vania-janet/multiturn-rag-retrieval-data huggingface dataset:
Updating variables with Schematics API 

. To update variables by using the IBM Cloud® Schematics Python APIs, create two Python files, and provide a name of your choice for those files, for example, schematics_variables_update.py and schematics_env_class.py. 2. Copy and paste the [schematics_variables_update.py](https://cloud.ibm.com/docs/hpc-slurm?topic=hpc-slurm-update-variablesexample-request-update-variables) and [schematics_env_class.py](https://cloud.ibm.com/docs/hpc-slurm?topic=hpc-slurm-update-variablesexample-request-update-variables-file) Python example code requests to the respective Python files. 3. Copy and paste the [config.json template file](https://cloud.ibm.com/docs/hpc-slurm?topic=hpc-slurm-update-variablestemplate-file) to a JSON file, for example config.json. 4. Change the following parameters as part of the request: * Provide the workspace ID w_id generated in both the following functions: schematic_obj.get_workspace(w_id="<w_id>) and schematic_obj.update_variables(w_id="<wi_id>"). 5. Make sure to update the required parameters, such as api_key, ssh_key_name, cluster_prefix in the config.json file. 6. Run the Python script by using python3 to update the variables in the Schematics workspace in the IBM Cloud.

The following parameters might not be required in config.json as the Schematics update variables API uses the workspace ID w_id to update the variables against that workspace.

{
  "name": "Schematic Dev Workspace",
  "type": [
    "terraform_v0.14"
  ],
update-example Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, workspace_id, intent, text, new_text Update a user input example. 
 create-counterexample Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, workspace_id, text Create a counterexample. 
 delete-counterexample Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, workspace_id, text Delete a counterexample. 
 get-counterexample Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, workspace_id, text, include_audit Get information about a counterexample. 
 list-counterexamples Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, workspace_id, page_limit, include_count, sort, cursor, include_audit List counterexamples. 
 update-counterexample Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, workspace_id, text, new_text Update a counterexample. 
 create-entity Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, workspace_id, entity, description, metadata, values, fuzzy_match Create an entity.
You can use the Secrets Manager CLI plug-in to update the metadata of a specific version of a secret.

To update the metadata of a secret, run the [ibmcloud secrets-manager secret-metadata-update](https://cloud.ibm.com/docs/secrets-manager?topic=secrets-manager-cli-plugin-secrets-manager-clisecrets-manager-cli-secret-metadata-update-command) command.

The following example shows the format of the ibmcloud secrets-manager secret-metadata-update command.

ibmcloud secrets-manager secret-version-metadata-update --secret-id SECRET-ID --id VERSION-ID --version-custom-metadata='{"anyKey": "anyValue"}'





 Updating secret versions metadata with the API 

If you're updating the metadata of a secret version, you can use the Secrets Manager API.

The following example request updates metadata properties for each version. When you call the API, replace the ID variables and IAM token with the values that are specific to your Secrets Manager instance. The options for {secret_type} are: arbitrary, iam_credentials, imported_cert, kv, private_cert, public_cert, and username_password.

curl -X PATCH
-H "Authorization: Bearer {iam_token}" -H "Accept: application/json" --H "Content-Type: application/merge-patch+json" -d '{ "version_custom_metadata": { "version_special_id" : "someString" } }' "https://{instance_ID}.{region}.secrets-manager.appdomain.cloud/api/v2/secrets/{id}/versions/{version_id}/metadata"

A successful response returns metadata details about each secret version.

{
"alias": "current",
"created_at": "2022-06-27T11:58:15Z",
When you are satisfied with the performance of the model, you can export a version to IBM Watson™ Discovery for IBM Cloud Pak for Data. This feature enables your applications to use the deployed machine learning model to enrich the insights that you get from your data to include the recognition of entities and relations that are relevant to your domain.



 Before you begin 

You must have administrative access to a [Discovery for IBM Cloud Pak for Data](https://cloud.ibm.com/docs/discovery-data) deployment.





