diff --git a/docs/clearml_data/data_management_examples/data_man_cifar_classification.md b/docs/clearml_data/data_management_examples/data_man_cifar_classification.md
index 1e4cc2a3..860c5af6 100644
--- a/docs/clearml_data/data_management_examples/data_man_cifar_classification.md
+++ b/docs/clearml_data/data_management_examples/data_man_cifar_classification.md
@@ -68,7 +68,8 @@ reproducibility.
Information about the dataset can be viewed in the WebApp, in the dataset's [details panel](../../webapp/datasets/webapp_dataset_viewing.md#version-details-panel).
In the panel's **CONTENT** tab, you can see a table summarizing version contents, including file names, file sizes, and hashes.
-
+
+
## Using the Dataset
diff --git a/docs/clearml_data/data_management_examples/data_man_python.md b/docs/clearml_data/data_management_examples/data_man_python.md
index c8e5ea14..5d4adc06 100644
--- a/docs/clearml_data/data_management_examples/data_man_python.md
+++ b/docs/clearml_data/data_management_examples/data_man_python.md
@@ -79,7 +79,8 @@ After a dataset has been closed, it can no longer be modified. This ensures futu
Information about the dataset can be viewed in the WebApp, in the dataset's [details panel](../../webapp/datasets/webapp_dataset_viewing.md#version-details-panel).
In the panel's **CONTENT** tab, you can see a table summarizing version contents, including file names, file sizes, and hashes.
-
+
+
## Data Ingestion
diff --git a/docs/deploying_clearml/clearml_server_config.md b/docs/deploying_clearml/clearml_server_config.md
index 014161cc..09b4e835 100644
--- a/docs/deploying_clearml/clearml_server_config.md
+++ b/docs/deploying_clearml/clearml_server_config.md
@@ -361,10 +361,16 @@ You can also use hashed passwords instead of plain-text passwords. To do that:
### Non-responsive Task Watchdog
-The non-responsive task watchdog monitors tasks that were not updated for a specified time interval, and then
-the watchdog marks them as `aborted`. The non-responsive experiment watchdog is always active.
+The non-responsive task watchdog monitors for running tasks that have stopped communicating with the ClearML Server for a specified
+time interval. If a task remains unresponsive beyond the set threshold, the watchdog marks it as `aborted`.
-Modify the following settings for the watchdog:
+A task is considered non-responsive if the time since its last communication with the ClearML Server exceeds the
+configured threshold. The watchdog starts counting after each successful communication with the server. If no further
+updates are received within the specified time, the task is considered non-responsive. This typically happens if:
+* The task's main process is stuck but has not exited.
+* There is a network issue preventing the task from communicating with the server.
+
+You can configure the following watchdog settings:
* Watchdog status - enabled / disabled
* The time threshold (in seconds) of experiment inactivity (default value is 7200 seconds (2 hours)).
@@ -372,10 +378,15 @@ Modify the following settings for the watchdog:
**To configure the non-responsive watchdog for the ClearML Server:**
-1. In the ClearML Server `/opt/clearml/config/services.conf` file, add or edit the `tasks.non_responsive_tasks_watchdog`
- section and specify the watchdog settings.
+1. Open the ClearML Server `/opt/clearml/config/services.conf` file.
+
+ :::tip
+ If the `services.conf` file does not exist, create your own in ClearML Server's `/opt/clearml/config` directory (or
+ an alternate folder you configured).
+ :::
+
+1. Add or edit the `tasks.non_responsive_tasks_watchdog` section and specify the watchdog settings. For example:
- For example:
```
tasks {
non_responsive_tasks_watchdog {
@@ -389,11 +400,6 @@ Modify the following settings for the watchdog:
}
}
```
-
- :::tip
- If the `services.conf` file does not exist, create your own in ClearML Server's `/opt/clearml/config` directory (or
- an alternate folder you configured), and input the modified configuration
- :::
1. Restart ClearML Server.
diff --git a/docs/faq.md b/docs/faq.md
index 3b5f642c..097a25ea 100644
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -137,7 +137,8 @@ the following numbers are displayed:
* API server version
* API version
-
+
+
ClearML Python package information can be obtained by using `pip freeze`.
@@ -593,7 +594,8 @@ Due to speed/optimization issues, the console displays only the last several hun
You can always download the full log as a file using the ClearML Web UI. In the **ClearML Web UI >** task's **CONSOLE**
tab, click `Download full log`.
