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jbegarek/ApplyPilot-Enhanced

ApplyPilot Enhanced

Fork of the original ApplyPilot, kept compatible with the existing applypilot package, CLI, and applypilot init setup flow.

This fork stays general-purpose. It does not hardcode one job level or one persona. Users still configure their own search targets, filters, resume facts, and preferences through applypilot init and their generated config files.

Applied to 1,000 jobs in 2 days. Fully autonomous. Open source.

PyPI version Python 3.11+ License: AGPL-3.0 GitHub stars ko-fi

0218.mp4

Fork Notes

This repository is a maintained fork intended to keep upstream compatibility while adding practical fixes and workflow improvements. The Python package name and console command remain applypilot for compatibility, but the documentation and metadata identify this repo as ApplyPilot Enhanced.

Replace the placeholder fork metadata in pyproject.toml with your actual GitHub fork URLs before publishing.

Changes From Upstream

This fork currently includes:

  • Smarter Lensa discovery using Lensa's current search route instead of the stale /jobs?k=...&l=... pattern.
  • Lensa API pagination support so discovery can fetch more than the first 20 results per search.
  • Tighter Lensa filtering for remote relevance, salary thresholding, and stronger title matching.
  • Exceptions that keep low-salary part-time, gig, contract, fractional, and executive consulting roles when appropriate.
  • Better per-site smart-extract resilience so one timed-out site does not abort the whole discovery batch.
  • Safer Playwright collection behavior with bounded page-load/idle waits and non-fatal headful fallback.
  • Gemini CLI fixes for Windows and large prompts by sending prompt text over stdin instead of command-line args.
  • Updated Gemini tailoring default model from the stale gemini-1.5-pro to gemini-2.5-pro.
  • Cleaner Gemini error reporting so actionable failures surface instead of noisy repo-scan warnings.
  • Additional tests covering Lensa target generation, pagination, filtering, smart-extract resilience, and Gemini CLI behavior.

What It Does

ApplyPilot is a 6-stage autonomous job application pipeline. It discovers jobs across 5+ boards, scores them against your resume with AI, tailors your resume per job, writes cover letters, and submits applications for you. It navigates forms, uploads documents, answers screening questions, all hands-free.

Canonical commands are direct and discoverable.

pip install applypilot
pip install --no-deps python-jobspy && pip install pydantic tls-client requests markdownify regex
applypilot init          # one-time setup: resume, profile, preferences, API keys
applypilot doctor        # verify your setup — shows what's installed and what's missing
applypilot pipeline      # full pipeline: discover > enrich > score > tailor > cover > pdf
applypilot score         # run one stage directly
applypilot apply         # autonomous browser-driven submission
applypilot apply -w 3    # parallel apply (3 Chrome instances)
applypilot apply --dry-run  # fill forms without submitting
applypilot help          # help without needing --help

Why two install commands? python-jobspy pins an exact numpy version in its metadata that conflicts with pip's resolver, but works fine at runtime with any modern numpy. The --no-deps flag bypasses the resolver; the second command installs jobspy's actual runtime dependencies. Everything except python-jobspy installs normally.


Two Paths

Full Pipeline (recommended)

Requires: Python 3.11+, Node.js (for npx), Gemini API key (free), Claude Code CLI, Chrome

Runs all 6 stages, from job discovery to autonomous application submission. This is the full power of ApplyPilot.

Discovery + Tailoring Only

Requires: Python 3.11+, Gemini API key (free)

Runs stages 1-5: discovers jobs, scores them, tailors your resume, generates cover letters. You submit applications manually with the AI-prepared materials.


The Pipeline

Stage What Happens
1. Discover Scrapes 5 job boards (Indeed, LinkedIn, Glassdoor, ZipRecruiter, Google Jobs) + 48 Workday employer portals + 30 direct career sites
2. Enrich Fetches full job descriptions via JSON-LD, CSS selectors, or AI-powered extraction
3. Score AI rates every job 1-10 based on your resume and preferences. Only high-fit jobs proceed
4. Tailor AI rewrites your resume per job: reorganizes, emphasizes relevant experience, adds keywords. Never fabricates
5. Cover Letter AI generates a targeted cover letter per job
6. Auto-Apply Claude Code navigates application forms, fills fields, uploads documents, answers questions, and submits

Each stage is independent. Run them all or pick what you need.


