Configuration options for the Live API


Even with the basic implementation for the Live API, you can build engaging and powerful interactions for your users. You can optionally customize the experience even more by using the following configuration options:


Response voice and language

You can make the model respond in a specific voice and influence the model to respond in different languages.

Specify a response voice

Click your Gemini API provider to view provider-specific content and code on this page.

The Live API uses Chirp 3 to support synthesized speech responses in HD voices.

If you don't specify a response voice, the default is Puck.

To specify a response voice, set the voice name within the speechConfig object as part of the model configuration.

Swift 


// ...

let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
  // Configure the model to use a specific voice for its audio response
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio],
    speech: SpeechConfig(voiceName: "VOICE_NAME")
  )
)

// ...

Kotlin 


// ...

val model = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to use a specific voice for its audio response
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
        speechConfig = SpeechConfig(voice = Voice("VOICE_NAME"))
    }
)

// ...

Java 


// ...

LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
    "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to use a specific voice for its audio response
    new LiveGenerationConfig.Builder()
        .setResponseModality(ResponseModality.AUDIO)
        .setSpeechConfig(new SpeechConfig(new Voice("VOICE_NAME")))
        .build()
);

// ...

Web 


// ...

const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

const liveModel = getLiveGenerativeModel(ai, {
  model: "gemini-2.5-flash-native-audio-preview-09-2025",
  // Configure the model to use a specific voice for its audio response
  generationConfig: {
    responseModalities: [ResponseModality.AUDIO],
    speechConfig: {
      voiceConfig: {
        prebuiltVoiceConfig: { voiceName: "VOICE_NAME" },
      },
    },
  },
});

// ...

Dart 


// ...

final _liveModel = FirebaseAI.googleAI().liveGenerativeModel(
  model: 'gemini-2.5-flash-native-audio-preview-09-2025',
  // Configure the model to use a specific voice for its audio response
  liveGenerationConfig: LiveGenerationConfig(
    responseModalities: [ResponseModalities.audio],
    speechConfig: SpeechConfig(voiceName: 'VOICE_NAME'),
  ),
);

// ...

Unity 


// ...

var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
    modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to use a specific voice for its audio response
    liveGenerationConfig: new LiveGenerationConfig(
        responseModalities: new[] { ResponseModality.Audio },
        speechConfig: SpeechConfig.UsePrebuiltVoice("VOICE_NAME")
    )
);

// ...

Influence the response language

The Live API models automatically choose the appropriate language for their responses.

If you want the model to respond in a non-English language or always in a specific language, you can use influence the model's responses by using system instructions like these examples:

  • Reinforce to the model that a non-English language may be appropriate

    Listen to the speaker carefully. If you detect a non-English language, respond
in the language you hear from the speaker. You must respond unmistakably in the
speaker's language.

  • Tell the model to always respond in a specific language

    RESPOND IN LANGUAGE. YOU MUST RESPOND UNMISTAKABLY IN LANGUAGE.


Transcriptions for audio input and output

Click your Gemini API provider to view provider-specific content and code on this page.

As part of the model's response, you can receive transcriptions of the audio input and the model's audio response. You set this configuration as part of the model configuration.

  • For transcription of the audio input, add inputAudioTranscription.

  • For transcription of the model's audio response, add outputAudioTranscription.

Note the following:

  • You can configure the model to return transcriptions of both input and output (as shown in the following example), or you can configure it to return only one or the other.

  • The transcripts are streamed along with the audio, so it's best to collect them like you do text parts with each turn.

  • The transcription language is inferred from the audio input and the model's audio response.

Swift 


// ...

let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
  // Configure the model to return transcriptions of the audio input and output
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio],
    inputAudioTranscription: AudioTranscriptionConfig(),
    outputAudioTranscription: AudioTranscriptionConfig()
  )
)

var inputTranscript: String = ""
var outputTranscript: String = ""

do {
  let session = try await liveModel.connect()
  for try await response in session.responses {
    if case let .content(content) = response.payload {
      if let inputText = content.inputAudioTranscription?.text {
        // Handle transcription text of the audio input
        inputTranscript += inputText
      }

      if let outputText = content.outputAudioTranscription?.text {
        // Handle transcription text of the audio output
        outputTranscript += outputText
      }

      if content.isTurnComplete {
        // Log the transcripts after the current turn is complete
        print("Input audio: \(inputTranscript)")
        print("Output audio: \(outputTranscript)")

        // Reset the transcripts for the next turn
        inputTranscript = ""
        outputTranscript = ""
      }
    }
  }


} catch {
  // Handle error
}

// ...

