Comparison
agentset vs DeepResearch
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 DeepResearch if deepResearch is an open-source AI research agent specialized for information-seeking tasks, built with Python and licensed under Apache-2.0.
Markdown twin · agentset alternatives · DeepResearch alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | agentset | DeepResearch |
|---|---|---|
| Maintenance | Very active (6d since push) As of 4w · github_public_v1 | Slowing (172d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4w · github_public_v1 | Not a fork · Organization account As of 1d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- DeepResearch
- Tongyi Deep Research, the Leading Open-source Deep Research Agent
Stars
- agentset
- 2.0k
- DeepResearch
- 20k
Forks
- agentset
- 183
- DeepResearch
- 1.5k
Open issues
- agentset
- 13
- DeepResearch
- 92
Language
- agentset
- TypeScript
- DeepResearch
- 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.
- DeepResearch
- DeepResearch is an open-source AI research agent specialized for information-seeking tasks, built with Python and licensed under Apache-2.0.
Persona
- agentset
- -
- DeepResearch
- -
Runtime
- agentset
- -
- DeepResearch
- -
License
- agentset
- AgentSet operates under the MIT License, allowing for broad usage and modification rights.
- DeepResearch
- Apache-2.0
Last pushed
- agentset
- Jul 16, 2026
- DeepResearch
- Feb 27, 2026
Categories
- agentset
- AI Agents, Data & Retrieval
- DeepResearch
- AI Agents, Inference & Serving
Trust and health
Maintenance
- agentset
- Very active (96%)
- DeepResearch
- Slowing (36%)
Days since push
- agentset
- 6d
- DeepResearch
- 172d
Open issues (now)
- agentset
- 13
- DeepResearch
- 92
Stars delta
- agentset
- Unknown
- DeepResearch
- +161 (30d)
Open issues delta
- agentset
- Unknown
- DeepResearch
- 0 (30d)
OSV dependency advisories
- agentset
- No lockfile (source not queried)
- DeepResearch
- Published findings
Full report
- agentset
- Trust report
- DeepResearch
- Trust report
Choose agentset if…
- agentset is primarily TypeScript; DeepResearch is Python.
- License: agentset is MIT, DeepResearch 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.
- Also covers Data & Retrieval.
- - 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 DeepResearch if…
- DeepResearch is primarily Python; agentset is TypeScript.
- License: DeepResearch is Apache-2.0, agentset is MIT.
- Tags unique to DeepResearch: agent, alibaba, artificial-intelligence, deep-research.
- Also covers Inference & Serving.
- When you need a tool backed by Alibaba’s ecosystem that offers a robust environment for conducting deep research using AI techniques.
When NOT to use DeepResearch
- Avoid DeepResearch if you require specialized features that are not covered under its deep research and information-seeking scope.
- Do not use this tool if your project necessitates proprietary solutions, as the open-source nature might be a constraint in such scenarios.
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 Jul 22, 2026
- GitHub forks (agentset-ai/agentset) · observed Jul 22, 2026
- Last push (agentset-ai/agentset) · observed Jul 16, 2026
- License file (MIT) · observed Jul 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Alibaba-NLP/DeepResearch) · observed Aug 19, 2026
- GitHub forks (Alibaba-NLP/DeepResearch) · observed Aug 19, 2026
- Last push (Alibaba-NLP/DeepResearch) · observed Feb 27, 2026
- License file (Apache-2.0) · observed Aug 19, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentset 2.0k · DeepResearch 20k (synced Jul 22, 2026).
Common questions
- What is the difference between agentset and DeepResearch?
- agentset: The open-source RAG platform with built-in citations and support for deep research. DeepResearch: Tongyi Deep Research, the Leading Open-source Deep Research Agent. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentset over DeepResearch?
- Choose agentset over DeepResearch when agentset is primarily TypeScript; DeepResearch is Python; License: agentset is MIT, DeepResearch 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; Also covers Data & Retrieval; - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats.
- When should I choose DeepResearch over agentset?
- Choose DeepResearch over agentset when DeepResearch is primarily Python; agentset is TypeScript; License: DeepResearch is Apache-2.0, agentset is MIT; Tags unique to DeepResearch: agent, alibaba, artificial-intelligence, deep-research; Also covers Inference & Serving; When you need a tool backed by Alibaba’s ecosystem that offers a robust environment for conducting deep research using AI techniques.
- 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 DeepResearch?
- Avoid DeepResearch if you require specialized features that are not covered under its deep research and information-seeking scope. Do not use this tool if your project necessitates proprietary solutions, as the open-source nature might be a constraint in such scenarios.
- Is agentset or DeepResearch more popular on GitHub?
- DeepResearch has more GitHub stars (19,846 vs 2,035). Stars measure visibility, not whether either tool fits your constraints.
- Are agentset and DeepResearch open source?
- Yes - both are open-source projects on GitHub (agentset: MIT, DeepResearch: Apache-2.0).
- Where can I find alternatives to agentset or DeepResearch?
- GraphCanon lists graph-backed alternatives at agentset alternatives and DeepResearch alternatives (agentset markdown twin, DeepResearch 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 DeepResearch?
- agentset: Very active. DeepResearch: Slowing. 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 DeepResearch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentset trust report; DeepResearch trust report.