Merge branch 'main' of https://github.com/allegroai/clearml-docs

docs/best_practices/data_best_practices.md

@@ -9,7 +9,8 @@ See [Hyper-Datasets](../hyperdatasets/overview.md) for ClearML's advanced querya
 
 The following are some recommendations for using ClearML Data. 
 
-![Dataset UI gif](../img/gif/dataset.gif)
+![Dataset UI gif](../img/gif/dataset.gif#light-mode-only)
+![Dataset UI gif](../img/gif/dataset_dark.gif#dark-mode-only)
 
 ## Versioning Datasets
 

docs/deploying_clearml/enterprise_deploy/change_artifact_links.md

@@ -0,0 +1,78 @@
+---
+title: Changing CleaML Artifacts Links
+---
+
+This guide describes how to update artifact references in the ClearML Enterprise server.
+
+By default, artifacts are stored on the file server; however, an external storage such as AWS S3, Minio, Google Cloud 
+Storage, etc. may be used to store artifacts. References to these artifacts may exist in ClearML databases: MongoDB and ElasticSearch.  
+This procedure should be used if external storage is being migrated to a different location or URL.
+
+:::important
+This procedure does not deal with the actual migration of the data--only with changing the references in ClearML that 
+point to the data.
+:::
+
+## Preparation
+
+### Version Confirmation
+
+To change the links, use the `fix_fileserver_urls.py` script, located inside the `allegro-apiserver` 
+Docker container. This script will be executed from within the `apiserver` container. Make sure the `apiserver` version 
+is 3.20 or higher.
+
+### Backup
+
+It is highly recommended to back up the ClearML MongoDB and ElasticSearch databases before running the script, as the 
+script changes the values in the databases, and can't be undone.
+
+## Fixing MongoDB links
+
+1. Access the `apiserver` Docker container:  
+  * In `docker-compose:`
+    
+     ```commandline
+     sudo docker exec -it allegro-apiserver /bin/bash
+      ```
+    
+  * In Kubernetes:
+   
+     ```commandline
+     kubectl exec -it -n clearml <clearml-apiserver-pod-name> -- bash
+     ```
+
+1. Navigate to the script location in the `upgrade` folder:
+
+   ```commandline
+   cd /opt/seematics/apiserver/server/upgrade
+   ```
+     
+1. Run the following command:
+ 
+    :::important
+    Before running the script, verify that this is indeed the correct version (`apiserver` v3.20 or higher, 
+    or that the script provided by ClearML was copied into the container).
+    ::::
+ 
+    ```commandline
+    python3 fix_fileserver_urls.py \
+    --mongo-host mongodb://mongo:27017 \
+    --elastic-host elasticsearch:9200 \
+    --host-source "<old fileserver host and/or port, as in artifact links>" \
+    --host-target "<new fileserver host and/or port>" --datasets
+    ```
+
+:::note Notes
+* If MongoDB or ElasticSearch services are accessed from the `apiserver` container using custom addresses, then 
+`--mongo-host` and `--elastic-host` arguments should be updated accordingly.  
+* If ElasticSearch is set up to require authentication then the following arguments should be used to pass the user 
+and password: `--elastic-user <es_user> --elastic-password <es_pass>`
+:::
+
+The script fixes the links in MongoDB, and outputs `cURL` commands for updating the links in ElasticSearch.
+
+## Fixing the ElasticSearch Links
+
+Copy the `cURL` commands printed by the script run in the previous stage, and run them one after the other. Make sure to 
+inspect that a "success" result was returned from each command. Depending on the amount of the data in the ElasticSearch, 
+running these commands may take some time.

