Files
santifer--career-ops/gemini-eval.mjs
T
wehub-resource-sync d083df1fdb
CodeQL Analysis / Analyze (javascript-typescript) (push) Failing after 2s
Web CI / web typecheck + build (push) Failing after 1s
Release Please / release-please (push) Failing after 1s
CodeQL Analysis / Analyze (go) (push) Failing after 16s
chore: import upstream snapshot with attribution
2026-07-13 12:02:43 +08:00

440 lines
17 KiB
JavaScript

#!/usr/bin/env node
/**
* gemini-eval.mjs — Gemini-powered Job Offer Evaluator for career-ops
*
* A free-tier alternative to the Claude-based pipeline.
* Reads evaluation logic from modes/oferta.md + modes/_shared.md,
* reads the user's resume from cv.md, and evaluates a Job Description
* passed as a command-line argument.
*
* Usage:
* node gemini-eval.mjs "Paste full JD text here"
* node gemini-eval.mjs --file ./jds/my-job.txt
*
* Requires:
* GEMINI_API_KEY in .env (or environment variable)
*
* Free-tier model: gemini-2.5-flash (generous quota, no billing required)
*
* Model deprecation reference (per Google AI for Developers, May 2026):
* - gemini-2.0-flash deprecated 2026-03-31 (do not use)
* - gemini-2.0-flash-lite deprecated 2026-03-31
* - gemini-2.5-flash deprecated 2026-06-17 (current default)
* - gemini-2.5-flash-lite deprecated 2026-07-22
* Stable Gemini models follow a 12-month lifecycle from their release date.
* Source: https://ai.google.dev/gemini-api/docs/models
*
* When the current default approaches its deprecation date, bump
* `modelName` below and the `--model` examples accordingly.
*/
import { readFileSync, existsSync, writeFileSync, mkdirSync, readdirSync } from 'fs';
import { join, dirname } from 'path';
import { fileURLToPath } from 'url';
import { execFileSync } from 'child_process';
// ---------------------------------------------------------------------------
// Bootstrap: load .env before anything else
// ---------------------------------------------------------------------------
try {
const { config } = await import('dotenv');
config();
} catch {
// dotenv is optional — fall back to process.env if not installed
}
import { GoogleGenerativeAI } from '@google/generative-ai';
// ---------------------------------------------------------------------------
// Paths
// ---------------------------------------------------------------------------
const ROOT = dirname(fileURLToPath(import.meta.url));
const PATHS = {
// Primary evaluation logic lives in these two mode files
shared: join(ROOT, 'modes', '_shared.md'),
oferta: join(ROOT, 'modes', 'oferta.md'),
// Canonical skill path referenced in Issue #344
evaluate: join(ROOT, '.claude', 'skills', 'career-ops', 'SKILL.md'),
cv: join(ROOT, 'cv.md'),
profile: join(ROOT, 'modes', '_profile.md'),
profileYml: join(ROOT, 'config', 'profile.yml'),
reports: join(ROOT, 'reports'),
tracker: join(ROOT, 'data', 'applications.md'),
trackerAdditions: join(ROOT, 'batch', 'tracker-additions'),
};
// ---------------------------------------------------------------------------
// CLI argument parsing
// ---------------------------------------------------------------------------
const args = process.argv.slice(2);
if (args.length === 0 || args[0] === '--help' || args[0] === '-h') {
console.log(`
╔══════════════════════════════════════════════════════════════════╗
║ career-ops — Gemini Evaluator (free-tier) ║
╚══════════════════════════════════════════════════════════════════╝
Evaluate a job offer using Google Gemini instead of Claude.
