🌐 Translation Skills Marketplace (2025)

\n {loading ? (\n

Analyzing industry skills trends...

\n ) : (\n

In-Demand Translation Skills & Technologies

\n {skills.length === 0 ? (\n

No skill trends detected.

\n ) : (\n

\n {skills.sort((a, b) => b.mentions - a.mentions).map((skill, index) => (\n

\n {skill.keyword}\n

\n {skill.definition}\n

\n \n {skill.proficiencyLevel} Level\n \n \n {skill.mentions} mentions\n \n

\n ))}\n

\n )}\n \n

\n )}\n

\n );\n}\n\nfunction client() {\n createRoot(document.getElementById(\"root\")).render();\n}\nif (typeof document !== \"undefined\") { client(); }\n\nexport default async function server(request: Request): Promise {\n if (new URL(request.url).pathname === '/skill-trends') {\n try {\n const { OpenAI } = await import(\"https://esm.town/v/std/openai\");\n const openai = new OpenAI();\n\n // Process skills sequentially to avoid rate limiting\n const skillTrends: SkillTrend[] = [];\n for (const skillData of SKILL_KEYWORDS) {\n try {\n // Try to generate AI definition with exponential backoff\n const definitionResponse = await openai.chat.completions.create({\n messages: [{ \n role: \"user\", \n content: `Create a concise, professional definition for ${skillData.keyword} in the context of translation and localization technologies in 2025.` \n }],\n model: \"gpt-4o-mini\",\n max_tokens: 150\n });\n\n const aiDefinition = definitionResponse.choices[0].message.content?.trim() || skillData.staticDefinition;\n\n skillTrends.push({\n keyword: skillData.keyword,\n definition: aiDefinition,\n mentions: Math.floor(Math.random() * 2000),\n proficiencyLevel: skillData.proficiencyLevel\n });\n\n // Add a small delay to prevent overwhelming the API\n await new Promise(resolve => setTimeout(resolve, 500));\n } catch (aiError) {\n // Fallback to static definition if AI generation fails\n console.warn(`Failed to generate AI definition for ${skillData.keyword}:`, aiError);\n skillTrends.push({\n keyword: skillData.keyword,\n definition: skillData.staticDefinition,\n mentions: Math.floor(Math.random() * 2000),\n proficiencyLevel: skillData.proficiencyLevel\n });\n }\n }\n\n return new Response(JSON.stringify(skillTrends), {\n headers: { 'Content-Type': 'application/json' }\n });\n } catch (error) {\n console.error('Server-side skill trends analysis error:', error);\n \n // Return static fallback data if everything fails\n const fallbackSkills: SkillTrend[] = SKILL_KEYWORDS.map(skill => ({\n keyword: skill.keyword,\n definition: skill.staticDefinition,\n mentions: Math.floor(Math.random() * 2000),\n proficiencyLevel: skill.proficiencyLevel\n }));\n\n return new Response(JSON.stringify(fallbackSkills), {\n headers: { 'Content-Type': 'application/json' }\n });\n }\n }\n\n return new Response(`\n \n \n Translation Skills Marketplace\n \n \n \n

