[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_284":285,"_286":287},"routes/_app.x.$handle.$name",{"_97":96,"_33":47,"_105":87,"_28":106,"_13":14,"_107":-5,"_11":108,"_109":110,"_111":112,"_113":114,"_115":116,"_20":-5,"_117":-5,"_118":-5,"_119":27,"_120":121,"_122":25,"_123":-5,"_124":-5,"_125":126},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_45":46,"_33":47,"_40":48,"_49":-5,"_50":27,"_51":52,"_53":52,"_54":-5,"_55":-5,"_18":56,"_57":58,"_59":25,"_60":25,"_61":-5,"_62":63,"_64":65,"_66":-5,"_67":-5,"_68":-5,"_69":-5,"_70":71,"_72":71,"_73":74,"_75":74,"_76":74,"_77":71,"_78":71,"_79":80,"_81":82,"_83":84,"_85":27},"version",42,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":27,"_28":29,"_30":29},"file",{"_31":32,"_33":34,"_35":36,"_37":39,"_40":41,"_42":14,"_43":44,"_24":27},"previous",{"_31":32,"_33":34,"_35":36,"_37":38},"deleted",true,"deletedHere",false,"path","backend/index.ts","latestPath","fileId","96698790-3fe8-11f0-b872-76b3cceeab13","name","index.ts","fileType","http","content","import { Hono } from \"https://esm.sh/hono@3.12.6\";\nimport { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\nimport OpenAI from \"npm:openai\";\nimport { PersonEnrichmentRequest, PersonEnrichmentResponse } from \"./types/enrichment.ts\";\nimport { extractSection, extractSources } from \"./utils/response.ts\";\n\nconst app = new Hono();\n\n// Serve static files\napp.get(\"/frontend/*\", (c) => serveFile(c.req.path, import.meta.url));\napp.get(\"/app.js\", (c) => serveFile(\"/frontend/app.ts\", import.meta.url));\n\n// Serve main HTML\napp.get(\"/\", async (c) => {\n console.log(\"hi\")\n const html = await readFile(\"/frontend/index.html\", import.meta.url);\n return c.html(html);\n});\n\n// API endpoint\napp.post(\"/api/enrich\", async (c) => {\n const apiKey = c.req.header(\"X-OpenAI-API-Key\");\n if (!apiKey) {\n return c.json(\n {\n success: false,\n error: \"OpenAI API key is required\",\n },\n 401,\n );\n }\n\n try {\n const body: PersonEnrichmentRequest = await c.req.json();\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 c.json(\n {\n success: false,\n error: \"At least one identifier is required (email, name, linkedin, twitter, or website)\",\n },\n 400,\n );\n }\n\n // Build search query based on available information\n let searchQuery = \"Research and find information about this person: \";\n const identifiers = [];\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: apiKey,\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 c.json(response);\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 c.json(response, 500);\n }\n});\n\n// Error handling\napp.onError((err, c) => {\n throw err;\n});\n\nexport default app.fetch;","import { Hono } from \"https://esm.sh/hono@3.12.6\";\nimport { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\nimport OpenAI from \"npm:openai\";\nimport { PersonEnrichmentRequest, PersonEnrichmentResponse } from \"./types/enrichment.ts\";\nimport { extractSection, extractSources } from \"./utils/response.ts\";\n\nconst app = new Hono();\n\n// Serve static files\napp.get(\"/frontend/*\", (c) => serveFile(c.req.path, import.meta.url));\napp.get(\"/app.js\", (c) => serveFile(\"/frontend/app.ts\", import.meta.url));\n\n// Serve main HTML\napp.get(\"/\", serveFile(\"/frontend/index.html\", import.meta.url));\n\n// API endpoint\napp.post(\"/api/enrich\", async (c) => {\n const apiKey = c.req.header(\"X-OpenAI-API-Key\");\n if (!apiKey) {\n return c.json(\n {\n success: false,\n error: \"OpenAI API key is required\",\n },\n 401,\n );\n }\n\n try {\n const body: PersonEnrichmentRequest = await c.req.json();\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 c.json(\n {\n success: false,\n error: \"At least one identifier is required (email, name, linkedin, twitter, or website)\",\n },\n 400,\n );\n }\n\n // Build search query based on available information\n let searchQuery = \"Research and find information about this person: \";\n const identifiers = [];\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: apiKey,\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 c.json(response);\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 c.json(response, 500);\n }\n});\n\n// Error handling\napp.onError((err, c) => {\n throw err;\n});\n\nexport default app.fetch;","createdAt",["D",1748893110193],"branchVersion","branchId","76743230-3fd6-11f0-9448-76b3cceeab13","id","7673e1a4-3fd6-11f0-9448-76b3cceeab13","openai_enrichment",["D",1748885079132],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","imageUrl","a0bf3b31-15a5-4d5c-880e-4b1e22c9bc18","pinnedFileId","c0a85930-3fd6-11f0-aa5d-76b3cceeab13","pinPreview","pinMigrated","screenshotVersion","likeCount",0,"orgId","e81e7335-6d4c-4764-a902-d0962bbfa9f7","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_97":96,"_104":100},"org",{"_97":96,"_98":-5,"_99":100,"_18":56,"_101":102,"_103":27},"branch",{"_13":86,"_33":87,"_45":44,"_88":46,"_89":-5,"_90":-5,"_91":-5,"_92":-5,"_93":-5,"_94":47,"_95":96},"isOwned",69,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","stevekrouse","handle","displayName","avatar","https://images.clerk.dev/uploaded/img_2PqHa2Gsy93xQrjh2w78Xu0cChW.jpeg","tier","pro","canRestrictVals","profileImageUrl","branchName","","adoptOrgId",{"_45":46,"_33":47,"_40":280,"_49":-5,"_50":27,"_51":52,"_53":52,"_54":-5,"_55":-5,"_18":56,"_57":58,"_59":25,"_60":25,"_61":-5,"_62":63,"_64":65,"_66":-5,"_67":-5,"_68":-5,"_69":-5,"_70":71,"_72":71,"_73":74,"_75":74,"_76":74,"_77":71,"_78":71,"_79":281,"_81":282,"_83":283,"_85":27},"tree",[187,189,195,198,199,200],"files",[187,188,189,190,191,192,193,194,195,196,197,198,199,200],"counts",{"_175":63,"_176":177,"_178":63,"_179":180,"_181":182},"contents",[127,128,129,130,131,132],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_45":169,"_33":170,"_31":171,"_134":-5,"_43":44,"_42":172,"_136":27,"_40":173,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_28":174},{"_45":163,"_33":164,"_31":165,"_134":-5,"_43":44,"_42":166,"_136":27,"_40":167,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_28":168},{"_45":156,"_33":157,"_31":158,"_134":-5,"_43":44,"_42":159,"_136":27,"_40":160,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_28":162},{"_45":149,"_33":150,"_31":151,"_134":-5,"_43":44,"_42":152,"_136":27,"_40":153,"_13":63,"_35":20,"_37":154,"_24":27,"_140":-5,"_28":155},{"_45":142,"_33":143,"_31":144,"_134":-5,"_43":44,"_42":145,"_136":27,"_40":146,"_13":63,"_35":20,"_37":147,"_24":27,"_140":-5,"_28":148},{"_45":133,"_33":34,"_31":58,"_134":-5,"_43":44,"_42":135,"_136":27,"_40":137,"_13":138,"_35":36,"_37":139,"_24":27,"_140":-5,"_28":141},"e4f1a8da-3fe7-11f0-a63a-76b3cceeab13","parentId",25,"latest",["D",1748892565941],9,"import OpenAI from \"npm:openai\";\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\n if (req.method !== 'POST') {\n return new Response(JSON.stringify({ \n success: false, \n error: 'Method not allowed. Use POST.' \n }), {\n status: 405,\n headers: { 'Content-Type': 'application/json' }\n });\n }\n\n try {\n // Parse request body\n const body: PersonEnrichmentRequest = await req.json();\n \n // Validate that at least one identifier is provided\n if (!body.email && !body.name && !body.linkedin && !body.twitter && !body.website) {\n return new Response(JSON.stringify({\n success: false,\n error: 'At least one identifier is required (email, name, linkedin, twitter, or website)'\n }), {\n status: 400,\n headers: { 'Content-Type': 'application/json' }\n });\n }\n\n // Build search query based on available information\n let searchQuery = \"Research and find information about this person: \";\n const identifiers = [];\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 role: \"user\",\n content: searchQuery\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(content, 'PROFESSIONAL_BACKGROUND'),\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\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(`${sectionName}:?