Lead Generation Agent 🕵️‍♂️

\n ${props.children}\n

Built on Val Town. View source: ${import.meta.url.replace(\"https://\", \"\").replace(\".esm.town\", \".val.town\")}

\n \n \n`;\n\nconst JobRow = (job: Job) =>\n html`\n \n ${job.id.substring(0, 8)}...\n ${job.search_query}\n ${job.status}\n ${new Date(job.created_at).toLocaleString()}\n ${new Date(job.updated_at).toLocaleString()}\n View Details\n \n ${\n job.error_message\n ? html`

Error: ${job.error_message}

`\n : \"\"\n }\n`;\n\nconst LeadRow = (lead: Lead) =>\n html`\n

\n ${lead.business_name || lead.website_url.replace(/^https?:\\/\\//, \"\").split(\"/\")[0]} - \n ${lead.status}\n ${lead.email_address ? ` - ${lead.email_address}` : \"\"}\n

Lead ID: ${lead.id.substring(0, 8)}...

Website: ${lead.website_url}

\n ${lead.email_address ? html`

Email: ${lead.email_address}

` : \"\"}\n ${lead.email_subject ? html`

Drafted Subject: ${lead.email_subject}

` : \"\"}\n ${lead.drafted_email_body ? html`

Drafted Body:

${lead.drafted_email_body}

` : \"\"}\n

Status: ${lead.status}

\n ${lead.error_message ? html`

Error: ${lead.error_message}

` : \"\"}\n

Last Updated: ${new Date(lead.updated_at).toLocaleString()}

\n`;\n\n// --- Hono Routes ---\napp.get(\"/\", async (c) => {\n const jobIdParam = c.req.query(\"job_id\");\n let jobs: Job[] = [];\n let leads: Lead[] = [];\n let selectedJob: Job | null = null;\n let metrics = { total: 0, emailFound: 0, emailDrafted: 0, errors: 0 };\n let generalError: string | null = null;\n\n try {\n const jobResults = await sqlite.execute(\n \"SELECT id, search_query, status, created_at, updated_at, error_message FROM jobs ORDER BY created_at DESC LIMIT 50;\",\n ); // Limit jobs displayed\n jobs = jobResults.rows as Job[];\n\n if (jobIdParam) {\n const selectedJobResult = await sqlite.execute({\n sql: \"SELECT id, search_query, status, created_at, updated_at, error_message FROM jobs WHERE id = ?;\",\n args: [jobIdParam],\n });\n selectedJob = selectedJobResult.rows[0] as Job || null;\n\n if (selectedJob) {\n const leadResults = await sqlite.execute({\n sql:\n \"SELECT id, job_id, business_name, website_url, email_address, email_subject, drafted_email_body, status, error_message, created_at, updated_at FROM leads WHERE job_id = ? ORDER BY created_at ASC;\",\n args: [jobIdParam],\n });\n leads = leadResults.rows as Lead[];\n\n metrics.total = leads.length;\n metrics.emailFound = leads.filter(l =>\n l.email_address && l.status !== \"error_scraping_fetch\" && l.status !== \"error_scraping\"\n ).length;\n metrics.emailDrafted = leads.filter(l => l.drafted_email_body && l.status !== \"error_drafting\").length;\n metrics.errors = leads.filter(l => l.status.startsWith(\"error_\") || l.error_message).length;\n } else {\n generalError = `Job with ID ${jobIdParam} not found.`;\n }\n }\n } catch (e) {\n console.error(\"Error fetching data for UI:\", e);\n generalError = `Error loading data: ${e.message}`;\n }\n\n return c.html(\n Layout({\n children: html`\n ${generalError ? html`

${generalError}

` : \"\"}\n

Start New Lead Generation Job

\n \n\n ${\n jobIdParam && selectedJob\n ? html`\n

Details for Job: \"${selectedJob.search_query}\" (${\n selectedJob.id.substring(0, 8)\n }...)

