From 642f55b892ca7de5b434952b7f4b47860f490e10 Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Thu, 20 Jun 2024 18:11:10 +0200 Subject: [PATCH 1/9] Update Argilla frontend readme --- argilla-frontend/README.md | 93 ++++++++++++++++++++++---------------- 1 file changed, 53 insertions(+), 40 deletions(-) diff --git a/argilla-frontend/README.md b/argilla-frontend/README.md index 33d042ba75..db23942d69 100644 --- a/argilla-frontend/README.md +++ b/argilla-frontend/README.md @@ -1,67 +1,82 @@

Argilla
- ✨ Argilla ✨ + Argilla

+

Work on data together, make your model outputs better!

+

-CI +CI - Codecov -CI +CI - - + +

-

Open-source data curation platform for LLMs

-

MLOps for NLP: from data labeling to model monitoring

- -
- -https://github.com/argilla-io/argilla/assets/1107111/49e28d64-9799-4cac-be49-19dce0f6bd86 -

- - + + - - + + - - + +

-
+Argilla is a **collaboration platform for AI engineers and domain experts** that require **high-quality outputs, full data ownership, and overall efficiency**. -

-

-πŸ“„ Documentation | -πŸš€ Quickstart | -🎼 Cheatsheet | -πŸ«±πŸΎβ€πŸ«²πŸΌ Contribute | -πŸ—ΊοΈ Roadmap -

