Home/Compare/pipelines vs awesome-llm-apps

Comparison

pipelines vs awesome-llm-apps

Verdict

Pick pipelines when tags unique to pipelines: data-science, machine-learning, pipeline, kubeflow-pipelines; pick awesome-llm-apps when pricing: Free with open-source licensing, but commercial exploitation is allowed..

Markdown twin · pipelines alternatives · awesome-llm-apps alternatives

GraphCanon updated today

pipelines logo

pipelines

kubeflow/pipelines

4.2kpushed Jul 11, 2026
vs
awesome-llm-apps logo

awesome-llm-apps

Shubhamsaboo/awesome-llm-apps

118kpushed Jul 11, 2026

Trust & integrity

Signalpipelinesawesome-llm-apps
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
2 low (2 low)
As of today · osv@v1
No lockfile
As of today · none

Tagline

pipelines
Machine Learning Pipelines for Kubeflow
awesome-llm-apps
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.

Stars

pipelines
4.2k
awesome-llm-apps
118k

Forks

pipelines
2.0k
awesome-llm-apps
17k

Open issues

pipelines
419
awesome-llm-apps
6

Language

pipelines
Python
awesome-llm-apps
Python

Adopt for

pipelines
-
awesome-llm-apps
awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python.

Persona

pipelines
-
awesome-llm-apps
-

Runtime

pipelines
-
awesome-llm-apps
-

License

pipelines
Apache-2.0
awesome-llm-apps
The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license.

Last pushed

pipelines
Jul 11, 2026
awesome-llm-apps
Jul 11, 2026

Categories

pipelines
Data & Retrieval, Inference & Serving
awesome-llm-apps
AI Agents, Data & Retrieval

Trust and health

Open issues (now)

pipelines
419
awesome-llm-apps
6

Owner type

pipelines
Organization
awesome-llm-apps
User

Security scan

pipelines
2 low (2 low)
awesome-llm-apps
No lockfile

Full report

pipelines
Trust report
awesome-llm-apps
Trust report

Choose pipelines if…

  • Tags unique to pipelines: data-science, machine-learning, pipeline, kubeflow-pipelines.
  • Also covers Inference & Serving.
  • More recently updated (last pushed Jul 11, 2026).

When NOT to use pipelines

  • Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.

Choose awesome-llm-apps if…

  • Pricing: Free with open-source licensing, but commercial exploitation is allowed..
  • Tags unique to awesome-llm-apps: llms, deployable, applications, agents.
  • Also covers AI Agents.
  • When you need quick implementations of various real-world use cases for AI Agents and RAG.

When NOT to use awesome-llm-apps

  • If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch.
  • When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: pipelines 4.2k · awesome-llm-apps 118k (synced Jul 11, 2026).

Common questions

What is the difference between pipelines and awesome-llm-apps?
pipelines: Machine Learning Pipelines for Kubeflow. awesome-llm-apps: 100+ AI Agent & RAG apps you can actually run — clone, customize, ship.. See the comparison table for live GitHub stats and shared categories.
When should I choose pipelines over awesome-llm-apps?
Choose pipelines over awesome-llm-apps when Tags unique to pipelines: data-science, machine-learning, pipeline, kubeflow-pipelines; Also covers Inference & Serving; More recently updated (last pushed Jul 11, 2026).
When should I choose awesome-llm-apps over pipelines?
Choose awesome-llm-apps over pipelines when Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: llms, deployable, applications, agents; Also covers AI Agents; When you need quick implementations of various real-world use cases for AI Agents and RAG.
When should I avoid pipelines?
Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
When should I avoid awesome-llm-apps?
If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.
Is pipelines or awesome-llm-apps more popular on GitHub?
awesome-llm-apps has more GitHub stars (117,774 vs 4,169). Stars measure visibility, not whether either tool fits your constraints.
Are pipelines and awesome-llm-apps open source?
Yes - both are open-source projects on GitHub (pipelines: Apache-2.0, awesome-llm-apps: Apache-2.0).
Where can I find alternatives to pipelines or awesome-llm-apps?
GraphCanon lists graph-backed alternatives at pipelines alternatives and awesome-llm-apps alternatives (pipelines markdown twin, awesome-llm-apps markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, pipelines or awesome-llm-apps?
pipelines: Very active. awesome-llm-apps: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for pipelines and awesome-llm-apps?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: pipelines trust report; awesome-llm-apps trust report.