Live Ozan Radio

Personal AI radio — no catalog music, ever. DeepSeek is the DJ. Google Lyria 3 composes every track. Taste comes from settings.json + taste_seeds.json — usually built from Spotify screenshots in Cursor (no Spotify API).

Inspired by Magenta RealTime 2 (live, ~200ms) and Lyria 3 (full songs via Gemini API). On Mac you can layer MRT2 for true live improvisation; this repo ships the cross-platform Lyria + DeepSeek stack first.

Stack

Layer	Product	Role
DJ brain	DeepSeek (Tinqs proxy or BYOK)	Mood, prompts, chat, variety
Music engine	Google Lyria 3 Pro / Clip	Generate MP3 tracks
Taste	settings.json + taste_seeds.json	Profile from screenshots or manual edit — see below
Player	FastAPI + gateway/player.html	Stream queue, library, chat, dashboard
Live (optional)	Magenta RealTime 2	Apple Silicon only — see below

Player dashboard

Open http://127.0.0.1:8787/player after starting the server.

Feature	What it does
Cost dashboard	Today's estimated spend, per-track cost, songs generated vs daily cap
Settings (gear icon)	Shuffle mode, mix saved + new tracks, new-song chance, max songs/day
Shuffle mode	On track end or Skip, picks a random saved song or composes a new one
Saved songs	Click any track in the library to play
DJ chat	Talk to DeepSeek — requests can trigger new Lyria generations

Shuffle behaviour

When shuffle is on (default):

1. If you have saved songs and daily quota remains, each next track has a new_song_chance (default 35%) of being freshly composed.
2. Otherwise a random saved song plays (never the same track twice in a row if alternatives exist).
3. If the library is empty, it generates until the daily cap is hit.

Daily generation stats live in songs/stats.json (gitignored, local runtime only).

Taste from Spotify screenshots (recommended)

No Spotify API keys. Screenshot your library (Home, Daily Mixes, playlists), open this repo in Cursor, attach images, and paste the prompt from docs/TASTE-FROM-SCREENSHOTS.md. The agent updates settings.json and taste_seeds.json.

Share that doc with friends — same flow for group taste (WhatsApp links + screenshots).

Taste (settings.json)

Edit settings.json at the repo root, or let Cursor fill it from screenshots. The DJ reloads it on every generate and chat.

{
  "taste": { "summary": "...", "genres": [], "mood": [], "instruments": [] },
  "playback": {
    "shuffle": true,
    "mix_existing_and_new": true,
    "new_song_chance": 0.35
  },
  "limits": { "max_new_songs_per_day": 10 },
  "costs": {
    "lyria_pro_usd": 0.08,
    "lyria_clip_usd": 0.04,
    "deepseek_per_track_usd": 0.002
  }
}

Example profile (Ozan): checked-in settings.json + taste_seeds.json — Anadolu psych + ethnic dubtronica from Spotify screenshots. Copy the structure for your own taste.

The player settings panel PATCHes playback and limits via /api/settings and writes back to this file.

Saved songs

Every track is written to ./songs/ and committed via Git LFS (audio) + plain git (metadata):

File	Storage	Contents
{id}_{title}.mp3	LFS	Audio
{id}.meta.json	git	Title, mood, DJ line, prompt, lyrics, timestamp
manifest.json	gitignored	Runtime queue index

Browse in the player under Saved songs, or GET /api/songs. After clone: git lfs install then git lfs pull.

Quick start (Forge / Windows)

cd live-ozan-radio
python -m venv .venv
.venv\Scripts\activate
pip install -e .
copy .env.example .env
# Fill GEMINI_API_KEY + DEEPSEEK_API_KEY
# Taste: docs/TASTE-FROM-SCREENSHOTS.md (Cursor + Spotify screenshots)

$env:DEEPSEEK_BASE_URL = "https://api.deepseek.com/v1"
python -m ozan_radio serve
# Open http://127.0.0.1:8787/player

One-shot track (no server):

python -m ozan_radio generate

Environment

Variable	Required	Notes
GEMINI_API_KEY	Yes	Google AI Studio — Lyria 3
DEEPSEEK_API_KEY	Yes	Tinqs proxy token or DeepSeek direct
DEEPSEEK_BASE_URL	No	Default https://api.deepseek.com/v1
LYRIA_MODEL	No	lyria-3-pro-preview (default) or lyria-3-clip-preview
RADIO_OUTPUT_DIR	No	Default ./songs

Cost estimates (defaults)

Model	~USD / track
Lyria 3 Pro + DeepSeek	~$0.082
Lyria 3 Clip	~$0.04

At the default cap of 10 new songs/day with Lyria Pro, projected max spend is ~$0.82/day. Adjust costs and limits in settings.json or the player settings panel.

API

Method	Path	Description
GET	/api/now	Current track metadata
GET	/api/queue	Full queue
GET	/api/stats	Dashboard: today's spend, quota, cost estimates
GET	/api/settings	Playback, limits, costs
PATCH	/api/settings	Update shuffle, daily cap, etc.
POST	/api/generate	DJ plans + Lyria renders next track
POST	/api/shuffle/next	Smart next: library shuffle or new generation
POST	/api/skip	Advance (uses shuffle when enabled)
GET/POST	/api/chat	DJ chat log and messages
GET	/api/songs	Saved library
POST	/api/songs/{id}/play	Play a saved track
GET	/stream/{file}	MP3 stream
GET	/player	Web UI

Magenta RealTime 2 (optional live layer)

On Apple Silicon (Kraken), install magenta-rt for sub-second live generation:

uv pip install "magenta-rt[mlx]"
mrt models init && mrt models download
mrt mlx generate --prompt "disco funk" --duration 4.0 --model=mrt2_small

Wire MRT2 as a bridge between tracks or as a live “bed” under the Lyria queue — PRs welcome.

Repo

Public on Git Studio: https://tinqs.com/tinqs/live-radio

git clone git@ssh.tinqs.com:tinqs/live-radio.git
cd live-radio
git lfs install && git lfs pull

Static player preview: https://tinqs.com/tinqs/live-radio/src/branch/main/gateway/player.html (shell only — audio streams from your running server).

Agent usage

DeepSeek (Pi, Cursor, Claude Code) can operate the station via HTTP or the skill in .cursor/skills/ozan-radio/SKILL.md.

License

Apache 2.0 — same spirit as Magenta RealTime 2 open weights.