-

+If you just want to get started, we recommend our [UI demo](https://demo.argilla.io/sign-in?auth=ZGVtbzoxMjM0NTY3OA%3D%3D) or our [free Hugging Face Spaces deployment integration](https://huggingface.co/new-space?template=argilla/argilla-template-space). Curious, and want to know more? Read our [documentation](https://argilla-io.github.io/argilla/latest/). + +## Why use Argilla? + +Whether you are working on monitoring and improving complex **generative tasks** involving LLM pipelines with RAG, or you are working on a **predictive task** for things like AB-testing of span- and text-classification models. Our versatile platform helps you ensure **your data work pays off**. + +### Improve your AI output quality through data quality + +Compute is expensive and output quality is important. We help you focus on data, which tackles the root cause of both of these problems at once. Argilla helps you to **achieve and keep high-quality standards** for your data. This means you can improve the quality of your AI output. + +### Take control of your data and models -## πŸš€ Quickstart +Most AI platforms are black boxes. Argilla is different. We believe that you should be the owner of both your data and your models. That's why we provide you with all the tools your team needs to **manage your data and models in a way that suits you best**. -Argilla is an open-source data curation platform for LLMs. Using Argilla, everyone can build robust language models through faster data curation using both human and machine feedback. We provide support for each step in the MLOps cycle, from data labeling to model monitoring. +### Improve efficiency by quickly iterating on the right data and models -There are different options to get started: +Gathering data is a time-consuming process. Argilla helps by providing a platform that allows you to **interact with your data in a more engaging way**. This means you can quickly and easily label your data with filters, AI feedback suggestions and semantic search. So you can focus on training your models and monitoring their performance. -1. Take a look at our [quickstart page](https://docs.argilla.io/en/latest/getting_started/quickstart.html) πŸš€ +## 🏘️ Community -2. Start contributing by looking at our [contributor guidelines](#πŸ«±πŸΎβ€πŸ«²πŸΌ-contribute) πŸ«±πŸΎβ€πŸ«²πŸΌ +We are an open-source community-driven project and we love to hear from you. Here are some ways to get involved: -3. Skip some steps with our [cheatsheet](#🎼-cheatsheet) 🎼 +- [Community Meetup](https://lu.ma/embed-checkout/evt-IQtRiSuXZCIW6FB): listen in or present during one of our bi-weekly events. + +- [Slack](https://join.slack.com/t/rubrixworkspace/shared_invite/zt-whigkyjn-a3IUJLD7gDbTZ0rKlvcJ5g): get direct support from the community. + +- [Roadmap](https://github.com/orgs/argilla-io/projects/10/views/1): plans change but we love to discuss those with our community so feel encouraged to participate. + +## What do people build with Argilla? + +### Open-source datasets and models + +Argilla is a tool that can be used to achieve and keep **high-quality data standards** with a **focus on NLP and LLMs**. Our community uses Argilla to create amazing open-source [datasets](https://huggingface.co/datasets?other=argilla) and [models](https://huggingface.co/models?other=distilabel), and **we love contributions to open-source** ourselves too. + +- Our [cleaned UltraFeedback dataset](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned) and the [Notus](https://huggingface.co/argilla/notus-7b-v1) and [Notux](https://huggingface.co/argilla/notux-8x7b-v1) models, where we improved benchmark and empirical human judgment for the Mistral and Mixtral models with cleaner data using **human feedback**. +- Our [distilabeled Intel Orca DPO dataset](https://huggingface.co/datasets/argilla/distilabel-intel-orca-dpo-pairs) and the [improved OpenHermes model](https://huggingface.co/argilla/distilabeled-OpenHermes-2.5-Mistral-7B), show how we improve model performance by filtering out 50% of the original dataset through **human and AI feedback**. + +### Internal Use cases + +AI teams from companies like [the Red Cross](https://510.global/), [Loris.ai](https://loris.ai/) and [Prolific](https://www.prolific.com/) use Argilla to **improve the quality and efficiency of AI** projects. They shared their experiences in our [AI community meetup](https://lu.ma/embed-checkout/evt-IQtRiSuXZCIW6FB). + +- AI for good: [the Red Cross presentation](https://youtu.be/ZsCqrAhzkFU?feature=shared) showcases **how their experts and AI team collaborate** by classifying and redirecting requests from refugees of the Ukrainian crisis to streamline the support processes of the Red Cross. +- Customer support: during [the Loris meetup](https://youtu.be/jWrtgf2w4VU?feature=shared) they showed how their AI team uses unsupervised and few-shot contrastive learning to help them **quickly validate and gain labelled samples for a huge amount of multi-label classifiers**. +- Research studies: [the showcase from Prolific](https://youtu.be/ePDlhIxnuAs?feature=shared) announced their integration with our platform. They use it to actively **distribute data collection projects** among their annotating workforce. This allows them to quickly and **efficiently collect high-quality data** for their research studies. ## πŸ–₯️ FRONTEND @@ -99,9 +114,7 @@ npm run generate ## πŸ«±πŸΎβ€πŸ«²πŸΌ Contribute - To help our community with the creation of contributions, we have created our [developer](https://docs.argilla.io/en/latest/community/developer_docs.html) and [contributor](https://docs.argilla.io/en/latest/community/contributing.html) docs. Additionally, you can always [schedule a meeting](https://calendly.com/david-berenstein-huggingface/30min) with our Developer Advocacy team so they can get you up to speed. - -## πŸ₯‡ Contributors +To help our community with the creation of contributions, we have created our [community](https://argilla-io.github.io/argilla/latest/community/) docs. Additionally, you can always [schedule a