#!/usr/bin/env node /** * ollama-eval.mjs — Ollama-powered Job Offer Evaluator for career-ops * * Local, free, private 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 CLI argument or file. * * Usage: * node ollama-eval.mjs "Paste full JD text here" * node ollama-eval.mjs --file ./jds/my-job.txt * node ollama-eval.mjs --model qwen2.5:72b --file ./jds/my-job.txt * * Requires: * Ollama running locally — https://ollama.com * A model pulled: ollama pull llama3.3 * * Context window guidance: * The prompt (cv + modes + JD) is ~10K-15K tokens. * Recommended models (32K+ context): llama3.3, mistral-nemo, qwen2.5, gemma3 * Smaller models (llama3.2:3b, phi3) may produce incomplete evaluations. */ import { readFileSync, existsSync, writeFileSync, mkdirSync } from 'fs'; import { join, dirname } from 'path'; import { fileURLToPath } from 'url'; import { getCareerOpsRoot, getProfilePath } from './path-resolver.mjs'; import { localToday } from './lib/local-today.mjs'; import { withJdArchiveSection } from './lib/jd-archive-section.mjs'; import { TSV_ADDITION_HEADER } from './tracker-parse.mjs'; import { outputLanguageInstruction, parseOutputLanguage } from './profile-language.mjs'; import { formatReportNumber, releaseReportNumbers, reserveReportNumbers, } from './reserve-report-num.mjs'; import { TokenAccumulator, formatBreakdown, normalizeOpenAIUsage } from './utils/token-tracker.mjs'; import { buildBudgetedPrompt } from './lib/context-budget.mjs'; import { assertLlmRequestAllowed } from './lib/llm-outbound.mjs'; import { installPiiInterceptor } from './lib/pii-interceptor.mjs'; import { isPostingUrl, normalizedTrackerScore, parseScoreSummary, slugifyCompany, tsvSafe, } from './lib/tracker-addition.mjs'; // Ambient guard over global fetch (idempotent); the explicit gate below is the // primary layer. installPiiInterceptor(); const tracker = new TokenAccumulator(); tracker.recordZeroToken('scan'); tracker.recordZeroToken('pdf payload'); try { const { config } = await import('dotenv'); // The data root's .env first: doctor.mjs, remember-cli.mjs, scan.mjs and the // plugin engine all read it there. The working directory's .env, the only one // read before, still supplies what the data root's leaves unset. config({ path: [join(getCareerOpsRoot(), '.env'), join(process.cwd(), '.env')] }); } catch { /* dotenv optional */ } const ROOT = dirname(fileURLToPath(import.meta.url)); const DATA_ROOT = getCareerOpsRoot(); // --------------------------------------------------------------------------- // Paths // --------------------------------------------------------------------------- const PATHS = { shared: join(ROOT, 'modes', '_shared.md'), oferta: join(ROOT, 'modes', 'oferta.md'), cv: join(DATA_ROOT, 'cv.md'), profile: join(DATA_ROOT, 'modes', '_profile.md'), custom: join(DATA_ROOT, 'modes', '_custom.md'), profileYml: getProfilePath(), reports: join(DATA_ROOT, 'reports'), // CAREER_OPS_ADDITIONS mirrors merge-tracker.mjs:43. Writing under DATA_ROOT // regardless would drop the addition somewhere the merge it instructs never // looks, so the evaluation would sit there unread. trackerAdditions: process.env.CAREER_OPS_ADDITIONS ? process.env.CAREER_OPS_ADDITIONS : join(DATA_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 — Ollama Evaluator (local / free) ║ ╚══════════════════════════════════════════════════════════════════╝ Evaluate a job offer using a local Ollama model instead of Claude. USAGE node ollama-eval.mjs "" node ollama-eval.mjs --file ./jds/my-job.txt node ollama-eval.mjs --model qwen2.5:72b "" OPTIONS --file Read JD from a file instead of inline text --model Ollama model to use (default: llama3.3) --url Ollama base URL (default: http://localhost:11434) --posting-url Posting URL, recorded in the report header and used as the tracker's dedup key --no-save Do not save report to reports/ directory --help Show this help SETUP 1. Install Ollama: https://ollama.com 2. Pull a model: ollama pull llama3.3 3. Start server: ollama serve (or it auto-starts) 4. Run this script EXAMPLES node ollama-eval.mjs "We are looking for a Senior AI Engineer..." node ollama-eval.mjs --file ./jds/openai-swe.txt