docs/deploying_clearml/enterprise_deploy/import_projects.md

@@ -0,0 +1,240 @@
+---
+title: Exporting and Importing ClearML Projects
+---
+
+When migrating from a ClearML Open Server to a ClearML Enterprise Server, you may need to transfer projects. This is done 
+using the `data_tool.py` script. This utility is available in the `apiserver` Docker image, and can be used for 
+exporting and importing ClearML project data for both open source and Enterprise versions.
+
+This guide covers the following:
+* Exporting data from Open Source and Enterprise servers  
+* Importing data into an Enterprise server 
+* Handling the artifacts stored on the file server. 
+
+:::note 
+Export instructions differ for ClearML open and Enterprise servers. Make sure you follow the guidelines that match your 
+server type.
+:::
+
+## Exporting Data
+
+The export process is done by running the ***data_tool*** script that generates a zip file containing project and task 
+data. This file should then be copied to the server on which the import will run.
+
+Note that artifacts stored in the ClearML ***file server*** should be copied manually if required (see [Handling Artifacts](#handling-artifacts)).
+
+### Exporting Data from ClearML Open Servers
+
+#### Preparation
+
+* Make sure the `apiserver` is at least Open Source server version 1.12.0.  
+* Note that any `pending` or `running` tasks will not be exported. If you wish to export them, make sure to stop/dequeue 
+them before exporting.
+
+#### Running the Data Tool
+
+Execute the data tool within the `apiserver` container.
+
+Open a bash session inside the `apiserver` container of the server:  
+* In docker-compose:
+  
+  ```commandline
+  sudo docker exec -it clearml-apiserver /bin/bash
+  ```
+
+* In Kubernetes:
+  
+  ```commandline
+  kubectl exec -it -n <clearml-namespace> <clearml-apiserver-pod-name> -- bash 
+  ```
+
+#### Export Commands
+**To export specific projects:**
+
+```commandline
+python3 -m apiserver.data_tool export --projects <project_id1> <project_id2>
+--statuses created stopped published failed completed --output <output-file-name>.zip
+```
+
+As a result, you should get a `<output-file-name>.zip` file that contains all the data from the specified projects and 
+their children.
+
+**To export all the projects:**
+
+```commandline
+python3 -m apiserver.data_tool export \
+  --all \
+  --statuses created stopped published failed completed \
+  --output <output-file-name>.zip
+```
+
+#### Optional Parameters
+
+* `--experiments <list of experiment IDs>` - If not specified then all experiments from the specified projects are exported  
+* `--statuses <list of task statuses>` - Export tasks of specific statuses. If the parameter 
+  is omitted, only `published` tasks are exported  
+* `--no-events` - Do not export task events, i.e. logs and metrics (scalar, plots, debug samples).
+
+Make sure to copy the generated zip file containing the exported data.
+
+### Exporting Data from ClearML Enterprise Servers
+
+#### Preparation
+
+* Make sure the `apiserver` is at least Enterprise Server version 3.18.0.  
+* Note that any `pending` or `running` tasks will not be exported. If you wish to export them, make sure to stop/dequeue 
+before exporting.
+
+#### Running the Data Tool
+
+Execute the data tool from within the `apiserver` docker container.
+
+Open a bash session inside the `apiserver` container of the server:  
+* In `docker-compose`:
+  
+  ```commandline
+  sudo docker exec -it allegro-apiserver /bin/bash
+  ```
+  
+* In Kubernetes:
+  
+  ```commandline
+  kubectl exec -it -n <clearml-namespace> <clearml-apiserver-pod-name> -- bash 
+  ```
+
+#### Export Commands
+
+**To export specific projects:**
+
+```commandline
+PYTHONPATH=/opt/seematics/apiserver/trains-server-repo python3 data_tool.py \
+  export \
+  --projects <project_id1> <project_id2> \
+  --statuses created stopped published failed completed \
+  --output <output-file-name>.zip
+```
+
+As a result, you should get `<output-file-name>.zip` file that contains all the data from the specified projects and 
+their children.
+
+**To export all the projects:**
+
+```commandline
+PYTHONPATH=/opt/seematics/apiserver/trains-server-repo python3 data_tool.py \
+  export \
+  --all \
+  --statuses created stopped published failed completed \
+  --output <output-file-name>.zip
+```
+
+#### Optional Parameters
+
+* `--experiments <list of experiment IDs>` - If not specified then all experiments from the specified projects are exported  
