tanyar09
c692853c38
- Added support for customizable AI context and model selection in job search analysis. - Improved logging to provide detailed information about AI analysis status and parameters. - Updated README to mask sensitive LinkedIn credentials for security. - Refactored AI analysis integration to streamline data preparation and result embedding.
317 lines
10 KiB
JavaScript
317 lines
10 KiB
JavaScript
#!/usr/bin/env node
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/**
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* Job Search Parser - Refactored
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*
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* Uses core-parser for browser management and site-specific strategies for parsing logic
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*/
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const path = require("path");
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const fs = require("fs");
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const CoreParser = require("../core-parser");
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const { skipthedriveStrategy } = require("./strategies/skipthedrive-strategy");
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const { linkedinJobsStrategy } = require("./strategies/linkedin-jobs-strategy");
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const { logger, analyzeBatch, checkOllamaStatus, DEFAULT_MODEL } = require("ai-analyzer");
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// Load environment variables
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require("dotenv").config({ path: path.join(__dirname, ".env") });
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// Configuration from environment
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const HEADLESS = process.env.HEADLESS !== "false";
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const SEARCH_KEYWORDS =
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process.env.SEARCH_KEYWORDS || "co-op,intern";//"software engineer,developer,programmer";
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const LOCATION_FILTER = process.env.LOCATION_FILTER;
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const ENABLE_AI_ANALYSIS = process.env.ENABLE_AI_ANALYSIS === "true";
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const AI_CONTEXT = process.env.AI_CONTEXT || "Job market analysis focusing on job postings, skills, and trends";
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const OLLAMA_MODEL = process.env.OLLAMA_MODEL || DEFAULT_MODEL;
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const MAX_PAGES = parseInt(process.env.MAX_PAGES) || 5;
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const EXCLUDE_REJECTED = process.env.EXCLUDE_REJECTED === "true";
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// Available site strategies
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const SITE_STRATEGIES = {
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skipthedrive: skipthedriveStrategy,
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linkedin: linkedinJobsStrategy,
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// Add more site strategies here
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// indeed: indeedStrategy,
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// glassdoor: glassdoorStrategy,
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};
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/**
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* Parse command line arguments
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*/
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function parseArguments() {
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const args = process.argv.slice(2);
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const options = {
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sites: ["skipthedrive"], // default
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keywords: null,
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locationFilter: null,
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maxPages: MAX_PAGES,
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excludeRejected: EXCLUDE_REJECTED,
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};
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args.forEach((arg) => {
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if (arg.startsWith("--sites=")) {
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options.sites = arg
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.split("=")[1]
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.split(",")
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.map((s) => s.trim());
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} else if (arg.startsWith("--keywords=")) {
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options.keywords = arg
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.split("=")[1]
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.split(",")
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.map((k) => k.trim());
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} else if (arg.startsWith("--location=")) {
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options.locationFilter = arg.split("=")[1];
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} else if (arg.startsWith("--max-pages=")) {
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const value = arg.split("=")[1];
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// Support "all" or "0" to mean unlimited pages
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if (value === "all" || value === "0") {
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options.maxPages = 0; // 0 means unlimited
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} else {
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options.maxPages = parseInt(value) || MAX_PAGES;
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}
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} else if (arg === "--no-rejected" || arg === "--exclude-rejected") {
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options.excludeRejected = true;
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}
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});
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return options;
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}
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/**
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* Main job search parser function
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*/
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async function startJobSearchParser(options = {}) {
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const cliOptions = parseArguments();
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const finalOptions = { ...cliOptions, ...options };
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const coreParser = new CoreParser({
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headless: HEADLESS,
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timeout: 30000,
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});
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try {
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logger.step("🚀 Job Search Parser Starting...");
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// Parse keywords
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const keywords =
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finalOptions.keywords || SEARCH_KEYWORDS.split(",").map((k) => k.trim());
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const locationFilter = finalOptions.locationFilter || LOCATION_FILTER;
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const sites = finalOptions.sites;
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const excludeRejected = finalOptions.excludeRejected !== undefined ? finalOptions.excludeRejected : EXCLUDE_REJECTED;
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logger.info(`📦 Selected job sites: ${sites.join(", ")}`);
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logger.info(`🔍 Search Keywords: ${keywords.join(", ")}`);
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logger.info(`📍 Location Filter: ${locationFilter || "None"}`);
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logger.info(
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`🧠 AI Analysis: ${ENABLE_AI_ANALYSIS ? "Enabled" : "Disabled"}`
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);
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if (ENABLE_AI_ANALYSIS) {
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logger.info(` Context: "${AI_CONTEXT}"`);
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logger.info(` Model: ${OLLAMA_MODEL}`);
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}
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const allResults = [];
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const allRejectedResults = [];
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const siteResults = {};
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// Process each selected site
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for (const site of sites) {
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const strategy = SITE_STRATEGIES[site];
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if (!strategy) {
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logger.error(`❌ Unknown site strategy: ${site}`);
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continue;
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}
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try {
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logger.step(`\n🌐 Parsing ${site}...`);
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const startTime = Date.now();
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// Prepare strategy options
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const strategyOptions = {
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keywords,
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locationFilter,
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maxPages: finalOptions.maxPages,
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};
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// Add credentials for LinkedIn
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if (site === "linkedin") {
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const LINKEDIN_USERNAME = process.env.LINKEDIN_USERNAME;
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const LINKEDIN_PASSWORD = process.env.LINKEDIN_PASSWORD;
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if (!LINKEDIN_USERNAME || !LINKEDIN_PASSWORD) {
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logger.error(`❌ LinkedIn credentials not found. Please set LINKEDIN_USERNAME and LINKEDIN_PASSWORD in .env file`);
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siteResults[site] = {
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count: 0,
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rejected: 0,
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duration: "0s",
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error: "LinkedIn credentials not found",
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};
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continue;
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}
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strategyOptions.credentials = {
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username: LINKEDIN_USERNAME,
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password: LINKEDIN_PASSWORD,
