cogflow 3.0.0b2

COGFlow — modular machine learning workflow management system

CogFlow

CogFlow is a modular, SDK-first machine learning workflow management system built on Kubeflow Pipelines, MLflow, Kubernetes, and MinIO.

It provides a clean Python API for:

• building production-grade ML pipelines
• managing datasets and components
• orchestrating federated learning workflows
• enforcing consistent error handling and validation

CogFlow is designed for real infrastructure, not notebooks only.

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Why CogFlow?

Modern ML platforms are powerful but fragmented:

• Kubeflow Pipelines → great orchestration, weak ergonomics
• MLflow → experiment tracking, limited workflow control
• Kubernetes → powerful, but verbose and error-prone
• Federated learning → no standard orchestration layer

CogFlow bridges these gaps by providing:

• a stable Python SDK
• safe lazy-loading of heavy dependencies
• unified error handling
• infrastructure-aware abstractions
• zero circular imports

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Core Features

🧩 Pipeline Orchestration

• Lazy-loaded Kubeflow Pipelines client
• Safe pipeline compilation and submission
• Runtime environment injection
• Kubernetes service lifecycle management

📦 Component Management

• YAML-based component registry
• MinIO-backed component storage
• Automatic component registration
• Runtime-safe component loading

📊 Dataset Management

• Dataset registration and metadata retrieval
• Secure dataset downloads
• Silent deletes with strict error semantics
• Pluggable storage backends

🤝 Federated Learning

• Auto-generated FL pipelines
• Dynamic pipeline signatures
• Connector-based and dataspace-based workflows
• Region-aware scheduling with node selectors

🧠 Unified Error Handling

• Strongly typed error hierarchy
• Context-aware exception wrapping
• API-ready error serialization
• Zero silent failures

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Architecture Overview

CogFlow follows a layered SDK architecture:

cogflow/ ├── core/ │ ├── pipelines/ # Kubeflow orchestration & FL pipelines │ ├── datasets/ # Dataset lifecycle management │ ├── components/ # Component registry & YAML handling │ └── models/ # (future extension) │ ├── utils/ │ ├── common.py # UUIDs, paths, Kubernetes helpers │ ├── network.py # HTTP utilities with retry & streaming │ ├── storage.py # MinIO client abstraction │ └── exceptions.py # Unified error framework │ ├── config.py └── api.py