional: Do not show the message of the day or update reminders.



 Example ingress alb create classic command 

ibmcloud oc ingress alb create classic --cluster mycluster --type public --vlan 2234945 --zone dal10 --ip 1.1.1.1 --version 1.1.2_2507_iks







 ibmcloud oc ingress alb disable 

Virtual Private Cloud

Classic infrastructure

Disable an ALB in your cluster. The ALB and its pods still exist, but stop routing traffic to your apps.

The previous alias for this command, ibmcloud oc ingress alb configure, is deprecated.

ibmcloud oc ingress alb disable --alb ALB_ID --cluster CLUSTER [-q]

Minimum required permissions
For more information on these response types, see [Response types reference](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-response-types-reference).



If you want to use the same action for an assistant that you deploy to many different platforms, add custom responses per integration type. You can add a conditioned response that tells the assistant to show the response only when the SMS integration is being used.

For reference documentation, see [SMS integration reference](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-sms-reference).





 Troubleshooting 

Find solutions to problems that you might encounter while using the integration.



* If you get a Forbidden message, it means the phone number that you specified when you configured the integration cannot be verified. Make sure the number fully matches the SMS phone number.







 Migrating from Voice Agent with Watson 

If you created an IBM® Voice Agent with Watson service instance in IBM Cloud to enable customers to exchange text messages with an assistant, use the SMS integration instead.

The SMS integration provides a more seamless integration with your assistant and supports as many phone numbers as needed. However, the integration currently does not support the following functions:



* Starting an SMS-only interaction with an outgoing text
* Configuring backup locations
* Reviewing the usage summary page. Use IBM Log Analysis instead.



To migrate from Voice Agent with Watson to the Watson Assistant SMS integration, complete the following step:



1. Do one of the following things:



* If your Voice Agent with Watson service instance uses an SMS service provider other than Twilio or IntelePeer, you cannot continue to use it. You must create an SMS account with Twilio or IntelePeer first.
See [ibmcloud ce secret](https://cloud.ibm.com/docs/codeengine?topic=codeengine-clicli-secret-create) commands. Use the --format option to specify the category of secret, such as basic_auth, generic, ssh, tls, or registry. The default value for the --format option is generic.

By using the secret create command, you can create and manage various secret formats. For descriptions of the various secret formats, see [What kind of secrets can I create in Code Engine?](https://cloud.ibm.com/docs/codeengine?topic=codeengine-configmap-secretsecret-categories)

Learn how to create the following types of secrets with the CLI,



* [Basic authentication](https://cloud.ibm.com/docs/codeengine?topic=codeengine-configmap-secretsecret-create-cli-basicauth)
* [Generic](https://cloud.ibm.com/docs/codeengine?topic=codeengine-configmap-secretsecret-create-cli-generic)
* [Registry](https://cloud.ibm.com/docs/codeengine?topic=codeengine-configmap-secretsecret-create-cli-registry)
* [SSH](https://cloud.ibm.com/docs/codeengine?topic=codeengine-configmap-secretsecret-create-cli-ssh)
* [TLS](https://cloud.ibm.com/docs/codeengine?topic=codeengine-configmap-secretsecret-create-cli-tls)





 Creating a basic authentication secret with the CLI 

A basic authentication secret contains a username and password key and is used to access a service that requires basic HTTP authentication. The following example creates a basic authentication secret with credentials for myusername and the associated password is provided in a file on the local workstation
--type TYPE
: The protocol to use for the health check: HTTP, HTTPS, or TCP. Default: HTTP

--method METHOD
: The method to use for the health check. Default for typeHTTP and HTTPS: GET. Default for typeTCP: connection_established.

--path PATH
: When type is HTTPS: The endpoint path to health check against. Default: /

--timeout TIMEOUT
: The timeout, in seconds, before the IP is considered unreachable. The health check waits the number of seconds specified in the interval parameter before trying to reach the IP again. The value must be an integer in the range 1 - 15. Default: 5

--retries RETRIES
: When a timeout occurs, the number of retries to attempt before the unreachable IP is considered unhealthy. Retries are attempted immediately. The value must be an integer in the range 1 - 5. Default: 2

--interval INTERVAL
: The interval, in seconds, between each health check. Short intervals might improve failover time, but increase load on the IPs. The value must be an integer in the range 10 - 3600 and must be greater than (RETRIES + 1)* TIMEOUT. Default: 60

--port PORT
: The port number to connect to for the health check. When type is TCP, this parameter is required. When type is HTTP or HTTPS, define the port only if you use a port other than 80 for HTTP or 443 for HTTPS. Default for TCP: 0. Default for HTTP: 80. Default for HTTPS: 443.