\\\\s*([\\\\s\\\\S]*?)(?=\\\\n\\\\d+\\\\.|\\\\n[A-Z_]+:|$)`, 'i');\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.split('\\n')\n .map(line => line.trim())\n .filter(line => line.length > 0 && !urls.some(url => line.includes(url)));\n \n return [...urls, ...lines].slice(0, 10); // Limit to 10 sources\n}","label",[34],"cd71383a-3fd6-11f0-90af-76b3cceeab13","README.md","cd71390c-3fd6-11f0-90af-76b3cceeab13",3,["D",1748885225071],"# Person Enrichment API\n\nAn HTTP endpoint that enriches person data using OpenAI's web search capabilities. Provide basic information about a person (email, name, etc.) and get back comprehensive research about them.\n\n## Setup\n\n1. Set your OpenAI API key as an environment variable: `OPENAI_API_KEY`\n2. The API uses the `gpt-4o-search-preview` model with web search capabilities\n\n## Usage\n\n### Endpoint\n- **Method**: POST\n- **Content-Type**: application/json\n\n### Request Body\n\n```json\n{\n \"email\": \"person@example.com\",\n \"name\": \"John Doe\",\n \"company\": \"Example Corp\",\n \"linkedin\": \"https://linkedin.com/in/johndoe\",\n \"twitter\": \"https://twitter.com/johndoe\",\n \"website\": \"https://johndoe.com\"\n}\n```\n\n**Note**: At least one field is required. You can provide any combination of the above fields.\n\n### Response\n\n#### Success Response (200)\n```json\n{\n \"success\": true,\n \"data\": {\n \"summary\": \"Brief overview of the person\",\n \"professional_background\": \"Career history and education\",\n \"current_role\": \"Current position and responsibilities\",\n \"company_info\": \"Information about their company\",\n \"recent_activities\": \"Recent news and projects\",\n \"social_presence\": \"Online presence and thought leadership\",\n \"achievements\": \"Notable accomplishments\",\n \"sources\": [\"https://example.com\", \"LinkedIn profile\", \"...\"]\n }\n}\n```\n\n#### Error Response (400/500)\n```json\n{\n \"success\": false,\n \"error\": \"Error description\"\n}\n```\n\n## Example Usage\n\n### cURL\n```bash\ncurl -X POST https://your-val-url.web.val.run \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"email\": \"elon@tesla.com\",\n \"name\": \"Elon Musk\"\n }'\n```\n\n### JavaScript\n```javascript\nconst response = await fetch('https://your-val-url.web.val.run', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json'\n },\n body: JSON.stringify({\n email: 'person@example.com',\n name: 'John Doe'\n })\n});\n\nconst data = await response.json();\nconsole.log(data);\n```\n\n## Features\n\n- **Web Search Integration**: Uses OpenAI's latest web search capabilities\n- **Comprehensive Research**: Provides structured information across multiple categories\n- **Flexible Input**: Accepts various identifiers (email, name, social profiles, etc.)