-
+
+
@@ -604,17 +606,19 @@ and accuracy values of several tasks. In the task comparison page, under the **H
you can visualize tasks' hyperparameter values in relation to performance metrics in a scatter plot or parallel
coordinates plot:
* [Scatter plot](webapp/webapp_exp_comparing.md#scatter-plot): View the correlation between a selected hyperparameter and
- metric. For example, the image below shows a scatter plot that displays the values of a performance metric (`epoch_accuracy`)
+ metric. For example, the image below shows a scatter plot that displays the values of a performance metric (`accuracy`)
and a hyperparameter (`epochs`) of a few tasks:
- 
+ 
+ 
* [Parallel coordinates plot](webapp/webapp_exp_comparing.md#parallel-coordinates-mode): View the impact of hyperparameters
on selected metric(s). For example, the image below shows
- a parallel coordinates plot which displays the values of selected hyperparameters (`base_lr`, `batch_size`, and
- `number_of_epochs`) and a performance metric (`accuracy`) of three tasks:
+ a parallel coordinates plot which displays the values of selected hyperparameters (`epochs`, `lr`, and `batch_size`)
+ and a performance metric (`accuracy`) of a few tasks:
- 
+ 
+ 
diff --git a/docs/guides/advanced/execute_remotely.md b/docs/guides/advanced/execute_remotely.md
index 9502deb1..171dffb4 100644
--- a/docs/guides/advanced/execute_remotely.md
+++ b/docs/guides/advanced/execute_remotely.md
@@ -57,24 +57,28 @@ Logger.current_logger().report_scalar(
These scalars can be visualized in plots, which appear in the ClearML web UI, in the task's **SCALARS** tab.
-
+
+
## Hyperparameters
ClearML automatically logs command line options defined with `argparse`. They appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **Args**.
-
+
+
## Console
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
-
+
+
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks models
and any snapshots created using PyTorch.
-
+
+
diff --git a/docs/guides/automation/manual_random_param_search_example.md b/docs/guides/automation/manual_random_param_search_example.md
index fd71f4ba..36e94ebd 100644
--- a/docs/guides/automation/manual_random_param_search_example.md
+++ b/docs/guides/automation/manual_random_param_search_example.md
@@ -31,4 +31,5 @@ the `examples` project. This starts the parameter search, and creates the tasks:
When these tasks are completed, their [results can be compared](../../webapp/webapp_exp_comparing.md).
-
\ No newline at end of file
+
+
\ No newline at end of file
diff --git a/docs/guides/distributed/distributed_pytorch_example.md b/docs/guides/distributed/distributed_pytorch_example.md
index c57e0341..a972e9ac 100644
--- a/docs/guides/distributed/distributed_pytorch_example.md
+++ b/docs/guides/distributed/distributed_pytorch_example.md
@@ -34,7 +34,8 @@ Task.current_task().upload_artifact(
All of these artifacts appear in the main Task under **ARTIFACTS** **>** **OTHER**.
-
+
+
## Scalars
@@ -54,7 +55,8 @@ Task.current_task().get_logger().report_scalar(
The single scalar plot for loss appears in **SCALARS**.
-
+
+
## Hyperparameters
@@ -69,12 +71,15 @@ Task.current_task().connect(param)
All the hyperparameters appear in **CONFIGURATION** **>** **HYPERPARAMETERS**.
-
+
+
-
+
+
## Console
Output to the console, including the text messages printed from the main Task object and each subprocess appear in **CONSOLE**.
-
\ No newline at end of file
+
+
\ No newline at end of file
diff --git a/docs/guides/distributed/subprocess_example.md b/docs/guides/distributed/subprocess_example.md
index 42eab687..4f9c80c4 100644
--- a/docs/guides/distributed/subprocess_example.md
+++ b/docs/guides/distributed/subprocess_example.md
@@ -26,14 +26,17 @@ Task.current_task().connect(additional_parameters)
Command line options appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **Args**.
-
+
+
Parameter dictionaries appear in **General**.
-
+
+
## Console
Output to the console, including the text messages from the Task in each subprocess, appear in **CONSOLE**.
-
\ No newline at end of file
+
+
\ No newline at end of file
diff --git a/docs/guides/frameworks/catboost/catboost.md b/docs/guides/frameworks/catboost/catboost.md
index 2c6b0aeb..365cea5a 100644
--- a/docs/guides/frameworks/catboost/catboost.md
+++ b/docs/guides/frameworks/catboost/catboost.md
@@ -15,25 +15,30 @@ The example script does the following:
ClearML automatically captures scalars logged by CatBoost. These scalars can be visualized in plots, which appear in the
[ClearML web UI](../../../webapp/webapp_overview.md), in the task's **SCALARS** tab.
