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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.

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

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

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

Project links

Data verified by PyPI on Aug 27, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Stable release available (1.13.8)

1 maintainer

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Data sourced directly from PyPI's database.
Avatar for sai_kireeti from gravatar.com sai_kireeti

Credits

Author: Sai Kireeti

GitHub Statistics

Data verified by PyPI on Aug 27, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.10

Provides Extra

dev docs agent agent-otel openai llm full

Tags

ml workflow kfp federated-learning cogflow mlops

Classifiers

Report project as malware

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