 Procedure 



1. [Export a machine learning model](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-publish-mlexporting-a-machine-learning-model).
2. From the Discovery service, follow the steps to create a Machine Learning enrichment, which include uploading the ZIP file. For more details, see [Machine Learning models](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-domainmachinelearning) in the Discovery v2 documentation.









 Deploying a machine learning model to IBM Watson Natural Language Understanding for IBM Cloud Pak for Data 

When you are satisfied with the performance of the model, you can deploy a version of it to IBM Watson Natural Language Understanding. This feature enables your applications to use the deployed machine learning model to analyze custom entities and relations.



 Before you begin 

You must have a [Natural Language Understanding for IBM Cloud Pak for Data](https://cloud.ibm.com/docs/natural-language-understanding-data) deployment.





 Procedure 



1. [Export a machine learning model](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-publish-mlexporting-a-machine-learning-model).
2. Follow the [Customizing](https://cloud.ibm.com/docs/natural-language-understanding-data?topic=natural-language-understanding-data-customizing) instructions in the Natural Language Understanding for IBM Cloud Pak for Data documentation to create an entities model with the .zip file that you downloaded.
Click Products.
![rep-api-list-2.png](https://cloud.ibm.com/docs-content/v1/content/78bb71851d95d7580503eb9ba10cf3ae31490ade/apiconnect/tutorials/images/rep-api-list-2.png)
10. Select Weather Provider API Product.
![rep-draft-prod-list.png](https://cloud.ibm.com/docs-content/v1/content/78bb71851d95d7580503eb9ba10cf3ae31490ade/apiconnect/tutorials/images/rep-draft-prod-list.png)
11. Change the Version to 2.0.0. Enter Updated API in the Description field. Click the disk icon to save the changes.
![rep-update-prod.png](https://cloud.ibm.com/docs-content/v1/content/78bb71851d95d7580503eb9ba10cf3ae31490ade/apiconnect/tutorials/images/rep-update-prod.png)
12. Click the Stage icon to upload the new version. Select the Sandbox catalog if it is not already selected. ![rep-stage-prod-2.png](https://cloud.ibm.com/docs-content/v1/content/78bb71851d95d7580503eb9ba10cf3ae31490ade/apiconnect/tutorials/images/rep-stage-prod-2.png)Note: It is possible to stage a new version to a different catalog, allowing control of what audience of developers can see this version. This capability can be helpful when moving API products from development to test to production.
13. Click >> to open the navigation menu, and select Dashboard.
* Updates the storage-secret-sidecar image to v1.2.10,
* Updates the csi-node-driver-registrar to v2.5.0
* Updates the livenessprobe to v2.6.0
* Updates the csi-provisioner to v3.2.1
* Updates the csi-attacher to v3.5.0
* Updates the csi-resizer to v1.5.0
* Resolves the following CVEs: [CVE-2022-37434](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-37434), [CVE-2022-2509](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-2509), [CVE-2022-40674](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-40674), [CVE-2020-35525](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-35525), [CVE-2020-35527](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-35527), [CVE-2022-3515](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-3515).







 Change log for version 4.4.11_1614, released 23 September 2022 



* Updates the storage-secret-sidecar image to v1.2.8.
* Updates the golang version to 1.18.6.
Update the Workspace terraform version using the IBM Cloud CLI:



* Login to the IBM Cloud CLI with ibmcloud login
* Set the CLI target region with ibmcloud target -r <region> to be the same as the workspace you are updating.
* Generate an IAM oauth token to use with the Schematics API, with the command ibmcloud iam oauth-tokens.
* Copy the token data and insert in to the following command text, replacing the string <token-data>, set <terraform_version> to the required Terraform version and the <workspace_id>:
* Execute the following cURL command:



curl --request PUT --url https://schematics.cloud.ibm.com/v1/workspaces/<workspace_id> -H "Authorization: Bearer <token-data>" -d '{"template_data":[{"type":"<terraform_version>"}]}'
3. Verify in the Workspace settings page the TF version is now set to the desired version.
4. Run a Generate Plan operation against the workspace. Validate that the command runs successfully without error and no unexpected messages are logged. The Plan should result in no proposed changes to the resources.
5. Run a Apply Plan operation against the workspace. Validate that the command runs successfully without error and no unexpected messages are logged.
6. You have now successfully upgraded.









