vania-janet/multiturn-rag-retrieval-data huggingface dataset:
: Used for pagination. The number of records to skip.

--expand EXPAND (optional)
: Expanded view the segment details.

--tags TAGS (optional)
: Filter segments by a list of comma-separated tags.

--sort SORT (optional)
: Sort the details based on the specified attribute.





 Example 

To list all segments, run the following command:

ibmcloud ac segment list



 Output 

The command returns the following output:

name segment_id
India IBMers ibm_employees_01
IBM Employees ibm_employees









 ibmcloud ac segment create 

You can create a segment, by using the command:

ibmcloud ac segment create {--file FILE-PATH | --name NAME [--segment_id SEGMENT_ID] --description DESCRIPTION --tags TAGS --rules RULES}



 Command options 

--name NAME
: Segment name. Required field - input either as a flag or from file.

--segment_id SEGMENT_ID (optional)
: Segment ID. If this value is not provided, name will automatically become the ID. Optional field - input either as a flag or from file.

--description DESCRIPTION
: Description of the segment. Required field - input either as a flag or from file.

--rules RULES
: List of rules that determine whether the entity is part of the segment. Required field - input either as a flag or from file.

--tags TAGS
: Tags associated with the segment. Required field - input either as a flag or from file.

--file FILE
: Input through a file. File format Supported - JSON





 Example 

To create a collection with name sample using flags ([click here](https://cloud.ibm.com/docs/app-configuration?topic=app-configuration-cli-plugin-app-configuration-cliac-fileinput) for using commands with '--file' flag), run the following command:
element '<element name>' as <auxiliary view name>
with attribute '<attribute name>' as <column name>]
and attribute '<attribute name>' as <column name>]
, element ...]];





 Description 



* <input view name>.<text column>



* <input view name>

Specifies the name of the input view on which to do the detag process. The <input view name> can be a simple identifier or a double-quoted identifier.
* <text column>

Specifies the text field of the input view on which to do the detag process. The <text column> can be a simple identifier or a double-quoted identifier.



* <output view name>

Specifies the name of the output view that contains the detagged text. The output view contains a single column that is called text, which holds the detagged text. The <output view name> can be a simple identifier or a double-quoted identifier.
* always|never

Specifies whether to verify that the contents are HTML or XML before the detag statement is processed. When you run non-HTML and non-XML text through a detagger, problems can occur if the text contains XML special characters such as <, >, or &. If the detect content_type clause is missing, the default value is always and the system always detects content.



* always

Specifies that verification always occurs before the operation is attempted to avoid problems with parsing documents that are not HTML or XML. If the value of the <text column> does not appear to contain a markup, the system skips detagging for the current document.
* never

Specifies that verification never occurs before the detag operation is attempted. The system attempts to detag the target text, even if the text does not contain any HTML or XML content.



* <element name>

Specifies the name of the HTML or XML element to be annotated. The optional annotate clause can direct the runtime component to remember information about the removed tags by creating one or more views.
* <auxiliary view name>
* addresses: An array that identifies addresses.



* text: An address.
* location: The location of the address as defined by its begin and end indexes.



* contacts: An array that defines the names and roles of contacts that are identified in the input document.



* name: The name of a contact.
* role: The role of the contact.



* mentions: n array of objects that identify mentions of the party.



* text: A string that lists the name of the party.
* location: The location of the mention as defined by its begin and end indexes.





The values of role that can be returned for contracts include, but are not limited to:



Supported role values

 role Description 

 Buyer The party responsible for paying for the goods or services that are listed in the contract. 
 End User The party who interacts with the provided goods or services, explicitly distinguished from the Buyer. 
 None No party was identified for the element. 
 Supplier The party responsible for providing the goods or services that are listed in the contract. 







 Categories 

The categories array defines the subject matter of the sentence. Currently, supported categories include:



Supported categories

 categories Description 

 Amendments Elements that specify changes to the contract after it was signed, or alterations to a standard contract. Includes discussions of the conditions for changing the terms of a contract. 
 Asset Use Elements that refer to how one party may or may not use the assets of another party. This category specifically applies to one party having access to or using assets such as licenses, equipment, tools, or personnel of the other party while conducting their duties under the agreement, including permissions and restrictions thereon. This category does not extend to specifications of a party's obligations or rights regarding any purchased goods, services, licenses, and so on, as those goods are the party's own assets, rather than assets of another party. 
 Assignments Elements that describe the transfer of rights, obligations, or both to a third party. 
 Audits Elements referring to either the right of a party to examine or review compliance, or requirements that a party be available for inspection or compliance review. This category includes references to record keeping (primarily as it relates to the right of inspection) and the maintenance and retention of activity records that may be examined.
Add a [tag](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_overviewoverview_elements_tag) that you specify in the command to an existing image, copy the tag to another repository, or copy the tag to a repository in a different namespace. When you copy a tag, any Red Hat® signatures for its [digest](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_overviewoverview_elements_digest) are also copied. The target image, TARGET_IMAGE, is the new image and the source image, SOURCE_IMAGE, is the existing image in IBM Cloud Container Registry. The source and target images must be in the same region. You can reference the source image that you want to tag by either digest, repository@digest, or by tag, repository:tag. You must reference the target image by tag.