meeting](https://calendly.com/david-berenstein-huggingface/30min) with our Developer Advocacy team so they can get you up to speed. From 29ab9520f7404083025c371f1e53bbeefdbe2f49 Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Thu, 20 Jun 2024 18:14:16 +0200 Subject: [PATCH 2/9] Update readmes --- argilla-frontend/README.md | 45 ++++---------------------------------- argilla-server/README.md | 32 ++++++++++++++++++--------- 2 files changed, 26 insertions(+), 51 deletions(-) diff --git a/argilla-frontend/README.md b/argilla-frontend/README.md index db23942d69..d36358ac47 100644 --- a/argilla-frontend/README.md +++ b/argilla-frontend/README.md @@ -35,48 +35,11 @@ Argilla is a **collaboration platform for AI engineers and domain experts** that If you just want to get started, we recommend our [UI demo](https://demo.argilla.io/sign-in?auth=ZGVtbzoxMjM0NTY3OA%3D%3D) or our [free Hugging Face Spaces deployment integration](https://huggingface.co/new-space?template=argilla/argilla-template-space). Curious, and want to know more? Read our [documentation](https://argilla-io.github.io/argilla/latest/). -## Why use Argilla? +This repository only contains developer info about the front end. If you want to get started, we recommend taking a +look at our [main repository](https://github.com/argilla-io/argilla) or our [documentation](https://argilla-io.github.io/argilla/latest/). -Whether you are working on monitoring and improving complex **generative tasks** involving LLM pipelines with RAG, or you are working on a **predictive task** for things like AB-testing of span- and text-classification models. Our versatile platform helps you ensure **your data work pays off**. - -### Improve your AI output quality through data quality - -Compute is expensive and output quality is important. We help you focus on data, which tackles the root cause of both of these problems at once. Argilla helps you to **achieve and keep high-quality standards** for your data. This means you can improve the quality of your AI output. - -### Take control of your data and models - -Most AI platforms are black boxes. Argilla is different. We believe that you should be the owner of both your data and your models. That's why we provide you with all the tools your team needs to **manage your data and models in a way that suits you best**. - -### Improve efficiency by quickly iterating on the right data and models - -Gathering data is a time-consuming process. Argilla helps by providing a platform that allows you to **interact with your data in a more engaging way**. This means you can quickly and easily label your data with filters, AI feedback suggestions and semantic search. So you can focus on training your models and monitoring their performance. - -## 🏘️ Community - -We are an open-source community-driven project and we love to hear from you. Here are some ways to get involved: - -- [Community Meetup](https://lu.ma/embed-checkout/evt-IQtRiSuXZCIW6FB): listen in or present during one of our bi-weekly events. - -- [Slack](https://join.slack.com/t/rubrixworkspace/shared_invite/zt-whigkyjn-a3IUJLD7gDbTZ0rKlvcJ5g): get direct support from the community. - -- [Roadmap](https://github.com/orgs/argilla-io/projects/10/views/1): plans change but we love to discuss those with our community so feel encouraged to participate. - -## What do people build with Argilla? - -### Open-source datasets and models - -Argilla is a tool that can be used to achieve and keep **high-quality data standards** with a **focus on NLP and LLMs**. Our community uses Argilla to create amazing open-source [datasets](https://huggingface.co/datasets?other=argilla) and [models](https://huggingface.co/models?other=distilabel), and **we love contributions to open-source** ourselves too. - -- Our [cleaned UltraFeedback dataset](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned) and the [Notus](https://huggingface.co/argilla/notus-7b-v1) and [Notux](https://huggingface.co/argilla/notux-8x7b-v1) models, where we improved benchmark and empirical human judgment for the Mistral and Mixtral models with cleaner data using **human feedback**. -- Our [distilabeled Intel Orca DPO dataset](https://huggingface.co/datasets/argilla/distilabel-intel-orca-dpo-pairs) and the [improved OpenHermes model](https://huggingface.co/argilla/distilabeled-OpenHermes-2.5-Mistral-7B), show how we improve model performance by filtering out 50% of the original dataset through **human and AI feedback**. - -### Internal Use cases - -AI teams from companies like [the Red Cross](https://510.global/), [Loris.ai](https://loris.ai/) and [Prolific](https://www.prolific.com/) use Argilla to **improve the quality and efficiency of AI** projects. They shared their experiences in our [AI community meetup](https://lu.ma/embed-checkout/evt-IQtRiSuXZCIW6FB). - -- AI for good: [the Red Cross presentation](https://youtu.be/ZsCqrAhzkFU?feature=shared) showcases **how their experts and AI team collaborate** by classifying and redirecting requests from refugees of the Ukrainian crisis to streamline the support processes of the Red Cross. -- Customer support: during [the Loris meetup](https://youtu.be/jWrtgf2w4VU?feature=shared) they showed how their AI team uses unsupervised and few-shot contrastive learning to help them **quickly validate and gain labelled samples for a huge amount of multi-label classifiers**. -- Research studies: [the showcase from Prolific](https://youtu.be/ePDlhIxnuAs?feature=shared) announced their integration with our platform. They use it to actively **distribute data collection projects** among their annotating workforce. This allows them to quickly and **efficiently collect high-quality data** for their research studies. +Are you a contributor or do you want to understand what is going on under the hood, please keep reading the +documentation below. ## πŸ–₯️ FRONTEND diff --git a/argilla-server/README.md b/argilla-server/README.md index ba2d4d6bda..cd0ad97813 100644 --- a/argilla-server/README.md +++ b/argilla-server/README.md @@ -1,19 +1,18 @@