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};
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strategyOptions.location = process.env.LINKEDIN_JOB_LOCATION || "";
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}
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const parseResult = await strategy(coreParser, strategyOptions);
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const { results, rejectedResults, summary } = parseResult;
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const duration = ((Date.now() - startTime) / 1000).toFixed(2);
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// Collect results
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logger.info(`📦 Strategy returned: ${results.length} results, ${rejectedResults.length} rejected`);
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allResults.push(...results);
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allRejectedResults.push(...rejectedResults);
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logger.info(`📦 Total accumulated: ${allResults.length} results, ${allRejectedResults.length} rejected`);
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siteResults[site] = {
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count: results.length,
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rejected: rejectedResults.length,
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duration: `${duration}s`,
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summary,
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};
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logger.success(
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`✅ ${site} completed in ${duration}s - Found ${results.length} jobs`
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);
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} catch (error) {
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logger.error(`❌ ${site} parsing failed: ${error.message}`);
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siteResults[site] = {
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count: 0,
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rejected: 0,
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duration: "0s",
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error: error.message,
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};
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}
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}
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// AI Analysis if enabled
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let analysisResults = null;
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if (ENABLE_AI_ANALYSIS && allResults.length > 0) {
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logger.step("🧠 Running AI Analysis...");
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const ollamaAvailable = await checkOllamaStatus(OLLAMA_MODEL);
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if (ollamaAvailable) {
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// Prepare data for analysis (analyzeBatch expects objects with 'text' field)
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const analysisData = allResults.map((job) => ({
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text: `${job.title || ""} at ${job.company || ""}. ${job.description || ""}`.trim(),
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location: job.location || "",
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keyword: job.keyword || "",
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timestamp: job.extractedAt || job.postedDate || "",
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}));
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analysisResults = await analyzeBatch(
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analysisData,
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AI_CONTEXT,
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OLLAMA_MODEL
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);
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// Embed AI analysis into each job result
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allResults.forEach((job, index) => {
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if (analysisResults && analysisResults[index]) {
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job.aiAnalysis = {
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isRelevant: analysisResults[index].isRelevant,
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confidence: analysisResults[index].confidence,
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reasoning: analysisResults[index].reasoning,
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context: AI_CONTEXT,
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model: OLLAMA_MODEL,
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analyzedAt: new Date().toISOString(),
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};
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}
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});
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logger.success(
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`✅ AI Analysis completed for ${allResults.length} jobs`
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);
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} else {
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logger.warning("⚠️ Ollama not available, skipping AI analysis");
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}
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}
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// Save results
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logger.info(`💾 Preparing to save: ${allResults.length} results, ${allRejectedResults.length} rejected`);
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logger.info(`💾 EXCLUDE_REJECTED env: ${process.env.EXCLUDE_REJECTED}, excludeRejected variable: ${excludeRejected}`);
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const outputData = {
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metadata: {
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extractedAt: new Date().toISOString(),
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parser: "job-search-parser",
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version: "2.0.0",
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sites: sites,
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keywords: keywords.join(", "),
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locationFilter,
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aiAnalysisEnabled: ENABLE_AI_ANALYSIS,
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aiContext: ENABLE_AI_ANALYSIS ? AI_CONTEXT : undefined,
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aiModel: ENABLE_AI_ANALYSIS ? OLLAMA_MODEL : undefined,
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analysisResults,
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rejectedJobsExcluded: excludeRejected,
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},
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results: allResults,
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siteResults,
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};
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// Always include rejectedResults if not excluded (make it explicit, not using spread)
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if (!excludeRejected) {
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outputData.rejectedResults = allRejectedResults;
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logger.info(`✅ Including ${allRejectedResults.length} rejected results in output`);
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} else {
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logger.info(`⏭️ Excluding rejected results (EXCLUDE_REJECTED=true)`);
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}
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logger.info(`💾 Final output: ${outputData.results.length} results, ${outputData.rejectedResults?.length || 0} rejected`);
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const resultsDir = path.join(__dirname, "results");
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if (!fs.existsSync(resultsDir)) {
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fs.mkdirSync(resultsDir, { recursive: true });
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}
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const timestamp = new Date().toISOString().replace(/[:.]/g, "-");
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const filename = `job-search-results-${timestamp}.json`;
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const filepath = path.join(resultsDir, filename);
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fs.writeFileSync(filepath, JSON.stringify(outputData, null, 2));
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// Final summary
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logger.step("\n📊 Job Search Parser Summary");
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logger.success(`✅ Total jobs found: ${allResults.length}`);
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logger.info(`❌ Total rejected: ${allRejectedResults.length}`);
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logger.info(`📁 Results saved to: ${filepath}`);
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logger.info("\n📈 Results by site:");
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for (const [site, stats] of Object.entries(siteResults)) {
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if (stats.error) {
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logger.error(` ${site}: ERROR - ${stats.error}`);
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} else {
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logger.info(
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` ${site}: ${stats.count} jobs found, ${stats.rejected} rejected (${stats.duration})`
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);
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}
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}
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logger.success("\n✅ Job Search Parser completed successfully!");
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return outputData;
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} catch (error) {
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logger.error(`❌ Job Search Parser failed: ${error.message}`);
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throw error;
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} finally {
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await coreParser.cleanup();
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}
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}
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// CLI handling
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if (require.main === module) {
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startJobSearchParser()
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.then(() => process.exit(0))
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.catch((error) => {
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console.error("Fatal error:", error.message);
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process.exit(1);
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});
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}
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module.exports = { startJobSearchParser };
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