\n Person Enrichment API\n

\n Enter information about a person to get enriched data. At least one\n field is required.\n

\n\n \n\n

\n API Information:\n

• At least one field must be filled out
• The API will search for information about the person
\n • Results include professional background, current role, and more\n
• Response format: JSON with structured data

\n \n\n",[],[192],{"_104":199,"_95":200,"_154":201,"_156":-5,"_157":138,"_158":202,"_160":161,"_106":203,"_101":185,"_163":204,"_165":205,"_167":22,"_168":-5,"_169":206,"_99":207},"890ea028-4077-11f0-a89b-76b3cceeab13","index.ts","e1ed7e80-2302-4bba-9d77-2bd5a33dfe98",7,["D",1748954259309],"http","import OpenAI from \"https://esm.sh/openai@4.28.0\";\nimport { serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n\ninterface PersonEnrichmentRequest {\n email?: string;\n name?: string;\n company?: string;\n linkedin?: string;\n twitter?: string;\n website?: string;\n}\n\ninterface PersonEnrichmentResponse {\n success: boolean;\n data?: {\n summary: string;\n professional_background: string;\n current_role: string;\n company_info: string;\n recent_activities: string;\n social_presence: string;\n achievements: string;\n sources: string[];\n };\n error?: string;\n}\n\nexport default async function (req: Request): Promise {\n // Only allow POST requests with form data\n if (req.method !== \"POST\") {\n return serveFile(\"/index.html\", import.meta.url);\n }\n\n try {\n // Parse form data\n const formData = await req.formData();\n\n // Extract form fields\n const body: PersonEnrichmentRequest = {\n email: formData.get(\"email\")?.toString() || undefined,\n name: formData.get(\"name\")?.toString() || undefined,\n company: formData.get(\"company\")?.toString() || undefined,\n linkedin: formData.get(\"linkedin\")?.toString() || undefined,\n twitter: formData.get(\"twitter\")?.toString() || undefined,\n website: formData.get(\"website\")?.toString() || undefined,\n };\n\n // Validate that at least one identifier is provided\n if (\n !body.email &&\n !body.name &&\n !body.linkedin &&\n !body.twitter &&\n !body.website\n ) {\n return new Response(\n JSON.stringify({\n success: false,\n error:\n \"At least one identifier is required (email, name, linkedin, twitter, or website)\",\n }),\n {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n }\n );\n }\n\n // Build search query based on available information\n let searchQuery = \"Research and find information about this person: \";\n const identifiers: string[] = [];\n\n if (body.name) identifiers.push(`Name: ${body.name}`);\n if (body.email) identifiers.push(`Email: ${body.email}`);\n if (body.company) identifiers.push(`Company: ${body.company}`);\n if (body.linkedin) identifiers.push(`LinkedIn: ${body.linkedin}`);\n if (body.twitter) identifiers.push(`Twitter: ${body.twitter}`);\n if (body.website) identifiers.push(`Website: ${body.website}`);\n\n searchQuery += identifiers.join(\", \");\n\n searchQuery += `\n\nPlease provide a comprehensive research report with the following sections:\n1. SUMMARY: A brief overview of who this person is\n2. PROFESSIONAL_BACKGROUND: Their career history, education, and expertise\n3. CURRENT_ROLE: Their current position and responsibilities\n4. COMPANY_INFO: Information about their current or most recent company\n5. RECENT_ACTIVITIES: Recent news, projects, or public activities\n6. SOCIAL_PRESENCE: Their online presence and thought leadership\n7. ACHIEVEMENTS: Notable accomplishments, awards, or recognition\n8. SOURCES: List the main sources you found this information from\n\nFormat your response as a structured report. If you cannot find information for any section, please indicate \"No information found\" for that section.