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Automate your job search pipeline — scrape, score, generate tailored resumes, and auto-apply.

Project description

ApplyBot

Automate your job search pipeline — for any profession.

Quick start

Technical users

pip install applybot
applybot init          # 2-min guided wizard
applybot run --dry-run # test without submitting
applybot run           # go live

Non-technical users

Double-click installers/install.bat (Windows) or installers/install.sh (Mac/Linux).

Commands

Command What it does
applybot init Guided setup wizard
applybot login linkedin Save LinkedIn session (for auto-apply)
applybot run Full pipeline
applybot run --dry-run Test without submitting
applybot run --no-apply Scrape + generate docs only
applybot status Print status table in terminal
applybot dashboard Rebuild + open dashboard

Configuration

All settings live in applybot.json (created by applybot init). Never commit this file — it contains your API key.

Browser automation

Auto-apply to LinkedIn Easy Apply, Greenhouse, and Lever.

Setup (one time):

pip install "applybot[browser]"
playwright install chrome
applybot login linkedin    # opens Chrome — log in, then close the window

Cookies are saved to sessions/linkedin_cookies.json. Keep this file private.

Supported platforms:

  • LinkedIn Easy Apply
  • Greenhouse
  • Lever

LLM setup (optional)

ApplyBot can use an LLM to answer open-text custom questions on application forms.

Set llm_provider in applybot.json to one of:

Provider Description
none (default) Skip custom questions — fill manually
claude Anthropic Claude (requires llm_api_key)
openai OpenAI GPT (requires llm_api_key)
custom Any OpenAI-compatible endpoint (set llm_custom_url)

Example config for Claude:

{
  "llm_provider": "claude",
  "llm_api_key": "sk-ant-...",
  "llm_model": "claude-haiku-4-5-20251001"
}

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