Prueba Lyria 3, nuestro nuevo modelo de generación de música capaz de producir audio estéreo de alta fidelidad a partir de entradas de texto y de imágenes.

Genera música con Lyria 3

Lyria 3 es la familia de modelos de generación de música de Google, disponible a través de la API de Gemini. Con Lyria 3, puedes generar audio estéreo de 48 kHz de alta calidad a partir de instrucciones de texto o imágenes. Estos modelos ofrecen coherencia estructural, incluidas voces, letras sincronizadas y arreglos instrumentales completos.

La familia Lyria 3 incluye dos modelos:

Modelo	ID de modelo	Ideal para	Duración	Salida
Lyria 3 Clip	`lyria-3-clip-preview`	Clips cortos, bucles y vistas previas	30 segundos	MP3
Lyria 3 Pro	`lyria-3-pro-preview`	Canciones completas con versos, estribillos y puentes	Un par de minutos (se puede controlar a través de la instrucción)	MP3, WAV

Ambos modelos se pueden usar con el método generateContent estándar y la nueva API de Interactions, que admite entradas multimodales (texto e imágenes) y produce audio estéreo de alta fidelidad de 48 kHz.

Genera un clip musical

El modelo Lyria 3 Clip siempre genera un clip de 30 segundos. Para generar un clip, llama al generateContent método y establece response_modalities en ["AUDIO", "TEXT"]. Si incluyes TEXT, puedes recibir la letra o la estructura de la canción generadas junto con el audio.

Python

from google import genai
from google.genai import types

client = genai.Client()

response = client.models.generate_content(
    model="lyria-3-clip-preview",
    contents="Create a 30-second cheerful acoustic folk song with "
             "guitar and harmonica.",
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
    ),
)

# Parse the response
for part in response.parts:
    if part.text is not None:
        print(part.text)
    elif part.inline_data is not None:
        with open("clip.mp3", "wb") as f:
            f.write(part.inline_data.data)
        print("Audio saved to clip.mp3")

JavaScript

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

const ai = new GoogleGenAI({});

async function main() {
  const response = await ai.models.generateContent({
    model: "lyria-3-clip-preview",
    contents: "Create a 30-second cheerful acoustic folk song with " +
              "guitar and harmonica.",
    config: {
      responseModalities: ["AUDIO", "TEXT"],
    },
  });

  for (const part of response.candidates[0].content.parts) {
    if (part.text) {
      console.log(part.text);
    } else if (part.inlineData) {
      const buffer = Buffer.from(part.inlineData.data, "base64");
      fs.writeFileSync("clip.mp3", buffer);
      console.log("Audio saved to clip.mp3");
    }
  }
}

main();

Go

package main

import (
    "context"
    "fmt"
    "log"
    "os"

    "google.golang.org/genai"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    config := &genai.GenerateContentConfig{
        ResponseModalities: []string{"AUDIO", "TEXT"},
    }

    result, err := client.Models.GenerateContent(
        ctx,
        "lyria-3-clip-preview",
        genai.Text("Create a 30-second cheerful acoustic folk song " +
                   "with guitar and harmonica."),
        config,
    )
    if err != nil {
        log.Fatal(err)
    }

    for _, part := range result.Candidates[0].Content.Parts {
        if part.Text != "" {
            fmt.Println(part.Text)
        } else if part.InlineData != nil {
            err := os.WriteFile("clip.mp3", part.InlineData.Data, 0644)
            if err != nil {
                log.Fatal(err)
            }
            fmt.Println("Audio saved to clip.mp3")
        }
    }
}

Java

import com.google.genai.Client;
import com.google.genai.types.GenerateContentConfig;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.Part;

import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Paths;

public class GenerateMusicClip {
  public static void main(String[] args) throws IOException {

    try (Client client = new Client()) {
      GenerateContentConfig config = GenerateContentConfig.builder()
          .responseModalities("AUDIO", "TEXT")
          .build();

