Merge pull request #11147 from RasaHQ/update-links-rasa-x-docs

update /docs/rasa-x links

docs/docs/command-line-interface.mdx

@@ -164,8 +164,8 @@ from scratch.
 
 ## rasa interactive
 
-You can [use Rasa X in local mode](https://rasa.com/docs/rasa-x) to do interactive learning in a UI,
-check out the [docs](https://rasa.com/docs/rasa-x/user-guide/test-assistant#talk-to-your-bot)
+You can [use Rasa X in local mode](https://rasa.com/docs/rasa-enterprise) to do interactive learning in a UI,
+check out the [docs](https://rasa.com/docs/rasa-enterprise/user-guide/test-assistant#talk-to-your-bot)
 for more details.
 
 If you'd rather use the command line, you can start an interactive learning session by running:
@@ -209,8 +209,8 @@ The following arguments can be used to configure the interactive learning sessio
 
 ## rasa shell
 
-You can [use Rasa X in local mode](https://rasa.com/docs/rasa-x) to talk to your assistant in a UI.
-Check out the [Rasa X docs](https://rasa.com/docs/rasa-x/user-guide/test-assistant#talk-to-your-bot)
+You can [use Rasa X in local mode](https://rasa.com/docs/rasa-enterprise) to talk to your assistant in a UI.
+Check out the [Rasa X docs](https://rasa.com/docs/rasa-enterprise/user-guide/test-assistant#talk-to-your-bot)
 for more details.
 
 If you'd rather use the command line, you can start a chat session by running:
@@ -489,7 +489,7 @@ should be published:
 
 :::tip Import conversations into Rasa X
 This command is most commonly used to import old conversations into Rasa X to annotate
-them. Read more about [importing conversations into Rasa X](https://rasa.com/docs/rasa-x/installation-and-setup/deploy#1-import-existing-conversations-from-rasa-open-source).
+them. Read more about [importing conversations into Rasa X](https://rasa.com/docs/rasa-enterprise/installation-and-setup/deploy#1-import-existing-conversations-from-rasa-open-source).
 :::
 
 ## rasa evaluate markers
@@ -543,13 +543,13 @@ Python Logging Options:
 ## rasa x
 
 Rasa X is a tool for practicing Conversation-Driven Development.
-You can find more information about it <a className="reference external" href="https://rasa.com/docs/rasa-x/" target="_blank">here</a>.You can start Rasa X in local mode by executing
+You can find more information about it <a className="reference external" href="https://rasa.com/docs/rasa-enterprise/" target="_blank">here</a>.You can start Rasa X in local mode by executing
 
 ```bash
 rasa x
 ```
 
-To be able to start Rasa X you need to have Rasa X local mode [installed](https://rasa.com/docs/rasa-x/installation-and-setup/install/local-mode)
+To be able to start Rasa X you need to have Rasa X local mode [installed](https://rasa.com/docs/rasa-enterprise/installation-and-setup/install/local-mode)
 and you need to be in a Rasa project directory.
 
 

docs/docs/connectors/your-own-website.mdx

@@ -7,7 +7,7 @@ description: Deploy and Run a Rasa Chat Bot on a Website
 
 If you just want an easy way for users to test your bot, the best option
 is usually the chat interface that ships with Rasa X, where you can [invite users
-to test your bot](https://rasa.com/docs/rasa-x/user-guide/share-assistant/#share-your-bot).
+to test your bot](https://rasa.com/docs/rasa-enterprise/user-guide/share-assistant/#share-your-bot).
 
