LlamaIndex Agents
by LlamaIndex
Data framework for LLM applications with agent support
Overview
LlamaIndex is a data framework for connecting LLMs with external data. Provides agent capabilities for tool calling and workflow orchestration.
Key Statistics
Overall Rating
4.4/5
GitHub Stars
44,600
Last Updated
2025-10
Version
0.12.8
Features
RAG applications
RAG applications capabilities
Data ingestion
Data ingestion capabilities
Agent workflows
Agent workflows capabilities
Tool integration
Tool integration capabilities
Getting Started
Installation
pip install llama-index
Quick Start
Install and create agent with tools
Code Example
from llama_index.agent.openai import OpenAIAgent
Pros & Cons
Advantages
Best-in-class for RAG applications
Excellent data connectors and loaders
Strong documentation and examples
Active community and development
MIT license
LlamaCloud for managed services
Works well with LangChain
Limitations
Primarily focused on RAG not general agents
Agent features less mature than core RAG
Can be complex for simple use cases
LlamaCloud requires subscription
Technical Details
Primary Language
Python
Supported Languages
License
MIT
Enterprise Ready
Yes
Community Size
Very Large
Pricing
Open Source + Cloud
Free open source. LlamaCloud for managed services with usage-based pricing
Performance Metrics
easeOfUse
4/5
scalability
4/5
documentation
5/5
community
5/5
performance
4/5
Common Use Cases
Document Q&A systems
Knowledge base retrieval
Semantic search applications
Chat over documents
Agent-based data retrieval
Research assistants