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Music

Organization
elevenlabs
music

Generate music using ElevenLabs Music API. Use when creating instrumental tracks, songs with lyrics, background music, jingles, or any AI-generated music composition. Supports prompt-based generation, composition plans for granular control, and detailed output with metadata.

Overview

Publisherelevenlabs
Repositoryskills
Skill namemusic
Stars
462
Forks
75
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by elevenlabs on GitHub. Read the source before you install it.

Installation

Install the Music AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/elevenlabs/skills/tree/main/music
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/elevenlabs/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/music .claude/skills/music
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Music in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Music on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Music is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ElevenLabs Music Generation

Generate music from text prompts - supports instrumental tracks, songs with lyrics, and fine-grained control via composition plans.

Setup: See Installation Guide. For JavaScript, use @elevenlabs/* packages only.

All examples below use music_v2_5, the most advanced generation model. Pass music_v2 or music_v1 only when an older model is explicitly requested.

Quick Start

Python

python
from elevenlabs import ElevenLabs

client = ElevenLabs()

audio = client.music.compose(
    prompt="A chill lo-fi hip hop beat with jazzy piano chords",
    music_length_ms=30000,
    model_id="music_v2_5",
)

with open("output.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)

TypeScript

typescript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createWriteStream } from "fs";

const client = new ElevenLabsClient();
const audio = await client.music.compose({
  prompt: "A chill lo-fi hip hop beat with jazzy piano chords",
  musicLengthMs: 30000,
  modelId: "music_v2_5",
});
audio.pipe(createWriteStream("output.mp3"));

CLI

bash
elevenlabs music compose \
  --prompt "A chill lo-fi beat" \
  --music-length-ms 30000 \
  --model-id music_v2_5 \
  --output output.mp3

Methods

MethodDescription
music.composeGenerate audio from a prompt or composition plan
music.streamStream audio chunks as they are generated (paid plans)
music.composition_plan.createGenerate a structured plan for fine-grained control
music.compose_detailedGenerate audio + composition plan + metadata; pass store_for_inpainting=True to enable inpainting
music.compose_detailed_streamStream audio plus composition plan, metadata, and optional word timestamps as Server-Sent Events
music.video_to_musicGenerate background music from one or more uploaded video files
music.uploadUpload an audio file for later inpainting workflows, optionally extracting its composition plan or word-level timestamps
music.finetunes.listList accessible music finetunes
music.finetunes.createTrain a music finetune from uploaded audio
music.finetunes.getRetrieve finetune status and metadata
music.finetunes.updateUpdate finetune metadata or visibility
music.finetunes.deleteDelete a music finetune

See API Reference for full parameter details.

music.upload is available to enterprise clients with access to the inpainting feature.

Music Finetunes

Create a finetune from training audio with POST /v1/music/finetunes, then poll the get endpoint until its status is completed. Pass the returned id as finetune_id when composing music.

Use the list, update, and delete endpoints to manage accessible finetunes.

Video to Music

Generate background music from uploaded video clips via POST /v1/music/video-to-music (client.music.video_to_music). This is separate from prompt-based music.compose (POST /v1/music).

The API combines videos in order, accepts an optional natural-language description, and lets you steer style with up to 10 tags such as upbeat or cinematic. This endpoint still defaults to music_v1; pass model_id="music_v2_5" to use the most advanced model.

Python

python
from elevenlabs import ElevenLabs

client = ElevenLabs()

audio = client.music.video_to_music(
    videos=["trailer.mp4"],
    description="Build suspense, then resolve with a warm cinematic finish.",
    tags=["cinematic", "suspenseful", "uplifting"],
    model_id="music_v2_5",
)

with open("video-score.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)

TypeScript

typescript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createReadStream, createWriteStream } from "fs";

const client = new ElevenLabsClient();

const audio = await client.music.videoToMusic({
  videos: [createReadStream("trailer.mp4")],
  description: "Build suspense, then resolve with a warm cinematic finish.",
  tags: ["cinematic", "suspenseful", "uplifting"],
  modelId: "music_v2_5",
});

audio.pipe(createWriteStream("video-score.mp3"));

CLI

bash
elevenlabs music video_to_music \
  --videos trailer.mp4 \
  --description "Build suspense, then resolve with a warm cinematic finish." \
  --tags cinematic \
  --model-id music_v2_5 \
  --output video-score.mp3

The CLI currently accepts one --videos file and one --tags value per request; use the Python or TypeScript SDK to send multiple videos or tags.

