v1.7.0

🔆 Highlights

OpenAI fine-tuning support

Use your data in Argilla to fine-tune OpenAI models. You can do this by getting your data in the specific format through the prepare_for_training method or train directly using ArgillaTrainer.

Argilla Trainer improvements

We’ve added CLI support for Argilla Trainer and two new frameworks for training: OpenAI & SpanMarker.

Logging and loading enhancements

We’ve improved the speed and robustness of rg.log and rg.load methods.

typer CLI

A more user-friendly command line interface with typer that includes argument suggestions and colorful messages.

Changelog 1.7.0

Added

• add max_retries and num_threads parameters to rg.log to run data logging request concurrently with backoff retry policy. See #2458 and #2533
• rg.load accepts include_vectors and include_metrics when loading data. Closes #2398
• Added settings param to prepare_for_training (#2689)
• Added prepare_for_training for openai (#2658)
• Added ArgillaOpenAITrainer (#2659)
• Added ArgillaSpanMarkerTrainer for Named Entity Recognition (#2693)
• Added ArgillaTrainer CLI support. Closes (#2809)

Changed

• Argilla quickstart image dependencies are externalized into quickstart.requirements.txt. See #2666
• bulk endpoints will upsert data when record id is present. Closes #2535
• moved from click to typer CLI support. Closes (#2815)
• Argilla server docker image is built with PostgreSQL support. Closes #2686
• The rg.log computes all batches and raise an error for all failed batches.
• The default batch size for rg.log is now 100.

Fixed

• argilla.training bugfixes and unification (#2665)
• Resolved several small bugs in the ArgillaTrainer.

Deprecated

• The rg.log_async function is deprecated and will be removed in next minor release.

As always, thanks to out amazing contributors!

• docs: Fix broken links in README.md (#2759) by @stephantul
• Update how_to.ipynb by @chainyo
• Update log_load_and_prepare_data.ipynb by @ignacioct