      GenerateContentResponse response = client.models.generateContent(
          "lyria-3-clip-preview",
          "Create a 30-second cheerful acoustic folk song with "
              + "guitar and harmonica.",
          config);

      for (Part part : response.parts()) {
        if (part.text().isPresent()) {
          System.out.println(part.text().get());
        } else if (part.inlineData().isPresent()) {
          var blob = part.inlineData().get();
          if (blob.data().isPresent()) {
            Files.write(Paths.get("clip.mp3"), blob.data().get());
            System.out.println("Audio saved to clip.mp3");
          }
        }
      }
    }
  }
}

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3-clip-preview:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "Create a 30-second cheerful acoustic folk song with guitar and harmonica."}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["AUDIO", "TEXT"]
    }
  }'

C#

using System.Threading.Tasks;
using Google.GenAI;
using Google.GenAI.Types;
using System.IO;

public class GenerateMusicClip {
  public static async Task main() {
    var client = new Client();
    var config = new GenerateContentConfig {
      ResponseModalities = { "AUDIO", "TEXT" }
    };

    var response = await client.Models.GenerateContentAsync(
      model: "lyria-3-clip-preview",
      contents: "Create a 30-second cheerful acoustic folk song with guitar and harmonica.",
      config: config
    );

    foreach (var part in response.Candidates[0].Content.Parts) {
      if (part.Text != null) {
        Console.WriteLine(part.Text);
      } else if (part.InlineData != null) {
        await File.WriteAllBytesAsync("clip.mp3", part.InlineData.Data);
        Console.WriteLine("Audio saved to clip.mp3");
      }
    }
  }
}

Genera una canción completa

Usa el modelo lyria-3-pro-preview para generar canciones completas que duren un par de minutos. El modelo Pro comprende la estructura musical y puede crear composiciones con versos, estribillos y puentes distintos. Puedes influir en la duración especificándola en tu instrucción (p.ej., "crea una canción de 2 minutos") o usando marcas de tiempo para definir la estructura.

Python

response = client.models.generate_content(
    model="lyria-3-pro-preview",
    contents="An epic cinematic orchestral piece about a journey home. "
             "Starts with a solo piano intro, builds through sweeping "
             "strings, and climaxes with a massive wall of sound.",
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
    ),
)

JavaScript

const response = await ai.models.generateContent({
  model: "lyria-3-pro-preview",
  contents: "An epic cinematic orchestral piece about a journey home. " +
            "Starts with a solo piano intro, builds through sweeping " +
            "strings, and climaxes with a massive wall of sound.",
  config: {
    responseModalities: ["AUDIO", "TEXT"],
  },
});

Go

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3-pro-preview",
    genai.Text("An epic cinematic orchestral piece about a journey " +
               "home. Starts with a solo piano intro, builds through " +
               "sweeping strings, and climaxes with a massive wall of sound."),
    config,
)

Java

GenerateContentResponse response = client.models.generateContent(
    "lyria-3-pro-preview",
    "An epic cinematic orchestral piece about a journey home. "
        + "Starts with a solo piano intro, builds through sweeping "
        + "strings, and climaxes with a massive wall of sound.",
    config);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3-pro-preview:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "An epic cinematic orchestral piece about a journey home. Starts with a solo piano intro, builds through sweeping strings, and climaxes with a massive wall of sound."}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["AUDIO", "TEXT"]
    }
  }'

C#

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3-pro-preview",
  contents: "An epic cinematic orchestral piece about a journey home. " +
            "Starts with a solo piano intro, builds through sweeping " +
            "strings, and climaxes with a massive wall of sound.",
  config: config
);

Analiza la respuesta

La respuesta de Lyria 3 contiene varias partes. Las partes de texto contienen la letra generada o una descripción JSON de la estructura de la canción. Las partes con inline_data contienen los bytes de audio.

