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691d61aaee
...
master
7
.gitignore
vendored
7
.gitignore
vendored
@ -8,10 +8,3 @@ zip*
|
||||
*.7z
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*obfuscated.js
|
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.history
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# Debug files
|
||||
debug-*.js
|
||||
debug-*.png
|
||||
*.png
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||||
*.log
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||||
# Install scripts (optional - remove if you want to commit)
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install-ollama.sh
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||||
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||||
2
ai-analyzer/cli.js
Executable file → Normal file
2
ai-analyzer/cli.js
Executable file → Normal file
@ -1,4 +1,4 @@
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#!/usr/bin/env node
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#!/usr/bin/env node
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/**
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* AI Analyzer CLI
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@ -1,491 +1,301 @@
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const { logger } = require("./logger");
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/**
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* AI Analysis utilities for post processing with Ollama
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* Extracted from ai-analyzer-local.js for reuse across parsers
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*/
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// Default model from environment variable or fallback to "mistral"
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const DEFAULT_MODEL = process.env.OLLAMA_MODEL || "mistral";
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/**
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* Check if Ollama is running and the model is available
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*/
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async function checkOllamaStatus(
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model = DEFAULT_MODEL,
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ollamaHost = "http://localhost:11434"
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) {
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try {
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// Check if Ollama is running
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||||
const response = await fetch(`${ollamaHost}/api/tags`);
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||||
if (!response.ok) {
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throw new Error(`Ollama not running on ${ollamaHost}`);
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}
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const data = await response.json();
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const availableModels = data.models.map((m) => m.name);
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logger.ai("Ollama is running");
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logger.info(
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`📦 Available models: ${availableModels
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.map((m) => m.split(":")[0])
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.join(", ")}`
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);
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// Check if requested model is available
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const modelExists = availableModels.some((m) => m.startsWith(model));
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if (!modelExists) {
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logger.error(`Model "${model}" not found`);
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logger.error(`💡 Install it with: ollama pull ${model}`);
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logger.error(
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`💡 Or choose from: ${availableModels
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||||
.map((m) => m.split(":")[0])
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||||
.join(", ")}`
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||||
);
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return false;
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||||
}
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||||
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logger.success(`Using model: ${model}`);
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return true;
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||||
} catch (error) {
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logger.error(`Error connecting to Ollama: ${error.message}`);
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logger.error("💡 Make sure Ollama is installed and running:");
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logger.error(" 1. Install: https://ollama.ai/");
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logger.error(" 2. Start: ollama serve");
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logger.error(` 3. Install model: ollama pull ${model}`);
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return false;
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}
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}
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/**
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* Analyze multiple posts using local Ollama
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*/
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async function analyzeBatch(
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posts,
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context,
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model = DEFAULT_MODEL,
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ollamaHost = "http://localhost:11434"
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) {
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logger.ai(`Analyzing batch of ${posts.length} posts with ${model}...`);
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try {
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// Detect if context is about a student profile
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const isStudentContext = /student|undergraduate|first year|second year|third year|fourth year|freshman|sophomore|junior|senior|co-op|internship/i.test(context);
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// Build enhanced prompt based on context type
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let analysisInstructions = "";
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if (isStudentContext) {
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analysisInstructions = `
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ANALYSIS FOCUS (Student Context Detected):
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- Pay special attention to the "Requirements" section
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- Evaluate if the job requirements match the student's level (${context})
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- Consider: Are requirements too advanced? Are they appropriate for entry-level/co-op/internship?
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- Check if the role duties are suitable for a student's skill level
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- Look for keywords like "co-op", "internship", "entry-level", "student", "junior"
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- If requirements mention "years of experience", "senior", "expert", "PhD", etc., this may not be suitable
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- If requirements are reasonable for a student (basic skills, willingness to learn), mark as relevant`;
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} else {
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||||
analysisInstructions = `
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ANALYSIS FOCUS:
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- Evaluate overall relevance to: "${context}"
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- Consider job title, description, duties, and requirements
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- Assess if the job matches the specified criteria`;
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}
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const prompt = `Analyze ${posts.length} job postings for relevance to: "${context}"
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${analysisInstructions}
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JOB POSTINGS:
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${posts
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.map(
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(post, i) => {
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// For student contexts, prioritize Requirements section if text is too long
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let jobText = post.text;
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if (isStudentContext && jobText.length > 1200) {
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// Try to extract Requirements section if present
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const requirementsMatch = jobText.match(/Requirements?:[\s\S]{0,600}/i);
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const dutiesMatch = jobText.match(/Role Duties?:[\s\S]{0,300}/i);
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const titleMatch = jobText.match(/Title:[\s\S]{0,100}/i);
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if (requirementsMatch) {
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// Prioritize: Title + Requirements (most important for students)
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jobText = (titleMatch ? titleMatch[0] + "\n\n" : "") +
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(requirementsMatch ? requirementsMatch[0] : "") +
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(dutiesMatch ? "\n\n" + dutiesMatch[0] : "");
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||||
} else {
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// Fallback to truncation
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jobText = jobText.substring(0, 1200) + "...";
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}
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} else if (jobText.length > 1200) {
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jobText = jobText.substring(0, 1200) + "...";
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||||
}
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||||
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||||
return `
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JOB ${i + 1}:
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${jobText}
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`;
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}
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)
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.join("")}
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REQUIRED FORMAT - Respond with EXACTLY ${posts.length} lines, one per post:
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JOB 1: YES | 0.8 | reason here
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JOB 2: NO | 0.2 | reason here
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JOB 3: YES | 0.9 | reason here
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|
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RULES:
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- Use YES or NO (uppercase)
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- Use pipe character | as separator
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- Confidence must be 0.0 to 1.0 (decimal number)
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- Keep reasoning brief (one sentence)
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- MUST include all ${posts.length} jobs in order
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${isStudentContext ? "- When analyzing requirements, explicitly mention if requirements are too advanced or appropriate for the student level" : ""}
|
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|
||||
Examples:
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JOB 1: YES | 0.9 | co-op position suitable for first year students
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JOB 2: NO | 0.2 | requires 5+ years experience, too advanced
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JOB 3: YES | 0.7 | entry-level role with basic requirements appropriate for students`;
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||||
|
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// Add timeout to prevent hanging (5 minutes max)
|
||||
const controller = new AbortController();
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const timeoutId = setTimeout(() => controller.abort(), 5 * 60 * 1000); // 5 minutes
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||||
|
||||
try {
|
||||
const response = await fetch(`${ollamaHost}/api/generate`, {
|
||||
method: "POST",
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||||
headers: {
|
||||
"Content-Type": "application/json",
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||||
},
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||||
body: JSON.stringify({
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model: model,
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prompt: prompt,
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stream: false,
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||||
options: {
|
||||
temperature: 0.3,
|
||||
top_p: 0.9,
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||||
},
|
||||
}),
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||||
signal: controller.signal,
|
||||
});
|
||||
|
||||
clearTimeout(timeoutId);
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(
|
||||
`Ollama API error: ${response.status} ${response.statusText}`
|
||||
);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
const aiResponse = data.response.trim();
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||||
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||||
// Parse the response
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||||
const analyses = [];
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||||
const lines = aiResponse.split("\n").filter((line) => line.trim());
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||||
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||||
// Log the raw response for debugging
|
||||
logger.debug(`AI Response length: ${aiResponse.length} chars`);
|
||||
if (aiResponse.length > 0) {
|
||||
logger.debug(`AI Response (first 1000 chars):\n${aiResponse.substring(0, 1000)}`);
|
||||
} else {
|
||||
logger.warning("⚠️ AI response is empty!");
|
||||
}
|
||||
|
||||
for (let i = 0; i < posts.length; i++) {
|
||||
let analysis = {
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||||
postIndex: i + 1,
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||||
isRelevant: false,
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||||
confidence: 0.5,
|
||||
reasoning: "Could not parse AI response",
|
||||
};
|
||||
|
||||
// Try multiple patterns to find the post analysis
|
||||
// IMPORTANT: Try numbered patterns first, only use generic pattern as last resort
|
||||
const numberedPatterns = [
|
||||
// Exact format: POST 1: YES | 0.8 | reason
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||||
new RegExp(`POST\\s*${i + 1}:?\\s*(.+)`, "i"),
|
||||
// Numbered list: 1. YES | 0.8 | reason
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||||
new RegExp(`^\\s*${i + 1}[.)]\\s*(.+)`, "i"),
|
||||
// Just the number: 1: YES | 0.8 | reason
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||||
new RegExp(`^\\s*${i + 1}:\\s*(.+)`, "i"),
|
||||
];
|
||||
|
||||
let found = false;
|
||||
let matchedContent = null;
|
||||
|
||||
// First, try to find a line with the specific post number
|
||||
for (const line of lines) {
|
||||
for (const pattern of numberedPatterns) {
|
||||
const match = line.match(pattern);
|
||||
if (match) {
|
||||
matchedContent = match[1].trim();
|
||||
found = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
if (found) break;
|
||||
}
|
||||
|
||||
// If not found with numbered patterns, try position-based matching as fallback
|
||||
if (!found && lines.length > i) {
|
||||
const targetLine = lines[i];
|
||||
if (targetLine) {
|
||||
// Try to parse the line even without post number
|
||||
const genericMatch = targetLine.match(/^(?:POST\s*\d+:?\s*)?(.+)$/i);
|
||||
if (genericMatch) {
|
||||
matchedContent = genericMatch[1].trim();
|
||||
found = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (found && matchedContent) {
|
||||
const content = matchedContent;
|
||||
|
||||
// Try to parse: YES/NO | 0.X | reasoning
|
||||
let parts = content.split("|").map((p) => p.trim());
|
||||
|
||||
// If no pipe separator, try other separators
|
||||
if (parts.length < 2) {
|
||||
// Try colon separator: YES: 0.8: reason
|
||||
parts = content.split(":").map((p) => p.trim());
|
||||
}
|
||||
if (parts.length < 2) {
|
||||
// Try dash separator: YES - 0.8 - reason
|
||||
parts = content.split("-").map((p) => p.trim());
|
||||
}
|
||||
|
||||
// Extract YES/NO
|
||||
const relevanceText = parts[0] || content;
|
||||
analysis.isRelevant =
|
||||
relevanceText.toUpperCase().includes("YES") ||
|
||||
relevanceText.toLowerCase().includes("relevant") ||
|
||||
relevanceText.toLowerCase().includes("yes");
|
||||
|
||||
// Extract confidence (look for number between 0 and 1)
|
||||
if (parts.length >= 2) {
|
||||
const confidenceMatch = parts[1].match(/(0?\.\d+|1\.0|0|1)/);
|
||||
if (confidenceMatch) {
|
||||
analysis.confidence = Math.max(
|
||||
0,
|
||||
Math.min(1, parseFloat(confidenceMatch[1]) || 0.5)
|
||||
);
|
||||
}
|
||||
} else {
|
||||
// Try to find confidence in the whole content
|
||||
const confidenceMatch = content.match(/(0?\.\d+|1\.0|0|1)/);
|
||||
if (confidenceMatch) {
|
||||
analysis.confidence = Math.max(
|
||||
0,
|
||||
Math.min(1, parseFloat(confidenceMatch[1]) || 0.5)
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
// Extract reasoning (everything after confidence, or whole content if no structure)
|
||||
if (parts.length >= 3) {
|
||||
analysis.reasoning = parts.slice(2).join(" ").trim() || parts[2] || "No reasoning provided";
|
||||
} else if (parts.length === 2) {
|
||||
// If only 2 parts, second part might be reasoning
|
||||
analysis.reasoning = parts[1].substring(0, 200);
|
||||
} else {
|
||||
// Use the whole content as reasoning, but remove YES/NO and confidence
|
||||
let reasoning = content
|
||||
.replace(/YES|NO/gi, "")
|
||||
.replace(/0?\.\d+|1\.0/g, "")
|
||||
.replace(/\|/g, "")
|
||||
.trim();
|
||||
analysis.reasoning = reasoning || "Analysis provided but format unclear";
|
||||
}
|
||||
}
|
||||
|
||||
// If still not found, try to extract from the entire response by position
|
||||
if (!found && lines.length > 0) {
|
||||
// Try to get the line at position i (allowing for some variance)
|
||||
const targetLine = lines[Math.min(i, lines.length - 1)];
|
||||
if (targetLine) {
|
||||
// Extract any YES/NO indication
|
||||
analysis.isRelevant =
|
||||
targetLine.toUpperCase().includes("YES") ||
|
||||
targetLine.toLowerCase().includes("relevant");
|
||||
|
||||
// Extract confidence
|
||||
const confidenceMatch = targetLine.match(/(0?\.\d+|1\.0|0|1)/);
|
||||
if (confidenceMatch) {
|
||||
analysis.confidence = Math.max(
|
||||
0,
|
||||
Math.min(1, parseFloat(confidenceMatch[1]) || 0.5)
|
||||
);
|
||||
}
|
||||
|
||||
// Use the line as reasoning
|
||||
analysis.reasoning = targetLine.substring(0, 200).trim() || "Parsed from unstructured response";
|
||||
found = true;
|
||||
}
|
||||
}
|
||||
|
||||
// Last resort: if still not found, try to extract from the entire response text
|
||||
if (!found && aiResponse.length > 0) {
|
||||
// Look for any mention of relevance in the response
|
||||
const responseLower = aiResponse.toLowerCase();
|
||||
const hasRelevant = responseLower.includes("relevant") || responseLower.includes("yes");
|
||||
analysis.isRelevant = hasRelevant;
|
||||
|
||||
// Try to find any confidence number
|
||||
const allConfidenceMatches = aiResponse.match(/(0?\.\d+|1\.0|0|1)/g);
|
||||
if (allConfidenceMatches && allConfidenceMatches.length > i) {
|
||||
analysis.confidence = Math.max(
|
||||
0,
|
||||
Math.min(1, parseFloat(allConfidenceMatches[i]) || 0.5)
|
||||
);
|
||||
}
|
||||
|
||||
// Use a portion of the response as reasoning
|
||||
const responseSnippet = aiResponse.substring(i * 100, (i + 1) * 200).trim();
|
||||
analysis.reasoning = responseSnippet || "Could not parse structured response, using fallback";
|
||||
|
||||
logger.warning(`⚠️ Post ${i + 1}: Using fallback parsing - AI response format unclear`);
|
||||
}
|
||||
|
||||
analyses.push(analysis);
|
||||
}
|
||||
|
||||
// If we didn't get enough analyses, fill in defaults
|
||||
while (analyses.length < posts.length) {
|
||||
analyses.push({
|
||||
postIndex: analyses.length + 1,
|
||||
isRelevant: false,
|
||||
confidence: 0.3,
|
||||
reasoning: "AI response parsing failed",
|
||||
});
|
||||
}
|
||||
|
||||
return analyses;
|
||||
} catch (error) {
|
||||
clearTimeout(timeoutId);
|
||||
if (error.name === 'AbortError') {
|
||||
throw new Error('Request timeout: AI analysis took longer than 5 minutes');
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Error in batch AI analysis: ${error.message}`);
|
||||
|
||||
// Fallback: mark all as relevant with low confidence
|
||||
return posts.map((_, i) => ({
|
||||
postIndex: i + 1,
|
||||
isRelevant: true,
|
||||
confidence: 0.3,
|
||||
reasoning: `Analysis failed: ${error.message}`,
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Analyze a single post using local Ollama (fallback)
|
||||
*/
|
||||
async function analyzeSinglePost(
|
||||
text,
|
||||
context,
|
||||
model = DEFAULT_MODEL,
|
||||
ollamaHost = "http://localhost:11434"
|
||||
) {
|
||||
const prompt = `Analyze this LinkedIn post for relevance to: "${context}"
|
||||
|
||||
Post: "${text}"
|
||||
|
||||
Is this post relevant to "${context}"? Provide:
|
||||
1. YES or NO
|
||||
2. Confidence (0.0 to 1.0)
|
||||
3. Brief reason
|
||||
|
||||
Format: YES/NO | 0.X | reason`;
|
||||
|
||||
try {
|
||||
const response = await fetch(`${ollamaHost}/api/generate`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: model,
|
||||
prompt: prompt,
|
||||
stream: false,
|
||||
options: {
|
||||
temperature: 0.3,
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama API error: ${response.status}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
const aiResponse = data.response.trim();
|
||||
|
||||
// Parse response
|
||||
const parts = aiResponse.split("|").map((p) => p.trim());
|
||||
|
||||
if (parts.length >= 3) {
|
||||
return {
|
||||
isRelevant: parts[0].toUpperCase().includes("YES"),
|
||||
confidence: Math.max(0, Math.min(1, parseFloat(parts[1]) || 0.5)),
|
||||
reasoning: parts[2],
|
||||
};
|
||||
} else {
|
||||
// Fallback parsing
|
||||
return {
|
||||
isRelevant:
|
||||
aiResponse.toLowerCase().includes("yes") ||
|
||||
aiResponse.toLowerCase().includes("relevant"),
|
||||
confidence: 0.6,
|
||||
reasoning: aiResponse.substring(0, 100),
|
||||
};
|
||||
}
|
||||
} catch (error) {
|
||||
return {
|
||||
isRelevant: true, // Default to include on error
|
||||
confidence: 0.3,
|
||||
reasoning: `Analysis failed: ${error.message}`,
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Find the most recent results file if none specified
|
||||
*/
|
||||
function findLatestResultsFile(resultsDir = "results") {
|
||||
const fs = require("fs");
|
||||
const path = require("path");
|
||||
|
||||
if (!fs.existsSync(resultsDir)) {
|
||||
throw new Error("Results directory not found. Run the scraper first.");
|
||||
}
|
||||
|
||||
const files = fs
|
||||
.readdirSync(resultsDir)
|
||||
.filter(
|
||||
(f) =>
|
||||
(f.startsWith("results-") || f.startsWith("linkedin-results-")) &&
|
||||
f.endsWith(".json") &&
|
||||
!f.includes("-ai-")
|
||||
)
|
||||
.sort()
|
||||
.reverse();
|
||||
|
||||
if (files.length === 0) {
|
||||
throw new Error("No results files found. Run the scraper first.");
|
||||
}
|
||||
|
||||
return path.join(resultsDir, files[0]);
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
checkOllamaStatus,
|
||||
analyzeBatch,
|
||||
analyzeSinglePost,
|
||||
findLatestResultsFile,
|
||||
DEFAULT_MODEL, // Export so other modules can use it
|
||||
};
|
||||
const { logger } = require("./logger");
|
||||
|
||||
/**
|
||||
* AI Analysis utilities for post processing with Ollama
|
||||
* Extracted from ai-analyzer-local.js for reuse across parsers
|
||||
*/
|
||||
|
||||
/**
|
||||
* Check if Ollama is running and the model is available
|
||||
*/
|
||||
async function checkOllamaStatus(
|
||||
model = "mistral",
|
||||
ollamaHost = "http://localhost:11434"
|
||||
) {
|
||||
try {
|
||||
// Check if Ollama is running
|
||||
const response = await fetch(`${ollamaHost}/api/tags`);
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama not running on ${ollamaHost}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
const availableModels = data.models.map((m) => m.name);
|
||||
|
||||
logger.ai("Ollama is running");
|
||||
logger.info(
|
||||
`📦 Available models: ${availableModels
|
||||
.map((m) => m.split(":")[0])
|
||||
.join(", ")}`
|
||||
);
|
||||
|
||||
// Check if requested model is available
|
||||
const modelExists = availableModels.some((m) => m.startsWith(model));
|
||||
if (!modelExists) {
|
||||
logger.error(`Model "${model}" not found`);
|
||||
logger.error(`💡 Install it with: ollama pull ${model}`);
|
||||
logger.error(
|
||||
`💡 Or choose from: ${availableModels
|
||||
.map((m) => m.split(":")[0])
|
||||
.join(", ")}`
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
logger.success(`Using model: ${model}`);
|
||||
return true;
|
||||
} catch (error) {
|
||||
logger.error(`Error connecting to Ollama: ${error.message}`);
|
||||
logger.error("💡 Make sure Ollama is installed and running:");
|
||||
logger.error(" 1. Install: https://ollama.ai/");
|
||||
logger.error(" 2. Start: ollama serve");
|
||||
logger.error(` 3. Install model: ollama pull ${model}`);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Analyze multiple posts using local Ollama
|
||||
*/
|
||||
async function analyzeBatch(
|
||||
posts,
|
||||
context,
|
||||
model = "mistral",
|
||||
ollamaHost = "http://localhost:11434"
|
||||
) {
|
||||
logger.ai(`Analyzing batch of ${posts.length} posts with ${model}...`);
|
||||
|
||||
try {
|
||||
const prompt = `You are an expert at analyzing LinkedIn posts for relevance to specific contexts.
|
||||
|
||||
CONTEXT TO MATCH: "${context}"
|
||||
|
||||
Analyze these ${
|
||||
posts.length
|
||||
} LinkedIn posts and determine if each relates to the context above.
