[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_164":165,"_166":167},"routes/_app.x.$handle.$name",{"_95":94,"_32":45,"_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":25,"_118":119,"_120":58,"_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",{"_43":44,"_32":45,"_38":46,"_47":-5,"_48":25,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":31,"_57":58,"_59":-5,"_60":-5,"_61":62,"_63":64,"_65":-5,"_66":-5,"_67":-5,"_68":-5,"_69":70,"_71":70,"_72":73,"_74":73,"_75":73,"_76":70,"_77":70,"_78":79,"_80":81,"_82":83,"_84":25},"version",3,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":25,"_27":28,"_29":28},"file",{"_30":31,"_32":28,"_33":34,"_35":37,"_38":39,"_40":14,"_41":42,"_24":25},"previous",{"_30":31,"_32":28,"_33":34,"_35":36},"deleted",false,"deletedHere","path","api.ts","latestPath","fileId","132ce530-4969-11f1-9088-42b51c65c3df","name","fileType","http","content","import Anthropic from \"npm:@anthropic-ai/sdk@0.39.0\";\n\n// ── Channel → SAP code mappings ──────────────────────────────────────\nconst CHANNEL_MAP: Record = {\n TR_ECOM: { uretim_yeri: \"8004\", depo_yeri: \"1450\", depo_yeri_2: \"1450\" },\n TR_PERAKENDE: { uretim_yeri: \"8000\", depo_yeri: \"9999\", depo_yeri_2: \"1020\" },\n TR_TOPTAN: { uretim_yeri: \"8000\", depo_yeri: \"9999\", depo_yeri_2: \"1010\" },\n};\n\n// ── Standard size distribution ───────────────────────────────────────\nconst STANDARD_SIZES: { size: string; pct: number }[] = [\n { size: \"XS\", pct: 3.6 },\n { size: \"S\", pct: 8.8 },\n { size: \"M\", pct: 26.4 },\n { size: \"L\", pct: 30.4 },\n { size: \"XL\", pct: 18.4 },\n { size: \"XXL\", pct: 7.8 },\n { size: \"XXXL\", pct: 4.6 },\n];\n\n// ── Distribute total across standard sizes, rounding to integers ─────\nfunction distributeStandard(total: number): { size: string; qty: number }[] {\n const raw = STANDARD_SIZES.map(s => ({ size: s.size, exact: total * s.pct / 100 }));\n const floored = raw.map(r => ({ size: r.size, qty: Math.floor(r.exact), remainder: r.exact - Math.floor(r.exact) }));\n let assigned = floored.reduce((sum, r) => sum + r.qty, 0);\n let diff = total - assigned;\n // assign remaining units to sizes with largest remainders\n const sorted = [...floored].sort((a, b) => b.remainder - a.remainder);\n for (let i = 0; i < diff && i < sorted.length; i++) {\n sorted[i].qty += 1;\n }\n return floored.map(r => ({ size: r.size, qty: r.qty }));\n}\n\n// ── Claude extraction prompt ─────────────────────────────────────────\nconst SYSTEM_PROMPT = `You are an order-parsing assistant for Mavi Jeans. You receive Turkish-language emails about orders and extract structured data.\n\nReturn ONLY valid JSON (no markdown, no explanation) with this exact shape:\n{\n \"type\": \"new_order\" | \"quantity_revision\" | \"price_revision\",\n \"model_name\": string | null,\n \"skus\": [{ \"description\": string, \"color_code\": string }],\n \"channels\": [{ \"name\": string, \"channel_code\": \"TR_ECOM\" | \"TR_PERAKENDE\" | \"TR_TOPTAN\" }],\n \"orders\": [{ \"color_code\": string, \"channel_code\": string, \"quantity\": number }],\n \"size_distribution\": \"standart\" | \"custom\",\n \"custom_sizes\": null | [{ \"size\": string, \"quantity\": number }],\n \"season\": string | null,\n \"order_type\": string | null,\n \"delivery_date\": string | null,\n \"psf\": number | null,\n \"currency\": string | null,\n \"confidence\": number,\n \"extraction_notes\": [string]\n}\n\nRules:\n- \"Ecom\" or \"e-ticaret\" → channel_code \"TR_ECOM\"\n- \"Perakende\" → channel_code \"TR_PERAKENDE\"\n- \"Toptan\" → channel_code \"TR_TOPTAN\"\n- If the email mentions \"standart beden dağılımı\" or just \"standart\", set size_distribution to \"standart\"\n- Parse Turkish number formats: \"4.000\" = 4000, \"2.099,99\" = 2099.99\n- Date format: convert to DD.MM.YYYY. \"27 Haziran\" in context of a business email likely means 2026.\n- For SKU color codes, extract from parentheses like \"(85370)\" → color_code \"85370\"\n- If model code prefix isn't explicit, leave it as the description (e.g. \"Keten\")\n- confidence is 0-1 reflecting how certain you are about the overall extraction\n- extraction_notes should list every inference you made`;\n\n// ── Main handler ─────────────────────────────────────────────────────\nexport default async function handler(req: Request): Promise {\n // CORS headers for the frontend\n const corsHeaders = {\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type\",\n };\n\n if (req.method === \"OPTIONS\") {\n return new Response(null, { status: 204, headers: corsHeaders });\n }\n\n if (req.method !== \"POST\") {\n return new Response(JSON.stringify({ error: \"POST only\" }), {\n status: 405,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n }\n\n try {\n const { subject, from, body } = await req.json();\n if (!body) {\n return new Response(JSON.stringify({ error: \"Missing 'body' field\" }), {\n status: 400,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n }\n\n // ── Step 1: Call Claude to parse the email ──\n const client = new Anthropic();\n const emailText = [\n subject ? `Konu: ${subject}` : \"\",\n from ? `Gönderen: ${from}` : \"\",\n \"\",\n body,\n ].filter(Boolean).join(\"\\n\");\n\n const msg = await client.messages.create({\n model: \"claude-sonnet-4-20250514\",\n max_tokens: 2048,\n system: SYSTEM_PROMPT,\n messages: [{ role: \"user\", content: emailText }],\n });\n\n const raw = (msg.content[0] as any).text;\n let parsed: any;\n try {\n parsed = JSON.parse(raw);\n } catch {\n // Try extracting JSON from possible markdown wrapping\n const match = raw.match(/```(?:json)?\\s*([\\s\\S]*?)```/);\n if (match) parsed = JSON.parse(match[1]);\n else throw new Error(\"Claude did not return valid JSON: \" + raw.slice(0, 200));\n }\n\n // ── Step 2: Build SAP rows deterministically ──\n const rows: any[] = [];\n const allNotes: string[] = [...(parsed.extraction_notes || [])];\n\n for (const order of parsed.orders) {\n const channelInfo = CHANNEL_MAP[order.channel_code];\n if (!channelInfo) {\n allNotes.push(`Unknown channel code: ${order.channel_code}`);\n continue;\n }\n\n // Find the SKU info for this color\n const skuInfo = parsed.skus.find((s: any) => s.color_code === order.color_code);\n const skuPrefix = parsed.model_name || skuInfo?.description || \"UNKNOWN\";\n const skuFull = `${skuPrefix}-${order.color_code}`;\n\n // Size distribution\n let sizeRows: { size: string; qty: number }[];\n let qtyConfidence: string;\n\n if (parsed.size_distribution === \"standart\") {\n sizeRows = distributeStandard(order.quantity);\n qtyConfidence = \"medium\";\n // Only add this note once\n if (!allNotes.some((n: string) => n.includes(\"standard size curve\"))) {\n allNotes.push(`'standart beden dağılımı' → applied standard size curve to ${order.quantity} units`);\n }\n } else if (parsed.custom_sizes) {\n sizeRows = parsed.custom_sizes.map((cs: any) => ({ size: cs.size, qty: cs.quantity }));\n qtyConfidence = \"high\";\n } else {\n // Fallback: put everything in one row with no size\n sizeRows = [{ size: \"ALL\", qty: order.quantity }];\n qtyConfidence = \"low\";\n allNotes.push(`No size distribution specified for ${skuFull}, channel ${order.channel_code}`);\n }\n\n for (const sr of sizeRows) {\n rows.push({\n sku: skuFull,\n ana_beden: sr.size,\n miktar: sr.qty,\n kanal: order.channel_code,\n uretim_yeri: channelInfo.uretim_yeri,\n depo_yeri: channelInfo.depo_yeri,\n depo_yeri_2: channelInfo.depo_yeri_2,\n teslimat_tarihi: parsed.delivery_date || \"\",\n etiket_psf1: parsed.psf || 0,\n para_birimi: parsed.currency || \"TRY\",\n evrak_sezonu: parsed.season || \"\",\n