Merge pull request #678 from RizaFarheen/main

AWS Bedrock Cohere integration doc

docs/integrations/ai-llm/aws-bedrock-cohere.md

@@ -0,0 +1,88 @@
+# Integrating with AWS Bedrock Cohere in Orkes Conductor
+
+To effectively utilize AI and LLM tasks in Orkes Conductor, it's essential to integrate your Conductor cluster with the necessary AI and LLM models. 
+
+AWS Bedrock Cohere offers a range of models that can be incorporated into the Orkes Conductor console. The choice of model depends on your unique use case, the functionalities you require, and the specific natural language processing tasks you intend to tackle. 
+
+This guide will provide the steps for integrating the AWS Bedrock Cohere provider with Orkes Conductor.
+
+## Steps to integrate with AWS Bedrock Cohere
+
+Before beginning the integration process in Orkes Conductor, you must get specific configuration credentials from your AWS account. 
+
+- AWS account ID & region where the resource is located. 
+- Amazon Resource Name (ARN) to set up the connection.
+- External ID - When you assume a role belonging to another account in AWS, you need to provide the external ID, which can be used in an IAM role trust policy to designate the person to assume the role. [Learn more](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create_for-user_externalid.html). 
+- [Access key and secret from AWS account](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html). 
+
+## Integrating with AWS Bedrock Cohere as a model provider
+
+Let’s integrate AWS Bedrock Cohere with Orkes Conductor.
+
+1. Navigate to **Integrations** from the left menu on your Orkes Conductor console.
+2. Click **+New integration** button from the top-right of your window.
+3. Under the **AI/LLM** section, choose **AWS Bedrock Cohere**. 
+4. Click **+Add** and provide the following parameters:
+
+<p align="center"><img src="/content/img/create-new-aws-bedrock-cohere-integration.png" alt="Create AWS Bedrock Cohere Integration" width="60%" height="auto"></img></p>
+
+| Parameters | Description |
+| ---------- | ----------- | 
+| Integration name | Provide a name for the integration. |
+| Connection type | Choose the required connection type. Depending upon how the connection is to be established, it can take the following values:<ul><li>**Current Conductor Role** - Choose this if you are using the current Conductor role to establish the connection. </li><li>Assume **External Role** - Choose this if you are assuming a role belonging to another AWS account. [Learn more](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create_for-user_externalid.html). </li><li>**Access Key/Secret** - Choose this if you are establishing the connection using the access key and secret.</li></ul> |
+| Region | Provide the valid AWS region where the resource is located. |
+| Account ID | Provide your AWS account ID. This field is optional. |
+| Role ARN | Specify the Amazon Resource Name (ARN) required to set up the connection.<br/><br/>**Note**: This field is applicable only if the **_Connection Type_** is chosen as **_Assume External Role_**. | 
+| External ID | If applicable, provide the external ID to assume the role.<br/><br/>**Note**: This field is applicable only if the **_Connection Type_** is chosen as **_Assume External Role_**. | 
+| Access key | Provide the AWS access key.<br/><br/>**Note**: This field is applicable only if the **_Connection Type_** is chosen as **_Access Key/Secret_**. | 
+| Access secret | Provide the AWS access secret.<br/><br/>**Note**: This field is applicable only if the **_Connection Type_** is chosen as **_Access Key/Secret_**. | 
+| Description | Provide a description of your integration. |
+
+5. You can toggle-on the **Active** button to activate the integration instantly.
+6. Click **Save**.
+
+## Adding AWS Bedrock Cohere models to integration
+
+You have now integrated your Conductor console with the AWS Bedrock Cohere provider. The next step is to integrate with the specific models. 
+AWS Bedrock Cohere has different models: Command, Command Light, Command R, Embed English and more. Each model is intended for different use cases, such as text completion and generating embeddings.
+
+Depending on your use case, you must configure the required model within your AWS Bedrock Cohere configuration.
+
+To add a new model to the AWS Bedrock Cohere integration:
+
+1. Navigate to the integrations page and click the '+' button next to the integration created.
+
+<p align="center"><img src="/content/img/create-new-aws-bedrock-cohere-integration-model-from-integrations-page.png" alt="Create AWS Bedrock Cohere Integration Model from Listed Integrations" width="100%" height="auto"></img></p>
+
+2. Click **+New model**.
+3. Provide the model name and an optional description. The complete [list of models in AWS Bedrock Cohere is available here](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html). 
+
+<p align="center"><img src="/content/img/create-new-aws-bedrock-cohere-integration-model.png" alt="Create AWS Bedrock Cohere Integration Model" width="70%" height="auto"></img></p>
+
+4. Toggle-on the **Active** button to enable the model immediately.
+5. Click **Save**.
+
+This ensures the integration model is saved for future use in LLM tasks within Orkes Conductor.
+
+## RBAC - Governance on who can use Integrations
+
+The integration with the required models is now ready. Next, we should determine the access control to these models. 
+
+The permission can be granted to applications/groups within the Orkes Conductor console. 
+
+To provide explicit permission to Groups:
+
+1. Navigate to **Access Control > Groups** from the left menu on your Orkes Conductor console.
+2. Create a new group or choose an existing group.
+3. Under the **Permissions** section, click **+Add Permission**.
+4. Under the **Integrations** tab, select the required integrations with the required permissions. 
+
+<p align="center"><img src="/content/img/rbac-aws-bedrock-cohere-integration.png" alt="Add Permissions for Integrations" width="70%" height="auto"></img></p>
+
+5. Click **Add Permissions**. This ensures that all the group members can access these integration models in their workflows. 
+
+Similarly, you can also provide permissions to [applications](https://orkes.io/content/access-control-and-security/applications#configuring-application). 
+
+:::note
+Once the integration is ready, [start creating workflows](https://orkes.io/content/reference-docs/api/metadata/creating-workflow-definition) with [LLM tasks](https://orkes.io/content/category/reference-docs/ai-tasks).
+:::

