Merge branch 'main' of https://github.com/allegroai/clearml-docs into images_4

docs/clearml_data/clearml_data_sdk.md

@@ -246,7 +246,7 @@ dataset.get_logger().report_table(
     title="Raw Dataset Metadata", series="Raw Dataset Metadata", csv="path/to/csv"
 )
 
-# Attach a historgram to the table
+# Attach a histogram to the table
 dataset.get_logger().report_histogram(
     title="Class distribution",
     series="Class distribution",
@@ -261,7 +261,7 @@ dataset.get_logger().report_histogram(
 
 To upload the dataset files to network storage, use [`Dataset.upload()`](../references/sdk/dataset.md#upload). 
 
-Use the `output_url` parameter to specify storage target, such as S3 / GS / Azure. For example:
+Use the `output_url` parameter to specify a storage target, such as S3 / GS / Azure. For example:
 * A shared folder: `/mnt/share/folder`
 * S3: `s3://bucket/folder`
 * Non-AWS S3-like services (such as MinIO): `s3://host_addr:port/bucket`. **Note that port specification is required**. 

docs/clearml_data/data_management_examples/data_man_simple.md

@@ -30,7 +30,7 @@ the needed files.
     ```
 
 1. Add a folder. File addition is recursive, so it's enough to point at the folder 
-to captures all files and subfolders:
+to capture all files and subfolders:
    
    ```bash
    clearml-data add --files data_samples

docs/community.md

@@ -8,7 +8,7 @@ For feature requests or bug reports, see **ClearML** [GitHub issues](https://git
 
 If you have any questions, post on the **ClearML** [Slack channel](https://joinslack.clear.ml).
 
-Or, tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/clearml) with the **clearml** tag.
+Or, tag your questions on [Stack Overflow](https://stackoverflow.com/questions/tagged/clearml) with the **clearml** tag.
 
 You can always find us at [support@clear.ml](mailto:support@clear.ml?subject=ClearML).
 

docs/deploying_clearml/clearml_server_linux_mac.md

@@ -127,7 +127,13 @@ Deploying the server requires a minimum of 8 GB of memory, 16 GB is recommended.
        ```
        sudo chown -R 1000:1000 /opt/clearml
        ```
-    
+       
+       :::note
+       This assumes the container processes run as UID 1000 and GID 1000. The ownership of `/opt/clearml` must match the 
+       UID and GID used inside the container. If the container runs as a different user or group, update the ownership 
+       accordingly to ensure they can access the mounted directories.
+       :::
+   
     * macOS:
 
        ```

docs/deploying_clearml/clearml_server_security.md

@@ -33,7 +33,7 @@ has been configured. It is recommended to use an [object storage solution](../in
 
 ## Server Credentials and Secrets
 
-By default, ClearML Server comes with default values that are designed to allow to set it up quickly and to start working 
+By default, ClearML Server comes with default values designed to allow you to quickly set it up and to start working 
 with the ClearML SDK.
 
 However, this also means that the **server must be secured** by either preventing any external access, or by changing 

docs/deploying_clearml/enterprise_deploy/k8s.md

@@ -58,83 +58,46 @@ that will have records pointing to the cluster’s ingress controller (see ingre
 :::
 
 
-```
+```yaml
 imageCredentials:
- password: "<clearml_enterprise_DockerHub_TOKEN>"
-
+  password: "<clearml_enterprise_DockerHub_TOKEN>"
 
