wehub-resource-sync
394 lines
16 KiB
JavaScript
394 lines
16 KiB
JavaScript
#!/usr/bin/env node
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/**
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* openai-eval.mjs — OpenAI-compatible Job Offer Evaluator for career-ops
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*
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* Evaluate job offers with ANY OpenAI-compatible chat endpoint instead of Claude.
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* Works with OpenAI, OpenRouter, Together, Groq, DeepSeek, Zhipu GLM, MiniMax,
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* Fireworks, and local servers that speak the OpenAI API (LM Studio, llama.cpp,
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* vLLM, Ollama's /v1). Point it at a base URL + model + key and go.
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*
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* Reads evaluation logic from modes/oferta.md + modes/_shared.md, reads the
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* user's resume from cv.md, and evaluates a Job Description passed inline or
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* via --file. Mirrors ollama-eval.mjs / gemini-eval.mjs.
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*
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* Usage:
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* node openai-eval.mjs "Paste full JD text here"
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* node openai-eval.mjs --file ./jds/my-job.txt
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* node openai-eval.mjs --url https://openrouter.ai/api/v1 --model meta-llama/llama-3.3-70b-instruct --file ./jds/job.txt
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*
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* Requires (for hosted endpoints):
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* OPENAI_API_KEY (or --key) — your provider key
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* OPENAI_BASE_URL (or --url) — the provider's OpenAI-compatible base, e.g.
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* https://openrouter.ai/api/v1
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* OPENAI_MODEL (or --model) — the model id
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*
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* Privacy: your cv.md + the full JD are sent to the configured endpoint. Pick a
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* provider you trust; for fully local/private use, run a local server and point
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* --url at http://localhost:... (or use ollama-eval.mjs).
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*/
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import { readFileSync, existsSync, writeFileSync, mkdirSync, readdirSync } from 'fs';
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import { join, dirname } from 'path';
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import { fileURLToPath } from 'url';
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try {
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const { config } = await import('dotenv');
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config();
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} catch { /* dotenv optional */ }
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const ROOT = dirname(fileURLToPath(import.meta.url));
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// ---------------------------------------------------------------------------
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// Paths
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// ---------------------------------------------------------------------------
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const PATHS = {
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shared: join(ROOT, 'modes', '_shared.md'),
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oferta: join(ROOT, 'modes', 'oferta.md'),
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cv: join(ROOT, 'cv.md'),
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reports: join(ROOT, 'reports'),
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};
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// ---------------------------------------------------------------------------
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// CLI argument parsing
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// ---------------------------------------------------------------------------
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const args = process.argv.slice(2);
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if (args.length === 0 || args[0] === '--help' || args[0] === '-h') {
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console.log(`
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╔══════════════════════════════════════════════════════════════════╗
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║ career-ops — OpenAI-compatible Evaluator (any endpoint) ║
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╚══════════════════════════════════════════════════════════════════╝
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Evaluate a job offer with any OpenAI-compatible chat API instead of Claude.