\n \n ⬅️ Back to All Jobs\n

Current Status: ${selectedJob.status}

\n ${selectedJob.error_message ? html`

Job Error: ${selectedJob.error_message}

` : \"\"}\n

Leads Identified/Attempted: ${metrics.total}

✅ Emails Found: ${metrics.emailFound}

✉️ Emails Drafted: ${metrics.emailDrafted}

⚠️ Leads with Errors: ${metrics.errors}

Leads:

\n ${\n leads.length > 0\n ? leads.map(LeadRow)\n : html`

No leads processed yet for this job, or job is in progress. Refresh to see updates.

`\n }\n `\n : html`\n

Previous Jobs

\n ${\n jobs.length > 0\n ? html`\n \n \n \n \n \n \n \n \n \n \n \n \n ${jobs.map(JobRow)}\n \n

ID	Query	Status	Created	Updated	Actions

\n `\n : html`

No jobs found. Start one above!

`\n }\n `\n }\n `,\n }),\n );\n});\n\napp.post(\n \"/start-job\",\n validator(\"form\", (value, c) => {\n const searchQuery = value[\"searchQuery\"];\n if (!searchQuery || typeof searchQuery !== \"string\" || searchQuery.trim().length === 0) {\n return c.text(\"Search query is required\", 400);\n }\n if (searchQuery.trim().length > 200) {\n return c.text(\"Search query is too long (max 200 chars)\", 400);\n }\n return { searchQuery: searchQuery.trim() };\n }),\n async (c) => {\n const { searchQuery } = c.req.valid(\"form\");\n const jobId = crypto.randomUUID();\n const now = new Date().toISOString();\n\n try {\n await sqlite.execute({\n sql: `INSERT INTO jobs (id, search_query, status, created_at, updated_at) VALUES (?, ?, ?, ?, ?);`,\n args: [jobId, searchQuery, \"pending\", now, now],\n });\n\n processJob(jobId, searchQuery).catch(err => {\n console.error(`Unhandled error in background job ${jobId}:`, err);\n updateJobStatus(jobId, \"failed_uncaught_exception\", err.message).catch(console.error);\n });\n } catch (e) {\n console.error(\"Error starting job:\", e);\n return c.html(\n Layout({\n children: html`