 Upgrading the Terraform template version 0.x to 1.x 

At 0.x releases, Terraform version upgrade is a stepwise process, upgrading through each release. Upgrading does not support upgrading across multiple releases and must be performed, release by release. Some updates will require execution of Terraform upgrade commands to modify the config files also changes to the Terraform state file. These steps cannot be performed within Schematics. Workspace Terraform templates must be upgraded using a local copy of Terraform. Follow the steps below for upgrading the 0.x releases.



Terraform versions list

 Version Recommendation
Review the changes that are in version 1.8.0 of the managed Istio add-on.

Previous version
: 1.8.0

Current version
: 1.7.5

Updates in this version
: See the Istio release notes for [Istio 1.8](https://istio.io/latest/news/releases/1.8.x/announcing-1.8/).
: If you created a custom IstioOperator (IOP) resource, remove the revision field from the resource before you update your add-on to version 1.8 so that the custom gateways use version 1.8 of istiod. After you update your Istio add-on, update the tag for any custom gateways to 1.8. All istio-monitoring support is removed, and in the managed-istio-custom ConfigMap, the istio-monitoring-components and istio-kiali-dashboard-viewOnlyMode options are unsupported. To use monitoring with Istio, you must install the Kiali, Prometheus, Jaeger, and Grafana components separately from the Istio add-on. For more information, see the [Istio documentation](https://istio.io/latest/docs/ops/integrations/).
: The istio-meshConfig-enableTracing and istio-egressgateway-public-1-enabled optional settings are added to the [managed-istio-custom ConfigMap resource](https://cloud.ibm.com/docs/containers?topic=containers-istiocustomize).







 Version 1.7 (unsupported) 

Version 1.7 of the managed Istio add-on is unsupported. (: deprecated)



 Change log for 1.7.8, released 10 March 2021 

Review the changes that are in version 1.7.8 of the managed Istio add-on.

Previous version
: 1.7.7

Current version
: 1.7.8

Updates in this version
Release notes for Natural Language Understanding 

The following new features and changes to the service are available.



 Service API versioning 

Current API version: 2022-08-10

API requests require a version parameter that takes the date in the format version=YYYY-MM-DD. Send the version parameter with every API request.

When we change the API in a backwards-incompatible way, we release a new minor version. To take advantage of the changes in a new version, change the value of the version parameter to the new date. If you're not ready to update to that version, don't change your version date.



 Active version dates 

The following table shows the service behavior changes for each version date. Switching to a later version date will activate all changes introduced in earlier versions.



 Version date Changes summary 

 [2022-08-10](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-release-notesnatural-language-understanding-aug1022) Language expansion of entities with a new model for improved accuracy and confidence scores.<br><br>Version 2 Russian entity type system.<br><br>Version 2 Swedish entity type system. 
 [2022-04-07](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-release-notesnatural-language-understanding-apr0722) Bug fix for Version 2 Categories type system. 
 [2021-08-15](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-release-notesnatural-language-understanding-aug1521) Classifications GA and Categories type system Version 2 features. 
 [2021-03-25](https://cloud.ibm.com/docs/natural-language-understanding?topic=natural-language-understanding-release-notesnatural-language-understanding-mar2521) Custom categories (beta) and custom classifications (beta) features.
If you are happy with the results from testing the autolearning improvements in the draft environment, publish a new version of your assistant to the live environment to apply the improvements. For more information, see [Publishing your content](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-publish).







 Learning from your data 

Observations are made of only your customers' choices to improve only your assistant. These observations are not reused by IBM or shared in any way.

