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Documentation Index

Fetch the complete documentation index at: https://docs.pipeshub.com/llms.txt

Use this file to discover all available pages before exploring further.

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Azure OpenAI Embeddings Configuration

Azure OpenAI Embeddings Configuration Interface The Azure OpenAI embeddings configuration screen in PipesHub where you’ll enter your Endpoint URL, API Key, Deployment Name, and Model Name PipesHub allows you to integrate with Azure OpenAI’s embedding models to enable vector search, semantic similarity, and document retrieval in your workspace, with enterprise-grade security and Azure compliance.

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Required Fields

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Endpoint URL *

The Endpoint URL connects PipesHub to your specific Azure OpenAI resource. How to obtain your Endpoint URL:
  1. Log in to the Azure Portal
  2. Navigate to your Azure OpenAI resource
  3. Go to “Keys and Endpoint” under Resource Management
  4. Copy the Endpoint URL (format: https://your-resource-name.openai.azure.com/)
Note: The endpoint is specific to your Azure deployment region and resource name.

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API Key *

The API Key authenticates your requests to your Azure OpenAI resource. How to obtain an API Key:
  1. In the Azure Portal, go to your Azure OpenAI resource
  2. Navigate to “Keys and Endpoint” under Resource Management
  3. Copy either Key 1 or Key 2 (both will work)
Security Note: Your API key should be kept secure and never shared publicly. PipesHub securely stores your API key and uses it only for authenticating requests to Azure OpenAI.

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Deployment Name *

The Deployment Name is the name you assigned when you deployed the embedding model inside your Azure OpenAI resource. How to find your Deployment Name:
  1. In the Azure Portal, navigate to your Azure OpenAI resource
  2. Select “Model deployments” from the left navigation
  3. Find the embedding deployment you want to use and copy the “Deployment name”
Note: This is the name you gave to the deployment, not the underlying model ID (e.g. you may have named it “my-embeddings” when deploying text-embedding-3-small).

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Model Name *

The Model Name field specifies the underlying embedding model that was deployed. Available Azure OpenAI embedding models:
  • text-embedding-3-small - Cost-effective model with excellent performance for most use cases
Note: Availability depends on which models you have deployed in your Azure OpenAI resource.

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Configuration Steps

As shown in the image above:
  1. Click Configure on the Azure OpenAI provider card
  2. Enter your Azure OpenAI Endpoint URL in the designated field (marked with *)
  3. Enter your Azure OpenAI API Key (marked with *)
  4. Specify your Deployment Name from your Azure OpenAI resource (marked with *)
  5. Specify your Model Name (marked with *)
  6. Click Add Model to save and validate your credentials
Endpoint URL, API Key, Deployment Name, and Model Name are all required fields to successfully configure Azure OpenAI embedding integration.

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Usage Considerations

  • API usage will count against your Azure OpenAI resource’s quota and billing
  • Different models have different pricing — check the Azure OpenAI pricing page for details
  • Azure OpenAI provides additional security, compliance, and data residency options compared to the standard OpenAI API

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Troubleshooting

  • If you encounter authentication errors, verify your API key and endpoint URL are correct
  • Ensure the embedding model is properly deployed in your Azure OpenAI resource
  • Verify the Deployment Name matches exactly as shown in your Azure deployment list
  • Check that your Azure subscription is active and has sufficient quota
  • Ensure your IP address is allowed if you have configured network access restrictions
For additional support, refer to the Azure OpenAI documentation or contact PipesHub support.