Error starting job: ${e.message}. Go back

`,\n }),\n );\n }\n\n return new Response(null, {\n status: 302,\n headers: { Location: `/?job_id=${jobId}` }, // Redirect to view the new job\n });\n },\n);\n\n// Corrected export for Val Town\nexport default app.fetch;","deleted","label","children",[],[99],"files",[143],"counts",{"_165":31,"_166":167,"_168":31,"_169":31},"pulls","branches",1,"forks","envVars","contents",[],"file",{"_103":144,"_95":99,"_145":115,"_146":-5,"_147":135,"_148":119,"_149":117,"_105":174,"_100":151,"_152":153,"_154":155,"_156":27,"_157":-5,"_98":175},["D",1747009279180],[99],"upstream","emptyEnvVars","isNew","routes/_app.x.$handle.$name.branch.$branch.history_.$",{"_93":94,"_95":96,"_97":41,"_98":99,"_101":181,"_172":185,"_188":189,"_214":215,"_223":-7,"_224":31,"_225":27},{"_103":104,"_95":96,"_105":182,"_107":-5,"_108":27,"_109":110,"_111":-5,"_112":-5,"_12":113,"_114":115,"_116":117,"_118":119,"_120":31,"_121":122,"_123":122,"_124":125,"_126":125,"_127":125,"_128":122,"_129":27,"_21":183,"_133":184},["D",1747009028595],{"_93":94,"_131":132},{"_100":119,"_95":41,"_103":135,"_136":104,"_137":-5,"_138":-5,"_139":-5,"_140":-5},{"_103":144,"_95":99,"_145":115,"_146":-5,"_147":135,"_148":119,"_149":117,"_105":186,"_100":151,"_152":153,"_154":155,"_156":27,"_157":-5,"_98":187},["D",1747009279180],[99],"history",[190,192,197,202,206,210],{"_103":144,"_147":135,"_145":115,"_95":99,"_154":155,"_152":153,"_100":151,"_146":-5,"_105":191,"_148":119,"_157":-5},["D",1747009279180],{"_103":193,"_147":135,"_145":115,"_95":99,"_154":194,"_152":153,"_100":195,"_146":-5,"_105":196,"_148":151,"_157":-5},"9334b302-2ec6-11f0-aa5d-569c3dd06744","import { Hono } from \"https://esm.sh/hono@4.3.7\";\nimport { serve } from \"https://esm.sh/hono@4.3.7/adapter/deno/serve.js\";\nimport { html } from \"https://esm.sh/hono@4.3.7/html\";\nimport { validator } from \"https://esm.sh/hono@4.3.7/validator\";\n// Using @valtown/sqlite\nimport { OpenAI } from \"https://esm.town/v/std/openai?v=1\";\nimport { Batch, sqlite, Statement } from \"https://esm.town/v/std/sqlite?v=4\";\n\n// --- Database Initialization ---\n// (Best effort initialization, errors are ignored if tables already exist)\nsqlite.batch([\n `CREATE TABLE IF NOT EXISTS jobs (\n id TEXT PRIMARY KEY,\n search_query TEXT NOT NULL,\n status TEXT NOT NULL,\n created_at TEXT NOT NULL,\n updated_at TEXT NOT NULL,\n error_message TEXT\n );`,\n `CREATE TABLE IF NOT EXISTS leads (\n id TEXT PRIMARY KEY,\n job_id TEXT NOT NULL,\n business_name TEXT,\n website_url TEXT NOT NULL,\n email_address TEXT,\n email_subject TEXT,\n drafted_email_body TEXT,\n status TEXT NOT NULL,\n error_message TEXT,\n created_at TEXT NOT NULL,\n updated_at TEXT NOT NULL,\n FOREIGN KEY (job_id) REFERENCES jobs(id)\n );`,\n]);\n\nconst app = new Hono();\n\n// --- Helper Functions ---\nasync function updateJobStatus(jobId: string, status: string, errorMessage?: string) {\n await sqlite.execute({\n sql: `UPDATE jobs SET status = ?, updated_at = ?, error_message = ? WHERE id = ?;`,\n args: [status, new Date().toISOString(), errorMessage || null, jobId],\n });\n}\n\nasync function updateLeadStatus(leadId: string, status: string, updates: Partial = {}, errorMessage?: string) {\n let sql = `UPDATE leads SET status = ?, updated_at = ?`;\n const args: any[] = [status, new Date().toISOString()];\n\n if (updates.email_address) {\n sql += `, email_address = ?`;\n args.push(updates.email_address);\n }\n if (updates.email_subject) {\n sql += `, email_subject = ?`;\n args.push(updates.email_subject);\n }\n if (updates.drafted_email_body) {\n sql += `, drafted_email_body = ?`;\n args.push(updates.drafted_email_body);\n }\n if (updates.business_name) {\n sql += `, business_name = ?`;\n args.push(updates.business_name);\n }\n if (errorMessage !== undefined) {\n sql += `, error_message = ?`;\n args.push(errorMessage || null);\n }\n\n sql += ` WHERE id = ?;`;\n args.push(leadId);\n\n await sqlite.execute({ sql, args });\n}\n\n// --- Core Lead Generation Logic ---\n\n// WARNING: Scraping search engines like DuckDuckGo is fragile and might break.