Argilla
- Argilla-Server + Argilla

-

The repository for the Python native FastAPI server for Argilla backend.

- +

Work on data together, make your model outputs better!

- + CI -Codecov - -CI +Codecov + +CI @@ -32,11 +31,10 @@

-Argilla is a **collaboration platform for AI engineers and domain experts** that require **high-quality outputs, full -data ownership, and overall efficiency**. +Argilla is a **collaboration platform for AI engineers and domain experts** that require **high-quality outputs, full data ownership, and overall efficiency**. This repository only contains developer info about the backend server. If you want to get started, we recommend taking a -look at our [main repository](https://github.com/argilla-io/argilla) or our [documentation](https://docs.argilla.io/). +look at our [main repository](https://github.com/argilla-io/argilla) or our [documentation](https://argilla-io.github.io/argilla/latest/). Are you a contributor or do you want to understand what is going on under the hood, please keep reading the documentation below. @@ -108,3 +106,17 @@ the [argilla-frontend](/argilla-frontend/README.md) project ```sh pdm server ``` + +## πŸ«±πŸΎβ€πŸ«²πŸΌ Contribute + +To help our community with the creation of contributions, we have created our [community](https://argilla-io.github.io/argilla/latest/community/) docs. Additionally, you can always [schedule a meeting](https://calendly.com/david-berenstein-huggingface/30min) with our Developer Advocacy team so they can get you up to speed. + + + + + + + +## πŸ—ΊοΈ Roadmap + +We continuously work on updating [our plans and our roadmap](https://github.com/orgs/argilla-io/projects/10/views/1) and we love to discuss those with our community. Feel encouraged to participate. From 98ebb342c5cb2a15de55e9c9019428d28c47cf12 Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Thu, 20 Jun 2024 18:25:27 +0200 Subject: [PATCH 3/9] Update start_page.md --- docs/_source/_common/snippets/start_page.md | 75 ++++++++++++--------- 1 file changed, 43 insertions(+), 32 deletions(-) diff --git a/docs/_source/_common/snippets/start_page.md b/docs/_source/_common/snippets/start_page.md index 0d81692825..7696f729bd 100644 --- a/docs/_source/_common/snippets/start_page.md +++ b/docs/_source/_common/snippets/start_page.md @@ -2,7 +2,7 @@ # Welcome to -## Argilla is a platform to build high-quality AI datasets +## Argilla is a platform for building high-quality AI datasets If you need support join the [Argilla Slack community](https://join.slack.com/t/rubrixworkspace/shared_invite/zt-whigkyjn-a3IUJLD7gDbTZ0rKlvcJ5g) @@ -12,19 +12,15 @@ If you need support join the [Argilla Slack community](https://join.slack.com/t/ Get started by publishing your first dataset. -### 1. Open an IDE, Jupyter or Collab - -If you're a Collab user, you can directly use our [introductory tutorial](https://colab.research.google.com/github/argilla-io/argilla/blob/develop/docs/_source/getting_started/quickstart_workflow_feedback.ipynb). - -### 2. Install the SDK with pip +### 1. Install the SDK with pip To work with Argilla datasets, you need to use the Argilla SDK. You can install the SDK with pip as follows: ```sh -pip install argilla -U +pip install argilla -U --pre ``` -### 3. Connect to your Argilla server +### 2. Connect to your Argilla server Get your `ARGILLA_API_URL`: @@ -38,51 +34,66 @@ Make sure to replace `ARGILLA_API_URL` and `ARGILLA_API_KEY` in the code below. ```python import argilla as rg -rg.init( - api_url="ARGILLA_API_URL", - api_key="ARGILLA_API_KEY", - # extra_headers={"Authorization": f"Bearer {"HF_TOKEN"}"} +client = rg.Argilla( + api_url="", + api_key="" + # extra_headers={"Authorization": f"Bearer {HF_TOKEN}"} ) ``` -### 4. Create your first dataset +### 3. Create your first dataset -Specify a workspace where the dataset will be created. Check your workspaces in ["My settings"](/user-settings). To create a new workspace, check the [docs](https://docs.argilla.io/en/latest/getting_started/installation/configurations/workspace_management.html). +Specify a workspace where the dataset will be created. Check your workspaces in ["My settings"](/user-settings). To create a new workspace, check the [docs](https://argilla-io.github.io/argilla/latest/how_to_guides/workspace/). -Create