You can identify source images by using either the digest <dns>/<namespace>/<repo>@<digest> or by tag <dns>/<namespace>/<repo>:<tag>. You must reference the target image by tag, <dns>/<namespace>/<repo>:<tag>. Where <dns> is the domain name, <namespace> is the namespace, <repo> is the repository, <digest> is the digest, and <tag> is the tag.

To find the names of your images, use one of the following alternatives:



* To identify your image by digest, run the ibmcloud cr image-digests command. Combine the content of the Repository column (repository) and the Digest column (digest) separated by an at (@) symbol to create the image name in the format repository@digest.
* To identify your image by tag, run the ibmcloud cr image-list command. Combine the content of the Repository column (repository) and Tag column (tag) separated by a colon (:) to create the image name in the format repository:tag.



If you get a manifest error when you try to tag your image, see [Why do I get a manifest type error when I tag my image?]
In the preceding example, you could query the category label by accessing enriched_text.categories.label

The label is the detected category. The hierarchy levels are separated by forward slashes. The score for that category ranges from 0.0 to 1.0. The higher the score, the greater the confidence in that category.





 Concept tagging 

Identifies concepts with which the input text is associated, based on other concepts and entities that are present in that text. Concept tagging understands how concepts relate, and can identify concepts that are not directly referenced in the text. For example, if an article mentions CERN and the Higgs boson, the Concepts API functions identifies Large Hadron Collider as a concept even if that term is not mentioned explicitly in the page. Concept tagging enables higher level analysis of input content than just basic keyword identification.

Example portion of a document enriched with Concept Tagging:

{
"text": "The stockholders were pleased that Acme Corporation plans to build a new factory in Atlanta, Georgia.",
"enriched_text": {
"concepts": [
{
"text": "Acme Corporation",
"relevance": 0.91136,
"dbpedia_resource": "http://dbpedia.org/resource/Acme_Corporation"
},
{
"text": "Factory",
"relevance": 0.886784,
"dbpedia_resource": "http://dbpedia.org/resource/Factory"
}
]
Show more

In the preceding example, you can query the concept text type by accessing enriched_text.concepts.text

The relevance score ranges from 0.0 to 1.0. The higher the score, the more relevant the concept. Links to the resource(s) are provided, if applicable.





 Semantic Role extraction 

Identifies subject, action, and object relations within sentences in the input content. Relation information can be used to automatically identify buying signals, key events, and other important actions.

Example portion of a document enriched with Semantic Role Extraction:

{
In a dictionary, individual lexical items are assigned part of speech (POS) tags. For example, the word 'fly' can be identified as a verb or a noun.
* performance

The measurement of a Watson system in terms of accuracy, precision, and recall, for example, when answering questions, discovering relationships, or annotating text.
* pre-annotation

The process of annotating a set of documents prior to human annotation. Documents can be pre-annotated by using a rule-based model, a machine-learning model, IBM Watson® Natural Language Understanding, or a dictionary. Pre-annotation can help human annotators more quickly prepare a set of ground truth documents.
* precision

A measurement that specifies the proportion of results that are relevant. Precision, which is a positive predictive value, is determined by the number of correct positive results divided by the number of all positive results. Accuracy is best measured by using both precision and recall. See also [accuracy](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-glossarygloss_A) and [recall](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-glossarygloss_R).
* processing engine archive (PEAR)

A .pear archive file that includes an Unstructured Information Management Architecture (UIMA) analysis engine and all of the resources that are required to use it for custom analysis.







 R 



* recall

A measurement that specifies the percentage of relevant results returned, out of all available relevant results. Recall, which is a measure of sensitivity, is determined by the number of correct positive results divided by the number of positive results that should have been returned. Accuracy is best measured by using both precision and recall. See also [accuracy](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-glossarygloss_A) and [precision](https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-glossarygloss_P).
* relation
: Value of the feature when it is unavailable. Required field - input either as a flag or from file.

--tags TAGS
: Tags associated with the feature. Required field - input either as a flag or from file.

--segment_rules SEGMENT_RULES
: Specify the targeting rules that are used to set different values for different segments.

