\n \n\n`;\n\napp.get(\"*\", (c) => {\n const val = parseVal();\n const slug = val.username + \"/\" + val.name;\n return c.html(SHELL(slug));\n});\n\nexport default app.fetch;\n","deleted","label",[122],"c0b47894-78c9-4a4f-881a-d87317d8d964","README.md","325a0b56-8030-11f1-bd25-1607ee4eb77e",["D",1784108646298],1,"# 🎯 AI Interview Coach\n\nAI-powered interview practice platform with resume analysis, personalized question generation, instant scoring, and detailed feedback.\n\n## Features\n\n- **Authentication** — Register & login with secure token-based auth\n- **Resume Upload** — Upload resume text to generate personalized interview questions\n- **AI Question Generation** — Auto-generates interview questions tailored to the role and difficulty (uses OpenAI if `OPENAI_API_KEY` is set, otherwise falls back to a curated question bank)\n- **AI Answer Scoring** — Submit answers and receive instant 1-10 scoring with strengths, improvements, and actionable feedback\n- **Dashboard** — Track total sessions, completion rate, average score, and questions answered\n- **Session History** — Review past sessions with question-by-question breakdown\n- **Modern Responsive UI** — Dark-themed React SPA with Twind/Tailwind, works on mobile and desktop\n\n## Architecture\n\n```\nindex.ts — Hono HTTP entry point (API routes + SPA shell)\napi/\n db.ts — SQLite schema (users, resumes, sessions, questions, answers)\n auth.ts — Token-based auth (register, login, middleware)\n ai.ts — AI question generation + answer scoring (OpenAI + fallback)\n resume.ts — Resume CRUD routes\n sessions.ts — Session creation, answer submission, scoring, stats\napp/\n App.tsx — Main React app with state-based routing & nav\n components.tsx — Shared UI: Button, Card, Input, ScoreRing, Badge, etc.\n pages/\n Login.tsx — Login / Register page\n Dashboard.tsx — Stats grid + session/resume tabs\n NewInterview.tsx — Role & difficulty selector\n Interview.tsx — Question-by-question practice with live scoring\n Results.tsx — Session summary + per-question breakdown\n ResumeUpload.tsx — File upload or paste resume text\n```\n\n## Tech Stack\n\n- **Backend**: Hono on Val Town (Deno runtime)\n- **Frontend**: React 18 + Twind (Tailwind at runtime)\n- **Database**: Val Town built-in SQLite (Turso/libSQL)\n- **AI**: OpenAI GPT-4o-mini (optional — works without it)\n\n## Environment Variables\n\n| Key | Required | Description |\n|-----|----------|-------------|\n| `OPENAI_API_KEY` | No | OpenAI API key for AI-powered questions & scoring. Without it, the app uses a built-in question bank and heuristic scoring. |\n| `AUTH_SECRET` | No | Secret key for password hashing & token signing. Without it, a default is used (set for production). |\n\n👉 Add OPENAI_API_KEY here: https://www.val.town/x/atchayaa/ai-interview-coach/environment-variables?key=OPENAI_API_KEY\n\n👉 Add AUTH_SECRET here: https://www.val.town/x/atchayaa/ai-interview-coach/environment-variables?key=AUTH_SECRET\n\n## API Endpoints\n\n| Method | Path | Description |\n|--------|------|-------------|\n| POST | `/api/auth/register` | Register new user |\n| POST | `/api/auth/login` | Login |\n| GET | `/api/auth/me` | Get current user |\n| POST | `/api/resume/upload` | Upload resume text |\n| GET | `/api/resume/list` | List user's resumes |\n| GET | `/api/resume/:id` | Get resume content |\n| DELETE | `/api/resume/:id` | Delete resume |\n| POST | `/api/sessions/create` | Create session + generate questions |\n| GET | `/api/sessions/list` | List user's sessions |\n| GET | `/api/sessions/:id` | Get session details with Q&A |\n| POST | `/api/sessions/:id/answer` | Submit answer & get score |\n| POST | `/api/sessions/:id/complete` | Mark session complete |\n| GET | `/api/sessions/stats/dashboard` | Dashboard aggregate stats |\n",[139],"d9f446f7-3e49-44c7-8db0-0f63286b312c","app","ec70965c-0073-4c31-b02a-96fb780e5865",8,["D",1784108379032],"directory",[146],"8e783c8b-8fca-473d-8b4d-194f4b6cfd53","api","cbb557f2-ab8d-418c-aa0b-a5c439150b4f",2,["D",1784108236504],[153],"pulls","forks","envVars",{"_164":54,"_166":54},"connections",{"_164":54,"_165":54},"count","unfilledCount","emptyCount",{"_20":152,"_13":153,"_123":154,"_124":-5,"_125":21,"_126":155,"_128":50,"_22":304,"_29":54,"_131":150,"_133":-5,"_135":38,"_136":-5,"_186":305,"_94":306},{"_20":297,"_13":298,"_123":299,"_124":154,"_125":21,"_126":155,"_128":50,"_22":300,"_29":54,"_131":196,"_133":301,"_135":38,"_136":-5,"_186":302,"_94":303},{"_20":289,"_13":290,"_123":291,"_124":154,"_125":21,"_126":292,"_128":50,"_22":293,"_29":142,"_131":196,"_133":294,"_135":38,"_136":-5,"_186":295,"_94":296},{"_20":281,"_13":282,"_123":283,"_124":154,"_125":21,"_126":284,"_128":50,"_22":285,"_29":54,"_131":196,"_133":286,"_135":38,"_136":-5,"_186":287,"_94":288},{"_20":273,"_13":274,"_123":275,"_124":154,"_125":21,"_126":276,"_128":50,"_22":277,"_29":142,"_131":196,"_133":278,"_135":38,"_136":-5,"_186":279,"_94":280},{"_20":265,"_13":266,"_123":267,"_124":154,"_125":21,"_126":268,"_128":50,"_22":269,"_29":142,"_131":196,"_133":270,"_135":38,"_136":-5,"_186":271,"_94":272},{"_20":145,"_13":146,"_123":147,"_124":-5,"_125":21,"_126":148,"_128":50,"_22":262,"_29":54,"_131":150,"_133":-5,"_135":38,"_136":-5,"_186":263,"_94":264},{"_20":258,"_13":217,"_123":211,"_124":147,"_125":21,"_126":237,"_128":50,"_22":259,"_29":54,"_131":150,"_133":-5,"_135":38,"_136":-5,"_186":260,"_94":261},{"_20":250,"_13":251,"_123":252,"_124":211,"_125":21,"_126":253,"_128":50,"_22":254,"_29":54,"_131":196,"_133":255,"_135":38,"_136":-5,"_186":256,"_94":257},{"_20":242,"_13":243,"_123":244,"_124":211,"_125":21,"_126":245,"_128":50,"_22":246,"_29":54,"_131":196,"_133":247,"_135":38,"_136":-5,"_186":248,"_94":249},{"_20":234,"_13":235,"_123":236,"_124":211,"_125":21,"_126":237,"_128":50,"_22":238,"_29":54,"_131":196,"_133":239,"_135":38,"_136":-5,"_186":240,"_94":241},{"_20":226,"_13":227,"_123":228,"_124":211,"_125":21,"_126":229,"_128":50,"_22":230,"_29":54,"_131":196,"_133":231,"_135":38,"_136":-5,"_186":232,"_94":233},{"_20":218,"_13":219,"_123":220,"_124":211,"_125":21,"_126":221,"_128":50,"_22":222,"_29":54,"_131":196,"_133":223,"_135":38,"_136":-5,"_186":224,"_94":225},{"_20":208,"_13":209,"_123":210,"_124":211,"_125":21,"_126":212,"_128":50,"_22":213,"_29":54,"_131":196,"_133":214,"_135":38,"_136":-5,"_186":215,"_94":216},{"_20":200,"_13":201,"_123":202,"_124":147,"_125":21,"_126":203,"_128":50,"_22":204,"_29":54,"_131":196,"_133":205,"_135":38,"_136":-5,"_186":206,"_94":207},{"_20":192,"_13":193,"_123":194,"_124":147,"_125":21,"_126":148,"_128":50,"_22":195,"_29":54,"_131":196,"_133":197,"_135":38,"_136":-5,"_186":198,"_94":199},{"_20":138,"_13":139,"_123":140,"_124":-5,"_125":21,"_126":30,"_128":50,"_22":189,"_29":142,"_131":106,"_133":143,"_135":38,"_136":-5,"_186":190,"_94":191},{"_20":121,"_13":122,"_123":48,"_124":-5,"_125":21,"_126":127,"_128":50,"_22":185,"_29":130,"_131":132,"_133":134,"_135":38,"_136":-5,"_186":187,"_94":188},["D",1784108607910],"children",[],[122],["D",1784108646298],[],[139],"d5841b54-c6e6-4160-b6da-41ccabe13ab6","components.tsx","194b66ae-8031-11f1-a5fb-1607ee4eb77e",["D",1784108379032],"script","import React from \"https://esm.sh/react@18.2.0\";\n\n// ─── Button ───────────────────────────────────────────────────────────\nexport function Button({\n children,\n onClick,\n variant = \"primary\",\n size = \"md\",\n disabled,\n className = \"\",\n type = \"button\",\n}: {\n children: React.ReactNode;\n onClick?: () => void;\n variant?: \"primary\" | \"secondary\" | \"ghost\" | \"danger\";\n size?: \"sm\" | \"md\" | \"lg\";\n disabled?: boolean;\n className?: string;\n type?: \"button\" | \"submit\";\n}) {\n const variants: Record = {\n primary: \"bg-indigo-600 hover:bg-indigo-500 text-white shadow-lg shadow-indigo-600/20\",\n secondary: \"bg-slate-800 hover:bg-slate-700 text-slate-200 border border-slate-700\",\n ghost: \"hover:bg-slate-800 text-slate-300\",\n danger: \"bg-red-600 hover:bg-red-500 text-white\",\n };\n const sizes: Record = {\n sm: \"px-3 py-1.5 text-sm\",\n md: \"px-4 py-2.5 text-sm\",\n lg: \"px-6 py-3 text-base\",\n };\n return (\n \n {children}\n \n );\n}\n\n// ─── Card ─────────────────────────────────────────────────────────────\nexport function Card({ children, className = \"\" }: { children: React.ReactNode; className?: string }) {\n return (\n

