From 03ee2523385cb82b6cd78be6aa079a9c3511b70a Mon Sep 17 00:00:00 2001 From: Oliver Rice Date: Wed, 9 Oct 2024 09:40:16 -0500 Subject: [PATCH] update docs with l1 --- docs/api.md | 1 + docs/concepts_indexes.md | 1 + docs/index.md | 2 +- 3 files changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/api.md b/docs/api.md index fa73c7c..7dd0cef 100644 --- a/docs/api.md +++ b/docs/api.md @@ -89,6 +89,7 @@ Available options for distance `measure` are: - `vecs.IndexMeasure.cosine_distance` - `vecs.IndexMeasure.l2_distance` +- `vecs.IndexMeasure.l1_distance` - `vecs.IndexMeasure.max_inner_product` which correspond to different methods for comparing query vectors to the vectors in the database. diff --git a/docs/concepts_indexes.md b/docs/concepts_indexes.md index d616f4a..8373484 100644 --- a/docs/concepts_indexes.md +++ b/docs/concepts_indexes.md @@ -26,6 +26,7 @@ Available options for distance `measure` are: - `vecs.IndexMeasure.cosine_distance` - `vecs.IndexMeasure.l2_distance` +- `vecs.IndexMeasure.l1_distance` - `vecs.IndexMeasure.max_inner_product` which correspond to different methods for comparing query vectors to the vectors in the database. diff --git a/docs/index.md b/docs/index.md index 8f0d0db..d082d74 100644 --- a/docs/index.md +++ b/docs/index.md @@ -30,7 +30,7 @@ Vecs is a Python client library for managing and querying vector stores in Postg ## Overview - Vector Management: create collections to persist and update vectors in a PostgreSQL database. -- Querying: Query vectors efficiently using measures such as cosine distance, l2 distance, or max inner product. +- Querying: Query vectors efficiently using measures such as cosine distance, l2 distance, l1 distance, or max inner product. - Metadata: Each vector can have associated metadata, which can also be used as filters during queries. - Hybrid Data: vecs creates its own schema and can coexist with your existing relational data