[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_193":194,"_195":196},"routes/_app.x.$handle.$name",{"_98":97,"_32":44,"_106":88,"_27":100,"_13":14,"_107":-5,"_11":108,"_109":110,"_111":112,"_113":114,"_115":116,"_20":-5,"_117":-5,"_118":-5,"_119":25,"_120":121,"_122":123,"_124":-5,"_125":-5,"_126":127},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_42":43,"_32":44,"_37":45,"_46":-5,"_47":25,"_48":49,"_50":49,"_51":52,"_53":-5,"_18":54,"_55":56,"_57":25,"_58":-5,"_59":-5,"_60":61,"_62":63,"_64":65,"_66":67,"_68":69,"_70":-5,"_71":72,"_73":72,"_74":75,"_76":75,"_77":75,"_78":72,"_79":72,"_80":81,"_82":83,"_84":85,"_86":25},"version",11,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":25,"_27":28,"_29":28},"file",{"_30":31,"_32":28,"_33":20,"_34":36,"_37":38,"_39":14,"_40":41,"_24":25},"previous",{"_30":31,"_32":28,"_33":20,"_34":35},"deleted",false,"deletedHere","path","icon.ts","latestPath","fileId","fa39a7b2-9b65-11f1-9d8d-1607ee4eb77e","name","fileType","content","// Placeholder tile — replaced by the real countdown-leader icon in build step 6.\nexport const ICON_BASE64 =\n\"iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAIAAAAlC+aJAAAAUElEQVR42u3PQQkAAAgEsGvgxwD2T2kE38JgBZbqeS0CAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICApcFC+UwPeI84OQAAAAASUVORK5CYII=\";\n","// Reel Time icon — a film countdown leader frame. Generated by make_icon.py at\n// the project root; edit the drawing there and regenerate, never hand-edit this.\nexport const ICON_BASE64 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\";\n\nexport const ICON_180_BASE64 =\n\"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* Reel Time — seed data.\n *\n * Written into the blob once, the first time /state is read and no blob exists.\n * After that the blob is the source of truth and this file is inert history:\n * editing it does NOT change a seeded blob (see resetState in main.tsx).\n *\n * Movie ids are stable slugs and are load-bearing — ratings and order are keyed\n * by id, so changing an id orphans that film's data.\n */\n\nexport type WatchMode = \"together\" | \"either\" | \"solo\";\nexport type MediaType = \"film\" | \"doc\" | \"series\" | \"book\";\n\nexport interface Movie {\n id: string;\n title: string;\n year: number | null;\n runtimeMin: number | null;\n seasons?: string;\n type: MediaType;\n status: \"unwatched\" | \"watched\";\n watchMode: WatchMode;\n reasoning: string;\n notes: string;\n ratings: { rob: number | null; robert: number | null };\n attentionFlag: { rob: boolean; robert: boolean };\n watchedDate: string | null;\n order: number;\n}\n\n/** watched: ratings and history are known, curation reasoning is not. */\nfunction w(\n id: string, title: string, year: number | null, runtimeMin: number | null,\n type: MediaType, mode: WatchMode, rob: number | null, robert: number | null,\n flags: { rob?: boolean; robert?: boolean }, notes: string, order: number,\n): Movie {\n return {\n id, title, year, runtimeMin, type, status: \"watched\", watchMode: mode,\n reasoning: \"\", notes,\n ratings: { rob, robert },\n attentionFlag: { rob: !!flags.rob, robert: !!flags.robert },\n watchedDate: null, order,\n };\n}\n\n/** unwatched: the reasoning is the point — it is why the film is on the list. */\nfunction u(\n