karlomikus

karlomikus/bar-assistant

PHP MIT Productivity

Bar assistant is a all-in-one solution for managing your home bar

1.1k stars
45 forks
active
GitHub +5 / week

1.1k

Stars

45

Forks

29

Open issues

9

Contributors

v5.15.3 09 Jul 2026

AI Analysis

Bar Assistant is a self-hosted API server and platform specifically designed for managing home bar cocktail recipes and inventory. It serves bartenders, cocktail enthusiasts, and home bar owners who need structured recipe management with cocktail-specific features like ABV calculations, ingredient substitutes, and shopping list generation. This is not a general recipe manager—it's built exclusively for cocktails and is not suitable for broader culinary use cases.

Productivity Application Discovery value: 6/10
Documentation 8/10
Activity 9/10
Community 7/10
Code quality 7/10

Inferred from signals mentioned in the README (tests, CI, type safety) — not a review of the actual code.

Overall score 8/10

AI's overall editorial judgment — not an average of the bars above, can weigh other factors too.

cocktail-recipes home-bar-management recipe-api self-hosted inventory-management
Actively maintained Well documented MIT licensed Niche/specialized use case Beginner friendly Production ready
Deep Analysis · Based on README and public signals
1w ago

Self-hosted cocktail recipe manager with multi-bar support and ingredient inventory tracking

Bar Assistant is a purpose-built API server for managing home bar operations, including cocktail recipes, ingredient inventories, shopping lists, and pricing. Built in PHP with a companion Vue frontend (Salt Rim), it targets home bartenders and small bar operators who want centralized recipe and inventory management. The project includes 500+ pre-loaded cocktail recipes and supports features like ABV calculations, ingredient substitutes, and user role-based access control.

Origin

Created in October 2022, Bar Assistant emerged as a specialist solution after observing that general recipe management tools lacked cocktail-specific features like ABV tracking, ingredient substitution, and glass/utensil taxonomy. The project is maintained by a single author (karlomikus) with a small contributor base.

Growth

The project has grown modestly and steadily from launch to mid-2026, reaching ~1,000 stars over 3.75 years. Recent activity shows 3 stars gained in the last 7 days (as of 2026-06-23), suggesting slow but consistent organic adoption. Docker pull metrics appear publicly but specific numbers are not disclosed in the README. The project maintains a managed cloud offering alongside the open-source version, indicating a sustainable revenue model.

In production

Adoption not verified with concrete numbers, but several signals suggest real-world use: (1) maintained Docker images on Docker Hub and GHCR with semantic versioning strategy, (2) official managed SaaS offering at barassistant.app, (3) community extension (Raycast) created by independent user, (4) documentation site maintained, (5) pre-populated dataset of 500+ recipes and 250+ ingredients suggests users expect out-of-box functionality. Docker pull counts exist but are not disclosed in README excerpt, preventing quantitative adoption assessment.

Code analysis
Architecture

Appears to be a Laravel-based PHP API server with Redis for caching and sessions, optional Meilisearch for full-text indexing, and Docker deployment as a first-class concern. The README documents extensive environment variable configuration for email, authentication, AI provider integration, and metrics. Likely uses a relational database backend (not explicitly named in excerpt). Architecture supports multi-tenancy (multiple bars, user roles, SSO).

Tests

README includes a GitHub Actions badge showing test status on the master branch, indicating continuous integration is active. Specific coverage percentages or test framework details are not documented in the truncated README.

Maintenance

Last push was 2026-06-23 (9 days before evaluation date), indicating active ongoing maintenance. The project has been continuously developed for 3.75 years without abandonment. Presence of recent environment variable documentation for LLM integration and Prometheus metrics suggests active feature development. Small fork count (45) and modest star velocity do not indicate stagnation but rather narrow, stable user base.

Honest verdict

ADOPT IF: you self-host, manage a home bar or small cocktail venue, want feature-rich inventory and recipe management, and prefer open-source tooling. AVOID IF: you need enterprise multi-location support, require extensive third-party integrations beyond SSO/email, or demand a proven large-scale user base. MONITOR IF: you are evaluating whether the managed cloud offering represents sustainable long-term maintenance, or if community adoption will expand the ecosystem of integrations and extensions.

Independent dimensions

Mainstream potential

3/10

Technical importance

5/10

Adoption evidence

4/10

Risks
  • Single-author maintenance creates bus factor risk; no evidence of established succession plan or large maintainer team.
  • Adoption limited to niche vertical (home bartenders + small bar operators); mainstream expansion into general recipe management is unlikely given explicit design choices against it.
  • Docker dependency and Redis/Meilisearch optional components add deployment complexity compared to simpler self-hosted tools.
  • No evidence of large-scale production deployments at bars/venues; primary users appear to be hobbyists. Unknown whether feature set meets professional POS/inventory needs.
  • LLM integration and AI features (referenced in environment variables) are recent additions; stability and utility of these features not yet established.
Prediction

Bar Assistant will likely remain a stable, well-maintained niche tool for home bartenders and small operators over the next 2–3 years. The project has found sustainable fit via a freemium SaaS model, reducing risk of abandonment. Growth will probably remain slow (single-digit percentage annually) unless the project actively markets to bars/venues or expands into adjacent verticals (e.g., general beverage management). Community extensions (like Raycast) may slowly accumulate but are unlikely to drive mainstream visibility.

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Languages

PHP
99.5%
Blade
0.4%
Dockerfile
0.1%

Information

Language
PHP
License
MIT
Last updated
17h ago
Created
46mo ago
Analyzed with
anthropic/claude-haiku-4-5

Stars over time

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Contributors over time

Top 100 contributors only — repos with more will plateau at 100.

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vs. alternatives
Saloon (PHP, 2,417 stars)

Saloon is a PHP HTTP client library for APIs; fundamentally different problem domain. Not a competitor.

Applite (Swift, 6,821 stars)

Applite is a macOS app wrapper for package managers. Not a competitor in the cocktail/recipe management space.

Part-DB (PHP, 1,664 stars)

Part-DB is an inventory management system for electronic components. Shares similar multi-tenancy and inventory concepts but serves a different vertical (electronics vs. bartending). Bar Assistant is purpose-built for cocktails; Part-DB is generic inventory.

Music Assistant (Python, 2,787 stars)

Music Assistant is a home music management platform. Serves parallel niche (home automation/media) with similar self-hosted and community-driven positioning, but entirely different domain.

General recipe apps (e.g., Cooklist, Bevy, Drinkify — not in repo list)

Bar Assistant explicitly positions itself as cocktail-specific, not general-purpose. Lacks direct open-source competitor of similar maturity in the README-provided similar projects list. Likely serves a narrower user base than general recipe managers, which is by design.