ApplyPilot vs The Alternatives

Feature ApplyPilot AIHawk Manual
Job discovery 5 boards + Workday + direct sites LinkedIn only One board at a time
AI scoring 1-10 fit score per job Basic filtering Your gut feeling
Resume tailoring Per-job AI rewrite Template-based Hours per application
Auto-apply Full form navigation + submission LinkedIn Easy Apply only Click, type, repeat
Supported sites Indeed, LinkedIn, Glassdoor, ZipRecruiter, Google Jobs, 46 Workday portals, 28 direct sites LinkedIn Whatever you open
License AGPL-3.0 MIT N/A

Requirements

Component Required For Details
Python 3.11+ Everything Core runtime
Node.js 18+ Auto-apply Needed for npx to run Playwright MCP server
Gemini API key Scoring, tailoring, cover letters Free tier (15 RPM / 1M tokens/day) is enough
Chrome/Chromium Auto-apply Auto-detected on most systems
Claude Code CLI Auto-apply Install from claude.ai/code

Gemini API key is free. Get one at aistudio.google.com. OpenAI and local models (Ollama/llama.cpp) are also supported.

Optional

Component What It Does
CapSolver API key Solves CAPTCHAs during auto-apply (hCaptcha, reCAPTCHA, Turnstile, FunCaptcha). Without it, CAPTCHA-blocked applications just fail gracefully

Note: python-jobspy is installed separately with --no-deps because it pins an exact numpy version in its metadata that conflicts with pip's resolver. It works fine with modern numpy at runtime.


Configuration

All generated by applypilot init:

profile.json

Your personal data in one structured file: contact info, work authorization, compensation, experience, skills, resume facts (preserved during tailoring), and EEO defaults. Powers scoring, tailoring, and form auto-fill.

searches.yaml

Job search queries, target titles, locations, boards. Run multiple searches with different parameters.

.env

Runtime config: LLM_PROVIDER, LLM_MODEL (provider-specific model override), CAPSOLVER_API_KEY (optional CAPTCHA solving).

Package configs (shipped with ApplyPilot)

  • config/employers.yaml - Workday employer registry (48 preconfigured)
  • config/sites.yaml - Direct career sites (30+), blocked sites, base URLs, manual ATS domains
  • config/searches.example.yaml - Example search configuration

How Stages Work

Discover

Queries Indeed, LinkedIn, Glassdoor, ZipRecruiter, Google Jobs via JobSpy. Scrapes 48 Workday employer portals (configurable in employers.yaml). Hits 30 direct career sites with custom extractors. Deduplicates by URL.

Enrich

Visits each job URL and extracts the full description. 3-tier cascade: JSON-LD structured data, then CSS selector patterns, then AI-powered extraction for unknown layouts.

Score

AI scores every job 1-10 against your profile. 9-10 = strong match, 7-8 = good, 5-6 = moderate, 1-4 = skip. Only jobs above your threshold proceed to tailoring.

Tailor

Generates a custom resume per job: reorders experience, emphasizes relevant skills, incorporates keywords from the job description. Your resume_facts (companies, projects, metrics) are preserved exactly. The AI reorganizes but never fabricates.

Cover Letter

Writes a targeted cover letter per job referencing the specific company, role, and how your experience maps to their requirements.

Auto-Apply

Claude Code launches a Chrome instance, navigates to each application page, detects the form type, fills personal information and work history, uploads the tailored resume and cover letter, answers screening questions with AI, and submits. A live dashboard shows progress in real-time.

The Playwright MCP server is configured automatically at runtime per worker. No manual MCP setup needed.