+* `--statuses <list of task statuses>` - Can be used to allow exporting tasks of specific statuses. If the parameter is
+  omitted, only `published` tasks are exported.  
+* `--no-events` - Do not export task events, i.e. logs, and metrics (scalar, plots, debug samples).
+
+Make sure to copy the generated zip file containing the exported data.
+
+## Importing Data
+
+This section explains how to import the exported data into a ClearML Enterprise server.
+
+### Preparation
+
+* It is highly recommended to back up the ClearML databases before importing data, as import injects data into the 
+databases, and can't be undone.
+* Make sure you are working with `apiserver` version 3.22.3 or higher.
+* Make the zip file accessible from within the `apiserver` container by copying the exported data to the 
+`apiserver` container or to a folder on the host, which the `apiserver` is mounted to.
+
+### Usage
+
+The data tool should be executed from within the `apiserver` docker container.
+
+1. Open a bash session inside the `apiserver` container of the server:  
+   * In `docker-compose`:
+  
+     ```commandline
+     sudo docker exec -it allegro-apiserver /bin/bash
+     ```
+  
+   * In Kubernetes:
+  
+     ```commandline
+     kubectl exec -it -n <clearml-namespace> <clearml-apiserver-pod-name> -- bash 
+     ```
+
+1. Run the data tool script in *import* mode:
+
+   ```commandline
+   PYTHONPATH=/opt/seematics/apiserver/trains-server-repo python3 data_tool.py \
+     import \
+     <path to zip file> \ 
+     --company <company_id> \
+     --user <user_id>
+   ```
+
+   * `company_id`- The default company ID used in the target deployment. Inside the `apiserver` container you can 
+     usually get it from the environment variable `CLEARML__APISERVER__DEFAULT_COMPANY`.   
+     If you do not specify the `--company` parameter then all the data will be imported as `Examples` (read-only)  
+   * `user_id` - The ID of the user in the target deployment who will become the owner of the imported data
+
+## Handling Artifacts
+
+***Artifacts*** refers to any content which the ClearML server holds references to. This can include: 
+* Dataset or Hyper-Dataset frame URLs
+* ClearML artifact URLs 
+* Model snapshots
+* Debug samples
+
+Artifacts may be stored in any external storage (e.g., AWS S3, minio, Google Cloud Storage) or in the ClearML file server.  
+* If the artifacts are **not** stored in the ClearML file server, they do not need to be moved during the export/import process, 
+as the URLs registered in ClearML entities pointing to these artifacts will not change.  
+* If the artifacts are stored in the ClearML file server, then the file server content must also be moved, and the URLs 
+  in the ClearML databases must point to the new location. See instructions [below](#exporting-file-server-data-for-clearml-open-server).
+
+### Exporting File Server Data for ClearML Open Server
+
+Data in the file server is organized by project. For each project, all data references by entities in that project is 
+stored in a folder bearing the name of the project. This folder can be located in: 
+
+```
+/opt/clearml/data/fileserver/<project name>
+```
+
+The entire projects' folders content should be copied to the target server (see [Importing Fileserver Data](#importing-file-server-data)).
+
+### Exporting File Server Data for ClearML Enterprise Server
+
+Data in the file server is organized by tenant and project. For each project, all data references by entities in that 
+project is stored in a folder bearing the name of the project. This folder can be located in:
+
+```
+/opt/allegro/data/fileserver/<company_id>/<project name>
+```
+
+The entire projects' folders content should be copied to the target server (see  [Importing Fileserver Data](#importing-file-server-data)).
+
+## Importing File Server Data
+
+### Copying the Data
+
+Place the exported projects' folder(s) content into the target file server's storage in the following folder:
+
+```
+/opt/allegro/data/fileserver/<company_id>/<project name>
+```
+
+### Fixing Registered URLs
+
+Since URLs pointing to the file server contain the file server's address, these need to be changed to the address of the 
+new file server.  
+
+Note that this is not required if the new file server is replacing the old file server and can be accessed using the same 
+exact address.
+
+Once the projects' data has been copied to the target server, and the projects themselves were imported, see 
+[Changing CleaML Artifacts Links](change_artifact_links.md) for information on how to fix the URLs.  
+
+

