Prodigy 1.12 alpha release: LLM-assisted workflows, prompt engineering & fully custom task routing for multi-annotator scenarios.

UPDATE: v1.12a4 has been released which fixes issues with the task router and session factory.
It also adds a new progress estimator which is based on the relative position in the source object. The motivation for this new way of estimating progress was to provide a more reliable estimate when the actual total target is unknown while working with the stream of data.
Since it is very different from the progress based on the number of annotated examples, we now distinguish in the UI between target progress (based on annotated examples if total_examples_target is set), source progress (the new source based progress) and progress (for custom progress functions in active learning).
Please check the docs for the details on how to interpret the new progress bars, especially in multi-user scenarios.
Looking forward to hearing what you think :slightly_smiling_face:

To install:

pip install --pre prodigy -f https://XXXX-XXXX-XXXX-XXXX@download.prodi.gy