# LlamaIndex — Data Framework for LLM Applications

> Connect your data to large language models. The leading framework for RAG, document indexing, knowledge graphs, and structured data extraction.

## Install

Save as a script file and run:

## Quick Use

```bash
pip install llama-index
```

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## Intro

LlamaIndex (formerly GPT Index) is the go-to framework for connecting custom data to LLMs. Ingest data from 160+ sources, build indexes for fast retrieval, and create production-ready RAG pipelines.

**Best for**: Document Q&A, knowledge base search, data extraction, enterprise RAG
**Works with**: OpenAI, Anthropic, Google, Ollama, HuggingFace

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## Key Features

### Data Connectors
Ingest from PDFs, databases, APIs, Notion, Slack, Google Drive, and 160+ sources:
```python
from llama_index.core import SimpleDirectoryReader
documents = SimpleDirectoryReader("./data").load_data()
```

### Indexing & Retrieval
```python
from llama_index.core import VectorStoreIndex
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("What is the revenue trend?")
```

### Agents
Build data-aware agents that can query multiple data sources, use tools, and maintain conversation state.

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### FAQ

**Q: What is LlamaIndex?**
A: Connect your data to large language models. The leading framework for RAG, document indexing, knowledge graphs, and structured data extraction.

**Q: How do I install LlamaIndex?**
A: Check the Quick Use section above for step-by-step installation instructions. Most assets can be set up in under 2 minutes.

## Source & Thanks

> Created by [LlamaIndex](https://github.com/run-llama). Licensed under MIT.
> [run-llama/llama_index](https://github.com/run-llama/llama_index) — 38K+ GitHub stars

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Source: https://tokrepo.com/en/workflows/1bd234e2-5c10-459f-91f4-00675625103b
Author: Script Depot