|
||||
|
||||
POSTS:
|
||||
${posts
|
||||
.map(
|
||||
(post, i) => `
|
||||
POST ${i + 1}:
|
||||
"${post.text.substring(0, 400)}${post.text.length > 400 ? "..." : ""}"
|
||||
`
|
||||
)
|
||||
.join("")}
|
||||
|
||||
For each post, provide:
|
||||
- Is it relevant to "${context}"? (YES/NO)
|
||||
- Confidence level (0.0 to 1.0)
|
||||
- Brief reasoning
|
||||
|
||||
Respond in this EXACT format for each post:
|
||||
POST 1: YES/NO | 0.X | brief reason
|
||||
POST 2: YES/NO | 0.X | brief reason
|
||||
POST 3: YES/NO | 0.X | brief reason
|
||||
|
||||
Examples:
|
||||
- For layoff context: "laid off 50 employees" = YES | 0.9 | mentions layoffs
|
||||
- For hiring context: "we're hiring developers" = YES | 0.8 | job posting
|
||||
- Unrelated content = NO | 0.1 | not relevant to context`;
|
||||
|
||||
const response = await fetch(`${ollamaHost}/api/generate`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: model,
|
||||
prompt: prompt,
|
||||
stream: false,
|
||||
options: {
|
||||
temperature: 0.3,
|
||||
top_p: 0.9,
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(
|
||||
`Ollama API error: ${response.status} ${response.statusText}`
|
||||
);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
const aiResponse = data.response.trim();
|
||||
|
||||
// Parse the response
|
||||
const analyses = [];
|
||||
const lines = aiResponse.split("\n").filter((line) => line.trim());
|
||||
|
||||
for (let i = 0; i < posts.length; i++) {
|
||||
let analysis = {
|
||||
postIndex: i + 1,
|
||||
isRelevant: false,
|
||||
confidence: 0.5,
|
||||
reasoning: "Could not parse AI response",
|
||||
};
|
||||
|
||||
// Look for lines that match "POST X:" pattern
|
||||
const postPattern = new RegExp(`POST\\s*${i + 1}:?\\s*(.+)`, "i");
|
||||
|
||||
for (const line of lines) {
|
||||
const match = line.match(postPattern);
|
||||
if (match) {
|
||||
const content = match[1].trim();
|
||||
|
||||
// Parse: YES/NO | 0.X | reasoning
|
||||
const parts = content.split("|").map((p) => p.trim());
|
||||
|
||||
if (parts.length >= 3) {
|
||||
analysis.isRelevant = parts[0].toUpperCase().includes("YES");
|
||||
analysis.confidence = Math.max(
|
||||
0,
|
||||
Math.min(1, parseFloat(parts[1]) || 0.5)
|
||||
);
|
||||
analysis.reasoning = parts[2] || "No reasoning provided";
|
||||
} else {
|
||||
// Fallback parsing
|
||||
analysis.isRelevant =
|
||||
content.toUpperCase().includes("YES") ||
|
||||
content.toLowerCase().includes("relevant");
|
||||
analysis.confidence = 0.6;
|
||||
analysis.reasoning = content.substring(0, 100);
|
||||
}
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
analyses.push(analysis);
|
||||
}
|
||||
|
||||
// If we didn't get enough analyses, fill in defaults
|
||||
while (analyses.length < posts.length) {
|
||||
analyses.push({
|
||||
postIndex: analyses.length + 1,
|
||||
isRelevant: false,
|
||||
confidence: 0.3,
|
||||
reasoning: "AI response parsing failed",
|
||||
});
|
||||
}
|
||||
|
||||
return analyses;
|
||||
} catch (error) {
|
||||
logger.error(`Error in batch AI analysis: ${error.message}`);
|
||||
|
||||
// Fallback: mark all as relevant with low confidence
|
||||
return posts.map((_, i) => ({
|
||||
postIndex: i + 1,
|
||||
isRelevant: true,
|
||||
confidence: 0.3,
|
||||
reasoning: `Analysis failed: ${error.message}`,
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Analyze a single post using local Ollama (fallback)
|
||||
*/
|
||||
async function analyzeSinglePost(
|
||||
text,
|
||||
context,
|
||||
model = "mistral",
|
||||
ollamaHost = "http://localhost:11434"
|
||||
) {
|
||||
const prompt = `Analyze this LinkedIn post for relevance to: "${context}"
|
||||
|
||||
Post: "${text}"
|
||||
|
||||
Is this post relevant to "${context}"? Provide:
|
||||
1. YES or NO
|
||||
2. Confidence (0.0 to 1.0)
|
||||
3. Brief reason
|
||||
|
||||
Format: YES/NO | 0.X | reason`;
|
||||
|
||||
try {
|
||||
const response = await fetch(`${ollamaHost}/api/generate`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: model,
|
||||
prompt: prompt,
|
||||
stream: false,
|
||||
options: {
|
||||
temperature: 0.3,
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama API error: ${response.status}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
const aiResponse = data.response.trim();
|
||||
|
||||
// Parse response
|
||||
const parts = aiResponse.split("|").map((p) => p.trim());
|
||||
|
||||
if (parts.length >= 3) {
|
||||
return {
|
||||
isRelevant: parts[0].toUpperCase().includes("YES"),
|
||||
confidence: Math.max(0, Math.min(1, parseFloat(parts[1]) || 0.5)),
|
||||
reasoning: parts[2],
|
||||
};
|
||||
} else {
|
||||
// Fallback parsing
|
||||
return {
|
||||
isRelevant:
|
||||
aiResponse.toLowerCase().includes("yes") ||
|
||||
aiResponse.toLowerCase().includes("relevant"),
|
||||
confidence: 0.6,
|
||||
reasoning: aiResponse.substring(0, 100),
|
||||
};
|
||||
}
|
||||
} catch (error) {
|
||||
return {
|
||||
isRelevant: true, // Default to include on error
|
||||
confidence: 0.3,
|
||||
reasoning: `Analysis failed: ${error.message}`,
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Find the most recent results file if none specified
|
||||
*/
|
||||
function findLatestResultsFile(resultsDir = "results") {
|
||||
const fs = require("fs");
|
||||
const path = require("path");
|
||||
|
||||
if (!fs.existsSync(resultsDir)) {
|
||||
throw new Error("Results directory not found. Run the scraper first.");
|
||||
}
|
||||
|
||||
const files = fs
|
||||
.readdirSync(resultsDir)
|
||||
.filter(
|
||||
(f) =>
|
||||
(f.startsWith("results-") || f.startsWith("linkedin-results-")) &&
|
||||
f.endsWith(".json") &&
|
||||
!f.includes("-ai-")
|
||||
)
|
||||
.sort()
|
||||
.reverse();
|
||||
|
||||
if (files.length === 0) {
|
||||
throw new Error("No results files found. Run the scraper first.");
|
||||
}
|
||||
|
||||
return path.join(resultsDir, files[0]);
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
checkOllamaStatus,
|
||||
analyzeBatch,
|
||||
analyzeSinglePost,
|
||||
findLatestResultsFile,
|
||||
};
|
||||
|
||||
@ -1,146 +1,107 @@
|
||||
/**
|
||||
* Text processing utilities for cleaning and validating content
|
||||
* Extracted from linkedout.js for reuse across parsers
|
||||
*/
|
||||
|
||||
/**
|
||||
* Clean text by removing hashtags, URLs, emojis, and normalizing whitespace
|
||||
*/
|
||||
function cleanText(text) {
|
||||
if (!text || typeof text !== "string") {
|
||||
return "";
|
||||
}
|
||||
|
||||
// Remove hashtags
|
||||
text = text.replace(/#\w+/g, "");
|
||||
|
||||
// Remove hashtag mentions
|
||||
text = text.replace(/\bhashtag\b/gi, "");
|
||||
text = text.replace(/hashtag-\w+/gi, "");
|
||||
|
||||
// Remove URLs
|
||||
text = text.replace(/https?:\/\/[^\s]+/g, "");
|
||||
|
||||
// Remove emojis (Unicode ranges for common emoji)
|
||||
text = text.replace(
|
||||
/[\u{1F600}-\u{1F64F}\u{1F300}-\u{1F5FF}\u{1F680}-\u{1F6FF}\u{1F1E0}-\u{1F1FF}]/gu,
|
||||
""
|
||||
);
|
||||
|
||||
// Normalize whitespace
|
||||
text = text.replace(/\s+/g, " ").trim();
|
||||
|
||||
return text;
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if text contains any of the specified keywords (case insensitive)
|
||||
*/
|
||||
function containsAnyKeyword(text, keywords) {
|
||||
if (!text || !Array.isArray(keywords)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
const lowerText = text.toLowerCase();
|
||||
return keywords.some((keyword) => lowerText.includes(keyword.toLowerCase()));
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if text contains all of the specified keywords (case insensitive)
|
||||
*/
|
||||
function containsAllKeywords(text, keywords) {
|
||||
if (!text || !Array.isArray(keywords)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
const lowerText = text.toLowerCase();
|
||||
return keywords.every((keyword) => lowerText.includes(keyword.toLowerCase()));
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if text matches keyword groups with AND logic between groups and OR logic within groups
|
||||
* @param {string} text - Text to search in
|
||||
* @param {Array<Array<string>>} keywordGroups - Array of keyword groups, each group is an array of OR keywords
|
||||
* @returns {boolean} - True if text matches all groups (AND logic) and at least one keyword in each group (OR logic)
|
||||
*/
|
||||
function matchesKeywordGroups(text, keywordGroups) {
|
||||
if (!text || !Array.isArray(keywordGroups) || keywordGroups.length === 0) {
|
||||
return false;
|
||||
}
|
||||
|
||||
const lowerText = text.toLowerCase();
|
||||
|
||||
// All groups must match (AND logic)
|
||||
return keywordGroups.every((group) => {
|
||||
if (!Array.isArray(group) || group.length === 0) {
|
||||
return false;
|
||||
}
|
||||
// At least one keyword in the group must match (OR logic)
|
||||
return group.some((keyword) =>
|
||||
lowerText.includes(keyword.toLowerCase().trim())
|
||||
);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Validate if text meets basic quality criteria
|
||||
*/
|
||||
function isValidText(text, minLength = 30) {
|
||||
if (!text || typeof text !== "string") {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check minimum length
|
||||
if (text.length < minLength) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check if text contains alphanumeric characters
|
||||
if (!/[a-zA-Z0-9]/.test(text)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract domain from URL
|
||||
*/
|
||||
function extractDomain(url) {
|
||||
if (!url || typeof url !== "string") {
|
||||
return null;
|
||||
}
|
||||
|
||||
try {
|
||||
const urlObj = new URL(url);
|
||||
return urlObj.hostname;
|
||||
} catch (error) {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Normalize URL by removing query parameters and fragments
|
||||
*/
|
||||
function normalizeUrl(url) {
|
||||
if (!url || typeof url !== "string") {
|
||||
return "";
|
||||
}
|
||||
|
||||
try {
|
||||
const urlObj = new URL(url);
|
||||
return `${urlObj.protocol}//${urlObj.hostname}${urlObj.pathname}`;
|
||||
} catch (error) {
|
||||
return url;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
cleanText,
|
||||
containsAnyKeyword,
|
||||
containsAllKeywords,
|
||||
matchesKeywordGroups,
|
||||
isValidText,
|
||||
extractDomain,
|
||||
normalizeUrl,
|
||||
};
|
||||
/**
|
||||
* Text processing utilities for cleaning and validating content
|
||||
* Extracted from linkedout.js for reuse across parsers
|
||||
*/
|
||||
|
||||
/**
|
||||
* Clean text by removing hashtags, URLs, emojis, and normalizing whitespace
|
||||
*/
|
||||
function cleanText(text) {
|
||||
if (!text || typeof text !== "string") {
|
||||
return "";
|
||||
}
|
||||
|
||||
// Remove hashtags
|
||||
text = text.replace(/#\w+/g, "");
|
||||
|
||||
// Remove hashtag mentions
|
||||
text = text.replace(/\bhashtag\b/gi, "");
|
||||
text = text.replace(/hashtag-\w+/gi, "");
|
||||
|
||||
// Remove URLs
|
||||
text = text.replace(/https?:\/\/[^\s]+/g, "");
|
||||
|
||||
// Remove emojis (Unicode ranges for common emoji)
|
||||
text = text.replace(
|
||||
/[\u{1F600}-\u{1F64F}\u{1F300}-\u{1F5FF}\u{1F680}-\u{1F6FF}\u{1F1E0}-\u{1F1FF}]/gu,
|
||||
""
|
||||
);
|
||||
|
||||
// Normalize whitespace
|
||||
text = text.replace(/\s+/g, " ").trim();
|
||||
|
||||
return text;
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if text contains any of the specified keywords (case insensitive)
|
||||
*/
|
||||
function containsAnyKeyword(text, keywords) {
|
||||
if (!text || !Array.isArray(keywords)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
const lowerText = text.toLowerCase();
|
||||
return keywords.some((keyword) => lowerText.includes(keyword.toLowerCase()));
|
||||
}
|
||||
|
||||
/**
|
||||
* Validate if text meets basic quality criteria
|
||||
*/
|
||||
function isValidText(text, minLength = 30) {
|
||||
if (!text || typeof text !== "string") {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check minimum length
|
||||
if (text.length < minLength) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check if text contains alphanumeric characters
|
||||
if (!/[a-zA-Z0-9]/.test(text)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract domain from URL
|
||||
*/
|
||||
function extractDomain(url) {
|
||||
if (!url || typeof url !== "string") {
|
||||
return null;
|
||||
}
|
||||
|
||||
try {
|
||||
const urlObj = new URL(url);
|
||||
return urlObj.hostname;
|
||||
} catch (error) {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Normalize URL by removing query parameters and fragments
|
||||
*/
|
||||
function normalizeUrl(url) {
|
||||
if (!url || typeof url !== "string") {
|
||||
return "";
|
||||
}
|
||||
|
||||
try {
|
||||
const urlObj = new URL(url);
|
||||
return `${urlObj.protocol}//${urlObj.hostname}${urlObj.pathname}`;
|
||||
} catch (error) {
|
||||
return url;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
cleanText,
|
||||
containsAnyKeyword,
|
||||
isValidText,
|
||||
extractDomain,
|
||||
normalizeUrl,
|
||||
};
|
||||
|
||||
@ -20,26 +20,7 @@ class CoreParser {
|
||||
this.browser = await playwright.chromium.launch({
|
||||
headless: this.config.headless
|
||||
});
|
||||
|
||||
// Create context with user agent to appear more like a real browser
|
||||
const contextOptions = {
|
||||
userAgent: this.config.userAgent || 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
|
||||
viewport: { width: 1920, height: 1080 },
|
||||
locale: 'en-US',
|
||||
timezoneId: 'America/New_York',
|
||||
};
|
||||
|
||||
// Add extra HTTP headers to appear more legitimate
|
||||
contextOptions.extraHTTPHeaders = {
|
||||
'Accept-Language': 'en-US,en;q=0.9',
|
||||
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
|
||||
'Accept-Encoding': 'gzip, deflate, br',
|
||||
'DNT': '1',
|
||||
'Connection': 'keep-alive',
|
||||
'Upgrade-Insecure-Requests': '1',
|
||||
};
|
||||
|
||||
this.context = await this.browser.newContext(contextOptions);
|
||||
this.context = await this.browser.newContext();
|
||||
}
|
||||
|
||||
async createPage(id) {
|
||||
@ -80,7 +61,3 @@ class CoreParser {
|
||||
}
|
||||
|
||||
module.exports = CoreParser;
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@ -1,9 +1,7 @@
|
||||
{
|
||||
"name": "core-parser",
|
||||
"version": "1.0.0",
|
||||
"main": "index.js",
|
||||
"description": "Core parser utilities for browser management",
|
||||
"dependencies": {
|
||||
"playwright": "^1.40.0"
|
||||
}
|
||||
}
|
||||
{
|
||||
"name": "core-parser",
|
||||
"version": "1.0.0",
|
||||
"main": "index.js",
|
||||
"description": "Core parser utilities for browser management",
|
||||
"dependencies": {}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@ -10,10 +10,7 @@ const path = require("path");
|
||||
const fs = require("fs");
|
||||
const CoreParser = require("../core-parser");
|
||||
const { skipthedriveStrategy } = require("./strategies/skipthedrive-strategy");
|
||||
const { linkedinJobsStrategy } = require("./strategies/linkedin-jobs-strategy");
|
||||
const { indeedStrategy } = require("./strategies/indeed-strategy");
|
||||
const { logger, analyzeBatch, checkOllamaStatus, DEFAULT_MODEL } = require("ai-analyzer");
|
||||
const { convertResultsToCsv } = require("./src/csv-utils");
|
||||
const { logger, analyzeBatch, checkOllamaStatus } = require("ai-analyzer");
|
||||
|
||||
// Load environment variables
|
||||
require("dotenv").config({ path: path.join(__dirname, ".env") });
|
||||
@ -21,23 +18,16 @@ require("dotenv").config({ path: path.join(__dirname, ".env") });
|
||||
// Configuration from environment
|
||||
const HEADLESS = process.env.HEADLESS !== "false";
|
||||
const SEARCH_KEYWORDS =
|
||||
process.env.SEARCH_KEYWORDS || "co-op,intern";//"software engineer,developer,programmer";
|
||||
process.env.SEARCH_KEYWORDS || "software engineer,developer,programmer";
|
||||
const LOCATION_FILTER = process.env.LOCATION_FILTER;
|
||||
const ENABLE_AI_ANALYSIS = process.env.ENABLE_AI_ANALYSIS === "true";
|
||||
const AI_CONTEXT = process.env.AI_CONTEXT || "Job market analysis focusing on job postings, skills, and trends";
|
||||
const OLLAMA_MODEL = process.env.OLLAMA_MODEL || DEFAULT_MODEL;
|
||||
const MAX_PAGES = parseInt(process.env.MAX_PAGES) || 5;
|
||||
const EXCLUDE_REJECTED = process.env.EXCLUDE_REJECTED === "true";
|
||||
const OUTPUT_FORMAT = process.env.OUTPUT_FORMAT || "json"; // "json", "csv", or "both"
|
||||
const MIN_DATE = process.env.MIN_DATE; // Minimum posted date (format: YYYY-MM-DD)
|
||||
const USE_AND_LOGIC = process.env.USE_AND_LOGIC === "true"; // Use AND logic for keywords
|
||||
|
||||
// Available site strategies
|
||||
const SITE_STRATEGIES = {
|
||||
skipthedrive: skipthedriveStrategy,
|
||||
linkedin: linkedinJobsStrategy,
|
||||
indeed: indeedStrategy,
|
||||
// Add more site strategies here
|
||||
// indeed: indeedStrategy,
|
||||
// glassdoor: glassdoorStrategy,
|
||||
};
|
||||
|
||||
@ -51,10 +41,6 @@ function parseArguments() {
|
||||
keywords: null,
|
||||
locationFilter: null,
|
||||
maxPages: MAX_PAGES,
|
||||
excludeRejected: EXCLUDE_REJECTED,
|
||||
outputFormat: OUTPUT_FORMAT,
|
||||
minDate: MIN_DATE,
|
||||
useAndLogic: USE_AND_LOGIC, // Use AND logic instead of OR logic for keywords (from env or CLI)
|
||||
};
|
||||
|
||||
args.forEach((arg) => {
|
||||
@ -71,26 +57,7 @@ function parseArguments() {
|
||||
} else if (arg.startsWith("--location=")) {
|
||||
options.locationFilter = arg.split("=")[1];
|
||||
} else if (arg.startsWith("--max-pages=")) {
|
||||
const value = arg.split("=")[1];
|
||||
// Support "all" or "0" to mean unlimited pages
|
||||
if (value === "all" || value === "0") {
|
||||
options.maxPages = 0; // 0 means unlimited
|
||||
} else {
|
||||
options.maxPages = parseInt(value) || MAX_PAGES;
|
||||
}
|
||||
} else if (arg === "--no-rejected" || arg === "--exclude-rejected") {
|
||||
options.excludeRejected = true;
|
||||
} else if (arg.startsWith("--output=") || arg.startsWith("--format=")) {
|
||||
const format = arg.split("=")[1].toLowerCase();
|
||||
if (["json", "csv", "both"].includes(format)) {
|
||||
options.outputFormat = format;
|
||||
} else {
|
||||
logger.warning(`⚠️ Unknown output format: ${format}. Using default: json`);
|
||||
}
|
||||
} else if (arg.startsWith("--min-date=")) {
|
||||
options.minDate = arg.split("=")[1];
|
||||
} else if (arg === "--and" || arg === "--all-keywords") {
|
||||
options.useAndLogic = true; // CLI flag overrides env variable
|
||||
options.maxPages = parseInt(arg.split("=")[1]) || MAX_PAGES;
|
||||
}
|
||||
});
|
||||
|
||||
@ -113,136 +80,21 @@ async function startJobSearchParser(options = {}) {
|
||||
logger.step("🚀 Job Search Parser Starting...");
|
||||
|
||||
// Parse keywords
|
||||
let keywords =
|
||||
const keywords =
|
||||
finalOptions.keywords || SEARCH_KEYWORDS.split(",").map((k) => k.trim());
|
||||
|
||||
// Parse keyword groups if AND logic is enabled and keywords contain pipe (|) separator
|
||||
// Format: "co-op|intern,summer 2026" means (co-op OR intern) AND (summer 2026)
|
||||
let keywordGroups = null;
|
||||
if (finalOptions.useAndLogic && keywords.some(k => k.includes('|'))) {
|
||||
keywordGroups = keywords.map(group =>
|
||||
group.split('|').map(k => k.trim()).filter(k => k.length > 0)
|
||||
);
|
||||
logger.info(`🔍 Keyword Groups: ${keywordGroups.map(g => `(${g.join(' OR ')})`).join(' AND ')}`);
|
||||
}
|
||||
|
||||
const locationFilter = finalOptions.locationFilter || LOCATION_FILTER;
|
||||
const sites = finalOptions.sites;
|
||||
const excludeRejected = finalOptions.excludeRejected !== undefined ? finalOptions.excludeRejected : EXCLUDE_REJECTED;
|
||||
|
||||
logger.info(`📦 Selected job sites: ${sites.join(", ")}`);
|
||||
logger.info(`🔍 Search Keywords: ${keywords.join(", ")}`);
|
||||
if (keywordGroups) {
|
||||
logger.info(`🔗 Keyword Logic: Grouped AND/OR - ${keywordGroups.map(g => `(${g.join(' OR ')})`).join(' AND ')}`);
|