--header HEADER
: Required when type is HTTP or HTTPS: HTTP request headers to send in the health check, such as a Host header. The User-Agent header can't be overridden. This option is valid only for type 'HTTP' or 'HTTPS'. To add more than one header to the requests, specify this option multiple times. This option accepts values in the following format: --header Header-Name=value.
The clone, fork, and new types instruct the Git tool integration to create the target repo (repo_url) on the premise that this repo does not exist. If the tool integration finds the target repo, it fails by design.

 How to fix it 

Change the type from clone, fork, or new to clone_if_not_exists, fork_if_not_exists, or new_if_not_exists. These types instruct the Git tool integration to create the target repo if it does not exist, or to use the target repo as-is if it does exist.

Although you can use other methods to resolve this error, these methods are not recommended because you might lose information. These methods also might require changes to your Terraform that are not good practices.



* Change repo_url to a repo that is created when you apply your Terraform again. Changing a Terraform resource after the initial creation to avoid errors during subsequent updates is an anti-pattern. This method also leaves the previously created repos intact, but no longer bound to the toolchain.
* Change type to existing, and then apply your Terraform again. Changing a Terraform resource after the initial creation to avoid errors during subsequent updates is an anti-pattern.
* Manually delete the target repo, and then apply your Terraform again. Manual changes between otherwise automated Terraform operations are not recommended. If you delete the repo, the deletion cannot be undone, and can cause permanent data loss.
* Change the template_source_data_request_model['type'] variable to the Terraform version that you are using to create IBM Cloud resources such as terraform_v0.14. Ensure that your Terraform templates are compatible with the version that you are mentioning in this field.
* Provide your GitHub or GitLab Repository HTTPS URL where your Terraform files reside in the template_repo_request_model['url'] variable. If you are using the [public repository](https://github.com/IBM-Cloud/hpc-cluster-openshift) that is provided by IBM Cloud, then set this variable as template_repo_request_model['url'] = 'https://github.com/IBM-Cloud/hpc-cluster-openshift'; otherwise, set it to the private repository you are using.



4. Inside the schematics_service.create_workspace function, provide the following parameters:



* Provide an optional description.
* Provide a name to identify your Schematics workspace, for example, terraform-dev-workspace.
* Change the type parameter to the Terraform version that you are using to create IBM Cloud resources, for example, terraform_v0.14.
* Change the location to a region where your Schematics workspace needs to be created, for example, us-south.
* Change the resource group to the resource group where your resources should be grouped, for example, Default for a default resource group.
* If you are using a private GitHub repository, provide your personal GitHub access token that you set up in [Setting up the IBM Cloud Schematics](https://cloud.ibm.com/docs/hpc-openshift?topic=hpc-openshift-setting-up-api) prerequisites in the x_github_token= "<github-api-token>" parameter. If you are using the public repository that is provided by IBM Cloud, you do not need to specify this parameter.
* Optional: Provide the tags if you want to filter resources by using the tag.



5.
For more information, see [Request logging](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-data-securitydata-security-request-logging).







 Creating a custom model 

To create a new custom model, use the POST /v1/customizations method. A new model is always empty when you first create it. You must use other methods to populate it with word/translation pairs. The new custom model is owned by the service instance whose credentials are used to create it. For more information, see [Ownership of custom models](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customModelscustomOwner).

You pass the following attributes as a JSON object with the body of a POST /v1/customizations request:

name (required string)
: A user-defined name for the new custom model. Use a localized name that matches the language of the custom model and describes the domain of the model, such as Medical custom model or Legal custom model.



* Include a maximum of 256 characters in the name.
* Do not use backslashes, slashes, colons, equal signs, ampersands, or question marks in the name.
* Use a name that is unique among all custom models that you own.



language (optional string)
: An identifier for the language of the custom model. The default is en-US for US English. The custom model can be used with any voice that is available in the specified language. For example, a custom model that is created for the en-US language can be used with any US English voice. It cannot, however, be used with an en-GB voice.

description (optional string)
: A recommended description of the new custom model.



* Use a localized description that matches the language of the custom model.
* Include a maximum of 128 characters in the description.



The following example example creates a new US English custom model named Test. The required Content-Type header identifies the type of the input as application/json.

IBM Cloud
Categories type system (Version 1) 



 Categories returned prior to version date 2021-08-15 

There is a [newer Categories model (Version 2)](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-categories-hierarchy) that is recommended if you are starting afresh with Natural Language Understanding

Categories stock models released prior to Natural Language Understanding version 2021-08-15 use the Alchemy taxonomy. You can download a spreadsheet with this information here: [XLSX ![External link icon](https://cloud.ibm.com/docs-content/v1/content/icons/launch-glyph.svg)](https://github.com/watson-developer-cloud/doc-tutorial-downloads/blob/master/natural-language-understanding/categories-hierarchy.xlsx).