docs/deploying_clearml/enterprise_deploy/sso_multi_tenant_login.md

@@ -0,0 +1,98 @@
+---
+title: Multi-Tenant Login Mode
+---
+
+In a multi-tenant setup, each external tenant can be represented by an SSO client defined in the customer Identity provider 
+(Keycloak). Each ClearML tenant can be associated with a particular external tenant. Currently, only one 
+ClearML tenant can be associated with a particular external tenant
+
+## Setup IdP/SSO Client in Identity Provider
+
+1. Add the following URL to "Valid redirect URIs": `<clearml_webapp_address>/callback_<client_id>`  
+2. Add the following URLs to "Valid post logout redirect URIs": 
+
+   ```
+   <clearml_webapp_address>/login
+   <clearml_webapp_address>/login/<external tenant ID>
+   ```
+3. Make sure the external tenant ID and groups are returned as claims for a each user
+
+## Configure ClearML to use Multi-Tenant Mode
+
+Set the following environment variables in the ClearML enterprise helm chart under the `apiserver` section:  
+* To turn on the multi-tenant login mode:
+
+  ```
+  - name: CLEARML__services__login__sso__tenant_login
+    value: "true"
+  ```
+* To hide any global IdP/SSO configuration that's not associated with a specific ClearML tenant:  
+
+  ```
+  - name: CLEARML__services__login__sso__allow_settings_providers
+    value: "false"
+  ```
+  
+Enable `onlyPasswordLogin` by setting the following environment variable in the helm chart under the `webserver` section:
+
+``` 
+- name: WEBSERVER__onlyPasswordLogin`  
+  value: “true”`
+```
+
+## Setup IdP for a ClearML Tenant
+
+To set an IdP client for a ClearML tenant, you’ll need to set the ClearML tenant settings and define an identity provider:
+
+1. Call the following API to set the ClearML tenant settings:
+
+   ```
+   curl $APISERVER_URL/system.update_company_sso_config -H "Content-Type: application/json" -u $APISERVER_KEY:$APISERVER_SECRET -d'{  
+     "company": "<company_id>",  
+     "sso": {  
+       "tenant": "<external tenant ID>",  
+       "group_mapping": {  
+         "IDP group name1": "Clearml group name1",  
+         "IDP group name2": "Clearml group name2"  
+       },  
+       "admin_groups": ["IDP admin group name1", "IDP admin group name2"]  
+     }}'  
+   ```
+2. Call the following API to define the ClearML tenant identity provider:
+
+   ```
+   curl $APISERVER_URL/sso.save_provider_configuration -H "Content-Type: application/json" -u $APISERVER_KEY:$APISERVER_SECRET -d'{  
+     "provider": "keycloak", 
+     "company": "<company_id>",  
+     "configuration": {  
+       "id": "<some unique id here, you can use company_id>",  
+       "display_name": "<The text that you want to see on the login button>",  
+       "client_id": "<client_id from IDP>",  
+       "client_secret": "<client secret from IDP>",  
+       "authorization_endpoint": "<authorization_endpoint from IDP OpenID configuration>",  
+       "token_endpoint": "<token_endpoint from IDP OpenID configuration>",  
+       "revocation_endpoint": "<revocation_endpoint from IDP OpenID configuration>",  
+       "end_session_endpoint": "<end_session_endpoint from IDP OpenID configuration>",  
+       "logout_from_provider": true,  
+       "claim_tenant": "tenant_key",  
+       "claim_name": "name",  
+       "group_enabled": true,  
+       "claim_groups": "ad_groups_trusted",  
+       "group_prohibit_user_login_if_not_in_group": true  
+     }}'  
+   ```
+   The above configuration assumes the following:  
+   * On logout from ClearML, the user is also logged out from the Identity Provider  
+   * External tenant ID for the user is returned under the `tenant_key` claim  
+   * User display name is returned under the `name` claim  
+   * User groups list is returned under the `ad_groups_trusted` claim  
+   * Group integration is turned on and a user will be allowed to log in if any of the groups s/he belongs to in the 
+     IdP exists under the corresponding ClearML tenant (this is after group name translation is done according to the ClearML tenant settings)
+
+## Webapp Login
+
+When running in multi-tenant login mode, a user belonging to some external tenant should use the following link to log in:  
+
+```
+<clearml_webapp_address>/login/<external tenant ID>
+```

