diff --git a/Dockerfile b/Dockerfile index 04fb80a..5f171b4 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,21 +1,20 @@ -# Production image for the static Resume Matcher site -FROM nginx:1.27-alpine AS production +# Production image for MatchlyPro with AI proxy support +FROM node:20-alpine AS production + +WORKDIR /app RUN apk add --no-cache curl -COPY nginx.conf /etc/nginx/nginx.conf -COPY index.html /usr/share/nginx/html/index.html -COPY health.html /usr/share/nginx/html/health.html +COPY package.json package-lock.json ./ +RUN npm ci --omit=dev -RUN chown -R nginx:nginx /usr/share/nginx/html /var/cache/nginx /var/log/nginx /etc/nginx/conf.d \ - && touch /var/run/nginx.pid \ - && chown nginx:nginx /var/run/nginx.pid +COPY . . -USER nginx +ENV PORT=8080 EXPOSE 8080 HEALTHCHECK --interval=30s --timeout=5s --start-period=10s --retries=3 \ CMD curl -fsS http://localhost:8080/health > /dev/null || exit 1 -CMD ["nginx", "-g", "daemon off;"] +CMD ["node", "server.mjs"] diff --git a/README.md b/README.md index 910ef2f..0e38b67 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,13 @@ # MatchlyPro -MatchlyPro is a production-oriented resume matcher web app that compares a resume against a job description, highlights keyword coverage, surfaces ATS risks, and suggests practical improvements. +MatchlyPro is a production-oriented resume matcher web app that compares a resume against a job description, highlights keyword coverage, surfaces ATS risks, and suggests practical improvements. It now supports server-side AI analysis through the Gemini API. This repository is designed as a portfolio project that shows both product engineering and delivery discipline: - product design and implementation - client-side PDF parsing with PDF.js -- production-ready static hosting with Vercel -- containerized runtime with Nginx and Docker +- production-ready hosting with a lightweight Node server +- containerized runtime with Node and Docker - CI checks with GitHub Actions - release-gated production promotion - basic security scanning and smoke validation @@ -25,9 +25,9 @@ This is a strong portfolio example for: - shipping polished browser-based tools - practical CI/CD ownership - containerization and deployment workflows -- release-based production control for a static app +- release-based production control for the app runtime -It is not a full multi-tenant SaaS yet because there is no backend, database, authentication, billing, or persistent user accounts. It is better described as a production-minded web product with DevOps discipline than as a complete SaaS platform. +It is not a full multi-tenant SaaS yet because there is no database, authentication, billing, or persistent user accounts. It is better described as a production-minded web product with AI-assisted analysis and practical DevOps discipline than as a complete SaaS platform. ## What The App Does @@ -45,7 +45,7 @@ It is not a full multi-tenant SaaS yet because there is no backend, database, au - CSS3 - Vanilla JavaScript - PDF.js -- Nginx +- Node.js - Docker - GitHub Actions - GitHub Releases @@ -57,8 +57,9 @@ It is not a full multi-tenant SaaS yet because there is no backend, database, au ```mermaid flowchart LR - U[User Browser] --> V[Vercel Production Deployment] - V --> S[Static Assets
index.html + health.html] + U[User Browser] --> A[MatchlyPro Node Server] + A --> S[Static App
index.html + health.html] + A --> R[Gemini API
gemini-2.5-flash-lite] S --> J[Browser App Logic] J --> P[PDF.js Parsing In Browser] J --> L[Local Storage Session History] @@ -188,6 +189,20 @@ In practical terms, someone can fork the repo and run their own copy, but they c ### Run with Node +1. Create a local env file from the example: + +```bash +cp .env.example .env +``` + +2. Set these values: + +- `GEMINI_API_KEY` +- `GEMINI_BASE_URL=https://generativelanguage.googleapis.com/v1beta/openai/` +- `GEMINI_MODEL=gemini-2.5-flash-lite` + +3. Start the app: + ```bash npm ci npm start @@ -195,6 +210,8 @@ npm start Open `http://localhost:3000` +If the Gemini env vars are not set, the app still runs and falls back to local heuristic analysis. + ### Run with Docker ```bash @@ -229,7 +246,7 @@ That release tag triggers the production workflow, publishes release artifacts, - `vercel.json` disables Git-based Vercel auto deployment - the app exposes `/health` for deployment verification -- Docker runtime uses Nginx for static delivery +- Docker runtime uses the Node server for app and API delivery - CI and release jobs depend on repository secrets for external integrations ## Repository Structure @@ -249,10 +266,12 @@ That release tag triggers the production workflow, publishes release artifacts, |-- Dockerfile |-- LICENSE |-- README.md +|-- .env.example |-- health.html |-- index.html |-- nginx.conf |-- package.json +|-- server.mjs `-- vercel.json ``` @@ -270,7 +289,7 @@ This repository is portfolio-ready for a production-minded web app because it in ## Current Limitations -- no backend API +- no persistent backend storage - no persistent database - no authentication or user accounts - no billing or subscriptions @@ -284,7 +303,7 @@ This repository is portfolio-ready for a production-minded web app because it in - add Lighthouse and accessibility checks in CI - add a custom domain - add analytics and error monitoring -- add a small backend for saved sessions or team features +- add persistent storage for saved sessions or team features ## Author diff --git a/index.html b/index.html index 97f323e..eb8e6bf 100644 --- a/index.html +++ b/index.html @@ -1,17 +1,16 @@ + MatchlyPro — AI Resume Matcher - - + + +
- +
@@ -1585,22 +2336,25 @@