OLLAMA_MODEL=mistral-nemo node ollama-eval.mjs --file ./jds/job.txt `); process.exit(0); } // Parse flags let jdText = ''; let postingUrl = ''; let modelName = process.env.OLLAMA_MODEL || 'llama3.3'; let baseUrl = (process.env.OLLAMA_BASE_URL || 'http://localhost:11434').replace(/\/$/, ''); // Context window for the request AND the prompt budget. Defaults to the previous hardcoded // 32768, so behaviour is unchanged unless OLLAMA_NUM_CTX is set. Raise it for a model with a // bigger window; `ollama show` reports each model's ceiling (qwen2.5 caps at 32768). // Digits only: parseInt read "32k" as 32, a 32-token context, and the prompt was // cut to fit it. const numCtxRaw = (process.env.OLLAMA_NUM_CTX || '32768').trim(); const numCtx = /^\d+$/.test(numCtxRaw) ? Number(numCtxRaw) : NaN; if (!Number.isSafeInteger(numCtx) || numCtx <= 0) { console.error(`❌ Invalid OLLAMA_NUM_CTX: "${process.env.OLLAMA_NUM_CTX}" — must be a positive integer (tokens).`); process.exit(1); } // Checked here, with the other settings, before the server is contacted. Digits // only (parseInt read "5m" as a 5 ms timeout) and at most 2^31-1 ms: // AbortSignal.timeout() fires a longer delay after 1 ms, and throws past 2^32-1. const timeoutRaw = (process.env.OLLAMA_TIMEOUT_MS || '300000').trim(); const timeoutMs = /^\d+$/.test(timeoutRaw) ? Number(timeoutRaw) : NaN; if (!Number.isSafeInteger(timeoutMs) || timeoutMs <= 0 || timeoutMs > 2_147_483_647) { console.error(`❌ Invalid OLLAMA_TIMEOUT_MS: "${process.env.OLLAMA_TIMEOUT_MS}" — must be a positive integer of at most 2147483647 (milliseconds).`); process.exit(1); } 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); } try { jdText = readFileSync(filePath, 'utf-8').trim(); } catch (err) { console.error(`❌ Could not read file: ${filePath}`); console.error(` ${err.message}`); process.exit(1); } } else if (args[i] === '--model' && args[i + 1]) { modelName = args[++i]; } else if (args[i] === '--url' && args[i + 1]) { baseUrl = args[++i].replace(/\/$/, ''); } else if (args[i] === '--posting-url' && args[i + 1]) { postingUrl = 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); } // A posting URL is the tracker's deterministic dedup key, so it is taken only in // a form that can actually become one. Parsed, not prefix-matched: `https://` // satisfies a prefix test and merge-tracker.mjs:697 would then classify it as // the URL extra, but normalizeUrl yields no key for it -- so it would sit in the // URL column looking like a key while deduping nothing. A placeholder written // there would be worse still, handing every such row the same key. if (postingUrl && !isPostingUrl(postingUrl)) { console.error(`❌ --posting-url must be a complete http(s) URL: "${postingUrl}"`); process.exit(1); } // --------------------------------------------------------------------------- // File helpers // --------------------------------------------------------------------------- /** * Read a file and return its trimmed contents, or a placeholder if missing. * Emits a console warning when the file is absent so the user knows context is incomplete. * @param {string} path - Absolute path to the file. * @param {string} label - Human-readable label used in the warning and placeholder. * @returns {string} File contents or a "[label not found]" placeholder. */ 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(); } // --------------------------------------------------------------------------- // Loopback guard — cv.md + full JD are sent to this endpoint. // A remote URL would silently exfiltrate private data. // --------------------------------------------------------------------------- { let hostname; try { hostname = new URL(baseUrl).hostname; } catch { console.error(`❌ Invalid OLLAMA_BASE_URL: "${baseUrl}"`); process.exit(1); } const isLoopback = hostname === 'localhost' || hostname === '127.0.0.1' || hostname === '::1'; if (!isLoopback && process.env.OLLAMA_ALLOW_REMOTE !