> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/guardrails/llms.txt.
> For full documentation content, see https://docs.nvidia.com/nemo/guardrails/llms-full.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/guardrails/_mcp/server.

# nemoguardrails.embeddings.providers.azureopenai

## Module Contents

### Classes

| Name                                                                                          | Description                         |
| --------------------------------------------------------------------------------------------- | ----------------------------------- |
| [`AzureEmbeddingModel`](#nemoguardrails-embeddings-providers-azureopenai-AzureEmbeddingModel) | Embedding model using Azure OpenAI. |

### Functions

| Name                                                                            | Description |
| ------------------------------------------------------------------------------- | ----------- |
| [`get_executor`](#nemoguardrails-embeddings-providers-azureopenai-get_executor) | -           |

### API

```python
class nemoguardrails.embeddings.providers.azureopenai.AzureEmbeddingModel(
    embedding_model: str
)
```

**Bases:** [EmbeddingModel](/guardrails-python-sdk/nemoguardrails/embeddings/providers/base#nemoguardrails-embeddings-providers-base-EmbeddingModel)

Embedding model using Azure OpenAI.

This class represents an embedding model that utilizes the Azure OpenAI API
for generating text embeddings.

**Parameters:**

The name of the Azure OpenAI deployment model (e.g., "text-embedding-ada-002").

```python
nemoguardrails.embeddings.providers.azureopenai.AzureEmbeddingModel._get_embedding_dimension()
```

Retrieve the embedding dimension for the specified model.

```python
nemoguardrails.embeddings.providers.azureopenai.AzureEmbeddingModel.encode(
    documents: typing.List[str]
) -> typing.List[typing.List[float]]
```

Encode a list of documents into their corresponding embeddings.

**Parameters:**

The list of documents to be encoded.

**Returns:** `List[List[float]]`

List\[List\[float]]: The list of embeddings, where each embedding is a list of floats.

**Raises:**

* `RuntimeError`: If the API call fails.

```python
nemoguardrails.embeddings.providers.azureopenai.AzureEmbeddingModel.encode_async(
    documents: typing.List[str]
) -> typing.List[typing.List[float]]
```

async

Asynchronously encode a list of documents into their corresponding embeddings.

**Parameters:**

The list of documents to be encoded.

**Returns:** `List[List[float]]`

List\[List\[float]]: The list of embeddings, where each embedding is a list of floats.

```python
nemoguardrails.embeddings.providers.azureopenai.get_executor()
```