--file FILE
: Input through the file. File format Supported - JSON





 Example 

To update description a feature with ID ibm-discount using flags ([click here](https://cloud.ibm.com/docs/app-configuration-cli-plugin?topic=app-configuration-cli-plugin-app-configuration-cliac-fileinput) for using commands with '--file' flag), run the following command:

ibmcloud ac feature update-values --environment_id "production" --name "Indian IBMers" --feature_id "ibm-discount" --description "Discount given to IBM Indian employees" --enabled_value true --disabled_value false --segment_rules '[{"rules":{"segments":"ibm_employees"]}],"value": true,"order": 1}]' --tags "discount,sale"



 Output 

The command returns the following output:

updated_time 2021-02-02T18:06:03Z
description Discount given to IBM Indian employees
enabled_value true
disabled_value false
segment_rules <Array>
created_time 2021-02-02T17:52:46Z
name Indian IBMers
type BOOLEAN
collections <Array>









 ibmcloud ac feature delete 

You can delete a feature, by using the command:

ibmcloud ac feature delete --environment_id ENVIRONMENT_ID --feature_id FEATURE_ID



 Command options 

--environment_id ENVIRONMENT_ID
: Environment ID

--feature_id FEATURE_ID
: Feature ID





 Example 

To delete a feature with ID ibm-discount, run the following command:
Tags are case-sensitive, and the maximum length of a tag is 128 characters.



* The characters that are permitted to name tags are A-Z, 0-9, spaces, underscore, hyphen, period, and colon.
* Colons turn the tag into a string where you can isolate two logical parts, like a key:value pair. You can't use a colon in a tag without creating this pairing.
* A comma separates tags and can't be used within the tag name itself.



If you add PII information in the name, you might be disclosing sensitive data to others in the same account.

When you define your tags, do not add sensitive information in the tag name.

Tags are visible to all members of an account.

To control tag visibility, circulate tagging guidelines, and let users know that tags are visible account-wide.







 Define the log ingestion strategy 

For non-IBM Cloud enabled services, you must decide the method to collect and forward logs from a log source that you want to monitor to a logging instance.

In IBM Log Analysis, you can collect and forward data to a logging instance by using any of the following methods:



* logging agent: Logging agent that automatically collects and forwards logs to 1 logging instance in your account.
* Syslog: Logging daemon that collects information across multiple devices and system-services, and forwards logs to 1 logging instance in your account.
* REST API: API that you can use to send log data and custom metadata to 1 logging instance in your account.
* Code libraries: Libraries that you can use to code ingestion of logs from your apps and services to 1 logging instance. logging offer libraries for Node.JS, Python, Rails, Ruby, Go, iOS, Java, and PHP.



For any method that you adopt, you have the flexibility to choose the logging instance where you want to send data per log source. Decide how many instances you might need to collect data from all your log sources based on who can see the data and the type of data that is collected. Avoid sending data to a logging instance that has the platform logs flag enabled.
* section_titles: An array that contains one object per section or subsection that is detected in the input document. Sections and subsections are not nested. Instead, they are flattened out and can be placed back in order by using the begin and end values of the element and the level value of the section.



* text: A string that lists the section title, if detected.
* location: The location of the title in the input document as defined by its begin and end indexes.
* level: An integer that indicates the level at which the section is located in the input document. For example, represents a root-level section, represents a subsection within the level section.
* element_locations: An array that specifies the begin and end values of the sentences in the section.



* leading_sentences: An array that contains one object per leading sentence of a list or subsection, in parallel with the section_titles and paragraph arrays. The object details the leading sentences in the matching section or subsection. As in the section_titles array, the objects are not nested. Instead, they are flattened out and can be placed back in order by using the begin and end values of the element or any level markers in the input document.



* text: A string that lists the leading sentence, if detected.
* location: The location of the leading sentence in the input document as defined by its begin and end indexes.
* element_locations: An array that specifies the begin and end values of the leading sentences in the section.



* paragraphs: An array that contains one object per paragraph, in parallel with the section_titles and leading_sentences arrays. Each object lists the span (beginning and end location) of the corresponding paragraph.



* location: The location of the paragraph in the input document as defined by its begin and end indexes.





* parties: An array that defines the parties that are identified by the service.



* party: A string that provides the normalized form of the party's name.
* role: A string that identifies the role of the party.
* importance: A string that identifies the importance of the party. Possible values include Primary for a primary party and Unknown for a non-primary party.
--tag-names value
: Comma separated list of tag names.

-q, --quiet
: Suppress verbose output.