Python

lyrics = []
audio_data = None

for part in response.parts:
    if part.text is not None:
        lyrics.append(part.text)
    elif part.inline_data is not None:
        audio_data = part.inline_data.data

if lyrics:
    print("Lyrics:\n" + "\n".join(lyrics))

if audio_data:
    with open("output.mp3", "wb") as f:
        f.write(audio_data)

JavaScript

const lyrics = [];
let audioData = null;

for (const part of response.candidates[0].content.parts) {
  if (part.text) {
    lyrics.push(part.text);
  } else if (part.inlineData) {
    audioData = Buffer.from(part.inlineData.data, "base64");
  }
}

if (lyrics.length) {
  console.log("Lyrics:\n" + lyrics.join("\n"));
}

if (audioData) {
  fs.writeFileSync("output.mp3", audioData);
}

Go

var lyrics []string
var audioData []byte

for _, part := range result.Candidates[0].Content.Parts {
    if part.Text != "" {
        lyrics = append(lyrics, part.Text)
    } else if part.InlineData != nil {
        audioData = part.InlineData.Data
    }
}

if len(lyrics) > 0 {
    fmt.Println("Lyrics:\n" + strings.Join(lyrics, "\n"))
}

if audioData != nil {
    err := os.WriteFile("output.mp3", audioData, 0644)
    if err != nil {
        log.Fatal(err)
    }
}

Java

List<String> lyrics = new ArrayList<>();
byte[] audioData = null;

for (Part part : response.parts()) {
  if (part.text().isPresent()) {
    lyrics.add(part.text().get());
  } else if (part.inlineData().isPresent()) {
    audioData = part.inlineData().get().data().get();
  }
}

if (!lyrics.isEmpty()) {
  System.out.println("Lyrics:\n" + String.join("\n", lyrics));
}

if (audioData != null) {
  Files.write(Paths.get("output.mp3"), audioData);
}

C#

var lyrics = new List<string>();
byte[] audioData = null;

foreach (var part in response.Candidates[0].Content.Parts) {
  if (part.Text != null) {
    lyrics.Add(part.Text);
  } else if (part.InlineData != null) {
    audioData = part.InlineData.Data;
  }
}

if (lyrics.Count > 0) {
  Console.WriteLine("Lyrics:\n" + string.Join("\n", lyrics));
}

if (audioData != null) {
  await File.WriteAllBytesAsync("output.mp3", audioData);
}

REST

# The output from the REST API is a JSON object containing base64 encoded data.
# You can extract the text or the audio data using a tool like jq.
# To extract the audio and save it to a file:
curl ... | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -d > output.mp3

Genera música a partir de imágenes

Lyria 3 admite entradas multimodales. Puedes proporcionar hasta 10 imágenes junto con tu instrucción de texto, y el modelo compondrá música inspirada en el contenido visual.

Python

from PIL import Image

image = Image.open("desert_sunset.jpg")

response = client.models.generate_content(
    model="lyria-3-pro-preview",
    contents=[
        "An atmospheric ambient track inspired by the mood and "
        "colors in this image.",
        image,
    ],
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
    ),
)

JavaScript

const imageData = fs.readFileSync("desert_sunset.jpg");
const base64Image = imageData.toString("base64");

const response = await ai.models.generateContent({
  model: "lyria-3-pro-preview",
  contents: [
    { text: "An atmospheric ambient track inspired by the mood " +
            "and colors in this image." },
    {
      inlineData: {
        mimeType: "image/jpeg",
        data: base64Image,
      },
    },
  ],
  config: {
    responseModalities: ["AUDIO", "TEXT"],
  },
});

Go

imgData, err := os.ReadFile("desert_sunset.jpg")
if err != nil {
    log.Fatal(err)
}

parts := []*genai.Part{
    genai.NewPartFromText("An atmospheric ambient track inspired " +
        "by the mood and colors in this image."),
    &genai.Part{
        InlineData: &genai.Blob{
            MIMEType: "image/jpeg",
            Data:     imgData,
        },
    },
}

contents := []*genai.Content{
    genai.NewContentFromParts(parts, genai.RoleUser),
}

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3-pro-preview",
    contents,
    config,
)

Java

GenerateContentResponse response = client.models.generateContent(
    "lyria-3-pro-preview",
    Content.fromParts(
        Part.fromText("An atmospheric ambient track inspired by "
            + "the mood and colors in this image."),
        Part.fromBytes(
            Files.readAllBytes(Path.of("desert_sunset.jpg")),
            "image/jpeg")),
    config);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3-pro-preview:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d "{
    \"contents\": [{
      \"parts\":[
          {\"text\": \"An atmospheric ambient track inspired by the mood and colors in this image.\"},
          {
            \"inline_data\": {
              \"mime_type\":\"image/jpeg\",
              \"data\": \"<BASE64_IMAGE_DATA>\"
            }
          }
      ]
    }],
    \"generationConfig\": {
      \"responseModalities\": [\"AUDIO\", \"TEXT\"]
    }
  }"