\n {children}\n

\n );\n}\n\n// ─── Input ────────────────────────────────────────────────────────────\nexport function Input({\n label,\n type = \"text\",\n value,\n onChange,\n placeholder,\n required,\n className = \"\",\n}: {\n label?: string;\n type?: string;\n value: string;\n onChange: (v: string) => void;\n placeholder?: string;\n required?: boolean;\n className?: string;\n}) {\n return (\n

\n {label && {label}}\n onChange(e.target.value)}\n placeholder={placeholder}\n required={required}\n className=\"w-full bg-slate-950 border border-slate-700 rounded-lg px-4 py-2.5 text-slate-100 placeholder-slate-500 focus:outline-none focus:border-indigo-500 focus:ring-1 focus:ring-indigo-500 transition-colors\"\n />\n

\n );\n}\n\n// ─── Textarea ─────────────────────────────────────────────────────────\nexport function Textarea({\n label,\n value,\n onChange,\n placeholder,\n rows = 5,\n className = \"\",\n}: {\n label?: string;\n value: string;\n onChange: (v: string) => void;\n placeholder?: string;\n rows?: number;\n className?: string;\n}) {\n return (\n

\n {label && {label}}\n onChange(e.target.value)}\n placeholder={placeholder}\n rows={rows}\n className=\"w-full bg-slate-950 border border-slate-700 rounded-lg px-4 py-3 text-slate-100 placeholder-slate-500 focus:outline-none focus:border-indigo-500 focus:ring-1 focus:ring-indigo-500 transition-colors\"\n />\n

\n );\n}\n\n// ─── ScoreRing (circular progress indicator) ──────────────────────────\nexport function ScoreRing({ score, size = 120 }: { score: number; size?: number }) {\n const radius = (size - 16) / 2;\n const circumference = 2 * Math.PI * radius;\n const offset = circumference - (score / 10) * circumference;\n const color = score >= 8 ? \"#22c55e\" : score >= 6 ? \"#eab308\" : score >= 4 ? \"#f97316\" : \"#ef4444\";\n\n return (\n

\n \n

\n {score}\n / 10\n

\n );\n}\n\n// ─── Badge ────────────────────────────────────────────────────────────\nexport function Badge({ children, variant = \"default\" }: { children: React.ReactNode; variant?: \"default\" | \"success\" | \"warning\" | \"danger\" | \"info\" }) {\n const variants: Record = {\n default: \"bg-slate-800 text-slate-300 border-slate-700\",\n success: \"bg-green-900/40 text-green-400 border-green-800\",\n warning: \"bg-yellow-900/40 text-yellow-400 border-yellow-800\",\n danger: \"bg-red-900/40 text-red-400 border-red-800\",\n info: \"bg-indigo-900/40 text-indigo-400 border-indigo-800\",\n };\n return (\n \n {children}\n \n );\n}\n\n// ─── Spinner ──────────────────────────────────────────────────────────\nexport function Spinner({ label }: { label?: string }) {\n return (\n

\n {label && {label}}\n

\n );\n}\n\n// ─── EmptyState ───────────────────────────────────────────────────────\nexport function EmptyState({ icon, title, subtitle, action }: { icon: string; title: string; subtitle: string; action?: React.ReactNode }) {\n return (\n

{icon}

{title}

{subtitle}

\n {action}\n

\n );\n}\n\n// ─── StatCard ─────────────────────────────────────────────────────────\nexport function StatCard({ label, value, icon, color = \"indigo\" }: { label: string; value: React.ReactNode; icon: string; color?: string }) {\n const colors: Record = {\n indigo: \"from-indigo-600/20 to-indigo-900/5 text-indigo-400\",\n green: \"from-green-600/20 to-green-900/5 text-green-400\",\n yellow: \"from-yellow-600/20 to-yellow-900/5 text-yellow-400\",\n blue: \"from-blue-600/20 to-blue-900/5 text-blue-400\",\n };\n return (\n

\n {icon}\n

{value}

{label}

\n );\n}\n",[],[146,193],"d2128ed0-7d23-4094-a269-2bb84858a06f","App.tsx","86b9288e-8031-11f1-a5fb-1607ee4eb77e",15,["D",1784108562715],"import React, { useState, useEffect, useCallback } from \"https://esm.sh/react@18.2.0\";\nimport { Button } from \"./components.tsx\";\nimport Login from \"./pages/Login.tsx\";\nimport Dashboard from \"./pages/Dashboard.tsx\";\nimport NewInterview from \"./pages/NewInterview.tsx\";\nimport Interview from \"./pages/Interview.tsx\";\nimport Results from \"./pages/Results.tsx\";\nimport ResumeUpload from \"./pages/ResumeUpload.tsx\";\n\ntype Page = \"login\" | \"dashboard\" | \"new-interview\" | \"interview\" | \"results\" | \"resume\";\n\nexport default function App() {\n const [token, setToken] = useState(null);\n const [user, setUser] = useState(null);\n const [page, setPage] = useState(\"login\");\n const [pageData, setPageData] = useState(null);\n const [bootLoading, setBootLoading] = useState(true);\n\n // Restore session on mount\n useEffect(() => {\n const savedToken = localStorage.getItem(\"token\");\n const savedUser = localStorage.getItem(\"user\");\n if (savedToken && savedUser) {\n // Validate token\n fetch(\"/api/auth/me\", { headers: { Authorization: `Bearer ${savedToken}` } })\n .then((r) => {\n if (r.ok) {\n setToken(savedToken);\n setUser(JSON.parse(savedUser));\n setPage(\"dashboard\");\n } else {\n localStorage.removeItem(\"token\");\n localStorage.removeItem(\"user\");\n }\n })\n .catch(() => {})\n .finally(() => setBootLoading(false));\n } else {\n setBootLoading(false);\n }\n }, []);\n\n const navigate = useCallback((p: string, data?: any) => {\n setPage(p as Page);\n setPageData(data);\n window.scrollTo(0, 0);\n }, []);\n\n const handleAuth = (t: string, u: any) => {\n setToken(t);\n setUser(u);\n setPage(\"dashboard\");\n };\n\n const logout = () => {\n localStorage.removeItem(\"token\");\n localStorage.removeItem(\"user\");\n setToken(null);\n setUser(null);\n setPage(\"login\");\n };\n\n if (bootLoading) {\n return (\n