||||
} else {
|
||||
logger.info(`🔗 Keyword Logic: ${finalOptions.useAndLogic ? "AND (all keywords must match)" : "OR (any keyword matches)"}`);
|
||||
}
|
||||
logger.info(`📍 Location Filter: ${locationFilter || "None"}`);
|
||||
const minDate = finalOptions.minDate || MIN_DATE;
|
||||
if (minDate) {
|
||||
logger.info(`📅 Min Date Filter: ${minDate} (jobs posted after this date)`);
|
||||
}
|
||||
logger.info(
|
||||
`🧠 AI Analysis: ${ENABLE_AI_ANALYSIS ? "Enabled" : "Disabled"}`
|
||||
);
|
||||
if (ENABLE_AI_ANALYSIS) {
|
||||
logger.info(` Context: "${AI_CONTEXT}"`);
|
||||
logger.info(` Model: ${OLLAMA_MODEL}`);
|
||||
}
|
||||
|
||||
const allResults = [];
|
||||
const allRejectedResults = [];
|
||||
const siteResults = {};
|
||||
let analysisResults = null;
|
||||
|
||||
// Initialize results directory and file for incremental saving
|
||||
const resultsDir = path.join(__dirname, "results");
|
||||
if (!fs.existsSync(resultsDir)) {
|
||||
fs.mkdirSync(resultsDir, { recursive: true });
|
||||
}
|
||||
|
||||
const timestamp = new Date().toISOString().replace(/[:.]/g, "-");
|
||||
const outputFormat = finalOptions.outputFormat || OUTPUT_FORMAT;
|
||||
let incrementalJsonFilepath = null;
|
||||
let incrementalCsvFilepath = null;
|
||||
|
||||
// Initialize incremental save files
|
||||
if (outputFormat === "json" || outputFormat === "both") {
|
||||
const jsonFilename = `job-search-results-${timestamp}.json`;
|
||||
incrementalJsonFilepath = path.join(resultsDir, jsonFilename);
|
||||
}
|
||||
if (outputFormat === "csv" || outputFormat === "both") {
|
||||
const csvFilename = `job-search-results-${timestamp}.csv`;
|
||||
incrementalCsvFilepath = path.join(resultsDir, csvFilename);
|
||||
}
|
||||
|
||||
/**
|
||||
* Save results incrementally as they're found
|
||||
*/
|
||||
const saveIncrementalResults = (currentResults, currentRejectedResults, currentSiteResults, currentAnalysisResults = null, isComplete = false) => {
|
||||
try {
|
||||
const outputData = {
|
||||
metadata: {
|
||||
extractedAt: new Date().toISOString(),
|
||||
parser: "job-search-parser",
|
||||
version: "2.0.0",
|
||||
sites: sites,
|
||||
keywords: keywords.join(", "),
|
||||
locationFilter,
|
||||
aiAnalysisEnabled: ENABLE_AI_ANALYSIS,
|
||||
aiContext: ENABLE_AI_ANALYSIS ? AI_CONTEXT : undefined,
|
||||
aiModel: ENABLE_AI_ANALYSIS ? OLLAMA_MODEL : undefined,
|
||||
analysisResults: currentAnalysisResults,
|
||||
rejectedJobsExcluded: excludeRejected,
|
||||
isComplete: isComplete,
|
||||
lastUpdated: new Date().toISOString(),
|
||||
},
|
||||
results: currentResults,
|
||||
siteResults: currentSiteResults,
|
||||
};
|
||||
|
||||
if (!excludeRejected) {
|
||||
outputData.rejectedResults = currentRejectedResults;
|
||||
}
|
||||
|
||||
// Save JSON incrementally
|
||||
if (incrementalJsonFilepath) {
|
||||
fs.writeFileSync(incrementalJsonFilepath, JSON.stringify(outputData, null, 2));
|
||||
}
|
||||
|
||||
// Save CSV incrementally (convert on each save)
|
||||
if (incrementalCsvFilepath) {
|
||||
const csvContent = convertResultsToCsv(outputData);
|
||||
fs.writeFileSync(incrementalCsvFilepath, csvContent);
|
||||
}
|
||||
|
||||
if (!isComplete) {
|
||||
logger.info(`💾 Incremental save: ${currentResults.length} results saved to ${incrementalJsonFilepath || incrementalCsvFilepath}`);
|
||||
}
|
||||
} catch (error) {
|
||||
logger.warning(`⚠️ Failed to save incremental results: ${error.message}`);
|
||||
}
|
||||
};
|
||||
|
||||
// Save initial empty state
|
||||
saveIncrementalResults([], [], {}, null, false);
|
||||
|
||||
// Set up signal handlers for graceful shutdown
|
||||
let isShuttingDown = false;
|
||||
const gracefulShutdown = async (signal) => {
|
||||
if (isShuttingDown) return;
|
||||
isShuttingDown = true;
|
||||
|
||||
logger.warning(`\n⚠️ Received ${signal}, saving current results before exit...`);
|
||||
saveIncrementalResults(allResults, allRejectedResults, siteResults, analysisResults, false);
|
||||
logger.info(`💾 Saved ${allResults.length} results before shutdown`);
|
||||
|
||||
await coreParser.cleanup();
|
||||
process.exit(0);
|
||||
};
|
||||
|
||||
process.on('SIGINT', () => gracefulShutdown('SIGINT'));
|
||||
process.on('SIGTERM', () => gracefulShutdown('SIGTERM'));
|
||||
|
||||
// Process each selected site
|
||||
for (const site of sites) {
|
||||
@ -256,49 +108,18 @@ async function startJobSearchParser(options = {}) {
|
||||
logger.step(`\n🌐 Parsing ${site}...`);
|
||||
const startTime = Date.now();
|
||||
|
||||
// Prepare strategy options
|
||||
const strategyOptions = {
|
||||
const parseResult = await strategy(coreParser, {
|
||||
keywords,
|
||||
keywordGroups, // Pass grouped keywords if available
|
||||
locationFilter,
|
||||
maxPages: finalOptions.maxPages,
|
||||
useAndLogic: finalOptions.useAndLogic || false,
|
||||
};
|
||||
|
||||
// Add credentials for LinkedIn
|
||||
if (site === "linkedin") {
|
||||
const LINKEDIN_USERNAME = process.env.LINKEDIN_USERNAME;
|
||||
const LINKEDIN_PASSWORD = process.env.LINKEDIN_PASSWORD;
|
||||
|
||||
if (!LINKEDIN_USERNAME || !LINKEDIN_PASSWORD) {
|
||||
logger.error(`❌ LinkedIn credentials not found. Please set LINKEDIN_USERNAME and LINKEDIN_PASSWORD in .env file`);
|
||||
siteResults[site] = {
|
||||
count: 0,
|
||||
rejected: 0,
|
||||
duration: "0s",
|
||||
error: "LinkedIn credentials not found",
|
||||
};
|
||||
continue;
|
||||
}
|
||||
|
||||
strategyOptions.credentials = {
|
||||
username: LINKEDIN_USERNAME,
|
||||
password: LINKEDIN_PASSWORD,
|
||||
};
|
||||
strategyOptions.location = process.env.LINKEDIN_JOB_LOCATION || "";
|
||||
strategyOptions.minDate = minDate; // Add date filter for LinkedIn
|
||||
}
|
||||
|
||||
const parseResult = await strategy(coreParser, strategyOptions);
|
||||
});
|
||||
|
||||
const { results, rejectedResults, summary } = parseResult;
|
||||
const duration = ((Date.now() - startTime) / 1000).toFixed(2);
|
||||
|
||||
// Collect results
|
||||
logger.info(`📦 Strategy returned: ${results.length} results, ${rejectedResults.length} rejected`);
|
||||
allResults.push(...results);
|
||||
allRejectedResults.push(...rejectedResults);
|
||||
logger.info(`📦 Total accumulated: ${allResults.length} results, ${allRejectedResults.length} rejected`);
|
||||
|
||||
siteResults[site] = {
|
||||
count: results.length,
|
||||
@ -310,9 +131,6 @@ async function startJobSearchParser(options = {}) {
|
||||
logger.success(
|
||||
`✅ ${site} completed in ${duration}s - Found ${results.length} jobs`
|
||||
);
|
||||
|
||||
// Save results incrementally after each site
|
||||
saveIncrementalResults(allResults, allRejectedResults, siteResults, analysisResults, false);
|
||||
} catch (error) {
|
||||
logger.error(`❌ ${site} parsing failed: ${error.message}`);
|
||||
siteResults[site] = {
|
||||
@ -321,126 +139,60 @@ async function startJobSearchParser(options = {}) {
|
||||
duration: "0s",
|
||||
error: error.message,
|
||||
};
|
||||
// Save even on error to preserve what we have
|
||||
saveIncrementalResults(allResults, allRejectedResults, siteResults, analysisResults, false);
|
||||
}
|
||||
}
|
||||
|
||||
// AI Analysis if enabled
|
||||
// Save results before AI analysis (in case AI analysis takes a long time)
|
||||
if (allResults.length > 0) {
|
||||
saveIncrementalResults(allResults, allRejectedResults, siteResults, null, false);
|
||||
}
|
||||
|
||||
let analysisResults = null;
|
||||
if (ENABLE_AI_ANALYSIS && allResults.length > 0) {
|
||||
logger.step("🧠 Running AI Analysis...");
|
||||
|
||||
const ollamaAvailable = await checkOllamaStatus(OLLAMA_MODEL);
|
||||
if (ollamaAvailable) {
|
||||
// Prepare data for analysis (analyzeBatch expects objects with 'text' field)
|
||||
const analysisData = allResults.map((job) => {
|
||||
// Build comprehensive text including all available job information
|
||||
const parts = [];
|
||||
if (job.title) parts.push(`Title: ${job.title}`);
|
||||
if (job.company) parts.push(`Company: ${job.company}`);
|
||||
if (job.description) parts.push(`Description: ${job.description}`);
|
||||
if (job.roleDuties) parts.push(`Role Duties: ${job.roleDuties}`);
|
||||
if (job.jobRequirements) parts.push(`Requirements: ${job.jobRequirements}`);
|
||||
|
||||
return {
|
||||
text: parts.join("\n\n"),
|
||||
location: job.location || "",
|
||||
keyword: job.keyword || "",
|
||||
timestamp: job.extractedAt || job.postedDate || "",
|
||||
roleDuties: job.roleDuties || "",
|
||||
jobRequirements: job.jobRequirements || "",
|
||||
};
|
||||
const ollamaStatus = await checkOllamaStatus();
|
||||
if (ollamaStatus.available) {
|
||||
analysisResults = await analyzeBatch(allResults, {
|
||||
context:
|
||||
"Job market analysis focusing on job postings, skills, and trends",
|
||||
});
|
||||
|
||||
// Process in smaller batches to avoid timeouts (5 jobs per batch)
|
||||
const BATCH_SIZE = parseInt(process.env.AI_BATCH_SIZE) || 5;
|
||||
analysisResults = [];
|
||||
|
||||
for (let i = 0; i < analysisData.length; i += BATCH_SIZE) {
|
||||
const batch = analysisData.slice(i, i + BATCH_SIZE);
|
||||
const batchNumber = Math.floor(i / BATCH_SIZE) + 1;
|
||||
const totalBatches = Math.ceil(analysisData.length / BATCH_SIZE);
|
||||
|
||||
logger.info(` Processing batch ${batchNumber}/${totalBatches} (${batch.length} jobs)...`);
|
||||
|
||||
try {
|
||||
const batchResults = await analyzeBatch(
|
||||
batch,
|
||||
AI_CONTEXT,
|
||||
OLLAMA_MODEL
|
||||
);
|
||||
analysisResults.push(...batchResults);
|
||||
logger.success(` ✅ Batch ${batchNumber} completed`);
|
||||
} catch (error) {
|
||||
logger.error(` ❌ Batch ${batchNumber} failed: ${error.message}`);
|
||||
// Add fallback results for this batch
|
||||
const fallbackResults = batch.map((_, idx) => ({
|
||||
postIndex: i + idx + 1,
|
||||
isRelevant: true,
|
||||
confidence: 0.3,
|
||||
reasoning: `Analysis failed: ${error.message}`,
|
||||
}));
|
||||
analysisResults.push(...fallbackResults);
|
||||
}
|
||||
}
|
||||
|
||||
// Embed AI analysis into each job result
|
||||
allResults.forEach((job, index) => {
|
||||
if (analysisResults && analysisResults[index]) {
|
||||
job.aiAnalysis = {
|
||||
isRelevant: analysisResults[index].isRelevant,
|
||||
confidence: analysisResults[index].confidence,
|
||||
reasoning: analysisResults[index].reasoning,
|
||||
context: AI_CONTEXT,
|
||||
model: OLLAMA_MODEL,
|
||||
analyzedAt: new Date().toISOString(),
|
||||
};
|
||||
}
|
||||
});
|
||||
|
||||
logger.success(
|
||||
`✅ AI Analysis completed for ${allResults.length} jobs`
|
||||
);
|
||||
|
||||
// Save results after AI analysis completes
|
||||
saveIncrementalResults(allResults, allRejectedResults, siteResults, analysisResults, false);
|
||||
} else {
|
||||
logger.warning("⚠️ Ollama not available, skipping AI analysis");
|
||||
}
|
||||
}
|
||||
|
||||
// Final save with complete flag
|
||||
logger.info(`💾 Preparing final save: ${allResults.length} results, ${allRejectedResults.length} rejected`);
|
||||
logger.info(`💾 EXCLUDE_REJECTED env: ${process.env.EXCLUDE_REJECTED}, excludeRejected variable: ${excludeRejected}`);
|
||||
|
||||
if (!excludeRejected) {
|
||||
logger.info(`✅ Including ${allRejectedResults.length} rejected results in output`);
|
||||
} else {
|
||||
logger.info(`⏭️ Excluding rejected results (EXCLUDE_REJECTED=true)`);
|
||||
}
|
||||
|
||||
logger.info(`💾 Final output: ${allResults.length} results, ${allRejectedResults.length} rejected`);
|
||||
// Save results
|
||||
const outputData = {
|
||||
metadata: {
|
||||
extractedAt: new Date().toISOString(),
|
||||
parser: "job-search-parser",
|
||||
version: "2.0.0",
|
||||
sites: sites,
|
||||
keywords: keywords.join(", "),
|
||||
locationFilter,
|
||||
analysisResults,
|
||||
},
|
||||
results: allResults,
|
||||
rejectedResults: allRejectedResults,
|
||||
siteResults,
|
||||
};
|
||||
|
||||
// Final save with isComplete flag
|
||||
saveIncrementalResults(allResults, allRejectedResults, siteResults, analysisResults, true);
|
||||
|
||||
const savedFiles = [];
|
||||
if (incrementalJsonFilepath) savedFiles.push(incrementalJsonFilepath);
|
||||
if (incrementalCsvFilepath) savedFiles.push(incrementalCsvFilepath);
|
||||
const resultsDir = path.join(__dirname, "results");
|
||||
if (!fs.existsSync(resultsDir)) {
|
||||
fs.mkdirSync(resultsDir, { recursive: true });
|
||||
}
|
||||
|
||||
const timestamp = new Date().toISOString().replace(/[:.]/g, "-");
|
||||
const filename = `job-search-results-${timestamp}.json`;
|
||||
const filepath = path.join(resultsDir, filename);
|
||||
|
||||
fs.writeFileSync(filepath, JSON.stringify(outputData, null, 2));
|
||||
|
||||
// Final summary
|
||||
logger.step("\n📊 Job Search Parser Summary");
|
||||
logger.success(`✅ Total jobs found: ${allResults.length}`);
|
||||
logger.info(`❌ Total rejected: ${allRejectedResults.length}`);
|
||||
logger.info(`📁 Results saved to:`);
|
||||
savedFiles.forEach(filepath => {
|
||||
logger.info(` ${filepath}`);
|
||||
});
|
||||
logger.info(`📁 Results saved to: ${filepath}`);
|
||||
|
||||
logger.info("\n📈 Results by site:");
|
||||
for (const [site, stats] of Object.entries(siteResults)) {
|
||||
@ -455,31 +207,6 @@ async function startJobSearchParser(options = {}) {
|
||||
|
||||
logger.success("\n✅ Job Search Parser completed successfully!");
|
||||
|
||||
// Construct output data for return
|
||||
const outputData = {
|
||||
metadata: {
|
||||
extractedAt: new Date().toISOString(),
|
||||
parser: "job-search-parser",
|
||||
version: "2.0.0",
|
||||
sites: sites,
|
||||
keywords: keywords.join(", "),
|
||||
locationFilter,
|
||||
aiAnalysisEnabled: ENABLE_AI_ANALYSIS,
|
||||
aiContext: ENABLE_AI_ANALYSIS ? AI_CONTEXT : undefined,
|
||||
aiModel: ENABLE_AI_ANALYSIS ? OLLAMA_MODEL : undefined,
|
||||
analysisResults: analysisResults,
|
||||
rejectedJobsExcluded: excludeRejected,
|
||||
isComplete: true,
|
||||
lastUpdated: new Date().toISOString(),
|
||||
},
|
||||
results: allResults,
|
||||
siteResults: siteResults,
|
||||
};
|
||||
|
||||
if (!excludeRejected) {
|
||||
outputData.rejectedResults = allRejectedResults;
|
||||
}
|
||||
|
||||
return outputData;
|
||||
} catch (error) {
|
||||
logger.error(`❌ Job Search Parser failed: ${error.message}`);
|
||||
|
||||
@ -1,345 +1,332 @@
|
||||
/**
|
||||
* SkipTheDrive Job Parser
|
||||
*
|
||||
* Parses remote job listings from SkipTheDrive.com
|
||||
* Supports keyword search, job type filters, and pagination
|
||||
*/
|
||||
|
||||
const { chromium } = require("playwright");
|
||||
const path = require("path");
|
||||
|
||||
// Import from ai-analyzer core package
|
||||
const {
|
||||
logger,
|
||||
cleanText,
|
||||
containsAnyKeyword,
|
||||
containsAllKeywords,
|
||||
parseLocationFilters,
|
||||
validateLocationAgainstFilters,
|
||||
extractLocationFromProfile,
|
||||
analyzeBatch,
|
||||
checkOllamaStatus,
|
||||
} = require("../../ai-analyzer");
|
||||
|
||||
/**
|
||||
* Build search URL for SkipTheDrive
|
||||
* @param {string} keyword - Search keyword
|
||||
* @param {string} orderBy - Sort order (date, relevance)
|
||||
* @param {Array<string>} jobTypes - Job types to filter (part time, full time, contract)
|
||||
* @returns {string} - Formatted search URL
|
||||
*/
|
||||
function buildSearchUrl(keyword, orderBy = "date", jobTypes = []) {
|
||||
let url = `https://www.skipthedrive.com/?s=${encodeURIComponent(keyword)}`;
|
||||
|
||||
if (orderBy) {
|
||||
url += `&orderby=${orderBy}`;
|
||||
}
|
||||
|
||||
// Add job type filters
|
||||
jobTypes.forEach((type) => {
|
||||
url += `&jobtype=${encodeURIComponent(type)}`;
|
||||
});
|
||||
|
||||
return url;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract job data from a single job listing element
|
||||
* @param {Element} article - Job listing DOM element
|
||||
* @returns {Object} - Extracted job data
|
||||
*/
|
||||
async function extractJobData(article) {
|
||||
try {
|
||||
// Extract job title and URL
|
||||
const titleElement = await article.$("h2.post-title a");
|
||||
const title = titleElement ? await titleElement.textContent() : "";
|
||||
const jobUrl = titleElement ? await titleElement.getAttribute("href") : "";
|
||||
|
||||
// Extract date
|
||||
const dateElement = await article.$("time.post-date");
|
||||
const datePosted = dateElement
|
||||
? await dateElement.getAttribute("datetime")
|
||||
: "";
|
||||
const dateText = dateElement ? await dateElement.textContent() : "";
|
||||
|
||||
// Extract company name
|
||||
const companyElement = await article.$(
|
||||
".custom_fields_company_name_display_search_results"
|
||||
);
|
||||
let company = companyElement ? await companyElement.textContent() : "";
|
||||
company = company.replace(/^\s*[^\s]+\s*/, "").trim(); // Remove icon
|
||||
|
||||
// Extract days ago
|
||||
const daysAgoElement = await article.$(
|
||||
".custom_fields_job_date_display_search_results"
|
||||
);
|
||||
let daysAgo = daysAgoElement ? await daysAgoElement.textContent() : "";
|
||||
daysAgo = daysAgo.replace(/^\s*[^\s]+\s*/, "").trim(); // Remove icon
|
||||
|
||||
// Extract job description excerpt
|
||||
const excerptElement = await article.$(".excerpt_part");
|
||||
const description = excerptElement
|
||||
? await excerptElement.textContent()
|
||||
: "";
|
||||
|
||||
// Check if featured/sponsored
|
||||
const featuredElement = await article.$(".custom_fields_sponsored_job");
|
||||
const isFeatured = !!featuredElement;
|
||||
|
||||
// Extract job ID from article ID
|
||||
const articleId = await article.getAttribute("id");
|
||||
const jobId = articleId ? articleId.replace("post-", "") : "";
|
||||
|
||||
return {
|
||||
jobId,
|
||||
title: cleanText(title),
|
||||
company: cleanText(company),
|
||||
jobUrl,
|
||||
datePosted,
|
||||
dateText: cleanText(dateText),
|
||||
daysAgo: cleanText(daysAgo),
|
||||
description: cleanText(description),
|
||||
isFeatured,
|
||||
source: "skipthedrive",
|
||||
timestamp: new Date().toISOString(),
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error(`Error extracting job data: ${error.message}`);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Parse SkipTheDrive job listings
|
||||
* @param {Object} options - Parser options
|
||||
* @returns {Promise<Array>} - Array of parsed job listings
|
||||
*/
|
||||
async function parseSkipTheDrive(options = {}) {
|
||||
const {
|
||||
keywords = process.env.SEARCH_KEYWORDS?.split(",").map((k) => k.trim()) || [
|
||||
"software engineer",
|
||||
"developer",
|
||||
],
|
||||
jobTypes = process.env.JOB_TYPES?.split(",").map((t) => t.trim()) || [],
|
||||
locationFilter = process.env.LOCATION_FILTER || "",
|
||||
maxPages = parseInt(process.env.MAX_PAGES) || 5,
|
||||
headless = process.env.HEADLESS !== "false",
|
||||
enableAI = process.env.ENABLE_AI_ANALYSIS === "true",
|
||||
aiContext = process.env.AI_CONTEXT || "remote job opportunities analysis",
|
||||
useAndLogic = false, // Use AND logic instead of OR logic for keywords
|
||||
} = options;
|
||||
|
||||
logger.step("Starting SkipTheDrive parser...");
|
||||
logger.info(`🔍 Keywords: ${keywords.join(", ")}`);
|
||||
logger.info(`🔗 Keyword Logic: ${useAndLogic ? "AND (all keywords must match)" : "OR (any keyword matches)"}`);
|
||||
logger.info(
|
||||
`📋 Job Types: ${jobTypes.length > 0 ? jobTypes.join(", ") : "All"}`
|
||||
);
|
||||
logger.info(`📍 Location Filter: ${locationFilter || "None"}`);
|
||||
logger.info(`📄 Max Pages: ${maxPages}`);
|
||||
|
||||
const browser = await chromium.launch({
|
||||
headless,
|
||||
args: [
|
||||
"--no-sandbox",
|
||||
"--disable-setuid-sandbox",
|
||||
"--disable-dev-shm-usage",
|
||||
],
|
||||
});
|
||||
|
||||
const context = await browser.newContext({
|
||||
userAgent:
|
||||
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
|
||||
});
|
||||
|
||||
const results = [];
|
||||
const rejectedResults = [];
|
||||
const seenJobs = new Set();
|
||||
|
||||
try {
|
||||
