Update how-to-deploy-models-cohere-embed.md

Author: shubhirajMsft

articles/machine-learning/how-to-deploy-models-cohere-embed.md

@@ -53,7 +53,7 @@ The previously mentioned Cohere models can be deployed as a service with pay-as-
 - An Azure Machine Learning workspace. If you don't have these, use the steps in the [Quickstart: Create workspace resources](quickstart-create-resources.md) article to create them.
 
     > [!IMPORTANT]
-    > Pay-as-you-go model deployment offering is only available in workspaces created in EastUS, EastUS2 or Sweden Central regions.
+    > Pay-as-you-go model deployment offering is only available in workspaces created in EastUS2 or Sweden Central regions.
 
 -  Azure role-based access controls (Azure RBAC) are used to grant access to operations. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the Resource Group.
 
@@ -64,7 +64,7 @@ The previously mentioned Cohere models can be deployed as a service with pay-as-
 To create a deployment:
 
 1. Go to [Azure Machine Learning studio](https://ml.azure.com/home).
-1. Select the workspace in which you want to deploy your models. To use the pay-as-you-go model deployment offering, your workspace must belong to the EastUS, EastUS2 or Sweden Central region.
+1. Select the workspace in which you want to deploy your models. To use the pay-as-you-go model deployment offering, your workspace must belong to the EastUS2 or Sweden Central region.
 1. Choose the model you want to deploy from the [model catalog](https://ml.azure.com/model/catalog).
 
    Alternatively, you can initiate deployment by going to your workspace and selecting **Endpoints** > **Serverless endpoints** > **Create**.
@@ -118,15 +118,15 @@ For more information on using the APIs, see the [reference](#embed-api-reference
     Content-type: application/json
 ```
 
-#### v1/emebeddings request schema
+#### v1/embeddings request schema
 
 Cohere Embed v3 - English and Embed v3 - Multilingual accept the following parameters for a `v1/embeddings` API call:
 
 | Property | Type | Default | Description |
 | --- | --- | --- | --- |
 |`input` |`array of strings` |Required |An array of strings for the model to embed. Maximum number of texts per call is 96. We recommend reducing the length of each text to be under 512 tokens for optimal quality. |
 
-#### v1/emebeddings response schema
+#### v1/embeddings response schema
 
 The response payload is a dictionary with the following fields:
 
@@ -329,6 +329,16 @@ Response:
 | OpenAI SDK (experimental)    | [openaisdk.ipynb](https://aka.ms/samples/cohere-embed/openaisdk)                                    |
 | LangChain      | [langchain.ipynb](https://aka.ms/samples/cohere-embed/langchain)                                |
 | Cohere SDK     | [cohere-sdk.ipynb](https://aka.ms/samples/cohere-embed/cohere-python-sdk)                                 |
+| LiteLLM SDK    | [litellm.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/cohere/litellm.ipynb) |
+
+##### Retrieval Augmented Generation (RAG) and Tool-Use samples
+**Description** | **Sample Type** | **Sample Notebook**
+--|--|--
+Create a local (FAISS) vector index using Cohere embeddings - Langchain|`langchain`, `langchain_cohere`|[cohere_faiss_langchain_embed.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/cohere/cohere_faiss_langchain_embed.ipynb)
+Use Cohere Command R/R+ to answer questions from data in local (FAISS) vector index - Langchain|`langchain`, `langchain_cohere`|[command_faiss_langchain.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/cohere/command_faiss_langchain.ipynb)
+Use Cohere Command R/R+ to answer questions from data in AI search vector index - Langchain|`langchain`, `langchain_cohere`|[cohere-aisearch-langchain-rag.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/cohere/cohere-aisearch-langchain-rag.ipynb)
+Use Cohere Command R/R+ to answer questions from data in AI search vector index - Cohere SDK| `cohere`, `azure_search_documents`|[cohere-aisearch-rag.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/cohere/cohere-aisearch-rag.ipynb)
+Command R+ tool/function calling using LangChain|`cohere`, `langchain`, `langchain_cohere`|[command_tools-langchain.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/cohere/command_tools-langchain.ipynb)
 
 ## Cost and quotas