Merge branch 'develop' into hotfix/replace_isort_by_ruff

.github/workflows/package.yml

@@ -222,9 +222,10 @@ jobs:
               - 'frontend/**'
               - 'pyproject.toml'
               - 'setup.py'
-              - 'scripts/start_argilla_server.sh'
+              - 'scripts/*.sh'
               - '*.Dockerfile'
               - '.dockerignore'
+              - '.github/workflows/package.yml'
       - name: Cache pip 👜
         uses: actions/cache@v2
         if: steps.filter.outputs.code_changes == 'true'
@@ -267,10 +268,12 @@ jobs:
           - image: argilla/argilla-server
             dockerfile: release.Dockerfile
             readme: README.md
+            platforms: linux/amd64
 
           - image: argilla/argilla-quickstart
             dockerfile: quickstart.Dockerfile
             readme: quickstart.README.md
+            platforms: linux/amd64,linux/arm64
 
     defaults:
       run:
@@ -285,6 +288,12 @@ jobs:
           name: python-package
           path: dist
 
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v2
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+
       - name: Docker meta
         id: meta
         uses: crazy-max/ghaction-docker-meta@v2
@@ -302,9 +311,10 @@ jobs:
         with:
           context: .
           file: ${{ matrix.dockerfile }}
-          push: true
+          platforms: ${{ matrix.platforms }}
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}
+          push: true
 
       - name: Docker Hub Description
         uses: peter-evans/dockerhub-description@v3

README.md

@@ -98,7 +98,7 @@ The simplest way is to use`Docker` by running:
 
 ```bash
 
-docker run -d --name es-for-argilla -p 9200:9200 -p 9300:9300 -e "ES_JAVA_OPTS=-Xms512m -Xmx512m" -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch-oss:7.10.2
+docker run -d --name elasticsearch-for-argilla --network argilla-net  -p 9200:9200 -p 9300:9300 -e "ES_JAVA_OPTS=-Xms512m -Xmx512m" -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:8.5.3
 
 ```
 > :information_source: **Check [the docs](https://docs.argilla.io/en/latest/getting_started/quickstart.html) for further options and configurations for Elasticsearch.**
@@ -153,7 +153,7 @@ dataset_rg = rg.DatasetForTextClassification.from_pandas(my_dataframe)
 rg.log(dataset_rg, name="sst-sentimentclassification")
 ```
 
-This will create two datasets which you can use to do a quick tour of the core features of Argilla.
+This will create two datasets that you can use to do a quick tour of the core features of Argilla.
 
 > 🚒 **If you find issues, get direct support from the team and other community members on the [Slack Community](https://join.slack.com/t/rubrixworkspace/shared_invite/zt-whigkyjn-a3IUJLD7gDbTZ0rKlvcJ5g)**
 

docker-compose.elasticsearch.yaml

@@ -3,7 +3,7 @@ version: "3.9"
 services:
 
   elasticsearch:
-    image: docker.elastic.co/elasticsearch/elasticsearch:8.5.0
+    image: docker.elastic.co/elasticsearch/elasticsearch:8.5.3
     ports:
       - "9200:9200"
       - "9300:9300"
@@ -23,7 +23,7 @@ services:
     volumes:
       - elasticsearch-data-8:/usr/share/elasticsearch/data/
   kibana:
-    image: docker.elastic.co/kibana/kibana:8.5.0
+    image: docker.elastic.co/kibana/kibana:8.5.3
     ports:
       - "5601:5601"
     environment:

docker-compose.yaml

@@ -20,7 +20,7 @@ services:
       - argilla
 
   elasticsearch:
-    image: docker.elastic.co/elasticsearch/elasticsearch:7.17.8
+    image: docker.elastic.co/elasticsearch/elasticsearch:8.5.3
     environment:
       - node.name=elasticsearch
       - cluster.name=es-argilla-local
@@ -40,7 +40,7 @@ services:
     volumes:
       - elasticdata:/usr/share/elasticsearch/data/
   kibana:
-    image: docker.elastic.co/kibana/kibana:7.17.8
+    image: docker.elastic.co/kibana/kibana:8.5.3
     ports:
       - "5601:5601"
     environment:

docs/_source/getting_started/argilla.md

@@ -2,22 +2,29 @@
 
 [Argilla](https://argilla.io) is a **production-ready framework for building and improving datasets** for NLP projects.
 
-```{admonition} Hugging Face Spaces Live Demo 🆕
+```{admonition} Argilla on HF Spaces
 :class: important
 
-Play with Argilla UI with this [live-demo](https://argilla-live-demo.hf.space) powered by Hugging Face Spaces (login:`argilla`, password:`1234`)
+Deploy your own Argilla Server on Spaces with a few clicks:
+
+<a  href="https://huggingface.co/new-space?template=argilla/argilla-template-space">
+    <img src="https://huggingface.co/datasets/huggingface/badges/raw/main/deploy-to-spaces-lg.svg" />
+</a>
 
