Update Argilla integration for v2.x SDK

[sdiazlor]

Describe changes

I updated the Argilla integration with the new version Argilla 2.0.

NOTES:

• I kept the convention using keyword arguments, but let me know if you prefer to specify the type hinting clearly.
• I didn't find tests for annotator integrations. I can add some. In a comment, I leave some basic workflow of how to use it.

cc @strickvl

Pre-requisites

Please ensure you have done the following:

• [x] I have read the CONTRIBUTING.md document.
• [x] If my change requires a change to docs, I have updated the documentation accordingly.
• [ ] I have added tests to cover my changes.
• [x] I have based my new branch on develop and the open PR is targeting develop. If your branch wasn't based on develop read Contribution guide on rebasing branch to develop.
• [ ] If my changes require changes to the dashboard, these changes are communicated/requested.

Types of changes

• [ ] Bug fix (non-breaking change which fixes an issue)
• [x] New feature (non-breaking change which adds functionality)
• [ ] Breaking change (fix or feature that would cause existing functionality to change)
• [ ] Other (add details above)

Summary by CodeRabbit

• Documentation Updates

  • Enhanced clarity in the documentation for available annotators and the Argilla tool.
  • Improved deployment instructions and updated the Argilla quickstart guide link.
  • Modifications to the Argilla settings for better usability, including port defaults and header naming.

• New Features

  • Added workspace-specific operations for Argilla annotation integration.
  • Introduced error handling and logging improvements during operations.

• Dependency Updates

  • Increased version requirement for the argilla package to >=2.0.0.

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📝 Walkthrough

Walkthrough

The recent changes enhance the documentation and functionality of the ZenML framework, particularly around the Argilla integration. Documentation has been clarified to better represent tools and their usage, while code updates improve exception handling, workspace management, and usability. Key modifications include upgrading the Argilla package requirement and refining methods to support workspace-specific operations, streamlining dataset management, and improving user interaction with new client features.

Changes

Files	Change Summary
docs/book/component-guide/annotators/*.md	Documentation updates for annotators, enhancing clarity around integrations and Argilla usage, including improved deployment details.
docs/mocked_libs.json	Removed specific Argilla SDK modules and added an exceptions API module, suggesting a restructuring of the library’s focus.
src/zenml/integrations/argilla/__init__.py	Updated Argilla version requirement from <2 to >=2.0.0, indicating a major dependency change.
src/zenml/integrations/argilla/annotators/*.py	Significant updates to support workspace-specific operations, improved error handling, and new methods for dataset management.
src/zenml/integrations/argilla/flavors/*.py	Modifications to settings attributes, including renaming and default values, indicating a shift in workspace handling.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant ArgillaAnnotator
    participant ArgillaAPI

    User->>ArgillaAnnotator: Launch Annotation Interface
    ArgillaAnnotator->>ArgillaAPI: Initialize Client
    ArgillaAnnotator->>ArgillaAPI: Get Datasets (with workspace)
    ArgillaAPI-->>ArgillaAnnotator: Return Datasets
    ArgillaAnnotator->>User: Display Datasets

🐰 In fields of green, I hop with glee,
New changes bloom, just wait and see!
With tools in hand and workspaces bright,
Data dances in the moonlight.
Let’s celebrate the joy we find,
With each update, we’re one of a kind! 🌼✨

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[sdiazlor]

from typing import List

import argilla as rg
from zenml import step, pipeline
from zenml.client import Client
from zenml.logger import get_logger

logger = get_logger(__name__)


@step
def get_data() -> List[str]:
    """Random text data for annotation."""
    texts = [
        "The quick brown fox jumps over the lazy dog.",
        "ZenML is an extensible, open-source MLOps framework.",
        "Argilla helps in managing and annotating data.",
        "Machine learning models require good quality data.",
        "Annotation tools are essential for supervised learning.",
    ]
    
    return texts


@step
def upload_to_argilla(
    texts: List[str],
    dataset_name: str = "default_dataset",
):
    """Creates a dataset and loads the data to Argilla.

    Args:
        texts: List of text data.
        dataset_name: Name of the dataset in Argilla.
    """
    
    annotator = Client().active_stack.annotator
    
    from zenml.integrations.argilla.annotators.argilla_annotator import (
        ArgillaAnnotator,
    )

    if not isinstance(annotator, ArgillaAnnotator):
        raise TypeError(
            "This step can only be used with the Argilla annotator."
        )
    
    argilla = annotator._get_client()
    

    # Create or get the dataset in Argilla
    try:
        dataset = annotator.get_dataset(dataset_name=dataset_name)
        if dataset is None:
            settings = rg.Settings(
                guidelines="These are some guidelines.",
                fields=[
                    rg.TextField(
                        name="text",
                    ),
                ],
                questions=[
                    rg.LabelQuestion(
                        name="label",
                        labels=["label_1", "label_2", "label_3"]
                    ),
                ],
                metadata=[
                    rg.TermsMetadataProperty(
                        name="terms",
                        title="Annotation groups",
                    ),
                ],
            )
            dataset = annotator.add_dataset(dataset_name=dataset_name, settings=settings)

            records = [
                rg.Record(
                    fields={"text": text}
                )
                for text in texts
            ]

            annotator.add_records(dataset_name=dataset_name, records=records)
    except Exception as e:
        logger.error(f"Error: {e}")
        raise e
    
    print(dataset)

@pipeline
def data_pipeline():
    data = get_data()
    upload_to_argilla(data)


if __name__ == "__main__":
    data_pipeline()
    

[strickvl]

Also a few errors from CI: https://github.com/zenml-io/zenml/actions/runs/10290280476/job/28480088504?pr=2915#step:6:41 @sdiazlor

[sdiazlor]

@strickvl Thank you! They should be fixed, I had missed those.

[strickvl]

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[strickvl]

@schustmi we'll have to look into conditionally ignoring / not installing argilla on our Python 3.8 instances on slow CI.

[AlexejPenner]

:seal: - thanks so much @sdiazlor for your contribution, i tested this in action an everything works as expected.