Comparison
agentic-rag-for-dummies vs docetl
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.
Markdown twin · agentic-rag-for-dummies alternatives · docetl alternatives
GraphCanon updated Sep 19, 2026
12views this month
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Trust & integrity
| Signal | agentic-rag-for-dummies | docetl |
|---|---|---|
| Maintenance | Active (20d since push) As of Sep 19, 2026 · github_public_v1 | Active (9d since push) As of Sep 15, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 19, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 15, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- 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
Stars
- agentic-rag-for-dummies
- 4.2k
- docetl
- 4.1k
Forks
- agentic-rag-for-dummies
- 552
- docetl
- 443
Open issues
- agentic-rag-for-dummies
- 0
- docetl
- 45
Language
- agentic-rag-for-dummies
- Jupyter Notebook
- docetl
- Python
Adopt for
- agentic-rag-for-dummies
- Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models.
- docetl
- 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
- agentic-rag-for-dummies
- -
- docetl
- -
Runtime
- agentic-rag-for-dummies
- -
- docetl
- -
License
- agentic-rag-for-dummies
- MIT
- docetl
- MIT
Last pushed
- agentic-rag-for-dummies
- Aug 30, 2026
- docetl
- Sep 5, 2026
Categories
- agentic-rag-for-dummies
- AI Agents, Data & Retrieval
- docetl
- AI Agents, Data & Retrieval
Trust and health
Days since push
- agentic-rag-for-dummies
- 20d
- docetl
- 9d
Open issues (now)
- agentic-rag-for-dummies
- 0
- docetl
- 45
Stars delta
- agentic-rag-for-dummies
- +295 (30d)
- docetl
- +131 (30d)
Open issues delta
- agentic-rag-for-dummies
- 0 (30d)
- docetl
- +3 (30d)
Owner type
- agentic-rag-for-dummies
- User
- docetl
- Organization
OSV dependency advisories
- agentic-rag-for-dummies
- Published findings
- docetl
- No lockfile (source not queried)
Full report
- agentic-rag-for-dummies
- Trust report
- docetl
- Trust report
Shared compatibility
- Python · agentic-rag-for-dummies: Python runtime · docetl: Python runtime
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.
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.
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (GiovanniPasq/agentic-rag-for-dummies) · observed Sep 19, 2026
- GitHub forks (GiovanniPasq/agentic-rag-for-dummies) · observed Sep 19, 2026
- Last push (GiovanniPasq/agentic-rag-for-dummies) · observed Aug 30, 2026
- License file (MIT) · observed Sep 19, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (ucbepic/docetl) · observed Sep 15, 2026
- GitHub forks (ucbepic/docetl) · observed Sep 15, 2026
- Last push (ucbepic/docetl) · observed Sep 5, 2026
- License file (MIT) · observed Sep 15, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: agentic-rag-for-dummies 4.2k · docetl 4.1k (synced Sep 19, 2026).
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 and docetl alternatives (agentic-rag-for-dummies markdown twin, docetl markdown twin), 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 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; docetl trust report.