\n );\n }\n\n // Not authenticated\n if (!token || !user) {\n return ;\n }\n\n // Authenticated — render page with nav\n return (\n

\n {/* Top Navigation */}\n

\n navigate(\"dashboard\")}\n className=\"flex items-center gap-2 font-bold text-white hover:opacity-80 transition-opacity\"\n >\n 🎯\n AI Interview Coach\n \n\n

\n navigate(\"dashboard\")}\n className={`text-sm px-3 py-1.5 rounded-lg transition-colors ${page === \"dashboard\" ? \"bg-slate-800 text-white\" : \"text-slate-400 hover:text-slate-200\"}`}\n >\n 📊Dashboard\n \n navigate(\"resume\")}\n className={`text-sm px-3 py-1.5 rounded-lg transition-colors ${page === \"resume\" ? \"bg-slate-800 text-white\" : \"text-slate-400 hover:text-slate-200\"}`}\n >\n 📄Resume\n \n

\n {user.name?.[0]?.toUpperCase() || \"U\"}\n

\n \n \n

\n\n {/* Page Content */}\n

\n {page === \"dashboard\" && }\n {page === \"new-interview\" && }\n {page === \"interview\" && pageData && }\n {page === \"results\" && pageData && }\n {page === \"resume\" && }\n

\n\n {/* Footer */}\n \n

\n );\n}\n",[],[146,201],"2a0eeede-fb83-4822-8e02-aa148cfad76a","ResumeUpload.tsx","7f1388d6-8031-11f1-81d0-1607ee4eb77e","a1f7b1a1-b6ac-45fc-a677-a41ebec81e22",14,["D",1784108549887],"import React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport { Card, Button, Input, Textarea, Spinner } from \"../components.tsx\";\n\nexport default function ResumeUpload({ token, navigate }: { token: string; navigate: (page: string, data?: any) => void }) {\n const [filename, setFilename] = useState(\"\");\n const [content, setContent] = useState(\"\");\n const [loading, setLoading] = useState(false);\n const [error, setError] = useState(\"\");\n const [success, setSuccess] = useState(false);\n\n const handleFile = async (e: React.ChangeEvent) => {\n const file = e.target.files?.[0];\n if (!file) return;\n setFilename(file.name);\n setError(\"\");\n\n if (file.size > 50000) {\n setError(\"File too large (max 50KB). Please paste your resume text manually.\");\n return;\n }\n\n const text = await file.text();\n setContent(text);\n };\n\n const upload = async () => {\n if (!filename || !content) {\n setError(\"Please provide a filename and resume content\");\n return;\n }\n setLoading(true);\n setError(\"\");\n\n try {\n const res = await fetch(\"/api/resume/upload\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\", Authorization: `Bearer ${token}` },\n body: JSON.stringify({ filename, content }),\n });\n const data = await res.json();\n if (!res.ok) {\n setError(data.error || \"Upload failed\");\n setLoading(false);\n return;\n }\n setSuccess(true);\n setTimeout(() => navigate(\"dashboard\"), 1500);\n } catch (e) {\n setError(\"Network error. Please try again.\");\n setLoading(false);\n }\n };\n\n return (\n

\n \n\n

📄 Upload Resume

Paste your resume text or upload a .txt file. We'll use it to generate personalized interview questions.

\n\n \n {/* File Upload */}\n

\n Upload File\n \n

📁

\n Click to select a .txt file\n Max 50KB\n \n \n

\n\n

— or —

\n\n {/* Manual Entry */}\n \n \n\n

{content.length} characters

\n\n {error && (\n

{error}

\n )}\n\n {success && (\n

\n ✅ Resume uploaded successfully! Redirecting...\n

\n )}\n\n \n \n

\n );\n}\n",[],[146,217,209],"pages","ef52ca78-c21b-4cc2-b0fc-74e8cf1d8dc4","Results.tsx","6e583f5a-8031-11f1-8900-1607ee4eb77e",13,["D",1784108521700],"import React, { useState, useEffect } from \"https://esm.sh/react@18.2.0\";\nimport { Card, Button, Badge, ScoreRing, Spinner, EmptyState } from \"../components.tsx\";\n\nexport default function Results({ token, data, navigate }: { token: string; data: any; navigate: (page: string, data?: any) => void }) {\n const [sessionData, setSessionData] = useState(null);\n const [loading, setLoading] = useState(true);\n\n useEffect(() => {\n fetch(`/api/sessions/${data.sessionId}`, {\n headers: { Authorization: `Bearer ${token}` },\n })\n .then((r) => r.json())\n .then((d) => {\n setSessionData(d);\n setLoading(false);\n });\n }, [token, data.sessionId]);\n\n if (loading) return ;\n\n const { session, questions, avgScore, totalAnswered } = sessionData;\n const scoreColor = avgScore >= 8 ? \"#22c55e\" : avgScore >= 6 ? \"#eab308\" : avgScore >= 4 ? \"#f97316\" : \"#ef4444\";\n const scoreLabel = avgScore >= 8 ? \"Excellent!\" : avgScore >= 6 ? \"Good Job!\" : avgScore >= 4 ? \"Keep Practicing\" : \"Needs Work\";\n\n return (\n

\n \n\n {/* Summary Header */}\n \n

{session.role} — Session Results

\n {session.difficulty}\n \n {session.status === \"completed\" ? \"Completed\" : \"In Progress\"}\n \n

\n\n

\n {avgScore !== null && avgScore !== undefined ? (\n

\n \n {scoreLabel}\n

\n ) : (\n

No answers submitted yet.

\n )}\n\n

\n 📝\n

{questions.length}

Total Questions

\n 💬\n

{totalAnswered}

Answered

\n\n

\n \n \n

\n \n\n {/* Question-by-Question Breakdown */}\n

📋 Question Breakdown

\n {questions.map((q: any, idx: number) => (\n \n

\n {idx + 1}\n

\n {q.category}\n \n {q.difficulty}\n \n {q.score !== null && q.score !== undefined && (\n = 8 ? \"success\" : q.score >= 6 ? \"warning\" : \"danger\"}>\n Score: {q.score}/10\n \n )}\n

\n\n

{q.question_text}

\n\n {q.answer_text ? (\n

Your Answer:

{q.answer_text}

\n\n {q.feedback && (\n

💬 {q.feedback}

\n {q.strengths &&

✅ {q.strengths}

}\n {q.improvements &&

💡 {q.improvements}

}\n

\n )}\n

\n ) : (\n

Not answered

\n )}\n

\n \n ))}\n

\n );\n}\n",[],[146,217,219],"f67a7075-d6f6-4489-bfc9-57949983c07f","NewInterview.tsx","566d33dc-8031-11f1-9d2e-1607ee4eb77e",11,["D",1784108481687],"import React, { useState, useEffect } from \"https://esm.sh/react@18.2.0\";\nimport { Card, Button, Input, Badge, Spinner } from \"../components.tsx\";\n\nconst ROLES = [\n \"Software Engineer\", \"Frontend Developer\", \"Backend Developer\", \"Full Stack Developer\",\n \"Data Scientist\", \"Product Manager\", \"DevOps Engineer\", \"Engineering Manager\",\n \"UX Designer\", \"ML Engineer\", \"Security Engineer\", \"QA Engineer\",\n];\n\nexport default function NewInterview({ token, navigate }: { token: string; navigate: (page: string, data?: any) => void }) {\n const [role, setRole] = useState(\"\");\n const [customRole, setCustomRole] = useState(\"\");\n const [difficulty, setDifficulty] = useState(\"medium\");\n const [questionCount, setQuestionCount] = useState(5);\n const [resumes, setResumes] = useState([]);\n const [selectedResume, setSelectedResume] = useState(null);\n const [loading, setLoading] = useState(false);\n const [error, setError] = useState(\"\");\n\n useEffect(() => {\n fetch(\"/api/resume/list\", { headers: { Authorization: `Bearer ${token}` } })\n .then((r) => r.json())\n .then((data) => setResumes(data.resumes || []));\n }, [token]);\n\n const startSession = async () => {\n const finalRole = role || customRole;\n if (!finalRole) {\n setError(\"Please select or enter a role\");\n return;\n }\n setLoading(true);\n setError(\"\");\n\n try {\n const res = await fetch(\"/api/sessions/create\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\", Authorization: `Bearer ${token}` },\n body: JSON.stringify({\n role: finalRole,\n difficulty,\n resumeId: selectedResume,\n questionCount,\n }),\n });\n const data = await res.json();\n if (!res.ok) {\n setError(data.error || \"Failed to create session\");\n setLoading(false);\n return;\n }\n navigate(\"interview\", { session: data.session, questions: data.questions });\n } catch (e) {\n setError(\"Network error. Please try again.\");\n setLoading(false);\n }\n };\n\n return (\n

\n \n

New Interview Session

Configure your practice session and let AI generate tailored questions.