C#

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3-pro-preview",
  contents: new List<Part> {
    Part.FromText("An atmospheric ambient track inspired by the mood and colors in this image."),
    Part.FromBytes(await File.ReadAllBytesAsync("desert_sunset.jpg"), "image/jpeg")
  },
  config: config
);

Proporciona letras personalizadas

Puedes escribir tu propia letra e incluirla en la instrucción. Usa etiquetas de sección como [Verse], [Chorus] y [Bridge] para ayudar al modelo a comprender la estructura de la canción:

Python

prompt = """
Create a dreamy indie pop song with the following lyrics:

[Verse 1]
Walking through the neon glow,
city lights reflect below,
every shadow tells a story,
every corner, fading glory.

[Chorus]
We are the echoes in the night,
burning brighter than the light,
hold on tight, don't let me go,
we are the echoes down below.

[Verse 2]
Footsteps lost on empty streets,
rhythms sync to heartbeats,
whispers carried by the breeze,
dancing through the autumn leaves.
"""

response = client.models.generate_content(
    model="lyria-3-pro-preview",
    contents=prompt,
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
    ),
)

JavaScript

const prompt = `
Create a dreamy indie pop song with the following lyrics:

[Verse 1]
Walking through the neon glow,
city lights reflect below,
every shadow tells a story,
every corner, fading glory.

[Chorus]
We are the echoes in the night,
burning brighter than the light,
hold on tight, don't let me go,
we are the echoes down below.

[Verse 2]
Footsteps lost on empty streets,
rhythms sync to heartbeats,
whispers carried by the breeze,
dancing through the autumn leaves.
`;

const response = await ai.models.generateContent({
  model: "lyria-3-pro-preview",
  contents: prompt,
  config: {
    responseModalities: ["AUDIO", "TEXT"],
  },
});

Go

prompt := `
Create a dreamy indie pop song with the following lyrics:

[Verse 1]
Walking through the neon glow,
city lights reflect below,
every shadow tells a story,
every corner, fading glory.

[Chorus]
We are the echoes in the night,
burning brighter than the light,
hold on tight, don't let me go,
we are the echoes down below.

[Verse 2]
Footsteps lost on empty streets,
rhythms sync to heartbeats,
whispers carried by the breeze,
dancing through the autumn leaves.
`

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3-pro-preview",
    genai.Text(prompt),
    config,
)

Java

String prompt = """
    Create a dreamy indie pop song with the following lyrics:

    [Verse 1]
    Walking through the neon glow,
    city lights reflect below,
    every shadow tells a story,
    every corner, fading glory.

    [Chorus]
    We are the echoes in the night,
    burning brighter than the light,
    hold on tight, don't let me go,
    we are the echoes down below.

    [Verse 2]
    Footsteps lost on empty streets,
    rhythms sync to heartbeats,
    whispers carried by the breeze,
    dancing through the autumn leaves.
    """;

GenerateContentResponse response = client.models.generateContent(
    "lyria-3-pro-preview",
    prompt,
    config);

C#

var prompt = @"
Create a dreamy indie pop song with the following lyrics:

[Verse 1]
Walking through the neon glow,
city lights reflect below,
every shadow tells a story,
every corner, fading glory.

[Chorus]
We are the echoes in the night,
burning brighter than the light,
hold on tight, don't let me go,
we are the echoes down below.

