vania-janet/multiturn-rag-retrieval-data huggingface dataset:
Currency Named Entity Recognition Combine a decimal number extractor with a literal to represent the local currency symbol in a sequence or define a regular expression. If more than one currency symbol is required, use a dictionary rather than a literal. 
 Date and time Named Entity Recognition For numeric formats, define a regular expression for the target text pattern. <br> <br>For alphabetic formats, define a sequence using integers for the days and years and a mapping table to represent the months. Use the full names and abbreviations for each month in the mapping table. For example, map the French months juillet and juil to juillet or July, if translating to English. 
 City, County, Country, Person, Location, Organization, State or province, Town Named Entity Recognition European and similar languages <br> <br>Add entries for the language to the appropriate dictionary. <br> <br>Arabic, Japanese and similar languages 
 Continent Named Entity Recognition Define a dictionary and specify entries to contain the names of the continents in the target language. If English results are also to be included, form a union between the provided continent extractor with your custom one. 
 Address Named Entity Recognition Define a sequence composed of the parts of the address, such as street, city, country and postal code. 
 All financial extractors Finance actions These extractors cannot be extended. 
 All machine-data analytics extractors Machine Data Analytics When possible, define a regular expression or sequence. The remaining extractors cannot be extended. 
 All sentiment analysis extractors Sentiment Analysis - GeneralSentiment Analysis - Surveys Add entries in the target language to the Customize Terms tab on the Extractor Properties pane. 









 Deploy advanced rules model to Natural Language Understanding 



 Export advanced rules project 

These instructions detail how to export an advanced rules model from the IBM Watson™ Knowledge Studio for IBM Cloud Pak for Data Advanced Rules Editor, but are common instructions for the public cloud.



1. Open the Advanced Rules workspace
2. Confirm that all models that you want to export are on the Canvas, and are not saved to the "Extractors" pane, except for provided extractors
3. Right click the project that you want to export on the "Projects" pane
4. Click Export Project!
If the base image for your Dockerfile build is pulled from a different registry than where the resulting built image is published and both registries require authentication, you can use kubectl to create a Kubernetes secret of type [kubernetes.io/dockerconfigjson](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/registry-secret-existing-credentials) that contains credentials to both registries. For information about working with access credentials for both registries, see [Kubernetes documentation on pulling an image from a private repository](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/registry-secret-existing-credentials).







 Resolution for build source not supported by buildpacks 

To check whether your build source repository is supported in Code Engine, see [Choose a build strategy](https://cloud.ibm.com/docs/codeengine?topic=codeengine-plan-buildbuild-strategy) for supported runtimes. If your language is listed, check the linked samples and ensure that you correctly structure your sources so that buildpacks can successfully detect and build them. If you cannot find a suitable buildpack for your source or the standardized way on how buildpacks runs the build does not meet your needs, then you can specify a Dockerfile, describe the container build manually in the Dockerfile, and then switch to use the dockerfile build strategy in the build configuration.





 Resolution for a problem with the Docker build 

If the build and push step failure problem isn't a problem with memory, a container registry secret, or a Dockerfile, then the problem is likely with the Docker build. The problem might be an error in the Dockerfile itself, for example, a syntax error, or in the correctness of the operation that it performs. The problem can also be in your source code, which might fail to compile, for example, if Java® code is included.
The pause indicates that the assistant is working on an answer, which gives the assistant time to make the webhook call and get a response. Then, you can jump to a child node to show the result.

To add a Pause response type, complete the following steps:



1. From the dialog node where you want to add the response type, click the dropdown menu in the Assistant responds field, and then choose Pause.
2. Add the length of time for the pause to last as a number of milliseconds (ms) to the Duration field.

The value cannot exceed 10,000 ms. Users are typically willing to wait about 8 seconds (8,000 ms) for someone to enter a response. To prevent a typing indicator from being displayed during the pause, choose Off.

Add another response type, such as a text response type, after the pause to clearly denote that the pause is over.



This response type does not render in the "Try it out" pane. You must access a node that uses this response type from a test deployment to see how your users will experience it. For more information, see [Testing your assistant from a web page](https://cloud.ibm.com/docs/assistant?topic=assistant-deploy-web-link).





 Adding a Search skill response type ![Plus or higher plan only](https://cloud.ibm.com/docs-content/v1/content/417db917d18067d9dcc4cf2612564a9a87c3ddc8/assistant/images/plus.png) 

If you have existing customer-facing material, such as an FAQ, a product catalog, or sales material that can answer questions that customers often ask, put that information to use. You can trigger a search of the existing material in real time to get the latest and most up-to-date answer for your customers.