This observed user choices data is separate from the log data for which metrics are displayed on the Analyze page. The observation data is also separate from the information that is collected in all but Enterprise plan service instances and used by IBM for general service improvements. You can opt out of such use by specifying an opt-out header in your /message API requests. For more information, see [Opting out of log data use](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-admin-securingsecuring-log-opt-out).

To prevent your own assistant from applying what it learns by observing user choices to your assistant, disable autolearning:



1. In Global settings, click the Autolearning tab.
2. Set the Use autolearning to modify responses with training from live environment switch to Off. This immediately disables the modifying of responses in the draft environment.
3. Publish a new version of your assistant to the live environment to completely disable the modifying of responses by autolearning.
You can download updates by going to the [VMware Patch Download Center](https://www.vmware.com/patchmgr/findPatchByReleaseName.portal), logging in and choosing VC from the Search by Product menu. Select the appropriate patch and click Download.
2. Using the vSphere Web Client, upload the ISO file to the vCenter data store repository.
3. Mount the update ISO file to the vCenter Server.
4. Take a snapshot of your vCenter Server.
5. Log in to vCenter appliance management console at https://pscip:5480 (for the PSC) or https://vcenterip:5480 (for the VCSA)
6. Go to the Update section and select Check Updates and then Check CDROM. The update is listed.
7. Select Install Updates and Accept the EULA. The update installs.
8. After the update is complete, you must go back to the appliance management console and select to restart the console.
9. Log back into the vSphere Web Client and check for any errors. Complete the following steps to scan VUM manually:



1. Go to Home > Hosts and Cluster.
2. Select a data center or cluster, click the Update Manager tab, and then click Scan for Updates.



10. After testing, if you need to back out, revert to snapshot or restore the vCenter with a previous backup.







 SSO-linked vCenter Server instances 

If you have primary and secondary vCenter Server instances, then your VCSAs are configured to be in a single vCenter Single Sign-On (SSO) domain. Each VCSA has a deployed VUM instance. The configuration properties that you modify are applied only to the VUM instance that you specify and are not propagated to the other instances in the group.

You can specify a VUM instance by selecting the name of the VCSA with which the VUM instance is registered from the navigation bar.
Use the revert function if you need to update a version of content that is already published to a version. For example, if you publish V1 of your content and then notice an error, you can revert your actions to V1 and use the draft environment to correct the error.

If you revert to a previous version, your published content isn't affected, but the content on the Actions page is overwritten with the version that you revert to. For example, if you decide to revert to V1 of your content, all content on the Actions page is overwritten with the V1 content so you can continue to work on it.

To revert to a previous version:



1. On the Publish page, click Revert.
2. On the Publish content tab, choose whether you want to save your in-progress actions as a content version so that you don't lose your current work. For example, if you are reverting to V1 and you choose to create a version, V2 is created so you can resume work on it later.

To create a version, check Publish content and add a description.

Zoom

![Publish content](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/revert-publish.png)

Publish content
3. Next, select the version of content that you want to revert to, then click Publish & Revert.

Zoom

![Revert to a prior version](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/revert-version.png)

Revert to a prior version
4. After you revert, you can go to the Actions page to make any fixes or updates. When you're ready to publish, go to the Publish page and publish your updated content as a new version (for example, V3).
Beta machine translation and language identification APIs upgraded
: The beta Machine Translator and beta Language Identification APIs have been upgraded and combined into the Language Translator API. To immediately start using the new service, understand and update your code to reflect these changes:



* New model_id parameter: In the beta API, you defined the sid parameter to select the model to use for translation. In this version, the sid parameter is renamed to model_id parameter. To retrieve the model_id allowed values, use the GET/language translator/api/v2/models operation. This returns a list of all models and their corresponding model_id values.
* Language pair support: Instead of selecting a model_id, you can now specify a source and target language instead, and the model will default to the one that's trained on the general news domain.
* JSON request body support: When making a POST translation request, you can now make the request as a JSON submission. The JSON formatting allows you to submit multiple paragraphs for translation, instead of just a single piece of text in the form submission format.
* JSON response body support: The translation request returns support JSON formatting as well as plain text formatting. The JSON format allows support for the translated words to be returned in multiple paragraphs instead of a single piece of text.
* Accept header support: The accept header can now be used to define the format of the response in all of the operations (text/plain or application/json).
* Language Identification support: Language identification methods have been added to this API. This allows you to identify the language of the input texts, and lists all supported languages that can be detected by the API.



