vania-janet/multiturn-rag-retrieval-data huggingface dataset:
If you don't want to give customers this choice, clear the Include link for customers to view up to 10 results checkbox.

This option was introduced with the 1.5.0 release.
6. Decide whether to be more selective with the answers that are returned.

By default, all search query matches, regardless of the confidence score of the match, are returned as search results. You can limit the search results to include only matches with a confidence score of 20% or higher in Discovery.

To enable the beta feature that filters the results, toggle the Refine results to return more selective answers switch to On.

This option was introduced with the 1.5.0 release.
7. Click Try it to open the Try it out pane for testing. Enter a test message to see the results that are returned when your configuration choices are applied to the search. Make adjustments as necessary.
8. Click Create.



If you want to change the configuration of the search result card later, open the search skill again, and make edits. You do not need to save changes as you make them; they are automatically applied. When you are happy with the search results, click Save to finish configuring the search skill.

If you decide you want to connect to a different Discovery service instance or data collection, then create a new search skill and configure it to connect to the other instance. You cannot change the service instance or data collection details for a search skill after you create it.



 Tips for collection field selection 

The appropriate collection fields to extract data from vary depending on your collection's data source and how the data source was enriched. After you choose a data collection type, the collection field values are prepopulated with source fields that are considered most likely to contain useful information given the collection's data source type. However, you know your data better than anyone. You can change the source fields to ones that contain the best information to meet your needs.

To learn more about the structure of the documents in your collection, including the names of fields that contain information you might want to extract, open the collection in Discovery.

The source fields are created when the collection is created.
Previously, it was generally available only for US and UK English. For more information, see [Split transcript at phrase end](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsingsplit-transcript).





 7 October 2020 

Updates to Japanese broadband model for improved speech recognition
: The ja-JP_BroadbandModel model has been updated for improved speech recognition. By default, the service automatically uses the updated model for all speech recognition requests. If you have custom language or custom acoustic models that are based on this model, you must upgrade your existing custom models to take advantage of the updates by using the following methods:



* POST /v1/customizations/{customization_id}/upgrade_model
* POST /v1/acoustic_customizations/{customization_id}/upgrade_model



For more information, see [Upgrading custom models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade).





 30 September 2020 

Updates to pricing plans for the service
: The pricing plans for the service have changed:



* The service continues to offer a Lite plan that provides basic no-charge access to limited minutes of speech recognition per month.
* The service offers a new Plus plan that provides a simple tiered pricing model and access to the service's customization capabilities.
* The service offers a new Premium plan that provides significantly greater capacity and enhanced features.



The Plus plan replaces the Standard plan. The Standard plan continues to be available for purchase for a short time. It also continues to be available indefinitely to existing users of the plan with no change in their pricing. Existing users can upgrade to the Plus plan at any time.

For more information about the available pricing plans, see the following resources:



* For general information about the pricing plans and answers to common questions, see the [Pricing FAQs](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-faq-pricing).
* SERVICE_PLAN_NAME is the type of plan. Valid values are lite, 7-day, 14-day, 30-day
* LOCATION is the region where the auditing instance is created. To get the latest list of locations that are available for the IBM Cloud Activity Tracker service, see [Locations](https://cloud.ibm.com/docs/services/activity-tracker?topic=activity-tracker-regions).
* PRIVATE_ENDPOINT is either true or false. If true only [private endpoints](https://cloud.ibm.com/docs/activity-tracker?topic=activity-tracker-endpoints) can be used to access the instance.

Unless otherwise specified when provisioning an instance, the default is for the instance to be accessible by both public and private endpoints.