`;\n\n // Initialize OpenAI client\n const client = new OpenAI({\n apiKey: Deno.env.get(\"OPENAI_API_KEY\"),\n });\n\n // Make the search request\n const completion = await client.chat.completions.create({\n model: \"gpt-4o-search-preview\",\n web_search_options: {},\n messages: [\n {\n role: \"user\",\n content: searchQuery,\n },\n ],\n max_tokens: 2000,\n });\n\n const content = completion.choices[0].message.content;\n\n if (!content) {\n throw new Error(\"No content returned from OpenAI\");\n }\n\n // Parse the structured response\n const sections = {\n summary: extractSection(content, \"SUMMARY\"),\n professional_background: extractSection(\n content,\n \"PROFESSIONAL_BACKGROUND\"\n ),\n current_role: extractSection(content, \"CURRENT_ROLE\"),\n company_info: extractSection(content, \"COMPANY_INFO\"),\n recent_activities: extractSection(content, \"RECENT_ACTIVITIES\"),\n social_presence: extractSection(content, \"SOCIAL_PRESENCE\"),\n achievements: extractSection(content, \"ACHIEVEMENTS\"),\n sources: extractSources(content),\n };\n\n const response: PersonEnrichmentResponse = {\n success: true,\n data: sections,\n };\n\n return new Response(JSON.stringify(response, null, 2), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (error) {\n console.error(\"Error in person enrichment:\", error);\n\n const response: PersonEnrichmentResponse = {\n success: false,\n error: error instanceof Error ? error.message : \"Unknown error occurred\",\n };\n\n return new Response(JSON.stringify(response), {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n}\n\n// Helper function to extract sections from the response\nfunction extractSection(content: string, sectionName: string): string {\n const regex = new RegExp(\n `${sectionName}:?\\\\s*([\\\\s\\\\S]*?)(?=\\\\n\\\\d+\\\\.|\\\\n[A-Z_]+:|$)`,\n \"i\"\n );\n const match = content.match(regex);\n return match ? match[1].trim() : \"No information found\";\n}\n\n// Helper function to extract sources\nfunction extractSources(content: string): string[] {\n const sourcesSection = extractSection(content, \"SOURCES\");\n if (sourcesSection === \"No information found\") {\n return [];\n }\n\n // Try to extract URLs or source names from the sources section\n const urlRegex = /https?:\\/\\/[^\\s]+/g;\n const urls = sourcesSection.match(urlRegex) || [];\n\n // Also try to extract bullet points or numbered items\n const lines = sourcesSection\n .split(\"\\n\")\n .map((line) => line.trim())\n .filter(\n (line) => line.length > 0 && !urls.some((url) => line.includes(url))\n );\n\n return [...urls, ...lines].slice(0, 10); // Limit to 10 sources\n}\n",[],[200],"files",[152,172,181,190,198],"counts",{"_212":32,"_213":185,"_214":32,"_215":176},"pulls","branches","forks","envVars","contents",[],{"_104":153,"_95":100,"_154":155,"_156":-5,"_157":138,"_158":159,"_160":161,"_106":219,"_101":32,"_163":164,"_165":166,"_167":22,"_168":-5,"_99":220},["D",1748954160506],[100],"upstreamProject","upstreamBranch",{"_104":141,"_106":224,"_225":226,"_95":43,"_139":105,"_101":227,"_140":-5,"_142":-5,"_228":229,"_108":-5,"_149":22,"_110":111,"_148":94,"_16":119,"_147":96},["D",1748885079132],"updatedAt",["D",1750961183784],69,"lockfileKey","1753381290500-esm.town_v_stevekrouse_openai_enrichment@69-main","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.history_.$",{"_93":94,"_95":96,"_97":98,"_99":100,"_102":236,"_164":241,"_244":245,"_248":249,"_252":-7,"_253":32,"_254":22},{"_104":105,"_95":96,"_106":237,"_108":-5,"_109":22,"_110":111,"_112":-5,"_113":-5,"_14":114,"_115":-5,"_116":22,"_117":-5,"_118":32,"_16":119,"_120":121,"_122":121,"_123":124,"_125":124,"_126":124,"_127":121,"_128":121,"_23":238,"_132":239,"_135":240,"_149":22},["D",1748885079132],{"_93":94,"_130":131},{"_93":94,"_134":131},{"_101":137,"_95":98,"_104":138,"_139":105,"_140":141,"_142":143,"_144":111,"_145":105,"_146":119,"_147":96,"_148":94},{"_104":153,"_95":100,"_154":155,"_156":-5,"_157":138,"_158":159,"_160":161,"_106":242,"_101":32,"_163":164,"_165":166,"_167":22,"_168":-5,"_99":243},["D",1748954160506],[100],"history",[246],{"_104":153,"_157":138,"_154":155,"_95":100,"_165":166,"_163":164,"_101":32,"_156":-5,"_106":247,"_158":159,"_168":-5},["D",1748954160506],"versions",[250],{"_164":246,"_251":-5},"previous","versionNumber","page","hasNext","actionData","errors"]

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