LlamaIndex
Data framework for LLM applications that provides tools for ingesting, structuring, and accessing private or domain-specific data
38K+
GitHub Stars
30M+
Monthly Downloads
160+
Data Connectors
Overview
LlamaIndex is the leading open-source data framework for building LLM-powered applications with private or domain-specific data. Originally known as GPT Index, it specializes in data ingestion, indexing, and retrieval for RAG (Retrieval-Augmented Generation) applications. The framework provides a comprehensive toolkit for connecting LLMs to external data sources through 160+ data connectors, advanced indexing strategies, and sophisticated query engines. LlamaIndex excels at production RAG systems and has expanded to include agent capabilities with LlamaAgents for multi-agent orchestration.
The Verdict
Who Should Use LlamaIndex?
Best For
- Building production RAG applications
- Complex document processing pipelines
- Enterprise knowledge bases and Q&A systems
- Teams needing advanced retrieval strategies
- Multi-modal data applications (text, images, PDFs)
Not Ideal For
- Simple chatbot applications (use LangChain)
- Complex multi-agent workflows (use LangGraph)
- Projects avoiding Python dependencies
- Real-time streaming use cases
What's Great
- Best-in-class RAG and retrieval capabilities
- 160+ data connectors (LlamaHub)
- Advanced indexing strategies (tree, keyword, vector)
- LlamaParse for complex document parsing
- Excellent documentation and examples
- Production-ready with LlamaCloud
Watch Out For
- Steeper learning curve than LangChain
- Agent capabilities less mature than LangGraph
- TypeScript version lags behind Python
- LlamaCloud pricing can add up quickly
- Less community content than LangChain
Pricing
LlamaIndex OSS
Free
Full framework, MIT license
LlamaCloud Free
Free
1K pages/day parsing, 10K tokens
LlamaCloud Starter
$35/mo
10K pages/day, managed RAG
LlamaCloud Enterprise
Custom
Unlimited, SSO, dedicated support
View all features & details
Core Components
- Data connectors (LlamaHub - 160+)
- Document loaders & transformations
- Index types (vector, tree, keyword, knowledge graph)
- Query engines & retrievers
- Response synthesizers
- Chat engines with memory
- Structured output extraction
- Multi-modal support
RAG Features
- Hybrid search (vector + keyword)
- Recursive retrieval
- Auto-merging retrieval
- Sentence window retrieval
- Metadata filtering
- Reranking support
- Query transformations
- Evaluation framework
LlamaCloud Services
- LlamaParse - document parsing
- Managed indexes & pipelines
- LlamaExtract - structured extraction
- Production RAG hosting
- API-first architecture
- SOC 2 compliance
Agent Capabilities
- LlamaAgents - multi-agent framework
- Tool use & function calling
- Agent orchestration
- ReAct agents
- OpenAI agents compatibility
- Workflow automation
Community Stats
- 1,500+ contributors
- 160+ data connectors on LlamaHub
- Active Discord (30K+ members)
Ecosystem
- LlamaParse document processing
- LlamaHub data connectors
- LlamaCloud managed services
- LlamaAgents orchestration
How It Compares
| Feature | LlamaIndex | LangChain | Haystack | Semantic Kernel |
|---|---|---|---|---|
| Primary Focus | RAG & data indexing | General LLM apps | Search pipelines | Multi-language |
| GitHub Stars | 38K+ | 98K+ | 18K+ | 25K+ |
| Data Connectors | 160+ | 100+ | 50+ | 30+ |
| RAG Capabilities | Best-in-class | Good | Good | Basic |
| Agent Support | LlamaAgents | LangGraph | Basic | Good |
| Production Tools | LlamaCloud | LangSmith | Haystack Cloud | Azure AI |
| Best For | RAG applications | Full-stack LLM | Enterprise search | .NET/Java apps |
User Reviews
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