USAGE
node gemini-eval.mjs "<JD text>"
node gemini-eval.mjs --file ./jds/my-job.txt
node gemini-eval.mjs --model gemini-2.5-flash "<JD text>"
OPTIONS
--file <path> Read JD from a file instead of inline text
--model <name> Gemini model to use (default: gemini-2.5-flash)
--no-save Do not save report to reports/ directory
--help Show this help
SETUP
1. Get a free API key at https://aistudio.google.com/apikey
2. Add GEMINI_API_KEY=<your-key> to .env
3. Run: npm install (installs @google/generative-ai + dotenv)
EXAMPLES
node gemini-eval.mjs "We are looking for a Senior AI Engineer..."
node gemini-eval.mjs --file ./jds/openai-swe.txt
`);
process.exit(0);
}
// Parse flags
let jdText = '';
let modelName = process.env.GEMINI_MODEL || 'gemini-2.5-flash';
let saveReport = true;
for (let i = 0; i < args.length; i++) {
if (args[i] === '--file' && args[i + 1]) {
const filePath = args[++i];
if (!existsSync(filePath)) {
console.error(`❌ File not found: ${filePath}`);
process.exit(1);
}
jdText = readFileSync(filePath, 'utf-8').trim();
} else if (args[i] === '--model' && args[i + 1]) {
modelName = args[++i];
} else if (args[i] === '--no-save') {
saveReport = false;
} else if (!args[i].startsWith('--')) {
jdText += (jdText ? '\n' : '') + args[i];
}
}
if (!jdText) {
console.error('❌ No Job Description provided. Run with --help for usage.');
process.exit(1);
}
// ---------------------------------------------------------------------------
// Validate environment
// ---------------------------------------------------------------------------
const apiKey = process.env.GEMINI_API_KEY;
if (!apiKey) {
console.error(`
❌ GEMINI_API_KEY not found.
1. Get a free key at https://aistudio.google.com/apikey
2. Add it to .env: GEMINI_API_KEY=your_key_here
3. Or export it: export GEMINI_API_KEY=your_key_here
`);
process.exit(1);
}
// ---------------------------------------------------------------------------
// File helpers
// ---------------------------------------------------------------------------
function readFile(path, label) {
if (!existsSync(path)) {
console.warn(`⚠️ ${label} not found at: ${path}`);
return `[${label} not found — skipping]`;
}
return readFileSync(path, 'utf-8').trim();
}
function nextReportNumber() {
if (!existsSync(PATHS.reports)) return '001';
const files = readdirSync(PATHS.reports)
.filter(f => /^\d{3}-/.test(f))
.map(f => parseInt(f.slice(0, 3)))
.filter(n => !isNaN(n));
if (files.length === 0) return '001';
return String(Math.max(...files) + 1).padStart(3, '0');
}
function validateEvaluationShape(text) {
const issues = [];
const requiredBlocks = [
['A', /(?:^|\n)#{1,3}\s*(?:A[).:-]?|Block A\b)/im],
['B', /(?:^|\n)#{1,3}\s*(?:B[).:-]?|Block B\b)/im],
['C', /(?:^|\n)#{1,3}\s*(?:C[).:-]?|Block C\b)/im],
['D', /(?:^|\n)#{1,3}\s*(?:D[).:-]?|Block D\b)/im],
['E', /(?:^|\n)#{1,3}\s*(?:E[).:-]?|Block E\b)/im],
['F', /(?:^|\n)#{1,3}\s*(?:F[).:-]?|Block F\b)/im],
['G', /(?:^|\n)#{1,3}\s*(?:G[).:-]?|Block G\b)/im],
];
for (const [label, pattern] of requiredBlocks) {
if (!pattern.test(text)) issues.push(`missing Block ${label}`);
}
const summary = text.match(/---SCORE_SUMMARY---\s*([\s\S]*?)---END_SUMMARY---/);
if (!summary) {
issues.push('missing SCORE_SUMMARY block');
} else {
const summaryBlock = summary[1];
for (const key of ['COMPANY', 'ROLE', 'ARCHETYPE', 'LEGITIMACY']) {
const field = summaryBlock.match(new RegExp(`^\\s*${key}:\\s*(.+)$`, 'mi'));
const value = field?.[1]?.trim() ?? '';
if (!value || (key !== 'COMPANY' && value.toLowerCase() === 'unknown')) {
issues.push(`SCORE_SUMMARY ${key} is required`);
}
}
const score = summaryBlock.match(/^\s*SCORE:\s*([0-9]+(?:\.[0-9]+)?)/mi);
const scoreValue = score ? Number(score[1]) : NaN;
if (!Number.isFinite(scoreValue) || scoreValue < 0 || scoreValue > 5) {
issues.push('SCORE_SUMMARY score must be a number between 0 and 5');
}
}
if (issues.length > 0) {
throw new Error(`Gemini returned an invalid career-ops report: ${issues.join('; ')}`);