a Dataset with two labels ("sadness" and "joy"). Don't forget to replace "". Here, we are using a task template, check the docs to [create a fully custom dataset](https://docs.argilla.io/en/latest/practical_guides/create_update_dataset/create_dataset.html). +Create a Dataset with two labels ("positive" and "negative"). Don't forget to replace "". Here, we are using a task template, check the docs to [create a fully custom dataset](https://argilla-io.github.io/argilla/latest/how_to_guides/dataset/). ```python -dataset = rg.FeedbackDataset.for_text_classification( - labels=["sadness", "joy"], - multi_label=False, - use_markdown=True, - guidelines=None, - metadata_properties=None, - vectors_settings=None, +settings = rg.Settings( + guidelines="Classify the reviews as positive or negative.", + fields=[ + rg.TextField( + name="review", + title="Text from the review", + use_markdown=False, + ), + ], + questions=[ + rg.LabelQuestion( + name="my_label", + title="In which category does this article fit?", + labels=["positive", "negative"], + ) + ], ) -dataset.push_to_argilla(name="my-first-dataset", workspace="") +dataset = rg.Dataset( + name=f"my_first_dataset", + workspace="", + settings=settings, + client=client, +) +dataset.create() ``` -### 5. Add records +### 4. Add records -Create a list with the records you want to add. Ensure that you match the fields with the ones specified in the previous step. +You canCreate a list with the records you want to add. Ensure that you match the fields with the ones specified in the previous step. -You can also use `pandas` or `load_dataset` to [read an existing dataset and create records from it](https://docs.argilla.io/en/latest/practical_guides/create_update_dataset/records.html#add-records). +You can also use `pandas` or `datasets.load_dataset` to [read an existing dataset and create records from it](https://argilla-io.github.io/argilla/latest/how_to_guides/record/). ```python records = [ - rg.FeedbackRecord( + rg.Record( fields={ - "text": "I am so happy today", + "review": "This is a great product.", }, ), - rg.FeedbackRecord( + rg.Record( fields={ - "text": "I feel sad today", + "review": "This is a bad product.", }, - ) + ), ] -dataset.add_records(records) +dataset.records.log(records) ``` From a0e1e9af59008323e8385733c07bfc2e7e4f6d8e Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Thu, 20 Jun 2024 18:34:08 +0200 Subject: [PATCH 4/9] Update note rendering --- argilla/docs/how_to_guides/annotate.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/argilla/docs/how_to_guides/annotate.md b/argilla/docs/how_to_guides/annotate.md index 97d40eb396..f8e3ab44e6 100644 --- a/argilla/docs/how_to_guides/annotate.md +++ b/argilla/docs/how_to_guides/annotate.md @@ -172,7 +172,7 @@ If the dataset contains metadata, responses and suggestions, click onΒ **Filter* From the `Responses` dropdown, type and select the question. You can set a range for rating questions and select specific values for label, multi-label, and span questions. !!! note - The text and ranking questions are not available for filtering. + The text and ranking questions are not available for filtering. === "By suggestions" From 296df1708dd8c60b8583f592de97cdb3e7f9e181 Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Thu, 20 Jun 2024 18:42:39 +0200 Subject: [PATCH 5/9] Update readme reference --- README.md | 4 ++++ argilla/CHANGELOG.md | 2 +- 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 296b766c52..af5ca42d24 100644 --- a/README.md +++ b/README.md @@ -81,6 +81,10 @@ AI teams from companies like [the Red Cross](https://510.global/), [Loris.ai](ht ## πŸ‘¨β€πŸ’» Getting started +> [!NOTE] +> This readme represent the release candidate for the 2.0.0 SDK version. The readme for the last stable version of the 1x SDK can be found [1.x](./argilla-v1/README.md) + + ### Installation First things first! You can install the SDK with pip as follows: diff --git a/argilla/CHANGELOG.md b/argilla/CHANGELOG.md index 4d82977d1b..e37bc8f4f2 100644 --- a/argilla/CHANGELOG.md +++ b/argilla/CHANGELOG.md @@ -17,7 +17,7 @@ These are the section headers that we use: ## [2.0.0rc1](https://github.com/argilla-io/argilla/compare/v1.29.0...v2.0.0rc) > [!NOTE] -> This releas for 2.0.0rc1 does