Music generation

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Sample output

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Pick a model

• Background / UI / ad beds → Lyria (instrumental, cheap, fast).
• Songs with lyrics, creator content → Suno.
• Sound effects, short stingers → Suno V5 sounds operation.

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Prompting that renders

[mood/energy], [genre/style], [key instruments], [production notes], [tempo/key if needed]

Example that works:
Bright, optimistic indie-pop,
ukulele and warm acoustic guitar,
hand-claps and soft kick drum, whistled melody,
modern clean mix,
around 110 BPM, major key, no vocals

• Say “no vocals” explicitly when you want an instrumental — Suno defaults to vocals.
• Reference era + region for style anchoring (”90s British trip-hop”, “early-2000s West Coast hip-hop”).
• Describe production, not just genre — “lo-fi tape warmth, sidechained pad, shuffled hi-hat” lands better than “chill beat”.
• Specify BPM when it matters (ads, workouts). Models don’t always honour it, but without you get unpredictable tempo.
• Avoid copyrighted artist names. Use stylistic descriptors instead (“operatic rock anthem in the vein of stadium classics”, not “in the style of Queen”).

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Async like video

import time

def generate_music(prompt: str, model: str = "suno-v4") -> dict:
    job = client.post("/v1/music/generations", json={
        "model": model,
        "prompt": prompt,
        "duration_seconds": 60,
    }).json()

    while True:
        status = client.get(f"/v1/music/generations/{job['job_id']}").json()
        if status["status"] == "completed":
            return status["result"]
        if status["status"] == "failed":
            raise RuntimeError(status.get("error"))
        time.sleep(5)

• Lyria clip (30 s): ~20–40 s
• Lyria pro (2 min): ~60–120 s
• Suno full song (3 min): ~60–90 s

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Suno custom mode

job = client.post("/v1/music/generations", json={
    "model": "suno-v5",
    "prompt": "Upbeat product launch anthem",
    "custom_mode": True,
    "title": "We Ship",
    "style": "Stadium pop-rock, anthemic",
    "lyrics": "[Verse 1]\nToday we push it live ...\n[Chorus]\nWe ship, we ship ...",
    "instrumental": False,
    "vocal_gender": "f",
    "negative_tags": "Heavy Metal, Screaming",
    "duration_seconds": 120,
}).json()

• custom_mode: true — unlocks title, style, lyrics
• style — genre/style string (max 1000 chars)
• lyrics — bring your own lyrics (max ~5000 chars), use [Verse] / [Chorus] / [Bridge] section tags for structure
• instrumental: true — generate without vocals even with lyrics supplied
• vocal_gender — m or f
• negative_tags — styles to steer away from
• style_weight, weirdness_constraint, audio_weight — 0.0–1.0 dials
• persona_id + persona_model — reuse a stylistic or vocal persona

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Operation modes (Suno)

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Persistence

import httpx
mp3 = httpx.get(result["data"][0]["url"]).content
f = client.files.create(file=("track.mp3", mp3), purpose="user_data")
# Now f.id is a forever-stable handle

import base64
if "b64_audio" in track:
    open("track.mp3", "wb").write(base64.b64decode(track["b64_audio"]))

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Costs at a glance

• Lyria 3 clip: ~10 credits per 30 s
• Lyria 3 pro: ~25 credits per minute
• Suno v4: ~30 credits per minute
• Suno v5: ~40 credits per minute
• Vocal removal (separate_vocal): ~10 credits; split_stem (up to 12 stems): ~30 credits

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Formats

• Default: mp3 (~128–192 kbps, universally supported, small enough to stream).
• wav is supported on Lyria 3 Pro and all Suno models — use for post-production editing only, files are ~10× larger.

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Pitfalls

• Non-English prompts to Lyria → 400 with a clear message. Translate or use Suno instead.
• Copyrighted artists/songs — refusal from upstream; not retryable by fallback. Describe the sound, not the artist.
• Suno instrumental: true + lyrics provided — lyrics are ignored, the track is instrumental. Don’t pay for generation that ignores a key input; set one or the other.
• Polling too fast — stick to 5-second intervals. Faster polling won’t speed up generation, it’ll just eat your RPM.
• Storing 5-minute tracks as base64 in JSON — the gateway already offloads to GCS and returns url; always prefer url over b64_audio when both are present.