vania-janet/multiturn-rag-retrieval-data huggingface dataset:
Using IBM Cloud Activity Tracker to audit user activity ![Enterprise plan only](https://cloud.ibm.com/docs-content/v1/content/417db917d18067d9dcc4cf2612564a9a87c3ddc8/assistant/includes/watson-assistant/includes/watson-assistant/images/enterprise.png) 

![IBM Cloud only](https://cloud.ibm.com/docs-content/v1/content/417db917d18067d9dcc4cf2612564a9a87c3ddc8/assistant/includes/watson-assistant/includes/watson-assistant/images/ibm-cloud.png)IBM Cloud only

You can use the IBM Cloud Activity Tracker service to track how users and applications interact with IBM Watson® Assistant in IBM Cloud®. This applies to both the classic and new experiences of Watson Assistant.

IBM Cloud Activity Tracker records user-initiated activities that change the state of a service in IBM Cloud. You can use this service to investigate abnormal activity and critical actions and to comply with regulatory audit requirements. In addition, you can be alerted about actions as they happen. The events that are collected comply with the Cloud Auditing Data Federation (CADF) standard. For more information, see [Getting started with IBM Cloud Activity Tracker](https://cloud.ibm.com/docs/activity-tracker?topic=activity-tracker-getting-started).



 Viewing events 

Events that are generated by an instance of the Watson Assistant service are automatically forwarded to the IBM Cloud Activity Tracker service instance that is available in the same location. However, if your service instance is hosted in the Washington DC location, create the IBM Cloud Activity Tracker service instance in the Dallas region.

IBM Cloud Activity Tracker can have only one instance per location. To view events, you must access the web UI of the IBM Cloud Activity Tracker service in the same location where your service instance is available. For more information, see [Navigating to the UI](https://cloud.ibm.com/docs/activity-tracker?topic=activity-tracker-launch).

!
[Build a database-driven Slackbot](https://cloud.ibm.com/docs/solution-tutorials?topic=solution-tutorials-slack-chatbot-database-watson)Build a database-driven Slackbot

In this tutorial, you are going to build a Slackbot which allows to search and create entries in a backend Db2 on Cloud database. The Slackbot is backed by the IBM Watson® Assistant service. You will integrate Slack and IBM Watson® Assistant using an Assistant integration. Db2 on Cloud is made available to Watson Assistant as custom extension.

Code Engine Watson Assistant

+1

Db2 on Cloud



* 2 hours
* 2023-05-05



[SQL Database for Cloud data](https://cloud.ibm.com/docs/solution-tutorials?topic=solution-tutorials-sql-database)SQL Database for Cloud data

This tutorial shows how to provision a SQL (relational) database service. As administrator, you create a table and load a large data set (city information) into the database. Then, you deploy a web app "worldcities" to Code Engine. The app allows regular users to look up records from the cloud database. The app is written in Python using the Flask framework.

Code Engine Db2 Warehouse on Cloud



* 2 hours
* 2023-05-05



[Text analysis with Code Engine](https://cloud.ibm.com/docs/solution-tutorials?topic=solution-tutorials-text-analysis-code-engine)Text analysis with Code Engine

In this tutorial, you will learn about IBM Cloud® Code Engine by deploying a text analysis with Natural Language Understanding application. You will create a Code Engine project, select the project and deploy Code Engine entities - applications and jobs - to the project. You will learn how to bind IBM Cloud services to your Code Engine entities. You will also understand the auto-scaling capability of Code Engine where instances are scaled up or down (to zero) based on incoming workload.

Code Engine Kubernetes service

+2

Object Storage,Natural Language Understanding



* 2 hours
* 2023-05-05
: The Watson Assistant tool now works with IBM Cloud Pak for Data 2.1. It does not work with stand-alone IBM Cloud Private. The following changes were made in this release:

Assistants are now available
: An assistant can manage user sessions on your behalf. See [Assistants](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-assistants).

Search skill is a new beta feature
: You can create a search skill to trigger a search in an external data source that you configure in Watson Discovery. See [Creating a search skill](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-skill-search-add).

Introducing dialog skills
: Instead of creating a workspace as the container for your training data and dialog, you create a dialog skill. See [Creating a dialog skill](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-skill-dialog-add).

Intent conflict resolution is available
: Prevent your assistant from answering the wrong question by keeping your intents distinct from one another. Intent conflict resolution is now available. It can find intents with overlapping user examples, and gives you a graphical user interface in which to fix them. Nondistinct intents can result in misclassifications of user input. See [Resolving intent conflicts](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-intentsintents-resolve-conflicts).

Synonym recommendations
: You can opt to see synonym recommendations that are made by Watson as you create a dictionary-based entity. See [Synonyms](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-entitiesentities-synonyms).