}
}
function slugifyCompany(value) {
return String(value || '')
.toLowerCase()
.replace(/[^a-z0-9]+/g, '-')
.replace(/^-|-$/g, '') || 'unknown';
}
function tsvSafe(value) {
return String(value ?? '').replace(/[\t\r\n]+/g, ' ').trim();
}
function normalizedTrackerScore(value) {
const clean = tsvSafe(value);
if (!clean || clean === '?') return 'N/A';
return /\/5$/i.test(clean) ? clean : `${clean}/5`;
}
// ---------------------------------------------------------------------------
// Load context files
// ---------------------------------------------------------------------------
console.log('\n📂 Loading context files...');
const sharedContext = readFile(PATHS.shared, 'modes/_shared.md');
const ofertaLogic = readFile(PATHS.oferta, 'modes/oferta.md');
const cvContent = readFile(PATHS.cv, 'cv.md');
const profileContent = readFile(PATHS.profile, 'modes/_profile.md');
const profileYml = readFile(PATHS.profileYml, 'config/profile.yml');
// ---------------------------------------------------------------------------
// Build the system prompt (mirrors the Claude skill router logic)
// ---------------------------------------------------------------------------
const systemPrompt = `You are career-ops, an AI-powered job search assistant.
You evaluate job offers against the user's CV using a structured A-G scoring system.
Your evaluation methodology is defined below. Follow it exactly.
═══════════════════════════════════════════════════════
SYSTEM CONTEXT (_shared.md)
═══════════════════════════════════════════════════════
${sharedContext}
═══════════════════════════════════════════════════════
EVALUATION MODE (oferta.md)
═══════════════════════════════════════════════════════
${ofertaLogic}
═══════════════════════════════════════════════════════
CANDIDATE RESUME (cv.md)
═══════════════════════════════════════════════════════
${cvContent}
═══════════════════════════════════════════════════════
CANDIDATE PROFILE & TARGETS (config/profile.yml)
═══════════════════════════════════════════════════════
${profileYml}
═══════════════════════════════════════════════════════
USER ARCHETYPES & NARRATIVE (_profile.md)
═══════════════════════════════════════════════════════
${profileContent}
═══════════════════════════════════════════════════════
IMPORTANT OPERATING RULES FOR THIS CLI SESSION
═══════════════════════════════════════════════════════
1. You do NOT have access to WebSearch, Playwright, or file writing tools.
- For Block D (Comp research): provide salary estimates based on your training data, clearly noted as estimates.
- For Block G (Legitimacy): analyze the JD text only; skip URL/page freshness checks.
- Post-evaluation file saving is handled by the script, not by you.
2. Generate Blocks A through G in full, in English, unless the JD is in another language.
3. At the very end, output a machine-readable summary block in this exact format:
---SCORE_SUMMARY---
COMPANY: <company name or "Unknown">
ROLE: <role title>
SCORE: <global score as decimal, e.g. 3.8>
ARCHETYPE: <detected archetype>
LEGITIMACY: <High Confidence | Proceed with Caution | Suspicious>
---END_SUMMARY---
`;
// ---------------------------------------------------------------------------
// Call Gemini API
// ---------------------------------------------------------------------------
console.log(`🤖 Calling Gemini (${modelName})... this may take 30-60 seconds.\n`);
const genAI = new GoogleGenerativeAI(apiKey);
const model = genAI.getGenerativeModel({
model: modelName,
generationConfig: {
temperature: 0.4, // deterministic enough for structured evaluation
maxOutputTokens: 8192, // full 7-block evaluation
},
});
let evaluationText;
try {
const result = await model.generateContent([
{ text: systemPrompt },
{ text: `\n\nJOB DESCRIPTION TO EVALUATE:\n\n${jdText}` },
]);
evaluationText = result.response.text();
} catch (err) {
const sanitizedMsg = (err.message || '').split(apiKey).join('[REDACTED]');
