Document agent and OCR platform; leading RAG framework with agent workflows
Key Features
Multi-Agent
Single Agent
Human-in-the-Loop
Streaming
Async Support
Type Safe
Short-Term Memory
Long-Term Memory
Shared Memory
Plugin System
Custom Tools
MCP Protocol
A2A Protocol
Code Execution
Web Browsing
File System Access
Sandboxing
Guardrails
Structured Output
DAG Workflows
Visual Builder
CLI
API Server
Self-Hosted
Cloud Hosted
Community Feedback
Strengths
- Best-in-class RAG
- 150+ data connectors
- Battle-tested
- Strong Discord community
Weaknesses
- Scalability challenges with many agents
- Limited cloud features
- Fewer third-party integrations than LangChain
LlamaIndex Details
| Organization | LlamaIndex Inc |
| Organization Type | Company |
| Funding | Series a |
| Category | Framework |
| Subcategory | Orchestration |
| Deployment | Hybrid |
| Primary Language | Python |
| Runtime | Python 3.9+ |
| License | MIT |
| Commercial Use | Unrestricted |
| Install Command | pip install llama-index |
| GitHub Stars | 47,950 |
| GitHub Forks | 7,087 |
| Release Cadence | Weekly |
| Maturity | Mature |
| Pricing Model | Open core |
| Free Tier | MIT-licensed core is free |
| Self-Hosted Free | Yes |
| Cost Model | free + LLM costs |
| Community Size | Very large |
| Community Activity | Very active |
| Sentiment | Positive |
| GPU Required | No |
| Confidence | High |
| Research Date | 2026-03-24 |
| LLM Providers | OpenAI, Anthropic, Google, Mistral, Cohere, Hugging Face, Ollama |
| API Keys Required | LLM provider API key |
Use Cases
- Retrieval-augmented generation (RAG)
- Document Q&A and analysis
- Multi-document agents
- Knowledge base construction
- Data ingestion and indexing pipelines
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When to Use
Best for: RAG-heavy applications and document-centric AI workflows
Avoid when: Pure agent orchestration without data retrieval is the goal
Original data from HuggingFace, OpenCompass and various public git repos.
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Release v20260324