[Verse 2]
Footsteps lost on empty streets,
rhythms sync to heartbeats,
whispers carried by the breeze,
dancing through the autumn leaves.
";

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3-pro-preview",
  contents: prompt,
  config: config
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3-pro-preview:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "Create a dreamy indie pop song with the following lyrics: ..."}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["AUDIO", "TEXT"]
    }
  }'

Controla el tiempo y la estructura

Puedes especificar exactamente lo que sucede en momentos específicos de la canción con marcas de tiempo. Esto es útil para controlar cuándo entran los instrumentos, cuándo se entrega la letra y cómo avanza la canción:

Python

prompt = """
[0:00 - 0:10] Intro: Begin with a soft lo-fi beat and muffled
              vinyl crackle.
[0:10 - 0:30] Verse 1: Add a warm Fender Rhodes piano melody
              and gentle vocals singing about a rainy morning.
[0:30 - 0:50] Chorus: Full band with upbeat drums and soaring
              synth leads. The lyrics are hopeful and uplifting.
[0:50 - 1:00] Outro: Fade out with the piano melody alone.
"""

response = client.models.generate_content(
    model="lyria-3-pro-preview",
    contents=prompt,
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
    ),
)

JavaScript

const prompt = `
[0:00 - 0:10] Intro: Begin with a soft lo-fi beat and muffled
              vinyl crackle.
[0:10 - 0:30] Verse 1: Add a warm Fender Rhodes piano melody
              and gentle vocals singing about a rainy morning.
[0:30 - 0:50] Chorus: Full band with upbeat drums and soaring
              synth leads. The lyrics are hopeful and uplifting.
[0:50 - 1:00] Outro: Fade out with the piano melody alone.
`;

const response = await ai.models.generateContent({
  model: "lyria-3-pro-preview",
  contents: prompt,
  config: {
    responseModalities: ["AUDIO", "TEXT"],
  },
});

Go

prompt := `
[0:00 - 0:10] Intro: Begin with a soft lo-fi beat and muffled
              vinyl crackle.
[0:10 - 0:30] Verse 1: Add a warm Fender Rhodes piano melody
              and gentle vocals singing about a rainy morning.
[0:30 - 0:50] Chorus: Full band with upbeat drums and soaring
              synth leads. The lyrics are hopeful and uplifting.
[0:50 - 1:00] Outro: Fade out with the piano melody alone.
`

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3-pro-preview",
    genai.Text(prompt),
    config,
)

Java

String prompt = """
    [0:00 - 0:10] Intro: Begin with a soft lo-fi beat and muffled
                  vinyl crackle.
    [0:10 - 0:30] Verse 1: Add a warm Fender Rhodes piano melody
                  and gentle vocals singing about a rainy morning.
    [0:30 - 0:50] Chorus: Full band with upbeat drums and soaring
                  synth leads. The lyrics are hopeful and uplifting.
    [0:50 - 1:00] Outro: Fade out with the piano melody alone.
    """;

GenerateContentResponse response = client.models.generateContent(
    "lyria-3-pro-preview",
    prompt,
    config);

C#

var prompt = @"
[0:00 - 0:10] Intro: Begin with a soft lo-fi beat and muffled
              vinyl crackle.
[0:10 - 0:30] Verse 1: Add a warm Fender Rhodes piano melody
              and gentle vocals singing about a rainy morning.
[0:30 - 0:50] Chorus: Full band with upbeat drums and soaring
              synth leads. The lyrics are hopeful and uplifting.
[0:50 - 1:00] Outro: Fade out with the piano melody alone.
";

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3-pro-preview",
  contents: prompt,
  config: config
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3-pro-preview:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "[0:00 - 0:10] Intro: ..."}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["AUDIO", "TEXT"]
    }
  }'

Genera pistas instrumentales

Para la música de fondo, las bandas sonoras de juegos o cualquier caso de uso en el que no se requieran voces, puedes indicarle al modelo que produzca pistas solo instrumentales:

Python

response = client.models.generate_content(
    model="lyria-3-clip-preview",
    contents="A bright chiptune melody in C Major, retro 8-bit "
             "video game style. Instrumental only, no vocals.",
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
    ),
)

JavaScript

const response = await ai.models.generateContent({
  model: "lyria-3-clip-preview",
  contents: "A bright chiptune melody in C Major, retro 8-bit " +
            "video game style. Instrumental only, no vocals.",
  config: {
    responseModalities: ["AUDIO", "TEXT"],
  },
});

