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Comparison

HippoRAG vs llm-applications

Verdict

Pick HippoRAG if hippoRAG is a RAG framework that leverages Knowledge Graphs and Personalized PageRank for improved information retrieval from external documents; 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.

Markdown twin · HippoRAG alternatives · llm-applications alternatives

GraphCanon updated 2w

HippoRAG logo

HippoRAG

OSU-NLP-Group/HippoRAG

★ 3.9kpushed Jul 29, 2026
vs
llm-applications logo

llm-applications

ray-project/llm-applications

★ 1.9kpushed Aug 2, 2024

Trust & integrity

SignalHippoRAGllm-applications
Maintenance
Very active (3d since push)
As of 2w · github_public_v1
Dormant (721d since push)
As of 4w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Organization account
As of 4w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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
HippoRAG trust reportllm-applications trust reportTrust methodology

Tagline

HippoRAG
HippoRAG is a RAG framework enabling LLMs to continuously integrate knowledge from external documents.
llm-applications
Comprehensive guide to building RAG-based LLM applications for production

Stars

HippoRAG
3.9k
llm-applications
1.9k

Forks

HippoRAG
416
llm-applications
255

Open issues

HippoRAG
7
llm-applications
13

Language

HippoRAG
Python
llm-applications
Jupyter Notebook

Adopt for

HippoRAG
HippoRAG is a RAG framework that leverages Knowledge Graphs and Personalized PageRank for improved information retrieval from external documents.
llm-applications
The llm-applications repository offers focused guidance on deploying RAG-based LLM apps in production environments with an emphasis on using Ray.

Persona

HippoRAG
-
llm-applications
-

Runtime

HippoRAG
-
llm-applications
-

License

HippoRAG
MIT
llm-applications
CC-BY-4.0

Last pushed

HippoRAG
Jul 29, 2026
llm-applications
Aug 2, 2024

Categories

HippoRAG
LLM Frameworks, Model Training
llm-applications
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

HippoRAG
Very active (96%)
llm-applications
Dormant (18%)

Days since push

HippoRAG
3d
llm-applications
721d

Open issues (now)

HippoRAG
7
llm-applications
13

OSV dependency advisories

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

Full report

HippoRAG
Trust report
llm-applications
Trust report

Shared compatibility

  • OpenAI API · HippoRAG: OpenAI API · llm-applications: OpenAI API
  • Python · HippoRAG: Python runtime · llm-applications: Python runtime

Choose HippoRAG if…

  • HippoRAG is primarily Python; llm-applications is Jupyter Notebook.
  • License: HippoRAG is MIT, llm-applications is CC-BY-4.0.
  • Tags unique to HippoRAG: knowledge graphs, knowledge integration, language-models, personalized pagerank.
  • Also covers Model Training.
  • When integrating human-like long-term memory capabilities into LLM models to handle vast amounts of external knowledge

When NOT to use HippoRAG

  • If your application does not require continuous integration of external documents or personalized information retrieval
  • For simpler applications where standard RAG frameworks without KG Personalized PageRank suffice for performance requirements
GitHubDetails

Choose llm-applications if…

  • llm-applications is primarily Jupyter Notebook; HippoRAG is Python.
  • License: llm-applications is CC-BY-4.0, HippoRAG is MIT.
  • Tags unique to llm-applications: anyscale, fine-tuning, llama2, machin-learning.
  • Also covers Inference & Serving.
  • 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

Explore

HippoRAG trust report →llm-applications trust report →LLM Frameworks category →Model Training category →Inference & Serving 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: HippoRAG 3.9k · llm-applications 1.9k (synced Aug 1, 2026).

Common questions

What is the difference between HippoRAG and llm-applications?
HippoRAG: HippoRAG is a RAG framework enabling LLMs to continuously integrate knowledge from external documents.. llm-applications: Comprehensive guide to building RAG-based LLM applications for production. See the comparison table for live GitHub stats and shared categories.
When should I choose HippoRAG over llm-applications?
Choose HippoRAG over llm-applications when HippoRAG is primarily Python; llm-applications is Jupyter Notebook; License: HippoRAG is MIT, llm-applications is CC-BY-4.0; Tags unique to HippoRAG: knowledge graphs, knowledge integration, language-models, personalized pagerank; Also covers Model Training; When integrating human-like long-term memory capabilities into LLM models to handle vast amounts of external knowledge.
When should I choose llm-applications over HippoRAG?
Choose llm-applications over HippoRAG when llm-applications is primarily Jupyter Notebook; HippoRAG is Python; License: llm-applications is CC-BY-4.0, HippoRAG is MIT; Tags unique to llm-applications: anyscale, fine-tuning, llama2, machin-learning; Also covers Inference & Serving; 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 avoid HippoRAG?
If your application does not require continuous integration of external documents or personalized information retrieval For simpler applications where standard RAG frameworks without KG Personalized PageRank suffice for performance requirements
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.
Is HippoRAG or llm-applications more popular on GitHub?
HippoRAG has more GitHub stars (3,902 vs 1,857). Stars measure visibility, not whether either tool fits your constraints.
Are HippoRAG and llm-applications open source?
Yes - both are open-source projects on GitHub (HippoRAG: MIT, llm-applications: CC-BY-4.0).
Where can I find alternatives to HippoRAG or llm-applications?
GraphCanon lists graph-backed alternatives at HippoRAG alternatives and llm-applications alternatives (HippoRAG markdown twin, llm-applications 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, HippoRAG or llm-applications?
HippoRAG: Very active. llm-applications: 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 HippoRAG and llm-applications?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: HippoRAG trust report; llm-applications trust report.

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