 clearml:
- cookieDomain: "<BASE_DOMAIN>"
- # Set values for improved security
- apiserverKey: "<GENERATED_API_SERVER_KEY>"
- apiserverSecret: "<GENERATED_API_SERVER_SECRET>"
- fileserverKey: "<GENERATED_FILE_SERVER_KEY>"
- fileserverSecret: "<GENERATED_FILE_SERVER_SECRET>"
- secureAuthTokenSecret: "<GENERATED_AUTH_TOKEN_SECRET>"
- testUserKey: "<GENERATED_TEST_USER_KEY>"
- testUserSecret: "<GENERATED_TEST_USER_SECRET>"
-
+  cookieDomain: "<BASE_DOMAIN>"
+  # Set values for improved security
+  apiserverKey: "<GENERATED_API_SERVER_KEY>"
+  apiserverSecret: "<GENERATED_API_SERVER_SECRET>"
+  fileserverKey: "<GENERATED_FILE_SERVER_KEY>"
+  fileserverSecret: "<GENERATED_FILE_SERVER_SECRET>"
+  secureAuthTokenSecret: "<GENERATED_AUTH_TOKEN_SECRET>"
+  testUserKey: "<GENERATED_TEST_USER_KEY>"
+  testUserSecret: "<GENERATED_TEST_USER_SECRET>"
 
 apiserver:
- ingress:
-   enabled: true
-   hostName: "api.<BASE_DOMAIN>"
- service:
-   type: ClusterIP
- extraEnvs:
-   - name: CLEARML__services__organization__features__user_management_advanced
-     value: "true"
-   - name: CLEARML__services__auth__ui_features_per_role__user__show_datasets
-     value: "false"
-   - name: CLEARML__services__auth__ui_features_per_role__user__show_orchestration
-     value: "false"
-   - name: CLEARML__services__workers__resource_usages__supervisor_company
-     value: "<SUPERVISOR_TENANT_ID>"
-   - name: CLEARML__secure__credentials__supervisor__role
-     value: "system"
-   - name: CLEARML__secure__credentials__supervisor__allow_login
-     value: "true"
-   - name: CLEARML__secure__credentials__supervisor__user_key
-     value: "<SUPERVISOR_USER_KEY>"
-   - name: CLEARML__secure__credentials__supervisor__user_secret
-     value: "<SUPERVISOR_USER_SECRET>"
-   - name: CLEARML__secure__credentials__supervisor__sec_groups
-     value: "[\"users\", \"admins\", \"queue_admins\"]"
-   - name: CLEARML__secure__credentials__supervisor__email
-     value: "\"<SUPERVISOR_USER_EMAIL>\""
-   - name: CLEARML__apiserver__company__unique_names
-     value: "true"
-
+  ingress:
+    enabled: true
+    hostName: "api.<BASE_DOMAIN>"
+  service:
+    type: ClusterIP
 
 fileserver:
- ingress:
-   enabled: true
-   hostName: "file.<BASE_DOMAIN>"
- service:
-   type: ClusterIP
-
+  ingress:
+    enabled: true
+    hostName: "file.<BASE_DOMAIN>"
+  service:
+    type: ClusterIP
 
 webserver:
- ingress:
-   enabled: true
-   hostName: "app.<BASE_DOMAIN>"
- service:
-   type: ClusterIP
-
+  ingress:
+    enabled: true
+    hostName: "app.<BASE_DOMAIN>"
+  service:
+    type: ClusterIP
 
 clearmlApplications:
- enabled: true
+  enabled: true
 ```
 
-
-The credentials specified in `<SUPERVISOR_USER_KEY>` and `<SUPERVISOR_USER_SECRET>` can be used to log in as the
-supervisor user from the ClearML Web UI accessible using the URL `app.<BASE_DOMAIN>`.
-
-
-Note that the `<SUPERVISOR_USER_EMAIL>` value must be explicitly quoted. To do so, put `\"` around the quoted value.
-For example `"\"email@example.com\""`.
-
-
 #### Additional Configuration Options
 ##### Fixed Users (Simple Login)
 
@@ -181,7 +144,7 @@ Substitute all `<PLACEHOLDER>`s with the correct value for your configuration.
 ##### Auth0 Identity Provider
 
 
-```
+```yaml
 apiserver:
  extraEnvs:
    - name: CLEARML__secure__login__sso__oauth_client__auth0__client_id
@@ -202,7 +165,7 @@ apiserver:
 ##### Keycloak Identity Provider
 
 
-```
+```yaml
 apiserver:
  extraEnvs:
    - name: CLEARML__secure__login__sso__oauth_client__keycloak__client_id
@@ -217,8 +180,6 @@ apiserver:
      value: "<KC_URL>/realms/<REALM_NAME>/protocol/openid-connect/token"
    - name: CLEARML__services__login__sso__oauth_client__keycloak__idp_logout
      value: "true"
-
-
 ```
 
