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LlamaIndex
The data framework for LLM apps — RAG, agents, and enterprise data connectors.
0Open Source
AI Agents RAG Frameworks
Overview
LlamaIndex is a data framework for LLM applications, specializing in connecting LLMs to external data sources for powerful RAG, agents, and structured data extraction.
Key Features
- 150+ data connectors (Notion, Slack, databases, S3, etc.)
- Advanced RAG with query routing and re-ranking
- Agentic workflows with multi-step reasoning
- Structured output and data extraction from documents
- Workflow engine for complex, event-driven agent pipelines
- LlamaCloud for managed RAG pipelines
Real-World Workflows
Enterprise knowledge base over internal docs
- 1Connect data sources with SimpleDirectoryReader or Notion/Confluence loaders
- 2Build a VectorStoreIndex from all your documents
- 3Add a query engine with reranking for better accuracy
- 4Expose via a REST API for internal Slack/Teams chatbots
Getting Started
pip install llama-index llama-index-llms-openai
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
docs = SimpleDirectoryReader('data/').load_data()
index = VectorStoreIndex.from_documents(docs)
query_engine = index.as_query_engine()
response = query_engine.query('What is our refund policy?')
print(response)Compare Alternatives
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