// For AND logic, combine all keywords into a single search query
|
||||
// For OR logic, search each keyword separately
|
||||
const searchKeywords = useAndLogic ? [keywords.join(" ")] : keywords;
|
||||
|
||||
// Search for each keyword (or combined keyword for AND logic)
|
||||
for (const keyword of searchKeywords) {
|
||||
logger.info(`\n🔍 Searching for: ${keyword}`);
|
||||
|
||||
const searchUrl = buildSearchUrl(keyword, "date", jobTypes);
|
||||
const page = await context.newPage();
|
||||
|
||||
try {
|
||||
logger.info(
|
||||
`Attempting navigation to: ${searchUrl} at ${new Date().toISOString()}`
|
||||
);
|
||||
await page.goto(searchUrl, {
|
||||
waitUntil: "domcontentloaded",
|
||||
timeout: 30000,
|
||||
});
|
||||
logger.info(
|
||||
`Navigation completed successfully at ${new Date().toISOString()}`
|
||||
);
|
||||
|
||||
// Wait for job listings to load
|
||||
logger.info("Waiting for selector #loops-wrapper");
|
||||
await page
|
||||
.waitForSelector("#loops-wrapper", { timeout: 5000 })
|
||||
.catch(() => {
|
||||
logger.warning(`No results found for keyword: ${keyword}`);
|
||||
});
|
||||
logger.info("Selector wait completed");
|
||||
|
||||
let currentPage = 1;
|
||||
let hasNextPage = true;
|
||||
|
||||
while (hasNextPage && currentPage <= maxPages) {
|
||||
logger.info(`📄 Processing page ${currentPage} for "${keyword}"`);
|
||||
|
||||
// Extract all job articles on current page
|
||||
const jobArticles = await page.$$("article[id^='post-']");
|
||||
logger.info(
|
||||
`Found ${jobArticles.length} job listings on page ${currentPage}`
|
||||
);
|
||||
|
||||
for (const article of jobArticles) {
|
||||
const jobData = await extractJobData(article);
|
||||
|
||||
if (!jobData || seenJobs.has(jobData.jobId)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
seenJobs.add(jobData.jobId);
|
||||
|
||||
// Add keyword that found this job
|
||||
jobData.searchKeyword = keyword;
|
||||
|
||||
// Validate job against keywords
|
||||
const fullText = `${jobData.title} ${jobData.description} ${jobData.company}`;
|
||||
const keywordMatch = useAndLogic
|
||||
? containsAllKeywords(fullText, keywords)
|
||||
: containsAnyKeyword(fullText, keywords);
|
||||
|
||||
if (!keywordMatch) {
|
||||
rejectedResults.push({
|
||||
...jobData,
|
||||
rejected: true,
|
||||
reason: useAndLogic
|
||||
? "Not all keywords found in job listing"
|
||||
: "Keywords not found in job listing",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
// Location validation (if enabled)
|
||||
if (locationFilter) {
|
||||
const locationFilters = parseLocationFilters(locationFilter);
|
||||
// For SkipTheDrive, most jobs are remote, but we can check the title/description
|
||||
const locationValid =
|
||||
fullText.toLowerCase().includes("remote") ||
|
||||
locationFilters.some((filter) =>
|
||||
fullText.toLowerCase().includes(filter.toLowerCase())
|
||||
);
|
||||
|
||||
if (!locationValid) {
|
||||
rejectedResults.push({
|
||||
...jobData,
|
||||
rejected: true,
|
||||
reason: "Location requirements not met",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
jobData.locationValid = locationValid;
|
||||
}
|
||||
|
||||
logger.success(`✅ Found: ${jobData.title} at ${jobData.company}`);
|
||||
results.push(jobData);
|
||||
}
|
||||
|
||||
// Check for next page
|
||||
const nextPageLink = await page.$("a.nextp");
|
||||
if (nextPageLink && currentPage < maxPages) {
|
||||
logger.info("📄 Moving to next page...");
|
||||
await nextPageLink.click();
|
||||
await page.waitForLoadState("domcontentloaded");
|
||||
await page.waitForTimeout(2000); // Wait for content to load
|
||||
currentPage++;
|
||||
} else {
|
||||
hasNextPage = false;
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Error processing keyword "${keyword}": ${error.message}`);
|
||||
} finally {
|
||||
await page.close();
|
||||
}
|
||||
}
|
||||
|
||||
logger.success(`\n✅ Parsing complete!`);
|
||||
logger.info(`📊 Total jobs found: ${results.length}`);
|
||||
logger.info(`❌ Rejected jobs: ${rejectedResults.length}`);
|
||||
|
||||
// Run AI analysis if enabled
|
||||
let aiAnalysis = null;
|
||||
if (enableAI && results.length > 0) {
|
||||
logger.step("Running AI analysis on job listings...");
|
||||
|
||||
const aiAvailable = await checkOllamaStatus();
|
||||
if (aiAvailable) {
|
||||
const analysisData = results.map((job) => ({
|
||||
text: `${job.title} at ${job.company}. ${job.description}`,
|
||||
metadata: {
|
||||
jobId: job.jobId,
|
||||
company: job.company,
|
||||
daysAgo: job.daysAgo,
|
||||
},
|
||||
}));
|
||||
|
||||
aiAnalysis = await analyzeBatch(analysisData, aiContext);
|
||||
|
||||
// Merge AI analysis with results
|
||||
results.forEach((job, index) => {
|
||||
if (aiAnalysis && aiAnalysis[index]) {
|
||||
job.aiAnalysis = {
|
||||
isRelevant: aiAnalysis[index].isRelevant,
|
||||
confidence: aiAnalysis[index].confidence,
|
||||
reasoning: aiAnalysis[index].reasoning,
|
||||
};
|
||||
}
|
||||
});
|
||||
|
||||
logger.success("✅ AI analysis completed");
|
||||
} else {
|
||||
logger.warning("⚠️ AI not available - skipping analysis");
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
results,
|
||||
rejectedResults,
|
||||
metadata: {
|
||||
source: "skipthedrive",
|
||||
totalJobs: results.length,
|
||||
rejectedJobs: rejectedResults.length,
|
||||
keywords: keywords,
|
||||
jobTypes: jobTypes,
|
||||
locationFilter: locationFilter,
|
||||
aiAnalysisEnabled: enableAI,
|
||||
aiAnalysisCompleted: !!aiAnalysis,
|
||||
timestamp: new Date().toISOString(),
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error(`Fatal error in SkipTheDrive parser: ${error.message}`);
|
||||
throw error;
|
||||
} finally {
|
||||
await browser.close();
|
||||
}
|
||||
}
|
||||
|
||||
// Export the parser
|
||||
module.exports = {
|
||||
parseSkipTheDrive,
|
||||
buildSearchUrl,
|
||||
extractJobData,
|
||||
};
|
||||
/**
|
||||
* SkipTheDrive Job Parser
|
||||
*
|
||||
* Parses remote job listings from SkipTheDrive.com
|
||||
* Supports keyword search, job type filters, and pagination
|
||||
*/
|
||||
|
||||
const { chromium } = require("playwright");
|
||||
const path = require("path");
|
||||
|
||||
// Import from ai-analyzer core package
|
||||
const {
|
||||
logger,
|
||||
cleanText,
|
||||
containsAnyKeyword,
|
||||
parseLocationFilters,
|
||||
validateLocationAgainstFilters,
|
||||
extractLocationFromProfile,
|
||||
analyzeBatch,
|
||||
checkOllamaStatus,
|
||||
} = require("../../ai-analyzer");
|
||||
|
||||
/**
|
||||
* Build search URL for SkipTheDrive
|
||||
* @param {string} keyword - Search keyword
|
||||
* @param {string} orderBy - Sort order (date, relevance)
|
||||
* @param {Array<string>} jobTypes - Job types to filter (part time, full time, contract)
|
||||
* @returns {string} - Formatted search URL
|
||||
*/
|
||||
function buildSearchUrl(keyword, orderBy = "date", jobTypes = []) {
|
||||
let url = `https://www.skipthedrive.com/?s=${encodeURIComponent(keyword)}`;
|
||||
|
||||
if (orderBy) {
|
||||
url += `&orderby=${orderBy}`;
|
||||
}
|
||||
|
||||
// Add job type filters
|
||||
jobTypes.forEach((type) => {
|
||||
url += `&jobtype=${encodeURIComponent(type)}`;
|
||||
});
|
||||
|
||||
return url;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract job data from a single job listing element
|
||||
* @param {Element} article - Job listing DOM element
|
||||
* @returns {Object} - Extracted job data
|
||||
*/
|
||||
async function extractJobData(article) {
|
||||
try {
|
||||
// Extract job title and URL
|
||||
const titleElement = await article.$("h2.post-title a");
|
||||
const title = titleElement ? await titleElement.textContent() : "";
|
||||
const jobUrl = titleElement ? await titleElement.getAttribute("href") : "";
|
||||
|
||||
// Extract date
|
||||
const dateElement = await article.$("time.post-date");
|
||||
const datePosted = dateElement
|
||||
? await dateElement.getAttribute("datetime")
|
||||
: "";
|
||||
const dateText = dateElement ? await dateElement.textContent() : "";
|
||||
|
||||
// Extract company name
|
||||
const companyElement = await article.$(
|
||||
".custom_fields_company_name_display_search_results"
|
||||
);
|
||||
let company = companyElement ? await companyElement.textContent() : "";
|
||||
company = company.replace(/^\s*[^\s]+\s*/, "").trim(); // Remove icon
|
||||
|
||||
// Extract days ago
|
||||
const daysAgoElement = await article.$(
|
||||
".custom_fields_job_date_display_search_results"
|
||||
);
|
||||
let daysAgo = daysAgoElement ? await daysAgoElement.textContent() : "";
|
||||
daysAgo = daysAgo.replace(/^\s*[^\s]+\s*/, "").trim(); // Remove icon
|
||||
|
||||
// Extract job description excerpt
|
||||
const excerptElement = await article.$(".excerpt_part");
|
||||
const description = excerptElement
|
||||
? await excerptElement.textContent()
|
||||
: "";
|
||||
|
||||
// Check if featured/sponsored
|
||||
const featuredElement = await article.$(".custom_fields_sponsored_job");
|
||||
const isFeatured = !!featuredElement;
|
||||
|
||||
// Extract job ID from article ID
|
||||
const articleId = await article.getAttribute("id");
|
||||
const jobId = articleId ? articleId.replace("post-", "") : "";
|
||||
|
||||
return {
|
||||
jobId,
|
||||
title: cleanText(title),
|
||||
company: cleanText(company),
|
||||
jobUrl,
|
||||
datePosted,
|
||||
dateText: cleanText(dateText),
|
||||
daysAgo: cleanText(daysAgo),
|
||||
description: cleanText(description),
|
||||
isFeatured,
|
||||
source: "skipthedrive",
|
||||
timestamp: new Date().toISOString(),
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error(`Error extracting job data: ${error.message}`);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Parse SkipTheDrive job listings
|
||||
* @param {Object} options - Parser options
|
||||
* @returns {Promise<Array>} - Array of parsed job listings
|
||||
*/
|
||||
async function parseSkipTheDrive(options = {}) {
|
||||
const {
|
||||
keywords = process.env.SEARCH_KEYWORDS?.split(",").map((k) => k.trim()) || [
|
||||
"software engineer",
|
||||
"developer",
|
||||
],
|
||||
jobTypes = process.env.JOB_TYPES?.split(",").map((t) => t.trim()) || [],
|
||||
locationFilter = process.env.LOCATION_FILTER || "",
|
||||
maxPages = parseInt(process.env.MAX_PAGES) || 5,
|
||||
headless = process.env.HEADLESS !== "false",
|
||||
enableAI = process.env.ENABLE_AI_ANALYSIS === "true",
|
||||
aiContext = process.env.AI_CONTEXT || "remote job opportunities analysis",
|
||||
} = options;
|
||||
|
||||
logger.step("Starting SkipTheDrive parser...");
|
||||
logger.info(`🔍 Keywords: ${keywords.join(", ")}`);
|
||||
logger.info(
|
||||
`📋 Job Types: ${jobTypes.length > 0 ? jobTypes.join(", ") : "All"}`
|
||||
);
|
||||
logger.info(`📍 Location Filter: ${locationFilter || "None"}`);
|
||||
logger.info(`📄 Max Pages: ${maxPages}`);
|
||||
|
||||
const browser = await chromium.launch({
|
||||
headless,
|
||||
args: [
|
||||
"--no-sandbox",
|
||||
"--disable-setuid-sandbox",
|
||||
"--disable-dev-shm-usage",
|
||||
],
|
||||
});
|
||||
|
||||
const context = await browser.newContext({
|
||||
userAgent:
|
||||
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
|
||||
});
|
||||
|
||||
const results = [];
|
||||
const rejectedResults = [];
|
||||
const seenJobs = new Set();
|
||||
|
||||
try {
|
||||
// Search for each keyword
|
||||
for (const keyword of keywords) {
|
||||
logger.info(`\n🔍 Searching for: ${keyword}`);
|
||||
|
||||
const searchUrl = buildSearchUrl(keyword, "date", jobTypes);
|
||||
const page = await context.newPage();
|
||||
|
||||
try {
|
||||
logger.info(
|
||||
`Attempting navigation to: ${searchUrl} at ${new Date().toISOString()}`
|
||||
);
|
||||
await page.goto(searchUrl, {
|
||||
waitUntil: "domcontentloaded",
|
||||
timeout: 30000,
|
||||
});
|
||||
logger.info(
|
||||
`Navigation completed successfully at ${new Date().toISOString()}`
|
||||
);
|
||||
|
||||
// Wait for job listings to load
|
||||
logger.info("Waiting for selector #loops-wrapper");
|
||||
await page
|
||||
.waitForSelector("#loops-wrapper", { timeout: 5000 })
|
||||
.catch(() => {
|
||||
logger.warning(`No results found for keyword: ${keyword}`);
|
||||
});
|
||||
logger.info("Selector wait completed");
|
||||
|
||||
let currentPage = 1;
|
||||
let hasNextPage = true;
|
||||
|
||||
while (hasNextPage && currentPage <= maxPages) {
|
||||
logger.info(`📄 Processing page ${currentPage} for "${keyword}"`);
|
||||
|
||||
// Extract all job articles on current page
|
||||
const jobArticles = await page.$$("article[id^='post-']");
|
||||
logger.info(
|
||||
`Found ${jobArticles.length} job listings on page ${currentPage}`
|
||||
);
|
||||
|
||||
for (const article of jobArticles) {
|
||||
const jobData = await extractJobData(article);
|
||||
|
||||
if (!jobData || seenJobs.has(jobData.jobId)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
seenJobs.add(jobData.jobId);
|
||||
|
||||
// Add keyword that found this job
|
||||
jobData.searchKeyword = keyword;
|
||||
|
||||
// Validate job against keywords
|
||||
const fullText = `${jobData.title} ${jobData.description} ${jobData.company}`;
|
||||
if (!containsAnyKeyword(fullText, keywords)) {
|
||||
rejectedResults.push({
|
||||
...jobData,
|
||||
rejected: true,
|
||||
reason: "Keywords not found in job listing",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
// Location validation (if enabled)
|
||||
if (locationFilter) {
|
||||
const locationFilters = parseLocationFilters(locationFilter);
|
||||
// For SkipTheDrive, most jobs are remote, but we can check the title/description
|
||||
const locationValid =
|
||||
fullText.toLowerCase().includes("remote") ||
|
||||
locationFilters.some((filter) =>
|
||||
fullText.toLowerCase().includes(filter.toLowerCase())
|
||||
);
|
||||
|
||||
if (!locationValid) {
|
||||
rejectedResults.push({
|
||||
...jobData,
|
||||
rejected: true,
|
||||
reason: "Location requirements not met",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
jobData.locationValid = locationValid;
|
||||
}
|
||||
|
||||
logger.success(`✅ Found: ${jobData.title} at ${jobData.company}`);
|
||||
results.push(jobData);
|
||||
}
|
||||
|
||||
// Check for next page
|
||||
const nextPageLink = await page.$("a.nextp");
|
||||
if (nextPageLink && currentPage < maxPages) {
|
||||
logger.info("📄 Moving to next page...");
|
||||
await nextPageLink.click();
|
||||
await page.waitForLoadState("domcontentloaded");
|
||||
await page.waitForTimeout(2000); // Wait for content to load
|
||||
currentPage++;
|
||||
} else {
|
||||
hasNextPage = false;
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Error processing keyword "${keyword}": ${error.message}`);
|
||||
} finally {
|
||||
await page.close();
|
||||
}
|
||||
}
|
||||
|
||||
logger.success(`\n✅ Parsing complete!`);
|
||||
logger.info(`📊 Total jobs found: ${results.length}`);
|
||||
logger.info(`❌ Rejected jobs: ${rejectedResults.length}`);
|
||||
|
||||
// Run AI analysis if enabled
|
||||
let aiAnalysis = null;
|
||||
if (enableAI && results.length > 0) {
|
||||
logger.step("Running AI analysis on job listings...");
|
||||
|
||||
const aiAvailable = await checkOllamaStatus();
|
||||
if (aiAvailable) {
|
||||
const analysisData = results.map((job) => ({
|
||||
text: `${job.title} at ${job.company}. ${job.description}`,
|
||||
metadata: {
|
||||
jobId: job.jobId,
|
||||
company: job.company,
|
||||
daysAgo: job.daysAgo,
|
||||
},
|
||||
}));
|
||||
|
||||
aiAnalysis = await analyzeBatch(analysisData, aiContext);
|
||||
|
||||
// Merge AI analysis with results
|
||||
results.forEach((job, index) => {
|
||||
if (aiAnalysis && aiAnalysis[index]) {
|
||||
job.aiAnalysis = {
|
||||
isRelevant: aiAnalysis[index].isRelevant,
|
||||
confidence: aiAnalysis[index].confidence,
|
||||
reasoning: aiAnalysis[index].reasoning,
|
||||
};
|
||||
}
|
||||
});
|
||||
|
||||
logger.success("✅ AI analysis completed");
|
||||
} else {
|
||||
logger.warning("⚠️ AI not available - skipping analysis");
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
results,
|
||||
rejectedResults,
|
||||
metadata: {
|
||||
source: "skipthedrive",
|
||||
totalJobs: results.length,
|
||||
rejectedJobs: rejectedResults.length,
|
||||
keywords: keywords,
|
||||
jobTypes: jobTypes,
|
||||
locationFilter: locationFilter,
|
||||
aiAnalysisEnabled: enableAI,
|
||||
aiAnalysisCompleted: !!aiAnalysis,
|
||||
timestamp: new Date().toISOString(),
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error(`Fatal error in SkipTheDrive parser: ${error.message}`);
|
||||
throw error;
|
||||
} finally {
|
||||
await browser.close();
|
||||
}
|
||||
}
|
||||
|
||||
// Export the parser
|
||||
module.exports = {
|
||||
parseSkipTheDrive,
|
||||
buildSearchUrl,
|
||||
extractJobData,
|
||||
};
|
||||
|
||||
@ -1,116 +0,0 @@
|
||||
/**
|
||||
* CSV Utilities
|
||||
*
|
||||
* Functions for converting job search results to CSV format
|
||||
*/
|
||||
|
||||
/**
|
||||
* Escapes a CSV field value
|
||||
* @param {string} value - The value to escape
|
||||
* @returns {string} - The escaped value
|
||||
*/
|
||||
function escapeCsvField(value) {
|
||||
if (value === null || value === undefined) {
|
||||
return "";
|
||||
}
|
||||
|
||||
const stringValue = String(value);
|
||||
|
||||
// If the value contains comma, newline, or double quote, wrap it in quotes and escape quotes
|
||||
if (stringValue.includes(",") || stringValue.includes("\n") || stringValue.includes('"')) {
|
||||
return `"${stringValue.replace(/"/g, '""')}"`;
|
||||
}
|
||||
|
||||
return stringValue;
|
||||
}
|
||||
|
||||
/**
|
||||
* Converts job results to CSV format
|
||||
* @param {Array} jobs - Array of job objects
|
||||
* @param {Object} metadata - Metadata object (optional)
|
||||
* @returns {string} - CSV string
|
||||
*/
|
||||
function convertJobsToCsv(jobs, metadata = null) {
|
||||
if (!jobs || jobs.length === 0) {
|
||||
return "";
|
||||
}
|
||||
|
||||
// Define CSV columns based on job object structure
|
||||
const columns = [
|
||||
"jobId",
|
||||
"title",
|
||||
"company",
|
||||
"location",
|
||||
"jobUrl",
|
||||
"postedDate",
|
||||
"description",
|
||||
"roleDuties",
|
||||
"jobRequirements",
|
||||
"jobType",
|
||||
"experienceLevel",
|
||||
"keyword",
|
||||
"extractedAt",
|
||||
"source",
|
||||
"aiRelevant",
|
||||
"aiConfidence",
|
||||
"aiReasoning",
|
||||
"aiContext",
|
||||
"aiModel",
|
||||
"aiAnalyzedAt"
|
||||
];
|
||||
|
||||
// Create header row
|
||||
const headerRow = columns.map(col => escapeCsvField(col)).join(",");
|
||||
|
||||
// Create data rows
|
||||
const dataRows = jobs.map(job => {
|
||||
const row = columns.map(col => {
|
||||
if (col.startsWith("ai")) {
|
||||
// Handle AI analysis fields
|
||||
const aiField = col.substring(2).charAt(0).toLowerCase() + col.substring(3);
|
||||
if (job.aiAnalysis) {
|
||||
if (aiField === "relevant") {
|
||||
return escapeCsvField(job.aiAnalysis.isRelevant ? "Yes" : "No");
|
||||
} else if (aiField === "confidence") {
|
||||
return escapeCsvField(job.aiAnalysis.confidence || "");
|
||||
} else if (aiField === "reasoning") {
|
||||
return escapeCsvField(job.aiAnalysis.reasoning || "");
|
||||
} else if (aiField === "context") {
|
||||
return escapeCsvField(job.aiAnalysis.context || "");
|
||||
} else if (aiField === "model") {
|
||||
return escapeCsvField(job.aiAnalysis.model || "");
|
||||
} else if (aiField === "analyzedAt") {
|
||||
return escapeCsvField(job.aiAnalysis.analyzedAt || "");
|
||||
}
|
||||
}
|
||||
return "";
|
||||
} else {
|
||||
return escapeCsvField(job[col] || "");
|
||||
}
|
||||
});
|
||||
return row.join(",");
|
||||
});
|
||||
|
||||
// Combine header and data rows
|
||||
return [headerRow, ...dataRows].join("\n");
|
||||
}
|
||||
|
||||
/**
|
||||
* Converts full results object (with metadata) to CSV
|
||||
* @param {Object} resultsData - Full results object with metadata, results, etc.
