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Generare musica con Lyria 3.5

Lyria 3.5 è la famiglia di modelli di generazione di musica di Google, disponibile tramite l'API Gemini. Con Lyria 3.5 puoi generare audio stereo di alta qualità a 44,1 kHz a partire da prompt di testo o immagini. Questi modelli offrono coerenza strutturale, tra cui voci, testi sincronizzati e arrangiamenti strumentali completi.

La famiglia Lyria include i modelli:

Modello	ID modello	Ideale per	Durata	Output
Lyria 3 Clip	`lyria-3-clip-preview`	Clip brevi, loop, anteprime	30 secondi	MP3
Lyria 3.5	`lyria-3.5`	Brani completi con strofe, ritornelli e ponti	Un paio di minuti (controllabile tramite prompt)	MP3

Entrambi i modelli possono essere utilizzati con la nuova API Interactions, supportano input multimodali (testo e immagini) e producono audio stereo ad alta fedeltà a 44,1 kHz.

Generare un clip musicale

Il modello Lyria 3 Clip genera sempre un clip di 30 secondi. Per generare un clip, chiama il metodo interactions.create con un prompt testuale. La risposta include sempre il testo e la struttura della canzone generati insieme all'audio nello schema steps.

Python

import base64
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="lyria-3-clip-preview",
    input="A short instrumental acoustic guitar piece.",
)

generated_audio = interaction.output_audio
if generated_audio:
    with open("music.mp3", "wb") as f:
        f.write(base64.b64decode(generated_audio.data))

lyrics = interaction.output_text
if lyrics:
    print(f"Lyrics:\n{lyrics}")

JavaScript

import { GoogleGenAI } from '@google/genai';
import * as fs from 'fs';

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    model: 'lyria-3-clip-preview',
    input: 'A short instrumental acoustic guitar piece.',
});

const generatedAudio = interaction.output_audio;
if (generatedAudio) {
  fs.writeFileSync('music.mp3', Buffer.from(generatedAudio.data, 'base64'));
}

const lyrics = interaction.output_text;
if (lyrics) {
  console.log(`Lyrics:\n${lyrics}`);
}

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Base64;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3-clip-preview"))
        .input(InteractionsInput.of("A short instrumental acoustic guitar piece."))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.outputAudio().isPresent() && interaction.outputAudio().get().data().isPresent()) {
  byte[] audioBytes = Base64.getDecoder().decode(interaction.outputAudio().get().data().get());
  Files.write(Paths.get("music.mp3"), audioBytes);
}

interaction.outputText().ifPresent(lyrics -> System.out.println("Lyrics:\n" + lyrics));

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-clip-preview",
    "input": "A short instrumental acoustic guitar piece."
}'

Puoi recuperare i dati musicali generati utilizzando la proprietà interaction.output_audio, che restituisce l'ultimo blocco audio generato. Puoi anche recuperare il testo e la struttura del brano utilizzando la proprietà interaction.output_text. Per informazioni dettagliate sulle proprietà di convenienza, consulta la panoramica delle interazioni.

Generare un brano completo

Utilizza il modello lyria-3.5 per generare brani completi che durano un paio di minuti. Il modello Pro comprende la struttura musicale e può creare composizioni con strofe, ritornelli e ponti distinti. Puoi influenzare la durata specificandola nel prompt (ad es. "crea una canzone di 2 minuti") o utilizzando timestamp per definire la struttura.

Python

interaction = client.interactions.create(
    model="lyria-3.5",
    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.",
)

JavaScript

const interaction = await client.interactions.create({
    model: 'lyria-3.5',
    input: 'A beautiful piano melody.',
});

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(
            InteractionsInput.of(
                "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."))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

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-3.5",
    "input": "A beautiful piano melody."
}'

Seleziona il formato di output

Per impostazione predefinita, i modelli Lyria 3.5 generano audio in formato MP3. Per Lyria 3.5, puoi anche richiedere l'output in formato WAV impostando response_format.

