--- title: "agentic-rag-for-dummies vs docetl" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/giovannipasq-agentic-rag-for-dummies-vs-ucbepic-docetl" tools: ["giovannipasq-agentic-rag-for-dummies", "ucbepic-docetl"] --- # agentic-rag-for-dummies vs docetl *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 docetl if docetl is an agentic system that employs large language models for data processing and ETL operations, specifically suited to handle unstructured document analysis tasks. [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. [docetl](https://docetl.org) has 4.1k stars, 443 forks, and 45 open issues, last pushed Sep 5, 2026. Figures are from public GitHub metadata via [agentic-rag-for-dummies's repository](https://github.com/GiovanniPasq/agentic-rag-for-dummies) and [docetl's repository](https://github.com/ucbepic/docetl). | | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | [docetl](/tools/ucbepic-docetl.md) | | --- | --- | --- | | Tagline | A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents | A system for agentic LLM-powered data processing and ETL | | Stars | 4,188 | 4,092 | | Forks | 552 | 443 | | Open issues | 0 | 45 | | Language | Jupyter Notebook | Python | | Adopt for | Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. | Docetl is an agentic system that employs large language models for data processing and ETL operations, specifically suited to handle unstructured document analysis tasks. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | 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) | [docetl](/tools/ucbepic-docetl.md) | | --- | --- | --- | | Days since push | 20d | 9d | | Open issues (now) | 0 | 45 | | Stars delta | +295 (30d) | +131 (30d) | | Open issues delta | 0 (30d) | +3 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust.md) | [trust report](/tools/ucbepic-docetl/trust.md) | ## Shared compatibility - **Python**: [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) - Python runtime; [docetl](/tools/ucbepic-docetl.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: docetl - **Adopt for:** Docetl is an agentic system that employs large language models for data processing and ETL operations, specifically suited to handle unstructured document analysis tasks. ## Choose when ### Choose agentic-rag-for-dummies if… - agentic-rag-for-dummies is primarily Jupyter Notebook; docetl is Python. - 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 docetl if… - docetl is primarily Python; agentic-rag-for-dummies is Jupyter Notebook. - Tags unique to docetl: agents, data, document-analysis, etl. - docetl ships Docker support for self-hosted deployment. - When you require integration with any LLM provider through API keys like OPENAI_API_KEY. ## 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 docetl - If your project strictly requires low-latency processing for real-time applications, as Docetl's agentic approach might introduce higher latency due to backend API calls. - In scenarios where the document datasets are predominantly structured or semi-structured, making traditional ETL tools more efficient. ## Common questions ### What is the difference between agentic-rag-for-dummies and docetl? agentic-rag-for-dummies: A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents. docetl: A system for agentic LLM-powered data processing and ETL. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentic-rag-for-dummies over docetl? Choose agentic-rag-for-dummies over docetl when agentic-rag-for-dummies is primarily Jupyter Notebook; docetl is Python; 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 docetl over agentic-rag-for-dummies? Choose docetl over agentic-rag-for-dummies when docetl is primarily Python; agentic-rag-for-dummies is Jupyter Notebook; Tags unique to docetl: agents, data, document-analysis, etl; docetl ships Docker support for self-hosted deployment; When you require integration with any LLM provider through API keys like OPENAI_API_KEY. ### 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 docetl? If your project strictly requires low-latency processing for real-time applications, as Docetl's agentic approach might introduce higher latency due to backend API calls. In scenarios where the document datasets are predominantly structured or semi-structured, making traditional ETL tools more efficient. ### Is agentic-rag-for-dummies or docetl more popular on GitHub? agentic-rag-for-dummies has more GitHub stars (4,188 vs 4,092). Stars measure visibility, not whether either tool fits your constraints. ### Are agentic-rag-for-dummies and docetl open source? Yes - both are open-source projects on GitHub (agentic-rag-for-dummies: MIT, docetl: MIT). ### Where can I find alternatives to agentic-rag-for-dummies or docetl? GraphCanon lists graph-backed alternatives at [agentic-rag-for-dummies alternatives](/tools/giovannipasq-agentic-rag-for-dummies/alternatives) and [docetl alternatives](/tools/ucbepic-docetl/alternatives) ([agentic-rag-for-dummies markdown twin](/tools/giovannipasq-agentic-rag-for-dummies/alternatives.md), [docetl markdown twin](/tools/ucbepic-docetl/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-ucbepic-docetl.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 docetl? agentic-rag-for-dummies: Active. docetl: 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 docetl? 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); [docetl trust report](/tools/ucbepic-docetl/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/_