+
+There are several ways how label studio can load the file, either as a URL or as a blob therefore, you can store the list of tasks or the assets themselves and load that.
+
+
+
+You can configure it to store the results back to s3/gcp, making Label Studio a part of your data processing pipeline. Read more about the configuration in the docs [here](/guide/storage.html).
+
+## Frontend package updates
+
+Finally with a lot of [work](https://github.com/heartexlabs/label-studio-frontend/pull/75) from [Andrew](https://github.com/hlomzik) there is an implementation of frontend testing. This will make sure that we don’t break things when we introduce new features. Along with that another Important part — improved building and publishing process, configured CI. Now the npm frontend package will be published along with the pip package.
+
+## Labeling Paragraphs and Dialogues
+
+Introducing a new object tag called “Paragraphs”. A paragraph is a piece of text with potentially additional metadata like the author and the timestamp. With this tag we’re also experimenting now with an idea of providing predefined layouts. For example to label the dialogue you can use the following config: `
+
+This feature is available in the [enterprise version](https://heartex.ai/) only
+
+## Different shapes on the same image
+
+One limitation label studio had was the ability to use only one shape on the same image, for example, you were able to put either bounding boxes or polygons. Now this limitation is waived and you can define different label groups and connect those to the same image.
+
+
+
+## maxUsages
+
+There are a couple of ways how you can make sure that the annotation is being performed in full. One of these concepts is a `required` flag, and we’ve created a new one called `maxUsages`. For some datasets you know how much objects of a particular type there is, therefore you can limit the usage of specific labels.
+
+## Bugfixes and Enhancements
+- Allow different types of shapes to be used in the same image. For example you can label the same image using both rectangles and ellipses.
+- Fixing double text deserialization https://github.com/heartexlabs/label-studio-frontend/pull/85
+- Fix bug with groups of required choices https://github.com/heartexlabs/label-studio-frontend/pull/74
+- Several fixes for NER labeling — empty captured text, double clicks, labels appearance
diff --git a/docs/source/guide/storage.md b/docs/source/guide/storage.md
new file mode 100644
index 000000000000..f2e3032eb569
--- /dev/null
+++ b/docs/source/guide/storage.md
@@ -0,0 +1,125 @@
+---
+title: Cloud storages
+type: guide
+order: 101
+---
+
+You can integrate the popular cloud storage with Label Studio, collect new tasks uploaded to your buckets, and sync back annotation results to use them in your machine learning pipelines.
+
+Cloud storage type and bucket need to be configured during the start of the server, and further configured during the runtime via UI.
+
+You can configure one or both:
+
+- _source storage_ (where tasks are stored)
+- _target storage_ (where completions are stored)
+
+The connection to both storages is synced, so you can see new tasks after uploading them to the bucket without restarting Label Studio.
+
+The parameters like prefix or matching filename regex could be changed any time from the webapp interface.
+
+## Amazon S3
+
+To connect your [S3](https://aws.amazon.com/s3) bucket with Label Studio, be sure you have programmatic access enabled. [Check this link](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html#configuration) to learn more how to set up access to your S3 bucket.
+
+### Create connection on startup
+
+The following commands launch Label Studio, configure the connection to your S3 bucket, scan for existing tasks, and load them into the labeling app.
+
+#### Read bucket with JSON-formatted tasks
+
+```bash
+label-studio start --init --source s3 --source-path my-s3-bucket
+```
+
+
+#### Write completions to bucket
+
+```bash
+label-studio start --init --target s3-completions --target-path my-s3-bucket
+```
+
+### Working with Binary Large OBjects (BLOBs)
+
+When you are storing BLOBs in your S3 bucket (like images or audio files), you might want to use then as is, by generating URLs pointing to those objects (e.g. `gs://my-s3-bucket/image.jpg`)
+Label Studio allows you to generate input tasks with corresponding URLs automatically on-the-fly. You can to this either specifying `--source-params` when launching app:
+
+```bash
+label-studio start --init --source s3 --source-path my-s3-bucket --source-params "{\"data_key\": \"my-object-tag-$value\", \"use_blob_urls\": true}"
+```
+
+You can leave `"data_key"` empty (or skip it at all) then LS generates it automatically with the first task key from label config (it's useful when you have only one object tag exposed).
+
+
+### Optional parameters
+
+You can specify additional parameters with the command line escaped JSON string via `--source-params` / `--target-params` or from UI.
+
+#### prefix
+
+Bucket prefix (typically used to specify internal folder/container)
+
+#### regex
+
+A regular expression for filtering bucket objects
+
+#### create_local_copy
+
+If set true, the local copy of the remote storage will be created.