== '1') { console.error(` ❌ Remote Ollama endpoint detected: ${baseUrl} Your CV and job description would be sent to a remote server. This tool is designed for local use only. If you intentionally want to use a remote endpoint (e.g. tunnelled Ollama on a home server), set: OLLAMA_ALLOW_REMOTE=1 node ollama-eval.mjs ... `); process.exit(1); } } // --------------------------------------------------------------------------- // Check Ollama is reachable before burning time on prompt assembly // --------------------------------------------------------------------------- try { const probe = await fetch(`${baseUrl}/api/tags`, { signal: AbortSignal.timeout(5_000) }); if (!probe.ok) throw new Error(`HTTP ${probe.status}`); } catch (err) { console.error(` ❌ Ollama not reachable at ${baseUrl} 1. Install Ollama: https://ollama.com 2. Start server: ollama serve 3. Pull a model: ollama pull ${modelName} `); process.exit(1); } // --------------------------------------------------------------------------- // 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'); // _custom.md is optional: an absent file is a valid end state, so no warning. const customContent = existsSync(PATHS.custom) ? readFileSync(PATHS.custom, 'utf-8').trim() : ''; const profileYml = readFile(PATHS.profileYml, 'config/profile.yml'); const languageInstruction = outputLanguageInstruction(parseOutputLanguage(profileYml)); // --------------------------------------------------------------------------- // Build system prompt with token budget management // --------------------------------------------------------------------------- const { contextBody, budgetReport } = buildBudgetedPrompt({ sharedContent: sharedContext, ofertaContent: ofertaLogic, cvContent, profileYml, profileContent, customContent, jdText, jdInContext: false, // The user message carries the JD; still budget it once. maxTokens: numCtx, // matches options.num_ctx below }); if (budgetReport.compressed) { console.log(`📊 Token budget: ${budgetReport.beforeTokens} → ${budgetReport.afterTokens} tokens (saved ${budgetReport.beforeTokens - budgetReport.afterTokens})`); console.log(` Trimmed sections: ${budgetReport.removed.join(', ')}`); if (budgetReport.overBudget) { console.log(` ⚠️ Still ${budgetReport.afterTokens - budgetReport.budget} tokens over budget after compression`); } } else if (budgetReport.overBudget) { console.log(`⚠️ Token budget: ${budgetReport.totalTokens} tokens exceeds ${budgetReport.budget} limit by ${budgetReport.totalTokens - budgetReport.budget}`); } else { console.log(`📊 Token budget: ${budgetReport.totalTokens} tokens (within ${budgetReport.budget} limit)`); } 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. ${contextBody} ═══════════════════════════════════════════════════════ IMPORTANT OPERATING RULES FOR THIS SESSION ═══════════════════════════════════════════════════════ 1. You do NOT have access to WebSearch, Playwright, or file writing tools. - Block D (Comp research): use training-data salary estimates; note them as estimates. - Block G (Legitimacy): analyze JD text only; skip URL/page freshness checks. - Post-evaluation file saving is handled by the script, not by you. 2. ${languageInstruction} 3. Generate Blocks A through G in full. 4. At the very end, output this exact machine-readable block: ---SCORE_SUMMARY--- COMPANY: ROLE: SCORE: ARCHETYPE: LEGITIMACY: ---END_SUMMARY--- `; // --------------------------------------------------------------------------- // Call Ollama // --------------------------------------------------------------------------- const endpoint = `${baseUrl}/api/chat`; console.log(`🤖 Calling Ollama (${modelName})... this may take a minute.\n`); let evaluationText; try { // Privacy gate: inspect the complete serialized request before the network // call. Ollama may be local, but it may equally be a remote host set via // OLLAMA_BASE_URL — either way the payload is checked. const requestBody = JSON.stringify({ model: modelName, messages: [ { role: 'system', content: systemPrompt }, { role: 'user', content: `JOB DESCRIPTION TO EVALUATE:\n\n${jdText}` }, ], // stream:true so response headers arrive with the FIRST token. With stream:false // Ollama sends nothing until the whole report is generated, and Node's undici client // gives up at its own 300s headersTimeout — a deadline neither OLLAMA_TIMEOUT_MS nor // AbortSignal.timeout controls, which