# Utility modes (no Chrome/Claude needed)
applypilot mark applied --url URL      # manually mark a job as applied
applypilot mark failed --url URL       # manually mark a job as failed
applypilot reset failed                # reset all failed jobs for retry
applypilot remove expired              # delete expired jobs from the database
applypilot reset in-progress           # clear stale in-progress locks
applypilot apply --gen --url URL       # generate prompt file for manual debugging

CLI Reference

applypilot init                         # First-time setup wizard
applypilot doctor                       # Verify setup, diagnose missing requirements
applypilot help                         # Show canonical help without requiring --help
applypilot pipeline                     # Run the full pipeline
applypilot pipeline run discover score  # Run only selected stages
applypilot discover                     # Run a single stage directly
applypilot score --llm openai           # Override provider for a single LLM-backed stage
applypilot tailor --llm gemini --llm-model gemini-2.5-pro
                                        # Direct stage command with standardized LLM flags
applypilot pipeline --workers 4         # Parallel discovery/enrichment
applypilot pipeline --stream            # Concurrent stages (streaming mode)
applypilot pipeline --min-score 8       # Override score threshold
applypilot pipeline --dry-run           # Preview without executing
applypilot pipeline run enrich score tailor --show-browser
                                        # Non-headless pipeline path into tailor (shows browser during enrich)
applypilot pipeline --validation lenient
                                        # Relax validation (recommended for Gemini free tier)
applypilot pipeline --validation strict # Strictest validation (retries on any banned word)
applypilot pipeline run enrich --reset-enrich-errors
                                        # Clear failed enrich attempts, then retry enrichment
applypilot run score tailor cover --llm openai
                                        # Legacy compatibility alias; prefer `applypilot pipeline run ...`
applypilot resume                       # Resume the last saved session (pipeline/apply)
applypilot apply                        # Launch auto-apply
applypilot apply --workers 3            # Parallel browser workers
applypilot apply --dry-run              # Fill forms without submitting
applypilot apply --continuous           # Run forever, polling for new jobs
applypilot apply --headless             # Headless browser mode
applypilot apply --llm claude --llm-model haiku
                                        # Auto-apply currently supports Claude-only provider/model overrides
applypilot apply --live-chrome-profile --chrome-profile-directory "Profile 1"
                                        # Reuse your signed-in Chrome profile
applypilot apply --live-chrome-profile --live-profile-fallback
                                        # If live profile fails, fallback to worker clone
applypilot apply --close-all-chrome     # Prompt, then close running Chrome before apply
applypilot apply --url URL              # Apply to a specific job
applypilot export ready-jobs            # Export ready manual-apply work to an .xlsx workbook
applypilot export ready-jobs --output exports/ready.xlsx
                                        # Curated ready_to_apply tab + raw_ready_jobs tab
applypilot mark applied --url URL       # Canonical utility command: mark applied
applypilot mark failed --url URL --reason "captcha"
                                        # Canonical utility command: mark failed with reason
applypilot reset failed                 # Canonical utility command: reset failed jobs
applypilot remove expired               # Canonical utility command: delete expired jobs from DB
applypilot reset in-progress            # Canonical utility command: clear stale in-progress locks
applypilot apply --gen --url URL        # Utility mode: generate manual-debug prompt file
applypilot status                       # Pipeline statistics
applypilot dashboard                    # Open HTML results dashboard

applypilot export ready-jobs does not require a cover letter. Any job with a tailored resume that is not already applied is eligible for export, and the workbook always includes both a curated ready_to_apply sheet and a raw_ready_jobs sheet.


Privacy And Publishing

Do not publish or commit any of the following:

  • ~/.applypilot/ contents such as profile.json, searches.yaml, resume.txt, resume.pdf, applypilot.db, tailored resumes, cover letters, and session state
  • .env files containing API keys or provider settings
  • browser profile data, Chrome worker state, or machine-specific MCP configs
  • generated prompt files, logs, screenshots, or debug artifacts that may contain personal resume data, job history, or secrets

This repository should only contain code, tests, templates, and scrubbed documentation. Keep all personal search criteria, compensation preferences, authorization answers, and API credentials out of version control.


Contributing

See CONTRIBUTING.md for development setup, coding standards, and PR guidelines.


License

ApplyPilot is licensed under the GNU Affero General Public License v3.0.

You are free to use, modify, and distribute this software. If you deploy a modified version as a service, you must release your source code under the same license.

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ApplyPilot Enhanced fork of Pickle-Pixel/ApplyPilot

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