For example, to provision an instance with the 7 days retention plan that can be accessed only by private endpoints, run the following command:

ibmcloud resource service-instance-create my-instance logdnaat 7-day us-south -p '{"private_endpoints_only": true}'

To provision an instance with the 14 days retention plan that can be accessed only by both public and private endpoints, run one of the following commands:

ibmcloud resource service-instance-create my-instance logdnaat 14-day us-south -p '{"private_endpoints_only": false}'

or

ibmcloud resource service-instance-create my-instance logdnaat 14-day us-south







 Step 2. Create the credentials for your instance 

Run the following command to create a service ID:

ibmcloud resource service-key-create NAME ROLE_NAME --instance-name SERVICE_INSTANCE_NAME

Where



* SERVICE_INSTANCE_NAME is the name of the instance that you provisioned in the previous step.
* NAME is the name of the service ID. Use the following format to name the key <SERVICE_INSTANCE_NAME>-key-admin
* ROLE_NAME is the permission that you grant this service ID. Set it to Manager.



For example, you can run the following command:
See [Troubleshooting skill import issues](https://cloud.ibm.com/docs/assistant?topic=assistant-skill-dialog-addskill-dialog-add-import-errors) for information about how to edit skills that you want to continue using.







 27 November 2018 

A new service plan, the Plus plan, is available
: The new plan offers premium-level features at a lower price point. Unlike previous plans, the Plus plan is a user-based billing plan. It measures usage by the number of unique users that interact with your assistant over a given time period. To get the most from the plan, if you build your own client application, design your app such that it defines a unique ID for each user, and passes the user ID with each /message API call. For the built-in integrations, the session ID is used to identify user interactions with the assistant. See [User-based plans](https://cloud.ibm.com/docs/assistant?topic=assistant-services-informationservices-information-user-based-plans) for more information.



Plus plan limits

 Artifact Limit 

 Assistants 100 
 Contextual entities 20 
 Contextual entity annotations 2,000 
 Dialog nodes 100,000 
 Entities 1,000 
 Entity synonyms 100,000 
 Entity values 100,000 
 Intents 2,000 
 Intent user examples 25,000 
 Integrations 100 
 Logs 30 days 
 Skills 50 



User-based Premium plan
: The Premium plan now bases its billing on the number of active unique users. If you choose to use this plan, design any custom applications that you build to properly identify the users who generate /message API calls. See [User-based plans](https://cloud.ibm.com/docs/assistant?topic=assistant-services-informationservices-information-user-based-plans) for more information.

Existing Premium plan service instances are not impacted by this change; they continue to use API-based billing methods. Only existing Premium plan users will see the API-based plan listed as the Premium (API) plan option.
[Cognitive Search Web App](https://developer.ibm.com/patterns/create-an-app-to-perform-intelligent-searches-on-data/?cm_sp=Developer-_-code-_-search_pattern) Uses publicly available reviews on Airbnb listings to demonstrate how to use individual UI components to visualize insights. You can then easily switch out the dataset to adapt it to your own use cases.



* [Get the Code](https://github.com/IBM/watson-discovery-ui?cm_sp=Developer-_-develop-a-fully-featured-web-app-built-on-the-watson-discovery-service-_-Get-the-Code)
* [View the Demo](https://www.youtube.com/watch?v=5EEmQwcjUa4&cm_sp=Developer-_-develop-a-fully-featured-web-app-built-on-the-watson-discovery-service-_-View-the-Video)



[Mine Enterprise Data for Insights](https://developer.ibm.com/patterns/import-enrich-and-gain-insight-from-data/?cm_sp=Developer-_-code-_-data_breaches) Use the Watson Node.js SDK to import and enrich your data using the Watson Discovery Service. You can then explore the data to find patterns, trends, and actionable insights.



* [Get the Code](https://github.com/IBM/watson-discovery-analyze-data-breaches?cm_sp=IBMCode-_-import-enrich-and-gain-insight-from-data-_-Get-the-Code)
* [View the Demo](https://www.youtube.com/watch?v=zAu9tHefdDc&cm_sp=IBMCode-_-import-enrich-and-gain-insight-from-data-_-View-the-Demo)
However, if you use an entity extractor enrichment, you can identify when a location is mentioned based on how the location is referenced in a sentence. With phrases such as, “I live in x” or “I'm from x” or “I'm traveling to x” in its training data, the entity extractor can learn that x is a reference to a location.

When you need to choose between using a dictionary or an entity extractor enrichment, follow these guidelines:



* If the list of possible examples is short, use a dictionary.

