Lyria 3 是 Google 的音乐生成模型系列，可通过 Gemini API 使用。借助 Lyria 3，您可以根据文本提示或图片生成高质量的 48 kHz 立体声音频。这些模型可提供结构一致性，包括人声、同步歌词和完整的器乐编曲。
Lyria 3 系列包含两款型号：
| 型号 | 模型 ID | 适用场景 | 时长 | 输出 |
|---|---|---|---|---|
| Lyria 3 片段 | lyria-3-clip-preview |
短视频、循环播放、预览 | 30 秒 | MP3 |
| Lyria 3 Pro | lyria-3-pro-preview |
包含主歌、副歌和桥段的完整歌曲 | 几分钟（可通过提示控制） | MP3、WAV |
这两种模型均可通过标准 generateContent 方法和新的 Interactions API 使用，支持多模态输入（文本和图片），并生成 48kHz 高保真立体声音频。
生成音乐片段
Lyria 3 Clip 模型始终生成 30 秒的片段。如需生成剪辑，请调用 generateContent 方法并将 response_modalities 设置为 ["AUDIO", "TEXT"]。添加 TEXT 后，您可以在音频旁边接收生成的歌词或歌曲结构。
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");
}
}
}
}
生成完整歌曲
使用 lyria-3-pro-preview 模型生成时长为几分钟的完整歌曲。Pro 模型可以理解音乐结构，并创作出具有不同主歌、副歌和桥段的乐曲。您可以在提示中指定时长（例如“创作一首 2 分钟的歌曲”），也可以使用时间戳来定义结构，从而影响时长。
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
);
解析响应
来自 Lyria 3 的响应包含多个部分。文本部分包含生成的歌词或歌曲结构的 JSON 说明。带有 inline_data 的部分包含音频字节。
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
根据图片生成音乐
Lyria 3 支持多模态输入，您最多可以提供 10 张图片以及文本提示，模型将根据视觉内容创作音乐。
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
);
提供自定义歌词
您可以自行撰写歌词，并将其添加到提示中。使用 [Verse]、[Chorus] 和 [Bridge] 等部分标记来帮助模型了解歌曲结构：
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"]
}
}'
控制时间和结构
您可以使用时间戳精确指定歌曲中特定时刻发生的情况。这有助于控制乐器何时进入、歌词何时出现以及歌曲的进度：
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"]
}
}'
生成纯音乐轨道
对于背景音乐、游戏配乐或不需要人声的任何使用场景，您可以提示模型生成纯乐器曲目：
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.",
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"]
}
}'
生成不同语言的音乐
Lyria 3 会根据提示的语言生成歌词。如需生成带有法语歌词的歌曲，请使用法语撰写提示。模型会调整其发音风格和发音，以匹配相应语言。
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"]
}
}'
模型智能
Lyria 3 会分析您的提示流程，其中模型会根据您的提示推断音乐结构（前奏、主歌、副歌、桥段等）。此过程在生成音频之前进行，可确保结构连贯性和音乐性。
Interactions API
您可以使用 Interactions API（用于与 Gemini 模型和代理交互的统一接口）来使用 Lyria 3 模型。它可简化复杂多模态用例的状态管理和长时间运行的任务。
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"]
}'
提示指南
提示越具体，结果就越好。以下是您可以添加的内容，以指导生成：
- 类型：指定一种类型或多种类型的混合（例如“低保真嘻哈”“爵士融合”“电影管弦乐”）。
- 乐器：指明具体乐器（例如“Fender Rhodes 钢琴”“滑棒吉他”“TR-808 鼓机”）。
- BPM：设置节奏（例如“120 BPM”“70 BPM 左右的慢节奏”）。
- 调/音阶：指定音乐调（例如“G 大调”“D 小调”）。
- 情绪和氛围：使用描述性形容词（例如“怀旧”“激进”“空灵”“梦幻”）。
- 结构：使用
[Verse]、[Chorus]、[Bridge]、[Intro]、[Outro]等标记或时间戳来控制歌曲的播放进度。 - 时长：Clip 模型始终生成 30 秒的片段。对于 Pro 模型，请在提示中指定所需的时长（例如，“创作一首 2 分钟的歌曲”），或使用时间戳来控制时长。
示例提示
以下是一些有效提示的示例：
"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."
最佳做法
- 先使用 Clip 进行迭代。使用速度更快的
lyria-3-clip-preview模型来测试提示，然后再使用lyria-3-pro-preview生成完整内容。 - 内容要具体。模糊的提示会生成一般性的结果。提及乐器、BPM、调、基调和结构，以获得最佳输出效果。
- 语言匹配。使用您想要的歌词语言发出提示。
- 使用部分标记。
[Verse]、[Chorus]、[Bridge]标记为模型提供了清晰的结构，以便模型遵循。 - 将歌词与说明分开。提供自定义歌词时，请务必将其与音乐指导说明分开。
限制
- 安全性：所有提示都会经过安全过滤器的检查。触发过滤条件的提示将被屏蔽。这包括要求使用特定音乐人的声音或生成受版权保护的歌词的提示。
- 水印：所有生成的音频都包含 SynthID 音频水印，以便进行识别。这种水印人耳无法察觉，不会影响聆听体验。
- 多轮编辑：音乐生成是一个单轮过程。 在当前版本的 Lyria 3 中，不支持通过多个提示迭代编辑或优化生成的剪辑。
- 时长：Clip 模型始终生成 30 秒的片段。Pro 模型生成的歌曲时长为几分钟；确切时长会受到提示的影响。
- 确定性：即使使用相同的提示，不同调用之间的结果也可能会有所不同。