|
||||
* @returns {string} - CSV string
|
||||
*/
|
||||
function convertResultsToCsv(resultsData) {
|
||||
if (!resultsData || !resultsData.results) {
|
||||
return "";
|
||||
}
|
||||
|
||||
return convertJobsToCsv(resultsData.results, resultsData.metadata);
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
convertJobsToCsv,
|
||||
convertResultsToCsv,
|
||||
escapeCsvField,
|
||||
};
|
||||
|
||||
@ -1,947 +0,0 @@
|
||||
/**
|
||||
* Indeed Parsing Strategy
|
||||
*
|
||||
* Uses core-parser for browser management and ai-analyzer for utilities
|
||||
*/
|
||||
|
||||
const {
|
||||
logger,
|
||||
cleanText,
|
||||
containsAnyKeyword,
|
||||
containsAllKeywords,
|
||||
matchesKeywordGroups,
|
||||
validateLocationAgainstFilters,
|
||||
} = require("ai-analyzer");
|
||||
|
||||
/**
|
||||
* Indeed URL builder
|
||||
*/
|
||||
function buildSearchUrl(keyword, location = "", filters = {}) {
|
||||
const baseUrl = "https://www.indeed.com/jobs";
|
||||
const params = new URLSearchParams({
|
||||
q: keyword,
|
||||
sort: "date", // Sort by date (newest first)
|
||||
});
|
||||
|
||||
if (location) {
|
||||
params.append("l", location);
|
||||
}
|
||||
|
||||
// Add date filter if provided
|
||||
if (filters.fromage) {
|
||||
// fromage is in days (e.g., 1 = last 24 hours, 7 = last 7 days, 30 = last 30 days)
|
||||
params.append("fromage", filters.fromage);
|
||||
}
|
||||
|
||||
// Add job type filter
|
||||
if (filters.jobType) {
|
||||
// jt=fulltime, parttime, contract, internship, temporary
|
||||
params.append("jt", filters.jobType);
|
||||
}
|
||||
|
||||
// Add remote filter
|
||||
if (filters.remote) {
|
||||
params.append("remote", "true");
|
||||
}
|
||||
|
||||
// Add experience level filter
|
||||
if (filters.experienceLevel) {
|
||||
// explvl=entry_level, mid_level, senior_level
|
||||
params.append("explvl", filters.experienceLevel);
|
||||
}
|
||||
|
||||
return `${baseUrl}?${params.toString()}`;
|
||||
}
|
||||
|
||||
/**
|
||||
* Indeed parsing strategy function
|
||||
*/
|
||||
async function indeedStrategy(coreParser, options = {}) {
|
||||
const {
|
||||
keywords = ["software engineer", "developer"],
|
||||
keywordGroups = null, // Array of keyword groups for grouped AND/OR logic
|
||||
locationFilter = null,
|
||||
maxPages = 5,
|
||||
location = "", // Indeed location search (e.g., "Toronto, ON", "Canada")
|
||||
minDate = null, // Minimum posted date (format: YYYY-MM-DD)
|
||||
useAndLogic = false, // Use AND logic instead of OR logic for keywords
|
||||
} = options;
|
||||
|
||||
const results = [];
|
||||
const rejectedResults = [];
|
||||
const seenJobs = new Set();
|
||||
|
||||
try {
|
||||
// Create main page
|
||||
const page = await coreParser.createPage("indeed-main");
|
||||
|
||||
logger.info("🚀 Starting Indeed parser...");
|
||||
logger.info(`🔍 Keywords: ${keywords.join(", ")}`);
|
||||
if (keywordGroups) {
|
||||
logger.info(`🔗 Keyword Logic: Grouped AND/OR - ${keywordGroups.map(g => `(${g.join(' OR ')})`).join(' AND ')}`);
|
||||
} else {
|
||||
logger.info(`🔗 Keyword Logic: ${useAndLogic ? "AND (all keywords must match)" : "OR (any keyword matches)"}`);
|
||||
}
|
||||
logger.info(`📍 Location Filter: ${locationFilter || "None"}`);
|
||||
logger.info(`🌍 Indeed Location: ${location || "None"}`);
|
||||
logger.info(`📄 Max Pages: ${maxPages}`);
|
||||
|
||||
// Convert minDate to fromage (days ago)
|
||||
let fromage = null;
|
||||
if (minDate) {
|
||||
try {
|
||||
const minDateObj = new Date(minDate);
|
||||
const now = new Date();
|
||||
const daysDiff = Math.floor((now - minDateObj) / (1000 * 60 * 60 * 24));
|
||||
if (daysDiff > 0 && daysDiff <= 30) {
|
||||
fromage = daysDiff;
|
||||
logger.info(`📅 Min Date Filter: ${minDate} (${fromage} days ago)`);
|
||||
} else if (daysDiff > 30) {
|
||||
fromage = 30; // Indeed's maximum is typically 30 days
|
||||
logger.info(`📅 Min Date Filter: ${minDate} (limited to 30 days)`);
|
||||
}
|
||||
} catch (error) {
|
||||
logger.warning(`⚠️ Invalid date format for minDate: ${minDate}. Expected format: YYYY-MM-DD`);
|
||||
}
|
||||
}
|
||||
|
||||
// Determine search keywords based on logic type
|
||||
let searchKeywords;
|
||||
if (keywordGroups) {
|
||||
// For grouped AND/OR logic, search each keyword in each group (OR within groups)
|
||||
searchKeywords = keywordGroups.flat(); // Flatten all keywords from all groups
|
||||
} else if (useAndLogic) {
|
||||
// For simple AND logic, combine all keywords into a single search query
|
||||
searchKeywords = [keywords.join(" ")];
|
||||
} else {
|
||||
// For OR logic, search each keyword separately
|
||||
searchKeywords = keywords;
|
||||
}
|
||||
|
||||
// Search for each keyword (or combined keyword for AND logic)
|
||||
for (const keyword of searchKeywords) {
|
||||
logger.info(`\n🔍 Searching Indeed for: "${keyword}"`);
|
||||
|
||||
const searchUrl = buildSearchUrl(keyword, location, {
|
||||
fromage: fromage,
|
||||
});
|
||||
logger.info(`🔗 Search URL: ${searchUrl}`);
|
||||
|
||||
try {
|
||||
// Navigate to job search results
|
||||
// Use domcontentloaded instead of networkidle for faster loading
|
||||
// Indeed can be slow to fully load, so we'll wait for DOM and then check for content
|
||||
try {
|
||||
await coreParser.navigateTo(searchUrl, {
|
||||
pageId: "indeed-main",
|
||||
retries: 2,
|
||||
waitUntil: "domcontentloaded",
|
||||
timeout: 60000, // Increase timeout to 60 seconds
|
||||
});
|
||||
} catch (navError) {
|
||||
// If navigation fails, try with load event instead
|
||||
logger.warning(`⚠️ Initial navigation failed, trying with 'load' event: ${navError.message}`);
|
||||
try {
|
||||
await coreParser.navigateTo(searchUrl, {
|
||||
pageId: "indeed-main",
|
||||
retries: 1,
|
||||
waitUntil: "load",
|
||||
timeout: 60000,
|
||||
});
|
||||
} catch (loadError) {
|
||||
// Last resort: try direct page navigation
|
||||
logger.warning(`⚠️ Load event failed, trying direct navigation: ${loadError.message}`);
|
||||
await page.goto(searchUrl, { timeout: 60000, waitUntil: "domcontentloaded" }).catch(() => {
|
||||
throw new Error(`Failed to navigate to Indeed after all attempts: ${loadError.message}`);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Wait for page to load and let JavaScript execute
|
||||
await new Promise((resolve) => setTimeout(resolve, 5000));
|
||||
|
||||
// Check if we're on the right page
|
||||
const currentUrl = page.url();
|
||||
logger.info(`📍 Current page URL: ${currentUrl}`);
|
||||
|
||||
// Check if we were redirected or blocked (check URL first)
|
||||
if (currentUrl.includes('captcha') || currentUrl.includes('blocked') || currentUrl.includes('access-denied') || currentUrl.includes('verify')) {
|
||||
logger.error(`❌ Indeed appears to be blocking access. URL: ${currentUrl}`);
|
||||
throw new Error('Indeed is showing a CAPTCHA or verification page. Please try running in non-headless mode (set HEADLESS=false in .env) or wait and try again later.');
|
||||
}
|
||||
|
||||
// Check page content for CAPTCHA/human verification indicators
|
||||
try {
|
||||
const pageContent = await page.evaluate(() => {
|
||||
const bodyText = document.body?.textContent?.toLowerCase() || '';
|
||||
const title = document.title?.toLowerCase() || '';
|
||||
|
||||
// Check for common CAPTCHA/verification indicators
|
||||
const captchaIndicators = [
|
||||
'verify you\'re human',
|
||||
'verify you are human',
|
||||
'captcha',
|
||||
'prove you\'re not a robot',
|
||||
'unusual traffic',
|
||||
'automated queries',
|
||||
'please verify',
|
||||
'security check',
|
||||
'access denied',
|
||||
'blocked',
|
||||
];
|
||||
|
||||
const foundIndicators = captchaIndicators.filter(indicator =>
|
||||
bodyText.includes(indicator) || title.includes(indicator)
|
||||
);
|
||||
|
||||
return {
|
||||
hasCaptcha: foundIndicators.length > 0,
|
||||
indicators: foundIndicators,
|
||||
title: document.title,
|
||||
bodyPreview: bodyText.substring(0, 500),
|
||||
};
|
||||
});
|
||||
|
||||
if (pageContent.hasCaptcha) {
|
||||
logger.error(`❌ Indeed is showing a CAPTCHA/verification page.`);
|
||||
logger.error(` Detected indicators: ${pageContent.indicators.join(', ')}`);
|
||||
logger.error(` Page title: ${pageContent.title}`);
|
||||
logger.error(`\n💡 Solutions:`);
|
||||
logger.error(` 1. Run in non-headless mode: Set HEADLESS=false in .env file`);
|
||||
logger.error(` 2. Wait a few minutes and try again`);
|
||||
logger.error(` 3. Use a different IP address or VPN`);
|
||||
logger.error(` 4. Manually solve the CAPTCHA in a browser, then try again`);
|
||||
throw new Error(`Indeed CAPTCHA detected: ${pageContent.indicators.join(', ')}. Please see suggestions above.`);
|
||||
}
|
||||
} catch (checkError) {
|
||||
// If the check itself fails, log but don't throw (might be a different error)
|
||||
if (checkError.message.includes('CAPTCHA')) {
|
||||
throw checkError; // Re-throw CAPTCHA errors
|
||||
}
|
||||
logger.debug(`Could not check for CAPTCHA: ${checkError.message}`);
|
||||
}
|
||||
|
||||
// Check for results count
|
||||
try {
|
||||
const resultsText = await page.evaluate(() => {
|
||||
const countElement = document.querySelector(".jobsearch-JobCountAndSortPane-jobCount");
|
||||
return countElement ? countElement.textContent : "No results count found";
|
||||
});
|
||||
logger.info(`📊 Indeed results info: ${resultsText}`);
|
||||
} catch (e) {
|
||||
logger.debug(`Could not get results count: ${e.message}`);
|
||||
}
|
||||
|
||||
// Wait for job listings container
|
||||
let hasResults = false;
|
||||
const possibleSelectors = [
|
||||
"#mosaic-provider-jobcards",
|
||||
".job_seen_beacon",
|
||||
"[data-jk]",
|
||||
".jobsearch-SerpJobCard",
|
||||
".jobCard",
|
||||
];
|
||||
|
||||
for (const selector of possibleSelectors) {
|
||||
try {
|
||||
await page.waitForSelector(selector, { timeout: 5000 });
|
||||
const count = await page.$$(selector).then((elements) => elements.length);
|
||||
if (count > 0) {
|
||||
hasResults = true;
|
||||
logger.info(`✅ Found job results container with selector: ${selector} (${count} jobs)`);
|
||||
break;
|
||||
}
|
||||
} catch (e) {
|
||||
// Try next selector
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
if (!hasResults) {
|
||||
logger.warning(`⚠️ No job results container found for keyword: ${keyword}`);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Process multiple pages
|
||||
let currentPage = 1;
|
||||
const maxPagesToProcess = maxPages > 0 ? maxPages : 999; // 0 means unlimited
|
||||
|
||||
logger.info(`📄 Processing pages (max: ${maxPagesToProcess === 999 ? 'unlimited' : maxPagesToProcess}) for "${keyword}"...`);
|
||||
|
||||
while (currentPage <= maxPagesToProcess) {
|
||||
logger.info(`📄 Processing page ${currentPage}...`);
|
||||
|
||||
// Wait for page to fully load
|
||||
await new Promise((resolve) => setTimeout(resolve, 2000));
|
||||
|
||||
// Extract jobs from current page
|
||||
const pageJobs = await extractJobsFromPage(page, keyword, locationFilter);
|
||||
logger.info(`📋 Extracted ${pageJobs.length} jobs from page ${currentPage}`);
|
||||
|
||||
if (pageJobs.length === 0) {
|
||||
logger.warning(`⚠️ No jobs found on page ${currentPage}, stopping pagination`);
|
||||
break;
|
||||
}
|
||||
|
||||
// Process each job
|
||||
for (const job of pageJobs) {
|
||||
// Skip duplicates
|
||||
if (seenJobs.has(job.jobId)) {
|
||||
continue;
|
||||
}
|
||||
seenJobs.add(job.jobId);
|
||||
|
||||
// Validate keywords based on logic type
|
||||
if (keywordGroups) {
|
||||
// Grouped AND/OR logic: all groups must match (AND), at least one keyword per group (OR)
|
||||
const fullText = `${job.title} ${job.description} ${job.company}`;
|
||||
if (!matchesKeywordGroups(fullText, keywordGroups)) {
|
||||
rejectedResults.push({
|
||||
...job,
|
||||
rejectionReason: "Job does not match all keyword groups",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
} else if (useAndLogic) {
|
||||
// Simple AND logic: all keywords must match
|
||||
const fullText = `${job.title} ${job.description} ${job.company}`.toLowerCase();
|
||||
if (!containsAllKeywords(fullText, keywords)) {
|
||||
rejectedResults.push({
|
||||
...job,
|
||||
rejectionReason: "Not all keywords found in job listing",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
// Validate location if filtering enabled
|
||||
if (locationFilter) {
|
||||
const locationValid = validateLocationAgainstFilters(
|
||||
job.location,
|
||||
locationFilter
|
||||
);
|
||||
|
||||
if (!locationValid.isValid) {
|
||||
rejectedResults.push({
|
||||
...job,
|
||||
rejectionReason: locationValid.reasoning || "Location filter mismatch",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
results.push(job);
|
||||
}
|
||||
|
||||
// Check if there's a next page
|
||||
const hasNext = await hasNextPageAvailable(page);
|
||||
if (!hasNext) {
|
||||
logger.info(`✅ No more pages available. Total jobs extracted: ${results.length}`);
|
||||
break;
|
||||
}
|
||||
|
||||
// Navigate to next page if we haven't reached maxPages
|
||||
if (currentPage < maxPagesToProcess) {
|
||||
logger.info(`➡️ Navigating to page ${currentPage + 1}...`);
|
||||
const navigationSuccess = await navigateToNextPage(page);
|
||||
|
||||
if (!navigationSuccess) {
|
||||
logger.warning(`⚠️ Failed to navigate to next page, stopping pagination`);
|
||||
break;
|
||||
}
|
||||
|
||||
currentPage++;
|
||||
} else {
|
||||
logger.info(`📊 Reached max pages limit (${maxPagesToProcess}). Total jobs extracted: ${results.length}`);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
const totalExtracted = results.length + rejectedResults.length;
|
||||
logger.info(`📋 Extracted ${results.length} accepted jobs, ${rejectedResults.length} rejected jobs (${totalExtracted} total) across ${currentPage} page(s) for "${keyword}"`);
|
||||
} catch (error) {
|
||||
logger.error(`Error processing keyword "${keyword}": ${error.message}`);
|
||||
logger.error(`Stack: ${error.stack}`);
|
||||
}
|
||||
}
|
||||
|
||||
logger.info(
|
||||
`🎯 Indeed parsing completed: ${results.length} jobs found, ${rejectedResults.length} rejected`
|
||||
);
|
||||
|
||||
return {
|
||||
results,
|
||||
rejectedResults,
|
||||
summary: {
|
||||
totalJobs: results.length,
|
||||
totalRejected: rejectedResults.length,
|
||||
keywords: keywords.join(", "),
|
||||
locationFilter,
|
||||
source: "indeed",
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error(`❌ Indeed parsing failed: ${error.message}`);
|
||||
logger.error(`Stack: ${error.stack}`);
|
||||
return {
|
||||
results,
|
||||
rejectedResults,
|
||||
summary: {
|
||||
totalJobs: results.length,
|
||||
totalRejected: rejectedResults.length,
|
||||
keywords: keywords.join(", "),
|
||||
locationFilter,
|
||||
source: "indeed",
|
||||
error: error.message,
|
||||
},
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract jobs from current page
|
||||
*/
|
||||
async function extractJobsFromPage(page, keyword, locationFilter) {
|
||||
const jobs = [];
|
||||
|
||||
try {
|
||||
// Indeed job listings are typically in divs with data-jk attribute (job key)
|
||||
const jobSelectors = [
|
||||
"[data-jk]",
|
||||
".job_seen_beacon",
|
||||
".jobsearch-SerpJobCard",
|
||||
".jobCard",
|
||||
"div[data-testid='job-card']",
|
||||
];
|
||||
|
||||
let jobElements = [];
|
||||
for (const selector of jobSelectors) {
|
||||
try {
|
||||
await page.waitForSelector(selector, { timeout: 3000 }).catch(() => {});
|
||||
const elements = await page.$$(selector);
|
||||
if (elements.length > 0) {
|
||||
jobElements = elements;
|
||||
logger.info(`✅ Found ${jobElements.length} job elements using selector: ${selector}`);
|
||||
break;
|
||||
}
|
||||
} catch (e) {
|
||||
// Try next selector
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
if (jobElements.length === 0) {
|
||||
logger.warning(`⚠️ No job elements found with any selector`);
|
||||
return jobs;
|
||||
}
|
||||
|
||||
for (const jobElement of jobElements) {
|
||||
try {
|
||||
// Try to scroll job into view, but don't fail if it times out
|
||||
// Some elements might be in hidden containers or lazy-loaded
|
||||
try {
|
||||
await Promise.race([
|
||||
jobElement.scrollIntoViewIfNeeded(),
|
||||
new Promise((_, reject) =>
|
||||
setTimeout(() => reject(new Error('Scroll timeout')), 2000)
|
||||
)
|
||||
]);
|
||||
await new Promise((resolve) => setTimeout(resolve, 100));
|
||||
} catch (scrollError) {
|
||||
// If scrolling fails, try a simpler scroll approach
|
||||
try {
|
||||
await jobElement.evaluate((el) => {
|
||||
el.scrollIntoView({ behavior: 'auto', block: 'center' });
|
||||
});
|
||||
await new Promise((resolve) => setTimeout(resolve, 100));
|
||||
} catch (simpleScrollError) {
|
||||
// If even simple scroll fails, continue anyway - we can still extract data
|
||||
logger.debug(`Could not scroll element into view, continuing anyway: ${simpleScrollError.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
const job = await extractJobData(jobElement, keyword);
|
||||
if (job && (job.title || job.jobId)) {
|
||||
jobs.push(job);
|
||||
}
|
||||
} catch (error) {
|
||||
logger.warning(`Failed to extract job data: ${error.message}`);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Failed to extract jobs from page: ${error.message}`);
