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return crypto.randomUUID(); } catch (_) { return (Date.now().toString(36) + Math.random().toString(36).slice(2)); }\n}\n\nfunction nowTs() { return Date.now(); }\n\nfunction summarizeJob(job) {\n return {\n id: job.id,\n running: !!job.running,\n cancelled: !!job.cancelled,\n total: job.total | 0,\n completed: job.completed | 0,\n createdAt: job.createdAt,\n updatedAt: job.updatedAt,\n systemPrompt: job.systemPrompt || '',\n items: job.items.map((it) => ({ id: it.id, email: it.email, status: it.status, result: it.result || null, error: it.error || null }))\n };\n}\n\nasync function runAsyncJob(job, apiKey, concurrency) {\n if (!Array.isArray(job.items) || job.items.length === 0) { job.running = false; job.updatedAt = nowTs(); return; }\n job.running = true; job.cancelled = false; job.updatedAt = nowTs();\n const systemPrompt = job.systemPrompt || '';\n const indices = job.items.map((_, i) => i);\n job.total = indices.length; job.completed = 0;\n\n // Pre-mark pending as checking\n for (const idx of indices) {\n const it = job.items[idx];\n if (!it) continue;\n if (it.status === 'done' || it.status === 'error') continue;\n it.status = 'checking';\n }\n job.updatedAt = nowTs();\n\n const limit = Math.max(1, Number(concurrency || 8) || 8);\n let cursor = 0;\n const runNext = async () => {\n if (job.cancelled) return;\n if (cursor >= indices.length) return;\n const idx = indices[cursor++];\n const item = job.items[idx];\n if (!item) return runNext();\n if (item.status === 'done' || item.status === 'error') { job.completed++; return runNext(); }\n try {\n const res = await backgroundAssessEmail(apiKey, item.email, systemPrompt);\n item.result = res;\n item.status = 'done';\n } catch (err) {\n item.error = err && err.message ? err.message : String(err);\n item.status = 'error';\n } finally {\n job.completed++;\n job.updatedAt = nowTs();\n await runNext();\n }\n };\n const runners = [];\n for (let k = 0; k < limit; k++) runners.push(runNext());\n try { await Promise.all(runners); } catch (_) {}\n job.running = false; job.updatedAt = nowTs();\n}\n\n\n// Helper: Collect readable text from tool records for URL-grounded extraction\nfunction collectToolTextFromArray(toolArray) {\n if (!Array.isArray(toolArray)) return '';\n const parts = [];\n for (const t of toolArray) {\n try {\n const name = t?.name || t?.tool || t?.function?.name || t?.id || '';\n const args = t?.arguments || t?.input || t?.params || null;\n const output = t?.output || t?.result || t?.content || null;\n const searchResults = t?.search_results || t?.results || null;\n if (name) parts.push('name: ' + String(name));\n if (args) parts.push('arguments: ' + (typeof args === 'string' ? args : JSON.stringify(args)));\n if (output) parts.push('output: ' + (typeof output === 'string' ? output : JSON.stringify(output)));\n if (searchResults) parts.push('search_results: ' + (typeof searchResults === 'string' ? searchResults : JSON.stringify(searchResults)));\n } catch (_) {\n // ignore malformed tool objects\n }\n }\n return parts.join('\\n');\n}\n\n\n\n// Reusable background-check helpers\nfunction isEmailAddress(s) {\n const str = String(s || '').trim();\n if (!str) return false;\n return /^[^\\s@]+@[^\\s@]+\\.[^\\s@]{2,}$/.test(str);\n}\nfunction mergeSpamStatus(current, next) {\n if (!next) return current || undefined;\n if (!current) return next;\n const score = (s) => (s === 'likely_spam' ? 3 : s === 'suspected_spam' ? 2 : s === 'not_spam' ? 1 : 0);\n return score(next) >= score(current) ? next : current;\n}\nfunction mergeStatus(current, next) {\n if (!next) return current || undefined;\n if (!current) return next;\n const score = (s) => (s === 'spam' ? 4 : s === 'person_none' ? 3 : s === 'person_low' ? 2 : s === 'person_high' ? 1 : 0);\n return score(next) >= score(current) ? next : current;\n}\nfunction extractJsonBetweenTags(text) {\n try {\n if (!text) return null;\n const m = String(text).match(/[\\s\\S]*?<\\/json>/i);\n const slice = m ? m[0] : null;\n if (!slice) return null;\n const inner = slice.replace(/^/i, '').replace(/<\\/json>$/i, '');\n const trimmed = inner.trim();\n return JSON.parse(trimmed);\n } catch (err) { \n console.error('Failed to parse JSON between tags:', trimmed, 'Error:', err.message);\n return null; \n }\n}\nfunction logGroqCurl(tag, apiKey, payload) {\n try {\n const compact = JSON.stringify(payload);\n const esc = compact.replace(/'/g, `'\"'\"'`);\n const curl = [\n 'curl --request POST \\\\\\n' +\n ' --url https://api.groq.com/openai/v1/chat/completions \\\\\\n' +\n ` --header 'authorization: Bearer ${apiKey}' \\\\\\n` +\n \" --header 'content-type: application/json' \\\\\\n\" +\n ` --data '${esc}'`\n ].join('');\n console.log(`>> [${tag}] curl script:\\n${curl}`);\n } catch (_) {}\n}\nfunction coerceJsonFromText(text) {\n try {\n if (!text) return null;\n // 1) Try to find a raw JSON object substring\n const raw = String(text);\n const firstBrace = raw.indexOf('{');\n const lastBrace = raw.lastIndexOf('}');\n if (firstBrace !== -1 && lastBrace > firstBrace) {\n const candidate = raw.slice(firstBrace, lastBrace + 1);\n try { return JSON.parse(candidate); } catch (_) {}\n }\n // 2) Try loose key extraction\n const statusMatch = raw.match(/status\\s*[:=]\\s*[\"']?([a-zA-Z_]+)[\"']?/);\n const messageMatch = raw.match(/message\\s*[:=]\\s*[\"']([^\"']+)[\"']/);\n const explMatch = raw.match(/explanation_short\\s*[:=]\\s*[\"']([^\"']+)[\"']/);\n const out = {};\n if (statusMatch) out.status = statusMatch[1];\n if (messageMatch) out.message = messageMatch[1];\n if (explMatch) out.explanation_short = explMatch[1];\n return Object.keys(out).length > 0 ? out : null;\n } catch (_) { return null; }\n}\n\nfunction getEmailDomain(address) {\n try { return String(address || '').split('@')[1]?.toLowerCase() || ''; } catch (_) { return ''; }\n}\nfunction isGenericEmailDomain(domain) {\n const generic = new Set(['gmail.com','yahoo.com','outlook.com','hotmail.com','icloud.com','gmx.com','aol.com','proton.me','protonmail.com','mail.com','yandex.com']);\n return generic.has(String(domain || '').toLowerCase());\n}\nfunction dedupeStrings(arr) {\n const seen = new Set();\n const out = [];\n for (const s of (arr || [])) { const v = String(s || '').trim(); if (v && !seen.has(v)) { seen.add(v); out.push(v); } }\n return out;\n}\n// Whitelist helpers\nfunction normalizeWhitelistTokens(list) {\n try {\n if (!Array.isArray(list)) return [];\n const out = [];\n const seen = new Set();\n for (const raw of list) {\n const t = String(raw || '').trim().toLowerCase();\n if (!t) continue;\n if (seen.has(t)) continue;\n seen.add(t);\n out.push(t);\n }\n return out;\n } catch (_) { return []; }\n}\nfunction domainMatches(supplied, actualDomain) {\n try {\n const d = String(actualDomain || '').toLowerCase();\n const token = String(supplied || '').toLowerCase();\n if (!token || !d) return false;\n const t = token.replace(/^\\*@/, '').replace(/^@/, '');\n if (!t) return false;\n if (d === t) return true;\n // allow subdomain suffix matches\n return d.endsWith('.' + t);\n } catch (_) { return false; }\n}\nfunction matchWhitelist(email, tokens) {\n try {\n const e = String(email || '').toLowerCase();\n const domain = getEmailDomain(e);\n const list = normalizeWhitelistTokens(tokens);\n for (const t of list) {\n if (!t) continue;\n if (t.includes('@') && !t.includes('*')) {\n // exact email or @domain\n if (t.startsWith('@')) { if (domainMatches(t, domain)) return t; }\n else if (e === t) return t;\n } else if (t.startsWith('*@')) {\n if (domainMatches(t, domain)) return t;\n } else if (t.startsWith('@')) {\n if (domainMatches(t, domain)) return t;\n } else if (t.includes('.')) {\n // bare domain like example.com\n if (domainMatches(t, domain)) return t;\n }\n }\n return null;\n } catch (_) { return null; }\n}\nfunction statusToLabel(status) {\n if (status === 'spam') return 'spam';\n if (status === 'person_none') return 'no evidence';\n if (status === 'person_low') return 'possible person';\n if (status === 'likely_spam') return 'spam';\n if (status === 'suspected_spam') return 'suspicious';\n if (status === 'not_spam' || status === 'person_high') return 'likely real person';\n return String(status || '');\n}\nfunction cleanDetailText(text) {\n try {\n if (!text) return '';\n let s = String(text);\n // Remove tool and output blocks often present in compound traces\n s = s.replace(/[\\s\\S]*?<\\/tool>/gi, '').replace(/[\\s\\S]*?<\\/output>/gi, '');\n // Drop embedded JSON blocks\n s = s.replace(/[\\s\\S]*?<\\/json>/gi, '');\n // Normalize whitespace\n s = s.replace(/[ \\t]+/g, ' ').replace(/\\n{3,}/g, '\\n\\n').trim();\n // Keep only 1-3 short paragraphs\n const paras = s.split(/\\n\\s*\\n/).filter(p => p && p.trim());\n const limited = paras.slice(0, 3).map(p => p.trim().slice(0, 500));\n const joined = limited.join('\\n\\n').trim();\n return joined.slice(0, 1400);\n } catch (_) { return ''; }\n}\n\n// Produce a concise one-sentence identity-first summary from an explanation\nfunction deriveIdentityShort(explanation) {\n try {\n if (!explanation) return '';\n let s = String(explanation).trim();\n // Take the first sentence\n try {\n const parts = s.split(/(?<=[.!?])\\s+/).filter(Boolean);\n if (parts.length > 0) s = parts[0];\n } catch (_) {}\n // Length guard\n if (s.length > 200) s = s.slice(0, 199).replace(/[,;:\\s]+$/, '').trim() + '…';\n return s;\n } catch (_) { return ''; }\n}\n\n// Convert a plain-text analysis (Status/Message/Explanation/Evidence sections) into strict JSON\n// Schema: { status: 'person_high|person_low|person_none|spam', message: string, explanation_short: string, evidence: string[] }\nasync function convertAnalysisToJson(apiKey, email, analysisText) {\n try {\n const convModel = 'openai/gpt-oss-20b';\n const convSys = [\n 'You convert analysis text into a strict JSON object. Do not browse or call tools.',\n 'Schema: { \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }',\n 'Rules:',\n '- message: one short sentence.',\n '- explanation_short: 2-3 sentences (<= 400 chars). If analysis indicates nothing credible was found, include \"No public evidence found.\" If known, include person background (name, role/title, organization). If credible negative signals are present (e.g., StopForumSpam, Spamhaus, scam-reporting communities), mention that.',\n '- evidence: 0-5 short bullets (no links). Include a background bullet when available (e.g., \"Name — Title, Organization, City\"). Include negative bullets when applicable (e.g., \"Flagged on StopForumSpam\"). Use [] when no credible evidence.',\n '- Only output a JSON object (no markdown, no extra text).'\n ].join('\\n');\n const convMessages = [\n { role: 'system', content: convSys },\n { role: 'user', content: 'Email: ' + email + '\\nAnalysis to convert:\\n' + analysisText }\n ];\n const convPayload = { model: convModel, messages: convMessages, stream: false, temperature: 0, response_format: { type: 'json_object' }, tool_choice: 'none' };\n const convRes = await groqChatCompletion(apiKey, convPayload);\n const t2 = convRes?.choices?.[0]?.message?.content || '';\n try { return JSON.parse(t2); } catch (_) { return null; }\n } catch (_) {\n return null;\n }\n}\nasync function llmCompoundAssess(apiKey, email, systemPrompt) {\n const baseSystem = [\n 'You assess whether an email belongs to a real person. Perform targeted web checks. If you cannot browse, reason only from public patterns in the address and provider; do not fabricate.',\n 'Make an effort to look for identity signals on LinkedIn, company/staff pages, academic directories, GitHub, personal sites, press/newsroom/author pages, and social profiles.',\n 'When identity is indicated, do light background digging: capture the person\\'s name, role/title, organization, department/team, and location/city if available.',\n 'Also look for negative signals: credible anti-abuse/anti-spam sources (e.g., StopForumSpam, Spamhaus, PhishTank), scam-reporting communities, or reputable media coverage indicating misuse. If credible negative signals exist, prefer status: spam.',\n 'Return ONLY JSON wrapped in ... tags using this schema:',\n '{ \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }',\n 'Guidelines:',\n '- person_high: strong identity signals clearly tie to the email/user (e.g., staff or author page, LinkedIn with matching name and employer, academic page listing the email).',\n '- person_low: weak or indirect signals; likely a person but unverified.',\n '- person_none: no public identity evidence.',\n '- spam: obvious spam/role-based/throwaway patterns, or credible anti-spam sources flag the address.',\n '- Leniency: If the domain appears to be a non-generic organization or an academic domain (e.g., .edu, .ac.*, or a known university/company), and there are weak but plausible signals (name match, role on org page without explicit email), lean toward person_low rather than person_none.',\n '- Escalation: When you find a plausible identity match (person name plus role/title and/or organization/institution) from credible sources and there are no credible negative signals, prefer status: person_high, even if the address uses a generic email provider (e.g., gmail).',\n '- message: one short sentence preferring an identity-first summary, e.g., \"Linked to Name — Title, Organization\" when available. explanation_short: 2-3 sentences (<= 400 chars), plain text; no tool logs, URLs, or headings. If known, include person background (name, role/title, organization).',\n '- evidence: 1-5 short bullets summarizing concrete findings (no links). Include at least one background bullet when available (e.g., \"Name — Title, Organization, City\"). Include negative bullets when applicable (e.g., \"Flagged on StopForumSpam\" or \"Reported in scam community\"). If nothing found, set evidence to [] and explicitly state \"No public evidence found.\" in explanation_short.',\n '- If the address indicates a role (e.g., info, noreply) or a notable role (e.g., reporter, journalist, professor, founder), include that in evidence.',\n '- Do not include any text outside the ... wrapper.'\n ].join('\\n');\n const messages = [\n { role: 'system', content: baseSystem + (systemPrompt ? ('\\nExtra instructions: ' + systemPrompt) : '') },\n { role: 'user', content: 'Email: ' + email + '\\nTask: quick legitimacy check.' }\n ];\n const model = 'compound-beta';\n const compoundPayload1 = { model, messages, stream: false, temperature: 0.2, tool_choice: 'none' };\n const r1 = await groqChatCompletion(apiKey, compoundPayload1);\n // logGroqCurl('compound r1', apiKey, compoundPayload1);\n // try { console.log('>> [compound] r1:', JSON.stringify(r1)); } catch (_) {}\n const t1 = r1?.choices?.[0]?.message?.content || '';\n const reasoning1 = r1?.choices?.[0]?.message?.reasoning || '';\n let parsed = extractJsonBetweenTags(t1);\n if (!parsed) {\n // In JSON mode, remove the wrapper instruction to avoid tool_use_failed\n const baseSystemJson = [\n 'You assess whether an email likely belongs to a real person based on quick web checks; do not fabricate.',\n 'Return ONLY a JSON object with this schema (no tags, no markdown):',\n '{ \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }',\n 'Keep message concise; explanation_short 2-3 sentences (<= 400 chars).'\n ].join('\\n');\n const messagesJson = [\n { role: 'system', content: baseSystemJson + (systemPrompt ? ('\\nExtra instructions: ' + systemPrompt) : '') },\n { role: 'user', content: 'Email: ' + email + '\\nTask: quick legitimacy check.' }\n ];\n const payload2 = { model, messages: messagesJson, stream: false, temperature: 0.2, response_format: { type: 'json_object' }, tool_choice: 'none' };\n // logGroqCurl('compound r2', apiKey, payload2);\n const r2 = await groqChatCompletion(apiKey, payload2);\n try { console.log('>> [compound] r2:', JSON.stringify(r2)); } catch (_) {}\n const t2 = r2?.choices?.[0]?.message?.content || '';\n try { parsed = JSON.parse(t2); } catch (_) { parsed = null; }\n if (!parsed) {\n return {\n status: 'person_low',\n message: 'no compound signal',\n fields: { bg_compound_debug: (t1 || t2 || '').slice(0, 800), bg_llm_model: model }\n };\n }\n }\n const out = { fields: { bg_llm_model: model } };\n if (parsed) {\n if (parsed.status && (parsed.status === 'person_high' || parsed.status === 'person_low' || parsed.status === 'person_none' || parsed.status === 'spam')) out.status = parsed.status;\n if (typeof parsed.message === 'string' && parsed.message.trim()) {\n out.message = parsed.message.trim();\n } else if (out.status) {\n const label = statusToLabel(out.status);\n out.message = 'compound: ' + label;\n } else {\n out.message = 'compound: ' + statusToLabel('person_low');\n }\n // Add compact label + short/long messages\n const label = statusToLabel(out.status || (parsed.status || 'person_low'));\n out.fields.bg_compound_label = label;\n out.fields.bg_compound_short = out.message || label;\n // Prefer model-provided reasoning if available, else raw content stripped of JSON tags\n let detail = '';\n if (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) {\n detail = cleanDetailText(parsed.explanation_short);\n // further limit to ~2-3 sentences / 450 chars\n try {\n const parts = detail.split(/(?<=[.!?])\\s+/).filter(Boolean).slice(0, 3);\n detail = parts.join(' ');\n if (detail.length > 450) detail = detail.slice(0, 449).replace(/[,;:\\s]+$/, '').trim() + '…';\n } catch (_) {}\n }\n if (!detail && reasoning1 && typeof reasoning1 === 'string') {\n detail = cleanDetailText(reasoning1);\n }\n if (!detail && t1) {\n detail = cleanDetailText(String(t1));\n }\n if (detail) out.fields.bg_compound_detail = detail;\n // Prefer an identity-first short derived from explanation when available\n try {\n const shortPref = (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) ? deriveIdentityShort(parsed.explanation_short) : '';\n if (shortPref) out.fields.bg_compound_short = shortPref;\n } catch (_) {}\n // Evidence list\n try {\n let ev = parsed.evidence;\n if (Array.isArray(ev)) {\n ev = ev.map((s) => String(s || '').trim()).filter(Boolean).slice(0, 5);\n } else if (typeof ev === 'string' && ev.trim()) {\n ev = [ev.trim()];\n } else {\n ev = [];\n }\n if (ev.length > 0) out.fields.bg_compound_evidence = ev;\n } catch (_) {}\n }\n return out;\n}\n\n// Browser search assessor using Groq's browser_search tool\nasync function browserSearchAssess(apiKey, email, systemPrompt) {\n const baseSystem = [\n 'Use web browsing to gather public signals about whether this email belongs to a real person; do not fabricate.',\n 'Call browser_search with multiple targeted queries. Try: the full email in quotes; the local part and domain; site:linkedin.com with likely name/handle; site:github.com with the handle; university/staff directories; newsroom/author pages; personal sites; press pages.',\n 'Prefer authoritative sources: LinkedIn, staff/author/company pages, academic directories, GitHub, reputable media. Also check credible anti-abuse/anti-spam sources (StopForumSpam, Spamhaus, PhishTank) and scam-reporting communities. Avoid data brokers and spammy aggregators.',\n 'When identity is indicated, do light background digging: capture the person\\'s name, role/title, organization, department/team, and location/city if available.',\n 'Leniency rule: If the domain appears to be a non-generic organization or academic domain (e.g., .edu, .ac.*, or a recognized university/company), and you find weak but plausible signals (name on org page, directory listing without explicit email, matching role), prefer Status: person_low over person_none unless there are credible negative signals.',\n 'Escalation rule: If you find a plausible identity match (person name plus role/title and/or organization/institution) from credible sources and no credible negative signals, prefer Status: person_high, even when the address uses a generic provider (e.g., gmail).',\n 'Produce a concise plain-text analysis with the following sections only (do not include any JSON):',\n 'Status: one of person_high | person_low | person_none | spam',\n 'Message: one short sentence preferring an identity-first summary, e.g., \"Linked to Name — Title, Organization\" when available',\n 'Explanation: 2-3 sentences (<= 400 chars), reference evidence or say No public evidence found. If known, include person background (name, role/title, organization).',\n 'Evidence: 1-5 short bullet points summarizing concrete findings (no links). Include at least one bullet with person background when available (e.g., \"Name — Title, Organization, City\"). Include negative bullets such as \"Flagged on StopForumSpam\" or \"Mentioned in scam-reporting community\" when applicable. If nothing credible found, leave this section empty.',\n 'Also note recognizable roles when present (reporter, journalist, professor, founder, recruiter).'\n ].join('\\n');\n const messages = [\n { role: 'system', content: baseSystem + (systemPrompt ? ('\\nExtra instructions: ' + systemPrompt) : '') },\n { role: 'user', content: 'Email: ' + email + '\\nTask: web search legitimacy check.' }\n ];\n const model = 'openai/gpt-oss-20b';\n const payload = { model, messages, stream: false, temperature: 0.2, tools: [{ type: 'browser_search' }] };\n const r1 = await groqChatCompletion(apiKey, payload);\n logGroqCurl('browser r1', apiKey, payload);\n // try { console.log('>> [browser] r1:', JSON.stringify(r1)); } catch (_) {}\n const t1 = r1?.choices?.[0]?.message?.content || '';\n const out = { fields: { bg_browser_model: model } };\n // Second pass: convert the plain-text analysis to strict JSON\n let parsed = await convertAnalysisToJson(apiKey, email, t1);\n\n if (!parsed) {\n // As a last resort, attempt to coerce\n parsed = coerceJsonFromText(t1);\n }\n\n if (parsed) {\n if (parsed.status && (parsed.status === 'person_high' || parsed.status === 'person_low' || parsed.status === 'person_none' || parsed.status === 'spam')) out.status = parsed.status;\n if (typeof parsed.message === 'string' && parsed.message.trim()) out.message = parsed.message.trim();\n const label = statusToLabel(out.status || (parsed.status || 'person_low'));\n out.fields.bg_browser_label = label;\n out.fields.bg_browser_short = out.message || label;\n if (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) {\n let detail = String(parsed.explanation_short).trim();\n if (detail.length > 450) detail = detail.slice(0, 449).replace(/[,;:\\s]+$/, '').trim() + '…';\n out.fields.bg_browser_detail = detail;\n // Prefer identity-first short if explanation is present\n try {\n const shortPref = deriveIdentityShort(parsed.explanation_short);\n if (shortPref) out.fields.bg_browser_short = shortPref;\n } catch (_) {}\n }\n try {\n let ev = parsed.evidence;\n if (Array.isArray(ev)) {\n ev = ev.map((s) => String(s || '').trim()).filter(Boolean).slice(0, 5);\n } else if (typeof ev === 'string' && ev.trim()) {\n ev = [ev.trim()];\n } else {\n ev = [];\n }\n if (ev.length > 0) out.fields.bg_browser_evidence = ev;\n } catch (_) {}\n } else {\n out.fields.bg_browser_debug = 'browser_search produced non-JSON analysis and conversion failed.';\n }\n\n return out;\n}\n\n// Final judge to consolidate all signals\nasync function finalJudgeAssess(apiKey, email, systemPrompt, evidence) {\n console.log('>> [final judge] evidence:', email, JSON.stringify(evidence));\n const model = 'openai/gpt-oss-120b';\n const schema = '{ \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }';\n const sys = [\n 'You are a strict judge that consolidates signals from two assessors and heuristics (academic, role, domain) to decide if an email belongs to a real person.',\n 'Decide using severity: spam > person_none > person_low > person_high.',\n 'Return ONLY JSON per schema:', schema,\n 'Rules:',\n '- Compose evidence as a deduplicated list of concrete bullets merged from all inputs (no links).',\n '- Include at least one bullet with person background when available (name, role/title, organization, location).',\n '- If credible anti-spam signals exist (e.g., StopForumSpam, Spamhaus, scam-reporting communities), prefer status: spam and include a negative bullet.',\n '- Leniency: For non-generic organization or academic domains with weak but plausible identity signals, prefer person_low over person_none unless negative signals exist.',\n '- Escalation: If there is a plausible identity match (person name plus role/title and/or organization/institution) from credible sources and no credible negative signals, prefer person_high even if the address uses a generic provider (e.g., gmail).',\n '- If no credible public evidence is present, set evidence to [] and explicitly say \"No public evidence found.\" in explanation_short.',\n '- message must be one short, specific sentence preferring an identity-first summary like \"Linked to Name — Title, Organization\" when available. explanation_short must be 2-3 sentences (<= 400 chars) and reference key evidence or lack thereof. If known, weave in person background (name, role/title, organization).',\n '- Note recognizable roles when present (reporter, journalist, professor, founder, recruiter).'\n ].join('\\n');\n const user = [\n 'Email: ' + email,\n 'Evidence (JSON):',\n JSON.stringify(evidence)\n ].join('\\n');\n // Ask for json_object to avoid extra parsing\n const judgePayload = { model, messages: [ { role: 'system', content: sys + (systemPrompt ? ('\\nExtra: ' + systemPrompt) : '') }, { role: 'user', content: user } ], stream: false, temperature: 0.2, response_format: { type: 'json_object' } };\n // logGroqCurl('judge', apiKey, judgePayload);\n const r = await groqChatCompletion(apiKey, judgePayload);\n // try { console.log('>> [judge] r:', JSON.stringify(r)); } catch (_) {}\n let parsed = null;\n try { parsed = JSON.parse(r?.choices?.[0]?.message?.content || '{}'); } catch (_) { parsed = null; }\n if (!parsed) return {};\n const out = { fields: { bg_final_model: model } };\n if (parsed.status && (parsed.status === 'person_high' || parsed.status === 'person_low' || parsed.status === 'person_none' || parsed.status === 'spam')) out.status = parsed.status;\n if (typeof parsed.message === 'string' && parsed.message.trim()) out.message = parsed.message.trim();\n const label = statusToLabel(out.status || (parsed.status || 'person_low'));\n out.fields.bg_final_label = label;\n out.fields.bg_final_short = out.message || label;\n if (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) {\n let d = String(parsed.explanation_short).trim();\n if (d.length > 450) d = d.slice(0, 449).replace(/[,;:\\s]+$/, '').trim() + '…';\n out.fields.bg_final_detail = d;\n // Prefer identity-first one-liner for the short summary\n try {\n const shortPref = deriveIdentityShort(parsed.explanation_short);\n if (shortPref) out.fields.bg_final_short = shortPref;\n } catch (_) {}\n }\n try {\n let ev = parsed.evidence;\n if (Array.isArray(ev)) {\n ev = ev.map((s) => String(s || '').trim()).filter(Boolean).slice(0, 5);\n } else if (typeof ev === 'string' && ev.trim()) {\n ev = [ev.trim()];\n } else {\n ev = [];\n }\n if (ev.length > 0) out.fields.bg_final_evidence = ev;\n } catch (_) {}\n return out;\n}\nasync function academicAssess(email) {\n const out = { fields: {} };\n try {\n const { Verifier } = await import('npm:academic-email-verifier');\n let isAcademic = false; let institution = null;\n try { isAcademic = await Verifier.isAcademic(email); } catch (_) { isAcademic = false; }\n try { institution = await Verifier.getInstitutionName(email); } catch (_) { institution = null; }\n const inst = typeof institution === 'string' ? institution.trim() : (institution ? String(institution) : null);\n out.fields.bg_academic = !!isAcademic; if (inst) out.fields.bg_institution = inst;\n if (isAcademic) out.fields.bg_academic_msg = inst || 'Academic domain';\n } catch (_) {}\n return out;\n}\nfunction roleHeuristicAssess(email) {\n try {\n const local = String(email || '').split('@')[0].toLowerCase();\n const roleList = ['info', 'support', 'admin', 'sales', 'contact', 'hello', 'team', 'marketing', 'noreply', 'no-reply'];\n if (roleList.includes(local)) return { status: 'suspected_spam', message: 'Role-based address' };\n } catch (_) {}\n return {};\n}\n\n\n// Check if server has API key\napp.get('/api/check-key', (c) => {\n return c.json({ hasServerKey: !!serverApiKey });\n});\n\n// Environment-aware file reading function\nasync function readFileContent(filePath) {\n // Check if we're in Val Town environment\n if (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) {\n // Use Val Town's readFile\n return await readFile(filePath, import.meta.url);\n } else {\n // Use Deno's native readTextFile for local development\n return await Deno.readTextFile(filePath);\n }\n}\n\n// Serve root with HTML content\napp.get('/', async (c) => {\n try {\n const htmlContent = await readFileContent('index.html');\n return c.html(htmlContent);\n } catch (error) {\n console.error('Error reading HTML file:', error);\n return c.text('Error loading page', 500);\n }\n});\n\n// Serve frontend modules (no static middleware)\n// Removed legacy research frontend\n\napp.get('/frontend/init.js', async (c) => {\n try {\n const js = await readFileContent('frontend/init.js');\n return new Response(js, {\n headers: { 'Content-Type': 'application/javascript; charset=utf-8', 'Cache-Control': 'no-store, must-revalidate', 'Pragma': 'no-cache' },\n });\n } catch (error) {\n console.error('Error reading init.js:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Removed legacy lorraine frontend\n\napp.get('/frontend/mailcheckApp.js', async (c) => {\n try {\n const js = await readFileContent('frontend/mailcheckApp.js');\n return new Response(js, {\n headers: { 'Content-Type': 'application/javascript; charset=utf-8', 'Cache-Control': 'no-store, must-revalidate', 'Pragma': 'no-cache' },\n });\n } catch (error) {\n console.error('Error reading mailcheckApp.js:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Academic email check (server-side; uses npm:academic-email-verifier)\n// Removed standalone academic check endpoint; academic is part of /api/check/background\n\n// Background check endpoint: runs sequential checkers server-side\napp.post('/api/check/background', async (c) => {\n try {\n const body = await c.req.json().catch(() => ({}));\n const email = String(body?.email || '').trim();\n const systemPrompt = typeof body?.systemPrompt === 'string' ? body.systemPrompt : '';\n const whitelist = Array.isArray(body?.whitelist) ? body.whitelist : [];\n const blacklist = Array.isArray(body?.blacklist) ? body.blacklist : [];\n // Prefer Authorization: Bearer header, then body.userApiKey, then env\n const authHeader = c.req.header('Authorization') || c.req.header('authorization') || '';\n const m = authHeader.match(/^Bearer\\s+(.+)$/i);\n const headerKey = m ? m[1].trim() : '';\n const apiKey = serverApiKey || headerKey || body?.userApiKey || Deno.env.get(\"GROQ_API_KEY\");\n if (!apiKey) return c.json({ error: 'No Groq API key available.' }, 400);\n if (!email) return c.json({ error: 'email required' }, 400);\n const out = await backgroundAssessEmail(apiKey, email, systemPrompt, whitelist, blacklist);\n // try { console.log('>> [/api/check/background] result:', JSON.stringify(out)); } catch (_) {}\n return c.json(out);\n } catch (error) {\n console.error('background check error:', error);\n return c.json({ error: 'background check error: ' + error.message }, 500);\n }\n});\n\n// Async job APIs\n// Create a job with one or more items. Body: { items: string[] | { email }[], systemPrompt?, concurrency?, userApiKey? }\napp.post('/api/jobs', async (c) => {\n try {\n const body = await c.req.json().catch(() => ({}));\n let items = Array.isArray(body?.items) ? body.items : [];\n const systemPrompt = typeof body?.systemPrompt === 'string' ? body.systemPrompt : '';\n const concurrency = Math.max(1, Number(body?.concurrency || 8) || 8);\n const authHeader = c.req.header('Authorization') || c.req.header('authorization') || '';\n const m = authHeader.match(/^Bearer\\s+(.+)$/i);\n const headerKey = m ? m[1].trim() : '';\n const apiKey = serverApiKey || headerKey || body?.userApiKey || Deno.env.get(\"GROQ_API_KEY\");\n if (!apiKey) return c.json({ error: 'No Groq API key available.' }, 400);\n // Normalize items to { id, email, status }\n items = items.map((v) => {\n const email = (v && typeof v === 'object') ? String(v.email || '').trim() : String(v || '').trim();\n return { id: generateId(), email, status: 'pending' };\n }).filter((it) => it.email);\n if (items.length === 0) return c.json({ error: 'no valid items' }, 400);\n const job = { id: generateId(), running: false, cancelled: false, total: 0, completed: 0, createdAt: nowTs(), updatedAt: nowTs(), items, systemPrompt };\n jobRegistry.set(job.id, job);\n // fire and forget\n runAsyncJob(job, apiKey, concurrency);\n return c.json(summarizeJob(job));\n } catch (error) {\n console.error('create job error:', error);\n return c.json({ error: 'create job error: ' + error.message }, 500);\n }\n});\n\n// Get job status by id\napp.get('/api/jobs/:id', (c) => {\n try {\n const id = c.req.param('id');\n const job = id && jobRegistry.get(id);\n if (!job) return c.json({ error: 'not found' }, 404);\n return c.json(summarizeJob(job));\n } catch (error) {\n console.error('get job error:', error);\n return c.json({ error: 'get job error: ' + error.message }, 500);\n }\n});\n\n// Cancel a job by id\napp.post('/api/jobs/:id/cancel', (c) => {\n try {\n const id = c.req.param('id');\n const job = id && jobRegistry.get(id);\n if (!job) return c.json({ error: 'not found' }, 404);\n job.cancelled = true;\n job.running = false;\n job.updatedAt = nowTs();\n return c.json(summarizeJob(job));\n } catch (error) {\n console.error('cancel job error:', error);\n return c.json({ error: 'cancel job error: ' + error.message }, 500);\n }\n});\n\n// LLM-based email legitimacy checker\n// Asks the model to return JSON wrapped in ... tags; retries with JSON modes if needed\n// Removed standalone llm-email endpoint; compound is part of /api/check/background\n\nexport default (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) ? app.fetch : app;",[153],"c444afde-9810-11f0-8c45-0224a6c84d84","index.html","cbfb404a-81f8-11f0-b660-0224a6c84d84",127,["D",1758585822735],"\n\n\n \n \n MCP Navigator\n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n\n \n\n\n

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--allow-env --allow-write --allow-net --reload=https://esm.town ./main.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}",[175],"cc2d67a0-81f8-11f0-9680-0224a6c84d84","chatStreaming.js","cc2d6872-81f8-11f0-9680-0224a6c84d84",45,["D",1756156602546],"// Removed legacy streaming utilities; not used by background checker.\n\n// Intentionally left minimal; streaming utilities were removed.\n\n\n",[182],"cbd94602-81f8-11f0-976d-0224a6c84d84","chatCompletion.js","cbd946e8-81f8-11f0-976d-0224a6c84d84",41,["D",1756156602030],"// Minimal Groq Chat Completions client using fetch (for background checker)\nexport async function groqChatCompletion(apiKey, payload) {\n // console.log('>>> [groqChatCompletion] Payload:', payload);\n let response;\n try {\n response = await fetch('https://api.groq.com/openai/v1/chat/completions', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${apiKey}`,\n },\n body: JSON.stringify(payload),\n });\n } catch (err) {\n console.error('>>> [groqChatCompletion] Network error:', err && err.message ? err.message : String(err));\n throw err;\n }\n console.log('>>> [groqChatCompletion] Status:', response.status);\n if (!response.ok) {\n const text = await response.text();\n console.error('>>> [groqChatCompletion] Error response:', response.status, text);\n throw new Error(`Groq API error: ${response.status} ${text}`);\n }\n const json = await response.json();\n // try { console.log('>>> [groqChatCompletion] JSON:', JSON.stringify(json)); } catch (_) {}\n return json;\n}\n\n\n",[189],"eda32d86-8534-11f0-96fe-0224a6c84d84","README.md","cc3b4d20-81f8-11f0-b51c-0224a6c84d84",121,["D",1756512281996],3,"## MailCheck — Real‑Person Email Verifier (Groq)\n\nVerify that email addresses belong to real people using lightweight web + LLM signals. Upload/paste lists, run concurrent checks, and export annotated results.\n\n## Features\n- Upload CSV/JSON or paste text; inline edit and delete rows\n- Jobs sidebar with autosave (localStorage)\n- Per‑email verification with concurrency and live row updates\n - Syntax check (invalid → spam)\n - Academic domain detection (institution annotation)\n - Role/alias heuristic (flags generic addresses)\n - Web + LLM assessments consolidated by a final judge into one decision\n- Allowlist/Blocklist with domains, exact emails, or regex\n- Export CSV/JSON (preserves original columns + `bg_*` fields)\n\n## How it works\n\n### UI (index.html)\nThe app is a single HTML page (`index.html`) that serves a light client built with Alpine.js and Tailwind. It lets you:\n- Paste or upload emails, edit rows inline, and run checks.\n- Provide an optional system prompt to steer LLM behavior.\n- Configure an Allowlist/Blocklist (one rule per line; supports domains, exact emails, and regex).\n- Kick off background jobs and download results as CSV/JSON.\n\n### Decision pipeline\nFor each email, MailCheck performs a staged evaluation and collapses results into a single status and message:\n\n1) Pre‑assessors (fast short‑circuits)\n- Syntax guard: invalid formats → `spam`.\n- Allowlist: immediate `whitelist` with rule annotation.\n- Blocklist: immediate `spam` with rule annotation.\n- Academic detector: annotate institution; enables leniency downstream.\n- Role heuristic: flags role/alias locals (e.g., `info`, `noreply`).\n\n2) Full assessors (run in parallel)\n- Compound LLM (model: `compound-beta`): returns strict JSON with\n - `status` in `{ person_high, person_low, person_none, spam }`\n - `message`, `explanation_short`, and `evidence[]`\n The prompt prefers identity‑first summaries and concrete evidence (role/title, org, city) and penalizes vague name‑only matches.\n- Browser Search (model: `openai/gpt-oss-20b` + `browser_search` tool): performs targeted queries (quoted email, handle+domain, site:linkedin, site:github, org/staff pages). Produces an analysis that is converted to JSON with status/message/explanation/evidence.\n\n3) Final judge (model: `openai/gpt-oss-120b`)\nConsolidates assessor outputs + heuristics (academic, role, domain). Policy:\n- Severity order: `spam > person_none > person_low > person_high`.\n- Credible anti‑abuse signals → `spam`.\n- Plausible identity from reputable sources, no negatives → promote to `person_high`.\n- Leniency: non‑generic org/academic domains with weak but plausible signals may prefer `person_low` over `person_none`.\nThe judge produces a single status/message, a short identity‑first summary, and deduplicated evidence bullets suitable for the UI.\n\n### Labels & messages\nStatuses map to compact UI labels (e.g., `person_low` → “possible person”). Where assessors supply explanations, we derive a short identity‑first one‑liner for readability.\n\n## Statuses\n- `person_high`\n- `person_low`\n- `person_none`\n- `spam`\n- `whitelist` (short‑circuit on allowlist)\n\n## Requirements\n- Deno 1.40+\n- Groq API key\n\n## Quick Start\n1) Install Deno: https://deno.land/#installation\n2) Start the dev server:\n```sh\ndeno task serve\n```\nThis runs: `deno serve --port 8013 --allow-sys --allow-read --allow-import --allow-env --allow-write --allow-net --reload=https://esm.town ./main.js`.\n\nOpen http://localhost:8013. If the server doesn’t have `GROQ_API_KEY`, add a user key in the UI.\n\n## Configuration\n- `GROQ_API_KEY`: Groq key (server). The UI also supports a per‑user key.\n\n## API Reference\n\n### Single check\nPOST `/api/check/background`\n - body\n ```json\n {\n \"email\": \"someone@example.com\",\n \"systemPrompt\": \"optional extra guidance\",\n \"userApiKey\": \"\",\n \"whitelist\": [\n \"@company.com\",\n \"*@partner.org\",\n \"/^first\\\\.last@org\\\\.edu$/i\"\n ],\n \"blacklist\": [\n \"@temp-mail.com\",\n \"*@noidem\",\n \"/^[a-z]{2,}\\\\d{2,4}@gmail\\\\.com$/i\"\n ]\n }\n ```\n - notes\n - `whitelist` (UI label: Allowlist) and `blacklist` (UI label: Blocklist) accept strings:\n - exact email: `\"user@example.com\"`\n - domain tokens: `\"@example.com\"`, `\"*@example.com\"`, or bare `\"example.com\"`\n - regex tokens: strings wrapped with slashes, e.g. `\"/^first\\\\.last@company\\\\.com$/i\"`\n - regexes are tested against the full raw email; for convenience we also test local‑part + `@`\n - If an allowlist rule matches, the request short‑circuits with status `whitelist`.\n - If a blocklist rule matches, the request short‑circuits with status `spam` and `bg_blacklist_*` fields.\n - If neither matches, the flow proceeds to heuristics + model assessors.\n - returns\n ```json\n {\n \"email\": \"someone@example.com\",\n \"status\": \"person_low | person_high | person_none | spam | whitelist\",\n \"message\": \"short description\",\n \"fields\": { \"bg_*\": \"diagnostic fields for UI\" }\n }\n ```\n\n### Async jobs\nCreate a job to process many emails concurrently.\n\n- Create job\n - POST `/api/jobs`\n - body\n ```json\n {\n \"items\": [\"a@example.com\", {\"email\": \"b@example.com\"}],\n \"systemPrompt\": \"\",\n \"concurrency\": 8,\n \"userApiKey\": \"\"\n }\n ```\n - response: job summary `{ id, running, total, completed, items: [{ id, email, status }] }`\n\n- Get status: GET `/api/jobs/:id`\n- Cancel: POST `/api/jobs/:id/cancel`\n\n> Tip: If you want per‑job allowlist/blocklist, they can be added to the job payload and threaded into the runner.\n\n## Notes\n- Focuses on real‑person verification, not SMTP deliverability.\n- The UI is a thin client over the API—use the endpoint directly if preferred.\n- Lists in the UI are “One per line”; for API requests pass arrays of strings.\n- Regex tips: escape dots in domains (`gmail\\.com`), anchor when needed (`^...$`).\n\nPowered by Groq — get a key at https://groq.com.\n",[196],"cd6e4698-81f8-11f0-b9be-0224a6c84d84",".vtignore","cd6e4738-81f8-11f0-b9be-0224a6c84d84",88,["D",1756156604684],".git\n.vscode\n.cursorrules\n.DS_Store\nnode_modules\nvendor\n.env",[204],"cc70d0ee-81f8-11f0-bbd2-0224a6c84d84",".gitignore","cc70d17a-81f8-11f0-bbd2-0224a6c84d84",52,["D",1756156602949],".env\n.DS_Store",[211],"cc334c7e-81f8-11f0-b660-0224a6c84d84",".cursorrules","cc334d0a-81f8-11f0-b660-0224a6c84d84",46,["D",1756156602621],"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 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array of row objects, each includes detected email and bg fields\n emailFieldName: '',\n detectedEmailCount: 0,\n\n // Whitelist/Blacklist rules UI (emails or domains or regex), persisted in localStorage\n whitelistText: '',\n blacklistText: '',\n\n // Single email spot-check\n singleEmailInput: '',\n singleChecking: false,\n singleResult: null,\n\n // Run state\n isRunning: false,\n cancelRequested: false,\n concurrency: 8,\n\n // Background job runners keyed by job name. Each runner manages its own queue/state.\n jobRunners: {},\n // Interval used to reflect active job runner state in the UI\n _activeRunnerInterval: null,\n // Map of jobName -> boolean running flag for sidebar indicators\n jobRunningMap: {},\n // Map of jobName -> last completion timestamp for \"done\" flash\n jobDoneAt: {},\n // Duration to show the done flash (ms)\n jobDoneFlashMs: 3500,\n\n // Sidebar/UI\n sidebarOpen: false,\n sidebarCollapsed: false,\n sidebarTransitioning: false,\n sidebarAnimMs: 300,\n\n async init() {\n // API key from localStorage\n try {\n const storedApiKey = localStorage.getItem('groq_api_key');\n if (storedApiKey) this.userApiKey = storedApiKey;\n } catch (_) {}\n await this.checkServerKey();\n\n // Load job name + jobs\n try {\n const storedJob = localStorage.getItem('mailcheck_job_name');\n if (storedJob) { this.jobName = storedJob; this.jobInput = storedJob; }\n } catch (_) {}\n try { this.loadJobsFromStorage(); this.refreshJobsArray(); } catch (_) {}\n // If active job exists, hydrate\n if (this.jobName && this.jobStore[this.jobName]) {\n this.hydrateFromJob(this.jobStore[this.jobName]);\n }\n // Load whitelist/blacklist from storage with UI-provided examples\n try {\n const wl = localStorage.getItem('mailcheck_whitelist_v1');\n this.whitelistText = (wl && wl.trim()) ? wl : '@groq.com';\n } catch (_) { this.whitelistText = '@groq.com'; }\n try {\n const bl = localStorage.getItem('mailcheck_blacklist_v1');\n this.blacklistText = (bl && bl.trim()) ? bl : '/^[a-z]{2,}[0-9]{1,4}@/i\\n@temp-mail.com\\n*@noidem';\n } catch (_) { this.blacklistText = '/^[a-z]{2,}[0-9]{1,4}@/i\\n@temp-mail.com\\n*@noidem'; }\n try { this._refreshJobRunningMap(); } catch (_) {}\n try { this._watchActiveRunner(); } catch (_) {}\n },\n\n async checkServerKey() {\n try {\n const r = await fetch('/api/check-key');\n const j = await r.json();\n this.hasServerKey = !!j.hasServerKey;\n } catch (_) { this.hasServerKey = false; }\n },\n\n setApiKey() {\n if (this.apiKeyInput && this.apiKeyInput.trim()) {\n this.userApiKey = this.apiKeyInput.trim();\n try { localStorage.setItem('groq_api_key', this.userApiKey); } catch (_) {}\n this.apiKeyInput = '';\n }\n },\n changeApiKey() { this.userApiKey = ''; },\n clearApiKey() { this.userApiKey = ''; try { localStorage.removeItem('groq_api_key'); } catch (_) {} },\n get maskedApiKey() {\n if (!this.userApiKey) return '';\n const k = this.userApiKey;\n return k.substring(0, 8) + '*'.repeat(Math.max(0, k.length - 12)) + k.substring(k.length - 4);\n },\n\n // Jobs\n loadJobsFromStorage() {\n try {\n const raw = localStorage.getItem('mailcheck_jobs_v1');\n this.jobStore = raw ? JSON.parse(raw) : {};\n } catch (_) { this.jobStore = {}; }\n },\n saveJobsToStorage() {\n try { localStorage.setItem('mailcheck_jobs_v1', JSON.stringify(this.jobStore)); } catch (_) {}\n this.refreshJobsArray();\n },\n saveActiveJob() {\n try {\n const name = (this.jobName || '').trim();\n if (!name) return;\n const existed = this.jobStore ? this.jobStore[name] : null;\n const payload = {\n job: name,\n items: Array.isArray(this.items) ? this.items : [],\n meta: {\n systemPrompt: this.systemPrompt || '',\n sourceKind: this.sourceKind || '',\n sourceHeaders: Array.isArray(this.sourceHeaders) ? this.sourceHeaders : [],\n emailFieldName: this.emailFieldName || '',\n sourceFileName: this.sourceFileName || ''\n },\n created_at: existed && existed.created_at ? existed.created_at : new Date().toISOString(),\n updated_at: new Date().toISOString()\n };\n this.jobStore[name] = payload;\n this.saveJobsToStorage();\n // Persist lists for the app\n try { localStorage.setItem('mailcheck_whitelist_v1', this.whitelistText || ''); } catch (_) {}\n try { localStorage.setItem('mailcheck_blacklist_v1', this.blacklistText || ''); } catch (_) {}\n } catch (_) {}\n },\n hydrateFromJob(jobPayload) {\n try {\n const p = jobPayload || {};\n this.items = Array.isArray(p.items) ? p.items : [];\n const m = p.meta || {};\n this.systemPrompt = m.systemPrompt || '';\n this.sourceKind = m.sourceKind || '';\n this.sourceHeaders = Array.isArray(m.sourceHeaders) ? m.sourceHeaders : [];\n this.emailFieldName = m.emailFieldName || '';\n this.sourceFileName = m.sourceFileName || '';\n // recompute detected count\n this.detectedEmailCount = (this.items || []).reduce((acc, it) => acc + (this.getRecordEmail(it) ? 1 : 0), 0);\n } catch (_) {}\n },\n refreshJobsArray() {\n try {\n const arr = Object.entries(this.jobStore || {}).map(([name, payload]) => {\n const items = Array.isArray(payload?.items) ? payload.items : [];\n const done = items.filter((it) => !!(it && (it.bg_status === 'person_high' || it.bg_status === 'person_low' || it.bg_status === 'person_none' || it.bg_status === 'spam' || it.bg_status === 'error'))).length;\n return { name, answersCount: done, created_at: payload?.created_at || payload?.updated_at || null };\n });\n arr.sort((a, b) => {\n const ta = a.created_at ? Date.parse(a.created_at) : 0;\n const tb = b.created_at ? Date.parse(b.created_at) : 0;\n if (ta !== tb) return ta - tb; // stable by creation time\n return a.name.localeCompare(b.name);\n });\n this.jobsArray = arr;\n } catch (_) { this.jobsArray = []; }\n },\n nextDefaultJobName() {\n try {\n const keys = Object.keys(this.jobStore || {});\n let maxN = 0;\n for (const k of keys) {\n const m = /^job-(\\d+)$/.exec(k);\n if (m) {\n const n = parseInt(m[1], 10);\n if (!Number.isNaN(n) && n > maxN) maxN = n;\n }\n }\n return `job-${maxN + 1}`;\n } catch (_) {\n return 'job-1';\n }\n },\n setJobName() {\n const newName = (this.jobInput || '').trim();\n const oldName = this.jobName || '';\n if (!newName) return;\n if (oldName && newName !== oldName) {\n try {\n const existed = this.jobStore && this.jobStore[oldName];\n if (existed) {\n const migrated = { ...existed, job: newName, updated_at: new Date().toISOString() };\n this.jobStore[newName] = migrated;\n try { delete this.jobStore[oldName]; } catch (_) {}\n this.saveJobsToStorage();\n }\n } catch (_) {}\n }\n this.jobName = newName;\n try { localStorage.setItem('mailcheck_job_name', this.jobName || ''); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n },\n selectJob(name) {\n try { this.saveActiveJob(); } catch (_) {}\n const j = this.jobStore && this.jobStore[name];\n if (!j) return;\n this.jobName = name;\n this.jobInput = name;\n try { localStorage.setItem('mailcheck_job_name', name); } catch (_) {}\n this.hydrateFromJob(j);\n try { this.saveActiveJob(); } catch (_) {}\n // Reflect background runner state for the newly selected job\n try {\n const s = this.getBackgroundRunStatus(this.jobName);\n this.isRunning = !!(s && s.running);\n this._watchActiveRunner();\n } catch (_) {}\n },\n createNewJob() {\n try { this.saveActiveJob(); } catch (_) {}\n const defaultName = this.nextDefaultJobName();\n this.jobName = defaultName;\n this.jobInput = defaultName;\n this.items = [];\n this.sourceHeaders = [];\n this.sourceKind = '';\n this.emailFieldName = '';\n this.detectedEmailCount = 0;\n try { this.saveActiveJob(); } catch (_) {}\n try { localStorage.setItem('mailcheck_job_name', defaultName); } catch (_) {}\n },\n deleteJob(name) {\n try {\n if (!name) return;\n if (this.jobStore && this.jobStore[name]) {\n delete this.jobStore[name];\n this.saveJobsToStorage();\n }\n if (this.jobName === name) {\n this.jobName = '';\n this.jobInput = '';\n this.items = [];\n this.sourceHeaders = [];\n this.sourceKind = '';\n this.emailFieldName = '';\n this.detectedEmailCount = 0;\n try { localStorage.removeItem('mailcheck_job_name'); } catch (_) {}\n }\n } catch (_) {}\n },\n\n // Sidebar helpers\n toggleSidebar() { this.sidebarOpen = !this.sidebarOpen; },\n collapseSidebar() { this.sidebarTransitioning = true; this.sidebarCollapsed = true; setTimeout(() => { this.sidebarTransitioning = false; }, this.sidebarAnimMs); },\n expandSidebar() { this.sidebarTransitioning = true; this.sidebarCollapsed = false; setTimeout(() => { this.sidebarTransitioning = false; }, this.sidebarAnimMs); },\n\n // Mark job as done just now (for UI flash)\n markJobDone(name) { try { if (!name) return; this.jobDoneAt[name] = Date.now(); } catch (_) {} },\n // Whether job recently completed (and not currently running)\n isJobDoneRecently(name) {\n try {\n if (!name) return false;\n if (this.isJobRunning(name)) return false;\n const ts = this.jobDoneAt && this.jobDoneAt[name];\n if (!ts) return false;\n return (Date.now() - ts) < (this.jobDoneFlashMs || 3000);\n } catch (_) { return false; }\n },\n // Refresh running map and, if fully idle, mark as done\n finishCheckForJob(name) {\n try { this._refreshJobRunningMap(); if (!this._computeJobIsRunning(name)) this.markJobDone(name); } catch (_) {}\n },\n\n // --- Multi-job Background Runners ---\n // Start a background run for a specific job name. Creates an isolated runner that\n // continues even if the UI switches to another job. Safe for multiple jobs in parallel.\n startBackgroundRunForJob(jobName, options = {}) {\n try {\n const name = String(jobName || '').trim();\n if (!name) return null;\n if (this.jobRunners[name] && this.jobRunners[name].status().running) {\n return this.jobRunners[name];\n }\n const runner = createJobRunner(this, name, {\n concurrency: Math.max(1, Number(options.concurrency || this.concurrency) || 8),\n onlyPending: options.onlyPending !== false\n });\n this.jobRunners[name] = runner;\n runner.start();\n try { this.jobRunningMap[name] = true; this._refreshJobRunningMap(); this._watchActiveRunner(); } catch (_) {}\n return runner;\n } catch (_) { return null; }\n },\n\n // Cancel a background run for a job, if one is active.\n cancelBackgroundRunForJob(jobName) {\n try {\n const r = this.jobRunners && this.jobRunners[jobName];\n if (r) r.cancel();\n try { this.jobRunningMap[jobName] = false; this._refreshJobRunningMap(); } catch (_) {}\n } catch (_) {}\n },\n\n // Shallow status snapshot for a job's runner (or a default if none).\n getBackgroundRunStatus(jobName) {\n try {\n const r = this.jobRunners && this.jobRunners[jobName];\n return r ? r.status() : { running: false, cancelled: false, total: 0, completed: 0 };\n } catch (_) { return { running: false, cancelled: false, total: 0, completed: 0 }; }\n },\n // Public helper for templates\n isJobRunning(name) {\n try { return !!this.jobRunningMap && !!this.jobRunningMap[name]; } catch (_) { return false; }\n },\n // Refresh the running map for all known jobs\n _refreshJobRunningMap() {\n try {\n const names = new Set(Object.keys(this.jobStore || {}));\n for (const n of Object.keys(this.jobRunners || {})) names.add(n);\n const next = {};\n for (const n of names) next[n] = this._computeJobIsRunning(n);\n this.jobRunningMap = next;\n } catch (_) {}\n },\n\n // Compute if a job appears to be running by either active runner state or any 'checking' items\n _computeJobIsRunning(jobName) {\n try {\n if (!jobName) return false;\n const s = this.getBackgroundRunStatus(jobName);\n if (s && s.running) return true;\n const payload = this.jobStore && this.jobStore[jobName];\n if (!payload || !Array.isArray(payload.items)) return false;\n for (const it of payload.items) { if (it && it.bg_status === 'checking') return true; }\n return false;\n } catch (_) { return false; }\n },\n\n // Parsing & ingest\n async handleFileChange(evt) {\n try {\n const file = (evt && evt.target && evt.target.files && evt.target.files[0]) ? evt.target.files[0] : null;\n if (!file) return;\n this.sourceFileName = file.name || '';\n this.ensureDefaultJobName(file.name || '(upload)');\n const text = await file.text();\n await this.parseInputText(text, file.name || 'upload');\n } catch (_) {}\n },\n async parsePaste() {\n this.ensureDefaultJobName('(pasted)');\n await this.parseInputText(this.pasteInput || '', '(pasted)', { append: true });\n this.pasteInput = '';\n },\n looksLikeJson(text) {\n const t = String(text || '').trim();\n return t.startsWith('{') || t.startsWith('[');\n },\n async parseInputText(text, filename, options = {}) {\n try {\n const trimmed = String(text || '').trim();\n if (!trimmed) {\n if (!options.append) {\n this.items = []; this.sourceHeaders = []; this.sourceKind = ''; this.emailFieldName=''; this.detectedEmailCount=0; this.saveActiveJob();\n }\n return;\n }\n\n // Always extract emails, regardless of whether it looks like JSON/CSV\n this.sourceKind = 'text'; // Explicitly set sourceKind to text\n const emails = this.extractEmailsFromText(trimmed);\n const objs = emails.map((email) => ({ email }));\n await this.ingestObjectsArray(objs, { append: !!options.append });\n\n this.saveActiveJob();\n } catch (_) {}\n },\n\n // Ensure a default job name exists before saving parsed content\n ensureDefaultJobName(sourceLabel) {\n try {\n if ((this.jobName || '').trim()) return;\n let candidate = this.nextDefaultJobName();\n // Avoid duplicates (paranoia)\n let ctr = 2;\n while (this.jobStore && this.jobStore[candidate]) { candidate = `job-${parseInt(candidate.split('-')[1] || '1', 10) + 1}`; ctr++; }\n this.jobName = candidate;\n this.jobInput = candidate;\n try { localStorage.setItem('mailcheck_job_name', candidate); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n } catch (_) {}\n },\n\n // Inline edit helpers\n enableEdit(idx) {\n try {\n const it = this.items[idx];\n if (!it) return;\n it._editingEmail = true;\n it._editEmailValue = this.getRecordEmail(it);\n } catch (_) {}\n },\n commitEdit(idx) {\n try {\n const it = this.items[idx];\n if (!it) return;\n const val = String(it._editEmailValue || '').trim();\n const key = (this.emailFieldName && (this.emailFieldName in it)) ? this.emailFieldName : 'email';\n it[key] = val;\n it.email = val;\n // reset status so it can be re-run\n it.bg_status = 'pending';\n it.bg_message = '';\n it.bg_checked_at = null;\n // end edit\n it._editingEmail = false;\n delete it._editEmailValue;\n this.recomputeDetectedEmails();\n this.saveActiveJob();\n } catch (_) {}\n },\n cancelEdit(idx) {\n try {\n const it = this.items[idx];\n if (!it) return;\n it._editingEmail = false;\n delete it._editEmailValue;\n } catch (_) {}\n },\n deleteItem(idx) {\n try {\n if (!confirm('Delete this row?')) return;\n if (idx < 0 || idx >= (this.items?.length || 0)) return;\n this.items.splice(idx, 1);\n this.recomputeDetectedEmails();\n this.saveActiveJob();\n } catch (_) {}\n },\n recomputeDetectedEmails() {\n try {\n this.detectedEmailCount = (this.items || []).reduce((acc, it) => acc + (this.getRecordEmail(it) ? 1 : 0), 0);\n } catch (_) { this.detectedEmailCount = 0; }\n },\n parseCsv(text) {\n // Minimal CSV parser supporting quotes and commas\n const rows = [];\n let row = [];\n let i = 0, inQuotes = false, field = '';\n const pushField = () => { row.push(field); field = ''; };\n const pushRow = () => { rows.push(row); row = []; };\n while (i < text.length) {\n const ch = text[i];\n if (inQuotes) {\n if (ch === '\"') {\n if (text[i + 1] === '\"') { field += '\"'; i++; } else { inQuotes = false; }\n } else { field += ch; }\n } else {\n if (ch === '\"') { inQuotes = true; }\n else if (ch === ',') { pushField(); }\n else if (ch === '\\n') { pushField(); pushRow(); }\n else if (ch === '\\r') { /* ignore */ }\n else { field += ch; }\n }\n i++;\n }\n // last field\n pushField();\n // last row if not added\n if (row.length > 0) pushRow();\n // Trim possible trailing empty row\n while (rows.length > 0 && rows[rows.length - 1].every(v => String(v || '').trim() === '')) rows.pop();\n // Determine headers: if first row has any non-email header-like strings, assume header row; else synthesize\n let headers = [];\n if (rows.length > 0) {\n const first = rows[0].map((s) => String(s || '').trim());\n const hasAlpha = first.some((s) => /[a-zA-Z]/.test(s));\n const looksHeaderish = hasAlpha && !first.every((s) => this.isEmail(s));\n if (looksHeaderish) {\n headers = first.map((h, idx) => h || ('col_' + (idx + 1)));\n rows.shift();\n } else {\n headers = first.map((_, idx) => 'col_' + (idx + 1));\n }\n }\n return { headers, rows };\n },\n async ingestCsvParsed(headers, rows, options = {}) {\n const normalizedHeaders = headers.map(h => String(h || '').trim());\n this.sourceHeaders = normalizedHeaders;\n // Build objects per row\n const items = rows.map((r) => {\n const obj = {};\n for (let i = 0; i < normalizedHeaders.length; i++) {\n const key = normalizedHeaders[i] || ('col_' + (i + 1));\n obj[key] = r[i] !== undefined ? r[i] : '';\n }\n return obj;\n });\n await this.ingestObjectsArray(items, { append: !!options.append });\n },\n async ingestObjectsArray(objs, options = {}) {\n const items = Array.isArray(objs) ? objs.map((o) => (o && typeof o === 'object') ? { ...o } : { value: String(o) }) : [];\n // Detect email field name if not already set\n if (!this.emailFieldName) this.emailFieldName = this.detectEmailFieldName(items);\n // Normalize each row with bg fields\n const newItems = items.map((it, idx) => {\n const email = this.extractEmailFromRecord(it);\n return {\n ...it,\n email: email || it.email || it.Email || it.e_mail || it.mail || '',\n _row_index: (this.items?.length || 0) + idx,\n bg_status: 'pending',\n bg_message: '',\n bg_checked_at: null\n };\n });\n if (options.append) {\n const existing = new Set((this.items || []).map((it) => this.emailKey(this.getRecordEmail(it))));\n const filtered = newItems.filter((it) => {\n const k = this.emailKey(this.getRecordEmail(it));\n if (!k) return false;\n if (existing.has(k)) return false;\n existing.add(k);\n return true;\n });\n this.items = [...(this.items || []), ...filtered];\n } else {\n this.items = newItems;\n }\n this.recomputeDetectedEmails();\n },\n emailKey(s) { return String(s || '').trim().toLowerCase(); },\n detectEmailFieldName(items) {\n // 1) Prefer property names that include 'email'\n const candidateNames = new Set();\n for (const it of (items || [])) {\n for (const k of Object.keys(it || {})) {\n const lower = k.toLowerCase();\n if (lower.includes('email')) candidateNames.add(k);\n }\n }\n if (candidateNames.size > 0) {\n // Choose the one with most valid-looking values\n let best = '', bestCount = -1;\n for (const k of candidateNames) {\n let count = 0;\n for (const it of (items || [])) { if (this.isEmail(String(it[k] || ''))) count++; }\n if (count > bestCount) { best = k; bestCount = count; }\n }\n if (best) return best;\n }\n // 2) Otherwise, scan all fields and pick the field with the most email-like values\n const counts = {};\n for (const it of (items || [])) {\n for (const [k, v] of Object.entries(it || {})) {\n if (this.isEmail(String(v || ''))) counts[k] = (counts[k] || 0) + 1;\n }\n }\n let maxK = '';\n let maxV = -1;\n for (const [k, v] of Object.entries(counts)) { if (v > maxV) { maxK = k; maxV = v; } }\n return maxV > 0 ? maxK : 'email';\n },\n isEmail(s) {\n const str = String(s || '').trim();\n if (!str) return false;\n // Simple, permissive email regex\n return /^[^\\s@]+@[^\\s@]+\\.[^\\s@]{2,}$/.test(str);\n },\n extractEmailsFromText(text) {\n try {\n const src = String(text || '');\n const matches = src.match(/[A-Z0-9._%+-]+@[A-Z0-9.-]+\\.[A-Z]{2,}/gi) || [];\n const seen = new Set();\n const out = [];\n for (let m of matches) {\n let e = String(m || '').trim();\n e = e.replace(/^[<({\\[\"']+/, '');\n e = e.replace(/[>)}\\]\"',.;:!?]+$/, '');\n e = e.toLowerCase();\n if (this.isEmail(e)) {\n const k = this.emailKey(e);\n if (!seen.has(k)) { seen.add(k); out.push(e); }\n }\n }\n return out;\n } catch (_) { return []; }\n },\n extractEmailFromRecord(it) {\n if (!it || typeof it !== 'object') return '';\n // 1) Direct by detected field name\n if (this.emailFieldName && it[this.emailFieldName]) return String(it[this.emailFieldName] || '').trim();\n // 2) Common keys\n for (const k of ['email', 'Email', 'e_mail', 'mail']) { if (it[k]) return String(it[k]).trim(); }\n // 3) Search values for email-looking string\n for (const v of Object.values(it)) { if (this.isEmail(v)) return String(v).trim(); }\n return '';\n },\n getRecordEmail(it) {\n return this.extractEmailFromRecord(it);\n },\n\n // Run checks with per-row updates\n async runChecks() {\n if (!Array.isArray(this.items) || this.items.length === 0) return;\n // Kick off a background run for the active job (include all rows)\n this.cancelRequested = false;\n this.startBackgroundRunForJob(this.jobName, { concurrency: this.concurrency, onlyPending: false });\n this.isRunning = true;\n this._watchActiveRunner();\n },\n async runPendingChecks() {\n if (!Array.isArray(this.items) || this.items.length === 0) return;\n // Kick off a background run for the active job (pending only)\n this.cancelRequested = false;\n this.startBackgroundRunForJob(this.jobName, { concurrency: this.concurrency, onlyPending: true });\n this.isRunning = true;\n this._watchActiveRunner();\n },\n // Individual row run for active job delegates to generic per-job API\n async runOne(idx) { return await this.runOneForJob(this.jobName, idx); },\n // Run one record by job name and row index (works even if a background run is active)\n async runOneForJob(jobName, idx) {\n try {\n const payload = this.jobStore && this.jobStore[jobName];\n if (!payload) return;\n const items = Array.isArray(payload.items) ? payload.items : [];\n if (idx < 0 || idx >= items.length) return;\n const rec = items[idx];\n if (!rec) return;\n if (rec.bg_status === 'checking') return; // already in flight\n const email = this.getRecordEmail ? this.getRecordEmail(rec) : (rec.email || '');\n // Clear previous per-check transient fields (fully reset assessment UI)\n delete rec.bg_compound_msg; delete rec.bg_compound_debug; delete rec.bg_browser_debug;\n delete rec.bg_compound_label; delete rec.bg_compound_short; delete rec.bg_compound_detail;\n delete rec.bg_browser_label; delete rec.bg_browser_short; delete rec.bg_browser_detail;\n delete rec.bg_final_label; delete rec.bg_final_short; delete rec.bg_final_detail;\n delete rec.bg_compound_evidence; delete rec.bg_browser_evidence; delete rec.bg_final_evidence;\n if (!email || !(this.isEmail && this.isEmail(email))) {\n rec.bg_status = 'error';\n rec.bg_message = 'No email detected';\n rec.bg_checked_at = new Date().toISOString();\n payload.items[idx] = rec; payload.updated_at = new Date().toISOString();\n this.jobStore[jobName] = payload; this.saveJobsToStorage(); this.refreshJobsArray();\n if (this.jobName === jobName) { this.items[idx] = { ...this.items[idx], ...rec }; this.recomputeDetectedEmails(); }\n return;\n }\n if (!this.hasServerKey && !this.userApiKey) throw new Error('No Groq API key set. Add a key to run checks.');\n // Mark as checking and persist before network call to avoid duplicate work by runners\n rec.bg_status = 'checking'; rec.bg_message = ''; rec.bg_checked_at = null;\n payload.items[idx] = rec; payload.updated_at = new Date().toISOString();\n this.jobStore[jobName] = payload; this.saveJobsToStorage(); this.refreshJobsArray();\n if (this.jobName === jobName) { this.items[idx] = { ...this.items[idx], ...rec }; this.recomputeDetectedEmails(); }\n // Perform the check\n const systemPrompt = payload?.meta?.systemPrompt || '';\n const result = await this.callBackgroundCheckApi(email, systemPrompt);\n rec.bg_status = result?.status || 'person_low';\n rec.bg_message = result?.message || '';\n if (result && result.fields && typeof result.fields === 'object') {\n for (const [k, v] of Object.entries(result.fields)) rec[k] = v;\n }\n rec.bg_checked_at = new Date().toISOString();\n payload.items[idx] = rec; payload.updated_at = new Date().toISOString();\n this.jobStore[jobName] = payload; this.saveJobsToStorage(); this.refreshJobsArray();\n if (this.jobName === jobName) { this.items[idx] = { ...this.items[idx], ...rec }; this.recomputeDetectedEmails(); }\n this.finishCheckForJob(jobName);\n } catch (e) {\n // Best-effort error capture to the active job if applicable\n try {\n const payload = this.jobStore && this.jobStore[jobName];\n if (!payload) return;\n const items = Array.isArray(payload.items) ? payload.items : [];\n if (idx < 0 || idx >= items.length) return;\n const rec = items[idx]; if (!rec) return;\n rec.bg_status = 'error';\n rec.bg_message = (e && e.message) ? e.message : 'Error';\n rec.bg_checked_at = new Date().toISOString();\n payload.items[idx] = rec; payload.updated_at = new Date().toISOString();\n this.jobStore[jobName] = payload; this.saveJobsToStorage(); this.refreshJobsArray();\n if (this.jobName === jobName) { this.items[idx] = { ...this.items[idx], ...rec }; this.recomputeDetectedEmails(); }\n this.finishCheckForJob(jobName);\n } catch (_) {}\n }\n },\n async runOne(idx) {\n try {\n if (idx < 0 || idx >= (this.items?.length || 0)) return;\n const rec = this.items[idx];\n if (!rec) return;\n if (!this.getRecordEmail(rec)) {\n rec.bg_status = 'error';\n rec.bg_message = 'No email detected';\n rec.bg_checked_at = new Date().toISOString();\n this.saveActiveJob();\n return;\n }\n // Clear prior assessment fields for this row (fully reset)\n delete rec.bg_compound_msg;\n delete rec.bg_compound_debug;\n delete rec.bg_browser_debug;\n delete rec.bg_compound_label;\n delete rec.bg_compound_short;\n delete rec.bg_compound_detail;\n delete rec.bg_browser_label;\n delete rec.bg_browser_short;\n delete rec.bg_browser_detail;\n delete rec.bg_final_label;\n delete rec.bg_final_short;\n delete rec.bg_final_detail;\n delete rec.bg_compound_evidence;\n delete rec.bg_browser_evidence;\n delete rec.bg_final_evidence;\n rec.bg_status = 'checking';\n rec.bg_message = '';\n this.saveActiveJob();\n // Ensure sidebar reflects running state for per-row checks\n try { this._refreshJobRunningMap(); this._watchActiveRunner(); } catch (_) {}\n if (!this.hasServerKey && !this.userApiKey) throw new Error('No Groq API key set. Add a key to run checks.');\n const email = this.getRecordEmail(rec);\n const result = await this.callBackgroundCheckApi(email, this.systemPrompt);\n rec.bg_status = result?.status || 'person_low';\n rec.bg_message = result?.message || '';\n if (result && result.fields && typeof result.fields === 'object') {\n for (const [k, v] of Object.entries(result.fields)) rec[k] = v;\n }\n rec.bg_checked_at = new Date().toISOString();\n } catch (e) {\n const rec = this.items[idx];\n if (rec) {\n rec.bg_status = 'error';\n rec.bg_message = (e && e.message) ? e.message : 'Error';\n rec.bg_checked_at = new Date().toISOString();\n }\n } finally {\n this.saveActiveJob();\n try { this.finishCheckForJob(this.jobName); } catch (_) {}\n }\n },\n cancelRun() {\n this.cancelRequested = true;\n try { if (this.jobName) this.cancelBackgroundRunForJob(this.jobName); } catch (_) {}\n // isRunning will flip false when the runner loop drains; also stop UI watcher\n try { if (this._activeRunnerInterval) { clearInterval(this._activeRunnerInterval); this._activeRunnerInterval = null; } } catch (_) {}\n },\n async runSingleCheck() {\n try {\n const raw = String(this.singleEmailInput || '').trim();\n let email = '';\n if (this.isEmail(raw)) {\n email = raw;\n } else {\n const found = this.extractEmailsFromText(raw);\n email = (found && found.length > 0) ? found[0] : '';\n }\n if (!email) return;\n if (!this.hasServerKey && !this.userApiKey) throw new Error('No Groq API key set. Add a key to run checks.');\n this.singleChecking = true;\n this.singleResult = null;\n // Ensure we have an active job to reflect sidebar state\n this.ensureDefaultJobName('(single)');\n // clear UI debug leftovers and transient fields\n for (const it of (this.items || [])) {\n delete it.bg_compound_debug;\n delete it.bg_browser_debug;\n }\n // Pre-mark target record as checking so sidebar shows spinner\n const key = this.emailKey(email);\n let idx = -1;\n for (let i = 0; i < (this.items?.length || 0); i++) {\n const k = this.emailKey(this.getRecordEmail(this.items[i]));\n if (k && k === key) { idx = i; break; }\n }\n if (idx >= 0) {\n const rec = this.items[idx];\n delete rec.bg_compound_msg;\n delete rec.bg_compound_label;\n delete rec.bg_compound_short;\n delete rec.bg_compound_detail;\n delete rec.bg_browser_label;\n delete rec.bg_browser_short;\n delete rec.bg_browser_detail;\n delete rec.bg_final_label;\n delete rec.bg_final_short;\n delete rec.bg_final_detail;\n delete rec.bg_compound_evidence;\n delete rec.bg_browser_evidence;\n delete rec.bg_final_evidence;\n rec.bg_status = 'checking';\n rec.bg_message = '';\n rec.bg_checked_at = null;\n this.items[idx] = rec;\n } else {\n const rec = {\n email,\n _row_index: (this.items?.length || 0),\n bg_status: 'checking',\n bg_message: '',\n bg_checked_at: null\n };\n this.items = [...(this.items || []), rec];\n this.recomputeDetectedEmails();\n idx = this.items.length - 1;\n }\n this.saveActiveJob();\n try { this._refreshJobRunningMap(); this._watchActiveRunner(); } catch (_) {}\n\n // Perform the check\n const result = await this.callBackgroundCheckApi(email, this.systemPrompt);\n this.singleResult = result;\n\n // Update the record with results\n const rec2 = this.items[idx] || { email, _row_index: idx };\n rec2.bg_status = result?.status || 'person_low';\n rec2.bg_message = result?.message || '';\n if (result && result.fields && typeof result.fields === 'object') {\n for (const [k, v] of Object.entries(result.fields)) rec2[k] = v;\n }\n rec2.bg_checked_at = new Date().toISOString();\n this.items[idx] = rec2;\n this.saveActiveJob();\n try { this._refreshJobRunningMap(); } catch (_) {}\n } catch (e) {\n this.singleResult = { email: this.singleEmailInput, status: 'error', message: (e && e.message) ? e.message : 'Error', fields: {} };\n } finally {\n this.singleChecking = false;\n try { this.finishCheckForJob(this.jobName); } catch (_) {}\n // Re-focus the single input for quick subsequent checks\n try { const el = document.querySelector('input[x-ref=\"singleEmailInputRef\"]'); if (el) el.focus(); } catch (_) {}\n }\n },\n // Background check orchestrator — sequentially runs an array of checker functions\n async backgroundCheck(email, prompt) {\n const checkers = this.buildCheckers(prompt);\n const messages = [];\n let status = undefined;\n const fields = {};\n for (const checker of checkers) {\n try {\n // Each checker may be sync or async\n // Shape: { status?, message?, fields? }\n const res = await checker(email);\n if (!res) continue;\n if (res.message) messages.push(String(res.message));\n if (res.fields && typeof res.fields === 'object') Object.assign(fields, res.fields);\n if (res.status) status = this.mergeStatus(status, res.status);\n } catch (_) { /* ignore individual checker errors */ }\n }\n // Fallback classification if still unset\n if (!status) {\n const fb = await this.heuristicFallbackChecker(email);\n status = fb.status;\n if (fb.message) messages.push(fb.message);\n }\n return { status, message: messages.join('; ') || this.statusToMessage(status), fields };\n },\n\n async callBackgroundCheckApi(email, systemPrompt) {\n const resp = await fetch('/api/check/background', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ email, systemPrompt: systemPrompt || '', userApiKey: this.userApiKey || undefined, whitelist: this.parseListText(this.whitelistText), blacklist: this.parseListText(this.blacklistText) })\n });\n if (!resp.ok) throw new Error(await resp.text().catch(() => resp.statusText));\n return await resp.json();\n },\n\n parseListText(text) {\n try {\n // Only split on newlines; commas are valid inside regex quantifiers (e.g., {2,4})\n const src = String(text || '').replace(/[\\r\\n]+/g, '\\n');\n const lines = src.split('\\n').map(s => String(s || '').trim()).filter(Boolean);\n const seen = new Set();\n const out = [];\n for (const s of lines) { const key = s.startsWith('/') ? s : s.toLowerCase(); if (!seen.has(key)) { seen.add(key); out.push(s); } }\n return out;\n } catch (_) { return []; }\n },\n\n // Compose the list of checkers to run in order\n buildCheckers(prompt) {\n return [\n // 1) Basic syntax validation\n async (email) => {\n if (!this.isEmail(email)) return { status: 'undeliverable', message: 'Invalid email format' };\n return { status: undefined };\n },\n // 2) Academic domain check (server-assisted)\n async (email) => {\n try {\n const info = await this.checkAcademic(email);\n if (!info) return null;\n const fields = { bg_academic: !!info.isAcademic };\n if (info.institution) fields.bg_institution = info.institution;\n // Academic domains are not penalized; annotate message only\n if (info.isAcademic) {\n const short = info.institution ? String(info.institution) : 'Academic domain';\n fields.bg_academic_msg = short;\n return { message: short, fields };\n }\n return { fields };\n } catch (_) {\n return null;\n }\n },\n // 2b) LLM legitimacy check (optional; annotate + potential status nudge)\n async (email) => {\n try {\n if (!this.userApiKey && !this.hasServerKey) return null;\n const data = await this.callLlmEmailCheck(email, prompt);\n if (!data) return null;\n const out = { fields: data.fields || {}, message: data.message || '' };\n if (data.status && (data.status === 'person_high' || data.status === 'person_low' || data.status === 'person_none' || data.status === 'spam')) {\n out.status = data.status;\n }\n if (out.message) out.fields.bg_compound_msg = out.message;\n return out;\n } catch (_) { return null; }\n },\n // 3) Role/alias heuristic (flag as suspicious)\n async (email) => {\n try {\n const local = String(email || '').split('@')[0].toLowerCase();\n const roleList = ['info', 'support', 'admin', 'sales', 'contact', 'hello', 'team', 'marketing', 'noreply', 'no-reply'];\n if (roleList.includes(local)) return { status: 'person_none', message: 'Role-based address' };\n return null;\n } catch (_) { return null; }\n }\n ];\n },\n\n async callLlmEmailCheck(email, systemPrompt) {\n try {\n const resp = await fetch('/api/check/llm-email', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ email, systemPrompt: systemPrompt || '', userApiKey: this.userApiKey || undefined })\n });\n if (!resp.ok) return null;\n return await resp.json();\n } catch (_) { return null; }\n },\n\n async heuristicFallbackChecker(email) {\n // Default to person_low when heuristic needed; avoid penalizing good emails\n await new Promise((res) => setTimeout(res, 120 + Math.floor(Math.random() * 300)));\n return { status: 'person_low', message: '' };\n },\n\n async checkAcademic(email) {\n try {\n const resp = await fetch('/api/check/academic', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ email })\n });\n if (!resp.ok) return null;\n const data = await resp.json();\n return { isAcademic: !!data?.isAcademic, institution: data?.institution || null };\n } catch (_) { return null; }\n },\n\n mergeStatus(current, next) {\n if (!next) return current || undefined;\n if (!current) return next;\n const score = (s) => (s === 'spam' ? 4 : s === 'person_none' ? 3 : s === 'person_low' ? 2 : s === 'person_high' ? 1 : 0);\n return score(next) >= score(current) ? next : current;\n },\n\n // Display label for statuses (new person confidence scale + legacy)\n statusLabel(status) {\n if (status === 'academic') return 'academic';\n if (status === 'whitelist') return 'whitelist';\n if (status === 'person_high') return 'likely real person';\n if (status === 'person_low') return 'possible person';\n if (status === 'person_none') return 'no evidence';\n if (status === 'spam') return 'spam';\n if (status === 'person_high') return 'likely real person';\n if (status === 'person_low') return 'possible person';\n if (status === 'person_none') return 'no evidence';\n if (status === 'spam') return 'spam';\n if (status === 'checking') return 'checking';\n if (status === 'error') return 'error';\n return String(status || '');\n },\n statusToMessage(status) {\n if (status === 'person_high') return 'Likely real person';\n if (status === 'person_low') return 'Possible person';\n if (status === 'person_none') return 'No public identity evidence';\n if (status === 'spam') return 'Spam or invalid';\n if (status === 'deliverable') return 'Looks good: deliverable address';\n if (status === 'suspicious') return 'Risky patterns: disposable/role-based or malformed parts';\n if (status === 'undeliverable') return 'Likely bounce or spamtrap';\n if (status === 'checking') return 'Checking...';\n if (status === 'error') return 'Error checking email';\n return String(status || '');\n },\n\n // Downloads\n downloadCsv() {\n try {\n const { headers, rows } = this.buildOutputTable();\n const escapeCsv = (v) => {\n const s = (v === null || v === undefined) ? '' : String(v);\n if (/[\",\\n]/.test(s)) return '\"' + s.replace(/\"/g, '\"\"') + '\"';\n return s;\n };\n const out = [headers.map(escapeCsv).join(',')];\n for (const r of rows) out.push(r.map(escapeCsv).join(','));\n const csv = out.join('\\n');\n const blob = new Blob([csv], { type: 'text/csv;charset=utf-8' });\n const url = URL.createObjectURL(blob);\n const a = document.createElement('a');\n a.href = url; a.download = (this.jobName ? (this.jobName + '_') : '') + 'mailcheck.csv';\n document.body.appendChild(a); a.click(); a.remove();\n URL.revokeObjectURL(url);\n } catch (_) {}\n },\n downloadJson() {\n try {\n const arr = this.buildOutputObjects();\n const blob = new Blob([JSON.stringify(arr, null, 2)], { type: 'application/json' });\n const url = URL.createObjectURL(blob);\n const a = document.createElement('a');\n a.href = url; a.download = (this.jobName ? (this.jobName + '_') : '') + 'mailcheck.json';\n document.body.appendChild(a); a.click(); a.remove();\n URL.revokeObjectURL(url);\n } catch (_) {}\n },\n async copyJson() {\n try { await navigator.clipboard.writeText(JSON.stringify(this.buildOutputObjects(), null, 2)); } catch (_) {}\n },\n buildOutputObjects() {\n // Preserve original fields, plus bg_status and bg_message\n const out = [];\n for (const it of (this.items || [])) {\n const obj = { ...it };\n // Keep explicit fields\n obj.bg_status = it.bg_status || 'pending';\n obj.bg_message = it.bg_message || '';\n obj.bg_checked_at = it.bg_checked_at || null;\n // Remove internal helper fields\n delete obj._row_index;\n out.push(obj);\n }\n return out;\n },\n buildOutputTable() {\n // Construct headers from input headers or dynamic keys\n const rows = [];\n const keysSet = new Set();\n if (Array.isArray(this.sourceHeaders) && this.sourceHeaders.length > 0) {\n for (const h of this.sourceHeaders) keysSet.add(h);\n } else {\n for (const it of (this.items || [])) {\n for (const k of Object.keys(it || {})) {\n if (k === '_row_index' || k === '_editingEmail' || k === '_editEmailValue') continue;\n keysSet.add(k);\n }\n }\n }\n // Ensure email field present\n if (this.emailFieldName && !keysSet.has(this.emailFieldName)) keysSet.add(this.emailFieldName);\n // Add bg fields at end\n const headers = Array.from(keysSet);\n for (const k of ['bg_status', 'bg_message', 'bg_checked_at']) if (!headers.includes(k)) headers.push(k);\n for (const it of (this.items || [])) {\n const row = headers.map((h) => it[h] !== undefined ? it[h] : '');\n rows.push(row);\n }\n return { headers, rows };\n },\n\n // UI helpers\n get totalCount() { return Array.isArray(this.items) ? this.items.length : 0; },\n get pendingCount() {\n let n = 0;\n for (const it of (this.items || [])) { if (it && (!it.bg_checked_at || it.bg_status === 'pending' || !it.bg_status)) n++; }\n return n;\n },\n get completedCount() {\n let n = 0;\n for (const it of (this.items || [])) {\n if (it && (it.bg_status === 'person_high' || it.bg_status === 'person_low' || it.bg_status === 'person_none' || it.bg_status === 'spam' || it.bg_status === 'not_spam' || it.bg_status === 'suspected_spam' || it.bg_status === 'likely_spam' || it.bg_status === 'academic' || it.bg_status === 'whitelist' || it.bg_status === 'error')) n++;\n }\n return n;\n },\n badgeClass(status) {\n if (status === 'person_high' || status === 'not_spam' || status === 'academic' || status === 'whitelist') return 'bg-green-100 text-green-800 border-green-200';\n if (status === 'person_low' || status === 'suspected_spam') return 'bg-amber-100 text-amber-800 border-amber-200';\n if (status === 'person_none') return 'bg-gray-100 text-gray-800 border-gray-300';\n if (status === 'spam' || status === 'likely_spam' || status === 'error') return 'bg-red-100 text-red-800 border-red-200';\n if (status === 'checking') return 'bg-blue-100 text-blue-800 border-blue-200';\n return 'bg-gray-100 text-gray-800 border-gray-200';\n },\n\n // i18n\n get i18n() {\n return {\n title: 'Email Background Checker',\n subtitle: 'Upload or paste emails; verify they belong to real people.',\n apiKey: 'API Key:', change: 'Change', clear: 'Clear', getKeyHere: 'Get your free key here'\n };\n }\n };\n try { _attachWatchActiveRunner(inst); } catch (_) {}\n return inst;\n}\n\n// createJobRunner\n// A small, copyable background runner that processes a single job's items with\n// controlled concurrency. It runs independently from UI state and persists\n// progress safely back into app.jobStore[jobName].\n//\n// Usage:\n// const runner = createJobRunner(app, 'my-job', { concurrency: 8, onlyPending: true });\n// runner.start();\n// runner.cancel();\n// const s = runner.status(); // { running, cancelled, total, completed }\nfunction createJobRunner(app, jobName, options = {}) {\n // Internal runner state — not reactive\n const state = {\n running: false,\n cancelled: false,\n total: 0,\n completed: 0\n };\n\n // Persist the updated job payload back to localStorage via app helpers,\n // refresh sidebar job counts, and live-update the UI list if this job is active.\n function persistAndMaybeUpdateUi(updatedPayload, idx) {\n try {\n app.jobStore[jobName] = updatedPayload;\n app.saveJobsToStorage();\n app.refreshJobsArray();\n if (app.jobName === jobName) {\n const uiItems = app.items || [];\n const jobItems = updatedPayload.items || [];\n if (idx >= 0 && idx < jobItems.length && idx < uiItems.length) {\n const updated = jobItems[idx];\n // Basic defensive sync by index\n app.items[idx] = { ...app.items[idx], ...updated };\n }\n app.recomputeDetectedEmails();\n }\n } catch (_) {}\n }\n\n // Build the list of indices to process for the job\n function collectTargetIndices(items) {\n const onlyPending = options.onlyPending !== false;\n const indices = [];\n for (let i = 0; i < (items?.length || 0); i++) {\n const it = items[i];\n if (!it) continue;\n if (!onlyPending) { indices.push(i); continue; }\n const pending = (!it.bg_checked_at || it.bg_status === 'pending' || !it.bg_status);\n if (pending) indices.push(i);\n }\n return indices;\n }\n\n async function start() {\n if (state.running) return;\n state.running = true;\n state.cancelled = false;\n try {\n const payload = app.jobStore && app.jobStore[jobName] ? { ...app.jobStore[jobName] } : null;\n if (!payload) { state.running = false; return; }\n const items = Array.isArray(payload.items) ? payload.items.slice() : [];\n const systemPrompt = payload?.meta?.systemPrompt || '';\n const indices = collectTargetIndices(items);\n state.total = indices.length;\n state.completed = 0;\n if (indices.length === 0) { state.running = false; return; }\n\n // Pre-mark queued rows as checking (or error if no email) and persist\n for (const idx of indices) {\n const rec = items[idx];\n if (!rec) continue;\n const email = app.getRecordEmail ? app.getRecordEmail(rec) : (rec.email || '');\n // Clear previous per-check transient fields\n delete rec.bg_compound_msg; delete rec.bg_compound_debug; delete rec.bg_browser_debug;\n delete rec.bg_compound_label; delete rec.bg_compound_short; delete rec.bg_compound_detail;\n delete rec.bg_browser_label; delete rec.bg_browser_short; delete rec.bg_browser_detail;\n delete rec.bg_compound_evidence; delete rec.bg_browser_evidence; delete rec.bg_final_evidence;\n if (!email || !(app.isEmail && app.isEmail(email))) {\n rec.bg_status = 'error';\n rec.bg_message = 'No email detected';\n rec.bg_checked_at = new Date().toISOString();\n } else {\n rec.bg_status = 'checking';\n rec.bg_message = '';\n rec.bg_checked_at = null;\n }\n payload.items[idx] = rec; payload.updated_at = new Date().toISOString();\n persistAndMaybeUpdateUi(payload, idx);\n }\n\n const limit = Math.max(1, Number(options.concurrency || app.concurrency) || 8);\n let cursor = 0;\n const runNext = async () => {\n if (state.cancelled) return;\n if (cursor >= indices.length) return;\n const idx = indices[cursor++];\n const rec = items[idx];\n if (!rec) { state.completed++; return runNext(); }\n if (rec.bg_status === 'error') { state.completed++; return runNext(); }\n try {\n const email = app.getRecordEmail ? app.getRecordEmail(rec) : (rec.email || '');\n if (!app.hasServerKey && !app.userApiKey) throw new Error('No Groq API key set. Add a key to run checks.');\n // Fully clear any previous assessment fields before each call\n delete rec.bg_compound_msg; delete rec.bg_compound_debug; delete rec.bg_browser_debug;\n delete rec.bg_compound_label; delete rec.bg_compound_short; delete rec.bg_compound_detail;\n delete rec.bg_browser_label; delete rec.bg_browser_short; delete rec.bg_browser_detail;\n delete rec.bg_final_label; delete rec.bg_final_short; delete rec.bg_final_detail;\n delete rec.bg_compound_evidence; delete rec.bg_browser_evidence; delete rec.bg_final_evidence;\n const result = await app.callBackgroundCheckApi(email, systemPrompt);\n rec.bg_status = result?.status || 'person_low';\n rec.bg_message = result?.message || '';\n if (result && result.fields && typeof result.fields === 'object') {\n for (const [k, v] of Object.entries(result.fields)) rec[k] = v;\n }\n rec.bg_checked_at = new Date().toISOString();\n } catch (e) {\n rec.bg_status = 'error';\n rec.bg_message = (e && e.message) ? e.message : 'Error';\n rec.bg_checked_at = new Date().toISOString();\n } finally {\n // Write back the single record and persist\n payload.items[idx] = rec;\n payload.updated_at = new Date().toISOString();\n persistAndMaybeUpdateUi(payload, idx);\n state.completed++;\n await runNext();\n }\n };\n const runners = [];\n for (let k = 0; k < limit; k++) runners.push(runNext());\n await Promise.all(runners);\n } catch (_) {\n // swallow\n } finally {\n state.running = false;\n }\n }\n\n function cancel() { state.cancelled = true; }\n function status() { return { running: state.running, cancelled: state.cancelled, total: state.total, completed: state.completed }; }\n\n return { start, cancel, status };\n}\n\n// UI helper: watch the active job runner state and reflect it in isRunning\n// Stops automatically when the runner finishes or job changes\n// (attached to the component instance via function expression to access `this`)\nmailcheckApp.prototype = mailcheckApp.prototype || {};\n// Attach as method on the returned object instead (Alpine pattern)\n// eslint-disable-next-line no-unused-vars\nfunction _attachWatchActiveRunner(instance) {\n instance._watchActiveRunner = function () {\n try { if (this._activeRunnerInterval) { clearInterval(this._activeRunnerInterval); this._activeRunnerInterval = null; } } catch (_) {}\n this._activeRunnerInterval = setInterval(() => {\n try {\n const s = this.getBackgroundRunStatus(this.jobName);\n this.isRunning = !!(s && s.running);\n // Keep a per-job map for sidebar indicators\n this._refreshJobRunningMap();\n // Stop watcher when no jobs are active or checking\n let anyRunning = false;\n try { anyRunning = Object.values(this.jobRunningMap || {}).some(Boolean); } catch (_) { anyRunning = this.isRunning; }\n if (!anyRunning) { clearInterval(this._activeRunnerInterval); this._activeRunnerInterval = null; }\n } catch (_) {\n try { clearInterval(this._activeRunnerInterval); this._activeRunnerInterval = null; } catch (_) {}\n }\n }, 400);\n };\n}\n// (wrapper removed) — default export is now the single factory with watcher injection\n\n\n\n",[],[232,351],"c4518880-9810-11f0-90e5-0224a6c84d84",["D",1758585822824],[],[232,33],["D",1756156596788],[275,276],[232],"a97787dc-8530-11f0-a8b8-0224a6c84d84","utils.js","a977889a-8530-11f0-a8b8-0224a6c84d84","a911465c-8530-11f0-b5d8-0224a6c84d84",116,["D",1756510449622],"// Shared assessment utilities\n\nexport function isEmailAddress(s) {\n const str = String(s || '').trim();\n if (!str) return false;\n return /^[^\\s@]+@[^\\s@]+\\.[^\\s@]{2,}$/.test(str);\n}\n\nexport function mergeSpamStatus(current, next) {\n if (!next) return current || undefined;\n if (!current) return next;\n const score = (s) => (s === 'likely_spam' ? 3 : s === 'suspected_spam' ? 2 : s === 'not_spam' ? 1 : 0);\n return score(next) >= score(current) ? next : current;\n}\n\nexport function mergeStatus(current, next) {\n if (!next) return current || undefined;\n if (!current) return next;\n const score = (s) => (s === 'spam' ? 4 : s === 'person_none' ? 3 : s === 'person_low' ? 2 : s === 'person_high' ? 1 : 0);\n return score(next) >= score(current) ? next : current;\n}\n\nexport function extractJsonBetweenTags(text) {\n try {\n if (!text) return null;\n const m = String(text).match(/[\\s\\S]*?<\\/json>/i);\n const slice = m ? m[0] : null;\n if (!slice) return null;\n const inner = slice.replace(/^/i, '').replace(/<\\/json>$/i, '');\n const trimmed = inner.trim();\n return JSON.parse(trimmed);\n } catch (err) {\n try { console.error('Failed to parse JSON between tags:', err && err.message ? err.message : String(err)); } catch (_) {}\n return null;\n }\n}\n\nexport function logGroqCurl(tag, apiKey, payload) {\n try {\n const compact = JSON.stringify(payload);\n const esc = compact.replace(/'/g, `'\"'\"'`);\n const curl = [\n \"curl --request POST \\\\\\n\",\n \" --url https://api.groq.com/openai/v1/chat/completions \\\\\\n\",\n \" --header 'authorization: Bearer \" + apiKey + \"' \\\\\\n\",\n \" --header 'content-type: application/json' \\\\\\n\",\n \" --data '\" + esc + \"'\"\n ].join('');\n console.log(\">> [\" + tag + \"] curl script:\\n\" + curl);\n } catch (_) {}\n}\n\nexport function coerceJsonFromText(text) {\n try {\n if (!text) return null;\n const raw = String(text);\n const firstBrace = raw.indexOf('{');\n const lastBrace = raw.lastIndexOf('}');\n if (firstBrace !== -1 && lastBrace > firstBrace) {\n const candidate = raw.slice(firstBrace, lastBrace + 1);\n try { return JSON.parse(candidate); } catch (_) {}\n }\n const statusMatch = raw.match(/status\\s*[:=]\\s*[\"']?([a-zA-Z_]+)[\"']?/);\n const messageMatch = raw.match(/message\\s*[:=]\\s*[\"']([^\"']+)[\"']/);\n const explMatch = raw.match(/explanation_short\\s*[:=]\\s*[\"']([^\"']+)[\"']/);\n const out = {};\n if (statusMatch) out.status = statusMatch[1];\n if (messageMatch) out.message = messageMatch[1];\n if (explMatch) out.explanation_short = explMatch[1];\n return Object.keys(out).length > 0 ? out : null;\n } catch (_) { return null; }\n}\n\nexport function getEmailDomain(address) {\n try { return String(address || '').split('@')[1]?.toLowerCase() || ''; } catch (_) { return ''; }\n}\n\nexport function isGenericEmailDomain(domain) {\n const generic = new Set(['gmail.com','yahoo.com','outlook.com','hotmail.com','icloud.com','gmx.com','aol.com','proton.me','protonmail.com','mail.com','yandex.com']);\n return generic.has(String(domain || '').toLowerCase());\n}\n\nexport function dedupeStrings(arr) {\n const seen = new Set();\n const out = [];\n for (const s of (arr || [])) { const v = String(s || '').trim(); if (v && !seen.has(v)) { seen.add(v); out.push(v); } }\n return out;\n}\n\nexport function statusToLabel(status) {\n if (status === 'spam') return 'spam';\n if (status === 'person_none') return 'no evidence';\n if (status === 'person_low') return 'possible person';\n if (status === 'likely_spam') return 'spam';\n if (status === 'suspected_spam') return 'suspicious';\n if (status === 'not_spam' || status === 'person_high') return 'likely real person';\n return String(status || '');\n}\n\nexport function cleanDetailText(text) {\n try {\n if (!text) return '';\n let s = String(text);\n s = s.replace(/[\\s\\S]*?<\\/tool>/gi, '').replace(/[\\s\\S]*?<\\/output>/gi, '');\n s = s.replace(/[\\s\\S]*?<\\/json>/gi, '');\n s = s.replace(/[ \\t]+/g, ' ').replace(/\\n{3,}/g, '\\n\\n').trim();\n const paras = s.split(/\\n\\s*\\n/).filter(p => p && p.trim());\n const limited = paras.slice(0, 3).map(p => p.trim().slice(0, 500));\n const joined = limited.join('\\n\\n').trim();\n return joined.slice(0, 1400);\n } catch (_) { return ''; }\n}\n\nexport function deriveIdentityShort(explanation) {\n try {\n if (!explanation) return '';\n let s = String(explanation).trim();\n try {\n const parts = s.split(/(?<=[.!?])\\s+/).filter(Boolean);\n if (parts.length > 0) s = parts[0];\n } catch (_) {}\n if (s.length > 200) s = s.slice(0, 199).replace(/[,;:\\s]+$/, '').trim() + '…';\n return s;\n } catch (_) { return ''; }\n}\n\n\n",[],[238,374,366],"assessments","a957cd16-8530-11f0-b9d8-0224a6c84d84","a957cde8-8530-11f0-b9d8-0224a6c84d84",110,["D",1756510449433],"// Central aggregator for assessments\n// Exposes a single backgroundAssessEmail() used by API routes\n\nimport { isEmailAddress as uIsEmailAddress, mergeSpamStatus as uMergeSpamStatus, getEmailDomain as uGetEmailDomain, isGenericEmailDomain as uIsGenericEmailDomain, dedupeStrings as uDedupeStrings, statusToLabel as uStatusToLabel } from './utils.js';\nimport { preWhitelistAssess as modPreWhitelistAssess } from './pre/whitelist.js';\nimport { preAcademicAssess as modPreAcademicAssess } from './pre/academic.js';\nimport { preBlacklistAssess as modPreBlacklistAssess } from './pre/blacklist.js';\nimport { roleHeuristicAssess as modRoleHeuristicAssess } from './full/roleHeuristic.js';\nimport { llmCompoundAssess as modLlmCompoundAssess } from './full/llmCompound.js';\nimport { browserSearchAssess as modBrowserSearchAssess } from './full/browserSearch.js';\nimport { finalJudgeAssess as modFinalJudgeAssess } from './full/finalJudge.js';\n\nexport async function backgroundAssessEmail(apiKey, email, systemPrompt, whitelistRules, blacklistRules) {\n let status = undefined; const messages = []; const fields = {};\n const assessments = [];\n if (!uIsEmailAddress(email)) { status = 'spam'; messages.push('Invalid email format'); }\n\n // Pre-assessments (early exits)\n try { console.log('>> [pre] starting', { email, whitelistCount: Array.isArray(whitelistRules) ? whitelistRules.length : 0, blacklistCount: Array.isArray(blacklistRules) ? blacklistRules.length : 0 }); } catch (_) {}\n const preAssessors = [\n { name: 'whitelist', run: () => modPreWhitelistAssess(email, whitelistRules) },\n { name: 'academic', run: () => modPreAcademicAssess(email) },\n { name: 'blacklist', run: () => modPreBlacklistAssess(email, blacklistRules) },\n ];\n for (const pre of preAssessors) {\n try {\n const r = await pre.run();\n try { console.log('>> [pre] result', pre.name, r); } catch (_) {}\n if (r && r.decided) {\n if (r.fields) Object.assign(fields, r.fields);\n if (r.assessment) assessments.push(r.assessment);\n fields.bg_assessments = assessments;\n return { email, status: r.status, message: r.message || '', fields, assessments };\n }\n } catch (_) {}\n }\n\n const role = modRoleHeuristicAssess(email);\n if (role.status) status = uMergeSpamStatus(status, role.status);\n if (role.message) messages.push(role.message);\n\n try {\n let llm = null; let browse = null;\n const [llmRes, browseRes] = await Promise.allSettled([\n modLlmCompoundAssess(apiKey, email, systemPrompt),\n modBrowserSearchAssess(apiKey, email, systemPrompt)\n ]);\n if (llmRes.status === 'fulfilled') {\n llm = llmRes.value;\n if (llm) {\n if (llm.status) status = uMergeSpamStatus(status, llm.status);\n if (llm.message) fields.bg_compound_msg = llm.message;\n if (llm.status) fields.bg_compound_label = uStatusToLabel(llm.status);\n if (!fields.bg_compound_short && llm.message) fields.bg_compound_short = llm.message;\n if (llm.fields) Object.assign(fields, llm.fields);\n assessments.push({ name: 'compound', status: llm.status || null, message: llm.message || null });\n }\n } else {\n try { console.error('>> [compound] error:', llmRes.reason && llmRes.reason.message ? llmRes.reason.message : String(llmRes.reason)); } catch (_) {}\n fields.bg_compound_debug = llmRes.reason && llmRes.reason.message ? llmRes.reason.message : String(llmRes.reason);\n }\n if (browseRes.status === 'fulfilled') {\n browse = browseRes.value;\n if (browse) {\n if (browse.status) status = uMergeSpamStatus(status, browse.status);\n if (browse.message) fields.bg_browser_msg = browse.message;\n if (!fields.bg_browser_short && browse.message) fields.bg_browser_short = browse.message;\n if (browse.fields) Object.assign(fields, browse.fields);\n assessments.push({ name: 'browser', status: browse.status || null, message: browse.message || null });\n }\n } else {\n try { console.error('>> [browser] error:', browseRes.reason && browseRes.reason.message ? browseRes.reason.message : String(browseRes.reason)); } catch (_) {}\n fields.bg_browser_debug = browseRes.reason && browseRes.reason.message ? browseRes.reason.message : String(browseRes.reason);\n }\n\n // Final judge\n const d = uGetEmailDomain(email);\n const evidence = {\n academic: { academic: !!fields.bg_academic, institution: fields.bg_institution || null },\n role: { message: role.message || null, status: role.status || null },\n domain: { domain: d || null, generic_provider: d ? uIsGenericEmailDomain(d) : null },\n compound: { status: llm?.status || null, message: llm?.message || null, short: fields.bg_compound_short || null, label: fields.bg_compound_label || null, evidence: Array.isArray(fields.bg_compound_evidence) ? fields.bg_compound_evidence : [] },\n browser: { status: browse?.status || null, message: browse?.message || null, short: fields.bg_browser_short || null, label: fields.bg_browser_label || null, evidence: Array.isArray(fields.bg_browser_evidence) ? fields.bg_browser_evidence : [] }\n };\n try { console.log('>> [final judge] evidence:', JSON.stringify(evidence)); } catch (_) {}\n const judge = await modFinalJudgeAssess(apiKey, email, systemPrompt, evidence);\n if (judge) {\n if (judge.status) status = judge.status;\n if (judge.message && !fields.bg_final_short) fields.bg_final_short = judge.message;\n if (judge.fields) Object.assign(fields, judge.fields);\n assessments.push({ name: 'final_judge', status: judge.status || null, message: judge.message || null });\n }\n try { console.log('>> [final judge] judge:', JSON.stringify(judge)); } catch (_) {}\n\n // Consolidate evidence bullets and UI detail if missing\n const allEvidence = [];\n if (Array.isArray(fields.bg_final_evidence)) allEvidence.push(...fields.bg_final_evidence);\n if (Array.isArray(fields.bg_browser_evidence)) allEvidence.push(...fields.bg_browser_evidence);\n if (Array.isArray(fields.bg_compound_evidence)) allEvidence.push(...fields.bg_compound_evidence);\n const domain = uGetEmailDomain(email);\n if (fields.bg_academic && fields.bg_institution) allEvidence.push('Academic institution: ' + fields.bg_institution);\n if (domain) {\n if (uIsGenericEmailDomain(domain)) allEvidence.push('Generic email provider: ' + domain); else allEvidence.push('Organization domain detected: ' + domain);\n }\n if (role && role.message) allEvidence.push(role.message);\n const deduped = uDedupeStrings(allEvidence).slice(0, 8);\n if (!fields.bg_final_evidence) fields.bg_final_evidence = deduped.length > 0 ? deduped : ['No public evidence found'];\n if (!fields.bg_final_detail) {\n const parts = [];\n if (fields.bg_academic && fields.bg_institution) parts.push('Academic institution: ' + fields.bg_institution + '.');\n else if (domain) parts.push(uIsGenericEmailDomain(domain) ? ('Generic provider: ' + domain + '.') : ('Organization domain: ' + domain + '.'));\n if (judge && judge.message) parts.push(judge.message);\n const fallback = parts.join(' ').trim();\n fields.bg_final_detail = fallback || 'No public evidence found.';\n }\n } catch (err) {\n try { console.error('>> [compound] error:', err && err.message ? err.message : String(err)); } catch (_) {}\n fields.bg_compound_debug = err && err.message ? err.message : String(err);\n }\n if (!status) status = 'person_low';\n fields.bg_assessments = assessments;\n return { email, status, message: messages.join('; '), fields, assessments };\n}\n\n\n",[],[238,374,153],"a960bdae-8530-11f0-becd-0224a6c84d84","whitelist.js","a960be58-8530-11f0-becd-0224a6c84d84","a93a0de4-8530-11f0-8e8a-0224a6c84d84",112,["D",1756510449504],"import { getEmailDomain } from '../utils.js';\n\nfunction isRegexToken(token) {\n try {\n const t = String(token || '');\n if (!t.startsWith('/')) return false;\n const last = t.lastIndexOf('/');\n return last > 0;\n } catch (_) { return false; }\n}\n\nfunction compileRegex(token) {\n try {\n const t = String(token || '');\n if (!isRegexToken(t)) return null;\n const last = t.lastIndexOf('/');\n const pattern = t.slice(1, last);\n const flags = t.slice(last + 1);\n return new RegExp(pattern, flags);\n } catch (_) { return null; }\n}\n\nfunction normalizeWhitelistTokens(list) {\n try {\n if (!Array.isArray(list)) return [];\n const out = [];\n const seen = new Set();\n for (const raw of list) {\n const rawStr = String(raw || '').trim();\n if (!rawStr) continue;\n const t = isRegexToken(rawStr) ? rawStr : rawStr.toLowerCase();\n if (!t) continue;\n if (seen.has(t)) continue;\n seen.add(t);\n out.push(t);\n }\n return out;\n } catch (_) { return []; }\n}\n\nfunction domainMatches(supplied, actualDomain) {\n try {\n const d = String(actualDomain || '').toLowerCase();\n const token = String(supplied || '').toLowerCase();\n if (!token || !d) return false;\n const t = token.replace(/^\\*@/, '').replace(/^@/, '');\n if (!t) return false;\n if (d === t) return true;\n return d.endsWith('.' + t);\n } catch (_) { return false; }\n}\n\nfunction matchWhitelist(email, tokens) {\n try {\n const eRaw = String(email || '');\n const e = eRaw.toLowerCase();\n const domain = getEmailDomain(e);\n const list = normalizeWhitelistTokens(tokens);\n for (const t of list) {\n if (!t) continue;\n if (isRegexToken(t)) {\n const re = compileRegex(t);\n if (re) {\n try {\n re.lastIndex = 0; const matched = re.test(eRaw);\n try { console.log('>> [whitelist regex]', { rule: t, email: eRaw, matched }); } catch (_) {}\n if (matched) return t;\n } catch (_) {}\n }\n continue;\n }\n if (t.includes('@') && !t.includes('*')) {\n if (t.startsWith('@')) { if (domainMatches(t, domain)) return t; }\n else if (e === t) return t;\n } else if (t.startsWith('*@')) {\n if (domainMatches(t, domain)) return t;\n } else if (t.startsWith('@')) {\n if (domainMatches(t, domain)) return t;\n } else if (t.includes('.')) {\n if (domainMatches(t, domain)) return t;\n }\n }\n return null;\n } catch (_) { return null; }\n}\n\nexport function preWhitelistAssess(email, whitelistRules) {\n try {\n const matched = matchWhitelist(email, whitelistRules);\n if (!matched) return null;\n const fields = { bg_whitelist_rule: matched, bg_whitelist_msg: 'Whitelisted' };\n return {\n decided: true,\n status: 'whitelist',\n message: 'Whitelisted via ' + matched,\n fields,\n assessment: { name: 'whitelist', status: 'pass', message: 'matched ' + matched }\n };\n } catch (_) { return null; }\n}\n\n\n",[],[238,374,391,383],"pre","a96c688e-8530-11f0-8e8a-0224a6c84d84","blacklist.js","a96c694c-8530-11f0-8e8a-0224a6c84d84",114,["D",1756510449582],"import { getEmailDomain } from '../utils.js';\n\nfunction isRegexToken(token) {\n try {\n const t = String(token || '');\n if (!t.startsWith('/')) return false;\n const last = t.lastIndexOf('/');\n return last > 0;\n } catch (_) { return false; }\n}\n\nfunction compileRegex(token) {\n try {\n const t = String(token || '');\n if (!isRegexToken(t)) return null;\n const last = t.lastIndexOf('/');\n const pattern = t.slice(1, last);\n const flags = t.slice(last + 1);\n return new RegExp(pattern, flags);\n } catch (_) { return null; }\n}\n\nfunction normalizeBlacklistTokens(list) {\n try {\n const input = Array.isArray(list) ? list : [];\n const out = [];\n const seen = new Set();\n for (const raw of input) {\n const rawStr = String(raw || '').trim();\n if (!rawStr) continue;\n const t = isRegexToken(rawStr) ? rawStr : rawStr.toLowerCase();\n if (seen.has(t)) continue;\n seen.add(t);\n out.push(t);\n }\n return out;\n } catch (_) { return []; }\n}\n\nfunction domainMatches(supplied, actualDomain) {\n try {\n const d = String(actualDomain || '').toLowerCase();\n const token = String(supplied || '').toLowerCase();\n if (!token || !d) return false;\n const t = token.replace(/^\\*@/, '').replace(/^@/, '');\n if (!t) return false;\n if (d === t) return true;\n // If token includes a dot, require suffix match like sub.domain.tld\n if (t.includes('.')) return d.endsWith('.' + t);\n // If token has no dot (e.g., \"noidem\"), match against any domain label\n const labels = d.split('.');\n return labels.includes(t);\n } catch (_) { return false; }\n}\n\nfunction matchBlacklist(email, tokens) {\n try {\n const eRaw = String(email || '');\n const e = eRaw.toLowerCase();\n const local = eRaw.split('@')[0] || '';\n const domain = getEmailDomain(e);\n const list = normalizeBlacklistTokens(tokens);\n try { console.log('>> [blacklist] normalized list', list); } catch (_) {}\n for (const t of list) {\n if (!t) continue;\n try { console.log('>> [blacklist] processing token', t, 'isRegex:', isRegexToken(t)); } catch (_) {}\n // Regex rule\n if (isRegexToken(t)) {\n const re = compileRegex(t);\n if (re) {\n try {\n let matched = false; let target = '';\n // reset lastIndex for safety in case of /g\n re.lastIndex = 0; if (!matched && re.test(eRaw)) { matched = true; target = 'raw'; }\n re.lastIndex = 0; if (!matched && re.test(e)) { matched = true; target = 'lower'; }\n if (!matched && local) {\n re.lastIndex = 0; if (re.test(local + '@')) { matched = true; target = 'local@'; }\n if (!matched) { re.lastIndex = 0; if (re.test((local.toLowerCase()) + '@')) { matched = true; target = 'local@-lower'; } }\n }\n try { console.log('>> [blacklist regex]', { rule: t, email: eRaw, matched, target }); } catch (_) {}\n if (matched) return t;\n } catch (_) {}\n }\n continue;\n }\n if (t.includes('@') && !t.includes('*')) {\n if (t.startsWith('@')) { if (domainMatches(t, domain)) return t; }\n else if (e === t) return t;\n } else if (t.startsWith('*@')) {\n if (domainMatches(t, domain)) return t;\n } else if (t.startsWith('@')) {\n if (domainMatches(t, domain)) return t;\n } else if (t.includes('.')) {\n if (domainMatches(t, domain)) return t;\n }\n }\n return null;\n } catch (_) { return null; }\n}\n\nexport function preBlacklistAssess(email, blacklistRules) {\n try {\n try { console.log('>> [blacklist] called with', { email, rules: blacklistRules }); } catch (_) {}\n const matched = matchBlacklist(email, blacklistRules);\n try { console.log('>> [blacklist] match result', matched); } catch (_) {}\n if (!matched) return null;\n const fields = { bg_blacklist_rule: matched, bg_blacklist_msg: 'Blacklisted', bg_blacklist: true };\n return {\n decided: true,\n status: 'spam',\n message: 'Blacklisted via ' + matched,\n fields,\n assessment: { name: 'blacklist', status: 'fail', message: 'matched ' + matched }\n };\n } catch (_) { return null; }\n}\n\n\n\n",[],[238,374,391,393],"a97333da-8530-11f0-bc4e-0224a6c84d84","academic.js","a97334ca-8530-11f0-bc4e-0224a6c84d84",115,["D",1756510449621],"export async function preAcademicAssess(email) {\n const fields = {};\n try {\n const { Verifier } = await import('npm:academic-email-verifier');\n let isAcademic = false; let institution = null;\n try { isAcademic = await Verifier.isAcademic(email); } catch (_) { isAcademic = false; }\n try { institution = await Verifier.getInstitutionName(email); } catch (_) { institution = null; }\n const inst = typeof institution === 'string' ? institution.trim() : (institution ? String(institution) : null);\n fields.bg_academic = !!isAcademic; if (inst) fields.bg_institution = inst;\n if (isAcademic) fields.bg_academic_msg = inst || 'Academic domain';\n } catch (_) {}\n if (fields.bg_academic) {\n const inst = fields.bg_institution || '';\n const msg = inst ? ('Academic institution: ' + inst) : 'Academic domain';\n return {\n decided: true,\n status: 'academic',\n message: msg,\n fields,\n assessment: { name: 'academic', status: 'pass', message: msg }\n };\n }\n return null;\n}\n\n\n",[],[238,374,391,401],"a93a0d4e-8530-11f0-8e8a-0224a6c84d84",107,["D",1756510449243],[269,270,271],[238,374,391],"a95340fc-8530-11f0-8b2d-0224a6c84d84","roleHeuristic.js","a95341c4-8530-11f0-8b2d-0224a6c84d84","a9251bf0-8530-11f0-8cd1-0224a6c84d84",109,["D",1756510449383],"export function roleHeuristicAssess(email) {\n try {\n const local = String(email || '').split('@')[0].toLowerCase();\n const roleList = ['info', 'support', 'admin', 'sales', 'contact', 'hello', 'team', 'marketing', 'noreply', 'no-reply'];\n if (roleList.includes(local)) return { status: 'suspected_spam', message: 'Role-based address' };\n } catch (_) {}\n return {};\n}\n\n\n",[],[238,374,422,414],"full","a94f46e6-8530-11f0-a077-0224a6c84d84","llmCompound.js","a94f47b8-8530-11f0-a077-0224a6c84d84",108,["D",1756510449383],"import { groqChatCompletion } from '../../../chatCompletion.js';\nimport { extractJsonBetweenTags, cleanDetailText, deriveIdentityShort, statusToLabel } from '../utils.js';\n\nexport async function llmCompoundAssess(apiKey, email, systemPrompt) {\n const baseSystem = [\n 'You assess whether an email belongs to a real person. Perform targeted web checks. If you cannot browse, reason only from public patterns in the address and provider; do not fabricate.',\n 'Make an effort to look for identity signals on LinkedIn, company/staff pages, academic directories, GitHub, personal sites, press/newsroom/author pages, and social profiles.',\n 'When identity is indicated, do light background digging: capture the person\\'s name, role/title, organization, department/team, and location/city if available.',\n 'Also look for negative signals: credible anti-abuse/anti-spam sources (e.g., StopForumSpam, Spamhaus, PhishTank), scam-reporting communities, or reputable media coverage indicating misuse. If credible negative signals exist, prefer status: spam.',\n 'Return ONLY JSON wrapped in ... tags using this schema:',\n '{ \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }',\n 'Guidelines:',\n '- person_high: strong identity signals clearly tie to the email/user (e.g., staff/author page, university/company directory, or a portfolio/personal site that credibly matches the individual).',\n '- person_low: requires at least one concrete, credible public signal about the person (e.g., portfolio/personal site with matching name/handle, staff/author/university/company page, or GitHub with substantive profile). Mere name-like matches or generic social profiles without a clear tie do NOT qualify.',\n '- person_none: choose this when there is no credible public identity evidence. Ambiguous name matches (e.g., multiple LinkedIn results for common names), generic provider emails with only a name-like local part, or signals that cannot be tied to the email/person should be person_none.',\n '- spam: obvious spam/role-based/throwaway patterns, or credible anti-spam sources flag the address.',\n '- Leniency: Only apply leniency toward person_low for non-generic organization or academic domains when there is at least one plausible institutional signal (e.g., being listed on an org/staff page). Do not apply leniency for generic providers or name-only signals.',\n '- Escalation: When you find a plausible identity match (person name plus role/title and/or organization/institution) from credible sources and there are no credible negative signals, prefer status: person_high, even if the address uses a generic email provider (e.g., gmail).',\n '- message: one short sentence preferring an identity-first summary, e.g., \"Linked to Name — Title, Organization\" when available. explanation_short: 2-3 sentences (<= 400 chars), plain text; no tool logs, URLs, or headings. If known, include person background (name, role/title, organization).',\n '- evidence: 1-5 short bullets summarizing concrete findings (no links). Include at least one background bullet when available (e.g., \"Name — Title, Organization, City\"). Include negative bullets when applicable (e.g., \"Flagged on StopForumSpam\" or \"Reported in scam community\"). If nothing credible is found, set evidence to [] and explicitly say \"No public evidence found.\" and prefer status person_none.',\n '- If the address indicates a role (e.g., info, noreply) or a notable role (e.g., reporter, journalist, professor, founder), include that in evidence.',\n '- Do not include any text outside the ... wrapper.'\n ].join('\\n');\n const messages = [\n { role: 'system', content: baseSystem + (systemPrompt ? ('\\nExtra instructions: ' + systemPrompt) : '') },\n { role: 'user', content: 'Email: ' + email + '\\nTask: quick legitimacy check.' }\n ];\n const model = 'compound-beta';\n const compoundPayload1 = { model, messages, stream: false, temperature: 0.2, tool_choice: 'none' };\n const r1 = await groqChatCompletion(apiKey, compoundPayload1);\n const t1 = r1?.choices?.[0]?.message?.content || '';\n const reasoning1 = r1?.choices?.[0]?.message?.reasoning || '';\n let parsed = extractJsonBetweenTags(t1);\n if (!parsed) {\n const baseSystemJson = [\n 'You assess whether an email likely belongs to a real person based on quick web checks; do not fabricate.',\n 'Return ONLY a JSON object with this schema (no tags, no markdown):',\n '{ \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }',\n 'Keep message concise; explanation_short 2-3 sentences (<= 400 chars).'\n ].join('\\n');\n const messagesJson = [\n { role: 'system', content: baseSystemJson + (systemPrompt ? ('\\nExtra instructions: ' + systemPrompt) : '') },\n { role: 'user', content: 'Email: ' + email + '\\nTask: quick legitimacy check.' }\n ];\n const payload2 = { model, messages: messagesJson, stream: false, temperature: 0.2, response_format: { type: 'json_object' }, tool_choice: 'none' };\n const r2 = await groqChatCompletion(apiKey, payload2);\n try { parsed = JSON.parse(r2?.choices?.[0]?.message?.content || ''); } catch (_) { parsed = null; }\n if (!parsed) {\n return {\n status: 'person_low',\n message: 'no compound signal',\n fields: { bg_compound_debug: (t1 || '').slice(0, 800), bg_llm_model: model }\n };\n }\n }\n const out = { fields: { bg_llm_model: model } };\n if (parsed) {\n if (parsed.status && (parsed.status === 'person_high' || parsed.status === 'person_low' || parsed.status === 'person_none' || parsed.status === 'spam')) out.status = parsed.status;\n if (typeof parsed.message === 'string' && parsed.message.trim()) {\n out.message = parsed.message.trim();\n } else if (out.status) {\n const label = statusToLabel(out.status);\n out.message = 'compound: ' + label;\n } else {\n out.message = 'compound: ' + statusToLabel('person_low');\n }\n const label = statusToLabel(out.status || (parsed.status || 'person_low'));\n out.fields.bg_compound_label = label;\n out.fields.bg_compound_short = out.message || label;\n let detail = '';\n if (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) {\n detail = cleanDetailText(parsed.explanation_short);\n try {\n const parts = detail.split(/(?<=[.!?])\\s+/).filter(Boolean).slice(0, 3);\n detail = parts.join(' ');\n if (detail.length > 450) detail = detail.slice(0, 449).replace(/[,;:\\s]+$/, '').trim() + '…';\n } catch (_) {}\n }\n if (!detail && reasoning1 && typeof reasoning1 === 'string') {\n detail = cleanDetailText(reasoning1);\n }\n if (!detail && t1) {\n detail = cleanDetailText(String(t1));\n }\n if (detail) out.fields.bg_compound_detail = detail;\n try {\n const shortPref = (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) ? deriveIdentityShort(parsed.explanation_short) : '';\n if (shortPref) out.fields.bg_compound_short = shortPref;\n } catch (_) {}\n try {\n let ev = parsed.evidence;\n if (Array.isArray(ev)) {\n ev = ev.map((s) => String(s || '').trim()).filter(Boolean).slice(0, 5);\n } else if (typeof ev === 'string' && ev.trim()) {\n ev = [ev.trim()];\n } else {\n ev = [];\n }\n if (ev.length > 0) out.fields.bg_compound_evidence = ev;\n } catch (_) {}\n }\n return out;\n}\n\n\n",[],[238,374,422,424],"a95baeae-8530-11f0-8cd1-0224a6c84d84","finalJudge.js","a95baf62-8530-11f0-8cd1-0224a6c84d84",111,["D",1756510449389],"import { groqChatCompletion } from '../../../chatCompletion.js';\nimport { statusToLabel, deriveIdentityShort } from '../utils.js';\n\nexport async function finalJudgeAssess(apiKey, email, systemPrompt, evidence) {\n console.log('>> [final judge] evidence:', email, JSON.stringify(evidence));\n const model = 'openai/gpt-oss-120b';\n const schema = '{ \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }';\n const sys = [\n 'You are a strict judge that consolidates signals from two assessors and heuristics (academic, role, domain) to decide if an email belongs to a real person.',\n 'Decide using severity: spam > person_none > person_low > person_high.',\n 'Return ONLY JSON per schema:', schema,\n 'Rules:',\n '- Compose evidence as a deduplicated list of concrete bullets merged from all inputs (no links).',\n '- Include at least one bullet with person background when available (name, role/title, organization, location).',\n '- If credible anti-spam signals exist (e.g., StopForumSpam, Spamhaus, scam-reporting communities), prefer status: spam and include a negative bullet.',\n '- Leniency: Only apply leniency toward person_low for non-generic organization or academic domains when at least one institutional or portfolio-like signal exists (e.g., org/staff page, university directory, personal site with substantive details). Do not apply leniency for generic providers or name-only matches.',\n '- Escalation: If there is a plausible identity match (person name plus role/title and/or organization/institution) from credible sources and no credible negative signals, prefer person_high even if the address uses a generic provider (e.g., gmail).',\n '- If no credible public evidence is present, set evidence to [] and explicitly say \"No public evidence found.\" in explanation_short and prefer status: person_none.',\n '- message must be one short, specific sentence preferring an identity-first summary like \"Linked to Name — Title, Organization\" when available. explanation_short must be 2-3 sentences (<= 400 chars) and reference key evidence or lack thereof. If known, weave in person background (name, role/title, organization).',\n '- Note recognizable roles when present (reporter, journalist, professor, founder, recruiter).'\n ].join('\\n');\n const user = [ 'Email: ' + email, 'Evidence (JSON):', JSON.stringify(evidence) ].join('\\n');\n const judgePayload = { model, messages: [ { role: 'system', content: sys + (systemPrompt ? ('\\nExtra: ' + systemPrompt) : '') }, { role: 'user', content: user } ], stream: false, temperature: 0.2, response_format: { type: 'json_object' } };\n const r = await groqChatCompletion(apiKey, judgePayload);\n let parsed = null;\n try { parsed = JSON.parse(r?.choices?.[0]?.message?.content || '{}'); } catch (_) { parsed = null; }\n if (!parsed) return {};\n const out = { fields: { bg_final_model: model } };\n if (parsed.status && (parsed.status === 'person_high' || parsed.status === 'person_low' || parsed.status === 'person_none' || parsed.status === 'spam')) out.status = parsed.status;\n if (typeof parsed.message === 'string' && parsed.message.trim()) out.message = parsed.message.trim();\n const label = statusToLabel(out.status || (parsed.status || 'person_low'));\n out.fields.bg_final_label = label;\n out.fields.bg_final_short = out.message || label;\n if (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) {\n let d = String(parsed.explanation_short).trim();\n if (d.length > 450) d = d.slice(0, 449).replace(/[,;:\\s]+$/, '').trim() + '…';\n out.fields.bg_final_detail = d;\n try {\n const shortPref = deriveIdentityShort(parsed.explanation_short);\n if (shortPref) out.fields.bg_final_short = shortPref;\n } catch (_) {}\n }\n try {\n let ev = parsed.evidence;\n if (Array.isArray(ev)) {\n ev = ev.map((s) => String(s || '').trim()).filter(Boolean).slice(0, 5);\n } else if (typeof ev === 'string' && ev.trim()) {\n ev = [ev.trim()];\n } else {\n ev = [];\n }\n if (ev.length > 0) out.fields.bg_final_evidence = ev;\n } catch (_) {}\n return out;\n}\n\n\n",[],[238,374,422,432],"a9681d4c-8530-11f0-b161-0224a6c84d84","browserSearch.js","a9681df6-8530-11f0-b161-0224a6c84d84",113,["D",1756510449389],"import { groqChatCompletion } from '../../../chatCompletion.js';\nimport { statusToLabel, deriveIdentityShort, coerceJsonFromText, logGroqCurl } from '../utils.js';\n\nasync function convertAnalysisToJson(apiKey, email, analysisText) {\n try {\n const convModel = 'openai/gpt-oss-20b';\n const convSys = [\n 'You convert analysis text into a strict JSON object. Do not browse or call tools.',\n 'Schema: { \"status\": \"person_high|person_low|person_none|spam\", \"message\": string, \"explanation_short\": string, \"evidence\": string[] }',\n 'Rules:',\n '- message: one short sentence.',\n '- explanation_short: 2-3 sentences (<= 400 chars). If analysis indicates nothing credible was found, include \"No public evidence found.\" If known, include person background (name, role/title, organization). If credible negative signals are present (e.g., StopForumSpam, Spamhaus, scam-reporting communities), mention that.',\n '- evidence: 0-5 short bullets (no links). Include a background bullet when available (e.g., \"Name — Title, Organization, City\"). Include negative bullets when applicable (e.g., \"Flagged on StopForumSpam\"). Use [] when no credible evidence.',\n '- Only output a JSON object (no markdown, no extra text).'\n ].join('\\n');\n const convMessages = [\n { role: 'system', content: convSys },\n { role: 'user', content: 'Email: ' + email + '\\nAnalysis to convert:\\n' + analysisText }\n ];\n const convPayload = { model: convModel, messages: convMessages, stream: false, temperature: 0, response_format: { type: 'json_object' }, tool_choice: 'none' };\n const convRes = await groqChatCompletion(apiKey, convPayload);\n const t2 = convRes?.choices?.[0]?.message?.content || '';\n try { return JSON.parse(t2); } catch (_) { return null; }\n } catch (_) {\n return null;\n }\n}\n\nexport async function browserSearchAssess(apiKey, email, systemPrompt) {\n const baseSystem = [\n 'Use web browsing to gather public signals about whether this email belongs to a real person; do not fabricate.',\n 'Call browser_search with multiple targeted queries. Try: the full email in quotes; the local part and domain; site:linkedin.com with likely name/handle; site:github.com with the handle; university/staff directories; newsroom/author pages; personal sites; press pages.',\n 'Prefer authoritative sources: LinkedIn, staff/author/company pages, academic directories, GitHub, reputable media. Also check credible anti-abuse/anti-spam sources (StopForumSpam, Spamhaus, PhishTank) and scam-reporting communities. Avoid data brokers and spammy aggregators.',\n 'When identity is indicated, do light background digging: capture the person\\'s name, role/title, organization, department/team, and location/city if available.',\n 'Leniency rule: Only apply leniency toward person_low for non-generic organization or academic domains when there is at least one plausible institutional signal (e.g., listed on org/staff page or directory). Do not apply leniency for generic providers or name-only matches.',\n 'Escalation rule: If you find a plausible identity match (person name plus role/title and/or organization/institution) from credible sources and no credible negative signals, prefer Status: person_high, even when the address uses a generic provider (e.g., gmail).',\n 'Produce a concise plain-text analysis with the following sections only (do not include any JSON):',\n 'Status: one of person_high | person_low | person_none | spam',\n 'Message: one short sentence preferring an identity-first summary, e.g., \"Linked to Name — Title, Organization\" when available',\n 'Explanation: 2-3 sentences (<= 400 chars), reference evidence or say No public evidence found. If known, include person background (name, role/title, organization).',\n 'Evidence: 1-5 short bullet points summarizing concrete findings (no links). Include at least one bullet with person background when available (e.g., \"Name — Title, Organization, City\"). Include negative bullets such as \"Flagged on StopForumSpam\" or \"Mentioned in scam-reporting community\" when applicable. If nothing credible found, leave this section empty and prefer Status: person_none.',\n 'Also note recognizable roles when present (reporter, journalist, professor, founder, recruiter).'\n ].join('\\n');\n const messages = [\n { role: 'system', content: baseSystem + (systemPrompt ? ('\\nExtra instructions: ' + systemPrompt) : '') },\n { role: 'user', content: 'Email: ' + email + '\\nTask: web search legitimacy check.' }\n ];\n const model = 'openai/gpt-oss-20b';\n const payload = { model, messages, stream: false, temperature: 0.2, tools: [{ type: 'browser_search' }] };\n const r1 = await groqChatCompletion(apiKey, payload);\n logGroqCurl('browser r1', apiKey, payload);\n const t1 = r1?.choices?.[0]?.message?.content || '';\n const out = { fields: { bg_browser_model: model } };\n let parsed = await convertAnalysisToJson(apiKey, email, t1);\n if (!parsed) parsed = coerceJsonFromText(t1);\n if (parsed) {\n if (parsed.status && (parsed.status === 'person_high' || parsed.status === 'person_low' || parsed.status === 'person_none' || parsed.status === 'spam')) out.status = parsed.status;\n if (typeof parsed.message === 'string' && parsed.message.trim()) out.message = parsed.message.trim();\n const label = statusToLabel(out.status || (parsed.status || 'person_low'));\n out.fields.bg_browser_label = label;\n out.fields.bg_browser_short = out.message || label;\n if (typeof parsed.explanation_short === 'string' && parsed.explanation_short.trim()) {\n let detail = String(parsed.explanation_short).trim();\n if (detail.length > 450) detail = detail.slice(0, 449).replace(/[,;:\\s]+$/, '').trim() + '…';\n out.fields.bg_browser_detail = detail;\n try {\n const shortPref = deriveIdentityShort(parsed.explanation_short);\n if (shortPref) out.fields.bg_browser_short = shortPref;\n } catch (_) {}\n }\n try {\n let ev = parsed.evidence;\n if (Array.isArray(ev)) {\n ev = ev.map((s) => String(s || '').trim()).filter(Boolean).slice(0, 5);\n } else if (typeof ev === 'string' && ev.trim()) {\n ev = [ev.trim()];\n } else {\n ev = [];\n }\n if (ev.length > 0) out.fields.bg_browser_evidence = ev;\n } catch (_) {}\n } else {\n out.fields.bg_browser_debug = 'browser_search produced non-JSON analysis and conversion failed.';\n }\n return out;\n}\n\n\n",[],[238,374,422,440],"a9251b5a-8530-11f0-8cd1-0224a6c84d84",106,["D",1756510449110],[264,265,266,267],[238,374,422],"a91145a8-8530-11f0-b5d8-0224a6c84d84",105,["D",1756510448984],[263,268,272,273],[238,374],["D",1756510448859],[262],[238],"cc4035b0-81f8-11f0-af77-0224a6c84d84","state.json","cc40365a-81f8-11f0-af77-0224a6c84d84",48,["D",1756156602547],"{\n \"val\": {\n \"id\": \"4849d342-81f8-11f0-9ed4-0224a6c84d84\"\n },\n \"branch\": {\n \"id\": \"484a2f22-81f8-11f0-9ed4-0224a6c84d84\",\n \"version\": 88\n },\n \"lastRun\": {\n \"pid\": 87094,\n \"time\": \"2025-08-25T21:13:10.136Z\"\n }\n}",[],[244,461],["D",1756156596911],[260],[244],["D",1756156596230],{"_98":97,"_105":101},{"_98":97,"_99":-5,"_100":101,"_18":56,"_102":103,"_104":25},{"_13":87,"_32":88,"_44":43,"_89":45,"_90":-5,"_91":-5,"_92":-5,"_93":-5,"_94":-5,"_95":46,"_96":97},"ctx",{"_80":-5,"_124":508,"_509":510,"_511":512,"_513":25,"_514":25,"_515":25,"_516":60,"_517":-5,"_518":-7,"_519":-7,"_520":64,"_521":25,"_522":25,"_523":-5,"_524":25,"_525":25,"_526":25,"_527":-5},"ENV",{"_479":480,"_481":482,"_483":88,"_484":485,"_486":487,"_488":489,"_490":491,"_492":493,"_494":495,"_496":497,"_498":499,"_500":501,"_502":503,"_504":505,"_506":507},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v129