README.md

---
title: README
emoji: 🦙
colorFrom: yellow
colorTo: purple
sdk: static
pinned: false
---


# 🗂️ LlamaIndex 🦙

LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data.

PyPI: 
- LlamaIndex: https://pypi.org/project/llama-index/.
- GPT Index (duplicate): https://pypi.org/project/gpt-index/.

Documentation: https://gpt-index.readthedocs.io/.

Twitter: https://twitter.com/gpt_index.

Discord: https://discord.gg/dGcwcsnxhU.

### Ecosystem

- LlamaHub (community library of data loaders): https://llamahub.ai
- LlamaLab (cutting-edge AGI projects using LlamaIndex): https://github.com/run-llama/llama-lab


## 💻 Example Usage

```
pip install llama-index
```

Examples are in the `examples` folder. Indices are in the `indices` folder (see list of indices below).

To build a simple vector store index:
```python
import os
os.environ["OPENAI_API_KEY"] = 'YOUR_OPENAI_API_KEY'

from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader
documents = SimpleDirectoryReader('data').load_data()
index = GPTVectorStoreIndex.from_documents(documents)
```


To query:
```python
query_engine = index.as_query_engine()
query_engine.query("<question_text>?")
```


By default, data is stored in-memory.
To persist to disk (under `./storage`):

```python
index.storage_context.persist()
```

To reload from disk:
```python
from llama_index import StorageContext, load_index_from_storage

# rebuild storage context
storage_context = StorageContext.from_defaults(persist_dir='./storage')
# load index
index = load_index_from_storage(storage_context)
```