${title} — Spend Agent

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Each val gets\n// its own isolated database, so we don't need any table prefix and remixers\n// don't inherit anyone else's data.\nimport { sqlite } from 'https://esm.town/v/std/sqlite/main.ts'\n\nexport { sqlite }\n\n// Canonical table names — exported so other modules can reference them by key.\nexport const T = {\n tx: 'transactions',\n summaries: 'monthly_summaries',\n config: 'config',\n tellerTokens: 'teller_tokens',\n} as const\n\n// ── Schema ──────────────────────────────────────────────────────\nexport async function ensureSchema() {\n await sqlite.batch([\n `CREATE TABLE IF NOT EXISTS transactions (\n id TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n source_id TEXT,\n date TEXT NOT NULL,\n description TEXT NOT NULL,\n amount REAL NOT NULL,\n abs_amount REAL NOT NULL,\n account_name TEXT,\n institution TEXT,\n category TEXT,\n category_source TEXT,\n llm_confidence REAL,\n llm_reasoning TEXT,\n is_transfer INTEGER DEFAULT 0,\n is_income INTEGER DEFAULT 0,\n is_duplicate INTEGER DEFAULT 0,\n duplicate_of TEXT,\n status TEXT DEFAULT 'posted',\n created_at TEXT DEFAULT (datetime('now'))\n )`,\n `CREATE TABLE IF NOT EXISTS monthly_summaries (\n month TEXT PRIMARY KEY,\n total_income REAL,\n total_spend REAL,\n total_transfers REAL,\n net_cash_flow REAL,\n category_breakdown TEXT,\n tx_count INTEGER\n )`,\n `CREATE TABLE IF NOT EXISTS config (\n key TEXT PRIMARY KEY,\n value TEXT\n )`,\n `CREATE TABLE IF NOT EXISTS teller_tokens (\n id TEXT PRIMARY KEY,\n access_token TEXT NOT NULL,\n enrollment_id TEXT,\n institution TEXT NOT NULL,\n linked_at TEXT DEFAULT (datetime('now'))\n )`,\n ])\n}\n\n// ── Config helpers ──────────────────────────────────────────────\nexport async function getConfig(key: string, fallback = ''): Promise {\n const res = await sqlite.execute({\n sql: 'SELECT value FROM config WHERE key = ?',\n args: [key],\n })\n return res.rows.length > 0 ? String(res.rows[0][0] ?? fallback) : fallback\n}\n\nexport async function setConfig(key: string, value: string) {\n await sqlite.execute({\n sql: 'INSERT OR REPLACE INTO config (key, value) VALUES (?, ?)',\n args: [key, value],\n })\n}\n\n// ── Monthly summary recompute ───────────────────────────────────\nexport async function recomputeMonth(month: string) {\n const stats = await sqlite.execute({\n sql: `SELECT\n SUM(CASE WHEN is_income = 1 AND is_transfer = 0 THEN abs_amount ELSE 0 END),\n SUM(CASE WHEN is_income = 0 AND is_transfer = 0 AND is_duplicate = 0 THEN abs_amount ELSE 0 END),\n SUM(CASE WHEN is_transfer = 1 THEN abs_amount ELSE 0 END),\n COUNT(*)\n FROM transactions WHERE substr(date, 1, 7) = ?`,\n args: [month],\n })\n const r = stats.rows[0] as any[]\n const income = Number(r[0]) || 0\n const spend = Number(r[1]) || 0\n const transfers = Number(r[2]) || 0\n const txCount = Number(r[3]) || 0\n\n const catRes = await sqlite.execute({\n sql: `SELECT category, SUM(abs_amount) FROM transactions\n WHERE substr(date, 1, 7) = ? AND is_income = 0 AND is_transfer = 0 AND is_duplicate = 0\n GROUP BY category ORDER BY SUM(abs_amount) DESC`,\n args: [month],\n })\n const cats: Record = {}\n for (const cr of catRes.rows)\n cats[String(cr[0] || 'Other')] = Math.round(Number(cr[1]) * 100) / 100\n\n await sqlite.execute({\n sql: `INSERT OR REPLACE INTO monthly_summaries (month, total_income, total_spend, total_transfers, net_cash_flow, category_breakdown, tx_count)\n VALUES (?, ?, ?, ?, ?, ?, ?)`,\n args: [\n month,\n Math.round(income * 100) / 100,\n Math.round(spend * 100) / 100,\n Math.round(transfers * 100) / 100,\n Math.round((income - spend) * 100) / 100,\n JSON.stringify(cats),\n txCount,\n ],\n })\n}\n\n// ── Default system prompt ───────────────────────────────────────\nexport const DEFAULT_SYSTEM_PROMPT = `You are a personal finance categorizer. Classify each transaction into exactly one category.\n\nCategories are enforced by schema — focus on rules for ambiguous cases:\n\nRules:\n- Venmo/Zelle payments TO someone are the actual spend category, not \"Transfers\"\n- Venmo/Zelle payments FROM someone are income or reimbursements\n- Credit card payments and bank transfers between own accounts are \"Transfers\"\n- Recurring charges (Netflix, Spotify, gym) are \"Subscriptions\"\n- Restaurant and food delivery (DoorDash, UberEats, Grubhub) are \"Food\"\n- Uber/Lyft rides are \"Transportation\"\n- Amazon purchases are \"Shopping\" unless clearly groceries\n\nIncome/credit classification:\n- PAYROLL, direct deposits from employers → \"Salary\"\n- Venmo/Zelle payments FROM someone for rent → \"Housing\"\n- Reimbursements: use the category of what was reimbursed (e.g., trip reimbursement → \"Travel\", utility reimbursement → \"Bills\")\n- Tax refunds (IRS, state) → \"Income\"\n- Credit card statement credits, hotel credits, rewards → use underlying category (travel credit → \"Travel\", entertainment credit → \"Entertainment\")\n- PayPal/Cash App transfers to yourself → \"Transfers\"\n- Family gifts via Zelle/Venmo → \"Gifts\"\n- Other misc income → \"Income\"`\n\n// ── Categories ──────────────────────────────────────────────────\nexport const DEFAULT_CATEGORIES = [\n 'Housing',\n 'Food',\n 'Transportation',\n 'Shopping',\n 'Entertainment',\n 'Health',\n 'Subscriptions',\n 'Bills',\n 'Travel',\n 'Investments',\n 'Transfers',\n 'Salary',\n 'Income',\n 'Gifts',\n 'Other',\n] as const\n\n// Keep CATEGORIES as alias for backward compat\nexport const CATEGORIES = DEFAULT_CATEGORIES\n\nexport type Category = (typeof DEFAULT_CATEGORIES)[number]\n\n// Get user-customized categories (falls back to defaults)\nexport async function getCategories(): Promise {\n const stored = await getConfig('categories', '')\n if (stored) {\n try {\n return JSON.parse(stored) as string[]\n } catch {}\n }\n return [...DEFAULT_CATEGORIES]\n}\n\nexport async function setCategories(cats: string[]) {\n // Always ensure \"Other\" exists as fallback\n if (!cats.includes('Other')) cats.push('Other')\n await setConfig('categories', JSON.stringify(cats))\n}\n","createdAt",["D",1779912848208],"branchVersion","branchId","0e663cfa-5877-11f1-a8f8-ee650bb23af1","id","0e656f14-5877-11f1-a8f8-ee650bb23af1","spend-agent",["D",1779740379107],"deletedAt","legacyEnvVars",false,"privacy","public","httpPrivacy","description","Your personal, AI-native finance tool. ","imageUrl","5751f21a-8735-41fd-9675-c4c5ee261e48","pinnedFileId","8ac5067e-5aab-11f1-bb3c-ee650bb23af1","pinPreview","pinMigrated","screenshotVersion","likeCount",4,"orgId","019d935d-aed7-71ff-b9f9-a9cc46cb7275","tursoName","0e656f14587711f1a8f8ee650bb23af1","tursoHostname","0e656f14587711f1a8f8ee650bb23af1-val-town.aws-us-east-2.turso.io","tursoMeasuredAt",["D",1789504908499],"pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_99":98,"_106":102},"org",{"_99":98,"_100":-5,"_101":102,"_18":55,"_103":104,"_105":48},"branch",{"_13":88,"_32":89,"_42":41,"_90":43,"_91":-5,"_92":-5,"_93":-5,"_94":-5,"_95":-5,"_96":44,"_97":98},"isOwned",204,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","kevinsuh","handle","displayName","avatar","https://avatars.githubusercontent.com/u/8541122?v=4","tier","pro","canRestrictVals","profileImageUrl","branchName","","adoptOrgId",{"_42":43,"_32":44,"_37":260,"_46":-5,"_47":48,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":57,"_58":25,"_59":-5,"_60":-5,"_61":62,"_63":64,"_65":66,"_67":68,"_69":261,"_71":-5,"_72":73,"_74":73,"_75":76,"_77":76,"_78":76,"_79":73,"_80":73,"_81":262,"_83":263,"_85":264,"_87":48},"tree",[223,224,225,226,227,228,229,230,231],"files",[223,224,225,226,227,228,229,230,231],"counts",{"_213":171,"_214":202,"_215":145,"_216":217,"_218":219},"contents",[129,130,131,132,133,134,135,136,137],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_42":206,"_32":207,"_30":208,"_141":-5,"_40":41,"_39":209,"_143":48,"_37":210,"_13":145,"_33":34,"_35":211,"_24":48,"_148":-5,"_27":212},{"_42":197,"_32":198,"_30":199,"_141":-5,"_40":41,"_39":200,"_143":48,"_37":201,"_13":202,"_33":203,"_35":204,"_24":48,"_148":-5,"_27":205},{"_42":189,"_32":190,"_30":191,"_141":-5,"_40":41,"_39":192,"_143":48,"_37":193,"_13":194,"_33":34,"_35":195,"_24":48,"_148":-5,"_27":196},{"_42":182,"_32":183,"_30":184,"_141":-5,"_40":41,"_39":185,"_143":25,"_37":186,"_13":155,"_33":34,"_35":187,"_24":48,"_148":-5,"_27":188},{"_42":174,"_32":175,"_30":176,"_141":-5,"_40":41,"_39":177,"_143":25,"_37":178,"_13":179,"_33":146,"_35":180,"_24":48,"_148":-5,"_27":181},{"_42":166,"_32":167,"_30":168,"_141":-5,"_40":41,"_39":169,"_143":48,"_37":170,"_13":171,"_33":34,"_35":172,"_24":48,"_148":-5,"_27":173},{"_42":158,"_32":159,"_30":160,"_141":-5,"_40":41,"_39":161,"_143":48,"_37":162,"_13":163,"_33":34,"_35":164,"_24":48,"_148":-5,"_27":165},{"_42":150,"_32":151,"_30":152,"_141":-5,"_40":41,"_39":153,"_143":48,"_37":154,"_13":155,"_33":34,"_35":156,"_24":48,"_148":-5,"_27":157},{"_42":138,"_32":139,"_30":140,"_141":-5,"_40":41,"_39":142,"_143":25,"_37":144,"_13":145,"_33":146,"_35":147,"_24":48,"_148":-5,"_27":149},"bb43f7d4-587a-11f1-8735-ee650bb23af1","sync.ts","4ca11b20-5877-11f1-85ed-ee650bb23af1","parentId",25,"latest",["D",1779741957609],2,"interval","// Spend Agent — Teller Sync Cron (15-minute interval)\nimport { runSync } from \"./sync-engine.ts\";\n\nexport default async function () {\n const result = await runSync();\n if (result.errors.length > 0) console.log(\"Sync errors:\", result.errors.join(\"; \"));\n}","label",[139],"7b19069c-5a08-11f1-9cbc-ee650bb23af1","sync-engine.ts","bb0671f2-587a-11f1-800c-ee650bb23af1",137,["D",1779912789596],3,"// Spend Agent — Sync Engine (shared logic)\n// Exported runSync used by app.ts (on-demand) and sync.ts (15min cron).