লাইভ এপিআই এর ক্ষমতা

import FirebaseAILogic

// Initialize the Gemini Developer API backend service
// Create a `liveModel` instance with a model that supports the Live API
let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
  // Configure the model to respond with audio
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio]
  )
)

do {
  let session = try await liveModel.connect()

  // Load the audio file, or tap a microphone
  guard let audioFile = NSDataAsset(name: "audio.pcm") else {
    fatalError("Failed to load audio file")
  }

  // Provide the audio data
  await session.sendAudioRealtime(audioFile.data)

  var outputText = ""
  for try await message in session.responses {
    if case let .content(content) = message.payload {
      content.modelTurn?.parts.forEach { part in
        if let part = part as? InlineDataPart, part.mimeType.starts(with: "audio/pcm") {
          // Handle 16bit pcm audio data at 24khz
          playAudio(part.data)
        }
      }
      // Optional: if you don't require to send more requests.
      if content.isTurnComplete {
        await session.close()
      }
    }
  }
} catch {
  fatalError(error.localizedDescription)
}

// Initialize the Gemini Developer API backend service
// Create a `liveModel` instance with a model that supports the Live API
val liveModel = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to respond with audio
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
   }
)

val session = liveModel.connect()

// This is the recommended approach.
// However, you can create your own recorder and handle the stream.
session.startAudioConversation()

ExecutorService executor = Executors.newFixedThreadPool(1);
// Initialize the Gemini Developer API backend service
// Create a `liveModel` instance with a model that supports the Live API
LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
        "gemini-2.5-flash-native-audio-preview-09-2025",
        // Configure the model to respond with audio
        new LiveGenerationConfig.Builder()
                .setResponseModality(ResponseModality.AUDIO)
                .build()
);
LiveModelFutures liveModel = LiveModelFutures.from(lm);

ListenableFuture<LiveSession> sessionFuture =  liveModel.connect();

Futures.addCallback(sessionFuture, new FutureCallback<LiveSession>() {
    @Override
    public void onSuccess(LiveSession ses) {
	 LiveSessionFutures session = LiveSessionFutures.from(ses);
        session.startAudioConversation();
    }
    @Override
    public void onFailure(Throwable t) {
        // Handle exceptions
    }
}, executor);

import { initializeApp } from "firebase/app";
import { getAI, getLiveGenerativeModel, GoogleAIBackend, ResponseModality } from "firebase/ai";

// TODO(developer) Replace the following with your app's Firebase configuration
// See: https://firebase.google.com/docs/web/learn-more#config-object
const firebaseConfig = {
  // ...
};

// Initialize FirebaseApp
const firebaseApp = initializeApp(firebaseConfig);

// Initialize the Gemini Developer API backend service
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

// Create a `LiveGenerativeModel` instance with a model that supports the Live API
const liveModel = getLiveGenerativeModel(ai, {
  model: "gemini-2.5-flash-native-audio-preview-09-2025",
  // Configure the model to respond with audio
  generationConfig: {
    responseModalities: [ResponseModality.AUDIO],
  },
});

const session = await liveModel.connect();

// Start the audio conversation
const audioConversationController = await startAudioConversation(session);

// ... Later, to stop the audio conversation
// await audioConversationController.stop()

import 'package:firebase_ai/firebase_ai.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';
import 'package:your_audio_recorder_package/your_audio_recorder_package.dart';

late LiveModelSession _session;
final _audioRecorder = YourAudioRecorder();

await Firebase.initializeApp(
  options: DefaultFirebaseOptions.currentPlatform,
);

// Initialize the Gemini Developer API backend service
// Create a `liveGenerativeModel` instance with a model that supports the Live API
final liveModel = FirebaseAI.googleAI().liveGenerativeModel(
  model: 'gemini-2.5-flash-native-audio-preview-09-2025',
  // Configure the model to respond with audio
  liveGenerationConfig: LiveGenerationConfig(
    responseModalities: [ResponseModalities.audio],
  ),
);

