--- title: "vault-ai vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pashpashpash-vault-ai-vs-pathwaycom-llm-app" tools: ["pashpashpash-vault-ai", "pathwaycom-llm-app"] --- # vault-ai vs llm-app *GraphCanon updated Aug 23, 2026* ## Verdict Pick vault-ai if vault-ai is a tool that gives long-term memory capabilities to ChatGPT by integrating Pinecone Vector Database with an easy-to-use React frontend for uploading various types of files into the system; 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. [vault-ai](https://vault.pash.city) reports 3.4k GitHub stars, 296 forks, and 50 open issues, last pushed Jul 8, 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 [vault-ai's repository](https://github.com/pashpashpash/vault-ai) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [vault-ai](/tools/pashpashpash-vault-ai.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | Enhances ChatGPT with long-term memory using Pinecone Vector Database and React frontend for custom knowledge base uploads. | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. | | Stars | 3,387 | 59,037 | | Forks | 296 | 1,466 | | Open issues | 50 | 8 | | Language | JavaScript | Jupyter Notebook | | Adopt for | vault-ai is a tool that gives long-term memory capabilities to ChatGPT by integrating Pinecone Vector Database with an easy-to-use React frontend for uploading various types of files into the system. | 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 | MIT | MIT | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [vault-ai](/tools/pashpashpash-vault-ai.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 410d | 41d | | Open issues (now) | 50 | 8 | | Stars delta | 0 (30d) | +11 (30d) | | Open issues delta | 0 (30d) | -2 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/pashpashpash-vault-ai/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## Decision facts: vault-ai - **Adopt for:** vault-ai is a tool that gives long-term memory capabilities to ChatGPT by integrating Pinecone Vector Database with an easy-to-use React frontend for uploading various types of files into the system. ## 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 vault-ai if… - vault-ai is primarily JavaScript; llm-app is Jupyter Notebook. - Tags unique to vault-ai: ai, artificial-intelligence, chatgpt, generative. - When you need a custom knowledge base that can be queried using a generative AI model, such as extending ChatGPT with historical context from uploaded documents in formats like PDFs or txt. ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; vault-ai is JavaScript. - 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 LLM Frameworks. - - 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 vault-ai - When your requirements do not include uploading custom content for the AI to learn from, as vault-ai focuses on integrating a knowledge base with ChatGPT. - If you prefer using other vector search databases such as Qdrant instead of Pinecone, as vault-ai is specifically designed around Pinecone. ## 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 vault-ai and llm-app? vault-ai: Enhances ChatGPT with long-term memory using Pinecone Vector Database and React frontend for custom knowledge base uploads.. 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 vault-ai over llm-app? Choose vault-ai over llm-app when vault-ai is primarily JavaScript; llm-app is Jupyter Notebook; Tags unique to vault-ai: ai, artificial-intelligence, chatgpt, generative; When you need a custom knowledge base that can be queried using a generative AI model, such as extending ChatGPT with historical context from uploaded documents in formats like PDFs or txt. ### When should I choose llm-app over vault-ai? Choose llm-app over vault-ai when llm-app is primarily Jupyter Notebook; vault-ai is JavaScript; 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 LLM Frameworks; - 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 vault-ai? When your requirements do not include uploading custom content for the AI to learn from, as vault-ai focuses on integrating a knowledge base with ChatGPT. If you prefer using other vector search databases such as Qdrant instead of Pinecone, as vault-ai is specifically designed around Pinecone. ### 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 vault-ai or llm-app more popular on GitHub? llm-app has more GitHub stars (59,037 vs 3,387). Stars measure visibility, not whether either tool fits your constraints. ### Are vault-ai and llm-app open source? Yes - both are open-source projects on GitHub (vault-ai: MIT, llm-app: MIT). ### Where can I find alternatives to vault-ai or llm-app? GraphCanon lists graph-backed alternatives at [vault-ai alternatives](/tools/pashpashpash-vault-ai/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([vault-ai markdown twin](/tools/pashpashpash-vault-ai/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/pashpashpash-vault-ai-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, vault-ai or llm-app? vault-ai: Dormant. 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 vault-ai and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [vault-ai trust report](/tools/pashpashpash-vault-ai/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=pashpashpash-vault-ai`](/api/graphcanon/graph?tool=pashpashpash-vault-ai) - 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/_