AutoMagik Spark - Automagion Engine with LangFlow integration
Project description
AutoMagik Spark
**Because magic shouldn't be complicated. **
AutoMagik Spark is an automagion engine that seamlessly integrates with multiple LangFlow instances. Deploy AI-driven flows, schedule one-time or recurring tasks, and monitor everything with minimal fuss—no coding required.
🔗 Ecosystem
- AutoMagik Agents: Develop production-level AI agents
- AutoMagik UI: Create agents using natural language with our dedicated UI
🚀 Installation
AutoMagik Spark provides two setup options:
Prerequisites
- Linux-based system (Ubuntu/Debian recommended)
- Docker and Docker Compose (automatically installed on Ubuntu/Debian if not present)
Local Production Setup
For a production-ready local environment:
./scripts/setup_local.sh
Development Setup
For development with PostgreSQL and Redis Docker containers:
./scripts/setup_dev.sh
What Happens During Setup
Both setup scripts will:
- Create necessary environment files
- Install Docker if needed (on Ubuntu/Debian)
- Set up all required services
- Install the CLI tool (optional)
- Guide you through the entire process
After Installation
You'll have access to:
- AutoMagik Spark API: Running at http://localhost:8883
- PostgreSQL Database: Available at
localhost:15432 - Worker Service: Running and ready to process tasks
- CLI Tool: Installed (if chosen during setup)
Verifying Your Installation
The setup automatically verifies all services, but you can also check manually:
# Access API documentation
open http://localhost:8883/api/v1/docs # Interactive Swagger UI
open http://localhost:8883/api/v1/redoc # ReDoc documentation
# List flows (requires CLI installation)
source .venv/bin/activate
automagik-spark flow list
🧩 System Components
- API Server: Handles all HTTP requests and core logic
- Worker: Processes tasks and schedules
- Database: PostgreSQL with all required tables automatically created
- LangFlow (optional): Visual flow editor for creating AI workflows
- CLI Tool (optional): Command-line interface for managing flows and tasks
🏗️ System Architecture
flowchart LR
subgraph Services
DB[PostgreSQL]
LF1[LangFlow Instance 1]
LF2[LangFlow Instance 2]
end
subgraph AutoMagik Spark
CLI[CLI]
API[API Server]
CW[Celery Worker]
W[Worker]
end
API -- uses --> DB
API -- triggers --> CW
W -- processes --> API
API -- integrates with --> LF1
API -- integrates with --> LF2
CLI -- controls --> API
API -- has UI --> UI[Automagik UI]
Core Components Explained
- API: Core service handling requests and business logic
- Worker: Processes tasks and schedules
- CLI: Command-line tool for managing flows and tasks
- PostgreSQL: Stores flows, tasks, schedules, and other data
- LangFlow: Optional service for creating and editing flows
📚 API Documentation
For complete API documentation, visit:
- Swagger UI: http://localhost:8883/api/v1/docs
- ReDoc: http://localhost:8883/api/v1/redoc
🛠️ Next Steps
- If you installed LangFlow, visit http://localhost:17860 to create your first flow
- Use the API at http://localhost:8883/api/v1/docs to manage your flows and tasks
- Try out the CLI commands with
automagik-spark --help - Monitor task execution through logs and API endpoints
🗺️ Roadmap
AutoMagik Spark's future development focuses on:
- TBA
AutoMagik Spark: Bringing AI Automation to Life
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