 21 February 2019 

IBM Watson® Assistant for IBM® Cloud Private version 1.1 is available
: The Watson Assistant tool now works with IBM Cloud Private 3.1.0. It does not work with IBM Cloud Private 2.1.0.3.
Getting started with Watson Assistant 

In this short tutorial, we introduce IBM Watson® Assistant and walk you through the process of creating your first assistant.



 Before you begin 



1. Provision an instance of Watson Assistant for IBM Cloud Pak® for Data. For information about how to provision an instance, see [Provisioning the Watson Assistant service](https://www.ibm.com/docs/en/cloud-paks/cp-data/4.5.x?topic=setup-provisioning-service).







 Step 1: Open Watson Assistant 



1. From the IBM Cloud Pak for Data web client menu, select Services > Instances.
2. From the Instances page, click on the name of your Watson Assistant instance, and then click Launch tool.



A new browser tab or window opens and Watson Assistant is displayed.





 Step 2: Create an assistant 

An assistant is a cognitive bot to which you add skills that enable it to interact with your customers in useful ways.



1. Click the Assistants icon ![Assistants menu icon](https://cloud.ibm.com/docs-content/v1/content/a2b18c153837bce00a5b4de496e4b4ca64bbf56e/assistant-data/images/nav-ass-icon.png), and then click Create assistant.

![Create assistant button on the Assistants page.](https://cloud.ibm.com/docs-content/v1/content/a2b18c153837bce00a5b4de496e4b4ca64bbf56e/assistant-data/images/gs-create-assistant.png)
2. Name the assistant My first assistant.
3. Click Create assistant.

![Finish creating the new assistant](https://cloud.ibm.com/docs-content/v1/content/a2b18c153837bce00a5b4de496e4b4ca64bbf56e/assistant-data/images/gs-create-assistant-done.png)







 Step 3: Create a dialog skill
accessKey: COS_ACCESS_KEY
name: wa-data-governor-cos-credentials
secretKey: COS_SECRET_KEY
cosImporter:
fromBucket: data-exhaust-backup-wa-data-governor-e58d5f4a1344
clearObjectTags: false
filter:
 Modify prefix value.
prefix: "20230322"
fromTenant: ""
 Modify schedule to run importer cron less frequently
schedule: '* * * * '
 See "How to generate a JSON mapping defintion" below for instructions on how to create the next line
schema: ${JSON_ID_MAPPING}
workers: 3
Show more
2. In the script, replace these placeholders with the actual values:



* <enter_COS_key_here>
* <enter_COS_secret_access_key_here>
* <enter_COS_endpoint here>



3. Run the script.
4. Wait 15 to 20 minutes and then check if the data governor pods are stable.
5. When the pods are stable, check that the importer cron is running as scheduled.
6. When the importer pod completes, check that chat logs data were imported in the correct assistant chat logs by opening Watson Assistant and checking the Analyze screen for imported data.





Parameters

 Parameter Description 

 fromBucket Cloud Object Storage bucket with the data to be imported 
 schedule Schedule for Cloud Object Storage cron job to run 
 clearObjectTags Set to true to allow the importer to rerun on already processed Cloud Object Storage objects 
 workers Number of worker threads. Increasing the number requires more job resources. 
 filter Provides control over which objects are imported from the Cloud Object Storage bucket 
 prefix Allows for objects from a specific date to be imported 
 documentTimestampWindow Allows for objects during a specific time range to be imported 
 cos Cloud Object Storage credentials 
 schema Transformation schema, which allows the importer to modify Watson Assistant fields to allow analytic data from pprd instance to be viewed in train.
3. In How do you want to assign access?, choose Access policy.

Zoom

![Access policy](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/access-policy.png)

Access policy
4. In Service, choose Watson Assistant, then click Next.

Zoom

![Service](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/access-service.png)

Service
5. In Resources, choose either All resources or Specific resources.

If you choose All resources, the user can access all the instances of Watson Assistant in your account.

If you choose Specific resources, you can narrow access in Attribute type. With this setting, you might need to add multiple access policies for a user to grant the correct access. For more information, see [Example of limiting access to one assistant](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-access-controlaccess-control-limit-access).

Choices include:



Attribute types

 Resource attribute type Description 

 Service Instance Choose a specific service instance of Watson Assistant 
 Assistant, Environment, or Skill ID Enter the ID value for the resource. Use the Assistant IDs and API details section in Assistant settings to get the ID values for your assistant, environments, action skill, or dialog skill. 
 Resource Type If you enter an ID value, choose Assistant ID, Environment ID, or Skill ID to identify the ID type 
 Region Choose a specific region (for example, Dallas or London) 
 Resource Group Enter or choose a resource group that you created 



Zoom

!
Sending events to Segment ![Enterprise plan only](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/enterprise.png) 

IBM Cloud

You can use the Segment extension to send Watson Assistant events to Segment.