 ```
 
+
 ```{admonition} Semantic Search data labelling 🆕
 :class: important
 
-🆕 Since `1.2.0` You can add embedding vectors to Argilla records and use them to find the most similar records with the UI. This feature uses vector search combined with traditional search (keyword and filter based).
+🆕 Use embeddings to find the most similar records with the UI. This feature uses vector search combined with traditional search (keyword and filter based).
 
 Get started: [Semantic Search Deep-dive guide](../guides/features/semantic-search.ipynb)
 
 ```
 
+
+
 <iframe width="100%" height="450" src="https://www.youtube.com/embed/jP3anvp7Rto" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
 
 ## Features

docs/_source/getting_started/installation/deployments/deployments.md

@@ -6,6 +6,10 @@
 ```{grid-item-card} Docker
 :link: docker.md
 
+```
+```{grid-item-card} Docker Quickstart
+:link: docker.md
+
 ```
 ```{grid-item-card} Docker-compose
 :link: docker_compose.md
@@ -34,6 +38,7 @@
 :hidden:
 
 docker.md
+docker-quickstart.md
 docker_compose.md
 cloud_providers.md
 from_development.md

docs/_source/getting_started/installation/deployments/docker-quickstart.md

@@ -1,13 +1,21 @@
-# Argilla Docker Quickstart
+# Docker Quickstart
 Argilla is composed of a Python Server with Elasticsearch as the database layer, and a Python Client to create and
 manage datasets.
 
 To get started you just need to run the docker image with following command:
 
 ``` bash
-  docker run -d --name quickstart -p 6900:6900 argilla/argilla-quickstart:latest
+  docker run -d --network argilla-net --name quickstart -p 6900:6900 argilla/argilla-quickstart:latest
 ```
 
+<div class="alert alert-warning">
+
+Apple Silicon Issues
+
+Apple Silicon M1/M2 users might have issues with this deployment. To resolve this, use the `--platform linux/arm64` parameter. If this doesn't work, deploying separate images or via docker-compose will work.
+
+</div>
+
 This will run the latest quickstart docker image with 2 users `argilla` and `team`. The password for these users is
 `1234` . You can also configure these [environment variables](#environment-variables) as per you needs.
 

docs/_source/getting_started/installation/deployments/docker.md

@@ -5,11 +5,16 @@ This guide explains how to launch the Elasticsearch backend and Argilla Server u
 (setting-up-elasticsearch-via-docker)=
 ## Elasticsearch
 
+First, you need to create a network to make both standalone containers visibles between them.
+Just run the folowing command:
+```bash
+docker network create argilla-net
+
 Setting up Elasticsearch (ES) via docker is straightforward.
 Simply run the following command:
 