Python

interaction = client.interactions.create(
    model="lyria-3.5",
    input="A beautiful piano melody.",
    response_format={"type": "audio"},
)

JavaScript

const interaction = await client.interactions.create({
    model: 'lyria-3.5',
    input: 'A beautiful piano melody.',
    response_format: {
        type: 'audio',
    },
});

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.AudioResponseFormat;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.CreateModelInteractionResponseFormat;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ResponseFormat;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(InteractionsInput.of("A beautiful piano melody."))
        .responseFormat(
            CreateModelInteractionResponseFormat.of(
                ResponseFormat.of(AudioResponseFormat.builder().build())))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "lyria-3.5",
    "input": "A beautiful piano melody.",
    "response_format": {
        "type": "audio"
    }
  }'

Analizza la risposta

La risposta di Lyria 3.5 contiene più blocchi di contenuti all'interno dello schema steps. Le interazioni restituiscono una sequenza di passaggi, in cui i passaggi model_output contengono i contenuti generati. I blocchi di contenuti di testo contengono i testi generati o una descrizione JSON della struttura del brano. I blocchi di contenuti di tipo audio contengono i dati audio codificati in base64.

Python

lyrics = []
audio_data = None

generated_audio = interaction.output_audio
if generated_audio:
    with open("output.mp3", "wb") as f:
        f.write(base64.b64decode(generated_audio.data))

lyrics = interaction.output_text
if lyrics:
    print(f"Lyrics:\n{lyrics}")

JavaScript

const lyrics = [];
let audioData = null;

const generatedAudio = interaction.output_audio;
if (generatedAudio) {
    fs.writeFileSync("output.mp3", Buffer.from(generatedAudio.data, 'base64'));
}

const lyrics = interaction.output_text;
if (lyrics) {
    console.log("Lyrics:\n" + lyrics);
}

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Base64;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(InteractionsInput.of("A song about a starry night."))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.outputAudio().isPresent() && interaction.outputAudio().get().data().isPresent()) {
  byte[] audioBytes = Base64.getDecoder().decode(interaction.outputAudio().get().data().get());
  Files.write(Paths.get("output.mp3"), audioBytes);
}

if (interaction.outputText().isPresent()) {
  System.out.println("Lyrics:\n" + interaction.outputText().get());
}

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 '.steps[] | select(.type=="model_output") | .content[] | select(.type=="audio") | .data' | base64 -d > output.mp3

Testi e musica alternati

Poiché l'output di Lyria 3.5 è complesso e contiene passaggi e blocchi separati per i testi generati (testo) e la canzone stessa (audio), le proprietà di convenienza offrono una scorciatoia rapida e consigliata.

Tuttavia, se vuoi un controllo programmatico completo sulla sequenza temporale non elaborata dei passaggi restituiti dal server (ad esempio, registrando i singoli blocchi di contenuti man mano che vengono ricevuti), puoi eseguire l'iterazione manualmente su steps:

Python

lyrics = []
audio_data = None

for step in interaction.steps:
    if step.type == "model_output":
        for content_block in step.content:
            if content_block.type == "audio":
                audio_data = base64.b64decode(content_block.data)
            elif content_block.type == "text":
                lyrics.append(content_block.text)

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 step of interaction.steps) {
    if (step.type === 'model_output') {
        for (const contentBlock of step.content) {
            if (contentBlock.type === 'audio') {
                audioData = Buffer.from(contentBlock.data, 'base64');
            } else if (contentBlock.type === 'text') {
                lyrics.push(contentBlock.text);
            }
        }
    }
}

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

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

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.AudioContent;
import com.google.genai.gaos.models.interactions.Content;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ModelOutputStep;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.ArrayList;
import java.util.Base64;
import java.util.List;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(InteractionsInput.of("A song about a starry night."))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

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

if (interaction.steps().isPresent()) {
  for (Step step : interaction.steps().get()) {
    if (step instanceof ModelOutputStep) {
      ModelOutputStep outputStep = (ModelOutputStep) step;
      if (outputStep.content().isPresent()) {
        for (Content contentBlock : outputStep.content().get()) {
          if (contentBlock instanceof AudioContent) {
            AudioContent audioBlock = (AudioContent) contentBlock;
            if (audioBlock.data().isPresent()) {
              audioData = Base64.getDecoder().decode(audioBlock.data().get());
            }
          } else if (contentBlock instanceof TextContent) {
            TextContent textBlock = (TextContent) contentBlock;
            textBlock.text().ifPresent(lyrics::add);
          }
        }
      }
    }
  }
}

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

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

Generare musica dalle immagini

Lyria 3.5 supporta input multimodali: puoi fornire fino a 10 immagini insieme al prompt testuale nell'elenco input e il modello comporrà musica ispirata ai contenuti visivi.