It is more efficient to define a dictionary term planet with synonyms such as Earth and Saturn than to create a planet entity because only 8 planets exist in our solar system. However, defining a list of every possible location on Earth is not feasible. An entity extractor can recognize more location mentions.
* If the list of possible examples is static, use a dictionary.

Controversy over Pluto aside, the planet category is a good example here too because the list of planets in our solar system is static. Or maybe you want to monitor general customer sentiment about your products. You need to be able to recognize product name mentions, but might not need specifics. If you have a large variety of product names, you can create a product name entity. As new products are added to your portfolio, or product names change over time, you do not need to maintain an overall product list. The entity extractor can continue to recognize general feedback about your products based on the context of the sentences in which products are mentioned.







 Add a resource 

When you add a custom enrichment to a project it is available to any collection in the project.

To add a resource, complete the following steps:



1. Open your project and go to the Improve and customize page.
2. On the Improvement tools panel, expand Teach domain concepts, and then choose the resource that you want to add.

After you create the resource, it becomes a new type of enrichment that you can apply to your data.
3. Specify the collection and field in which to apply the enrichment.

You can apply enrichments to the text and html fields, and to custom fields that were added from uploaded JSON or CSV files or from the Smart Document Understanding (SDU) tool.
If you create a Lite-plan instance, it is automatically deleted 30 days after creation. For more information about Continuous Delivery service plans, see [Plan limitations and usage](https://cloud.ibm.com/docs/ContinuousDelivery?topic=ContinuousDelivery-limitations_usage).
7. In the Configure your resource section, specify a name for the Continuous Delivery instance that you are creating.
8. Select the resource group where you want to create the Continuous Delivery service instance. You cannot change the selected resource group after you create the Continuous Delivery service instance. For more information about how to organize resources in your IBM Cloud account, see [Best practices for organizing resources in a resource group](https://cloud.ibm.com/docs/account?topic=account-account_setup).
9. Specify the tags that you want to use to organize and filter the resources in your resource list. You can also use these tags to identify team usage or cost allocation. These tags are visible account wide. For more information about using tags, see [Working with tags](https://cloud.ibm.com/docs/account?topic=account-tag).
10. If you chose a Professional pricing plan, you can select the instance of the IBM® Key Protect for IBM Cloud® service or the instance of the IBM Cloud® Hyper Protect Crypto Services, and the root key that is used to encrypt your personal information. Make sure that the Key Protect instance or the Hyper Protect Crypto Services instance and the root key exist and the toolchain resources are authorized to access Key Protect or Hyper Protect Crypto Services in the Manage Authorizations section. Only private endpoints are currently supported for the Hyper Protect Crypto Services service instance. For more information about what types of data are encrypted, see [Protecting your personal data when you use the Professional plan](https://cloud.ibm.com/docs/ContinuousDelivery?topic=ContinuousDelivery-cd_data_securitycd_professional_plan).
11. Click Create.







 Creating a Continuous Delivery service instance from the CLI 



1.
Then, the user says, Oh wait. I want to fly to Madrid instead. If you set up the Found condition as follows, then your dialog can handle this type of change gracefully.

When user responds, if @destination is found:

Condition: (event.previous_value != null) &&
(event.previous_value != event.current_value)
Response: Ok, updating destination from
<? event.previous_value ?> to <? event.current_value ?>.
Response: Ok, destination is $destination.

This slot configuration enables your dialog to react to the user's change in destination by saying, Ok, updating the destination from Paris to Madrid.





 Avoiding slot filling confusion 

When a user input is evaluated, the slot with the first slot condition to match it is filled only. Test for the following possible causes of misinterpretation, and address them:



* Problem: The same entity is used in more than one slot.

For example, @sys-date is used to capture the departure date in one slot and arrival date in another.

Solution: Use slot found conditions that get clarification from the user about which date you are saving in a slot before you save it.
* Problem: A term fully or partially matches the entities in more than one slot condition.