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USAGE
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node openai-eval.mjs "<JD text>"
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node openai-eval.mjs --file ./jds/my-job.txt
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node openai-eval.mjs --url <base> --model <id> --file ./jds/job.txt
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OPTIONS
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--file <path> Read JD from a file instead of inline text
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--model <id> Model id (env OPENAI_MODEL, default gpt-4o-mini)
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--url <base> OpenAI-compatible base URL, including any /v1
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(env OPENAI_BASE_URL, default https://api.openai.com/v1)
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--key <key> API key (env OPENAI_API_KEY)
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--no-save Do not save report to reports/ directory
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--help Show this help
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ENV
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OPENAI_API_KEY, OPENAI_BASE_URL, OPENAI_MODEL, OPENAI_TIMEOUT_MS
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PROVIDER EXAMPLES (cheap / free-tier friendly — addresses token cost)
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OpenRouter: --url https://openrouter.ai/api/v1 --model deepseek/deepseek-chat
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Together: --url https://api.together.xyz/v1 --model meta-llama/Llama-3.3-70B-Instruct-Turbo
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Groq: --url https://api.groq.com/openai/v1 --model llama-3.3-70b-versatile
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DeepSeek: --url https://api.deepseek.com/v1 --model deepseek-chat
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Zhipu GLM: --url https://open.bigmodel.cn/api/paas/v4 --model glm-4-flash
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LM Studio: --url http://localhost:1234/v1 --model <loaded-model> (no key)
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EXAMPLES
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OPENAI_API_KEY=sk-... node openai-eval.mjs --file ./jds/job.txt
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node openai-eval.mjs --url http://localhost:1234/v1 --model local "<JD text>"
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`);
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process.exit(0);
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}
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// Parse flags
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let jdText = '';
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let modelName = process.env.OPENAI_MODEL || 'gpt-4o-mini';
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let baseUrl = (process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1').replace(/\/$/, '');
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let apiKey = process.env.OPENAI_API_KEY || '';
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let saveReport = true;
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for (let i = 0; i < args.length; i++) {
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if (args[i] === '--file' && args[i + 1]) {
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const filePath = args[++i];
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if (!existsSync(filePath)) {
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console.error(`❌ File not found: ${filePath}`);
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process.exit(1);
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}
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try {
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jdText = readFileSync(filePath, 'utf-8').trim();
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} catch (err) {
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console.error(`❌ Could not read file: ${filePath}`);
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console.error(` ${err.message}`);
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process.exit(1);
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}
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} else if (args[i] === '--model' && args[i + 1]) {
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modelName = args[++i];
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} else if (args[i] === '--url' && args[i + 1]) {
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baseUrl = args[++i].replace(/\/$/, '');
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} else if (args[i] === '--key' && args[i + 1]) {
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apiKey = args[++i];
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} else if (args[i] === '--no-save') {
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saveReport = false;
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} else if (!args[i].startsWith('--')) {
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jdText += (jdText ? '\n' : '') + args[i];
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}
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}
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if (!jdText) {
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console.error('❌ No Job Description provided. Run with --help for usage.');
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process.exit(1);
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}
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// ---------------------------------------------------------------------------
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// Endpoint + security guard.
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// cv.md + the full JD (and the API key) are sent to this endpoint, so:
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// - Non-loopback endpoints MUST use HTTPS (never leak credentials/data in
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// cleartext); plain http is allowed only for localhost dev servers.
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// - Hosted (non-loopback) endpoints require an API key.
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// ---------------------------------------------------------------------------
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let endpointHost;
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{
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let parsed;
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try {
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parsed = new URL(baseUrl);
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} catch {
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console.error(`❌ Invalid OPENAI_BASE_URL: "${baseUrl}"`);
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process.exit(1);
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}
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endpointHost = parsed.hostname;
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const isLoopback = endpointHost === 'localhost' || endpointHost === '127.0.0.1' || endpointHost === '::1';
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if (!isLoopback && parsed.protocol !== 'https:') {
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console.error(`
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❌ Refusing to use a non-HTTPS remote endpoint: ${baseUrl}
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Your CV, the job description, and your API key would be sent in cleartext.
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Use an https:// endpoint, or http://localhost:... for a local server.
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`);
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process.exit(1);
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}
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if (!isLoopback && !apiKey) {
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console.error(`
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❌ No API key for ${endpointHost}.
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Set one and re-run:
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OPENAI_API_KEY=your_key node openai-eval.mjs ...
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or pass --key <key>. (Local servers at localhost may not need one.)
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`);
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process.exit(1);
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}
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}
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// Build the chat-completions endpoint from the base URL (which already includes
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// any provider version segment, e.g. ".../v1"), matching the OpenAI SDK convention.
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const endpoint = `${baseUrl}/chat/completions`;
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// ---------------------------------------------------------------------------
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// File helpers
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// ---------------------------------------------------------------------------
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/**
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* Read a file and return its trimmed contents, or a placeholder if missing.
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* @param {string} path - Absolute path to the file.
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* @param {string} label - Human-readable label used in the warning and placeholder.
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* @returns {string} File contents or a "[label not found]" placeholder.
