An AI-powered, fullstack task manager with real-time UI and observability — built for real-world software teams.

SprintSync - AI-Powered Task Management

A production-ready task management system built with FastAPI, HTMX, and Google Gemini AI. Deployed on Railway with full observability and comprehensive testing.

Live Demo

Deployed Application: SprintSync on Railway

Demo Access:

• Admin User: admin / admin123 (Full system overview, user management, analytics)
• Regular Users: user1, user2, user3 / password123 (Personal task management)

What I Built

SprintSync is a task management system with AI integration, real-time updates, and admin features.

Key Features:

• Real-time UI with HTMX for seamless interactions
• AI-powered task generation using Google Gemini
• Production deployment with monitoring and logging
• Comprehensive testing with full API coverage
• Admin dashboard with system analytics
• Secure authentication with JWT and role-based access

Architecture

See docs/ARCHITECTURE.md for detailed system design and technical decisions.

Tech Stack: FastAPI, PostgreSQL, HTMX, Google Gemini, Railway

Quick Start

# Clone and setup
git clone https://github.com/basedavishkar/SprintSync
cd SprintSync
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Setup environment
cp env.example .env
# Add your GEMINI_API_KEY to .env

# Database setup
alembic upgrade head
python -m app.seed_data

# Run development server
uvicorn app.main:app --reload

Features

• Task Management: Create, update, delete, and track task status
• Real-time Updates: HTMX-powered dynamic UI without page refreshes
• AI Integration: Generate task descriptions and daily plans with Google Gemini
• User Authentication: Secure JWT-based authentication with role-based access
• Admin Dashboard: System overview, user management, completion analytics
• Production Ready: Structured logging, health checks, error handling

API

See docs/API.md for complete API documentation and examples.

Testing

# Run all tests
pytest

Test Coverage: Comprehensive API testing with edge cases

Monitoring

• Prometheus Metrics: Request counts, error rates, response times
• Structured Logging: Per-request logging with correlation IDs
• Health Checks: Application health monitoring

Development

# Database migrations
alembic revision --autogenerate -m "description"
alembic upgrade head

# Seed database
python -m app.seed_data

Technology Choices

See docs/DECISIONS.md for detailed reasoning behind each technology choice and architectural decision.

Conclusion

Deployed and ready for use.

Repository: https://github.com/basedavishkar/SprintSync

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Built with FastAPI, HTMX, Google Gemini, and Swagger UI