 
@@ -247,24 +208,24 @@ To configure the agent you will need to choose a Redis password and use that whe
 The Helm Chart must be installed with `overrides.yaml`:
 
 
-```
+```yaml
 imageCredentials:
- password: "<CLEARML_DOCKERHUB_TOKEN>"
+  password: "<CLEARML_DOCKERHUB_TOKEN>"
 clearml:
- agentk8sglueKey: "<ACCESS_KEY>"
- agentk8sglueSecret: "<SECRET_KEY>"
+  agentk8sglueKey: "<ACCESS_KEY>"
+  agentk8sglueSecret: "<SECRET_KEY>"
 agentk8sglue:
- apiServerUrlReference: "https://api.<BASE_DOMAIN>"
- fileServerUrlReference: "https://files.<BASE_DOMAIN>"
- webServerUrlReference: "https://app.<BASE_DOMAIN>"
- defaultContainerImage: "python:3.9"
+  apiServerUrlReference: "https://api.<BASE_DOMAIN>"
+  fileServerUrlReference: "https://files.<BASE_DOMAIN>"
+  webServerUrlReference: "https://app.<BASE_DOMAIN>"
+  defaultContainerImage: "python:3.9"
 ```
 
 
 #### Installing the Chart
 
 
-```
+```bash
 helm install -n <WORKLOAD_NAMESPACE> \
     clearml-agent \
     clearml-enterprise/clearml-enterprise-agent \
@@ -276,7 +237,7 @@ helm install -n <WORKLOAD_NAMESPACE> \
 To create a queue by API:
 
 
-```
+```bash
 curl $APISERVER_URL/queues.create \
 -H "Content-Type: application/json" \
 -H "X-Clearml-Impersonate-As:<USER_ID>" \
@@ -294,22 +255,22 @@ curl $APISERVER_URL/queues.create \
 The Helm Chart must be installed with `overrides.yaml`:
 
 
-```
+```yaml
 imageCredentials:
- password: "<DOCKERHUB_TOKEN>"
+  password: "<DOCKERHUB_TOKEN>"
 clearml:
- apiServerKey: ""
- apiServerSecret: ""
- apiServerUrlReference: "https://api."
- authCookieName: ""
+  apiServerKey: ""
+  apiServerSecret: ""
+  apiServerUrlReference: "https://api."
+  authCookieName: ""
 ingress:
- enabled: true
- hostName: "task-router.dev"
+  enabled: true
+  hostName: "task-router.dev"
 tcpSession:
- routerAddress: "<NODE_IP OR EXTERNAL_NAME>"
- portRange:
-   start: <START_PORT>
-   end: <END_PORT>
+  routerAddress: "<NODE_IP OR EXTERNAL_NAME>"
+  portRange:
+    start: <START_PORT>
+    end: <END_PORT>
 ```
 
 
@@ -330,7 +291,7 @@ tcpSession:
 ### Installing the Chart
 
 
-```
+```bash
 helm install -n <WORKLOAD_NAMESPACE> \
     clearml-ttr \
     clearml-enterprise/clearml-enterprise-task-traffic-router \
@@ -429,20 +390,20 @@ This example configures a specific queue, but you can include this setting in th
 apply it to all tasks.
 