_session = await liveModel.connect();

final audioRecordStream = _audioRecorder.startRecordingStream();
// Map the Uint8List stream to InlineDataPart stream
final mediaChunkStream = audioRecordStream.map((data) {
  return InlineDataPart('audio/pcm', data);
});
await _session.startMediaStream(mediaChunkStream);

// In a separate thread, receive the audio response from the model
await for (final message in _session.receive()) {
   // Process the received message
}

using Firebase;
using Firebase.AI;

async Task SendTextReceiveAudio() {
  // Initialize the Gemini Developer API backend service
  // Create a `LiveModel` instance with a model that supports the Live API
  var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
      modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
      // Configure the model to respond with audio
      liveGenerationConfig: new LiveGenerationConfig(
          responseModalities: new[] { ResponseModality.Audio })
    );

  LiveSession session = await liveModel.ConnectAsync();

  // Start a coroutine to send audio from the Microphone
  var recordingCoroutine = StartCoroutine(SendAudio(session));

  // Start receiving the response
  await ReceiveAudio(session);
}

IEnumerator SendAudio(LiveSession liveSession) {
  string microphoneDeviceName = null;
  int recordingFrequency = 16000;
  int recordingBufferSeconds = 2;

  var recordingClip = Microphone.Start(microphoneDeviceName, true,
                                       recordingBufferSeconds, recordingFrequency);

  int lastSamplePosition = 0;
  while (true) {
    if (!Microphone.IsRecording(microphoneDeviceName)) {
      yield break;
    }

    int currentSamplePosition = Microphone.GetPosition(microphoneDeviceName);

    if (currentSamplePosition != lastSamplePosition) {
      // The Microphone uses a circular buffer, so we need to check if the
      // current position wrapped around to the beginning, and handle it
      // accordingly.
      int sampleCount;
      if (currentSamplePosition > lastSamplePosition) {
        sampleCount = currentSamplePosition - lastSamplePosition;
      } else {
        sampleCount = recordingClip.samples - lastSamplePosition + currentSamplePosition;
      }

      if (sampleCount > 0) {
        // Get the audio chunk
        float[] samples = new float[sampleCount];
        recordingClip.GetData(samples, lastSamplePosition);

        // Send the data, discarding the resulting Task to avoid the warning
        _ = liveSession.SendAudioAsync(samples);

        lastSamplePosition = currentSamplePosition;
      }
    }

    // Wait for a short delay before reading the next sample from the Microphone
    const float MicrophoneReadDelay = 0.5f;
    yield return new WaitForSeconds(MicrophoneReadDelay);
  }
}

Queue audioBuffer = new();

async Task ReceiveAudio(LiveSession liveSession) {
  int sampleRate = 24000;
  int channelCount = 1;

  // Create a looping AudioClip to fill with the received audio data
  int bufferSamples = (int)(sampleRate * channelCount);
  AudioClip clip = AudioClip.Create("StreamingPCM", bufferSamples, channelCount,
                                    sampleRate, true, OnAudioRead);

  // Attach the clip to an AudioSource and start playing it
  AudioSource audioSource = GetComponent();
  audioSource.clip = clip;
  audioSource.loop = true;
  audioSource.Play();

  // Start receiving the response
  await foreach (var message in liveSession.ReceiveAsync()) {
    // Process the received message
    foreach (float[] pcmData in message.AudioAsFloat) {
      lock (audioBuffer) {
        foreach (float sample in pcmData) {
          audioBuffer.Enqueue(sample);
        }
      }
    }
  }
}