\nimport { sqlite, ensureSchema } from './db.ts'\nimport { fixPem } from './lib.ts'\nimport { blob } from 'https://esm.town/v/std/blob'\n\nexport async function runSync(): Promise<{\n accounts: number\n inserted: number\n skipped: number\n errors: string[]\n}> {\n await ensureSchema()\n\n const tokensRes = await sqlite.execute('SELECT id, access_token, institution FROM teller_tokens')\n if (tokensRes.rows.length === 0) {\n return { accounts: 0, inserted: 0, skipped: 0, errors: ['No Teller tokens linked'] }\n }\n\n // Sandbox mode doesn't use mTLS — only development/production need certs.\n const tellerEnv = Deno.env.get('TELLER_ENV') || 'sandbox'\n let client: Deno.HttpClient | undefined\n if (tellerEnv !== 'sandbox') {\n try {\n const certRaw = Deno.env.get('TELLER_CERT')\n const keyRaw = Deno.env.get('TELLER_KEY')\n if (!certRaw || !keyRaw)\n throw new Error(`Missing TELLER_CERT or TELLER_KEY (required when TELLER_ENV=${tellerEnv})`)\n client = Deno.createHttpClient({ cert: fixPem(certRaw), key: fixPem(keyRaw) })\n } catch (e: any) {\n return { accounts: 0, inserted: 0, skipped: 0, errors: [e.message] }\n }\n }\n\n const allAccounts: any[] = []\n const balances: Record = {}\n const errors: string[] = []\n const seenAccountIds = new Set()\n let txInserted = 0\n let txSkipped = 0\n\n const existingRes = await sqlite.execute(\"SELECT id FROM transactions WHERE source = 'teller'\")\n const existingIds = new Set(existingRes.rows.map((r: any) => String(r[0])))\n\n for (const row of tokensRes.rows) {\n const accessToken = String(row[1])\n const institution = String(row[2])\n\n try {\n const accounts = await tellerFetch('/accounts', accessToken, client)\n\n for (const acct of accounts) {\n if (seenAccountIds.has(acct.id)) continue\n seenAccountIds.add(acct.id)\n\n allAccounts.push({\n id: acct.id,\n name: acct.name,\n type: acct.type,\n subtype: acct.subtype,\n institution,\n status: acct.status,\n })\n\n try {\n const bal = await tellerFetch(`/accounts/${acct.id}/balances`, accessToken, client)\n balances[acct.id] = {\n available: parseFloat(bal.available || '0'),\n ledger: parseFloat(bal.ledger || '0'),\n }\n } catch (e: any) {\n errors.push(`${institution}/${acct.name}/bal: ${e.message}`)\n }\n\n try {\n const txns = await tellerFetch(\n `/accounts/${acct.id}/transactions`,\n accessToken,\n client\n )\n for (const tx of txns) {\n if (tx.status !== 'posted') {\n txSkipped++\n continue\n }\n if (existingIds.has(tx.id)) {\n txSkipped++\n continue\n }\n\n const amount = parseFloat(tx.amount || '0')\n const absAmount = Math.round(Math.abs(amount) * 100) / 100\n const isIncome = acct.type === 'credit' ? (amount < 0 ? 1 : 0) : amount > 0 ? 1 : 0\n\n try {\n await sqlite.execute({\n sql: `INSERT INTO transactions (id, source, source_id, date, description, amount, abs_amount, account_name, institution, is_income, status)\n VALUES (?, 'teller', ?, ?, ?, ?, ?, ?, ?, ?, 'posted')`,\n args: [\n tx.id,\n tx.id,\n tx.date,\n tx.description,\n amount,\n absAmount,\n acct.name,\n institution,\n isIncome,\n ],\n })\n txInserted++\n } catch {\n txSkipped++\n }\n }\n } catch (e: any) {\n errors.push(`${institution}/${acct.name}/txns: ${e.message}`)\n }\n }\n } catch (e: any) {\n errors.push(`${institution}: ${e.message}`)\n }\n }\n\n // Save snapshot blob\n let totalChecking = 0,\n totalSavings = 0,\n totalCredit = 0\n for (const a of allAccounts) {\n const b = balances[a.id]\n if (!b) continue\n if (a.type === 'depository' && a.subtype === 'checking') totalChecking += b.available\n else if (a.type === 'depository' && a.subtype === 'savings') totalSavings += b.available\n else if (a.type === 'credit') totalCredit += Math.abs(b.ledger)\n }\n\n await blob.setJSON('spend-agent-snapshot', {\n lastUpdated: new Date().toISOString(),\n accounts: allAccounts,\n balances,\n errors,\n summary: {\n totalChecking: Math.round(totalChecking * 100) / 100,\n totalSavings: Math.round(totalSavings * 100) / 100,\n totalCreditOwed: Math.round(totalCredit * 100) / 100,\n },\n })\n\n console.log(\n `Sync: ${allAccounts.length} accounts, ${txInserted} new txns, ${txSkipped} skipped, ${errors.length} errors`\n )\n return { accounts: allAccounts.length, inserted: txInserted, skipped: txSkipped, errors }\n}\n\nasync function tellerFetch(\n endpoint: string,\n accessToken: string,\n client?: Deno.HttpClient\n): Promise {\n // Sandbox mode hits api.teller.io without an mTLS client — only dev/prod\n // attach the cert-backed HttpClient.\n const init: any = {\n headers: {\n Authorization: `Basic ${btoa(accessToken + ':')}`,\n 'Content-Type': 'application/json',\n },\n }\n if (client) init.client = client\n const res = await fetch(`https://api.teller.io${endpoint}`, init)\n if (!res.ok) throw new Error(`${endpoint}: ${res.status} ${await res.text()}`)\n return res.json() as Promise\n}\n",[151],"2ac9f3f0-5a07-11f1-b309-ee650bb23af1","lib.ts","3af9b56c-5877-11f1-855d-ee650bb23af1",129,["D",1779912225422],14,"// Spend Agent — Shared Utilities\n//\n// `TELLER_APP_ID` resolution order:\n// 1. `TELLER_APP_ID` env var (set this when you remix — see README)\n// 2. The template's own sandbox-only App ID (lets Connect Bank work immediately\n// on a fresh remix, but you should replace it with your own)\n//\n// Teller App IDs are public identifiers (they appear in the browser), not\n// secrets. Sandbox-only — never use this default for production.\nconst TEMPLATE_DEFAULT_APP_ID = 'app_pr4h9kg679tq045oi0000'\nexport const TELLER_APP_ID = Deno.env.get('TELLER_APP_ID') || TEMPLATE_DEFAULT_APP_ID\n\n// ── Formatting ──────────────────────────────────────────────────\nexport function fmt(n: number): string {\n return (\n '$' +\n Math.abs(n).toLocaleString('en-US', { minimumFractionDigits: 2, maximumFractionDigits: 2 })\n )\n}\n\nexport function fmtK(n: number): string {\n const abs = Math.abs(n)\n return (n < 0 ? '-' : '') + (abs >= 1000 ? '$' + (abs / 1000).toFixed(1) + 'K' : fmt(n))\n}\n\nexport function pct(n: number, d: number): string {\n return d === 0 ? '0%' : ((n / d) * 100).toFixed(0) + '%'\n}\n\nexport function ago(iso: string): string {\n const ms = Date.now() - new Date(iso).getTime()\n const mins = Math.floor(ms / 60000)\n if (mins < 60) return `${mins}m ago`\n const hrs = Math.floor(mins / 60)\n if (hrs < 24) return `${hrs}h ago`\n return `${Math.floor(hrs / 24)}d ago`\n}\n\nexport function escHtml(s: string): string {\n return s\n .replace(/&/g, '&')\n .replace(//g, '>')\n .replace(/\"/g, '"')\n}\n\n// ── PEM Reconstruction ──────────────────────────────────────────\n// Val Town env vars strip newlines. This rebuilds valid PEM from flattened input.\nexport function fixPem(raw: string): string {\n if (raw.includes('\\n')) return raw\n const beginMatch = raw.match(/-----BEGIN ([A-Z ]+)-----/)\n const endMatch = raw.match(/-----END ([A-Z ]+)-----/)\n if (!beginMatch || !endMatch) return raw\n const type = beginMatch[1]\n let b64 = raw\n .replace(`-----BEGIN ${type}-----`, '')\n .replace(`-----END ${type}-----`, '')\n .replace(/\\s+/g, '')\n const lines: string[] = []\n for (let i = 0; i < b64.length; i += 64) {\n lines.push(b64.slice(i, i + 64))\n }\n return `-----BEGIN ${type}-----\\n${lines.join('\\n')}\\n-----END ${type}-----\\n`\n}\n\n// ── Category Colors ─────────────────────────────────────────────\nexport const CAT_COLORS: Record = {\n Housing: '#8b5cf6',\n Food: '#f97316',\n Transportation: '#3b82f6',\n Shopping: '#a855f7',\n Entertainment: '#ec4899',\n Health: '#ef4444',\n Subscriptions: '#6366f1',\n Bills: '#64748b',\n Travel: '#14b8a6',\n Investments: '#22d3ee',\n Transfers: '#475569',\n Salary: '#059669',\n Income: '#10b981',\n Gifts: '#f59e0b',\n Other: '#6b7280',\n}\n\n// ── HTML Shell ──────────────────────────────────────────────────\nexport function pageShell(title: string, activePath: string, body: string, scripts = ''): string {\n const nav = [\n { path: '/', label: 'Overview' },\n { path: '/ask', label: 'Ask' },\n { path: '/settings', label: 'Settings' },\n ]\n .map((n) => {\n const active = activePath === n.path\n return `${n.label}`\n })\n .join('')\n\n return `\n\n\n \n ${title} — Spend Agent\n \n \n\n\n