not contain any changelog entries because it is the first release candidate for the 2.0.0 version. The following versions will contain the changelog entries again. For a general overview of the changes in the 2.0.0 version, please refer to [our blog](https://argilla.io/blog/) or [our new documentation](https://argilla-io.github.io/argilla/latest). +> This release for 2.0.0rc1 does not contain any changelog entries because it is the first release candidate for the 2.0.0 version. The following versions will contain the changelog entries again. For a general overview of the changes in the 2.0.0 version, please refer to [our blog](https://argilla.io/blog/) or [our new documentation](https://argilla-io.github.io/argilla/latest). ## [1.29.0](https://github.com/argilla-io/argilla/compare/v1.28.0...v1.29.0) From 28f86b32c3083ed3b901f65c7649d77b2c95db4b Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Thu, 20 Jun 2024 18:50:35 +0200 Subject: [PATCH 6/9] Updated changelogs --- argilla-server/CHANGELOG.md | 2 ++ argilla-v1/CHANGELOG.md | 2 ++ 2 files changed, 4 insertions(+) diff --git a/argilla-server/CHANGELOG.md b/argilla-server/CHANGELOG.md index a6fc455df0..a665acf0e3 100644 --- a/argilla-server/CHANGELOG.md +++ b/argilla-server/CHANGELOG.md @@ -16,6 +16,8 @@ These are the section headers that we use: ## [Unreleased]() +## [2.0.0rc1](https://github.com/argilla-io/argilla/compare/v1.29.0...v2.0.0rc1) + ### Removed - Removed all API v0 endpoints. ([#4852](https://github.com/argilla-io/argilla/pull/4852)) diff --git a/argilla-v1/CHANGELOG.md b/argilla-v1/CHANGELOG.md index 18e67b7cad..b68022463a 100644 --- a/argilla-v1/CHANGELOG.md +++ b/argilla-v1/CHANGELOG.md @@ -16,6 +16,8 @@ These are the section headers that we use: ## [Unreleased]() +## [2.0.0rc1](https://github.com/argilla-io/argilla/compare/v1.29.0...v2.0.0rc1) + > [!NOTE] > As per the release of our 2.0 SDK, this changelog is deprecated and will only contain potential bug fixes for the 1.x SDK, but it will not contain any new features. For the latest features and changes, please refer to the [2.0 SDK changelog](../argilla/CHANGELOG.md). From 638dde9cfff76fc3a6c50ef430a81e9a41832fd7 Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Thu, 20 Jun 2024 18:57:38 +0200 Subject: [PATCH 7/9] Update README references --- README.md | 7 +++---- argilla-server/README.md | 3 +++ argilla-v1/README.md | 3 +++ 3 files changed, 9 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index af5ca42d24..d583c3ffb9 100644 --- a/README.md +++ b/README.md @@ -34,6 +34,9 @@ Argilla is a **collaboration platform for AI engineers and domain experts** that require **high-quality outputs, full data ownership, and overall efficiency**. +> [!NOTE] +> This README represents the release candidate for the 2.0.0 SDK version. The README for the last stable version of the 1x SDK can be found [1.x](./argilla-v1/README.md) + If you just want to get started, we recommend our [UI demo](https://demo.argilla.io/sign-in?auth=ZGVtbzoxMjM0NTY3OA%3D%3D) or our [free Hugging Face Spaces deployment integration](https://huggingface.co/new-space?template=argilla/argilla-template-space). Curious, and want to know more? Read our [documentation](https://argilla-io.github.io/argilla/latest/). ## Why use Argilla? @@ -81,10 +84,6 @@ AI teams from companies like [the Red Cross](https://510.global/), [Loris.ai](ht ## πŸ‘¨β€πŸ’» Getting started -> [!NOTE] -> This readme represent the release candidate for the 2.0.0 SDK version. The readme for the last stable version of the 1x SDK can be found [1.x](./argilla-v1/README.md) - - ### Installation First things first! You can install the SDK with pip as follows: diff --git a/argilla-server/README.md b/argilla-server/README.md index cd0ad97813..b2de9c85ae 100644 --- a/argilla-server/README.md +++ b/argilla-server/README.md @@ -33,6 +33,9 @@ Argilla is a **collaboration platform for AI engineers and domain experts** that require **high-quality outputs, full data ownership, and overall efficiency**. +> [!NOTE] +> This README represents the release candidate for the 2.0.0 SDK version. The README for the last stable version of the 1x SDK can be found [1.x](../argilla-v1/README.md) + This repository only contains developer info about the backend server. If