[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_312":313,"_314":315},"routes/_app.x.$handle.$name",{"_11":12,"_13":14,"_15":16,"_18":19,"_17":-7,"_232":-5,"_20":233,"_22":234,"_235":236,"_237":238,"_26":239,"_24":240,"_241":-5,"_242":-5,"_243":56,"_244":245,"_246":47,"_247":-5,"_248":-5,"_249":250},"routes/_app.x.$handle.$name.branch.$branch.code.$",{"_11":12,"_13":14,"_15":16,"_17":-7,"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_28":-5,"_29":-5,"_30":-5,"_31":-5,"_32":-5},"handle","saltmine","name","lead-extraction-tool","branchName","main","version","path","backend","project",{"_35":178,"_13":14,"_48":179,"_180":-5,"_181":56,"_182":183,"_184":183,"_185":186,"_187":-5,"_188":189,"_190":77,"_191":47,"_192":-5,"_193":-5,"_194":50,"_195":196,"_197":-5,"_198":-5,"_199":-5,"_200":-5,"_201":202,"_203":202,"_204":205,"_206":205,"_207":205,"_208":202,"_209":202,"_210":211,"_212":213,"_214":215,"_216":56},"tree",[71,72,73,74],"file",{"_35":67,"_42":43,"_38":41,"_13":19,"_53":-5,"_51":68,"_17":50,"_40":-5,"_48":69,"_44":45,"_57":-5,"_18":70},"contents",[33,34],"upstream","pull","ahead","behind","envVars",{"_35":59,"_13":60,"_38":61,"_40":41,"_42":43,"_44":62,"_46":47,"_48":63,"_17":64,"_51":52,"_53":65,"_55":56,"_57":-5,"_18":66},{"_35":36,"_13":37,"_38":39,"_40":41,"_42":43,"_44":45,"_46":47,"_48":49,"_17":50,"_51":52,"_53":54,"_55":56,"_57":-5,"_18":58},"id","7e310cc2-39b4-11f1-b6fc-42b51c65c3df","scraper.ts","fileId","7e310d80-39b4-11f1-b6fc-42b51c65c3df","parentId","4345b1fc-5211-45ab-9c7d-c98189ce527e","branchId","1d19d2fc-39b4-11f1-90cb-42b51c65c3df","branchVersion",6,"latest",true,"createdAt",["D",1776358279913],0,"fileType","script","content","import { load } from \"npm:cheerio\";\n\n/** Fetch a page and extract all email addresses + internal links */\nexport async function scrapePage(url: string): Promise<{\n emails: string[];\n links: string[];\n text: string;\n}> {\n const res = await fetch(url, {\n headers: {\n \"User-Agent\":\n \"Mozilla/5.0 (compatible; LeadExtractorBot/1.0; +https://val.town)\",\n Accept: \"text/html,application/xhtml+xml\",\n },\n redirect: \"follow\",\n });\n\n if (!res.ok) {\n throw new Error(`Failed to fetch ${url}: ${res.status}`);\n }\n\n const contentType = res.headers.get(\"content-type\") || \"\";\n if (!contentType.includes(\"text/html\")) {\n return { emails: [], links: [], text: \"\" };\n }\n\n const html = await res.text();\n const $ = load(html);\n\n // Extract emails from mailto links\n const emails = new Set();\n $(\"a[href^='mailto:']\").each((_, el) => {\n const href = $(el).attr(\"href\") || \"\";\n const email = href.replace(\"mailto:\", \"\").split(\"?\")[0].toLowerCase().trim();\n if (email && isValidEmail(email)) {\n emails.add(email);\n }\n });\n\n // Extract emails from visible text using regex\n const bodyText = $(\"body\").text();\n const emailRegex = /[a-zA-Z0-9._%+\\-]+@[a-zA-Z0-9.\\-]+\\.[a-zA-Z]{2,}/g;\n const textEmails = bodyText.match(emailRegex) || [];\n for (const e of textEmails) {\n const clean = e.toLowerCase().trim();\n if (isValidEmail(clean)) {\n emails.add(clean);\n }\n }\n\n // Also check href attributes and other common places\n $(\"a[href]\").each((_, el) => {\n const href = $(el).attr(\"href\") || \"\";\n const hrefEmails = href.match(emailRegex) || [];\n for (const e of hrefEmails) {\n if (isValidEmail(e.toLowerCase())) emails.add(e.toLowerCase());\n }\n });\n\n // Extract internal links for further crawling\n const baseUrl = new URL(url);\n const internalLinks = new Set();\n\n $(\"a[href]\").each((_, el) => {\n const href = $(el).attr(\"href\") || \"\";\n try {\n const resolved = new URL(href, url);\n if (resolved.hostname === baseUrl.hostname && resolved.protocol.startsWith(\"http\")) {\n // Clean the URL (remove hash, normalize)\n resolved.hash = \"\";\n internalLinks.add(resolved.toString());\n }\n } catch {\n // ignore invalid URLs\n }\n });\n\n // Get useful text context (truncated)\n const pageText = $(\"body\").text().replace(/\\s+/g, \" \").trim().slice(0, 3000);\n\n return {\n emails: Array.from(emails),\n links: Array.from(internalLinks),\n text: pageText,\n };\n}\n\nfunction isValidEmail(email: string): boolean {\n // Basic validation — exclude common false positives\n if (email.length > 254) return false;\n if (email.endsWith(\".png\") || email.endsWith(\".jpg\") || email.endsWith(\".gif\")) return false;\n if (email.includes(\"@example.