import { Index } from "@upstash/vector"
import { personalInfo, technicalSkills, skills, workExperience, extracurricularExperience, projects, education, leadershipAchievements, references, skillsMetrics } from "../lib/resume-data"
import { readFileSync } from "fs"
import { resolve } from "path"
// Load environment variables from .env.local
try {
const envPath = resolve(process.cwd(), '.env.local')
const envContent = readFileSync(envPath, 'utf-8')
envContent.split('\n').forEach(line => {
const match = line.match(/^([^=:#]+)=(.*)$/)
if (match) {
const key = match[1].trim()
const value = match[2].trim().replace(/^["'](.*)["']$/, '$1')
process.env[key] = value
}
})
console.log("✅ Loaded environment variables from .env.local")
} catch (error) {
console.warn("⚠️ Could not load .env.local file")
}
// Initialize Upstash Vector client
function getVectorClient() {
const url = process.env.UPSTASH_VECTOR_REST_URL
const token = process.env.UPSTASH_VECTOR_REST_TOKEN
if (!url || !token) {
throw new Error("Missing Upstash Vector configuration. Please set UPSTASH_VECTOR_REST_URL and UPSTASH_VECTOR_REST_TOKEN in .env.local")
}
// Initialize with embedding model configuration
return new Index({
url,
token,
// Let the server handle embeddings automatically
})
}
async function updateVectorDatabase() {
console.log("🚀 Starting Upstash Vector Database Update...")
try {
const index = getVectorClient()
console.log("✅ Connected to Upstash Vector Database")
// Note: Not using reset() to preserve index configuration with embedding model
// Upsert will update existing IDs or add new ones
console.log("📝 Updating records (will overwrite existing IDs)...")
// Create chunks from updated resume data
const chunks: any[] = []
// Personal Info - Multiple chunks for different aspects
chunks.push({
id: "personal-info",
data: `${personalInfo.name} - ${personalInfo.title}: ${personalInfo.subtitle}. Located in ${personalInfo.location}. ${personalInfo.summary}`,
metadata: {
content: `${personalInfo.name} is a ${personalInfo.title} specializing in ${personalInfo.subtitle}. Located in ${personalInfo.location}. Contact: ${personalInfo.contact.email}, ${personalInfo.contact.phone}. ${personalInfo.summary}`,
source: "Personal Information",
category: "Overview"
}
})
chunks.push({
id: "elevator-pitch",
data: personalInfo.elevatorPitch,
metadata: {
content: `Elevator Pitch: ${personalInfo.elevatorPitch}`,
source: "Personal Information",
category: "Overview"
}
})
chunks.push({
id: "career-objective",
data: `Career Objective: ${personalInfo.careerObjective}`,
metadata: {
content: `Career path: ${personalInfo.careerObjective}`,
source: "Personal Information",
category: "Career Goals"
}
})
chunks.push({
id: "visa-status",
data: `Visa: ${personalInfo.visaStatus.current}, expires ${personalInfo.visaStatus.expiry}. Work rights: ${personalInfo.visaStatus.workRights}`,
metadata: {
content: `Visa Status: ${personalInfo.visaStatus.current} expiring ${personalInfo.visaStatus.expiry}. Work rights: ${personalInfo.visaStatus.workRights}`,
source: "Personal Information",
category: "Legal Status"
}
})
chunks.push({
id: "availability",
data: `Availability: ${personalInfo.availability.currentStatus}. Start date: ${personalInfo.availability.startDate}`,
metadata: {
content: `Availability: ${personalInfo.availability.currentStatus}. Can start: ${personalInfo.availability.startDate}. Flexible schedule: ${personalInfo.availability.flexibleSchedule}`,
source: "Personal Information",
category: "Availability"
}
})
chunks.push({
id: "salary-expectations",
data: `Salary expectations: ${personalInfo.salaryExpectations.target} ${personalInfo.salaryExpectations.currency}, minimum ${personalInfo.salaryExpectations.minimum}`,
metadata: {
content: `Salary: Target ${personalInfo.salaryExpectations.target} ${personalInfo.salaryExpectations.currency}, negotiable: ${personalInfo.salaryExpectations.negotiable}`,
source: "Personal Information",
category: "Compensation"
}
})
// Work Experience
workExperience.forEach((job, i) => {
chunks.push({
id: `work-${i}`,
data: `${job.position} at ${job.company} (${job.duration}, ${job.location}). ${job.description}`,
metadata: {
content: `${job.position} at ${job.company}, ${job.location} (${job.duration}). ${job.description} Achievements: ${job.achievements.join(". ")}`,
source: job.company,
category: "Work Experience"
}
})
})
// Extracurricular
extracurricularExperience.forEach((exp, i) => {
chunks.push({
id: `extra-${i}`,
data: `${exp.position} at ${exp.company} (${exp.duration}). ${exp.description}`,
