[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_280":281,"_282":283},"routes/_app.x.$handle.$name",{"_96":95,"_32":45,"_104":86,"_27":53,"_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":58,"_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",13,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":25,"_27":28,"_29":28},"file",{"_30":31,"_32":28,"_33":37,"_35":36,"_38":39,"_40":14,"_41":42,"_24":25},"previous",{"_30":31,"_32":28,"_33":34,"_35":36},"deleted",false,"deletedHere","path","main.js","latestPath","fileId","786f8b08-7fb8-11f0-b010-0224a6c84d84","name","fileType","script","content","import { Hono } from \"https://deno.land/x/hono@v3.11.7/mod.ts\";\nimport \"jsr:@std/dotenv/load\";\nimport { load as cheerioLoad } from \"npm:cheerio@1.0.0-rc.12\";\nimport { listFiles, readFile } from \"https://esm.town/v/std/utils/index.ts\";\n\nconst pipeline_url = `https://yawnxyz-executeproxy.web.val.run/execute`;\n\nconst app = new Hono();\n\n// Environment-aware file reading function\nasync function readFileContent(filePath) {\n if (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) {\n return await readFile(filePath, import.meta.url);\n } else {\n return await Deno.readTextFile(filePath);\n }\n}\n\n// Utils for scraping Groq examples\nconst GROQ_EXAMPLES_URL = \"https://console.groq.com/docs/examples\";\n\nfunction toAbsoluteUrl(path) {\n if (!path) return null;\n if (path.startsWith(\"http://\") || path.startsWith(\"https://\")) return path;\n return \"https://console.groq.com\" + (path.startsWith(\"/\") ? path : \"/\" + path);\n}\n\nfunction parseExamplesFromHtml(htmlText) {\n const $ = cheerioLoad(htmlText);\n const cards = $(\n \"div.rounded-lg.border.bg-card.text-card-foreground.overflow-hidden.h-full.flex.flex-col\"\n );\n const items = [];\n\n cards.each((_idx, el) => {\n const card = $(el);\n const title = card.find(\"h3\").first().text().trim();\n\n let description = card.find(\"p.text-sm\").first().text().trim();\n if (!description) {\n const firstP = card.find(\"p\").filter((_, p) => $(p).text().trim().length > 0).first();\n description = firstP.text().trim();\n }\n\n const imageSrc = card.find(\".aspect-video img\").attr(\"src\") || null;\n const image = toAbsoluteUrl(imageSrc);\n\n const authorP = card.find(\"p.text-xs\").first();\n const avatarUrl = toAbsoluteUrl(authorP.find(\"img\").attr(\"src\") || null);\n let username = authorP.text().replace(/\\s+/g, \" \").trim();\n username = username.replace(/^by\\s*/i, \"\").trim();\n\n let github = null;\n let demo = null;\n card.find(\"a\").each((_, a) => {\n const href = $(a).attr(\"href\") || \"\";\n const text = $(a).text().toLowerCase();\n const abs = href ? (href.startsWith(\"http\") ? href : toAbsoluteUrl(href)) : null;\n if (!abs) return;\n if (text.includes(\"view repository\") || abs.includes(\"github.com\")) github = abs;\n if (text.includes(\"live demo\")) demo = abs;\n });\n\n const item = {\n title,\n description,\n image,\n imageFit: \"cover\",\n username,\n avatarUrl,\n github,\n demo,\n };\n\n if (item.title || item.github || item.demo) items.push(item);\n });\n\n return items;\n}\n\n\nasync function fetchGroqExamples() {\n const res = await fetch(GROQ_EXAMPLES_URL, {\n headers: {\n \"user-agent\":\n \"Mozilla/5.0 (compatible; GroqExamplesFetcher/1.0; +https://labspace.ai)\",\n accept: \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n },\n });\n const htmlText = await res.text();\n const items = parseExamplesFromHtml(htmlText);\n return { items: Array.isArray(items) ? items : [], fallbackUsed: false };\n}\n\n// --- GitHub cookbook adapter helpers ---\nfunction convertGithubToRawUrls(githubUrl) {\n const urls = [];\n const refsHeadsUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/refs/heads/')\n .replace('/tree/', '/refs/heads/');\n urls.push(refsHeadsUrl);\n const directUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/')\n .replace('/tree/', '/');\n urls.push(directUrl);\n if (githubUrl.includes('raw.githubusercontent.com')) urls.push(githubUrl);\n return urls;\n}\n\nasync function tryFetchJsonFromPossibleUrls(possibleUrls) {\n for (const u of possibleUrls) {\n try {\n const resp = await fetch(u);\n if (!resp.ok) continue;\n const contentType = resp.headers.get('content-type') || '';\n if (contentType.includes('application/json')) {\n const json = await resp.json();\n return json;\n }\n const text = await resp.text();\n try {\n const parsed = JSON.parse(text);\n return parsed;\n } catch (_) {\n // Not JSON, skip\n }\n } catch (_) {\n // ignore and continue\n }\n }\n return null;\n}\n\nfunction githubApiHeaders() {\n const headers = {\n accept: 'application/vnd.github+json',\n 'user-agent': 'GroqCookbookScraper/1.0 (+https://labspace.ai)'\n };\n try {\n const token = (typeof Deno !== 'undefined' && Deno.env) ? (Deno.env.get('GITHUB_TOKEN') || Deno.env.get('GH_TOKEN')) : null;\n if (token) headers['authorization'] = `Bearer ${token}`;\n } catch (_) {}\n return headers;\n}\n\nfunction mapCookbookItemToSchema(entry) {\n const authorName = entry?.author?.username || (Array.isArray(entry?.authors) ? entry.authors.map(a => a.username).join(', ') : null);\n const avatarUrl = entry?.author?.imageUrl || (Array.isArray(entry?.authors) && entry.authors.length ? entry.authors[0].imageUrl : null);\n const githubFromCtas = Array.isArray(entry?.ctas) ? (entry.ctas.find(c => (c.icon || '').includes('github'))?.href || null) : null;\n const demoFromCtas = Array.isArray(entry?.ctas) ? (entry.ctas.find(c => /demo|vercel|app|run|spaces|live|render|heroku|netlify|railway/i.test(c.href || ''))?.href || null) : null;\n\n return {\n id: entry?.id ?? null,\n slug: entry?.slug ?? null,\n title: entry?.title ?? null,\n description: entry?.description ?? null,\n image: entry?.image || null,\n imageFit: 'cover',\n username: authorName,\n avatarUrl,\n github: entry?.githubLink || githubFromCtas || null,\n demo: demoFromCtas || null,\n // Cookbook-specific fields\n language: entry?.language || null,\n difficulty: entry?.difficulty || null,\n tags: entry?.tags || [],\n sections: entry?.sections || [],\n date: entry?.date || null,\n readmeSource: entry?.readmeSource || null,\n ipynbLink: entry?.ipynbLink || null,\n ctas: entry?.ctas || [],\n authors: entry?.authors || (entry?.author ? [entry.author] : []),\n featured: entry?.featured || false,\n markdown: entry?.markdown || null,\n };\n}\n\n// No fallback cookbook examples; adapters must fetch live or return empty\n\nfunction slugifyTitle(title) {\n if (!title) return null;\n return title\n .toLowerCase()\n .replace(/[^a-z0-9]+/g, '-')\n .replace(/(^-|-$)+/g, '');\n}\n\nfunction parseGithubDirUrl(dirUrl) {\n try {\n const m = dirUrl.match(/^https?:\\/\\/github\\.com\\/([^/]+)\\/([^/]+)\\/tree\\/([^/]+)\\/?(.*)$/);\n if (!m) return null;\n const [, org, repo, branch, pathRest] = m;\n const dirPath = (pathRest || '').replace(/^\\/+|\\/+$/g, '');\n return { org, repo, branch, dirPath };\n } catch (_) {\n return null;\n }\n}\n\nfunction buildRawBase({ org, repo, branch, dirPath }) {\n const suffix = dirPath ? `/${dirPath}` : '';\n return `https://raw.githubusercontent.com/${org}/${repo}/${branch}${suffix}`;\n}\n\nasync function fetchReadmeFromGithubDir(dirUrl) {\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { content: '', rawUrl: null, rawBase: null };\n const rawBase = buildRawBase(info);\n const candidates = [\n `${rawBase}/README.md`,\n `${rawBase}/Readme.md`,\n `${rawBase}/readme.md`,\n `${rawBase}/README.MD`,\n `${rawBase}/README.markdown`,\n `${rawBase}/README.MARKDOWN`,\n ];\n for (const u of candidates) {\n try {\n const res = await fetch(u);\n if (res.ok) {\n const text = await res.text();\n return { content: text, rawUrl: u, rawBase };\n }\n } catch (_) {\n // continue\n }\n }\n // Fallback: list directory contents and try to find a README file\n try {\n const infoForList = parseGithubDirUrl(dirUrl);\n if (infoForList) {\n const apiUrl = buildGithubApiContentsUrl(infoForList);\n const res = await fetch(apiUrl, {\n headers: {\n accept: 'application/vnd.github+json',\n 'user-agent': 'GroqCookbookScraper/1.0 (+https://labspace.ai)'\n }\n });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data) && data.length) {\n let readmeEntry = data.find((e) => e && e.type === 'file' && /^readme(\\.|$)/i.test(e.name));\n if (!readmeEntry) readmeEntry = data.find((e) => e && e.type === 'file' && /\\.md$/i.test(e.name));\n if (readmeEntry) {\n const url = `${rawBase.replace(/\\/$/, '')}/${readmeEntry.name}`;\n try {\n const res2 = await fetch(url);\n if (res2.ok) {\n const text = await res2.text();\n return { content: text, rawUrl: url, rawBase };\n }\n } catch (_) {}\n }\n }\n }\n }\n } catch (_) {\n // ignore\n }\n return { content: '', rawUrl: null, rawBase };\n}\n\nfunction extractTitleAndDescriptionFromMarkdown(md) {\n if (!md) return { title: null, description: null };\n const lines = md.split(/\\r?\\n/);\n let title = null;\n let startIdx = 0;\n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n if (line.startsWith('# ')) {\n title = line.replace(/^#\\s+/, '').trim();\n startIdx = i + 1;\n break;\n }\n }\n // find first non-empty paragraph after title\n let description = null;\n let para = [];\n for (let i = startIdx; i < lines.length; i++) {\n const line = lines[i];\n // stop at next header\n if (/^#{1,6}\\s+/.test(line)) break;\n if (line.trim() === '') {\n if (para.length) break;\n continue;\n }\n para.push(line.trim());\n }\n if (para.length) description = para.join(' ');\n return { title, description };\n}\n\nfunction extractFirstImageUrlFromMarkdown(md, rawBase) {\n if (!md) return null;\n const m = md.match(/!\\[[^\\]]*\\]\$([^)]+)\$/);\n if (!m) return null;\n const url = m[1].trim();\n if (/^https?:\\/\\//i.test(url)) return url;\n if (url.startsWith('/')) return null; // absolute repo path unsupported here\n const base = rawBase?.replace(/\\/$/, '') || '';\n return `${base}/${url}`;\n}\n\nfunction extractFirstIpyNbLinkFromMarkdown(md) {\n if (!md) return null;\n // Prefer markdown links containing .ipynb\n const mdLink = md.match(/\\[[^\\]]*\\]\$([^)]+\\.ipynb(?:\\?[^)]*)?)\$/i);\n if (mdLink) return mdLink[1];\n // Fallback: plain URLs\n const plain = md.match(/https?:[^\\s)]+\\.ipynb/gi);\n return plain && plain.length ? plain[0] : null;\n}\n\nfunction extractDemoLinkFromMarkdown(md) {\n if (!md) return null;\n const links = Array.from(md.matchAll(/\\[[^\\]]*\\]\$([^)]+)\$/g)).map(m => m[1]);\n const candidates = links.filter(u => /https?:\\/\\//i.test(u));\n const prefer = candidates.find(u => /(vercel|demo|live|appgen|groqlabs|render|railway|heroku|netlify)/i.test(u));\n return prefer || null;\n}\n\nasync function probeRawFile(rawBase, filename) {\n const url = `${rawBase.replace(/\\/$/, '')}/${filename}`;\n try {\n const head = await fetch(url, { method: 'HEAD' });\n if (head.ok) return { exists: true, url };\n } catch (_) {}\n try {\n const get = await fetch(url, { method: 'GET', headers: { 'range': 'bytes=0-0' } });\n return { exists: get.ok, url };\n } catch (_) {\n return { exists: false, url };\n }\n}\n\nasync function fetchGithubCookbookFromDir(query) {\n const dirUrl = query?.dir || query?.repoDirUrl;\n if (!dirUrl) return { items: [], fallbackUsed: false, sourceUrl: null };\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { items: [], fallbackUsed: false, sourceUrl: dirUrl };\n const { content, rawUrl, rawBase } = await fetchReadmeFromGithubDir(dirUrl);\n const slugFromPath = (info.dirPath ? info.dirPath.split('/').pop() : null) || null;\n let title = null;\n let description = null;\n let image = null;\n let ipynbLink = null;\n let demoLink = null;\n\n if (content) {\n const parsed = extractTitleAndDescriptionFromMarkdown(content);\n title = parsed.title || null;\n description = parsed.description || null;\n image = extractFirstImageUrlFromMarkdown(content, rawBase);\n ipynbLink = extractFirstIpyNbLinkFromMarkdown(content);\n demoLink = extractDemoLinkFromMarkdown(content);\n }\n\n // List directory to find notebooks and detect app.py\n let appExists = false;\n try {\n const apiUrl = buildGithubApiContentsUrl(info);\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) {\n if (!ipynbLink) {\n const nb = data.find((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n if (nb) {\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${nb.name}`;\n }\n }\n const appEntry = data.find((e) => e && e.type === 'file' && e.name === 'app.py');\n appExists = !!appEntry;\n }\n }\n } catch (_) {}\n\n if (!title) title = slugifyTitle(slugFromPath || '') || slugFromPath || dirUrl;\n\n const item = {\n slug: slugifyTitle(title) || slugFromPath,\n title,\n description,\n image: image || null,\n imageFit: 'cover',\n username: null,\n avatarUrl: null,\n github: dirUrl,\n demo: demoLink || null,\n language: appExists ? 'python' : null,\n difficulty: null,\n tags: [],\n sections: [],\n date: null,\n readmeSource: rawUrl,\n ipynbLink: ipynbLink || null,\n ctas: [\n { icon: 'mdi:github', href: dirUrl },\n ...(ipynbLink ? [ { icon: 'mdi:notebook', href: ipynbLink } ] : []),\n ...(demoLink ? [ { icon: 'mdi:play-circle-outline', href: demoLink } ] : []),\n ],\n authors: [],\n featured: false,\n markdown: null,\n };\n return { items: [item], fallbackUsed: false, sourceUrl: dirUrl };\n}\n\nfunction buildGithubApiContentsUrl({ org, repo, branch, dirPath }) {\n const path = dirPath ? `/contents/${dirPath}` : `/contents`;\n return `https://api.github.com/repos/${org}/${repo}${path}?ref=${encodeURIComponent(branch)}`;\n}\n\nasync function listGithubSubdirectories(parentDirUrl) {\n const info = parseGithubDirUrl(parentDirUrl);\n if (!info) return [];\n const apiUrl = buildGithubApiContentsUrl(info);\n try {\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (!res.ok) return [];\n const data = await res.json();\n if (!Array.isArray(data)) return [];\n const children = data.filter((e) => e && e.type === 'dir');\n const prefix = `https://github.com/${info.org}/${info.repo}/tree/${info.branch}`;\n return children.map((d) => ({\n name: d.name,\n path: d.path,\n url: `${prefix}/${d.path}`\n }));\n } catch (_) {\n return [];\n }\n}\n\nasync function fetchGithubCookbooksFromParentDir(query) {\n const parent = query?.parent || query?.parentDir || query?.parentUrl;\n if (!parent) return { items: [], fallbackUsed: false, sourceUrl: null };\n const limit = query?.limit ? Number(query.limit) : undefined;\n // Fetch all entries (dirs and files) in the parent directory\n const info = parseGithubDirUrl(parent);\n const apiUrl = info ? buildGithubApiContentsUrl(info) : null;\n let entries = [];\n if (apiUrl) {\n try {\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) entries = data;\n }\n } catch (_) {}\n }\n\n const dirEntries = entries.filter((e) => e && e.type === 'dir').map((d) => ({\n name: d.name,\n url: `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${d.path}`\n }));\n\n const nbFiles = entries.filter((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n\n const selectedDirs = typeof limit === 'number' && limit > 0 ? dirEntries.slice(0, limit) : dirEntries;\n const dirResults = await Promise.all(selectedDirs.map((d) => fetchGithubCookbookFromDir({ dir: d.url })));\n const dirItems = dirResults.flatMap((r) => r.items || []);\n\n // Convert ipynb files into minimal items\n const fileItems = nbFiles.map((f) => {\n const slug = slugifyTitle(f.name.replace(/\\.ipynb$/i, '')) || f.name.replace(/\\.ipynb$/i, '');\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n const ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${f.name}`;\n const github = `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${info.dirPath || ''}`.replace(/\\/$/, '');\n return {\n slug,\n title: slug,\n description: null,\n image: null,\n imageFit: 'cover',\n username: null,\n avatarUrl: null,\n github,\n demo: null,\n language: null,\n difficulty: null,\n tags: [],\n sections: [],\n date: null,\n readmeSource: null,\n ipynbLink,\n ctas: [ { icon: 'mdi:notebook', href: ipynbLink } ],\n authors: [],\n featured: false,\n markdown: null,\n };\n });\n\n const items = [...dirItems, ...fileItems];\n return { items, fallbackUsed: false, sourceUrl: parent };\n}\n\nasync function fetchGithubCookbookExamples(query) {\n const urlParam = query?.url || query?.cookbooksUrl || null;\n let entries = null;\n let resolvedFrom = urlParam || null;\n\n if (urlParam) {\n try {\n const urls = urlParam.includes('github.com') ? convertGithubToRawUrls(urlParam) : [urlParam];\n const json = await tryFetchJsonFromPossibleUrls(urls);\n if (Array.isArray(json)) {\n entries = json;\n resolvedFrom = urlParam;\n }\n } catch (_) {\n // ignore\n }\n }\n\n if (!Array.isArray(entries)) {\n return { items: [], fallbackUsed: false, sourceUrl: resolvedFrom };\n }\n\n const items = entries.map(mapCookbookItemToSchema);\n return { items, fallbackUsed: false, sourceUrl: resolvedFrom };\n}\n\n// --- Custom curated data (hard-coded) ---\nfunction getGroqCookbookRootItem() {\n const repoRoot = \"https://github.com/groq/groq-api-cookbook/tree/main\";\n const rawLogo = \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/images/groq-logo.png\";\n return {\n slug: \"groq-api-cookbook\",\n title: \"Groq API Cookbook\",\n description: \"Getting Started • Tutorials • Questions • Bug Reporting • Contributing\",\n image: rawLogo,\n imageFit: \"cover\",\n username: \"Groq\",\n avatarUrl: \"https://console.groq.com/groq-circle.png\",\n github: repoRoot,\n demo: null,\n language: null,\n difficulty: null,\n tags: [\"overview\", \"cookbook\"],\n sections: [\"overview\"],\n date: null,\n readmeSource: \"https://github.com/groq/groq-api-cookbook/blob/main/README.md\",\n ipynbLink: null,\n ctas: [\n { icon: \"mdi:github\", href: repoRoot },\n { icon: \"mdi:book-open-outline\", href: \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\" },\n { icon: \"mdi:help-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/discussions\" },\n { icon: \"mdi:alert-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/issues\" },\n { icon: \"mdi:account-plus-outline\", href: \"https://github.com/groq/groq-api-cookbook/blob/main/CONTRIBUTING.md\" }\n ],\n authors: [],\n featured: true,\n markdown: \"Groq API Cookbook — Getting Started, Tutorials, Questions, Bug Reporting, Contributing\",\n };\n}\n\nconst html = `\n\n\n\n \n \n \n Boink - A kitchen sink of common interface elements\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n

\n \n

Boink

A kitchen sink of common interface elements

\n\n

\n \n

\n Boink is a simple tool for processing text data.\n

\n\n

\n \n

\n Simply paste your text in the input box below and click Execute.\n

\n\n

Example of summary / details toggle

\n \n

\n\n

\n Select dropdown example:\n

\n \n

\n\n \n \n

\n \n

Output will appear here

\n\n

\n 0 characters • 0 words\n

\n \n

Output will appear here

\n\n

\n A labspace.ai experiment\n

\n\n \n\n\n`;\n\n// Adapter registry and helpers\nconst adaptersRegistry = {\n \"groq-console\": {\n name: \"groq-console\",\n label: \"Groq Console Examples\",\n source: \"groq-console\",\n sourceUrl: GROQ_EXAMPLES_URL,\n async fetchItems() {\n const { items, fallbackUsed } = await fetchGroqExamples();\n return { items, fallbackUsed, sourceUrl: GROQ_EXAMPLES_URL };\n },\n },\n \"github-cookbooks\": {\n name: \"github-cookbooks\",\n label: \"Groq Cookbook Examples (GitHub)\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook\",\n // Accepts optional query.url or query.cookbooksUrl pointing to JSON array (cookbookExamples)\n async fetchItems(query) {\n // If a specific directory is provided, scrape just that one (e.g., Website Guru)\n if (query?.dir || query?.repoDirUrl) {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbookFromDir(query || {});\n return { items, fallbackUsed, sourceUrl: sourceUrl || this.sourceUrl };\n }\n // If a parent tutorials directory is provided, enumerate child dirs and scrape each\n if (query?.parent || query?.parentDir || query?.parentUrl) {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbooksFromParentDir(query || {});\n return { items, fallbackUsed, sourceUrl: sourceUrl || this.sourceUrl };\n }\n // Default: scrape tutorials parent directory\n const defaultParent = \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\";\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbooksFromParentDir({ parent: defaultParent, limit: (query || {}).limit });\n return { items, fallbackUsed, sourceUrl: sourceUrl || defaultParent };\n },\n },\n \"github-website-guru\": {\n name: \"github-website-guru\",\n label: \"Website Guru (GitHub)\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\",\n async fetchItems() {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbookFromDir({ dir: this.sourceUrl });\n return { items, fallbackUsed, sourceUrl };\n },\n },\n \"groq-cookbook-root\": {\n name: \"groq-cookbook-root\",\n label: \"Groq API Cookbook\",\n source: \"custom\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main\",\n async fetchItems() {\n return { items: [getGroqCookbookRootItem()], fallbackUsed: false, sourceUrl: this.sourceUrl };\n },\n },\n \"github-replit-examples\": {\n name: \"github-replit-examples\",\n label: \"Replit Examples (GitHub)\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples\",\n async fetchItems(query) {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbooksFromParentDir({ parent: this.sourceUrl, limit: (query || {}).limit });\n return { items, fallbackUsed, sourceUrl };\n },\n },\n // Additional adapters can be registered here, e.g. \"github-cookbooks\"\n};\n\nfunction listAdapters() {\n return Object.values(adaptersRegistry).map((a) => ({\n name: a.name,\n label: a.label,\n source: a.source,\n sourceUrl: a.sourceUrl,\n }));\n}\n\nasync function runAdapter(adapterName, queryArgs) {\n const adapter = adaptersRegistry[adapterName];\n if (!adapter) {\n return {\n adapter: adapterName,\n error: \"Adapter not found\",\n count: 0,\n items: [],\n fetchedAt: new Date().toISOString(),\n };\n }\n try {\n const { items, fallbackUsed, sourceUrl } = await adapter.fetchItems(queryArgs);\n const itemsWithAdapter = Array.isArray(items) ? items.map((it) => ({ adapter: adapter.name, ...it })) : [];\n return {\n adapter: adapter.name,\n label: adapter.label,\n source: adapter.source,\n sourceUrl: sourceUrl || adapter.sourceUrl,\n count: itemsWithAdapter.length,\n items: itemsWithAdapter,\n fallbackUsed: !!fallbackUsed,\n fetchedAt: new Date().toISOString(),\n };\n } catch (error) {\n return {\n adapter: adapter.name,\n label: adapter.label,\n source: adapter.source,\n sourceUrl: adapter.sourceUrl,\n count: 0,\n items: [],\n error: String(error?.message || error),\n fetchedAt: new Date().toISOString(),\n };\n }\n}\n\n// Keep UI under /ui\napp.get(\"/ui\", (c) => c.html(html));\n\n// List available adapters\napp.get(\"/adapters\", (c) => {\n return c.json({ adapters: listAdapters() });\n});\n\n// Root: run one or more adapters, return per-adapter results (not combined)\napp.get(\"/\", async (c) => {\n // Try prebuilt snapshot first\n try {\n const snapshot = await readFileContent(\"./projects.json\");\n if (snapshot) {\n const parsed = JSON.parse(snapshot);\n if (parsed && Array.isArray(parsed.adapters)) {\n return c.json(parsed);\n }\n }\n } catch (_) {}\n\n const adapterQuery = c.req.query(\"adapter\");\n const requested = adapterQuery\n ? adapterQuery.split(\",\").map((s) => s.trim()).filter(Boolean)\n : Object.keys(adaptersRegistry);\n\n // Collect all query params (first value only) and pass to adapters\n const queries = c.req.queries();\n const queryArgs = {};\n for (const key in queries) {\n if (key === \"adapter\") continue;\n const val = queries[key];\n queryArgs[key] = Array.isArray(val) ? val[0] : val;\n }\n\n const results = await Promise.all(requested.map((name) => runAdapter(name, queryArgs)));\n return c.json({ adapters: results });\n});\n\n// Fetch a single adapter by name\napp.get(\"/adapters/:name\", async (c) => {\n const name = c.req.param('name');\n const queries = c.req.queries();\n const queryArgs = {};\n for (const key in queries) {\n const val = queries[key];\n queryArgs[key] = Array.isArray(val) ? val[0] : val;\n }\n const result = await runAdapter(name, queryArgs);\n return c.json(result);\n});\n\n// Removed legacy boink UI/API\n\nexport default (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) ? app.fetch : app;\n","http","createdAt",["D",1755909106957],"branchVersion","branchId","78113dc8-7fb8-11f0-a529-0224a6c84d84","id","781102e0-7fb8-11f0-a529-0224a6c84d84","groq-api-projects",["D",1755909071355],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","","imageUrl","a8270e74-6479-475a-8025-9b69544ee0e7","pinnedFileId","pinPreview",true,"pinMigrated","screenshotVersion","likeCount",0,"orgId","8319defa-6e1a-46d4-ba66-2114ffd3360b","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_96":95,"_103":99},"org",{"_96":95,"_97":-5,"_98":99,"_18":55,"_100":101,"_102":25},"branch",{"_13":85,"_32":86,"_43":42,"_87":44,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":-5,"_93":45,"_94":95},"isOwned",22,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","yawnxyz","handle","displayName","avatar","https://images.clerk.dev/oauth_github/img_2NnaHhpxNuH1xWRIRjQNoo16TVc.jpeg","tier","pro","canRestrictVals","profileImageUrl","branchName","adoptOrgId",{"_43":44,"_32":45,"_38":276,"_47":-5,"_48":25,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":31,"_57":58,"_59":58,"_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":277,"_80":278,"_82":279,"_84":25},"tree",[222,224,225,226,227,228,229,230,231,232,233],"files",[222,223,224,225,226,227,228,229,230,231,232,233],"counts",{"_212":62,"_213":162,"_214":62,"_215":216,"_217":218},"contents",[125,126,127,128,129,130,131,132,133,134,135],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_43":206,"_32":207,"_30":208,"_139":-5,"_41":42,"_40":162,"_141":58,"_38":209,"_13":62,"_33":210,"_35":-5,"_24":25,"_144":-5,"_27":211},{"_43":199,"_32":200,"_30":201,"_139":-5,"_41":42,"_40":202,"_141":58,"_38":203,"_13":62,"_33":20,"_35":204,"_24":25,"_144":-5,"_27":205},{"_43":192,"_32":193,"_30":194,"_139":-5,"_41":42,"_40":195,"_141":58,"_38":196,"_13":62,"_33":20,"_35":197,"_24":25,"_144":-5,"_27":198},{"_43":185,"_32":186,"_30":187,"_139":-5,"_41":42,"_40":188,"_141":58,"_38":189,"_13":62,"_33":20,"_35":190,"_24":25,"_144":-5,"_27":191},{"_43":178,"_32":179,"_30":180,"_139":-5,"_41":42,"_40":181,"_141":58,"_38":182,"_13":62,"_33":20,"_35":183,"_24":25,"_144":-5,"_27":184},{"_43":171,"_32":172,"_30":173,"_139":-5,"_41":42,"_40":174,"_141":58,"_38":175,"_13":62,"_33":20,"_35":176,"_24":25,"_144":-5,"_27":177},{"_43":164,"_32":165,"_30":166,"_139":-5,"_41":42,"_40":167,"_141":58,"_38":168,"_13":62,"_33":34,"_35":169,"_24":25,"_144":-5,"_27":170},{"_43":160,"_32":28,"_30":31,"_139":-5,"_41":42,"_40":14,"_141":25,"_38":161,"_13":162,"_33":37,"_35":36,"_24":25,"_144":45,"_27":163},{"_43":153,"_32":154,"_30":155,"_139":-5,"_41":42,"_40":156,"_141":25,"_38":157,"_13":62,"_33":20,"_35":158,"_24":25,"_144":-5,"_27":159},{"_43":146,"_32":147,"_30":148,"_139":-5,"_41":42,"_40":149,"_141":25,"_38":150,"_13":62,"_33":34,"_35":151,"_24":25,"_144":-5,"_27":152},{"_43":136,"_32":137,"_30":138,"_139":-5,"_41":42,"_40":140,"_141":58,"_38":142,"_13":62,"_33":34,"_35":143,"_24":25,"_144":-5,"_27":145},"78902e26-7fb8-11f0-bf2c-0224a6c84d84","summarizer.js","78902ef8-7fb8-11f0-bf2c-0224a6c84d84","parentId",12,"latest",["D",1755909072185],"import \"jsr:@std/dotenv/load\";\n\nconst GROQ_CHAT_URL = \"https://api.groq.com/openai/v1/chat/completions\";\n\nfunction stripMarkdownAndHtml(input) {\n if (!input) return \"\";\n let text = String(input);\n // Remove HTML tags\n text = text.replace(/<[^>]*>/g, \" \");\n // Replace markdown images ![alt](url) with alt\n text = text.replace(/!\\[([^\\]]*)\\]\$[^)]*\$/g, \"$1\");\n // Replace markdown links [text](url) with text\n text = text.replace(/\\[([^\\]]+)\\]\$[^)]*\$/g, \"$1\");\n // Remove code fences and inline backticks\n text = text.replace(/```[\\s\\S]*?```/g, \" \");\n text = text.replace(/`+/g, \" \");\n // Collapse whitespace\n text = text.replace(/\\s+/g, \" \").trim();\n return text;\n}\n\nfunction toRawGithubUrl(possibleBlobUrl) {\n if (!possibleBlobUrl) return null;\n try {\n // Convert GitHub blob URLs to raw URLs; keep raw URLs intact\n if (possibleBlobUrl.includes('github.com')) {\n return possibleBlobUrl\n .replace('https://github.com/', 'https://raw.githubusercontent.com/')\n .replace('/blob/', '/');\n }\n return possibleBlobUrl;\n } catch (_) {\n return possibleBlobUrl;\n }\n}\n\nasync function fetchNotebookMarkdown(ipynbUrl) {\n try {\n const rawUrl = toRawGithubUrl(ipynbUrl);\n if (!rawUrl) return '';\n const res = await fetch(rawUrl);\n if (!res.ok) return '';\n const json = await res.json();\n const cells = Array.isArray(json?.cells) ? json.cells : [];\n const md = cells\n .filter((c) => (c?.cell_type || c?.cellType) === 'markdown' && Array.isArray(c?.source))\n .map((c) => c.source.join(''))\n .join('\\n\\n');\n // Fallback: if no markdown cells, concatenate first few code cells as text\n if (md && md.trim().length > 0) return md;\n const code = cells\n .filter((c) => (c?.cell_type || c?.cellType) === 'code' && Array.isArray(c?.source))\n .slice(0, 3)\n .map((c) => c.source.join(''))\n .join('\\n\\n');\n return code || '';\n } catch (_) {\n return '';\n }\n}\n\nfunction refineSummary(input) {\n let t = (input || \"\").trim();\n t = t.replace(/^(?:This\\s+(?:repository|project|tutorial|notebook|application|app|example)\\s+(?:appears\\s+to\\s+be|is|provides|contains|includes|builds|demonstrates|implements|offers)\\s+)/i, \"\");\n t = t.replace(/^(?:This\\s+(?:repository|project|tutorial|notebook|application|app|example)\\s*:\\s*)/i, \"\");\n t = t.replace(/^(?:This\\s+(?:repository|project|tutorial|notebook|application|app|example)\\s+)/i, \"\");\n t = t.replace(/^(?:It\\s+(?:is|provides|offers)\\s+)/i, \"\");\n t = t.replace(/^(?:An?\\s+|The\\s+)/i, \"\");\n return t.trim();\n}\n\nasync function callGroqOneSentence(readmeText, apiKey) {\n const prompt = \"Summarize into ONE plain-English sentence (<=25 words). Output a direct noun phrase without leading articles or meta phrases like 'This project/repository'. No markdown, no code, no title. Neutral tone.\";\n const content = stripMarkdownAndHtml(readmeText).slice(0, 12000);\n const body = {\n // model: \"openai/gpt-oss-20b\",\n model: \"llama-3.1-8b-instant\",\n messages: [\n { role: \"system\", content: prompt },\n { role: \"user\", content }\n ],\n temperature: 0.2,\n };\n const res = await fetch(GROQ_CHAT_URL, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${apiKey}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(body),\n });\n if (!res.ok) throw new Error(`Groq API error ${res.status}`);\n const json = await res.json();\n let text = json?.choices?.[0]?.message?.content || \"\";\n text = text.replace(/\\s+/g, \" \").trim();\n // Post-sanitize: strip any residual HTML/markdown and URLs\n text = stripMarkdownAndHtml(text).replace(/https?:[^\\s]+/gi, \"\").replace(/\\s+/g, \" \").trim();\n // Remove explainer prefaces\n text = refineSummary(text);\n // Limit length roughly to ~25 words / 200 chars\n if (text.length > 200) text = text.slice(0, 200).replace(/[,;:\\s]+[^,;:\\s]*$/, \"\").trim();\n return text;\n}\n\nexport async function summarizeSnapshotDescriptions(snapshot, { apiKey, force = false } = {}) {\n if (!snapshot || !Array.isArray(snapshot.adapters)) return snapshot;\n if (!apiKey) throw new Error(\"Missing GROQ_API_KEY\");\n\n const updated = { adapters: [] };\n for (const group of snapshot.adapters) {\n const items = Array.isArray(group.items) ? group.items : [];\n const newItems = [];\n for (const item of items) {\n let description = item?.description || null;\n const readmeUrl = item?.readmeSource || null;\n const ipynbUrl = item?.ipynbLink || null;\n\n if (force || !description) {\n let sourceText = \"\";\n // Try README first\n if (readmeUrl) {\n try {\n const res = await fetch(readmeUrl);\n const text = res.ok ? await res.text() : \"\";\n if (text && text.trim().length > 0) sourceText = text;\n } catch (_) {}\n }\n // Fallback to ipynb content if still missing\n if (!sourceText && ipynbUrl) {\n try {\n const nb = await fetchNotebookMarkdown(ipynbUrl);\n if (nb && nb.trim().length > 0) sourceText = nb;\n } catch (_) {}\n }\n // Last resort: synthesize from known fields\n if (!sourceText) {\n const parts = [];\n if (item.title) parts.push(String(item.title));\n if (item.description) parts.push(stripMarkdownAndHtml(item.description));\n const repoPath = (item.github || \"\").toString().split(\"/\").slice(-2).join(\"/\");\n if (repoPath) parts.push(repoPath);\n if (Array.isArray(item.tags) && item.tags.length) parts.push(item.tags.join(\", \"));\n sourceText = parts.join(\". \");\n }\n try {\n const repoSlug = (item.github || item.slug || item.title || \"item\").toString().split(\"/\").filter(Boolean).slice(-1)[0];\n description = await callGroqOneSentence(sourceText, apiKey);\n try { console.log(`[${repoSlug}]: \"${description}\"`); } catch (_) {}\n } catch (_) {}\n }\n newItems.push({ ...item, description });\n }\n updated.adapters.push({ ...group, items: newItems, count: newItems.length });\n }\n return updated;\n}\n\n\n","label",[137],"7880c21a-7fb8-11f0-841f-0224a6c84d84","snapshot.js","7880c2d8-7fb8-11f0-841f-0224a6c84d84",9,["D",1755909072047],"import \"jsr:@std/dotenv/load\";\nimport { fetchGroqExamples, fetchGithubCookbooksFromParentDir, fetchGithubCookbookFromDir, getGroqCookbookRootItem } from \"./extractors.js\";\nimport { summarizeSnapshotDescriptions } from \"./summarizer.js\";\n\n// Produces a consolidated projects.json snapshot so runtime endpoints can read from disk\nconst outputs = [];\n\n// 1) Groq console examples\ntry {\n const { items } = await fetchGroqExamples();\n outputs.push({ adapter: \"groq-console\", items });\n} catch (e) {\n console.error(\"Failed groq-console:\", e);\n outputs.push({ adapter: \"groq-console\", items: [] });\n}\n\n// 2) Tutorials parent\ntry {\n const { items } = await fetchGithubCookbooksFromParentDir({ parent: \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\", limit: 400, nested: 1 });\n outputs.push({ adapter: \"github-cookbooks\", items });\n} catch (e) {\n console.error(\"Failed github-cookbooks tutorials:\", e);\n outputs.push({ adapter: \"github-cookbooks\", items: [] });\n}\n\n// 3) Replit examples\ntry {\n const { items } = await fetchGithubCookbooksFromParentDir({ parent: \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples\", limit: 400, nested: 1 });\n outputs.push({ adapter: \"github-replit-examples\", items });\n} catch (e) {\n console.error(\"Failed github-replit-examples:\", e);\n outputs.push({ adapter: \"github-replit-examples\", items: [] });\n}\n\n// 4) Website Guru dedicated\ntry {\n const { items } = await fetchGithubCookbookFromDir({ dir: \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\" });\n outputs.push({ adapter: \"github-website-guru\", items });\n} catch (e) {\n console.error(\"Failed github-website-guru:\", e);\n outputs.push({ adapter: \"github-website-guru\", items: [] });\n}\n\n// 5) Cookbook root curated\ntry {\n outputs.push({ adapter: \"groq-cookbook-root\", items: [getGroqCookbookRootItem()] });\n} catch (e) {\n console.error(\"Failed groq-cookbook-root:\", e);\n outputs.push({ adapter: \"groq-cookbook-root\", items: [] });\n}\n\nconst apiKey = Deno.env.get(\"GROQ_API_KEY\") || Deno.env.get(\"GROQ_KEY\") || Deno.env.get(\"GROQ_TOKEN\");\nlet finalSnapshot = { adapters: outputs };\nif (apiKey) {\n try {\n finalSnapshot = await summarizeSnapshotDescriptions(finalSnapshot, { apiKey, force: true });\n console.log(\"Descriptions summarized via Groq\");\n } catch (e) {\n console.warn(\"Summary step failed:\", e?.message || e);\n }\n} else {\n console.warn(\"No GROQ_API_KEY set; skipping summarization.\");\n}\n\nawait Deno.writeTextFile(new URL(\"./projects.json\", import.meta.url), JSON.stringify(finalSnapshot, null, 2));\nconsole.log(\"Wrote projects.json with\", finalSnapshot.adapters.reduce((n, s) => n + (s.items?.length || 0), 0), \"items\");\n\n\n",[147],"78764678-7fb8-11f0-a364-0224a6c84d84","projects.json","7876474a-7fb8-11f0-a364-0224a6c84d84",7,["D",1755909071979],"{\n \"adapters\": [\n {\n \"adapter\": \"groq-console\",\n \"items\": [\n {\n \"title\": \"Stock Bot\",\n \"description\": \"Stock Bot is an AI chatbot offering real-time stock data, charts, financials, and market insights.\",\n \"image\": \"https://console.groq.com/templates/stockbot.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/bklieger-groq/stockbot-on-groq\",\n \"demo\": \"https://groq-stockbot.vercel.app/\"\n },\n {\n \"title\": \"Starter Chatbot\",\n \"description\": \"Open-source AI chatbot app template built with Next.js and the Vercel AI SDK.\",\n \"image\": \"https://console.groq.com/templates/ai-sdk-starter-groq.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Vercel\",\n \"avatarUrl\": null,\n \"github\": \"https://github.com/vercel-labs/ai-sdk-starter-groq\",\n \"demo\": \"https://ai-sdk-starter-groq.vercel.app/\"\n },\n {\n \"title\": \"Blog Generator from Audio\",\n \"description\": \"Groq's Blog Wizard generates structured blog posts from audio or video content using AI models like Whisper and Llama3.\",\n \"image\": \"https://console.groq.com/templates/blogwizard.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/blogwizard\",\n \"demo\": \"https://blogwizard.groqlabs.com/\"\n },\n {\n \"title\": \"Groq App Generator\",\n \"description\": \"Groq App Generator is an interactive web application that generates and modifies web applications in microseconds.\",\n \"image\": \"https://console.groq.com/showcase-applications/appgen.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Rick Lamers, Jose Menendez, Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-appgen\",\n \"demo\": \"https://appgen.groqlabs.com/\"\n },\n {\n \"title\": \"Groq x Gradio Voice Assistant\",\n \"description\": \"Groq and Gradio collaboration enables a voice-powered AI application with real-time speech recognition capabilities.\",\n \"image\": \"https://console.groq.com/showcase-applications/voiceapp.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Hatice Ozen\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/groq-gradio/groq-gradio-tutorial.ipynb\",\n \"demo\": null\n },\n {\n \"title\": \"Magic Spell\",\n \"description\": \"AI-powered text editor built with Next.js, Vercel AI SDK, and Groq.\",\n \"image\": \"https://console.groq.com/showcase-applications/magic-spell.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Ai-ng and Nick Oates\",\n \"avatarUrl\": null,\n \"github\": \"https://github.com/ai-ng/magic-spell\",\n \"demo\": \"https://magic-spell.vercel.app/\"\n },\n {\n \"title\": \"Groq MCP Server\",\n \"description\": \"Groq MCP Server is a server for querying Groq models from clients like Claude.\",\n \"image\": \"https://console.groq.com/showcase-applications/groq-mcp-server.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Jan Zheng\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-mcp-server\",\n \"demo\": null\n },\n {\n \"title\": \"Groq Compound CLI\",\n \"description\": \"Groq Compound CLI is an interactive command line interface for the Groq compound-beta system.\",\n \"image\": \"https://console.groq.com/showcase-applications/compound-cli.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/bklieger-groq/compound-cli\",\n \"demo\": null\n },\n {\n \"title\": \"Groq Desktop\",\n \"description\": \"Groq Desktop is a local MCP client with server support for Groq models.\",\n \"image\": \"https://console.groq.com/showcase-applications/groq-desktop-beta.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Rick Lamers\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-desktop-beta\",\n \"demo\": null\n },\n {\n \"title\": \"Groq Compound MCP Server\",\n \"description\": \"Groq Compound MCP Server is a server for interacting with Groq models.\",\n \"image\": \"https://console.groq.com/showcase-applications/groq-compound-mcp-server.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Rick Lamers, John Barrus\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/compound-mcp-server\",\n \"demo\": null\n }\n ],\n \"count\": 10\n },\n {\n \"adapter\": \"github-cookbooks\",\n \"items\": [\n {\n \"slug\": \"portkey-ai-with-groq\",\n \"title\": \"Portkey AI with Groq\",\n \"description\": \"Portkey AI is a control panel for AI apps that enables teams to build reliable, cost-efficient, and fast applications by integrating with various AI models.\",\n \"image\": \"https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/refs/heads/main/Portkey-Dashboard.png\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/Portkey-with-Groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/Portkey-with-Groq/Readme.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/Portkey-with-Groq\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"agno-groq-mlb-game-recap-generator\",\n \"title\": \"Agno + Groq MLB Game Recap Generator\",\n \"description\": \"Mixture of Agents project uses Agno Agents and the Groq API to generate comprehensive MLB game recaps by combining multiple AI-generated articles.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/agno-mixture-of-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/agno-mixture-of-agents/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/agno-mixture-of-agents/Mixture-of-Agents-Agno-Groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/agno-mixture-of-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/agno-mixture-of-agents/Mixture-of-Agents-Agno-Groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"travel-agent-powered-by-aixplain\",\n \"title\": \"Travel Agent Powered by aiXplain\",\n \"description\": \"Travel Agent is a modular multi-agent system powered by aiXplain for fast inference speed and personalized travel planning experiences.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/aiXplain-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/aiXplain-agents/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/aiXplain-agents/aiXplain_Agents.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/aiXplain-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/aiXplain-agents/aiXplain_Agents.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"arize-phoenix-evaluate-groq-agent\",\n \"title\": \"arize-phoenix-evaluate-groq-agent\",\n \"description\": \"Phoenix is an open-source AI observability platform for tracing, evaluating, and experimenting with Groq applications.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/arize-phoenix-evaluate-groq-agent\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/arize-phoenix-evaluate-groq-agent/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/arize-phoenix-evaluate-groq-agent/trace_and_evaluate_function_calling_agent.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/arize-phoenix-evaluate-groq-agent\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/arize-phoenix-evaluate-groq-agent/trace_and_evaluate_function_calling_agent.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"audio-chunking\",\n \"title\": \"audio-chunking\",\n \"description\": \"Audio chunking is a method used to process long audio files efficiently by breaking them down into manageable chunks.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/audio-chunking\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/audio-chunking/audio_chunking_tutorial.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/audio-chunking\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/audio-chunking/audio_chunking_tutorial.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"analyze-and-tag-images-with-llama-4-on-groq-batch\",\n \"title\": \"Analyze and Tag Images with Llama 4 on Groq Batch\",\n \"description\": \"Analyzing a bulk set of images to tag and categorize them using the Groq Batch API and Llama 4 model.\",\n \"image\": \"https://github.com/user-attachments/assets/f5c1fd4a-8e88-441d-af5f-a303e7611cf9\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-analyze-images\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/batch-analyze-images/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-analyze-images\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-batch-processing\",\n \"title\": \"Groq Batch Processing\",\n \"description\": \"Groq API batch processing involves setting up dependencies, uploading a JSONL file, creating a batch object, monitoring status, and retrieving results.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-processing\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/batch-processing/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-processing\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"benchmarking-rag-langchain\",\n \"title\": \"benchmarking-rag-langchain\",\n \"description\": \"Retrieval Augmented Generation pipeline is benchmarked using Llama3 and LangChain to evaluate its performance and potential for improvement.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/benchmarking-rag-langchain\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/benchmarking-rag-langchain/benchmarking_rag.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/benchmarking-rag-langchain\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/benchmarking-rag-langchain/benchmarking_rag.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"composio-newsletter-summarizer-agent\",\n \"title\": \"composio-newsletter-summarizer-agent\",\n \"description\": \"Groq's LLMs are integrated with Composio for seamless interactions with external applications through pre-defined actions.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/composio-newsletter-summarizer-agent\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/composio-newsletter-summarizer-agent/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/composio-newsletter-summarizer-agent/composio-groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/composio-newsletter-summarizer-agent\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/composio-newsletter-summarizer-agent/composio-groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"crewai-mixture-of-agents\",\n \"title\": \"crewai-mixture-of-agents\",\n \"description\": \"collaborative AI system using Crew AI and Groq API generates a polished MLB game recap by aggregating and refining articles from multiple agents with different language models.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/crewai-mixture-of-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/crewai-mixture-of-agents/Mixture-of-Agents-Crew-AI-Groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/crewai-mixture-of-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/crewai-mixture-of-agents/Mixture-of-Agents-Crew-AI-Groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"function-calling-101-ecommerce\",\n \"title\": \"function-calling-101-ecommerce\",\n \"description\": \"Function calling in large language models allows for invoking pre-defined functions to perform specific tasks, combining flexibility and creativity with consistent and repeatable actions.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-101-ecommerce\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-101-ecommerce/Function-Calling-101-Ecommerce.