Spend Agent

${nav}

\n ${body}\n

\n ${scripts}\n\n`\n}\n",[159],"7b0f1330-5a08-11f1-a326-ee650bb23af1","digest.ts","7b0f140c-5a08-11f1-a326-ee650bb23af1",136,["D",1779912789589],0,"// Spend Agent — Weekly Digest Email\n// Sends a weekly burn report with trends, category breakdown, subscription detection.\nimport { sqlite, ensureSchema } from './db.ts'\nimport { fmt, pct } from './lib.ts'\nimport { email as sendEmail } from 'https://esm.town/v/std/email'\n\nexport default async function (_interval: Interval) {\n await ensureSchema()\n\n const recipient = await getConfigValue('email_recipient')\n if (!recipient) {\n console.log('No email_recipient configured. Skipping digest.')\n return\n }\n\n const now = new Date()\n const weekAgo = new Date(now.getTime() - 7 * 24 * 3600 * 1000)\n const weekStart = weekAgo.toISOString().slice(0, 10)\n const weekEnd = now.toISOString().slice(0, 10)\n const curMonth = `${now.getFullYear()}-${String(now.getMonth() + 1).padStart(2, '0')}`\n\n // This week's spending\n const weekRes = await sqlite.execute({\n sql: `SELECT category, SUM(abs_amount) as total, COUNT(*) as cnt\n FROM transactions\n WHERE date >= ? AND date <= ? AND is_income = 0 AND is_transfer = 0 AND is_duplicate = 0\n GROUP BY category ORDER BY total DESC`,\n args: [weekStart, weekEnd],\n })\n const weekCats = weekRes.rows.map((r: any) => ({\n cat: String(r[0] || 'Other'),\n total: Number(r[1]),\n cnt: Number(r[2]),\n }))\n const weekTotal = weekCats.reduce((s, c) => s + c.total, 0)\n\n // Monthly pace\n const dayOfMonth = now.getDate()\n const daysInMonth = new Date(now.getFullYear(), now.getMonth() + 1, 0).getDate()\n const monthRes = await sqlite.execute({\n sql: `SELECT SUM(abs_amount) FROM transactions WHERE substr(date,1,7) = ? AND is_income = 0 AND is_transfer = 0 AND is_duplicate = 0`,\n args: [curMonth],\n })\n const monthSpend = Number(monthRes.rows[0]?.[0]) || 0\n const monthPace = Math.round((monthSpend / dayOfMonth) * daysInMonth * 100) / 100\n\n // 3-month average\n const avgRes = await sqlite.execute({\n sql: `SELECT AVG(total_spend) FROM (\n SELECT total_spend FROM monthly_summaries WHERE month < ? ORDER BY month DESC LIMIT 3\n )`,\n args: [curMonth],\n })\n const avg3mo = Number(avgRes.rows[0]?.[0]) || 0\n\n // Subscriptions (recurring merchants: 3+ months)\n const subRes = await sqlite.execute(`\n SELECT description, COUNT(DISTINCT substr(date,1,7)) as months, ROUND(AVG(abs_amount),2) as avg_amt, MAX(date) as last\n FROM transactions\n WHERE is_income = 0 AND is_transfer = 0 AND is_duplicate = 0\n GROUP BY description HAVING months >= 3\n ORDER BY avg_amt DESC LIMIT 10\n `)\n const subs = subRes.rows.map((r: any) => ({\n desc: String(r[0]),\n months: Number(r[1]),\n avg: Number(r[2]),\n last: String(r[3]),\n }))\n\n // Unclassified count\n const uncRes = await sqlite.execute(\n 'SELECT COUNT(*), SUM(abs_amount) FROM transactions WHERE category IS NULL AND is_duplicate = 0'\n )\n const uncCount = Number(uncRes.rows[0]?.[0]) || 0\n const uncAmount = Number(uncRes.rows[0]?.[1]) || 0\n\n // Format email\n const catRows = weekCats\n .slice(0, 8)\n .map((c) => {\n const barLen = Math.round((c.total / (weekTotal || 1)) * 20)\n const bar = '█'.repeat(barLen) + '░'.repeat(20 - barLen)\n return `${c.cat.padEnd(20)} ${fmt(c.total).padStart(8)} ${bar} ${pct(c.total, weekTotal)}`\n })\n .join('\\n')\n\n const subRows = subs\n .slice(0, 6)\n .map((s) => `${s.desc.slice(0, 30).padEnd(30)} ${fmt(s.avg).padStart(8)} (${s.months} months)`)\n .join('\\n')\n\n const paceColor = monthPace > avg3mo * 1.1 ? '⚠️ ' : monthPace < avg3mo * 0.9 ? '✅ ' : ''\n\n const body = `\nBURN RATE\nThis week: ${fmt(weekTotal)}\nMonthly pace: ${paceColor}${fmt(monthPace)} (vs ${fmt(avg3mo)} 3-mo avg)\n\nTOP CATEGORIES\n${catRows || '(no spending this week)'}\n\n${subs.length > 0 ? `RECURRING / SUBSCRIPTIONS\\n${subRows}` : ''}\n\n${uncCount > 0 ? `NEEDS ATTENTION\\n${uncCount} unclassified transactions (${fmt(uncAmount)} total)` : 'All transactions classified ✓'}\n\n— Spend Agent\n`.trim()\n\n const weekLabel = `${weekAgo.toLocaleDateString('en-US', { month: 'short', day: 'numeric' })} – ${now.toLocaleDateString('en-US', { month: 'short', day: 'numeric' })}`\n\n try {\n await sendEmail({\n to: recipient,\n subject: `Your Week in Spending — ${weekLabel}`,\n text: body,\n })\n console.log(`Digest sent to ${recipient}`)\n } catch (e: any) {\n console.error(`Email failed: ${e.message}`)\n }\n}\n\nasync function getConfigValue(key: string): Promise {\n const res = await sqlite.execute({\n sql: 'SELECT value FROM config WHERE key = ?',\n args: [key],\n })\n return res.rows.length > 0 ? String(res.rows[0][0]) : null\n}\n",[167],"25b57a7a-59f2-11f1-9279-ee650bb23af1","classify.ts","62089d3a-5877-11f1-ab13-ee650bb23af1",86,["D",1779903197447],6,"// Spend Agent — Daily Classification Cron\n// Thin wrapper around classify-engine.ts for Val Town's interval runner.\nimport { runClassification } from './classify-engine.ts'\n\nexport default async function () {\n const result = await runClassification()\n if (result.errors.length > 0) console.log('Classification errors:', result.errors.join('; '))\n}\n",[175],"eb0117e8-59ee-11f1-bfca-ee650bb23af1","classify-ui.ts","d1610e4a-59eb-11f1-a639-ee650bb23af1",83,["D",1779901810486],"// Spend Agent — Classification Drawer UI\n// Extracted to stay under Val Town's 80K char file limit.\nimport { fmt, escHtml, CAT_COLORS } from './lib.ts'\n\ntype UncTx = {\n id: string\n date: string\n description: string\n abs_amount: number\n account_name: string\n institution: string\n}\n\nexport function classifyDrawerHtml(\n uncCount: number,\n uncTxs: UncTx[],\n currentPrompt: string\n): { banner: string; drawer: string; scripts: string } {\n const banner =\n uncCount > 0\n ? `

\n ${uncCount} unclassified transaction${uncCount > 1 ? 's' : ''}\n Review & Classify ▶\n

`\n : ''\n\n const drawer = `\n \n `\n\n const escapedTxs = JSON.stringify(uncTxs)\n const escapedPrompt = JSON.stringify(currentPrompt)\n const escapedColors = JSON.stringify(CAT_COLORS)\n\n const scripts = `\n var uncTxData = ${escapedTxs};\n var previewResults = null;\n var drawerPrompt = ${escapedPrompt};\n var originalPrompt = ${escapedPrompt};\n var catColors = ${escapedColors};\n\n function getCatColor(cat) {\n return catColors[cat] || '#6b7280';\n }\n\n function openClassifyDrawer() {\n document.getElementById('classify-overlay').style.display = 'block';\n document.getElementById('classify-drawer').style.display = 'block';\n document.getElementById('drawer-step-list').style.display = 'block';\n document.getElementById('drawer-step-preview').style.display = 'none';\n document.getElementById('drawer-prompt').value = drawerPrompt;\n renderTxList();\n }\n function closeClassifyDrawer() {\n document.getElementById('classify-overlay').style.display = 'none';\n document.getElementById('classify-drawer').style.display = 'none';\n }\n function onPromptEdit() {\n var btn = document.getElementById('drawer-save-prompt-btn');\n var changed = document.getElementById('drawer-prompt').value !== originalPrompt;\n btn.style.display = changed ? 'inline' : 'none';\n }\n function onPreviewPromptEdit() {\n var btn = document.getElementById('preview-save-prompt-btn');\n var changed = document.getElementById('preview-prompt').value !== originalPrompt;\n btn.style.display = changed ? 'inline' : 'none';\n }\n async function savePrompt() {\n var promptEl = document.getElementById('drawer-prompt') || document.getElementById('preview-prompt');\n var val = promptEl.value;\n var btns = [document.getElementById('drawer-save-prompt-btn'), document.getElementById('preview-save-prompt-btn')];\n btns.forEach(function(b) { if (b) b.textContent = 'Saving...'; });\n try {\n await fetch('/save-prompt', { method: 'POST', headers: {'Content-Type':'application/json'}, body: JSON.stringify({prompt: val}) });\n originalPrompt = val;\n btns.forEach(function(b) { if (b) { b.style.display = 'none'; b.textContent = 'Save'; } });\n // Sync both textareas\n var dp = document.getElementById('drawer-prompt');\n var pp = document.getElementById('preview-prompt');\n if (dp) dp.value = val;\n if (pp) pp.value = val;\n } catch(e) { btns.forEach(function(b) { if (b) b.textContent = 'Error'; }); }\n }\n function renderTxList() {\n var el = document.getElementById('drawer-tx-list');\n if (uncTxData.length === 0) { el.innerHTML = '

No unclassified transactions

'; return; }\n el.innerHTML = uncTxData.map(function(tx) {\n var d = new Date(tx.date + 'T12:00:00').toLocaleDateString('en-US', {month:'short',day:'numeric'});\n return '

' +\n '

' + tx.description.slice(0,45) + '

' +\n '

' + d + ' \\\\u00b7 ' + (tx.account_name || '') + '

' +\n '$' + tx.abs_amount.toFixed(2) + '

';\n }).join('');\n }\n async function runPreview() {\n var btn = document.getElementById('drawer-preview-btn');\n btn.textContent = 'Classifying...'; btn.disabled = true;\n try {\n var promptVal = document.getElementById('drawer-prompt').value;\n var body = {};\n if (promptVal !== originalPrompt) {\n body.prompt = promptVal;\n }\n var res = await fetch('/preview-classify', { method: 'POST', headers: {'Content-Type':'application/json'}, body: JSON.stringify(body) });\n var data = await res.json();\n if (data.error) { btn.textContent = 'Error: ' + data.error; btn.disabled = false; return; }\n previewResults = data.results;\n drawerPrompt = promptVal;\n renderPreview(data);\n document.getElementById('drawer-step-list').style.display = 'none';\n document.getElementById('drawer-step-preview').style.display = 'block';\n document.getElementById('preview-prompt').value = promptVal;\n } catch(e) { alert('Error: ' + e.message); }\n btn.textContent = 'Preview Classification'; btn.disabled = false;\n }\n async function retryFromPreview() {\n var btn = document.getElementById('drawer-retry-btn');\n btn.textContent = 'Classifying...'; btn.disabled = true;\n try {\n var promptVal = document.getElementById('preview-prompt').value;\n var body = {};\n if (promptVal !== originalPrompt) {\n body.prompt = promptVal;\n }\n var res = await fetch('/preview-classify', { method: 'POST', headers: {'Content-Type':'application/json'}, body: JSON.stringify(body) });\n var data = await res.json();\n if (data.error) { btn.textContent = 'Error: ' + data.error; btn.disabled = false; return; }\n previewResults = data.results;\n drawerPrompt = promptVal;\n // Sync prompt back to list step\n document.getElementById('drawer-prompt').value = promptVal;\n renderPreview(data);\n } catch(e) { alert('Error: ' + e.message); }\n btn.textContent = '\\\\u21bb Retry'; btn.disabled = false;\n }\n function renderPreview(data) {\n document.getElementById('preview-count').textContent = data.results.length + ' classified' + (data.errors.length ? ', ' + data.errors.length + ' errors' : '');\n var el = document.getElementById('drawer-preview-list');\n el.innerHTML = data.results.map(function(r) {\n var d = new Date(r.date + 'T12:00:00').toLocaleDateString('en-US', {month:'short',day:'numeric'});\n var conf = r.confidence >= 0.7 ? '#22c55e' : '#f59e0b';\n var catColor = getCatColor(r.category);\n return '

' +\n '

' +\n '' + r.description.slice(0,40) + '' +\n '$' + r.abs_amount.toFixed(2) + '

' +\n '

' +\n '' + r.category + '' +\n '' + Math.round(r.confidence * 100) + '%' +\n '' + (r.reasoning || '').slice(0,60) + '