\n- **Source Attribution**: Returns sources where information was found\n- **Error Handling**: Graceful error handling with descriptive messages\n\n## Privacy & Ethics\n\nThis tool is designed for legitimate business purposes such as:\n- Sales prospecting and lead qualification\n- Partnership research\n- Due diligence for business relationships\n- Professional networking\n\nPlease ensure you comply with:\n- GDPR and other privacy regulations\n- Your organization's data handling policies\n- Ethical guidelines for data collection and use\n- Terms of service of the platforms being researched\n\n## Rate Limits\n\nThe API is subject to OpenAI's rate limits for the `gpt-4o-search-preview` model. Consider implementing your own rate limiting if needed for production use.",[143],"9641179c-3fe8-11f0-b533-76b3cceeab13",".cursorrules","9641185a-3fe8-11f0-b533-76b3cceeab13",34,["D",1748892863423],"You are an advanced assistant specialized in generating Val Town code.\n\n## Core Guidelines\n\n- Ask clarifying questions when requirements are ambiguous\n- Provide complete, functional solutions rather than skeleton implementations\n- Test your logic against edge cases before presenting the final solution\n- Ensure all code follows Val Town's specific platform requirements\n- If a section of code that you're working on is getting too complex, consider refactoring it into subcomponents\n\n## Code Standards\n\n- Generate code in TypeScript or TSX\n- Add appropriate TypeScript types and interfaces for all data structures\n- Prefer official SDKs or libraries than writing API calls directly\n- Ask the user to supply API or library documentation if you are at all unsure about it\n- **Never bake in secrets into the code** - always use environment variables\n- Include comments explaining complex logic (avoid commenting obvious operations)\n- Follow modern ES6+ conventions and functional programming practices if possible\n\n## Types of triggers\n\n### 1. HTTP Trigger\n\n- Create web APIs and endpoints\n- Handle HTTP requests and responses\n- Example structure:\n\n```ts\nexport default async function (req: Request) {\n return new Response(\"Hello World\");\n}\n```\n\nFiles that are HTTP triggers have http in their name like `foobar.http.tsx`\n\n### 2. Cron Triggers\n\n- Run on a schedule\n- Use cron expressions for timing\n- Example structure:\n\n```ts\nexport default async function () {\n // Scheduled task code\n}\n```\n\nFiles that are Cron triggers have cron in their name like `foobar.cron.tsx`\n\n### 3. Email Triggers\n\n- Process incoming emails\n- Handle email-based workflows\n- Example structure:\n\n```ts\nexport default async function (email: Email) {\n // Process email\n}\n```\n\nFiles that are Email triggers have email in their name like `foobar.email.tsx`\n\n\n## Val Town Standard Libraries\n\nVal Town provides several hosted services and utility functions.\n\n### Blob Storage\n\n```ts\nimport { blob } from \"https://esm.town/v/std/blob\";\nawait blob.setJSON(\"myKey\", { hello: \"world\" });\nlet blobDemo = await blob.getJSON(\"myKey\");\nlet appKeys = await blob.list(\"app_\");\nawait blob.delete(\"myKey\");\n```\n\n### SQLite\n\n```ts\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nconst TABLE_NAME = 'todo_app_users_2';\n// Create table - do this before usage and change table name when modifying schema\nawait sqlite.execute(`CREATE TABLE IF NOT EXISTS ${TABLE_NAME} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n name TEXT NOT NULL\n)`);\n// Query data\nconst result = await sqlite.execute(`SELECT * FROM ${TABLE_NAME} WHERE id = ?`, [1]);\n```\n\nNote: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.\n\n### OpenAI\n\n```ts\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nconst openai = new OpenAI();\nconst completion = await openai.chat.completions.create({\n messages: [\n { role: \"user\", content: \"Say hello in a creative way\" },\n ],\n model: \"gpt-4o-mini\",\n max_tokens: 30,\n});\n```\n\n### Email\n\n```ts\nimport { email } from \"https://esm.town/v/std/email\";\n// By default emails the owner of the val\nawait email({ \n subject: \"Hi\", \n text: \"Hi\", \n html: \"

