Interactions API 現已正式發布。建議使用這個 API，存取所有最新功能和模型。

Google 會運用 AI 技術將內容翻譯成你偏好的語言，但可能會出錯。

使用 Lyria 3.5 生成音樂

Lyria 3.5 是 Google 的音樂生成模型系列，可透過 Gemini API 使用。使用 Lyria 3.5，你可以根據文字提示或圖片生成高品質的 44.1 kHz 立體聲音訊。這類模型可提供結構一致的音樂，包括人聲、歌詞時間碼和完整樂器編曲。

Lyria 系列包含以下模型：

模型	模型 ID	適用情境	時間長度	輸出內容
Lyria 3 Clip	`lyria-3-clip-preview`	短片、循環播放、預覽	30 秒	MP3
Lyria 3.5	`lyria-3.5`	含主歌、副歌和橋段的完整歌曲	幾分鐘 (可透過提示詞控制)	MP3

這兩款模型都可透過標準 generateContent 方法和新的 Interactions API 使用，支援多模態輸入 (文字和圖片)，並生成 44.1 kHz 高精準度立體聲音訊。

生成音樂短片

Lyria 3 Clip 模型一律會生成 30 秒的片段。如要生成短片，請使用文字提示詞呼叫 generateContent 方法。回覆一律會包含生成的歌詞和歌曲結構，以及音訊。

Python

from google import genai

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.",
)

# 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.",

  });

  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)
    }

    result, err := client.Models.GenerateContent(
        ctx,
        "lyria-3-clip-preview",
        genai.Text("Create a 30-second cheerful acoustic folk song " +
                   "with guitar and harmonica."),
        nil,
    )
    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.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()) {
      GenerateContentResponse response = client.models.generateContent(
          "lyria-3-clip-preview",
          "Create a 30-second cheerful acoustic folk song with "
              + "guitar and harmonica.");

      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."}
      ]
    }]
  }'

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

    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");
      }
    }
  }
}

生成完整歌曲

使用 lyria-3.5 模型生成完整歌曲，長度約為幾分鐘。Pro 版模型可理解音樂結構，並創作具有不同主歌、副歌和橋段的樂曲。如要影響時長，可以在提示中指定 (例如「創作 2 分鐘的歌曲」)，或使用時間戳記定義結構。

Python

response = client.models.generate_content(
    model="lyria-3.5",
    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.",
)

JavaScript

const response = await ai.models.generateContent({
  model: "lyria-3.5",
  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.",

});

Go

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3.5",
    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."),
    nil,
)

Java

GenerateContentResponse response = client.models.generateContent(
    "lyria-3.5",
    "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.");

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3.5: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."}
      ]
    }]
  }'

C#

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3.5",
  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."
);

選取輸出格式

根據預設，Lyria 3.5 模型會生成 MP3 格式的音訊。對於 Lyria 3.5，您也可以在 generationConfig 中設定 response_format，要求以 WAV 格式輸出。

Python

from google.genai import types

response = client.models.generate_content(
    model="lyria-3.5",
    contents="An atmospheric ambient track.",
    config=types.GenerateContentConfig(
        response_modalities=["AUDIO", "TEXT"],
        response_format={"audio": {"mime_type": "audio/wav"}},
    ),
)

JavaScript

const response = await ai.models.generateContent({
  model: "lyria-3.5",
  contents: "An atmospheric ambient track.",
  config: {
    responseModalities: ["AUDIO", "TEXT"],
    responseFormat: { audio: { mimeType: "audio/wav" } },
  },
});

Go

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

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3.5",
    genai.Text("An atmospheric ambient track."),
    config,
)

Java

GenerateContentConfig config = GenerateContentConfig.builder()
    .responseModalities("AUDIO", "TEXT")
    .responseFormat(ResponseFormat.builder().audio(AudioFormat.builder().mimeType("audio/wav").build()).build())
    .build();

GenerateContentResponse response = client.models.generateContent(
    "lyria-3.5",
    "An atmospheric ambient track.",
    config);

C#

var config = new GenerateContentConfig {
  ResponseModalities = { "AUDIO", "TEXT" },
  ResponseMimeType = "audio/wav"
};

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3.5",
  contents: "An atmospheric ambient track.",
  config: config
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3.5:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "An atmospheric ambient track."}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["AUDIO", "TEXT"],
      "responseFormat": { "audio": { "mimeType": "audio/wav" } }
    }
  }'

剖析回應

Lyria 3.5 的回覆包含多個部分。文字部分包含生成的歌詞，或歌曲結構的 JSON 說明。含有音訊位元組的部分為 inline_data。

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

根據圖片生成音樂

Lyria 3.5 支援多模態輸入，您最多可以提供 10 張圖片和文字提示詞，模型會根據視覺內容創作音樂。

Python

from PIL import Image

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

response = client.models.generate_content(
    model="lyria-3.5",
    contents=[
        "An atmospheric ambient track inspired by the mood and "
        "colors in this image.",
        image,
    ],
)

JavaScript

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

const response = await ai.models.generateContent({
  model: "lyria-3.5",
  contents: [
    { text: "An atmospheric ambient track inspired by the mood " +
            "and colors in this image." },
    {
      inlineData: {
        mimeType: "image/jpeg",
        data: base64Image,
      },
    },
  ],

});

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-3.5",
    contents,
    nil,
)

Java

GenerateContentResponse response = client.models.generateContent(
    "lyria-3.5",
    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")));

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3.5: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>\"
            }
          }
      ]
    }]
  }"

C#

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3.5",
  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")
  }
);

提供自訂歌詞

你可以自行撰寫歌詞，並加入提示。使用 [Verse]、[Chorus] 和 [Bridge] 等區段標記，協助模型瞭解歌曲結構：

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-3.5",
    contents=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 response = await ai.models.generateContent({
  model: "lyria-3.5",
  contents: prompt,

