From e3da7db5d91b5532bc6833014247310198c9d7cb Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 2 Mar 2026 07:34:10 +0000 Subject: [PATCH 1/2] Bump crate-ci/typos from 1.43.5 to 1.44.0 Bumps [crate-ci/typos](https://github.com/crate-ci/typos) from 1.43.5 to 1.44.0. - [Release notes](https://github.com/crate-ci/typos/releases) - [Changelog](https://github.com/crate-ci/typos/blob/master/CHANGELOG.md) - [Commits](https://github.com/crate-ci/typos/compare/v1.43.5...v1.44.0) --- updated-dependencies: - dependency-name: crate-ci/typos dependency-version: 1.44.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- .github/workflows/spellcheck.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/spellcheck.yaml b/.github/workflows/spellcheck.yaml index fcc66ad40b..da7be3decc 100644 --- a/.github/workflows/spellcheck.yaml +++ b/.github/workflows/spellcheck.yaml @@ -17,6 +17,6 @@ jobs: uses: actions/checkout@v6 - name: Spell Check Repo - uses: crate-ci/typos@v1.43.5 + uses: crate-ci/typos@v1.44.0 with: files: docs/**/**/*.md docs/**/**/*.mdx From 24e8203cb056427436c936cf8380a76ca1910919 Mon Sep 17 00:00:00 2001 From: Sajid Ali Date: Tue, 3 Mar 2026 10:12:38 -0500 Subject: [PATCH 2/2] natual -> natural --- docs/genai/04_how_to_guides/02_embeddings.mdx | 4 ++-- .../04_how_to_guides/03_retrieval_augmented_generation.mdx | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/genai/04_how_to_guides/02_embeddings.mdx b/docs/genai/04_how_to_guides/02_embeddings.mdx index 972313dab2..a43dca4df0 100644 --- a/docs/genai/04_how_to_guides/02_embeddings.mdx +++ b/docs/genai/04_how_to_guides/02_embeddings.mdx @@ -4,7 +4,7 @@ While Decoder-only LLMs gained massive popularity via their usage in chatbots, E ```mermaid flowchart LR; - A["natual language text:
*GenAI can be used for research*"] + A["natural language text:
*GenAI can be used for research*"] B["encoder-only LLM"] C["vector embedding
[0.052, 0.094, 0.244, ...]"] A-- "Input" -->B; @@ -12,7 +12,7 @@ flowchart LR; ``` :::tip -Embeddings have the ability to encode the semantic meaning of the natual language text/images! +Embeddings have the ability to encode the semantic meaning of the natural language text/images! ::: The snippet below uses the `text-embedding-3-small` model to create 32-dimensional floating point vector embeddings for the input string: diff --git a/docs/genai/04_how_to_guides/03_retrieval_augmented_generation.mdx b/docs/genai/04_how_to_guides/03_retrieval_augmented_generation.mdx index 9c82e00e85..a92a6fc1e7 100644 --- a/docs/genai/04_how_to_guides/03_retrieval_augmented_generation.mdx +++ b/docs/genai/04_how_to_guides/03_retrieval_augmented_generation.mdx @@ -17,7 +17,7 @@ flowchart TB; C["encoder-only LLM"] D@{shape: procs, label: "text chunk embedding"} E[("vector database")] - F["natual language prompt"] + F["natural language prompt"] G["query embedding"] I["relevant chunks"] J["original prompt with added context"]