\nasync function searchWebsites(searchQuery: string, jobId: string): Promise<{ name: string; url: string }[]> {\n const searchUrl = `https://html.duckduckgo.com/html/?q=${encodeURIComponent(searchQuery)}`;\n console.log(`Searching: ${searchUrl}`);\n let foundSites: { name: string; url: string }[] = [];\n\n try {\n const response = await fetch(searchUrl, {\n headers: {\n // Minimal headers to mimic a browser\n \"User-Agent\":\n \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\",\n },\n });\n if (!response.ok) {\n console.error(`DuckDuckGo search failed: ${response.status}`);\n await updateJobStatus(jobId, \"error_searching\", `DuckDuckGo search HTTP error: ${response.status}`);\n return [];\n }\n const htmlContent = await response.text();\n\n // Regex to find search result links and titles (this is very basic and fragile)\n // Looks for ...\n const resultRegex = /]*href=\"([^\"]+)\"[^>]*>([^<]+)<\\/a>/g;\n let match;\n while ((match = resultRegex.exec(htmlContent)) !== null) {\n let url = match[1];\n const name = match[2].trim();\n\n // DuckDuckGo uses redirect URLs, try to clean them\n if (url.startsWith(\"/l/?kh=-1&uddg=\")) {\n const decodedUrl = decodeURIComponent(url.substring(\"/l/?kh=-1&uddg=\".length));\n const actualUrlMatch = decodedUrl.match(/^(.*?)(&rut=|&rut=|$)/);\n if (actualUrlMatch && actualUrlMatch[1]) {\n url = actualUrlMatch[1];\n }\n }\n\n // Basic filter for valid http(s) URLs, ignore internal DDG links\n if (url.startsWith(\"http\") && !url.includes(\"duckduckgo.com\")) {\n foundSites.push({ name, url });\n }\n }\n console.log(`Found ${foundSites.length} potential sites for job ${jobId}.`);\n } catch (error) {\n console.error(`Error during web search for job ${jobId}:`, error);\n await updateJobStatus(jobId, \"error_searching\", `Search exception: ${error.message}`);\n return [];\n }\n return foundSites.slice(0, 10); // Limit to 10 sites for now to avoid long runs\n}\n\nasync function extractEmailsFromWebsite(websiteUrl: string, leadId: string): Promise {\n console.log(`Scraping ${websiteUrl} for lead ${leadId}`);\n try {\n const response = await fetch(websiteUrl, {\n headers: { \"User-Agent\": \"Mozilla/5.0 ValTownLeadGen/1.0\" },\n signal: AbortSignal.timeout(10000),\n }); // 10s timeout\n if (!response.ok) {\n console.warn(`Failed to fetch ${websiteUrl}: ${response.status}`);\n await updateLeadStatus(leadId, \"error_scraping_fetch\", {}, `HTTP ${response.status}`);\n return null;\n }\n const htmlContent = await response.text();\n\n // Regex for emails (simplified)\n const emailRegex = /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}/g;\n const emails = htmlContent.match(emailRegex);\n\n if (emails && emails.length > 0) {\n // Filter out common image/font emails if any, prioritize generic ones\n const filteredEmails = emails.filter(email =>\n !email.endsWith(\".png\")\n && !email.endsWith(\".jpg\")\n && !email.endsWith(\".gif\")\n && !email.endsWith(\".svg\")\n && !email.endsWith(\".woff\")\n && !email.endsWith(\".ttf\")\n && !email.includes(\"example.com\")\n && !email.includes(\"domain.com\")\n && !email.startsWith(\"sentry\") // common support email prefix\n && email.length < 100 // avoid overly long strings\n );\n const uniqueEmails = [...new Set(filteredEmails)];\n const primaryEmail = uniqueEmails.find(e => !e.includes(\"wixpress\") && !e.includes(\"squarespace\"))\n || uniqueEmails[0];\n\n if (primaryEmail) {\n console.log(`Found email ${primaryEmail} on ${websiteUrl} for lead ${leadId}`);\n await updateLeadStatus(leadId, \"email_extracted\", { email_address: primaryEmail });\n return primaryEmail;\n }\n }\n console.log(`No email found on ${websiteUrl} for lead ${leadId}`);\n await updateLeadStatus(leadId, \"no_email_found\");\n return null;\n } catch (error) {\n console.error(`Error scraping ${websiteUrl} for lead ${leadId}:`, error);\n await updateLeadStatus(leadId, \"error_scraping\", {}, `Scrape exception: ${error.message}`);\n return null;\n }\n}\n\nasync function draftColdEmail(\n openai: OpenAI,\n businessName: string | undefined,\n websiteUrl: string,\n emailAddress: string,\n searchQuery: string,\n leadId: string,\n): Promise<{ subject: string; body: string } | null> {\n console.log(`Drafting email for ${emailAddress} (lead ${leadId})`);\n const prompt = `\nYou are an AI assistant writing a concise and professional cold outreach email.\nThe email should be slightly charming but direct. Avoid generic phrases like \"Dear Sir or Madam\".\nThe goal is to initiate contact for potential business related to: \"${searchQuery}\".\n\nBusiness Information:\n${businessName ? `Name: ${businessName}` : \"\"}\nWebsite: ${websiteUrl}\nRecipient Email: ${emailAddress}\n\nDraft a subject line and a short email body (max 3-4 sentences).