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Copy file name to clipboardExpand all lines: articles/ai-studio/how-to/deploy-models-cohere-command.md
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- An [Azure AI hub resource](../how-to/create-azure-ai-resource.md).
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> [!IMPORTANT]
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> For Cohere family models, the pay-as-you-go model deployment offering is only available with AI hubs created in EastUS, EastUS2 or Sweden Central regions.
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> For Cohere family models, the pay-as-you-go model deployment offering is only available with AI hubs created in EastUS2 or Sweden Central region.
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- An [Azure AI project](../how-to/create-projects.md) in Azure AI Studio.
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- Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Studio. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Studio](../concepts/rbac-ai-studio.md).
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:::image type="content" source="../media/deploy-monitor/cohere-command/command-r-deploy-pay-as-you-go.png" alt-text="A screenshot showing how to deploy a model with the pay-as-you-go option." lightbox="../media/deploy-monitor/cohere-command/command-r-deploy-pay-as-you-go.png":::
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1. Select the project in which you want to deploy your model. To deploy the model your project must be in the EastUS, EastUS2 or Sweden Central regions.
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1. Select the project in which you want to deploy your model. To deploy the model your project must be in the EastUS2 or Sweden Central region.
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1. In the deployment wizard, select the link to **Azure Marketplace Terms** to learn more about the terms of use.
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1. You can also select the **Marketplace offer details** tab to learn about pricing for the selected model.
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1. If this is your first time deploying the model in the project, you have to subscribe your project for the particular offering. This step requires that your account has the **Azure AI Developer role** permissions on the Resource Group, as listed in the prerequisites. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending. Select **Subscribe and Deploy**. Currently you can have only one deployment for each model within a project.
Create a local Facebook AI similarity search (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)
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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)
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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)
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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)
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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)
Copy file name to clipboardExpand all lines: articles/ai-studio/how-to/deploy-models-cohere-embed.md
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- An [Azure AI hub resource](../how-to/create-azure-ai-resource.md).
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> [!IMPORTANT]
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> For Cohere family models, the pay-as-you-go model deployment offering is only available with AI hubs created in EastUS, EastUS2 or Sweden Central regions.
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> For Cohere family models, the pay-as-you-go model deployment offering is only available with AI hubs created in EastUS2 or Sweden Central region.
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- An [Azure AI project](../how-to/create-projects.md) in Azure AI Studio.
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- Azure role-based access controls are used to grant access to operations in Azure AI Studio. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Studio](../concepts/rbac-ai-studio.md).
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:::image type="content" source="../media/deploy-monitor/cohere-embed/embed-english-deploy-pay-as-you-go.png" alt-text="A screenshot showing how to deploy a model with the pay-as-you-go option." lightbox="../media/deploy-monitor/cohere-embed/embed-english-deploy-pay-as-you-go.png":::
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1. Select the project in which you want to deploy your model. To deploy the model, your project must be in the EastUS, EastUS2 or Sweden Central regions.
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1. Select the project in which you want to deploy your model. To deploy the model, your project must be in the EastUS2 or Sweden Central region.
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1. In the deployment wizard, select the link to **Azure Marketplace Terms** to learn more about the terms of use.
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1. You can also select the **Marketplace offer details** tab to learn about pricing for the selected model.
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1. If it is your first time deploying the model in the project, you have to subscribe your project for the particular offering. This step requires that your account has the **Azure AI Developer role** permissions on the Resource Group, as listed in the prerequisites. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending. Select **Subscribe and Deploy**. Currently you can have only one deployment for each model within a project.
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Content-type: application/json
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```
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#### v1/emebeddings request schema
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#### v1/embeddings request schema
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Cohere Embed v3 - English and Embed v3 - Multilingual accept the following parameters for a `v1/embeddings` API call:
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| Property | Type | Default | Description |
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| --- | --- | --- | --- |
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|`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. |
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#### v1/emebeddings response schema
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#### v1/embeddings response schema
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The response payload is a dictionary with the following fields:
Create a local Facebook AI Similarity Search (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)
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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)
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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)
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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)
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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)
Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-deploy-models-cohere-command.md
+12-2Lines changed: 12 additions & 2 deletions
Display the source diff
Display the rich diff
Original file line number
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Diff line change
@@ -73,7 +73,7 @@ The previously mentioned Cohere models can be deployed as a service with pay-as-
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- 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.
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> [!IMPORTANT]
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> Pay-as-you-go model deployment offering is only available in workspaces created in EastUS, EastUS2 or Sweden Central regions.
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> Pay-as-you-go model deployment offering is only available in workspaces created in EastUS2 or Sweden Central region.
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- 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.
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To create a deployment:
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1. Go to [Azure Machine Learning studio](https://ml.azure.com/home).
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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.
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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.
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1. Choose the model you want to deploy from the [model catalog](https://ml.azure.com/model/catalog).
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Alternatively, you can initiate deployment by going to your workspace and selecting **Endpoints** > **Serverless endpoints** > **Create**.
Create a local Facebook AI Similarity Search (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)
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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)
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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)
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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)
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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)
Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-deploy-models-cohere-embed.md
+14-4Lines changed: 14 additions & 4 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -53,7 +53,7 @@ The previously mentioned Cohere models can be deployed as a service with pay-as-
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- 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.
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> [!IMPORTANT]
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> Pay-as-you-go model deployment offering is only available in workspaces created in EastUS, EastUS2 or Sweden Central regions.
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+
> Pay-as-you-go model deployment offering is only available in workspaces created in EastUS2 or Sweden Central region.
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- 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.
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@@ -64,7 +64,7 @@ The previously mentioned Cohere models can be deployed as a service with pay-as-
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To create a deployment:
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1. Go to [Azure Machine Learning studio](https://ml.azure.com/home).
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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.
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+
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.
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1. Choose the model you want to deploy from the [model catalog](https://ml.azure.com/model/catalog).
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Alternatively, you can initiate deployment by going to your workspace and selecting **Endpoints** > **Serverless endpoints** > **Create**.
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Content-type: application/json
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```
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#### v1/emebeddings request schema
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#### v1/embeddings request schema
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Cohere Embed v3 - English and Embed v3 - Multilingual accept the following parameters for a `v1/embeddings` API call:
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| Property | Type | Default | Description |
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| --- | --- | --- | --- |
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|`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. |
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#### v1/emebeddings response schema
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+
#### v1/embeddings response schema
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The response payload is a dictionary with the following fields:
Create a local Facebook AI Similarity Search (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)
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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)
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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)
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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)
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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)
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