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NEW hard 200KB size cap with graceful trim (Clay cell limit).\n// 2. NEW text-level speaker fallback — catches \"Name said,\" \"said Name,\"\n// and plain \"Name: quote\" patterns even when HTML formatting is weird.\n// 3. NEW exhibit body fetched in parallel (was serial) — ~3x faster.\n// 4. Stricter item title extraction — drops garbage when the item header\n// format is unusual.\n// ============================================================================\n\nconst HEADERS = {\n \"User-Agent\": \"AlexKrasiuk alex@myrunbook.com\",\n \"Accept-Encoding\": \"gzip, deflate\",\n};\n\nconst CONTEXT_CHARS = 500;\nconst ITEM_PREVIEW_CHARS = 600;\nconst EXHIBIT_PREVIEW_CHARS = 800;\nconst MAX_FILINGS = 20;\nconst LOOKBACK_DAYS = 365;\nconst MAX_HITS_RETURNED = 75;\nconst MAX_ITEMS_RETURNED = 15;\nconst MIN_ITEM_SCORE = 2;\nconst MIN_ITEM_CONTENT_CHARS = 150;\nconst MAX_BYTES = 180_000;\n\nconst HIGH_SIGNAL_ITEMS: Record = {\n \"1.01\": { title: \"Entry into Material Definitive Agreement\", boost: 5 },\n \"1.02\": { title: \"Termination of Material Definitive Agreement\", boost: 4 },\n \"2.01\": {\n title: \"Completion of Acquisition or Disposition of Assets\",\n boost: 6,\n },\n \"2.02\": { title: \"Results of Operations and Financial Condition\", boost: 3 },\n \"2.05\": {\n title: \"Costs Associated with Exit or Disposal Activities\",\n boost: 10,\n },\n \"2.06\": { title: \"Material Impairments\", boost: 8 },\n \"3.02\": { title: \"Unregistered Sales of Equity Securities\", boost: 2 },\n \"5.02\": { title: \"Departure/Appointment of Officers or Directors\", boost: 7 },\n \"5.03\": { title: \"Amendments to Articles/Bylaws\", boost: 2 },\n \"7.01\": { title: \"Regulation FD Disclosure\", boost: 2 },\n \"8.01\": { title: \"Other Events\", boost: 2 },\n};\n\nconst TRIVIAL_ITEMS = new Set([\"9.01\"]);\n\nconst KEYWORDS = [\n \"artificial intelligence\",\n \"AI agent\",\n \"AI agents\",\n \"generative AI\",\n \"gen AI\",\n \"GenAI\",\n \"machine learning\",\n \"large language model\",\n \"LLM\",\n \"AI-enabled\",\n \"AI-powered\",\n \"AI initiative\",\n \"AI technology\",\n \"AI tool\",\n \"headcount reduction\",\n \"headcount reductions\",\n \"workforce reduction\",\n \"reduction in force\",\n \"reduction-in-force\",\n \"workforce optimization\",\n \"restructuring\",\n \"severance\",\n \"severance charges\",\n \"layoff\",\n \"layoffs\",\n \"job cut\",\n \"overhead reduction\",\n \"workforce transformation\",\n \"reorganization\",\n \"back office\",\n \"back-office\",\n \"shared services\",\n \"administrative function\",\n \"administrative functions\",\n \"centralize\",\n \"centralization\",\n \"outsourc\",\n \"process automation\",\n \"robotic process automation\",\n \"RPA\",\n \"automate\",\n \"automated\",\n \"automation\",\n \"intelligent automation\",\n \"workflow automation\",\n \"digital transformation\",\n \"technology transformation\",\n \"digital initiative\",\n \"modernize\",\n \"modernization\",\n \"process optimization\",\n \"operational efficiency\",\n \"cost savings\",\n \"cost reduction\",\n \"margin expansion\",\n \"margin improvement\",\n \"efficiency initiative\",\n \"efficiency program\",\n \"manual processes\",\n \"streamline\",\n \"streamlined\",\n \"dispatch\",\n \"scheduling\",\n \"route optimization\",\n \"field service\",\n \"work order\",\n \"call center\",\n \"contact center\",\n \"margin pressure\",\n \"labor cost\",\n \"labor shortage\",\n];\n\nconst FALSE_POSITIVE_CONTEXTS: Array<{ keyword: string; nearby: RegExp }> = [\n {\n keyword: \"offshore\",\n nearby:\n /\\b(regulation\\s+s|rule\\s+144a|qualified\\s+institutional\\s+buyers)\\b/i,\n },\n];\n\n// ============================================================================\n// Ticker cache + fetch\n// ============================================================================\n\nlet tickerCache: { data: any; ts: number } | null = null;\nconst CACHE_TTL_MS = 24 * 60 * 60 * 1000;\n\nasync function secFetch(url: string, retries = 3): Promise {\n for (let i = 0; i < retries; i++) {\n const resp = await fetch(url, { headers: HEADERS });\n if (resp.ok) return resp.text();\n if (resp.status === 429) {\n await new Promise((r) => setTimeout(r, 1000 * (i + 1)));\n continue;\n }\n throw new Error(`SEC fetch failed: ${resp.status} for ${url}`);\n }\n throw new Error(`SEC fetch failed after ${retries} retries for ${url}`);\n}\n\nasync function getTickers(): Promise {\n if (tickerCache && Date.now() - tickerCache.ts < CACHE_TTL_MS) {\n return tickerCache.data;\n }\n const data = JSON.parse(\n await secFetch(\"https://www.sec.gov/files/company_tickers.json\"),\n );\n tickerCache = { data, ts: Date.now() };\n return data;\n}\n\nfunction stripHtml(html: string): string {\n let text = html.replace(/]*>.*?<\\/script>/gis, \" \");\n text = text.replace(/]*>.*?<\\/style>/gis, \" \");\n text = text.replace(/<\\/?ix:[^>]+>/gi, \" \");\n text = text.replace(/<[^>]+>/g, \" \");\n text = text\n .replace(/&/g, \"&\").replace(/</g, \"<\").replace(/>/g, \">\")\n .replace(/"/g, '\"').replace(/'/g, \"'\").replace(/ /g, \" \")\n .replace(/&#\\d+;/g, \" \").replace(/&[a-zA-Z]+;/g, \" \");\n text = text.replace(/\\s+/g, \" \").trim();\n return text;\n}\n\nfunction normalize(s: string): string {\n return s.toLowerCase().replace(/[^a-z0-9\\s]/g, \"\").replace(/\\s+/g, \" \")\n .trim();\n}\n\n// ============================================================================\n// Exhibit discovery\n// ============================================================================\n\ntype ExhibitRef = { name: string; key: string; cleanType: string; url: string };\n\nfunction getFilingDir(primaryUrl: string): string {\n return primaryUrl.substring(0, primaryUrl.lastIndexOf(\"/\") + 1);\n}\n\nfunction normalizeExhibitKey(type: string, name: string): string | null {\n const typeMatch = type.match(/99[.\\-_]?(\\d+)?/i);\n if (typeMatch) return typeMatch[1] ? `99.${typeMatch[1]}` : \"99\";\n const nameMatch = name.match(/ex(?:hibit)?[-_]?99[.\\-_]?(\\d+)?/i);\n if (nameMatch) return nameMatch[1] ? `99.${nameMatch[1]}` : \"99\";\n return null;\n}\n\nasync function getExhibits(primaryUrl: string): Promise {\n const dir = getFilingDir(primaryUrl);\n try {\n const json = JSON.parse(await secFetch(`${dir}index.json`));\n const items = json?.directory?.item || [];\n const exhibits: ExhibitRef[] = [];\n for (const it of items) {\n const type = String(it.type || \"\");\n const name = String(it.name || \"\");\n if (!/\\.html?$/i.test(name)) continue;\n if (!/^EX-99/i.test(type) && !/ex.