Argilla repo skill

SkillDatabases & data

"Use Argilla 2.x for human-feedback dataset annotation, Python SDK

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Argilla repo skill skill

What this skill tells your AI

The instructions your AI receives, as published by vectorspacelab/arex-skill in skills/repositories/repo-skills/argilla/SKILL.md and read by ahel’s review.

Argilla is a self-hosted/open-source collaboration platform for building high-quality datasets for AI projects. Use this skill when a task involves Argilla 2.x SDK code, annotation dataset schemas, record logging, search/filter/export, Argilla server deployment, webhooks, or migration from Argilla v1/Rubrix.

The source project is mature/stable; prefer current documented Argilla 2.x workflows for new work and route legacy APIs only through the migration sub-skill.

Fast route map

User request signalRead this firstWhy
Create/configure an Argilla dataset, fields/questions/metadata/vectors, log records, map columns, query/filter/export, use users/workspaces, or build a webhook listenersub-skills/python-sdk/SKILL.mdCurrent Argilla 2.x SDK API and dataset-feedback workflows
Deploy or operate the server with Hugging Face Spaces, Docker Compose, Kubernetes/Helm, python -m argilla_server, database/search/Redis, OAuth/SSO, telemetry, proxy/base URL, or reindexingsub-skills/server-ops/SKILL.mdServer package, CLI, service stack, config, and operational troubleshooting
Migrate old Argilla v1/Rubrix users, workspaces, or task-specific legacy datasets into Argilla 2.xsub-skills/legacy-migration/SKILL.mdSafe v1 compatibility and dataset schema migration guidance
Check whether this skill matches a checkout/versionreferences/repo-provenance.mdSource commit, package versions, evidence paths, and refresh baseline
Need a high-level capability/dependency overview before choosing a routereferences/package-overview.mdMonorepo layout, package split, selected/excluded scope, and dependencies
Cross-cutting install/import/API-url/service troubleshootingreferences/troubleshooting.mdQuick triage and route-to-sub-skill guidance

Minimal install and import checks

For current SDK-only workflows:

python -m pip install argilla
python - <<'PY'
import argilla as rg
print(rg.__version__)
print(rg.Argilla)
PY

For server operations, the server package is separate in source and deployments often use Docker/Spaces. If installed as a Python package, check it without starting services:

python - <<'PY'
import argilla_server
print(hasattr(argilla_server, "app"))
PY
python -m argilla_server --help

Run scripts/check_argilla_env.py for a safe local import/version check. Add --check-server only when the user intentionally wants a live API check and provides a reachable API URL/key.

Operating rules

  1. Treat Argilla as a service-backed package. Dataset creation, record logging, user/workspace changes, Hub import/export, webhook registration, server starts, migrations, reindexing, and deployment commands can mutate data or contact external services.
  2. For SDK work, create an explicit rg.Argilla(api_url=..., api_key=...) client before constructing resources unless environment defaults are guaranteed.
  3. For private Hugging Face Spaces, keep the Argilla API key separate from the Hugging Face bearer token header.
  4. For deployment work, validate configs and render CLI help before starting Docker/Kubernetes/server processes or running migrations.
  5. For legacy migration, export/back up first; do not install broad old argilla-v1 extras into a current Argilla 2.x server environment.
  6. Do not route frontend implementation changes, repository CI, docs-generation, or heavy old notebooks through this runtime skill.

Bundled safe helpers

Signals

GitHub stars
278
Forks
21
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
argilla
Source
github.com/vectorspacelab/arex-skill