 ```bash
-docker run -d --name elasticsearch-for-argilla -p 9200:9200 -p 9300:9300 -e "ES_JAVA_OPTS=-Xms512m -Xmx512m" -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch-oss:7.10.2
+docker run -d --name elasticsearch-for-argilla --network argilla-net  -p 9200:9200 -p 9300:9300 -e "ES_JAVA_OPTS=-Xms512m -Xmx512m" -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:8.5.3
 ```
 
 This will create an ES docker container named *"elasticsearch-for-argilla"* that will run in the background.
@@ -35,9 +40,11 @@ docker rm elasticsearch-for-argilla
 you will loose all your datasets in Argilla!
 :::
 
-For more details about the ES installation with docker, see their [official documentation](https://www.elastic.co/guide/en/elasticsearch/reference/7.10/docker.html).
-For MacOS and Windows, Elasticsearch also provides [homebrew formulae](https://www.elastic.co/guide/en/elasticsearch/reference/7.10/brew.html) and a [msi package](https://www.elastic.co/guide/en/elasticsearch/reference/7.10/windows.html), respectively.
-We recommend ES version 7.10 to work with Argilla.
+For more details about the ES installation with docker, see their [official documentation](https://www.elastic.co/guide/en/elasticsearch/reference/8.5/docker.html).
+Also, you can visit the [docs](https://www.elastic.co/guide/en/elasticsearch/reference/8.5/install-elasticsearch.html#elasticsearch-install-packages) for other
+platforms installation.
+
+We recommend ES version 8.5.x to work with Argilla.
 
 ## Argilla Server and UI
 
@@ -54,7 +61,7 @@ By default, the Argilla server will look for your Elasticsearch endpoint at `htt
 But you can customize this by setting the `ELASTICSEARCH` environment variable.
 
 ```bash
-docker run -p 6900:6900 -e "ELASTICSEARCH=<your-elasticsearch-endpoint>" --name argilla argilla/argilla-server
+docker run --network argilla-net -p 6900:6900 -e "ELASTICSEARCH=http://elasticsearch-for-argilla:9200" --name argilla argilla/argilla-server
 ```
 :::{note}
 By default, telemetry is enabled. This helps us to improve our product. For more info about the metrics and disabling them check [telemetry](../../reference/telemetry.md).
@@ -74,3 +81,4 @@ docker stop argilla
 ```
 
 If you want to deploy your own Elasticsearch cluster via docker, we refer you to the excellent guide on the [Elasticsearch homepage](https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html).
+

docs/_source/getting_started/installation/deployments/docker_compose.md

@@ -58,7 +58,7 @@ To this end, **modify the elasticsearch service and create a new volume** in the
 ```yaml
 services:
   elasticsearch:
-    image: docker.elastic.co/elasticsearch/elasticsearch:7.11.1
+    image: docker.elastic.co/elasticsearch/elasticsearch:8.5.3
     container_name: elasticsearch
     environment:
       - node.name=elasticsearch

docs/_source/getting_started/installation/deployments/from_development.md

@@ -30,5 +30,5 @@ If you want to run the web app of the master branch **without** docker, we refer
 If you want to use vanilla docker (and have your own Elasticsearch instance running), you can just use our master image:
 
 ```bash
-docker run -p 6900:6900 -e "ELASTICSEARCH=<your-elasticsearch-endpoint>" --name argilla argilla/argilla-server:develop
+docker run -p 6900:6900 -e "ELASTICSEARCH=<your-elasticsearch-endpoint>" --network argilla-net --name argilla argilla/argilla-server:develop
 ```

docs/_source/getting_started/installation/deployments/google-colab.md

@@ -1,6 +1,7 @@
 # Google Colab
 Google Colab is a free tool that allows users to run and share Jupyter notebooks on Google's servers. It can be useful for quickly trying out models and using GPUs for training and prediction tasks. In the context of Argilla, it can be used for experimenting with pre-trained models, active learning, and computing text embeddings.
 
-To use Argilla with Google Colab, the recommended method is to use Hugging Face Spaces, as [described in this guide](huggingface-spaces.md). This is the easiest way to set up Argilla for use with Google Colab. For other installations, we recommend you to read the [cloud providers guide](cloud_providers.md).
+You can run all Argilla tutorials using the Open in Colab button at the top of each tutorial page. To use Argilla with Google Colab, the recommended method is to use Hugging Face Spaces, as [described in this guide](huggingface-spaces.md). This is the easiest way to set up Argilla for use with Google Colab. For other installations, we recommend the [deployments guide](cloud_providers.md).
+
+If you want to deploy and run Argilla entirely on Google Colab, check [this tutorial by Moritz Laurer](../../../tutorials/notebooks/deploying-textclassification-colab-activelearning.ipynb).
 
-If you are looking for an end-to-end example using Google Colab and Hugging Face Spaces, check out this [Colab notebook](https://colab.research.google.com/drive/1GeBBuRw8CIZ6SYql5Vdx4Q2Vv74eFa1I?usp=sharing).