britcummings1837/system-catalyst

# system-catalyst A modular orchestration framework for managing complex data flows, applying security protocols, tracking system metadata, and facilitating model evolution within highly dynamic environments. System Catalyst serves as a central nervous system, providing tools and mechanisms to define, execute, and report on sophisticated system operations. It connects diverse components through tightly managed workflow definitions, robust data parsing utilities, system monitoring and history management, and advanced AI/ML capabilities focused on state and evolution. ## Features - **Modular Orchestration:** Manages complex data flows and system configurations through defined workflows and configuration files (`workflow_definition.json`, `build_configuration.json`). - **System Metadata Management:** Tracks and stores comprehensive system metadata and historical records, including worker implementation, core history, and migration logic. - **Security and Protocols:** Includes utilities for handling secrets (`create_secret_body.py`) and managing authentication processes through specialized test suites. - **AI/ML Integration:** Leverages advanced mathematical models, specifically a Gaussian Process Regressor (`gaussian_process_regressor.py`), for data analysis and prediction relevant to system states. - **Data and Context Processing:** Provides sophisticated utility functions for data decoding (`decoder.py`), contextual compression (`compress_context.py`), hardware detection (`hardware_detection.py`), and multimedia processing (`screenshot_utility.py`). - **Analysis Toolkit:** Offers specialized agents for system analysis, including namespace analysis (`nsys_analysis_toolkit.py`) and classification based on dynamic parameters (`classifier_target.py`). - **API and Communication:** Includes modules for exposing service interactions (`plugin_service.py`) and managing data queues (`mcp_queue.py`). - **Developer Workflow:** Supports explicit definition of module interaction patterns (`mcp_server_patterns.py`) and thorough testing for all core functionalities. ## Setup ### Prerequisites Ensure you have Python 3.x and Docker installed on your system. ### Installation 1. **Clone the Repository:** git clone https://github.com/britcummings1837/system-catalyst.git cd system-catalyst 2. **Build Container:** Use the provided `Dockerfile` to build the containerized environment. docker build -t system-catalyst . 3. **Run Applications:** Start the container to access the orchestration framework and core services. docker run -it system-catalyst ## Core Components Overview The framework is structured into core logic, useful utilities, abstract systems, and API interface layers: **Core Logic:** Modules handling central decision-making, history management, system metrics, and model evaluation (`src/core/`). **Utility Operations:** Functions handling input/output processing, style definitions, hardware interaction, data decoding, and context compression (`src/utils/`). **System Interfaces:** Modules defining external interactions, such as the plugin API, network routing (`share_router.py`), database interfacing, and system documentation. **Metadata and Configuration:** JSON configuration files define specific workflows, build requirements, and operational metadata.