For example, if one slot captures a product ID (@id) with a syntax like GR1234 and another slot captures a number (@number), such as 1234, then user input that contains an ID, such as BR3344 might get claimed by the @number slot as a number reference and fill the $number context variable with 3344.

Solution: Place the slot with the entity condition that captures the longer pattern (@id) higher in the list of slots than the condition that captures the shorter pattern (@number).
* Problem: A term is recognized as more than one system entity type.

For example, if the user enters May 2, then your assistant recognizes both the @sys-date (2017-05-02) and @sys-number (2) entities.
The spoke has egress routes that were initialized with one of the NLB appliance IPs. The spoke next hop will not be updated on NLB appliance fail over!

It will be required to maintain an ingress route in the transit VPC which will be rewritten by the NLB to reflect the active appliance. The spoke egress route will deliver packets to the correct zone of the transit VPC. Routing within the transit VPC zone will find the matching ingress rule which will contain the active appliance.

Below is the transit VPC ingress route table discussed earlier. The next hop will be kept up to date with the active NLB appliance. Note that Dallas 3 has a change written by the NLB route mode service to reflect the active appliance.



 Zone Destination Next hop 

 Dallas 1 0.0.0.0/0 10.1.0.196 
 Dallas 2 0.0.0.0/0 10.2.0.196 
 Dallas 3 0.0.0.0/0 10.3.0.197 







 Step 3: DNS 

The IBM Cloud DNS Services service is used to convert names to IP addresses. In this example a separate DNS service is created for the transit and each of the spokes. This approach provides isolation between teams and allows the architecture to spread across different accounts. If a single DNS service in a single account meets your isolation requirements it will be simpler to configure. All zones are configured similarly and below is a diagram for a two zone architecture:

Zoom

![DNS Layout](https://cloud.ibm.com/docs-content/v1/content/f84e2238288b7f0355715a4c355609ce7ac48fb0/solution-tutorials/images/vpc-transit/vpc-transit-dns.svg)

DNS Layout



 DNS Resources 



1. Apply the dns_tf layer to create the DNS services and add a DNS zone for each VPC and an A record for each of the test instances:

./apply.sh dns_tf
2.
Why can't I submit the form to add my credit card information? 

You can't submit your credit card information to upgrade your Lite account to a billable account.

  What’s happening 

The Upgrade account button is disabled.

  Why it’s happening 

This problem happens when your information isn't entered correctly.

  How to fix it 

Complete the following steps:



1.  Complete all of the required fields to add your credit card and billing information in the IBM Cloud console.

Ensure that you specified a business account and not a personal account type, if you are providing a VAT ID or tax identification number.
2.  Click Upgrade account.
Select a region for the service instance.
6. Select the Lite service plan.

By default, the Lite plan is set.

For more information about other service plans, see [Pricing plans](https://cloud.ibm.com/docs/log-analysis?topic=log-analysis-service_plans).
7. Specify a Service name for your IBM Log Analysis service instance.
8. Select the Default resource group.

By default, the Default resource group is set.
9. To provision the IBM Log Analysis service in the IBM Cloud selected resource group, click Create.



After you provision an instance, the IBM Log Analysis dashboard opens.

To provision an instance of logging through the CLI, see [Provisioning logging through the IBM Cloud CLI](https://cloud.ibm.com/docs/log-analysis?topic=log-analysis-provisionprovision_cli).





 Step 3: Configure a bare metal server to send logs to your logging instance 

To configure your bare metal server to send logs to your IBM Log Analysis instance, you must install a logging-agent. The logging agent reads log files from /var/log or other directories you specify, and forwards the log data to your logging instance.

To configure your bare metal server to forward logs to your logging instance, complete the following steps from an Ubuntu terminal:



1. Install the logging agent. Run the following commands:

echo "deb https://assets.logdna.com stable main" | sudo tee /etc/apt/sources.list.d/logdna.list

wget -O- https://assets.logdna.com/logdna.gpg | sudo apt-key add -

sudo apt-get update

sudo apt-get install logdna-agent < "/dev/null"
2. Set the ingestion key that the logging agent will use to forward logs to the IBM Log Analysis instance.

sudo logdna-agent -k <INGESTION_KEY>
Discovery archives 

This topic contains information about Discovery features that have been replaced with newer options.