Python

import base64

with open("desert_sunset.jpg", "rb") as f:
    image_bytes = f.read()
    image_b64 = base64.b64encode(image_bytes).decode("utf-8")

response = client.interactions.create(
    model="lyria-3.5",
    input=[
        {
            "type": "text",
            "text": "An atmospheric ambient track inspired by the mood and colors in this image.",
        },
        {
            "type": "image",
            "mime_type": "image/jpeg",
            "data": image_b64,
        },
    ],
)

JavaScript

import * as fs from "fs";

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

const interaction = await client.interactions.create({
    model: "lyria-3.5",
    input: [
        {
            type: "text",
            text: "An atmospheric ambient track inspired by the mood and colors in this image.",
        },
        {
            type: "image",
            mime_type: "image/jpeg",
            data: imageBytes,
        },
    ],
});

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.Content;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.ImageContent;
import com.google.genai.gaos.models.interactions.ImageContentMimeType;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;
import java.util.List;

Client client = new Client();

byte[] imageBytes = Files.readAllBytes(Paths.get("desert_sunset.jpg"));
String imageB64 = Base64.getEncoder().encodeToString(imageBytes);

Content textContent =
    TextContent.builder()
        .text("An atmospheric ambient track inspired by the mood and colors in this image.")
        .build();
Content imageContent =
    ImageContent.builder()
        .mimeType(ImageContentMimeType.IMAGE_JPEG)
        .data(imageB64)
        .build();

List<Content> contents = Arrays.asList(textContent, imageContent);

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(InteractionsInput.ofContent(contents))
        .build();

Interaction response =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

REST

# Pass base64 encoded image data directly:
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "lyria-3.5",
    "input": [
      {"type": "text", "text": "An atmospheric ambient track inspired by the mood and colors in this image."},
      {"type": "image", "mime_type": "image/jpeg", "data": "/9j/4AAQSkZJRgABAQEASABIAAD/2wBDAP//////////////////////////////////////////////////////////////////////////////////////wgALCAABAAEBAREA/8QAFBABAAAAAAAAAAAAAAAAAAAAAP/aAAgBAQABPxA="}
    ]
  }'

Fornire testi personalizzati

Puoi scrivere i tuoi testi e includerli nel prompt. Utilizza i tag di sezione come [Verse], [Chorus] e [Bridge] per aiutare il modello a comprendere la struttura del brano:

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.
"""

interaction = client.interactions.create(
    model="lyria-3.5",
    input=prompt,
)

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 interaction = await client.interactions.create({
    model: 'lyria-3.5',
    input: prompt,
});

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

String prompt =
    "Create a dreamy indie pop song with the following lyrics:\n\n"
        + "[Verse 1]\n"
        + "Walking through the neon glow,\n"
        + "city lights reflect below,\n"
        + "every shadow tells a story,\n"
        + "every corner, fading glory.\n\n"
        + "[Chorus]\n"
        + "We are the echoes in the night,\n"
        + "burning brighter than the light,\n"
        + "hold on tight, don't let me go,\n"
        + "we are the echoes down below.\n\n"
        + "[Verse 2]\n"
        + "Footsteps lost on empty streets,\n"
        + "rhythms sync to heartbeats,\n"
        + "whispers carried by the breeze,\n"
        + "dancing through the autumn leaves.";

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(InteractionsInput.of(prompt))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "lyria-3.5",
    "input": "Create a dreamy indie pop song with the following lyrics: ..."
  }'

Controllare la tempistica e la struttura

Puoi specificare esattamente cosa succede in momenti specifici del brano utilizzando i timestamp. Questo è utile per controllare quando entrano gli strumenti, quando vengono fornite le parole e come procede la canzone:

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.
"""

interaction = client.interactions.create(
    model="lyria-3.5",
    input=prompt,
)

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 interaction = await client.interactions.create({
    model: 'lyria-3.5',
    input: prompt,
});

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

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

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(InteractionsInput.of(prompt))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "lyria-3.5",
    "input": "[0:00 - 0:10] Intro: ..."
  }'

Generare tracce strumentali

Per la musica di sottofondo, le colonne sonore dei giochi o qualsiasi caso d'uso in cui non sono richieste le parti vocali, puoi chiedere al modello di produrre tracce solo strumentali:

Python

interaction = client.interactions.create(
    model="lyria-3-clip-preview",
    input="A bright chiptune melody in C Major, retro 8-bit video game style. Instrumental only, no vocals.",
)

JavaScript

const interaction = await client.interactions.create({
    model: 'lyria-3-clip-preview',
    input: 'A bright chiptune melody in C Major, retro 8-bit video game style. Instrumental only, no vocals.',
});

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3-clip-preview"))
        .input(
            InteractionsInput.of(
                "A bright chiptune melody in C Major, retro 8-bit video game style. Instrumental only, no vocals."))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "lyria-3-clip-preview",
    "input": "A bright chiptune melody in C Major, retro 8-bit video game style. Instrumental only, no vocals."
  }'

Generare musica in lingue diverse

Lyria 3.5 genera testi nella lingua del prompt. Per generare una canzone con un testo in francese, scrivi il prompt in francese. Il modello adatta lo stile vocale e la pronuncia in base alla lingua.

Python

interaction = client.interactions.create(
    model="lyria-3.5",
    input="Crée une chanson pop romantique en français sur un coucher de soleil à Paris. Utilise du piano et de la guitare acoustique.",
)

JavaScript

const interaction = await client.interactions.create({
    model: 'lyria-3.5',
    input: 'Crée une chanson pop romantique en français sur un coucher de soleil à Paris. Utilise du piano et de la guitare acoustique.',
});

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("lyria-3.5"))
        .input(
            InteractionsInput.of(
                "Crée une chanson pop romantique en français sur un coucher de soleil à Paris. Utilise du piano et de la guitare acoustique."))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "lyria-3.5",
    "input": "Crée une chanson pop romantique en français sur un coucher de soleil à Paris. Utilise du piano et de la guitare acoustique."
  }'

Model Intelligence

Lyria 3.5 analizza il processo di prompt in cui il modello ragiona sulla struttura musicale (intro, strofa, ritornello, bridge e così via) in base al prompt. Ciò avviene prima della generazione dell'audio e garantisce coerenza strutturale e musicalità.

Guida ai prompt

Per scoprire come creare prompt efficaci per generi musicali, strumenti, struttura dei brani, testi personalizzati e stili di esecuzione vocale, consulta la Guida ai prompt di Lyria.

Best practice

Esegui l'iterazione con Clip. Utilizza il modello lyria-3-clip-preview più veloce per sperimentare con i prompt prima di eseguire una generazione completa con lyria-3.5.
Usa un testo specifico. I prompt vaghi producono risultati generici. Menziona strumenti, BPM, tonalità, stato d'animo e struttura per ottenere il miglior output.
Scegli la tua lingua. Prompt nella lingua in cui vuoi che vengano visualizzati i testi.
Utilizza i tag di sezione. I tag [Verse], [Chorus] e [Bridge] forniscono al modello una struttura chiara da seguire.
Separa i testi dalle istruzioni. Quando fornisci testi personalizzati, separali chiaramente dalle istruzioni per la direzione musicale.

Limitazioni

Sicurezza: tutti i prompt vengono controllati dai filtri di sicurezza. I prompt che attivano i filtri verranno bloccati. Ciò include i prompt che richiedono voci di artisti specifici o la generazione di testi protetti da copyright.
Filigrana: tutto l'audio generato include una filigrana audio SynthID per l'identificazione. Questa filigrana è impercettibile all'orecchio umano e non influisce sull'esperienza di ascolto.
Modifica multi-turno: la generazione di musica è un processo in un solo passaggio. L'editing iterativo o il perfezionamento di un clip generato tramite più prompt non è supportato nella versione attuale di Lyria 3.5.
Durata: il modello Clip genera sempre clip di 30 secondi. Il modello Pro genera brani che durano un paio di minuti; la durata esatta può essere influenzata dal prompt.
Determinismo: i risultati possono variare tra le chiamate, anche con lo stesso prompt.

Passaggi successivi

Consulta i prezzi dei modelli Lyria 3.5.
Prova la generazione di musica in streaming in tempo reale con Lyria RealTime.
Genera conversazioni con più interlocutori con i modelli TTS.
Scopri come generare immagini o video.
Scopri come Gemini può comprendere i file audio.
Avvia una conversazione in tempo reale con Gemini utilizzando l'API Live.