docs/integrations/ai-llm/aws-bedrock-llama2.md

@@ -55,7 +55,7 @@ To add a new model to the AWS Bedrock Llama 2 integration:
 <p align="center"><img src="/content/img/create-new-aws-bedrock-llama2-integration-model-from-integrations-page.png" alt="Create AWS Bedrock Llama 2 Integration Model from Listed Integrations" width="100%" height="auto"></img></p>
 
 2. Click **+New model**.
-3. Provide the model name and an optional description for the model. [You can get the complete list of models in AWS Bedrock Llama 2 here](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html). 
+3. Provide the model name and an optional description for the model. The complete [list of models in AWS Bedrock Llama 2 is available here](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html). 
 
 <p align="center"><img src="/content/img/create-new-aws-bedrock-llama2-integration-model.png" alt="Create AWS Bedrock Llama 2 Integration Model" width="70%" height="auto"></img></p>
 

docs/integrations/ai-llm/aws-bedrock-titan.md

@@ -56,7 +56,7 @@ To add a new model to the AWS Bedrock Titan integration:
 <p align="center"><img src="/content/img/create-new-aws-bedrock-titan-integration-model-from-integrations-page.png" alt="Create AWS Bedrock Titan Integration Model from Listed Integrations" width="100%" height="auto"></img></p>
 
 2. Click **+New model**.
-3. Provide the model name and an optional description for the model. [You can get the complete list of models in AWS Bedrock Titan here](https://docs.aws.amazon.com/bedrock/latest/userguide/titan-models.html). 
+3. Provide the model name and an optional description for the model. The complete [list of models in AWS Bedrock Titan is available here](https://docs.aws.amazon.com/bedrock/latest/userguide/titan-models.html). 
 