\n\n \n {/* Role Selection */}\n

\n Target Role\n

\n {ROLES.map((r) => (\n { setRole(r); setCustomRole(\"\"); }}\n className={`px-3 py-2.5 text-sm rounded-lg border transition-all ${role === r ? \"bg-indigo-600 border-indigo-500 text-white\" : \"bg-slate-950 border-slate-700 text-slate-300 hover:border-slate-600\"}`}\n >\n {r}\n \n ))}\n

\n { setCustomRole(v); setRole(\"\"); }} placeholder=\"Or enter a custom role...\" />\n

\n\n {/* Difficulty */}\n

\n Difficulty Level\n

\n {([\"easy\", \"medium\", \"hard\"] as const).map((d) => (\n setDifficulty(d)}\n className={`px-4 py-3 rounded-lg border transition-all capitalize ${difficulty === d ? \"bg-indigo-600 border-indigo-500 text-white\" : \"bg-slate-950 border-slate-700 text-slate-300 hover:border-slate-600\"}`}\n >\n {d === \"easy\" && \"🟢 \"}{d === \"medium\" && \"🟡 \"}{d === \"hard\" && \"🔴 \"}{d}\n \n ))}\n

\n\n {/* Question Count */}\n

\n Number of Questions: {questionCount}\n setQuestionCount(parseInt(e.target.value))}\n className=\"w-full accent-indigo-500\"\n />\n

\n 3 (Quick)10 (Thorough)\n

\n\n {/* Resume Selection */}\n {resumes.length > 0 && (\n

\n Attach Resume (Optional)\n setSelectedResume(e.target.value ? parseInt(e.target.value) : null)}\n className=\"w-full bg-slate-950 border border-slate-700 rounded-lg px-4 py-2.5 text-slate-100 focus:outline-none focus:border-indigo-500\"\n >\n \n {resumes.map((r: any) => (\n \n ))}\n \n

📎 Attaching a resume generates personalized questions based on your experience.

\n )}\n\n {resumes.length === 0 && (\n

\n 💡 Upload a resume for personalized questions\n \n

\n )}\n\n {error && (\n

{error}

\n )}\n\n \n \n

\n );\n}\n",[],[146,217,227],"dce57697-9eef-4c40-ac43-e4b5ca14e79e","Login.tsx","354bbfd4-8031-11f1-a328-1607ee4eb77e",9,["D",1784108426095],"import React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport { Button, Input, Card } from \"../components.tsx\";\n\nexport default function Login({ onAuth }: { onAuth: (token: string, user: any) => void }) {\n const [mode, setMode] = useState<\"login\" | \"register\">(\"login\");\n const [email, setEmail] = useState(\"\");\n const [password, setPassword] = useState(\"\");\n const [name, setName] = useState(\"\");\n const [error, setError] = useState(\"\");\n const [loading, setLoading] = useState(false);\n\n const handleSubmit = async (e: React.FormEvent) => {\n e.preventDefault();\n setError(\"\");\n setLoading(true);\n\n try {\n const endpoint = mode === \"login\" ? \"/api/auth/login\" : \"/api/auth/register\";\n const body = mode === \"login\" ? { email, password } : { email, password, name };\n const res = await fetch(endpoint, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify(body),\n });\n const data = await res.json();\n\n if (!res.ok) {\n setError(data.error || \"Something went wrong\");\n setLoading(false);\n return;\n }\n\n localStorage.setItem(\"token\", data.token);\n localStorage.setItem(\"user\", JSON.stringify(data.user));\n onAuth(data.token, data.user);\n } catch (e) {\n setError(\"Network error. Please try again.\");\n setLoading(false);\n }\n };\n\n return (\n

🎯

AI Interview Coach

Practice smarter. Land your dream job.

\n\n \n

\n { setMode(\"login\"); setError(\"\"); }}\n className={`flex-1 py-2 rounded-md text-sm font-medium transition-colors ${mode === \"login\" ? \"bg-indigo-600 text-white\" : \"text-slate-400 hover:text-slate-200\"}`}\n >\n Sign In\n \n { setMode(\"register\"); setError(\"\"); }}\n className={`flex-1 py-2 rounded-md text-sm font-medium transition-colors ${mode === \"register\" ? \"bg-indigo-600 text-white\" : \"text-slate-400 hover:text-slate-200\"}`}\n >\n Sign Up\n \n

\n\n \n \n\n

\n By continuing, you agree to our Terms of Service and Privacy Policy.\n

\n );\n}\n",[],[146,217,235],"4a53babf-05de-47ed-9ced-3dc5103bda4d","Interview.tsx","65b5324a-8031-11f1-b2a0-1607ee4eb77e",12,["D",1784108507324],"import React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport { Card, Button, Textarea, Badge, ScoreRing, Spinner } from \"../components.tsx\";\n\nexport default function Interview({ token, data, navigate }: { token: string; data: any; navigate: (page: string, data?: any) => void }) {\n const { session, questions } = data;\n const [currentIdx, setCurrentIdx] = useState(0);\n const [answers, setAnswers] = useState>({});\n const [results, setResults] = useState>({});\n const [submitting, setSubmitting] = useState(false);\n const [showFeedback, setShowFeedback] = useState(false);\n\n const currentQuestion = questions[currentIdx];\n const isLastQuestion = currentIdx === questions.length - 1;\n const answeredCount = Object.keys(results).length;\n\n const submitAnswer = async () => {\n const answer = answers[currentQuestion.id] || \"\";\n if (answer.trim().length < 10) return;\n\n setSubmitting(true);\n setShowFeedback(false);\n\n try {\n const res = await fetch(`/api/sessions/${session.id}/answer`, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\", Authorization: `Bearer ${token}` },\n body: JSON.stringify({ questionId: currentQuestion.id, answer }),\n });\n const data = await res.json();\n if (res.ok) {\n setResults({ ...results, [currentQuestion.id]: data });\n setShowFeedback(true);\n }\n } catch (e) {\n console.error(\"Submit error:\", e);\n }\n setSubmitting(false);\n };\n\n const nextQuestion = () => {\n setShowFeedback(false);\n if (isLastQuestion) {\n completeSession();\n } else {\n setCurrentIdx(currentIdx + 1);\n }\n };\n\n const completeSession = async () => {\n await fetch(`/api/sessions/${session.id}/complete`, {\n method: \"POST\",\n headers: { Authorization: `Bearer ${token}` },\n });\n navigate(\"results\", { sessionId: session.id });\n };\n\n return (\n

\n {/* Header */}\n

\n \n

{session.role} Interview

\n {session.difficulty}\n Question {currentIdx + 1} of {questions.length}\n

\n {answeredCount}/{questions.length} answered\n

\n\n {/* Progress Bar */}\n

\n \n

\n\n {/* Question Card */}\n \n

\n ❓\n

\n {currentQuestion.category}\n \n {currentQuestion.difficulty}\n \n

{currentQuestion.question_text}

\n \n\n {/* Answer Area */}\n \n setAnswers({ ...answers, [currentQuestion.id]: v })}\n placeholder=\"Type your answer here. Use the STAR method: Situation, Task, Action, Result. Be specific and include metrics where possible.\"\n rows={8}\n />\n

\n \n {(answers[currentQuestion.id] || \"\").trim().split(/\\s+/).filter(Boolean).length} words\n {(answers[currentQuestion.id] || \"\").trim().length < 10 && \" — at least 10 characters required\"}\n \n \n

\n \n\n {/* Feedback */}\n {showFeedback && results[currentQuestion.id] && (\n \n

