https://github.com/rfivesix/train-libre
Private workout and nutrition tracking for Android & iOS
https://github.com/rfivesix/train-libre
ai android bodybuilding calorie-calculator calories calories-calculator calories-tracker dart fitness flutter gym health healthcare-ai healthkit ios nutrition nutrition-tracker offline-first workout workout-tracker
Last synced: 25 days ago
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Private workout and nutrition tracking for Android & iOS
- Host: GitHub
- URL: https://github.com/rfivesix/train-libre
- Owner: rfivesix
- License: gpl-3.0
- Created: 2025-09-15T13:38:47.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2026-06-09T14:01:08.000Z (25 days ago)
- Last Synced: 2026-06-09T14:20:51.515Z (25 days ago)
- Topics: ai, android, bodybuilding, calorie-calculator, calories, calories-calculator, calories-tracker, dart, fitness, flutter, gym, health, healthcare-ai, healthkit, ios, nutrition, nutrition-tracker, offline-first, workout, workout-tracker
- Language: Dart
- Homepage: https://rfivesix.github.io/train-libre/
- Size: 160 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Roadmap: ROADMAP.md
Awesome Lists containing this project
README
# Train Libre
**Private workout and nutrition tracking for Android and iOS.**
Train Libre is an open-source, offline-first fitness app for logging workouts, calories, macros, bodyweight, and recovery — without ads, mandatory accounts, or analytics SDKs.
Designed for people who want serious tracking without social feeds, gamification, or subscription pressure, Train Libre prioritizes **privacy**, **local data ownership**, and **transparent analytics**.
## Download & Install
iOS Public TestFlight Beta
Android (via Obtainium)
*Google Play release is currently not available.*
## Platform Support
Train Libre is built with Flutter and supports:
- **iOS** (Active)
- **Android** (Active)
## Key Features
- **Workout Tracker:** Log sets (warm-up, failure, dropsets), routines, and session history.
- **Calorie & Macro Tracker:** Track nutrition, hydration, and supplements with adaptive weekly guidance.
- **Bodyweight & Recovery Analytics:** Deep insights into muscle readiness, volume trends, and body measurements.
- **Next-Gen AI Meal Capture:** Capture meals from photos or text via BYOK (Bring Your Own Key) setup. Fully integrated with a holistic culinary anchor (`mealContext`) and a state-aware "Top-N Fuzzy Alternatives" SQLite matching system that prevents hallucinations. Always reviewable and self-repairing before saving.
- **Privacy & Local-First:** Data stays on device. Optional one-way health export to Apple Health and Google Health Connect.
## Privacy & Philosophy
- **No Ads. No Mandatory Account. No Analytics SDKs.**
- **Offline-First:** Your data stays local unless you explicitly choose otherwise.
- **Open-Source Transparency:** Trust through public code and understandable data flows.
- **User-Controlled AI:** Optional AI features require your own API key; no data is sent to providers without opt-in.
## Documentation
This project features a comprehensive, modular documentation suite split by target audience and component. Use the links below to access the technical resources:
### Developer Resources
* [Developer Overview](documentation/developer/overview.md): Technical vision, key architectural pillars, technology stack, and testing philosophy.
* [Architecture & SQLite Lifecycle](documentation/developer/architecture.md): Clean Architecture layering and database connection lifecycle pattern.
* [Data Flow & State Lifecycle](documentation/developer/data_flow_and_state.md): Reactive reads, imperative writes, subscription cancellation, and UI concurrency guards.
### Advanced Features & Algorithmic Transparency
* [Smart Features Overview](documentation/features/overview.md): Overview of algorithmic features and architectural privacy invariants.
* [Bayesian TDEE Estimator](documentation/features/bayesian_tdee_estimator.md): Comprehensive mathematical and statistical formulation of the Kalman filter-based adaptive energy expenditure engine.
* [BYOK AI Meal Validation](documentation/features/byok_ai_validation.md): AI meal capture pipeline details, fuzzy validation scoring, and the 3-pass self-repair verification loop.
* [One-Way Health Sync & Export](documentation/features/health_sync_export.md): Data export pipelines, SQLite-backed idempotency tracking, step segment merging policies, and fault-tolerance patterns.
For the full interlinked documentation map, see the main [Documentation Entry Point](documentation/README.md).
## Roadmap
The long-term vision, future modules, and planned features are maintained in the [ROADMAP.md](ROADMAP.md) file.
## Credits
- **[Open Food Facts](https://openfoodfacts.org/)** for food database coverage.
- **[wger](https://github.com/wger-project/wger)** for the workout database foundation.
## License
[GPL-3.0](LICENSE)