To use the search skill response type, you must create a search skill and add it to the same assistant that uses this dialog skill. For more information, see [Creating a search skill](https://cloud.ibm.com/docs/assistant?topic=assistant-skill-search-add).
Scale the store deployment back up:

oc scale deployment ${STORE_DEPLOYMENT} --replicas=${ORIGINAL_NUMBER_OF_REPLICAS}
oc scale deploy ibm-watson-assistant-operator -n ${OPERATOR_NS} --replicas=1

You might need to wait a few minutes before the skills you restored are visible from the web interface.
12. After restoring the data, you have to train the backend model. Ensure you reopen only one assistant or dialog skill at a time. Each time you open a dialog skill after its training data has been changed, training is initiated automatically. Give the skill time to retrain on the restored data. It usually takes less than 10 minutes to get trained. Remember that the process of training a machine learning model requires at least one node to have 4 CPUs that can be dedicated to training. Therefore, open restored assistants and skills during low traffic periods and open them one at a time. If the assistant or dialog skill does not respond, then modify the workspace (for example, add an intent and then remove it). Check and confirm.





 Creating the resourceController.yaml file 

The resourceController.yaml file contains details about the new environment where you are adding the backed-up data. Add the following information to the file:

accessTokens:
- value
- value2
host: localhost
port: 5000

To add the values that are required but currently missing from the file, complete the following steps:



1. To get the accessTokens values list, you need to get a list of bearer tokens for the service instances.



* Log in to the IBM Cloud Pak for Data web client.
* From the main IBM Cloud Pak for Data web client navigation menu, select My instances.
* On the Provisioned instances tab, click your Watson Assistant instance.
* In the Access information of the instance, find the Bearer token. Copy the token and paste it into the accessTokens list.



A bearer token for an instance can access all instances that are owned by the user. Therefore, if a single user owns all of the instances, then only one bearer token is required.
The following factors govern the complexity of migration:



* Project-based factors - such as how is the project that is being staffed.
* Architecture factors - such as changes to the existing NSX-V environment since deployment.
* Micro-segmentation factors - such as the use of distributed firewall rules and the use of tagging in these rules.
* Integration factors - what systems are integrating with NSX-V Manager and vCenter as both these components are replaced in the migration. Integrated systems can include VMware Aria Automation, VMware Aria Operations, VMware Aria Orchestrator, SEIM or security tools, backup and recovery, replication, F5, vSRX, FortiGate, or other third-party network applications.



For more information, see [Assess migration complexity](https://cloud.ibm.com/docs/vmwaresolutions?topic=vmwaresolutions-v2t-complexity).

Classifying or assessing migration complexity is just an informative step to provide you guidance. So that you can estimate the migration timescales, required tools, skills and knowledge, and you can prepare in the best possible way.





 Required skills 

When you assess the complexity, you must focus on skills and resource availability. You must assess:



* If existing resources have time to participate in migration activities while they are delivering their existing duties.
* If existing resources have the skills, knowledge and experience that are needed to successfully deliver the required tasks.



If it is deemed that in-house skills need to be supplemented, then it is advised to engage a migration services provider as soon as possible.

In addition, to ensure successful Day 2 operations, improve the core VMware NSX-T™ skills by using the available [VMware Learning for NSX-T education](https://www.vmware.com/learning.html).





 Engage a migration services provider 

You can engage PrimaryIO’s experienced Professional Services team through the IBM Catalog. For more information, see [HDM Cloud Connect NSX-V to NSX-T](https://cloud.ibm.com/catalog/services/hdm-cloud-connect-nsx-v-to-nsx-t).
Track API events
: Premium plan users can now use the Activity Tracker service to track how users and applications interact with IBM Watson® Assistant in IBM Cloud®. See [Activity Tracker events](https://cloud.ibm.com/docs/assistant?topic=assistant-at-events).





 5 February 2020 

New API version
: The current API version is now 2020-02-05. The following changes were made with this version:



* When a dialog node's response type is connect-to-agent, the node's title is used as the topic value. Previously, user_label was used.
* The alternate_intents property is stored as a Boolean value instead of a String.







 4 February 2020 

Product user interface makeover
: The UI has been updated to be more intuitive, responsive, and consistent across its pages. While the look and feel of the UI elements has changed, their function has not.

Requesting early access
: The button you click to request participation in the early access program has moved from the Skills page to the user account menu. For more information, see [Feedback](https://cloud.ibm.com/docs/assistant?topic=assistant-feedbackfeedback-beta).





 24 January 2020 

New system entities are now generally available in multiple languages
: The new and improved numeric system entities are now generally available in all supported languages, except Arabic, Chinese, Japanese, and Korean, where they are available as a beta feature. They are not used by your dialog skill unless you enable them from the Options>System entities page. For more information, see [New system entities](https://cloud.ibm.com/docs/assistant?topic=assistant-system-entities).