// This method is called by the AudioClip to load audio data.
private void OnAudioRead(float[] data) {
  int samplesToProvide = data.Length;
  int samplesProvided = 0;

  lock(audioBuffer) {
    while (samplesProvided < samplesToProvide && audioBuffer.Count > 0) {
      data[samplesProvided] = audioBuffer.Dequeue();
      samplesProvided++;
    }
  }

  while (samplesProvided < samplesToProvide) {
    data[samplesProvided] = 0.0f;
    samplesProvided++;
  }
}

import FirebaseAILogic

// Initialize the Gemini Developer API backend service
// Create a `liveModel` instance with a model that supports the Live API
let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
  // Configure the model to respond with audio
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio]
  )
)

do {
  let session = try await liveModel.connect()

  // Provide a text prompt
  let text = "tell a short story"

  await session.sendTextRealtime(text)

  var outputText = ""
  for try await message in session.responses {
    if case let .content(content) = message.payload {
      content.modelTurn?.parts.forEach { part in
        if let part = part as? InlineDataPart, part.mimeType.starts(with: "audio/pcm") {
          // Handle 16bit pcm audio data at 24khz
          playAudio(part.data)
        }
      }
      // Optional: if you don't require to send more requests.
      if content.isTurnComplete {
        await session.close()
      }
    }
  }
} catch {
  fatalError(error.localizedDescription)
}

// Initialize the Gemini Developer API backend service
// Create a `liveModel` instance with a model that supports the Live API
val liveModel = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to respond with audio
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
   }
)

val session = liveModel.connect()

// Provide a text prompt
val text = "tell a short story"

session.send(text)

session.receive().collect {
    if(it.turnComplete) {
        // Optional: if you don't require to send more requests.
        session.stopReceiving();
    }
    // Handle 16bit pcm audio data at 24khz
    playAudio(it.data)
}

ExecutorService executor = Executors.newFixedThreadPool(1);
// Initialize the Gemini Developer API backend service
// Create a `liveModel` instance with a model that supports the Live API
LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
        "gemini-2.5-flash-native-audio-preview-09-2025",
        // Configure the model to respond with text
        new LiveGenerationConfig.Builder()
                .setResponseModality(ResponseModality.AUDIO)
                .build()
);
LiveModelFutures model = LiveModelFutures.from(lm);
ListenableFuture<LiveSession> sessionFuture =  model.connect();
class LiveContentResponseSubscriber implements Subscriber<LiveContentResponse> {
    @Override
    public void onSubscribe(Subscription s) {
        s.request(Long.MAX_VALUE); // Request an unlimited number of items
    }
    @Override
    public void onNext(LiveContentResponse liveContentResponse) {
        // Handle 16bit pcm audio data at 24khz
	liveContentResponse.getData();
    }
    @Override
    public void onError(Throwable t) {
        System.err.println("Error: " + t.getMessage());
    }
    @Override
    public void onComplete() {
        System.out.println("Done receiving messages!");
    }
}
Futures.addCallback(sessionFuture, new FutureCallback<LiveSession>() {
    @Override
    public void onSuccess(LiveSession ses) {
	 LiveSessionFutures session = LiveSessionFutures.from(ses);
        // Provide a text prompt
        String text = "tell me a short story?";
        session.send(text);
        Publisher<LiveContentResponse> publisher = session.receive();
        publisher.subscribe(new LiveContentResponseSubscriber());
    }
    @Override
    public void onFailure(Throwable t) {
        // Handle exceptions
    }
}, executor);

import { initializeApp } from "firebase/app";
import { getAI, getLiveGenerativeModel, GoogleAIBackend, ResponseModality } from "firebase/ai";

// TODO(developer) Replace the following with your app's Firebase configuration
// See: https://firebase.google.com/docs/web/learn-more#config-object
const firebaseConfig = {
  // ...
};

// Initialize FirebaseApp
const firebaseApp = initializeApp(firebaseConfig);

// Initialize the Gemini Developer API backend service
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

// Create a `LiveGenerativeModel` instance with a model that supports the Live API
const liveModel = getLiveGenerativeModel(ai, {
  model: "gemini-2.5-flash-native-audio-preview-09-2025",
  // Configure the model to respond with audio
  generationConfig: {
    responseModalities: [ResponseModality.AUDIO],
  },
});

const session = await liveModel.connect();