 LEVEL 1 LEVEL 2 LEVEL 3 LEVEL 4 LEVEL 5 

 art and entertainment books and literature best-sellers 
 art and entertainment books and literature children's books 
 art and entertainment books and literature e-books 
 art and entertainment books and literature fan fiction 
 art and entertainment books and literature magazines 
 art and entertainment books and literature mythology 
 art and entertainment books and literature non-fiction 
 art and entertainment books and literature poetry 
 art and entertainment books and literature reference books 
 art and entertainment books and literature romance novels 
 art and entertainment books and literature science fiction 
 art and entertainment books and literature textbooks 
 art and entertainment books and literature 
 art and entertainment celebrity fan and gossip 
 art and entertainment comics and animation anime and manga 
 art and entertainment comics and animation cartoons 
 art and entertainment comics and animation comics 
 art and entertainment dance ballet 
 art and entertainment dance ballroom dance 
 art and entertainment dance belly dance 
 art and entertainment dance modern dance 
 art and entertainment dance pole dancing 
 art and entertainment dance 
 art and entertainment humor 
 art and entertainment movies film festivals and awards 
 art and entertainment movies and tv action 
 art and entertainment movies and tv animated 
 art and entertainment movies and tv bollywood 
 art and entertainment movies and tv children's 
 art and entertainment movies and tv classics silent films 
 art and entertainment movies and tv classics
Click to open the NeuralSeek search action that you just added to the assistant.
7. Add the following user example queries to the first step in the action:

What Watson Discovery project types are available and what do they do?

What external data sources are supported by Watson Discovery?

Can I add a custom dictionary to Watson Discovery?

How do I use the Content Mining application?

When should I add query expansions to my project?

Which file types support Smart Document Understanding models?

Can I enable optical character recognition for all file types?

Does my data have to be written in English?

Watson Assistant uses the sample questions to recognize the types of user questions it should route to this action.
8. Click to open Step 3 for editing.

In the And then section, click Edit extension.

Choose NeuralSeek, and then click Apply.

Zoom

![Shows the extension setup page](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/tut-neural-setup.png)

Figure 14. Set up the NeuralSeek extension
9. Click to open Step 6 for editing.

This step shows a link that users can click to get more information. We want this link to go directly to the product documentation on the IBM Cloud Docs site.

Change the hypertext reference in the anchor HTML element to contain the following URL:

<a href="https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-about" target="_blank">

![Shows the extension setup page](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/tut-neural-edit-url.png){: caption="Figure 15.
A set of annotated documents that can be used to train machine learning models. See also [blind data](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-glossarygloss_B) and [testing data](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-glossarygloss_T).
* true negative

An answer or annotation that is actually incorrect and is predicted to be incorrect.
* true positive

An answer or annotation that is actually correct and is predicted to be correct.
* type system

The type system defines the types of objects that can be discovered in a document. The type system defines all possible entity types and relationships between entity types. You can define any number of different types in a type system. Type systems are generally domain-specific and application-specific.
You can configure feature flags and properties with App Configuration, supporting the following data types: Boolean, Numeric, String, and SecretRef. The String data type can be a text string, JSON, or YAML. The SDK processes each format as shown in the table.



Table 1. Example outputs

 Feature or Property value Data type Data format Type of data returned by GetCurrentValue() Example output 

 true BOOLEAN not applicable bool true 
 25 NUMERIC not applicable float64 25 
 { <br>"secret_type": "kv", <br>"id": "secret_id_data_here", <br>"sm_instance_crn": "crn_data_added-here" <br>} SECRETREF (this type is applicable only for Property) not applicable map[string]interface{} { <br>"metadata": { <br>"collection_type":"application/vnd.ibm.secrets-manager.secret+json", <br>"collection_total": 1 <br>},"resources": [{"created_by": "iam-ServiceId-e4a2f0a4-3c76-4bef-b1f2-fbeae11c0f21", <br>"creation_date": "2020-10-05T21:33:11Z", <br>"crn": "crn:v1:bluemix:public:secrets-manager:us-south:a/a5ebf2570dcaedf18d7ed78e216c263a:f1bc94a6-64aa-4c55-b00f-f6cd70e4b2ce:secret:cb7a2502-8ede-47d6-b5b6-1b7af6b6f563", <br>"description": "Extended description for this secret."