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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with adaptive difficulty.
| Date | Stars |
|---|---|
| 2026-07-31 | 254 |
| 2026-08-06 | 252 |
Today
-2 stars today
This week
— stars this week
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— stars this month
Momentum
0.0
growth rate 0.00%/day
<div align="center"> <img src="docs/banner.png" alt="FindJobs-Agent" width="100%"> [](https://www.python.org/downloads/) [](LICENSE) [](https://github.com/he-yufeng/FindJobs-Agent/actions/workflows/ci.yml) **[English](README.md) · [中文](README_CN.md)** · [Quick Start](#quick-start) · [How It Works](#how-it-works) · [Features](#features) </div> --- ## 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. ## How It Works Four pieces wired into one flow: a crawler pulls postings from company career sites, an LLM reads each one for requirements and skills, your resume gets parsed and scored against them, and any posting can drive an AI mock interview straight off its job description. The React frontend ties it together, so you go from "what's out there" to "let me practice for this one" without leaving the app.  ## Features - **Job crawler** — pulls postings from Tencent, NetEase, ByteDance, Amazon and more, via API or Selenium, with automatic cleaning and normalization. - **LLM analysis** — extracts education/major requirements, scores skill tags (1–5), and classifies each posting into a job taxonomy. - **Resume parsing & matching** — parses PDF/Word resumes, scores skills, and computes a case-insensitive job-resume match percentage. - **AI mock interview** — generates questions from any job description and runs a multi-turn interview with real-time feedback. - **SQLite persistence** — analyzed postings are stored in a local `jobs.db`; existing CSV data is migrated automatically on first run, with CSV/JSON as fallback. ## 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 ├── storage.py # SQLite job store (jobs.db) ├── interview_agent.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 ```bash git clone https://github.com/he-yufeng/FindJobs-Agent.git cd FindJobs-Agent ``` ### 2. Install backend dependencies ```bash 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 ```bash python api_server.py ``` ### 5. Start the frontend ```bash cd FrontEnd npm install npm run dev ``` ### 6. Open the app Visit http://localhost:8080 in your browser. ## Data Pipeline `pipeline.py` chains crawl → analyze → score → serve. Run the whole thing, or a single stage: ```bash python pipeline.py # crawl + analyze + build site data python job_crawler_v2.py -c tencent netease amazon -m 300 # crawl only (--list shows companies) python pipeline.py --analyze-only --max-jobs 50 # analyze only (for t
Excerpt of 6,199 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4cdac91141f7846d, llm:Topics: ai-agent, crawler, interview, job-search, llm, resume; description: 'LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with adaptive difficulty.'
matched fp:4cdac91141f7846d, llm:Topics: ai-agent, crawler, interview, job-search, llm, resume; description: 'LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with adaptive difficulty.'
matched fp:4cdac91141f7846d, llm:Topics: ai-agent, crawler, interview, job-search, llm, resume; description: 'LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with adaptive difficulty.'