Go

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3-clip-preview",
    genai.Text("A bright chiptune melody in C Major, retro 8-bit " +
               "video game style. Instrumental only, no vocals."),
    config,
)

Java

GenerateContentResponse response = client.models.generateContent(
    "lyria-3-clip-preview",
    "A bright chiptune melody in C Major, retro 8-bit "
        + "video game style. Instrumental only, no vocals.",
    config);

C#

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3-clip-preview",
  contents: "A bright chiptune melody in C Major, retro 8-bit " +
            "video game style. Instrumental only, no vocals.",
  config: config
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3-clip-preview:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "A bright chiptune melody in C Major, retro 8-bit video game style. Instrumental only, no vocals."}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["AUDIO", "TEXT"]
    }
  }'

Genera música en diferentes idiomas

Lyria 3 genera letras en el idioma de tu instrucción. Para generar una canción con letra en francés, escribe tu instrucción en francés. El modelo adapta su estilo vocal y pronunciación para que coincidan con el idioma.

Python

response = client.models.generate_content(
    model="lyria-3-pro-preview",
    contents="Crée une chanson pop romantique en français sur un "
             "coucher de soleil à Paris. Utilise du piano et de "
             "la guitare acoustique.",
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
    ),
)

JavaScript

const response = await ai.models.generateContent({
  model: "lyria-3-pro-preview",
  contents: "Crée une chanson pop romantique en français sur un " +
            "coucher de soleil à Paris. Utilise du piano et de " +
            "la guitare acoustique.",
  config: {
    responseModalities: ["AUDIO", "TEXT"],
  },
});

Go

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3-pro-preview",
    genai.Text("Crée une chanson pop romantique en français sur un " +
               "coucher de soleil à Paris. Utilise du piano et de " +
               "la guitare acoustique."),
    config,
)

Java

GenerateContentResponse response = client.models.generateContent(
    "lyria-3-pro-preview",
    "Crée une chanson pop romantique en français sur un "
        + "coucher de soleil à Paris. Utilise du piano et de "
        + "la guitare acoustique.",
    config);

C#

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3-pro-preview",
  contents: "Crée une chanson pop romantique en français sur un " +
            "coucher de soleil à Paris. Utilise du piano et de " +
            "la guitare acoustique.",
  config: config
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3-pro-preview:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "Crée une chanson pop romantique en français sur un coucher de soleil à Paris. Utilise du piano et de la guitare acoustique."}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["AUDIO", "TEXT"]
    }
  }'

Inteligencia del modelo

Lyria 3 analiza el proceso de tu instrucción, en el que el modelo razona a través de la estructura musical (introducción, verso, estribillo, puente, etcétera) según tu instrucción. Esto sucede antes de que se genere el audio y garantiza la coherencia estructural y la musicalidad.

API de Interactions

Puedes usar modelos de Lyria 3 con la API de Interactions; una interfaz unificada para interactuar con modelos y agentes de Gemini. Simplifica la administración de estados y las tareas de larga duración para casos de uso multimodales complejos.

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="lyria-3-pro-preview",
    input="An epic cinematic orchestral piece about a journey home. " +
          "Starts with a solo piano intro, builds through sweeping " +
          "strings, and climaxes with a massive wall of sound.",
    response_modalities=["AUDIO", "TEXT"]
)

for output in interaction.outputs:
    if output.text:
        print(output.text)
    elif output.inline_data:
         with open("interaction_output.mp3", "wb") as f:
            f.write(output.inline_data.data)
         print("Audio saved to interaction_output.mp3")

JavaScript

import { GoogleGenAI } from '@google/genai';

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
  model: 'lyria-3-pro-preview',
  input: 'An epic cinematic orchestral piece about a journey home. ' +
         'Starts with a solo piano intro, builds through sweeping ' +
         'strings, and climaxes with a massive wall of sound.',
  responseModalities: ['AUDIO', 'TEXT'],
});

for (const output of interaction.outputs) {
  if (output.text) {
    console.log(output.text);
  } else if (output.inlineData) {
    const buffer = Buffer.from(output.inlineData.data, 'base64');
    fs.writeFileSync('interaction_output.mp3', buffer);
    console.log('Audio saved to interaction_output.mp3');
  }
}

