--- title: "agentset vs llama-hub" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentset-ai-agentset-vs-run-llama-llama-hub" tools: ["agentset-ai-agentset", "run-llama-llama-hub"] --- # agentset vs llama-hub *GraphCanon updated Aug 22, 2026* ## 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 llama-hub if community-driven data loaders for LlamaIndex/LangChain. [agentset](https://agentset.ai) reports 2.1k GitHub stars, 185 forks, and 14 open issues, last pushed Jul 16, 2026. [llama-hub](https://llamahub.ai/) has 3.5k stars, 721 forks, and 96 open issues, last pushed Mar 1, 2024. Figures are from public GitHub metadata via [agentset's repository](https://github.com/agentset-ai/agentset) and [llama-hub's repository](https://github.com/run-llama/llama-hub). | | [agentset](/tools/agentset-ai-agentset.md) | [llama-hub](/tools/run-llama-llama-hub.md) | | --- | --- | --- | | Tagline | The open-source RAG platform with built-in citations and support for deep research | A library of data loaders for LLMs made by the community | | Stars | 2,066 | 3,469 | | Forks | 185 | 721 | | Open issues | 14 | 96 | | Language | TypeScript | Jupyter Notebook | | Adopt for | 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. | community-driven data loaders for LlamaIndex/LangChain | | Persona | - | - | | Runtime | - | - | | License | AgentSet operates under the MIT License, allowing for broad usage and modification rights. | MIT | | Categories | AI Agents, Data & Retrieval | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentset](/tools/agentset-ai-agentset.md) | [llama-hub](/tools/run-llama-llama-hub.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Archived (8%) | | Days since push | 36d | 889d | | Archived on GitHub | No | Yes | | Open issues (now) | 14 | 96 | | Stars delta | +31 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Full report | [trust report](/tools/agentset-ai-agentset/trust.md) | [trust report](/tools/run-llama-llama-hub/trust.md) | ## Decision facts: agentset - **Pricing:** freemium - 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. - **Adopt for:** 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. - **License detail:** AgentSet operates under the MIT License, allowing for broad usage and modification rights. ## Decision facts: llama-hub - **Adopt for:** community-driven data loaders for LlamaIndex/LangChain ## Choose when ### Choose agentset if… - agentset is primarily TypeScript; llama-hub is Jupyter Notebook. - 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. - Also covers AI Agents. - - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### Choose llama-hub if… - llama-hub is primarily Jupyter Notebook; agentset is TypeScript. - Tags unique to llama-hub: community-driven, jupyter-notebook, langchain, llamaindex. - Also covers Model Training. - Community-specific features require engagement with community ## 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. ## When NOT to use llama-hub - Limited support if the community lacks activity - Not suitable without familiarity with Poetry for dependency management ## Common questions ### What is the difference between agentset and llama-hub? agentset: The open-source RAG platform with built-in citations and support for deep research. llama-hub: A library of data loaders for LLMs made by the community. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentset over llama-hub? Choose agentset over llama-hub when agentset is primarily TypeScript; llama-hub is Jupyter Notebook; 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; Also covers AI Agents; - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### When should I choose llama-hub over agentset? Choose llama-hub over agentset when llama-hub is primarily Jupyter Notebook; agentset is TypeScript; Tags unique to llama-hub: community-driven, jupyter-notebook, langchain, llamaindex; Also covers Model Training; Community-specific features require engagement with community. ### 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 llama-hub? Limited support if the community lacks activity Not suitable without familiarity with Poetry for dependency management ### Is agentset or llama-hub more popular on GitHub? llama-hub has more GitHub stars (3,469 vs 2,066). Stars measure visibility, not whether either tool fits your constraints. ### Are agentset and llama-hub open source? Yes - both are open-source projects on GitHub (agentset: MIT, llama-hub: MIT). ### Where can I find alternatives to agentset or llama-hub? GraphCanon lists graph-backed alternatives at [agentset alternatives](/tools/agentset-ai-agentset/alternatives) and [llama-hub alternatives](/tools/run-llama-llama-hub/alternatives) ([agentset markdown twin](/tools/agentset-ai-agentset/alternatives.md), [llama-hub markdown twin](/tools/run-llama-llama-hub/alternatives.md)), 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](/compare/agentset-ai-agentset-vs-run-llama-llama-hub.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentset or llama-hub? agentset: Steady. llama-hub: Archived. 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 llama-hub? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentset trust report](/tools/agentset-ai-agentset/trust); [llama-hub trust report](/tools/run-llama-llama-hub/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentset-ai-agentset`](/api/graphcanon/graph?tool=agentset-ai-agentset) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_