|
||||
}
|
||||
|
||||
return jobs;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract data from individual job element
|
||||
*/
|
||||
async function extractJobData(jobElement, keyword) {
|
||||
try {
|
||||
const jobData = await jobElement.evaluate((el) => {
|
||||
const data = {
|
||||
jobId: "",
|
||||
title: "",
|
||||
company: "",
|
||||
location: "",
|
||||
jobUrl: "",
|
||||
postedDate: "",
|
||||
description: "",
|
||||
salary: "",
|
||||
jobType: "",
|
||||
};
|
||||
|
||||
// Extract job ID from data-jk attribute
|
||||
data.jobId = el.getAttribute("data-jk") || "";
|
||||
|
||||
// Extract title and URL
|
||||
const titleSelectors = [
|
||||
"h2.jobTitle a",
|
||||
"h2.jobTitle",
|
||||
"a[data-jk]",
|
||||
"h2 a",
|
||||
".jobTitle a",
|
||||
"[class*='jobTitle'] a",
|
||||
];
|
||||
|
||||
for (const selector of titleSelectors) {
|
||||
const titleElement = el.querySelector(selector);
|
||||
if (titleElement) {
|
||||
data.title = titleElement.textContent?.trim() || titleElement.innerText?.trim() || "";
|
||||
if (titleElement.tagName === "A") {
|
||||
data.jobUrl = titleElement.getAttribute("href") || "";
|
||||
} else {
|
||||
const link = titleElement.querySelector("a");
|
||||
if (link) {
|
||||
data.jobUrl = link.getAttribute("href") || "";
|
||||
}
|
||||
}
|
||||
if (data.title) break;
|
||||
}
|
||||
}
|
||||
|
||||
// Extract company name
|
||||
const companySelectors = [
|
||||
"[data-testid='company-name']",
|
||||
".companyName",
|
||||
"[class*='companyName']",
|
||||
"span.companyName",
|
||||
"a[data-testid='company-name']",
|
||||
];
|
||||
|
||||
for (const selector of companySelectors) {
|
||||
const companyElement = el.querySelector(selector);
|
||||
if (companyElement) {
|
||||
const text = companyElement.textContent?.trim() || companyElement.innerText?.trim() || "";
|
||||
if (text && text.length > 0) {
|
||||
data.company = text;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Extract location
|
||||
const locationSelectors = [
|
||||
"[data-testid='job-location']",
|
||||
".companyLocation",
|
||||
"[class*='companyLocation']",
|
||||
"[class*='location']",
|
||||
];
|
||||
|
||||
for (const selector of locationSelectors) {
|
||||
const locationElement = el.querySelector(selector);
|
||||
if (locationElement) {
|
||||
const text = locationElement.textContent?.trim() || locationElement.innerText?.trim() || "";
|
||||
if (text && text.length > 0) {
|
||||
data.location = text;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Extract salary
|
||||
const salarySelectors = [
|
||||
"[data-testid='attribute_snippet_testid']",
|
||||
".salary-snippet",
|
||||
"[class*='salary']",
|
||||
".salaryText",
|
||||
];
|
||||
|
||||
for (const selector of salarySelectors) {
|
||||
const salaryElement = el.querySelector(selector);
|
||||
if (salaryElement) {
|
||||
const text = salaryElement.textContent?.trim() || salaryElement.innerText?.trim() || "";
|
||||
if (text && text.includes("$") || text.match(/\d+/)) {
|
||||
data.salary = text;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Extract posted date
|
||||
const dateSelectors = [
|
||||
"[data-testid='myJobsStateDate']",
|
||||
".date",
|
||||
"[class*='date']",
|
||||
"span.date",
|
||||
];
|
||||
|
||||
for (const selector of dateSelectors) {
|
||||
const dateElement = el.querySelector(selector);
|
||||
if (dateElement) {
|
||||
const text = dateElement.textContent?.trim() || dateElement.innerText?.trim() || "";
|
||||
if (text) {
|
||||
// Parse relative dates like "2 days ago", "Just posted", etc.
|
||||
const now = new Date();
|
||||
if (text.match(/just posted|today/i)) {
|
||||
data.postedDate = now.toISOString().split("T")[0];
|
||||
} else if (text.match(/\d+\s*(day|days)/i)) {
|
||||
const match = text.match(/(\d+)\s*day/i);
|
||||
if (match) {
|
||||
const daysAgo = parseInt(match[1]);
|
||||
const date = new Date(now);
|
||||
date.setDate(date.getDate() - daysAgo);
|
||||
data.postedDate = date.toISOString().split("T")[0];
|
||||
}
|
||||
} else {
|
||||
data.postedDate = text;
|
||||
}
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Extract description snippet
|
||||
const descSelectors = [
|
||||
".job-snippet",
|
||||
"[class*='job-snippet']",
|
||||
"[class*='summary']",
|
||||
".summary",
|
||||
];
|
||||
|
||||
for (const selector of descSelectors) {
|
||||
const descElement = el.querySelector(selector);
|
||||
if (descElement) {
|
||||
const text = descElement.textContent?.trim() || descElement.innerText?.trim() || "";
|
||||
if (text && text.length > 20) {
|
||||
data.description = text.substring(0, 500); // Limit description length
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return data;
|
||||
});
|
||||
|
||||
// Clean and format
|
||||
const title = cleanText(jobData.title);
|
||||
let jobUrl = jobData.jobUrl || "";
|
||||
|
||||
// Make URL absolute if relative
|
||||
if (jobUrl && !jobUrl.startsWith("http")) {
|
||||
if (jobUrl.startsWith("/")) {
|
||||
jobUrl = `https://www.indeed.com${jobUrl}`;
|
||||
} else {
|
||||
jobUrl = `https://www.indeed.com/viewjob?jk=${jobData.jobId}`;
|
||||
}
|
||||
} else if (!jobUrl && jobData.jobId) {
|
||||
jobUrl = `https://www.indeed.com/viewjob?jk=${jobData.jobId}`;
|
||||
}
|
||||
|
||||
// Generate job ID if not found
|
||||
const jobId = jobData.jobId || `indeed-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`;
|
||||
|
||||
if (!jobId && !title) {
|
||||
return null;
|
||||
}
|
||||
|
||||
return {
|
||||
jobId,
|
||||
title,
|
||||
company: cleanText(jobData.company),
|
||||
location: cleanText(jobData.location),
|
||||
jobUrl,
|
||||
postedDate: jobData.postedDate,
|
||||
description: cleanText(jobData.description),
|
||||
salary: cleanText(jobData.salary),
|
||||
jobType: jobData.jobType,
|
||||
keyword,
|
||||
extractedAt: new Date().toISOString(),
|
||||
source: "indeed",
|
||||
};
|
||||
} catch (error) {
|
||||
logger.warning(`Error extracting job data: ${error.message}`);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Parse job description to separate role duties from job requirements
|
||||
*/
|
||||
function parseDutiesAndRequirements(description) {
|
||||
if (!description || description.trim().length === 0) {
|
||||
return { duties: "", requirements: "" };
|
||||
}
|
||||
|
||||
// Common section headers that indicate duties/responsibilities
|
||||
const dutiesKeywords = [
|
||||
/responsibilities?:/i,
|
||||
/duties?:/i,
|
||||
/what you['\u2019]ll do/i,
|
||||
/key responsibilities/i,
|
||||
/your role/i,
|
||||
/position overview/i,
|
||||
/about the role/i,
|
||||
];
|
||||
|
||||
// Common section headers that indicate requirements/qualifications
|
||||
const requirementsKeywords = [
|
||||
/requirements?:/i,
|
||||
/qualifications?:/i,
|
||||
/must have/i,
|
||||
/required:/i,
|
||||
/what you['\u2019]ll bring/i,
|
||||
/you have:/i,
|
||||
/skills required/i,
|
||||
/minimum requirements/i,
|
||||
];
|
||||
|
||||
// Split description into sections
|
||||
const sections = description.split(/\n\s*\n|\r\n\s*\r\n/).filter(s => s.trim().length > 0);
|
||||
|
||||
let currentSection = "duties";
|
||||
let dutiesText = "";
|
||||
let requirementsText = "";
|
||||
|
||||
for (const section of sections) {
|
||||
let isRequirementsSection = false;
|
||||
for (const keyword of requirementsKeywords) {
|
||||
if (keyword.test(section)) {
|
||||
isRequirementsSection = true;
|
||||
currentSection = "requirements";
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (!isRequirementsSection) {
|
||||
for (const keyword of dutiesKeywords) {
|
||||
if (keyword.test(section)) {
|
||||
currentSection = "duties";
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (currentSection === "requirements") {
|
||||
requirementsText += (requirementsText ? "\n\n" : "") + section.trim();
|
||||
} else {
|
||||
dutiesText += (dutiesText ? "\n\n" : "") + section.trim();
|
||||
}
|
||||
}
|
||||
|
||||
// Fallback: if we still have nothing separated, put first 60% in duties, rest in requirements
|
||||
if (!dutiesText && !requirementsText && description) {
|
||||
const midPoint = Math.floor(description.length * 0.6);
|
||||
dutiesText = description.substring(0, midPoint).trim();
|
||||
requirementsText = description.substring(midPoint).trim();
|
||||
}
|
||||
|
||||
return {
|
||||
duties: dutiesText.trim(),
|
||||
requirements: requirementsText.trim(),
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if next page is available
|
||||
*/
|
||||
async function hasNextPageAvailable(page) {
|
||||
try {
|
||||
const nextButtonSelectors = [
|
||||
"a[aria-label='Next']",
|
||||
"a[aria-label='Next Page']",
|
||||
"a[data-testid='pagination-page-next']",
|
||||
"[data-testid='pagination-page-next']",
|
||||
"a[aria-label*='Next']",
|
||||
];
|
||||
|
||||
for (const selector of nextButtonSelectors) {
|
||||
try {
|
||||
const nextButton = await page.$(selector);
|
||||
if (nextButton) {
|
||||
const isDisabled = await nextButton.evaluate((el) => {
|
||||
return el.hasAttribute("disabled") ||
|
||||
el.getAttribute("aria-disabled") === "true" ||
|
||||
el.classList.contains("disabled");
|
||||
}).catch(() => false);
|
||||
|
||||
if (!isDisabled) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
} catch (e) {
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
return false;
|
||||
} catch (error) {
|
||||
logger.debug(`Error checking for next page: ${error.message}`);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Navigate to next page
|
||||
*/
|
||||
async function navigateToNextPage(page) {
|
||||
try {
|
||||
const nextButtonSelectors = [
|
||||
"a[aria-label='Next']",
|
||||
"a[aria-label='Next Page']",
|
||||
"a[data-testid='pagination-page-next']",
|
||||
"[data-testid='pagination-page-next']",
|
||||
"a[aria-label*='Next']",
|
||||
];
|
||||
|
||||
for (const selector of nextButtonSelectors) {
|
||||
try {
|
||||
const nextButton = await page.$(selector);
|
||||
if (nextButton) {
|
||||
const isDisabled = await nextButton.evaluate((el) => {
|
||||
return el.hasAttribute("disabled") ||
|
||||
el.getAttribute("aria-disabled") === "true" ||
|
||||
el.classList.contains("disabled");
|
||||
}).catch(() => false);
|
||||
|
||||
if (!isDisabled) {
|
||||
// Get current URL before navigation
|
||||
const urlBefore = page.url();
|
||||
|
||||
await nextButton.scrollIntoViewIfNeeded().catch(() => {});
|
||||
await new Promise((resolve) => setTimeout(resolve, 500));
|
||||
|
||||
await nextButton.click();
|
||||
logger.info(`✅ Clicked next page button`);
|
||||
|
||||
// Wait for navigation to complete (URL change or content load)
|
||||
// Indeed might use AJAX, so wait for either URL change or content update
|
||||
let navigationComplete = false;
|
||||
const maxWaitTime = 10000; // 10 seconds max wait
|
||||
const startTime = Date.now();
|
||||
|
||||
while (!navigationComplete && (Date.now() - startTime) < maxWaitTime) {
|
||||
await new Promise((resolve) => setTimeout(resolve, 500));
|
||||
|
||||
// Check if URL changed (full page navigation)
|
||||
const currentUrl = page.url();
|
||||
if (currentUrl !== urlBefore) {
|
||||
logger.info(`📍 URL changed to: ${currentUrl}`);
|
||||
navigationComplete = true;
|
||||
break;
|
||||
}
|
||||
|
||||
// Check if job elements appeared (AJAX navigation)
|
||||
const jobCount = await page.$$eval(
|
||||
"[data-jk], .job_seen_beacon, .jobsearch-SerpJobCard, .jobCard",
|
||||
(elements) => elements.length
|
||||
).catch(() => 0);
|
||||
|
||||
if (jobCount > 0) {
|
||||
logger.info(`✅ Found ${jobCount} job elements (AJAX navigation)`);
|
||||
navigationComplete = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Additional wait for content to stabilize
|
||||
await new Promise((resolve) => setTimeout(resolve, 2000));
|
||||
|
||||
// Check for CAPTCHA after navigation
|
||||
const currentUrl = page.url();
|
||||
if (currentUrl.includes('captcha') || currentUrl.includes('verify') || currentUrl.includes('blocked')) {
|
||||
logger.error(`❌ CAPTCHA detected after navigation to page. URL: ${currentUrl}`);
|
||||
throw new Error('Indeed is showing a CAPTCHA. Please run in non-headless mode (HEADLESS=false) or wait and try again.');
|
||||
}
|
||||
|
||||
// Check page content for CAPTCHA
|
||||
try {
|
||||
const hasCaptcha = await page.evaluate(() => {
|
||||
const bodyText = document.body?.textContent?.toLowerCase() || '';
|
||||
const indicators = ['verify you\'re human', 'captcha', 'unusual traffic', 'automated queries'];
|
||||
return indicators.some(ind => bodyText.includes(ind));
|
||||
});
|
||||
|
||||
if (hasCaptcha) {
|
||||
logger.error(`❌ CAPTCHA detected on page content after navigation`);
|
||||
throw new Error('Indeed CAPTCHA detected. Please run in non-headless mode (HEADLESS=false) to solve it manually.');
|
||||
}
|
||||
} catch (captchaError) {
|
||||
if (captchaError.message.includes('CAPTCHA')) {
|
||||
throw captchaError;
|
||||
}
|
||||
}
|
||||
|
||||
// Scroll page to trigger any lazy loading
|
||||
try {
|
||||
await page.evaluate(() => {
|
||||
window.scrollTo(0, 300);
|
||||
});
|
||||
await new Promise((resolve) => setTimeout(resolve, 1000));
|
||||
} catch (e) {
|
||||
// Ignore scroll errors
|
||||
}
|
||||
|
||||
// Final check for job elements with multiple selectors
|
||||
const finalJobCount = await page.$$eval(
|
||||
"[data-jk], .job_seen_beacon, .jobsearch-SerpJobCard, .jobCard, div[data-testid='job-card']",
|
||||
(elements) => elements.length
|
||||
).catch(() => 0);
|
||||
|
||||
if (finalJobCount > 0) {
|
||||
logger.info(`✅ Navigation successful, found ${finalJobCount} job elements`);
|
||||
return true;
|
||||
} else {
|
||||
logger.warning(`⚠️ No job elements found after navigation (waited ${maxWaitTime}ms)`);
|
||||
// Debug: check what's on the page
|
||||
try {
|
||||
const pageTitle = await page.title();
|
||||
const pageUrl = page.url();
|
||||
logger.debug(`Page title: ${pageTitle}, URL: ${pageUrl}`);
|
||||
|
||||
// Check if it's a CAPTCHA page
|
||||
const bodyText = await page.evaluate(() => document.body?.textContent?.toLowerCase() || '');
|
||||
if (bodyText.includes('captcha') || bodyText.includes('verify')) {
|
||||
logger.error(`❌ Page appears to be a CAPTCHA page`);
|
||||
throw new Error('Indeed is showing a CAPTCHA. Please run in non-headless mode (HEADLESS=false).');
|
||||
}
|
||||
} catch (e) {
|
||||
if (e.message.includes('CAPTCHA')) {
|
||||
throw e;
|
||||
}
|
||||
// Ignore other debug errors
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch (e) {
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
logger.warning(`⚠️ Could not find or click next page button`);
|
||||
return false;
|
||||
} catch (error) {
|
||||
logger.warning(`Failed to navigate to next page: ${error.message}`);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
indeedStrategy,
|
||||
buildSearchUrl,
|
||||
};
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@ -1,493 +1,302 @@
|
||||
/**
|
||||
* SkipTheDrive Parsing Strategy
|
||||
*
|
||||
* Uses core-parser for browser management and ai-analyzer for utilities
|
||||
*/
|
||||
|
||||
const {
|
||||
logger,
|
||||
cleanText,
|
||||
containsAnyKeyword,
|
||||
containsAllKeywords,
|
||||
matchesKeywordGroups,
|
||||
validateLocationAgainstFilters,
|
||||
} = require("ai-analyzer");
|
||||
|
||||
/**
|
||||
* SkipTheDrive URL builder
|
||||
*/
|
||||
function buildSearchUrl(keyword, orderBy = "date", jobTypes = []) {
|
||||
const baseUrl = "https://www.skipthedrive.com/";
|
||||
const params = new URLSearchParams({
|
||||
s: keyword,
|
||||
orderby: orderBy,
|
||||
});
|
||||
|
||||
if (jobTypes && jobTypes.length > 0) {
|
||||
params.append("job_type", jobTypes.join(","));
|
||||
}
|
||||
|
||||
return `${baseUrl}?${params.toString()}`;
|
||||
}
|
||||
|
||||
/**
|
||||
* SkipTheDrive parsing strategy function
|
||||
*/
|
||||
async function skipthedriveStrategy(coreParser, options = {}) {
|
||||
const {
|
||||
keywords = ["software engineer", "developer", "programmer"],
|
||||
keywordGroups = null, // Array of keyword groups for grouped AND/OR logic
|
||||
locationFilter = null,
|
||||
maxPages = 5,
|
||||
jobTypes = [],
|
||||
useAndLogic = false, // Use AND logic instead of OR logic for keywords
|
||||
} = options;
|
||||
|
||||
const results = [];
|
||||
const rejectedResults = [];
|
||||
const seenJobs = new Set();
|
||||
|
||||
try {
|
||||
// Create main page
|
||||
const page = await coreParser.createPage("skipthedrive-main");
|
||||
|
||||
logger.info("🚀 Starting SkipTheDrive parser...");
|
||||
logger.info(`🔍 Keywords: ${keywords.join(", ")}`);
|
||||
if (keywordGroups) {
|
||||
logger.info(`🔗 Keyword Logic: Grouped AND/OR - ${keywordGroups.map(g => `(${g.join(' OR ')})`).join(' AND ')}`);
|
||||
} else {
|
||||
logger.info(`🔗 Keyword Logic: ${useAndLogic ? "AND (all keywords must match)" : "OR (any keyword matches)"}`);
|
||||
}
|
||||
logger.info(`📍 Location Filter: ${locationFilter || "None"}`);
|
||||
logger.info(`📄 Max Pages: ${maxPages}`);
|
||||
|
||||
// Determine search keywords based on logic type
|
||||
let searchKeywords;
|
||||
if (keywordGroups) {