metadata: {
content: `${exp.position} at ${exp.company}: ${exp.description} Impact: ${exp.impact}`,
source: exp.company,
category: "Leadership"
}
})
})
// Skills
skills.technical.forEach((cat, i) => {
chunks.push({
id: `skill-${i}`,
data: `${cat.category}: ${cat.skills.map(s => s.name).join(", ")}`,
metadata: {
content: `Technical skills in ${cat.category}: ${cat.skills.map(s => `${s.name} (${s.proficiency})`).join(", ")}`,
source: "Technical Skills",
category: cat.category
}
})
})
// Projects
projects.forEach((proj, i) => {
chunks.push({
id: `project-${i}`,
data: `${proj.name} - ${proj.description}`,
metadata: {
content: `Project: ${proj.name}. ${proj.description} Outcomes: ${proj.outcomes.join(". ")}`,
source: proj.name,
category: "Projects"
}
})
})
// Education
education.forEach((edu, i) => {
chunks.push({
id: `edu-${i}`,
data: `${edu.degree} from ${edu.institution}, ${edu.location}. Graduated ${edu.graduation}`,
metadata: {
content: `Education: ${edu.degree} in ${edu.field} from ${edu.institution}, ${edu.location}. Graduated ${edu.graduation}. ${edu.relevantCoursework ? 'Coursework: ' + edu.relevantCoursework.join(', ') : ''}`,
source: edu.institution,
category: "Education"
}
})
})
// Leadership Achievements
leadershipAchievements.forEach((achievement, i) => {
chunks.push({
id: `leadership-${i}`,
data: `${achievement.achievement}`,
metadata: {
content: `Leadership Achievement: ${achievement.achievement}. Impact: ${achievement.impact}`,
source: "Leadership Experience",
category: "Leadership"
}
})
})
// References
references.forEach((ref, i) => {
chunks.push({
id: `reference-${i}`,
data: `Reference: ${ref.name}, ${ref.title} at ${ref.company}. Relationship: ${ref.relationship}`,
metadata: {
content: `Reference: ${ref.name} (${ref.title} at ${ref.company}). Relationship: ${ref.relationship}. Contact: ${ref.contact}`,
source: ref.company,
category: "References"
}
})
})
// Technical Skills - Detailed breakdown
Object.entries(technicalSkills).forEach(([category, skillsList], i) => {
chunks.push({
id: `tech-skill-${i}`,
data: `${category}: ${Array.isArray(skillsList) ? skillsList.join(', ') : skillsList}`,
metadata: {
content: `Technical expertise in ${category}: ${Array.isArray(skillsList) ? skillsList.join(', ') : skillsList}`,
source: "Technical Skills",
category: category
}
})
})
// Skills Metrics - Technical
skillsMetrics.technical.forEach((skill, i) => {
chunks.push({
id: `skill-metric-tech-${i}`,
data: `${skill.name}: ${skill.description}`,
metadata: {
content: `Skill: ${skill.name} (${skill.category}). ${skill.description} Source: ${skill.source}`,
source: skill.source,
category: "Skills Development"
}
})
})
// Skills Metrics - Leadership
skillsMetrics.leadership.forEach((skill, i) => {
chunks.push({
id: `skill-metric-leadership-${i}`,
data: `${skill.name}: ${skill.description}`,
metadata: {
content: `Leadership Skill: ${skill.name} (${skill.category}). ${skill.description} Source: ${skill.source}`,
source: skill.source,
category: "Leadership Development"
}
})
})
// Skills Metrics - Business
skillsMetrics.business.forEach((skill, i) => {
chunks.push({
id: `skill-metric-business-${i}`,
data: `${skill.name}: ${skill.description}`,
metadata: {
content: `Business Skill: ${skill.name} (${skill.category}). ${skill.description} Source: ${skill.source}`,
source: skill.source,
category: "Business Skills"
}
})
})
console.log(`📦 Created ${chunks.length} data chunks`)
// Upload in batches
const BATCH_SIZE = 10
for (let i = 0; i < chunks.length; i += BATCH_SIZE) {
const batch = chunks.slice(i, i + BATCH_SIZE)
console.log(`⬆️ Uploading batch ${Math.floor(i / BATCH_SIZE) + 1}/${Math.ceil(chunks.length / BATCH_SIZE)}...`)
await index.upsert(batch)
}
console.log("✅ Upload complete!")
console.log(`📊 Total chunks uploaded: ${chunks.length}`)
// Test query
console.log("\n🔍 Testing search...")
const testResults = await index.query({
data: "Where does Binal live?",
topK: 3,
includeMetadata: true
})
console.log(`✅ Search test successful! Found ${testResults.length} results`)
if (testResults.length > 0 && testResults[0].metadata) {
console.log("Sample result:", (testResults[0].metadata.content as string)?.substring(0, 150) + "...")
}
} catch (error) {
console.error("❌ Error during update:", error)
throw error
}
}
updateVectorDatabase()
.then(() => {
console.log("\n✨ Database updated successfully!")
process.exit(0)
})
.catch((error) => {
console.error("\n❌ Update failed:", error)
process.exit(1)
})