Constraints from the current API schema:

  • Upload 1-10 video files per request
  • Keep total combined upload size at or below 200 MB
  • Keep total combined video duration at or below 600 seconds
  • Use description for high-level musical direction and tags for concise style cues

Composition Plans

music_v2_5 composition plans are an ordered list of chunks. Each chunk specifies its own text (section label, lyrics, inline cues), duration_ms, positive_styles, negative_styles, and context_adherence (low, medium, or high, default high). Up to 30 chunks per plan, each 3,000–120,000 ms, total length 3 s to 10 minutes. Each chunk's text supports up to 6,132 characters, with up to 30 lines of 200 characters each.

Generate a plan first, edit it, then compose:

python
plan = client.music.composition_plan.create(
    prompt="An epic orchestral piece building to a climax",
    music_length_ms=60000,
    model_id="music_v2_5",
)

# Edit chunks in place
plan["chunks"][0]["text"] = "[Intro]\nQuiet strings rising"

audio = client.music.compose(
    composition_plan=plan,
    model_id="music_v2_5",
)
typescript
const plan = await client.music.compositionPlan.create({
  prompt: "An epic orchestral piece building to a climax",
  musicLengthMs: 60000,
  modelId: "music_v2_5",
});

plan.chunks[0].text = "[Intro]\nQuiet strings rising";

const audio = await client.music.compose({
  compositionPlan: plan,
  modelId: "music_v2_5",
});

Or hand-build a plan to control lyrics and style per section:

python
composition_plan = {
    "chunks": [
        {
            "text": "[Verse]\nWalking down an empty street",
            "duration_ms": 15000,
            "positive_styles": ["pop", "upbeat", "female vocals", "acoustic guitar"],
            "negative_styles": ["dark", "slow"],
            "context_adherence": "high",
        },
        {
            "text": "[Chorus]\nThis is my moment",
            "duration_ms": 15000,
            "positive_styles": ["powerful vocals", "full band"],
            "negative_styles": [],
            "context_adherence": "high",
        },
    ]
}

audio = client.music.compose(composition_plan=composition_plan, model_id="music_v2_5")
typescript
const compositionPlan = {
  chunks: [
    {
      text: "[Verse]\nWalking down an empty street",
      durationMs: 15000,
      positiveStyles: ["pop", "upbeat", "female vocals", "acoustic guitar"],
      negativeStyles: ["dark", "slow"],
      contextAdherence: "high",
    },
    {
      text: "[Chorus]\nThis is my moment",
      durationMs: 15000,
      positiveStyles: ["powerful vocals", "full band"],
      negativeStyles: [],
      contextAdherence: "high",
    },
  ],
};

const audio = await client.music.compose({
  compositionPlan,
  modelId: "music_v2_5",
});

Put broader characteristics (genre, instrumentation, vocal style) in positive_styles, not in text. The first chunk's styles set the overall tone — include 6–7 styles there.

Output Formats

Use the output_format query parameter on compose, detailed compose, or stream requests to select the generated audio format. auto chooses a model-appropriate MP3 format; for music_v2 and music_v2_5, it selects mp3_48000_192. Higher-bitrate MP3 options include mp3_48000_240 and mp3_48000_320.

Streaming

For paid plans, stream audio chunks as they are generated instead of waiting for the full file:

python
from io import BytesIO

stream = client.music.stream(
    prompt="A driving synthwave track with arpeggiated leads",
    music_length_ms=30000,
    model_id="music_v2_5",
)

buffer = BytesIO()
for chunk in stream:
    if chunk:
        buffer.write(chunk)
typescript
const stream = await client.music.stream({
  prompt: "A driving synthwave track with arpeggiated leads",
  musicLengthMs: 30000,
  modelId: "music_v2_5",
});

const chunks: Buffer[] = [];
for await (const chunk of stream) {
  chunks.push(chunk);
}

Detailed streaming

Use detailed streaming when the application needs generated music metadata while audio is still arriving. POST /v1/music/detailed/stream accepts the same prompt or composition-plan body as detailed compose, streams text/event-stream, and can include word timestamps with with_timestamps.

bash
elevenlabs music compose_detailed_stream \
  --prompt "A bright indie pop hook with warm guitars" \
  --music-length-ms 30000 \
  --model-id music_v2_5 \
  --with-timestamps true \
  --output-format auto

Inpainting

Inpainting edits or extends a stored song by mixing audio reference chunks (unchanged slices of a stored song) with new generation chunks in a single composition plan.