 If you already have an existing website and want to add a Rasa assistant to it,
 you can use the [Rasa Chat Widget](#chat-widget) a widget which you can incorporate into your existing webpage by adding a HTML snippet.

docs/docs/contextual-conversations.mdx

@@ -100,7 +100,7 @@ always have a higher [policy priority](./policies.mdx#policy-priority) and will
 
 The [TEDPolicy](https://blog.rasa.com/unpacking-the-ted-policy-in-rasa-open-source/) is made to handle
 unexpected user behaviors. For example,
-in the conversation below (extracted from a conversation on [Rasa X](https://rasa.com/docs/rasa-x/user-guide/review-conversations/)):
+in the conversation below (extracted from a conversation on [Rasa X](https://rasa.com/docs/rasa-enterprise/user-guide/review-conversations/)):
 
 ```yaml-rasa
 stories:
@@ -137,7 +137,7 @@ path, without asking all the qualifying questions first.
 
 Since the machine-learning policy has generalized to this situation, you should add this story
 to your training data to continuously improve your bot and help the model generalize
-better in future. [Rasa X](https://rasa.com/docs/rasa-x/) is a tool that can help
+better in future. [Rasa X](https://rasa.com/docs/rasa-enterprise/) is a tool that can help
 you improve your bot and make it more contextual.
 
 

docs/docs/conversation-driven-development.mdx

@@ -24,7 +24,7 @@ CDD is not a linear process; you'll circle back to the same actions over and ove
 
 Read more about these actions and the concept of CDD on the [Rasa Blog](https://blog.rasa.com/conversation-driven-development-a-better-approach-to-building-ai-assistants/).
 
-You can also check out [Rasa X](https://rasa.com/docs/rasa-x/), a purpose-built tool for CDD.
+You can also check out [Rasa X](https://rasa.com/docs/rasa-enterprise/), a purpose-built tool for CDD.
 
 ## CDD in early stages of development
 
@@ -42,13 +42,13 @@ If you're at the earliest stage of bot development, it might seem like CDD has n
     CDD leads to frequent, smaller updates to your bot as you gather insights from bot conversations. [Setting up a CI/CD pipeline](setting-up-ci-cd.mdx) early on in development will enable you to act quickly on what you see in conversations.
 
 
-At this stage, you can [install Rasa X in local mode](https://rasa.com/docs/rasa-x/installation-and-setup/installation-guide/#local-mode) to make it easier to share your bot with test users, collect conversations, and apply NLU and Story best practices based on the conversations you collect.
+At this stage, you can [install Rasa X in local mode](https://rasa.com/docs/rasa-enterprise/installation-and-setup/installation-guide/#local-mode) to make it easier to share your bot with test users, collect conversations, and apply NLU and Story best practices based on the conversations you collect.
 
 
 ## CDD with a bot in production
 
 Once your bot is in production, you'll have more conversations to gain insights from. Then you can fully apply CDD actions.
-At this stage, you can [install Rasa X on a server](https://rasa.com/docs/rasa-x/installation-and-setup/installation-guide/#helm-chart)
+At this stage, you can [install Rasa X on a server](https://rasa.com/docs/rasa-enterprise/installation-and-setup/installation-guide/#helm-chart)
 to both deploy your bot and enable CDD with a bot in production.
 
 ### Review

docs/docs/deploy/deploy-rasa-x.mdx

@@ -10,9 +10,9 @@ import variables from './../variables.json';
 
 ## a. Deploy Rasa X
 
-Visit the [Installation Guide for Rasa X](https://rasa.com/docs/rasa-x/installation-and-setup/installation-guide) where you can learn about available installation methods and
+Visit the [Installation Guide for Rasa X](https://rasa.com/docs/rasa-enterprise/installation-and-setup/installation-guide) where you can learn about available installation methods and
 how to deploy Rasa X by following one of them.
 
 ## b. Connect Rasa Open Source deployment to Rasa X
 
-Visit the [Connect Rasa Open Source deployment](https://rasa.com/docs/rasa-x/installation-and-setup/deploy#2-connect-rasa-open-source-deployment-the-rasa-helm-chart) section to learn how to connect your Rasa Assistant to Rasa X deployment.
