This version is still in development and is not considered stable yet. For the latest snapshot version, please use Spring AI 1.0.0-SNAPSHOT!

Azure OpenAI Transcriptions

Spring AI supports Azure Whisper model.

Prerequisites

Obtain your Azure OpenAI endpoint and api-key from the Azure OpenAI Service section on the Azure Portal. Spring AI defines a configuration property named spring.ai.azure.openai.api-key that you should set to the value of the API Key obtained from Azure. There is also a configuration property named spring.ai.azure.openai.endpoint that you should set to the endpoint URL obtained when provisioning your model in Azure. Exporting an environment variable is one way to set that configuration property:

Auto-configuration

Spring AI provides Spring Boot auto-configuration for the Azure OpenAI Transcription Generation Client. To enable it, add the following dependency to your project’s Maven pom.xml file:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-azure-openai-spring-boot-starter</artifactId>
</dependency>

or to your Gradle build.gradle build file.

dependencies {
    implementation 'org.springframework.ai:spring-ai-azure-openai-spring-boot-starter'
}
Refer to the Dependency Management section to add the Spring AI BOM to your build file.

Transcription Properties

The prefix spring.ai.openai.audio.transcription is used as the property prefix that lets you configure the retry mechanism for the OpenAI image model.

Property Description Default

spring.ai.azure.openai.audio.transcription.enabled

Enable Azure OpenAI transcription model.

true

spring.ai.azure.openai.audio.transcription.options.model

ID of the model to use. Only whisper is currently available.

whisper

spring.ai.azure.openai.audio.transcription.options.deployment-name

The deployment name under which the model is deployed.

spring.ai.azure.openai.audio.transcription.options.response-format

The format of the transcript output, in one of these options: json, text, srt, verbose_json, or vtt.

json

spring.ai.azure.openai.audio.transcription.options.prompt

An optional text to guide the model’s style or continue a previous audio segment. The prompt should match the audio language.

spring.ai.azure.openai.audio.transcription.options.language

The language of the input audio. Supplying the input language in ISO-639-1 format will improve accuracy and latency.

spring.ai.azure.openai.audio.transcription.options.temperature

The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.

0

spring.ai.azure.openai.audio.transcription.options.timestamp-granularities

The timestamp granularities to populate for this transcription. response_format must be set verbose_json to use timestamp granularities. Either or both of these options are supported: word, or segment. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency.

segment

Runtime Options

The AzureOpenAiAudioTranscriptionOptions class provides the options to use when making a transcription. On start-up, the options specified by spring.ai.azure.openai.audio.transcription are used, but you can override these at runtime.

For example:

AzureOpenAiAudioTranscriptionOptions.TranscriptResponseFormat responseFormat = AzureOpenAiAudioTranscriptionOptions.TranscriptResponseFormat.VTT;

AzureOpenAiAudioTranscriptionOptions transcriptionOptions = AzureOpenAiAudioTranscriptionOptions.builder()
    .withLanguage("en")
    .withPrompt("Ask not this, but ask that")
    .withTemperature(0f)
    .withResponseFormat(this.responseFormat)
    .build();
AudioTranscriptionPrompt transcriptionRequest = new AudioTranscriptionPrompt(audioFile, this.transcriptionOptions);
AudioTranscriptionResponse response = azureOpenAiTranscriptionModel.call(this.transcriptionRequest);

Manual Configuration

Add the spring-ai-openai dependency to your project’s Maven pom.xml file:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-azure-openai</artifactId>
</dependency>

or to your Gradle build.gradle build file.

dependencies {
    implementation 'org.springframework.ai:spring-ai-azure-openai'
}
Refer to the Dependency Management section to add the Spring AI BOM to your build file.

Next, create a AzureOpenAiAudioTranscriptionModel

var openAIClient = new OpenAIClientBuilder()
    .credential(new AzureKeyCredential(System.getenv("AZURE_OPENAI_API_KEY")))
    .endpoint(System.getenv("AZURE_OPENAI_ENDPOINT"))
    .buildClient();

var azureOpenAiAudioTranscriptionModel = new AzureOpenAiAudioTranscriptionModel(this.openAIClient, null);

var transcriptionOptions = AzureOpenAiAudioTranscriptionOptions.builder()
    .withResponseFormat(TranscriptResponseFormat.TEXT)
    .withTemperature(0f)
    .build();

var audioFile = new FileSystemResource("/path/to/your/resource/speech/jfk.flac");

AudioTranscriptionPrompt transcriptionRequest = new AudioTranscriptionPrompt(this.audioFile, this.transcriptionOptions);
AudioTranscriptionResponse response = this.azureOpenAiAudioTranscriptionModel.call(this.transcriptionRequest);