evrak_turu: parsed.order_type || \"\",\n confidence: {\n sku: skuInfo ? \"high\" : \"low\",\n miktar: qtyConfidence,\n uretim_yeri: \"derived\",\n depo_yeri: \"derived\",\n },\n });\n }\n }\n\n // ── Step 3: Assemble response ──\n const result = {\n parsed: {\n type: parsed.type,\n model_name: parsed.model_name,\n skus: parsed.skus.map((s: any) => `${parsed.model_name || s.description}-${s.color_code}`),\n channels: parsed.orders.map((o: any) => o.channel_code).filter((v: string, i: number, a: string[]) => a.indexOf(v) === i),\n season: parsed.season,\n order_type: parsed.order_type,\n delivery_date: parsed.delivery_date,\n psf: parsed.psf,\n currency: parsed.currency,\n confidence: parsed.confidence,\n },\n rows,\n source: {\n subject: subject || \"\",\n from: from || \"\",\n body: body,\n extraction_notes: allNotes,\n },\n };\n\n return new Response(JSON.stringify(result, null, 2), {\n status: 200,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n\n } catch (err: any) {\n return new Response(JSON.stringify({ error: err.message, stack: err.stack }), {\n status: 500,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n }\n}\n","import Anthropic from \"npm:@anthropic-ai/sdk@0.39.0\";\n\n// ── Channel → SAP code mappings ──────────────────────────────────────\nconst CHANNEL_MAP: Record = {\n TR_ECOM: { uretim_yeri: \"8004\", depo_yeri: \"1450\", depo_yeri_2: \"1450\" },\n TR_PERAKENDE: { uretim_yeri: \"8000\", depo_yeri: \"9999\", depo_yeri_2: \"1020\" },\n TR_TOPTAN: { uretim_yeri: \"8000\", depo_yeri: \"9999\", depo_yeri_2: \"1010\" },\n};\n\n// ── Standard size distribution ───────────────────────────────────────\nconst STANDARD_SIZES: { size: string; pct: number }[] = [\n { size: \"XS\", pct: 3.6 },\n { size: \"S\", pct: 8.8 },\n { size: \"M\", pct: 26.4 },\n { size: \"L\", pct: 30.4 },\n { size: \"XL\", pct: 18.4 },\n { size: \"XXL\", pct: 7.8 },\n { size: \"XXXL\", pct: 4.6 },\n];\n\n// ── Distribute total across standard sizes, rounding to integers ─────\nfunction distributeStandard(total: number): { size: string; qty: number }[] {\n const raw = STANDARD_SIZES.map(s => ({ size: s.size, exact: total * s.pct / 100 }));\n const floored = raw.map(r => ({ size: r.size, qty: Math.floor(r.exact), remainder: r.exact - Math.floor(r.exact) }));\n let assigned = floored.reduce((sum, r) => sum + r.qty, 0);\n let diff = total - assigned;\n // assign remaining units to sizes with largest remainders\n const sorted = [...floored].sort((a, b) => b.remainder - a.remainder);\n for (let i = 0; i < diff && i < sorted.length; i++) {\n sorted[i].qty += 1;\n }\n return floored.map(r => ({ size: r.size, qty: r.qty }));\n}\n\n// ── Claude extraction prompt ─────────────────────────────────────────\nconst SYSTEM_PROMPT = `You are an order-parsing assistant for Mavi Jeans. You receive Turkish-language emails about orders and extract structured data.\n\nReturn ONLY valid JSON (no markdown, no explanation) with this exact shape:\n{\n \"type\": \"new_order\" | \"quantity_revision\" | \"price_revision\",\n \"model_name\": string | null,\n \"skus\": [{ \"description\": string, \"color_code\": string }],\n \"channels\": [{ \"name\": string, \"channel_code\": \"TR_ECOM\" | \"TR_PERAKENDE\" | \"TR_TOPTAN\" }],\n \"orders\": [{ \"color_code\": string, \"channel_code\": string, \"quantity\": number }],\n \"size_distribution\": \"standart\" | \"custom\",\n \"custom_sizes\": null | [{ \"size\": string, \"quantity\": number }],\n \"season\": string | null,\n \"order_type\": string | null,\n \"delivery_date\": string | null,\n \"psf\": number | null,\n \"currency\": string | null,\n \"confidence\": number,\n \"extraction_notes\": [string]\n}\n\nRules:\n- \"Ecom\" or \"e-ticaret\" → channel_code \"TR_ECOM\"\n- \"Perakende\" → channel_code \"TR_PERAKENDE\"\n- \"Toptan\" → channel_code \"TR_TOPTAN\"\n- If the email mentions \"standart beden dağılımı\" or just \"standart\", set size_distribution to \"standart\"\n- Parse Turkish number formats: \"4.000\" = 4000, \"2.099,99\" = 2099.99\n- Date format: convert to DD.MM.YYYY. \"27 Haziran\" in context of a business email likely means 2026.\n- For SKU color codes, extract from parentheses like \"(85370)\" → color_code \"85370\"\n- If model code prefix isn't explicit, leave it as the description (e.g. \"Keten\")\n- confidence is 0-1 reflecting how certain you are about the overall extraction\n- extraction_notes should list every inference you made`;\n\n// ── Main handler ─────────────────────────────────────────────────────\nexport default async function handler(req: Request): Promise {\n // CORS headers for the frontend\n const corsHeaders = {\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type\",\n };\n\n if (req.method === \"OPTIONS\") {\n return new Response(null, { status: 204, headers: corsHeaders });\n }\n\n if (req.method !== \"POST\") {\n return new Response(JSON.stringify({ error: \"POST only\" }), {\n status: 405,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n }\n\n try {\n // Check for API key\n const apiKey = Deno.env.get(\"ANTHROPIC_API_KEY\");\n if (!apiKey) {\n return new Response(JSON.stringify({\n error: \"ANTHROPIC_API_KEY not set. Add it in Val Town project settings → Environment Variables.\",\n }), {\n status: 500,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n }\n\n const { subject, from, body } = await req.json();\n if (!body) {\n return new Response(JSON.stringify({ error: \"Missing 'body' field\" }), {\n status: 400,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n }\n\n // ── Step 1: Call Claude to parse the email ──\n const client = new Anthropic({ apiKey });\n const emailText = [\n subject ? `Konu: ${subject}` : \"\",\n from ? `Gönderen: ${from}` : \"\",\n \"\",\n body,\n ].filter(Boolean).join(\"\\n\");\n\n const msg = await client.messages.create({\n model: \"claude-sonnet-4-20250514\",\n max_tokens: 2048,\n system: SYSTEM_PROMPT,\n messages: [{ role: \"user\", content: emailText }],\n });\n\n const raw = (msg.content[0] as any).text;\n let parsed: any;\n try {\n parsed = JSON.parse(raw);\n } catch {\n // Try extracting JSON from possible markdown wrapping\n const match = raw.match(/```(?:json)?\\s*([\\s\\S]*?)```/);\n if (match) parsed = JSON.parse(match[1]);\n else throw new Error(\"Claude did not return valid JSON: \" + raw.slice(0, 200));\n }\n\n // ── Step 2: Build SAP rows deterministically ──\n const rows: any[] = [];\n const allNotes: string[] = [...(parsed.extraction_notes || [])];\n\n for (const order of parsed.orders) {\n const channelInfo = CHANNEL_MAP[order.channel_code];\n if (!channelInfo) {\n allNotes.push(`Unknown channel code: ${order.channel_code}`);\n continue;\n }\n\n // Find the SKU info for this color\n const skuInfo = parsed.skus.find((s: any) => s.color_code === order.color_code);\n const skuPrefix = parsed.model_name || skuInfo?.description || \"UNKNOWN\";\n const skuFull = `${skuPrefix}-${order.color_code}`;\n\n // Size distribution\n let sizeRows: { size: string; qty: number }[];\n let qtyConfidence: string;\n\n if (parsed.size_distribution === \"standart\") {\n sizeRows = distributeStandard(order.quantity);\n qtyConfidence = \"medium\";\n // Only add this note once\n if (!allNotes.some((n: string) => n.includes(\"standard size curve\"))) {\n allNotes.push(`'standart beden dağılımı' → applied standard size curve to ${order.quantity} units`);\n }\n } else if (parsed.custom_sizes) {\n sizeRows = parsed.custom_sizes.map((cs: any) => ({ size: cs.size, qty: cs.quantity }));\n qtyConfidence = \"high\";\n } else {\n // Fallback: put everything in one row with no size\n sizeRows = [{ size: \"ALL\", qty: order.quantity }];\n qtyConfidence = \"low\";\n allNotes.push(`No size distribution specified for ${skuFull}, channel ${order.channel_code}`);\n }\n\n for (const sr of sizeRows) {\n rows.push({\n sku: skuFull,\n ana_beden: sr.size,\n miktar: sr.qty,\n kanal: order.channel_code,\n uretim_yeri: channelInfo.uretim_yeri,\n depo_yeri: channelInfo.depo_yeri,\n depo_yeri_2: channelInfo.depo_yeri_2,\n teslimat_tarihi: parsed.delivery_date || \"\",\n etiket_psf1: parsed.psf || 0,\n para_birimi: parsed.currency || \"TRY\",\n evrak_sezonu: parsed.season || \"\",\n evrak_turu: parsed.order_type || \"\",\n confidence: {\n sku: skuInfo ? \"high\" : \"low\",\n miktar: qtyConfidence,\n uretim_yeri: \"derived\",\n depo_yeri: \"derived\",\n },\n });\n }\n }\n\n // ── Step 3: Assemble response ──\n const result = {\n parsed: {\n type: parsed.type,\n model_name: parsed.model_name,\n skus: parsed.skus.map((s: any) => `${parsed.model_name || s.description}-${s.color_code}`),\n channels: parsed.orders.map((o: any) => o.channel_code).filter((v: string, i: number, a: string[]) => a.indexOf(v) === i),\n season: parsed.season,\n order_type: parsed.order_type,\n delivery_date: parsed.delivery_date,\n psf: parsed.psf,\n currency: parsed.currency,\n confidence: parsed.confidence,\n },\n rows,\n source: {\n subject: subject || \"\",\n from: from || \"\",\n body: body,\n extraction_notes: allNotes,\n },\n };\n\n return new Response(JSON.stringify(result, null, 2), {\n status: 200,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n\n } catch (err: any) {\n return new Response(JSON.stringify({ error: err.message, stack: err.stack }), {\n status: 500,\n headers: { ...corsHeaders, \"Content-Type\": \"application/json\" },\n });\n }\n}\n","createdAt",["D",1778085219899],"branchVersion","branchId","f89aac20-4968-11f1-9d3f-42b51c65c3df","id","f899fa1e-4968-11f1-9d3f-42b51c65c3df","mavi-order-parser",["D",1778085062145],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Parse Turkish order emails into SAP-format data for Mavi","imageUrl","019a7db0-4b0d-7085-b46e-d1d1301524a0","pinnedFileId","pinPreview",true,"pinMigrated","screenshotVersion","likeCount",0,"orgId","019a7db0-4b0d-7085-b46e-d4bc87bae199","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":25},"branch",{"_13":14,"_32":85,"_43":42,"_86":44,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":45,"_93":94},"isOwned","main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","nazli","handle","displayName","avatar","https://img.clerk.com/eyJ0eXBlIjoiZGVmYXVsdCIsImlpZCI6Imluc18yTm10cGhQUklwU0tqZHNiOHNnNGd2ZjJURFUiLCJyaWQiOiJ1c2VyXzM1UWJZY2cxNk9TS05CZE5Sekl3SGhhMWdCdyJ9","tier","free","canRestrictVals","profileImageUrl","branchName","","adoptOrgId",{"_43":44,"_32":45,"_38":160,"_47":-5,"_48":25,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":31,"_57":58,"_59":-5,"_60":-5,"_61":62,"_63":64,"_65":-5,"_66":-5,"_67":-5,"_68":-5,"_69":70,"_71":70,"_72":73,"_74":73,"_75":73,"_76":70,"_77":70,"_78":161,"_80":162,"_82":163,"_84":25},"tree",[151,152],"files",[151,152],"counts",{"_141":62,"_142":139,"_143":62,"_144":145,"_146":147},"contents",[125,126],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_43":137,"_32":28,"_30":31,"_130":-5,"_41":42,"_40":14,"_132":58,"_38":138,"_13":139,"_33":34,"_35":37,"_24":25,"_135":-5,"_27":140},{"_43":127,"_32":128,"_30":129,"_130":-5,"_41":42,"_40":131,"_132":58,"_38":133,"_13":62,"_33":34,"_35":134,"_24":25,"_135":-5,"_27":136},"31bcb1a6-4969-11f1-ae4f-42b51c65c3df","frontend.ts","31bcb25a-4969-11f1-ae4f-42b51c65c3df","parentId",2,"latest",["D",1778085157995],"export default async function handler(req: Request): Promise {\n const API_URL = \"https://nazli--132ce530496911f1908842b51c65c3df.web.val.run\";\n\n const html = `\n\n\n\n\nMavi Jeans - Order Email Parser (Demo)\n\n\n\n

