---
title: "agentic-rag-for-dummies vs awesome-llm-apps"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/giovannipasq-agentic-rag-for-dummies-vs-shubhamsaboo-awesome-llm-apps"
tools: ["giovannipasq-agentic-rag-for-dummies", "shubhamsaboo-awesome-llm-apps"]
---

# agentic-rag-for-dummies vs awesome-llm-apps

*GraphCanon updated Sep 20, 2026*

## Verdict

Pick agentic-rag-for-dummies if agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models; 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 cases in Python.

[agentic-rag-for-dummies](https://github.com/GiovanniPasq/agentic-rag-for-dummies) reports 4.2k GitHub stars, 552 forks, and 0 open issues, last pushed Aug 30, 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 [agentic-rag-for-dummies's repository](https://github.com/GiovanniPasq/agentic-rag-for-dummies) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps).

| | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) |
| --- | --- | --- |
| Tagline | A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents | Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy. |
| Stars | 4,188 | 136,444 |
| Forks | 552 | 20,078 |
| Open issues | 0 | 10 |
| Language | Jupyter Notebook | Python |
| Adopt for | Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. | 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 | MIT | 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._

| | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Very active (96%) |
| Days since push | 20d | 4d |
| Open issues (now) | 0 | 10 |
| Stars delta | +295 (30d) | +5.2k (30d) |
| Open issues delta | 0 (30d) | -3 (30d) |
| Full report | [trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) |

## Shared compatibility

- **Python**: [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) - Python runtime; [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) - Python runtime

## Decision facts: agentic-rag-for-dummies

- **Adopt for:** Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models.

## 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 agentic-rag-for-dummies if…

- agentic-rag-for-dummies is primarily Jupyter Notebook; awesome-llm-apps is Python.
- License: agentic-rag-for-dummies is MIT, awesome-llm-apps is Apache-2.0.
- Tags unique to agentic-rag-for-dummies: agent, agentic-ai, bm25, gradio.
- When aiming to quickly develop a retrieval-augmented generation agent, thanks to its streamlined setup with LangGraph.

### Choose awesome-llm-apps if…

- awesome-llm-apps is primarily Python; agentic-rag-for-dummies is Jupyter Notebook.
- License: awesome-llm-apps is Apache-2.0, agentic-rag-for-dummies is MIT.
- Pricing: Free with open-source licensing, but commercial exploitation is allowed..
- Tags unique to awesome-llm-apps: agents, applications, customizable, deployable.
- When you need quick implementations of various real-world use cases for AI Agents and RAG.

## When NOT to use agentic-rag-for-dummies

- If smaller language model sizes are required as they might ignore retrieval instructions or hallucinate details.
- Projects sensitive about Docker and system requirements must carefully review the outlined conditions for deployment.

## 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 agentic-rag-for-dummies and awesome-llm-apps?

agentic-rag-for-dummies: A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents. 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 agentic-rag-for-dummies over awesome-llm-apps?

Choose agentic-rag-for-dummies over awesome-llm-apps when agentic-rag-for-dummies is primarily Jupyter Notebook; awesome-llm-apps is Python; License: agentic-rag-for-dummies is MIT, awesome-llm-apps is Apache-2.0; Tags unique to agentic-rag-for-dummies: agent, agentic-ai, bm25, gradio; When aiming to quickly develop a retrieval-augmented generation agent, thanks to its streamlined setup with LangGraph.

### When should I choose awesome-llm-apps over agentic-rag-for-dummies?

Choose awesome-llm-apps over agentic-rag-for-dummies when awesome-llm-apps is primarily Python; agentic-rag-for-dummies is Jupyter Notebook; License: awesome-llm-apps is Apache-2.0, agentic-rag-for-dummies is MIT; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; When you need quick implementations of various real-world use cases for AI Agents and RAG.

### When should I avoid agentic-rag-for-dummies?

If smaller language model sizes are required as they might ignore retrieval instructions or hallucinate details. Projects sensitive about Docker and system requirements must carefully review the outlined conditions for deployment.

### 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 agentic-rag-for-dummies or awesome-llm-apps more popular on GitHub?

awesome-llm-apps has more GitHub stars (136,444 vs 4,188). Stars measure visibility, not whether either tool fits your constraints.

### Are agentic-rag-for-dummies and awesome-llm-apps open source?

Yes - both are open-source projects on GitHub (agentic-rag-for-dummies: MIT, awesome-llm-apps: Apache-2.0).

### Where can I find alternatives to agentic-rag-for-dummies or awesome-llm-apps?

GraphCanon lists graph-backed alternatives at [agentic-rag-for-dummies alternatives](/tools/giovannipasq-agentic-rag-for-dummies/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([agentic-rag-for-dummies markdown twin](/tools/giovannipasq-agentic-rag-for-dummies/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/giovannipasq-agentic-rag-for-dummies-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, agentic-rag-for-dummies or awesome-llm-apps?

agentic-rag-for-dummies: 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 agentic-rag-for-dummies and awesome-llm-apps?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentic-rag-for-dummies trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=giovannipasq-agentic-rag-for-dummies`](/api/graphcanon/graph?tool=giovannipasq-agentic-rag-for-dummies)
- 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/_