\nPersonalize it slightly based on the business and the search query.\nIf the business name is generic (like \"Home\"), try to infer the business type from the website URL or search query if possible for better personalization, but don't invent information.\nFocus on brevity and a clear call to action (e.g., a brief chat).\n\nExample Subject: Quick Question re: [Business Name/Type] & [Relevant Aspect from Search Query]\nExample Body Start:\nHi [Try to infer a generic salutation if no name, e.g., \"Hi team at [Business Name]\"],\n\nI came across your website while looking for [search query relevance]. We specialize in [Your Vague Specialization - e.g., \"helping businesses like yours improve X\"] and I noticed [Something specific if possible, otherwise a general observation].\n\nWould you be open to a brief 5-10 minute chat next week to see if there's a potential fit?\n\nBest,\n[Your Name/Company - use placeholder like \"A Concerned Professional\" for now]\n`;\n\n try {\n const chatCompletion = await openai.chat.completions.create({\n model: \"gpt-3.5-turbo\",\n messages: [{ role: \"user\", content: prompt }],\n max_tokens: 250,\n temperature: 0.7,\n });\n\n const responseText = chatCompletion.choices[0]?.message?.content?.trim();\n if (!responseText) {\n await updateLeadStatus(leadId, \"error_drafting_empty_response\", {}, \"OpenAI returned empty response\");\n return null;\n }\n\n // Attempt to parse Subject and Body (assuming a simple format)\n let subject = `Regarding ${businessName || websiteUrl}`; // Default subject\n let body = responseText;\n\n const subjectMatch = responseText.match(/Subject:(.*?)(\\n|$)/i);\n if (subjectMatch && subjectMatch[1]) {\n subject = subjectMatch[1].trim();\n body = responseText.substring(subjectMatch[0].length).trim();\n } else {\n // If no explicit \"Subject:\", take the first line as subject if it's short\n const lines = responseText.split(\"\\n\");\n if (lines.length > 1 && lines[0].length < 80 && !lines[0].includes(\"Hi\")) {\n subject = lines[0].trim();\n body = lines.slice(1).join(\"\\n\").trim();\n }\n }\n\n // Clean up common AI artifacts if any\n body = body.replace(/^Body:\\s*/i, \"\").trim();\n\n console.log(`Email drafted for ${emailAddress} (lead ${leadId})`);\n await updateLeadStatus(leadId, \"email_drafted\", { email_subject: subject, drafted_email_body: body });\n return { subject, body };\n } catch (error) {\n console.error(`Error drafting email for ${emailAddress} (lead ${leadId}):`, error);\n await updateLeadStatus(leadId, \"error_drafting\", {}, `OpenAI API error: ${error.message}`);\n return null;\n }\n}\n\nasync function processJob(jobId: string, searchQuery: string) {\n await updateJobStatus(jobId, \"processing_search\");\n const openaiApiKey = Deno.env.get(\"openai\");\n if (!openaiApiKey) {\n console.error(\"OpenAI API key secret 'openai' is not set.\");\n await updateJobStatus(jobId, \"failed_config\", \"OpenAI API key not configured.\");\n return;\n }\n const openai = new OpenAI({ apiKey: openaiApiKey });\n\n const websites = await searchWebsites(searchQuery, jobId);\n if (websites.length === 0) {\n await updateJobStatus(jobId, \"completed_no_sites\", \"No websites found or search failed.\");\n return;\n }\n await updateJobStatus(jobId, \"processing_leads\");\n\n for (const site of websites) {\n const leadId = crypto.randomUUID();\n const now = new Date().toISOString();\n await sqlite.execute({\n sql: `INSERT INTO leads (id, job_id, business_name, website_url, status, created_at, updated_at)\n VALUES (?, ?, ?, ?, ?, ?, ?);`,\n args: [leadId, jobId, site.name, site.url, \"pending_scrape\", now, now],\n });\n\n const emailAddress = await extractEmailsFromWebsite(site.url, leadId);\n if (emailAddress) {\n await draftColdEmail(openai, site.name, site.url, emailAddress, searchQuery, leadId);\n }\n }\n await updateJobStatus(jobId, \"completed\");\n}\n\n// --- UI Components (Hono HTML templating) ---\ntype Job = {\n id: string;\n search_query: string;\n status: string;\n created_at: string;\n updated_at: string;\n error_message?: string;\n};\ntype Lead = {\n id: string;\n job_id: string;\n business_name?: string;\n website_url: string;\n email_address?: string;\n email_subject?: string;\n drafted_email_body?: string;\n status: string;\n error_message?: string;\n created_at: string;\n updated_at: string;\n};\n\nconst Layout = (props: { children?: any; title?: string }) =>\n html`\n \n \n ${props.title || \"Lead Gen Agent\"}\n \n \n \n \n \n

