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Spotify is kept for exactly what works there:\n * mapping Last.fm tracks to real Spotify track URIs (via search) and writing\n * them to a Spotify playlist.\n */\nexport interface Axis {\n label: string;\n value: number; // 0..1\n}\n\nexport type Profile = Axis[];\n\nexport interface TrackInfo {\n name: string;\n uri: string; // Spotify track uri (may be empty until searched)\n previewUrl: string | null;\n}\n\nexport interface DiscoveredArtist {\n id: string; // artist name (used as key)\n name: string;\n images: { url: string }[];\n popularity: number; // 0..100 (log-scaled listener count = obscurity)\n listeners: number;\n genres: string[]; // Last.fm tags\n match: number; // Last.fm similarity 0..1\n radar: Profile;\n tracks: TrackInfo[];\n}\n\nconst LASTFM_SEEDS = 4; // how many of your top artists we crawl\nconst SIMILAR_LIMIT = 30; // similar artists per seed\nconst FINALISTS = 32; // how many get tags+listeners fetched\nconst LOG_MAX = 7; // listeners log base (1e7 ≈ huge artist)\n\n/** `me/top/artists` names (used as Last.fm discovery seeds). */\nasync function topArtistNames(user: StoredUser): Promise {\n const top = await api<{ items: { name: string }[] }>(\n user,\n \"me/top/artists?time_range=medium_term&limit=30\",\n );\n return top.items.map((a) => a.name).filter(Boolean);\n}\n\n/**\n * Taste profile from Last.fm tags across your top artists. The axes become the\n * radar, the direction chips, and the similarity match for discovery.\n */\nexport async function computeProfile(user: StoredUser): Promise {\n const names = (await topArtistNames(user)).slice(0, 8);\n const counts = new Map();\n await Promise.allSettled(names.map(async (n) => {\n const tags = await getTopTags(n);\n for (const t of tags) counts.set(t, (counts.get(t) ?? 0) + 1);\n }));\n const ranked = [...counts.entries()].sort((a, b) => b[1] - a[1]).slice(0, 6);\n const max = ranked.length ? ranked[0][1] : 1;\n return ranked.map(([label, count]) => ({ label, value: count / max }));\n}\n\nexport interface DiscoverOptions {\n /** Last.fm tags to constrain discovery to. Default: profile tags. */\n genres?: string[];\n /** 0..1 — how obscure to go. Higher = prefer more listeners-poor artists. */\n obscurity?: number;\n /** 0..1 — randomizes which seeds/ordering, so \"explore more\" varies. */\n seed?: number;\n /** Max artists to return. Default 40 (capped by track-mapping success). */\n limit?: number;\n /** Representive tracks per artist to map to Spotify. */\n tracksPerArtist?: number;\n}\n\nfunction logNorm(listeners: number): number {\n return Math.max(0, Math.min(1, Math.log10(listeners + 1) / LOG_MAX));\n}\n\n/** Map a Last.fm artist + track name to a Spotify track uri via search. */\nasync function toSpotifyUri(user: StoredUser, artist: string, track: string): Promise {\n try {\n const res = await api<{ tracks: { items: { uri: string }[] } }>(\n user,\n `search?q=${encodeURIComponent(`track:\"${track}\" artist:\"${artist}\"`)}&type=track&limit=1&market=US`,\n );\n return res.tracks?.items?.[0]?.uri ?? null;\n } catch {\n return null;\n }\n}\n\n/**\n * Discover under-discovered artists close to your taste, using Last.fm.\n * 1) crawl the similar-artist graph from your top artists,\n * 2) fetch tags + listener counts for the best matches,\n * 3) rank by match and obscurity,\n * 4) map each artist's top Last.fm tracks to Spotify URIs.\n */\nexport async function discover(\n user: StoredUser,\n profile: Profile,\n opts: DiscoverOptions = {},\n): Promise {\n const seeds = (await topArtistNames(user)).slice(0, LASTFM_SEEDS);\n const profileTags = new Set(opts.genres?.length ? opts.genres : profile.map((a) => a.label));\n\n // 1. Similar-artist graph.\n const pool = new Map();\n await Promise.allSettled(seeds.map(async (seed) => {\n const { similar } = await getSimilar(seed, SIMILAR_LIMIT);\n for (const s of similar) {\n const cur = pool.get(s.name);\n if (!cur || s.match > cur.match) {\n pool.set(s.name, {\n name: s.name,\n match: s.match,\n image: bestImage(s.image) ? [{ url: bestImage(s.image)! }] : [],\n });\n }\n }\n }));\n\n // 2. Tags + listeners for the strongest matches only (bounds API load).\n let finalists = [...pool.values()].sort((a, b) => b.match - a.match).slice(0, FINALISTS);\n const details = await Promise.all(finalists.map(async (c) => {\n const [tags, info] = await Promise.all([getTopTags(c.name), getInfo(c.name)]);\n return { ...c, tags, listeners: info.listeners, image: bestImage(info.image) ? [{ url: bestImage(info.image)! }] : c.image };\n }));\n\n // 3. Rank by taste-match and obscurity.\n const obsc = Math.max(0, Math.min(1, opts.obscurity ?? 0.5));\n const lam = 0.1 + obsc * 1.1;\n const total = profile.reduce((s, a) => s + a.value, 0) || 1;\n const ranked = details\n .map((c) => {\n const hit = c.tags.reduce((s, t) => s + (profile.find((p) => p.label === t)?.value ?? 0), 0);\n const match = hit / total; // tag overlap with your taste (0..1)\n const score = match - lam * logNorm(c.listeners);\n return { c, match, score };\n })\n .filter((r) => r.match >= 0.08)\n .sort((a, b) => b.score - a.score);\n\n const limit = Math.max(6, Math.min(80, opts.limit ?? 40));\n const chosen = ranked.slice(0, limit);\n\n // 4. 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