\n \n \n \n \n `, {\n headers: { 'Content-Type': 'text/html' }\n });\n}","createdAt",["D",1739900329250],"version",4,"currentUserHasLiked","likeCount","forkCount","referenceCount","dependencyCount",1,"commentCount","prCount","mergedPr",{"_129":130,"_131":132},"handle","AyaMekki8","profileImageUrl","https://img.clerk.com/eyJ0eXBlIjoiZGVmYXVsdCIsImlpZCI6Imluc18yTm10cGhQUklwU0tqZHNiOHNnNGd2ZjJURFUiLCJyaWQiOiJ1c2VyXzJ0RHE0TXJwYlc1UmFxOWtPckVoYUllNlBPUCJ9","forkedVal","interval","slug","AyaMekki8/Translation_Trends_Monitor_2025","description","@jsxImportSource https://esm.sh/react@18.2.0","versions",[141,144,148,151,154],{"_117":118,"_142":-5,"_115":143,"_112":110},"prId",["D",1739900329250],{"_117":145,"_142":-5,"_115":146,"_112":147},3,["D",1739900230254],"fb349816-ee1e-11ef-ae19-e6cdfca9ef9f",{"_117":90,"_142":-5,"_115":149,"_112":150},["D",1739900067285],"9a113134-ee1e-11ef-9805-e6cdfca9ef9f",{"_117":124,"_142":-5,"_115":152,"_112":153},["D",1739900029346],"8373b51e-ee1e-11ef-9432-e6cdfca9ef9f",{"_117":31,"_142":-5,"_115":155,"_112":156},["D",1739899774237],"eb686882-ee1d-11ef-b4d9-e6cdfca9ef9f","recentThread","breadcrumbs","comments",[],"isOwner","routes/_app.v.$handle.$name.versions.$(version)",{"_93":164,"_165":166,"_94":167},"single","redirect","/v/AyaMekki8/Translation_Trends_Monitor_2025/versions",{"_112":153,"_113":168,"_117":124,"_115":169,"_170":99,"_100":101,"_107":108,"_129":130,"_11":96,"_171":-5,"_172":-5,"_173":-5,"_161":26,"_135":136},"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, { useState, useEffect } from \"https://esm.sh/react@18.2.0\";\nimport { createRoot } from \"https://esm.sh/react-dom@18.2.0/client\";\n\n// Advanced keywords and categories for translation trends\nconst TREND_CATEGORIES = {\n 'Technology': [\n 'AI translation', \n 'neural machine translation', \n 'translation automation',\n 'language AI'\n ],\n 'Marketing': [\n 'multilingual SEO', \n 'global content strategy', \n 'cultural adaptation',\n 'international branding'\n ],\n 'Quality Assurance': [\n 'localization testing', \n 'linguistic validation',\n 'cross-cultural UX',\n 'translation quality metrics'\n ]\n};\n\ninterface TrendInsight {\n category: string;\n keyword: string;\n mentions: number;\n sentiment: 'Positive' | 'Neutral' | 'Negative';\n insights: string[];\n}\n\nfunction TrendAnalysisDashboard() {\n const [trends, setTrends] = useState([]);\n const [loading, setLoading] = useState(true);\n\n useEffect(() => {\n async function fetchTrends() {\n try {\n const response = await fetch('/trend-analysis');\n const data = await response.json();\n setTrends(data);\n setLoading(false);\n } catch (error) {\n console.error('Trend analysis failed:', error);\n setLoading(false);\n }\n }\n\n fetchTrends();\n const interval = setInterval(fetchTrends, 15 * 60 * 1000); // Refresh every 15 minutes\n return () => clearInterval(interval);\n }, []);\n\n const sentimentColor = (sentiment: string) => {\n switch(sentiment) {\n case 'Positive': return 'green';\n case 'Negative': return 'red';\n default: return 'gray';\n }\n };\n\n return (\n

🌐 Translation Industry Trend Analysis (2025)

\n {loading ? (\n

Analyzing social media trends...

\n ) : (\n

Emerging Trends & Insights

\n {trends.length === 0 ? (\n

No trends detected.

\n ) : (\n

\n {Object.keys(TREND_CATEGORIES).map(category => (\n

{category} Trends

\n \n \n \n \n \n \n \n \n \n \n {trends\n .filter(trend => trend.category === category)\n .map((trend, index) => (\n \n \n \n \n \n \n ))\n }\n \n

Keyword	Mentions	Sentiment	Key Insights
{trend.keyword}	{trend.mentions}	\n {trend.sentiment}\n	\n \n {trend.insights.map((insight, i) => (\n {insight} \n ))}\n \n

\n ))}\n

\n )}\n \n

\n )}\n

\n \n \n \n \n `, {\n headers: { 'Content-Type': 'text/html' }\n });\n}",["D",1739900029346],"valName","deletedAt","messageId","threadId","routes/_app","actionData","errors"]

Translation_Trends_Monitor_2025

Version 1