Lead Generation Agent 🕵️‍♂️

\n ${props.children}\n

View source for this val: ${\n import.meta.url.replace(\"https://\", \"\").replace(\".esm.town\", \".val.town\")\n }

Error: ${job.error_message}

`\n : \"\"\n }\n`;\n\nconst LeadRow = (lead: Lead) =>\n html`\n

\n ${lead.business_name || lead.website_url} - \n ${lead.status}\n ${lead.email_address ? ` - ${lead.email_address}` : \"\"}\n

Lead ID: ${lead.id.substring(0, 8)}...

Website: ${lead.website_url}

\n ${lead.email_address ? html`

Email: ${lead.email_address}

` : \"\"}\n ${lead.email_subject ? html`

Drafted Subject: ${lead.email_subject}

` : \"\"}\n ${lead.drafted_email_body ? html`

Drafted Body:

${lead.drafted_email_body}

` : \"\"}\n

Status: ${lead.status}

\n ${lead.error_message ? html`

Error: ${lead.error_message}

` : \"\"}\n

Last Updated: ${new Date(lead.updated_at).toLocaleString()}

\n`;\n\n// --- Hono Routes ---\napp.get(\"/\", async (c) => {\n const jobIdParam = c.req.query(\"job_id\");\n let jobs: Job[] = [];\n let leads: Lead[] = [];\n let selectedJob: Job | null = null;\n let metrics = { total: 0, emailFound: 0, emailDrafted: 0, errors: 0 };\n\n try {\n const jobResults = await sqlite.execute(\n \"SELECT id, search_query, status, created_at, updated_at, error_message FROM jobs ORDER BY created_at DESC;\",\n );\n jobs = jobResults.rows as Job[];\n\n if (jobIdParam) {\n const selectedJobResult = await sqlite.execute({\n sql: \"SELECT id, search_query, status, created_at, updated_at, error_message FROM jobs WHERE id = ?;\",\n args: [jobIdParam],\n });\n selectedJob = selectedJobResult.rows[0] as Job || null;\n\n const leadResults = await sqlite.execute({\n sql:\n \"SELECT id, job_id, business_name, website_url, email_address, email_subject, drafted_email_body, status, error_message, created_at, updated_at FROM leads WHERE job_id = ? ORDER BY created_at ASC;\",\n args: [jobIdParam],\n });\n leads = leadResults.rows as Lead[];\n\n metrics.total = leads.length;\n metrics.emailFound = leads.filter(l => l.email_address).length;\n metrics.emailDrafted = leads.filter(l => l.drafted_email_body).length;\n metrics.errors = leads.filter(l => l.status.startsWith(\"error_\") || l.error_message).length;\n }\n } catch (e) {\n console.error(\"Error fetching data for UI:\", e);\n return c.html(Layout({ children: html`

Error loading data: ${e.message}

` }));\n }\n\n return c.html(\n Layout({\n children: html`\n

Start New Lead Generation Job

\n \n\n ${\n jobIdParam && selectedJob\n ? html`\n

Details for Job: ${selectedJob.search_query} (${selectedJob.id.substring(0, 8)}...)