';\n }).join('');\n }\n function backToList() {\n document.getElementById('drawer-step-list').style.display = 'block';\n document.getElementById('drawer-step-preview').style.display = 'none';\n }\n async function approveResults() {\n if (!previewResults || previewResults.length === 0) return;\n var btn = document.getElementById('drawer-approve-btn');\n btn.textContent = 'Saving...'; btn.disabled = true;\n try {\n var promptEl = document.getElementById('preview-prompt');\n var body = { results: previewResults };\n if (promptEl.value !== originalPrompt) body.prompt = promptEl.value;\n var res = await fetch('/approve-classify', { method: 'POST', headers: {'Content-Type':'application/json'}, body: JSON.stringify(body) });\n var data = await res.json();\n btn.textContent = data.applied + ' applied!';\n setTimeout(function() { location.reload(); }, 1000);\n } catch(e) { btn.textContent = 'Error'; btn.disabled = false; }\n }`\n\n return { banner, drawer, scripts }\n}\n",[183],"7b493fce-5a08-11f1-9022-ee650bb23af1","classify-engine.ts","28683b24-5879-11f1-ab12-ee650bb23af1",140,["D",1779912789892],11,"// Spend Agent — Classification Engine (shared logic)\n// Exported functions used by app.ts (on-demand) and classify.ts (daily cron).\nimport {\n sqlite,\n ensureSchema,\n getConfig,\n DEFAULT_SYSTEM_PROMPT,\n CATEGORIES,\n getCategories,\n recomputeMonth,\n} from './db.ts'\nimport Anthropic from 'npm:@anthropic-ai/sdk'\n\n// ── Shared tool-use classification helper ───────────────────────\ntype RawTx = {\n id: string\n date: string\n description: string\n amount: number\n abs_amount: number\n account_name: string\n institution: string\n is_income: number\n}\n\ntype ClassifyResult = {\n id: string\n category: string\n confidence: number\n reasoning: string\n}\n\nasync function classifyBatch(\n client: Anthropic,\n batch: RawTx[],\n cats: string[],\n systemPrompt: string\n): Promise<{ results: ClassifyResult[]; error?: string }> {\n const txLines = batch\n .map(\n (tx, idx) =>\n `${idx + 1}. [${tx.id}] ${tx.date} | ${tx.description} | $${tx.abs_amount} | ${tx.account_name} (${tx.institution}) | ${tx.is_income ? 'CREDIT/INCOME' : 'DEBIT/SPEND'}`\n )\n .join('\\n')\n\n const tool: Anthropic.Tool = {\n name: 'classify_transactions',\n description: 'Classify a batch of financial transactions into categories',\n input_schema: {\n type: 'object' as const,\n properties: {\n classifications: {\n type: 'array',\n items: {\n type: 'object',\n properties: {\n id: { type: 'string', description: 'Transaction ID' },\n category: { type: 'string', enum: cats, description: 'Exactly one valid category' },\n confidence: { type: 'number', description: 'Confidence 0-1' },\n reasoning: { type: 'string', description: 'Brief reasoning' },\n },\n required: ['id', 'category', 'confidence', 'reasoning'],\n },\n },\n },\n required: ['classifications'],\n },\n }\n\n const response = await client.messages.create({\n model: 'claude-haiku-4-5-20251001',\n max_tokens: 8192,\n system: systemPrompt,\n tools: [tool],\n tool_choice: { type: 'tool', name: 'classify_transactions' },\n messages: [\n {\n role: 'user',\n content: `Classify these ${batch.length} transactions.\n\nIMPORTANT: For CREDIT/INCOME transactions, classify by underlying purpose — do NOT default to \"Income\":\n- Payroll / direct deposits from employers → \"Salary\"\n- Rent payments from roommate (Venmo/Zelle with \"rent\" in description) → \"Housing\"\n- Travel credits, hotel refunds → \"Travel\"\n- Entertainment credits → \"Entertainment\"\n- Uber/Lyft refunds → \"Transportation\"\n- Utility/wifi reimbursements → \"Bills\"\n- Self-transfers (Cash App to yourself, PayPal transfer) → \"Transfers\"\n- Zelle/Venmo from friends or family (not for rent/bills) → \"Gifts\"\n- Only use \"Income\" for truly miscellaneous income (tax refunds, unknown deposits)\n\nTransactions:\n${txLines}`,\n },\n ],\n })\n\n const toolBlock = response.content.find((b) => b.type === 'tool_use')\n if (!toolBlock || toolBlock.type !== 'tool_use') {\n return { results: [], error: 'No tool_use block in response' }\n }\n\n const input = toolBlock.input as { classifications: ClassifyResult[] }\n return { results: input.classifications }\n}\n\nexport async function runClassification(\n reclassifyAll = false\n): Promise<{ classified: number; skipped: number; deduped: number; errors: string[] }> {\n await ensureSchema()\n const apiKey = Deno.env.get('ANTHROPIC_API_KEY')\n if (!apiKey)\n return { classified: 0, skipped: 0, deduped: 0, errors: ['Missing ANTHROPIC_API_KEY'] }\n\n const errors: string[] = []\n const deduped = await runDedup()\n\n const sql = reclassifyAll\n ? \"SELECT id, date, description, amount, abs_amount, account_name, institution, is_income FROM transactions WHERE category_source != 'user' AND is_duplicate = 0 ORDER BY date DESC\"\n : 'SELECT id, date, description, amount, abs_amount, account_name, institution, is_income FROM transactions WHERE category IS NULL AND is_duplicate = 0 ORDER BY date DESC'\n\n const txRes = await sqlite.execute(sql)\n const uncategorized = txRes.rows.map((r: any) => ({\n id: String(r[0]),\n date: String(r[1]),\n description: String(r[2]),\n amount: Number(r[3]),\n abs_amount: Number(r[4]),\n account_name: String(r[5] || ''),\n institution: String(r[6] || ''),\n is_income: Number(r[7]),\n }))\n\n if (uncategorized.length === 0) {\n console.log(`Classification: 0 to classify, ${deduped} deduped`)\n return { classified: 0, skipped: 0, deduped, errors }\n }\n\n const systemPrompt = await getConfig('system_prompt', DEFAULT_SYSTEM_PROMPT)\n const cats = await getCategories()\n const client = new Anthropic({ apiKey })\n let classified = 0\n let skipped = 0\n const batchSize = 50\n const affectedMonths = new Set()\n\n for (let i = 0; i < uncategorized.length; i += batchSize) {\n const batch = uncategorized.slice(i, i + batchSize)\n\n try {\n const { results, error: batchError } = await classifyBatch(client, batch, cats, systemPrompt)\n if (batchError) {\n errors.push(`Batch ${i}: ${batchError}`)\n skipped += batch.length\n continue\n }\n\n for (const r of results) {\n const cat = r.category\n const isTransfer = cat === 'Transfers' || cat === 'Investments' ? 1 : 0\n const tx = batch.find((t) => t.id === r.id)\n const isIncome = cat === 'Income' ? 1 : (tx?.is_income ?? 0)\n try {\n await sqlite.execute({\n sql: `UPDATE transactions SET category = ?, category_source = 'llm', llm_confidence = ?, llm_reasoning = ?, is_transfer = ?, is_income = ? WHERE id = ? AND (category_source != 'user' OR category_source IS NULL)`,\n args: [cat, r.confidence, r.reasoning, isTransfer, isIncome, r.id],\n })\n classified++\n if (tx) affectedMonths.add(tx.date.slice(0, 7))\n } catch {\n skipped++\n }\n }\n } catch (e: any) {\n errors.push(`Batch ${i}: ${e.message}`)\n skipped += batch.length\n }\n }\n\n for (const month of affectedMonths) await recomputeMonth(month)\n console.log(\n `Classification: ${classified} classified, ${skipped} skipped, ${deduped} deduped, ${errors.length} errors`\n )\n return { classified, skipped, deduped, errors }\n}\n\nexport type PreviewResult = {\n id: string\n date: string\n description: string\n abs_amount: number\n account_name: string\n institution: string\n is_income: number\n category: string\n confidence: number\n reasoning: string\n}\n\nexport async function previewClassification(\n customPrompt?: string\n): Promise<{ results: PreviewResult[]; errors: string[] }> {\n await ensureSchema()\n const apiKey = Deno.env.get('ANTHROPIC_API_KEY')\n if (!apiKey) return { results: [], errors: ['Missing ANTHROPIC_API_KEY'] }\n\n const txRes = await sqlite.execute(\n 'SELECT id, date, description, amount, abs_amount, account_name, institution, is_income FROM transactions WHERE category IS NULL AND is_duplicate = 0 ORDER BY date DESC'\n )\n const uncategorized = txRes.rows.map((r: any) => ({\n id: String(r[0]),\n date: String(r[1]),\n description: String(r[2]),\n amount: Number(r[3]),\n abs_amount: Number(r[4]),\n account_name: String(r[5] || ''),\n institution: String(r[6] || ''),\n is_income: Number(r[7]),\n }))\n\n if (uncategorized.length === 0) return { results: [], errors: [] }\n\n const systemPrompt = customPrompt || (await getConfig('system_prompt', DEFAULT_SYSTEM_PROMPT))\n const cats = await getCategories()\n const client = new Anthropic({ apiKey })\n const allResults: PreviewResult[] = []\n const errors: string[] = []\n const batchSize = 50\n\n for (let i = 0; i < uncategorized.length; i += batchSize) {\n const batch = uncategorized.slice(i, i + batchSize)\n\n try {\n const { results, error: batchError } = await classifyBatch(client, batch, cats, systemPrompt)\n if (batchError) {\n errors.push(`Batch ${i}: ${batchError}`)\n continue\n }\n\n for (const r of results) {\n const tx = batch.find((t) => t.id === r.id)\n if (!tx) continue\n allResults.push({\n ...tx,\n category: r.category,\n confidence: r.confidence,\n reasoning: r.reasoning,\n })\n }\n } catch (e: any) {\n errors.push(`Batch ${i}: ${e.message}`)\n }\n }\n\n return { results: allResults, errors }\n}\n\nexport async function applyClassification(\n results: PreviewResult[]\n): Promise<{ applied: number; errors: string[] }> {\n await ensureSchema()\n const cats = await getCategories()\n let applied = 0\n const errors: string[] = []\n const affectedMonths = new Set()\n\n for (const r of results) {\n const cat = cats.includes(r.category) ? r.category : 'Other'\n const isTransfer = cat === 'Transfers' || cat === 'Investments' ? 1 : 0\n const isIncome = cat === 'Income' ? 1 : r.is_income\n try {\n await sqlite.execute({\n sql: `UPDATE transactions SET category = ?, category_source = 'llm', llm_confidence = ?, llm_reasoning = ?, is_transfer = ?, is_income = ? WHERE id = ? AND (category_source != 'user' OR category_source IS NULL)`,\n args: [cat, r.confidence, r.reasoning, isTransfer, isIncome, r.id],\n })\n applied++\n affectedMonths.add(r.date.slice(0, 7))\n } catch (e: any) {\n errors.push(`${r.id}: ${e.message}`)\n }\n }\n\n for (const month of affectedMonths) await recomputeMonth(month)\n return { applied, errors }\n}\n\nasync function runDedup(): Promise {\n const res = await sqlite.execute(`\n SELECT a.id, b.id, a.description, b.description, a.institution, b.institution\n FROM transactions a\n JOIN transactions b ON a.abs_amount = b.abs_amount\n AND ABS(julianday(a.date) - julianday(b.date)) <= 2\n AND a.id < b.id AND a.institution != b.institution\n WHERE a.is_duplicate = 0 AND b.is_duplicate = 0 AND a.abs_amount > 50\n `)\n\n let deduped = 0\n for (const row of res.rows) {\n const idA = String(row[0]),\n idB = String(row[1])\n const descA = String(row[2]).toUpperCase(),\n descB = String(row[3]).toUpperCase()\n const genericPatterns = ['VENMO PAYMENT', 'ZELLE PAYMENT', 'PAYPAL']\n const aIsGeneric = genericPatterns.some((p) => descA.includes(p))\n const bIsGeneric = genericPatterns.some((p) => descB.includes(p))\n\n if (aIsGeneric && !bIsGeneric) {\n await sqlite.execute({\n sql: \"UPDATE transactions SET is_duplicate = 1, duplicate_of = ?, is_transfer = 1, category = 'Transfers', category_source = 'dedup' WHERE id = ?\",\n args: [idB, idA],\n })\n deduped++\n } else if (bIsGeneric && !aIsGeneric) {\n await sqlite.execute({\n sql: \"UPDATE transactions SET is_duplicate = 1, duplicate_of = ?, is_transfer = 1, category = 'Transfers', category_source = 'dedup' WHERE id = ?\",\n args: [idA, idB],\n })\n deduped++\n }\n }\n return deduped\n}\n",[190],"7b7601e4-5a08-11f1-934b-ee650bb23af1","app.ts","bc926470-5a07-11f1-98a3-ee650bb23af1",141,["D",1779912789611],1,"http","// Spend Agent — Lean burn tracker\n// Home: stacked bar chart + burn number + category breakdown (expandable)\n// Settings: connect bank + classification prompt + CSV upload\nimport {\n sqlite,\n ensureSchema,\n getConfig,\n setConfig,\n DEFAULT_SYSTEM_PROMPT,\n getCategories,\n recomputeMonth,\n} from './db.ts'\nimport { runClassification, previewClassification, applyClassification } from './classify-engine.ts'\nimport { classifyDrawerHtml } from './classify-ui.ts'\nimport { runSync } from './sync-engine.ts'\nimport { blob } from 'https://esm.town/v/std/blob'\nimport { fmt, escHtml, CAT_COLORS, pageShell, TELLER_APP_ID } from './lib.ts'\n\nexport default async function (req: Request): Promise {\n await ensureSchema()\n const url = new URL(req.url)\n const path = url.pathname\n\n if (path === '/sync' && req.method === 'POST') return handleSync()\n if (path === '/classify' && req.method === 'POST') return handleClassify(false)\n if (path === '/reclassify' && req.method === 'POST') return handleClassify(true)\n if (path === '/save-token' && req.method === 'POST') return handleSaveToken(req)\n if (path === '/update-category' && req.method === 'POST') return handleUpdateCategory(req)\n if (path === '/save-prompt' && req.method === 'POST') return handleSavePrompt(req)\n if (path === '/upload-csv' && req.method === 'POST') return handleCsvUpload(req)\n\n if (path === '/preview-classify' && req.method === 'POST') return handlePreviewClassify(req)\n if (path === '/approve-classify' && req.method === 'POST') return handleApproveClassify(req)\n if (path === '/add-rule' && req.method === 'POST') return handleAddRule(req)\n if (path === '/ask' && req.method === 'POST') return handleAsk(req)\n if (path === '/diagram.png') {\n const png = await blob.get('spend-agent-diagram')\n return new Response(png.body, {\n headers: { 'Content-Type': 'image/png', 'Cache-Control': 'public, max-age=86400' },\n })\n }\n if (path === '/ask') return html(await askPage())\n if (path === '/settings') return html(await settingsPage())\n return html(await burnPage(url))\n}\n\nfunction html(body: string): Response {\n return new Response(body, { headers: { 'Content-Type': 'text/html' } })\n}\n\n// ── Burn Page (Home) ────────────────────────────────────────────\nasync function burnPage(url: URL): Promise {\n const now = new Date()\n const monthParam = url.searchParams.get('month') || ''\n const curMonth =\n monthParam || `${now.getFullYear()}-${String(now.getMonth() + 1).padStart(2, '0')}`\n\n // Check setup state for empty-state\n const hasCert = !!Deno.env.get('TELLER_CERT')\n const tokensRes = await sqlite.execute('SELECT COUNT(*) FROM teller_tokens')\n const hasAccounts = Number(tokensRes.rows[0]?.[0]) > 0\n const txCountRes = await sqlite.execute('SELECT COUNT(*) FROM transactions')\n const txTotal = Number(txCountRes.rows[0]?.[0]) || 0\n\n if (txTotal === 0) {\n const steps = []\n if (!TELLER_APP_ID) {\n steps.push(`