This command is only valid for access management tags. For example:



* Run the following command to create the access management tag project:myproject:

ibmcloud resource tag-create —tag-names “project:myproject”









 ibmcloud resource tag-attach 

Attach one or more tags to a resource:

ibmcloud resource tag-attach --tag-names TAG_NAMES (--resource-name NAME | --resource-id RESOURCE_ID ) [--resource-type RESOURCE_TYPE] [--tag-type TAG_TYPE] [--account-id ACCOUNT_ID]



 Command options 

--tag-names value
: Comma-separated list of tag names.

--resource-name value
: Name of the resource on which the tags should be attached.

--resource-id value
: CRN of the resource on which the tags should be attached (for Classic Infrastructure resource, it is the ID of the resource).

--resource-type value
: Type of the tag. Only allowed values are: user, service or access (default value : user).

--tag-type value
: The type of the tag. The only allowed values are user or service. The default value is user.

--account-id value
: The ID of the account that owns the resources to be tagged (required if tag-type is set to service).

-q, --quiet
: Suppress verbose output.





 Examples 



* To attach the user tag MyTag to a Kubernetes cluster named MyCluster, first look for the CRN of the cluster you would like to tag:

ibmcloud resource search 'type:k8-cluster AND name:MyCluster'

Take note of the CRN, which is a string similar to the following example:
Include indications of where in the car the part is, or something which just refers to a portion of a car without being a specific part. <br> <br>Can be plural. Can include specification of position in the vehicle, such as "[driver airbag]", "[RF door]" (meaning right-front), "[RR] passenger", "[LF and RF air bags]", "[first row passive/automatic restraints]", "[safety system] with EDR capabilities". <br> <br>Include towed boats, tanks, etc., except semi-trailers, which have a distinct year/model/manufacturer. Cross-section, front plane, tire, steering wheel, airbag, etc. 
 PERSON Any person described in an accident scene in a report (could be a driver or a passenger/occupant of a vehicle, pedestrian, or witness). <br> <br>Don't annotate adjectives, so don't annotate "a [69-year-old] drove", but do annotate "a 69-year-old [male] drove". Can be plural, for example, "LR and RF [occupants]". Excludes people who arrive after incident. <br> <br>>In the absence of an "animal" entity type, use PERSON to tag wildlife involved in / causing collisions, as their ability to move makes them more like a PERSON than a STRUCTURE. <br> <br>Note: "passenger airbag" is a PART_OF_CAR; it does not imply that a person is present. 
 STRUCTURE A structure that is on, near, or part of a road. Include specific road adjectives likely to be relevant to the configuration of an accident; omit other adjectives. [two-lane, two-way road], [left lane], eastbound [lane], 2-foot [ditch], [right lane line], [exit ramp], [pole], [tree], steep descending [embankment] 
 VEHICLE Any reference to vehicle other than MODEL, MANUFACTURER, and MODEL_YEAR. Can be plural, in which case coreference is very unlikely and no part-of-group relation.
"google_key_purpose" : "encrypt_decrypt",
"google_kms_algorithm" : "google_symmetric_encryption"
} ]





 Tag[] 

The following example shows the format of the Tag[] object.

[ {
"name" : "exampleString",
"value" : "exampleString"
} ]





 VaultReferenceInCreationRequest 

The following example shows the format of the VaultReferenceInCreationRequest object.

{
"id" : "5295ad47-2ce9-43c3-b9e7-e5a9482c362b"
}
--tags TAGS (optional)
: Tags associated with the environment. Required field - input either as a flag or from file.

--color_code COLOR_CODE (optional)
: Color code to distinguish the environment. The Hex code for the color. Required field - input either as a flag or from file.

--file FILE
: Input through the file. File format Supported - JSON





 Example 

To update an environment with ID prodEnvironment using flags ([click here](https://cloud.ibm.com/docs/app-configuration-cli-plugin?topic=app-configuration-cli-plugin-app-configuration-cliac-fileinput) for using commands with '--file' flag), run the following command:

ibmcloud ac environment update --name Production_Environment --environment_id prodEnvironment --description sampleUpdatedDesc --tags sampleUpdatedTag --color_code "FF0000"



 Output 

The command returns the following output:

name Production_Environment
environment_id prodEnvironment
description sampleUpdatedDesc
tags sampleUpdatedTag
color_code FF0000
created_time 2021-05-21T05:28:07.000Z
updated_time 2021-05-21T05:33:00.000Z









 ibmcloud ac environment delete 

You can delete an environment, by using the command:

ibmcloud ac environment delete --environment_id ENVIRONMENT_ID



 Command options 

--environment_id ENVIRONMENT_ID
: Environment ID.





 Example 

To delete an environment with ID prodEnvironment, run the following command:

ibmcloud ac environment delete --environment_id prodEnvironment



 Output 

The command returns the following output:

OK









 ibmcloud ac collection list 

You can list all collections, by using the command: