A full-stack job search assistant automating the process of finding, analyzing, and preparing for job applications. It targets tech professionals by streamlining job discovery, resume assessment, and AI-driven interview practice, reducing manual effort.

How It Works

The system comprises four integrated components: a job crawler (API/Selenium) for tech company postings, an LLM engine for requirement extraction and skill scoring, a resume parser (PDF/Word) for skill matching, and an AI mock interviewer generating questions from job descriptions. A React frontend unifies these functions.

Quick Start & Requirements

• Prerequisites: Python 3.9+, Node.js 18+, Google Chrome.
• Installation: Clone repo, pip install -r requirements.txt, create API_key.md (OpenAI key).
• Running: Start backend: python api_server.py. Frontend: cd FrontEnd, npm install, npm run dev.
• Access: http://localhost:8080.
• Links: LICENSE, CI Workflow.

Highlighted Details

• Job Crawler: Supports major tech firms (Tencent, NetEase, Amazon) via API or Selenium.
• LLM Analysis: Extracts education/major requirements, scores skills (1-5), classifies job roles.
• Resume Parsing: Handles PDF/Word, scores skills, computes job-resume match percentage.
• AI Mock Interview: Generates questions from job descriptions, provides real-time feedback.

Maintenance & Community

Active maintenance indicated by CI. No specific community channels or contributor details are provided in the README.

Licensing & Compatibility

MIT License, generally permissive for commercial use.

Limitations & Caveats

Job source coverage is limited to specific companies; expansion is planned. Current implementation re-crawls all data. Application tracking and voice interviews are future roadmap items.