Get started

Upload a CSV below, or connect a bank by setting TELLER_APP_ID in your env vars. Sandbox works without certificates — add TELLER_CERT + TELLER_KEY for real banks.

`)\n } else if (!hasAccounts) {\n steps.push(`

Connect your bank

Link a checking or credit card account to start tracking.

\n Go to Settings\n

`)\n } else {\n steps.push(`

Syncing transactions...

Your bank is connected. Transactions will appear after the next sync.

\n \n

`)\n }\n steps.push(`

Or upload a CSV export from your credit card or Venmo

\n Upload CSV\n

`)\n const scripts = ``\n return pageShell('Burn', '/', steps.join(''), scripts)\n }\n\n // ── Stacked bar chart data: per-month per-category ──\n const stackRes = await sqlite.execute(\n `SELECT substr(date,1,7) AS m, COALESCE(category, 'Unclassified') AS cat, SUM(abs_amount) AS spend\n FROM transactions\n WHERE is_income = 0 AND is_transfer = 0 AND is_duplicate = 0\n GROUP BY m, cat\n ORDER BY m DESC`\n )\n\n // Build per-month structure\n const monthMap: Record<\n string,\n { month: string; total: number; cats: { cat: string; spend: number }[] }\n > = {}\n for (const r of stackRes.rows) {\n const m = String(r[0])\n const cat = String(r[1])\n const spend = Number(r[2])\n if (!monthMap[m]) monthMap[m] = { month: m, total: 0, cats: [] }\n monthMap[m].total += spend\n monthMap[m].cats.push({ cat, spend })\n }\n\n const allMonths = Object.values(monthMap)\n .sort((a, b) => a.month.localeCompare(b.month))\n .slice(-12)\n const maxSpend = Math.max(...allMonths.map((m) => m.total), 1)\n\n // Per-month income for net chart\n const incomeStackRes = await sqlite.execute(\n `SELECT substr(date,1,7) AS m, SUM(abs_amount) AS inc\n FROM transactions\n WHERE is_income = 1 AND is_transfer = 0 AND is_duplicate = 0\n GROUP BY m ORDER BY m DESC`\n )\n const monthIncomeMap: Record = {}\n for (const r of incomeStackRes.rows) {\n monthIncomeMap[String(r[0])] = Number(r[1])\n }\n\n // Current month spend\n const curData = allMonths.find((m) => m.month === curMonth)\n const monthSpend = curData?.total || 0\n\n // Unclassified count\n const uncRes = await sqlite.execute({\n sql: 'SELECT COUNT(*) FROM transactions WHERE category IS NULL AND is_duplicate = 0 AND substr(date,1,7) = ?',\n args: [curMonth],\n })\n const uncCount = Number(uncRes.rows[0]?.[0]) || 0\n\n // Category breakdown for current month\n const cats = await getCategories()\n const catRes = await sqlite.execute({\n sql: `SELECT category, SUM(abs_amount) as total, COUNT(*) as cnt\n FROM transactions WHERE substr(date,1,7) = ? AND is_income = 0 AND is_transfer = 0 AND is_duplicate = 0\n GROUP BY category ORDER BY SUM(abs_amount) DESC`,\n args: [curMonth],\n })\n\n // Income total for current month\n const incRes = await sqlite.execute({\n sql: `SELECT SUM(abs_amount) FROM transactions\n WHERE substr(date,1,7) = ? AND is_income = 1 AND is_transfer = 0 AND is_duplicate = 0`,\n args: [curMonth],\n })\n const monthIncome = Number(incRes.rows[0]?.[0]) || 0\n const netCashFlow = monthIncome - monthSpend\n\n // All transactions for this month\n const txRes = await sqlite.execute({\n sql: `SELECT id, date, description, abs_amount, category, category_source, llm_confidence, llm_reasoning, is_income, is_transfer, account_name, institution\n FROM transactions WHERE substr(date,1,7) = ? AND is_duplicate = 0\n ORDER BY date DESC, abs_amount DESC`,\n args: [curMonth],\n })\n\n // Group by category + collect income transactions\n const txByCategory: Record = {}\n const incomeTxs: any[] = []\n for (const r of txRes.rows) {\n const cat = r[4] ? String(r[4]) : 'Unclassified'\n const isIncome = Number(r[8])\n const isTransfer = Number(r[9])\n const txObj = {\n id: String(r[0]),\n date: String(r[1]),\n desc: String(r[2]),\n amount: Number(r[3]),\n category: r[4] ? String(r[4]) : null,\n source: r[5] ? String(r[5]) : null,\n confidence: r[6] != null ? Number(r[6]) : null,\n reasoning: r[7] ? String(r[7]) : null,\n account: String(r[10] || ''),\n institution: String(r[11] || ''),\n }\n if (isTransfer) continue\n if (isIncome) {\n incomeTxs.push(txObj)\n } else {\n if (!txByCategory[cat]) txByCategory[cat] = []\n txByCategory[cat].push(txObj)\n }\n }\n\n // ── Stacked bar chart HTML ──\n // Collect global category totals for legend (top 7)\n const globalCatTotals: Record = {}\n for (const m of allMonths) {\n for (const c of m.cats) {\n globalCatTotals[c.cat] = (globalCatTotals[c.cat] || 0) + c.spend\n }\n }\n const legendCats = Object.entries(globalCatTotals)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 7)\n .map(([cat]) => cat)\n\n const barChart = allMonths\n .map((m) => {\n const totalH = Math.max(Math.round((m.total / maxSpend) * 120), 2)\n const active = m.month === curMonth\n const label = new Date(m.month + '-15').toLocaleDateString('en-US', {\n month: 'short',\n })\n const shortYear = m.month.slice(2, 4)\n\n // Consolidate small categories (<4% of month) into \"Other\" for cleaner bars\n const threshold = m.total * 0.04\n const bigCats: { cat: string; spend: number }[] = []\n let smallSum = 0\n for (const c of m.cats) {\n if (c.spend >= threshold) bigCats.push(c)\n else smallSum += c.spend\n }\n if (smallSum > 0) bigCats.push({ cat: 'Other', spend: smallSum })\n bigCats.sort((a, b) => a.spend - b.spend)\n\n const segments = bigCats\n .map((c) => {\n const segH = Math.max(Math.round((c.spend / m.total) * totalH), 2)\n const color = CAT_COLORS[c.cat] || '#6b7280'\n return `

`\n })\n .join('')\n\n return `

${m.total >= 1000 ? '$' + (m.total / 1000).toFixed(1) + 'k' : '$' + Math.round(m.total)}

${segments}

${label}
'${shortYear}

`\n })\n .join('')\n\n const legend = legendCats\n .map((cat) => {\n const color = CAT_COLORS[cat] || '#6b7280'\n return `${cat}`\n })\n .join('')\n\n // ── Net income bar chart ──\n const netMonths = allMonths.map((m) => {\n const inc = monthIncomeMap[m.month] || 0\n const net = inc - m.total\n return { month: m.month, spend: m.total, income: inc, net }\n })\n const maxNetAbs = Math.max(...netMonths.map((m) => Math.abs(m.net)), 1)\n\n const netBarChart = netMonths\n .map((m) => {\n const active = m.month === curMonth\n const label = new Date(m.month + '-15').toLocaleDateString('en-US', { month: 'short' })\n const shortYear = m.month.slice(2, 4)\n const barH = Math.max(Math.round((Math.abs(m.net) / maxNetAbs) * 100), 2)\n const color = m.net >= 0 ? '#22c55e' : '#ef4444'\n const sign = m.net >= 0 ? '+' : '-'\n const valStr =\n Math.abs(m.net) >= 1000\n ? `${sign}$${(Math.abs(m.net) / 1000).toFixed(1)}k`\n : `${sign}$${Math.round(Math.abs(m.net))}`\n\n return `

${valStr}

${label}
'${shortYear}

`\n })\n .join('')\n\n const netLegend = `Positive\n Negative`\n\n // Category accordion\n const catRows = catRes.rows\n .map((r: any) => {\n const cat = String(r[0] || 'Unclassified')\n const total = Number(r[1])\n const count = Number(r[2])\n const color = CAT_COLORS[cat] || '#6b7280'\n const pctVal = monthSpend > 0 ? Math.round((total / monthSpend) * 100) : 0\n const barW = monthSpend > 0 ? Math.round((total / monthSpend) * 100) : 0\n const slug = cat.toLowerCase().replace(/[^a-z]/g, '')\n\n const txs = txByCategory[cat] || []\n const txRowsHtml = txs\n .map((tx) => {\n const dateLabel = new Date(tx.date + 'T12:00:00').toLocaleDateString('en-US', {\n month: 'short',\n day: 'numeric',\n })\n const confBadge =\n tx.confidence != null && tx.confidence < 0.7\n ? 'LOW'\n : ''\n const catOptions = cats\n .map(\n (c: string) =>\n ``\n )\n .join('')\n\n return `

\n ${dateLabel}\n ${escHtml(tx.desc.slice(0, 40))}\n -${fmt(tx.amount)}\n

${escHtml(tx.desc)}

\n ${escHtml(tx.account)}${tx.institution ? ' · ' + escHtml(tx.institution) : ''}\n ${tx.reasoning ? `${escHtml(tx.reasoning)}` : ''}\n

