[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_157":158,"_159":160},"routes/_app.x.$handle.$name",{"_95":94,"_32":44,"_103":85,"_27":104,"_13":14,"_105":-5,"_11":106,"_107":108,"_109":110,"_111":112,"_113":114,"_20":-5,"_115":-5,"_116":-5,"_117":48,"_118":119,"_120":25,"_121":-5,"_122":-5,"_123":124},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_42":43,"_32":44,"_37":45,"_46":-5,"_47":48,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":-5,"_57":48,"_58":-5,"_59":-5,"_60":61,"_62":63,"_64":-5,"_65":-5,"_66":-5,"_67":-5,"_68":69,"_70":69,"_71":72,"_73":72,"_74":72,"_75":69,"_76":69,"_77":78,"_79":80,"_81":82,"_83":48},"version",13,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":25,"_27":28,"_29":28},"file",{"_30":31,"_32":28,"_33":34,"_35":36,"_37":38,"_39":14,"_40":41,"_24":25},"previous",{"_30":31,"_32":28,"_33":34,"_35":36},"deleted",true,"deletedHere","path","main-copy.ts","latestPath","fileId","85b8f228-a7e3-11f1-99cb-1607ee4eb77e","name","fileType","http","content","// process-b2b-orders.ts\n// Val Town interval val — polls orders@sodafountain.uk for genuine B2B/wholesale\n// POs, matches customer + products in Breww, creates the order at book price,\n// and accepts it automatically when confident. Falls back to a Draft + email\n// flag when the customer or product match is ambiguous. See SKILL.md\n// (lifeblood-order-processing) for the full business logic this implements.\n\nimport { blob } from \"https://esm.town/v/std/blob\";\n\n// ---------- Secrets (set these as Val Town secrets on this val) ----------\nconst TENANT_ID = \"2ff21b32-fd4b-4dc0-b43b-8d66bbe9d9fa\";\nconst CLIENT_ID = \"865646e4-96c0-4b95-aa0d-4520883e005f\";\nconst GRAPH_CLIENT_SECRET = Deno.env.get(\"GRAPH_CLIENT_SECRET\")!;\nconst BREWW_API_KEY = Deno.env.get(\"BREWW_API_KEY\")!;\nconst MAILBOX = \"orders@sodafountain.uk\";\nconst NOTIFY_TO = \"chris@sodafountain.uk\";\nconst NOTIFY_FROM = \"lucy@drinklifeblood.com\";\n\nconst BREWW_BASE = \"https://breww.com/api/\";\nconst BREWW_HEADERS = {\n Authorization: `Bearer ${BREWW_API_KEY}`,\n \"User-Agent\":\n \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 Chrome/124.0.0.0 Safari/537.36\",\n Accept: \"application/json\",\n \"Content-Type\": \"application/json\",\n};\n\n// ---------- Dynamic customer matching ----------\n// No hardcoded account table. Every run pulls the live Breww customer list\n// and matches purely on whether a customer's own name/address text appears\n// in the incoming PO — since a customer's PO will always contain their own\n// business name somewhere (letterhead, delivery address, stock location).\n// This means brand-new customers work automatically the moment they exist\n// as a Breww record; nothing needs to be added here by hand.\n//\n// A learned cache (sender email domain -> customer ID) is kept in a Val\n// Town blob so repeat orders from the same sender skip the fuzzy scan\n// entirely after the first successful match — faster, and immune to PO\n// wording changing between orders.\nconst MIN_MATCH_LENGTH = 6; // ignore customer names/fragments shorter than this to avoid false positives\n\ninterface BrewwCustomer {\n id: number;\n name: string;\n price_book_in_use?: { id: number; name: string } | null;\n billing_address?: { first_line?: string };\n delivery_address?: { first_line?: string };\n entity_type_display?: string;\n}\n\n// Price book names that mean \"this is a DTC/Shopify consumer, not a B2B\n// trade account\" — excluded from the matching pool entirely. This is what\n// cuts ~900 total customer records down to the ~100 that are actually\n// wholesale/trade accounts, both for speed and to stop a DTC customer's\n// personal name ever being mistaken for a trade account.\nconst NON_B2B_PRICE_BOOKS = [\"D2C\", \"tester\"];\n\nasync function getAllBrewwCustomers(): Promise {\n let url = BREWW_BASE + \"customers-suppliers/?page_size=200\";\n const all: BrewwCustomer[] = [];\n while (url) {\n const res = await fetch(url, { headers: BREWW_HEADERS });\n const data = await res.json();\n all.push(...