---
title: 'AzureOpenAIEmbed'
description: 'The AzureOpenAIEmbed connector is designed to generate embeddings for text data using Azure OpenAI’s models, providing a bridge between Neum AI documents and OpenAI’s powerful embedding capabilities.'
---

The `AzureOpenAIEmbed` class serves as an interface to Azure's OpenAI embedding services. It is designed to create embeddings for textual data, which is essential for various machine learning tasks.

## Properties

Required properties:
- `deployment_name`: The specific deployment of the OpenAI model to be used.
- `api_key`: The API key for authentication with Azure OpenAI services.
- `endpoint`: The endpoint URL for the Azure OpenAI API.

<CodeGroup>
```python Local Development
from neumai.EmbedConnectors import AzureOpenAIEmbed

azure_openai_embed = AzureOpenAIEmbed(
    deployment_name = "<Insert AZURE OPEN AI DEPLOYMENT NAME>",
    api_key = "<Insert Azure OPEN AI API Key>",
    endpoint = "<Insert AZURE OPEN AI ENDPOINT>"
)

```

```json Cloud
{
    # Add source connectors
    "embed": {
        "embed_name":"AzureOpenAIEmbed",
        "embed_information":{
            "deployment_name": "<Insert AZURE OPEN AI DEPLOYMENT NAME>",
            "api_key": "<Insert Azure OPEN AI API Key>",
            "endpoint": "<Insert AZURE OPEN AI ENDPOINT>"
        }
    }
    # Add sink connector
}
```
</CodeGroup>