Software Development & Delivery · Public

zenml

ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.

Best fitUsers who want source-backed project understanding before installing it.

Check whether this project matches your task before installing it.

What it can doskill, recipe, host_instruction, eval, preflight

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot5.5k stars

626 forks · 139 contributors

Doramagic.ai Last verification date: 2026-06-20 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-06-20

What is zenml?

ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Best fit: Users who want source-backed project understanding before installing it.
Not for: Not for users who want to skip sandbox verification or cannot accept configuration, permission, or maintenance overhead.
Capability added to an AI workflow: skill, recipe, host_instruction, eval, preflight
First safe verification step: Verify the smallest path in an isolated environment and keep a rollback path.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/zenml-io/zenml, https://github.com/zenml-io/zenml#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forUsers who want source-backed project understanding before installing it.

Match the project to your task before installing it.

Capabilityskill, recipe, host_instruction, eval, preflight

ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.

Repositoryzenml-io/zenml

5.5k stars · 626 forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Pipeline Authoring: Steps, Pipelines, Snapshots, and Dynamic Execution

Related topics: Stacks, Orchestrators, and Integration Ecosystem, Containerization, Image Building, and Server Deployment, Server, REST API, Data Models, and Persistence

Source: https://github.com/zenml-io/zenml / Human Manual

Stacks, Orchestrators, and Integration Ecosystem

Related topics: Pipeline Authoring: Steps, Pipelines, Snapshots, and Dynamic Execution, Containerization, Image Building, and Server Deployment

Source: https://github.com/zenml-io/zenml / Human Manual

Containerization, Image Building, and Server Deployment

Related topics: Stacks, Orchestrators, and Integration Ecosystem, Server, REST API, Data Models, and Persistence

Source: https://github.com/zenml-io/zenml / Human Manual

Server, REST API, Data Models, and Persistence

Related topics: Pipeline Authoring: Steps, Pipelines, Snapshots, and Dynamic Execution, Stacks, Orchestrators, and Integration Ecosystem, Containerization, Image Building, and Server Deplo...

Source: https://github.com/zenml-io/zenml / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/zenml-io/zenml, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars5.5k stars

Forks626 forks

Contributors139 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using zenml with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
More flexible numpy versioning
github / github_issue
02
Display failure/success hooks and their output
github / github_issue
03
OAuth-Based Authentication for Managed MLflow Backends
github / github_issue
04
Add dependency audit workflow
github / github_issue
05
Kubernetes deployer Service selector mismatch (ZenML 0.94.2)
github / github_issue
06
Pending pods visibility
github / github_issue
07
Clean up the failing tests on the CI
github / github_issue
08
Extend platform trigger event sources (+ snapshots)
github / github_issue
09
skypilot/utils.py: create_docker_run_command passes -e KEY without value
github / github_issue
10
0.95.1
github / github_release
11
0.95.0
github / github_release
12
0.94.6
github / github_release

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install zenml

Official start command · https://github.com/zenml-io/zenml#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

zenml Manual

ZenML's pipeline authoring layer is the user-facing surface for describing ML and AI workflows in Python. It provides a small, opinionated vocabulary: @step defines the smallest executable...

Open the full manual

https://github.com/zenml-io/zenml Project Manual
Table of Contents
Pipeline Authoring: Steps, Pipelines, Snapshots, and Dynamic Execution
Related Pages
Overview
Steps: The Executable Unit
Pipelines: Composing Steps into a DAG
Snapshots: Freezing a Pipeline for Reproducibility

Pipeline Authoring: Steps, Pipelines, Snapshots, and Dynamic Execution

Related topics: Stacks, Orchestrators, and Integration Ecosystem, Containerization, Image Building, and Server Deployment, Server, REST API, Data Models, and Persistence

Source: https://github.com/zenml-io/zenml / Human Manual

Stacks, Orchestrators, and Integration Ecosystem

Related topics: Pipeline Authoring: Steps, Pipelines, Snapshots, and Dynamic Execution, Containerization, Image Building, and Server Deployment

Source: https://github.com/zenml-io/zenml / Human Manual

Containerization, Image Building, and Server Deployment

Related topics: Stacks, Orchestrators, and Integration Ecosystem, Server, REST API, Data Models, and Persistence

Source: https://github.com/zenml-io/zenml / Human Manual

Server, REST API, Data Models, and Persistence

Related topics: Pipeline Authoring: Steps, Pipelines, Snapshots, and Dynamic Execution, Stacks, Orchestrators, and Integration Ecosystem, Containerization, Image Building, and Server Deplo...

Source: https://github.com/zenml-io/zenml / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.