Lyria 2

This documentation is valid for the following list of our models:

google/lyria2

An advanced audio generation model designed to create high-quality audio tracks from textual prompts.

How to Make a Call

Step-by-Step Instructions

1️ Setup You Can’t Skip

▪️ Create an Account: Visit the AI/ML API website and create an account (if you don’t have one yet). ▪️ Generate an API Key: After logging in, navigate to your account dashboard and generate your API key. Ensure that key is enabled on UI.

2️ Copy the code example

At the bottom of this page, you'll find a code example that shows how to structure the request. Choose the code snippet in your preferred programming language and copy it into your development environment.

Generating a music piece using this model involves sequentially calling two endpoints:

The first one is for creating and sending a music generation task to the server (returns a generation ID).
The second one is for requesting the generated piece from the server using the generation ID received from the first endpoint.

The code example combines both endpoint calls.

3️ Modify the code example

▪️ Replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key from your account. ▪️ Provide your instructions via the prompt parameter. The model will use them to generate a musical composition.

4️ ^_(Optional) Adjust other optional parameters if needed

Only prompt is a required parameter for this model (and we’ve already filled it in for you in the example), but you can include optional parameters if needed to adjust the model’s behavior. Below, you can find the corresponding API schema ("Generate a music sample"), which lists all available parameters along with notes on how to use them.

5️ Run your modified code

Run your modified code in your development environment. Response time depends on various factors, but for simple prompts it rarely exceeds 40 seconds.

If you need a more detailed walkthrough for setting up your development environment and making a request step by step — feel free to use our Quickstart guide.

API Schemas

Generate a music sample

This endpoint creates and sends a music generation task to the server — and returns a generation ID and the task status.

post

Authorizations

AuthorizationstringRequired

Bearer key

Body

modelundefined · enumRequiredPossible values:

promptstringRequired

The prompt to generate audio.

negative_promptstringOptional

A description of what to exclude from the generated audio

seedintegerOptional

A seed for deterministic generation. If provided, the model will attempt to produce the same audio given the same prompt and other parameters.

Responses

default

application/json

default

{
  "id": "text",
  "status": "queued"
}

Retrieve the generated music sample from the server

After sending a request for music generation, this task is added to the queue. Based on the service's load, the generation can be completed in 30-40 seconds or take a bit more.

get

Authorizations

AuthorizationstringRequired

Bearer key

Query parameters

generation_idstringRequired

Responses

default

application/json

default

{
  "audio_file": {
    "url": "https://example.com"
  },
  "id": "text",
  "status": "queued",
  "error": null
}

Quick Code Example

Here is an example of generation an audio file based on a prompt using the music model Lyria 2.

How it works

As an example, we will generate a song using the new Google's model Lyria 2. As you can verify in its API Schemas above, this model accepts a prompt as input—extracting information about its vocals and instruments for use in the generation process.

We generated our prompt in Chat GPT:

Majestic orchestral film score recorded in a top-tier London studio. A 100-piece orchestra delivers sweeping, cinematic music with rich emotional depth. The composition features soaring themes, dynamic contrasts, and complex harmonies. Expect powerful percussion, expressive strings, and prominent French horns and timpani. The arrangement emphasizes a dramatic narrative arc with intricate orchestrations and a profound, awe-inspiring atmosphere.

A notable feature of our audio and video models is that uploading the prompt or sample, generating the content, and retrieving the final file from the server are handled through separate API calls. (AIML API tokens are only consumed during the first step—i.e., the actual content generation.)

We’ve written a complete code example that sequentially calls both endpoints — you can view and copy it below. Don’t forget to replace <YOUR_AIMLAPI_KEY> with your actual AIML API Key from your account!

The structure of the code is simple: there are two separate functions for calling each endpoint, and a main function that orchestrates everything.

Execution starts automatically from main(). It first runs the function that creates and sends a music generation task to the server — this is where you pass your prompt describing the desired musical fragment. This function returns a generation ID and the initial task status:

Generation: {'id': 'ac94b938-a53a-483a-bef3-2bea9dd12bb8:lyria2', 'status': 'queued'}

This indicates that the file upload and our generation has been queued on the server (which took 4.5 seconds in our case).

Next, main() launches the second function — the one that checks the task status and, once ready, retrieves the download URL from the server. This second function is called in a loop every 10 seconds.

During execution, you’ll see messages in the output:

If the file is not yet ready:

Still waiting... Checking again in 10 seconds.

Once the file is ready, a completion message appears with the download info. In our case, after three reruns of the second code block (waiting a total of about 30-40 seconds), we saw the following output:

Generation complete:/n {'id': 'ac94b938-a53a-483a-bef3-2bea9dd12bb8:lyria2', 'status': 'completed', 'audio_file': {'url': 'https://cdn.aimlapi.com/eagle/files/lion/5N4F_QWb5K8rDSHfpUN0S_output.wav', 'content_type': 'audio/wav', 'file_name': 'output.wav', 'file_size': 6291544}}

As you can see, the 'status' is now 'completed', and further in the output line, we have a URL where the generated audio file can be downloaded.

