--- title: "local-deep-research vs openagent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/learningcircuit-local-deep-research-vs-the-open-agent-openagent" tools: ["learningcircuit-local-deep-research", "the-open-agent-openagent"] --- # local-deep-research vs openagent *GraphCanon updated Sep 20, 2026* ## Verdict Pick local-deep-research if for deep research locally encrypted, supports retrieval-augmented generation using diverse LLM frameworks on local GPU or cloud, searches through arXiv, PubMed, personal documents; pick openagent if next-generation personal AI assistant powered by LLM, RAG and agent loops focusing on tasks like computer-use, browser navigation, coding support with an emphasis on Go language. [local-deep-research](https://github.com/LearningCircuit/local-deep-research) reports 9.1k GitHub stars, 824 forks, and 887 open issues, last pushed Sep 19, 2026. [openagent](https://openagentai.org) has 5.6k stars, 657 forks, and 45 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [local-deep-research's repository](https://github.com/LearningCircuit/local-deep-research) and [openagent's repository](https://github.com/the-open-agent/openagent). | | [local-deep-research](/tools/learningcircuit-local-deep-research.md) | [openagent](/tools/the-open-agent-openagent.md) | | --- | --- | --- | | Tagline | Supports local and cloud LLMs with encrypted search from diverse sources. | next-generation personal AI assistant powered by LLM, RAG and agent loops | | Stars | 9,109 | 5,628 | | Forks | 824 | 657 | | Open issues | 887 | 45 | | Language | Python | Go | | Adopt for | For deep research locally encrypted, supports retrieval-augmented generation using diverse LLM frameworks on local GPU or cloud, searches through arXiv, PubMed, personal documents. | next-generation personal AI assistant powered by LLM, RAG and agent loops focusing on tasks like computer-use, browser navigation, coding support with an emphasis on Go language | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, LLM Frameworks | AI Agents, Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [local-deep-research](/tools/learningcircuit-local-deep-research.md) | [openagent](/tools/the-open-agent-openagent.md) | | --- | --- | --- | | Days since push | 0d | 2d | | Open issues (now) | 887 | 45 | | Stars delta | +209 (30d) | +176 (30d) | | Open issues delta | +535 (30d) | -2 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/learningcircuit-local-deep-research/trust.md) | [trust report](/tools/the-open-agent-openagent/trust.md) | ## Decision facts: local-deep-research - **Adopt for:** For deep research locally encrypted, supports retrieval-augmented generation using diverse LLM frameworks on local GPU or cloud, searches through arXiv, PubMed, personal documents. ## Decision facts: openagent - **Adopt for:** next-generation personal AI assistant powered by LLM, RAG and agent loops focusing on tasks like computer-use, browser navigation, coding support with an emphasis on Go language ## Choose when ### Choose local-deep-research if… - local-deep-research is primarily Python; openagent is Go. - License: local-deep-research is MIT, openagent is Apache-2.0. - Tags unique to local-deep-research: academia, anthropic, arxiv, encryption. - You need encryption for all data processing steps and want support for various sources like academic articles and personal files. ### Choose openagent if… - openagent is primarily Go; local-deep-research is Python. - License: openagent is Apache-2.0, local-deep-research is MIT. - Tags unique to openagent: agent, agentic-ai, agi, chatbot. - Also covers AI Agents. - When needing advanced coding assistance, offering deep integration with the Go programming environment ## When NOT to use local-deep-research - If you require real-time collaboration features that are not supported by this tool's framework. - In scenarios where online connectivity is unreliable and external search engine support is considered critical. ## When NOT to use openagent - If looking for broader language support beyond the focus on Go, as openagent may not cater to other programming languages or frameworks as seamlessly - In environments where real-time performance is critical, as its reliance on LLM and RAG might introduce latency ## Common questions ### What is the difference between local-deep-research and openagent? local-deep-research: Supports local and cloud LLMs with encrypted search from diverse sources.. openagent: next-generation personal AI assistant powered by LLM, RAG and agent loops. See the comparison table for live GitHub stats and shared categories. ### When should I choose local-deep-research over openagent? Choose local-deep-research over openagent when local-deep-research is primarily Python; openagent is Go; License: local-deep-research is MIT, openagent is Apache-2.0; Tags unique to local-deep-research: academia, anthropic, arxiv, encryption; You need encryption for all data processing steps and want support for various sources like academic articles and personal files. ### When should I choose openagent over local-deep-research? Choose openagent over local-deep-research when openagent is primarily Go; local-deep-research is Python; License: openagent is Apache-2.0, local-deep-research is MIT; Tags unique to openagent: agent, agentic-ai, agi, chatbot; Also covers AI Agents; When needing advanced coding assistance, offering deep integration with the Go programming environment. ### When should I avoid local-deep-research? If you require real-time collaboration features that are not supported by this tool's framework. In scenarios where online connectivity is unreliable and external search engine support is considered critical. ### When should I avoid openagent? If looking for broader language support beyond the focus on Go, as openagent may not cater to other programming languages or frameworks as seamlessly In environments where real-time performance is critical, as its reliance on LLM and RAG might introduce latency ### Is local-deep-research or openagent more popular on GitHub? local-deep-research has more GitHub stars (9,109 vs 5,628). Stars measure visibility, not whether either tool fits your constraints. ### Are local-deep-research and openagent open source? Yes - both are open-source projects on GitHub (local-deep-research: MIT, openagent: Apache-2.0). ### Where can I find alternatives to local-deep-research or openagent? GraphCanon lists graph-backed alternatives at [local-deep-research alternatives](/tools/learningcircuit-local-deep-research/alternatives) and [openagent alternatives](/tools/the-open-agent-openagent/alternatives) ([local-deep-research markdown twin](/tools/learningcircuit-local-deep-research/alternatives.md), [openagent markdown twin](/tools/the-open-agent-openagent/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/learningcircuit-local-deep-research-vs-the-open-agent-openagent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, local-deep-research or openagent? local-deep-research: Very active. openagent: 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 local-deep-research and openagent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [local-deep-research trust report](/tools/learningcircuit-local-deep-research/trust); [openagent trust report](/tools/the-open-agent-openagent/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=learningcircuit-local-deep-research`](/api/graphcanon/graph?tool=learningcircuit-local-deep-research) - 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/_