\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",[],[190],{"_104":197,"_95":198,"_153":199,"_155":-5,"_156":138,"_157":200,"_159":22,"_106":201,"_100":202,"_162":203,"_164":204,"_166":22,"_167":-5,"_168":205,"_98":206},"249fa114-407c-11f0-b612-76b3cceeab13","index.ts","c0a85930-3fd6-11f0-aa5d-76b3cceeab13",62,["D",1748956238288],14,"http","import OpenAI from \"npm:openai\";\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\nexport interface 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 body.\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_]+:|$)`,\n \"i\",\n );\n const match = content.match(regex);\n return match ? match[1].trim() : \"No information found\";\n}\n\n// Helper function to extract sources\nfunction extractSources(content: string): string[] {\n const sourcesSection = extractSection(content, \"SOURCES\");\n if (sourcesSection === \"No information found\") {\n return [];\n }\n\n // Try to extract URLs or source names from the sources section\n const urlRegex = /https?:\\/\\/[^\\s]+/g;\n const urls = sourcesSection.match(urlRegex) || [];\n\n // Also try to extract bullet points or numbered items\n const lines = sourcesSection\n .split(\"\\n\")\n .map((line) => line.trim())\n .filter(\n (line) => line.length > 0 && !urls.some((url) => line.includes(url)),\n );\n\n return [...urls, ...lines].slice(0, 10); // Limit to 10 sources\n}",[],[198],{"_104":208,"_95":209,"_153":210,"_155":-5,"_156":138,"_157":101,"_159":22,"_106":211,"_100":32,"_162":212,"_164":72,"_166":22,"_167":-5,"_168":213,"_98":214},"85818b0a-407c-11f0-8e52-76b3cceeab13","new-file-8011.tsx","85818bd2-407c-11f0-8e52-76b3cceeab13",["D",1748956400841],"script",[],[209],"files",[150,171,181,188,196,207],"counts",{"_219":32,"_220":221,"_222":32,"_223":224},"pulls","branches",2,"forks","envVars",1,"contents",[],{"_104":182,"_95":99,"_153":183,"_155":-5,"_156":138,"_157":158,"_159":160,"_106":228,"_100":32,"_162":163,"_164":185,"_166":22,"_167":-5,"_98":229},["D",1748954370696],[99],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.version.$version.code.$",{"_93":94,"_95":96,"_97":43,"_100":101,"_98":99,"_102":238,"_148":243,"_215":262,"_163":263,"_225":265,"_266":-5,"_267":22,"_268":-5,"_269":-5,"_270":-5,"_271":272},{"_104":105,"_95":96,"_106":239,"_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":240,"_132":241,"_135":242,"_147":22},["D",1748885079132],{"_93":94,"_130":131},{"_93":94,"_134":131},{"_100":137,"_95":43,"_104":138,"_139":105,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":-5,"_145":96,"_146":94},[244,247,250,253,256,259],{"_104":151,"_95":152,"_153":154,"_155":-5,"_156":138,"_157":158,"_159":160,"_106":161,"_100":32,"_162":163,"_164":165,"_166":22,"_167":-5,"_168":245,"_98":246},[],[152],{"_104":172,"_95":173,"_153":174,"_155":-5,"_156":138,"_157":175,"_159":160,"_106":176,"_100":177,"_162":163,"_164":178,"_166":22,"_167":-5,"_168":248,"_98":249},[],[173],{"_104":182,"_95":99,"_153":183,"_155":-5,"_156":138,"_157":158,"_159":160,"_106":184,"_100":32,"_162":163,"_164":185,"_166":22,"_167":-5,"_168":251,"_98":252},[],[99],{"_104":189,"_95":190,"_153":191,"_155":-5,"_156":138,"_157":158,"_159":160,"_106":192,"_100":32,"_162":163,"_164":193,"_166":22,"_167":-5,"_168":254,"_98":255},[],[190],{"_104":197,"_95":198,"_153":199,"_155":-5,"_156":138,"_157":200,"_159":22,"_106":201,"_100":202,"_162":203,"_164":204,"_166":22,"_167":-5,"_168":257,"_98":258},[],[198],{"_104":208,"_95":209,"_153":210,"_155":-5,"_156":138,"_157":101,"_159":22,"_106":211,"_100":32,"_162":212,"_164":72,"_166":22,"_167":-5,"_168":260,"_98":261},[],[209],[244,247,250,253,256,259],{"_104":182,"_95":99,"_153":183,"_155":-5,"_156":138,"_157":158,"_159":160,"_106":228,"_100":32,"_162":163,"_164":185,"_166":22,"_167":-5,"_98":264},[99],[],"upstream","showCompareCallout","pull","ahead","behind","templates",[],"actionData","errors"]