 <p align="center"><img src="/content/img/create-new-aws-bedrock-titan-integration-model.png" alt="Create AWS Bedrock Titan Integration Model" width="70%" height="auto"></img></p>
 

docs/integrations/ai-llm/azure-open-ai.md

@@ -58,7 +58,7 @@ To add a new model to the Azure OpenAI integration:
 <p align="center"><img src="/content/img/create-new-azure-open-ai-integration-model-from-integrations-page.png" alt="Create Azure Open AI Integration Model from Listed Integrations" width="100%" height="auto"></img></p>
 
 2. Click **+New model**.
-3. Provide the model name and an optional description for the model. You can get the [complete list of models in Azure OpenAI here](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/legacy-models). 
+3. Provide the model name and an optional description for the model. The complete [list of models in Azure OpenAI is available here](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/legacy-models). 
 
 <p align="center"><img src="/content/img/create-new-azure-open-ai-integration-model.png" alt="Create Azure Open AI Integration Model" width="70%" height="auto"></img></p>
 

docs/integrations/ai-llm/cohere.md

@@ -53,7 +53,7 @@ To add a new model to the Cohere integration:
 <p align="center"><img src="/content/img/create-new-cohere-integration-model-from-integrations-page.png" alt="Create Cohere Integration Model from Listed Integrations" width="100%" height="auto"></img></p>
 
 2. Click **+New model**.
-3. Provide the model name and an optional description for the model. [You can get the complete list of models in Cohere here](https://docs.cohere.com/docs/command-beta). 
+3. Provide the model name and an optional description for the model. The complete [list of models in Cohere is available here](https://docs.cohere.com/docs/command-beta). 
 
 <p align="center"><img src="/content/img/create-new-cohere-integration-model.png" alt="Create Cohere Integration Model" width="60%" height="auto"></img></p>
 

docs/integrations/ai-llm/hugging-face.md

@@ -60,7 +60,7 @@ To add a new model to the Hugging Face integration:
 <p align="center"><img src="/content/img/create-new-model-for-hugging-face-integration.png" alt="Create new model for Hugging Face Integration" width="100%" height="auto"></img></p>
 
 2. Click **+New model**.
-3. Provide the model name, endpoint (the one you created in the previous step), and an optional description for the model. You can get the [complete list of models in Hugging Face here](https://huggingface.co/models).
+3. Provide the model name, endpoint (the one you created in the previous step), and an optional description for the model. The complete [list of models in Hugging Face is available here](https://huggingface.co/models).
 
 <p align="center"><img src="/content/img/creating-new-model-for-hugging-face-integration.png" alt="Creating new model for Hugging Face Integration" width="60%" height="auto"></img></p>
 

docs/integrations/ai-llm/mistral.md

@@ -51,7 +51,7 @@ To add a new model to the Mistral integration:
 <p align="center"><img src="/content/img/create-new-mistral-integration-model-from-integrations-page.png" alt="Create Mistral Integration Model from Listed Integrations" width="100%" height="auto"></img></p>
 
 2. Click **+New model**.
-3. Provide the model name and an optional description for the model. [You can get the complete list of Mistral models here](https://docs.mistral.ai/getting-started/models/). 
+3. Provide the model name and an optional description for the model. The complete [list of models in Mistral is available here](https://docs.mistral.ai/getting-started/models/). 
 
 <p align="center"><img src="/content/img/create-new-mistral-integration-model.png" alt="Create Mistral Integration Model" width="70%" height="auto"></img></p>
 

docs/integrations/ai-llm/open-ai.md

@@ -56,7 +56,7 @@ To add a new model to the OpenAI integration:
 <p align="center"><img src="/content/img/create-new-model-for-open-ai-integration.png" alt="Create new model for OpenAI Integration" width="100%" height="auto"></img></p>
 
 2. Click **+New model.**
-3. Provide the model name and an optional description for the model. You can get the [complete list of models in OpenAI here](https://platform.openai.com/docs/models/overview). 
+3. Provide the model name and an optional description for the model. The complete [list of models in Open AI is available here](https://platform.openai.com/docs/models/overview). 
 
 <p align="center"><img src="/content/img/creating-new-model-for-open-ai-integration.png" alt="Creating new model for OpenAI Integration" width="70%" height="auto"></img></p>
 

docs/integrations/ai-llm/vertex-ai.md

@@ -1,20 +1,20 @@
-# Integrating with Vertex AI in Orkes Conductor
+# Integrating with Google Vertex AI in Orkes Conductor
 
 To effectively utilize AI and LLM tasks in Orkes Conductor, it's essential to integrate your Conductor cluster with the necessary AI and LLM models. 
 
