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Fix Docs : minor grammar fixes (#2218)

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* fix(docs): fix typos and some links in documentation

* fix(docs): correct typo in filtering.md

* Update qdrant-landing/content/documentation/headless/snippets/inference/jinaai-upsert/generated/typescript.md

Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>

* Update qdrant-landing/content/documentation/headless/snippets/inference/multiple/generated/typescript.md

Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>

* Update qdrant-landing/content/documentation/hybrid-cloud/configure-scale-upgrade.md

Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>

* Update qdrant-landing/content/documentation/cloud-api.md

Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>

---------

Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>
This commit is contained in:
Mohamed Arbi
2026-03-26 17:23:36 +01:00
committed by GitHub
co-authored by Abdon Pijpelink
parent 3f3ef1ad20
commit c0db45ed8f
58 changed files with 75 additions and 75 deletions
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qdrant-landing/content/documentation/tutorials-build-essentials/rag-deepseek.md
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@@ -70,7 +70,7 @@ Qdrant will use vector embeddings of our facts to enrich the original prompt wit
We'll be using the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) model via [FastEmbed](https://github.com/qdrant/fastembed/) - A lightweight, fast, Python library for embeddings generation.
The Qdrant client provides a handy integration with FastEmbed that makes building a knowledge base very straighforward.
The Qdrant client provides a handy integration with FastEmbed that makes building a knowledge base very straightforward.
First, we need to create a collection, so Qdrant would know what vectors it will be dealing with, and then, we just pass our raw documents
wrapped into `models.Document` to compute and upload the embeddings.