Listen to the track we generated below the code and response blocks.

import time
import requests

# Insert your AI/ML API key instead of <YOUR_AIMLAPI_KEY>:
aimlapi_key = '<YOUR_AIMLAPI_KEY>'

# Creating and sending an audio generation task to the server (returns a generation ID)
def generate_audio():
    url = "https://api.aimlapi.com/v2/generate/audio"
    payload = {
        "model": "google/lyria2",
        "prompt": '''
        Majestic orchestral film score recorded in a top-tier London studio. A full-scale symphony orchestra delivers sweeping, cinematic music with rich emotional depth. The composition features soaring themes, dynamic contrasts, and complex harmonies. Expect powerful percussion, expressive strings, and prominent French horns and timpani. The arrangement emphasizes a dramatic narrative arc with intricate orchestrations and a profound, awe-inspiring atmosphere.
        '''
    }
    headers = {"Authorization": f"Bearer {aimlapi_key}", "Content-Type": "application/json"}

    response = requests.post(url, json=payload, headers=headers)

    if response.status_code >= 400:
        print(f"Error: {response.status_code} - {response.text}")
    else:
        response_data = response.json()
        print("Generation:", response_data)
        return response_data


# Requesting the result of the generation task from the server using the generation_id:
def retrieve_audio(gen_id):
    url = "https://api.aimlapi.com/v2/generate/audio"
    params = {
        "generation_id": gen_id,
    }
    headers = {"Authorization": f"Bearer {aimlapi_key}", "Content-Type": "application/json"}

    response = requests.get(url, params=params, headers=headers)
    return response.json()
    
    
# This is the main function of the program. From here, we sequentially call the audio generation and then repeatedly request the result from the server every 10 seconds:
def main():
    generation_response = generate_audio()
    gen_id = generation_response.get("id")
        
    if gen_id:
        start_time = time.time()

        timeout = 600
        while time.time() - start_time < timeout:
            response_data = retrieve_audio(gen_id)

            if response_data is None:
                print("Error: No response from API")
                break
        
            status = response_data.get("status")
            if status == "generating" or status == "queued" or status == "waiting":
                print("Still waiting... Checking again in 10 seconds.")
                time.sleep(10)
            else:
                print("Generation complete:/n", response_data)
                return response_data
   
        print("Timeout reached. Stopping.")
        return None    

if __name__ == "__main__":
    main()

// Insert your AI/ML API key instead of <YOUR_AIMLAPI_KEY>:
const API_KEY = '<YOUR_AIMLAPI_KEY>';

async function generateAudio() {
  const url = 'https://api.aimlapi.com/v2/generate/audio';
  const payload = {
    model: 'google/lyria2',
    prompt: `
Majestic orchestral film score recorded in a top-tier London studio. A full-scale symphony orchestra delivers sweeping, cinematic music with rich emotional depth. The composition features soaring themes, dynamic contrasts, and complex harmonies. Expect powerful percussion, expressive strings, and prominent French horns and timpani. The arrangement emphasizes a dramatic narrative arc with intricate orchestrations and a profound, awe-inspiring atmosphere.
`
  };

  const response = await fetch(url, {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify(payload)
  });

  if (!response.ok) {
    console.error(`Error: ${response.status} - ${await response.text()}`);
    return null;
  }

  const data = await response.json();
  console.log('Generation:', data);
  return data;
}

async function retrieveAudio(generationId) {
  const url = `https://api.aimlapi.com/v2/generate/audio?generation_id=${generationId}`;

  const response = await fetch(url, {
    method: 'GET',
    headers: {
      'Authorization': `Bearer ${API_KEY}`,
      'Content-Type': 'application/json'
    }
  });

  if (!response.ok) {
    console.error(`Error: ${response.status} - ${await response.text()}`);
    return null;
  }

  return await response.json();
}

async function main() {
  const generationResponse = await generateAudio();

  if (!generationResponse || !generationResponse.id) {
    console.error('No generation ID received.');
    return;
  }

  const genId = generationResponse.id;
  const timeout = 600000; // 10 minutes
  const interval = 10000; // 10 seconds
  const start = Date.now();

  const intervalId = setInterval(async () => {
    if (Date.now() - start > timeout) {
      console.log('Timeout reached. Stopping.');
      clearInterval(intervalId);
      return;
    }

    const result = await retrieveAudio(genId);

    if (!result) {
      console.error('No response from API.');
      clearInterval(intervalId);
      return;
    }

    const status = result.status;
    if (['generating', 'queued', 'waiting'].includes(status)) {
      console.log('Still waiting... Checking again in 10 seconds.');
    } else {
      console.log('Generation complete:\n', result);
      clearInterval(intervalId);
    }
  }, interval);
}

main();

Response

Generation: {'id': 'ac94b938-a53a-483a-bef3-2bea9dd12bb8:lyria2', 'status': 'queued'}
Still waiting... Checking again in 10 seconds.
Still waiting... Checking again in 10 seconds.
Still waiting... Checking again in 10 seconds.
Generation complete:/n {'id': 'ac94b938-a53a-483a-bef3-2bea9dd12bb8:lyria2', 'status': 'completed', 'audio_file': {'url': 'https://cdn.aimlapi.com/eagle/files/lion/5N4F_QWb5K8rDSHfpUN0S_output.wav', 'content_type': 'audio/wav', 'file_name': 'output.wav', 'file_size': 6291544}}

Listen to the track we generated:

PreviousGoogle NextMiniMax

Last updated 18 days ago

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