 14 January 2020 

Fixed an error message that was displayed when opening an instance
: An error that was displayed when you launched Watson Assistant from the IBM Cloud® dashboard has been fixed. Previously, an error message that said, Module 'ui-router' is not available! You either misspelled the module name or forgot to load it would sometimes be displayed.





 12 December 2019 

Support for private network endpoints
For more information about supported regions, see [Regions and locations](https://cloud.ibm.com/docs/hs-crypto?topic=hs-crypto-regions).



 Before you begin 

To use the command, you need to make sure that the recovery crypto unit and all target crypto units meet the following requirements:



* They are not in imprint mode.
* They have the same signature threshold value.
* A common set of administrators is added to the recovery crypto unit and all target crypto units, which can meet the signature threshold value.



To check that initial conditions are met, select the source and target crypto units by using the ibmcloud tke cryptounit-add command, and then run the ibmcloud tke cryptounit-compare command.





 Recovering master keys 

Run the following command to recover a master key value from a recovery crypto unit:

ibmcloud tke auto-mk-recover

With this command, you can transfer the value in the current master key register of a recovery crypto unit to the current master key registers of any other crypto units in the same resource group. These can be operational crypto units or other recovery crypto units. With this command, you can use the same master key value in multiple service instances if they are in the same resource group.

To learn more about resource groups, see [Managing resource groups](https://cloud.ibm.com/docs/account?topic=account-rgs).





 What's next 

For a complete TKE CLI plug-in command reference, see [IBM Cloud TKE CLI](https://cloud.ibm.com/docs/hs-crypto?topic=hs-crypto-cli-plugin-hpcs-cli-plugintke-cli-plugin).
When you use Terraform to manage resources such as Continuous Delivery service instances, toolchains, and Tekton pipelines, avoid changing the resources by using the console, APIs, or CLI, or by any other method outside of Terraform's control.

If you circumvent Terraform by directly changing resources, you might cause [resource drift](https://developer.hashicorp.com/terraform/tutorials/state/resource-drift), a situation in which the states of your actual resources on IBM Cloud deviate from the definition of the resources in Terraform. The next time that you apply the Terraform configuration, Terraform attempts to update your resources to bring them back in alignment with the Terraform configuration. This action might lead to unintended consequences, such as reverting changes or deleting and then re-creating resources.

For more information about resource drift, see [Manage Resource Drift](https://developer.hashicorp.com/terraform/tutorials/state/resource-drift).



Domain Name Registration



* What are the DNS servers?

The DNS servers are 161.26.0.10 and 161.26.0.11.
* What are the local (or private) IBM Cloud DNS resolvers?

The local resolving name servers on the IBM Cloud private network are:



* rs1.service.softlayer.com 10.0.80.11
* rs2.service.softlayer.com 10.0.80.12



These local resolving name servers are on our private network, so they don't use up public bandwidth.
* What are the IBM Cloud name server addresses?

IBM has two addresses for authoritative name servers and two addresses for resolving name servers. These local resolving name servers are on the IBM private network, so they don't use up public bandwidth.



* Authoritative name servers



* ns1.softlayer.com 67.228.254.4
* ns2.softlayer.com 67.228.255.5



* Resolving name servers



* rs1.service.softlayer.com 10.0.80.11
* rs2.service.softlayer.com 10.0.80.12
In order for an ISO to be imported to the Image Templates screen, the ISO must be bootable.

IBM Cloud supported operating systems can be used only to load an ISO template onto an instance. For more information, see [Supported Operating Systems](https://cloud.ibm.com/docs/bare-metal?topic=bare-metal-about-software&locale=ensupported-operating-systems-for-ibm-cloud-virtual-servers).
* What is the difference between a public image and a private image?

A public image is an image that can be viewed and applied to a new virtual server by any IBM Cloud user. IBM Cloud currently creates public images as a solution for configuration options on different devices. You can also make images public and available to any user. A private image is an image that can be viewed only by authorized users. Authorized users default to any user on your account; however, images also can be shared between multiple accounts by updating the sharing options in the IBM Cloud console.
* Can I capture and deploy virtual servers with my self-managed hypervisor?

Only servers that are provisioned by IBM Cloud can be captured and deployed. Individual virtual servers that you manually created on personal devices cannot be captured, provisioned, or deployed.
* Can I share my private ISO template with other customers?

The only ISO templates that are made public to all customers are templates that are generated by IBM Cloud. Private ISO templates are account-specific and cannot be shared between customers through the IBM Cloud console.
* Does my ISO template need to be in the same data center as my virtual server to complete a boot from image?