Match Your Resume Perfectly

- +
@@ -1650,8 +2407,9 @@

Match Your Resume Perfectly

- - + +

No analysis yet

Add a job description and resume, then click Analyze Match to see results.

@@ -1669,12 +2427,13 @@

No analysis yet

- - + + - - + + MatchlyPro @@ -1691,56 +2450,71 @@

No analysis yet

- + + \ No newline at end of file diff --git a/package.json b/package.json index 7a93f19..11eb029 100644 --- a/package.json +++ b/package.json @@ -4,8 +4,9 @@ "description": "A web application for matching resumes with job descriptions", "main": "index.html", "scripts": { - "start": "serve -s . -p 3000", - "dev": "serve -s . -p 3000", + "start": "node server.mjs", + "dev": "node server.mjs", + "static": "serve -s . -p 3000", "build": "node ./scripts/validate-project.mjs", "lint": "node ./scripts/validate-project.mjs", "test": "node ./scripts/smoke-static-site.mjs", diff --git a/server.mjs b/server.mjs new file mode 100644 index 0000000..ede5ba7 --- /dev/null +++ b/server.mjs @@ -0,0 +1,468 @@ +import { createServer } from "node:http"; +import { readFile, stat } from "node:fs/promises"; +import { createReadStream, existsSync, readFileSync } from "node:fs"; +import { extname, join, normalize, resolve } from "node:path"; +import { fileURLToPath } from "node:url"; + +const __filename = fileURLToPath(import.meta.url); +const __dirname = resolve(__filename, ".."); +const root = resolve(__dirname); + +function loadEnvFile() { + const envPath = join(root, ".env"); + if (!existsSync(envPath)) return; + const contents = readFileSync(envPath, "utf8"); + contents.split(/\r?\n/).forEach(line => { + const trimmed = line.trim(); + if (!trimmed || trimmed.startsWith("#")) return; + const separator = trimmed.indexOf("="); + if (separator <= 0) return; + const key = trimmed.slice(0, separator).trim(); + const value = trimmed.slice(separator + 1).trim().replace(/^['"]|['"]$/g, ""); + if (!(key in process.env)) process.env[key] = value; + }); +} + +loadEnvFile(); + +const port = Number(process.env.PORT || 3000); + +const aiConfig = { + provider: "AI", + model: process.env.GEMINI_MODEL || "gemini-2.5-flash-lite", + apiKey: process.env.GEMINI_API_KEY || "", + baseUrl: process.env.GEMINI_BASE_URL || "https://generativelanguage.googleapis.com/v1beta/openai/" +}; + +const activeProvider = aiConfig; + +const mimeTypes = { + ".html": "text/html; charset=utf-8", + ".js": "text/javascript; charset=utf-8", + ".mjs": "text/javascript; charset=utf-8", + ".css": "text/css; charset=utf-8", + ".json": "application/json; charset=utf-8", + ".svg": "image/svg+xml", + ".png": "image/png", + ".jpg": "image/jpeg", + ".jpeg": "image/jpeg", + ".ico": "image/x-icon" +}; + +function json(res, status, payload) { + res.writeHead(status, { "content-type": "application/json; charset=utf-8" }); + res.end(JSON.stringify(payload)); +} + +function getChatCompletionsUrl(rawBaseUrl, providerName = "") { + const trimmed = String(rawBaseUrl || "").trim().replace(/\/+$/, ""); + if (!trimmed) return ""; + if (/\/chat\/completions$/i.test(trimmed)) return trimmed; + if (/\/openai$/i.test(trimmed)) return `${trimmed}/chat/completions`; + if (providerName === "AI") return `${trimmed}/chat/completions`; + if (/\/v1$/i.test(trimmed)) return `${trimmed}/chat/completions`; + return `${trimmed}/v1/chat/completions`; +} + +function readBody(req) { + return new Promise((resolveBody, rejectBody) => { + let body = ""; + req.on("data", chunk => { + body += chunk; + if (body.length > 1024 * 1024 * 2) { + rejectBody(new Error("Request body too large.")); + req.destroy(); + } + }); + req.on("end", () => resolveBody(body)); + req.on("error", rejectBody); + }); +} + +function normalizeLine(line) { + return String(line || "").replace(/\s+/g, " ").trim(); +} + +function parseResumeSections(text) { + const lines = String(text || "").replace(/\r/g, "").split("\n"); + const sections = []; + let current = { name: "General", content: [] }; + const matchers = [ + { pattern: /professional summary|summary|profile/i, name: "Summary" }, + { pattern: /experience highlights|experience|employment|work history/i, name: "Experience" }, + { pattern: /projects|project highlights/i, name: "Projects" }, + { pattern: /skills|additional skills|technical skills|core skills/i, name: "Skills" }, + { pattern: /education|academic/i, name: "Education" }, + { pattern: /certifications|certificates/i, name: "Certifications" } + ]; + + for (const line of lines) { + const trimmed = normalizeLine(line); + const match = matchers.find(item => item.pattern.test(trimmed) && trimmed.length < 40); + if (match) { + if (current.content.join(" ").trim()) { + sections.push({ name: current.name, content: current.content.join("\n").trim() }); + } + current = { name: match.name, content: [] }; + } else { + current.content.push(line); + } + } + + if (current.content.join(" ").trim()) { + sections.push({ name: current.name, content: current.content.join("\n").trim() }); + } + + return sections.length ? sections : [{ name: "General", content: String(text || "") }]; +} + +function buildFallbackSections(resume, missingTerms = []) { + const sections = parseResumeSections(resume); + return sections.map((section, index) => ({ + name: section.name, + score: Math.max(18, 74 - index * 9), + suggestion: missingTerms[index] + ? `Add "${missingTerms[index]}" with a concrete example.` + : "This section looks aligned." + })); +} + +function buildPrompt(jd, resume) { + return ` +You are an elite Technical Recruiter and ATS Optimization Expert. Your goal is to provide a brutal, honest, and high-depth analysis of how a resume matches a specific Job Description (JD). + +Return ONLY valid JSON. + +### Analysis Instructions: +1. **Deep Semantic Matching**: Don't just look for keywords. Understand the context, seniority level, and domain expertise required. +2. **Evidence-Based Scoring**: + - **High Match**: Clear, quantifiable evidence (e.g., "3 years of React", "Led a team of 5"). + - **Partial Match**: Mentioned but lacks depth or specific experience. + - **Missing**: No evidence found for a critical requirement. +3. **Role Sensitivity**: If the JD is for a non-tech role (Marketing, HR, etc.), do not use tech jargon. Match the domain language. +4. **ATS Risk Assessment**: Identify formatting issues, missing standard sections, or over-complex language that might trip up older ATS systems. +5. **Actionable Feedback**: Provide specific, high-value suggestions. Instead of "add skills", say "include metrics for your impact on user engagement using React". + +### JSON Output Schema: +{ + "score": number (0-100), + "confidence": "High Match" | "Medium Match" | "Low Match", + "roleTitle": "Optimized role title based on JD", + "roleFamily": "General industry category", + "highMatch": [ + { "term": "Skill/Requirement", "weight": number (1-20), "evidence": "Briefly quote