  AlchemyLanguage enrichments 

AlchemyLanguage enrichments were deprecated effective 1 March 2018.





  Data Crawler 

The Data Crawler is no longer supported or available for download beginning [17 April 2019](https://cloud.ibm.com/docs/discovery?topic=discovery-release-notes17apr19). See [Connecting to Data Sources](https://cloud.ibm.com/docs/discovery?topic=discovery-sources) for other connectivity options.

For more information about working with existing installations of the Data Crawler, see [Adding content with the Data Crawler](https://cloud.ibm.com/docs/discovery?topic=discovery-adding-content-with-data-crawler).





  Watson Discovery News Original 

IBM Watson™ Discovery News Original was retired from service 15 January 2018. A new version of IBM Watson™ Discovery News is available. For more information about the new version, see [Watson Discovery News](https://cloud.ibm.com/docs/discovery?topic=discovery-watson-discovery-news).



  Querying Watson Discovery News Original 

IBM Watson™ Discovery News Original was retired from service 15 January 2018. A new version of IBM Watson™ Discovery News is available, see [Watson Discovery News](https://cloud.ibm.com/docs/discovery?topic=discovery-watson-discovery-news) for more information. For information on querying the new version, see [Querying Watson Discovery News](https://cloud.ibm.com/docs/discovery?topic=discovery-query-conceptsquerying-news).







  Watson Discovery Knowledge Graph 

As of 30 September 2019, the IBM Watson™ Discovery Knowledge Graph Beta APIs (Knowledge graph entity query /v1/environments/{environment_id}/collections/{collection_id}/query_entities and Knowledge Graph relationship query /v1/environments/{environment_id}/collections/{collection_id}/query_relations) are no longer accessible. See the [3 September 2019 release notes](https://cloud.ibm.com/docs/discovery?topic=discovery-release-notes3sept19) for the announcement.
This results in 2 toggles per feature, one to activate the feature for testers, and one to remove targeting and activate for the general user population.

You will need the App Configuration Enterprise plan since both feature flags and segmentation are required.

For this example, assume an Enterprise plan instance is $500 per month, active entity IDs are $0.01 each, and API calls are $10 per 100,000. NOTE: These prices are assumed for this example only. Current pricing may be different from the amounts shown in the example. See the App Configuration catalog page for current pricing.

App Configuration Enterprise instances: 1 @ $500 per month Active Entity IDs: 5 entity IDs per region * 3 regions = 15 Included Active Entity IDs: 10,000 Net Active Entity IDs: 0 (all included) = $0 API Calls: 3 instances per region * 3 regions * (10 dark launches per month * 2 toggles per release) = 180 Included API Calls: 1,000,000 Net API Calls: 0 (all included) = $0 TOTAL COST: $500 + $0 + $0 = $500 per month

You might use the same instance of App Configuration for both scenarios for a total cost of just over $1600 per month.







 What are the capabilities, quotas, and limits for various aspects of the App Configuration plans? 



Table 2. Capabilities, quotas, and limits for various pricing plans

 Lite Standard Enterprise 

 Number of collaborators (team members) No restriction No restriction No restriction 
 Max number of instances 1 No restriction No restriction 
 Instance life 30 days of inactivity No restriction No restriction 
 Base price for instance (monthly) Free Charge (see catalog page) Charge (see catalog page) 
 Monthly active entity IDs included with instance 10 1000 10,000 
 Monthly active entity ID overage Overage not allowed overage allowed overage allowed 
 Max monthly active entity IDs per instance 10 Unlimited Unlimited 
 API calls included with instance 5,000 100,000 1,000,000 
 API call overage price Overage not allowed Overage allowed Overage allowed 
 Max monthly API calls per instance 5,000 Unlimited Unlimited 
 Environments 1 15 15 
 Collections 1 20 Unlimited 
 Properties 10 (properties + flags) 1000 Unlimited 
 Property types All All All