GraphCanon
Home/Compare/llm-applications vs llmflows

Comparison

llm-applications vs llmflows

Verdict

Pick llm-applications if the llm-applications repository offers focused guidance on deploying RAG-based LLM apps in production environments with an emphasis on using Ray; pick llmflows if lLMFlows is a Python library designed for creating and managing LLM applications with a focus on simplicity and transparency.

Markdown twin · llm-applications alternatives · llmflows alternatives

GraphCanon updated Sep 20, 2026

14views this month

llm-applications logo

llm-applications

ray-project/llm-applications

★ 1.9kpushed Aug 15, 2026
vs
llmflows logo

llmflows

stoyan-stoyanov/llmflows

★ 708pushed Feb 20, 2025

Trust & integrity

Signalllm-applicationsllmflows
Maintenance
Steady (35d since push)
As of Sep 19, 2026 · github_public_v1
Dormant (574d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 19, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
Published findings
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
llm-applications trust reportllmflows trust reportTrust methodology

Tagline

llm-applications
Comprehensive guide to building RAG-based LLM applications for production
llmflows
Simple, Explicit and Transparent LLM Apps

Stars

llm-applications
1.9k
llmflows
708

Forks

llm-applications
258
llmflows
35

Open issues

llm-applications
15
llmflows
19

Language

llm-applications
Jupyter Notebook
llmflows
Python

Adopt for

llm-applications
The llm-applications repository offers focused guidance on deploying RAG-based LLM apps in production environments with an emphasis on using Ray.
llmflows
LLMFlows is a Python library designed for creating and managing LLM applications with a focus on simplicity and transparency.

Persona

llm-applications
-
llmflows
-

Runtime

llm-applications
-
llmflows
-

License

llm-applications
CC-BY-4.0
llmflows
LLMFlows is distributed under the MIT license, allowing for free use, modification, and distribution.

Last pushed

llm-applications
Aug 15, 2026
llmflows
Feb 20, 2025

Categories

llm-applications
Inference & Serving, LLM Frameworks
llmflows
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

llm-applications
Steady (60%)
llmflows
Dormant (18%)

Days since push

llm-applications
35d
llmflows
574d

Open issues (now)

llm-applications
15
llmflows
19

Stars delta

llm-applications
0 (30d)
llmflows
+1 (30d)

Open issues delta

llm-applications
+2 (30d)
llmflows
0 (30d)

Owner type

llm-applications
Organization
llmflows
User

OSV dependency advisories

llm-applications
No lockfile (source not queried)
llmflows
Published findings

Full report

llm-applications
Trust report
llmflows
Trust report

Shared compatibility

  • Python · llm-applications: Python runtime · llmflows: Python runtime

Choose llm-applications if…

  • llm-applications is primarily Jupyter Notebook; llmflows is Python.
  • License: llm-applications is CC-BY-4.0, llmflows is MIT.
  • Tags unique to llm-applications: anyscale, fine-tuning, llama2, machin-learning.
  • You require a detailed guide specifically tailored to the development and deployment of RAG-based applications, leveraging Ray for performance and scalability.

When NOT to use llm-applications

  • If you are looking for a more generalized approach to LLM application development that does not specifically cater to RAG-based designs and Ray optimizations.
  • When your project workflow is incompatible with or cannot support Jupyter Notebook dependencies and the resources assume.
GitHubDetails

Choose llmflows if…

  • llmflows is primarily Python; llm-applications is Jupyter Notebook.
  • License: llmflows is MIT, llm-applications is CC-BY-4.0.
  • Pricing: The library is free to use, but additional services or support might incur costs..
  • Requirements: Min 2 GB RAM; Python environment is required..
  • Tags unique to llmflows: ai, chatgpt, gpt-4, llm.
  • When you need a straightforward and transparent approach to building LLM applications, LLMFlows offers a simple framework that prioritizes clarity in the development process.

When NOT to use llmflows

  • Avoid LLMFlows if you require advanced customization options that go beyond its simple and explicit design philosophy.
  • Do not use LLMFlows if your project demands a more complex framework that integrates a wide range of third-party services, as LLMFlows focuses on simplicity and may lack extensive integration features
GitHubDetails

Explore

llm-applications trust report →llmflows trust report →Inference & Serving category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: llm-applications 1.9k · llmflows 708 (synced Sep 20, 2026).

Common questions

What is the difference between llm-applications and llmflows?
llm-applications: Comprehensive guide to building RAG-based LLM applications for production. llmflows: Simple, Explicit and Transparent LLM Apps. See the comparison table for live GitHub stats and shared categories.
When should I choose llm-applications over llmflows?
Choose llm-applications over llmflows when llm-applications is primarily Jupyter Notebook; llmflows is Python; License: llm-applications is CC-BY-4.0, llmflows is MIT; Tags unique to llm-applications: anyscale, fine-tuning, llama2, machin-learning; You require a detailed guide specifically tailored to the development and deployment of RAG-based applications, leveraging Ray for performance and scalability.
When should I choose llmflows over llm-applications?
Choose llmflows over llm-applications when llmflows is primarily Python; llm-applications is Jupyter Notebook; License: llmflows is MIT, llm-applications is CC-BY-4.0; Pricing: The library is free to use, but additional services or support might incur costs.; Requirements: Min 2 GB RAM; Python environment is required.; Tags unique to llmflows: ai, chatgpt, gpt-4, llm; When you need a straightforward and transparent approach to building LLM applications, LLMFlows offers a simple framework that prioritizes clarity in the development process.
When should I avoid llm-applications?
If you are looking for a more generalized approach to LLM application development that does not specifically cater to RAG-based designs and Ray optimizations. When your project workflow is incompatible with or cannot support Jupyter Notebook dependencies and the resources assume.
When should I avoid llmflows?
Avoid LLMFlows if you require advanced customization options that go beyond its simple and explicit design philosophy. Do not use LLMFlows if your project demands a more complex framework that integrates a wide range of third-party services, as LLMFlows focuses on simplicity and may lack extensive integration features
Is llm-applications or llmflows more popular on GitHub?
llm-applications has more GitHub stars (1,857 vs 708). Stars measure visibility, not whether either tool fits your constraints.
Are llm-applications and llmflows open source?
Yes - both are open-source projects on GitHub (llm-applications: CC-BY-4.0, llmflows: MIT).
Where can I find alternatives to llm-applications or llmflows?
GraphCanon lists graph-backed alternatives at llm-applications alternatives and llmflows alternatives (llm-applications markdown twin, llmflows 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, llm-applications or llmflows?
llm-applications: Steady. llmflows: Dormant. 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 llm-applications and llmflows?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm-applications trust report; llmflows trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.