|
||||
// For grouped AND/OR logic, search each keyword in each group (OR within groups)
|
||||
searchKeywords = keywordGroups.flat(); // Flatten all keywords from all groups
|
||||
} else if (useAndLogic) {
|
||||
// For simple AND logic, combine all keywords into a single search query
|
||||
searchKeywords = [keywords.join(" ")];
|
||||
} else {
|
||||
// For OR logic, search each keyword separately
|
||||
searchKeywords = keywords;
|
||||
}
|
||||
|
||||
// Search for each keyword (or combined keyword for AND logic)
|
||||
for (const keyword of searchKeywords) {
|
||||
logger.info(`\n🔍 Searching for: ${keyword}`);
|
||||
|
||||
const searchUrl = buildSearchUrl(keyword, "date", jobTypes);
|
||||
|
||||
try {
|
||||
// Navigate to search results
|
||||
await coreParser.navigateTo(searchUrl, {
|
||||
pageId: "skipthedrive-main",
|
||||
retries: 2,
|
||||
timeout: 30000,
|
||||
});
|
||||
|
||||
// Wait for job listings to load
|
||||
const hasResults = await page
|
||||
.waitForSelector("#loops-wrapper", {
|
||||
timeout: 5000,
|
||||
})
|
||||
.then(() => true)
|
||||
.catch(() => {
|
||||
logger.warning(`No results found for keyword: ${keyword}`);
|
||||
return false;
|
||||
});
|
||||
|
||||
if (!hasResults) {
|
||||
continue;
|
||||
}
|
||||
|
||||
// Process multiple pages
|
||||
let currentPage = 1;
|
||||
let hasNextPage = true;
|
||||
|
||||
while (hasNextPage && currentPage <= maxPages) {
|
||||
logger.info(`📄 Processing page ${currentPage} for "${keyword}"`);
|
||||
|
||||
// Extract jobs from current page
|
||||
const pageJobs = await extractJobsFromPage(
|
||||
page,
|
||||
keyword,
|
||||
locationFilter,
|
||||
keywords,
|
||||
keywordGroups,
|
||||
useAndLogic
|
||||
);
|
||||
|
||||
for (const job of pageJobs) {
|
||||
// Skip duplicates
|
||||
if (seenJobs.has(job.jobId)) continue;
|
||||
seenJobs.add(job.jobId);
|
||||
|
||||
// Validate keywords based on logic type
|
||||
if (keywordGroups) {
|
||||
// Grouped AND/OR logic: all groups must match (AND), at least one keyword per group (OR)
|
||||
const fullText = `${job.title} ${job.description} ${job.company}`;
|
||||
if (!matchesKeywordGroups(fullText, keywordGroups)) {
|
||||
rejectedResults.push({
|
||||
...job,
|
||||
rejectionReason: "Job does not match all keyword groups",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
} else if (useAndLogic) {
|
||||
// Simple AND logic: all keywords must match
|
||||
const fullText = `${job.title} ${job.description} ${job.company}`.toLowerCase();
|
||||
if (!containsAllKeywords(fullText, keywords)) {
|
||||
rejectedResults.push({
|
||||
...job,
|
||||
rejectionReason: "Not all keywords found in job listing",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
// Validate location if filtering enabled
|
||||
if (locationFilter) {
|
||||
const locationValid = validateLocationAgainstFilters(
|
||||
job.location,
|
||||
locationFilter
|
||||
);
|
||||
|
||||
if (!locationValid) {
|
||||
rejectedResults.push({
|
||||
...job,
|
||||
rejectionReason: "Location filter mismatch",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
results.push(job);
|
||||
}
|
||||
|
||||
// Check for next page
|
||||
hasNextPage = await hasNextPageAvailable(page);
|
||||
if (hasNextPage && currentPage < maxPages) {
|
||||
await navigateToNextPage(page, currentPage + 1);
|
||||
currentPage++;
|
||||
|
||||
// Wait for new page to load
|
||||
await page.waitForTimeout(2000);
|
||||
} else {
|
||||
hasNextPage = false;
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Error processing keyword "${keyword}": ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
logger.info(
|
||||
`🎯 SkipTheDrive parsing completed: ${results.length} jobs found, ${rejectedResults.length} rejected`
|
||||
);
|
||||
|
||||
return {
|
||||
results,
|
||||
rejectedResults,
|
||||
summary: {
|
||||
totalJobs: results.length,
|
||||
totalRejected: rejectedResults.length,
|
||||
keywords: keywords.join(", "),
|
||||
locationFilter,
|
||||
source: "skipthedrive",
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error(`❌ SkipTheDrive parsing failed: ${error.message}`);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract jobs from current page
|
||||
*/
|
||||
async function extractJobsFromPage(page, keyword, locationFilter, allKeywords = [], keywordGroups = null, useAndLogic = false) {
|
||||
const jobs = [];
|
||||
|
||||
try {
|
||||
// Get all job article elements
|
||||
const jobElements = await page.$$("article.job_listing");
|
||||
|
||||
for (const jobElement of jobElements) {
|
||||
try {
|
||||
const job = await extractJobData(jobElement, keyword);
|
||||
if (job) {
|
||||
jobs.push(job);
|
||||
}
|
||||
} catch (error) {
|
||||
logger.warning(`Failed to extract job data: ${error.message}`);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Failed to extract jobs from page: ${error.message}`);
|
||||
}
|
||||
|
||||
return jobs;
|
||||
}
|
||||
|
||||
/**
|
||||
* Parse job description to separate role duties from job requirements
|
||||
*/
|
||||
function parseDutiesAndRequirements(description) {
|
||||
if (!description || description.trim().length === 0) {
|
||||
return { duties: "", requirements: "" };
|
||||
}
|
||||
|
||||
// Common section headers that indicate duties/responsibilities
|
||||
const dutiesKeywords = [
|
||||
/responsibilities?:/i,
|
||||
/duties?:/i,
|
||||
/what you['\u2019]ll do/i,
|
||||
/key responsibilities/i,
|
||||
/your role/i,
|
||||
/position overview/i,
|
||||
/about the role/i,
|
||||
/role overview/i,
|
||||
/what we need/i,
|
||||
/you will:/i,
|
||||
/you['\u2019]ll be responsible/i,
|
||||
];
|
||||
|
||||
// Common section headers that indicate requirements/qualifications
|
||||
const requirementsKeywords = [
|
||||
/requirements?:/i,
|
||||
/qualifications?:/i,
|
||||
/must have/i,
|
||||
/required:/i,
|
||||
/what you['\u2019]ll bring/i,
|
||||
/you have:/i,
|
||||
/skills required/i,
|
||||
/minimum requirements/i,
|
||||
/preferred qualifications/i,
|
||||
/education:/i,
|
||||
/experience:/i,
|
||||
/you must have/i,
|
||||
/we['\u2019]re looking for/i,
|
||||
];
|
||||
|
||||
// Split description into sections (by common delimiters)
|
||||
const sections = description.split(/\n\s*\n|\r\n\s*\r\n/).filter(s => s.trim().length > 0);
|
||||
|
||||
let currentSection = "duties"; // Default to duties
|
||||
let dutiesText = "";
|
||||
let requirementsText = "";
|
||||
|
||||
for (const section of sections) {
|
||||
const sectionLower = section.toLowerCase();
|
||||
|
||||
// Check if this section is about requirements
|
||||
let isRequirementsSection = false;
|
||||
for (const keyword of requirementsKeywords) {
|
||||
if (keyword.test(section)) {
|
||||
isRequirementsSection = true;
|
||||
currentSection = "requirements";
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Check if this section is about duties/responsibilities
|
||||
if (!isRequirementsSection) {
|
||||
for (const keyword of dutiesKeywords) {
|
||||
if (keyword.test(section)) {
|
||||
currentSection = "duties";
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Add to appropriate section
|
||||
if (currentSection === "requirements") {
|
||||
requirementsText += (requirementsText ? "\n\n" : "") + section.trim();
|
||||
} else {
|
||||
dutiesText += (dutiesText ? "\n\n" : "") + section.trim();
|
||||
}
|
||||
}
|
||||
|
||||
// If we couldn't split by sections, try to find bullet points or numbered lists
|
||||
if (!dutiesText && !requirementsText) {
|
||||
const lines = description.split(/\n/);
|
||||
let foundRequirementsHeader = false;
|
||||
|
||||
for (let i = 0; i < lines.length; i++) {
|
||||
const line = lines[i].trim();
|
||||
if (line.length === 0) continue;
|
||||
|
||||
// Check if this line is a requirements header
|
||||
for (const keyword of requirementsKeywords) {
|
||||
if (keyword.test(line)) {
|
||||
foundRequirementsHeader = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (foundRequirementsHeader) {
|
||||
requirementsText += (requirementsText ? "\n" : "") + line;
|
||||
} else {
|
||||
// Check if it's a duties header
|
||||
let isDutiesHeader = false;
|
||||
for (const keyword of dutiesKeywords) {
|
||||
if (keyword.test(line)) {
|
||||
isDutiesHeader = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (!isDutiesHeader) {
|
||||
// Add to duties if we haven't found requirements header yet
|
||||
if (!foundRequirementsHeader) {
|
||||
dutiesText += (dutiesText ? "\n" : "") + line;
|
||||
} else {
|
||||
requirementsText += (requirementsText ? "\n" : "") + line;
|
||||
}
|
||||
} else {
|
||||
dutiesText += (dutiesText ? "\n" : "") + line;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Fallback: if we still have nothing separated, put first 60% in duties, rest in requirements
|
||||
if (!dutiesText && !requirementsText && description) {
|
||||
const midPoint = Math.floor(description.length * 0.6);
|
||||
const lastRequirementsKeyword = description.toLowerCase().lastIndexOf("requirement");
|
||||
const lastQualificationsKeyword = description.toLowerCase().lastIndexOf("qualification");
|
||||
const splitPoint = Math.max(
|
||||
lastRequirementsKeyword > 0 ? lastRequirementsKeyword : midPoint,
|
||||
lastQualificationsKeyword > 0 ? lastQualificationsKeyword : midPoint
|
||||
);
|
||||
|
||||
dutiesText = description.substring(0, splitPoint).trim();
|
||||
requirementsText = description.substring(splitPoint).trim();
|
||||
}
|
||||
|
||||
return {
|
||||
duties: dutiesText.trim(),
|
||||
requirements: requirementsText.trim(),
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract data from individual job element
|
||||
*/
|
||||
async function extractJobData(jobElement, keyword) {
|
||||
try {
|
||||
// Extract job ID
|
||||
const articleId = (await jobElement.getAttribute("id")) || "";
|
||||
const jobId = articleId ? articleId.replace("post-", "") : "";
|
||||
|
||||
// Extract title
|
||||
const titleElement = await jobElement.$(".job_listing-title a");
|
||||
const title = titleElement
|
||||
? cleanText(await titleElement.textContent())
|
||||
: "";
|
||||
const jobUrl = titleElement ? await titleElement.getAttribute("href") : "";
|
||||
|
||||
// Extract company
|
||||
const companyElement = await jobElement.$(".company");
|
||||
const company = companyElement
|
||||
? cleanText(await companyElement.textContent())
|
||||
: "";
|
||||
|
||||
// Extract location
|
||||
const locationElement = await jobElement.$(".location");
|
||||
const location = locationElement
|
||||
? cleanText(await locationElement.textContent())
|
||||
: "";
|
||||
|
||||
// Extract date posted
|
||||
const dateElement = await jobElement.$(".job-date");
|
||||
const dateText = dateElement
|
||||
? cleanText(await dateElement.textContent())
|
||||
: "";
|
||||
|
||||
// Extract description
|
||||
const descElement = await jobElement.$(".job_listing-description");
|
||||
const description = descElement
|
||||
? cleanText(await descElement.textContent())
|
||||
: "";
|
||||
|
||||
// Check if featured
|
||||
const featuredElement = await jobElement.$(".featured");
|
||||
const isFeatured = featuredElement !== null;
|
||||
|
||||
// Parse date
|
||||
let datePosted = null;
|
||||
let daysAgo = null;
|
||||
|
||||
if (dateText) {
|
||||
const match = dateText.match(/(\d+)\s+days?\s+ago/);
|
||||
if (match) {
|
||||
daysAgo = parseInt(match[1]);
|
||||
const date = new Date();
|
||||
date.setDate(date.getDate() - daysAgo);
|
||||
datePosted = date.toISOString().split("T")[0];
|
||||
}
|
||||
}
|
||||
|
||||
// Parse duties and requirements from description if available
|
||||
const parsed = parseDutiesAndRequirements(description);
|
||||
|
||||
return {
|
||||
jobId,
|
||||
title,
|
||||
company,
|
||||
location,
|
||||
jobUrl,
|
||||
datePosted,
|
||||
dateText,
|
||||
daysAgo,
|
||||
description,
|
||||
roleDuties: parsed.duties,
|
||||
jobRequirements: parsed.requirements,
|
||||
isFeatured,
|
||||
keyword,
|
||||
extractedAt: new Date().toISOString(),
|
||||
source: "skipthedrive",
|
||||
};
|
||||
} catch (error) {
|
||||
logger.warning(`Error extracting job data: ${error.message}`);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if next page is available
|
||||
*/
|
||||
async function hasNextPageAvailable(page) {
|
||||
try {
|
||||
const nextButton = await page.$(".next-page");
|
||||
return nextButton !== null;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Navigate to next page
|
||||
*/
|
||||
async function navigateToNextPage(page, pageNumber) {
|
||||
try {
|
||||
const nextButton = await page.$(".next-page");
|
||||
if (nextButton) {
|
||||
await nextButton.click();
|
||||
}
|
||||
} catch (error) {
|
||||
logger.warning(
|
||||
`Failed to navigate to page ${pageNumber}: ${error.message}`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
skipthedriveStrategy,
|
||||
buildSearchUrl,
|
||||
extractJobsFromPage,
|
||||
extractJobData,
|
||||
};
|
||||
/**
|
||||
* SkipTheDrive Parsing Strategy
|
||||
*
|
||||
* Uses core-parser for browser management and ai-analyzer for utilities
|
||||
*/
|
||||
|
||||
const {
|
||||
logger,
|
||||
cleanText,
|
||||
containsAnyKeyword,
|
||||
validateLocationAgainstFilters,
|
||||
} = require("ai-analyzer");
|
||||
|
||||
/**
|
||||
* SkipTheDrive URL builder
|
||||
*/
|
||||
function buildSearchUrl(keyword, orderBy = "date", jobTypes = []) {
|
||||
const baseUrl = "https://www.skipthedrive.com/";
|
||||
const params = new URLSearchParams({
|
||||
s: keyword,
|
||||
orderby: orderBy,
|
||||
});
|
||||
|
||||
if (jobTypes && jobTypes.length > 0) {
|
||||
params.append("job_type", jobTypes.join(","));
|
||||
}
|
||||
|
||||
return `${baseUrl}?${params.toString()}`;
|
||||
}
|
||||
|
||||
/**
|
||||
* SkipTheDrive parsing strategy function
|
||||
*/
|
||||
async function skipthedriveStrategy(coreParser, options = {}) {
|
||||
const {
|
||||
keywords = ["software engineer", "developer", "programmer"],
|
||||
locationFilter = null,
|
||||
maxPages = 5,
|
||||
jobTypes = [],
|
||||
} = options;
|
||||
|
||||
const results = [];
|
||||
const rejectedResults = [];
|
||||
const seenJobs = new Set();
|
||||
|
||||
try {
|
||||
// Create main page
|
||||
const page = await coreParser.createPage("skipthedrive-main");
|
||||
|
||||
logger.info("🚀 Starting SkipTheDrive parser...");
|
||||
logger.info(`🔍 Keywords: ${keywords.join(", ")}`);
|
||||
logger.info(`📍 Location Filter: ${locationFilter || "None"}`);
|
||||
logger.info(`📄 Max Pages: ${maxPages}`);
|
||||
|
||||
// Search for each keyword
|
||||
for (const keyword of keywords) {
|
||||
logger.info(`\n🔍 Searching for: ${keyword}`);
|
||||
|
||||
const searchUrl = buildSearchUrl(keyword, "date", jobTypes);
|
||||
|
||||
try {
|
||||
// Navigate to search results
|
||||
await coreParser.navigateTo(searchUrl, {
|
||||
pageId: "skipthedrive-main",
|
||||
retries: 2,
|
||||
timeout: 30000,
|
||||
});
|
||||
|
||||
// Wait for job listings to load
|
||||
const hasResults = await coreParser
|
||||
.waitForSelector(
|
||||
"#loops-wrapper",
|
||||
{
|
||||
timeout: 5000,
|
||||
},
|
||||
"skipthedrive-main"
|
||||
)
|
||||
.catch(() => {
|
||||
logger.warning(`No results found for keyword: ${keyword}`);
|
||||
return false;
|
||||
});
|
||||
|
||||
if (!hasResults) {
|
||||
continue;
|
||||
}
|
||||
|
||||
// Process multiple pages
|
||||
let currentPage = 1;
|
||||
let hasNextPage = true;
|
||||
|
||||
while (hasNextPage && currentPage <= maxPages) {
|
||||
logger.info(`📄 Processing page ${currentPage} for "${keyword}"`);
|
||||
|
||||
// Extract jobs from current page
|
||||
const pageJobs = await extractJobsFromPage(
|
||||
page,
|
||||
keyword,
|
||||
locationFilter
|
||||
);
|
||||
|
||||
for (const job of pageJobs) {
|
||||
// Skip duplicates
|
||||
if (seenJobs.has(job.jobId)) continue;
|
||||
seenJobs.add(job.jobId);
|
||||
|
||||
// Validate location if filtering enabled
|
||||
if (locationFilter) {
|
||||
const locationValid = validateLocationAgainstFilters(
|
||||
job.location,
|
||||
locationFilter
|
||||
);
|
||||
|
||||
if (!locationValid) {
|
||||
rejectedResults.push({
|
||||
...job,
|
||||
rejectionReason: "Location filter mismatch",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
results.push(job);
|
||||
}
|
||||
|
||||
// Check for next page
|
||||
hasNextPage = await hasNextPageAvailable(page);
|
||||
if (hasNextPage && currentPage < maxPages) {
|
||||
await navigateToNextPage(page, currentPage + 1);
|
||||
currentPage++;
|
||||
|
||||
// Wait for new page to load
|
||||
await page.waitForTimeout(2000);
|
||||
} else {
|
||||
hasNextPage = false;
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Error processing keyword "${keyword}": ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
logger.info(
|
||||
`🎯 SkipTheDrive parsing completed: ${results.length} jobs found, ${rejectedResults.length} rejected`
|
||||
);
|
||||
|
||||
return {
|
||||
results,
|
||||
rejectedResults,
|
||||
summary: {
|
||||
totalJobs: results.length,
|
||||
totalRejected: rejectedResults.length,
|
||||
keywords: keywords.join(", "),
|
||||
locationFilter,
|
||||
source: "skipthedrive",