\n \n Your Score\n

📊 AI Feedback

{results[currentQuestion.id].feedback}

\n\n {results[currentQuestion.id].strengths && (\n

✅ Strengths

{results[currentQuestion.id].strengths}

\n )}\n\n {results[currentQuestion.id].improvements && (\n

💡 Areas to Improve

{results[currentQuestion.id].improvements}

\n )}\n

\n\n

\n \n \n

\n \n )}\n\n {/* Question Navigator */}\n

\n {questions.map((q: any, idx: number) => (\n { setCurrentIdx(idx); setShowFeedback(!!results[q.id]); }}\n className={`w-9 h-9 rounded-lg text-sm font-medium transition-all ${\n idx === currentIdx\n ? \"bg-indigo-600 text-white\"\n : results[q.id]\n ? \"bg-green-900/40 text-green-400 border border-green-800\"\n : \"bg-slate-800 text-slate-400 border border-slate-700\"\n }`}\n >\n {idx + 1}\n \n ))}\n

\n );\n}\n",[],[146,217,243],"47667314-13bd-4632-b8f0-4d37c2eefd0b","Dashboard.tsx","45aef90e-8031-11f1-81d0-1607ee4eb77e",10,["D",1784108453591],"import React, { useState, useEffect, useCallback } from \"https://esm.sh/react@18.2.0\";\nimport { Card, Button, Badge, StatCard, EmptyState, Spinner } from \"../components.tsx\";\n\nexport default function Dashboard({ token, user, navigate }: { token: string; user: any; navigate: (page: string, data?: any) => void }) {\n const [stats, setStats] = useState(null);\n const [sessions, setSessions] = useState([]);\n const [resumes, setResumes] = useState([]);\n const [loading, setLoading] = useState(true);\n const [tab, setTab] = useState<\"overview\" | \"sessions\" | \"resumes\">(\"overview\");\n\n const api = useCallback((path: string, opts: any = {}) => {\n return fetch(path, {\n ...opts,\n headers: { ...opts.headers, Authorization: `Bearer ${token}` },\n }).then((r) => r.json());\n }, [token]);\n\n useEffect(() => {\n Promise.all([\n api(\"/api/sessions/stats/dashboard\"),\n api(\"/api/sessions/list\"),\n api(\"/api/resume/list\"),\n ]).then(([s, sess, res]) => {\n setStats(s);\n setSessions(sess.sessions || []);\n setResumes(res.resumes || []);\n setLoading(false);\n });\n }, [api]);\n\n const deleteResume = async (id: number) => {\n if (!confirm(\"Delete this resume?\")) return;\n await api(`/api/resume/${id}`, { method: \"DELETE\" });\n setResumes(resumes.filter((r) => r.id !== id));\n };\n\n if (loading) return ;\n\n return (\n

\n {/* Header */}\n

Welcome back, {user.name} 👋

Ready to crush your next interview?

\n \n

\n\n {/* Stats Grid */}\n

\n \n \n \n \n

\n\n {/* Tabs */}\n

\n {([\"overview\", \"sessions\", \"resumes\"] as const).map((t) => (\n setTab(t)}\n className={`px-4 py-2.5 text-sm font-medium border-b-2 transition-colors ${tab === t ? \"border-indigo-500 text-indigo-400\" : \"border-transparent text-slate-400 hover:text-slate-200\"}`}\n >\n {t === \"overview\" ? \"Recent Sessions\" : t === \"sessions\" ? \"All Sessions\" : \"My Resumes\"}\n \n ))}\n

\n\n {/* Tab Content */}\n {tab === \"overview\" || tab === \"sessions\" ? (\n sessions.length === 0 ? (\n navigate(\"new-interview\")}>Start Your First Session}\n />\n ) : (\n

\n {sessions.slice(0, tab === \"overview\" ? 5 : 100).map((s: any) => (\n \n

navigate(\"results\", { sessionId: s.id })}>\n

\n {s.status === \"completed\" ? \"✅\" : \"🎤\"}\n

{s.role}

\n \n {s.difficulty}\n \n {s.answered_questions || 0}/{s.total_questions || 0} answered\n {s.avg_score && ★ {s.avg_score}}\n

\n \n \n

\n \n ))}\n

\n )\n ) : (\n /* Resumes Tab */\n

\n {resumes.length === 0 ? (\n navigate(\"resume\")}>Upload Resume}\n />\n ) : (\n