Hi

\"\n});\n```\n\n## Val Town Utility Functions\n\nVal Town provides several utility functions to help with common project tasks.\n\n### Importing Utilities\n\nAlways import utilities with version pins to avoid breaking changes:\n\n```ts\nimport { parseProject, readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n```\n\n### Available Utilities\n\n\n#### **serveFile** - Serve project files with proper content types\n\nFor example, in Hono:\n\n```ts\n// serve all files in frontend/ and shared/\napp.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\napp.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n```\n\n#### **readFile** - Read files from within the project:\n\n```ts\n// Read a file from the project\nconst fileContent = await readFile(\"/frontend/index.html\", import.meta.url);\n```\n\n#### **listFiles** - List all files in the project\n\n```ts\nconst files = await listFiles(import.meta.url);\n```\n\n#### **parseProject** - Extract information about the current project from import.meta.url\n\nThis is useful for including info for linking back to a val, ie in \"view source\" urls:\n\n```ts\nconst projectVal = parseProject(import.meta.url);\nconsole.log(projectVal.username); // Owner of the project\nconsole.log(projectVal.name); // Project name\nconsole.log(projectVal.version); // Version number\nconsole.log(projectVal.branch); // Branch name\nconsole.log(projectVal.links.self.project); // URL to the project page\n```\n\nHowever, it's *extremely importing* to note that `parseProject` and other Standard Library utilities ONLY RUN ON THE SERVER.\nIf you need access to this data on the client, run it in the server and pass it to the client by splicing it into the HTML page\nor by making an API request for it.\n\n## Val Town Platform Specifics\n\n- **Redirects:** Use `return new Response(null, { status: 302, headers: { Location: \"/place/to/redirect\" }})` instead of `Response.redirect` which is broken\n- **Images:** Avoid external images or base64 images. Use emojis, unicode symbols, or icon fonts/libraries instead\n- **AI Image:** To inline generate an AI image use: `

`\n- **Storage:** DO NOT use the Deno KV module for storage\n- **Browser APIs:** DO NOT use the `alert()`, `prompt()`, or `confirm()` methods\n- **Weather Data:** Use open-meteo for weather data (doesn't require API keys) unless otherwise specified\n- **View Source:** Add a view source link by importing & using `import.meta.url.replace(\"ems.sh\", \"val.town)\"` (or passing this data to the client) and include `target=\"_top\"` attribute\n- **Error Debugging:** Add `` to HTML to capture client-side errors\n- **Error Handling:** Only use try...catch when there's a clear local resolution; Avoid catches that merely log or return 500s. Let errors bubble up with full context\n- **Environment Variables:** Use `Deno.env.get('keyname')` when you need to, but generally prefer APIs that don't require keys\n- **Imports:** Use `https://esm.sh` for npm and Deno dependencies to ensure compatibility on server and browser\n- **Storage Strategy:** Only use backend storage if explicitly required; prefer simple static client-side sites\n- **React Configuration:** When using React libraries, pin versions with `?deps=react@18.2.0,react-dom@18.2.0` and start the file with `/** @jsxImportSource https://esm.sh/react@18.2.0 */`\n- Ensure all React dependencies and sub-dependencies are pinned to the same version\n- **Styling:** Default to using TailwindCSS via `` unless otherwise specified\n\n## Project Structure and Design Patterns\n\n### Recommended Directory Structure\n```\n├── backend/\n│ ├── database/\n│ │ ├── migrations.ts # Schema definitions\n│ │ ├── queries.ts # DB query functions\n│ │ └── README.md\n│ └── routes/ # Route modules\n│ ├── [route].ts\n│ └── static.ts # Static file serving\n│ ├── index.ts # Main entry point\n│ └── README.md\n├── frontend/\n│ ├── components/\n│ │ ├── App.tsx\n│ │ └── [Component].tsx\n│ ├── favicon.svg\n│ ├── index.html # Main HTML template\n│ ├── index.tsx # Frontend JS entry point\n│ ├── README.md\n│ └── style.css\n├── README.md\n└── shared/\n ├── README.md\n └── utils.ts # Shared types and functions\n```\n\n### Backend (Hono) Best Practices\n\n- Hono is the recommended API framework\n- Main entry point should be `backend/index.ts`\n- **Static asset serving:** Use the utility functions to read and serve project files:\n ```ts\n import { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n \n // serve all files in frontend/ and shared/\n app.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\n app.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n \n // For index.html, often you'll want to bootstrap with initial data\n app.get(\"/\", async c => {\n let html = await readFile(\"/frontend/index.html\", import.meta.url);\n \n // Inject data to avoid extra round-trips\n const initialData = await fetchInitialData();\n const dataScript = ``;\n \n html = html.replace(\"\", `${dataScript}`);\n return c.html(html);\n });\n ```\n- Create RESTful API routes for CRUD operations\n- Always include this snippet at the top-level Hono app to re-throwing errors to see full stack traces:\n ```ts\n // Unwrap Hono errors to see original error details\n app.onError((err, c) => {\n throw err;\n });\n ```\n\n### Database Patterns\n- Run migrations on startup or comment out for performance\n- Change table names when modifying schemas rather than altering\n- Export clear query functions with proper TypeScript typing\n\n## Common Gotchas and Solutions\n\n1. **Environment Limitations:** \n - Val Town runs on Deno in a serverless context, not Node.js\n - Code in `shared/` must work in both frontend and backend environments\n - Cannot use `Deno` keyword in shared code\n - Use `https://esm.sh` for imports that work in both environments\n\n2. **SQLite Peculiarities:**\n - Limited support for ALTER TABLE operations\n - Create new tables with updated schemas and copy data when needed\n - Always run table creation before querying\n\n3. **React Configuration:**\n - All React dependencies must be pinned to 18.2.0\n - Always include `@jsxImportSource https://esm.sh/react@18.2.0` at the top of React files\n - Rendering issues often come from mismatched React versions\n\n4. **File Handling:**\n - Val Town only supports text files, not binary\n - Use the provided utilities to read files across branches and forks\n - For files in the project, use `readFile` helpers\n\n5. **API Design:**\n - `fetch` handler is the entry point for HTTP vals\n - Run the Hono app with `export default app.fetch // This is the entry point for HTTP