\n ${confBadge}\n

`\n })\n .join('')\n\n return `

\n \n ${escHtml(cat)}\n ${count}\n

\n ${fmt(total)}\n ${pctVal}%\n ▶\n

${txRowsHtml}

`\n })\n .join('')\n\n // Collect unclassified transactions for drawer\n const uncTxs = (txByCategory['Unclassified'] || []).map((tx: any) => ({\n id: tx.id,\n date: tx.date,\n description: tx.desc,\n abs_amount: tx.amount,\n account_name: tx.account,\n institution: tx.institution,\n }))\n const currentPrompt = await getConfig('system_prompt', DEFAULT_SYSTEM_PROMPT)\n const drawerUi = classifyDrawerHtml(uncCount, uncTxs, currentPrompt)\n const uncBanner = drawerUi.banner\n\n const monthLabel = new Date(curMonth + '-15').toLocaleDateString('en-US', {\n month: 'long',\n year: 'numeric',\n })\n\n // Group income by category\n const incomeByCategory: Record = {}\n for (const tx of incomeTxs) {\n const cat = tx.category || 'Income'\n if (!incomeByCategory[cat]) incomeByCategory[cat] = { txs: [], total: 0 }\n incomeByCategory[cat].txs.push(tx)\n incomeByCategory[cat].total += tx.amount\n }\n // ── Budget view: merged spend + income per category ──\n const spendByCategory: Record = {}\n for (const r of catRes.rows) {\n spendByCategory[String(r[0] || 'Unclassified')] = Number(r[1])\n }\n const allBudgetCats = new Set([...Object.keys(spendByCategory), ...Object.keys(incomeByCategory)])\n const budgetRows = [...allBudgetCats]\n .map((cat) => {\n const spend = spendByCategory[cat] || 0\n const income = incomeByCategory[cat]?.total || 0\n const net = income - spend\n const spendTxs = txByCategory[cat] || []\n const incTxs = incomeByCategory[cat]?.txs || []\n return { cat, spend, income, net, spendTxs, incTxs, totalActivity: spend + income }\n })\n .sort((a, b) => b.totalActivity - a.totalActivity)\n\n const budgetCatRows = budgetRows\n .map((row) => {\n const color = CAT_COLORS[row.cat] || '#6b7280'\n const slug = 'bgt-' + row.cat.toLowerCase().replace(/[^a-z]/g, '')\n const netColor = row.net >= 0 ? '#22c55e' : '#ef4444'\n const netSign = row.net >= 0 ? '+' : '-'\n const txCount = row.spendTxs.length + row.incTxs.length\n // Sub-labels showing spend and income breakdown\n const parts: string[] = []\n if (row.spend > 0) parts.push(`-${fmt(row.spend)}`)\n if (row.income > 0) parts.push(`+${fmt(row.income)}`)\n const breakdown =\n parts.length === 2\n ? `(${parts.join(' ')})`\n : ''\n\n // Mix spend + income transactions sorted by date\n const allTxs = [\n ...row.spendTxs.map((tx: any) => ({ ...tx, _type: 'spend' })),\n ...row.incTxs.map((tx: any) => ({ ...tx, _type: 'income' })),\n ].sort((a: any, b: any) => b.date.localeCompare(a.date))\n\n const txRowsHtml = allTxs\n .map((tx: any) => {\n const dateLabel = new Date(tx.date + 'T12:00:00').toLocaleDateString('en-US', {\n month: 'short',\n day: 'numeric',\n })\n const amtColor = tx._type === 'income' ? '#22c55e' : '#ef4444'\n const amtSign = tx._type === 'income' ? '+' : '-'\n const catOptions = cats\n .map(\n (c: string) =>\n ``\n )\n .join('')\n return `

\n ${dateLabel}\n ${escHtml(tx.desc.slice(0, 40))}\n ${amtSign}${fmt(tx.amount)}\n

${escHtml(tx.desc)}

\n ${escHtml(tx.account)}${tx.institution ? ' · ' + escHtml(tx.institution) : ''}\n ${tx.reasoning ? `${escHtml(tx.reasoning)}` : ''}\n

\n \n

`\n })\n .join('')\n\n return `

\n \n ${escHtml(row.cat)}\n ${txCount}\n

\n ${netSign}${fmt(Math.abs(row.net))}\n ${breakdown}\n ▶\n

${txRowsHtml}

`\n })\n .join('')\n\n const body = `\n ${uncBanner}\n

${barChart}

${legend}

${netBarChart}

${netLegend}

\n ${monthLabel}\n

\n \n \n

Total Spend

\n ${fmt(monthSpend)}\n

Income

\n ${monthIncome > 0 ? '+' : ''}${fmt(monthIncome)}\n

−

Spend

\n ${fmt(monthSpend)}\n

Net

\n = 0 ? '#22c55e' : '#ef4444'}\">${netCashFlow >= 0 ? '+' : '-'}${fmt(Math.abs(netCashFlow))}\n

${catRows || '

No spending this month

\n \n ${drawerUi.drawer}`\n\n const scripts = ``\n\n return pageShell('Burn', '/', body, scripts)\n}\n\n// ── Ask Page (Agent Q&A) ────────────────────────────────────────\nasync function askPage(): Promise {\n const suggestions = [\n \"Where's my money going this month?\",\n 'How does this month compare to last?',\n 'Any new subscriptions I should know about?',\n \"What's my biggest spending spike?\",\n 'Am I spending more on food than usual?',\n 'What can I cut to save $500/month?',\n ]\n\n const chips = suggestions\n .map(\n (s) => ``\n )\n .join('')\n\n const body = `\n

Ask about your spending

AI-powered insights from your real transaction data

${chips}

\n \n

\n \n \n \n \n

`\n\n const scripts = ``\n\n return pageShell('Ask', '/ask', body, scripts)\n}\n\nasync function gatherFinancialContext(): Promise {\n const now = new Date()\n const curMonth = `${now.getFullYear()}-${String(now.getMonth() + 1).padStart(2, '0')}`\n\n // Last 6 months summaries\n const summaries = await sqlite.execute(\n `SELECT month, total_spend, total_income, category_breakdown, tx_count\n FROM monthly_summaries ORDER BY month DESC LIMIT 6`\n )\n\n let ctx = `## Monthly Summaries (last 6 months)\\n`\n for (const r of summaries.rows) {\n const month = String(r[0])\n const spend = Number(r[1])\n const income = Number(r[2])\n const cats = r[3] ? String(r[3]) : '{}'\n ctx += `${month}: $${spend.toFixed(0)} spent, $${income.toFixed(0)} income | ${cats}\\n`\n }\n\n // Current month transactions (last 50)\n const txRes = await sqlite.execute({\n sql: `SELECT date, description, abs_amount, category, account_name, institution, is_income, is_transfer\n FROM transactions\n WHERE substr(date,1,7) = ? AND is_duplicate = 0\n ORDER BY date DESC LIMIT 50`,\n args: [curMonth],\n })\n\n ctx += `\\n## Current month transactions (${curMonth}, most recent 50)\\n`\n ctx += `date | description | amount | category | account\\n`\n for (const r of txRes.rows) {\n const isIncome = Number(r[6])\n const isTransfer = Number(r[7])\n const tag = isIncome ? ' [INCOME]' : isTransfer ? ' [TRANSFER]' : ''\n ctx += `${r[0]} | ${String(r[1]).slice(0, 50)} | $${Number(r[2]).toFixed(2)}${tag} | ${r[3] || 'Unclassified'} | ${r[4] || ''}\\n`\n }\n\n // Recurring charges detection\n const recurRes = await sqlite.execute(\n `SELECT description, COUNT(*) as cnt, ROUND(AVG(abs_amount),2) as avg_amt\n FROM transactions\n WHERE is_income = 0 AND is_transfer = 0 AND is_duplicate = 0\n GROUP BY LOWER(TRIM(description))\n HAVING cnt >= 3\n ORDER BY cnt DESC LIMIT 20`\n )\n\n ctx += `\\n## Likely recurring charges (appeared 3+ times)\\n`\n for (const r of recurRes.rows) {\n ctx += `${r[0]} — ${r[1]}x, avg $${r[2]}\\n`\n }\n\n // Recent user corrections (for context)\n const overrides = await sqlite.execute(\n `SELECT description, category FROM transactions\n WHERE category_source = 'user' ORDER BY created_at DESC LIMIT 20`\n )\n if (overrides.rows.length > 0) {\n ctx += `\\n## Recent user corrections (these override LLM classifications)\\n`\n for (const r of overrides.rows) {\n ctx += `${String(r[0]).slice(0, 50)} → ${r[1]}\\n`\n }\n }\n\n return ctx\n}\n\nasync function handleAsk(req: Request): Promise {\n try {\n const { question, images } = await req.json()\n if (!question && (!images || images.length === 0))\n return Response.json({ error: 'No question' }, { status: 400 })\n\n const apiKey = Deno.env.get('ANTHROPIC_API_KEY')\n if (!apiKey)\n return Response.json({\n answer: 'ANTHROPIC_API_KEY not set. Add it in Val Town environment variables.',\n })\n\n const context = await gatherFinancialContext()\n const hasImages = images && images.length > 0\n\n // Build multimodal content blocks\n const content: any[] = []\n if (hasImages) {\n for (const img of images) {\n const match = img.match(/^data:(image\\/[a-zA-Z+]+);base64,(.+)$/)\n if (match) {\n content.push({\n type: 'image',\n source: { type: 'base64', media_type: match[1], data: match[2] },\n })\n }\n }\n }\n content.push({\n type: 'text',\n text:\n question || 'What do you see in this screenshot? Suggest any classification corrections.',\n })\n\n const systemPrompt = `You are a helpful personal finance assistant analyzing the user's real transaction data.${hasImages ? ' The user has shared a screenshot — analyze it alongside their transaction data to identify any misclassified transactions.' : ''} Be concise, specific, and use actual dollar amounts from the data. Format responses with markdown: use **bold** for key numbers and totals, bullet lists for category breakdowns, and ### headings to organize sections. Keep paragraphs short. If you spot concerning patterns, flag them directly. Don't be preachy — be useful.${hasImages ? '\\n\\nWhen suggesting category corrections, list each one clearly: the transaction description, its current category, and what it should be changed to.' : ''}\\n\\n${context}`\n\n const res = await fetch('https://api.anthropic.com/v1/messages', {\n method: 'POST',\n headers: {\n 'x-api-key': apiKey,\n 'anthropic-version': '2023-06-01',\n 'content-type': 'application/json',\n },\n body: JSON.stringify({\n model: 'claude-haiku-4-5-20251001',\n max_tokens: 2048,\n system: systemPrompt,\n messages: [{ role: 'user', content }],\n }),\n })\n\n const data = await res.json()\n const answer = data.content?.[0]?.text || 'No response from AI.'\n return Response.json({ answer })\n } catch (e: any) {\n return Response.json({ answer: 'Error: ' + e.message })\n }\n}\n\n// ── Settings Page ───────────────────────────────────────────────\nasync function settingsPage(): Promise {\n const prompt = await getConfig('system_prompt', DEFAULT_SYSTEM_PROMPT)\n const tellerEnv = Deno.env.get('TELLER_ENV') || 'sandbox'\n const isSandbox = tellerEnv === 'sandbox'\n\n // Teller tokens\n const tokensRes = await sqlite.execute(\n 'SELECT id, institution, linked_at FROM teller_tokens ORDER BY linked_at DESC'\n )\n const tellerTokens = tokensRes.rows.map((r: any) => ({\n id: String(r[0]),\n inst: String(r[1]),\n linked: String(r[2]),\n }))\n\n // Sandbox credentials disclosed via a small

accordion below the\n // \"Get one free\" / \"Connect Bank\" affordance. Discoverable but unobtrusive.\n // Source: https://teller.io/docs/guides/sandbox\n const sandboxCredsHtml = isSandbox\n ? `\n

View sandbox test credentials

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

Username	`username` (or `otp` / `challenge` for MFA flows)
Password	`password`
OTP code	`0000` (if username = `otp`)
Challenge	`blue` (if username = `challenge`)

All sandbox institutions behave identically. Teller sandbox docs →

`\n : ''\n\n function renderAccountList(\n tokens: { id: string; inst: string; linked: string }[],\n source: string\n ) {\n if (tokens.length === 0)\n return `No ${source} accounts linked`\n return tokens\n .map(\n (\n t\n ) => `

\n \n ${escHtml(t.inst)}\n Linked ${new Date(t.linked).toLocaleDateString('en-US', { month: 'short', day: 'numeric' })}\n \n

`\n )\n .join('')\n }\n\n const body = `\n

Teller Accounts

\n Banks & credit cards\n

\n ${renderAccountList(tellerTokens, 'Teller')}\n ${!TELLER_APP_ID ? `

The accounts above are demo placeholders. Set TELLER_APP_ID in env vars to connect a real (sandbox or production) bank. Get one free at teller.io

` : ''}\n ${TELLER_APP_ID ? `

` : ''}\n ${sandboxCredsHtml}\n

CSV Import

\n \n \n

\n \n

Select a format above first

\n \n

\n \n \n \n

Classification Prompt

Tell the AI how to categorize. Use natural language.

