[{"_1":2,"_260":-5,"_261":-5},"loaderData",{"_3":4,"_92":93,"_225":226,"_259":-5},"root",{"_5":6,"_31":32,"_61":62},"ctx",{"_7":8,"_19":-5,"_20":21,"_22":23,"_24":25,"_26":25,"_27":25,"_28":29,"_30":25},"auth",{"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5},"sessionClaims","sessionId","sessionStatus","userId","actor","orgId","orgRole","orgSlug","orgPermissions","factorVerificationAge","user","preferencesKeybindings","default","preferencesTheme","light","preferencesFixers",false,"preferencesCopilot","preferencesSelectionAi","notificationCount",0,"flagDenols","ENV",{"_33":34,"_35":36,"_37":38,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58,"_59":60},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","VAL_RUNTIME_NAME","prod","RENDER_GIT_COMMIT","a67dfb5cf923e20cce83a3e5fcaf363c7c69c9e6","RENDER_GIT_BRANCH","main","CLERK_PUBLISHABLE_KEY","pk_live_Y2xlcmsudmFsLnRvd24k","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","API_URL","https://api.val.town","clerkState",{"_63":64},"__internal_clerk_state",{"_65":66,"_67":42,"_68":69,"_70":69,"_71":25,"_72":69,"_73":69,"_74":69,"_75":69,"_76":69,"_77":69,"_78":69,"_79":69,"_80":81,"_90":25,"_91":25},"__clerk_ssr_state",{"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5},"__publishableKey","__proxyUrl","","__domain","__isSatellite","__signInUrl","__signUpUrl","__afterSignInUrl","__afterSignUpUrl","__signInForceRedirectUrl","__signUpForceRedirectUrl","__signInFallbackRedirectUrl","__signUpFallbackRedirectUrl","__clerk_debug",{"_82":25,"_83":69,"_84":85,"_86":69,"_87":42,"_88":25,"_89":69},"isSignedIn","proxyUrl","reason","session-token-and-uat-missing","message","publishableKey","isSatellite","domain","__telemetryDisabled","__telemetryDebug","routes/_app.x.$handle.$name",{"_94":95,"_96":97,"_98":-7,"_99":69,"_100":-7,"_101":102,"_147":148,"_197":198,"_199":200,"_206":207,"_220":-5,"_221":-5,"_222":-5,"_223":25,"_224":25},"handle","Shmully","name","Mullbot","branchName","path","version","project",{"_103":104,"_96":97,"_105":106,"_107":-5,"_108":25,"_109":110,"_111":-5,"_112":-5,"_12":113,"_114":-5,"_115":25,"_116":-5,"_117":29,"_14":118,"_119":120,"_121":120,"_122":123,"_124":123,"_125":123,"_126":120,"_127":120,"_19":128,"_131":132,"_134":135,"_146":25},"id","5e64a4a6-32c3-11f0-bd44-569c3dd06744","createdAt",["D",1747447513212],"deletedAt","legacyEnvVars","privacy","public","description","imageUrl","e036ffc0-26f1-11f0-a049-f3a9b7a94124","pinnedFileId","pinPreview","screenshotVersion","likeCount","d03bf8cd-f815-4c06-aa3c-6ba76ff72b74","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm",{"_94":95,"_129":130},"profileImageUrl","https://img.clerk.com/eyJ0eXBlIjoicHJveHkiLCJzcmMiOiJodHRwczovL2ltYWdlcy5jbGVyay5kZXYvb2F1dGhfZ2l0aHViL2ltZ18yd1dDZkVOdUdyaXpzek42bjJyRm5vR2xuZlAifQ","org",{"_94":95,"_133":130},"avatar","branch",{"_100":136,"_96":40,"_103":137,"_138":104,"_139":-5,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":97,"_145":95},12,"5e64f438-32c3-11f0-bd44-569c3dd06744","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","isOwned","tree",[149,171,180,189],{"_103":150,"_96":151,"_152":153,"_154":-5,"_155":137,"_156":157,"_158":159,"_105":160,"_100":161,"_162":163,"_164":165,"_166":25,"_167":-5,"_168":169,"_99":170},"e503735a-3455-11f0-922e-9e149126039e","generateFunFacts.tsx","fileId","cdeaf8b0-3454-11f0-87c2-9e149126039e","parentId","branchId","branchVersion",9,"latest",true,["D",1747620396750],2,"fileType","script","content","import { DateTime } from \"https://esm.sh/luxon@3.4.4\";\nimport { nanoid } from \"https://esm.sh/nanoid@5.0.5\";\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport OpenAI from \"npm:openai@4.26.0\";\n\nconst TABLE_NAME = `memories`;\nconst TAG_NAME = \"fun_fact\";\n\n/**\n * Retrieves previously generated fun facts from the memories database\n * @returns Array of previous fun facts\n */\nasync function getPreviousFunFacts() {\n try {\n const result = await sqlite.execute(\n `SELECT date(date) as date, text FROM ${TABLE_NAME}\n WHERE tags = ?\n ORDER BY date DESC\n LIMIT 50`,\n [TAG_NAME],\n );\n\n return result.rows || [];\n } catch (error) {\n console.error(\"Error retrieving previous fun facts:\", error);\n return [];\n }\n}\n\n/**\n * Deletes existing fun facts for the specified dates\n * @param dates Array of date strings in ISO format\n */\nasync function deleteExistingFunFacts(dates) {\n try {\n for (const date of dates) {\n await sqlite.execute(\n `DELETE FROM ${TABLE_NAME}\n WHERE date = ? AND tags = ?`,\n [date, TAG_NAME],\n );\n }\n } catch (error) {\n console.error(\"Error deleting existing fun facts:\", error);\n }\n}\n\n/**\n * Inserts a fun fact into the memories database\n * @param date Date for the fun fact in ISO format\n * @param factText The fun fact text\n */\nasync function insertFunFact(date, factText) {\n try {\n await sqlite.execute(\n `INSERT INTO ${TABLE_NAME} (id, date, text, createdBy, createdDate, tags)\n VALUES (?, ?, ?, ?, ?, ?)`,\n [\n nanoid(10),\n date,\n `fun fact: ${factText}`,\n \"fun_fact_generator\",\n Date.now(),\n TAG_NAME,\n ],\n );\n } catch (error) {\n console.error(`Error inserting fun fact for ${date}:`, error);\n }\n}\n\n/**\n * Generates fun facts for the next 7 days using OpenAI API\n * @param previousFacts Previous fun facts to avoid duplication\n * @returns Array of generated fun facts\n */\nasync function generateFunFacts(previousFacts) {\n try {\n // Get API key from environment\n const apiKey = Deno.env.get(\"OPENAI_API_KEY\");\n if (!apiKey) {\n console.error(\"OpenAI API key is not configured.\");\n return null;\n }\n\n // Initialize OpenAI client\n const openai = new OpenAI({ apiKey });\n\n // Format previous facts for the prompt\n const previousFactsText = previousFacts\n .map((fact) => `- ${fact.date}: ${fact.text}`)\n .join(\"\\n\");\n\n // Get today's date in US Eastern Time\n const today = DateTime.now().setZone(\"America/New_York\").startOf(\"day\");\n\n // Hana's birthday - adjust as needed\n const hanaBirthday = \"2025-03-26\";\n const currentDate = today.toFormat(\"yyyy-MM-dd\");\n\n // Format dates for the next 7 days\n const nextSevenDays = Array.from({ length: 7 }, (_, i) => {\n const date = today.plus({ days: i });\n return date.toFormat(\"yyyy-MM-dd\");\n });\n\n const message =\n `Generate 7 unique fun facts, one for each of the next 7 days. Each fact should be brief (1-2 sentences) and relate to one of these categories:\n\n1. Infant development appropriate for Miss Hana, who was born on ${hanaBirthday} (today is ${currentDate})\n2. Cute animals: capybaras, border