\n {resumes.map((r: any) => (\n \n

📄

{r.filename}

\n {new Date(r.uploaded_at).toLocaleDateString()}\n

\n \n \n ))}\n

\n \n

\n )}\n

\n );\n}\n",[],[146,217,251],"6815cdf0-5823-456c-80b8-ed92ded64f01",["D",1784108426095],[175,176,177,178,179,180],[146,217],["D",1784108379032],[174,181,182],[146],"78162972-3589-4481-a308-04eca4d98a07","sessions.ts","eb16212a-8030-11f1-9d9e-1607ee4eb77e",21,["D",1784108596503],"import { Hono } from \"npm:hono\";\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { getAuthUser } from \"./auth.ts\";\nimport { generateQuestions, scoreAnswer } from \"./ai.ts\";\n\nconst sessions = new Hono();\n\n// Create a new interview session with auto-generated questions\nsessions.post(\"/create\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const body = await c.req.json();\n const { role, difficulty, resumeId, questionCount } = body;\n\n if (!role) {\n return c.json({ error: \"Role is required\" }, 400);\n }\n\n const diff = difficulty || \"medium\";\n const count = Math.min(10, Math.max(3, questionCount || 5));\n\n // Fetch resume content if provided\n let resumeText: string | null = null;\n if (resumeId) {\n const resumeResult = await sqlite.execute({\n sql: \"SELECT content FROM resumes WHERE id = ? AND user_id = ?\",\n args: [resumeId, user.id],\n });\n if (resumeResult.rows.length > 0) {\n resumeText = (resumeResult.rows[0] as { content: string }).content;\n }\n }\n\n // Create session\n const sessionResult = await sqlite.execute({\n sql: \"INSERT INTO sessions (user_id, resume_id, role, difficulty) VALUES (?, ?, ?, ?)\",\n args: [user.id, resumeId || null, role, diff],\n });\n const sessionId = Number(sessionResult.lastInsertRowid);\n\n // Generate questions\n const questions = await generateQuestions(role, diff, resumeText, count);\n\n // Insert questions\n for (let i = 0; i < questions.length; i++) {\n await sqlite.execute({\n sql: \"INSERT INTO questions (session_id, question_text, category, difficulty, order_idx) VALUES (?, ?, ?, ?, ?)\",\n args: [sessionId, questions[i].question, questions[i].category, questions[i].difficulty, i],\n });\n }\n\n // Fetch inserted questions with IDs\n const qResult = await sqlite.execute({\n sql: \"SELECT id, question_text, category, difficulty, order_idx FROM questions WHERE session_id = ? ORDER BY order_idx\",\n args: [sessionId],\n });\n\n return c.json({\n session: {\n id: sessionId,\n role,\n difficulty: diff,\n status: \"in_progress\",\n },\n questions: qResult.rows,\n });\n});\n\n// List user's sessions\nsessions.get(\"/list\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const result = await sqlite.execute({\n sql: `SELECT s.id, s.role, s.difficulty, s.status, s.created_at, s.completed_at,\n (SELECT COUNT(*) FROM questions q WHERE q.session_id = s.id) as total_questions,\n (SELECT COUNT(*) FROM answers a JOIN questions q ON a.question_id = q.id WHERE q.session_id = s.id) as answered_questions,\n (SELECT ROUND(AVG(a.score), 1) FROM answers a JOIN questions q ON a.question_id = q.id WHERE q.session_id = s.id) as avg_score\n FROM sessions s WHERE s.user_id = ? ORDER BY s.created_at DESC`,\n args: [user.id],\n });\n\n return c.json({ sessions: result.rows });\n});\n\n// Get session details with questions and answers\nsessions.get(\"/:id\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const id = parseInt(c.req.param(\"id\"));\n const sessionResult = await sqlite.execute({\n sql: \"SELECT * FROM sessions WHERE id = ? AND user_id = ?\",\n args: [id, user.id],\n });\n\n if (sessionResult.rows.length === 0) {\n return c.json({ error: \"Session not found\" }, 404);\n }\n\n const questionsResult = await sqlite.execute({\n sql: `SELECT q.id, q.question_text, q.category, q.difficulty, q.order_idx,\n a.id as answer_id, a.answer_text, a.score, a.feedback, a.strengths, a.improvements\n FROM questions q\n LEFT JOIN answers a ON a.question_id = q.id\n WHERE q.session_id = ? ORDER BY q.order_idx`,\n args: [id],\n });\n\n const answersResult = await sqlite.execute({\n sql: `SELECT a.score FROM answers a JOIN questions q ON a.question_id = q.id WHERE q.session_id = ?`,\n args: [id],\n });\n\n const scores = answersResult.rows.map((r) => (r as { score: number }).score).filter((s) => s !== null);\n const avgScore = scores.length > 0 ? (scores.reduce((a, b) => a + b, 0) / scores.length).toFixed(1) : null;\n\n return c.json({\n session: sessionResult.rows[0],\n questions: questionsResult.rows,\n avgScore: avgScore ? parseFloat(avgScore) : null,\n totalAnswered: scores.length,\n });\n});\n\n// Submit answer for a question\nsessions.post(\"/:id/answer\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const sessionId = parseInt(c.req.param(\"id\"));\n const body = await c.req.json();\n const { questionId, answer } = body;\n\n if (!questionId || !answer || answer.trim().length < 10) {\n return c.json({ error: \"Question ID and a meaningful answer (at least 10 characters) are required\" }, 400);\n }\n\n // Verify question belongs to user's session\n const qResult = await sqlite.execute({\n sql: `SELECT q.id, q.question_text, s.role FROM questions q\n JOIN sessions s ON q.session_id = s.id\n WHERE q.id = ? AND s.id = ? AND s.user_id = ?`,\n args: [questionId, sessionId, user.id],\n });\n\n if (qResult.rows.length === 0) {\n return c.json({ error: \"Question not found\" }, 404);\n }\n\n const question = qResult.rows[0] as { id: number; question_text: string; role: string };\n\n // Check if answer already exists — update if so\n const existingAnswer = await sqlite.execute({\n sql: \"SELECT id FROM answers WHERE question_id = ?\",\n args: [questionId],\n });\n\n // Score the answer\n const scoring = await scoreAnswer(question.question_text, answer, question.role);\n\n if (existingAnswer.rows.length > 0) {\n await sqlite.execute({\n sql: \"UPDATE answers SET answer_text = ?, score = ?, feedback = ?, strengths = ?, improvements = ? WHERE question_id = ?\",\n args: [answer, scoring.score, scoring.feedback, scoring.strengths, scoring.improvements, questionId],\n });\n } else {\n await sqlite.execute({\n sql: \"INSERT INTO answers (question_id, answer_text, score, feedback, strengths, improvements) VALUES (?, ?, ?, ?, ?, ?)\",\n args: [questionId, answer, scoring.score, scoring.feedback, scoring.strengths, scoring.improvements],\n });\n }\n\n return c.json({\n score: scoring.score,\n feedback: scoring.feedback,\n strengths: scoring.strengths,\n improvements: scoring.improvements,\n });\n});\n\n// Complete a session\nsessions.post(\"/:id/complete\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const id = parseInt(c.req.param(\"id\"));\n await sqlite.execute({\n sql: \"UPDATE sessions SET status = 'completed', completed_at = datetime('now') WHERE id = ? AND user_id = ?\",\n args: [id, user.id],\n });\n\n // Get final stats\n const result = await sqlite.execute({\n sql: `SELECT s.role, s.difficulty,\n (SELECT COUNT(*) FROM questions q WHERE q.session_id = s.id) as total_questions,\n (SELECT ROUND(AVG(a.score), 1) FROM answers a JOIN questions q ON a.question_id = q.id WHERE q.session_id = s.id) as avg_score\n FROM sessions s WHERE s.id = ?`,\n args: [id],\n });\n\n return c.json({ result: result.rows[0] });\n});\n\n// Get dashboard stats\nsessions.get(\"/stats/dashboard\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const sessionCount = await sqlite.execute({\n sql: \"SELECT COUNT(*) as count FROM sessions WHERE user_id = ?\",\n args: [user.id],\n });\n\n const completedCount = await sqlite.execute({\n sql: \"SELECT COUNT(*) as count FROM sessions WHERE user_id = ? AND status = 'completed'\",\n args: [user.id],\n });\n\n const avgScore = await sqlite.execute({\n sql: `SELECT ROUND(AVG(a.score), 1) as avg FROM answers a\n JOIN questions q ON a.question_id = q.id\n JOIN sessions s ON q.session_id = s.id\n WHERE s.user_id = ?`,\n args: [user.id],\n });\n\n const questionCount = await sqlite.execute({\n sql: `SELECT COUNT(*) as count FROM answers a\n JOIN questions q ON a.question_id = q.id\n JOIN sessions s ON q.session_id = s.id\n WHERE s.user_id = ?`,\n args: [user.id],\n });\n\n return c.json({\n totalSessions: (sessionCount.rows[0] as { count: number }).count,\n completedSessions: (completedCount.rows[0] as { count: number }).count,\n avgScore: (avgScore.rows[0] as { avg: number | null }).avg,\n totalQuestionsAnswered: (questionCount.rows[0] as { count: number }).count,\n });\n});\n\nexport default sessions;\n",[],[153,266],"5a035704-9d84-41be-bbfb-3ada26401de9","resume.ts","eb1c372c-8030-11f1-b5de-1607ee4eb77e",20,["D",1784108596505],"import { Hono } from \"npm:hono\";\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { getAuthUser } from \"./auth.ts\";\n\nconst resume = new Hono();\n\n// Upload resume (text content or file text extraction)\nresume.post(\"/upload\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const body = await c.req.json();\n const { filename, content } = body;\n\n if (!content || !filename) {\n return c.json({ error: \"Filename and content are required\" }, 400);\n }\n\n if (content.length > 50000) {\n return c.json({ error: \"Resume content too large (max 50KB)\" }, 400);\n }\n\n const result = await sqlite.execute({\n sql: \"INSERT INTO resumes (user_id, filename, content) VALUES (?, ?, ?)