--- title: "pipeshub-ai vs awesome-llm-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pipeshub-ai-pipeshub-ai-vs-shubhamsaboo-awesome-llm-apps" tools: ["pipeshub-ai-pipeshub-ai", "shubhamsaboo-awesome-llm-apps"] --- # pipeshub-ai vs awesome-llm-apps *GraphCanon updated Sep 20, 2026* ## Verdict Pick pipeshub-ai if pipesHub-ai is an open-source platform aimed at unifying business data for enterprise search and automating workflows with integrations into tools such as LangChain, LlamaParse, Notion, Slack, among others; pick awesome-llm-apps if awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use. [pipeshub-ai](https://pipeshub.com) reports 3.8k GitHub stars, 579 forks, and 154 open issues, last pushed Sep 20, 2026. [awesome-llm-apps](https://www.theunwindai.com) has 136k stars, 20k forks, and 10 open issues, last pushed Sep 2, 2026. Figures are from public GitHub metadata via [pipeshub-ai's repository](https://github.com/pipeshub-ai/pipeshub-ai) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps). | | [pipeshub-ai](/tools/pipeshub-ai-pipeshub-ai.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Tagline | An open-source extensible AI context layer for explainable enterprise search and workflow automation. | Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy. | | Stars | 3,760 | 136,444 | | Forks | 579 | 20,078 | | Open issues | 154 | 10 | | Language | Python | Python | | Adopt for | PipesHub-ai is an open-source platform aimed at unifying business data for enterprise search and automating workflows with integrations into tools such as LangChain, LlamaParse, Notion, Slack, among others. | awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. | | Persona | - | - | | Runtime | - | - | | License | The tool is distributed under the Apache-2.0 license. | The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [pipeshub-ai](/tools/pipeshub-ai-pipeshub-ai.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Days since push | 0d | 4d | | Open issues (now) | 154 | 10 | | Stars delta | +567 (30d) | +5.2k (30d) | | Open issues delta | +62 (30d) | -3 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/pipeshub-ai-pipeshub-ai/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) | ## Decision facts: pipeshub-ai - **Pricing:** freemium - The core product is free to use, but for additional plugins or enterprise support services that may not be open-source, there could be paid tiers. - **Requirements:** Docker Compose must be installed and configured properly. An HTTPS endpoint should be used when deploying on cloud servers. - **Adopt for:** PipesHub-ai is an open-source platform aimed at unifying business data for enterprise search and automating workflows with integrations into tools such as LangChain, LlamaParse, Notion, Slack, among others. - **License detail:** The tool is distributed under the Apache-2.0 license. ## Decision facts: awesome-llm-apps - **Pricing:** freemium - Free with open-source licensing, but commercial exploitation is allowed. - **Adopt for:** awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. - **License detail:** The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. ## Choose when ### Choose pipeshub-ai if… - Pricing: The core product is free to use, but for additional plugins or enterprise support services that may not be open-source, there could be paid tiers.. - Requirements: Docker Compose must be installed and configured properly. An HTTPS endpoint should be used when deploying on cloud servers.. - Tags unique to pipeshub-ai: agent, ai, drive, glean. - pipeshub-ai ships Docker support for self-hosted deployment. - Use PipesHub-ai if you require a platform that supports local or cloud deployments via Docker Compose to manage and automate workflows within an enterprise setting. ### Choose awesome-llm-apps if… - Pricing: Free with open-source licensing, but commercial exploitation is allowed.. - Tags unique to awesome-llm-apps: applications, customizable, deployable, llms. - When you need quick implementations of various real-world use cases for AI Agents and RAG. ## When NOT to use pipeshub-ai - Avoid PipesHub-ai if your project does not align with the Python-based ecosystem, or if you do not require an open-source solution. - Do not use this platform if HTTPS support for cloud deployments cannot be assured as it may lead to frontend security issues and deployment failures. ## When NOT to use awesome-llm-apps - If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. - When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ## Common questions ### What is the difference between pipeshub-ai and awesome-llm-apps? pipeshub-ai: An open-source extensible AI context layer for explainable enterprise search and workflow automation.. awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. See the comparison table for live GitHub stats and shared categories. ### When should I choose pipeshub-ai over awesome-llm-apps? Choose pipeshub-ai over awesome-llm-apps when Pricing: The core product is free to use, but for additional plugins or enterprise support services that may not be open-source, there could be paid tiers.; Requirements: Docker Compose must be installed and configured properly. An HTTPS endpoint should be used when deploying on cloud servers.; Tags unique to pipeshub-ai: agent, ai, drive, glean; pipeshub-ai ships Docker support for self-hosted deployment; Use PipesHub-ai if you require a platform that supports local or cloud deployments via Docker Compose to manage and automate workflows within an enterprise setting. ### When should I choose awesome-llm-apps over pipeshub-ai? Choose awesome-llm-apps over pipeshub-ai when Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: applications, customizable, deployable, llms; When you need quick implementations of various real-world use cases for AI Agents and RAG. ### When should I avoid pipeshub-ai? Avoid PipesHub-ai if your project does not align with the Python-based ecosystem, or if you do not require an open-source solution. Do not use this platform if HTTPS support for cloud deployments cannot be assured as it may lead to frontend security issues and deployment failures. ### When should I avoid awesome-llm-apps? If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ### Is pipeshub-ai or awesome-llm-apps more popular on GitHub? awesome-llm-apps has more GitHub stars (136,444 vs 3,760). Stars measure visibility, not whether either tool fits your constraints. ### Are pipeshub-ai and awesome-llm-apps open source? Yes - both are open-source projects on GitHub (pipeshub-ai: Apache-2.0, awesome-llm-apps: Apache-2.0). ### Where can I find alternatives to pipeshub-ai or awesome-llm-apps? GraphCanon lists graph-backed alternatives at [pipeshub-ai alternatives](/tools/pipeshub-ai-pipeshub-ai/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([pipeshub-ai markdown twin](/tools/pipeshub-ai-pipeshub-ai/alternatives.md), [awesome-llm-apps markdown twin](/tools/shubhamsaboo-awesome-llm-apps/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/pipeshub-ai-pipeshub-ai-vs-shubhamsaboo-awesome-llm-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, pipeshub-ai or awesome-llm-apps? pipeshub-ai: Very active. awesome-llm-apps: 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 pipeshub-ai and awesome-llm-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [pipeshub-ai trust report](/tools/pipeshub-ai-pipeshub-ai/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=pipeshub-ai-pipeshub-ai`](/api/graphcanon/graph?tool=pipeshub-ai-pipeshub-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/_