you want to get started, we recommend taking a look at our [main repository](https://github.com/argilla-io/argilla) or our [documentation](https://argilla-io.github.io/argilla/latest/). diff --git a/argilla-v1/README.md b/argilla-v1/README.md index 37aff75763..a52ba8ed74 100644 --- a/argilla-v1/README.md +++ b/argilla-v1/README.md @@ -34,6 +34,9 @@ Argilla is a **collaboration platform for AI engineers and domain experts** that require **high-quality outputs, full data ownership, and overall efficiency**. +> [!NOTE] +> This README represents the 1.29 SDK version. We have stopped development for the 1.x SDK version, while still committing to bug fixes. If you are looking for the README of the 2.x SDK version take a look [here](../README.md). + If you just want to get started, we recommend our [UI demo](https://demo.argilla.io/sign-in?auth=ZGVtbzoxMjM0NTY3OA%3D%3D) or our [2-click deployment quick start](https://docs.argilla.io/en/latest/getting_started/cheatsheet.html). Curious, and want to know more? Read our [documentation](https://docs.argilla.io/). ## Why use Argilla? From e87a5cf67144ef851a11d70ac6d028ec502d97d0 Mon Sep 17 00:00:00 2001 From: David Berenstein Date: Thu, 20 Jun 2024 20:18:34 +0200 Subject: [PATCH 8/9] Apply suggestions from code review Co-authored-by: burtenshaw --- docs/_source/_common/snippets/start_page.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/_source/_common/snippets/start_page.md b/docs/_source/_common/snippets/start_page.md index 7696f729bd..eddfa95440 100644 --- a/docs/_source/_common/snippets/start_page.md +++ b/docs/_source/_common/snippets/start_page.md @@ -45,7 +45,7 @@ client = rg.Argilla( Specify a workspace where the dataset will be created. Check your workspaces in ["My settings"](/user-settings). To create a new workspace, check the [docs](https://argilla-io.github.io/argilla/latest/how_to_guides/workspace/). -Create a Dataset with two labels ("positive" and "negative"). Don't forget to replace "". Here, we are using a task template, check the docs to [create a fully custom dataset](https://argilla-io.github.io/argilla/latest/how_to_guides/dataset/). +Here, we are defining a creating a dataset with a text field and a label question ("positive" and "negative"), check the docs to [create a fully custom dataset](https://argilla-io.github.io/argilla/latest/how_to_guides/dataset/). Don't forget to replace "". ```python settings = rg.Settings( @@ -76,7 +76,7 @@ dataset.create() ### 4. Add records -You canCreate a list with the records you want to add. Ensure that you match the fields with the ones specified in the previous step. +You can create a list with records that you want to add. Ensure that you match the fields with those specified in the question settings. You can also use `pandas` or `datasets.load_dataset` to [read an existing dataset and create records from it](https://argilla-io.github.io/argilla/latest/how_to_guides/record/). From 227ac00a5f0dc290609661c6d5ba817e9a964890 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 20 Jun 2024 18:19:00 +0000 Subject: [PATCH 9/9] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- docs/_source/_common/snippets/start_page.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/_source/_common/snippets/start_page.md b/docs/_source/_common/snippets/start_page.md index eddfa95440..8b7b1ef96f 100644 --- a/docs/_source/_common/snippets/start_page.md +++ b/docs/_source/_common/snippets/start_page.md @@ -45,7 +45,7 @@ client = rg.Argilla( Specify a workspace where the dataset will be created. Check your workspaces in ["My settings"](/user-settings). To create a new workspace, check the [docs](https://argilla-io.github.io/argilla/latest/how_to_guides/workspace/). -Here, we are defining a creating a dataset with a text field and a label question ("positive" and "negative"), check the docs to [create a fully custom dataset](https://argilla-io.github.io/argilla/latest/how_to_guides/dataset/). Don't forget to replace "". +Here, we are defining a creating a dataset with a text field and a label question ("positive" and "negative"), check the docs to [create a fully custom dataset](https://argilla-io.github.io/argilla/latest/how_to_guides/dataset/). Don't forget to replace "". ```python settings = rg.Settings(