vals`\n\n",[150],"95effb00-3fe8-11f0-8724-76b3cceeab13","frontend","95effba0-3fe8-11f0-8724-76b3cceeab13",26,["D",1748892862892],"directory",[157],"95faf8e8-3fe8-11f0-b919-76b3cceeab13","backend","95fafb22-3fe8-11f0-b919-76b3cceeab13",27,["D",1748892862963],[164],"9604d552-3fe8-11f0-b919-76b3cceeab13",".vscode","9604d642-3fe8-11f0-b919-76b3cceeab13",28,["D",1748892863029],[170],"pulls","branches",2,"forks","envVars",{"_183":185,"_186":63},"connections",{"_183":63,"_184":63},"count","unfilledCount",1,"emptyCount",{"_45":169,"_33":170,"_31":171,"_134":-5,"_43":44,"_42":172,"_136":27,"_40":277,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_202":278,"_28":279},{"_45":269,"_33":270,"_31":271,"_134":171,"_43":44,"_42":272,"_136":27,"_40":273,"_13":63,"_35":20,"_37":274,"_24":27,"_140":-5,"_202":275,"_28":276},{"_45":163,"_33":164,"_31":165,"_134":-5,"_43":44,"_42":166,"_136":27,"_40":266,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_202":267,"_28":268},{"_45":261,"_33":260,"_31":254,"_134":165,"_43":44,"_42":262,"_136":27,"_40":263,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_202":264,"_28":265},{"_45":251,"_33":252,"_31":253,"_134":254,"_43":44,"_42":255,"_136":27,"_40":256,"_13":63,"_35":224,"_37":257,"_24":27,"_140":-5,"_202":258,"_28":259},{"_45":246,"_33":245,"_31":239,"_134":165,"_43":44,"_42":247,"_136":27,"_40":248,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_202":249,"_28":250},{"_45":236,"_33":237,"_31":238,"_134":239,"_43":44,"_42":240,"_136":27,"_40":241,"_13":63,"_35":224,"_37":242,"_24":27,"_140":-5,"_202":243,"_28":244},{"_45":231,"_33":34,"_31":32,"_134":165,"_43":44,"_42":14,"_136":27,"_40":232,"_13":233,"_35":36,"_37":39,"_24":27,"_140":-5,"_202":234,"_28":235},{"_45":156,"_33":157,"_31":158,"_134":-5,"_43":44,"_42":159,"_136":27,"_40":228,"_13":63,"_35":161,"_37":-5,"_24":27,"_140":-5,"_202":229,"_28":230},{"_45":219,"_33":220,"_31":221,"_134":158,"_43":44,"_42":222,"_136":27,"_40":223,"_13":63,"_35":224,"_37":225,"_24":27,"_140":-5,"_202":226,"_28":227},{"_45":211,"_33":212,"_31":213,"_134":158,"_43":44,"_42":214,"_136":27,"_40":215,"_13":63,"_35":20,"_37":216,"_24":27,"_140":-5,"_202":217,"_28":218},{"_45":149,"_33":150,"_31":151,"_134":-5,"_43":44,"_42":152,"_136":27,"_40":208,"_13":63,"_35":20,"_37":154,"_24":27,"_140":-5,"_202":209,"_28":210},{"_45":142,"_33":143,"_31":144,"_134":-5,"_43":44,"_42":145,"_136":27,"_40":205,"_13":63,"_35":20,"_37":147,"_24":27,"_140":-5,"_202":206,"_28":207},{"_45":133,"_33":34,"_31":58,"_134":-5,"_43":44,"_42":135,"_136":27,"_40":201,"_13":138,"_35":36,"_37":139,"_24":27,"_140":-5,"_202":203,"_28":204},["D",1748892565941],"children",[],[34],["D",1748885225071],[],[143],["D",1748892863423],[],[150],"9635138e-3fe8-11f0-8ab3-76b3cceeab13","index.html","9635144c-3fe8-11f0-8ab3-76b3cceeab13",31,["D",1748892863346]," ",[],[157,212],"9637ac84-3fe8-11f0-8724-76b3cceeab13","app.ts","9637ad38-3fe8-11f0-8724-76b3cceeab13",32,["D",1748892863351],"script","/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React from \"https://esm.sh/react@18.2.0\";\nimport ReactDOM from \"https://esm.sh/react-dom@18.2.0\";\n\n// Types\ninterface EnrichmentData {\n name?: string;\n email?: string;\n company?: string;\n linkedin?: string;\n twitter?: string;\n website?: string;\n}\n\ninterface EnrichmentResponse {\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\n// API Key Management\nconst API_KEY_STORAGE_KEY = \"openai_api_key\";\n\nfunction getStoredApiKey(): string | null {\n return localStorage.getItem(API_KEY_STORAGE_KEY);\n}\n\nfunction storeApiKey(key: string): void {\n localStorage.setItem(API_KEY_STORAGE_KEY, key);\n}\n\n// DOM Elements\nconst apiKeyInput = document.getElementById(\"apiKey\") as HTMLInputElement;\nconst saveApiKeyButton = document.getElementById(\"saveApiKey\");\nconst apiKeySection = document.getElementById(\"apiKeySection\");\nconst enrichmentForm = document.getElementById(\n \"enrichmentForm\"\n) as HTMLFormElement;\nconst resultsDiv = document.getElementById(\"results\");\nconst resultsContent = document.getElementById(\"resultsContent\");\n\n// Initialize UI\nfunction initializeUI() {\n const storedKey = getStoredApiKey();\n if (storedKey) {\n apiKeyInput.value = storedKey;\n apiKeySection?.classList.add(\"hidden\");\n enrichmentForm?.classList.remove(\"hidden\");\n }\n}\n\n// Event Listeners\nsaveApiKeyButton?.addEventListener(\"click\", () => {\n const apiKey = apiKeyInput.value.trim();\n if (apiKey) {\n storeApiKey(apiKey);\n apiKeySection?.classList.add(\"hidden\");\n enrichmentForm?.classList.remove(\"hidden\");\n } else {\n alert(\"Please enter a valid API key\");\n }\n});\n\nenrichmentForm?.addEventListener(\"submit\", async (e) => {\n e.preventDefault();\n\n const apiKey = getStoredApiKey();\n if (!apiKey) {\n alert(\"Please enter your OpenAI API key first\");\n apiKeySection?.classList.remove(\"hidden\");\n enrichmentForm?.classList.add(\"hidden\");\n return;\n }\n\n const form = e.target as HTMLFormElement;\n const formData = new FormData(form);\n const data: EnrichmentData = Object.fromEntries(formData.entries());\n\n // Remove empty fields\n Object.keys(data).forEach((key) => {\n if (!data[key as keyof EnrichmentData]) {\n delete data[key as keyof EnrichmentData];\n }\n });\n\n try {\n const response = await fetch(\"/api/enrich\", {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n \"X-OpenAI-API-Key\": apiKey,\n },\n body: JSON.stringify(data),\n });\n\n const result: EnrichmentResponse = await response.json();\n\n if (result.success && result.data) {\n resultsContent!.innerHTML = `\n