 Overview 

With this extension, you can use [Segment](https://segment.com/) to capture and centralize data about your customers' behavior, including their interactions with your assistant. Events are sent from Watson Assistant to Segment, making them available to destinations such as data warehouses, raw data tools, and analytic tools.

For more information about the events that are sent to Segment, see [Segment event reference](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-segment-event-reference).

This feature is available only to Enterprise plan users.





 Adding the extension to the draft environment 

To add the Segment extension to your assistant, follow these steps:



1. On the ![Integrations icon](https://cloud.ibm.com/docs-content/v1/content/ca9232b3702768f24bb897f48f10778fcda28718/watson-assistant/images/integrations-icon.png)Integrations page, scroll to the Extensions section and find the tile for the Segment extension.
2. Click Add. Review the overview of the extension and click Add to configure it for your assistant.

When you first add the Segment extension to an assistant, the configuration settings you provide are applied only to the draft environment. You must complete configuration for the draft environment before you can add the extension in the live environment.
3. In the Connect step, click the link to log in to your Segment account in another browser tab.

If you do not already have a Segment account, click Sign up for free account to create one. Verify your email address and complete your profile to activate your account.
4. In the Segment web app, go to your workspace.
If a customer accidentally input Pflegegelb, the assistant would incorrectly match with Pflege rather than Pflegegeld.

With this fix, the Pflegegelb input value would correctly match Pflegegeld, not Pflege. For more information, see [How fuzzy matching works](https://cloud.ibm.com/docs/assistant?topic=assistant-entitiesentities-fuzzy-matching).





 11 August 2022 

Algorithm version options available in more languages
: Algorithm version options are now available in Arabic, Czech, and Dutch. This allows you to choose which Watson Assistant algorithm to apply to your future trainings. For more information, see [Algorithm version](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-algorithm-version).

Improved enhanced intent detection available in more languages
: Previously, the exact match in enhanced intent detection was improved to better handle small differences between training examples and runtime utterances when the differences do not change the meaning of a sentence. For example, suppose in your training examples, covid-19 is in the covid intent and @doctortype_facilitytype around Palm Beach is in the find_provide_master intent. In this example, the @doctortype_facilitytype direct entity reference contains entity values, including hospital. At run time, covid19 is predicted as 100% confident for the covid intent, and hospital around palm beach is predicted as 100% confident for the find_provide_master intent.

This update now includes the following languages: Arabic, Czech, and Dutch. For more information, see [Accessing intents](https://cloud.ibm.com/docs/assistant?topic=assistant-expression-languageexpression-language-intent).





 24 June 2022 

Algorithm version options available in more languages
: Algorithm version options are now available in Chinese (Traditional), Japanese, and Korean. This allows you to choose which Watson Assistant algorithm to apply to your future trainings. For more information, see [Algorithm version](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-algorithm-version).

Improved enhanced intent detection available in more languages
This documentation is for the classic Watson Assistant experience. To see the documentation for the new Watson Assistant, please go [here](https://cloud.ibm.com/docs/watson-assistant).



 Advanced analysis and log-related tasks 

Learn about APIs and other tools you can use to access and analyze log data.



 Using Jupyter notebooks for analysis 

IBM created Jupyter notebooks that you can use to analyze the behavior or your assistant. A Jupyter notebook is a web-based environment for interactive computing. You can run small pieces of code that process your data, and you can immediately view the results of your computation.

You can use the notebooks with English-language skills only.



 Analysis notebooks 

There is a set of analysis notebooks that you can use with standard Python tools and a set that is designed for optimal use with IBM Watson® Studio.

Watson Studio is a product that provides an environment in which you can pick and choose the tools you need to analyze and visualize data, to cleanse and shape data, to ingest streaming data, or to create, train, and deploy machine learning models. See the [product documentation](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/welcome-main.html) for more details.

The [Watson Assistant Continuous Improvement Best Practices Guide](https://github.com/watson-developer-cloud/assistant-improve-recommendations-notebook/raw/master/notebook/IBM%20Watson%20Assistant%20Continuous%20Improvement%20Best%20Practices.pdf) describes how to get the most out of these notebooks.





 Using the notebooks with Watson Studio 

The following notebooks are available:



* [Dialog skill analysis for Watson Assistant](https://dataplatform.cloud.ibm.com/exchange/public/entry/view/4d77701840fcb2f21587e39fdb887049)
[Screen capture of the connection dialog.](https://cloud.ibm.com/docs-content/v1/content/417db917d18067d9dcc4cf2612564a9a87c3ddc8/assistant/images/zd-account-key.png)
* Return to the setup page in Watson Assistant, and then paste the key into the field.



4. Install the Watson Assistant private application in your Zendesk Chat subdomain.

When you create a Zendesk Chat account, you specify a subdomain. Afterward, your Zendesk console is available from a URL with the syntax: <subdomain>.zendesk.com. For example, ibm.zendesk.com.

