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

# agentic-rag-for-dummies vs ragtune

*GraphCanon updated Aug 14, 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 ragtune if ragtune is a Go-based benchmarking tool for RAG retrieval systems that allows users to inspect, debug, benchmark, and tune the retrieval layer.

[agentic-rag-for-dummies](https://github.com/GiovanniPasq/agentic-rag-for-dummies) reports 3.9k GitHub stars, 499 forks, and 0 open issues, last pushed Jul 25, 2026. [ragtune](https://github.com/metawake/ragtune) has 13 stars, 1 forks, and 0 open issues, last pushed Mar 25, 2026. Figures are from public GitHub metadata via [agentic-rag-for-dummies's repository](https://github.com/GiovanniPasq/agentic-rag-for-dummies) and [ragtune's repository](https://github.com/metawake/ragtune).

| | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | [ragtune](/tools/metawake-ragtune.md) |
| --- | --- | --- |
| Tagline | A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents | Benchmarking tool for RAG retrieval, aiding in tuning and evaluating retrieval layers |
| Stars | 3,893 | 13 |
| Forks | 499 | 1 |
| Open issues | 0 | 0 |
| Language | Jupyter Notebook | Go |
| Adopt for | Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. | Ragtune is a Go-based benchmarking tool for RAG retrieval systems that allows users to inspect, debug, benchmark, and tune the retrieval layer. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | MIT |
| Categories | AI Agents, Data & Retrieval | Data & Retrieval, Evaluation & Observability |

## Trust and health

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

| | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | [ragtune](/tools/metawake-ragtune.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Slowing (36%) |
| Days since push | 19d | 129d |
| Full report | [trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust.md) | [trust report](/tools/metawake-ragtune/trust.md) |

## 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: ragtune

- **Adopt for:** Ragtune is a Go-based benchmarking tool for RAG retrieval systems that allows users to inspect, debug, benchmark, and tune the retrieval layer.

## Choose when

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

- agentic-rag-for-dummies is primarily Jupyter Notebook; ragtune is Go.
- 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.

### Choose ragtune if…

- ragtune is primarily Go; agentic-rag-for-dummies is Jupyter Notebook.
- Tags unique to ragtune: benchmarking, embeddings, metrics, retrieval-augmented-generation.
- Also covers Evaluation & Observability.
- For organizations using multiple vector search engines like Chroma or Pinecone because Ragtune supports them directly.

## 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 ragtune

- If your project relies on languages other than Go, as Ragtune might not integrate smoothly without additional effort.
- When the primary focus of retrieval layer tuning lies outside supported vector search engines like Chroma or Qdrant and no customization can be applied via the tool.

## Common questions

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

agentic-rag-for-dummies: A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents. ragtune: Benchmarking tool for RAG retrieval, aiding in tuning and evaluating retrieval layers. See the comparison table for live GitHub stats and shared categories.

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

Choose agentic-rag-for-dummies over ragtune when agentic-rag-for-dummies is primarily Jupyter Notebook; ragtune is Go; 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 choose ragtune over agentic-rag-for-dummies?

Choose ragtune over agentic-rag-for-dummies when ragtune is primarily Go; agentic-rag-for-dummies is Jupyter Notebook; Tags unique to ragtune: benchmarking, embeddings, metrics, retrieval-augmented-generation; Also covers Evaluation & Observability; For organizations using multiple vector search engines like Chroma or Pinecone because Ragtune supports them directly.

### 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 ragtune?

If your project relies on languages other than Go, as Ragtune might not integrate smoothly without additional effort. When the primary focus of retrieval layer tuning lies outside supported vector search engines like Chroma or Qdrant and no customization can be applied via the tool.

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

agentic-rag-for-dummies has more GitHub stars (3,893 vs 13). Stars measure visibility, not whether either tool fits your constraints.

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

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

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

GraphCanon lists graph-backed alternatives at [agentic-rag-for-dummies alternatives](/tools/giovannipasq-agentic-rag-for-dummies/alternatives) and [ragtune alternatives](/tools/metawake-ragtune/alternatives) ([agentic-rag-for-dummies markdown twin](/tools/giovannipasq-agentic-rag-for-dummies/alternatives.md), [ragtune markdown twin](/tools/metawake-ragtune/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-metawake-ragtune.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 ragtune?

agentic-rag-for-dummies: Active. ragtune: Slowing. 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 ragtune?

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); [ragtune trust report](/tools/metawake-ragtune/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/_