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\n To one day improve my little word games, I \"made\"{\" \"}\n an app{\" \"}\n to let me rate whether words in the Wordnik word game list are \"real words\" or not. This page let's me track my\n progress as I judge. Both the Judge Words app and this dashboard were built leaning quite heavily on Val Town's\n Townie AI interface. If you're in the mood for a very simple word game, check out{\" \"}\n Loopy Letters{\" \"}- Alex.\n

\n );\n}\n\nfunction Dashboard() {\n const [stats, setStats] = useState([]);\n\n useEffect(() => {\n fetch(\"/stats\")\n .then(response => response.json())\n .then(setStats);\n }, []);\n\n const grandTotal = stats.length > 0 ? stats[0] : null;\n\n return (\n

Word Judgment Dashboard

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n {grandTotal && (\n \n \n \n \n \n \n \n \n \n )}\n {stats.slice(1).map(stat => (\n \n \n \n \n \n \n \n \n \n ))}\n \n

Word Length	Total Words	Judged Words	% Judged	Pie Chart	Avg Rating	Rating Distribution
Grand Total	{grandTotal.totalWords}	{grandTotal.judgedWords}	{(grandTotal.percentJudged * 100).toFixed(2)}%	\n \n	{grandTotal.avgRating.toFixed(2)}	\n \n
{stat.wordLength}	{stat.totalWords}	{stat.judgedWords}	{(stat.percentJudged * 100).toFixed(2)}%	\n \n	{stat.avgRating.toFixed(2)}	\n \n

\n \n View Source\n \n

\n );\n}\n\nfunction client() {\n createRoot(document.getElementById(\"root\")).render();\n}\nif (typeof document !== \"undefined\") { client(); }\n\nexport default async function server(request: Request): Promise {\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n\n // Handle stats request\n if (new URL(request.url).pathname === \"/stats\") {\n const stats = await sqlite.execute(`\n WITH WordStats AS (\n SELECT \n length(word) as wordLength,\n COUNT(*) as totalWords,\n COUNT(judgment) as judgedWords,\n AVG(judgment) as avgRating,\n json_object(\n '0', COUNT(CASE WHEN judgment = 0 THEN 1 END),\n '1', COUNT(CASE WHEN judgment = 1 THEN 1 END),\n '2', COUNT(CASE WHEN judgment = 2 THEN 1 END),\n '3', COUNT(CASE WHEN judgment = 3 THEN 1 END),\n '4', COUNT(CASE WHEN judgment = 4 THEN 1 END),\n '5', COUNT(CASE WHEN judgment = 5 THEN 1 END)\n ) as distribution\n FROM judgments\n GROUP BY length(word)\n\n UNION ALL\n\n SELECT \n 'total' as wordLength,\n COUNT(*) as totalWords,\n COUNT(judgment) as judgedWords,\n AVG(CASE WHEN judgment > 0 THEN judgment END) as avgRating,\n json_object(\n '0', COUNT(CASE WHEN judgment = 0 THEN 1 END),\n '1', COUNT(CASE WHEN judgment = 1 THEN 1 END),\n '2', COUNT(CASE WHEN judgment = 2 THEN 1 END),\n '3', COUNT(CASE WHEN judgment = 3 THEN 1 END),\n '4', COUNT(CASE WHEN judgment = 4 THEN 1 END),\n '5', COUNT(CASE WHEN judgment = 5 THEN 1 END)\n ) as distribution\n FROM judgments\n )\n SELECT \n wordLength, \n totalWords, \n judgedWords, \n CAST(judgedWords AS FLOAT) / totalWords as percentJudged, \n COALESCE(avgRating, 0) as avgRating,\n distribution\n FROM WordStats\n ORDER BY \n CASE WHEN wordLength = 'total' THEN 0 ELSE 1 END,\n CAST(wordLength AS INTEGER)\n `);\n\n return new Response(JSON.stringify(stats.rows), {\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n\n // Render HTML\n return new Response(\n `\n \n \n Word Judgment Dashboard\n \n \n \n \n