\n \n

\n \n \n

`\n\n const scripts = `${TELLER_APP_ID ? '' : ''}\n `\n\n return pageShell('Settings', '/settings', body, scripts)\n}\n\n// ── API Handlers ────────────────────────────────────────────────\nasync function handleSync(): Promise {\n try {\n return Response.json(await runSync())\n } catch (e: any) {\n return Response.json({ error: e.message }, { status: 500 })\n }\n}\n\nasync function handleClassify(reclassifyAll: boolean): Promise {\n try {\n return Response.json(await runClassification(reclassifyAll))\n } catch (e: any) {\n return Response.json({ error: e.message }, { status: 500 })\n }\n}\n\nasync function handlePreviewClassify(req: Request): Promise {\n try {\n const body = await req.json().catch(() => ({}))\n const result = await previewClassification(body.prompt || undefined)\n return Response.json(result)\n } catch (e: any) {\n return Response.json({ error: e.message }, { status: 500 })\n }\n}\n\nasync function handleApproveClassify(req: Request): Promise {\n try {\n const { results, prompt } = await req.json()\n if (prompt) await setConfig('system_prompt', prompt)\n const result = await applyClassification(results)\n return Response.json(result)\n } catch (e: any) {\n return Response.json({ error: e.message }, { status: 500 })\n }\n}\n\nasync function handleSaveToken(req: Request): Promise {\n const { accessToken, enrollment } = await req.json()\n const instName = enrollment?.institution?.name || 'Unknown'\n const existing = await sqlite.execute({\n sql: 'SELECT id FROM teller_tokens WHERE institution = ?',\n args: [instName],\n })\n if (existing.rows.length > 0) {\n await sqlite.execute({\n sql: \"UPDATE teller_tokens SET access_token = ?, enrollment_id = ?, linked_at = datetime('now') WHERE institution = ?\",\n args: [accessToken, enrollment?.id, instName],\n })\n } else {\n const id = crypto.randomUUID()\n await sqlite.execute({\n sql: 'INSERT INTO teller_tokens (id, access_token, enrollment_id, institution) VALUES (?, ?, ?, ?)',\n args: [id, accessToken, enrollment?.id, instName],\n })\n }\n let syncResult = {\n accounts: 0,\n inserted: 0,\n skipped: 0,\n errors: [] as string[],\n }\n try {\n syncResult = await runSync()\n } catch {}\n if (syncResult.inserted > 0) {\n try {\n await runClassification()\n } catch {}\n }\n return Response.json({ ok: true, institution: instName, ...syncResult })\n}\n\nasync function handleUpdateCategory(req: Request): Promise {\n const { id, category } = await req.json()\n\n // Get full transaction context before updating (for intelligent learned rule)\n const txRes = await sqlite.execute({\n sql: `SELECT description, category, date, abs_amount, source, account_name, institution\n FROM transactions WHERE id = ?`,\n args: [id],\n })\n if (txRes.rows.length === 0) return Response.json({ ok: false, error: 'Transaction not found' })\n\n const row = txRes.rows[0]\n const oldCategory = String(row[1] || 'Unclassified')\n const txContext = {\n description: String(row[0]),\n date: String(row[2]),\n amount: Number(row[3]),\n source: String(row[4] || ''),\n account: String(row[5] || ''),\n institution: String(row[6] || ''),\n }\n\n await sqlite.execute({\n sql: \"UPDATE transactions SET category = ?, category_source = 'user', llm_confidence = NULL, llm_reasoning = NULL WHERE id = ?\",\n args: [category || null, id],\n })\n\n const month = txContext.date.slice(0, 7)\n await recomputeMonth(month)\n\n // Generate intelligent learned rule with full context\n if (category && category !== oldCategory) {\n await appendLearnedRule(txContext, category, oldCategory)\n }\n\n return Response.json({ ok: true })\n}\n\nconst LEARNED_RULES_HEADER = '\\n\\n## Learned from your corrections'\n\nasync function generateSmartRule(\n tx: {\n description: string\n date: string\n amount: number\n source: string\n account: string\n institution: string\n },\n newCategory: string,\n oldCategory: string\n): Promise {\n const apiKey = Deno.env.get('ANTHROPIC_API_KEY')\n if (!apiKey) {\n // Fallback to template rule if no API key\n return `${tx.description.trim().slice(0, 50)} (${tx.institution || tx.source}, ~$${Math.round(tx.amount)}) → ${newCategory}`\n }\n\n try {\n const res = await fetch('https://api.anthropic.com/v1/messages', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'x-api-key': apiKey,\n 'anthropic-version': '2023-06-01',\n },\n body: JSON.stringify({\n model: 'claude-haiku-4-5-20251001',\n max_tokens: 150,\n messages: [\n {\n role: 'user',\n content: `Write a ONE-LINE classification rule for a personal finance categorizer. The user corrected this transaction from \"${oldCategory}\" to \"${newCategory}\".\n\nTransaction: \"${tx.description}\"\nAmount: $${tx.amount.toFixed(2)}\nSource: ${tx.source} (${tx.institution}, ${tx.account})\nDate: ${tx.date}\n\nWrite a concise rule that captures the PATTERN (not just this one transaction). Include relevant context like the payment platform, merchant name, amount range, or frequency if it helps. Format: \"pattern description → ${newCategory}\"\n\nExamples of good rules:\n- Venmo payments to \"May\" (~$3,300, monthly) → Housing (rent via Venmo)\n- DoorDash orders from San Francisco → Food\n- SCV Labs LLC ACH payments (~$2,000-5,000) → Transfers (own business)\n- Monthly Spotify charge (~$16) → Subscriptions\n\nRespond with ONLY the rule text, nothing else.`,\n },\n ],\n }),\n })\n\n if (res.ok) {\n const data = await res.json()\n const ruleText = data.content?.[0]?.text?.trim()\n if (ruleText && ruleText.length < 200) return ruleText\n }\n } catch {}\n\n // Fallback: enriched template\n const src = tx.institution || tx.source || 'unknown'\n return `${tx.description.trim().slice(0, 50)} (${src}, ~$${Math.round(tx.amount)}) → ${newCategory}`\n}\n\nasync function appendLearnedRule(\n tx: {\n description: string\n date: string\n amount: number\n source: string\n account: string\n institution: string\n },\n newCategory: string,\n oldCategory: string\n) {\n const prompt = await getConfig('system_prompt', DEFAULT_SYSTEM_PROMPT)\n const cleanDesc = tx.description.trim().slice(0, 50)\n\n // Generate an intelligent rule\n const ruleText = await generateSmartRule(tx, newCategory, oldCategory)\n const newRule = `\\n- ${ruleText}`\n\n // Check if rule already exists for this description pattern\n if (prompt.includes(cleanDesc)) {\n // Find and replace the existing rule line containing this description\n const lines = prompt.split('\\n')\n const updatedLines = lines.map((line) => {\n if (line.includes(cleanDesc) && line.trimStart().startsWith('- ')) {\n return `- ${ruleText}`\n }\n return line\n })\n await setConfig('system_prompt', updatedLines.join('\\n'))\n return\n }\n\n // Append new rule\n if (prompt.includes(LEARNED_RULES_HEADER)) {\n await setConfig('system_prompt', prompt + newRule)\n } else {\n await setConfig('system_prompt', prompt + LEARNED_RULES_HEADER + newRule)\n }\n}\n\nasync function handleSavePrompt(req: Request): Promise {\n const { prompt } = await req.json()\n await setConfig('system_prompt', prompt)\n return Response.json({ ok: true })\n}\n\nasync function handleAddRule(req: Request): Promise {\n try {\n const { rule } = await req.json()\n if (!rule) return Response.json({ error: 'No rule' }, { status: 400 })\n const prompt = await getConfig('system_prompt', DEFAULT_SYSTEM_PROMPT)\n const newRule = `\\n- ${rule.trim()}`\n if (prompt.includes(LEARNED_RULES_HEADER)) {\n await setConfig('system_prompt', prompt + newRule)\n } else {\n await setConfig('system_prompt', prompt + LEARNED_RULES_HEADER + newRule)\n }\n return Response.json({ ok: true })\n } catch (e: any) {\n return Response.json({ error: e.message }, { status: 500 })\n }\n}\n\nasync function handleCsvUpload(req: Request): Promise {\n try {\n const form = await req.formData()\n const file = form.get('file') as File\n const type = form.get('type') as string\n if (!file) return Response.json({ ok: false, error: 'No file' })\n const text = await file.text()\n const lines = text.split('\\n')\n let inserted = 0,\n skipped = 0\n const affectedMonths = new Set()\n const rows: { date: string; desc: string; amount: number }[] = []\n\n if (type === 'credit_card') {\n // Generic credit card CSV parser — auto-detects column layout from headers\n const headerLine = parseCSVLine(lines[0]).map((h) => h.toLowerCase().trim())\n const dateCol = headerLine.findIndex(\n (h) => /^(transaction\\s*)?date$/.test(h) || h === 'trans date' || h === 'posting date'\n )\n const descCol = headerLine.findIndex(\n (h) =>\n /^desc(ription)?$/.test(h) ||\n h === 'merchant' ||\n h === 'merchant name' ||\n h === 'payee' ||\n h === 'name'\n )\n const amountCol = (() => {\n // Prefer 'amount', fall back to 'amt', 'charge', 'debit'\n const i = headerLine.findLastIndex((h) => /^(amount|amt|charge|debit)$/.test(h))\n return i >= 0\n ? i\n : headerLine.findLastIndex((h) => h.includes('amount') || h.includes('amt'))\n })()\n if (dateCol < 0 || descCol < 0 || amountCol < 0)\n return Response.json({\n ok: false,\n error:\n 'Could not find Date, Description, and Amount columns in header. Found: ' +\n headerLine.join(', '),\n })\n // Sign convention: Chase amounts are negative for charges, Amex are positive\n const isChaseStyle = headerLine.some((h) => h === 'post date' || h === 'posting date')\n // Detect institution from headers\n const institution = isChaseStyle ? 'Chase' : 'American Express'\n const accountName = isChaseStyle ? 'Chase Card' : 'Amex Card'\n const sourceTag = isChaseStyle ? 'csv_chase' : 'csv_amex'\n\n for (let i = 1; i < lines.length; i++) {\n const parts = parseCSVLine(lines[i])\n if (parts.length <= Math.max(dateCol, descCol, amountCol)) continue\n const date = formatDate(parts[dateCol])\n const desc = parts[descCol]\n const rawAmount = parseFloat(parts[amountCol])\n if (!date || isNaN(rawAmount)) continue\n // Normalize: negative = spend. Chase already negative, Amex needs negation\n const amount = isChaseStyle ? rawAmount : -rawAmount\n const id = makeId(sourceTag, date, desc, amount)\n try {\n await sqlite.execute({\n sql: `INSERT INTO transactions (id, source, date, description, amount, abs_amount, account_name, institution) VALUES (?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [id, sourceTag, date, desc, amount, Math.abs(amount), accountName, institution],\n })\n inserted++\n rows.push({ date, desc, amount })\n affectedMonths.add(date.slice(0, 7))\n } catch {\n skipped++\n }\n }\n } else if (type === 'venmo') {\n let headerIdx = -1\n for (let i = 0; i < lines.length; i++) {\n if (lines[i].includes(',ID,Datetime,')) {\n headerIdx = i\n break\n }\n }\n if (headerIdx === -1)\n return Response.json({\n ok: false,\n error: 'Could not find Venmo CSV header',\n })\n for (let i = headerIdx + 1; i < lines.length; i++) {\n const parts = parseCSVLine(lines[i])\n if (parts.length < 9) continue\n const datetime = parts[2]\n const desc = parts[5] || parts[4]\n const amountStr = (parts[8] || '').replace(/[$ +,]/g, '')\n const amount = parseFloat(amountStr)\n if (!datetime || isNaN(amount)) continue\n const date = datetime.slice(0, 10)\n const id = makeId('venmo', date, desc, amount)\n const isIncome = amount > 0 ? 1 : 0\n try {\n await sqlite.execute({\n sql: \"INSERT INTO transactions (id, source, date, description, amount, abs_amount, account_name, institution, is_income) VALUES (?, 'csv_venmo', ?, ?, ?, ?, 'Venmo', 'Venmo', ?)