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

# minima vs agentic-rag-for-dummies

*GraphCanon updated Aug 15, 2026*

## Verdict

Pick minima if minima is an on-premises conversational RAG tool with flexible deployment options through Docker-compose configurations, catering to fully local setups (Ollama), custom LLMs, ChatGPT integration, and MCP usage; pick agentic-rag-for-dummies if agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models.

[minima](https://github.com/dmayboroda/minima) reports 1.0k GitHub stars, 107 forks, and 14 open issues, last pushed Jan 22, 2026. [agentic-rag-for-dummies](https://github.com/GiovanniPasq/agentic-rag-for-dummies) has 3.9k stars, 499 forks, and 0 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [minima's repository](https://github.com/dmayboroda/minima) and [agentic-rag-for-dummies's repository](https://github.com/GiovanniPasq/agentic-rag-for-dummies).

| | [minima](/tools/dmayboroda-minima.md) | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) |
| --- | --- | --- |
| Tagline | On-premises conversational RAG with configurable containers | A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents |
| Stars | 1,048 | 3,893 |
| Forks | 107 | 499 |
| Open issues | 14 | 0 |
| Language | Python | Jupyter Notebook |
| Adopt for | Minima is an on-premises conversational RAG tool with flexible deployment options through Docker-compose configurations, catering to fully local setups (Ollama), custom LLMs, ChatGPT integration, and MCP usage. | Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. |
| Persona | - | - |
| Runtime | - | - |
| License | MPL-2.0 | MIT |
| Categories | Data & Retrieval, Inference & Serving, Model Training | AI Agents, Data & Retrieval |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [minima](/tools/dmayboroda-minima.md) | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Active (82%) |
| Days since push | 204d | 19d |
| Open issues (now) | 14 | 0 |
| Stars delta | -4 (30d) | Unknown |
| Open issues delta | 0 (30d) | Unknown |
| Owner type | Organization | User |
| Full report | [trust report](/tools/dmayboroda-minima/trust.md) | [trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust.md) |

## Decision facts: minima

- **Adopt for:** Minima is an on-premises conversational RAG tool with flexible deployment options through Docker-compose configurations, catering to fully local setups (Ollama), custom LLMs, ChatGPT integration, and MCP usage.

## 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.

## Choose when

### Choose minima if…

- minima is primarily Python; agentic-rag-for-dummies is Jupyter Notebook.
- License: minima is MPL-2.0, agentic-rag-for-dummies is MIT.
- Tags unique to minima: ai, claude, custom-gpts, docker.
- Also covers Inference & Serving, Model Training.
- - Use Minima for full local control over sensitive data in high-security environments where on-premises deployments are essential.

### Choose agentic-rag-for-dummies if…

- agentic-rag-for-dummies is primarily Jupyter Notebook; minima is Python.
- License: agentic-rag-for-dummies is MIT, minima is MPL-2.0.
- Tags unique to agentic-rag-for-dummies: agent, agentic-ai, bm25, gradio.
- Also covers AI Agents.
- When aiming to quickly develop a retrieval-augmented generation agent, thanks to its streamlined setup with LangGraph.

## When NOT to use minima

- - Avoid using Minima if your organization requires strict adherence to a cloud-only deployment strategy.
- - Do not choose Minima if you prefer tools that handle local file storage and security entirely through cloud services rather than on-premises configurations.

## 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.

## Common questions

### What is the difference between minima and agentic-rag-for-dummies?

minima: On-premises conversational RAG with configurable containers. agentic-rag-for-dummies: A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents. See the comparison table for live GitHub stats and shared categories.

### When should I choose minima over agentic-rag-for-dummies?

Choose minima over agentic-rag-for-dummies when minima is primarily Python; agentic-rag-for-dummies is Jupyter Notebook; License: minima is MPL-2.0, agentic-rag-for-dummies is MIT; Tags unique to minima: ai, claude, custom-gpts, docker; Also covers Inference & Serving, Model Training; - Use Minima for full local control over sensitive data in high-security environments where on-premises deployments are essential.

### When should I choose agentic-rag-for-dummies over minima?

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

### When should I avoid minima?

- Avoid using Minima if your organization requires strict adherence to a cloud-only deployment strategy. - Do not choose Minima if you prefer tools that handle local file storage and security entirely through cloud services rather than on-premises configurations.

### 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.

### Is minima or agentic-rag-for-dummies more popular on GitHub?

agentic-rag-for-dummies has more GitHub stars (3,893 vs 1,048). Stars measure visibility, not whether either tool fits your constraints.

### Are minima and agentic-rag-for-dummies open source?

Yes - both are open-source projects on GitHub (minima: MPL-2.0, agentic-rag-for-dummies: MIT).

### Where can I find alternatives to minima or agentic-rag-for-dummies?

GraphCanon lists graph-backed alternatives at [minima alternatives](/tools/dmayboroda-minima/alternatives) and [agentic-rag-for-dummies alternatives](/tools/giovannipasq-agentic-rag-for-dummies/alternatives) ([minima markdown twin](/tools/dmayboroda-minima/alternatives.md), [agentic-rag-for-dummies markdown twin](/tools/giovannipasq-agentic-rag-for-dummies/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/dmayboroda-minima-vs-giovannipasq-agentic-rag-for-dummies.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, minima or agentic-rag-for-dummies?

minima: Slowing. agentic-rag-for-dummies: 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 minima and agentic-rag-for-dummies?

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

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=dmayboroda-minima`](/api/graphcanon/graph?tool=dmayboroda-minima)
- 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/_