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*/
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function readFile(path, label) {
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if (!existsSync(path)) {
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console.warn(`⚠️ ${label} not found at: ${path}`);
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return `[${label} not found — skipping]`;
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}
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return readFileSync(path, 'utf-8').trim();
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}
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/**
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* Determine the next zero-padded report number based on existing files in reports/.
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* @returns {string} Zero-padded report number string, e.g. "042" or "1001".
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*/
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function nextReportNumber() {
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if (!existsSync(PATHS.reports)) return '001';
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const files = readdirSync(PATHS.reports)
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.map(f => { const m = f.match(/^(\d+)-/); return m ? parseInt(m[1], 10) : NaN; })
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.filter(n => !isNaN(n));
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if (files.length === 0) return '001';
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return String(Math.max(...files) + 1).padStart(3, '0');
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}
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// ---------------------------------------------------------------------------
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// Load context files
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// ---------------------------------------------------------------------------
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console.log('\n📂 Loading context files...');
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const sharedContext = readFile(PATHS.shared, 'modes/_shared.md');
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const ofertaLogic = readFile(PATHS.oferta, 'modes/oferta.md');
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const cvContent = readFile(PATHS.cv, 'cv.md');
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// ---------------------------------------------------------------------------
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// Build system prompt
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// ---------------------------------------------------------------------------
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const systemPrompt = `You are career-ops, an AI-powered job search assistant.
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You evaluate job offers against the user's CV using a structured A-G scoring system.
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Your evaluation methodology is defined below. Follow it exactly.
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═══════════════════════════════════════════════════════
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SYSTEM CONTEXT (_shared.md)
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═══════════════════════════════════════════════════════
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${sharedContext}
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═══════════════════════════════════════════════════════
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EVALUATION MODE (oferta.md)
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═══════════════════════════════════════════════════════
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${ofertaLogic}
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═══════════════════════════════════════════════════════
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CANDIDATE RESUME (cv.md)
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═══════════════════════════════════════════════════════
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${cvContent}
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═══════════════════════════════════════════════════════
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IMPORTANT OPERATING RULES FOR THIS SESSION
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═══════════════════════════════════════════════════════
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1. You do NOT have access to WebSearch, Playwright, or file writing tools.
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- Block D (Comp research): use training-data salary estimates; note them as estimates.
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- Block G (Legitimacy): analyze JD text only; skip URL/page freshness checks.
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- Post-evaluation file saving is handled by the script, not by you.
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2. Generate Blocks A through G in full.
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3. At the very end, output this exact machine-readable block:
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---SCORE_SUMMARY---
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COMPANY: <company name or "Unknown">
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ROLE: <role title>
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SCORE: <global score as decimal, e.g. 3.8>
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ARCHETYPE: <detected archetype>
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LEGITIMACY: <High Confidence | Proceed with Caution | Suspicious>
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---END_SUMMARY---
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`;
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// ---------------------------------------------------------------------------
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// Call the OpenAI-compatible endpoint
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// ---------------------------------------------------------------------------
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const timeoutMs = parseInt(process.env.OPENAI_TIMEOUT_MS || '300000', 10);
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if (Number.isNaN(timeoutMs) || timeoutMs <= 0) {
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console.error(`❌ Invalid OPENAI_TIMEOUT_MS: "${process.env.OPENAI_TIMEOUT_MS}" — must be a positive integer (milliseconds).`);
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process.exit(1);
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}
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console.log(`\n🔒 Privacy: your cv.md + JD will be sent to ${endpointHost}.`);
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console.log(`🤖 Calling ${modelName} via ${endpointHost}... this may take a minute.\n`);
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const headers = { 'Content-Type': 'application/json' };
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if (apiKey) headers['Authorization'] = `Bearer ${apiKey}`;
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let evaluationText;
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try {
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const res = await fetch(endpoint, {
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method: 'POST',
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headers,
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body: JSON.stringify({
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model: modelName,
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messages: [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: `JOB DESCRIPTION TO EVALUATE:\n\n${jdText}` },
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],
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stream: false,
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temperature: 0.4,