*99/i.test(name)) continue;\n const key = normalizeExhibitKey(type, name);\n if (!key) continue;\n exhibits.push({\n name,\n key,\n cleanType: `EX-${key}`,\n url: `${dir}${name}`,\n });\n }\n return exhibits;\n } catch {\n return [];\n }\n}\n\n// ============================================================================\n// 8-K Item parsing (unchanged, works well)\n// ============================================================================\n\ntype ItemBlock = {\n item_code: string;\n item_title: string;\n content: string;\n start: number;\n};\n\nfunction parseItems(text: string): ItemBlock[] {\n const markers: { code: string; idx: number }[] = [];\n const markerRe = /Item\\s+(\\d{1,2}\\.\\d{2})\\b/g;\n let m;\n while ((m = markerRe.exec(text)) !== null) {\n markers.push({ code: m[1], idx: m.index });\n }\n\n const deduped: { code: string; idx: number }[] = [];\n for (const mk of markers) {\n const prev = deduped[deduped.length - 1];\n if (prev && prev.code === mk.code && mk.idx - prev.idx < 200) continue;\n deduped.push(mk);\n }\n\n const items: ItemBlock[] = [];\n for (let i = 0; i < deduped.length; i++) {\n const start = deduped[i].idx;\n const end = i + 1 < deduped.length ? deduped[i + 1].idx : text.length;\n const block = text.slice(start, end).trim();\n\n const titleMatch = block.match(\n /^Item\\s+\\d+\\.\\d+\\.?\\s+([A-Z][^\\n]{5,200}?)(?=\\s{2,}|\\.\\s+[A-Z]|\\bOn\\s|\\bThe\\s|\\bPursuant)/,\n );\n let title = titleMatch\n ? titleMatch[1].trim().replace(/\\s+/g, \" \")\n : HIGH_SIGNAL_ITEMS[deduped[i].code]?.title || \"Unknown\";\n // Reject nonsense titles (e.g., random punctuation or just numbers)\n if (title.length < 4 || !/[A-Za-z]{3}/.test(title)) {\n title = HIGH_SIGNAL_ITEMS[deduped[i].code]?.title || \"Unknown\";\n }\n\n items.push({\n item_code: deduped[i].code,\n item_title: title,\n content: block,\n start,\n });\n }\n return items;\n}\n\nfunction findContainingItem(\n items: ItemBlock[],\n matchIdx: number,\n): ItemBlock | null {\n for (let i = 0; i < items.length; i++) {\n const start = items[i].start;\n const end = i + 1 < items.length\n ? items[i + 1].start\n : Number.MAX_SAFE_INTEGER;\n if (matchIdx >= start && matchIdx < end) return items[i];\n }\n return null;\n}\n\nfunction mapExhibitsToItems(items: ItemBlock[]): Record {\n const map: Record = {};\n for (const item of items) {\n const refs = [...item.content.matchAll(/Exhibit\\s+99(?:\\.(\\d+))?/gi)];\n for (const r of refs) {\n const key = r[1] ? `99.${r[1]}` : \"99\";\n if (!map[key]) map[key] = item.item_code;\n }\n }\n return map;\n}\n\n// ============================================================================\n// Speaker extraction — IMPROVED\n// Tries multiple patterns in order of specificity.\n// ============================================================================\n\nfunction extractNearbySpeaker(\n context: string,\n): { speaker: string | null; title: string | null } {\n // Pattern A: \"said Name, Title\" — most common in press releases\n const pA = context.match(\n /said\\s+([A-Z][a-z]+(?:\\s+[A-Z]\\.?)?(?:\\s+[A-Z][a-z]+){1,3})\\s*,\\s*([A-Z][^.]{3,100}?)(?=\\.|,\\s+[A-Z][a-z]+\\s+of\\s|$)/,\n );\n if (pA) {\n return { speaker: pA[1].trim(), title: pA[2].trim().replace(/\\s+/g, \" \") };\n }\n\n // Pattern B: \"Name, Title, said\" — less common\n const pB = context.match(\n /\\b([A-Z][a-z]+(?:\\s+[A-Z]\\.?)?(?:\\s+[A-Z][a-z]+){1,3})\\s*,\\s*([A-Z][^,.]{3,100}?)\\s*,\\s*said\\b/,\n );\n if (pB) return { speaker: pB[1].trim(), title: pB[2].trim() };\n\n // Pattern C: \"said Name\" (no comma title) — caught but no title\n const pC = context.match(\n /said\\s+([A-Z][a-z]+(?:\\s+[A-Z]\\.?)?(?:\\s+[A-Z][a-z]+){1,3})(?=[.,\\s])/,\n );\n if (pC) return { speaker: pC[1].trim(), title: null };\n\n // Pattern D: \"Name said\" (no title)\n const pD = context.match(\n /\\b([A-Z][a-z]+(?:\\s+[A-Z]\\.?)?(?:\\s+[A-Z][a-z]+){1,3})\\s+said\\b/,\n );\n if (pD) return { speaker: pD[1].trim(), title: null };\n\n return { speaker: null, title: null };\n}\n\n// ============================================================================\n// Scoring\n// ============================================================================\n\nfunction scoreHit(\n context: string,\n itemCode: string | null,\n source: string,\n speakerTitle: string | null,\n): number {\n const lower = context.toLowerCase();\n let score = 0;\n\n if (itemCode && HIGH_SIGNAL_ITEMS[itemCode]) {\n score += HIGH_SIGNAL_ITEMS[itemCode].boost;\n }\n\n if (source.startsWith(\"ex-99.1\")) score += 3;\n else if (source.startsWith(\"ex-99\")) score += 2;\n\n if (speakerTitle) {\n const t = speakerTitle.toLowerCase();\n if (/(chief executive|ceo|president)/.test(t)) score += 6;\n else if (/(chief financial|cfo)/.test(t)) score += 5;\n else if (\n /(chief (information|technology|operating|transformation)|cio|cto|coo)/\n .test(t)\n ) score += 4;\n else if (/(chief|head of|svp|senior vice president)/.test(t)) score += 3;\n else if (/(vp|vice president|director)/.test(t)) score += 2;\n }\n\n const neighbors = [\n \"initiative\",\n \"invest\",\n \"deploy\",\n \"implement\",\n \"launch\",\n \"reduce\",\n \"reduction\",\n \"eliminate\",\n \"transform\",\n \"strategy\",\n \"pilot\",\n \"acquired\",\n \"acquisition\",\n \"partnership\",\n \"committed\",\n \"priority\",\n \"accelerate\",\n \"expand\",\n ];\n for (const w of neighbors) if (lower.includes(w)) score += 1;\n\n const hasDollar = /\\$\\s*\\d+(?:\\.\\d+)?\\s*(?:million|billion|M|B)\\b/i.test(\n context,\n );\n const hasHeadcount =\n /\\b(headcount|severance|workforce reduction|layoff|reduction in force)/i\n .test(lower);\n const hasBackOffice =\n /\\b(back[\\s-]?office|administrative function|shared service)/i.test(lower);\n\n if (hasHeadcount && hasDollar) score += 8;\n if (hasBackOffice) score += 3;\n\n return score;\n}\n\nfunction scoreItem(item: ItemBlock): number {\n let score = HIGH_SIGNAL_ITEMS[item.item_code]?.boost || 0;\n if (/\\$\\s*\\d+(?:\\.\\d+)?\\s*(?:million|billion|M|B)\\b/i.test(item.content)) {\n score += 3;\n }\n if (\n /\\b(severance|layoff|reduction in force|exit charges?)\\b/i.test(\n item.content,\n )\n ) score += 4;\n return score;\n}\n\nfunction isFalsePositive(keyword: string, context: string): boolean {\n for (const fp of FALSE_POSITIVE_CONTEXTS) {\n if (fp.keyword === keyword && fp.nearby.test(context)) return true;\n }\n return false;\n}\n\n// ============================================================================\n// Size cap\n// ============================================================================\n\nfunction fitResponse(resp: any): any {\n let json = JSON.stringify(resp);\n // Drop lowest-scored keyword hits first\n while (json.length > MAX_BYTES && resp.keyword_hits.length > 15) {\n resp.keyword_hits.pop();\n json = JSON.stringify(resp);\n }\n resp.total_keyword_hits_returned = resp.keyword_hits.length;\n // Drop lowest-scored items next\n while (json.length > MAX_BYTES && resp.items_disclosed.length > 5) {\n resp.items_disclosed.pop();\n json = JSON.stringify(resp);\n }\n resp.total_items_returned = resp.items_disclosed.length;\n // Shrink exhibit previews\n if (json.length > MAX_BYTES) {\n for (const e of resp.exhibits) {\n if (e.text_preview && e.text_preview.length > 400) {\n e.text_preview = e.text_preview.slice(0, 400) + \"…\";\n }\n }\n json = JSON.stringify(resp);\n }\n // Shrink keyword hit contexts\n if (json.length > MAX_BYTES) {\n for (const h of resp.keyword_hits) {\n if (h.context && h.context.length > 350) {\n h.context = h.context.slice(0, 350) + \"…\";\n }\n }\n }\n return resp;\n}\n\n// ============================================================================\n// Main handler\n// ============================================================================\n\nexport default async function handler(req: Request): Promise {\n const url = new URL(req.url);\n let ticker = (url.searchParams.get(\"ticker\") || \"\").toUpperCase().trim();\n\n if (!ticker && req.method === \"POST\") {\n try {\n const body = await req.json();\n ticker = (body.ticker || \"\").toUpperCase().trim();\n } catch { /* ignore */ }\n }\n\n if (!ticker) {\n return Response.json(\n { error: 'Pass ?ticker=AAPL or POST {\"ticker\": \"AAPL\"}' },\n { status: 400 },\n );\n }\n\n try {\n const tickersJson = await getTickers();\n let cik: string | null = null;\n let company: string | null = null;\n for (const entry of Object.values(tickersJson) as any[]) {\n if (entry.ticker.toUpperCase() === ticker) {\n cik = String(entry.cik_str).padStart(10, \"0\");\n company = entry.title;\n break;\n }\n }\n if (!cik) {\n return Response.json(\n { error: `Ticker ${ticker} not found in SEC EDGAR` },\n { status: 404 },\n );\n }\n\n const subs = JSON.parse(\n await secFetch(`https://data.sec.gov/submissions/CIK${cik}.json`),\n );\n const recent = subs.filings.recent;\n\n type FilingInfo = { url: string; date: string; acc: string };\n const filings: FilingInfo[] = [];\n const cutoffDate = new Date(Date.now() - LOOKBACK_DAYS * 86400 * 1000)\n .toISOString().slice(0, 10);\n\n for (\n let i = 0; i < recent.form.length && filings.length < MAX_FILINGS; i++\n ) {\n if (recent.form[i] !== \"8-K\") continue;\n if (recent.filingDate[i] < cutoffDate) break;\n const acc = recent.accessionNumber[i].replace(/-/g, \"\");\n const doc = recent.primaryDocument[i];\n filings.push({\n url: `https://www.sec.gov/Archives/edgar/data/${\n parseInt(cik)\n }/${acc}/${doc}`,\n date: recent.filingDate[i],\n acc: recent.accessionNumber[i],\n });\n }\n\n if (filings.length === 0) {\n return Response.json(\n { error: `No 8-K found for ${ticker} in last ${LOOKBACK_DAYS} days` },\n { status: 404 },\n );\n }\n\n type ItemHit = {\n item_code: string;\n item_title: string;\n content_preview: string;\n score: number;\n filing_date: string;\n filing_url: string;\n };\n type ExhibitSummary = {\n exhibit_key: string;\n exhibit_type: string;\n filename: string;\n mapped_to_item: string | null;\n text_preview: string;\n chars: number;\n filing_date: string;\n exhibit_url: string;\n };\n type KeywordHit = {\n keyword: string;\n context: string;\n source: string;\n item_code: string | null;\n item_title: string | null;\n speaker: string | null;\n speaker_title: string | null;\n score: number;\n filing_date: string;\n filing_url: string;\n };\n\n const allItems: ItemHit[] = [];\n const allExhibits: ExhibitSummary[] = [];\n const allKwHits: KeywordHit[] = [];\n\n for (const filing of filings) {\n const bodyHtml = await secFetch(filing.url);\n const bodyText = stripHtml(bodyHtml);\n const items = parseItems(bodyText);\n\n for (const it of items) {\n if (TRIVIAL_ITEMS.has(it.item_code) && scoreItem(it) === 0) continue;\n if (it.content.length < MIN_ITEM_CONTENT_CHARS) continue;\n const score = scoreItem(it);\n if (score < MIN_ITEM_SCORE) continue;\n allItems.push({\n item_code: it.item_code,\n item_title: it.item_title,\n content_preview: it.content.slice(0, ITEM_PREVIEW_CHARS),\n score,\n filing_date: filing.date,\n filing_url: filing.url,\n });\n }\n\n const exhibits = await getExhibits(filing.url);\n const exhibitToItem = mapExhibitsToItems(items);\n\n // NEW: parallel exhibit fetching\n type ExText = { ex: ExhibitRef; text: string };\n const exhibitFetches = exhibits.map(\n async (ex): Promise => {\n try {\n const text = stripHtml(await secFetch(ex.url));\n return { ex, text };\n } catch (e) {\n console.error(`Failed to fetch exhibit ${ex.url}:`, e);\n return null;\n }\n },\n );\n const exhibitTexts = (await Promise.all(exhibitFetches))\n .filter((x): x is ExText => x !== null);\n\n for (const et of exhibitTexts) {\n allExhibits.push({\n exhibit_key: et.ex.key,\n exhibit_type: et.ex.cleanType,\n filename: et.ex.name,\n mapped_to_item: exhibitToItem[et.ex.key] ?? null,\n text_preview: et.text.slice(0, EXHIBIT_PREVIEW_CHARS),\n chars: et.text.length,\n filing_date: filing.date,\n exhibit_url: et.ex.url,\n });\n }\n\n type Scan = { text: string; source: string; mappedItem: string | null };\n const scans: Scan[] = [\n { text: bodyText, source: \"body\", mappedItem: null },\n ...exhibitTexts.map((et) => ({\n text: et.text,\n source: `ex-${et.ex.key}`,\n mappedItem: exhibitToItem[et.ex.key] ?? null,\n })),\n ];\n\n for (const scan of scans) {\n for (const kw of KEYWORDS) {\n const pattern = new RegExp(\n \"\\\\b\" + kw.replace(/[.*+?^${}()|[\\]\\\\]/g, \"\\\\$&\") + \"\\\\b\",\n \"gi\",\n );\n let match;\n while ((match = pattern.exec(scan.text)) !== null) {\n const cStart = Math.max(0, match.index - CONTEXT_CHARS);\n const cEnd = Math.min(\n scan.text.length,\n match.index + kw.length + CONTEXT_CHARS,\n );\n const context = scan.text.slice(cStart, cEnd).trim();\n\n if (isFalsePositive(kw, context)) continue;\n\n let itemCode: string | null = null;\n let itemTitle: string | null = null;\n if (scan.source === \"body\") {\n const it = findContainingItem(items, match.index);\n itemCode = it?.item_code ?? null;\n itemTitle = it?.item_title ?? null;\n } else {\n itemCode = scan.mappedItem;\n itemTitle = itemCode\n ? (items.find((i) => i.item_code === itemCode)?.item_title ??