collies, elephants, or penguins\n3. Plants: monsteras, orchids, ficus, or other common houseplants\n\nRequirements:\n- Each fact must be interesting, educational, and appropriate for formal communication\n- Keep each fact to 1-2 sentences maximum\n- Use different categories across the 7 days for variety\n- Ensure facts are scientifically accurate\n- Make infant development facts age-appropriate for Miss Hana based on her birthdate\n- Do not repeat any previous facts from this list:\n\n${previousFactsText}\n\nFORMAT YOUR RESPONSE AS STRUCTURED JSON INSIDE XML TAGS:\n\n[\n {\n \"date\": \"YYYY-MM-DD\",\n \"text\": \"The fun fact text here\",\n \"category\": \"infant\" | \"animal\" | \"plant\"\n },\n ... (repeat for all 7 days)\n]\n\n\nUse these dates for the 7 facts:\n${nextSevenDays.join(\"\\n\")}`;\n\n console.log({ message });\n\n // Call OpenAI API\n const response = await openai.chat.completions.create({\n model: \"gpt-4-turbo-preview\", // You can adjust the model as needed\n messages: [\n {\n role: \"system\",\n content: \"You are a helpful assistant that generates educational fun facts.\",\n },\n {\n role: \"user\",\n content: message,\n },\n ],\n max_tokens: 1000,\n });\n\n // Extract the response text\n const responseText = response.choices[0].message.content.trim();\n\n // Extract JSON between tags\n const factsMatch = responseText.match(/([\\s\\S]*?)<\\/facts>/);\n\n if (!factsMatch || factsMatch.length < 2) {\n console.error(\"Failed to parse facts from response:\", responseText);\n return [];\n }\n\n try {\n // Parse the JSON from the extracted content\n const factData = JSON.parse(factsMatch[1]);\n\n // Validate and format facts\n const facts = factData.map((fact) => ({\n date: fact.date,\n text: fact.text,\n category: fact.category,\n }));\n\n return facts;\n } catch (parseError) {\n console.error(\"Failed to parse facts JSON:\", parseError);\n console.log(\"Raw response:\", responseText);\n\n // Fallback to regex parsing if JSON parsing fails\n return parseFallbackFacts(responseText, nextSevenDays);\n }\n } catch (error) {\n console.error(\"Error generating fun facts:\", error);\n return [];\n }\n}\n\n/**\n * Fallback parser for when JSON parsing fails\n * @param responseText The raw response text from OpenAI\n * @param expectedDates Array of expected dates for facts\n * @returns Array of parsed facts\n */\nfunction parseFallbackFacts(responseText, expectedDates) {\n // Try to extract facts using regex\n const factPattern = /(\\d{4}-\\d{2}-\\d{2})[\"']?[,:]?\\s*[\"']?(.*?)[\"']?[,}]/gs;\n const facts = [];\n let match;\n\n while ((match = factPattern.exec(responseText)) !== null) {\n if (match.length >= 3) {\n facts.push({\n date: match[1],\n text: match[2].trim(),\n });\n }\n }\n\n // If we couldn't extract any facts, try another approach\n if (facts.length === 0) {\n // Look for quoted text that might be facts\n const lines = responseText.split(\"\\n\");\n let currentDate = null;\n\n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n\n // Check if this line contains a date\n const dateMatch = line.match(/(\\d{4}-\\d{2}-\\d{2})/);\n if (dateMatch) {\n currentDate = dateMatch[1];\n } else if (currentDate && line.length > 10) {\n // If we have a date and this is a non-empty line, treat it as a fact\n facts.push({\n date: currentDate,\n text: line.replace(/[\"']/g, \"\").trim(),\n });\n currentDate = null;\n }\n }\n }\n\n // As a last resort, assign facts to dates in order\n if (facts.length === 0 && expectedDates.length > 0) {\n // Extract any sentences that look like facts\n const sentences = responseText.match(/[^.!?]+[.!?]+/g) || [];\n\n for (let i = 0; i < Math.min(sentences.length, expectedDates.length); i++) {\n let factText = sentences[i].trim();\n\n // Clean up the fact text\n factText = factText.replace(/[\"']/g, \"\").trim();\n\n if (factText.length > 10) {\n facts.push({\n date: expectedDates[i],\n text: factText,\n });\n }\n }\n }\n\n return facts;\n}\n\n/**\n * Main function to generate and store fun facts for the next 7 days\n */\nexport async function generateAndStoreFunFacts() {\n try {\n // Get previous fun facts\n const previousFacts = await getPreviousFunFacts();\n\n // Generate new fun facts\n const newFacts = await generateFunFacts(previousFacts);\n\n if (!newFacts || newFacts.length === 0) {\n console.error(\"Failed to generate fun facts\");\n return \"Failed to generate fun facts\";\n }\n\n // Get dates for the next 7 days\n const today = DateTime.now().setZone(\"America/New_York\").startOf(\"day\");\n const nextSevenDays = Array.from({ length: 7 }, (_, i) => {\n return today.plus({ days: i }).toFormat(\"yyyy-MM-dd\");\n });\n\n // Delete existing fun facts for these dates\n await deleteExistingFunFacts(nextSevenDays);\n\n // Insert new fun facts\n for (const fact of newFacts) {\n await insertFunFact(fact.date, fact.text);\n }\n\n console.log(`Generated and stored ${newFacts.length} fun facts`);\n return `Generated and stored ${newFacts.length} fun facts`;\n } catch (error) {\n console.error(\"Error in generateAndStoreFunFacts:\", error);\n return \"Error generating fun facts\";\n }\n}\n\n/**\n * Cron job entry point - runs weekly to generate fun facts for the next 7 days\n * Intended to be used as a Val Town cron job\n */\nexport default async function() {\n console.log(\"Running fun facts generation cron job...\");\n return await generateAndStoreFunFacts();\n}\n\n// For testing with Deno directly\nif (import.meta.main) {\n await generateAndStoreFunFacts();\n}","deleted","label","children",[],[151],{"_103":172,"_96":173,"_152":174,"_154":-5,"_155":137,"_156":175,"_158":159,"_105":176,"_100":161,"_162":163,"_164":177,"_166":25,"_167":-5,"_168":178,"_99":179},"b5408cc6-3454-11f0-9c6f-9e149126039e","initializeMemoriesDB.tsx","58931304-3454-11f0-b8fc-9e149126039e",6,["D",1747619887122],"/**\n * Creates a SQLite database table called 'memories' with specified columns\n * @returns {Promise} A success message\n */\nexport async function memoryTableCreator() {\n // Import the better-sqlite3 library\n // This is available in Val Town's environment\n const Database = require(\"better-sqlite3\");\n\n // Create in-memory database for testing\n // For persistence, you'd use a file path instead\n const db = new Database(\":memory:\");\n\n try {\n // Create the memories table with the specified columns\n db.exec(`\n CREATE TABLE IF NOT EXISTS memories (\n id TEXT PRIMARY KEY,\n date TEXT,\n text TEXT,\n createdBy TEXT,\n createdDate INTEGER,\n tags TEXT\n );\n `);\n\n // Optional: Insert a test record to verify functionality\n const stmt = db.prepare(`\n INSERT INTO memories (id, date, text, createdBy, createdDate, tags)\n VALUES (?, ?, ?, ?, ?, ?)\n `);\n\n const testId = \"mem_\" + Date.now().toString();\n stmt.run(\n testId,\n new Date().toISOString().split(\"T\")[0], // Current date in YYYY-MM-DD format\n \"This is a test memory\",\n \"system\",\n Date.now(),\n \"test,setup\",\n );\n\n // Verify the record was inserted\n const row = db.prepare(\"SELECT * FROM memories WHERE id = ?\").get(testId);\n\n return {\n success: true,\n message: \"Memories table created successfully!\",\n testRecord: row,\n };\n } catch (error) {\n return {\n success: false,\n message: `Error creating memories table: ${error.message}`,\n };\n } finally {\n // Close the database connection\n db.close();\n }\n}\n\n// For persistent storage in Val Town, you might want to use:\n// - val.storage to store the database file path\n// - val.storage.put/get to save/load data if SQLite isn't preferred",[],[173],{"_103":181,"_96":182,"_152":183,"_154":-5,"_155":137,"_156":184,"_158":159,"_105":185,"_100":161,"_162":163,"_164":186,"_166":25,"_167":-5,"_168":187,"_99":188},"476e19a2-3454-11f0-bd3c-9e149126039e","migrateMemoriesDB.tsx","1d4f5c44-3454-11f0-b8fc-9e149126039e",3,["D",1747619702872],"// Script to migrate the memories table in SQLite\n// Run this script manually to add new columns to the memories table\n\nexport default async function migrateMemoriesDb() {\n try {\n // Import SQLite module\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n\n // First, backup the current table contents\n const backup = await sqlite.execute(`SELECT * FROM memories`);\n console.log(\"Backup of memories table (JSON format):\");\n console.log(JSON.stringify(backup.rows, null, 2));\n\n // Create a new table with the updated schema\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS memories_new (\n id TEXT,\n date TEXT,\n text TEXT,\n createdBy TEXT,\n createdDate INTEGER,\n tags TEXT\n )\n `);\n\n // Copy data from old table to new table\n await sqlite.execute(`\n INSERT INTO memories_new (date, text)\n SELECT date, text FROM memories\n `);\n\n // Drop the old table\n await sqlite.execute(`DROP TABLE memories`);\n\n // Rename the new table to the original name\n await sqlite.execute(`ALTER TABLE memories_new RENAME TO memories`);\n\n // Create an index on id for faster lookups\n await sqlite.execute(`\n CREATE INDEX IF NOT EXISTS idx_memories_id ON memories(id)\n `);\n\n return \"Memories table migrated successfully with new columns.\";\n } catch (error) {\n console.error(\"Error migrating memories table:\", error);\n throw error;\n }\n}\n\nmigrateMemoriesDb();",[],[182],{"_103":190,"_96":191,"_152":192,"_154":-5,"_155":137,"_156":136,"_158":159,"_105":193,"_100":161,"_162":163,"_164":194,"_166":25,"_167":-5,"_168":195,"_99":196},"0d644dec-3456-11f0-8a4f-9e149126039e","viewMemories.tsx","eb887356-3455-11f0-a604-9e149126039e",["D",1747620464494],"/**\n * View the contents of the memories table\n * @returns {Promise} Table contents\n */\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\n\nexport async function viewMemoriesTable() {\n try {\n // Query all data from the memories table\n const result = await sqlite.execute(\n `SELECT * FROM memories ORDER BY date DESC LIMIT 100`,\n );\n\n return {\n success: true,\n