\") || email.includes(\"@test.\")) return false;\n if (email.startsWith(\"@\") || email.endsWith(\"@\")) return false;\n return /^[a-zA-Z0-9._%+\\-]+@[a-zA-Z0-9.\\-]+\\.[a-zA-Z]{2,}$/.test(email);\n}\n","deleted",false,"label",[19,37],"0d2af582-39b5-11f1-b31d-42b51c65c3df","agent.ts","90cb1760-39b4-11f1-b5ef-42b51c65c3df",11,["D",1776358519783],1,"import { Agent, run, tool } from \"npm:@openai/agents@0.7\";\nimport { z } from \"npm:zod\";\nimport { scrapePage } from \"./scraper.ts\";\n\n/** Tool: scrape a URL for emails and links */\nconst scrapeUrl = tool({\n name: \"scrape_url\",\n description:\n \"Fetch a web page and extract all email addresses and internal links found on it. \" +\n \"Use this to scan pages for lead information. Returns emails found, internal links to explore, \" +\n \"and a snippet of the page text.\",\n parameters: z.object({\n url: z.string().describe(\"The full URL to scrape, e.g. https://example.com\"),\n }),\n async execute({ url }) {\n try {\n const result = await scrapePage(url);\n return JSON.stringify(result);\n } catch (e: any) {\n return JSON.stringify({ error: e.message, emails: [], links: [], text: \"\" });\n }\n },\n});\n\nconst leadExtractorAgent = new Agent({\n name: \"Lead Extractor\",\n model: \"gpt-4o-mini\",\n instructions: `You are a lead extraction agent. Given a website URL, your job is to find email addresses \nand contact information of people who work at or are associated with that website.\n\nStrategy:\n1. Start by scraping the given URL.\n2. Look at the internal links found and prioritize pages likely to contain contact info:\n - \"about\", \"team\", \"contact\", \"people\", \"staff\", \"leadership\", \"our-team\"\n - Footer links, \"get in touch\", etc.\n3. Scrape up to 5-6 of the most promising pages (don't go overboard).\n4. For each email you find, try to identify the person's name and role from the surrounding context.\n\nIMPORTANT: When you're done, respond with ONLY a valid JSON object (no markdown, no backticks) in this exact format:\n{\n \"leads\": [\n {\n \"email\": \"person@company.com\",\n \"name\": \"John Smith\",\n \"role\": \"CEO\",\n \"source\": \"https://example.com/about\"\n }\n ],\n \"summary\": \"A brief summary of what you found\",\n \"pagesScanned\": [\"https://example.com\", \"https://example.com/about\"]\n}\n\nIf name or role aren't available, use null for those fields. Always include the source URL where each email was found.`,\n tools: [scrapeUrl],\n});\n\nexport async function extractLeads(url: string) {\n const result = await run(\n leadExtractorAgent,\n `Extract leads from this website: ${url}`,\n { maxTurns: 10 },\n );\n\n // Parse the agent's JSON output\n try {\n const output = result.finalOutput.trim();\n // Try to extract JSON if agent wrapped it in markdown\n const jsonMatch = output.match(/```(?:json)?\\s*([\\s\\S]*?)```/) || [null, output];\n return JSON.parse(jsonMatch[1]!.trim());\n } catch {\n // Fallback if parsing fails\n return {\n leads: [],\n summary: result.finalOutput,\n pagesScanned: [],\n };\n }\n}\n",[19,60],"7e313ff8-39b4-11f1-b6fc-42b51c65c3df","directory",["D",1776358279913],[19],{"_35":67,"_13":19,"_38":41,"_40":-5,"_42":43,"_44":45,"_46":47,"_48":167,"_17":50,"_51":68,"_53":-5,"_55":56,"_57":-5,"_82":168,"_18":169},{"_35":93,"_13":94,"_38":95,"_40":-5,"_42":43,"_44":64,"_46":47,"_48":96,"_17":50,"_51":68,"_53":-5,"_55":56,"_57":-5,"_82":97,"_18":98},{"_35":85,"_13":86,"_38":87,"_40":-5,"_42":43,"_44":88,"_46":47,"_48":89,"_17":64,"_51":24,"_53":90,"_55":56,"_57":-5,"_82":91,"_18":92},{"_35":75,"_13":76,"_38":77,"_40":-5,"_42":43,"_44":78,"_46":47,"_48":79,"_17":64,"_51":80,"_53":81,"_55":56,"_57":-5,"_82":83,"_18":84},"9b5cd0f6-39b4-11f1-b6fc-42b51c65c3df","index.ts","019d9731-ceb7-76bd-9726-ce7caf42baef",8,["D",1776358328810],"http","import { parseVal, serveFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Hono } from \"npm:hono\";\nimport { extractLeads } from \"./backend/agent.ts\";\n\nconst app = new Hono();\n\n// Serve index.html at the root /\napp.get(\"/\", () => serveFile(\"/frontend/index.html\"));\n\n// Serve all /frontend files\napp.get(\"/frontend/*\", (c) => serveFile(c.req.path));\n\n// View source redirect\napp.get(\"/source\", (c) => c.redirect(parseVal().links.self.val));\n\n// Lead extraction API\napp.post(\"/api/extract\", async (c) => {\n const { url } = await c.req.json<{ url: string }>();\n\n if (!url) {\n return c.json({ error: \"URL is required\" }, 400);\n }\n\n // Basic URL validation\n try {\n new URL(url);\n } catch {\n return c.json({ error: \"Invalid URL format\" }, 400);\n }\n\n try {\n const result = await extractLeads(url);\n return c.json(result);\n } catch (e: any) {\n console.error(\"Extraction error:\", e);\n return c.json({ error: e.message || \"Extraction failed\" }, 500);\n }\n});\n\n// Unwrap and rethrow Hono errors as the original error\napp.onError((err) => Promise.reject(err));\n\n// HTTP vals expect an exported \"fetch handler\"\nexport default app.fetch;\n","children",[],[76],"ad46eb94-39b4-11f1-b5ef-42b51c65c3df","README.md","019d9731-ceb7-76bd-9726-c9eff147349f",10,["D",1776358358901],"# 🔍 Lead Extraction Tool\n\nAn AI-powered lead extractor that scans websites to find email addresses and contact information.\n\n## How it works\n\n```mermaid\nflowchart LR\n A[Enter URL] --> B[AI Agent]\n B -->|scrape_url tool| C[Fetch & Parse HTML]\n C -->|emails + links| B\n B -->|picks next page| C\n B --> D[Structured leads JSON]\n D --> E[Results table]\n```\n\n1. You enter a website URL in the form\n2. An **OpenAI Agent** (GPT-4o-mini) receives the URL and uses a `scrape_url` tool\n3. The agent strategically crawls the site — prioritizing about/team/contact pages\n4. Emails are extracted from `mailto:` links and page text via regex\n5. The agent returns structured lead data (email, name, role, source page)\n6. Results are displayed in a table with a \"copy all emails\" button\n\n## Setup\n\n1. Set the `OPENAI_API_KEY` environment variable → [Get your key](https://platform.openai.com/api-keys)\n\n## Tech Stack\n\n- **Frontend**: React + Twind (Tailwind)\n- **Backend**: Hono API on Val Town\n- **AI**: OpenAI Agents SDK (`@openai/agents`)\n- **Scraping**: Cheerio HTML parser\n",[],[86],"1d1f65b4-39b4-11f1-90cb-42b51c65c3df","frontend","019d9731-ceb7-76bd-9726-c5bb005ecf3e",["D",1776358116966],[99,100,101,102],[94],{"_35":126,"_13":127,"_38":128,"_40":95,"_42":43,"_44":64,"_46":47,"_48":129,"_17":50,"_51":68,"_53":-5,"_55":56,"_57":-5,"_82":130,"_18":131},{"_35":118,"_13":119,"_38":120,"_40":95,"_42":43,"_44":121,"_46":47,"_48":122,"_17":64,"_51":24,"_53":123,"_55":56,"_57":-5,"_82":124,"_18":125},{"_35":110,"_13":111,"_38":112,"_40":95,"_42":43,"_44":113,"_46":47,"_48":114,"_17":64,"_51":24,"_53":115,"_55":56,"_57":-5,"_82":116,"_18":117},{"_35":103,"_13":104,"_38":105,"_40":95,"_42":43,"_44":64,"_46":47,"_48":106,"_17":50,"_51":52,"_53":107,"_55":56,"_57":-5,"_82":108,"_18":109},"1d1f6280-39b4-11f1-90cb-42b51c65c3df","index.tsx","019d9731-ceb7-76bd-9726-c1aa93d584aa",["D",1776358116966],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { createRoot } from \"https://esm.sh/react-dom@18.2.0/client\";\nimport { App } from \"./components/App.tsx\";\n\nconst root = document.getElementById(\"root\");\nif (!root) {\n throw new Error(\"No root element found\");\n}\n\ncreateRoot(root).render();",[],[94,104],"57bac074-39b4-11f1-9c1c-42b51c65c3df","index.html","019d9731-ceb7-76bd-9726-bfe9e9e2f02a",2,["D",1776358215373],"\n\n \n \n \n Lead Extractor\n \n \n \n \n

\n \n \n \n",[],[94,111],"a259f26c-39b4-11f1-b5ef-42b51c65c3df","favicon.svg","019d9731-ceb7-76bd-9726-b83463316c6a",9,["D",1776358340560],"",[],[94,119],"1d1f520e-39b4-11f1-90cb-42b51c65c3df","components","019d9731-ceb7-76bd-9726-b67d8460c785",["D",1776358116966],[132,133,134,135],[94,127],{"_35":159,"_13":160,"_38":161,"_40":128,"_42":43,"_44":162,"_46":47,"_48":163,"_17":64,"_51":52,"_53":164,"_55":56,"_57":-5,"_82":165,"_18":166},{"_35":152,"_13":153,"_38":154,"_40":128,"_42":43,"_44":64,"_46":47,"_48":155,"_17":50,"_51":52,"_53":156,"_55":56,"_57":-5,"_82":157,"_18":158},{"_35":144,"_13":145,"_38":146,"_40":128,"_42":43,"_44":147,"_46":47,"_48":148,"_17":50,"_51":52,"_53":149,"_55":56,"_57":-5,"_82":150,"_18":151},{"_35":136,"_13":137,"_38":138,"_40":128,"_42":43,"_44":139,"_46":47,"_48":140,"_17":50,"_51":52,"_53":141,"_55":56,"_57":-5,"_82":142,"_18":143},"6be35c6e-39b4-11f1-8360-42b51c65c3df","LeadResults.tsx","6be35d0e-39b4-11f1-8360-42b51c65c3df",5,["D",1776358249208],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport type { ExtractionResult, Lead } from \"./App.tsx\";\n\ninterface LeadResultsProps {\n result: ExtractionResult;\n}\n\nexport function LeadResults({ result }: LeadResultsProps) {\n const { leads, summary, pagesScanned } = result;\n\n return (\n

