Merge pull request #4392 from ovh/YC-Fixes-230323

AI & Machine Learning - Rasa Tutorials - Fixes and improvements

Author: OVH-Team-Guides

pages/index.md

@@ -769,7 +769,7 @@
                 + [AI Training - Tutorial - Connect to VSCode via remote](platform/ai/training_tuto_04_vscode_remote)
                 + [AI Training - Tutorial - Use tensorboard inside a job](platform/ai/training_tuto_05_tensorboard)
                 + [AI Training - Tutorial - Compare models with W&B for audio classification task](platform/ai/training_tuto_06_models_comparaison_weights_and_biases)
-                + [AI Training - Tutorial - Train a rasa chatbot with docker and AI Training](platform/ai/training_tuto_07_train_rasa_chatbot)
+                + [AI Training - Tutorial - Train a Rasa chatbot with Docker and AI Training](platform/ai/training_tuto_07_train_rasa_chatbot)
         + [AI Deploy](public-cloud-ai-and-machine-learning-ai-deploy)
             + [Guides](public-cloud-ai-and-machine-learning-ai-deploy-guides)
                 + [AI Deploy - Capabilities and limitations](platform/ai/deploy_guide_01_capabilities)
@@ -789,7 +789,7 @@
                 + [AI Deploy - Tutorial - Deploy and call a spam classifier with FastAPI](platform/ai/deploy_tuto_08_fastapi_spam_classifier)
                 + [AI Deploy - Tutorial - Create and deploy a Speech to Text application using Streamlit](platform/ai/deploy_tuto_09_streamlit_speech_to_text_app)
                 + [AI Deploy - Tutorial - How to load test your application with Locust](platform/ai/deploy_tuto_10_locust)
-                + [AI Deploy - Tutorial - Deploy a rasa chatbot with a simple flask app](platform/ai/deploy_tuto_11_rasa_chatbot_flask)
+                + [AI Deploy - Tutorial - Deploy a Rasa chatbot with a simple Flask app](platform/ai/deploy_tuto_11_rasa_chatbot_flask)
     + [Data Analytics](public-cloud-data-analytics)
         + [Data Processing](public-cloud-data-analytics-data-processing)
             + [Concepts](public-cloud-data-analytics-data-processing-concepts)

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.de-de.md

@@ -4,7 +4,6 @@ slug: notebooks/create-rasa-chatbot
 excerpt: Understand how to create  and train a chatbot with AI Notebooks
 section: AI Notebooks - Tutorials
 order: 10
-hidden: true
 updated: 2023-03-20
 routes:
     canonical: 'https://docs.ovh.com/gb/en/publiccloud/ai/notebooks/create-rasa-chatbot/'
@@ -14,7 +13,7 @@ routes:
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/de/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/de/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -41,7 +40,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/de/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/de/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -119,7 +118,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/de/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/de/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-asia.md

@@ -4,15 +4,14 @@ slug: notebooks/create-rasa-chatbot
 excerpt: Understand how to create  and train a chatbot with AI Notebooks
 section: AI Notebooks - Tutorials
 order: 10
-hidden: true
 updated: 2023-03-20
 ---
 
 **Last updated 20th March, 2023.**
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +38,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/asia/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/asia/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +116,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-au.md

@@ -4,15 +4,14 @@ slug: notebooks/create-rasa-chatbot
 excerpt: Understand how to create  and train a chatbot with AI Notebooks
 section: AI Notebooks - Tutorials
 order: 10
-hidden: true
 updated: 2023-03-20
 ---
 
 **Last updated 20th March, 2023.**
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +38,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/au/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/au/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +116,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-ca.md

@@ -4,15 +4,14 @@ slug: notebooks/create-rasa-chatbot
 excerpt: Understand how to create  and train a chatbot with AI Notebooks
 section: AI Notebooks - Tutorials
 order: 10
-hidden: true
 updated: 2023-03-20
 ---
 
 **Last updated 20th March, 2023.**
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +38,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ca/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ca/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +116,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-ie.md

@@ -4,15 +4,14 @@ slug: notebooks/create-rasa-chatbot
 excerpt: Understand how to create  and train a chatbot with AI Notebooks
 section: AI Notebooks - Tutorials
 order: 10
-hidden: true
 updated: 2023-03-20
 ---
 
 **Last updated 20th March, 2023.**
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +38,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ie/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ie/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +116,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-sg.md

@@ -4,15 +4,14 @@ slug: notebooks/create-rasa-chatbot
 excerpt: Understand how to create  and train a chatbot with AI Notebooks
 section: AI Notebooks - Tutorials
 order: 10
-hidden: true
 updated: 2023-03-20
 ---
 
 **Last updated 20th March, 2023.**
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +38,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/sg/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/sg/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +116,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-us.md

@@ -4,15 +4,14 @@ slug: notebooks/create-rasa-chatbot
 excerpt: Understand how to create  and train a chatbot with AI Notebooks
 section: AI Notebooks - Tutorials
 order: 10
-hidden: true
 updated: 2023-03-20
 ---
 
 **Last updated 20th March, 2023.**
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +38,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/us/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/us/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +116,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback