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{ coerceMacros, roundNumber, type MacroKey } from \"./food_enrich.ts\";\n\nexport type FatsecretConfig = {\n accessToken: string;\n includeFoodData?: boolean;\n};\n\nconst FATSECRET_NLP_URL = \"https://platform.fatsecret.com/rest/natural-language-processing/v1\";\nconst MACRO_KEYS: MacroKey[] = [\"calories\", \"protein\", \"carbs\", \"fat\", \"fiber\", \"sugar\", \"sodium\"];\n\nexport async function fetchFatsecretNutrition(\n foodName: string,\n config: FatsecretConfig,\n): Promise> | null> {\n const payload: Record = {\n user_input: foodName,\n include_food_data: config.includeFoodData ?? true,\n };\n\n const response = await fetch(FATSECRET_NLP_URL, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${config.accessToken}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(payload),\n });\n\n if (!response.ok) {\n console.warn(\"Fatsecret NLP request failed.\", {\n status: response.status,\n statusText: response.statusText,\n });\n return null;\n }\n\n const data = (await response.json()) as unknown;\n return extractFatsecretMacros(data);\n}\n\nfunction extractFatsecretMacros(\n data: unknown,\n): Partial> | null {\n if (!data || typeof data !== \"object\") return null;\n const record = data as Record;\n\n const direct = extractTotalMacros(record.total_nutritional_content);\n if (direct) return direct;\n\n const responses = collectFoodResponses(record);\n if (!responses.length) return null;\n\n const totals: Partial> = {};\n let found = false;\n for (const response of responses) {\n const macros = extractTotalMacros(response.total_nutritional_content);\n if (!macros) continue;\n found = true;\n for (const key of MACRO_KEYS) {\n const value = macros[key];\n if (typeof value !== \"number\") continue;\n totals[key] = (totals[key] ?? 0) + value;\n }\n }\n\n if (!found) return null;\n return roundMacroTotals(totals);\n}\n\nfunction extractTotalMacros(\n value: unknown,\n): Partial> | null {\n if (!value || typeof value !== \"object\") return null;\n const raw = value as Record;\n const mapped: Record = {\n calories: raw.calories,\n protein: raw.protein,\n carbs: raw.carbohydrate ?? raw.carbs,\n fat: raw.fat,\n fiber: raw.fiber,\n sugar: raw.sugar,\n sodium: raw.sodium,\n };\n const macros = coerceMacros(mapped);\n return Object.keys(macros).length ? macros : null;\n}\n\nfunction collectFoodResponses(record: Record): Record[] {\n const responses: Record[] = [];\n responses.push(...asRecordArray(record.food_response));\n responses.push(...asRecordArray(record.food));\n\n const foods = record.foods;\n if (foods && typeof foods === \"object\") {\n const foodsRecord = foods as Record;\n responses.push(...asRecordArray(foodsRecord.food));\n } else {\n responses.push(...asRecordArray(foods));\n }\n\n return responses;\n}\n\nfunction asRecordArray(value: unknown): Record[] {\n if (!value) return [];\n if (Array.isArray(value)) {\n return value.filter((item) => item && typeof item === \"object\") as Record[];\n }\n if (typeof value === \"object\") return [value as Record];\n return [];\n}\n\nfunction roundMacroTotals(\n totals: Partial>,\n): Partial> {\n const rounded: Partial> = {};\n for (const key of MACRO_KEYS) {\n const value = totals[key];\n if (typeof value === \"number\") rounded[key] = roundNumber(value);\n }\n return rounded;\n}\n","import { coerceMacros, roundNumber, type MacroKey } from \"./food_enrich.ts\";\n\nexport type FatsecretConfig = {\n accessToken: string;\n includeFoodData?: boolean;\n compareAlways?: boolean;\n};\n\nconst FATSECRET_NLP_URL = \"https://platform.fatsecret.com/rest/natural-language-processing/v1\";\nconst MACRO_KEYS: MacroKey[] = [\"calories\", \"protein\", \"carbs\", \"fat\", \"fiber\", \"sugar\", \"sodium\"];\n\nexport async function fetchFatsecretNutrition(\n foodName: string,\n config: FatsecretConfig,\n): Promise> | null> {\n const payload: Record = {\n user_input: foodName,\n include_food_data: config.includeFoodData ?? true,\n };\n\n const response = await fetch(FATSECRET_NLP_URL, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${config.accessToken}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(payload),\n });\n\n if (!response.ok) {\n console.warn(\"Fatsecret NLP request failed.\", {\n status: response.status,\n statusText: response.statusText,\n });\n return null;\n }\n\n const data = (await response.json()) as unknown;\n return extractFatsecretMacros(data);\n}\n\nfunction extractFatsecretMacros(\n data: unknown,\n): Partial> | null {\n if (!data || typeof data !== \"object\") return null;\n const record = data as Record;\n\n const direct = extractTotalMacros(record.total_nutritional_content);\n if (direct) return direct;\n\n const responses = collectFoodResponses(record);\n if (!responses.length) return null;\n\n const totals: Partial> = {};\n let found = false;\n for (const response of responses) {\n const macros = extractTotalMacros(response.total_nutritional_content);\n if (!macros) continue;\n found = true;\n for (const key of MACRO_KEYS) {\n const value = macros[key];\n if (typeof value !== \"number\") continue;\n totals[key] = (totals[key] ?? 0) + value;\n }\n }\n\n if (!found) return null;\n return roundMacroTotals(totals);\n}\n\nfunction extractTotalMacros(\n value: unknown,\n): Partial> | null {\n if (!value || typeof value !== \"object\") return null;\n const raw = value as Record;\n const mapped: Record = {\n calories: raw.calories,\n protein: raw.protein,\n carbs: raw.carbohydrate ?? raw.carbs,\n fat: raw.fat,\n fiber: raw.fiber,\n sugar: raw.sugar,\n sodium: raw.sodium,\n };\n const macros = coerceMacros(mapped);\n return Object.keys(macros).length ? macros : null;\n}\n\nfunction collectFoodResponses(record: Record): Record[] {\n const responses: Record[] = [];\n responses.push(...asRecordArray(record.food_response));\n responses.push(...asRecordArray(record.food));\n\n const foods = record.foods;\n if (foods && typeof foods === \"object\") {\n const foodsRecord = 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\"$schema\": \"https://raw.githubusercontent.com/denoland/deno/98f62cee78e85bfc47c62ed703777c6bc8794f1c/cli/schemas/config-file.v1.json\",\n \"lock\": false,\n \"compilerOptions\": {\n \"noImplicitAny\": false,\n \"strict\": true,\n \"types\": [\"https://www.val.town/types/valtown.d.ts\"],\n \"lib\": [\n \"dom\",\n \"dom.iterable\",\n \"dom.asynciterable\",\n \"deno.ns\",\n \"deno.unstable\"\n ]\n },\n \"lint\": {\n \"include\": [\"**/*.ts\", \"**/*.tsx\", \"deno:/https/esm.town/**/*\"],\n \"rules\": {\n \"exclude\": [\"no-explicit-any\", \"no-import-prefix\"]\n }\n },\n \"node_modules_dir\": false,\n \"experimental\": {\n \"unstable-node-globals\": true,\n \"unstable-temporal\": true,\n \"unstable-worker-options\": true,\n \"unstable-sloppy-imports\": true\n },\n \"tasks\": {\n \"test\": \"deno test --allow-import --reporter=dot\"\n }\n}\n","label",[142],"4f85528a-f4c6-11f0-971c-42dde27851f2","TUTORIAL.md","4f855334-f4c6-11f0-971c-42dde27851f2",360,["D",1768779301679],"# Notion Life Tracker Tutorial (Val Town)\n\nThis walkthrough shows how to build, deploy, and operate the Notion-backed logging app in this repo. It is based on the commit log, `README.md`, and `PLAN.md`, and it explains why the architecture evolves as features are added.\n\n## 0) What you are building\n\nYou will end up with three Val Town scripts:\n- A weekly blood sugar report that emails a summary and persists rollups to SQLite.\n- A weekly food log enricher that estimates macros with OpenAI and writes them back to Notion.\n- A monthly report page that renders HTML from the stored weekly rollups.\n\nThe design is intentionally layered so the system stays fast and predictable as data grows.\n\n## 1) Architecture overview (and why it is shaped this way)\n\nThe code is split by responsibility:\n- `collectors/`: scheduled jobs that pull the last 7 days of Notion data and compute a weekly rollup.\n- `shared/`: reusable parsing and rollup logic shared across collectors.\n- `storage/`: SQLite persistence so reports do not have to re-scan Notion.\n- `services/`: HTTP endpoints for reporting (monthly report page) and optional rollup ingestion.\n\nWhy this architecture works as the app grows:\n1) **Short Notion queries stay fast.** Each collector only asks Notion for a one-week window. This keeps API calls cheap and predictable even as your Notion database grows.\n2) **Rollups make reporting cheap.** Once a weekly rollup is computed, it is stored in SQLite (`weekly_rollups_1`). Monthly pages and future yearly summaries can use SQLite instead of Notion.\n3) **Idempotent writes avoid duplicates.** Rollups use a deterministic `runId` (for example `blood_sugar-YYYY-MM-DD-YYYY-MM-DD`) and SQLite has a unique constraint on `run_id`, so re-running a week does not double-count.\n4) **Collectors stay focused.** Each collector normalizes its own Notion database, then hands off common logic to `shared/` and storage to `storage/`.\n5) **HTTP services scale reporting.** The monthly report page is just a read-only HTTP val that reads SQLite and renders HTML. This keeps interactive reporting separate from scheduled ingestion.\n\n## 2) Set up Notion databases\n\nCreate two Notion databases (table view recommended).\n\n### Blood Sugar Log\nProperties (exact names expected):\n- `Entry` (Title)\n- `Created Time` (Created time) or `Created Time` (Text)\n- `Measurement Date` (Date)\n- `Blood Sugar Level` (Number)\n\n### Food Log (Macro Enrichment)\nProperties (exact names expected):\n- `food` (Title or Text)\n- `Created time` (Created time)\n- `calories` (Number)\n- `protein` (Number)\n- `carbs` (Number)\n- `fats` (Number)\n- `fiber` (Number)\n- `sugar` (Number)\n- `sodium` (Number)\n\nOnly `food` and `Created time` are required to read; the rest will be written by the food enricher.\n\n## 3) Create a Notion integration\n\n1. Go to https://www.notion.so/my-integrations and create a new integration.\n2. Copy the **Internal Integration Token**.\n3. Open each database, click **Share**, and invite the integration.\n4. Copy each database ID (the 32-character ID in the URL).\n\n## 4) Create Val Town vals and deploy\n\nCreate vals for each script:\n```bash\nvt create blood_sugar_report\nvt create food_report\nvt create monthly_report_page\n```\n\nReplace the contents of the new vals with these repo files:\n- `collectors/blood_sugar_report.cron.tsx`\n- `collectors/food_report.cron.tsx`\n- `services/monthly_report_page.http.tsx`\n\nPush everything:\n```bash\nvt push\n```\n\n## 5) Configure secrets in Val Town\n\nShared:\n- `NOTION_TOKEN`\n\nBlood sugar report:\n- `NOTION_BLOOD_SUGAR_DB_ID`\n\nFood report:\n- `NOTION_FOOD_DB_ID`\n\nNotes:\n- On the free tier, the blood sugar report always emails the account owner; sender options are not configurable.\n- The food val uses Val Town's `std/openai` proxy with `gpt-5-nano`, so you do not need an OpenAI API key.\n\n## 6) Schedule the weekly collectors\n\nSchedule both collectors in Val Town. A typical schedule is Tuesday at 9:30am EST.\n\n```\n30 9 * * 2\n```\n\nCron fields:\n```\nminute hour day-of-month month day-of-week\n```\n\n## 7) Operate and verify\n\n### Validate after the first run\n- Blood sugar val should send an email and write a rollup row to SQLite.\n- Food val should enrich any missing macros and write a rollup row to SQLite.\n- Monthly report page should render without errors.\n\nIf you need to manually trigger a week, run the vals once in Val Town. The rollup table is idempotent because `run_id` is unique.\n\n### Where the data goes\n- Weekly rollups: `storage/rollups.ts` stores them in `weekly_rollups_1`.\n- Monthly report page: `services/monthly_report_page.http.tsx` reads from SQLite and renders the month.\n\n### Monthly report page usage\nThe monthly report page supports query parameters:\n- `?month=YYYY-MM` (defaults to previous month)\n- `?partial=true` to include weeks that overlap the month boundary\n\n## 8) Why the architecture evolves (from commit history)\n\nThe project grew in stages:\n1) **Weekly Notion email**: the first goal was a friendly weekly report without heavy infrastructure.\n2) **Tests and logic extraction**: core rollup logic moved into `shared/` with tests, keeping collectors small.\n3) **Macro enrichment**: a second collector was added for food logs, reusing the same weekly-window approach.\n4) **SQLite persistence**: weekly rollups were persisted so monthly/annual summaries could be built without re-reading Notion.\n5) **Monthly report page**: an HTTP val renders a full HTML report from SQLite data.\n\nEach step keeps the system simple while expanding capabilities:\n- We never need to scan all of Notion.\n- Scheduled jobs do a single week of work.\n- Reports are built from stored rollups, not raw entries.\n\n## 9) Extend the system (pattern for new trackers)\n\nTo add a new tracker:\n1. Create a new Notion database and define its properties.\n2. Add a new collector val in `collectors/` that:\n - pulls a weekly window from Notion,\n - maps it into a shared rollup format,\n - persists to SQLite using `upsertWeeklyRollup`.\n3. Add new aggregations in `shared/` and extend the monthly report page if desired.\n\nThis keeps the system consistent and avoids one-off logic when more categories are added.\n\n## 10) Local development\n\nRun tests:\n```bash\ndeno test --allow-import --reporter=dot\n```\n\nRun lint:\n```bash\ndeno lint\n```\n",[152],"4f899f48-f4c6-11f0-8f2a-42dde27851f2","README.md","904dec56-f0bf-11f0-a3c7-42dde27851f2",361,["D",1768779301699],24,"# Notion Life Tracker (Val Town)\n\nThis repo contains Val Town-ready scripts that:\n- fetch Notion entries for the last 7 days (UTC)\n- send a weekly blood sugar rollup via email\n- enrich food log entries with estimated macros and write them back to Notion\n\n## What this does (plain language)\n\nThink of this as two simple helpers:\n- You write down blood sugar readings in Notion.\n- Once a week, the script looks at the last 7 days and emails you a summary.\n- You write down foods you ate in another Notion database.\n- The food script estimates macros and fills them in.\n\n## A tiny bit of computer science (friendly version)\n\nEven though this feels simple, it uses a few classic CS ideas:\n- **Data modeling:** you define what a “reading” is (date, time, value).\n- **Filtering:** you only look at a specific window of time (last 7 days).\n- **Aggregation:** you summarize many values into a few stats (avg/min/max).\n- **Automation:** a scheduled job runs the same steps every week.\n\nIf you can build or understand this, you’re already practicing real CS thinking—just without the scary jargon.\n\n## Praise Cage mode\n\nThis project includes playful, Praise Cage-themed badges:\n- “Mandy-Mode Consistency”\n- “Cage Match: Full Week”\n- “Cage Match: Double-Check Champion”\n- “National Treasure: Healthy Average”\n\nYou can rename or swap these in `collectors/blood_sugar_report.cron.tsx`.\n\n## Medical disclaimer\n\nThis report is for informational purposes only and is not medical advice.\nHealthy blood sugar ranges referenced here come from:\nhttps://www.ynhhs.org/articles/what-is-healthy-blood-sugar\n\n## 1) Create the Notion databases\n\n### Blood Sugar Log\n\nCreate a new database in Notion (table view is easiest) with these properties:\n\n- **Entry** (Title)\n- **Created Time** (Created time) or **Created Time** (Text)\n- **Measurement Date** (Date) (e.g., `January 13, 2026`)\n- **Blood Sugar Level** (Number)\n\nYou can name the database anything (e.g., \"Blood Sugar Log\").\n\n### Food Log (Macro Enrichment)\n\nCreate another Notion database with these properties (exact names expected):\n\n- `food` (Title or Text)\n- `Created time` (Created time)\n- `calories` (Number)\n- `protein` (Number)\n- `carbs` (Number)\n- `fats` (Number)\n- `fiber` (Number)\n- `sugar` (Number)\n- `sodium` (Number)\n\nOnly `food` and `Created time` are required for reading. The rest are written by the val.\n\n## 2) Create a Notion integration\n\n1. Go to https://www.notion.so/my-integrations and create a new integration.\n2. Copy the **Internal Integration Token**.\n3. Open your database in Notion, click **Share**, and invite the integration.\n\n### Database IDs\nOpen each database in the browser and copy the 32‑character ID in the URL.\n\n## 3) Configure Val Town (CLI)\n\nCreate new Vals with the `vt` CLI, then sync from this repo:\n\n```\nvt create blood_sugar_report\nvt create food_report\nvt create monthly_report_page\n```\n\nReplace each generated Val file with the corresponding script from this repo:\n- `collectors/blood_sugar_report.cron.tsx`\n- `collectors/food_report.cron.tsx`\n- `services/monthly_report_page.http.tsx`\n\nThen push each Val:\n\n```\nvt push\n```\n\n### Secrets\n\nShared:\n- `NOTION_TOKEN`\n\nBlood sugar val:\n- `NOTION_BLOOD_SUGAR_DB_ID`\n\nFood log val:\n- `NOTION_FOOD_DB_ID`\n\nFree tier note: the blood sugar val always emails the account owner by default, and sender options are not configurable on free accounts.\n\nThe food val uses Val Town's `std/openai` proxy with `gpt-5-nano`, so no OpenAI API key is required.\n\nThe monthly report val renders a Memphis-inspired report page from SQLite rollups, with a month selector and partial-week toggle (auto-refresh).\n\n## 4) Schedule the report\n\nIn Val Town, schedule the Val to run weekly at 9:30am on Tuesdays (EST).\n\nSuggested cron (set Val Town timezone to EST):\n```\n30 9 * * 2\n```\n\n### What the cron line means\n\nCron is a simple way to say “run this on a schedule.” It has five fields:\n\n```\nminute hour day-of-month month day-of-week\n```\n\nSo `30 9 * * 2` means:\n- minute = 30\n- hour = 9\n- day-of-month = * (every day of the month)\n- month = * (every month)\n- day-of-week = 2 (Tuesday)\n\nIn other words: every Tuesday at 9:30am.\n\n## 5) Customize\n\n- Adjust the stats, date range, or email formatting in `collectors/blood_sugar_report.cron.tsx`.\n- If you prefer different property names, update them in the script.\n- Weekly rollups for both categories are persisted to Val Town SQLite for monthly/quarterly summaries.\n- Monthly report page supports query params:\n - `?month=YYYY-MM` (defaults to previous month)\n - `?partial=true` to include overlapping weeks\n\n## Development\n\nRun tests:\n```\ndeno test --allow-import --reporter=dot\n```\n\nRun lint:\n```\ndeno lint\n```\n\nMade with 🖖 by Paul Chin Jr. and Markal.\n",[159],"5aa8cd80-f328-11f0-99c3-42dde27851f2","PLAN.md","ff57afba-f0c9-11f0-8caa-42dde27851f2",346,["D",1768601509366],7,"# Notion Life Tracker Plan\n\n## What we've built so far\n\n- A Notion database for blood sugar readings\n- A Val Town script that pulls the last 7 days of entries\n- Weekly stats with streaks, XP, and Praise Cage-themed badges\n- A friendly email report sent on a schedule (free tier friendly)\n- Tests for core logic (streaks, badges, XP)\n- A SQLite rollup module stub for future storage\n- A food log enricher that reads Notion entries, estimates macros with OpenAI, and writes them back\n- Weekly rollups persisted to SQLite for blood sugar and food\n- Monthly rollup report page with a month selector (Memphis-styled)\n\n## Why this works well\n\n- We only query Notion for a small time window (fast even as Notion grows)\n- We compute the rollup once per week and send it as a summary\n- We can reuse the same pattern for other life areas (exercise, meals, goals)\n\n## Next step: extend rollup reporting\n\nWe store weekly rollups (badges, streaks, XP) in Val Town’s SQLite so we can:\n- build monthly and yearly summaries without re-reading Notion\n- compare across categories (e.g., blood sugar vs exercise)\n- keep a long-term history even if we rename Notion pages\n\n## Proposed storage shape\n\n- `weekly_rollups`: one row per category per week\n- `badge_events`: a history of badges earned\n\nEach rollup stores:\n- category (e.g., `blood_sugar`)\n- period start/end (YYYY-MM-DD)\n- streak, completion rate, XP\n- badges as JSON\n- summary stats as JSON\n\n## How new trackers fit in\n\nFor each new Notion database:\n1) Add a small “collector” val that maps entries into a shared event format.\n2) Reuse the rollup logic and write weekly results to SQLite.\n3) Generate emails or dashboards from the stored rollups.\n\nThis keeps the system simple while still scaling to many life areas.\n\n## What’s left to do\n\n- Define XP/badge rule config so new trackers can reuse it\n- Add yearly rollup report (from SQLite, not Notion)\n- Add a sample “collector” val for another Notion database (e.g., exercise)\n - Add run_id generation strategy (UUID or deterministic) and document it\n - Validate email layout on Gmail mobile and adjust spacing if needed\n- Improve food enrichment matching (confidence threshold, caching, or manual overrides)\n",[167],"8ac8f058-f0c1-11f0-8753-42dde27851f2",".gitignore","8ac8f116-f0c1-11f0-8753-42dde27851f2",8,["D",1768337449610],".DS_Store\n.env\n*.log\n.vt\n",[175],"4f8d04f8-f4c6-11f0-8183-42dde27851f2",".env.example","8ac592f0-f0c1-11f0-b3c8-42dde27851f2",362,["D",1768779301719],9,"NOTION_TOKEN=\nNOTION_BLOOD_SUGAR_DB_ID=\nNOTION_FOOD_DB_ID=\nFATSECRET_ACCESS_TOKEN=\nFATSECRET_INCLUDE_FOOD_DATA=true\nREPORT_FROM_EMAIL=\nREPORT_FROM_NAME=\nREPORT_REPLY_TO=\nROLLUP_PERSIST_URL=\nROLLUP_PERSIST_TOKEN=\n",[182],"0817ce82-f309-11f0-9638-42dde27851f2","tests","0817cf4a-f309-11f0-9638-42dde27851f2",272,["D",1768588056443],"directory",[190],"082c3930-f0ca-11f0-9dc7-42dde27851f2","storage","082c3a0c-f0ca-11f0-9dc7-42dde27851f2",27,["D",1768341095957],[197],"25688aae-f23b-11f0-a33f-42dde27851f2","shared","25688b9e-f23b-11f0-a33f-42dde27851f2",96,["D",1768499629303],[203],"250d8f1e-f23b-11f0-88fe-42dde27851f2","services","250d8fd2-f23b-11f0-88fe-42dde27851f2",92,["D",1768499628695],[209],"25490ec2-f23b-11f0-a33f-42dde27851f2","collectors","25490f94-f23b-11f0-a33f-42dde27851f2",95,["D",1768499629095],[215],"25774a44-f23b-11f0-a33f-42dde27851f2",".vscode","25774b16-f23b-11f0-a33f-42dde27851f2",97,["D",1768499629401],[221],"pulls","branches",1,"forks","envVars",{"_234":236,"_237":63},"connections",{"_234":63,"_235":63},"count","unfilledCount",12,"emptyCount",{"_45":220,"_33":221,"_31":222,"_144":-5,"_43":44,"_42":223,"_146":25,"_40":442,"_13":63,"_35":194,"_37":-5,"_24":27,"_149":-5,"_268":443,"_28":444},{"_45":434,"_33":435,"_31":436,"_144":222,"_43":44,"_42":437,"_146":25,"_40":438,"_13":63,"_35":20,"_37":439,"_24":27,"_149":-5,"_268":440,"_28":441},{"_45":426,"_33":427,"_31":428,"_144":222,"_43":44,"_42":429,"_146":25,"_40":430,"_13":63,"_35":20,"_37":431,"_24":27,"_149":-5,"_268":432,"_28":433},{"_45":214,"_33":215,"_31":216,"_144":-5,"_43":44,"_42":217,"_146":25,"_40":423,"_13":63,"_35":194,"_37":-5,"_24":27,"_149":-5,"_268":424,"_28":425},{"_45":414,"_33":415,"_31":416,"_144":216,"_43":44,"_42":417,"_146":27,"_40":418,"_13":419,"_35":410,"_37":420,"_24":27,"_149":-5,"_268":421,"_28":422},{"_45":405,"_33":406,"_31":407,"_144":216,"_43":44,"_42":408,"_146":27,"_40":409,"_13":199,"_35":410,"_37":411,"_24":27,"_149":-5,"_268":412,"_28":413},{"_45":208,"_33":209,"_31":210,"_144":-5,"_43":44,"_42":211,"_146":25,"_40":402,"_13":63,"_35":194,"_37":-5,"_24":27,"_149":-5,"_268":403,"_28":404},{"_45":393,"_33":394,"_31":395,"_144":210,"_43":44,"_42":396,"_146":27,"_40":397,"_13":398,"_35":389,"_37":399,"_24":27,"_149":-5,"_268":400,"_28":401},{"_45":384,"_33":385,"_31":386,"_144":210,"_43":44,"_42":387,"_146":25,"_40":388,"_13":228,"_35":389,"_37":390,"_24":27,"_149":-5,"_268":391,"_28":392},{"_45":202,"_33":203,"_31":204,"_144":-5,"_43":44,"_42":205,"_146":25,"_40":381,"_13":63,"_35":194,"_37":-5,"_24":27,"_149":-5,"_268":382,"_28":383},{"_45":372,"_33":373,"_31":374,"_144":204,"_43":44,"_42":375,"_146":27,"_40":376,"_13":377,"_35":36,"_37":378,"_24":27,"_149":-5,"_268":379,"_28":380},{"_45":364,"_33":365,"_31":366,"_144":204,"_43":44,"_42":367,"_146":25,"_40":368,"_13":228,"_35":36,"_37":369,"_24":27,"_149":-5,"_268":370,"_28":371},{"_45":360,"_33":34,"_31":32,"_144":204,"_43":44,"_42":14,"_146":27,"_40":361,"_13":339,"_35":36,"_37":39,"_24":27,"_149":-5,"_268":362,"_28":363},{"_45":351,"_33":352,"_31":353,"_144":204,"_43":44,"_42":354,"_146":27,"_40":355,"_13":356,"_35":36,"_37":357,"_24":27,"_149":-5,"_268":358,"_28":359},{"_45":343,"_33":344,"_31":345,"_144":204,"_43":44,"_42":346,"_146":25,"_40":347,"_13":228,"_35":36,"_37":348,"_24":27,"_149":-5,"_268":349,"_28":350},{"_45":334,"_33":335,"_31":336,"_144":204,"_43":44,"_42":337,"_146":27,"_40":338,"_13":339,"_35":36,"_37":340,"_24":27,"_149":-5,"_268":341,"_28":342},{"_45":196,"_33":197,"_31":198,"_144":-5,"_43":44,"_42":199,"_146":25,"_40":331,"_13":63,"_35":194,"_37":-5,"_24":27,"_149":-5,"_268":332,"_28":333},{"_45":322,"_33":323,"_31":324,"_144":198,"_43":44,"_42":325,"_146":27,"_40":326,"_13":327,"_35":36,"_37":328,"_24":27,"_149":-5,"_268":329,"_28":330},{"_45":189,"_33":190,"_31":191,"_144":-5,"_43":44,"_42":192,"_146":25,"_40":319,"_13":63,"_35":194,"_37":-5,"_24":27,"_149":-5,"_268":320,"_28":321},{"_45":311,"_33":312,"_31":313,"_144":191,"_43":44,"_42":314,"_146":27,"_40":315,"_13":171,"_35":36,"_37":316,"_24":27,"_149":-5,"_268":317,"_28":318},{"_45":303,"_33":304,"_31":305,"_144":191,"_43":44,"_42":306,"_146":25,"_40":307,"_13":63,"_35":36,"_37":308,"_24":27,"_149":-5,"_268":309,"_28":310},{"_45":294,"_33":295,"_31":296,"_144":191,"_43":44,"_42":297,"_146":27,"_40":298,"_13":299,"_35":36,"_37":300,"_24":27,"_149":-5,"_268":301,"_28":302},{"_45":286,"_33":287,"_31":288,"_144":191,"_43":44,"_42":289,"_146":25,"_40":290,"_13":228,"_35":36,"_37":291,"_24":27,"_149":-5,"_268":292,"_28":293},{"_45":181,"_33":182,"_31":183,"_144":-5,"_43":44,"_42":184,"_146":27,"_40":283,"_13":186,"_35":20,"_37":187,"_24":27,"_149":-5,"_268":284,"_28":285},{"_45":174,"_33":175,"_31":176,"_144":-5,"_43":44,"_42":177,"_146":27,"_40":280,"_13":63,"_35":20,"_37":179,"_24":27,"_149":-5,"_268":281,"_28":282},{"_45":166,"_33":167,"_31":168,"_144":-5,"_43":44,"_42":169,"_146":27,"_40":277,"_13":171,"_35":20,"_37":172,"_24":27,"_149":-5,"_268":278,"_28":279},{"_45":158,"_33":159,"_31":160,"_144":-5,"_43":44,"_42":161,"_146":27,"_40":274,"_13":163,"_35":20,"_37":164,"_24":27,"_149":-5,"_268":275,"_28":276},{"_45":151,"_33":152,"_31":153,"_144":-5,"_43":44,"_42":154,"_146":27,"_40":271,"_13":63,"_35":20,"_37":156,"_24":27,"_149":-5,"_268":272,"_28":273},{"_45":141,"_33":142,"_31":143,"_144":-5,"_43":44,"_42":145,"_146":27,"_40":267,"_13":63,"_35":20,"_37":148,"_24":27,"_149":-5,"_268":269,"_28":270},["D",1768499698155],"children",[],[142],["D",1768779301679],[],[152],["D",1768779301699],[],[159],["D",1768601509366],[],[167],["D",1768337449610],[],[175],["D",1768779301719],[],[182],"d38333c4-f311-11f0-9c46-42dde27851f2","rollups.test.ts","cf244a02-f311-11f0-8a46-42dde27851f2",326,["D",1768591833699],"import { buildUpsertWeeklyRollupQuery, type WeeklyRollup } from \"../storage/rollups.ts\";\nimport { assertEquals } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\n// Ensures persistence overwrites by runId instead of inserting duplicates.\nDeno.test(\"buildUpsertWeeklyRollupQuery uses INSERT OR REPLACE with runId\", () => {\n const rollup: WeeklyRollup = {\n category: \"food\",\n periodStart: \"2026-01-01\",\n periodEnd: \"2026-01-07\",\n streak: 3,\n completionRate: 57,\n xp: 12,\n badges: [\"A\"],\n stats: { totalEntries: 4 },\n runId: \"food-2026-01-01-2026-01-07\",\n };\n const createdAt = \"2026-01-08T00:00:00.000Z\";\n const query = buildUpsertWeeklyRollupQuery(rollup, createdAt);\n assertEquals(query.sql.startsWith(\"INSERT OR REPLACE\"), true);\n assertEquals(query.args[8], rollup.runId);\n assertEquals(query.args[9], createdAt);\n});\n",[],[190,287],"d7dd5e86-f311-11f0-84ea-42dde27851f2","notion_weekly_report.test.ts","46d7e2ba-f0ca-11f0-b918-42dde27851f2",327,["D",1768591841001],15,"import {\n buildBadges,\n buildEncouragement,\n buildBloodSugarRollup,\n calculateXp,\n formatCreatedTime,\n formatGroupedEntryLine,\n groupEntriesByDate,\n hasPerfectWeekStreak,\n type Entry,\n} from \"../shared/blood_sugar_logic.ts\";\nimport { calculateCurrentStreak, countEntriesByDate, listDateRange } from \"../shared/date.ts\";\nimport { assertEquals, assertStringIncludes } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\nDeno.test(\"listDateRange returns inclusive dates\", () => {\n const dates = listDateRange(\"2026-01-01\", \"2026-01-03\");\n assertEquals(dates, [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\"]);\n});\n\nDeno.test(\"calculateCurrentStreak counts trailing days with entries\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\", \"2026-01-04\"];\n const counts = { \"2026-01-02\": 1, \"2026-01-03\": 2, \"2026-01-04\": 1 };\n const streak = calculateCurrentStreak(range, counts);\n assertEquals(streak, 3);\n});\n\nDeno.test(\"calculateCurrentStreak stops at first missing day\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\"];\n const counts = { \"2026-01-01\": 1, \"2026-01-03\": 1 };\n const streak = calculateCurrentStreak(range, counts);\n assertEquals(streak, 1);\n});\n\nDeno.test(\"countEntriesByDate aggregates by date\", () => {\n const entries: Entry[] = [\n { date: \"2026-01-01\", createdTime: null, value: 90 },\n { date: \"2026-01-01\", createdTime: null, value: 95 },\n { date: \"2026-01-02\", createdTime: null, value: 100 },\n ];\n assertEquals(countEntriesByDate(entries), { \"2026-01-01\": 2, \"2026-01-02\": 1 });\n});\n\nDeno.test(\"buildBadges awards consistency and healthy average\", () => {\n const range = [\n \"2026-01-01\",\n \"2026-01-02\",\n \"2026-01-03\",\n \"2026-01-04\",\n \"2026-01-05\",\n \"2026-01-06\",\n \"2026-01-07\",\n ];\n const counts = {\n \"2026-01-01\": 2,\n \"2026-01-02\": 2,\n \"2026-01-03\": 2,\n \"2026-01-04\": 2,\n \"2026-01-05\": 2,\n \"2026-01-06\": 2,\n \"2026-01-07\": 2,\n };\n const badges = buildBadges(range, counts, 14, 95, true);\n assertEquals(badges.includes(\"Cage Match: Double-Check Champion\"), true);\n assertEquals(badges.includes(\"National Treasure: Healthy Average\"), true);\n});\n\nDeno.test(\"buildEncouragement returns positive message\", () => {\n const message = buildEncouragement(85, 2);\n assertStringIncludes(message, \"Great\");\n});\n\nDeno.test(\"hasPerfectWeekStreak requires two entries per day\", () => {\n const range = [\n \"2026-01-01\",\n \"2026-01-02\",\n \"2026-01-03\",\n \"2026-01-04\",\n \"2026-01-05\",\n \"2026-01-06\",\n \"2026-01-07\",\n ];\n const counts = {\n \"2026-01-01\": 2,\n \"2026-01-02\": 2,\n \"2026-01-03\": 2,\n \"2026-01-04\": 2,\n \"2026-01-05\": 2,\n \"2026-01-06\": 2,\n \"2026-01-07\": 1,\n };\n assertEquals(hasPerfectWeekStreak(range, counts), false);\n});\n\nDeno.test(\"calculateXp applies streak and healthy average bonuses\", () => {\n const xp = calculateXp(14, 95, true);\n assertEquals(xp, 242);\n});\n\n// Boundary check: average at threshold should not get the healthy bonus.\nDeno.test(\"calculateXp does not apply healthy bonus at threshold\", () => {\n const xp = calculateXp(10, 100, true);\n assertEquals(xp, 144);\n});\n\n// Ensure minimum thresholds gate badges.\nDeno.test(\"buildBadges respects minimum thresholds\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\", \"2026-01-04\", \"2026-01-05\", \"2026-01-06\", \"2026-01-07\"];\n const counts = Object.fromEntries(range.map((date) => [date, 2]));\n const badges = buildBadges(range, counts, 6, 110, false);\n assertEquals(badges.includes(\"Mandy-Mode Consistency\"), false);\n assertEquals(badges.includes(\"Cage Match: Double-Check Champion\"), false);\n});\n\n// Perfect week requires 2+ entries every day in a 7-day window.\nDeno.test(\"hasPerfectWeekStreak returns true for full week\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\", \"2026-01-04\", \"2026-01-05\", \"2026-01-06\", \"2026-01-07\"];\n const counts = Object.fromEntries(range.map((date) => [date, 2]));\n assertEquals(hasPerfectWeekStreak(range, counts), true);\n});\n\nDeno.test(\"formatCreatedTime extracts time from Notion-style string\", () => {\n const formatted = formatCreatedTime(\"January 13, 2026 6:33 PM\");\n assertEquals(formatted, \"6:33 PM\");\n});\n\nDeno.test(\"formatCreatedTime formats ISO timestamps\", () => {\n const formatted = formatCreatedTime(\"2026-01-13T18:33:00.000Z\");\n assertEquals(formatted, \"6:33 PM\");\n});\n\nDeno.test(\"formatGroupedEntryLine orders entries by time\", () => {\n const entries: Entry[] = [\n { date: \"2026-01-01\", createdTime: \"6:30 PM\", value: 110 },\n { date: \"2026-01-01\", createdTime: \"6:30 AM\", value: 90 },\n ];\n const grouped = groupEntriesByDate(entries, [\"2026-01-01\"]);\n const line = formatGroupedEntryLine(grouped[0]);\n assertEquals(line, \"2026-01-01 | 1st: 90 | 2nd: 110\");\n});\n\nDeno.test(\"buildBloodSugarRollup uses deterministic runId and stats\", () => {\n const entries: Entry[] = [\n { date: \"2026-01-01\", createdTime: \"7:00 AM\", value: 90 },\n { date: \"2026-01-01\", createdTime: \"7:00 PM\", value: 100 },\n ];\n const rollup = buildBloodSugarRollup(entries, \"2026-01-01\", \"2026-01-07\");\n assertEquals(rollup.category, \"blood_sugar\");\n assertEquals(rollup.runId, \"blood_sugar-2026-01-01-2026-01-07\");\n assertEquals(rollup.stats.totalEntries, 2);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-01\"], 2);\n});\n",[],[190,295],"0452ba82-f31d-11f0-9bc9-42dde27851f2","monthly_report.test.ts","0452bb22-f31d-11f0-9bc9-42dde27851f2",331,["D",1768596640052],"import {\n aggregateBloodSugarMonth,\n aggregateFoodMonth,\n resolveMonthRange,\n type Rollup,\n} from \"../shared/monthly_report.ts\";\nimport { assertEquals } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\n// Overlapping rollups should not double-count entries by date.\nDeno.test(\"aggregateFoodMonth de-dupes overlapping entriesByDate\", () => {\n const rollups: Rollup[] = [\n {\n category: \"food\",\n periodStart: \"2026-01-01\",\n periodEnd: \"2026-01-07\",\n streak: 2,\n completionRate: 50,\n xp: 0,\n badges: [],\n stats: { entriesByDate: { \"2026-01-02\": 1 } },\n runId: \"food-2026-01-01-2026-01-07\",\n },\n {\n category: \"food\",\n periodStart: \"2026-01-05\",\n periodEnd: \"2026-01-11\",\n streak: 1,\n completionRate: 40,\n xp: 0,\n badges: [],\n stats: { entriesByDate: { \"2026-01-02\": 1, \"2026-01-06\": 2 } },\n runId: \"food-2026-01-05-2026-01-11\",\n },\n ];\n const summary = aggregateFoodMonth(rollups, \"2026-01-01\", \"2026-01-31\", {\n includePartialWeeks: true,\n });\n assertEquals(summary.entriesByDate[\"2026-01-02\"], 1);\n assertEquals(summary.entriesByDate[\"2026-01-06\"], 2);\n assertEquals(summary.totalEntries, 3);\n});\n\n// Monthly aggregation should compute weighted averages and totals.\nDeno.test(\"aggregateBloodSugarMonth computes weighted average and totals\", () => {\n const rollups: Rollup[] = [\n {\n category: \"blood_sugar\",\n periodStart: \"2026-01-01\",\n periodEnd: \"2026-01-07\",\n streak: 3,\n completionRate: 70,\n xp: 120,\n badges: [\"A\"],\n stats: {\n entriesByDate: { \"2026-01-01\": 2 },\n avg: 90,\n min: 80,\n max: 110,\n totalEntries: 2,\n },\n runId: \"blood_sugar-2026-01-01-2026-01-07\",\n },\n {\n category: \"blood_sugar\",\n periodStart: \"2026-01-08\",\n periodEnd: \"2026-01-14\",\n streak: 1,\n completionRate: 50,\n xp: 60,\n badges: [\"B\"],\n stats: {\n entriesByDate: { \"2026-01-08\": 2 },\n avg: 110,\n min: 85,\n max: 130,\n totalEntries: 2,\n },\n runId: \"blood_sugar-2026-01-08-2026-01-14\",\n },\n ];\n const summary = aggregateBloodSugarMonth(rollups, \"2026-01-01\", \"2026-01-31\");\n assertEquals(summary.totalEntries, 4);\n assertEquals(summary.average, 100);\n assertEquals(summary.min, 80);\n assertEquals(summary.max, 130);\n assertEquals(summary.xp, 180);\n});\n\nDeno.test(\"resolveMonthRange defaults to previous month\", () => {\n const now = new Date(\"2026-02-15T10:00:00.000Z\");\n const range = resolveMonthRange(null, now);\n assertEquals(range.start, \"2026-01-01\");\n assertEquals(range.end, \"2026-01-31\");\n});\n",[],[190,304],"dc4d3266-f311-11f0-b56a-42dde27851f2","food_report.test.ts","e01ea7f2-f308-11f0-8ecb-42dde27851f2",328,["D",1768591848438],"import {\n buildNutritionProperties,\n buildNutritionPrompt,\n coerceMacros,\n coerceNumber,\n extractFoodName,\n extractMacros,\n parseEntry,\n PROPERTY_NAMES,\n roundNumber,\n safeParseJson,\n shouldEnrich,\n type Entry,\n buildFoodRollup,\n} from \"../shared/food_enrich.ts\";\nimport { assert, assertEquals, assertStringIncludes } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\nDeno.test(\"extractFoodName handles title and rich text\", () => {\n const titleName = extractFoodName({\n title: [{ plain_text: \"cheese omelette\" }],\n });\n assertEquals(titleName, \"cheese omelette\");\n\n const richTextName = extractFoodName({\n rich_text: [{ plain_text: \" tofu bowl \" }],\n });\n assertEquals(richTextName, \"tofu bowl\");\n\n const missingName = extractFoodName(undefined);\n assertEquals(missingName, null);\n});\n\nDeno.test(\"parseEntry uses Created time and extracts food/macros\", () => {\n const page = {\n id: \"page-1\",\n properties: {\n [PROPERTY_NAMES.loggedAt]: { created_time: \"2026-01-16T14:12:00.000Z\" },\n [PROPERTY_NAMES.title]: { title: [{ plain_text: \"cheese omelette\" }] },\n [PROPERTY_NAMES.macros.calories]: { number: 320 },\n [PROPERTY_NAMES.macros.protein]: { number: 18 },\n [PROPERTY_NAMES.macros.carbs]: { number: null },\n },\n };\n const entry = parseEntry(page);\n assert(entry);\n assertEquals(entry.pageId, \"page-1\");\n assertEquals(entry.date, \"2026-01-16\");\n assertEquals(entry.food, \"cheese omelette\");\n assertEquals(entry.macros, { calories: 320, protein: 18 });\n});\n\nDeno.test(\"parseEntry ignores pages without a timestamp\", () => {\n const page = {\n id: \"page-2\",\n properties: {\n [PROPERTY_NAMES.title]: { title: [{ plain_text: \"missing time\" }] },\n },\n };\n const entry = parseEntry(page);\n assertEquals(entry, null);\n});\n\nDeno.test(\"extractMacros only returns numeric values\", () => {\n const macros = extractMacros({\n [PROPERTY_NAMES.macros.calories]: { number: 300 },\n [PROPERTY_NAMES.macros.protein]: { number: null },\n [PROPERTY_NAMES.macros.carbs]: { number: 12 },\n [PROPERTY_NAMES.macros.fat]: { number: \"10\" },\n });\n assertEquals(macros, { calories: 300, carbs: 12 });\n});\n\nDeno.test(\"shouldEnrich returns true if any core macros are missing\", () => {\n const base: Entry = {\n pageId: \"page-3\",\n date: \"2026-01-16\",\n loggedAt: \"2026-01-16T10:00:00.000Z\",\n food: \"toast\",\n macros: { calories: 200, protein: 8, carbs: 20, fat: 4 },\n };\n assertEquals(shouldEnrich(base), false);\n assertEquals(shouldEnrich({ ...base, macros: { ...base.macros, fat: undefined } }), true);\n});\n\nDeno.test(\"buildNutritionProperties maps to Notion property names\", () => {\n const props = buildNutritionProperties({\n calories: 120,\n protein: 6,\n carbs: 10,\n fat: 4,\n fiber: 2,\n sugar: 1,\n sodium: 300,\n });\n assertEquals(props, {\n [PROPERTY_NAMES.macros.calories]: { number: 120 },\n [PROPERTY_NAMES.macros.protein]: { number: 6 },\n [PROPERTY_NAMES.macros.carbs]: { number: 10 },\n [PROPERTY_NAMES.macros.fat]: { number: 4 },\n [PROPERTY_NAMES.macros.fiber]: { number: 2 },\n [PROPERTY_NAMES.macros.sugar]: { number: 1 },\n [PROPERTY_NAMES.macros.sodium]: { number: 300 },\n });\n});\n\nDeno.test(\"buildNutritionPrompt includes the food text\", () => {\n const prompt = buildNutritionPrompt(\"cheese omelette\");\n assertStringIncludes(prompt, \"cheese omelette\");\n});\n\nDeno.test(\"safeParseJson returns null for invalid JSON\", () => {\n assertEquals(safeParseJson(\"{oops}\"), null);\n assertEquals(safeParseJson(\"\"), null);\n assertEquals(safeParseJson('{\"ok\":true}'), { ok: true });\n});\n\nDeno.test(\"coerceNumber handles strings and rounds\", () => {\n assertEquals(coerceNumber(2.345), 2.35);\n assertEquals(coerceNumber(\"12.1\"), 12.1);\n assertEquals(coerceNumber(\"bad\"), undefined);\n});\n\nDeno.test(\"coerceMacros filters invalid fields\", () => {\n const macros = coerceMacros({\n calories: \"100.4\",\n protein: 12,\n carbs: \"bad\",\n fat: null,\n fiber: 3.333,\n sugar: \"4.2\",\n sodium: \"350\",\n });\n assertEquals(macros, {\n calories: 100.4,\n protein: 12,\n fiber: 3.33,\n sugar: 4.2,\n sodium: 350,\n });\n});\n\nDeno.test(\"roundNumber rounds to two decimals\", () => {\n assertEquals(roundNumber(3.14159), 3.14);\n});\n\n// Rollup should aggregate entries and use deterministic runId.\nDeno.test(\"buildFoodRollup aggregates weekly stats\", () => {\n const entries: Entry[] = [\n {\n pageId: \"page-1\",\n date: \"2026-01-01\",\n loggedAt: \"2026-01-01T12:00:00.000Z\",\n food: \"toast\",\n macros: { calories: 100, protein: 4 },\n },\n {\n pageId: \"page-2\",\n date: \"2026-01-02\",\n loggedAt: \"2026-01-02T12:00:00.000Z\",\n food: \"eggs\",\n macros: { calories: 200, protein: 12 },\n },\n ];\n const rollup = buildFoodRollup(entries, \"2026-01-01\", \"2026-01-07\");\n assertEquals(rollup.category, \"food\");\n assertEquals(rollup.stats.totalEntries, 2);\n assertEquals(rollup.stats.uniqueDays, 2);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-01\"], 1);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-02\"], 1);\n assertEquals(rollup.runId, \"food-2026-01-01-2026-01-07\");\n});\n",[],[190,312],["D",1768588056443],[257,258,259,260],[190],"8c4cb124-f311-11f0-b07e-42dde27851f2","rollups.ts","08468100-f0ca-11f0-80e1-42dde27851f2",317,["D",1768591714215],3,"import { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\n\nconst WEEKLY_ROLLUPS_TABLE = \"weekly_rollups_1\";\nconst BADGE_EVENTS_TABLE = \"badge_events_1\";\n\nexport type WeeklyRollup = {\n category: string;\n periodStart: string; // YYYY-MM-DD\n periodEnd: string; // YYYY-MM-DD\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: Record;\n runId: string;\n};\n\nexport type BadgeEvent = {\n category: string;\n badge: string;\n periodStart: string; // YYYY-MM-DD\n periodEnd: string; // YYYY-MM-DD\n awardedAt: string; // ISO timestamp\n reason?: string;\n};\n\nexport async function initRollupSchema() {\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS ${WEEKLY_ROLLUPS_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n category TEXT NOT NULL,\n period_start TEXT NOT NULL,\n period_end TEXT NOT NULL,\n streak INTEGER NOT NULL,\n completion_rate REAL NOT NULL,\n xp INTEGER NOT NULL,\n badges_json TEXT NOT NULL,\n stats_json TEXT NOT NULL,\n run_id TEXT NOT NULL,\n created_at TEXT NOT NULL,\n UNIQUE(category, period_start),\n UNIQUE(run_id)\n )`);\n\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS ${BADGE_EVENTS_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n category TEXT NOT NULL,\n badge TEXT NOT NULL,\n period_start TEXT NOT NULL,\n period_end TEXT NOT NULL,\n awarded_at TEXT NOT NULL,\n reason TEXT\n )`);\n}\n\nexport async function upsertWeeklyRollup(rollup: WeeklyRollup) {\n const createdAt = new Date().toISOString();\n await sqlite.execute(\n buildUpsertWeeklyRollupQuery(rollup, createdAt),\n );\n}\n\nexport function buildUpsertWeeklyRollupQuery(rollup: WeeklyRollup, createdAt: string) {\n return {\n sql: `INSERT OR REPLACE INTO ${WEEKLY_ROLLUPS_TABLE} (\n category,\n period_start,\n period_end,\n streak,\n completion_rate,\n xp,\n badges_json,\n stats_json,\n run_id,\n created_at\n ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [\n rollup.category,\n rollup.periodStart,\n rollup.periodEnd,\n rollup.streak,\n rollup.completionRate,\n rollup.xp,\n JSON.stringify(rollup.badges),\n JSON.stringify(rollup.stats),\n rollup.runId,\n createdAt,\n ],\n };\n}\n\nexport async function insertBadgeEvents(events: BadgeEvent[]) {\n for (const event of events) {\n await sqlite.execute(\n `INSERT INTO ${BADGE_EVENTS_TABLE} (\n category,\n badge,\n period_start,\n period_end,\n awarded_at,\n reason\n ) VALUES (?, ?, ?, ?, ?, ?)`,\n [\n event.category,\n event.badge,\n event.periodStart,\n event.periodEnd,\n event.awardedAt,\n event.reason ?? null,\n ],\n );\n }\n}\n\nexport async function getWeeklyRollups(category: string, start: string, end: string) {\n const result = await sqlite.execute(\n `SELECT * FROM ${WEEKLY_ROLLUPS_TABLE}\n WHERE category = ?\n AND period_start >= ?\n AND period_end <= ?\n ORDER BY period_start ASC`,\n [category, start, end],\n );\n return result.rows;\n}\n",[],[197,323],["D",1768341095957],[255],[197],"e86bd2c0-f328-11f0-b05e-42dde27851f2","notion.ts","2dc9ba38-f23b-11f0-b902-42dde27851f2",353,["D",1768601747203],2,"export const NOTION_VERSION = \"2022-06-28\";\n\n// Minimal Notion types used by the collectors.\nexport type NotionRichText = { plain_text: string };\nexport type NotionDateProperty = { date: { start: string } | null };\nexport type NotionNumberProperty = { number: number | null };\nexport type NotionTextProperty = { rich_text: NotionRichText[] };\nexport type NotionCreatedTimeProperty = { created_time: string };\nexport type NotionTitleProperty = { title: NotionRichText[] };\n\nexport type NotionPage = {\n id: string;\n properties: Record;\n};\n\nexport type NotionQueryResponse = {\n results: NotionPage[];\n has_more: boolean;\n next_cursor: string | null;\n};\n\n// Fetch all pages from a Notion database (handles pagination).\nexport async function fetchNotionPages(\n databaseId: string,\n token: string,\n buildBody: (cursor?: string) => Record,\n): Promise {\n const url = `https://api.notion.com/v1/databases/${databaseId}/query`;\n const headers = {\n Authorization: `Bearer ${token}`,\n \"Notion-Version\": NOTION_VERSION,\n \"Content-Type\": \"application/json\",\n };\n\n const pages: T[] = [];\n let cursor: string | null | undefined;\n\n do {\n const body = buildBody(cursor ?? undefined);\n const response = await fetch(url, {\n method: \"POST\",\n headers,\n body: JSON.stringify(body),\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`Notion query failed: ${response.status} ${text}`);\n }\n\n const data = (await response.json()) as unknown;\n if (!isNotionQueryResponse(data)) {\n throw new Error(\"Notion query returned unexpected shape.\");\n }\n\n pages.push(...(data.results as T[]));\n cursor = data.has_more && data.next_cursor ? data.next_cursor : undefined;\n } while (cursor);\n\n return pages;\n}\n\n// Update a Notion page's properties.\nexport async function updateNotionPage(\n pageId: string,\n token: string,\n properties: Record,\n): Promise {\n const url = `https://api.notion.com/v1/pages/${pageId}`;\n const headers = {\n Authorization: `Bearer ${token}`,\n \"Notion-Version\": NOTION_VERSION,\n \"Content-Type\": \"application/json\",\n };\n\n const response = await fetch(url, {\n method: \"PATCH\",\n headers,\n body: JSON.stringify({ properties }),\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`Notion update failed: ${response.status} ${text}`);\n }\n}\n\n// Runtime guard for Notion query responses.\nfunction isNotionQueryResponse(value: unknown): value is NotionQueryResponse {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n return (\n Array.isArray(record.results) &&\n typeof record.has_more === \"boolean\" &&\n (typeof record.next_cursor === \"string\" || record.next_cursor === null)\n );\n}\n",[],[203,335],"0459b77c-f329-11f0-9209-42dde27851f2","monthly_report.ts","045b9332-f31d-11f0-9776-42dde27851f2",356,["D",1768601794059],"import { calculateCurrentStreak, listDateRange } from \"./date.ts\";\n\n// Types shared by the monthly rollup page.\nexport type Rollup = {\n category: string;\n periodStart: string;\n periodEnd: string;\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: Record;\n runId: string;\n};\n\nexport type MonthlySummary = {\n monthStart: string;\n monthEnd: string;\n rollupsIncluded: number;\n};\n\nexport type BloodSugarMonthlySummary = MonthlySummary & {\n totalEntries: number;\n average: number;\n min: number;\n max: number;\n completionRate: number;\n streak: number;\n xp: number;\n badges: string[];\n entriesByDate: Record;\n};\n\nexport type FoodMacroStats = {\n count: number;\n total: number;\n avg: number;\n};\n\nexport type FoodMonthlySummary = MonthlySummary & {\n totalEntries: number;\n uniqueDays: number;\n avgEntriesPerDay: number;\n minEntriesPerDay: number;\n maxEntriesPerDay: number;\n completionRate: number;\n streak: number;\n macroSummary: Record;\n entriesByDate: Record;\n};\n\ntype FoodStatsShape = {\n entriesByDate?: Record;\n macroSummary?: Record;\n totalEntries?: number;\n};\n\ntype BloodSugarStatsShape = {\n entriesByDate?: Record;\n avg?: number;\n min?: number;\n max?: number;\n totalEntries?: number;\n};\n\n// Aggregate blood sugar rollups into a single monthly summary.\nexport function aggregateBloodSugarMonth(\n rollups: Rollup[],\n monthStart: string,\n monthEnd: string,\n options: { includePartialWeeks?: boolean } = {},\n): BloodSugarMonthlySummary {\n // Default to full-week rollups to avoid double counting across overlaps.\n const dateRange = listDateRange(monthStart, monthEnd);\n const filtered = filterRollups(rollups, monthStart, monthEnd, options.includePartialWeeks ?? false);\n const entriesByDate = mergeEntriesByDate(filtered, monthStart, monthEnd);\n const totalEntries = sumValues(entriesByDate);\n\n // Use weighted average and min/max across weeks that are fully included.\n let weightedSum = 0;\n let weightedCount = 0;\n let min = Number.POSITIVE_INFINITY;\n let max = Number.NEGATIVE_INFINITY;\n let xp = 0;\n const badgeSet = new Set();\n\n for (const rollup of filtered) {\n const stats = (rollup.stats ?? {}) as BloodSugarStatsShape;\n const count = stats.totalEntries ?? 0;\n if (typeof stats.avg === \"number\" && count > 0) {\n weightedSum += stats.avg * count;\n weightedCount += count;\n }\n if (typeof stats.min === \"number\") min = Math.min(min, stats.min);\n if (typeof stats.max === \"number\") max = Math.max(max, stats.max);\n xp += rollup.xp;\n for (const badge of rollup.badges ?? []) badgeSet.add(badge);\n }\n\n const average = weightedCount ? Number((weightedSum / weightedCount).toFixed(1)) : 0;\n const resolvedMin = Number.isFinite(min) ? min : 0;\n const resolvedMax = Number.isFinite(max) ? max : 0;\n const expected = dateRange.length * 2;\n const completionRate = expected ? Math.round((totalEntries / expected) * 100) : 0;\n const streak = calculateCurrentStreak(dateRange, entriesByDate);\n\n return {\n monthStart,\n monthEnd,\n rollupsIncluded: filtered.length,\n totalEntries,\n average,\n min: resolvedMin,\n max: resolvedMax,\n completionRate,\n streak,\n xp,\n badges: Array.from(badgeSet),\n entriesByDate,\n };\n}\n\n// Aggregate food rollups into a single monthly summary.\nexport function aggregateFoodMonth(\n rollups: Rollup[],\n monthStart: string,\n monthEnd: string,\n options: { includePartialWeeks?: boolean } = {},\n): FoodMonthlySummary {\n const dateRange = listDateRange(monthStart, monthEnd);\n const filtered = filterRollups(rollups, monthStart, monthEnd, options.includePartialWeeks ?? false);\n const entriesByDate = mergeEntriesByDate(filtered, monthStart, monthEnd);\n const totalEntries = sumValues(entriesByDate);\n const uniqueDays = Object.values(entriesByDate).filter((count) => count > 0).length;\n const avgEntriesPerDay = dateRange.length ? Number((totalEntries / dateRange.length).toFixed(2)) : 0;\n const minEntriesPerDay = dateRange.length\n ? Math.min(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const maxEntriesPerDay = dateRange.length\n ? Math.max(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const completionRate = dateRange.length ? Math.round((uniqueDays / dateRange.length) * 100) : 0;\n const streak = calculateCurrentStreak(dateRange, entriesByDate);\n const macroSummary = aggregateMacroSummary(filtered);\n\n return {\n monthStart,\n monthEnd,\n rollupsIncluded: filtered.length,\n totalEntries,\n uniqueDays,\n avgEntriesPerDay,\n minEntriesPerDay,\n maxEntriesPerDay,\n completionRate,\n streak,\n macroSummary,\n entriesByDate,\n };\n}\n\n// Resolve the month range from a YYYY-MM string (or default to last month).\nexport function resolveMonthRange(monthParam?: string | null, now = new Date()) {\n if (monthParam) {\n const match = monthParam.match(/^(\\d{4})-(\\d{2})$/);\n if (match) {\n const year = Number(match[1]);\n const month = Number(match[2]) - 1;\n const start = new Date(Date.UTC(year, month, 1));\n const end = new Date(Date.UTC(year, month + 1, 0));\n return { start: formatDate(start), end: formatDate(end) };\n }\n }\n const year = now.getUTCFullYear();\n const month = now.getUTCMonth();\n const start = new Date(Date.UTC(year, month - 1, 1));\n const end = new Date(Date.UTC(year, month, 0));\n return { start: formatDate(start), end: formatDate(end) };\n}\n\n// Filter rollups to the desired month window.\nfunction filterRollups(\n rollups: Rollup[],\n monthStart: string,\n monthEnd: string,\n includePartialWeeks: boolean,\n) {\n return rollups.filter((rollup) => {\n if (includePartialWeeks) {\n return rollup.periodStart <= monthEnd && rollup.periodEnd >= monthStart;\n }\n return rollup.periodStart >= monthStart && rollup.periodEnd <= monthEnd;\n });\n}\n\n// Merge per-day counts across rollups (handling overlap safely).\nfunction mergeEntriesByDate(rollups: Rollup[], monthStart: string, monthEnd: string) {\n const entriesByDate: Record = {};\n for (const rollup of rollups) {\n const stats = rollup.stats as FoodStatsShape | BloodSugarStatsShape;\n const entries = stats.entriesByDate ?? {};\n for (const [date, count] of Object.entries(entries)) {\n if (date < monthStart || date > monthEnd) continue;\n const current = entriesByDate[date];\n // When rollups overlap, prefer the larger count for a given day.\n entriesByDate[date] = current === undefined ? count : Math.max(current, count);\n }\n }\n return entriesByDate;\n}\n\n// Roll up macro stats across all matching rollups.\nfunction aggregateMacroSummary(rollups: Rollup[]) {\n const summary: Record = {};\n for (const rollup of rollups) {\n const stats = rollup.stats as FoodStatsShape;\n const macroSummary = stats.macroSummary ?? {};\n for (const [key, value] of Object.entries(macroSummary)) {\n const existing = summary[key] ?? { count: 0, total: 0, avg: 0 };\n existing.count += value.count ?? 0;\n existing.total += value.total ?? 0;\n existing.avg = existing.count ? Number((existing.total / existing.count).toFixed(2)) : 0;\n summary[key] = existing;\n }\n }\n return summary;\n}\n\n// Sum values of a date->count map.\nfunction sumValues(record: Record) {\n return Object.values(record).reduce((sum, value) => sum + value, 0);\n}\n\n// Format a Date as YYYY-MM-DD (UTC).\nfunction formatDate(value: Date) {\n return value.toISOString().slice(0, 10);\n}\n",[],[203,344],"fe2fb036-f328-11f0-b456-42dde27851f2","food_enrich.ts","659ce588-f309-11f0-b22d-42dde27851f2",355,["D",1768601783718],6,"import {\n type NotionCreatedTimeProperty,\n type NotionDateProperty,\n type NotionNumberProperty,\n type NotionPage,\n type NotionTextProperty,\n type NotionTitleProperty,\n} from \"./notion.ts\";\nimport { calculateCurrentStreak, countEntriesByDate, listDateRange } from \"./date.ts\";\n\n// Macro keys and entry types for the food log.\nexport type MacroKey = \"calories\" | \"protein\" | \"carbs\" | \"fat\" | \"fiber\" | \"sugar\" | \"sodium\";\n\nexport type Entry = {\n pageId: string;\n date: string;\n loggedAt: string;\n food: string;\n macros: Partial>;\n};\n\nexport type MacroStats = {\n count: number;\n total: number;\n avg: number;\n};\n\nexport type FoodStats = {\n totalEntries: number;\n uniqueDays: number;\n entriesByDate: Record;\n avgEntriesPerDay: number;\n minEntriesPerDay: number;\n maxEntriesPerDay: number;\n macroSummary: Partial>;\n};\n\nexport type FoodRollup = {\n category: string;\n periodStart: string;\n periodEnd: string;\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: FoodStats;\n runId: string;\n};\n\n// Mapping from Notion property names to macro fields.\nexport const PROPERTY_NAMES = {\n title: \"food\",\n loggedAt: \"Created time\",\n macros: {\n calories: \"calories\",\n protein: \"protein\",\n carbs: \"carbs\",\n fat: \"fats\",\n fiber: \"fiber\",\n sugar: \"sugar\",\n sodium: \"sodium\",\n },\n};\n\n// Parse a Notion page into a normalized food entry.\nexport function parseEntry(page: NotionPage): Entry | null {\n const props = page.properties ?? {};\n const loggedAtProp = props[PROPERTY_NAMES.loggedAt] as\n | NotionDateProperty\n | NotionCreatedTimeProperty\n | undefined;\n let loggedAt: string | null = null;\n if (loggedAtProp) {\n if (\"date\" in loggedAtProp) loggedAt = loggedAtProp.date?.start ?? null;\n if (\"created_time\" in loggedAtProp) loggedAt = loggedAtProp.created_time ?? null;\n }\n if (!loggedAt) return null;\n\n const foodProp = props[PROPERTY_NAMES.title] as NotionTitleProperty | NotionTextProperty | undefined;\n const food = extractFoodName(foodProp) ?? \"Unknown\";\n const macros = extractMacros(props);\n\n return {\n pageId: page.id,\n date: loggedAt.slice(0, 10),\n loggedAt,\n food,\n macros,\n };\n}\n\n// Normalize Notion title/rich_text into a single plain string.\nexport function extractFoodName(\n prop:\n | NotionTitleProperty\n | NotionTextProperty\n | undefined,\n): string | null {\n // Normalize Notion title/rich_text into a single plain string.\n if (!prop) return null;\n if (\"title\" in prop) {\n const value = prop.title?.map((item) => item.plain_text).join(\"\").trim();\n return value ? value : null;\n }\n if (\"rich_text\" in prop) {\n const value = prop.rich_text?.map((item) => item.plain_text).join(\"\").trim();\n return value ? value : null;\n }\n return null;\n}\n\n// Read macro number properties from a Notion page.\nexport function extractMacros(\n props: Record,\n): Partial> {\n const macros: Partial> = {};\n for (const key of Object.keys(PROPERTY_NAMES.macros) as MacroKey[]) {\n const propName = PROPERTY_NAMES.macros[key];\n const value = (props[propName] as NotionNumberProperty | undefined)?.number;\n if (typeof value === \"number\") macros[key] = value;\n }\n return macros;\n}\n\n// Only enrich entries missing core macros.\nexport function shouldEnrich(entry: Entry): boolean {\n return (\n entry.macros.calories === undefined ||\n entry.macros.protein === undefined ||\n entry.macros.carbs === undefined ||\n entry.macros.fat === undefined\n );\n}\n\n// Shape Notion property updates for numeric columns only.\nexport function buildNutritionProperties(macros: Partial>): Record {\n const props: Record = {};\n if (macros.calories !== undefined) props[PROPERTY_NAMES.macros.calories] = { number: macros.calories };\n if (macros.protein !== undefined) props[PROPERTY_NAMES.macros.protein] = { number: macros.protein };\n if (macros.carbs !== undefined) props[PROPERTY_NAMES.macros.carbs] = { number: macros.carbs };\n if (macros.fat !== undefined) props[PROPERTY_NAMES.macros.fat] = { number: macros.fat };\n if (macros.fiber !== undefined) props[PROPERTY_NAMES.macros.fiber] = { number: macros.fiber };\n if (macros.sugar !== undefined) props[PROPERTY_NAMES.macros.sugar] = { number: macros.sugar };\n if (macros.sodium !== undefined) props[PROPERTY_NAMES.macros.sodium] = { number: macros.sodium };\n return props;\n}\n\n// Build the weekly food rollup stored in SQLite.\nexport function buildFoodRollup(entries: Entry[], start: string, end: string): FoodRollup {\n const dateRange = listDateRange(start, end);\n const entriesByDate = countEntriesByDate(entries);\n const uniqueDays = dateRange.filter((date) => (entriesByDate[date] ?? 0) > 0).length;\n const totalEntries = entries.length;\n const avgEntriesPerDay = dateRange.length ? Number((totalEntries / dateRange.length).toFixed(2)) : 0;\n const minEntriesPerDay = dateRange.length\n ? Math.min(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const maxEntriesPerDay = dateRange.length\n ? Math.max(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const completionRate = dateRange.length ? Math.round((uniqueDays / dateRange.length) * 100) : 0;\n const streak = calculateCurrentStreak(dateRange, entriesByDate);\n const macroSummary = calculateMacroSummary(entries);\n\n const runId = `food-${start}-${end}`;\n\n return {\n category: \"food\",\n periodStart: start,\n periodEnd: end,\n streak,\n completionRate,\n xp: 0,\n badges: [],\n stats: {\n totalEntries,\n uniqueDays,\n entriesByDate,\n avgEntriesPerDay,\n minEntriesPerDay,\n maxEntriesPerDay,\n macroSummary,\n },\n runId,\n };\n}\n\n// Consistent rounding helper for macro math.\nexport function roundNumber(value: number): number {\n return Number(value.toFixed(2));\n}\n\n// Simple prompt for the macro estimation model.\nexport function buildNutritionPrompt(food: string): string {\n return `Estimate macros for: \"${food}\". Assume a typical single serving.`;\n}\n\n// Guard against non-JSON responses from the model.\nexport function safeParseJson(value: string): unknown {\n try {\n return JSON.parse(value);\n } catch {\n return null;\n }\n}\n\n// Aggregate macro stats across entries.\nfunction calculateMacroSummary(entries: Entry[]): Partial> {\n const summary: Partial> = {};\n for (const entry of entries) {\n for (const key of Object.keys(entry.macros) as MacroKey[]) {\n const value = entry.macros[key];\n if (typeof value !== \"number\") continue;\n const current = summary[key] ?? { count: 0, total: 0, avg: 0 };\n current.count += 1;\n current.total += value;\n current.avg = Number((current.total / current.count).toFixed(2));\n summary[key] = current;\n }\n }\n return summary;\n}\n\n// Coerce model output into numeric macro fields.\nexport function coerceMacros(value: Record): Partial> {\n const macros: Partial> = {};\n macros.calories = coerceNumber(value.calories);\n macros.protein = coerceNumber(value.protein);\n macros.carbs = coerceNumber(value.carbs);\n macros.fat = coerceNumber(value.fat);\n macros.fiber = coerceNumber(value.fiber);\n macros.sugar = coerceNumber(value.sugar);\n macros.sodium = coerceNumber(value.sodium);\n return Object.fromEntries(\n Object.entries(macros).filter(([, v]) => typeof v === \"number\" && Number.isFinite(v)),\n ) as Partial>;\n}\n\n// Convert a string or number into a rounded macro value.\nexport function coerceNumber(value: unknown): number | undefined {\n if (typeof value === \"number\" && Number.isFinite(value)) return roundNumber(value);\n if (typeof value === \"string\") {\n const trimmed = value.trim();\n const parsed = Number(trimmed);\n if (Number.isFinite(parsed)) return roundNumber(parsed);\n }\n return undefined;\n}\n",[],[203,352],"72f0cc44-f4c7-11f0-a775-42dde27851f2",["D",1768779791246],[],[203,34],"e4d88144-f328-11f0-8a43-42dde27851f2","date.ts","2de18fc8-f23b-11f0-8627-42dde27851f2",352,["D",1768601741204],"// Date helpers shared across rollup logic.\nexport function getWeeklyRange(): { start: string; end: string } {\n const today = new Date();\n const end = toDateOnly(today);\n const startDate = new Date(Date.UTC(today.getUTCFullYear(), today.getUTCMonth(), today.getUTCDate()));\n startDate.setUTCDate(startDate.getUTCDate() - 6);\n const start = toDateOnly(startDate);\n return { start, end };\n}\n\n// Convert a Date into YYYY-MM-DD (UTC).\nexport function toDateOnly(date: Date): string {\n return date.toISOString().slice(0, 10);\n}\n\n// Count days between two YYYY-MM-DD values, inclusive.\nexport function daysBetweenInclusive(start: string, end: string): number {\n const startDate = new Date(`${start}T00:00:00Z`);\n const endDate = new Date(`${end}T00:00:00Z`);\n const ms = endDate.getTime() - startDate.getTime();\n return Math.floor(ms / 86400000) + 1;\n}\n\n// List each day (YYYY-MM-DD) between two dates, inclusive.\nexport function listDateRange(start: string, end: string): string[] {\n const startDate = new Date(`${start}T00:00:00Z`);\n const endDate = new Date(`${end}T00:00:00Z`);\n const dates: string[] = [];\n const cursor = new Date(startDate.getTime());\n while (cursor <= endDate) {\n dates.push(toDateOnly(cursor));\n cursor.setUTCDate(cursor.getUTCDate() + 1);\n }\n return dates;\n}\n\n// Tally entries per date for quick rollup math.\nexport function countEntriesByDate(entries: T[]): Record {\n return entries.reduce>((acc, entry) => {\n acc[entry.date] = (acc[entry.date] ?? 0) + 1;\n return acc;\n }, {});\n}\n\n// Count consecutive days from the end of the range with at least one entry.\nexport function calculateCurrentStreak(dateRange: string[], dateCounts: Record): number {\n let streak = 0;\n for (let i = dateRange.length - 1; i >= 0; i -= 1) {\n const date = dateRange[i];\n if ((dateCounts[date] ?? 0) > 0) {\n streak += 1;\n } else {\n break;\n }\n }\n return streak;\n}\n",[],[203,365],"f3bf389c-f328-11f0-97e0-42dde27851f2","blood_sugar_logic.ts","e6a27e5e-f309-11f0-8d21-42dde27851f2",354,["D",1768601766202],5,"import { calculateCurrentStreak, countEntriesByDate, listDateRange } from \"./date.ts\";\nimport {\n type NotionCreatedTimeProperty,\n type NotionDateProperty,\n type NotionNumberProperty,\n type NotionTextProperty,\n} from \"./notion.ts\";\n\n// Scoring constants for XP and bonuses.\nconst XP_PER_ENTRY = 12;\nconst STREAK_BONUS_MULTIPLIER = 1.2;\nconst HEALTHY_AVG_BONUS_MULTIPLIER = 1.2;\nconst HEALTHY_AVG_THRESHOLD = 100;\n\n// Notion page shape and normalized entry types.\nexport type BloodSugarNotionPage = {\n id: string;\n properties: {\n \"Measurement Date\"?: NotionDateProperty;\n \"Blood Sugar Level\"?: NotionNumberProperty;\n \"Created Time\"?: NotionCreatedTimeProperty | NotionTextProperty;\n };\n};\n\nexport type Entry = {\n date: string;\n createdTime: string | null;\n value: number;\n};\n\nexport type BloodSugarRollup = {\n category: string;\n periodStart: string;\n periodEnd: string;\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: {\n totalEntries: number;\n avg: number;\n min: number;\n max: number;\n entriesByDate: Record;\n expected: number;\n missing: number;\n };\n runId: string;\n};\n\nexport type GroupedEntries = {\n date: string;\n am: Entry[];\n pm: Entry[];\n};\n\n// Parse a Notion page into a normalized entry.\nexport function parseEntry(page: BloodSugarNotionPage): Entry | null {\n // Normalize a Notion page into the minimal shape used by the report.\n const props = page.properties ?? {};\n const date = props[\"Measurement Date\"]?.date?.start ?? null;\n const value = props[\"Blood Sugar Level\"]?.number ?? null;\n if (!date || typeof value !== \"number\") return null;\n\n const createdProp = props[\"Created Time\"];\n const createdTimeRaw = isCreatedTimeProperty(createdProp)\n ? createdProp.created_time\n : isTextProperty(createdProp)\n ? createdProp.rich_text?.[0]?.plain_text ?? null\n : null;\n const createdTime = formatCreatedTime(createdTimeRaw);\n return { date: date.slice(0, 10), createdTime, value };\n}\n\n// Normalize various Notion \"created time\" formats into readable time strings.\nexport function formatCreatedTime(value: string | null): string | null {\n if (!value) return null;\n const trimmed = value.trim();\n const timeMatch = trimmed.match(/(\\d{1,2}:\\d{2}\\s*[AP]M)/i);\n if (timeMatch) {\n return timeMatch[1].toUpperCase().replace(/\\s+/, \" \");\n }\n const parsed = new Date(trimmed);\n if (Number.isNaN(parsed.getTime())) return trimmed;\n return parsed.toLocaleTimeString(\"en-US\", {\n hour: \"numeric\",\n minute: \"2-digit\",\n hour12: true,\n timeZone: \"UTC\",\n });\n}\n\n// Perfect streak means 2+ readings per day for a full week.\nexport function hasPerfectWeekStreak(dateRange: string[], dateCounts: Record): boolean {\n return dateRange.length >= 7 && dateRange.every((date) => (dateCounts[date] ?? 0) >= 2);\n}\n\n// XP is weighted by streak and healthy average bonuses.\nexport function calculateXp(totalCount: number, avg: number, perfectWeekStreak: boolean): number {\n const baseXp = totalCount * XP_PER_ENTRY;\n if (baseXp === 0) return 0;\n const streakBonus = perfectWeekStreak ? STREAK_BONUS_MULTIPLIER : 1;\n const healthyAvgBonus = avg > 0 && avg < HEALTHY_AVG_THRESHOLD ? HEALTHY_AVG_BONUS_MULTIPLIER : 1;\n return Math.round(baseXp * streakBonus * healthyAvgBonus);\n}\n\n// Build the weekly rollup stored in SQLite.\nexport function buildBloodSugarRollup(entries: Entry[], start: string, end: string): BloodSugarRollup {\n const values = entries.map((entry) => entry.value);\n const count = values.length;\n const avg = count ? Math.round((values.reduce((a, b) => a + b, 0) / count) * 10) / 10 : 0;\n const min = count ? Math.min(...values) : 0;\n const max = count ? Math.max(...values) : 0;\n\n const dateCounts = countEntriesByDate(entries);\n const dateRange = listDateRange(start, end);\n const expected = dateRange.length * 2;\n const missing = Math.max(0, expected - count);\n const completionRate = expected ? Math.round((count / expected) * 100) : 0;\n const currentStreak = calculateCurrentStreak(dateRange, dateCounts);\n const perfectWeekStreak = hasPerfectWeekStreak(dateRange, dateCounts);\n const badges = buildBadges(dateRange, dateCounts, count, avg, perfectWeekStreak);\n const xp = calculateXp(count, avg, perfectWeekStreak);\n\n return {\n category: \"blood_sugar\",\n periodStart: start,\n periodEnd: end,\n streak: currentStreak,\n completionRate,\n xp,\n badges,\n stats: {\n totalEntries: count,\n avg,\n min,\n max,\n entriesByDate: dateCounts,\n expected,\n missing,\n },\n runId: `blood_sugar-${start}-${end}`,\n };\n}\n\n// Decide which badges to award for the week.\nexport function buildBadges(\n _dateRange: string[],\n _dateCounts: Record,\n totalCount: number,\n avg: number,\n perfectWeekStreak: boolean,\n): string[] {\n const badges: string[] = [];\n if (totalCount >= 7) badges.push(\"Mandy-Mode Consistency\");\n if (totalCount >= 14) badges.push(\"Cage Match: Full Week\");\n if (perfectWeekStreak) badges.push(\"Cage Match: Double-Check Champion\");\n if (avg > 0 && avg < HEALTHY_AVG_THRESHOLD) badges.push(\"National Treasure: Healthy Average\");\n return badges;\n}\n\n// Short motivational copy for emails.\nexport function buildEncouragement(completionRate: number, streak: number): string {\n if (completionRate >= 90) return \"Amazing work — you kept a near-perfect log this week.\";\n if (completionRate >= 70) return \"Great consistency — you’re building a strong habit.\";\n if (completionRate >= 40) return \"Nice progress — a few more check-ins will make this even stronger.\";\n if (streak >= 3) return \"You’re on a streak — keep it going!\";\n return \"Every entry helps — you’ve got this.\";\n}\n\n// Group entries into a per-day AM/PM structure for reports.\nexport function groupEntriesByDate(entries: Entry[], dateRange: string[]): GroupedEntries[] {\n // Bucket entries by date and AM/PM for consistent report formatting.\n const buckets: Record = {};\n for (const date of dateRange) {\n buckets[date] = { am: [], pm: [] };\n }\n for (const entry of entries) {\n if (!buckets[entry.date]) {\n buckets[entry.date] = { am: [], pm: [] };\n }\n const meridiem = getMeridiem(entry.createdTime);\n if (meridiem === \"AM\") {\n buckets[entry.date].am.push(entry);\n } else if (meridiem === \"PM\") {\n buckets[entry.date].pm.push(entry);\n } else {\n buckets[entry.date].pm.push(entry);\n }\n }\n return dateRange.map((date) => ({\n date,\n am: buckets[date]?.am ?? [],\n pm: buckets[date]?.pm ?? [],\n }));\n}\n\n// Format a single line of the daily summary table.\nexport function formatGroupedEntryLine(group: GroupedEntries): string {\n const [first, second] = formatFirstSecondText(group);\n return `${group.date} | 1st: ${first} | 2nd: ${second}`;\n}\n\n// Type guard for Notion created_time fields.\nexport function isCreatedTimeProperty(value: unknown): value is NotionCreatedTimeProperty {\n return (\n !!value &&\n typeof value === \"object\" &&\n \"created_time\" in value &&\n typeof (value as { created_time?: unknown }).created_time === \"string\"\n );\n}\n\n// Type guard for Notion rich_text fields.\nexport function isTextProperty(value: unknown): value is NotionTextProperty {\n return (\n !!value &&\n typeof value === \"object\" &&\n \"rich_text\" in value &&\n Array.isArray((value as { rich_text?: unknown }).rich_text)\n );\n}\n\n// Extract AM/PM from a time string if possible.\nfunction getMeridiem(value: string | null): \"AM\" | \"PM\" | null {\n if (!value) return null;\n const match = value.match(/\\b(AM|PM)\\b/i);\n if (!match) return null;\n return match[1].toUpperCase() as \"AM\" | \"PM\";\n}\n\n// Pick the first two readings (with an overflow indicator).\nfunction formatFirstSecondText(group: GroupedEntries): [string, string] {\n const ordered = orderEntries(group);\n if (!ordered.length) return [\"—\", \"—\"];\n const first = String(ordered[0].value);\n if (ordered.length === 1) return [first, \"—\"];\n const secondValue = String(ordered[1].value);\n const overflow = ordered.length > 2 ? ` (+${ordered.length - 2})` : \"\";\n return [first, `${secondValue}${overflow}`];\n}\n\n// Order entries by time when present (unknown times go last).\nfunction orderEntries(group: GroupedEntries): Entry[] {\n const combined = [...group.am, ...group.pm];\n return combined.sort((a, b) => {\n const aMinutes = parseTimeToMinutes(a.createdTime);\n const bMinutes = parseTimeToMinutes(b.createdTime);\n if (aMinutes === null && bMinutes === null) return 0;\n if (aMinutes === null) return 1;\n if (bMinutes === null) return -1;\n return aMinutes - bMinutes;\n });\n}\n\n// Convert \"h:mm AM/PM\" into minutes since midnight.\nfunction parseTimeToMinutes(value: string | null): number | null {\n if (!value) return null;\n const match = value.match(/(\\d{1,2}):(\\d{2})\\s*([AP]M)/i);\n if (!match) return null;\n let hours = Number(match[1]);\n const minutes = Number(match[2]);\n const meridiem = match[3].toUpperCase();\n if (meridiem === \"PM\" && hours < 12) hours += 12;\n if (meridiem === \"AM\" && hours === 12) hours = 0;\n return hours * 60 + minutes;\n}\n",[],[203,373],["D",1768499629303],[248,249,250,251,252,253],[203],"2d1a4f62-f23b-11f0-a85a-42dde27851f2","weekly_rollup_persist.http.tsx","f84d1afa-f233-11f0-9eff-42dde27851f2",190,["D",1768499642189],"http","import { initRollupSchema, insertBadgeEvents, upsertWeeklyRollup, type BadgeEvent, type WeeklyRollup } from \"../storage/rollups.ts\";\n\ntype PersistPayload = {\n rollup: WeeklyRollup;\n badgeEvents?: BadgeEvent[];\n};\n\nexport default async function (req: Request) {\n if (req.method !== \"POST\") {\n return new Response(\"Method Not Allowed\", { status: 405 });\n }\n\n const authError = checkAuth(req);\n if (authError) {\n return new Response(authError, { status: 401 });\n }\n\n const data = (await req.json()) as unknown;\n if (!isPersistPayload(data)) {\n return new Response(\"Invalid payload.\", { status: 400 });\n }\n\n await initRollupSchema();\n await upsertWeeklyRollup(data.rollup);\n if (data.badgeEvents?.length) {\n await insertBadgeEvents(data.badgeEvents);\n }\n\n return new Response(\"Persisted.\", { status: 200 });\n}\n\nfunction checkAuth(req: Request): string | null {\n const token = Deno.env.get(\"ROLLUP_PERSIST_TOKEN\");\n if (!token) return null;\n const header = req.headers.get(\"Authorization\") ?? \"\";\n const match = header.match(/^Bearer\\s+(.+)$/i);\n if (!match || match[1] !== token) return \"Unauthorized.\";\n return null;\n}\n\nfunction isPersistPayload(value: unknown): value is PersistPayload {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n if (!isWeeklyRollup(record.rollup)) return false;\n if (record.badgeEvents === undefined) return true;\n return Array.isArray(record.badgeEvents) && record.badgeEvents.every(isBadgeEvent);\n}\n\nfunction isWeeklyRollup(value: unknown): value is WeeklyRollup {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n return (\n typeof record.category === \"string\" &&\n typeof record.periodStart === \"string\" &&\n typeof record.periodEnd === \"string\" &&\n typeof record.streak === \"number\" &&\n typeof record.completionRate === \"number\" &&\n typeof record.xp === \"number\" &&\n Array.isArray(record.badges) &&\n typeof record.stats === \"object\" &&\n record.stats !== null &&\n typeof record.runId === \"string\"\n );\n}\n\nfunction isBadgeEvent(value: unknown): value is BadgeEvent {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n return (\n typeof record.category === \"string\" &&\n typeof record.badge === \"string\" &&\n typeof record.periodStart === \"string\" &&\n typeof record.periodEnd === \"string\" &&\n typeof record.awardedAt === \"string\"\n );\n}\n",[],[209,385],"b1f64f0e-f328-11f0-a330-42dde27851f2","monthly_report_page.http.tsx","044f06e4-f31d-11f0-b40c-42dde27851f2",351,["D",1768601655836],16,"import React from \"https://esm.sh/react@18.2.0\";\nimport { renderToString } from \"https://esm.sh/react-dom@18.2.0/server\";\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport {\n aggregateBloodSugarMonth,\n aggregateFoodMonth,\n resolveMonthRange,\n type Rollup,\n} from \"../shared/monthly_report.ts\";\n\nexport default async function (req: Request) {\n const url = new URL(req.url);\n const monthParam = url.searchParams.get(\"month\");\n const now = new Date();\n // Keep defaults aligned with the dropdown so the first render has data.\n const startYear = 2026;\n const selectedMonth = resolveSelectedMonth(monthParam, now, startYear);\n const { start, end } = resolveMonthRange(selectedMonth, now);\n const includePartialWeeks = url.searchParams.get(\"partial\") === \"true\";\n const monthOptions = buildMonthOptions(startYear, now);\n\n // Pull all rollups for the requested month window, then split by category.\n const rollups = await fetchRollups(start, end, includePartialWeeks);\n const bloodSugar = aggregateBloodSugarMonth(rollups.filter((r) => r.category === \"blood_sugar\"), start, end, {\n includePartialWeeks,\n });\n const food = aggregateFoodMonth(rollups.filter((r) => r.category === \"food\"), start, end, {\n includePartialWeeks,\n });\n\n // Render a full HTML page as a string (server-side React).\n const html = renderToString(\n ,\n );\n\n return new Response(`${html}`, {\n headers: { \"Content-Type\": \"text/html; charset=utf-8\" },\n });\n}\n\n// Fetch weekly rollups for the month; optionally include overlapping weeks.\n// Query weekly rollups that overlap the selected month.\nasync function fetchRollups(start: string, end: string, includePartialWeeks: boolean): Promise {\n const where = includePartialWeeks\n ? \"period_start <= ? AND period_end >= ?\"\n : \"period_start >= ? AND period_end <= ?\";\n const args = includePartialWeeks ? [end, start] : [start, end];\n const result = await sqlite.execute({\n sql: `\n SELECT\n category,\n period_start,\n period_end,\n streak,\n completion_rate,\n xp,\n badges_json,\n stats_json,\n run_id\n FROM weekly_rollups_1\n WHERE ${where}\n ORDER BY period_start ASC\n `,\n args,\n });\n\n return result.rows.map((row) => rowToRollup(row as Record | unknown[]));\n}\n\n// Convert SQLite array or object rows into typed rollup objects.\n// (The SQLite client can return either shape depending on context.)\nfunction rowToRollup(row: Record | unknown[]): Rollup {\n const values = Array.isArray(row) ? row : [\n row.category,\n row.period_start,\n row.period_end,\n row.streak,\n row.completion_rate,\n row.xp,\n row.badges_json,\n row.stats_json,\n row.run_id,\n ];\n const [\n category,\n periodStart,\n periodEnd,\n streak,\n completionRate,\n xp,\n badgesJson,\n statsJson,\n runId,\n ] = values;\n return {\n category: String(category),\n periodStart: String(periodStart),\n periodEnd: String(periodEnd),\n streak: Number(streak ?? 0),\n completionRate: Number(completionRate ?? 0),\n xp: Number(xp ?? 0),\n badges: safeParseJsonArray(badgesJson),\n stats: safeParseJsonObject(statsJson),\n runId: String(runId),\n };\n}\n\nfunction safeParseJsonArray(value: unknown): string[] {\n const parsed = safeParseJson(value);\n return Array.isArray(parsed) ? parsed.map(String) : [];\n}\n\nfunction safeParseJsonObject(value: unknown): Record {\n const parsed = safeParseJson(value);\n return parsed && typeof parsed === \"object\" ? (parsed as Record) : {};\n}\n\n// Guard against invalid JSON in stored rollup columns.\nfunction safeParseJson(value: unknown) {\n if (typeof value !== \"string\") return null;\n try {\n return JSON.parse(value);\n } catch {\n return null;\n }\n}\n\n// Present the monthly report as a static HTML page.\nfunction ReportPage(props: {\n monthStart: string;\n monthEnd: string;\n includePartialWeeks: boolean;\n selectedMonth: string;\n monthOptions: string[];\n bloodSugar: ReturnType;\n food: ReturnType;\n}) {\n const { monthStart, monthEnd, includePartialWeeks, selectedMonth, monthOptions, bloodSugar, food } = props;\n const title = \"Praise Cage Monthly Rollup\";\n return (\n \n \n \n \n {title}\n \n \n \n {/* Decorative background layers */}\n

\n \n

{title}

\n Range: {monthStart} → {monthEnd} {includePartialWeeks ? \"(partial weeks included)\" : \"(full weeks only)\"}\n

\n {/* Month navigation is query-string driven for shareable URLs. */}\n \n

\n\n {/* Main content: two summary cards */}\n

Blood Sugar

\n \n \n \n \n \n \n \n

\n {(bloodSugar.badges.length ? bloodSugar.badges : [\"No badges yet\"]).map((badge) => (\n \n {badge}\n \n ))}\n

\n\n

Food Log

\n \n \n \n \n \n \n \n

\n Macro averages (per entry)\n {Object.keys(food.macroSummary).length === 0 &&

No macro data yet.

}\n {Object.entries(food.macroSummary).map(([key, value]) => (\n

\n {key}\n {value.avg}\n

\n ))}\n

\n\n

\n Praise Cage mode: keep logging, keep winning. Data from weekly rollups stored in Val Town SQLite.\n

\n \n \n \n );\n}\n\nfunction Stat(props: { label: string; value: string | number }) {\n return (\n

\n {props.label}\n {props.value}\n

\n );\n}\n\n// Build the month dropdown from the first data year through the current month.\nfunction buildMonthOptions(startYear: number, now: Date): string[] {\n const options: string[] = [];\n const start = new Date(Date.UTC(startYear, 0, 1));\n const end = new Date(Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), 1));\n if (end < start) {\n return [formatMonth(start)];\n }\n for (let cursor = start; cursor <= end; cursor = addMonths(cursor, 1)) {\n options.push(formatMonth(cursor));\n }\n return options;\n}\n\n// Use the query string if valid, otherwise default to last month.\nfunction resolveSelectedMonth(monthParam: string | null, now: Date, startYear: number): string {\n const minMonth = `${startYear}-01`;\n if (monthParam && /^\\d{4}-\\d{2}$/.test(monthParam)) {\n return monthParam < minMonth ? minMonth : monthParam;\n }\n const year = now.getUTCFullYear();\n const month = now.getUTCMonth();\n const previous = new Date(Date.UTC(year, month - 1, 1));\n const fallback = formatMonth(previous);\n return fallback < minMonth ? minMonth : fallback;\n}\n\n// Format a Date as YYYY-MM for query params and dropdown values.\nfunction formatMonth(date: Date): string {\n const year = date.getUTCFullYear();\n const month = String(date.getUTCMonth() + 1).padStart(2, \"0\");\n return `${year}-${month}`;\n}\n\n// Date helper for iterating month-by-month.\nfunction addMonths(date: Date, amount: number): Date {\n return new Date(Date.UTC(date.getUTCFullYear(), date.getUTCMonth() + amount, 1));\n}\n",[],[209,394],["D",1768499628695],[245,246],[209],"ac169fc2-f4c6-11f0-b236-42dde27851f2","food_report.cron.tsx","f851115a-f233-11f0-a807-42dde27851f2",364,["D",1768779457627],"interval","import { getWeeklyRange } from \"../shared/date.ts\";\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { fetchNotionPages, type NotionPage, updateNotionPage } from \"../shared/notion.ts\";\nimport {\n buildNutritionPrompt,\n buildNutritionProperties,\n buildFoodRollup,\n coerceMacros,\n roundNumber,\n type Entry,\n type MacroKey,\n parseEntry,\n PROPERTY_NAMES,\n safeParseJson,\n shouldEnrich,\n} from \"../shared/food_enrich.ts\";\nimport { fetchFatsecretNutrition, type FatsecretConfig } from \"../shared/fatsecret.ts\";\nimport { initRollupSchema, upsertWeeklyRollup } from \"../storage/rollups.ts\";\n\ntype NotionConfig = {\n token: string;\n databaseId: string;\n};\n\nexport default async function () {\n // Resolve configs and hydrate external clients first to fail fast.\n const notionConfig = getNotionConfig();\n if (!notionConfig) {\n return new Response(\"Missing Notion secrets.\", { status: 500 });\n }\n const openai = new OpenAI();\n const fatsecretConfig = getFatsecretConfig();\n\n const { start, end } = getWeeklyRange();\n const entries = await fetchEntries(start, end, notionConfig);\n console.log(`Food entries ${start} to ${end}:`, entries);\n\n let enriched = 0;\n for (const entry of entries) {\n // Only enrich entries missing core macros to avoid overwriting manual edits.\n if (!shouldEnrich(entry)) continue;\n if (!entry.food || entry.food === \"Unknown\") continue;\n const openaiResult = await fetchNutritionOpenAI(entry.food, openai);\n const fatsecretResult = fatsecretConfig\n ? await fetchFatsecretNutrition(entry.food, fatsecretConfig)\n : null;\n\n if (fatsecretConfig) {\n const comparison = buildMacroComparison(openaiResult?.macros ?? null, fatsecretResult);\n console.log(\"Nutrition comparison\", {\n pageId: entry.pageId,\n food: entry.food,\n loggedAt: entry.loggedAt,\n openai: openaiResult?.macros ?? null,\n fatsecret: fatsecretResult,\n diff: comparison,\n });\n }\n\n const mergedMacros = mergeMacros(fatsecretResult, openaiResult?.macros ?? null);\n if (!mergedMacros) continue;\n const properties = buildNutritionProperties(mergedMacros);\n if (!Object.keys(properties).length) continue;\n console.log(\"Enriching entry\", {\n pageId: entry.pageId,\n food: entry.food,\n loggedAt: entry.loggedAt,\n macros: mergedMacros,\n });\n console.log(\"Notion update properties\", {\n pageId: entry.pageId,\n properties,\n });\n await updateNotionPage(entry.pageId, notionConfig.token, properties);\n entry.macros = { ...entry.macros, ...mergedMacros };\n enriched += 1;\n }\n\n await initRollupSchema();\n const rollup = buildFoodRollup(entries, start, end);\n await upsertWeeklyRollup(rollup);\n\n return new Response(`Weekly food entries logged. Enriched ${enriched}.`, { status: 200 });\n}\n\nfunction getNotionConfig(): NotionConfig | null {\n const token = Deno.env.get(\"NOTION_TOKEN\");\n const databaseId = Deno.env.get(\"NOTION_FOOD_DB_ID\");\n if (!token || !databaseId) return null;\n return { token, databaseId };\n}\n\nfunction getFatsecretConfig(): FatsecretConfig | null {\n const accessToken = Deno.env.get(\"FATSECRET_ACCESS_TOKEN\");\n if (!accessToken) return null;\n const includeFoodDataValue = Deno.env.get(\"FATSECRET_INCLUDE_FOOD_DATA\");\n const includeFoodData = includeFoodDataValue\n ? includeFoodDataValue.trim().toLowerCase() === \"true\"\n : true;\n return { accessToken, includeFoodData };\n}\n\nasync function fetchEntries(start: string, end: string, config: NotionConfig): Promise {\n // Pull just the last-week window to keep the Notion query fast.\n const pages = await fetchNotionPages(config.databaseId, config.token, (cursor) => ({\n filter: {\n and: [\n { property: PROPERTY_NAMES.loggedAt, date: { on_or_after: start } },\n { property: PROPERTY_NAMES.loggedAt, date: { on_or_before: end } },\n ],\n },\n sorts: [{ property: PROPERTY_NAMES.loggedAt, direction: \"ascending\" }],\n ...(cursor ? { start_cursor: cursor } : {}),\n }));\n\n const entries: Entry[] = [];\n for (const page of pages) {\n const entry = parseEntry(page);\n if (entry) entries.push(entry);\n }\n\n return entries;\n}\n\nasync function fetchNutritionOpenAI(\n foodName: string,\n openai: OpenAI,\n): Promise<{\n macros: Partial>;\n} | null> {\n // Ask the model for a strict JSON payload and coerce to numeric fields.\n const prompt = buildNutritionPrompt(foodName);\n // Keep the OpenAI request compact to control costs.\n\n const completion = await openai.chat.completions.create({\n model: \"gpt-5-nano\",\n messages: [\n {\n role: \"system\",\n content:\n \"You estimate nutrition macros from short food descriptions. \" +\n \"Respond with a single JSON object with numeric fields: \" +\n \"calories, protein, carbs, fat, fiber, sugar, sodium. \" +\n \"Use grams for macros and milligrams for sodium. \" +\n \"If unsure, make a reasonable estimate. No extra text.\",\n },\n { role: \"user\", content: prompt },\n ],\n max_tokens: 120,\n });\n\n const text = completion.choices[0]?.message?.content?.trim();\n if (!text) return null;\n const parsed = safeParseJson(text);\n if (!parsed || typeof parsed !== \"object\") return null;\n const macros = coerceMacros(parsed as Record);\n if (!Object.keys(macros).length) return null;\n return { macros };\n}\n\nfunction mergeMacros(\n primary: Partial> | null,\n secondary: Partial> | null,\n): Partial> | null {\n if (!primary && !secondary) return null;\n const merged: Partial> = {};\n for (const key of Object.keys(PROPERTY_NAMES.macros) as MacroKey[]) {\n if (primary && typeof primary[key] === \"number\") {\n merged[key] = primary[key];\n continue;\n }\n if (secondary && typeof secondary[key] === \"number\") {\n merged[key] = secondary[key];\n }\n }\n return Object.keys(merged).length ? merged : null;\n}\n\nfunction buildMacroComparison(\n openai: Partial> | null,\n fatsecret: Partial> | null,\n): Partial> | null {\n if (!openai || !fatsecret) return null;\n const diff: Partial> = {};\n for (const key of Object.keys(PROPERTY_NAMES.macros) as MacroKey[]) {\n const openaiValue = openai[key];\n const fatsecretValue = fatsecret[key];\n if (typeof openaiValue !== \"number\" || typeof fatsecretValue !== \"number\") continue;\n diff[key] = roundNumber(fatsecretValue - openaiValue);\n }\n return Object.keys(diff).length ? diff : null;\n}\n",[],[215,406],"4f53f136-f4c6-11f0-b407-42dde27851f2","blood_sugar_report.cron.tsx","905c839c-f0bf-11f0-b356-42dde27851f2",358,["D",1768779301679],53,"import { email } from \"https://esm.town/v/std/email\";\nimport { getWeeklyRange, listDateRange } from \"../shared/date.ts\";\nimport { fetchNotionPages } from \"../shared/notion.ts\";\nimport { initRollupSchema, upsertWeeklyRollup } from \"../storage/rollups.ts\";\nimport {\n buildEncouragement,\n buildBloodSugarRollup,\n formatGroupedEntryLine,\n groupEntriesByDate,\n parseEntry,\n type GroupedEntries,\n type BloodSugarNotionPage,\n type Entry,\n hasPerfectWeekStreak,\n} from \"../shared/blood_sugar_logic.ts\";\n\nexport default async function handler(): Promise {\n const notionConfig = getNotionConfig();\n\n if (!notionConfig) {\n return new Response(\"Missing required secrets.\", { status: 500 });\n }\n\n // Use a fixed 7-day range ending today (UTC) for weekly rollups.\n const { start, end } = getWeeklyRange();\n console.log(`Weekly range: ${start} to ${end}`);\n const entries = await fetchEntries(start, end, notionConfig);\n console.log(`Fetched ${entries.length} entries from Notion`);\n const report = buildReport(entries, start, end);\n console.log(\"Report subject:\", report.subject);\n console.log(\"Sending email to Val Town account owner (free tier default).\");\n\n // Build the payload to match Val Town's std/email expectations.\n const emailPayload = {\n subject: report.subject,\n text: report.text,\n html: report.html,\n };\n\n await email(emailPayload);\n console.log(\"Email sent.\");\n\n await initRollupSchema();\n await upsertWeeklyRollup(report.rollup);\n\n return new Response(\"Weekly report sent.\", { status: 200 });\n}\n\ntype NotionConfig = {\n token: string;\n databaseId: string;\n};\n\nfunction getNotionConfig(): NotionConfig | null {\n const token = Deno.env.get(\"NOTION_TOKEN\");\n const databaseId = Deno.env.get(\"NOTION_BLOOD_SUGAR_DB_ID\");\n if (!token || !databaseId) return null;\n return { token, databaseId };\n}\n\nexport async function fetchEntries(\n start: string,\n end: string,\n notionConfig: NotionConfig,\n): Promise {\n const pages = await fetchNotionPages(notionConfig.databaseId, notionConfig.token, (cursor) => ({\n filter: {\n and: [\n { property: \"Measurement Date\", date: { on_or_after: start } },\n { property: \"Measurement Date\", date: { on_or_before: end } },\n ],\n },\n sorts: [{ property: \"Measurement Date\", direction: \"ascending\" }],\n ...(cursor ? { start_cursor: cursor } : {}),\n }));\n\n const entries: Entry[] = [];\n for (const page of pages) {\n const entry = parseEntry(page);\n if (entry) entries.push(entry);\n }\n\n return entries;\n}\n\nexport function buildReport(entries: Entry[], start: string, end: string) {\n // Compute summary stats and derive copy for email-friendly output.\n // Summary stats for the weekly rollup.\n const rollup = buildBloodSugarRollup(entries, start, end);\n const subject = `Blood Sugar Weekly Rollup (${start} → ${end})`;\n const dateRange = listDateRange(start, end);\n const groupedEntries = groupEntriesByDate(entries, dateRange);\n const encouragement = buildEncouragement(rollup.completionRate, rollup.streak);\n const disclaimer =\n \"Not medical advice. Educational info only. Source: https://www.ynhhs.org/articles/what-is-healthy-blood-sugar\";\n\n const lines = [\n `Range: ${start} to ${end}`,\n `Entries: ${rollup.stats.totalEntries} (expected ${rollup.stats.expected}, missing ${rollup.stats.missing})`,\n `Average: ${rollup.stats.avg}`,\n `Min: ${rollup.stats.min}`,\n `Max: ${rollup.stats.max}`,\n `Completion: ${rollup.completionRate}%`,\n `Current streak: ${rollup.streak} day${rollup.streak === 1 ? \"\" : \"s\"}`,\n `Perfect week streak: ${hasPerfectWeekStreak(dateRange, rollup.stats.entriesByDate) ? \"Yes\" : \"No\"}`,\n `XP earned: ${rollup.xp}`,\n `Badges: ${rollup.badges.length ? rollup.badges.join(\", \") : \"No badges yet\"}`,\n `Encouragement: ${encouragement}`,\n `Disclaimer: ${disclaimer}`,\n \"\",\n \"Entries:\",\n ...groupedEntries.map(formatGroupedEntryLine),\n ];\n\n const text = lines.join(\"\\n\");\n const html = renderHtmlReport(groupedEntries, {\n start,\n end,\n count: rollup.stats.totalEntries,\n expected: rollup.stats.expected,\n missing: rollup.stats.missing,\n avg: rollup.stats.avg,\n min: rollup.stats.min,\n max: rollup.stats.max,\n completionRate: rollup.completionRate,\n currentStreak: rollup.streak,\n badges: rollup.badges,\n encouragement,\n disclaimer,\n xp: rollup.xp,\n perfectWeekStreak: hasPerfectWeekStreak(dateRange, rollup.stats.entriesByDate),\n });\n\n return { subject, text, html, rollup };\n}\n\nfunction formatFirstSecondHtml(group: GroupedEntries): [string, string] {\n const ordered = orderEntries(group);\n if (!ordered.length) return [\"—\", \"—\"];\n const first = String(ordered[0].value);\n if (ordered.length === 1) return [first, \"—\"];\n const secondValue = String(ordered[1].value);\n const overflow = ordered.length > 2 ? ` (+${ordered.length - 2})` : \"\";\n return [first, `${secondValue}${overflow}`];\n}\n\nfunction orderEntries(group: GroupedEntries): Entry[] {\n const combined = [...group.am, ...group.pm];\n return combined.sort((a, b) => {\n const aMinutes = parseTimeToMinutes(a.createdTime);\n const bMinutes = parseTimeToMinutes(b.createdTime);\n if (aMinutes === null && bMinutes === null) return 0;\n if (aMinutes === null) return 1;\n if (bMinutes === null) return -1;\n return aMinutes - bMinutes;\n });\n}\n\nfunction parseTimeToMinutes(value: string | null): number | null {\n if (!value) return null;\n const match = value.match(/(\\d{1,2}):(\\d{2})\\s*([AP]M)/i);\n if (!match) return null;\n let hours = Number(match[1]);\n const minutes = Number(match[2]);\n const meridiem = match[3].toUpperCase();\n if (meridiem === \"PM\" && hours < 12) hours += 12;\n if (meridiem === \"AM\" && hours === 12) hours = 0;\n return hours * 60 + minutes;\n}\n\nexport function renderHtmlReport(\n groupedEntries: GroupedEntries[],\n stats: {\n start: string;\n end: string;\n count: number;\n expected: number;\n missing: number;\n avg: number;\n min: number;\n max: number;\n completionRate: number;\n currentStreak: number;\n badges: string[];\n encouragement: string;\n disclaimer: string;\n xp: number;\n perfectWeekStreak: boolean;\n },\n): string {\n // Simple HTML table for quick scanning in email clients.\n const rows = groupedEntries\n .map((group) => {\n const [first, second] = formatFirstSecondHtml(group);\n return `\n ${group.date}\n ${escapeHtml(first)}\n ${escapeHtml(second)}\n `;\n })\n .join(\"\");\n\n return `\n

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n

Blood Sugar Weekly Rollup

${stats.start} to ${stats.end}

\n 🔺 🔷 〰️ 🟢 〰️ 🔶 〰️ 🟡 〰️ 🟣 🔺 🔵 〰️\n

\n \n \n \n \n \n \n

Avg

${stats.avg}

Min

${stats.min}

Max

${stats.max}

\n \n \n \n \n \n \n \n \n \n

\n \n Entries \n ${stats.count}/${stats.expected} \n \n	\n \n Completion \n ${stats.completionRate}% \n \n
\n \n Streak \n ${stats.currentStreak} day${stats.currentStreak === 1 ? \"\" : \"s\"} \n \n	\n \n XP \n ${stats.xp} \n \n

\n Perfect Week Streak: ${stats.perfectWeekStreak ? \"Yes\" : \"No\"}\n

\n Badges:\n

\n ${\n stats.badges.length\n ? stats.badges\n .map(\n (badge) =>\n `${escapeHtml(badge)}`,\n )\n .join(\"\")\n : `No badges yet`\n }\n

\n ${escapeHtml(stats.encouragement)}\n

\n ${escapeHtml(stats.disclaimer)}\n

\n Entries\n

\n \n \n \n \n \n \n \n \n \n ${rows || ``}\n \n

Date	1st	2nd
No entries

\n `;\n}\n\nexport function escapeHtml(value: string): string {\n return value\n .replaceAll(\"&\", \"&\")\n .replaceAll(\"<\", \"<\")\n .replaceAll(\">\", \">\")\n .replaceAll('\"', \""\")\n .replaceAll(\"'\", \"'\");\n}\n",[],[215,415],["D",1768499629095],[242,243],[215],"2de47576-f23b-11f0-a135-42dde27851f2","settings.json","2de4762a-f23b-11f0-a135-42dde27851f2",228,["D",1768499643522],"{\n \"deno.enable\": true,\n \"deno.enablePaths\": [\"./\"]\n }",[],[221,427],"2de68492-f23b-11f0-93cf-42dde27851f2","extensions.json","2de68528-f23b-11f0-93cf-42dde27851f2",229,["D",1768499643540],"{\n \"recommendations\": [\n \"denoland.vscode-deno\"\n ]\n}",[],[221,435],["D",1768499629401],[239,240],[221],["D",1768332030028],["D",1789516910456],{"_100":99,"_107":103},{"_100":99,"_101":-5,"_102":103,"_18":57,"_104":105,"_106":27},{"_13":89,"_33":90,"_45":44,"_91":46,"_92":-5,"_93":-5,"_94":-5,"_95":-5,"_96":-5,"_97":47,"_98":99},"ctx",{"_82":-5,"_126":483,"_484":485,"_486":487,"_488":27,"_489":27,"_490":27,"_491":25,"_492":-5,"_493":-7,"_494":-7,"_495":63,"_496":27,"_497":27,"_498":-5,"_499":27,"_500":27,"_501":27,"_502":-5},"ENV",{"_454":455,"_456":457,"_458":90,"_459":460,"_461":462,"_463":464,"_465":466,"_467":468,"_469":470,"_471":472,"_473":474,"_475":476,"_477":478,"_479":480,"_481":482},"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"]

Diff · v365