Class AzureOpenAiEmbeddingModel

java.lang.Object
dev.langchain4j.model.embedding.DimensionAwareEmbeddingModel
dev.langchain4j.model.azure.AzureOpenAiEmbeddingModel
All Implemented Interfaces:
dev.langchain4j.model.embedding.EmbeddingModel
public class AzureOpenAiEmbeddingModel extends dev.langchain4j.model.embedding.DimensionAwareEmbeddingModel
Represents an OpenAI embedding model, hosted on Azure, such as text-embedding-ada-002.

Mandatory parameters for initialization are: endpoint and apikey (or an alternate authentication method, see below for more information). Optionally you can set serviceVersion (if not, the latest version is used) and deploymentName (if not, a default name is used). You can also provide your own OpenAIClient instance, if you need more flexibility.

There are 3 authentication methods:

1. Azure OpenAI API Key Authentication: this is the most common method, using an Azure OpenAI API key. You need to provide the OpenAI API Key as a parameter, using the apiKey() method in the Builder, or the apiKey parameter in the constructor: For example, you would use `builder.apiKey("{key}")`.

2. non-Azure OpenAI API Key Authentication: this method allows to use the OpenAI service, instead of Azure OpenAI. You can use the nonAzureApiKey() method in the Builder, which will also automatically set the endpoint to "https://api.openai.com/v1". For example, you would use `builder.nonAzureApiKey("{key}")`. The constructor requires a KeyCredential instance, which can be created using `new AzureKeyCredential("{key}")`, and doesn't set up the endpoint.

3. Azure OpenAI client with Microsoft Entra ID (formerly Azure Active Directory) credentials. - This requires to add the `com.azure:azure-identity` dependency to your project. - You need to provide a TokenCredential instance, using the tokenCredential() method in the Builder, or the tokenCredential parameter in the constructor. As an example, DefaultAzureCredential can be used to authenticate the client: Set the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET. Then, provide the DefaultAzureCredential instance to the builder: `builder.tokenCredential(new DefaultAzureCredentialBuilder().build())`.

  • Constructor Details

  • Method Details

    • embedAll

      public dev.langchain4j.model.output.Response<List<dev.langchain4j.data.embedding.Embedding>> embedAll(List<dev.langchain4j.data.segment.TextSegment> textSegments)
      Embeds the provided text segments, processing a maximum of 16 segments at a time. For more information, refer to the documentation here.
      Parameters:
      textSegments - A list of text segments.
      Returns:
      A list of corresponding embeddings.

    • builder

      public static AzureOpenAiEmbeddingModel.Builder builder()

    • knownDimension

      protected Integer knownDimension()
      Overrides:
      knownDimension in class dev.langchain4j.model.embedding.DimensionAwareEmbeddingModel