or summarize resume evidence" } + ], + "partialMatch": [ + { "term": "Skill/Requirement", "resumeTerm": "What resume has", "weight": number (1-15), "reason": "Why it is only a partial match" } + ], + "missing": [ + { "term": "Critical Missing Skill", "weight": number (1-25), "reason": "Impact on the application" } + ], + "topKeywords": [ + { "term": "Keyword", "weight": number (1-10) } + ], + "keywordCategories": [ + { "label": "e.g., Technical Skills", "top": ["Skill1", "Skill2"], "coverage": number (0-100) } + ], + "jdInsights": [ + { "title": "Priority", "detail": "What the JD prioritizes most", "note": "Strategic tip" } + ], + "atsRisks": [ + { "level": "low" | "medium" | "high", "title": "Risk Category", "note": "Specific observation" } + ], + "sectionAnalysis": [ + { "name": "Section Name", "score": number (0-100), "suggestion": "Specific improvement" } + ], + "experienceSignals": [ + { "title": "Longevity/Impact", "detail": "Analysis of their career progression", "note": "Recruiter's takeaway" } + ], + "suggestions": [ + { "term": "Action Step", "weight": number (1-10), "reason": "Why this will boost the score" } + ], + "summary": "5-8 lines of professional, hard-hitting analysis. Highlight the 'Why' behind the score." +} + +### Constraint: +- Maximum 8 items per list (highMatch, partialMatch, missing, suggestions). +- Be strict. A 90%+ score should be very rare and reserved for perfect candidates. + +### Input Data: +--- +JOB DESCRIPTION: +${jd} + +--- +RESUME: +${resume} +--- +`.trim(); +} + +function clamp(value, min, max) { + return Math.min(Math.max(Number(value) || 0, min), max); +} + +function ensureArray(value) { + return Array.isArray(value) ? value : []; +} + +function normalizeAnalysisShape(raw, jd, resume) { + const score = clamp(raw?.score, 0, 100); + const missing = ensureArray(raw?.missing).map(item => ({ + term: normalizeLine(item?.term), + weight: clamp(item?.weight || 12, 1, 100), + reason: normalizeLine(item?.reason) + })).filter(item => item.term); + + const highMatch = ensureArray(raw?.highMatch).map(item => ({ + term: normalizeLine(item?.term), + weight: clamp(item?.weight || 12, 1, 100), + evidence: normalizeLine(item?.evidence) + })).filter(item => item.term); + + const partialMatch = ensureArray(raw?.partialMatch).map(item => ({ + term: normalizeLine(item?.term), + resumeTerm: normalizeLine(item?.resumeTerm || item?.evidence || item?.reason), + weight: clamp(item?.weight || 10, 1, 100), + reason: normalizeLine(item?.reason) + })).filter(item => item.term); + + const topKeywords = ensureArray(raw?.topKeywords).map(item => ({ + term: normalizeLine(item?.term), + weight: clamp(item?.weight || 10, 1, 100) + })).filter(item => item.term).slice(0, 10); + + const keywordCategories = ensureArray(raw?.keywordCategories).map(item => ({ + label: normalizeLine(item?.label) || "General Fit", + top: ensureArray(item?.top).map(normalizeLine).filter(Boolean).slice(0, 4), + coverage: clamp(item?.coverage, 0, 100) + })).slice(0, 6); + + const resumeSections = parseResumeSections(resume).map(section => section.name); + const sectionAnalysis = (ensureArray(raw?.sectionAnalysis).length ? ensureArray(raw?.sectionAnalysis) : buildFallbackSections(resume, missing.map(item => item.term))) + .map((item, index) => ({ + name: normalizeLine(item?.name) || resumeSections[index] || "General", + score: clamp(item?.score || 40, 0, 100), + suggestion: normalizeLine(item?.suggestion) || "Add more direct evidence for this section." + })).slice(0, 6); + + const atsRisks = ensureArray(raw?.atsRisks).map(item => ({ + level: ["low", "medium", "high"].includes(item?.level) ? item.level : "medium", + title: normalizeLine(item?.title) || "Needs review", + note: normalizeLine(item?.note) || "The AI found a potential mismatch." + })).slice(0, 5); + + const jdInsights = ensureArray(raw?.jdInsights).map(item => ({ + title: normalizeLine(item?.title) || "Insight", + detail: normalizeLine(item?.detail), + note: normalizeLine(item?.note) + })).filter(item => item.title && item.detail).slice(0, 5); + + const experienceSignals = ensureArray(raw?.experienceSignals).map(item => ({ + title: normalizeLine(item?.title) || "Signal", + detail: normalizeLine(item?.detail) || "Limited", + note: normalizeLine(item?.note) || "Review resume evidence." + })).slice(0, 5); + + const suggestions = ensureArray(raw?.suggestions).map(item => ({ + term: normalizeLine(item?.term), + weight: clamp(item?.weight || 8, 1, 100), + reason: normalizeLine(item?.reason) || "Add a concrete result tied to this requirement." + })).filter(item => item.term).slice(0, 8); + + const confidence = ["High Match", "Medium Match", "Low Match"].includes(raw?.confidence) + ? raw.confidence + : score >= 78 ? "High Match" : score >= 52 ? "Medium Match" : "Low Match"; + + const roleTitle = normalizeLine(raw?.roleTitle) || "Resume Match Analysis"; + const roleFamily = normalizeLine(raw?.roleFamily) || "General Professional"; + + const summary = normalizeLine(raw?.summary) + ? String(raw.summary) + : [ + "Match Overview", + `Role Family: ${roleFamily}`, + `Match Score: ${score.toFixed(1)}%`, + `Confidence: ${confidence}`, + `Top Evidence Areas: ${topKeywords.slice(0, 5).map(item => item.term).join(", ") || "Limited evidence"}`, + `Suggested Additions: ${missing.slice(0, 5).map(item => item.term).join(", ") || "No urgent gaps"}` + ].join("\n"); + + return { + score, + confidence, + roleTitle, + roleFamily, + highMatch, + partialMatch, + missing, + topKeywords, + keywordCategories, + jdInsights, + atsRisks, + sectionAnalysis, + experienceSignals, + suggestions, + summary + }; +} + +function extractJson(text) { + if (typeof text !== "string") return text; + try { + return JSON.parse(text); + } catch { + const match = text.match(/```(?:json)?\s*([\s\S]*?)\s*```/); + if (match && match[1]) { + try { return JSON.parse(match[1]); } catch { /* ignore */ } + } + const firstBrace = text.indexOf("{"); + const lastBrace = text.lastIndexOf("}"); + if (firstBrace !== -1 && lastBrace !== -1 && lastBrace > firstBrace) { + try { return JSON.parse(text.slice(firstBrace, lastBrace + 1)); } catch { /* ignore */ } + } + throw new Error("The AI response was not valid JSON."); + } +} + +async function requestAiAnalysis(jd, resume) { + const endpoint = getChatCompletionsUrl(activeProvider.baseUrl, activeProvider.provider); + if (!activeProvider.apiKey || !endpoint) { + throw new Error("AI analyze is not configured. Set the required API key in your environment."); + } + + const payload = { + model: activeProvider.model, + temperature: 0.1, + max_tokens: 8192, + response_format: { type: "json_object" }, + messages: [ + { + role: "system", + content: "You are a strict resume-matching assistant. Always return valid json." + }, + { + role: "user", + content: buildPrompt(jd, resume) + } + ] + }; + + const