WorkBento - Python HR and Payroll Platform

WorkBento is a self-hosted HR and workplace application with people management, attendance, leave, payroll, recruitment, projects and CRM. An optional AI assistant works with company data. The package includes editable Python and web application source, a Docker Compose stack and installation documentation.

Features

• AI assistant (optional)
  • Plain-English questions about people, leave, attendance, payroll, recruitment, projects and CRM.
  • Answers with tables, totals and quick-access buttons.
  • Permission-aware and runs on a read-only guarded SQL layer.
  • A server-side model allowlist; any OpenRouter model.
• People: employees, departments, positions, org chart, and contracts with base salary or salary grades.
• Time & leave: self check-in and check-out, attendance logs, timesheets, shifts, leave types and balances, and requests with team approvals.
• Payroll:
  • Periods calculated from contracts, attendance, approved leave, overtime, insurance and advances.
  • Payslips, adjustments and CSV export.
• Talent: job requisitions, a candidate pipeline with interviews, one-click hiring, onboarding, training, performance reviews, KPIs, OKRs, and rewards and discipline.
• Work: projects, tasks with workflow history, calendar, intranet, incoming, outgoing and internal documents, internal document sign-off with an audit trail, and company assets.
• CRM: leads with conversion, opportunities with pipeline value, customers, and orders with order lines.
• Administration: 4 system roles plus custom roles with a permission matrix, user management, and workspace locale, timezone, currency and date format.
• Security:
  • Argon2id passwords.
  • Instant session revocation.
  • Login lockout.
  • Every query is scoped to the workspace.
  • API docs are off in production.
• Ready to run:
  • Docker Compose stack and a secure setup script.
  • Demo-data seeder and a self-resetting public demo kit.
  • HTTPS setups for Caddy, Nginx and Cloudflare.
  • A backup script and 625 automated tests.

Requirements

• Docker Engine 24+ with Docker Compose v2.24+
• 4 CPU cores, 8 GB RAM, 20 GB free disk (Linux server recommended for production)
• Optional: an OpenRouter API key for the AI assistant
• A modern browser (Chrome, Edge, Firefox, Safari)

Instructions

1. Unzip the package.
2. Run sh scripts/setup.sh. It creates .env with unique secrets and a random administrator password, and prints the password.
3. Run docker compose up -d --build.
4. Open and sign in as the administrator.
5. Optional: to load the demo company, add DEMO_PASSWORD to .env and run sh scripts/demo_reset.sh.
6. Optional: to enable the AI assistant, add OPENROUTER_API_KEY to .env and run docker compose up -d.
7. For a public server with HTTPS, backups and upgrades, follow docs/DEPLOYMENT.md.

README.md and the docs/ folder cover installation, security, roles and permissions, the API reference and the AI assistant.