¶ LlamaIndex
LlamaIndex is the leading open-source document agent and OCR platform for building agentic applications with large language models. With over 47,500 GitHub stars, LlamaIndex specializes in connecting custom data sources to LLMs, enabling powerful retrieval-augmented generation (RAG) and document understanding capabilities.
License: MIT
GitHub: jerryjliu/llama_index
- 📄 Document Agents - AI agents that understand and process documents
- 🔍 Advanced RAG - State-of-the-art retrieval-augmented generation
- 📊 OCR Platform - Optical character recognition for scanned documents
- 🔗 Data Connectors - 100+ integrations with data sources
- 🧩 Composable Components - Modular building blocks for LLM apps
- 🤖 Multi-Modal Support - Process text, images, tables, and more
- 📈 Evaluation Tools - Measure and improve RAG performance
- 🚀 LlamaHub - Community-driven library of data loaders and tools
- 💻 TypeScript Support - LlamaIndex.TS for JavaScript/TypeScript projects
- Document Q&A - Ask questions about your documents
- Knowledge Base - Build searchable knowledge repositories
- Data Extraction - Extract structured data from unstructured sources
- Research Assistant - Academic literature search and summarization
- Enterprise Search - Internal document search and retrieval
| Component |
Technology |
| Language |
Python (61.0%), Jupyter Notebook (36.7%) |
| Package Manager |
pip, Poetry |
| Deployment |
Python application (no official Docker image) |
| Vector Stores |
Chroma, Pinecone, Weaviate, Qdrant, 30+ more |
| LLM Providers |
OpenAI, Anthropic, Google, Azure, Ollama, 50+ more |
Note: A TypeScript/JavaScript version is available at LlamaIndex.TS.
| Component |
Minimum |
Recommended |
| OS |
Linux, macOS, Windows |
Linux (Ubuntu 20.04+) |
| Python |
3.9+ |
3.11+ |
| CPU |
1 core |
2+ cores |
| RAM |
512 MB |
2+ GB |
| Disk |
500 MB |
2+ GB |
- ✅ Open-source (MIT License)
- ✅ Active development (v0.14.18 - March 16, 2026)
- ✅ 47.9k+ GitHub stars, 7.1k forks
- ✅ 490+ releases, 7,593 commits
- ✅ 1,849+ contributors
- ✅ PyPI package:
llama-index
- ✅ Used by 23.7k+ repositories
- ℹ️ No official Docker image - deploy as Python application
¶ History and References
Any questions?
Feel free to contact us. Find all contact information on our contact page.
Setting up RAG systems can be complex. We offer consulting services for:
- Production-ready deployments
- Performance tuning and optimization
- High-availability configurations
- Migration from legacy systems
Contact us at office@linux-server-admin.com or visit our contact page.