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AutoMagik Spark - Automagion Engine with LangFlow integration

Project description

AutoMagik Spark Logo

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

🚀 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:

🛠️ Next Steps

  1. If you installed LangFlow, visit http://localhost:17860 to create your first flow
  2. Use the API at http://localhost:8883/api/v1/docs to manage your flows and tasks
  3. Try out the CLI commands with automagik-spark --help
  4. 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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