-
+
+
## Hyperparameters
ClearML automatically logs command line options defined with argparse. They appear in **CONFIGURATIONS > HYPERPARAMETERS > Args**.
-
+
+
## Console
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
-
+
+
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks
models created using CatBoost.
-
+
+
Clicking on the model name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can view
the model's details and access the model.
-
+
+
diff --git a/docs/guides/frameworks/fastai/fastai_with_tensorboard.md b/docs/guides/frameworks/fastai/fastai_with_tensorboard.md
index 1b58978e..59b9fd3c 100644
--- a/docs/guides/frameworks/fastai/fastai_with_tensorboard.md
+++ b/docs/guides/frameworks/fastai/fastai_with_tensorboard.md
@@ -18,16 +18,19 @@ The example code does the following:
ClearML automatically logs the histogram output to TensorBoard. They appear in **PLOTS**.
-
+
+
## Plots
Histograms output to TensorBoard. They appear in **PLOTS**.
-
+
+
## Logs
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
-
+
+
diff --git a/docs/guides/frameworks/huggingface/transformers.md b/docs/guides/frameworks/huggingface/transformers.md
index c095f3a9..a9a96ade 100644
--- a/docs/guides/frameworks/huggingface/transformers.md
+++ b/docs/guides/frameworks/huggingface/transformers.md
@@ -36,7 +36,8 @@ ClearML captures all of the `TrainingArguments` passed to the Trainer.
View these parameters in the task's **CONFIGURATION** tab **> Hyperparameters** section.
-
+
+
### Models
@@ -47,10 +48,12 @@ variable is set to `True`.
ClearML automatically captures the model snapshots created by the Trainer, and saves them as artifacts. View the snapshots in the
task's **ARTIFACTS** tab.
-
+
+
### Scalars
ClearML automatically captures the Trainer's scalars, which can be viewed in the task's **Scalars** tab.
-
+
+
diff --git a/docs/guides/frameworks/pytorch/model_updating.md b/docs/guides/frameworks/pytorch/model_updating.md
index 4822eed8..cb5360a7 100644
--- a/docs/guides/frameworks/pytorch/model_updating.md
+++ b/docs/guides/frameworks/pytorch/model_updating.md
@@ -83,18 +83,22 @@ if CONDITION:
## WebApp
The model appears in the task's **ARTIFACTS** tab.
-
+
+
Clicking on the model name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can view the
model's details and access the model.
-
+
+
The model's **NETWORK** tab displays its configuration.
-
+
+
The model's **LABELS** tab displays its label enumeration.
-
+
+
diff --git a/docs/guides/frameworks/pytorch/pytorch_distributed_example.md b/docs/guides/frameworks/pytorch/pytorch_distributed_example.md
index 31f63da4..1b81edf1 100644
--- a/docs/guides/frameworks/pytorch/pytorch_distributed_example.md
+++ b/docs/guides/frameworks/pytorch/pytorch_distributed_example.md
@@ -35,7 +35,8 @@ Task.current_task().upload_artifact(
All of these artifacts appear in the main Task, **ARTIFACTS** **>** **OTHER**.
-
+
+
## Scalars
@@ -54,7 +55,8 @@ Task.current_task().get_logger().report_scalar(
The single scalar plot for loss appears in **SCALARS**.
-
+
+
## Hyperparameters
@@ -69,7 +71,8 @@ Task.current_task().connect(param)
Command line options appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **Args**.
-
+
+
Parameter dictionaries appear in the **General** section of **HYPERPARAMETERS**.
@@ -78,10 +81,12 @@ param = {'worker_{}_stuff'.format(dist.get_rank()): 'some stuff ' + str(randint(
Task.current_task().connect(param)
```
-
+
+
## Log
Output to the console, including the text messages printed from the main Task object and each subprocess, appears in **CONSOLE**.
-
\ No newline at end of file
+
+
\ No newline at end of file
diff --git a/docs/guides/frameworks/pytorch/pytorch_matplotlib.md b/docs/guides/frameworks/pytorch/pytorch_matplotlib.md
index afc20955..0e580fd7 100644
--- a/docs/guides/frameworks/pytorch/pytorch_matplotlib.md
+++ b/docs/guides/frameworks/pytorch/pytorch_matplotlib.md
@@ -14,15 +14,18 @@ The example does the following:
The images shown in the example script's `imshow` function appear according to metric in **DEBUG SAMPLES**.
