TaskPilot API

TaskPilot API is the robust backend service for the TaskPilot project management application. Built with modern Python technologies, it provides a scalable foundation for managing workspaces, projects, tasks, and real-time team collaboration.

🚀 Key Features

• 🔐 Secure Authentication: Full JWT-based generic authentication system with secure password hashing.
• 🏢 Workspace Management: Multi-tenant architecture allowing users to create and manage isolated workspaces.
• 📊 Project & Task Tracking: Comprehensive project lifecycles with granular task management (status updates, priorities, assignments).
• 💬 Collaboration Tools: Real-time commenting system on tasks to facilitate team communication.
• 🤖 Context-Aware AI: Integrated DeepSeek AI assistant that understands your project context (tasks, deadlines, members) to provide intelligent suggestions.
• 📜 Activity Logging: Detailed audit trails for all user actions within workspaces and projects.
• 🛡️ Role-Based Access Control: Granular permission systems for workspace members (Admins, Members, etc.).

🛠️ Tech Stack

• Language: Python 3.10+
• Web Framework: FastAPI - High-performance, easy-to-learn, fast-to-code, ready-for-production.
• Database: PostgreSQL - The world's most advanced open source relational database.
• ORM: SQLAlchemy (Async) - The Python SQL Toolkit and Object Relational Mapper.
• Migrations: Alembic - A lightweight database migration tool for usage with SQLAlchemy.
• Caching: Redis - In-memory data store for caching and message brokerage.
• Async Tasks: Celery - Distributed task queue for handling background jobs (emails, AI processing).
• Containerization: Docker & Docker Compose - For consistent development and deployment environments.

📂 Detailed File Structure

taskpilot-api/
├── alembic/                # Database migration scripts and revisions
├── app/
│   ├── api/
│   │   └── v1/             # API Version 1 endpoints
│   │       ├── routes_auth.py          # Login, Register, Refresh Token
│   │       ├── routes_users.py         # User profile management
│   │       ├── routes_workspaces.py    # Workspace CRUD & settings
│   │       ├── routes_workspace_members.py # Member management
│   │       ├── routes_projects.py      # Project creation & tracking
│   │       ├── routes_tasks.py         # Task assignment & status
│   │       ├── routes_comments.py      # Task comments
│   │       ├── routes_activity_logs.py # User activity history
│   │       └── routes_ai.py            # AI assistant endpoints
│   ├── core/               # Application capability configuration
│   │   ├── config.py           # Environment variables (Pydantic BaseSettings)
│   │   ├── security.py         # JWT handling & Password hashing
│   │   └── logging_config.py   # Structured logging setup
│   ├── db/                 # Database layer
│   │   ├── session.py          # Async session factory
│   │   ├── base.py             # SQLAlchemy Declarative Base
│   │   └── init_db.py          # Initial data seeding script
│   ├── models/             # SQLAlchemy Database Tables
│   │   ├── user.py
│   │   ├── workspace.py
│   │   ├── project.py
│   │   ├── task.py
│   │   ├── comment.py
│   │   ├── activity_log.py
│   │   └── ai_request.py
│   ├── schemas/            # Pydantic Models (Data Transfer Objects)
│   │   ├── user_schema.py
│   │   ├── task_schema.py
│   │   ├── project_schema.py
│   │   └── ...
│   ├── services/           # Business Logic Layer
│   │   ├── ai_service.py       # AI Context & DeepSeek integration
│   │   ├── project_service.py  # Project-related logic
│   │   ├── task_service.py     # Complex task operations
│   │   └── deepseek_client.py  # External AI API client
│   ├── tasks/              # Celery Background Tasks
│   │   ├── ai_tasks.py         # Async AI processing
│   │   └── email_tasks.py      # Async email notifications
│   ├── utils/              # Shared Utilities
│   ├── celery_app.py       # Celery application configuration
│   └── main.py             # Application entrypoint & middleware
├── docker-compose.yml      # Orchestration for API, DB, and Redis
├── Dockerfile              # Production-ready Docker image
└── requirements.txt        # Python dependencies

⚡ Getting Started

Prerequisites

• Docker and Docker Compose installed (recommended).
• (Optional) Python 3.10+ and PostgreSQL for local setup.

🐳 Running with Docker (Quickstart)

1. Clone the repository:

   git clone <repository_url>
   cd taskpilot-api

2. Environment Setup: Create a .env file in the root directory (copy the example structure below).

3. Start the Stack:

   docker-compose up --build

   This spins up:

   • API Service: http://localhost:8000
   • PostgreSQL: Port 5432
   • Redis: Port 6379

4. Explore the API: Open your browser to http://localhost:8000/docs for the interactive Swagger UI.

💻 Local Development (Manual)

1. Set up Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # Windows: venv\Scripts\activate

2. Install Dependencies:

   pip install -r requirements.txt

3. Start Logic Dependencies: Use Docker to run just the DB and Cache:

   docker-compose up db redis -d

4. Apply Migrations:

   alembic upgrade head

5. Run API:

   uvicorn app.main:app --reload

⚙️ Configuration

Create a .env file in the root directory.

# --- Security ---
SECRET_KEY=change_this_to_a_secure_random_string
ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=60

# --- Database ---
# Local execution:
DATABASE_URL=postgresql+asyncpg://postgres:password@localhost:5432/taskpilot
# Docker execution (service name 'db'):
# DATABASE_URL=postgresql+asyncpg://postgres:password@db:5432/taskpilot

# --- Redis ---
# Local execution:
REDIS_URL=redis://localhost:6379/0
# Docker execution (service name 'redis'):
# REDIS_URL=redis://redis:6379/0

# --- AI Integration (DeepSeek) ---
DEEPSEEK_API_KEY=your_deepseek_api_key_here
//v1

🤝 Contributing

1. Fork the project.
2. Create your feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the feature branch (git push origin feature/AmazingFeature).
5. Open a Pull Request.