Added embedding dimensions by model (#307)

platform/embedding.mdx

@@ -59,9 +59,16 @@ on Hugging Face:
 
 ## Generate embeddings
 
-To generate embeddings, choose one of the following embedding providers in the **Providers** section of an **Embedder** node in a workflow:
+To generate embeddings, choose one of the following embedding providers and models in the **Providers** section of an **Embedder** node in a workflow:
 
 <Note>You can change a workflow's predefined provider only through [Custom](/platform/workflows#create-a-custom-workflow) workflow settings.</Note>
 
-- **OpenAI**: Use [OpenAI](https://openai.com) to generate embeddings.
-- **Vertex AI**: Use [Vertex AI](https://cloud.google.com/vertex-ai) to generate embeddings.
+- **OpenAI**: Use [OpenAI](https://openai.com) to generate embeddings. Also, choose the model to use:
+
+  - **text-embedding-3-small**, with 1536 dimensions.
+  - **text-embedding-3-large**, with 3072 dimensions.
+  - **Ada 002 (Text)**, with 1536 dimensions.
+
+  [Learn more](https://platform.openai.com/docs/guides/embeddings).
+
+- **Vertex AI**: Use [Vertex AI](https://cloud.google.com/vertex-ai) to generate embeddings by using the [textembedding-gecko@001](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings) model, with 768 dimensions.

platform/workflows.mdx

@@ -171,8 +171,15 @@ There are two ways to create a custom workflow:
 16. In the **Embed** area, for **Provider**, choose one of the following:
 
     - **None**: Do not generate embeddings.
-    - **OpenAI**: Use OpenAI to generate embeddings.
-    - **Vertex AI**: Use Vertex AI to generate embeddings.
+    - **OpenAI**: Use OpenAI to generate embeddings. Also, choose the model to use:
+
+      - **text-embedding-3-small**, with 1536 dimensions.
+      - **text-embedding-3-large**, with 3072 dimensions.
+      - **Ada 002 (Text)**, with 1536 dimensions.
+
+      [Learn more](https://platform.openai.com/docs/guides/embeddings).
+
+    - **Vertex AI**: Use Vertex AI to generate embeddings by using the `textembedding-gecko@001` model, with 768 dimensions. [Learn more](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings).
 
     Learn more:
 
@@ -299,8 +306,15 @@ There are two ways to create a custom workflow:
     <Accordion title="Embedder node">
         For **Providers**, select one of the following:
 
-        - **OpenAI**: Use OpenAI to generate embeddings.
-        - **Vertex AI**: Use Vertex AI to generate embeddings.
+        - **OpenAI**: Use OpenAI to generate embeddings. Also, choose the model to use:
+
+          - **text-embedding-3-small**, with 1536 dimensions.
+          - **text-embedding-3-large**, with 3072 dimensions.
+          - **Ada 002 (Text)**, with 1536 dimensions.
+
+          [Learn more](https://platform.openai.com/docs/guides/embeddings).
+
+        - **Vertex AI**: Use Vertex AI to generate embeddings by using the `textembedding-gecko@001` model, with 768 dimensions. [Learn more](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings).
 
         Learn more:
 

snippets/ingest-configuration-shared/embedding-configuration.mdx

@@ -31,16 +31,16 @@ A common embedding configuration is a critical component that allows for dynamic
 
 * `aws-bedrock`: None
 
-* `huggingface`: `sentence-transformers/all-MiniLM-L6-v2`
+* `huggingface`: `sentence-transformers/all-MiniLM-L6-v2`, with 384 dimensions
 
-* `mixedbread-ai`: `mixedbread-ai/mxbai-embed-large-v1`
+* `mixedbread-ai`: `mixedbread-ai/mxbai-embed-large-v1`, with 1024 dimensions
 
-* `octoai`: `thenlper/gte-large`
+* `octoai`: `thenlper/gte-large`, with 1024 dimensions
 
-* `openai`: `text-embedding-ada-002`
+* `openai`: `text-embedding-ada-002`, with 1536 dimensions
 
-* `togetherai`: `togethercomputer/m2-bert-80M-8k-retrieval`
+* `togetherai`: `togethercomputer/m2-bert-80M-8k-retrieval`, with 768 dimensions
 
-* `vertexai`: `textembedding-gecko@001`
+* `vertexai`: `textembedding-gecko@001`, with 768 dimensions
 
 * `voyageai`: None