Summary

${result.data.summary}

Professional Background

${result.data.professional_background}

Current Role

${result.data.current_role}

Company Info

${result.data.company_info}

Recent Activities

${result.data.recent_activities}

Social Presence

${result.data.social_presence}

Achievements

${result.data.achievements}

Sources

${source}

\n `;\n\n resultsDiv?.classList.remove(\"hidden\");\n resultsDiv?.scrollIntoView({ behavior: \"smooth\" });\n } else {\n alert(\"Error: \" + result.error);\n }\n } catch (error) {\n alert(\n \"Error: \" +\n (error instanceof Error ? error.message : \"Unknown error occurred\")\n );\n }\n});\n\n// Initialize the UI when the page loads\ndocument.addEventListener(\"DOMContentLoaded\", initializeUI);\n",[],[157,220],["D",1748892862892],[196,197],[157],"2957e09c-3fe9-11f0-bbe1-76b3cceeab13",["D",1748893110193],5,[],[164,34],"963b7fbc-3fe8-11f0-9ec6-76b3cceeab13","response.ts","963b8066-3fe8-11f0-9ec6-76b3cceeab13","96244d42-3fe8-11f0-a93c-76b3cceeab13",33,["D",1748892863354],"export function 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\nexport function extractSources(content: string): string[] {\n const sourcesSection = extractSection(content, \"SOURCES\");\n if (sourcesSection === \"No information found\") {\n return [];\n }\n\n const urlRegex = /https?:\\/\\/[^\\s]+/g;\n const urls = sourcesSection.match(urlRegex) || [];\n\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);\n}\n",[],[164,245,237],"utils","96244c8e-3fe8-11f0-a93c-76b3cceeab13",30,["D",1748892863233],[193],[164,245],"9651558a-3fe8-11f0-b011-76b3cceeab13","enrichment.ts","96515666-3fe8-11f0-b011-76b3cceeab13","9611f1ce-3fe8-11f0-ab87-76b3cceeab13",36,["D",1748892863355],"export interface 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",[],[164,260,252],"types","9611f0fc-3fe8-11f0-ab87-76b3cceeab13",29,["D",1748892863113],[191],[164,260],["D",1748892862963],[190,192,194],[164],"96448cba-3fe8-11f0-ab87-76b3cceeab13","extensions.json","96448d78-3fe8-11f0-ab87-76b3cceeab13",35,["D",1748892863445],"{\n \"recommendations\": [\n \"denoland.vscode-deno\"\n ]\n}",[],[170,270],["D",1748892863029],[188],[170],["D",1748885079132],{"_97":96,"_104":100},{"_97":96,"_98":-5,"_99":100,"_18":56,"_101":102,"_103":27},{"_13":86,"_33":87,"_45":44,"_88":46,"_89":-5,"_90":-5,"_91":-5,"_92":-5,"_93":-5,"_94":47,"_95":96},"ctx",{"_79":-5,"_124":317,"_318":319,"_320":321,"_322":27,"_323":27,"_324":27,"_325":25,"_326":-5,"_327":-7,"_328":-7,"_329":63,"_330":27,"_331":27,"_332":-5,"_333":27,"_334":27,"_335":27,"_336":-5},"ENV",{"_288":289,"_290":291,"_292":87,"_293":294,"_295":296,"_297":298,"_299":300,"_301":302,"_303":304,"_305":306,"_307":308,"_309":310,"_311":312,"_313":314,"_315":316},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","71c1b20804b3232a7e513be260cfffc1932a9e97","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"]

Diff · v42