 
-```
+```yaml
 agentk8sglue: 
- queues:
-   GPUshm:
-     templateOverrides:
-       env:
-         - name: VLLM_SKIP_P2P_CHECK
-           value: "1"
-       volumeMounts:
-         - name: dshm
-           mountPath: /dev/shm
-       volumes:
-         - name: dshm
-           emptyDir:
-             medium: Memory
-             sizeLimit: <SIZE>Gi
+  queues:
+    GPUshm:
+      templateOverrides:
+        env:
+          - name: VLLM_SKIP_P2P_CHECK
+            value: "1"
+        volumeMounts:
+          - name: dshm
+            mountPath: /dev/shm
+        volumes:
+          - name: dshm
+            emptyDir:
+              medium: Memory
+              sizeLimit: <SIZE>Gi
 ```

docs/fundamentals/models.md

@@ -58,7 +58,7 @@ ClearML provides flexibility for explicitly connecting input models and experime
 
 ## WebApp Interface
 
-In the ClearML's web UI, model information can be located through a project's Model Table or through the model's creating 
+In the ClearML web UI, model information can be located through a project's Model Table or through the model's creating 
 task.
 
 Models associated with a task appear in the task's **ARTIFACTS** tab. To see further model details, including design, 

docs/guides/reporting/clearml_logging_example.md

@@ -17,7 +17,7 @@ In the ``clearml`` GitHub repository, this example includes a clickable icon to
 
 ## Scalars
 
-To reports scalars, call [`Logger.report_scalar()`](../../references/sdk/logger.md#report_scalar). 
+To report scalars, call [`Logger.report_scalar()`](../../references/sdk/logger.md#report_scalar). 
 The scalar plots appear in the **web UI** in **SCALARS**.
 
 ```python

docs/guides/reporting/hyper_parameters.md

@@ -49,7 +49,7 @@ flags.DEFINE_string('echo5', '5', 'Text to echo.', module_name='test')
 
 ```    
 
-TensorFlow Definitions appear in **HYPEPARAMETERS** **>** **TF_DEFINE**.
+TensorFlow Definitions appear in **HYPERPARAMETERS** **>** **TF_DEFINE**.
 
 ![TF Defines](../../img/examples_reporting_hyper_param_03.png#light-mode-only)
 ![TF Defines](../../img/examples_reporting_hyper_param_03_dark.png#dark-mode-only)

docs/guides/reporting/scalar_reporting.md

@@ -7,7 +7,8 @@ demonstrates explicit scalar reporting. ClearML reports scalars in the **ClearML
 
 When the script runs, it creates a task named `scalar reporting` in the `examples` project.
 
-To reports scalars, call [`Logger.report_scalar()`](../../references/sdk/logger.md#report_scalar). 
+## Reporting Scalar Series 
+To report scalar series, call [`Logger.report_scalar()`](../../references/sdk/logger.md#report_scalar). 
 To report more than one series on the same plot, use the same `title` argument. For different plots, use different 
 `title` arguments. 
 
@@ -31,4 +32,20 @@ for i in range(100):
     )
 ```
 
-![image](../../img/examples_reporting_14.png)
+![Scalars series](../../img/examples_reporting_14.png#light-mode-only)
+![Scalars series](../../img/examples_reporting_14_dark.png#dark-mode-only)
+
+## Reporting Single Scalar Values 
+
+To report single scalar values (individual metrics, not part of a series), use [`Logger.report_single_value()`](../../references/sdk/logger.md#report_single_value).
+
+```python
+# Report individual scalar values
+Logger.current_logger().report_single_value(name="metric A", value=486)
+Logger.current_logger().report_single_value(name="metric B", value=305.95)
+```
+
+Single value scalars are shown in the UI in the task's **SCALARS** tab under the `Summary` table.
+
+![Single scalars](../../img/examples_reporting_14a.png#light-mode-only)
+![Single scalars](../../img/examples_reporting_14a_dark.png#dark-mode-only)

docs/guides/reporting/text_reporting.md

@@ -3,15 +3,46 @@ title: Text Reporting
 ---
 
 The [text_reporting.py](https://github.com/clearml/clearml/blob/master/examples/reporting/text_reporting.py) script 
-demonstrates reporting explicit text by calling [`Logger.report_text()`](../../references/sdk/logger.md#report_text). 
-
-ClearML reports the text in the **ClearML Web UI**, in the task's **CONSOLE** tab. 
+demonstrates reporting text output and samples. 
 