Kotlin 


// ...

val liveModel = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to return transcriptions of the audio input and output
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
        inputAudioTranscription = AudioTranscriptionConfig()
        outputAudioTranscription = AudioTranscriptionConfig()
   }
)

val liveSession = liveModel.connect()

fun handleTranscription(input: Transcription?, output: Transcription?) {
    input?.text?.let { text ->
        // Handle transcription text of the audio input
        println("Input Transcription: $text")
    }
    output?.text?.let { text ->
        // Handle transcription text of the audio output
        println("Output Transcription: $text")
    }
}

liveSession.startAudioConversation(null, ::handleTranscription)

// ...

Java 


// ...

ExecutorService executor = Executors.newFixedThreadPool(1);

LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
    "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to return transcriptions of the audio input and output
    new LiveGenerationConfig.Builder()
            .setResponseModality(ResponseModality.AUDIO)
            .setInputAudioTranscription(new AudioTranscriptionConfig())
            .setOutputAudioTranscription(new AudioTranscriptionConfig())
            .build()
    );

LiveModelFutures liveModel = LiveModelFutures.from(lm);
ListenableFuture sessionFuture = liveModel.connect();

Futures.addCallback(sessionFuture, new FutureCallback() {
    @Override
    public void onSuccess(LiveSessionFutures ses) {
        LiveSessionFutures session = ses;
        session.startAudioConversation((Transcription input, Transcription output) -> {
            if (input != null) {
                // Handle transcription text of the audio input
                System.out.println("Input Transcription: " + input.getText());
            }
            if (output != null) {
                // Handle transcription text of the audio output
                System.out.println("Output Transcription: " + output.getText());
            }
            return null;
        });
    }

    @Override
    public void onFailure(Throwable t) {
        // Handle exceptions
        t.printStackTrace();
    }
}, executor);

// ...

Web 


// ...

const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

const liveModel = getLiveGenerativeModel(ai, {
  model: 'gemini-2.5-flash-native-audio-preview-09-2025',
  // Configure the model to return transcriptions of the audio input and output
  generationConfig: {
    responseModalities: [ResponseModality.AUDIO],
    inputAudioTranscription: {},
    outputAudioTranscription: {},
  },
});

const liveSession = await liveModel.connect();

liveSession.sendAudioRealtime({ data, mimeType: "audio/pcm" });

const messages = liveSession.receive();
for await (const message of messages) {
  switch (message.type) {
    case 'serverContent':
      if (message.inputTranscription) {
        // Handle transcription text of the audio input
        console.log(`Input transcription: ${message.inputTranscription.text}`);
      }
      if (message.outputTranscription) {
        // Handle transcription text of the audio output
        console.log(`Output transcription: ${message.outputTranscription.text}`);
      } else {
      	 // Handle other message types (modelTurn, turnComplete, interruption)
      }
    default:
      // Handle other message types (toolCall, toolCallCancellation)
  }
}

// ...

Dart 


// ...

final _liveModel = FirebaseAI.googleAI().liveGenerativeModel(
  model: 'gemini-2.5-flash-native-audio-preview-09-2025',
  // Configure the model to return transcriptions of the audio input and output
  liveGenerationConfig: LiveGenerationConfig(
    responseModalities: [ResponseModalities.audio],
    inputAudioTranscription: AudioTranscriptionConfig(),
    outputAudioTranscription: AudioTranscriptionConfig(),
  ),
);

final LiveSession _session = _liveModel.connect();

await for (final response in _session.receive()) {
  LiveServerContent message = response.message;
  if (message.inputTranscription?.text case final inputText?) {
    // Handle transcription text of the audio input
    print('Input: $inputText');
  }

  if (message.outputTranscription?.text case final outputText?) {
    // Handle transcription text of the audio output
    print('Output: $outputText');
  }
}

// ...

Unity 


// ...

var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
    modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to return transcriptions of the audio input and output
    liveGenerationConfig: new LiveGenerationConfig(
        responseModalities: new[] { ResponseModality.Audio },
        inputAudioTranscription: new AudioTranscriptionConfig(),
        outputAudioTranscription: new AudioTranscriptionConfig()
    )
);

try
{
    var session = await liveModel.ConnectAsync();
    var stream = session.ReceiveAsync();
    await foreach (var response in stream) {
        if (response.Message is LiveSessionContent sessionContent) {
            if (!string.IsNullOrEmpty(sessionContent.InputTranscription?.Text)) {
              // handle transcription text of input audio
            }

            if (!string.IsNullOrEmpty(sessionContent.OutputTranscription?.Text)) {
              // handle transcription text of output audio
            }
        }
    }
}
catch (Exception e)
{
    // Handle error
}

// ...


Voice activity detection (VAD)

The model automatically performs voice activity detection (VAD) on a continuous audio input stream. VAD is enabled by default.


Session management

  • Learn about the following sessions-related topics:

  • Firebase AI Logic does not yet support the following features for session management. Check back soon!

    • Handling interruptions
    • Extending session length
    • Resuming a session
    • Maintaining context across sessions and requests
    • Compressing the context window