Step 1 — get a song_id, either by storing a fresh generation or uploading existing audio:

python
# Option A: keep a generation for later editing
result = client.music.compose_detailed(
    prompt="An upbeat pop song with verse and chorus",
    music_length_ms=60000,
    model_id="music_v2_5",
    store_for_inpainting=True,
)
song_id = result.song_id

# Option B: upload an existing track and extract its plan
uploaded = client.music.upload(
    file=open("my-song.mp3", "rb"),
    extract_composition_plan="music_v2_5",
)
song_id = uploaded.song_id
composition_plan = uploaded.composition_plan
typescript
import { createReadStream } from "fs";

// Option A: keep a generation for later editing
const result = await client.music.composeDetailed({
  prompt: "An upbeat pop song with verse and chorus",
  musicLengthMs: 60000,
  modelId: "music_v2_5",
  storeForInpainting: true,
});
let songId = result.songId;

// Option B: upload an existing track and extract its plan
const uploaded = await client.music.upload({
  file: createReadStream("my-song.mp3"),
  extractCompositionPlan: "music_v2_5",
});
songId = uploaded.songId;
const compositionPlan = uploaded.compositionPlan;

Step 2 — compose a plan that references the stored audio and regenerates the part you want to change:

python
plan = {
    "chunks": [
        {"song_id": song_id, "range": {"start_ms": 0, "end_ms": 30000}},
        {
            "text": "[Chorus]\nWe're rising up tonight",
            "duration_ms": 30000,
            "positive_styles": ["bigger drums", "layered vocals", "anthemic"],
            "negative_styles": ["sparse"],
            "context_adherence": "high",
        },
    ]
}

audio = client.music.compose(composition_plan=plan, model_id="music_v2_5")
typescript
const plan = {
  chunks: [
    { songId, range: { startMs: 0, endMs: 30000 } },
    {
      text: "[Chorus]\nWe're rising up tonight",
      durationMs: 30000,
      positiveStyles: ["bigger drums", "layered vocals", "anthemic"],
      negativeStyles: ["sparse"],
      contextAdherence: "high",
    },
  ],
};

const audio = await client.music.compose({
  compositionPlan: plan,
  modelId: "music_v2_5",
});

To match the feel of a stored slice without copying it, attach a conditioning_ref (up to 30,000 ms) plus a condition_strength of low, medium, high, or xhigh to a generation chunk. Conditioning placed on the first chunk influences every later chunk.

See API Reference for the full inpainting parameter list.

Content Restrictions

  • Cannot reference specific artists, bands, or copyrighted lyrics
  • bad_prompt errors include a prompt_suggestion with alternative phrasing
  • bad_composition_plan errors include a composition_plan_suggestion

Error Handling

python
try:
    audio = client.music.compose(prompt="...", music_length_ms=30000)
except Exception as e:
    print(f"API error: {e}")
typescript
try {
  const audio = await client.music.compose({
    prompt: "...",
    musicLengthMs: 30000,
  });
} catch (err) {
  console.error("API error:", err);
}

Common errors: 401 (invalid key), 422 (invalid params), 429 (rate limit).

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Music AI skill do?

Generate music using ElevenLabs Music API. Use when creating instrumental tracks, songs with lyrics, background music, jingles, or any AI-generated music composition. Supports prompt-based generation, composition plans for granular control, and detailed output with metadata.

Why use Music on TypingMind?

Because you install it once and use it with any model. Music is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Music in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/elevenlabs/skills/tree/main/music. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Music?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Music?

As many as you like. As long as a model supports skills, you can use Music with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Music AI skill free?

Yes. It is published on GitHub by elevenlabs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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