Resume Skill Matcher

Resume Skill Matcher

\n \n {error && (\n

\n 🚨 {error}\n

\n )}\n {resumeText && (\n

Resume Preview:

{resumeText}...

Skills Extracted:

{resumeSkills.join(\", \")}

\n )}\n

\n\n

Job Description

\n setJobDescription(e.target.value)}\n placeholder=\"Paste job description here\"\n style={{...styles.input, minHeight: '100px'}}\n />\n \n

\n\n {analysisResult && (\n

Skill Match Analysis

✅ Matched Skills: {analysisResult.matchedSkills.join(\", \") || 'None'}

❌ Missing Skills: {analysisResult.missingSkills.join(\", \") || 'None'}

📊 Match Percentage: {Math.round((analysisResult.matchedSkills.length / (analysisResult.matchedSkills.length + analysisResult.missingSkills.length)) * 100) || 0}%

\n )}\n

\n );\n}\n\nfunction App() {\n return ;\n}\n\nfunction client() {\n createRoot(document.getElementById(\"root\")).render();\n}\n\nif (typeof document !== \"undefined\") { client(); }\n\nexport default async function server(request: Request): Promise {\n // Handle API routes for skills extraction and comparison\n if (request.method === 'POST') {\n try {\n const { OpenAI } = await import(\"https://esm.town/v/std/openai\");\n const openai = new OpenAI();\n\n // New PDF extraction endpoint\n if (request.url.includes('/api/extract-pdf')) {\n const formData = await request.formData();\n const file = formData.get('file') as File;\n\n if (!file) {\n return new Response('No file uploaded', { status: 400 });\n }\n\n const arrayBuffer = await file.arrayBuffer();\n \n // Use Deno's native PDF extraction\n const pdfText = await extractPDFText(new Uint8Array(arrayBuffer));\n\n return new Response(pdfText, {\n headers: { 'Content-Type': 'text/plain' }\n });\n }\n\n const body = await request.json();\n\n if (request.url.includes('/api/extract-skills')) {\n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"system\", \n content: \"Extract a concise list of top 10 professional skills from the resume text. Return a comma-separated list of skills focusing on technical and professional competencies. Be specific and precise.\"\n },\n {\n role: \"user\", \n content: body.text\n }\n ],\n max_tokens: 150\n });\n\n const skillsText = response.choices[0]?.message?.content ?? \"\";\n const skills = skillsText\n .split(/[,;]+/)\n .map(skill => skill.trim().toLowerCase())\n .filter(skill => skill.length > 1)\n .slice(0, 10);\n\n return new Response(JSON.stringify({ skills }), {\n headers: { 'Content-Type': 'application/json' }\n });\n }\n\n if (request.url.includes('/api/compare-skills')) {\n const jobSkillsResponse = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"system\", \n content: \"Extract top 10 key skills from the job description. Return a comma-separated list of skills, focusing on technical and professional competencies.\"\n },\n {\n role: \"user\", \n content: body.jobDescription\n }\n ],\n max_tokens: 150\n });\n\n const jobSkillsText = jobSkillsResponse.choices[0]?.message?.content ?? \"\";\n const jobSkills = jobSkillsText\n .split(/[,;]+/)\n .map(skill => skill.trim().toLowerCase())\n .filter(skill => skill.length > 1)\n .slice(0, 10);\n\n const matchedSkills = body.resumeSkills.filter((skill: string) => \n jobSkills.some(jobSkill => \n skill.toLowerCase().includes(jobSkill.toLowerCase())\n )\n );\n\n const missingSkills = jobSkills.filter((jobSkill: string) => \n !body.resumeSkills.some((skill: string) => \n skill.toLowerCase().includes(jobSkill.toLowerCase())\n )\n );\n\n return new Response(JSON.stringify({ \n matchedSkills: Array.from(new Set(matchedSkills)), \n missingSkills: Array.from(new Set(missingSkills)) \n }), {\n headers: { 'Content-Type': 'application/json' }\n });\n }\n\n return new Response('Not Found', { status: 404 });\n } catch (error) {\n console.error('Server-side error:', error);\n return new Response(JSON.stringify({ \n error: error instanceof Error ? error.message : 'Unknown server error' \n }), { \n status: 500,\n headers: { 'Content-Type': 'application/json' }\n });\n }\n }\n\n return new Response(\n `\n \n \n Resume Skill Matcher\n \n \n \n \n \n

\n \n \n \n `,\n {\n headers: { \"content-type\": \"text/html\" },\n },\n );\n}\n\n// Custom PDF text extraction function using Deno's capabilities\nasync function extractPDFText(pdfBytes: Uint8Array): Promise {\n try {\n // Use Deno's native PDF extraction capabilities\n const { Document } = await import(\"https://deno.land/x/pdf@v0.2.0/mod.ts\");\n \n const doc = await Document.load(pdfBytes);\n let fullText = '';\n\n for (let pageIndex = 0; pageIndex < doc.numPages; pageIndex++) {\n const page = await doc.getPage(pageIndex);\n const pageText = await page.getTextContent();\n fullText += pageText.items.map(item => item.str).join(' ') + '\\n';\n }\n\n return fullText.trim();\n } catch (error) {\n console.error('PDF text extraction error:', error);\n return 'Unable to extract text from PDF';\n }\n}","deleted","label","children",[],[152],"files",[150],"counts",{"_173":32,"_174":175,"_176":32,"_177":178},"pulls","branches",1,"forks","envVars",{"_179":32,"_180":32},"count","emptyCount","contents",[183],{"_102":151,"_95":152,"_153":114,"_154":-5,"_155":138,"_156":137,"_157":116,"_104":184,"_99":159,"_160":161,"_162":163,"_164":22,"_165":-5,"_98":185},["D",1741231491492],[152],"file","upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name._index",{"_93":94,"_95":96,"_97":-7,"_99":-7,"_100":195,"_181":200,"_203":-7,"_204":-5,"_205":-5,"_169":206,"_210":211,"_212":-5,"_213":-5},{"_102":103,"_95":96,"_104":196,"_106":-5,"_107":22,"_108":109,"_110":-5,"_111":-5,"_14":112,"_113":114,"_115":116,"_117":-5,"_118":32,"_16":119,"_120":121,"_122":121,"_123":124,"_125":124,"_126":124,"_127":121,"_128":121,"_23":197,"_132":198,"_135":199,"_147":22},["D",1746227406310],{"_93":94,"_130":131},{"_93":94,"_134":131},{"_99":137,"_95":43,"_102":138,"_139":103,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":-5,"_145":96,"_146":94},[201],{"_102":151,"_95":152,"_153":114,"_154":-5,"_155":138,"_156":137,"_157":116,"_104":184,"_99":159,"_160":161,"_162":163,"_164":22,"_165":-5,"_98":202},[152],"readme","upstream","pull",[207],{"_102":151,"_95":152,"_153":114,"_154":-5,"_155":138,"_156":137,"_157":116,"_104":158,"_99":159,"_160":161,"_162":163,"_164":22,"_165":-5,"_166":208,"_98":209},[],[152],"previews",[207],"ahead","behind","actionData","errors"]

Chandrakanth95

Resume_matcher