(data.results ?? []));\n url = data.next ?? null;\n }\n // Only match against real, B2B trade customers — not leads, suppliers,\n // or DTC/Shopify consumers (identified by price_book_in_use.name).\n return all.filter(\n (c) =>\n c.entity_type_display === \"Customer\" &&\n c.price_book_in_use?.name &&\n !NON_B2B_PRICE_BOOKS.includes(c.price_book_in_use.name),\n );\n}\n\nfunction matchableStrings(c: BrewwCustomer): string[] {\n return [c.name, c.billing_address?.first_line, c.delivery_address?.first_line]\n .filter((s): s is string => !!s && s.length >= MIN_MATCH_LENGTH);\n}\n\n// Finds the customer whose name/address text appears in the PO, preferring\n// the longest (most specific) match. Returns null if zero or multiple\n// distinct customers match, so ambiguous cases fall to manual review\n// instead of guessing.\nfunction findCustomerInText(customers: BrewwCustomer[], text: string) {\n const lowerText = text.toLowerCase();\n let best: { customer: BrewwCustomer; matchLength: number } | null = null;\n const distinctMatches = new Set();\n\n for (const c of customers) {\n for (const s of matchableStrings(c)) {\n if (lowerText.includes(s.toLowerCase())) {\n distinctMatches.add(c.id);\n if (!best || s.length > best.matchLength) {\n best = { customer: c, matchLength: s.length };\n }\n }\n }\n }\n\n if (distinctMatches.size !== 1 || !best) return null; // none, or ambiguous\n return best.customer;\n}\n\n// Flavour keyword -> product name fragment (case-insensitive substring match\n// against Breww's live product list, so this survives product ID changes).\nconst FLAVOUR_KEYWORDS: { keyword: RegExp; nameContains: string }[] = [\n { keyword: /original/i, nameContains: \"The Original\" },\n { keyword: /hopical/i, nameContains: \"Hopical Punch\" },\n { keyword: /mangosaurus/i, nameContains: \"Mangosaurus\" },\n { keyword: /lemondrop/i, nameContains: \"Lemondrop\" },\n { keyword: /ginger/i, nameContains: \"Ginger Beer\" },\n];\n\n// Ignore these — DTC Shopify order emails, never touch.\nconst IGNORE_SENDER_DOMAINS = [\"drinklifeblood.com\"];\nconst IGNORE_SUBJECT_PATTERNS = [/^\\[Raw Culture\\] Order/i];\n\ninterface ReviewItem {\n subject: string;\n reason: string;\n messageId: string;\n}\ninterface ProcessedItem {\n subject: string;\n orderNumber: string;\n orderId: number;\n total: number;\n breww_url: string;\n}\n\nasync function getGraphToken(): Promise {\n const res = await fetch(\n `https://login.microsoftonline.com/${TENANT_ID}/oauth2/v2.0/token`,\n {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body: new URLSearchParams({\n grant_type: \"client_credentials\",\n client_id: CLIENT_ID,\n client_secret: GRAPH_CLIENT_SECRET,\n scope: \"https://graph.microsoft.com/.default\",\n }),\n },\n );\n const data = await res.json();\n return data.access_token;\n}\n\nasync function getUnreadOrderEmails(token: string) {\n const url =\n `https://graph.microsoft.com/v1.0/users/${MAILBOX}/mailFolders/inbox/messages` +\n `?$filter=isRead eq false and hasAttachments eq true` +\n `&$top=25&$orderby=receivedDateTime desc` +\n `&$select=id,subject,from,receivedDateTime,hasAttachments`;\n const res = await fetch(url, {\n headers: { Authorization: `Bearer ${token}` },\n });\n const data = await res.json();\n return data.value ?? [];\n}\n\nasync function getAttachmentText(\n token: string,\n messageId: string,\n): Promise {\n const url =\n `https://graph.microsoft.com/v1.0/users/${MAILBOX}/messages/${messageId}/attachments`;\n const res = await fetch(url, {\n headers: { Authorization: `Bearer ${token}` },\n });\n const data = await res.json();\n const pdfAttachment = (data.value ?? []).find((a: any) =>\n a.name?.toLowerCase().endsWith(\".pdf\")\n );\n if (!pdfAttachment?.contentBytes) return null;\n\n // Extract text via a PDF-to-text endpoint. Val Town doesn't ship a native\n // PDF parser, so this uses a small npm import — pdf-parse works fine here.\n const pdfParse = (await import(\"npm:pdf-parse\")).default;\n const buffer = Uint8Array.from(\n atob(pdfAttachment.contentBytes),\n (c) => c.charCodeAt(0),\n );\n const parsed = await pdfParse(buffer);\n return parsed.text as string;\n}\n\nasync function markRead(token: string, messageId: string) {\n await fetch(\n `https://graph.microsoft.com/v1.0/users/${MAILBOX}/messages/${messageId}`,\n {\n method: \"PATCH\",\n headers: {\n Authorization: `Bearer ${token}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({ isRead: true }),\n },\n );\n}\n\nasync function getBrewwProducts() {\n const res = await fetch(BREWW_BASE + \"products/?page_size=200\", {\n headers: BREWW_HEADERS,\n });\n const data = await res.json();\n return data.results ?? data;\n}\n\n// Very rough line-item extraction: looks for \" Case \"\n// patterns per flavour keyword. This is deliberately conservative — if it\n// can't parse a line confidently, it should surface a review item rather\n// than guess.\nfunction extractLines(poText: string) {\n const lines: { flavour: string; quantity: number }[] = [];\n for (const { keyword, nameContains } of FLAVOUR_KEYWORDS) {\n const lineMatch = poText.match(\n new RegExp(\n `(\\\\d+(?:\\\\.\\\\d+)?)\\\\s*Case[\\\\s\\\\S]{0,40}${keyword.source}`,\n \"i\",\n ),\n );\n if (lineMatch) {\n lines.push({\n flavour: nameContains,\n quantity: Math.round(parseFloat(lineMatch[1])),\n });\n }\n }\n return lines;\n}\n\nasync function createOrder(\n customerId: number,\n priceBook: number,\n poNumber: string,\n orderLines: { product: number; quantity: number }[],\n) {\n const payload = {\n customer: customerId,\n price_book: priceBook,\n issue_date: new Date().toISOString().slice(0, 10),\n po_number: poNumber,\n order_status: 1, // draft first, promote after sanity check\n fulfillment_required: true,\n order_lines: orderLines,\n };\n const res = await fetch(BREWW_BASE + \"orders/\", {\n method: \"POST\",\n headers: BREWW_HEADERS,\n body: JSON.stringify(payload),\n });\n return res.json();\n}\n\nasync function acceptOrder(orderId: number) {\n await fetch(`${BREWW_BASE}orders/${orderId}/`, {\n method: \"PATCH\",\n headers: BREWW_HEADERS,\n body: JSON.stringify({ order_status: 3 }),\n });\n}\n\nasync function sendSummaryEmail(\n token: string,\n processed: ProcessedItem[],\n review: ReviewItem[],\n) {\n if (processed.length === 0 && review.length === 0) return; // nothing to report\n\n const rows = (arr: string[]) => arr.map((r) => `

${r}

`).join(\"\");\n const processedRows = rows(\n processed.map(\n (p) =>\n `${p.subject} — Order ${p.orderNumber}, £${\n p.total.toFixed(2)\n } — ` +\n `view in Breww`,\n ),\n );\n const reviewRows = rows(\n review.map((r) => `${r.subject} — needs manual review: ${r.reason}`),\n );\n\n const html = `\n

B2B order processing run — ${new Date().toISOString()}

\n ${\n processed.length\n ? `

Auto-accepted (${processed.length})

${processedRows}`\n : \"\"\n }\n ${\n review.length\n ? `

Needs manual review (${review.length})

${reviewRows}`\n : \"\"\n }\n `;\n\n await fetch(\n `https://graph.microsoft.com/v1.0/users/${NOTIFY_FROM}/sendMail`,\n {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${token}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n message: {\n subject:\n `B2B orders processed: ${processed.length} accepted, ${review.length} need review`,\n body: { contentType: \"HTML\", content: html },\n toRecipients: [{ emailAddress: { address: NOTIFY_TO } }],\n },\n saveToSentItems: true,\n }),\n },\n );\n}\n\nasync function processOrders() {\n const token = await getGraphToken();\n const processedIds: string[] =\n (await blob.getJSON(\"lifeblood_orders_processed\")) ?? [];\n // Learned map of sender email domain -> Breww customer ID, built up\n // automatically as orders are matched. Makes repeat senders instant and\n // resilient to their PO wording changing between orders.