Mavi Jeans Order Parser

\n Demo\n

\n\n

\n Konu (Subject)\n \n

\n Gönderen (From)\n \n

\n Email İçeriği (Body)\n \n

\n \n \n

\n\n

Parsed Summary

\n\n

\n \n \n \n

\n\n

Extraction Notes

\n\n Show raw JSON\n

\n\n\n\n`;\n\n return new Response(html, {\n headers: { \"Content-Type\": \"text/html; charset=utf-8\" },\n });\n}\n","label",[128],"56a4cc9c-4969-11f1-8f7e-42b51c65c3df",["D",1778085219899],1,[28],"pulls","branches","forks","envVars",{"_148":139,"_150":62},"connections",{"_148":62,"_149":62},"count","unfilledCount","emptyCount",{"_43":137,"_32":28,"_30":31,"_130":-5,"_41":42,"_40":14,"_132":58,"_38":157,"_13":139,"_33":34,"_35":37,"_24":25,"_135":-5,"_154":158,"_27":159},{"_43":127,"_32":128,"_30":129,"_130":-5,"_41":42,"_40":131,"_132":58,"_38":153,"_13":62,"_33":34,"_35":134,"_24":25,"_135":-5,"_154":155,"_27":156},["D",1778085157995],"children",[],[128],["D",1778085219899],[],[28],["D",1778085062145],{"_95":94,"_102":98},{"_95":94,"_96":-5,"_97":98,"_18":55,"_99":100,"_101":25},{"_13":14,"_32":85,"_43":42,"_86":44,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":45,"_93":94},"ctx",{"_78":-5,"_122":197,"_198":199,"_200":201,"_202":25,"_203":25,"_204":25,"_205":58,"_206":-5,"_207":-7,"_208":-7,"_209":62,"_210":25,"_211":25,"_212":-5,"_213":25,"_214":25,"_215":25,"_216":-5},"ENV",{"_168":169,"_170":171,"_172":85,"_173":174,"_175":176,"_177":178,"_179":180,"_181":182,"_183":184,"_185":186,"_187":188,"_189":190,"_191":192,"_193":194,"_195":196},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","71c1b20804b3232a7e513be260cfffc1932a9e97","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 · v3