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-d '{
    "model": "lyria-3-pro-preview",
    "input": "An epic cinematic orchestral piece about a journey home. Starts with a solo piano intro, builds through sweeping strings, and climaxes with a massive wall of sound.",
    "responseModalities": ["AUDIO", "TEXT"]
}'

Guía de instrucciones

Cuanto más específica sea tu instrucción, mejores serán los resultados. Esto es lo que puedes incluir para guiar la generación:

Género: Especifica un género o una combinación de géneros (p.ej., "lo-fi hip hop", "jazz fusion", "cinematic orchestral").
Instrumentos: Nombra instrumentos específicos (p.ej., "Fender Rhodes piano", "slide guitar", "TR-808 drum machine").
BPM: Establece el tempo (p.ej., "120 BPM", "slow tempo around 70 BPM").
Tono/escala: Especifica un tono musical (p.ej., "in G major", "D minor").
Estado de ánimo y atmósfera: Usa adjetivos descriptivos (p.ej., "nostalgic", "aggressive", "ethereal", "dreamy").
Estructura: Usa etiquetas como [Verse], [Chorus], [Bridge], [Intro], [Outro] o marcas de tiempo para controlar el progreso de la canción.
Duración: El modelo Clip siempre produce clips de 30 segundos. Para el modelo Pro, especifica la duración deseada en tu instrucción (p.ej., "crea una canción de 2 minutos") o usa marcas de tiempo para controlar la duración.

Ejemplos de instrucciones

Estos son algunos ejemplos de instrucciones eficaces:

"A 30-second lofi hip hop beat with dusty vinyl crackle, mellow Rhodes piano chords, a slow boom-bap drum pattern at 85 BPM, and a jazzy upright bass line. Instrumental only."
"An upbeat, feel-good pop song in G major at 120 BPM with bright acoustic guitar strumming, claps, and warm vocal harmonies about a summer road trip."
"A dark, atmospheric trap beat at 140 BPM with heavy 808 bass, eerie synth pads, sharp hi-hats, and a haunting vocal sample. In D minor."

Prácticas recomendadas

Primero, itera con Clip. Usa el modelo lyria-3-clip-preview más rápido para experimentar con instrucciones antes de comprometerte con una generación completa con lyria-3-pro-preview.
Sé específico. Las instrucciones vagas producen resultados genéricos. Menciona instrumentos, BPM, tono, estado de ánimo y estructura para obtener el mejor resultado.
Haz coincidir tu idioma. Escribe la instrucción en el idioma en el que quieres que esté la letra.
Usa etiquetas de sección. Las etiquetas [Verse], [Chorus] y [Bridge] le dan al modelo una estructura clara para seguir.
Separa la letra de las instrucciones. Cuando proporciones letras personalizadas, sepáralas claramente de las instrucciones de dirección musical.

Limitaciones

Seguridad: Todos los filtros de seguridad verifican todas las instrucciones. Se bloquearán las instrucciones que activen los filtros. Esto incluye las instrucciones que solicitan voces de artistas específicos o la generación de letras protegidas por derechos de autor.
Marcas de agua: Todo el audio generado incluye una marca de agua de audio de SynthID para su identificación. Esta marca de agua es imperceptible para el oído humano y no afecta la experiencia auditiva.
Edición de varios turnos: La generación de música es un proceso de un solo turno. La edición iterativa o el perfeccionamiento de un clip generado a través de varias instrucciones no se admite en la versión actual de Lyria 3.
Longitud: El modelo Clip siempre genera clips de 30 segundos. El modelo Pro genera canciones que duran un par de minutos. La duración exacta se puede influir a través de tu instrucción.
Determinismo: Los resultados pueden variar entre las llamadas, incluso con la misma instrucción.

¿Qué sigue?

Consulta los precios de los modelos de Lyria 3.
Prueba la generación de música en tiempo real y transmisión con Lyria RealTime.
Genera conversaciones con varios oradores con los modelos de TTS.
Descubre cómo generar imágenes o videos.
Descubre cómo Gemini puede comprender archivos de audio.
Ten una conversación en tiempo real con Gemini usando la API de Live.