--- title: "Dot vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/alexpinel-dot-vs-pathwaycom-llm-app" tools: ["alexpinel-dot", "pathwaycom-llm-app"] --- # Dot vs llm-app *GraphCanon updated Jul 12, 2026* ## Verdict Pick Dot when dot is primarily JavaScript; llm-app is Jupyter Notebook; pick llm-app when llm-app is primarily Jupyter Notebook; Dot is JavaScript. [Dot](https://dotapp.uk/) reports 1.9k GitHub stars, 111 forks, and 14 open issues, last pushed Dec 9, 2024. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.4k forks, and 10 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [Dot's repository](https://github.com/alexpinel/Dot) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [Dot](/tools/alexpinel-dot.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | Text-To-Speech, RAG, and LLMs. All local! | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. | | Stars | 1,909 | 59,068 | | Forks | 111 | 1,432 | | Open issues | 14 | 10 | | Language | JavaScript | Jupyter Notebook | | 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 | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | MIT | | Categories | Data & Retrieval, LLM Frameworks, Speech & Audio | Data & Retrieval, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Dot](/tools/alexpinel-dot.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 578d | 5d | | Open issues (now) | 14 | 10 | | Owner type | User | Organization | | Full report | [trust report](/tools/alexpinel-dot/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## 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 Dot if… - Dot is primarily JavaScript; llm-app is Jupyter Notebook. - License: Dot is GPL-3.0, llm-app is MIT. - Tags unique to Dot: document-chat, embeddings, faiss, langchain. - Also covers Speech & Audio. ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; Dot is JavaScript. - License: llm-app is MIT, Dot is GPL-3.0. - 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 Dot - Last GitHub push was 579 days ago (dormant maintenance, Dec 9, 2024). Validate activity before betting a new project on Dot. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## 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 Dot and llm-app? Dot: Text-To-Speech, RAG, and LLMs. All local!. 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 Dot over llm-app? Choose Dot over llm-app when Dot is primarily JavaScript; llm-app is Jupyter Notebook; License: Dot is GPL-3.0, llm-app is MIT; Tags unique to Dot: document-chat, embeddings, faiss, langchain; Also covers Speech & Audio. ### When should I choose llm-app over Dot? Choose llm-app over Dot when llm-app is primarily Jupyter Notebook; Dot is JavaScript; License: llm-app is MIT, Dot is GPL-3.0; 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 Dot? Last GitHub push was 579 days ago (dormant maintenance, Dec 9, 2024). Validate activity before betting a new project on Dot. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### 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 Dot or llm-app more popular on GitHub? llm-app has more GitHub stars (59,068 vs 1,909). Stars measure visibility, not whether either tool fits your constraints. ### Are Dot and llm-app open source? Yes - both are open-source projects on GitHub (Dot: GPL-3.0, llm-app: MIT). ### Where can I find alternatives to Dot or llm-app? GraphCanon lists graph-backed alternatives at [Dot alternatives](/tools/alexpinel-dot/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([Dot markdown twin](/tools/alexpinel-dot/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/alexpinel-dot-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, Dot or llm-app? Dot: Dormant. llm-app: 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 Dot and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Dot trust report](/tools/alexpinel-dot/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=alexpinel-dot`](/api/graphcanon/graph?tool=alexpinel-dot) - 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/_