\n const domainCache: Record =\n (await blob.getJSON(\"lifeblood_customer_domain_cache\")) ?? {};\n const emails = await getUnreadOrderEmails(token);\n const allCustomers = await getAllBrewwCustomers();\n const customersById = new Map(allCustomers.map((c) => [c.id, c]));\n\n const processed: ProcessedItem[] = [];\n const review: ReviewItem[] = [];\n\n for (const email of emails) {\n if (processedIds.includes(email.id)) continue;\n\n const senderDomain =\n email.from?.emailAddress?.address?.split(\"@\")[1]?.toLowerCase() ?? \"\";\n if (IGNORE_SENDER_DOMAINS.includes(senderDomain)) continue;\n if (IGNORE_SUBJECT_PATTERNS.some((p) => p.test(email.subject))) continue;\n\n const poText = await getAttachmentText(token, email.id);\n if (!poText) {\n review.push({\n subject: email.subject,\n reason: \"No readable PDF attachment\",\n messageId: email.id,\n });\n continue;\n }\n\n // Fast path: we've matched this sender domain to a customer before.\n let account: BrewwCustomer | null = null;\n if (domainCache[senderDomain]) {\n account = customersById.get(domainCache[senderDomain]) ?? null;\n }\n // Otherwise, fuzzy-match against the live customer list. This is what\n // makes brand-new customers work with zero setup — no table to update.\n if (!account) {\n account = findCustomerInText(allCustomers, poText);\n if (account && senderDomain) {\n domainCache[senderDomain] = account.id; // learn it for next time\n }\n }\n\n if (!account) {\n review.push({\n subject: email.subject,\n reason:\n \"Could not confidently match a customer — either they're not in Breww yet, \" +\n \"or their name matched more than one record. Create/fix the customer record, \" +\n \"then re-forward or let the next run pick it up.\",\n messageId: email.id,\n });\n await markRead(token, email.id);\n processedIds.push(email.id);\n continue;\n }\n if (!account.price_book_in_use?.id) {\n review.push({\n subject: email.subject,\n reason:\n `Matched customer \"${account.name}\" but they have no price book set in Breww`,\n messageId: email.id,\n });\n await markRead(token, email.id);\n processedIds.push(email.id);\n continue;\n }\n\n const lines = extractLines(poText);\n if (lines.length === 0) {\n review.push({\n subject: email.subject,\n reason: \"Could not parse any order lines\",\n messageId: email.id,\n });\n await markRead(token, email.id);\n processedIds.push(email.id);\n continue;\n }\n\n const products = await getBrewwProducts();\n const orderLines: { product: number; quantity: number }[] = [];\n let allMatched = true;\n for (const line of lines) {\n const product = products.find((p: any) =>\n p.name?.toLowerCase().includes(line.flavour.toLowerCase()) &&\n p.name?.toLowerCase().includes(\"12 x 330ml\")\n );\n if (!product) {\n allMatched = false;\n break;\n }\n orderLines.push({ product: product.id, quantity: line.quantity });\n }\n\n if (!allMatched) {\n review.push({\n subject: email.subject,\n reason: \"One or more product lines could not be matched confidently\",\n messageId: email.id,\n });\n await markRead(token, email.id);\n processedIds.push(email.id);\n continue;\n }\n\n const poNumberMatch = poText.match(/Order number\\s*\\n?\\s*([\\w-]+)/i);\n const poNumber = poNumberMatch?.[1] ?? email.subject;\n\n const order = await createOrder(\n account.id,\n account.price_book_in_use!.id,\n poNumber,\n orderLines,\n );\n\n if (!order?.id) {\n review.push({\n subject: email.subject,\n reason: \"Breww order creation failed\",\n messageId: email.id,\n });\n await markRead(token, email.id);\n processedIds.push(email.id);\n continue;\n }\n\n // Sanity check: total should roughly match quantity * book price sum.\n // If Breww's returned value is 0 or wildly off, don't auto-accept.