Comparison
awesome-argo vs llm-app
Verdict
Pick awesome-argo if curated list of projects and resources for Argo ecosystem components like argocd and workflows; pick llm-app if llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.
Markdown twin · awesome-argo alternatives · llm-app alternatives
GraphCanon updated Oct 4, 2026
8views this month
vs
Trust & integrity
| Signal | awesome-argo | llm-app |
|---|---|---|
| Maintenance | Active (16d since push) As of Oct 4, 2026 · github_public_v1 | Steady (74d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 4, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- awesome-argo
- Curated list of projects and resources for Argo
- llm-app
- Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data
Stars
- awesome-argo
- 2.5k
- llm-app
- 59k
Forks
- awesome-argo
- 201
- llm-app
- 1.5k
Open issues
- awesome-argo
- 2
- llm-app
- 8
Language
- awesome-argo
- -
- llm-app
- Jupyter Notebook
Adopt for
- awesome-argo
- Curated list of projects and resources for Argo ecosystem components like argocd and workflows
- llm-app
- llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.
Persona
- awesome-argo
- -
- llm-app
- -
Runtime
- awesome-argo
- -
- llm-app
- -
License
- awesome-argo
- Apache-2.0 licensed, open source and permissive license suitable for broad usage scenarios and ecosystems including commercial products.
- llm-app
- MIT License
Last pushed
- awesome-argo
- Sep 18, 2026
- llm-app
- Jul 5, 2026
Categories
- awesome-argo
- Evaluation & Observability, Inference & Serving, Model Training
- llm-app
- Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training
Trust and health
Maintenance
- awesome-argo
- Active (82%)
- llm-app
- Steady (60%)
Days since push
- awesome-argo
- 16d
- llm-app
- 74d
Open issues (now)
- awesome-argo
- 2
- llm-app
- 8
Stars delta
- awesome-argo
- +31 (30d)
- llm-app
- -117 (30d)
Open issues delta
- awesome-argo
- +2 (30d)
- llm-app
- 0 (30d)
Full report
- awesome-argo
- Trust report
- llm-app
- Trust report
Choose awesome-argo if…
- License: awesome-argo is Apache-2.0, llm-app is MIT.
- Tags unique to awesome-argo: argo-events, argo-rollouts, argo-workflows, argocd.
- Need curated resources for learning about specific Argo tools like Argocd, Workflows or Rollouts
When NOT to use awesome-argo
- Looking for a general-purpose CI/CD tool without Kubernetes focus
- Require deep integration with non-Kubernetes orchestration platforms
Choose llm-app if…
- License: llm-app is MIT, awesome-argo is Apache-2.0.
- Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs..
- Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs..
- Tags unique to llm-app: chatbot, hugging-face, llm, llm-local.
- Also covers Data & Retrieval.
- When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti
When NOT to use llm-app
- Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support.
- Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (akuity/awesome-argo) · observed Oct 4, 2026
- GitHub forks (akuity/awesome-argo) · observed Oct 4, 2026
- Last push (akuity/awesome-argo) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Oct 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pathwaycom/llm-app) · observed Sep 20, 2026
- GitHub forks (pathwaycom/llm-app) · observed Sep 20, 2026
- Last push (pathwaycom/llm-app) · observed Jul 5, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: awesome-argo 2.5k · llm-app 59k (synced Oct 4, 2026).
Common questions
- What is the difference between awesome-argo and llm-app?
- awesome-argo: Curated list of projects and resources for Argo. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-argo over llm-app?
- Choose awesome-argo over llm-app when License: awesome-argo is Apache-2.0, llm-app is MIT; Tags unique to awesome-argo: argo-events, argo-rollouts, argo-workflows, argocd; Need curated resources for learning about specific Argo tools like Argocd, Workflows or Rollouts.
- When should I choose llm-app over awesome-argo?
- Choose llm-app over awesome-argo when License: llm-app is MIT, awesome-argo is Apache-2.0; Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.; Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.; Tags unique to llm-app: chatbot, hugging-face, llm, llm-local; Also covers Data & Retrieval; When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti.
- When should I avoid awesome-argo?
- Looking for a general-purpose CI/CD tool without Kubernetes focus Require deep integration with non-Kubernetes orchestration platforms
- When should I avoid llm-app?
- Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities.
- Is awesome-argo or llm-app more popular on GitHub?
- llm-app has more GitHub stars (58,920 vs 2,495). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-argo and llm-app open source?
- Yes - both are open-source projects on GitHub (awesome-argo: Apache-2.0, llm-app: MIT).
- Where can I find alternatives to awesome-argo or llm-app?
- GraphCanon lists graph-backed alternatives at awesome-argo alternatives and llm-app alternatives (awesome-argo markdown twin, llm-app 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, awesome-argo or llm-app?
- awesome-argo: Active. llm-app: Steady. 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 awesome-argo and llm-app?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-argo trust report; llm-app trust report.