Comparison
agentset vs awesome-llm-apps
Verdict
Pick agentset if agentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management; pick awesome-llm-apps if 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.
Markdown twin · agentset alternatives · awesome-llm-apps alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | agentset | awesome-llm-apps |
|---|---|---|
| Maintenance | Steady (36d since push) As of 1d · github_public_v1 | Very active (4d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1d · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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 |
Tagline
- agentset
- The open-source RAG platform with built-in citations and support for deep research
- awesome-llm-apps
- Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.
Stars
- agentset
- 2.1k
- awesome-llm-apps
- 131k
Forks
- agentset
- 185
- awesome-llm-apps
- 19k
Open issues
- agentset
- 14
- awesome-llm-apps
- 13
Language
- agentset
- TypeScript
- awesome-llm-apps
- Python
Adopt for
- agentset
- AgentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management.
- 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
- agentset
- -
- awesome-llm-apps
- -
Runtime
- agentset
- -
- awesome-llm-apps
- -
License
- agentset
- AgentSet operates under the MIT License, allowing for broad usage and modification rights.
- 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
- agentset
- Jul 16, 2026
- awesome-llm-apps
- Aug 3, 2026
Categories
- agentset
- AI Agents, Data & Retrieval
- awesome-llm-apps
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- agentset
- Steady (60%)
- awesome-llm-apps
- Very active (96%)
Days since push
- agentset
- 36d
- awesome-llm-apps
- 4d
Open issues (now)
- agentset
- 14
- awesome-llm-apps
- 13
Stars delta
- agentset
- +31 (30d)
- awesome-llm-apps
- +14k (30d)
Open issues delta
- agentset
- +1 (30d)
- awesome-llm-apps
- +6 (30d)
Owner type
- agentset
- Organization
- awesome-llm-apps
- User
Full report
- agentset
- Trust report
- awesome-llm-apps
- Trust report
Choose agentset if…
- agentset is primarily TypeScript; awesome-llm-apps is Python.
- License: agentset is MIT, awesome-llm-apps is Apache-2.0.
- Pricing: Free to use as it is open-source..
- Requirements: Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities..
- Tags unique to agentset: agentic-rag, ai-agents, embeddings, memory-management.
- - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats.
When NOT to use agentset
- - Avoid selecting AgentSet if your application does not benefit from or necessitate support for a wide array of file types, as its complexity might overwhelm simpler use-cases.
- - If seamless integration with third-party citation services is more preferred, another tool might be better suited since AgentSet focuses on built-in citation capabilities.
Choose awesome-llm-apps if…
- awesome-llm-apps is primarily Python; agentset is TypeScript.
- License: awesome-llm-apps is Apache-2.0, agentset is MIT.
- Pricing: Free with open-source licensing, but commercial exploitation is allowed..
- Tags unique to awesome-llm-apps: agents, applications, customizable, deployable.
- 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 (agentset-ai/agentset) · observed Aug 22, 2026
- GitHub forks (agentset-ai/agentset) · observed Aug 22, 2026
- Last push (agentset-ai/agentset) · observed Jul 16, 2026
- License file (MIT) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Shubhamsaboo/awesome-llm-apps) · observed Aug 7, 2026
- GitHub forks (Shubhamsaboo/awesome-llm-apps) · observed Aug 7, 2026
- Last push (Shubhamsaboo/awesome-llm-apps) · observed Aug 3, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentset 2.1k · awesome-llm-apps 131k (synced Aug 22, 2026).
Common questions
- What is the difference between agentset and awesome-llm-apps?
- agentset: The open-source RAG platform with built-in citations and support for deep research. awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentset over awesome-llm-apps?
- Choose agentset over awesome-llm-apps when agentset is primarily TypeScript; awesome-llm-apps is Python; License: agentset is MIT, awesome-llm-apps is Apache-2.0; Pricing: Free to use as it is open-source.; Requirements: Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities.; Tags unique to agentset: agentic-rag, ai-agents, embeddings, memory-management; - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats.
- When should I choose awesome-llm-apps over agentset?
- Choose awesome-llm-apps over agentset when awesome-llm-apps is primarily Python; agentset is TypeScript; License: awesome-llm-apps is Apache-2.0, agentset is MIT; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; When you need quick implementations of various real-world use cases for AI Agents and RAG.
- When should I avoid agentset?
- - Avoid selecting AgentSet if your application does not benefit from or necessitate support for a wide array of file types, as its complexity might overwhelm simpler use-cases. - If seamless integration with third-party citation services is more preferred, another tool might be better suited since AgentSet focuses on built-in citation capabilities.
- 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 agentset or awesome-llm-apps more popular on GitHub?
- awesome-llm-apps has more GitHub stars (131,230 vs 2,066). Stars measure visibility, not whether either tool fits your constraints.
- Are agentset and awesome-llm-apps open source?
- Yes - both are open-source projects on GitHub (agentset: MIT, awesome-llm-apps: Apache-2.0).
- Where can I find alternatives to agentset or awesome-llm-apps?
- GraphCanon lists graph-backed alternatives at agentset alternatives and awesome-llm-apps alternatives (agentset 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, agentset or awesome-llm-apps?
- agentset: Steady. 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 agentset and awesome-llm-apps?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentset trust report; awesome-llm-apps trust report.