--- title: "search_with_lepton vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/leptonai-search-with-lepton-vs-pathwaycom-llm-app" tools: ["leptonai-search-with-lepton", "pathwaycom-llm-app"] --- # search_with_lepton vs llm-app *GraphCanon updated Aug 16, 2026* ## Verdict 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; pick llm-app if llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz. [search_with_lepton](https://search.lepton.run) reports 8.1k GitHub stars, 998 forks, and 44 open issues, last pushed Dec 2, 2025. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [search_with_lepton's repository](https://github.com/leptonai/search_with_lepton) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [search_with_lepton](/tools/leptonai-search-with-lepton.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | Building a quick conversation-based search demo with Lepton AI. | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. | | Stars | 8,081 | 59,037 | | Forks | 998 | 1,466 | | Open issues | 44 | 8 | | Language | TypeScript | Jupyter Notebook | | 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. | llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 license, providing freedom to use, modify and distribute the software while requiring preservation of copyright notices. | MIT | | Categories | Data & Retrieval, LLM Frameworks | Data & Retrieval, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [search_with_lepton](/tools/leptonai-search-with-lepton.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Steady (60%) | | Days since push | 248d | 41d | | Archived on GitHub | Yes | No | | Open issues (now) | 44 | 8 | | Stars delta | Unknown | +11 (30d) | | Open issues delta | Unknown | -2 (30d) | | Full report | [trust report](/tools/leptonai-search-with-lepton/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## 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. ## Decision facts: llm-app - **Requirements:** Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others. - **Adopt for:** llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz ## Choose when ### Choose search_with_lepton if… - search_with_lepton is primarily TypeScript; llm-app is Jupyter Notebook. - License: search_with_lepton is Apache-2.0, llm-app 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. ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; search_with_lepton is TypeScript. - License: llm-app is MIT, search_with_lepton is Apache-2.0. - Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.. - Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation. - Also covers Vector Databases. - - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs. ## 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. ## When NOT to use llm-app - - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app. ## Common questions ### What is the difference between search_with_lepton and llm-app? search_with_lepton: Building a quick conversation-based search demo with Lepton AI.. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. See the comparison table for live GitHub stats and shared categories. ### When should I choose search_with_lepton over llm-app? Choose search_with_lepton over llm-app when search_with_lepton is primarily TypeScript; llm-app is Jupyter Notebook; License: search_with_lepton is Apache-2.0, llm-app 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 choose llm-app over search_with_lepton? Choose llm-app over search_with_lepton when llm-app is primarily Jupyter Notebook; search_with_lepton is TypeScript; License: llm-app is MIT, search_with_lepton is Apache-2.0; Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation; Also covers Vector Databases; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs. ### 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. ### When should I avoid llm-app? - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app. ### Is search_with_lepton or llm-app more popular on GitHub? llm-app has more GitHub stars (59,037 vs 8,081). Stars measure visibility, not whether either tool fits your constraints. ### Are search_with_lepton and llm-app open source? Yes - both are open-source projects on GitHub (search_with_lepton: Apache-2.0, llm-app: MIT). ### Where can I find alternatives to search_with_lepton or llm-app? GraphCanon lists graph-backed alternatives at [search_with_lepton alternatives](/tools/leptonai-search-with-lepton/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([search_with_lepton markdown twin](/tools/leptonai-search-with-lepton/alternatives.md), [llm-app markdown twin](/tools/pathwaycom-llm-app/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/leptonai-search-with-lepton-vs-pathwaycom-llm-app.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, search_with_lepton or llm-app? search_with_lepton: Archived. llm-app: Steady. 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 search_with_lepton and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [search_with_lepton trust report](/tools/leptonai-search-with-lepton/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=leptonai-search-with-lepton`](/api/graphcanon/graph?tool=leptonai-search-with-lepton) - 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/_