Comparison
llama_index vs rags
Verdict
Coexists - Rags is a building block for creating query-over-data agents, while LlamaIndex expands with OCR, parsing, and more.
Markdown twin · llama_index alternatives · rags alternatives
GraphCanon updated Sep 30, 2026
19views this month
vs
Trust & integrity
| Signal | llama_index | rags |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (865d since push) As of Aug 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Aug 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | Published findings As of Jul 11, 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
- llama_index
- Document processing platform for AI
- rags
- Build ChatGPT over your data with natural language
Stars
- llama_index
- 52k
- rags
- 6.5k
Forks
- llama_index
- 8.2k
- rags
- 656
Open issues
- llama_index
- 802
- rags
- 37
Language
- llama_index
- Python
- rags
- Python
Adopt for
- llama_index
- LlamaIndex is an open-source framework for building AI-powered document processing applications, including RAG and agent applications, with a focus on document parsing and extraction. It offers over 300 integration packs
- rags
- Decision-critical facts for 'rags':
Persona
- llama_index
- -
- rags
- -
Runtime
- llama_index
- -
- rags
- -
License
- llama_index
- MIT
- rags
- MIT License
Last pushed
- llama_index
- Sep 18, 2026
- rags
- Apr 5, 2024
Categories
- llama_index
- AI Agents, Data & Retrieval, Developer Tools, Model Training
- rags
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- llama_index
- Very active (96%)
- rags
- Dormant (18%)
Days since push
- llama_index
- 0d
- rags
- 865d
Open issues (now)
- llama_index
- 802
- rags
- 37
Stars delta
- llama_index
- +765 (30d)
- rags
- +6 (30d)
Open issues delta
- llama_index
- +187 (30d)
- rags
- -1 (30d)
OSV dependency advisories
- llama_index
- No lockfile (source not queried)
- rags
- Published findings
Full report
- llama_index
- Trust report
- rags
- Trust report
Typed relationship
llama_index successor ragsLlamaIndex provides more comprehensive document parsing and extraction services on top of RAG capabilities, indicating it builds on similar foundational concepts but offers additional features.Coexists - Rags is a building block for creating query-over-data agents, while LlamaIndex expands with OCR, parsing, and more.
Shared compatibility
- Python · llama_index: Python runtime · rags: Python runtime
Choose llama_index if…
- LlamaIndex provides more comprehensive document parsing and extraction services on top of RAG capabilities, indicating it builds on similar foundational concepts but offers additional features.
- Tags unique to llama_index: agents, application, data, fine-tuning.
- Also covers Developer Tools, Model Training.
- When you need a framework that focuses on document parsing and extraction, as LlamaIndex has evolved to prioritize these capabilities
When NOT to use llama_index
- If your project requires enterprise-level features such as agentic OCR, as LlamaIndex's primary focus has shifted towards LlamaParse, an enterprise platform
- When you need a tool that is actively developed and maintained as the primary focus of the company has shifted towards LlamaParse and LiteParse, and the OSS framework is now a secondary focus
Choose rags if…
- Requirements: Installation leverages poetry for dependency management.; Setup requires configuration with OpenAI key and potentially creating a virtual environment..
- LlamaIndex provides more comprehensive document parsing and extraction services on top of RAG capabilities, indicating it builds on similar foundational concepts but offers additional features.
- Tags unique to rags: agent, chatbot, chatgpt, openai.
- When leveraging natural language queries over proprietary user data using OpenAI services.
When NOT to use rags
- Not suitable if you seek solutions not dependent on OpenAI's services as the underlying framework is tightly coupled with OpenAI APIs.
- Avoid using rags if your project involves sensitive or highly confidential data since it requires integrating API keys, potentially posing security concerns.
- If your team does not have familiarity or access to Streamlit for app development, you might find setting up and deploying a conversational agent more challenging.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (run-llama/llama_index) · observed Sep 20, 2026
- GitHub forks (run-llama/llama_index) · observed Sep 20, 2026
- Last push (run-llama/llama_index) · observed Sep 18, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (run-llama/rags) · observed Sep 20, 2026
- GitHub forks (run-llama/rags) · observed Sep 20, 2026
- Last push (run-llama/rags) · observed Apr 5, 2024
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: llama_index 52k · rags 6.5k (synced Sep 20, 2026).
Common questions
- What is the difference between llama_index and rags?
- llama_index: Document processing platform for AI. rags: Build ChatGPT over your data with natural language. See the comparison table for live GitHub stats and shared categories.
- When should I choose llama_index over rags?
- Choose llama_index over rags when LlamaIndex provides more comprehensive document parsing and extraction services on top of RAG capabilities, indicating it builds on similar foundational concepts but offers additional features; Tags unique to llama_index: agents, application, data, fine-tuning; Also covers Developer Tools, Model Training; When you need a framework that focuses on document parsing and extraction, as LlamaIndex has evolved to prioritize these capabilities.
- When should I choose rags over llama_index?
- Choose rags over llama_index when Requirements: Installation leverages poetry for dependency management.; Setup requires configuration with OpenAI key and potentially creating a virtual environment.; LlamaIndex provides more comprehensive document parsing and extraction services on top of RAG capabilities, indicating it builds on similar foundational concepts but offers additional features; Tags unique to rags: agent, chatbot, chatgpt, openai; When leveraging natural language queries over proprietary user data using OpenAI services.
- When should I avoid llama_index?
- If your project requires enterprise-level features such as agentic OCR, as LlamaIndex's primary focus has shifted towards LlamaParse, an enterprise platform When you need a tool that is actively developed and maintained as the primary focus of the company has shifted towards LlamaParse and LiteParse, and the OSS framework is now a secondary focus
- When should I avoid rags?
- Not suitable if you seek solutions not dependent on OpenAI's services as the underlying framework is tightly coupled with OpenAI APIs. Avoid using rags if your project involves sensitive or highly confidential data since it requires integrating API keys, potentially posing security concerns. If your team does not have familiarity or access to Streamlit for app development, you might find setting up and deploying a conversational agent more challenging.
- Is llama_index or rags more popular on GitHub?
- llama_index has more GitHub stars (52,207 vs 6,549). Stars measure visibility, not whether either tool fits your constraints.
- Are llama_index and rags open source?
- Yes - both are open-source projects on GitHub (llama_index: MIT, rags: MIT).
- Where can I find alternatives to llama_index or rags?
- GraphCanon lists graph-backed alternatives at llama_index alternatives and rags alternatives (llama_index markdown twin, rags 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, llama_index or rags?
- llama_index: Very active. rags: Dormant. 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 llama_index and rags?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llama_index trust report; rags trust report.