\n {/* Summary */}\n

📋 Summary

{summary}

\n\n {/* Leads Table */}\n {leads.length > 0 ? (\n

\n 🎯 Found {leads.length} lead{leads.length !== 1 ? \"s\" : \"\"}\n

\n copyToClipboard(leads)}\n className=\"text-sm px-3 py-1 bg-white border border-gray-300 rounded-md\n hover:bg-gray-50 transition-colors text-gray-600\"\n >\n 📋 Copy all emails\n \n

\n \n \n \n \n \n \n \n \n \n \n {leads.map((lead, i) => (\n \n \n \n \n \n \n ))}\n \n

Email	Name	Role	Source
\n \n {lead.email}\n \n	{lead.name \|\| \"—\"}	{lead.role \|\| \"—\"}	{lead.source \|\| \"—\"}

\n ) : (\n

\n No email leads found on this website. Try a different URL, like a company's\n \"About\" or \"Contact\" page.\n

\n )}\n\n {/* Pages Scanned */}\n {pagesScanned.length > 0 && (\n

\n Pages scanned ({pagesScanned.length})\n

\n \n {page}\n \n

\n )}\n

\n );\n}\n\nfunction copyToClipboard(leads: Lead[]) {\n const emails = leads.map((l) => l.email).join(\"\\n\");\n navigator.clipboard.writeText(emails).then(() => {\n alert(`Copied ${leads.length} email(s) to clipboard!`);\n });\n}",[],[94,127,137],"6504cbc6-39b4-11f1-8360-42b51c65c3df","LeadForm.tsx","6504cc5c-39b4-11f1-8360-42b51c65c3df",4,["D",1776358237679],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { useState } from \"https://esm.sh/react@18.2.0\";\n\ninterface LeadFormProps {\n onSubmit: (url: string) => void;\n loading: boolean;\n}\n\nexport function LeadForm({ onSubmit, loading }: LeadFormProps) {\n const [url, setUrl] = useState(\"\");\n\n function handleSubmit(e: React.FormEvent) {\n e.preventDefault();\n const trimmed = url.trim();\n if (!trimmed) return;\n\n // Add https:// if no protocol\n const finalUrl = trimmed.match(/^https?:\\/\\//) ? trimmed : `https://${trimmed}`;\n onSubmit(finalUrl);\n }\n\n return (\n

\n setUrl(e.target.value)}\n placeholder=\"e.g. example.com or https://example.com/about\"\n disabled={loading}\n className=\"flex-1 px-4 py-3 border border-gray-300 rounded-lg text-lg\n focus:outline-none focus:ring-2 focus:ring-blue-500 focus:border-transparent\n disabled:bg-gray-100 disabled:text-gray-400\n placeholder-gray-400\"\n />\n \n {loading ? \"Scanning...\" : \"Extract Leads\"}\n \n \n );\n}",[],[94,127,145],"1d1f4a48-39b4-11f1-90cb-42b51c65c3df","Counter.tsx","019d9731-ceb7-76bd-9726-b3a0f7e0dc0f",["D",1776358116966],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { useState } from \"https://esm.sh/react@18.2.0\";\n\nexport function Counter() {\n const [count, setCount] = useState(0);\n return (\n

\n Clicked\n setCount((c) => c + 1)}\n class=\"bg-blue-500 hover:bg-blue-600 text-white font-medium px-4 py-2 rounded-lg transition-colors cursor-pointer\"\n >\n {count}\n \n times\n

\n );\n}\n",[],[94,127,153],"5fb93134-39b4-11f1-8701-42b51c65c3df","App.tsx","019d9731-ceb7-76bd-9726-ad7554057fa1",3,["D",1776358228786],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { useState } from \"https://esm.sh/react@18.2.0\";\nimport { LeadForm } from \"./LeadForm.tsx\";\nimport { LeadResults } from \"./LeadResults.tsx\";\n\nexport interface Lead {\n name?: string;\n email: string;\n role?: string;\n source?: string;\n}\n\nexport interface ExtractionResult {\n leads: Lead[];\n summary: string;\n pagesScanned: string[];\n}\n\nexport function App() {\n const [loading, setLoading] = useState(false);\n const [result, setResult] = useState(null);\n const [error, setError] = useState(null);\n\n async function handleExtract(url: string) {\n setLoading(true);\n setError(null);\n setResult(null);\n\n try {\n const res = await fetch(\"/api/extract\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({ url }),\n });\n\n if (!res.ok) {\n const errData = await res.json().catch(() => ({ error: \"Extraction failed\" }));\n throw new Error(errData.error || `HTTP ${res.status}`);\n }\n\n const data: ExtractionResult = await res.json();\n setResult(data);\n } catch (e: any) {\n setError(e.message || \"Something went wrong\");\n } finally {\n setLoading(false);\n }\n }\n\n return (\n

\n 🔍 Lead Extractor\n

\n Enter a website URL and our AI agent will scan it for contact information\n

\n\n \n\n {error && (\n

\n ⚠️ {error}\n

\n )}\n\n {loading && (\n

\n AI agent is scanning the website for leads... this may take a minute.\n

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