});

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-3.5",
    genai.Text(prompt),
    nil,
)

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-3.5",
    prompt);

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-3.5",
  contents: prompt
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3.5: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: ..."}
      ]
    }]
  }'

控制時間和結構

你可以使用時間戳記，在歌曲的特定時間點指定要執行的動作。這項功能可控制樂器進入的時間、歌詞的傳送時間，以及歌曲的進展方式：

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-3.5",
    contents=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 response = await ai.models.generateContent({
  model: "lyria-3.5",
  contents: prompt,

});

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-3.5",
    genai.Text(prompt),
    nil,
)

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-3.5",
    prompt);

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-3.5",
  contents: prompt
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3.5:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "[0:00 - 0:10] Intro: ..."}
      ]
    }]
  }'

生成配樂

如要製作背景音樂、遊戲配樂，或任何不需要人聲的用途，可以提示模型製作純音樂曲目：

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.",
)

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.",

});

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."),
    nil,
)

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.");

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."
);

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."}
      ]
    }]
  }'

生成不同語言的音樂

Lyria 3.5 會以提示詞的語言生成歌詞。如要生成法文歌詞的歌曲，請用法文撰寫提示。模型會根據語言調整語音風格和發音。

Python

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

JavaScript

const response = await ai.models.generateContent({
  model: "lyria-3.5",
  contents: "Crée une chanson pop romantique en français sur un " +
            "coucher de soleil à Paris. Utilise du piano et de " +
            "la guitare acoustique.",

});

Go

result, err := client.Models.GenerateContent(
    ctx,
    "lyria-3.5",
    genai.Text("Crée une chanson pop romantique en français sur un " +
               "coucher de soleil à Paris. Utilise du piano et de " +
               "la guitare acoustique."),
    nil,
)

Java

GenerateContentResponse response = client.models.generateContent(
    "lyria-3.5",
    "Crée une chanson pop romantique en français sur un "
        + "coucher de soleil à Paris. Utilise du piano et de "
        + "la guitare acoustique.");

C#

var response = await client.Models.GenerateContentAsync(
  model: "lyria-3.5",
  contents: "Crée une chanson pop romantique en français sur un " +
            "coucher de soleil à Paris. Utilise du piano et de " +
            "la guitare acoustique."
);

REST

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/lyria-3.5: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."}
      ]
    }]
  }'

模型智慧

Lyria 3.5 會分析提示程序，模型會根據提示，推論音樂結構 (前奏、主歌、副歌、橋段等)。這項程序會在生成音訊前執行，確保結構一致性和音樂性。

Interactions API

您可以使用 Interactions API 搭配 Lyria 3.5 模型，這個 API 是與 Gemini 模型和代理程式互動的統一介面。可簡化複雜多模態用途的狀態管理和長時間執行的工作。

Python

import base64
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="lyria-3.5",
    input="A melancholic jazz fusion track in D minor, " +
          "featuring a smooth saxophone melody, walking bass line, " +
          "and complex drum rhythms.",
)

generated_audio = interaction.output_audio
if generated_audio:
    with open("interaction_output.mp3", "wb") as f:
        f.write(base64.b64decode(generated_audio.data))
    print("Audio saved to interaction_output.mp3")

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-3.5',
  input: 'A melancholic jazz fusion track in D minor, ' +
         'featuring a smooth saxophone melody, walking bass line, ' +
         'and complex drum rhythms.',
});

const generatedAudio = interaction.output_audio;
if (generatedAudio) {
  fs.writeFileSync('interaction_output.mp3', Buffer.from(generatedAudio.data, 'base64'));
  console.log('Audio saved to interaction_output.mp3');
}

const lyrics = interaction.output_text;
if (lyrics) {
  console.log(`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-3.5",
    "input": "A melancholic jazz fusion track in D minor, featuring a smooth saxophone melody, walking bass line, and complex drum rhythms."
}'

提示指南

如要瞭解如何為音樂類型、樂器、歌曲結構、自訂歌詞和演唱風格撰寫有效的提示詞，請參閱 Lyria 提示詞指南。

最佳做法

先使用 Clip 進行疊代。使用速度較快的 lyria-3-clip-preview 模型實驗提示詞，再使用 lyria-3.5 生成完整長度的內容。
提供清楚明確的說明，籠統的提示詞只會產出一般結果。提及樂器、BPM、調性、情境和結構，以獲得最佳輸出內容。
語言要相符。以所需語言輸入提示。
使用章節標記。[Verse]、[Chorus]、[Bridge] 標記可為模型提供明確的結構。
將歌詞與操作說明分開。提供自訂歌詞時，請清楚區分歌詞和音樂方向指令。

限制

安全性：所有提示都會經過安全篩選器檢查。系統會封鎖觸發篩選器的提示。包括要求特定藝人聲音的提示，或是生成受著作權保護的歌詞。
浮水印：所有生成的音訊都會加上 SynthID 音訊浮水印，方便識別。這種浮水印人耳無法辨識，不會影響聆聽體驗。
多輪遞進編輯：音樂生成是單輪程序。目前版本的 Lyria 3.5 不支援透過多個提示，反覆編輯或修正生成的片段。
長度：Clip 模型一律會生成 30 秒的短片。Pro 模型會生成幾分鐘的歌曲，確切時長取決於提示。
決定性：即使使用相同提示，每次通話的結果也可能不同。

後續步驟

查看 Lyria 3.5 模型的定價。
使用 Lyria RealTime 即時生成串流音樂。
使用 TTS 模型生成多人對話。
瞭解如何生成圖片或影片。
瞭解 Gemini 如何解讀音訊檔案。
使用 Live API 與 Gemini 即時對話。