\",\n args: [id, date, desc, amount, Math.abs(amount), isIncome],\n })\n inserted++\n rows.push({ date, desc, amount })\n affectedMonths.add(date.slice(0, 7))\n } catch {\n skipped++\n }\n }\n }\n for (const m of affectedMonths) await recomputeMonth(m)\n return Response.json({ ok: true, inserted, skipped, rows })\n } catch (e: any) {\n return Response.json({ ok: false, error: e.message })\n }\n}\n\nfunction makeId(source: string, date: string, desc: string, amount: number): string {\n const key = `${source}_${date}_${desc.trim().toLowerCase()}_${amount.toFixed(2)}`\n let h = 0\n for (let i = 0; i < key.length; i++) {\n h = ((h << 5) - h + key.charCodeAt(i)) | 0\n }\n return `csv_${source}_${date}_${Math.abs(h).toString(36)}`\n}\n\nfunction formatDate(d: string): string {\n if (d.includes('/')) {\n const [m, day, y] = d.split('/')\n return `${y}-${m.padStart(2, '0')}-${day.padStart(2, '0')}`\n }\n return d.slice(0, 10)\n}\n\nfunction parseCSVLine(line: string): string[] {\n const result: string[] = []\n let current = ''\n let inQuotes = false\n for (const ch of line) {\n if (ch === '\"') {\n inQuotes = !inQuotes\n } else if (ch === ',' && !inQuotes) {\n result.push(current.trim())\n current = ''\n } else {\n current += ch\n }\n }\n result.push(current.trim())\n return result\n}\n",[198],"7b201842-5a08-11f1-a13e-ee650bb23af1","README.md","6b344338-5a06-11f1-a1de-ee650bb23af1",138,["D",1779912789686],"# Spend Agent\n\nPersonal burn tracker. Connect your bank via [Teller](https://teller.io) (a developer-friendly bank API — free for personal use, supports Chase, BofA, Amex, and most major US banks) or upload CSVs, get AI-powered categorization, and see where your money goes.\n\n> This template uses Val Town's per-val scoped SQLite — when you remix, you get your own isolated database with no leftover state from the template author.\n\n## Setup (5 minutes)\n\n1. **Remix this project** on Val Town.\n2. **Set `ANTHROPIC_API_KEY`** (Settings > Environment Variables). Get a key from [anthropic.com](https://anthropic.com) — needed for AI classification + the Ask tab.\n3. **Replace the Teller App ID** (see \"Teller setup\" below) — required before you can connect a real (or sandbox) bank.\n4. Open the Settings page and click **Connect Bank** — Teller Connect opens with sandbox institutions. Use the test credentials shown in the \"View sandbox test credentials\" accordion (`username` / `password`).\n5. After linking, the dashboard populates with the synced transactions. Or upload a CSV (Chase, Amex, Venmo) from Settings.\n6. Hit **Preview Classification** on the dashboard banner to categorize transactions with AI.\n\n## Teller setup (required — 2 minutes)\n\nThis template ships with the **author's own Teller App ID baked in as a default** (`app_pr4h9kg679tq045oi0000`) so the Connect Bank button works the moment you remix. **You must replace it with your own** before sharing the val publicly or using it seriously — App IDs are public identifiers tied to a developer account, and sandbox transactions made under someone else's App ID show up in their Teller dashboard.\n\n**Steps:**\n\n1. Sign up at [teller.io](https://teller.io) (free, no credit card, ~30 seconds).\n2. From your Teller dashboard, copy your **Application ID** (format: `app_xxxxxxxxxxxxx` — this is a public string, not a secret).\n3. On your remixed val, add it as an env var: `TELLER_APP_ID = app_yourIdHere`. It overrides the baked-in default automatically (`lib.ts:11`).\n4. Refresh the Settings page — the Connect Bank button now uses your App ID.\n\n**Teller environment modes:**\n\n| `TELLER_ENV` | Certs required? | Real bank data? | When to use |\n| ------------------- | ---------------------------------- | --------------- | ----------------------------------------------------------------------- |\n| `sandbox` (default) | No | No | Default — fake test institutions, sandbox credentials shown in Settings |\n| `development` | Yes (`TELLER_CERT` + `TELLER_KEY`) | Limited | Teller's dev tier — small set of real institutions, no PCI scope |\n| `production` | Yes (`TELLER_CERT` + `TELLER_KEY`) | Yes | Live bank connections — requires Teller paid plan |\n\nFor sandbox, **no mTLS certs are needed.** When you click \"Connect Bank\" with `TELLER_ENV=sandbox`, Teller Connect opens with a list of fake institutions. Use the test credentials shown in the \"View sandbox test credentials\" accordion on the Settings page:\n\n- Username: `username` (or `otp` / `challenge` for MFA flows)\n- Password: `password`\n- OTP code: `0000` (if username = `otp`)\n- Challenge answer: `blue` (if username = `challenge`)\n\nSee the [Teller sandbox docs](https://teller.io/docs/guides/sandbox) for full details.\n\n## How It Works\n\n![Architecture](https://kevinsuh--b6105878587711f18c02ee650bb23af1.web.val.run/diagram.png?v=2)\n\nThe template handles the boring part — syncing transactions from banks + Venmo and classifying them with AI. Once your data lands as structured rows, **your app** is whatever you build on top: the included dashboard and ask-agent, plus anything else you wire up (alerts, digests, custom views).\n\n**The feedback loop is the key insight**: more data + prompt refinement = better classification over time. Once your data is categorized, the structured output powers everything downstream.\n\n## Ideas After You Remix\n\nOnce your transactions are classified, the structured data is yours to build on:\n\n- **Find & cancel subscriptions** — \"Show me all my recurring subscriptions. Which ones haven't I used in 3 months? Help me cancel them by next billing cycle.\"\n- **Budget guardrails with alerts** — Set up a cron that texts you when a category (restaurants, golf, shopping) exceeds your monthly budget. Proactive, not reactive.\n- **Spending trends & accountability** — \"How much do I spend on food per day on average? How do I trend that down?\" Have the agent check in weekly and keep you honest.\n- **Smart digest emails** — Weekly or monthly email: \"You spent $X this month, up 15% from last month. Top 3 categories that grew: ...\" (Val Town free tier sends emails to yourself via `std/email`)\n- **Ask anything** — The `/ask` tab already lets you chat with your financial data. Ask \"what did I spend on travel last quarter?\" or \"am I on track for my savings goal?\"\n- **Custom automations** — Val Town crons + Claude + your categorized data = any workflow you can imagine. Budget forecasting, tax prep summaries, spending comparisons across months.\n\n## Data Sources\n\n| Source | Provider | Cost | Best For |\n| -------------------- | -------- | ------------------------- | ----------------------- |\n| Banks & credit cards | Teller | Free (up to 100 accounts) | Chase, BofA, Amex, etc. |\n| CSV upload | Built-in | Free | Any bank, manual import |\n\nAll sources flow into the same transaction table. Connect N Teller accounts — they all normalize and classify together.\n\n## Classification Engine\n\n**AI classification** — Claude Haiku batch-classifies uncategorized transactions using Anthropic tool use with JSON schema enforcement. The `category` field is constrained to an `enum` — no hallucinated categories possible.\n\n**Interactive flow:**\n\n1. Click \"Review & Classify\" banner — drawer opens with unclassified transactions\n2. Review/edit the classification prompt — click \"Preview Classification\"\n3. Review results with color-coded category pills + confidence scores\n4. Edit prompt inline and \"Retry\" or \"Approve All\" to commit\n\n**Manual overrides** — Click any transaction to re-categorize. Manual changes stick permanently and are never re-classified.\n\n## Dashboard\n\n- **Burn page** — Stacked bar chart (color-coded by category) over 12 months. Click a month to drill down. Categories expand to show transactions with full descriptions and AI reasoning.\n- **Ask page** — Chat with your financial data using Claude (natural language queries).\n- **Settings page** — Connect banks (Teller), upload CSVs (Chase, Amex, Venmo), edit classification prompt, manage categories.\n\n## Files\n\n| File | Type | Purpose |\n| -------------------- | ---------------- | ----------------------------------------------------- |\n| `app.ts` | http | Dashboard, settings, API routes |\n| `db.ts` | script | SQLite schema, config helpers, default categories |\n| `lib.ts` | script | Formatting, HTML shell, category colors |\n| `classify-engine.ts` | script | LLM classification engine (tool use with JSON schema) |\n| `classify-ui.ts` | script | Classification drawer UI |\n| `classify.ts` | interval (daily) | Thin cron wrapper — calls `runClassification()` |\n| `sync-engine.ts` | script | Teller mTLS sync logic |\n| `sync.ts` | interval (15min) | Thin cron wrapper — calls `runSync()` |\n\n## Customizing Categories\n\nDefault: Housing, Food, Transportation, Shopping, Entertainment, Health, Subscriptions, Bills, Travel, Investments, Transfers, Salary, Income, Gifts, Other\n\nCustomizable on the Settings page. Edit the prompt with natural language rules:\n\n```\n- DoorDash and UberEats are Food, not Transportation\n- Recurring charges like Netflix are Subscriptions\n- Venmo payments TO someone are actual spend, not Transfers\n```\n\nHit \"Re-classify All\" after updating. Manual overrides preserved.\n\n## Cost\n\n- **Teller**: Free (up to 100 accounts)\n- **Claude Haiku**: ~$0.01/day for ~100 transactions\n- **Val Town**: Free tier works for personal use\n",[207],"pulls","branches","forks","envVars",{"_220":62,"_222":171},"connections",{"_220":171,"_221":171},"count","unfilledCount","emptyCount",{"_42":206,"_32":207,"_30":208,"_141":-5,"_40":41,"_39":209,"_143":48,"_37":257,"_13":145,"_33":34,"_35":211,"_24":48,"_148":-5,"_233":258,"_27":259},{"_42":197,"_32":198,"_30":199,"_141":-5,"_40":41,"_39":200,"_143":48,"_37":254,"_13":202,"_33":203,"_35":204,"_24":48,"_148":-5,"_233":255,"_27":256},{"_42":189,"_32":190,"_30":191,"_141":-5,"_40":41,"_39":192,"_143":48,"_37":251,"_13":194,"_33":34,"_35":195,"_24":48,"_148":-5,"_233":252,"_27":253},{"_42":182,"_32":183,"_30":184,"_141":-5,"_40":41,"_39":185,"_143":25,"_37":248,"_13":155,"_33":34,"_35":187,"_24":48,"_148":-5,"_233":249,"_27":250},{"_42":174,"_32":175,"_30":176,"_141":-5,"_40":41,"_39":177,"_143":25,"_37":245,"_13":179,"_33":146,"_35":180,"_24":48,"_148":-5,"_233":246,"_27":247},{"_42":166,"_32":167,"_30":168,"_141":-5,"_40":41,"_39":169,"_143":48,"_37":242,"_13":171,"_33":34,"_35":172,"_24":48,"_148":-5,"_233":243,"_27":244},{"_42":158,"_32":159,"_30":160,"_141":-5,"_40":41,"_39":161,"_143":48,"_37":239,"_13":163,"_33":34,"_35":164,"_24":48,"_148":-5,"_233":240,"_27":241},{"_42":150,"_32":151,"_30":152,"_141":-5,"_40":41,"_39":153,"_143":48,"_37":236,"_13":155,"_33":34,"_35":156,"_24":48,"_148":-5,"_233":237,"_27":238},{"_42":138,"_32":139,"_30":140,"_141":-5,"_40":41,"_39":142,"_143":25,"_37":232,"_13":145,"_33":146,"_35":147,"_24":48,"_148":-5,"_233":234,"_27":235},["D",1779741957609],"children",[],[139],["D",1779912789596],[],[151],["D",1779912225422],[],[159],["D",1779912789589],[],[167],["D",1779903197447],[],[175],["D",1779901810486],[],[183],["D",1779912789892],[],[190],["D",1779912789611],[],[198],["D",1779912789686],[],[207],["D",1779740379107],["D",1789504908499],{"_99":98,"_106":102},{"_99":98,"_100":-5,"_101":102,"_18":55,"_103":104,"_105":48},{"_13":88,"_32":89,"_42":41,"_90":43,"_91":-5,"_92":-5,"_93":-5,"_94":-5,"_95":-5,"_96":44,"_97":98},"ctx",{"_81":-5,"_126":298,"_299":300,"_301":302,"_303":48,"_304":48,"_305":48,"_306":25,"_307":-5,"_308":-7,"_309":-7,"_310":171,"_311":48,"_312":48,"_313":-5,"_314":48,"_315":48,"_316":48,"_317":-5},"ENV",{"_269":270,"_271":272,"_273":89,"_274":275,"_276":277,"_278":279,"_280":281,"_282":283,"_284":285,"_286":287,"_288":289,"_290":291,"_292":293,"_294":295,"_296":297},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

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