// Provide a text prompt
const prompt = "tell a short story";
session.send(prompt);

// Handle the model's audio output
const messages = session.receive();
for await (const message of messages) {
  switch (message.type) {
    case "serverContent":
      if (message.turnComplete) {
        // TODO(developer): Handle turn completion
      } else if (message.interrupted) {
        // TODO(developer): Handle the interruption
        break;
      } else if (message.modelTurn) {
        const parts = message.modelTurn?.parts;
        parts?.forEach((part) => {
          if (part.inlineData) {
            // TODO(developer): Play the audio chunk
          }
        });
      }
      break;
    case "toolCall":
      // Ignore
    case "toolCallCancellation":
      // Ignore
  }
}

import 'package:firebase_ai/firebase_ai.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';
import 'dart:async';
import 'dart:typed_data';

late LiveModelSession _session;

Future<Stream<Uint8List>> textToAudio(String textPrompt) async {
  WidgetsFlutterBinding.ensureInitialized();

  await Firebase.initializeApp(
    options: DefaultFirebaseOptions.currentPlatform,
  );

  // Initialize the Gemini Developer API backend service
  // Create a `liveGenerativeModel` instance with a model that supports the Live API
  final liveModel = FirebaseAI.googleAI().liveGenerativeModel(
    model: 'gemini-2.5-flash-native-audio-preview-09-2025',
    // Configure the model to respond with audio
    liveGenerationConfig: LiveGenerationConfig(
      responseModalities: [ResponseModalities.audio],
    ),
  );

  _session = await liveModel.connect();

  final prompt = Content.text(textPrompt);

  await _session.send(input: prompt);

  return _session.receive().asyncMap((response) async {
    if (response is LiveServerContent && response.modelTurn?.parts != null) {
       for (final part in response.modelTurn!.parts) {
         if (part is InlineDataPart) {
           return part.bytes;
         }
       }
    }
    throw Exception('Audio data not found');
  });
}

Future<void> main() async {
  try {
    final audioStream = await textToAudio('Convert this text to audio.');

    await for (final audioData in audioStream) {
      // Process the audio data (e.g., play it using an audio player package)
      print('Received audio data: ${audioData.length} bytes');
      // Example using flutter_sound (replace with your chosen package):
      // await _flutterSoundPlayer.startPlayer(fromDataBuffer: audioData);
    }
  } catch (e) {
    print('Error: $e');
  }
}

using Firebase;
using Firebase.AI;

async Task SendTextReceiveAudio() {
  // Initialize the Gemini Developer API backend service
  // Create a `LiveModel` instance with a model that supports the Live API
  var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
    modelName: "gemini-2.5-flash-native-audio-preview-09-2025",
    // Configure the model to respond with audio
    liveGenerationConfig: new LiveGenerationConfig(
        responseModalities: new[] { ResponseModality.Audio })
  );

  LiveSession session = await liveModel.ConnectAsync();

  // Provide a text prompt
  var prompt = ModelContent.Text("Convert this text to audio.");
  await session.SendAsync(content: prompt, turnComplete: true);

  // Start receiving the response
  await ReceiveAudio(session);
}

Queue<float> audioBuffer = new();

async Task ReceiveAudio(LiveSession session) {
  int sampleRate = 24000;
  int channelCount = 1;

  // Create a looping AudioClip to fill with the received audio data
  int bufferSamples = (int)(sampleRate * channelCount);
  AudioClip clip = AudioClip.Create("StreamingPCM", bufferSamples, channelCount,
                                    sampleRate, true, OnAudioRead);

  // Attach the clip to an AudioSource and start playing it
  AudioSource audioSource = GetComponent<AudioSource>();
  audioSource.clip = clip;
  audioSource.loop = true;
  audioSource.Play();