-Vertex AI offers a range of models that can be incorporated into the Orkes Conductor cluster. The choice of model depends on your unique use case, the functionalities you require, and the specific natural language processing tasks you intend to tackle. 
+Google Vertex AI offers a range of models that can be incorporated into the Orkes Conductor cluster. The choice of model depends on your unique use case, the functionalities you require, and the specific natural language processing tasks you intend to tackle. 
 
-This guide will provide the steps for integrating the Vertex AI provider with Orkes Conductor.
+This guide will provide the steps for integrating the Google Vertex AI provider with Orkes Conductor.
 
-## Steps to integrate with Vertex AI
+## Steps to integrate with Google Vertex AI
 
 :::note
-Vertex AI integration is compatible with GCP clusters only.
+Google Vertex AI integration is compatible with GCP clusters only.
 :::
 
 1. Navigate to **Integrations** from the left menu on your Orkes Conductor console.
 2. Click **+New integration** button from the top-right of your window.
-3. Under the **AI / LLM** section, choose **Vertex AI**. 
+3. Under the **AI / LLM** section, choose **Google Vertex AI**. 
 4. Click **+Add** and provide the following parameters:
 
 <p align="center"><img src="/content/img/create-new-vertex-ai-integration.png" alt="Create new Vertex AI Integration" width="60%" height="auto"></img></p>
@@ -30,22 +30,22 @@ Vertex AI integration is compatible with GCP clusters only.
 5. You can toggle-on the **Active** button to activate the integration instantly.
 6. Click **Save**.
 
-## Adding Vertex AI models to the integration
+## Adding Google Vertex AI models to the integration
 
-Now, you have integrated your Conductor console with the Vertex AI provider. The next step is integrating with the specific Vertex AI models. 
+Now, you have integrated your Conductor console with the Google Vertex AI provider. The next step is integrating with the specific Vertex AI models. 
 
-Vertex AI has different models, such as Bison, Gecko, etc. Each model is to be used for different use cases, such as text completion, generating embeddings, etc.
+Google Vertex AI has different models, such as Bison, Gecko, etc. Each model is to be used for different use cases, such as text completion, generating embeddings, etc.
 
-Depending on your use case, you must configure different models within your Vertex AI configuration.
+Depending on your use case, you must configure different models within your Google Vertex AI configuration.
 
-To add a new model to the Vertex AI integration:
+To add a new model to the Google Vertex AI integration:
 
 1. Navigate to the integrations page and click the '+' button next to the integration created.
 
 <p align="center"><img src="/content/img/create-new-model-for-vertex-ai-integration.png" alt="Create new model for Vertex AI Integration" width="100%" height="auto"></img></p>
 
 2. Click **+New model**.
-3. Provide the model name and an optional description for the model. You can get the [complete list of models in Vertex AI here](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/models). 
+3. Provide the model name and an optional description for the model. The complete [list of models in Google Vertex AI is available here](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/models). 
 
 <p align="center"><img src="/content/img/creating-new-model-for-vertex-ai-integration.png" alt="Creating new model for Vertex AI Integration" width="60%" height="auto"></img></p>
 

sidebars.js

@@ -423,13 +423,18 @@ const sidebars = {
                         {
                             type: 'doc',
                             id: 'integrations/ai-llm/vertex-ai',
-                            label: 'Vertex AI',
+                            label: 'Google Vertex AI',
                         },
                         {
                             type: 'doc',
                             id: 'integrations/ai-llm/hugging-face',
                             label: 'Hugging Face',
                         },
+                        {
+                            type: 'doc',
+                            id: 'integrations/ai-llm/aws-bedrock-cohere',
+                            label: 'AWS Bedrock Cohere',
+                        },
                         {
                             type: 'doc',
                             id: 'integrations/ai-llm/aws-bedrock-llama2',