+
+#### use_blob_urls
+
+Generate task data with URLs pointed to your bucket objects(for resources like jpg, mp3, etc). If not selected, bucket objects will be interpreted as tasks in Label Studio JSON format, one object per task.
+
+
+## Google Cloud Storage
+
+To connect your [GCS](https://cloud.google.com/storage) bucket with Label Studio, be sure you have enabled programmatic access. [Check this link](https://cloud.google.com/storage/docs/reference/libraries) to learn more about how to set up access to your GCS bucket.
+
+
+### Create connection on startup
+
+The following commands launch Label Studio, configure the connection to your GCS bucket, scan for existing tasks, and load them into the app for the labeling.
+
+#### Read bucket with JSON-formatted tasks
+
+```bash
+label-studio start --init --source gcs --source-path my-gcs-bucket
+```
+
+#### Write completions to bucket
+
+```bash
+label-studio start --init --target gcs-completions --source-path my-gcs-bucket
+```
+
+### Working with Binary Large OBjects (BLOBs)
+
+When you are storing BLOBs in your GCS bucket (like images or audio files), you might want to use then as is, by generating URLs pointing to those objects (e.g. `gs://my-gcs-bucket/image.jpg`)
+Label Studio allows you to generate input tasks with corresponding URLs automatically on-the-fly. You can to this either specifying `--source-params` when launching app:
+
+```bash
+label-studio start --init --source gcs --source-path my-gcs-bucket --source-params "{\"data_key\": \"my-object-tag-$value\", \"use_blob_urls\": true}"
+```
+
+You can leave `"data_key"` empty (or skip it at all) then LS generates it automatically with the first task key from label config (it's useful when you have only one object tag exposed).
+
+
+### Optional parameters
+
+You can specify additional parameters with the command line escaped JSON string via `--source-params` / `--target-params` or from UI.
+
+#### prefix
+
+Bucket prefix (typically used to specify internal folder/container)
+
+#### regex
+
+A regular expression for filtering bucket objects
+
+#### create_local_copy
+
+If set true, the local copy of the remote storage will be created.
+
+#### use_blob_urls
+
+Generate task data with URLs pointed to your bucket objects(for resources like jpg, mp3, etc). If not selected, bucket objects will be interpreted as tasks in Label Studio JSON format, one object per task.
diff --git a/docs/themes/htx/layout/layout.ejs b/docs/themes/htx/layout/layout.ejs
index cdebd9e4eb70..b0d9de4f2842 100644
--- a/docs/themes/htx/layout/layout.ejs
+++ b/docs/themes/htx/layout/layout.ejs
@@ -45,6 +45,9 @@
<%- css(isIndex ? 'css/index' : 'css/page') %>
<%- css('css/search') %>
+
+
<% if (page.type === "playground") { %>
<%- css('css/codemirror') %>
@@ -56,7 +59,7 @@
-
+
+
+
+
+
+
+
+
+
+
+
+
-
+
+
+
+
+
+
+
+
+
+
- 
" alt="label studio logo"
- height="180"/>
+
- Open-source
Open-source
data labeling, annotation
and exploration tool
+
+ Open Source
Data Labeling Tool
Data Labeling Tool
- — Simplicity built-in, no overcomplicated UIs -
- — Mobile-Friendly, adaptable for any device +
- — Supports different datatypes
- — Visually configurable from top to the bottom
+
+
+
+ 
+
+ Introducing version 0.7.0 - Cloud Storage Enablement
+Load assets from AWS S3 or GCP. + Read more in our blog.
+
+
+
+ 10000+ Users
+Data Scientists, Machine Learning Engineers, and aspiring developers are using Label Studio to produce innovative machine learning models for real-world applications.
+
+
+ Why Label Studio?
+Configurable
Using HTML-like tags, you can quickly configure the UI for your particular needs. It's not just an image or text. It can be a pairwise comparison, multi-type classification, and beyond. Label Studio is a swiss army knife of data labeling and annotation.
- " class="underline">Learn More + " class="btn">Learn MoreMultiple data types
@@ -478,11 +584,25 @@Embeddable and Extendable
Label Studio includes a powerful embedding feature that enables you to embed entire UI in your pipeline. You can extend core functionality with new visual constructs and customize it for different use cases.
- " class="underline">Learn More + " class="btn">Read More
+
+ Compatible with your favorite framework
+
+ " height="50" />
+ " height="60" />
+ " height="50" />
+ " height="50" />
+
+
+