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error(`❌ SkipTheDrive parsing failed: ${error.message}`);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract jobs from current page
|
||||
*/
|
||||
async function extractJobsFromPage(page, keyword, locationFilter) {
|
||||
const jobs = [];
|
||||
|
||||
try {
|
||||
// Get all job article elements
|
||||
const jobElements = await page.$$("article.job_listing");
|
||||
|
||||
for (const jobElement of jobElements) {
|
||||
try {
|
||||
const job = await extractJobData(jobElement, keyword);
|
||||
if (job) {
|
||||
jobs.push(job);
|
||||
}
|
||||
} catch (error) {
|
||||
logger.warning(`Failed to extract job data: ${error.message}`);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(`Failed to extract jobs from page: ${error.message}`);
|
||||
}
|
||||
|
||||
return jobs;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract data from individual job element
|
||||
*/
|
||||
async function extractJobData(jobElement, keyword) {
|
||||
try {
|
||||
// Extract job ID
|
||||
const articleId = (await jobElement.getAttribute("id")) || "";
|
||||
const jobId = articleId ? articleId.replace("post-", "") : "";
|
||||
|
||||
// Extract title
|
||||
const titleElement = await jobElement.$(".job_listing-title a");
|
||||
const title = titleElement
|
||||
? cleanText(await titleElement.textContent())
|
||||
: "";
|
||||
const jobUrl = titleElement ? await titleElement.getAttribute("href") : "";
|
||||
|
||||
// Extract company
|
||||
const companyElement = await jobElement.$(".company");
|
||||
const company = companyElement
|
||||
? cleanText(await companyElement.textContent())
|
||||
: "";
|
||||
|
||||
// Extract location
|
||||
const locationElement = await jobElement.$(".location");
|
||||
const location = locationElement
|
||||
? cleanText(await locationElement.textContent())
|
||||
: "";
|
||||
|
||||
// Extract date posted
|
||||
const dateElement = await jobElement.$(".job-date");
|
||||
const dateText = dateElement
|
||||
? cleanText(await dateElement.textContent())
|
||||
: "";
|
||||
|
||||
// Extract description
|
||||
const descElement = await jobElement.$(".job_listing-description");
|
||||
const description = descElement
|
||||
? cleanText(await descElement.textContent())
|
||||
: "";
|
||||
|
||||
// Check if featured
|
||||
const featuredElement = await jobElement.$(".featured");
|
||||
const isFeatured = featuredElement !== null;
|
||||
|
||||
// Parse date
|
||||
let datePosted = null;
|
||||
let daysAgo = null;
|
||||
|
||||
if (dateText) {
|
||||
const match = dateText.match(/(\d+)\s+days?\s+ago/);
|
||||
if (match) {
|
||||
daysAgo = parseInt(match[1]);
|
||||
const date = new Date();
|
||||
date.setDate(date.getDate() - daysAgo);
|
||||
datePosted = date.toISOString().split("T")[0];
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
jobId,
|
||||
title,
|
||||
company,
|
||||
location,
|
||||
jobUrl,
|
||||
datePosted,
|
||||
dateText,
|
||||
daysAgo,
|
||||
description,
|
||||
isFeatured,
|
||||
keyword,
|
||||
extractedAt: new Date().toISOString(),
|
||||
source: "skipthedrive",
|
||||
};
|
||||
} catch (error) {
|
||||
logger.warning(`Error extracting job data: ${error.message}`);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if next page is available
|
||||
*/
|
||||
async function hasNextPageAvailable(page) {
|
||||
try {
|
||||
const nextButton = await page.$(".next-page");
|
||||
return nextButton !== null;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Navigate to next page
|
||||
*/
|
||||
async function navigateToNextPage(page, pageNumber) {
|
||||
try {
|
||||
const nextButton = await page.$(".next-page");
|
||||
if (nextButton) {
|
||||
await nextButton.click();
|
||||
}
|
||||
} catch (error) {
|
||||
logger.warning(
|
||||
`Failed to navigate to page ${pageNumber}: ${error.message}`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
skipthedriveStrategy,
|
||||
buildSearchUrl,
|
||||
extractJobsFromPage,
|
||||
extractJobData,
|
||||
};
|
||||
|
||||
@ -10,34 +10,20 @@ const path = require("path");
|
||||
const fs = require("fs");
|
||||
const CoreParser = require("../core-parser");
|
||||
const { linkedinStrategy } = require("./strategies/linkedin-strategy");
|
||||
const { logger, analyzeBatch, checkOllamaStatus, DEFAULT_MODEL } = require("ai-analyzer");
|
||||
const { logger, analyzeBatch, checkOllamaStatus } = require("ai-analyzer");
|
||||
|
||||
// Load environment variables - check both linkedin-parser/.env and root .env
|
||||
const localEnvPath = path.join(__dirname, ".env");
|
||||
const rootEnvPath = path.join(__dirname, "..", ".env");
|
||||
|
||||
// Try local .env first, then root .env
|
||||
if (fs.existsSync(localEnvPath)) {
|
||||
require("dotenv").config({ path: localEnvPath });
|
||||
} else if (fs.existsSync(rootEnvPath)) {
|
||||
require("dotenv").config({ path: rootEnvPath });
|
||||
} else {
|
||||
// Try default dotenv behavior (looks in current directory and parent directories)
|
||||
require("dotenv").config();
|
||||
}
|
||||
// Load environment variables
|
||||
require("dotenv").config({ path: path.join(__dirname, ".env") });
|
||||
|
||||
// Configuration from environment
|
||||
const LINKEDIN_USERNAME = process.env.LINKEDIN_USERNAME;
|
||||
const LINKEDIN_PASSWORD = process.env.LINKEDIN_PASSWORD;
|
||||
const HEADLESS = process.env.HEADLESS !== "false";
|
||||
const SEARCH_KEYWORDS =
|
||||
process.env.SEARCH_KEYWORDS || "layoff";//,downsizing";//,job cuts";
|
||||
process.env.SEARCH_KEYWORDS || "layoff,downsizing,job cuts";
|
||||
const LOCATION_FILTER = process.env.LOCATION_FILTER;
|
||||
const ENABLE_AI_ANALYSIS = process.env.ENABLE_AI_ANALYSIS !== "false";
|
||||
const AI_CONTEXT = process.env.AI_CONTEXT || "job market analysis and trends";
|
||||
const OLLAMA_MODEL = process.env.OLLAMA_MODEL || DEFAULT_MODEL;
|
||||
const ENABLE_AI_ANALYSIS = process.env.ENABLE_AI_ANALYSIS === "true";
|
||||
const MAX_RESULTS = parseInt(process.env.MAX_RESULTS) || 50;
|
||||
const EXTRACT_LOCATION_FROM_PROFILE = process.env.EXTRACT_LOCATION_FROM_PROFILE === "true";
|
||||
|
||||
/**
|
||||
* Main LinkedIn parser function
|
||||
@ -72,7 +58,6 @@ async function startLinkedInParser(options = {}) {
|
||||
keywords,
|
||||
locationFilter: LOCATION_FILTER,
|
||||
maxResults: MAX_RESULTS,
|
||||
extractLocationFromProfile: EXTRACT_LOCATION_FROM_PROFILE,
|
||||
credentials: {
|
||||
username: LINKEDIN_USERNAME,
|
||||
password: LINKEDIN_PASSWORD,
|
||||
@ -81,109 +66,52 @@ async function startLinkedInParser(options = {}) {
|
||||
|
||||
const { results, rejectedResults, summary } = parseResult;
|
||||
|
||||
// AI Analysis if enabled - embed results into each post
|
||||
let resultsWithAI = results;
|
||||
let aiAnalysisCompleted = false;
|
||||
// AI Analysis if enabled
|
||||
let analysisResults = null;
|
||||
if (ENABLE_AI_ANALYSIS && results.length > 0) {
|
||||
logger.step("🧠 Running AI Analysis...");
|
||||
|
||||
const ollamaAvailable = await checkOllamaStatus(OLLAMA_MODEL);
|
||||
if (ollamaAvailable) {
|
||||
// Prepare data for analysis (analyzeBatch expects posts with 'text' field)
|
||||
const analysisData = results.map((post) => ({
|
||||
text: post.text || post.content || "",
|
||||
location: post.location || "",
|
||||
keyword: post.keyword || "",
|
||||
timestamp: post.timestamp || post.extractedAt || "",
|
||||
}));
|
||||
|
||||
const analysisResults = await analyzeBatch(
|
||||
analysisData,
|
||||
AI_CONTEXT,
|
||||
OLLAMA_MODEL
|
||||
);
|
||||
|
||||
// Embed AI analysis into each result
|
||||
resultsWithAI = results.map((post, index) => {
|
||||
const aiResult = analysisResults[index];
|
||||
return {
|
||||
...post,
|
||||
aiAnalysis: {
|
||||
isRelevant: aiResult.isRelevant,
|
||||
confidence: aiResult.confidence,
|
||||
reasoning: aiResult.reasoning,
|
||||
context: AI_CONTEXT,
|
||||
model: OLLAMA_MODEL,
|
||||
analyzedAt: new Date().toISOString(),
|
||||
},
|
||||
};
|
||||
const ollamaStatus = await checkOllamaStatus();
|
||||
if (ollamaStatus.available) {
|
||||
analysisResults = await analyzeBatch(results, {
|
||||
context:
|
||||
"LinkedIn posts analysis focusing on job market trends and layoffs",
|
||||
});
|
||||
|
||||
aiAnalysisCompleted = true;
|
||||
logger.success(`✅ AI Analysis completed for ${results.length} posts`);
|
||||
} else {
|
||||
logger.warning("⚠️ Ollama not available, skipping AI analysis");
|
||||
}
|
||||
}
|
||||
|
||||
// Prepare results with embedded AI analysis
|
||||
// Save results
|
||||
const outputData = {
|
||||
metadata: {
|
||||
timestamp: new Date().toISOString(),
|
||||
totalPosts: resultsWithAI.length,
|
||||
rejectedPosts: rejectedResults.length,
|
||||
aiAnalysisEnabled: ENABLE_AI_ANALYSIS,
|
||||
aiAnalysisCompleted: aiAnalysisCompleted,
|
||||
aiContext: aiAnalysisCompleted ? AI_CONTEXT : undefined,
|
||||
aiModel: aiAnalysisCompleted ? OLLAMA_MODEL : undefined,
|
||||
locationFilter: LOCATION_FILTER || undefined,
|
||||
extractedAt: new Date().toISOString(),
|
||||
parser: "linkedin-parser",
|
||||
version: "2.0.0",
|
||||
summary,
|
||||
analysisResults,
|
||||
},
|
||||
results: resultsWithAI,
|
||||
results,
|
||||
rejectedResults,
|
||||
};
|
||||
|
||||
// Prepare rejected posts file
|
||||
const rejectedData = rejectedResults.map((post) => ({
|
||||
rejected: true,
|
||||
reason: post.rejectionReason || "Location filter failed: Location not in filter",
|
||||
keyword: post.keyword,
|
||||
text: post.text || post.content,
|
||||
profileLink: post.profileLink || post.authorUrl,
|
||||
location: post.location || post.profileLocation,
|
||||
timestamp: post.timestamp || post.extractedAt,
|
||||
}));
|
||||
|
||||
const resultsDir = path.join(__dirname, "results");
|
||||
if (!fs.existsSync(resultsDir)) {
|
||||
fs.mkdirSync(resultsDir, { recursive: true });
|
||||
}
|
||||
|
||||
const timestamp = new Date().toISOString().replace(/[:.]/g, "-");
|
||||
const resultsFilename = `linkedin-results-${timestamp}.json`;
|
||||
const rejectedFilename = `linkedin-rejected-${timestamp}.json`;
|
||||
const resultsFilepath = path.join(resultsDir, resultsFilename);
|
||||
const rejectedFilepath = path.join(resultsDir, rejectedFilename);
|
||||
const filename = `linkedin-results-${timestamp}.json`;
|
||||
const filepath = path.join(resultsDir, filename);
|
||||
|
||||
// Save results with AI analysis
|
||||
fs.writeFileSync(resultsFilepath, JSON.stringify(outputData, null, 2));
|
||||
|
||||
// Save rejected posts separately
|
||||
if (rejectedData.length > 0) {
|
||||
fs.writeFileSync(
|
||||
rejectedFilepath,
|
||||
JSON.stringify(rejectedData, null, 2)
|
||||
);
|
||||
}
|
||||
fs.writeFileSync(filepath, JSON.stringify(outputData, null, 2));
|
||||
|
||||
// Final summary
|
||||
logger.success("✅ LinkedIn parsing completed successfully!");
|
||||
logger.info(`📊 Total posts found: ${resultsWithAI.length}`);
|
||||
logger.info(`📊 Total posts found: ${results.length}`);
|
||||
logger.info(`❌ Total rejected: ${rejectedResults.length}`);
|
||||
logger.info(`📁 Results saved to: ${resultsFilepath}`);
|
||||
if (rejectedData.length > 0) {
|
||||
logger.info(`📁 Rejected posts saved to: ${rejectedFilepath}`);
|
||||
}
|
||||
logger.info(`📁 Results saved to: ${filepath}`);
|
||||
|
||||
return outputData;
|
||||
} catch (error) {
|
||||
|
||||
3705
linkedin-parser/package-lock.json
generated
3705
linkedin-parser/package-lock.json
generated
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
3667
package-lock.json
generated
3667
package-lock.json
generated
File diff suppressed because it is too large
Load Diff
@ -1,80 +1,80 @@
|
||||
const fs = require("fs");
|
||||
const assert = require("assert");
|
||||
const { analyzeSinglePost, checkOllamaStatus } = require("../ai-analyzer");
|
||||
|
||||
console.log("AI Analyzer logic tests");
|
||||
|
||||
const testData = JSON.parse(
|
||||
fs.readFileSync(__dirname + "/test-data.json", "utf-8")
|
||||
);
|
||||
const aiResults = testData.positive;
|
||||
const context = "job layoffs and workforce reduction";
|
||||
const model = process.env.OLLAMA_MODEL || "mistral"; // Use OLLAMA_MODEL from env or default to mistral
|
||||
|
||||
(async () => {
|
||||
// Check if Ollama is available
|
||||
const ollamaAvailable = await checkOllamaStatus(model);
|
||||
if (!ollamaAvailable) {
|
||||
console.log("SKIP: Ollama not available - skipping AI analyzer tests");
|
||||
console.log("PASS: AI analyzer tests skipped (Ollama not running)");
|
||||
return;
|
||||
}
|
||||
|
||||
console.log(`Testing AI analyzer with ${aiResults.length} posts...`);
|
||||
|
||||
for (let i = 0; i < aiResults.length; i++) {
|
||||
const post = aiResults[i];
|
||||
console.log(`Testing post ${i + 1}: "${post.text.substring(0, 50)}..."`);
|
||||
|
||||
const aiOutput = await analyzeSinglePost(post.text, context, model);
|
||||
|
||||
// Test that the function returns the expected structure
|
||||
assert(
|
||||
typeof aiOutput === "object" && aiOutput !== null,
|
||||
`Post ${i} output is not an object`
|
||||
);
|
||||
|
||||
assert(
|
||||
typeof aiOutput.isRelevant === "boolean",
|
||||
`Post ${i} isRelevant is not a boolean: ${typeof aiOutput.isRelevant}`
|
||||
);
|
||||
|
||||
assert(
|
||||
typeof aiOutput.confidence === "number",
|
||||
`Post ${i} confidence is not a number: ${typeof aiOutput.confidence}`
|
||||
);
|
||||
|
||||
assert(
|
||||
typeof aiOutput.reasoning === "string",
|
||||
`Post ${i} reasoning is not a string: ${typeof aiOutput.reasoning}`
|
||||
);
|
||||
|
||||
// Test that confidence is within valid range
|
||||
assert(
|
||||
aiOutput.confidence >= 0 && aiOutput.confidence <= 1,
|
||||
`Post ${i} confidence out of range: ${aiOutput.confidence} (should be 0-1)`
|
||||
);
|
||||
|
||||
// Test that reasoning exists and is not empty
|
||||
assert(
|
||||
aiOutput.reasoning && aiOutput.reasoning.length > 0,
|
||||
`Post ${i} missing or empty reasoning`
|
||||
);
|
||||
|
||||
// Test that relevance is a boolean value
|
||||
assert(
|
||||
aiOutput.isRelevant === true || aiOutput.isRelevant === false,
|
||||
`Post ${i} isRelevant is not a valid boolean: ${aiOutput.isRelevant}`
|
||||
);
|
||||
|
||||
console.log(
|
||||
` ✓ Post ${i + 1}: relevant=${aiOutput.isRelevant}, confidence=${
|
||||
aiOutput.confidence
|
||||
}`
|
||||
);
|
||||
}
|
||||
|
||||
console.log(
|
||||
"PASS: AI analyzer returns valid structure and values for all test posts."
|
||||
);
|
||||
})();
|
||||
const fs = require("fs");
|
||||
const assert = require("assert");
|
||||
const { analyzeSinglePost, checkOllamaStatus } = require("../ai-analyzer");
|
||||
|
||||
console.log("AI Analyzer logic tests");
|
||||
|
||||
const testData = JSON.parse(
|
||||
fs.readFileSync(__dirname + "/test-data.json", "utf-8")
|
||||
);
|
||||
const aiResults = testData.positive;
|
||||
const context = "job layoffs and workforce reduction";
|
||||
const model = "mistral"; // or your default model
|
||||
|
||||
(async () => {
|
||||
// Check if Ollama is available
|
||||
const ollamaAvailable = await checkOllamaStatus(model);
|
||||
if (!ollamaAvailable) {
|
||||
console.log("SKIP: Ollama not available - skipping AI analyzer tests");
|
||||
console.log("PASS: AI analyzer tests skipped (Ollama not running)");
|
||||
return;
|
||||
}
|
||||
|
||||
console.log(`Testing AI analyzer with ${aiResults.length} posts...`);
|
||||
|
||||
for (let i = 0; i < aiResults.length; i++) {
|
||||
const post = aiResults[i];
|
||||
console.log(`Testing post ${i + 1}: "${post.text.substring(0, 50)}..."`);
|
||||
|
||||
const aiOutput = await analyzeSinglePost(post.text, context, model);
|
||||
|
||||
// Test that the function returns the expected structure
|
||||
assert(
|
||||
typeof aiOutput === "object" && aiOutput !== null,
|
||||
`Post ${i} output is not an object`
|
||||
);
|
||||
|
||||
assert(
|
||||
typeof aiOutput.isRelevant === "boolean",
|
||||
`Post ${i} isRelevant is not a boolean: ${typeof aiOutput.isRelevant}`
|
||||
);
|
||||
|
||||
assert(
|
||||
typeof aiOutput.confidence === "number",
|
||||
`Post ${i} confidence is not a number: ${typeof aiOutput.confidence}`
|
||||
);
|
||||
|
||||
assert(
|
||||
typeof aiOutput.reasoning === "string",
|
||||
`Post ${i} reasoning is not a string: ${typeof aiOutput.reasoning}`
|
||||
);
|
||||
|
||||
// Test that confidence is within valid range
|
||||
assert(
|
||||
aiOutput.confidence >= 0 && aiOutput.confidence <= 1,
|
||||
`Post ${i} confidence out of range: ${aiOutput.confidence} (should be 0-1)`
|
||||
);
|
||||
|
||||
// Test that reasoning exists and is not empty
|
||||
assert(
|
||||
aiOutput.reasoning && aiOutput.reasoning.length > 0,
|
||||
`Post ${i} missing or empty reasoning`
|
||||
);
|
||||
|
||||
// Test that relevance is a boolean value
|
||||
assert(
|
||||
aiOutput.isRelevant === true || aiOutput.isRelevant === false,
|
||||
`Post ${i} isRelevant is not a valid boolean: ${aiOutput.isRelevant}`
|
||||
);
|
||||
|
||||
console.log(
|
||||
` ✓ Post ${i + 1}: relevant=${aiOutput.isRelevant}, confidence=${
|
||||
aiOutput.confidence
|
||||
}`
|
||||
);
|
||||
}
|
||||
|
||||
console.log(
|
||||
"PASS: AI analyzer returns valid structure and values for all test posts."
|
||||
);
|
||||
})();
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user