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-101-ecommerce\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-101-ecommerce/Function-Calling-101-Ecommerce.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"function-calling-sql\",\n \"title\": \"function-calling-sql\",\n \"description\": \"Researchers explored two methods for using Large Language Models to query databases, comparing the benefits and drawbacks of each approach.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-sql\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-sql/json-mode-function-calling-for-sql.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-sql\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-sql/json-mode-function-calling-for-sql.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-gradio\",\n \"title\": \"groq-gradio\",\n \"description\": \"voice-powered AI application is built using Groq for real-time speech recognition and text generation, Gradio for creating an interactive web interface, and Hugging Face Spaces for hosting.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq-gradio\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/groq-gradio/groq-gradio-tutorial.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq-gradio\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/groq-gradio/groq-gradio-tutorial.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-chat-streamlit-app\",\n \"title\": \"Groq Chat Streamlit App\",\n \"description\": \"Streamlit app integrates with the Groq API to provide a chat interface with advanced language models and customizable features.\",\n \"image\": \"https://static.streamlit.io/badges/streamlit_badge_black_white.svg\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq_streamlit_demo\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/groq_streamlit_demo/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq_streamlit_demo\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"instagram-reel-subtitler\",\n \"title\": \"instagram-reel-subtitler\",\n \"description\": \"Automated Instagram Reel subtitle generator using Groq Whisper extracts audio, transcribes it, and overlays word-by-word subtitles onto the video.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/instagram-reel-subtitler\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/instagram-reel-subtitler/subtitler-tutorial.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/instagram-reel-subtitler\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/instagram-reel-subtitler/subtitler-tutorial.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"jigsawstack-prompt-engine\",\n \"title\": \"jigsawstack-prompt-engine\",\n \"description\": \"JigsawStack Prompt Engine is a feature that automates tasks using custom fine-tuned models and automatically chooses the best Large Language Model for every prompt.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/jigsawstack-prompt-engine\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/jigsawstack-prompt-engine/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/jigsawstack-prompt-engine/jigsawstack-prompt-engine.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/jigsawstack-prompt-engine\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/jigsawstack-prompt-engine/jigsawstack-prompt-engine.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"json-mode-social-determinants-of-health\",\n \"title\": \"json-mode-social-determinants-of-health\",\n \"description\": \"Groq API's JSON mode is used to extract social determinants of health from clinical notes and structure them into a table for analytics.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/json-mode-social-determinants-of-health\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/json-mode-social-determinants-of-health/SDOH-Json-mode.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/json-mode-social-determinants-of-health\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/json-mode-social-determinants-of-health/SDOH-Json-mode.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"follow-up-question-works-since-agent-maintains-conversation-history\",\n \"title\": \"follow-up question works since agent maintains conversation history\",\n \"description\": \"To use Langroid with Groq, create a virtual environment, set the GROQ_API_KEY in a .env file, and specify the model name to groq/ in Langroid scripts.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/langroid-llm-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/langroid-llm-agents/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/langroid-llm-agents/search-assistant.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/langroid-llm-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/langroid-llm-agents/search-assistant.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"use-litellm-proxy-to-call-groq-api\",\n \"title\": \"Use LiteLLM Proxy to Call Groq API\",\n \"description\": \"LiteLLM Proxy is a tool for calling multiple large language models from various platforms, including Groq, in a unified format.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/litellm-proxy-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/litellm-proxy-groq/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/litellm-proxy-groq\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"llama-guard-safe-chatbot\",\n \"title\": \"llama-guard-safe-chatbot\",\n \"description\": \"Llama Guard 4 is an advanced content moderation tool designed to assess user messages for harmful content across 14 categories.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama-guard-safe-chatbot\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama-guard-safe-chatbot/Llama-Guard-4-Ensuring-Safe-Chatbot.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama-guard-safe-chatbot\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama-guard-safe-chatbot/Llama-Guard-4-Ensuring-Safe-Chatbot.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"llama3-stock-market-function-calling\",\n \"title\": \"llama3-stock-market-function-calling\",\n \"description\": \"Meta's Llama 3 model is used in conjunction with Groq's LangChain integration to leverage the yfinance API for real-time stock market analysis.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama3-stock-market-function-calling\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama3-stock-market-function-calling/llama3-stock-market-function-calling.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama3-stock-market-function-calling\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama3-stock-market-function-calling/llama3-stock-market-function-calling.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"minions-with-groq-api-cookbook-for-multi-hop-reasoning\",\n \"title\": \"Minions with Groq API Cookbook for Multi-Hop Reasoning\",\n \"description\": \"Minions is a framework that enables efficient collaboration between local and cloud models for multi-hop reasoning tasks.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/minions-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/minions-groq/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/minions-groq\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"mixture-of-agents\",\n \"title\": \"mixture-of-agents\",\n \"description\": \"Mixture of Agents (MoA) is an advanced approach in Generative AI that combines multiple AI models to produce more robust and comprehensive responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/mixture-of-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/mixture-of-agents/mixture_of_agents.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/mixture-of-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/mixture-of-agents/mixture_of_agents.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"multimodal-image-processing\",\n \"title\": \"multimodal-image-processing\",\n \"description\": \"Groq API offers a powerful vision model called LLaVA that combines language and image analysis capabilities for generating text descriptions of images and creating short stories.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/multimodal-image-processing\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/multimodal-image-processing/dog-picture-storytelling-with-llava.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/multimodal-image-processing\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/multimodal-image-processing/dog-picture-storytelling-with-llava.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"open-source-platform-for-ai-engineering\",\n \"title\": \"Open Source Platform for AI Engineering\",\n \"description\": \"OpenLIT is an open-source tool for monitoring AI performance with one line of code, providing analytics and observability features.\",\n \"image\": \"https://img.shields.io/github/license/openlit/openlit?label=License&logo=github&color=f80&logoColor=white\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/opentelemetry-observability-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/opentelemetry-observability-groq/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/opentelemetry-observability-groq/groq_opentelemetry_tracing_evals.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/opentelemetry-observability-groq\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/opentelemetry-observability-groq/groq_opentelemetry_tracing_evals.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"parallel-tool-use\",\n \"title\": \"parallel-tool-use\",\n \"description\": \"Parallel tool use enables Large Language Models to interact with external resources by invoking multiple tools simultaneously for more efficient and effective responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/parallel-tool-use\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/parallel-tool-use/parallel-tool-use.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/parallel-tool-use\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/parallel-tool-use/parallel-tool-use.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"portkey-openai-to-groq\",\n \"title\": \"portkey-openai-to-groq\",\n \"description\": \"Portkey is a control panel for AI apps that connects to 150+ models through a unified API and provides observability and load balancing features.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/portkey-openai-to-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/portkey-openai-to-groq/Switch_from_OpenAI_to_Groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/portkey-openai-to-groq\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/portkey-openai-to-groq/Switch_from_OpenAI_to_Groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"presidential-speeches-rag\",\n \"title\": \"presidential-speeches-rag\",\n \"description\": \"Retrieval-Augmented Generation system using Groq API and Langchain is implemented to gather pertinent information from external data sources and provide it to a Large Language Model.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/presidential-speeches-rag\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/presidential-speeches-rag/rag-langchain-presidential-speeches.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/presidential-speeches-rag\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/presidential-speeches-rag/rag-langchain-presidential-speeches.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"structured-output-instructor\",\n \"title\": \"structured-output-instructor\",\n \"description\": \"Groq and Instructor libraries simplify generating structured outputs from Large Language Models.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/structured-output-instructor\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/structured-output-instructor/structured_output_instructor.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/structured-output-instructor\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/structured-output-instructor/structured_output_instructor.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"toolhouse-for-tool-use-with-groq-api\",\n \"title\": \"toolhouse-for-tool-use-with-groq-api\",\n \"description\": \"Groq API and Toolhouse integration enables LLMs to perform tasks like web searches, email sending, and code execution without manual coding or prompting.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/toolhouse-for-tool-use-with-groq-api\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/toolhouse-for-tool-use-with-groq-api/Groq <> Toolhouse.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/toolhouse-for-tool-use-with-groq-api\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/toolhouse-for-tool-use-with-groq-api/Groq <> Toolhouse.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"whisper-podcast-rag\",\n \"title\": \"whisper-podcast-rag\",\n \"description\": \"podcast chat app is built using Whisper for audio transcription and Retrieval-Augmented Generation (RAG) for answering user queries based on podcast content.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/whisper-podcast-rag\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/whisper-podcast-rag/whisper-podcast-rag.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/whisper-podcast-rag\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/whisper-podcast-rag/whisper-podcast-rag.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"ai-code-execution-with-groq\",\n \"title\": \"AI Code Execution with Groq\",\n \"description\": \"AI data analyst uses Groq-powered LLMs and E2B's Code Interpreter SDK to plot a linear regression chart from uploaded CSV data.\",\n \"image\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-js/image_1.png\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-js\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-js/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-js\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"ai-code-execution-with-models-powered-by-groq\",\n \"title\": \"AI Code Execution with models powered by Groq\",\n \"description\": \"AI data analyst uses LLMs powered by Groq and the E2B Code Interpreter SDK to plot a linear regression chart from uploaded CSV data.\",\n \"image\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-python/image.png\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-python\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-python/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/e2b-code-interpreting/code-interpreter-python/groq_with_e2b_code_interpreter.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-python\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/e2b-code-interpreting/code-interpreter-python/groq_with_e2b_code_interpreter.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"image-moderation\",\n \"title\": \"image-moderation\",\n \"description\": \"Groq and Gradio are used to build an image moderation application for fast image analysis and content safety checking.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/image_moderation.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/image_moderation.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n }\n ],\n \"count\": 34\n },\n {\n \"adapter\": \"github-replit-examples\",\n \"items\": [\n {\n \"slug\": \"a-guide-on-implementing-chat-history-in-your-groq-based-llm-applications\",\n \"title\": \"A guide on implementing chat history in your Groq based LLM applications\",\n \"description\": \"Groq-based LLM applications can implement chat history using simple JSON files to store previous queries and answers.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/chat-history\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/chat-history/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/chat-history\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-langchain-conversational-chatbot\",\n \"title\": \"Groq LangChain Conversational Chatbot\",\n \"description\": \"conversational chatbot application powered by LangChain and the Groq API provides a user interface for interacting with a chatbot that generates human-like responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/conversational-chatbot-langchain\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/conversational-chatbot-langchain/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/conversational-chatbot-langchain\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"crewai-machine-learning-assistant\",\n \"title\": \"CrewAI Machine Learning Assistant\",\n \"description\": \"CrewAI is a command line machine learning assistant that leverages AI agents to guide users through project steps and automate tasks.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/crewai-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/crewai-agents/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/crewai-agents\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-quickstart-conversational-chatbot\",\n \"title\": \"Groq Quickstart Conversational Chatbot\",\n \"description\": \"conversational chatbot application powered by Groq allows users to interact with a simple interface and receive short, concise responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groq-quickstart-conversational-chatbot\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/groq-quickstart-conversational-chatbot/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groq-quickstart-conversational-chatbot\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groqing-the-stock-market-with-llama-3-function-calling\",\n \"title\": \"'Groqing the Stock Market' with Llama 3 Function Calling\",\n \"description\": \"application uses the yfinance API and Llama 3 model to provide stock market insights and plot historical prices based on user prompts.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groqing-the-stock-market-function-calling-llama3\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/groqing-the-stock-market-function-calling-llama3/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groqing-the-stock-market-function-calling-llama3\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"llamachat-conversational-chatbot-with-llamaindex-and-llama3\",\n \"title\": \"LlamaChat: Conversational Chatbot with LlamaIndex and Llama3\",\n \"description\": \"conversational chatbot application powered by LlamaIndex and Meta's Llama3 model uses the Groq API to generate responses in different interaction modes.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/llamachat-conversational-chatbot-with-llamaIndex\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/llamachat-conversational-chatbot-with-llamaIndex/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/llamachat-conversational-chatbot-with-llamaIndex\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"presidential-speeches-rag-with-pinecone\",\n \"title\": \"Presidential Speeches RAG with Pinecone\",\n \"description\": \"command line application uses Retrieval-Augmented Generation to answer user questions about US presidential speeches by retrieving relevant speeches from a Pinecone vector database.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/presidential-speeches-rag-with-pinecone\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/presidential-speeches-rag-with-pinecone/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/dan/replit-conversion/presidential-speeches-rag/presidential-speeches-rag.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/presidential-speeches-rag-with-pinecone\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/dan/replit-conversion/presidential-speeches-rag/presidential-speeches-rag.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"duckdb-text-to-sql-with-json-mode\",\n \"title\": \"DuckDB Text-to-SQL with JSON Mode\",\n \"description\": \"command line application that uses natural language processing to convert user questions into SQL queries for querying DuckDB databases.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/text-to-sql-json-mode\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/text-to-sql-json-mode/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/text-to-sql-json-mode\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"executing-verified-queries-with-function-calling\",\n \"title\": \"Executing Verified Queries with Function Calling\",\n \"description\": \"command line application uses function calling to execute pre-verified SQL queries against DuckDB data based on user input.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/verified-sql-function-calling\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/verified-sql-function-calling/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/verified-sql-function-calling\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"jigsawstack-prompt-engine\",\n \"title\": \"JigsawStack Prompt Engine\",\n \"description\": \"JigsawStack is a powerful AI SDK that automates tasks such as web scraping and translation using custom fine-tuned models.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/node-example\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/jigsawstack-prompt-engine/node-example/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/node-example\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"jigsawstack-prompt-engine\",\n \"title\": \"JigsawStack Prompt Engine\",\n \"description\": \"JigsawStack is a powerful AI SDK that automates tasks using custom fine-tuned models and allows for automatic Large Language Model selection.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/python-example\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/jigsawstack-prompt-engine/python-example/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/python-example\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n }\n ],\n \"count\": 11\n },\n {\n \"adapter\": \"github-website-guru\",\n \"items\": [\n {\n \"slug\": \"website-guru\",\n \"title\": \"Website Guru\",\n \"description\": \"Streamlit application called Website Guru uses Large Language Models to answer questions about a given website's content.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\",\n \"demo\": null,\n \"language\": \"python\",\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/chat_with_website/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n }\n ],\n \"count\": 1\n },\n {\n \"adapter\": \"groq-cookbook-root\",\n \"items\": [\n {\n \"slug\": \"groq-api-cookbook\",\n \"title\": \"Groq API Cookbook\",\n \"description\": \"GitHub repository \\\"groq-api-cookbook\\\" contains a collection of tutorials and guides for using the Groq API.\",\n \"image\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/images/groq-logo.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Groq\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [\n \"overview\",\n \"cookbook\"\n ],\n \"sections\": [\n \"overview\"\n ],\n \"date\": null,\n \"readmeSource\": \"https://github.com/groq/groq-api-cookbook/blob/main/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main\"\n },\n {\n \"icon\": \"mdi:book-open-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\"\n },\n {\n \"icon\": \"mdi:help-circle-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/discussions\"\n },\n {\n \"icon\": \"mdi:alert-circle-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/issues\"\n },\n {\n \"icon\": \"mdi:account-plus-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/CONTRIBUTING.md\"\n }\n ],\n \"authors\": [],\n \"featured\": true,\n \"markdown\": \"Groq API Cookbook — Getting Started, Tutorials, Questions, Bug Reporting, Contributing\"\n }\n ],\n \"count\": 1\n }\n ]\n}",[154],"8d4af76a-7fb8-11f0-ac86-0224a6c84d84",["D",1755909106957],1,[28],"78611ff0-7fb8-11f0-b98a-0224a6c84d84","extractors.js","78612090-7fb8-11f0-b98a-0224a6c84d84",3,["D",1755909071854],"import { load as cheerioLoad } from \"npm:cheerio@1.0.0-rc.12\";\n\nexport const GROQ_EXAMPLES_URL = \"https://console.groq.com/docs/examples\";\n\nfunction toAbsoluteUrl(path) {\n if (!path) return null;\n if (path.startsWith(\"http://\") || path.startsWith(\"https://\")) return path;\n return \"https://console.groq.com\" + (path.startsWith(\"/\") ? path : \"/\" + path);\n}\n\nfunction parseExamplesFromHtml(htmlText) {\n const $ = cheerioLoad(htmlText);\n const cards = $(\n \"div.rounded-lg.border.bg-card.text-card-foreground.overflow-hidden.h-full.flex.flex-col\"\n );\n const items = [];\n\n cards.each((_idx, el) => {\n const card = $(el);\n const title = card.find(\"h3\").first().text().trim();\n\n let description = card.find(\"p.text-sm\").first().text().trim();\n if (!description) {\n const firstP = card.find(\"p\").filter((_, p) => $(p).text().trim().length > 0).first();\n description = firstP.text().trim();\n }\n\n const imageSrc = card.find(\".aspect-video img\").attr(\"src\") || null;\n const image = toAbsoluteUrl(imageSrc);\n\n const authorP = card.find(\"p.text-xs\").first();\n const avatarUrl = toAbsoluteUrl(authorP.find(\"img\").attr(\"src\") || null);\n let username = authorP.text().replace(/\\s+/g, \" \").trim();\n username = username.replace(/^by\\s*/i, \"\").trim();\n\n let github = null;\n let demo = null;\n card.find(\"a\").each((_, a) => {\n const href = $(a).attr(\"href\") || \"\";\n const text = $(a).text().toLowerCase();\n const abs = href ? (href.startsWith(\"http\") ? href : toAbsoluteUrl(href)) : null;\n if (!abs) return;\n if (text.includes(\"view repository\") || abs.includes(\"github.com\")) github = abs;\n if (text.includes(\"live demo\")) demo = abs;\n });\n\n const item = { title, description, image, imageFit: \"cover\", username, avatarUrl, github, demo };\n if (item.title || item.github || item.demo) items.push(item);\n });\n\n return items;\n}\n\nexport async function fetchGroqExamples() {\n const res = await fetch(GROQ_EXAMPLES_URL, {\n headers: {\n \"user-agent\": \"Mozilla/5.0 (compatible; GroqExamplesFetcher/1.0; +https://labspace.ai)\",\n accept: \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n },\n });\n const htmlText = await res.text();\n const items = parseExamplesFromHtml(htmlText);\n return { items: Array.isArray(items) ? items : [], fallbackUsed: false };\n}\n\n// --- GitHub helpers and cookbook scrapers ---\nfunction convertGithubToRawUrls(githubUrl) {\n const urls = [];\n const refsHeadsUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/refs/heads/')\n .replace('/tree/', '/refs/heads/');\n urls.push(refsHeadsUrl);\n const directUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/')\n .replace('/tree/', '/');\n urls.push(directUrl);\n if (githubUrl.includes('raw.githubusercontent.com')) urls.push(githubUrl);\n return urls;\n}\n\nasync function tryFetchJsonFromPossibleUrls(possibleUrls) {\n for (const u of possibleUrls) {\n try {\n const resp = await fetch(u);\n if (!resp.ok) continue;\n const contentType = resp.headers.get('content-type') || '';\n if (contentType.includes('application/json')) {\n const json = await resp.json();\n return json;\n }\n const text = await resp.text();\n try {\n const parsed = JSON.parse(text);\n return parsed;\n } catch (_) {}\n } catch (_) {}\n }\n return null;\n}\n\nexport function githubApiHeaders() {\n const headers = {\n accept: 'application/vnd.github+json',\n 'user-agent': 'GroqCookbookScraper/1.0 (+https://labspace.ai)'\n };\n try {\n const token = (typeof Deno !== 'undefined' && Deno.env) ? (Deno.env.get('GITHUB_TOKEN') || Deno.env.get('GH_TOKEN')) : null;\n if (token) headers['authorization'] = `Bearer ${token}`;\n } catch (_) {}\n return headers;\n}\n\nexport function slugifyTitle(title) {\n if (!title) return null;\n return title.toLowerCase().replace(/[^a-z0-9]+/g, '-').replace(/(^-|-$)+/g, '');\n}\n\nexport function parseGithubDirUrl(dirUrl) {\n try {\n const m = dirUrl.match(/^https?:\\/\\/github\\.com\\/([^/]+)\\/([^/]+)\\/tree\\/([^/]+)\\/?(.*)$/);\n if (!m) return null;\n const [, org, repo, branch, pathRest] = m;\n const dirPath = (pathRest || '').replace(/^\\/+|\\/+$/g, '');\n return { org, repo, branch, dirPath };\n } catch (_) {\n return null;\n }\n}\n\nfunction buildRawBase({ org, repo, branch, dirPath }) {\n const suffix = dirPath ? `/${dirPath}` : '';\n return `https://raw.githubusercontent.com/${org}/${repo}/${branch}${suffix}`;\n}\n\nfunction buildGithubApiContentsUrl({ org, repo, branch, dirPath }) {\n const path = dirPath ? `/contents/${dirPath}` : `/contents`;\n return `https://api.github.com/repos/${org}/${repo}${path}?ref=${encodeURIComponent(branch)}`;\n}\n\nasync function fetchReadmeFromGithubDir(dirUrl) {\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { content: '', rawUrl: null, rawBase: null };\n const rawBase = buildRawBase(info);\n const candidates = [\n `${rawBase}/README.md`, `${rawBase}/Readme.md`, `${rawBase}/readme.md`,\n `${rawBase}/README.MD`, `${rawBase}/README.markdown`, `${rawBase}/README.MARKDOWN`,\n ];\n for (const u of candidates) {\n try {\n const res = await fetch(u);\n if (res.ok) {\n const text = await res.text();\n return { content: text, rawUrl: u, rawBase };\n }\n } catch (_) {}\n }\n // Fallback: list directory contents and try to find a README file\n try {\n const apiUrl = buildGithubApiContentsUrl(info);\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data) && data.length) {\n let readmeEntry = data.find((e) => e && e.type === 'file' && /^readme(\\.|$)/i.test(e.name));\n if (!readmeEntry) readmeEntry = data.find((e) => e && e.type === 'file' && /\\.md$/i.test(e.name));\n if (readmeEntry) {\n const url = `${rawBase.replace(/\\/$/, '')}/${readmeEntry.name}`;\n try {\n const res2 = await fetch(url);\n if (res2.ok) {\n const text = await res2.text();\n return { content: text, rawUrl: url, rawBase };\n }\n } catch (_) {}\n }\n }\n }\n } catch (_) {}\n return { content: '', rawUrl: null, rawBase };\n}\n\nfunction extractTitleAndDescriptionFromMarkdown(md) {\n if (!md) return { title: null, description: null };\n const lines = md.split(/\\r?\\n/);\n let title = null;\n let startIdx = 0;\n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n if (line.startsWith('# ')) { title = line.replace(/^#\\s+/, '').trim(); startIdx = i + 1; break; }\n }\n let description = null;\n let para = [];\n for (let i = startIdx; i < lines.length; i++) {\n const line = lines[i];\n if (/^#{1,6}\\s+/.test(line)) break;\n if (line.trim() === '') { if (para.length) break; continue; }\n para.push(line.trim());\n }\n if (para.length) description = para.join(' ');\n return { title, description };\n}\n\nfunction extractFirstImageUrlFromMarkdown(md, rawBase) {\n if (!md) return null;\n const m = md.match(/!\\[[^\\]]*\\]\$([^)]+)\$/);\n if (!m) return null;\n const url = m[1].trim();\n if (/^https?:\\/\\//i.test(url)) return url;\n if (url.startsWith('/')) return null;\n const base = rawBase?.replace(/\\/$/, '') || '';\n return `${base}/${url}`;\n}\n\nfunction extractFirstIpyNbLinkFromMarkdown(md) {\n if (!md) return null;\n const mdLink = md.match(/\\[[^\\]]*\\]\$([^)]+\\.ipynb(?:\\?[^)]*)?)\$/i);\n if (mdLink) return mdLink[1];\n const plain = md.match(/https?:[^\\s)]+\\.ipynb/gi);\n return plain && plain.length ? plain[0] : null;\n}\n\nfunction extractDemoLinkFromMarkdown(md) {\n if (!md) return null;\n const links = Array.from(md.matchAll(/\\[[^\\]]*\\]\$([^)]+)\$/g)).map(m => m[1]);\n const candidates = links.filter(u => /https?:\\/\\//i.test(u));\n const prefer = candidates.find(u => /(vercel|demo|live|appgen|groqlabs|render|railway|heroku|netlify)/i.test(u));\n return prefer || null;\n}\n\nasync function probeRawFile(rawBase, filename) {\n const url = `${rawBase.replace(/\\/$/, '')}/${filename}`;\n try {\n const head = await fetch(url, { method: 'HEAD' });\n if (head.ok) return { exists: true, url };\n } catch (_) {}\n try {\n const get = await fetch(url, { method: 'GET', headers: { 'range': 'bytes=0-0' } });\n return { exists: get.ok, url };\n } catch (_) { return { exists: false, url }; }\n}\n\nexport async function fetchGithubCookbookFromDir(query) {\n const dirUrl = query?.dir || query?.repoDirUrl;\n if (!dirUrl) return { items: [], fallbackUsed: false, sourceUrl: null };\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { items: [], fallbackUsed: false, sourceUrl: dirUrl };\n const { content, rawUrl, rawBase } = await fetchReadmeFromGithubDir(dirUrl);\n const slugFromPath = (info.dirPath ? info.dirPath.split('/').pop() : null) || null;\n let title = null, description = null, image = null, ipynbLink = null, demoLink = null;\n if (content) {\n const parsed = extractTitleAndDescriptionFromMarkdown(content);\n title = parsed.title || null;\n description = parsed.description || null;\n image = extractFirstImageUrlFromMarkdown(content, rawBase);\n ipynbLink = extractFirstIpyNbLinkFromMarkdown(content);\n demoLink = extractDemoLinkFromMarkdown(content);\n }\n let appExists = false;\n try {\n const apiUrl = buildGithubApiContentsUrl(info);\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) {\n if (!ipynbLink) {\n const nb = data.find((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n if (nb) {\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${nb.name}`;\n }\n }\n const appEntry = data.find((e) => e && e.type === 'file' && e.name === 'app.py');\n appExists = !!appEntry;\n }\n }\n } catch (_) {}\n\n // If neither README/markdown content nor an ipynb exists, skip this folder entirely\n const hasReadableContent = (content && content.trim().length > 0) || !!ipynbLink;\n if (!hasReadableContent) {\n // However, if this folder has child directories, allow it to pass when nested scraping is enabled upstream\n return { items: [], fallbackUsed: false, sourceUrl: dirUrl };\n }\n\n if (!title) title = slugifyTitle(slugFromPath || '') || slugFromPath || dirUrl;\n const item = {\n slug: slugifyTitle(title) || slugFromPath,\n title,\n description,\n image: image || null,\n imageFit: 'cover',\n username: null,\n avatarUrl: null,\n github: dirUrl,\n demo: demoLink || null,\n language: appExists ? 'python' : null,\n difficulty: null,\n tags: [],\n sections: [],\n date: null,\n readmeSource: rawUrl,\n ipynbLink: ipynbLink || null,\n ctas: [ { icon: 'mdi:github', href: dirUrl }, ...(ipynbLink ? [ { icon: 'mdi:notebook', href: ipynbLink } ] : []), ...(demoLink ? [ { icon: 'mdi:play-circle-outline', href: demoLink } ] : []) ],\n authors: [],\n featured: false,\n markdown: null,\n };\n return { items: [item], fallbackUsed: false, sourceUrl: dirUrl };\n}\n\nexport async function fetchGithubCookbooksFromParentDir(query) {\n const parent = query?.parent || query?.parentDir || query?.parentUrl;\n if (!parent) return { items: [], fallbackUsed: false, sourceUrl: null };\n const limit = query?.limit ? Number(query.limit) : undefined;\n const nested = String(query?.nested || \"\").toLowerCase() === \"1\" || String(query?.nested || \"\").toLowerCase() === \"true\";\n const info = parseGithubDirUrl(parent);\n const apiUrl = info ? buildGithubApiContentsUrl(info) : null;\n let entries = [];\n if (apiUrl) {\n try {\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) entries = data;\n }\n } catch (_) {}\n }\n const dirEntries = entries.filter((e) => e && e.type === 'dir').map((d) => ({\n name: d.name,\n url: `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${d.path}`\n }));\n let nestedDirEntries = [];\n for (const d of dirEntries) {\n try {\n const childInfo = parseGithubDirUrl(d.url);\n const childApiUrl = childInfo ? buildGithubApiContentsUrl(childInfo) : null;\n if (!childApiUrl) continue;\n const res = await fetch(childApiUrl, { headers: githubApiHeaders() });\n if (!res.ok) continue;\n const data = await res.json();\n if (!Array.isArray(data)) continue;\n const subs = data.filter((e) => e && e.type === 'dir').map((sd) => ({\n name: sd.name,\n url: `https://github.com/${childInfo.org}/${childInfo.repo}/tree/${childInfo.branch}/${sd.path}`\n }));\n nestedDirEntries.push(...subs);\n } catch (_) {}\n }\n const nbFiles = entries.filter((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n // Always include both first-level dirs and one-level nested dirs (deduped)\n const unionDirs = Array.from(new Map([...dirEntries, ...nestedDirEntries].map((d) => [d.url, d])).values());\n const baseList = unionDirs;\n const selectedDirs = typeof limit === 'number' && limit > 0 ? baseList.slice(0, limit) : baseList;\n const dirResults = await Promise.all(selectedDirs.map((d) => fetchGithubCookbookFromDir({ dir: d.url })));\n const dirItems = dirResults.flatMap((r) => r.items || []);\n const fileItems = nbFiles.map((f) => {\n const slug = slugifyTitle(f.name.replace(/\\.ipynb$/i, '')) || f.name.replace(/\\.ipynb$/i, '');\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n const ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${f.name}`;\n // Prefer a folder URL if present, otherwise use parent URL\n const github = parent || `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${info.dirPath || ''}`.replace(/\\/$/, '');\n return {\n slug, title: slug, description: null, image: null, imageFit: 'cover', username: null, avatarUrl: null,\n github, demo: null, language: null, difficulty: null, tags: [], sections: [], date: null,\n readmeSource: null, ipynbLink, ctas: [ { icon: 'mdi:notebook', href: ipynbLink } ], authors: [], featured: false, markdown: null,\n };\n });\n const items = [...dirItems, ...fileItems];\n return { items, fallbackUsed: false, sourceUrl: parent };\n}\n\nexport function getGroqCookbookRootItem() {\n const repoRoot = \"https://github.com/groq/groq-api-cookbook/tree/main\";\n const rawLogo = \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/images/groq-logo.png\";\n return {\n slug: \"groq-api-cookbook\",\n title: \"Groq API Cookbook\",\n description: \"Getting Started • Tutorials • Questions • Bug Reporting • Contributing\",\n image: rawLogo,\n imageFit: \"cover\",\n username: \"Groq\",\n avatarUrl: \"https://console.groq.com/groq-circle.png\",\n github: repoRoot,\n demo: null,\n language: null,\n difficulty: null,\n tags: [\"overview\", \"cookbook\"],\n sections: [\"overview\"],\n date: null,\n readmeSource: \"https://github.com/groq/groq-api-cookbook/blob/main/README.md\",\n ipynbLink: null,\n ctas: [\n { icon: \"mdi:github\", href: repoRoot },\n { icon: \"mdi:book-open-outline\", href: \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\" },\n { icon: \"mdi:help-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/discussions\" },\n { icon: \"mdi:alert-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/issues\" },\n { icon: \"mdi:account-plus-outline\", href: \"https://github.com/groq/groq-api-cookbook/blob/main/CONTRIBUTING.md\" }\n ],\n authors: [],\n featured: true,\n markdown: \"Groq API Cookbook — Getting Started, Tutorials, Questions, Bug Reporting, Contributing\",\n };\n}\n\n\n",[165],"787227aa-7fb8-11f0-a63d-0224a6c84d84","deno.lock","7872285e-7fb8-11f0-a63d-0224a6c84d84",6,["D",1755909071987],"{\n \"version\": \"5\",\n \"specifiers\": {\n \"jsr:@smallweb/sandbox@0.1.0\": \"0.1.0\",\n \"jsr:@std/dotenv@*\": \"0.225.2\",\n \"jsr:@std/encoding@1.0.8\": \"1.0.8\",\n \"jsr:@std/html@1.0.3\": \"1.0.3\",\n \"jsr:@std/http@1.0.12\": \"1.0.12\",\n \"npm:@google/generative-ai@*\": \"0.17.1\",\n \"npm:@valtown/sdk@*\": \"0.21.2\",\n \"npm:git-repo-parser@*\": \"2.0.7\",\n \"npm:graphemer@*\": \"1.4.0\",\n \"npm:hono@*\": \"4.6.3\",\n \"npm:js-tiktoken@*\": \"1.0.15\",\n \"npm:marked@*\": \"14.1.0\",\n \"npm:tiktoken@*\": \"1.0.17\",\n \"npm:zod@*\": \"3.23.8\",\n \"npm:zodex@*\": \"0.18.2_zod@3.23.8\"\n },\n \"jsr\": {\n \"@smallweb/sandbox@0.1.0\": {\n \"integrity\": \"840a6120563b20be994fdac3fa858d2cc2e815c6f9b5ea8f14bd02ddd7f71be8\",\n \"dependencies\": [\n \"jsr:@std/encoding\",\n \"jsr:@std/html\",\n \"jsr:@std/http\"\n ]\n },\n \"@std/dotenv@0.225.2\": {\n \"integrity\": \"e2025dce4de6c7bca21dece8baddd4262b09d5187217e231b033e088e0c4dd23\"\n },\n \"@std/encoding@1.0.8\": {\n \"integrity\": \"a6c8f3f933ab1bed66244f435d1dc0fd23a888e07195532122ddc3d5f8f0e6b4\"\n },\n \"@std/html@1.0.3\": {\n \"integrity\": \"7a0ac35e050431fb49d44e61c8b8aac1ebd55937e0dc9ec6409aa4bab39a7988\"\n },\n \"@std/http@1.0.12\": {\n \"integrity\": \"85246d8bfe9c8e2538518725b158bdc31f616e0869255f4a8d9e3de919cab2aa\"\n }\n },\n \"npm\": {\n \"@google/generative-ai@0.17.1\": {\n \"integrity\": \"sha512-TgWz02c5l2XJlEDys81UVat5+Qg9xqmYah7tQt6xlsBwFvzIFPz64aZFGd1av2sxT22NsssqLATjNsusAIJICA==\"\n },\n \"@kwsites/file-exists@1.1.1\": {\n \"integrity\": \"sha512-m9/5YGR18lIwxSFDwfE3oA7bWuq9kdau6ugN4H2rJeyhFQZcG9AgSHkQtSD15a8WvTgfz9aikZMrKPHvbpqFiw==\",\n \"dependencies\": [\n \"debug\"\n ]\n },\n \"@kwsites/promise-deferred@1.1.1\": {\n \"integrity\": \"sha512-GaHYm+c0O9MjZRu0ongGBRbinu8gVAMd2UZjji6jVmqKtZluZnptXGWhz1E8j8D2HJ3f/yMxKAUC0b+57wncIw==\"\n },\n \"@types/node-fetch@2.6.11\": {\n \"integrity\": \"sha512-24xFj9R5+rfQJLRyM56qh+wnVSYhyXC2tkoBndtY0U+vubqNsYXGjufB2nn8Q6gt0LrARwL6UBtMCSVCwl4B1g==\",\n \"dependencies\": [\n \"@types/node@22.5.4\",\n \"form-data\"\n ]\n },\n \"@types/node@18.19.55\": {\n \"integrity\": \"sha512-zzw5Vw52205Zr/nmErSEkN5FLqXPuKX/k5d1D7RKHATGqU7y6YfX9QxZraUzUrFGqH6XzOzG196BC35ltJC4Cw==\",\n \"dependencies\": [\n \"undici-types@5.26.5\"\n ]\n },\n \"@types/node@22.5.4\": {\n \"integrity\": \"sha512-FDuKUJQm/ju9fT/SeX/6+gBzoPzlVCzfzmGkwKvRHQVxi4BntVbyIwf6a4Xn62mrvndLiml6z/UBXIdEVjQLXg==\",\n \"dependencies\": [\n \"undici-types@6.19.8\"\n ]\n },\n \"@valtown/sdk@0.21.2\": {\n \"integrity\": \"sha512-KBHODXnwGtj68SA1hRW+6rba1zu5c2FrYxttGgPemiPGgLoF8Yo29RvNhsA8Qc08bmj5IJS0Mzn0tfqis6Qr+Q==\",\n \"dependencies\": [\n \"@types/node@18.19.55\",\n \"@types/node-fetch\",\n \"abort-controller\",\n \"agentkeepalive\",\n \"form-data-encoder\",\n \"formdata-node\",\n \"node-fetch\"\n ]\n },\n \"abort-controller@3.0.0\": {\n \"integrity\": \"sha512-h8lQ8tacZYnR3vNQTgibj+tODHI5/+l06Au2Pcriv/Gmet0eaj4TwWH41sO9wnHDiQsEj19q0drzdWdeAHtweg==\",\n \"dependencies\": [\n \"event-target-shim\"\n ]\n },\n \"agentkeepalive@4.5.0\": {\n \"integrity\": \"sha512-5GG/5IbQQpC9FpkRGsSvZI5QYeSCzlJHdpBQntCsuTOxhKD8lqKhrleg2Yi7yvMIf82Ycmmqln9U8V9qwEiJew==\",\n \"dependencies\": [\n \"humanize-ms\"\n ]\n },\n \"asynckit@0.4.0\": {\n \"integrity\": \"sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q==\"\n },\n \"base64-js@1.5.1\": {\n \"integrity\": \"sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA==\"\n },\n \"combined-stream@1.0.8\": {\n \"integrity\": \"sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg==\",\n \"dependencies\": [\n \"delayed-stream\"\n ]\n },\n \"debug@4.3.7\": {\n \"integrity\": \"sha512-Er2nc/H7RrMXZBFCEim6TCmMk02Z8vLC2Rbi1KEBggpo0fS6l0S1nnapwmIi3yW/+GOJap1Krg4w0Hg80oCqgQ==\",\n \"dependencies\": [\n \"ms\"\n ]\n },\n \"delayed-stream@1.0.0\": {\n \"integrity\": \"sha512-ZySD7Nf91aLB0RxL4KGrKHBXl7Eds1DAmEdcoVawXnLD7SDhpNgtuII2aAkg7a7QS41jxPSZ17p4VdGnMHk3MQ==\"\n },\n \"event-target-shim@5.0.1\": {\n \"integrity\": \"sha512-i/2XbnSz/uxRCU6+NdVJgKWDTM427+MqYbkQzD321DuCQJUqOuJKIA0IM2+W2xtYHdKOmZ4dR6fExsd4SXL+WQ==\"\n },\n \"form-data-encoder@1.7.2\": {\n \"integrity\": \"sha512-qfqtYan3rxrnCk1VYaA4H+Ms9xdpPqvLZa6xmMgFvhO32x7/3J/ExcTd6qpxM0vH2GdMI+poehyBZvqfMTto8A==\"\n },\n \"form-data@4.0.1\": {\n \"integrity\": \"sha512-tzN8e4TX8+kkxGPK8D5u0FNmjPUjw3lwC9lSLxxoB/+GtsJG91CO8bSWy73APlgAZzZbXEYZJuxjkHH2w+Ezhw==\",\n \"dependencies\": [\n \"asynckit\",\n \"combined-stream\",\n \"mime-types\"\n ]\n },\n \"formdata-node@4.4.1\": {\n \"integrity\": \"sha512-0iirZp3uVDjVGt9p49aTaqjk84TrglENEDuqfdlZQ1roC9CWlPk6Avf8EEnZNcAqPonwkG35x4n3ww/1THYAeQ==\",\n \"dependencies\": [\n \"node-domexception\",\n \"web-streams-polyfill\"\n ]\n },\n \"git-repo-parser@2.0.7\": {\n \"integrity\": \"sha512-51bz2UL04epQnxR4eZC1CaQXVtpEnhtekRs4UeTkiio74kYcIfSsaSb4kLPHuDbJaEuLEZeGNjh63bJkVhCQHw==\",\n \"dependencies\": [\n \"simple-git\"\n ],\n \"bin\": true\n },\n \"graphemer@1.4.0\": {\n \"integrity\": \"sha512-EtKwoO6kxCL9WO5xipiHTZlSzBm7WLT627TqC/uVRd0HKmq8NXyebnNYxDoBi7wt8eTWrUrKXCOVaFq9x1kgag==\"\n },\n \"hono@4.6.3\": {\n \"integrity\": \"sha512-0LeEuBNFeSHGqZ9sNVVgZjB1V5fmhkBSB0hZrpqStSMLOWgfLy0dHOvrjbJh0H2khsjet6rbHfWTHY0kpYThKQ==\"\n },\n \"humanize-ms@1.2.1\": {\n \"integrity\": \"sha512-Fl70vYtsAFb/C06PTS9dZBo7ihau+Tu/DNCk/OyHhea07S+aeMWpFFkUaXRa8fI+ScZbEI8dfSxwY7gxZ9SAVQ==\",\n \"dependencies\": [\n \"ms\"\n ]\n },\n \"js-tiktoken@1.0.15\": {\n \"integrity\": \"sha512-65ruOWWXDEZHHbAo7EjOcNxOGasQKbL4Fq3jEr2xsCqSsoOo6VVSqzWQb6PRIqypFSDcma4jO90YP0w5X8qVXQ==\",\n \"dependencies\": [\n \"base64-js\"\n ]\n },\n \"marked@14.1.0\": {\n \"integrity\": \"sha512-P93GikH/Pde0hM5TAXEd8I4JAYi8IB03n8qzW8Bh1BIEFpEyBoYxi/XWZA53LSpTeLBiMQOoSMj0u5E/tiVYTA==\",\n \"bin\": true\n },\n \"mime-db@1.52.0\": {\n \"integrity\": \"sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg==\"\n },\n \"mime-types@2.1.35\": {\n \"integrity\": \"sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw==\",\n \"dependencies\": [\n \"mime-db\"\n ]\n },\n \"ms@2.1.3\": {\n \"integrity\": \"sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA==\"\n },\n \"node-domexception@1.0.0\": {\n \"integrity\": \"sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ==\",\n \"deprecated\": true\n },\n \"node-fetch@2.7.0\": {\n \"integrity\": \"sha512-c4FRfUm/dbcWZ7U+1Wq0AwCyFL+3nt2bEw05wfxSz+DWpWsitgmSgYmy2dQdWyKC1694ELPqMs/YzUSNozLt8A==\",\n \"dependencies\": [\n \"whatwg-url\"\n ],\n \"optionalPeers\": [\n \"encoding@^0.1.0\"\n ]\n },\n \"simple-git@2.48.0\": {\n \"integrity\": \"sha512-z4qtrRuaAFJS4PUd0g+xy7aN4y+RvEt/QTJpR184lhJguBA1S/LsVlvE/CM95RsYMOFJG3NGGDjqFCzKU19S/A==\",\n \"dependencies\": [\n \"@kwsites/file-exists\",\n \"@kwsites/promise-deferred\",\n \"debug\"\n ]\n },\n \"tiktoken@1.0.17\": {\n \"integrity\": \"sha512-UuFHqpy/DxOfNiC3otsqbx3oS6jr5uKdQhB/CvDEroZQbVHt+qAK+4JbIooabUWKU9g6PpsFylNu9Wcg4MxSGA==\"\n },\n \"tr46@0.0.3\": {\n \"integrity\": \"sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==\"\n },\n \"type-fest@4.26.1\": {\n \"integrity\": \"sha512-yOGpmOAL7CkKe/91I5O3gPICmJNLJ1G4zFYVAsRHg7M64biSnPtRj0WNQt++bRkjYOqjWXrhnUw1utzmVErAdg==\"\n },\n \"undici-types@5.26.5\": {\n \"integrity\": \"sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA==\"\n },\n \"undici-types@6.19.8\": {\n \"integrity\": \"sha512-ve2KP6f/JnbPBFyobGHuerC9g1FYGn/F8n1LWTwNxCEzd6IfqTwUQcNXgEtmmQ6DlRrC1hrSrBnCZPokRrDHjw==\"\n },\n \"web-streams-polyfill@4.0.0-beta.3\": {\n \"integrity\": \"sha512-QW95TCTaHmsYfHDybGMwO5IJIM93I/6vTRk+daHTWFPhwh+C8Cg7j7XyKrwrj8Ib6vYXe0ocYNrmzY4xAAN6ug==\"\n },\n \"webidl-conversions@3.0.1\": {\n \"integrity\": \"sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==\"\n },\n \"whatwg-url@5.0.0\": {\n \"integrity\": \"sha512-saE57nupxk6v3HY35+jzBwYa0rKSy0XR8JSxZPwgLr7ys0IBzhGviA1/TUGJLmSVqs8pb9AnvICXEuOHLprYTw==\",\n \"dependencies\": [\n \"tr46\",\n \"webidl-conversions\"\n ]\n },\n \"zod@3.23.8\": {\n \"integrity\": \"sha512-XBx9AXhXktjUqnepgTiE5flcKIYWi/rme0Eaj+5Y0lftuGBq+jyRu/md4WnuxqgP1ubdpNCsYEYPxrzVHD8d6g==\"\n },\n \"zodex@0.18.2_zod@3.23.8\": {\n \"integrity\": \"sha512-GE0/S68lJhhBhJWeOSvq4BCigrguOeKFr7h3sbsMPd6kF4ZCHeVU/hOzNLHlj6d+ezNXcpQ4nHj6purY5RxQBg==\",\n \"dependencies\": [\n \"type-fest\",\n \"zod\"\n ]\n }\n },\n \"remote\": {\n \"https://deno.land/x/hono@v3.11.7/client/client.ts\": \"ff340f58041203879972dd368b011ed130c66914f789826610869a90603406bf\",\n \"https://deno.land/x/hono@v3.11.7/client/index.ts\": \"3ff4cf246f3543f827a85a2c84d66a025ac350ee927613629bda47e854bfb7ba\",\n \"https://deno.land/x/hono@v3.11.7/client/types.ts\": \"ca165b8738d384361b927964466ecc8bc1436edad3d0414e30a28f40ba4ca496\",\n \"https://deno.land/x/hono@v3.11.7/client/utils.ts\": \"053273c002963b549d38268a1b423ac8ca211a8028bdab1ed0b781a62aa5e661\",\n \"https://deno.land/x/hono@v3.11.7/compose.ts\": \"37d6e33b7db80e4c43a0629b12fd3a1e3406e7d9e62a4bfad4b30426ea7ae4f1\",\n \"https://deno.land/x/hono@v3.11.7/context.ts\": \"5cac561498e1f4af7a355673a047f07f47349056c5167ed9aec8a20cdcac8464\",\n \"https://deno.land/x/hono@v3.11.7/helper.ts\": \"719df05d8deefb5986ccdb0051f892a837dd8b91e48cd6db43fef237153f1057\",\n \"https://deno.land/x/hono@v3.11.7/helper/adapter/index.ts\": \"eea9b4caedbfa3a3b4a020bf46c88c0171a00008cd6c10708cd85a3e39d86e62\",\n \"https://deno.land/x/hono@v3.11.7/helper/cookie/index.ts\": \"a05ce7e3bafe1f8c7f45d04abf79822716011be75904fe1aad2e99126fd985b9\",\n \"https://deno.land/x/hono@v3.11.7/helper/dev/index.ts\": \"e78ee9d96713211f957e89df180aaa48f8ce9407a938979b393a79547d7f8029\",\n \"https://deno.land/x/hono@v3.11.7/helper/factory/index.ts\": \"45c9f0a981c23d6b5e481697637b0f66fec3234aec442d0cb285048b07ed54c6\",\n \"https://deno.land/x/hono@v3.11.7/helper/html/index.ts\": \"a4ac61c54cd432e708dd019aced59273e5e053933f4804b0b5758d9916468b3e\",\n \"https://deno.land/x/hono@v3.11.7/helper/streaming/index.ts\": \"90dd4424d8d8271efd602ab7a8fcc0539a1573c98ee03e4c910bc0bbd7d20f27\",\n \"https://deno.land/x/hono@v3.11.7/helper/testing/index.ts\": \"bc49c049aa0d6426417e3d1a2f52a471a09edb1fb8610b7545eae1968e7d7874\",\n \"https://deno.land/x/hono@v3.11.7/hono-base.ts\": \"ab40351c5198cedef9e235ca0a958a161fec822b62aa7fb1eaa36559dc05e0d5\",\n \"https://deno.land/x/hono@v3.11.7/hono.ts\": \"2cc4c292e541463a4d6f83edbcea58048d203e9564ae62ec430a3d466b49a865\",\n \"https://deno.land/x/hono@v3.11.7/http-exception.ts\": \"6071df078b5f76d279684d52fe82a590f447a64ffe1b75eb5064d0c8a8d2d676\",\n \"https://deno.land/x/hono@v3.11.7/mod.ts\": \"90114a97be9111b348129ad0143e764a64921f60dd03b8f3da529db98a0d3a82\",\n \"https://deno.land/x/hono@v3.11.7/request.ts\": \"71a67261d14bba95e9a8b4782a1c1704d12d54a77390ce404741df15ab99a109\",\n \"https://deno.land/x/hono@v3.11.7/router.ts\": \"880316f561918fc197481755aac2165fdbe2f530b925c5357a9f98d6e2cc85c7\",\n \"https://deno.land/x/hono@v3.11.7/router/linear-router/index.ts\": \"8a2a7144c50b1f4a92d9ee99c2c396716af144c868e10608255f969695efccd0\",\n \"https://deno.land/x/hono@v3.11.7/router/linear-router/router.ts\": \"bc63e8b5bc1dabc815306d50bebd1bb5877ffa3936ba2ad7550d093c95ee6bd1\",\n \"https://deno.land/x/hono@v3.11.7/router/pattern-router/index.ts\": \"304a66c50e243872037ed41c7dd79ed0c89d815e17e172e7ad7cdc4bc07d3383\",\n \"https://deno.land/x/hono@v3.11.7/router/pattern-router/router.ts\": \"a9a5a2a182cce8c3ae82139892cc0502be7dd8f579f31e76d0302b19b338e548\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/index.ts\": \"52755829213941756159b7a963097bafde5cc4fc22b13b1c7c9184dc0512d1db\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/node.ts\": \"5b3fb80411db04c65df066e69fedb2c8c0844753c2633d703336de84d569252c\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/router.ts\": \"7f7af7ce45a4327f9ac7dbdee186f7ba9a24f2eff14c720e3f670be001e71780\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/trie.ts\": \"852ce7207e6701e47fa30889a0d2b8bfcd56d8862c97e7bc9831e0a64bd8835f\",\n \"https://deno.land/x/hono@v3.11.7/router/smart-router/index.ts\": \"74f9b4fe15ea535900f2b9b048581915f12fe94e531dd2b0032f5610e61c3bef\",\n \"https://deno.land/x/hono@v3.11.7/router/smart-router/router.ts\": \"f1848a2a1eefa316a11853ae12e749552747771fb8a11fe713ae04ea6461140b\",\n \"https://deno.land/x/hono@v3.11.7/router/trie-router/index.ts\": \"3eb75e7f71ba81801631b30de6b1f5cefb2c7239c03797e2b2cbab5085911b41\",\n \"https://deno.land/x/hono@v3.11.7/router/trie-router/node.ts\": \"e9ea493da22913b2e60a88284c5edb5330506f2ceb0ac631909219bb139c4b60\",\n \"https://deno.land/x/hono@v3.11.7/router/trie-router/router.ts\": \"54ced78d35676302c8fcdda4204f7bdf5a7cc907fbf9967c75674b1e394f830d\",\n \"https://deno.land/x/hono@v3.11.7/types.ts\": \"82f95c64c13c21129130d7bb383956306e19d23b3e986c02c914d7aa08808d1d\",\n \"https://deno.land/x/hono@v3.11.7/utils/body.ts\": \"7a16a6656331a96bcae57642f8d5e3912bd361cbbcc2c0d2157ecc3f218f7a92\",\n \"https://deno.land/x/hono@v3.11.7/utils/buffer.ts\": \"9066a973e64498cb262c7e932f47eed525a51677b17f90893862b7279dc0773e\",\n \"https://deno.land/x/hono@v3.11.7/utils/cookie.ts\": \"19920ba6756944aae1ad8585c3ddeaa9df479733f59d05359db096f7361e5e4b\",\n \"https://deno.land/x/hono@v3.11.7/utils/crypto.ts\": \"bda0e141bbe46d3a4a20f8fbcb6380d473b617123d9fdfa93e4499410b537acc\",\n \"https://deno.land/x/hono@v3.11.7/utils/html.ts\": \"4d2f3975238819fa756e0e51cb7090702136b1e3c54c5049694e26c62d2fcd84\",\n \"https://deno.land/x/hono@v3.11.7/utils/http-status.ts\": \"e0c4343ea7717c314dc600131e16b636c29d61cfdaf9df93b267258d1729d1a0\",\n \"https://deno.land/x/hono@v3.11.7/utils/stream.ts\": \"1789dcc73c5b0ede28f83d7d34e47ae432c20e680907cb3275a9c9187f293983\",\n \"https://deno.land/x/hono@v3.11.7/utils/types.ts\": \"41c4e7d8028f3dec43ff7c26e9498fed53d9ec7c3b47071d066b40f7b7a8ef58\",\n \"https://deno.land/x/hono@v3.11.7/utils/url.ts\": \"5fc3307ef3cb2e6f34ec2a03e3d7f2126c6a9f5f0eab677222df3f0e40bd7567\",\n \"https://deno.land/x/hono@v3.11.7/validator/index.ts\": \"6c986e8b91dcf857ecc8164a506ae8eea8665792a4ff7215471df669c632ae7c\",\n \"https://deno.land/x/hono@v3.11.7/validator/validator.ts\": \"f6139f0b6eb2040bc9f7ed4148905d5affc898235952772b2d6585fdae8d4731\"\n }\n}\n",[172],"78698398-7fb8-11f0-9730-0224a6c84d84","deno.json","78698488-7fb8-11f0-9730-0224a6c84d84",4,["D",1755909071853],"{\n \"name\": \"labkit\",\n \"description\": \"A design kit for labspace\",\n \"tasks\": {\n \"serve\": \"deno serve --port 8012 --watch --allow-read --allow-env --allow-import --allow-write --allow-net ./main.js\",\n \"snapshot\": \"deno run --allow-read --allow-env --allow-write --allow-net ./snapshot.js\"\n },\n \"$schema\": \"https://raw.githubusercontent.com/denoland/deno/348900b8b79f4a434cab4c74b3bc8d4d2fa8ee74/cli/schemas/config-file.v1.json\",\n \"lock\": false,\n \"compilerOptions\": {\n \"noImplicitAny\": false,\n \"strict\": false,\n \"types\": [\n \"https://www.val.town/types/valtown.d.ts\"\n ],\n \"lib\": [\n \"dom\",\n \"dom.iterable\",\n \"dom.asynciterable\",\n \"deno.ns\",\n \"deno.unstable\"\n ]\n },\n \"lint\": {\n \"files\": {\n \"include\": [\n \"deno:/https/esm.town/**/*\"\n ]\n },\n \"rules\": {\n \"exclude\": [\n \"no-explicit-any\"\n ]\n }\n },\n \"node_modules_dir\": false,\n \"experimental\": {\n \"unstable-node-globals\": true,\n \"unstable-temporal\": true,\n \"unstable-worker-options\": true,\n \"unstable-sloppy-imports\": true\n }\n}\n",[179],"788813c6-7fb8-11f0-a529-0224a6c84d84",".vtignore","7888147a-7fb8-11f0-a529-0224a6c84d84",11,["D",1755909072118],".git\n.vscode\n.cursorrules\n.DS_Store\nnode_modules\nvendor",[186],"787b2594-7fb8-11f0-9730-0224a6c84d84",".env","787b262a-7fb8-11f0-9730-0224a6c84d84",8,["D",1755909072046],"GITHUB_TOKEN=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\nGROQ_API_KEY=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",[193],"785d5abe-7fb8-11f0-8880-0224a6c84d84",".cursorrules","785d5b72-7fb8-11f0-8880-0224a6c84d84",2,["D",1755909071853],"You are an advanced assistant specialized in generating Val Town code.\n\n## Core Guidelines\n\n- Ask clarifying questions when requirements are ambiguous\n- Provide complete, functional solutions rather than skeleton implementations\n- Test your logic against edge cases before presenting the final solution\n- Ensure all code follows Val Town's specific platform requirements\n- If a section of code that you're working on is getting too complex, consider refactoring it into subcomponents\n\n## Code Standards\n\n- Generate code in TypeScript or TSX\n- Add appropriate TypeScript types and interfaces for all data structures\n- Prefer official SDKs or libraries than writing API calls directly\n- Ask the user to supply API or library documentation if you are at all unsure about it\n- **Never bake in secrets into the code** - always use environment variables\n- Include comments explaining complex logic (avoid commenting obvious operations)\n- Follow modern ES6+ conventions and functional programming practices if possible\n\n## Types of triggers\n\n### 1. HTTP Trigger\n\n- Create web APIs and endpoints\n- Handle HTTP requests and responses\n- Example structure:\n\n```ts\nexport default async function (req: Request) {\n return new Response(\"Hello World\");\n}\n```\n\nFiles that are HTTP triggers have http in their name like `foobar.http.tsx`\n\n### 2. Cron Triggers\n\n- Run on a schedule\n- Use cron expressions for timing\n- Example structure:\n\n```ts\nexport default async function () {\n // Scheduled task code\n}\n```\n\nFiles that are Cron triggers have cron in their name like `foobar.cron.tsx`\n\n### 3. Email Triggers\n\n- Process incoming emails\n- Handle email-based workflows\n- Example structure:\n\n```ts\nexport default async function (email: Email) {\n // Process email\n}\n```\n\nFiles that are Email triggers have email in their name like `foobar.email.tsx`\n\n\n## Val Town Standard Libraries\n\nVal Town provides several hosted services and utility functions.\n\n### Blob Storage\n\n```ts\nimport { blob } from \"https://esm.town/v/std/blob\";\nawait blob.setJSON(\"myKey\", { hello: \"world\" });\nlet blobDemo = await blob.getJSON(\"myKey\");\nlet appKeys = await blob.list(\"app_\");\nawait blob.delete(\"myKey\");\n```\n\n### SQLite\n\n```ts\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nconst TABLE_NAME = 'todo_app_users_2';\n// Create table - do this before usage and change table name when modifying schema\nawait sqlite.execute(`CREATE TABLE IF NOT EXISTS ${TABLE_NAME} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n name TEXT NOT NULL\n)`);\n// Query data\nconst result = await sqlite.execute(`SELECT * FROM ${TABLE_NAME} WHERE id = ?`, [1]);\n```\n\nNote: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.\n\n### OpenAI\n\n```ts\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nconst openai = new OpenAI();\nconst completion = await openai.chat.completions.create({\n messages: [\n { role: \"user\", content: \"Say hello in a creative way\" },\n ],\n model: \"gpt-4o-mini\",\n max_tokens: 30,\n});\n```\n\n### Email\n\n```ts\nimport { email } from \"https://esm.town/v/std/email\";\n// By default emails the owner of the val\nawait email({ \n subject: \"Hi\", \n text: \"Hi\", \n html: \"