+Visit the [Connect Rasa Open Source deployment](https://rasa.com/docs/rasa-enterprise/installation-and-setup/deploy#2-connect-rasa-open-source-deployment-the-rasa-helm-chart) section to learn how to connect your Rasa Assistant to Rasa X deployment.

docs/docs/deploy/deploy-rasa.mdx

@@ -285,4 +285,4 @@ Visit [the Rasa helm chart README](https://github.com/RasaHQ/helm-charts/tree/ma
 ## Next Steps
 
 - Visit [the Rasa helm chart repository](https://github.com/RasaHQ/helm-charts/tree/main/charts/rasa) where you can find examples of configuration
-- Visit [the Rasa X docs](https://rasa.com/docs/rasa-x/) and learn how to [integrate your Rasa Open Source deployment with Rasa X](https://rasa.com/docs/rasa-x/installation-and-setup/deploy#2-connect-rasa-open-source-deployment-the-rasa-helm-chart).
+- Visit [the Rasa X docs](https://rasa.com/docs/rasa-enterprise/) and learn how to [integrate your Rasa Open Source deployment with Rasa X](https://rasa.com/docs/rasa-enterprise/installation-and-setup/deploy#2-connect-rasa-open-source-deployment-the-rasa-helm-chart).

docs/docs/deploy/introduction.mdx

@@ -21,10 +21,10 @@ conversations to inform further development of your assistant.
 
 Connecting your deployed assistant to Rasa X makes it easy to share your assistant
 with test users via the [share your assistant feature in
-Rasa X](https://rasa.com/docs/rasa-x/user-guide/share-assistant#share-your-bot).
+Rasa X](https://rasa.com/docs/rasa-enterprise/user-guide/share-assistant#share-your-bot).
 Then, when you're ready to make your assistant available via one or more [Messaging and Voice Channels](../messaging-and-voice-channels.mdx),
 you can add them to your existing deployment set up.
-See the [Rasa X Installation Guide](https://rasa.com/docs/rasa-x/installation-and-setup/installation-guide/) to learn how to deploy Rasa X and connect it to your Rasa Open Source deployment.
+See the [Rasa X Installation Guide](https://rasa.com/docs/rasa-enterprise/installation-and-setup/installation-guide/) to learn how to deploy Rasa X and connect it to your Rasa Open Source deployment.
 
 
 ## Recommended Deployment Method

docs/docs/event-brokers.mdx

@@ -7,7 +7,7 @@ description: Find out how open source chatbot framework Rasa allows you to strea
 
 An event broker allows you to connect your running assistant to other services that process the data coming
 in from conversations. For example, you could [connect your live assistant to
-Rasa X](https://rasa.com/docs/rasa-x/installation-and-setup/deploy#connect-an-existing-deployment)
+Rasa X](https://rasa.com/docs/rasa-enterprise/installation-and-setup/deploy#connect-an-existing-deployment)
 to review and annotate conversations or forward messages to an external analytics
 service. The event broker publishes messages to a message streaming service,
 also known as a message broker, to forward Rasa [Events](https://rasa.com/docs/action-server/events) from the Rasa server to other services.

docs/docs/glossary.mdx

@@ -125,7 +125,7 @@ Dual Intent and Entity Transformer. The default NLU architecture used by Rasa Op
 
   Natural Language Understanding (NLU) deals with parsing and understanding human language into a structured format.  
 
-## [NLU Inbox](https://rasa.com/docs/rasa-x/user-guide/annotate-nlu-examples)
+## [NLU Inbox](https://rasa.com/docs/rasa-enterprise/user-guide/annotate-nlu-examples)
 
   The area within Rasa X where new user messages are collected for review and annotation. Only messages not already represented in the training data will appear in the NLU Inbox.
 
@@ -153,7 +153,7 @@ Dual Intent and Entity Transformer. The default NLU architecture used by Rasa Op
 
   An element in the Rasa NLU pipeline (see [Pipeline](#pipeline)) that processes incoming messages. Components perform tasks ranging from entity extraction to intent classification to pre-processing.
 
-## [Rasa X](https://rasa.com/docs/rasa-x/)
+## [Rasa X](https://rasa.com/docs/rasa-enterprise/)
 