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}),
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signal: AbortSignal.timeout(timeoutMs),
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});
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if (!res.ok) {
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const body = await res.text();
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console.error(`❌ API error: HTTP ${res.status}`);
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console.error(` ${body.slice(0, 300)}`);
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if (res.status === 401 || res.status === 403) {
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console.error(` → Check your API key for ${endpointHost}.`);
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} else if (res.status === 404) {
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console.error(` → Check --url (it should include any /v1 segment) and --model id.`);
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}
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process.exit(1);
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}
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const data = await res.json();
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evaluationText = data.choices?.[0]?.message?.content?.trim();
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if (!evaluationText) {
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console.error('❌ The endpoint returned an empty response.');
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process.exit(1);
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}
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} catch (err) {
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if (err.name === 'TimeoutError') {
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console.error(`❌ Request timed out after ${Math.round(timeoutMs / 1000)}s.`);
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console.error(` Try a smaller/faster model, or increase OPENAI_TIMEOUT_MS.`);
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} else {
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console.error(`❌ API call failed: ${err.message}`);
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}
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process.exit(1);
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}
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// ---------------------------------------------------------------------------
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// Display evaluation
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// ---------------------------------------------------------------------------
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console.log('\n' + '═'.repeat(66));
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console.log(' CAREER-OPS EVALUATION — powered by ' + modelName + ' (' + endpointHost + ')');
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console.log('═'.repeat(66) + '\n');
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console.log(evaluationText);
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// ---------------------------------------------------------------------------
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// Parse score summary
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// ---------------------------------------------------------------------------
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const summaryMatch = evaluationText.match(/---SCORE_SUMMARY---\s*([\s\S]*?)---END_SUMMARY---/);
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let company = 'unknown';
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let role = 'unknown';
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let score = '?';
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let archetype = 'unknown';
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let legitimacy = 'unknown';
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if (summaryMatch) {
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const extract = (key) => {
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const m = summaryMatch[1].match(new RegExp(`${key}:\\s*(.+)`));
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return m ? m[1].trim() : 'unknown';
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};
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company = extract('COMPANY');
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role = extract('ROLE');
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score = extract('SCORE');
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archetype = extract('ARCHETYPE');
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legitimacy = extract('LEGITIMACY');
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}
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// ---------------------------------------------------------------------------
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// Save report
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// ---------------------------------------------------------------------------
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if (saveReport) {
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try {
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if (!existsSync(PATHS.reports)) {
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mkdirSync(PATHS.reports, { recursive: true });
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}
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const num = nextReportNumber();
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const today = new Date().toISOString().split('T')[0];
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const companySlug = company.toLowerCase().replace(/[^a-z0-9]+/g, '-').replace(/^-|-$/g, '');
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const filename = `${num}-${companySlug}-${today}.md`;
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const reportPath = join(PATHS.reports, filename);
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const reportContent = `# Evaluation: ${company} — ${role}
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**Date:** ${today}
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**Archetype:** ${archetype}
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**Score:** ${score}/5
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**Legitimacy:** ${legitimacy}
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**PDF:** pending
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**Tool:** OpenAI-compatible (${modelName} @ ${endpointHost})
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---
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${evaluationText.replace(/---SCORE_SUMMARY---[\s\S]*?---END_SUMMARY---/, '').trim()}
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`;
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writeFileSync(reportPath, reportContent, 'utf-8');
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console.log(`\n✅ Report saved: reports/${filename}`);
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console.log(`\n📊 Tracker entry (add to data/applications.md):`);
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console.log(` | ${num} | ${today} | ${company} | ${role} | ${score}/5 | Evaluated | ❌ | [${num}](reports/${filename}) |`);
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} catch (err) {
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console.warn(`⚠️ Could not save report: ${err.message}`);
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}
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}
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console.log('\n' + '─'.repeat(66));
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console.log(` Score: ${score}/5 | Archetype: ${archetype} | Legitimacy: ${legitimacy}`);
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console.log('─'.repeat(66) + '\n');
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