surfaced as a bare "fetch failed" at 5:01. stream: true, // Ollama's native /api/chat reads generation params from `options` only. // This call targets that endpoint (NOT the OpenAI-compatible /v1 route, // which ignores `options` and has no num_ctx equivalent), so both the // deterministic temperature and the enlarged context window actually take // effect. Without num_ctx here Ollama defaults to a 2048-token context and // silently truncates the prompt; without temperature it runs at 0.8. options: { temperature: 0.4, num_ctx: numCtx }, }); assertLlmRequestAllowed(endpoint, requestBody); const res = await fetch(endpoint, { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: requestBody, signal: AbortSignal.timeout(timeoutMs), }); if (!res.ok) { const body = await res.text(); console.error(`❌ Ollama API error: HTTP ${res.status}`); console.error(` ${body.slice(0, 300)}`); process.exit(1); } // Streamed /api/chat is newline-delimited JSON: one object per token, the last carrying // done:true and the token counts. let acc = '', buf = '', promptCount = 0, evalCount = 0; const decoder = new TextDecoder(); for await (const chunk of res.body) { buf += decoder.decode(chunk, { stream: true }); let nl; while ((nl = buf.indexOf('\n')) !== -1) { const line = buf.slice(0, nl).trim(); buf = buf.slice(nl + 1); if (!line) continue; let obj; try { obj = JSON.parse(line); } catch { continue; } if (obj.error) { console.error(`❌ Ollama error: ${obj.error}`); process.exit(1); } if (obj.message?.content) acc += obj.message.content; if (obj.done) { promptCount = obj.prompt_eval_count ?? 0; evalCount = obj.eval_count ?? 0; } } } // Flush a final line that arrived without a trailing newline. Ollama terminates every // chunk with one, but a body that ends mid-line would otherwise be dropped silently. const tail = buf.trim(); if (tail) { try { const obj = JSON.parse(tail); if (obj.error) { console.error(`❌ Ollama error: ${obj.error}`); process.exit(1); } if (obj.message?.content) acc += obj.message.content; if (obj.done) { promptCount = obj.prompt_eval_count ?? promptCount; evalCount = obj.eval_count ?? evalCount; } } catch { /* a truncated final line is not recoverable; the empty-response check below reports it */ } } evaluationText = acc.trim(); // Native /api/chat reports tokens as prompt_eval_count / eval_count, not an // OpenAI-shaped `usage` object; map them through the shared normalizer. const usage = normalizeOpenAIUsage({ prompt_tokens: promptCount, completion_tokens: evalCount, total_tokens: promptCount + evalCount, }); tracker.record('evaluation', usage); if (!evaluationText) { console.error('❌ Ollama returned an empty response.'); process.exit(1); } } catch (err) { if (err.name === 'TimeoutError') { console.error(`❌ Request timed out after ${Math.round(timeoutMs / 1000)}s.`); console.error(` Try a smaller/faster model, or increase OLLAMA_TIMEOUT_MS.`); } else { console.error(`❌ Ollama API call failed: ${err.message}`); } process.exit(1); } // --------------------------------------------------------------------------- // Display evaluation // --------------------------------------------------------------------------- console.log('\n' + '═'.repeat(66)); console.log(' CAREER-OPS EVALUATION — powered by Ollama (' + modelName + ')'); console.log('═'.repeat(66) + '\n'); console.log(evaluationText); // --------------------------------------------------------------------------- // Parse score summary // --------------------------------------------------------------------------- const summary = parseScoreSummary(evaluationText); const company = summary?.company || 'unknown'; const role = summary?.role || 'unknown'; const score = summary?.score || '?'; const archetype = summary?.archetype || 'unknown'; const legitimacy = summary?.legitimacy || 'unknown'; // An addition for company and role "unknown" would merge as a real application. const trackable = Boolean(summary?.company && summary.role && summary.role.toLowerCase() !