headers = { + "content-type": "application/json", + authorization: `Bearer ${activeProvider.apiKey}` + }; + + const response = await fetch(endpoint, { + method: "POST", + headers, + body: JSON.stringify(payload) + }); + + const rawText = await response.text(); + let parsedResponse = null; + + try { + parsedResponse = rawText ? JSON.parse(rawText) : null; + } catch { + parsedResponse = null; + } + + if (!response.ok) { + let detail = ""; + if (Array.isArray(parsedResponse) && parsedResponse[0]?.error) { + detail = parsedResponse[0].error.message; + } else { + detail = parsedResponse?.error?.message || parsedResponse?.message || rawText || `HTTP ${response.status}`; + } + + if (response.status === 429 || detail.includes("quota")) { + detail = "You've reached the free daily limit for AI analysis. Please try again tomorrow!"; + } else if (detail.length > 150) { + detail = `API Error (HTTP ${response.status}). Check server console for full details.`; + } + + throw new Error(`AI analyze failed: ${detail}`); + } + + const content = parsedResponse?.choices?.[0]?.message?.content; + if (!content) { + throw new Error("The AI response was empty."); + } + + let analysisRaw = null; + try { + analysisRaw = extractJson(content); + } catch (err) { + throw err; + } + + return normalizeAnalysisShape(analysisRaw, jd, resume); +} + +async function serveStatic(req, res, pathname) { + const relativePath = pathname === "/" ? "/index.html" : pathname; + const filePath = normalize(join(root, relativePath)); + if (!filePath.startsWith(root) || !existsSync(filePath)) { + const indexHtml = await readFile(join(root, "index.html"), "utf8"); + res.writeHead(200, { "content-type": "text/html; charset=utf-8" }); + res.end(indexHtml); + return; + } + + const fileInfo = await stat(filePath); + if (fileInfo.isDirectory()) { + const indexHtml = await readFile(join(root, "index.html"), "utf8"); + res.writeHead(200, { "content-type": "text/html; charset=utf-8" }); + res.end(indexHtml); + return; + } + + res.writeHead(200, { "content-type": mimeTypes[extname(filePath).toLowerCase()] || "application/octet-stream" }); + createReadStream(filePath).pipe(res); +} + +const server = createServer(async (req, res) => { + try { + const requestUrl = new URL(req.url || "/", `http://${req.headers.host || "localhost"}`); + const { pathname } = requestUrl; + + if (req.method === "GET" && pathname === "/api/config") { + json(res, 200, { + enabled: Boolean(activeProvider.apiKey && activeProvider.baseUrl), + provider: activeProvider.provider, + model: activeProvider.model + }); + return; + } + + if (req.method === "POST" && pathname === "/api/analyze") { + const body = await readBody(req); + const payload = body ? JSON.parse(body) : {}; + const jd = String(payload?.jd || "").trim(); + const resume = String(payload?.resume || "").trim(); + + if (!jd || !resume) { + json(res, 400, { error: "Both job description and resume are required." }); + return; + } + + const analysis = await requestAiAnalysis(jd, resume); + json(res, 200, analysis); + return; + } + + if (req.method === "GET") { + await serveStatic(req, res, pathname); + return; + } + + json(res, 404, { error: "Not found." }); + } catch (error) { + json(res, 500, { error: error instanceof Error ? error.message : "Unexpected server error." }); + } +}); + +server.listen(port, () => { + console.log(`MatchlyPro server listening on http://localhost:${port}`); +});