Hi

\"\n});\n```\n\n## Val Town Utility Functions\n\nVal Town provides several utility functions to help with common project tasks.\n\n### Importing Utilities\n\nAlways import utilities with version pins to avoid breaking changes:\n\n```ts\nimport { parseProject, readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n```\n\n### Available Utilities\n\n\n#### **serveFile** - Serve project files with proper content types\n\nFor example, in Hono:\n\n```ts\n// serve all files in frontend/ and shared/\napp.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\napp.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n```\n\n#### **readFile** - Read files from within the project:\n\n```ts\n// Read a file from the project\nconst fileContent = await readFile(\"/frontend/index.html\", import.meta.url);\n```\n\n#### **listFiles** - List all files in the project\n\n```ts\nconst files = await listFiles(import.meta.url);\n```\n\n#### **parseProject** - Extract information about the current project from import.meta.url\n\nThis is useful for including info for linking back to a val, ie in \"view source\" urls:\n\n```ts\nconst projectVal = parseProject(import.meta.url);\nconsole.log(projectVal.username); // Owner of the project\nconsole.log(projectVal.name); // Project name\nconsole.log(projectVal.version); // Version number\nconsole.log(projectVal.branch); // Branch name\nconsole.log(projectVal.links.self.project); // URL to the project page\n```\n\nHowever, it's *extremely importing* to note that `parseProject` and other Standard Library utilities ONLY RUN ON THE SERVER.\nIf you need access to this data on the client, run it in the server and pass it to the client by splicing it into the HTML page\nor by making an API request for it.\n\n## Val Town Platform Specifics\n\n- **Redirects:** Use `return new Response(null, { status: 302, headers: { Location: \"/place/to/redirect\" }})` instead of `Response.redirect` which is broken\n- **Images:** Avoid external images or base64 images. Use emojis, unicode symbols, or icon fonts/libraries instead\n- **AI Image:** To inline generate an AI image use: `

`\n- **Storage:** DO NOT use the Deno KV module for storage\n- **Browser APIs:** DO NOT use the `alert()`, `prompt()`, or `confirm()` methods\n- **Weather Data:** Use open-meteo for weather data (doesn't require API keys) unless otherwise specified\n- **View Source:** Add a view source link by importing & using `import.meta.url.replace(\"ems.sh\", \"val.town)\"` (or passing this data to the client) and include `target=\"_top\"` attribute\n- **Error Debugging:** Add `` to HTML to capture client-side errors\n- **Error Handling:** Only use try...catch when there's a clear local resolution; Avoid catches that merely log or return 500s. Let errors bubble up with full context\n- **Environment Variables:** Use `Deno.env.get('keyname')` when you need to, but generally prefer APIs that don't require keys\n- **Imports:** Use `https://esm.sh` for npm and Deno dependencies to ensure compatibility on server and browser\n- **Storage Strategy:** Only use backend storage if explicitly required; prefer simple static client-side sites\n- **React Configuration:** When using React libraries, pin versions with `?deps=react@18.2.0,react-dom@18.2.0` and start the file with `/** @jsxImportSource https://esm.sh/react@18.2.0 */`\n- Ensure all React dependencies and sub-dependencies are pinned to the same version\n- **Styling:** Default to using TailwindCSS via `` unless otherwise specified\n\n## Project Structure and Design Patterns\n\n### Recommended Directory Structure\n```\n├── backend/\n│ ├── database/\n│ │ ├── migrations.ts # Schema definitions\n│ │ ├── queries.ts # DB query functions\n│ │ └── README.md\n│ └── routes/ # Route modules\n│ ├── [route].ts\n│ └── static.ts # Static file serving\n│ ├── index.ts # Main entry point\n│ └── README.md\n├── frontend/\n│ ├── components/\n│ │ ├── App.tsx\n│ │ └── [Component].tsx\n│ ├── favicon.svg\n│ ├── index.html # Main HTML template\n│ ├── index.tsx # Frontend JS entry point\n│ ├── README.md\n│ └── style.css\n├── README.md\n└── shared/\n ├── README.md\n └── utils.ts # Shared types and functions\n```\n\n### Backend (Hono) Best Practices\n\n- Hono is the recommended API framework\n- Main entry point should be `backend/index.ts`\n- **Static asset serving:** Use the utility functions to read and serve project files:\n ```ts\n import { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n \n // serve all files in frontend/ and shared/\n app.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\n app.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n \n // For index.html, often you'll want to bootstrap with initial data\n app.get(\"/\", async c => {\n let html = await readFile(\"/frontend/index.html\", import.meta.url);\n \n // Inject data to avoid extra round-trips\n const initialData = await fetchInitialData();\n const dataScript = ``;\n \n html = html.replace(\"\", `${dataScript}`);\n return c.html(html);\n });\n ```\n- Create RESTful API routes for CRUD operations\n- Always include this snippet at the top-level Hono app to re-throwing errors to see full stack traces:\n ```ts\n // Unwrap Hono errors to see original error details\n app.onError((err, c) => {\n throw err;\n });\n ```\n\n### Database Patterns\n- Run migrations on startup or comment out for performance\n- Change table names when modifying schemas rather than altering\n- Export clear query functions with proper TypeScript typing\n\n## Common Gotchas and Solutions\n\n1. **Environment Limitations:** \n - Val Town runs on Deno in a serverless context, not Node.js\n - Code in `shared/` must work in both frontend and backend environments\n - Cannot use `Deno` keyword in shared code\n - Use `https://esm.sh` for imports that work in both environments\n\n2. **SQLite Peculiarities:**\n - Limited support for ALTER TABLE operations\n - Create new tables with updated schemas and copy data when needed\n - Always run table creation before querying\n\n3. **React Configuration:**\n - All React dependencies must be pinned to 18.2.0\n - Always include `@jsxImportSource https://esm.sh/react@18.2.0` at the top of React files\n - Rendering issues often come from mismatched React versions\n\n4. **File Handling:**\n - Val Town only supports text files, not binary\n - Use the provided utilities to read files across branches and forks\n - For files in the project, use `readFile` helpers\n\n5. **API Design:**\n - `fetch` handler is the entry point for HTTP vals\n - Run the Hono app with `export default app.fetch // This is the entry point for HTTP vals`\n\n",[200],"784b689a-7fb8-11f0-8880-0224a6c84d84",".vscode","784b693a-7fb8-11f0-8880-0224a6c84d84",["D",1755909071734],"directory",[207],"pulls","branches","forks","envVars",{"_219":62,"_221":62},"connections",{"_219":62,"_220":62},"count","unfilledCount","emptyCount",{"_43":206,"_32":207,"_30":208,"_139":-5,"_41":42,"_40":162,"_141":58,"_38":273,"_13":62,"_33":210,"_35":-5,"_24":25,"_144":-5,"_235":274,"_27":275},{"_43":265,"_32":266,"_30":267,"_139":208,"_41":42,"_40":268,"_141":58,"_38":269,"_13":62,"_33":20,"_35":270,"_24":25,"_144":-5,"_235":271,"_27":272},{"_43":199,"_32":200,"_30":201,"_139":-5,"_41":42,"_40":202,"_141":58,"_38":262,"_13":62,"_33":20,"_35":204,"_24":25,"_144":-5,"_235":263,"_27":264},{"_43":192,"_32":193,"_30":194,"_139":-5,"_41":42,"_40":195,"_141":58,"_38":259,"_13":62,"_33":20,"_35":197,"_24":25,"_144":-5,"_235":260,"_27":261},{"_43":185,"_32":186,"_30":187,"_139":-5,"_41":42,"_40":188,"_141":58,"_38":256,"_13":62,"_33":20,"_35":190,"_24":25,"_144":-5,"_235":257,"_27":258},{"_43":178,"_32":179,"_30":180,"_139":-5,"_41":42,"_40":181,"_141":58,"_38":253,"_13":62,"_33":20,"_35":183,"_24":25,"_144":-5,"_235":254,"_27":255},{"_43":171,"_32":172,"_30":173,"_139":-5,"_41":42,"_40":174,"_141":58,"_38":250,"_13":62,"_33":20,"_35":176,"_24":25,"_144":-5,"_235":251,"_27":252},{"_43":164,"_32":165,"_30":166,"_139":-5,"_41":42,"_40":167,"_141":58,"_38":247,"_13":62,"_33":34,"_35":169,"_24":25,"_144":-5,"_235":248,"_27":249},{"_43":160,"_32":28,"_30":31,"_139":-5,"_41":42,"_40":14,"_141":25,"_38":244,"_13":162,"_33":37,"_35":36,"_24":25,"_144":45,"_235":245,"_27":246},{"_43":153,"_32":154,"_30":155,"_139":-5,"_41":42,"_40":156,"_141":25,"_38":241,"_13":62,"_33":20,"_35":158,"_24":25,"_144":-5,"_235":242,"_27":243},{"_43":146,"_32":147,"_30":148,"_139":-5,"_41":42,"_40":149,"_141":25,"_38":238,"_13":62,"_33":34,"_35":151,"_24":25,"_144":-5,"_235":239,"_27":240},{"_43":136,"_32":137,"_30":138,"_139":-5,"_41":42,"_40":140,"_141":58,"_38":234,"_13":62,"_33":34,"_35":143,"_24":25,"_144":-5,"_235":236,"_27":237},["D",1755909072185],"children",[],[137],["D",1755909072047],[],[147],["D",1755909071979],[],[154],["D",1755909106957],[],[28],["D",1755909071854],[],[165],["D",1755909071987],[],[172],["D",1755909071853],[],[179],["D",1755909072118],[],[186],["D",1755909072046],[],[193],["D",1755909071853],[],[200],"788513d8-7fb8-11f0-a63d-0224a6c84d84","extensions.json","7885148c-7fb8-11f0-a63d-0224a6c84d84",10,["D",1755909072112],"{\n \"recommendations\": [\n \"denoland.vscode-deno\"\n ]\n}",[],[207,266],["D",1755909071734],[223],[207],["D",1755909071355],{"_96":95,"_103":99},{"_96":95,"_97":-5,"_98":99,"_18":55,"_100":101,"_102":25},{"_13":85,"_32":86,"_43":42,"_87":44,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":-5,"_93":45,"_94":95},"ctx",{"_78":-5,"_122":313,"_314":315,"_316":317,"_318":25,"_319":25,"_320":25,"_321":58,"_322":-5,"_323":-7,"_324":-7,"_325":62,"_326":25,"_327":25,"_328":-5,"_329":25,"_330":25,"_331":25,"_332":-5},"ENV",{"_284":285,"_286":287,"_288":86,"_289":290,"_291":292,"_293":294,"_295":296,"_297":298,"_299":300,"_301":302,"_303":304,"_305":306,"_307":308,"_309":310,"_311":312},"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"]

Boink

\n \n What is Boink?\n \n \n \n \n \n

\n \n How do I use it?\n \n \n \n \n \n

Hi

\n \n

\n \n

Diff · v13