   A tool for [conversation-driven development](./conversation-driven-development.mdx). Rasa X helps teams share and test an assistant built with Rasa Open Source, annotate user messages, and view conversations.
 
@@ -175,7 +175,7 @@ Dual Intent and Entity Transformer. The default NLU architecture used by Rasa Op
   answering FAQs, filling [Forms](./forms.mdx), or handling
   [Fallbacks](./fallback-handoff.mdx#fallbacks).
 
-## [Share Your Bot](https://rasa.com/docs/rasa-x/user-guide/share-assistant)
+## [Share Your Bot](https://rasa.com/docs/rasa-enterprise/user-guide/share-assistant)
   Rasa X feature that generates a link to a chat UI for test users. **Share your bot** allows test users to talk to an assistant while it’s still in development. 
 
 ## [Slot](./domain.mdx#slots)
@@ -186,7 +186,7 @@ Dual Intent and Entity Transformer. The default NLU architecture used by Rasa Op
 
   Training data format for the dialogue model, consisting of a conversation between a user and a bot. The user's messages are represented as annotated intents and entities, and the bot’s responses are represented as a sequence of actions. 
 
-## [Talk to Your Bot](https://rasa.com/docs/rasa-x/user-guide/share-assistant#talk-to-your-bot)
+## [Talk to Your Bot](https://rasa.com/docs/rasa-enterprise/user-guide/share-assistant#talk-to-your-bot)
 
   Chat interface within Rasa X that allows bot developers to talk to, test, and correct their assistant. Can be enabled in strict Interactive Learning mode, which requires each prediction to be confirmed before the conversation can proceed.
 

docs/docs/reaching-out-to-user.mdx

@@ -152,7 +152,7 @@ The response will use the value from the slot `plant` to warn about the specific
 
 ### Try it out
 
-To try out the dry plant notification example, you'll need to start either [Rasa X](https://rasa.com/docs/rasa-x/)
+To try out the dry plant notification example, you'll need to start either [Rasa X](https://rasa.com/docs/rasa-enterprise/)
 or a [CallbackChannel](./connectors/your-own-website.mdx#callbackinput).
 
 :::caution
@@ -432,7 +432,7 @@ intents:
 
 ### Try it Out
 
-To try out reminders you'll need to start either [Rasa X](https://rasa.com/docs/rasa-x/)
+To try out reminders you'll need to start either [Rasa X](https://rasa.com/docs/rasa-enterprise/)
 or a [CallbackChannel](./connectors/your-own-website.mdx#callbackinput).
 You'll also need to start the action server to schedule, react to, and cancel your reminders.
 See the [reminderbot README](https://github.com/RasaHQ/rasa/blob/main/examples/reminderbot) for details.

docs/docs/rei/deploy.mdx

@@ -171,6 +171,6 @@ For the rest channel, no credentials are required. To learn more see: https://ra
 
 ## Next steps
 
-- [Learn how to deploy Rasa X / Enterprise](https://rasa.com/docs/rasa-x/installation-and-setup/installation-guide)
-- [Learn how to connect Rasa OSS to Rasa X / Enterprise](https://rasa.com/docs/rasa-x/installation-and-setup/deploy#2-connect-rasa-open-source-deployment-the-rasa-helm-chart)
+- [Learn how to deploy Rasa X / Enterprise](https://rasa.com/docs/rasa-enterprise/installation-and-setup/installation-guide)
+- [Learn how to connect Rasa OSS to Rasa X / Enterprise](https://rasa.com/docs/rasa-enterprise/installation-and-setup/deploy#2-connect-rasa-open-source-deployment-the-rasa-helm-chart)
 - Visit [Rasa OSS Helm chart](https://github.com/RasaHQ/helm-charts/tree/main/charts/rasa)

docs/docs/setting-up-ci-cd.mdx

@@ -27,7 +27,7 @@ whatever Git repository you use.
 
 ## Continuous Integration (CI)
 
-The best way to improve an assistant is with frequent [incremental updates](https://rasa.com/docs/rasa-x/user-guide/fix-problems).
+The best way to improve an assistant is with frequent [incremental updates](https://rasa.com/docs/rasa-enterprise/user-guide/fix-problems).
 No matter how small a change is, you want to be sure that it doesn't introduce
 new problems or negatively impact the performance of your assistant.
 
@@ -116,8 +116,8 @@ Rasa server if the CI results are satisfactory. For example, to upload a model t
 curl -k -F "model=@models/my_model.tar.gz" "https://example.rasa.com/api/projects/default/models?api_token={your_api_token}"
 ```
 