IBM provides an application that you can install in your Zendesk Chat domain. When a customer asks to speak to a person, your assistant will share a chat summary for the transferred conversation with the Zendesk agent by using this private app.



* Download the Watson Assistant Zendesk application from the Zendesk Chat setup page in Watson Assistant.

On Safari, the application files are extracted from the ZIP file into a folder. To keep the file archived as a .zip file, so you can upload it later, edit the Safari preferences. Clear the Open safe files after downloading checkbox.
* Log in to Zendesk with a user ID that has administrative privileges.
* Install the Watson Assistant Zendesk app to your Zendesk Chat subdomain as a new private app.



* First, make sure the Zendesk Agent Workspace is not enabled for your account: From the Zendesk navigation pane, go to Settings, and then click Agents. Deselect the Enable the Zendesk Agent Workspace checkbox.
* Then download the app. From the Chat dashboard navigation pane, expand Settings, and then click Account.
* Open the App tab.
* Click Upload private app, and then browse for the application file that you downloaded earlier.



![Screen capture of the Zendesk Account page where you can upload a private app.]
Publishing dialog and actions 

If the dialog feature is enabled, the publishing and deployment processes remain the same. However, some slight differences in functionality exist.

To learn about the overall publishing and deployment model for Watson Assistant, see the [Publishing and deploying your assistant overview](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-publish-overview). For more information about the Publish page and how the publishing process works, see [Publishing your content](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-publish). The following slight differences exist when the dialog feature is enabled in an assistant:



*  On the Publish page, the information in the Content type column lists whether your content changes contain a dialog.
*  The version tiles on the Publish and Environments pages show whether the published content contains actions, or actions and a dialog. For example, if the dialog feature is enabled in your assistant, the version tile displays Contains actions & dialog.
*  When you export a version of your content from the Publish page, two JSON files are downloaded. One file is for actions and one file is for the dialog.
Service architecture 

Learn about the components that comprise IBM Watson® Assistant for IBM Cloud Pak® for Data and how data flows through the service.

Watson Assistant for IBM Cloud Pak for Data consists of the following types of resources:



* [Microservices](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-architecturearchitecture-microservices)
* [Supporting data stores](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-architecturearchitecture-datasources)
* [Training component](https://cloud.ibm.com/docs/assistant-data?topic=assistant-data-architecturearchitectture-slad)



Watson Assistant for IBM Cloud Pak for Data uses the following patterns to communicate and pass information among its resources:



* REST API: Sends representational state transfer (REST) API calls over secure HTTP.
* gRPC: Makes method calls by using an open source remote procedure call framework, which enables the service to call a resource that is running on another system in the cluster as if it were a local object. For more information, see [gRPC](https://grpc.io/).
* LiteLinks: Uses the LiteLinks protocol that was developed by IBM. LiteLinks has a custom service discovery layer that serves as a wrapper for an underlying Apache Thrift-based remote procedure call framework.



The following diagram illustrates the components that are used by the service.

![Diagram of the components used by the assistant service](https://cloud.ibm.com/docs-content/v1/content/a2b18c153837bce00a5b4de496e4b4ca64bbf56e/assistant-data/images/components.png)

The following sections provide more detail about each resource that is used by the system. The objective is to give you information that can help you to do initial resource planning and help you to manage changes in data needs over time.



 Microservices 

Watson Assistant consists of the following stateless microservices:
For more information, see [Storing a value in a session variable](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-manage-infostore-session-variable).

Changes to validation of OpenAPI specifications
: When you build a custom extension, you work with OpenAPI specification files. This release includes changes to the validation of OpenAPI files, which might affect the connection between your actions and extensions

You can import an action with references to a custom extension and Watson Assistant can automatically connect the action and extension. With the validation change, modifications to the OpenAPI specification for your custom extension might affect this automatic connection. For more information, see [Building a custom extension](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-build-custom-extension).





 22 May 2023 

Changes to the date and number formats in assistant responses
: Beginning 22 May 2023, customers might see changes to the date and number formats in assistant responses.

Examples of date changes include removed or added periods, such as:



* In Spanish, 18 abr. 2021 changes to 18 abr 2021
* In Portuguese, 18 de abr changes to 18 de abr.



The delimiter character changes for numbers in some languages. For example, in French, nonbreaking space (NBSP) changes to narrow no-break space (NNBSP).

These changes are the result of migrating the Watson Assistant platform to Java 17, where locale values are updated by using specifications in [CLDR 39](https://cldr.unicode.org/index/downloads/cldr-39).

To avoid or minimize the impact of similar changes in the future, you can use [Display formats](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-actions-global-settingsactions-global-settings-display-formats).





 18 May 2023 

Differences in contextual entity detection for dialog skills with few annotations