Status: ${selectedJob.status}

\n ${selectedJob.error_message ? html`

Job Error: ${selectedJob.error_message}

` : \"\"}\n

Leads Processed: ${metrics.total}

Emails Found: ${metrics.emailFound}

Emails Drafted: ${metrics.emailDrafted}

Leads with Errors: ${metrics.errors}

Leads:

\n ${\n leads.length > 0\n ? leads.map(LeadRow)\n : html`

No leads processed yet for this job, or job is in progress.

`\n }\n `\n : \"\"\n }\n \n

All Jobs

\n ${\n jobs.length > 0\n ? html`\n \n \n \n \n \n \n \n \n \n \n \n \n ${jobs.map(JobRow)}\n \n

ID	Query	Status	Created	Updated	Actions

\n `\n : html`

No jobs found. Start one above!

`\n }\n `,\n }),\n );\n});\n\napp.post(\n \"/start-job\",\n validator(\"form\", (value, c) => {\n const searchQuery = value[\"searchQuery\"];\n if (!searchQuery || typeof searchQuery !== \"string\" || searchQuery.trim().length === 0) {\n return c.text(\"Search query is required\", 400);\n }\n return { searchQuery: searchQuery.trim() };\n }),\n async (c) => {\n const { searchQuery } = c.req.valid(\"form\");\n const jobId = crypto.randomUUID();\n const now = new Date().toISOString();\n\n try {\n await sqlite.execute({\n sql: `INSERT INTO jobs (id, search_query, status, created_at, updated_at) VALUES (?, ?, ?, ?, ?);`,\n args: [jobId, searchQuery, \"pending\", now, now],\n });\n\n // Intentionally not awaiting processJob here so the HTTP request returns quickly.\n // The job will run in the background.\n processJob(jobId, searchQuery).catch(err => {\n console.error(`Unhandled error in background job ${jobId}:`, err);\n updateJobStatus(jobId, \"failed_uncaught_exception\", err.message).catch(console.error);\n });\n } catch (e) {\n console.error(\"Error starting job:\", e);\n // This error won't be shown on redirect, but good for logging\n return c.html(\n Layout({\n children: html`

Error starting job: ${e.message}. Go back

`,\n }),\n );\n }\n\n // Redirect to the page showing details for the new job\n return new Response(null, {\n status: 302,\n headers: { Location: `/?job_id=${jobId}` },\n });\n },\n);\n\nexport default async function(req: Request) {\n try {\n // Ensure OpenAI secret is checked early if needed for all paths, or handle it per-path.\n // For this app, it's mainly needed by `processJob`.\n } catch (e) {\n return new Response(`Configuration error: ${e.message}`, { status: 500 });\n }\n return serve(app)(req);\n}",4,["D",1747009085650],{"_103":198,"_147":135,"_145":115,"_95":99,"_154":199,"_152":153,"_100":200,"_146":-5,"_105":201,"_148":195,"_157":-5},"80905224-2ec6-11f0-9f49-569c3dd06744","export default async function (req: Request): Promise {\n return Response.json({ ok: true })\n}",3,["D",1747009054370],{"_103":203,"_147":135,"_145":115,"_95":99,"_154":68,"_152":153,"_100":204,"_146":-5,"_105":205,"_148":200,"_157":-5},"807d4d5a-2ec6-11f0-b197-569c3dd06744",2,["D",1747009054247],{"_103":207,"_147":135,"_145":115,"_95":99,"_154":68,"_152":208,"_100":167,"_146":-5,"_105":209,"_148":204,"_157":-5},"7e50656c-2ec6-11f0-a95e-569c3dd06744","script",["D",1747009050597],{"_103":211,"_147":135,"_145":115,"_95":212,"_154":68,"_152":208,"_100":31,"_146":-5,"_105":213,"_148":167,"_157":-5},"78253ffa-2ec6-11f0-a95e-569c3dd06744","new-file-6720.tsx",["D",1747009040251],"versions",[216,218,219,220,221,222],{"_172":190,"_217":192},"previous",{"_172":192,"_217":197},{"_172":197,"_217":202},{"_172":202,"_217":206},{"_172":206,"_217":210},{"_172":210,"_217":-5},"versionNumber","page","hasNext","routes/_app","actionData","errors"]

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