FindJobs-Agent

LLM-powered job hunting toolkit — from crawling to interview prep, all in one place.

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What is FindJobs-Agent?

A full-stack job search assistant that crawls postings from major tech companies, analyzes them with LLMs, parses your resume, and runs AI mock interviews — so you can focus on preparing, not sifting through job boards.

Features

Job Crawler

• Crawl job postings from Tencent, NetEase, ByteDance, Amazon, and more
• Dual mode: API crawling + Selenium browser automation
• Automatic data cleaning and format normalization

LLM Job Analysis

• Extract education and major requirements automatically
• Skill tag recognition with importance scoring (1-5)
• Job taxonomy classification (primary/secondary categories)

Resume Parsing & Matching

• Parse PDF/Word resumes intelligently
• Extract and score skill tags
• Calculate job-resume match percentage

AI Mock Interview

• Generate targeted interview questions from job descriptions
• Multi-turn conversational interview simulation
• Real-time feedback and suggestions

Project Structure

FindJobs-Agent/
├── FrontEnd/                # React frontend
│   ├── src/
│   │   ├── components/      # Page components
│   │   │   ├── JobsPage.tsx       # Job browsing
│   │   │   ├── ResumePage.tsx     # Resume analysis
│   │   │   └── InterviewPage.tsx  # AI interview
│   │   └── App.tsx
│   └── package.json
├── job_crawler_v2.py        # Multi-company crawler (primary)
├── job_crawler_selenium.py  # Selenium crawler
├── job_agent.py             # LLM job analysis agent
├── pipeline.py              # Data processing pipeline
├── api_server.py            # Flask API server
├── AI_interviewer.py        # AI interview module
├── resume_parser.py         # Resume parser
├── tag_rate.py              # Skill scoring
├── llm_client.py            # LLM client
├── tech_taxonomy.json       # Job taxonomy
├── all_labels.csv           # Skill tag library
└── requirements.txt

Quick Start

Prerequisites

• Python 3.9+
• Node.js 18+
• Chrome (required for Selenium crawler)

1. Clone the repo

git clone https://github.com/he-yufeng/FindJobs-Agent.git
cd FindJobs-Agent

2. Install backend dependencies

pip install -r requirements.txt

3. Set up your API key

Create an API_key.md file with your OpenAI API key:

sk-your-api-key-here

4. Start the backend

python api_server.py

5. Start the frontend

cd FrontEnd
npm install
npm run dev

6. Open the app

Visit http://localhost:8080 in your browser.

Data Pipeline

The processing flow goes through four stages:

1. Crawl (job_crawler_v2.py) — Fetch job postings from company career sites
2. Analyze (job_agent.py) — LLM extracts requirements, skills, and classifications
3. Score (tag_rate.py) — Match and score skill tags against the taxonomy
4. Serve (api_server.py) — Expose results via REST API for the frontend

Run the full pipeline

# Crawl + analyze + generate website data
python pipeline.py

# Crawl only
python job_crawler_v2.py -c tencent netease amazon -m 300

# Analyze only (for testing)
python pipeline.py --analyze-only --max-jobs 50

Key Modules

job_crawler_v2.py

Multi-company job crawler supporting:

• Tencent, NetEase, ByteDance, Amazon (stable, API-based)
• Alibaba, Meituan, JD, etc. (Selenium mode)

# Crawl specific companies
python job_crawler_v2.py -c tencent netease -m 500

# List supported companies
python job_crawler_v2.py --list

job_agent.py

LLM-driven job analysis agent:

• Education requirement extraction (Bachelor's/Master's/PhD)
• Major requirement identification
• Skill tag matching and scoring
• Job classification

AI_interviewer.py

AI mock interview system:

• Generates interview questions from job descriptions
• Multi-turn conversational interaction
• Answer evaluation and feedback

API Endpoints

Endpoint	Method	Description
/api/jobs	GET	List job postings
/api/jobs/<id>	GET	Get job details
/api/resume/upload	POST	Upload resume
/api/resume/analyze	POST	Analyze resume
/api/interview/start	POST	Start mock interview
/api/interview/answer	POST	Submit interview answer

Contributing

Issues and pull requests are welcome!

License

MIT License