  // Start receiving the response
  await foreach (var message in session.ReceiveAsync()) {
    // Process the received message
    foreach (float[] pcmData in message.AudioAsFloat) {
      lock (audioBuffer) {
        foreach (float sample in pcmData) {
          audioBuffer.Enqueue(sample);
        }
      }
    }
  }
}

// This method is called by the AudioClip to load audio data.
private void OnAudioRead(float[] data) {
  int samplesToProvide = data.Length;
  int samplesProvided = 0;

  lock(audioBuffer) {
    while (samplesProvided < samplesToProvide && audioBuffer.Count > 0) {
      data[samplesProvided] = audioBuffer.Dequeue();
      samplesProvided++;
    }
  }

  while (samplesProvided < samplesToProvide) {
    data[samplesProvided] = 0.0f;
    samplesProvided++;
  }
}

// Define initial turns (history/context).
let turns: [ModelContent] = [
  ModelContent(role: "user", parts: [TextPart("What is the capital of France?")]),
  ModelContent(role: "model", parts: [TextPart("Paris")]),
]

// Send history, keeping the conversational turn OPEN (false).
await session.sendContent(turns, turnComplete: false)

// Define the new user query.
let newTurn: [ModelContent] = [
  ModelContent(role: "user", parts: [TextPart("What is the capital of Germany?")]),
]

// Send the final query, CLOSING the turn (true) to trigger the model response.
await session.sendContent(newTurn, turnComplete: true)

Not yet supported for Android apps - check back soon!

Not yet supported for Android apps - check back soon!

const turns = [{ text: "Hello from the user!" }];

await session.send(
  turns,
  false // turnComplete: false
);

console.log("Sent history. Waiting for next input...");

// Define the new user query.
const newTurn [{ text: "And what is the capital of Germany?" }];

// Send the final query, CLOSING the turn (true) to trigger the model response.
await session.send(
    newTurn,
    true // turnComplete: true
);
console.log("Sent final query. Model response expected now.");

// Define initial turns (history/context).
final List turns = [
  Content(
    "user",
    [Part.text("What is the capital of France?")],
  ),
  Content(
    "model",
    [Part.text("Paris")],
  ),
];

// Send history, keeping the conversational turn OPEN (false).
await session.send(
  input: turns,
  turnComplete: false,
);

// Define the new user query.
final List newTurn = [
  Content(
    "user",
    [Part.text("What is the capital of Germany?")],
  ),
];

// Send the final query, CLOSING the turn (true) to trigger the model response.
await session.send(
  input: newTurn,
  turnComplete: true,
);

// Define initial turns (history/context).
List turns = new List {
    new ModelContent("user", new ModelContent.TextPart("What is the capital of France?") ),
    new ModelContent("model", new ModelContent.TextPart("Paris") ),
};

// Send history, keeping the conversational turn OPEN (false).
foreach (ModelContent turn in turns)
{
    await session.SendAsync(
        content: turn,
        turnComplete: false
    );
}

// Define the new user query.
ModelContent newTurn = ModelContent.Text("What is the capital of Germany?");

// Send the final query, CLOSING the turn (true) to trigger the model response.
await session.SendAsync(
    content: newTurn,
    turnComplete: true
);

await session.sendContent(
  [ModelContent(
    role: "system",
    parts: [TextPart("new system instruction")]
  )],
  turnComplete: false
)

Not yet supported for Android apps - check back soon!

Not yet supported for Android apps - check back soon!

Not yet supported for Web apps - check back soon!

try {
  await _session.send(
    input: Content(
      'system',
      [Part.text('new system instruction')],
    ),
    turnComplete: false,
  );
} catch (e) {
  print('Failed to update system instructions: $e');
}

try
{
    await session.SendAsync(
        content: new ModelContent(
            "system",
            new ModelContent.TextPart("new system instruction")
        ),
        turnComplete: false
    );
}
catch (Exception e)
{
    Debug.LogError($"Failed to update system instructions: {e.Message}");
}