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This blog post is co-authored by our great contributor Thomas Vitale.
OpenAI provides specialized models for speech-to-text and text-to-speech conversion, recognized for their performance and cost-efficiency. Spring AI integrates these capabilities via Voice-to-Text and Text-to-Speech (TTS).
The new Audio Generation feature (gpt-4o-audio-preview) goes further, enabling mixed input and output modalities. Audio inputs can contain richer data than text alone. Audio can convey nuanced information like tone and inflection, and together with the audio outputs it enables asynchronous speech-to-speech interactions. Additionally, this new multimodality opens up possibilities for innovative applications, such as structured data extraction. Developers can extract structured information not just from simple text, but also from images and audio, building complex, structured objects seamlessly.

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Spring AI Audio Integrations

The Spring AI Multimodality Message API simplifies the integration of multimodal capabilities with various AI models. Now it fully supports OpenAI’s Audio Input and Audio Output modalities, thanks in large part to community member Thomas Vitale, who contributed to this feature’s development.

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Setup

Follow the Spring AI-OpenAI integration documentation to prepare your environment.

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Audio Input

OpenAI’s User Message API accepts base64-encoded audio files within messages using the Media type. Supported formats include audio/mp3 and audio/wav. Example: Adding audio to an input prompt: 
// Prepare the audio resource
var audioResource = new ClassPathResource("speech1.mp3");

// Create a user message with audio and send it to the chat model
String response = chatClient.prompt()
        .user(u -> u.text("What is this recording about?")
                    .media(MimeTypeUtils.parseMimeType("audio/mp3"), audioResource))                    
        .options(OpenAiChatOptions.builder()
            .withModel(OpenAiApi.ChatModel.GPT_4_O_AUDIO_PREVIEW).build())
        .call()
        .content();

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Audio Output Generation

The OpenAI Assistant Message API can return base64-encoded audio files using the Media type. Example: Generating audio output: 
// Generate an audio response
ChatResponse response = chatClient
    .prompt("Tell me a joke about the Spring Framework")
    .options(OpenAiChatOptions.builder()
        .withModel(OpenAiApi.ChatModel.GPT_4_O_AUDIO_PREVIEW)
        .withOutputModalities(List.of("text", "audio"))
        .withOutputAudio(new AudioParameters(Voice.ALLOY, AudioResponseFormat.WAV))
        .build())
    .call()
    .chatResponse();

// Access the audio transcript
String audioTranscript = response.getResult().getOutput().getContent();

// Retrieve the generated audio
byte[] generatedAudio = response.getResult().getOutput().getMedia().get(0).getDataAsByteArray();
To generate audio output, specify the audio modality in OpenAiChatOptions. Use the AudioParameters class to customize the voice and the audio format.

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Voice ChatBot Demo

This example demonstrates building an interactive chatbot using Spring AI that supports input and output audio. It shows how AI can enhance user interaction with natural-sounding audio responses.

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Setup

Add the Spring AI OpenAI starter: 
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
Configure the API key, model name, and output audio modality in application.properties: 
spring.main.web-application-type=none

spring.ai.openai.api-key=${OPENAI_API_KEY}
spring.ai.openai.chat.options.model=gpt-4o-audio-preview

spring.ai.openai.chat.options.output-modalities=text,audio
spring.ai.openai.chat.options.output-audio.voice=ALLOY
spring.ai.openai.chat.options.output-audio.format=WAV

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Implementation

The Java implementation of the voice chatbot, detailed below, creates a conversational AI assistant using audio input and output. It leverages Spring AI’s integration with OpenAI models to enable seamless interactions with users. VoiceAssistantApplication
  • VoiceAssistantApplication serves as the main application.
  • The CommandLineRunner bean initializes the chatbot:
    • The ChatClient is configured using the systemPrompt for contextual understanding and an in-memory chat memory for conversation history.
    • The Audio utility is used to record voice input from the user and play back audio responses generated by the AI.
  • Chat Loop: Inside the loop:
    • Voice Recording: The audio.startRecording() and audio.stopRecording() methods handle the recording process, pausing for user input.
    • Processing AI Response: The user message is sent to the AI model via chatClient.prompt(). The audio data is encapsulated in the Media object.
    • Response Handling: The AI-generated response is retrieved as text and played back as audio using the Audio.play() method.
Refer to the following code snippet for the implementation: 
@Bean
public CommandLineRunner chatBot(ChatClient.Builder chatClientBuilder,
        @Value("${chatbot.prompt:classpath:/marvin.paranoid.android.txt}") Resource systemPrompt) {
    return args -> {

        var chatClient = chatClientBuilder.defaultSystem(systemPrompt)
            .defaultAdvisors(new MessageChatMemoryAdvisor(new InMemoryChatMemory()))
            .build();

        try (Scanner scanner = new Scanner(System.in)) {

            Audio audio = new Audio();

            while (true) {                    
                audio.startRecording();
                System.out.print("Recording your question ... press <Enter> to stop! ");
                scanner.nextLine();
                audio.stopRecording();

                System.out.print("PROCESSING ... ");

                AssistantMessage response = chatClient.prompt()
                    .messages(new UserMessage("Please answer the questions in the audio input",
                            new Media(MediaType.parseMediaType("audio/wav"),
                                    new ByteArrayResource(audio.getLastRecording()))))
                    .call()
                    .chatResponse()
                    .getResult()
                    .getOutput();

                System.out.println("ASSISTANT: " + response.getContent());
                Audio.play(response.getMedia().get(0).getDataAsByteArray());
            }
        }
    };
}
The Audio utility, for capturing and playing back audio, is a single class leveraging the plain Java Sound API. 
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2024-12-01T11:00:11.274+01:00  INFO 31297 --- [voice-assistant-chatbot] [           main] s.a.d.a.m.VoiceAssistantApplication      : Started VoiceAssistantApplication in 0.827 seconds (process running for 1.054)

Recording your question ... press <Enter> to stop!
The complete demo is available on GitHub: voice-assistant-chatbot

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Important Considerations

  • One hour of audio input is roughly equivalent to 128k tokens.
  • The model currently supports modalities = ["text", "audio"].
  • Future updates may offer more flexible modality controls.

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Conclusion

The gpt-4o-audio-preview model unlocks new possibilities for dynamic audio interactions, enabling developers to build rich, AI-powered audio applications. Disclaimer: API capabilities and features may evolve. Refer to the latest OpenAI and Spring AI documentation for updates.