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

# agentic-rag-for-dummies vs rag-fusion

*GraphCanon updated Aug 23, 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 rag-fusion if rAG-Fusion leverages multi-query generation and Reciprocal Rank Fusion for enhanced retrieval-augmented generation tasks, supporting evaluations via NFCorpus/BEIR.

[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. [rag-fusion](https://github.com/Raudaschl/rag-fusion) has 952 stars, 115 forks, and 0 open issues, last pushed Apr 26, 2026. Figures are from public GitHub metadata via [agentic-rag-for-dummies's repository](https://github.com/GiovanniPasq/agentic-rag-for-dummies) and [rag-fusion's repository](https://github.com/Raudaschl/rag-fusion).

| | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | [rag-fusion](/tools/raudaschl-rag-fusion.md) |
| --- | --- | --- |
| Tagline | A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents | multi-query generation + Reciprocal Rank Fusion for retrieval-augmented generation |
| Stars | 3,893 | 952 |
| Forks | 499 | 115 |
| Open issues | 0 | 0 |
| Language | Jupyter Notebook | Python |
| Adopt for | Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. | RAG-Fusion leverages multi-query generation and Reciprocal Rank Fusion for enhanced retrieval-augmented generation tasks, supporting evaluations via NFCorpus/BEIR. |
| 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) | [rag-fusion](/tools/raudaschl-rag-fusion.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Slowing (36%) |
| Days since push | 19d | 118d |
| Stars delta | Unknown | +6 (30d) |
| Open issues delta | Unknown | 0 (30d) |
| Full report | [trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust.md) | [trust report](/tools/raudaschl-rag-fusion/trust.md) |

## Shared compatibility

- **Python**: [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) - Python runtime; [rag-fusion](/tools/raudaschl-rag-fusion.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: rag-fusion

- **Adopt for:** RAG-Fusion leverages multi-query generation and Reciprocal Rank Fusion for enhanced retrieval-augmented generation tasks, supporting evaluations via NFCorpus/BEIR.

## Choose when

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

- agentic-rag-for-dummies is primarily Jupyter Notebook; rag-fusion is Python.
- 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 rag-fusion if…

- rag-fusion is primarily Python; agentic-rag-for-dummies is Jupyter Notebook.
- Tags unique to rag-fusion: chromadb, information-retrieval, openai, python.
- Also covers Evaluation & Observability.
- For enhancing precision in retrieval-augmented generation tasks needing complex query processing

## 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 rag-fusion

- If you require real-time performance, as multi-query generation may introduce latency
- In scenarios where only simple keyword-based search suffices without the need for advanced fusion techniques

## Common questions

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

agentic-rag-for-dummies: A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents. rag-fusion: multi-query generation + Reciprocal Rank Fusion for retrieval-augmented generation. See the comparison table for live GitHub stats and shared categories.

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

Choose agentic-rag-for-dummies over rag-fusion when agentic-rag-for-dummies is primarily Jupyter Notebook; rag-fusion is Python; 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 rag-fusion over agentic-rag-for-dummies?

Choose rag-fusion over agentic-rag-for-dummies when rag-fusion is primarily Python; agentic-rag-for-dummies is Jupyter Notebook; Tags unique to rag-fusion: chromadb, information-retrieval, openai, python; Also covers Evaluation & Observability; For enhancing precision in retrieval-augmented generation tasks needing complex query processing.

### 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 rag-fusion?

If you require real-time performance, as multi-query generation may introduce latency In scenarios where only simple keyword-based search suffices without the need for advanced fusion techniques

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

agentic-rag-for-dummies has more GitHub stars (3,893 vs 952). Stars measure visibility, not whether either tool fits your constraints.

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

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

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

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

agentic-rag-for-dummies: Active. rag-fusion: 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 rag-fusion?

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); [rag-fusion trust report](/tools/raudaschl-rag-fusion/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/_