[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_157":158,"_159":160},"routes/_app.x.$handle.$name",{"_11":12,"_13":14,"_15":16,"_18":19,"_17":-7,"_119":-5,"_20":120,"_22":121,"_122":123,"_124":125,"_25":126,"_24":-5,"_127":-5,"_128":-5,"_129":53,"_130":131,"_132":44,"_133":-5,"_134":-5,"_135":136},"routes/_app.x.$handle.$name.branch.$branch.code.$",{"_11":12,"_13":14,"_15":16,"_17":-7,"_18":19,"_20":21,"_22":23,"_24":-7,"_25":26,"_27":-5,"_28":-5,"_29":-5,"_30":-5,"_31":-5},"handle","izatbekboev","name","Calorietracker2","branchName","main","version","path","","project",{"_33":61,"_13":14,"_45":62,"_63":-5,"_64":53,"_65":66,"_67":66,"_68":19,"_69":-5,"_70":71,"_72":37,"_73":44,"_74":-5,"_75":-5,"_76":77,"_78":79,"_80":81,"_82":83,"_84":85,"_86":-5,"_87":88,"_89":88,"_90":91,"_92":91,"_93":91,"_94":88,"_95":88,"_96":97,"_98":99,"_100":101,"_102":53},"tree",[56],"file","contents",[32],"upstream","pull","ahead","behind","envVars",{"_33":34,"_13":35,"_36":37,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_17":47,"_48":49,"_50":51,"_52":53,"_54":-5,"_18":55},"id","eab409fa-f682-4627-9686-d6b0cc17db0b","main.ts","fileId","e29e6632-8978-11f1-b807-1607ee4eb77e","parentId","branchId","179cfb7c-fe24-4b67-8abc-569da632b1f3","branchVersion",19,"latest",true,"createdAt",["D",1786595427574],18,"fileType","http","content","// =============================================================================\n// Calorie Tracker / Aura — ОБЛАЧНЫЙ AI-посредник для Val.town (версия 10)\n//\n// Новое в v10: /parse-text и /parse-photo теперь также просят и возвращают\n// шесть \"ключевых нутриентов\" (sodium, zinc, magnesium, omega3, vitaminB12,\n// vitaminD) для каждого пункта — раньше модель их не оценивала вовсе, и Aura\n// показывала для AI-залогированной еды (голос/фото/текст) жёсткие нули в\n// виджете Key Nutrients, даже если у блюда реально высокое содержание, напр.\n// омега-3 у жирной рыбы. calorie-tracker эти новые поля просто не читает —\n// его модель Dish под них не заведена, лишние ключи в ответе безвредны.\n// Новое в v9: дневной лимит на AI-запросы (/parse-text, /parse-photo,\n// /transcribe, /chat — все вместе, один общий счётчик) на анонимный\n// deviceId, который каждый клиент теперь генерирует и хранит у себя\n// (см. src/lib/deviceId.ts в обоих приложениях). Лимит защищает от сценария\n// \"купил Lifetime один раз — жжёт Gemini API бесплатно годами\", а заодно и\n// от произвольного стороннего вызова эндпоинта в обход обоих приложений.\n// Хранится в собственной SQLite-базе этого val'а (std/sqlite), ключ —\n// (device_id, день по UTC). Если клиент не прислал deviceId (старая версия\n// приложения, ещё не обновилась) — считаем лимит по IP-адресу запроса, это\n// грубее, но не оставляет совсем без защиты. При превышении лимита — 429 с\n// понятным телом ответа, а не голая ошибка 500.\n// Новое в v8: /chat принимает необязательный \"topic\" (\"nutrition\" | \"support\",\n// по умолчанию \"nutrition\" — обратная совместимость с calorie-tracker, который\n// topic не отправляет). Aura's новый экран Support шлёт topic=\"support\" и\n// получает отдельный системный промпт SUPPORT_SYSTEM_BY_LANG — ассистент по\n// использованию самого приложения (Settings/Profile/Premium/экспорт/\n// конфиденциальность), а не по питанию; на вопросы о еде отвечает\n// перенаправлением к Nutrition Assistant в Diary.\n// Новое в v7: чат-ассистент теперь явно отказывается отвечать на вопросы,\n// не связанные с питанием/здоровьем/приложением, и вежливо возвращает\n// разговор к теме — во всех трёх языках CHAT_SYSTEM_BY_LANG.\n// Новое в v6: \"lang\" теперь понимает и \"es\" (Aura добавила выбор языка в\n// настройках — en/es/ru). /chat тоже стал lang-aware: раньше системный\n// промпт ассистента был жёстко на русском независимо от языка приложения,\n// теперь отвечает на языке, который прислал клиент. Без lang по умолчанию\n// остаётся русский везде, для обратной совместимости со старыми клиентами.\n// Новое в v5: /parse-text и /parse-photo принимают \"lang\" в теле запроса\n// (\"ru\" | \"en\") и называют блюда на ЭТОМ языке, а не всегда по-русски —\n// раньше Aura (английский UI) получала названия блюд на русском, даже если\n// голосовой запрос был на английском. Без lang по умолчанию остаётся\n// русский, для обратной совместимости.\n// Новое в v4: страница Privacy Policy на GET /privacy — публичная ссылка для\n// App Store Connect, общая для обоих приложений (Calorie Tracker и Aura),\n// оба используют этот же бэкенд.\n// Новое в v3: распознавание еды по ФОТО (маршрут /parse-photo, Gemini vision).\n// Маршрут /parse-text (текст) работает как раньше.\n// =============================================================================\n\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\n// Pinned (not \"-latest\") so cost/behavior can't silently change under us —\n// the \"-latest\" alias moved from Gemini 2.5 Flash to Gemini 3.6 Flash on\n// 2026-08-09 with no code change on our side, ~5x pricier per token.\n// NOTE 2026-08-09: gemini-2.5-flash-lite (first choice) turned out to return\n// HTTP 404 \"no longer available to new users\" for a freshly created/paid API\n// key, even though Google's own model list still shows it as Stable — that\n// restriction is undocumented and key-specific, not a real deprecation.\n// gemini-3.5-flash-lite is the current-generation Stable lite model and\n// works for new keys; still far cheaper than the \"-latest\" alias's 3.6\n// Flash. Revisit pricing/accuracy if this ever needs to change again.\nconst MODEL = \"gemini-3.5-flash-lite\";\n\n/** Thrown when Gemini itself rejects a request with 429 (TooManyRequests) or\n * 503 (ServiceUnavailable) — its own free-tier rate limit or a transient\n * overload, not our DAILY_AI_LIMIT and not a real connectivity problem.\n * Kept distinct from a plain Error so the top-level catch can give it its\n * own honest response instead of a generic 500. */\nclass GeminiUpstreamError extends Error {\n constructor(public status: number, message: string) {\n super(message);\n }\n}\n\n/** Generous but finite — real users won't get near this in a day; it exists\n * purely to cap worst-case cost from one abandoned/malicious/unlimited-plan\n * caller, not to police normal usage. One shared counter across all four\n * AI-costing routes (parse-text, parse-photo, transcribe, chat), since\n * they all cost real Gemini API money the same way. */\nconst DAILY_AI_LIMIT = 50;\n\nlet usageTableReady: Promise | null = null;\nfunction ensureUsageTable(): Promise {\n if (!usageTableReady) {\n usageTableReady = sqlite.execute(\n `create table if not exists ai_usage(\n device_id text not null,\n day text not null,\n count integer not null default 0,\n primary key (device_id, day)\n )`,\n );\n }\n return usageTableReady;\n}\n\nfunction todayUtc(): string {\n return new Date().toISOString().slice(0, 10); // \"YYYY-MM-DD\"\n}\n\n/** Increments today's counter for this id and returns the count AFTER the\n * increment — so a fresh id's first call returns 1, not 0. Doing the\n * increment and the read in one step avoids a race between \"check\" and\n * \"increment\" under concurrent requests from the same id. */\nasync function incrementAndGetUsage(deviceId: string): Promise {\n await ensureUsageTable();\n const day = todayUtc();\n await sqlite.execute({\n sql: `insert into ai_usage(device_id, day, count) values (:id, :day, 1)\n on conflict(device_id, day) do update set count = count + 1`,\n args: { id: deviceId, day },\n });\n const result = await sqlite.execute({\n sql: `select count from ai_usage where device_id = :id and day = :day`,\n args: { id: deviceId, day },\n });\n const row = result.rows[0] as { count: number } | undefined;\n return row?.count ?? 1;\n}\n\n/** Prefers the client-sent anonymous deviceId; falls back to the request's\n * IP if an old client build didn't send one yet, rather than skipping the\n * check entirely for those callers. */\nfunction rateLimitKey(req: Request, bodyDeviceId: unknown): string {\n if (typeof bodyDeviceId === \"string\" && bodyDeviceId.trim()) {\n return \"device:\" + bodyDeviceId.trim();\n }\n const ip = req.headers.get(\"x-forwarded-for\")?.split(\",\")[0]?.trim();\n return \"ip:\" + (ip || \"unknown\");\n}\n\nconst PRIVACY_HTML = `\n\n\n\n\nPrivacy Policy — Calorie Tracker & LogFood AI\n\n\n\n

Privacy Policy

Applies to Calorie Tracker and LogFood AI. Last updated: August 3, 2026.

\n\n

These apps are built and operated by an independent developer (contact below). This policy explains what\n stays on your device, what is sent off it, and why.

\n\n

What stays on your device

Your food diary, profile (name, height, weight, goals), targets, macro split and reminder times are stored\n only on your device. There is no account and no account-linked server storage of this data.

\n\n

What is sent off the device, and why

Manual food entry and search never leave the device. Three optional AI features do send something to our\n server to work, only while you're actively using them:

Voice logging — the audio recording, to transcribe it to text.
Photo recognition — the photo you take or pick, to identify what's on the plate.
AI nutrition assistant — your message, plus a short summary of your day (calories and\n macros eaten/remaining), so it can answer specifically for you.

These are processed by our server and forwarded to Google's Gemini API to generate a result. We do not\n store this content after the response is generated, and we do not use it to train any model. Google processes\n it under its own API terms — see Google's\n Gemini API Additional Terms of Service and \n Google's Privacy Policy for how they handle it on their end.

\n\n

No ads, no analytics, no third-party tracking

As of this writing, neither app includes advertising SDKs or third-party analytics/tracking libraries.

\n\n

Deleting your data

Both apps include an \"Erase all data\" option in Settings/Privacy that permanently removes your diary,\n profile and settings from the device. Because nothing is retained on our server, there is nothing further to\n delete remotely.

\n\n

Children's privacy

These apps are not directed at children, and we do not knowingly collect information from children.

\n\n

Changes to this policy

If this policy changes in a way that affects what's collected, we'll update the \"Last updated\" date above.

\n\n

Contact

Questions about this policy or your data: ibekboev@gmail.com

\n\n`;\n\n/** \"ru\" -> \"Russian\", \"en\" -> \"English\", \"es\" -> \"Spanish\". Each app tells us\n * its own UI language explicitly (see `lang` in the request body) — we name\n * items in THAT language, not whatever language the input happened to be\n * in, so a Russian voice note inside the English-only Aura still comes back\n * in English. Defaults to Russian for calorie-tracker clients that predate\n * this field. */\nfunction langLabel(lang: string | undefined): string {\n if (lang === \"en\") return \"English\";\n if (lang === \"es\") return \"Spanish\";\n return \"Russian\";\n}\n\nfunction textPrompt(\n input: string,\n meal: string,\n libraryNames: string[],\n lang?: string,\n): string {\n return [\n \"You are a careful nutrition estimator for a calorie-tracking app.\",\n \"The user describes food they ate in free text (any language).\",\n \"Break it into individual food items and estimate nutrition.\",\n \"\",\n jsonShape(lang),\n \"\",\n rules(),\n `Meal context: ${meal}.`,\n libraryLine(libraryNames),\n `User input: \"\"\"${input}\"\"\"`,\n ]\n .filter(Boolean)\n .join(\"\\n\");\n}\n\nfunction photoPrompt(\n meal: string,\n libraryNames: string[],\n lang?: string,\n): string {\n return [\n \"You are a careful nutrition estimator for a calorie-tracking app.\",\n \"Look at the PHOTO of a meal and identify the food items on the plate.\",\n \"Estimate the portion size of each item from what you can see.\",\n \"\",\n jsonShape(lang),\n \"\",\n rules(),\n 'Photo portions are always estimates: set amountKnown=false and never use confidence \"high\" — use \"medium\" or \"low\".',\n `Meal context: ${meal}.`,\n libraryLine(libraryNames),\n 'If the photo has no recognizable food, return {\"recognized\": false, \"items\": []}.',\n ]\n .filter(Boolean)\n .join(\"\\n\");\n}\n\nfunction jsonShape(lang?: string): string {\n return [\n \"Return ONLY a JSON object of EXACTLY this shape (no extra text):\",\n \"{\",\n ' \"recognized\": true,',\n ' \"items\": [',\n \" {\",\n ` \"name\": \"short dish name in ${langLabel(lang)}\",`,\n ' \"grams\": 0,',\n ' \"amountKnown\": true,',\n ' \"kcal\": 0, \"protein\": 0, \"fat\": 0, \"carbs\": 0, \"fiber\": 0,',\n ' \"sodium\": 0, \"zinc\": 0, \"magnesium\": 0, \"omega3\": 0, \"vitaminB12\": 0, \"vitaminD\": 0,',\n ' \"confidence\": \"high\"',\n \" }\",\n \" ]\",\n \"}\",\n ].join(\"\\n\");\n}\n\nfunction rules(): string {\n return [\n \"Rules:\",\n \"- grams = estimated weight of THAT portion in grams;\",\n \"- kcal/protein/fat/carbs/fiber = values for THAT WHOLE portion (not per 100 g);\",\n \"- sodium (mg), zinc (mg), magnesium (mg), omega3 (g), vitaminB12 (mcg), vitaminD (mcg) = your best \" +\n \"realistic estimate for THAT WHOLE portion, same convention as the macros above — base it on what \" +\n \"that food is actually known to contain (e.g. fatty fish is high in omega3 and vitaminD, red meat \" +\n \"and shellfish are high in zinc and B12, leafy greens and nuts are high in magnesium); use 0 only \" +\n \"when the food genuinely has none or a negligible trace, not as a default;\",\n \"- amountKnown = true only if an explicit amount is given, otherwise false;\",\n '- confidence must be exactly one of: \"high\", \"medium\", \"low\";',\n \"- be realistic, do not overestimate.\",\n ].join(\"\\n\");\n}\n\nfunction libraryLine(libraryNames: string[]): string {\n return libraryNames && libraryNames.length\n ? `User's known dishes (prefer these names if they match): ${\n libraryNames.slice(0, 40).join(\", \")\n }.`\n : \"\";\n}\n\nasync function callGemini(parts: any[], apiKey: string): Promise {\n const url =\n `https://generativelanguage.googleapis.com/v1beta/models/${MODEL}:generateContent?key=${apiKey}`;\n const res = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{ parts }],\n generationConfig: {\n responseMimeType: \"application/json\",\n temperature: 0.2,\n },\n }),\n });\n if (!res.ok) {\n const body = await res.text();\n if (res.status === 429 || res.status === 503) {\n throw new GeminiUpstreamError(\n res.status,\n `Gemini HTTP ${res.status}: ${body.slice(0, 500)}`,\n );\n }\n throw new Error(`Gemini HTTP ${res.status}: ${body.slice(0, 500)}`);\n }\n const data = await res.json();\n const text = data?.candidates?.[0]?.content?.parts?.[0]?.text;\n if (!text) {\n throw new Error(\n \"Gemini returned empty text. Full: \" + JSON.stringify(data).slice(0, 500),\n );\n }\n return JSON.parse(text);\n}\n\n/** Aura sends `lang` on /chat too now; calorie-tracker clients that predate\n * this still default to Russian, unchanged from before. */\nconst CHAT_SYSTEM_BY_LANG: Record<\"en\" | \"es\" | \"ru\", string> = {\n en: \"You are a friendly nutrition assistant inside a calorie-tracking app. \" +\n \"Reply briefly, to the point, and in English. Help with calories, macros, food choices, \" +\n \"meal plans and healthy habits. Give practical, realistic advice. \" +\n \"Do not give medical diagnoses, and for serious health questions suggest seeing a doctor or dietitian. \" +\n \"If the user asks about something unrelated to nutrition, health, fitness or this app, do not answer \" +\n \"it — briefly and politely say that's outside what you help with here, and steer the conversation back \" +\n \"to food, calories or habits.\",\n es:\n \"Eres un asistente de nutrición amigable dentro de una app de conteo de calorías. \" +\n \"Responde de forma breve, concreta y en español. Ayuda con calorías, macros, elección de \" +\n \"alimentos, planes de comida y hábitos saludables. Da consejos prácticos y realistas. \" +\n \"No hagas diagnósticos médicos y, ante preguntas de salud serias, sugiere consultar a un médico o nutricionista. \" +\n \"Si el usuario pregunta algo que no tiene que ver con nutrición, salud, ejercicio o esta app, no lo \" +\n \"respondas — indica breve y amablemente que eso queda fuera de lo que puedes ayudar aquí, y vuelve a \" +\n \"encaminar la conversación hacia la comida, las calorías o los hábitos.\",\n ru:\n \"Ты дружелюбный ассистент по питанию внутри приложения для подсчёта калорий. \" +\n \"Отвечай кратко, по делу и на русском языке. Помогай с калориями, БЖУ, выбором блюд, \" +\n \"планами питания и полезными привычками. Давай практичные, реалистичные советы. \" +\n \"Не ставь медицинских диагнозов и при серьёзных вопросах со здоровьем советуй обратиться к врачу или диетологу. \" +\n \"Если пользователь спрашивает о чём-то, не связанном с питанием, здоровьем, тренировками или этим \" +\n \"приложением, не отвечай по существу — коротко и вежливо скажи, что это вне того, с чем ты можешь \" +\n \"помочь здесь, и верни разговор к еде, калориям или привычкам.\",\n};\n\nfunction chatSystemPrompt(lang: string | undefined): string {\n return CHAT_SYSTEM_BY_LANG[lang === \"en\" || lang === \"es\" ? lang : \"ru\"];\n}\n\n/** Only Aura sends topic=\"support\" (see app/support.tsx) — calorie-tracker\n * never reaches this prompt. The opposite of CHAT_SYSTEM_BY_LANG: helps with\n * using the app itself (Settings, Profile, Premium, export, privacy), and\n * explicitly refuses nutrition questions rather than answering them, since\n * that's what the Nutrition Assistant in Diary is for. */\nconst SUPPORT_SYSTEM_BY_LANG: Record<\"en\" | \"es\" | \"ru\", string> = {\n en:\n \"You are a support assistant inside LogFood AI, a calorie-tracking iOS app. You help ONLY with using \" +\n \"the app itself, not with nutrition or diet: finding your way around Settings, Profile, My Data, \" +\n \"Diary and Report; understanding your Premium/Free status (today this is a status stored only on \" +\n \"this device — there is no real App Store billing connected yet, so nothing is actually being \" +\n \"charged); exporting your diary as a CSV file; switching the app language; and privacy controls \" +\n \"(Settings → Privacy, including erasing all data). Reply briefly, to the point, and in English. \" +\n \"If the question is about nutrition, diet, calories or food choices, do not answer it — briefly \" +\n \"say that for nutrition questions they should use the AI Nutrition Assistant in their Diary \" +\n \"instead. If the question is about a bug, a payment problem, or anything you can't actually \" +\n \"resolve from how the app works, tell them to use the Contact Us button below to email support \" +\n \"instead of guessing.\",\n es:\n \"Eres un asistente de soporte dentro de LogFood AI, una app de conteo de calorías para iOS. Ayudas \" +\n \"SOLO con el uso de la propia app, no con nutrición ni dietas: cómo moverte por Configuración, \" +\n \"Perfil, Mis Datos, Diario e Informe; entender tu estado Premium/Gratis (hoy es un estado guardado \" +\n \"solo en este dispositivo — todavía no hay una facturación real de la App Store conectada, así que \" +\n \"no se cobra nada de verdad); exportar tu diario como archivo CSV; cambiar el idioma de la app; y \" +\n \"los controles de privacidad (Configuración → Privacidad, incluyendo borrar todos los datos). \" +\n \"Responde de forma breve, concreta y en español. Si la pregunta es sobre nutrición, dieta, \" +\n \"calorías o elección de alimentos, no la respondas — indica brevemente que para preguntas de \" +\n \"nutrición usen el Asistente de Nutrición con IA en su Diario. Si la pregunta es sobre un error, \" +\n \"un problema de pago, o algo que de verdad no puedes resolver según cómo funciona la app, diles \" +\n \"que usen el botón Contáctanos de abajo para escribir a soporte en vez de adivinar.\",\n ru:\n \"Ты ассистент поддержки внутри LogFood AI, приложения для подсчёта калорий на iOS. Ты помогаешь ТОЛЬКО \" +\n \"с использованием самого приложения, а не с питанием или диетами: как ориентироваться в Настройках, \" +\n \"Профиле, Моих данных, Дневнике и Отчёте; что значит статус Premium/Бесплатно (сегодня это статус, \" +\n \"сохранённый только на этом устройстве — реального биллинга через App Store пока нет, поэтому \" +\n \"никакого реального списания не происходит); как экспортировать дневник в CSV-файл; как сменить \" +\n \"язык приложения; и настройки конфиденциальности (Настройки → Конфиденциальность, включая стирание \" +\n \"всех данных). Отвечай кратко, по делу и на русском языке. Если вопрос о питании, диете, калориях \" +\n \"или выборе еды — не отвечай по существу, а коротко скажи, что по вопросам питания нужно \" +\n \"использовать ИИ-ассистента по питанию в Дневнике. Если вопрос о баге, проблеме с оплатой или о \" +\n \"чём-то, что ты действительно не можешь решить исходя из того, как устроено приложение — скажи \" +\n \"написать в поддержку через кнопку «Написать нам» ниже, а не гадать.\",\n};\n\nfunction supportSystemPrompt(lang: string | undefined): string {\n return SUPPORT_SYSTEM_BY_LANG[lang === \"en\" || lang === \"es\" ? lang : \"ru\"];\n}\n\nasync function callGeminiChat(\n contents: any[],\n systemText: string,\n apiKey: string,\n): Promise {\n const url =\n `https://generativelanguage.googleapis.com/v1beta/models/${MODEL}:generateContent?key=${apiKey}`;\n const res = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n systemInstruction: { parts: [{ text: systemText }] },\n contents,\n generationConfig: { temperature: 0.6 },\n }),\n });\n if (!res.ok) {\n const body = await res.text();\n if (res.status === 429 || res.status === 503) {\n throw new GeminiUpstreamError(\n res.status,\n `Gemini HTTP ${res.status}: ${body.slice(0, 500)}`,\n );\n }\n throw new Error(`Gemini HTTP ${res.status}: ${body.slice(0, 500)}`);\n }\n const data = await res.json();\n const text = data?.candidates?.[0]?.content?.parts?.[0]?.text;\n return typeof text === \"string\" ? text : \"\";\n}\n\nfunction round1(x: number): number {\n return Math.round((Number(x) || 0) * 10) / 10;\n}\n\nfunction round2(x: number): number {\n return Math.round((Number(x) || 0) * 100) / 100;\n}\n\nfunction matchDish(\n name: string,\n libraryById: [string, string][],\n): string | undefined {\n if (!name) return undefined;\n const n = name.trim().toLowerCase();\n for (const [id, dishName] of libraryById) {\n if (dishName.trim().toLowerCase() === n) return id;\n }\n return undefined;\n}\n\nfunction toParseResult(\n model: any,\n libraryById: [string, string][],\n source: \"text\" | \"photo\",\n): any {\n if (\n !model?.recognized || !Array.isArray(model.items) ||\n model.items.length === 0\n ) {\n return {\n status: \"unrecognized\",\n items: [],\n hint: source === \"photo\"\n ? \"Не удалось разобрать фото. Попробуйте снять тарелку ближе и при хорошем свете.\"\n : \"Назовите блюдо и количество — например «овсянка 80 г».\",\n source,\n };\n }\n const items = model.items.map((it: any) => {\n // Photos are always approximate, no matter what the model claims.\n const approximate = source === \"photo\" ? true : it.confidence !== \"high\";\n const macros = {\n kcal: Math.round(it.kcal),\n protein: round1(it.protein),\n fat: round1(it.fat),\n carbs: round1(it.carbs),\n fiber: round1(it.fiber ?? 0),\n // Six \"key nutrient\" fields — additive to the response shape, kept\n // separate from the macros clients already trusted before this: a\n // shaky zinc/omega3 guess shouldn't be a reason to distrust kcal.\n // Aura's Key Nutrients widget reads these; calorie-tracker's Dish\n // model doesn't have anywhere to put them and just ignores the extra\n // keys, same as it already ignores kcalInterval today.\n sodium: Math.round(Number(it.sodium) || 0),\n zinc: round2(it.zinc),\n magnesium: Math.round(Number(it.magnesium) || 0),\n omega3: round2(it.omega3),\n vitaminB12: round2(it.vitaminB12),\n vitaminD: round2(it.vitaminD),\n };\n return {\n name: it.name,\n grams: it.grams != null ? Math.round(it.grams) : null,\n macros,\n confidence: source === \"photo\" && it.confidence === \"high\"\n ? \"medium\"\n : it.confidence,\n approximate,\n needsAmount: false,\n matchedDishId: matchDish(it.name, libraryById),\n kcalInterval: approximate\n ? {\n min: Math.round(macros.kcal * 0.75),\n max: Math.round(macros.kcal * 1.3),\n }\n : undefined,\n };\n });\n const anyApprox = items.some((i: any) => i.approximate);\n return { status: anyApprox ? \"partial\" : \"ok\", items, source };\n}\n\nexport default async function (req: Request): Promise {\n const apiKey = Deno.env.get(\"GEMINI_API_KEY\");\n const url = new URL(req.url);\n\n if (req.method === \"GET\" && url.pathname.endsWith(\"/health\")) {\n return Response.json({ ok: true, model: MODEL, keyConfigured: !!apiKey });\n }\n\n if (req.method === \"GET\" && url.pathname.endsWith(\"/privacy\")) {\n return new Response(PRIVACY_HTML, {\n headers: { \"content-type\": \"text/html; charset=utf-8\" },\n });\n }\n\n if (req.method === \"POST\") {\n try {\n if (!apiKey) {\n return Response.json({ error: \"GEMINI_API_KEY не задан\" }, {\n status: 500,\n });\n }\n const body = await req.json().catch(() => ({}));\n const meal = body?.meal ?? \"lunch\";\n const lang = typeof body?.lang === \"string\" ? body.lang : undefined;\n const library = Array.isArray(body?.library) ? body.library : [];\n const libraryNames = library.map((d: any) => d.name);\n const libraryById = library.map((d: any) => [d.id, d.name]) as [\n string,\n string,\n ][];\n\n // Every route below this point calls Gemini and costs real money —\n // one shared daily counter per anonymous device (or IP, for clients\n // too old to send one yet).\n const usageKey = rateLimitKey(req, body?.deviceId);\n const usedToday = await incrementAndGetUsage(usageKey);\n if (usedToday > DAILY_AI_LIMIT) {\n return Response.json(\n {\n error: \"daily_limit_reached\",\n message:\n \"You've reached today's AI usage limit. It resets tomorrow — manual entry and search still work normally.\",\n },\n { status: 429 },\n );\n }\n\n // ----- PHOTO -----\n if (url.pathname.endsWith(\"/parse-photo\")) {\n const imageBase64 = body?.imageBase64;\n const mimeType = body?.mimeType ?? \"image/jpeg\";\n if (!imageBase64) {\n return Response.json({ error: \"no image\" }, { status: 400 });\n }\n const parts = [\n { inline_data: { mime_type: mimeType, data: imageBase64 } },\n { text: photoPrompt(meal, libraryNames, lang) },\n ];\n const model = await callGemini(parts, apiKey);\n return Response.json(toParseResult(model, libraryById, \"photo\"));\n }\n\n // ----- VOICE (speech -> text) -----\n if (url.pathname.endsWith(\"/transcribe\")) {\n const audioBase64 = body?.audioBase64;\n const mimeType = body?.mimeType ?? \"audio/m4a\";\n if (!audioBase64) {\n return Response.json({ error: \"no audio\" }, { status: 400 });\n }\n const parts = [\n { inline_data: { mime_type: mimeType, data: audioBase64 } },\n {\n text:\n \"Transcribe the spoken words exactly, in the original language. \" +\n 'Return ONLY JSON: {\"text\": \"the transcription\"}. ' +\n 'If nothing intelligible is said, return {\"text\": \"\"}.',\n },\n ];\n const model = await callGemini(parts, apiKey);\n const text = typeof model?.text === \"string\" ? model.text : \"\";\n return Response.json({ text, confidence: \"high\" });\n }\n\n // ----- CHAT (assistant) -----\n if (url.pathname.endsWith(\"/chat\")) {\n const messages = Array.isArray(body?.messages) ? body.messages : [];\n const contents = messages\n .filter((m: any) => m && typeof m.text === \"string\" && m.text.trim())\n .map((m: any) => ({\n role: m.role === \"assistant\" ? \"model\" : \"user\",\n parts: [{ text: String(m.text) }],\n }));\n if (contents.length === 0) {\n return Response.json({ error: \"no messages\" }, { status: 400 });\n }\n const context = typeof body?.context === \"string\"\n ? body.context.trim()\n : \"\";\n // Default \"nutrition\" keeps calorie-tracker (which never sends topic)\n // on exactly the behavior it always had.\n const topic = body?.topic === \"support\" ? \"support\" : \"nutrition\";\n const chatSystem = topic === \"support\"\n ? supportSystemPrompt(lang)\n : chatSystemPrompt(lang);\n const systemText = context ? chatSystem + \"\\n\\n\" + context : chatSystem;\n const reply = await callGeminiChat(contents, systemText, apiKey);\n return Response.json({ reply });\n }\n\n // ----- TEXT (default) -----\n const input = body?.input;\n if (!input || !String(input).trim()) {\n return Response.json({ error: \"empty input\" }, { status: 400 });\n }\n const parts = [{\n text: textPrompt(String(input), meal, libraryNames, lang),\n }];\n const model = await callGemini(parts, apiKey);\n return Response.json(toParseResult(model, libraryById, \"text\"));\n } catch (err) {\n if (err instanceof GeminiUpstreamError) {\n return Response.json(\n {\n error: \"upstream_busy\",\n message:\n \"The AI service is busy right now. Please try again in a moment.\",\n },\n { status: 503 },\n );\n }\n const message = String((err as Error).message ?? err);\n console.error(\"parse FAILED:\", message);\n return Response.json({ error: message }, { status: 500 });\n }\n }\n\n return Response.json({ error: \"not found\" }, { status: 404 });\n}","deleted",false,"label",[35],{"_33":34,"_13":35,"_36":37,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":57,"_17":47,"_48":49,"_50":51,"_52":53,"_54":-5,"_58":59,"_18":60},["D",1786595427574],"children",[],[35],"9afdd725-f534-407b-8095-c3ce13367b02",["D",1785128771613],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","imageUrl","userId","2cd7adfa-1036-4583-aabc-25a1230efb2c","pinnedFileId","pinPreview","pinMigrated","screenshotVersion","likeCount",0,"orgId","019fa1f5-b9a4-75fa-b9bc-58ebe341238b","tursoName","9afdd725f534407b8095c3ce13367b02","tursoHostname","9afdd725f534407b8095c3ce13367b02-val-town.aws-us-east-2.turso.io","tursoMeasuredAt",["D",1789518064818],"pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_11":12,"_118":114},"org",{"_11":12,"_111":112,"_113":114,"_70":71,"_115":116,"_117":53},"branch",{"_17":42,"_13":16,"_33":40,"_103":61,"_104":-5,"_105":-5,"_106":-5,"_107":-5,"_108":-5,"_109":14,"_110":12},"isOwned","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","displayName","Izat Bekboev","avatar","https://lh3.googleusercontent.com/a/ACg8ocL4dSIMUlZxyJ08SBKihfgjC0U8Bmq4rSYhOepRpiZHp1W9QKBuIw=s96-c","tier","free","canRestrictVals","profileImageUrl","adoptOrgId",{"_33":61,"_13":14,"_45":152,"_63":-5,"_64":53,"_65":66,"_67":66,"_68":19,"_69":-5,"_70":71,"_72":37,"_73":44,"_74":-5,"_75":-5,"_76":77,"_78":79,"_80":81,"_82":83,"_84":153,"_86":-5,"_87":88,"_89":88,"_90":91,"_92":91,"_93":91,"_94":88,"_95":88,"_96":154,"_98":155,"_100":156,"_102":53},[149],"files",[149],"counts",{"_139":77,"_140":141,"_142":77,"_31":143,"_144":145},[137],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_33":34,"_13":35,"_36":37,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_17":47,"_48":49,"_50":51,"_52":53,"_54":-5,"_18":138},[35],"pulls","branches",1,"forks",{"_146":141,"_148":77},"connections",{"_146":77,"_147":77},"count","unfilledCount","emptyCount",{"_33":34,"_13":35,"_36":37,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":57,"_17":47,"_48":49,"_50":51,"_52":53,"_54":-5,"_58":150,"_18":151},[],[35],["D",1785128771613],["D",1789518064818],{"_11":12,"_118":114},{"_11":12,"_111":112,"_113":114,"_70":71,"_115":116,"_117":53},{"_17":42,"_13":16,"_33":40,"_103":61,"_104":-5,"_105":-5,"_106":-5,"_107":-5,"_108":-5,"_109":14,"_110":12},"ctx",{"_96":-5,"_134":190,"_191":192,"_193":194,"_195":53,"_196":53,"_197":53,"_198":44,"_199":-5,"_200":-7,"_201":-7,"_202":77,"_203":53,"_204":53,"_205":-5,"_206":53,"_207":53,"_208":53,"_209":-5},"ENV",{"_161":162,"_163":164,"_165":16,"_166":167,"_168":169,"_170":171,"_172":173,"_174":175,"_176":177,"_178":179,"_180":181,"_182":183,"_184":185,"_186":187,"_188":189},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

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