 When the script runs, it creates a task named `text reporting` in the `examples` project.
 
+
+
+## Reporting Text to Console
+To report text to the task console, call [`Logger.report_text()`](../../references/sdk/logger.md#report_text):
+
 ```python
 # report text
 Logger.current_logger().report_text("hello, this is plain text")
 ```
 
-![image](../../img/examples_reporting_text.png)
+Text reported with `Logger.report_text()` appears in the task's **CONSOLE** tab in the ClearML Web UI. 
+
+![Text to console](../../img/examples_reporting_text.png#light-mode-only)
+![Text to console](../../img/examples_reporting_text_dark.png#dark-mode-only)
+
+## Reporting Text as Debug Samples
+To report longer text as a debug sample (e.g., logs, large text outputs, or structured text files),
+use [`Logger.report_media()`](../../references/sdk/logger.md#report_media) with a text stream and `.txt` file extension:
+
+```python
+text_to_send = """
+Lorem ipsum dolor sit amet, consectetur adipiscing elit.
+Suspendisse ac justo ut dolor scelerisque posuere.
+...
+"""
+
+Logger.current_logger().report_media(
+    title="text title",
+    series="text series",
+    iteration=1,
+    stream=six.StringIO(text_to_send),
+    file_extension=".txt",
+)
+```
+
+Text samples appear in the task's **DEBUG SAMPLES** tab in the ClearML Web UI.
+
+![Text debug sample](../../img/examples_reporting_text_debug.png#light-mode-only)
+![Text debug sample](../../img/examples_reporting_text_debug_dark.png#dark-mode-only)

docs/hyperdatasets/dataviews.md

@@ -380,7 +380,7 @@ list_of_frames = myDataView.to_list()
 ##### Frame Query for Time Interval
 
 This example demonstrates a frame query filtering for frames containing the meta key `updated` with any value between 
-`08:000` and `09:00` on October 20th, 2024: 
+`08:00` and `09:00` on October 20th, 2024: 
 
 ```python
 # Add a frame query for frames with the meta key's value between 08:00:00 and 09:00:00 on 2024-10-20

docs/hyperdatasets/webapp/webapp_datasets_versioning.md

@@ -248,7 +248,7 @@ Filter by date/time metadata fields using Lucene queries.
   
   * Open a frame in the frame viewer to see its metadata.  
 
-    ![Frame datetimee metadata in frame viewer](../../img/hyperdatasets/frame_filtering_14.png#light-mode-only)
+    ![Frame datetime metadata in frame viewer](../../img/hyperdatasets/frame_filtering_14.png#light-mode-only)
     ![Frame datetime metadata in frame viewer](../../img/hyperdatasets/frame_filtering_14_dark.png#dark-mode-only)
   
 </Collapsible>

docs/model_registry.md

@@ -101,7 +101,7 @@ input_model_2 = InputModel.import_model(
 )
 ```
 
-After instantiating an InputModel instance, you can connect it to a task object, so the model can be traced to n 
+After instantiating an InputModel instance, you can connect it to a task object, so the model can be traced to a
 task. 
 
 ```python
@@ -138,7 +138,7 @@ output_model.update_weights(weights_filename='models/model.pth')
 ```
 
 ## Analyzing Models 
-While experimenting, you build up your model catalog. In the ClearML's web UI, model information can be located through 
+While experimenting, you build up your model catalog. In the ClearML web UI, model information can be located through 
 a project's Model Table or through the model's associated task.
 