-If you are using Rasa X, you can also [tag the uploaded model](https://rasa.com/docs/rasa-x/pages/http-api/#tag/Models/paths/~1projects~1{project_id}~1models~1{model}~1tags~1{tag}/put)
-as production (or whichever deployment you want to tag if using multiple [deployment environments](https://rasa.com/docs/rasa-x/enterprise/deployment-environments/#)):
+If you are using Rasa X, you can also [tag the uploaded model](https://rasa.com/docs/rasa-enterprise/pages/http-api/#tag/Models/paths/~1projects~1{project_id}~1models~1{model}~1tags~1{tag}/put)
+as production (or whichever deployment you want to tag if using multiple [deployment environments](https://rasa.com/docs/rasa-enterprise/enterprise/deployment-environments/#)):
 
 ```bash
 curl -X PUT "https://example.rasa.com/api/projects/default/models/my_model/tags/production"

docs/docs/testing-your-assistant.mdx

@@ -185,7 +185,7 @@ Conversation testing is only as thorough and accurate as the test
 cases you include, so you should continue to grow your set of test stories
 as you make improvements to your assistant. A good rule of thumb to follow is that you should aim for your test stories
 to be representative of the true distribution of real conversations.
-Rasa X makes it easy to [add test conversations based on real conversations](https://rasa.com/docs/rasa-x/user-guide/test-assistant/#how-to-create-tests).
+Rasa X makes it easy to [add test conversations based on real conversations](https://rasa.com/docs/rasa-enterprise/user-guide/test-assistant/#how-to-create-tests).
 
 See the [CLI documentation on `rasa test`](./command-line-interface.mdx#rasa-test) for
 more configuration options.

docs/docs/writing-stories.mdx

@@ -497,9 +497,9 @@ your bot doesn't know how to do something yet, you can just teach it!
 
 In Rasa Open Source, you can run interactive learning in the command line with
 [`rasa interactive`](./command-line-interface.mdx#rasa-interactive).
-[Rasa X](http://rasa.com/docs/rasa-x) provides a UI for interactive learning,
+[Rasa X](http://rasa.com/docs/rasa-enterprise) provides a UI for interactive learning,
 and you can use any user conversation as a starting point.
-See [Talk to Your Bot](https://rasa.com/docs/rasa-x/user-guide/share-assistant/#talk-to-your-bot)
+See [Talk to Your Bot](https://rasa.com/docs/rasa-enterprise/user-guide/share-assistant/#talk-to-your-bot)
 in the Rasa X docs.
 
 ### Command-line Interactive Learning

docs/docusaurus.config.js

@@ -11,7 +11,7 @@ const isPreview = process.env.NETLIFY && process.env.CONTEXT === 'deploy-preview
 
 const BASE_URL = '/docs/rasa/';
 const SITE_URL = 'https://rasa.com';
-// NOTE: this allows switching between local dev instances of rasa/rasa-x
+// NOTE: this allows switching between local dev instances of rasa/rasa-enterprise
 const SWAP_URL = isDev ? 'http://localhost:3001' : SITE_URL;
 
 let existingVersions = [];
@@ -86,9 +86,9 @@ module.exports = {
         },
         {
           target: '_self',
-          label: 'Rasa X',
+          label: 'Rasa Enterprise',
           position: 'left',
-          href: `${SWAP_URL}/docs/rasa-x/`,
+          href: `${SWAP_URL}/docs/rasa-enterprise/`,
         },
         {
           target: '_self',

rasa/shared/constants.py

@@ -32,7 +32,7 @@
     f"{DOCS_URL_MIGRATION_GUIDE}#rasa-21-to-rasa-22"
 )
 DOCS_URL_TELEMETRY = DOCS_BASE_URL + "/telemetry/telemetry"
-DOCS_BASE_URL_RASA_X = "https://rasa.com/docs/rasa-x"
+DOCS_BASE_URL_RASA_X = "https://rasa.com/docs/rasa-enterprise"
 DOCS_BASE_URL_ACTION_SERVER = "https://rasa.com/docs/action-server"
 
 INTENT_MESSAGE_PREFIX = "/"