order: number, id: string, title: string, year: number | null,\n runtimeMin: number | null, type: MediaType, mode: WatchMode,\n reasoning: string, notes = \"\", seasons?: string,\n): Movie {\n const m: Movie = {\n id, title, year, runtimeMin, type, status: \"unwatched\", watchMode: mode,\n reasoning, notes,\n ratings: { rob: null, robert: null },\n attentionFlag: { rob: false, robert: false },\n watchedDate: null, order,\n };\n if (seasons) m.seasons = seasons;\n return m;\n}\n\nconst WATCHED: Movie[] = [\n w(\"forrest-gump-1994\", \"Forrest Gump\", 1994, 142, \"film\", \"together\", 10, 10, {}, \"Original favorite\", 1),\n w(\"good-will-hunting-1997\", \"Good Will Hunting\", 1997, 126, \"film\", \"together\", 10, 10, {}, \"Original favorite\", 2),\n w(\"interstellar-2014\", \"Interstellar\", 2014, 169, \"film\", \"together\", 10, 10, {}, \"Original favorite\", 3),\n w(\"fight-club-1999\", \"Fight Club\", 1999, 139, \"film\", \"together\", 10, 10, {}, \"Original favorite\", 4),\n w(\"the-truman-show-1998\", \"The Truman Show\", 1998, 103, \"film\", \"together\", 10, 10, {}, \"Original favorite\", 5),\n w(\"whiplash-2014\", \"Whiplash\", 2014, 106, \"film\", \"together\", 10, 10, {}, \"\", 6),\n w(\"the-martian-2015\", \"The Martian\", 2015, 144, \"film\", \"together\", 10, 10, {}, \"\", 7),\n w(\"project-hail-mary\", \"Project Hail Mary\", null, null, \"book\", \"either\", 10, null, {},\n \"Film adaptation in development (Ryan Gosling) — auto-add when released\", 8),\n w(\"the-thinking-game-2024\", \"The Thinking Game\", 2024, 84, \"doc\", \"either\", 9.5, null, {},\n \"AI doc (Hassabis/DeepMind); watched w/ wife\", 9),\n w(\"the-pursuit-of-happyness-2006\", \"The Pursuit of Happyness\", 2006, 117, \"film\", \"together\", 8, 10, {},\n \"Father-son\", 10),\n w(\"ex-machina-2014\", \"Ex Machina\", 2014, 108, \"film\", \"solo\", 8, null, {}, \"Solo watch\", 11),\n w(\"disclosure-day-2026\", \"Disclosure Day\", 2026, 140, \"film\", \"either\", 8, null, {},\n \"Spielberg; seen in theaters\", 12),\n w(\"another-earth-2011\", \"Another Earth\", 2011, 92, \"film\", \"either\", 8, null, {},\n \"Quiet indie sci-fi; solo\", 13),\n w(\"moon-2009\", \"Moon\", 2009, 97, \"film\", \"either\", 7, null, {}, \"Solo watch\", 14),\n w(\"the-social-network-2010\", \"The Social Network\", 2010, 120, \"film\", \"together\", 7, 7.5, {},\n \"Sorkin rapid-fire dialogue grated — wit as velocity, not realism\", 15),\n w(\"coherence-2013\", \"Coherence\", 2013, 89, \"film\", \"together\", 6.5, 7, { rob: true },\n \"Attention drifted (pizza night, no subtitles) — rewatch candidate\", 16),\n w(\"inception-2010\", \"Inception\", 2010, 148, \"film\", \"together\", 5, null, { rob: true },\n \"Viewing conditions, not the film — rewatch candidate\", 17),\n w(\"the-island-2005\", \"The Island\", 2005, 136, \"film\", \"either\", 4.5, null, {},\n \"Fast-forwarded; ideas traded for action\", 18),\n];\n\nconst UNWATCHED: Movie[] = [\n u(1, \"the-prestige-2006\", \"The Prestige\", 2006, 130, \"film\", \"together\",\n \"Top shared pick — twist film, full-attention night, subtitles on\"),\n u(2, \"a-beautiful-mind-2001\", \"A Beautiful Mind\", 2001, 135, \"film\", \"together\",\n \"Genius shown interior, not performed — preferred register\"),\n u(3, \"catch-me-if-you-can-2002\", \"Catch Me If You Can\", 2002, 141, \"film\", \"together\",\n \"Warm, fun, father-son undercurrent\"),\n u(4, \"alphago-2017\", \"AlphaGo\", 2017, 90, \"doc\", \"together\",\n \"Doc, free on YouTube; competition story will land with a wrestler\"),\n u(5, \"october-sky-1999\", \"October Sky\", 1999, 108, \"film\", \"together\",\n \"Intelligence via trial-and-error; father-son heart; pizza-night safe\"),\n u(6, \"the-ai-doc-2026\", \"The AI Doc\", 2026, null, \"doc\", \"together\",\n \"Doc; Altman/Hassabis/Amodei — great for Robert's AI coursework\"),\n u(7, \"no-country-for-old-men-2007\", \"No Country for Old Men\", 2007, 122, \"film\", \"either\",\n \"Nothing awkward; violent + bleak ending — pick the right night\"),\n u(8, \"there-will-be-blood-2007\", \"There Will Be Blood\", 2007, 158, \"film\", \"either\",\n \"Nothing awkward; long, slow, heavy — mood-dependent\"),\n u(9, \"zero-days-2016\", \"Zero Days\", 2016, 116, \"doc\", \"either\",\n \"Doc (Stuxnet); fine together, may skew adult-wonky\"),\n u(10, \"life-story-1987\", \"Life Story (Race for the Double Helix)\", 1987, 97, \"film\", \"either\",\n \"DNA race; hard to stream — check YouTube\"),\n u(11, \"steve-jobs-man-in-the-machine-2015\", \"Steve Jobs: The Man in the Machine\", 2015, 128, \"doc\", \"either\",\n \"Gibney doc; the Jobs story done right for this taste\"),\n u(12, \"zodiac-2007\", \"Zodiac\", 2007, 157, \"film\", \"either\",\n \"Murders depicted but not gratuitous; long procedural\"),\n u(13, \"prisoners-2013\", \"Prisoners\", 2013, 153, \"film\", \"either\",\n \"Heavy, but thematically about fatherhood — interesting shared watch\"),\n u(14, \"gattaca-1997\", \"Gattaca\", 1997, 112, \"film\", \"together\",\n \"Willpower vs destiny; nothing awkward\"),\n u(15, \"memento-2000\", \"Memento\", 2000, 113, \"film\", \"together\",\n \"Puzzle film — fun to compare notes after; full attention\"),\n u(16, \"arrival-2016\", \"Arrival\", 2016, 116, \"film\", \"together\",\n \"Cerebral + emotional; strong shared pick\"),\n u(17, \"nightcrawler-2014\", \"Nightcrawler\", 2014, 117, \"film\", \"either\",\n \"One coercive-relationship subplot, offscreen; otherwise fine\"),\n u(18, \"sicario-2015\", \"Sicario\", 2015, 121, \"film\", \"either\",\n \"Violent, morally hollow ending — tone, not appropriateness\"),\n u(19, \"game-night-2018\", \"Game Night\", 2018, 100, \"film\", \"together\",\n \"The comedy option; plays best with company\"),\n u(20, \"the-imitation-game-2014\", \"The Imitation Game\", 2014, 114, \"film\", \"together\",\n \"Some performed-wit dialogue, but fine shared watch\"),\n u(21, \"eternal-sunshine-2004\", \"Eternal Sunshine of the Spotless Mind\", 2004, 108, \"film\", \"either\",\n \"Relationship-centric; may resonate more solo, nothing awkward\"),\n u(22, \"blade-runner-1982\", \"Blade Runner\", 1982, 117, \"film\", \"either\",\n \"Brief nudity; mild — watch before 2049\"),\n u(23, \"blade-runner-2049-2017\", \"Blade Runner 2049\", 2017, 164, \"film\", \"either\",\n \"More nudity than the original; manageable, worth it\"),\n u(24, \"the-man-from-earth-2007\", \"The Man from Earth\", 2007, 87, \"film\", \"together\",\n \"All slow, deliberate dialogue — the Musk-interview register\"),\n u(25, \"big-fish-2003\", \"Big Fish\", 2003, 125, \"film\", \"together\",\n \"Father-son core; save for the right sentimental night\"),\n u(26, \"contact-1997\", \"Contact\", 1997, 150, \"film\", \"together\",\n \"Awe-driven; nothing awkward\"),\n u(27, \"rain-man-1988\", \"Rain Man\", 1988, 133, \"film\", \"together\",\n \"Nothing awkward; character-driven\"),\n u(28, \"ad-astra-2019\", \"Ad Astra\", 2019, 123, \"film\", \"either\",\n \"Father-son theme but cold/distant; emotionally muted\"),\n u(29, \"chinatown-1974\", \"Chinatown\", 1974, 130, \"film\", \"either\",\n \"Dark reveal, nothing graphic; fine for mature 15\"),\n u(30, \"parallel-2020\", \"Parallel\", 2020, 104, \"film\", \"either\",\n \"Indie multiverse; mild content\"),\n u(31, \"limitless-2011\", \"Limitless\", 2011, 105, \"film\", \"either\",\n \"Brief mild sexuality; easy watch\"),\n u(32, \"automata-2014\", \"Automata\", 2014, 109, \"film\", \"either\",\n \"Brief robot-brothel scene; mild\"),\n u(33, \"shutter-island-2010\", \"Shutter Island\", 2010, 138, \"film\", \"either\",\n \"Nothing awkward; dim/rainy palette — mood pick\"),\n u(34, \"good-night-and-good-luck-2005\", \"Good Night, and Good Luck\", 2005, 93, \"film\", \"either\",\n \"Fine together; quiet and talky\"),\n u(35, \"fahrenheit-451-1966\", \"Fahrenheit 451\", 1966, 112, \"film\", \"either\",\n \"Fine together; contemplative (two versions)\", \"Two versions: 1966 (112 min) or 2018 (100 min)\"),\n u(36, \"level-16-2018\", \"Level 16\", 2018, 102, \"film\", \"either\",\n \"Teen protagonists; fine together\"),\n u(37, \"her-2013\", \"Her\", 2013, 126, \"film\", \"solo\",\n \"Phone-sex scene + sexual-surrogate subplot — genuinely awkward shared\"),\n u(38, \"the-machinist-2004\", \"The Machinist\", 2004, 101, \"film\", \"solo\",\n \"Sex-worker storyline with several scenes — more comfortable solo\"),\n u(39, \"gone-girl-2014\", \"Gone Girl\", 2014, 149, \"film\", \"solo\",\n \"Explicit sex incl. graphic murder-during-sex scene — the classic awkward-with-parent film\"),\n u(40, \"humans-2015\", \"Humans\", 2015, null, \"series\", \"together\",\n \"Strong fit; relatively complete\", \"\", \"3\"),\n u(41, \"the-peripheral-2022\", \"The Peripheral\", 2022, null, \"series\", \"together\",\n \"Gibson adaptation; cancelled, no resolution\", \"\", \"1\"),\n u(42, \"night-sky-2022\", \"Night Sky\", 2022, null, \"series\", \"either\",\n \"Spacek/Simmons; cancelled on cliffhanger\", \"\", \"1\"),\n u(43, \"parks-and-recreation-2009\", \"Parks and Recreation\", 2009, null, \"series\", \"together\",\n \"Comfort/comedy — S1 rough, great from S2; on Peacock\", \"\", \"7\"),\n u(44, \"the-paper-2025\", \"The Paper\", 2025, null, \"series\", \"together\",\n \"Comfort/comedy — Office spinoff; slow start, gels ~ep5; on Peacock\", \"\", \"1+\"),\n];\n\n/** Curation profile. Informs future picks; the app never branches on it. */\nconst ABOUT = [\n \"10s = fully absorbing: big idea + character depth + emotional payoff (Gump, Interstellar, Whiplash, Martian, Fight Club, Truman Show).\",\n \"Prefers intelligence shown through behavior/problem-solving, not performed through rapid-fire dialogue (Sorkin patter actively grates).\",\n \"Low tolerance for ideas traded for generic action (The Island 4.5).\",\n \"AI/science documentaries score very high (The Thinking Game 9.5).\",\n \"Attention-demanding films fail under bad viewing conditions, not bad taste (Inception, Coherence) — hence the attention flag.\",\n \"Watch-mode solo means explicit-content awkwardness only; Robert is 15 and mature — an R rating alone is never the reason.\",\n];\n\nexport function seedState() {\n return {\n version: 1,\n users: [\"rob\", \"robert\"],\n about: ABOUT,\n movies: [...UNWATCHED, ...WATCHED],\n };\n}\n","label",[133],"6a4167bb-f0c5-4042-98fc-bbdc11565ff0","main.tsx",8,["D",1787102384531],"http","/**\n * Reel Time — movie watchlist and ratings for Rob and Robert.\n * Third of the family suite (Tau Zero, Mat Time); same val + blob + passcode shape.\n *\n * Routes:\n * GET / → the app (index.html)\n * GET /icon.png → 1024px icon (manifest, retina home screen)\n * GET /icon-180.png → 180px apple-touch-icon\n * GET /manifest.webmanifest → home-screen manifest\n * GET /state → { user, data } for the passcode in X-Reel-Code\n * POST /state → replace the shared state (JSON body = full state object)\n *\n * Auth: the passcode travels in the X-Reel-Code header (not the query string, so it stays\n * out of access logs). REEL_TIME_CODES holds \"user:code\" pairs, comma-separated — the code\n * identifies WHICH user, so ratings are attributed by the server rather than by a client\n * that could claim to be anyone.\n *\n * Storage: ONE shared blob, not one per passcode (this is the deliberate difference from\n * Tau Zero, where each reader keeps private progress). Rob and Robert curate the same list;\n * only the per-user fields inside each movie differ. Last-write-wins — two users, low\n * collision risk, per spec.\n */\nimport { blob } from \"https://esm.town/v/std/blob\";\nimport { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { seedState } from \"./seed.ts\";\nimport { ICON_180_BASE64, ICON_BASE64 } from \"./icon.ts\";\n\nconst STATE_KEY = \"reel_time_state_v1\";\n\n/** Constant-time compare so the allowlist check can't be timed. */\nfunction sameCode(a: string, b: string): boolean {\n if (a.length !== b.length) return false;\n let diff = 0;\n for (let i = 0; i < a.length; i++) diff |= a.charCodeAt(i) ^ b.charCodeAt(i);\n return diff === 0;\n}\n\n/** REEL_TIME_CODES = \"rob:xxxx,robert:yyyy\" */\nfunction codeTable(): { user: string; code: string }[] {\n return (Deno.env.get(\"REEL_TIME_CODES\") ?? \"\")\n .split(\",\")\n .map((pair) => pair.trim())\n .filter(Boolean)\n .map((pair) => {\n const i = pair.indexOf(\":\");\n if (i < 0) return null;\n return { user: pair.slice(0, i).trim().toLowerCase(), code: pair.slice(i + 1).trim() };\n })\n .filter((e): e is { user: string; code: string } => !!e && !!e.user && !!e.code);\n}\n\nconst json = (body: unknown, status = 200) =>\n new Response(JSON.stringify(body), {\n status,\n headers: { \"content-type\": \"application/json; charset=utf-8\", \"cache-control\": \"no-store\" },\n });\n\nconst iconCache = new Map();\nfunction icon(b64: string): Uint8Array {\n let bytes = iconCache.get(b64);\n if (!bytes) {\n bytes = Uint8Array.from(atob(b64), (ch) => ch.charCodeAt(0));\n iconCache.set(b64, bytes);\n }\n return bytes;\n}\n\n/** Read the shared state, seeding it on first ever run. */\nasync function loadState(): Promise> {\n const saved = await blob.getJSON(STATE_KEY);\n if (saved && typeof saved === \"object\" && Array.isArray((saved as any).movies)) {\n return saved as Record;\n }\n const fresh = seedState();\n await blob.setJSON(STATE_KEY, fresh);\n return fresh as unknown as Record;\n}\n\nexport default async function (req: Request): Promise {\n const url = new URL(req.url);\n const path = url.pathname;\n\n if (path === \"/icon.png\" || path === \"/icon-180.png\") {\n return new Response(icon(path === \"/icon.png\" ? ICON_BASE64 : ICON_180_BASE64), {\n headers: { \"content-type\": \"image/png\", \"cache-control\": \"public, max-age=31536000, immutable\" },\n });\n }\n\n if (path === \"/manifest.webmanifest\") {\n return json({\n name: \"Reel Time\",\n short_name: \"Reel Time\",\n description: \"Movie watchlist and ratings — Rob & Robert\",\n start_url: \"/\",\n scope: \"/\",\n display: \"standalone\",\n orientation: \"portrait\",\n background_color: \"#0f1420\",\n theme_color: \"#0f1420\",\n icons: [\n { src: \"/icon-180.png\", sizes: \"180x180\", type: \"image/png\", purpose: \"any\" },\n { src: \"/icon.png\", sizes: \"1024x1024\", type: \"image/png\", purpose: \"any\" },\n { src: \"/icon.png\", sizes: \"1024x1024\", type: \"image/png\", purpose: \"maskable\" },\n ],\n });\n }\n\n if (path === \"/state\") {\n const supplied = req.headers.get(\"x-reel-code\")?.trim() ?? \"\";\n if (!supplied) return json({ error: \"Passcode required.\" }, 401);\n\n const table = codeTable();\n if (table.length === 0) {\n return json({ error: \"Server not configured — REEL_TIME_CODES is unset.\" }, 503);\n }\n const match = table.find((e) => sameCode(e.code, supplied));\n if (!match) return json({ error: \"That passcode isn't recognised.\" }, 401);\n\n if (req.method === \"GET\") {\n return json({ user: match.user, data: await loadState() });\n }\n\n if (req.method === \"POST\") {\n let body: unknown;\n try {\n body = await req.json();\n } catch {\n return json({ error: \"Body must be JSON.\" }, 400);\n }\n // Unwrap {data:…} so a backup blob can be POSTed verbatim.\n const data = body && typeof body === \"object\" && \"data\" in (body as Record)\n ? (body as Record).data\n : body;\n // Never let a malformed or empty payload blank the shared list.\n if (typeof data !== \"object\" || data === null || Array.isArray(data) || !Array.isArray((data as any).movies)) {\n return json({ error: \"Expected a state object with a movies array.\" }, 400);\n }\n if ((data as any).movies.length === 0) {\n return json({ error: \"Refusing to save an empty movie list.\" }, 400);\n }\n await blob.setJSON(STATE_KEY, data);\n return json({ ok: true, user: match.user });\n }\n\n return json({ error: \"Method not allowed.\" }, 405);\n }\n\n if (path === \"/\" || path === \"/index.html\") {\n const html = await readFile(\"/index.html\", import.meta.url);\n return new Response(html, {\n headers: { \"content-type\": \"text/html; charset=utf-8\", \"cache-control\": \"no-store\" },\n });\n }\n\n return new Response(\"Not found\", { status: 404 });\n}\n",[144],"fa0e777b-a329-4128-8b1a-91a982090d96","index.html","f9e0fb44-9b65-11f1-92ef-1607ee4eb77e",9,["D",1787102384742],4,"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nReel Time — Rob & Robert\n\n\n\n\n\n\n\n\n\n\n

REEL TIME

Rob & Robert

\n\n\n\n

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Diff · v11