Merge pull request #306 from NYU-RTS/dependabot/github_actions/crate-ci/typos-1.44.0

Bump crate-ci/typos from 1.43.5 to 1.44.0

Author: s-sajid-ali

.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

docs/genai/04_how_to_guides/02_embeddings.mdx

@@ -4,15 +4,15 @@ While Decoder-only LLMs gained massive popularity via their usage in chatbots, E
 
 ```mermaid
 flowchart LR;
-    A["natual language text: <br> *GenAI can be used for research*"]
+    A["natural language text: <br> *GenAI can be used for research*"]
     B["encoder-only LLM"]
     C["vector embedding <br> [0.052, 0.094, 0.244, ...]"]
     A-- "Input" -->B;
     B-- "Output" -->C;
 ```
 
 :::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:

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"]