\n \n \n \n \n `,\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n}\n\nconst styles = {\n container: {\n fontFamily: \"\\\"Roboto Mono\\\", monospace\",\n maxWidth: \"1100px\",\n margin: \"0 auto\",\n padding: \"20px\",\n },\n introBox: {\n backgroundColor: \"#f0f0f0\",\n border: \"1px solid #ddd\",\n borderRadius: \"5px\",\n padding: \"15px\",\n marginBottom: \"20px\",\n },\n table: {\n width: \"100%\",\n borderCollapse: \"collapse\",\n marginBottom: \"20px\",\n },\n cell: {\n padding: \"8px\",\n border: \"1px solid #ddd\",\n },\n cellNumber: {\n padding: \"8px\",\n border: \"1px solid #ddd\",\n textAlign: \"right\",\n },\n cellCenter: {\n padding: \"8px\",\n border: \"1px solid #ddd\",\n textAlign: \"center\",\n },\n grandTotal: {\n backgroundColor: \"#f5f5f5\",\n fontWeight: \"bold\",\n },\n grandTotalCell: {\n padding: \"8px\",\n border: \"2px solid #aaa\",\n },\n grandTotalCellNumber: {\n padding: \"8px\",\n border: \"2px solid #aaa\",\n textAlign: \"right\",\n },\n grandTotalCellCenter: {\n padding: \"8px\",\n border: \"2px solid #aaa\",\n textAlign: \"center\",\n },\n sourceLink: {\n color: \"#666\",\n textDecoration: \"none\",\n fontSize: \"0.8em\",\n },\n};","createdAt",["D",1740539014307],"version",22,"currentUserHasLiked","likeCount","forkCount","referenceCount","dependencyCount",1,"commentCount","prCount","mergedPr",{"_130":131,"_132":133},"handle","alexwein","profileImageUrl","https://img.clerk.com/eyJ0eXBlIjoicHJveHkiLCJzcmMiOiJodHRwczovL2ltYWdlcy5jbGVyay5kZXYvb2F1dGhfZ2l0aHViL2ltZ18ycjh6emNHdk9mMnY5djU3OFZBbEdleGhQZFAifQ","forkedVal","interval","slug","alexwein/judgeWordsDash","description","@jsxImportSource https://esm.sh/react@18.2.0","versions",[142,145,149,153,157,161,165,169,173,177,181,185,189,193,197,201,205,209,213,217,221,224,227],{"_118":119,"_143":-5,"_116":144,"_113":111},"prId",["D",1740539014307],{"_118":146,"_143":-5,"_116":147,"_113":148},21,["D",1740527628997],"c1ffdece-f3d3-11ef-9773-569c3dd06744",{"_118":150,"_143":-5,"_116":151,"_113":152},20,["D",1740527585418],"a806017e-f3d3-11ef-a00f-569c3dd06744",{"_118":154,"_143":-5,"_116":155,"_113":156},19,["D",1740521146143],"a9eb115a-f3c4-11ef-b6f9-569c3dd06744",{"_118":158,"_143":-5,"_116":159,"_113":160},18,["D",1740520655790],"85a57480-f3c3-11ef-8766-569c3dd06744",{"_118":162,"_143":-5,"_116":163,"_113":164},17,["D",1740519885426],"ba7842ac-f3c1-11ef-89d6-569c3dd06744",{"_118":166,"_143":-5,"_116":167,"_113":168},16,["D",1740517274188],"a60ce418-f3bb-11ef-8921-569c3dd06744",{"_118":170,"_143":-5,"_116":171,"_113":172},15,["D",1740511840724],"ff743c48-f3ae-11ef-8314-569c3dd06744",{"_118":174,"_143":-5,"_116":175,"_113":176},14,["D",1740511757245],"cdb242a4-f3ae-11ef-9c67-569c3dd06744",{"_118":178,"_143":-5,"_116":179,"_113":180},13,["D",1740511578574],"6332f748-f3ae-11ef-8220-569c3dd06744",{"_118":182,"_143":-5,"_116":183,"_113":184},12,["D",1740509345142],"2ff7e780-f3a9-11ef-ba44-569c3dd06744",{"_118":186,"_143":-5,"_116":187,"_113":188},11,["D",1740509312484],"1c809b16-f3a9-11ef-b03c-569c3dd06744",{"_118":190,"_143":-5,"_116":191,"_113":192},10,["D",1740509296225],"12d03fb8-f3a9-11ef-86a0-569c3dd06744",{"_118":194,"_143":-5,"_116":195,"_113":196},9,["D",1740509181744],"ce96f36e-f3a8-11ef-bdde-569c3dd06744",{"_118":198,"_143":-5,"_116":199,"_113":200},8,["D",1740508521874],"45437d9a-f3a7-11ef-8230-569c3dd06744",{"_118":202,"_143":-5,"_116":203,"_113":204},7,["D",1740507880962],"c7401990-f3a5-11ef-a32f-569c3dd06744",{"_118":206,"_143":-5,"_116":207,"_113":208},6,["D",1740507781569],"8c0228e6-f3a5-11ef-8c50-569c3dd06744",{"_118":210,"_143":-5,"_116":211,"_113":212},5,["D",1740507602960],"218c1b8e-f3a5-11ef-8e36-569c3dd06744",{"_118":214,"_143":-5,"_116":215,"_113":216},4,["D",1740507507477],"e8a46858-f3a4-11ef-8e36-569c3dd06744",{"_118":218,"_143":-5,"_116":219,"_113":220},3,["D",1740507339125],"844b09fc-f3a4-11ef-8db1-569c3dd06744",{"_118":91,"_143":-5,"_116":222,"_113":223},["D",1740507221176],"3dfcff50-f3a4-11ef-a1ba-569c3dd06744",{"_118":125,"_143":-5,"_116":225,"_113":226},["D",1740507155864],"170f776a-f3a4-11ef-91c9-569c3dd06744",{"_118":32,"_143":-5,"_116":228,"_113":229},["D",1740507112430],"fd2c6d58-f3a3-11ef-980a-569c3dd06744","recentThread","breadcrumbs","comments",[],"isOwner","routes/_app.v.$handle.$name.dependencies",{"_237":238,"_294":125,"_295":137,"_296":32,"_95":297},"dependenciesList",[239],{"_101":240,"_241":242},"08f95904-3584-11ef-8995-0e10024e3b32","initialData",{"_99":243,"_96":244,"_101":240,"_103":245,"_104":-5,"_105":106,"_107":246,"_108":247,"_110":248,"_112":26,"_113":248,"_114":249,"_116":250,"_118":178,"_120":26,"_121":186,"_123":251,"_124":125,"_126":125,"_122":146,"_127":32,"_128":-5,"_20":252,"_134":255,"_135":-7,"_138":259,"_260":-5,"_136":261,"_140":262},"sqlite","a0bf3b31-15a5-4d5c-880e-4b1e22c9bc18","76a8911e-393e-11ef-8e71-de64eea55b61","# LLM-Safe Fork of @std/sqlite\n\nWe found that LLMs have trouble with the inputs and outputs of our @std/sqlite method.\n\n1. It expects the input to be `(sql: string, args: any[])` but it's `{ sql: string, args: any[] }`\n2. It expects the output to be objects, but they are arrays\n\nInstead of struggling to teach it, we built this val to be a wrapper around @std/sqlite that adheres to what the LLMs expect. \n\nThis val is also backwards-compatible with @std/sqlite, so we're considering merging it in.","script","5631f2d0-dcb9-11ef-80ec-e6cdfca9ef9f","import { API_URL } from \"https://esm.town/v/std/API_URL\";\nimport { LibsqlError, type ResultSet, type Row, type TransactionMode } from \"npm:@libsql/client\";\nimport { z } from \"npm:zod\";\n\n/**\n * Every Val Town account comes with its own private\n * [SQLite database](https://www.sqlite.org/) that\n * is accessible from any of your vals.\n * ([Docs ↗](https://docs.val.town/std/sqlite))\n */\nexport const sqlite = {\n /**\n * Executes a SQLite statement.\n *\n * @param {InStatement} statement - The SQLite statement to execute.\n * @example String query:\n * `sqlite.execute(\"SELECT 1;\")`\n * @example Query with arguments:\n * `sqlite.execute({sql: \"SELECT * from books WHERE year > ?;\", args: [2020]})`\n */\n execute,\n\n /**\n * Executes a batch of SQLite statements.\n *\n * @param {InStatement[]} statements - An array of SQLite statements to execute.\n * @param {TransactionMode} [mode] - The transaction mode for the batch execution.\n */\n batch,\n};\n\n// ------------\n// Functions\n// ------------\n\nasync function execute(statement: InStatement, args?: InArgs): Promise {\n const res = await fetch(`${API_URL}/v1/sqlite/execute`, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${Deno.env.get(\"valtown\")}`,\n },\n body: JSON.stringify({ statement: normalizeStatement(statement, args) }),\n });\n if (!res.ok) {\n throw createResError(await res.text());\n }\n const resultSet = await res.json();\n return upgradeResultSet(resultSet);\n}\n\nasync function batch(statements: InStatement[], mode?: TransactionMode): Promise {\n if (mode && ![\"write\", \"read\", \"deferred\"].includes(mode)) {\n throw new Error(\"Invalid transaction mode provided to sqlite.batch. Must be 'write', 'read', or 'deferred.\");\n }\n const res = await fetch(`${API_URL}/v1/sqlite/batch`, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${Deno.env.get(\"valtown\")}`,\n },\n body: JSON.stringify({ statements: statements.map(s => normalizeStatement(s)), mode }),\n });\n if (!res.ok) {\n throw createResError(await res.text());\n }\n const resultSets = await res.json();\n return resultSets.map(upgradeResultSet);\n}\n\nfunction createResError(body: string) {\n try {\n const e = zLibsqlError.parse(JSON.parse(body));\n // e.message already contains the code, and LibsqlError adds the\n // code to the beginning, so we remove it here\n const msg = e.message.replace(e.code, \"\").replace(/^:\\s+/, \"\");\n return new LibsqlError(msg, e.code, e.rawCode);\n } catch (_) {\n // Failed to parse libsql error\n }\n return new Error(body);\n}\n\n/* Val Town's Turso Proxy returns rows as an array of values\n * Yet the LibSQL API has a Row type which behave as an array or object,\n * ie you can access it via numerical index or string\n */\ninterface ImpoverishedResultSet extends ResultSet {\n rows: any[];\n}\n\nfunction normalizeStatement(statement: InStatement, args?: InArgs) {\n if (Array.isArray(statement)) {\n // for the case of an array of arrays\n return normalizeStatement(statement[0], statement[1]);\n }\n if (typeof statement === \"string\") {\n if (args) {\n return { sql: statement, args };\n } else return statement;\n }\n else if (typeof statement === \"object\") {\n if (statement.args) {\n return statement;\n }\n if (args) {\n return { sql: statement.sql, args };\n }\n return statement.sql;\n }\n else throw new Error(\"Error normalizing sql input\");\n}\n\nfunction upgradeResultSet(results: ImpoverishedResultSet): ResultSet {\n return {\n ...results,\n rows: results.rows.map(row => rowFromSql(row, results.columns)),\n };\n}\n\n// adapted from\n// https://github.com/tursodatabase/libsql-client-ts/blob/17dd996b840c950dd22b871adfe4ba0eb4a5ead3/packages/libsql-client/src/sqlite3.ts#L314C1-L337C2\nfunction rowFromSql(\n sqlRow: Array,\n columns: Array,\n): Row {\n const row = {};\n // make sure that the \"length\" property is not enumerable\n Object.defineProperty(row, \"length\", { value: sqlRow.length });\n for (let i = 0; i < sqlRow.length; ++i) {\n const value = sqlRow[i];\n Object.defineProperty(row, i, { value });\n\n const column = columns[i];\n if (!Object.hasOwn(row, column)) {\n Object.defineProperty(row, column, {\n value,\n enumerable: true,\n configurable: true,\n writable: true,\n });\n }\n }\n return row as Row;\n}\n\n// ------------\n// Helpers\n// ------------\n\nconst zLibsqlError = z.object({\n message: z.string(),\n code: z.string(),\n rawCode: z.number().optional(),\n});\n\n// We patch these types to only support JSON values\nexport type InValue = null | string | number | boolean;\nexport type InArgs = Array | Record;\nexport type InStatement = {\n /**\n * The SQL statement to execute.\n */\n sql: string;\n\n /**\n * The arguments to bind to the SQL statement.\n */\n args: InArgs;\n} | string;",["D",1737987404484],16040,{"_130":253,"_132":254},"stevekrouse","https://images.clerk.dev/uploaded/img_2PqHa2Gsy93xQrjh2w78Xu0cChW.jpeg",{"_113":256,"_130":257,"_99":243,"_118":206,"_258":-5},"56c849ee-f1f8-11ee-9b87-cab58f78796a","std","prDisabledHint","LLM-Safe Fork of @std/sqlite We found that LLMs have trouble with the inputs and outputs of our @std/sqlite method. 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