-
+
+
Select a debug sample by metric.
-
+
+
-Open the debug sample in the image viewer.
+Click a debug sample to view it in the image viewer.
-
+
+
diff --git a/docs/guides/frameworks/pytorch/pytorch_mnist.md b/docs/guides/frameworks/pytorch/pytorch_mnist.md
index ec46c3e6..aae3ed37 100644
--- a/docs/guides/frameworks/pytorch/pytorch_mnist.md
+++ b/docs/guides/frameworks/pytorch/pytorch_mnist.md
@@ -36,28 +36,33 @@ Logger.current_logger().report_scalar(
These scalars can be visualized in plots, which appear in the ClearML [web UI](../../../webapp/webapp_overview.md),
in the task's **SCALARS** tab.
-
+
+
## Hyperparameters
ClearML automatically logs command line options defined with `argparse`. They appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **Args**.
-
+
+
## Console
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
-
+
+
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks models
and any snapshots created using PyTorch.
-
+
+
Clicking on the model name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can view
the model's details and access the model.
-
\ No newline at end of file
+
+
\ No newline at end of file
diff --git a/docs/guides/frameworks/pytorch/pytorch_tensorboard.md b/docs/guides/frameworks/pytorch/pytorch_tensorboard.md
index 2dec7c79..41b282c0 100644
--- a/docs/guides/frameworks/pytorch/pytorch_tensorboard.md
+++ b/docs/guides/frameworks/pytorch/pytorch_tensorboard.md
@@ -18,34 +18,40 @@ In the example script, the `train` and `test` functions call the TensorBoard `Su
These scalars, along with the resource utilization plots, which are titled **:monitor: machine**, appear in the task's
page in the [ClearML web UI](../../../webapp/webapp_overview.md) under **SCALARS**.
-
+
+
## Debug Samples
ClearML automatically tracks images and text output to TensorFlow. They appear in **DEBUG SAMPLES**.
-
+
+
## Hyperparameters
ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **TF_DEFINE**.
-
+
+
## Console
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
-
+
+
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks
models and any snapshots created using PyTorch.
-
+
+
Clicking on a model's name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can view
the model's details and access the model.
-
\ No newline at end of file
+
+
\ No newline at end of file
diff --git a/docs/guides/frameworks/pytorch/pytorch_tensorboardx.md b/docs/guides/frameworks/pytorch/pytorch_tensorboardx.md
index 6bc91d63..d1f08722 100644
--- a/docs/guides/frameworks/pytorch/pytorch_tensorboardx.md
+++ b/docs/guides/frameworks/pytorch/pytorch_tensorboardx.md
@@ -18,29 +18,34 @@ The loss and accuracy metric scalar plots, along with the resource utilization p
appear in the task's page in the [web UI](../../../webapp/webapp_overview.md), under **SCALARS**.
-
+
+
## Hyperparameters
ClearML automatically logs command line options defined with `argparse`. They appear in **CONFIGURATION** **>**
**HYPERPARAMETERS** **>** **Args**.
-
+
+
## Log
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
-
+
+
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks
models and any snapshots created using PyTorch.
-
+
+
Clicking on the model name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can view
the model's details and access the model.
-
+
+
diff --git a/docs/guides/frameworks/pytorch/tensorboard_toy_pytorch.md b/docs/guides/frameworks/pytorch/tensorboard_toy_pytorch.md
index dcde66a8..cf17ac86 100644
--- a/docs/guides/frameworks/pytorch/tensorboard_toy_pytorch.md
+++ b/docs/guides/frameworks/pytorch/tensorboard_toy_pytorch.md
@@ -11,10 +11,12 @@ associated with the `examples` project.
The debug sample images appear according to metric, in the task's **DEBUG SAMPLES** tab.
-
+
+
## Hyperparameters
ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **TF_DEFINE**.