console.error('❌ Gemini API error:', sanitizedMsg);
if (sanitizedMsg.includes('API_KEY')) {
console.error(' Check your GEMINI_API_KEY in .env');
} else if (sanitizedMsg.includes('quota') || sanitizedMsg.includes('rate')) {
console.error(' You may have hit the free-tier rate limit. Wait 60s and retry.');
}
process.exit(1);
}
try {
validateEvaluationShape(evaluationText);
} catch (err) {
console.error('❌ Gemini output failed validation:', err.message);
console.error(' No report was saved. Retry, lower temperature, or use the Claude pipeline for this JD.');
process.exit(1);
}
// ---------------------------------------------------------------------------
// Display evaluation
// ---------------------------------------------------------------------------
console.log('\n' + '═'.repeat(66));
console.log(' CAREER-OPS EVALUATION — powered by Google Gemini');
console.log('═'.repeat(66) + '\n');
console.log(evaluationText);
// ---------------------------------------------------------------------------
// Parse score summary
// ---------------------------------------------------------------------------
const summaryMatch = evaluationText.match(
/---SCORE_SUMMARY---\s*([\s\S]*?)---END_SUMMARY---/
);
let company = 'unknown';
let role = 'unknown';
let score = '?';
let archetype = 'unknown';
let legitimacy = 'unknown';
if (summaryMatch) {
const block = summaryMatch[1];
const extract = (key) => {
const prefix = `${key}:`;
const lines = block.split('\n');
for (const line of lines) {
const trimmed = line.trimStart();
if (trimmed.startsWith(prefix)) {
return trimmed.slice(prefix.length).trim();
}
}
return 'unknown';
};
company = extract('COMPANY');
role = extract('ROLE');
score = extract('SCORE');
archetype = extract('ARCHETYPE');
legitimacy = extract('LEGITIMACY');
}
// ---------------------------------------------------------------------------
// Save report
// ---------------------------------------------------------------------------
if (saveReport) {
let reportSaved = false;
try {
if (!existsSync(PATHS.reports)) {
mkdirSync(PATHS.reports, { recursive: true });
}
const num = nextReportNumber();
const today = new Date().toISOString().split('T')[0];
const companySlug = slugifyCompany(company);
const filename = `${num}-${companySlug}-${today}.md`;
const reportPath = join(PATHS.reports, filename);
const trackerPath = join(PATHS.trackerAdditions, `${num}-${companySlug}.tsv`);
const reportContent = `# Evaluation: ${company}${role}
**Date:** ${today}
**Archetype:** ${archetype}
**Score:** ${score}/5
**Legitimacy:** ${legitimacy}
**PDF:** pending
**Tool:** Gemini (${modelName})
---
${evaluationText.replace(/---SCORE_SUMMARY---[\s\S]*?---END_SUMMARY---/, '').trim()}
`;
writeFileSync(reportPath, reportContent, 'utf-8');
mkdirSync(PATHS.trackerAdditions, { recursive: true });
const trackerFields = [
String(parseInt(num, 10)),
today,
tsvSafe(company),
tsvSafe(role),
'Evaluated',
normalizedTrackerScore(score),
'❌',
`[${num}](reports/${filename})`,
'Gemini evaluation',
];
writeFileSync(trackerPath, `${trackerFields.join('\t')}\n`, 'utf-8');
console.log(`\n✅ Report saved: reports/${filename}`);
console.log(`📊 Tracker addition saved: batch/tracker-additions/${num}-${companySlug}.tsv`);
reportSaved = true;
} catch (err) {
console.warn(`⚠️ Could not save report: ${err.message}`);
process.exitCode = 1;
}
if (reportSaved) {
try {
const mergeOutput = execFileSync(process.execPath, [join(ROOT, 'merge-tracker.mjs')], {
cwd: ROOT,
encoding: 'utf-8',
stdio: ['ignore', 'pipe', 'pipe'],
});
if (mergeOutput.trim()) console.log(mergeOutput.trim());
console.log('📊 Tracker merged into data/applications.md.');
} catch (err) {
console.warn(`⚠️ Report saved, but could not merge tracker addition into data/applications.md: ${err.message}`);
process.exitCode = 1;
}
}
}
console.log('\n' + '─'.repeat(66));
console.log(` Score: ${score}/5 | Archetype: ${archetype} | Legitimacy: ${legitimacy}`);
console.log('─'.repeat(66) + '\n');