\",\n args: [user.id, filename, content],\n });\n\n const resumeId = Number(result.lastInsertRowid);\n return c.json({\n id: resumeId,\n filename,\n uploaded_at: new Date().toISOString(),\n preview: content.slice(0, 200) + (content.length > 200 ? \"...\" : \"\"),\n });\n});\n\n// List user's resumes\nresume.get(\"/list\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const result = await sqlite.execute({\n sql: \"SELECT id, filename, uploaded_at, substr(content, 1, 200) as preview FROM resumes WHERE user_id = ? ORDER BY uploaded_at DESC\",\n args: [user.id],\n });\n\n return c.json({ resumes: result.rows });\n});\n\n// Get resume content\nresume.get(\"/:id\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const id = c.req.param(\"id\");\n const result = await sqlite.execute({\n sql: \"SELECT id, filename, content, uploaded_at FROM resumes WHERE id = ? AND user_id = ?\",\n args: [parseInt(id), user.id],\n });\n\n if (result.rows.length === 0) {\n return c.json({ error: \"Resume not found\" }, 404);\n }\n\n return c.json({ resume: result.rows[0] });\n});\n\n// Delete resume\nresume.delete(\"/:id\", async (c) => {\n const user = await getAuthUser(c.req.raw);\n if (!user) return c.json({ error: \"Unauthorized\" }, 401);\n\n const id = c.req.param(\"id\");\n await sqlite.execute({\n sql: \"DELETE FROM resumes WHERE id = ? AND user_id = ?\",\n args: [parseInt(id), user.id],\n });\n\n return c.json({ success: true });\n});\n\nexport default resume;\n",[],[153,274],"8ac156d7-ebc1-4b92-a435-380b927b1496","db.ts","d3c76d94-8030-11f1-b5de-1607ee4eb77e",3,["D",1784108262491],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nexport async function initDB() {\n await sqlite.batch([\n {\n sql: `CREATE TABLE IF NOT EXISTS users (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n email TEXT UNIQUE NOT NULL,\n password_hash TEXT NOT NULL,\n name TEXT NOT NULL,\n created_at TEXT DEFAULT (datetime('now'))\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS resumes (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n user_id INTEGER NOT NULL,\n filename TEXT NOT NULL,\n content TEXT NOT NULL,\n uploaded_at TEXT DEFAULT (datetime('now')),\n FOREIGN KEY (user_id) REFERENCES users(id)\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS sessions (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n user_id INTEGER NOT NULL,\n resume_id INTEGER,\n role TEXT NOT NULL,\n difficulty TEXT DEFAULT 'medium',\n status TEXT DEFAULT 'in_progress',\n created_at TEXT DEFAULT (datetime('now')),\n completed_at TEXT,\n FOREIGN KEY (user_id) REFERENCES users(id),\n FOREIGN KEY (resume_id) REFERENCES resumes(id)\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS questions (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n session_id INTEGER NOT NULL,\n question_text TEXT NOT NULL,\n category TEXT NOT NULL,\n difficulty TEXT NOT NULL,\n order_idx INTEGER DEFAULT 0,\n FOREIGN KEY (session_id) REFERENCES sessions(id)\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS answers (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n question_id INTEGER NOT NULL,\n answer_text TEXT NOT NULL,\n score INTEGER,\n feedback TEXT,\n strengths TEXT,\n improvements TEXT,\n created_at TEXT DEFAULT (datetime('now')),\n FOREIGN KEY (question_id) REFERENCES questions(id)\n )`,\n },\n ]);\n}\n",[],[153,282],"4ba9a20f-2cc3-46f3-920f-744973aaeb72","auth.ts","d3ce57d0-8030-11f1-badd-1607ee4eb77e",19,["D",1784108596492],"import { createHmac } from \"node:crypto\";\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { initDB } from \"./db.ts\";\n\nawait initDB();\n\nfunction hashPassword(password: string): string {\n const key = Deno.env.get(\"AUTH_SECRET\") || \"ai-interview-coach-default-salt\";\n return createHmac(\"sha256\", key).update(password).digest(\"hex\");\n}\n\nexport function generateToken(userId: number, email: string): string {\n const payload = `${userId}:${email}:${Date.now()}`;\n const key = Deno.env.get(\"AUTH_SECRET\") || \"ai-interview-coach-default-salt\";\n const sig = createHmac(\"sha256\", key).update(payload).digest(\"hex\");\n return btoa(`${payload}:${sig}`);\n}\n\nexport function verifyToken(token: string): { userId: number; email: string } | null {\n try {\n const decoded = atob(token);\n const parts = decoded.split(\":\");\n const userId = parseInt(parts[0]);\n const email = parts[1];\n const timestamp = parts[2];\n const sig = parts.slice(3).join(\":\");\n\n const payload = `${userId}:${email}:${timestamp}`;\n const key = Deno.env.get(\"AUTH_SECRET\") || \"ai-interview-coach-default-salt\";\n const expectedSig = createHmac(\"sha256\", key).update(payload).digest(\"hex\");\n\n if (sig !== expectedSig) return null;\n if (Date.now() - parseInt(timestamp) > 7 * 24 * 60 * 60 * 1000) return null;\n\n return { userId, email };\n } catch {\n return null;\n }\n}\n\nexport async function register(email: string, password: string, name: string) {\n if (!email || !password || !name) {\n return { error: \"Email, password, and name are required\", status: 400 };\n }\n if (password.length < 6) {\n return { error: \"Password must be at least 6 characters\", status: 400 };\n }\n\n const existing = await sqlite.execute({\n sql: \"SELECT id FROM users WHERE email = ?\",\n args: [email.toLowerCase()],\n });\n if (existing.rows.length > 0) {\n return { error: \"Email already registered\", status: 409 };\n }\n\n const hash = hashPassword(password);\n const result = await sqlite.execute({\n sql: \"INSERT INTO users (email, password_hash, name) VALUES (?, ?, ?)\",\n args: [email.toLowerCase(), hash, name],\n });\n\n const userId = Number(result.lastInsertRowid);\n const token = generateToken(userId, email.toLowerCase());\n return { token, user: { id: userId, email: email.toLowerCase(), name } };\n}\n\nexport async function login(email: string, password: string) {\n if (!email || !password) {\n return { error: \"Email and password are required\", status: 400 };\n }\n\n const hash = hashPassword(password);\n const result = await sqlite.execute({\n sql: \"SELECT id, email, name FROM users WHERE email = ? AND password_hash = ?\",\n args: [email.toLowerCase(), hash],\n });\n\n if (result.rows.length === 0) {\n return { error: \"Invalid email or password\", status: 401 };\n }\n\n const user = result.rows[0] as { id: number; email: string; name: string };\n const token = generateToken(user.id, user.email);\n return { token, user: { id: user.id, email: user.email, name: user.name } };\n}\n\nexport async function getAuthUser(req: Request): Promise<{ id: number; email: string; name: string } | null> {\n const auth = req.headers.get(\"Authorization\");\n if (!auth || !auth.startsWith(\"Bearer \")) return null;\n const token = auth.slice(7);\n const payload = verifyToken(token);\n if (!payload) return null;\n\n const result = await sqlite.execute({\n sql: \"SELECT id, email, name FROM users WHERE id = ?\",\n args: [payload.userId],\n });\n if (result.rows.length === 0) return null;\n return result.rows[0] as { id: number; email: string; name: string };\n}\n",[],[153,290],"b2036ec3-b45d-4f0c-85c2-472796321345","ai.ts","c44a9468-8030-11f1-94af-1607ee4eb77e",["D",1784108236504],"// AI helper — uses OpenAI if OPENAI_API_KEY is set, otherwise falls back to\n// a built-in question bank and heuristic scoring.\n\nconst OPENAI_API_KEY = Deno.env.get(\"OPENAI_API_KEY\");\n\ninterface Question {\n question: string;\n category: string;\n difficulty: string;\n}\n\n// ─── Fallback Question Bank ──────────────────────────────────────────\nconst QUESTION_BANK: Record = {\n technical: [\n { question: \"Tell me about a challenging technical problem you solved recently. What was your approach?\", category: \"Problem Solving\", difficulty: \"medium\" },\n { question: \"How do you ensure code quality in your projects? Describe your testing strategy.\", category: \"Engineering Practices\", difficulty: \"medium\" },\n { question: \"Describe a time you had to learn a new technology quickly. How did you approach it?\", category: \"Adaptability\", difficulty: \"easy\" },\n { question: \"Walk me through the architecture of a system you designed. What trade-offs did you consider?\", category: \"System Design\", difficulty: \"hard\" },\n { question: \"How do you handle technical debt in a fast-moving codebase?\", category: \"Engineering Practices\", difficulty: \"hard\" },\n { question: \"Tell me about a production incident you dealt with. What was your role and how did you resolve it?\", category: \"Problem Solving\", difficulty: \"hard\" },\n ],\n behavioral: [\n { question: \"Tell me about yourself and why you're interested in this role.\", category: \"Introduction\", difficulty: \"easy\" },\n { question: \"Describe a conflict you had with a colleague and how you resolved it.\", category: \"Conflict Resolution\", difficulty: \"medium\" },\n { question: \"Tell me about a time you failed. What did you learn from it?