New API authentication process
: The Language Translator service has a new API authentication process for service instances that are hosted in the following locations:



* Dallas as of June 15, 2018
* Frankfurt as of June 15, 2018
* London
* Seoul
* Sydney as of June 12, 2018
* Tokyo
* Washington, DC as of June 12, 2018



IBM Cloud is migrating to token-based Identity and Access Management (IAM) authentication. With some service instances, you authenticate to the API by using IAM.

IBM Cloud IAM available for service instances
Upgrading the service 

Learn how to upgrade the version of your installed service deployment.

IBM Cloud Pak for Data

This information applies only to installed deployments.



  Upgrade your deployment 

The steps to follow to upgrade your Discovery service instance are described in the IBM Cloud Pak for Data documentation. The following in-place upgrades are supported:



*  From a 4.6.x release to the latest 4.7 release. For more information, see [Upgrading Watson Discovery](https://www.ibm.com/docs/SSQNUZ_4.7.x/svc-discovery/discovery-upgrade.html).
*  From a 4.0.x, 4.5.x, or earlier 4.6.x release to the latest 4.6 release. For more information, see [Upgrading Watson Discovery](https://www.ibm.com/docs/SSQNUZ_4.6.x/svc-discovery/discovery-upgrade.html).
*  From a 4.0.x release or from one 4.5.x release to a later 4.5.y release. For more information, see [Upgrading Watson Discovery](https://www.ibm.com/docs/SSQNUZ_4.5.x/svc-discovery/discovery-upgrade.html).
*  From one 4.0.x release to a later 4.0.y release. For more information, see [Upgrading Watson Discovery to a newer 4.0 refresh](https://www.ibm.com/docs/SSQNUZ_4.0/svc-discovery/discovery-upgrade-v4.html).



You cannot do an in-place upgrade from releases prior to version 4.x. For information about how to move from a 2.x deployment to IBM Watson® Discovery 4.5, see [Backing up and restoring data in IBM Cloud Pak for Data](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-backup-restore).
Updating variables with Schematics API 



1. To update variables by using the IBM Cloud® Schematics Python APIs, create two Python files, and provide a name of your choice for those files, for example, schematics_variables_update.py and schematics_env_class.py.
2. Copy and paste the schematics_variables_update.py and schematics_env_class.py Python example code requests to the respective Python files.
3. Copy and paste the [config.json template file](https://cloud.ibm.com/docs/hpc-spectrum-scale?topic=hpc-spectrum-scale-update-variables&interface=apitemplate-file) to a JSON file, for example config.json.
4. Change the following parameters as part of the request:



* Provide the workspace ID w_id generated in both the following functions: schematic_obj.get_workspace(w_id="<w_id>) and schematic_obj.update_variables(w_id="<wi_id>").



5. Make sure to update the required parameters in the config.json file. For more information, see [Deployment values](https://cloud.ibm.com/docs/hpc-spectrum-scale?topic=hpc-spectrum-scale-deployment-values).
6. Run the Python script by using python3 to update the variables in the Schematics workspace in the IBM Cloud.



The following parameters might not be required in config.json as the Schematics update variables API uses the workspace ID w_id to update the variables against that workspace.

{
  "name": "Schematic Dev Workspace",
  "type": [
    "terraform_v0.13.7"
  ],
  "location": "us-south",
  "description": "Schematic Dev Workspace",
  "tags": [],
  "template_repo": {