-
\ No newline at end of file
+
+
\ No newline at end of file
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diff --git a/docs/img/pipelines_new_run.png b/docs/img/pipelines_new_run.png
index 67b40acf..4bcda63f 100644
Binary files a/docs/img/pipelines_new_run.png and b/docs/img/pipelines_new_run.png differ
diff --git a/docs/img/pipelines_new_run_dark.png b/docs/img/pipelines_new_run_dark.png
new file mode 100644
index 00000000..d517eef9
Binary files /dev/null and b/docs/img/pipelines_new_run_dark.png differ
diff --git a/docs/integrations/transformers.md b/docs/integrations/transformers.md
index 93c9d03a..532b20f7 100644
--- a/docs/integrations/transformers.md
+++ b/docs/integrations/transformers.md
@@ -50,7 +50,8 @@ To log the models created during training, set the `CLEARML_LOG_MODEL` environme
You can see all the captured data in the task's page of the ClearML [WebApp](../webapp/webapp_exp_track_visual.md).
-
+
+
Additionally, you can view all of your Transformers runs tracked by ClearML in the [Task Table](../webapp/webapp_model_table.md).
Add custom columns to the table, such as mAP values, so you can easily sort and see what is the best performing model.
diff --git a/docs/pipelines/pipelines.md b/docs/pipelines/pipelines.md
index 2c0e742d..0860087c 100644
--- a/docs/pipelines/pipelines.md
+++ b/docs/pipelines/pipelines.md
@@ -103,7 +103,12 @@ You can rerun the pipeline programmatically or via the ClearML Web UI:
* To launch a new pipeline run in the UI, click **+ NEW RUN** in the [pipeline runs](../webapp/pipelines/webapp_pipeline_table.md) page. This opens a **NEW RUN** modal, where you
can set the run's parameters and execution queue.
- 
+
+
+ 
+ 
+
+
The new pipeline run will be executed through the execution queue by a ClearML agent. The agent will rebuild
the pipeline according to the configuration and DAG that was captured in the original run, and override the original
diff --git a/docs/pipelines/pipelines_sdk_function_decorators.md b/docs/pipelines/pipelines_sdk_function_decorators.md
index 97f43e75..5345d116 100644
--- a/docs/pipelines/pipelines_sdk_function_decorators.md
+++ b/docs/pipelines/pipelines_sdk_function_decorators.md
@@ -67,7 +67,12 @@ def main(pickle_url, mock_parameter='mock'):
When the function is called, a corresponding ClearML Controller Task is created: its arguments are logged as the task's
parameters. When launching a new pipeline run from the [UI](../webapp/pipelines/webapp_pipeline_page.md), you can modify their values for the new run.
-
+
+
+
+
+
+
## @PipelineDecorator.component
Using the [`@PipelineDecorator.component`](../references/sdk/automation_controller_pipelinedecorator.md#pipelinedecoratorcomponent)
diff --git a/docs/pipelines/pipelines_sdk_tasks.md b/docs/pipelines/pipelines_sdk_tasks.md
index 36eefe5e..f1d03fd8 100644
--- a/docs/pipelines/pipelines_sdk_tasks.md
+++ b/docs/pipelines/pipelines_sdk_tasks.md
@@ -42,7 +42,12 @@ These parameters can be programmatically injected into a step's configuration us
When launching a new pipeline run from the [UI](../webapp/pipelines/webapp_pipeline_table.md), you can modify their
values for the new run.
-
+
+
+
+
+
+
### Additional Configuration
You can connect configuration dictionaries or files to a pipeline controller using
diff --git a/docs/webapp/applications/apps_embed_model_deployment.md b/docs/webapp/applications/apps_embed_model_deployment.md
index 2463f1ee..d78afd25 100644
--- a/docs/webapp/applications/apps_embed_model_deployment.md
+++ b/docs/webapp/applications/apps_embed_model_deployment.md
@@ -16,7 +16,8 @@ endpoint activity and shuts down if the model remains inactive for a specified m
The Embedding Model Deployment app makes use of the ClearML Traffic Router which implements a secure, authenticated
network endpoint for the model.
-If the ClearML AI application Gateway is not available, the model endpoint might not be accessible.
+If the ClearML AI application Gateway is not available, the model endpoint might not be accessible.
+For more information, see [AI Application Gateway](../../deploying_clearml/enterprise_deploy/appgw.md).
:::
After starting an Embedding Model Deployment instance, you can view the following information in its dashboard:
diff --git a/docs/webapp/applications/apps_gradio.md b/docs/webapp/applications/apps_gradio.md
index b04c0982..31e48b92 100644
--- a/docs/webapp/applications/apps_gradio.md
+++ b/docs/webapp/applications/apps_gradio.md
@@ -20,6 +20,7 @@ The Gradio Launcher relies on the ClearML Traffic Router which implements user a
to the IP/port served by the Gradio app.