\n if (!order.value || order.value <= 0) {\n review.push({\n subject: email.subject,\n reason:\n `Order ${order.number} created but value looks wrong (£${order.value}) — left as Draft`,\n messageId: email.id,\n });\n } else {\n await acceptOrder(order.id);\n processed.push({\n subject: email.subject,\n orderNumber: order.number,\n orderId: order.id,\n total: order.value,\n breww_url: `https://app.breww.com/orders/${order.id}/`,\n });\n }\n\n await markRead(token, email.id);\n processedIds.push(email.id);\n }\n\n await blob.setJSON(\"lifeblood_orders_processed\", processedIds.slice(-500)); // keep log bounded\n await blob.setJSON(\"lifeblood_customer_domain_cache\", domainCache);\n await sendSummaryEmail(token, processed, review);\n\n return { processed: processed.length, review: review.length };\n}\n\n// HTTP val entry point. Val Town HTTP vals must return a Response — this is\n// what the earlier plain-object return was missing, causing the 400s in\n// the logs. Runs the same processing logic either way; call this val's URL\n// manually to trigger a run, or set up a Cron Trigger on it in Val Town's\n// val settings (Cron Triggers work on HTTP vals — no need to recreate this\n// as a separate val type) to run it automatically, e.g. every 15 minutes.\nexport default async function (req: Request): Promise {\n try {\n const result = await processOrders();\n return new Response(JSON.stringify(result), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (err) {\n console.error(err);\n return new Response(\n JSON.stringify({ error: String(err) }),\n { status: 500, headers: { \"Content-Type\": \"application/json\" } },\n );\n }\n}","createdAt",["D",1788473119523],"branchVersion","branchId","2c09e060-a096-466d-9443-db1e4e96781b","id","a6edd5b8-946d-4be2-beb9-47563fc9ec91","orders-inbox-watch",["D",1788469719673],"deletedAt","legacyEnvVars",false,"privacy","public","httpPrivacy","description","processing the incoming orders inbox","imageUrl","019d5060-1a72-70ea-92a9-e2c91a100d5a","pinnedFileId","pinPreview","pinMigrated","screenshotVersion","likeCount",0,"orgId","019d5060-1a72-70ea-92a9-e7b6c0748108","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_95":94,"_102":98},"org",{"_95":94,"_96":-5,"_97":98,"_18":55,"_99":100,"_101":48},"branch",{"_13":84,"_32":85,"_42":41,"_86":43,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":44,"_93":94},"isOwned",36,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","Gearymeister","handle","displayName","avatar","https://img.clerk.com/eyJ0eXBlIjoiZGVmYXVsdCIsImlpZCI6Imluc18yTm10cGhQUklwU0tqZHNiOHNnNGd2ZjJURFUiLCJyaWQiOiJ1c2VyXzNCb3l3RnlPc1h0RkMwd2w3S3F0aDU2TWtzRSJ9","tier","free","canRestrictVals","profileImageUrl","branchName","","adoptOrgId",{"_42":43,"_32":44,"_37":153,"_46":-5,"_47":48,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":-5,"_57":48,"_58":-5,"_59":-5,"_60":61,"_62":63,"_64":-5,"_65":-5,"_66":-5,"_67":-5,"_68":69,"_70":69,"_71":72,"_73":72,"_74":72,"_75":69,"_76":69,"_77":154,"_79":155,"_81":156,"_83":48},"tree",[148],"files",[148],"counts",{"_136":61,"_137":138,"_139":61,"_140":141,"_142":143},"contents",[125],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_42":126,"_32":127,"_30":128,"_129":-5,"_40":41,"_39":130,"_131":48,"_37":132,"_13":133,"_33":34,"_35":36,"_24":48,"_134":-5,"_27":135},"85fd174a-e5fc-461b-ac92-4f84553bb4e8","main.ts","16019e1c-a7de-11f1-a990-1607ee4eb77e","parentId",9,"latest",["D",1788471098891],5,"label",[127],"pulls","branches",1,"forks","envVars",{"_144":146,"_147":61},"connections",{"_144":61,"_145":61},"count","unfilledCount",2,"emptyCount",{"_42":126,"_32":127,"_30":128,"_129":-5,"_40":41,"_39":130,"_131":48,"_37":149,"_13":133,"_33":34,"_35":36,"_24":48,"_134":-5,"_150":151,"_27":152},["D",1788471098891],"children",[],[127],["D",1788469719673],{"_95":94,"_102":98},{"_95":94,"_96":-5,"_97":98,"_18":55,"_99":100,"_101":48},{"_13":84,"_32":85,"_42":41,"_86":43,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":44,"_93":94},"ctx",{"_77":-5,"_122":190,"_191":192,"_193":194,"_195":48,"_196":48,"_197":48,"_198":25,"_199":-5,"_200":-7,"_201":-7,"_202":61,"_203":48,"_204":48,"_205":-5,"_206":48,"_207":48,"_208":48,"_209":-5},"ENV",{"_161":162,"_163":164,"_165":85,"_166":167,"_168":169,"_170":171,"_172":173,"_174":175,"_176":177,"_178":179,"_180":181,"_182":183,"_184":185,"_186":187,"_188":189},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v13