== 'unknown'); // --------------------------------------------------------------------------- // Save report // --------------------------------------------------------------------------- if (saveReport) { let reservedNumbers = []; let saveStage = 'report'; try { if (!existsSync(PATHS.reports)) { mkdirSync(PATHS.reports, { recursive: true }); } reservedNumbers = await reserveReportNumbers(1, { rootDir: DATA_ROOT, reportsDir: PATHS.reports }); const num = formatReportNumber(reservedNumbers[0]); // LOCAL calendar day (#3070). This one value becomes three things that have to // agree with each other and with the user's calendar: the report FILENAME // ({num}-{slug}-{today}.md), the report's own `**Date:**` header, and the date // column of the tracker row written for it. // // On the UTC day an evaluation run on a Sunday evening in the Americas produces // 042-acme-2026-08-18.md, dated the 18th, in a tracker row dated the 18th — // while every other date the user sees, and every date the other scripts now // stamp, says the 17th. The filename is the part that cannot be corrected // later: reports are addressed by it. const today = localToday(); const companySlug = slugifyCompany(company); const filename = `${num}-${companySlug}-${today}.md`; const reportPath = join(PATHS.reports, filename); const reportContent = `# Evaluation: ${company} — ${role} **Date:** ${today} **Archetype:** ${archetype} **Score:** ${score}/5 **URL:** ${postingUrl || '(pasted)'} **Legitimacy:** ${legitimacy} **PDF:** pending **Tool:** Ollama (${modelName}) --- ${evaluationText.replace(/---SCORE_SUMMARY---[\s\S]*?---END_SUMMARY---/, '').trim()} `; writeFileSync(reportPath, withJdArchiveSection(reportContent, jdText), 'utf-8'); console.log(`\n✅ Report saved: reports/${filename}`); if (!trackable) { console.warn(`\n⚠️ The reply has no ${summary ? 'company and role in its SCORE_SUMMARY' : 'SCORE_SUMMARY block'}, so no tracker row was written.`); console.warn(' Re-run the evaluation, or use a model that follows the report format.'); } else { // AGENTS.md Pipeline Integrity rule 1: never hand the user a row to paste // into data/applications.md. Evaluations persist as a tracker addition and // merge-tracker.mjs applies dedup, status validation, report-link // normalization and the tracker lock. A pasted literal skipped all of that, // and at 8 cells it was also silently dropped by every reader's width guard. // Field order is the TSV contract's -- status BEFORE score; merge-tracker // swaps them into the tracker's own column order, resolved by name. const additionName = `${num}-${companySlug}.tsv`; const trackerFields = [ String(parseInt(num, 10)), today, tsvSafe(company), tsvSafe(role), 'Evaluated', normalizedTrackerScore(score), '❌', `[${num}](reports/${filename})`, tsvSafe(`Ollama evaluation (${modelName})`), ]; // Optional tenth field, labelled in the header below so it resolves by name. // Pass 0 can then match on it instead of waiting for --backfill-urls. if (postingUrl) trackerFields.push(tsvSafe(postingUrl)); // Header row first (#3517/#3706): merge-tracker resolves the fields by name, // so this row cannot be ingested into the wrong columns. The optional URL // needs its own label -- values are read BY label, so a tenth field the // header does not name is not mis-mapped, it is dropped. const additionHeader = postingUrl ? `${TSV_ADDITION_HEADER}\turl` : TSV_ADDITION_HEADER; saveStage = 'tracker addition'; mkdirSync(PATHS.trackerAdditions, { recursive: true }); writeFileSync( join(PATHS.trackerAdditions, additionName), `${additionHeader}\n${trackerFields.join('\t')}\n`, 'utf-8', ); console.log(`\n📊 Tracker addition saved: batch/tracker-additions/${additionName}`); console.log(' Run `node merge-tracker.mjs` to merge it into the tracker.'); } } catch (err) { console.warn(`⚠️ Could not save evaluation (${saveStage}): ${err.message}`); process.exitCode = 1; } finally { if (reservedNumbers.length > 0) { try { await releaseReportNumbers(reservedNumbers, { reportsDir: PATHS.reports }); } catch (err) { console.warn(`⚠️ Could not release report reservation: ${err.message}`); } } } } console.log('\n' + '─'.repeat(66)); console.log(` Score: ${score}/5 | Archetype: ${archetype} | Legitimacy: ${legitimacy}`); console.log('─'.repeat(66) + '\n'); console.log(formatBreakdown(tracker, modelName, 'ollama'));