docs/integrations/autokeras.md

@@ -95,7 +95,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/catboost.md

@@ -93,7 +93,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/fastai.md

@@ -92,7 +92,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/keras.md

@@ -105,7 +105,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/lightgbm.md

@@ -94,7 +94,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/megengine.md

@@ -90,7 +90,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/pytorch.md

@@ -114,7 +114,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/pytorch_lightning.md

@@ -120,7 +120,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/scikit_learn.md

@@ -96,7 +96,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/tao.md

@@ -113,7 +113,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/tensorflow.md

@@ -107,7 +107,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/transformers.md

@@ -78,7 +78,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/xgboost.md

@@ -120,7 +120,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/yolov5.md

@@ -169,7 +169,8 @@ and shuts down instances as needed, according to a resource budget that you set.
 
 ### Cloning, Editing, and Enqueuing
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)
 
 Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task 
 with the new configuration on a remote machine:

docs/integrations/yolov8.md

@@ -166,4 +166,5 @@ with the new configuration on a remote machine:
 
 The ClearML Agent executing the task will use the new values to [override any hard coded values](../clearml_agent.md). 
 
-![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
+![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

package-lock.json

@@ -15,7 +15,7 @@
         "@docusaurus/plugin-google-analytics": "^3.6.1",
         "@docusaurus/plugin-google-gtag": "^3.6.1",
         "@docusaurus/preset-classic": "^3.6.1",
-        "@easyops-cn/docusaurus-search-local": "^0.48.0",
+        "@easyops-cn/docusaurus-search-local": "^0.48.5",
         "@mdx-js/react": "^3.0.0",
         "clsx": "^1.1.1",
         "joi": "^17.4.0",

package.json

@@ -23,7 +23,7 @@
     "@docusaurus/plugin-google-analytics": "^3.6.1",
     "@docusaurus/plugin-google-gtag": "^3.6.1",
     "@docusaurus/preset-classic": "^3.6.1",
-    "@easyops-cn/docusaurus-search-local": "^0.48.0",
+    "@easyops-cn/docusaurus-search-local": "^0.48.5",
     "@mdx-js/react": "^3.0.0",
     "clsx": "^1.1.1",
     "medium-zoom": "^1.0.6",

sidebars.js

@@ -652,6 +652,8 @@ module.exports = {
             ]
         },
         'deploying_clearml/enterprise_deploy/delete_tenant',
+        'deploying_clearml/enterprise_deploy/import_projects',
+        'deploying_clearml/enterprise_deploy/change_artifact_links',
         {
             'Enterprise Applications': [
                 'deploying_clearml/enterprise_deploy/app_install_ubuntu_on_prem',
@@ -671,6 +673,7 @@ module.exports = {
                     label: 'Identity Provider Integration',
                     link: {type: 'doc', id: 'user_management/identity_providers'},
                     items: [
+                        'deploying_clearml/enterprise_deploy/sso_multi_tenant_login',
                         'deploying_clearml/enterprise_deploy/sso_saml_k8s',
                         'deploying_clearml/enterprise_deploy/sso_keycloak',
                         'deploying_clearml/enterprise_deploy/sso_active_directory'