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Microsoft Azure OpenAI

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To start using a Microsoft Azure OpenAI model with Cognigy.AI features, follow these steps:

  1. Add a Model
  2. Apply the Model

Add a Model

To add a model provided by Microsoft Azure OpenAI to Cognigy.AI, follow these steps:

  1. Open the Cognigy.AI interface.
  2. Go to Build > LLM.
  3. Click +New LLM.
  4. In the New LLM window, select a model from the Model Type list.
  5. Add a unique name and description for your model.

  6. From the Provider list, select an LLM's provider:
    6.1 From the Model list, select a model presented in the list or add a custom model that is not listed. If you select Custom Model, configure the following fields:
    - Model Type — select Chat for models that support the Chat Completions API, Completion for the Completions API, or Embedding for the Embedding API. For more information, refer to the Azure OpenAI documentation.
    - Model Name — specify an ID of the model that you want to use as a custom. To find model IDs, refer to the Azure OpenAI documentation.
    6.2 Click Save.
    6.3 On the LLM Editor page, go to the Generative AI Connection field.
    6.4 On the right side of the field, click +.
    6.5 In the Connection name, enter a unique name for your connection.
    6.6 From the Connection Type list, select one of the following authorization methods:
    - API Key — add an Azure API Key. This value can be found in the Keys & Endpoint section when examining your resource from the Azure portal. You can use either KEY1 or KEY2.
    - OAuth2 — this method is experimental, hidden behind the FEATURE_ENABLE_OAUTH2_AZURE_CONNECTION_WHITELIST feature flag, and may encounter some issues. Add credentials for the OAuth 2.0 authorization code flow. OAuth 2.0 offers more control and security than API keys by allowing specific permissions, expiring tokens, and reducing exposure through short-lived tokens instead of constant client secret use. To use this type of connection, fill in the following fields:
        - Client ID — add the Application (client) ID assigned to your app, can be found in the in Azure AI app registration overview.
        - Client Secret — add the application secret created in the Certificates & secrets section of the Azure AI app registration portal.
        - OAuth URL — add the URL to retrieve the access token. The URL should be in the https://<your-domain>.com/as/token.oauth2 format.
        - Scope — add a list of scopes for user permissions, for example, urn:grp:chatgpt.
    6.7 Click Create.
    6.8 Fill in the remaining fields:
    - Resource Name — add a resource name. To find this value, go to the Microsoft Azure home page. Under Azure services, click Azure OpenAI. In the left-side menu, under the Azure AI Services section, select Azure Open AI. Copy the desired resource name from the Name column.
    - Deployment Name — add a deployment name. To find this value, go to the Microsoft Azure home page. Under Azure services, click Azure OpenAI. In the left-side menu, under the Azure AI Services section, select Azure Open AI. Select a resource from the Name column. On the resource page, go to Resource Management > Model deployments. On the Model deployments page, click Manage Deployments. On the Deployments page, copy the desired deployment name from the Deployment name column.
    - Api Version — add an API version. The API version to use for this operation in the YYYY-MM-DD format. Note that the version may have an extended format, for example, YYYY-MM-DD-preview.
    - Custom URL — this parameter is optional. To control the connection between your clusters and the Azure OpenAI provider, you can route connections through dedicated proxy servers, creating an additional layer of security. To do this, specify the URL in the following pattern:https://<resource-name>.openai.azure.com/openai/deployments/<deployment-name>/<model-type>?api-version=<api-verson>. When a Custom URL is added, the Resource Name, Deployment Name, and API Version fields will be ignored.

  7. To apply changes, click Save.

  8. To check if the connection was set up, click Test.

When the model is added, you will see it in the list of models.

To apply this model for Cognigy.AI features, go to the settings by clicking Manage LLM Features.

Deprecation of Old Connections for Microsoft Azure OpenAI

In recent releases, we have updated the connection settings to Microsoft Azure OpenAI models.

If you have old connections (for example, created in the 4.53 release) to Azure OpenAI, these connections have an AzureOpenAIProvider type and are marked with a Deprecated label. Although these connections can still be active, we strongly recommend creating a model with the new AzureOpenAIProviderV2 type, as old connection types will no longer be available in the future.

Note that for some Microsoft Azure OpenAI models, such as text-embedding-ada-002 for knowledge search features, you might encounter the following error when an LLM is triggered: Error while performing knowledge search. Remote returned error: Search failed: Could not fetch embeddings due to missing API resource name for Azure OpenAI. To resolve the issue, recreate the model and the connection so that both are updated to the latest format.

Apply the Model

To apply a model, follow these steps:

  1. Open the Cognigy.AI interface.
  2. In the left-side menu, click Manage > Settings.
  3. Go to the section based on your use case for using a model:
    • Generative AI Settings. In the Generative AI Settings section, activate Enable Generative AI Features. This setting is toggled on by default if you have previously set up the Generative AI credentials.
    • Knowledge AI Settings. Use this section if you need to add a model for Knowledge AI. Select a model for the Knowledge Search and Answer Extraction features. Refer to the list of standard models and find the models that support these features.
  4. Navigate to the desired feature and select a model from the list. If there are no models available for the selected feature, the system will automatically select None.
  5. Click Save.

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