\n null)\n : null;\n }\n\n const { speaker, title: speakerTitle } = scan.source === \"body\"\n ? { speaker: null, title: null }\n : extractNearbySpeaker(context);\n\n const score = scoreHit(\n context,\n itemCode,\n scan.source,\n speakerTitle,\n );\n\n allKwHits.push({\n keyword: kw,\n context,\n source: scan.source,\n item_code: itemCode,\n item_title: itemTitle,\n speaker,\n speaker_title: speakerTitle,\n score,\n filing_date: filing.date,\n filing_url: filing.url,\n });\n }\n }\n }\n }\n\n // Dedupe keyword hits\n const seen = new Set();\n const uniqueKwHits: KeywordHit[] = [];\n for (const h of allKwHits) {\n const key = normalize(h.context) + \"|\" + h.source;\n if (!seen.has(key)) {\n seen.add(key);\n uniqueKwHits.push(h);\n }\n }\n\n uniqueKwHits.sort((a, b) => b.score - a.score);\n allItems.sort((a, b) =>\n b.score - a.score || b.filing_date.localeCompare(a.filing_date)\n );\n allExhibits.sort((a, b) => b.filing_date.localeCompare(a.filing_date));\n\n const returnedHits = uniqueKwHits.slice(0, MAX_HITS_RETURNED);\n const returnedItems = allItems.slice(0, MAX_ITEMS_RETURNED);\n\n const kwCounts: Record = {};\n for (const h of uniqueKwHits) {\n kwCounts[h.keyword] = (kwCounts[h.keyword] || 0) + 1;\n }\n\n const itemCodeCounts: Record = {};\n for (const it of allItems) {\n itemCodeCounts[it.item_code] = (itemCodeCounts[it.item_code] || 0) + 1;\n }\n\n const sourceCounts: Record = {};\n for (const h of uniqueKwHits) {\n sourceCounts[h.source] = (sourceCounts[h.source] || 0) + 1;\n }\n\n const response = {\n ticker,\n company,\n total_filings_scanned: filings.length,\n total_items_found: allItems.length,\n total_items_returned: returnedItems.length,\n items_disclosed: returnedItems,\n item_code_counts: itemCodeCounts,\n total_exhibits_fetched: allExhibits.length,\n exhibits: allExhibits,\n total_keyword_hits_found: uniqueKwHits.length,\n total_keyword_hits_returned: returnedHits.length,\n keyword_counts: kwCounts,\n source_counts: sourceCounts,\n keyword_hits: returnedHits,\n };\n\n const trimmed = fitResponse(response);\n const finalJson = JSON.stringify(trimmed);\n return new Response(\n JSON.stringify({ ...trimmed, _response_size_bytes: finalJson.length }),\n { headers: { \"content-type\": \"application/json\" } },\n );\n } catch (e: any) {\n return Response.json({ error: e.message }, { status: 500 });\n }\n}","deleted","label",[114],"pulls",1,"forks","envVars",{"_137":52,"_139":52},"connections",{"_137":52,"_138":52},"count","unfilledCount","emptyCount",{"_20":113,"_13":114,"_115":116,"_117":-5,"_118":21,"_119":30,"_120":107,"_22":141,"_29":122,"_123":124,"_125":126,"_127":38,"_128":-5,"_142":143,"_88":144},["D",1776979810900],"children",[],[114],["D",1776975121245],{"_11":12,"_86":82},{"_11":12,"_80":-5,"_81":82,"_45":46,"_83":84,"_85":38},{"_29":30,"_13":26,"_20":21,"_27":28,"_31":-5,"_32":-5,"_75":-5,"_76":-5,"_77":-5,"_78":14,"_79":12},"ctx",{"_68":-5,"_109":182,"_183":184,"_185":186,"_187":38,"_188":38,"_189":38,"_190":107,"_191":-5,"_192":-7,"_193":-7,"_194":52,"_195":38,"_196":38,"_197":-5,"_198":38,"_199":38,"_200":38,"_201":-5},"ENV",{"_153":154,"_155":156,"_157":26,"_158":159,"_160":161,"_162":163,"_164":165,"_166":167,"_168":169,"_170":171,"_172":173,"_174":175,"_176":177,"_178":179,"_180":181},"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"]

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