 Models associated with a task appear in the task's **ARTIFACTS** tab. To see further model details, including design, 

docs/overview.md

@@ -77,6 +77,6 @@ For detailed instructions on each step, refer to the respective sections in this
 ## Support
 For feature requests or bug reports, see ClearML on [GitHub](https://github.com/clearml/clearml/issues).
 
-If you have any questions, join the discussion on the **ClearML** [Slack channel](https://joinslack.clear.ml), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/clearml) with the **clearml** tag.
+If you have any questions, join the discussion on the **ClearML** [Slack channel](https://joinslack.clear.ml), or tag your questions on [Stack Overflow](https://stackoverflow.com/questions/tagged/clearml) with the **clearml** tag.
 
 Lastly, you can always find us at [support@clearml.ai](mailto:support@clearml.ai?subject=ClearML).

docs/release_notes/clearml_server/enterprise/ver_3_23.md

@@ -82,5 +82,5 @@ user access to these objects or their containing project.
 * Fix pipeline run version not set when re-executed via the UI
 * Fix UI DataView successfully created with identical IDs in label enumeration
 * Fix UI DataView created successfully when "Limit Frames" repetition option is selected, but the maximum number of frames is not set
-* Fix moving a enqueued experiment to a new UI queue results in error 
+* Fix moving an enqueued experiment to a new UI queue results in error 
 * Fix metric and hyperparameter group string not searchable in UI table 

docs/release_notes/clearml_server/enterprise/ver_3_24.md

@@ -2,6 +2,17 @@
 title: Version 3.24
 ---
 
+### Enterprise Server 3.24.7
+
+**Bug Fix**
+
+* Fix duplicate emails can be added to user list 
+
+### Enterprise Server 3.24.6
+
+**Bug Fix**
+* Fix setting a service account as admin navigates to incorrect page
+
 ### Enterprise Server 3.24.5
 
 **New Feature**

docs/release_notes/clearml_server/open_source/ver_0_10.md

@@ -15,7 +15,7 @@ title: Version 0.10
 
 * Replace the Python web-server with NGINX.
 
-* Improve sub-domain support ([GitHub trains-server Issue 9](https://github.com/clearml/clearml-server/issues/9)).
+* Improve subdomain support ([GitHub trains-server Issue 9](https://github.com/clearml/clearml-server/issues/9)).
 
 * Extend configuration options
     

docs/release_notes/sdk/open_source/ver_0_10.md

@@ -68,7 +68,7 @@ title: Version 0.10
 * Add scikit-learn support (load/store using joblib) ([GitHub Issue #20](https://github.com/clearml/clearml/issues/20)).
 * Add xgboost support ([GitHub Issue #10](https://github.com/clearml/clearml/issues/10)).
 * Add loguru support ([GitHub Issue #29](https://github.com/clearml/clearml/issues/29)).
-* Add sub-domain support [trains.conf](https://github.com/clearml/clearml/blob/master/docs/trains.conf#L3) ([GitHub Issue #27](https://github.com/clearml/clearml/issues/27)).
+* Add subdomain support [trains.conf](https://github.com/clearml/clearml/blob/master/docs/trains.conf#L3) ([GitHub Issue #27](https://github.com/clearml/clearml/issues/27)).
 * Fix sub-process support.
 * Fix multiple TensorBoard writers ([GitHub Issue #26](https://github.com/clearml/clearml/issues/26)).
 

package-lock.json

@@ -10127,7 +10127,9 @@
       }
     },
     "node_modules/http-proxy-middleware": {
-      "version": "2.0.7",
+      "version": "2.0.9",
+      "resolved": "https://registry.npmjs.org/http-proxy-middleware/-/http-proxy-middleware-2.0.9.tgz",
+      "integrity": "sha512-c1IyJYLYppU574+YI7R4QyX2ystMtVXZwIdzazUIPIJsHuWNd+mho2j+bKoHftndicGj9yh+xjd+l0yj7VeT1Q==",
       "license": "MIT",
       "dependencies": {
         "@types/http-proxy": "^1.17.8",