Carbon AI Job Scheduler is an intelligent task scheduling system that optimizes computing workloads to minimize carbon emissions. By leveraging real-time carbon intensity data and multiple AI services, it provides smart scheduling recommendations and detailed environmental impact analysis for resource-intensive computing tasks.
- Dark/Light Mode Toggle
- Seamless theme switching
- System preference detection
- Persistent theme selection
- Material UI theme customization
-
Jobs Dashboard
- Real-time job queue management
- Task status monitoring
- Cancel/Clear job operations
- Job details and insights display
-
Analytics Dashboard
- Carbon intensity trends
- Savings visualization
- Historical data analysis
- Interactive charts and graphs
-
Task Scheduling
- Intuitive task submission form
- Resource usage specification
- Duration and priority settings
- Immediate scheduling feedback
-
Intelligent Task Scheduling
- Real-time carbon intensity monitoring
- AI-powered scheduling recommendations
- Priority-based task queuing
- Dependency management for complex workflows
-
Environmental Impact Analysis
- Real-time carbon intensity tracking
- Projected carbon savings calculations
- Cost savings estimates
- Alternative scheduling windows
-
Advanced Analytics
- Interactive data visualization
- Historical trend analysis
- Carbon impact forecasting
- Resource usage optimization
-
Robust Architecture
- RESTful API endpoints
- WebSocket real-time updates
- Database persistence
- Error handling and fallbacks
-
Core
- React.js
- Material-UI (MUI)
- Emotion for styled components
- Framer Motion for animations
-
Data Visualization
- Recharts
- Date-fns for time manipulation
-
Core Framework
- FastAPI
- Uvicorn ASGI server
- Pydantic for data validation
-
Database
- SQLAlchemy ORM
- PostgreSQL
- Alembic for migrations
-
AI/ML Integration
- OpenAI API client
- Groq API integration
- Perplexity AI
-
WattTime API
- Real-time grid carbon intensity
- Regional power grid data
- Historical emissions data
-
Groq API
- LLM inference
- Task analysis
- Scheduling optimization
-
Perplexity AI
- Dynamic insights generation
- Environmental impact analysis
- Resource optimization recommendations
-
Version Control
- Git
- GitHub
-
Development
- Python 3.11
- Node.js
- npm/yarn
- Clone the Repository
git clone https://github.com/yourusername/carbon-ai-job-scheduler.git
cd carbon-ai-job-scheduler- Backend Setup
cd backend
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
# Configure environment variables
cp .env.example .env
# Add your API keys:
# PERPLEXITY_API_KEY=
# GROQ_API_KEY=
# WATTTIME_USERNAME=
# WATTTIME_PASSWORD=
# Initialize database
alembic upgrade head
# Start the backend server
uvicorn main:app --reload- Frontend Setup
cd frontend
npm install
npm startThe application supports both light and dark modes, with smooth transitions between themes. Users can:
- Toggle between light and dark mode
- System theme detection
-
Jobs Tab
- View all scheduled tasks
- Monitor job status in real-time
- Cancel running jobs
- Clear completed tasks
- View detailed job insights
-
Analytics Tab
- Carbon intensity graphs
- Cost savings metrics
- Environmental impact scores
- Resource utilization charts
- Historical trend analysis
-
Schedule Tab
- Task submission interface
- Resource specification
- Priority selection
- Duration setting
- Real-time scheduling recommendations
This project is licensed under the MIT License - see the LICENSE file for details.
- WattTime for providing carbon intensity data
- Groq for AI inference capabilities
- Perplexity AI for insights generation
- The open-source community
Made with 💚 for a greener computing future