If the ClearML AI application Gateway is not available, the Gradio app might not be accessible.
+For more information, see [AI Application Gateway](../../deploying_clearml/enterprise_deploy/appgw.md).
:::
Once you start a Gradio launcher instance, you can view the following information in its dashboard:
diff --git a/docs/webapp/applications/apps_llama_deployment.md b/docs/webapp/applications/apps_llama_deployment.md
index 596586b3..e1233569 100644
--- a/docs/webapp/applications/apps_llama_deployment.md
+++ b/docs/webapp/applications/apps_llama_deployment.md
@@ -16,6 +16,7 @@ The llama.cpp Model Deployment app makes use of the ClearML Traffic Router which
network endpoint for the model.
If the ClearML AI application Gateway is not available, the model endpoint might not be accessible.
+For more information, see [AI Application Gateway](../../deploying_clearml/enterprise_deploy/appgw.md).
:::
After starting a llama.cpp Model Deployment instance, you can view the following information in its dashboard:
diff --git a/docs/webapp/applications/apps_model_deployment.md b/docs/webapp/applications/apps_model_deployment.md
index e0c0afe4..6bddd620 100644
--- a/docs/webapp/applications/apps_model_deployment.md
+++ b/docs/webapp/applications/apps_model_deployment.md
@@ -17,6 +17,7 @@ The vLLM Model Deployment app makes use of the ClearML Traffic Router which impl
network endpoint for the model.
If the ClearML AI application Gateway is not available, the model endpoint might not be accessible.
+For more information, see [AI Application Gateway](../../deploying_clearml/enterprise_deploy/appgw.md).
:::
Once you start a vLLM Model Deployment instance, you can view the following information in its dashboard:
diff --git a/docs/webapp/applications/apps_streamlit.md b/docs/webapp/applications/apps_streamlit.md
index 3aefbe21..4741a3e5 100644
--- a/docs/webapp/applications/apps_streamlit.md
+++ b/docs/webapp/applications/apps_streamlit.md
@@ -21,6 +21,7 @@ The Streamlit Launcher relies on the ClearML Traffic Router which implements use
to the IP/port served by the Streamlit app.
If the ClearML AI application Gateway is not available, the Streamlit app might not be accessible.
+For more information, see [AI Application Gateway](../../deploying_clearml/enterprise_deploy/appgw.md).
:::
Once you start a Streamlit launcher instance, you can view the following information in its dashboard:
diff --git a/docs/webapp/settings/webapp_settings_profile.md b/docs/webapp/settings/webapp_settings_profile.md
index e7e92d8e..e2cf4454 100644
--- a/docs/webapp/settings/webapp_settings_profile.md
+++ b/docs/webapp/settings/webapp_settings_profile.md
@@ -103,7 +103,8 @@ these credentials cannot be recovered.
The AI Application Gateway is available under the ClearML Enterprise plan.
:::
-The AI Application Gateway enables external access to ClearML tasks and applications. The gateway is configured with an
+The [AI Application Gateway](../../deploying_clearml/enterprise_deploy/appgw.md) enables external access to ClearML
+tasks and applications. The gateway is configured with an
endpoint or external address (ingress), accessible from outside ClearML.
Generate tokens providing API access to the AI Application Gateway endpoints:
diff --git a/docs/webapp/webapp_reports.md b/docs/webapp/webapp_reports.md
index e84057c6..7e79eb6c 100644
--- a/docs/webapp/webapp_reports.md
+++ b/docs/webapp/webapp_reports.md
@@ -429,7 +429,11 @@ image enclosed in parentheses:
The rendered output should look like this:
-
+
+
+
+
+
To add a title to the image, which you can see in a tooltip when hovering over the image, add the title after the image's
link:
@@ -439,7 +443,9 @@ link:
```
The rendered output should look like this:
-
+
+
+
Hover over the image to see its title.
diff --git a/src/css/custom.css b/src/css/custom.css
index 160fad9e..665be87c 100644
--- a/src/css/custom.css
+++ b/src/css/custom.css
@@ -620,6 +620,15 @@ html[data-theme=dark] .medium-zoom-image.medium-zoom-image--opened {border-radiu
[data-theme='dark'] img[src$='#light-mode-only'] {
display: none;
}
+
+[data-theme='dark'] .light-mode-only {
+ display: none;
+}
+
+[data-theme='light'] .dark-mode-only {
+ display: none;
+}
+
/* table */
.markdown table {
border-spacing: 0;