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FitQuest Backend
Fitness & NutritionC# / .NET 10MIT

FitQuest Backend Review

A .NET 10 / ASP.NET Core backend API for AI-generated workout plans, nutrition advice, session logging, and daily check-ins.

Deployability
3/5
Value
3/5
Privacy
3/5
View source

Each review covers deployability, value versus commercial alternatives, and privacy model. Tools that can run locally were started and exercised; mobile or backend-dependent tools were assessed from published builds, source code, and deploy guides. Ratings reflect what we were able to verify.

FitQuest Backend — AI Fitness Coaching API

A .NET 10 / ASP.NET Core backend API for AI-generated workout plans, nutrition advice, session logging, and daily check-ins. Last updated: 2026-06-21.

One-sentence verdict: A clean, modern fitness backend API with a two-agent reasoning pipeline, useful as a foundation for a fitness coaching product.

What the System Is

FitQuest Backend is an ASP.NET Core REST API. It is built as:

  • .NET 10 / ASP.NET Core runtime.
  • Entity Framework Core for data access.
  • SQLite in development, PostgreSQL / Supabase in production.
  • JWT Bearer tokens for authentication.
  • Azure AI Foundry or DeepSeek AI for AI features (auto-detected from base URL).
  • Two-agent reasoning pipeline: Training Plan Agent and Nutrition Agent.

Endpoints cover registration/login, user profile, AI plan generation and adjustment, training session logging, daily check-ins, weekly plan, nutrition advice, and training stats.

Key data
Category Fitness & Nutrition
Language C# / .NET 10
License MIT
Self-hosted Yes
AI Azure AI Foundry or DeepSeek AI
Database SQLite (dev) / PostgreSQL (prod)
Deployment Docker Compose

How to Install and Deploy

The deploy guide uses Docker Compose and remaps the host port to 8086.

cd /data2/docker/going-global/repos/fitquest-backend
cp .env.example .env

# Edit .env:
#   PORT=8086 (container internal port remains 8080)
#   DATABASE_PROVIDER=sqlite
#   DATABASE_URL=Data Source=/app/data/fitness.db
#   AI_API_KEY=dummy (AI features are disabled without a real key, but the API still starts)
#   FRONTEND_ORIGINS=http://localhost:8086

# Avoid port conflicts
sed -i 's/"8080:8080"/"8086:8080"/' docker-compose.yml

# Optional: avoid compose validation failure
 echo "CLOUDFLARE_TUNNEL_TOKEN=dummy" >> .env

docker compose up -d api

Then the API is available at http://localhost:8086.

How to Test

The documented test flow is:

  1. Register a user via POST /api/auth/register.
  2. Log in via POST /api/auth/login to receive a JWT.
  3. Call GET /api/me with the Authorization: Bearer <token> header.
  4. Test POST /api/plan/generate and GET /api/nutrition with a real AI key.
  5. Log a training session via POST /api/training-sessions and view history.
  6. Submit a daily check-in via POST /api/checkin.

Privacy & Compliance

FitQuest Backend stores data locally when using SQLite, but AI plan and nutrition endpoints send user profile and activity data to Azure AI Foundry or DeepSeek. It is not HIPAA compliant and is intended for consumer fitness use.

FitQuest Backend vs Commercial Fitness Coaching APIs

Dimension FitQuest Backend Commercial Fitness API / App (e.g., Trainerize, Future)
Cost Free / self-hosted Subscription / per-user
Data location Your server + AI provider cloud Vendor cloud
AI provider choice Azure AI Foundry or DeepSeek Vendor-managed
Frontend Not included (backend only) Bundled native/Web app
Setup effort Medium: Docker Compose, .env, AI key Low: sign up
Multi-agent reasoning Two-agent plan + nutrition chain Varies
Open source Yes No

Who Should Use It

  • Developers building a fitness coaching product who need a backend scaffold.
  • Teams that want .NET 10 + JWT + SQLite/PostgreSQL with AI plan generation.
  • Builders comfortable with Azure AI Foundry or DeepSeek integration.

Who Shouldn't Use It

  • End users looking for a finished app; this is a backend API only.
  • Teams needing a polished mobile or web frontend out of the box.
  • Anyone needing clinical-grade fitness or nutrition advice.

FAQ

Is there a frontend for FitQuest Backend?

This repository is the backend API only. A separate fitquest-frontend project exists, but the deploy guide focuses on the backend.

Can I run it without an AI key?

Yes. The API starts with a dummy key, but AI plan generation and nutrition advice require a real Azure AI Foundry or DeepSeek key.

What database does it use?

SQLite in development and PostgreSQL / Supabase in production. The schema is created automatically on startup.

Verdict

FitQuest Backend is a well-structured fitness API with a clear separation of auth, planning, sessions, and nutrition. The two-agent reasoning chain is a nice architectural touch. It is a backend-only project, so it is best viewed as a foundation rather than a finished product.

Ratings: Deployability 3/5 · Value vs Commercial 3/5 · Privacy Compliance 3/5