--- title: "local-deep-research vs search_with_lepton" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/learningcircuit-local-deep-research-vs-leptonai-search-with-lepton" tools: ["learningcircuit-local-deep-research", "leptonai-search-with-lepton"] --- # local-deep-research vs search_with_lepton *GraphCanon updated Aug 12, 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 search_with_lepton if **search_with_lepton** is a TypeScript-based conversational search demo integrating Lepton AI's LLM and offering flexible backend options like Bing, Google SearchAPI, Serper, or Programmable Search Engine. [local-deep-research](https://github.com/LearningCircuit/local-deep-research) reports 8.9k GitHub stars, 788 forks, and 352 open issues, last pushed Aug 12, 2026. [search_with_lepton](https://search.lepton.run) has 8.1k stars, 998 forks, and 44 open issues, last pushed Dec 2, 2025. Figures are from public GitHub metadata via [local-deep-research's repository](https://github.com/LearningCircuit/local-deep-research) and [search_with_lepton's repository](https://github.com/leptonai/search_with_lepton). | | [local-deep-research](/tools/learningcircuit-local-deep-research.md) | [search_with_lepton](/tools/leptonai-search-with-lepton.md) | | --- | --- | --- | | Tagline | Supports local and cloud LLMs with encrypted search from diverse sources. | Building a quick conversation-based search demo with Lepton AI. | | Stars | 8,900 | 8,081 | | Forks | 788 | 998 | | Open issues | 352 | 44 | | Language | Python | TypeScript | | 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. | **search_with_lepton** is a TypeScript-based conversational search demo integrating Lepton AI's LLM and offering flexible backend options like Bing, Google SearchAPI, Serper, or Programmable Search Engine. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 license, providing freedom to use, modify and distribute the software while requiring preservation of copyright notices. | | Categories | Data & Retrieval, LLM Frameworks | 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) | [search_with_lepton](/tools/leptonai-search-with-lepton.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 0d | 248d | | Archived on GitHub | No | Yes | | Open issues (now) | 352 | 44 | | Owner type | User | Organization | | Full report | [trust report](/tools/learningcircuit-local-deep-research/trust.md) | [trust report](/tools/leptonai-search-with-lepton/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: search_with_lepton - **Adopt for:** **search_with_lepton** is a TypeScript-based conversational search demo integrating Lepton AI's LLM and offering flexible backend options like Bing, Google SearchAPI, Serper, or Programmable Search Engine. - **License detail:** Apache-2.0 license, providing freedom to use, modify and distribute the software while requiring preservation of copyright notices. ## Choose when ### Choose local-deep-research if… - local-deep-research is primarily Python; search_with_lepton is TypeScript. - License: local-deep-research is MIT, search_with_lepton is Apache-2.0. - Tags unique to local-deep-research: academia, anthropic, arxiv, encryption. - local-deep-research ships Docker support for self-hosted deployment. - You need encryption for all data processing steps and want support for various sources like academic articles and personal files. ### Choose search_with_lepton if… - search_with_lepton is primarily TypeScript; local-deep-research is Python. - License: search_with_lepton is Apache-2.0, local-deep-research is MIT. - Tags unique to search_with_lepton: ai-applications, bing-api, conversational-search, google-search. - - When you need a quick prototype of a conversation-driven search engine leveraging Lepton AI. ## 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 search_with_lepton - - Avoid if your project strictly requires only native integration with other LLMs besides Lepton AI as this tool is tightly coupled with it. - - Not recommended if you aim to build a large-scale production system as the demo focuses on rapid development rather than high throughput or enterprise-level robustness. ## Common questions ### What is the difference between local-deep-research and search_with_lepton? local-deep-research: Supports local and cloud LLMs with encrypted search from diverse sources.. search_with_lepton: Building a quick conversation-based search demo with Lepton AI.. See the comparison table for live GitHub stats and shared categories. ### When should I choose local-deep-research over search_with_lepton? Choose local-deep-research over search_with_lepton when local-deep-research is primarily Python; search_with_lepton is TypeScript; License: local-deep-research is MIT, search_with_lepton is Apache-2.0; Tags unique to local-deep-research: academia, anthropic, arxiv, encryption; local-deep-research ships Docker support for self-hosted deployment; You need encryption for all data processing steps and want support for various sources like academic articles and personal files. ### When should I choose search_with_lepton over local-deep-research? Choose search_with_lepton over local-deep-research when search_with_lepton is primarily TypeScript; local-deep-research is Python; License: search_with_lepton is Apache-2.0, local-deep-research is MIT; Tags unique to search_with_lepton: ai-applications, bing-api, conversational-search, google-search; - When you need a quick prototype of a conversation-driven search engine leveraging Lepton AI. ### 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 search_with_lepton? - Avoid if your project strictly requires only native integration with other LLMs besides Lepton AI as this tool is tightly coupled with it. - Not recommended if you aim to build a large-scale production system as the demo focuses on rapid development rather than high throughput or enterprise-level robustness. ### Is local-deep-research or search_with_lepton more popular on GitHub? local-deep-research has more GitHub stars (8,900 vs 8,081). Stars measure visibility, not whether either tool fits your constraints. ### Are local-deep-research and search_with_lepton open source? Yes - both are open-source projects on GitHub (local-deep-research: MIT, search_with_lepton: Apache-2.0). ### Where can I find alternatives to local-deep-research or search_with_lepton? GraphCanon lists graph-backed alternatives at [local-deep-research alternatives](/tools/learningcircuit-local-deep-research/alternatives) and [search_with_lepton alternatives](/tools/leptonai-search-with-lepton/alternatives) ([local-deep-research markdown twin](/tools/learningcircuit-local-deep-research/alternatives.md), [search_with_lepton markdown twin](/tools/leptonai-search-with-lepton/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-leptonai-search-with-lepton.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 search_with_lepton? local-deep-research: Very active. search_with_lepton: 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 local-deep-research and search_with_lepton? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [local-deep-research trust report](/tools/learningcircuit-local-deep-research/trust); [search_with_lepton trust report](/tools/leptonai-search-with-lepton/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/_