From 03e273fa9bb937f9d392b2f55fb9f37a15a121b8 Mon Sep 17 00:00:00 2001 From: qdrant Date: Thu, 25 May 2023 13:35:46 +0000 Subject: [PATCH] docs auto-sync --- qdrant-landing/content/documentation/collections.md | 4 ++-- qdrant-landing/content/documentation/integrations.md | 2 +- qdrant-landing/content/documentation/security.md | 4 ---- 3 files changed, 3 insertions(+), 7 deletions(-) diff --git a/qdrant-landing/content/documentation/collections.md b/qdrant-landing/content/documentation/collections.md index 61a599ecd..19b061287 100644 --- a/qdrant-landing/content/documentation/collections.md +++ b/qdrant-landing/content/documentation/collections.md @@ -8,7 +8,7 @@ weight: 30 A collection is a named set of points (vectors with a payload) among which you can search. Vectors within the same collection must have the same dimensionality and be compared by a single metric. -Distance metrics used to measure similarities among vectors. +Distance metrics are used to measure similarities among vectors. The choice of metric depends on the way vectors obtaining and, in particular, on the method of neural network encoder training. Qdrant supports these most popular types of metrics: @@ -385,7 +385,7 @@ from qdrant_client import QdrantClient client = QdrantClient("localhost", port=6333) -client.list_aliases() +client.get_aliases() ``` ### List all collections diff --git a/qdrant-landing/content/documentation/integrations.md b/qdrant-landing/content/documentation/integrations.md index 06373fd11..c267699b3 100644 --- a/qdrant-landing/content/documentation/integrations.md +++ b/qdrant-landing/content/documentation/integrations.md @@ -81,7 +81,7 @@ client = qdrant_client.QdrantClient( index = GPTQdrantIndex.from_documents(documents, client=client, collection_name="documents") ``` -The library [comes with a notebook](https://github.com/jerryjliu/llama_index/blob/main/examples/vector_indices/QdrantIndexDemo.ipynb) +The library [comes with a notebook](https://github.com/jerryjliu/llama_index/blob/main/docs/examples/vector_stores/QdrantIndexDemo.ipynb) that shows an end-to-end example of how to use Qdrant within LlamaIndex. ## DocArray diff --git a/qdrant-landing/content/documentation/security.md b/qdrant-landing/content/documentation/security.md index 9b2c83561..4d688e183 100644 --- a/qdrant-landing/content/documentation/security.md +++ b/qdrant-landing/content/documentation/security.md @@ -5,10 +5,6 @@ weight: 165 There are various ways to secure your own Qdrant instance. -For authentication on Qdrant cloud refer to its -[Authentication](https://qdrant.tech/documentation/cloud/cloud-quick-start/#authentication) -section. - ## Authentication *Available as of v1.2.0*