From 993ea90d50bfdda3744a373396bad3693ad62f04 Mon Sep 17 00:00:00 2001 From: Brendan Clement Date: Tue, 6 Oct 2026 10:17:18 -0700 Subject: [PATCH] docs: keep the LeRobot page's framing around its Geneva example The previous commit restored production's sentence so the example is attributed to Geneva. This brings back the newer page's customer-facing framing, that feature engineering costs nothing until it is used and never copies the dataset or touches the videos, while keeping the Geneva link and naming the API the code calls: @udf, add_columns and backfill. The code and its timings, measured with Geneva, are unchanged. --- docs/web/integrations/lerobotdataset.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/web/integrations/lerobotdataset.mdx b/docs/web/integrations/lerobotdataset.mdx index 9c87575f9..08cf8bd15 100644 --- a/docs/web/integrations/lerobotdataset.mdx +++ b/docs/web/integrations/lerobotdataset.mdx @@ -115,7 +115,7 @@ Filter with SQL over any feature, using the indexes built at conversion: From here it is standard LanceDB. The examples below are from our DROID walkthrough, all on the table the trainer reads. -**Derived columns are added without rewriting existing data.** With [Geneva](/geneva/udfs/udfs), `add_columns` registers a Python function and its input columns as a new derived column. No values are computed at that point. `backfill` computes and stores the derived values later, in parallel, without rewriting the existing columns or video blobs: +**Feature engineering costs nothing until you use it.** With [Geneva](/geneva/udfs/udfs), `add_columns` registers a `@udf` function and its input columns as a new column and computes nothing; `backfill` computes and stores the values later, in parallel. No copy of the dataset, and the videos are never touched: ```python @udf(data_type=pa.float32(), input_columns=["action_joint_velocity"])