count: result.rows?.length || 0,\n data: result.rows || [],\n };\n } catch (error) {\n console.error(\"Error viewing memories table:\", error);\n return {\n success: false,\n error: error.message,\n };\n }\n}\n\n// Call the function when the Val is run directly\nexport default async function() {\n return await viewMemoriesTable();\n}",[],[191],"files",[149,171,180,189],"counts",{"_201":29,"_202":203,"_204":29,"_205":29},"pulls","branches",1,"forks","envVars","contents",[208,211,214,217],{"_103":150,"_96":151,"_152":153,"_154":-5,"_155":137,"_156":157,"_158":159,"_105":209,"_100":161,"_162":163,"_164":165,"_166":25,"_167":-5,"_99":210},["D",1747620396750],[151],{"_103":172,"_96":173,"_152":174,"_154":-5,"_155":137,"_156":175,"_158":159,"_105":212,"_100":161,"_162":163,"_164":177,"_166":25,"_167":-5,"_99":213},["D",1747619887122],[173],{"_103":181,"_96":182,"_152":183,"_154":-5,"_155":137,"_156":184,"_158":159,"_105":215,"_100":161,"_162":163,"_164":186,"_166":25,"_167":-5,"_99":216},["D",1747619702872],[182],{"_103":190,"_96":191,"_152":192,"_154":-5,"_155":137,"_156":136,"_158":159,"_105":218,"_100":161,"_162":163,"_164":194,"_166":25,"_167":-5,"_99":219},["D",1747620464494],[191],"file","upstreamProject","upstreamBranch","emptyEnvVars","isNew","routes/_app.x.$handle.$name._index",{"_94":95,"_96":97,"_98":-7,"_100":-7,"_101":227,"_206":232,"_241":-7,"_242":-5,"_243":-5,"_197":244,"_257":258},{"_103":104,"_96":97,"_105":228,"_107":-5,"_108":25,"_109":110,"_111":-5,"_112":-5,"_12":113,"_114":-5,"_115":25,"_116":-5,"_117":29,"_14":118,"_119":120,"_121":120,"_122":123,"_124":123,"_125":123,"_126":120,"_127":120,"_19":229,"_131":230,"_134":231,"_146":25},["D",1747447513212],{"_94":95,"_129":130},{"_94":95,"_133":130},{"_100":136,"_96":40,"_103":137,"_138":104,"_139":-5,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":97,"_145":95},[233,235,237,239],{"_103":150,"_96":151,"_152":153,"_154":-5,"_155":137,"_156":157,"_158":159,"_105":209,"_100":161,"_162":163,"_164":165,"_166":25,"_167":-5,"_99":234},[151],{"_103":172,"_96":173,"_152":174,"_154":-5,"_155":137,"_156":175,"_158":159,"_105":212,"_100":161,"_162":163,"_164":177,"_166":25,"_167":-5,"_99":236},[173],{"_103":181,"_96":182,"_152":183,"_154":-5,"_155":137,"_156":184,"_158":159,"_105":215,"_100":161,"_162":163,"_164":186,"_166":25,"_167":-5,"_99":238},[182],{"_103":190,"_96":191,"_152":192,"_154":-5,"_155":137,"_156":136,"_158":159,"_105":218,"_100":161,"_162":163,"_164":194,"_166":25,"_167":-5,"_99":240},[191],"readme","upstream","pull",[245,248,251,254],{"_103":150,"_96":151,"_152":153,"_154":-5,"_155":137,"_156":157,"_158":159,"_105":160,"_100":161,"_162":163,"_164":165,"_166":25,"_167":-5,"_168":246,"_99":247},[],[151],{"_103":172,"_96":173,"_152":174,"_154":-5,"_155":137,"_156":175,"_158":159,"_105":176,"_100":161,"_162":163,"_164":177,"_166":25,"_167":-5,"_168":249,"_99":250},[],[173],{"_103":181,"_96":182,"_152":183,"_154":-5,"_155":137,"_156":184,"_158":159,"_105":185,"_100":161,"_162":163,"_164":186,"_166":25,"_167":-5,"_168":252,"_99":253},[],[182],{"_103":190,"_96":191,"_152":192,"_154":-5,"_155":137,"_156":136,"_158":159,"_105":193,"_100":161,"_162":163,"_164":194,"_166":25,"_167":-5,"_168":255,"_99":256},[],[191],"previews",[],"routes/_app","actionData","errors"]