\", category: \"Self-Awareness\", difficulty: \"medium\" },\n { question: \"Describe a situation where you had to persuade your team to adopt your idea.\", category: \"Leadership\", difficulty: \"medium\" },\n { question: \"How do you prioritize tasks when everything seems urgent?\", category: \"Time Management\", difficulty: \"easy\" },\n { question: \"Tell me about a time you went above and beyond what was expected.\", category: \"Initiative\", difficulty: \"easy\" },\n ],\n leadership: [\n { question: \"How do you mentor junior team members?\", category: \"Mentorship\", difficulty: \"medium\" },\n { question: \"Describe how you handle underperforming team members.\", category: \"People Management\", difficulty: \"hard\" },\n { question: \"Tell me about a strategic decision you made that had a significant impact.\", category: \"Strategy\", difficulty: \"hard\" },\n { question: \"How do you build trust within a newly formed team?\", category: \"Team Building\", difficulty: \"medium\" },\n ],\n general: [\n { question: \"What are your greatest strengths and how do they apply to this role?\", category: \"Self-Assessment\", difficulty: \"easy\" },\n { question: \"Where do you see yourself in five years?\", category: \"Career Goals\", difficulty: \"easy\" },\n { question: \"Why are you leaving your current position?\", category: \"Motivation\", difficulty: \"medium\" },\n { question: \"What questions do you have for us?\", category: \"Engagement\", difficulty: \"easy\" },\n { question: \"Describe your ideal work environment.\", category: \"Culture Fit\", difficulty: \"easy\" },\n { question: \"How do you stay current with developments in your field?\", category: \"Continuous Learning\", difficulty: \"medium\" },\n ],\n};\n\nexport async function generateQuestions(\n role: string,\n difficulty: string,\n resumeText: string | null,\n count: number = 5,\n): Promise {\n if (OPENAI_API_KEY) {\n try {\n return await generateQuestionsAI(role, difficulty, resumeText, count);\n } catch (e) {\n console.error(\"AI question generation failed, using fallback:\", e);\n }\n }\n return generateQuestionsFallback(role, difficulty, count);\n}\n\nasync function generateQuestionsAI(\n role: string,\n difficulty: string,\n resumeText: string | null,\n count: number,\n): Promise {\n const systemPrompt = `You are an expert interview coach. Generate exactly ${count} interview questions for a ${role} position at ${difficulty} difficulty. Return a JSON array of objects with fields: question, category, difficulty. Mix technical and behavioral questions appropriately for the role.`;\n\n const userPrompt = resumeText\n ? `Based on this resume, generate personalized interview questions:\\n\\n${resumeText.slice(0, 2000)}`\n : `Generate general interview questions for a ${role} role.`;\n\n const res = await fetch(\"https://api.openai.com/v1/chat/completions\", {\n method: \"POST\",\n headers: {\n \"Authorization\": `Bearer ${OPENAI_API_KEY}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n model: \"gpt-4o-mini\",\n messages: [\n { role: \"system\", content: systemPrompt },\n { role: \"user\", content: userPrompt },\n ],\n response_format: { type: \"json_object\" },\n temperature: 0.8,\n }),\n });\n\n if (!res.ok) throw new Error(`OpenAI API error: ${res.status}`);\n const data = await res.json();\n const content = data.choices[0].message.content;\n const parsed = JSON.parse(content);\n const questions = parsed.questions || parsed;\n return questions.slice(0, count).map((q: any) => ({\n question: q.question,\n category: q.category || \"General\",\n difficulty: q.difficulty || difficulty,\n }));\n}\n\nfunction generateQuestionsFallback(role: string, difficulty: string, count: number): Question[] {\n const categories = [\"technical\", \"behavioral\", \"general\"];\n if (role.toLowerCase().includes(\"lead\") || role.toLowerCase().includes(\"manager\")) {\n categories.push(\"leadership\");\n }\n\n let pool: Question[] = [];\n for (const cat of categories) {\n const qs = QUESTION_BANK[cat] || [];\n pool.push(...qs.filter((q) => q.difficulty === difficulty || q.difficulty === \"easy\"));\n }\n if (pool.length < count) {\n for (const cat of categories) {\n pool.push(...(QUESTION_BANK[cat] || []));\n }\n }\n\n // Shuffle and pick\n const shuffled = [...pool].sort(() => Math.random() - 0.5);\n return shuffled.slice(0, Math.min(count, shuffled.length));\n}\n\n// ─── Answer Scoring ──────────────────────────────────────────────────\nexport interface ScoreResult {\n score: number;\n feedback: string;\n strengths: string;\n improvements: string;\n}\n\nexport async function scoreAnswer(\n question: string,\n answer: string,\n role: string,\n): Promise {\n if (OPENAI_API_KEY) {\n try {\n return await scoreAnswerAI(question, answer, role);\n } catch (e) {\n console.error(\"AI scoring failed, using fallback:\", e);\n }\n }\n return scoreAnswerFallback(question, answer);\n}\n\nasync function scoreAnswerAI(\n question: string,\n answer: string,\n role: string,\n): Promise {\n const systemPrompt = `You are an expert interview coach evaluating a candidate's answer for a ${role} position. Score from 1-10 and provide constructive feedback. Return JSON with fields: score (integer 1-10), feedback (string), strengths (string), improvements (string).`;\n\n const userPrompt = `Question: ${question}\\n\\nCandidate's Answer: ${answer}\\n\\nEvaluate this answer. Consider clarity, relevance, use of specific examples, and depth. Provide actionable feedback.`;\n\n const res = await fetch(\"https://api.openai.com/v1/chat/completions\", {\n method: \"POST\",\n headers: {\n \"Authorization\": `Bearer ${OPENAI_API_KEY}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n model: \"gpt-4o-mini\",\n messages: [\n { role: \"system\", content: systemPrompt },\n { role: \"user\", content: userPrompt },\n ],\n response_format: { type: \"json_object\" },\n temperature: 0.3,\n }),\n });\n\n if (!res.ok) throw new Error(`OpenAI API error: ${res.status}`);\n const data = await res.json();\n const content = data.choices[0].message.content;\n const parsed = JSON.parse(content);\n return {\n score: Math.max(1, Math.min(10, parsed.score || 5)),\n feedback: parsed.feedback || \"\",\n strengths: parsed.strengths || \"\",\n improvements: parsed.improvements || \"\",\n };\n}\n\nfunction scoreAnswerFallback(question: string, answer: string): ScoreResult {\n const words = answer.trim().split(/\\s+/);\n const wordCount = words.length;\n const hasExample = /example|instance|when i|at my|project|situation|once|time when/i.test(answer);\n const hasStructure = /first|then|after|finally|because|so that|as a result|therefore|consequently/i.test(answer);\n const hasMetrics = /increased|decreased|reduced|improved|%\\d|\\d+%|\\d+ (hours|days|weeks|months|users|customers|percent)/i.test(answer);\n\n let score = 3;\n const strengths: string[] = [];\n const improvements: string[] = [];\n\n if (wordCount >= 50) { score += 1; strengths.push(\"Sufficient detail provided\"); }\n else { improvements.push(\"Provide more detail — aim for at least 3-4 sentences using the STAR method\"); }\n\n if (hasExample) { score += 2; strengths.push(\"Good use of specific examples\"); }\n else { improvements.push(\"Include a concrete example from your experience\"); }\n\n if (hasStructure) { score += 1; strengths.push(\"Logical structure in the response\"); }\n else { improvements.push(\"Structure your answer using STAR: Situation, Task, Action, Result\"); }\n\n if (hasMetrics) { score += 2; strengths.push(\"Excellent use of quantifiable results\"); }\n else { improvements.push(\"Add measurable outcomes (e.g., 'reduced load time by 40%')\"); }\n\n if (wordCount >= 150) { score += 1; strengths.push(\"Comprehensive response\"); }\n\n score = Math.max(1, Math.min(10, score));\n\n const feedback = score >= 8\n ? \"Excellent answer! This response is well-structured and demonstrates strong communication skills.\"\n : score >= 6\n ? \"Good answer with room for improvement. Focus on making it more specific and structured.\"\n : score >= 4\n ? \"Fair answer. Try to provide more concrete examples and quantifiable results.\"\n : \"This answer needs significant improvement. Use the STAR method and add specific examples.\";\n\n return {\n score,\n feedback,\n strengths: strengths.join(\"; \"),\n improvements: improvements.join(\"; \"),\n };\n}\n",[],[153,298],["D",1784108236504],[168,169,170,171,172],[153],["D",1784107974931],["D",1789527031073],{"_11":12,"_92":88},{"_11":12,"_85":86,"_87":88,"_45":46,"_89":90,"_91":38},{"_29":30,"_13":26,"_20":21,"_27":28,"_31":-5,"_32":-5,"_80":-5,"_81":-5,"_82":-5,"_83":14,"_84":12},"ctx",{"_73":-5,"_114":345,"_346":347,"_348":349,"_350":38,"_351":38,"_352":38,"_353":50,"_354":-5,"_355":-7,"_356":-7,"_357":54,"_358":38,"_359":38,"_360":-5,"_361":38,"_362":38,"_363":38,"_364":-5},"ENV",{"_316":317,"_318":319,"_320":26,"_321":322,"_323":324,"_325":326,"_327":328,"_329":330,"_331":332,"_333":334,"_335":336,"_337":338,"_339":340,"_341":342,"_343":344},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","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"]

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