Yes, ISO templates must be in the same data center as a virtual server to boot from the image. If the ISO template isn't in the same data center, the ISO template must be copied to the appropriate data center. If this situation occurs, a warning appears about the transaction. When an ISO template is copied to a different data center, a small fee is charged to the account as they are for copying other types of image templates.
* What is the difference between physical data and volume size?
The improved process now offers:



1. Faster copy of stock image to your private project.
2. The stock image cannot be exported. One can do VM capture and export on a deployed VM that uses the stock image.
3. Storage pool and tier of a stock image shows "Empty" (API) or "Any" (UI) as VM can be deployed to any tier/pool by using the stock image.



* Can I select a specific resource group when I create a cloud connection?

NO. When you create a cloud connection by using Power Systems Virtual Server, the cloud connection is always created in the default resource group even if you choose a specific resource group.



Qiskit Runtime



* What is Qiskit Runtime service?

Qiskit Runtime service is a runtime environment through the IBM Cloud that provides access to the IBM Quantum processors and simulators. They allow users to run quantum programs, which require specialized quantum hardware that is coupled closely with traditional “classical”, computer hardware.
* Why is IBM launching Qiskit Runtime service?

IBM made quantum computers available through the cloud in 2016. In 2022, IBM integrates with IBM Cloud® accounts to offer Qiskit Runtime API access. This access creates a smoother customer experience and the ability to combine Qiskit Runtime with other kinds of cloud compute resources for their particular workflow or application.
* What can Qiskit Runtime service not do?

Qiskit Runtime service provides access to IBM Quantum systems. Today’s quantum systems are somewhat constrained in the size of problems that they can address due to available scale and quantum volume. Nonetheless, these systems can already be used to solve small problems and to explore this new and exciting field.
* What skills are required to use the Qiskit Runtime service?

The Qiskit Runtime service is meant to be accessible to anyone comfortable with Python. Use of Qiskit Runtime primitives requires expressing a problem as quantum circuits. The Qiskit application modules can facilitate this task for various application domains such as optimization, chemistry, finance, and machine learning. Creation of novel Qiskit Runtime programs requires more knowledge of the Qiskit backend interface.
Gateway firewall 

Does your source environment include gateway firewalls such as FortiGate®, vRAs, or Juniper® vSRX?

Due to the architectural differences between NSX-V and NSX-T, these aspects might require advanced configuration skills to build the wanted network topology. In some cases, gateway firewalls might be rebuilt with new IP addresses. For example, when the new deployment is in a new IBM Cloud data center or POD. This action requires skills and work effort to reconfigure the related firewalls.

This is not a key parameter. However, it gives guidance on where more project tasks and skills are required.





 Distributed firewall 

If you use the NSX-V distributed firewalling feature, the configurations must be migrated to the NSX-T environment. The number and complexity of these rules impact the migration. Depending on the complexity of the rules, some of them can be migrated easily. However, if the rules use vCenter tagging, then they cannot be migrated as-is, as this feature doesn't exist in NSX-T. Consider the usage of a third-party tool for a large number or complex use of distributed firewall.

This is a key parameter and also gives guidance on where more project tasks, tools, and skills are required.





 Load balancing 

The use of load-balancers number and the complexity of the rules impact the migration of the VMs. Due to the architectural differences between NSX-V and NSX-T, these aspects might require advanced configuration skills to build the wanted load-balancing solution.

This is not a key parameter. However, it gives guidance on where more project tasks and skills are required.





 Additional services 

The optional vCenter server instance services, such as Veeam or Zerto are linked to your vCenter server instance. By deleting the source vCenter Server instance, these services are deleted, and so are your historical backups. Additional work effort is required to reconfigure the services or migrate configurations post the automated deployment. This action is done to match your needs and requirements in the new target NSX-T based vCenter Server instance.

This is not a key parameter.
Only the names of people that you assigned to the project manager role from the User Account Management page for the instance are displayed. See [Assembling a team](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-team) for more information about adding users.

If you have a Lite plan subscription, skip this step. You cannot add other users, so you cannot assign anyone to the project manager role. You do not need a separate project manager. As an administrator, you can perform all the tasks that a project manager would typically perform.
6. Click Create.







 What to do next 

After the workspace is created, you can start configuring the workspace resources.

To change the workspace description or workspace name, or to add or remove project managers later, an administrator can edit the workspace. From the Knowledge Studio home page, click the Show menu icon on the workspace tile, and choose the Edit menu option.

Related concepts:

[Uploading resources from another workspace](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-exportimport)

Related reference:

[Language support](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-language-support)





 Tokenizers 

A tokenizer groups characters into tokens, and tokens into sentences. A token is loosely equivalent to a word.

The actions that a tokenizer must take to identify a document's tokens differ depending on the language of the document. In English, tokens are often equated to words as delimited by white spaces in a sentence. However, they do not always match one-to-one with words; other textual elements are considered tokens in some situations. For example, punctuation at the end of a sentence is considered a token, and contractions are often expanded into two tokens. In languages that do not use white spaces, such as Chinese, more complicated statistical algorithms are used to identify the tokens.